From 8bfacc6a5ba6fc3bd0e0aa0b171e688758bf8821 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 18 Jul 2022 16:17:44 +0100
Subject: [PATCH 001/192] Format AF data and demo weighted average

---
 code/{scapeAF.py => scrapeAF.py} | 34 ++++++++++++++++++++++++++++----
 readme.md                        |  8 +++++++-
 2 files changed, 37 insertions(+), 5 deletions(-)
 rename code/{scapeAF.py => scrapeAF.py} (76%)

diff --git a/code/scapeAF.py b/code/scrapeAF.py
similarity index 76%
rename from code/scapeAF.py
rename to code/scrapeAF.py
index 353b8a3..cbef691 100644
--- a/code/scapeAF.py
+++ b/code/scrapeAF.py
@@ -12,6 +12,10 @@
 import pandas as pd
 import logging
 
+def makeURL(country):
+    url = "http://www.allelefrequencies.net/hla6006a.asp?hla_locus_type=Classical&hla_country=%s&hla_level=2&" %(country)
+    return url
+
 def parseAF(bs):
     """Generate a dataframe from a given url
 
@@ -25,7 +29,7 @@ def parseAF(bs):
     tab = bs.find('div', {'id': 'divGenDetail'}).find('table', {'class': 'tblNormal'})
     # Get the column headers from the first row of the table
     columns = [
-        'line', 'allele', 'flag', 'population', '%individuals',
+        'line', 'allele', 'flag', 'population', 'carriers%',
         'allele_freq', 'AF_graphic', 'sample_size', 'database',
         'distribution','haplotype_association', 'notes'
         ]
@@ -37,9 +41,14 @@ def parseAF(bs):
     # Make dataframe of table rows
     # skip the first row as it's `th` headers
     df = pd.DataFrame(rows[1:], columns = columns)
+
+    # Get HLA loci
+    df['loci'] = df.allele.apply(lambda x: x.split("*")[0])
+
     # Drop unwanted columns
-    df = df[['allele', 'population', 'allele_freq', 'sample_size']]
+    df = df[['allele', 'loci', 'population', 'allele_freq', 'carriers%', 'sample_size']]
     return df
+   
 
 def Npages(bs):
     """How many pages of results are there?
@@ -86,11 +95,28 @@ def getAFdata(base_url):
         tab = parseAF(bs)
         tabs.append(tab)
     tabs = pd.concat(tabs)
+    tabs = formatAF(tabs)
+    validateAF(tabs)
     return tabs
 
+def formatAF(df):
+    # Force convert columns to numeric
+    df.allele_freq = pd.to_numeric(df.allele_freq)
+    df.sample_size = pd.to_numeric(df.sample_size)
+    return df
+
+def validateAF(df):
+    if not all(df.allele_freq <= 1):
+        print("Allele frequency greater 1 reported")
+
 
 url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
-base_url = "http://www.allelefrequencies.net/hla6006a.asp?hla_locus_type=Classical&hla_country=Thailand&hla_level=2&"
+base_url = makeURL("Philippines")
 
-aftab = getAFdata(base_url)
+# aftab = getAFdata(base_url)
 aftab
+
+import numpy as np
+
+aftab.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
+aftab.groupby('allele').size()
diff --git a/readme.md b/readme.md
index ac8922b..f9c8b31 100644
--- a/readme.md
+++ b/readme.md
@@ -7,4 +7,10 @@ Scrape allele frequency data from
 This gives frequencies by population, which can be averaged
 across studies, weighted by sample size. Frequencies can then
 be averaged across populations if a relative weighting can
-found, i.e. population size.
\ No newline at end of file
+found, i.e. population size.
+
+```
+import sys
+sys.path.append("/home/dwells/work/tools/scrapeAF/code")
+import scrapeAF
+```
\ No newline at end of file

From 01d3db0766dc607f8708cf1f849171db070e9ade Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 18 Jul 2022 16:59:39 +0100
Subject: [PATCH 002/192] Removed formatting and validation

This prevents errors when data is unusually formatted,
eg sample sizes with commas 1,000
---
 code/scrapeAF.py | 24 ++++++------------------
 1 file changed, 6 insertions(+), 18 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index cbef691..042338e 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -95,28 +95,16 @@ def getAFdata(base_url):
         tab = parseAF(bs)
         tabs.append(tab)
     tabs = pd.concat(tabs)
-    tabs = formatAF(tabs)
-    validateAF(tabs)
     return tabs
 
-def formatAF(df):
-    # Force convert columns to numeric
-    df.allele_freq = pd.to_numeric(df.allele_freq)
-    df.sample_size = pd.to_numeric(df.sample_size)
-    return df
-
-def validateAF(df):
-    if not all(df.allele_freq <= 1):
-        print("Allele frequency greater 1 reported")
-
 
-url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
-base_url = makeURL("Philippines")
+# url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
+# base_url = makeURL("Philippines")
 
 # aftab = getAFdata(base_url)
-aftab
+# aftab
 
-import numpy as np
+# import numpy as np
 
-aftab.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
-aftab.groupby('allele').size()
+# aftab.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
+# aftab.groupby('allele').size()

From 4559d49d23aceaa9fd9ebd65e4cfe0de26ae4c10 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 19 Jul 2022 13:44:48 +0100
Subject: [PATCH 003/192] Demo to compare allele freq of countries

---
 code/demos/compare_countries.py | 66 +++++++++++++++++++++++++++++++++
 1 file changed, 66 insertions(+)
 create mode 100644 code/demos/compare_countries.py

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
new file mode 100644
index 0000000..3dd3c00
--- /dev/null
+++ b/code/demos/compare_countries.py
@@ -0,0 +1,66 @@
+"""
+Compare HLA frequencies of different countries.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+countries = [
+    'United+Kingdom',
+    'Thailand',
+    'Uganda'
+]
+
+# Download HLA allele frequencies
+for country in countries:
+    print(country)
+    base_url = scrapeAF.makeURL(country)
+    aftab = scrapeAF.getAFdata(base_url)
+    aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
+
+wavs = []
+for country in countries:
+    df = pd.read_csv("data/example/%s_raw.csv" %country)
+    # Handle commmas in sample size
+    if df.sample_size.dtype == 'O':
+        df.sample_size = pd.to_numeric(df.sample_size.str.replace(",",""))
+    # Weighted AVerage
+    wav = df.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
+    wav.name = "allele_freq"
+    wav = pd.DataFrame(wav)
+    wav['country'] = country
+    wavs.append(wav)
+
+wavs = pd.concat(wavs, axis=0).reset_index()
+
+# Keep only alleles with frequency over threshold
+threshold = 0.02
+common_alleles = wavs[wavs.allele_freq > threshold].allele.unique()
+wavs = wavs[wavs.allele.isin(common_alleles)]
+
+# Focus on locus A and locus B
+wavsa = wavs[wavs.allele.str.contains("^A\*")]
+wavsb = wavs[wavs.allele.str.contains("^B\*")]
+
+fig, ax = plt.subplots(2)
+
+sns.barplot(
+    data = wavsa,
+    x = 'allele',
+    y = 'allele_freq',
+    hue = 'country',
+    ax=ax[0]
+)
+sns.barplot(
+    data = wavsb,
+    x = 'allele',
+    y = 'allele_freq',
+    hue = 'country',
+    ax=ax[1]
+)
+
+plt.xticks(rotation=90)
+plt.show()
\ No newline at end of file

From d2dcc10a06d6b2ef2cb6f3407ae9c23b98efa7df Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 19 Jul 2022 16:47:03 +0100
Subject: [PATCH 004/192] Calculate AF weighted average: combineAF()

---
 code/demos/compare_countries.py | 11 ++---------
 code/scrapeAF.py                | 35 ++++++++++++++++++++++++++++++++-
 code/setup.sh                   |  2 ++
 readme.md                       | 14 ++++++++++++-
 4 files changed, 51 insertions(+), 11 deletions(-)
 create mode 100644 code/setup.sh

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 3dd3c00..bbeecd9 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -24,15 +24,8 @@
 wavs = []
 for country in countries:
     df = pd.read_csv("data/example/%s_raw.csv" %country)
-    # Handle commmas in sample size
-    if df.sample_size.dtype == 'O':
-        df.sample_size = pd.to_numeric(df.sample_size.str.replace(",",""))
-    # Weighted AVerage
-    wav = df.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
-    wav.name = "allele_freq"
-    wav = pd.DataFrame(wav)
-    wav['country'] = country
-    wavs.append(wav)
+    df = scrapeAF.formatAF(df)
+    wav = scrapeAF.combineAF(df)
 
 wavs = pd.concat(wavs, axis=0).reset_index()
 
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 042338e..bcbee18 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -10,6 +10,7 @@
 from bs4 import BeautifulSoup
 import requests
 import pandas as pd
+import numpy as np
 import logging
 
 def makeURL(country):
@@ -17,7 +18,7 @@ def makeURL(country):
     return url
 
 def parseAF(bs):
-    """Generate a dataframe from a given url
+    """Generate a dataframe from a given html page
 
     Args:
         bs (bs4.BeautifulSoup): BeautifulSoup object from allelefrequencies.net page
@@ -97,6 +98,38 @@ def getAFdata(base_url):
     tabs = pd.concat(tabs)
     return tabs
 
+def formatAF(df):
+    if df.sample_size.dtype == "O":
+        df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
+    return df
+
+def combineAF(df):
+    """Combine allele frequencies at multiple levels
+
+    Args:
+        df (pd.DataFrame): Table of Allele frequency data
+
+    Returns:
+        pd.DataFrame: Table of allele frequency data with alleles
+        grouped to make a weighted average based on sample size.
+    """
+    grouped = df.groupby('allele')
+    combined = grouped.apply(
+        lambda row: [
+        row.name,
+        row.loci.unique()[0],
+        np.average(row.allele_freq, weights=row.sample_size),
+        row.sample_size.sum()
+        ]
+    )
+    combined = pd.DataFrame(
+        combined.tolist(),
+        columns = ['allele', 'loci', 'allele_freq', 'sample_size']
+    )
+    combined = combined.reset_index(drop=True)
+    return combined
+
+
 
 # url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
 # base_url = makeURL("Philippines")
diff --git a/code/setup.sh b/code/setup.sh
new file mode 100644
index 0000000..e21fb06
--- /dev/null
+++ b/code/setup.sh
@@ -0,0 +1,2 @@
+#!/usr/bin/env bash
+mkdir data/example -p
\ No newline at end of file
diff --git a/readme.md b/readme.md
index f9c8b31..32b8f7e 100644
--- a/readme.md
+++ b/readme.md
@@ -13,4 +13,16 @@ found, i.e. population size.
 import sys
 sys.path.append("/home/dwells/work/tools/scrapeAF/code")
 import scrapeAF
-```
\ No newline at end of file
+```
+
+When selecting alleles to represent a population, all supertypes
+should be represented.
+
+When combining extimates of allele frequency larger samples should
+weigh more heavily. However, when combining estiamtes that disagree
+the uncertainty on the estimate should be larger than when combining
+equivalent samples that agree.
+
+When combining studies we must weight averages by sample size but
+when combining countries are we not better to weight by national population?
+Should sample size also have an effect?
\ No newline at end of file

From e7782e25710c7159ffdfff985f1c24e942a45a8f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 19 Jul 2022 16:48:53 +0100
Subject: [PATCH 005/192] Calculate population coverage using HWE

Note that if AF doesn't sum to 1 this gives coverage outside 0-1
---
 code/demos/population_coverage.py | 24 ++++++++++++++++++++++++
 code/scrapeAF.py                  | 13 +++++++++++++
 2 files changed, 37 insertions(+)
 create mode 100644 code/demos/population_coverage.py

diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
new file mode 100644
index 0000000..779836c
--- /dev/null
+++ b/code/demos/population_coverage.py
@@ -0,0 +1,24 @@
+"""
+How much of the population is covered by the top n alleles?
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import matplotlib.pyplot as plt
+
+alleles = pd.read_csv("data/example/Uganda_raw.csv")
+alleles = scrapeAF.formatAF(alleles)
+
+# Weighted average alleles
+wav = scrapeAF.combineAF(alleles)
+
+wav = wav.sort_values('allele_freq', ascending=False, ignore_index = True)
+
+plt.plot(wav.allele_freq)
+plt.show()
+
+plt.plot(wav.allele_freq.cumsum())
+plt.show()
+
+plt.plot(wav.allele_freq.cumsum().apply(scrapeAF.population_coverage))
+plt.show()
\ No newline at end of file
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index bcbee18..54fe1ba 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -129,7 +129,20 @@ def combineAF(df):
     combined = combined.reset_index(drop=True)
     return combined
 
+def population_coverage(p):
+    """Calculate the proportion of people with at least 1 copy of this allele
+        assuming HWE.
 
+    Args:
+        p (float): Allele frequency
+
+    Returns:
+        float: Sum of homozygotes and heterozygotes for this allele
+    """
+    q = 1-p
+    homo = p**2
+    hetero = 2*p*q
+    return homo + hetero
 
 # url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
 # base_url = makeURL("Philippines")

From 49c941eacbca80b44df19cd04c48773ac6f0ee72 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 19 Jul 2022 16:49:37 +0100
Subject: [PATCH 006/192] makeURL from parts, specify query

---
 code/scrapeAF.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 54fe1ba..2c7cb40 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -13,8 +13,13 @@
 import numpy as np
 import logging
 
-def makeURL(country):
-    url = "http://www.allelefrequencies.net/hla6006a.asp?hla_locus_type=Classical&hla_country=%s&hla_level=2&" %(country)
+def makeURL(country, standard='s'):
+    base = "http://www.allelefrequencies.net/hla6006a.asp?"
+    locus_type = "hla_locus_type=Classical&"
+    country = "hla_country=%s&" %(country)
+    resolution = "hla_level=2&"
+    standard = "standard=%s&" %standard
+    url = base + locus_type + country + resolution + standard
     return url
 
 def parseAF(bs):

From 90624277321e74b45d6c9b89e19b060e002160fb Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Jul 2022 10:04:58 +0100
Subject: [PATCH 007/192] Add .gitignore

---
 .gitignore | 4 ++++
 1 file changed, 4 insertions(+)
 create mode 100644 .gitignore

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..c1bd234
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+data/
+docs/
+*__pycache__/
+*.code-workspace

From abbbd34c231754c348f0fc065ad54e5e8044284b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Jul 2022 10:05:33 +0100
Subject: [PATCH 008/192] Demo population coverage calculation

adding missing alleles
---
 code/demos/population_coverage.py | 35 ++++++++++++++++++++++++-------
 1 file changed, 28 insertions(+), 7 deletions(-)

diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index 779836c..519d879 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -6,19 +6,40 @@
 import pandas as pd
 import matplotlib.pyplot as plt
 
-alleles = pd.read_csv("data/example/Uganda_raw.csv")
-alleles = scrapeAF.formatAF(alleles)
+AFtab = pd.read_csv("data/example/Uganda_raw.csv")
+AFtab = scrapeAF.formatAF(AFtab)
+
+loci = AFtab.loci.unique()
+for locus in loci:
+    populations = AFtab[AFtab.loci == locus].population.unique()
+    for population in populations:
+# locus = "A"
+# population = 'Uganda Kampala'
+        popAF = AFtab[(AFtab.population == population) & (AFtab.loci == locus)]
+        pop_sample_size = popAF.sample_size.unique()
+        assert len(pop_sample_size) == 1, "pop_sample_size must be 1, not %s" %len(pop_sample_size)
+        pop_sample_size = pop_sample_size[0]
+        ualleles = AFtab[AFtab.loci == locus].allele.unique()
+        missing_alleles = [allele for allele in ualleles if not allele in popAF.allele.values]
+        missing_rows = [(al, locus, population, 0, 0, pop_sample_size) for al in missing_alleles]
+        missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci','population','allele_freq','carriers%','sample_size'])
+        AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
 
 # Weighted average alleles
-wav = scrapeAF.combineAF(alleles)
+wav = scrapeAF.combineAF(AFtab)
 
 wav = wav.sort_values('allele_freq', ascending=False, ignore_index = True)
 
-plt.plot(wav.allele_freq)
-plt.show()
+wava = wav[wav.loci == "A"]
 
-plt.plot(wav.allele_freq.cumsum())
+plt.bar(wava.allele, wava.allele_freq)
+plt.xticks(rotation=90)
 plt.show()
 
-plt.plot(wav.allele_freq.cumsum().apply(scrapeAF.population_coverage))
+# cumsum exceeds 1, possibly because rare alleles are not found
+# in all populations within a country
+
+plt.plot(wava.allele_freq.cumsum())
+plt.plot(wava.allele_freq.cumsum().apply(scrapeAF.population_coverage))
+plt.axhline(y=1, color="black", linestyle="--")
 plt.show()
\ No newline at end of file

From 0564447b67fe63a55a835d58e10cfaa2ee171e17 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Jul 2022 10:25:01 +0100
Subject: [PATCH 009/192] Add missing alleles as a function

---
 code/demos/population_coverage.py | 31 +++++++----------------------
 code/scrapeAF.py                  | 33 +++++++++++++++++++++++++++++++
 2 files changed, 40 insertions(+), 24 deletions(-)

diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index 519d879..3cf1518 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -9,37 +9,20 @@
 AFtab = pd.read_csv("data/example/Uganda_raw.csv")
 AFtab = scrapeAF.formatAF(AFtab)
 
-loci = AFtab.loci.unique()
-for locus in loci:
-    populations = AFtab[AFtab.loci == locus].population.unique()
-    for population in populations:
-# locus = "A"
-# population = 'Uganda Kampala'
-        popAF = AFtab[(AFtab.population == population) & (AFtab.loci == locus)]
-        pop_sample_size = popAF.sample_size.unique()
-        assert len(pop_sample_size) == 1, "pop_sample_size must be 1, not %s" %len(pop_sample_size)
-        pop_sample_size = pop_sample_size[0]
-        ualleles = AFtab[AFtab.loci == locus].allele.unique()
-        missing_alleles = [allele for allele in ualleles if not allele in popAF.allele.values]
-        missing_rows = [(al, locus, population, 0, 0, pop_sample_size) for al in missing_alleles]
-        missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci','population','allele_freq','carriers%','sample_size'])
-        AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
+# Add unreported alleles so AF sums to 1
+AFtab = scrapeAF.unmeasured_alleles(AFtab)
 
 # Weighted average alleles
 wav = scrapeAF.combineAF(AFtab)
 
-wav = wav.sort_values('allele_freq', ascending=False, ignore_index = True)
-
-wava = wav[wav.loci == "A"]
+wava = wav[wav.loci == "A"].sort_values('allele_freq', ascending=False, ignore_index = True)
 
 plt.bar(wava.allele, wava.allele_freq)
 plt.xticks(rotation=90)
 plt.show()
 
-# cumsum exceeds 1, possibly because rare alleles are not found
-# in all populations within a country
-
-plt.plot(wava.allele_freq.cumsum())
-plt.plot(wava.allele_freq.cumsum().apply(scrapeAF.population_coverage))
+plt.plot(wava.allele_freq.cumsum(), label="Cumulative AF")
+plt.plot(wava.allele_freq.cumsum().apply(scrapeAF.population_coverage), label="Cumulative coverage")
 plt.axhline(y=1, color="black", linestyle="--")
-plt.show()
\ No newline at end of file
+plt.legend()
+plt.show()
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 2c7cb40..b5636ca 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -108,6 +108,39 @@ def formatAF(df):
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
     return df
 
+def unmeasured_alleles(AFtab):
+    """When combining AF estimates, unreported alleles can inflate frequencies
+        so AF sums to >1. Therefore we add unreported alleles with frequency zero.
+
+    Args:
+        AFtab (pd.DataFrame): Formatted allele frequency data
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all locus alleles reported 
+            for each population
+    """
+    loci = AFtab.loci.unique()
+    # Iterate over loci separately
+    for locus in loci:
+        # Iterate over each population reporting that locus
+        populations = AFtab[AFtab.loci == locus].population.unique()
+        for population in populations:
+            # Single locus, single population data
+            popAF = AFtab[(AFtab.population == population) & (AFtab.loci == locus)]
+            # What was the sample size for this data?
+            pop_sample_size = popAF.sample_size.unique()
+            assert len(pop_sample_size) == 1, "pop_sample_size must be 1, not %s" %len(pop_sample_size)
+            pop_sample_size = pop_sample_size[0]
+            # Get all alleles for this locus (across populations)
+            ualleles = AFtab[AFtab.loci == locus].allele.unique()
+            # Which of these alleles are not in this population?
+            missing_alleles = [allele for allele in ualleles if not allele in popAF.allele.values]
+            missing_rows = [(al, locus, population, 0, 0, pop_sample_size) for al in missing_alleles]
+            missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci','population','allele_freq','carriers%','sample_size'])
+            # Add them in with zero frequency
+            AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
+    return AFtab
+
 def combineAF(df):
     """Combine allele frequencies at multiple levels
 

From e6a57d7bb2ad5b5fbb3df4dba8073dc43d0ac0dc Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Jul 2022 16:10:19 +0100
Subject: [PATCH 010/192] Demo averaging allele frequencies across countries

---
 code/demos/international_frequencies.py | 61 +++++++++++++++++++++++++
 1 file changed, 61 insertions(+)
 create mode 100644 code/demos/international_frequencies.py

diff --git a/code/demos/international_frequencies.py b/code/demos/international_frequencies.py
new file mode 100644
index 0000000..0e90987
--- /dev/null
+++ b/code/demos/international_frequencies.py
@@ -0,0 +1,61 @@
+"""
+Calculate International average allele frequencies
+using population estimates.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+countries = [
+    'United+Kingdom',
+    'Thailand',
+    'Uganda'
+]
+population_sizes = {
+    'United+Kingdom': 67081234,
+    'Thailand': 66813717,
+    'Uganda': 42885900
+}
+
+# Get weighted average for each county
+wavs = []
+for country in countries:
+    # Load raw county data
+    AFtab = pd.read_csv("data/example/%s_raw.csv" %country)
+    # format data
+    AFtab = scrapeAF.formatAF(AFtab)
+    # Add unreported alleles so AF sums to 1
+    AFtab = scrapeAF.unmeasured_alleles(AFtab)
+    # Weighted average alleles
+    wav = scrapeAF.combineAF(AFtab)
+    # Add country to dataset
+    wav['country'] = country
+    wavs.append(wav)
+
+international = pd.concat(wavs, ignore_index=True)
+international = scrapeAF.unmeasured_alleles(international, 'country')
+# Add population size to weight averages
+international['population_size'] = international.country.apply(lambda x: population_sizes[x])
+
+#International Weighted Average
+iwav = scrapeAF.combineAF(international, 'population_size')
+
+intA = international[international.loci == 'A']
+iwava = iwav[iwav.loci == 'A']
+
+plt.scatter(
+    intA.allele,
+    intA.allele_freq,
+    c=[intA.country.unique().tolist().index(x) for x in intA.country],
+    s=intA.population_size/10000000
+    )
+plt.scatter(
+    iwava.allele,
+    iwava.allele_freq,
+    c='black',
+    marker='x'
+)
+plt.xticks(rotation=90)
+plt.show()

From 9fc7469d069ad8f32b2f8d95ebddac16a4d5ef8e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Jul 2022 16:11:07 +0100
Subject: [PATCH 011/192] Check for unequal sample sizes after combineAF

---
 code/scrapeAF.py | 50 ++++++++++++++++++++++++++++++++----------------
 1 file changed, 33 insertions(+), 17 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index b5636ca..94b30fe 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -108,7 +108,7 @@ def formatAF(df):
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
     return df
 
-def unmeasured_alleles(AFtab):
+def unmeasured_alleles(AFtab, datasetID='population'):
     """When combining AF estimates, unreported alleles can inflate frequencies
         so AF sums to >1. Therefore we add unreported alleles with frequency zero.
 
@@ -117,31 +117,31 @@ def unmeasured_alleles(AFtab):
 
     Returns:
         pd.DataFrame: Allele frequency data with all locus alleles reported 
-            for each population
+            for each dataset
     """
     loci = AFtab.loci.unique()
     # Iterate over loci separately
     for locus in loci:
-        # Iterate over each population reporting that locus
-        populations = AFtab[AFtab.loci == locus].population.unique()
-        for population in populations:
-            # Single locus, single population data
-            popAF = AFtab[(AFtab.population == population) & (AFtab.loci == locus)]
+        # Iterate over each dataset reporting that locus
+        datasets = AFtab[AFtab.loci == locus][datasetID].unique()
+        for dataset in datasets:
+            # Single locus, single dataset
+            datasetAF = AFtab[(AFtab[datasetID] == dataset) & (AFtab.loci == locus)]
             # What was the sample size for this data?
-            pop_sample_size = popAF.sample_size.unique()
-            assert len(pop_sample_size) == 1, "pop_sample_size must be 1, not %s" %len(pop_sample_size)
-            pop_sample_size = pop_sample_size[0]
-            # Get all alleles for this locus (across populations)
+            dataset_sample_size = datasetAF.sample_size.unique()
+            assert len(dataset_sample_size) == 1, "dataset_sample_size must be 1, not %s" %len(dataset_sample_size)
+            dataset_sample_size = dataset_sample_size[0]
+            # Get all alleles for this locus (across datasets)
             ualleles = AFtab[AFtab.loci == locus].allele.unique()
-            # Which of these alleles are not in this population?
-            missing_alleles = [allele for allele in ualleles if not allele in popAF.allele.values]
-            missing_rows = [(al, locus, population, 0, 0, pop_sample_size) for al in missing_alleles]
-            missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci','population','allele_freq','carriers%','sample_size'])
+            # Which of these alleles are not in this dataset?
+            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
+            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
+            missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci',datasetID,'allele_freq','carriers%','sample_size'])
             # Add them in with zero frequency
             AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
     return AFtab
 
-def combineAF(df):
+def combineAF(df, weights='sample_size'):
     """Combine allele frequencies at multiple levels
 
     Args:
@@ -156,7 +156,7 @@ def combineAF(df):
         lambda row: [
         row.name,
         row.loci.unique()[0],
-        np.average(row.allele_freq, weights=row.sample_size),
+        np.average(row.allele_freq, weights=row[weights]),
         row.sample_size.sum()
         ]
     )
@@ -165,8 +165,24 @@ def combineAF(df):
         columns = ['allele', 'loci', 'allele_freq', 'sample_size']
     )
     combined = combined.reset_index(drop=True)
+    # Check that all alleles in a locus have the same sample size
+    # after merging
+    if duplicated_sample_size(combined):
+        id_duplicated_allele(grouped)
+
     return combined
 
+def duplicated_sample_size(df):
+    """Returns True if any loci has more than 1 unique sample size"""
+    locus_sample_sizes = df.groupby('loci').sample_size.apply(lambda x: len(x.unique()))
+    return any(locus_sample_sizes != 1)
+
+def id_duplicated_allele(grouped):
+    """ Reports the allele that has mupltiple sample sizes """
+    duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
+    assert all(~duplicated_population), "duplicated population within allele %s" %duplicated_population[duplicated_population]
+
+
 def population_coverage(p):
     """Calculate the proportion of people with at least 1 copy of this allele
         assuming HWE.

From 8f3f61304728198c41ce69186acba01fd238f1e5 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 19 Aug 2022 16:39:59 +0100
Subject: [PATCH 012/192] View supertype population coverage

---
 code/demos/population_coverage.py | 30 +++++++++++++++++++++++++++---
 readme.md                         | 14 ++++++++++++--
 2 files changed, 39 insertions(+), 5 deletions(-)

diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index 3cf1518..61b97aa 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -1,10 +1,16 @@
 """
 How much of the population is covered by the top n alleles?
+What is the population coverage of different supertypes?
 """
 
 import code.scrapeAF as scrapeAF
 import pandas as pd
 import matplotlib.pyplot as plt
+import seaborn as sns
+
+# Which supertypes are represented
+super1 = pd.read_csv("data/HLA1supertypes_Sidney2008.csv")
+super1.allele = super1.allele.apply(lambda x: x[:4]+':'+x[4:])
 
 AFtab = pd.read_csv("data/example/Uganda_raw.csv")
 AFtab = scrapeAF.formatAF(AFtab)
@@ -14,11 +20,17 @@
 
 # Weighted average alleles
 wav = scrapeAF.combineAF(AFtab)
-
+# Add HLA1 supertypes
+wav = pd.merge(wav, super1)
 wava = wav[wav.loci == "A"].sort_values('allele_freq', ascending=False, ignore_index = True)
 
-plt.bar(wava.allele, wava.allele_freq)
-plt.xticks(rotation=90)
+# Plot allele frequencies coloured by supertype
+sns.barplot(
+    y=wava.allele,
+    x=wava.allele_freq,
+    hue=wava.supertype,
+    dodge=False
+    )
 plt.show()
 
 plt.plot(wava.allele_freq.cumsum(), label="Cumulative AF")
@@ -26,3 +38,15 @@
 plt.axhline(y=1, color="black", linestyle="--")
 plt.legend()
 plt.show()
+
+for supertype in wava.supertype.unique():
+    print(supertype)
+    supertypedf = wava[wava.supertype == supertype].reset_index()
+    plt.plot(supertypedf.allele_freq.cumsum().apply(scrapeAF.population_coverage), label=supertype)
+plt.legend()
+plt.show()
+
+mask = wava.allele_freq.cumsum() > 0.95
+wava[~mask]
+wava[~mask].supertype.unique()
+
diff --git a/readme.md b/readme.md
index 32b8f7e..ae229bb 100644
--- a/readme.md
+++ b/readme.md
@@ -18,11 +18,21 @@ import scrapeAF
 When selecting alleles to represent a population, all supertypes
 should be represented.
 
-When combining extimates of allele frequency larger samples should
+When combining estimates of allele frequency larger samples should
 weigh more heavily. However, when combining estiamtes that disagree
 the uncertainty on the estimate should be larger than when combining
 equivalent samples that agree.
 
 When combining studies we must weight averages by sample size but
 when combining countries are we not better to weight by national population?
-Should sample size also have an effect?
\ No newline at end of file
+Should sample size also have an effect?
+
+IEDB provide reference sets of HLA alleles designed to cover the
+majority of the "general population". However, all populations are
+not likely to be equally well covered by them. Using population
+specific allele frequencies we should be able to select more
+appropriate HLA sets. However, allele frequency is not the only
+determinent when selecting a pannel of alleles. The pannel must
+also contain representatives of commonly shared binding specificities
+(i.e., supertypes).
+

From 80d02cca2fdf844d7d06828c133e8a01a237cf21 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 19 Aug 2022 16:46:51 +0100
Subject: [PATCH 013/192] Add colour to country data

---
 code/demos/compare_countries.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index bbeecd9..0f204f3 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -26,6 +26,8 @@
     df = pd.read_csv("data/example/%s_raw.csv" %country)
     df = scrapeAF.formatAF(df)
     wav = scrapeAF.combineAF(df)
+    wav['country'] = country
+    wavs.append(wav)
 
 wavs = pd.concat(wavs, axis=0).reset_index()
 

From a807b3ca763627376f544878fd1f23da82ce8980 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 22 Aug 2022 12:03:00 +0100
Subject: [PATCH 014/192] formatAF & unmeasured_alleles handled in combineAF

---
 code/demos/compare_countries.py         |  1 -
 code/demos/globalPCA.py                 | 40 +++++++++++++++++++++++++
 code/demos/international_frequencies.py |  4 ---
 code/demos/population_coverage.py       |  5 ----
 code/scrapeAF.py                        | 13 ++++++--
 5 files changed, 51 insertions(+), 12 deletions(-)
 create mode 100644 code/demos/globalPCA.py

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 0f204f3..96f57a6 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -24,7 +24,6 @@
 wavs = []
 for country in countries:
     df = pd.read_csv("data/example/%s_raw.csv" %country)
-    df = scrapeAF.formatAF(df)
     wav = scrapeAF.combineAF(df)
     wav['country'] = country
     wavs.append(wav)
diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
new file mode 100644
index 0000000..cb66f70
--- /dev/null
+++ b/code/demos/globalPCA.py
@@ -0,0 +1,40 @@
+"""
+Global PCA
+
+Calculate average AF for ~all countries and perform dimension
+reduction on that data to 2D (PCA, UMAP, t-SNE). Then plot
+those points coloured by geographic area.
+
+For this each country must have an estimate for the same set
+of alleles.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+countries = [
+    'United+Kingdom',
+    'Thailand',
+    'Uganda'
+]
+
+# # Download HLA allele frequencies
+# for country in countries:
+#     print(country)
+#     base_url = scrapeAF.makeURL(country)
+#     aftab = scrapeAF.getAFdata(base_url)
+#     aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
+
+wavs = []
+for country in countries:
+    df = pd.read_csv("data/example/%s_raw.csv" %country)
+    wav = scrapeAF.combineAF(df)
+    wav['country'] = country
+    wavs.append(wav)
+
+wavs = pd.concat(wavs, axis=0).reset_index()
+
+scrapeAF.unmeasured_alleles(wavs, 'country')
\ No newline at end of file
diff --git a/code/demos/international_frequencies.py b/code/demos/international_frequencies.py
index 0e90987..ff38e50 100644
--- a/code/demos/international_frequencies.py
+++ b/code/demos/international_frequencies.py
@@ -24,10 +24,6 @@
 for country in countries:
     # Load raw county data
     AFtab = pd.read_csv("data/example/%s_raw.csv" %country)
-    # format data
-    AFtab = scrapeAF.formatAF(AFtab)
-    # Add unreported alleles so AF sums to 1
-    AFtab = scrapeAF.unmeasured_alleles(AFtab)
     # Weighted average alleles
     wav = scrapeAF.combineAF(AFtab)
     # Add country to dataset
diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index 61b97aa..d062534 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -13,11 +13,6 @@
 super1.allele = super1.allele.apply(lambda x: x[:4]+':'+x[4:])
 
 AFtab = pd.read_csv("data/example/Uganda_raw.csv")
-AFtab = scrapeAF.formatAF(AFtab)
-
-# Add unreported alleles so AF sums to 1
-AFtab = scrapeAF.unmeasured_alleles(AFtab)
-
 # Weighted average alleles
 wav = scrapeAF.combineAF(AFtab)
 # Add HLA1 supertypes
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 94b30fe..0a1a744 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -114,6 +114,7 @@ def unmeasured_alleles(AFtab, datasetID='population'):
 
     Args:
         AFtab (pd.DataFrame): Formatted allele frequency data
+        datasetID (str): Unique identifier column for study
 
     Returns:
         pd.DataFrame: Allele frequency data with all locus alleles reported 
@@ -141,16 +142,24 @@ def unmeasured_alleles(AFtab, datasetID='population'):
             AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
     return AFtab
 
-def combineAF(df, weights='sample_size'):
+def combineAF(df, weights='sample_size', format=True, add_unmeasured=True, datasetID='population'):
     """Combine allele frequencies at multiple levels
 
     Args:
         df (pd.DataFrame): Table of Allele frequency data
+        weights (str): Column to weight averages by. Default 'sample_size'
+        format (boolean): run formatAF(), Default = True
+        add_unmeasured (boolean): run unmeasured_alleles(), Default = True
+        datasetID (str): Unique identifier column for study used by unmeasured_alleles()
 
     Returns:
         pd.DataFrame: Table of allele frequency data with alleles
-        grouped to make a weighted average based on sample size.
+        grouped to make a weighted average based on weights.
     """
+    if format:
+        df = formatAF(df)
+    if add_unmeasured:
+        df = unmeasured_alleles(df, datasetID)
     grouped = df.groupby('allele')
     combined = grouped.apply(
         lambda row: [

From 63d210fad3a9af581302c5ba30c43c45f3360b8e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 22 Aug 2022 12:45:11 +0100
Subject: [PATCH 015/192] Prepare allele frequencies for dimension reduction

---
 code/demos/globalPCA.py | 28 ++++++++++++++++++++++++++--
 1 file changed, 26 insertions(+), 2 deletions(-)

diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index cb66f70..47474d1 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -35,6 +35,30 @@
     wav['country'] = country
     wavs.append(wav)
 
-wavs = pd.concat(wavs, axis=0).reset_index()
+wavs = pd.concat(wavs, axis=0).reset_index(drop=True)
 
-scrapeAF.unmeasured_alleles(wavs, 'country')
\ No newline at end of file
+# Give record for all alleles to all countries
+wavs = scrapeAF.unmeasured_alleles(wavs, 'country')
+
+# Filter to single loci
+wavsa = wavs[wavs.loci == 'A']
+
+# Check all countries have the same number of alleles
+wavsa.groupby('country').allele.unique().apply(len)
+
+# Sort by allele then select a single country,
+# check that its alleles match a specified list
+# then use the frequencies as features
+wavsa = wavsa.sort_values('allele')
+
+sorted_alleles = sorted(list(wavsa.allele.unique()))
+
+AFeatures = []
+for country in countries:
+    mask = wavsa['country'] == country 
+    assert all(wavsa[mask].allele.unique() == sorted_alleles)
+    features = [country] + wavsa[mask].allele_freq.tolist()
+    AFeatures.append(features)
+
+# Dataframe of allele frequencies read for dimension reduction
+AFeatures = pd.DataFrame(AFeatures, columns = ['country'] + sorted_alleles)

From 1343dfddc017ac5800248698cd81db9b388b12f1 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 30 Aug 2022 16:55:51 +0100
Subject: [PATCH 016/192] Add loci to makeURL and error handling to Npages

---
 code/scrapeAF.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 0a1a744..ee7903c 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -13,13 +13,14 @@
 import numpy as np
 import logging
 
-def makeURL(country, standard='s'):
+def makeURL(country, standard='s', locus=""):
     base = "http://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
+    hla_locus = "hla_locus=%s&" %(locus)
     country = "hla_country=%s&" %(country)
     resolution = "hla_level=2&"
     standard = "standard=%s&" %standard
-    url = base + locus_type + country + resolution + standard
+    url = base + locus_type + hla_locus + country + resolution + standard
     return url
 
 def parseAF(bs):
@@ -67,6 +68,7 @@ def Npages(bs):
     """
     # Get the table with number of pages
     navtab = bs.find('div', {'id': 'divGenNavig'}).find('table', {'class': 'table10'})
+    assert navtab, f"navtab does not evaluate to True. Check URL returns results in web browser."
     # Get cell with ' of ' in 
     pagesOfN = [td.get_text(strip=True) for td in navtab.find_all('td') if " of " in td.text]
     # Check single cell returned

From 0f68fc6f7dd13533a320d0d8bea96153da8fcc30 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 30 Aug 2022 16:56:34 +0100
Subject: [PATCH 017/192] Download all  country HLA-A data & plot by region

---
 code/demos/globalPCA.py  | 67 ++++++++++++++++++++++++++++------------
 code/demos/globalPCA2.py | 51 ++++++++++++++++++++++++++++++
 code/setup.sh            |  3 +-
 3 files changed, 100 insertions(+), 21 deletions(-)
 create mode 100644 code/demos/globalPCA2.py

diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index 47474d1..7265be1 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -9,31 +9,54 @@
 of alleles.
 """
 
+import os
 import code.scrapeAF as scrapeAF
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-countries = [
-    'United+Kingdom',
-    'Thailand',
-    'Uganda'
-]
+regions = pd.read_csv("data/example/globalPCA/countries.csv")
 
-# # Download HLA allele frequencies
-# for country in countries:
-#     print(country)
-#     base_url = scrapeAF.makeURL(country)
-#     aftab = scrapeAF.getAFdata(base_url)
-#     aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
+# countries = [
+#     'United+Kingdom',
+#     'Thailand',
+#     'Uganda',
+#     'Greece',
+#     'Japan',
+#     'Germany',
+#     'Brazil',
+#     'Iraq',
+#     'Iran',
+#     'Israel',
+#     'Chile',
+#     'Kenya',
+#     'Spain',
+# ]
+
+countries = regions.Country.tolist()
+
+# Download HLA allele frequencies
+for country in countries:
+    print()
+    print(country)
+    if not os.path.exists("data/example/globalPCA/%s_raw.csv" %country):
+        base_url = scrapeAF.makeURL(country, standard="g", locus="A")
+        try:
+            aftab = scrapeAF.getAFdata(base_url)
+            aftab.to_csv("data/example/globalPCA/%s_raw.csv" %country, index=False)
+        except:
+            print(f"Failed to get data for {country}: {base_url}")
 
 wavs = []
 for country in countries:
-    df = pd.read_csv("data/example/%s_raw.csv" %country)
-    wav = scrapeAF.combineAF(df)
-    wav['country'] = country
-    wavs.append(wav)
+    try:
+        df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+        wav = scrapeAF.combineAF(df)
+        wav['country'] = country
+        wavs.append(wav)
+    except:
+        pass
 
 wavs = pd.concat(wavs, axis=0).reset_index(drop=True)
 
@@ -44,7 +67,7 @@
 wavsa = wavs[wavs.loci == 'A']
 
 # Check all countries have the same number of alleles
-wavsa.groupby('country').allele.unique().apply(len)
+wavsa.groupby('country').allele.unique().apply(len).unique()
 
 # Sort by allele then select a single country,
 # check that its alleles match a specified list
@@ -55,10 +78,14 @@
 
 AFeatures = []
 for country in countries:
-    mask = wavsa['country'] == country 
-    assert all(wavsa[mask].allele.unique() == sorted_alleles)
-    features = [country] + wavsa[mask].allele_freq.tolist()
-    AFeatures.append(features)
+    mask = wavsa['country'] == country
+    # Only generate features for countries with records
+    # e.g. Thailand has no loci A records
+    if any(mask):
+        assert all(wavsa[mask].allele.unique() == sorted_alleles)
+        features = [country] + wavsa[mask].allele_freq.tolist()
+        AFeatures.append(features)
 
 # Dataframe of allele frequencies read for dimension reduction
 AFeatures = pd.DataFrame(AFeatures, columns = ['country'] + sorted_alleles)
+AFeatures.to_csv("data/example/globalPCA/AF_features.csv", index=False)
diff --git a/code/demos/globalPCA2.py b/code/demos/globalPCA2.py
new file mode 100644
index 0000000..59e5b96
--- /dev/null
+++ b/code/demos/globalPCA2.py
@@ -0,0 +1,51 @@
+"""
+Global PCA
+
+Calculate average AF for ~all countries and perform dimension
+reduction on that data to 2D (PCA, UMAP, t-SNE). Then plot
+those points coloured by geographic area.
+
+For this each country must have an estimate for the same set
+of alleles.
+"""
+
+# Use umap conda env
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from sklearn.decomposition import PCA
+import umap
+
+AFeatures = pd.read_csv("data/example/globalPCA/AF_features.csv")
+regions = pd.read_csv("data/example/globalPCA/countries.csv")
+
+pca = PCA(n_components=2)
+pca_embedding = pca.fit_transform(AFeatures.loc[:,'A*01:01':].values)
+AFeatures['pca0'] = pca_embedding[:,0]
+AFeatures['pca1'] = pca_embedding[:,1]
+
+umapper = umap.UMAP(transform_seed=1234)
+umap_embedding = umapper.fit_transform(AFeatures.loc[:,'A*01:01':].values)
+AFeatures['umap0'] = umap_embedding[:,0]
+AFeatures['umap1'] = umap_embedding[:,1]
+
+# Add region to countries
+AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
+
+# plt.style.use('ggplot')
+
+for region in AFeatures.largeRegion.unique():
+    mask = AFeatures.largeRegion == region
+    plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
+    for i in AFeatures[mask].index:
+        plt.annotate(AFeatures.loc[i].country, AFeatures.loc[i][['pca0','pca1']])
+plt.legend()
+plt.show()
+
+for region in AFeatures.largeRegion.unique():
+    mask = AFeatures.largeRegion == region
+    plt.scatter(AFeatures.umap0[mask], AFeatures.umap1[mask], label=region)
+    for i in AFeatures[mask].index:
+        plt.annotate(AFeatures.loc[i].country, AFeatures.loc[i][['umap0','umap1']])
+plt.legend()
+plt.show()
diff --git a/code/setup.sh b/code/setup.sh
index e21fb06..37cb7e3 100644
--- a/code/setup.sh
+++ b/code/setup.sh
@@ -1,2 +1,3 @@
 #!/usr/bin/env bash
-mkdir data/example -p
\ No newline at end of file
+mkdir data/example -p
+mkdir data/example/globalPCA -p
\ No newline at end of file

From 9f02aef4630513118f3afe0d5419ee8e7eeff8e2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 1 Sep 2022 17:05:37 +0100
Subject: [PATCH 018/192] Change plot style

---
 code/demos/globalPCA2.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/code/demos/globalPCA2.py b/code/demos/globalPCA2.py
index 59e5b96..d7e6725 100644
--- a/code/demos/globalPCA2.py
+++ b/code/demos/globalPCA2.py
@@ -32,7 +32,7 @@
 # Add region to countries
 AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
 
-# plt.style.use('ggplot')
+# plt.style.use('fivethirtyeight')
 
 for region in AFeatures.largeRegion.unique():
     mask = AFeatures.largeRegion == region

From e4bbb7f3dd7bfbb04d4917109bb243154c0a4ca9 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 1 Sep 2022 17:05:53 +0100
Subject: [PATCH 019/192] Get started with scipy dirichlet

---
 code/dirichlet_test.py | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)
 create mode 100644 code/dirichlet_test.py

diff --git a/code/dirichlet_test.py b/code/dirichlet_test.py
new file mode 100644
index 0000000..9e74456
--- /dev/null
+++ b/code/dirichlet_test.py
@@ -0,0 +1,26 @@
+"""
+Tests with the dirichlet distribution
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.stats import dirichlet
+
+# define a Dirichlet Distributions with parameters alpha
+alpha = np.array([0.4, 5, 15])  # specify concentration parameters
+dd = dirichlet(alpha)
+
+dd.mean()
+dd.var()
+dd.entropy()
+
+dd.pdf([.6,.3,.1])
+
+# Visualise a dirichlet distribution as k normal distriubtions?
+# or let k=3 and plot a 3d surface like https://en.wikipedia.org/wiki/Dirichlet_distribution#/media/File:LogDirichletDensity-alpha_0.3_to_alpha_2.0.gif
+
+# update a dirichlet distribution with new info
+
+# show the reduction in variance
+
+# Compare addition of n agreeing samples and n disagreeing samples

From 307646bd7fb312fd5ba2e1a73637bb834f6325f6 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 2 Sep 2022 11:13:20 +0100
Subject: [PATCH 020/192] Visualise dirichlet and updates for k=3

---
 code/dirichlet_test.py | 122 +++++++++++++++++++++++++++++++++++++++--
 1 file changed, 117 insertions(+), 5 deletions(-)

diff --git a/code/dirichlet_test.py b/code/dirichlet_test.py
index 9e74456..ae38eb8 100644
--- a/code/dirichlet_test.py
+++ b/code/dirichlet_test.py
@@ -2,10 +2,29 @@
 Tests with the dirichlet distribution
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+from matplotlib import cm
+import numpy as np
 from scipy.stats import dirichlet
 
+def get_logpdf(x, y, z, alpha=[1,1,1]):
+    c = (x,y,z)
+    dd = dirichlet(alpha)
+    if all(a >= 0 and a<=1 for a in c):
+        logpdf = dd.logpdf(c)
+    else:
+        logpdf = np.nan
+    return logpdf
+
+def get_pdf(x, y, z, alpha=[1,1,1]):
+    c = (x,y,z)
+    dd = dirichlet(alpha)
+    if all(a >= 0 and a<=1 for a in c):
+        pdf = dd.pdf(c)
+    else:
+        pdf = np.nan
+    return pdf
+
 # define a Dirichlet Distributions with parameters alpha
 alpha = np.array([0.4, 5, 15])  # specify concentration parameters
 dd = dirichlet(alpha)
@@ -16,11 +35,104 @@
 
 dd.pdf([.6,.3,.1])
 
-# Visualise a dirichlet distribution as k normal distriubtions?
-# or let k=3 and plot a 3d surface like https://en.wikipedia.org/wiki/Dirichlet_distribution#/media/File:LogDirichletDensity-alpha_0.3_to_alpha_2.0.gif
+# Make data for k=3.
+k1 = np.arange(0, 1, 0.05)
+k2 = np.arange(0, 1, 0.05)
+k1, k2 = np.meshgrid(k1, k2)
+k3 = 1 - k1 - k2
+k3[k3<0] = np.nan
+
+################################
+#                              #
+#   Compare pdf and log pdf    #
+#                              #
+################################
+alpha = (3,3,3)
+
+pdf = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        pdf[i,j] =  dirichlet(alpha).pdf([k1[i,j], k2[i,j], k3[i,j]])
+
+logpdf = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        logpdf[i,j] =  dirichlet(alpha).logpdf([k1[i,j], k2[i,j], k3[i,j]])
+
+# Plot the surface.
+fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
+ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[0].set_title('PDF')
+ax[1].plot_surface(k1, k2, logpdf, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[1].set_title('Log pdf')
+plt.show()
+
+################################
+#                              #
+#       Update dirichlet       #
+#                              #
+################################
 
 # update a dirichlet distribution with new info
+# plot pdf before and after
+alpha = np.array([1,1,1])
+c = np.array([2,0,1])
+alpha2 = alpha+c
+
+pdf = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        pdf[i,j] =  dirichlet(alpha).pdf([k1[i,j], k2[i,j], k3[i,j]])
+
+pdf2 = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        pdf2[i,j] =  dirichlet(alpha2).pdf([k1[i,j], k2[i,j], k3[i,j]])
+
+# Plot the surface.
+fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
+ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[0].set_title(f'PDF {alpha}')
+ax[1].plot_surface(k1, k2, pdf2, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[1].set_title(f'PDF {alpha2}')
+plt.show()
+
+############################
+#                          #
+#   Study error ignored    #
+#                          #
+############################
+
+# Does not account for study level error
+alpha = np.array([1,1,1])
+# Two studies in agreement
+agree = alpha + np.array([3,3,0]) + np.array([3,3,0])
+#Two studies disagreeing
+disagree = alpha + np.array([6,0,0]) + np.array([0,6,0])
+
+all(agree == disagree)
+
+pdf = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        pdf[i,j] =  dirichlet(agree).pdf([k1[i,j], k2[i,j], k3[i,j]])
+
+pdf2 = np.zeros(k1.shape)
+for i in range(k1.shape[0]):
+    for j in range(k1.shape[1]):
+        pdf2[i,j] =  dirichlet(disagree).pdf([k1[i,j], k2[i,j], k3[i,j]])
 
-# show the reduction in variance
+# Plot the surface.
+fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
+ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[0].set_title(f'PDF agree')
+ax[1].plot_surface(k1, k2, pdf2, cmap=cm.plasma,
+    linewidth=0, antialiased=False)
+ax[1].set_title(f'PDF disagree')
+plt.show()
 
-# Compare addition of n agreeing samples and n disagreeing samples

From aa00cdac6c3ce3506652ab5e66e27b7b7ad023f2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 2 Sep 2022 16:21:30 +0100
Subject: [PATCH 021/192] Calculate average allele_freq from Dirichlet
 distribution

combineAF now uses the scipy dirichlet distribution means as the combined allele frequency.
To do this it calculates c for each row as reported allele freq
multiplied by the supplied weights argument, which defaults to
2n (which is also created as sample_size *2).
The default prior is [1]*k.

This function requires a single loci so this is asserted.

The demo files have been updated accordingly.
Mostly filtering to single loci, and removing unmeasured_alleles calls
because these are handled by combineAF().
---
 code/demos/compare_countries.py         | 14 ++++----
 code/demos/globalPCA.py                 | 15 ++++-----
 code/demos/international_frequencies.py | 19 +++++------
 code/demos/population_coverage.py       |  1 +
 code/dirichlet_test.py                  | 43 ++++++++++++++-----------
 code/scrapeAF.py                        | 25 ++++++++++++--
 6 files changed, 69 insertions(+), 48 deletions(-)

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 96f57a6..0d6c3ec 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -24,6 +24,7 @@
 wavs = []
 for country in countries:
     df = pd.read_csv("data/example/%s_raw.csv" %country)
+    df = df[df.loci=="A"]
     wav = scrapeAF.combineAF(df)
     wav['country'] = country
     wavs.append(wav)
@@ -35,26 +36,23 @@
 common_alleles = wavs[wavs.allele_freq > threshold].allele.unique()
 wavs = wavs[wavs.allele.isin(common_alleles)]
 
-# Focus on locus A and locus B
-wavsa = wavs[wavs.allele.str.contains("^A\*")]
-wavsb = wavs[wavs.allele.str.contains("^B\*")]
-
 fig, ax = plt.subplots(2)
 
 sns.barplot(
-    data = wavsa,
+    data = wavs,
     x = 'allele',
     y = 'allele_freq',
     hue = 'country',
     ax=ax[0]
 )
+
 sns.barplot(
-    data = wavsb,
+    data = wavs,
     x = 'allele',
-    y = 'allele_freq',
+    y = 'wav',
     hue = 'country',
     ax=ax[1]
 )
 
 plt.xticks(rotation=90)
-plt.show()
\ No newline at end of file
+plt.show()
diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index 7265be1..340510e 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -63,27 +63,24 @@
 # Give record for all alleles to all countries
 wavs = scrapeAF.unmeasured_alleles(wavs, 'country')
 
-# Filter to single loci
-wavsa = wavs[wavs.loci == 'A']
-
 # Check all countries have the same number of alleles
-wavsa.groupby('country').allele.unique().apply(len).unique()
+wavs.groupby('country').allele.unique().apply(len).unique()
 
 # Sort by allele then select a single country,
 # check that its alleles match a specified list
 # then use the frequencies as features
-wavsa = wavsa.sort_values('allele')
+wavs = wavs.sort_values('allele')
 
-sorted_alleles = sorted(list(wavsa.allele.unique()))
+sorted_alleles = sorted(list(wavs.allele.unique()))
 
 AFeatures = []
 for country in countries:
-    mask = wavsa['country'] == country
+    mask = wavs['country'] == country
     # Only generate features for countries with records
     # e.g. Thailand has no loci A records
     if any(mask):
-        assert all(wavsa[mask].allele.unique() == sorted_alleles)
-        features = [country] + wavsa[mask].allele_freq.tolist()
+        assert all(wavs[mask].allele.unique() == sorted_alleles)
+        features = [country] + wavs[mask].allele_freq.tolist()
         AFeatures.append(features)
 
 # Dataframe of allele frequencies read for dimension reduction
diff --git a/code/demos/international_frequencies.py b/code/demos/international_frequencies.py
index ff38e50..6508912 100644
--- a/code/demos/international_frequencies.py
+++ b/code/demos/international_frequencies.py
@@ -24,6 +24,7 @@
 for country in countries:
     # Load raw county data
     AFtab = pd.read_csv("data/example/%s_raw.csv" %country)
+    AFtab = AFtab[AFtab.loci == "A"]
     # Weighted average alleles
     wav = scrapeAF.combineAF(AFtab)
     # Add country to dataset
@@ -31,25 +32,21 @@
     wavs.append(wav)
 
 international = pd.concat(wavs, ignore_index=True)
-international = scrapeAF.unmeasured_alleles(international, 'country')
 # Add population size to weight averages
 international['population_size'] = international.country.apply(lambda x: population_sizes[x])
 
 #International Weighted Average
-iwav = scrapeAF.combineAF(international, 'population_size')
-
-intA = international[international.loci == 'A']
-iwava = iwav[iwav.loci == 'A']
+iwav = scrapeAF.combineAF(international, weights='population_size', datasetID='country')
 
 plt.scatter(
-    intA.allele,
-    intA.allele_freq,
-    c=[intA.country.unique().tolist().index(x) for x in intA.country],
-    s=intA.population_size/10000000
+    international.allele,
+    international.allele_freq,
+    c=[international.country.unique().tolist().index(x) for x in international.country],
+    s=international.population_size/10000000
     )
 plt.scatter(
-    iwava.allele,
-    iwava.allele_freq,
+    iwav.allele,
+    iwav.allele_freq,
     c='black',
     marker='x'
 )
diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index d062534..634ee9b 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -13,6 +13,7 @@
 super1.allele = super1.allele.apply(lambda x: x[:4]+':'+x[4:])
 
 AFtab = pd.read_csv("data/example/Uganda_raw.csv")
+AFtab =  AFtab[AFtab.loci=="A"]
 # Weighted average alleles
 wav = scrapeAF.combineAF(AFtab)
 # Add HLA1 supertypes
diff --git a/code/dirichlet_test.py b/code/dirichlet_test.py
index ae38eb8..49c5d5b 100644
--- a/code/dirichlet_test.py
+++ b/code/dirichlet_test.py
@@ -6,24 +6,8 @@
 from matplotlib import cm
 import numpy as np
 from scipy.stats import dirichlet
-
-def get_logpdf(x, y, z, alpha=[1,1,1]):
-    c = (x,y,z)
-    dd = dirichlet(alpha)
-    if all(a >= 0 and a<=1 for a in c):
-        logpdf = dd.logpdf(c)
-    else:
-        logpdf = np.nan
-    return logpdf
-
-def get_pdf(x, y, z, alpha=[1,1,1]):
-    c = (x,y,z)
-    dd = dirichlet(alpha)
-    if all(a >= 0 and a<=1 for a in c):
-        pdf = dd.pdf(c)
-    else:
-        pdf = np.nan
-    return pdf
+import pandas as pd
+import code.scrapeAF as scrapeAF
 
 # define a Dirichlet Distributions with parameters alpha
 alpha = np.array([0.4, 5, 15])  # specify concentration parameters
@@ -136,3 +120,26 @@ def get_pdf(x, y, z, alpha=[1,1,1]):
 ax[1].set_title(f'PDF disagree')
 plt.show()
 
+#############################
+#                           #
+#   Dirichlet allele freq   #
+#                           #
+#############################
+
+country = "Thailand"
+df = pd.read_csv("data/example/%s_raw.csv" %country)
+loci = "DPB1"
+dfa = df[df.loci == loci]
+caf = scrapeAF.combineAF(dfa)
+
+plt.scatter(
+    caf.wav,
+    caf.allele_freq
+)
+plt.show()
+
+plt.scatter(
+    caf.wav,
+    caf.wav-caf.allele_freq
+)
+plt.show()
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index ee7903c..152af94 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -11,6 +11,7 @@
 import requests
 import pandas as pd
 import numpy as np
+from scipy.stats import dirichlet
 import logging
 
 def makeURL(country, standard='s', locus=""):
@@ -144,7 +145,7 @@ def unmeasured_alleles(AFtab, datasetID='population'):
             AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
     return AFtab
 
-def combineAF(df, weights='sample_size', format=True, add_unmeasured=True, datasetID='population'):
+def combineAF(df, weights='2n', alpha = [], format=True, add_unmeasured=True, datasetID='population'):
     """Combine allele frequencies at multiple levels
 
     Args:
@@ -158,31 +159,51 @@ def combineAF(df, weights='sample_size', format=True, add_unmeasured=True, datas
         pd.DataFrame: Table of allele frequency data with alleles
         grouped to make a weighted average based on weights.
     """
+    single_loci(df)
     if format:
         df = formatAF(df)
     if add_unmeasured:
         df = unmeasured_alleles(df, datasetID)
+    try:
+        df['2n'] = df.sample_size * 2
+    except:
+        print("column '2n' could not be created")
+    df['c'] =  df.allele_freq * df[weights]
     grouped = df.groupby('allele')
     combined = grouped.apply(
         lambda row: [
         row.name,
         row.loci.unique()[0],
         np.average(row.allele_freq, weights=row[weights]),
+        row.c.sum(),
         row.sample_size.sum()
         ]
     )
     combined = pd.DataFrame(
         combined.tolist(),
-        columns = ['allele', 'loci', 'allele_freq', 'sample_size']
+        columns = ['allele', 'loci',
+            'wav',
+            'c', 'sample_size']
     )
     combined = combined.reset_index(drop=True)
     # Check that all alleles in a locus have the same sample size
     # after merging
     if duplicated_sample_size(combined):
         id_duplicated_allele(grouped)
+    if not alpha:
+        alpha = default_prior(len(combined.allele))
+    # Calculate Dirichlet mean for each allele
+    combined['allele_freq'] = dirichlet(alpha + combined.c).mean()
 
     return combined
 
+def default_prior(k):
+    alpha = [1] * k
+    return alpha
+
+def single_loci(df):
+    assert len(df.loci.unique()) == 1, f"'df' must conatain only 1 loci"
+
 def duplicated_sample_size(df):
     """Returns True if any loci has more than 1 unique sample size"""
     locus_sample_sizes = df.groupby('loci').sample_size.apply(lambda x: len(x.unique()))

From c0f918b3bf36717e8d6434bf8751488c6d678bdf Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 2 Sep 2022 17:08:59 +0100
Subject: [PATCH 022/192] Identify incomplete, or overfilled studies

---
 code/demos/check_study_completeness.py | 31 ++++++++++++++++++++++++++
 code/scrapeAF.py                       | 19 ++++++++++++++++
 2 files changed, 50 insertions(+)
 create mode 100644 code/demos/check_study_completeness.py

diff --git a/code/demos/check_study_completeness.py b/code/demos/check_study_completeness.py
new file mode 100644
index 0000000..34a0718
--- /dev/null
+++ b/code/demos/check_study_completeness.py
@@ -0,0 +1,31 @@
+"""
+Check that study-loci allele frequency sums to ~1.
+Some studies report alleles that do not sum to 1.
+Also download errors can lead to incomplete datasets.
+Some download settings can also lead to unexpected results.
+E.g. some studies report alleles to mixed resolution, therefore;
+if you search for a specific allele resolution you will download
+an incomplete dataset.
+
+Having the complete dataset is important, especially when
+calculating the Dirichlet distribution as reported alleles
+will be over weighted if some alleles are unreported.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+country = 'Thailand'
+# Because resolution equals 2, an incomplete dataset is returned
+base_url = scrapeAF.makeURL(country, standard="s")
+aftab = scrapeAF.getAFdata(base_url)
+aftab.to_csv("data/example/incomplete_raw.csv", index=False)
+
+df = pd.read_csv("data/example/incomplete_raw.csv")
+
+scrapeAF.study_completeness(df)
+
+# How to filter incomplete studies...
\ No newline at end of file
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 152af94..74edb7f 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -111,6 +111,24 @@ def formatAF(df):
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
     return df
 
+def study_completeness(df, llimit=0.95, ulimit=1.1):
+    """Report any studies with allele freqs that don't sum to 1
+
+    Args:
+        df (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+    """
+    poplocs = df.groupby(['population', 'loci']).allele_freq.sum()
+    lmask = poplocs < llimit
+    if sum(lmask>0):
+        print(poplocs[lmask])
+        print(f"{sum(lmask)} studies have total allele frequency < {llimit}")
+    umask = poplocs > ulimit
+    if sum(umask>0):
+        print(poplocs[umask])
+        print(f"{sum(umask)} studies have total allele frequency > {ulimit}")
+
 def unmeasured_alleles(AFtab, datasetID='population'):
     """When combining AF estimates, unreported alleles can inflate frequencies
         so AF sums to >1. Therefore we add unreported alleles with frequency zero.
@@ -160,6 +178,7 @@ def combineAF(df, weights='2n', alpha = [], format=True, add_unmeasured=True, da
         grouped to make a weighted average based on weights.
     """
     single_loci(df)
+    study_completeness(df)
     if format:
         df = formatAF(df)
     if add_unmeasured:

From f96861eb20c206979ecd28d28da857e69166e23e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 5 Sep 2022 16:19:56 +0100
Subject: [PATCH 023/192] Check study allele freq sum and allele resolution

---
 code/demos/check_study_completeness.py | 69 ++++++++++++++++++++++++--
 code/scrapeAF.py                       | 53 ++++++++++++++------
 2 files changed, 105 insertions(+), 17 deletions(-)

diff --git a/code/demos/check_study_completeness.py b/code/demos/check_study_completeness.py
index 34a0718..1771f0f 100644
--- a/code/demos/check_study_completeness.py
+++ b/code/demos/check_study_completeness.py
@@ -10,6 +10,15 @@
 Having the complete dataset is important, especially when
 calculating the Dirichlet distribution as reported alleles
 will be over weighted if some alleles are unreported.
+
+How to identify and resolve allele resolution. Because allele
+frequency estimates can only be combined if the allele name is
+identical all alleles in a study must have the same resolution
+i.e. A*01 is 2 digit resolution (or 1 field) and A*01:01 is
+4 digit (or 2 field). These cannot be combined as we cannot
+tell whether A*01 is A*01:01, A*01:02 etc. For the same reason
+we can decrease the resolution of an allele but we cannot
+increase it.
 """
 
 import code.scrapeAF as scrapeAF
@@ -19,13 +28,67 @@
 import seaborn as sns
 
 country = 'Thailand'
+
 # Because resolution equals 2, an incomplete dataset is returned
-base_url = scrapeAF.makeURL(country, standard="s")
+base_url = scrapeAF.makeURL(country, resolution_pattern="equal", resolution=2, standard="s")
 aftab = scrapeAF.getAFdata(base_url)
 aftab.to_csv("data/example/incomplete_raw.csv", index=False)
 
 df = pd.read_csv("data/example/incomplete_raw.csv")
 
-scrapeAF.study_completeness(df)
+# How to filter incomplete studies
+
+# Identify incomplete studies
+noncomplete = scrapeAF.incomplete_studies(df)
+
+# Returns False if population AND loci are in the noncomplete.index
+# AS A PAIR
+# This is important so that we don't throw away all data on a population
+# just because one loci is incomplete.
+complete_mask = df.apply(lambda x: (x.population, x.loci) not in noncomplete.index, axis=1)
+
+df = df[complete_mask]
+
+# Check filtering success
+scrapeAF.incomplete_studies(df)
+
+#################################
+#                               #
+#  Differing allele resolution  #
+#                               #
+#################################
+
+base_url = scrapeAF.makeURL(
+    'Thailand', locus="A",
+    resolution_pattern="bigger_equal_than", resolution=1
+)
+aftab = scrapeAF.getAFdata(base_url)
+aftab.to_csv("data/example/multiresolution_raw.csv", index=False)
+
+df = pd.read_csv("data/example/multiresolution_raw.csv")
+scrapeAF.check_resolution(df)
+
+# How many fields are reported for each allele?
+1 + df.allele.str.count(":")
+# How many alleles report to exactly n fields?
+(1 + df.allele.str.count(":")).value_counts()
+
+# You cant increase resolution 
+scrapeAF.decrease_resolution(df, 2)
+
+# But you can decrease
+df = scrapeAF.decrease_resolution(df, 1)
+scrapeAF.check_resolution(df)
+
+# In principal you could use 2 digit resolution
+# to estimate 4 digit resolution. E.g if A*01 has
+# frequency p we could increase the resolution by
+# spreading this across all possible A*01:xx alleles
+# More formally for k A*:01:xx alleles they would have
+# frequency p/k. This would effectively update the
+# Dirichlet distribution with a flat prior about which
+# allele A*01 was actually measured.
+
+# If this is of interest to you please open an issue or
+# pull request on github.
 
-# How to filter incomplete studies...
\ No newline at end of file
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 74edb7f..7456b99 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -14,14 +14,15 @@
 from scipy.stats import dirichlet
 import logging
 
-def makeURL(country, standard='s', locus=""):
+def makeURL(country, standard='s', locus="", resolution_pattern="bigger_equal_than", resolution=2):
     base = "http://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
     hla_locus = "hla_locus=%s&" %(locus)
     country = "hla_country=%s&" %(country)
-    resolution = "hla_level=2&"
+    hla_level_pattern = "hla_level_pattern=%s&" %(resolution_pattern)
+    hla_level = "hla_level=%s&" %(resolution)
     standard = "standard=%s&" %standard
-    url = base + locus_type + hla_locus + country + resolution + standard
+    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard
     return url
 
 def parseAF(bs):
@@ -106,12 +107,13 @@ def getAFdata(base_url):
     tabs = pd.concat(tabs)
     return tabs
 
-def formatAF(df):
+def formatAF(AFtab):
+    df = AFtab.copy()
     if df.sample_size.dtype == "O":
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
     return df
 
-def study_completeness(df, llimit=0.95, ulimit=1.1):
+def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
     """Report any studies with allele freqs that don't sum to 1
 
     Args:
@@ -119,7 +121,7 @@ def study_completeness(df, llimit=0.95, ulimit=1.1):
         llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
         ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
     """
-    poplocs = df.groupby(['population', 'loci']).allele_freq.sum()
+    poplocs = AFtab.groupby([datasetID, 'loci']).allele_freq.sum()
     lmask = poplocs < llimit
     if sum(lmask>0):
         print(poplocs[lmask])
@@ -128,6 +130,25 @@ def study_completeness(df, llimit=0.95, ulimit=1.1):
     if sum(umask>0):
         print(poplocs[umask])
         print(f"{sum(umask)} studies have total allele frequency > {ulimit}")
+    incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
+    return incomplete
+
+def check_resolution(AFtab):
+    resolution = 1 + AFtab.allele.str.count(":")
+    resVC = resolution.value_counts()
+    pass_check = len(resVC) == 1
+    if not pass_check:
+        print(resVC)
+        print(f"Multiple resolutions in AFtab. Fix with decrease_resolution()")
+    return pass_check
+
+def decrease_resolution(AFtab, newres):
+    df = AFtab.copy()
+    resolution = 1 + df.allele.str.count(":")
+    assert all(resolution >= newres), f"Some alleles have resolution below {newres}"
+    new_allele = df.allele.str.split(":").apply(lambda x: ":".join(x[:newres]))
+    df.allele = new_allele
+    return df
 
 def unmeasured_alleles(AFtab, datasetID='population'):
     """When combining AF estimates, unreported alleles can inflate frequencies
@@ -160,10 +181,10 @@ def unmeasured_alleles(AFtab, datasetID='population'):
             missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
             missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci',datasetID,'allele_freq','carriers%','sample_size'])
             # Add them in with zero frequency
-            AFtab = pd.concat([AFtab, missing_rows], ignore_index=True)
-    return AFtab
+            df = pd.concat([AFtab, missing_rows], ignore_index=True)
+    return df
 
-def combineAF(df, weights='2n', alpha = [], format=True, add_unmeasured=True, datasetID='population'):
+def combineAF(AFtab, weights='2n', alpha = [], format=True, add_unmeasured=True, complete=True, resolution=True, datasetID='population'):
     """Combine allele frequencies at multiple levels
 
     Args:
@@ -177,8 +198,12 @@ def combineAF(df, weights='2n', alpha = [], format=True, add_unmeasured=True, da
         pd.DataFrame: Table of allele frequency data with alleles
         grouped to make a weighted average based on weights.
     """
+    df = AFtab.copy()
     single_loci(df)
-    study_completeness(df)
+    if complete:
+        assert incomplete_studies(df).empty, "ATfab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+    if resolution:
+        assert check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
         df = formatAF(df)
     if add_unmeasured:
@@ -220,12 +245,12 @@ def default_prior(k):
     alpha = [1] * k
     return alpha
 
-def single_loci(df):
-    assert len(df.loci.unique()) == 1, f"'df' must conatain only 1 loci"
+def single_loci(AFtab):
+    assert len(AFtab.loci.unique()) == 1, f"'AFtab' must conatain only 1 loci"
 
-def duplicated_sample_size(df):
+def duplicated_sample_size(AFtab):
     """Returns True if any loci has more than 1 unique sample size"""
-    locus_sample_sizes = df.groupby('loci').sample_size.apply(lambda x: len(x.unique()))
+    locus_sample_sizes = AFtab.groupby('loci').sample_size.apply(lambda x: len(x.unique()))
     return any(locus_sample_sizes != 1)
 
 def id_duplicated_allele(grouped):

From 17906c5c9173ac65e0f813449fa35aa5a5560330 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 6 Sep 2022 10:56:16 +0100
Subject: [PATCH 024/192] Collapse alleles after reducing resolution

This fix is part of the changes made to calculate dirichlet means.
Also check that each allele is unique in a dataset when combining.
Fixed a bug in unmeasured_alleles.
---
 code/demos/check_study_completeness.py  | 15 ++++--
 code/demos/compare_countries.py         | 10 +++-
 code/demos/globalPCA.py                 | 23 +++------
 code/demos/globalPCA2.py                |  2 +-
 code/demos/international_frequencies.py |  4 ++
 code/scrapeAF.py                        | 62 ++++++++++++++++++++-----
 6 files changed, 81 insertions(+), 35 deletions(-)

diff --git a/code/demos/check_study_completeness.py b/code/demos/check_study_completeness.py
index 1771f0f..e456a2f 100644
--- a/code/demos/check_study_completeness.py
+++ b/code/demos/check_study_completeness.py
@@ -68,11 +68,6 @@
 df = pd.read_csv("data/example/multiresolution_raw.csv")
 scrapeAF.check_resolution(df)
 
-# How many fields are reported for each allele?
-1 + df.allele.str.count(":")
-# How many alleles report to exactly n fields?
-(1 + df.allele.str.count(":")).value_counts()
-
 # You cant increase resolution 
 scrapeAF.decrease_resolution(df, 2)
 
@@ -80,6 +75,16 @@
 df = scrapeAF.decrease_resolution(df, 1)
 scrapeAF.check_resolution(df)
 
+# Alleles that were distinct at a higher resolution but
+# are indistinguishable at this new lower resolution,
+# have been collapsed into one allele with the same
+# sample size but the sum of constituent allele frequencies
+
+# You can check that each allele is still unique but this is
+# done automatically when reducing resolution or combining
+# allele frequencies.
+scrapeAF.alleles_unique_in_study(df)
+
 # In principal you could use 2 digit resolution
 # to estimate 4 digit resolution. E.g if A*01 has
 # frequency p we could increase the resolution by
diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 0d6c3ec..cb9ed45 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -10,7 +10,6 @@
 
 countries = [
     'United+Kingdom',
-    'Thailand',
     'Uganda'
 ]
 
@@ -56,3 +55,12 @@
 
 plt.xticks(rotation=90)
 plt.show()
+
+# Similarity of weighted allele freq and Diriclet mean
+x = max(max(wavs.allele_freq),max(wavs.wav))
+plt.plot((0,x), (0,x), 'k--')
+plt.scatter(
+    wavs.allele_freq,
+    wavs.wav
+)
+plt.show()
diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index 340510e..590d78e 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -16,27 +16,15 @@
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-regions = pd.read_csv("data/example/globalPCA/countries.csv")
-
-# countries = [
-#     'United+Kingdom',
-#     'Thailand',
-#     'Uganda',
-#     'Greece',
-#     'Japan',
-#     'Germany',
-#     'Brazil',
-#     'Iraq',
-#     'Iran',
-#     'Israel',
-#     'Chile',
-#     'Kenya',
-#     'Spain',
-# ]
+# Countries in regions as defined on 
+# http://www.allelefrequencies.net/datasets.asp#tag_4
+regions = pd.read_csv("data/example/countries.csv")
 
 countries = regions.Country.tolist()
 
 # Download HLA allele frequencies
+# Not all countries have data
+# those without will print "Failed to get data for..."
 for country in countries:
     print()
     print(country)
@@ -52,6 +40,7 @@
 for country in countries:
     try:
         df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+        df = scrapeAF.decrease_resolution(df, 2)
         wav = scrapeAF.combineAF(df)
         wav['country'] = country
         wavs.append(wav)
diff --git a/code/demos/globalPCA2.py b/code/demos/globalPCA2.py
index d7e6725..db235b8 100644
--- a/code/demos/globalPCA2.py
+++ b/code/demos/globalPCA2.py
@@ -17,7 +17,7 @@
 import umap
 
 AFeatures = pd.read_csv("data/example/globalPCA/AF_features.csv")
-regions = pd.read_csv("data/example/globalPCA/countries.csv")
+regions = pd.read_csv("data/example/countries.csv")
 
 pca = PCA(n_components=2)
 pca_embedding = pca.fit_transform(AFeatures.loc[:,'A*01:01':].values)
diff --git a/code/demos/international_frequencies.py b/code/demos/international_frequencies.py
index 6508912..a4ac244 100644
--- a/code/demos/international_frequencies.py
+++ b/code/demos/international_frequencies.py
@@ -31,6 +31,10 @@
     wav['country'] = country
     wavs.append(wav)
 
+AFtab[AFtab.allele=="A*66:02"]
+AFtab[AFtab.allele=="A*66:03"]
+
+
 international = pd.concat(wavs, ignore_index=True)
 # Add population size to weight averages
 international['population_size'] = international.country.apply(lambda x: population_sizes[x])
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 7456b99..6f92fcf 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -142,13 +142,40 @@ def check_resolution(AFtab):
         print(f"Multiple resolutions in AFtab. Fix with decrease_resolution()")
     return pass_check
 
-def decrease_resolution(AFtab, newres):
+def decrease_resolution(AFtab, newres, datasetID='population'):
     df = AFtab.copy()
     resolution = 1 + df.allele.str.count(":")
-    assert all(resolution >= newres), f"Some alleles have resolution below {newres}"
+    assert all(resolution >= newres), f"Some alleles have resolution below {newres} fields"
     new_allele = df.allele.str.split(":").apply(lambda x: ":".join(x[:newres]))
     df.allele = new_allele
-    return df
+    collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
+    return collapsed
+
+def collapse_reduced_alleles(AFtab, datasetID='population'):
+    df = AFtab.copy()
+    # Group by alleles withing datasets
+    grouped = df.groupby([datasetID,'allele'])
+    # Sum allele freq but keep other columns
+    collapsed = grouped.apply(
+        lambda row: [
+            sum(row.allele_freq),
+            row.sample_size.unique()[0],
+            row.loci.unique()[0],
+            len(row.loci.unique()),
+            len(row.sample_size.unique())
+        ]
+    )
+    collapsed = pd.DataFrame(
+        collapsed.tolist(),
+        index=collapsed.index,
+        columns = ['allele_freq', 'sample_size', 'loci', '#loci', '#sample_sizes']
+    ).reset_index()
+    # Within a study each all identical alleles should have the same loci and sample size
+    assert all(collapsed['#loci'] == 1), "Multiple loci found for a single allele in a single population"
+    assert all(collapsed['#sample_sizes'] == 1), "Multiple sample_sizes found for a single allele in a single population"
+    collapsed = collapsed[['allele', 'loci','population','allele_freq','sample_size']]
+    alleles_unique_in_study(collapsed)
+    return collapsed
 
 def unmeasured_alleles(AFtab, datasetID='population'):
     """When combining AF estimates, unreported alleles can inflate frequencies
@@ -162,29 +189,30 @@ def unmeasured_alleles(AFtab, datasetID='population'):
         pd.DataFrame: Allele frequency data with all locus alleles reported 
             for each dataset
     """
-    loci = AFtab.loci.unique()
+    df = AFtab.copy()
+    loci = df.loci.unique()
     # Iterate over loci separately
     for locus in loci:
         # Iterate over each dataset reporting that locus
-        datasets = AFtab[AFtab.loci == locus][datasetID].unique()
+        datasets = df[df.loci == locus][datasetID].unique()
         for dataset in datasets:
             # Single locus, single dataset
-            datasetAF = AFtab[(AFtab[datasetID] == dataset) & (AFtab.loci == locus)]
+            datasetAF = df[(df[datasetID] == dataset) & (df.loci == locus)]
             # What was the sample size for this data?
             dataset_sample_size = datasetAF.sample_size.unique()
             assert len(dataset_sample_size) == 1, "dataset_sample_size must be 1, not %s" %len(dataset_sample_size)
             dataset_sample_size = dataset_sample_size[0]
             # Get all alleles for this locus (across datasets)
-            ualleles = AFtab[AFtab.loci == locus].allele.unique()
+            ualleles = df[df.loci == locus].allele.unique()
             # Which of these alleles are not in this dataset?
             missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
             missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
             missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci',datasetID,'allele_freq','carriers%','sample_size'])
             # Add them in with zero frequency
-            df = pd.concat([AFtab, missing_rows], ignore_index=True)
+            df = pd.concat([df, missing_rows], ignore_index=True)
     return df
 
-def combineAF(AFtab, weights='2n', alpha = [], format=True, add_unmeasured=True, complete=True, resolution=True, datasetID='population'):
+def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
     """Combine allele frequencies at multiple levels
 
     Args:
@@ -200,8 +228,10 @@ def combineAF(AFtab, weights='2n', alpha = [], format=True, add_unmeasured=True,
     """
     df = AFtab.copy()
     single_loci(df)
+    if unique:
+        assert alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
     if complete:
-        assert incomplete_studies(df).empty, "ATfab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        assert incomplete_studies(df, datasetID=datasetID).empty, "ATfab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
     if resolution:
         assert check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
@@ -248,6 +278,16 @@ def default_prior(k):
 def single_loci(AFtab):
     assert len(AFtab.loci.unique()) == 1, f"'AFtab' must conatain only 1 loci"
 
+def alleles_unique_in_study(AFtab, datasetID='population'):
+    df = AFtab.copy()
+    grouped = df.groupby([datasetID,'allele'])
+    # Are allele alleles unique? i.e. do any occur multiple times in grouping?
+    unique = grouped.size()[grouped.size()>1].empty
+    if not unique:
+        print("Non unique alleles in population")
+        print(grouped.size()[grouped.size()>1])
+    return unique
+
 def duplicated_sample_size(AFtab):
     """Returns True if any loci has more than 1 unique sample size"""
     locus_sample_sizes = AFtab.groupby('loci').sample_size.apply(lambda x: len(x.unique()))
@@ -256,7 +296,7 @@ def duplicated_sample_size(AFtab):
 def id_duplicated_allele(grouped):
     """ Reports the allele that has mupltiple sample sizes """
     duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
-    assert all(~duplicated_population), "duplicated population within allele %s" %duplicated_population[duplicated_population]
+    assert all(~duplicated_population), "duplicated population within allele %s" %duplicated_population[duplicated_population].index.tolist()
 
 
 def population_coverage(p):

From 4501eccf42c4e1d3284ab93a58e5698800fd105b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Sep 2022 11:29:04 +0100
Subject: [PATCH 025/192] Add notes about why to save downloaded AF

---
 code/demos/compare_countries.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index cb9ed45..17c0d7a 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -19,6 +19,9 @@
     base_url = scrapeAF.makeURL(country)
     aftab = scrapeAF.getAFdata(base_url)
     aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
+# If you use the data directly without saving and loading it
+# pandas treats the numeric columns as strings (allele_freq and sample size)
+# which throws errors later when doing maths
 
 wavs = []
 for country in countries:

From d2d06cc46ecb045c5b85b1aac19f52bbbee2de38 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Sep 2022 11:29:57 +0100
Subject: [PATCH 026/192] Explicitly sort grouped dataframe when combining

This doesn't change anything as it sorts by default
---
 code/scrapeAF.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 6f92fcf..d9a05d0 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -243,7 +243,7 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
     except:
         print("column '2n' could not be created")
     df['c'] =  df.allele_freq * df[weights]
-    grouped = df.groupby('allele')
+    grouped = df.groupby('allele', sort=True)
     combined = grouped.apply(
         lambda row: [
         row.name,

From 770314ad81ed4bd3761091ad0a9edc0e750231f3 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Sep 2022 14:17:43 +0100
Subject: [PATCH 027/192] Add conda env dependencies

---
 readme.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/readme.md b/readme.md
index ae229bb..08fec7b 100644
--- a/readme.md
+++ b/readme.md
@@ -36,3 +36,7 @@ determinent when selecting a pannel of alleles. The pannel must
 also contain representatives of commonly shared binding specificities
 (i.e., supertypes).
 
+# Dependencies
+scrapeAF
+umap
+maps

From 8be3b3e5b6bdfa7b3ef86919121d13410886a9f2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Sep 2022 14:17:57 +0100
Subject: [PATCH 028/192] Calculate entropy and plot as choropleth

---
 code/demos/entropy_map.py | 66 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 66 insertions(+)
 create mode 100644 code/demos/entropy_map.py

diff --git a/code/demos/entropy_map.py b/code/demos/entropy_map.py
new file mode 100644
index 0000000..6339fa2
--- /dev/null
+++ b/code/demos/entropy_map.py
@@ -0,0 +1,66 @@
+"""
+Entropy of country average allele frequencies
+"""
+
+# use maps conda env
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import geopandas as gpd
+import geoplot as gplt
+from scipy.stats import dirichlet
+
+regions = pd.read_csv("data/example/countries.csv")
+regions.index = regions.Country
+regions['country'] = regions.Country.str.replace("+"," ")
+
+regions['entropy'] = np.nan
+regions['total_sample_size'] = np.nan
+regions['populations'] = np.nan
+
+countries = regions.Country.tolist()
+
+for country in countries:
+    print(country)
+    try:
+        df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+        df = scrapeAF.decrease_resolution(df, 2)
+        caf = scrapeAF.combineAF(df)
+        # Recreate the Dirichlet distribution
+        alpha = scrapeAF.default_prior(len(caf.allele))
+        dd = dirichlet(alpha + caf.c)
+        # Calculate entropy
+        regions.loc[country, 'entropy'] = dd.entropy()
+        # How many populations in the country?
+        regions.loc[country, 'populations'] = len(df.population.unique())
+        # Calculate total sample size
+        regions.loc[country, 'total_sample_size'] = caf.sample_size.unique()[0]
+    except:
+        pass
+
+######## World plot
+world = gpd.read_file(
+    gpd.datasets.get_path('naturalearth_lowres')
+)
+
+# Not all countries are in both datasets,
+# Some of this is due to alternative naming
+# Will require manual editting.
+regions[~regions.country.isin(world.name)].country
+world.name[~world.name.isin(regions.country)]
+
+world_regions = pd.merge(world, regions, how="left", left_on="name", right_on="country")
+
+fig, ax = plt.subplots(2,2)
+gplt.choropleth(world_regions, hue="entropy", legend=True, ax=ax[0,0])
+ax[0,0].set_title('Entropy')
+gplt.choropleth(world_regions, hue="populations", legend=True, ax=ax[0,1])
+ax[0,1].set_title('Populations')
+gplt.choropleth(world_regions, hue="total_sample_size", legend=True, ax=ax[1,0])
+ax[1,0].set_title('Total sample size')
+plt.show()
+
+world_regions[world_regions.name.str.contains('ahara')]
+world_regions.sort_values('entropy')
\ No newline at end of file

From dd7285712b349cdcbd486f1e64f8af9701e55374 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Sep 2022 17:20:43 +0100
Subject: [PATCH 029/192] Visualise high K dirichlet as beta distributions

Also allows plotting sample estimates onto distribution
---
 code/visualise_high_k_dirichlet.py | 124 +++++++++++++++++++++++++++++
 1 file changed, 124 insertions(+)
 create mode 100644 code/visualise_high_k_dirichlet.py

diff --git a/code/visualise_high_k_dirichlet.py b/code/visualise_high_k_dirichlet.py
new file mode 100644
index 0000000..8cf0132
--- /dev/null
+++ b/code/visualise_high_k_dirichlet.py
@@ -0,0 +1,124 @@
+"""
+Visualise high k Dirichlet
+"""
+
+import matplotlib.pyplot as plt
+from matplotlib import cm
+import numpy as np
+from scipy.stats import dirichlet, beta
+import pandas as pd
+import math
+import code.scrapeAF as scrapeAF
+
+#####################
+#                   #
+#   Define alpha    #
+#                   #
+#####################
+
+# Load allele frequency data
+AFtab = pd.read_csv(f"data/example/outlier_raw.csv")
+# Reduce resolution to 2 fields and collapse alleles
+AFtab = scrapeAF.decrease_resolution(AFtab, 2)
+# Combined allle frequency
+# noncomplete = scrapeAF.incomplete_studies(AFtab)
+# complete_mask = AFtab.apply(lambda x: (x.population, x.loci) not in noncomplete.index, axis=1)
+# AFtab = AFtab[complete_mask]
+caf = scrapeAF.combineAF(AFtab)
+# Recreate the Dirichlet distribution
+naivealpha = scrapeAF.default_prior(len(caf.allele))
+
+# Dirichlet distribution concentration parameters 
+# based on allele frequency data
+alpha = naivealpha + caf.c
+
+######################
+#                    #
+# View k=3 Dirichlet #
+#                    #
+######################
+if len(alpha) == 3:
+    dd = dirichlet(alpha)
+    # Make data for k=3.
+    k1 = np.arange(0, 1, 0.05)
+    k2 = np.arange(0, 1, 0.05)
+    k1, k2 = np.meshgrid(k1, k2)
+    k3 = 1 - k1 - k2
+    k3[k3<0] = np.nan
+
+    pdf = np.zeros(k1.shape)
+    for i in range(k1.shape[0]):
+        for j in range(k1.shape[1]):
+            pdf[i,j] =  dd.pdf([k1[i,j], k2[i,j], k3[i,j]])
+
+    # Plot the surface.
+    fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
+    ax.plot_surface(k1, k2, pdf, cmap=cm.plasma,
+        linewidth=0, antialiased=False)
+    ax.set_title('PDF')
+else:
+    print( "Surface plot only works with k==3")
+
+######################
+#                    #
+#   View Dirichlet   #
+#       as beta      #
+#                    #
+######################
+    
+def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", log=False, psteps=1000, ncol=2):
+    """Plot the (log) posterior density function of all frequencies
+        for all alleles based on supplied alpha for Dirichlet
+        distribution. Options for adding empirical values
+        and plotting the log pdf.
+
+    Args:
+        alpha (list): Dirichlet concentration parameters, can be prior + caf.c
+        caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by scrapeAF.combinedAF(). You must use the same dataframe as this function doesn't have the error checking that scrapeAF.combineAF() has. Defaults to pd.DataFrame().
+        datasetID (str, optional): The column used to define datasets. Defaults to "population".
+        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
+        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
+        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
+    """
+    # Get beta parameters for each k in Dirichlet
+    ab = [(a,sum(alpha)-a) for a in alpha]
+    pline = np.linspace(0,1,psteps)
+    if not AFtab.empty:
+        # Format the populatoin allele frequencies
+        df = AFtab.copy()
+        df = scrapeAF.unmeasured_alleles(df, datasetID=datasetID)
+        df = df.sort_values('allele')
+        assert all(df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
+    fig, axs = plt.subplots(math.ceil(len(alpha)/ncol), ncol)
+    for i,x in enumerate(alpha):
+        subplotselector = i//ncol, i%ncol
+        a,b = ab[i]
+        bd = beta(a,b)
+        if log:
+            pdf = [bd.logpdf(p) for p in pline]
+        else:
+            pdf = [bd.pdf(p) for p in pline]
+        ax = axs[subplotselector]
+        if not AFtab.empty:
+            # Add the empirical allele frequency for each population
+            for af in df.groupby('population').allele_freq.apply(list).apply(lambda x: x[i]):
+                # x is the reported allele freq, y is it's pdf with scatter
+                if log:
+                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
+                else:
+                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
+        ax.plot(pline, pdf)
+        # Annotate with alpha
+        ax.text(0.5, max(pdf)/2, f"alpha {round(alpha[i])}")
+        if not caf.empty:
+            # Plot the combined average
+            ax.axvline(caf.allele_freq[i], color="black", ls="--")
+        # fig.tight_layout()
+    plt.show()
+
+# plotAFprob(alpha)
+# plotAFprob(alpha, caf)
+plotAFprob(alpha, caf, AFtab)
+plotAFprob(alpha, caf, AFtab, log=True)
+

From 37580b071982cd33bd2d930f7483fa22ad69202a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 30 Sep 2022 16:35:22 +0100
Subject: [PATCH 030/192] Fail to identify outlier populations

Commited code but will imediately delete.

Test demo to identify outlier populations based on pdf.
However is unsuccessful because the AF pdf peaks are so sharp that
effectively all real world populations have pdf zero.
---
 code/demos/outlier_populations.py | 70 +++++++++++++++++++++++++++++++
 1 file changed, 70 insertions(+)
 create mode 100644 code/demos/outlier_populations.py

diff --git a/code/demos/outlier_populations.py b/code/demos/outlier_populations.py
new file mode 100644
index 0000000..d74981e
--- /dev/null
+++ b/code/demos/outlier_populations.py
@@ -0,0 +1,70 @@
+"""
+Identify poulations that are outliers relative to the country.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+from scipy.stats import dirichlet
+
+# Dirichlet throws an error if frequencies do not sum to 1.
+# Massage the frequencies to sum to 2
+def sumto1(af):
+    # Compress/Inflate all values by a factor so they sum to 1
+    ciFactor = 1/np.sum(af)
+    af1 = [x*ciFactor for x in af]
+    return af1
+
+country = "Thailand"
+# Download dataset
+# base_url = scrapeAF.makeURL(country, 'g', locus='DQB1')
+# AFtab = scrapeAF.getAFdata(base_url)
+# AFtab.to_csv("data/example/outlier_raw.csv", index=False)
+
+AFtab = pd.read_csv(f"data/example/outlier_raw.csv")
+# Reduce resolution to 2 fields and collapse alleles
+AFtab = scrapeAF.decrease_resolution(AFtab, 2)
+# Combined allle frequency
+caf = scrapeAF.combineAF(AFtab)
+
+# Recreate the Dirichlet distribution
+alpha = scrapeAF.default_prior(len(caf.allele))
+dd = dirichlet(alpha + caf.c)
+
+# Get allele freqs from a single population
+# it must be in the same order as the dirichlet
+datasetID = 'population'
+df = scrapeAF.unmeasured_alleles(AFtab, datasetID=datasetID)
+df = df.sort_values('allele')
+
+df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())
+df.groupby('population').allele_freq.apply(list)
+
+# The probability density function of actual samples is almost always zero
+# This may be because some alleles are never seen in some samples
+# This could be solved by adding pseudo counts...
+for i in range(5):
+    # print(i)
+    af = df.groupby('population').allele_freq.apply(list)[i]
+    # pseudoAF = [x if x>0 else x+0.1 for x in af]
+    # af1 = sumto1(pseudoAF)
+    af1 = sumto1(af)
+    # [round(x,3) for x in af1]
+    dd.logpdf(af1)
+
+[round(x,3) for x in caf.allele_freq.tolist()]
+
+# Random draws from the Dirichlet distribution
+# do not have zero pdf
+draws = pd.DataFrame(np.random.dirichlet(alpha+caf.c, 1000))
+pdfs = draws.apply(lambda x: dd.pdf(list(x)), axis=1)
+plt.hist(pdfs)
+plt.show()
+
+
+
+# Should we have a function/class that creates
+# and holds the dirichlet distribution?
\ No newline at end of file

From 8e946a7f0420a7b339d40d3fded449fadf92ec11 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 30 Sep 2022 16:36:18 +0100
Subject: [PATCH 031/192] Outlier population demo deleted as pdf always 0

---
 code/demos/outlier_populations.py | 70 -------------------------------
 1 file changed, 70 deletions(-)
 delete mode 100644 code/demos/outlier_populations.py

diff --git a/code/demos/outlier_populations.py b/code/demos/outlier_populations.py
deleted file mode 100644
index d74981e..0000000
--- a/code/demos/outlier_populations.py
+++ /dev/null
@@ -1,70 +0,0 @@
-"""
-Identify poulations that are outliers relative to the country.
-"""
-
-import code.scrapeAF as scrapeAF
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-from scipy.stats import dirichlet
-
-# Dirichlet throws an error if frequencies do not sum to 1.
-# Massage the frequencies to sum to 2
-def sumto1(af):
-    # Compress/Inflate all values by a factor so they sum to 1
-    ciFactor = 1/np.sum(af)
-    af1 = [x*ciFactor for x in af]
-    return af1
-
-country = "Thailand"
-# Download dataset
-# base_url = scrapeAF.makeURL(country, 'g', locus='DQB1')
-# AFtab = scrapeAF.getAFdata(base_url)
-# AFtab.to_csv("data/example/outlier_raw.csv", index=False)
-
-AFtab = pd.read_csv(f"data/example/outlier_raw.csv")
-# Reduce resolution to 2 fields and collapse alleles
-AFtab = scrapeAF.decrease_resolution(AFtab, 2)
-# Combined allle frequency
-caf = scrapeAF.combineAF(AFtab)
-
-# Recreate the Dirichlet distribution
-alpha = scrapeAF.default_prior(len(caf.allele))
-dd = dirichlet(alpha + caf.c)
-
-# Get allele freqs from a single population
-# it must be in the same order as the dirichlet
-datasetID = 'population'
-df = scrapeAF.unmeasured_alleles(AFtab, datasetID=datasetID)
-df = df.sort_values('allele')
-
-df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())
-df.groupby('population').allele_freq.apply(list)
-
-# The probability density function of actual samples is almost always zero
-# This may be because some alleles are never seen in some samples
-# This could be solved by adding pseudo counts...
-for i in range(5):
-    # print(i)
-    af = df.groupby('population').allele_freq.apply(list)[i]
-    # pseudoAF = [x if x>0 else x+0.1 for x in af]
-    # af1 = sumto1(pseudoAF)
-    af1 = sumto1(af)
-    # [round(x,3) for x in af1]
-    dd.logpdf(af1)
-
-[round(x,3) for x in caf.allele_freq.tolist()]
-
-# Random draws from the Dirichlet distribution
-# do not have zero pdf
-draws = pd.DataFrame(np.random.dirichlet(alpha+caf.c, 1000))
-pdfs = draws.apply(lambda x: dd.pdf(list(x)), axis=1)
-plt.hist(pdfs)
-plt.show()
-
-
-
-# Should we have a function/class that creates
-# and holds the dirichlet distribution?
\ No newline at end of file

From 424d2498083f74d6a1bc803d5e96e5574b62168e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 30 Sep 2022 16:39:36 +0100
Subject: [PATCH 032/192] Calculate central credibility interval for beta

---
 code/dirichlet_test.py             | 19 +++++-
 code/scrapeAF.py                   | 95 +++++++++++++++++++++++++++++-
 code/visualise_high_k_dirichlet.py | 57 +-----------------
 3 files changed, 112 insertions(+), 59 deletions(-)

diff --git a/code/dirichlet_test.py b/code/dirichlet_test.py
index 49c5d5b..153c55a 100644
--- a/code/dirichlet_test.py
+++ b/code/dirichlet_test.py
@@ -5,7 +5,7 @@
 import matplotlib.pyplot as plt
 from matplotlib import cm
 import numpy as np
-from scipy.stats import dirichlet
+from scipy.stats import dirichlet, beta
 import pandas as pd
 import code.scrapeAF as scrapeAF
 
@@ -143,3 +143,20 @@
     caf.wav-caf.allele_freq
 )
 plt.show()
+
+########################
+#                      #
+#   Central credible   #
+#   region from beta   #
+#                      #
+########################
+
+pline = np.linspace(0, 1, 1000)
+a,b = 2,5
+bd = beta(a,b)
+pdf = bd.pdf(pline)
+cl,cu = scrapeAF.betaCI(a,b)
+
+plt.plot(pline, pdf)
+plt.fill_between([cl,cu], [bd.pdf(cl), bd.pdf(cu)], alpha=0.5)
+plt.show()
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index d9a05d0..0c74035 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -11,7 +11,9 @@
 import requests
 import pandas as pd
 import numpy as np
-from scipy.stats import dirichlet
+import matplotlib.pyplot as plt
+import math
+from scipy.stats import dirichlet, beta
 import logging
 
 def makeURL(country, standard='s', locus="", resolution_pattern="bigger_equal_than", resolution=2):
@@ -231,7 +233,7 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
     if unique:
         assert alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
     if complete:
-        assert incomplete_studies(df, datasetID=datasetID).empty, "ATfab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        assert incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
     if resolution:
         assert check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
@@ -266,8 +268,9 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
         id_duplicated_allele(grouped)
     if not alpha:
         alpha = default_prior(len(combined.allele))
+    combined['alpha'] = alpha
     # Calculate Dirichlet mean for each allele
-    combined['allele_freq'] = dirichlet(alpha + combined.c).mean()
+    combined['allele_freq'] = dirichlet(combined.alpha + combined.c).mean()
 
     return combined
 
@@ -314,6 +317,92 @@ def population_coverage(p):
     hetero = 2*p*q
     return homo + hetero
 
+def betaAB(alpha):
+    """Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
+
+    Args:
+        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
+
+    Returns:
+        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.
+    """
+    ab = [(a,sum(alpha)-a) for a in alpha]
+    return ab
+
+def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", log=False, psteps=1000, ncol=2, ci=0.95):
+    """Plot the (log) posterior density function of all frequencies
+        for all alleles based on supplied alpha for Dirichlet
+        distribution. Options for adding empirical values
+        and plotting the log pdf.
+
+    Args:
+        alpha (list): Dirichlet concentration parameters, can be prior + caf.c
+        caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by scrapeAF.combinedAF(). You must use the same dataframe as this function doesn't have the error checking that scrapeAF.combineAF() has. Defaults to pd.DataFrame().
+        datasetID (str, optional): The column used to define datasets. Defaults to "population".
+        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
+        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
+        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
+        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+    """
+    # Get beta parameters for each k in Dirichlet
+    ab = betaAB(alpha)
+    pline = np.linspace(0,1,psteps)
+    if not AFtab.empty:
+        # Format the population allele frequencies
+        df = AFtab.copy()
+        df = unmeasured_alleles(df, datasetID=datasetID)
+        df = df.sort_values('allele')
+        assert all(df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
+    fig, axs = plt.subplots(math.ceil(len(alpha)/ncol), ncol)
+    for i,x in enumerate(alpha):
+        subplotselector = i//ncol, i%ncol
+        a,b = ab[i]
+        bd = beta(a,b)
+        if log:
+            pdf = [bd.logpdf(p) for p in pline]
+        else:
+            pdf = [bd.pdf(p) for p in pline]
+        ax = axs[subplotselector]
+        if not AFtab.empty:
+            # Add the empirical allele frequency for each population
+            for af in df.groupby('population').allele_freq.apply(list).apply(lambda x: x[i]):
+                # x is the reported allele freq, y is it's pdf with scatter
+                if log:
+                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
+                else:
+                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
+        ax.plot(pline, pdf)
+        # Annotate with alpha
+        ax.text(0.5, max(pdf)/2, f"alpha {round(alpha[i])}")
+        if not caf.empty:
+            # Plot the combined average
+            ax.axvline(caf.allele_freq[i], color="black", ls="--")
+        if ci:
+            cl,cu = betaCI(a,b, ci)
+            ax.axvline(cl, color="black", linestyle="dotted")
+            ax.axvline(cu, color="black", linestyle="dotted")
+        # fig.tight_layout()
+    plt.show()
+
+def betaCI(a,b,credible_interval=0.95):
+    """Calculat the central credible interval of a beta distribution
+
+    Args:
+        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
+        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
+        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+    Returns:
+        _type_: _description_
+    """
+    bd = beta(a,b)
+    lower_quantile = (1-credible_interval)/2
+    upper_quantile = 1-lower_quantile
+    lower_interval = bd.ppf(lower_quantile)
+    upper_interval = bd.ppf(upper_quantile)
+    return lower_interval, upper_interval
+
 # url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
 # base_url = makeURL("Philippines")
 
diff --git a/code/visualise_high_k_dirichlet.py b/code/visualise_high_k_dirichlet.py
index 8cf0132..307ed86 100644
--- a/code/visualise_high_k_dirichlet.py
+++ b/code/visualise_high_k_dirichlet.py
@@ -7,7 +7,6 @@
 import numpy as np
 from scipy.stats import dirichlet, beta
 import pandas as pd
-import math
 import code.scrapeAF as scrapeAF
 
 #####################
@@ -65,60 +64,8 @@
 #       as beta      #
 #                    #
 ######################
-    
-def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", log=False, psteps=1000, ncol=2):
-    """Plot the (log) posterior density function of all frequencies
-        for all alleles based on supplied alpha for Dirichlet
-        distribution. Options for adding empirical values
-        and plotting the log pdf.
-
-    Args:
-        alpha (list): Dirichlet concentration parameters, can be prior + caf.c
-        caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by scrapeAF.combinedAF(). You must use the same dataframe as this function doesn't have the error checking that scrapeAF.combineAF() has. Defaults to pd.DataFrame().
-        datasetID (str, optional): The column used to define datasets. Defaults to "population".
-        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
-        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
-        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
-    """
-    # Get beta parameters for each k in Dirichlet
-    ab = [(a,sum(alpha)-a) for a in alpha]
-    pline = np.linspace(0,1,psteps)
-    if not AFtab.empty:
-        # Format the populatoin allele frequencies
-        df = AFtab.copy()
-        df = scrapeAF.unmeasured_alleles(df, datasetID=datasetID)
-        df = df.sort_values('allele')
-        assert all(df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
-    fig, axs = plt.subplots(math.ceil(len(alpha)/ncol), ncol)
-    for i,x in enumerate(alpha):
-        subplotselector = i//ncol, i%ncol
-        a,b = ab[i]
-        bd = beta(a,b)
-        if log:
-            pdf = [bd.logpdf(p) for p in pline]
-        else:
-            pdf = [bd.pdf(p) for p in pline]
-        ax = axs[subplotselector]
-        if not AFtab.empty:
-            # Add the empirical allele frequency for each population
-            for af in df.groupby('population').allele_freq.apply(list).apply(lambda x: x[i]):
-                # x is the reported allele freq, y is it's pdf with scatter
-                if log:
-                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
-                else:
-                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
-        ax.plot(pline, pdf)
-        # Annotate with alpha
-        ax.text(0.5, max(pdf)/2, f"alpha {round(alpha[i])}")
-        if not caf.empty:
-            # Plot the combined average
-            ax.axvline(caf.allele_freq[i], color="black", ls="--")
-        # fig.tight_layout()
-    plt.show()
 
 # plotAFprob(alpha)
 # plotAFprob(alpha, caf)
-plotAFprob(alpha, caf, AFtab)
-plotAFprob(alpha, caf, AFtab, log=True)
-
+scrapeAF.plotAFprob(alpha, caf, AFtab)
+scrapeAF.plotAFprob(alpha, caf, AFtab, log=True)

From 1a44f5d672d9a522e474c90d8f7ce356bf89a4d7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 7 Oct 2022 14:01:13 +0100
Subject: [PATCH 033/192] Calculate and plot credible intervals

---
 code/demos/compare_countries.py               |  2 +
 .../{ => demos}/visualise_high_k_dirichlet.py |  8 ++-
 code/scrapeAF.py                              | 70 ++++++++++++-------
 3 files changed, 51 insertions(+), 29 deletions(-)
 rename code/{ => demos}/visualise_high_k_dirichlet.py (94%)

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 17c0d7a..8f5e8c1 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -28,6 +28,8 @@
     df = pd.read_csv("data/example/%s_raw.csv" %country)
     df = df[df.loci=="A"]
     wav = scrapeAF.combineAF(df)
+    # Add credible intervals
+    wav['cl','cu'] = scrapeAF.AFci(wav)
     wav['country'] = country
     wavs.append(wav)
 
diff --git a/code/visualise_high_k_dirichlet.py b/code/demos/visualise_high_k_dirichlet.py
similarity index 94%
rename from code/visualise_high_k_dirichlet.py
rename to code/demos/visualise_high_k_dirichlet.py
index 307ed86..abfda8a 100644
--- a/code/visualise_high_k_dirichlet.py
+++ b/code/demos/visualise_high_k_dirichlet.py
@@ -65,7 +65,9 @@
 #                    #
 ######################
 
-# plotAFprob(alpha)
+scrapeAF.plotAFprob(concentration=alpha)
 # plotAFprob(alpha, caf)
-scrapeAF.plotAFprob(alpha, caf, AFtab)
-scrapeAF.plotAFprob(alpha, caf, AFtab, log=True)
+scrapeAF.plotAFprob(caf, AFtab)
+scrapeAF.plotAFprob(caf, AFtab, log=True)
+
+
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 0c74035..817c902 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -329,24 +329,60 @@ def betaAB(alpha):
     ab = [(a,sum(alpha)-a) for a in alpha]
     return ab
 
-def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", log=False, psteps=1000, ncol=2, ci=0.95):
+def betaCI(a,b,credible_interval=0.95):
+    """Calculat the central credible interval of a beta distribution
+
+    Args:
+        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
+        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
+        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+    Returns:
+        _type_: _description_
+    """
+    bd = beta(a,b)
+    lower_quantile = (1-credible_interval)/2
+    upper_quantile = 1-lower_quantile
+    lower_interval = bd.ppf(lower_quantile)
+    upper_interval = bd.ppf(upper_quantile)
+    return lower_interval, upper_interval
+
+def AFci(caf, credible_interval=0.95):
+    """Calculate credible interval for combined allele frequency table
+
+    Args:
+        caf (pd.DataFrame): Table produced by scrapeAF.combineAF()
+        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
+
+    Returns:
+        list: Lower and upper credible intervals as a list of tuples
+    """
+    ab = betaAB(
+        caf.alpha + caf.c,
+    )
+    ci = [betaCI(a, b, credible_interval) for a,b in ab]
+    return ci
+
+def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, ci=0.95):
     """Plot the (log) posterior density function of all frequencies
-        for all alleles based on supplied alpha for Dirichlet
+        for all alleles based on concentration for Dirichlet
         distribution. Options for adding empirical values
         and plotting the log pdf.
 
     Args:
-        alpha (list): Dirichlet concentration parameters, can be prior + caf.c
         caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
         AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by scrapeAF.combinedAF(). You must use the same dataframe as this function doesn't have the error checking that scrapeAF.combineAF() has. Defaults to pd.DataFrame().
         datasetID (str, optional): The column used to define datasets. Defaults to "population".
+        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
         log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
         psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
         ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
         ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
     """
+    if concentration.empty:
+        concentration = caf.alpha + caf.c
     # Get beta parameters for each k in Dirichlet
-    ab = betaAB(alpha)
+    ab = betaAB(concentration)
     pline = np.linspace(0,1,psteps)
     if not AFtab.empty:
         # Format the population allele frequencies
@@ -354,8 +390,8 @@ def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="popul
         df = unmeasured_alleles(df, datasetID=datasetID)
         df = df.sort_values('allele')
         assert all(df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
-    fig, axs = plt.subplots(math.ceil(len(alpha)/ncol), ncol)
-    for i,x in enumerate(alpha):
+    fig, axs = plt.subplots(math.ceil(len(concentration)/ncol), ncol)
+    for i,x in enumerate(concentration):
         subplotselector = i//ncol, i%ncol
         a,b = ab[i]
         bd = beta(a,b)
@@ -373,8 +409,8 @@ def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="popul
                 else:
                     ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
         ax.plot(pline, pdf)
-        # Annotate with alpha
-        ax.text(0.5, max(pdf)/2, f"alpha {round(alpha[i])}")
+        # Annotate with concentration
+        ax.text(0.5, max(pdf)/2, f"Concentration {round(concentration[i])}")
         if not caf.empty:
             # Plot the combined average
             ax.axvline(caf.allele_freq[i], color="black", ls="--")
@@ -385,24 +421,6 @@ def plotAFprob(alpha, caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="popul
         # fig.tight_layout()
     plt.show()
 
-def betaCI(a,b,credible_interval=0.95):
-    """Calculat the central credible interval of a beta distribution
-
-    Args:
-        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
-        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
-        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
-
-    Returns:
-        _type_: _description_
-    """
-    bd = beta(a,b)
-    lower_quantile = (1-credible_interval)/2
-    upper_quantile = 1-lower_quantile
-    lower_interval = bd.ppf(lower_quantile)
-    upper_interval = bd.ppf(upper_quantile)
-    return lower_interval, upper_interval
-
 # url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
 # base_url = makeURL("Philippines")
 

From 6d874f21c256c6156acedf1b6573542ede2dd156 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 7 Oct 2022 15:14:14 +0100
Subject: [PATCH 034/192] Replace "population" with datasetID in plotAFprob

---
 code/scrapeAF.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 817c902..3567e6f 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -389,7 +389,7 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         df = AFtab.copy()
         df = unmeasured_alleles(df, datasetID=datasetID)
         df = df.sort_values('allele')
-        assert all(df.groupby('population').allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
+        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
     fig, axs = plt.subplots(math.ceil(len(concentration)/ncol), ncol)
     for i,x in enumerate(concentration):
         subplotselector = i//ncol, i%ncol
@@ -402,7 +402,7 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         ax = axs[subplotselector]
         if not AFtab.empty:
             # Add the empirical allele frequency for each population
-            for af in df.groupby('population').allele_freq.apply(list).apply(lambda x: x[i]):
+            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
                 # x is the reported allele freq, y is it's pdf with scatter
                 if log:
                     ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))

From b4e736dc11f7d8a6756a53e61f154089057ef5ef Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 7 Oct 2022 16:04:28 +0100
Subject: [PATCH 035/192] Allow plotting only a subset of alleles

---
 code/demos/visualise_high_k_dirichlet.py | 12 +++++----
 code/scrapeAF.py                         | 32 ++++++++++++++++++++----
 2 files changed, 34 insertions(+), 10 deletions(-)

diff --git a/code/demos/visualise_high_k_dirichlet.py b/code/demos/visualise_high_k_dirichlet.py
index abfda8a..52e4b56 100644
--- a/code/demos/visualise_high_k_dirichlet.py
+++ b/code/demos/visualise_high_k_dirichlet.py
@@ -65,9 +65,11 @@
 #                    #
 ######################
 
-scrapeAF.plotAFprob(concentration=alpha)
-# plotAFprob(alpha, caf)
+# View pdf only
+scrapeAF.plotAFprob(concentration=alpha, ci=0)
+# View estimated AF
+scrapeAF.plotAFprob(caf)
+# View estimated AF with individual studies
 scrapeAF.plotAFprob(caf, AFtab)
-scrapeAF.plotAFprob(caf, AFtab, log=True)
-
-
+# View subset of alleles
+scrapeAF.plotAFprob(caf, AFtab, alleles=["DQB1*03:01","DQB1*05:01","DQB1*05:02"])
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 3567e6f..52f661b 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -363,7 +363,7 @@ def AFci(caf, credible_interval=0.95):
     ci = [betaCI(a, b, credible_interval) for a,b in ab]
     return ci
 
-def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, ci=0.95):
+def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, ci=0.95, alleles=[]):
     """Plot the (log) posterior density function of all frequencies
         for all alleles based on concentration for Dirichlet
         distribution. Options for adding empirical values
@@ -379,6 +379,22 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
         ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
     """
+    def allele_mask(alleles, concentration):
+        """Create boolean mask either to keep only supplied `alleles`. If empty keep all.
+
+        Args:
+            alleles (list): list of alleles
+            concentration (list): Dirichlet concentration
+
+        Returns:
+            list: List of booleans to use as mask
+        """
+        if not alleles:
+            mask = [True] * len(concentration)
+        else:
+            mask = caf.allele.isin(alleles)
+        return mask
+
     if concentration.empty:
         concentration = caf.alpha + caf.c
     # Get beta parameters for each k in Dirichlet
@@ -390,9 +406,12 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         df = unmeasured_alleles(df, datasetID=datasetID)
         df = df.sort_values('allele')
         assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
-    fig, axs = plt.subplots(math.ceil(len(concentration)/ncol), ncol)
-    for i,x in enumerate(concentration):
-        subplotselector = i//ncol, i%ncol
+    mask = allele_mask(alleles, concentration)
+    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol)
+    # Only indexes that pass the mask
+    masked_indexes = [i for i,x in enumerate(mask) if x]
+    for subploti,i in enumerate(masked_indexes):
+        subplotselector = subploti//ncol, subploti%ncol
         a,b = ab[i]
         bd = beta(a,b)
         if log:
@@ -409,8 +428,11 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
                 else:
                     ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
         ax.plot(pline, pdf)
+        # Annotate with allele
+        if not caf.empty:
+            ax.text(0.5, max(pdf)/2, f"{caf.allele.iloc[i]}")
         # Annotate with concentration
-        ax.text(0.5, max(pdf)/2, f"Concentration {round(concentration[i])}")
+        # ax.text(0.5, max(pdf)/3, f"Concentration {round(concentration.iloc[i])}")
         if not caf.empty:
             # Plot the combined average
             ax.axvline(caf.allele_freq[i], color="black", ls="--")

From f6f8971e9ea349b3a60312021c7e7b6404ad93e3 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 10 Oct 2022 10:46:09 +0100
Subject: [PATCH 036/192] Demo single country allele frequency combination

---
 code/demos/compare_countries.py |   5 +-
 code/demos/single_country.py    | 102 ++++++++++++++++++++++++++++++++
 code/scrapeAF.py                |  52 +++++++++++++---
 3 files changed, 146 insertions(+), 13 deletions(-)
 create mode 100644 code/demos/single_country.py

diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index 8f5e8c1..ee8b636 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -19,9 +19,6 @@
     base_url = scrapeAF.makeURL(country)
     aftab = scrapeAF.getAFdata(base_url)
     aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
-# If you use the data directly without saving and loading it
-# pandas treats the numeric columns as strings (allele_freq and sample size)
-# which throws errors later when doing maths
 
 wavs = []
 for country in countries:
@@ -29,7 +26,7 @@
     df = df[df.loci=="A"]
     wav = scrapeAF.combineAF(df)
     # Add credible intervals
-    wav['cl','cu'] = scrapeAF.AFci(wav)
+    wav[['cl','cu']] = scrapeAF.AFci(wav)
     wav['country'] = country
     wavs.append(wav)
 
diff --git a/code/demos/single_country.py b/code/demos/single_country.py
new file mode 100644
index 0000000..e1f0f0c
--- /dev/null
+++ b/code/demos/single_country.py
@@ -0,0 +1,102 @@
+"""
+Single country
+
+Calculate average
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+#########################
+#                       #
+#   Download AF data    #
+#                       #
+#########################
+"""
+Pick a country to download AF data for. Spaces in country names
+are replaced with '+', if in doubt use the allelefrequencies.net
+website to search for a country and then check the url for the
+appropriate spelling.
+"""
+
+country = "Thailand"
+
+base_url = scrapeAF.makeURL(country)
+aftab = scrapeAF.getAFdata(base_url)
+aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
+#aftab = pd.read_csv("data/example/%s_raw.csv" %country)
+
+#########################
+#                       #
+#   Check completeness  #
+#                       #
+#########################
+"""
+We can't yet combine allele frequency estimates because not all
+studies sum to an allele frequency of 1. In this case it is because some studies
+reported allele frequencies at 1 field of resolution and we only downloaded
+alleles with >2.
+
+To drop incomplete studies use `only_complete()` which will print out the studies
+that were incomplete. To view incomplete studies without dropping them use
+`incomplete_studies()` before dropping studies.
+"""
+
+# Drop any incomplete studies
+aftab = scrapeAF.only_complete(aftab)
+
+#########################
+#                       #
+#   Check resolution    #
+#                       #
+#########################
+"""
+Because allele frequency estimates can only be combined if the
+allele name is identical, all alleles in a set of studies must have
+the same resolution i.e. A*01 is 2 digit resolution (or 1 field) and
+A*01:01 is 4 digit (or 2 field). These cannot be combined as we
+cannot tell whether A*01 is A*01:01, A*01:02 etc. For the same reason
+we can decrease the resolution of an allele but we cannot
+increase it.
+
+Before combining allele frequency estimates we may have to reduce the
+resolution of some alleles. `check_resolution()` will report if all
+alleles are at the same resolution and the number of estimates at
+each resolution.
+
+`decrease_resolution()` reduces the resolution of all alleles to a
+specified level so they can be combined.
+"""
+
+scrapeAF.check_resolution(aftab)
+
+aftab = scrapeAF.decrease_resolution(aftab, 2)
+
+
+#########################
+#                       #
+#     Combine AFs       #
+#                       #
+#########################
+
+"""
+We can only combine allele frequency estimates for a single loci
+at a time. So we filter the data to a single loci and then combine
+allele frequency estimates using `combineAF()`
+"""
+
+scrapeAF.combineAF(aftab)
+
+afloc = aftab[aftab.loci=="DRB1"]
+caf = scrapeAF.combineAF(afloc)
+
+# Calculate credible interval
+caf[['cl','cu']] = scrapeAF.AFci(caf)
+
+caf.plot.barh('allele', 'allele_freq')
+plt.show()
+
+scrapeAF.plotAFprob(caf, afloc)
+scrapeAF.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 52f661b..324744a 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -15,6 +15,7 @@
 import math
 from scipy.stats import dirichlet, beta
 import logging
+import warnings
 
 def makeURL(country, standard='s', locus="", resolution_pattern="bigger_equal_than", resolution=2):
     base = "http://www.allelefrequencies.net/hla6006a.asp?"
@@ -82,7 +83,15 @@ def Npages(bs):
     N = int(N)
     return N
 
-def getAFdata(base_url):
+def formatAF(AFtab):
+    df = AFtab.copy()
+    if df.sample_size.dtype == "O":
+        df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
+    if df.allele_freq.dtype == "O":
+        df.allele_freq = pd.to_numeric(df.allele_freq)
+    return df
+
+def getAFdata(base_url, format=True):
     """Get all allele frequency data from a search base url. Iterates over all
         pages regardless of which page is based.
 
@@ -106,22 +115,23 @@ def getAFdata(base_url):
         bs = BeautifulSoup(requests.get(url).text, 'html.parser')
         tab = parseAF(bs)
         tabs.append(tab)
+    print("Download complete")
     tabs = pd.concat(tabs)
+    if format:
+        try:
+            tabs = formatAF(tabs)
+        except:
+            print("Formatting failed, non-numeric datatypes may remain.")
     return tabs
 
-def formatAF(AFtab):
-    df = AFtab.copy()
-    if df.sample_size.dtype == "O":
-        df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
-    return df
-
 def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
     """Report any studies with allele freqs that don't sum to 1
 
     Args:
-        df (pd.DataFrame): Dataframe containing multiple studies
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
         llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
         ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study
     """
     poplocs = AFtab.groupby([datasetID, 'loci']).allele_freq.sum()
     lmask = poplocs < llimit
@@ -135,6 +145,28 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
     incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
     return incomplete
 
+def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
+    """Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+    This prevents throwing away data if another loci in the population is incomplete
+
+    Args:
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study. Defaults to 'population'.
+
+    Returns:
+        pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
+    """
+    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
+    # Returns False if population AND loci are in the noncomplete.index
+    # AS A PAIR
+    # This is important so that we don't throw away all data on a population
+    # just because one loci is incomplete.
+    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
+    df = AFtab[complete_mask]
+    return df
+
 def check_resolution(AFtab):
     resolution = 1 + AFtab.allele.str.count(":")
     resVC = resolution.value_counts()
@@ -417,7 +449,9 @@ def allele_mask(alleles, concentration):
         if log:
             pdf = [bd.logpdf(p) for p in pline]
         else:
-            pdf = [bd.pdf(p) for p in pline]
+            with warnings.catch_warnings():
+                warnings.simplefilter("ignore")
+                pdf = [bd.pdf(p) for p in pline]
         ax = axs[subplotselector]
         if not AFtab.empty:
             # Add the empirical allele frequency for each population

From 50eab29b8d16ea6695bdff497dd4a75c7a0a6537 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 10 Oct 2022 17:00:29 +0100
Subject: [PATCH 037/192] demo multicountry average. add custom xlim to plot

---
 code/demos/multi_country.py | 156 ++++++++++++++++++++++++++++++++++++
 code/scrapeAF.py            |   7 +-
 2 files changed, 160 insertions(+), 3 deletions(-)
 create mode 100644 code/demos/multi_country.py

diff --git a/code/demos/multi_country.py b/code/demos/multi_country.py
new file mode 100644
index 0000000..fd642da
--- /dev/null
+++ b/code/demos/multi_country.py
@@ -0,0 +1,156 @@
+"""
+Calculate multi-country average
+
+We can calculate the average allele frequency of multiple countries
+by combining studies within countries and then between countries.
+This second step is very similar except we set `datasetID` as the country
+rather than the population which is the default. 
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+countries = ['Cameroon','Cape+Verde','Ghana','Guinea',
+    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',
+    'South+Africa','Uganda','Zimbabwe']
+
+# Download HLA allele frequencies
+for country in countries:
+    print(country)
+    base_url = scrapeAF.makeURL(
+        country, standard='s', locus="A",
+        resolution_pattern="bigger_equal_than", resolution=2)
+    aftab = scrapeAF.getAFdata(base_url)
+    aftab.to_csv("data/example/multi_country/%s_raw.csv" %country, index=False)
+
+# Combine alleles frequencies within country
+cafs = []
+for country in countries:
+    # Load raw county data
+    aftab = pd.read_csv("data/example/multi_country/%s_raw.csv" %country)
+    # Drop any incomplete studies
+    aftab = scrapeAF.only_complete(aftab)
+    # Ensure all alleles have the same resolution
+    aftab = scrapeAF.decrease_resolution(aftab, 2)
+    # Combine studies within country
+    caf = scrapeAF.combineAF(aftab)
+    # Add country name to dataset, this is used as `datasetID` going forward
+    caf['country'] = country
+    cafs.append(caf)
+
+# Concatenate all combined single country allele frequency data
+# into a single dataframe
+cafs = pd.concat(cafs, ignore_index=True)
+# Combine allele frequency data of all countries
+international = scrapeAF.combineAF(cafs, datasetID='country')
+
+# Plot international averages as bar plot
+international.plot.barh('allele', 'allele_freq')
+plt.show()
+
+# Plot national averages as grouped bar plot
+cafs.pivot(index='allele', columns='country', values='allele_freq').plot.bar()
+plt.show()
+
+# Plot international allele frequencies estimates and individual countries
+scrapeAF.plotAFprob(international, cafs, datasetID='country', ncol=4)
+
+# Plot specific alleles and zoom in on frequencies
+# Select alleles to plot
+hifreq = international[international.allele_freq > 0.01].allele
+# Must be a list
+hifreq = hifreq.tolist()
+# Plot only selected alleles
+scrapeAF.plotAFprob(
+    international,
+    cafs,
+    datasetID='country',
+    ncol=4,
+    xmax=cafs.allele_freq.max(),
+    alleles=hifreq)
+
+"""
+From these plots we can clearly see that one country has much
+higher frequencies of A*24:02, A*11:01, and A*34:01.
+It is also clear that the international average allele
+frequency for A*24:02 is being skewed by this country. We can view the
+`cafs` dataset to see which country this is, Guinea.
+
+This method can
+also be applied to individual countries to identify studies which
+differ from the majority, possibly because it focuses on a specific
+ethnic group.
+"""
+
+cafs[cafs.allele == "A*24:02"].sort_values('allele_freq')
+
+# How to weight countries differently?
+
+"""
+When calculating the average allele frequency the "concentration"
+parameter of the Dirichlet distribution is calculated as `weights`
+multiplied by the dataset allele frequency (where dataset is usually
+a single study but can be a country etc, this is what `datasetID`
+refers to). By default `weights` is double the sample size as each
+sample provides 2n due to diploidy.
+
+If estimating allele frequency for a region, it may be important to
+account for the size of national populations. Below we calculate an
+individual weight for each country, individuals from large countries
+contibute more to the total sample but the total sample size is
+unchanged. A county's populaion, as a proportion of the sum of
+countries' populations, multiplied by the number of countries is
+used as the weight for each individual in that country.
+"""
+
+population_sizes = {'Cameroon':24348251,
+    'Cape+Verde':563198,
+    'Ghana':30832019,
+    'Guinea':12907395,
+    'Guinea-Bissau':1646077,
+    'Kenya':47564296,
+    'Sao+Tome+and+Principe':214610,
+    'Senegal':17223497,
+    'South+Africa':60604992,
+    'Uganda':42885900,
+    'Zimbabwe':15178979
+}
+
+country_data = pd.DataFrame(
+    {'country':population_sizes.keys(),
+    'population':population_sizes.values()}
+)
+
+# What proportion of the regional population does each country account for
+country_data['proportion'] = country_data.population/country_data.population.sum()
+# How much will each individual in the country count towards the sample size?
+country_data['individual_weight'] = country_data['proportion'] * len(country_data.country)
+# Add country data to Combined Allele Frequency data
+cafs = pd.merge(cafs, country_data, how="left", on='country')
+# Sample size is multiplied by this individual weight and doubled
+# this accounts for diploid samples from each individual
+cafs['weighted_sample_size'] = cafs.sample_size * 2 * cafs.individual_weight
+
+# Combine allele frequency data of all countries
+# Using the custom column 'weighted_sample_size'
+# The interpretation of the column used for `weights` is that n
+# samples were observed with allele x. If unspecified this defaults
+# to double the sample size (to accound for diploid samples from each
+# individual)
+winternational = scrapeAF.combineAF(cafs, datasetID='country', weights='weighted_sample_size')
+
+scrapeAF.plotAFprob(international, cafs, datasetID='country', ncol=4)
+
+hifreq = winternational[winternational.allele_freq > 0.01].allele
+# Must be a list
+hifreq = hifreq.tolist()
+# Plot only selected alleles
+scrapeAF.plotAFprob(
+    winternational,
+    cafs,
+    datasetID='country',
+    ncol=4,
+    xmax=cafs.allele_freq.max(),
+    alleles=hifreq)
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 324744a..2c1c053 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -395,7 +395,7 @@ def AFci(caf, credible_interval=0.95):
     ci = [betaCI(a, b, credible_interval) for a,b in ab]
     return ci
 
-def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, ci=0.95, alleles=[]):
+def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
     """Plot the (log) posterior density function of all frequencies
         for all alleles based on concentration for Dirichlet
         distribution. Options for adding empirical values
@@ -439,7 +439,7 @@ def allele_mask(alleles, concentration):
         df = df.sort_values('allele')
         assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
     mask = allele_mask(alleles, concentration)
-    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol)
+    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
     # Only indexes that pass the mask
     masked_indexes = [i for i,x in enumerate(mask) if x]
     for subploti,i in enumerate(masked_indexes):
@@ -453,6 +453,7 @@ def allele_mask(alleles, concentration):
                 warnings.simplefilter("ignore")
                 pdf = [bd.pdf(p) for p in pline]
         ax = axs[subplotselector]
+        ax.set_xlim(xmin,xmax)
         if not AFtab.empty:
             # Add the empirical allele frequency for each population
             for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
@@ -464,7 +465,7 @@ def allele_mask(alleles, concentration):
         ax.plot(pline, pdf)
         # Annotate with allele
         if not caf.empty:
-            ax.text(0.5, max(pdf)/2, f"{caf.allele.iloc[i]}")
+            ax.text((xmax-xmin)/2, max(pdf)/2, f"{caf.allele.iloc[i]}")
         # Annotate with concentration
         # ax.text(0.5, max(pdf)/3, f"Concentration {round(concentration.iloc[i])}")
         if not caf.empty:

From ca73713432635848436e93bd98b23d4343cac514 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 10 Oct 2022 17:00:42 +0100
Subject: [PATCH 038/192] Confidence intervals are misleadingly tight

---
 code/demos/visualise_high_k_dirichlet.py | 22 ++++++++++++++++++++++
 1 file changed, 22 insertions(+)

diff --git a/code/demos/visualise_high_k_dirichlet.py b/code/demos/visualise_high_k_dirichlet.py
index 52e4b56..f898e11 100644
--- a/code/demos/visualise_high_k_dirichlet.py
+++ b/code/demos/visualise_high_k_dirichlet.py
@@ -73,3 +73,25 @@
 scrapeAF.plotAFprob(caf, AFtab)
 # View subset of alleles
 scrapeAF.plotAFprob(caf, AFtab, alleles=["DQB1*03:01","DQB1*05:01","DQB1*05:02"])
+
+# CI may be misleading
+
+# Use cafs from multi_country.py
+x = cafs[cafs.allele == 'A*23:01']
+
+clist = 1 + x.allele_freq * x.sample_size
+long_c = []
+for c in clist:
+    long_c.append(c)
+    long_c.append(0)
+scrapeAF.plotAFprob(concentration=pd.Series(long_c), ncol=2)
+
+pline = np.linspace(0,1,500)
+fig, ax = plt.subplots()
+for a,b in zip(x.c, x.sample_size):
+    bd = beta(a,b)
+    pdf = [bd.pdf(p) for p in pline]
+    ax.plot(pline, pdf)
+    ax.set_xlim(0,0.4)
+plt.show()
+plt.subplots()
\ No newline at end of file

From 708f706cb118b366339a0f27f6d57e0ed2882832 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 12 Oct 2022 17:23:54 +0100
Subject: [PATCH 039/192] Writing demos

concentration for plotAFpdf is now a list.
select HLA panel demon.
calculate population coverage in single pop demo
Demo on priors.
---
 code/demos/select_hla_panel.py           | 213 +++++++++++++++++++++++
 code/demos/single_country.py             |  18 ++
 code/demos/visualise_high_k_dirichlet.py |   1 +
 code/demos/working_with_priors.py        |  91 ++++++++++
 code/scrapeAF.py                         |   5 +-
 5 files changed, 326 insertions(+), 2 deletions(-)
 create mode 100644 code/demos/select_hla_panel.py
 create mode 100644 code/demos/working_with_priors.py

diff --git a/code/demos/select_hla_panel.py b/code/demos/select_hla_panel.py
new file mode 100644
index 0000000..fa5b6f0
--- /dev/null
+++ b/code/demos/select_hla_panel.py
@@ -0,0 +1,213 @@
+"""
+Some countries are not well covered by the IEDB reference set.
+We can select a panel of alleles to better represent these
+populations, being sure to select a range of supertypes.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+iedb_ref = ['B*35:01', 'A*30:01', 'A*02:03', 'B*15:01', 'B*57:01', 'A*68:02', 'A*23:01', 'B*53:01', 'A*03:01', 'B*40:01', 'B*44:02', 'B*51:01', 'A*33:01', 'A*01:01', 'A*68:01', 'A*24:02', 'B*07:02', 'B*08:01', 'A*02:06', 'A*26:01', 'A*11:01', 'A*30:02', 'A*31:01', 'B*58:01', 'B*44:03', 'A*32:01', 'A*02:01']
+
+regions = pd.read_csv("data/example/countries.csv")
+countries = regions.Country.tolist()
+
+# Which supertypes are represented
+super1 = pd.read_csv("data/HLA1supertypes_Sidney2008.csv")
+super1.allele = super1.allele.apply(lambda x: x[:4]+':'+x[4:])
+
+##################
+# Download A and B data for all countries to identify 
+# Countries poorly covered by the IEDB reference set
+# for locus in ['A', 'B']:
+#     # for country in ['Indonesia', 'Philippines']:
+#     for country in countries:
+#         print(country)
+#         try:
+#             base_url = scrapeAF.makeURL(country, standard='s', locus=locus)
+#             aftab = scrapeAF.getAFdata(base_url)
+#             aftab.to_csv(f"data/example/population_coverage/{country}_{locus}_raw.csv", index=False)
+#         except:
+#             pass
+
+# Calculate total population coverage of IEDB reference
+# set (locus A and B) for each country
+
+iedb_cov = []
+iedb_country = []
+
+for country in countries:
+    try:
+        afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
+        afa = scrapeAF.only_complete(afa)
+        afa = scrapeAF.decrease_resolution(afa, 2)
+        cafa = scrapeAF.combineAF(afa)
+        maska = cafa.allele.isin(iedb_ref)
+        p = cafa[maska].allele_freq.sum()
+
+        afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
+        afb = scrapeAF.only_complete(afb)
+        afb = scrapeAF.decrease_resolution(afb, 2)
+        cafb = scrapeAF.combineAF(afb)
+        maskb = cafb.allele.isin(iedb_ref)
+        m = cafb[maskb].allele_freq.sum()
+        # Population proportion with no IEDB ref alleles
+        # at HLA A or HLA B
+        coverage = 1 - ((1-p)**2 * (1-m)**2)
+        iedb_cov.append(coverage)
+        iedb_country.append(country)
+    except:
+        pass
+
+df = pd.DataFrame({'country':iedb_country, 'coverage':iedb_cov})
+df = df.sort_values('coverage')
+df = pd.merge(df, regions, how="left", left_on="country", right_on="Country")
+
+plt.barh(df.country, df.coverage, color="black")
+plt.barh()
+for region in df.largeRegion.unique():
+    mask = df.largeRegion == region
+    plt.barh(df[mask].country, df[mask].coverage, label=region)
+plt.axvline(0.95, linestyle="--", c="black")
+plt.legend()
+plt.show()
+
+#############
+country = "Indonesia"
+# country="Philippines"
+afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
+afa = scrapeAF.only_complete(afa)
+afa = scrapeAF.decrease_resolution(afa, 2)
+cafa = scrapeAF.combineAF(afa)
+maska = cafa.allele.isin(iedb_ref)
+p = cafa[maska].allele_freq.sum()
+
+afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
+afb = scrapeAF.only_complete(afb)
+afb = scrapeAF.decrease_resolution(afb, 2)
+cafb = scrapeAF.combineAF(afb)
+maskb = cafb.allele.isin(iedb_ref)
+m = cafb[maskb].allele_freq.sum()
+# Population proportion with no IEDB ref alleles
+# at HLA A or HLA B
+coverage = 1 - ((1-p)**2 * (1-m)**2)
+
+cafa = cafa.sort_values("allele_freq", ascending=False, ignore_index=True)
+cafb = cafb.sort_values("allele_freq", ascending=False, ignore_index=True)
+# Add HLA1 supertypes
+cafa = pd.merge(cafa, super1, how="left", on="allele")
+cafb = pd.merge(cafb, super1, how="left", on="allele")
+
+fig, ax = plt.subplots(1,2, gridspec_kw={'width_ratios': [1,2]})
+ax[0].plot(cafa.allele,
+    cafa.allele_freq.cumsum().apply(scrapeAF.population_coverage),
+    c="black",
+    zorder=0)
+for supertype in cafa.supertype.unique():
+    mask = cafa.supertype == supertype
+    ax[0].scatter(
+        cafa[mask].allele,
+        cafa.allele_freq.cumsum().apply(scrapeAF.population_coverage)[mask],
+        label=supertype,
+        zorder=10)
+ax[0].set_title("HLA A")
+ax[0].set_ylabel("Cumulative population coverage")
+ax[0].grid(True)
+ax[0].legend()
+ax[0].tick_params(labelrotation=90)
+
+ax[1].plot(cafb.allele,
+    cafb.allele_freq.cumsum().apply(scrapeAF.population_coverage),
+    c="black",
+    zorder=0)
+for supertype in cafb.supertype.unique():
+    mask = cafb.supertype == supertype
+    ax[1].scatter(
+        cafb[mask].allele,
+        cafb.allele_freq.cumsum().apply(scrapeAF.population_coverage)[mask],
+        label=supertype,
+        zorder=10)
+ax[1].set_title("HLA B")
+ax[1].grid(True)
+ax[1].legend()
+ax[1].tick_params(labelrotation=90)
+
+plt.tight_layout()
+plt.show()
+
+#########################
+#                       #
+#   Design a new panel  #
+#                       #
+#########################
+
+def multilocus_homozygous_coverage(AFs):
+    coverage = np.prod([p**2 for p in AFs])
+    return coverage
+
+def remainingAF(x, cumAF, is_locus):
+    return [1-c-x*modifier for c,modifier in zip(cumAF, is_locus)]
+    
+
+def population_uncoverage(row, covered_dict):
+    loci = np.array(list(covered_dict.keys()))
+    is_locus = loci == row.loci
+    remains = remainingAF(row.allele_freq, covered_dict.values(), is_locus)
+    uncovered = multilocus_homozygous_coverage(remains)
+    return uncovered
+
+def sum_panel_AF(panel, locus):
+    return sum([x.allele_freq for x in panel if x.loci == locus])
+
+all_loci = pd.concat([cafa, cafb], ignore_index=True)
+
+covered_dict = {
+    'A':0,
+    'B':0
+}
+panel = []
+mask = [True] *  all_loci.shape[0]
+
+for n in range(4):
+    # Select allele
+    i = all_loci[mask].apply(population_uncoverage, axis=1, args=[covered_dict]).idxmin()
+    # Add selected allele to panel
+    panel.append(all_loci.loc[i])
+    # Update mask to omited selected loci from choice
+    mask = ~all_loci.allele.isin([x.allele for x in panel])
+    # Update coverd_dict
+    covered_dict = {key: sum_panel_AF(panel, key) for key, value in covered_dict.items()}
+
+
+panel = pd.concat(panel, axis=1, ignore_index=True).T
+panel
+
+# To my surprise it generally favours adding more alleles to which
+# ever locus already has the highest cumulative frequency
+
+def f(p,m):
+    return (1-p)**2*(1-m)**2
+    # return (1-p)*(1-m)
+
+# def f(q,n):
+    # return (q**2) * (n**2)
+    # return q*n
+
+x = np.linspace(1, 0, 21)
+y = np.linspace(1, 0, 21)
+z = np.array([f(j,i) for j in y for i in x])
+X, Y = np.meshgrid(x, y)
+Z = z.reshape(21, 21)
+
+from matplotlib import cm
+# Plot the surface.
+fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
+surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
+                       linewidth=0, antialiased=False)
+plt.show()
+
+plt.plot(f(0.2, x))
+plt.plot(f(0.8, x))
+plt.show()
\ No newline at end of file
diff --git a/code/demos/single_country.py b/code/demos/single_country.py
index e1f0f0c..4fe9b2c 100644
--- a/code/demos/single_country.py
+++ b/code/demos/single_country.py
@@ -96,7 +96,25 @@
 caf[['cl','cu']] = scrapeAF.AFci(caf)
 
 caf.plot.barh('allele', 'allele_freq')
+plt.tight_layout()
 plt.show()
 
 scrapeAF.plotAFprob(caf, afloc)
 scrapeAF.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])
+
+#############################
+#                           #
+#    Population coverage    #
+#                           #
+#############################
+
+# Sort by allele frequency
+caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
+
+plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(scrapeAF.population_coverage))
+plt.plot(caf.allele_freq.cumsum().apply(scrapeAF.population_coverage), label="Cumulative coverage")
+plt.grid(True)
+plt.xticks(rotation=90)
+plt.legend()
+plt.tight_layout()
+plt.show()
diff --git a/code/demos/visualise_high_k_dirichlet.py b/code/demos/visualise_high_k_dirichlet.py
index f898e11..5678ff9 100644
--- a/code/demos/visualise_high_k_dirichlet.py
+++ b/code/demos/visualise_high_k_dirichlet.py
@@ -55,6 +55,7 @@
     ax.plot_surface(k1, k2, pdf, cmap=cm.plasma,
         linewidth=0, antialiased=False)
     ax.set_title('PDF')
+    plt.show()
 else:
     print( "Surface plot only works with k==3")
 
diff --git a/code/demos/working_with_priors.py b/code/demos/working_with_priors.py
new file mode 100644
index 0000000..4b63561
--- /dev/null
+++ b/code/demos/working_with_priors.py
@@ -0,0 +1,91 @@
+"""
+Working with priors to improve estimates of undersampled populations.
+Priors can be based on other related, populations, or specified by
+hand.
+"""
+
+import code.scrapeAF as scrapeAF
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+"""
+Venezuela is one of the least sampled countries on allelefrequency.net
+We found only 55 gold standard samples for HLA A.
+"""
+
+venezuelaAF = pd.read_csv("data/example/globalPCA/Venezuela_raw.csv")
+venezuelaAF = scrapeAF.only_complete(venezuelaAF)
+venezuelaAF = scrapeAF.decrease_resolution(venezuelaAF, 2)
+cafV = scrapeAF.combineAF(venezuelaAF)
+cafV['study'] =  'Venezuela'
+
+scrapeAF.plotAFprob(cafV, venezuelaAF)
+
+"""
+We can specify priors manually. For simplicity we use
+a prior of 1 for each observed allele but this could be any
+n length list of positive real numbers.
+
+The interpretation of the prior is that n copies were found for each
+allele. Note that `combineAF()` uses the first value in the prior for
+the first allele alphabetically and so on.
+
+By viewing the posterior we can see that the prior has moved the
+estimate away from the observed study.
+"""
+manual_prior = [10, 1, 1, 1, 1]
+
+# View prior distribution
+scrapeAF.plotAFprob(concentration=manual_prior)
+
+# Combine Allele Freq of study with Manual Prior
+cafMP = scrapeAF.combineAF(venezuelaAF, alpha=manual_prior)
+
+# View posterior distribution
+scrapeAF.plotAFprob(cafMP, AFtab=venezuelaAF)
+
+"""
+Alternatively we can use another population as our prior.
+For example we will use data for Colombia, a neighbouring country
+with many more samples for HLA A.
+
+When using other studies as a prior we can downweight their samples
+so they count less than the samples in our actual population.
+The amount of downweighting depends on how relevent you believe the
+other study is. Here we use downweight by a factor 0.01 so that the
+Venezuela data is not drowned out by the Colombia data.
+
+When recalculating the prior to plot, sample size is doubled
+as each person in the study is diploid and so provides two alleles.
+"""
+
+colombiaAF = pd.read_csv("data/example/globalPCA/Colombia_raw.csv")
+colombiaAF = scrapeAF.only_complete(colombiaAF)
+colombiaAF = scrapeAF.decrease_resolution(colombiaAF, 2)
+cafC = scrapeAF.combineAF(colombiaAF)
+cafC['population'] =  'Colombia'
+
+study_prior = cafC.copy()
+study_prior.sample_size = study_prior.sample_size * 0.01
+
+# View prior
+scrapeAF.plotAFprob(
+    concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()
+)
+
+# (2 * study_prior.sample_size * study_prior.allele_freq)-(study_prior.c * 0.01)
+# plt.scatter(
+# (2 * study_prior.sample_size * study_prior.allele_freq).tolist(),
+# (study_prior.c * 0.01).tolist()
+# )
+# plt.show()
+
+# Combine Allele Frequency with Study Prior
+cafSP = scrapeAF.combineAF(
+    pd.concat([venezuelaAF, study_prior], join="inner")
+    )
+
+# View posterior
+scrapeAF.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"))
+scrapeAF.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"), alleles=venezuelaAF.allele.tolist())
diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 2c1c053..49ce389 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -395,7 +395,7 @@ def AFci(caf, credible_interval=0.95):
     ci = [betaCI(a, b, credible_interval) for a,b in ab]
     return ci
 
-def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=pd.Series(), log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
+def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
     """Plot the (log) posterior density function of all frequencies
         for all alleles based on concentration for Dirichlet
         distribution. Options for adding empirical values
@@ -421,13 +421,14 @@ def allele_mask(alleles, concentration):
         Returns:
             list: List of booleans to use as mask
         """
+        assert isinstance(alleles, list), f"alleles must be a list, not {type(alleles)}"
         if not alleles:
             mask = [True] * len(concentration)
         else:
             mask = caf.allele.isin(alleles)
         return mask
 
-    if concentration.empty:
+    if not concentration:
         concentration = caf.alpha + caf.c
     # Get beta parameters for each k in Dirichlet
     ab = betaAB(concentration)

From 26fe1460f7ca5291f7fe089bd7b09ea50bc78984 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 12 Oct 2022 17:24:02 +0100
Subject: [PATCH 040/192] scrapeAF env

---
 envs/scrapeAF.yml | 102 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 102 insertions(+)
 create mode 100644 envs/scrapeAF.yml

diff --git a/envs/scrapeAF.yml b/envs/scrapeAF.yml
new file mode 100644
index 0000000..0df8543
--- /dev/null
+++ b/envs/scrapeAF.yml
@@ -0,0 +1,102 @@
+name: scrapeAF
+channels:
+  - conda-forge
+  - anaconda
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=main
+  - _openmp_mutex=5.1=1_gnu
+  - beautifulsoup4=4.11.1=py310h06a4308_0
+  - blas=1.0=mkl
+  - bottleneck=1.3.4=py310h9102076_0
+  - brotli=1.0.9=h166bdaf_7
+  - brotli-bin=1.0.9=h166bdaf_7
+  - brotlipy=0.7.0=py310h7f8727e_1002
+  - bzip2=1.0.8=h7b6447c_0
+  - ca-certificates=2022.4.26=h06a4308_0
+  - certifi=2022.6.15=py310h06a4308_0
+  - cffi=1.15.0=py310hd667e15_1
+  - charset-normalizer=2.0.4=pyhd3eb1b0_0
+  - cryptography=37.0.1=py310h9ce1e76_0
+  - cycler=0.11.0=pyhd8ed1ab_0
+  - dbus=1.13.6=he372182_0
+  - expat=2.4.8=h27087fc_0
+  - fontconfig=2.13.1=h6c09931_0
+  - fonttools=4.25.0=pyhd3eb1b0_0
+  - freetype=2.10.4=h0708190_1
+  - giflib=5.2.1=h36c2ea0_2
+  - glib=2.69.1=h4ff587b_1
+  - gst-plugins-base=1.14.0=hbbd80ab_1
+  - gstreamer=1.14.0=h28cd5cc_2
+  - icu=58.2=hf484d3e_1000
+  - idna=3.3=pyhd3eb1b0_0
+  - intel-openmp=2021.4.0=h06a4308_3561
+  - jpeg=9e=h166bdaf_1
+  - kiwisolver=1.4.2=py310h295c915_0
+  - lcms2=2.12=hddcbb42_0
+  - ld_impl_linux-64=2.38=h1181459_1
+  - libbrotlicommon=1.0.9=h166bdaf_7
+  - libbrotlidec=1.0.9=h166bdaf_7
+  - libbrotlienc=1.0.9=h166bdaf_7
+  - libffi=3.3=he6710b0_2
+  - libgcc-ng=11.2.0=h1234567_1
+  - libgfortran-ng=7.5.0=ha8ba4b0_17
+  - libgfortran4=7.5.0=ha8ba4b0_17
+  - libgomp=11.2.0=h1234567_1
+  - libpng=1.6.37=h21135ba_2
+  - libstdcxx-ng=11.2.0=h1234567_1
+  - libtiff=4.2.0=h85742a9_0
+  - libuuid=1.0.3=h7f8727e_2
+  - libwebp=1.2.2=h55f646e_0
+  - libwebp-base=1.2.2=h7f98852_1
+  - libxcb=1.13=h7f98852_1004
+  - libxml2=2.9.14=h74e7548_0
+  - lz4-c=1.9.3=h9c3ff4c_1
+  - matplotlib=3.5.2=py310hff52083_0
+  - matplotlib-base=3.5.2=py310h5701ce4_0
+  - mkl=2021.4.0=h06a4308_640
+  - mkl-service=2.4.0=py310h7f8727e_0
+  - mkl_fft=1.3.1=py310hd6ae3a3_0
+  - mkl_random=1.2.2=py310h00e6091_0
+  - munkres=1.1.4=pyh9f0ad1d_0
+  - ncurses=6.3=h7f8727e_2
+  - numexpr=2.8.1=py310hcea2de6_2
+  - numpy=1.22.3=py310hfa59a62_0
+  - numpy-base=1.22.3=py310h9585f30_0
+  - openssl=1.1.1o=h7f8727e_0
+  - packaging=21.3=pyhd3eb1b0_0
+  - pandas=1.4.2=py310h295c915_0
+  - pcre=8.45=h9c3ff4c_0
+  - pillow=9.2.0=py310hace64e9_1
+  - pip=21.2.4=py310h06a4308_0
+  - pthread-stubs=0.4=h36c2ea0_1001
+  - pycparser=2.21=pyhd3eb1b0_0
+  - pyopenssl=22.0.0=pyhd3eb1b0_0
+  - pyparsing=3.0.4=pyhd3eb1b0_0
+  - pyqt=5.9.2=py310h295c915_6
+  - pysocks=1.7.1=py310h06a4308_0
+  - python=3.10.4=h12debd9_0
+  - python-dateutil=2.8.2=pyhd3eb1b0_0
+  - python_abi=3.10=2_cp310
+  - pytz=2022.1=py310h06a4308_0
+  - qt=5.9.7=h5867ecd_1
+  - readline=8.1.2=h7f8727e_1
+  - requests=2.27.1=pyhd3eb1b0_0
+  - scipy=1.7.3=py310hfa59a62_0
+  - seaborn=0.11.2=pyhd3eb1b0_0
+  - setuptools=61.2.0=py310h06a4308_0
+  - sip=4.19.13=py310h295c915_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - soupsieve=2.3.1=pyhd3eb1b0_0
+  - sqlite=3.38.5=hc218d9a_0
+  - tk=8.6.12=h1ccaba5_0
+  - tornado=6.1=py310h7f8727e_0
+  - tzdata=2022a=hda174b7_0
+  - urllib3=1.26.9=py310h06a4308_0
+  - wheel=0.37.1=pyhd3eb1b0_0
+  - xorg-libxau=1.0.9=h7f98852_0
+  - xorg-libxdmcp=1.1.3=h7f98852_0
+  - xz=5.2.5=h7f8727e_1
+  - zlib=1.2.12=h7f8727e_2
+  - zstd=1.4.9=ha95c52a_0
+prefix: /home/dwells/miniconda3/envs/scrapeAF

From b189886d0946471c4196ed2615a1bd7a97a08f5f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 11:32:22 +0100
Subject: [PATCH 041/192] Correct country name matches and use only complete
 studies

---
 code/demos/entropy_map.py | 21 ++++++++++++++++++---
 1 file changed, 18 insertions(+), 3 deletions(-)

diff --git a/code/demos/entropy_map.py b/code/demos/entropy_map.py
index 6339fa2..a509f68 100644
--- a/code/demos/entropy_map.py
+++ b/code/demos/entropy_map.py
@@ -26,6 +26,7 @@
     print(country)
     try:
         df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+        df = scrapeAF.only_complete(df)
         df = scrapeAF.decrease_resolution(df, 2)
         caf = scrapeAF.combineAF(df)
         # Recreate the Dirichlet distribution
@@ -40,6 +41,9 @@
     except:
         pass
 
+# Drop regions without data
+regions = regions.dropna(subset=['entropy'])
+
 ######## World plot
 world = gpd.read_file(
     gpd.datasets.get_path('naturalearth_lowres')
@@ -48,9 +52,23 @@
 # Not all countries are in both datasets,
 # Some of this is due to alternative naming
 # Will require manual editting.
+
+#regions not in world
 regions[~regions.country.isin(world.name)].country
+# world not in regions
 world.name[~world.name.isin(regions.country)]
 
+# Change world names to match region country
+# key becomes value
+renames={
+"United States of America":"United States",
+'Bosnia and Herz.': "Bosnia and Herzegovina",
+"Czechia": "Czech Republic",
+}
+
+for key,value in renames.items():
+    world.loc[world.name == key, 'name'] = value
+
 world_regions = pd.merge(world, regions, how="left", left_on="name", right_on="country")
 
 fig, ax = plt.subplots(2,2)
@@ -61,6 +79,3 @@
 gplt.choropleth(world_regions, hue="total_sample_size", legend=True, ax=ax[1,0])
 ax[1,0].set_title('Total sample size')
 plt.show()
-
-world_regions[world_regions.name.str.contains('ahara')]
-world_regions.sort_values('entropy')
\ No newline at end of file

From 875a865e39aba496156382c00febc30cc4559107 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 11:32:50 +0100
Subject: [PATCH 042/192] Handle G group when formatting alleles

---
 code/scrapeAF.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index 49ce389..a232966 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -83,20 +83,23 @@ def Npages(bs):
     N = int(N)
     return N
 
-def formatAF(AFtab):
+def formatAF(AFtab, ignoreG=True):
     df = AFtab.copy()
     if df.sample_size.dtype == "O":
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
     if df.allele_freq.dtype == "O":
+        if ignoreG:
+            df.allele_freq = df.allele_freq.str.replace("(*)", "", regex=False)
         df.allele_freq = pd.to_numeric(df.allele_freq)
     return df
 
-def getAFdata(base_url, format=True):
+def getAFdata(base_url, format=True, ignoreG=True):
     """Get all allele frequency data from a search base url. Iterates over all
         pages regardless of which page is based.
 
     Args:
         base_url (str): URL for base search
+        ignoreG (boolean): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
 
     Returns:
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
@@ -119,7 +122,7 @@ def getAFdata(base_url, format=True):
     tabs = pd.concat(tabs)
     if format:
         try:
-            tabs = formatAF(tabs)
+            tabs = formatAF(tabs, ignoreG)
         except:
             print("Formatting failed, non-numeric datatypes may remain.")
     return tabs
@@ -246,13 +249,14 @@ def unmeasured_alleles(AFtab, datasetID='population'):
             df = pd.concat([df, missing_rows], ignore_index=True)
     return df
 
-def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
     """Combine allele frequencies at multiple levels
 
     Args:
         df (pd.DataFrame): Table of Allele frequency data
         weights (str): Column to weight averages by. Default 'sample_size'
         format (boolean): run formatAF(), Default = True
+        ignoreG (boolean): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
         add_unmeasured (boolean): run unmeasured_alleles(), Default = True
         datasetID (str): Unique identifier column for study used by unmeasured_alleles()
 
@@ -269,7 +273,7 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
     if resolution:
         assert check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
-        df = formatAF(df)
+        df = formatAF(df, ignoreG)
     if add_unmeasured:
         df = unmeasured_alleles(df, datasetID)
     try:

From c587822e8cd51a245fe7359f7f506cadb0af644c Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 11:33:40 +0100
Subject: [PATCH 043/192] Only complete in global PCA, rename wav to caf
 Replace + in annotations

---
 code/demos/globalPCA.py  | 27 +++++++++++++--------------
 code/demos/globalPCA2.py |  4 ++--
 2 files changed, 15 insertions(+), 16 deletions(-)

diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index 590d78e..175738f 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -13,8 +13,6 @@
 import code.scrapeAF as scrapeAF
 import pandas as pd
 import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
 
 # Countries in regions as defined on 
 # http://www.allelefrequencies.net/datasets.asp#tag_4
@@ -36,40 +34,41 @@
         except:
             print(f"Failed to get data for {country}: {base_url}")
 
-wavs = []
+cafs = []
 for country in countries:
     try:
         df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+        df = scrapeAF.only_complete(df)
         df = scrapeAF.decrease_resolution(df, 2)
-        wav = scrapeAF.combineAF(df)
-        wav['country'] = country
-        wavs.append(wav)
+        caf = scrapeAF.combineAF(df)
+        caf['country'] = country
+        cafs.append(caf)
     except:
         pass
 
-wavs = pd.concat(wavs, axis=0).reset_index(drop=True)
+cafs = pd.concat(cafs, axis=0).reset_index(drop=True)
 
 # Give record for all alleles to all countries
-wavs = scrapeAF.unmeasured_alleles(wavs, 'country')
+cafs = scrapeAF.unmeasured_alleles(cafs, 'country')
 
 # Check all countries have the same number of alleles
-wavs.groupby('country').allele.unique().apply(len).unique()
+cafs.groupby('country').allele.unique().apply(len).unique()
 
 # Sort by allele then select a single country,
 # check that its alleles match a specified list
 # then use the frequencies as features
-wavs = wavs.sort_values('allele')
+cafs = cafs.sort_values('allele')
 
-sorted_alleles = sorted(list(wavs.allele.unique()))
+sorted_alleles = sorted(list(cafs.allele.unique()))
 
 AFeatures = []
 for country in countries:
-    mask = wavs['country'] == country
+    mask = cafs['country'] == country
     # Only generate features for countries with records
     # e.g. Thailand has no loci A records
     if any(mask):
-        assert all(wavs[mask].allele.unique() == sorted_alleles)
-        features = [country] + wavs[mask].allele_freq.tolist()
+        assert all(cafs[mask].allele.unique() == sorted_alleles)
+        features = [country] + cafs[mask].allele_freq.tolist()
         AFeatures.append(features)
 
 # Dataframe of allele frequencies read for dimension reduction
diff --git a/code/demos/globalPCA2.py b/code/demos/globalPCA2.py
index db235b8..9e86bd3 100644
--- a/code/demos/globalPCA2.py
+++ b/code/demos/globalPCA2.py
@@ -38,7 +38,7 @@
     mask = AFeatures.largeRegion == region
     plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
     for i in AFeatures[mask].index:
-        plt.annotate(AFeatures.loc[i].country, AFeatures.loc[i][['pca0','pca1']])
+        plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['pca0','pca1']])
 plt.legend()
 plt.show()
 
@@ -46,6 +46,6 @@
     mask = AFeatures.largeRegion == region
     plt.scatter(AFeatures.umap0[mask], AFeatures.umap1[mask], label=region)
     for i in AFeatures[mask].index:
-        plt.annotate(AFeatures.loc[i].country, AFeatures.loc[i][['umap0','umap1']])
+        plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['umap0','umap1']])
 plt.legend()
 plt.show()

From 5d857f510ed135f1742f7cf7ddf57f2f9ee7b5c3 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 11:34:06 +0100
Subject: [PATCH 044/192] Calculating study prior is correct

---
 code/demos/working_with_priors.py | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/code/demos/working_with_priors.py b/code/demos/working_with_priors.py
index 4b63561..2a81b4a 100644
--- a/code/demos/working_with_priors.py
+++ b/code/demos/working_with_priors.py
@@ -74,13 +74,6 @@
     concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()
 )
 
-# (2 * study_prior.sample_size * study_prior.allele_freq)-(study_prior.c * 0.01)
-# plt.scatter(
-# (2 * study_prior.sample_size * study_prior.allele_freq).tolist(),
-# (study_prior.c * 0.01).tolist()
-# )
-# plt.show()
-
 # Combine Allele Frequency with Study Prior
 cafSP = scrapeAF.combineAF(
     pd.concat([venezuelaAF, study_prior], join="inner")

From 9c5857fa1d02a956b08b3a63a76ca0a7b0116b09 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 13:53:26 +0100
Subject: [PATCH 045/192] Add more options to makeURL

---
 code/scrapeAF.py | 45 ++++++++++++++++++++++++++++++++++++++-------
 1 file changed, 38 insertions(+), 7 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index a232966..a6a4e97 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -1,10 +1,11 @@
 """
-Scrape Allele [allelefrequencies.net](www.allelefrequencies.net)
-for HLA frequencies by population or larger region to calculate
-the regional HLA frequencies e.g. global.
+HLAfreq
 
-The database can be searched based on url as described in
-[automated access](http://www.allelefrequencies.net/extaccess.asp).
+Download allele frequency data from
+[allelefrequencies.net](www.allelefrequencies.net). Allele
+frequencies from different populations can be combined to
+estimate HLA frequencies countries or other regions such as
+global HLA frequencies.
 """
 
 from bs4 import BeautifulSoup
@@ -17,15 +18,45 @@
 import logging
 import warnings
 
-def makeURL(country, standard='s', locus="", resolution_pattern="bigger_equal_than", resolution=2):
+def makeURL(
+        country="",
+        standard='s',
+        locus="",
+        resolution_pattern="bigger_equal_than",
+        resolution=2,
+        region="",
+        ethnic="",
+        study_type="",
+        dataset_source=""
+    ):
+    """Create URL for search of allele frequency net database. All arguments are documented [here](www.allelefrequencies.net/extaccess.asp)
+
+    Args:
+        country (str, optional): Country name to retrieve records from. Defaults to "".
+        standard (str, optional): Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
+        locus (str, optional): The locus to return allele data for. Defaults to "".
+        resolution_pattern (str, optional): Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using `resolution` and `resolution_pattern`. Defaults to "bigger_equal_than".
+        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
+        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to "".
+        ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to "".
+        study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
+        dataset_source (str, optional): Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
+
+    Returns:
+        str: URL to search allelefrequencies.net
+    """
     base = "http://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
     hla_locus = "hla_locus=%s&" %(locus)
     country = "hla_country=%s&" %(country)
+    region = "hla_region=%s&" %(region)
+    ethnic = "hla_ethnic=%s&" %(ethnic)
+    study_type = "hla_study=%s&" %(study_type)
+    dataset_source = "hla_dataset_source=%s&" %(dataset_source)
     hla_level_pattern = "hla_level_pattern=%s&" %(resolution_pattern)
     hla_level = "hla_level=%s&" %(resolution)
     standard = "standard=%s&" %standard
-    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard
+    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source
     return url
 
 def parseAF(bs):

From f0280f220aba209122dcdb560b84ab77b5b6bf30 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 14:53:42 +0100
Subject: [PATCH 046/192] Update docstrings for all functions

---
 code/scrapeAF.py | 116 +++++++++++++++++++++++++++++++++++------------
 1 file changed, 86 insertions(+), 30 deletions(-)

diff --git a/code/scrapeAF.py b/code/scrapeAF.py
index a6a4e97..8224d5d 100644
--- a/code/scrapeAF.py
+++ b/code/scrapeAF.py
@@ -4,7 +4,7 @@
 Download allele frequency data from
 [allelefrequencies.net](www.allelefrequencies.net). Allele
 frequencies from different populations can be combined to
-estimate HLA frequencies countries or other regions such as
+estimate HLA frequencies of countries or other regions such as
 global HLA frequencies.
 """
 
@@ -92,7 +92,6 @@ def parseAF(bs):
     df = df[['allele', 'loci', 'population', 'allele_freq', 'carriers%', 'sample_size']]
     return df
    
-
 def Npages(bs):
     """How many pages of results are there?
 
@@ -115,6 +114,18 @@ def Npages(bs):
     return N
 
 def formatAF(AFtab, ignoreG=True):
+    """Format allele frequency table.
+    Convert sample_size and allele_freq to numeric data type.
+    Removes commas from sample size. Removes "(*)" from allele frequency if 
+    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
+        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+
+    Returns:
+        pd.DataFrame: The formatted allele frequency data.
+    """
     df = AFtab.copy()
     if df.sample_size.dtype == "O":
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
@@ -129,8 +140,9 @@ def getAFdata(base_url, format=True, ignoreG=True):
         pages regardless of which page is based.
 
     Args:
-        base_url (str): URL for base search
-        ignoreG (boolean): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+        base_url (str): URL for base search.
+        format (bool): Format the downloaded data using `formatAF()`.
+        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
 
     Returns:
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
@@ -202,6 +214,15 @@ def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
     return df
 
 def check_resolution(AFtab):
+    """Check if all alleles in AFtab have the same resolution.
+    Will print the number of records with each resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+
+    Returns:
+        bool: True only if all alleles have the same resolution, else False.
+    """
     resolution = 1 + AFtab.allele.str.count(":")
     resVC = resolution.value_counts()
     pass_check = len(resVC) == 1
@@ -211,6 +232,16 @@ def check_resolution(AFtab):
     return pass_check
 
 def decrease_resolution(AFtab, newres, datasetID='population'):
+    """Decrease allele resolution to a specified value so all alleles have the same resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data.
+        newres (int): The desired number of fields for resolution.
+        datasetID (str, optional): Column to use as stud identifier. Defaults to 'population'.
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all alleles of requested resolution.
+    """
     df = AFtab.copy()
     resolution = 1 + df.allele.str.count(":")
     assert all(resolution >= newres), f"Some alleles have resolution below {newres} fields"
@@ -221,7 +252,7 @@ def decrease_resolution(AFtab, newres, datasetID='population'):
 
 def collapse_reduced_alleles(AFtab, datasetID='population'):
     df = AFtab.copy()
-    # Group by alleles withing datasets
+    # Group by alleles within datasets
     grouped = df.groupby([datasetID,'allele'])
     # Sum allele freq but keep other columns
     collapsed = grouped.apply(
@@ -281,19 +312,31 @@ def unmeasured_alleles(AFtab, datasetID='population'):
     return df
 
 def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
-    """Combine allele frequencies at multiple levels
+    """Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
+    Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
+    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
+    If `alpha` is not set the prior defaults to 1 observation of each allele.
 
     Args:
-        df (pd.DataFrame): Table of Allele frequency data
-        weights (str): Column to weight averages by. Default 'sample_size'
-        format (boolean): run formatAF(), Default = True
-        ignoreG (boolean): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
-        add_unmeasured (boolean): run unmeasured_alleles(), Default = True
-        datasetID (str): Unique identifier column for study used by unmeasured_alleles()
+        AFtab (pd.DataFrame): Table of Allele frequency data
+        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
+        datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
+        format (bool, optional): Run `formatAF()`. Defaults to True.
+        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
+        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
+        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
+        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
+        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
 
     Returns:
-        pd.DataFrame: Table of allele frequency data with alleles
-        grouped to make a weighted average based on weights.
+        pd.DataFrame: Allele frequencies after combining estimates from all studies.
+        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
+        *alpha* is the prior used for the Dirichlet distribution.
+        *c* is the observations used for the Dirichlet distribution.
+        *sample_size* is the total sample size of all combined studies.
+        *wav* is the weighted average.
     """
     df = AFtab.copy()
     single_loci(df)
@@ -342,19 +385,41 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
     return combined
 
 def default_prior(k):
+    """Calculate a default prior, 1 observation of each class.
+
+    Args:
+        k (int): Number of classes in the Dirichlet distribution.
+
+    Returns:
+        list: List of k 1s to use as prior.
+    """
     alpha = [1] * k
     return alpha
 
 def single_loci(AFtab):
+    """Check that allele frequency data is only of one locus
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+    """
     assert len(AFtab.loci.unique()) == 1, f"'AFtab' must conatain only 1 loci"
 
 def alleles_unique_in_study(AFtab, datasetID='population'):
+    """Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+        datasetID (str, optional): Unique identifier column to define study. Defaults to 'population'.
+
+    Returns:
+        bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
+    """
     df = AFtab.copy()
     grouped = df.groupby([datasetID,'allele'])
     # Are allele alleles unique? i.e. do any occur multiple times in grouping?
     unique = grouped.size()[grouped.size()>1].empty
     if not unique:
-        print("Non unique alleles in population")
+        print(f"Non unique alleles in study, is datasetID correct? {datasetID}")
         print(grouped.size()[grouped.size()>1])
     return unique
 
@@ -368,7 +433,6 @@ def id_duplicated_allele(grouped):
     duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
     assert all(~duplicated_population), "duplicated population within allele %s" %duplicated_population[duplicated_population].index.tolist()
 
-
 def population_coverage(p):
     """Calculate the proportion of people with at least 1 copy of this allele
         assuming HWE.
@@ -405,7 +469,7 @@ def betaCI(a,b,credible_interval=0.95):
         credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
 
     Returns:
-        _type_: _description_
+        tuple: Lower and upper credible interval of beta distribution.
     """
     bd = beta(a,b)
     lower_quantile = (1-credible_interval)/2
@@ -431,10 +495,9 @@ def AFci(caf, credible_interval=0.95):
     return ci
 
 def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
-    """Plot the (log) posterior density function of all frequencies
+    """Plot the posterior density function of all frequencies
         for all alleles based on concentration for Dirichlet
-        distribution. Options for adding empirical values
-        and plotting the log pdf.
+        distribution. Supply AFtab to add empirical values to plot.
 
     Args:
         caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
@@ -444,7 +507,10 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
         psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
         ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
+        xmin (float, optional): Set x axis min. Defaults to -0.05.
+        xmax (float, optional): Set x axis max. Defaults to 1.05.
         ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
     """
     def allele_mask(alleles, concentration):
         """Create boolean mask either to keep only supplied `alleles`. If empty keep all.
@@ -514,13 +580,3 @@ def allele_mask(alleles, concentration):
         # fig.tight_layout()
     plt.show()
 
-# url = "http://www.allelefrequencies.net/hla6006a.asp?hla_selection=A*01%3A01&hla_region=South+Asia"
-# base_url = makeURL("Philippines")
-
-# aftab = getAFdata(base_url)
-# aftab
-
-# import numpy as np
-
-# aftab.groupby('allele').apply(lambda x: np.average(x.allele_freq, weights=x.sample_size))
-# aftab.groupby('allele').size()

From bce51e6c4ec7e390bbc2fe3dcda5fa0a4024804b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 16:03:27 +0100
Subject: [PATCH 047/192] Change scrapeAF to HLAfreq

---
 code/{scrapeAF.py => HLAfreq.py}         |  6 ++--
 code/demos/check_study_completeness.py   | 24 +++++++--------
 code/demos/compare_countries.py          | 10 +++----
 code/demos/entropy_map.py                | 10 +++----
 code/demos/globalPCA.py                  | 14 ++++-----
 code/demos/international_frequencies.py  |  6 ++--
 code/demos/multi_country.py              | 24 +++++++--------
 code/demos/population_coverage.py        |  8 ++---
 code/demos/select_hla_panel.py           | 38 ++++++++++++------------
 code/demos/single_country.py             | 26 ++++++++--------
 code/demos/visualise_high_k_dirichlet.py | 20 ++++++-------
 code/demos/working_with_priors.py        | 30 +++++++++----------
 code/dirichlet_test.py                   |  6 ++--
 readme.md                                | 18 ++++++-----
 14 files changed, 122 insertions(+), 118 deletions(-)
 rename code/{scrapeAF.py => HLAfreq.py} (98%)

diff --git a/code/scrapeAF.py b/code/HLAfreq.py
similarity index 98%
rename from code/scrapeAF.py
rename to code/HLAfreq.py
index 8224d5d..5b05f09 100644
--- a/code/scrapeAF.py
+++ b/code/HLAfreq.py
@@ -482,7 +482,7 @@ def AFci(caf, credible_interval=0.95):
     """Calculate credible interval for combined allele frequency table
 
     Args:
-        caf (pd.DataFrame): Table produced by scrapeAF.combineAF()
+        caf (pd.DataFrame): Table produced by combineAF()
         credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
 
     Returns:
@@ -500,8 +500,8 @@ def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population",
         distribution. Supply AFtab to add empirical values to plot.
 
     Args:
-        caf (pd.DataFrame, optional): Combined allele frequence data produced by scrapeAF.combineAF(). Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by scrapeAF.combinedAF(). You must use the same dataframe as this function doesn't have the error checking that scrapeAF.combineAF() has. Defaults to pd.DataFrame().
+        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().
         datasetID (str, optional): The column used to define datasets. Defaults to "population".
         concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
         log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
diff --git a/code/demos/check_study_completeness.py b/code/demos/check_study_completeness.py
index e456a2f..040ed8a 100644
--- a/code/demos/check_study_completeness.py
+++ b/code/demos/check_study_completeness.py
@@ -21,7 +21,7 @@
 increase it.
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -30,8 +30,8 @@
 country = 'Thailand'
 
 # Because resolution equals 2, an incomplete dataset is returned
-base_url = scrapeAF.makeURL(country, resolution_pattern="equal", resolution=2, standard="s")
-aftab = scrapeAF.getAFdata(base_url)
+base_url = HLAfreq.makeURL(country, resolution_pattern="equal", resolution=2, standard="s")
+aftab = HLAfreq.getAFdata(base_url)
 aftab.to_csv("data/example/incomplete_raw.csv", index=False)
 
 df = pd.read_csv("data/example/incomplete_raw.csv")
@@ -39,7 +39,7 @@
 # How to filter incomplete studies
 
 # Identify incomplete studies
-noncomplete = scrapeAF.incomplete_studies(df)
+noncomplete = HLAfreq.incomplete_studies(df)
 
 # Returns False if population AND loci are in the noncomplete.index
 # AS A PAIR
@@ -50,7 +50,7 @@
 df = df[complete_mask]
 
 # Check filtering success
-scrapeAF.incomplete_studies(df)
+HLAfreq.incomplete_studies(df)
 
 #################################
 #                               #
@@ -58,22 +58,22 @@
 #                               #
 #################################
 
-base_url = scrapeAF.makeURL(
+base_url = HLAfreq.makeURL(
     'Thailand', locus="A",
     resolution_pattern="bigger_equal_than", resolution=1
 )
-aftab = scrapeAF.getAFdata(base_url)
+aftab = HLAfreq.getAFdata(base_url)
 aftab.to_csv("data/example/multiresolution_raw.csv", index=False)
 
 df = pd.read_csv("data/example/multiresolution_raw.csv")
-scrapeAF.check_resolution(df)
+HLAfreq.check_resolution(df)
 
 # You cant increase resolution 
-scrapeAF.decrease_resolution(df, 2)
+HLAfreq.decrease_resolution(df, 2)
 
 # But you can decrease
-df = scrapeAF.decrease_resolution(df, 1)
-scrapeAF.check_resolution(df)
+df = HLAfreq.decrease_resolution(df, 1)
+HLAfreq.check_resolution(df)
 
 # Alleles that were distinct at a higher resolution but
 # are indistinguishable at this new lower resolution,
@@ -83,7 +83,7 @@
 # You can check that each allele is still unique but this is
 # done automatically when reducing resolution or combining
 # allele frequencies.
-scrapeAF.alleles_unique_in_study(df)
+HLAfreq.alleles_unique_in_study(df)
 
 # In principal you could use 2 digit resolution
 # to estimate 4 digit resolution. E.g if A*01 has
diff --git a/code/demos/compare_countries.py b/code/demos/compare_countries.py
index ee8b636..61b5d37 100644
--- a/code/demos/compare_countries.py
+++ b/code/demos/compare_countries.py
@@ -2,7 +2,7 @@
 Compare HLA frequencies of different countries.
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -16,17 +16,17 @@
 # Download HLA allele frequencies
 for country in countries:
     print(country)
-    base_url = scrapeAF.makeURL(country)
-    aftab = scrapeAF.getAFdata(base_url)
+    base_url = HLAfreq.makeURL(country)
+    aftab = HLAfreq.getAFdata(base_url)
     aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
 
 wavs = []
 for country in countries:
     df = pd.read_csv("data/example/%s_raw.csv" %country)
     df = df[df.loci=="A"]
-    wav = scrapeAF.combineAF(df)
+    wav = HLAfreq.combineAF(df)
     # Add credible intervals
-    wav[['cl','cu']] = scrapeAF.AFci(wav)
+    wav[['cl','cu']] = HLAfreq.AFci(wav)
     wav['country'] = country
     wavs.append(wav)
 
diff --git a/code/demos/entropy_map.py b/code/demos/entropy_map.py
index a509f68..d23ee0e 100644
--- a/code/demos/entropy_map.py
+++ b/code/demos/entropy_map.py
@@ -4,7 +4,7 @@
 
 # use maps conda env
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -26,11 +26,11 @@
     print(country)
     try:
         df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
-        df = scrapeAF.only_complete(df)
-        df = scrapeAF.decrease_resolution(df, 2)
-        caf = scrapeAF.combineAF(df)
+        df = HLAfreq.only_complete(df)
+        df = HLAfreq.decrease_resolution(df, 2)
+        caf = HLAfreq.combineAF(df)
         # Recreate the Dirichlet distribution
-        alpha = scrapeAF.default_prior(len(caf.allele))
+        alpha = HLAfreq.default_prior(len(caf.allele))
         dd = dirichlet(alpha + caf.c)
         # Calculate entropy
         regions.loc[country, 'entropy'] = dd.entropy()
diff --git a/code/demos/globalPCA.py b/code/demos/globalPCA.py
index 175738f..b5c0fcf 100644
--- a/code/demos/globalPCA.py
+++ b/code/demos/globalPCA.py
@@ -10,7 +10,7 @@
 """
 
 import os
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 
@@ -27,9 +27,9 @@
     print()
     print(country)
     if not os.path.exists("data/example/globalPCA/%s_raw.csv" %country):
-        base_url = scrapeAF.makeURL(country, standard="g", locus="A")
+        base_url = HLAfreq.makeURL(country, standard="g", locus="A")
         try:
-            aftab = scrapeAF.getAFdata(base_url)
+            aftab = HLAfreq.getAFdata(base_url)
             aftab.to_csv("data/example/globalPCA/%s_raw.csv" %country, index=False)
         except:
             print(f"Failed to get data for {country}: {base_url}")
@@ -38,9 +38,9 @@
 for country in countries:
     try:
         df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
-        df = scrapeAF.only_complete(df)
-        df = scrapeAF.decrease_resolution(df, 2)
-        caf = scrapeAF.combineAF(df)
+        df = HLAfreq.only_complete(df)
+        df = HLAfreq.decrease_resolution(df, 2)
+        caf = HLAfreq.combineAF(df)
         caf['country'] = country
         cafs.append(caf)
     except:
@@ -49,7 +49,7 @@
 cafs = pd.concat(cafs, axis=0).reset_index(drop=True)
 
 # Give record for all alleles to all countries
-cafs = scrapeAF.unmeasured_alleles(cafs, 'country')
+cafs = HLAfreq.unmeasured_alleles(cafs, 'country')
 
 # Check all countries have the same number of alleles
 cafs.groupby('country').allele.unique().apply(len).unique()
diff --git a/code/demos/international_frequencies.py b/code/demos/international_frequencies.py
index a4ac244..8597dad 100644
--- a/code/demos/international_frequencies.py
+++ b/code/demos/international_frequencies.py
@@ -3,7 +3,7 @@
 using population estimates.
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
@@ -26,7 +26,7 @@
     AFtab = pd.read_csv("data/example/%s_raw.csv" %country)
     AFtab = AFtab[AFtab.loci == "A"]
     # Weighted average alleles
-    wav = scrapeAF.combineAF(AFtab)
+    wav = HLAfreq.combineAF(AFtab)
     # Add country to dataset
     wav['country'] = country
     wavs.append(wav)
@@ -40,7 +40,7 @@
 international['population_size'] = international.country.apply(lambda x: population_sizes[x])
 
 #International Weighted Average
-iwav = scrapeAF.combineAF(international, weights='population_size', datasetID='country')
+iwav = HLAfreq.combineAF(international, weights='population_size', datasetID='country')
 
 plt.scatter(
     international.allele,
diff --git a/code/demos/multi_country.py b/code/demos/multi_country.py
index fd642da..9af2bbd 100644
--- a/code/demos/multi_country.py
+++ b/code/demos/multi_country.py
@@ -7,7 +7,7 @@
 rather than the population which is the default. 
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -19,10 +19,10 @@
 # Download HLA allele frequencies
 for country in countries:
     print(country)
-    base_url = scrapeAF.makeURL(
+    base_url = HLAfreq.makeURL(
         country, standard='s', locus="A",
         resolution_pattern="bigger_equal_than", resolution=2)
-    aftab = scrapeAF.getAFdata(base_url)
+    aftab = HLAfreq.getAFdata(base_url)
     aftab.to_csv("data/example/multi_country/%s_raw.csv" %country, index=False)
 
 # Combine alleles frequencies within country
@@ -31,11 +31,11 @@
     # Load raw county data
     aftab = pd.read_csv("data/example/multi_country/%s_raw.csv" %country)
     # Drop any incomplete studies
-    aftab = scrapeAF.only_complete(aftab)
+    aftab = HLAfreq.only_complete(aftab)
     # Ensure all alleles have the same resolution
-    aftab = scrapeAF.decrease_resolution(aftab, 2)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
     # Combine studies within country
-    caf = scrapeAF.combineAF(aftab)
+    caf = HLAfreq.combineAF(aftab)
     # Add country name to dataset, this is used as `datasetID` going forward
     caf['country'] = country
     cafs.append(caf)
@@ -44,7 +44,7 @@
 # into a single dataframe
 cafs = pd.concat(cafs, ignore_index=True)
 # Combine allele frequency data of all countries
-international = scrapeAF.combineAF(cafs, datasetID='country')
+international = HLAfreq.combineAF(cafs, datasetID='country')
 
 # Plot international averages as bar plot
 international.plot.barh('allele', 'allele_freq')
@@ -55,7 +55,7 @@
 plt.show()
 
 # Plot international allele frequencies estimates and individual countries
-scrapeAF.plotAFprob(international, cafs, datasetID='country', ncol=4)
+HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)
 
 # Plot specific alleles and zoom in on frequencies
 # Select alleles to plot
@@ -63,7 +63,7 @@
 # Must be a list
 hifreq = hifreq.tolist()
 # Plot only selected alleles
-scrapeAF.plotAFprob(
+HLAfreq.plotAFprob(
     international,
     cafs,
     datasetID='country',
@@ -139,15 +139,15 @@
 # samples were observed with allele x. If unspecified this defaults
 # to double the sample size (to accound for diploid samples from each
 # individual)
-winternational = scrapeAF.combineAF(cafs, datasetID='country', weights='weighted_sample_size')
+winternational = HLAfreq.combineAF(cafs, datasetID='country', weights='weighted_sample_size')
 
-scrapeAF.plotAFprob(international, cafs, datasetID='country', ncol=4)
+HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)
 
 hifreq = winternational[winternational.allele_freq > 0.01].allele
 # Must be a list
 hifreq = hifreq.tolist()
 # Plot only selected alleles
-scrapeAF.plotAFprob(
+HLAfreq.plotAFprob(
     winternational,
     cafs,
     datasetID='country',
diff --git a/code/demos/population_coverage.py b/code/demos/population_coverage.py
index 634ee9b..6d5dc86 100644
--- a/code/demos/population_coverage.py
+++ b/code/demos/population_coverage.py
@@ -3,7 +3,7 @@
 What is the population coverage of different supertypes?
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
@@ -15,7 +15,7 @@
 AFtab = pd.read_csv("data/example/Uganda_raw.csv")
 AFtab =  AFtab[AFtab.loci=="A"]
 # Weighted average alleles
-wav = scrapeAF.combineAF(AFtab)
+wav = HLAfreq.combineAF(AFtab)
 # Add HLA1 supertypes
 wav = pd.merge(wav, super1)
 wava = wav[wav.loci == "A"].sort_values('allele_freq', ascending=False, ignore_index = True)
@@ -30,7 +30,7 @@
 plt.show()
 
 plt.plot(wava.allele_freq.cumsum(), label="Cumulative AF")
-plt.plot(wava.allele_freq.cumsum().apply(scrapeAF.population_coverage), label="Cumulative coverage")
+plt.plot(wava.allele_freq.cumsum().apply(HLAfreq.population_coverage), label="Cumulative coverage")
 plt.axhline(y=1, color="black", linestyle="--")
 plt.legend()
 plt.show()
@@ -38,7 +38,7 @@
 for supertype in wava.supertype.unique():
     print(supertype)
     supertypedf = wava[wava.supertype == supertype].reset_index()
-    plt.plot(supertypedf.allele_freq.cumsum().apply(scrapeAF.population_coverage), label=supertype)
+    plt.plot(supertypedf.allele_freq.cumsum().apply(HLAfreq.population_coverage), label=supertype)
 plt.legend()
 plt.show()
 
diff --git a/code/demos/select_hla_panel.py b/code/demos/select_hla_panel.py
index fa5b6f0..886db7a 100644
--- a/code/demos/select_hla_panel.py
+++ b/code/demos/select_hla_panel.py
@@ -4,7 +4,7 @@
 populations, being sure to select a range of supertypes.
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -26,8 +26,8 @@
 #     for country in countries:
 #         print(country)
 #         try:
-#             base_url = scrapeAF.makeURL(country, standard='s', locus=locus)
-#             aftab = scrapeAF.getAFdata(base_url)
+#             base_url = HLAfreq.makeURL(country, standard='s', locus=locus)
+#             aftab = HLAfreq.getAFdata(base_url)
 #             aftab.to_csv(f"data/example/population_coverage/{country}_{locus}_raw.csv", index=False)
 #         except:
 #             pass
@@ -41,16 +41,16 @@
 for country in countries:
     try:
         afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
-        afa = scrapeAF.only_complete(afa)
-        afa = scrapeAF.decrease_resolution(afa, 2)
-        cafa = scrapeAF.combineAF(afa)
+        afa = HLAfreq.only_complete(afa)
+        afa = HLAfreq.decrease_resolution(afa, 2)
+        cafa = HLAfreq.combineAF(afa)
         maska = cafa.allele.isin(iedb_ref)
         p = cafa[maska].allele_freq.sum()
 
         afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
-        afb = scrapeAF.only_complete(afb)
-        afb = scrapeAF.decrease_resolution(afb, 2)
-        cafb = scrapeAF.combineAF(afb)
+        afb = HLAfreq.only_complete(afb)
+        afb = HLAfreq.decrease_resolution(afb, 2)
+        cafb = HLAfreq.combineAF(afb)
         maskb = cafb.allele.isin(iedb_ref)
         m = cafb[maskb].allele_freq.sum()
         # Population proportion with no IEDB ref alleles
@@ -78,16 +78,16 @@
 country = "Indonesia"
 # country="Philippines"
 afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
-afa = scrapeAF.only_complete(afa)
-afa = scrapeAF.decrease_resolution(afa, 2)
-cafa = scrapeAF.combineAF(afa)
+afa = HLAfreq.only_complete(afa)
+afa = HLAfreq.decrease_resolution(afa, 2)
+cafa = HLAfreq.combineAF(afa)
 maska = cafa.allele.isin(iedb_ref)
 p = cafa[maska].allele_freq.sum()
 
 afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
-afb = scrapeAF.only_complete(afb)
-afb = scrapeAF.decrease_resolution(afb, 2)
-cafb = scrapeAF.combineAF(afb)
+afb = HLAfreq.only_complete(afb)
+afb = HLAfreq.decrease_resolution(afb, 2)
+cafb = HLAfreq.combineAF(afb)
 maskb = cafb.allele.isin(iedb_ref)
 m = cafb[maskb].allele_freq.sum()
 # Population proportion with no IEDB ref alleles
@@ -102,14 +102,14 @@
 
 fig, ax = plt.subplots(1,2, gridspec_kw={'width_ratios': [1,2]})
 ax[0].plot(cafa.allele,
-    cafa.allele_freq.cumsum().apply(scrapeAF.population_coverage),
+    cafa.allele_freq.cumsum().apply(HLAfreq.population_coverage),
     c="black",
     zorder=0)
 for supertype in cafa.supertype.unique():
     mask = cafa.supertype == supertype
     ax[0].scatter(
         cafa[mask].allele,
-        cafa.allele_freq.cumsum().apply(scrapeAF.population_coverage)[mask],
+        cafa.allele_freq.cumsum().apply(HLAfreq.population_coverage)[mask],
         label=supertype,
         zorder=10)
 ax[0].set_title("HLA A")
@@ -119,14 +119,14 @@
 ax[0].tick_params(labelrotation=90)
 
 ax[1].plot(cafb.allele,
-    cafb.allele_freq.cumsum().apply(scrapeAF.population_coverage),
+    cafb.allele_freq.cumsum().apply(HLAfreq.population_coverage),
     c="black",
     zorder=0)
 for supertype in cafb.supertype.unique():
     mask = cafb.supertype == supertype
     ax[1].scatter(
         cafb[mask].allele,
-        cafb.allele_freq.cumsum().apply(scrapeAF.population_coverage)[mask],
+        cafb.allele_freq.cumsum().apply(HLAfreq.population_coverage)[mask],
         label=supertype,
         zorder=10)
 ax[1].set_title("HLA B")
diff --git a/code/demos/single_country.py b/code/demos/single_country.py
index 4fe9b2c..13eff39 100644
--- a/code/demos/single_country.py
+++ b/code/demos/single_country.py
@@ -4,7 +4,7 @@
 Calculate average
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -23,8 +23,8 @@
 
 country = "Thailand"
 
-base_url = scrapeAF.makeURL(country)
-aftab = scrapeAF.getAFdata(base_url)
+base_url = HLAfreq.makeURL(country)
+aftab = HLAfreq.getAFdata(base_url)
 aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
 #aftab = pd.read_csv("data/example/%s_raw.csv" %country)
 
@@ -45,7 +45,7 @@
 """
 
 # Drop any incomplete studies
-aftab = scrapeAF.only_complete(aftab)
+aftab = HLAfreq.only_complete(aftab)
 
 #########################
 #                       #
@@ -70,9 +70,9 @@
 specified level so they can be combined.
 """
 
-scrapeAF.check_resolution(aftab)
+HLAfreq.check_resolution(aftab)
 
-aftab = scrapeAF.decrease_resolution(aftab, 2)
+aftab = HLAfreq.decrease_resolution(aftab, 2)
 
 
 #########################
@@ -87,20 +87,20 @@
 allele frequency estimates using `combineAF()`
 """
 
-scrapeAF.combineAF(aftab)
+HLAfreq.combineAF(aftab)
 
 afloc = aftab[aftab.loci=="DRB1"]
-caf = scrapeAF.combineAF(afloc)
+caf = HLAfreq.combineAF(afloc)
 
 # Calculate credible interval
-caf[['cl','cu']] = scrapeAF.AFci(caf)
+caf[['cl','cu']] = HLAfreq.AFci(caf)
 
 caf.plot.barh('allele', 'allele_freq')
 plt.tight_layout()
 plt.show()
 
-scrapeAF.plotAFprob(caf, afloc)
-scrapeAF.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])
+HLAfreq.plotAFprob(caf, afloc)
+HLAfreq.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])
 
 #############################
 #                           #
@@ -111,8 +111,8 @@
 # Sort by allele frequency
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
 
-plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(scrapeAF.population_coverage))
-plt.plot(caf.allele_freq.cumsum().apply(scrapeAF.population_coverage), label="Cumulative coverage")
+plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.plot(caf.allele_freq.cumsum().apply(HLAfreq.population_coverage), label="Cumulative coverage")
 plt.grid(True)
 plt.xticks(rotation=90)
 plt.legend()
diff --git a/code/demos/visualise_high_k_dirichlet.py b/code/demos/visualise_high_k_dirichlet.py
index 5678ff9..ba9b999 100644
--- a/code/demos/visualise_high_k_dirichlet.py
+++ b/code/demos/visualise_high_k_dirichlet.py
@@ -7,7 +7,7 @@
 import numpy as np
 from scipy.stats import dirichlet, beta
 import pandas as pd
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 
 #####################
 #                   #
@@ -18,14 +18,14 @@
 # Load allele frequency data
 AFtab = pd.read_csv(f"data/example/outlier_raw.csv")
 # Reduce resolution to 2 fields and collapse alleles
-AFtab = scrapeAF.decrease_resolution(AFtab, 2)
+AFtab = HLAfreq.decrease_resolution(AFtab, 2)
 # Combined allle frequency
-# noncomplete = scrapeAF.incomplete_studies(AFtab)
+# noncomplete = HLAfreq.incomplete_studies(AFtab)
 # complete_mask = AFtab.apply(lambda x: (x.population, x.loci) not in noncomplete.index, axis=1)
 # AFtab = AFtab[complete_mask]
-caf = scrapeAF.combineAF(AFtab)
+caf = HLAfreq.combineAF(AFtab)
 # Recreate the Dirichlet distribution
-naivealpha = scrapeAF.default_prior(len(caf.allele))
+naivealpha = HLAfreq.default_prior(len(caf.allele))
 
 # Dirichlet distribution concentration parameters 
 # based on allele frequency data
@@ -67,13 +67,13 @@
 ######################
 
 # View pdf only
-scrapeAF.plotAFprob(concentration=alpha, ci=0)
+HLAfreq.plotAFprob(concentration=alpha, ci=0)
 # View estimated AF
-scrapeAF.plotAFprob(caf)
+HLAfreq.plotAFprob(caf)
 # View estimated AF with individual studies
-scrapeAF.plotAFprob(caf, AFtab)
+HLAfreq.plotAFprob(caf, AFtab)
 # View subset of alleles
-scrapeAF.plotAFprob(caf, AFtab, alleles=["DQB1*03:01","DQB1*05:01","DQB1*05:02"])
+HLAfreq.plotAFprob(caf, AFtab, alleles=["DQB1*03:01","DQB1*05:01","DQB1*05:02"])
 
 # CI may be misleading
 
@@ -85,7 +85,7 @@
 for c in clist:
     long_c.append(c)
     long_c.append(0)
-scrapeAF.plotAFprob(concentration=pd.Series(long_c), ncol=2)
+HLAfreq.plotAFprob(concentration=pd.Series(long_c), ncol=2)
 
 pline = np.linspace(0,1,500)
 fig, ax = plt.subplots()
diff --git a/code/demos/working_with_priors.py b/code/demos/working_with_priors.py
index 2a81b4a..c5223aa 100644
--- a/code/demos/working_with_priors.py
+++ b/code/demos/working_with_priors.py
@@ -4,7 +4,7 @@
 hand.
 """
 
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -15,12 +15,12 @@
 """
 
 venezuelaAF = pd.read_csv("data/example/globalPCA/Venezuela_raw.csv")
-venezuelaAF = scrapeAF.only_complete(venezuelaAF)
-venezuelaAF = scrapeAF.decrease_resolution(venezuelaAF, 2)
-cafV = scrapeAF.combineAF(venezuelaAF)
+venezuelaAF = HLAfreq.only_complete(venezuelaAF)
+venezuelaAF = HLAfreq.decrease_resolution(venezuelaAF, 2)
+cafV = HLAfreq.combineAF(venezuelaAF)
 cafV['study'] =  'Venezuela'
 
-scrapeAF.plotAFprob(cafV, venezuelaAF)
+HLAfreq.plotAFprob(cafV, venezuelaAF)
 
 """
 We can specify priors manually. For simplicity we use
@@ -37,13 +37,13 @@
 manual_prior = [10, 1, 1, 1, 1]
 
 # View prior distribution
-scrapeAF.plotAFprob(concentration=manual_prior)
+HLAfreq.plotAFprob(concentration=manual_prior)
 
 # Combine Allele Freq of study with Manual Prior
-cafMP = scrapeAF.combineAF(venezuelaAF, alpha=manual_prior)
+cafMP = HLAfreq.combineAF(venezuelaAF, alpha=manual_prior)
 
 # View posterior distribution
-scrapeAF.plotAFprob(cafMP, AFtab=venezuelaAF)
+HLAfreq.plotAFprob(cafMP, AFtab=venezuelaAF)
 
 """
 Alternatively we can use another population as our prior.
@@ -61,24 +61,24 @@
 """
 
 colombiaAF = pd.read_csv("data/example/globalPCA/Colombia_raw.csv")
-colombiaAF = scrapeAF.only_complete(colombiaAF)
-colombiaAF = scrapeAF.decrease_resolution(colombiaAF, 2)
-cafC = scrapeAF.combineAF(colombiaAF)
+colombiaAF = HLAfreq.only_complete(colombiaAF)
+colombiaAF = HLAfreq.decrease_resolution(colombiaAF, 2)
+cafC = HLAfreq.combineAF(colombiaAF)
 cafC['population'] =  'Colombia'
 
 study_prior = cafC.copy()
 study_prior.sample_size = study_prior.sample_size * 0.01
 
 # View prior
-scrapeAF.plotAFprob(
+HLAfreq.plotAFprob(
     concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()
 )
 
 # Combine Allele Frequency with Study Prior
-cafSP = scrapeAF.combineAF(
+cafSP = HLAfreq.combineAF(
     pd.concat([venezuelaAF, study_prior], join="inner")
     )
 
 # View posterior
-scrapeAF.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"))
-scrapeAF.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"), alleles=venezuelaAF.allele.tolist())
+HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"))
+HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"), alleles=venezuelaAF.allele.tolist())
diff --git a/code/dirichlet_test.py b/code/dirichlet_test.py
index 153c55a..17c2fa2 100644
--- a/code/dirichlet_test.py
+++ b/code/dirichlet_test.py
@@ -7,7 +7,7 @@
 import numpy as np
 from scipy.stats import dirichlet, beta
 import pandas as pd
-import code.scrapeAF as scrapeAF
+import code.HLAfreq as HLAfreq
 
 # define a Dirichlet Distributions with parameters alpha
 alpha = np.array([0.4, 5, 15])  # specify concentration parameters
@@ -130,7 +130,7 @@
 df = pd.read_csv("data/example/%s_raw.csv" %country)
 loci = "DPB1"
 dfa = df[df.loci == loci]
-caf = scrapeAF.combineAF(dfa)
+caf = HLAfreq.combineAF(dfa)
 
 plt.scatter(
     caf.wav,
@@ -155,7 +155,7 @@
 a,b = 2,5
 bd = beta(a,b)
 pdf = bd.pdf(pline)
-cl,cu = scrapeAF.betaCI(a,b)
+cl,cu = HLAfreq.betaCI(a,b)
 
 plt.plot(pline, pdf)
 plt.fill_between([cl,cu], [bd.pdf(cl), bd.pdf(cu)], alpha=0.5)
diff --git a/readme.md b/readme.md
index 08fec7b..6462b11 100644
--- a/readme.md
+++ b/readme.md
@@ -1,13 +1,17 @@
-# scrapeAF
+# HLAfreq
 
 The aim of this tool is to be able to estimate the HLA allele
-frequencies at large multi population scale, e.g. globally.
-Scrape allele frequency data from
+frequencies at large multi population scale, e.g. combine data from
+several studies within a country or combine countries.
+Allele frequency data from
 [allele frequencies.net](http://www.allelefrequencies.net/).
-This gives frequencies by population, which can be averaged
-across studies, weighted by sample size. Frequencies can then
-be averaged across populations if a relative weighting can
-found, i.e. population size.
+This gives frequencies by population, which can be combined across
+studies. Estimates are combined by modelling allele frequency as a 
+Dirichlet distribution which defines the probability of drawing each
+allele. When combining studies are weighted by 2 x sample size by
+default. Sample size is doubled as each person in the study
+contributes two alleles. Alternative weightings can be used
+for example population size when averaging across countries.
 
 ```
 import sys

From 82204780e271d25e9512ab7b341a796f6b65e92c Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 16:21:50 +0100
Subject: [PATCH 048/192] Restructuring to confirm to package guide

---
 readme.md => README.md                                 | 0
 {code/demos => examples}/check_study_completeness.py   | 0
 {code/demos => examples}/compare_countries.py          | 0
 {code => examples}/dirichlet_test.py                   | 0
 {code/demos => examples}/entropy_map.py                | 0
 {code/demos => examples}/globalPCA.py                  | 0
 {code/demos => examples}/globalPCA2.py                 | 0
 {code/demos => examples}/international_frequencies.py  | 0
 {code/demos => examples}/multi_country.py              | 0
 {code/demos => examples}/population_coverage.py        | 0
 {code/demos => examples}/select_hla_panel.py           | 0
 {code/demos => examples}/single_country.py             | 0
 {code/demos => examples}/visualise_high_k_dirichlet.py | 0
 {code/demos => examples}/working_with_priors.py        | 0
 code/setup.sh => setup.sh                              | 0
 {code => src}/HLAfreq.py                               | 0
 {code => src}/__init__.py                              | 0
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 rename readme.md => README.md (100%)
 rename {code/demos => examples}/check_study_completeness.py (100%)
 rename {code/demos => examples}/compare_countries.py (100%)
 rename {code => examples}/dirichlet_test.py (100%)
 rename {code/demos => examples}/entropy_map.py (100%)
 rename {code/demos => examples}/globalPCA.py (100%)
 rename {code/demos => examples}/globalPCA2.py (100%)
 rename {code/demos => examples}/international_frequencies.py (100%)
 rename {code/demos => examples}/multi_country.py (100%)
 rename {code/demos => examples}/population_coverage.py (100%)
 rename {code/demos => examples}/select_hla_panel.py (100%)
 rename {code/demos => examples}/single_country.py (100%)
 rename {code/demos => examples}/visualise_high_k_dirichlet.py (100%)
 rename {code/demos => examples}/working_with_priors.py (100%)
 rename code/setup.sh => setup.sh (100%)
 rename {code => src}/HLAfreq.py (100%)
 rename {code => src}/__init__.py (100%)

diff --git a/readme.md b/README.md
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diff --git a/code/demos/check_study_completeness.py b/examples/check_study_completeness.py
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diff --git a/code/demos/compare_countries.py b/examples/compare_countries.py
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rename to examples/compare_countries.py
diff --git a/code/dirichlet_test.py b/examples/dirichlet_test.py
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rename from code/dirichlet_test.py
rename to examples/dirichlet_test.py
diff --git a/code/demos/entropy_map.py b/examples/entropy_map.py
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rename to examples/entropy_map.py
diff --git a/code/demos/globalPCA.py b/examples/globalPCA.py
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diff --git a/code/demos/globalPCA2.py b/examples/globalPCA2.py
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diff --git a/code/demos/international_frequencies.py b/examples/international_frequencies.py
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rename to examples/international_frequencies.py
diff --git a/code/demos/multi_country.py b/examples/multi_country.py
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rename to examples/multi_country.py
diff --git a/code/demos/population_coverage.py b/examples/population_coverage.py
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rename to examples/population_coverage.py
diff --git a/code/demos/select_hla_panel.py b/examples/select_hla_panel.py
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diff --git a/code/demos/single_country.py b/examples/single_country.py
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diff --git a/code/demos/visualise_high_k_dirichlet.py b/examples/visualise_high_k_dirichlet.py
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diff --git a/code/demos/working_with_priors.py b/examples/working_with_priors.py
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diff --git a/code/setup.sh b/setup.sh
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From b9c04d62f5088d68cb7ca18d3f704e439067c389 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 13 Oct 2022 16:48:26 +0100
Subject: [PATCH 049/192] Build package

---
 dist/hlafreq-0.0.1.dev0-py3-none-any.whl | Bin 0 -> 27446 bytes
 dist/hlafreq-0.0.1.dev0.tar.gz           | Bin 0 -> 21324 bytes
 pyproject.toml                           |  21 +++++++++++++++++++++
 3 files changed, 21 insertions(+)
 create mode 100644 dist/hlafreq-0.0.1.dev0-py3-none-any.whl
 create mode 100644 dist/hlafreq-0.0.1.dev0.tar.gz
 create mode 100644 pyproject.toml

diff --git a/dist/hlafreq-0.0.1.dev0-py3-none-any.whl b/dist/hlafreq-0.0.1.dev0-py3-none-any.whl
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literal 0
HcmV?d00001

diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..738268b
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,21 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "HLAfreq"
+version = "0.0.1dev0"
+authors = [
+  { name="David Wells", email="david.wells@vaccitech.co.uk" },
+]
+description = "Download and combine HLA frequency data from multiple studies"
+readme = "README.md"
+requires-python = ">=3.7"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "Operating System :: OS Independent",
+]
+
+[project.urls]
+"Homepage" = "https://github.com/Vaccitech/HLAfreq"
+"Bug Tracker" = "https://github.com/Vaccitech/HLAfreq/issues"
\ No newline at end of file

From 819c12d24365edab2bccb12c68add9affd918ad6 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 10:06:36 +0100
Subject: [PATCH 050/192] Change build process to setuptools

---
 MANIFEST.in                   |  1 +
 pyproject.toml                | 21 ---------------------
 setup.py                      | 28 ++++++++++++++++++++++++++++
 src/{ => HLAfreq}/HLAfreq.py  |  0
 src/{ => HLAfreq}/__init__.py |  0
 5 files changed, 29 insertions(+), 21 deletions(-)
 create mode 100644 MANIFEST.in
 delete mode 100644 pyproject.toml
 create mode 100644 setup.py
 rename src/{ => HLAfreq}/HLAfreq.py (100%)
 rename src/{ => HLAfreq}/__init__.py (100%)

diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..9a839a9
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1 @@
+include src/data/*.csv
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index 738268b..0000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,21 +0,0 @@
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-[project]
-name = "HLAfreq"
-version = "0.0.1dev0"
-authors = [
-  { name="David Wells", email="david.wells@vaccitech.co.uk" },
-]
-description = "Download and combine HLA frequency data from multiple studies"
-readme = "README.md"
-requires-python = ">=3.7"
-classifiers = [
-    "Programming Language :: Python :: 3",
-    "Operating System :: OS Independent",
-]
-
-[project.urls]
-"Homepage" = "https://github.com/Vaccitech/HLAfreq"
-"Bug Tracker" = "https://github.com/Vaccitech/HLAfreq/issues"
\ No newline at end of file
diff --git a/setup.py b/setup.py
new file mode 100644
index 0000000..da9084e
--- /dev/null
+++ b/setup.py
@@ -0,0 +1,28 @@
+import setuptools
+
+setuptools.setup(
+    name="HLAfreq",
+    version="0.0.1dev0",
+    url="https://github.com/Vaccitech/HLAfreq",
+    project_urls={
+        'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
+    },
+    author="David Wells",
+    author_email="david.wells@vaccitech.co.uk",
+    description="Download and combine HLA frequency data from multiple studies",
+    long_description=open('README.md').read(),
+    packages=setuptools.find_packages(),
+    install_requires=[
+        'bs4',
+        'requests',
+        'pandas',
+        'numpy',
+        'matplotlib',
+        'scipy',
+    ],
+    classifiers=[
+    "Programming Language :: Python :: 3",
+    "Operating System :: OS Independent",
+    ],
+    include_package_data=True
+)
\ No newline at end of file
diff --git a/src/HLAfreq.py b/src/HLAfreq/HLAfreq.py
similarity index 100%
rename from src/HLAfreq.py
rename to src/HLAfreq/HLAfreq.py
diff --git a/src/__init__.py b/src/HLAfreq/__init__.py
similarity index 100%
rename from src/__init__.py
rename to src/HLAfreq/__init__.py

From 6f23db33f60cccad7c328098a8ea120cf46712f8 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 10:11:34 +0100
Subject: [PATCH 051/192] python -m build with setuptools

---
 HLAfreq.egg-info/PKG-INFO                |  57 +++++++++++++++++++++++
 HLAfreq.egg-info/SOURCES.txt             |  10 ++++
 HLAfreq.egg-info/dependency_links.txt    |   1 +
 HLAfreq.egg-info/requires.txt            |   6 +++
 HLAfreq.egg-info/top_level.txt           |   1 +
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl | Bin 0 -> 2031 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz           | Bin 0 -> 6997 bytes
 dist/hlafreq-0.0.1.dev0-py3-none-any.whl | Bin 27446 -> 0 bytes
 dist/hlafreq-0.0.1.dev0.tar.gz           | Bin 21324 -> 0 bytes
 9 files changed, 75 insertions(+)
 create mode 100644 HLAfreq.egg-info/PKG-INFO
 create mode 100644 HLAfreq.egg-info/SOURCES.txt
 create mode 100644 HLAfreq.egg-info/dependency_links.txt
 create mode 100644 HLAfreq.egg-info/requires.txt
 create mode 100644 HLAfreq.egg-info/top_level.txt
 create mode 100644 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
 create mode 100644 dist/HLAfreq-0.0.1.dev0.tar.gz
 delete mode 100644 dist/hlafreq-0.0.1.dev0-py3-none-any.whl
 delete mode 100644 dist/hlafreq-0.0.1.dev0.tar.gz

diff --git a/HLAfreq.egg-info/PKG-INFO b/HLAfreq.egg-info/PKG-INFO
new file mode 100644
index 0000000..aee4b47
--- /dev/null
+++ b/HLAfreq.egg-info/PKG-INFO
@@ -0,0 +1,57 @@
+Metadata-Version: 2.1
+Name: HLAfreq
+Version: 0.0.1.dev0
+Summary: Download and combine HLA frequency data from multiple studies
+Home-page: https://github.com/Vaccitech/HLAfreq
+Author: David Wells
+Author-email: david.wells@vaccitech.co.uk
+Project-URL: Tracker, https://github.com/Vaccitech/HLAfreq/issues
+Classifier: Programming Language :: Python :: 3
+Classifier: Operating System :: OS Independent
+
+# HLAfreq
+
+The aim of this tool is to be able to estimate the HLA allele
+frequencies at large multi population scale, e.g. combine data from
+several studies within a country or combine countries.
+Allele frequency data from
+[allele frequencies.net](http://www.allelefrequencies.net/).
+This gives frequencies by population, which can be combined across
+studies. Estimates are combined by modelling allele frequency as a 
+Dirichlet distribution which defines the probability of drawing each
+allele. When combining studies are weighted by 2 x sample size by
+default. Sample size is doubled as each person in the study
+contributes two alleles. Alternative weightings can be used
+for example population size when averaging across countries.
+
+```
+import sys
+sys.path.append("/home/dwells/work/tools/scrapeAF/code")
+import scrapeAF
+```
+
+When selecting alleles to represent a population, all supertypes
+should be represented.
+
+When combining estimates of allele frequency larger samples should
+weigh more heavily. However, when combining estiamtes that disagree
+the uncertainty on the estimate should be larger than when combining
+equivalent samples that agree.
+
+When combining studies we must weight averages by sample size but
+when combining countries are we not better to weight by national population?
+Should sample size also have an effect?
+
+IEDB provide reference sets of HLA alleles designed to cover the
+majority of the "general population". However, all populations are
+not likely to be equally well covered by them. Using population
+specific allele frequencies we should be able to select more
+appropriate HLA sets. However, allele frequency is not the only
+determinent when selecting a pannel of alleles. The pannel must
+also contain representatives of commonly shared binding specificities
+(i.e., supertypes).
+
+# Dependencies
+scrapeAF
+umap
+maps
diff --git a/HLAfreq.egg-info/SOURCES.txt b/HLAfreq.egg-info/SOURCES.txt
new file mode 100644
index 0000000..c54ec4f
--- /dev/null
+++ b/HLAfreq.egg-info/SOURCES.txt
@@ -0,0 +1,10 @@
+MANIFEST.in
+README.md
+setup.py
+HLAfreq.egg-info/PKG-INFO
+HLAfreq.egg-info/SOURCES.txt
+HLAfreq.egg-info/dependency_links.txt
+HLAfreq.egg-info/requires.txt
+HLAfreq.egg-info/top_level.txt
+src/data/HLA1supertypes_Sidney2008.csv
+src/data/countries.csv
\ No newline at end of file
diff --git a/HLAfreq.egg-info/dependency_links.txt b/HLAfreq.egg-info/dependency_links.txt
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/HLAfreq.egg-info/dependency_links.txt
@@ -0,0 +1 @@
+
diff --git a/HLAfreq.egg-info/requires.txt b/HLAfreq.egg-info/requires.txt
new file mode 100644
index 0000000..db17ae5
--- /dev/null
+++ b/HLAfreq.egg-info/requires.txt
@@ -0,0 +1,6 @@
+bs4
+requests
+pandas
+numpy
+matplotlib
+scipy
diff --git a/HLAfreq.egg-info/top_level.txt b/HLAfreq.egg-info/top_level.txt
new file mode 100644
index 0000000..8b13789
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@@ -0,0 +1 @@
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diff --git a/dist/hlafreq-0.0.1.dev0-py3-none-any.whl b/dist/hlafreq-0.0.1.dev0-py3-none-any.whl
deleted file mode 100644
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From 12e3dd7dd2af9395315389b8c1dad4a9cb18b098 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 11:09:02 +0100
Subject: [PATCH 052/192] Add data loading functions, remove src directory

---
 {src/HLAfreq => HLAfreq}/HLAfreq.py  |  0
 HLAfreq/HLAfreq_data.py              | 13 +++++++++++++
 {src/HLAfreq => HLAfreq}/__init__.py |  0
 MANIFEST.in                          |  1 -
 setup.py                             |  3 ++-
 5 files changed, 15 insertions(+), 2 deletions(-)
 rename {src/HLAfreq => HLAfreq}/HLAfreq.py (100%)
 create mode 100644 HLAfreq/HLAfreq_data.py
 rename {src/HLAfreq => HLAfreq}/__init__.py (100%)
 delete mode 100644 MANIFEST.in

diff --git a/src/HLAfreq/HLAfreq.py b/HLAfreq/HLAfreq.py
similarity index 100%
rename from src/HLAfreq/HLAfreq.py
rename to HLAfreq/HLAfreq.py
diff --git a/HLAfreq/HLAfreq_data.py b/HLAfreq/HLAfreq_data.py
new file mode 100644
index 0000000..c040648
--- /dev/null
+++ b/HLAfreq/HLAfreq_data.py
@@ -0,0 +1,13 @@
+"""
+Data loaders
+"""
+import pkg_resources
+import pandas as pd
+
+def load_countries():
+    stream = pkg_resources.resource_stream(__name__, 'data/countries.csv')
+    return pd.read_csv(stream, encoding='latin-1')
+
+def load_HLA1supertypes_Sidney2008():
+    stream = pkg_resources.resource_stream(__name__, 'data/HLA1supertypes_Sidney2008.csv')
+    return pd.read_csv(stream, encoding='latin-1')
diff --git a/src/HLAfreq/__init__.py b/HLAfreq/__init__.py
similarity index 100%
rename from src/HLAfreq/__init__.py
rename to HLAfreq/__init__.py
diff --git a/MANIFEST.in b/MANIFEST.in
deleted file mode 100644
index 9a839a9..0000000
--- a/MANIFEST.in
+++ /dev/null
@@ -1 +0,0 @@
-include src/data/*.csv
\ No newline at end of file
diff --git a/setup.py b/setup.py
index da9084e..9867f2e 100644
--- a/setup.py
+++ b/setup.py
@@ -24,5 +24,6 @@
     "Programming Language :: Python :: 3",
     "Operating System :: OS Independent",
     ],
-    include_package_data=True
+    include_package_data=True,
+    package_data={'': ['data/*.csv']}
 )
\ No newline at end of file

From 7926abf14203905712646131a3e1321b110ca5f7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 11:47:28 +0100
Subject: [PATCH 053/192] import HLAfreq from __init__.py

---
 HLAfreq.egg-info/SOURCES.txt             |   8 +++++---
 HLAfreq.egg-info/top_level.txt           |   2 +-
 HLAfreq/__init__.py                      |   1 +
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl | Bin 2031 -> 15121 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz           | Bin 6997 -> 15221 bytes
 5 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/HLAfreq.egg-info/SOURCES.txt b/HLAfreq.egg-info/SOURCES.txt
index c54ec4f..277f285 100644
--- a/HLAfreq.egg-info/SOURCES.txt
+++ b/HLAfreq.egg-info/SOURCES.txt
@@ -1,10 +1,12 @@
-MANIFEST.in
 README.md
 setup.py
+HLAfreq/HLAfreq.py
+HLAfreq/HLAfreq_data.py
+HLAfreq/__init__.py
 HLAfreq.egg-info/PKG-INFO
 HLAfreq.egg-info/SOURCES.txt
 HLAfreq.egg-info/dependency_links.txt
 HLAfreq.egg-info/requires.txt
 HLAfreq.egg-info/top_level.txt
-src/data/HLA1supertypes_Sidney2008.csv
-src/data/countries.csv
\ No newline at end of file
+HLAfreq/data/HLA1supertypes_Sidney2008.csv
+HLAfreq/data/countries.csv
\ No newline at end of file
diff --git a/HLAfreq.egg-info/top_level.txt b/HLAfreq.egg-info/top_level.txt
index 8b13789..b260130 100644
--- a/HLAfreq.egg-info/top_level.txt
+++ b/HLAfreq.egg-info/top_level.txt
@@ -1 +1 @@
-
+HLAfreq
diff --git a/HLAfreq/__init__.py b/HLAfreq/__init__.py
index e69de29..d2604df 100644
--- a/HLAfreq/__init__.py
+++ b/HLAfreq/__init__.py
@@ -0,0 +1 @@
+from .HLAfreq import *
\ No newline at end of file
diff --git a/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
index 034eca88777c61bdc66867ab2c1454f2dc07a071..515c582ff4a5d11d8db2d1abd459e76abc461b0e 100644
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From 276b36662c947c61420d512208edfdc9131852eb Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 11:59:20 +0100
Subject: [PATCH 054/192] include data in MANIFEST

---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 MANIFEST.in

diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..33f9894
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1 @@
+include data/*.csv
\ No newline at end of file

From c9f9ef6486fe03727ddb098393ac5ed65d834f48 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 12:00:36 +0100
Subject: [PATCH 055/192] Add MANIFEST to build

---
 HLAfreq.egg-info/SOURCES.txt             |   4 +++-
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl | Bin 15121 -> 15121 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz           | Bin 15221 -> 18084 bytes
 3 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/HLAfreq.egg-info/SOURCES.txt b/HLAfreq.egg-info/SOURCES.txt
index 277f285..a5314ae 100644
--- a/HLAfreq.egg-info/SOURCES.txt
+++ b/HLAfreq.egg-info/SOURCES.txt
@@ -1,3 +1,4 @@
+MANIFEST.in
 README.md
 setup.py
 HLAfreq/HLAfreq.py
@@ -9,4 +10,5 @@ HLAfreq.egg-info/dependency_links.txt
 HLAfreq.egg-info/requires.txt
 HLAfreq.egg-info/top_level.txt
 HLAfreq/data/HLA1supertypes_Sidney2008.csv
-HLAfreq/data/countries.csv
\ No newline at end of file
+HLAfreq/data/countries.csv
+data/HLA1supertypes_Sidney2008.csv
\ No newline at end of file
diff --git a/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
index 515c582ff4a5d11d8db2d1abd459e76abc461b0e..c65591413aff950802db03dd9bbb2f91bf7f3518 100644
GIT binary patch
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diff --git a/dist/HLAfreq-0.0.1.dev0.tar.gz b/dist/HLAfreq-0.0.1.dev0.tar.gz
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From d73584e0e0d99ce62a8504a50058fb7dee88822f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 14 Oct 2022 16:56:55 +0100
Subject: [PATCH 056/192] Correctly add data to package that can be used

Data loaded with HLAfreq.HLAfreq_data.load_countries() etc.
---
 MANIFEST.in                               |   2 +-
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl  | Bin 15121 -> 15147 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz            | Bin 18084 -> 16495 bytes
 pyproject.toml                            |   3 ++
 setup.py                                  |  11 ++--
 src/HLAfreq.egg-info/PKG-INFO             |  58 ++++++++++++++++++++++
 src/HLAfreq.egg-info/SOURCES.txt          |  14 ++++++
 src/HLAfreq.egg-info/dependency_links.txt |   1 +
 src/HLAfreq.egg-info/requires.txt         |   6 +++
 src/HLAfreq.egg-info/top_level.txt        |   1 +
 {HLAfreq => src/HLAfreq}/HLAfreq.py       |   0
 {HLAfreq => src/HLAfreq}/HLAfreq_data.py  |   0
 {HLAfreq => src/HLAfreq}/__init__.py      |   0
 13 files changed, 91 insertions(+), 5 deletions(-)
 create mode 100644 pyproject.toml
 create mode 100644 src/HLAfreq.egg-info/PKG-INFO
 create mode 100644 src/HLAfreq.egg-info/SOURCES.txt
 create mode 100644 src/HLAfreq.egg-info/dependency_links.txt
 create mode 100644 src/HLAfreq.egg-info/requires.txt
 create mode 100644 src/HLAfreq.egg-info/top_level.txt
 rename {HLAfreq => src/HLAfreq}/HLAfreq.py (100%)
 rename {HLAfreq => src/HLAfreq}/HLAfreq_data.py (100%)
 rename {HLAfreq => src/HLAfreq}/__init__.py (100%)

diff --git a/MANIFEST.in b/MANIFEST.in
index 33f9894..6961c5e 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1 +1 @@
-include data/*.csv
\ No newline at end of file
+include src/HLAfreq/data/*.csv
\ No newline at end of file
diff --git a/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
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diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..7fd26b9
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools"]
+build-backend = "setuptools.build_meta"
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 9867f2e..96a1b7f 100644
--- a/setup.py
+++ b/setup.py
@@ -1,6 +1,6 @@
-import setuptools
+from setuptools import setup, find_packages
 
-setuptools.setup(
+setup(
     name="HLAfreq",
     version="0.0.1dev0",
     url="https://github.com/Vaccitech/HLAfreq",
@@ -11,7 +11,7 @@
     author_email="david.wells@vaccitech.co.uk",
     description="Download and combine HLA frequency data from multiple studies",
     long_description=open('README.md').read(),
-    packages=setuptools.find_packages(),
+    long_description_content_type="text/markdown",
     install_requires=[
         'bs4',
         'requests',
@@ -24,6 +24,9 @@
     "Programming Language :: Python :: 3",
     "Operating System :: OS Independent",
     ],
+    package_dir={'':'src'},
+    packages=find_packages(
+        where='src'
+    ),
     include_package_data=True,
-    package_data={'': ['data/*.csv']}
 )
\ No newline at end of file
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
new file mode 100644
index 0000000..2630395
--- /dev/null
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -0,0 +1,58 @@
+Metadata-Version: 2.1
+Name: HLAfreq
+Version: 0.0.1.dev0
+Summary: Download and combine HLA frequency data from multiple studies
+Home-page: https://github.com/Vaccitech/HLAfreq
+Author: David Wells
+Author-email: david.wells@vaccitech.co.uk
+Project-URL: Tracker, https://github.com/Vaccitech/HLAfreq/issues
+Classifier: Programming Language :: Python :: 3
+Classifier: Operating System :: OS Independent
+Description-Content-Type: text/markdown
+
+# HLAfreq
+
+The aim of this tool is to be able to estimate the HLA allele
+frequencies at large multi population scale, e.g. combine data from
+several studies within a country or combine countries.
+Allele frequency data from
+[allele frequencies.net](http://www.allelefrequencies.net/).
+This gives frequencies by population, which can be combined across
+studies. Estimates are combined by modelling allele frequency as a 
+Dirichlet distribution which defines the probability of drawing each
+allele. When combining studies are weighted by 2 x sample size by
+default. Sample size is doubled as each person in the study
+contributes two alleles. Alternative weightings can be used
+for example population size when averaging across countries.
+
+```
+import sys
+sys.path.append("/home/dwells/work/tools/scrapeAF/code")
+import scrapeAF
+```
+
+When selecting alleles to represent a population, all supertypes
+should be represented.
+
+When combining estimates of allele frequency larger samples should
+weigh more heavily. However, when combining estiamtes that disagree
+the uncertainty on the estimate should be larger than when combining
+equivalent samples that agree.
+
+When combining studies we must weight averages by sample size but
+when combining countries are we not better to weight by national population?
+Should sample size also have an effect?
+
+IEDB provide reference sets of HLA alleles designed to cover the
+majority of the "general population". However, all populations are
+not likely to be equally well covered by them. Using population
+specific allele frequencies we should be able to select more
+appropriate HLA sets. However, allele frequency is not the only
+determinent when selecting a pannel of alleles. The pannel must
+also contain representatives of commonly shared binding specificities
+(i.e., supertypes).
+
+# Dependencies
+scrapeAF
+umap
+maps
diff --git a/src/HLAfreq.egg-info/SOURCES.txt b/src/HLAfreq.egg-info/SOURCES.txt
new file mode 100644
index 0000000..8984b0c
--- /dev/null
+++ b/src/HLAfreq.egg-info/SOURCES.txt
@@ -0,0 +1,14 @@
+MANIFEST.in
+README.md
+pyproject.toml
+setup.py
+src/HLAfreq/HLAfreq.py
+src/HLAfreq/HLAfreq_data.py
+src/HLAfreq/__init__.py
+src/HLAfreq.egg-info/PKG-INFO
+src/HLAfreq.egg-info/SOURCES.txt
+src/HLAfreq.egg-info/dependency_links.txt
+src/HLAfreq.egg-info/requires.txt
+src/HLAfreq.egg-info/top_level.txt
+src/HLAfreq/data/HLA1supertypes_Sidney2008.csv
+src/HLAfreq/data/countries.csv
\ No newline at end of file
diff --git a/src/HLAfreq.egg-info/dependency_links.txt b/src/HLAfreq.egg-info/dependency_links.txt
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/src/HLAfreq.egg-info/dependency_links.txt
@@ -0,0 +1 @@
+
diff --git a/src/HLAfreq.egg-info/requires.txt b/src/HLAfreq.egg-info/requires.txt
new file mode 100644
index 0000000..db17ae5
--- /dev/null
+++ b/src/HLAfreq.egg-info/requires.txt
@@ -0,0 +1,6 @@
+bs4
+requests
+pandas
+numpy
+matplotlib
+scipy
diff --git a/src/HLAfreq.egg-info/top_level.txt b/src/HLAfreq.egg-info/top_level.txt
new file mode 100644
index 0000000..b260130
--- /dev/null
+++ b/src/HLAfreq.egg-info/top_level.txt
@@ -0,0 +1 @@
+HLAfreq
diff --git a/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
similarity index 100%
rename from HLAfreq/HLAfreq.py
rename to src/HLAfreq/HLAfreq.py
diff --git a/HLAfreq/HLAfreq_data.py b/src/HLAfreq/HLAfreq_data.py
similarity index 100%
rename from HLAfreq/HLAfreq_data.py
rename to src/HLAfreq/HLAfreq_data.py
diff --git a/HLAfreq/__init__.py b/src/HLAfreq/__init__.py
similarity index 100%
rename from HLAfreq/__init__.py
rename to src/HLAfreq/__init__.py

From d5f84a480ae59f33715e181fdf0c64c426286e27 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 09:59:38 +0100
Subject: [PATCH 057/192] Create tests

---
 examples/{dirichlet_test.py => dirichlet.py} |  0
 tests/test_single_country_caf.py             | 49 ++++++++++++++++++++
 2 files changed, 49 insertions(+)
 rename examples/{dirichlet_test.py => dirichlet.py} (100%)
 create mode 100644 tests/test_single_country_caf.py

diff --git a/examples/dirichlet_test.py b/examples/dirichlet.py
similarity index 100%
rename from examples/dirichlet_test.py
rename to examples/dirichlet.py
diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
new file mode 100644
index 0000000..96b1e43
--- /dev/null
+++ b/tests/test_single_country_caf.py
@@ -0,0 +1,49 @@
+"""
+"""
+import pytest
+import HLAfreq
+
+import pandas as pd
+from scipy.stats import dirichlet
+
+dfa =  pd.DataFrame({
+    'allele':['A*02:03','A*02:05','A*02:07'],
+    'loci':['A','A','A'],
+    'population':['test1','test1','test1'],
+    'allele_freq':[0.1, 0.3, 0.6],
+    'sample_size':[10,10,10]
+})
+dfb =  pd.DataFrame({
+    'allele':['A*02:03','A*02:05:01','A*02:05:02'],
+    'loci':['A','A', 'A'],
+    'population':['test2','test2', 'test2'],
+    'allele_freq':[0.5, 0.25, 0.25],
+    'sample_size':[5, 5, 5]
+})
+dfc =  pd.DataFrame({
+    'allele':['A*02:03','A*02:05'],
+    'loci':['A','A'],
+    'population':['test3','test3'],
+    'allele_freq':[0.5, 0.1],
+    'sample_size':[5, 5]
+})
+aftab = pd.concat([dfa, dfb, dfc])
+
+# Drop incomplete test3
+aftab = HLAfreq.only_complete(aftab)
+def test_drop_incomplete_test():
+    assert not any(aftab.population == 'test3')
+
+# Collapse 3 field alleles
+aftab = HLAfreq.decrease_resolution(aftab, 2)
+def test_resolution_decreased_correctly():
+    mask = (aftab.allele=="A*02:05") & (aftab.population=='test2')
+    assert sum(mask) == 1
+    collapsed = aftab[mask]
+    assert all(collapsed.allele_freq == 0.5)
+    assert all(collapsed.sample_size == 5)
+
+# Combine allele frequencies
+caf = HLAfreq.combineAF(aftab)
+def test_combined_allele_freq():
+    assert all(caf.allele_freq == dirichlet([8,12,13]).mean())
\ No newline at end of file

From f7bbaf825fd0043ad73fb3496500bd3ec011a431 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 10:00:51 +0100
Subject: [PATCH 058/192] Add readme to tests

---
 tests/test_single_country_caf.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index 96b1e43..92c9cc8 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -1,4 +1,8 @@
 """
+Tests on a toy allele frequency data set
+
+Tests dropping incomplete studies, merging different resolution
+alleles, and combing allele frequency estimates.
 """
 import pytest
 import HLAfreq

From 1e8e3021971f6fcd425ff907f3ddebfa3baed8cc Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 10:26:06 +0100
Subject: [PATCH 059/192] Update readme, list section (to be written)

---
 README.md | 57 ++++++++++++++++++++-----------------------------------
 1 file changed, 21 insertions(+), 36 deletions(-)

diff --git a/README.md b/README.md
index 6462b11..f9da90a 100644
--- a/README.md
+++ b/README.md
@@ -1,46 +1,31 @@
 # HLAfreq
 
-The aim of this tool is to be able to estimate the HLA allele
+`HLAfreq` allows you to estimate the HLA allele
 frequencies at large multi population scale, e.g. combine data from
 several studies within a country or combine countries.
-Allele frequency data from
+
+Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
-This gives frequencies by population, which can be combined across
-studies. Estimates are combined by modelling allele frequency as a 
+
+## Details
+Estimates are combined by modelling allele frequency as a 
 Dirichlet distribution which defines the probability of drawing each
-allele. When combining studies are weighted by 2 x sample size by
+allele. When combining studies their estimates are weighted as 2x sample size by
 default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-```
-import sys
-sys.path.append("/home/dwells/work/tools/scrapeAF/code")
-import scrapeAF
-```
-
-When selecting alleles to represent a population, all supertypes
-should be represented.
-
-When combining estimates of allele frequency larger samples should
-weigh more heavily. However, when combining estiamtes that disagree
-the uncertainty on the estimate should be larger than when combining
-equivalent samples that agree.
-
-When combining studies we must weight averages by sample size but
-when combining countries are we not better to weight by national population?
-Should sample size also have an effect?
-
-IEDB provide reference sets of HLA alleles designed to cover the
-majority of the "general population". However, all populations are
-not likely to be equally well covered by them. Using population
-specific allele frequencies we should be able to select more
-appropriate HLA sets. However, allele frequency is not the only
-determinent when selecting a pannel of alleles. The pannel must
-also contain representatives of commonly shared binding specificities
-(i.e., supertypes).
-
-# Dependencies
-scrapeAF
-umap
-maps
+A note on credible intervals...
+
+When selecting a panel of HLA alleles to represent a population,
+allele frequency is not the only thing to consider. Depending on
+the purpose of the panel, you should include a range of loci and
+supertypes (groups alleles sharing binding specificies).
+
+## Install
+
+## Minimal example
+
+## Detailed examples
+
+## Citation

From 3e8e490cdf9a08173b036b11028132c5f76192e7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 13:03:09 +0100
Subject: [PATCH 060/192] Sort examples

Convert key examples to jupyter
Move paper exampes to examples/paper
delete redundant examples
---
 examples/check_study_completeness.py     |  99 ----
 examples/compare_countries.py            |  68 ---
 examples/dirichlet.py                    | 162 -------
 examples/international_frequencies.py    |  58 ---
 examples/multi_country.ipynb             | 551 +++++++++++++++++++++++
 examples/multi_country.py                | 156 -------
 examples/{ => paper}/entropy_map.py      |   0
 examples/{ => paper}/globalPCA.py        |   0
 examples/{ => paper}/globalPCA2.py       |   0
 examples/{ => paper}/select_hla_panel.py |   0
 examples/population_coverage.py          |  48 --
 examples/single_country.ipynb            | 283 ++++++++++++
 examples/single_country.py               | 120 -----
 examples/visualise_high_k_dirichlet.py   |  98 ----
 examples/working_with_priors.ipynb       | 305 +++++++++++++
 examples/working_with_priors.py          |  84 ----
 src/HLAfreq.egg-info/PKG-INFO            |  57 +--
 17 files changed, 1160 insertions(+), 929 deletions(-)
 delete mode 100644 examples/check_study_completeness.py
 delete mode 100644 examples/compare_countries.py
 delete mode 100644 examples/dirichlet.py
 delete mode 100644 examples/international_frequencies.py
 create mode 100644 examples/multi_country.ipynb
 delete mode 100644 examples/multi_country.py
 rename examples/{ => paper}/entropy_map.py (100%)
 rename examples/{ => paper}/globalPCA.py (100%)
 rename examples/{ => paper}/globalPCA2.py (100%)
 rename examples/{ => paper}/select_hla_panel.py (100%)
 delete mode 100644 examples/population_coverage.py
 create mode 100644 examples/single_country.ipynb
 delete mode 100644 examples/single_country.py
 delete mode 100644 examples/visualise_high_k_dirichlet.py
 create mode 100644 examples/working_with_priors.ipynb
 delete mode 100644 examples/working_with_priors.py

diff --git a/examples/check_study_completeness.py b/examples/check_study_completeness.py
deleted file mode 100644
index 040ed8a..0000000
--- a/examples/check_study_completeness.py
+++ /dev/null
@@ -1,99 +0,0 @@
-"""
-Check that study-loci allele frequency sums to ~1.
-Some studies report alleles that do not sum to 1.
-Also download errors can lead to incomplete datasets.
-Some download settings can also lead to unexpected results.
-E.g. some studies report alleles to mixed resolution, therefore;
-if you search for a specific allele resolution you will download
-an incomplete dataset.
-
-Having the complete dataset is important, especially when
-calculating the Dirichlet distribution as reported alleles
-will be over weighted if some alleles are unreported.
-
-How to identify and resolve allele resolution. Because allele
-frequency estimates can only be combined if the allele name is
-identical all alleles in a study must have the same resolution
-i.e. A*01 is 2 digit resolution (or 1 field) and A*01:01 is
-4 digit (or 2 field). These cannot be combined as we cannot
-tell whether A*01 is A*01:01, A*01:02 etc. For the same reason
-we can decrease the resolution of an allele but we cannot
-increase it.
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-country = 'Thailand'
-
-# Because resolution equals 2, an incomplete dataset is returned
-base_url = HLAfreq.makeURL(country, resolution_pattern="equal", resolution=2, standard="s")
-aftab = HLAfreq.getAFdata(base_url)
-aftab.to_csv("data/example/incomplete_raw.csv", index=False)
-
-df = pd.read_csv("data/example/incomplete_raw.csv")
-
-# How to filter incomplete studies
-
-# Identify incomplete studies
-noncomplete = HLAfreq.incomplete_studies(df)
-
-# Returns False if population AND loci are in the noncomplete.index
-# AS A PAIR
-# This is important so that we don't throw away all data on a population
-# just because one loci is incomplete.
-complete_mask = df.apply(lambda x: (x.population, x.loci) not in noncomplete.index, axis=1)
-
-df = df[complete_mask]
-
-# Check filtering success
-HLAfreq.incomplete_studies(df)
-
-#################################
-#                               #
-#  Differing allele resolution  #
-#                               #
-#################################
-
-base_url = HLAfreq.makeURL(
-    'Thailand', locus="A",
-    resolution_pattern="bigger_equal_than", resolution=1
-)
-aftab = HLAfreq.getAFdata(base_url)
-aftab.to_csv("data/example/multiresolution_raw.csv", index=False)
-
-df = pd.read_csv("data/example/multiresolution_raw.csv")
-HLAfreq.check_resolution(df)
-
-# You cant increase resolution 
-HLAfreq.decrease_resolution(df, 2)
-
-# But you can decrease
-df = HLAfreq.decrease_resolution(df, 1)
-HLAfreq.check_resolution(df)
-
-# Alleles that were distinct at a higher resolution but
-# are indistinguishable at this new lower resolution,
-# have been collapsed into one allele with the same
-# sample size but the sum of constituent allele frequencies
-
-# You can check that each allele is still unique but this is
-# done automatically when reducing resolution or combining
-# allele frequencies.
-HLAfreq.alleles_unique_in_study(df)
-
-# In principal you could use 2 digit resolution
-# to estimate 4 digit resolution. E.g if A*01 has
-# frequency p we could increase the resolution by
-# spreading this across all possible A*01:xx alleles
-# More formally for k A*:01:xx alleles they would have
-# frequency p/k. This would effectively update the
-# Dirichlet distribution with a flat prior about which
-# allele A*01 was actually measured.
-
-# If this is of interest to you please open an issue or
-# pull request on github.
-
diff --git a/examples/compare_countries.py b/examples/compare_countries.py
deleted file mode 100644
index 61b5d37..0000000
--- a/examples/compare_countries.py
+++ /dev/null
@@ -1,68 +0,0 @@
-"""
-Compare HLA frequencies of different countries.
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-countries = [
-    'United+Kingdom',
-    'Uganda'
-]
-
-# Download HLA allele frequencies
-for country in countries:
-    print(country)
-    base_url = HLAfreq.makeURL(country)
-    aftab = HLAfreq.getAFdata(base_url)
-    aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
-
-wavs = []
-for country in countries:
-    df = pd.read_csv("data/example/%s_raw.csv" %country)
-    df = df[df.loci=="A"]
-    wav = HLAfreq.combineAF(df)
-    # Add credible intervals
-    wav[['cl','cu']] = HLAfreq.AFci(wav)
-    wav['country'] = country
-    wavs.append(wav)
-
-wavs = pd.concat(wavs, axis=0).reset_index()
-
-# Keep only alleles with frequency over threshold
-threshold = 0.02
-common_alleles = wavs[wavs.allele_freq > threshold].allele.unique()
-wavs = wavs[wavs.allele.isin(common_alleles)]
-
-fig, ax = plt.subplots(2)
-
-sns.barplot(
-    data = wavs,
-    x = 'allele',
-    y = 'allele_freq',
-    hue = 'country',
-    ax=ax[0]
-)
-
-sns.barplot(
-    data = wavs,
-    x = 'allele',
-    y = 'wav',
-    hue = 'country',
-    ax=ax[1]
-)
-
-plt.xticks(rotation=90)
-plt.show()
-
-# Similarity of weighted allele freq and Diriclet mean
-x = max(max(wavs.allele_freq),max(wavs.wav))
-plt.plot((0,x), (0,x), 'k--')
-plt.scatter(
-    wavs.allele_freq,
-    wavs.wav
-)
-plt.show()
diff --git a/examples/dirichlet.py b/examples/dirichlet.py
deleted file mode 100644
index 17c2fa2..0000000
--- a/examples/dirichlet.py
+++ /dev/null
@@ -1,162 +0,0 @@
-"""
-Tests with the dirichlet distribution
-"""
-
-import matplotlib.pyplot as plt
-from matplotlib import cm
-import numpy as np
-from scipy.stats import dirichlet, beta
-import pandas as pd
-import code.HLAfreq as HLAfreq
-
-# define a Dirichlet Distributions with parameters alpha
-alpha = np.array([0.4, 5, 15])  # specify concentration parameters
-dd = dirichlet(alpha)
-
-dd.mean()
-dd.var()
-dd.entropy()
-
-dd.pdf([.6,.3,.1])
-
-# Make data for k=3.
-k1 = np.arange(0, 1, 0.05)
-k2 = np.arange(0, 1, 0.05)
-k1, k2 = np.meshgrid(k1, k2)
-k3 = 1 - k1 - k2
-k3[k3<0] = np.nan
-
-################################
-#                              #
-#   Compare pdf and log pdf    #
-#                              #
-################################
-alpha = (3,3,3)
-
-pdf = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        pdf[i,j] =  dirichlet(alpha).pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-logpdf = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        logpdf[i,j] =  dirichlet(alpha).logpdf([k1[i,j], k2[i,j], k3[i,j]])
-
-# Plot the surface.
-fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
-ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[0].set_title('PDF')
-ax[1].plot_surface(k1, k2, logpdf, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[1].set_title('Log pdf')
-plt.show()
-
-################################
-#                              #
-#       Update dirichlet       #
-#                              #
-################################
-
-# update a dirichlet distribution with new info
-# plot pdf before and after
-alpha = np.array([1,1,1])
-c = np.array([2,0,1])
-alpha2 = alpha+c
-
-pdf = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        pdf[i,j] =  dirichlet(alpha).pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-pdf2 = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        pdf2[i,j] =  dirichlet(alpha2).pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-# Plot the surface.
-fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
-ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[0].set_title(f'PDF {alpha}')
-ax[1].plot_surface(k1, k2, pdf2, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[1].set_title(f'PDF {alpha2}')
-plt.show()
-
-############################
-#                          #
-#   Study error ignored    #
-#                          #
-############################
-
-# Does not account for study level error
-alpha = np.array([1,1,1])
-# Two studies in agreement
-agree = alpha + np.array([3,3,0]) + np.array([3,3,0])
-#Two studies disagreeing
-disagree = alpha + np.array([6,0,0]) + np.array([0,6,0])
-
-all(agree == disagree)
-
-pdf = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        pdf[i,j] =  dirichlet(agree).pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-pdf2 = np.zeros(k1.shape)
-for i in range(k1.shape[0]):
-    for j in range(k1.shape[1]):
-        pdf2[i,j] =  dirichlet(disagree).pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-# Plot the surface.
-fig, ax = plt.subplots(nrows=1, ncols=2, subplot_kw={"projection": "3d"})
-ax[0].plot_surface(k1, k2, pdf, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[0].set_title(f'PDF agree')
-ax[1].plot_surface(k1, k2, pdf2, cmap=cm.plasma,
-    linewidth=0, antialiased=False)
-ax[1].set_title(f'PDF disagree')
-plt.show()
-
-#############################
-#                           #
-#   Dirichlet allele freq   #
-#                           #
-#############################
-
-country = "Thailand"
-df = pd.read_csv("data/example/%s_raw.csv" %country)
-loci = "DPB1"
-dfa = df[df.loci == loci]
-caf = HLAfreq.combineAF(dfa)
-
-plt.scatter(
-    caf.wav,
-    caf.allele_freq
-)
-plt.show()
-
-plt.scatter(
-    caf.wav,
-    caf.wav-caf.allele_freq
-)
-plt.show()
-
-########################
-#                      #
-#   Central credible   #
-#   region from beta   #
-#                      #
-########################
-
-pline = np.linspace(0, 1, 1000)
-a,b = 2,5
-bd = beta(a,b)
-pdf = bd.pdf(pline)
-cl,cu = HLAfreq.betaCI(a,b)
-
-plt.plot(pline, pdf)
-plt.fill_between([cl,cu], [bd.pdf(cl), bd.pdf(cu)], alpha=0.5)
-plt.show()
diff --git a/examples/international_frequencies.py b/examples/international_frequencies.py
deleted file mode 100644
index 8597dad..0000000
--- a/examples/international_frequencies.py
+++ /dev/null
@@ -1,58 +0,0 @@
-"""
-Calculate International average allele frequencies
-using population estimates.
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-countries = [
-    'United+Kingdom',
-    'Thailand',
-    'Uganda'
-]
-population_sizes = {
-    'United+Kingdom': 67081234,
-    'Thailand': 66813717,
-    'Uganda': 42885900
-}
-
-# Get weighted average for each county
-wavs = []
-for country in countries:
-    # Load raw county data
-    AFtab = pd.read_csv("data/example/%s_raw.csv" %country)
-    AFtab = AFtab[AFtab.loci == "A"]
-    # Weighted average alleles
-    wav = HLAfreq.combineAF(AFtab)
-    # Add country to dataset
-    wav['country'] = country
-    wavs.append(wav)
-
-AFtab[AFtab.allele=="A*66:02"]
-AFtab[AFtab.allele=="A*66:03"]
-
-
-international = pd.concat(wavs, ignore_index=True)
-# Add population size to weight averages
-international['population_size'] = international.country.apply(lambda x: population_sizes[x])
-
-#International Weighted Average
-iwav = HLAfreq.combineAF(international, weights='population_size', datasetID='country')
-
-plt.scatter(
-    international.allele,
-    international.allele_freq,
-    c=[international.country.unique().tolist().index(x) for x in international.country],
-    s=international.population_size/10000000
-    )
-plt.scatter(
-    iwav.allele,
-    iwav.allele_freq,
-    c='black',
-    marker='x'
-)
-plt.xticks(rotation=90)
-plt.show()
diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
new file mode 100644
index 0000000..daac255
--- /dev/null
+++ b/examples/multi_country.ipynb
@@ -0,0 +1,551 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Combine multi-country HLA data\n",
+    "We can calculate the average allele frequency of multiple countries\n",
+    "by combining studies within countries and then between countries.\n",
+    "This second step is very similar except we set `datasetID` as the country\n",
+    "rather than the population which is the default.\n",
+    "\n",
+    "The estimates from different countries can be weighted by sample size or another supplied variable such as population size. Both are described below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import HLAfreq\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Download HLA data for each specified country"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "countries = ['Cameroon','Cape+Verde','Ghana','Guinea',\n",
+    "    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',\n",
+    "    'South+Africa','Uganda','Zimbabwe']\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "for country in countries:\n",
+    "    print(country)\n",
+    "    base_url = HLAfreq.makeURL(\n",
+    "        country, standard='s', locus=\"A\",\n",
+    "        resolution_pattern=\"bigger_equal_than\", resolution=2)\n",
+    "    aftab = HLAfreq.getAFdata(base_url)\n",
+    "    aftab.to_csv(\"../data/example/multi_country/%s_raw.csv\" %country, index=False)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Combine allele frequencies within country"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "population               loci\n",
+      "South Africa Natal Zulu  A       0.935\n",
+      "Name: allele_freq, dtype: float64\n",
+      "1 studies have total allele frequency < 0.95\n"
+     ]
+    }
+   ],
+   "source": [
+    "cafs = []\n",
+    "for country in countries:\n",
+    "    # Load raw county data\n",
+    "    aftab = pd.read_csv(\"../data/example/multi_country/%s_raw.csv\" %country)\n",
+    "    # Drop any incomplete studies\n",
+    "    aftab = HLAfreq.only_complete(aftab)\n",
+    "    # Ensure all alleles have the same resolution\n",
+    "    aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "    # Combine studies within country\n",
+    "    caf = HLAfreq.combineAF(aftab)\n",
+    "    # Add country name to dataset, this is used as `datasetID` going forward\n",
+    "    caf['country'] = country\n",
+    "    cafs.append(caf)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Combine all country data\n",
+    "Concatenate each single county dataset into a single country.\n",
+    "Combine allele frequencies, using the manually added `country` column as `datasetID`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cafs = pd.concat(cafs, ignore_index=True)\n",
+    "international = HLAfreq.combineAF(cafs, datasetID='country')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# View allele frequencies\n",
+    "Plot allele frequencies averaged across countries.\n",
+    "Filter to only alleles with >1% frequency after averaging."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot international averages as bar plot\n",
+    "mask = international.allele_freq > 0.01\n",
+    "international[mask].plot.barh('allele', 'allele_freq')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "mask2 = cafs.allele.isin(international.allele[mask])\n",
+    "# Plot national averages as grouped bar plot\n",
+    "cafs[mask2].pivot(index='allele', columns='country', values='allele_freq').plot.bar()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 88 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot international allele frequencies estimates and individual countries\n",
+    "# Without filtering\n",
+    "HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 24 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot specific alleles and zoom in on frequencies\n",
+    "# Select alleles to plot\n",
+    "hifreq = international[international.allele_freq > 0.01].allele\n",
+    "# Must be a list\n",
+    "hifreq = hifreq.tolist()\n",
+    "# Plot only selected alleles\n",
+    "HLAfreq.plotAFprob(\n",
+    "    international,\n",
+    "    cafs,\n",
+    "    datasetID='country',\n",
+    "    ncol=4,\n",
+    "    xmax=cafs.allele_freq.max(),\n",
+    "    alleles=hifreq)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From these plots we can clearly see that one country has much\n",
+    "higher frequencies of A\\*24:02, A\\*11:01, and A\\*34:01.\n",
+    "It is also clear that the international average allele\n",
+    "frequency for A\\*24:02 is being skewed by this country. We can view the\n",
+    "`cafs` dataset to see which country this is, Guinea.\n",
+    "\n",
+    "This method can\n",
+    "also be applied to individual countries to identify studies which\n",
+    "differ from the majority, possibly because it focuses on a specific\n",
+    "ethnic group."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>allele</th>\n",
+       "      <th>loci</th>\n",
+       "      <th>wav</th>\n",
+       "      <th>c</th>\n",
+       "      <th>sample_size</th>\n",
+       "      <th>alpha</th>\n",
+       "      <th>allele_freq</th>\n",
+       "      <th>country</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>383</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.004000</td>\n",
+       "      <td>1.8400</td>\n",
+       "      <td>230</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.005818</td>\n",
+       "      <td>Zimbabwe</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>262</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.005000</td>\n",
+       "      <td>1.6500</td>\n",
+       "      <td>165</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.007458</td>\n",
+       "      <td>Senegal</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>183</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.010700</td>\n",
+       "      <td>16.0280</td>\n",
+       "      <td>749</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.010936</td>\n",
+       "      <td>Kenya</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.010322</td>\n",
+       "      <td>5.9660</td>\n",
+       "      <td>289</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.011301</td>\n",
+       "      <td>Cameroon</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>136</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.020740</td>\n",
+       "      <td>7.9640</td>\n",
+       "      <td>192</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.021445</td>\n",
+       "      <td>Guinea-Bissau</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>342</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.025292</td>\n",
+       "      <td>16.9960</td>\n",
+       "      <td>336</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.024831</td>\n",
+       "      <td>Uganda</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>231</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.025449</td>\n",
+       "      <td>4.9880</td>\n",
+       "      <td>98</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.026148</td>\n",
+       "      <td>Sao+Tome+and+Principe</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.068500</td>\n",
+       "      <td>16.9880</td>\n",
+       "      <td>124</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.064939</td>\n",
+       "      <td>Cape+Verde</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>297</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.077965</td>\n",
+       "      <td>61.5924</td>\n",
+       "      <td>395</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.074961</td>\n",
+       "      <td>South+Africa</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>A*24:02</td>\n",
+       "      <td>A</td>\n",
+       "      <td>0.327856</td>\n",
+       "      <td>419.6560</td>\n",
+       "      <td>640</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.319246</td>\n",
+       "      <td>Guinea</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      allele loci       wav         c  sample_size  alpha  allele_freq  \\\n",
+       "383  A*24:02    A  0.004000    1.8400          230      1     0.005818   \n",
+       "262  A*24:02    A  0.005000    1.6500          165      1     0.007458   \n",
+       "183  A*24:02    A  0.010700   16.0280          749      1     0.010936   \n",
+       "11   A*24:02    A  0.010322    5.9660          289      1     0.011301   \n",
+       "136  A*24:02    A  0.020740    7.9640          192      1     0.021445   \n",
+       "342  A*24:02    A  0.025292   16.9960          336      1     0.024831   \n",
+       "231  A*24:02    A  0.025449    4.9880           98      1     0.026148   \n",
+       "45   A*24:02    A  0.068500   16.9880          124      1     0.064939   \n",
+       "297  A*24:02    A  0.077965   61.5924          395      1     0.074961   \n",
+       "99   A*24:02    A  0.327856  419.6560          640      1     0.319246   \n",
+       "\n",
+       "                   country  \n",
+       "383               Zimbabwe  \n",
+       "262                Senegal  \n",
+       "183                  Kenya  \n",
+       "11                Cameroon  \n",
+       "136          Guinea-Bissau  \n",
+       "342                 Uganda  \n",
+       "231  Sao+Tome+and+Principe  \n",
+       "45              Cape+Verde  \n",
+       "297           South+Africa  \n",
+       "99                  Guinea  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cafs[cafs.allele == \"A*24:02\"].sort_values('allele_freq')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Weighting countries by population size\n",
+    "When combining allele frequencies across studies, larger studies are given more weight. This is handled by the `weights` parameter. (Specifically the `weights` is multiplied by the allele frequency to calculate the \"concentration\" of the Dirichlet distribution before adding the prior). By default `weights` is double the sample size as each sample provides 2n due to diploidy. However, alternative `weights` can be specified. The interpretation of the column used for `weights` is that $n$\n",
+    "samples were observed with allele $x$.\n",
+    "\n",
+    "If estimating allele frequency for a region, it may be important to\n",
+    "account for the size of national populations. Below we calculate an\n",
+    "individual weight for each country. A county's populaion, as a proportion\n",
+    "of the sum of countries' populations, multiplied by the number of countries is\n",
+    "used as the weight for each individual in that country. This means that\n",
+    "individuals from large countries contibute more to the total sample but the total sample size is unchanged. Therefore, the uncertainty of estimates is still determined by the overall samplesize."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "population_sizes = {'Cameroon':24348251,\n",
+    "    'Cape+Verde':563198,\n",
+    "    'Ghana':30832019,\n",
+    "    'Guinea':12907395,\n",
+    "    'Guinea-Bissau':1646077,\n",
+    "    'Kenya':47564296,\n",
+    "    'Sao+Tome+and+Principe':214610,\n",
+    "    'Senegal':17223497,\n",
+    "    'South+Africa':60604992,\n",
+    "    'Uganda':42885900,\n",
+    "    'Zimbabwe':15178979\n",
+    "}\n",
+    "\n",
+    "country_data = pd.DataFrame(\n",
+    "    {'country':population_sizes.keys(),\n",
+    "    'population':population_sizes.values()}\n",
+    ")\n",
+    "\n",
+    "# What proportion of the regional population does each country account for\n",
+    "country_data['proportion'] = country_data.population/country_data.population.sum()\n",
+    "# How much will each individual in the country count towards the sample size?\n",
+    "country_data['individual_weight'] = country_data['proportion'] * len(country_data.country)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 24 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Add country data to Combined Allele Frequency data\n",
+    "cafs = pd.merge(cafs, country_data, how=\"left\", on='country')\n",
+    "# Sample size is multiplied by this individual weight and doubled\n",
+    "# this accounts for diploid samples from each individual\n",
+    "cafs['weighted_sample_size'] = cafs.sample_size * 2 * cafs.individual_weight\n",
+    "\n",
+    "# Calculate allele frequency, weighting each country by the column weighted_sample_szie\n",
+    "winternational = HLAfreq.combineAF(cafs, datasetID='country', weights='weighted_sample_size')\n",
+    "\n",
+    "hifreq = winternational[winternational.allele_freq > 0.01].allele\n",
+    "# Must be a list\n",
+    "hifreq = hifreq.tolist()\n",
+    "# Plot only selected alleles\n",
+    "HLAfreq.plotAFprob(\n",
+    "    winternational,\n",
+    "    cafs,\n",
+    "    datasetID='country',\n",
+    "    ncol=4,\n",
+    "    xmax=cafs.allele_freq.max(),\n",
+    "    alleles=hifreq)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.6 ('hlatest')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/multi_country.py b/examples/multi_country.py
deleted file mode 100644
index 9af2bbd..0000000
--- a/examples/multi_country.py
+++ /dev/null
@@ -1,156 +0,0 @@
-"""
-Calculate multi-country average
-
-We can calculate the average allele frequency of multiple countries
-by combining studies within countries and then between countries.
-This second step is very similar except we set `datasetID` as the country
-rather than the population which is the default. 
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-
-countries = ['Cameroon','Cape+Verde','Ghana','Guinea',
-    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',
-    'South+Africa','Uganda','Zimbabwe']
-
-# Download HLA allele frequencies
-for country in countries:
-    print(country)
-    base_url = HLAfreq.makeURL(
-        country, standard='s', locus="A",
-        resolution_pattern="bigger_equal_than", resolution=2)
-    aftab = HLAfreq.getAFdata(base_url)
-    aftab.to_csv("data/example/multi_country/%s_raw.csv" %country, index=False)
-
-# Combine alleles frequencies within country
-cafs = []
-for country in countries:
-    # Load raw county data
-    aftab = pd.read_csv("data/example/multi_country/%s_raw.csv" %country)
-    # Drop any incomplete studies
-    aftab = HLAfreq.only_complete(aftab)
-    # Ensure all alleles have the same resolution
-    aftab = HLAfreq.decrease_resolution(aftab, 2)
-    # Combine studies within country
-    caf = HLAfreq.combineAF(aftab)
-    # Add country name to dataset, this is used as `datasetID` going forward
-    caf['country'] = country
-    cafs.append(caf)
-
-# Concatenate all combined single country allele frequency data
-# into a single dataframe
-cafs = pd.concat(cafs, ignore_index=True)
-# Combine allele frequency data of all countries
-international = HLAfreq.combineAF(cafs, datasetID='country')
-
-# Plot international averages as bar plot
-international.plot.barh('allele', 'allele_freq')
-plt.show()
-
-# Plot national averages as grouped bar plot
-cafs.pivot(index='allele', columns='country', values='allele_freq').plot.bar()
-plt.show()
-
-# Plot international allele frequencies estimates and individual countries
-HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)
-
-# Plot specific alleles and zoom in on frequencies
-# Select alleles to plot
-hifreq = international[international.allele_freq > 0.01].allele
-# Must be a list
-hifreq = hifreq.tolist()
-# Plot only selected alleles
-HLAfreq.plotAFprob(
-    international,
-    cafs,
-    datasetID='country',
-    ncol=4,
-    xmax=cafs.allele_freq.max(),
-    alleles=hifreq)
-
-"""
-From these plots we can clearly see that one country has much
-higher frequencies of A*24:02, A*11:01, and A*34:01.
-It is also clear that the international average allele
-frequency for A*24:02 is being skewed by this country. We can view the
-`cafs` dataset to see which country this is, Guinea.
-
-This method can
-also be applied to individual countries to identify studies which
-differ from the majority, possibly because it focuses on a specific
-ethnic group.
-"""
-
-cafs[cafs.allele == "A*24:02"].sort_values('allele_freq')
-
-# How to weight countries differently?
-
-"""
-When calculating the average allele frequency the "concentration"
-parameter of the Dirichlet distribution is calculated as `weights`
-multiplied by the dataset allele frequency (where dataset is usually
-a single study but can be a country etc, this is what `datasetID`
-refers to). By default `weights` is double the sample size as each
-sample provides 2n due to diploidy.
-
-If estimating allele frequency for a region, it may be important to
-account for the size of national populations. Below we calculate an
-individual weight for each country, individuals from large countries
-contibute more to the total sample but the total sample size is
-unchanged. A county's populaion, as a proportion of the sum of
-countries' populations, multiplied by the number of countries is
-used as the weight for each individual in that country.
-"""
-
-population_sizes = {'Cameroon':24348251,
-    'Cape+Verde':563198,
-    'Ghana':30832019,
-    'Guinea':12907395,
-    'Guinea-Bissau':1646077,
-    'Kenya':47564296,
-    'Sao+Tome+and+Principe':214610,
-    'Senegal':17223497,
-    'South+Africa':60604992,
-    'Uganda':42885900,
-    'Zimbabwe':15178979
-}
-
-country_data = pd.DataFrame(
-    {'country':population_sizes.keys(),
-    'population':population_sizes.values()}
-)
-
-# What proportion of the regional population does each country account for
-country_data['proportion'] = country_data.population/country_data.population.sum()
-# How much will each individual in the country count towards the sample size?
-country_data['individual_weight'] = country_data['proportion'] * len(country_data.country)
-# Add country data to Combined Allele Frequency data
-cafs = pd.merge(cafs, country_data, how="left", on='country')
-# Sample size is multiplied by this individual weight and doubled
-# this accounts for diploid samples from each individual
-cafs['weighted_sample_size'] = cafs.sample_size * 2 * cafs.individual_weight
-
-# Combine allele frequency data of all countries
-# Using the custom column 'weighted_sample_size'
-# The interpretation of the column used for `weights` is that n
-# samples were observed with allele x. If unspecified this defaults
-# to double the sample size (to accound for diploid samples from each
-# individual)
-winternational = HLAfreq.combineAF(cafs, datasetID='country', weights='weighted_sample_size')
-
-HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)
-
-hifreq = winternational[winternational.allele_freq > 0.01].allele
-# Must be a list
-hifreq = hifreq.tolist()
-# Plot only selected alleles
-HLAfreq.plotAFprob(
-    winternational,
-    cafs,
-    datasetID='country',
-    ncol=4,
-    xmax=cafs.allele_freq.max(),
-    alleles=hifreq)
diff --git a/examples/entropy_map.py b/examples/paper/entropy_map.py
similarity index 100%
rename from examples/entropy_map.py
rename to examples/paper/entropy_map.py
diff --git a/examples/globalPCA.py b/examples/paper/globalPCA.py
similarity index 100%
rename from examples/globalPCA.py
rename to examples/paper/globalPCA.py
diff --git a/examples/globalPCA2.py b/examples/paper/globalPCA2.py
similarity index 100%
rename from examples/globalPCA2.py
rename to examples/paper/globalPCA2.py
diff --git a/examples/select_hla_panel.py b/examples/paper/select_hla_panel.py
similarity index 100%
rename from examples/select_hla_panel.py
rename to examples/paper/select_hla_panel.py
diff --git a/examples/population_coverage.py b/examples/population_coverage.py
deleted file mode 100644
index 6d5dc86..0000000
--- a/examples/population_coverage.py
+++ /dev/null
@@ -1,48 +0,0 @@
-"""
-How much of the population is covered by the top n alleles?
-What is the population coverage of different supertypes?
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import matplotlib.pyplot as plt
-import seaborn as sns
-
-# Which supertypes are represented
-super1 = pd.read_csv("data/HLA1supertypes_Sidney2008.csv")
-super1.allele = super1.allele.apply(lambda x: x[:4]+':'+x[4:])
-
-AFtab = pd.read_csv("data/example/Uganda_raw.csv")
-AFtab =  AFtab[AFtab.loci=="A"]
-# Weighted average alleles
-wav = HLAfreq.combineAF(AFtab)
-# Add HLA1 supertypes
-wav = pd.merge(wav, super1)
-wava = wav[wav.loci == "A"].sort_values('allele_freq', ascending=False, ignore_index = True)
-
-# Plot allele frequencies coloured by supertype
-sns.barplot(
-    y=wava.allele,
-    x=wava.allele_freq,
-    hue=wava.supertype,
-    dodge=False
-    )
-plt.show()
-
-plt.plot(wava.allele_freq.cumsum(), label="Cumulative AF")
-plt.plot(wava.allele_freq.cumsum().apply(HLAfreq.population_coverage), label="Cumulative coverage")
-plt.axhline(y=1, color="black", linestyle="--")
-plt.legend()
-plt.show()
-
-for supertype in wava.supertype.unique():
-    print(supertype)
-    supertypedf = wava[wava.supertype == supertype].reset_index()
-    plt.plot(supertypedf.allele_freq.cumsum().apply(HLAfreq.population_coverage), label=supertype)
-plt.legend()
-plt.show()
-
-mask = wava.allele_freq.cumsum() > 0.95
-wava[~mask]
-wava[~mask].supertype.unique()
-
diff --git a/examples/single_country.ipynb b/examples/single_country.ipynb
new file mode 100644
index 0000000..fc0cc12
--- /dev/null
+++ b/examples/single_country.ipynb
@@ -0,0 +1,283 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Single country HLA frequency"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import HLAfreq\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Download AF data\n",
+    "Pick a country to download AF data for. Spaces in country names\n",
+    "are replaced with '+', if in doubt use the allelefrequencies.net\n",
+    "website to search for a country and then check the url for the\n",
+    "appropriate spelling."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5 pages of results\n",
+      "Download complete\n"
+     ]
+    }
+   ],
+   "source": [
+    "country = \"Thailand\"\n",
+    "\n",
+    "base_url = HLAfreq.makeURL(country)\n",
+    "aftab = HLAfreq.getAFdata(base_url)\n",
+    "aftab.to_csv(\"../data/example/%s_raw.csv\" %country, index=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Check completeness\n",
+    "We can't yet combine allele frequency estimates because not all\n",
+    "studies sum to an allele frequency of 1. In this case it is because some studies\n",
+    "reported allele frequencies at 1 field of resolution and we only downloaded\n",
+    "alleles with >2.\n",
+    "\n",
+    "To drop incomplete studies use `only_complete()` which will print out the studies\n",
+    "that were incomplete. To view incomplete studies without dropping them use\n",
+    "`incomplete_studies()` before dropping studies."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "population          loci\n",
+      "Thailand Northeast  A       0.317\n",
+      "                    B       0.259\n",
+      "                    C       0.245\n",
+      "                    DRB1    0.835\n",
+      "Thailand pop 2      DQA1    0.742\n",
+      "Name: allele_freq, dtype: float64\n",
+      "5 studies have total allele frequency < 0.95\n"
+     ]
+    }
+   ],
+   "source": [
+    "aftab = HLAfreq.only_complete(aftab)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Check resolution\n",
+    "Because allele frequency estimates can only be combined if the\n",
+    "allele name is identical, all alleles in a set of studies must have\n",
+    "the same resolution i.e. A*01 is 2 digit resolution (or 1 field) and\n",
+    "A*01:01 is 4 digit (or 2 field). These cannot be combined as we\n",
+    "cannot tell whether A*01 is A*01:01, A*01:02 etc. For the same reason\n",
+    "we can decrease the resolution of an allele but we cannot\n",
+    "increase it.\n",
+    "\n",
+    "Before combining allele frequency estimates we may have to reduce the\n",
+    "resolution of some alleles. `check_resolution()` will report if all\n",
+    "alleles are at the same resolution and the number of estimates at\n",
+    "each resolution.\n",
+    "\n",
+    "`decrease_resolution()` reduces the resolution of all alleles to a\n",
+    "specified level so they can be combined."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2    352\n",
+      "3     21\n",
+      "Name: allele, dtype: int64\n",
+      "Multiple resolutions in AFtab. Fix with decrease_resolution()\n"
+     ]
+    }
+   ],
+   "source": [
+    "HLAfreq.check_resolution(aftab)\n",
+    "aftab = HLAfreq.decrease_resolution(aftab, 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Combine AF from studies\n",
+    "We can only combine allele frequency estimates for a single loci\n",
+    "at a time. So we filter the data to a single loci and then combine\n",
+    "allele frequency estimates using `combineAF()`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "afloc = aftab[aftab.loci==\"DRB1\"]\n",
+    "caf = HLAfreq.combineAF(afloc)\n",
+    "\n",
+    "# Calculate credible interval\n",
+    "caf[['cl','cu']] = HLAfreq.AFci(caf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "caf.plot.barh('allele', 'allele_freq')\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can view the probability density function of the allele frequency estimates with `plotAFprob()`. By passing the uncombined allele frequency data we can see the individual study estimates.\n",
+    "\n",
+    "The dashed line is the Dirichlet mean, and the dotted lines are the Dirichlet credible intervals. Note that these confidence intervals ignore study level variance so can be very tight with large sample sizes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "HLAfreq.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Population coverage\n",
+    "We can calculate and plot the cumulative population coverage of these alleles.\n",
+    "This is calculated with `population_coverage()` which assumes Hardy-Weinberg equilibrium to calculate the population coverage as $p^2+2pq$ where $q=1-p$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)\n",
+    "\n",
+    "plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(HLAfreq.population_coverage))\n",
+    "plt.plot(caf.allele_freq.cumsum().apply(HLAfreq.population_coverage), label=\"Cumulative coverage\")\n",
+    "plt.grid(True)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.6 ('hlatest')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/single_country.py b/examples/single_country.py
deleted file mode 100644
index 13eff39..0000000
--- a/examples/single_country.py
+++ /dev/null
@@ -1,120 +0,0 @@
-"""
-Single country
-
-Calculate average
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-
-#########################
-#                       #
-#   Download AF data    #
-#                       #
-#########################
-"""
-Pick a country to download AF data for. Spaces in country names
-are replaced with '+', if in doubt use the allelefrequencies.net
-website to search for a country and then check the url for the
-appropriate spelling.
-"""
-
-country = "Thailand"
-
-base_url = HLAfreq.makeURL(country)
-aftab = HLAfreq.getAFdata(base_url)
-aftab.to_csv("data/example/%s_raw.csv" %country, index=False)
-#aftab = pd.read_csv("data/example/%s_raw.csv" %country)
-
-#########################
-#                       #
-#   Check completeness  #
-#                       #
-#########################
-"""
-We can't yet combine allele frequency estimates because not all
-studies sum to an allele frequency of 1. In this case it is because some studies
-reported allele frequencies at 1 field of resolution and we only downloaded
-alleles with >2.
-
-To drop incomplete studies use `only_complete()` which will print out the studies
-that were incomplete. To view incomplete studies without dropping them use
-`incomplete_studies()` before dropping studies.
-"""
-
-# Drop any incomplete studies
-aftab = HLAfreq.only_complete(aftab)
-
-#########################
-#                       #
-#   Check resolution    #
-#                       #
-#########################
-"""
-Because allele frequency estimates can only be combined if the
-allele name is identical, all alleles in a set of studies must have
-the same resolution i.e. A*01 is 2 digit resolution (or 1 field) and
-A*01:01 is 4 digit (or 2 field). These cannot be combined as we
-cannot tell whether A*01 is A*01:01, A*01:02 etc. For the same reason
-we can decrease the resolution of an allele but we cannot
-increase it.
-
-Before combining allele frequency estimates we may have to reduce the
-resolution of some alleles. `check_resolution()` will report if all
-alleles are at the same resolution and the number of estimates at
-each resolution.
-
-`decrease_resolution()` reduces the resolution of all alleles to a
-specified level so they can be combined.
-"""
-
-HLAfreq.check_resolution(aftab)
-
-aftab = HLAfreq.decrease_resolution(aftab, 2)
-
-
-#########################
-#                       #
-#     Combine AFs       #
-#                       #
-#########################
-
-"""
-We can only combine allele frequency estimates for a single loci
-at a time. So we filter the data to a single loci and then combine
-allele frequency estimates using `combineAF()`
-"""
-
-HLAfreq.combineAF(aftab)
-
-afloc = aftab[aftab.loci=="DRB1"]
-caf = HLAfreq.combineAF(afloc)
-
-# Calculate credible interval
-caf[['cl','cu']] = HLAfreq.AFci(caf)
-
-caf.plot.barh('allele', 'allele_freq')
-plt.tight_layout()
-plt.show()
-
-HLAfreq.plotAFprob(caf, afloc)
-HLAfreq.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])
-
-#############################
-#                           #
-#    Population coverage    #
-#                           #
-#############################
-
-# Sort by allele frequency
-caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
-
-plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(HLAfreq.population_coverage))
-plt.plot(caf.allele_freq.cumsum().apply(HLAfreq.population_coverage), label="Cumulative coverage")
-plt.grid(True)
-plt.xticks(rotation=90)
-plt.legend()
-plt.tight_layout()
-plt.show()
diff --git a/examples/visualise_high_k_dirichlet.py b/examples/visualise_high_k_dirichlet.py
deleted file mode 100644
index ba9b999..0000000
--- a/examples/visualise_high_k_dirichlet.py
+++ /dev/null
@@ -1,98 +0,0 @@
-"""
-Visualise high k Dirichlet
-"""
-
-import matplotlib.pyplot as plt
-from matplotlib import cm
-import numpy as np
-from scipy.stats import dirichlet, beta
-import pandas as pd
-import code.HLAfreq as HLAfreq
-
-#####################
-#                   #
-#   Define alpha    #
-#                   #
-#####################
-
-# Load allele frequency data
-AFtab = pd.read_csv(f"data/example/outlier_raw.csv")
-# Reduce resolution to 2 fields and collapse alleles
-AFtab = HLAfreq.decrease_resolution(AFtab, 2)
-# Combined allle frequency
-# noncomplete = HLAfreq.incomplete_studies(AFtab)
-# complete_mask = AFtab.apply(lambda x: (x.population, x.loci) not in noncomplete.index, axis=1)
-# AFtab = AFtab[complete_mask]
-caf = HLAfreq.combineAF(AFtab)
-# Recreate the Dirichlet distribution
-naivealpha = HLAfreq.default_prior(len(caf.allele))
-
-# Dirichlet distribution concentration parameters 
-# based on allele frequency data
-alpha = naivealpha + caf.c
-
-######################
-#                    #
-# View k=3 Dirichlet #
-#                    #
-######################
-if len(alpha) == 3:
-    dd = dirichlet(alpha)
-    # Make data for k=3.
-    k1 = np.arange(0, 1, 0.05)
-    k2 = np.arange(0, 1, 0.05)
-    k1, k2 = np.meshgrid(k1, k2)
-    k3 = 1 - k1 - k2
-    k3[k3<0] = np.nan
-
-    pdf = np.zeros(k1.shape)
-    for i in range(k1.shape[0]):
-        for j in range(k1.shape[1]):
-            pdf[i,j] =  dd.pdf([k1[i,j], k2[i,j], k3[i,j]])
-
-    # Plot the surface.
-    fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
-    ax.plot_surface(k1, k2, pdf, cmap=cm.plasma,
-        linewidth=0, antialiased=False)
-    ax.set_title('PDF')
-    plt.show()
-else:
-    print( "Surface plot only works with k==3")
-
-######################
-#                    #
-#   View Dirichlet   #
-#       as beta      #
-#                    #
-######################
-
-# View pdf only
-HLAfreq.plotAFprob(concentration=alpha, ci=0)
-# View estimated AF
-HLAfreq.plotAFprob(caf)
-# View estimated AF with individual studies
-HLAfreq.plotAFprob(caf, AFtab)
-# View subset of alleles
-HLAfreq.plotAFprob(caf, AFtab, alleles=["DQB1*03:01","DQB1*05:01","DQB1*05:02"])
-
-# CI may be misleading
-
-# Use cafs from multi_country.py
-x = cafs[cafs.allele == 'A*23:01']
-
-clist = 1 + x.allele_freq * x.sample_size
-long_c = []
-for c in clist:
-    long_c.append(c)
-    long_c.append(0)
-HLAfreq.plotAFprob(concentration=pd.Series(long_c), ncol=2)
-
-pline = np.linspace(0,1,500)
-fig, ax = plt.subplots()
-for a,b in zip(x.c, x.sample_size):
-    bd = beta(a,b)
-    pdf = [bd.pdf(p) for p in pline]
-    ax.plot(pline, pdf)
-    ax.set_xlim(0,0.4)
-plt.show()
-plt.subplots()
\ No newline at end of file
diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
new file mode 100644
index 0000000..d44be6f
--- /dev/null
+++ b/examples/working_with_priors.ipynb
@@ -0,0 +1,305 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# working with priors\n",
+    "\n",
+    "In Bayesian statistics a prior is used to specify prior belief.\n",
+    "Working with priors to improve estimates of undersampled populations.\n",
+    "Priors can be based on other related, populations, or specified by\n",
+    "hand."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import HLAfreq\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Venezuela is one of the least sampled countries on allelefrequency.net\n",
+    "We found only 55 gold standard samples for HLA A."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 pages of results\n",
+      "Download complete\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download data for Venezuela\n",
+    "country = \"Venezuela\"\n",
+    "base_url = HLAfreq.makeURL(country, locus=\"A\", standard=\"g\",)\n",
+    "venezuelaAF = HLAfreq.getAFdata(base_url)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "venezuelaAF = HLAfreq.only_complete(venezuelaAF)\n",
+    "venezuelaAF = HLAfreq.decrease_resolution(venezuelaAF, 2)\n",
+    "cafV = HLAfreq.combineAF(venezuelaAF)\n",
+    "cafV['study'] =  'Venezuela'\n",
+    "HLAfreq.plotAFprob(cafV, venezuelaAF)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can specify priors manually. For simplicity we use\n",
+    "a prior of 1 for each observed allele but this could be any\n",
+    "$n$ length list of positive real numbers.\n",
+    "\n",
+    "The interpretation of the prior is that $n$ copies were found for each\n",
+    "allele. Note that `combineAF()` uses the first value in the prior for\n",
+    "the first allele alphabetically and so on.\n",
+    "\n",
+    "By viewing the posterior we can see that the prior has moved the\n",
+    "estimate away from the observed study."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "manual_prior = [10, 1, 1, 1, 1]\n",
+    "\n",
+    "# View prior distribution\n",
+    "HLAfreq.plotAFprob(concentration=manual_prior)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "# Combine Allele Freq of study with Manual Prior\n",
+    "cafMP = HLAfreq.combineAF(venezuelaAF, alpha=manual_prior)\n",
+    "\n",
+    "# View posterior distribution\n",
+    "HLAfreq.plotAFprob(cafMP, AFtab=venezuelaAF)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Alternatively we can use another population as our prior.\n",
+    "For example we will use data for Colombia, a neighbouring country\n",
+    "with many more samples for HLA A.\n",
+    "\n",
+    "When using other studies as a prior we can downweight their samples\n",
+    "so they count less than the samples in our actual population.\n",
+    "The amount of downweighting depends on how relevent you believe the\n",
+    "other study is. Here we arbitrarily downweight by a factor 0.01 as\n",
+    "an example so that the Venezuela data is not drowned out by the Colombia data.\n",
+    "\n",
+    "When recalculating the prior to plot, sample size is doubled\n",
+    "as each person in the study is diploid and so provides two alleles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 pages of results\n",
+      "Download complete\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download data for Colombia\n",
+    "country = \"Colombia\"\n",
+    "base_url = HLAfreq.makeURL(country, locus=\"A\", standard=\"g\",)\n",
+    "colombiaAF = HLAfreq.getAFdata(base_url)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Combine Colombia studies into a national average\n",
+    "colombiaAF = HLAfreq.only_complete(colombiaAF)\n",
+    "colombiaAF = HLAfreq.decrease_resolution(colombiaAF, 2)\n",
+    "cafC = HLAfreq.combineAF(colombiaAF)\n",
+    "cafC['population'] =  'Colombia'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 60 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Create a prior from Colombia\n",
+    "study_prior = cafC.copy()\n",
+    "study_prior.sample_size = study_prior.sample_size * 0.01\n",
+    "\n",
+    "# View prior\n",
+    "HLAfreq.plotAFprob(\n",
+    "    concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 60 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Combine Allele Frequency with Study Prior\n",
+    "cafSP = HLAfreq.combineAF(\n",
+    "    pd.concat([venezuelaAF, study_prior], join=\"inner\")\n",
+    "    )\n",
+    "\n",
+    "# View posterior of all alleles\n",
+    "HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join=\"inner\"))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# View posterior of just alleles observed in Venezuela\n",
+    "HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join=\"inner\"), alleles=venezuelaAF.allele.tolist())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.6 ('hlatest')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/working_with_priors.py b/examples/working_with_priors.py
deleted file mode 100644
index c5223aa..0000000
--- a/examples/working_with_priors.py
+++ /dev/null
@@ -1,84 +0,0 @@
-"""
-Working with priors to improve estimates of undersampled populations.
-Priors can be based on other related, populations, or specified by
-hand.
-"""
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-
-"""
-Venezuela is one of the least sampled countries on allelefrequency.net
-We found only 55 gold standard samples for HLA A.
-"""
-
-venezuelaAF = pd.read_csv("data/example/globalPCA/Venezuela_raw.csv")
-venezuelaAF = HLAfreq.only_complete(venezuelaAF)
-venezuelaAF = HLAfreq.decrease_resolution(venezuelaAF, 2)
-cafV = HLAfreq.combineAF(venezuelaAF)
-cafV['study'] =  'Venezuela'
-
-HLAfreq.plotAFprob(cafV, venezuelaAF)
-
-"""
-We can specify priors manually. For simplicity we use
-a prior of 1 for each observed allele but this could be any
-n length list of positive real numbers.
-
-The interpretation of the prior is that n copies were found for each
-allele. Note that `combineAF()` uses the first value in the prior for
-the first allele alphabetically and so on.
-
-By viewing the posterior we can see that the prior has moved the
-estimate away from the observed study.
-"""
-manual_prior = [10, 1, 1, 1, 1]
-
-# View prior distribution
-HLAfreq.plotAFprob(concentration=manual_prior)
-
-# Combine Allele Freq of study with Manual Prior
-cafMP = HLAfreq.combineAF(venezuelaAF, alpha=manual_prior)
-
-# View posterior distribution
-HLAfreq.plotAFprob(cafMP, AFtab=venezuelaAF)
-
-"""
-Alternatively we can use another population as our prior.
-For example we will use data for Colombia, a neighbouring country
-with many more samples for HLA A.
-
-When using other studies as a prior we can downweight their samples
-so they count less than the samples in our actual population.
-The amount of downweighting depends on how relevent you believe the
-other study is. Here we use downweight by a factor 0.01 so that the
-Venezuela data is not drowned out by the Colombia data.
-
-When recalculating the prior to plot, sample size is doubled
-as each person in the study is diploid and so provides two alleles.
-"""
-
-colombiaAF = pd.read_csv("data/example/globalPCA/Colombia_raw.csv")
-colombiaAF = HLAfreq.only_complete(colombiaAF)
-colombiaAF = HLAfreq.decrease_resolution(colombiaAF, 2)
-cafC = HLAfreq.combineAF(colombiaAF)
-cafC['population'] =  'Colombia'
-
-study_prior = cafC.copy()
-study_prior.sample_size = study_prior.sample_size * 0.01
-
-# View prior
-HLAfreq.plotAFprob(
-    concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()
-)
-
-# Combine Allele Frequency with Study Prior
-cafSP = HLAfreq.combineAF(
-    pd.concat([venezuelaAF, study_prior], join="inner")
-    )
-
-# View posterior
-HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"))
-HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join="inner"), alleles=venezuelaAF.allele.tolist())
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index 2630395..8ec355b 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -12,47 +12,32 @@ Description-Content-Type: text/markdown
 
 # HLAfreq
 
-The aim of this tool is to be able to estimate the HLA allele
+`HLAfreq` allows you to estimate the HLA allele
 frequencies at large multi population scale, e.g. combine data from
 several studies within a country or combine countries.
-Allele frequency data from
+
+Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
-This gives frequencies by population, which can be combined across
-studies. Estimates are combined by modelling allele frequency as a 
+
+## Details
+Estimates are combined by modelling allele frequency as a 
 Dirichlet distribution which defines the probability of drawing each
-allele. When combining studies are weighted by 2 x sample size by
+allele. When combining studies their estimates are weighted as 2x sample size by
 default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-```
-import sys
-sys.path.append("/home/dwells/work/tools/scrapeAF/code")
-import scrapeAF
-```
-
-When selecting alleles to represent a population, all supertypes
-should be represented.
-
-When combining estimates of allele frequency larger samples should
-weigh more heavily. However, when combining estiamtes that disagree
-the uncertainty on the estimate should be larger than when combining
-equivalent samples that agree.
-
-When combining studies we must weight averages by sample size but
-when combining countries are we not better to weight by national population?
-Should sample size also have an effect?
-
-IEDB provide reference sets of HLA alleles designed to cover the
-majority of the "general population". However, all populations are
-not likely to be equally well covered by them. Using population
-specific allele frequencies we should be able to select more
-appropriate HLA sets. However, allele frequency is not the only
-determinent when selecting a pannel of alleles. The pannel must
-also contain representatives of commonly shared binding specificities
-(i.e., supertypes).
-
-# Dependencies
-scrapeAF
-umap
-maps
+A note on credible intervals...
+
+When selecting a panel of HLA alleles to represent a population,
+allele frequency is not the only thing to consider. Depending on
+the purpose of the panel, you should include a range of loci and
+supertypes (groups alleles sharing binding specificies).
+
+## Install
+
+## Minimal example
+
+## Detailed examples
+
+## Citation

From 74c00989a0a60a402de0268fe085f7fbd4eb21e4 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 13:31:01 +0100
Subject: [PATCH 061/192] Clarify descriptions in examples

---
 examples/multi_country.ipynb       | 2 +-
 examples/working_with_priors.ipynb | 3 +--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index daac255..a9e3759 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -433,7 +433,7 @@
    "metadata": {},
    "source": [
     "## Weighting countries by population size\n",
-    "When combining allele frequencies across studies, larger studies are given more weight. This is handled by the `weights` parameter. (Specifically the `weights` is multiplied by the allele frequency to calculate the \"concentration\" of the Dirichlet distribution before adding the prior). By default `weights` is double the sample size as each sample provides 2n due to diploidy. However, alternative `weights` can be specified. The interpretation of the column used for `weights` is that $n$\n",
+    "When combining allele frequencies across studies, larger studies are given more weight. This is handled by the `weights` parameter. (Specifically the `weights` is multiplied by the allele frequency to calculate the \"concentration\" of the Dirichlet distribution before adding the prior). By default `weights` is double the sample size as two alleles are measured for person sampled due to diploidy. However, alternative `weights` can be specified. The interpretation of the column used for `weights` is that $n$\n",
     "samples were observed with allele $x$.\n",
     "\n",
     "If estimating allele frequency for a region, it may be important to\n",
diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
index d44be6f..7842450 100644
--- a/examples/working_with_priors.ipynb
+++ b/examples/working_with_priors.ipynb
@@ -81,8 +81,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can specify priors manually. For simplicity we use\n",
-    "a prior of 1 for each observed allele but this could be any\n",
+    "We can specify priors manually, this could be any\n",
     "$n$ length list of positive real numbers.\n",
     "\n",
     "The interpretation of the prior is that $n$ copies were found for each\n",

From ee4680ec7820f451fabbe4ce24dc9d85bab83dfc Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:10:08 +0100
Subject: [PATCH 062/192] Add pdoc3 docs

---
 docs/HLAfreq/HLAfreq.html      | 1771 ++++++++++++++++++++++++++++++++
 docs/HLAfreq/HLAfreq_data.html |  109 ++
 docs/HLAfreq/index.html        |   71 ++
 3 files changed, 1951 insertions(+)
 create mode 100644 docs/HLAfreq/HLAfreq.html
 create mode 100644 docs/HLAfreq/HLAfreq_data.html
 create mode 100644 docs/HLAfreq/index.html

diff --git a/docs/HLAfreq/HLAfreq.html b/docs/HLAfreq/HLAfreq.html
new file mode 100644
index 0000000..dbeb4da
--- /dev/null
+++ b/docs/HLAfreq/HLAfreq.html
@@ -0,0 +1,1771 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
+<meta name="generator" content="pdoc 0.8.1" />
+<title>HLAfreq.HLAfreq API documentation</title>
+<meta name="description" content="HLAfreq …" />
+<link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
+<link href='https://cdnjs.cloudflare.com/ajax/libs/10up-sanitize.css/8.0.0/sanitize.min.css' rel='stylesheet'>
+<link href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/github.min.css" rel="stylesheet">
+<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}#sidebar > *:last-child{margin-bottom:2cm}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{margin-top:.6em;font-weight:bold}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
+<style media="screen and (min-width: 700px)">@media screen and (min-width:700px){#sidebar{width:30%;height:100vh;overflow:auto;position:sticky;top:0}#content{width:70%;max-width:100ch;padding:3em 4em;border-left:1px solid #ddd}pre code{font-size:1em}.item .name{font-size:1em}main{display:flex;flex-direction:row-reverse;justify-content:flex-end}.toc ul ul,#index ul{padding-left:1.5em}.toc > ul > li{margin-top:.5em}}</style>
+<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
+</head>
+<body>
+<main>
+<article id="content">
+<header>
+<h1 class="title">Module <code>HLAfreq.HLAfreq</code></h1>
+</header>
+<section id="section-intro">
+<p>HLAfreq</p>
+<p>Download allele frequency data from
+<a href="www.allelefrequencies.net">allelefrequencies.net</a>. Allele
+frequencies from different populations can be combined to
+estimate HLA frequencies of countries or other regions such as
+global HLA frequencies.</p>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">&#34;&#34;&#34;
+HLAfreq
+
+Download allele frequency data from
+[allelefrequencies.net](www.allelefrequencies.net). Allele
+frequencies from different populations can be combined to
+estimate HLA frequencies of countries or other regions such as
+global HLA frequencies.
+&#34;&#34;&#34;
+
+from bs4 import BeautifulSoup
+import requests
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import math
+from scipy.stats import dirichlet, beta
+import logging
+import warnings
+
+def makeURL(
+        country=&#34;&#34;,
+        standard=&#39;s&#39;,
+        locus=&#34;&#34;,
+        resolution_pattern=&#34;bigger_equal_than&#34;,
+        resolution=2,
+        region=&#34;&#34;,
+        ethnic=&#34;&#34;,
+        study_type=&#34;&#34;,
+        dataset_source=&#34;&#34;,
+        sample_year=&#34;&#34;,
+        sample_year_pattern=&#34;&#34;,
+        sample_size=&#34;&#34;,
+        sample_size_pattern=&#34;&#34;
+    ):
+    &#34;&#34;&#34;Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+    Args:
+        country (str, optional): Country name to retrieve records from. Defaults to &#34;&#34;.
+        standard (str, optional): Filter study quality standard to this or higher. {&#39;g&#39;, &#39;s&#39;, &#39;a&#39;} Gold, silver, all. Defaults to &#39;s&#39;.
+        locus (str, optional): The locus to return allele data for. Defaults to &#34;&#34;.
+        resolution_pattern (str, optional): Resolution comparitor {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Filter created using `resolution` and `resolution_pattern`. Defaults to &#34;bigger_equal_than&#34;.
+        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
+        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
+        ethnic (str, optional): Filter to ethnicity. {&#34;Amerindian&#34;, &#34;Black&#34;, &#34;Caucasian&#34;, ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
+        study_type (str, optional): Type of study. {&#34;Anthropology&#34;, &#34;Blood+Donor&#34;, &#34;Bone+Marrow+Registry&#34;, &#34;Controls+for+Disease+Study&#34;, &#34;Disease+Study+Patients&#34;, &#34;Other&#34;, &#34;Solid+Organd+Unrelated+Donors&#34;, &#34;Stem+cell+donors&#34;}. Defaults to &#34;&#34;.
+        dataset_source (str, optional): Source of data. {&#34;Literature&#34;, &#34;Proceedings+of+IHWs&#34;, &#34;Unpublished&#34;}. Defaults to &#34;&#34;.
+        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to &#34;&#34;.
+        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
+        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to &#34;&#34;.
+        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
+
+    Returns:
+        str: URL to search allelefrequencies.net
+    &#34;&#34;&#34;
+    base = &#34;http://www.allelefrequencies.net/hla6006a.asp?&#34;
+    locus_type = &#34;hla_locus_type=Classical&amp;&#34;
+    hla_locus = &#34;hla_locus=%s&amp;&#34; %(locus)
+    country = &#34;hla_country=%s&amp;&#34; %(country)
+    region = &#34;hla_region=%s&amp;&#34; %(region)
+    ethnic = &#34;hla_ethnic=%s&amp;&#34; %(ethnic)
+    study_type = &#34;hla_study=%s&amp;&#34; %(study_type)
+    dataset_source = &#34;hla_dataset_source=%s&amp;&#34; %(dataset_source)
+    sample_year = &#34;hla_sample_year=%s&amp;&#34; %(sample_year)
+    sample_year_pattern = &#34;hla_sample_year_pattern=%s&amp;&#34; %(sample_year_pattern)
+    sample_size = &#34;hla_sample_size=%s&amp;&#34; %(sample_size)
+    sample_size_pattern = &#34;hla_sample_size_pattern=%s&amp;&#34; %(sample_size_pattern)
+    hla_level_pattern = &#34;hla_level_pattern=%s&amp;&#34; %(resolution_pattern)
+    hla_level = &#34;hla_level=%s&amp;&#34; %(resolution)
+    standard = &#34;standard=%s&amp;&#34; %standard
+    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
+    return url
+
+def parseAF(bs):
+    &#34;&#34;&#34;Generate a dataframe from a given html page
+
+    Args:
+        bs (bs4.BeautifulSoup): BeautifulSoup object from allelefrequencies.net page
+
+    Returns:
+        pd.DataFrame: Table of allele, allele frequency, samplesize, and population
+    &#34;&#34;&#34;
+    # Get the results table from the div `divGenDetail`
+    tab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenDetail&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;tblNormal&#39;})
+    # Get the column headers from the first row of the table
+    columns = [
+        &#39;line&#39;, &#39;allele&#39;, &#39;flag&#39;, &#39;population&#39;, &#39;carriers%&#39;,
+        &#39;allele_freq&#39;, &#39;AF_graphic&#39;, &#39;sample_size&#39;, &#39;database&#39;,
+        &#39;distribution&#39;,&#39;haplotype_association&#39;, &#39;notes&#39;
+        ]
+    rows =[]
+    for row in tab.find_all(&#39;tr&#39;):
+        rows.append(
+            [td.get_text(strip=True) for td in row.find_all(&#39;td&#39;)]
+            )
+    # Make dataframe of table rows
+    # skip the first row as it&#39;s `th` headers
+    df = pd.DataFrame(rows[1:], columns = columns)
+
+    # Get HLA loci
+    df[&#39;loci&#39;] = df.allele.apply(lambda x: x.split(&#34;*&#34;)[0])
+
+    # Drop unwanted columns
+    df = df[[&#39;allele&#39;, &#39;loci&#39;, &#39;population&#39;, &#39;allele_freq&#39;, &#39;carriers%&#39;, &#39;sample_size&#39;]]
+    return df
+   
+def Npages(bs):
+    &#34;&#34;&#34;How many pages of results are there?
+
+    Args:
+        bs (bs4.BeautifulSoup): BS object of allelefrequencies.net results page
+
+    Returns:
+        int: Total number of results pages
+    &#34;&#34;&#34;
+    # Get the table with number of pages
+    navtab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenNavig&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;table10&#39;})
+    assert navtab, f&#34;navtab does not evaluate to True. Check URL returns results in web browser.&#34;
+    # Get cell with &#39; of &#39; in 
+    pagesOfN = [td.get_text(strip=True) for td in navtab.find_all(&#39;td&#39;) if &#34; of &#34; in td.text]
+    # Check single cell returned
+    assert len(pagesOfN) == 1, &#34;divGenNavig should contain 1 of not %s&#34; %len(pagesOfN)
+    # Get total number of pages
+    N = pagesOfN[0].split(&#34;of &#34;)[1]
+    N = int(N)
+    return N
+
+def formatAF(AFtab, ignoreG=True):
+    &#34;&#34;&#34;Format allele frequency table.
+    Convert sample_size and allele_freq to numeric data type.
+    Removes commas from sample size. Removes &#34;(*)&#34; from allele frequency if 
+    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
+        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+
+    Returns:
+        pd.DataFrame: The formatted allele frequency data.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    if df.sample_size.dtype == &#34;O&#34;:
+        df.sample_size = pd.to_numeric(df.sample_size.str.replace(&#34;,&#34;, &#34;&#34;))
+    if df.allele_freq.dtype == &#34;O&#34;:
+        if ignoreG:
+            df.allele_freq = df.allele_freq.str.replace(&#34;(*)&#34;, &#34;&#34;, regex=False)
+        df.allele_freq = pd.to_numeric(df.allele_freq)
+    return df
+
+def getAFdata(base_url, format=True, ignoreG=True):
+    &#34;&#34;&#34;Get all allele frequency data from a search base url. Iterates over all
+        pages regardless of which page is based.
+
+    Args:
+        base_url (str): URL for base search.
+        format (bool): Format the downloaded data using `formatAF()`.
+        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+
+    Returns:
+        pd.DataFrame: allele frequency data parsed into a pandas dataframe
+    &#34;&#34;&#34;
+    # Get BS object from base search
+    bs = BeautifulSoup(requests.get(base_url).text, &#39;html.parser&#39;)
+    # How many pages of results
+    N = Npages(bs)
+    print(&#34;%s pages of results&#34; %N)
+    # iterate over pages, parse and combine data from each
+    tabs = []
+    for i in range(N):
+        # print (&#34; Parsing page %s&#34; %(i+1))
+        print (&#34; Parsing page %s&#34; %(i+1), end=&#34;\r&#34;)
+        url = base_url + &#34;page=&#34; + str(i+1)
+        bs = BeautifulSoup(requests.get(url).text, &#39;html.parser&#39;)
+        tab = parseAF(bs)
+        tabs.append(tab)
+    print(&#34;Download complete&#34;)
+    tabs = pd.concat(tabs)
+    if format:
+        try:
+            tabs = formatAF(tabs, ignoreG)
+        except:
+            print(&#34;Formatting failed, non-numeric datatypes may remain.&#34;)
+    return tabs
+
+def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Report any studies with allele freqs that don&#39;t sum to 1
+
+    Args:
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study
+    &#34;&#34;&#34;
+    poplocs = AFtab.groupby([datasetID, &#39;loci&#39;]).allele_freq.sum()
+    lmask = poplocs &lt; llimit
+    if sum(lmask&gt;0):
+        print(poplocs[lmask])
+        print(f&#34;{sum(lmask)} studies have total allele frequency &lt; {llimit}&#34;)
+    umask = poplocs &gt; ulimit
+    if sum(umask&gt;0):
+        print(poplocs[umask])
+        print(f&#34;{sum(umask)} studies have total allele frequency &gt; {ulimit}&#34;)
+    incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
+    return incomplete
+
+def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+    This prevents throwing away data if another loci in the population is incomplete
+
+    Args:
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study. Defaults to &#39;population&#39;.
+
+    Returns:
+        pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
+    &#34;&#34;&#34;
+    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
+    # Returns False if population AND loci are in the noncomplete.index
+    # AS A PAIR
+    # This is important so that we don&#39;t throw away all data on a population
+    # just because one loci is incomplete.
+    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
+    df = AFtab[complete_mask]
+    return df
+
+def check_resolution(AFtab):
+    &#34;&#34;&#34;Check if all alleles in AFtab have the same resolution.
+    Will print the number of records with each resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+
+    Returns:
+        bool: True only if all alleles have the same resolution, else False.
+    &#34;&#34;&#34;
+    resolution = 1 + AFtab.allele.str.count(&#34;:&#34;)
+    resVC = resolution.value_counts()
+    pass_check = len(resVC) == 1
+    if not pass_check:
+        print(resVC)
+        print(f&#34;Multiple resolutions in AFtab. Fix with decrease_resolution()&#34;)
+    return pass_check
+
+def decrease_resolution(AFtab, newres, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Decrease allele resolution to a specified value so all alleles have the same resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data.
+        newres (int): The desired number of fields for resolution.
+        datasetID (str, optional): Column to use as stud identifier. Defaults to &#39;population&#39;.
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all alleles of requested resolution.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    resolution = 1 + df.allele.str.count(&#34;:&#34;)
+    assert all(resolution &gt;= newres), f&#34;Some alleles have resolution below {newres} fields&#34;
+    new_allele = df.allele.str.split(&#34;:&#34;).apply(lambda x: &#34;:&#34;.join(x[:newres]))
+    df.allele = new_allele
+    collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
+    return collapsed
+
+def collapse_reduced_alleles(AFtab, datasetID=&#39;population&#39;):
+    df = AFtab.copy()
+    # Group by alleles within datasets
+    grouped = df.groupby([datasetID,&#39;allele&#39;])
+    # Sum allele freq but keep other columns
+    collapsed = grouped.apply(
+        lambda row: [
+            sum(row.allele_freq),
+            row.sample_size.unique()[0],
+            row.loci.unique()[0],
+            len(row.loci.unique()),
+            len(row.sample_size.unique())
+        ]
+    )
+    collapsed = pd.DataFrame(
+        collapsed.tolist(),
+        index=collapsed.index,
+        columns = [&#39;allele_freq&#39;, &#39;sample_size&#39;, &#39;loci&#39;, &#39;#loci&#39;, &#39;#sample_sizes&#39;]
+    ).reset_index()
+    # Within a study each all identical alleles should have the same loci and sample size
+    assert all(collapsed[&#39;#loci&#39;] == 1), &#34;Multiple loci found for a single allele in a single population&#34;
+    assert all(collapsed[&#39;#sample_sizes&#39;] == 1), &#34;Multiple sample_sizes found for a single allele in a single population&#34;
+    collapsed = collapsed[[&#39;allele&#39;, &#39;loci&#39;,&#39;population&#39;,&#39;allele_freq&#39;,&#39;sample_size&#39;]]
+    alleles_unique_in_study(collapsed)
+    return collapsed
+
+def unmeasured_alleles(AFtab, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;When combining AF estimates, unreported alleles can inflate frequencies
+        so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.
+
+    Args:
+        AFtab (pd.DataFrame): Formatted allele frequency data
+        datasetID (str): Unique identifier column for study
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all locus alleles reported 
+            for each dataset
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    loci = df.loci.unique()
+    # Iterate over loci separately
+    for locus in loci:
+        # Iterate over each dataset reporting that locus
+        datasets = df[df.loci == locus][datasetID].unique()
+        for dataset in datasets:
+            # Single locus, single dataset
+            datasetAF = df[(df[datasetID] == dataset) &amp; (df.loci == locus)]
+            # What was the sample size for this data?
+            dataset_sample_size = datasetAF.sample_size.unique()
+            assert len(dataset_sample_size) == 1, &#34;dataset_sample_size must be 1, not %s&#34; %len(dataset_sample_size)
+            dataset_sample_size = dataset_sample_size[0]
+            # Get all alleles for this locus (across datasets)
+            ualleles = df[df.loci == locus].allele.unique()
+            # Which of these alleles are not in this dataset?
+            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
+            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
+            missing_rows = pd.DataFrame(missing_rows, columns=[&#39;allele&#39;,&#39;loci&#39;,datasetID,&#39;allele_freq&#39;,&#39;carriers%&#39;,&#39;sample_size&#39;])
+            # Add them in with zero frequency
+            df = pd.concat([df, missing_rows], ignore_index=True)
+    return df
+
+def combineAF(AFtab, weights=&#39;2n&#39;, alpha = [], datasetID=&#39;population&#39;, format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+    &#34;&#34;&#34;Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
+    Allele frequencies combined using a Dirichlet distribution where each study&#39;s contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
+    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
+    If `alpha` is not set the prior defaults to 1 observation of each allele.
+
+    Args:
+        AFtab (pd.DataFrame): Table of Allele frequency data
+        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to &#39;2n&#39;.
+        alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
+        datasetID (str, optional): Unique identifier column for study. Defaults to &#39;population&#39;.
+        format (bool, optional): Run `formatAF()`. Defaults to True.
+        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
+        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
+        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
+        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
+        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
+
+    Returns:
+        pd.DataFrame: Allele frequencies after combining estimates from all studies.
+        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
+        *alpha* is the prior used for the Dirichlet distribution.
+        *c* is the observations used for the Dirichlet distribution.
+        *sample_size* is the total sample size of all combined studies.
+        *wav* is the weighted average.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    single_loci(df)
+    if unique:
+        assert alleles_unique_in_study(df, datasetID=datasetID), &#34;The same allele appears multiple times in a dataset&#34;
+    if complete:
+        assert incomplete_studies(df, datasetID=datasetID).empty, &#34;AFtab contains studies with AF that doesn&#39;t sum to 1. Check incomplete_studies(AFtab)&#34;
+    if resolution:
+        assert check_resolution(df), &#34;AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)&#34;
+    if format:
+        df = formatAF(df, ignoreG)
+    if add_unmeasured:
+        df = unmeasured_alleles(df, datasetID)
+    try:
+        df[&#39;2n&#39;] = df.sample_size * 2
+    except:
+        print(&#34;column &#39;2n&#39; could not be created&#34;)
+    df[&#39;c&#39;] =  df.allele_freq * df[weights]
+    grouped = df.groupby(&#39;allele&#39;, sort=True)
+    combined = grouped.apply(
+        lambda row: [
+        row.name,
+        row.loci.unique()[0],
+        np.average(row.allele_freq, weights=row[weights]),
+        row.c.sum(),
+        row.sample_size.sum()
+        ]
+    )
+    combined = pd.DataFrame(
+        combined.tolist(),
+        columns = [&#39;allele&#39;, &#39;loci&#39;,
+            &#39;wav&#39;,
+            &#39;c&#39;, &#39;sample_size&#39;]
+    )
+    combined = combined.reset_index(drop=True)
+    # Check that all alleles in a locus have the same sample size
+    # after merging
+    if duplicated_sample_size(combined):
+        id_duplicated_allele(grouped)
+    if not alpha:
+        alpha = default_prior(len(combined.allele))
+    combined[&#39;alpha&#39;] = alpha
+    # Calculate Dirichlet mean for each allele
+    combined[&#39;allele_freq&#39;] = dirichlet(combined.alpha + combined.c).mean()
+
+    return combined
+
+def default_prior(k):
+    &#34;&#34;&#34;Calculate a default prior, 1 observation of each class.
+
+    Args:
+        k (int): Number of classes in the Dirichlet distribution.
+
+    Returns:
+        list: List of k 1s to use as prior.
+    &#34;&#34;&#34;
+    alpha = [1] * k
+    return alpha
+
+def single_loci(AFtab):
+    &#34;&#34;&#34;Check that allele frequency data is only of one locus
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+    &#34;&#34;&#34;
+    assert len(AFtab.loci.unique()) == 1, f&#34;&#39;AFtab&#39; must conatain only 1 loci&#34;
+
+def alleles_unique_in_study(AFtab, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+        datasetID (str, optional): Unique identifier column to define study. Defaults to &#39;population&#39;.
+
+    Returns:
+        bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    grouped = df.groupby([datasetID,&#39;allele&#39;])
+    # Are allele alleles unique? i.e. do any occur multiple times in grouping?
+    unique = grouped.size()[grouped.size()&gt;1].empty
+    if not unique:
+        print(f&#34;Non unique alleles in study, is datasetID correct? {datasetID}&#34;)
+        print(grouped.size()[grouped.size()&gt;1])
+    return unique
+
+def duplicated_sample_size(AFtab):
+    &#34;&#34;&#34;Returns True if any loci has more than 1 unique sample size&#34;&#34;&#34;
+    locus_sample_sizes = AFtab.groupby(&#39;loci&#39;).sample_size.apply(lambda x: len(x.unique()))
+    return any(locus_sample_sizes != 1)
+
+def id_duplicated_allele(grouped):
+    &#34;&#34;&#34; Reports the allele that has mupltiple sample sizes &#34;&#34;&#34;
+    duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
+    assert all(~duplicated_population), &#34;duplicated population within allele %s&#34; %duplicated_population[duplicated_population].index.tolist()
+
+def population_coverage(p):
+    &#34;&#34;&#34;Calculate the proportion of people with at least 1 copy of this allele
+        assuming HWE.
+
+    Args:
+        p (float): Allele frequency
+
+    Returns:
+        float: Sum of homozygotes and heterozygotes for this allele
+    &#34;&#34;&#34;
+    q = 1-p
+    homo = p**2
+    hetero = 2*p*q
+    return homo + hetero
+
+def betaAB(alpha):
+    &#34;&#34;&#34;Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
+
+    Args:
+        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
+
+    Returns:
+        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn&#39;t observed.
+    &#34;&#34;&#34;
+    ab = [(a,sum(alpha)-a) for a in alpha]
+    return ab
+
+def betaCI(a,b,credible_interval=0.95):
+    &#34;&#34;&#34;Calculat the central credible interval of a beta distribution
+
+    Args:
+        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
+        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
+        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+    Returns:
+        tuple: Lower and upper credible interval of beta distribution.
+    &#34;&#34;&#34;
+    bd = beta(a,b)
+    lower_quantile = (1-credible_interval)/2
+    upper_quantile = 1-lower_quantile
+    lower_interval = bd.ppf(lower_quantile)
+    upper_interval = bd.ppf(upper_quantile)
+    return lower_interval, upper_interval
+
+def AFci(caf, credible_interval=0.95):
+    &#34;&#34;&#34;Calculate credible interval for combined allele frequency table
+
+    Args:
+        caf (pd.DataFrame): Table produced by combineAF()
+        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
+
+    Returns:
+        list: Lower and upper credible intervals as a list of tuples
+    &#34;&#34;&#34;
+    ab = betaAB(
+        caf.alpha + caf.c,
+    )
+    ci = [betaCI(a, b, credible_interval) for a,b in ab]
+    return ci
+
+def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID=&#34;population&#34;, concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
+    &#34;&#34;&#34;Plot the posterior density function of all frequencies
+        for all alleles based on concentration for Dirichlet
+        distribution. Supply AFtab to add empirical values to plot.
+
+    Args:
+        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn&#39;t have the error checking that combineAF() has. Defaults to pd.DataFrame().
+        datasetID (str, optional): The column used to define datasets. Defaults to &#34;population&#34;.
+        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
+        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
+        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
+        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
+        xmin (float, optional): Set x axis min. Defaults to -0.05.
+        xmax (float, optional): Set x axis max. Defaults to 1.05.
+        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
+    &#34;&#34;&#34;
+    def allele_mask(alleles, concentration):
+        &#34;&#34;&#34;Create boolean mask either to keep only supplied `alleles`. If empty keep all.
+
+        Args:
+            alleles (list): list of alleles
+            concentration (list): Dirichlet concentration
+
+        Returns:
+            list: List of booleans to use as mask
+        &#34;&#34;&#34;
+        assert isinstance(alleles, list), f&#34;alleles must be a list, not {type(alleles)}&#34;
+        if not alleles:
+            mask = [True] * len(concentration)
+        else:
+            mask = caf.allele.isin(alleles)
+        return mask
+
+    if not concentration:
+        concentration = caf.alpha + caf.c
+    # Get beta parameters for each k in Dirichlet
+    ab = betaAB(concentration)
+    pline = np.linspace(0,1,psteps)
+    if not AFtab.empty:
+        # Format the population allele frequencies
+        df = AFtab.copy()
+        df = unmeasured_alleles(df, datasetID=datasetID)
+        df = df.sort_values(&#39;allele&#39;)
+        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), &#34;Alleles not matching between AFtab and caf&#34;
+    mask = allele_mask(alleles, concentration)
+    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
+    # Only indexes that pass the mask
+    masked_indexes = [i for i,x in enumerate(mask) if x]
+    for subploti,i in enumerate(masked_indexes):
+        subplotselector = subploti//ncol, subploti%ncol
+        a,b = ab[i]
+        bd = beta(a,b)
+        if log:
+            pdf = [bd.logpdf(p) for p in pline]
+        else:
+            with warnings.catch_warnings():
+                warnings.simplefilter(&#34;ignore&#34;)
+                pdf = [bd.pdf(p) for p in pline]
+        ax = axs[subplotselector]
+        ax.set_xlim(xmin,xmax)
+        if not AFtab.empty:
+            # Add the empirical allele frequency for each population
+            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
+                # x is the reported allele freq, y is it&#39;s pdf with scatter
+                if log:
+                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
+                else:
+                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
+        ax.plot(pline, pdf)
+        # Annotate with allele
+        if not caf.empty:
+            ax.text((xmax-xmin)/2, max(pdf)/2, f&#34;{caf.allele.iloc[i]}&#34;)
+        # Annotate with concentration
+        # ax.text(0.5, max(pdf)/3, f&#34;Concentration {round(concentration.iloc[i])}&#34;)
+        if not caf.empty:
+            # Plot the combined average
+            ax.axvline(caf.allele_freq[i], color=&#34;black&#34;, ls=&#34;--&#34;)
+        if ci:
+            cl,cu = betaCI(a,b, ci)
+            ax.axvline(cl, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
+            ax.axvline(cu, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
+        # fig.tight_layout()
+    plt.show()</code></pre>
+</details>
+</section>
+<section>
+</section>
+<section>
+</section>
+<section>
+<h2 class="section-title" id="header-functions">Functions</h2>
+<dl>
+<dt id="HLAfreq.HLAfreq.AFci"><code class="name flex">
+<span>def <span class="ident">AFci</span></span>(<span>caf, credible_interval=0.95)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Calculate credible interval for combined allele frequency table</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>caf</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Table produced by combineAF()</dd>
+<dt><strong><code>credible_interval</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>The desired confidence interval. Defaults to 0.95.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>list</code></dt>
+<dd>Lower and upper credible intervals as a list of tuples</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def AFci(caf, credible_interval=0.95):
+    &#34;&#34;&#34;Calculate credible interval for combined allele frequency table
+
+    Args:
+        caf (pd.DataFrame): Table produced by combineAF()
+        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
+
+    Returns:
+        list: Lower and upper credible intervals as a list of tuples
+    &#34;&#34;&#34;
+    ab = betaAB(
+        caf.alpha + caf.c,
+    )
+    ci = [betaCI(a, b, credible_interval) for a,b in ab]
+    return ci</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.Npages"><code class="name flex">
+<span>def <span class="ident">Npages</span></span>(<span>bs)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>How many pages of results are there?</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>bs</code></strong> :&ensp;<code>bs4.BeautifulSoup</code></dt>
+<dd>BS object of allelefrequencies.net results page</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>int</code></dt>
+<dd>Total number of results pages</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def Npages(bs):
+    &#34;&#34;&#34;How many pages of results are there?
+
+    Args:
+        bs (bs4.BeautifulSoup): BS object of allelefrequencies.net results page
+
+    Returns:
+        int: Total number of results pages
+    &#34;&#34;&#34;
+    # Get the table with number of pages
+    navtab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenNavig&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;table10&#39;})
+    assert navtab, f&#34;navtab does not evaluate to True. Check URL returns results in web browser.&#34;
+    # Get cell with &#39; of &#39; in 
+    pagesOfN = [td.get_text(strip=True) for td in navtab.find_all(&#39;td&#39;) if &#34; of &#34; in td.text]
+    # Check single cell returned
+    assert len(pagesOfN) == 1, &#34;divGenNavig should contain 1 of not %s&#34; %len(pagesOfN)
+    # Get total number of pages
+    N = pagesOfN[0].split(&#34;of &#34;)[1]
+    N = int(N)
+    return N</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.alleles_unique_in_study"><code class="name flex">
+<span>def <span class="ident">alleles_unique_in_study</span></span>(<span>AFtab, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by <code>datasetID</code>.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Allele frequency data</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Unique identifier column to define study. Defaults to 'population'.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>bool</code></dt>
+<dd><code>True</code> on if no alleles occur more than once in any study, otherwise <code>False</code>.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def alleles_unique_in_study(AFtab, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+        datasetID (str, optional): Unique identifier column to define study. Defaults to &#39;population&#39;.
+
+    Returns:
+        bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    grouped = df.groupby([datasetID,&#39;allele&#39;])
+    # Are allele alleles unique? i.e. do any occur multiple times in grouping?
+    unique = grouped.size()[grouped.size()&gt;1].empty
+    if not unique:
+        print(f&#34;Non unique alleles in study, is datasetID correct? {datasetID}&#34;)
+        print(grouped.size()[grouped.size()&gt;1])
+    return unique</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.betaAB"><code class="name flex">
+<span>def <span class="ident">betaAB</span></span>(<span>alpha)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>alpha</code></strong> :&ensp;<code>list</code></dt>
+<dd>Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>list</code></dt>
+<dd>List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def betaAB(alpha):
+    &#34;&#34;&#34;Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
+
+    Args:
+        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
+
+    Returns:
+        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn&#39;t observed.
+    &#34;&#34;&#34;
+    ab = [(a,sum(alpha)-a) for a in alpha]
+    return ab</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.betaCI"><code class="name flex">
+<span>def <span class="ident">betaCI</span></span>(<span>a, b, credible_interval=0.95)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Calculat the central credible interval of a beta distribution</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>a</code></strong> :&ensp;<code>float</code></dt>
+<dd>Beta shape parameter <code>a</code>, i.e. the number of times the allele was observed.</dd>
+<dt><strong><code>b</code></strong> :&ensp;<code>float</code></dt>
+<dd>Beta shape parameter <code>b</code>, i.e. the number of times the allele was not observed.</dd>
+<dt><strong><code>credible_interval</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>The size of the credible interval requested. Defaults to 0.95.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>tuple</code></dt>
+<dd>Lower and upper credible interval of beta distribution.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def betaCI(a,b,credible_interval=0.95):
+    &#34;&#34;&#34;Calculat the central credible interval of a beta distribution
+
+    Args:
+        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
+        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
+        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+    Returns:
+        tuple: Lower and upper credible interval of beta distribution.
+    &#34;&#34;&#34;
+    bd = beta(a,b)
+    lower_quantile = (1-credible_interval)/2
+    upper_quantile = 1-lower_quantile
+    lower_interval = bd.ppf(lower_quantile)
+    upper_interval = bd.ppf(upper_quantile)
+    return lower_interval, upper_interval</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.check_resolution"><code class="name flex">
+<span>def <span class="ident">check_resolution</span></span>(<span>AFtab)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Check if all alleles in AFtab have the same resolution.
+Will print the number of records with each resolution.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Allele frequency data</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>bool</code></dt>
+<dd>True only if all alleles have the same resolution, else False.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def check_resolution(AFtab):
+    &#34;&#34;&#34;Check if all alleles in AFtab have the same resolution.
+    Will print the number of records with each resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+
+    Returns:
+        bool: True only if all alleles have the same resolution, else False.
+    &#34;&#34;&#34;
+    resolution = 1 + AFtab.allele.str.count(&#34;:&#34;)
+    resVC = resolution.value_counts()
+    pass_check = len(resVC) == 1
+    if not pass_check:
+        print(resVC)
+        print(f&#34;Multiple resolutions in AFtab. Fix with decrease_resolution()&#34;)
+    return pass_check</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.collapse_reduced_alleles"><code class="name flex">
+<span>def <span class="ident">collapse_reduced_alleles</span></span>(<span>AFtab, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def collapse_reduced_alleles(AFtab, datasetID=&#39;population&#39;):
+    df = AFtab.copy()
+    # Group by alleles within datasets
+    grouped = df.groupby([datasetID,&#39;allele&#39;])
+    # Sum allele freq but keep other columns
+    collapsed = grouped.apply(
+        lambda row: [
+            sum(row.allele_freq),
+            row.sample_size.unique()[0],
+            row.loci.unique()[0],
+            len(row.loci.unique()),
+            len(row.sample_size.unique())
+        ]
+    )
+    collapsed = pd.DataFrame(
+        collapsed.tolist(),
+        index=collapsed.index,
+        columns = [&#39;allele_freq&#39;, &#39;sample_size&#39;, &#39;loci&#39;, &#39;#loci&#39;, &#39;#sample_sizes&#39;]
+    ).reset_index()
+    # Within a study each all identical alleles should have the same loci and sample size
+    assert all(collapsed[&#39;#loci&#39;] == 1), &#34;Multiple loci found for a single allele in a single population&#34;
+    assert all(collapsed[&#39;#sample_sizes&#39;] == 1), &#34;Multiple sample_sizes found for a single allele in a single population&#34;
+    collapsed = collapsed[[&#39;allele&#39;, &#39;loci&#39;,&#39;population&#39;,&#39;allele_freq&#39;,&#39;sample_size&#39;]]
+    alleles_unique_in_study(collapsed)
+    return collapsed</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.combineAF"><code class="name flex">
+<span>def <span class="ident">combineAF</span></span>(<span>AFtab, weights='2n', alpha=[], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Combine allele frequencies from multiple studies. <code>datasetID</code> is the unique identifier for studies to combine.
+Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+Sample size is doubled to get <code>2n</code> due to diploidy. If an alternative <code>weights</code> is set it is not doubled.
+The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior <code>alpha</code>.
+If <code>alpha</code> is not set the prior defaults to 1 observation of each allele.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Table of Allele frequency data</dd>
+<dt><strong><code>weights</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.</dd>
+<dt><strong><code>alpha</code></strong> :&ensp;<code>list</code>, optional</dt>
+<dd>Prior to use for Dirichlet distribution. Defaults to [].</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Unique identifier column for study. Defaults to 'population'.</dd>
+<dt><strong><code>format</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Run <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>. Defaults to True.</dd>
+<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Treat allele G groups as normal, see <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>. Defaults to True.</dd>
+<dt><strong><code>add_unmeasured</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See <code>add_unmeasured()</code>. Defaults to True.</dd>
+<dt><strong><code>complete</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Check study completeness. Uses default values for <code><a title="HLAfreq.HLAfreq.incomplete_studies" href="#HLAfreq.HLAfreq.incomplete_studies">incomplete_studies()</a></code>. If you are happy with your study completeness can be switched off with False. Defaults to True.</dd>
+<dt><strong><code>resolution</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Check that all alleles have the same resolution, see <code><a title="HLAfreq.HLAfreq.check_resolution" href="#HLAfreq.HLAfreq.check_resolution">check_resolution()</a></code>. Defaults to True.</dd>
+<dt><strong><code>unique</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Check that each allele appears no more than once per study. See <code><a title="HLAfreq.HLAfreq.alleles_unique_in_study" href="#HLAfreq.HLAfreq.alleles_unique_in_study">alleles_unique_in_study()</a></code>. Defaults to True.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>Allele frequencies after combining estimates from all studies.</dd>
+</dl>
+<p><em>allele_freq</em> is the combined frequency estimate from the Dirichlet mean where the concentration is <code>alpha</code> + <code>c</code>.
+<em>alpha</em> is the prior used for the Dirichlet distribution.
+<em>c</em> is the observations used for the Dirichlet distribution.
+<em>sample_size</em> is the total sample size of all combined studies.
+<em>wav</em> is the weighted average.</p></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def combineAF(AFtab, weights=&#39;2n&#39;, alpha = [], datasetID=&#39;population&#39;, format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+    &#34;&#34;&#34;Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
+    Allele frequencies combined using a Dirichlet distribution where each study&#39;s contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
+    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
+    If `alpha` is not set the prior defaults to 1 observation of each allele.
+
+    Args:
+        AFtab (pd.DataFrame): Table of Allele frequency data
+        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to &#39;2n&#39;.
+        alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
+        datasetID (str, optional): Unique identifier column for study. Defaults to &#39;population&#39;.
+        format (bool, optional): Run `formatAF()`. Defaults to True.
+        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
+        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
+        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
+        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
+        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
+
+    Returns:
+        pd.DataFrame: Allele frequencies after combining estimates from all studies.
+        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
+        *alpha* is the prior used for the Dirichlet distribution.
+        *c* is the observations used for the Dirichlet distribution.
+        *sample_size* is the total sample size of all combined studies.
+        *wav* is the weighted average.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    single_loci(df)
+    if unique:
+        assert alleles_unique_in_study(df, datasetID=datasetID), &#34;The same allele appears multiple times in a dataset&#34;
+    if complete:
+        assert incomplete_studies(df, datasetID=datasetID).empty, &#34;AFtab contains studies with AF that doesn&#39;t sum to 1. Check incomplete_studies(AFtab)&#34;
+    if resolution:
+        assert check_resolution(df), &#34;AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)&#34;
+    if format:
+        df = formatAF(df, ignoreG)
+    if add_unmeasured:
+        df = unmeasured_alleles(df, datasetID)
+    try:
+        df[&#39;2n&#39;] = df.sample_size * 2
+    except:
+        print(&#34;column &#39;2n&#39; could not be created&#34;)
+    df[&#39;c&#39;] =  df.allele_freq * df[weights]
+    grouped = df.groupby(&#39;allele&#39;, sort=True)
+    combined = grouped.apply(
+        lambda row: [
+        row.name,
+        row.loci.unique()[0],
+        np.average(row.allele_freq, weights=row[weights]),
+        row.c.sum(),
+        row.sample_size.sum()
+        ]
+    )
+    combined = pd.DataFrame(
+        combined.tolist(),
+        columns = [&#39;allele&#39;, &#39;loci&#39;,
+            &#39;wav&#39;,
+            &#39;c&#39;, &#39;sample_size&#39;]
+    )
+    combined = combined.reset_index(drop=True)
+    # Check that all alleles in a locus have the same sample size
+    # after merging
+    if duplicated_sample_size(combined):
+        id_duplicated_allele(grouped)
+    if not alpha:
+        alpha = default_prior(len(combined.allele))
+    combined[&#39;alpha&#39;] = alpha
+    # Calculate Dirichlet mean for each allele
+    combined[&#39;allele_freq&#39;] = dirichlet(combined.alpha + combined.c).mean()
+
+    return combined</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.decrease_resolution"><code class="name flex">
+<span>def <span class="ident">decrease_resolution</span></span>(<span>AFtab, newres, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Decrease allele resolution to a specified value so all alleles have the same resolution.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Allele frequency data.</dd>
+<dt><strong><code>newres</code></strong> :&ensp;<code>int</code></dt>
+<dd>The desired number of fields for resolution.</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Column to use as stud identifier. Defaults to 'population'.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>Allele frequency data with all alleles of requested resolution.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def decrease_resolution(AFtab, newres, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Decrease allele resolution to a specified value so all alleles have the same resolution.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data.
+        newres (int): The desired number of fields for resolution.
+        datasetID (str, optional): Column to use as stud identifier. Defaults to &#39;population&#39;.
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all alleles of requested resolution.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    resolution = 1 + df.allele.str.count(&#34;:&#34;)
+    assert all(resolution &gt;= newres), f&#34;Some alleles have resolution below {newres} fields&#34;
+    new_allele = df.allele.str.split(&#34;:&#34;).apply(lambda x: &#34;:&#34;.join(x[:newres]))
+    df.allele = new_allele
+    collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
+    return collapsed</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.default_prior"><code class="name flex">
+<span>def <span class="ident">default_prior</span></span>(<span>k)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Calculate a default prior, 1 observation of each class.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>k</code></strong> :&ensp;<code>int</code></dt>
+<dd>Number of classes in the Dirichlet distribution.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>list</code></dt>
+<dd>List of k 1s to use as prior.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def default_prior(k):
+    &#34;&#34;&#34;Calculate a default prior, 1 observation of each class.
+
+    Args:
+        k (int): Number of classes in the Dirichlet distribution.
+
+    Returns:
+        list: List of k 1s to use as prior.
+    &#34;&#34;&#34;
+    alpha = [1] * k
+    return alpha</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.duplicated_sample_size"><code class="name flex">
+<span>def <span class="ident">duplicated_sample_size</span></span>(<span>AFtab)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Returns True if any loci has more than 1 unique sample size</p></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def duplicated_sample_size(AFtab):
+    &#34;&#34;&#34;Returns True if any loci has more than 1 unique sample size&#34;&#34;&#34;
+    locus_sample_sizes = AFtab.groupby(&#39;loci&#39;).sample_size.apply(lambda x: len(x.unique()))
+    return any(locus_sample_sizes != 1)</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.formatAF"><code class="name flex">
+<span>def <span class="ident">formatAF</span></span>(<span>AFtab, ignoreG=True)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Format allele frequency table.
+Convert sample_size and allele_freq to numeric data type.
+Removes commas from sample size. Removes "(*)" from allele frequency if
+<code>ignoreG</code> is <code>True</code>. <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code> is used internally by combineAF and getAFdata by default.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Allele frequency data downloaded from allelefrequency.net using <code><a title="HLAfreq.HLAfreq.getAFdata" href="#HLAfreq.HLAfreq.getAFdata">getAFdata()</a></code>.</dd>
+<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Treat G group alleles as normal. See <a href="http://hla.alleles.org/alleles/g_groups.html">http://hla.alleles.org/alleles/g_groups.html</a> for details. Defaults to True.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>The formatted allele frequency data.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def formatAF(AFtab, ignoreG=True):
+    &#34;&#34;&#34;Format allele frequency table.
+    Convert sample_size and allele_freq to numeric data type.
+    Removes commas from sample size. Removes &#34;(*)&#34; from allele frequency if 
+    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
+        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+
+    Returns:
+        pd.DataFrame: The formatted allele frequency data.
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    if df.sample_size.dtype == &#34;O&#34;:
+        df.sample_size = pd.to_numeric(df.sample_size.str.replace(&#34;,&#34;, &#34;&#34;))
+    if df.allele_freq.dtype == &#34;O&#34;:
+        if ignoreG:
+            df.allele_freq = df.allele_freq.str.replace(&#34;(*)&#34;, &#34;&#34;, regex=False)
+        df.allele_freq = pd.to_numeric(df.allele_freq)
+    return df</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.getAFdata"><code class="name flex">
+<span>def <span class="ident">getAFdata</span></span>(<span>base_url, format=True, ignoreG=True)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Get all allele frequency data from a search base url. Iterates over all
+pages regardless of which page is based.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>base_url</code></strong> :&ensp;<code>str</code></dt>
+<dd>URL for base search.</dd>
+<dt><strong><code>format</code></strong> :&ensp;<code>bool</code></dt>
+<dd>Format the downloaded data using <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>.</dd>
+<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code></dt>
+<dd>treat allele G groups as normal. See <a href="http://hla.alleles.org/alleles/g_groups.html">http://hla.alleles.org/alleles/g_groups.html</a> for details. Default = True</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>allele frequency data parsed into a pandas dataframe</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def getAFdata(base_url, format=True, ignoreG=True):
+    &#34;&#34;&#34;Get all allele frequency data from a search base url. Iterates over all
+        pages regardless of which page is based.
+
+    Args:
+        base_url (str): URL for base search.
+        format (bool): Format the downloaded data using `formatAF()`.
+        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+
+    Returns:
+        pd.DataFrame: allele frequency data parsed into a pandas dataframe
+    &#34;&#34;&#34;
+    # Get BS object from base search
+    bs = BeautifulSoup(requests.get(base_url).text, &#39;html.parser&#39;)
+    # How many pages of results
+    N = Npages(bs)
+    print(&#34;%s pages of results&#34; %N)
+    # iterate over pages, parse and combine data from each
+    tabs = []
+    for i in range(N):
+        # print (&#34; Parsing page %s&#34; %(i+1))
+        print (&#34; Parsing page %s&#34; %(i+1), end=&#34;\r&#34;)
+        url = base_url + &#34;page=&#34; + str(i+1)
+        bs = BeautifulSoup(requests.get(url).text, &#39;html.parser&#39;)
+        tab = parseAF(bs)
+        tabs.append(tab)
+    print(&#34;Download complete&#34;)
+    tabs = pd.concat(tabs)
+    if format:
+        try:
+            tabs = formatAF(tabs, ignoreG)
+        except:
+            print(&#34;Formatting failed, non-numeric datatypes may remain.&#34;)
+    return tabs</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.id_duplicated_allele"><code class="name flex">
+<span>def <span class="ident">id_duplicated_allele</span></span>(<span>grouped)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Reports the allele that has mupltiple sample sizes</p></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def id_duplicated_allele(grouped):
+    &#34;&#34;&#34; Reports the allele that has mupltiple sample sizes &#34;&#34;&#34;
+    duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
+    assert all(~duplicated_population), &#34;duplicated population within allele %s&#34; %duplicated_population[duplicated_population].index.tolist()</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.incomplete_studies"><code class="name flex">
+<span>def <span class="ident">incomplete_studies</span></span>(<span>AFtab, llimit=0.95, ulimit=1.1, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Report any studies with allele freqs that don't sum to 1</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Dataframe containing multiple studies</dd>
+<dt><strong><code>llimit</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Lower allele_freq sum limit that counts as complete. Defaults to 0.95.</dd>
+<dt><strong><code>ulimit</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Upper allele_freq sum limit that will not be reported. Defaults to 1.1.</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
+<dd>Unique identifier column for study</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Report any studies with allele freqs that don&#39;t sum to 1
+
+    Args:
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study
+    &#34;&#34;&#34;
+    poplocs = AFtab.groupby([datasetID, &#39;loci&#39;]).allele_freq.sum()
+    lmask = poplocs &lt; llimit
+    if sum(lmask&gt;0):
+        print(poplocs[lmask])
+        print(f&#34;{sum(lmask)} studies have total allele frequency &lt; {llimit}&#34;)
+    umask = poplocs &gt; ulimit
+    if sum(umask&gt;0):
+        print(poplocs[umask])
+        print(f&#34;{sum(umask)} studies have total allele frequency &gt; {ulimit}&#34;)
+    incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
+    return incomplete</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.makeURL"><code class="name flex">
+<span>def <span class="ident">makeURL</span></span>(<span>country='', standard='s', locus='', resolution_pattern='bigger_equal_than', resolution=2, region='', ethnic='', study_type='', dataset_source='', sample_year='', sample_year_pattern='', sample_size='', sample_size_pattern='')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Create URL for search of allele frequency net database. All arguments are documented <a href="http://www.allelefrequencies.net/extaccess.asp">here</a></p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>country</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Country name to retrieve records from. Defaults to "".</dd>
+<dt><strong><code>standard</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.</dd>
+<dt><strong><code>locus</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>The locus to return allele data for. Defaults to "".</dd>
+<dt><strong><code>resolution_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using <code>resolution</code> and <code>resolution_pattern</code>. Defaults to "bigger_equal_than".</dd>
+<dt><strong><code>resolution</code></strong> :&ensp;<code>int</code>, optional</dt>
+<dd>Number of fields of resolution of allele. Filter created using <code>resolution</code> and <code>resolution_pattern</code>. Defaults to 2.</dd>
+<dt><strong><code>region</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Filter to geographic region. {Asia, Australia, Eastern Europe, &hellip;}. All regions listed <a href="http://www.allelefrequencies.net/pop6003a.asp">here</a>. Defaults to "".</dd>
+<dt><strong><code>ethnic</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Filter to ethnicity. {"Amerindian", "Black", "Caucasian", &hellip;}. All ethnicities listed <a href="http://www.allelefrequencies.net/pop6003a.asp">here</a>. Defaults to "".</dd>
+<dt><strong><code>study_type</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".</dd>
+<dt><strong><code>dataset_source</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".</dd>
+<dt><strong><code>sample_year</code></strong> :&ensp;<code>int</code>, optional</dt>
+<dd>Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".</dd>
+<dt><strong><code>sample_year_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".</dd>
+<dt><strong><code>sample_size</code></strong> :&ensp;<code>int</code>, optional</dt>
+<dd>Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".</dd>
+<dt><strong><code>sample_size_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>str</code></dt>
+<dd>URL to search allelefrequencies.net</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def makeURL(
+        country=&#34;&#34;,
+        standard=&#39;s&#39;,
+        locus=&#34;&#34;,
+        resolution_pattern=&#34;bigger_equal_than&#34;,
+        resolution=2,
+        region=&#34;&#34;,
+        ethnic=&#34;&#34;,
+        study_type=&#34;&#34;,
+        dataset_source=&#34;&#34;,
+        sample_year=&#34;&#34;,
+        sample_year_pattern=&#34;&#34;,
+        sample_size=&#34;&#34;,
+        sample_size_pattern=&#34;&#34;
+    ):
+    &#34;&#34;&#34;Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+    Args:
+        country (str, optional): Country name to retrieve records from. Defaults to &#34;&#34;.
+        standard (str, optional): Filter study quality standard to this or higher. {&#39;g&#39;, &#39;s&#39;, &#39;a&#39;} Gold, silver, all. Defaults to &#39;s&#39;.
+        locus (str, optional): The locus to return allele data for. Defaults to &#34;&#34;.
+        resolution_pattern (str, optional): Resolution comparitor {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Filter created using `resolution` and `resolution_pattern`. Defaults to &#34;bigger_equal_than&#34;.
+        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
+        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
+        ethnic (str, optional): Filter to ethnicity. {&#34;Amerindian&#34;, &#34;Black&#34;, &#34;Caucasian&#34;, ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
+        study_type (str, optional): Type of study. {&#34;Anthropology&#34;, &#34;Blood+Donor&#34;, &#34;Bone+Marrow+Registry&#34;, &#34;Controls+for+Disease+Study&#34;, &#34;Disease+Study+Patients&#34;, &#34;Other&#34;, &#34;Solid+Organd+Unrelated+Donors&#34;, &#34;Stem+cell+donors&#34;}. Defaults to &#34;&#34;.
+        dataset_source (str, optional): Source of data. {&#34;Literature&#34;, &#34;Proceedings+of+IHWs&#34;, &#34;Unpublished&#34;}. Defaults to &#34;&#34;.
+        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to &#34;&#34;.
+        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
+        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to &#34;&#34;.
+        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
+
+    Returns:
+        str: URL to search allelefrequencies.net
+    &#34;&#34;&#34;
+    base = &#34;http://www.allelefrequencies.net/hla6006a.asp?&#34;
+    locus_type = &#34;hla_locus_type=Classical&amp;&#34;
+    hla_locus = &#34;hla_locus=%s&amp;&#34; %(locus)
+    country = &#34;hla_country=%s&amp;&#34; %(country)
+    region = &#34;hla_region=%s&amp;&#34; %(region)
+    ethnic = &#34;hla_ethnic=%s&amp;&#34; %(ethnic)
+    study_type = &#34;hla_study=%s&amp;&#34; %(study_type)
+    dataset_source = &#34;hla_dataset_source=%s&amp;&#34; %(dataset_source)
+    sample_year = &#34;hla_sample_year=%s&amp;&#34; %(sample_year)
+    sample_year_pattern = &#34;hla_sample_year_pattern=%s&amp;&#34; %(sample_year_pattern)
+    sample_size = &#34;hla_sample_size=%s&amp;&#34; %(sample_size)
+    sample_size_pattern = &#34;hla_sample_size_pattern=%s&amp;&#34; %(sample_size_pattern)
+    hla_level_pattern = &#34;hla_level_pattern=%s&amp;&#34; %(resolution_pattern)
+    hla_level = &#34;hla_level=%s&amp;&#34; %(resolution)
+    standard = &#34;standard=%s&amp;&#34; %standard
+    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
+    return url</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.only_complete"><code class="name flex">
+<span>def <span class="ident">only_complete</span></span>(<span>AFtab, llimit=0.95, ulimit=1.1, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+This prevents throwing away data if another loci in the population is incomplete</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Dataframe containing multiple studies</dd>
+<dt><strong><code>llimit</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Lower allele_freq sum limit that counts as complete. Defaults to 0.95.</dd>
+<dt><strong><code>ulimit</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Upper allele_freq sum limit that will not be reported. Defaults to 1.1.</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
+<dd>Unique identifier column for study. Defaults to 'population'.</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>Allele frequency data of multiple studies, but only complete studies.</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+    This prevents throwing away data if another loci in the population is incomplete
+
+    Args:
+        AFtab (pd.DataFrame): Dataframe containing multiple studies
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        datasetID (str): Unique identifier column for study. Defaults to &#39;population&#39;.
+
+    Returns:
+        pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
+    &#34;&#34;&#34;
+    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
+    # Returns False if population AND loci are in the noncomplete.index
+    # AS A PAIR
+    # This is important so that we don&#39;t throw away all data on a population
+    # just because one loci is incomplete.
+    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
+    df = AFtab[complete_mask]
+    return df</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.parseAF"><code class="name flex">
+<span>def <span class="ident">parseAF</span></span>(<span>bs)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Generate a dataframe from a given html page</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>bs</code></strong> :&ensp;<code>bs4.BeautifulSoup</code></dt>
+<dd>BeautifulSoup object from allelefrequencies.net page</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>Table of allele, allele frequency, samplesize, and population</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def parseAF(bs):
+    &#34;&#34;&#34;Generate a dataframe from a given html page
+
+    Args:
+        bs (bs4.BeautifulSoup): BeautifulSoup object from allelefrequencies.net page
+
+    Returns:
+        pd.DataFrame: Table of allele, allele frequency, samplesize, and population
+    &#34;&#34;&#34;
+    # Get the results table from the div `divGenDetail`
+    tab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenDetail&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;tblNormal&#39;})
+    # Get the column headers from the first row of the table
+    columns = [
+        &#39;line&#39;, &#39;allele&#39;, &#39;flag&#39;, &#39;population&#39;, &#39;carriers%&#39;,
+        &#39;allele_freq&#39;, &#39;AF_graphic&#39;, &#39;sample_size&#39;, &#39;database&#39;,
+        &#39;distribution&#39;,&#39;haplotype_association&#39;, &#39;notes&#39;
+        ]
+    rows =[]
+    for row in tab.find_all(&#39;tr&#39;):
+        rows.append(
+            [td.get_text(strip=True) for td in row.find_all(&#39;td&#39;)]
+            )
+    # Make dataframe of table rows
+    # skip the first row as it&#39;s `th` headers
+    df = pd.DataFrame(rows[1:], columns = columns)
+
+    # Get HLA loci
+    df[&#39;loci&#39;] = df.allele.apply(lambda x: x.split(&#34;*&#34;)[0])
+
+    # Drop unwanted columns
+    df = df[[&#39;allele&#39;, &#39;loci&#39;, &#39;population&#39;, &#39;allele_freq&#39;, &#39;carriers%&#39;, &#39;sample_size&#39;]]
+    return df</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.plotAFprob"><code class="name flex">
+<span>def <span class="ident">plotAFprob</span></span>(<span>caf=Empty DataFrame
+Columns: []
+Index: [], AFtab=Empty DataFrame
+Columns: []
+Index: [], datasetID='population', concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[])</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Plot the posterior density function of all frequencies
+for all alleles based on concentration for Dirichlet
+distribution. Supply AFtab to add empirical values to plot.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>caf</code></strong> :&ensp;<code>pd.DataFrame</code>, optional</dt>
+<dd>Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().</dd>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code>, optional</dt>
+<dd>The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
+<dd>The column used to define datasets. Defaults to "population".</dd>
+<dt><strong><code>concentration</code></strong> :&ensp;<code>pd.Series</code>, optional</dt>
+<dd>Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False</dd>
+<dt><strong><code>log</code></strong> :&ensp;<code>bool</code>, optional</dt>
+<dd>Plot log pdf instead of pdf? Defaults to False.</dd>
+<dt><strong><code>psteps</code></strong> :&ensp;<code>int</code>, optional</dt>
+<dd>Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.</dd>
+<dt><strong><code>ncol</code></strong> :&ensp;<code>int</code>, optional</dt>
+<dd>How many columns to arrange subplots in. Defaults to 2.</dd>
+<dt><strong><code>xmin</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Set x axis min. Defaults to -0.05.</dd>
+<dt><strong><code>xmax</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Set x axis max. Defaults to 1.05.</dd>
+<dt><strong><code>ci</code></strong> :&ensp;<code>float</code>, optional</dt>
+<dd>Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.</dd>
+<dt><strong><code>alleles</code></strong> :&ensp;<code>list</code>, optional</dt>
+<dd>List of alleles to plot. Plots all if none supplied. Defaults to [].</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID=&#34;population&#34;, concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
+    &#34;&#34;&#34;Plot the posterior density function of all frequencies
+        for all alleles based on concentration for Dirichlet
+        distribution. Supply AFtab to add empirical values to plot.
+
+    Args:
+        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn&#39;t have the error checking that combineAF() has. Defaults to pd.DataFrame().
+        datasetID (str, optional): The column used to define datasets. Defaults to &#34;population&#34;.
+        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
+        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
+        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
+        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
+        xmin (float, optional): Set x axis min. Defaults to -0.05.
+        xmax (float, optional): Set x axis max. Defaults to 1.05.
+        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
+    &#34;&#34;&#34;
+    def allele_mask(alleles, concentration):
+        &#34;&#34;&#34;Create boolean mask either to keep only supplied `alleles`. If empty keep all.
+
+        Args:
+            alleles (list): list of alleles
+            concentration (list): Dirichlet concentration
+
+        Returns:
+            list: List of booleans to use as mask
+        &#34;&#34;&#34;
+        assert isinstance(alleles, list), f&#34;alleles must be a list, not {type(alleles)}&#34;
+        if not alleles:
+            mask = [True] * len(concentration)
+        else:
+            mask = caf.allele.isin(alleles)
+        return mask
+
+    if not concentration:
+        concentration = caf.alpha + caf.c
+    # Get beta parameters for each k in Dirichlet
+    ab = betaAB(concentration)
+    pline = np.linspace(0,1,psteps)
+    if not AFtab.empty:
+        # Format the population allele frequencies
+        df = AFtab.copy()
+        df = unmeasured_alleles(df, datasetID=datasetID)
+        df = df.sort_values(&#39;allele&#39;)
+        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), &#34;Alleles not matching between AFtab and caf&#34;
+    mask = allele_mask(alleles, concentration)
+    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
+    # Only indexes that pass the mask
+    masked_indexes = [i for i,x in enumerate(mask) if x]
+    for subploti,i in enumerate(masked_indexes):
+        subplotselector = subploti//ncol, subploti%ncol
+        a,b = ab[i]
+        bd = beta(a,b)
+        if log:
+            pdf = [bd.logpdf(p) for p in pline]
+        else:
+            with warnings.catch_warnings():
+                warnings.simplefilter(&#34;ignore&#34;)
+                pdf = [bd.pdf(p) for p in pline]
+        ax = axs[subplotselector]
+        ax.set_xlim(xmin,xmax)
+        if not AFtab.empty:
+            # Add the empirical allele frequency for each population
+            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
+                # x is the reported allele freq, y is it&#39;s pdf with scatter
+                if log:
+                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
+                else:
+                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
+        ax.plot(pline, pdf)
+        # Annotate with allele
+        if not caf.empty:
+            ax.text((xmax-xmin)/2, max(pdf)/2, f&#34;{caf.allele.iloc[i]}&#34;)
+        # Annotate with concentration
+        # ax.text(0.5, max(pdf)/3, f&#34;Concentration {round(concentration.iloc[i])}&#34;)
+        if not caf.empty:
+            # Plot the combined average
+            ax.axvline(caf.allele_freq[i], color=&#34;black&#34;, ls=&#34;--&#34;)
+        if ci:
+            cl,cu = betaCI(a,b, ci)
+            ax.axvline(cl, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
+            ax.axvline(cu, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
+        # fig.tight_layout()
+    plt.show()</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.population_coverage"><code class="name flex">
+<span>def <span class="ident">population_coverage</span></span>(<span>p)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Calculate the proportion of people with at least 1 copy of this allele
+assuming HWE.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>p</code></strong> :&ensp;<code>float</code></dt>
+<dd>Allele frequency</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>float</code></dt>
+<dd>Sum of homozygotes and heterozygotes for this allele</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def population_coverage(p):
+    &#34;&#34;&#34;Calculate the proportion of people with at least 1 copy of this allele
+        assuming HWE.
+
+    Args:
+        p (float): Allele frequency
+
+    Returns:
+        float: Sum of homozygotes and heterozygotes for this allele
+    &#34;&#34;&#34;
+    q = 1-p
+    homo = p**2
+    hetero = 2*p*q
+    return homo + hetero</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.single_loci"><code class="name flex">
+<span>def <span class="ident">single_loci</span></span>(<span>AFtab)</span>
+</code></dt>
+<dd>
+<div class="desc"><p>Check that allele frequency data is only of one locus</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Allele frequency data</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def single_loci(AFtab):
+    &#34;&#34;&#34;Check that allele frequency data is only of one locus
+
+    Args:
+        AFtab (pd.DataFrame): Allele frequency data
+    &#34;&#34;&#34;
+    assert len(AFtab.loci.unique()) == 1, f&#34;&#39;AFtab&#39; must conatain only 1 loci&#34;</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq.unmeasured_alleles"><code class="name flex">
+<span>def <span class="ident">unmeasured_alleles</span></span>(<span>AFtab, datasetID='population')</span>
+</code></dt>
+<dd>
+<div class="desc"><p>When combining AF estimates, unreported alleles can inflate frequencies
+so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.</p>
+<h2 id="args">Args</h2>
+<dl>
+<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
+<dd>Formatted allele frequency data</dd>
+<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
+<dd>Unique identifier column for study</dd>
+</dl>
+<h2 id="returns">Returns</h2>
+<dl>
+<dt><code>pd.DataFrame</code></dt>
+<dd>Allele frequency data with all locus alleles reported
+for each dataset</dd>
+</dl></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def unmeasured_alleles(AFtab, datasetID=&#39;population&#39;):
+    &#34;&#34;&#34;When combining AF estimates, unreported alleles can inflate frequencies
+        so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.
+
+    Args:
+        AFtab (pd.DataFrame): Formatted allele frequency data
+        datasetID (str): Unique identifier column for study
+
+    Returns:
+        pd.DataFrame: Allele frequency data with all locus alleles reported 
+            for each dataset
+    &#34;&#34;&#34;
+    df = AFtab.copy()
+    loci = df.loci.unique()
+    # Iterate over loci separately
+    for locus in loci:
+        # Iterate over each dataset reporting that locus
+        datasets = df[df.loci == locus][datasetID].unique()
+        for dataset in datasets:
+            # Single locus, single dataset
+            datasetAF = df[(df[datasetID] == dataset) &amp; (df.loci == locus)]
+            # What was the sample size for this data?
+            dataset_sample_size = datasetAF.sample_size.unique()
+            assert len(dataset_sample_size) == 1, &#34;dataset_sample_size must be 1, not %s&#34; %len(dataset_sample_size)
+            dataset_sample_size = dataset_sample_size[0]
+            # Get all alleles for this locus (across datasets)
+            ualleles = df[df.loci == locus].allele.unique()
+            # Which of these alleles are not in this dataset?
+            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
+            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
+            missing_rows = pd.DataFrame(missing_rows, columns=[&#39;allele&#39;,&#39;loci&#39;,datasetID,&#39;allele_freq&#39;,&#39;carriers%&#39;,&#39;sample_size&#39;])
+            # Add them in with zero frequency
+            df = pd.concat([df, missing_rows], ignore_index=True)
+    return df</code></pre>
+</details>
+</dd>
+</dl>
+</section>
+<section>
+</section>
+</article>
+<nav id="sidebar">
+<h1>Index</h1>
+<div class="toc">
+<ul></ul>
+</div>
+<ul id="index">
+<li><h3>Super-module</h3>
+<ul>
+<li><code><a title="HLAfreq" href="index.html">HLAfreq</a></code></li>
+</ul>
+</li>
+<li><h3><a href="#header-functions">Functions</a></h3>
+<ul class="">
+<li><code><a title="HLAfreq.HLAfreq.AFci" href="#HLAfreq.HLAfreq.AFci">AFci</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.Npages" href="#HLAfreq.HLAfreq.Npages">Npages</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.alleles_unique_in_study" href="#HLAfreq.HLAfreq.alleles_unique_in_study">alleles_unique_in_study</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.betaAB" href="#HLAfreq.HLAfreq.betaAB">betaAB</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.betaCI" href="#HLAfreq.HLAfreq.betaCI">betaCI</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.check_resolution" href="#HLAfreq.HLAfreq.check_resolution">check_resolution</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.collapse_reduced_alleles" href="#HLAfreq.HLAfreq.collapse_reduced_alleles">collapse_reduced_alleles</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.combineAF" href="#HLAfreq.HLAfreq.combineAF">combineAF</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.decrease_resolution" href="#HLAfreq.HLAfreq.decrease_resolution">decrease_resolution</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.default_prior" href="#HLAfreq.HLAfreq.default_prior">default_prior</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.duplicated_sample_size" href="#HLAfreq.HLAfreq.duplicated_sample_size">duplicated_sample_size</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.getAFdata" href="#HLAfreq.HLAfreq.getAFdata">getAFdata</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.id_duplicated_allele" href="#HLAfreq.HLAfreq.id_duplicated_allele">id_duplicated_allele</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.incomplete_studies" href="#HLAfreq.HLAfreq.incomplete_studies">incomplete_studies</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.makeURL" href="#HLAfreq.HLAfreq.makeURL">makeURL</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.only_complete" href="#HLAfreq.HLAfreq.only_complete">only_complete</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.parseAF" href="#HLAfreq.HLAfreq.parseAF">parseAF</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.plotAFprob" href="#HLAfreq.HLAfreq.plotAFprob">plotAFprob</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.population_coverage" href="#HLAfreq.HLAfreq.population_coverage">population_coverage</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.single_loci" href="#HLAfreq.HLAfreq.single_loci">single_loci</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq.unmeasured_alleles" href="#HLAfreq.HLAfreq.unmeasured_alleles">unmeasured_alleles</a></code></li>
+</ul>
+</li>
+</ul>
+</nav>
+</main>
+<footer id="footer">
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.8.1</a>.</p>
+</footer>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
+<script>hljs.initHighlightingOnLoad()</script>
+</body>
+</html>
\ No newline at end of file
diff --git a/docs/HLAfreq/HLAfreq_data.html b/docs/HLAfreq/HLAfreq_data.html
new file mode 100644
index 0000000..6daf4b7
--- /dev/null
+++ b/docs/HLAfreq/HLAfreq_data.html
@@ -0,0 +1,109 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
+<meta name="generator" content="pdoc 0.8.1" />
+<title>HLAfreq.HLAfreq_data API documentation</title>
+<meta name="description" content="Data loaders" />
+<link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
+<link href='https://cdnjs.cloudflare.com/ajax/libs/10up-sanitize.css/8.0.0/sanitize.min.css' rel='stylesheet'>
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+<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}#sidebar > *:last-child{margin-bottom:2cm}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{margin-top:.6em;font-weight:bold}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
+<style media="screen and (min-width: 700px)">@media screen and (min-width:700px){#sidebar{width:30%;height:100vh;overflow:auto;position:sticky;top:0}#content{width:70%;max-width:100ch;padding:3em 4em;border-left:1px solid #ddd}pre code{font-size:1em}.item .name{font-size:1em}main{display:flex;flex-direction:row-reverse;justify-content:flex-end}.toc ul ul,#index ul{padding-left:1.5em}.toc > ul > li{margin-top:.5em}}</style>
+<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
+</head>
+<body>
+<main>
+<article id="content">
+<header>
+<h1 class="title">Module <code>HLAfreq.HLAfreq_data</code></h1>
+</header>
+<section id="section-intro">
+<p>Data loaders</p>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">&#34;&#34;&#34;
+Data loaders
+&#34;&#34;&#34;
+import pkg_resources
+import pandas as pd
+
+def load_countries():
+    stream = pkg_resources.resource_stream(__name__, &#39;data/countries.csv&#39;)
+    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)
+
+def load_HLA1supertypes_Sidney2008():
+    stream = pkg_resources.resource_stream(__name__, &#39;data/HLA1supertypes_Sidney2008.csv&#39;)
+    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
+</details>
+</section>
+<section>
+</section>
+<section>
+</section>
+<section>
+<h2 class="section-title" id="header-functions">Functions</h2>
+<dl>
+<dt id="HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008"><code class="name flex">
+<span>def <span class="ident">load_HLA1supertypes_Sidney2008</span></span>(<span>)</span>
+</code></dt>
+<dd>
+<div class="desc"></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def load_HLA1supertypes_Sidney2008():
+    stream = pkg_resources.resource_stream(__name__, &#39;data/HLA1supertypes_Sidney2008.csv&#39;)
+    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
+</details>
+</dd>
+<dt id="HLAfreq.HLAfreq_data.load_countries"><code class="name flex">
+<span>def <span class="ident">load_countries</span></span>(<span>)</span>
+</code></dt>
+<dd>
+<div class="desc"></div>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def load_countries():
+    stream = pkg_resources.resource_stream(__name__, &#39;data/countries.csv&#39;)
+    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
+</details>
+</dd>
+</dl>
+</section>
+<section>
+</section>
+</article>
+<nav id="sidebar">
+<h1>Index</h1>
+<div class="toc">
+<ul></ul>
+</div>
+<ul id="index">
+<li><h3>Super-module</h3>
+<ul>
+<li><code><a title="HLAfreq" href="index.html">HLAfreq</a></code></li>
+</ul>
+</li>
+<li><h3><a href="#header-functions">Functions</a></h3>
+<ul class="">
+<li><code><a title="HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008" href="#HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008">load_HLA1supertypes_Sidney2008</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq_data.load_countries" href="#HLAfreq.HLAfreq_data.load_countries">load_countries</a></code></li>
+</ul>
+</li>
+</ul>
+</nav>
+</main>
+<footer id="footer">
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.8.1</a>.</p>
+</footer>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
+<script>hljs.initHighlightingOnLoad()</script>
+</body>
+</html>
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diff --git a/docs/HLAfreq/index.html b/docs/HLAfreq/index.html
new file mode 100644
index 0000000..d0f83df
--- /dev/null
+++ b/docs/HLAfreq/index.html
@@ -0,0 +1,71 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
+<meta name="generator" content="pdoc 0.8.1" />
+<title>HLAfreq API documentation</title>
+<meta name="description" content="" />
+<link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
+<link href='https://cdnjs.cloudflare.com/ajax/libs/10up-sanitize.css/8.0.0/sanitize.min.css' rel='stylesheet'>
+<link href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/styles/github.min.css" rel="stylesheet">
+<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}#sidebar > *:last-child{margin-bottom:2cm}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{margin-top:.6em;font-weight:bold}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
+<style media="screen and (min-width: 700px)">@media screen and (min-width:700px){#sidebar{width:30%;height:100vh;overflow:auto;position:sticky;top:0}#content{width:70%;max-width:100ch;padding:3em 4em;border-left:1px solid #ddd}pre code{font-size:1em}.item .name{font-size:1em}main{display:flex;flex-direction:row-reverse;justify-content:flex-end}.toc ul ul,#index ul{padding-left:1.5em}.toc > ul > li{margin-top:.5em}}</style>
+<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
+</head>
+<body>
+<main>
+<article id="content">
+<header>
+<h1 class="title">Package <code>HLAfreq</code></h1>
+</header>
+<section id="section-intro">
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">from .HLAfreq import *</code></pre>
+</details>
+</section>
+<section>
+<h2 class="section-title" id="header-submodules">Sub-modules</h2>
+<dl>
+<dt><code class="name"><a title="HLAfreq.HLAfreq" href="HLAfreq.html">HLAfreq.HLAfreq</a></code></dt>
+<dd>
+<div class="desc"><p>HLAfreq …</p></div>
+</dd>
+<dt><code class="name"><a title="HLAfreq.HLAfreq_data" href="HLAfreq_data.html">HLAfreq.HLAfreq_data</a></code></dt>
+<dd>
+<div class="desc"><p>Data loaders</p></div>
+</dd>
+</dl>
+</section>
+<section>
+</section>
+<section>
+</section>
+<section>
+</section>
+</article>
+<nav id="sidebar">
+<h1>Index</h1>
+<div class="toc">
+<ul></ul>
+</div>
+<ul id="index">
+<li><h3><a href="#header-submodules">Sub-modules</a></h3>
+<ul>
+<li><code><a title="HLAfreq.HLAfreq" href="HLAfreq.html">HLAfreq.HLAfreq</a></code></li>
+<li><code><a title="HLAfreq.HLAfreq_data" href="HLAfreq_data.html">HLAfreq.HLAfreq_data</a></code></li>
+</ul>
+</li>
+</ul>
+</nav>
+</main>
+<footer id="footer">
+<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.8.1</a>.</p>
+</footer>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
+<script>hljs.initHighlightingOnLoad()</script>
+</body>
+</html>
\ No newline at end of file

From 48f0b8d5fccfd5cf9ca5879362fce0d27758108f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:11:59 +0100
Subject: [PATCH 063/192] Add sample_year and sample_size to makeURL

---
 src/HLAfreq/HLAfreq.py | 19 +++++++++++++++----
 1 file changed, 15 insertions(+), 4 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 5b05f09..5b7c6fd 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -27,10 +27,13 @@ def makeURL(
         region="",
         ethnic="",
         study_type="",
-        dataset_source=""
+        dataset_source="",
+        sample_year="",
+        sample_year_pattern="",
+        sample_size="",
+        sample_size_pattern=""
     ):
-    """Create URL for search of allele frequency net database. All arguments are documented [here](www.allelefrequencies.net/extaccess.asp)
-
+    """Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
     Args:
         country (str, optional): Country name to retrieve records from. Defaults to "".
         standard (str, optional): Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
@@ -41,6 +44,10 @@ def makeURL(
         ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to "".
         study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
         dataset_source (str, optional): Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
+        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".
+        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
+        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".
+        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
 
     Returns:
         str: URL to search allelefrequencies.net
@@ -53,10 +60,14 @@ def makeURL(
     ethnic = "hla_ethnic=%s&" %(ethnic)
     study_type = "hla_study=%s&" %(study_type)
     dataset_source = "hla_dataset_source=%s&" %(dataset_source)
+    sample_year = "hla_sample_year=%s&" %(sample_year)
+    sample_year_pattern = "hla_sample_year_pattern=%s&" %(sample_year_pattern)
+    sample_size = "hla_sample_size=%s&" %(sample_size)
+    sample_size_pattern = "hla_sample_size_pattern=%s&" %(sample_size_pattern)
     hla_level_pattern = "hla_level_pattern=%s&" %(resolution_pattern)
     hla_level = "hla_level=%s&" %(resolution)
     standard = "standard=%s&" %standard
-    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source
+    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
     return url
 
 def parseAF(bs):

From 3b4023122a8a5484262c4127c347544aa235abac Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:26:06 +0100
Subject: [PATCH 064/192] Change docs to markdown

---
 docs/HLAfreq.md                |  808 +++++++++++++++
 docs/HLAfreq/HLAfreq.html      | 1771 --------------------------------
 docs/HLAfreq/HLAfreq_data.html |  109 --
 docs/HLAfreq/index.html        |   71 --
 4 files changed, 808 insertions(+), 1951 deletions(-)
 create mode 100644 docs/HLAfreq.md
 delete mode 100644 docs/HLAfreq/HLAfreq.html
 delete mode 100644 docs/HLAfreq/HLAfreq_data.html
 delete mode 100644 docs/HLAfreq/index.html

diff --git a/docs/HLAfreq.md b/docs/HLAfreq.md
new file mode 100644
index 0000000..ca11030
--- /dev/null
+++ b/docs/HLAfreq.md
@@ -0,0 +1,808 @@
+---
+description: |
+    API documentation for modules: HLAfreq, HLAfreq.HLAfreq, HLAfreq.HLAfreq_data.
+
+lang: en
+
+classoption: oneside
+geometry: margin=1in
+papersize: a4
+
+linkcolor: blue
+links-as-notes: true
+...
+
+
+    
+# Module `HLAfreq` {#HLAfreq}
+
+
+
+
+    
+## Sub-modules
+
+* [HLAfreq.HLAfreq](#HLAfreq.HLAfreq)
+* [HLAfreq.HLAfreq_data](#HLAfreq.HLAfreq_data)
+
+
+
+
+
+
+    
+# Module `HLAfreq.HLAfreq` {#HLAfreq.HLAfreq}
+
+HLAfreq
+
+Download allele frequency data from
+[allelefrequencies.net](www.allelefrequencies.net). Allele
+frequencies from different populations can be combined to
+estimate HLA frequencies of countries or other regions such as
+global HLA frequencies.
+
+
+
+
+    
+## Functions
+
+
+    
+### Function `AFci` {#HLAfreq.HLAfreq.AFci}
+
+
+
+    
+> `def AFci(caf, credible_interval=0.95)`
+
+
+Calculate credible interval for combined allele frequency table
+
+
+###### Args
+
+**```caf```** :&ensp;<code>pd.DataFrame</code>
+:   Table produced by combineAF()
+
+
+**```credible_interval```** :&ensp;<code>float</code>, optional
+:   The desired confidence interval. Defaults to 0.95.
+
+
+
+###### Returns
+
+<code>list</code>
+:   Lower and upper credible intervals as a list of tuples
+
+
+
+    
+### Function `Npages` {#HLAfreq.HLAfreq.Npages}
+
+
+
+    
+> `def Npages(bs)`
+
+
+How many pages of results are there?
+
+
+###### Args
+
+**```bs```** :&ensp;<code>bs4.BeautifulSoup</code>
+:   BS object of allelefrequencies.net results page
+
+
+
+###### Returns
+
+<code>int</code>
+:   Total number of results pages
+
+
+
+    
+### Function `alleles_unique_in_study` {#HLAfreq.HLAfreq.alleles_unique_in_study}
+
+
+
+    
+> `def alleles_unique_in_study(AFtab, datasetID='population')`
+
+
+Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by <code>datasetID</code>.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Allele frequency data
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   Unique identifier column to define study. Defaults to 'population'.
+
+
+
+###### Returns
+
+<code>bool</code>
+:   <code>True</code> on if no alleles occur more than once in any study, otherwise <code>False</code>.
+
+
+
+    
+### Function `betaAB` {#HLAfreq.HLAfreq.betaAB}
+
+
+
+    
+> `def betaAB(alpha)`
+
+
+Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
+
+
+###### Args
+
+**```alpha```** :&ensp;<code>list</code>
+:   Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
+
+
+
+###### Returns
+
+<code>list</code>
+:   List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.
+
+
+
+    
+### Function `betaCI` {#HLAfreq.HLAfreq.betaCI}
+
+
+
+    
+> `def betaCI(a, b, credible_interval=0.95)`
+
+
+Calculat the central credible interval of a beta distribution
+
+
+###### Args
+
+**```a```** :&ensp;<code>float</code>
+:   Beta shape parameter <code>a</code>, i.e. the number of times the allele was observed.
+
+
+**```b```** :&ensp;<code>float</code>
+:   Beta shape parameter <code>b</code>, i.e. the number of times the allele was not observed.
+
+
+**```credible_interval```** :&ensp;<code>float</code>, optional
+:   The size of the credible interval requested. Defaults to 0.95.
+
+
+
+###### Returns
+
+<code>tuple</code>
+:   Lower and upper credible interval of beta distribution.
+
+
+
+    
+### Function `check_resolution` {#HLAfreq.HLAfreq.check_resolution}
+
+
+
+    
+> `def check_resolution(AFtab)`
+
+
+Check if all alleles in AFtab have the same resolution.
+Will print the number of records with each resolution.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Allele frequency data
+
+
+
+###### Returns
+
+<code>bool</code>
+:   True only if all alleles have the same resolution, else False.
+
+
+
+    
+### Function `collapse_reduced_alleles` {#HLAfreq.HLAfreq.collapse_reduced_alleles}
+
+
+
+    
+> `def collapse_reduced_alleles(AFtab, datasetID='population')`
+
+
+
+
+    
+### Function `combineAF` {#HLAfreq.HLAfreq.combineAF}
+
+
+
+    
+> `def combineAF(AFtab, weights='2n', alpha=[], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True)`
+
+
+Combine allele frequencies from multiple studies. <code>datasetID</code> is the unique identifier for studies to combine.
+Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+Sample size is doubled to get <code>2n</code> due to diploidy. If an alternative <code>weights</code> is set it is not doubled.
+The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior <code>alpha</code>.
+If <code>alpha</code> is not set the prior defaults to 1 observation of each allele.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Table of Allele frequency data
+
+
+**```weights```** :&ensp;<code>str</code>, optional
+:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+
+
+**```alpha```** :&ensp;<code>list</code>, optional
+:   Prior to use for Dirichlet distribution. Defaults to [].
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   Unique identifier column for study. Defaults to 'population'.
+
+
+**```format```** :&ensp;<code>bool</code>, optional
+:   Run <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>. Defaults to True.
+
+
+**```ignoreG```** :&ensp;<code>bool</code>, optional
+:   Treat allele G groups as normal, see <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>. Defaults to True.
+
+
+**```add_unmeasured```** :&ensp;<code>bool</code>, optional
+:   Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See <code>add\_unmeasured()</code>. Defaults to True.
+
+
+**```complete```** :&ensp;<code>bool</code>, optional
+:   Check study completeness. Uses default values for <code>[incomplete\_studies()](#HLAfreq.HLAfreq.incomplete\_studies "HLAfreq.HLAfreq.incomplete\_studies")</code>. If you are happy with your study completeness can be switched off with False. Defaults to True.
+
+
+**```resolution```** :&ensp;<code>bool</code>, optional
+:   Check that all alleles have the same resolution, see <code>[check\_resolution()](#HLAfreq.HLAfreq.check\_resolution "HLAfreq.HLAfreq.check\_resolution")</code>. Defaults to True.
+
+
+**```unique```** :&ensp;<code>bool</code>, optional
+:   Check that each allele appears no more than once per study. See <code>[alleles\_unique\_in\_study()](#HLAfreq.HLAfreq.alleles\_unique\_in\_study "HLAfreq.HLAfreq.alleles\_unique\_in\_study")</code>. Defaults to True.
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   Allele frequencies after combining estimates from all studies.
+
+
+*allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is <code>alpha</code> + <code>c</code>.
+*alpha* is the prior used for the Dirichlet distribution.
+*c* is the observations used for the Dirichlet distribution.
+*sample_size* is the total sample size of all combined studies.
+*wav* is the weighted average.
+
+    
+### Function `decrease_resolution` {#HLAfreq.HLAfreq.decrease_resolution}
+
+
+
+    
+> `def decrease_resolution(AFtab, newres, datasetID='population')`
+
+
+Decrease allele resolution to a specified value so all alleles have the same resolution.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Allele frequency data.
+
+
+**```newres```** :&ensp;<code>int</code>
+:   The desired number of fields for resolution.
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   Column to use as stud identifier. Defaults to 'population'.
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   Allele frequency data with all alleles of requested resolution.
+
+
+
+    
+### Function `default_prior` {#HLAfreq.HLAfreq.default_prior}
+
+
+
+    
+> `def default_prior(k)`
+
+
+Calculate a default prior, 1 observation of each class.
+
+
+###### Args
+
+**```k```** :&ensp;<code>int</code>
+:   Number of classes in the Dirichlet distribution.
+
+
+
+###### Returns
+
+<code>list</code>
+:   List of k 1s to use as prior.
+
+
+
+    
+### Function `duplicated_sample_size` {#HLAfreq.HLAfreq.duplicated_sample_size}
+
+
+
+    
+> `def duplicated_sample_size(AFtab)`
+
+
+Returns True if any loci has more than 1 unique sample size
+
+    
+### Function `formatAF` {#HLAfreq.HLAfreq.formatAF}
+
+
+
+    
+> `def formatAF(AFtab, ignoreG=True)`
+
+
+Format allele frequency table.
+Convert sample_size and allele_freq to numeric data type.
+Removes commas from sample size. Removes "(*)" from allele frequency if 
+<code>ignoreG</code> is <code>True</code>. <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code> is used internally by combineAF and getAFdata by default.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Allele frequency data downloaded from allelefrequency.net using <code>[getAFdata()](#HLAfreq.HLAfreq.getAFdata "HLAfreq.HLAfreq.getAFdata")</code>.
+
+
+**```ignoreG```** :&ensp;<code>bool</code>, optional
+:   Treat G group alleles as normal. See <http://hla.alleles.org/alleles/g_groups.html> for details. Defaults to True.
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   The formatted allele frequency data.
+
+
+
+    
+### Function `getAFdata` {#HLAfreq.HLAfreq.getAFdata}
+
+
+
+    
+> `def getAFdata(base_url, format=True, ignoreG=True)`
+
+
+Get all allele frequency data from a search base url. Iterates over all
+    pages regardless of which page is based.
+
+
+###### Args
+
+**```base_url```** :&ensp;<code>str</code>
+:   URL for base search.
+
+
+**```format```** :&ensp;<code>bool</code>
+:   Format the downloaded data using <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>.
+
+
+**```ignoreG```** :&ensp;<code>bool</code>
+:   treat allele G groups as normal. See <http://hla.alleles.org/alleles/g_groups.html> for details. Default = True
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   allele frequency data parsed into a pandas dataframe
+
+
+
+    
+### Function `id_duplicated_allele` {#HLAfreq.HLAfreq.id_duplicated_allele}
+
+
+
+    
+> `def id_duplicated_allele(grouped)`
+
+
+Reports the allele that has mupltiple sample sizes
+
+    
+### Function `incomplete_studies` {#HLAfreq.HLAfreq.incomplete_studies}
+
+
+
+    
+> `def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population')`
+
+
+Report any studies with allele freqs that don't sum to 1
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Dataframe containing multiple studies
+
+
+**```llimit```** :&ensp;<code>float</code>, optional
+:   Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+
+
+**```ulimit```** :&ensp;<code>float</code>, optional
+:   Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+
+
+**```datasetID```** :&ensp;<code>str</code>
+:   Unique identifier column for study
+
+
+
+    
+### Function `makeURL` {#HLAfreq.HLAfreq.makeURL}
+
+
+
+    
+> `def makeURL(country='', standard='s', locus='', resolution_pattern='bigger_equal_than', resolution=2, region='', ethnic='', study_type='', dataset_source='', sample_year='', sample_year_pattern='', sample_size='', sample_size_pattern='')`
+
+
+Create URL for search of allele frequency net database. All arguments are documented [here](<http://www.allelefrequencies.net/extaccess.asp>)
+
+###### Args
+
+**```country```** :&ensp;<code>str</code>, optional
+:   Country name to retrieve records from. Defaults to "".
+
+
+**```standard```** :&ensp;<code>str</code>, optional
+:   Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
+
+
+**```locus```** :&ensp;<code>str</code>, optional
+:   The locus to return allele data for. Defaults to "".
+
+
+**```resolution_pattern```** :&ensp;<code>str</code>, optional
+:   Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using <code>resolution</code> and <code>resolution\_pattern</code>. Defaults to "bigger_equal_than".
+
+
+**```resolution```** :&ensp;<code>int</code>, optional
+:   Number of fields of resolution of allele. Filter created using <code>resolution</code> and <code>resolution\_pattern</code>. Defaults to 2.
+
+
+**```region```** :&ensp;<code>str</code>, optional
+:   Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](<http://www.allelefrequencies.net/pop6003a.asp>). Defaults to "".
+
+
+**```ethnic```** :&ensp;<code>str</code>, optional
+:   Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}. All ethnicities listed [here](<http://www.allelefrequencies.net/pop6003a.asp>). Defaults to "".
+
+
+**```study_type```** :&ensp;<code>str</code>, optional
+:   Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
+
+
+**```dataset_source```** :&ensp;<code>str</code>, optional
+:   Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
+
+
+**```sample_year```** :&ensp;<code>int</code>, optional
+:   Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".
+
+
+**```sample_year_pattern```** :&ensp;<code>str</code>, optional
+:   Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
+
+
+**```sample_size```** :&ensp;<code>int</code>, optional
+:   Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".
+
+
+**```sample_size_pattern```** :&ensp;<code>str</code>, optional
+:   Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
+
+
+
+###### Returns
+
+<code>str</code>
+:   URL to search allelefrequencies.net
+
+
+
+    
+### Function `only_complete` {#HLAfreq.HLAfreq.only_complete}
+
+
+
+    
+> `def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population')`
+
+
+Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+This prevents throwing away data if another loci in the population is incomplete
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Dataframe containing multiple studies
+
+
+**```llimit```** :&ensp;<code>float</code>, optional
+:   Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
+
+
+**```ulimit```** :&ensp;<code>float</code>, optional
+:   Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+
+
+**```datasetID```** :&ensp;<code>str</code>
+:   Unique identifier column for study. Defaults to 'population'.
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   Allele frequency data of multiple studies, but only complete studies.
+
+
+
+    
+### Function `parseAF` {#HLAfreq.HLAfreq.parseAF}
+
+
+
+    
+> `def parseAF(bs)`
+
+
+Generate a dataframe from a given html page
+
+
+###### Args
+
+**```bs```** :&ensp;<code>bs4.BeautifulSoup</code>
+:   BeautifulSoup object from allelefrequencies.net page
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   Table of allele, allele frequency, samplesize, and population
+
+
+
+    
+### Function `plotAFprob` {#HLAfreq.HLAfreq.plotAFprob}
+
+
+
+    
+> `def plotAFprob(caf=Empty DataFrame
+Columns: []
+Index: [], AFtab=Empty DataFrame
+Columns: []
+Index: [], datasetID='population', concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[])`
+
+
+Plot the posterior density function of all frequencies
+    for all alleles based on concentration for Dirichlet
+    distribution. Supply AFtab to add empirical values to plot.
+
+
+###### Args
+
+**```caf```** :&ensp;<code>pd.DataFrame</code>, optional
+:   Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
+
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>, optional
+:   The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   The column used to define datasets. Defaults to "population".
+
+
+**```concentration```** :&ensp;<code>pd.Series</code>, optional
+:   Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
+
+
+**```log```** :&ensp;<code>bool</code>, optional
+:   Plot log pdf instead of pdf? Defaults to False.
+
+
+**```psteps```** :&ensp;<code>int</code>, optional
+:   Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
+
+
+**```ncol```** :&ensp;<code>int</code>, optional
+:   How many columns to arrange subplots in. Defaults to 2.
+
+
+**```xmin```** :&ensp;<code>float</code>, optional
+:   Set x axis min. Defaults to -0.05.
+
+
+**```xmax```** :&ensp;<code>float</code>, optional
+:   Set x axis max. Defaults to 1.05.
+
+
+**```ci```** :&ensp;<code>float</code>, optional
+:   Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+
+
+**```alleles```** :&ensp;<code>list</code>, optional
+:   List of alleles to plot. Plots all if none supplied. Defaults to [].
+
+
+
+    
+### Function `population_coverage` {#HLAfreq.HLAfreq.population_coverage}
+
+
+
+    
+> `def population_coverage(p)`
+
+
+Calculate the proportion of people with at least 1 copy of this allele
+    assuming HWE.
+
+
+###### Args
+
+**```p```** :&ensp;<code>float</code>
+:   Allele frequency
+
+
+
+###### Returns
+
+<code>float</code>
+:   Sum of homozygotes and heterozygotes for this allele
+
+
+
+    
+### Function `single_loci` {#HLAfreq.HLAfreq.single_loci}
+
+
+
+    
+> `def single_loci(AFtab)`
+
+
+Check that allele frequency data is only of one locus
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Allele frequency data
+
+
+
+    
+### Function `unmeasured_alleles` {#HLAfreq.HLAfreq.unmeasured_alleles}
+
+
+
+    
+> `def unmeasured_alleles(AFtab, datasetID='population')`
+
+
+When combining AF estimates, unreported alleles can inflate frequencies
+    so AF sums to >1. Therefore we add unreported alleles with frequency zero.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Formatted allele frequency data
+
+
+**```datasetID```** :&ensp;<code>str</code>
+:   Unique identifier column for study
+
+
+
+###### Returns
+
+<code>pd.DataFrame</code>
+:   Allele frequency data with all locus alleles reported 
+    for each dataset
+
+
+
+
+
+
+    
+# Module `HLAfreq.HLAfreq_data` {#HLAfreq.HLAfreq_data}
+
+Data loaders
+
+
+
+
+    
+## Functions
+
+
+    
+### Function `load_HLA1supertypes_Sidney2008` {#HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008}
+
+
+
+    
+> `def load_HLA1supertypes_Sidney2008()`
+
+
+
+
+    
+### Function `load_countries` {#HLAfreq.HLAfreq_data.load_countries}
+
+
+
+    
+> `def load_countries()`
+
+
+
+
+
+
+-----
+Generated by *pdoc* 0.8.1 (<https://pdoc3.github.io>).
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-<article id="content">
-<header>
-<h1 class="title">Module <code>HLAfreq.HLAfreq</code></h1>
-</header>
-<section id="section-intro">
-<p>HLAfreq</p>
-<p>Download allele frequency data from
-<a href="www.allelefrequencies.net">allelefrequencies.net</a>. Allele
-frequencies from different populations can be combined to
-estimate HLA frequencies of countries or other regions such as
-global HLA frequencies.</p>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">&#34;&#34;&#34;
-HLAfreq
-
-Download allele frequency data from
-[allelefrequencies.net](www.allelefrequencies.net). Allele
-frequencies from different populations can be combined to
-estimate HLA frequencies of countries or other regions such as
-global HLA frequencies.
-&#34;&#34;&#34;
-
-from bs4 import BeautifulSoup
-import requests
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import math
-from scipy.stats import dirichlet, beta
-import logging
-import warnings
-
-def makeURL(
-        country=&#34;&#34;,
-        standard=&#39;s&#39;,
-        locus=&#34;&#34;,
-        resolution_pattern=&#34;bigger_equal_than&#34;,
-        resolution=2,
-        region=&#34;&#34;,
-        ethnic=&#34;&#34;,
-        study_type=&#34;&#34;,
-        dataset_source=&#34;&#34;,
-        sample_year=&#34;&#34;,
-        sample_year_pattern=&#34;&#34;,
-        sample_size=&#34;&#34;,
-        sample_size_pattern=&#34;&#34;
-    ):
-    &#34;&#34;&#34;Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
-    Args:
-        country (str, optional): Country name to retrieve records from. Defaults to &#34;&#34;.
-        standard (str, optional): Filter study quality standard to this or higher. {&#39;g&#39;, &#39;s&#39;, &#39;a&#39;} Gold, silver, all. Defaults to &#39;s&#39;.
-        locus (str, optional): The locus to return allele data for. Defaults to &#34;&#34;.
-        resolution_pattern (str, optional): Resolution comparitor {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Filter created using `resolution` and `resolution_pattern`. Defaults to &#34;bigger_equal_than&#34;.
-        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
-        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
-        ethnic (str, optional): Filter to ethnicity. {&#34;Amerindian&#34;, &#34;Black&#34;, &#34;Caucasian&#34;, ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
-        study_type (str, optional): Type of study. {&#34;Anthropology&#34;, &#34;Blood+Donor&#34;, &#34;Bone+Marrow+Registry&#34;, &#34;Controls+for+Disease+Study&#34;, &#34;Disease+Study+Patients&#34;, &#34;Other&#34;, &#34;Solid+Organd+Unrelated+Donors&#34;, &#34;Stem+cell+donors&#34;}. Defaults to &#34;&#34;.
-        dataset_source (str, optional): Source of data. {&#34;Literature&#34;, &#34;Proceedings+of+IHWs&#34;, &#34;Unpublished&#34;}. Defaults to &#34;&#34;.
-        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to &#34;&#34;.
-        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
-        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to &#34;&#34;.
-        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
-
-    Returns:
-        str: URL to search allelefrequencies.net
-    &#34;&#34;&#34;
-    base = &#34;http://www.allelefrequencies.net/hla6006a.asp?&#34;
-    locus_type = &#34;hla_locus_type=Classical&amp;&#34;
-    hla_locus = &#34;hla_locus=%s&amp;&#34; %(locus)
-    country = &#34;hla_country=%s&amp;&#34; %(country)
-    region = &#34;hla_region=%s&amp;&#34; %(region)
-    ethnic = &#34;hla_ethnic=%s&amp;&#34; %(ethnic)
-    study_type = &#34;hla_study=%s&amp;&#34; %(study_type)
-    dataset_source = &#34;hla_dataset_source=%s&amp;&#34; %(dataset_source)
-    sample_year = &#34;hla_sample_year=%s&amp;&#34; %(sample_year)
-    sample_year_pattern = &#34;hla_sample_year_pattern=%s&amp;&#34; %(sample_year_pattern)
-    sample_size = &#34;hla_sample_size=%s&amp;&#34; %(sample_size)
-    sample_size_pattern = &#34;hla_sample_size_pattern=%s&amp;&#34; %(sample_size_pattern)
-    hla_level_pattern = &#34;hla_level_pattern=%s&amp;&#34; %(resolution_pattern)
-    hla_level = &#34;hla_level=%s&amp;&#34; %(resolution)
-    standard = &#34;standard=%s&amp;&#34; %standard
-    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
-    return url
-
-def parseAF(bs):
-    &#34;&#34;&#34;Generate a dataframe from a given html page
-
-    Args:
-        bs (bs4.BeautifulSoup): BeautifulSoup object from allelefrequencies.net page
-
-    Returns:
-        pd.DataFrame: Table of allele, allele frequency, samplesize, and population
-    &#34;&#34;&#34;
-    # Get the results table from the div `divGenDetail`
-    tab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenDetail&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;tblNormal&#39;})
-    # Get the column headers from the first row of the table
-    columns = [
-        &#39;line&#39;, &#39;allele&#39;, &#39;flag&#39;, &#39;population&#39;, &#39;carriers%&#39;,
-        &#39;allele_freq&#39;, &#39;AF_graphic&#39;, &#39;sample_size&#39;, &#39;database&#39;,
-        &#39;distribution&#39;,&#39;haplotype_association&#39;, &#39;notes&#39;
-        ]
-    rows =[]
-    for row in tab.find_all(&#39;tr&#39;):
-        rows.append(
-            [td.get_text(strip=True) for td in row.find_all(&#39;td&#39;)]
-            )
-    # Make dataframe of table rows
-    # skip the first row as it&#39;s `th` headers
-    df = pd.DataFrame(rows[1:], columns = columns)
-
-    # Get HLA loci
-    df[&#39;loci&#39;] = df.allele.apply(lambda x: x.split(&#34;*&#34;)[0])
-
-    # Drop unwanted columns
-    df = df[[&#39;allele&#39;, &#39;loci&#39;, &#39;population&#39;, &#39;allele_freq&#39;, &#39;carriers%&#39;, &#39;sample_size&#39;]]
-    return df
-   
-def Npages(bs):
-    &#34;&#34;&#34;How many pages of results are there?
-
-    Args:
-        bs (bs4.BeautifulSoup): BS object of allelefrequencies.net results page
-
-    Returns:
-        int: Total number of results pages
-    &#34;&#34;&#34;
-    # Get the table with number of pages
-    navtab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenNavig&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;table10&#39;})
-    assert navtab, f&#34;navtab does not evaluate to True. Check URL returns results in web browser.&#34;
-    # Get cell with &#39; of &#39; in 
-    pagesOfN = [td.get_text(strip=True) for td in navtab.find_all(&#39;td&#39;) if &#34; of &#34; in td.text]
-    # Check single cell returned
-    assert len(pagesOfN) == 1, &#34;divGenNavig should contain 1 of not %s&#34; %len(pagesOfN)
-    # Get total number of pages
-    N = pagesOfN[0].split(&#34;of &#34;)[1]
-    N = int(N)
-    return N
-
-def formatAF(AFtab, ignoreG=True):
-    &#34;&#34;&#34;Format allele frequency table.
-    Convert sample_size and allele_freq to numeric data type.
-    Removes commas from sample size. Removes &#34;(*)&#34; from allele frequency if 
-    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
-        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
-
-    Returns:
-        pd.DataFrame: The formatted allele frequency data.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    if df.sample_size.dtype == &#34;O&#34;:
-        df.sample_size = pd.to_numeric(df.sample_size.str.replace(&#34;,&#34;, &#34;&#34;))
-    if df.allele_freq.dtype == &#34;O&#34;:
-        if ignoreG:
-            df.allele_freq = df.allele_freq.str.replace(&#34;(*)&#34;, &#34;&#34;, regex=False)
-        df.allele_freq = pd.to_numeric(df.allele_freq)
-    return df
-
-def getAFdata(base_url, format=True, ignoreG=True):
-    &#34;&#34;&#34;Get all allele frequency data from a search base url. Iterates over all
-        pages regardless of which page is based.
-
-    Args:
-        base_url (str): URL for base search.
-        format (bool): Format the downloaded data using `formatAF()`.
-        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
-
-    Returns:
-        pd.DataFrame: allele frequency data parsed into a pandas dataframe
-    &#34;&#34;&#34;
-    # Get BS object from base search
-    bs = BeautifulSoup(requests.get(base_url).text, &#39;html.parser&#39;)
-    # How many pages of results
-    N = Npages(bs)
-    print(&#34;%s pages of results&#34; %N)
-    # iterate over pages, parse and combine data from each
-    tabs = []
-    for i in range(N):
-        # print (&#34; Parsing page %s&#34; %(i+1))
-        print (&#34; Parsing page %s&#34; %(i+1), end=&#34;\r&#34;)
-        url = base_url + &#34;page=&#34; + str(i+1)
-        bs = BeautifulSoup(requests.get(url).text, &#39;html.parser&#39;)
-        tab = parseAF(bs)
-        tabs.append(tab)
-    print(&#34;Download complete&#34;)
-    tabs = pd.concat(tabs)
-    if format:
-        try:
-            tabs = formatAF(tabs, ignoreG)
-        except:
-            print(&#34;Formatting failed, non-numeric datatypes may remain.&#34;)
-    return tabs
-
-def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Report any studies with allele freqs that don&#39;t sum to 1
-
-    Args:
-        AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-        datasetID (str): Unique identifier column for study
-    &#34;&#34;&#34;
-    poplocs = AFtab.groupby([datasetID, &#39;loci&#39;]).allele_freq.sum()
-    lmask = poplocs &lt; llimit
-    if sum(lmask&gt;0):
-        print(poplocs[lmask])
-        print(f&#34;{sum(lmask)} studies have total allele frequency &lt; {llimit}&#34;)
-    umask = poplocs &gt; ulimit
-    if sum(umask&gt;0):
-        print(poplocs[umask])
-        print(f&#34;{sum(umask)} studies have total allele frequency &gt; {ulimit}&#34;)
-    incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
-    return incomplete
-
-def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
-    This prevents throwing away data if another loci in the population is incomplete
-
-    Args:
-        AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-        datasetID (str): Unique identifier column for study. Defaults to &#39;population&#39;.
-
-    Returns:
-        pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
-    &#34;&#34;&#34;
-    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
-    # Returns False if population AND loci are in the noncomplete.index
-    # AS A PAIR
-    # This is important so that we don&#39;t throw away all data on a population
-    # just because one loci is incomplete.
-    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
-    df = AFtab[complete_mask]
-    return df
-
-def check_resolution(AFtab):
-    &#34;&#34;&#34;Check if all alleles in AFtab have the same resolution.
-    Will print the number of records with each resolution.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-
-    Returns:
-        bool: True only if all alleles have the same resolution, else False.
-    &#34;&#34;&#34;
-    resolution = 1 + AFtab.allele.str.count(&#34;:&#34;)
-    resVC = resolution.value_counts()
-    pass_check = len(resVC) == 1
-    if not pass_check:
-        print(resVC)
-        print(f&#34;Multiple resolutions in AFtab. Fix with decrease_resolution()&#34;)
-    return pass_check
-
-def decrease_resolution(AFtab, newres, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Decrease allele resolution to a specified value so all alleles have the same resolution.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data.
-        newres (int): The desired number of fields for resolution.
-        datasetID (str, optional): Column to use as stud identifier. Defaults to &#39;population&#39;.
-
-    Returns:
-        pd.DataFrame: Allele frequency data with all alleles of requested resolution.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    resolution = 1 + df.allele.str.count(&#34;:&#34;)
-    assert all(resolution &gt;= newres), f&#34;Some alleles have resolution below {newres} fields&#34;
-    new_allele = df.allele.str.split(&#34;:&#34;).apply(lambda x: &#34;:&#34;.join(x[:newres]))
-    df.allele = new_allele
-    collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
-    return collapsed
-
-def collapse_reduced_alleles(AFtab, datasetID=&#39;population&#39;):
-    df = AFtab.copy()
-    # Group by alleles within datasets
-    grouped = df.groupby([datasetID,&#39;allele&#39;])
-    # Sum allele freq but keep other columns
-    collapsed = grouped.apply(
-        lambda row: [
-            sum(row.allele_freq),
-            row.sample_size.unique()[0],
-            row.loci.unique()[0],
-            len(row.loci.unique()),
-            len(row.sample_size.unique())
-        ]
-    )
-    collapsed = pd.DataFrame(
-        collapsed.tolist(),
-        index=collapsed.index,
-        columns = [&#39;allele_freq&#39;, &#39;sample_size&#39;, &#39;loci&#39;, &#39;#loci&#39;, &#39;#sample_sizes&#39;]
-    ).reset_index()
-    # Within a study each all identical alleles should have the same loci and sample size
-    assert all(collapsed[&#39;#loci&#39;] == 1), &#34;Multiple loci found for a single allele in a single population&#34;
-    assert all(collapsed[&#39;#sample_sizes&#39;] == 1), &#34;Multiple sample_sizes found for a single allele in a single population&#34;
-    collapsed = collapsed[[&#39;allele&#39;, &#39;loci&#39;,&#39;population&#39;,&#39;allele_freq&#39;,&#39;sample_size&#39;]]
-    alleles_unique_in_study(collapsed)
-    return collapsed
-
-def unmeasured_alleles(AFtab, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;When combining AF estimates, unreported alleles can inflate frequencies
-        so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.
-
-    Args:
-        AFtab (pd.DataFrame): Formatted allele frequency data
-        datasetID (str): Unique identifier column for study
-
-    Returns:
-        pd.DataFrame: Allele frequency data with all locus alleles reported 
-            for each dataset
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    loci = df.loci.unique()
-    # Iterate over loci separately
-    for locus in loci:
-        # Iterate over each dataset reporting that locus
-        datasets = df[df.loci == locus][datasetID].unique()
-        for dataset in datasets:
-            # Single locus, single dataset
-            datasetAF = df[(df[datasetID] == dataset) &amp; (df.loci == locus)]
-            # What was the sample size for this data?
-            dataset_sample_size = datasetAF.sample_size.unique()
-            assert len(dataset_sample_size) == 1, &#34;dataset_sample_size must be 1, not %s&#34; %len(dataset_sample_size)
-            dataset_sample_size = dataset_sample_size[0]
-            # Get all alleles for this locus (across datasets)
-            ualleles = df[df.loci == locus].allele.unique()
-            # Which of these alleles are not in this dataset?
-            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
-            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
-            missing_rows = pd.DataFrame(missing_rows, columns=[&#39;allele&#39;,&#39;loci&#39;,datasetID,&#39;allele_freq&#39;,&#39;carriers%&#39;,&#39;sample_size&#39;])
-            # Add them in with zero frequency
-            df = pd.concat([df, missing_rows], ignore_index=True)
-    return df
-
-def combineAF(AFtab, weights=&#39;2n&#39;, alpha = [], datasetID=&#39;population&#39;, format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
-    &#34;&#34;&#34;Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
-    Allele frequencies combined using a Dirichlet distribution where each study&#39;s contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
-    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
-    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
-    If `alpha` is not set the prior defaults to 1 observation of each allele.
-
-    Args:
-        AFtab (pd.DataFrame): Table of Allele frequency data
-        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to &#39;2n&#39;.
-        alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
-        datasetID (str, optional): Unique identifier column for study. Defaults to &#39;population&#39;.
-        format (bool, optional): Run `formatAF()`. Defaults to True.
-        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
-        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
-        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
-        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
-        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
-
-    Returns:
-        pd.DataFrame: Allele frequencies after combining estimates from all studies.
-        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
-        *alpha* is the prior used for the Dirichlet distribution.
-        *c* is the observations used for the Dirichlet distribution.
-        *sample_size* is the total sample size of all combined studies.
-        *wav* is the weighted average.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    single_loci(df)
-    if unique:
-        assert alleles_unique_in_study(df, datasetID=datasetID), &#34;The same allele appears multiple times in a dataset&#34;
-    if complete:
-        assert incomplete_studies(df, datasetID=datasetID).empty, &#34;AFtab contains studies with AF that doesn&#39;t sum to 1. Check incomplete_studies(AFtab)&#34;
-    if resolution:
-        assert check_resolution(df), &#34;AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)&#34;
-    if format:
-        df = formatAF(df, ignoreG)
-    if add_unmeasured:
-        df = unmeasured_alleles(df, datasetID)
-    try:
-        df[&#39;2n&#39;] = df.sample_size * 2
-    except:
-        print(&#34;column &#39;2n&#39; could not be created&#34;)
-    df[&#39;c&#39;] =  df.allele_freq * df[weights]
-    grouped = df.groupby(&#39;allele&#39;, sort=True)
-    combined = grouped.apply(
-        lambda row: [
-        row.name,
-        row.loci.unique()[0],
-        np.average(row.allele_freq, weights=row[weights]),
-        row.c.sum(),
-        row.sample_size.sum()
-        ]
-    )
-    combined = pd.DataFrame(
-        combined.tolist(),
-        columns = [&#39;allele&#39;, &#39;loci&#39;,
-            &#39;wav&#39;,
-            &#39;c&#39;, &#39;sample_size&#39;]
-    )
-    combined = combined.reset_index(drop=True)
-    # Check that all alleles in a locus have the same sample size
-    # after merging
-    if duplicated_sample_size(combined):
-        id_duplicated_allele(grouped)
-    if not alpha:
-        alpha = default_prior(len(combined.allele))
-    combined[&#39;alpha&#39;] = alpha
-    # Calculate Dirichlet mean for each allele
-    combined[&#39;allele_freq&#39;] = dirichlet(combined.alpha + combined.c).mean()
-
-    return combined
-
-def default_prior(k):
-    &#34;&#34;&#34;Calculate a default prior, 1 observation of each class.
-
-    Args:
-        k (int): Number of classes in the Dirichlet distribution.
-
-    Returns:
-        list: List of k 1s to use as prior.
-    &#34;&#34;&#34;
-    alpha = [1] * k
-    return alpha
-
-def single_loci(AFtab):
-    &#34;&#34;&#34;Check that allele frequency data is only of one locus
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-    &#34;&#34;&#34;
-    assert len(AFtab.loci.unique()) == 1, f&#34;&#39;AFtab&#39; must conatain only 1 loci&#34;
-
-def alleles_unique_in_study(AFtab, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-        datasetID (str, optional): Unique identifier column to define study. Defaults to &#39;population&#39;.
-
-    Returns:
-        bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    grouped = df.groupby([datasetID,&#39;allele&#39;])
-    # Are allele alleles unique? i.e. do any occur multiple times in grouping?
-    unique = grouped.size()[grouped.size()&gt;1].empty
-    if not unique:
-        print(f&#34;Non unique alleles in study, is datasetID correct? {datasetID}&#34;)
-        print(grouped.size()[grouped.size()&gt;1])
-    return unique
-
-def duplicated_sample_size(AFtab):
-    &#34;&#34;&#34;Returns True if any loci has more than 1 unique sample size&#34;&#34;&#34;
-    locus_sample_sizes = AFtab.groupby(&#39;loci&#39;).sample_size.apply(lambda x: len(x.unique()))
-    return any(locus_sample_sizes != 1)
-
-def id_duplicated_allele(grouped):
-    &#34;&#34;&#34; Reports the allele that has mupltiple sample sizes &#34;&#34;&#34;
-    duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
-    assert all(~duplicated_population), &#34;duplicated population within allele %s&#34; %duplicated_population[duplicated_population].index.tolist()
-
-def population_coverage(p):
-    &#34;&#34;&#34;Calculate the proportion of people with at least 1 copy of this allele
-        assuming HWE.
-
-    Args:
-        p (float): Allele frequency
-
-    Returns:
-        float: Sum of homozygotes and heterozygotes for this allele
-    &#34;&#34;&#34;
-    q = 1-p
-    homo = p**2
-    hetero = 2*p*q
-    return homo + hetero
-
-def betaAB(alpha):
-    &#34;&#34;&#34;Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
-
-    Args:
-        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
-
-    Returns:
-        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn&#39;t observed.
-    &#34;&#34;&#34;
-    ab = [(a,sum(alpha)-a) for a in alpha]
-    return ab
-
-def betaCI(a,b,credible_interval=0.95):
-    &#34;&#34;&#34;Calculat the central credible interval of a beta distribution
-
-    Args:
-        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
-        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
-        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
-
-    Returns:
-        tuple: Lower and upper credible interval of beta distribution.
-    &#34;&#34;&#34;
-    bd = beta(a,b)
-    lower_quantile = (1-credible_interval)/2
-    upper_quantile = 1-lower_quantile
-    lower_interval = bd.ppf(lower_quantile)
-    upper_interval = bd.ppf(upper_quantile)
-    return lower_interval, upper_interval
-
-def AFci(caf, credible_interval=0.95):
-    &#34;&#34;&#34;Calculate credible interval for combined allele frequency table
-
-    Args:
-        caf (pd.DataFrame): Table produced by combineAF()
-        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
-
-    Returns:
-        list: Lower and upper credible intervals as a list of tuples
-    &#34;&#34;&#34;
-    ab = betaAB(
-        caf.alpha + caf.c,
-    )
-    ci = [betaCI(a, b, credible_interval) for a,b in ab]
-    return ci
-
-def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID=&#34;population&#34;, concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
-    &#34;&#34;&#34;Plot the posterior density function of all frequencies
-        for all alleles based on concentration for Dirichlet
-        distribution. Supply AFtab to add empirical values to plot.
-
-    Args:
-        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn&#39;t have the error checking that combineAF() has. Defaults to pd.DataFrame().
-        datasetID (str, optional): The column used to define datasets. Defaults to &#34;population&#34;.
-        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
-        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
-        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
-        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
-        xmin (float, optional): Set x axis min. Defaults to -0.05.
-        xmax (float, optional): Set x axis max. Defaults to 1.05.
-        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
-        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
-    &#34;&#34;&#34;
-    def allele_mask(alleles, concentration):
-        &#34;&#34;&#34;Create boolean mask either to keep only supplied `alleles`. If empty keep all.
-
-        Args:
-            alleles (list): list of alleles
-            concentration (list): Dirichlet concentration
-
-        Returns:
-            list: List of booleans to use as mask
-        &#34;&#34;&#34;
-        assert isinstance(alleles, list), f&#34;alleles must be a list, not {type(alleles)}&#34;
-        if not alleles:
-            mask = [True] * len(concentration)
-        else:
-            mask = caf.allele.isin(alleles)
-        return mask
-
-    if not concentration:
-        concentration = caf.alpha + caf.c
-    # Get beta parameters for each k in Dirichlet
-    ab = betaAB(concentration)
-    pline = np.linspace(0,1,psteps)
-    if not AFtab.empty:
-        # Format the population allele frequencies
-        df = AFtab.copy()
-        df = unmeasured_alleles(df, datasetID=datasetID)
-        df = df.sort_values(&#39;allele&#39;)
-        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), &#34;Alleles not matching between AFtab and caf&#34;
-    mask = allele_mask(alleles, concentration)
-    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
-    # Only indexes that pass the mask
-    masked_indexes = [i for i,x in enumerate(mask) if x]
-    for subploti,i in enumerate(masked_indexes):
-        subplotselector = subploti//ncol, subploti%ncol
-        a,b = ab[i]
-        bd = beta(a,b)
-        if log:
-            pdf = [bd.logpdf(p) for p in pline]
-        else:
-            with warnings.catch_warnings():
-                warnings.simplefilter(&#34;ignore&#34;)
-                pdf = [bd.pdf(p) for p in pline]
-        ax = axs[subplotselector]
-        ax.set_xlim(xmin,xmax)
-        if not AFtab.empty:
-            # Add the empirical allele frequency for each population
-            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
-                # x is the reported allele freq, y is it&#39;s pdf with scatter
-                if log:
-                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
-                else:
-                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
-        ax.plot(pline, pdf)
-        # Annotate with allele
-        if not caf.empty:
-            ax.text((xmax-xmin)/2, max(pdf)/2, f&#34;{caf.allele.iloc[i]}&#34;)
-        # Annotate with concentration
-        # ax.text(0.5, max(pdf)/3, f&#34;Concentration {round(concentration.iloc[i])}&#34;)
-        if not caf.empty:
-            # Plot the combined average
-            ax.axvline(caf.allele_freq[i], color=&#34;black&#34;, ls=&#34;--&#34;)
-        if ci:
-            cl,cu = betaCI(a,b, ci)
-            ax.axvline(cl, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
-            ax.axvline(cu, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
-        # fig.tight_layout()
-    plt.show()</code></pre>
-</details>
-</section>
-<section>
-</section>
-<section>
-</section>
-<section>
-<h2 class="section-title" id="header-functions">Functions</h2>
-<dl>
-<dt id="HLAfreq.HLAfreq.AFci"><code class="name flex">
-<span>def <span class="ident">AFci</span></span>(<span>caf, credible_interval=0.95)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Calculate credible interval for combined allele frequency table</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>caf</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Table produced by combineAF()</dd>
-<dt><strong><code>credible_interval</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>The desired confidence interval. Defaults to 0.95.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>list</code></dt>
-<dd>Lower and upper credible intervals as a list of tuples</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def AFci(caf, credible_interval=0.95):
-    &#34;&#34;&#34;Calculate credible interval for combined allele frequency table
-
-    Args:
-        caf (pd.DataFrame): Table produced by combineAF()
-        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
-
-    Returns:
-        list: Lower and upper credible intervals as a list of tuples
-    &#34;&#34;&#34;
-    ab = betaAB(
-        caf.alpha + caf.c,
-    )
-    ci = [betaCI(a, b, credible_interval) for a,b in ab]
-    return ci</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.Npages"><code class="name flex">
-<span>def <span class="ident">Npages</span></span>(<span>bs)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>How many pages of results are there?</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>bs</code></strong> :&ensp;<code>bs4.BeautifulSoup</code></dt>
-<dd>BS object of allelefrequencies.net results page</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>int</code></dt>
-<dd>Total number of results pages</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def Npages(bs):
-    &#34;&#34;&#34;How many pages of results are there?
-
-    Args:
-        bs (bs4.BeautifulSoup): BS object of allelefrequencies.net results page
-
-    Returns:
-        int: Total number of results pages
-    &#34;&#34;&#34;
-    # Get the table with number of pages
-    navtab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenNavig&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;table10&#39;})
-    assert navtab, f&#34;navtab does not evaluate to True. Check URL returns results in web browser.&#34;
-    # Get cell with &#39; of &#39; in 
-    pagesOfN = [td.get_text(strip=True) for td in navtab.find_all(&#39;td&#39;) if &#34; of &#34; in td.text]
-    # Check single cell returned
-    assert len(pagesOfN) == 1, &#34;divGenNavig should contain 1 of not %s&#34; %len(pagesOfN)
-    # Get total number of pages
-    N = pagesOfN[0].split(&#34;of &#34;)[1]
-    N = int(N)
-    return N</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.alleles_unique_in_study"><code class="name flex">
-<span>def <span class="ident">alleles_unique_in_study</span></span>(<span>AFtab, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by <code>datasetID</code>.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Allele frequency data</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Unique identifier column to define study. Defaults to 'population'.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>bool</code></dt>
-<dd><code>True</code> on if no alleles occur more than once in any study, otherwise <code>False</code>.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def alleles_unique_in_study(AFtab, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-        datasetID (str, optional): Unique identifier column to define study. Defaults to &#39;population&#39;.
-
-    Returns:
-        bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    grouped = df.groupby([datasetID,&#39;allele&#39;])
-    # Are allele alleles unique? i.e. do any occur multiple times in grouping?
-    unique = grouped.size()[grouped.size()&gt;1].empty
-    if not unique:
-        print(f&#34;Non unique alleles in study, is datasetID correct? {datasetID}&#34;)
-        print(grouped.size()[grouped.size()&gt;1])
-    return unique</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.betaAB"><code class="name flex">
-<span>def <span class="ident">betaAB</span></span>(<span>alpha)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>alpha</code></strong> :&ensp;<code>list</code></dt>
-<dd>Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>list</code></dt>
-<dd>List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def betaAB(alpha):
-    &#34;&#34;&#34;Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
-
-    Args:
-        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
-
-    Returns:
-        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn&#39;t observed.
-    &#34;&#34;&#34;
-    ab = [(a,sum(alpha)-a) for a in alpha]
-    return ab</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.betaCI"><code class="name flex">
-<span>def <span class="ident">betaCI</span></span>(<span>a, b, credible_interval=0.95)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Calculat the central credible interval of a beta distribution</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>a</code></strong> :&ensp;<code>float</code></dt>
-<dd>Beta shape parameter <code>a</code>, i.e. the number of times the allele was observed.</dd>
-<dt><strong><code>b</code></strong> :&ensp;<code>float</code></dt>
-<dd>Beta shape parameter <code>b</code>, i.e. the number of times the allele was not observed.</dd>
-<dt><strong><code>credible_interval</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>The size of the credible interval requested. Defaults to 0.95.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>tuple</code></dt>
-<dd>Lower and upper credible interval of beta distribution.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def betaCI(a,b,credible_interval=0.95):
-    &#34;&#34;&#34;Calculat the central credible interval of a beta distribution
-
-    Args:
-        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
-        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
-        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
-
-    Returns:
-        tuple: Lower and upper credible interval of beta distribution.
-    &#34;&#34;&#34;
-    bd = beta(a,b)
-    lower_quantile = (1-credible_interval)/2
-    upper_quantile = 1-lower_quantile
-    lower_interval = bd.ppf(lower_quantile)
-    upper_interval = bd.ppf(upper_quantile)
-    return lower_interval, upper_interval</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.check_resolution"><code class="name flex">
-<span>def <span class="ident">check_resolution</span></span>(<span>AFtab)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Check if all alleles in AFtab have the same resolution.
-Will print the number of records with each resolution.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Allele frequency data</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>bool</code></dt>
-<dd>True only if all alleles have the same resolution, else False.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def check_resolution(AFtab):
-    &#34;&#34;&#34;Check if all alleles in AFtab have the same resolution.
-    Will print the number of records with each resolution.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-
-    Returns:
-        bool: True only if all alleles have the same resolution, else False.
-    &#34;&#34;&#34;
-    resolution = 1 + AFtab.allele.str.count(&#34;:&#34;)
-    resVC = resolution.value_counts()
-    pass_check = len(resVC) == 1
-    if not pass_check:
-        print(resVC)
-        print(f&#34;Multiple resolutions in AFtab. Fix with decrease_resolution()&#34;)
-    return pass_check</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.collapse_reduced_alleles"><code class="name flex">
-<span>def <span class="ident">collapse_reduced_alleles</span></span>(<span>AFtab, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def collapse_reduced_alleles(AFtab, datasetID=&#39;population&#39;):
-    df = AFtab.copy()
-    # Group by alleles within datasets
-    grouped = df.groupby([datasetID,&#39;allele&#39;])
-    # Sum allele freq but keep other columns
-    collapsed = grouped.apply(
-        lambda row: [
-            sum(row.allele_freq),
-            row.sample_size.unique()[0],
-            row.loci.unique()[0],
-            len(row.loci.unique()),
-            len(row.sample_size.unique())
-        ]
-    )
-    collapsed = pd.DataFrame(
-        collapsed.tolist(),
-        index=collapsed.index,
-        columns = [&#39;allele_freq&#39;, &#39;sample_size&#39;, &#39;loci&#39;, &#39;#loci&#39;, &#39;#sample_sizes&#39;]
-    ).reset_index()
-    # Within a study each all identical alleles should have the same loci and sample size
-    assert all(collapsed[&#39;#loci&#39;] == 1), &#34;Multiple loci found for a single allele in a single population&#34;
-    assert all(collapsed[&#39;#sample_sizes&#39;] == 1), &#34;Multiple sample_sizes found for a single allele in a single population&#34;
-    collapsed = collapsed[[&#39;allele&#39;, &#39;loci&#39;,&#39;population&#39;,&#39;allele_freq&#39;,&#39;sample_size&#39;]]
-    alleles_unique_in_study(collapsed)
-    return collapsed</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.combineAF"><code class="name flex">
-<span>def <span class="ident">combineAF</span></span>(<span>AFtab, weights='2n', alpha=[], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Combine allele frequencies from multiple studies. <code>datasetID</code> is the unique identifier for studies to combine.
-Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
-Sample size is doubled to get <code>2n</code> due to diploidy. If an alternative <code>weights</code> is set it is not doubled.
-The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior <code>alpha</code>.
-If <code>alpha</code> is not set the prior defaults to 1 observation of each allele.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Table of Allele frequency data</dd>
-<dt><strong><code>weights</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.</dd>
-<dt><strong><code>alpha</code></strong> :&ensp;<code>list</code>, optional</dt>
-<dd>Prior to use for Dirichlet distribution. Defaults to [].</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Unique identifier column for study. Defaults to 'population'.</dd>
-<dt><strong><code>format</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Run <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>. Defaults to True.</dd>
-<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Treat allele G groups as normal, see <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>. Defaults to True.</dd>
-<dt><strong><code>add_unmeasured</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See <code>add_unmeasured()</code>. Defaults to True.</dd>
-<dt><strong><code>complete</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Check study completeness. Uses default values for <code><a title="HLAfreq.HLAfreq.incomplete_studies" href="#HLAfreq.HLAfreq.incomplete_studies">incomplete_studies()</a></code>. If you are happy with your study completeness can be switched off with False. Defaults to True.</dd>
-<dt><strong><code>resolution</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Check that all alleles have the same resolution, see <code><a title="HLAfreq.HLAfreq.check_resolution" href="#HLAfreq.HLAfreq.check_resolution">check_resolution()</a></code>. Defaults to True.</dd>
-<dt><strong><code>unique</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Check that each allele appears no more than once per study. See <code><a title="HLAfreq.HLAfreq.alleles_unique_in_study" href="#HLAfreq.HLAfreq.alleles_unique_in_study">alleles_unique_in_study()</a></code>. Defaults to True.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>Allele frequencies after combining estimates from all studies.</dd>
-</dl>
-<p><em>allele_freq</em> is the combined frequency estimate from the Dirichlet mean where the concentration is <code>alpha</code> + <code>c</code>.
-<em>alpha</em> is the prior used for the Dirichlet distribution.
-<em>c</em> is the observations used for the Dirichlet distribution.
-<em>sample_size</em> is the total sample size of all combined studies.
-<em>wav</em> is the weighted average.</p></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def combineAF(AFtab, weights=&#39;2n&#39;, alpha = [], datasetID=&#39;population&#39;, format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
-    &#34;&#34;&#34;Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
-    Allele frequencies combined using a Dirichlet distribution where each study&#39;s contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
-    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
-    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
-    If `alpha` is not set the prior defaults to 1 observation of each allele.
-
-    Args:
-        AFtab (pd.DataFrame): Table of Allele frequency data
-        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to &#39;2n&#39;.
-        alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
-        datasetID (str, optional): Unique identifier column for study. Defaults to &#39;population&#39;.
-        format (bool, optional): Run `formatAF()`. Defaults to True.
-        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
-        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
-        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
-        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
-        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
-
-    Returns:
-        pd.DataFrame: Allele frequencies after combining estimates from all studies.
-        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
-        *alpha* is the prior used for the Dirichlet distribution.
-        *c* is the observations used for the Dirichlet distribution.
-        *sample_size* is the total sample size of all combined studies.
-        *wav* is the weighted average.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    single_loci(df)
-    if unique:
-        assert alleles_unique_in_study(df, datasetID=datasetID), &#34;The same allele appears multiple times in a dataset&#34;
-    if complete:
-        assert incomplete_studies(df, datasetID=datasetID).empty, &#34;AFtab contains studies with AF that doesn&#39;t sum to 1. Check incomplete_studies(AFtab)&#34;
-    if resolution:
-        assert check_resolution(df), &#34;AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)&#34;
-    if format:
-        df = formatAF(df, ignoreG)
-    if add_unmeasured:
-        df = unmeasured_alleles(df, datasetID)
-    try:
-        df[&#39;2n&#39;] = df.sample_size * 2
-    except:
-        print(&#34;column &#39;2n&#39; could not be created&#34;)
-    df[&#39;c&#39;] =  df.allele_freq * df[weights]
-    grouped = df.groupby(&#39;allele&#39;, sort=True)
-    combined = grouped.apply(
-        lambda row: [
-        row.name,
-        row.loci.unique()[0],
-        np.average(row.allele_freq, weights=row[weights]),
-        row.c.sum(),
-        row.sample_size.sum()
-        ]
-    )
-    combined = pd.DataFrame(
-        combined.tolist(),
-        columns = [&#39;allele&#39;, &#39;loci&#39;,
-            &#39;wav&#39;,
-            &#39;c&#39;, &#39;sample_size&#39;]
-    )
-    combined = combined.reset_index(drop=True)
-    # Check that all alleles in a locus have the same sample size
-    # after merging
-    if duplicated_sample_size(combined):
-        id_duplicated_allele(grouped)
-    if not alpha:
-        alpha = default_prior(len(combined.allele))
-    combined[&#39;alpha&#39;] = alpha
-    # Calculate Dirichlet mean for each allele
-    combined[&#39;allele_freq&#39;] = dirichlet(combined.alpha + combined.c).mean()
-
-    return combined</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.decrease_resolution"><code class="name flex">
-<span>def <span class="ident">decrease_resolution</span></span>(<span>AFtab, newres, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Decrease allele resolution to a specified value so all alleles have the same resolution.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Allele frequency data.</dd>
-<dt><strong><code>newres</code></strong> :&ensp;<code>int</code></dt>
-<dd>The desired number of fields for resolution.</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Column to use as stud identifier. Defaults to 'population'.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>Allele frequency data with all alleles of requested resolution.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def decrease_resolution(AFtab, newres, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Decrease allele resolution to a specified value so all alleles have the same resolution.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data.
-        newres (int): The desired number of fields for resolution.
-        datasetID (str, optional): Column to use as stud identifier. Defaults to &#39;population&#39;.
-
-    Returns:
-        pd.DataFrame: Allele frequency data with all alleles of requested resolution.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    resolution = 1 + df.allele.str.count(&#34;:&#34;)
-    assert all(resolution &gt;= newres), f&#34;Some alleles have resolution below {newres} fields&#34;
-    new_allele = df.allele.str.split(&#34;:&#34;).apply(lambda x: &#34;:&#34;.join(x[:newres]))
-    df.allele = new_allele
-    collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
-    return collapsed</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.default_prior"><code class="name flex">
-<span>def <span class="ident">default_prior</span></span>(<span>k)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Calculate a default prior, 1 observation of each class.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>k</code></strong> :&ensp;<code>int</code></dt>
-<dd>Number of classes in the Dirichlet distribution.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>list</code></dt>
-<dd>List of k 1s to use as prior.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def default_prior(k):
-    &#34;&#34;&#34;Calculate a default prior, 1 observation of each class.
-
-    Args:
-        k (int): Number of classes in the Dirichlet distribution.
-
-    Returns:
-        list: List of k 1s to use as prior.
-    &#34;&#34;&#34;
-    alpha = [1] * k
-    return alpha</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.duplicated_sample_size"><code class="name flex">
-<span>def <span class="ident">duplicated_sample_size</span></span>(<span>AFtab)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Returns True if any loci has more than 1 unique sample size</p></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def duplicated_sample_size(AFtab):
-    &#34;&#34;&#34;Returns True if any loci has more than 1 unique sample size&#34;&#34;&#34;
-    locus_sample_sizes = AFtab.groupby(&#39;loci&#39;).sample_size.apply(lambda x: len(x.unique()))
-    return any(locus_sample_sizes != 1)</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.formatAF"><code class="name flex">
-<span>def <span class="ident">formatAF</span></span>(<span>AFtab, ignoreG=True)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Format allele frequency table.
-Convert sample_size and allele_freq to numeric data type.
-Removes commas from sample size. Removes "(*)" from allele frequency if
-<code>ignoreG</code> is <code>True</code>. <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code> is used internally by combineAF and getAFdata by default.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Allele frequency data downloaded from allelefrequency.net using <code><a title="HLAfreq.HLAfreq.getAFdata" href="#HLAfreq.HLAfreq.getAFdata">getAFdata()</a></code>.</dd>
-<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Treat G group alleles as normal. See <a href="http://hla.alleles.org/alleles/g_groups.html">http://hla.alleles.org/alleles/g_groups.html</a> for details. Defaults to True.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>The formatted allele frequency data.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def formatAF(AFtab, ignoreG=True):
-    &#34;&#34;&#34;Format allele frequency table.
-    Convert sample_size and allele_freq to numeric data type.
-    Removes commas from sample size. Removes &#34;(*)&#34; from allele frequency if 
-    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
-        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
-
-    Returns:
-        pd.DataFrame: The formatted allele frequency data.
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    if df.sample_size.dtype == &#34;O&#34;:
-        df.sample_size = pd.to_numeric(df.sample_size.str.replace(&#34;,&#34;, &#34;&#34;))
-    if df.allele_freq.dtype == &#34;O&#34;:
-        if ignoreG:
-            df.allele_freq = df.allele_freq.str.replace(&#34;(*)&#34;, &#34;&#34;, regex=False)
-        df.allele_freq = pd.to_numeric(df.allele_freq)
-    return df</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.getAFdata"><code class="name flex">
-<span>def <span class="ident">getAFdata</span></span>(<span>base_url, format=True, ignoreG=True)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Get all allele frequency data from a search base url. Iterates over all
-pages regardless of which page is based.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>base_url</code></strong> :&ensp;<code>str</code></dt>
-<dd>URL for base search.</dd>
-<dt><strong><code>format</code></strong> :&ensp;<code>bool</code></dt>
-<dd>Format the downloaded data using <code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF()</a></code>.</dd>
-<dt><strong><code>ignoreG</code></strong> :&ensp;<code>bool</code></dt>
-<dd>treat allele G groups as normal. See <a href="http://hla.alleles.org/alleles/g_groups.html">http://hla.alleles.org/alleles/g_groups.html</a> for details. Default = True</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>allele frequency data parsed into a pandas dataframe</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def getAFdata(base_url, format=True, ignoreG=True):
-    &#34;&#34;&#34;Get all allele frequency data from a search base url. Iterates over all
-        pages regardless of which page is based.
-
-    Args:
-        base_url (str): URL for base search.
-        format (bool): Format the downloaded data using `formatAF()`.
-        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
-
-    Returns:
-        pd.DataFrame: allele frequency data parsed into a pandas dataframe
-    &#34;&#34;&#34;
-    # Get BS object from base search
-    bs = BeautifulSoup(requests.get(base_url).text, &#39;html.parser&#39;)
-    # How many pages of results
-    N = Npages(bs)
-    print(&#34;%s pages of results&#34; %N)
-    # iterate over pages, parse and combine data from each
-    tabs = []
-    for i in range(N):
-        # print (&#34; Parsing page %s&#34; %(i+1))
-        print (&#34; Parsing page %s&#34; %(i+1), end=&#34;\r&#34;)
-        url = base_url + &#34;page=&#34; + str(i+1)
-        bs = BeautifulSoup(requests.get(url).text, &#39;html.parser&#39;)
-        tab = parseAF(bs)
-        tabs.append(tab)
-    print(&#34;Download complete&#34;)
-    tabs = pd.concat(tabs)
-    if format:
-        try:
-            tabs = formatAF(tabs, ignoreG)
-        except:
-            print(&#34;Formatting failed, non-numeric datatypes may remain.&#34;)
-    return tabs</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.id_duplicated_allele"><code class="name flex">
-<span>def <span class="ident">id_duplicated_allele</span></span>(<span>grouped)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Reports the allele that has mupltiple sample sizes</p></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def id_duplicated_allele(grouped):
-    &#34;&#34;&#34; Reports the allele that has mupltiple sample sizes &#34;&#34;&#34;
-    duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
-    assert all(~duplicated_population), &#34;duplicated population within allele %s&#34; %duplicated_population[duplicated_population].index.tolist()</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.incomplete_studies"><code class="name flex">
-<span>def <span class="ident">incomplete_studies</span></span>(<span>AFtab, llimit=0.95, ulimit=1.1, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Report any studies with allele freqs that don't sum to 1</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Dataframe containing multiple studies</dd>
-<dt><strong><code>llimit</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Lower allele_freq sum limit that counts as complete. Defaults to 0.95.</dd>
-<dt><strong><code>ulimit</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Upper allele_freq sum limit that will not be reported. Defaults to 1.1.</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
-<dd>Unique identifier column for study</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Report any studies with allele freqs that don&#39;t sum to 1
-
-    Args:
-        AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-        datasetID (str): Unique identifier column for study
-    &#34;&#34;&#34;
-    poplocs = AFtab.groupby([datasetID, &#39;loci&#39;]).allele_freq.sum()
-    lmask = poplocs &lt; llimit
-    if sum(lmask&gt;0):
-        print(poplocs[lmask])
-        print(f&#34;{sum(lmask)} studies have total allele frequency &lt; {llimit}&#34;)
-    umask = poplocs &gt; ulimit
-    if sum(umask&gt;0):
-        print(poplocs[umask])
-        print(f&#34;{sum(umask)} studies have total allele frequency &gt; {ulimit}&#34;)
-    incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
-    return incomplete</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.makeURL"><code class="name flex">
-<span>def <span class="ident">makeURL</span></span>(<span>country='', standard='s', locus='', resolution_pattern='bigger_equal_than', resolution=2, region='', ethnic='', study_type='', dataset_source='', sample_year='', sample_year_pattern='', sample_size='', sample_size_pattern='')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Create URL for search of allele frequency net database. All arguments are documented <a href="http://www.allelefrequencies.net/extaccess.asp">here</a></p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>country</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Country name to retrieve records from. Defaults to "".</dd>
-<dt><strong><code>standard</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.</dd>
-<dt><strong><code>locus</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>The locus to return allele data for. Defaults to "".</dd>
-<dt><strong><code>resolution_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using <code>resolution</code> and <code>resolution_pattern</code>. Defaults to "bigger_equal_than".</dd>
-<dt><strong><code>resolution</code></strong> :&ensp;<code>int</code>, optional</dt>
-<dd>Number of fields of resolution of allele. Filter created using <code>resolution</code> and <code>resolution_pattern</code>. Defaults to 2.</dd>
-<dt><strong><code>region</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Filter to geographic region. {Asia, Australia, Eastern Europe, &hellip;}. All regions listed <a href="http://www.allelefrequencies.net/pop6003a.asp">here</a>. Defaults to "".</dd>
-<dt><strong><code>ethnic</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Filter to ethnicity. {"Amerindian", "Black", "Caucasian", &hellip;}. All ethnicities listed <a href="http://www.allelefrequencies.net/pop6003a.asp">here</a>. Defaults to "".</dd>
-<dt><strong><code>study_type</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".</dd>
-<dt><strong><code>dataset_source</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".</dd>
-<dt><strong><code>sample_year</code></strong> :&ensp;<code>int</code>, optional</dt>
-<dd>Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".</dd>
-<dt><strong><code>sample_year_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".</dd>
-<dt><strong><code>sample_size</code></strong> :&ensp;<code>int</code>, optional</dt>
-<dd>Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".</dd>
-<dt><strong><code>sample_size_pattern</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>str</code></dt>
-<dd>URL to search allelefrequencies.net</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def makeURL(
-        country=&#34;&#34;,
-        standard=&#39;s&#39;,
-        locus=&#34;&#34;,
-        resolution_pattern=&#34;bigger_equal_than&#34;,
-        resolution=2,
-        region=&#34;&#34;,
-        ethnic=&#34;&#34;,
-        study_type=&#34;&#34;,
-        dataset_source=&#34;&#34;,
-        sample_year=&#34;&#34;,
-        sample_year_pattern=&#34;&#34;,
-        sample_size=&#34;&#34;,
-        sample_size_pattern=&#34;&#34;
-    ):
-    &#34;&#34;&#34;Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
-    Args:
-        country (str, optional): Country name to retrieve records from. Defaults to &#34;&#34;.
-        standard (str, optional): Filter study quality standard to this or higher. {&#39;g&#39;, &#39;s&#39;, &#39;a&#39;} Gold, silver, all. Defaults to &#39;s&#39;.
-        locus (str, optional): The locus to return allele data for. Defaults to &#34;&#34;.
-        resolution_pattern (str, optional): Resolution comparitor {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Filter created using `resolution` and `resolution_pattern`. Defaults to &#34;bigger_equal_than&#34;.
-        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
-        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
-        ethnic (str, optional): Filter to ethnicity. {&#34;Amerindian&#34;, &#34;Black&#34;, &#34;Caucasian&#34;, ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to &#34;&#34;.
-        study_type (str, optional): Type of study. {&#34;Anthropology&#34;, &#34;Blood+Donor&#34;, &#34;Bone+Marrow+Registry&#34;, &#34;Controls+for+Disease+Study&#34;, &#34;Disease+Study+Patients&#34;, &#34;Other&#34;, &#34;Solid+Organd+Unrelated+Donors&#34;, &#34;Stem+cell+donors&#34;}. Defaults to &#34;&#34;.
-        dataset_source (str, optional): Source of data. {&#34;Literature&#34;, &#34;Proceedings+of+IHWs&#34;, &#34;Unpublished&#34;}. Defaults to &#34;&#34;.
-        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to &#34;&#34;.
-        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
-        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to &#34;&#34;.
-        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {&#39;equal&#39;, &#39;different&#39;, &#39;less_than&#39;, &#39;bigger_than&#39;, &#39;less_equal_than&#39;, &#39;bigger_equal_than&#39;}. Defaults to &#34;&#34;.
-
-    Returns:
-        str: URL to search allelefrequencies.net
-    &#34;&#34;&#34;
-    base = &#34;http://www.allelefrequencies.net/hla6006a.asp?&#34;
-    locus_type = &#34;hla_locus_type=Classical&amp;&#34;
-    hla_locus = &#34;hla_locus=%s&amp;&#34; %(locus)
-    country = &#34;hla_country=%s&amp;&#34; %(country)
-    region = &#34;hla_region=%s&amp;&#34; %(region)
-    ethnic = &#34;hla_ethnic=%s&amp;&#34; %(ethnic)
-    study_type = &#34;hla_study=%s&amp;&#34; %(study_type)
-    dataset_source = &#34;hla_dataset_source=%s&amp;&#34; %(dataset_source)
-    sample_year = &#34;hla_sample_year=%s&amp;&#34; %(sample_year)
-    sample_year_pattern = &#34;hla_sample_year_pattern=%s&amp;&#34; %(sample_year_pattern)
-    sample_size = &#34;hla_sample_size=%s&amp;&#34; %(sample_size)
-    sample_size_pattern = &#34;hla_sample_size_pattern=%s&amp;&#34; %(sample_size_pattern)
-    hla_level_pattern = &#34;hla_level_pattern=%s&amp;&#34; %(resolution_pattern)
-    hla_level = &#34;hla_level=%s&amp;&#34; %(resolution)
-    standard = &#34;standard=%s&amp;&#34; %standard
-    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
-    return url</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.only_complete"><code class="name flex">
-<span>def <span class="ident">only_complete</span></span>(<span>AFtab, llimit=0.95, ulimit=1.1, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
-This prevents throwing away data if another loci in the population is incomplete</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Dataframe containing multiple studies</dd>
-<dt><strong><code>llimit</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Lower allele_freq sum limit that counts as complete. Defaults to 0.95.</dd>
-<dt><strong><code>ulimit</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Upper allele_freq sum limit that will not be reported. Defaults to 1.1.</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
-<dd>Unique identifier column for study. Defaults to 'population'.</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>Allele frequency data of multiple studies, but only complete studies.</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
-    This prevents throwing away data if another loci in the population is incomplete
-
-    Args:
-        AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-        datasetID (str): Unique identifier column for study. Defaults to &#39;population&#39;.
-
-    Returns:
-        pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
-    &#34;&#34;&#34;
-    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
-    # Returns False if population AND loci are in the noncomplete.index
-    # AS A PAIR
-    # This is important so that we don&#39;t throw away all data on a population
-    # just because one loci is incomplete.
-    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
-    df = AFtab[complete_mask]
-    return df</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.parseAF"><code class="name flex">
-<span>def <span class="ident">parseAF</span></span>(<span>bs)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Generate a dataframe from a given html page</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>bs</code></strong> :&ensp;<code>bs4.BeautifulSoup</code></dt>
-<dd>BeautifulSoup object from allelefrequencies.net page</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>Table of allele, allele frequency, samplesize, and population</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def parseAF(bs):
-    &#34;&#34;&#34;Generate a dataframe from a given html page
-
-    Args:
-        bs (bs4.BeautifulSoup): BeautifulSoup object from allelefrequencies.net page
-
-    Returns:
-        pd.DataFrame: Table of allele, allele frequency, samplesize, and population
-    &#34;&#34;&#34;
-    # Get the results table from the div `divGenDetail`
-    tab = bs.find(&#39;div&#39;, {&#39;id&#39;: &#39;divGenDetail&#39;}).find(&#39;table&#39;, {&#39;class&#39;: &#39;tblNormal&#39;})
-    # Get the column headers from the first row of the table
-    columns = [
-        &#39;line&#39;, &#39;allele&#39;, &#39;flag&#39;, &#39;population&#39;, &#39;carriers%&#39;,
-        &#39;allele_freq&#39;, &#39;AF_graphic&#39;, &#39;sample_size&#39;, &#39;database&#39;,
-        &#39;distribution&#39;,&#39;haplotype_association&#39;, &#39;notes&#39;
-        ]
-    rows =[]
-    for row in tab.find_all(&#39;tr&#39;):
-        rows.append(
-            [td.get_text(strip=True) for td in row.find_all(&#39;td&#39;)]
-            )
-    # Make dataframe of table rows
-    # skip the first row as it&#39;s `th` headers
-    df = pd.DataFrame(rows[1:], columns = columns)
-
-    # Get HLA loci
-    df[&#39;loci&#39;] = df.allele.apply(lambda x: x.split(&#34;*&#34;)[0])
-
-    # Drop unwanted columns
-    df = df[[&#39;allele&#39;, &#39;loci&#39;, &#39;population&#39;, &#39;allele_freq&#39;, &#39;carriers%&#39;, &#39;sample_size&#39;]]
-    return df</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.plotAFprob"><code class="name flex">
-<span>def <span class="ident">plotAFprob</span></span>(<span>caf=Empty DataFrame
-Columns: []
-Index: [], AFtab=Empty DataFrame
-Columns: []
-Index: [], datasetID='population', concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[])</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Plot the posterior density function of all frequencies
-for all alleles based on concentration for Dirichlet
-distribution. Supply AFtab to add empirical values to plot.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>caf</code></strong> :&ensp;<code>pd.DataFrame</code>, optional</dt>
-<dd>Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().</dd>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code>, optional</dt>
-<dd>The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code>, optional</dt>
-<dd>The column used to define datasets. Defaults to "population".</dd>
-<dt><strong><code>concentration</code></strong> :&ensp;<code>pd.Series</code>, optional</dt>
-<dd>Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False</dd>
-<dt><strong><code>log</code></strong> :&ensp;<code>bool</code>, optional</dt>
-<dd>Plot log pdf instead of pdf? Defaults to False.</dd>
-<dt><strong><code>psteps</code></strong> :&ensp;<code>int</code>, optional</dt>
-<dd>Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.</dd>
-<dt><strong><code>ncol</code></strong> :&ensp;<code>int</code>, optional</dt>
-<dd>How many columns to arrange subplots in. Defaults to 2.</dd>
-<dt><strong><code>xmin</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Set x axis min. Defaults to -0.05.</dd>
-<dt><strong><code>xmax</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Set x axis max. Defaults to 1.05.</dd>
-<dt><strong><code>ci</code></strong> :&ensp;<code>float</code>, optional</dt>
-<dd>Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.</dd>
-<dt><strong><code>alleles</code></strong> :&ensp;<code>list</code>, optional</dt>
-<dd>List of alleles to plot. Plots all if none supplied. Defaults to [].</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID=&#34;population&#34;, concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
-    &#34;&#34;&#34;Plot the posterior density function of all frequencies
-        for all alleles based on concentration for Dirichlet
-        distribution. Supply AFtab to add empirical values to plot.
-
-    Args:
-        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn&#39;t have the error checking that combineAF() has. Defaults to pd.DataFrame().
-        datasetID (str, optional): The column used to define datasets. Defaults to &#34;population&#34;.
-        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
-        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
-        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
-        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
-        xmin (float, optional): Set x axis min. Defaults to -0.05.
-        xmax (float, optional): Set x axis max. Defaults to 1.05.
-        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
-        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
-    &#34;&#34;&#34;
-    def allele_mask(alleles, concentration):
-        &#34;&#34;&#34;Create boolean mask either to keep only supplied `alleles`. If empty keep all.
-
-        Args:
-            alleles (list): list of alleles
-            concentration (list): Dirichlet concentration
-
-        Returns:
-            list: List of booleans to use as mask
-        &#34;&#34;&#34;
-        assert isinstance(alleles, list), f&#34;alleles must be a list, not {type(alleles)}&#34;
-        if not alleles:
-            mask = [True] * len(concentration)
-        else:
-            mask = caf.allele.isin(alleles)
-        return mask
-
-    if not concentration:
-        concentration = caf.alpha + caf.c
-    # Get beta parameters for each k in Dirichlet
-    ab = betaAB(concentration)
-    pline = np.linspace(0,1,psteps)
-    if not AFtab.empty:
-        # Format the population allele frequencies
-        df = AFtab.copy()
-        df = unmeasured_alleles(df, datasetID=datasetID)
-        df = df.sort_values(&#39;allele&#39;)
-        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), &#34;Alleles not matching between AFtab and caf&#34;
-    mask = allele_mask(alleles, concentration)
-    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
-    # Only indexes that pass the mask
-    masked_indexes = [i for i,x in enumerate(mask) if x]
-    for subploti,i in enumerate(masked_indexes):
-        subplotselector = subploti//ncol, subploti%ncol
-        a,b = ab[i]
-        bd = beta(a,b)
-        if log:
-            pdf = [bd.logpdf(p) for p in pline]
-        else:
-            with warnings.catch_warnings():
-                warnings.simplefilter(&#34;ignore&#34;)
-                pdf = [bd.pdf(p) for p in pline]
-        ax = axs[subplotselector]
-        ax.set_xlim(xmin,xmax)
-        if not AFtab.empty:
-            # Add the empirical allele frequency for each population
-            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
-                # x is the reported allele freq, y is it&#39;s pdf with scatter
-                if log:
-                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
-                else:
-                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
-        ax.plot(pline, pdf)
-        # Annotate with allele
-        if not caf.empty:
-            ax.text((xmax-xmin)/2, max(pdf)/2, f&#34;{caf.allele.iloc[i]}&#34;)
-        # Annotate with concentration
-        # ax.text(0.5, max(pdf)/3, f&#34;Concentration {round(concentration.iloc[i])}&#34;)
-        if not caf.empty:
-            # Plot the combined average
-            ax.axvline(caf.allele_freq[i], color=&#34;black&#34;, ls=&#34;--&#34;)
-        if ci:
-            cl,cu = betaCI(a,b, ci)
-            ax.axvline(cl, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
-            ax.axvline(cu, color=&#34;black&#34;, linestyle=&#34;dotted&#34;)
-        # fig.tight_layout()
-    plt.show()</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.population_coverage"><code class="name flex">
-<span>def <span class="ident">population_coverage</span></span>(<span>p)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Calculate the proportion of people with at least 1 copy of this allele
-assuming HWE.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>p</code></strong> :&ensp;<code>float</code></dt>
-<dd>Allele frequency</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>float</code></dt>
-<dd>Sum of homozygotes and heterozygotes for this allele</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def population_coverage(p):
-    &#34;&#34;&#34;Calculate the proportion of people with at least 1 copy of this allele
-        assuming HWE.
-
-    Args:
-        p (float): Allele frequency
-
-    Returns:
-        float: Sum of homozygotes and heterozygotes for this allele
-    &#34;&#34;&#34;
-    q = 1-p
-    homo = p**2
-    hetero = 2*p*q
-    return homo + hetero</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.single_loci"><code class="name flex">
-<span>def <span class="ident">single_loci</span></span>(<span>AFtab)</span>
-</code></dt>
-<dd>
-<div class="desc"><p>Check that allele frequency data is only of one locus</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Allele frequency data</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def single_loci(AFtab):
-    &#34;&#34;&#34;Check that allele frequency data is only of one locus
-
-    Args:
-        AFtab (pd.DataFrame): Allele frequency data
-    &#34;&#34;&#34;
-    assert len(AFtab.loci.unique()) == 1, f&#34;&#39;AFtab&#39; must conatain only 1 loci&#34;</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq.unmeasured_alleles"><code class="name flex">
-<span>def <span class="ident">unmeasured_alleles</span></span>(<span>AFtab, datasetID='population')</span>
-</code></dt>
-<dd>
-<div class="desc"><p>When combining AF estimates, unreported alleles can inflate frequencies
-so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.</p>
-<h2 id="args">Args</h2>
-<dl>
-<dt><strong><code>AFtab</code></strong> :&ensp;<code>pd.DataFrame</code></dt>
-<dd>Formatted allele frequency data</dd>
-<dt><strong><code>datasetID</code></strong> :&ensp;<code>str</code></dt>
-<dd>Unique identifier column for study</dd>
-</dl>
-<h2 id="returns">Returns</h2>
-<dl>
-<dt><code>pd.DataFrame</code></dt>
-<dd>Allele frequency data with all locus alleles reported
-for each dataset</dd>
-</dl></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def unmeasured_alleles(AFtab, datasetID=&#39;population&#39;):
-    &#34;&#34;&#34;When combining AF estimates, unreported alleles can inflate frequencies
-        so AF sums to &gt;1. Therefore we add unreported alleles with frequency zero.
-
-    Args:
-        AFtab (pd.DataFrame): Formatted allele frequency data
-        datasetID (str): Unique identifier column for study
-
-    Returns:
-        pd.DataFrame: Allele frequency data with all locus alleles reported 
-            for each dataset
-    &#34;&#34;&#34;
-    df = AFtab.copy()
-    loci = df.loci.unique()
-    # Iterate over loci separately
-    for locus in loci:
-        # Iterate over each dataset reporting that locus
-        datasets = df[df.loci == locus][datasetID].unique()
-        for dataset in datasets:
-            # Single locus, single dataset
-            datasetAF = df[(df[datasetID] == dataset) &amp; (df.loci == locus)]
-            # What was the sample size for this data?
-            dataset_sample_size = datasetAF.sample_size.unique()
-            assert len(dataset_sample_size) == 1, &#34;dataset_sample_size must be 1, not %s&#34; %len(dataset_sample_size)
-            dataset_sample_size = dataset_sample_size[0]
-            # Get all alleles for this locus (across datasets)
-            ualleles = df[df.loci == locus].allele.unique()
-            # Which of these alleles are not in this dataset?
-            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
-            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
-            missing_rows = pd.DataFrame(missing_rows, columns=[&#39;allele&#39;,&#39;loci&#39;,datasetID,&#39;allele_freq&#39;,&#39;carriers%&#39;,&#39;sample_size&#39;])
-            # Add them in with zero frequency
-            df = pd.concat([df, missing_rows], ignore_index=True)
-    return df</code></pre>
-</details>
-</dd>
-</dl>
-</section>
-<section>
-</section>
-</article>
-<nav id="sidebar">
-<h1>Index</h1>
-<div class="toc">
-<ul></ul>
-</div>
-<ul id="index">
-<li><h3>Super-module</h3>
-<ul>
-<li><code><a title="HLAfreq" href="index.html">HLAfreq</a></code></li>
-</ul>
-</li>
-<li><h3><a href="#header-functions">Functions</a></h3>
-<ul class="">
-<li><code><a title="HLAfreq.HLAfreq.AFci" href="#HLAfreq.HLAfreq.AFci">AFci</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.Npages" href="#HLAfreq.HLAfreq.Npages">Npages</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.alleles_unique_in_study" href="#HLAfreq.HLAfreq.alleles_unique_in_study">alleles_unique_in_study</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.betaAB" href="#HLAfreq.HLAfreq.betaAB">betaAB</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.betaCI" href="#HLAfreq.HLAfreq.betaCI">betaCI</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.check_resolution" href="#HLAfreq.HLAfreq.check_resolution">check_resolution</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.collapse_reduced_alleles" href="#HLAfreq.HLAfreq.collapse_reduced_alleles">collapse_reduced_alleles</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.combineAF" href="#HLAfreq.HLAfreq.combineAF">combineAF</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.decrease_resolution" href="#HLAfreq.HLAfreq.decrease_resolution">decrease_resolution</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.default_prior" href="#HLAfreq.HLAfreq.default_prior">default_prior</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.duplicated_sample_size" href="#HLAfreq.HLAfreq.duplicated_sample_size">duplicated_sample_size</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.formatAF" href="#HLAfreq.HLAfreq.formatAF">formatAF</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.getAFdata" href="#HLAfreq.HLAfreq.getAFdata">getAFdata</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.id_duplicated_allele" href="#HLAfreq.HLAfreq.id_duplicated_allele">id_duplicated_allele</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.incomplete_studies" href="#HLAfreq.HLAfreq.incomplete_studies">incomplete_studies</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.makeURL" href="#HLAfreq.HLAfreq.makeURL">makeURL</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.only_complete" href="#HLAfreq.HLAfreq.only_complete">only_complete</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.parseAF" href="#HLAfreq.HLAfreq.parseAF">parseAF</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.plotAFprob" href="#HLAfreq.HLAfreq.plotAFprob">plotAFprob</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.population_coverage" href="#HLAfreq.HLAfreq.population_coverage">population_coverage</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.single_loci" href="#HLAfreq.HLAfreq.single_loci">single_loci</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq.unmeasured_alleles" href="#HLAfreq.HLAfreq.unmeasured_alleles">unmeasured_alleles</a></code></li>
-</ul>
-</li>
-</ul>
-</nav>
-</main>
-<footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.8.1</a>.</p>
-</footer>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/9.12.0/highlight.min.js"></script>
-<script>hljs.initHighlightingOnLoad()</script>
-</body>
-</html>
\ No newline at end of file
diff --git a/docs/HLAfreq/HLAfreq_data.html b/docs/HLAfreq/HLAfreq_data.html
deleted file mode 100644
index 6daf4b7..0000000
--- a/docs/HLAfreq/HLAfreq_data.html
+++ /dev/null
@@ -1,109 +0,0 @@
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-<title>HLAfreq.HLAfreq_data API documentation</title>
-<meta name="description" content="Data loaders" />
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-<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}#sidebar > *:last-child{margin-bottom:2cm}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{margin-top:.6em;font-weight:bold}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
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-<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
-</head>
-<body>
-<main>
-<article id="content">
-<header>
-<h1 class="title">Module <code>HLAfreq.HLAfreq_data</code></h1>
-</header>
-<section id="section-intro">
-<p>Data loaders</p>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">&#34;&#34;&#34;
-Data loaders
-&#34;&#34;&#34;
-import pkg_resources
-import pandas as pd
-
-def load_countries():
-    stream = pkg_resources.resource_stream(__name__, &#39;data/countries.csv&#39;)
-    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)
-
-def load_HLA1supertypes_Sidney2008():
-    stream = pkg_resources.resource_stream(__name__, &#39;data/HLA1supertypes_Sidney2008.csv&#39;)
-    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
-</details>
-</section>
-<section>
-</section>
-<section>
-</section>
-<section>
-<h2 class="section-title" id="header-functions">Functions</h2>
-<dl>
-<dt id="HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008"><code class="name flex">
-<span>def <span class="ident">load_HLA1supertypes_Sidney2008</span></span>(<span>)</span>
-</code></dt>
-<dd>
-<div class="desc"></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def load_HLA1supertypes_Sidney2008():
-    stream = pkg_resources.resource_stream(__name__, &#39;data/HLA1supertypes_Sidney2008.csv&#39;)
-    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
-</details>
-</dd>
-<dt id="HLAfreq.HLAfreq_data.load_countries"><code class="name flex">
-<span>def <span class="ident">load_countries</span></span>(<span>)</span>
-</code></dt>
-<dd>
-<div class="desc"></div>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def load_countries():
-    stream = pkg_resources.resource_stream(__name__, &#39;data/countries.csv&#39;)
-    return pd.read_csv(stream, encoding=&#39;latin-1&#39;)</code></pre>
-</details>
-</dd>
-</dl>
-</section>
-<section>
-</section>
-</article>
-<nav id="sidebar">
-<h1>Index</h1>
-<div class="toc">
-<ul></ul>
-</div>
-<ul id="index">
-<li><h3>Super-module</h3>
-<ul>
-<li><code><a title="HLAfreq" href="index.html">HLAfreq</a></code></li>
-</ul>
-</li>
-<li><h3><a href="#header-functions">Functions</a></h3>
-<ul class="">
-<li><code><a title="HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008" href="#HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008">load_HLA1supertypes_Sidney2008</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq_data.load_countries" href="#HLAfreq.HLAfreq_data.load_countries">load_countries</a></code></li>
-</ul>
-</li>
-</ul>
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diff --git a/docs/HLAfreq/index.html b/docs/HLAfreq/index.html
deleted file mode 100644
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--- a/docs/HLAfreq/index.html
+++ /dev/null
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-<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
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-<meta name="description" content="" />
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-<body>
-<main>
-<article id="content">
-<header>
-<h1 class="title">Package <code>HLAfreq</code></h1>
-</header>
-<section id="section-intro">
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">from .HLAfreq import *</code></pre>
-</details>
-</section>
-<section>
-<h2 class="section-title" id="header-submodules">Sub-modules</h2>
-<dl>
-<dt><code class="name"><a title="HLAfreq.HLAfreq" href="HLAfreq.html">HLAfreq.HLAfreq</a></code></dt>
-<dd>
-<div class="desc"><p>HLAfreq …</p></div>
-</dd>
-<dt><code class="name"><a title="HLAfreq.HLAfreq_data" href="HLAfreq_data.html">HLAfreq.HLAfreq_data</a></code></dt>
-<dd>
-<div class="desc"><p>Data loaders</p></div>
-</dd>
-</dl>
-</section>
-<section>
-</section>
-<section>
-</section>
-<section>
-</section>
-</article>
-<nav id="sidebar">
-<h1>Index</h1>
-<div class="toc">
-<ul></ul>
-</div>
-<ul id="index">
-<li><h3><a href="#header-submodules">Sub-modules</a></h3>
-<ul>
-<li><code><a title="HLAfreq.HLAfreq" href="HLAfreq.html">HLAfreq.HLAfreq</a></code></li>
-<li><code><a title="HLAfreq.HLAfreq_data" href="HLAfreq_data.html">HLAfreq.HLAfreq_data</a></code></li>
-</ul>
-</li>
-</ul>
-</nav>
-</main>
-<footer id="footer">
-<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.8.1</a>.</p>
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From dc11d339464dddfbb056ce2a46b2ace2ca15bbe7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:30:46 +0100
Subject: [PATCH 065/192] Update readme

---
 README.md | 38 +++++++++++++++++++++++++++++++++++++-
 1 file changed, 37 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index f9da90a..f3ded39 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@ default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-A note on credible intervals...
+A note on credible intervals... **(to be written)**
 
 When selecting a panel of HLA alleles to represent a population,
 allele frequency is not the only thing to consider. Depending on
@@ -23,9 +23,45 @@ the purpose of the panel, you should include a range of loci and
 supertypes (groups alleles sharing binding specificies).
 
 ## Install
+```
+pip install HLAfreq
+```
 
 ## Minimal example
+Download HLA data using `makeURL()` and `getAFdata()`.
+All arguments that can be specified in the webpage form are available,
+see `help(HLAfreq.makeURL)` for details (press `q` to exit).
+```
+import HLAfreq
+base_url = HLAfreq.makeURL("Uganda", locus="A")
+aftab = HLAfreq.getAFdata(base_url)
+```
+
+After downloading the data, it must be filtered so that all studies
+sum to allele frequency 1 (within tolerence). Then we must ensure
+that all studies report alleles at the same resolution.
+Finaly we can combine frequency estimates.
+```
+aftab = HLAfreq.only_complete(aftab)
+aftab = HLAfreq.decrease_resolution(aftab, 2)
+caf = HLAfreq.combineAF(aftab)
+```
 
 ## Detailed examples
+For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
+
+- [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
+- [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
+- [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
+
+## Docs
+Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/blob/main/docs/HLAfreq.md)
+created with pdoc3 in pdf mode.
+
+<!-- ## Developer notes
+Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
+Build with `pythom -m build`.
+Run tests `pytest` -->
 
 ## Citation
+*In prep.*

From 56007a7a694533498b92f633ec9552dfa3701e6e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:37:57 +0100
Subject: [PATCH 066/192] Improve readme

---
 README.md                          | 5 +++--
 examples/working_with_priors.ipynb | 2 +-
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index f3ded39..0e66461 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
 # HLAfreq
 
-`HLAfreq` allows you to estimate the HLA allele
-frequencies at large multi population scale, e.g. combine data from
+`HLAfreq` allows you to download and combine HLA allele
+frequencies from multiple datasets, e.g. combine data from
 several studies within a country or combine countries.
 
 Automated download of allele frequency data download from 
@@ -55,6 +55,7 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 - [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
 
 ## Docs
+For help on specific functions view the docstring, `help(function_name)`.
 Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/blob/main/docs/HLAfreq.md)
 created with pdoc3 in pdf mode.
 
diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
index 7842450..d10356b 100644
--- a/examples/working_with_priors.ipynb
+++ b/examples/working_with_priors.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# working with priors\n",
+    "# Working with priors\n",
     "\n",
     "In Bayesian statistics a prior is used to specify prior belief.\n",
     "Working with priors to improve estimates of undersampled populations.\n",

From 23083520ce86966590dd1fedbfb1464ddc1a9707 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Oct 2022 14:41:14 +0100
Subject: [PATCH 067/192] Update build 0.0.1.dev1

---
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl | Bin 15147 -> 14842 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz           | Bin 16495 -> 15839 bytes
 dist/HLAfreq-0.0.1.dev1-py3-none-any.whl | Bin 0 -> 15602 bytes
 dist/HLAfreq-0.0.1.dev1.tar.gz           | Bin 0 -> 17215 bytes
 setup.py                                 |   2 +-
 src/HLAfreq.egg-info/PKG-INFO            |  45 +++++++++++++++++++++--
 6 files changed, 42 insertions(+), 5 deletions(-)
 create mode 100644 dist/HLAfreq-0.0.1.dev1-py3-none-any.whl
 create mode 100644 dist/HLAfreq-0.0.1.dev1.tar.gz

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HcmV?d00001

diff --git a/setup.py b/setup.py
index 96a1b7f..ac0b840 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.1dev0",
+    version="0.0.1dev1",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index 8ec355b..afaa5d5 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: HLAfreq
-Version: 0.0.1.dev0
+Version: 0.0.1.dev1
 Summary: Download and combine HLA frequency data from multiple studies
 Home-page: https://github.com/Vaccitech/HLAfreq
 Author: David Wells
@@ -12,8 +12,8 @@ Description-Content-Type: text/markdown
 
 # HLAfreq
 
-`HLAfreq` allows you to estimate the HLA allele
-frequencies at large multi population scale, e.g. combine data from
+`HLAfreq` allows you to download and combine HLA allele
+frequencies from multiple datasets, e.g. combine data from
 several studies within a country or combine countries.
 
 Automated download of allele frequency data download from 
@@ -27,7 +27,7 @@ default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-A note on credible intervals...
+A note on credible intervals... **(to be written)**
 
 When selecting a panel of HLA alleles to represent a population,
 allele frequency is not the only thing to consider. Depending on
@@ -35,9 +35,46 @@ the purpose of the panel, you should include a range of loci and
 supertypes (groups alleles sharing binding specificies).
 
 ## Install
+```
+pip install HLAfreq
+```
 
 ## Minimal example
+Download HLA data using `makeURL()` and `getAFdata()`.
+All arguments that can be specified in the webpage form are available,
+see `help(HLAfreq.makeURL)` for details (press `q` to exit).
+```
+import HLAfreq
+base_url = HLAfreq.makeURL("Uganda", locus="A")
+aftab = HLAfreq.getAFdata(base_url)
+```
+
+After downloading the data, it must be filtered so that all studies
+sum to allele frequency 1 (within tolerence). Then we must ensure
+that all studies report alleles at the same resolution.
+Finaly we can combine frequency estimates.
+```
+aftab = HLAfreq.only_complete(aftab)
+aftab = HLAfreq.decrease_resolution(aftab, 2)
+caf = HLAfreq.combineAF(aftab)
+```
 
 ## Detailed examples
+For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
+
+- [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
+- [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
+- [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
+
+## Docs
+For help on specific functions view the docstring, `help(function_name)`.
+Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/blob/main/docs/HLAfreq.md)
+created with pdoc3 in pdf mode.
+
+<!-- ## Developer notes
+Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
+Build with `pythom -m build`.
+Run tests `pytest` -->
 
 ## Citation
+*In prep.*

From 3bdb5ce61bc21de29269ce1f5600765b6c820a0d Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 18 Oct 2022 11:22:42 +0100
Subject: [PATCH 068/192] improve hla panel plot

---
 examples/paper/select_hla_panel.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/examples/paper/select_hla_panel.py b/examples/paper/select_hla_panel.py
index 886db7a..166b184 100644
--- a/examples/paper/select_hla_panel.py
+++ b/examples/paper/select_hla_panel.py
@@ -69,9 +69,11 @@
 plt.barh()
 for region in df.largeRegion.unique():
     mask = df.largeRegion == region
-    plt.barh(df[mask].country, df[mask].coverage, label=region)
-plt.axvline(0.95, linestyle="--", c="black")
-plt.legend()
+    plt.barh(df[mask].country, df[mask].coverage, label=region, zorder=3)
+plt.axvline(0.95, linestyle="--", c="black", zorder=5)
+plt.tight_layout()
+plt.legend(loc="upper left")
+plt.grid(zorder=0)
 plt.show()
 
 #############
@@ -93,6 +95,7 @@
 # Population proportion with no IEDB ref alleles
 # at HLA A or HLA B
 coverage = 1 - ((1-p)**2 * (1-m)**2)
+print(coverage)
 
 cafa = cafa.sort_values("allele_freq", ascending=False, ignore_index=True)
 cafb = cafb.sort_values("allele_freq", ascending=False, ignore_index=True)

From 20184a8c8d0d391c2d6cb79b5d1fc4d51243d408 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 1 Nov 2022 09:25:50 +0000
Subject: [PATCH 069/192] Add blurb to readme

---
 README.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/README.md b/README.md
index 0e66461..f292c23 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,9 @@
 `HLAfreq` allows you to download and combine HLA allele
 frequencies from multiple datasets, e.g. combine data from
 several studies within a country or combine countries.
+Useful for studying regional diversity in immune genes
+and, when paired with epitope prediction, estimating a population's ability to mount an immune response to
+ specific epitopes.
 
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).

From c8f0ad61b2c5973fc7e7328775aac32c58b1dff8 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 1 Nov 2022 09:48:32 +0000
Subject: [PATCH 070/192] edit blurb spacing

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index f292c23..c9dcd56 100644
--- a/README.md
+++ b/README.md
@@ -4,8 +4,8 @@
 frequencies from multiple datasets, e.g. combine data from
 several studies within a country or combine countries.
 Useful for studying regional diversity in immune genes
-and, when paired with epitope prediction, estimating a population's ability to mount an immune response to
- specific epitopes.
+and, when paired with epitope prediction, estimating a population's
+ability to mount an immune response to specific epitopes.
 
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).

From d0ab8eb2e252a941aaca858bdf1940dc936b8aae Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 4 Nov 2022 17:10:31 +0000
Subject: [PATCH 071/192] Ignore paper write ups

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index c1bd234..0c81704 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,5 @@
 data/
 docs/
+paper/
 *__pycache__/
 *.code-workspace

From 49f10008d7e43eb99da066c853795cd8831a8a67 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 4 Nov 2022 17:12:40 +0000
Subject: [PATCH 072/192] Use prior for Venezuela and plot result

---
 examples/paper/globalPCA.py  | 41 ++++++++++++++++++++++++++++++++++--
 examples/paper/globalPCA2.py | 13 ++++++++++++
 2 files changed, 52 insertions(+), 2 deletions(-)

diff --git a/examples/paper/globalPCA.py b/examples/paper/globalPCA.py
index b5c0fcf..1d0637d 100644
--- a/examples/paper/globalPCA.py
+++ b/examples/paper/globalPCA.py
@@ -10,7 +10,7 @@
 """
 
 import os
-import code.HLAfreq as HLAfreq
+import HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
 
@@ -20,6 +20,9 @@
 
 countries = regions.Country.tolist()
 
+############
+# Download data
+############
 # Download HLA allele frequencies
 # Not all countries have data
 # those without will print "Failed to get data for..."
@@ -34,6 +37,37 @@
         except:
             print(f"Failed to get data for {country}: {base_url}")
 
+############
+# Using prior for Venezuela
+############
+# Load Venezuela data
+country = "Venezuela"
+venezuelaAF = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+venezuelaAF = HLAfreq.only_complete(venezuelaAF)
+venezuelaAF = HLAfreq.decrease_resolution(venezuelaAF, 2)
+cafV = HLAfreq.combineAF(venezuelaAF)
+
+# Load Colombia data
+country = "Colombia"
+colombiaAF = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
+colombiaAF = HLAfreq.only_complete(colombiaAF)
+colombiaAF = HLAfreq.decrease_resolution(colombiaAF, 2)
+cafC = HLAfreq.combineAF(colombiaAF)
+cafC['country'] = country
+cafC['population'] = country
+
+# Create a prior from Colombia
+study_prior = cafC.copy()
+study_prior.sample_size = study_prior.sample_size / 30
+# Combine Allele Frequency with Study Prior
+cafSP = HLAfreq.combineAF(
+    pd.concat([venezuelaAF, study_prior], join="inner")
+    )
+cafSP['country'] = "Venezuela with prior"
+
+############
+# Load each country data
+############
 cafs = []
 for country in countries:
     try:
@@ -46,6 +80,9 @@
     except:
         pass
 
+# Add Venezuela with prior to dataset
+cafs.append(cafSP)
+
 cafs = pd.concat(cafs, axis=0).reset_index(drop=True)
 
 # Give record for all alleles to all countries
@@ -62,7 +99,7 @@
 sorted_alleles = sorted(list(cafs.allele.unique()))
 
 AFeatures = []
-for country in countries:
+for country in cafs.country.unique():
     mask = cafs['country'] == country
     # Only generate features for countries with records
     # e.g. Thailand has no loci A records
diff --git a/examples/paper/globalPCA2.py b/examples/paper/globalPCA2.py
index 9e86bd3..182c10b 100644
--- a/examples/paper/globalPCA2.py
+++ b/examples/paper/globalPCA2.py
@@ -11,6 +11,7 @@
 
 # Use umap conda env
 
+import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 from sklearn.decomposition import PCA
@@ -32,6 +33,11 @@
 # Add region to countries
 AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
 
+# Select Venezuela With Prior
+vwp = AFeatures[AFeatures.country == "Venezuela with prior"]
+# Drop countries without largeRegion, this is Venezuela with a prior
+AFeatures = AFeatures.dropna(subset=['largeRegion'])
+
 # plt.style.use('fivethirtyeight')
 
 for region in AFeatures.largeRegion.unique():
@@ -40,6 +46,13 @@
     for i in AFeatures[mask].index:
         plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['pca0','pca1']])
 plt.legend()
+# Arrow shows change of Venezuela with prior
+plt.annotate(
+    "",
+    xy=(vwp.pca0, vwp.pca1),
+    xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
+    arrowprops=dict(arrowstyle="->")
+    )
 plt.show()
 
 for region in AFeatures.largeRegion.unique():

From 5b2a81a13ec5258eb7a5ebb77161f6033352d6cb Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 4 Nov 2022 17:12:52 +0000
Subject: [PATCH 073/192] Basic use case for paper

---
 examples/paper/basic_use_case.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)
 create mode 100644 examples/paper/basic_use_case.py

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
new file mode 100644
index 0000000..5207868
--- /dev/null
+++ b/examples/paper/basic_use_case.py
@@ -0,0 +1,14 @@
+import matplotlib.pyplot as plt
+from HLAfreq import makeURL, getAFdata, combineAF, plotAFprob, population_coverage
+
+base_url = makeURL("Mongolia", standard="g", locus="DQB1")
+aftab = getAFdata(base_url)
+aftab.population.unique()
+caf = combineAF(aftab)
+plotAFprob(caf, aftab, ncol=2, xmin=-0.02, xmax=0.5)
+
+caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
+plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+plt.tight_layout(); plt.show()

From c493ef6768f5e89d3891d91493a026edcab6e1bd Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 4 Nov 2022 17:13:50 +0000
Subject: [PATCH 074/192] Rename paper > writeup and update gitignore

Required because paper is already a folder that does need version control
---
 .gitignore | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 0c81704..b6da47c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,5 @@
 data/
 docs/
-paper/
+writeup/
 *__pycache__/
 *.code-workspace

From 4b408e4a60fe8e7fdf9f1a96d029ae4977ae1395 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Dec 2022 10:12:42 +0000
Subject: [PATCH 075/192] Improve examples

---
 examples/multi_country.ipynb       |  3 +-
 examples/paper/entropy_map.py      |  2 +-
 examples/paper/globalPCA2.py       |  5 +-
 examples/paper/select_hla_panel.py | 92 ++++++------------------------
 4 files changed, 26 insertions(+), 76 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index a9e3759..8b9d302 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -99,11 +99,12 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Combine all country data\n",
-    "Concatenate each single county dataset into a single country.\n",
+    "Concatenate each single county dataset into a single multicountry dataset.\n",
     "Combine allele frequencies, using the manually added `country` column as `datasetID`."
    ]
   },
diff --git a/examples/paper/entropy_map.py b/examples/paper/entropy_map.py
index d23ee0e..55c69f9 100644
--- a/examples/paper/entropy_map.py
+++ b/examples/paper/entropy_map.py
@@ -53,7 +53,7 @@
 # Some of this is due to alternative naming
 # Will require manual editting.
 
-#regions not in world
+# Regions not in world
 regions[~regions.country.isin(world.name)].country
 # world not in regions
 world.name[~world.name.isin(regions.country)]
diff --git a/examples/paper/globalPCA2.py b/examples/paper/globalPCA2.py
index 182c10b..d369912 100644
--- a/examples/paper/globalPCA2.py
+++ b/examples/paper/globalPCA2.py
@@ -40,7 +40,9 @@
 
 # plt.style.use('fivethirtyeight')
 
-for region in AFeatures.largeRegion.unique():
+regions = AFeatures.largeRegion.unique()
+regions.sort()
+for region in regions:
     mask = AFeatures.largeRegion == region
     plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
     for i in AFeatures[mask].index:
@@ -53,6 +55,7 @@
     xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
     arrowprops=dict(arrowstyle="->")
     )
+plt.xlabel('1st principal component'); plt.ylabel('2nd principal component')
 plt.show()
 
 for region in AFeatures.largeRegion.unique():
diff --git a/examples/paper/select_hla_panel.py b/examples/paper/select_hla_panel.py
index 166b184..90f31da 100644
--- a/examples/paper/select_hla_panel.py
+++ b/examples/paper/select_hla_panel.py
@@ -4,11 +4,12 @@
 populations, being sure to select a range of supertypes.
 """
 
-import code.HLAfreq as HLAfreq
+import HLAfreq
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 
+# The IEDB reference panel
 iedb_ref = ['B*35:01', 'A*30:01', 'A*02:03', 'B*15:01', 'B*57:01', 'A*68:02', 'A*23:01', 'B*53:01', 'A*03:01', 'B*40:01', 'B*44:02', 'B*51:01', 'A*33:01', 'A*01:01', 'A*68:01', 'A*24:02', 'B*07:02', 'B*08:01', 'A*02:06', 'A*26:01', 'A*11:01', 'A*30:02', 'A*31:01', 'B*58:01', 'B*44:03', 'A*32:01', 'A*02:01']
 
 regions = pd.read_csv("data/example/countries.csv")
@@ -38,6 +39,10 @@
 iedb_cov = []
 iedb_country = []
 
+# Load and combine within country data for HLA-A and HLA-B separately
+# Calculate the proportion of each population with no alleles
+# in the IEDB reference set, assuming no linkage disequilibrium
+# between HLA-A and HLA-B
 for country in countries:
     try:
         afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
@@ -65,18 +70,24 @@
 df = df.sort_values('coverage')
 df = pd.merge(df, regions, how="left", left_on="country", right_on="Country")
 
+# Plot the proportion of each population with no alleles
+# in the IEDB reference set, assuming no linkage disequilibrium
+# between HLA-A and HLA-B
 plt.barh(df.country, df.coverage, color="black")
-plt.barh()
-for region in df.largeRegion.unique():
+regions = df.largeRegion.unique()
+regions.sort()
+for region in regions:
     mask = df.largeRegion == region
     plt.barh(df[mask].country, df[mask].coverage, label=region, zorder=3)
-plt.axvline(0.95, linestyle="--", c="black", zorder=5)
+plt.axvline(0.97, linestyle="--", c="black", zorder=5)
 plt.tight_layout()
 plt.legend(loc="upper left")
 plt.grid(zorder=0)
 plt.show()
 
 #############
+# Plot the cumulative allele frequency of HLA-A and HLA-B
+# a single country, with alleles coloured by supertype
 country = "Indonesia"
 # country="Philippines"
 afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
@@ -145,72 +156,7 @@
 #   Design a new panel  #
 #                       #
 #########################
-
-def multilocus_homozygous_coverage(AFs):
-    coverage = np.prod([p**2 for p in AFs])
-    return coverage
-
-def remainingAF(x, cumAF, is_locus):
-    return [1-c-x*modifier for c,modifier in zip(cumAF, is_locus)]
-    
-
-def population_uncoverage(row, covered_dict):
-    loci = np.array(list(covered_dict.keys()))
-    is_locus = loci == row.loci
-    remains = remainingAF(row.allele_freq, covered_dict.values(), is_locus)
-    uncovered = multilocus_homozygous_coverage(remains)
-    return uncovered
-
-def sum_panel_AF(panel, locus):
-    return sum([x.allele_freq for x in panel if x.loci == locus])
-
-all_loci = pd.concat([cafa, cafb], ignore_index=True)
-
-covered_dict = {
-    'A':0,
-    'B':0
-}
-panel = []
-mask = [True] *  all_loci.shape[0]
-
-for n in range(4):
-    # Select allele
-    i = all_loci[mask].apply(population_uncoverage, axis=1, args=[covered_dict]).idxmin()
-    # Add selected allele to panel
-    panel.append(all_loci.loc[i])
-    # Update mask to omited selected loci from choice
-    mask = ~all_loci.allele.isin([x.allele for x in panel])
-    # Update coverd_dict
-    covered_dict = {key: sum_panel_AF(panel, key) for key, value in covered_dict.items()}
-
-
-panel = pd.concat(panel, axis=1, ignore_index=True).T
-panel
-
-# To my surprise it generally favours adding more alleles to which
-# ever locus already has the highest cumulative frequency
-
-def f(p,m):
-    return (1-p)**2*(1-m)**2
-    # return (1-p)*(1-m)
-
-# def f(q,n):
-    # return (q**2) * (n**2)
-    # return q*n
-
-x = np.linspace(1, 0, 21)
-y = np.linspace(1, 0, 21)
-z = np.array([f(j,i) for j in y for i in x])
-X, Y = np.meshgrid(x, y)
-Z = z.reshape(21, 21)
-
-from matplotlib import cm
-# Plot the surface.
-fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
-surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
-                       linewidth=0, antialiased=False)
-plt.show()
-
-plt.plot(f(0.2, x))
-plt.plot(f(0.8, x))
-plt.show()
\ No newline at end of file
+# When selecting a panel of HLA alleles to represent a country,
+# consider different genes,
+# and different supertypes,
+# not only the most common alleles.
\ No newline at end of file

From f0f7e2bbdfdc628d787fc902930e763554361b0a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 8 Dec 2022 10:13:34 +0000
Subject: [PATCH 076/192] Add title to plotAFprob

---
 src/HLAfreq/HLAfreq.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 5b7c6fd..b1858a8 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -553,6 +553,7 @@ def allele_mask(alleles, concentration):
         assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
     mask = allele_mask(alleles, concentration)
     fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
+    fig.suptitle("Allele frequency vs probability density")
     # Only indexes that pass the mask
     masked_indexes = [i for i,x in enumerate(mask) if x]
     for subploti,i in enumerate(masked_indexes):

From 96372611f874e8d9075d7033f178bd3b2bbcf6f8 Mon Sep 17 00:00:00 2001
From: DAWells <49305334+DAWells@users.noreply.github.com>
Date: Wed, 11 Jan 2023 16:52:49 +0000
Subject: [PATCH 077/192] Create LICENSE

---
 LICENSE | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)
 create mode 100644 LICENSE

diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..506480a
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2022 Vaccitech PLC
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

From d73f581198ba35f22509aaadf69eaa6e204d517a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 18 Jan 2023 21:48:59 +0000
Subject: [PATCH 078/192] Calculate confidence intervals on simulated data

---
 examples/CI_simulated_data.py | 92 +++++++++++++++++++++++++++++++++++
 1 file changed, 92 insertions(+)
 create mode 100644 examples/CI_simulated_data.py

diff --git a/examples/CI_simulated_data.py b/examples/CI_simulated_data.py
new file mode 100644
index 0000000..b889c2d
--- /dev/null
+++ b/examples/CI_simulated_data.py
@@ -0,0 +1,92 @@
+"""
+Estimate confidence intervals on simulated data
+using pymc and pymc_env
+"""
+
+import pymc as pm
+import matplotlib.pyplot as plt
+import numpy as np
+import arviz as az
+import pandas as pd
+import scipy as sp
+
+def simulateAF(k, concentration, n, samplesize_lo=5, samplesize_hi=200):
+    """ Simulate allele frequency dataset for k alleles and n populations.
+    The global allele frequency is a random draw from a uniform Dirichlet.
+    This is used with the concentration parameter to define a new dirichlet.
+    Each of n populations is then an independent draw from this new Dirichlet.
+    The observed allele_counts then use these population allele frequencies to
+    define a multinomial distribution and take a random number of samples from it.
+    The range of posible sample size is between samplesize_lo and samplesize_hi.
+    """
+    # Global AF
+    alpha = sp.stats.dirichlet(np.ones(k)).rvs()
+    alpha = alpha.reshape(-1)
+    # The Dirichlet distribution which populations are drawn from
+    dd = sp.stats.dirichlet(alpha*concentration)
+    # Population AF
+    popAF =  dd.rvs(n)
+    sample_size = np.random.randint(samplesize_lo, samplesize_hi, size=n)
+    allele_counts = np.vstack([sp.stats.multinomial(n=samples, p=af).rvs() for samples,af in zip(sample_size, popAF)])
+    return alpha, popAF, allele_counts
+
+results = []
+for i in range(100):
+    print(i)
+    alpha, popAF, allele_counts = simulateAF(4, 10, 3)
+
+    # Key data derived from simulated data
+    # Number of alleles
+    k = len(alpha)
+    # Number of populations
+    n = popAF.shape[0]
+    # Sample size for each population
+    sample_size = np.apply_along_axis(sum, 1, allele_counts)
+
+    # Define and fit model
+    with pm.Model() as m1:
+        frac = pm.Dirichlet('frac', a=np.ones(k))
+        conc = pm.Lognormal('conc', mu=1, sigma=1)
+        y = pm.DirichletMultinomial('y', n=sample_size, a=frac*conc, shape=(n,k), observed=allele_counts)
+
+    with m1:
+        idata1 = pm.sample()
+
+    # Store results
+    result = {
+        'lo': az.summary(idata1)[:k]['hdi_3%'],
+        'hi':az.summary(idata1)[:k]['hdi_97%'],
+        'alpha': alpha,
+        'popAF': popAF
+    }
+    results.append(result)
+
+# View summary results
+def alpha_in_hdi(result):
+    """What proportion of true global allele frequencies are in the estimated hdi?"""
+    in_hdi = (result['lo'] < result['alpha']) & (result['alpha'] < result['hi'])
+    aih = in_hdi.mean()
+    return aih
+
+def popAF_in_hdi(result):
+    """What proportion of true population allele frequencies are in the estimated hdi?
+    Note that the hdi applies to the global allele frequency."""
+    in_hdi = np.apply_along_axis(lambda x: (result['lo']<x)&(x<result['hi']), 1, result['popAF'])
+    pih = in_hdi.mean()
+    return pih
+
+aih = [alpha_in_hdi(result) for result in results]
+pih = [popAF_in_hdi(result) for result in results]
+
+# 97% simulated global AF are within the estimated hdi intervals
+np.mean(aih)
+# 80% simulated population AF are within the estimated hdi intervals
+# This is expected to be <95% because the hdi is on the global AF
+np.mean(pih)
+
+fig, ax = plt.subplots(2)
+ax[0].hist(aih)
+ax[0].axvline(np.mean(aih), color="black")
+ax[1].hist(pih)
+ax[1].axvline(np.mean(pih), color="black")
+plt.show()

From 1149d379bc360926d3fe2697fea17fdb2615ec7d Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 19 Jan 2023 17:51:19 +0000
Subject: [PATCH 079/192] Use more realistic simulation parameters

---
 examples/CI_simulated_data.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/examples/CI_simulated_data.py b/examples/CI_simulated_data.py
index b889c2d..715d9bf 100644
--- a/examples/CI_simulated_data.py
+++ b/examples/CI_simulated_data.py
@@ -33,7 +33,7 @@ def simulateAF(k, concentration, n, samplesize_lo=5, samplesize_hi=200):
 results = []
 for i in range(100):
     print(i)
-    alpha, popAF, allele_counts = simulateAF(4, 10, 3)
+    alpha, popAF, allele_counts = simulateAF(k=15, concentration=10, n=5)
 
     # Key data derived from simulated data
     # Number of alleles
@@ -78,9 +78,9 @@ def popAF_in_hdi(result):
 aih = [alpha_in_hdi(result) for result in results]
 pih = [popAF_in_hdi(result) for result in results]
 
-# 97% simulated global AF are within the estimated hdi intervals
+# 95-97% simulated global AF are within the estimated hdi intervals
 np.mean(aih)
-# 80% simulated population AF are within the estimated hdi intervals
+# 50-80% simulated population AF are within the estimated hdi intervals
 # This is expected to be <95% because the hdi is on the global AF
 np.mean(pih)
 

From e5476494c2264a4b09662ca466682c7b5050b714 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 19 Jan 2023 17:52:18 +0000
Subject: [PATCH 080/192] Use pymc to estimate HDI for empirical data

---
 examples/CI_empirical_data.py | 99 +++++++++++++++++++++++++++++++++++
 src/HLAfreq/HLAfreq.py        |  8 +--
 src/HLAfreq/HLAfreq_pymc.py   | 70 +++++++++++++++++++++++++
 3 files changed, 173 insertions(+), 4 deletions(-)
 create mode 100644 examples/CI_empirical_data.py
 create mode 100644 src/HLAfreq/HLAfreq_pymc.py

diff --git a/examples/CI_empirical_data.py b/examples/CI_empirical_data.py
new file mode 100644
index 0000000..6d987de
--- /dev/null
+++ b/examples/CI_empirical_data.py
@@ -0,0 +1,99 @@
+"""
+CI empirical data
+"""
+
+import HLAfreq
+from HLAfreq import HLAfreq_pymc as HLAhdi
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+import pymc as pm
+import numpy as np
+import arviz as az
+import pandas as pd
+import scipy as sp
+
+#                   #
+#   Download data   #
+#                   #
+
+country = "Thailand"
+locus = "DRB1"
+
+country = "Mongolia"
+locus = "DQB1"
+
+base_url = HLAfreq.makeURL(country, locus=locus)
+aftab = HLAfreq.getAFdata(base_url)
+aftab = HLAfreq.only_complete(aftab)
+HLAfreq.check_resolution(aftab)
+aftab = HLAfreq.decrease_resolution(aftab, 2)
+caf = HLAfreq.combineAF(aftab)
+
+HLAfreq.plotAFprob(caf, aftab, xmax=1.1*caf.allele_freq.max())
+
+#                                   #
+#   Calculate credible intervals    #
+#                                   #
+
+# pymc hdi
+hdi = HLAhdi.AFhdi(aftab)
+# Dirichlet only ci, too narrow
+Dci = HLAfreq.AFci(caf)
+
+# To access the model you have to call the internal functions like so
+c_array, allele_names = HLAhdi._make_c_array(aftab)
+idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)
+hdi = az.hdi(idata).frac.values
+
+# Compare dirichlet and pymc estimates and intervals
+shift = .3
+plt.scatter(caf.allele_freq, range(caf.shape[0]))
+plt.scatter(az.summary(idata)['mean'][:-1], shift+pd.Series(range(caf.shape[0])))
+for i in range(caf.shape[0]):
+    plt.hlines(
+        y = (i),
+        xmin = Dci[i][0],
+        xmax = Dci[i][1]
+    )
+    plt.hlines(
+        y = i+shift,
+        xmin = float(hdi[i][0]),
+        xmax = float(hdi[i][1]),
+        color="tab:orange"
+    )
+plt.show()
+
+# Compare sub populations to country
+aftab['allele_i'] = ""
+for i,allele in enumerate(caf.allele):
+    aftab.loc[aftab.allele==allele,'allele_i'] = i
+
+for i in range(caf.shape[0]):
+    plt.hlines(
+        y = i,
+        xmin = float(hdi[i][0]),
+        xmax = float(hdi[i][1]),
+        color="black"
+    )
+    plt.hlines(
+        y = i,
+        xmin = float(Dci[i][0]),
+        xmax = float(Dci[i][1]),
+        color="red",
+    )
+    # mask = aftab.allele==caf.allele[i]
+    # plt.scatter(
+    #     aftab[mask].allele_freq,
+    #     [i] * mask.sum()
+    # )
+for pop in aftab.population.unique():
+    pop
+    mask = aftab.population == pop
+    plt.scatter(
+        aftab[mask].allele_freq,
+        aftab[mask].allele_i
+    )
+plt.scatter(caf.allele_freq, range(caf.shape[0]), color='black')
+plt.show()
diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index b1858a8..afac728 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -14,7 +14,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import math
-from scipy.stats import dirichlet, beta
+import scipy as sp
 import logging
 import warnings
 
@@ -391,7 +391,7 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
         alpha = default_prior(len(combined.allele))
     combined['alpha'] = alpha
     # Calculate Dirichlet mean for each allele
-    combined['allele_freq'] = dirichlet(combined.alpha + combined.c).mean()
+    combined['allele_freq'] = sp.stats.dirichlet(combined.alpha + combined.c).mean()
 
     return combined
 
@@ -482,7 +482,7 @@ def betaCI(a,b,credible_interval=0.95):
     Returns:
         tuple: Lower and upper credible interval of beta distribution.
     """
-    bd = beta(a,b)
+    bd = sp.stats.beta(a,b)
     lower_quantile = (1-credible_interval)/2
     upper_quantile = 1-lower_quantile
     lower_interval = bd.ppf(lower_quantile)
@@ -559,7 +559,7 @@ def allele_mask(alleles, concentration):
     for subploti,i in enumerate(masked_indexes):
         subplotselector = subploti//ncol, subploti%ncol
         a,b = ab[i]
-        bd = beta(a,b)
+        bd = sp.stats.beta(a,b)
         if log:
             pdf = [bd.logpdf(p) for p in pline]
         else:
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
new file mode 100644
index 0000000..0f424a2
--- /dev/null
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -0,0 +1,70 @@
+import math
+import pymc as pm
+import numpy as np
+import arviz as az
+import pandas as pd
+import HLAfreq
+
+def _make_c_array(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
+    df = AFtab.copy()
+    df = HLAfreq.unmeasured_alleles(df, datasetID)
+    try:
+        df['2n'] = df.sample_size * 2
+    except:
+        print("column '2n' could not be created")
+    df['c'] =  df.allele_freq * df[weights]
+
+    # Sort by alleles so it matches the combined alleles
+    df = df.sort_values('allele')
+    c_array = np.array(df.groupby(datasetID).c.apply(list).tolist())
+    allele_names = sorted(df.allele.unique())
+    # Imperfect check that allele order matches between caf and c_array.
+    # caf is sorted automatically so should match sorted AFloc
+    # Therefore we check that sorted AFloc matches c_array
+    # The check is that the sum of allele i is the same
+    for a,b in zip(
+        np.apply_along_axis(sum, 0, c_array),
+        df.groupby('allele').c.sum()
+        ):
+        assert math.isclose(a,b), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
+    return c_array, allele_names
+
+def _fit_Dirichlet_Multinomial(c_array):
+    # Number of populations
+    n = c_array.shape[0]
+    # number of alleles
+    k = c_array.shape[1]
+
+    # Round c array so that it and effective ssamples are whole numbers
+    # for the multinomial
+    c_array = np.round(c_array)
+    effective_samples = np.apply_along_axis(sum, 1, c_array)
+
+    with pm.Model() as mod:
+        frac = pm.Dirichlet('frac', a=np.ones(k))
+        conc = pm.Lognormal('conc', mu=1, sigma=1)
+        y = pm.DirichletMultinomial('y', n=effective_samples, a=frac*conc, shape=(n,k), observed=c_array)
+
+    with mod:
+        idata = pm.sample()
+    return idata
+
+def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
+    """Calculate high posterior density interval on combined allele frequency
+
+    Args:
+        AFtab (pd.DataFrame): Table of allele frequency data
+        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
+        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+    Returns:
+        np.array: Pairs of high density interval limits as a 2 by n array.
+            In alphabetical order of alleles, regardless of input order.
+            This way it matches the output of combineAF().
+    """
+    c_array, allele_names = _make_c_array(AFtab, weights, datasetID, credible_interval)
+    idata = _fit_Dirichlet_Multinomial(c_array)
+    hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
+    hdi = np.column_stack([hdi, allele_names])
+    return hdi
\ No newline at end of file

From 7b2953c6090b4002d61f516aa5ccaebef471f238 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 24 Jan 2023 18:37:17 +0000
Subject: [PATCH 081/192] confidence interval plot based on pymc.

plotAFprob replaced by plotAF
---
 src/HLAfreq/HLAfreq.py      | 232 +++++++++++++++++++-----------------
 src/HLAfreq/HLAfreq_pymc.py |  12 +-
 2 files changed, 131 insertions(+), 113 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index afac728..fa71604 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -17,6 +17,7 @@
 import scipy as sp
 import logging
 import warnings
+import matplotlib.colors as mcolors
 
 def makeURL(
         country="",
@@ -471,124 +472,131 @@ def betaAB(alpha):
     ab = [(a,sum(alpha)-a) for a in alpha]
     return ab
 
-def betaCI(a,b,credible_interval=0.95):
-    """Calculat the central credible interval of a beta distribution
+# def betaCI(a,b,credible_interval=0.95):
+#     """Calculat the central credible interval of a beta distribution
+
+#     Args:
+#         a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
+#         b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
+#         credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+
+#     Returns:
+#         tuple: Lower and upper credible interval of beta distribution.
+#     """
+#     bd = sp.stats.beta(a,b)
+#     lower_quantile = (1-credible_interval)/2
+#     upper_quantile = 1-lower_quantile
+#     lower_interval = bd.ppf(lower_quantile)
+#     upper_interval = bd.ppf(upper_quantile)
+#     return lower_interval, upper_interval
+
+# def AFci(caf, credible_interval=0.95):
+#     """Calculate credible interval for combined allele frequency table.
+#     Note that this ignores sampling error so confidence interval is too tight.
+#     Use HLAhdi.AFhdi() instead.
+
+#     Args:
+#         caf (pd.DataFrame): Table produced by combineAF()
+#         credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
+
+#     Returns:
+#         list: Lower and upper credible intervals as a list of tuples
+#     """
+#     ab = betaAB(
+#         caf.alpha + caf.c,
+#     )
+#     ci = [betaCI(a, b, credible_interval) for a,b in ab]
+#     return ci
+
+def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
+    """Plot probability density function for prior values.
 
     Args:
-        a (float): Beta shape parameter `a`, i.e. the number of times the allele was observed.
-        b (float): Beta shape parameter `b`, i.e. the number of times the allele was not observed.
-        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
-
-    Returns:
-        tuple: Lower and upper credible interval of beta distribution.
+        concentration (list): Vector of the prior Dirichlet concentration values.
+        ncol (int, optional): Number of columns. Defaults to 2.
+        labels (list, optional): Labels for elements of concentration in the same order. Defaults to "".
     """
-    bd = sp.stats.beta(a,b)
-    lower_quantile = (1-credible_interval)/2
-    upper_quantile = 1-lower_quantile
-    lower_interval = bd.ppf(lower_quantile)
-    upper_interval = bd.ppf(upper_quantile)
-    return lower_interval, upper_interval
-
-def AFci(caf, credible_interval=0.95):
-    """Calculate credible interval for combined allele frequency table
-
-    Args:
-        caf (pd.DataFrame): Table produced by combineAF()
-        credible_interval (float, optional): The desired confidence interval. Defaults to 0.95.
-
-    Returns:
-        list: Lower and upper credible intervals as a list of tuples
-    """
-    ab = betaAB(
-        caf.alpha + caf.c,
-    )
-    ci = [betaCI(a, b, credible_interval) for a,b in ab]
-    return ci
+    ab = betaAB(concentration)
+    pline = np.linspace(0, 1, psteps)
+    nrow = math.ceil(len(concentration)/ncol)
+    fig, ax = plt.subplots(nrow, ncol, sharex=True)
+    fig.suptitle("Probability density")
+    # If labels is a list nothing happens,
+    # But if it's a series it converts to a list
+    labels = list(labels)
+    if not labels:
+        labels = [""] * len(concentration)
+    assert len(concentration) == len(labels), "concentration must be same length as labels"
+    for i,alpha in enumerate(concentration):
+        a,b = ab[i]
+        bd = sp.stats.beta(a,b)
+        pdf = [bd.pdf(p) for p in pline]
+        ax.flat[i].plot(pline, pdf)
+        ax.flat[i].set_title(labels[i])
+    for axi in ax[-1,:]:
+        axi.set(xlabel='Allele freq')
+    for axi in ax[:,0]:
+        axi.set(ylabel='PDF')
+    plt.show()
 
-def plotAFprob(caf=pd.DataFrame(), AFtab=pd.DataFrame(), datasetID="population", concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[]):
-    """Plot the posterior density function of all frequencies
-        for all alleles based on concentration for Dirichlet
-        distribution. Supply AFtab to add empirical values to plot.
+def plotAF(
+    caf=pd.DataFrame(),
+    AFtab=pd.DataFrame(),
+    cols = list(mcolors.TABLEAU_COLORS.keys()),
+    datasetID="population",
+    weights = "2n",
+    credible_interval=None,
+    ):
+    """Plot combined allele frequencies, individual allele frequencies,
+    and credible intervals on combined allele frequency estimates.
+    Credible interval is only plotted if a value is given for `credible_interval`.
+    Credible interval is calculated using HLAfreq_pymc.AFhdi() and PyMc.
 
     Args:
-        caf (pd.DataFrame, optional): Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().
-        datasetID (str, optional): The column used to define datasets. Defaults to "population".
-        concentration (pd.Series, optional): Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
-        log (bool, optional): Plot log pdf instead of pdf? Defaults to False.
-        psteps (int, optional): Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
-        ncol (int, optional): How many columns to arrange subplots in. Defaults to 2.
-        xmin (float, optional): Set x axis min. Defaults to -0.05.
-        xmax (float, optional): Set x axis max. Defaults to 1.05.
-        ci (float, optional): Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
-        alleles (list, optional): List of alleles to plot. Plots all if none supplied. Defaults to [].
+        caf (pd.DataFrame, optional): Combined allele frequency estimates from HLAfreq.combineAF. Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): Table of allele frequency data. Defaults to pd.DataFrame().
+        cols (list, optional): List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
+        datasetID (str, optional): Column used to define separate datasets. Defaults to "population".
+        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        credible_interval (float, optional): The credible interval to plot. Defaults to None.
     """
-    def allele_mask(alleles, concentration):
-        """Create boolean mask either to keep only supplied `alleles`. If empty keep all.
-
-        Args:
-            alleles (list): list of alleles
-            concentration (list): Dirichlet concentration
-
-        Returns:
-            list: List of booleans to use as mask
-        """
-        assert isinstance(alleles, list), f"alleles must be a list, not {type(alleles)}"
-        if not alleles:
-            mask = [True] * len(concentration)
-        else:
-            mask = caf.allele.isin(alleles)
-        return mask
-
-    if not concentration:
-        concentration = caf.alpha + caf.c
-    # Get beta parameters for each k in Dirichlet
-    ab = betaAB(concentration)
-    pline = np.linspace(0,1,psteps)
+    # Plot allele frequency for each dataset
     if not AFtab.empty:
-        # Format the population allele frequencies
-        df = AFtab.copy()
-        df = unmeasured_alleles(df, datasetID=datasetID)
-        df = df.sort_values('allele')
-        assert all(df.groupby(datasetID).allele.apply(list).apply(lambda x: x == caf.allele.tolist())), "Alleles not matching between AFtab and caf"
-    mask = allele_mask(alleles, concentration)
-    fig, axs = plt.subplots(math.ceil(sum(mask)/ncol), ncol, sharex=True)
-    fig.suptitle("Allele frequency vs probability density")
-    # Only indexes that pass the mask
-    masked_indexes = [i for i,x in enumerate(mask) if x]
-    for subploti,i in enumerate(masked_indexes):
-        subplotselector = subploti//ncol, subploti%ncol
-        a,b = ab[i]
-        bd = sp.stats.beta(a,b)
-        if log:
-            pdf = [bd.logpdf(p) for p in pline]
-        else:
-            with warnings.catch_warnings():
-                warnings.simplefilter("ignore")
-                pdf = [bd.pdf(p) for p in pline]
-        ax = axs[subplotselector]
-        ax.set_xlim(xmin,xmax)
-        if not AFtab.empty:
-            # Add the empirical allele frequency for each population
-            for af in df.groupby(datasetID).allele_freq.apply(list).apply(lambda x: x[i]):
-                # x is the reported allele freq, y is it's pdf with scatter
-                if log:
-                    ax.scatter(af, bd.logpdf(af)*(0.95+np.random.random()/5))
-                else:
-                    ax.scatter(af, bd.pdf(af)*(0.95+np.random.random()/5))
-        ax.plot(pline, pdf)
-        # Annotate with allele
-        if not caf.empty:
-            ax.text((xmax-xmin)/2, max(pdf)/2, f"{caf.allele.iloc[i]}")
-        # Annotate with concentration
-        # ax.text(0.5, max(pdf)/3, f"Concentration {round(concentration.iloc[i])}")
-        if not caf.empty:
-            # Plot the combined average
-            ax.axvline(caf.allele_freq[i], color="black", ls="--")
-        if ci:
-            cl,cu = betaCI(a,b, ci)
-            ax.axvline(cl, color="black", linestyle="dotted")
-            ax.axvline(cu, color="black", linestyle="dotted")
-        # fig.tight_layout()
+        # Cols must be longer than the list of alleles
+        # If not, repeat the list of cols
+        repeat_cols = np.ceil(len(AFtab[datasetID])/len(cols))
+        repeat_cols = int(repeat_cols)
+        cols = cols * repeat_cols
+        # Make a dictionary mapping datasetID to colours
+        cmap = dict(zip(AFtab[datasetID].unique(), cols))
+        plt.scatter(
+            x = AFtab.allele_freq,
+            y = AFtab.allele,
+            c = [cmap[x] for x in AFtab[datasetID]],
+            alpha = 0.7,
+            zorder=2
+            )
+    # Plot combined allele frequency
+    if not caf.empty:
+        plt.scatter(
+            x = caf.allele_freq,
+            y = caf.allele,
+            edgecolors='black',
+            facecolors='none',
+            zorder=3
+            )
+    # Plot high density interval
+    if credible_interval:
+        assert not AFtab.empty, "AFtab is needed to calculate credible interval"
+        from HLAfreq import HLAfreq_pymc as HLAhdi
+        print("Fitting model with PyMc, make take a few seconds")
+        hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval)
+        for interval in hdi:
+            plt.hlines(
+                y = interval[2],
+                xmin = float(interval[0]),
+                xmax = float(interval[1]),
+                color="black"
+            )
+    plt.grid(zorder=0)
     plt.show()
-
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 0f424a2..04cf1c2 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -50,7 +50,17 @@ def _fit_Dirichlet_Multinomial(c_array):
     return idata
 
 def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
-    """Calculate high posterior density interval on combined allele frequency
+    """Calculate high posterior density interval on combined allele frequency.
+    Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
+    
+    In brief, the global allele frequency is modelled as a Dirichlet distribution,
+    and each population (defined by `datasetID`) is a Dirichlet distribution draw from
+    the global Dirichlet distribution, and the observed allele count data of that
+    population is multinomial count data drawn from the population Dirichlet distribution.
+
+    The observed allele frequencies are transformed into allele counts using `weights`.
+    The variability of population allele frequencies around the global mean is defined
+    by a latent, lognormal variable `conc`.
 
     Args:
         AFtab (pd.DataFrame): Table of allele frequency data

From 23ca8712419488d857013d9ec3209f48c19c8bb7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 24 Jan 2023 18:38:10 +0000
Subject: [PATCH 082/192] Update examples with new plotAF()

---
 examples/multi_country.ipynb       | 200 ++++++++++++++++++++++++-----
 examples/single_country.ipynb      | 173 +++++++++++++++++++++++--
 examples/working_with_priors.ipynb |  73 ++++++-----
 3 files changed, 369 insertions(+), 77 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index 8b9d302..8a98518 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -8,7 +9,7 @@
     "We can calculate the average allele frequency of multiple countries\n",
     "by combining studies within countries and then between countries.\n",
     "This second step is very similar except we set `datasetID` as the country\n",
-    "rather than the population which is the default.\n",
+    "rather than the population, which is the default.\n",
     "\n",
     "The estimates from different countries can be weighted by sample size or another supplied variable such as population size. Both are described below."
    ]
@@ -45,9 +46,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cameroon\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Cape+Verde\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Ghana\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Guinea\n",
+      "3 pages of results\n",
+      "Download complete\n",
+      "Guinea-Bissau\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Kenya\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Sao+Tome+and+Principe\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Senegal\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "South+Africa\n",
+      "3 pages of results\n",
+      "Download complete\n",
+      "Uganda\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Zimbabwe\n",
+      "1 pages of results\n",
+      "Download complete\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "for country in countries:\n",
@@ -68,7 +109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -110,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -152,7 +193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -175,14 +216,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 88 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -192,19 +233,19 @@
    "source": [
     "# Plot international allele frequencies estimates and individual countries\n",
     "# Without filtering\n",
-    "HLAfreq.plotAFprob(international, cafs, datasetID='country', ncol=4)"
+    "HLAfreq.plotAF(international, cafs, datasetID='country')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 24 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -218,13 +259,10 @@
     "# Must be a list\n",
     "hifreq = hifreq.tolist()\n",
     "# Plot only selected alleles\n",
-    "HLAfreq.plotAFprob(\n",
-    "    international,\n",
-    "    cafs,\n",
-    "    datasetID='country',\n",
-    "    ncol=4,\n",
-    "    xmax=cafs.allele_freq.max(),\n",
-    "    alleles=hifreq)"
+    "HLAfreq.plotAF(\n",
+    "    international[international.allele.isin(hifreq)],\n",
+    "    cafs[cafs.allele.isin(hifreq)],\n",
+    "    datasetID='country')"
    ]
   },
   {
@@ -245,7 +283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -420,7 +458,7 @@
        "99                  Guinea  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -447,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -477,14 +515,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 24 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -505,13 +543,109 @@
     "# Must be a list\n",
     "hifreq = hifreq.tolist()\n",
     "# Plot only selected alleles\n",
-    "HLAfreq.plotAFprob(\n",
-    "    winternational,\n",
-    "    cafs,\n",
+    "HLAfreq.plotAF(\n",
+    "    international[international.allele.isin(hifreq)],\n",
+    "    cafs[cafs.allele.isin(hifreq)],\n",
+    "    datasetID='country')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fitting model with PyMc, make take a few seconds\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:07&lt;00:00 Sampling 4 chains, 0 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 8 seconds.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "HLAfreq.plotAF(\n",
+    "    international[international.allele.isin(hifreq)],\n",
+    "    cafs[cafs.allele.isin(hifreq)],\n",
     "    datasetID='country',\n",
-    "    ncol=4,\n",
-    "    xmax=cafs.allele_freq.max(),\n",
-    "    alleles=hifreq)\n"
+    "    credible_interval=0.95)"
    ]
   },
   {
diff --git a/examples/single_country.ipynb b/examples/single_country.ipynb
index fc0cc12..c77a055 100644
--- a/examples/single_country.ipynb
+++ b/examples/single_country.ipynb
@@ -11,9 +11,18 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+     ]
+    }
+   ],
    "source": [
     "import HLAfreq\n",
+    "from HLAfreq import HLAfreq_pymc as HLAhdi\n",
     "import pandas as pd\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
@@ -146,20 +155,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:14&lt;00:00 Sampling 4 chains, 0 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 15 seconds.\n"
+     ]
+    }
+   ],
    "source": [
     "afloc = aftab[aftab.loci==\"DRB1\"]\n",
     "caf = HLAfreq.combineAF(afloc)\n",
     "\n",
-    "# Calculate credible interval\n",
-    "caf[['cl','cu']] = HLAfreq.AFci(caf)"
+    "# Calculate High Density interval\n",
+    "# This takes a few seconds and can be skipped if not needed\n",
+    "hdi = HLAhdi.AFhdi(afloc, credible_interval=0.95)\n",
+    "hdi = pd.DataFrame(hdi, columns=['cl', 'cu', 'allele'])\n",
+    "\n",
+    "# Add low and high credible interval\n",
+    "caf = pd.merge(caf, hdi, how=\"left\", on=\"allele\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -180,24 +256,95 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "You can view the probability density function of the allele frequency estimates with `plotAFprob()`. By passing the uncombined allele frequency data we can see the individual study estimates.\n",
+    "You can view the combined allele frequency estimates with `plotAF()`. By passing the uncombined allele frequency data we can see the individual study estimates.\n",
     "\n",
-    "The dashed line is the Dirichlet mean, and the dotted lines are the Dirichlet credible intervals. Note that these confidence intervals ignore study level variance so can be very tight with large sample sizes."
+    "The black open points are the Dirichlet mean, the coloured points are individual study estimates, coloured by population, and the black horizontal lines are the credible intervals on the combined estimate.\n",
+    "\n",
+    "Estimating the confidence intervals can take a few seconds. If `credible_interval` is not set it is not estimated or plotted."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fitting model with PyMc, make take a few seconds\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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",
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
       "text/plain": [
-       "<Figure size 640x480 with 4 Axes>"
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:13&lt;00:00 Sampling 4 chains, 0 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 14 seconds.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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02aq5Kjo79cE2bWxsStXOuHHjKG5RkbGBf//3zZa/StV2ab2w9QXuae+RmpGKRq0xPi4y/GoWudQJ8qlVLnWCfGoVdVaj7NTqnptakjp16lCrVq1S7WNqtuqDKjo7tSbl2sUmxGKhsCBwdyAqharA8zWp1uKIOmseudQqlzpBPrXKuc5qk51a3XNTS/Lzzz+XWVslqejs1Afz3hISEkza32Aw0K5dO5o3b86P33/PvfdnoAsPx8wzZ7C78swZfjh/nn3Dh2OdkIBZLU88Pv0ExSMs8RGSGMJH/36ERqXBxiz/GUMDBqKyo3iy3pM82TR/FJvI8KtZ5FInyKdWudQJ8qlV1FmNslOre25qeTA1W/VBFZ2d+mC7pck8nTdvHi+99BIz585lUr8ALNb+Rsq9aNZFR7Pq7Fn+r3kL3NPSwdwClxHPY+fq+kh9bWPfhq5xXdkXug+VWoW9uT0KhYKM7Axi0mLwsPagf93+Rb5Ocs7wq4nkUifIp1a51AnyqVXOdZZ33WUyiMvNTZ00aVKhz+fNTf3rr+LviaoKuallJTdbNe/yI6Zkq1YnL774IklJSUydOpXvvvsOT2dnomNj0RkMvOzjw6TaXqhsbXF47jls+/R55OMpFArGtRyHudKcw+GHuZtyFxSgUqio61CXcf7j8LYtu/XoBEEQBKGqKvUgrqblpkLOvWtRUVHG45w/fx5bW1vq1KmDk5MTAC+//DJeXl4sXLjQ2HbumnOpqanExMQQHByMubm58WxjSdmqNcX48eMZOXIk69ev5/bt2zjb2fFk3Xq4m5ujsrfHqn27Mk1tsDKzYkLrCQxtMJTzMefRGXR42nji7+qPWinWrxYEQRDkodT/x6tpuakAq1atyjeRIHdixZo1a4xxXaGhoQXqa926tfHfp06dYu3atfj4+BiXMykpW7UmcXBwYOzYsRV6TC8bL7xsvCr0mIIgCIJQVZRqEFcTc1MB5s6dm2/gWJjCLtWa0q/islUrS9bt2yQH7kF7/DhekZHEXLiAfd++7Lp7l5UrV/Lvv/+iVqsJCAhg4sSJmNU1I+huEDcSbmCmMqNjrY70qtNLXLYUBEEQhEpU6sQGEb2V3/79+2nTpg0WFhbUr1+/2EHuJ598gkKhKDKiqyKknThBxIwPSPrzT7LjYlFmZqA9eIjxI0bwzDPPoNfrmT9/PlOnTuXixYt07daVNxa+wZHwI6TqUolNj+X3a78z+/BsgqODK60OQRAEQZC7Ug/iQERv5bp16xYDBw6kZ8+eBAcHM3HiRF5//XV2795dYNsTJ07wzTff0LJlS5PbL2v6xERiVq5En5SEmY8Pajc39La27JMM/HTzJvNbtmTnZ4uZPHkyH3zwAd/u/hafvj6c+fIM9qn2uFi64G7ljo+tD/EZ8XwZ/CWpWamVVo8gCIIgyNlD3QUuordyrFq1Cj8/P5YsWQJAkyZNOHToEEuXLqVfv37G7VJTUxk5ciTfffcdH330kcntl7XUw4fJjonFzMsLhUJhvBz844ULtHZzY7C7B/d27MC9eTMAdl3fRcPnGxJxKILzf53nsdH/JWm4KF0Ijw9nX8g+etXpVeKxra2ty6coQRAEQZCpMpvKJ8foraNHj9LngWUz+vXrV+By6fjx4xk4cCB9+vQxaRBXXrFb6TdvIhn0SEoFkmRAMuQM4o7en7nbMvBvCPwb5hVMizj751nO/nm2wOM7KXhmtTBZWVkP3e+yIOJfaha51AnyqVUudYJ8ahV1VqPYLZBf9FZRsVrJycmkp6djaWnJunXrOH36NCdOnDD5OOUVu+UYEoJdqhZddPRDt/Gw8s5Irkxyjn+pieRSJ8inVrnUCfKpVc51VpvYLRDRWw+6e/cu77zzDoGBgWg0mpJ3uK+8YrfSHByIuX4dtYMDCnNzJINETGwMT9Wtx+noe/zVvgMOAwfi9NqrAHx7/lt2nNvBgXcO8Ngrj9H8yf+WRsk0ZBKfEc/kNpNp49amxGNX9uVUEf9Ss8ilTpBPrXKpE+RTq6izGsVugfyit4qK1bKzs8PS0pJTp04RHR1Nmzb/DXL0ej0HDhxg5cqVZGZmolIVDGkvr9gt244dSanfgMyrV1F7eqIwy3n7x7RswdC/bjL/Zgjf9u5lfC8ec3iMRV8swszGjKYDm2JhndOnTH0m8dp4mnk2o2v9rpgpq8+HU87xLzWRXOoE+dQqlzpBPrXKuc5qEbsF8oze6tSpU4HLhHljtXr37s358+fzPf/KK6/QuHFjpk2bVugArjwpLSxwmzKF6M8+I/PGDaTsbMzStDS2tmFply68e/w4fo8/Tu/evUlPTycoKAhbB1v6fNiHaCka7v9BoVKoaOLUhEltJ1WrAZwgCIIg1CQPNYgT0Vs50Vvjxo1j5cqVTJ06lVdffZWgoCA2bNjA9u3bgZzZuQ+mM1hbW+Ps7FxpqQ3mtb3wXPQpaf/+S2pwMFGXr+DdpzfjundnaEYG3333HcePH8fCwoJly5bx8ssvk2WWxeHww4SmhGKuNKeFawvaubfDXFX0JBVBEARBEMrXQw3iRPRWDj8/P7Zv386kSZNYvnw5tWvX5vvvv8+3vEhVpLSwwKZrVyw6duT4jh3YPfEEajMzvKDI5IrB9QdXaB8FQRAEQSheqQdxInqrYN/OnDljcl8q8nJvWbl06RKrVq3izJkzWFhYMHDgQEaPHl2mk0aqBF063DoIoUdz/u1cD+r3ASe/kvcVBEEQhAomYrfuGzt2LPXq1cPS0hJXV1cGDx7MlStXin0tLl68yLBhw4y1Llu2rMA2CxcupH379tja2uLm5saQIUOMl3Org+XLl9O8eXPWr1+Pr68vVlZWTJs2jcaNG5dq8FrlJUfA5jfh75lweSvcDILjq+DP1+H8H5XdO0EQBEEoQMRu3de2bVvWrFnD5cuX2b17N5IkERAQgF6vL3KftLQ06tatyyeffGK8t+5B//zzD+PHj+fYsWMEBgai0+kICAhAq9UW2W5VERgYyMSJE5k8eTJ3797ll19+YcuWLdy+fRtvb28GDhxYLeookUEPez6EqHNg55lzBs7RD5zqgUEHR1bAnaOV3UtBEARByEfEbt2XN+HB19eXjz76CH9/f27fvk29evUK3ad9+/a0b98egOnTpxe6Td7Lx5BzOdrNzY1Tp06VakHj8pKRkYFWqy10GvSiRYto06YNc+fOzZcWYW9vz48//kjLli358ccfS7xUXZzKXj8OgLCTEHUebD1BnWdpF4UCbGtBXAhc3Ag+nSqvj4IgCILwABG7VQitVsuaNWvw8/PD29vb+Livry+jR48u8d654iQlJQEYZ7wWprxitx6k0+mMkzyKY2trW+RzEyZMYMKECQ/dh4qK4youFkUZfgalPhNJrYE8twQYWdhB+Bn0aclgZlneXX0kIuam5pFLrXKpE+RTq6hTxG6ZpKxit7766iumTp2KVqulUaNGBAYG5ht01qtXDxcXF5Pbe5DBYGDixIl06dKl2CVGyit2qyqq6DiuwmJR/GLO45eqRasrPI7MLDsVBRJHdu1ErzI9eaMyyTnmpqaSS61yqRPkU6uc6xSxWyYoq9itkSNH0rdvXyIjI1m8eDHDhw/n8OHDxsisvPfpPYzx48dz4cIFDh06VOx25RW79SCdTse6devo1atXoZdT+/bti52dHX/++WeB52JiYmjevDmzZs16pDNxFXU5tbhYFMVNK1SBJ7C2sc9/OTVXYjpSrdb0GzQ05xJrFSZibmoeudQqlzpBPrWKOkXslknHLavYLXt7e+zt7WnQoAEdO3bE0dGRTZs2lUmE14QJE9i2bRsHDhwwnnksSnnFbhVGo9Hg4OBQaLuTJk1i5MiR/PHHH/nOoGZkZDBlyhTMzMx44403jO9ddVDoa1ivG5yuhyL2Ojj6gjJPkkZ6Qs73zYeiKuZWgKpGzjE3NZVcapVLnSCfWuVcp4jdKqWyWodNkiQkScp3b9rDtvPWW2+xadMm9u/fn2+QW9WNGDGCQ4cOMWbMGH744QcGDhxIUlIS//vf/4iPj+fPP//E2dm5srv56NQW0GsW/P0BJNwGtTko1ZCVlvNcy+egQUBl91IQBEEQ8hGxWx4e3Lx5k/Xr1xMQEICrqythYWF88sknWFpa8sQTTxjb6d27N0OHDjVePszKyuLSpUvGf4eHhxMcHIyNjY3xsvH48eNZu3Ytf/31F7a2tkRFRQE5Z/0sLav2TfIKhYIvv/ySfv368eWXX7J8+XIsLCx46qmneOedd2jSpElld7HsuDeFIV/DtV1wc3/OAM61ETQaAHU6VfnLqIIgCIL8iNituXPRaDQcPHiQZcuWkZCQgLu7O926dePIkSO4ubkZ9wsJCSE2Ntb4fUREBK1btzZ+v3jxYhYvXkz37t2NZwS//vproOAixHnjvKoyhULB4MGDGTxYBrFbth7QdnTOlyAIgiBUcSJ2C/D09DRpluSDNfn6+pbYr0fpd1V39+5dfv31VyIjI/Hw8ODFF1+kTp06JGQk8G/UvyRnJWNnbkd7j/Y4aYpeUqXKkKScNeHC/oXsTHDwBp/Hwax6zEgVBEEQ5EUWsVuSJDF79mxq1aqFpaUlffr04fr164Xun5mZSatWrYqM53rQl19+ia+vLxqNhscee4x///230O0kSWLAgAEl9r86kCSJ999/H19fXz7++GP27dvHwoUL8fPzY+iYoby15y2+PPMlv176lS/PfMk7Qe+w6fqmqj2gzUzNSW348zU4+Dkc+wp2zYD1L8Ldwt9TQRAEQahMsojdWrRoEStWrGDVqlUcP34ca2tr+vXrR0ZGRoG2pk6diqenp0mvw/r165k8eTJz5szh9OnT+Pv7069fP6KjC643tmzZsnzLr1Rnn376KZ988gnz5s0jIiKC8+fPExkZycvvvszm7zcTvC4YL1svvG29qW1bmyx9Fr9c+oXdd3ZXdtcLJ0nwzyK4sg3UGnCqm/Nl5wWJoRA4G2KqT96tIAiCIA8PNYjLjd3KjdyaMWMGf/31Fzt37sx3qTU3dqtu3bpMmzYNJyenQhfDc3Nzw8PDAz8/P95++238/PzyDcoGDBjARx99xNChQwvtT926dXn//feZM2eOMXZr3759uLi4IEkSy5YtY+bMmQwePJiWLVvy888/ExERUeCM2M6dO/n7779ZvHixSa/D559/zpgxY3jllVdo2rQpq1atwsrKitWrV+fbLjg4mCVLlhR4vKrRarUlfsXExLBo0SLGjRvHxIkTUSqVaLVadAYdZl3NqPtEXa5vvk5mYia6dB36DD0OCgf0mXr+PP8n8cnxJh2npK8yFXMFbu0HaxewdPhvEoPaPGfJEW0MXCi4Vp4gCIIgVKYaH7t18+ZNoqKi6NOnj3F7e3t7HnvsMY4ePWqc5HDv3j3GjBnD5s2bi0xFUCgUxgkJWVlZnDp1ivfff9/4vFKppE+fPhw9+l9YelpaGi+88AJffvmlMUe2JBUZu5X3vzY2Nibvu2rVKlatWlXk82ueXVPo49/zfaGPl1Zp47qKi0VR3DqMMlMLVm6Fx26Z28LNf9B3egdUVXutOBFzU/PIpVa51AnyqVXUKWK3TFJc7Fbukh7u7u759nF3dzc+J0kSo0ePZty4cbRr167ISRmNGjXC3t4egNjYWPR6faHtXrlyxfj9pEmT6Ny5c6lmd1Z07FZ1jER52LiuwmqtG30GX60WbXZMofuYZWtRkMzRHVvJVlXtZWFyVcf39GHIpU6QT61yqRPkU6uc6xSxWyYoLnbLFF988QUpKSn5zqoVJu/gzBRbtmwhKCiIM2fOlGq/iozdyhsVkpCQUOI+Fy5coGvXrvz6668MHDjQ+HhkaiQzj84k+nQ0hz45xJClQ3Cp+1/ObKoulSxDFvM6zcPLxuuR+17auK5iY7euSKj2H8fa3ilnkd8HJd0FRz8CBg0FxUPdgVBhRMxNzSOXWuVSJ8inVlGniN0y6bjFxW6p1Tkl3rt3j1q1ahmfv3fvHq1atQJy0iaOHj1aIOqqXbt2jBw5kp9++qlA+y4uLqhUKu7du5fv8Xv37hkvmwYFBRESElIglmrYsGF07dq1yHSJiozdytuuKfFZjz/+OB07duTTTz9l0KBBxjOTDg4ONHduzrL1y3Bt5IpXi/8GanqDnhR9Cp28OtGsdrMy739pFPoaNugJp75HkRoF9t75F/bVpYGkh2aDUZoXkqtaRck55qamkkutcqkT5FOrnOss77rL7LRCbuzWsGHDCn0+b+xWScoydsvPzw8PD498s12Tk5M5fvw4nTp1AmDFihWcPXuW4OBggoODjZfq1q9fz4IFCwo9jrm5OW3bts3XrsFgYO/evcZ2p0+fzrlz54zt5i5ZsnTpUtasKfyeserg22+/5e7du7Rq1YrPP/+cwMBAli5dyo+v/UhGdAaN/q8RsemxpGalEpsey93Uu9SxrcPLzYpO86hUGnt4fBKYWUJ8CKTFQUYSJIVBShT4dYOmMljsWBAEQahWanzslkKhYOLEiXz00Uc0aNAAPz8/Zs2ahaenJ0OGDAEo0EbuDf716tXLF1bfuHFjFi5caJwlO3nyZEaNGkW7du3o0KEDy5YtQ6vVGtMhcmO9HlSnTp1qlaH6oBYtWnDs2DE+/PBDpk+fjk6nQ61WM2zYMMZPGc918+scDD9IRnYGlmpL+vr0ZWDdgXhYmzaxo1LU7w2WjnD+dwg7kbPYr31taDwImg/LGeAJgiAIQhUii9itqVOnotVq+b//+z8SExN5/PHH2bVrFxpN6Vbiv3r1KklJScbvn3vuOWJiYpg9ezZRUVG0atWKXbt2FZjsUBM1atSItWvX8s033xAXF4ezszO2trYAdKUrLzR5Aa1Oi7WZNRp1NUk88GqT85WRBHodaBxAVaZ3HAiCIAhCmZFF7JZCoWDevHnMmzfPpO2LitMq7LEJEyYwYcIEk/tSpVMLHoKtra1x8JaXRq2pPoO3B2nsy6ddSYLoSznrzlnYgkdLUBV9v0SGTs/FiCQydQY87DX4uVhX2wWjJUniVtItotOjsVRb0sSpCeYlLNeSnJxMYGAgWq2Wpk2b0rZt22pbv1D9SAYDmdevo4+PR2lji6ZJYxRq8UedULXIInZr48aNBAQE4OzsXGyc1tGjR+nVqxfW1tbY2dnRrVu3Eu/N279/P23atMHCwoL69esXGOAuXLiQ9u3bY2tri5ubG0OGDOHqVbH6v+xEBMOmsbBpHOyYAn+9BRtehmt/F9hUkiT+Cg7n/34+yfsbzzPrrwu8ve4MH2y+wO3YMl7ouALcTLzJ3KNzmX5wOh8f+5i5R+Yycd9E/r79d6F/1BgMBmbPno2XlxfPPPMMo0aNon379rRr167UM70F4WGknz9PxNSpREyfTtT8j4ic+QHhEyeRevhwZXdNEPKRReyWVqvl8ccf59NPPy2ypqNHj9K/f38CAgL4999/OXHiBBMmTCj28vCtW7cYOHAgPXv2JDg4mIkTJ/L666+ze/d/8VL//PMP48eP59ixYwQGBqLT6QgICCj71AGh6oq6ALveh/DTYGGXkwJh7QLxN2HfR3A1/2diw8m7fLU/hJiUTNxtNdRxssLSTMXRkDjmbLlIROLDTfqpDHeT7/Lx8Y85de8UVmoratvWxsXShShtFN+c+4btt7YX2GfSpEksWLCACRMmcPv2bdLT09mxYweSJNGzZ89SL/UjCKWRfuEi9z5eSPrFS6hs7TCrXRuVgyOZt24Rs3QZqQcPVXYXBcHooc4N58ZuAcborY4dO9K7d29+/PFH44K+ubFbkLPw76JFiwgMDGTAgAH52nNzczMub/H222+zYsUKTp8+Te/evYGc2K0H98mrbt26TJo0iY4dOxpjtxwdHQkICADgpZdeAoq+xAs5/+N4++23mT59uvGx3Hv1irJq1Sr8/PxYsmQJAE2aNOHQoUMsXbqUfv36AfkvH0PO5Wg3NzdOnTpVqgWNheol3yD98HcQHwmOdUFSQKYBMAPL2jlr0B38Btw7gJmG2NRM1h66jjJbj6udBvSZ6PVgqQBPawW3ouJYf+Q6/9e9XqHH1el0ZGRkoNVqq8SU/vXn1xMWF4a3rTdKvRK9Xo8SJa4qV6LTo1l3bh3tHNtha55zSf7mzZt88cUXfPzxx7z11lsA6PV6unXrxvbt2+ncuTNz5szhm2++qVJ1loXSrn0olD1JkkhYvw59YgLmdXyMl+8VlpaY1a6NLiyMhLVrsX6sA4pi0ocEoaLU+NgtU0RHR3P8+HFGjhxJ586dCQkJoXHjxixYsIDHH3/cuF2PHj3w9fU1XjI9evRovjgvgH79+jFx4sQij5U7McLJyanIbSordqsmq+haC48wO1v0DmP+Mrntg8DkEreqPv7H/wo89v777xe5HNHt27fZsGFDeXerwhUVJSeXz2lVqFN3N4yMi5dQOjohIRW43K90dSEr7C4pZ89h2cr/4Y9TBWqtCKJOEbtlkuJitxwdHUvc/+bNmwDMnTuXxYsX06pVK37++Wd69+7NhQsXaNCgAZCzNEjeBYOjoqIKjd1KTk4mPT0dS8v8y1IYDAYmTpxIly5daN68eZH9EbFb5UdOtQrVS0lRcnL52a3MOi3CwvCIi0NnZwvphcQlSRLmCYncCtqLNiL8kY8n3tOaRcRulUPslimDuNwJGWPHjjWu8da6dWv27t3L6tWrWbhwIQA///yzSf0pyvjx47lw4QKHDhV/T0VlxW7VZBVdqzHCLDkK1eYxoDQrfNarPhNFajT6fh8j1e7A35fu8eX+EDwdLFEpC87EjE3JxMpczdcvtMLCTFXgeZ1OR1BQEL169ar09zQlK4UpB6eQbcjG0aLg5zBbyuZe2j3G+4+ni2cXABYvXsyKFSu4dOlSoWczly1bxieffMLVq1c5duxYlaizrBR1OVUun9OqUKcuLIyooCCwsEBVyKx7Q0YGBr2Bun36oGnZ8uGPUwVqrQiiThG7ZdJxi4vdMkXu2bUH+9WkSRNCQ0OL3M/Dw6PQ2C07O7sCZ+EmTJjAtm3bOHDgQL4FhAtTWbFbclBRtRojzBwcoEFnuB4Ils75s1clCRIjwaMuNO4BanP6+Fux4VwcyVl6POzyL9GiN0hkKuDp1t64uzoXelydTodGo8HBwaHS31MHHOhWrxs7bu7AzMoM5QO5swnaBDycPOhevzs25jkDtjFjxrBw4UJ+/vlnZsyYkW/7+Ph4Vq9ezXPPPYenp2eVqbOiyOVzWpl1qn19sWzRgrRjx1HY2KLIM7FNkiQMsXGY+/pi4+9fJsuNiPe0ZhGxW/eVZeyWKXx9ffH09Cyw9Me1a9fw8fEpcr9OnTrlm0ULOadTc2O3IOeDP2HCBDZt2kRQUFC1TmoQHlK7V8GuVs5s1IwkMGRDlhYSboOZBh4bC+qce0WdrM15oUMd9AaJsIQ00nV6svUGEtOyuBOvpZ6rNYNbeRV/vCpkcP3B1LatTWhyKMmZyWQbsknPTicsJQwFCp5r9JxxAAfg4+PDlClT+OCDD3jrrbe4ePEicXFxbNiwga5du5KWlsbs2bMrsSKhJlMoFDiOGIHa1RVdaCj6lBSk7GwMWi260FCU1lY4vfSSWC9OqDJqfOwW5PwFHxoaSkREBIBxsJYbi6VQKJgyZQpz5szB39+fVq1a8dNPP3HlyhX++OMPYzsvv/wyXl5exsur48aNY+XKlUydOpVXX32VoKAgNmzYwPbt/y2bMH78eNauXctff/2Fra0tUVFRANjb2xc4WyfUUK6NYMBncPwbiAyG9IScy6vuTXMGeH757/8c2toLK3M1f5y6S1hCOnqDhJW5it6N3XnlcT/c7arPIspeNl580PEDfr30K2djzpKsTUalVOFr78vTDZ6mq1fXAvssXLgQJycnFi1axMqVK42Pd+vWjT/++IN69erV+BulhcqjadQI9w9mEP/Lr2RevowuKRGFmRmapk1wfP55rNq3r+wuCsJ/pFIaNWqUBEiApFarJVdXV6lPnz7S6tWrJb1eb9zOx8dHWrp0aYH9+/XrJw0YMECSJEnat2+fsa3c9vz8/KT33ntPSk1NNe7z4Ha5X6NGjTKpz2vWrCl0/zlz5uTbbuHChVLt2rUlKysrqVOnTtLBgwfzPd+9e/cCx9y3b5/UqlUrydzcXKpbt660Zs2afM8XdlygwHbFSUpKkgApKSnJ5H1MkZWVJW3evFnKysoq03aroipRq8EgSbE3JOnOMUmKuihJeT4vhcnU6aXzYYnSydtxUnhCmkmHqBJ1FiEsJUw6c++MdDnusqTT60rcPj09Xdq9e7f0559/SpcuXcr3XFWus6zJpdaqVqfBYJAybt6UtKdOS+lXr0qGEj6vpVHVai0vos7y+/93LlnEbo0ePZrRo0eXuN306dPzrRP3oMIu1fbo0aPYVeQfpd+VJTIykri4OLy8vFBZ2pCcrsPe0gxbTc2/p6FcKRTgXC/nywTmaiXNvcopAqwSeNl44WVj+qVgjUZjXOtRECqaQqHAws8PxB0wQhUmLuwLRgcOHGDOnDnGwapKbUYt/+40eOJ1HGt583h9F55pWxtvp7Jf5kQQBEEQhNIR2al59svbF4VCwbhx40p8PX7//XcaN26MRqOhRYsWxa71NG7cOBQKBcuWLSux3Yq2fft2evfuTVpaGku++p6Aad/iO2AMcTfPc2TZGyRH3WXL2Qg+2HSeW9Uwv1MQBEEQahqRnZrHmDFjiIyMNH4tWrSo2O2PHDnCiBEjeO211zhz5gxDhgxhyJAhXLhwocC2mzZt4tixY3h6ehbbZmXQ6XSMGTOGfv36cejQIWLc25Pl0oCuQ0YxZO7PmGusuLblK3ycrLibkMaaw7cqu8uCIAiCIHsiOzUPKysrY39NsXz5cvr378+UKVMAmD9/PoGBgaxcuZJVq1YZtwsPD+ett95i9+7dDBw40OT2K8rGjRuJjIxk1qxZXAmP50xIFI7mKvS6DNQWGpr2fZ5/f1tKakwY9hb2nLgeyZVQd7ydTb+sKnIhBUEQBKFsiezUPP73v//x66+/4uHhwZNPPsmsWbPyxVz5+voyevRo5s6dC+Rkp+ZNVoCc7NS8l3sNBgMvvfQSU6ZMoVmzZib1o6KzU3MHuR07dix2+z+n/7cG4K4ppTtWUbmQFUVk+NUscqkT5FOrXOoE+dQq6hTZqSZ51OxUgBdeeAEfHx88PT05d+4c06ZN4+rVq2zcuNG4Tb169XBxcTF+X1R2au5acACffvoparWat99+2+R6Kjo7tSKUlAtZUeSc4VcTyaVOkE+tcqkT5FOrnOsU2akmeNTsVCDfmbsWLVpQq1YtevfuTUhICPXq5SwJ8WA6Q0lOnTrF8uXLOX36dL7XpSQVnZ164cIFWrduzfTp0xn/9kQm/36OqKR0ajlYIkkS/3z9ASkxEQyavYbIxAy8naxY/EwLzFSm31JZ2ZdTRYZfzSKXOkE+tcqlTpBPraJOkZ1q0nEfNTu1MLmXc2/cuGEcxD2oqOzU3PvqDh48SHR0dL5UCb1ez7vvvsuyZcuKvEevorNTGzZsyPjx4/n444+xt7fnma6D+fZIBBHRcYTt/Ynw80fpNvYjErJUaKxseLFrQ1ydncq8HxVBzhl+NZFc6gT51CqXOkE+tcq5zvKuu8wGcbnZqZMmTSr0+bzZqX/99VexbVV0dmphcpchqVWrVpHb5GanTpw40fhY3uzUl156iT59+uTbp1+/frz00ku88sorZdLPsvLZZ5+RnZ3N1KlT0WhmY+PgTExUBEq1GY2fmYxZgy7YWZrxYkcf+jRxq+zuCoIgCILsiexUDw9CQkJYu3YtTzzxBM7Ozpw7d45JkybRrVs3WrZsaWynd+/eDB06lAkTJhjr6d69O0uWLGHgwIGsW7eOkydPGte5c3Z2xtnZOV9fzMzM8PDwoFGjRiX2uyKp1Wq++OILpk6dyvr164mLi6OWtw8+7fqgU2lwsDTjsbpOIrVBEARBEKqIhxrE7dq1i1q1aqFWq3F0dMTf358VK1YwatQolMqi75Nq2rQpAQEBzJ49O9+N7rkDGrVajbe3N2PHjjXOAAU4efIkPXv2NH6fe7/YqFGjTIoA27JlS74zX88//zwAc+bMYe7cuZibm7Nnzx6WLVuGVqvF29ubYcOGMXPmzHzthISEEBsba/y+c+fOrF27lpkzZzJjxgwaNGjA5s2bad68eYl9qqq8vb157733KrsbgiAIgiCUQGSnkjNw+eeff0psp7Cann32WZ599lmT+1LSWnWCICt6HdzYC1e3Q/xtsLCB+n2g8UCwNX3NRqHqSM3MZu/le+y5fI/YlCxcbM3p08Sd3k3csbGomkmPBw8eZOnSpezZswe9Xk+nTp146623GDx4cGV3rVxk6bM4GH6Q/aH7idBGYGtuS1evrvSs0xMnTfW83/lhZFy7RkrgHtJPn0aSJCybN8O2Tx8s81yBq+pE7Fae/co6dkun0zFt2jRatGiBtbU1np6evPzyy8bLuoIga9mZsPdD2DMXQo9DViokhsKxr2DLBIi9Xtk9FEopXpvFrM0XWLH3OlejUtBmZnM1KoUVe68za/MF4rWVu15kYVatWkX37t25fv0606dPZ968eaSnpzNkyBCmTZtW2d0rc+nZ6Sw5uYQvTn/BudhzaHVa7qbc5ceLPzL78GzCUsIqu4sVImXfPiJnziJp21b0CQkYkpJICdxD1IcfklTCfftViYjdyqOsY7fS0tI4ffo0s2bN4vTp02zcuJGrV6/y1FNPFduuIMjChT/h2m6wcgYnP7BxA/va4OgH8bdg38dg0Fd2L4VSWH3oFsF3E/C0t8Tb0QpXWwu8Ha3wtLck+G4Cqw9Vrci+K1euMH78eCZMmMDZs2eZMWMG7777LocPH2bp0qUsWrQo39WjmmBryFaORBzB2dIZb1tvXCxdqGVdCy8bL24n32bV2VWPdOWrOtCFhxP37XdIGRmY1/FB7eaG2tUVcx8fQEH8L7+QcflyZXfTJCJ2K4+yjt2yt7cvsPjfypUr6dChA6GhoSZNyhCEGkmvg0t/gco85xJqXkoV2HpCzFUIPwXeHSqkS1qttkKOU1o6nY6MjAy0Wm2VXqYhOjmD/RfvYqMEhT4TXZ7xtwKwUer55+JdhrV0wc1OU2D/yqjziy++wMnJiblz5xZYEeH111/np59+Yvny5XTt2rVMj1tZ72lGdgY7r+5Ena1GrVMXSBNwUDhwMeIiZ8LO0Mjpv8l3lb3OZ1lLPXAAfUICZnXqFFjDVeXiQlboHVKC9qFp0qSSemg6EbuVR3nEbj0oKSkJhUJhHLQWpqJjt2p6JArIp9ZqU2dyBKrkKDC3hTy3YRipNaDPwhB9DcmjdYGny6NOGxubkjcSHtm2dyu7BwU9uIrAg+T2s7GZzfm+f9jYxKr6+yjtylUklQpJAZJU8PePwsKC9MuXTe63iN2qwbFbeWVkZDBt2jRGjBhRbPJCRcduySUSBeRTa1Wv00KXyGPJSegVaWSrClkTUpKwzkrl6rnzhIfZFtlOVa9TEGqCR41NrGqfU5fwMKyTk9FFF34WVJ2YRJaFBWdKWbeI3aphsVt56XQ6hg8fjiRJfP3118VuW9GxWzU9EgXkU2u1qVOSUG49jCLiDDgWsnh0RhJku+E/YBT+zg0KPF0edSYkJJRJO2VNp9MRFBREr169qvR7mpqZzcT150jJ0OFqVzBxJiY5E1uNGcuea1noLNXKqHPZsmV88sknXLhwId8f6JBz9ql169b07duXZcuWlelxK+s91Rv0zD02l1vJt6hlVXAh++SsZPSSno86f4SH9X+3Fj3s5dSq+vsoRakk/suvUDs5oVDn/1mUDAay09JxePJJ2jzxhEntiditGhq7lSt3AHfnzh2CgoJKHIhVdOyWXCJRQD61Vos6/Z+D6Eugjc6Z1KC4P88qSwvpcdCwH0r3JlBM7nBZ1lncLQ6VSafTodFocHBwqNLvqQMwtEM9Vh++RbrBHHtLNQqFAkmSSErPJlsFQzv4UdvdpdD9K6POCRMmsGLFCl555RU2bNhgTOhJTEzkrbfeIjY2lvfee6/MfzYq8z0d2nwoK8+sJFWZipPGyXjiRavTotVr6efTj8Zejcv0mFXt95F99+5ot20jK/QuZp6eKO73TcrOJjsyEjN3d+x79y51nysjduuhZqcWJjd2a9iwYYU+nzd2qyTVLXYrr7yxW/DfAO769evs2bOnxHsvBEE26vWCTm+CUg3xNyE+BOJuQFoc+HaDblOLHcAJVc/w9t485e9JRraeW3Fp3I7TcisujYxsPU/5ezK8vXdldzEfFxcXtm/fzqVLl6hTpw79+vXjqaeewsvLiy1btrBu3bpqvXh7YXp69+S5Rs8BcCflDqHJodxJvkNyVjJdPLvwaotXK7mH5U9lZ4fblCmY+/igi4oi8/Ztsm7fRhcejtrNDbd3J2NWzP/7qxIRu1WOsVs6nY5nnnmG06dPs23bNvR6vfF+OScnp2IneQhCjadQQKsXwKcLhOyFpHAwtwafzuDVDlRVc2FYoWhmKiVv925AQDMPDt+IJUGbhaO1OV3qu9DYw7bATMCqoFOnToSEhPDTTz8RGBiITqdj+vTpvP7668X+EV9dKRQKnmv8HJ08O3Ek4gjRadHYmNvQzr0dzZyboVKqKruLFcKifn28lixGe+wYGZevIBn0aOrXx7pLF1T29pXdPdNJpTRq1CgJkABJrVZLrq6uUp8+faTVq1dLer3euJ2Pj4+0dOnSAvv369dPGjBggCRJkrRv3z5jW7nt+fn5Se+9956Umppq3OfB7XK/Ro0aZVKf16xZU+j+c+bMkSRJkkJDQ6Vu3bpJTk5OkoWFhVS/fn1pypQpUlJSUr52fHx8jPvk2rBhg9SwYUPJ3NxcatasmbR9+3bjc7du3Sr0uIC0b98+k/ouSZKUlJQkAQX686iysrKkzZs3S1lZWWXablUkl1pFnTWPXGqVS52SJJ9aRZ3l9//vXCJ2i/KL3fL19a3xiyYKMpCdBaFH4PYhyEwBhzo50ViujUrel5wJT7eSbnEo/BAxUTepcymO9OAYdp4L4bZWi72nJ8+OGMGIESMeavZ1YloWB67Hcj4sEYDGHnZ0b+SKi03B+0oFQRBqEhG7lWe/so7dMvXYglBlpcXDtkmwcxpc3AQ398PJ1bBpLPz7PZTwR4okSay/up4Zh2ZwdO8v1P98CxsW/sao1es5cOE8HklJaC9dYsyYMbRu3ZrQ0NBSde9iRDJv/3aG5XuuEXQlmn1Xovly/w3eWnuak7fjH6FwQRCEqk/EbuVR1rFbpTm2IFQ5kgT7P4HQo2DjDs71wdEXnOoBypzB3LXdxTbxT9g/bLi6AZuUbIbu1XLoeix/RMYxpqUvSwOa8naXJvzYujWBTz5J1v28SlPPXqfqYPHf1wlLSMfb0QpfZ2t8nK2p42hFTGoWn+2+Snjiw02QEgRBqA5E7FYeZR27VZpjCzVHZcY3lWmcT/RVuHEYzJxAbwb6//5AQ+0IqXfg5G/g9Xihs0gNkoHNlzaTlZ5F00tKlDFa1kbE0MnTmf5+tdAbsrmXnoC9Y0PcomL5ZMQLPL/oU3bs2FHoGfUH6zx7L5PQpHi8Ha0x6DLIu+66hxXcjUtkx+lbvPCYz6O9DpWkpkUdCYJQ9kTsVh4VEbtlChG7VfYqslZ5RfScAn4ucavtef4doc1g2F9H8zxy/yz63j0ADBo0qMx6dwAo/W+CqiE36kgun1O51AnyqVXUKWK3TFJdYrdMJWK3yo+cahWqtwfvr5XLz65c6gT51CrnOkXslgmqQ+xWaYjYrbJXkbVWZnxTWcb5KCKDUe6aBhp7MCvk0l5yODjUQT9kVc6CvQ/2xaBj5uGZRGgj6HMqm8aHwxlx+grtazky1r8ueoOebCmb+nb1sbgXT2j7Djz5yUJ++eWXEs/G6XQ6PvptH6dTrPF2skL5wOVcSZIIjU9nqL8nrz7u+ygvQ6XJvZwql8+pXOoE+dQq6hSxWyYdt6rHbpWWiN0qPxVRa2XGN5VpnI9dN7jsD+GnwNY2/0AtMxnMgXbDwanwGCWAQU0H8f3577npb0+LCwkM9XTl59uRdPFyppmLJS5mdjilZpFia8e8nTuoU6cOzz//PGp18b+adDodrT0sCFM7EJeRjZeDpfEPSEmSiErOxMnBjqc61MPBwfbRXocqQi6fU7nUCfKpVc51ititUqpqsVuCUG0pldBzBrg0hIQ7kBgKKVE5EVnpidDkSWg2tNgm+vv1p3ed3ty1zWJXN2uerutKewcb5hy+zKcHb7AzOIwPL16k555AQu7eZePGjSUO4HI5WsD4HnWxtlBzKy6NyKR0opIyuB2XhplKwbhu9ajvVjMGcIIgCIURsVvlGLtlyrEFoUpz9IXBX8K1XXBjb85iv46+0GgA+HYtMRrLTGnGm63epL1He/Z77OdInauMaetDwOFwtt64y0+RUdg6OvJ/b77JhAkT8PYuXbZm1wYu+LraEnjpHifvJCBJEv7eDgQ09aCRhxjACYJQw5U24kHEbs3J91hxsVumHNsUInbr0cmlVlFnzSOXWuVSpyTJp1ZRp4jdKtV2Rams2C1Tjl0dSJLE0aNH2bJlC+np6fj7+/P888+XOFM2K9vAydvx3IlPQ6VU4F/bgYbuNlUyBFsQBEEQqhsRu/UASZIYMGBAiccBuHjxIsOGDTPWumzZskK3+/LLL/H19UWj0fDYY4/x77//FttuVRIbG0vPnj3p0qULP//8M4GBgbz++uvUrl2b7du3F7nfxYgkxv/vNHO2XOSHgzdZtT+EyRuCmbf1EklpNXvNIEEQBEGoCCJ26wHLli0z+UxRWloadevW5ZNPPiny/rb169czefJk5syZw+nTp/H396dfv35ER0ebdIzKZDAYeOqpp7h06RJbt24lLCyMS5cuERISQteuXXn66ac5efJkgf3uxqexYPtlbsam4m5ngY+zNb7OVlibq9h/LYZFu6+gNzz8mVVBEARBEETsVj7BwcEsWbKEkydPFjsrNVf79u1p3749ANOnTy90m88//5wxY8bwyiuvALBq1Sq2b9/O6tWri9ynohUV0bR3716OHj3K1q1b6dmzp3HGsJubGz/++COPPfYYCxYs4Ndff82335aTtwiLSaCOkxVKfRY6fc7jGgU4mxs4fi2C49cc8fd2FNFCgiAIgvCQROzWfWlpabzwwgt8+eWXRZ5VezB2qyRZWVmcOnUq37IqSqWSPn36cPTo0SL3q+jYrZIWRC5sHb5c169ff6iYqb33x6+50ULlTcS/1CxyqRPkU6tc6gT51CrqFLFbJimL2K1JkybRuXNnBg8eXOQ2D8ZulSQ2Nha9Xl9oNNeVK1eK3K+iY7cq04PRQuVNzvEvNZFc6gT51CqXOkE+tcq5ThG7ZYJHjd3asmULQUFBnDlzptjtamrsVnR0dKGXUz/77DOWL1/OpUuXCj3u22+/bVzkOe/7PnPzRS5GJOPlZFlgH4NBIjwxnVe7+DLY37PCLqeK+JeaRS51gnxqlUudIJ9aRZ0idsuk4z5q7FZQUBAhISEF4pKGDRtG165dHzoFwsXFBZVKVeporoqO3SoqounNN99k0aJFLFmypMCEjxMnTvD7778zc+bMAgPlp9rX49rfV9EpzLGx+O9HTJIkopIzcHF0YECbujjYasq8lpLIOf6lJpJLnSCfWuVSJ8inVjnXKWK3SulhBlzTp0/n3LlzBAcHG78Ali5dypo1ax6qHwDm5ua0bds23xk8g8HA3r17q0U0l5eXF0uXLmXFihX07t2btWvXsmvXLiZOnEiPHj1o1aoVkyZNKrBfj0Zu9GjkRpw2i7CENJIzdCSkZRnXi3v9cT/cKmEAJwiCIAg1iYjdyvP1oDp16uQ7s/hg7FZWVhaXLl0y/js8PJzg4GBsbGyMl40nT57MqFGjaNeuHR06dGDZsmVotVrjbNWqLjcK6ZNPPmHkyJFAzhnGt99+m5kzZxZ6j565Wsl7AY1oWsuOnRciiUrKQKlQ0LmeC0+18qS9r1NFlyEIgiAINc5DDeJ27dpFrVq1UKvVODo64u/vz4oVKxg1ahRKZdEn95o2bUpAQACzZ8/Od0N7o0aNcjqjVuPt7c3YsWPzzQA9efIkPXv2NH6fe7/YqFGjTEqP2LJlS75B0/PPPw/AnDlzTJ5pChASEkJsbKzx+4iICFq3bm38fvHixSxevJju3bsbzwg+99xzxMTEMHv2bKKiomjVqhW7du0qMNmhKhs8eDCDBw82DrZr1apV4ilic7WSIa29GNSyFknpOtQqJfaWNf90uiAIgiBUFBG7VYTCjvdgTb6+vib1a8KECcazd9WJ3iBxOTKZpHQdDskx1MlMwsbcDKWTM5h4nV+tUpKeGMOBAweQJIlOnTpRt27dQrc1SAauJVwjMTMRW3NbGjk2Qq0s09s2S5alhajzkJ0JDt7gVHhfBUEQBKGyiditB5Qmdgvg999/p3Hjxmg0Glq0aFFgyYy8r1fuV//+/Utst7IdvxnHW7+dYf6P/3Bm+lzC3pnEuSkfcPP9mYSNH0/C+vVIedI5CpOUlMSIESPw9fVl5MiRvPjii9SvX5/BgwcTExOTb9vg6GCmHZjGzEMz+fjYx8w+PJupB6ZyIupEeZb5H4MegtfCuhdg60TY8R788SrsmAKJoRXTB0EQBEEoBRG79YDSxG4dOXKEESNG8Nprr3HmzBmGDBnCkCFDuHDhQr7tcl+v3K/ffvvNpPYry/GbcXy88zJhtyMYfnQDrcMvgJkZEZaO3JCsSI1LIP7nX4grZtJHVlYWTzzxBDt37mT58uXEx8eTlJTE999/z/Hjx+nVqxepqalAzgBu8cnFXIm/gp25Hd623jhYOBCSEMLnpz6vmIHciR/g8HJIiwe7WuDoCyoLCAnKGcilRJV/HwRBEAShFETsVh6ljd1avnw5/fv3Z8qUKQDMnz+fwMBAVq5cyapVqwp9vao6vUHi56N3SM3I5snoS3jEh5Nk74pBpYbsbJKzDVwzWNDQ0kDG9u2ounTB3MenQDsbNmzgyJEj7Nmzh44dOxoff+6552jZsiUdO3bkm2++YezYsfwS/AtxSXF423ijyFaQnZ2NGjXuanfCk8P5+czPNHy84SNdWtXpdGRkZBQeMZYUDif+B5IGLF2wVt0/jqUDWNhA3A24uAk6mrbkjSAIgiBUBBG7dd/DxG4dPXo036K8AP369StwGXb//v24ubnh6OhIr169+Oijj3B2di6yLxUdu5W3zUuRyYTEpOBibUa9G6fRqczQq1SAxPC//yjYyF9/FXuMPn36FPnce++9x3vvvWdSX1ey0qTtyoL+l2fyfKcEtRVc2YG+9Wio6Hv0SknE3NQ8cqlVLnWCfGoVdYrYLZNUVuxWVFRUoZFaUVH/XXrr378/Tz/9NH5+foSEhDBjxgwGDBjA0aNHUalUhR6nomO38kaFXE9SkJCoRGWejSolkQwUFZZvWlVER0fn+94sOx1Fipaj2/8iW1UwhaIqknPMTU0ll1rlUifIp1Y51ylit0xQlWO3cpczAWjRogUtW7akXr167N+/33i5+EEVHbuVNyrkSlQKe+PPY6NRkW3niF1SLLr7Z083BAxDb5DINkg0cbfBLDoS+xdewP7poQXaHj58OMnJyflmI+f1wgsvEBMTw3d/fMeHxz/EUm2JtbpgBFe6Pp2UrBQ+6PABDR0bPlKtQUFB9OrVq8DlVMXFP1Ee/QIcfAAl1poHPhYpkWDlRMDAwdXiTJzcY25qGrnUKpc6QT61ijpF7JZJx62s2C0PD49SR2rVrVsXFxcXbty4UeQgrqJjt/K228zLkfrutlyKSOZGg7Z0OL4DlV6PQaVGozYjPUuPq7UZjtmZKBwcqNWnN+YPvG4AY8aMYfjw4Zw5cybfGn+Qc+/h7t27+eqrr/Cv40+zu804G3MWRyvHfH8ESJJEVEoUjT0a0863HUrFwweM6HQ6NBpN4RFjLZ6Ay7+BIQlsHli/T6+D7HRo8iRKi+pxFg7kHXNTU8mlVrnUCfKpVc51ititUqrI2K1OnToVODsXGBhYbKRWWFgYcXFxJk2cqAxKpYLRnf2wtzRjr2sTIly8sUuKwVybTGZGFpaSntr6FKS0NOwGDcK8iMSMoUOH0rNnT5588kkWLVpkTMzIjfBq3bo1L7/8MgqFghFNRuCocSQ0JZRUXSrZhmy0Oi2hKaHYW9gzssnIRxrAlciuFrR6MWdtuKS7oEsHfXbOTNXEO+DaGJoOKb/jC4IgCMJDELFbjxC79c4779C9e3eWLFnCwIEDWbduHSdPnjSuc5eamsqHH37IsGHD8PDwICQkhKlTp1K/fn369etXYr8rS1sfR2YNasrPR+/wh+o5OgXvoUnEFWplJeNgY4GtZy3sBw3CrpAzoLnUajVbt25l4sSJzJ49m2nTphkfHz58OF9++SWWljlntpo5N2Nah2n8dvm3nMV+MxIxU5nR3KU5zzd+Hn9X/wooehRobOHsekgOy1k3ztwaGg3MmZVq41r+fRAEQRCEUhCxW48Qu9W5c2fWrl3LzJkzmTFjBg0aNGDz5s00b94cyDmjeO7cOX766ScSExPx9PQkICCA+fPnF3q5tCppXceRVt4OhMTUIym9I3baZLwyElCYm2PRoD5KE/pvbW3Nd999x8KFCzly5AiSJNGhQ4dCz0I2c27G/C7zuZ18m6TMJOzM7fCz9zN5zb5HplBA82HQ+EmIvgT6LLCvDXaeFXN8QRAEQSglEbtVBFNitwCeffZZnn322ULbsLS0ZPfu3aU6blWiUCio72Z7/zsnwPeh2nFxceGpp54y6Xh+9n4lbkd2FmijcyYZ2LjnDMDKitocPFsBoNVpSUqNwNrMGnW2mtu3b2NtbY2Pj49xcKnTG4hJyUSpAGedFrKyUDk7mzTIFQRBEIRHUbWn2glCXroMuPAHXNoCqfdAoQTXRtDiGajXu8wGc/e099h8YzNHIo6QFJ/Epf9d4s7+O2Sl5yy10qpVK6ZNfx/zBp3ZcT4KzdULtLl6jLqJYThqVDi4O2Pbuzf2gwejsrEpkz4JgiAIwoNEduoDyjo7Na9x48ahUChYtmxZie0KD8jOgr3zcqKxksNz7ldTW0D4aQicC2fLJsosMjWS+cfmszVkKymJKfwz4x/uHLqDz1M+PLH4CVb+vBJ3d3dGPP8c73/0GbbBxxlyeD31I66Smi1xJ10iNiyGhF9/5d6Cj9GnasukX4IgCILwIJGd+oDyyE4F2LRpE8eOHcPTU9xj9VBu7IGQvWDjlnOvmoUtaOzByQ+Uqpzs0zIIql93dR23km/hbevNrU23SItL45kVz9D39b4o6yq563OX6ct+wvvxp7mx5SseO70dc302yY7uYGNHtrklt5VWZDm5kh4cTPLOogf1giAIgvAoRHZqHuWVnRoeHs5bb73F7t27GThwYIntypVWW8xZq+DNkKkHSw1kZOd/Tu0ECbfg/A5o81KhuxebnXpfTFoMR28fxVZhS3ZaNpd3XaZxQGNsXGzIzsjGQeHAlagrJN09iHeP54g8tpW9t67Qv1ErJL0eAAlI1+kJT1fhoVQSvXMnZgEBKNQVc+eCKXUWxdq64GLLgiAIQtUlslPvK6/sVIPBwEsvvcSUKVNo1qyZSX2pzOzUymRj0v1jp4p57o37X2Xn3KZznNt07oFH/8uL/f7uLb6/e6v4RopZa7AqqU7xalXtZ7c8yaVWudQJ8qlV1CmyU01SlbNTP/30U9RqNW+//bbJ9VRmdqogX8Xdz1lVyelnVy61yqVOkE+tcq5TZKeaoKpmp546dYrly5dz+vTpUq13VpnZqZUpISGhyOeUZ35GcfKHnHxThSr/kzotpCdi6LcQyattofsXl52ayyAZ+PDYh1xPvI6XtRd/L/iblHspDFkyBJWZiuj0aOwt7HncbiJLv/uDK+sW8rl/e+rZO5GpyTmLqJdylh1p4GqFVUwUNgF9cRo79uFekIdgSp1FqU6XU6vaz255kkutcqkT5FOrqFNkp5p03KqanXrw4EGio6PzpUro9Xreffddli1bVuQ9epWZnVqZHnz982k3HMIP5Nz7ZusJ5lYgSZCRBNlx0LA7NOmRM8mhEMVmp+bxvP/zLDu1jDhDHG1GtmHLe1sI+iyIJqOboKmlYUjDIdw7fJaQzStwavwYmlbdcbp2ggxlBqkW1kgGCU8LBS5JCZh5euLx7HAsiqurjJlaZ01RVX52K4JcapVLnSCfWuVcZ3nXXWaDuNzs1EmTJhX6fN7s1L/++qvQbXJVRnbqg5d5W7RowdKlSwsdIObKzU6dOHGi8bG82akvvfQSffr0ybdPv379eOmll/IlSAgmsPWA/gth30KIvQKpUTmDOAsbaNgfuk8tcgBXGp08O5Genc7ay2uJrRNLu2ntCF4RzJ037uDq5cq+1H0kJSXRb+BT1Ht2Gjti0knJlmh+5zwO6dFozNU4m1tg4euLyxvjsKhrwuLFgiAIgvAQRHZqOWanOjs74+zsnK9NMzMzPDw8jFFjQim4NIBh3+WsDRcfkpPY4NkanOuV6WF61elFx1odOXnvJAnNE7B4yYKwo2HcunYLKysrhg4dStOmTTEYJM6HJxHSqxFSfAyesbdws1Bi5uWJVatWKIqZxCMIgiAIj0pkp5ZjdqpQDpQq8G6f81WOrMys6FY7z+SahoV0RanA39sBf28HoDbQulz7JAiCIAh5iezUIpRFdmphSlqrrjKFhYWxbNky1q5dS3x8PC61auPTeRCeHQfj4WJPnybu9G7ijo2FSGsTBEEQhMomYrceUJaxWzqdjmnTptGiRQusra3x9PTk5ZdfNl7WrUouXLhAmzZtWLNmDYOffoaOz79DtpMfR9d/ReBnb3DhViQr9l5n1uYLJKZVn/XEBEEQBKGmErFbDyjL2K20tDROnz7NrFmzOH36NBs3buTq1as89dRTJrVfUSRJYsSIEdSqVYurV6/iO+hNFM0H0PeNj3hq9hrS4yKI/PsHatlbEnw3kdWHSljcVhAEQRCEcidit/Io69gte3v7Aov/rVy5kg4dOhAaGmrSpIyKEBgYyIULF9i+fTvJWQoOXgrDVgkKfSZ27t406TOcCzt/pdWQ17FWmrP/4l2ebumKq23BZVBKUp3WIhMEQRCEqkzEbt1XXrFbD0pKSkKhUBS7JlpFx24NGjQIoMRc1/WT/nt+6+RiNixGZUU7ifiXmkUudYJ8apVLnSCfWkWdInbLJFU5diuvjIwMpk2bxogRI4pNXqjo2K2KVNnRTnKOf6mJ5FInyKdWudQJ8qlVznWK2C0TVNXYrbx0Oh3Dhw9HkiS+/vrrYret6NitI0eO0LlzZ77++msGDnmGievPkpqVbbxcenzt54SdPczQj9cTq9Vjb2nG8udaYmVe+h+fyrqcKuJfaha51AnyqVUudYJ8ahV1itgtk45bVWO3cuUO4O7cuUNQUFCJA7GKjt1q164dgwcPZsaMGTRu3JjB7evx09HbpOtVRP67nRuHttHumfFkKizRq3QM7eCHp5tLyQ1XQXKOf6mJ5FInyKdWudQJ8qlVznWK2K1SqkqxW/DfAO769evs27evQIJDVfHjjz8yaNAgevbsSatWrTHYuHH00lnS46Pw7Pgk1u2GkpltYHArL4a3867s7gqCIAiC7InYrXKM3dLpdDzzzDOcPn2abdu2odfrjffLOTk5FTvJo6I5ODjwzz//sGPHDtauXUtcXByNnuhPg66DcajTGCcbC7rUd6aRu63JS7AIgiAIglB+ROxWOcZuhYeHs2XLFgBatWqVr619+/YVujBxZVKpVDz55JPFnn0UBEEQBKFqELFbRSiL2C1fX99H6rdQwXTpcOsghB7N+bdzPajfB5z8Ct08OjmD/VdjuHYvJSdHtbYDXRu6YKep3Hs/7ty5wzvvvMP58+fRaDQ8+eSTjBo1Cnt7+yL30el1nLx3kpP3TqLVafG09uTx2o9T175uBfa8YumTktAePkz6xYugN2DRqBE2XR9H7VI97/cUBEF+ROzWA8oydqu0xxYqUXIEbH4T/p4Jl7fCzSA4vgr+fB3O/1Fg8yM3YnnrtzOs+ieE/Vej2Xv5Hp8HXuWd385w7V5KJRSQY8mSJbzzzjts2rQJX19fLCwsePfdd2nSpAnnz58vdJ+EjATmHZvHpyc+5e/bf3Ms4hgbrm1gxsEZ/H719xr5h0jGlSuEv/suMV+sJHXfflIPHCDu228Jn/wuaSdOVHb3BEEQTCJitx5QlrFbpT22UEkMetjzIUSdAzvPnDNwjn7gVA8MOjiyAu4cNW5+K1bLksBrJKRl4eNshY+zNb7O1tR2sCQ0Po2FOy6TklHxi1tu376d999/n2HDhhESEsIvv/zCtm3buHnzJu7u7gwcOJCMjIx8+0iSxFfBX3Em+gwuGhd87HyobVsbH1sfFChYd3UdB8MPVngt5UmfmEj0Z4vRhUdg5uWFeZ06mNepg1nt2mTHxRG9fDlZYeGV3U1BEIQSiditPMo6dqs0xxbKX0ZGBlqttuCU77sn4E4wWLlBtgry/CGCmSvE34RT68ClJQDbTt0kJiEJHycr9FkZ6PM05W4JtyLjCDwbSr/mhSd/lJdFixbx2GOP8cwzz5CVlWU8g+bk5MTq1atp06YNv/76a77ld24k3ODU3VPYqe1Q6VT5Vhe3w46wtDD+uvQXbRzaVKkJLTqdrtD305R1CFMPHUYXEYFZ7dooVCrj4wqVCjMvL3ShoaQE7cW5mElagiAIVYGI3bqvomK3TFHRsVs1PRIFcmrMndDycIKBFfkeKe781D8fPMKhHlFxaySOGTOGMWPGlKq9Hezgcz5/1G5VCFNi3bTBZ5AASalAkgz5n1QA5uZoT57CrhRrTZYnuXxO5VInyKdWUaeI3TJJdYndMlVFx27JJRJFqPlMiXVzvXkTK60WXXR0oc+rU1PQhYdzppIj4h4kl8+pXOoE+dQq5zpF7JYJqkPsVmlUdOxWTY9EgZxa161bR69evQrUqrh1AFXQh0g27qAqmJRBUiiShz+GJ5aAQsFX+0PYdfEe3k6WBS4x6g0S4YnpvNbFl8H+nuVZUgHdu3enVq1avPLKKwXqjIyMpGXLlixYsCDfWeqLcRf59OSn2JnbYamyLNBmVFoUtW1qM7/zfNTKMv118Uh0Oh1BQUEF6jTlcmpSejqJET+idnFB8cCSSJIkkZ2ejm3vXrR+4oky7/fDkMvnVC51gnxqFXWK2C2TjlvVY7dKq6Jjt+QSiaLRaHBwcChYa4t+cOU3iL0Ojr6g/O8+KdITwNIc2g2H+38QPNW+PkfvppOkk3CztTAO5CRJIiwxHU8XRwa2rYeDTSEDwnI0ceJEXn31VRo3bszTTz9trDM9PZ333nsPKysrxo4dm2+pkU72nWgS3oRLcZewsbTJN1BLzUpFpVExqOkgXJyq1rIbOp2u6PezBPY9e5K6dRv6qHuY3Z/xDjnvnz4mBpWtLfZ9+lS5z4RcPqdyqRPkU6uc6yzvuh9qdmphcmO3hg0bVujzeWO3SlIZsVvnzp0jODjY+AWwdOlS1qxZU+R+ubFbeT0YuyVUA2oL6DULHLwh4TYk3YWUSIgLgSwttHwOGgQYN2/uZc9rj/uhUCi4HZdGVHIGkUnp3IpLw87SjIl9GuJSwQM4yFn+55VXXmH58uX06NGDBQsW8O6771K3bl327dvH77//XmCtOKVCyYTWE/Cx8yE8NZyI1Ahi0mIITQ4lKSuJ3nV608+3X4XXUp7M3N1xHf8mKhsbsu7cQRcVhe7ePbJC76BQqXB+9VU0DRtWdjcFQRBKJGK3yjF2y5RjC1WEe1MY8jVc2wU390NWGrg2gkYDoE4neOCy6ZDWXjRwt+Hvi/e4EJGEWqmkg68jfZt6UMe57O9bNIVCoWDVqlW4ublx4sQJli1bhkaj4emnn+btt982JqM8yNvWm/ld5nMg7ACHww+jzdbibetND+8etHdvjyrvmckawrpzZ8w8PUnZt4+0k6fAYEDTvDm2fXqjKeJ1EgRBqHKkUho1apQEOZO71Gq15OrqKvXp00davXq1pNfrjdv5+PhIS5cuLbB/v379pAEDBkiSJEn79u0ztpXbnp+fn/Tee+9Jqampxn0e3C73a9SoUSb1ec2aNYXuP2fOnCL3AaRNmzble8zHx6fAPhs2bJAaNmwomZubS82aNZO2b9/+yMd+UFJSkgRISUlJJu9jiqysLGnz5s1SVlZWmbZbFcmlVlFnzSOXWuVSpyTJp1ZRZ/n9/zuXiN0qQmHHK23s1sMeu7xJkkTmtetoz57FPjiYNBcX7Nq3R1HM8i959923bx+7du0iKyuL9u3b88wzz+S/h08bB7cPkK1NICRFzUXzlmRbOuNf24GG7jZVar0xQRAEQaiuROzWfWPHjqVevXpYWlri6urK4MGDuXLlSomvR3GxWzqdjmnTptGiRQusra3x9PTk5ZdfNl5arQz6xETufbSAiOnTSVi9GoeDB4n5eCFhkyeTcf9Sb1HCwsJo3749vXv35rfffmPXrl28+OKL+Pj4cODAAZAkCF4L60aQ+fd8ogOXYnnoExruG8vtwG+YvP4M87ZeIimtZq8ZJAiCIAgVQcRu3de2bVvWrFnD5cuX2b17N5IkERAQgF6vL3KfkmK30tLSOH36NLNmzeL06dNs3LiRq1ev8tRTTxXZZnmSsrOJ/vxzUg8fRmllhbqONzoXZ1SuLmSF3OTeJ5+ii4wsdN+srCz69etHdHQ0e/fuJTQ0lCtXrnDlyhWaNm3KwIEDubbjKziykqyMNC5lOHHH4E6cuSfWaj0jDFvpYzjC/msxLNp9Bb2h5uVxCoIgCEJFErFb9+VdO8vX15ePPvoIf39/bt++Tb169Qrdp6TYLXt7+wKL/61cuZIOHToQGhpq0qSMspR+7hzpwWcxc3NDaWWF4f5q9UoLC1Te3iTdvIli2zacX3ihwL4bNmzg0qVLHDlyhJYtWxoXMKxduzbr1q3D378liz5bwvLBrtw12BOfloGVuZKMbIjCHsfsGDoZ/uZfu1YcvxbB8WuO+HubthAzmLb+lyAIgiDIiYjdKoRWq2XNmjX4+fnh7e1tfLwsYreSkpJQKBQF1qTLq7xit1JPnsSQmYnKUoNBMiDdPxsmGSRQKmi5dw/s3QPFvHadO3cu8rkfouCHf26V0It9AOydXrq+mxKnVBwR/1KzyKVOkE+tcqkT5FOrqFPEbpmkLGK3AL766iumTp2KVqulUaNGBAYG5ht0PmrsVkZGBtOmTWPEiBHFJi+UV+yW07nz2BYSNxQTG/PQbVYUU+KUTCHn+JeaSC51gnxqlUudIJ9a5VyniN0ywaPGbuUaOXIkffv2JTIyksWLFzN8+HAOHz6MRqMBHi12S6fTMXz4cCRJ4uuvvy522/KK3UrOzCThxg1j3JBkkIiJjcHVxRWFUsHZvgFoWrTAbdbMAvtOnz6dTZs2cf78+ULPpo4c/jThl//l4PQOXElUkpKhx9L8v1suLQ2pmEk6vnWaQnCqPa+WMpbqUS+niviXmkUudYJ8apVLnSCfWkWdInbLpOM+auxWLnt7e+zt7WnQoAEdO3bE0dGRTZs2FdmWqbFbuQO4O3fuEBQUVOJArLxit+y6dyd54yYMsXGYubtjUObcE6dQKpC0aVhbWOA2cCC2hVzqfeutt/jmm2/45ptvmDVrVr7ngoKC2LX3H756sze2+lh8nbwIiUvHTKVEpVSgkPS4ZadySdOG65IXLo5qBrSpi4Ot5qFreVhyjn+pieRSJ8inVrnUCfKpVc51ititUnqY2K3CSJKUs55annvTHmRK7FbuAO769evs2bMHZ2fnMunfwzBzd8d51MsolAqyQu+gT0pCmZ6BLiICfUICNj26Y9P18UL3bdasGXPnzmX27NkMGjSI33//nR07djBu3DgGDBhA3759eXXWV+BcD2ddOHXMU1Bnp2KZGYurLpxwpQdrpIGolApef9wPt0oYwAmCIAhCTSJitzw8uHnzJuvXrycgIABXV1fCwsL45JNPsLS05IknnjC2U9rYLZ1OxzPPPMPp06fZtm0ber3eeL+ck5NTsZM8yovdgAGoXVxI2r6d9IuXUGRnY16/Hvb9+mPXLwBFMX81zJkzh/r16/PZZ58xfPhwADw9PZk5cyZTp07FzMICnlyO8twGPK79jWVyEtEZVgQqH+egpid+derzVCtP2vs6VVS5giAIglBzlTbioSbGboWHh0sDBgyQ3NzcJDMzM6l27drSCy+8IF25ciVfO6WN3bp161ahxwWkffv2mdR3SSqf2A6DwSClx8RKW3/9VcpMTy/1vpGRkdKdO3cknU5X+EZZaZKUEi3p0lOl2JQMKTGtcmNXRPxLzSKXOiVJPrXKpU5Jkk+tok4Ru1Wq7YpSUvSVp6enSbMfSxu75evr+0j9Lk+G1FSyblzH/N49smNiMM+zlEphwlPDCU8JR61U08ipUYH7/gowswQzS1SSxPXg41y7dg1bW1sCAgJKNUlBm5nNpchkdNkGvJ2s8HaygqQwiL8JSjW4NwONvcntCYIgCEJNIWK37iuP2C1Tj12RpKws4tf+Rtib44me/xFumzYTNWky9z5bTHZsbIHto9OiWXRiEe/tf4+Pjn3EvKPzeDvobX6/+jvZhuxCjvCf48eP06pVKzp16sSoUaN4+umn8fLyYsGCBSUObrP1Bn77N5QxP59kxsbzzPrrAjN+DeLw12+StfZF2P4ubJsEv42A499C9qOtIycIgiAI1Y2I3bqvPGK3TD12RZEkidjvviPh118xaLWoPdzROTmCWkXKnj1ELViAPs906MSMRBYeX8iBsAOolWpq29bG3dqdlKwUfr38Kz9d/KnIY509e5bevXtjaWnJ33//TUZGBiEhIbz66qvMnDmTDz74oNi+rj58i9WHbpGUrqOWvYZGDhJjtd9SJ3ofoYmZZNl4g50XZGnhxHdwcHFOdqsgCIIgyISI3bqvPGK3TD12Rcm8fp3UvUGo7O1R2dvnxG4plajs7VFb25B55SopQUE4DBkCwLYr27gSdQVPa0/UBjX6jJwBraPCkUR9Ijuv7qSzS2fq2BWcXPLBBx9Qu3Zttm7dipWVFdnZ2bi7uzN//nysra355JNPeO211wq9LBsap2XziZtoFAocLcwhO5Nmqf/gkX6DcJUraWkqDPHpeDlYgZkL6BPh3Hbw6QvuTQu0BzmTTDIyMsrstRQEQRCEyiZitwpRnrFbpiiv2K2UI0fQp6WhdnEuGLulVoFaTfKevVgPHIgkSbzU+qUS2/yTP4t93s3NrcjnClv4uSi/mLLRxA4lbqLVak0+ZnUkYm5qHrnUKpc6QT61ijpF7JZJqkvslqnKLXbr5ElstanoYvLHbOXGbqky0pFCbnBm+3b0GAprotqTc/xLTSSXOkE+tcqlTpBPrXKuU8RumaA6xG6VRnnFbiUmJpF0/QZqV1cUCkWB2C1ddjYWfnVpef9M3JgtY4jSRuFu5V6gLQmJsNQwnm/0PEPqDcn3XEJCAg0aNGDhwoWMGTOmwL4JCQk0adKEOXPmFPoebzwTzo9H7lDbyRLl/Z+n12I/w0t3hzi1Oxk6Axq1kuaeua+FhCLhFoY2ozC0fbXQ2nU6HUFBQbKOf6lJ5FInyKdWudQJ8qlV1Clit0w6blWP3SqtcovderwLqVu2ICUlo3J0zBe7hS4bRbYeu759jMcY0HgAqy+sRqlRYqbKf9z4jHgc7Rzp3aA3DnYO+Z5zcHBg8ODBfPvtt4wdO7bAwPOzzz7DYDDw2muvGd/3vPr6m/PXxQS0enCxyXkdrjt0pVHiHTJVBkBFHWcrbK3unyVNiwc7e2jxBBTSHuR8yDQajazjX2oiudQJ8qlVLnWCfGqVc50idquUqlrsVlViXrcutv37YUhNRRcVhZSZCXo9+vgEsiMi0DRvjk3Pnsbte9XpRWOnxoSnhpOQkUC2IZtMfSZR2ijSdGkM8BuAt13h68vNnz+f6OhounXrxsaNG4mLi+PcuXP83//9Hx9//DGzZs0q8n45bycrnm7jRVqWnojEdDJ0ek5ZPMZVVQMcsqLwUKfiZqWE7AxIjoCMJGgyGFwblcvrJgiCIAhVkYjdKsfYLVOOXZEUCgXOr7yC2smZpO3byY6Jxiw5GTyssHtiAE4vv4zKxsa4vb2FPe8/9j7/u/Q/jkYeJUobhVKhxM3KjYF1BzKw7sAij9W0aVMOHDjAG2+8kW9g7+bmxrJly3j77beL7etLHX2xtzRnc3A4UUkZRBuU/GAzlrGaPXQ0nMFMGwkKJdi4Q/Nh4D8C8lzKFwRBEIQar7QRDyJ2a06+x4qL3TLl2KYoj9gOfVqalHz6tLRr+XIpLTKyxO2jtdHSmXtnpAuxF6SM7IxSHev8+fPSn3/+KQUGBkqZmZml2jc9K1s6dzdROnk7XrqXdD8eLCVakkKPS1LYSUnK1JrUjoh/qVnkUqckyadWudQpSfKpVdQpYrdKtV1RKit2y5RjVxalpSWa5s3JCA1F7exc4vauVq64Wrk+1LGaN29O8+bNH2pfjZmKFrUfiNWycc35EqolSa83poOoXVxQqFSV3COhOtNqtdy5cwcrKyt8fHzyTa57KJIE2tic2zWsXcFMUzYdfYBegsikDCzM9bjaWKBU1qwrCXqDnui0aJINyegNesyo+ffEVYYyndggCIJQFMlgIOXvQJJ37UQXFg5ImHl6YTegP7YBAWIwJ5RKQkICs2bN4qeffiI1NRWAli1bMmPGDJ577rmHa/TOUTi3DiLPg6QHS0doMghaPgcWtmXSb53ewF/BEfx0Vcnq0GCUCgV+LtY86e9J7yZujz4IrWR6g549oXvYfXs3YSlhJKUmcfrwaQbUHUDvOr1RKcXnvCyJ7FRy7lt76623aNSoEZaWltSpU4e3336bpKSkEl+P4rJTdTod06ZNo0WLFlhbW+Pp6cnLL79svD9OEORCkiTiVq8mZuVKMm+EoNBoUGgsybx1i5gvvyLu++8f6Wy7IC+JiYl0796d//3vf0yePJlDhw6xefNmvL29ef7551m6dGnpG72yA3a/D3eOgMoMzG0gLQ6OrYLdM3Ii/h5Rtt7Asj3X+frALWIzwdJcicZMyaXIZD77+yq/HrtTrT8HkiSx+sJqvj77NbeSbqFRaTBTmHEr+RZfnf2KNRfXVOv6qiKRnQpEREQQERHB4sWLuXDhAj/++CO7du3itddeK/Z1KCk7NS0tjdOnTzNr1ixOnz7Nxo0buXr1Kk899VSx7QpCTZNx4QLJ23egsrHBvHZtVDY2Of/28kJla0vyzl2kP/DHlSAUZdGiRdy6dYvDhw/z4Ycf0qVLFwYPHszWrVuZPHkyU6ZMITw83PQG0+Lh6ErQZ4GjH1g6gIUN2HnmfIUeg0t/PXK/j92MZ8/lezhameFkATYWamw1ZtRxskKjVrLhZBghMamPfJzKcj72PLtv78bWzBYvGy9szGzQKDR4Wntia2bL7lu7uRB7oeSGBJOJ7FRy7tn688//4qPq1avHggULePHFF8nOzkatLvxlKik71d7evsAKzitXrqRDhw6EhoaaNLNWEGqC1AMHkDIyUBayrIzK3h59YiKp/xzAqnXrMjleTYpXy8391Wq1NXqtLVPrNBgMfPfdd7z00kv4+PgUeK/fffddvvnmG7799lumTp1q2sEv7oK4SHCoA5n6B540A50SzmyEek+C8uFX5tpx5haZaVpcNZakZGWgy0xHqchpz04tERqfxt/Bd6jVxa/INqytrR/6+OXtYNhBsvRZeFgXXHnB3sKexMxEDoYfpIVri0roXc0kslOLkJSUhJ2dXb4BXFlkpyYlJaFQKApd5DZXeWWnPkguuXYgn1qrap2Zd0LBTI2EVPjlFHMzMkPvmNzvkuq0ybNUjlAzff3113z99ddFPj9v3jzmzZtXylaDi3nuX3i1+KzosnAAGF/M81lZWeXeh4cVmhyKWqk23lqV+1mXJAmDwYCZwow7SaZ/zqsLkZ1aRbJTc8XGxjJ//vwCA8FHzU7NyMhg2rRpjBgxotj4rPLKTi2KXHLtQD61VrU6XWNjsUpMRFfE5AWzhETS4+I5bcIs8byqWp2CUN5MWUmhssSlxZGYnYgyNf/Zypj7ed2JhkTi0+OrdA2PQmSnVnJ2KuSc9Ro4cCBNmzY1nnHL9SjZqTqdjuHDhyNJUrF/PUL5ZacW1ic55NqBfGqtqnWmaiyJW74ctYMDigfOxks6HdkZmfg8N5x2ffua1F5JdSYkJJRJv6uC3NzfXr16Van3tKyVps5Ro0Zx+fJlDh48WCCicMeOHYwcOZKdO3fSsWNH0w4edx3VtomgtgCLB5Y0woAi4TaGZs9g6PyW6QUV4q+zEfxw+DaedhoSEuJwcXbJiT0EMnV6YlOymNa/ER3rOhXZRlW+nKq5q2Hl2ZU4WjpipjJDkiRiYmJwdXVFZ9CRlZ7Fs/7P0tO7Z8mNVSMiO7WKZKempKTQv39/bG1t2bRpU4m/SEzNTs0dwN25c4egoKASB2LllZ1aFLnk2oF8aq1qddp3fZy0v/8m4+JFVC4uKO//j8iQloY+JgZN48bYdeuOqpR9LqrO4m5XqG5yc38dHByq1Hta1kpT5+zZs+nSpQujR49m6dKlNG7cGJ1Ox++//84bb7xB37596devn+nLddi3g+b94NIWQJmztIhCCboMSA4HV2947IUis5lN9VQ7Kw7dTuNGdAoqlQYzjSVKhZKUzGxiMzNp19CTXi19MVeXWSJmherq3ZXAu4Fcib+Cq6UrGqUGSZJIy04jLjOOJk5NeNz78Rr7cyyyU++rjOzU5ORkAgICMDc3Z8uWLWg0JS/waEp2au4A7vr16+zZswdnExbWFYSaRmllhdu0qVh1aI9Bq0V3NxTd3bsYUlOxbNsW9/eno7KpumcYhKqlbdu2bNmyhdOnT9OkSRN8fHxwc3Nj5MiR9OjRgz/++KN0660pFNBtSk6En8EA8bdyvlLvgWtDCPgInOs9cr8drc2Z/WRTWta2Jy1bQWh8Bnfi00jP0tOtoRvvD2hSbQdwAFZmVkxtP5W27m1J1aUSlhpGvBSPNltLO/d2TGk/BSuzsr8lSM5EdqqHh3EAl5aWxq+//kpycrLxFKirqyuq+/fxlDY7VafT8cwzz3D69Gm2bduGXq833i/n5ORU7CQPQahpzNzc8PjwQzKvXSPz2jWQJCwaNMCiceNqv8CpUPECAgIIDQ1l06ZNnD9/HktLS4YMGfLQ6TCYWULP96H1ixB2Ime5EXtv8O6Qs25cGfF2smLR08359o+7eDT0w9xMTTNPO+q52tSIz4GblRtzO83lWsI1rsReIfhsMM90fIamrk1rRH1VTmlzumpidmpR7QPSrVu38tVUmuzUW7duFdnuvn37TOq7JJVf9ppccu0kST61ijprHrnUKpc6JUk+tYo6RXZqqbYrSkn5paa2X9rsVF9f32q/OrUkSaQd/5eUvXvJvH4dhbk51p06YtO7N7vOnOGLL77g6NGjqFQq+vTpw6TxY+nqmox0dQfJsZHczbLmH9py3qYzbRp4E9DUA18XcdlMEARBEB6ViN2i/GK3TDl2VSZJEvGr13Bv4cdoDx3CkJpKdkwM8evW886AAQwZMoT09HTmzZvH9OnTuXblMt379ufrBe+RcPscUTGxWCVe46mk/zH83lJ2HL/IlD/OcuJ2fGWXJgiCIAjVnojdovxit0w5dlWmPXyEpC1bUFpaYe7jg9rFBTN3d44oFXxz6RKzO3TgwO7dvPvuu8yYMYNzK15gQldXJvweSmCYOclqR5I1niSZu9PUcJ3XVDtISNOxNPAaSek1a7FHQRAEQahoInaL8ovdMuXYVVFujM297dtJS0/H3MUF8qw6vebiRZo5OzPMzp7ooCDseveGlHtwZS9zhzbhl5OJbDh2l/cGNSJbbwAUGPTW+CafooFLAJdjLNlzNpT+LQpGszyKqrx+kiAIgiCUNRG7VYTyit0yRWXHbpkaWeS/JxD2FL5i/sZ/w9n4b2EB1DlL0PxjejdNVlwcTVWNoypros6aRy61yqVOkE+tok4Ru2WS6hK7ZSoRu/VwTIlyqSm1lkTUWfPIpVa51AnyqVXOdYrYLRNUh9it0qjs2K3cyKL4r1eRumcP6jre+d7X2YcPczAsjO1dHqfWtKlYtW0LWamoNr5ObGwcjT88zahuPrzS3Q/u72anjyNdYc1yx+mEpapLjJZ5GMVdTq2qcVRlTdRZ88ilVrnUCfKpVdQpYrdMOm5Vj90qrcqO3cp9LzRPDyXyzBmkuHjUHh4olDnzYF5v0oS/rl/nwzu3+ally/vbOxDp24+XP5uNtbmSZx+rjUKpQKNSYiWlYqPQ8691D8KybGnma1dp0TJVLY6qvIg6ax651CqXOkE+tcq5ThG7VUpVLXarOtM0aoTrWxNQ2tqgu3uXrDt3yLp9m/rZer4cOIi/79yhtq8vTz31FP369aPOk1O5HGtgx/hmdHFOxluKxDnrLmSns1vRhQ2GnjStZcf7T1TvaBlBEARBqApE7FY5xm6ZcuyqzqZrVzRNmpB68BBZd+6gMDfH0r8lr7Vvz6C4OL7//nuOHDmCubk5ixcvZtTLL+OQFQE3/4HEe1xPMeeM2p8Uu4ZMr+PIY35OaMxUlV2WIAiCIFR7DzWI27VrF7Vq1UKtVuPo6Ii/vz8rVqxg1KhRKJVFn2Fp2rQpAQEBzJ49O99N6I0aNcrpjFqNt7c3Y8eOzXc/2smTJ+nZs6fx+9z7xUaNGmVSesSWLVt45ZVXjN8///zzAMyZM4e5c+dy+vRpjh8/DlDgnr1bt27h6+sLQEhICLGxscbnOnfuzNq1a5k5cyYzZsygQYMGbN68OV92X0nHrg7ULi44DB1S4PFatWoxa9asQvZwBPdmWAH+978EQRAEQShbInarFO2XNnbLlGPLUVJSEj///DNbtmwhPT0df39/xo0bR4sWLUxuIz1Lz5GQWE7dSSBdp6euqw09Grri7VT2s3fLhCTBvQtwIwhSIkDjCHW7Qe0OoCrTW1MFQRAEmSjVjUk1MXIL4Ntvv6VHjx7Y2dmhUChITEw06fXYv38/bdq0wcLCgvr16xc6uA0PD+fFF1/E2dkZS0tLWrRowcmTJ01qvya6cOECTZo0YfLkyVhYWFC3bl02bdpEy5YtWbRokUlthCem8+6GYBbuvMKui1Ecuh7LmkO3ePu3M2w/F1nOFTwEgx4OL4PN4+HMz3BzP1z4Hba/C7umQ2ZKZfdQEARBqIZKfXd5TYvcgpx1XPr378+MGTNMfh1u3brFwIED6dmzJ8HBwUycOJHXX3+d3bt3G7dJSEigS5cumJmZsXPnTi5dusSSJUseau26miAjI4MnnngCV1dXbt68ybZt2/j555+5c+cOM2bMYNq0aWzdurXYNnR6A5/uvMLlqBRq2Wnwc7amjpMVPs5WZGUbWPVPCGdCEyqoIhNd+BPOrgO1BTjVA0dfcK4PVk5wcx8c/qKyeygIgiBUQ6W+jlPTIrcAJk6cCJRuZuuqVavw8/NjyZIlADRp0oRDhw6xdOlS+vXrB8Cnn36Kt7c3a9asMe6XdwmWqi43fqusrFu3jrt377J582acnJzytf/++++zb98+Fi1aRK9evYps48StOC7euYebjQUKfSY6/X/POVlIhMansflECA2dm+TbT6fTkZGRgVarNf68VYjsrJxBnFKVM2jLy9wGLB0hZA+0Gw12nhXXL0EQBKHaK5ObcWpa5FZhevToga+vr/GS6dGjR+nTp0++bfr162ccEELOpIZ+/frx7LPP8s8//+Dl5cWbb77JmDFjij1WZcdu5TI1fqu02rZtW+zzj3rcA8C8Yp4vLp6rzMVeR5UUlnMPXJ5bDows7FEk3kYfHoxk6frIhxMxNzWPXGqVS50gn1pFndUodqumRG4VpU6dOtSqVcv4fVGRW8nJyaSnp2NpacnNmzf5+uuvmTx5MjNmzODEiRO8/fbbmJubM2rUqCKPJWK3ypcp8VxlxTY9jLZJSWRqDRiUqQU3kCSss7RcPPEv966V3YddLu+pXOoE+dQqlzpBPrXKuc5qE7tVEyK3ivPzzz+Xeh+DwUC7du34+OOPAWjdujUXLlxg1apVxQ7iKjt2K1du/FZZ+fbbb5kxYwbnz5/PNyDONWLECMLDwzlw4ECRbRy4Hsvngddxt7PArJAFg8Pi02nt7cCcJwteTg0KCqJXr14Vezk1S4vq953YpieBrVvB5zOSINuNtv2ez7lf7hGJmJuaRy61yqVOkE+tos5qFLtV3SO3SquoyC07OzssLS2BnHXUHqy3SZMm/Pnnn8W2XdmxW7nKerAzduxYPv74YyZPnszGjRuNrxPAL7/8wq5du/jhhx+KPW5AK1s2X0zgTpyWOlZWKJX//eGQoM1CY6VkyGP1C7Sh0+nQaDQ4ODhU7C8TMwdo8hT8+y1kp4N5nnxXfRakxUH9XijdG5ftYWUcc1NTyaVWudQJ8qlVznWWd91lMojLjdyaNGlSoc/njdz666+/im2rMiK3HkanTp0KXJZ7MHKrS5cuxoSGXNeuXcPHx6dC+ljV2Nvb8/vvvzN48GD8/PwYOXIkTk5O7Ny5k8OHD/Pqq6/mWxi5MBozFe8FNGLBjkvciU/DXK1ErVSQptNjoVbxTNvadGvgUkEVmajNSxB/IyfFIjUazCwhOyNn6ZFaLaHru5XdQ0EQBKEaKvUgrqZFbkHO/W1RUVHG45w/fx5bW1vq1KmDk1POjMKXX34ZLy8vFi5cCMC4ceNYuXIlU6dO5dVXXyUoKIgNGzawfft247EnTZpE586d+fjjjxk+fDj//vsv3377bYG18OSkb9++BAcHs2LFCjZs2EBGRgb+/v78+eefDB06NN8l+aI09bTj8+Gt2HP5Hoevx5KRbaCBmw19m7rT1sfRpDYqlJkl9P0oZ324azshKSxnpmr9vtCgL2jsK7uHgiAIQnUklcKoUaMkQAIktVotubq6Sn369JFWr14t6fV643Y+Pj7S0qVLC+zfr18/acCAAZIkSdK+ffuMbeW25+fnJ7333ntSamqqcZ8Ht8v9GjVqlEl9XrNmTaH7z5kzx7jNnDlzCt1mzZo1xm26d+9e4Jj79u2TWrVqJZmbm0t169bNt32urVu3Ss2bN5csLCykxo0bS99++61J/c4rKSlJAqSkpKRS71ucrKwsafPmzVJWVlaZtlsVyaVWUWfNI5da5VKnJMmnVlFn+f3/O1epzsTVxMgtgLlz55aYY1rYpdoePXpw5syZYvcbNGgQgwYNKqGXNUt2WAhpO/+HPiEOlaMzVgNGoK7doFL7pDPouJV9i003NmGmNqOpc1MaOjYscNbu0qVLrF+/noSEBOrVq2dM26jO9AaJ4LsJXL+XikIBjT3saOFln+9+QkEQBKH6EbFblF/sVmn6XhNIBgOJy6cRNuppYn5YR/ymQGJ+WEfYqGdIXDoFqbB10ipASGIIMw7PYGvaVn658gurL6xm5uGZfHTsIxIycmbgZmRkMHLkSJo1a8bKlSsJCgpi6tSp1K5dm6+//rpS+l0WQuPSmLQ+mA82XeC7gzf59sBNpv95jql/niUqKaOyuycIgiA8AhG7RfnFbpXU95om5YePiN+wDUOWHjNnK8xdbDBztkLSGYj/Ywcp38+v8D5Fp0Wz6MQiQhJDsFHY4G3jTR3bOlirrTkedZzPT32OzqBj3LhxbNy4kR9++MH4cxsWFsYrr7zCm2++yR9//FHhfX9USWk65m+/xPnwJJyszPF1tsbHyQp7SzNO3Unko+2XSMvKLrkhQRAEoUoSsVuUX+xWSX2vSQxpKST+tQ1QYObw34LECqUStb0lSbGpRGz8C8XgMShtKu5G/p1Xd3In9g5e1l7EZcahS9ehVCqxwAJnpTPBYcH8eeBPfv75Z5YsWcJzzz1nTMawsrJi0aJFhISEMHfuXPr371+lJk1YW1sX+/y+q9GExKRSx9EStSrn7zWFQoG1hZraKiVXolI4dD2WgGYeFdFdQRAEoYyJ2C0TPUzs1sOqKrFbpZF5aBu6BC0qG3MKu4OxxbHLOf/w8HrkY5W1bWwDYPLkyfkWWX6Qra1tRXXJJIXFh+V9Tw9ej0alAKUSDFL+S9lqVc5n88iNGHo2rH73/MklzgfkU6tc6gT51CrqFLFbJarKsVsPqzrGbrldOoFLtgGDPhtFZuXc+yY3xcWHBQYGEnJbSVoGROtSCt0mPROuhqSyY8fN8upiuZNLnA/Ip1a51AnyqVXOdYrYrRJU5dith1VVYrdK1ZafK1G7AlEYlKgsC6ZNXOjWHElvwP2zpZg16fBIxyqNz05+xpmYM3haexIbE4uLqwsKcn5OJSTCUsOoG1qXr9//mmPHjtGoUaMCbaxYsYIFCxZw9erVio3sKkFhl1PzvqeXzW7z96Vo3JwL/kEhSRJp8ek87u/FE938Cjxf1cklzgfkU6tc6gT51CrqFLFbJarKsVsPq6rEbpWqjZadsWroTeq526gszVAo/5szIxkMaDL1WDWrg2ungEftbqkMaDKAS9pLZKmzUGvUmFuao7zft+i0aJztnZkyZgp/Lv2T+fPns2nTpnyvRWhoKF9//TXPPfccvr6+Fdr3R2FmZkbfZrX453ocyenZOFjlv5UhTpuJjYWa3s08qvUvV7nE+YB8apVLnSCfWuVcZ3nXXerZqYXJjd0aNmxYoc/njd0qSXWK3co7ixYKxm7JjdOkOVi4WpMVm0Z2cjr69Cyyk9PJik3DzMUa54mzK7xPHWt1pJd3L5KykkgwJJCSlUJSZhKhyaEAjGgyAj9nP9asWcPff/9Nhw4d+O677/j777+ZO3cu7dq1Q6PRFDu7uapqU8eBwa08ScnMJjQ+jaR0HUnpOu7EpZGRbWB4O28auVet+/wEQRAE04nYLcovdutR+17dmDd9DI9l35O0Zinaf89iyMpGYa7GoUsb7Ee/g1nDNhXeJ7VSzRut3sDPzo9f//0VnSFndmpb97YM8BtAh1o5l3afeOIJ9u/fz/z5840TY6ytrXnxxReZO3eu8WelOlEoFPxf17r4uViz41wkt+O0oAB/b3sG+XvSo6FrlZptKwiCIJRSaeIdROxW/mOWFLv1qH3PVR1jt/TJ8ZLuzlVJnxxf5m0/jKysLGnjpo3SveR7UmJGomQwGIrcNj4+Xrp9+7aUlpZWgT0sG0W9pwaDQYpLzZTiUzOLrb26kEucjyTJp1a51ClJ8qlV1Clit6p17Naj9r0qCU8NJzwlHLVSTSOnRlibFb1GmaTXk3U3En1SEqrUbCwa2aFQqfJtc+3aNXbtO0Rihp72nR7n8Zb1sdWU870DCiWOGsfi71HI0uKYchVHfSak68Gybrn2qaIoFAqcrIte4kcQBEGofkp9T1xNjd7KyMhg/PjxODs7Y2Njw7BhwwpMXCjM77//TuPGjdFoNLRo0aLAsg+mHLsqy008eG//e3x07CPmHZ3H20Fv8/vV38k2FFztP+3UKcLffY+I92cQNW8+Ee/PIPzdd0k7cQKA8PBwevUJoFGjRrwz7jXmTPw/BnZuiX/voXwfdAmdvpKWJzHoIXgtrHsBtk6EHe/BH6/CjimQGFo5fRIEQRCEYjzUxIaaGL01adIktm7dyu+//84///xDREQETz/9dLGvw5EjRxgxYgSvvfYaZ86cYciQIQwZMoQLFy7k63tJx66qEjMSWXh8IQfCDqBWqqltWxt3a3dSslL49fKv/HTxp3zbp506xb1Fi8i8dg2VvT1m3t6oHBzIvHade58tJnzvXrp178GJ4HM0fn4GTy35m+eX7abNsPGEngxi2riX+XLvtco5e3niBzi8HNLiwa4WOPqCygJCgnIGcilRFd8nQRAEQSjGQy0xUtOit5KSkvjhhx9Yu3YtvXr1AmDNmjU0adKEY8eO0bFjx0L3W758Of3792fKlCkAzJ8/n8DAQFauXMmqVatMOnZVtid0DzcSb1DbpjZqZc6PilKhxM3KjZjEGHZe3Ulnl87UsauDZDAQ+dNPZCQkYla7NtkKBej1oFYjeXigCwtjzcyZhIWF4T/hK+rV9cPsfhRU015P4+Dhzd4V7/HLuj/oWf916pfxrEmdTkdGRgZarbbg5dSkcDjxP5A0YOkCOgADKGzAUgMRV+HkOugwxrhLSZFXgiAIglDeymyduOocvXXq1Cl0Ol2+GK3GjRtTp04djh49ahzE+fr6Mnr0aOP9c0ePHi0Q09SvX79iL/eaoirEbkmSRNCdIMyV5ihR5rtUDrDhmQ0A/MmfpT7uiSWvcqKI506vmUWrNbNK3Wb5m3T/K0dhkVdVgYi5qXnkUqtc6gT51CrqrEaxW1B9o7eioqIwNzcvsBq/u7s7UVH/XUarV68eLi4u+fYrLHor7z4PoyrEbuklPXdS72CQDESnRpf5Mau74iKvqgI5x9zUVHKpVS51gnxqlXOd1SZ2C2p+9NaDi/uWl6oQuyVJEnsP7CUyNRI3a7cC+77212uEpYbxfKPnGVJvCJkhIUTPmYvSxgalVcHECkN6Ok9t24amfis8nptBLYf820iSxI6PXsfMuTbzlqzk+fbeZVZnbq1BQUH06tWrQK2Ki3+iPPoFOPhQ6G2iqVFg5Yj+mZ/h/mXlqno5VcTc1DxyqVUudYJ8ahV1VqPYLai+0VseHh5kZWWRmJiY72zcvXv3il3ktajorUddGLaqxG718enD6gur0Ut6zFT5n09TpeFo50jvBr1xsHNAatOG7KZNSD9/AXN7+3yDeUmS0EVG8Xzr1nx2/F9sE2JQuDTCXP3fgCn0zAESI27y2ODx9G3lh4ODTZnWqNPp0Gg0ODg4FKy1xRNw+TcwJIFN/jOr6HWQngWthoKTC9WFnGNuaiq51CqXOkE+tcq5zmoRuwXVO3qrbdu2mJmZ5TvTdvXqVUJDQ4uN0arp0Vu96vSisVNjwlPDSchIINuQTaY+kyhtFGm6NAb4DcDbLueMmUKhwOnFF1E72JMVGoo+NRUpOxt9aipZoaGo7O15++OPqVevLue/mczxnesIj4wkISqMk5u/I+jrGbg07cTLzz5JXZcKPstlVwtavQjZmZB0F3TpoM/OmamaeAdcG0PTIRXbJ0EQBEEowUOdiatp0Vv29va89tprTJ48GScnJ+zs7Hjrrbfo1KlTvpmpvXv3ZujQoUyYMMFYT/fu3VmyZAkDBw5k3bp1nDx5Mt86d6bEflVV9hb2vP/Y+/zv0v84GnmUKG2UcXbqwLoDGVh3YL7tLVu2xH3GDOL/t5bMa1fRJyagMDPHsmVLnF4YgaW/P//s389rY8ayffMKrm9cBoDSzIIGXQcze/7HPNexXuVEQbUdBRpbOLseksNy1o0zt4ZGA6HjG2DjWvF9EgRBEITilDbioaZGb6Wnp0tvvvmm5OjoKFlZWUlDhw6VIiMj87Xj4+OTbx9JkqQNGzZIDRs2lMzNzaVmzZpJ27dvL/WxS1IVYreitdHSmXtnpAuxF6SM7IxitzUYDFJGSIikPXVayrhxo9CYp7t370o/rt0gLf3hN+nghdtSelb2Q9dhCpNr1WVKUvgZSQo9LklJ4eXap/IgYm5qHrnUKpc6JUk+tYo6q1jsFtTc6C2NRsOXX35Z5ILCUHhNzz77LM8+++wjHbs6cLVyxdXKtLNRCoUCi7rFx1XVrl2bUSOKft0qjdocPFtVdi/kJ+v/27vzuKir/Y/jr1nZ9x0FBNfcsDS3ypVcS20z00r7mWW7rS6ldq2uXrVszza3a920q6lXS1PRckFccRcVFVRAZIcZlmHm/P4gJkcQQRhgmPN8PHioM9/v+Z7PfGeY43c5bz3oM0DjDC4+9d2bGhFCkJZXhNEk8HdzQK2qtatWap1er+fChQs4OTmZU3bqksFoIKMwA5VChYfao063bWtMOh3G7GyULi6orptJQbJftXpjgyRJUrXoM+HwfyD+NyjKK737t2lniHwMgm+v795VixCC6FNprItL5ny6DoEg0N2JwR0Cua9jsMWNPPUtOzubGTNmsGTJEvLy8gBo3749U6dOZfTo0VbffpGxiA3nNrAlcQsZhRkoURLuHo6PwafR5E3XFkNaGjlr15L/x5+IggJQq3Hu0hmP4cNxbNWqvrsn1TO7yE4VQjBjxgyCgoJwcnIiKiqKM2fOWCxz8OBB7r33Xjw9PfHx8eGZZ54hPz//pq9HY89OlSSr0WfChjdg/6LSAZzWFZQqOLu1NOrs/I767mG1/BCbyLxN8ZxIycVBo8RZq+Zilp4vtyewYMtpSuorF/g6ubm59O3bl2XLlvHKK6+wY8cO1q5dS0REBGPGjGHu3LlW3X6xsZiP9n/EkmNLSNOn4ax2RqPScCzjGJsKNvHbhfLRjPbKkJZG6j9mkb1qNaKwEOVf84Tmbd1K6qxZFBw9dpMWpMbOLrJT586dy6effsrChQuJjY3FxcWFgQMHUlhYCEBycjJRUVG0aNGC2NhYNm7cyPHjx296GrSxZ6dKklUd/g+kHgbPUHALBAdXcPIC7+alg7pdn4ChsL57WSUJV/NZue8SDmolod7OuDtqcHVQ08TTCW9nLVtPXiHmXEZ9dxOADz/8kNOnT7Njxw7ee+897r77boYNG8batWuZMmUKU6dOJSkpyWrb//PSn8SmxOLr5EugSyAuGhfcte40dS2d9H3F6RVc0V25SSv2IXvFSooSEtA2bYra1xeliwtqLy+0oWEYMzPJ+O47xDXfuZL9afTZqUIIPv74Y9555x2GDx8OwLJlywgICGDNmjWMGjWK9evXo9Fo+OKLL1AqS8e1CxcupGPHjpw9e7bCCYqh8WenSlJ16XS6qi1YrIej60E4gUEJhuu+iLT+cOU8nNoKEX3KrV5pFm49+D3uAtl5eYR5O2MospweyVEBxQV6fj10gTuCq5+4Upu1CiH45ptvGD16NBEREeX216RJk/jiiy9YuHAhb7/9do22dSO/xf9GSWEJGrUGQ8nfkUQmkwmnIicyczOJPhvNsBbDrLL9ijTEybtLsrLQ7d6Fyt0dhdryq1qhVKL286f4/HkKjx/HKTKynnop1bdGn5167tw5UlNTLXJRPTw86NatGzExMYwaNYqioiK0Wq15AAfg5FSaKLBz507zIM6eslMbG3uptb7rdHWt3Uma4b5abs+6KjsB/Acwp646chPfffdductbrjV79mxmz55dhz2ytIlNdbq9us5CrsrntCg1FaNOj9LbC5Oo4FS8owMmg4HClBTU102g31DU9++juiKzU62YnVqWY1pZxmm/fv147bXXmDdvHq+88go6nY4pU6YAkJKSYl7HnrJTGyt7qdVe6pSk2lBfWciVfU7VmZkE63SYDMWYHB3LL2A0otHlc/7IEfTX/Ke/IbKX30cyO9UK2alV0a5dO5YuXcprr73G1KlTUalUvPzyywQEBFgcnbOn7NTGxl5qre86s7Kyqryscuu7KM9tR3g1A66b2kKfAQoFxhHfgFtAuXUry8KtD7HnM5mzMR4fVy2OGpXFc0aTicvZhYy/qxnDI4Or3XZt1zp+/Hji4uLYtWsXjtcNDjZv3szIkSP53//+x913313jbVXk59M/s+rsKpq4NkF5zWXZAsHltMuoXdVM6zqN27xvs8r2K1LXp1Or8jkVQpB26hSFR46i9vMrN/1LSdpVlKGhtHn6aVRubnXR7Wqr799HdUVmp1oxO1X917UEV65cISgoyPz8lStX6NSpk/nfo0ePZvTo0Vy5cgUXFxcUCgUfffQREZXMd9bYs1MbI3uptb7q9KzO/FU9n4Ks41CUAm5BoHYAYSodwCkL4I4nIaR1hatWmoVbD/p2cGdrQh77LmTiq9Hi5qBGoVCgLy4hNb+IVk38uL9LCzxdbnw5yY3Udq0zZsyge/fuPPnkk3z88ce0bdsWg8HA6tWree655+jbty9Dhw612pxxw9oNY1/2PlJ0KQQ4B+CodkQIQU5RDoUOhdwbdi/dwruhVDScKVms5WafU+9HHuFKwjmMKalo/P1RaDQIoxFjZiYYDHgOG46jt3cd9vjW2PPvXZmdWk3XZ6eGh4cTGBhocRQtNzeX2NjYCjNOAwICcHV1ZcWKFTg6OnLvvffecFuNPTtVkqwqKBKi3i29OzUvBTLPQ9YFUChLB3DdJtZ3D6tMq1YydfBt9G7lT0GxkcRMPRcydGTrDXQK8WTGfe3wvoUBnDVERkayYcMGjh49Srt27QgLC8Pf359Ro0bRo0cPVq9ebdVJfwNcApjSdQqtvVqTWZRJUl4SF/MuYjAZuE1zG89FPmcXA7iqcO7SBb9XXkbt54chNZXipCQMly+j0GrxenwMng89WN9dlOpZo89OVSgUTJo0iffff5+WLVsSHh7O9OnTCQ4OZsSIEeblPv/8c3r27ImrqyubN2/mzTffZM6cORZHFuwtO1WSrK7ZXdCkM1zcA7kpoHGC0O6lU47YGC8XLTPvb0vC1XyOJ+diNAma+7nSoYkHSmU95AFXol+/fiQmJrJmzRoOHz6Mk5MTw4YNo2PHjnWy/QjPCOb0msOx9GNczLuIWqmmtUdrju44iqumtm+OsW2u99yDc+fO6A8coCQ9A6WrC85duqD28qrvrkkNQXVzumwxO9VkMonp06eLgIAA4eDgIPr37y/i4+MtlnniiSeEt7e30Gq1omPHjmLZsmXl2rHn7FRbZy+1yjobH3up1V7qFMJ+apV1yuzUai13IwqFglmzZjFr1qwbLrNs2bKbtmPP2alVZczXkb9tG3nbtmHMyEDl44Nb3z649u2HyvXGFw/rDXr+uPQH2y9uJ70gHS9HL3o37U2fkD64actftHsxU8/vx1PZeTadohITLf1dGdAukE5Bznz77Td8++23JCQk4OnpyahRo8xHT6UGxmgoTWiI3wCZF0on/G0RBW2G2uTROEmSpLokY7f+cvr0aYYPH46vry/u7u7cfffdbNu27aavx81it959913atGmDi4sLXl5eREVFERsbe9N2bVFJVhaps2aR/tVXFJ05g0mno+jMGdK/WkjqP/5ByQ3uXMwpyuGD2A/46vBXnM46jc6gIyE7gW+PfMt7e94jo8BypvvDF7N587+HWR6bRFpuEfmFJew8m87MVfvp2O0e3nrrLTp06MC8efN4/PHH+eGHH+jWrRsJCQl18TJIVVVSBFv/AVvehaRYKM6H7CTY8yWsexHSz9y0CUmSJHsmY7f+Utb36OhoDhw4QGRkJPfdd1+lc75VJXarVatWfP755xw9epSdO3fSrFkzBgwYUOXpT2xJ1rJ/U3jkCOrAQLRNmqD29S39MzCQwqNHyVyytML1fjz5I4evHibAOYAmrk3wdfKliWsTglyCOJF+gmUn/j5Kqi8u4cPN8aTnFdHMx5lAD0f83Bxo5uNC4u+LSTx7ko+Xr+Wnn37ipZdeYv78+Zw5c4bw8HDmzZtn8R8NqZ4dWwWnN4GzD3iHg6s/eDQFr/DSmxy2/RNMxvrupSRJUoMlY7dGjSI9PZ0zZ87w/fffmy/snTNnDl9++SXHjh274Q0IVYndGj16tMU6H330Ed9//z1Hjhwx19cYlFy9Sv7u3Sg9PFBel8qh1GpRenig2xND9vnhaPz9zc9lFGTwx7k/cBbOKIuVGLCc3doVV2IuxDA8ZDgBLgFEn7zCxStZBHo4YiwupOwr3lBUQOLuDTTpMYz4Yi/y8/PNd9hpNBpmz57NgAEDWLduHUOGDLHqa2FtDTEiqNqMBjixFlTa0lOo11KqwC0YrsbD5QMQ0rV++ihJktTAyditUaPw8fGhdevWLFu2jDvuuAMHBwe+/vpr/P396dy5s3m9msZuFRcX88033+Dh4UFkJVl3thi7VXDuHMa8PNRBgRVGxCjcXClJTsGrknn3KvMzP1dpuaTtK/h0+wo+vcHzI0eOvKXtNySVRQTZTMxNbjKq3FTQukFFR0fVjmAsxpR2GhF4e7mnbabOWmAvtdpLnWA/tco6ZexWldQ0dkuhULBlyxZGjBiBm5sbSqUSf39/Nm7ciNc1t3HfauzW+vXrGTVqFHq9nqCgIDZv3mzRzvVsMXbLMTGJAJ0OQ1oaqCt4W5UY0VQ1HF2qVFUighp6zI2DIZtuuTkYFXpKVBXMCSkELsX5xB85yuVLN56NvqHXWZvspVZ7qRPsp1Z7rlPGblVBTWO3hBC88MIL+Pv7s2PHDpycnPjuu++4//772bdvnznp4VZjt/r27UtcXBzp6el8++23jBw5ktjYWPyvOa14LVuM3TLp9aTs348xLxd1BXWVXL2KKiyMjEuXUF5zOrCgpIApu6aQU5iDn5NfufUyCjNw0jgx5645uGndOJSUxfu/xuPlrMFR+3e8kclkZN30MbiEtuO5t+cwKaqlRTurV69m/PjxbN26lTvuuKNGtda3yk6n2kzMjRAo/7cLRfIh8Krgc1CYAyX+RA4eS6RPy3JP20ydtcBearWXOsF+apV1ytitKm23prFb0dHRrF+/nqysLPMg6csvv2Tz5s0sXbqUKVOmVLjdqsZuubi4mF+H7t2707JlS77//vsbplfYZOyWhwceQ4eQuXQZIjcPpbs7CoUCIQSm3FwoLML94UfwbtLEYjVPPBnedjhLjy+lUF2Iu/bv9fKK8zBoDDzS5hFC/EMAuMfNnY4nc4i7mEWwk6M5p9IkBKF9RnFy9ScUHN+K64jbzft+9+7dTJkyhcjISO65555G/cukjE3E3EQ+CmknQJdWelND2Sz9xTooyIBWA1EG3AaVpAfYRJ21xF5qtZc6wX5qtec6ZexWNd1K7FbZ4c5rw+7L/l3Z3Yy3GrtlMpksrnlrLDwffBD3oUMxFRViSEykODERQ2IipsJC3IcMwevhit8bw5oPY2jEUIqMRSTlJZGUm0RSXhIFxgIGhQ/i4VZ/p3eoVUqmDG5Dx6aepOUVcS5dx4V0HYkZem7r/wgPPvEMc9+dSnh4OA8//DB33nknd911F2FhYbz++ut19VJIVdG8H/R4HpRqyDwHmQmQcbY0O7VZL+j1VqUDOEmSJHsnY7coHYx5eXkxduxYZsyYgZOTE99++y3nz59n6NCh5raqG7ul0+n44IMPGDZsGEFBQaSnp/PFF19w+fLlSicItlUKjQbf55/DLSoK/Z4YSjIzUXl54dKjBw6tWt0wj1GtVDOhwwT6hvRlT8oeMgsz8XTwpHtQd1p5lV8vwN2ReQ9Hsu9CJgeTsigymAj1caZPKz/8n7+LQ69ONE/2GxERwbRp0xg0aBC///57XbwMUlUpFNBpNITdBQlbIecyaF0grCc06QKqWj1RIEmS1Ojc0m/JjRs3EhQUhFqtxsvLi8jISD799FPGjh1b7mjWtdq2bcuAAQOYMWOGxcXZrVu3Lu2MWk1ISAjPPvus+Q5QgP3799O3b1/zv8uuFxs7dmyV0iPeeustdDodzzzzDNnZ2dx9991s3LgRR0dHoPS078aNG3n77bfp168fBoOBdu3asXbtWou7SBMSEkhPTzf/u2fPnvz444+88847TJs2jZYtW7JmzRrat28PlB5RPHXqFEuXLiU9PR0fHx/uvPNOduzYQbt27W7ab1ukUChwbN0Kx9atqr1eS6+WtPQqf/1TRbRqJXe18OWuFuVvELn99tv58ssvLR5r7HdH2TSvMOjyf/XdC0mSJJsjY7f+0qVLFzZt2lRpO9WN3XJ0dGT16tXV6mtDkZOTy5zPvmHNmjXk6XLwaOZJlxHt6dS5FZ38O9EtqBvOmtq/U1aSJEmSpKqRsVt/sUbslsFgYPLkyXTo0AEXFxeCg4N58sknSU5Ovmm79enw0eOEtWjNv2ZOIVWfid4zm9N79rJs4kIWzPmSBQcWMG3nNC7lXarvrkqSJEmS3ZKxW3+xRuyWXq/n4MGDTJ8+nYMHD7J69Wri4+MZNmxYFV7l+mEwGLh30BBKVA70nfURrd9qTotnO9Bl3oM0Gd6Bi6vOkrwzh7PZZ1lwYAEGozxNKUmSJEn1QcZuWTF2y8PDo9zkf59//jldu3YlKSnppjdl1DWdTsfyn37manISPV/9CnzjKS7S4YAfCgShg9uSezKVU78cp809Q4lPjWfH+R10C6p6ukZVNIpYKUmSJEmyMhm7VYexWwA5OTkoFArzoLUi9RW75er6d4bl7gWVz9H3wwOlofQb2FBr/SlTWazUrZLxL42LvdQJ9lOrvdQJ9lOrrFPGblVJQ4/dKlNYWMjkyZN57LHHKk1esMXYrdpUlVipW9XQarUWWWfjYy+12kudYD+12nOdMnarChp67BaUjsZHjhyJEIKvvvqq0mXrK3YrKyuLz7/+nulT36TP1CWYQmPIJR5H/o7DOvX1LgpTcnnw8xFkFaczseNEejWp+oC7KqxxOlXGvzQu9lIn2E+t9lIn2E+tsk4Zu1Wl7Tb02K2yAVxiYiLR0dE3HYjVV+yWp6cnr744kdkfvEfcyk/oOWkCBS6JCArR4MaV2Atkx12m7VPdyFNmE+obSlSrKJuaasSe418aI3upE+ynVnupE+ynVnuuU8ZuVVNDi90qG8CdOXOGLVu24OPjc0t11RUXFxdWrPwvuosn2Tx5KpeWZZG07iSHZm/gzMJd+PYIJnSQD/7O/rx0x0s2NYCTJEmSpMZExm5hvdgtg8HAww8/zMGDB1m/fj1Go9F8vZy3t3elN3nUp/sGRXHg4EGm/3M+0Rs3UFSkwy3Eiw5v3MGdAztwV9Me9A7pTaBLxXftSpIkSZJkfTJ2C+vFbl2+fJl169YBmE/dltm2bVuFExM3FB3atmHN8u9uvqAkSZIkSfVCxm79xRqxW82aNatRv21VSVYW+thYjDm5qDzcce7aFbW3d313S6ojRUVFrF69mr1796JWqxk4cCA9evVg35V9XC24iqPKkc4BnQl2Da7vrlZLQbGR2PMZJGcX4qBW0jnMi2a+NjqnoRBw5TikxIGpBLwjIKQ7qBvm2QFJkiomY7cq6Me1P/v27av09fjiiy9o1qwZjo6OdOvWjb1791o8/80339CnTx/c3d1RKBRkZ2dX2p4tE0KQ/csaLr3wAlc//YzMpUu5+smnXHrhRbJXrbbLAa292b17N+Hh4YwePZpff/2VFStWcO+99xLWLowPNn7Av0/8m2+OfMPrf7zOt0e+tZnEj73nM5m4/ADvbzjJ9zvP8cW2s7z0n0N8+Hs8BcXG+u5e9egz4be3YM3zsOtjiPkCfn0L/juudGAnSZLNkLFblJ4WTUlJsfh5+umnCQ8Pt7h273orVqzgtddeY+bMmRw8eJDIyEgGDhxIWlqaeRm9Xs+gQYOYNm1aFV5Z25a3aROZixdjKixC06QJ2tBQNE2bIoqKyFy6hLxrjsJKjU9CQgKDBg2iRYsWnDhxgvj4eP63/3/0m92PgtwC9s/aT7BDMKFuoShR8r9z/2PZiWX13e2bOpWay79+O8Xl7AKC3B1p5uNCMx9ntCoFG46m8MW2MzdvpKEwlsCWf0DCVtC6gFdE6VE41wC4eho2TYMcmYksSbZCxm6NGoVWq7WYFsRgMLB27Vpeeukli3nvrvfRRx8xYcIEnnrqKQAWLlzIhg0bWLRokXlakkmTJgHl75ptbEzFxWT/sgYAjb+/+XGFSoXa3x9DcjLZv6zBtV8/lBVMn9LQ6HS6+u7CLTEYDBQWFqLT6er8lv558+bh6OjIypUrcXNzIz8/n1XHV6EN0zJ4+mBWvbSK+M3xtOrXCldcMRgNbDq9ib4BfQlwCbj5Bq5RF3WWzVe4Ni6ZTH0x4T7O5t8HCoUCT2ctoOCP0+k81FlHuC2cWr20Dy7tBbfg0kFcGY0jeIVD1jk4uR66T6y/PkqSVGUydmvUqHLtrVu3joyMDPPgrIxCoWDx4sWMGzeO4uJiDhw4YDFlilKpJCoqipiYmCr3vSL1FbtVE4XHj2NITkbp441JlJ+WReHthSElGd3x4zh26FDj7VVXdWu9NoJMqp5r52O83vYF29m+YLvFYz/zs5V7dGuKi4vRF5ewJyEdd0cVAlHukgA3RyVJmUXEJlylqYd1rierzc+p8sJulCVFCLUTVDR9ksoRzmzG2Hl8jbdVXfYS0QT2U6usU8ZuVUlNY7eu9/333zNw4EBzv8q0bt0aDw8PANLT0zEajRW2e+rUqSr3vSK2GLvldP48/jk5GJQKqOgOZZMJTU4OCX/8QcHFizXe3q2yl/gXqeZ+/fVXdAbIyFShVgpKbnBwVleo4EDcEZxSD1u1P7Xx3m2dcoQmOh26krQKn9ca9Jj0l9hlxei7m7Gnz6i91GrPdcrYrSqoaezWtS5dusSmTZtYuXJluedqOjirqvqK3apRW5cvk7pjJ2g1qCroozE3F9QaWg0fgSakaQUtWFd1a83KyqqDXtU+g8FAdHQ0/fr1q/PTqf3798fX15cVK1YAUFhSyFs73yKvOA9vtTc/TfiJsG5h3DXxLgCKTcWkF6TzWufX6OzfuVrbqos6XVxcKDGa+D03jtTcQvw9HMv3w2iiMKeIqLta0a+1XwWt1Fxtfk4VcZkoY47h4uULigr+s5WtRzS9kyFDhtRoO7fCXiKawH5qlXXK2K0qbbemsVvXWrx4MT4+PgwbNqzSbfr6+qJSqaoUu1Vd9RW7VaM2mjXD+Y7byf9zB2pXNxQqlfk5YTQisrJx7tkT54jwSlqxvqrWWvZ+tDUGgwFHR0c8PT3r/Jfm888/z4QJE4iNjWXgwIEADGg1gBXxKzj6v6PoM/V0HNERBxcHhBCk5acR7h9Or+a90Kiq19e6qlOjgSEdgvn6zwSKSwSOmmve10KQlldMkIcT97TyR6Op1V+nFfSlFj7/rQfC4R9Alwbu103xUpRXOrBrez+qevzCtZeIJrCfWu25Thm7VU23ErtVRgjB4sWLefLJJ2/6wmu1Wjp37mzRrslkYuvWreXatRfeY8fh0CyM4otJlFy9ijEvj5L0dIqTktCEhuLz1Lj67qJkRWPHjmXIkCHcf//9TJgwgV9//RVxRHBq/in2Ld5Hm0fa4BDiQGZhJom5iXg6eDKh44RqD+Dq2n2RQXQN9yYlt5Dk7ALyCg1k6oq5kKHH1UHN832b46y17gCu1rgHQ/fnQaGAjAQoyILCHMhOAn06tB4CzfvXdy8lSaoiGbt1jejoaM6fP1/hdXtQes3f7NmzeeCBB4DS5IixY8fSpUsXunbtyscff4xOp7O4ISI1NZXU1FRz/48ePYqbmxuhoaF4N7IJcLVNmxA4axY56/6H7s8/MRUUoHByxHPgADzuuw9NJRe8S7ZPrVazevVq5s2bx1dffWWeF7Jd+3Y8P+d5ijsVk2/IR6VUERUWxX0R99HCq/zlFQ2Ns1bN9Pvasi4umY3HU8nSFaNUKuh/mz/DOzWhfROP+u5i9bR/sHRKkaP/hdQjIAzg0wJuGwbtRoDKRgakkiTJ2K1rff/99/Ts2ZM2bdpU2E58fDw5OTnmfz/66KNcvXqVGTNmkJqaSqdOndi4caPFzQ4LFy60uEmh7IaNsrtcGxtNQAC+E57G+4nHMel0KF1cUDqWv5ZIapy0Wi1vv/02U6ZMITk5GbVaTWBgIAqFAoPRQG5xLo5qR1w0NjAdxzWctWpGdQ3loc5NySkw4KBW4ubYsI8gVqrZXRDWEwqzwWQEJy9Qqm66miRJDYuM3brGjz/+WOnzFfXhxRdf5MUXX7zhOu+++67FgNRWXc6/zOW8y6iValp7t670S1gYjRSfO4cxJweVhwcOrVtbXCNXE0VFRWxZ+xPpSfGENgmi9/DHUTp71UrbtyI1p5Bz6fmoFAraBLrj4WzDX+y1SKVSERISYvGYRqXBx8mnnnpUOzQqJb6uDX+ewypRKEoHb5Ik2SwZu3WdoqIiOnXqhEKhIC4u7qavx81itwBiYmLo168fLi4uuLu706tXr1u+5q+upenTmLtvLm9sf4P397zPrJhZvBz9Mj/H/0yJqaTc8voDB7j8+hskT51G6qz3SJ46jcuvv47+JvFlVfHNpx8SGujDfY+OY9ybs+k3+mVahTfltwUvQ0lxjduvjmx9MfM3nWLi8gNMX3OMd9Yc4+ll+/huxzkKDTYWwyRJkiTZJBm7dZ233nqL4OCqBXNXJXYrJiaGQYMGMWDAAPbu3cu+fft48cUXKz3t3FBkF2YzO3Y2f176E7VSTVO3pgS4BJBXnMfyk8tZenypxfL6Awe4MncuRadPo/LwQBMSgsrTk6LTZ7gyb36NBnJfffoRz77yBkNaO3Ds3e4ULX6AXdN70cLXgfvf+IzNCyaWhnrXAV1RCbPWn2DD0RQUQIiXM8EejhQZTPy4N4mPt5zGZJI5sZIkSZJ1yditaxIbfvvtN37//XdWrVpV4WDzelWJ3Xr11Vd5+eWXzf+Gv68BbOi2JG3hbPZZmro2Ra0sfasoFUr8nf3JKszit/jf6Onbk1D3UITJRMrSpRRmZaNp2pQShQKMRlCrEYGBGC5dwrBsGcFt2qCo5gBWr9fz9jszGNfNh8+f7gFKLQYTRDbzZcWk3tw3bztvfLKSXQ9ORBHYrsI2ajOmaePRVA6eTSHQwxGt2ojpryNvnlpQm4xsPZpEnwh3OjT1NEc3SZIkSVJtk7Fbfw3irly5woQJE1izZs0NUxGqG7uVlpZGbGwsY8aMoWfPniQkJNCmTRs++OAD7r777hvW0xBit4QQRCdGo1VqUaK0OFUO4K5xZ+F9C1nFqqpvcPPv8Pnnt9zfJbE6lsSuv+Hzbi2q/p6xti2TS/8sLq7b07wy5qbxsZda7aVOsJ9aZZ0ydqtKahq7JYRg3LhxTJw4kS5dutzwpozqxm6dO3cOKL25Yf78+XTq1Illy5bRv39/jh07RsuWLSvcTkOI3TIKI4n5iZiEibT8iiN6pJv7tZ7ii+w55qaxspda7aVOsJ9a7blOGbtVBTWN3frss8/Iy8u76UTE1Y3dKjt69eyzz5pPud5+++1s3bqVRYsWMXv27ArXawixW0IItv65lZT8FPxd/MutK4Rg4A8DGdV6FCOaj6AoIYG0me+idHVF6exUbnlTQQGmvDz8Z87E4QaD1xtZt24dY8eO5cDkdrRsUX7dDXHJPPbFXmK/f5NWD067Ya21FdM0Y+0Jjl7OoYl3+TqFEFzMLGB4ZDDj725W56dTZcxN42MvtdpLnWA/tco6ZexWlbZb09it6OhoYmJiykVddenShTFjxrB0qeUF/GW13Sx2q2x719d72223kZSUdMN6GkrsVlRYFIuOLcIojOVm1c8szMTL3Yv+Lfvj6e6JuOMOStreRsHRY2g9PCwG80IIDCmpOLZri3+XLhbPVcXIkSN57ZUX+WRbKktua45C8/e8c8UlRj7dGE/XZm50ve//4AZxWbUZ0zSkczgn0uMRKkeLGCaAnAIDrq5qBt4ejqdn/U0Ca88xN42VvdRqL3WC/dRqz3XK2K1qupXYrU8//ZTDhw8TFxdHXFyc+RTYihUr+OCDDyrcTlVit5o1a0ZwcDDx8fEW654+fZqwsLBbqq8u9QvtRxvvNlzOv0xWYRYlphKKjEWk6lLRG/QMDh9MiHvpXGAKhQLvxx9H7elBcVISxvx8REkJxvx8ipOSUHl44P3449UewAE4Ojoyf+5clu3N4NGP/yT2aAKZOTp+P5RE1HubOZCYy7zXHge/urlhpHcrfzqHeZOSU0h6fhEGo4niEhNXcgvJ0hcT1dafdsG1d8RUkiRJkioiY7egXBuurq4ANG/e3Hy9HlQ/dkuhUPDmm28yc+ZMIiMj6dSpE0uXLuXUqVP897//rbTfDYGHgwdTu03lhxM/EJMSQ6ou1Xx36tCIoQyNGGqxvFPHjgRMm0bmDz9SdDoeY3YWCo0Wp44d8R79GE6Rkbfcl3ETJqJRKZg2bQrd5xwwP96hqTubvphCr/GzSicvrQNOWhVv33cby3ZfYNupq6TmFqIAfFwdeKxrKCPvDLmlwaokSZIkVYeM3aqGW4ndmjRpEoWFhbz66qtkZmYSGRnJ5s2bad68ebW2XV+8Hb156Y6XGKUfxeX8y2hUGlp4tsBBVfGs9U4dOhA8+58Unz+PMTsHlYc72oiIWhnUjPm/Zxk19ml2bd7A1cQThIU0oXP/B1E41P00Hu6OGl7s15LR3cK4kKFDpVDQwt8VFweZOylJkiTVDRm7VYFmzZpVuL1bid0CmDJlisU8cbbIz9kPP2e/Ki2rUChwiIiwSj9UKhW9Bg0Dhlml/erydtHi7XLjaXPKKcqHgkzQuoKzt9X6lVWYhbHIiJejF47qyv+zUmI0kZ5fOhWKp6OSC+fPoVQqad68OapaikurS8bsbEw6HSovL5RWuJtbkiSpoZCHDSSpLuSlQtyPcGYzGPSg0kBoT+g0Gvzb1NpmjmccZ71+PT/98RMmYcJV60rfkL7c3/x+PBwsb7QoMZr47Vgqvx5NISk9j7O//5uLu9dSkJMBlF5m8PLLL/Pqq6/aRMJIYfxpctauQX/gIJSUoHR2xqVXLzwffAC1j21ntkqSJFVEZqdep7azU/v06WNRo0KhYOLEiTdtV2pEcpNh/atwaDmUFIJD6TWXxG+ADa9B8qFa2cyelD38a/+/OFtyFiVKnDXO5Bfn81P8T/wz9p/kFP19KYDJJPjqjwQ+3XqGhCs5xC2ezpnfl+HT/h46P7eAV+YvoV+/frz55puMHz++RkfC60LB4cOkzvoHedHbUCgUKJ2dMRUUkLNqFanvvktJFacbkiRJsiUyO/U6tZ2dCjBhwgRSUlLMP3Pnzq1S+1IjsX8xXI0H73Bw9f/rVKoPeEdAfhrs+gRMxhptQm/Qs/jYYvQlerwV3ng4eOCiccHP2Y9gl2BOZJzg1/N/X4d6MCmLX4+k4OGkwXA2huQjO4l6aR4Dnp5GaLs7OaOJ4LX3Pmbx4sUsWbKE6Ojomr4KViNKSsj49juMWdlow8JQeXqidHFB7euLpmlTCs+cIevnhn8jkSRJUnXJ7FQrZ6cCODs7m18HyTbodLpaaigDTm4FpTsUA5RYPq/1g8snISEGgm+/5c3suryLSxmX8HPyI7soG0OBwXwKVIECTYmGTac3MSh4EFqVlt8OXUCv1+Hn5MLObasIaNWJwDZ3YCgqwEUlyMjRs+nwBSY+9BD/+te/+PLLL+nevfutvw617NosXMPx42SfS0Dl5W3xn8gyJU7OXN2+HYcHRqCq5mTZMvtWkqSGTGanWjE7tcwPP/zA8uXLCQwM5P7772f69OmVxmc1hOzUxqa6tZZNM1NnXr2nTjazlPITV5f598TeFv/+E3jzr7+fPHmS1atXW69jdeHnldVepa6zbytiL59Te6kT7KdWWafMTq2ShpqdCjB69GjCwsIIDg7myJEjTJ48mfj4+Eq/EBtCdmpjZU+1SjVXX9m3FbGX96691An2U6s91ymzU6ugoWanAuYjggAdOnQgKCiI/v37k5CQcMO54hpCdmpjU91as7KyamfDQqDc8CqK1MPgGQZcN19efio4uGF88HtwcLvlzVzRXeGdmHdAgCHXgK+fL4q/tiUQXMq/RK8mvXg+8nkANh2/wpd/JBDk4cjJjf/m+O8/Mfy9H3By96a4xERabhGT+rcgRJ1L165dmTt3LuPHj7/l/tW2a7NwlXo9qW++hamwALWvr8VyQghKLl7CsVMn/N6eVu35ChvC6VR7+ZzaS51gP7XKOmV2apW221CzUytSdpr47NmzNxzENZTs1MaoqrV63iCD9Zbc/TT8/g4UXwG3QFBpS29k0F0FjYBuT0BASI024enpyaDWg1hzdg0l2hLUjmrUKjXFxmLS9Gn4efrxUIeHzHUN6ezCH+fzOZmaR7NeD3Nmx//Y9tlkOo16E5N/SzqGB6DNOs/IF54jPDycZ599tu5PMVfCIgvXzw/lQw+S+e/lKHPzUHl5oVCpEAYDhqtpOHl5ETB6NM5eXvXd7Rqxl8+pvdQJ9lOrPdcps1OrqSFlp1akbNqSaweUUiPX7G7oMw1cAyD3MmSeg+xEUDtCt2eh05ha2cyTbZ9keMRwUMBl3WUu5l0krSCNpq5Nea3La7T2/jtb1s1Rw/T729KlmRcGrTsdJ8ynqKiIbfOf5cDsR/nPK4MZOnggnp6ebNmypUEN4Cri+fDDeI0ejUKjxnD5MsVJSRhSU9H4++M36RWc77j1m0YkSZIaKpmdivWyUxMSEvjxxx8ZMmQIPj4+HDlyhFdffZVevXrRsWPHSvstNTKtBkCzuyAxpvQInINr6WS/LrU3Ca1GpWFs27E4nHPAt6MvBgwEOAdwu//taFXlbygK8nBi7kMdOZGSy+kr4YhR/ck8vY8Lxw+iUqno378/99xzj03kwCpUKrxHP4b7oIHoDxzAlK9D7euLc5fOKJ2c6rt7kiRJViGzU6uhutmpWq2WLVu2mAd3ISEhPPTQQ7zzzjvV2q7USGhdoGXUzZerIXelO1GhUVU6jK9QKGgX7EG74L/SHDqHAA9at4NWpPb2xv3ee+u7G5IkSXVCZqdWoLayU0NCQvjjjz+q11kbpzPo2H5xO9svbiezMBNvR296h/Smb0hfXDQ3vkjcpNORt307+dHbKElPR+XtjVvfPrj06cP66Gg+++wz9uzZg0ql4t5772X0+OfIdotg59l0ikpMtPR3ZUC7QHpE+KBU3uKRo+yLcGo9JGwrTVbwbQlthkJ4b1DaXoaoJEmS1LjJ2K3r1Hbs1rPPPkvz5s1xcnLCz8+P4cOH39JdrrYguzCb9/e8z9eHv+Zs9ll0Bh1ns8/yzeFveC/mPbIKK77j05idTcp775P+xZcUxsdj0ukoPnuWq19+xYv9+vHAAw9QVFTErFmzmDJlCoePneDh+wYw9+PPScstIr+whJ1n03lv/Qm++uMsJtMtDPiT42Dt87DvO8hLhqI8OP8nbHob/pxf40QFSZIkSaptMnbrOrUdu9W5c2cWL17MyZMn2bRpE0IIBgwYgNHY+AYFy08u5+jVowS6BNLEtQm+Tr40cW1CoEsgxzKO8e8T/65wvczlP1AQF4c6IABt06alcUlNmrDTaOTrAwd4f8QIdu7cyeuvv86kN96ix5uLaNpzBGd++QSngiv4uTnQzMcFVwc16+JS2H46rcLt3JChELZ9UBpS7x0B7k1K47G8I8DRA078AvE3T/CQJEmSpLokY7esHLt17TxxzZo14/333ycyMpILFy7ccIoRW5RekE5McgwuwgVFsQIDf89SrUCBi8mFned3MixkGH7OfubnSjIyuLp9O8LZGaNSCdfMbr3k1Enae3kxQqEk+9w5NAEBRJ+8wqWrOfR4ZCLrDkdzYstKujxSejrbWQkZhXrW7j9P16YuFhfkXxvTVO5asbPRkHoOPIKhyASYrnnSBQrT4dAqCOkDtXCRf0OYe0ySJEmyfTJ2qw5it8rodDoWL15MeHg4ISE3nhfMFmO3zmWeI784n3UPr6t0uZ/5udptt/9lNfxSccLFya0/c3KrZZvbgU+rvRWAg5U8dwBYckutXs+aUU4y5qbxsZda7aVOsJ9aZZ0ydqtKGnLsFsCXX35pvkO2devWbN68udLBrC3Gbl0suUi+Pr8WetP41UWUkz3H3DRW9lKrvdQJ9lOrPdcpY7eqoCHHbgGMGTOGe++9l5SUFObPn8/IkSPZtWvXDac4scXYLb1Bz8E/DzJixQh8HX3LPZ9emI6r1pU5d82xuEvV9FdkkjEnG7W/v8U603fuZNfFS/x2//2EfDgflZsbh5KyeP/XeJyM+fz27mgih42n7b2PAqXvv0tZBfRt5cekqJblai2Labq+VkVyHMpNk0uvfyt3B61AkZ2IKaIPpn4za/AK/c2ap1NlzE3jYy+12kudYD+1yjpl7FaVttvQY7c8PDzw8PCgZcuWdO/eHS8vL3755RdzH69ni7FbHhoPBocP5t8n/02huhB3rTsKhQIhBLnFuRi1Roa2GUoTvyaWK3p6onxgBBmLF6PSF6D08DCvN755C9adPct7F5NY5O6Oh4cH97i5E7HrDCvn/gO1gxO39X0QB0cXTEKQmlOIp7s7D3Vvhaenh8VmLGKarq/VvRec7gIX94CzI2j+mhxWmCA3Bdw9oOsYqM0oLiuz55ibxspearWXOsF+arXnOmXsVjU19NgtIQRCCItr3hqLES1HMCR8CEXGIhLzEknKTSIxL5EiYxGDmw3moZYVvzc8RozA4/77EcXFGBITKU5MxJCYSGtHRxaOe4oNhw4RHBzMsGHDGDpkMEteHkpx+iUix88muVDDhXQdiRl6XBzUvNSvJR2aelS4nRtSKiFqJjTpAvlpkHEWMhNK47G0znDP69C0y83bkSRJkqQ6JGO3sF7s1rlz51ixYgUDBgzAz8+PS5cuMWfOHJycnBgyZEil/bZFGqWGZzs+S7/QfsSmxJJZmImXgxfdgrrRyqvVDeObFGo1Ps8+i2u/fuhjYijJzETl6YVLj+481bo1g95/j++++46YmBi0Wi0ffvghj415gtNZRg4mZVFkMBHq40yfVn74u1cvhcPM1R+GfVZ6NO7i3tJpR7zCoEV/cK/alDOSJEmSVJdk7FY1VDd2y9HRkR07dvDxxx+TlZVFQEAAvXr1Yvfu3fhfd/1XY6FQKGjl1YpWXq2qvZ5jq1Y4tiq/XnBwMDNmzCj3uJ8P3NWi/PV3t0ythfBepT+SJEmS1MDJ2K0K1FbsVnBwcJ3ciVhdxnwdupjd6A4dwvf0GXL0ejz69kVzzbV8OTm5zPnsG9asWUOeLgePZp50GdGeTp1b0cm/E92CuuGsqf07ZSVJkiRJqhoZu3Wd2o7d+uabb+jTpw/u7qUX+mdnZ9+0TWsqvnCB5Lfe4uqCj9FFb8PldDzZS5dx+bXXyPvresLDR48T1qI1/5o5hVR9JnrPbE7v2cuyiQtZMOdLFhxYwLSd07iUd6lea5EkSZIkeyZjt65T27Fber2eQYMGMW3atCq1aU2mwkKuzP+QovPn0AQFoQkLxeDjgzqkKaZ8HelffkXesePcO2gIJSoH+s76iNZvNafFsx3oMu9BmgzvwMVVZ0nemcPZ7LMsOLAAg7FxT+IoSZIkSQ3VLQ3iymK3yiK3pk2bxtq1a/ntt98sTrWWxW5FREQwefJkvL29K5wMz9/fn8DAQMLDw3n55ZcJDw+3GJQNHjyY999/33xDwfUiIiKYOnUqM2fONMdubdu2DV9f33KxWx07dmTZsmUkJyeXO6JXFrs1f/78Kr0O18ZutW3bloULF+Ls7MyiRYvMy0yaNIkpU6bQvXv3KrVpTfrYWIrPnUMbFIzimtueFUolxb6+5GdlsWj2HK4mJxE5egr4nqe4SIeqyA2FURA6uC1urfw49ctxPBU+xKfGs+P8DnQ6Xa38SJIkSZJUdTJ2qw5jt6rKWrFbuuPHESYTQqNGCBPCVHqNnzAJblu8yGLZ3Qsqn6PvhweWAbCBDbfcn+vJOKqak3U2PvZSq73UCfZTq6xTxm5VSUOP3aoua8VueZ88hXt+PsXXnO4FuJpetWQLa5NxVLVH1tn42Eut9lIn2E+t9lynjN2qgoYeu1Vd1ordylepyTh7Fg8fHxQqFcIkuJp+FT9fP0489RSGpIuscnBg1m+/0mfqEkyhMeQSjyN+5jZOfb2LwpRcHvx8BFnF6UzsOJFeTWpnSg4ZR1Vzss7Gx15qtZc6wX5qlXXK2K0qbbehx25Vl7Vit9x79yJ31SpKUlLRNGkCytIBt0KpwDE7Hwc3N158/TXm79hJ3MpP6DlpAgUuiQgK0eDGldgLZMddpu1T3chTZhPqG0pUqyibmmrEnuNfGiN7qRPsp1Z7qRPsp1Z7rlPGblVTQ4/dqk8qNzf8J72C2tub4qQkSlJTUefkYkhMAqMRr1GP4nvXXaxY+V90F0+yefJULi3LImndSQ7N3sCZhbvw7RFM6CAf/J39eemOl2xqACdJkiRJjYmM3cJ6sVsAqamppKammvt/9OhR3NzcCA0Nxdvbu9K+W4NTZCTB/5pDXvQ28mNiKEm+jOvd9+Ax4F4c27dHoVBw36AoDhw8yPR/zid64waKinS4hXjR4Y07uHNgB+5q2oPeIb0JdKnZEUdJkiRJkm6djN2qhurGbgEsXLjQ4iaFshs2yu5yrQ+a4GC8Hx+D26MjOfTrr3QaMqTcId8ObduwZvl3N2hBkiRJkqT6JmO3KlBbsVsA7777rsWAVJJs0cVMPfsTMykoNuHv5sCdoW4k7vuVHRv+x84jZ1C6edFrwP2MGfO4+Uh2gyAEJB+CK8dBmMCvDTTpDKpavRxYkiSpXsjYrb8MGzaM0NBQHB0dCQoK4oknniA5Ofmmr4etxW5JUnUUlRj5PPoML/54kM+iz/L9znN8tWo9yx7rz1MPPsWLHy5j0/Z97Nq4leefe47goCB++eWX+u52qdwUWPsirHsJdn0Cuz+D9ZNg9TOQea6+eydJklRjMnbrL3379mXlypXEx8ezatUqEhISLK7Lq4itxW5JUnV9v+M8vxy6jFKhIMzbmeYuhYzY+x2L/jzKaV0BU7u2Zun93VjYN5L/dG5NRy9HRo4cya5du+q348V6+P0duLgHnDzBOwJ8moOLL6Qeho1TQZ9Zv32UJEmqoVs6p1AWuwWYo7e6d+9O//79WbJkiXlC37LYLSid+Hfu3Lls3ryZwYMHW7Tn7+9vnmLk5Zdf5tNPP+XgwYP0798fKI3dun6da0VERPDqq6/SvXt3c+yWl5cXAwYMKBe7BbBs2TICAgJYs2aNObHh1VdfNbcXFhbGlClTGDFiBAaD4Ya3CF8buwWl179t2LCBRYsWMWXKFKA0dgvK3zUrNQ4NLS7MYDBQWFiITqer8a3tqTkF/HroAk4KcFMrMRYb8Y//H8kJKcTl6ni5Uwtu83bHYDRhUKvQBLgzRa3iFaHmgw8+4Oeff66lqsq7aZ2nN0NiHLgHgckBiox/PaEFp6aQfBqOrIMOj1itj5Wx5pyIkiTZDxm79dcg7lqZmZn88MMP9OzZ0+ILwtZjt65nL5EoYL1aG9T1X3Xs07izN3zu3KXfbOC1eeqvn7pXnYg5e/mc2kudYD+1yjpl7FaV1DR269r+fv755+j1erp378769estnrf12K0bsZdIFLCvWqWG61Yi5uzlvWsvdYL91GrPdcrYrSqoaezWtf0dP348iYmJ/OMf/+DJJ59k/fr15ppsPXbrevYSiQLWqzUrK6vW2qoNBoOB6Oho+vXrV+M6Y89n8q+N8fi6OaBVl14+23b3R5zdHsvyy1eZf09H3BzUuDtqUCgAk8D5aj6fFhs4cCmbEydOoFKpaqGq8m5Wp3Lv1ygP/4jwCgcU5Z5XZJ/H1HIQpt5TrNK/m6nO6VR7+ZzaS51gP7XKOmXsVpW2W9PYrWv76+vrS6tWrbjtttsICQlhz549FSYw2GLs1o3YSyQK1H6tZe/bhsJgMODo6Iinp2eN6+zTwY2fj2RwIUNPqIsTCoWCq7f1ZcCZBP596SprziXzQqfmOGlKP2PqXD0XjCVsP5nEa6+9jo+PT22UVKGb1tlpOFz4DUy54Opn+VxBFri4wO0joIHtv8rYy+fUXuoE+6nVnuuUsVvVdCuxWxUpmy7l2mvTrmWLsVuSVB0OahXP9WmBp7OG8xl6MnTFXPK8k1MdOvJCRBDbLl7l3Z3H2H76EsfiL/HtyYtMOnyOtm3bMXny5PrtvF9ruGMsGIsg83zpwK0wB7IuQGEutH8IQqp+3a0kSVJDJGO3gNjYWPbt28fdd9+Nl5cXCQkJTJ8+nebNm1sMyBpD7JYkVUfnMC8+GNGBNXGXiT2XQbERErq+zN23tWX6+tWsPnCGeUcvAODu6szzL73MjBkzcHNzq9+OKxTQeRx4hMDx1XD1FAggoD20GwGth5YuI0mSZMNk7Bbg7OzM6tWrmTlzJjqdjqCgIAYNGsQ777xjcVqzscRuSVJ1tA50Y/KgNuQXlVBoMOLuqEGr7oHplbeZlHaR9PQMtK7eBAcHV3r3eZ1TKKBlFLToX3okTghw9paDN0mSGg0ZuwV06NCB6Ojom7bTmGK3jHl5FBw/jlNCAobUVDQhIeWWyc3LZ/HKtVzNyKLtbW0YOaQfalUVzsCbjHDlWOkXp5NX6dEPpXUucJfqjquDGleHv39lKJVKvAPD8A4Mq8deVYFCUTp4kyRJamRk7NZfPvjgA3r27Imzs3O1Llb/+eefadOmDY6OjnTo0KHc1AGrV69mwIAB+Pj4oFAoiIuLq3Lb1iCKi8n88T9cev4F0t57H/9f1pD66mtcmTefkvT00mWE4Lk33sEvMIhJTz/OB5NfYsywewkIb82iXzZVvoHEGFg1HtY8D7++Ufrnf/8PLtTzDP6SJEmS1MjI2K2/FBcX88gjj1T5jliA3bt389hjjzF+/HgOHTrEiBEjGDFiBMeOHbPo+913382//vWvKrdrLUII0r/9lqzlyzHpdKgDAzB4e4FaRd6WLaR+8AHG3FyeeuF1Fn74AQFdBnH/+//lia930GfSJ5QotTwzagQ//vpHxRtIjCmNOrpyvPQInFc4OHlD2gnYPF0O5CRJkiSpFsnYrb8SG8quW6vKqeIyn3zyCYMGDeLNN98E4L333mPz5s18/vnnLFy4EIAnnngCuPHp5bpUdOYM+VujUXl4oPLwwCRMoFRS5OyMQutA1rHjXFn+A8u++ZSw/o9zz8NPl86RJ0yEtOlE4Gsfse79Cbz99jsM6/WbxZyAmEyw4yvIzQLPZmBSQJGJ0pijEMi+UPq8T0e4wXWTMopIkiRJkqpOxm5VELt1I82aNWPcuHHma9xiYmIsJuUFGDhwYKWne6vCWrFbebt3Y9TrUfv6YBImhKn0Gr+2ixf/vdCW0hmnE7cuJ3Hr8grbuXD14k3uPjxUyeM/3HCt6kQRVZeMf2lc7KVOsJ9a7aVOsJ9aZZ0ydqtKait262aaN2+Or6+v+d+pqam10u71rBW75b1/P266fAzVTLKoK7cSRVRd9hz/0hjZS51gP7XaS51gP7Xac50ydqsKait262auvU7PmqwVu5WdnUPOmbOo/fxQKBQIk+Bq+lWOjx2HQqnAkJLC0swcPj64nyGzfsLDq/wdfUe3rOLoL1+yZU8cd7S85o7W9HhU6yeBgytoKgg+N+igKBfj0I/Br02F/bPm6VQZ/9K42EudYD+12kudYD+1yjpl7FaVtltbsVvVFRgYaFOxW+5330X+unWInFxUXl6YlKV3E7s4aMFQQgkKJj4/kY/Hj+follX0e/wVi0F5sT6fM3+soXmXPvTt0t7ymjiPrhDaAS4fBHcvy7m4hCidbiQkElp0q9d5uuw5/qUxspc6wX5qtZc6wX5qtec6ZexWNdVW7FZV9OjRo9zRuc2bNzfY2C1tRARugwZiys/HkJqKKCoCoxFjZhYlyck4tm9PxEMP8sykt0iM/pGNX8/iUsJJ8nOyOLVnK2ven4AhP4s5H7xvOYCD0oFZ12fB2Qsyz0FRHphKSv/MPAdOnqXPy4lWJUmSJKlWyNitvyQlJZGZmUlSUhJGo9E8n1uLFi1wdS09Pdi/f38eeOAB8+S+r7zyCr179+bDDz9k6NCh/PTTT+zfv99inruyNpOTk4HS6/eg9CheTY/YVZdCocDnqadQe/uQs2EDJVfT0OTmQqAz7kMG4/3kk6hcXfly3vu4ubnxxYJ5/B67wbx+UMsOfLfoNx6KusEgtWlnGDQH9n4LV06APgNUDtCkC3R9Gpp2qXg9SZIkSZKqT1TT2LFjBaUphEKtVgs/Pz8RFRUlFi1aJIxGo3m5sLAwsWDBgnLrDxw4UAwePFgIIcS2bdvMbZW1Fx4eLt544w2Rn59vXuf65cp+xo4dW6U+m0wmMX36dBEQECAcHBxE//79RXx8/A3ruvZn27ZtFjXNnDnTYr2VK1eKVq1aCa1WK9q1ayc2bNhg8fzixYsrbPf6diqTk5MjAJGTk1PldW7GqNeL3IMHxcZPPhH6lJQKlyksLBRLVq4VcxcuERu2xwqTyVS1xk0mIdLihUjcI0TaqdJ/17Pi4mKxZs0aUVxcXN9dsSpZZ+NjL7XaS51C2E+tsk7rfH9fS8Zu/aUqdVVU0yOPPMIjjzxyw3XGjRvXIDNSlU5OOLZvT2FSEmofnwqXcXBwYOwjw6rfuEIBfq1q2ENJkiRJkipTa9fESZIkSZIkSXVHDuIkSZIkSZJskBzESZIkSZIk2SA5iJMkSZIkSbJBchAnSZIkSZJkg+QgTpIkSZIkyQbJQZwkSZIkSZINkoM4SZIkSZIkGyQHcZIkSZIkSTbolrJTpbpVllaRm5tbq+0aDAb0ej25ubloNJpabbuhsZdaZZ2Nj73Uai91gv3UKuv8+3u7JqlTlZGDOBuQl5cHQEhISD33RJIkSZKk6srLy8PDw6PW21UIaw0PpVpjMplITk7Gzc0NhUJRa+3m5uYSEhLCxYsXcXd3r7V2GyJ7qVXW2fjYS632UifYT62yztIjcHl5eQQHB6NU1v4VbPJInA1QKpU0bdrUau27u7s36g/YteylVlln42MvtdpLnWA/tdp7ndY4AldG3tggSZIkSZJkg+QgTpIkSZIkyQbJQZwdc3BwYObMmTg4ONR3V6zOXmqVdTY+9lKrvdQJ9lOrrNP65I0NkiRJkiRJNkgeiZMkSZIkSbJBchAnSZIkSZJkg+QgTpIkSZIkyQbJQZwkSZIkSZINkoM4G/bFF1/QrFkzHB0d6datG3v37q10+Z9//pk2bdrg6OhIhw4d+PXXXy2eF0IwY8YMgoKCcHJyIioqijNnzlgsk5mZyZgxY3B3d8fT05Px48eTn59f67VdrzZrNRgMTJ48mQ4dOuDi4kJwcDBPPvkkycnJFm00a9YMhUJh8TNnzhyr1FemtvfpuHHjytUwaNAgi2Uawz4FytVZ9jNv3jzzMg19nx4/fpyHHnrI3M+PP/74ltosLCzkhRdewMfHB1dXVx566CGuXLlSm2VVu0/Xqkqds2fP5s4778TNzQ1/f39GjBhBfHy8xTJ9+vQptz8nTpxY26WVU9u1vvvuu+XqaNOmjcUyjWGfVvT5UygUvPDCC+ZlbGGffvvtt9xzzz14eXnh5eVFVFRUueXr7PtUSDbpp59+ElqtVixatEgcP35cTJgwQXh6eoorV65UuPyuXbuESqUSc+fOFSdOnBDvvPOO0Gg04ujRo+Zl5syZIzw8PMSaNWvE4cOHxbBhw0R4eLgoKCgwLzNo0CARGRkp9uzZI3bs2CFatGghHnvsMZuqNTs7W0RFRYkVK1aIU6dOiZiYGNG1a1fRuXNni3bCwsLErFmzREpKivknPz/fZuoUQoixY8eKQYMGWdSQmZlp0U5j2KdCCIsaU1JSxKJFi4RCoRAJCQnmZRr6Pt27d6944403xH/+8x8RGBgoFixYcEttTpw4UYSEhIitW7eK/fv3i+7du4uePXtaq0yr1Dlw4ECxePFicezYMREXFyeGDBkiQkNDLfZX7969xYQJEyz2Z05OjrXKFEJYp9aZM2eKdu3aWdRx9epVi2Uawz5NS0uzqHHz5s0CENu2bTMvYwv7dPTo0eKLL74Qhw4dEidPnhTjxo0THh4e4tKlS+Zl6ur7VA7ibFTXrl3FCy+8YP630WgUwcHBYvbs2RUuP3LkSDF06FCLx7p16yaeffZZIYQQJpNJBAYGinnz5pmfz87OFg4ODuI///mPEEKIEydOCEDs27fPvMxvv/0mFAqFuHz5cq3Vdr3arrUie/fuFYBITEw0PxYWFlbhLyJrsUadY8eOFcOHD7/hNhvzPh0+fLjo16+fxWMNfZ9e60Z9vVmb2dnZQqPRiJ9//tm8zMmTJwUgYmJialDNjVmjzuulpaUJQPzxxx/mx3r37i1eeeWVW+nyLbNGrTNnzhSRkZE3XK+x7tNXXnlFNG/eXJhMJvNjtrZPhRCipKREuLm5iaVLlwoh6vb7VJ5OtUHFxcUcOHCAqKgo82NKpZKoqChiYmIqXCcmJsZieYCBAwealz9//jypqakWy3h4eNCtWzfzMjExMXh6etKlSxfzMlFRUSiVSmJjY2utvmtZo9aK5OTkoFAo8PT0tHh8zpw5+Pj4cPvttzNv3jxKSkpuvZhKWLPO7du34+/vT+vWrXnuuefIyMiwaKMx7tMrV66wYcMGxo8fX+65hrxPa6PNAwcOYDAYLJZp06YNoaGht7zdmvapNuTk5ADg7e1t8fgPP/yAr68v7du3Z+rUqej1+lrb5vWsWeuZM2cIDg4mIiKCMWPGkJSUZH6uMe7T4uJili9fzv/93/+hUCgsnrO1farX6zEYDOb3Zl1+n6qrvKTUYKSnp2M0GgkICLB4PCAggFOnTlW4TmpqaoXLp6ammp8ve6yyZfz9/S2eV6vVeHt7m5epbdao9XqFhYVMnjyZxx57zCK8+OWXX+aOO+7A29ub3bt3M3XqVFJSUvjoo49qWFV51qpz0KBBPPjgg4SHh5OQkMC0adMYPHgwMTExqFSqRrtPly5dipubGw8++KDF4w19n9ZGm6mpqWi12nL/Ians9aoJa9R5PZPJxKRJk7jrrrto3769+fHRo0cTFhZGcHAwR44cYfLkycTHx7N69epa2e71rFVrt27dWLJkCa1btyYlJYV//OMf3HPPPRw7dgw3N7dGuU/XrFlDdnY248aNs3jcFvfp5MmTCQ4ONg/a6vL7VA7iJLtmMBgYOXIkQgi++uori+dee+018987duyIVqvl2WefZfbs2TYTIzNq1Cjz3zt06EDHjh1p3rw527dvp3///vXYM+tatGgRY8aMwdHR0eLxxrBP7dELL7zAsWPH2Llzp8XjzzzzjPnvHTp0ICgoiP79+5OQkEDz5s3rupu3bPDgwea/d+zYkW7duhEWFsbKlSsrPJrcGHz//fcMHjyY4OBgi8dtbZ/OmTOHn376ie3bt5f7fVMX5OlUG+Tr64tKpSp3Z9KVK1cIDAyscJ3AwMBKly/782bLpKWlWTxfUlJCZmbmDbdbU9aotUzZAC4xMZHNmzdbHIWrSLdu3SgpKeHChQvVL+QmrFnntSIiIvD19eXs2bPmNhrTPgXYsWMH8fHxPP300zftS0Pbp7XRZmBgIMXFxWRnZ9fadmvap5p48cUXWb9+Pdu2baNp06aVLtutWzcA8/u7tlm71jKenp60atXK4nPamPZpYmIiW7ZsqfJnFBrmPp0/fz5z5szh999/p2PHjubH6/L7VA7ibJBWq6Vz585s3brV/JjJZGLr1q306NGjwnV69OhhsTzA5s2bzcuHh4cTGBhosUxubi6xsbHmZXr06EF2djYHDhwwLxMdHY3JZDJ/0GqbNWqFvwdwZ86cYcuWLfj4+Ny0L3FxcSiVynKHwGuDteq83qVLl8jIyCAoKMjcRmPZp2W+//57OnfuTGRk5E370tD2aW202blzZzQajcUy8fHxJCUl3fJ2a9qnWyGE4MUXX+SXX34hOjqa8PDwm64TFxcHYH5/1zZr1Xq9/Px8EhISzHU0ln1aZvHixfj7+zN06NCbLttQ9+ncuXN577332Lhxo8V1bVDH36dVvgVCalB++ukn4eDgIJYsWSJOnDghnnnmGeHp6SlSU1OFEEI88cQTYsqUKebld+3aJdRqtZg/f744efKkmDlzZoVTjHh6eoq1a9eKI0eOiOHDh1d4S/Ttt98uYmNjxc6dO0XLli3rZDqK2qy1uLhYDBs2TDRt2lTExcVZ3MpeVFQkhBBi9+7dYsGCBSIuLk4kJCSI5cuXCz8/P/Hkk0/aTJ15eXnijTfeEDExMeL8+fNiy5Yt4o477hAtW7YUhYWF5nYawz4tk5OTI5ydncVXX31Vbpu2sE+LiorEoUOHxKFDh0RQUJB44403xKFDh8SZM2eq3KYQpdNRhIaGiujoaLF//37Ro0cP0aNHD5uq87nnnhMeHh5i+/btFp9RvV4vhBDi7NmzYtasWWL//v3i/PnzYu3atSIiIkL06tXLanVaq9bXX39dbN++XZw/f17s2rVLREVFCV9fX5GWlmZepjHsUyFK7/wMDQ0VkydPLrdNW9mnc+bMEVqtVvz3v/+1eG/m5eVZLFMX36dyEGfDPvvsMxEaGiq0Wq3o2rWr2LNnj/m53r17i7Fjx1osv3LlStGqVSuh1WpFu3btxIYNGyyeN5lMYvr06SIgIEA4ODiI/v37i/j4eItlMjIyxGOPPSZcXV2Fu7u7eOqppyzeuNZSm7WeP39eABX+lM1XdODAAdGtWzfh4eEhHB0dxW233Sb++c9/Wgx+Gnqder1eDBgwQPj5+QmNRiPCwsLEhAkTLL7shWgc+7TM119/LZycnER2dna552xhn97ovdm7d+8qtymEEAUFBeL5558XXl5ewtnZWTzwwAMiJSXFmmXWep03+owuXrxYCCFEUlKS6NWrl/D29hYODg6iRYsW4s0337T6nGLWqPXRRx8VQUFBQqvViiZNmohHH31UnD171mKbjWGfCiHEpk2bBFDuu0UI29mnYWFhFdY6c+ZM8zJ19X2qEEKIqh+3kyRJkiRJkhoCeU2cJEmSJEmSDZKDOEmSJEmSJBskB3GSJEmSJEk2SA7iJEmSJEmSbJAcxEmSJEmSJNkgOYiTJEmSJEmyQXIQJ0mSJEmSZIPkIE6SJEmSJMkGyUGcJEmSJEmSDZKDOEmSJEmSJBskB3GSJEmSJEk2SA7iJEmSJEmSbND/A6HdCGTGqxIRAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -205,7 +352,7 @@
     }
    ],
    "source": [
-    "HLAfreq.plotAFprob(caf, afloc, alleles=['DRB1*09:01', 'DRB1*15:02', 'DRB1*07:01', 'DRB1*12:02',])"
+    "HLAfreq.plotAF(caf, afloc, credible_interval=0.95)"
    ]
   },
   {
@@ -219,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
index d10356b..dbb44c7 100644
--- a/examples/working_with_priors.ipynb
+++ b/examples/working_with_priors.ipynb
@@ -55,14 +55,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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WIHH3uZ4eXiGhGEjCRdgmJFFRUZiy+F9Yt78MsqgoREVF4b4XPsIX+0phYEKHctu2bQteQwkhVzx3ccjdFRJ3n7PfhK+thIRiIAkXYZ0uW5rm1IuaBrXSaq2EkHDje5dNDADgTI0GViutL0LCX3gnJE0noZBPSGwj1JuPISGEkFBltTK+y8bbhCQzIRpiIQedyYIKlT4QzSOkQ4VtQqLT6fDpU1NRvuoRWEwGaDQaPHvX1Sh9+w+ob2h0KJebm4vc3FzodLogtpi0ZefOnRAKhSgoKHD6fmFhIQoLC1ttv3DhAgoKChAdHY3k5GT89a9/dZhNUFFRgT/84Q/o1asXBAIBHnvsMY/ao9frMXfuXHTu3BmxsbG48847UVVV5VDm0UcfxdChQyGVSpGbm+vpoZIrjKs4VKM2wGC2QijgkBbfetEyjUaDpKQkJCUlOSwdDwBioQBZnW1XSdwtIU8xkISLsE1IrFYr6i6cgKn6LASwXSlRK+th1amgNpgcyh08eBAHDx6E1Wp1VR0JAStXrsQjjzyCn3/+GeXl5fz2ZcuWobHxcpLZ2NiIZcuWAQAsFgsKCgpgNBqxY8cOfPzxxygsLMSiRYv48gaDAUlJSXj22WcxaNAgj9vz+OOP45tvvsG6deuwfft2lJeX44477mhV7o9//COmTJnipAZCbFzFIXt3TZpCBrHQeTiura1FbW2t0/fs3TbuxpFQDCThImwHtcpkMtz813ex//ylVsshN1+HRCaT4fvvv+efk9CkVqvxxRdfYN++faisrERhYSH+7//+DwDQqVMnjBs3DgMGDAAArFixAg899BAA4Pvvv0dJSQl++OEHpKSkIDc3Fy+88AKeeuop/O1vf4NEIkG3bt3w1ltvAQA++ugjj9qjVCqxcuVKfPbZZ7jxxhsBAKtWrULfvn2xa9cuXH311QCAt99+GwBQU1ODQ4cO+e8PQiKKqzjEz7Dp5F13jZ1tYGuV24SEYiAJF2F7hUQoFCKt3whEZQ+GuMW8+uaDWoVCIcaNG4dx48ZBKHS9vDIJrrVr16JPnz7o3bs37rvvPnz00Uf8jcBmzpyJtWvXYuPGjdi4cSPWrl2LmTNnArB181x11VVISUnh6xo/fjxUKhWKi4s93v+2bdvAcRzOnTsHANi/fz9MJhPGjh3Ll+nTpw+6du2KnTt3tv+AyRXFVRyyr9KamRDlU732mTbubrJ3JcTAQHX3fvXVVxg3bhySkpIgl8uRn5+P7777rs321NfXY9q0aZDL5YiPj8fs2bOhVl/+jvR6PWbOnImrrroKIpEIkydP9vqYI5FXCcnSpUsxfPhwxMXFITk5GZMnT8bx48cdynjS7+4v9lk2whZLx2uMNKg13KxcuRL33XcfAGDChAlQKpXYvn07AGD16tW45557UFBQgIKCAtxzzz1YvXo1AKCystIhGQHAv66srPR4/9HR0ejduzfEYjH/WYlEgvj4+FZ1e1MvIe6UXmrnFRJ+LZIre/n4QHX3/vzzzxg3bhy+/fZb7N+/HzfccAMmTpyIAwcOuG3PtGnTUFxcjC1btmDjxo34+eef8eCDD/LvWywWREVF4dFHH3X40XOl8yoh2b59O+bOnYtdu3Zhy5YtMJlMuOmmmxwGW3na795eZrMZ54t+hfb0XsDquHR8Y4ul4zdt2oRNmzbRsskh6vjx49izZw/uvfdeAIBIJMKUKVOwcuVKAEB1dTW2bNmCUaNGYdSoUdiyZQuqq6v92oYRI0bg2LFjyMjI8Gu9hACu45C7RdE8YR9DUtNogFJnclom0mOgvbv34YcfRkFBgcOVEHt376+//opff/0V48aNQ6dOnQBc7u5dvXo1cnNzcfPNN+OFF17A8uXLYTQaAQBvvvkmnnzySQwfPhw5OTl4+eWXkZOTg2+++cZle44ePYrNmzfjX//6F/Ly8nDttdfinXfewZo1a/hkKSYmBu+99x7mzJmD1NTUwP1xwoxXY0g2b97s8LqwsBDJycnYv38/rrvuOo/73f3BYDBg29t/AQBYF0xzeE9tMMNqZRAIOBgMBtx666227bRsckhauXIlzGYz0tPT+W2MMUilUrz77rtYsGCBQ/m4uDh+W2pqKvbs2ePwvv2KXHtO9NTUVBiNRjQ0NDhcJamqqqIAQrzmKg6VXWpfl02cTIwUuRRVKgPO1KgxuGsnj/cdKVp29z722GNYuHAhOI7DzJkzceONN2LEiBEAgD179qBr164AXHf3PvzwwyguLsbgwYNb7ctqtaKxsREJCQn8tsLCQsyaNYvvYt65cyfi4+MxbNgwvszYsWMhEAiwe/du3H777QH5O0SCdo0hUSqVAMB/Ob70uxsMBqhUKoeHRw0XCNApqw8kqTkQCQUQCAQYMnQYJKk5YOCgNVn4csOGDcOwYcNo2eQQZDab8cknn+CNN95AUVER/zh48CDS09Px+eef82VnzpzJjx2xy8/Px+HDhx2umGzZsgVyuRz9+vXzuV1Dhw6FWCzG1q1b+W3Hjx/HhQsXkJ+f73O95MrkLA6ZLFZUKJsSEhddNp7Er8srtjrvton0GNiR3b2vv/461Go1f28gAFAoFOjduzf/urKyEsnJyQ6fE4lESEhIoO7eNvicKlutVjz22GMYOXIkP/vBl373pUuXYsmSJV7vPyoqCjc+tRL7zl9CTHQ0oqKisG/vHuQ88z+YrQyNehNipSJERUVh7969XtdPOsbGjRtx6dIlzJ49GwqFwuG9O++8EytXruRn1Dhz0003oV+/frj//vvx6quvorKyEs8++yzmzp0LqVTKlysqKgJg+4VYU1ODoqIiSCQSPmnZs2cPpk+fjq1btyIjIwMKhQKzZ8/GggULkJCQALlcjkceeQT5+fkOV/pOnToFtVqNyspK6HQ6fj/9+vWDRCLx01+JhDtncaiiQQ8rA6QiAZLipB5/rqUeSbHYcbrO5UybSI6B9u7e9evXA3Ds7h09ejTf3fuf//wHgK0L5sMPP/RpX5999hmWLFmCr7/+2iHhuP322+mqh5/4nJDMnTsXR44cwa+//tquBixcuNDhkrxKpUJmZqZHnzU3rdQq4GyDWjmOQ5xMhEtak23qr8Ldp0koWLlyJcaOHdsqGQFsCcmrr76KQ4cOYeDAgU4/LxQKsXHjRjz88MPIz89HTEwMZsyYgeeff96hXPPLr/v378dnn32GrKwsflaNVqvF8ePHYTJd7odftmwZBAIB7rzzThgMBowfPx7//Oc/Hep94IEH+F9jzfdz9uxZdOvWzau/Bbmy2Ae0ZnSKAsdxbZR2jV+LxM1Mm0jVUd29a9aswQMPPIB169a1OQg1NTW11Rg3s9mM+vp66u5tg08Jybx58/iRw126dOG3+9LvLpVKHX7JesNqv5eN8PLJHNuUkKjofjZhwd3gsBEjRvD9su5kZWXh22+/dVumrXpGjx7dqoxMJsPy5cuxfPlyl5+jm5b5x9/+9rdWV0p79+6NY8eOBalFgdfeNUjsenh4199I07y796abbnJ4b/Lkyfj888/5q6stu3oBW3fvSy+9hOrqav6Kh7Pu3s8//xx//OMfsWbNGpfTilvW29DQgP3792Po0KEAgB9//BFWqxV5eXm+Hu4VwasORcYY5s2bh/Xr1+PHH39Edna2w/sd2e+u0+nwyz8eRuXqv8Jk0EOr1aJbt27Y/8o0WE16NOpNfLmRI0di5MiRtGwyISGsf//+qKio4B/tvfoaSpzFIX7Kr5sBrfa41q1bN2i1Wqdl7GNIztdpYbK0Xok1UmNg8+7eAQMGODzs3b3uNO/uPXjwIL777rtW3b2fffYZpk+fjjfeeAN5eXmorKxEZWUlP34SANavX48+ffrwr/v27YsJEyZgzpw52LNnD3777TfMmzcPU6dOdbiSU1JSgqKiItTX10OpVPLj565ozAsPP/wwUygUbNu2bayiooJ/aLVavsxDDz3Eunbtyn788Ue2b98+lp+fz/Lz8z3eh1KpZACYUql0W06tVjMADAD7vuicw+vMx79k3xy82KqcWq325nAJuWJ5eh76y+LFi9mgQYPaVUdHt9kbzuLQI5/9zrKe2shWbDvl1edaslisrO9z/2NZT21kJ6safaojHN16663slltucfre7t27GQB28OBBt3WcO3eO3XzzzSwqKoolJiayv/zlL8xkMvHvX3/99fzfrvljxowZfJlVq1axlv+U1tXVsXvvvZfFxsYyuVzOZs2axRobHb+brKwsp3WHs/aeg1512bz33nsAbJe3m1u1ahV/ScyTfnd/kEqlGDjzBVQo9U6XQ7avRSKVSvkBT752DRFCAu/kyZNIT0+HTCZDfn4+li5dyk/RdMZgMMBgMPCvPZ2hFwzO4tDlKyTt67IRCDh0T4rBkYsqnK5Ro2dTF467fUeCjuju9aRL1tnsv4SEBHz22WduP2cfv0Yu8yoh8eQL9qTf3R9EIhE6978WyloNpBJxq/ft97OhZXkJCX15eXkoLCxE7969UVFRgSVLlmDUqFE4cuQI4uLinH7G1xl6weAsDvHLxrdzDAkA9EyK5RMST/ZNSCgK60np9lk2LZeOB8CPISGEhL6bb74Zd999NwYOHIjx48fj22+/RUNDA9auXevyMwsXLoRSqeQfpaWlHdji9tGbLKhV267udOnk26JozfFrkVRf2UvIk/AWtkv2WSwW1J86AL3aALDWK8DaZ9lYLBb88ssvAIBRo0ZF7M2lCIkk8fHx6NWrF06dOuWyTHtm6HW0lnGorKm7JlYqQnx06yu83nI304ZiIAkXYZuQ6PV6FH9oWzresmQGAMdxJGqDmS93ww032Lap1YiJienQdhJCvKdWq3H69Gncf//9wW6KX7SMQ/bumi7tXIPE7vJqrWowxhzqpBhIwkXYJiQcx0GWnAWLhUEoEIDjOPTr1892gynucpeNfbv9OSEk9DzxxBOYOHEisrKyUF5ejsWLF0MoFPI3XAx3LeOQpwNaPY1fWZ2jIeBsg/lr1AYkx13+gUYxkISLsE1IoqOj0Xfeh6jXGBEXG4Po6GgUFxfj66KLmL+miJ9lY99OCAldZWVluPfee1FXV4ekpCRce+212LVrF5KSkoLdNL9oGYc8XRTN0/glEwuRmRCN83VanK7WOCQkFANJuAjbhAQALC2WjgeAOJntkFQ0qJWQsLFmzZpgN6FD8TNsfLzLrzM9kmJtCUmNGvk9OvutXkI6SljPsrEnJKJms2w6RdtuaHZJQwkJISQ0nauzzYbp1tl/4zns97Q5WdXotzoJ6Uhhm5DodDqc/fdCVK15ll86vn///phy00hYTXrUa4x8uXHjxmHcuHERtWwyISR8NI9DGo32ckKS6D4hsce1/v37u1w63q5vmhwAcLTCMSGhGEjCRdh22VitVmjPHgAAcGBgjKGkpAQAkHkLoDNZoDNaYLVa8cMPP/CfIYSQjtY8DlUpddCbrBAKuDbXIGke19pamLJfui0hKalQwWplEDRdOaYYSMJF2CYkUqkUSROfgJUxREU5TvmVCAUwA6jTGJAaJ8Xq1av5zxBCSEeTSi/HoYuNtgH3XTpFQSz030XqHkmxkAgFUBvMKLukQ9fO0a32TTGQhLKwTUiEQiGi+40GgKal4838e51ixKjR28aRdOkUjWnTpgWnkYQQAtvy7fY49PmeCwD8O34EAMRCAXql2paQL6lQ8glJ830TEsrCdgyJtdnVS2GLufX2ga11GgMIISSUnKu1jR/JbmP8iC/6pjZ125SH7o0GCXElbK+QGEwmGCpONL0a4/BeQowEqDehXmOExWLB77//DgAYMmQILZtMCOlwzePQmRrbOI5undt/U72W+qXLgf1ASbOBrRQDSbgI24REq9Wj8pMFAADTsj9CIr18KLYrJBrUa4zQ6/UYMWIEAFo2mRASHM3j0I1LNwNoe4aNL/rxM20uXyGhGEjCRdgmJBbGIJQnAwBEQtvS8VlZWQCAhFhbl029xuiwnZZNJoQEQ/M4dOGSFuAkHo0h8TZ+9W2aaXOxQYcGrRHx0RKKgSRshG1CIpNFo8vDHwEA4mJjIBYKcO7cOQDAO1tPAqhCndqI6OhofjshhASDPQ5dbNBh5Cs/QuTBlN/mn/OUXCZG14RoXKjX4lCZEtf1SqIYSMJG2A5qNTebT99yUGuy3Da1rapR36FtIoQQd+yrqGYnxkDkxym/zeVmxgMAikobAlI/IYEStgmJpWmRII4DvwCQXYrcti5JpZISEkJI6DhZpQYA9EqJC9g+hnSNBwD8fuFSwPZBSCCEbUKi0epQ/dWLqPnqRej1euh0OgwfPhzDhw+HQmxLVqpUeuj1ekyePBmTJ0+GXk8JCiGk49nj0Kt/mQ1mNqJncqxHn2se1zxd9n1w104AgAMXGsAYoxhIwkbYjiExmczQndwFwDatDQD27dsHAEhqGtR6SWuCRm/E119/7VCOEEI6ksVi4eNQ5qh5Hl8hsVqtfFzzdNn3vmlySEUCKHUmnK3VICWaoxhIwkLYJiQCkRgJ4+dBKhJAIpHAaDTy78VHiyERCWA0W6E0MHzwwQcAAIlEEqzmEkKuYBKJBO+//z7+9t9icEIReqV4doXEp32JBLgqQ4F95y/hwIUG3DYwhWIgCQvhm5AIRYjLnYA4mQhisdghIeE4DqlyGS7Ua1Gns2DOnDlBbCkh5EonFotxy9334eUzP0Es5AKyBklzQ7I6Yd/5S9h/4RLuHNqFYiAJC2E7hsTStHa8SOB8Xn0qDWwlhIQQ+4DW7MQYv95Uz5nh3RIAADtP1wV0P4T4U9heITFZLDDWnIcxWuy0bzVFYUtILl7SoLi4GADQt29fCARhm4MRQsKU1WrFDzv2wVhzHr2vygv4/vK6J0DAAWdrNSit10BVcQ4AxUAS2sI2IVFrtKj4aC4qAOhe+UOr97MSbPeJOF1Rj4dvuNr2GVo2mRASBDqdDi/PLgAA9L7ncMD3J5eJMbBLPIpKG/BTcRlmXDcAAMVAEtrCNiGxMgZBlByCZouiJSYm8s+zmm5cVVqvc9hOCCHBIIpRwGplthvgecHX+HVtz0QUlTZg9+k6ioEkLIRtQiKRRSPz0c+QmRDFZ/w1NTX8+90SDQCAMrXVYTshhHQ0A8TImPcpAGBYTprHn4uJifE5fl3TszPe/ekUdpVqUFlVDaGL8XaEhIqw7Uy0Ng1qbblsvJ39Ckl5gw4GM829J4QEz+GLSgC2Aa1ymbhD9jm8WwLkMhHqNEZatZWEhbBNSMz2hMRF1p8UK0W0RAgrA8ouebbCISGEBML+c/UAgEFdFB22T7FQgDF9UwAA3x2p7LD9EuKrsE1IdDodar55DSWfvcQvHT969GiMHj0aOp0OHMchOzEGzGzEnFnTMW3aNFo2mRASFDtOVKDmm9ewt3CJV3GoZVzz1vj+KWBmI95+7lGKgSTkhe0YEqPJDG3JdmhxeTnk7du3A7i8xHK/NDkOn6vGT5vWAwC/WiEhhHQUg9mCoguXoC3Zjh0l3i3fbrVaW8U1b1zXKwlSIXChaCs+K6IYSEJb2CYkApEYnW6cgzSFrNXS8Xb90+XghCLk3fs4po7oSssmE0I63MFSJUxMgC43P4wF43I6NA5FS0S4eWAX1N44B4O7xlMMJCEtbBMSTiCCfPgk9MyMb7V0vF3/DAU4oQgYUIDHHhsThFYSQq50P5+oAScU4bb7HsDjfxjS4fv/Q353fH14EiolQhitHDpmSC0h3gvbMSQW5n7peMB210uOAypVelSpqO+UENLxtpRUAQDG9k0Oyv5HZCcgOzEGGqMFX+4vC0obCPFE2CYkJrMFZmUV9PWVLvtWY6UiDEiLg1lZha+2H/CpD5YQQnx1oU6L41WNEHAMPWRanDt3rsPjEGMME7uLYFZW4b2fTtIyCCRkhW1CotPpcHHFbHz77J1uR5/ndY3FxRWz8efbrvFplDohhPhq0+EKAMCQ9GgM6tcb2dnZHR6HdDod/nLnKFxcMRvldSqs3VvaofsnxFNhm5BYrAycWAqhRMZvi46ORnR0tEO5/B6dwYmlEIilMFnoCgkhpGMwxrB2n+0f/4mD0p3GJ0/4+rmWdUhkUQCA1747jppGQ7vqIyQQwjYhEUuj0HXBfzDtve2IiYlBTEwMNBoNNBqNw82jru+XiSGLNiJzwX+wp1QTxBYTQq4k20/U4GytBjESIe7K6+k0PrXFVVzzBl+HWo2B2clQ6c14dsNhsKZxeISEirBNSCxtrNRqJxIKcMeQDADAv3edD3i7CCGEMYY3fzgJAJg6oitipMGf0CgSCrD09oEQCzl8V1yFd388FewmEeIgfBMS5llCAgD35WVBLOTwy8labD9BN9ojhATWmr2lKCptgEwswJ+u7x7s5vCu6qLA85MGAADe2HICb/1wkq6UkJARsIRk+fLl6NatG2QyGfLy8rBnzx6/1q/T61H3v7fx60cvwWAwQK/Xo6CgAAUFBQ7LIxsMBrzw9HzI930EZjbhL2sP4nwddd0QEooCHTc6wp6z9fjbf4sBAE/c1BvJcTIYDAbMmTMHc+bMgcHg+fgNV3HNGy33fe+Irpg/JgcAsOyHE5j+0R6crGr0qW5C/IljAUiPv/jiC0yfPh0rVqxAXl4e3nzzTaxbtw7Hjx9HcrL7ufgqlQoKhQJKpRJyudxluQ+2luBPY/sDANRqNQAgNjaWf23vb9VoNPz2Ma9sxqlLZiiixHjkxp64LTcdyXEyJ7UTcmXz9Dz0p/bEDSA4bW6uptGAz/dcwLs/nYLRbMWNfZLx4fRhEAo4hzjUPD61xdfPeVLHp7vP4/lvSmAw2wb7j8pJxE39UzGkazx6JsdCKhJ6vS9yZWvvORiQhCQvLw/Dhw/Hu+++C8B2D4bMzEw88sgjePrppx3KGgwGh18MKpUKmZmZbR7Q+z8dx9OLX0KftDhs//cymEwmpyed0WjEa6+9BgCY8adH8Oc1h3CoTMnXkyKXIiM+CnEyMWKlIoiFHDiOA8cBAo6DgAM42F5zbfcOERIA/v0fLy87AZMHZ7gtE4x/3L2JG4DvsePlb49CpTOBMYCBwcrAPwcDrIyBwb7N9hr2slbbf+3vMcZgMFtxoV6LC/Va2KPpuH4peGtqLqIltrEjzePQX//6V4+XcPdHQuJu36dr1Hht83FsLna8G7CAAzrHSpEYK0V8lBhSsQASoQASke2/XFMwtMdE+/+hXFO8dHiP/9+XAmi4+8tNvZAYK3X5fnvjht9HWhmNRuzfvx8LFy7ktwkEAowdOxY7d+5sVX7p0qVYsmSJ1/sRCMVQXDMF+YMzIJFIYDKZnJaTSCR45pln+NdfPXwNvthXirV7S3GwTIkqlQFVKpoCR64cHIc2E5KO5m3cAHyPHesPXAzYtNerMhSYc113TByYxv+jDbSOQx3J3b57JMVixf1Dca5Wg/8dqcTPJ2pQUqGCUmdCTaOBpgcTB3+6rrvbhKS9/J6Q1NbWwmKxICUlxWF7SkoKjh071qr8woULsWDBAv61/VdOW4Z264QnbuqFXilxXrVPJBRgWl4WpuVlQaU34VS1GtUqA9QGM9R6E8xW268fK7P9crIyBsYYaNwXiRQDMhTBbkIr3sYNwPfY8dD1PaAzmvmEQdB0RZRr9hwAOP4K6eXn4Lim101lYYspXTpFoXtSTNh2AXdLjMHDo3vg4dE9wBizJSNqA2rVRih1JhjNVhjMFhjNVpgsVv4KEQA+NtqvHDVnvwBP8TMyxEcH9k5IQZ+LJpVKIZV6n3ENzoxHZpQZANyOEmeMoba2FgCQmJjo8KtFLhNjSNdOXu+bEBJ8vsaO2ddmB6A17rmLQ6G2b47jkCyXIVkenskVCV9+T0gSExMhFApRVVXlsL2qqgqpqal+249Wq+UHutkHtXpSztfFhQghgdNRcSNYghmHKAaScOH3hEQikWDo0KHYunUrJk+eDMA2OG3r1q2YN29em5+3X+1QqVRuy2k0l6futiyrUqlgsViclrNvJ4S4Zj+nOmqNivbGDcDz2BEMvsYhf8QvioGko7Q7brAAWLNmDZNKpaywsJCVlJSwBx98kMXHx7PKyso2P1taWsrQNICdHvSgR3AfpaWlgQgRTrUnbjBGsYMe9AiVh69xIyBjSKZMmYKamhosWrQIlZWVyM3NxebNm1sNWHMmPT0dpaWliIuLa7Ov0z6IrbS0NCjrDvgTHUtoiqRjATw/HsYYGhsbkZ6e3mFta0/cADyPHZH0nUbSsQCRdTxX4rG0N24EZB2SjhLshZD8iY4lNEXSsQCRdzy+iKS/QSQdCxBZx0PH4r2wvZcNIYQQQiIHJSSEEEIICbqwTkikUikWL17s01oEoYaOJTRF0rEAkXc8voikv0EkHQsQWcdDx+K9sB5DQgghhJDIENZXSAghhBASGSghIYQQQkjQUUJCCCGEkKCjhIQQQgghQUcJCSGEEEKCjhISQgghhAQdJSSEEEIICTpKSAghhBASdJSQEEIIISToKCEhhBBCSNBRQkIIIYSQoKOEhBBCCCFBRwkJIYQQQoKOEhJCCCGEBJ0o2A1oyWq1ory8HHFxceA4LtjNIeSKxBhDY2Mj0tPTIRCEx+8Wih2EBFd740bIJSTl5eXIzMwMdjMIIQBKS0vRpUuXYDfDIxQ7CAkNvsaNkEtI4uLiANgOSC6XB2QfW0oq8cr/jqFSqYdVrwIApCUnYeEtfTGuX2pA9klIOFGpVMjMzOTPx3DQEbHDjmIIIa21N26EXEJiv9Qql8vbFVQ0Gg3i4+MBAA0NDYiJiQEAbD5SgSc2nASDEJxAiPL35wAARI9/iSc2nMR7sXGYMCDNqzoJiVTh1PXhr9gBuD/XKYYQ4p6vcSM8Ood9ZDabYTab+dcWK8OSb0rAnJS1b1vyTQksVmclnNdJCIlMzs51iiGEBE7IXSHxl6ioKJSVlfHPAWDP2XpUKPUuP8MAVCj12HO2Hvk9OntUJyEk8rg61ymGEBI4EZuQCAQCZGRkOGyrbnQdSDwp56xOQkjkcXWuUwwhJHAiusumpeQ4mV/LEUKuLBRDCAmciL1CYjQa8dZbbwEA5s+fD4lEghHZCUhTyFCp1DvtA+YApCpkGJGd4HGdhJDI4+pcpxhCSOBwjDHXo6+CQKVSQaFQQKlUtnuWTWxsLABArVY7zLJ5ePXvAACLUY/SZXcBALo+/iUEEhneu2+I2xHyzuokJNL46zzsSP5ss7tzffORCjzUFEOsFEMI4bX3HIzYKyQikQgzZszgn9tNGJCG9+4bgiXflKC8zoSYAWMAAKmdorHk9lyXgcRdnYSQyOLuXJ8wIA0FV6Vi0+FKcAIhxRBC/CRir5C0xWJl2HO2HtWNeiTH2S6xCgXhs+YCIYF0pV8hacut7/yCIxdV/Ovp+VlYPLE/xRByRaMrJD4SCjin0/IIIcQdld6EknJbMjL72mys/PUsztdpKRkhpJ2uqFk2LTHGoNFooNFoEGIXigghIerAhQZYGdCtczRuH5wOq1GPvScrYLFYg900QsJaxCYk9iWa4+PjodFonJbRarWIjY1FbGwstFqtX+okhIQ/d+f6qWo1AKBfuhyZcUKULrsLR1+ZjGNlte2ql5ArXUR32SiVyrCokxASelyd66drbAlJj6RYiISXf9MVV6jQPyvZ53oJudJFbEISFRWFEydO8M9DtU5CSOhxd67br5D0SIp12H68UoW2UAwhxLWITUgEAgFycnJcvl9ar8W/fz3h1zoJIZHB3bl+psZ5QnK2tu0uGIohhLgWsQmJO0azFdP+tRvnKuuD3RRCSBhRak2oVRsBANlJMYDZwL93robGhBDSHhGbkJhMJnzwwQcAgAcffBBisZh/78djVbhQ3/YgVm/qJIREDlfnelmDLW50jpEgViqCpllCcr5eC7PF6jCuxNN6CSERnJAYjUbMmzcPADBz5kyHE//nk7bR8FFiod/qJIREDlfnekWD7S6+afGtb55nsjCUXdKhW6Lr5eAphhDiWsQmJEKhEHfddRf/vLnfz18CAMwf2xt//XokOA4wWBjauquEuzoJIZHD1bleodQBANIUUQ7lfjlZC04gwOkatduEhGIIIa5FbEIik8mwbt26VtvVBjOOVzUCAO6+ujtWz1iCcqUeR6v1GCmPbVXekzoJIZHF1blerrRdIUlXyBzKPfTv/dhcXImySzqf6iWERPDCaK6cqVGDMSA5ToqkOCkGdokHABytaHvKHiHkylbR0HSFJN5xym6XTrbXZZe8H5tGCLG54hIS+9Q8+2XVPmlxAIBjlY1BaxMhJDzYr5CkKRzHkFxOSNxfISGEuBaxCYlWq0VGRgYyMjIcloU/0zQ1r3tiDDQaDR4f1xvn/34rjpyv8rlOQkhkcXWu28eQpDddIdFoNOA4DrOu7Q6rUY/SNq6QUAwhxLWIHUPCGEN5eTn/3M5+hSS7xcCzU9WaNqfsuaqTEBJZnJ3rjDFUq2zTfFPiWs+yAdq+QkIxhBDXIjYhkclkOHDgAP/czlVCYjRbcaFei+5Jrge2uqqTEBJZnJ3rWqMFBrPtjr4JsRKnn2vQmtCoNyFO5nw6L8UQQlyL2IREKBQiNze31fbzdY5jSBzeayMhcVUnISSyODvX6zW2FVolIgFiJK2n7CqixWg0AxcbdOiT6jwhoRhCiGsRO4bEGa3RDJXeDKD1oDQAOO/BvSgIIVcme0LSOUYCjuNavZ/RtFhaaT0NbCXEFxF7hcRkMuHTTz8FAEybNg1isRiVTSPkY6UixMnE0DQFGLvzbSwn76xOQkjkcXau2xOShBjn3TVd4qNxrFbpduovxRBCXIvYhMRoNGLWrFkAgLvvvtshIUmRS51+5nyd+4TEWZ2EkMjj7FyvayMhSY+XAVC6HdhKMYQQ1yI2IREKhbjlllv45wBQwa8hEOVQ5pLGiIsCAc7Vue+ycVYnISTyODvX6zW2GTadmyUkzct1SYgFUIXyBtcJCcUQQlyL2IREJpNh06ZNDtsqVbaEJLXZss+bNm3CxQYdRr7yI0rrtbBYGYSC1v3DruokhEQeZ+f65SskUqflvi+uBGAb1OpNvYQQmytqUKu9yyZV7jigNU0ug0QogMnC3P66IYRcuerVTYNaXUz5tS+WRjGEEN9cUQmJvcsmtcUMG4GAa+r/df/rhhBy5WprUGtGU0JSqzZCb7J0WLsIiRQRm5BotVrk5OQgJyeHX6K5Vm3rA06Ks11y1Wg0iImJQUxMDFKibZ9z9+vGWZ2EkMjj7Fx3Nqi1eQwRMyOim9YncRVHKIYQ4lrEJiSMMZw6dQqnTp3il2huvo6AnVarhVar5Qe6XnQzQt5ZnYSQtv3888+YOHEi0tPTwXEcNmzY4PA+YwyLFi1CWloaoqKiMHbsWJw8eTI4jYXn8QO4HEM4jmvWbaP3uF5CiE1ED2r99ddf+eeA+0uu6faEpI0BaS3rJIS0TaPRYNCgQfjjH/+IO+64o9X7r776Kt5++218/PHHyM7OxnPPPYfx48ejpKQkKOeat/HDLiM+Cqeq1S6vkFAMIcS1iE1IhEIhRo4cyb82mC1QG2yrtHaOab0OSXqnthOSlnUSQjxz88034+abb3b6HmMMb775Jp599llMmjQJAPDJJ58gJSUFGzZswNSpUzuyqQC8jx929iskZS7iCMUQQlyL2C6bluy/bkQCDvKo1nlYmsIWZNx12RBC/O/s2bOorKzE2LFj+W0KhQJ5eXnYuXOny88ZDAaoVCqHR6C0FT/s7MvH00wbQrwXsQmJ2WzGunXrsG7dOpjNZtQ1Tdnr5Oo+FArbqNaLDTqXfbst6ySEtF9lpW39jpSUFIftKSkp/HvOLF26FAqFgn9kZmb6rU3exg+7jE7ux6JRDCHEtYjtsjEYDLjnnnsAAGq1mh8h33JAml2KQgaOAwxmK+o0RiTGtr4s27JOkShi/3yEhLyFCxdiwYIF/GuVSuW3pKTlue5qQGtL9rFo5UrnCQnFEEJci9izQSAQ4Prrr+ef25d9bj4grXkZmUSElDgZKlV6XLykc5qQtKyTENJ+qampAICqqiqkpaXx26uqqpCbm+vyc1KpFFKp6/Ec7dE6fjgf0NqynP0KSUWDHlYrg6DFqs8UQwhxLWITkqioKGzbto1/bb/k2jygtCyT0SnKlpA06DAoM77NOgkh7ZednY3U1FRs3bqVT0BUKhV2796Nhx9+OChtahU/XCQkLculSKwQcIDRYkWt2oDkFqtCUwwhxLWITUhasv/CcXblwy49Pgr7z1+iga2E+JlarcapU6f412fPnkVRURESEhLQtWtXPPbYY3jxxReRk5PDT/tNT0/H5MmTg9foZpzdWM8ZsVCAFLkMFUrbD5uWCQkhxLUrLiFpaw0BgJaPJ8Tf9u3bhxtuuIF/bR/7MWPGDBQWFuLJJ5+ERqPBgw8+iIaGBlx77bXYvHlzyKzVUa8xAXC8sZ4rGfFRqFDqUd6gx+CugW4ZIZHD607McFlxUafTITc3F7m5udDpdC6XfU5KSkJSUhI0Gs3lEfIuEpKWdRJCPDN69Ggwxlo9CgsLAQAcx+H5559HZWUl9Ho9fvjhB/Tq1Sto7W15rvNj0FrcWK9lDAEur0VysaH10vAUQwhxzeuExL7i4vLly52+b19xccWKFdi9ezdiYmIwfvx46PXOl1IOFKvVioMHD+LgwYOwWq0uR8nX1taitrYWANAl3v2UvZZ1EkIik6v4kRDd+gpr8xgCXJ7662z5eIohgbFz504IhUIUFBQ4fb+wsJBPfpu7cOECCgoKEB0djeTkZPz1r391mI791VdfYdy4cUhKSoJcLkd+fj6+++47t205d+4cZs+ejezsbERFRaFHjx5YvHgxjEYjX2bbtm2YNGkS0tLSEBMTg9zcXHz66ae+HXwE8brLxt8rLhoMBhgMBv61vxY3kslk+P777/nnHnXZtHGFpGWdhJDI1PJcdzWo1Rl+tVYnP2wohgTGypUr8cgjj2DlypUoLy9Heno6AGDZsmV44IEH+HKNjY3417/+hccffxwWiwUFBQVITU3Fjh07UFFRgenTp0MsFuPll18GYOsRGDduHF5++WXEx8dj1apVmDhxInbv3o3Bgwc7bcuxY8dgtVrx/vvvo2fPnjhy5AjmzJkDjUaD119/HQCwY8cODBw4EE899RRSUlKwceNGTJ8+HQqFArfeemuA/1ohjLUDALZ+/Xr+9enTpxkAduDAAYdy1113HXv00Ued1rF48WIGoNVDqVS2p2mtXLV4M8t6aiM7WaXit6nVan5/arWaqfUmlvXURpb11Eam0hn9un9CwolSqQzIeRhIgWzzoCXfsaynNrLjlSqH7S1jCGOMbT1aybKe2shufvNnv7eDtNbY2MhiY2PZsWPH2JQpU9hLL73Ev7dq1SqWl5fHZs+ezWbPns3y8vLYqlWrGGOMffvtt0wgELDKykq+/HvvvcfkcjkzGAwu99evXz+2ZMkSr9r46quvsuzsbLdlbrnlFjZr1iyv6g017T0H/ToR3pcVFxcuXAilUsk/SktL/dkkAIDJYoVKb7sM525QWoxUhPhoMQAa2EoIsTFbrGjQ2ge1tn2FJCPetuqzq8XRiH+tXbsWffr0Qe/evXHffffho48+4lfbnjlzJtauXYuNGzdi48aNWLt2LWbOnAnA1s1z1VVXOfx7NX78eKhUKhQXFzvdl9VqRWNjIxISEvhthYWFblfvBQClUunwGV/LRLqgr8wjlUohl8sdHv5gNpuxadMmbNq0CTVK2+AyAQfER4ndfq5LU7dNWX3rYNK8Tlr2mZDI5RA/VLZYwHFAJydjSFpKb7qfTYPWBI3BMU5QDPG/lStX4r777gMATJgwAUqlEtu3bwcArF69Gvfccw8KCgpQUFCAe+65B6tXrwZg+wHt7Mez/T1nXn/9dajVan61XcB236XevXu7bN+pU6fwzjvv4E9/+pPLMmvXrsXevXsxa9YsD444cvk1IWm+4mJzVVVV/HsdxWAw4NZbb8Wtt96KikuNAGzBpOXKiS11ib98Txt3dTYf90L8I5QGpgHASy+9hGuuuQbR0dGIj4932h6O45w+qqurPT5uEnqan+uVTfEjPkoMYRvxAwDiZGLIZbbheS1vskcxxL+OHz+OPXv24N577wUAiEQiTJkyBStXrgQAVFdXY8uWLRg1ahRGjRqFLVu2+HxufvbZZ1iyZAnWrl2L5ORkfvvtt9+OY8eOOf3MxYsXMWHCBNx9992YM2eO0zI//fQTZs2ahQ8//BD9+/f3qW2Rwq8JSfMVF+3sKy7m5+f7c1dtEggEGDZsGIYNGwalzt5d03rZZ3sZ+zLO9oGtZZdaT9lzVp74j31g2s8//4zy8nJ++7Jly9DY2Mi/bmxsxLJlywCAH5hmNBqxY8cOfPzxxygsLMSiRYv48vaBad9++y3279+PG264ARMnTsSBAwfctsdoNOLuu+92uVrolClTUFFR4fAYP348rr/+eoeARcJP83O9Qee6u8ZVTEh3saYRxRD/WrlyJcxmM9LT0yESiSASifDee+/hP//5D5RKJRYsWIC4uDi+fFxcHL8GTmpqqtMfz/b3mluzZg0eeOABrF271uGu1O6Ul5fjhhtuwDXXXIMPPvjAaZnt27dj4sSJWLZsGaZPn+7xcUcsbwedNDY2sgMHDrADBw4wAOwf//gHO3DgADt//jxjjLFXXnmFxcfHs6+//podOnSITZo0iWVnZzOdTudR/YEYmPZ10UWW9dRGds+KHW2W/ejXMyzrqY3soX/v89v+SdtCeWDaqlWrmEKhaLNcdXU1E4vF7JNPPvGo3lBGg1ov++agLX7c/V7b8cPuj6v2sKynNrLVu875tS3kMpPJxFJSUtgbb7zBDh8+7PDo0aMHe++999x+3h47qqqq+G3vv/8+k8vlTK/X89s+++wzJpPJ2IYNGzxuW1lZGcvJyWFTp05lZrPZaZmffvqJxcTEsHfffdfjekNde89BrxOSn376yemsmBkzZjDGGLNarey5555jKSkpTCqVsjFjxrDjx497XH8ggsqqpiTj4dVtJxnfF9tGyE985xe/7Z+0beXKlWzYsGGMMca++eYb1qNHD2a1Wvn3z58/z1JSUlhKSgqf/DLG2HPPPccGDRrkUNeZM2cYAPb777873ZfFYmGZmZnsnXfe4betWrWKucrPPU1IXn/9daZQKJhWq22zbKijhOSyj3ecZVlPbWR/+sTzHynPbTjMsp7ayF7dfNSvbSGXrV+/nkkkEtbQ0NDqvSeffJKPJ66YzWY2YMAAdtNNN7GioiK2efNmlpSUxBYuXMiX+fTTT5lIJGLLly9nFRUV/KP5Pr/66ivWu3dv/nVZWRnr2bMnGzNmDCsrK3P4nN2PP/7IoqOj2cKFCx3er6ura8+fJOg6fJZNuK24CHi2bLxdhps1BEjghPrANE+P4Q9/+AOioqLaVQ8JLfyNOWPbjh929i4bZ4ujEf9YuXIlxo4dC4VC0eq9O++8E/v27cOhQ4dcfl4oFGLjxo0QCoXIz8/Hfffdh+nTp+P555/ny3zwwQcwm82YO3cu0tLS+Mf8+fP5MkqlEsePH+dfb9myBadOncLWrVvRpUsXh8/Zffzxx9BqtVi6dKnD+3fccUd7/yxhLWI7MXU6HUaOHImRI0eiot622FrLKb9arRbdunVDt27doNXaxozYx5DUa4zQGs0u66Rln/0n1AemeWLnzp04evQoZs+e7XMdJHQ0P9ermuKHsxvrOYshQLP7YrX4YUMxxH+++eYbbNq0yel7I0aMAGMMAwcOdFtHVlYWvv32W2i1WtTU1OD111+HSHR5vdBt27a5/QEO2KYWs6Zpxs1fO3vYFRYWOn3/Sr8TdMTeXM9qtWLHjh0AgD6znN+pkzGG8+fP888BQBElRpxMhEa9GRcv6ZCTEue0Tlr22X+aD0yzY4xBKpXi3Xff5Qeh2bUcmLZnzx6H99samLZu3TqPB6Z56l//+hdyc3MxdOhQv9ZLgqP5ud7/j033sXGSkDiLIYDrQa0UQwhxLWITEqlUivXr1wMAVl+0BQpPumwAoEunaBytUKGsRULSvE6ptO27fpK2mc1mfPLJJ3jjjTdw0003Obw3efJkfP7553jooYcAgF/QqLn8/Hy89NJLqK6u5q94bNmyBXK5HP369ePLff755/jjH/+INWvWuJxW7Cu1Wo21a9di6dKlfq2XBE/zc/2zClvi4Gn8AC5fIalU6WG2WCESClrVSzGEEEcRm5CIRCJMnjwZAPDOG9sAOL/k6kyXTlFNCYnj1N/mdRL/2LhxIy5duoTZs2e36gu+8847sXLlSj4hceamm25Cv379cP/99+PVV19FZWUlnn32WcydO5cP+J999hlmzJiBt956C3l5efzYkqioKH6f69evx8KFCx26bS5cuID6+npcuHABFosFRUVFAICePXsiNjaWL/fFF1/AbDbzY2BI+Gt+rv9zmW0sU2c3qzy3lBwnhVjIwWRhqG408FdMKIYQ4lrEjiFpjh/U6uGgNH5gKy0fH3ChOjANABYtWoTBgwdj8eLFUKvVGDx4MAYPHox9+/a1OoY77rjD6eJpJPx5MyjeTiDgkKqwrdjacnE0QohzEXuFxGKx4JdffoHFynBJowc4oRddNs5n2tjrBIBRo0ZBKBT6t9FXoG+++cble/aBaW2xD0xzxZOBYjNnzmzVJeRqZdiW7GMCSOSwn+tWK0O9Wg9AgM5ezLIBbD9sSut1uNigw7AW9QIUQwhpKWITEr1ejxtuuAEAkPn4lxBIhB7dhwKwjSEBWickzetUq9WIiYnxY4sJIaGidfyQeRw/7JwNbKUYQohrEZuQcByHfv36wWi2wsDZZs+IhQKnZezP7exXSFpO2XNVnhASWfj4YbHFjziZCBJR6x5udzEhg1+LROdReUKudBGbkERHR6O4uBg7T9fh3g93OR3Qai/Tkj0hqVUboDdZIBML3ZYnhEQW+7m+91w97l6x0+WAeHcxwdlaJBRDCHEt4ge1+jIgTRElRozEloTQiq2EXLnq1E1rGMV6P0WXVmslxDtXQELielEjVziOQ2aCbRzJhXpNQNpFCAl9NU3Lxid6OaAVuLzq88UGnUeDswm50kVsQqLT6TBu3Di8OHcarCYDEuNa/8LRarXo378/+vfv77DsMwBkJ9oGm52tvbzdXue4ceNo2WdCItjl+PEHWE0Gl1dI3MWQdIUtIVEbzFDpzQ71UgwhpLWIHUNitVrxww8/AAAyRy9Aootln0tKSvjnzdkTknO1l6+QNK+Tln0mJHI5xI/rnccPwH0MiZLYlhqo1xhR3qCDIkpMMYQQNyI2IZFKpVi9ejU++vUsTonETq+QuNONv0JyOSGx12l/TgiJTPZzfdVvZ3FSJPZpDAkAZHaKQr3GiPN1WvRNk1MMIcSNiE1IRCIRpk2bhg2NO8Cdu+TVss8A0N1JQmKvkxAS2ezn+tfqneDO1nu9KJpddmIMDpYpcaZW7VAvIaS1iB1DYlfXNCjN24Bi77IpV+qgN1n83i5CSOjjZ9l4+YPGrkeS7Z5HZ2pocDwhbYnYhMRisWDv3r24cPwQmNXi9Sj5hBgJ5DIRGAPO12kd6ty7dy8sFkpSCIlU9nO99MRhn+KHXfemhOR0jdqhXoohhLQWsV02er0eI0aMAGBb+tnbXzgcxyE7KRYHSxtwtlaN3qlxDnXSss+ERK5W8cPHMSQ9km0x4nS1GowxiiGEuBGxCQnHceiS2RUVSj2EQg6KKLHTMllZWfzzlrI7RzclJFqPyhNCIgPHcejStSsqGvQQCIB4J/HDXs5dTOjWOQYcB6j0ZtRpjIgWUAwhxJWITUiio6Pxv52HcOs7vyIpTgqBoPXJHx0djXPnzrmsIzvR3v+r9qg8ISQyREdHY/POQyh4+1ckxjqPH/Zy7mKCTCxEl062u/6erlYjr3tniiGEuBCxY0gA271oAN+WfQaAnsm2hOREtdpvbSKEhIe6dqzS2lx3+w+bWhrYSog7EZ2QtDeg9EmLAwCcqGyExUpLPxNyJalruu1Eoo8/aOzsP2yOVza2u02ERLKITUj0ej1eeGwWqr96EQqx82RCp9Nh+PDhGD58uNNlnLt1joFMLIDOZMGFei30ej0mT56MyZMnQ6+nG2YREqn0ej2WPNoUPySuf4y0FUMAoF+aHABQUqGiGEKIGxE7hsRiseDgr7YlmjtFOz9Mq9WKffv28c9bEgo49E6Jw8EyJY5VqJDcXY6vv/6ar58QEpmax4+kWOcDWoG2YwgA9Eu3JSRHy1Uwm80UQwhxIWITEolEgrEPPoffz19CcrzvU+v6pMpxsEyJo5WNGNsnER988AFfPyEkMkkkEoye/QwOlSmRlhDXrrp6JMVCIhSg0WBGtcZCMYQQFyI2IRGLxUgefgviOtUhox0BxT6O5GiFCmKxGHPmzPFXEwkhIUosFqPz0FsQl3gJXdqZkEhEAuSkxKK4XIUTNTqKIYS4ELFjSACgUmnro02Vy3yuo09q0+XWCpVf2kQICQ+Vqqb4oWj/TfCajyMhhDgXsQmJ1WrF+VPHYaw5j6Q43y+N9s+Qg+OAsks6VKt0KC4uRnFxMd06nJAIZrFYUHr6hC1+tHPaLwD0bxpHcqT0EsUQQlyI2C6bmoZGnF7xEABA8Zrvd9eUy8TISY7FiSo1dp2owKThAwDQss+ERLKLtUpc+PBhAEDcP+5vd32DMuMBAPvOVGHA7KsBUAwhpKWITUiqlHoIouTgOA4xUteHmZiY2GZdgzM74USVGgfLGjwqTwgJb1WNtvgh4DhIRO4vJHsSE/qnKyAVCdCg1aNT584Q0rLxhLQSsQmJyixE5qOfISc51uWvkJiYGNTU1LRZ15CseHyxrxTF1QaPyhNCwpvSaIsfAzLkbq9ieBpDJCIBcjPjsfusFf/89ndMHdHVn80lJCJE7BiSywPSfB/QajekaycAQFFpAwxmWjuAkEh3vt52Q82sBP91qQzvlgAA2Hvukt/qJCSSRGxCUt5gWzWxPTNs7HomxyIpTgq9yYr95ymYEBLpSpsSksyEaL/VOTzblpDsOF0LxuhWFIS0FLEJyemKS6j55jVse/85l0s063Q6jB49GqNHj3a57DNgu034qJ6JYGYj5j4wC9OmTaNlnwmJYGeqbPHjmzefdnuuexpDACAvOwESzoxDq1/AbXdOoRhCSAsRO4bkfG0jtCXbsa/E9RLNVqsV27dv55+7M6pXIr7cfRpF2zaiCOBXWySERJ4LNbb4scNN/AC8iyEysRB53Tphdcl2bCwBLJZVfm0zIeEuYhOSUqUJnW6cgwdGZftlieZreyZBIBKh041z8MiYnrTsMyERympluNhoDsi5fkO/NGy6cQ4yE6IohhDSQkQmJBqDGXU6C+TDJ+GZJ2+CWOz65lieSoqTIr9nCnYKJiFtZB+/1EkICT3lSh1MTIDOV0/Gc09NgEjov57tWwZm4oURk6BkQGWjCZkJFEcIsYvIMSTn62wD0uKjxVBE+++EnzgoHQDw36Jyv9VJCAktxysbAdhuiufPZASwzfq7pkdnAMD6Axf9Wjch4S4iE5KT1Y1gzIpkToVz5875bYnm8f2SwalrcOjYSew9W+eXOgkhoeVYpS1+pAkb/Ro/ANs4k5EpDGZlFdbsPg+ThZaPJ8QuIhOSkgoVmMmILYvuRnZ2dpuj3z0lE1hwbvksXFwxGx/+eMwvdRJCQsuxykYwkxGFj97q1/gB2GblzL3tGlxcMRtltUpsOlTht7oJCXeRmZCU2+6oKZVFITra/ToC0dHRbZZpLioqGpxYiu9KKnHkorJd7SSEhJ7fm9YakkV5Fhu8jSHR0dGQyKIAAG//eBJGM10lIQSIwITEYmU4VKaEQCLDnpPl0Gg0bpeO12g0bsu0LK/VajD3453gxDL87b/FsFhpgSNCIsXFBh0uNugglkWh9pKyzdjgSwzRaDSorlciOUGOMzUafPjLGX8eAiFhK+ISksMXlVDqTIiTidAvTR6QfSy8uQ+ixELsO38Jb/5wIiD7IIR0vF9O2O5LMyBD4famnO2liBLj/27pCwBYtuUEdp2hMWmEBCwhWb58Obp16waZTIa8vDzs2bMnULty8OOxagBAfvfOfh8hb5ceH4WX7xgAAHjnx1NY/tMpWgqaED8IVtyw29g0puOmfikB39ftgzNw26B0mK0MD3y8D7+erA34PgkJZQH5F/uLL77AggULsHjxYvz+++8YNGgQxo8fj+rq6kDsjmcwW7B2bykA4KY+CZgzZw7mzJkDg8HgtLxer0dBQQEKCgo8WsbZYDDwdd7SLwmP3tgTAPDad8cx7V+7se9cPSUmhPgoWHHD7shFJX49VQuOA27q3bnN+AG0L4YYjUb8/c6BuLp7AtQGM+5buRsLvzqEs7Uafx4WIWGDYwH4FzQvLw/Dhw/Hu+++C8A21S0zMxOPPPIInn76abefValUUCgUUCqVkMtdd7kodSbUqg0wmKwwWqzQmyz4bPcF/PdgOZLipPhu3gh0jlcAANRqtdP+XY1Gg9jYWLdl2ir/713n8dKmEuhNtoFp6QoZhmcnoGdSLFIUMiiixJDLxJCIOAgFAogEHIQCDiIBB45zu7s2+P7h9u2XhLs4mQjJce5vOunpeehP7YkbgOdtvlCnhcFsgcnCYLZaYbIw1DQasPR/R3G+TovbBqVj6W29PIoN/oghepMFf/tvMdY0/ZgCbDf0HNI1Ht0SY5AqlyFOJkasVASZWAChgIOAs8UP+3MBB7QnJkQ6inn+kdkpGhKR6+sY7Y0bfu8kNRqN2L9/PxYuXMhvEwgEGDt2LHbu3NmqvMFgcPgFolKpPNrP53su4JX/tZ56y3HAy7dfhdgoGV588UUA8NuqqmKxuFWd91+dhetyEvHPn05jQ9FFlCv1+JoWTiMh7A95XfHy7VcFuxkOvI0bgO+x4/Z//oY6jdHpe+kKGZ69tS/EYoHf44e9rpb1ysRCvHLnQEwenIEV209j+4kanKpW41S12m/7JcQftj0xGt0S2x687Su/JyS1tbWwWCxISXHsg01JScGxY60TiKVLl2LJkiVe7ydGKoJcJoJULIREKIBULEC6Igp/ur47RuUkAQCeeeYZ3w7CBYlE4rTOrM4x+PtdA7FkUn/sPluPknIVTteoUas2QKkzoVFvhtlihdnKYLEymK0M5nYsiNSeS1rUo0SixMJgN6EVb+MG4HvsUESLYWEMIoEAYiEHkZBDtFiEq7snYN6NOUiKkwLwf/wAXMcQALi6e2dc3b0zGrRG7DpTh2OVjThfp0Wt2oBGvRlqgxl6kwWMAVZmiyVWBjDGYKET2yX60/iPIMCXmoJ+L5uFCxdiwYIF/GuVSoXMzMw2P3f/1Vm4/+qsQDbNazKxENf3SsL1vZKC3RRCIp6vsePHv4wOYKvaLz5aggkD0jBhQFqwm0JIh/J7QpKYmAihUIiqqiqH7VVVVUhNTW1VXiqVQiqV+rsZYIyhtraWbxPnh8wuEHUSQryPG0DgYgcQuHOdYgghrvl9lo1EIsHQoUOxdetWfpvVasXWrVuRn5/v7925pNVqkZycjOTkZGi12pCtkxASOnHDLlDnOsUQQlwLSJfNggULMGPGDAwbNgwjRozAm2++CY1Gg1mzZrX5WfukH08HqLmi0VyeOqdSqWCxWHwq057yhIQr+/nXkdPY2xM3AP/FDsDzc51iCCGXtTtusAB55513WNeuXZlEImEjRoxgu3bt8uhzpaWlDLZxm/SgBz2C/CgtLQ1UiHDK17jBGMUOetAjVB6+xo2ArEPSHlarFeXl5YiLi2uzf9U+iK20tLTD1koIFDqW0BRJxwJ4fjyMMTQ2NiI9PR0CQXjcYcLT2BFJ32kkHQsQWcdzJR5Le+NG0GfZtCQQCNClSxevPiOXy8P+C7ejYwlNkXQsgGfHo1AoOqg1/uFt7Iik7zSSjgWIrOO50o6lPXEjPH76EEIIISSiUUJCCCGEkKAL64REKpVi8eLFAVuLoCPRsYSmSDoWIPKOxxeR9DeIpGMBIut46Fi8F3KDWgkhhBBy5QnrKySEEEIIiQyUkBBCCCEk6CghIYQQQkjQUUJCCCGEkKCjhIQQQgghQUcJCSGEEEKCjhISQgghhAQdJSSEEEIICTpKSAghhBASdJSQEEIIISToKCEhhBBCSNBRQkII8buff/4ZEydORHp6OjiOw4YNG9r8zLZt2zBkyBBIpVL07NkThYWFAW8nISR0UEJCCPE7jUaDQYMGYfny5R6VP3v2LAoKCnDDDTegqKgIjz32GB544AF89913AW4pISRU0N1+CSEBxXEc1q9fj8mTJ7ss89RTT2HTpk04cuQIv23q1KloaGjA5s2bO6CVhJBgEwW7AS1ZrVaUl5cjLi4OHMcFuzmEXJEYY2hsbER6ejoEgsBfSN25cyfGjh3rsG38+PF47LHHXH7GYDDAYDDwr61WK+rr69G5c2eKHYQEQXvjRsglJOXl5cjMzAx2MwghAEpLS9GlS5eA76eyshIpKSkO21JSUqBSqaDT6RAVFdXqM0uXLsWSJUsC3jZCiHd8jRshl5DExcUBsB2QXC4PcmuINzQaDZ9MlpaWIiYmxud60tPTAdgS1PbU44/2XIlUKhUyMzP58zEULVy4EAsWLOBfK5VKdO3alWIHIUHS3rgRcgmJ/VKrXC6noBJmhEIhLBYLANv352sCIBQK+edyuRyyqGjsOVuP6kY9kuNkGJGdAKGg7Uvy/mrPlayjuj5SU1NRVVXlsK2qqgpyudzp1REAkEqlkEqlrbZT7CAkuHyNGyGXkJDwFRUVhbKyMv65P7y6+Si+O96AStXlsQJpChkWT+yHCQPSOrw9JDDy8/Px7bffOmzbsmUL8vPzg9QiQkhHo2m/xG8EAgEyMjKQkZHRroGQhy828M9X/XbeIRkBgEqlHg+v/h2bj1R0SHuI99RqNYqKilBUVATANq23qKgIFy5cAGDrbpk+fTpf/qGHHsKZM2fw5JNP4tixY/jnP/+JtWvX4vHHHw9G8wkhQUBRmoQUs8WK//vPYbdl7PPUl3xTAouVZq2Hon379mHw4MEYPHgwAGDBggUYPHgwFi1aBACoqKjgkxMAyM7OxqZNm7BlyxYMGjQIb7zxBv71r39h/PjxQWk/IaTjUZcN8Ruj0Yi33noLADB//nxIJBKv6/iuuAqnajRtlmMAKpR67Dlbj/wenQPWHuKb0aNHw90SR85WYR09ejQOHDgQwFYRQkIZJSTEb0wmE5588kkAwJ///GefEoDCHWe9Kl/dqA9oewghhHQMSkiI34hEIsyYMYN/7q0KpQ57z12CQCjEmNvuwa4zdeAEQrefSY6TBaw9hBBCOg5FaeI3Uqm0XTdE+77YNu1zWPdkfPH3Nbj27z+iUqmHswv/HIBUhW0KcKDaQwghpOPQoFYSMr4rrgQAjO+fCqGAw+KJ/ZyWs89wXzyxn0frkRBCCAl9lJCQkKAzWrD3XD0AYEzfZGg0GozKluOf0wYjTeHYLZOqkOG9+4a0uQ4JIYSQ8EEJCfEbjUaD+Ph4xMfHQ6Npe6ZMcwcuXILJwpAqlyE5CoiNjUVsbCyu667Ar0/diDsGZwAAru2ZiF+futGjZKQ97SGEENKxKCEhfqVUKqFUKr3+3O6ztqsjed0TWi07LBRwuH2ILSE5W6vxqpvG1/YQQgjpWDSolfhNVFQUTpw4wT/3xp6mhMTVINUhXTtBKOBwsUGHiw06ZMS3XX972kMIIaRjUUJC/EYgECAnJ8frzxnMFvx+4RIAIM9FQhIjFWFAuhwHy5TYd64eGbkZAWsPIYSQjkddNiTojlY0wmC2IiFGgh5JsS7L5WbGAwAOlVEXDCGERBq6QkL8xmQy4YMPPgAAPPjggxCLxR597vBFW4JxVYbC7W2rB2QoHMoHqj2EEEI6HiUkxG+MRiPmzZsHAJg5c6bHCcCRsssJiTtXdbG9X1KugtXKIGhjcKuv7SGEENLxKCEhfiMUCnHXXXfxzz1lv+IxIEPutp6eSbGQiQVQG8w4W6dx273TnvYQQgjpeJSQEL+RyWRYt26dV5/Rmyw4UdUI4HKXjKt6REIB+qbJceBCA45cVLaZkPjSHkIIIcFBg1pJUB2vbITZytApWuzRVN6B9nEkNLCVEEIiCiUkJKiOlNu7a9wPaLXrl27r1jnedFWFEEJIZKCEhPiNVqtFRkYGMjIyoNVqPfpMcbkKgOOAVo1GA47jwHFcqyXfe6XEAbBdWQlEewghhAQHjSEhfsMYQ3l5Of/cEyebrnT0To3zqHxOU0JS3WhAg9aI+GiJX9tDCCEkOCghIX4jk8lw4MAB/nlbGGM4UaUGAOQke5aQxEpFyIiPwsUGHU5UqV0uNe9LewghhAQPJSTEb4RCIXJzcz0uX6M2QKkzQcAB3ZNiPP5c79Q4XGzQ4XhVo9uExNv2EEIICR4aQ0KC5mTT1ZGszjGQiT1fJ8Q+juSEB+NICCGEhAe6QkL8xmQy4dNPPwUATJs2rc2VUe3rj+Qku19PpKXeqbbybc208bY9hBBCgocSEuI3RqMRs2bNAgDcfffdbSYAJ6ubxo+keJeQ8FdIqhrBGHM5Xdjb9hBCCAkeSkiI3wiFQtxyyy3887bYZ9jYEwxP6+mRFAsBBzRoTahpNCBZ7nzAqrftIYQQEjyUkBC/kclk2LRpk0dlm8+w6dmiy6atemRiIbp1jsGZWg1OVKldJiTetIcQQkhw0aBWEhTNZ9i0dU8aZ3o0JTGna9T+bhohhJAgoISEBMUpH2fY2NmTGEpICCEkMlBCQvxGq9UiJycHOTk5bS7Vbp9h07K7BrAtHR8TE4OYmJhWS8fb9What8RdQuJNewghhAQXjSEhfsMYw6lTp/jn7pxommHTy8UMm7YSCHuXzZka5wmLt+0hhBASXJSQEL+RyWT49ddf+efunPJyyfiWeiTaEpIKpR5qgxmx0tb/K3vTHkIIIcFFCQnxG6FQiJEjR7ZZjjGGE9VNi6J5uQaJnSJajMRYCWrVRpyt0eCqLopWZTxtDyGEkOCjMSSkw9WqjWjQ+j7Dxq47DWwlhJCIQQkJ8Ruz2Yx169Zh3bp1MJvNLsvZF0TrmhDt0wwbu7Zm2njaHkIIIcFHXTbEbwwGA+655x4AgFqthkjk/H+vyzNsfBs/YtfWTBtP20MIIST4KEITvxEIBLj++uv5566cbGOGjaf18IujVTufaeNpPYQQQoKPEhLiN1FRUdi2bVub5U5W2RMS51dIPK2nZ1OXzdlaDSxWBqHA8SZ7ntZDCCEk+Pz+s/Fvf/sbOI5zePTp08ffuyFhqvkMG2eLonkjPT4KUpEARosVZZdo4TNCCAlnAblC0r9/f/zwww+Xd0J996SJfYYNx7U/IREKOGQnxuBYZSNO16iR1TnGT60khBDS0QLSsS4SiZCamso/EhMTXZY1GAxQqVQODxKedDodcnNzkZubC51O57TMyWrXM2x27twJoVCICRMmICkpCUlJSQ5LxxcWFqKwsNDhMwpdOWr++yruui4XUVFR6Nu3L9566y2X7fntt98gEomQm5vb5vHU19dj2rRpkMvliI+Px+zZs6FWXx5Au23bNkyaNAlpaWmIiYlBbm4uPv300zbrJYQQ0lpAEpKTJ08iPT0d3bt3x7Rp03DhwgWXZZcuXQqFQsE/MjMzA9Ek0gGsVisOHjyIgwcPwmq1Oi1z0s0KrStXrsQjjzyC3377DbW1taitrQUALFu2DI2NjXy5xsZGLFu2zPai9gyE0QpMmPcSiouL8cwzz2DhwoV49913W7WnoaEB06dPx5gxYzw6nmnTpqG4uBhbtmzBxo0b8fPPP+PBBx/k39+xYwcGDhyI//znPzh06BBmzZqF6dOnY+PGjR7VTwgh5DKO+fkmH//73/+gVqvRu3dvVFRUYMmSJbh48SKOHDmCuLjW/wgZDAYYDAb+tUqlQmZmJpRKJeRyuT+bRgLMYrHgxx9/BADceOONEApbrzHyzPrD+HT3BTw8ugeemnB5bJFarUZaWhr27duHZ555Bv/5z3/47evWrcOKFSswYMAAAMCRI0fw0EMPYebMmfi66CLmrynCiG4JWPtQPgBg7ty5OHr0KLZs2eLQnmnTpiEnJwdCoRAbNmxAUVGRy2M5evQo+vXrh71792LYsGEAgM2bN+OWW25BWVkZ0tPTnX6uoKAAKSkp+Oijj7z864UWlUoFhUIRVudhOLaZkEjS3nPQ74M7br75Zv75wIEDkZeXh6ysLKxduxazZ89uVV4qlUIqlfq7GSQIhEIhxo0b57aMqym/a9euRZ8+fdC7d29MnTqVT0gAYObMmbjxxhsxYsQIAMCePXvQtWtXAM4XR1MqlUhISHBoz6pVq3DmzBmsXr0aL774Yqt2FRYWYtasWfxN+Hbu3In4+Hg+GQGAsWPHQiAQYPfu3bj99tudHp9SqUTfvn3d/g0IIYS0FvDRpvHx8ejVqxd/11Vy5WKM8au0tuyyWblyJe677z4AaJXUrF69Gu+++y4KCgoAAPfccw/mzZuH++67D9mJtoGsdRojLmmMOHpwH7744gts2rSJ//zJkyfx9NNP45dffnE5wFqhUKB3797868rKSiQnJzuUEYlESEhIQGVlpdM61q5di7179+L9999v829BCCHEUcBXi1Kr1Th9+jTS0tICvSsSZGazGZs2bcKmTZucLtVeqzbiUtMMm+b3sDl+/Dj27NmDe++9F0DrWVnV1dXYsmULRo0ahVGjRmHLli2orq4GAMRIRUhX2O7k+/1vezFp0iQsXrwYN910E8xmM/773/+ioKAAixYtQq9evVy2/fbbb8exY8d8PvaffvoJs2bNwocffoj+/fv7XE8kWb58Obp16waZTIa8vDzs2bPHZdnCwsJWywXQHZoJubL4/QrJE088gYkTJyIrKwvl5eVYvHgxhEIh/48NiVwGgwG33norAOdLtduXjM9KiEaU5PL4kpUrV8JsNjsdl6FUKrFgwQKHbXFxcQ7beiTH4tzpE/jTvTMx96EH8eyzz/LtmTRpEgBg/vz5mD9/PgDb4FvGGEQiEb7//nvceOONrfabmprKJz12ZrMZ9fX1SE1Nddi+fft2TJw4EcuWLcP06dPd/IWuHF988QUWLFiAFStWIC8vD2+++SbGjx+P48ePt7ryZCeXy3H8+HH+NcdxTssRQiKT36+QlJWV4d5770Xv3r1xzz33oHPnzti1axeSkpL8vSsSYgQCAYYNG4Zhw4Y5XardnpDkNFuh1Ww245NPPsEbb7yBoqIiFBUVYdeuXejfvz+kUim+/PJLvuzMmTMxc+bMVvXG6SpR9fn/YeANt+Gll15yaM/QoUPRv39/7Nq1i6//oYceQu/evVFUVIS8vDynx5Kfn4+Ghgbs37+f3/bjjz/CarU6fGbbtm0oKCjA3//+d4cZOFe6f/zjH5gzZw5mzZqFfv36YcWKFYiOjnY72JfjOIflAlJSUjqwxYSQYPP7FZI1a9b4u0oSJqKiorB3716X75+oaj2gdePGjbh06RJmz54NhULBbz9y5Aieeuop/Pvf/8ajjz7qss4jR45g9aLZiMoejPRRd/HjO4RCIZKSkrBv375Wn0lOToZMJuNn7QDA+vXrsXDhQr7bpm/fvpgwYQLmzJmDFStWwGQyYd68eZg6dSp/Jeenn37Crbfeivnz5+POO+/k9y2RSJCQkNDm3ytSGY1G7N+/HwsXLuS3CQQCjB07Fjt37nT5ObVajaysLFitVgwZMgQvv/yy2+4vZzP0CCHhi+44RjqMfUBr83vYrFy5EmPHjnVIRuzuvPNO7Nu3D4cOHXJZ55dffonGS3XQFP+ELx67BWlpaUhLS8Pw4cO9aptSqXToLgCATz/9FH369MGYMWNwyy234Nprr8UHH3zAv//xxx9Dq9Vi6dKl/H7T0tJwxx13eLXvSFNbWwuLxdLqCkdKSorLAcG9e/fGRx99hK+//hqrV6+G1WrFNddcg7KyMpf7oTWMCIksfl+HpL1oLYHIxBjDoCXfQ6U343/zR6Fvmv++2zq1AUNf/AEcBxQvGY9oCd2qoL3acx6Wl5cjIyMDO3bsQH5+Pr/9ySefxPbt27F79+426zCZTOjbty/uvfdevPDCC07L0BpGhISW9v77TVdIiN/odDqMHDkSI0eObLV0fJXKAJXeDKGAQ/ck9/ec0Wq16NatG7p16wattu2b5nWOlSIhRgLGgDM1l5ead9ceEjiJiYkQCoWoqqpy2F5VVdVqQLArYrEYgwcPdrtcgFQqhVwud3gQQsIXJSTEb6xWK3bs2IEdO3a0Wjqen2HTORpSUesVXJtjjOH8+fM4f/48PL2AZ79Rn/1eOW21hwSORCLB0KFDsXXrVn6b1WrF1q1bHa6YuGOxWHD48GFaLoCQKwhd2yZ+I5VKsX79ev55c/aEpHdK69sH+ENOciz2nK3n75XTVntIYC1YsAAzZszAsGHDMGLECLz55pvQaDSYNWsWAGD69OnIyMjA0qVLAQDPP/88rr76avTs2RMNDQ147bXXcP78eTzwwAPBPAxCSAeihIT4jUgkwuTJk52+x99UL4AJCXB5afq22kMCa8qUKaipqcGiRYtQWVmJ3NxcbN68mR/oeuHCBYep4ZcuXcKcOXNQWVmJTp06YejQodixYwf69esXrEMghHQwSkhIhzjOz7CJbaOkb+yJzqlmCQkJrnnz5mHevHlO39u2bZvD62XLll2+gzMh5IpECQnxG4vFgl9++QUAMGrUKP5uv4wxPlHoFeArJOfrNNCbLJCJhS7bQwghJPRQQkL8Rq/X44YbbgBgW+QqJsY2m+Zigw5qgxkiAYdund3PsPFVUpwUcpkIKr0ZZ2s16Jsmd9keQgghoYcSEuI3HMfxff7N70NytMLWXdMzORYSUdsTu1zV09ZnclLisP/8JZysVqNvmtynegghhAQHJSTEb6Kjo1FcXNxqe0m5bUnvfumerRPhqp625CTHYv/5SzjVNF7F13oIIYR0PFqHhARccbkSANDPj6uzOtPTyUwbQggh4YESEhJwJRW2KyT901vfr8af7ANmj1U2tlGSEEJIqKGEhPiNTqfDuHHjMG7cOH6pdqXOhLJLtueeXiHRarXo378/+vfv79HS8Xb2++Ocq9NAYzA7bQ8hhJDQRGNIiN9YrVb88MMP/HPg8viRjPgoKKLFHtXDGENJSQn/3FNJcVIkxUlR02jAscpG9EmUtGoPIYSQ0EQJCfEbqVSK1atX88+B5t01HXPjs35pcmxvrMHRChUGZWS0ag8hhJDQRAkJ8RuRSIRp06Y5bPN2hk179UuXY/uJGpRUqCASZbVqDyGEkNBEY0hIQB252DEzbOzs+7EnQoQQQsIDXSEhfmOxWPD7778DAIYMGQKdmeFEtW3GS25mfIe0wX4l5lilCkaTGQeLDvDtoaXjCSEkdFFCQvxGr9djxIgRAGxLtR+q1IExIF0hQ7Jc1iFt6NY5BlFiIXQmC46V1Tm0h5aOJ4SQ0EUJCfEbjuOQlZXFPy8qbQAADO7aqV31eEMo4NAnLQ4HLjTgWGWjz/UQQgjpWJSQEL+Jjo7GuXPn+NdFFxoAeN9d07Ieb/VPl+PAhQacqDO2qx5CCCEdhwa1koBgjOFA0xWS3K7xHbrvwZm2KzL2KzSEEEJCHyUkJCDKlXrUNBogFHAYEOAl41sa3JQAHb6ohNFMC6IRQkg4oISE+I1er8fkyZMxefJk7DheDsA2DTdK4t3sFp1Oh+HDh2P48OE+LfmenRgDRZQYer0eEwomYvLkydDr9V7XQwghpOPQGBLiNxaLBV9//TUAoPvdTwMA8nt09roeq9WKffv28c+9xXEcBneNx4+HG/HT99/ybSOEEBK6KCEhfiORSPDBBx8AAP5dalt/5OruCUFpS25mPH4qqcCYOc9hyvBMSCSSoLSDEEKIZ6jLhviNWCzGnDlzcOs99+FCgxECDhjWLTgJyeCuncAJRTD2vAFz5syBWOzZjf0IIYQEByUkxO92nakDAFyVoYBcFpxEYEjXeAgFHC7Ua1F2SRuUNhBCCPEcJSTEb6xWK4qLi/Hfn3aDMSuu7u79+BF/iZOJMTA9Dsaa8/ji+x0+jUUhhBDScSghIX6j0+kwYMAAFP7lLjCTEdfmJAa1PcMzY1Hx0Vw8MXWcT7N1CCGEdBwa1Er8qlNCZyh1JsRIhMjL9v0KSWJi+5OZvO4JEETJIeA4MMbaXR8hhJDAoYSE+E1MTAyeXbMDb289idEDUiER+XYBLiYmBjU1Ne1uz8g+XdBzwRoYzFZUaBhyYttdJSGEkAChLhviVz+UVAEAxvRNCXJLAJlYiBHZtlk+Px6rDnJrCCGEuEMJCfGb0zVqlFSoIBRwuKF3UrCbAwC4qZ8tMfquuDLILSGEEOIOJSTEb77cfQY137wG/PQ2YkS+j9nQ6XQYPXo0Ro8e3a7BqHq9HuuXPY2ab17D/jPVqFLR8vGEEBKqaAwJ8QvGGP5bVAZtyXacQfuWardardi+fTv/3FcWiwXr131ha9/4R/B9cSXuz+/mc32EEEIChxIS4hc7TtehTGlCyk0PYsG4XiGxVLtEIsGyZcuw83QddglF+PL3i5SQEEJIiKKEhPjFqt/OghOK8OCfH8GTkwYEuzkAbEvZP/bYY7hPbUD+0q04WNqAoxUq9E2TB7tphBBCWqAxJKTdztVqsLVpFsvMa7oFtzFOJMZKMa5pcOuaPReC3BpCCCHOUEJC2m3ZDyfAGHBDr0QINLU4d+5cSCzVbrVace7cOZw7dw5ThnUBAKzdV4Y6tSHILSOEENISJSSkXY5cVOLronIAwMOjMpGdnY3s7OyQWKpdp9Px7RmaEYOBXRTQmSz48JezwW4aIYSQFighIT4zWaz4v/WHAQCTctPRP12B6OhoREdHt7tuf9fDcRwevTEHAPDxjnMorac7ABNCSCihhIT47J2tJ3GoTAm5TISFN/dFTEwMNBoNNBoNYmJifK43UPWM6ZuMEdkJ0JkseGbDEbq/DSGEhBBKSIhPvvq9DG//eAoA8MLkAUhVyILcorZxHIeld1wFiUiAn0/U4L3tp4PdJEIIIU0oISFeYYyh8LezeGLdQQDAg9d1x6TcjCC3ynM9kmLxXEFfAMCrm49j9a7zQW4RIYQQIIAJyfLly9GtWzfIZDLk5eVhz549gdoV6SBHK1SYVbgXf/umBFYGTB2eiacn9OHfNxgMmDNnDubMmQODwfeZLHq9HgUFBSgoKIBe7/ty767ac39+N/xxZDYA4NkNR/DklwdxSWP0eT+EEELaj2MB6Ej/4osvMH36dKxYsQJ5eXl48803sW7dOhw/fhzJycluP6tSqaBQKKBUKiGX0wJWwWK1MtRpjDhZ1Yiisgb8eLQa+85fAgBIhAI8Mb4X5ozqDo7j+M9oNBrExsYCANRqtc/jPzqiHsYY3vnxFP6x5QQAIEosxMRBaRjdOxmDMuORKpdBKOCc1nslCMfzMBzbTEgkae85GJCVWv/xj39gzpw5mDVrFgBgxYoV2LRpEz766CM8/fTTDmUNBoPDr1eVSuXRPjYfqcAXe0sBAM0zqubpleN253mXY3nmfLsnZZzstM2yLdrlyXHAo/KeHIfzNpgsVjRoTWjQmWCxOv7NBBxw84A0PD6uF3omx6IlsViMF198kX8ebO7aw3EcHh2Tg6u7d8bf/luMkgoV1u4rw9p9ZbbyQg6JsVLESEWIkQghFQsh4AABx4Hj/8tBwAHhlraM7p2MGSG4gB0h5Mrm94TEaDRi//79WLhwIb9NIBBg7Nix2LlzZ6vyS5cuxZIlS7zeT2m9Dj8dr2lXW4l7HAdkJUSjV0ocRuUkYkzfFKTHR7ksL5FI8Mwzz3RgC93zpD0jshOw6dFrsffcJXx7uAK7ztThdI0aJgtDhTIy7w6c5uY7JISQYPF7QlJbWwuLxYKUlBSH7SkpKTh27Fir8gsXLsSCBQv41yqVCpmZmW3u57peSYiPvvyrt3nXQfNfrM02Oz5vVopz8xPXo3pd1OWqPDwq7/vxtPyQN/UKBRw6RUuQECNBfLQYUpEQkY7jOIzITsCI7AQAgMXKUKnSo05tgNpghsZggcFsAWOAlTEwZrsKZbUCljCcOtwjyfep1IQQEihBv7meVCqFVCr1+nO9U+PQOzUuAC0ivmKMoba2FgCQmJjokPyEU3uEAg4Z8VHIoCsJ7bJ8+XK89tprqKysxKBBg/DOO+9gxIgRLsuvW7cOzz33HM6dO4ecnBz8/e9/xy233NKBLSaEBJPfZ9kkJiZCKBSiqqrKYXtVVRVSU1P9vTsSQrRaLZKTk5GcnAytNvgroYZae64kX3zxBRYsWIDFixfj999/x6BBgzB+/HhUV1c7Lb9jxw7ce++9mD17Ng4cOIDJkydj8uTJOHLkSAe3nBASLAGZZZOXl4cRI0bgnXfeAWC7yVnXrl0xb968VoNaW1IqlYiPj0dpaSmNlA8zGo0G6enpAIDy8vJ2zY4JpXquRPau04aGBigUCq8/n5eXh+HDh+Pdd98FYIsBmZmZeOSRR5zGgClTpkCj0WDjxo38tquvvhq5ublYsWKF0320HBCvVCrRtWtXih2EBEl74wZYAKxZs4ZJpVJWWFjISkpK2IMPPsji4+NZZWVlm58tLS1lsE0CoQc96BHkR2lpqdfnv8FgYEKhkK1fv95h+/Tp09ltt93m9DOZmZls2bJlDtsWLVrEBg4c6HI/ixcvDvrfhx70oEfrhy9xgzHGAjKGZMqUKaipqcGiRYtQWVmJ3NxcbN68udVAV2fS09NRWlqKuLi4Nvv87dlYJPwiomMJTZF0LIDnx8MYQ2NjI3+FyRveDmwHgMrKSqflKysrXe6n5YB4q9WK+vp6dO7c2W3siKTvNJKOBYis47kSj6U9cQMI4KDWefPmYd68eV5/TiAQoEuXLl59Ri6Xh/0XbkfHEpoi6VgAz47Hp0uuHcjZgPj4+HiPPx9J32kkHQsQWcdzpR1Le+IG3cuGEOJXvgxsT01NpYHwhFzhKCEhhPiVRCLB0KFDsXXrVn6b1WrF1q1bkZ+f7/Qz+fn5DuUBYMuWLS7LE0IiT9DXIWkPqVSKxYsX+7SOSaihYwlNkXQsQMcdz4IFCzBjxgwMGzYMI0aMwJtvvgmNRsPfTmL69OnIyMjA0qVLAQDz58/H9ddfjzfeeAMFBQVYs2YN9u3bhw8++MDvbYuk7zSSjgWIrOOhY/FeQKb9EkLIu+++yy+Mlpubi7fffht5eXkAgNGjR6Nbt24oLCzky69btw7PPvssvzDaq6++SgujEXIFoYSEEEIIIUFHY0gIIYQQEnSUkBBCCCEk6CghIYQQQkjQUUJCCCGEkKALqYRk+fLl6NatG2QyGfLy8rBnzx635detW4c+ffpAJpPhqquuwrfffuvwPmMMixYtQlpaGqKiojB27FicPHkykIfA8+ZYPvzwQ4waNQqdOnVCp06dMHbs2FblZ86cCY7jHB4TJkwI9GHwvDmewsLCVm2VyWQOZcLluxk9enSrY+E4DgUFBXyZYH03P//8MyZOnIj09HRwHIcNGza0+Zlt27ZhyJAhkEql6Nmzp8MsFztvz8NQQLEjNGMHxQ2KG17x6Q44AbBmzRomkUjYRx99xIqLi9mcOXNYfHw8q6qqclr+t99+Y0KhkL366quspKSEPfvss0wsFrPDhw/zZV555RWmUCjYhg0b2MGDB9ltt93GsrOzmU6nC6lj+cMf/sCWL1/ODhw4wI4ePcpmzpzJFAoFKysr48vMmDGDTZgwgVVUVPCP+vr6gB6Hr8ezatUqJpfLHdra8saK4fLd1NXVORzHkSNHmFAoZKtWreLLBOu7+fbbb9kzzzzDvvrqKwag1c3sWjpz5gyLjo5mCxYsYCUlJeydd95hQqGQbd68mS/j7d8nFFDsCM3YQXGD4oa3cSNkEpIRI0awuXPn8q8tFgtLT09nS5cudVr+nnvuYQUFBQ7b8vLy2J/+9CfGGGNWq5Wlpqay1157jX+/oaGBSaVS9vnnnwfgCC7z9lhaMpvNLC4ujn388cf8thkzZrBJkyb5u6ke8fZ4Vq1axRQKhcv6wvm7WbZsGYuLi2NqtZrfFszvxs6TwPLkk0+y/v37O2ybMmUKGz9+PP+6vX+fYKDYcVkoxQ6KG5dR3PBMSHTZGI1G7N+/H2PHjuW3CQQCjB07Fjt37nT6mZ07dzqUB4Dx48fz5c+ePYvKykqHMgqFAnl5eS7r9AdfjqUlrVYLk8mEhIQEh+3btm1DcnIyevfujYcffhh1dXV+bbszvh6PWq1GVlYWMjMzMWnSJBQXF/PvhfN3s3LlSkydOhUxMTEO24Px3XirrXPGH3+fjkaxw1GoxA6KG44obngmJBISd7crd3X78bZuV27/r7e3NG8vX46lpaeeegrp6ekOX/CECRPwySefYOvWrfj73/+O7du34+abb4bFYvFr+1vy5Xh69+6Njz76CF9//TVWr14Nq9WKa665BmVlZQDC97vZs2cPjhw5ggceeMBhe7C+G2+5OmdUKhV0Op1f/t/taBQ7HIVK7KC4cRnFDc+F9b1sItErr7yCNWvWYNu2bQ4DuqZOnco/v+qqqzBw4ED06NED27Ztw5gxY4LRVJfy8/Mdbop2zTXXoG/fvnj//ffxwgsvBLFl7bNy5UpcddVVGDFihMP2cPpuSOQK99hBcSM0v5eOFBJXSAJxu3L7fzv6lua+HIvd66+/jldeeQXff/89Bg4c6LZs9+7dkZiYiFOnTrW7ze6053jsxGIxBg8ezLc1HL8bjUaDNWvWYPbs2W3up6O+G2+5OmfkcjmioqL88l13NIodNqEWOyhu2FDc8O57CYmEJBC3K8/OzkZqaqpDGZVKhd27dwf0lua+HAsAvPrqq3jhhRewefNmDBs2rM39lJWVoa6uDmlpaX5ptyu+Hk9zFosFhw8f5tsabt8NYJsmajAYcN9997W5n476brzV1jnjj++6o1HsCM3YQXHDhuKGl9+LV0NgA2jNmjVMKpWywsJCVlJSwh588EEWHx/PT/u6//772dNPP82X/+2335hIJGKvv/46O3r0KFu8eLHTqXvx8fHs66+/ZocOHWKTJk3qsCli3hzLK6+8wiQSCfvyyy8dpoA1NjYyxhhrbGxkTzzxBNu5cyc7e/Ys++GHH9iQIUNYTk4O0+v1AT0WX45nyZIl7LvvvmOnT59m+/fvZ1OnTmUymYwVFxc7HHM4fDd21157LZsyZUqr7cH8bhobG9mBAwfYgQMHGAD2j3/8gx04cICdP3+eMcbY008/ze6//36+vH363l//+ld29OhRtnz5cqfT99z9fUIRxY7QjB0UNyhueBs3QiYhYYyxd955h3Xt2pVJJBI2YsQItmvXLv6966+/ns2YMcOh/Nq1a1mvXr2YRCJh/fv3Z5s2bXJ432q1sueee46lpKQwqVTKxowZw44fP94Rh+LVsWRlZTEArR6LFy9mjDGm1WrZTTfdxJKSkphYLGZZWVlszpw5HfqPhDfH89hjj/FlU1JS2C233MJ+//13h/rC5bthjLFjx44xAOz7779vVVcwv5uffvrJ6f839vbPmDGDXX/99a0+k5ubyyQSCevevbvDugh27v4+oYpiR2jGDoobFDe8wTHGmHfXVAghhBBC/CskxpAQQggh5MpGCQkhhBBCgo4SEkIIIYQEHSUkhBBCCAk6SkgIIYQQEnSUkBBCCCEk6CghIYQQQkjQUUJCCCGEkKCjhIQQQgghQUcJCSGEEEKCjhISQgghhATd/wN9oZcs3Gp45AAAAABJRU5ErkJggg==",
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",
       "text/plain": [
-       "<Figure size 640x480 with 6 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -74,32 +74,33 @@
     "venezuelaAF = HLAfreq.decrease_resolution(venezuelaAF, 2)\n",
     "cafV = HLAfreq.combineAF(venezuelaAF)\n",
     "cafV['study'] =  'Venezuela'\n",
-    "HLAfreq.plotAFprob(cafV, venezuelaAF)"
+    "HLAfreq.plotAF(cafV, venezuelaAF)"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "We can specify priors manually, this could be any\n",
-    "$n$ length list of positive real numbers.\n",
+    "$n$ length list of positive real numbers. This defaults to a list of ones and is why the plot above shows a small difference between the black and blue points.\n",
     "\n",
     "The interpretation of the prior is that $n$ copies were found for each\n",
     "allele. Note that `combineAF()` uses the first value in the prior for\n",
     "the first allele alphabetically and so on.\n",
     "\n",
-    "By viewing the posterior we can see that the prior has moved the\n",
+    "By using a more informative prior we can see how a prior can moved the\n",
     "estimate away from the observed study."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 6 Axes>"
       ]
@@ -109,22 +110,22 @@
     }
    ],
    "source": [
-    "manual_prior = [10, 1, 1, 1, 1]\n",
+    "manual_prior = [1, 10, 1, 1, 1]\n",
     "\n",
     "# View prior distribution\n",
-    "HLAfreq.plotAFprob(concentration=manual_prior)\n"
+    "HLAfreq.plot_prior(concentration=manual_prior, labels=cafV.allele)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 6 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -136,8 +137,8 @@
     "# Combine Allele Freq of study with Manual Prior\n",
     "cafMP = HLAfreq.combineAF(venezuelaAF, alpha=manual_prior)\n",
     "\n",
-    "# View posterior distribution\n",
-    "HLAfreq.plotAFprob(cafMP, AFtab=venezuelaAF)"
+    "# View posterior\n",
+    "HLAfreq.plotAF(cafMP, AFtab=venezuelaAF)"
    ]
   },
   {
@@ -160,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -181,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -194,12 +195,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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iKGbbBw8epLS01NaXEQRBEARBsBrt1b6B+tiyZQuzZ88mISGB9PR0Vq1axd133206rigKcXFxfPHFF+Tk5HDLLbcwf/58wsPDLb5GZWUlZ86cwd3dHZVK1QStEAShLhRFIT8/n6CgINTqxj+XvfHGG7z55ptm+9q1a8eRI0cAKCkp4cUXX2TZsmWUlpYSExPDvHnz8Pf3t/gaEjcE4erTmNhh8w6QSqUyCwZVtxtKYWEhN910E0888QQjRoyodvydd97hww8/5KuvviIsLIxp06YRExPDoUOH0Ol0Fl3jzJkzBAcHW32PgiDYhtTUVFq2bGmTujp27Mj69etN21rtpXD3wgsv8NNPP/Hf//4XT09Pxo8fz4gRI9i6davF9UvcEAT7wZrYYfMOkKIoDBo0yBRsioqKGD58OI6Ojmbn7dmzx6L6hgwZwpAhQ2q91ty5c3nttde46667AFiyZAn+/v6sXr2akSNH1vi50tJSs9dyxtd2qampeHh41HtPv/2Vxfile6moVGjRTEfHQA/O5JZy8EwuxjeAbXxdGduvDTEdA1Cr5elQEOoiLy+P4OBg3N3dbVanVqslICCg2v7c3FwWLFjA0qVLGThwIACLFi2iQ4cO/PHHH/Ts2dOi+o33Wl/c+GnfGf753X56tvbmy9juVrREEITaaEzssHkHKC4uzmzb2DFpClJSUsjIyGDw4MGmfZ6enkRFRbF9+/ZaO0AzZ86sNjwO4OHhUW8HqLBUz9vrTqA4OHNv1xbMurczjlrDsFtGbgn//uMkX20/QUqenn/+kMSCnRk8PyiCIZ2kIyQI9WHLV0l//fUXQUFB6HQ6oqOjmTlzJiEhISQkJFBeXm4WN9q3b09ISAjbt2+vtQNU9cEpPz8fqD9uNG9WhNrJhTK1zqIHLEEQGo41saPJO0BNSUZGBkC19/b+/v6mYzUxZcoUJk2aZNo29iAtYfG2E2TklRDs7czMETeaOj8AAZ46Jse045l+rVm89QRf/nacY5kFPLt0D+0D3Jk4OJzbbpCOkCA0NVFRUSxevJh27dqRnp7Om2++SZ8+fThw4AAZGRk4Ojri5eVl9pn64kZtD0714epkCLPFZRUN/qwgCE1Hk06Czs7O5sSJE6hUKlq1akXz5s2b8nIW4+TkhJOTU4M/V1GpsHTHKQAmDopA56Cp8TwPnQPPDQontlcrFv6ewsLfUziSkc/Yf++hQ6AHEweHM7iDPxrpCAlCk3D5a/POnTsTFRVFaGgo3377Lc7OzlbVae2Dk7OjIU4Ulkl+NEGwJ5okE/TBgwfp27cv/v7+REVF0aNHD/z8/Bg4cCBHjx612XWM7/czMzPN9mdmZtb47r+xJKbmcDqnGHedlmGdA+s939PZgRdujeD3fw7kuYFtcXPScjg9jzFfJ9Bn1kbm/HKU1PNFNr9PQRDM8fLyIiIigqSkJAICAigrKyMnJ8fsnPrihpOTk+l1lyWvy400dzXMf8zKL6WiUqnnbEEQrhQ27wBlZGTQr18/srKymDNnDmvWrOGnn35i9uzZpKen06dPH86ePWuTa4WFhREQEMCGDRv45JNPaNWqFU5OTvz222/4+vra5BqXs+VYFgB9w31rHf2pCU8XBybd1o7fXh7AswPa4OnswJncEj7cmESfdzYx5IPfeO+XoyScPE+pXobJBcHWFBQUkJycTGBgIN26dcPBwYENGzYA8Mknn9CiRQtOnTrFl19+yc6dO2167ZbNXHDSqinVV3JKHngEwW6w+Suw999/n9DQULZu3Wq2DP32229n3Lhx9O7dm/fff5+ZM2daVF9BQQFJSUmm7ZSUFBITE/H29iYkJISJEycSFxdHaWkpr7/+Ops3b2bXrl28++67PPPMM/j5+dmsbX8cPwdAn3Afqz7fzNWRl2LaM2FgOL8eyuTb3alsTcrmcHoeh9Pz+GhjEo4aNZ1aeHBTsBdt/dxo6+tGGz83mrs6Sq4RQbCQyZMnM3z4cEJDQzlz5gxxcXFoNBpGjRqFp6cnTz75JJMmTeLPP/9k5syZhIaG0qVLF7p3705MTAxHjx61WezQqFVE+Luz/3Qum46cJax3mE3qFQShcaiUqqmbG8nNN9/MK6+8wgMPPFDj8WXLljFt2jQOHz5slpejNjZv3syAAQOq7Y+NjWXx4sUoikLLli25cOEClZWV9O7dm48//phBgwYxYcIEXnnllXqvkZeXh6enJ7m5uXUOa9/89q+cLyzjxwm96dTCs956LeFCYRmbjp5lw+Gz/HH8HOcKy2o8z0mrxt9Dh7+HE37uOrxcHHDTafHQOeDmpMXNSYurkwYHjdpUHLUqs221CtQqFaqLPwHT7yoVqFChVgHGfVzM43TxPKHpMfy1rzFUhtfBdWHpd9BSRo4cyZYtWzh37hy+vr707t2b//u//6NNmzbApUSIn332GSqViuHDhzNv3jz8/PwIDg62KHY05J4X/p7CWz8eQq2CIZ0C6RrihZ+HjuaujugcNDhp1Thq1Thq1GjUF7+Pl333jN9HLn5PDd9X+X4KV5emjldODup637Y0JnbYvAPk5eXF7t27adu2bY3Hk5KSCA8PJzMz0/SE1bNnT7777jtatGjR4OuVlZXh4uLCihUrzDJEx8bGkpOTw/fff1/tM1WXs+bm5hISElJnPo/zBaX0nb0ZgJ1TB+HiaPv544qikHqhiL0ncziamc/x7AJSsgs5k1OCbf8rCcKVw8fNkc0vVX+IuRzjhOKcnBw8PW3zcFEfDY0d1sQNI+UVlUxbfYAf96XbtA2CcC3zUkwEsb3qHjFtTOyw+b/i+fn5dQaDmpIVNcYXlp2dTUVFRY1L4Y1p76tS23JWS5fCB85t8G0KwnVLKuA53bJz8/Pzr1gHqKGxo7FxQxCEhvHcXHjOwnOtiR1Nsgw+Pz+/Vg1FXl6eTa/13nvvAdCrVy/Tvnbt2nHnnXfW+pmqy1krKys5f/48zZs3r3OejbGnaWnGaHtG2mK/XEvtsbQtl/t87BWJGwaupfZIW+yThrSlMbGjSVQYERERdR4HbOYLc3FxAWDhwoWm3B9arZYXX3yx1iWtVfMAVVZWUlBQYNX1BUH4e+Lj44NGo7E4jYbEDUG4trB5B2jTpk31njNgwACb+cI0Gg0uLi7s2bOHxx9/HDAEpg0bNjB+/HiL7rmhUsNrachb2mK/XEvtsbQttpKhWmqDB3jggQdMk6B9fX0tjh3Xc9yAa6s90hb7pCFtsQsZau/evXn33Xf53//+R1lZGYMGDSIuLs4s+6qtfWEVFRV8/PHHLF++nB49euDp6UlhYaGpQ1SVxspQG0NJeQVLtp9g8dYT5JUYMsM6aNT0auNNVOvm3BDgQaCXDi8XRyoVhZKyCtLzSkg9X8TBM3n8mZrDwTN56C9LqNbc1ZHbOwVweyd/bmrZTFQbwt+OppChWmKDnzJlCrNmzeLPP/9kyJAhdO/evc7YcTmWylB/PZjBC9/+yc0hXix5MqoRLRIEoSp2JUOdMWMGb7zxBoMHD8bZ2ZkPPviAs2fPsnDhQtM5tvSFRUVF8fXXX7Nnzx4WLFjAmjVrcHBw4Oeff642udFIY2So1qIoCj/sS2fWz0c4nVMMONI6yIsne4dxV9cWeOhqXybcpsp2Xkk5v/+VzcYjZ1l/OJMLReX8JzGb/yRm08LLmTs6B3JH5yA6tfCQ3EHC3wpb/v/VEhv8fffdh7+/PzNmzCA5OZnS0lLWrl1ba+yo6V7rixs+zUtFhioITYw1scPmy+DDw8OZPHkyY8aMAWD9+vUMGzaM4uJi1Orqiadt7QvLyckhNDSUOXPm8OSTT9Z4TtURIGMP0lY5SKqSdDafqasOsCPlPACBnjpevr0dd97UotE+sDJ9JVuTsvnhzzP8ciiTgtJLvqGWzZwZ0imA2zsF0jXYS0aGBLvF1nmA3njjDWbPno2np2c1G/zGjRsZNGgQFy5cMBOihoaGMnHiRF544YUa67Q2buw+cZ77Pt1Oq+Yu9aYDEAShYTQmdth8BOjUqVMMHTrUtD148GBUKhVnzpwxez938OBBxo0bx9atW80+369fP+bPn0+7du2suv7lzp/asFaG2lCKyyr4eNNffL7lOOUVCjoHNf/o35an+7Q2CRIbi6NWzYD2fgxo70dJeQWbj57lhz/T2XjkLGkXivnitxS++C2FAA8dMR396d/ej6gw7ybJYyQI9oI92eA9LiaBPFdYhqIoMiorCHaCzf8V1Ov11ZbAOzg4UF5ebto2+sJ8fX2ZM2cO7du3R1EUDh06xBdffGEKVNakojc6fx599NFGt8VaFEVh/eGzvPXjQVLPFwMwqL0fb9zZkWBvlya7rs5Bw+2dArm9UyDFZRXEHzvLzwcy2HD4LBl5JXy1/SRfbT+Jg0bFzSHN6BPuQ2Qrb25s4Ymrk3SIhGsHe7LBh3i7oFZBfomes/ml+HvUnCJEEIQrS5Msg3/sscfMRlhKSkoYO3Ysrq6uABw4cMBmvjCj8yc+Pp558+Zx9uxZNBqN1SNIjUFRFHamnGf2uqPsPnkBMLzueuPOjtx2g/8VffJzdrzUGSopr2BrUja/Hsrkt7+yOZ1TzI6U86ZXcmoVhPu507mlJ+0DPWjt60pbXzeCvJwb/YpOEOyBy0eGb731VpMN3svLi08++YTZs2dz8uRJMjMzuffee+nRo0e1OqwdOdY5aGjl48rxrEISU3OI6Vi7cV4QhCuHzTtAsbGx1fY98sgjZtvnzp1j+vTpNSZLdHZ25qWXXuKdd96xqAOUlpbGPffcw4ULF2jWrBm33347Hh4ejBw50qZCw9pQFIUT54rYdOQsKxLSOJRuSPTopFXz+C1hTBjY9qqPrugcNAzq4M+gDv6m+/39ryy2JZ/jz9QczuSWcDQzn6OZ+Wafc9KqadnMmQBPHf4eOgI8dAR4GlaoeTo74KHTGn46G3xkTlq1DO8LdsnlI8OX2+D1ej2TJk0iLi6OqVOn0qVLF5vLUAEGtPPjeFYKb/7vICXlFfQI88bfXSfz8gThKmLzSdAbN26kb9++dYpOLfGFRUZGkpOTY9E1o6Ki6N69Ox9//DFgyANUl9DQmsmMGbklvPXjQUrLKymrqKS0vJLCMj0nzxWZTTx20qoZcXNLnhvUlkBP64barzRn80r4My2XfWk5JJ0t4HhWISnZhZRVVDa4Liet+qLY0SB4dHIwCB61GhWaiwkv1SouCh8N+9Rqg+xRffGYUc5aO3X/o1FfH6yuw/V/Vv7Baigezlreue+mOs9p6ETGLVu2MHv2bBISEkhPT2fVqlVmPq8XX3yR7Oxsfv75Z3Jzc3Fzc0NRFI4ePYqvry/jxo3jhx9+ID8/n6KiIhRFwdvbm6SkJDp06FBj7GjM4onsglLum7+NE+eKTPu0ahXero44O2rQaTXoHNQ4aTWm78MlUbHh/3WXfzeM++wNe3v+sc+/kmAp93Zrya031L0i064mQd96662kp6fXKTq1xBdmaYbVsrIyEhISmDJlimmfWq1m8ODBbN++vcbP1DaZsS5NR/aFQn7cfbzGYw4aFV2DmzGgvS/DbwrCy8URKCcvr7zG8+0NHRDV0pmolpc6bBWVCqdzijhzoYSz+SVk5peQlVdKZn4JecV68kr05BWXk19aTkFJhelzxaVQfBXaINgvPm6O5N1Wv9AQLuXkqo/CwkJuuukmnnjiCUaMGFHt+Pr169m/fz8ajQZvb2+0Wi0ajcaUK+T999/np59+Ii8vDwcHB6Kjo0lLS2Ps2LG1xg5r4oYRR+CrR25kyfYTxB/LIulsAWUKZBQXWtReQbge6eirNft3qSYaGjvMUGyMSqVSMjMzTdtubm5KcnKy2TlqtVpJSkpScnNzayzHjh1T1Gq1Rdc7ffq0Aijbtm0z2//SSy8pPXr0qPEzJSUlZtc7dOiQAkiRIuUql9TU1AZGHEUBlFWrVpm2KysrlYCAAGX27NmmfTk5OYqTk5Pyn//8R1EUxew7b4wdP//8s6JSqZRx48bVGDskbkiRYr/FmthxVSanKBb4wlQqFTNnzmTlypUcOXIEZ2dnevXqxaxZs8wmON93332AuQx1zJgxdY4wVZ3M6OLiws6dO/H3968xV5GR/Px8brjhBg4dOmTTjLVXA2mL/XIttcfStlRWVtbq4GooKSkpZGRkMHjwYNM+T09PoqKi2L59OyNHjmT79u2mYXMjgwcPRq1Wc+bMGYuu4+/vz2+//UZISMh1Ezfg2mqPtMU+aUhbGhM7bN4Bqio2rUl0aokvDAxDzs8++yzdu3dHr9fz6quvctttt3Ho0CHTijIHBwdUKhULFiwwLX11cXFhwoQJFv9BMjIyalz1URs33HCDxefaO9IW++Vaao+lbbGFC8yYy6dqNufL8/xkZGTg5+dHQUGBSYaq1Wrx9vYmIyOjxthhbR4gI9fSf0+4ttojbbFPGtIWu3CBKYpikej0wQcfrNMXBoakiJezePFi/Pz8SEhIoG/fvoChg+Xn59coGaqlTp+B727mbH4py5/pSccWnhbVLQhC/TSFC6w+VCoV3bp1Y8OGDWYTqI8cOWK2baRqHqDc3FxCQkLqd4EdyuSF5Ync1NKTb57uacsmCMJ1j125wCwRncbHx/Pqq6/W6QurCeNwtbe3t9n+oqIiPv74Y1atWsWQIUOorKxskAw1P9+w/Ls+p4+HhwfZZYWonVzE6SMITYAt0igYR28yMzMJDAw07c/MzKRLly6mc86ePctbb71FbGwskZGR3HzzzWRnZ+Ps7Fxj7KgtD1B9cSPItxy1kwtFOErcEIQmwprY0eQdoJoIDw9n3rx51XxhX375Za3v0isrK5k4cSK33HILnTp1Mu1/6KGHmDJlCvHx8Xz++ed8+eWXNGvWrE6hobVD2UZ9RVF5RT1nCoJwtQgLCyMgIIANGzaYOjx5eXns2LGDcePGARAdHU1OTg5t27bl3Xff5fXXX+fMmTMoisLy5cstkqFaio+bYfQ7M69UVBiCYEfUPnPPBmRnZ7N7924SEhI4d+6caX9dvrDaePbZZzlw4ADLli0z2//MM88QExPDjBkzyM7OZsOGDVy4cAEfH59a65oyZQq5ubmmkpqaalF7XC52gIrLpAMkCFeTgoICEhMTSUxMBAwTnxMTEzl16hQqlYqJEycyffp0/ve//7F//35Gjx5NUFCQ6dVWhw4duP3223n66afp0aMHS5cuJSwsjFGjRnHHHXfY9F5b+bjiqFFTUKo3qXEEQbj6NMkqsPpEp5b4wi5n/Pjx/Pjjj2zZsqXeSU5RUVGAIZlimzZtajzH2pT2Pm6Gz6TnljT4s4Ig2I7du3czYMAls7pxbk5sbCyLFy/m5ZdfprCwkGeeeYacnBx69+7N2rVrzeLON998w/jx4xk0aBBqtZp7772XDz/80Ob36qBR0z7QnX1puWxNziakeYjNryEIQsOxeQfIEtFpZWVlvb4wgO+++44JEyawatUqNm/eTFhY7cnUjD4f4yhSdna2rZtGuL87Px/I4FhGfv0nC4LQZPTv37/OxGcqlYq33nqLt956q9ZzvL29Wbp0qSl2LF26lIMHD/LRRx81aFWoJdzROZB9abnMXX+M3m19mlSKLAiCZdhchfHPf/6T9evXVxOdAhQXF9O7d2/Ky8vp1q1bvXU5OzuzdOlSvv/+e7PcP56enjg7O5OcnMzSpUvRarXExcUxduxYVq9eTXl5OSUlJRb7fCxNpf3z/nTGfbOHQE8dayf2xdPZod66BUGon8aks28My5cvZ/To0Xz66adERUUxd+5c/vvf/1oUOxpyz0VleoZ/9DvJWYW4OWl5IDKYwTf4cWMLT9x1EkcEwVoaEzts3gEKDw/nrbfeYtSoUTUeX7ZsGe+88w579uyp/+ZqmSy4aNEiHnvsMVJTU3nkkUdMr9rCwsK45557ePXVV+nYsWOtLrCqWPoHLCmvoO87mzibX4qHTkuPsOYEezvTzMURd50WrUaNo0aFg0aNg0ZtMqkbW2Fojsr0+6X9l84zNtlwXCZLCn9/HLVqbmlb+5w8uHodoIZ6BC+nofd8JqeY8Uv3sOdUjtl+o2TYx80Rb1dHXJ20ODto0DkY/GDODhq0GrXJBaau4s/TqA0OPdXF7bqoL6JYMj+70b48CWuChbT1dat3tNSuXGBJSUm0bt3atF3VBRYZGcnx4zU7tapSX98sODiYX3/9FRcXF1asWGGWu6MuF1jVZfDG5fWWOH0+vLcdL/73T1LP5/FLYv3nC8L1jo+bI5tfGlDnOY3y+VhJQz2CjYkbAG5qWPhQJ35LymLt/gx2pJznbH4pZ7KKOJPVyMYIwjXISzERxPayrUfQjAbLM+oBUA4cOGDaruoCy8jIUDQajUV1zZgxQ4mMjFTc3NwUX19f5a677lKOHDlidk50dHQ1J8iYMWPqdIHFxcVddW+JFClSqhdrfD7W0lCPoMQNKVLst9iNC6ywsNDsqSg/P9+0nZeXZ3FPLT4+vl4VhpEffviByMhIwKDCmD59eq31Vs3oqtfrOXz4MMHBwdeN00faYr9cS+25Gi6wpkLihoFrqT3SFvvkSrnAmmQESKVSKWq1WlGr1dW2jb9bw9mzZxVAiY+PN+3r27evolKpzGzQiqIoo0ePVu68884a6xGrsxQp9lmu5AhQaWmpotFoGhQ7Lic1NfWq/72kSJFiKHYxAqRSqQgLC0OjMSQNTE5OJiQkBAeHxq90qEmFoVKp0Gg0jBo1ijZt2jB8+HCmTp1apwustkzQ9Tl9+r2ziXOFZXw3Lpp2AZLSXhBsha1dYFu2bGH27NkkJCSQnp7OqlWrzOYIKorC9OnTUavV3HffffTv35/58+fTpk0biz2CljoE/5d4mldXHSC6TXO+GB3Z6LYJgnAJu3KBTZs2jW3btnH06FEqKiqIjo6mf//+je4A1aXC6NWrF++++y633HILixYtYtmyZXW6wKoOZRv/gPU5fdw9PLigL0Lt5CpOH0FoAmyliSgsLOSmm27iiSeeYMSIEdWOv/POO3z44Yc8//zzfPDBB5w/f56BAwdy22231Rk7arrX+uKGj7fBH6jX6CRuCEITYRcuMK1Wy8aNG02i03Xr1hEREVGv6LQ+jCqM33//3Wz/M888A0BQUBCzZ8/m3Llz6PV6VqxYUavPx9pM0KLCEIS/B0OGDGHIkCE1HlMUhblz5/Laa68xefJkQkNDmTVrFmlpacTHx9fpEbQGZ0dDmC2SuCEIdoXNXWBLlixh3rx5rFu3ji+//JJ3332Xr7/+mqws69d5GlUYmzZtqlWFMX78eE6ePElOTg4Abm5uVl+vNkwy1DK9zesWBOHKkJKSQkZGBoMHDwYMsSM1NZW+ffsybNgwk06nKqWlpeTl5ZkVS7j04CRxQxDsCZt3gE6dOkWbNm3o27cv/v7+PPfcc+j1egICAhg4cCBHjx61uC5FURg/fjyrVq1i48aNdaowjBjliIGBgdY2oVbcnAxPcjnFNTvLBEGwfzIyMgCqjfL4+/ubjtXEzJkz8fT0NJXg4GCLrud6cQQoV+KGINgVNu8AlZeX8+CDD5KVlcWcOXNYs2YNOp2OV155hfT0dPr06cPZs2ctquvZZ5/l3//+N0uXLsXd3Z2MjAwyMjIoLjYYlZOTk3n77bdJSEjgxIkT/O9//2P06NH07duXzp0727pptPYxLL1PPltg87oFQbBvpkyZQm5urqmkpqZa9LnQ5oZMtheKyjlfWNaUtygIQgOweQdIURT0ej0RERHEx8fz2Wefodfr2b17NxEREZSXl9OnTx+L6po/fz65ubn079+fwMBAU1m+fDkAjo6OrF+/nttuu43w8HDuvfdeTp48SWFhITt37rR10wj3N8wy/zMtx+Z1C4JwZTDmC8nMzAQMIuVWrVqxYsUK4uPja40dTk5OpgnP9U18vhxXJy3B3s4A7D+da4MWCIJgC2zeAXJ3d6dLly54e3ubhoofeeQRgoKC8Pb2pnPnzhab2hVFqbE89thjgEGFER8fz7x581Cr1Xz++efs27ePm2++mZiYGItHmizllrY+qFTwx/HzTF21n41HMjmWmc/ZvBJKyivQV1Re0VT+giA0nLCwMAICAtiwYQPLly9n0qRJvPzyyzg4ONCxY8cmiR29L7rQXlu9n6U7TrH31AVSzxeRW1QucUMQrhI2l6GqVCr++OMP00TCqi6wpKQkIiMjTZOVbUFDhYZVnT7GZfCWyNTe++UoH21MqvMcB40KrVqNVqOqLjw1yk6r7jdtG2u5tKSv6mcE4e9Eczcnfn6+7lFfW8tQCwoKSEoyfE+7du3KnDlzGDBgAN7e3oSEhDBr1iz+9a9/4evrS7du3SguLmbfvn0cOHCA8PDwGmNHY+JGem4x983fzumc4lrP0agNYlPtxZ8adXWtaNWlvtWPV61VVedxiSmCPfP84HAejgqt8xy7kqGC+QqsgwcPmgUNd3d3CgpsN4emoUJDqD0RoiWrOp7uGcgNPg788OcZjmbkk5VfQl6JnsrLupGlF4sgCKAvcaz3u2VrGeru3bsZMOCSgNWY9ys2NpbFixfz8ssvk5eXx4wZMzhx4gR9+/Zl7dq1uLi41Bo7GhM3XFXwTWxnvt2Vyu6T5zmeVUBOsZ4yfaXpnEpApkkLwiXOX8ghL69ZnefYnQx1x44dJs2Em5ubkpiYaNo+duyY1SqMmmio0FBRRIUhRYq9FnuWoUrckCLFfotdqDDA8NrLOFRbWVlJ165dTduKotgs26u1VE2E6OLiws6dO/H3979upIbSFvvlWmrPtSRDlbhh4Fpqj7TFPvnbylBVKpXSunVrJTw8XAkPD1fUarXSqlUr07ax2IrGCg0VRaSGUqTYS7HVCFBcXFy1utu1a2c6XlxcrIwZM0YBFJ1Op4wYMULJyMhoUOyQuCFFiv0UuxgBsqUL7I033qj2zr1du3YcOXIEgJKSEl588UUAHnjgAYYPH868efPw9fW1WGgIlksNb50TT3puCUufjqJzS68Gt0cQhJqxtQwVoGPHjqxfv960rdVeCncvvPACa9asoX379nTu3JlTp04xYsQIfvvtN5vLUHccP8eTX+2mlY8LP06wLAWIIAiWYVcyVFu7wOoLYj/99BNTpkxh1qxZ/PnnnwwZMoTu3btbLDQEy6WGnp4eZJaoUTu6iNRQEJoAW74e12q1NQ6L5+bmsmDBApYuXUpFRQWxsbHExcXx6quvMmLECJvLUNu21KB2ciG7VIO7u/tVnwIgCNcidiFDNbrAxowZQ3Z2NsuXL2fixInMmjULX1/fht+gBUHsvvvuw9/fnxkzZpCcnExpaanNhYYALhdT2heK1FAQ7J6//vqLoKAgdDod0dHRzJw5k5CQEBISEigvL2fw4MF4eXmRlZXF7NmzAdi7d2+tsaOmZfCWEOChAwwy1LxiPZ4uDR8NFwTB9ti1CwwuBbHWrVvz8MMPc+rUKQCzIAYGoeGZM2cICQnhqaeeqlVoCNZLDd11hg7QBUlnLwh2TVRUFIsXL2bt2rXMnz+flJQU+vTpQ35+PhkZGTg6OuLl5QVcEil3796dkSNH1ho7rHWBOTtqTDqMbcmWJYEVBKHpsWsXWEOCmJH6hIZgfSBr42vIb5SUJS4wQbBnhgwZwv3330/nzp2JiYlhzZo15OTk8O2331pdp7UuMICYjoZR7HmbkynVywiyINgDdu0Ca0gQM/p8du/ezddff12nC8zaQBZhdIGl5lh0viAI9oGXlxcREREkJSUREBBAWVmZKRu9MXbs2rWLZcuW2dwFBvB0n9a4O2nZfzqXRxfs5EiGZaPOgiA0HTbvAHl7e9O1a1ebuMCqUlsQM/p84uLiCAgIIDQ0tE6fj7WB7Ja2zVGpYEfKeeZvThazsyD8TSgoKCA5OZnAwEC6deuGg4ODmQvsmWeeAaBLly5N4gLzdXfis0e74eygYWfKeW6f+xvDP/qdmWsO89O+dA6cziW3SPJAC8KVxOYuMDc3N3bv3k379u1rPN4YF1hBQQEhISG88cYbxMbG4uvry3/+8x/eeecdunfvzoQJE2jfvj1bt27l/vvvr9UFVpWGuESm/3iIL39PMW37ujsR4KHDy8UBnYMGZwcNOgc1Wo0atQrUKhVqlQqV6Xcubht+byjWLCCpbhRqqusIQnVcnLSM7demznNs7QKbPHkyw4cPJzQ0lDNnzhAXF0diYiKHDh3C19eXcePGsWbNGlxcXLjxxhtJS0sD4Pfff6/TI9jYez55rpBZa4/wy8FM9JXVQ6+jVo2HzgFPZy2ezg44O2pw0Khx1Khx1F76afAMXoorgOl31WW/U2WfNbHAHvi7Lpz7m9623dCvnS/dQr3rPMeuXGCFhYVUVFx6x11VhtoQF1hNQUyj0TBq1Cg8PT158sknmTRpEmlpaTzwwAM8/vjjREdH06tXrzpdYFVXc+Tm5gKWreoY37sF/i6VLNuRyl9nC8gsLSJT5jUKQq34uDnyUNe6V4Da2gWWlpbGqFGjOHfuHL6+vvTu3Zs//vjDtBL1/fffR1EUPvvsM1JSUhg6dCjz5s2r0yPYmLhhpJkD/Gt4OC8PCGHLX9kkpuZwLDOf0xeKOVdYRkkplBSCbcefBOHviUNlBOHN6u6mXLMusAcffFAJDAxUHB0dlRYtWigPPvigkpSUZDpeXFysxMbGKmDI5nrPPfco6enpiqLU7QKrKUusFClSrn6xZxeYxA0pUuy3WBM7bP4KTHXx9c7lLrDLt5WLLrDLR4kaw5kzZ2jRogXbtm0jOjratP/ll18mPj6eHTt2VPtM1Sc5vV7P4cOHCQ4Ovm6cPtIW++Vaak9DXWBdu3Y1S3balDQ0dkjcMHAttUfaYp9Y4wKzJnbYPNKo1WpWrlxpWp4+dOhQFixYQGBgoK0vBYCPjw8ajYbMzEyz/XXJ0apKDdPS0ujdu7fF17zhhhusu1k7RNpiv1xL7bG0LampqbRs2bKJ78ZAQ2OHxA1zrqX2SFvsk4a0xZrYYfMOkKIojB07lvz8fBRFobi4mLffftsscADs2bPHovq2bNnC7NmzSUhIID09nVWrVnH33Xebjjs4OODv78/DDz9MZWUlt9xyC5988kmTuMAGzN5EVkEZ/x3bkw6BnhbVLQhC/djaBXYlPIKWxo2f9p3hn9/tJyrMmwWPdbe2SYIg1IBducD69+/P5s2bad26NVqtluTkZBwdHbnrrrusqq+wsJCbbrqJJ554ghEjRlQ7/s4775CTk0NZWRlxcXFs3LiR7t27o1arbe4Cc/fw4Fx5ERonV3GBCUITYEtPVlN7BC2NG77exaidXCjT6CRuCEITYRcusNTUVObPn8+YMWMAWL9+PcOGDSMhIaHO9+S1MWTIEIYMGVLjMUVRmDt3Lm+++SY6nY7Zs2eTnp6OXq/nrbfesrkLzPmiC6xIXGCCYPfY2iNorQvMxUkDQFGp3sqWCILQFDSJC2zo0KEAZGdn4+XlhaIoHDx40NaXIiUlhYyMDAYPHmzy+ZSVldGnTx+ysrJq/Zy1LjAXx4uBTDpAgmD32NojaK1Cx9UoUZYOkCDYFTbvAOn1ek6cOGGSoUZFRVFeXk6XLl2skqHWhdH5VfVprT4fmLWBzNPZYHE+V1haz5mCIFxNmsIjaK1Cx8/DMP8xM79UPGCCYEfYvANUWVnJoEGD2Lt3Lx07dqRnz56o1Wratm3Lrl276Ny5M8OGDbP1ZU0+H51Ox4YNGzh//nyt51obyNr6GWSof2WKDFUQ7Jmm8Ahaq9AJ8NDh7qSlolIhJbuwUe0SBMF22LwD1KlTJzw8PLj77rvp1q0bERERjB49ml69enH33Xfj7u7eIItyXRjf7y9ZssTkAtuzZw+Ojo5s2bLF5i4wowz1j+PnqKwhjb0gCPaJrTyC1qBSqbghyBBjVu05bbN6BUFoHDafBF1SUsJHH33EqFGjajy+bNky3nnnHZtcKywsjICAAD755BOefvppHn/8cfLy8rhw4QKurq4sXLjQIheYpfRv54vOQc2RjHzumb+NvuE+BHu74KFzwEOnxclBjVqlQqtWo1Gr0GpUaNQqk6vHSE1z1atOYK/q7Klvgvvf1ZUjXPto1CoCPZ2v6j0YZaiPPvqomQx1zpw5PP300/Tq1Yv09HRWrFjB/fffb/PYMTq6FTtSzvPZluNsP36O7q28aeHljI+7k8kfqHPQ4KRV1+gPVKm46A80RAbjcaFu5G/098bT2QF3nUOT1W/zDlBSUhKtW7c2bVd1gUVGRnL8+HGL6ysoKCApKcm0nZKSQmJiIt7e3oSEhDBhwgSmTp2Kh4cH+/fvZ9q0aQQFBdGrVy+bu8AcgTdvb82rqw+wN+kMe5POWNwOQbhe8XFzZPNLA+o8x9YusKbwCDbGBdY71IVnbwni0/hkEpOLSExOt0k7BeFa5qWYCGJ7hdV5jt25wA4cOGDadnNzU5KTk03bGRkZikajsbi+TZs21ej9iI2NVRRFUdLS0hRA8fb2VpycnJRBgwYpR48eFReYFCl/w2IrF1hTeAQlbkiRYr/FmtjRJNKdwsJCs6ei/Px803ZeXl6Demr9+/ev83xj8qMff/zRzOdTF1OmTGHSpEmm7evR6SNtsV+upfY01AVWm76moSxbtqzO4zqdjhkzZvDVV1+xceNGi2KHxA0D11J7pC32iTUuMKtih7VPWLUBKCqVSlGr1Ypara62bfzdEmbMmKFERkYqbm5uiq+vr3LXXXcpR44cMTunb9++1XqCY8aMUUaPHq3ceeedFl0nNTX1qvdepUiRcmVt8KWlpYpGo1FWrVpltt/S2CFxQ4oU+yl2MQKkUqkICwtDozEkDUxOTiYkJAQHh4ZPZIqPj+fZZ5+le/fu6PV6Xn31VW677TYOHTqEq6ur6Xq+vr7ccccdzJgxAzA83XXq1MnmLrAHPt3OofQ8/nl7Ox6NbtXg9giCUDO2doHV5xBUFIXp06ejVqu577776N+/P/Pnz6dNmzY2d4Gt3nua11YfoFfb5nz+aGSj2yYIwiXsygU2bdo0tm3bxtGjR6moqCA6Opr+/ftb1QFau3at2fbixYvx8/MjISGBvn37mvZHRkaydOlS+vXrR48ePZg7d67FPh+w3OnzcJ92TPv+IAt2ZnJ/dAR+HroGt0kQhNqxlQvMEofghx9+yPPPP88HH3zA+fPnGThwILfddpvNXWA+3oWonVyoEBeYIDQZduEC02q1bNy4kcGDB+Ps7My6deuIiIhg4cKFja7buOrC29vbbP+uXbvQarU8/fTTVFRU0LVr11p9PmC902dkjxC+2XGKIxn5PLVkN/9+KgqPJlyiJwiCdVjiEHzttdeYPHkyoaGhzJo1i7S0NOLj4+uMHdbgLAodQbBLbJ4IccmSJcybN49169bx5Zdf8u677/L111/X6eayhMrKSiZOnMgtt9xCp06dTPsfeugh/v3vf7N9+3YWLVpEYGAgISEhtfp8wHoVhoNGzWePdqOZiwP70nJ54NPtnDpX1Kh2CYJwZbncIQgGF1hqaip9+/Zl2LBhtcYOqx2CDoYOULF0gATBrmgSGWqbNm1MLrDnnnsOvV5PQEBAo1xgzz77LAcOHKi2uuOZZ54hJiaGG2+8kYcffpglS5awatUqkpOTa63LWhUGQGhzV/79VBS+7k4cychnyAdb+GrbCcorKq1qlyAIV5Yr7RB0dTIMtOeLDFUQ7Aqbd4DKy8t58MEHycrKYs6cOaxZswadTscrr7xCeno6ffr0aXCa+fHjx/Pjjz+yadMmWrZsWee5xqe3y5MnVsVaFYaRjkGerH72FnqEeVNYVkHc/w4yeE48i7emkFtc3qC6BEH4e2Dtg1PLZoYs2Fn5peSXSHwQBHvB5h0gRVHQ6/VEREQQHx/PZ599hl6vZ/fu3URERFBeXk6fPn0srmv8+PGsWrWKjRs3EhZWe0ZIo9CwWbNmAGRnZ9ukPbXRwsuZ/zzdk7fv6oiPmxMnzxXxxg+H6P5/63ls0U6WbD/BoTN5MjIkCHaGMV9IZmYmcCl2rFixgvj4eJvLUL1cHPFzNxjhj2Tk26AFgiDYApWi2Cj3/EU8PDzo2rWrmQ7jco4fP86BAwc4d+5cvXX94x//YOnSpXz//fe0a9fOtN/T0xNnZ2eSk5NZunQpWq2WuLg4xo4dy+rVqykvL6ekpISjR4/i5+dX73Xy8vLw9PQkNzfXqlUahaV6ViSksXTHKY5mmgc4J62a9gHuBHu7EOLtQstmLjR3c8TL2YFmro54uTjg5qTFSatBoxZxjXB90tjvYF2oVCqzZfCKohAUFMTkyZNp2bIlo0eP5v333+eFF16gd+/e7Nmzx6LY0ZB7/sc3CazZn8HNIV5MGdqBGwI9TK/GBEGwnsbEDpt3gFQqFX/88YfpVVRVF1hSUhKRkZHk5ORYVFdNLFq0iMcee4zU1FQeeeQRtm7dChjkqPfccw+vvvoqHTt2ZMKECTUKDWtaBRYcHNzo4KsoCn+dLWDjkbNsOZbF/rTcBr33d9CocNIaxIhOWg0OGhXqizJVzUX5oVGuatiP6ViNhlVq3W04Vutnaj5Q6/kNrEe4vvB0ceCTh26u8xxbd4Audwh27dqVOXPmMGDAAJNDcNasWfzrX//C19eXbt26UVxczL59+zhw4ADh4eE1xo7GxI0jGXmMmLfNbCWYs4MGd50WNyctGrXqkkBZpTJtm32HqgmTL/u9DplytWOqms8TBHvjoagQht4YWOc5jYkdTfII4ubmZvr94MGDZkHD3d2dgoICi+qpr28WHBzMr7/+iouLCytWrDBLdFab0BAMkxnffPPNavstXdVRFwHO8FBXXx7q6ktlpcKpC0X8lVnAmZwi0i4UcyanmAtF5eQWl5NTVEZeiR5jM0svlsbfhSDYDz5ujuTlta3zHFvLUHfv3s2AAZcErEaFRWxsLIsXL+bll18mLy+PGTNmcOLECfr27cvatWtxcXGpNXY0Jm4EucCSRzvxxZYUdp04T3ZBGYWlUGhZKBSE65KoljryQl3rPMfuZKg7duxQcnNzldzcXMXNzU1JTEw0bR87dsxiFYaiKEp8fLxyxx13KIGBgQpQLW29UYbavHlzRafTKYMGDVKOHTtWpwy1pKTEdD+5ubnKoUOHrnoabylSpFxZFcbp06cVQNm2bZvZ/tpih8QNKVLst9iFCgMMr72Mr68qKyvp2rWraVtRlAZlbKwvo+u8efMAeOmllxgyZAjTpk0jJibGbDSoKk5OTjg5OZm2XVxc2LlzJ/7+/teN1FDaYr9cS+25WjLUpkDihoFrqT3SFvvkbytDValUSuvWrZXw8HAlPDxcUavVSqtWrUzbxmINYD4CVFlZqQQEBCgqlcq0PycnR3FyclL69OkjMlQpUv5mxVYjQHFxcdXqbteunel4cXGxMmbMGAVQdDqdMmLECCUjI0NRFJGhSpHydyx2MQJkSxdYfRgzunbs2JENGzZw99134+npSVRUFAkJCbz22ms1fq7qZEbl4rvD+qSGRlbuSeP17w8CcNsNfvRs40NOURlbk86RcPKC6bxb2jbn2QFt6dzSqxGtFIRrH1vLUAE6duzI+vXrTdta7aVw98ILL7BmzRrat29P586dOXXqFCNGjOC3336zuQz15/3pvLRiH91bNWPR4z0a0SJBEKpiVzLUpnSBVcWYtXX8+PFMnDiRyMhIevToQVpaGmVlZbUKDWubzGhJbo/sglLe25yK2smF5waFM+nWCNOxyUByVgGfbEri+8QzbE8tZvuS/Qxq78cLt0bQqYWn9Y0VhOsAW8lQwRCLahoWz83NZcGCBSxdupSKigpiY2OJi4vj1VdfZcSIETaXofo2L0bt5EK5yFAFocmwCxmq0QU2ZswYsrOzWb58ORMnTmTWrFn4+vra+nIA3HXXXej1el5//XUyMjJwc3MzqThqYsqUKaZVIXCpB2kJX28/SX6Jno5BHjw/KLza8Ta+bsx5oAvPDwrnww1JrNqbxoYjZ9lw5Cy33eDPxMER3BAkQVAQmpq//vqLoKAgdDod0dHRzJw5k5CQEBISEigvL2fw4MF4eXmRlZXF7NmzAdi7d2+tMlRrJcoujoYwWygqDEGwK/42LrCauDyj6/jx4zl58iSlpaV06tSJjh071vo5azO6lldUsnTnKQDG9W9TZ+LC0OauvPfATayf1I+7uwShUsEvhzIZ+uFvPPXVbjYfPUtlpdKA1gqCYClRUVEsXryYtWvXMn/+fFJSUujTpw/5+flkZGTg6OiIl5cXgCl2dO/enZEjR9YqQ7XaBXaxA5RfIh0gQbAn/hYusNoICwsjICCADRs2mPbl5eWxY8cOoqOjbXKNy9l14jxZ+aU0d3UkpqNlM85b+7oxd2RXfn2hL8NvMnSE1h/O5LFFu+g7exNzfj3G4fQ8m+U/EQQBhgwZwv3330/nzp2JiYlhzZo15OTk8O2331pdp7UusBYXXWBn80tlFEgQ7Ai7doGBIaNrYmIiiYmJgGHic2JiIqdOnUKlUjFx4kSmT5/OmDFjCAoKMrnAjJmnbUn80SwA+rXzxUHTsD9dWz93Phpl6Ag91qsVHjotaReK+XDDXwz54Df6v7uZ11bv539/niEzr8Tm9y4I1zNeXl5ERESQlJREQEAAZWVlpmz0RhfYrl27WLZsmc1dYN6ujvi4GZbPH8sUF5gg2As2V2E0b96cG2+8sVZxaUNcYACbN282y+hqxJjRVVEU7rvvPlauXIlWqyUyMtKUIdrWLrB75m1l76kc5j7Yhbu7Nq6DVVxWwdqD6azZn8GWY1mU6s2lqX7uTkT4uxPh704bP1eCvJwJ9NQR6OGMh7PWppNFBeFq05QuMDA8SIWEhPDGG28QGxuLr68v//nPf9Dr9YwePZq4uDimTp3KnXfeyZYtW2zuAnvqq92sP5xJTEd/3n+wi2lekCAIjcOuXGBubm7s3r2b9u3b13i8IS4wS4mKiqJ79+58/PHHgCExUnBwcK0usKpY8gdUFIVOcesoLKvg1xf6Eu5vu+W6RWV6fvsrmx3Hz7PzxDkOncmjrulBTlo1ns4OeDg74KHT4uHsgLvOASetGketGkeNGiet+tK2Vm3wh6kM/jCV2U/j7zVs29ATZK/9NelINj1OWnW9r4xt3QGaPHkyw4cPJzQ0lDNnzhAXF0diYiKHDh3C19eXcePGsWbNGlxcXLjxxhtJS0sD4Pfff7c4djTknhNOnueBz/6golLB2UFDpxYeBHo64+PmhLOjGp1Wg9NFB6BabfjmqS/6/9QXv4uqy767xmOCdcj3/u/BDYEetPVzq/Mcu3KBFRYWUlFxSfhXVYbaEBeYJZSVlZGQkMCUKVNM+9RqdZ0usKqrOXJzc4G6V3WcvlBEfn4+DhoV3o4VNvGGXU50sAvRwS7QryWFpXqSswpIyizgr6wCTp4rJDOvlMzcYnKK9RSXQnEhZNj0DgShafBxcyT6peqjuJdjaxdYWloao0aN4ty5c/j6+tK7d2/++OMP00rU999/H0VR+Oyzz0hJSWHo0KHMmzevzthhTdwwEt5My/v3RDBr7RFSz+ez46i8ChOE+ngpJoLYXjW/TTJyTbvA6qOhPh9FqTlLrBQpUq5+sWcXmMQNKVLst9hFJmiwrQusKaiaB0iv13P48GGCg4OvG6ePtMV+uZbacy25wCRuGLiW2iNtsU+ulAvM5h0gtVrNypUrTTk2hg4dyoIFCwgMDLT1pQDw8fFBo9GQmZlptr+uP0hVqWFaWhq9e/e2+Jo33HCDdTdrh0hb7JdrqT2WtiU1NZWWLVs28d0YaGjskLhhzrXUHmmLfdKQtlgTO2zeAVIUhbFjx5Kfn4+iKBQXF/P222+bBQ6APXv2WFTfli1bmD17NgkJCaSnp7Nq1Soz07uDgwP+/v48/PDDVFZWcsstt/DJJ59Y7PMBy50+8zcl88nmJHQOalQqKC4zrNy69+YWTLq1HZ4utvedCcL1gK1dYPXFDUVRmD59Omq1mvvuu4/+/fszf/582rRpY3MX2A9/nmbKygNEt27OF7GRjW6bIAiXsCsXWP/+/dm8eTOtW7dGq9WSnJyMo6Mjd911l1X1FRYWctNNN/HEE08wYsSIasffeecdcnJyKCsrIy4ujo0bN9K9e3fUarVFPh+w3OmTkFGC2smFN+65kZiO/rz36zGW7jjFqoMX+P3UXt66syNDbmyakS5BuB6w1etxS+LGhx9+yPPPP88HH3zA+fPnGThwILfddpvNXWDNmxVddIE5iQtMEJoIu3CBpaamMn/+fMaMGQPA+vXrGTZsGAkJCXW+J6+NIUOGMGTIkBqPKYrC3LlzefPNN9HpdMyePZv09HT0ej1vvfVWrS4wazmSbphtfnOoF83dnJhxz43c07UF//xuH8ezChn3zR5uu8Gft+7qRICnzqbXFgTBciyJG6+99hqTJ08mNDSUWbNmkZaWRnx8fK0uMGtxcdQAUFRWUc+ZgiBcSZrEBTZ06FAAsrOz8fLyQlEUDh48aOtLkZKSQkZGBoMHDzb5fMrKyujTpw9ZWVm1fq60tJS8vDyzYgkl5YZXXh66S6+6urfyZs1zfZgwsC1atYpfDmVy65x4/v3HSSrE9SUIdsflcQMMLrDU1FT69u3LsGHDanWBWRs3jB2g4nLpAAmCPWHzDpBer+fEiRMmGWpUVBTl5eV06dLF5jLUjAxDJpyqT2v+/v6mYzVhjdRQURTKKgwdICet+Z9N56Dhxdva8eNzvbkp2Iv8Uj2vrT7AwPc28+8/TlIsT36CYDdcybgB4KYzDLTnFpdbeceCIDQFNu8AVVZWMmjQIPbu3UvHjh3p2bMnarWatm3bsmvXLjp37sywYcNsfVmTz0en07FhwwbOnz9f67nWSA0vV1U4OWhqPKd9gAcrx/Xi9TtuoJmLAyfPFfHa6gNETv+VSd8msvnoWekMCYKdYYwd3333HevXr6/VBWatDDXU2xWVCnKKyskuKK3/A4IgXBFsPgeoU6dOpKenM2TIELRaQ/URERGAYXTo559/tjhw1IdxqeqSJUt4/fXX+fTTT4mKimLQoEFs2bKFs2fP1ujzqbqc1RLMOkDa2vuNGrWKJ3qHMbJHMMt3pbJo6wlOnS9i5Z7TrNxzGketmsjQZnQLbUbHIA9uCPSkZTNn1GpJzS4IVwJj3MjMzGTLli1MmjSJTz/9lHnz5lFcXExMTEyNLjBr4gaAs6OGEG8XTp4r4s/UHAZ1sO3cREEQrMPmHaCSkhI++ugjRo0aVePxZcuW8c4779jkWmFhYQQEBPDJJ5/w9NNP8/jjj5OXl8eFCxdwdXVl4cKFFrnALKFUbxi5UatAa0FnxcVRy+O3hPFYr1bsOXWBlXtOs+nIWc7klrAt+Rzbki/JYB01agK9dLTwcibIy5nmro54ujjg5eyIl4sDbk5anLRqdA6XfEE6B4PzS6NWoVKp0KgvOYLUl21f7aSTgmBvGOPGhg0b+Pbbb3n66ae59957GTduHAsXLuSll16yaewA6Bfhy5LtJ3l11X6eOFvADUEe+Lg54a7T4uakRaNWoVUbvs/y3RWEK4PNO0BJSUm0bt3atF3VBRYZGcnx48ctrq+goICkpCTTdkpKComJiXh7exMSEsKECROYOnUqHh4e7N+/n2nTphEUFESvXr0sdoFZMpmxtNw4/0fToMCkUqnoFupNt1BvFEXheHYh25KyOXA6j0PpeRzNyKesopKT54o4ea7I4nobgimg1ic3reNwfS2u709S37Ul1l+7+Lg5seXlul1gtqa+uDFx4kSmT59OXl4eDz30EKNHjyYoKIgRI0awbt06i1xgDfEBThgYzm9/ZZOSXcjMn49Y9BmN2vxbU/U7Yna02jHLPiffO8GeeTmmHY/dUrcLrDHY3AavUqk4cOAAHTt2BAzJwv78809TpygzM5MWLVqg1+stqm/z5s0MGFA9eMbGxrJ48WJOnz5Ny5Yt8fb2prCwkN69ezNv3jy+/PJL4uPj2bFjR7XPvvHGG7z55pvV9teV0Cw5q4C7Pt6Kh07LtimDLLp3S9BXVJKZV0J6TglncovJyCshp6ic3OKLpaicovIKSvUVlJZXUqavoFRfSam+kvIKWWUm2D8+bo5stkCGGhwcTE5ODp6eno2+Zn1xQ1EUoqOjq8WHdu3aceedd9YYO6yJG5eTX1LO94mn2XXiPCnZReQWlZNXoqe8orLezwrC9YilMlSrY0eD7WH1APYvQy0pKTHdT25urnLo0KGrLnKTIkXKlZWhTpo0SQGUH374QUlPT1fS09OVrKysWmOHxA0pUuy3XHMy1JkzZ7Jy5UqOHDmCs7MzvXr1YtasWbRr1850jnGuUa9evUz7xowZQ3FxscUuMBcXF3bu3Im/v/91IzWUttgv11J77FmG6uLiAhgWZ1x+XUtdYNdj3IBrqz3SFvvkSslQbT4CpFKplNatWyvh4eFKeHi4olarlVatWpm2jcUSYmJilEWLFikHDhxQEhMTlaFDhyohISFKQUGB6Zx+/fopvr6+yuOPP256irtw4YLSokULZebMmRZdJzU19ar3XqVIkXJlR4Di4uIUtVqtuLi4KGFhYcpDDz2kpKSk1Bo7ZARIihT7LXYxAjRt2jS2bdvG0aNHqaioIDo6mv79++Pg0HBR6Nq1a822Fy9ejJ+fHwkJCfTt29e0PzIykqVLl9KvXz969OjB3Llz6/T5VJ3MqFycBlXfu/xlu04x/cfDuDiq+XZsL1o1d21wmwRBqI6tZaiWEBUVxXPPPccnn3zCiBEj2LBhAzfeeCMajabG2DFz5sxGzQG6UpTqK/hpXzpfbz/JX2cLTPs1ahU3tvCkc0tPWvu4EtzMBXdnLc6OGvQVCsXlFWQXlHH6QhEnzhVy8Ew+RzPyq81RCvdzY2B7PwZ18KNDoIesVhOuKnYlQ9VqtWzcuJHBgwfj7OzMunXriIiIYOHChY2uOzc3FwBvb2+z/bt27UKr1fL0009TUVFB165d6/T51BbI6pMaPjmgI7/+lceuExf4x7eH+e/YaAI9nRvRIkEQLudK/mNq9IW1adPG5BGsrKzkn//8Z42xY8qUKUyaNMm0bQy89cWNK0V+STlLd5xi4dYUMvMMD3g6VzcGtffjri5B9A73xc2pYSG/TF/JvrQctvyVzW9/ZfFnag7JuZUk78jgix0ZtPBy5raO/sR0DCAytBlajc1z6wqCRVgTO2y+Ciw8PJzJkyczZswYsrOzWb58ORMnTuTMmTP4+vpaXW9lZSV33nknOTk5/P7776b9n3/+OaGhoQQFBbFv3z7++c9/0qNHD1auXFlrXTUtZw0ODiY3N7feQHY2v4QHPt3OiXNF+Hs48dmjkXQJ9rK6XYIgGL6Dnp6eFn0Hm5Lu3bszePBgZs6cWe+59nLPZ/NKWLj1BN/8cZL8UsPqWn8PJ57sHcaD3UPwdG746Htt5BSVsfHIWdYdzCD+WJbJjwjg7erIoPZ+DOrgT+9wnwZ3tgTBGhrzPbR5B8jJyYmffvqJt956i61btwKGzotaraZfv37Mnz/fbBKzpYwbN46ff/6Z33//nZYtW9Z63saNGxk0aBBJSUm0adPGorob+gdMu1DE44t28dfZArRqFc/0bc2EgeE4O9asyBAEoW7soTNRUFBASEgIb7zxBs8991y951/te046W8CXvx1n5Z7TJk9hWz83nunbmru7tMCxjoz1tqC4rILf/spi3cFMNhzJJKfokuvMQaOieytvBrTzY0B7X9r4usmrMqFJsKsOkFqtplmzZvj5+TF27Fjat2/P3XffzaRJk1i5ciXnzp3jwIEDNSoqamP8+PF8//33bNmyhbCwunMCFBYW4ubmxtq1a4mJibGofmv+gPkl5fzzu32s2W+QJ/q4OfJk79Y82D0Yb1dHi+oQBMHA1ehMTJ48meHDhxMaGsqZM2eIi4sjMTGRQ4cOWTRafTXuWVEUth8/x5e/pbDxyFnT/sjQZozp14ZB7f2uilZHX1HJzpTz/HIok/hjWaRkF5od9/dwonsrb1NpF+CORvQ/gg1ozPfQ5mOUiqKg1+uJiIggPj6e+Ph49Ho9u3fvJiIigi1bttCnTx+LrPCKojBhwgRWrVrF5s2b6+z8fPLJJ8yePZszZ84AkJ2dbbM21YS7zoF5D3dj3cEM3vrhEKdzipm19gjv/XKU/u18GdDej15tfGjV3EWefATBDklLS2PUqFFkZWWhKAqKotCpUydSUlIa9bq+KUjPLWbVXoNPMOnixGaVCgZ38GdM39ZEtvKup4amRatR06utD73a+gCQkl3I5qNn2XQ0iz+OnyMzr5Qf96Xz4750AFwdNbQP9KBDoDsdAj1oH+BBmI8rzVwcJF4KVwybjwA1b96cG2+8sdbOyvHjxzlw4ADnzp2r8fjl/OMf/2Dp0qV8//33Zq/NPD09cXZ2Jjk5maVLl6LVaomLi2Ps2LGsXr2a8vJySkpKahQa1kRjn+TKKypZvfc0i7ed4OAZ8/T4Pm6OtAtwJ8LfnVbNXfH30BHoqcPfQ4eXiwNOWrV84YXrnqv1Omn58uWMHj3aJFKeO3cu//3vfy2KHU11z4qikJFXwuF0w4KLLceyzOKKzkHNfd1a8mTv1oT52P9K1OKyChJTc9h94jw7T5xnz8kLFJZV1Hiuu5OWYG8XQrxdDF5EN0d83ZzwcXfEx82JZi6OuDppcXXS4KSVKQfCFXwFtnHjRvr27WuyvNeEl5cXu3fvpm3btjUeT0pKIjIykpycnPpvrpaOwaJFi3jsscdITU3lkUceMc01CgsL45577uHVV1+lY8eOTJgwoUahYWMmQdfHX5n5rNmfwbbkbPaeyjG9m68NrVplECLqtLg5OeCoVeOoUeGgUV8sl343uYEuer1UKoPzR626+PvFg8b9qotyVMPv0skSrg7uOi0v3lb3vL+r1QGKioqie/fufPzxx4BhvmJwcHCNscPauPHDn2dIOHmBikqFCkWhslJBX2n4WaFc+j2nqJysglIy80rIL6muCurRypt7u7Vg6I2BuOtsN7H5SqOvqCQlu5BD6QYf4uH0fI5m5JlWrlmKg0Zl6Aw5anFx1Bji5MX4qVVf+t1Bo0arUV/0IRpi4uUxVH15PL0ooTXGTxUipr2a3NbRn15tfOo854q9Arv11ltJT083PRlVFZ2CIYNjXTfh7u5OQYFhCHfLli3Mnj2bhIQE0tPTWbVqFXfffbfp3MrKSuLi4vjiiy/IycnhlltuYf78+YSHhwMQHBzM8uXLCQoKQqfTkZWVxblz59BqtQwePLhWGWpty+AbIjesDX9neLyHP4/38KekvIKks/kcyywg6WwBZ3KKycwzBLjsglIqFSgDzhVD/eNhgvD3xMfNkad7BtZ5jvG7Z+nzWH2xQ1GUOmMHQEZGBrt27WL//v38+9//5t577+WDDz6oNXZYGzc27T/JioQ0i9plRKNWEebjQodAD3q1aU50ax983A1ZqJWyYvLKihtUn73h7wz+rd0Z0PpS7paS8gpO5xSRdqGY1PNFZOaXcr6gjHOFpZwrKONcQRm5JeUmMXUpUFoE569SG4Smp7mjnk6+dc+pbWjsMKMhWRNVKpWSmZlp2nZzc1OSk5PNzlGr1UpSUpJZxtTLy+UusDVr1ihTp05VVq5cqQDKqlWrzOr617/+pXh6eiqrV69W/vzzT+XOO+9UwsLClOLiYtM5AwYMUADliy++UH777Telbdu2yqhRo8QFJkXK37BYms31asQOiRtSpNhvsYtM0IqiEBERUedx43CiMRFZbefNnTuX1157jbvuuguAJUuW4O/vz+rVqxk5ciSHDx9m06ZNAHTs2JHo6Gg++ugjhg4dytixY2u9B3H6SFvsmWupPU3lArsasUPihoFrqT3SFvvkSrnAGtQBUqlUZu9Cq24DpqDSWFJSUsjIyGDw4MGmfZ6enkRFRbF9+3ZGjhzJ9u3b8fLyIj8/n8zMTAAGDx6MWq3m8OHDtf5Bqr7LP336ND169LD43m644QYrW2V/SFvsl2upPZa2JTU1tc48X5bQVLFD4oY511J7pC32SUPaYk3saFAHSFEUBg0aZJoEXVRUxPDhw3F0NH9H9+CDD/K///2PsrIyBg0aRFxcHM7ODVNGZGQY8utUTUnv7+9vOpaRkYGfnx8RERFs2LCBu+++G61Wi7e3N3v37q1xAjRY7/S5dU486bklfPNUD24Kbtag9giCUDu2dIE1VeywNm6sO5DBi//9k26hzfjqCcs7TIIg1M8Vc4HFxcWZbRuHly8nPj6eV1991eQC++CDDzh79qxNXGC1MWnSJGJjY4mMjKRHjx7k5+ejUqlqlaFa6/TxbuZFZkkelQ4uduH+EYRrjSu92qYhscPauOHvU4rayYViHCVuCEITYU3saFQHqCbCw8OZN28eY8aMAWD9+vUMGzaML7/8ss735FUxDkFnZmYSGHhpBUlmZiZdunQxnXP27FkefPBBsrKyeP3110lPT6e8vJx//etftcpQq77LtxQPneHPdaGwrMGfFQThytBUscPquHHRxZVXXF7PmYIgXEmslsVkZ2eze/duEhISzJIanjp1iqFDh5q2Bw8ejEqlMmVotpSwsDACAgLYsGGDaV9eXh47duwgOjoagOjoaHJyckhISGD8+PGcPHmSH3/8EZVKxaOPPmpt02qlVXND0jFjJlZBEOwPe4sdLZsZXv+n55VQVFY9v48gCFeHBq8CO3jwIOPGjTMlHzRiFJ3q9Xp0Op3ZMQcHB8rLqz/9FBQUkJSUZNpOSUkhMTERb29vQkJCmDhxItOnTyc8PJywsDCmTZtGUFCQKd9Hhw4duP3223n66af59NNPKS8vZ/z48YwcOZKgoKCGNq1eOgQa3jHuP51r87oFQbCcv1Ps8HFzwtfdiaz8Uo5k5HNziMwfFAR7oEEdoIyMDPr164evry9z5syhffv2KIrCoUOH+OKLL+jTpw+VlZU89thjZkPFJSUljB07FlfXS2nbV65cye7duxkwYIBpn/H9emxsLIsXL+bll1+msLCQZ555hpycHHr37s3atWvNOljffPMN48ePp2/fvpSVlaFSqfDw8GDnzp0NWqFhCdEXM1JuTcrmWGY+Ef5/76WGgvB35e8WO24O8WLdwUz+uztNOkCCYCc0SIXxz3/+k/Xr17N169ZqozzFxcX07t2b8vJyunXrVm9dixYtavjd1kJjfD7QsFTajy/ayaajWXi7OvLC4HBiOgXg566r8zOCINTNte4C25aczUNf7ADg4agQHr8ljDa+rqJYEIRGcsVcYDfffDOvvPIKDzzwQI3Hly1bxrRp0zh8+HCdvjBb0xCfT0005A+YXVDK6AU7OZR+Kf19Cy9nWvm40NLLBS8XBzycDcXZQYODRoWj0eulNbi9NBfzJ13u7KImt9fFfUC1bUGwBHv4/4tWraKtX92jpX8HF1hVGnrPH6z/i/fXHzNt+7g50tbPjSAvZ/w9dLg5aXFz0uLqpMXZQYNWo0KrVqFRG9xWGrUKrUZ1yQnIpZUvl7Yv/uTyfG3m91H1nMtjjCDYE75uTjR3q3vhwRVzgR0/fpybb7651uORkZEkJSVx/vz5On1htqSsrIyEhASmTJli2qdWq+t0gVVNaJaba5jTY4kLzBFY/EgnvktIZVXiGY5m5JOaWURqpti8BKEmfNwc2fzSgDrPaZTPx0oaGjsaEzfA4Ajs0FzLwm0p7Eq5wNlzRZw9l9O4RgjCNcxLMRHE9gqr85wr5gJTq9VmLrCqZGRkKEC9vjBbcvr0aQVQtm3bZra/LhdYXFzcVfeWSJEipXqxxudTEzNmzFAiIyMVNzc3xdfXV7nrrruUI0eOmJ0THR1d7fpjxoypNXZI3JAixX7LFXGB5efnV5v/Y8QWNvUrQdWEZnq9nsOHDxMcHHzdOH2kLfbLtdSepnKB1Ud8fDzPPvss3bt3R6/X8+qrr3Lbbbdx6NAhs8UYAD/88AORkZGAwe81ffr0GuuUuGHgWmqPtMU+uVIusAbb4NVqda1FpVIpgHL27FnTZ9zd3ZXjx483uGdmKaWlpYpGo6lmgx49erRy5513WlRHamrqVe+9SpEixXYjQFU5e/asAijx8fGmfX379lVUKpXFsUNs8FKk2G9p8hEgS0SnAwYMsMgXtmfPHouuuWXLFmbPnk1CQgLp6emsWrXKlMsDDDmG/P39efjhh6msrOSWW27hk08+YcOGDYwfP96iaxh7mPU5ffrO2sj5onJW/iOaCH9JaS8ItsKWLrCaMM7X8fb2Nu1TqVRoNBpGjRpFmzZtGD58OFOnTq01dljrAvt+72mmrj5AdJvmfDE60gatEQTByBVzgfXu3Zt33323TtGpJb6whlBYWMhNN93EE088wYgRI6odf+edd8jJyaGsrIy4uDg2btxI9+7dUavVtbrAqmJcSVGf08fNw4OcimLUTq7i9BGEJqAploVXVlYyceJEbrnlFjp16mTa/9BDD9GrVy/effddbrnlFhYtWsSyZcsoLCy0qQvMx7sQtZMLFRqdxA1BaCKa3AU2Y8YM3njjjTpFp5b4whrCkCFDGDJkSI3HFEVh7ty5vPnmm+h0OmbPnk16ejp6vZ633nqrVheYtbg4agAoLquwab2CIDQdzz77LAcOHOD333832//MM88AEBQUxOzZszl37hx6vZ4VK1bY1AXmfDFuFEncEAS7okEusCVLljBv3jzWrVvH6tWr+eGHH/jmm2+orKys8fzafGG2IiUlhYyMDAYPHmzy+ZSVldGnTx+ysrJq/VxpaSl5eXlmxRKcHS++1pNAJgh/C8aPH8+PP/7Ipk2baNmyZa3nnDx5kpycHADc3Nxseg8uF+NGcbnEDUGwJxrUAbJUdHrw4EH69u2Lv78/UVFR9OjRAz8/PwYOHMjRo0dtc+cY1BxAtac1f39/07GamDlzJp6enqYSHBxs0fXcnAxPcvklYnUWBHtGURTGjx/PqlWr2LhxI2FhdecSAUhMTAQwM8jbAteLcUNs8IJgXzToFZglolNLfGEHDhywSFHRVNT2Lr8+Qrxd2Mo5UrILm/L2BEFoJM8++yxLly7l+++/x93d3fRA5OnpibOzM8nJySxdupShQ4fSvHlz9u3bxwsvvEDfvn3p3LmzTe8lxNsFgHOFZeQWlePp4mDT+gVBsI4GdYAURalXdHrgwAFCQ0Or+cJuv/12xo0bR+/evXn//feZOXNmo2/euO4/MzOTlStXMnv2bDIyMnB0dKx13hBY/y7fKD89eObvke9IEK5X5s+fD0D//v3N9i9atIjHHnsMR0dH1q9fz9y5c80yyTZr1szmMlR3nQNBnjrO5JZw8Ewuvdr62KxuQRCsp0GvwGJjY/Hz8zN7ffTII48QFBRk2s7IyGDy5Mk1Jkt0dnbmpZdeYt26dTa5+bCwMAICAnjvvfeYNGkScXFxbNmyhaKiIn788UfOnj1rk+sY6d7KsIR289GzfBafzJGMPApL9Vc0fb8gCPWjKEqN5bHHHgMgODiY+Ph45s2bh1qt5vPPP2ffvn3cfPPNxMTE2Dx2RLVuDsBbPx5i/aFMzuQUU6qXOUGCcDVpkAzVogpVKv744w+ioqKA6i6wpKQkIiMjTRMO66OgoICkpCQAunbtypw5cxgwYADe3t6EhIQwa9Yspk6dSkxMDP/617+YNm0a+/bto6SkhOeee65GoWFVp4/xFZglMrVJ3yaycs9ps31atQp3nRZHrfqStFCtQn3xZ9XleTUt1qtNWHjpM6p6jguCfeLl4shXT9Q9ovJ3kKE2Jm6cyC7knnlbuVBkPg/IxVGDzkGDVq0yCJM1KrQa9UVhsnkdl8eRavLTOiSoEhuEvytP9A7jri51e0SvmAzVUi5fRXHw4EGzoOHu7k5BQYHFde3evZsBAy6JFI1zd2JjY1m8eDETJ05kypQpbNu2je7du9O7d2/Wrl3L//3f/9UqQ60toZklq8Gm3RZGh+Za1uzL4OjZPApKKigDzhVb3CRBuK7wcXOs97v1d5ChNiZueDvCN6M789X2E+xIOc/Jc0VUVCoUlILl0VAQri9OtXUnL6/uBIdXTIZqCYCyY8cOU7p4Nzc3JTEx0bR97NgxRa1W2+x61shQJaW9FCn2WZpKhVETDY0dEjekSLHfckVkqJbQs2dP03BtZWUlXbt2NW0ritIk2V4bQtVJ0C4uLuzcuRN/f//rRmoobbFfrqX2XC0ZalMgccPAtdQeaYt9cqVkqDbvAKlUKsLCwtBoDLkvkpOTCQkJwcGhaZZ++vj4oNFoyMzMNNvfkD9IRkZGg1Z93HDDDQ26R3tG2mK/XEvtsbQtqamptSYstDWNjR3Xc9yAa6s90hb7pCFtsSZ22LwDNG3aNLZt28bRo0epqKggOjqa/v37W90BsicZ6qD3NpOZV8ryZ3rSsYWnVe0RBKE6tpah1hc3FEVh+vTpqNVq7rvvPvr378/8+fNp06aNxbHD0rjx8/50Xlqxj+6tmrHocdstrxcE4QrKUC2qUKtl48aNJl/YunXriIiIMPOFNQR7kqG6e3iQVWoQG4rUUBBsj61ej1sSNz788EOef/55PvjgA86fP8/AgQO57bbbapWh1nav9ctQi1E7uaAXGaogNBlNLkO1BKMvbMyYMWRnZ7N8+XImTpzIrFmz8PX1bXB9TSFDrWk5qyUYZahF4vQRBLvGkrjx2muvMXnyZEJDQ5k1axZpaWnEx8ezdu3aGmOHtXFDZKiCYJ80KBGiJZw6dYo2bdqYXGDPPfccer2egIAAm7vArJWhWusCc3G4KEMtlUAmCH9XLo8bYJChpqam0rdvX4YNG2bKYVYVq+OGSJQFwS6xeQeovLycBx98kKysLObMmcOaNWvQ6XS88sorpKen06dPH5tlWbVWhjplyhRyc3NNJTU11aLr+bobVoCk50rSH0H4u3Kl44aPmyMAZ/NLKK+otPKuBUGwNTbvACmKgl6vJyIigvj4eD777DP0ej27d+8mIiKC8vJy+vTpY+vL8sknn9CqVSt0Oh0bNmzg/PnztZ7r5ORkem9f3/v7ywn3NyR4PJKRb5N7FgTh6mOMHd999x3r169n586dNZ5nbdwI8nTG1VFDeYXCCREpC4LdYPMOkLe3N127dsXb27uaL8zb25vOnTuTnZ1tk2sZl6ouWbLE5ALbs2cPjo6ObNmyxeY+nw6BhoC3+WgWmXklNq1bEIQrw+US5eXLl5tix80330xgYKDNXWBqtYr2F2PHfxPSqKxUbFa3IAjWY/NJ0KWlpXz66ae0b9++xuNGF5gtMMpQP/nkE55++mkef/xx8vLyuHDhAq6urixcuLBGF5i19G/nS8tmzqRdKKbPrE10CHQn2NsFD2cH3HVanLQaNCoVWo3K5APTqFWoq7rAapisXm1XPf6w+lxhgmAv6BzUjLj5yuT2sQRj3NiwYQPffvstTz/9NPfeey/jxo1j4cKFvPTSSzaPHaOjQ0k4eYHPtxxn9d7TdAj0wMfNCXedFjcn7aV4oTHGDTUaVfWVLfU6ACVuCNcQXUO8TAMPTYHNO0CFhYVUVFya7FdVhtpQF9jlMlQwTGBMTEw0yVAnTJjA1KlT8fDwYP/+/UybNo2goCB69epVqwus6mqO3NxcwLJVHR/f354p3+3n4Jk89iYXsDfZ4qYIwnWJj5sjg9vWHcRs7QKrL25MnDiR6dOnk5eXx0MPPcTo0aMJCgpixIgRrFu3rsbY0Zi40T/MjRf6teDT+ONkZBeRkX3BBq0UhGubl2IiaOEaVuc517QLbNOmTTV6P2JjYxVFUZS0tDQFULy9vRUnJydl0KBBytGjR+t0gcXFxV11b4kUKVKqF1u5wOqLG5WVlcrEiRMVQHF0dDTFDUWp3QUmcUOKFPst1sQOlaLYVr+sUqlMBQyejsu3lYsusMtHiRrDmTNnaNGiBdu2bSM6Otq0/+WXXyY+Pp4dO3ZU+0zVJzm9Xs/hw4cJDg6+bpw+0hb75VpqT0NdYF27dkWrbRJFYTUaGjskbhi4ltojbbFPrHGBWRM7bB5p1Go1K1euxMvLC4ChQ4eyYMECAgMDbX0pwDqfT1WpYVpaGr1797b4mtera8XeuZbaAtdWe64FF5jEDXOupfZIW+yTv50LTFEUxo4dS35+PoqiUFxczNtvv20WOAD27NljUX325ALr984mzhWWsWJstGlVhyAIjedadoH98Odppqw8QHTr5nwRa5sFIIIgGLArF1j//v3ZvHkzrVu3RqvVkpycjKOjI3fddZdV9dmbC+yCvgiNTlxggtAUXIsusObNilA7uVCucZK4IQhNhF24wFJTU5k/fz5jxowBYP369QwbNoyEhIQ635PXhl26wCSlvSDYNU3hArMWiRuCYJ80iQts6NChAGRnZ+Pl5YWiKBw8eNDWl7riLjCRGgrC3x9rXWClpaXk5eWZFUswdoCKRaIsCHaFzTtAer2eEydOmGSoUVFRlJeX06VLF5vLUK+008dD5wBATlGZlXcsCMLVxtq4Ye2Dk/vFuHGhsMxmeY4EQWg8Nu8AVVZWMmjQIPbu3UvHjh3p2bMnarWatm3bsmvXLjp37sywYcNsfdkr4gJr7esKwF+ZlidyFATBvrHUBWbtg1NocxfUKsgr0ZOVX1r/BwRBuCLYfA5Qp06dSE9PZ8iQIaY1+REREYBhdOjnn3+2OHDUx+UusNdff51PP/2UqKgoBg0aZHKB+fn52eRaABH+hlnme05dsFmdgiBcWS53gW3ZsoVJkybx6aefMm/ePIqLi4mJieHo0aPVYkfVZfCWonPQ0Kq5K8ezC9lz6gK3d2qalCCCIDQMm3eASkpK+Oijjxg1alSNx5ctW8Y777xjk2tdaRdYn3AftGoVe07lMObr3fSL8CPE2wUPZy3uOgcctWqT/0urVqE2/rRgdnp9jp76HEC2Wj0jCE2BRm0///+8Gi6wAe39OP57ClNWGjQ6RheYh7MWV0ftZf5ANRqVwQmmUalq9AZejsQN4VpGhUEm3FTYvAOUlJRE69atTdtVXWCRkZEcP37c4vquhAvM0smMLZu5MGVoB97+8RDrDmay7mBm/R8ShOscX3cndk0dfEWveSVcYJbGDYAJA9uyLfkch9Pz+GhjUv0fEASB14Z14Kk+res/0UqaJOe8m5ub6feDBw+aBY2GylB3797NgAEDTNuTJk0CIDY2lsWLFxMbG8vUqVP57LPPmDNnDr1792bt2rV8+eWXxMfH11jnzJkzefPNN6vttySg3d+5OZ18O7NmfwZHMvI5V1BKXnE5+aV6yioUKisVKiploqMgGKlw0Nf73Wqo0LC+RIe7du1i4MCBpu2qcePll1/mxIkTfPrpp0ycOBGtVstdd92FXq/H39+fI0eOVLtmY+KGGvjqkU6sPZDBrhPnOZ5VSF5JOfnF5RSWV5jihoQOQbhEcWG+zWOHGQ22h9UD2FaGWh+nT59WAGXbtm1m++uSoZaUlJjuJzc3Vzl06NBVF7lJkSLFcqHhmjVrlKlTpyorV65UAGXVqlVmx//1r38pnp6eyurVq5U///xTufPOO5WwsDCluLjYdM6AAQMUQPniiy+U3377TWnbtq0yatSoWmOHxA0pUuy3WCNDbZIRoJ49e5rJULt27VpNhmorbOECc3FxYefOnfj7+183UkNpi/1yLbWnoTLU2r6zVbE00aExA/2SJUvw9/dn9erVjBw5ksOHD7Np0ybUajU+Pj707t2bjz76iKFDh3Lvvfda5AK7HuMGXFvtkbbYJ9bIUC2NHWY0uMtUDyqVSmndurUSHh6uhIeHK2q1WmnVqpVp21gsJT4+XrnjjjuUwMBABao/6VVWVipBQUGKi4uLotPplEGDBilHjhxRWrRoocycOdOia6Smpl713qsUKVKse4oD87iQnJysAMrevXvNzuvbt6/y3HPPKYqiKAsWLFC8vLyUHj16KOPHj1cURVHKy8sVjUajeHt71xg7ZARIihT7LXYxAjRt2jS2bdvG0aNHqaioIDo6mv79++Pg4GBVfVfCBWap1PDWOfGk55aw9OkoOrf0sqo9giBUx5YyVEsSHWZkZODn58ekSZOIjY0lMjKSHj164ODgQHFxcY2xo7Y5QPXFjV8PZfLC8kS6BHvx76dqzjItCIJ12JUMVavVsnHjRgYPHoyzszPr1q0jIiKChQsXWlVfU7jAqtIQGWpmiRq1k8hQBaEpuNLLsh988EGysrJ4/fXXycjIoLKykhdeeKHG2DFlyhTTZGq4FHjrixv+zctQO7lQqhIZqiA0FdbEDptngl6yZAnz5s1j3bp1fPnll7z77rt8/fXXdbq5rMVaF1ijnT7iAhMEu+XyRIeXc/k8gYCAAM6ePQtgih2FhYUoikJ0dHSN9VqbQd5NZ3jOLCjVW9UeQRCahiaRobZp08bkAnvuuefQ6/UEBATYjQvMWqePsQMkgUwQ7JfLEx0aycvLY8eOHabOTXR0NDk5OSQkJJjO2bhxI5WVlbXKUK3F38MwcTojr4RSvTw8CYK9YPMOUHl5uWlYec6cOaxZswadTscrr7xCeno6ffr0MT15XS2sdfoEeTkDcOpcUVPeniAI9VBQUEBiYiKJiYnApUSHp06dQqVSmRId/u9//2P//v2mRIfGXEEdOnTg9ttv5+mnn2bnzp1s3bqV8ePHM3LkSIKCgmx6rwEeOjx0WioqFZLPFtq0bkEQrMfmHSBFUdDr9URERBAfH89nn32GXq9n9+7dREREUF5eTp8+fWxyrcuHui+Xoa5du7bOz1k7lG10gR3JyG/cjQuC0Ch2795N165d6dq1K2BIdNi1a1def/11AF5++WUmTJjAM888Q/fu3SkoKGDt2rXodDpTHd988w3t27enb9++9OnTh+TkZI4dO1arDNVaVCoVnVp4ArBmf7pN6xYEwXps3gHy9vama9eueHt7m14xPfLIIwQFBeHt7U3nzp3Jzs62ybWMQ93vvfcekyZNIi4uji1btlBUVMSPP/5o85Gmmy6u/NpwJJNNR87KcLYgXCX69++PoijVyuLFiwFDp+Ott94iIyODkpIS1q9fb5IyG/H29uauu+5CURQWLFjA/v37ufnmm4mJibF57BjVIwSATzYnMWXlfrYcyyIzr8S67LWCINgEm68CKy0t5dNPP6V9+/Y1Hk9KSiIyMtLi+ixx+kydOpWYmBgiIyOZNm0aISEhlJSU1Co0tNbp07O1Nz3CvNmZcp7HF+9Co1YR4KHDXafFQ+eAk4MatUp1SYiqUaFRq6nqcqtprnrVGezVzmmg9FAQ7AV3nZa44R2v9m3UyJw5c0wiZYBPP/2Un376qcbY0RgX2B2dA9l14jxLtp/kPztP8Z+dpwBw1KjxcHYwCJWdtGg1BqGyg0aNVmOQozpoDFJU03dedSkcqFSGvapLh0yxRGX6H8NnJUYIfzeG3xREvwjfJqtfpdj4EUSlUnHgwAE6djQEvKoy1MzMTFq0aIFeb9lE4s2bN5u5wIwYnT6lpaU4Ozvj6elJcXExvXv3Zt68efzf//0fOTk5fP/999U++8Ybb1iVzwMME6A/2vAXP+47Q26xTIYWhPrwcXNk80vVv8OXY1xSnpOTg6en5xW5r7KyMlxcXFixYoWZRyw2NrbG2NGYuGFkx/Fz/PDnGRJOXeBMTol4AwWhDl6KiSC2V1id5zQqdjQ4dWI9gLjApEiRYl2xJpurtTQ0dkjckCLFfotdZIKGK+sCswZx+khb7JlrqT1N5QK7GkjcMHAttUfaYp/8bV1garVaWb16tbJ582Zl8+bNiouLi/Kf//zHtG0slhAXF1etl9euXTvT8eLiYmXMmDEKoOh0OmXEiBFKRkaGoiiKMnr0aOXOO++06DriApMixT7KlRwBKi0tVTQaTTW/oKWxQ+KGFCn2U+xiBEhRFMaOHUt+fj6KolBcXMzbb79t9uQEsGfPHovq69ixI+vXrzdta7WXbvmFF15gzZo1tG/fns6dO3Pq1ClGjBjBb7/9xoYNGxg/frxF17DUBXbPJ1v562wBnz7ajd5tfSyqWxCE+rGlCwxgy5YtzJ49m4SEBNLT01m1apXZPB9FUZg+fTpqtZr77ruP/v37M3/+fNq0aWNx7LA0bvy07wz//G4/PVp5s/Dx7o1umyAIl7ArF1j//v3ZvHkzrVu3RqvVkpycjKOjI3fddZdV9Wm12hqHtnJzc1mwYAFLly6loqKC2NhY4uLiePXVVxkxYgSFhYUWy1AtdYGFBDQnObeSPL1WnD6C0ATY6vW4JRLlDz/8kOeff54PPviA8+fPM3DgQG677TaLY4elccPHuxi1kwvlWp3EDUFoIqyJHTbvAKWmpjJ//nzGjBkDwPr16xk2bBgJCQl1vievjb/++ougoCB0Oh3R0dHMnDmTkJAQEhISKC8vZ/DgwXh5eZGVlcXs2bMB2Lt3L2vXrq1VhmrtctbAi5mg0y4UN7gdgiBcOSyRKL/22mtMnjyZ0NBQZs2aRVpaGvHx8bXGDmvjxiWHoKwaFQR7oklcYEOHDgUgOzsbLy8vFEXh4MGDDa4rKiqKxYsXs3btWubPn09KSgp9+vQhPz+fjIwMHB0d8fLyAi4JDbt3787IkSPr9PlY6wLrEGh4etuabJtEjoIgXHkulyiDIXakpqbSt29fhg0bVmvssDZuOF/sABWJRFkQ7Aqbd4D0ej0nTpwwyVCjoqIoLy+nS5cuDZahDhkyhPvvv5/OnTsTExPDmjVryMnJ4dtvv23UPVrrAru1gz8atYq9p3KIP2Z7u70gCE2PtRJla+NGMxdHALILSqmUvD+CYDfYvANUWVnJoEGD2Lt3Lx07dqRnz56o1Wratm3Lrl276Ny5M8OGDbOqbi8vLyIiIkhKSiIgIICysjJycnIATC6wXbt2sWzZsjp9Pta6wAI8dTwSZUhp/49/J7B672kJaILwN8cYO7777jvWr19fa+ywNm4EN3PGUaumpLxSXp8Lgh1h8w5Qp06d8PDw4O6776Zbt25EREQwevRoevXqxd133427u7vFT05VKSgoIDk5mcDAQLp164aDgwMbNmxg+fLlTJo0iWeeeQaALl26NInPB+CVIR3o1aY5hWUVTFyeyMD3NjPz58PEH8virLh9BMHuuVyibIwdcXFx3HzzzQQGBto8dmg1atr6ugGw8UimzeoVBKFx2FyFER4ezltvvcWoUaNqPL5s2TLeeecdi5bBT548meHDhxMaGsqZM2eIi4sjMTGRQ4cO4evry7hx41izZg0uLi7ceOONpKWlAfD7778THBzMhAkTanSBVSUvLw9PT09yc3Mteqor01fy+ZZkPos/Tn6p+cRGdyctLZo54+PmRHM3R5q5OOLiqMHZQYPOQYPOUYNOq8ZBo0atVqFRqVCruPS7GtQqg0tMrapq/LpIPV4wqNkNVnVXTbPmLfmcIDQErUZNl2CvOs9p6HewIahUKrNl8IqiEBQUxOTJk/n222/p3r07M2bMwM/Pj4ULF/LSSy9ZFDsacs9f/nac6T8dRqWCXm2ac0OgBz5uTrjrHHB10qBVqw3+wIseQWNprBOwvu+8+MEEeya4mQsBnro6z2lM7LD5KrCkpCRat25t2q7qAouMjOT48eMW1bV27Vree+89s32tW7fG19cgR5s5cyZbtmzh0KFDHDlyhKCgINauXYtarWbw4MFs3769xnqrrubIzc0FGiY3HB3pz32dm7Px8Fm2Hz/H3lMXSLtQTG4p5DagHkG41rHUBQbYbATVEony9OnTycvL46GHHmL06NEEBQUxYsQI1q1bV2PsaEzcuKeTN38e9+L7xDP8drCI3xq+JkQQrjssdYGBlbGjwakT6wFQDhw4YNp2c3NTkpOTTdsZGRmKRqOxqK64uDilY8eOSnp6uqlkZWWZjo8dO1YJCgpSAGXhwoVKz549lV69eimKUrcLrKYM01KkSLn6xVaZoDdt2lRj/bGxsYqiKEplZaUyceJEBVAcHR2VQYMGKUePHq0zdkjckCLFfotdZIIGQxKyy5+K8vPzTdt5eXkN6qnVlwjx448/ZsyYMbRv355FixbRoUMH/vjjjzrrnDRpEk899ZRpW6/Xk5KSQps2ba4bp4+0xX65ltpztVxg/fv3rzPOqFQqXnrpJebOncvmzZuJjo6ut84pU6YwadIk07Zer+fw4cMEBwdfN3EDrq32SFvsk7+tCwxQVCqVolarFbVaXW3b+LslxMXFKS4uLkpgYKASFhamPPTQQ8rJkycVRVGUDRs2KICSmZlp5vMJCQlR5syZU6fPR57kpEixzyIuMClSpFhT7GIESKVSERYWhkZjSP6VnJxMSEgIDg4ODa7LmAixXbt2pKen8+abb9KnTx8OHDhgSoTo5+dHt27d2LBhA3fffTf+/v6kp6fX6fOp+iSXm5tLSEhIvU6ffu9s5FxhOd+Ni6ZdgKS0FwRbcS27wMAwCXru+r8AcHXSUFhqSIoY5KXjn7e3Z1CHmrPWC4JQN3blAps2bRrbtm3j6NGjVFRUEB0dTf/+/a3qAF2eyr5z585ERUURGhrKt99+i7Ozs+nYpEmTiI2NJTIykpKSEn755Zc6fT5OTk7V5KxQv9PHzcODC/pi1E6u4vQRhCbgWnSBKYrCd/vPo3Zy4V8jbuS+bi35aX86//r5COm5Jbyw6hiDj+Twxp0dadnMxfpGC8J1jF24wLRaLRs3bmTw4ME4Ozuzbt06IiIiWLhwYaPrvjwR4q233mpKhPjggw+SlZXF66+/zqlTpwgJCanTBWYtro6GP1expLQXBLvGnlxg6bklnM4pRqNWcXfXFmg1au7q0oJbb/Dno41JfLHlOOsPn2Vr0jmeGxTOU33CcNDYPEWbIAhVsPm3bMmSJcybN49169bx5Zdf8u677/L111+TldV4dURtiRDB4PP55ZdfAFi+fHmdLjBrueT0EamhIPxdudIusAOnDcvlw/3c0DloTPtdHLX88/b2rHm+Dz3CvCkur2DW2iMM/eA31h7IkCzzgtDENIkMtU2bNiYX2HPPPYderycgIKDBLrDJkycTHx/PiRMn2LZtG/fccw8ajYZRo0bh6enJk08+yaRJk9i0aRMJCQk8/vjjREdH07NnT1s3CwB3neE1Xk5ReZPULwhC03OlXWCZeSUAtGruWuPxCH93lj/Tk3fvvwlvV0f+OlvA2H8nMPTD3/guIU1GnAWhibB5B6i8vNz0SmrOnDmsWbMGnU7HK6+8Qnp6On369LE4zXxaWhqjRo2iXbt2PPDAAzRv3pw//vjDlAjx/fff54477uDee++lb9++BAQEsHLlSls3yURrH0MAS8oqaLJrCIJgn1jrAisuN3RgXBw1tZ6jUqm4r1tLNr7YjwkD2+LupOVIRj4v/vdPesxYz9RV+4k/lkWpXjpDgmArbN4BUhQFvV5PREQE8fHxfPbZZ+j1enbv3k1ERATl5eX06dPHorqWLVvGmTNnKC0tJS0tjWXLltGmTRvTcZ1OxyeffML58+dNeo1WrVoRFRVVpwzVWiL8DbPME1NzbF63IAhXhstdYHBJhrpixQri4+NtHjuKyyoB0NXRATLi5eLIi7e14/d/DuSlmHa0bOZMfomeb3acInbhTrq+9SuPLdrJB+v/YsuxLM7mi39QEKzF5pOg3d3d6dKlC97e3qZ9jzzyiOn3zp07c+DAAZte0yg0/PTTT4mKimLu3LnExMRw9OhR/Pz8bHad3m19UKtgZ8p5Xlu9n5iOAYR4u9DM1RF3J63NVrAIgtB0hIWFERAQwIYNGzh69CiTJk3i/fff54UXXqBjx442jx3GESBnh/o7QEY8XRx4dkBbxvVrw9bkbNbsT2fD4bOczS9l89EsNh+9NKfSzUlLKx8XQr1d8XV3wsfN8aKL0AlXJw2ujlpcnTS4OGpxddTi5HDJOyYxS7iesbkMVaVS8ccff5gmElZ1gSUlJREZGUlOTo7NrhkVFUX37t35+OOPAUNmyLpkqDWt5ggODrZIpjZ3/TFTPo+qOGrUOGhUOGjVOGrUBpnpxfii4tIyPZWKy/YbzjEeN4UjiUvCNUJzV0f+O7ZXnefYWoZ6uQusa9euzJkzhwEDBphcYLNmzeJf//oXvr6+dOvWjeLiYvbt28eBAwcIDw+vMXZYGzfe+N9BFm87wfgBbZkc087qNimKwsEzeew+cZ69qTn8mZrDyfNFNCaCG6WrDsafFyXNhnhkOOfyGAXmccz403iO4XyJZYJtGNuvDQ9E1r3YwK5kqABubm6m3w8ePGgWNNzd3SkosN0cmrKyMhISEpgyZYppX30y1JkzZ/Lmm29W22/JstYnegQQ4a3lf3tPcyg9j8z8EtMQd8nFIgjCJXLcHOv9btlahrp7924GDLgkYDUmPo2NjWXx4sW8/PLL5OXlMWPGDE6cOEHfvn1Zu3YtLi4utcYOa+NGTk4ulaVFUF7UIOFyTYS4qwi5sTkjbmwOQKm+grQLRZw8V8zpC0WcKyjjXGEp5wrLOF9YTnGZnqKyCorK9BSVVVJeUWlWXyVQjsQtwT7JzG5GXp5nnefYnQx1x44dSm5urpKbm6u4ubkpiYmJpu1jx45ZrMKwhNOnTyuAsm3bNrP9dclQS0pKTPeTm5urHDp06Kqn8ZYiRcqVVWE0NHZI3JAixX6LXagwwPDayzhMWllZSdeuXU3biqJc9ffOVTNBu7i4sHPnTvz9/a8bqaG0xX65ltpztWSoTYHEDQPXUnukLfbJ31aGqlKplNatWyvh4eFKeHi4olarlVatWpm2jcVS4uPjlTvuuEMJDAxUgGriwpKSEkWlUinNmjVTdDqdMmjQIOXYsWMWCw0VRaSGUqTYSxEZqhQpUqwpdjECZEsXGNTv9Jk7dy5qtZro6GhmzpzJtGnTiImJobS0lAkTJlh0DUulhoPe20xmXinLnomiUwsvq9ojCEJ1bC1DfeONN6rN12nXrh1HjhwBoKSkhBdffBGABx54gOHDhzNv3jx8fX1tLkPdlpzNM0sSaOvnyupne1vbJEEQasCuZKi2doFZ4vQZOXIkK1asYO/evUydOpVevXrh5ORkkdAQLJcaunt4kFVaKDJUQWgibPl6vGPHjqxfv960rdVeCncvvPACP/30E1OmTGHWrFn8+eefDBkyhO7du9tchto6SIXayYVzZVqJG4LQRNiFDNXoAhszZgzZ2dksX76ciRMnMmvWLFMGZ1thdPpMnjyZnj178vrrr5ORkYGLiwtDhgypVYZqrdTQmMlVUtMLgv2j1WprnBeQm5vLggULWLp0Kffddx/+/v7MmDGD5ORkSktLbS5D9XM3zBvKLS6npLzCzAcmCMLVw65dYPVxudNn/PjxnDx5ktLSUm6//fY6P2et1NDFwdBfLBQZqiDYPX/99RdBQUG0bt2ahx9+mFOnTgGQkJBAeXm5mQz1zJkzhISE8NRTT9lchurp7IC7kyF2HE5v3DJ4QRBsh127wJoKa6WGfh6GJ7nTF4qb8vYEQWgkUVFRLF68mLVr1zJ//nxSUlLo06cP+fn5ZGRk4OjoiJeXl9lnmkqGqlKp6BthGP3+dnea1W0SBMG22LULrD4ud/oYfT46nY61a9fW+TlrpYZGF9jRzPzG3bggCE3KkCFDuP/+++ncuTMxMTGsWbOGnJwcvv3222rnGmPH7t27+frrr2t1gVkbNwBGR4cCsGzXKb787Tj6KgkJBUG48ti8A+Tt7U3Xrl3x9vY2DRU/8sgjBAUF4e3tTefOncnOzrbJtYxOn/fee49JkyYRFxfHli1bKCoq4scff7T5SNMNgYaAt/loFifPFdq0bkEQmg4vLy8iIiJISkoiICCAsrIycnJyTB7BuLg4AgICCA0NJSYmxuaxI6p1c564JQxFgek/HabPO5t484eD/Lw/nb8y8ykpl3mFgnClsfkk6NLSUj799FPat29f43GjC8xSLnf6gGHic2JiosnpM3HiRKZOnUpMTAyRkZFMmzaNkJAQSkpKWLhwYY0uMGvp186X1j6uHM8upP+7mwnzcSXE2wUPnQPuOi2OWjVatQqN2vBTfVE4qK4yOb2u2eqXH1JVkeiYH6v9c4JgTzg7anm0Z+hVvYeCggKSk5N59NFH6datGw4ODmzYsIE5c+bw9NNP06tXL9LT01mxYgX333+/zWMHwLQ7OhDm48KcX4+RnlvCoq0nWLT1BGD4/no5O+Dl4oinswNeLg44adU4ajU4atQ4atU4aQ2uQYOryxBXVCoMzkEu+rcu21arL3MPXgEh15WIQVcqzEk8tQ96tm5O55ZeTVZ/k8hQDxw4QMeOHYHqMtTMzExatGiBXm/ZROLNmzebOX2MGJ0+paWlODs74+npSXFxMb1792bevHn83//9Hzk5OXz//ffVPlt1NUdubi4hISH15vMASDtfRNz/DrIj5bxF9y8I1zs+bo5sfqn6d/hyjLk8cnJy8PT0bPQ1J0+ezPDhwwkNDeXMmTPExcWRmJjIoUOH8PX1Zdy4caxZs4a0tDTeeecdvvvuOwC2bdtGbGxsjbGjMXHjckrKK9hyLIsdKefYl5ZL6vkiCkplBEgQqvJSTASxvcLqPKdRsaPBqRPrAWznAouLi6uW7bFdu3am48XFxUpsbKwCKM7OzsqIESOUjIwMRVHqdoHVVK8UKVKufrFVJugHH3xQCQwMVBwdHZUWLVooDz74oJKUlFRj7NDpdMo999yjpKen1xk7JG5IkWK/xS4yQYNtXWD1JTP79ddfAcNExs8//5wRI0awdevWOuucMmWKyQ4NoNfrOXz4MMHBwdeN00faYr9cS+25Wi6w9u3bs3z5cgBOnz7N8uXLSUxMNGWCvhzDqyNVvXFJ4oaBa6k90hb75Eq5wGzeAVKr1axcudK0xHTo0KEsWLCAwMBAq+qrL5nZkiVLeOSRR2jWrBmLFi2iQ4cO/PHHH3X+QapKDdPS0ujd2/IU9TfccEPDG2KnSFvsl2upPZa2JTU1lZYtW9rkmvU9PG3cuBG1Ws3bb7/NihUrTA9PtcUOiRvmXEvtkbbYJw1pizWxw+YdIEVRGDt2LPn5+SiKQnFxMW+//bZZ4ADYs2ePRfUZk5npdDqT7yskJMSUzOz222+nW7dubNiwgbvvvpuQkBC2bdtWp8+n6rt85eI0qPre5Y+Yt5VjmQV88nBX+kX4WXT/giDUj61dYGBZJujZs2dz4sQJ08NTfbHjcix1gf207wz//G4/PVt782Vsd+sbJAhCNezKBda/f382b95M69at0Wq1JCcn4+joyF133dXguozJzNq1a0d6ejpvvvkmffr04cCBA2bJzCZNmkRsbCyRkZF4enqyZMmSOn0+M2fOrCZKhPqdPuEt/UjKqeRsiUacPoLQBNjSBVbfw9PgwYOpqKgwxY7AwEBefPHFWmNH1Qen/HxDPrD64kbzZkWonVwoU+skbghCE2EXLrDU1FTmz5/PmDFjAFi/fj3Dhg0jISGhzvfkNXG5BLVz585ERUURGhrKt99+i7Ozs+mYMfP066+/TmpqKgEBAbX6fKD6u3xjD7I+2vq5AbD31AWg7pnpgiBcPSx9eLo8dhizQNcWO2p7cKoP14saDHEICoJ90SQusKFDhwKQnZ2Nl5cXiqJw8ODBRtddWzIzwOQCCw4O5qWXXqrV5wPWZ3Qd1MEQFH85lEnq+aJGt0cQhKahIZmgjbEjMjKSRx99tNbYYa0Kw/miRFkcgoJgX9i8A6TX6zlx4oRJhhoVFUV5eTldunRptAzVmMwsMDDQLJmZkaNHj3Lq1Cmio6Nt0ZRq3NTSk15tmlOmr+Qf3+zhQmFZk1xHEATbUtfDk5H6VpJY++DU3NURgKz8UioqFavbIAiCbbF5B6iyspJBgwaxd+9eOnbsSM+ePVGr1bRt25Zdu3bRuXNnhg0bZlFdkydPJj4+nhMnTrBt2zbu+f/2zjwuqur//687M8yCbKKsBogLaCpuIIKKlnzEJdO0T2mZWH1y+YplpOWSUulHcvmpLWqWCpmZ+jExM9JyAXNLxRUXFALFZFBQYEC2gfP7Y5ybAzPDzHDBEd/Px+M84N575sw9jPP23HPveT9feAFisRhjx46Fo6Mj3nzzTURHR+PgwYP44IMP0LVrV3Ach3feecegz6c+cByHRS90QYtmUlz4uxBDPvsDO07fRCV5fQjCqjF28bRq1Sq0atUKN27cwLp16wSPHU81t4VMIkK5uho3aOaYIKwGwZ8B6ty5M3JycjBkyBB+2amfnx8AzezQr7/+avLU8c2bNzF27Fjk5+fDxcUFffv2xfHjx+HiojErr1ixAiKRCMOHD0dJSQl69OiB5cuX4/vvv0dERATS0tLg6irsaq3WLZth81u9MWVTCv7KK0H0tnNY+MtlDO7sjmBfZ/Twbo5WTgo+DT1BEI2PvkzQ+i6ezp07h9jYWPj4+KBbt24ICgoSPHaIRRz83Oxx4e9CHLxyG7596flBgrAGBFdhtG/fHp988gnGjh2r9/iWLVuwZMkSk5fBm0JwcDCCgoLw5ZdfAtDMQnl5eWHatGkm+XyKiorg6OiIwsJCk6e171eoEX80CxsOZyKvWPdWmMJGjNYtm6GVkwItmknRwk4K52ZS2MkkUEjFkNtoisJGDJlEBLGIg4jjIBZxEIvA//7PPk6vm8aYK0xzvMa2nkbqcoo1hkOIaOJwgKPCxmgVS76DxhgzZgwOHTqkc/H03//+F23btgUAlJWV4b333sPatWvBcRyGDx+O1atXw9XV1eTYYc45xx3JxMc/X4KIAwZ3dkd3r+ZwdZChpZ0M8gdxQCoRQSoW8d93jnd8/eP3wgOvl8bvpVuHIBqbhv7/QWYjgtxGbLROfWJHg7jAjh8/zj9IWNMFppWh1rz/ro/Y2Fjs2LEDV65cgUKhQGhoKBYvXgx/f3++TlFREZycnNCsWTMwxhAREYHVq1fj/fffbxAXWE3UVdU4nnkXf1y9gzM3CnA1VwU13ecnCJ5H4QIzhYqKCtja2mL79u0YOXIkv78hXGDqqmp8uDMVu8/nCNoHgmjKPJYusNTUVH7bzs6OZWRk8NtKpZKJxWKT2oqIiGBxcXEsNTWVnT17lg0dOpR5e3uz4uJivs5rr73GALDPP/+cnTp1ivXu3ZuFhoaSC4wKlcewCOUCM4W///6bAWBHjx7V2U8uMCpUHr9iNS6wkpISFBUV8dsqlYrfLioq4jMv18WePXt0tuPj4+Hq6oqUlBSEhYWhsLAQW7ZsAQAEBgaiZ8+efEZXX1/Do8aaeYCqq6tx9+5dtGjRwmgyJe1I05KZImuD+mK9NKX+mNoXxhhUKhU8PT0b8ezMg+KGhqbUH+qLdWJOX+oTO6xehvowhYWFAABnZ2cA4DO6ikQi5ObmAtBIEL29vZGWlmbVwZQgiIbDlNvn2ucUQ0ND+X2TJk1CaWmpSS6w6upqFBcXN2AvCIJoUCyaOzYCx3GsTZs2rH379qx9+/ZMJBKx1q1b89vaYi5VVVVs2LBhrE+fPvy+77//nkmlUtarVy8WFRXF7w8KCmJ2dnYsNjZWb1s0lU2FinUWoW6BmXL7vH///szFxYW9/vrrLCcnh+Xk5LB79+6xVq1aGYwdD5Odnf3I/15UqFDRFKu4BTZv3jwcPXoUaWlpqKqqQkhICAYMGAAbG+OrQOpi6tSpSE1NxeHDh2sde9gF1qtXL2RlZaGystKgC6zmVLapDzP+a3kycgrLMGdoB5zLLsAvFzSp87t7OWHRqC7wcratVx8J4klFaBlqXbfPtQQGBmLz5s3o378/evXqhZUrV5rsAmMmSpR/u6hE9LZz6OHthI1vGs5QTxCE+ViVDFUikeDAgQMIDw+HQqHA3r174efnhw0bNljcZlRUFHbv3o1Dhw7p6O61GV0jIiKwbNkyHZ/PlClTDLrAak5la6kru2tRlQ1EMhGG9WyLyf+yxU9n/8aHCak4d7sC/95wFnOHdcQrvbwFFToSxJNEQ313at4+13Ly5ElIJBK89dZbqKqqQvfu3c12gdUpQ3Uug0hmi0oxyVAJoqGwJHYIngl648aNWL16Nfbu3Yt169Zh2bJl+O6773Dnzh2z22KMISoqCgkJCThw4ECtB5sfzuiq9fmcP38eFRUVGDNmjFBd4ql4kPFZKtH82UZ0a4XEd/oh2NcZ9yuqMDchFa+u+xOXbhUZa4YgiEakuroa06dPR58+fdC5c2d+/yuvvIJNmzbh2LFjiIuLg4eHB7y9vQV3gdk+yGNCMlSCsC4EnwG6ceMG2rZti7CwMBw5cgSAJgC5u7ujf//+WLNmjc6DiMaYOnUqNm/ejJ9++gn29vb87I6joyMUCoVORldnZ2c4ODhg2rRpCAkJQe/evQXtV1U14z0+UvE/40YvZ1v88FZvxB3NwpI9V3A0Ix/DvvgDo3s8hUlhbdDeTZgpfYIgLMPQ7fOJEyfyv3fp0gUeHh4YOHAgMjIy+ISJD2No5rgutDZ4VTnJUAnCmhB8BqiyshIvv/wy7ty5g+XLlyMxMRFyuRyzZs1CTk4O+vXrh9u3b5vU1po1a1BYWIgBAwbAw8ODL1u3buXrrFixAs899xxGjx6NsLAwuLu7Y8eOHUJ3CxXqf3xf2hkgLSIRhzf7+uL3d/tjWIAHGAO2p9zEv1YcQuSGE/jp7N8opuBHEI2O9vb5wYMHdW6f60M785Oeni7oOXg11zwbeEdVDlVZpaBtEwRhOYIPgBhjUKvV8PPzQ3JyMtauXQu1Wo1Tp07Bz88PlZWV6Nevn8lt6SsTJkzg68jlcqxatQoLFiyAi4sLEhMTMWLECMGFhsYGQFq8W9hi1Ss9kPB/oYjo5AaOA5Kv3sE7W86i54Lf8XrcCaxNzsDZ7AKUVdJ0OEE0FHXdPn+YVatWoXXr1mjevDkAIC8vT9BzcbS1gZuDZuboilIlaNsEQViO4LfAnJ2d0aVLF52HDceNG8f/HhAQgNTUVEHfc+vWrYiOjsZXX32F4OBgrFy5UnChYXmVZsDCcYCkDtFpd+/mWPtaIG7k38e2U9nYff4WsvLv42DaHRxM0zwLJeIAnxbN0N7VDl7OtvBwlMPNQVMcFBLYy23gIJegmVRCYlWCMJO6bp9nZGRg8+bNkEgkiImJweTJk7Fz505UVlYiKioK//rXvwQVKff0aY7EC0os/vUK5g9/Gh3cHQxeSBEE0TgI7gKzs7PDqVOn0KFDB73HzXGBmYq5MtSay1m1y+iMydRu3ruPvosPQiYRIW3hELPOjzGGyzkqHM3Iw/G/7iLl+l3cu2/aVDjHAc2kEl6UaCPhYCPW/C6ViGAjFkH0sCBRK0588BPQ3eYFio04pmqst2qsPpEg1jwcFBIsebGr0TpCy1ANrQiJi4vDhAkTkJ2djXHjxvHPKfr6+uKFF17AnDlz0KlTJ72xw5K4oeVyThFGrzmK+w8ehBZxgJOtFE4KG8hsxJCKNd9ryYOf2vN/WHSq/e5qfwd/jON/191PEI83L/b0wr+e1r+aW0t9YofgM0AlJSWoqvrn9k5NGaq9vb2g2VMrKiqQkpKC2bNn8/tEIhHCw8Nx7Ngxva8xtJz1YX1HTfLvFaO6/D7EnNhoPUM8ZQe81LUlXuraEowx5BWXI+N2CTLuqKAsKkduYRlyi8pxp7gMxWVqqMrVqKzSjE2Lysx+O4KwGlraSVE0qG6hIQCTNTl1UVc7Xl5e+P333/XKUA3FDkvihpZWzYD4Vzvjq+QMHM/MR3FZFfLK7kPYm20E0bTo7GKD4KcURuvUK3aYnTqxDgCwP//8kxUWFrLCwkJmZ2fHzp49y29fvXqViUQiwd7PXKEhY4yVlZXx51NYWMguXbr0yLNYUqFCxbplqBQ3qFCx3mIVmaCBhnOBCUXN5ay2trY4ceIE3NzcIBIZvi+vUqnw9NNP49KlS4JlrH1UUF+sl6bUH1P7Ul1djdzcXL0OLmuB4oaGptQf6ot1Yk5f6hM7BH8GSCwWY8eOHXBycgIADB06FOvXr4eHh4dOvf79+wvyfhUVFXqnsSMjI1FQUICffvqpzjZu3rwJLy8vQc6HIAjLyc7OrnO5uimYIkPt378/Dh06pPM6rQzVlNhBcYMgrAdLYofgM0CMMUyePBkqlQqMMZSWlmLBggW1EoidPn3apPYOHTqEpUuXIiUlBTk5OUhISNAZ6NjY2MDNzQ2vvvoqqqur0adPH6xatYrPDm0K2hFmXU6fZ5cdxG1VBbZN6o2nPR1NapsgiLoR2gWWnJyMqVOnIigoCGq1GnPmzMGgQYNw6dIlNGvWDIDmgWIXFxc899xzWLRoEQBNWo3OnTubFDtMjRuJF3Lw/vbzCGrdHHGv9xKgdwRBaLEqF9iAAQOQlJSENm3aQCKRICMjA1KpFCNGjLCovZKSEnTt2hVvvPEGRo0aVev4kiVLUFBQgIqKCsTExODAgQMICgqCSCQyKEOtifaWXF1OH3sHR+RVlEAka0ZOH4JoAIS6Pd4QMlRD51pX3GjZvBQimS3U5AIjiAbDktgh+AAoOzsba9aswaRJkwAA+/btw7Bhw5CSkmL0PrkhhgwZgiFD9C87Z4xh5cqV+PjjjyGXy7F06VLk5ORArVbjk08+MShD1bec1RQUD5w+9ysoqzNBPE4IIUO1NG7YSrVxg5KfEoQ1IXgmrhs3bmDo0KEANBlVnZycwBjDxYsXhX4rZGZmQqlUIjw8nJehVlRUoF+/fkblq7GxsXB0dOSLqffxtYGMpIYE8fgglAzV4rjxwAVGAyCCsC4EHwCp1WpkZWUhLCwMbm5uCA4ORmVlJbp164Znn30WaWlpgr2XNrtrzas1Nzc3/pg+LLU6OzeTat6XEvMQxGODVoa6ZcsWnf0TJ05EREQEunTpgldffRUbN25EQkICMjIy9LZjadxo8SBu3FaVobKquo7aBEE0FoIPgKqrqzFw4ECcOXMGnTp1Qu/evSESidCuXTucPHkSAQEBGDZsmNBvy/t85HI59u/fj7t37xqsK5PJ+Pv2dd2/fxi/B2b3q7nCJXIkCKLhMEWGqo0d2lvtv/zyi956lsaNVk4K2ErFqKxiuJ5fYllHCIIQHMEHQJ07d4aDgwNGjhyJnj17ws/PD+PHj0doaChGjhwJe3t7k6+c6kK77n/jxo2Ijo5GTEwMTp8+DalUikOHDplsnTcVf3fNAOiPa3dQQnZ3grBamIkyVK1HMCYmBuvXrwcAfPjhh4LGDpGIQ4cHseOns7cEa5cgiPoh+EPQZWVl+OKLLzB27Fi9x7ds2YIlS5YI8l6+vr5wd3fHqlWr8NZbb+H1119HUVER7t27h2bNmmHDhg16XWCW8mwHV7RoJsXNe6UIW3IQQa2d4eWsgIPcBvZyCWQ2Yog5DmIRB4n4wU8RV+vpdH3PqtdVp+YD7rW2yU9FWClSiQh92rVs1Pc0VYa6detWvPzyy2jRogXeffddhIWFIT09XfDY8WqwD07fKMAXB9KxJ1WJLq0c4WIvQ/NmUsglItg88PrZiDlIRCLe3wfo+sCgdf5ptzhOx//FcRQLiKZDuwey8IZC8AFQeno62rRpw2/XdIEFBgbir7/+Mrm94uJipKen89uZmZk4e/YsnJ2d4e3tjWnTpmHu3LlwcHDAhQsXMG/ePHh6eiI0NNSgC6zmag7tChFTVnUsf8EPM/53Drl3C5B4t8DkfhDEk0pLOymSZj5jtI7QLrA1a9YA0KTleBitDFUqleL333/HxYsXcfXqVRw7dgyjR4/Ghx9+iGnTpumNHfWJG+Ht7DGxtwfWH85EWvZ9pGULOztNEE2RmRF+iAxtQI+g2fKMOgDAUlNT+W07OzuWkZHBbyuVSiYWi01qa9GiRczf31+v9yMyMpIxxljv3r1rHXv55ZeNusBiYmIeubeEChUqtYs1u8AoblChYr3FalxgJSUlOldFKpWK3y4qKjJ5pJacnIxZs2bpZHNNTU2tlc0VAH7++WcEBgYC0Dh6Fi5caLDd2bNnIzo6mt9Wq9W4fPkyvLy8nhinD/XFemlK/XlULrCPPvqolrnd398fV65cAaC5VT9nzhwAwMCBAzFkyBCsXr3aYO4wgOKGlqbUH+qLddJYLrAGmQHiOI6JRCImEolqbWt/t4Tbt28zACw5OZnfFxYWxjiOYwkJCTp1x48fz55//nm97ZDVmQoV6yxCzQDFxMSwTp06sZycHL7cuXOHPz558mTm5eXFRCIRW7ZsGevduzcLDQ2tM3Y8THZ29iP/e1GhQkVTrGIGiOM4+Pr6QizWJA3MyMiAt7c3bGxs6t22vmyuHMdBLBZj7NixaNu2LYYPH465c+cadYHFxsbWujoE6nb69F9yEPklFfhxSgj83SmlPUEIhdAuMACQSCR6rwoLCwuxfv16bN68GUuXLkVWVhbi4uLQsWNHHD161GSPoKkusANXbuPtH86gg4c9tk8OtbxDBEHUwqpcYPPmzcPRo0eRlpaGqqoqhISEYMCAAfUeABnL5hoaGoply5ahT58+iIuLw5YtW4z6fGpOZWv/gHW7wBxwT32fXGAE0UAI5QIDgGvXrsHT0xNyuRwhISGIjY2Ft7c3UlJSUFlZifDwcFRVVSEyMhKBgYHw8PDAe++9ZzB21HwIWqVSAajbBfa0DweRzBY5JRzs7e0F7SNBEBqswgUmkUhw4MABhIeHQ6FQYO/evfDz88OGDRvq1a42m+vhw4d19k+cOBEA4OnpiaVLlyI/Px9qtRrbt283eD9fJpPVstObAqkwCOLxIDg4GPHx8fD390dOTg4+/vhj9OvXD6mpqVAqlZBKpXBycsLLL7+MO3fuYP78+fxSeUMuMEMzx3Xh/WAZr6pcjTvF5XC1l9evcwRBCILgiRA3btyI1atXY+/evVi3bh2WLVuG7777zqibqy5MyeaqdYEVFBQAAOzs7Cx+P0MopCRDJYjHgSFDhuDf//43AgICEBERgcTERBQUFGDbtm216mpjR2BgIF577TWDLjBLVRhyGzE6t9LMEP16wbCihyCIxqVBZKht27blXWBvv/021Go13N3dzXaBMROzuT7M2bNnAQAeHh6WdsEgdg+khgWllYK3TRBEw+Hk5AQ/Pz+kp6fD3d0dFRUV/MWSlrpWkliqwgCAF3toLty+OHANtwpKLeoDQRDCIvgAqLKykp9WXr58ORITEyGXyzFr1izk5OSgX79+JqeZnzp1KjZt2oTNmzfz2VyVSiVKSzUBJCMjAwsWLEBKSgqysrKwa9cujB8/HmFhYQgICBC6a2jTUrP0PuM2ucAI4nGiuLgYGRkZ8PDwQM+ePWFjY4P9+/fzx9PS0nDjxg2EhIQ0yPu/EuwDPzc75BVX4N9fHcPha3mCJX0kCMIyBB8AMcagVqvh5+eH5ORkrF27Fmq1GqdOnYKfnx8qKyvRr18/k9pas2YNCgsLMWDAAHh4ePBl69atAACpVIp9+/Zh0KBBaN++PUaPHo3r16+jpKQEJ06cELpraP9AhnruZoHgbRMEIRwzZsxAcnIysrKycPToUbzwwgv8alFHR0e8+eabiI6OxsGDB/HBBx+ga9eu4DgO77zzToPEDqlEhPjXe6F1C1v8XVCKcev/xMjVR7H+cCbSb6tQXU2DIYJobMx6CPrAgQMICwuDRGL4Zc7OzujSpYvOUvVx48bxvwcEBCA1NdWk96vrCsnLywvJycnYunUrxo8fj6+++grBwcFYuXIlIiIikJaWBldXV5PeyxT6tGsJjgOO/3UXcxMuYGBHV7RyskVzWxs4KGwgEWn8X7TKgyAeLTdv3sTYsWORn58PFxcX9O3bF8ePH4eLiwsAYMWKFRCJRBg+fDhKSkrQo0cPLF++HN9//32DxA4A8HRSYPfb/bBsbxo2n7iBc9kFOJddgAUA7GUS+Lvbw8vZFk81V8DVXgYHhQ2cbKVwVNjATiaGVCyGVCLii0wi0usaJAjCNDhmxjysWCxGTk4OHxhqer4Azb32U6dOoV27dnrbSE9PR2BgIAoKCnDo0CEsXboUKSkpyMnJQUJCAkaOHMnXZYwhJiYG33zzDQoKCtCnTx+sWbMG7du35+vcvXsXfn5+KCoqgq2tLUaPHo0VK1agY8eOmDZtml6hYc3lrNpl8IWFhXXe11/+Wxo+P5ButI5WaCgRczrSQs3PB9s19/Pb2lb+CWo1X0MQjxMt7GT49R3js75FRUVwdHQ06TsoJMHBwQgKCsKXX34JQJNuw8vLS2/sqE/cqMltVRl2n8vBb5eUOJddiNJKy1eWijhAxHEQPbCkarc5gJeqchz3z/4GDSQN03hDnTPFVOvmnfD2eDXYx2id+sQOs2aAao6VLl68qBMQAE1uDKO5dOztUVyseYampKQEXbt2xRtvvIFRo0bVqrtkyRJ8/vnn+Pbbb+Hr64t58+YhIiICly5dglyuWUqqvcpbvHgxQkND8frrr2Py5MkIDw83KEM1tJzVFKnhf3p7oGNLG+w+dwtpuSrcLipDUZkaD89glz8oBEEA6jJpnd8tc4WGQlw8KZVKnDx5EhcuXMCmTZswevRofPbZZwZjR33iRk3kAF4MaIEXA1pAXVWNjDvFyMwrwc17pbhVUIq7JRUoLK1EUZkahfcrcL+iChVV1aisYqiqcbus2ux3J4jHg7v3ClBU1NxonUaToXIcx3Jzc/ntmqJTxhgTiUQsPT1dRzXxcLl69apeFQYAHZ1FdXU1c3d3Z0uXLuX3FRQUMJlMxn744QfGGNNRWGiFhr/++ivjOI5NmTLFoAyVVBhUqFhnMTWdfWJiIps7dy7bsWMHA1BLhfPpp58yR0dHtnPnTnbu3Dn2/PPPM19fX1ZaWsrXeeaZZxgA9s0337A//viDtWvXjo0dO9agDJXiBhUq1lsaXIXBcbr3m2tuAwBjDH5+fgbbYIyZdM86MzMTSqUS4eHh/D5HR0cEBwfj2LFjGDNmDI4dO8ZPfWkJDw+HSCTCrVu3TO6Xm5sb/vjjD3h7ez8xUkPqi/XSlPrTUDLUIUOGYMiQIXqPMcawcuVKfPjhhxgxYgQATX4yNzc37Ny5E2PGjMHly5dx8OBBAECnTp0QEhKCL774AkOHDsXkyZP1tlszgaqtrS1OnDgBNze3JyZuAE2rP9QX66SxZKhm3wIbOHAg/xD0/fv3MXz4cEilUr5Ou3bt8M0335h9IjXRZmWtmZHVzc2NP6ZUKuHq6ori4mLk5uYC0GSidnZ2hlKpNPgHsTSjq5ann37a4tdaG9QX66Up9cfUvmRnZxtMdmoqpl48OTk5QaVS8bFDe/F0+fJlvbGj5jNAf//9N3r16mXyeTWlzxNoWv2hvlgn5vTFkthh1gAoJiZGZ1t7dfUw1dXVOH78OHbt2oWKigoMHDgQMTExUCgUZp2YqXAch549e2L//v06zwBcuXJFZ/tharrACgsL4e3tXafU8LnP/0BW/n3ETwhCoK+zwXoEQZiHkDJUcy6e/Pz8+NihvXg6c+aM3sUTlkqUf7+Ui3e3nkXXpxzx/Vu969M1giBq0Ggy1JoDIH0sWLAAc+bM4V1gn332GW7fvm22C0x7BZabm6uT1Tk3NxfdunXj69y+fRuffPIJLzTs0aMH8vLyoFAoDMpQDbnA6sru2sLZCTeKgQqxnGSoBNEANPaS7ujoaD529OrVCyqVChzH6Y0dlkqU3VtWQCSzRblIRnGDIBqIRpWh5uXlISsrCxzHoXXr1mjRogWAf1xgkyZNAgDs27cPw4YNw7p164zeJ6+Jr68v3N3dsX//fn7AU1RUhD///BNTpkwBAISEhKCgoADt2rXDsmXLMH/+fNy6dQuMMWzdutWgDNVS3B5IDG/euy9ouwRBCIc5F08Py1BzcnJQWVmJTz/9VG/ssFSibC/XhNlCUugQhFVhdiboixcv8p6v4OBg9OrVC66urrzn68aNGxg6dChfPzw8HBzH6X0oubi4GGfPnuX9XZmZmTh79ixu3LgBjuMwffp0LFy4ELt27cKFCxcwfvx4eHp68re2OnbsiMGDB+Ott95Cr169sHnzZvj6+mLs2LF47rnnLPuLGKGjh+bq7dIt85e9EgTRODx88aRFe/GkVV1oL55SUlJ4Geru3bvBcRxee+01Qc9Ha4PPLSqHqowGQQRhLZg1A6RUKtG/f3+4uLhg+fLl6NChAxhjuHTpEr755hv069cPlZWVfI4eLTY2NqisrP3FP3XqFJ555hl+Wzu9HBkZifj4eLz//vsoKSnBxIkTUVBQgL59+2LPnj067X///feIiorCwIEDIRKJMHr0aHz++edm/RFMpauXIwAg+eodlFVWQW4jbpD3IQjCOMXFxUhP/ychqfbiydnZGd7e3vzFU/v27fkcYoYunr766itUVlYiKioKY8aMgaenp6Dn6mQrhZuDDLlF5biiVCGoNT0/SBDWgFmZoD/44APs27cPR44cqTXIKS0tRd++fXH69GkMHTpUZ6r4559/xrPPPotmzZrx+3bs2CHA6f/DqlWrsHTpUiiVSnTt2hVffPGFySs0TM0kWVlVjf5LDuJWYRmGdnHH0he7opnM4ruIBEE8wNxsrklJSToXT1q0F0/sQSLEr7/+mr94Wr16tU6Kjrt37yIqKgo7duxARUUFOI5D9+7dsXr1apNihznnPPX70/jlQg6e7+qJz8Z0I30FQQhEfTJBm3UL7Pfff8cHH3xQa/ADAAqFAjNnzoSzszNcXV3h6OjIl3HjxsHT01Nnn5Bs3boV0dHRiImJwenTp9G1a1dERESYbJ03FRuxCEte7AqxiEPiBSX6LD6AWT+ex09n/8alW0UoKVcL+n4EQehnwIABYIzVKvHx8QA0D0R+8sknUCqVKCsrw759+2rlJ3N2dsaIESPAGMP69etx4cIF9OjRo0Fixxt9W4PjgF3nbmFC3En8cj4HN+/dJyM8QTxCzJoBMsXz1a1bNxQUFBgVpgqNOT4ffZg7gjyWkY/ZO84jK7/2w9AKGzFa2EnhZGsDuUQMhVQM2YOfUrEIYhF4YaqIA8Sc9ncOYpHW1WO6r8fU60jT2zOtIl3AEqZiK5VgyoC2Rus8Di6wmph7zt8dv45Pfr6Iyqp/Qq6NmIOLnQwt7GSwlYohtxFDYaOJFzZijo8H2tggsqJYoWmT4gXRcPT3c0FgHbeMG80FZornq6SkBHfv3jUqTDWV2NhY7NixA1euXIFCoUBoaCgWL14Mf39/vk7//v1x4sQJnDhxAqtWrQIATJo0yagLrGZCM20maVOdPp1cbJDwVg8c+ysff1y7g8u3ipB+uxhFZWqUlAMlxcANs3tLEE2TlnZSvNrDxWidevl8LKSiogIpKSmYPXs2v08kEhmMHfWNGyOebo4urt3wY8pNHP/rLjJuF6O8nOHm/RLcFHbCiSCaBNJqP/g5Gx+m1Cd2mD1No1Kp9N4Ce/hEHkafMNVUkpOTMXXqVAQFBUGtVmPOnDkYNGgQLl26xD9PpH24+ueff0ZgYCAATYr6hQsX4sqVK3rbNZTQzMvLy6LzJAjCMNkAHBeaVlelUgl+i9wQeXl5qKqq0pswUV/soLhBEI3L2yuBt02sa0nsMFuFUZfnS0j27Nmjsx0fHw9XV1ekpKQgLCxM51iLFi1MdoHUTGimVqtx+fJleHl5PTFOH+qL9dKU+tNQLrC6+Oijj2oNVvz9/fmBTVlZGebMmQMAGDhwIIYMGYLVq1cbzR1GcUNDU+oP9cU6sUoXmFYeaIxnn322TmGqpWinnJ2d/7knaGNjAwCIiIiAt7c3hg8fjnnz5pn1B8nNzUXfvn1NPo8n1bVi7TSlvgBNqz+N6QLT0qlTJ+zbt4/ffvi5xHfffRcHDhyASCTCggULsH37dowaNQpHjhwxGDtqJkK8efPmExs3gKbVH+qLdWJVLrC+ffti2bJlRj1fpghTAeD06dNmnWh1dTWmT5+OPn36oHPnzvz+V199FUqlEj169MBzzz2HDz74AFeuXMHJkycRFRWlty1LnT7PLD2IO8UV2DapN572bJxpeoJ4EhDSBaZFIpHoHcgUFhZi/fr12Lx5M5YuXYqsrCzExcWhY8eOOHr0KPbv328wdjyM9lzrihu/nL+FD368gGBfZ6yfEGR5hwiCqEWjucAWLVqEjz76yKjnyxRhqiVMnToVqampOHz4sM7+iRMnwtHREZGRkRg8eDAWLFiAN954A/b29gZdYJY6fewdHJBfeR9ieTNy+hBEAyBkfpxr167B09MTcrkcISEhiI2Nhbe3N1JSUlBZWYnw8HBUVVXxLjAPDw+89957KCkp0Rs7aj4ErVKpANTtEGzpXAqRzBaV5BAkiAajwV1gpni+TBGmmktUVBR2796NQ4cO6Z3iqunzATRSVkP38y11+iikD2a1KqrMfi1BEI1HcHAw4uPj4e/vj5ycHHz88cfo168fUlNToVQqIZVK4eTkpBM7tKb4PXv26I0dhmaO66KZVJMx/n4F5QkjCGvCrESI5ni+AM0qi1OnTiElJQX5+flmnxxjDFFRUUhISMCBAwfg6+trsK7W56N9Tklfltj6YvsgkJVSICMIq2bIkCH497//jYCAAERERCAxMREFBQXYtm1brbra2BEYGIjXXnsNwcHBetucPXs2CgsL+ZKdnW3SuSgexI2ScrpwIghrwqwBkFqtNsnzVZcw1VSmTp2KTZs2YfPmzbC3t4dSqYRSqURpaSkAICMjAwsWLEBKSgqysrKwa9cujB8/HmFhYQgICDCnaybhpNA8cJ1XXCF42wRBNBxOTk7w8/NDeno63N3dUVFRgYKCAp06dS2ckMlk/O2uum57PUxLO81s8x1VOdRV1Rb3gSAIYTF7GfyECRN0bh+VlZVh8uTJfF6esrIynDhxwqgwNTU1lU+UaIw1a9YA0KS9f5i4uDhMmDABUqkU+/btw8qVK3WSITVv3hwnTpww2QVmKu1c7bD/ym1cy1UJ2i5BEA1LcXExMjIy8Nprr6Fnz56wsbHB/v37MXr0aKxatQqLFi3CrVu3sG7dOvTp00fQ2NHKSQGFjRillVW4fvc+2rrYCdY2QRCWY9YMUGRkZJ2er+zsbPj4+ODMmTN45513EBERgcGDByM6OhqnT5+Gl5cXVqxYYdL76XP9aAdhgCYBWXJyMlavXg2RSISvv/4a58+fbzCfj5+b5inzY3/lo6qaHD4EYa3MmDEDycnJyMrKwtGjR/HCCy9ALBZj7NixcHR0xJtvvono6GjMnz8f06dPh0KhQLdu3dCnTx/BY4dIxMHPXRM7fruYK1i7BEHUD7NcYKbQvn17fPLJJxg7dqze41u2bMGSJUvMXgZvjMZygd0tqUDfxQdwv6IKnVs5YICfK55qroCTrQ0c5DaQiEWQiDnYiB78FHPQGni0D6hrn1PXPrH+z7b2uG79hyGfDvE4IhZx8HBUGK0jtAtszJgxOHToEPLz8+Hi4oK+ffviv//9L9q21TjJysrK8N5772Ht2rXgOA7Dhw/H6tWr4erq2iAusO//vI65CakAgH7tW6K7d3O4OcjQopmM9wRKJSLIJKIHrkBNLND8BO/84n8HdOoQxKOgof/tOSpsYC+3MVqnPrFD8AEQx3E4fvw4/yBhTRdYeno6AgMDa91/t5SKigrY2tpi+/btGDlyJL8/MjISBQUF+Omnn2q9Rp/Tx9vbu858HgDw+0UlPthxARVqupdPEKbQ0k6KpJnGFyVoU1EUFBQ0mgrD3NhRn7hRVc0Qm3gZW06a9uA0QRDAzAg/RIYaXvwE1C92NIiy3c7un3vcNV1g9vb2KC4uFuy9zPX5AOT0IYjGhFxgBEFYglW5wEylpKRER4yqUqn47aKiokY1PuuDnD7UF2umKfXnUbnAGgKKGxqaUn+oL9ZJY7nAwAQGAOM4jolEIiYSiWpta383hUWLFrHAwEBmZ2fHXFxc2IgRI9iVK1d06oSFhTEAOmXSpEls/Pjx7PnnnzfpfbKzs2u1QYUKlcYv2dnZZsccSykvL2disZglJCTo7Dc1dlDcoELFeoolsUPwGSCO4+Dr6wuxWJP8KyMjA97e3ry01BySk5MxdepUBAUFQa1WY86cORg0aBAuXbrEL7vnOA4uLi547rnnsGjRIgCAXC5H586dTfL5AKY7fcIWH8Dd+5XY8X8h8HOjlPYEIRRCu8BMscG/9957AICXXnqJfwjaxcVFcBfYT2f+xtydqQht1wJfvxZoaZcIgtBDo7nATGHevHk4evQo0tLSUFVVhZCQEAwYMMCiAdCePXt0tuPj4+Hq6oqUlBSEhYXx+wMDA7F582b0798fvXr1wsqVKw36fADLnT52Dg4oqCqFSEYuMIJoCIR0gdVlg//ll18we/ZsLF68GOfOncOQIUMQFBRkNHboO9e64oZLixKIZLZQi8gFRhANRYO7wExqUCLBgQMHeGHq3r174efnpyNMtZTCwkIAgLOzs87+kydPQiKR4K233kJVVRW6d+9u0OcDWO70+UeFQSntCcLaMcUG/+KLL8LNzQ2LFi1CRkYGysvLjcYOS7B94BAsobhBEFaFWYkQTUErTN27dy/WrVuHZcuW4bvvvsOdO3fq1W51dTWmT5+OPn36oHPnzvz+V155BZs2bcKxY8cQFxcHDw8PeHt7G/T5APVx+pAMlSAeF7Q2+DZt2uDVV1/FjRs3AEDHBg9oXGC3bt2Ct7c3/vOf/xiMHeXl5SgqKtIpptBMRjJUgrBGBJ8BunHjBtq2bYuwsDAcOXIEgGbw4u7ujv79+2PNmjXw9/c3u92pU6ciNTUVhw8f1tk/ceJE/vcuXbrAw8MDAwcOREZGBp/0rCaW2uDtHgQyVVllHTUJgniUmGqDfxg3NzfeCK8PS2eOHR4kcssvrgBjTNDbfARBWI7gM0CVlZV4+eWXcefOHSxfvhyJiYmQy+WYNWsWcnJy0K9fP7PTzEdFRWH37t04ePAgnnrqKaN1tVdv6enpFvfBEN7Omgev/7pTInjbBEEIhzk2eFOxdObYp0UzSEQcisvVUBaVWfz+BEEIi+ADIMYY1Go1/Pz8kJycjLVr10KtVuPUqVPw8/NDZWUl+vXrZ3JbUVFRSEhIwIEDB+Drazgj5KpVq9C6dWs0b94cgCbJmdD4uWkSPF68VSh42wRBNBzGbPDa2HHy5Els2bIFJ06c0NuGpTZ4qUSE1i01F08p1+8J0h+CIOqP4AMge3t7dOvWDc7OzrWEqc7OzggICDB5cDJ16lRs2rQJmzdvhr29PZRKJZRKJUpLSwFoltgvWLAAsbGxePfdd/H888/D3d0d7u7uiIqKElyGGtRa8/B18tU7WPfHX7ieXwJ1FSkxCMLa0drgPTw8dGzwW7duRXR0NH8rvVu3bg0iUv7X05qHqj/adRGbjl/H1VwVSsrpmSCCeJRYtQvM0L3yuLg4TJgwAdnZ2Rg3bhz/rJGvry9eeOEFzJkzB506dTIoNKy5DF6bR8AUmVr01rPYceZvnX0Ocgns5TawEXOwEYs0RSKCWCs4fUh8qiM9rSVI1ZWh0qMCRFPASSHFqld7GK0jtAx1xowZGD58OHx8fHDr1i3ExMTg7NmzuHTpElxcXDBlyhQkJibC1tYWXbp0wc2bNwEAhw8fNihDrU/cKLxfiZe/PoYrSpXOfoWNGAqpGHKJCHIbMaQPZKgirfyU4yB6ECpEnGY/ODzYZ30BwtpilrWdD2Eerwb7YGgXD6N16hM7rNoFVtfYzMvLC7///rteoWF4eDiOHTum93WGHmY0ZVXHvAhf+DmLsetcDtJyVahUV6OgHCigu2IEoZeWdlIUFbUzWkf73RPqeuzmzZsYO3asjg3++PHjcHFxAQCsWLECjDGsXbsWmZmZGDp0KFavXg2RSGQwdtQnbnAANrzaGVtP3kBy2h2k5apQUl6FknKAnigkCP30fkqBIp9mRuvUK3aYnTu6DgCwP//8kxUWFrLCwkJmZ2fHzp49y29fvXrVZBVGTExMrXTX/v7+/PHS0lIWGRnJADCFQsFGjRrFlEolY4yxmTNnsl69eultt6ysjD+fwsJCdunSpUeexpsKFSqNq8L4+++/GQB29OhRnf2GYgfFDSpUrLdYhQoD0Nz20t72qa6uRvfu3fltZuYy0Lqyuf7+++8ANA8yfv311xg1ahR/S8wQNZfB29ra4sSJE3Bzc3tipIbUF+ulKfWnKclQKW5oaEr9ob5YJ40lQ7VqFxhQdzbXjRs3Yty4cWjevDni4uLQsWNHHD9+3OgfpOa9/L///hu9evUy+Zyefvpp8ztipVBfrJem1B9T+5KdnV1nqguhaNmyJcRiMXJzc3X2mxpMlUrlExs3gKbVH+qLdWJOXyyJHVbtAgP+yeYql8sREhKC2NhYeHt789lcBw8ejJ49e2L//v0YOXIkvL29cfToUaNCQ0P38uuSGg78f0nILSrH1om90amVo0X9IQiiNkLLUA8dOoSlS5ciJSUFOTk5SEhI0HlGkDGGhQsXQiQS4cUXX8SAAQOwZs0atG3bVnAZauKFHLy//TyCWjdH3OumD5gIgqgbq5KhCukCMzWba3R0NCIjIxEYGAhHR0ds3LjRqNBw9uzZiI6O5re1f8C6cnvYOzjgTrlGbEhSQ4IQHqGyJJeUlKBr16544403MGrUqFrHlyxZgs8//xzvvPMOPvvsM9y9exfPPvssBg0aJLgMtWXzUo0MVUwyVIJoKKxChqp1gU2aNAl5eXnYunUrpk+fjsWLF/MrMExlyJAh/O8BAQEIDg6Gj48Ptm3bBoVCwR/TZp6eP38+srOz4e7ublRoaKkKoxm5wAjisWDIkCE68eNhGGNYuXIlPvzwQ8yYMQM+Pj5YvHgxbt68ieTkZIOxQ98yeFPQSpQpbhCEdSF4IsSHXWBubm54++23oVar4e7ujmeffRZpaWkWt20sm2tUVBSuX78OLy8vzJw506gM1VIUDwJZCUkNCeKxJTMzE0qlUkeGmp2djbCwMAwbNsxg7IiNjeWTuzo6OsLLy8uk91PQAIggrJLHwgWmxVA2Vy1paWm4ceMGQkJChOqODu4OcgBA9t3SBmmfIIiGRys8rTnLU5cM1VIXWEs7zWzzHVU5ZY4nCCvCql1gM2bMQHJyMrKysnD06FG88MILEIvFGDt2LBwdHfHmm28iOjoaBw8exAcffICuXbuC4zi88847Bn0+9cHfXfOQVZrStKlvgiCsH60L7Mcff8S+ffsEd4G1clJAYSNGRVU1rt+9L+SpEwRRDwQfADk7O6N79+6CuMC02Vz9/f3x0ksvoUWLFrWyuT733HMYPnw4lixZgk6dOuHgwYPo2rVrg/h8nvbUBLyDaXdwI58CGUE8jmiXuOfm5vIusJiYGPTo0QMeHh6Cxw6RiIPfg4unXWdvCdYuQRD1Q3AXmJ2dHU6dOoUOHTroPW6OC8xUgoODERQUhC+//BKAJjGSIZ+PPkx1iairqjH4sz+QfrsYEhGHTq0c4eNsC+dmUjgobCAVc5BKRLwPTCzianu+OK0TrMaxB8fJXUM0NeQ2YkR0Mp5XR2gX2MNwHKezDJ4xBk9PT8yYMQPbtm1DUFAQFi1aBFdXV2zYsAEzZ840KXaYc85bT97ABz9eAAC0cWmGjh4OcLGTwV4uQTOZBBIRB7GIe/BTBImIg0hU2/ZVMz7U2q7xirriiVCr7giiIXjawwHtXO2M1rEqF1hJSQmqqv552K+mDNUcF5gpVFRUICUlBbNnz+b3GfP5ALVXcxQWakRepqzq+PLFDpi94wJSrt/DmfQSnKnn+RNEU6elnRQhM58xWkdoF1hxcTHS09P57czMTJw9exbOzs7w9vbG9OnTsXDhQhQVFeGVV17B+PHj4enpiVGjRmHv3r16Y0d94sZgP0ekB7tjw5EspN+8j/SbdwToJUE0bWZG+CEy1NdonSbrAjMFc30+jOl3jFGhQuXRF6FcYAcPHtTbfmRkJGOMserqajZ9+nQGgEmlUjZw4ECWlpZmNHZQ3KBCxXpLk3SBNQQ1EyGq1WpcvnwZXl5eT4zTh/pivTSl/jwqF1hSUlKtff7+/oiPjwegmc25d+8eAEAsFvPPKxqD4oaGptQf6ot10lguMMFngEQiEdu5cydLSkpiSUlJzNbWlv3www/8traYSnJyMnvuueeYh4cHA8ASEhJ0jpeVlTGO41jz5s2ZXC5nAwcOZFevXmXjx49nzz//vEnvkZ2d/chHr1SoUBFuBigmJoZ16tSJ5eTk8OXOnTv88cmTJzMvLy8mEonYsmXLWO/evVloaChjjJkcOyhuUKFiPcUqZoAYY5g8eTJUKhUYYygtLcWCBQtqZV4+ffq0Se3VldJ+5cqVEIlEvCds3rx5iIiIQHl5OaZNm2bSe5jq9AGA7Lv38eJXR1FSXoWWdlK0tJchPbcY6moGAGjn2gxvD/TDM/4uj3ymiyAeF4R2gQF1i5Q3b96MpUuXIisrixcp1+URfBhT48ahq3fwf9+fhr+7PX6cEmp5hwiCqIVVucAGDBiApKQktGnTBhKJBBkZGZBKpRgxYoRF7ZmS0n7MmDHYvn07zpw5g7lz5yI0NBQymcygz6fmw4wqlQpA3U4fAPg6MQOlkKGXX3Ns+k8w5DZi3C2pwPfHr+ObP/7CX4VqTN+RhqDWtzF7aEf08G5uUb8J4klEyIuGukTK4eHhqKqq4j2CHh4eeO+99wy6wCyNGx19RBDJbHGrRDNoogsjghAeq3CBZWdnY82aNZg0aRIAYN++fRg2bBhSUlKM3ie3BG1K+xkzZqB3796YP38+lEolbG1tMWTIEIMuMEM2+LrIKy7H7vM5AICPnu8EuY0mxb1zMymmDWyP8aGtsTY5A+sPZ+Jk1j2MWn0Ugzu54/3B/mjjYnwpH0EQwmGqSPlhj6A2C7QhF5ilceOp5gqIOKCkogo375XCy9m23v0jCKL+NIgLbOjQoQCAvLw8ODk5gTGGixcvCv1WOinttS6w8vJyDB482OjrLE1pfyQ9D1XVDB09HNC5lWOt444KG7w/uAOSZg7AS4FPQcQBey4q8a8VhzA34QJyCkmhQRCNwZAhQ/Dvf/8bAQEBiIiIQGJiIgoKCrBt27ZadbWxIzAwEK+99ppBF5ilcUMmESPQxxkAsOP035Z3iiAIQRF8AKRWq5GVlcXLUIODg1FZWYlu3brVW4YqFJamtD98TZPBul/7lkbreTgqsOTFrvj1nTAM7OCKqmqG7/+8gb6LD2LKphQcTc9D9YNnhgiCaHiMiZS11LWSxNK4AQCv9vYGAKw9lIHUvwst6gNBEMIi+ACouroaAwcOxJkzZ9CpUyf07t0bIpEI7dq1w8mTJxEQEIBhw4YJ8l4Pp7TX+nzkcjn27NkjSPs1uXZbk8Cxu5eTSfX93e2xfkIQtkzsjd5tnFFVzfBrqhKvrPsTvWP3I+anVBy+lodSskQTRINiTKS8atUqtGrVCjdu3MC6desaxCM4PMATfdu1xP2KKry89hg2Hb+OShKjEsQjRXAVRpcuXZCTk4MhQ4ZAItF9xEitVuPXX3+Fp6cnzp8/b3bbhlLah4eHY9u2bfjqq6/QqVMn/iHozMxMuLq61tmuqam0Q2P341ZhGXZO7YNuJg6CHiZNqcJ3x7Pw09lbUJWp+f02Yg5dn3JCd28ndHB3gL+7Pdq52vHPGBFEU0doFcaMGTMwfPhw+Pj44NatW4iJicHZs2dx6dIluLi4YMqUKUhMTERkZCRiY2Ph4+MDe3t7BAUF4X//+x/S0tLqjB3mnrOqrBL/+fYU/sy8CwBwd5DjuQAP9Pd3QVcvJzjIberdb4J40rAqFUZZWRm++OILjB07Vu/xLVu2YMmSJSa3Z0pK+7lz5yIiIgKBgYGYN28evL29UVZWhg0bNpjkAjOF6mqG2yrNChA3B1kdtfXj726PhSO7YP5znXAkPQ+JF3JwOD0POYVlOHX9Hk5dv6dTv6WdDJ5Ocng6KuDqIIOjwgaOChs4PPhpJ5NAJhFBKhFBJhFDJhFBZiOCVCyCRCQCJwJEHAcRp/35z+8a/xitRiGaJlqRcn5+PlxcXNC3b99aImWRSIRFixaB4zgEBARg9erVcHV1xS+//CJo7NBiL7fB5rd649ujWVidlAFlURnWHc7EusOZAABvZ1v4tLDFU81t4e4gh5OtDZxsH/6uiyGzEel8523EHP/d5h76bmu/6/QdJwjDCD4DxHEcjh8/zj9IWNMFZq4MNSkpCc88U9sjFBkZifj4eJSXl0OhUMDR0RGlpaXo27cvVq9ejf/+978oKCjATz/9VOu1NZezavMIGBtB5hWXI3DhPnAccHXhENiIhbl7yBhD9t1SHP8rHxdvFeKKUoUrShUKSysFad8YOoGylnbR2AsbpKrZIlizzpl4ZLS0l+KP9581WqchZaiGqKiogK2tLbZv387PKgOa2KIvdlgSNwxRVlmF5Kt3sDdViVPX7+HG3fv16osxHr4AEuorI9Q3T6jxGcWCpsn7g/3xep+6XWBWMwMEaIzwWi5evKgTNMyRocbGxmLHjh2ws7ODQqFAaGgoFi9eDH9/f77OM888A8YYP6Dav38/li9fDjc3N1y5csVgu/qWsxqTGmbkFKK6/D5aNJOitKQYQq7ncrIBBvs7YrC/ZmUZYwz37ldCWViKnMIy5BSW4m5xJYrKKlFUWonCskoUlapRVlmFcnUVKtTVqFBXo7yqGhVqZtazBfT0EdHQKCCtUxgqtAzVFPLy8lBVVVVrybuh2GFJ3DBGiJctQrzaAADuFpfjrzslyL53H3/fK0VeSQWKSitQWKpGQWkl7leo+e95RZXmZ2WVaX8retKIeFwpVhU1bOwwO3d0HQDCyVAjIiJYXFwcS01NZWfPnmVDhw5l3t7erLi4mK8TEhLCALCff/6ZT3lfWFhoVIZaVlbGn09hYSG7dOnSI0/jTYUKFeFUGKZgrkiZ4gYVKtZbrEKFAQgnQ625mis+Ph6urq5ISUlBWFgYAMDGxgYcx0GtVussYTW2pFUmk+moOWxtbXHixAm4ubk9MVJD6ov10pT686hkqKbQsmVLiMVi5Obm6uw3dB4UNzQ0pf5QX6yTx1aGynEca9OmDWvfvj1r3749E4lErHXr1vy2tljCtWvXGAB24cIFfl///v2ZRCJhcrmcderUic2aNYupVCrWqlUrFhsbq7cdupKjQsU6S2POADHGWK9evVhUVBS/XVVVZTR2PAzJUKlQsZ5iFTNA8+bNw9GjR5GWloaqqiqEhIRgwIABsLGp3xLP6upqTJ8+HX369EHnzp35/a+88gpCQ0OxbNky9OnTB3FxcdiyZYtBnw9g+F5+XVLDfy1PRk5hGTa/FYyAp5zq1R+CIP5BaBnqoUOHsHTpUqSkpCAnJ0cnfQYAMMYQExODq1ev4sSJEzhw4ACWLVuGnTt3Go0dD2OqDHVvqhLv/e8cevo0x7dv9Kp33wiC+AerkqFKJBIcOHAA4eHhUCgU2Lt3L/z8/LBhw4Z6tTt16lSkpqbi8OHDOvsnTpwIAPD09MTSpUuRn58PtVqN7du3G3SBzZ49G9HR0fy29g9YV3ZXewcH5JZpxIaNtVKFIJ4khFq2XVJSgq5du+KNN97AqFGjah1fsmQJPv/8c3z77bc4fvw4PvvsMwwdOhSBgYEGXWCGzrWuuNHSuQwimS3UYjnFDYJoIKxChrpx40asXr0akyZNQl5eHrZu3Yrp06dj8eLFfA4Oc4mKisLu3btx6NAhPPXUUwbrREVFoaSkBHZ2djor0WpS816+qdhKNYkJKXMzQVg3Q4YMwZAhQ/QeY4xh5cqV+PDDDzFixAiMGDECs2bNgpubG9577z2DLjB9y+BNQfEgbtyvUNdRkyCIxqRBZKht27blXWBvv/02/4CyuS4wxhiioqKQkJCAAwcOwNfXeD4AADh79iwAwMPDw9IuGETxIDNzCQ2ACOKxJTMzE0qlEuHh4fw+R0dHBAcH49ixYwZfFxsbC0dHR754eXmZ9H7aC6eScoobBGFNCD4AqqysxMsvv4w7d+5g+fLlSExMhFwux6xZs5CTk4N+/frh9u3bJrU1depUbNq0CZs3b4a9vT2USiWUSiVKSzVZeDIyMrBgwQKkpKQgKysLu3btwvjx4xEWFoaAgAChu4ZWTgoAwI38EsHbJgiicVAqlQCgN/+P9pg+LLXBuzvKAQC5qjKUVdIgiCCsBcEHQIwxqNVq+Pn5ITk5GWvXroVarcapU6fg5+eHyspK9OvXz6S21qxZg8LCQgwYMAAeHh582bp1KwBAKpVi3759GDRoENq3b4/Ro0fj+vXrKCkpaRChoZ+75iGry0qV4G0TBPFo0IqUf/zxR+zbt89g7LDUBu9iJ4OTrQ0YA9Jvm5YEliCIhkfwAZCzszO6d+8OZ2dnfqp43Lhx8PT0hLOzMwICApCXl2dSW4wxvWXChAkAAC8vLyQnJ2P16tUQiUT4+uuvcf78efTo0QMREREmzzSZSkArRwDAwSu3cTQjD9XVTND2CYJoeLT5QnJzc7F161ZER0cjJiYGPXr0gIeHh+Cxg+M4dHkQO9YkZeBeSYVgbRMEYTmCu8Ds7Oxw6tQpdOjQQe9xc11gphAcHIygoCB8+eWXADRL5r28vDBt2jS9QkNLnT6MMbz41TGkPJCW2krF8HRSwOmBoFQi4mAjFkEi5iARiWAj5h5y3Wh+0W5rd/+zrf+4Zh95bojHF3u5BO8N8jdapyFdYBzH6SyDZ4zB09MTM2bMwLZt2xAUFIRFixbB1dUVGzZswMyZM/XGjvq4wI6m5+HV9X9CG209HeVoaS+DvVyCZlIJJGIOYpEIEhEHsYiDRMRBJKptuKoZCmrWqH289t+CIB4XBnVyQ2jblkbrWJULrKSkBFVV/9znrilDNccFZgoVFRVISUnB7Nmz+X0ikQjh4eEGH2isj9Nn5Sh/LP8tDb9cyEGxqhpXVXQ7jCCM0dJOird6G1+UYK7Pp648PyqVCu+99x4SEhIAAO+//z44jkP37t3h7e2N6dOn45NPPkFRURHOnTuHtWvXQi6XY9CgQdi7d6/e2FGfuNHZVYrPRvnj8/3XcDW3GDdv38dNYSeoCaLJ0UKqRmcXqdE6TdYFZgrm+nwYo0zQVKhYazE1m2tiYiKbO3cu27FjBwPAEhISdI5PnDhRb/vjxo1jjDFWXV3NfHx8GAAmkUhYz549mY+PDxs7diy5wKhQeQyLVWSCBoRzgTUU5PShvlgzTak/DeUCqyvPz65du7B06VLMmDEDAFBYWAg3NzcMGzYMAHDlyhVcv34dgGY2KSQkBHv27MHQoUMxefJkve1S3NDQlPpDfbFOHlsXmEgkYjt37mRJSUksKSmJ2drash9++IHf1hZTiImJqTXK8/f354+XlpaySZMmMQBMLpezUaNGMaVSyRhjbPz48ez555836X3I6UOFinUUS67iAN0ZoIyMDAaAnTlzRqdeWFgYe/vttxljjK1fv545OTkxsVjMv7ayspKJxWI2YMAAvbGDZoCoULHeYhUzQIwxTJ48GSqVCowxlJaWYsGCBbUyL58+fdqk9jp16oR9+/bx2xLJP6f87rvvIjExER06dEBAQABu3LiBUaNG4Y8//sD+/fsRFRVl0nuY6vR5dtlB3FZVYNuk3nja09GktgmCqBshXWCm5PlRKpVwdXWFn58f9u/fj5EjR0IikcDZ2RlnzpzRu3jCUodg4oUcvL/9PHq1dsaG14Pq0zWCIGpgVS6wAQMGICkpCW3atIFEIkFGRgakUilGjBhhUXsSiUTv1FZhYSHWr1+PzZs3o6qqCpGRkYiJicGcOXMwatQok4WGgOlOHwcHR+RVlEAka0ZOH4JoABr79nh0dDQiIyMRGBiIXr16QaVSgeM4vbHDUoegi3MpRDJbVIhlFDcIooGwChdYdnY21qxZg0mTJgEA9u3bh2HDhiElJcXofXJDXLt2DZ6enpDL5QgJCUFsbCy8vb2RkpKCyspKhIeHw8nJCXfu3MHSpUsBAGfOnDEqNLTU6WMr06owyOlDENbKw3l+Hlbi5Obmolu3bnyd27dv81nr58+fj5ycHFRWVuLTTz/VGzssdQg2k2nCbEk5xQ2CsCYaxAU2dOhQAEBeXh6cnJzAGMPFixfNbis4OBjx8fHYs2cP1qxZg8zMTPTr1w8qlQpKpRJSqRROTk4ANDLU69evIygoCGPGjDEoNATq4/ShQEYQ1o6vry/c3d2xf/9+fl9RURH+/PNPhISEAABCQkJQUFCAlJQUPnbs3r0bHMfhtddeE/R87B4MgIrKKG4QhDUh+AyQWq1GVlYWXn31VRw5cgSA5intbt26oX///lizZg38/Y0nRdPy8CqPgIAABAcHw8fHB9u2bYNCobD4HA1NZdeFu4PG6ZN9t9Ti9yYIov4UFxcjPT2d387MzMTZs2fh7OzM5/lZuHAh2rdvD19fX8ybNw+enp58rqCOHTti8ODBeOutt/DVV1+hsrISUVFRGDNmDDw9PQU9V6/mtgCAO6pyqMoqYS+3EbR9giAsQ/AZoOrqagwcOBBnzpxBp06d0Lt3b4hEIrRr1w4nT55EQEAAvxTVXJycnODn54f09HS4u7ujoqKCzyit9fmcPHkSW7ZsMeoCs9Tp4//ABXYtl5IfEsSj5NSpU+jevTu6d+8OQPMsT/fu3TF//nwAmsSH06ZNw8SJExEUFITi4mLs2bMHcrmcb+P7779Hhw4dEBYWhn79+iEjIwNXr14V3CPoaGsDNwfNrbM08ggShNUg+ACoc+fOcHBwwMiRI9GzZ0/4+flh/PjxCA0NxciRI2Fvb2+yRbkmxcXFyMjIgIeHB3r27AkbGxvs37+f9/lMnDgRANCtW7cGcYE97akZKB1Mu43cojJB2yYIwnQGDBig1xMYHx8PQPNA5CeffAKlUomysjLs27cPfn5+Om04OztjxIgRYIxh/fr1uHDhQoN5BHv6NAcArE7KICM8QVgJgrvA2rdvj08++QRjx47Ve3zLli1YsmSJScvgZ8yYgeHDh8PHxwe3bt1CTEwMzp49i0uXLsHFxQVTpkxBYmIibG1t0aVLF9y8eRMAcPjwYaMusJqY6hJRV1Vj0IpD+CuvBM2kYoS2a4m2LnZwtZfBQWEDuY0IMokYchsRJCIRRJwmEGt/chwg0m5Ds81xtX0+1oQ1q4Os+dyIf5CIOLRzNb5EtSFdYMYw1yP4MOac8/mbBRi95igqqxgcFTYIau0Mb2dbuDvKYCezga1UDIVUDJlEBLGIg5jjwHEaL5hYpIkfYo6DiOMs/ndf1+uMxSFjr6XvIdFQuNjJ0MLO+MIDq3KBpaeno02bNvx2TRdYYGAg/vrrL5PaunnzJsaOHYv8/Hy4uLigb9++OH78OFxcXAAAK1asAGMMa9euRWZmJoYOHcqb4Y25wGquAissLARg2mqwz0b7492tZ3E1V4W9Z2g6myDqoqWdFEkznzFap14+HwvZv38/Tpw4gWvXrmHVqlW8T8xQ7KhP3GjtIMKKF/yxYPcl5BQU4rezhcJ1hCCaKDMj/BAZ6mu0Tn1iR4OoMOzs7PjfL168qBM0zJGhdu3aFRkZGVCpVKioqEBZWRnU6n9WUsjlcpw/fx6AJjglJCQgISEBkyZNgpubG65cuaK3XUMJzUxdDUYQhOlkA3BcaFpdlUoFR8fGSTKak5MDQPO80MMyZUOxg+IGQTQub68E3jaxriWxo0EGQCUlJTpXRSqVit8uKioyeaSWnJyMqVOnIigoCGq1GnPmzMGgQYNw6dIlNGvWTKfuzz//jMDAQAAaR8/ChYYjbs1VYGq1GpcvX4aXl9cT4/ShvlgvTak/DeUCE4Jnn30WANC/f3+T6kdHR+M///kPv61Wq5GZmYm2bds+MXEDaFr9ob5YJ4+tCwwA4ziOiUQiJhKJam1rf7eE27dvMwAsOTmZ3xcWFsY4jqtlgzbmAiOnDxUq1lks8flYSnl5Oe8CA/7xiRmKHfrchFSoULGOYhUuMI7j4OvrC7FYkzU5IyMD3t7esLGpf+4L7T13Z2dnnfcTi8UYO3Ys2rZti+HDh2Pu3LlGXWCWOn3CFh/A3fuV2PF/IfBzo5T2BCEUQrrATEUqlaJnz546CROrq6sNxo6aM8eFhYXw9vauM24QBNFwWJULbN68eTh69CjS0tJQVVWFkJAQDBgwoN4DoOrqakyfPh19+vRB586d+f2vvPIKQkNDsWzZMvTp0wdxcXHYsmWLUReYpU4fOwcHFFSVkguMIBqIR+UCAzQXQFOmTDEYOwypMMzJJUYQRMNgFS4wiUSCAwcOIDw8HAqFAnv37oWfnx82bNhQr3anTp2K1NRUHD58WGe/NvePp6cnli5divz8fKjVamzfvt2gC8xSp4+tVDOrVVpBeTwIoimgdYFNmzYN0dHR6NGjh1GPIEEQTQfBEyFu3LgRq1evxt69e7Fu3TosW7YM3333He7cuWNxm1FRUdi9ezcOHjyIp556ymCd69ev85mhH16JJhSKBy6w+zQAIogmg/Z21//+9z/8+eefRj2CBEE0HQSfAbpx4wbatm2LsLAwHReYu7u72S4wxhimTZuGhIQEJCUlwdfXeD4AADh79iwA6FighcLugQ2+qLRS8LYJgmhc6vKJEQTRtBF8BqiyspKfVl6+fDkSExMhl8sxa9Ys5OTkoF+/fianmZ86dSo2bdqEzZs3w97eHkqlEkqlEqWlGhlpRkYGFixYgJSUFGRlZWHXrl0YP348wsLCEBAQIHTX4NNCs/T+rzzT8hgRBGG91OUTIwiiaSP4AIgxBrVaDT8/PyQnJ2Pt2rVQq9U4deoU/Pz8UFlZiX79+pnU1po1a1BYWIgBAwbAw8ODL1u3bgWgWcWxb98+DBo0CO3bt8fo0aNx/fp1lJSUCC40BAA/V81ttYu36s78ShCEdaP1iX355Zfw8fGBTCZDr1698H//93+P+tQIgmgEBB8AOTs7o3v37nB2doajoyMcHR0xbtw4eHp6wtnZGQEBAcjLyzOpLaZHdsgYw4QJEwBoMrAmJyfz+ouvv/4a58+fbzChYXCbFgCApLQ7+PLANVzOKUJRWWWjpu8nCEI4tCLlmJgYnD59Gl27dm2Q2EEQhPUhuAzVyckJp06dQrt27fQeT09PR2BgIP+wshCYKzSs6fTRLoM3RaY268fz2HJS12YvFnGwl0sgEYlgI+YgEXOwEYkgEXO8YLDmCj3tkj2O367x8yEx4T/7COLxw8lWim/f6GW0TlOXoRIE0TBYlQxVpVIZPQlzXGCmUFFRgZSUFB2XT10yVEOJEE2RGs4a6IMOzhL8fP4WriiLoCqrQjWAu6UWd4EgmjQt7aR1frcehQzV3NhRHxkqQRANg9XJUFUqFeRyud5j5rjATCEvLw9VVVW18nYYk6HWTIT4999/4+mnnyapIUE0ANYqQzU3dpAMlSCsF6uQoTLG4OfnZ/R4Y2d7rUnNRIh2dnbIzs6Gvb290XPT3iprCqnvqS/WS1Pqj6l9YYxBpVLB09OzEc/OPGpeOFVXV+Pu3bto0aLFExM3gKbVH+qLdWJOX+oTOwQfAB08eFDoJo3SsmVLiMVi5Obm6uw3xw4rEokMJljUR1NKfU99sV6aUn9M6UtjzfxoMTd26Msg7+TkZPL7NaXPE2ha/aG+WCem9sXS2CH4AKhv375YtmwZdu3ahYqKCgwcOBAxMTFQKBRCvxUAXaHhyJEjARgXGhIEQQAUOwjiSUfwAdCiRYvw0Ucf8S6wzz77DLdv3663C8wYWqFhYGAgevXqhZUrVxqVoRIEQQAUOwjiSUbwAZDWBTZp0iQAwL59+zBs2DCsW7cOIpHgaYcA/CM0nD9/PpRKJbp169YgQkOZTIaYmBiLRKrWBvXFemlK/bH2vjRG7LD2v4G5NKX+UF+sk8bqi+B5gGQyGdLT03VWRsjlcqSnp5v1nA1BEARBEERDIfiUjFqtrrUE3sbGBpWVJBAlCIIgCMI6aJBl8BMmTNCZuiorK8PkyZPRrFkzft+OHTuEfmuCIAiCIAiTEHwAFBkZWWvfuHHjhH4bgiAIgiAIixH8GSCCIAiCIAhrp2GWZT0mrFq1Cq1bt4ZcLkdwcDBOnDhhtP7//vc/dOjQAXK5HF26dEFiYqLOccYY5s+fDw8PDygUCoSHh+PatWsN2QUdzOnPN998g379+qF58+Zo3rw5wsPDa9WfMGECOI7TKYMHD27obgAwry/x8fG1zrPmc2iP8rMxpy8DBgyo1ReO4zBs2DC+zqP6XA4dOoThw4fD09MTHMdh586ddb4mKSkJPXr0gEwmQ7t27RAfH1+rjrnfQ2ugKcUOihvWGTcAih0NHjvYE8qWLVuYVCplGzZsYBcvXmRvvfUWc3JyYrm5uXrrHzlyhInFYrZkyRJ26dIl9uGHHzIbGxt24cIFvs6nn37KHB0d2c6dO9m5c+fY888/z3x9fVlpaanV9eeVV15hq1atYmfOnGGXL19mEyZMYI6OjuzmzZt8ncjISDZ48GCWk5PDl7t371pdX+Li4piDg4POeSqVSp06j+qzMbcv+fn5Ov1ITU1lYrGYxcXF8XUe1eeSmJjI5s6dy3bs2MEAsISEBKP1//rrL2Zra8uio6PZpUuX2BdffMHEYjHbs2cPX8fcv4810JRiB8UN64wblvSHYof5seOJHQD16tWLTZ06ld+uqqpinp6eLDY2Vm/9l156iQ0bNkxnX3BwMJs0aRJjjLHq6mrm7u7Oli5dyh8vKChgMpmM/fDDDw3QA13M7U9N1Go1s7e3Z99++y2/LzIyko0YMULoU60Tc/sSFxfHHB0dDbb3KD+b+n4uK1asYPb29qy4uJjf96g+l4cxJYi9//77rFOnTjr7Xn75ZRYREcFv1/fv8yhoSrGD4oajwfYe95hOsaNunshbYBUVFUhJSUF4eDi/TyQSITw8HMeOHdP7mmPHjunUB4CIiAi+fmZmJpRKpU4dR0dHBAcHG2xTKCzpT03u37+PyspKODs76+xPSkqCq6sr/P39MWXKFOTn5wt67jWxtC/FxcXw8fGBl5cXRowYgYsXL/LHHtVnI8Tnsn79eowZM0ZnBSXQ+J+LJdT1nRHi79PYNKXYQXHDOuMGQLGjsWLHEzkAysvLQ1VVVa1sr25ublAqlXpfo1QqjdbX/jSnTaGwpD81+eCDD+Dp6anzD2rw4MHYuHEj9u/fj8WLFyM5ORlDhgxBVVWVoOf/MJb0xd/fHxs2bMBPP/2ETZs2obq6GqGhobh58yaAR/fZ1PdzOXHiBFJTU/Gf//xHZ/+j+FwswdB3pqioCKWlpYL8u21smlLsoLhhnXEDoNjRWLFD8GXwxOPHp59+ii1btiApKUnnIcAxY8bwv3fp0gUBAQFo27YtkpKSMHDgwEdxqnoJCQlBSEgIvx0aGoqOHTti7dq1WLBgwSM8s/qxfv16dOnSBb169dLZ/7h8LkTThuKG9UKxwzSeyBmgli1bQiwWIzc3V2d/bm4u3N3d9b7G3d3daH3tT3PaFApL+qNl2bJl+PTTT/Hbb78hICDAaN02bdqgZcuWSE9Pr/c5G6I+fdFiY2OD7t278+f5qD6b+vSlpKQEW7ZswZtvvlnn+zTG52IJhr4zDg4OUCgUgnzWjU1Tih0UN3SxlrgBUOxorNjxRA6ApFIpevbsif379/P7qqursX//fp0rgocJCQnRqQ8Av//+O1/f19cX7u7uOnWKiorw559/GmxTKCzpDwAsWbIECxYswJ49exAYGFjn+9y8eRP5+fnw8PAQ5Lz1YWlfHqaqqgoXLlzgz/NRfTb16cv//vc/lJeXm5REtDE+F0uo6zsjxGfd2DSl2EFxQxdriRsAxY5Gix0mPy7dxNiyZQuTyWQsPj6eXbp0iU2cOJE5OTnxyyBfe+01NmvWLL7+kSNHmEQiYcuWLWOXL19mMTExepeyOjk5sZ9++omdP3+ejRgxolGXTJrTn08//ZRJpVK2fft2nSWRKpWKMcaYSqViM2bMYMeOHWOZmZls3759rEePHqx9+/asrKzMqvry8ccfs71797KMjAyWkpLCxowZw+RyObt48aJOfx/FZ2NuX7T07duXvfzyy7X2P8rPRaVSsTNnzrAzZ84wAGz58uXszJkz7Pr164wxxmbNmsVee+01vr52KevMmTPZ5cuX2apVq/QuZTX297FGmlLsoLhhnXHDkv5oodhheux4YgdAjDH2xRdfMG9vbyaVSlmvXr3Y8ePH+WP9+/dnkZGROvW3bdvG/Pz8mFQqZZ06dWK//PKLzvHq6mo2b9485ubmxmQyGRs4cCBLS0trjK4wxszrj4+PDwNQq8TExDDGGLt//z4bNGgQc3FxYTY2NszHx4e99dZbjfYfkzl9mT59Ol/Xzc2NDR06lJ0+fVqnvUf52Zj77+zKlSsMAPvtt99qtfUoP5eDBw/q/TejPf/IyEjWv3//Wq/p1q0bk0qlrE2bNjo5SbQY+/tYK00pdlDcsM64wRjFjoaOHaTCIAiCIAjiieOJfAaIIAiCIIgnGxoAEQRBEATxxEEDIIIgCIIgnjhoAEQQBEEQxBMHDYAIgiAIgnjioAEQQRAEQRBPHDQAIgiCIAjiiYMGQARBEARBPHHQAIhocJKSksBxHAoKCgAA8fHxcHJyMqsNjuOwc+fOep3HkSNH0KVLF9jY2GDkyJH1aosgiIaHYgfRkNAAiBCEY8eOQSwWY9iwYY/6VAwSHR2Nbt26ITMzE/Hx8Y/6dAiCAMUO4tFBAyBCENavX49p06bh0KFDuHXr1qM+Hb1kZGTg2WefxVNPPaX3KpIxBrVa3fgnRhBPMBQ7iEcFDYCIelNcXIytW7diypQpGDZsmEVXSD/99BN69OgBuVyONm3a4OOPPzYaULKzs/HSSy/ByckJzs7OGDFiBLKysvTWzcrKAsdxyM/PxxtvvAGO4xAfH89Pr//666/o2bMnZDIZDh8+jOrqasTGxsLX1xcKhQJdu3bF9u3bddpMTEyEn58fFAoFnnnmGcTHx+tM1RMEUTcUOyh2PFIsELsShA7r169ngYGBjDHGfv75Z9a2bVtWXV3NH9eagO/du8cYYywuLo45Ojryxw8dOsQcHBxYfHw8y8jIYL/99htr3bo1++ijj/g6AFhCQgJjjLGKigrWsWNH9sYbb7Dz58+zS5cusVdeeYX5+/uz8vLyWuenVqtZTk4Oc3BwYCtXrmQ5OTns/v37/HkFBASw3377jaWnp7P8/Hy2cOFC1qFDB7Znzx6WkZHB4uLimEwmY0lJSYwxxm7cuMFkMhmLjo5mV65cYZs2bWJubm46fSQIom4odlDseJTQAIioN6GhoWzlypWMMcYqKytZy5Yt2cGDB/njdQWxgQMHskWLFum0+d133zEPDw9+++Eg9t133zF/f3+dQFleXs4UCgXbu3evwfN0dHRkcXFxtc5r586d/L6ysjJma2vLjh49qvPaN998k40dO5Yxxtjs2bPZ008/rXP8gw8+oCBGEGZCsYNix6NE0vhzTkRTIi0tDSdOnEBCQgIAQCKR4OWXX8b69esxYMAAk9o4d+4cjhw5gv/+97/8vqqqKpSVleH+/fuwtbWtVT89PR329vY6+8vKypCRkWF2HwIDA/nf09PTcf/+ffzrX//SqVNRUYHu3bsDAC5fvozg4GCd4yEhIWa/L0E8yVDs0ECx49FBAyCiXqxfvx5qtRqenp78PsYYZDIZvvzySzg6OtbZRnFxMT7++GOMGjWq1jG5XK63fs+ePfH999/XOubi4mJmD4BmzZrptA0Av/zyC1q1aqVTTyaTmd02QRD6odhBPGpoAERYjFqtxsaNG/H//t//w6BBg3SOjRw5Ej/88AMmT55cZzs9evRAWloa2rVrZ9L79ujRA1u3boWrqyscHBwsOndDPP3005DJZLhx4wb69++vt07Hjh2xa9cunX3Hjx8X9DwIoilDseMfKHY8OmgVGGExu3fvxr179/Dmm2+ic+fOOmX06NFYv369Se3Mnz8fGzduxMcff4yLFy/i8uXL2LJlCz788EO99V999VW0bNkSI0aMwB9//IHMzEwkJSXh7bffxs2bN+vVJ3t7e8yYMQPvvvsuvv32W2RkZOD06dP44osv8O233wIAJk+ejGvXrmHmzJlIS0vD5s2bKTcIQZgBxQ6KHdYADYAIi1m/fj3Cw8P1TlWPHj0ap06dwvnz5+tsJyIiArt378Zvv/2GoKAg9O7dGytWrICPj4/e+ra2tjh06BC8vb0xatQodOzYEW+++SbKysoEuapbsGAB5s2bh9jYWHTs2BGDBw/GL7/8Al9fXwCAt7c3fvzxR+zcuRNdu3bFV199hUWLFtX7fQniSYFiB8UOa4BjjLFHfRIE8biTlJSEZ555Bvfu3TM7VT9BEE8uFDseHTQDRBAEQRDEEwcNgAiCIAiCeOKgW2AEQRAEQTxx0AwQQRAEQRBPHDQAIgiCIAjiiYMGQARBEARBPHHQAIggCIIgiCcOGgARBEEQBPHEQQMggiAIgiCeOGgARBAEQRDEEwcNgAiCIAiCeOL4//V68sPc0t9rAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 60 Axes>"
       ]
@@ -214,21 +215,21 @@
     "study_prior.sample_size = study_prior.sample_size * 0.01\n",
     "\n",
     "# View prior\n",
-    "HLAfreq.plotAFprob(\n",
+    "HLAfreq.plot_prior(\n",
     "    concentration = (2 * study_prior.sample_size * study_prior.allele_freq).tolist()\n",
     ")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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j45wx1E+hHdvfkHb8s3EZSYkJVKz9MQULFSXg1BF2rphJ/0lLqFw/9XfJELC2MOG7T8pkWCY7upEWeb4UfulSXfyTJk2a6OWvXr2avn37YmZmxr59+9BqtQwePBgXFxe6du3KL7/8wtSpU7l+/XqqOl/ftpi8IymzXUTbT92WfrYQSdLPkZGRFChQgB41inHoZZ42IRaENs16vE7dSjNf5u2iTYwn6KAPDj1nonS+zSKPpdjU1RmMxdyNZO/AnpgW0e0O8V6/GuuPWnLe9xJxged5fv82ypaj2HYzCbDDrFZXDnuv5aZ9ExQqEyilm4m7dFcAkVC8BQqbPaxcuwnb+t3SbE9S6CNC/I/h0HMG3oEKwBTq9uL89hk8KdsBlfXLHXPluvAIeBF7EBEWwe++l97sjcoDnAqAk1XGZZK/f1l57mnSpEmG5RQKBVOmTNGL3fQ6Wq0WIQSHDh2SXhuBbpdRWroB2dCOeyfhmW5nR2iC/nCgXpI/Xi9/3nTiVroPNzKGy+vasTAH2rE1hXYc8l7LjTetHXa6+GE3HgAPwsGiOuYu1di0eTOFw4q82RuWQ+wLmtOjerEMy2RHN9IkLxbWZJfHjx8LQJw8eVIvf9SoUaJu3bqpyqe3ilpOcpJT/qecRrZ807ohhKwdcpKToaac6ka+BB0oWrQoKpWKJ0+e6OU/efIkzYBzY8eOZfjw4dJntVrNtWvXcHZ2ztC7ICoqisqVKxMQEEDBggXzrgP5xLvUn5z0pXPnzrRv354BAwagVqupVasWy5Ytw83NDS8vLzw9PaXXCTdv3qRv37506dKFMWPG8OjRI733wXFxcZQvX56///47zdcWS5cuZcmSJRw5coSiRYsC4Ovry6xZszhy5AgAixcvZtu2bfj4+Oj1pXr16gwfPpzevXvr1Tls2DAiIyMzjQ2Rn2Tn/0Wr1ab7nX2dvPAeUiqVKBQKmjdvLr0eWrhwYYZtkLVD7gsYv3YA7Nq1i6FDh7Jnzx69pReGQlb/b7KjG2mSo6FOBhw9elS0b99eFC9eXEBqjxGtVismTJggTE1NhUqlEs2bNxc3b94UGo1GlChRQsyYMSPTa8j+IXKSk+Gkt+k9ZGVlJbp16yZ5D/Xo0SPLuiFrh5zkZDjJYGZaYmJiqFatGv3796dLly6pjs+ePZtFixbx008/sXDhQkJDQ2nWrBmtWrUiJiaGfv36ZXqN5FFcht5Db5Hw2ET6e57h5pPozAsDs7p+RLuqWfNKkdHxtvxDtm3bhru7O2vWrKF169YZtmnt2rWMHz+eBw8eSHlqtRp7e3vWrFlDhw4d9MoPHDiQiIgINmzYkIM7YHgke4hk5Yn3008/5dNPP03zmBCC33//nV9++YXPPvsMgL///hsHBwe2b98ueQ/t3buXadOmMWXKFNq3b8+oUaP4/vvvsbGxyZJuQMbaodEKWi04ypPIhLRORQHY25izf1hjVEp5GayxYOzacfz4cbp37860adOy/HtuyGRHN9IkR0OdLAL6T1RarVY4OjqKOXPmCCGEWLx4sShZsqQARJkyZcR///2XpXpzG5wmp8THx4tvvvlGfPPNNyI+XhcZMyYhSXzmcVy4jvER1X7dJ1zH+AiXEV7C8oPawvKD2sJlhJde0DrXMT7i5O3n6dYnk5qkpCTh4OAg5s2bJy5fvqyXypQpI5YuXZrh+Xv27BFKpVI8efJEylu+fLmwsbHRu+8bNmwQFhYWYvv27VlqV0BAgACEv7+/lLdv3z6hUCjE48ePU5Xv06eP+Oyzz7JUtzGQX8HlFi9eLFxcXKSglDNnzkz3WtkJTHny9vOX319vUeCjFkJVsKiwKF1TOP+0WVhXbSWsq7YSLiO8pe+vjOFj7Npx+PBhUaBAAeHh4ZHVLhs8Bh0RNyfilBY5joibx0RHR0tTW9HR0UKj0Yof1vrrBiyT94mrjyNE/en/CJcU0TSdh23TG7DUnLJfsgh4vT6ZtPH29hZmZmYiPDw81bHRo0eL2rVrZ3i+Wq0WVapUEa1atRIXLlwQe/fuFcWKFRNjx46Vyqxfv16YmJiIJUuWiODgYCmlvKaXl5eoUKGCXt1t2rQRNWrUEKdOnRLHjx8X5cqVEz179tQrc/XqVXH+/HnRoUMH0aRJE3H+/PlU3wFjxBjC+GfHAmT7+UfCdYyPXjRcQJRwX6f3fd5+/lG2+iuTfxizdhw6dEhYWVmJsWPH6tX74sWLnN4Og8BgI+KmRVaM0dIiq6ZnbxpTU1OmTp3K1KlTMTU15feDt/C9EoKpSsGfvWtT2cmGSR3S35cPEBWv5uSd52nWJ5M2K1eupEWLFmnamHft2hV/f38uXUp/G7FKpcLHxweVSoWbmxtfffUVvXv31tteu2LFCtRqNYMGDaJ48eJS+umnn6QyERER3LhxQ6/u9evXU7FiRZo3b07btm1p1KgRK1as0CvTtm1batSowa5duzhy5Ag1atSgRo0aOb0dMtlg7NixRERESOnhw4fplk02TVSoVNg26CnlK5Qq7D7+GruPv0ahUumZK8oYNsasHWvWrCE2NpYZM2bo1ZvWsov3iTwPLqdXuUKht0vg5MmTNGzYkKCgIIoXfxUSu3v37igUCjZv3pxmPa/HWkh+J5bT4DR5wY4Lj/lp0wUA5nSryue1Xw2ktp++Q+d6ZYFXQescbcwpXMCcgOBIzFRKPL6sQasPX1s9rdXA/ZMQ/QSsHcC1AShVyMgYIjkNEvW6Lty9e5cyZcpw/vx5qlevLpVr3Lgx1atXZ+HChaxatYoRI0YQFhYmHVer1VhYWLB161Y6d+6c6zZrtIJGsw7xJCIWdWIiDxfoYmy4DNuCwswKBeBoa8HxMc3kNS0yMjkkt8Hl3upMS/IWp+StzkuWLKFUqVJs27aNo0ePcvr06TTPy7H30Bti75Vghm+5CMB3n3ygN2ABaJliMDLn86ps/LY+J35ujvegBnxaxZFEjZaB68+x8J9bJGleBrQL2KmLyLmmPfxvgO7f36vo8mVk3mGy4z109uxZSTesrKzQaDSYmZnlSTtUSgV/1HyEj9lYvfxuqn9po9Rp06QOleUBi4xMPvJWBy0pxSnZMHH06NGYmpry4Ycf0rp16zwxPntTxCWq+W3rf3z352HUGi1dapRgTJuKGZ7TvqoTbmWKoFIqMDdRsbhnDbrXLolGK5h/4AZNp+5k1bp1xGz6BiKD9E+ODIYtveWBi4zRk1feQ926dWPo0KF8+eWXODk5UaZMGb766qu80Y2X3kOF0Pce2quuzbDEFayscZfWr8+OysjIvFXy/PVQdHQ0t2/rwufXqFGD+fPn07RpUwoXLoyLiwuzZs1i5syZFCtWjFq1ahEXF8elS5e4cuUK5cqVY/Dgwfz8888ZXiOr00vPoxOIS9QAoBUCIV7+i27Lm+4zCARare5fIdAlBFqhmzIOCo/j8uMItp+5w5lfdVvRRmz4j1lf1E3zqSsmJgZra2vpfhQoUEDvuBCCnReDmLDtLJen6bZ4lhu2nnoW96miCMRZ8YxiinDsFDGYocbMuhBmfbxQqUz0vE4Ur7mPZOSDkp8eKXnJ2dOn6NK2BU2at2TNZq9Ux7dsWAtA9y+/1st//Ogh40b8xMnj/1KgQAG69ejFzxOnYGKi2/Xvu2sHa1f9ydUrl0lMSKB8xUoMGzOOJs1bZtiesLBQJo4ZwT97fVEqlXza4TMmz5hDgZf//ykJvHuHT5s0QKVUcfVeUBq1GQ6FC5hhZZZxRITsTPMuXLiQoUOHpspP9h7SarU0adKEEydOoNVqKVSoEJs2baJVq1ZS2Tt37lC5cmUSExMBKFeuHEeOHKFOnTpZ0o0M25zCe+hmQmEqzLwnHUrpPXQi4D5FChWSvIfeFO/K99WQMDbtePjgPg2qp14juWPfYWrWqZuje/CmUSkVFLfN2Kcvt6+H8nzQkhVjtF9++YXp06djamrKJ598Ihmj9enTJ03js7T8Q1xcXDKN0zJo/VmO3nyeZ33TJsbz+A9dpMKgoKBUg5FkYmJicHJyyrTck9Bwypd2BaDEj3/LniZZIPTAMhSmFsRcPUTxPr9L/j5R53woUKU5cbdOAWBZrh4xVw5SsGZ7hFbLk/WjUBaww67R12hiwgjd70GBKs2xa/glAGFHPFFZF8K85IcozQsQE3CYqLO7cOgxHTP7tJ3KAZ55T0cTE0ah5t+BVkPogT8wcyhDkU9/0isnNGqebJmAytKGhKAblPzR883coDxidreqtP2oeIZlkteWhYeHp7nQMSW+vr6cOHGCWrVq0aVLl1QRcWfNmsWMGTNYs2YNpUuXZsKECVy+fJmAgAAsLHTfi9atW7N//35mzZpFgwYN6NevH3Xq1MHU1DRdw8Qsa8e9k7CxOwDX4otR//e70qFK383n2gpdVF35e2q8GJt2qCOeErzanWJdJki+SABKC2ud55EBYl/QnEMjm2RYJju6kSZ5s4kpe8jeQ3KS07uTshvZEjKO3ySEEOHh4cLc3Fxs3LhRCPEqrgW80g1fX1+hUCjEwIEDZe8hOcnJyJLBRMR9E8j+ITrepf7kpC+bNm1i7dq17N69m3/++Ydff/2VY8eOoXg5l/748WMpkuSuXbsoUaIEAHPnzuXAgQPs27dPquvBgwc0bNgQX19fqlSpkupaWq0WNzc3Bg4cSN++fQHYsmULI0aMkLbNbtq0ialTp+Ln5yf1xdLSkrJly7J06VIpAuyJEycYPXo0e/fuxdfXl8mTJ3P16tWc3bg3zJvyHsqIwMBAQkJCaNGihZRna2tLvXr18PPzo0ePHvj5+UlTysm0aNECpVJJUFD6r9pk7ZD7AsapHQ8fPqRBgwY4OTmRkJDABx98wA8//KD3ytSQMFjvoax6Czk6OgoLCwvJWyglwcHBQqFQCEtLS2Frayv69+8voqKiRO/evUXHjh0zbYPsHyInORlOyu1MS1aDy5UrV06oVCq9c4sVKybq1auXrm68Hpgy5YyNnOQkp/xLb22mJaveQinfTbdu3Vrv3XS/fv2wtLSkbdu2/PTTT/Tr149vv/2WY8eO4e7unmkbMvIPOX03lP5rzmRax6o+daj7QeGsdFnGALh16xb169fn+vXrFCtWDICRI0cSGRnJihUr8PDwoE+fPuzcqdtp1bFjR9asWYO7uztDhgzh4cOHeHt7S/XFxsZSvHhxtm3bRsuW+gvmtm7dypAhQ9iwYUOa67OSmTt3Lhs3buTs2bN6+WXKlGHs2LF888039OrVi7JlyzJ58mRAF1Bq7Nixep4jxkquPUSyiUKhoFatWhw8eFBvPcz169f1PqdkxowZ0r1PSWbr4apM0j1Zm5ooOT8h4wWVMoaNsWpHWnz//ffcv3+fvXv35uheGAK51Y1sD1oMwfgseUovrZgtMUShNLfKtI4YTPM93otM1tm8eTNqtVrPkl28ND1bvnw548aNA8DSUrdyvUSJElKei4sLFy5c0Pv/fvHiBQAffPCBXv6mTZsYPHgwW7dupV27dhm2qVSpUjx//lzvfLVaTVhYGKVLl8bGxoZjx47h6+vL4sWLpTZrtVoKFy7MihUr6N+/f25ui0GgyOVWl5Txm1IGnXzy5IkUbM7R0ZGnT58yZcoU+vTpQ+3atalZsybPnz/H0tIyXd14/fVQsmBmFu8pWUM0QJLSnCLW5rnqo0z+YazakRaNGjXiyJEj78TfrhzrRo7mZ14Cb8f4TDY9e78xZtOzgIAAvfZOnTpVFCxYUFy+fFmEhoZm5zYYHHnlPZS8EHfu3Ll6dae1ENff31/SDRMTEwGIXbt25Wmb4+PjhXXVV9rxv9N3ZHNTI8WYtSMtvvnmG1GjRo0sXcNQyVfDxNfF500Zn2XH9Eyt0aYyLQR907M6v+6STAtlDB9jNj17ndWrVwtbW9ss9tywyY74REVFSUaRgJg/f744f/68uH//vhBCiJkzZwo7OzuxY8cOcenSJfHZZ5+J0qVLi7i4OKmO7N7rnLY5MjJKTzu+WnZUbDp5U/osm5saD8asHZ6enmLDhg3i2rVr4tq1a2LatGlCqVSKVatW5fR2GATvxaAluy7PvpeDROmR/xPFG3SShMZ5yAZh9/HXwu7jr8XOc/dy2GOZ/KB9+/aibdu2aR47deqUAMTFixczrOPevXvi008/FZaWlqJo0aJixIgRIikpSTreuHHjNAfGffr0kcqsXr1avD45+eLFC9GzZ09hbW0tbGxsRL9+/URUVFS67XhfBy2HDx/O8P4mL+B3cHAQ5ubmonnz5uLGjRt6dWT3Xue0zRGRUcK2Qc9X2jFsq3AZ6S3sPv5aOLfsJ+uHEWHM2uHp6SkqVaokrKyshI2Njahbt67YunVrDu6CYWFQg5bsvh7y8PAQrq6uwszMTABi1qxZWbpupp2+ukPEziwvhowcIv0C9Rrxixjz21Thezko7XNkZGSyRW7FJ6ck64a5ubmoW7euOHXqVJbPzYp2RMypLpxTzNQ6D9smuv88S7iO8RGlXiZZR2RkckZudSNPvYeyY3w2Y8YMhg8fzqRJk/Dw8ABg2rRpufcQCdgJW3pjGReCRrxySD6lrcyIpOW0UWa+s0hGRsYwSfYsmzRpEufOnaNatWp551n2UjsSo56lOlRIEU1r5WnEy8+TdwWg0YpU5WRkZN4s2R605JXx2dSpU+nYsSPly5dnzpw59OjRA2tra1atWpXz3mg1sHcMIBBCEBGbKB2KF6YMj/iCwC3jERp1zq8hk6/4+fmhUqnSXZ3v6emJp6dnqvwHDx7Qrl07rKyssLe3Z9SoUajVr34PvLy8aNmyJcWKFcPGxgY3Nze9gFLpERoaSq9evbCxscHOzo4BAwYQHR2tV0YIwdy5cylfvjzm5uaUKFGCadOmZa/jMgDMnz+fb7/9ln79+lG5cmWWLVuGlZVV7nQD9LQjUZjoGSYq0eKrqUvR2HtoY8PQCkFwRDynA0Nzd02Zt4qxacevv/6KQqFIldKzhXlfyLb3UFa8hSZNmsSKFSsIDw+nUaNGkrdQMiEhITg5OWFubo6ZmRldu3Zl0aJFDBo0KEveQ8nbFlMZLgUegzXtAYhJFFjPiJIOubp7ct+jLwCfTPbCrog9ZioFJkplts3JcrJT63VzQ5mc8d+aaZiYW3Hn+C46TN2MlZ0u7sK1Axsp+3FHHpw9DIBLrabcPraTSi17otVq2DOlN5Y2hanRbTBxEc/xWzWFsh9/RvUuAwHw37QAS7uiOFaohamVNXdP7Oba/vW0HreSwi4V0m3PoYVDiQ9/Qd2vx6DVqPnPcyqFS1Wm0bdTpDL+G+cRHHCaGl0HYVeiLAmxkSTGRFC8cr03eKdyx49Ny9CgTNEMy+TW+Cy7JCYmYmVlxbZt2/TisqTnWQY5047r8UWpNOuV99DsUV+yWN2Fhwu6AeA8bBtKMwtKFy1AsYLmqBQKlEr5O27oGJt2JMXHok6I0zvn4Dx3ipSqhFv/iW/iFuWaQgXMWNyzRoZlcqsb2Y7T0qRJEzIa5ygUCqZMmcKUKVPSLaPVahFCcOjQIem1EYCDgwPXr19PVT69AFGRkZH6GSGBkKBrW0yifhtnahbS8+XPd55EowyTZ1uMDW1iPEGnDuDQcyamrg855L0em7q6AIcxYUlcmfaDZCx2bu9mrD9qybOrD4gLPE9E0F0KtB3DlSgLUJbEqm43Ag6uJ6Jsa5352EddiQVexAKxQIV2KE8d5MSB3djWT9u1NCn0ESFX/sOh5wwC4nRfPvMGvbm/fQZJVbugsi6sK3PEC8ev5nHX1AmeqgErwIpbVw03wFz7SnZUKWaWYZnk7182n3tyzPPnz9FoNDg4OOjlp6cbkDPtCE3QH3z0Uu/EWvOMH19+1ibEgtBy53Esd3LWFZm3jDFqx+skPrtHRHAg5o368q+Baod9QXMiI8tkWCbXupE3S2uyR3YNE+VQ3HKSk+GmnIbjftO6IYSsHXKSk6EmozJMLFq0KCqViidPnujlp2eiZG5ujrn5q4iUVlZWnD59GgcHh/fG9Azerf7kpC+dO3emffv2DBgwALVaTa1atVi2bBlubm54eXnh6ekpvYa8efMmffv2pUuXLowZM4ZHjx6xfv16qa64uDjKly/P33//nebrzqVLl7JkyRKOHDlC0aK61yS+vr7MmjWLI0eOALB48WK2bduGj4+PXl+qV6/O8OHD6d27N2PHjmXr1q1UrlyZ8ePHo9VqmTx5Mra2tmzevDmXdzHvyQ/DxKySXd0AWTtA7gsYp3akJD4+ntq1azNo0CAGDhyY3dv2VninDRNfvHghihQpIkxNTSXDxIiICFGiRAkxY8aMTNsgGybKSU6Gk7LyxGQIuiFrh5zkZDjJqAwTe/XqhbW1NZGRkQwaNIh169ZRs2ZNYmJisuQ9JBsmvn9MmDCBRYsWoVK92sYuXvqH3LhxA1tbWwDpiahXr15SuWnTpuHr68vx48elvHv37lGtWjX+/fdfqlWrJuVv27YNd3d31qxZQ+vWrTNs09q1axk/frye+aFarcbe3p41a9bQoUMHpk+fzrx58yS/EtA9qTk6OuLt7U2zZs1yeEfyn+wYnxmCbkD62iHrxruLsWpHSjp06ICNjY3ejI+xkmuj1RwNdV4CaXuIzJkzR8oLDw9P00PkzJkzOfYQySg4TXIYf9cMvIfqTtkjh/E3IozZP2Tfvn0CELdv35bKXLhwQQCpIr4aG3ntPfSmdSOjNifrRqkMfMvsa38qYmLj0qlZxhAxZu1I5u7du0KhUGTr99yQMeqIuMkkJSUJlUolvLy80rxOTsL4Z+Q95H3qdprnyRgmxuwfotFoRM2aNcUnn3wizp07J/z9/UW9evVEy5Ytc3o7DIa8GrS8Kd0QInva4Xs5SJQa46MXDRcQJVNoh+w7ZFwYs3Yk88svvwgnJyehVquz232DxKAGLYZgmJjMznP3RNGPv3wlPEM2CueW/UTvwWNEQkJCDnork18Ys3+IELpdL126dBHW1tbCwcFB9O3bV7x48SKbd8HwyKtBy5vSDSGyrx2+l4NEncl79LyHav3iJXoPHiOmTp0qa4eRYezaodFoRMmSJcW4ceOy2XPDxagHLSk9RExMTMTo0aPTvE52Z1qEEEJo1GLosh3SL9BgzxPyKyEZmTwkvwYtWdUNIXKmHWFRsXqzLY9CnmerfzIyMuljUN5DyVuYMtqS6OjoyNOnT/U8RE6fPo1Go8HDwyNNDxFzc3NsbGz0UoYE7ITfq6C5dUjKunHVH+W1XbnsoYyMTF7zpnQDcqYd2mWN9LJOLv1epykyMjL5Tr4ZJv7222+Sh0hISAigW9mfaw+Rl6ZnIuIxkSm8hwKSnNi2cjbPjq99axE8ZWRkMscgdANeGSZGPtPzHloe2YCHq/rJ2iEjYwBke8tzdHQ0t2/flj4nGyYWLlwYFxcXyTCxXLly0tbF1w0TW7Vqxf79++nduzcnTpzA3d2dHj16YGpqip+fX857k8L0LDYJ1ixdKh0S6gS6e5yABSdY7FuNYkXsUCmVmCgVKBQ6+wEZw+f6RX/G9utMjQZNmOixNtXxgzt0Aduaf/aFXv6z4McsnfYzl/1PYmlZgKYdPqf3kLGoTHRfAb+De/Dd8jeBN6+SlJiIS5ny9PhhBDUbNMmwPVv+XIj/sYME3ryKqYkZG45fS1VmxawJXL9whvu3b+Bcuiy/bzmQw96/PWq62FGykFWe1WfQugF62hGRqCJo+QDp0PUkB1w8QmFeb/78pyY2tjaYKBWolApZN4wIY9OOyPBQ5o8bzL1b14gKD8O2cBHqNWnN14N/xsraMIMEWpgoafXhmw02mS+GiVevXqVKlSpYWVlhYmIiGSZOmTKFo0ePcurUKb26Xzc9i4iIwMXFJXWclnsnYWN3QOc95DT/lWNmt++HsG35IgBK/Pg3SjOL7HRbxkAIPbAMhakFMVcPUbzP75JHR9Q5HwpUaU7cLd3vjmW5esRcOUjBmu0RWi1P1o9CWcAOu0Zfo4kJI3S/BwWqNMeu4ZcAhB3xRGVdCPOSH6I0L0BMwGGizu7Cocd0zOxLp9ueCL8tKM2tUEeHEnPlECV/9ExVJuzIKkwKOZEYcpukZ/dx/GpO3t+YPGZ2t6q0/ah4hmWS4y2Eh4dLsS7SIz90A3KmHQHxxXD7/ZVhYrnvFnJrxU+ArB3GjLFphzY+mtgbJzFzLIPS0gZ1eAhhh1diZl+aIp/+9GZuUi6xL2jOoZFNMiyTHd1IkzxbXZMNsushkt4OADnJSU75nwzZe0jWDjnJyTDTW4uI+++//zJnzhzOnj1LcHAw3t7eejbx4uUT059//kl4eDgNGzZk6dKllCtXTiqjVCpRKBQ0b94cMzMzunbtysKFC9P1Ixg7dizDhw+XPqvVaq5du4azs/N74x8C71Z/ctKXTZs2sXbtWnbv3s0///zDr7/+yrFjx6Qp+sePH0uRJHft2kWJEiUAmDt3LgcOHGDfvn1SXQ8ePKBhw4b4+vpSpUqVVNfSarW4ubkxcOBA+vbtC8CWLVsYMWIEDx8+TLMvBQsWJCAgIN32z58/n3379um1w9B417yHZO2Q+wLGrx0AISEhDB48mOLFi7No0aIs9/1tYbDeQ3v27BHjx48XXl5eAlJ7iMycOVPY2tqK7du3i4sXL4qOHTuK0qVLi7i4V5Ek27RpI6ysrES3bt3EsWPHRNmyZUWPHj1k7yE5yckI09uaaRFCiLp16wp3d3fps0ajkb2H5CQnI0w51Y1sr2lJiUKh0JtpEULg5OTEiBEjGDlyJKB7h+zg4ICnpyc9evTg2rVrVK5cmWnTpjFlyhSWL19OQkIC33//PTY2Nty8eRMHB4cMrxsREYGdnV2a3kPJHAgIYeTWS2i0r7rnYGPOz59WpGXlt/NkKJN33Lp1i/r163P9+nWKFSsGwMiRI4mMjGTFihV4eHjQp08fdu7UbU3t2LEja9aswd3dnSFDhvDw4UO8vb2l+mJjYylevDjbtm2jZcuWetfaunUrQ4YMYcOGDWmuw0iL9evXM3bsWD0vkdeZMWMGu3fv1vMxMWZy/W46Bb/++iuTJ0/Wy6tQoQLXr18HdC63I0aM4O+//yY6OppatWqxYMEC1q1bx5YtW7h+/XqmugFZ0w6AutMOEJuoBeDipFaolPKCW2PF2LXjyZMnREREcPv2bSZPnkzDhg2ZP39+Tm6FQZBb3cj266GMCAwMJCQkhBYtWkh5tra21KtXDz8/P3r06IGfnx92dnaMGzcOGxsbJk6cSHBwMADjxo1LU3heX0wXFRUFkG7chb1Xghm5/RbC1FJvT/fzBBi5/RZLrQvSpkrGiwxlDIvNmzejVqupUKGClCdemp4tX76ccePGAWBpaQlAiRIlpDwXFxcuXLig97uSbGD4wQcf6OVv2rSJwYMHs3XrVtq1a5fl9iVfN6M/hObm5iiVysxjhRgZebWD5sMPP+Sff/6RPpuYvJKnYcOGsXv3bnbs2MHevXtZuHAhjRs3pk6dOuzduzdLA5aUbc0sZouppTVKhRqAuxEaarnKJonGirFrR3J+7dq1KVmyJB9//DG//fYbxYsb99+wnOpGng5akuMmvC4gDg4O0rGQkBDs7e0BcHd3x93dHQB7e/t0/9NmzJiR6iksPTRaweRdAWjVSYQeWIoQWjTRoQCorAujUCiZVGAoLSs7yk9PRoJarebvv/9m3rx5tGrVSu9Yp06d2LhxIz/88AOA9A45JW5ubkybNo2nT59Kv3sHDhzAxsaGypUrS+U2btxI//792bRpU7ZERyZvMDExSfM9d0REBCtXrmTDhg00a9aMZs2a0b9/fypVqsTChQupV69enrYjISGBBzsWoNFo0ESH8tXhgvy3f4c0e+zh4YG5uXmeXlPmzfCuaYdWq5v9S/kQ/76Rp4OWN8Xri+mSp5fS4nRgKMER8QithuhL+9MsE9z8O04HhuJWpsgbaa9M3uLj40NYWBgDBgxINZ3YtWtXVq5cKQlPWrRq1YrKlSvz9ddfM3v2bEJCQvjll18YNGiQ9Mdnw4YN9OnTR/ojmDzItrS0lK7p7e3N2LFjpVcWoFuUFxoayoMHD9BoNFy4cAGAsmXLYm1tDcDt27eJjo4mJCSEuLg4qUzlypUxMzPLk3v0LnDr1i2cnJywsLDAzc2NGTNm4OLiwtmzZ0lKStKbwa1YsSIuLi74+flRv379dOt8fZY2MjIy03YkJSUReeHVwsvrgXD8ejB//fUXAPPmL5AHLUaCMWvHnj17ePLkCXXq1MHa2pqrV68yatQoGjZsSKlSpfLwLhkZOVoJ8xJ4e26tKcnIu2D7+UfCdYyPKDXyf6LEx930jM9sG/QUdh9/LVxGeovt5x9lr7My+YYhm5716dMnzfMOHz6cad2BgYHZvheGRG49RFKyZ88esWXLFnHx4kWxd+9e4ebmJlxcXERkZKRYv369MDMzS3VOnTp1MvQdEiJnZquRUdHC7uOv9bSj5JCNwu7jr4Xdx1+LulN8he/loHTPlzEcjFk7Dh06JNzc3IStra2wsLAQ5cqVE2PGjBFhYWE5uheGQm51440sxB05ciQjRowAdE829vb2qRbi+vv7899//zFnzhyCgoJISkrCx8cnS1NrkZGR2NraEhERkeqVkt+dF3iuXMQk07+Zr/6cLXH1eLigGwBfDx/Hv6YNANj4bX15pkVGJhdk9D3MLeHh4bi6ujJ//nwsLS3p16+fNGOyZMkS5syZw4MHD3B0dGT79u3UrVs3zXrSmmlxdnZOv80BO4naM5GPnk9DmxgvaUfT4b9z17QsAMkvlZd+VVNeGycjk01yqxvZ9h6Kjo7mwoUL0lRWcjjuBw8eoFAopHDcO3fu5PLly/Tu3TtVOO42bdrQrVs3hg4dypdffomTkxNlypThq6++Stf4LKvUjT/OMrPfcSQUtVDpHaunvE4b5WmK21pQt7S8sE5GxlCxs7OjfPny3L59G0dHRxITEwkPD9czTHR0dMTV1ZXWrVvnjWFisvdQ1PNUh0JFQZoqzgG6x2GAybsC9HYnysjIvHmyPWjx9/enRo0a1KhRA4Dhw4dTo0YNJk6cCMDo0aMZPHgw3333HXXq1CE6Opq9e/diYfEq9PX69euJjIxEoVCwZMkSmjVrxrlz57Cyssqd8ZlWg2rfzwAoEETGJugZn82LasUHcVcZ1LgUWiFk8zMZGQMlOjqaO3fuULx4cWrVqoWpqSkHDx5k/vz5fPvttzRo0IDg4GDmzZuXe90APe+hBGGCJjYCZWyodPiFsOFurAXa2DCEEAggOCKe04Gh6VYpY1j4+fmhUqnSnc339PTE09MzVf6DBw9o164dVlZW2NvbM2rUKNRqtXTcy8uLli1bUqxYMWxsbHBzc8tSAMlp06bRoEEDrKyssLOzS7M9CoUizZTbh3tjJlevh3JKYmIiVlZWbNu2TS+abp8+fQgPD2fHjh165bM8xRt4DNa0B3TeQ9YzotK8vvOwbZJ/iKnqpfEZxrWT6H31aYt9dI37niMpUKYWLj2npDoeflFnRmhXTT9+QlLEU4L3eBB77xJKMwtsq7XAvlk/FErdbFzktROEn91N/JM7CHUS5sVcKdr4K6zL1MqwPc+PbST69hniQ+6iUJlQYfS2dMuqYyMJXPEj6qgXlB+1FZWFdXa7/9aY+3m1LHkP5dXroY8//phnz57x6NEjTE1NMTU1JSkpiZs3b1KsWDEGDhzI6tWrU+2a+P7774mLi0tTNyBn2nEtviiVZ93Vq+dD92Vc9dAt2EypH0oFmKiUqBSK9/Y7aSwE7fodpZkFERf288GPf2JaULc84MV/3tjVaE3U9RMAFKzYkPDz+yhSvzNCqyFwhTsm1oWwbzEAdXQoQTvmYlfjU+yb9QUgZN8yTAsWwapUVVTm1oRfPMALv/9Ruv8CLIqXTbc9z46sRWlhjTrqOeHn96XSDm1SAtqEGP0+7JyPUCfi2nt2Ht6ZvMPBxoLDWfAeyo1u5MvuoefPn6PRaNLcGp1ydXUy6W15TrUTICQQEnRjsJjE9MdiqqQYNOLl1rHsNl4mXwk97YN1tTbEXD1ERPD9VKZnCXHxAES+ePqa6dkvKAvYYd/9N8n0LEmtkUzPIm6fw6REZYrU+1wyPXu4aVKmpmcJcbGYf1AHlX0ZYq4cIjoq7YEywPOdczAp4oI66gUxUdEokwx3pi8yMpLIyAKZlgHyZMby9u3bxMXFkZCQQIECBVCpVJiammJlpXOaXrBgAd7e3jx58gRzc3OaNWvGzJkzKVWqFFOnTk1TNyBn2hGakHoC+i/xK24vf9YmxMJL/dAC6lSlZQwNbWI8kVeP4tBzJubhz3h22gebul0AUGPCvb9/xrSIbkfqi9O7sP6oJdFRUcQFnifh+X2KdBqHuoAdFLDHpn53Qo+vx7LmZyhUJlg36AWA5mWyqtOViGsneHHlGLbW6ccPsqzVSXf9q0cQQqSjHabST5rYSGICL1C45cAMdSY/sSIx0x16udaNPFkOnE2ya3wWHx8vIiIipBQQEJDvIYjlJCc56dKbCOP/9OlTAYijR49KeW5ubgKyZ5goa4ec5GSY6a0ZJuYF2TU+Mzc314uLYGVlxenTp3FwcHhvTM/g3erP+2SYePPmTXr27MnOnTt58OAB3bt358qVK7kOff8mMBTDxIgI3Vq0woVfLZg3NdU9dbZu3RoXFxc6dOjAhAkTMmyDrB1yXwA6d+5M+/btGTBgAGq1mlq1arFs2TLc3Nzw8vLC09OT8uXLA7rva9++fenSpQtjxozh0aNHrF+/XqorLi6O8uXL8/fff6cZqn/p0qUsWbKEI0eOULRoUQB8fX2ZNWsWR44cSbM/WTFMbNasGfXr12f69OlZ7vfbxGANE48ePSrat28vihcvLiC1YaJWqxUTJkwQjo6OwsLCQjRv3lzcvHlTr8yLFy9EkSJFhKmpqbC1tRX9+/cXERERsmGinORkhCmvZ1o0Go1o166daNiwoV7+8uXLRfny5UWPHj3EunXrRIkSJUSnTp0y1A15pkVOcjLM9NZmWmJiYqhWrRr9+/enS5cuqY7Pnj2bRYsWsWbNGkqXLs2ECRNo3bo1AQEB0g6iXr16YW1tTWRkJIMGDWLdunXUrFmTmJgY+vXrl2kbkkdxr5uenb4bSv81ZzI9f1WfOtT9QN7ybEwYq+nZuHHjCA4OZvXq1QAcO3aM9u3bc//+/TR3DBgTyYta8/rpfdCgQVy5ciWVseR3332Hra0tffr0oU2bNvz222/079+fggULpqsb6a1pycwwMSN+/t8lfC4FU6l4QVpUcmDxodsoFLD861o0KFM0R3XKvDkmTJjAokWLUKlehcAQL72Hbty4Ic14Js+m9OrVSyo3bdo0fH199X4X7927R7Vq1fj333+pVq2alL9t2zbc3d1Zs2YNrVu3znL7smK2OmjQIC5evPhOmK3mWjdyNNR5CejPtGi1WuHo6CjmzJkj5YWHhwtzc3OxceNGIYSQnnTOnDkjFi9eLFxcXISJiYkAxK5du7J03fQi6qk1WlF/+j+i1Bgf4TLCWxT4qIVQFSwqLErXFM4/bRbWVVsJ+9qfipjYuNx0WyYfGDVqlACESqWSklKpFJaWliI8PFwqt3r1arF69Wq9cydMmCCqVauml3f37l0BiHPnzunlb9y4UVhaWgofH59stW/16tXC1tY2VX61atWEUqnUa3NyPyZOnJitaxgaeRkRN5lBgwaJkiVLirt376ZbJlk3TE1NBSB+//33dMu+PtOSPEub3TbHx8eLb775RvT8uq8oPWq7cB3jI87cChFt27YVZWp+LFxGeIm60w6I8JhEvfLffPONiI+Pz9a1ZPKOpKQk4eDgIObNmycuX76sl8qUKSOWLl2a4fl79uwRSqVSPHnyRMpbvny5sLGx0ft/3bBhg7CwsBDbt2/PdhvT045koqKihLW1tVi8eHG26zZEcqsb71wYf9/LQbpBy7BtelNRJdzXST9HR0dnr6My+YoxC8/t27f12rtq1SoBusWkKdtjjOTloEWr1YpBgwYJJyenVK+T0+P48eMCMg/DnpKctjk6OlrSD+dh20SvP//Ty/tk2h7hOsZHDNl4TgiNWkRf2fdKbyLzblAnkz28vb2FmZmZ3oNNMqNHjxa1a9fO8Hy1Wi2qVKkiWrVqJS5cuCD27t0rihUrJsaOHSuVWb9+vTAxMRFLliwRwcHBUkp5TS8vL1GhQgW9uu/fvy/Onz8vJk+eLKytrcX58+fF+fPnRVRUlF65v/76S1hYWBh9+P5kDGrQcuLECQGIoCB9X47PP/9cdO/eXQghxLRp00T58uVT1VWsWDHxxx9/pHmd7D4t+V4OEvUn+4jiDTpJwlFj3FbRe/AYMXXqVJGQkJDDHsvkB++C8CRz+PBhAbwTApSXg5aBAwcKW1tbceTIEb37HxsbK4TQDf6mTJki/P39RWBgoNixY4f44IMPxCeffPJG2qzWaMXJ28/F9vOPxMnbz0VsXLz45dfJwr5pH+Ey0lscuv5Eb9By8voj8cHY3cJ1jI/YNe0LkfBLQTG1qbmY2tRcJMyqIMTVHTm+NzI5x5i9h5Jxc3MTX375ZfY6bsAY9aDFw8NDuLq6CnNzc2FiYpKu+Vm2Tc+u7hDaeRXF8JHuUtk/J34lC4eR8i4ITzLyoCVt0rqHgPSq78GDB+KTTz4RhQsXFiYmJsLExESoVCpRq1YtcerUqTxts+/lIFF/+j/CdYyPlOpP/0cM33xeuI7xEc3nHREajVZv0BIdHS3mrd8pXMf4iGpjNooHEz4QYpLNy2SrS7L+yMjkWjeyHcY/I5K3MGW0ldnR0ZGnT5/qeYicPn0ajUaDh4dHmuGJx44dS0REhJRe33Kqx0v/EEVkEEkpvIf2xVSALb11x2WMil27drF79+40j9WtWxchBFWrVs2wDldXV/bs2UNsbCzPnj1j7ty5mJi8Wod+5MgRXXj211LKsN59+/ZNFRDJ09MzzfOaNGmSZjuaNGmCEMLoF+HmNWndQyGEtN3c2dmZo0eP8scff6BUKlmxYgWXLl2iZs2aGXoPZZe9V4IZuO4cwRHxevnBEfH879xjAL5pVBql8rXwt1oNg4N/5iPFXcIpSK+k8QRqk7d0vvyd2fuzzi5ARkYmx+TpoKV06dI4Ojpy8OBBKS8yMpJTp07h5qaLJ+nm5kZ4eDi//fYb3377Lf369SMkJATQ7QpKy0Mky6ZnKfxDhBBExiZKh/7TVGRDZHWebRuJ0MgxLI0VQ/IPuXfvHgMGDKB06dJYWlpSpkwZJk2aRGLiq9+7I0eO8Nlnn1G8eHEKFChA9erV9WI+yGSPZO+hfv36UblyZZYtW5Y33kOARiuYvCsAkcYxIQSa2AhEXAQdqqZhb/DgP0yjHvGn2TxcFE+4r7Xn0/DRzIxoTbDWDhAQ+Rjun8x1O2Vk3meyveU5Ojqa27dvS5+TXZ4LFy6Mi4sL1apVY8yYMfzyyy9YWlpibm5O0aJF9VyeCxUqxNWrV7l69SpLliwBoGzZsjRo0AA/P79U10zLPyRN7p+EyCAAYpNgzdKl0iGhTqCXx1EAviu8m0LFS2Oi0j0tKXjlG6IAKViZjOGxc/Fc6rT7kn8OeDFi9WEKFrEHwG/H39Rs2ZVr53VPwzcsTnPuwP9w+6w3Wo2G5cO6YW1XhN7T1xIV9ow/fh/Hf/fCaf71UAD2enpTsERVOrUZgEUBGy4c9KZt+/Z8M2cjxT+olGZbbp87ztV7oTTqO5bCxV14ev828xZO4sCl+7TqNwqAY1u9SbIoTtuhcyhgV4Sb/kf5undvdl8Pp3ydJm/8fuWUbrVKUqWEbZ7VN2PGDLy8vLh+/TqWlpY0aNCAWbNmUaFCBalMfHw8I0aMYNOmTSQkJNC6dWv++OMPye4jMTERf39/NBoNVlZWWFtb06dPH5o1a5ambkA2tAM4HRiaaoYlGZGUwKPFuq2wp75pRLOPXPQLROtmehwVYWw1m8zA6O/xXjyescAfw7ZR0iyaUsoQbPaEYW1/EVOVAlCgVIDypW+RUtadN8rD6xdYPbY3ZWs05MuJS1Mdv3BwOwDVm3fSy494FszupVMIvHwGM0srqjXtSIveQ1GqdH8+r/kdwN93MyGBN1AnJWLvUpbGPX6kbM2GWWqXOimRv0b15EngDb5fsA3HDyoCEP7kMQu/S711esDs9ZSsUC1VviFgY2HC8FYVMi+YC7I9aPH399eLXTF8+HBAZ3aY/ITbrl07Tpw4QWRkJEqlEqVSiUbzalq0TJky+Pv7Y2lpKT01z58/n99///2NeQ91SDrAspc/774WifLOjex2XSaf0SbGE3R0Dw49Z6JyucvKv1ZI/iExD6M5MuwryT/Ed8sarD9qybXDAcQFnuf5g9uYtBrFnvtaoAjmtbtyYud67hVvhkJlAmU6AnDjEUAMlGyF0mYvmzZvxbZ+t3RaVBiqfsnRcCA8CnDA5KO2nD7ky6NSL2eCijYC4F4IEBIN1rUwd6nGTq9tFI62fzM3Kg+oWMQEl4IZ/xHNjofI0aNHGTRoEHXq1EGtVjNu3DhatWpFQEAABQroPI6GDRvG7t272bp1K7a2tri7u9OlSxdOnNAZ2T158gStVotSqeTkyZMEBwfTu3dvypQpk24bsqwdwL3gZzpfoTTQJr4azNx/8oJIVztiYl6Z2UVSAM1L7bEkjEViJslRgbQJsTwSVjziA7idALdvZnq/ZPKe0AOrKFC1DbcvHeLPXcdT+ZbF3dI98Pqrz77mWzYKZQE7inSbgiYmjFP7PLjyOFzyLQs7cgBVwTJYt+2I0rwAEQGHWf/bj5n6liUTdmQ1aqHz2Np+5i5m93W+VuoI3UC4WJcJkq4B7HuoQBGUcfTc/MK+oDnf1M/caBWyphtpksO1NFkmLzxE5KiWcpKT4aacRLZ8XRfCw8OFqamp2Lp1q1Tm2rVrAhB+fn5CCCHWrl0rAL0YOkuXLhVmZmbp7iCTtUNOcjLMZLDeQ3nlIZISBwcHjh07houLy3vjHwLvVn9y0hdD9w/x9fWle/fu/PLLL3z55Zdp9mHXrl0MHTqUPXv26L0aMRTelvfQ67pw9uxZkpKSaNGihVSmYsWKuLi44OfnR/369bl27RoASUlJUpnWrVuTmJgozdZkxvuoHXJfDNO37NmzZ3z66ac8efKEAwcO0LJlS/bu3cuHH34I6KI2N2jQACcnJxISEvjggw/44YcfaNWqVfZu2lvCYL2HskNeeYikt+VZTnKSU/6n7D4xpaUL69evF2ZmZqnK1qlTRwqF8O233wobGxvh7u4uHY+KihKA6Nu3b5rXkrVDTnIyzGSQMy155SEyduxYae0M6J7SXFxccuUfkkxQeByd/zhBTIKGGs523HkWTWS8moZli7C0V63UWxtl8gVD9g8JDg6mXbt21KlTh6VLl6b5BH/8+HG6d+/OtGnTsuSvZQzk1EMkPV3ICqVKleLPP/+kdu3a1K1bl7lz5wKk8o9KJqvaIfuWvbsYom/ZsmXL8Pb2Zs+ePahUKu7fv0/VqlU5duxYhuEbvv/+e+7fv8/evXtzc0vylXz1HsqIvPYQSUlug9Ok9AUZsfGMcB3jIzotOS4io2PEx81aiQJl6wiXEV7iz3/vpHmO7CXydjHkMP6PHj0S5cqVEz169BBqtTrNMocPHxYFChQQHh4eWa7XGMjJ9zA9XTh48KCA1EH3XFxcxPz584UQrzykknXDzMxMVKtWTUBqD6nstln2LXt3MUTfss8++0zPk0ylUklt7N27d7rneXh4CEdHx8w7bcDka0TctHgbHiK57XREZJQ0ReU6fJvO/CzwRSp/kXLj9oirjyNkL5F8xlDD+D969EiULVtWNG/eXDx69EjvvGQOHTokrKysxNixY/WOv3jxIje3xCDIzvcwM11IXoi7bds2Ke/69esCXi3EzergM6dtTs+3rKTsW2a0GOoDz/379/Xasm+f7u/Ltm3bMnxt8s0334gaNWpk6RqGisENWt6Gh0huOu17OUjUneIr7D7+Wth9/LVwGektyo/fI3wvB+kNWvqs+Fe4jvERTaftEpFzqsleIvmIoYbxT/6cVkomvTD/jRs3ztnNMCCy8z3MTBeEEOKHH34QLi4u4tChQ8Lf31+4ubkJNzc36XhWBp+5bbPv5SBRZ/IeYdugp/R/VesXL9m3zEgx1Aee1wkMDBSgbzbs6ekpNmzYIK5duyauXbsmpk2bJpRKpVi1alU27oDhYXCDlvREPC0PEXNzc1G2bFkxatSobHUgp51OfpJyTSOVGuMjvE/dltr74EmocJu8S7iO8RE/jJ0gNBNtZS8RGZkUZOd7mJkuCCFEXFyc+PHHH0WhQoWElZWV6Ny5s96slRCZDz7zos1RMfHCOcVsS0Qaf/BkjANDfeB5nfQGLZUqVRJWVlbCxsZG1K1bVy8kgLGS20GLQoicRnjJPUuWLGHOnDmEhIRQrVo1Fi9eTN26dTM9LzIyEltbWyIiIrK8EFejFTSadSjdiJcKoJil4Myvum1v0ZER3Pzjc7qH/UgSJvRQHWKayUpUCvHqDBsnGHoZlKo065SReZfJyfcwL8ipbkAW2hywk4g9v/JR0HgeLtAFFbw5tQ7lOv8ClTvmZTdkZN5Lcqsbeeo9lB1SGiaeO3eOatWq5anx2eukDNEtXvqIaGIjpKh8AgiJeBXumwf/USPuP+aaLkWJlo3qpnSLGIJflOPLc4TsJSIj85Z5o7rx0mw1PvIZmtgIKXtNWDWerf6KZ8fX5jyKp4yMTJ6QbzMt9erVo06dOnh4eAC6gDPOzs4MHjyYn3/+OcNzszpSexweR0RsEkkaLYdvPOX3f27prpUYLz1FOQ/bhtLMIlV+9H9rKeA7CIA9mroMj+nLjQVfAdBu+EwaWtyllOIJRRv2xqrcJ1iaqTBRpuFlJHka6fJke5Hccd7/NF991ppGTVuwfN3WVMe9N+u2PHf+opdeftCjh0z+eTinTxzDqkABOnXvybBxv0pOz2dP+TFv2iTu3r5JfFwcTiWc6f51P/p+PyjD9oSHhTJt/GgOH9iLUqmkZbsOjPttFgUKWAOQEB/Pr2OGcfXSBe7eukGTFm3w8NyQF7fijVLc1hJbS9MMy+THTEtudAMyaLNWA79XgcggbiYUpsLMe9KhEu7reOyh++4fvhRIkUKF9L7HCoXu+y39LH/HDRJj047TJ4+xZsUfXDp/lpioKFw/KEP/gUPo0LV7XtyON4KJUkFZ+4y3MudWN954RNy0SExM5OzZs4wdO1bKUyqVtGjRIkuGicnRNDMyPwMYvcGfY7depMpP6SOiTYgFoU2Vn9JLpBGnWCPuUv/lsQvxTlzSfqD7sF8D+w9n2A6ZvCP0wDKsqrbh2L+HaD5hYxr+IVcAWHJze5r+IXZdJqOJCcPT04Ot/g8l/5DEp4EkFamHZcXuWJmYExF0ndlTJ7Pi2D2sP2qRbnueeU9HExNGoXY/g1bDTt8/2HuuO0U+/QkAbVI84deeYVaiEaZxppy89YRWszJ2jzYEZnerStuP3rCHSDbJrm5ANrTj3kl4pjPbDIvXn4DWJr7yI/pq2THpIUfGuDA27Yg87YVQW2DRxB07K1tCAs8xevB3zN5/G8sPar3hu5Uz7Auac2hkkwzLGJz3UFoRKFOumo6Li5N2VFhaWoouXbqIkJAQIUT63kNyVEs5yclwU04jW2aXx48fC8i6Z5kQsnbISU6GmgwqIu6HH37IP//8I31OnkYDnZPrgQMHAN2CuhUrVug5uabF61Et1Wo1165dw9nZ+b3xD4F3qz856cvb9A+5cuUKvXv3ZtSoUfTs2RNI7R+yadMmpk6dip+fn9QXS0tLypYty9KlS/n000/16hw2bBiRkZGsXLkym3fr7fGmvIf+/fdf5syZw9mzZwkODsbb25tOnTpJx4UQTJo0iT///JPw8HAaNmzI0qVLKVeunFQmLCwMgBYtWmBqakrXrl1ZuHBhhteVtUPuCxi/diTTpUsXatSowYQJE7Lc97eF0XoPTZo0KVUEwWSSA0ht3LhRqFQq4e3trefk2rt3b9GxY8dMr/Hw4cN8HyXKSU5y0qWsPDHt2bNHjB8/Xnh5eQlAeHt76x2fOXOmsLW1Fdu3bxcXL14UHTt2FKVLlxZxca8i0LZq1UoAYtasWeLYsWOibNmyomfPnlnWDVk75CQnw0kGNdNy69YtnJycsLCwwM3NjRkzZuDi4iI5ubZp04ZatWpx8OBBOnXqhIuLCydPnuTgwYO4u7unqu/199Li5buwrHgPHQh4wrDNFwDd+7YDwxujkv2EjI635R9y7949YmJiOHPmDL/++itz586lW7duabZp7ty5bNy4kbNnz+rllylThrFjx/LNN9/o5Q8cOJCIiAg2bDD8hbhZITseIp9++mm6T49CCH7//Xd++eUXPvvsMwD+/vtvHBwc2L59Oz169ODatWvs37+fypUr8/DhQxo1asTixYtp27YtDg4O/PTTT1lqc3Jb09OOAwEhDN98EfFafrJizP+iGi0r5/AJUSZfeBe0499//+WLL75g/vz50uyNsZJb76E8H7TUq1cPT09PKlSoQHBwMJMnT+bjjz/mypUrhISEYGZmhp2dHcOHD6dPnz7Url0bW1tb/v77b2JiYtI0k5sxYwaTJ09OlW9jY5PpoOVm6GOU5lYAPE+ECyEJNK1onzedlXlrbN68GbVaTYUKFaQ88dIwcfny5YwbNw4AS0tLAEqUKCHlubi4cOHCBb3flRcvdAu0P/jgA738ZLMyNzc3IiMjmTVrFv3790+zTaVKleL58+d656vVasLCwihdunSq301TU1NMTEzeakyTt4Eil9tlAgMDCQkJoUWLV4sWbW1tqVevHn5+fvTo0QM/Pz/s7OyYOHGipBs1a9YEdCKYVRPK5LampR0arWDu4TMozK1Iq0cKYO7hh3SqW05+8DEijF07jh49So8ePViwYAHfffddru6FIZFT3cjzQUvKp6mqVatSr149XF1d2bJli/RLAfDFF1/w7NkzJk6cyMOHD3F0dGTv3r04ODikqvP199LJI7XMSEhI4O/ZY3keGoMmJhQFStaW/Z0GpW2lGR0PDw/Mzc1z02WZN4xarebvv/9m3rx5tGrVSu9Yp06d2LhxIz/88AMAffv2TXW+m5sb06ZN4+nTp9jb6wasBw4cwMbGhsqVK6d7Xa1WqzfDl1a94eHhnD17llq1dKv5Dx06hFarpV69etnt5ntLSEgIQKrvvoODg3QsJCQEe3t7Pd0ICQlBpVIxaNCgNHUDUs/SZrTjMDmWk1An8WL/EuLvXcC0qAvFOo4h7LBuHZK25UBOB4biVqZIrvos83Ywdu04cuQI7du3Z9asWe/UgCVX5OilUjapXbu2+Pnnn7Pk5JoVshoGOKWXUHIqPeJ/4m7wc+mzbIBm+LwN/xAPDw+xc+dOcfPmTXHz5k3x119/iYIFC4rx48dLZdLyD2nTpo2oUaOGOHXqlDh+/LgoV66c6Nmzp16Zq1evivPnz4sOHTqIJk2aiPPnz+uF6zZWchqOG/TXtJw4cUIAIigoSK/c559/Lrp37y6EEGLatGmifPnyqeoqVqyY+OOPP9K9Vnq7h9Jq8/bzj4TrGB+9EP6AKJHCMNF52Dax/fyjbPVXJv8wZu14V81WDc576HWioqJEoUKFxMKFC7Pk5JoVstRpjVrEX/tHFG38lZ75mfOwbWLR/gAxdepUPQM0tUYrTt5+LraffyRO3n4u1Bptjvssk7e8Df+QRYsWiQ8//FDy+ahRo4b4448/hEajkcqk5R/y4sUL0bNnT2FtbS1sbGxEv379RFRUlF4ZV1fXNP9wGjt5NWi5c+eOAFIN5D755BMxZMgQIYQQK1euFHZ2dnrHk5KShEqlEl5eXuleKz4+XkREREgpeSFuWm0+efu5zots5P/0NWPIBj2D1ZO3n2ervzL5hzFrx7tqtmpwg5YRI0aII0eOiMDAQHHixAnRokULUbRoUfH06VMhhL6T6+jRo4W5ublQKBSibt264tSpU1m6RqadvrpDiHkVRchEF50Z4rDNeoOWWr8dEDEJr37pfC8HifrT/9EzUKw//R/hezko7fplZGTybNCi1WqFo6OjmDt3rl7d5ubmYuPGjUIIIQICAgQg/P39hYeHh3B1dRWmpqYCED4+PnnSZrVGK8b8NlVcm1BZb7Zl/qgvxHdjJ4pSL3VBfqCRkck5uR205Ln30KNHj+jZsycVKlSge/fuFClShP/++09atb1gwQLat29Phw4dmD17Nh9++CGHDx/OOw+Rl/4hRAZxT+hW+TspXkXFdbYWPI9OYM6+GwDsvRLMwHXnUhkphkTEM3DdOfZeCc5de2RkZIiOjubChQtcuHAB0C2+vXDhAg8ePEChUDB06FCmTp3Kzp07uXz5Mr1798bJyUmK5VKpUiXatGlDt27dGDp0KF9++SVOTk6UKVOGr776Kk+8h1TXdzFDPYdCROnl79PUYYnJQlorTzOpQ2V5Ea6MTD6S54OWTZs2ERQUREJCAo8ePWLTpk2UKVNGOm5hYcGSJUv48MMPGTRoEGfPnqVx48YsW7YMKysrVq1alfOLazWwdwy83LB4T2OPJjYC+7hAqcjPKp3p2V8HLjLM8yi/eF9Otb0RqQaYvCsAjTatEjL5gZ+fHyqVinbt2qV53NPTE09Pz1T5Q4YMoVatWpibm1O9evVUx+Pj4+nbty8fffQRJiYmeoHPMkIIwcSJEylevDiWlpa0aNGCW7du6ZWZNm0aDRo0wMrKCjs7uyzV+67h7+9PjRo1qFGjBgDDhw+nRo0aTJw4EYDRo0czePBgvvvuO+rUqUN0dDR79+7FwuJVyPz169cTGRmJQqFgyZIlNGvWjHPnzuVeN0DSDgWCJFR6holXta5MivyMocottK5ULHfXkck3DE07vLy8aNWqFUWKFEGhUEgD+mRCQ0MZPHgwFSpUwNLSEhcXF4YMGSJZUbyvGKX3ULo7AO6fhMgg6eOVxOI8WtyLRymKNEs4zNBq3zC8Vy9+R98w8XUEEBwRT6sFR7E2z5dbJfMaFzbMpNQnXdl30IfW07ZjYVsUgDuHNuPaoANBF24CsPX5fu6f3EWZZl8AcPlSENZlGmOvKkZg0B0+8ziuV686IY6rd8Kxq/IphTVWnLr7IlWZtLh1YD23DqyjxlfjqFCkOFd3r6S6W2Oajl+LylS3K+368duYOtaieH0XHvy3O0v15jcjWlXgk/J59we6SZMmGXqNKBQKpkyZwpQpU9ItY21tTUREBNu2bdP7w5Ad76GsaEdUopKg5QOkQ0KdwHSPv5kO1FXupKBdEcxNlCgz2LKZ3iF5jib/MDTteHj6HLGmzji3rkHoxtkM3XQe2+PR0vHIoLvcOHYZ5yb9cXYsRWxoCKs2zWXbsUvUGTA1r25LnlLE2pxVfeu80Wvky1/i58+fo9Fo0tzieP369VTl04vTkkqAQgIh4ZUwnoormfqcBEEPxxCSN1CnNExMj1uPYjM8LvN20CbGE+R/EIeeMzELesypPZuxqdsFgJhoLbfmuWNaRLcVPuDgNqw/aknknZev92p8QTgQ+eAhcQlJnL+Txmu/2r0IBWIunkbExKRdJgVCCIL+2UTB2p0IKVAW4kHV6BtiV3zLfwd2YVWhoa5gxbbEATHRR9BotJnWawgEPStGpGPGoQDetmFidnUDcqYdYQn6Q4txmhUk+/U+fhGDMkqTsw7I5BuGph0AFKkGRaoRGaF7tXn94XPMEqxTFLDEpOkggoHgSMDECYs6nxO8bzHnbj1CoVTl8G68OewLmmdqZPxeGCa+vgMgeVGenOQkp/xPhmyYKGuHnORkmMmgwvhnZph46NAhlEolv/32G9u2bZMME9MzUTI3N9cLAGdlZcXp06dxcHB4b0zP4N3qT0760rlzZ9q3b8+AAQNQq9XUqlWLZcuW4ebmhpeXF56enpQvXx6Amzdv0rdvX7p06aJXx/z589m3b5+eAdrrpGdsGBwcTM+ePVmwYAE1atTA39+fzp07c/ToURo3biz1ZeDAgQAsXbpU7/wtW7YwefJkrl69mqX+5gdvyjAxLyhatCgqlYonT57o5WfUBlk75L6A4WnH6/0B2Lt3Lx9++GG6dYeGhtK2bVs6d+7MmDFjstz3t8U7bZi4detWUbduXeHu7i4ZJp44cUKUKFFCzJgxI9NryKZncpKT4aSsPDEdPXpUtG/fXhQvXlxAasNErVYrJkyYIBwdHYWFhYVo3ry5uHnzpl6ZFy9eiCJFighTU1Nha2sr+vfvLyIiIrKsG7J2yElOhpMMaqYlM8PEFi1aoNFoJA+R4sWLM2LEiHS9h14nM9OzlDSbe4SnUbqFeCNalaNfww9y30GZt86ECRNYtGgRKtWr97jipX/IjRs3sLW1BXQ7TAB69eqVZj0zZsxg9+7dHD+e/kK5rBobBgYGUr16dY4dOyb5jgC0bduWjz76iFmzZumVX79+PWPHjuXBgwcZd9ZIyI7xWUxMDNWqVaN///6pnmABZs+ezaJFi1izZg2lS5dmwoQJtG7dmoCAAGkHUa9evbC2tiYyMpJBgwaxbt06atasmWXdgPS14/TdUPqvOZPp+av61KHuB4WzdC0Zw8AQtSMl9+/fp2rVqql0JJmoqCi6dOmCpaUlW7Zs0dtRZ4wYrWHi6x4iQLreQ6/vAIiK0sVRyMwwMSQ0ihs7liCEFk10KNP3m9H35F5GjhwJyL5DxoJarWbz5s3p+ofs3r1b8g9JfjWTHubm5iiVygx/b7JqbFi1alUcHR05deoUjRo1AnRfSH9/f9zd3VOdn+y99T4aJuaFy/PevXs5c+YM//33H3PmzCEoKAi1Ws2uXbvS9R5Kr62va0fTqgUpYX+HkIh4tOl4D1mZqWgwvQNWlsb9R+N9wlC1IyXJf7ytra1TnRcZGUm3bt2wtLRkz549WFlZZbleQ8foDBMB3N3dcXd3p27dujRt2jRdk7n0dgBkRnB4DNGX9kuf44G7IWH89ddfAPz+++/yoMUI8PHxISwsjAEDBkhPRcl07dqVlStXSsKTHrdv3yY6OpqQkBDi4uKkmAiVK1fGzMwMgICAABITEwkNDSUqKkoqkxyb4fHjxzRv3py///6bunXr6gVFK1eunDRDkDIoGsCDBw8IDQ3lwYMHaDQaqd6yZctibZ1yt8D7SXZcnmvXrk3t2rVxd3dHrVZjYWFBUlJSunVndcuzSqlgUofKDFx3DqHVEHNZtyZPE/UcoUki+tJ+ogGhlXcOGROGqh2ApAlBQbqt9jdu6AKeOjo64ujoSGRkJK1atSI2NpZ169YRGRkp/f4WK1ZMb+bovSJHL5WySW4NE7PjH5KSI1cfC7uPvxalW/aW3qP9tu10Kt8hGcMmL/xDGjdunOZ71cDAQKlMZh5BgYGBAhCHDx+W8pLXYjg4OAhzc3PRvHlzcePGDb1rp+chkrIeY+RdM0wUQmfpUWfyHj3voVq/eIneg8fImmGEGLJ2JPsRvZ4mTZokhBDi8OHD6a4HSXltY8PgvIdeJyPDRA8PD+Hk5CQAUbly5bzzHhJCCI1a7Nh/ULiO8RFdZ3tL/9n1JvuIJLXOyEo2SZSRyTn5NWhJ9h4yNzcXJiYmYvTo0eleKycPPGFRcXreQyFPjdtVV0bGkDA476GRI0dy9OhR7t27x8mTJ+ncuTMqlYqePXtia2vLgAEDGD58OBMnTmTo0KFYWlpSvXp1GjZsmDfeQ6DzH/q9Ci+OLgOg8JOT0qGg8Hg2+z9k75VgGs06RM8//+OnTRfo+ed/NJp1SPYakpF5yyRvfcxoK7OjoyNPnz5l8+bNDB8+nEmTJnH69Gk0Gg0eHh7p6oa5ubm0fiWzNXAABOxEu6yhXpbfHwN0miIjI5Pv5Jth4vTp0wHduhdfX9+88R4CPcPE59qCaGIjsIx7JWhCCCZt9uPbFYcJCo/TO1U2STR8cuIfcvHiRXr27ImzszOWlpZUqlSJhQsX6pU5fvw4DRs2pEiRIlhaWlKxYkUWLFiQaXtCQ0Pp1asXNjY22NnZMWDAAKKjX4XizqkvyftE6dKlcXR05ODBg1JeZGQkp06dws3NDQA3NzfCw8P57bff+Pbbb+nXr5+0gL9gwYK51w2QtCMx8pme99AfEQ15uKofz46vfWvRf2XynjelHSk5ceIEJiYmaXoUvU5m2nHkyBE+++wzihcvToECBahevbq0w+l9Js8X4m7atCnD4xYWFixYsIDly5ezdevWLHuIZInXDBNDkgrwaHEvFqUoUpMb7FzwC6DzHVKk8B1KlqPR2y7xLCohS6ubs7MAWiE7j+SaP2cspNXnfTm0azNLfM5QqJhu14jvxr9o0rEHp+/oHL01hwI4snMTn/b8hiO79hOmtaTvuHkUcXDi5iV/Ro/5mfMPI2j1eV8A7t2NpEabHnzmXglzC0tuXDzD2HHjuPo0gWadvky3PbOG9ib8xTNGLliLRq1m+dSRXOvaC/cpiwGIj4vlUaSGeu2/Qmnty6OwODacMvwtzw3KFKFU0QJ5Vl90dDS3b9+WPie7PBcuXBgXF5dMFzRXqlSJVq1asX//fnr37s2JEydwd3enR48emJqa5k43QE87IhJVet5DAUnFcfEIhXm9WbC7KgVtbDBRKlApFRn6D8kYFm9KO5KJiYrgl75fUrl2Q8JCn2f6Pc9MO3Zs3oOyiCvfT+mDbeFinD9xkK979+Z8SCI1GzXP+xuUB1iZqehUo8QbvYZReA+9vgMg2eUy1U6Aeyfh2WPpY3C8Waq6piQtIHmiNz3fofAEGL8l85gNMm8XbWI8QXt34NBzJoqS1xk/Y/4r/5CAF2zZ3EnyD/H8aznWH7Xk6KZTQClwKkXATeBmMFACswqfsGnzFg5pKqW4giOcDgPCgBIoS3zExu172B9fhrRICn1EyH9Hceg5g7+uJAKgqf0lfttncN+lLSrrl/E8XDtyMx5eRIBICOXnTafewN3JW2Z3q0phs+IZlsmOh4i/vz9NmzaVPg8frnP/6tOnD56enowePZqYmBi+++47wsPDadSoUSqX5/nz51OlShUmT56MiYkJXbt2ZdGiRUyZMiVd76GcaEdYgv4EdMHEZ9LPc3dfStdgVcZwefPaAc/3/I5pidrcR0lc2P0Mv+dZ0g6LOmABZwM0QAjwIeYu1Vi26m8KPzLMXYf2Bc1pVibj+CsG5z2UFbLrIZLeDgA5yUlO+Z/yynsos6i5jx49EoAoUqSIXtTcjLyHZO2Qk5wMMxlMRNxff/01VUyVChUqSE9C8fHxkv18s2bNaNu2LX/88QcODg7p+hGMHTtWejIDXcCga9eu4ezs/N74h8C71Z/88h4C3VP/559/jqenJ40bN9Y7VqdOHUJDQ1Gr1QwbNoyhQ4dKx3x9fZk1axZHjhwBYPHixWzbtg0fHx+9vlSvXp3hw4fTu3dvvbrT8yUxJPLTeyizqLlr1qwB4Ntvv6Vnz55S1NwGDRqk2wZZO+S+wJvVjsDAQLp06cL//vc/PvjggzQ9inKrHQC7du1i6NCh7NmzhwoVKmTntr0VjNp76MMPPxTBwcFSevbsmXT8hx9+EM7OzqJixYqie/fuon79+qJBgwZCo9HI3kNykpMRpjfh8gz6My1arVY4OjoKZ2dn4e7uLoTQeZmZm5uLQoUKyd5DcpKTkSWDmWkBnatzWqOoiIgIVq5cyYYNGyTvoUmTJjFu3Di6dOmS595DMQlq6k3X7UhQKRX4/9ICU1Web5iSeQvkhX/I9evXad++Pb1792bixImZXnPOnDls2rSJs2fPpnl87dq1jB8/Xs9LSK1WY29vz5o1a+jQoYNe+Zz4khgyufUQyQ7JUXNnzpzJpEmTqF27NnXr1qVw4cK8ePEiXd14fU2LePkePSu+ZTKpUWu0/H7wFp4n7kl5FRwLUsTajHvPYwgKjwfA3FTJT83L0aueKypl/i5WfpPaER4ejqurq17dWq0WIQQqlQpvb+9Us7mQPe04fvw43bt3Z9q0aVn22DJkDM57CLJmmGhnZ8ezZ8+YM2cOAOfPn0/Xe+h10vMPSdWO+2EozXVeDQK49lxNo3JFc99BmbdKXviHXL16lQ4dOtC3b19mz56dpeuampqSlJSU7u9Ys2bNiIiI4NatW9SqVQuA/fv3o9Vqadq0aarzcuJLYgzk1EMkOyRvb+7duzcFChSQPMusra35+OOP09WN9CxAshSzRUaPZ1EJDN56jv/uhqI0t+LzWiUZ0rwczoVfaqwQnHsQzpx91/nvbihzDz/k+P0Yfv+iBo62+bN4+U1rh7W1NZcvX9bL++OPPzh06BDbtm2jdOnSFCiQehdeVrXjyJEjdO/enVmzZjFo0KCc3QQDJce6kaP5mQzYs2eP2LJli7h48aLYu3evcHNzEy4uLiIyMlKsX79emJmZpTqnTp06eR7VUgghdvgHigIftRCqgkWFRemaYvSmMyI+Pl5888034ptvvhHx8fG57q/Mm8fb21uYmZmJ8PDwVMdGjx4tateuneH5ly9fFsWKFRNfffWV3mvLp0+fSmU8PDzEzp07xc2bN8XNmzfFX3/9JQoWLCjGjx8vlfHy8hIVKlTQq7tNmzaiRo0a4tSpU+L48eOiXLlyomfPnnplrl69Ks6fPy86dOggmjRpIs6fPy/Onz+fgzthWOQ2smVGQPaj5qZFTrXjfSQjbfS/90LUnXZAuI7xEZUn+Irdl179P8TFxYm2bduKtm3biri4OKHVasW6/+6JShN8hesYH1Ft8j6x70pwtq6XV7wN7XidSZMmiWrVqunl5UQ7Dh06JKysrMTYsWP1rv3ihXFHaDb4MP5hYWHCxsZG/PXXXzketGTXPySZNUev65WvPmGniIiMkj5HR0fnun8yb57c+oek9/vj6uoqlVm0aJH48MMPhZWVlbCxsRE1atQQf/zxh9BoNFKZZK+QlLx48UL07NlTWFtbCxsbG9GvXz8RFRWlVyYzXxJj5W0OWu7cuSOAVIO9Tz75RAwZMiTL9b7JNhs70dHRqbRRq9WK1cfvijJjdwvXMT6i+bwj4taTqEzPE0KIO0+jRLtF/wrXMT7CdYyP+MX7sohLVGd6Xl7yNrQjrXNeH7TkRDvS8yxr3Lhxpv02ZHL7HVQI8eZDPNapU4cWLVrQsmVLmjdvTlhYGHZ2dtJxV1dXhg4dyrBhw9I8Py2nVmdnZyIiItKf4tVqWOa1n58XrCXi5EZAF0xu4/cNObT1Lx6FxdGyxzeUKGxD3dKF8/29q4yMsREZGYmtrW3G38McolAo8Pb2loLLCSFwcnJi5MiRjBgxQrq+vb09np6e9OjRI9/bnB9otILTgaE8jYrHvqBFrrQsMTFRel0/atQo4jQKfv7fJXyv6F7NtatanNldq1LAXH9VQUxMjORWHh0drfc6JFGtZc6+6/x5LBCACg4FWdSzBhUcC6a6XrJj8ltFq4H7JyH6CVg7gGsDUL6n7slvidx+B994cLno6Gju3LnD119/Ta1atTA1NeXgwYN07dqVJUuWMH36dIKCgvjrr79o2LChZNudEnNzc8zNzbN+0YCdsHcM8aH1sanXVRq0ACw8fJeHKjeCTePZ978AAIrbWjCpQ2XaVMk4mJaMjMybI6tRc2/evMmuXbt48uQJpqamlCjxZiNwGip7rwQzeVcAwRHxUl5utMzMzIzx48cD8E/AEybtvMrj8DhMVQrGflqJfg1LZXsdgpmJkvHtKtOoXDFGbLnIjSdRdPQ4zs+fVqRXPVfpevnCy78TRAa9yrNxgjazoHLH/GuXTIbk+UzLyJEj6dChA66urgQFBTFp0iQuXLhAQEAAxYoVY+DAgezZs4c+ffowY8YMXF1dKViwIHXq1GHr1q3cuHEDe3v7DK+R4Ugt2XsIwW9JX/FnXDMeLugG6GZalGbm8Fo4/eRPS7+qKQ9cZGSySF7PWhw5ckQvam4yyVFzhRB069YNLy8vTExMqF27Ns7Ozhw4cCBLuvEm2pxf7L0SzMB153hdvHOjZUkaLUdvPOPPY3c5FRgKQMlCliz5sibVnO3SPS+jmZaUPI9OYOTWixy5oYsw7GRrQZ8GpehQzQknO8tstTXXpPg7oc/LO9j9b3ng8oYwuJmWZMPEFy9eUKxYMRo1apTKMFGpVDJ9+nQUCgVVq1bljz/+wN7ent27d7Nq1Sp+/vnnnF38Ne+hSGGhZ3zWSXmMHaIF2rhwQIHS0gaFQiH92v668ypNK9hjIm+Lzhey8gzn5+fHJ598TOvWbfDx8Ul1PNnwrG/fvlLexYsXmTVrFidOHOf58+eUKlWK77//niFDfkrzGidOnKBp0yZUqVKFc+fOZ9ie0NBQhgwZgo/PLpRKJV26dOH33xdKIn7jxg1+/HEgAQEBRERE4OTkRM+ePZk4cRKmpqZZ6HH+oFC8nV1BKWnSpEmGob0VCgWPHj1i0KBBeHh4ALrtpc7OzrnTjdcQQqAV6LVFSMeSPwu9z2Ry/NX5Is36UmZmdq5aK5i442qqP7cpy07ccZWPSthJr4perzNRreVFTALPohK58yyaq0ERHL/1nLBQnf+OubUt335ShsHNymJlljd/Jopam7OqTx3Wn37AooO3eBwex9T/nWLq/6BSqRLUdC1EOYeClLCzwN7GAmtzE6zMVFiZmWCi0vk8KRU6DzeFApQK3b8Ksva76ufnR+NPPqZ169bsan7v5c16dd6aC7pw+n2qm4PvWCjflouXrzD7Ne34LhPtaNZUpx1nM9GO6dOnsWfPHi5euICZmRkvQsPSLfvixQtq1qjO48ePef4iVG95haHxppdaZHum5d9//2XOnDmcPXuW4OBgvffOoPtiTZo0iT///JPw8HAaNmzI0qVLKVeunFQmJCRE2hJtZmZG165dWbhwIYMGDSI8PJwdO3boXTPLa1oCj8Ga9tLHb6IHsnLerFfX/bkYAxOH4j1fNyWpm3mRfUSMiRe+i1CYWhB9+QBO3yzDpGARACLPbMe6aitib54EwKp8A6Iv7cemTieiL+0n8WkgVuUboLIpRsLja4Tu9cCuSV9saunHUtHGRxO8ZigmdsXRxIbj1G9xhu15smUSmphQirR2R2jVvNjzO2aO5SnWcRQASeEhJDy4jJljGZTm1iQ+DeTF3sVYV21JocZ93sAdyhsW9axBx2pOGZbJzhNTfugG5Gw93J1n0TSfdzTD/ryLaBPjpVnpW4+eUbZE1sJDZHWmJSXxSRo2nrxF/yY6/563ocWGph3hx9ajtCiAOuo50ZcO4DJ0c7pln3pNRWiSiL97FuefNqG0MEzvIUcbC/4bl7GZ41ufacks1Pbs2bNZtGgRa9askdxaW7duTUBAgGR+9uWXXyKEYNGiRVSsWJF+/frx3XffUbJkyTSNz9KLtZDK9CwkEBJejcHCE/RHfNrEOBaKWXgnf07HMFHGMNEmxhNz7V8ces7UfdEv+EqmZwqVGU82jZdMz6LO7cb6o5ZoE2KxqtAIqwqNpHqsytYjofJlYq8fx7qK/hfsue8irMo3AIWSuDtndL8j6ZAU+oj4wLM49JwhXdeucT+eb59BUsOeqKwLo7K0wapCQ+kcC5ePsKrQkPgHlzOsO7+JjY5K/f16jewYn+WHbkA2tCMFUVHRBv1/k1WUKWYjdCikf0yVUKiAGYWtzClZyJKKxQtSsagZbRfoihRQJmX6/59MTEyM9HNkZCQajSZL57Upbyv9PLtDWW6GJvEwLJbgiHieRSUQl6gmNklLojr3Gm1o2gFgU7czADFXj4AQ6ZaPvrgfbWwkNvW7EX/3LNqEOFAY5tsAdbwmT3UjTXKzdQnSDrU9Z84cKS851PbGjRuFEEIEBARIW7eSDRN9fX2FQqEQAwcOTNP47PVYCynrkJOc5JS/KbvhuOHt6IasHXKSk+Emgwjjnxxqu0WLFlKera0t9erVw8/Pjx49euDn54ednR1RUVE8efIEgBYtWqBUKrl27VqWTJQcHBw4duwYLi4u743pGbxb/TE0w8Q3bXrWqVMnrly5QkJCAr169WL69OkZ/u7mF/lhmPi2dAPeT+2Q+2J42vF6fwoWLEhAQIDesYSEBDp06MAPP/xAly5d8PPzo3v37ly5ckWyHjAkjMIwEbIftXLatGmifPnyom7dupLxmRBCFCtWTNja2qZpfCbby8tJToabcjvT8qZ0Q9YOOcnJcJNBzLRkh+HDh9OnTx/J+CwqKgqFQpGmIdTr9vIRERG4uLhkanrmcfAWy/69C8CvHSrTrbZz3ndE5q1g7KZnKdm8eTM//fQTjx8/1rumsfE2DROTyY5uQM61o8ok3VOySqng4qRW6ZaTMXwMUTtSsn79esaOHaunIwCNGjXi6tWr0s4oIQRarRaVSsXIkSMZN25cNu+EYWBQhonJ0z1PnjyhePFXMQKePHlC9erVpTJPnz7liy++4NmzZ0ycOJHg4GCSkpKYOXNmmsZn6QWXy8j0LCEhge3LZxIaFI4mOpRf/rHA4o8/2eQxA/uC5ixZsiR7Aetk8g1jNz17HXNzc5KSkrC2tjbobc9ZJbdbo9+UbkDOtSP04Ari713AtKgLuzt9yOoFv2FhqmKT559YWco7Do0FQ9WOlFha6mLUvP776O3tTVxcnPT5zJkz9O/fn2PHjlGmTBmjjjME+WSYCGkvqJs7d66UFxERkeaCOn9/f6nMvn37hEKhEI8fP87SdbPiXZDS1yI5lXBfJ/3sfep2Nnsrk18Ys+nZunXrxObNm0VAQIC4c+eO2Lx5s3BychK9evXKQs8Nm5x6iOSXbmS1zSn9yV7XjTq/7hK+l4PSPVfGsDBk7bh//744f/68mDx5srC2tpaMVF/3Lkvm8OHDAhBhYWEZttnQeeuGiVFRUdLNBcT8+fPF+fPnxf3794UQQsycOVPY2dmJHTt2iEuXLonPPvtMlC5dWsTFxUl1ZMUZNyOy0umEuFhRu30vYdugpyQ4JYdsFHYffy3sPv5auI70lsXHSDBm07NNmzaJmjVrCmtra1GgQAFRuXJlMX36dL3vg7GSHfExBN3IapsjIqNe040NerpRaoyPrB1GgiFrR3qGiIcPH06zXnnQoiPbg5bkG/d66tOnjxBC99Q0YcIE4eDgIMzNzUXz5s3FjRs39OpIFnpzc3OhUCiEUqkUtWrVEqdOncpSGzLt9NUdQjuvohgzbrhwHrZNamPjYYskx9FSY3xE/en/CLVGm91bICMjI7InPoagG1lq89UdInxOdT3dqDhsrRjw86+ydsjI5AG5HbRke89lcqjt11Ny+HSFQsGUKVMICQkhPj6ef/75R9pKlkzhwoX57LPPEEKwcuVKLl++TM2aNWndujVPnz7NbpP0SfaUiAwi8bV1xlFY0kLhD+jUKDgintMvPTZkZGTeHAavGyBpR1LUM73sGCz5WHWJ1srTgKwdMjL5Sb4Fipg/fz7ffvst/fr1o3LlyixbtgwrKytWrVqV80pTeg8JQWRsgp730FNhR2JcFNrYMCka39Oo+HQqkzFE/Pz8UKlUtGvXLs3jnp6e0h/CZC5evEjPnj1xdnbG0tKSSpUqsXDhwnSvceLECUxMTKRFoBkxbdo0GjRogJWVVaZ+IC9evKBkyZIoFArCw8OlfC8vL1q2bEmxYsWwsbHBzc1NL8aDzCveiG6AnnYkCZWebgghmBX5KS3j/0EhXkV7lbVDRubtky9bnhMTEzl79ixjx46V8pRKJS1atMDPzy9V+bT8Q9Lk/knJZjw2CVa+9odJoY5jrcc8QOd1oTCzYNOZhxy6/jSF+VbKsNcyhsa+ZXOo3qYHBw5t54flB7AurHP2Peuzlo+ad+HmGd22wXPKk1w+6EWt9l9z+dB2nkUoaPDNrxQs4kjQjYuMHP0zOy+FUKNND73642MiWffzl5SsUpeg8BeM3Hoxw/acuPAAi3INqFykLFcOeWdYfvvsoZjZl4LHj/ll+2UsCuhW/x/2/B8FHD6k9fC+mBcoyJXDO2jbrj1fTl+HQ+mKubhbOadXPRdquBTKl2unR3Z1A3KmHZGJKoKWD5AOVdFcY+/iiXwOlB8WRYKZHQCbU2oHgKwfBk3QzYtsmtCPUtUb0GWsR6rjV47ovKuqNPlMynt67want6/m8Y3zxEeGY2PvRLWW3ajZNvW2aIDH18+z+ddvKOpcht5ztmTYnv+8/uTuuWM8u3cTlYkJ7p7HU5WZ1716qrx2P82kYsM2GdadX9hamjKhfeU3eo18GbQ8f/4cjUaTapuig4NDnnkPxSSKVOWnahbT5+XPyb5DJwKM32PkfUGbGE/QMV8ces7ExOUem/5eJfmHxATHcXJMX8k/5LDXOqw/asmdkzfBojJUqMzzcCA8FkzKYVHxE07s38Utm5p613i+53dMXesSplASFxPElpM3M25UyRYvr3+ERLU23fLRF/cTG/wUm/rd4PwJtp+6g9Li5VbI8p14Btx7CpAApdqgtN3PTm8vbOt3y9nNyiW1nSwoY5dxDJlce4hkk+zqBuRMO0Jf8yybrl3I3pc/xyRoUQqdZhyXtcOoCD2whgLV2nDvyiE27v8PlXVhAKLO+VCgSnPibukiLV/hIjFXDlKwZnuirx4mKVaBZdOBFCxYhISgGxxZt5Dz915QsLr+wEEbH0PIxp8xL1mF8JjwTLUjIvAJSsfqWFi7EHPlULrlC7f8EYtS1aXPFzVWXMpMl/IJ+4Lm/PRJyQzL5Kv3UE55/PixgFceIsmMGjVK9h6Sk5yMLOU0suWb1g0hZO2Qk5wMNRlVRNyiRYuiUqkkD5Fk0vMjeD1AlJWVFadPn8bBweG98Q+Bd6s/74L30Ot9ySv/kKVLl7JkyRKOHDlC0aJFs3Rv8or88B7KKtnVDZC1A+S+AGzatIm1a9eye/du/vnnH3799VeOHTsmBTh7/PixFMF6165dlChRIt26hgwZQkJCAsuXL5fyNm/ezNq1a9m+fTuLFi1KpR1btmxhxIgRPHz4MM3+pKUdAM7Ozjg4OJCYmIiLiwtfffUVX3zxRa4DOr4JDNZ76OjRo6J9+/aiePHiAvSDRAnxauuio6OjsLCwEM2bNxc3b97UK/PixQtRpEgRYWpqKmxtbUX//v1FRESEKFGiRLoeIil5+PBhvo8S5SQnOelSVp6YDEE3ZO2Qk5wMJ721mZaYmBiqVatG//7903yKnT17NosWLWLNmjWULl2aCRMm0Lp1awICArCw0IW/7tWrF9bW1kRGRjJo0CDWrVtHzZo1iYmJSddDJCXJo7jX/UNO3w2l/5ozmZ6/qk8d6n5QOKtdljEA3gf/kG3btuHu7s6aNWto3bp1Vm9NvpEdDxFD0A2QteN95NatW9SvX5/r169TrFgxAEaOHElkZCQrVqzAw8ODPn36sHPnTgA6duzImjVrcHd316snICCA9u3bM3DgQEaNGgWARqOhefPmfP311wwYoFu8PWPGDHbv3s3x46kX1qZFetqRFtOmTWP9+vVpzsoYC7n2LMvRUOclkHY47jlz5kh54eHhaYbjPnPmjFi8eLFwcXERJiYmAhC7du3K0nXTC06j1mhF/en/iFJjfITLCG9R4KMWQlWwqLAoXVM4/7RZWFdtJexrfypiYo0/Gun7RFJSknBwcBDz5s0Tly9f1ktlypQRS5cuzbSOK1euCHt7ezFq1KhUxzQaTap6Bw4cKCpUqCAuX74soqOjM61/9erVwtbWNlX+7du39epdtWqVAN26jCdPnkjlNmzYICwsLMT27dszvZahkNdh/N+0bmTUZlk73l1GjRolAKFSqaSkVCqFpaWlXnj/1atXi9WrV6dZx9WrV4W9vb0YN26cXn5YWFiquhUKhZR38ODBTNuXnnakhY+PjwBEfHx8lsobIrkNLpena1oCAwMJCQmhRYsWUp6trS316tXDz8+PHj164Ofnh52dHbVr16Z27dq4u7ujVquxsLAgKSkpzXqzum1RpVQwqUNlBq47B1oNMZf/AUAT9RytJonoS/uJBoRWk+b5MoaJj48PYWFhDBgwINU6kK5du7Jy5UrJ9Cwtrly5QrNmzWjdujXDhw8nJCQEAJVKRbFixVAqlVSpUkXvHHt7eywsLPTyvb29GTt2rN5OlQcPHhAaGsqDBw/QaDRcuHABgLJly2JtbU2ZMmX06n3+/DkAlSpVkuK6bNiwgT59+rBw4ULq1asntc/S0jLddS/vEm9KN7JDSu0Qr2mHkLXDaFGr1fz999/pGiZu3LhR0o6+ffumWcfVq1dp1qwZffr0Ydq0aXrHbGxsMjVMzEsuXLhAoUKF3muz3zwdtCSLbVpbEpOPhYSEYG9vr98IExMKFy4slXmd9LYtpkWbKsVZ+lVNJnlfJKJBTyJObgSgcEELmg8eQ3mHgu+Es+77xMqVK2nRokWaf8C7du3K7NmzuXTpElWrVk3z/G3btvHs2TPWrVvHunXrpHxXV1fu3buX5XZERERw48YNvbyJEyeyZs0a6XONGjUAOHz4ME2aNMlSvStWrECtVjNo0CAGDRok5ffp0ydVoLx3kTelG5CNOC280o6JXheITKEdDnZWNJO1wygx5geeXbt28eTJE+rXr4+FhQUHDhxg+vTpjBw5Mre3xbjJzTQPr03znjhxQgAiKEjfTOzzzz8X3bt3F0IIMW3aNFG+fHkhhBAeHh7C1dVVmJubCxMTEzF69Og0r/P6tsXkxXQZTS+pk5JEv/mv/ENm7zyXm67KyMi8Rl69HnpTuiFE+oZ3GRomRsfpeQ+FhoZlq38yhoMxGyb6+vqK6tWrS2ar1apVE8uWLRMajSZLfTdU3rphot7Jr4nPnTt3BCDOnz+vV+6TTz4RQ4YMEUIIsXLlSmFnZyc2bdokzMzMxKpVq8TFixeFQqEQVlZWeu/50yMrpmdiXkUxeMRP0i9Cx9FzdfkyMjJ5Ql4NWt6kbmT7gefqDhE6p6beoOXI5JaydsjI5BFv3TAxI0qXLo2joyMHDx6U8iIjIzl16hRubm4AuLm5ER4ezm+//SZ5iCRPuRUsWDD3HiIvTc9ExGMiYxOl7HOJruxdOZlnx9e+tQieMjIymfMmdcPc3BwbGxu9lC4vtSMx8pme99DyiPo8XfWVrB0yMgZAtte0REdHc/v2belzYGAgFy5coHDhwri4uDB06FCmTp1KuXLlpK2LTk5OdOrUCdAtQGzVqhX79++nd+/enDhxAnd3d3r06IGpqWm6HiJZIoXpWWwSrFm6VDok1Al86nEO5vdmm199ihSyxVSlxESpQKnM/0A9+d8C4+DSuTN8+3lb3Bo35/dVm1Id37VtAwAdun0p5d0MuMKaZQu54P8fEaGhFC/pTJde/ejZ7/s0r3HR/xTf9+jAB+UrsWHP0Qzbs8pjHscPH+BmwBVMTU05fCkwVXumjBqc5rn7zlyncNFiGdafX5QuWoAi1nm32M+gdQP0tCMiSd976N/ECjh4RMG83uw60wBbWxtUCgUqA9EOY+Vt3zlD047h3/Ti5rXLhD1/TkFbO+o2/ITBP0+imEPxVGUf3rvLV+2boFSqUmmMIWGqUlLN2e6NXkMhsvnocOTIEZo2bZoqP3nRoBCCSZMmsWLFCsLDw2nUqBF//PGHns381atXqVKlClZWVpiYmNC1a1cWLVrElClTOHr0KKdOndKr+/XFdBEREbi4uKSKtcC9k7CxO6DzHnKaHy0davb9eA4t1638LvHj3yjNLLLTbRkDIfTAMhSmFsRcPUTxPr+n4R+i+92xLFcvhX/IIZKe3ceybD1MXvqHhB1cgW2jr9L1DzG1dUQTG47jV3MybE+E3xaU5laoo0OJuXKIkj966tenTkQk6HvUhO5fglAnYf/5r7m7GW+Q2d2q0vaj1OKZkuR4C+Hh4ZnucsoP3YCcace1+GLU//2udKjkd8t4tEK3WFPWDuPF0LQj6pwPZsXLoypQCE10KOHH1gLg8MVUvXJCo+bJlgmoLG1ICLqRSmMMCfuC5hwa2STDMtnRjTTJsxdV2SC7HiLpLYaSk5zklP/JkL2HZO2Qk5wMM73T3kNjx45l+PDh0me1Ws21a9dwdnZ+b/xD4N3qT076Yqz+ISlZvnw5ixYtwt/fH0tLyyz1+23yrnkPydoh9wUMXztOnjzJ9OnTefLkCV5eXtLxEydOMHr0aPbu3Yuvry+TJ0/m6tWrWe7320T2HsoA2T9ETnIynPS2ZlqEEKJu3brC3d1d+qzRaGTvITnJyQiT7D0E7L4UxJj/XU7vNIlZXT+iXVWnrHZZxgB4F/xDTp8+TcuWLTly5IgUhM6YyY6HyL///sucOXM4e/YswcHBeHt7S4tsAWlNy59//kl4eDgNGzZk6dKllCtXTioTGhqKqakpHh4erFy5kk8//RRbW9s88R6StePdxZC148WLF4SFhfHgwQNmzZqFjY0NW7ZsQaFQ0KtXL8qWLSsFVs2OR5EhI3sPpeDk7efCdYxPpunk7ee56bZMPvAu+If0799fVK9ePdO6jIXsxFvYs2ePGD9+vPDy8kqlG0IIMXPmTGFrayu2b98uLl68KDp27ChKly4t4uJeef20adNGVKtWTYwYMULY29sLQBQuXFj8999/uW6zrB3vLoauHckkzwImr9mytbVN1ebkeleuXJn9G2EgGG1wuZQkJSUJlUolvLy80rxOVgNEyaZn7ybGbJiYTFRUlLC2thaLFy/OtC5jIb8ME5Px9fUVCoVCPH78ONdtlrXj3cQYtCOZ+/fvC3gVETcgIECv3qlTp4qCBQuKy5cvi9DQ0CzXa2gYlGFifnsPyYaJ7ybG7B+SzObNm1Gr1Xz11Vc5vg/vKtk1TEymRYsWKJVKTp06RefOndOsOydmq7Jh4ruDoWrHqVOnOHPmDI0aNaJQoULcuXOHCRMmUKZMGSmgYqVKlfTq9ff3T/N67xt5GhH3TTF27FgiIiKk9PoK7JQkm5452VlQvEEnKd/Wyozeg8cwdepU2fTMyMjMMNHf359Lly6le35Kw8TixYtLqU6dOtlqR3qGiTVq1GDSpElER0dTo0YNatSogb+/f6o+dOnSRXJ2lnnFmzRMnDFjBra2tlJydnZOt2yydhS3Nce2QU8pv7idhawdRoqhaoeVlRVeXl40b96cChUqMGDAAKpWrcrRo0ffawfnLJGbaR5y+Xoo2fjMzMxMAGLWrFlZum5WvIe08yqKISOHSCuVv/15ouwfIiOThxiDYWJOvIfC5tTQ8x66PrWurB0yMnmE0XoPzZgxg+HDhzNp0iQ8PDwAmDZtGk+fPs1dI176hygig1CnePt1OKEizze7647LyMgYDMnxGjKKv+Lo6MjTp0/ZvHmzpBunT59Go9Hg4eGRrm7kxHsoKeqZXrZ3eHnY0lvWDhkZAyDbg5bo6GguXLggvbtP9hB58OABCoVC8hDZuXMnly9fpnfv3qk8RNq0acPUqVPp2LEj5cuXZ86cOfTo0QNra+vcGSam8A8RQugZJsYLU36M+JpLm39Dq07K+TVkZGTyFIMwWk2hHYlCpWeYuErdmk2RVQnaOhqhUefuOjL5hp+fHyqVinbt2qV53NPTE09PT728ixcv0rNnT5ydnbG0tKRSpUosXLgw3WucOHECExMTqlevnml7SpUqhUKh0EszZ86Ujv/666+pjisUCgoUKJCl/r6rZHshrr+/v56HSHK0yWQPkdGjRxMTE8N3330neYjs3btXitECsHr1apycnPDx8WH//v2Sh8igQYPSND7L6mI67p+EyCAAYpNg3VIP6ZCpOoqtHtPZClSK30lBW1tMlEpMVQqUCgMwPTOAJhgDEfeucm7JEApXqEO1b2amOh58Zi8Axeu88gWJDrrN/UMbiQi8TFJMBBaFHXFy64Dzx93SvEZ44GUuLB1KAcfS1Bn+V4bt8ZvWg/gw/RmCD9p+i2sznela7NMH3PjfAmKe3EcTH42ZTVEcajSnVKs+KFX5EpA6S/zSrhLNKjpkXjCL5JdhYk60IzJR3zAxVq2gp8cxAKon7sSqoB1KJZgolRiCdMhkjetb5uDUsDP7Du6h4cRtmNsWBeDhv1spXrcdzy7rFsmueryH4NO7cf7kc4JP7yE6KJGiHUZQ0s6eiHtXGT5qDEuO3KVkI/3F30lx0fj//j02ZWpw51kYzeYdybA9TyLjKd26H8XrtZfyfLWW7H95ntqsHg0m/k/vnAvLh2PjXDHTuvOLotbmbPne7Y1eI9uq2aRJkwzt2RUKBVOmTGHKlCnpltFqtQghOHTokPQkBbqFdyl3ZiST3u6hVAIUEggJurbFJOq38XftHD5LPi86luhEbbrtkzFcQg97YV2tDWFXD3Hj+o3UpmehUbrPdx+kMD07SxLm2LQcJJme3dm9gucRcemYnk3DvORHJMSGc/vRs1RtSEmSWouNW3esq7za+ZJgZiGdp46IRPGBG4Xrf4nSvABJz+7z8OByQiOjsWv4ZXrV5jtPXxQnMjJjm4Hk719GepBMXjzszJ8/nypVqjB58uRUholp6QbkTDvCEvRHIt2TfFjw8udn4TEoY+UdRMaGNjGekPOHcOg5E7MnwVw9+D9s6uqCo8bEwQOPoZgW0S3SvnvUC+uPWpLw6Bk41UHhVIcXAHGAQ3WsKjXmgf9B4ks10rvG8z2/Y1amPhqFkoTQZ1nSjrA4LerIlL9P0S9TahKf3SP2yX2sP+mfad35RWRB8/QfDJLLZEM30iTvltdknewan72+mC45ZoOc5CSn/E+GbJgoa4ec5GSY6Z02TDQ3N9fbBmZlZcXp06dxcHB4b0zP4N3qz7timOjm5kZcXBwvXrygYsWKdO3alW+++QYTk7S/WoGBgQwYMIA2bdowevToLPX7bfKuGSbK2iH3BaBz5860b9+eAQMGoFarqVWrFsuWLcPNzQ0vLy88PT0pX748ADdv3qRv375p2tT4+/vz+eef4+npSePGjQHdd7pLly7873//44MPPmD+/PmptMPX15dZs2Zx5MgRKW/FihWUKVOGvn37MnHiRBYuXMjnn3/OpEmTUl03Pj6e2rVrM2jQIAYOHJjlfr9NZMPEDJBNz+QkJ8NJWXliMgTdkLVDTnIynCQbJgKn74bSf82ZTM9f1acOdT8onNUuyxgAhmx6lpK1a9cydOhQgoKC9J7wHz16RHR0NFeuXGHChAl8//33DB06NKe3wyDIjvGZIegGyNrxPjJhwgQWLVqESqWS8oQQmJubc+PGDSnw3Pr16wHd79nrXL9+nfbt29O7d28mTpwo5YeHh+Pq6qpXd/KaTZVKhbe3tzQjkxnXrl2jfv36+Pv76xmFAnTo0AEbGxupjcaMbJiYAtk/5N3FWEzPrly5IgBx/fr1dMusXbtWWFpaCrVaneV6DZH88h7KqW5k1GZZO95NjMl7aN26dUKpVKbyFbp7965QKBTZ+j03ZAzKeyi7HiK1a9fG3d0dtVqNhYUFSUm5i58iew+9m6jVav7++2/mzZtHq1at9I516tSJjRs3Sv4hffv2TbOO/7N33mFRHG8c/xwdRMBKUUF+9t6N2I0YG2osMRqjWGKMUZPYo7HHhjX2FhVbrLH32I1iBxuKJXbABhy93vz+OG/l6FXudD/P8z5yO7OzO8vxdXd25v3evn2bzz//HHd3d6ZNm6ZVZmVlxc2bN7W2LV26lBMnTrBjxw6cnZ0zfK4+Pj4YGBgkSzmfGJVKRVxcHCqVSusJ7VMlN3VD9h76tNFV7yEvLy8uXrxIs2bNyJ8/P15eXgwdOpRvv/2WAgUKaLW3Zs0a7O3tad26dbauxceCXhgmZjjXAu/9Qybuuo6yfneU5zcDUNjanOZDRlPWNr/sH6Jn6LPwbNq0CWNjY6pUqYKpqSlXrlxhzJgxfP311/L38B257T2UEbNVeK8dE3b6EJpIO2xtLPhc1g69JD3voVmzZnHjxg2qVq2a4v6JvYc2btwobXdycuLx48cZPo+k3kOmpqZs2bKFSZMmERMTg7OzM0OHDpVSAWhQqVR4enrSu3dv+QFHQ3aGeeDDeIhMnDgxxYk8aQ0vxcfFiX7z3/uHrD15OztdlclD3NzcRJs2bVIsu3jxogDE9evXU90/te+Pk5NTmvtUq1ZNa9vatWtF4j+Zq1evis8++0xYW1sLMzMzUaFCBTF9+nQRHR0t1dmyZYuoWbOmsLS0FPny5RMVK1YU06dPF1FR+v+a4aP0HhJCBIVGankP/ffiVab6JyMjkzrZfT2UZ4aJW7ZsESYmJmLNmjXi+vXrQqFQCAsLC/Hy5ctkx8mK6ZmYW178NOJnSXh6jJ4mm57JyOQgOXXTklu6kaVzvr1HvJldS+umZe2E7rJ2yMjkEHprmJgZD5GsmJ4J5QtCI957D52OKcvBP6fw+t8NWc/EJyMjk+PohPcQSNoRG/pay3toZVhDHq7pL2uHnpNb3kOnTp1K0SMordeWAEFBQfTo0QMrKytsbGzo168f4eHvs+FGR0fTu3dvqlSpgpGRkWRp8amT6TkteeUhkiESmZ5FxoHnsmVSkYiPoe3iqzC/FxO2l6eAjTXGhu/v2RQKUKB49y+yp4iO8vDWNWYP6Ualuo0Z4pHcF+j8IbVXR/3WnaVtzx7c4cimFTy4eYVwZTCF7IrTuEN3mnfpneIxHty8ytyfv8HBuSzjV+9L83ye3rvFzuWzeex3AwMDQ2o0bslXg8ZiZvHe1GxAk9LJ9vtuwh/Uae6WbLuu8Hl5W0oXtcyx9nRaN0BLO5J6Dz2Ns6b04lcwtxe/76xI/vxWGL3zLDP4RHVCH/Vx/az5NO3Ui+MHtjNr53lsCqvnUB3btoaGbl255qd2Cg89fJ1/92/DtWtfzh04xKs4U74e6UGBovY8vHWNkaN/5cKjIJp16gWA3/UXAEzZ+A9mFu//ZnbfDcPgXkSq57NwZF+UQa8ZNGstCfHxrJs5mptffsN3E+YDEBMVyaPgOKq36obK4giP30aw8szDXLk2OYWFiRHf1nPK1WPkiWFiZj1Ekk7EVSrVT0HJJuQ+Pg+v1V+gpN5DLnEX2fHu59Un72JgYoaM/hH0z3LyVW3F7asnmLzhWHLvoftPADgWei6R99AJ4oISMG/yA4XfeQ9tXzaLozf9U/Ee+hWTYpV5GRLC1F3XUj2XhPAgAjcMx7xsfaw7/Y4qNpJLp9dxdcj3FHYbrlW3YIsfMStZXfp8OMiCI2m0nddYdalKUTP7NOvog/dQVrQjKIn3kG3cc168+3n5MV9ZO/QQVWw0/kf3Ydt9JgYl7jF97qL33kP3QtjT5yvJe2iz559YVmnBhV3XgFJQohT3HwGP3gCOmJZrzK6//+acQj1JP/rZfQBW/PscA7PEDszPSI24oOcEXjqDbfcZbPJTAQao6vTg8u4ZvHBuK+ka//uSR/HwNuwfREzaeqQLFM1vSvuKBdKs80l4D6U2kVIOOeTI+/hQGXE1OXAsLCykjLhhYWFpeg/J2iGHHLoZH7X30JgxY7SWgsXHx3Pnzh1KlCjxyfiHwMfVn4/Be2jt2rUsW7aM48ePS3158+YNjRs3Zu7cuXTt2hWAEiVKYGtrS2xsLI6Ojnz77bd8/fXX0nnrErnlPZQTGXE1GjBx4kTq169Pnz59+P777zE2Nk71HGTtkPsCues99PDhQ7y8vKhatSqxsbFs3ryZnTt3snfvXqpUqQIk9x5atGgRO3bsYP/+/Vr9qV69OsOGDaNXr15axx06dCihoaGsXr06K5ftgyB7D6WB7B8ihxy6E5l9YoKsZ8StWLGiGDx4sBBCiEOHDgmFQiHs7Oxk7yE55NCzkL2HgAM3/Bn9983UdpPw6FyFtlUdMtplGR1AV72Htm/fztixY3n79i2GhoYMGDCArVu38uOPPzJ06NAU95k2bRqbNm3C19c3W9ckr8m2h8g7MpMRd8KECbi7u1O7dm1q1qwpnUdqupF0Tot49x49qXYkpfJE9QhbnZIF6FKrOEUszahVsgCGn+rMWz0mN72HUmPcuHFcuHCBY8eOpVi+YcMGfvvtN54+fSpti4+Pp2jRoqxbt04aMdYwcOBAlEolf/31V/od1nFk76FEnH/wRjiN3i+c0vAPsaz6hTh1+0V2ui2TB+i691BgYKAICwsT4eHhwsDAQGzbti3Vuvv37xeAVhI6fSSvkstpdMPExEQYGRml6AmjISuJKaOjo1P1Htpz9VGm+iqTt+S291BquLq6io4dO6Zarvl/8MqVK9K2I0eOCIVCIV68SP7/k7u7u+jQoUOGj6/LyN5DiajrXBB7azMCldGoUvEeAqhRIo08LzI6hz54D2lS0K9ZswYzMzNatGiRal0fHx8KFCig5QItk3EGDx4sjaAVLVo0zd9P0jktmqe8tDjg/SxV37IhG69iYmJKq8ppr6yS0Q1y2wIE4I8//sDZ2ZlKlSoRHR3Nn3/+yYkTJzh69KjUTlILkAoVKtCqVSv69+/P8uXLiYuLk5bwOzi8fwvg6+tLbGwsQUFBhIWF4ePjA0D16tVz4vLoJR+V91Bi0zMDQ0OsE/mHKAwMsWnUk/bVHTAzNclaB2XyBF31HgJYvHgx9evXx9LSkn/++YeRI0cyc+ZMbGxsAPWE4JcvX1KvXj3MzMz4559/mD59OiNGjMjuZflo0EzIe/nyJfb2728GXr58KYmznZ0dr1690tovPj6eoKCgNCf0mZqaZurmMEElmHn0foraAaAwNGTyPl9aVLSTXxXpAR/Ceyg2Npbhw4fz4sULLCwsqFq1KseOHdNa4p/UewjUr6MGDx5M8+bNMTAwkJbwJ6ZNmzY8efJE+lyjRg2ATzvJYXaGecjmMG9iihQpIpYuXZricTI7xHvopr+oP+2IqDl0lVS3yphd4tBN/xTry+g2uuo9JIQQPXv2FAULFhQmJiaiatWqYv369Vrlhw4dEtWrV5e8h6pVqyaWL18uEhIS0u60HpBTr4c0r5XnzJmj1XZKr5UzOpye1XM+/+CNKDl6r1Ya/xJDt0uvnTVx/sGbTPVZRkZGjU6l8U/8xJSYxMubEj8xLVmyhJIlS2Jqasrr168JCwtLsd0xY8agVCql0Cw5TY1WBpf51+xnGhq+H/JvIK7SyuBylvsmk3fs27ePAwcOpFhWt25dhBCpPikBTJo0CaH22dKKtFxaJ02aJA3Faujdu3eyJ5z169fz9u1bYmJiuH79Oj179tQqb9WqFd7e3oSFhREeHo6Pjw8DBgxIc7ntx4im75prqsmI+/TpUxQKhZQRd+/evdy8eZNevXoly4irGU4fOXIkdnZ2tGrVigIFCvD8+fMcO09Dv30cMBmjtc2eIL5QXNLa9iosOseOKSMjk3HyzHtoxowZDBs2jIkTJ7J48WJAvaoi6RAwZM17COULwhJ5Dx2NrsCtNUNk/xAZmTzgypUr1KhRQxreHjZsGDVq1JBWYowaNYohQ4bw/fffU6dOHcLDw5NlxN20aRPm5ubMmTOH0NBQvvzyS9q3b0/Lli1T1I1M47uXOpd+wUaEankP+YuCNIg+S+Pok5J2FM0vZ8WVkckL8sR7qFWrVkydOpX27dtTtmxZ+vTpQ7du3Thz5gxr1qzh119/zVpvkngPrV22XCqKiRdU+eMpzO2Fz4PmFC2sXr5oqFBgaKBAgfx+Wh+4dPECrVyb4tqiJdt27klWvmnDegB69HyfnOnmjev8MXc2F7zO8/btGxydnOjT73sGDhqitW9MTAyzZkxl65bNvHoZiK2dPaN+/Y2e7r1TPZ/o6GjGjRnF3zu2ERsTw+euLZg7fxFFE83rGjViKBe9znPH9zZly5Xn3wtXsnkVch9zE0NMjHLumaZp06ZpPiwoFAqmTJnClClTUq1TsGBB4uPjGTRokPSgo1KpOHr0aPZ0A7S0Izxe23tIxMfQe/FJ4CROQz+jSCEbShay4HVYDAoFkgeRrCG6ja5ph+eaP9m+bQs3fNQjsY9fvJLmwgGcPXOadq1TntB/4sx5ataqnYnefyAUYG1unLuHEJkcdjh16pTWBCMNGg8RIQQTJ05k5cqVkofI0qVLpWyDoJ6M6+DggKmpKSYmJtIEpEGDBhESEsKePdpfqJT8QxwdHZPnWnh8Hjars5BGxAoc5r13zCz//XzurlTnzSj243rZP0RPCfpnOQpjMyJun8De/Y8UvIcuAmBe5jNt76HXTzAv/RlG77yHgo+vxLrht1reQ6/3zkIVqcS6/tcYWduREBECqDB1KJ/6+RxfRfTjaxT8YhAGJhYEn1wNCgNsv/5dqhN8ag1GBRyIDXxA3Osn2H07O1euTU4yq0tV2lRJ33uoRIkShISEpDjRMaeJjY3FwsKCHTt2aDneuru7p6gbkDXtuBNdhHp//CcVdRgwjD0r5gGydugzuqYdYdcOIBLUK2aV5/6i2A9rtbyLREI8quhwrX2UXluIfnoL+z6LdDKjdtH8ppwY0TTNOtnWjexPq8k8sveQHHJ8PJHVzJa5rRtCyNohhxy6GnrlPZRZkuZaUKlUBAUFUahQoTTvNjV3dOllv9QXPqb+ZKUvGzZsYPXq1Zw6dYrDhw/z66+/4u3tLX0Hnj17xueffw7AiRMn0szH0b9/f6Kjo9mwYQOgnmPx4MEDatSowdatW7GwsKB169aMGzcOc3NzAM6ePYubmxs3btzAycmJ06dP0759e27dukXlypWlvlSuXJmBAwcyaNAgrWNmNMtuXpKZ34sQgrCwMK28ErqGrB1yX0D3tCNpfwCePHmi9XooKXv27KF3797cunUrTV+1vCKjv5vs6kaeLGHIrGFiShNxTUzkXCufGhs2bODrr78GwNXVldDQUOkGYOvWrfTu3ZsvvviCL774gt69e7N169YU27l48SI7d+7USkT3+PFjLly4wJ07d9i0aRMzZ85k7969DB8+XKpjYWFBmTJlMDZWv7N99eoVJiYmyYY4ixQpkuy7/alz5swZ2rVrh4ODAwqFgt27d2uVCyGYMGEC9vb2mJub4+rqyv3797XqGBgYoFAoaN68OTY2NvTr14/w8PA0zddk7ZAB3dOOrPahefPmOnnD8kHJ0vhMGqQ0HFuuXDmpPCoqSvz444/C0NBQGBsbi06dOonAwECRkJAgGybKIYceRkaGeQ8ePCh+++03sXPnTgHJjVZnzpwprK2txe7du8X169dF+/bthbOzs4iKipLqtGrVSlhYWIguXbqIs2fPitKlS4tu3bplWDdk7ZBDDt2JrL4eyvRE3PSYNGkSO3bs0DKKMjIyonDhwoDa+OnAgQO4u7vj4eGBo6MjVlZW1KlTh23btnH37t1kGXWTolQqsbGxSXcYasvlp0zdfweAZuWLsKh7zRzooUxekNumZz/88AMXLlzQys3i5+dH3bp1uXbtGqVKlUrWnub1UNJhXX1+PZQZsjqhTqFQsGvXLmkyrRACBwcHhg8fLmUKViqV2Nra4unpSbdu3bhz5w4VK1Zk2rRpTJkyhRUrVhATE8OAAQOwsrLi3r176eqGpt2UtOPSf0H0XZd+Hqc17nWo+7+CGe6rTN6ji9qRGM2ro7ReD82aNYsVK1Zw9+7dbI3W6AI6NxE3pUyiGkJCQoSxsbHYvn27EEJtfGZvby9AbTl/4cKFDB0jIxn1oqOjRb3WX4l8VVyFmXNNka90HfHyzVvx3Xffie+++07vzeo+JT6E6dmKFSuEubm5CAsLk7bt3r1bGBgYiMjIyBT30Xyfd+zYIW27e/euAISXl1ey+mn9begjOZUR9+HDhwIQ3t7eWvUaN24sfvrpJyGEEKtXrxY2NjZCiPeGicbGxgIQM2fOzPY5xyeoRL3px0TJNMxWi9ZuLSIio1JpWUYX0VXtSMzJkycFIIKDg1MsV6lUwtnZWQwfPjzdtvSB7GbEzZWbFgsLC2Fvby+cnZ3FN998I548eSKEEOL48eMp/nIcHR3FvHnzUm0zOjpaKJVKKTRDvGl1Ojw8PNlw1O7zt6Wfj994IuITVDnSZ5ncZdeuXcLExETLzVnDqFGjRO3atdPc/+bNm6JIkSLi22+/FQEBAVK8evVKqhMWFiaKFy8uunTpIm7fvi1Onz4typQpI7777jupzsWLF0W5cuXE8+fPpW0//PCDcHR0FCdOnBBXrlwRLi4uwsXFRev49+/fF97e3mLAgAGibNmywtvbW3h7e4uYmJisXhKdIK9cnhOTlv2HEJnTjkM3/UXJ0fu1UvgDovjgjdLP4eHhmeqrTN6iy9oREBAgvL29xapVaruZM2fOCG9vb/H27Vutczh27JgAxJ07d7J6GXQKnbtpOXjwoNi2bZu4fv26OHz4sHBxcRGOjo4iNDRUbNq0SZiYmCTbp06dOmLUqFGptpkVe/mYqEjx+Ve9hXX97lL9ciO2CZtGPYVNo57CccQuUW/6MdmPSA/4UN5Dd+7cEa6ursLc3FwUL15cDBs2TOtJSfNE9OjRI2mbZo5WgQIFhIWFhejYsaMICAjQardJkyYpHj9xO/qIPty0ZMW3rO6kfVq6Ufu37aLXkNFi6tSpen+j+amhy9qRWttr167Vart79+6ifv36me67rqJzNy1JCQ4OFlZWVuLPP/9MdtOyePFi4eTkJBQKhbC3txcXL15MsY1Mj7Tc3iPE3PLit7E/az01lRm6Scv0rOS7kG9cZGQyT169HtLohomJiQCEh4dHqsfKinYEz66hpRs3f3dRa4qMjEy20SnDxJSwsbGhbNmyPHjwADs7O2JjYwkJCWHr1q2S95CdnR1OTk6peohkyXso1J8YtCcsRWNKFcVD6bNmBvLkfb4kqHJ0PrKMjEwGyS3PMsiadsSFvdbafCC0lFpTfPdms6cyMjLZJddvWsLDw3n48CH29vbUqlULY2Njjh8/zrx58+jfvz/169cnICCAuXPnYmFhwZo1a7J+sET+IUIIQiLitIzPhBA8jLBAFRks+aAIIEAZzaVHQdnrqMwHwcvLC0NDQ9q2bZtiuaenJ56enlrbrl+/Tvfu3SlRogTm5uZUqFCBBQsWJNt3yZIlVKhQAXNzc8qVK8f69evTPZ/o6GgGDRpEoUKFsLS0pHPnzslytPz000/UqlULU1NTqlevnuG+fkzklMtzYs+y2bNn061bNywtLbOnG6ClHXHCUEs31sW14HRYcV7vGIFIiM/ecWTyDH3Tjowe+1MjxzPijhgxgnbt2uHk5IS/vz8TJ07E0NCQ7t27Y21tTb9+/Rg2bBjPnz+na9eu9OnTBxcXF+rXr4+rqyteXl7J2kzqHxIaGprywZ+ch1B/ACLj4M8kv+BKCXc4ski9XK3E0B0oEnmITDvgi72NuWx8puOcXu1BRdev+efEHnouPEy+AkUAuHF4E+WbfMmjK48BOBN7hrund1O1VQ/unt7D2yCo0Ws8lgVtCbx/gxGjRrP96gsqt1AnnLp9fAcXty6icd/fqPG/irz67zbfDRjIXz5vKVmjcarnc9ZzBk99/qXp99MwMbfk3/WzqNboC74c//4/0XN3X2Fd2RUnczueP3vADxuu5t4FyiH6NXKmTsmcW9p75coVLc8yTZZajWfZqFGjiIiI4Pvvv5c8y5K6PK9duxYHBwf279/P0aNHtTzLUtINyJp2hMZqGyaGxhvSdPFtADqb7ydfIQeMDBQYGKiNEj819FUf9U07MnJsXcPGwpiZnavm6jFy/Kbl+fPndO/enbdv31KkSBEaNmzIhQsXKFJE/QWZP38+UVFRrFu3jnHjxtG6dWuWLl0KgK2tLXfv3k3W5owZM5g8eXKy7ckEKPARxKhHUCJik7/u8VAt4Mi7n1UxkSBUUtmNR5HcyEqHZT4Yqtho/M8fwbb7TIwcn7Bv6zqs6nYCIOJ1DFcnfodxIXVK7PP7/sKySgueX/sP8leBilXwiQQiY8G8PGblm3Dl5EGeFqoDwMujOzGr9Dn3TEpz73ksmJTBtOLnnNy6AltRPOXziYnkxandFGr9M9ejC0E0GDToS+D6oew6cBhT+3cmoZU6owSUfv8RFRnDwWv/pdieLtH0f5aUK5i2PGj+/kQGUj3lhMuzSqVCCMGJEyek10aQum5A1rQjKEb7P+VGcefZ8u7nC4/DMPB/kuo5yugmeqkdGTi2rlE0vymhLUqmWSczupEiOTW5JjNk1vgs6WQ6X1/fD5q5Tw455Eg9csIwMSOZtN3d3QUgzM3NpUzaaemGrB1yyKG78cEME8+cOcPs2bO5evUqAQEBWpktAYQQTJw4kVWrVhESEkKDBg1YtmwZZcqUkeok9hAxMTGhc+fOLFiwIE3vIVNTU+mzhYUFly5dwtbWFgOD1KflhIWFUbFiRXx9fcmfP39mu6pzfEz9yUpfOnbsiJubG/369SM+Pp5atWqxfPlyXFxc2LlzJ56enpQtqx7duHfvHr1796ZTp07J2rly5QpfffUVnp6eNGnSBICZM2eyfft21q5dS5UqVbhx4wZ9+vTh9evXXLlyBVtbW7y9vRk6dCibN2/G3t6eXbt2MWLECHx8fLT64ubmRv369Rk7dqzWcefNm8eRI0c4cuRIsnPSFTLze1GpVGn6/mSWSpUqJcukrWHo0KGcOHECAwMDfv/9d3bs2EGnTp04d+5cut5Dn7p2yH3Rf+1I7di6REZ/N9nWjcze5eiCh4jsHyKHHLoTOTXSkpFM2nXr1hWDBw8Wd+7cEYA4d+6c7D0khxx6GB9spKV169a0bt06xTIhBH/88Qfjxo2jQ4cOAKxfvx5bW1t2794teYgcPnxY8hBxc3Nj5MiRkodInz590j0HzV1cSt5DB274M/rvm+m24dG5Cm2rZs0aW+bDk9v+IRri4uJ49eoVdnZ2rF27lkmTJvH06dMUn8pl7yG1h0hOPb3fv38fBwcHzMzMcHFxYcaMGTg6OnL16lXi4uJwdXUlISEBd3d3ateujb29PcOHDyciIiJV3Ug6EVe8e4+enm/ZxYdv6bf+ivT54M8NcSyYL0f6KfNh0XftyMix9Yls60aWbnXeAXnjIZJWcprzD94IpzT8QyyrfiEch+8S5x+8yVqnZT44H8I/JCUaN24sunfvnmq57D2UvSRRiclMJm2NbmiSUqblWZaVbNrR0dGiaftukm+Z+f9qi+l7r4vo6GjZu0zP0HftyMqxdZ08zYib9KYlt9JxZyarpcb4zDGJf0ixRP4hdSbtk32H9IgP4R/i5+cnNmzYIO7duycuXrwovv76a1GwYEGttNuy95A2OXnTkpS0MmlrSM/+Q4ic8y2rPXGfUIaGSZ9lDyL9QJ+1IyPH1kd0PiNuTjBjxgysra2lKFGiRKp1DQ0UTGxXEYWhIdb1u0vbFQaG2DTqiU2jnoxvXwXDTzHBgp6yevVqXF1dU7Qx79y5M1euXOHGjdQXrO/YsYPXr1+zceNG7O3tpahT5/2ywYSEBObOnUu1atVo0aIF0dHRnD9/npIlS0p1IiMj8fPzIy4uTto2f/583Nzc6Ny5M40bN8bOzo6dO3dqHf+7776jRo0arFixgnv37lGjRg1q1KiBv79/Nq7Kx01qmbQTk5HJfJnKiPsOY2NjGnYbpKUfL0NjuPAohKlTpzJ16lSMjY3TaEFGV9Bn7cjIsT9JsnPHRDZfD2XUQyQrT0uHbjwT9Uatlp6MSgzdLhskysjkILk50hIWFiYKFCggFixYkGwoffHixcLBwUEAomLFiql6lmX5nBPiRc9Fh7T8h0oM3SEGrL8iVYlPUInzD96I3d7PxfkHb+SRWxmZDJJd3cjR5HKJPUQ06co1HiIDBw4EtD1EJk2axPLly4mPj+f7779n2rRp9O7dm6JFi2q1m3TZYrr47qXVP6M5kNCKC+82FVUoOe1mjEll+xzoqYyMTE6S0Uza169fZ8aMGTg5OVG9enXq1KlDy5Yt8fPzS6YbWcJ3LxwezcvXPwHa7R2785JAZTQ+z4KZvM+XAGW0VGZvbcbEdhVpJeuLjEyukunXQzrvIfLO9EwoXxAaGSttfqmyZs2aFbz+d0PWM/HJyMjkCppM2uXKlaNr164UKlQoWSZtNzc3pk+fDkDVqlU5dOgQy5cvz75nmYZE2vEiQtt/qKbiHnEJKr5ecIT+K0/iHxKltWugMpqBG69x+FZA9s9DRkYmVRQik/+Dnzp1SstDRIPGQ0S8Sy63cuVKyUNk6dKlUuIegMDAQBwcHDA1NZWSy2k8REJCQtizZ0+a5xAaGoq1tTVKpVL7HbUqAf6oDKH+RMQKLGeESUXFBm/kxeJvAVh17Ba2hQtgZKDA0ECBkaFCb/00PjVue1/m52/bU6fh58xYsSlZ+eFd6oTrrTp2k7Y9vHubv1Yt5Na1SyiDg7ArVoJ2X/eic6/vtfbdvWkNu/9aQ+CLZxS1L8a3A37hiy+7pnk++7et5/j+Xdz3vUFkRDh7L97D0kr7/XloSDCLpo3F6+RRFAYGNG7RlsFjp2GeT3eX0FZ0sMLWyizNOqn+HeYSsbGxWFhYsGPHDq2Elu7u7hnSDciYdryNMaLwTG0D1eujy/JV7CTuzf8GUHuXGZgkvz4FLIyZ1aUqhgaypugaWdEOZXAQ00f9yH9+voSGBGNTqDD1P2/Fd0PHks/y/ZJdn0vnWDpzIk8e+FHE3oFvfxiq1U5KpKcLsTHRzJ80inu3r/Pkv/u4NG3B74vX5cSlyDVMjQyoX7pwmnWyqxuZfj2UFx4iSXMtKJXqJ6Bk/iGPz8PrF0By7yHXuLNoft2Tdl5LUXBkdJ+gf5ZjUbUVl7xO8O3cXRhaqk39wq7tJ1/l5kTd9wNg0/PDRNw6Tv6aboTfPkHc6xjMG35PofyFCPf3Y+ns39nk9Yj81VsBEH79KCHnNlGw+QAKNSlFVOADPCaM5E+vZ5j/r3aq5xN27RbCpCTG1UvCub8YuPYcBmbaNyOvd00nISKYAm5jQJXAP/8s5fTtnhRq/XPuXKQcYFaXqrSpkvarjmx7iGSSN2/ekJCQgK2trdb2tLyHsqIdj6KtAO2bliJx/iwUM2j17nNS7zINb2Og36qzmeiVzIciK9qhig4n0rgUJq5fUNjciviQQA4cWs0/V/2kv9945SsCNwwnX9UWFOreh8int5j121DWXHqJecnqqZ5Perqgiosm5GEQJo6NMYk15dqjN7ivOJ27FymbFM1vyokRTdOs80l4D6WWa0EOOeTI+8iJjLi5oRtCyNohhxy6Gh8sI25OULhwYQwNDXn58qXW9tSWMI4ZM0aysgeIj4/nzp07lChR4pPxD4GPqz9Z6cuWLVvYsGEDBw4c4NixY0yaNImzZ8+iUKiH4V+8eEG7du0A2LdvH8WKFUu1rZ9++omYmBhWrFgBQJs2bWjWrBkjR46U6syaNYvly5fj5+eHsbExXl5edO3alfPnz2stu9f0BeDWrVtayyu3bNnC1KlTuXXrlrQtPj6e0qVLs2zZslSzS+cVeek9lB6Z1Q2QtQPkvkDOaUdgYCBDhgzB3t6ehQsXAuql01WqVGHSpElSva1btzJ58mR8fX0B2LZtG8OHD+fZs2fS+UydOhUvLy+pP+bm5qnqwtChQwkNDWX16tUZ7vOHRme9h3IKjYeIhoSEBNl7SA459DA+1EiLENnTDSFk7ZBDDl0JvXJ5DgoKwtjYmMWLF7N69Wpat26NtbV1mh4iiUnNe0j2Hfp4uX//PvXq1ePu3bvSipIRI0YQGhrKypUrWbx4Me7u7uzduxeA9u3bs27dOgYPHqzVjq+vL25ubgwcOFBrVCUqKooRI0awZcsWhBAULVqUrl27smDBAu7fv5/uctqzZ8/i5uaWzEtkzpw5bN68matXr2rVL1WqFGPGjOG7777LzmXJU3LSe2jSpElMnjxZa1u5cuWkuSrR0dEMHz4cX19fLl26hJeXF/Pnz2fjxo0Z1g1I27csMZUnvnfivjnpC+mJXEb/yAntePnyJUqlkgcPHjB58mQaNGjAvHnzAKhZsyY9evRg+PDhUv2jR4/y1VdfERgYiLm5ebJzyqwuDBw4EKVSyV9//ZUzFyUPya5uZPqmJSIigmrVqtG3b98UrbtnzZrFwoULWbduHc7OzowfP56WLVvi6+uLmZl68muPHj0IDw9n+PDhbNiwgZ07d1KwYEEOHz6cbJJdSmgEJGmGy5L2cRiYWqS7f0n7Ih9ktYNMzrF161bi4+MpV66ctE28Mz1bsWKFZOWuEYhixYols3f39fWlQ4cODBgwgN9//12rzMrKig0bNrBmzRpevnyJvb09K1euJH/+/Pzvf/9L81UCQL53M/6TfSdLluTNmzda2+Lj4wkODsbZ2fmj+B7m1H/olSpV4tixY9JnI6P38jR06FAOHDjAnj17OHz4MAsWLKBJkybUqVMnw7qR+FzTy45rZGaBSqh/Do4zomRh3V3pJZM2OaEdmu9K7dq1KV68OI0aNeL333/H3t4eBweHZCthwsLCsLKySvV7mVldMDY2xsjI6KPQCw1Z1o0sjc+8A7Qz4qpUKmFnZydmz54tbQsJCRGmpqZi8+bNQgghfH19BSAuX74s1Tl06JBQKBTixYsXGTpuahn1NL5DJdMwTCxau7WIiIzKRq9lPjS6anqWmJMnTwpABAcHa23XfN+vXHmfTfXIkSOZ+r7rKjmZETctM0lNRtzt27dL2+7cuSMgZWPKtMjIOUdHRwvLqu+1Y/Wpu7JZop6SE9qRlNOnTwtA8hYaNWqUqFy5slad7t27i5YtW6baRmZ1wd3dXXTo0CHT56qL6JRhYmbT+GuIi4sThoaGYufOnSkeJzNp/A/d9FfftKRhmCibnekXumx6FhAQILy9vcWqVasEIM6cOSO8vb3F27dvpTqtWrUSNWrUEBcvXhT//vuvKFOmTIZvhnSZnL5psbCwEPb29sLZ2Vl888034smTJ0IIIY4fP57iDaGjo6OYN29emu1mxQIkNJExIiDazTsmtpy/J+uHHpJd7Thw4IBYs2aNuHnzpnj06JHYv3+/qFChgmjQoIFU57///hMWFhZi5MiR4s6dO2LJkiXC0NBQHD58WKqzc+dOUa5cOa22M6ILt2/fFt7e3qJdu3aiadOmktmqPqNTNy255fKcWXv5Qzf9Rb3J+4VD/S+lulV+3SZ6DRktpk6dqvfuup8abm5uok2bNimWXbx4UQDi+vXrqe6f2vfHyclJquPr6yuqV68uzM3NhZWVlejQoYO4e/euVjua0ZTENzKptb127Vqpztu3b0X37t2FpaWlsLKyEn369BFhYWFZuha6RE7etBw8eFBs27ZNXL9+XRw+fFi4uLgIR0dHERoami2X58xqhxBCKEPDhHX97lLdEkO3C8cRu4RNo56iRIs+Yu+1x9nur8yHIbvaceLECeHi4iKsra2FmZmZKFOmjBg9enSyG+iTJ0+K6tWrCxMTE/G///1P6+9fCCHWrl0rkr7YyIguODk5pfj91Wf0+qZFY5hoamoqjIyMUhWgTD8t3d4jVHPLi19G/CT9kseO/UWI23uy010ZGZlE5KZhYnBwsLCyshJ//vlnspsWjW4oFAphb2+fpmFiVrRDObt6MrNEt18XCKfR+0XJdyEbr8rIZI3s6kamvYfSQrPuOq08CnZ2drx69YqtW7cybNgwJk6cyKVLl0hISGDx4sW8evUqWbuZspd/5x+iCPUnThhKmw9GVSZya391uYyMjE5jY2ND2bJlefDgAXZ2dsTGxhISEqKlG3Z2djg5OdGyZcsUdQOyph0xYW+SFUVjSgvFZd7NzWXyPl8SNDN1ZWRkPhg5etOS2OVZg8blWZOuX+Py/Pvvv9O/f3/69OlDYGAgoF6OmC3jM1UCHB4NCIQQKBMZJr4R1vyo7MnVLdOJj4vL+jFk8hQvLy8MDQ1p27ZtiuWenp54enpqbXv79i2tWrWS/K5KlCjB4MGDk6VyP3XqFDVr1sTU1JTSpUsnayclgoKC6NGjB1ZWVtjY2NCvXz/Cw8O12uzQoQP29vbky5eP6tWrs2lTct8TGW3Cw8N5+PAh9vb21KpVC2NjY44fP868efPo378/9evXJyAggLlz5+aMYWIi7YgV2maJ1oRxT1WMoKh4VJHBqIQgQBnNpUdBqbcno3Pom3Yk5sGDB+TPn18rncKnSqYNE8PDw3nw4AEANWrUYN68eTRr1oyCBQvi6OiIh4cHM2fO1FryfOPGDa0lzy1btuTo0aN4eHjQoEED+vTpQ+3atTE2Nk7R+Cypf4hmnXcyw6VHZ2GdG0Ayw0SnwZ48WdwbgJLDdmBpaYnBO8NEA4UCOQ1DzpGbl/LRrrkYmpjz+uphqvyyBhMrtTlX4Lm/KVK7NcG31b4vBSo14vWVQ9g16Ex8VBhBN06Rr3hZjCxsiAl6wZN9i7FwKE2pruqljTFBAdxa9D1F6ralSK3WhP7nzdODyyjbcyrWZeqkej731o0lNuwtJTv8gkhI4NGu2eQrVk5q1//UX6jiY7EuWwfjfAUI8bvAs0MrKNNjMjbl6+Xilcoev39ZmZaV0s5YmZOGiSNGjKBdu3Y4OTnh7+/PxIkT8fHxwdfXlyJFijBw4EAOHjzI8+fPmTVrFn///TcA58+fT9MwMSva4RtdhEoeD6Wig6NcGBL3Ew/ndwfemyVamBhiamSAQqG2RlRriFpLZDnRPfRNOzSoEuK5s/JnjPNZE/7Ul5rjdufOBcoBilqZsn9IozTrfHDDxCtXrmi5PGtSZGtcnkeNGkVERATff/+95PJ8+PBh6YYFYN68eVSuXJnJkydjZGQkuTxPmTIlReOzGTNmJEs8BSmYngU+ghj1PVhSw8S5qjl0efdzXHQkSlVyszMZ3UYVG83bG6ew7T4T07cvefzvHqzqqnMFRcQb8HLVCIwLqdPrvzi/B8sqLQh8E6zeuVRDwgASAGtnzCo1R3l1n1QecnYHBlZFMKnzNUqA0k0wL+3N01NbKVKgdIrnExf0HOX9y9h2n0G4ufo/+PyNevNm9wzM6n6NoWVBDCq3xgCIAPUMibLNMPO9gP+140QXLpdiu7pAcIiS0NC0cx7lpGHi8+fP6d69O2/fvqVIkSI0bNiQCxcuSMnA5s+fT1RUFOvWrWPcuHG0bt2apUuXAmkbJmZFO4JjtG85qsffZKWYQvN3nzVmieExkPJzsYyuoY/aoSHk7EbIb4thiSqoHt9+f146iCrGNPnfVhI+CcPEpJPpNGvc5ZBDjrwPXTZMlLVDDjl0Mz5qw0RTU1NMTU2lzxYWFly6dAlbW9tPxvQMPq7+ZKUvHTt2xM3NjX79+hEfH0+tWrVYvnw5Li4u7Ny5E09PT8qWLQvAvXv36N27t1bW5kGDBnH06FGio6NxdXVl2bJl0ghg48aN6dq1q1bq7hMnTuDu7s69e/cwNzfn0KFDeHh4cOrUKQAWLVrEjh072L9/v1ZfqlevzrBhw+jVq1eyPuzbt49ffvmFgwcPamXo1BVyyzAxJ+w/DAzUr2KaN2+OiYkJnTt3ZsGCBWmeg6wdcl9AP7UjODiYVq1asWDBAurVq8e2bduYPHkyt2/fzoErmfPorWFiSnkREifViYqKEj/++KMwNDQUxsbGolOnTiIwMFA2TJRDDj2NjDwxHTx4UPz2229i586dArRTJQghxMyZM4W1tbXYvXu3uH79umjfvr1wdnYWUVHvs1e3atVKWFhYiC5duoizZ8+K0qVLi27dusmGiXLIoYeR1ZGWTE/ETY9JkyaxY8eOZB4ihQurJz0NHDiQAwcO4O7ujoeHB46OjlhZWVGnTh22bdvG3bt30/URUSqV2NjYpGt6dvR2IMO2XQegWnFrNvXX3YmPMmkzfvx4Fi5ciKHh+2Xs4p1/iJ+fH9bW1gDSypwePXqk2Z6XlxetWrXCz88POzs7WrduTbVq1Zg5c6ZUZ+PGjYwZM0ayk0/Khg0b+O2333j69Km0LT4+nqJFi7Ju3TrJ6h7g33//pWvXrkybNi3D5n66jmZSa0hIiHT9M4JCodAaaRFC4ODgwPDhwxkxYgSg/hu3tbXF09OTbt26cefOHSpWrMi0adOYMmUKK1asICYmhgEDBmBlZcW9e/cy5D+UmnZc+i+Ivusup7v/Gvc61P1fwXTryegO+qodjo6OWquJhBCoVCoMDQ1ZsGABPXv2zPzF0AGyqhsacuX1kJGRUYpDP0qlktWrV/PXX3/RpUsXbG1tmT59Og8fPiQmJibbhonJjhcbQNDxlUQ/9uF1EUdC3U9QJL+ZNIy3ePFiraFjGd0kPj6erVu3MnfuXL744gutsi+//JIDBw7www8/AOqb4oygMUczMTHBysqKhg0bcvDgQa3v07///ouLi0uq37HPP/8cpVLJ/fv3qVWrFqB2d1WpVDRr1kza79SpU3Tt2hUPDw8GDRqUuc7rAdk1THz06BGBgYG4urpK26ytrfnss8/w8vKiW7dueHl5YWNjw9ixY7GysmLChAkEBAQAMHbs2FR1I+nqobAw9YrCpNoRQZhktiri43h7dAnRj30wLuxIkfajCT65GoCQ7rU+KtO6jx191g4vLy8SEhKkffbs2YOHhwfnz5+nWLFiev89zBPDxJTIDQ+RrPiHCCHEzL3eWsNRG876ifDwcOmz7CGiH+izf8iJEyeEhYWFGDNmjJbvUWJvIn0lq5kt4cPYfwiR8TT+5x+8EU6j9wun0fu1suGCtm/Z8RtPMtVXmbxFn7UjKWvXrhXW1tYZ7LnuolMZcQE+++wzPD09OXz4MMuWLePRo0c0atSIsLAwAgMDMTExSZYgx9bWVkowlxIzZszA2tpaihIlSmToXOKEAdb1u0ufT959xdWnofQYNIrvh43FwDBP5iHLZJLVq1fj6uqa4lBi586duXLlCjdu3Eh1f3Nzc1atWkXDhg2pUKECQ4cOpX379uzfv1+q4+zszIEDB/jnn3+oVq0ac+fO5c8//6Rly5ZSHaVSiZ+fn1bbmzZtonz58jRv3pw2bdrQsGFDVq5cKZWvW7eOyMhIZsyYgb29vRSJJ/nJ5B5jxoxBqVRKkdpwfV3ngthbm6nzrRgaaumGwsAQm0Y9KdGiDy5l0h8JltEd9Fk7ZFImx+e0JCUkJAQnJyfmzZuHubk5ffr0kYZrlyxZwuzZs3n69Cl2dnbs3r2bunXrJmsjwwmiEqNKYNJfJ1hzLZRn89UZWjRJoTTYW5sxsV1FWlW2z8Eey8h8GmQ1SVTSOS3//fcfpUqVwtvbm+rVq0v1mjRpQvXq1VmwYAFr1qxh+PDhBAcHS7oREBBAbGwsHh4ejBo1KtvnfPhWAAM3XkOBivjYWEk3nIZuQ2FiwbJva8paISOTTbKbXC7HR1qSkhMeIpnyDwG1h8gflYm5cyjNaoHKaAZuvMbhWwHZ6aKMjEw2yIz9x4wZMyTdWLx4MQDTpk1L1XsoM7SqbM/OZm84YPqb1va2hhfY2eyNfMMiI6MD5PpNywf3EHlnekaoP9EqYy0PEQCFSCAhUklCpBLVu0Em2fxMf8gt/5CAgAC++eYbypYti4GBAb/88kuGzic6OppBgwZRqFAhLC0t6dy5c7L8Qz/99BO1atXC1NRUayThUyI8PBwfHx98fHwA9eRbHx8fnj59ikKh4JdffmHq1Kns3buXmzdv0qtXLxwcHKTRmAoVKtCqVSumTp1K+/btKVu2LLNnz6Zbt25YWlpmXzcAfPdSw+tnrESolm4ciq+D8ugcXv+7IUey/8rkDfqmHdevX6d79+6UKFECc3NzKlSowIIFCzLd74+NHJ/UkZKHiKGhId27d8fa2pp+/foxbNgwnj9/TteuXenTpw8uLi7Ur18fV1dXvLy8sn7wRKZnABFx4L+in1Tc2MCHM3HVeb5IvaStxNAdCBMzApTRDN3qg2NBC9mDSMfZNn8eDdp/y/EjO5iw+QzWhdRzDM7s9KRuqy7cfDdq9mL3VS4d3kHjTr2JDFOSr0w9urp9Rz7rgrz1f8q2xVM4f/sxPcbMBSAo8DnPooyo1aEfEbvWce1JMHOP+qV6Hhr+XjiJO5dO8/XoeZjns2TXkt+p93lrBs/fLNXxfhqMk0tbFAVKEPDIL0Pt5jVtqthTwT7nVifkhP3H2rVrcXBwYP/+/Rw9elSy/xg0aFD2dAO0tCM81kBLN2LjE2i2+BbM68XwTWWwym+FsZECIwMFijx0GZK1KnPom3ZcOnIA/2hj2v08HZsi9jz29Wbk6F85de8NDTt8mzsXKZtYmhoxoEmpXD1Gjt+05IaHSNI5LUql+ikomcfB4/Pw+oX0MSxG219oimopc+K/Ytm7zxoPEYDdlx5kq98yuY8qNhr/4/ux7T4TgxIPWLh42Xv/kP9COTywu+QfsmvTWiyrtMD70LtJdkaVuPxQAG+BfMSVasKNK/t4cyjRJLyS7XgSD2+jFYQ+fsPjQ6lP0AP19+fFoe0Uav0zBwMsABVxdXoTuH4os9bswNRenWET5/Y8AZThd4gKjWJBOu3qAsXyqSMtMuMh0rRp0zTrKRQKpkyZwpQpU1Kto1KpEEJw4sQJ6bURpO09lBXtCEriPfRZ3BV2vvt5y7n7WvPiZPQD/dSOMlCyDE9eAC+CgZKYlmvMob27uGpSNYevUM5QNL8p3WsUSbPOJ+E9lNqyRTnkkCPvQ5e9h2TtkEMO3Qyd8R6aNGlSMlfVcuXKSU9C0dHR0tPU559/Tps2bVi6dCm2trap+hGMGTNGGk4GdcKgO3fuUKJEiU/GPwQ+rv7omvdQYr766isqVarEpEmTtLZ7e3szdOhQNm/ejL29Pbt27WLEiBH4+Pho9cXNzY369eszdqy2xfy8efM4cuQIR44cyeTV+nDklvdQTpBZzzKQtQPkvoD+aweoX7F+9dVXeHp60qRJkwz3/UOh195DlSpV0kqk9fr1a6n8hx9+ECVKlBDly5cXXbt2FfXq1RP169eXvYfkkENPIyNPTKdPnxZubm7C3t5eQHLvIZVKJcaPHy/s7OyEmZmZaN68ubh3755Wnbdv34pChQoJY2NjYW1tLfr27SuUSqXsPSSHHHoYOjPSAhlL45+QkIC7uzsTJ05k7NixdOrUiYiIiAz5smju4tLzHgL4fM4pXoWp32kv7F6Dz8sXzUKPZPKa3PYPSUzbtm2pUqWKlpdISpw+fZr27dvz5MkTrYSJlStXZuDAgclS9s+YMYMDBw7w77//pttffUCTLykjT7wRERFUq1aNvn37pphYb9asWSxcuJB169bh7OzM+PHjadmyJb6+vtITbY8ePbC0tCQ0NJRBgwaxceNGatasmWHdgNS148ANf0b/fTPd/T06V6FtVYcMHUtGN9B37bh79y5ubm706tWLCRMmZKjPukxmdCMlcuWm5f79+zg4OGBmZoaLiwszZszA0dGRq1evEhcXh6urKzY2Nrx+/ZrZs2cD6uGz1LyHMuofkpSAoDD89ixBCBUJ4UH8fNKcG6cPSKZssveQfvAh/EMSY2homOL2pDRu3BhjY2MuX75M586dAfDz8+PZs2da3kMaTE1NMTAw0HvPkKRkxEOkdevWtG7dOsUyIQR//PEH48aNo0OHDgCsX78eW1tbdu/eLRkmHj58mMuXL3PhwgVmz56Nv78/8fHx7Nu3L0OeZYnPNal2lLSPy5D3kEP/tR/d7+9jRt+14/bt27Rr147evXsza9asDJ2fvqAz3kMHDx4U27ZtE9evXxeHDx8WLi4uwtHRUYSGhopNmzYJExOTZPvUqVNHjBo1KtU2M+ofkpRrDwOS7XP/0XPpZ9l7SD/4EP4hQgjh7e0tvL29Ra1atcQ333wjvL29xe3bt6XyixcvinLlyonnz59L23744Qfh6OgoTpw4Ia5cuSJcXFyEi4uLVrv3798X3t7eYsCAAaJs2bLScWJiYrJyOXSGnPIeevjwoQCEt7e3Vr3GjRuLn376SQghxOrVq4WNjY1WeVxcnDA0NBQ7d+5M9VgZ9S2LT1CJetOPiZLpeA8pQ8My1VeZvEWftePmzZuiSJEi4ttvv9WabvHq1ausXg6dILveQ7m+eig4OFhYWVmJP//8M8s3LVk1TDzl+0LYNOopSrr2kkRnxdHrYurUqWLq1Kl6/5/Gp4Kbm5to06ZNimUXL14UgLh+/Xqq+584cUK4uLgIa2trYWZmJsqUKSNGjx6dzLgzpRtjJycnqfzkyZMCEI8ePZK2RUVFiR9//FEUKFBAWFhYiI4dO4qAgACtdps0aZJi24nb0Uc+JsNEIYQ4dNNflBy9XziO2CWs63eX6pb4abOwadRT9BoyWtYMPUOftSO1727idvURnb9pEUKI2rVri19//TXLLs9JyVCnE+LFvn+OC6fR+0XHmbukX/iXfxwTQqifrM4/eCN2ez8X5x+8EfEJqqx0TUbmk0Ufbloy+8Bz6Ka/qDf1sNZoS50Ju8Whm/4p1peRkckcOufynJTU0viD2jCxWLFiPH36lD///JNLly7lzEHfeQ8FnVInrSv4+oJUdPVJCJ7nHtHQ4wTdV13g5y0+dF91gYYeJ2QPIhmZPEAzmTGtpcx2dnaSv9CSJUsoWbIkpqamvH79WprjlhKZ9S1rZXCZ/abay01HKjbQyuBypvslIyOT8+T4TcuIESM4ffo0jx8/5vz583Ts2DHFNP4TJkzgl19+wdzcnOrVq9OgQYNUDRMzRSLvodeq/CREKjGNei0VCyEYv9WL5wEvtTLyyeaJMjJ5g64YJmq0Iy70tZb3kGdoHQLX9JS9h2RkdIBMrR6aMWMGO3fu5O7du5ibm1O/fn08PDwoV66cVOfJkye0adOGyMhIFAoFxYoVY//+/Vpp/CMiIvj9998B9dLDfv368ccff3DgwAHWrFnDr7/+mrXeJPEeehlnwfNFPViaqIppfCgPF6t9RUoM3YHiXUpujRSN33OLCvZWGOSBsYfsJSKjKxTMZ4KFSc4tLgwPD+fBg/dWGRrDxIIFC+Lo6CgZJpYpU0Za8pyeYWKfPn3o1q0bZ86cyZ5ugJZ2hMYZankPXY8rjv3iUJjbi4t3m1LAxgYTI4MPphGyLuQMVy9dpFMbV5o2b8G6rTuTlW/7awMAXb/pKW0LDnrLkO/7csf3FiFBQRQqXIQv2rgxetwk8r8btXsZGMDv48dww8ebx/89pO/3A5k0Y3a657PJcw27/97Gres+hIeHcevRC6ytbaTyZ0+fsGD2TM6fPc2rVy+xtbOn01fdGDJ8FCYmJtm8GrmDoYECe2vzXD1GplTp9OnTDBo0iDp16hAfH8/YsWP54osv8PX1JV8+tVFJ4cKFKVSoEPv27cPa2prBgwczbNgwzp07B4CxsTHXrl0D1BlCy5cvT69evbCxsUnVMDGr3kMvo5P/YmckLKDru58Tew9J+8RE0mjqwcxcFpkPSIz/PV5tH4+ZU3WKfDkmWXnE7VMA5KvUVNqWEBVG0OGFxL55iio6DENza8xL1ca6fndpmWtCRDAhZ9YT+/I/4kMCsazemgJNe6d7PiI+lpAz64m8dx6REIeZUzUKNPsOw3w2yeomRIXxctNIEsKDKPbDWgzM0jH3yUNmdalKmyr2adbJjIdIXhkmZkU7gqO1B6AVseHSz50WnpK9h/SUoH+WY1G1FSdPneCzURswtCwIQNi1/eSr3Jyo+2q/oHm+O4i4dZz8Nd1QRYcTKUpi0qw5hcytiA8JZNPfq9l+9haFWv8MQLzyFWEPwzEp1RKj0ANsvfiYo1MOpHs+YdeuICiBYbUScO4vWnoc1dKEqMc+RN57Sr5a31LQxo7IN89YuGQpq4/fxKZxr1y4QtmnaH5TToxommadPPUeevXqlQDE6dOnhRBChISECGNjY7F9+3apzp07dwQgvLy8hBDqJdEGBgYC3nuILFu2TFhZWYlhw4bJ3kNyyKFnIXsPySGHHJmNPMmIq3lqKVhQfceaOHmchvLly+Po6IiXlxf16tXDy8uL8uXL4+vrK9Vp2bIlAwcO5M2bNykeR/YPUfMx9ScrfYmIiKBWrVocOHCAuXPnUqFCBYYMGQLAtm3b2Lhxo/Sq0s/Pj2+//ZauXbum2NaaNWtYvnx5ipO/U/MPSUpoaCjVq1dn1qxZDB06FF9fX16+fEmzZs3Ys2cPNWvWlOquX7+effv28csvv9CtWzdu3bolZeLUJXTZeygryNoh9wVgy5YtbNiwgQMHDnDs2DEmTZrE2bNnpQRnL168oF27dgDs27ePYsWKpdhOYGAgQ4YMwd7enoULFyYrT007vLy86Nq1K+fPn6dEiRLJ+gNkSBNmzZrFqVOnOHhQ994G6Lz3UEJCgmjbtq1Wkp2M5GHp37+/cHV1FYaGhtKyx4iICAGI5s2bi/bt2yfbP+myRV9f3zy/S5RDDjnU8aG8hwICAoRCoRDm5uaS91BYWJjo1atXirqRErL3kBxy6EZ88JGWQYMGcevWrSz5qBgYGFCrVi2OHz8uTbQD8PHxkVLsJ2bGjBnJnKNB9g/51Pjiiy/o2LEjAwcOJD4+nrJly7Ju3ToaNWrE1q1bWblyJeXLlwfUfh3ff/89X3/9tbR/3759OXjwIFFRUbRu3RpPT88UnVpT8w+5evUqAwYMYO/evTg4OLB9+3Z+/PFHXr9+rVWvWbNmNGrUiClTphATE8Pnn3/OTz/9xNdff83Zs2dxc3NL5jmij3xo76E+ffpgbm5OmzZt+Pnnn+nTpw/9+/fn7NmzDB48OEPnLHsPfXrcv3+fevXqcffuXWlByIgRIwgNDWXlypUsXrwYd3d39u7dC0D79u1Zt26d1nfq5cuXKJVKHjx4wOTJk2nQoAHz5s1LdqyMeg8lJiOa4O/vT5s2bWjYsKG0ak5fyRPvocGDB7N//37OnDlD8eLFpe12dnbExsYSEhKidfGT5lu4dOkSY8aMwd3dndq1a+PgoBaBmJiYFI3Pkg7xajqdln9IWpS0LyL7h+gZfn5+XL16lb1790q/u27durFlyxbatm1LWFgYJ06c4O+//wZg6dKlrFq1Suv3vHjxYkJCQrh37x5jxoxh0qRJLF26NNmxUvMPadasGffu3ZM+azxIUvIf0eQHGTZsGJUqVaJ///4A0oT1jOQM0Rc+pPfQtGnTmDJlCm5ubowcOZIBAwZgZWWVYcPEjHgPpYWsHfrH1q1biY+P11rlKt4ZJq5YsYKxY9V5eTR/z8WKFZO2adD8zmvXrk3x4sVp1KgRv//+O/b22pPVM+o9lJj0NMHf35/27dvTsGFDPD0903ytqU98EO8hlUolBg0aJBwcHJIN3QrxfiLujh07pG13794VkHwi7suXL8WiRYuEo6OjMDQ0FIaGhuLMmTMZOo/UMuol9g9xHL5L5KviKgzzFxZmzjVFiZ+3CsuqX4iitVuLiMiozHRbRgcYOXKkAKTviqGhoTAwMBDm5uZaviJr164Va9euTbe9s2fPCkiehVUIddr9n3/+Od02MpLhuVq1asLAwEDrnDX9mDBhQrrH0GXyyntIoxvGxsYCEDNnzkz1WFnxHpK14+MhLi5O2Nrairlz54qbN29qRalSpcSyZcsy3ebp06cFpGzDkVHtSIwmxX9SHRFCiOfPn4syZcqIbt26ifj4+Eyfqy6S3Yy4mRppGTRoEH/99Rd79uwhf/78BAYGAmBtbY25ublW8riCBQtiZWXFkCFDcHFxoV69eoB6iL9ixYr07NmTWbNmUaZMGXr27Ml3331Ho0aNsnbn9Q5DAwUT21Vk4MZroEog4uYxABLC3qBKiCP8xlHCAaFKyNZxZD4s8fHxrF+/PlWn1s2bN0tOrb17985QmyqVeql74uWwmSVxhufETq1Pnz6VkqL9/fffREVFSftcvnyZvn37cvbsWUqVKpXlY39MaHQkqVOzra2tVBYYGEjRokUB9UivZui+aNGiaT7VpvZqOSmJtUMk0Q4ha4fesn//foKDg+nXr1+ySa6dO3dm9erVknakxMGDB3n58iV16tTB0tKS27dvM3LkSBo0aEDJkiWlej4+PoA6H9Hr16/x8fHBxMREmmR76dIlevXqxfHjx6VJvoGBgQQGBkr5i27evEn+/PlxdHSkYMGCvHjxgqZNm+Lk5MScOXO0XkPr8uT3XCczdzikMqEm8ZNtRgzkHj9+LFq3bi3Mzc1F4cKFxfDhw0VcXFyGzyO9O7VDN/1Fvcn7hUP9L6VzrD5mu+g1ZLRslKiH6LNTa1LSeqrSNz5W76G6k/ZpGSbW/k3WDn1Flw0TU1uOr/n/dO3atan+n6vP6IVhYmosXrxYODk5CVNTU1G3bl1x8eLFDO2Xbqdv7xGqueXFsBFDpF/y4vG9hbi9JwfPXuZDocvCk5Gb9MTINy3Zfz2k0Q0TExMBCA8Pj5w759t7RNDsGlqGif9O+VzWDhmZHEJvb1q2bNkiTExMxJo1a8Tt27dF//79hY2NjXj58mW6+6bZ6dt7hJhoLcREKzFk+M+S8LQeNkuoJljL4iMjk0Pk1E2LSqUSdnZ2Ys6cOVptm5qais2bNwshhJTmYPr06ZJurFy5UgDCysoqQ7qR7jm/046XE0po3bQMGzFYrSmydsjIZBudd3lOjXnz5tG/f3/69OlDxYoVWb58ORYWFqxZsybrjSbyDxFCoIyMk4puqpzxCP2CgO2jEAnx2e+ATJ7g5eWFoaEhbdu2TbHc09MTT09PrW1v376lVatWODg4YGpqSokSJRg8eLBWKveAgAC++eYbypYti4GBAb/88kuGzmflypU0bdoUKysrFAoFISEhyeqULFkShUKhFZlZEvkxEB4ejo+Pj/TuX+M99PTpUxQKheQ9tHfvXm7evEmvXr3S9R6aPXs23bp1w9LSMnu6AVraEScMtAwTd8Y3YEtoVV5tHyFrhx6TW9qxc+dOWrRoQZEi6pVlLi4uHDlyJN3zCQoKokePHlhZWWFjY0O/fv0ID39vGREdHU3v3r2pUqUKRkZGWulBPmUUQnx429LY2FgsLCzYsWOH1i/C3d2dkJAQ9uzZo1U/qX+IZsmzUqnUnoT36CyscwMgIlZgOeO9ZX2xwRt5sfhbAD7/fSfWBYtiZKi+Z1Pw3pRMgQKFQjYp01UurpuOkak5D//dj9vULVjYqPMu3P1nM6UatefZ1VMAlKjVlIdn91K+RXdiI0J5cvkYBUtWwCy/DWGvnnPlrzkUcCxHg/5TAAh/E8DdY1so6FgOv2NbKFq2BrW6DU33fO4e20JCXCwA13cuo8uCo5hYaOcf2PNrR/7XsB2lG3WQthmbWWBkmrvGYtlhULPS1C9VOM06oaGhWFtbJ/87TIFTp05peQ9p0HgPCSGYOHEiK1eulLyHli5dStmyZaW6gYGB0n8eJiYmWt5DKekGZE077kQXpqLHf1JRYu1oMXUn+QoUxcTQAEOD3BcJWYdyjtzSjqtb5mNuUwTbcjUxtsjPf+f2c/foX3wx9k8KOpZL7XQ4uWAoUSFvqdtzNKqEeC54TqVQyQpSu/ExUVzbvoiCjuV4du0khsamNB7kkbsXKZsUsDBh8Tc106yTGd1IiZyzcc0Eb968ISEhIcXVAnfv3k1WP7UVAMlMzwIfQYz6HiwiVvtebEj8RjQesH4B4Ri8lZ+Y9A1VbDT+F//BtvtMjJ2ec3LXX1jVVScqiwiO59a0gRgXUqfIvnZ4K5ZVWvD69jP1zkXqEBgBRMQDdhiU+5znV/dxVlMOUKULL4BI1d+8eBtOZOKy1LBvAED0s9sAeN15kcwIMTo2gWfBsYQ8j0y0NRJdpl2FAlQukraTbGaMz5o2bZpmPYVCwZQpU5gyZUqqdVQqFUIITpw4Ia3OgtR1A7KmHcEx2ncKneMOoknY7usfjsEbWTv0jVzVjipdiATeRqL+sy7nhsHFE5z/5yDW9VLO/RMX9JzAWxew7T6DO1Hq/7jN6vfiye4ZxFXtLJk5UqM7AYBS5YUIjdDWKx2kaH5TQkNLp1knTw0Ts0pmjc/kNP5yyKG7ocuGibJ2yCGHbsYHS+N/5swZZs+ezdWrVwkICGDXrl1ar3jEu2HeVatWERISQoMGDVi2bBllypSR6hgYGKBQKGjevLk0zLtgwYJUTZRMTU0xNTWVPltYWHDp0iVsbW0/GdMz+Lj6k5W+dOzYETc3N/r160d8fDy1atVi+fLluLi4sHPnTjw9PaXXCffu3aN3795aKeMHDRrE0aNHiY6OxtXVlWXLlqWYxj810zNvb2+GDh3K5s2btTJhpmd6tnLlSqpUqYKNjQ1XrlzBw8ODr776iokTJ2ao3x8SXTZMLFy4MIaGhrx8+VJre1rnIGuH3Bf4cNoBsGzZMpYsWcKpU6coXFj9ivXQoUN4eHhw6tQpABYtWsSOHTvYv3+/Vn+qV6/OsGHD6NWrl1abQ4cOJTQ0lNWrV2fmcn1QdNYw8eDBg+K3334TO3fuFJDc+GzmzJnC2tpa7N69W1y/fl20b99eODs7i6io95kkW7VqJSwsLESXLl3E2bNnRenSpUW3bt1EsWLFxIwZM9I9B9n0TA45dCdyYqQlpZwV5cqVk8o1S8sNDQ2FsbGx6NSpkwgMDBQJCQkZ1g1ZO+SQQ3ciq7qRrYm4CoVCa6RFCIGDgwPDhw+XjA+VSiW2trZ4enpKHiIVK1aUPERWrFhBTEyM5CFy7969ZHNdkqJUKrGxsUlmegZw6b8g+q67nO65r3GvQ93/Fcxax2U+OOPHj2fhwoUYGhpK28Q7/xA/Pz9pdGPTpk0A9OjRI832vLy8aNWqFX5+fsnu+HPL9EzDnTt3qFevHleuXNEagdQ3NJNaQ0JCko0uZZZJkyaxY8cOjh07Jm0zMjKSnlQHDhzIgQMHcHd3x8PDA0dHR6ysrKhTpw7btm3j7t276eoGpK0diem87Dx+geqJ/Kt61calVKFs9U8m7/hQ2rFjxw4GDx7MunXraNmyZZptbNiwgd9++42nT59K2+Lj4ylatCjr1q2jXbt2WvUHDhyIUqnkr7/+ylindZjs6kaOTsR99OgRgYGBuLq6Stusra357LPP8PLyolu3bnh5eWFjY8PYsWOxsrJiwoQJBAQEADB27NgMCU9qpmcAzarmp1jRhwS8DePN0SVEP/bBuLAjRdqPJvikemitYpdfaFbV6YPM/pfJPvHx8WzdujXVNP4HDhyQUnEPHDgwQ21qzNFSMjfLDdOzxDx48AADAwP+97//fRTme1k2PkuCkZFRikPGSqWS1atX89dff9GlSxdsbW2ZPn06Dx8+JCYmhsOHD2dINxKfa1q/p5iYGG7sWEhETBwJ4UEM+Tcfl4/tkx7EFi9erPXKSUZ3+VDasXnzZgYNGsSWLVsk08+0+Pzzz1Eqldy/f59atWoBcPToUVQqFc2aNUv23TQ2NsbIyOij0AsNH8QwMSnwYdJxZyUVt2Oi5FCAKDZ4o/TzrosPsthjmbxAl9P4BwQECG9vb7Fq1SoBiDNnzghvb2/x9u1bIYQQ58+fF/Pnzxc+Pj7i4cOHYuPGjaJIkSKiV69e2bkkOkF2k0QlZuLEicLCwkLY29sLZ2dn8c0334gnT54IITJmTJkamdUOIYQIDw9PNpQdGBgo/RweHp7t/sp8GD6EdmzatEkYGRmJJUuWiICAACkSH3Pnzp1arzuFUE+TqFGjhrh48aL4999/RZkyZUT37t216ty+fVt4e3uLdu3aiaZNm0oapc/kaUbcD3XTkppHQ1qd3nvtsSjc6BupbvGfNosSLfqIXkNGy/4heoYup/FPzz/k6tWr4rPPPpOOXaFCBTF9+nQRHR2d1cuhM+TkTcvBgwfFtm3bxPXr18Xhw4eFi4uLcHR0FKGhoWLTpk3CxMQk2T516tQRo0aNSrPdrGhHdHS0KNC4p5b/0MU7T8T3w8aKHoNGidO+/iI+QZXtPsvkPh9CO5o0aZLid8zd3V2qo/ERSszbt29F9+7dhaWlpbCyshJ9+vQRYWFhWnWcnJxSbFuf0ambltzyEMnK05JIiBc/L98j/ZK///OsLDQyMjlITt60JCU4OFhYWVmJP//8M9lNi0Y3FAqFsLe3T9OzLCvaERsbK5xG79dK5V9xzG7hNHq/FPWmHxOHbvqn2oaMjEzK6FQaf2dnZ+zs7Dh+/Li0LTQ0lIsXL0rJoFxcXAgJCWHGjBkMGzaMiRMnsnjxYgCmTZvGq1evkrVramoqvYPOyJwBfPfCH5VJuH9S2nT37i0Ud/blQC9lZGRyGxsbG8qWLcuDBw+ws7MjNjaWkJAQtm7dKumGnZ0dTk5OtGzZMkXdgKxpR8yCOsk2x0dHaH0OVEYzcOM1Dt8KyHIfZWRkMk+mb1p03kPEdy9s64VQviA0Mlba/F98YTauXsDrfzdkPROfjIzMByE8PJyHDx9ib29PrVq1MDY25vjx45JnWf369QkICGDu3LnZ9yzT8E47okNfkxCp1PIfihQmOET6kRCpRAiBRkEm7/MlQSXriYzMhyLTS54XLFiQopmcxkNEpVLRtGlTzp07h0qlokCBAmzZskVr5rZm2bOGMmXKcObMGUaPHp2qh0hiUvUuUCXAH5Uh1D9N76FFh65TqKANRgYKjA0N8tzfI6dWX3wK3L1+hTF9OlKjflMmLN6QrPz4nq0ANO/wtbQtNCSIeWOH8Pj+HcJCgrEuWIjPmrak55BfsbBUJ0Hy9b7Euj+m8eLxA2KioyliX4yWnb+lQ8/v0zyfMGUwK2eO5/KZfzBQGODi2obvRk3B3EK9mig2JpplU3/l4Z2bPHt0nzqNXBn7Rw78B5vL1HS0oXiBlFOQa8iuh0hiRowYQbt27XBycsLf35+JEyfi4+ODr68vRYoUYeDAgRw8eJDnz58za9Ys/v77bwDOnz+fqmdZps45kXY8iLGhzMynWvsl1o8SQ3dgYPI+sdiPTUtRzk79PZL/lnUXfdOO548fsGzqrzz77z6R4WEULGJL49Zf0m3AMIyMjXPqsuQoZkYGfFEp7aRxH9x7qGzZsvz222/UqlWLTp06JcuIO3v2bG7cuMHOnTtxdnZm/Pjx/PDDD/j6+koZBAcNGgTAqlWrKF++PH369GHYsGEUL148RQ+RpKZnSqX6CSiZf8jj8/D6BZDce6hJ3L9oVrjP3HddS3Rk9Iegf5ZjUbUV1y6eYODifZJHR9i1/eSr3Jyo+w8A+PvlMSJuHSd/TTdU0eFEmpbGxLUlRcytiA8J5OjR1ZzyuU+h1j8DEPvqEXH29clXtTuWRqZE+d9l7YKZ7PIJwLKKa6rn83rXdBIigingNgZUCZz6Zynn7/SR2lXFRRPyOAQTp8aYxJly4+lbBnuey+WrlH1mdalKmyr2adbJjIdIepm0nz17hpubm+Rya2try5YtWyhSRG1qN3/+fEJCQtiyZQsjRozA2NiYLl26EB4enqb3UFa04210cllM7F2miokEoZLKFh+5mW7/ZfIefdOOeOVLogtUx6x1RyxM8xH3+gl//7WCw9efYtPgm1y+WlmjaH5T6o1ommadPPUeIslEXJVKJezs7MTs2bOlbSEhIcLU1FRs3rxZCCG0vD80HiKHDh0SCoVCDBw4MEUPkdRWAMghhxx5HxnJbJkTmbSbNWsmALFq1Sopk3b37t3T9B6StUMOOXQzPpj3UFpkJrlcWFiY5CHi6uqKgYEBd+7cSTG51LBhw/juu++kz/Hx8Tx69IhSpUp9Mv4h8HH1Jyt92bJlCxs2bODAgQMcO3aMSZMmcfbsWWlI/sWLF1ImyX379lGsWLEU2wkMDGTIkCHY29uzcOHCFOvcunWLXr16MXLkSLp37w7Atm3bGD58OM+ePZPOZ+rUqXh5eUl9MTc3p3Tp0ixbtozWrVtrtfkx+YdA5jxEWrdunex6aBBC8McffzBu3DgpMdf69euxtbVl9+7dUibtkydPYmBgQOHChWnYsCGLFi2iTZs2dO7cOdVzGDNmDMOGDZM+x8fHc+fOHUqUKPHJaIfcF/3XDlD//9qvXz9atWrFqFGjMtz3D4XOeg8lBrKep6Vu3bpi8ODBUp0iRYoIa2vrFD1E5KclOeTQ3cjsExNkPVVCYt2Ii4sThoaGomDBgql6D8kuz3LIoZuhEyMtmWHYsGG4u7tTu3Zt6tatS1hYGAqFgj59+iSrm/RpSalU4ujomK5/yAavx3gc9gNgQbfqNK+QsVTfMrrH/fv3qVevHnfv3pXmOYwYMYLQ0FBWrlzJ4sWLcXd3Z+/evQC0b9+edevWMXjwYKmNly9folQqefDgAZMnT6ZBgwbMmzdP6ziPHz8mIiKCy5cvM2nSJObMmUOXLl1SPKc5c+awefNmrl69qrW9VKlSjBkzRmt0ED4u/xB47yGS3af3wMBAgGSp+G1tbaWywMBAihYtmkw3jI2NiYqKSlE3AGbMmMHkyZOTbU9POypPPAJAbacCePatm6V+yegG+q4dz58/Jzw8nFu3bjF+/HgGDBiQ4mIYfSG7upGjNy2a4Z6XL19ib/9+Et/Lly+pXr26VOfVq1d8/fXXvH79WvIeiouLY+bMmSl6iCS1l9eQXt6FGIUpBqbqFRBXA6Lp+NnH49vwqbF161bi4+MpV66ctE28Mz1bsWIFY8eOBd77ghQrVkzapkHzXalduzbFixenUaNG/P7771rf1apVqwLqfEKhoaF4eHjQt2/fFM+pZMmSvHnzRus7GB8fT3BwMM7Ozp+Efwh82BUziXUjMDAQlUrF0KFDU/UeSvrAoxHM9LRDoxvegTGceBiKrZU5dZ0Lyn5leoi+a4dmpW3dunUxMTHh+++/57ffftMygNRHsqobeZZc7urVqwwePJgnT56wf/9+FAoFPXv2zLFziYmJYfO8cbw5+Acvt01g2Zj+KJVK+vfvT//+/bVWFMjoNvHx8axfv565c+dKOYJ8fHy4fv06Dg4ObN68Warbu3dvevfunW6bKpV69Uda3wOVSpVmeeLvsoYTJ06gUqn47LPPMtAzGdB+2ElM4vfemocdQNKNiIgIhBCStqREppPLAVFR0bw5+AfPl/YmcNsEflp3ni86fYPDZ23Ze+1xFnspkxd8bNqhUqmIi4uTzuGTJLPvk8LCwiTTJkDMmzdPeHt7S+ZmM2fOFDY2NmLPnj3ixo0bokOHDslWAWTEKCotMpIGOCXTs/Unrks/K0PDUt1XRrf4EKZnixcvFnv37hX37t0T9+7dE3/++afInz+/+O2336Q6sumZNllNxw0przqcM2eOVtsprTq8cuWKVOfIkSNCoVCIFy9e5Og5b/O6p6Ubic1WHYfukNP36xH6rB0bN24UW7duFb6+vuLhw4di69atwsHBQfTo0SOrl0Mn+ODeQxrTuKShMYdSqVRi/PjxwtbWVpiamormzZsLPz8/rTYyYhSVFhnpdExUpGjS2V3L9Kz4T5uFTaOewqZRT1F3yiFZfPSED2F6tnDhQlGpUiVhYWEhrKysRI0aNcTSpUtFQkKCVEc2PdMmM+KjCw87GTnn+ASVqDtpXxLd+EvSDacRu0S96cdkHzM9QZ+1Y8uWLaJmzZrC0tJS5MuXT1SsWFFMnz5d629CH8nuTUumM+LmJEuWLGH27NkEBgZSrVo1Fi1aRN266U96Szejnu9eODya0W/bsjnKhWfz1ZOhKg9dS5iJeiKW5m3asm9r0qpy2km0ZGRkkpOZzJanTp2iWbNmybZrMmkLIZg4cSIrV64kJCSEhg0bsnTpUsqWLSvVDQoKYvDgwezcuZPY2FgUCgU1atRg6dKlGdKNjJyz38lNiJPT+SJ8iqQb5YZupIHpA46L2lK9zf3r4VKqUIaOKSMj857sZsTN0TktmSGx8dm1a9eoVq1amsZnGeadfwih/sQlWRylJD+1FerMmZo7Ndk7REYm92natKnasydJeHp6AupJeVOmTCEwMJDo6GiOHTumdcMCULBgQTp06IAQgtWrV3Pz5k1q1qyZM7oB4LuXsqcHUYAwrc2RmFHT4D4tDS5J216FRWf/eDIyMpkmz25aNMZnffr0oWLFiixfvjz7xmeqBDg8GlALYkhkjJbpmRCCOxFWqCKDJdOzAGU0lx4FZbs/Mh8GLy8vDA0Nadu2bYrlnp6e0n+EGt6+fUurVq1wcHDA1NSUEiVKMHjwYK1U7v/++y8NGjSgUKFCmJubU758eebPn5/u+UybNo369etjYWGBjY1NinUuX75M8+bNsbGxoUCBArRs2ZLr169nuM8y78kV3QAt7YjDMJluzA37AvvIByASACiaX7YB0TdySzsSc+7cOYyMjKTVsmkRFBREjx49sLKywsbGhn79+kk2FqAenezQoQP29vbky5eP6tWrs2nTpgz392MlT14PxcbGYmFhwY4dO7T8R1IzPkvqH6JZtphseOnRWVjnBpDMMBHgiyFTObpoHKBtemagACMDtXGigWx4ptME7P8DAxMzlD5HcR64CuP86iH6oIu7sK7ekrC7al+f/OUboPQ5QsHPOpIQFUao72nM7MtiZGFNbLA/Lw8vxcyuNA4dRwMQHfiA2DfPMbV1RmFsRtSz2wQeXIhti++xqdkm1fN5fXoDhmaWxIW+QelzhLIjd2iVq2KjeLDInfxl6lGwQVcUqgRen95A5DNfyvy8HoVhnqVKSpM5X1XLkPdQThkmZoTM6gZkTTt8o4tQyeOhVNTvp59Y/S77qUY3DN5phUKhHiUyUIACWTt0mdzSDg0J0eE8/nMIJgUdiI8Iwbn/kjTP59nm8cSHB2HXZggiIZ6AffMxdygrtfvm3y2I+FjylaqNUT4bwh9c4tU/qyjedQKWZXRzdaKdtRknM+A99EENE3OCN2/ekJCQkGIyqZSMz1JLEJXsbjfwEcSo78GSGiYCzFPNofK7nxObnqmA+Mx3Q+YDo4qNJvT2aWy7z8Q05DVvLu/Hqm4nAOIx4smGXzEuVAKAoMv7sKzSgohw9Y2rSbkmqIBYgCKlsajsStjVfVI5lrYYWtpK3wMj5zqYOVYj9D8fjMs2SvWcLGp9qT7+7VMIId63947Ylw9RRYVhUacj8abW6n1qdyTs7jlC/B9hbJPFVNa5TGhoKKGh+dKtA2Td+CyTZFY3IGvaERyjffMxKmENGuMFEROOSqj4hBec6iW5qh3veHPwD8zL1geFAbGhl5OVJyYu6DkRD69g230GKmu1ZYB1k9682T0DS5duGFoWxLy6ekRIAHGAacXmmN27RPDNUyjsK+bg1ck5whSxqY5CachTw8Ss8uLFCwHvDRM1pGZ8JqfilkMO3Y2spuPObd0QQtYOOeTQ1fhgafzTs5gX71YBrFq1ipCQEBo0aMCyZcsoU6aMVMfAwACFQkHz5s0xMTGhc+fOLFiwIFUTpaQZcS0sLLh06RK2trafjOkZfFz9yUpfOnbsiJubG/369SM+Pp5atWqxfPlyXFxc2LlzJ56entLkzXv37tG7d286deok7T9o0CCOHj1KdHQ0rq6uLFu2DDMz7bkJderUISgoiPj4eIYOHaqVLvvQoUN4eHhw6tSpFPuSP39+fH19k5333bt3+e677ySzNGdnZzZu3Ejx4sUz1O8PSW4ZJuaFboCsHSD3BXJXOx49ekSnTp34+++/+d///se8efM4cuQIR44ckfZPqh2LFi1ix44d7N+/X6s/1atXZ9iwYfTq1StZH/bt28cvv/zCwYMHtbL76go6a5iYExbzrVq1EhYWFqJLly6SxXy3bt1EsWLFUjU+S8yzZ8/y/C5RDjnkUEdGnph0QTdk7ZBDDt2JrI60ZGsirkKh0HpiEkLg4ODA8OHDGTFiBKA2N7S1tcXT01OymK9YsSLTpk1jypQprFixgpiYGAYMGICVlRX37t1L1UdEg1KpxMbGJkXTs0v/BdF33eV0z32Nex3q/q9g1jou88EZP348Cxcu1PLbEO/8Q/z8/LC2tgaQZtf36NEjzfa8vLxo1aoVfn5+qd7xz549my1btiQzNUuJTZs2MWbMGJ4+faq1ff369UyZMoV79+5JT/axsbE4OTmxaNGiVA3V9AHNpNaQkBDp+meEvNINTbspaYesGx8vuakdZmZmODk5abWtUqkQQmBoaMiuXbto0qRJsjY2bNjAb7/9pqUX8fHxFC1alHXr1tGuXTtp+7///kvXrl2ZNm1aqsag+kRWdUNDjk7EffToEYGBgbi6ukrbrK2t+eyzz/Dy8qJbt254eXlhY2PD2LFjsbKykgwTAcaOHZsh4dEYLaXkJdKsan6KFX1IwNsw3hxdQvRjH4wLO1Kk/WiCT6qn01Xs8gvNqjrJ5md6Qnx8PFu3bmXu3Ll88cUXWmVffvklBw4c4IcffgDUTsoZQWOOZmJikuoMdmNjY+Li4jI0w13TXtK6GvGytraWvrfx8fEoFArMzMw+CvPE7Bom5qZuJF09FBamnhyZVDsiCJNMEkV8HG9T0Y6Q7rU+it/Zp0Jua0fx4sW5efOmVvnSpUs5ceIEO3bswNnZmXz5kk9o//zzz1Eqldy/f59atWoBcPToUVQqFc2aNZO+Y6dOnaJr1654eHgwaNCgzHVex8mqbuToTUtmLOZBbXymsf8uWrRoqmKQ0rLF1DA0UDCxXUUGrDlPxM1jACSEvUGVEEf4jaMAjFm1VL5h0SP2799PcHAw/fr1S3Zn3rlzZ1avXi0JT0ocPHiQly9fUqdOHSwtLbl9+zYjR46kQYMGlCxZElBnZ3Z0dKR8+fKAeg7GnDlz+Omnn6R2du3axZgxY7RWqjx9+pSgoCCePn1KQkICPj4+AJQuXRpLS0tatGjByJEjGTRoEEOGDEGlUjFz5kyMjIxSzBD7KZJbugGprx5KSuK8K0KVkKp2FDTXzSXqMinzIbSjcuXKWvsULVoUMzMzre1JtaNChQq0atWK/v37s3z5cuLi4hg8eDDdunXDwcEBgJMnT+Lm5sbPP/9M586dpb8FExMTChb8dEf78iy5XGaYMWMG1tbWUpQoUSLN+q0q27P42xo4NuoobTMwMKBEiz70GjKaNtXT3l9Gt1i9ejWurq4pDiV27tyZK1eucOPGjVT3Nzc3Z9WqVTRs2JAKFSowdOhQ2rdvz/79+6U6KpWKMWPGUL16dWrXrs2SJUvw8PBgypQpUh2lUomfn59W2xMmTKBGjRpMnDiR8PBwatSoQY0aNbhy5QoA5cuXZ9++fdy4cQMXFxcaNWqEv78/hw8f1rK1l8kdxowZg1KplEIzGTopdZ0LYm9thgIwMFRgXb+7VGZgYIBNo56UaNEHlzLpjwTL6A4fQjsyQkrasWnTJsqXL0/z5s1p06YNDRs2ZOXKlVL5unXriIyMZMaMGdjb20uReILwJ0mWZsK8A7Qn1D18+FAAyRxsGzduLH766SchhBCrV68WNjY2Qgi1O6aTk5MwMTERgPDw8EjxOEmXLWom06VquHR7jxBzy4ufR/wkTfr56ddRIv7W7ux0V0ZGJhE55fKcW7qR2XM+dNNfDBgzQdwZX0GUGLpD0o7No1zFgDETZINVGZkcILuGiTk60uLs7IydnR3Hjx+XtoWGhnLx4kVcXFwAcHFxISQkhBkzZkjeQ4sXLwbUKdFT8hAxNTWV3kGnNI9Fi0TeQwni/eSoUzHlidv2nbpcRkZGZ8gt3cgsrQwus8xkAQUU2knBzqsqscxkAa0M0p+oKyMjk7tk+qYlPDwcHx8f6d39o0eP8PHx4enTpygUCn755RemTp3K3r17uXnzJr169cLBwUFaKaB5lzd16lTat29P2bJlmT17Nt26dcPS0jJHvYeUkbFSUZDIz+/KNrzaPgKRIOe/lZH5kOi0boCkHQoE8ULbe2hvvAuHw0rxeoesHfpMVryHEpdVrVoVMzMzihYtmmxSrBCCOXPmULZsWUxNTSlWrBjTpk1L83yEEEyYMAF7e3vMzc1xdXXl/v37WnUy4m32qZHpJc85YTEfGBgoGVBpkkQtXLiQQYMG5Zr3ULHBG3mx+FsA+i3YTQH7khgbGWBsoMj26geZD8ezuz6sHdOL0jUa8M2EZcnKfY7vBqB68y+lbZGhIeycN5qXj+8RFRZCPuuClPvsc5r3/BlTC0upXnxcLKe3LOPm6f2EB7/BsmARmnz9AzVcU3+HHB8bw5E1s7n97yHi42IpXaMBbX4Yh6VNYanOoZXTeXbXh1dP7lO4xP/44Y+/s38hcpkutYpTuVjayxEz4yGSF7oBWdOOu9GFqeDxn1SUWDt+WLyb/LYlMTY0wEjWDr1i76IJmJhb4P3PTgYv3U/+QuqJ3V571lOzRWfueP0DQAWXFlz7529cOvR6V74Or93raNF7OMXKViEuJoqQl/6U++z99/nQyuk89PGihfswipYsQ1SYkqhwJaWq10/1fP79ezX//v0nX/48jQK2xTi5aTEvn9xn0OI9GJmoEyKe/GsxZvmsCH37Eu9jO/n1L6/cujw5gpWZEcO+SDvx3Qf3HtJYzKeGxmI+8QTGpGjWsZ84cUIa/oXc9R4aEr+RX9/9fNgvFINH91I9PxndJeifNeSr2ooHN06wat+/GFqqZ9GHXdtPvsrNibrvD8CV+KtE3DpO/ppuqKLDibSpQL5WbuQ3tyI+JBDvk6u5/fAphVr/LLX9eu8sVJFKrBv1o6i1HQkRIVx4qcL7ZPIst9L5HF9F9ONrFPziZwxMLHh4cjWLfh2A7de/S3WCXwRh5FgPU5PCBL1+wpo02tMVyhcywjF/2v8hZ8ZDJC90A7KmHUFJvIc+jzvLhnc/7/MNxeCBrB36hio2Gv/TB7HtPhNDx/9Y/edKyXso4lk4p4Z+K3kPHdq2DssqLbhz0hdVdDj+6xdQuP1oLqucuXxX48Jsy7l3f8dxQc8JPLQVu2/nci7SFnxDAQVgw+lU/taFEPjvWEv+Wh04H2kHjxJQ1XIn5Gp/lq9Zj0W5BuqK9p+/O8dTxMYl6Lx2FM1vynf10jdahYzpRopke1ZNFpC9h+SQ4+MJ2XtIDjnkyGx8MO+hnKBw4cIYGhry8uVLre2y91DafEz9yUpftmzZwoYNGzhw4ADHjh1j0qRJnD17Vhqif/HihZRJct++fRQrVizFdgIDAxkyZAj29vYsXLgQUCcoe/ToEVWrVuXvv//GwsKCFi1aMGLECCmZlJeXF127duX8+fOUKFGCc+fO0a1bNy5cuEC9evWkvtSrV49+/frRv39/reOm5Emia8jeQ5m/DrqO3Jesew8tWbKEuXPn4ujoyKRJk7CysmL27NkEBARw9OhRTExMGDNmDNu3b6dixYr89ttvqFQqJk+ejLW1NVu3bgUgICCA7t27M3/+fCklQseOHTl9+jRNmjSR+qNJcLdsmfar723btjF58mRu376dQ1cy59FZ76HTp08LNzc3YW9vLyC5h4hKpRLjx48XdnZ2wszMTDRv3lzcu3dPq87bt29FoUKFhLGxsbC2thZ9+/YVSqVS9h6SQw49DNl7SA455MhsfDDvoUOHDnHu3Dlq1apFp06dkj0xeXh4MGPGDNatW4ezszPjx4/n5s2b+Pr6Sq6YrVu35s6dO/j7+zNy5Eg2btyIsbExb9++5e7du7L3kEwy7t+/T7169bh79y5FihQBYMSIEYSGhrJy5UoWL16Mu7s7e/eql7S3b9+edevWSZlTQT2Sp1QqefDgAZMnT6ZBgwbMmzcPUKf09vLy4t69e1Iiqr1799KrVy8CAgKk0ZbEbN++nR9//JHXr19rbW/WrBmNGjVKNj9jxowZHDhwgH///TfnLkwe8jF5D2n4xzeQYVuvk1QUNbNc5n1djRYVs/iEKJMnZMd7aOPGjQwaNAhfX1+tkdvSpUszbtw4evfuzfTp05k7dy5v376VyqOiorCzs2PXrl18/vnnyc7p0aNHVK9enbNnz1K1alVpe5s2bahSpQoeHh5a9VPzNtNHsus9lKPJ5VQqlbCzsxOzZ8+WtoWEhAhTU1OxefNmIYSQ3ilfvnxZLFq0SDg6OgojIyMBiH379mXouGklp4lPUIl6048Jp+G7RL4qrsIwf2Fh5lxTlPh5q7Cs+oWwrPqFqDvloIhPUGWn6zIfmJEjRwpAGBoaSmFgYCDMzc1FSEiIVG/t2rVi7dq16bZ39uxZAQh/f3XCsF69eolSpUpp1dF8V5OOFGo4fvy4AERwcLDWdkdHRzFv3rxk9SdOnCiqVauW7rnpC3mVXE6jG8bGxgIQM2fOTPVYmUlMqdEOR1k7Phri4uKEra2tmDt3rrh586ZWlCpVSixbtizN/f38/AQgjh07Jm17+/atMDAwEEeOHBFCCHHkyBEBiAcPHkh1fHx8BCD8/PxSbFfzf+WcOXOkbUqlUuv/ysSsXbtWWFtbZ6brOotOJZdLz/gMkIzPateuzeDBg3ny5AlRUVEYGhoSFxeXYrsxMTGEhoZqRWpovIc0/iEJYW+IfnRN8g8Jv3GUMS3Lyt5DekR8fDzr169n7ty5Uq4PHx8frl+/joODA5s3b5bq9u7dm969e6fbpkqlApCWwzZo0AB/f3/Cw8OlOhpn5uLFi6fYRq1atTA2NtZKiubn58fTp0+1VrfIpE1WvIeePHlCbGwsRYoUSdd7KKMWIJceBRGgjE5TOwKCI7n0KCi7XZb5QCT2HqpcubJWaLyH0qJs2bJ06NCBn3/+mfPnz3Pr1i3c3d0pX768tITf1dWVmjVr0rdvX7y9vbl69SoDBgygRYsW0jyZFy9eUL58eS5dugSQodxEoPY20+Qz0nib+fj4aOnUp0aO3rRkVnw0GBkZAxAuQAAAP6FJREFUUbBgQalOUrLkPdSzNoUbfSNtUxgYyt5Dekp2hefgwYOsXbuWW7du8fjxY8nZNbHp2TfffEOhQoXo06cPvr6+nDlzhpEjR9K3b1/p1dClS5coX748L168ANQ35P369WPYsGGcPHmSq1ev0qdPH1xcXKhXr550/AcPHuDj40NgYCBRUVGS8MTGxiY7V5mcJaPeQwCvwqIBUBgaankPKQwMsWnUE5tGPVEYGkr1ZHSf7HoPAaxfv57PPvuMtm3b0qRJE4yNjTl8+DDGxsaAeoL4vn37KFy4MI0bN6Zt27ZUqFCBLVu2SG3ExcXh5+dHZGSktG3UqFEMGTKE77//njp16hAeHs7hw4elaRSQvrfZJ0l2hnlIMsx77tw5rSF3DV999ZXo2rWrEEKIadOmibJlyyZrq0iRImLp0qUpHifT3kNCCJEQL4Yu3yNN+vllw3l5WFdPcXNzE23atEmx7OLFiwIQ169fT3X/EydOCBcXF2FtbS3MzMxEmTJlxOjRo5O91rlz545wdXUV5ubmonjx4mLYsGEiMjJSKj958qQAxKNHj6RtUVFR4scffxQFChQQFhYWomPHjiIgIECr3SZNmqQ4ES1xO/pIXr0e0hAXFycMDQ3Fzp07c+Sczz94I5xG7xclR+/V8h5yHLpNOI3eL8X5B28y3lkZGRktsvt6KEeXPGuWML18+VLLwfbly5dUr15dqqPxCVmyZIm0fCw2NpawsLBkbULyZYvp4rsXDo8mIaCltOnRzfMY3n0NFdtnslcyec2+fftSLatbt266SYqaNWvG+fPn0z1O+fLl+eeff1ItTylBmpmZGUuWLGHJkiWp7nfq1Kl0j/0pk9h7SKMTGu8hzRJQjffQ1atXuXDhArNnz8bf35+EhARMTExy5DzqOhekm6UPvWI30yr2fUK6Lw3/JdrAhqOquthZm1HXWZ7ALyOTV+iFYWKmeGeYKJQvCI14P/x+NdaJf1ZP5PW/G7KeiU9GRiZL5JT3UJcuXfjll1/45ptvcHBwoFSpUnz77bc5YphoeHcfM+JnYyNCtbyHjsTXZkjMahpHn2SCWwV5PpyMTB6S6ZGW8PBwHjx4IH3WiE/BggVxdHSUxKdMmTLSkuf0jM/69OlDt27dOHPmDGvWrOHXX39N5ejpkMgwMTIOPBMl6BHxMXyx2Afm9eLg1QYULWSDkYEBRoYKDPLYP0S2L8k43lcu8W2HljRs5sqKjduTle/aql622PHrHimWea5YwuP/HmBpmZ+W7b5kwoy5UrkQgrXLF7Ftoyf+z59RoGAhurv344dfRqZ6PkIIFs2ezvZN6wgLVVKjzmdMnDmfkv8rBcCLZ09YOn8WF/89w5vXryhqa0e7zl8z4OcROTZCkBvYW5tjbW6cY+1duXJFy3to2LBhwHvvoVGjRhEREcH3338veQ8lfb+/adMmypQpg0KhYMmSJXTu3Jk//viDChUqZE83QMswMTzeEP8V/aSi8HgDqix+AczlG/cfufI4CBMjAwwNFCjI+B9vZv7OZU3IefRNOwB+dO/G3Vs3efv2NVbWNrg0asqIcZMpapd2qvy8wshAQemiuZvAUC8NE5VKJY6OjslzLTw+D5u7AmrvIYd572dYNx4wgTMr1Hkziv24HgOT92Iooz8E/bMchbEZEbdPYO/+RwreQxcBMC/zmeQ9pCkPu7oP60Y9MbUrjSouhoTQ15iXqi21HXxqDdFPbmDT8FuMCzuiig5HFR2OmVPV5CfyjtDLuwm9vJtCLQdhaFUUpddW4t48xb7XPBRGJkQ99iHy3nnylWuAkY0dcW+eEXR8BfnKN8Kmca9cvFLZY1aXqrSpkr6HSLbyLWSS2NhYLCws2LFjh9YKC3d39wwbJmZEO+5EF6HeH+8NE6t+P4sbK0cBsnboM/qmHZpjm9iXxTBfARLCgwg5q3bBsv16aq5co+xSNL8pJ0Y0TbNOnuZpySqZ9RCZOHFinmfvk0MOOVIOXfYekrVDDjl0M/TKeyizjBkzRhpOBnXejjt37lCiRIlPxj8EPq7+fEjvoX379jF06FBmzpzJkiVLCA8Pp3bt2tKrS1B7fWzZsoVvvvmGdevWIYSgYcOGjB07lgIFCgDw7Nkz6tevz7Zt23BxceHJkyc0bNiQv//+m86dO0t96dKlC5UqVUrRXRhg1qxZnDp1ioMHD2brGuYGueU9lFfI2iH3BT4O7QgODmbs2LG8fPmSnTt3Zus65gYftfdQQECAUCgUwtzcXPIeCgsLE7169RLt27dP9xxk/xA55NCd+FAjLTExMcLQ0DCZ5mRUN4SQtUMOOXQlPthIS0REBNWqVaNv37506tQpWfmsWbNYuHChlvdQy5YttbyH+vTpg7m5OW3atOHnn3+mT58+9O/fn7Nnz2p5xaSG5i5O9h76dMiO99CcOXP4/fff2blzJ82bNwfgzZs3lClThu3bt+Pq6spPP/3EunXruHr1KqVLlwbAx8eHJk2acOXKFS23YQ0XL17kiy++wM/PT+upwd3dHYVCgaenp1Z9f39/2rRpQ8OGDaUVc/qM5t10Rp54c8LlOTw8HBsbG7p27YqFhQWdO3dm/vz5HD9+PEO6Aalrx4Eb/oz++2a6+3t0rkLbqg4ZOpaMbqDv2vH27VuCg4N5+vQpHh4eWFlZsW3bNmmUSN/IjG6kRKZvWlq3bk3r1q1TLBNC8McffzBu3Dg6dOgAqLMJ2trasnv3bsn47PDhw5LxmZubGyNHjpSMz/r06ZPuOWh+WVZWVsluWiIIw8DUIt02IjBOM/23jG6xdetW4uPjKVeunLRNvDM9W7FiBWPHjgWQstcWK1ZM2ubs7AxAnTp1pN+5lZUVhQsX5u3bt1hZWeHk5ISRkRE1a9aU2q9Tpw4AQUFBKX5XSpVSz/KPjIzUKg8KCqJ69epa2/z9/Wnfvj0NGzbE09MzzVcT+kZGxDMnHnZ69OiBpaUloaGhDBo0iI0bN1KzZk0iIiIypBuJzzWpdpS0j8uQbpS0T9s2QEb30HftsLKywtnZmZo1a1K7dm1KlCiBr6+v3luFZPmmK0vjM++AD2N8lpmMuJqslmmZnjkO3yVntdQj9N307Pnz56JMmTKiW7duIj4+PkvXQBfJqYy4H8poNa1z1pgllkxDO4rWbi0iIqMy1VeZvEXftSMpT548EYA4efJkRrqvk2Q3I65epPFPbQVAmk6tidJwA6LY4I3Sz3Um7ZNT+usRu3btEiYmJlpuzhpGjRolateunW4bHTp0EJUqVRLnzp0TN2/eFG5ubqJixYoiNjZWCCFEQkKCqFmzpmjcuLG4du2auHLlivjss89EixYtpDaeP38uypUrJy5evChtmzlzprCxsRF79uwRN27cEB06dBDOzs4iKipK2qd06dKiefPm4vnz5yIgIEAKfUcf0vhn5oHn0E1/UXL0fq0U/oAonkg7wsPDM9VXmbxFn7XjwoULYtGiRcLb21s8fvxYHD9+XNSvX1+UKlVKREdHZ/fS5Bk65fKcW2TG9Ezj8mxoqMC+/pfSdgMDA8n0bHz7KnJWSz1Cn03P/vnnHx48eMDx48cpXrw49vb2UsioyS2jVcic2WqryvYs+7YmDtamWoaJ9jZm9BoymqlTp0rfFxn9QJ+1w8LCQppLU65cOfr160fVqlU5ffp05mxtPjayc8dENp+YFi9eLJycnISJiYkAhIeHR4aOm+6d2u09InJmWfHTiJ+kJ6Q2wzzE6N+nikM3/VPeR0ZGJlPk1EhLZkdoNbphamoqjIyMxKhRo1I9VqbNVm/vESGzq2uNtjydVk2I23sy1UcZGZmU0amRFl3yHjKPCiQ+0eKo28KZ72I30sog/ZVFMjIyH47ERquJSZzLQWO0unXrVkk3Ll26REJCAosXL05VN0xNTaVJtylN3NfinXbEhb3R2nwoxBm29VKXy8jI5CmZvmnJKeOzxN5Ds2fPplu3blhaWrJmzZqs9yaR95AQgtDI94aJCULBz8pvuL71d0RCfNaPIZOneHl5YWhoSNu2bVMs9/T0TLbUOHFZ1apVMTMzo2jRogwaNEir/MiRI9SrV4/8+fNTpEgROnfuzOPHj9M8HyEEEyZMwN7eHnNzc1xdXbl//75WnWnTplG/fn0sLCywsbHJaFc/GTLzsPP777/Tv39/+vTpI70Wyp8/f/Z0A7S0I0YYahkmLoxrz5Gw//Fq+whZO/QYfdOOx48f069fP5ydnTE3N6dUqVJMnDiR2NjYNFr9+NFL7yHNOm+lUqn95PToLKxT+0VExAosZ4RJRRUGr+TO4u8BqDrmbwoXKoixodr0TG18JqMP+Pw1EyNTC5547af5+L8wsy4MwMMTW3Gq3w5/n1MAOFRvypPz+yj1+dfvyrfw8MRWKn75IwWcKhIfG0VUUCB2VRoCEPHGn5PTelKqWVccXdyIiw7n9s5FxEdH0mR06v8h3v9nE/f/2UiNb8diUcgevwOrCfV/SLPfNmBorH7vfPfAaozNLYkKec3TCwdoM+tQLl6hnGH4F+VoXLZImnVCQ0OxtrZO/neYAomNVmvUqMG8efNo1qyZZLTq4eHBzJkztZY837hxQ2vJc8uWLTl69CgeHh40aNCAPn36ULt2bYyNjTPsPZQR7bgTXZiKHu+9h4oN3siLxd8C0GjSTiysC6FQKDBQqI0NDRSyfugD+qYdr3wv8uLacYrVciVfkeKEBfyHz+ZZlKjTkkodB6Xabl5SyNKUNb3rpFknM7qREpnO09K0aVPSus+ZPHkyv//+u/T5+PHjtG/fnrt37wIQHR3Nr7/+ihAChUKBq6srM2bMwNLSEltbW6leYmbMmJFiWuPQ0FDtDYGPIEZ9bhGx2uc4XzWLVu9+fquMIDgqISPdldEhVLHR+F85jm33mZj4v+Diwa1Y1VXn/IgIV3F/7mCMC6knWvoe34FllRaEPgxAFR2O/75VFG4/mtcFKvM6FCAfWJQi4GEAAJH3L6JSJRBV0Y17oQaAFYqKLVHunc21e89QGCb/UxFC4H9sC/lrf0lgvtIQDYYNvyNyZX8u/LMPi3IN1BXLtyEKiAg/RUKCCu93x9Rl/F8XIdQu7cl+mr+/jDz35ITL87x586hcuTKTJ0/GyMhIetiZMmVKiroBWdOO4BjtW5CWcafQ/Nfz36twDELk0RZ9Qy+1w9QRXPrwAkAJWJTCvFpbHl85SmzV5LmOdIGi+U2T/20lITO6kSI5MK9Gi4kTJ4pKlSppLe18/fq1VP7DDz8IBwcHAYg1a9aIevXqifr16wshUjc+SzqZTpOzQQ455Mj70GXDRFk75JBDN0OnDBONjIxSNENSKpWsXr2a9evX8+2331KgQAHWrl1LhQoVuHDhQqomSqamplpLvCwsLLh06RK2trafjOkZfFz9yUpfOnbsiJubG/369SM+Pp5atWqxfPlyXFxc2LlzJ56entJryHv37tG7d286derEkiVLmDt3Lo6OjkyaNAkrKytmz55NQEAAR48excREbQPv5eXFjz/+SHBwMAkJCdSqVYt169ZJyyUDAgLo3r078+fPp0aNGly5coWOHTty+vRpmjRpIvVl4MCBgNpILTHbtm1j8uTJ3L59O6cuY46jy4aJhQsXxtDQMM0Ju0mRtUPuC+i/doB6/mjbtm0ZN24c33zzTXYvZY6js4aJ6TFx4kRhYWEh7O3thbOzs/jmm2/EkydPhBBCHD9+XAAiODhY1K1bVwwePFgIIYSjo6OYO3euKFasmJgxY0a6x5BNz+SQQ3ciJ0ZaUkogWa5cOak8KipK/Pjjj8LQ0FAYGxuLTp06icDAQJGQkJBh3ZC1Qw45dCd0ZqTls88+w9PTk3LlyhEQEMDkyZNp1KgRt27dIjAwEBMTE2xsbBg2bBju7u7Url0ba2tr1q9fn6qHSNLJdOLdu7CUDBOTMubvG+y7oX736GBjxuGfG2MgJ5bTO8aPH8/ChQsxNDSUtol3/iF+fn7SE82mTZsAtU+Nho0bNzJo0CB8fX0ly3mA0qVLM27cOHr37s3UqVM5duwYp06dkspfvHhBxYoVOXbsmOQlkphHjx5RvXp1zp49S9WqVaXtbdq0oUqVKnh4eGjV37RpE2PGjOHp06fZuxg6QnaNz5JSqVIljh07Jn02MnovT0OHDuXAgQOMGTMGDw8Prl+/TuvWralTp06mvIfSMltNTLcVXtzyV797/7NXbeqVKpSVLsnoAPquHQEBAbRt25Y6deqwbNkyvfcty7ZuZOlWJxMEBwcLKysr8eeff4pNmzYJExMTqUzjIaJQKIS9vb24cOFCim1kJo1/YqKjo4XDZ21Fviquwsy5pjD/X21xyve5iI6OFt9995347rvv9Dod8qfCh/APGTZsWLJ5Ef7+/gIQ586dS7HdzPqHrF27VlhbW2e02zpPdpNEJWbixImiWrVqKZaFhIQIY2NjsX37diGEWjfs7e0FICpWrJiqbmT1nKOjo0XROm0k3ShTu5EICQmRNUMP0Xft+Bh9y/LUeyij1K5dW/z6669ar4cS4+joKObNm5fq/pnOavmOsLCwZDc6Q9Z5ifDwcOmz7CWi+3wI/5Djx48LhUIhJk+eLO7duyeuXr0qWrZsKZycnERkZKQQImv+IUKoTc68vb3F5MmThaWlpfD29hbe3t4iLCwsu5cmT8npm5aMvFZOTHq6IUTWtCOxPmgiMDBQ1gw9RJ+142P1LdP5m5awsDBRoEABsWDBAumJaceOHVL53bt3BSC8vLwy3GZGO/3ibaiwadRTWDfoLglO2VG7xBtluJg6daqYOnWqiImJyXLfZD4Mbm5uok2bNimWXbx4UQDi+vXrabahVCpF3759hY2NjShYsKDo2LGjePr0qVadzZs3ixo1aoh8+fKJIkWKiPbt24s7d+5I5Y8ePRKg7bCqUqnE+PHjha2trTA1NRXNmzdP5uzq7u6e4kihPju1CpGzNy0HDx4U27ZtE9evXxeHDx8WLi4uwtHRUYSGhiYbodVQp06dNFP4C5G1Udro6GhRoHFPYV3/vW5cvvNEfD9srOgxaJQ47esvG67qCfqsHWvXrk11Pog+k13dyHRyufQYMWIE7dq1w8nJCX9/fyZOnIiPjw++vr4UKVKEgQMHcvDgQTw9PTl8+DALFiwgNjaWOnXqsGjRIurWrZvuMTKUnEaVwI0rZ2m/M4IixjFcmdoZgBJDdzD1q1r0cikpVU1QCS49CuJVWDRF85tR17mgbKgoI5MO2U0SlRYhISE4OTkxb948zM3N6dOnjzSvbcmSJcyePZunT59iZ2fH7t27U9WNDCeXS0RcXBxlxh9FFRvNs/ldAKjw624iE00BtLc2Y2K7irSqLBtfyshkhg+eXC49nj9/Tvfu3Xn79i1FihShYcOGXLhwgSJF1Nk158+fj4GBAe3atSMiIoKaNWsyb948Nm3aRMuWLfHz80vm5pppfPfC4dG8CC4GDMU+8p5W8cLjD+hYoxj5zYw5fCuAyft8CVBGS+WyIMnI5C02NjaULVuWBw8e0KJFC2JjYwkJCeHIkSMMGzaM5cuX89tvv+Hk5JSmbiRd8pwuvnuJPjgBmKa1OS4mEkzeC2ygMpqBG6+x7Nuask7IyHxAcnwa8pYtW/D39ycmJobnz5+zZcsWSpUqJZWbmZmxZMkSKlWqxKBBg7h69SpNmjRh+fLlWFhYZN9D5J3pGaH+PFcVJiFSSYGoZ1KxY37B67Bo+q84wboT1/lhw1WtGxZ4L0iHb+l+5lIZmY+R8PBwHj58iL29PbVq1cLY2Jjjx48zb948+vfvT/369QkICGDu3Lk5oxsgaUd06BsSIpVa/kPRwhjbyAckRCoRQqAZnp68z5cEVY4OVsvIyKRBriSXS4/Y2FiuXr3KmDFjpG0GBga4urri5eWV9YYTmZ4BPIq14fmiHqxPVGWW0TLcxWC2/tKOrahfFxmYmGk1o5GgUTtu8Co0RloirXj3xkh2Gsk77t+8yuQBXahWrwkj53kmKz+9fzsATdy+SrHs0OY/CXz2CPN8ltT9vA19Rk6Vym9cOM2OVfN58egexiamlK9elx4/jaOIQ4lUz0cIwd+r5nFyz2YiwkMpW6U2fUdNw87RWaue97nj7Fq9kKcP72BsYkqFGvUYNmtVFq9C7lO/VCFKFs73wY6X0mtlQ0NDunfvjrW1Nf369WPYsGE8f/6crl270qdPH1xcXKhfv372dQO0tCMkzojni3pol8dHcWnxL4BaMxQmZgggQBnNtAO+lCpqmb3j5xGfkpbpmnZcPnmIY7s28fjuTcJDQ5i2/iAly1bSqvPy+RP+WjQNv+uXiYuNpZpLE9yHTca6UNq+YHmFhYkhX9Yoln7FbJAnNy1v3rwhISEBW1tbre2peQ8lfS+tVKqfgJJ5HDw+D69fvP8YnVxInEMusahpAq1nqz+rYiJBqFI8z5AYGLf9cob6JPNhCPpnOfmqtuL65ROM/PMQhpYFAQi7tp98lZsTdV9tdHcg6BQRt46Tv6abVB52dR/WjXpSuFFpVHEx+IS+5tctFwGIV74iYP1Q8tdsS4GufVDFRnLj9Dp8BvTErodHyicDhF7eTejl3RRqOYiCVkV56LWVUd91xb7XPBRG6myZkfcvEHxsBdYNulOoTm9QqXj89ql0bF1kVpeqFDRJ+7VHtj1EEpGR18pRUVGsW7eOcePG0bp1a5YuXQqkrhuQNe14G21IUsYm/MmP735Oqhl/nvDNUp9lPiy6ph0Rd24Rb2CPcd2KcGwFCw/fwuRauFSuiosmcONITAo7YeU2FoAb57fwS9+vKdptGgqF7uVrKZrflM9LpZ1/Ree8hzJCZj1EUlsBIIcccuR96LL3kKwdcsihm6EzGXEzQmY9RMaMGSO5wgLEx8dz584dSpQo8cn4h8DH1Z+s9GXLli1s2LCBAwcOcOzYMSZNmsTZs2dRvHtv9+LFC9q1awfAvn37pAyW+/btY+jQocycOZMlS5YQHh5O7dq1GT9+PA4ODgA8ffqUZs2aMW3aNL766isiIiIYPXo0SqWSv/76C1BnUa1fvz7btm3DxcWFJ0+e0LBhQ/7++286d+4s9aVLly5UqlSJyZMn4+3tTfv27ZkzZw5r167l9evXVKxYkd9++43y5cvn9GXNNh+b95CsHXJfQPe0I2l/AA4fPkylSu9fD/3zzz/0798fPz8/aTJ5TEwM5cqV46efftL6XusCOus9dPr0aeHm5iZlpNy1a5dWuWbtuZ2dnTAzMxPNmzcX9+7d06rz9u1bUahQIWFsbCysra1F3759hVKplL2H5JBDDyMjT0y6oBuydsghh+7EBxtpiYiIoFq1avTt25dOnTolK581axYLFy5k3bp1ODs7M378eFq2bImvry9mZuoJrz169MDS0pLQ0FAGDRrExo0bqVmzZoY9RNLyDzlww5/Rf99Mtw2PzlVoW9UhI12W0QHu379PvXr1uHv3rjTPYcSIEYSGhrJy5UoWL16Mu7s7e/fuBaB9+/asW7eOwYMHM2fOHH7//Xd27txJ8+bNAfW8qjJlyrB9+3ZcXV15+fIlrVu3pm3btnTp0oXw8HCmT5+OoaEhe/bskZ7IEnPx4kW++OIL/Pz8tJ4a3N3dUSgUeHp6sn37dr777jv++OMP6bsdExNDhQoVGDduHH379s3tS5drZMZDRBd0A1LXDlk3Pl50UTsS8+TJE6pWrZrMhwjg+PHjDBs2jCdPnmBgYECXLl24e/cutWrVYv78+blwtXKf7HoPZfqmpXXr1rRu3TrFMiEEf/zxB+PGjaNDhw4ArP9/e2ce1sTVvv87hCSACojIpoJoRaxiWRSEWrWKivvalloVrUtfC63Kt9WqVV6Xvrhr3artT1yqda1g1Yq0KtaKilpQBMRqUauIFSj7muT5/REzMhCWECAJns91nQs4czI5z0xyc2bmnOfeuxfW1taIiIiAv78/kpOTERkZiWvXruHKlStYs2YN0tLSIJVKceLEiUqTc1Wh/BCYmppWGrS0ty2DgcSkxn20t21d7wmxGA3HoUOHIJVK0blzZ66OXpie7dixAwsXKiaqGRsbAwDatGnD1Tk6Klby9OzZkzvnpqamsLS0RGZmJmc337JlS3z99dfc/l1cXNCuXTskJyejV69elfqkXMpfWFjI+yxlZWXB1dUVpqam6NChAwDAw8OD16Zjx454/vx5k/gM1iTKgG7oRvm+VtQOphtNF13UjvIo/3k3b9680mdrzJgxGDNmDDIyMmBoaAhzc3PY2NjA2dlZ7z+HtdENVdTr9OPU1FSkp6fD19eXqzMzM4OXlxe3JPHy5cswNzdHjx49EBQUhIcPH6KoqAhCoRBlZWUq91tSUoLc3FxeqQpPRwvYmhkB0jJk/LwRj7dNwbPDSyAvLkDm6U3IPL0J1s0M4OloUZ+hMxoQqVSKvXv3Yt26dYiPj+fKzZs3YWdnhwMHDnBtp0yZgilTpvBe/+abbwIAUlJSuLqsrCxkZGTAwcEBgGLgUXGOg9IVVi5XvbrM0dERNjY2OHv2LFeXm5uLq1evcs+tPTw8ODdZJWVlZXjw4AH33q86DaUbQO21Q6kbAgBUhXYUnd2KN+wabxk4Q3N0VTvUxdLSEubm5jh37hz++ecfjBw5sl72q5fU6aHSCwD+s+lLly4RAEpLS+O1e+edd+jdd98lIqKvvvqKnJycKu2rdevWtG3bNpXvo65/yOmENLKfe5TXtk3QPu738Kv36hgxQxvos+kZEdHs2bOpTZs2dObMGbpz5w5NmzaNrKysKCsrS9NDo1Xq6iHSWLpBpJ52nE5Io/bzT1K7CtrRtpx2MLNE/UKXtSMzM5Pi4uLo1KlTBIAOHjxIcXFxPEPEsLAwunz5Mt27d4++//57srCwoODgYE0Pi1bR1HtI9xZ6q2DBggXIycnhyt9//11te79uttgy0Q3t3hrD1RkYGKDdwKmY/Ml8DHWtOuEPQ/fYuXMnfH19YWZmVmnbuHHjcP36ddy6davafezduxdeXl4YNmwY+vbtC5FIhMjISIhEIgBA//798cMPPyAiIgJubm7w8/ODRCJBZGQkd9u4rKwMKSkpKCws5PY7b948fPLJJ5g5cyZ69uyJ/Px8REZGcvMwAGDNmjXw9/fHpEmT0LNnTzx8+BDnzp1Dy5Yt6+PwMKpBHe3w62aLbya6w9ZMAjOf97l6GzMJJn8yHytWrOA+Lwz9QJe146effoKbmxuGDRsGAPD394ebmxu2b9/OtUlJScHo0aPRpUsXLFu2DIsWLcLatWs1Pi56jSYjJlS4Yrp//z4BoLi4OF67Pn360KeffkpERDt37iRzc3MiItqyZQs5ODiQWCwmALRq1apavW+NI7XE40TrnOnTz2ZzV0gfzFtO0tsRasfIYDBUU193WhpLN2rV58TjlLnGnXe35dzSQQpNYTAYGqNTd1pq84zf29sb2dnZCA0NRXBwMEJCQrBlyxYAwFdffYV//vlHs06U8x6S0svMlpfKnPD40OeK7QwGQ2fQCd0AOO2Q5mXwqg/kuio0hWkHg6F11B605Ofnc5OZAMUkuvj4eDx69AgCgQBz5szBihUr8NNPPyEhIQGTJ0+GnZ0dRo8eDQDo0qUL/Pz8sGLFCowcORJOTk7c7fPmzZtrZnxWzj+EiJBbWMptkpIBpuTMQPj+7XiSmYecojIUlkpRKpVDKtN+kcmJlVqU3y/FQCgUYujQYSq3h4XtQljYriq3de/eHUZGRrCyssLHH3/M237w4CG4urrCxMQEDg4OWLV6dY39kcrk+HLxYtja2sLY2BgDfH1xJ+Uur83yFSvg7eMDExMTmJuba/0Y1qbI5VT376EKdFo3AJ52lJIBzyzxtKwnFmePxMUDa5GZW4iCEimKy2QoY99bvSp10Y6wsF0QCAQqy9P0Z5X28dvF32FoaAhXV9ca+/M8IxMTJnwAU1NTmJub48MPP0RObh63vaCwCAEBU+Di4gJDQ0OMGjVa68ewNqWhERCpZwAQHR2Nt99+u1J9QEAAdu/eDSJCSEgIvv32W2RnZ6N3797Ytm0bnJycuLbp6emws7ODRCKBWCzGuHHjsGnTJgQGBiI7OxvHjx/n7buif4hynXdOTg5/2VfqRWCPwi+ioJTQPDSP29QtaBtub1G4h6gySWToB5mnN0EgMkJ+wi+wm74dhi1aAVB4ADXvPgiFd2MAACZOPsi/FQXTnqMV22PDkXstHC3f/hBi286gsmJIc/6BSScvAEDR/ev459hyWPh+BCNHd5Rl/o2syM0w7fUOTD1GVNmfnCtHkXPlCCyHzYWhmTWyL+5D2fMHsJv+Dec9lH1xPwyMmkGal4H8W7/Afs6hBjxC9cOm990w8o3q85Hk5ubCzMys8vdQBdrQDaBu2pFU3BpdV93nNrUJ2ocnWyYCYNqhz9RFO+RlJaCSQt5+Mn7eAJKWwmbCSl69vDgfT/fMgaG5LWSF2bCburna/jw7HAJZQRZaDQ4CyaXI/HkjxDZOaD3yc8X+Sovx7/mdEFt3ROHdGAgMxbAa+2V9HY4GwcbUCFcWDqi2jTq6oQq187T069evWqMjgUCAZcuWYdmyZVW2kcvlICKcO3eOl9K4KuOz0NBQLF26tFJ9peWL6alAiaJvBaX8Pn5LK+Dz4neD0gLIqzBJZOgu8tJiFCT/Buv3VyoGAPGnYeqpSFQmEIrx7OAiiFopJlnn/XEKzV0GQl5SCHlxPrIvfg/LkfNhZO/yYm9mMDSzVpjfAchP+AXGHXui2ev9AADCtl3Rosco5F45imZd+6vMKUBEyL0WAVPPMTCyVySFshg4C0++nYGCpAsw6axYLmnqqZgQXpAYDRBx76nLFObnVZtaAFDP+EwbugHUTTv+LeGf6xDZN5ip7EM1BqsM3aWu2gEAApGE24+sMBfFD2/CYuCsSt/jjNObYOLkAwgMUHT/WrXf87KsxyhOvQHr90O59zXvOxUZEaEoe/N9zsyxZT9F0sTiRwmgkgKd1w5psaxedUMl6k6CqY903Ldv3yYAZGJiwqXjzsvLq9L4rLi4mHJycriSlJSk9RTErLDCiqI0Vhp/dXWDaQcrrOhu0as0/kqjp5CQEPj4+GDq1KmYOXMmRCKRShMliUTCGUYBgImJCWJjY2Ftbf3KmJ4BTSueusQyZswYDB8+HNOmTYNUKoWHhwe2b98Ob29vHDt2DLt37+YeJ9y9exdTpkzB2LFjsXXrVqxbtw729vb473//y2WxfPr0KaKioiAWi7F//34sXboUYWFh8PHxwYMHDzBt2jTcu3cPERER8PDwwNOnT/H+++9jw4YNcHNzw/Xr1zFmzBhcuHABffv25WKZNWsWAOCbb77h9f/w4cNYunQpEhMT6/dg1iMNZZioDd0AmHYALBag7tpRkf79+6NXr1743//+x9WlpqZi7Nix+PHHH9GhQwesX78eZ86cwZkzZ7g2p0+fxqpVqxAdHQ0A2Lx5M44ePYqTJ0/y4nF1dUVwcDAmT57Me9+5c+ciNzcXO3fuVOdwNSo6a5hYHoB/xSSXy8nGxobWrFnD1WVnZ5NEIqEDBw4QEXFXOq+//joFBQUREdHp06dJIBCQjY0NM0xkhRU9K+peMQHa0Q2mHaywojul0e60VEdN6bj9/f25dNxLlixBQEAAevToAXd3dwCKZ12aGibK5IRBGy7gWW6JqpdCAMDKVIKouX0hNKib9wGj8Vm8eDE2bdrEpccGwPmHpKSkcMmj9u/fD0Bhrqdk3759CAwMRFJSEmc5DwCvvfYavvzyS17qbplMhmfPnsHS0hIXLlzA+PHjcf/+fVhaWlbqU2pqKlxdXSsZnQ0dOhQuLi5YtWoVr/3+/fuxYMECPHr0SLODoSNoanympCF1o+JEXHrxHF2VdgDAL0npCD50E1ShXqkU6997AwNfr+MVIkMraKId5QkMDMTNmzfx+++/c3XZ2dlwcHDg7Vs590ooFCI8PBx9+/attK/vv/8eixYt4mmBVCqFlZUV9uzZgxEj+JP/Z82ahZycHPzwww91OAK6RaMbJlZHeno6AFQyL7O2tua2paenw8rKCu+99x6eP3+OJUuWID09HUKhEIGBgSqNzyoKT16eYlWQKsPEy/cz8bxECIFQhMyorSh+EA+RpT1aj5yPf8+/uLU2cBbuZErh3bFVvcXOaDikUikOHTqEdevWYdCgQbxto0ePxqlTp/Cf//wHALhHM+VR/jNMS0tDly5dACj8QzIzM1Uajykz1R4/fhze3t6c6WFFunfvDhsbG1y9ehW9e/cGoPhCXr9+HUFBQZX2q8yOqe9GZxWpq/GZkobSDaDqibiqtEMmJ6w9fw0QipBVQTuyXmjHaos5GO3ZiV3w6AmaaoeS/Px8REREIDQ0lPe5ad68ORIS+O7g27Ztw7lz53D06FE4OjqiWbPKflX9+/dHTk4O/vzzT3h4eAAAoqKiIJfL8fbbb1f6bIpEIhgaGjYp7dAJw0R1URqflZSUoGXLlpyjZkVCQ0NhZmbGlXbtqk7D/09eMQCA5DIUJPwKWV4GilP/gFxWhvxbUci/FQWSy7h2DN3n5MmT+PfffzFt2jR069aNV8aNG1fjc14nJyeMGjUKs2fPRkxMDG7fvo2AgAA4Oztzy3AzMjKwfft23LlzB/Hx8Zg9ezaOHDmCjRs3cvt58uQJnJ2dERsbCwC1yi8CAI8ePeJykshkMi5fSX5+fr0fq1eB2uoGoF4a/9jULDzNKa5WO57+W4jY1KyGCIvRAGiqHUqUTtETJ07k1RsYGFTar5WVFYyMjNCtWzduwBIeHg5nZ2fudcq8QzNmzEBsbCwuXbqEoKAg+Pv7w87uZaqBpKQkxMfHIysrCzk5ObxcR68q9TpoUU6sefbsGa++/KQbGxubStkrpVIpsrKyqpyYo47wWLVQTNoTCgWw9RnN1QsMDGD+1iSYvzUJAqGQa8fQfRrDPwQA9uzZgx49euDNN99EYmIioqOj4enpyW2vq/fQkiVL4ObmhpCQEOTn58PNzY2byMtoON0AFBNxlXdVVN1dKY/yQsZAKOB5DxlU0A52waM/1Id2KPczduxYmJub16kfOTk5PKdoQPE4ytnZGQMGDMDQoUPRu3dvfPvtt7w2Q4cOhZubG06cOIHo6GhOO15p6jQT5gWA6gl1a9eu5epycnJUTqi7fv065yEiEokIAJ08ebJW71udd4FUJqf5y1fQkyXtafZnn3KTfvoHb6SZC5ZQ+/knqdf/fiWpTK5J6AzGK099eQ81lm7U1OeYexk0c8ESSl7chec9tOizGTRzwRJymH+SHOafpJh7GWrFy2AwXqKp95Dac1ry8/Nx79497m9lOm4LCwvY29tzt8s7derELV1UlY57/PjxePz4MT7//HP88MMPMDQ0xMSJE5GSkgIrK6s6D8KEd04gVLoGBOJ5D/1JbbFJ+P8gADB6xH/YM2kGoxHRdd0AAM/i39FLvBH/yPl3Y87K3HHeeCHmSD/BzRZ94OloodH7MBgMDVB3lHP+/HmVy5cCAgKI6GWSKGtra5JIJDRgwABKSUnh7SMzM5MsLCxIJBKRqakpTZ06lXJycsjOzq5WSxerHKnJpETrnIlCTEm+pAVNnBXI9a/tnCM07NOllLCwK8mlZeqGzdARYmJiyMDAgIYOHapy+65du2jXrl2V6mNjY6l///5kZmZG5ubmNGjQIIqPj+e1uXnzJvXu3ZskEgm1bdu2Vu7BRUVF9PHHH5OFhQU1a9aMxo4dS+np6bw2n3zyCbm7u5NYLKY33nij1rHqOupcMemCblTb5xfaIQ8xpceLHcjuo5087Zg3eyr9Edyefr75qFbvw2AwVKPpnRa1vYfqg9LSUpiYmODo0aO8CYsBAQEN5j3kFPQd7m6ZAQAYtTIcrW3bwkgkhEjVHRdBxT8rt9FwwQSjjpzZvhRiI2MknIvAhxsj0NxCcXV94+T3cBkwFnev/goAcPLyRcLZY/AYPgmlxYX47uMh6NijLzxHfwi5TIqYw9vx5E4cZn4TCaGhCCWF+QibPQoOLl7wHPMhMh7dw5lv/ou3p3yG7r7jq+zPr999hb/+uAi/wGWQmDTH2Z0rITAQ4P3le7g258JWoaWdA9Lv3cbzh3cxec3hhj1I9cAHXvZws29ZbRtNPUTUpbS0FMbGxnB3d8eTJ0/w9OlThIeHIzw8vF69h+4UW6LLqr+4TeW9h95ZHY5Wtu0gNjTgVEEgeKEQAoVWMG1gvKqYGYuwePjr1bZpdO+h+iAjIwMymUzlEseG8h5aI1+PUS9+v/4oDwbpqXUPgKEV5KXFSLt4Gtbvr4Sh/QMc3BvG+YcUPC1CzPwpnI/H+WP70NxlIO7H3EXps/sozs9BVkc//PpA4fxd2skPhVd/xcGoyxCZ2yD/ZhSKi4uR5zYR5/6WA4IOMO4+GOePhOGOSXfV/SkpxJOzx9BqyGxcyTUHcgHynoqne+fi+x9PQmL7wuzPeQwyAOSU3ENRQQkOx9xt6EOlMT3sjNDRXFhtG409RNQkIyMDcrkcXbt2xcKFC7mMpfXtPZRVwXtonnQnZr/4PeZBHgzS/gKDwaiMVQsJZvdpW22bRvceqg+ePHlCACgmJoZXz7yHWGFF/0pdM1tqqhuAYkIv8x5ihRX9KzqREbe2WFpaQigUVrvEsTzMP0RBU4qnMb2HAODOnTuYPn06t1ze0dER+/btQ9u2iquCCRMmwN7eHitXvrSbv3v3LgYMGIBz586hU6dOiIuLw9y5c3HgwAHY2toiPDwcn332GeLj43mxDB8+HD4+Pli4cCGv/6o8SXSNhvIeqg/U1Q1VWFtb4+LFi7C3t39ltIPFors0pXh01nuoPtxaMzMzqVWrViQSiTi31pycHGrTpg3zHmKFFT0rjXWnhYjI09OT8x4CQD/++GO1uhESEqL148MKK6xULnrl8vzBBx+gefPmyM3NRWBgIPbt2wd3d3cUFBRo7D106lYa5v+YoOplPFaNc8Gw7nY1tmPoBpr4h+zduxfLli3D3bt3uavr0tJSODg4YPPmzRg/fjw++ugj5OXl8bw9fvvtN4wYMQIPHjzgUvuX58KFCxg5ciQePnzISzrVrVs3zJo1C4GBgbz2oaGhOHXqFM+7RJ+pL+8hdQgODua8hwBgx44d1erGggULOHdoQJHky97evkrvIQaD0bA0uvfQkCFDMGTIEJXbiAgbN27El19+iVGjRgFQ/MOwtrZGREQE/P39kZycjMjISFy7dg1XrlzBmjVrkJaWBqlUihMnTlTpIVIepWeBqgyX7W3LYCAxAUnLqvQeshg4C+1tWzPR0hM09Q+hF+ZlZmZm3GdHKpVCIBDAyMgIpqam6NOnDxYtWgRjY2MuS25MTAw6d+4MBwcHlf3q06cPRCIRrl27hnHjxgEAUlJS8Pfff6v0D5FIJDAwMGhynztNvYfUobz3EKDI9xIZGVmlblR8tKykpuy4DAajYdEJ76Ga3FoBcG6tPXr04DxEioqKIBQKUVZWpnK/JSUlyM3N5ZWq8HS0gK2ZEVCNf4h1C0OWIEqP0NQ/ZODAgfj3338RGBiI5ORkJCYmYurUqTA0NOS8hyZMmACxWIxp06YhMTERhw4dwtdff827So+NjYWzszOePHkCQPHZnjZtGoKDg3H+/HncuHEDU6dOhbe3N3r16sW97t69e4iPj0d6ejqKioo4/5DS0tIGOFpNH6VuAIo7u15eXlruEYPBaCzqddCijltreQwNDWFhYcG1qYg6holCAwFCRrwOgVDI8w8RGAg5/5DFI11YRlw9QlP/EGdnZ5w4cQK3bt2Ct7c33nrrLaSlpSEyMhK2trYAFAOQqKgopKamwsPDA//3f/+HJUuWYObMmdx+CgsLkZKSwhtcb9iwAcOHD8e4cePQp08f2NjY4NixY7z3nz59Otzc3LBjxw7cvXuX8w9JS0vT9NC8cuTn5/NM45SZdR89eqTdjjEYjMahbtPhFAD8ibiXLl0iAJSWlsZr984779C7775LRERfffUVOTk5ERFxHiISiYQMDQ1p3rx5Kt+n4rJF5UTc6jLqnb71N3nPe5nVst3cI9Trf7/S6YS0Kl/DYDBqj6aZLetCTZl1a0IbfWYwGC/R9DuoNZfnQ4cOITg4GCEhIYiNjYVMJsOWLVsqObkC6jm1AgCSfoLfLwPRQ/by6ruTMB0XR+TDr5uthlEyGAxt0a9fP2zZsgUODg6QSCTw9PTE1atXsXv3bm13jcFgNAL1OmhxdHSEjY0Nzp49y9Xl5ubi6tWr8Pb2BgB4e3sjOzsby5cvx4wZMzB16lTusVCLFi0QFhamWSeSfgIOTwblPEFu4cs5A3elNvgpbBWe//59o2XwZDAY9Uv5i50//vgDb7zxBgYPHqzyYofBYDQ9tOLyPGjQIERFRWHy5Mm4dOkSgoKC4O/vD5FIxE3YrRNyGRA5HwChsAzY88033CaSlmDclsvAhss4HOMFSwtziIUGMDQQNNrqB+ZJwtAXOlg2Q6vmlVfdaJv169dzFzsAsH37dpw6dQphYWH44osvtNw7BoPR0Kg9aLl+/Tq34gIAt7oiICAAu3fvxrx581BQUICZM2ciOzsbvXv3RmRkJJejBVAIT7du3bB06VIYGhpi3Lhx2LRpE5YtW6bSQ6Si6VlOTg4AFf4hD2KA54qVHRW9h7qXJeDJi9/n7rsKA7ERGAyGalaP746hLtU/Sm1s76HS0lLcuHEDCxYs4OoMDAzg6+tb5cVOrbWDwWA0Cq+E9xDLaskKK7pbtOU9VJNuEDHtYIUVXS1N2nuoYlZLuVyOrKwstGrVqtpHO8rMe00l+2VTiofFopuoEwsRIS8vD3Z2uptZmmkHi0WXaUrx1DYWTXVDK4MWsVgMDw8PnD17lpvrIpfLcfbsWQQFBVVqryqrZfm06TXR1LJfNqV4WCy6SW1jUZU7p6Goi2Ei046XsFh0l6YUT21i0UQ36nX1kDoEBwfju+++w549e5CcnIxZs2bV2nuIwWC8epS/2FGivNhRrk5kMBhNG63caQH4HiLp6elwdXWt1kOEwWAwyhsmenp6YuPGjexih8F4hdDaoAVQeIioehxUX0gkEoSEhKg0TNNHmlI8LBbdRNdjaayLHV0/DurAYtFdmlI8jRWLgIhlWmMwGAwGg6H7aG1OC4PBYDAYDIY6sEELg8FgMBgMvYANWhgMBoPBYOgFbNDCYDAYDAZDL9C7QcvWrVvRvn17GBkZwcvLC7GxsdW2P3LkCJydnWFkZAQXFxf8/PPPvO1EhCVLlsDW1hbGxsbw9fXFn3/+2ZAhcKgTy3fffYe33noLLVu2RMuWLeHr61up/ZQpUyAQCHjFz8+vocMAoF4su3fvrtTP8t5UgHbPC6BePP369asUj0AgwLBhw7g22jg3v/32G0aMGAE7OzsIBAJERETU+Jro6Gi4u7tDIpHgtddew+7duyu1Ufc7qAs0Jd0AmHboqnY0Bd0AdFw76pT8X0scPHiQxGIxhYWFUWJiIs2YMYPMzc3p2bNnKttfunSJhEIhrV69mpKSkujLL78kkUhECQkJXJuVK1eSmZkZRURE0M2bN2nkyJHk6OhIRUVFOhXLhAkTaOvWrRQXF0fJyck0ZcoUMjMzo8ePH3NtAgICyM/Pj54+fcqVrKysBo2jLrHs2rWLTE1Nef1MT0/ntdHWealLPJmZmbxYbt++TUKhkHbt2sW10ca5+fnnn2nRokV07NgxAkDh4eHVtv/rr7/IxMSEgoODKSkpiTZv3kxCoZAiIyO5NuoeG12gKelGXeJh2qGbmq6rukGk29qhV4MWT09PCgwM5P6WyWRkZ2dHoaGhKtu/++67NGzYMF6dl5cXffTRR0REJJfLycbGhtasWcNtz87OJolEQgcOHGiACF6ibiwVkUql1KJFC9qzZw9XFxAQQKNGjarvrtaIurHs2rWLzMzMqtyfNs8LkebnZsOGDdSiRQvKz8/n6rR1bpTURnjmzZtHXbt25dW99957NHjwYO5vTY+NNmhKukHEtENXtaMp6gaR7mmH3jweUtrS+/r6cnU12dJfvnyZ1x4ABg8ezLVPTU1Feno6r42ZmRm8vLyq3Gd9UJdYKlJYWIiysjJYWFjw6qOjo2FlZYXOnTtj1qxZyMzMrNe+V6SuseTn58PBwQHt2rXDqFGjkJiYyG3T1nkB6ufc7Ny5E/7+/mjWrBmvvrHPjbrU9H2pj2PT2DQl3QCYdgC6qR2vsm4AjasdejNoycjIgEwmq5T50traGunp6Spfk56eXm175U919lkf1CWWisyfPx92dna8D4Gfnx/27t2Ls2fPYtWqVbhw4QKGDBkCmUxWr/0vT11i6dy5M8LCwnD8+HHs27cPcrkcPj4+ePz4MQDtnRdA83MTGxuL27dvY/r06bx6bZwbdanq+5Kbm4uioqJ6+dw2Nk1JNwCmHbqqHa+ybgCNqx1aTePPqBsrV67EwYMHER0dzZuE5u/vz/3u4uKC7t27o2PHjoiOjsaAAQO00VWVeHt78wzufHx80KVLF+zYsQPLly/XYs80Z+fOnXBxcYGnpyevXl/ODaNpw7RDN2G6UXv05k5LXWzpbWxsqm2v/KnOPuuDusSiZO3atVi5ciWioqLQvXv3att26NABlpaWuHfvnsZ9rgpNYlEiEong5ubG9VNb5wXQLJ6CggIcPHgQ06ZNq/F9GuPcqEtV3xdTU1MYGxvXy7lubJqSbgBMOyqiK9rxKusG0LjaoTeDlrrY0nt7e/PaA8Avv/zCtXd0dISNjQ2vTW5uLq5evdqgVvd1iQUAVq9ejeXLlyMyMhI9evSo8X0eP36MzMxM2Nra1ku/VVHXWMojk8mQkJDA9VNb5wXQLJ4jR46gpKQEEydOrPF9GuPcqEtN35f6ONeNTVPSDYBpR0V0RTteZd0AGlk71Jq2q2UOHjxIEomEdu/eTUlJSTRz5kwyNzfnlrxNmjSJvvjiC679pUuXyNDQkNauXUvJyckUEhKicumiubk5HT9+nG7dukWjRo1qtOVx6sSycuVKEovFdPToUd7yt7y8PCIiysvLo88++4wuX75Mqamp9Ouvv5K7uzt16tSJiouLdSqWpUuX0pkzZ+j+/ft048YN8vf3JyMjI0pMTOTFq43zUpd4lPTu3Zvee++9SvXaOjd5eXkUFxdHcXFxBIDWr19PcXFx9PDhQyIi+uKLL2jSpElce+Wyxc8//5ySk5Np69atKpctVndsdJGmpBt1iYdph25quhJd0w3le+uqdujVoIWIaPPmzWRvb09isZg8PT3pypUr3La+fftSQEAAr/3hw4fJycmJxGIxde3alU6dOsXbLpfLafHixWRtbU0SiYQGDBhAKSkpjRGKWrE4ODgQgEolJCSEiIgKCwtp0KBB1Lp1axKJROTg4EAzZsxotH8m6sQyZ84crq21tTUNHTqU/vjjD97+tHleiNT/nN25c4cAUFRUVKV9aevcnD9/XuVnRtn3gIAA6tu3b6XXuLq6klgspg4dOvByRiip7tjoKk1JN4iYduiqdjQF3SDSbe0QEBGpd2+GwWAwGAwGo/HRmzktDAaDwWAwXm3YoIXBYDAYDIZewAYtDAaDwWAw9AI2aGEwGAwGg6EXsEELg8FgMBgMvYANWhgMBoPBYOgFbNDCYDAYDAZDL2CDFgaDwWAwGHoBG7QwGAwGg8HQC9ighcFgMBgMhl7ABi0MBoPBYDD0AjZoYTAYDAaDoRf8f9EzbwcujGonAAAAAElFTkSuQmCC",
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",
       "text/plain": [
-       "<Figure size 640x480 with 60 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -236,25 +237,30 @@
     }
    ],
    "source": [
+    "# Allelel Frequency TABle with Study Prior\n",
+    "AFtabSP = pd.concat([venezuelaAF, study_prior], join=\"inner\")\n",
+    "\n",
     "# Combine Allele Frequency with Study Prior\n",
-    "cafSP = HLAfreq.combineAF(\n",
-    "    pd.concat([venezuelaAF, study_prior], join=\"inner\")\n",
-    "    )\n",
+    "# As we're using a dataset as the prior we should set the\n",
+    "# argument for priors, `alpha` to 0. 59 Is the number all alleles\n",
+    "# in our dataset\n",
+    "nalleles = len(AFtabSP.allele.unique())\n",
+    "cafSP = HLAfreq.combineAF(AFtabSP, alpha=[0]*nalleles)\n",
     "\n",
     "# View posterior of all alleles\n",
-    "HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join=\"inner\"))\n"
+    "HLAfreq.plotAF(cafSP, AFtabSP)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 640x480 with 6 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -263,7 +269,12 @@
    ],
    "source": [
     "# View posterior of just alleles observed in Venezuela\n",
-    "HLAfreq.plotAFprob(cafSP, pd.concat([venezuelaAF, study_prior], join=\"inner\"), alleles=venezuelaAF.allele.tolist())"
+    "\n",
+    "venezuela_alleles = cafV.allele\n",
+    "HLAfreq.plotAF(\n",
+    "    cafSP[cafSP.allele.isin(venezuela_alleles)],\n",
+    "    AFtabSP[AFtabSP.allele.isin(venezuela_alleles)]\n",
+    ")"
    ]
   },
   {

From c1c1caf53695d882a9315f79b26e2c75ef1dd911 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 13:49:54 +0000
Subject: [PATCH 083/192] Add posterior mean to AFhdi() and format as dataframe

Examples updated to use new code and
explain PyMC model an credible intervals
---
 examples/CI_empirical_data.py     |   74 +-
 examples/credible_intervals.ipynb | 1223 +++++++++++++++++++++++++++++
 examples/multi_country.ipynb      |  118 +--
 src/HLAfreq/HLAfreq.py            |   11 +-
 src/HLAfreq/HLAfreq_pymc.py       |   15 +-
 5 files changed, 1260 insertions(+), 181 deletions(-)
 create mode 100644 examples/credible_intervals.ipynb

diff --git a/examples/CI_empirical_data.py b/examples/CI_empirical_data.py
index 6d987de..58003b9 100644
--- a/examples/CI_empirical_data.py
+++ b/examples/CI_empirical_data.py
@@ -31,69 +31,17 @@
 aftab = HLAfreq.decrease_resolution(aftab, 2)
 caf = HLAfreq.combineAF(aftab)
 
-HLAfreq.plotAFprob(caf, aftab, xmax=1.1*caf.allele_freq.max())
+#           #
+#   Plot CI #
+#           #
 
-#                                   #
-#   Calculate credible intervals    #
-#                                   #
+HLAfreq.plotAF(AFtab=aftab, credible_interval=0.95)
 
-# pymc hdi
-hdi = HLAhdi.AFhdi(aftab)
-# Dirichlet only ci, too narrow
-Dci = HLAfreq.AFci(caf)
-
-# To access the model you have to call the internal functions like so
-c_array, allele_names = HLAhdi._make_c_array(aftab)
-idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)
-hdi = az.hdi(idata).frac.values
-
-# Compare dirichlet and pymc estimates and intervals
-shift = .3
-plt.scatter(caf.allele_freq, range(caf.shape[0]))
-plt.scatter(az.summary(idata)['mean'][:-1], shift+pd.Series(range(caf.shape[0])))
-for i in range(caf.shape[0]):
-    plt.hlines(
-        y = (i),
-        xmin = Dci[i][0],
-        xmax = Dci[i][1]
-    )
-    plt.hlines(
-        y = i+shift,
-        xmin = float(hdi[i][0]),
-        xmax = float(hdi[i][1]),
-        color="tab:orange"
-    )
-plt.show()
-
-# Compare sub populations to country
-aftab['allele_i'] = ""
-for i,allele in enumerate(caf.allele):
-    aftab.loc[aftab.allele==allele,'allele_i'] = i
+#                   #
+#   Calculate CI    #
+#                   #
 
-for i in range(caf.shape[0]):
-    plt.hlines(
-        y = i,
-        xmin = float(hdi[i][0]),
-        xmax = float(hdi[i][1]),
-        color="black"
-    )
-    plt.hlines(
-        y = i,
-        xmin = float(Dci[i][0]),
-        xmax = float(Dci[i][1]),
-        color="red",
-    )
-    # mask = aftab.allele==caf.allele[i]
-    # plt.scatter(
-    #     aftab[mask].allele_freq,
-    #     [i] * mask.sum()
-    # )
-for pop in aftab.population.unique():
-    pop
-    mask = aftab.population == pop
-    plt.scatter(
-        aftab[mask].allele_freq,
-        aftab[mask].allele_i
-    )
-plt.scatter(caf.allele_freq, range(caf.shape[0]), color='black')
-plt.show()
+hdi = HLAhdi.AFhdi(aftab)
+# Add to caf
+caf = pd.merge(caf, hdi, 'left', on='allele')
+caf[['allele', 'allele_freq', 'post_mean', 'lo', 'hi']]
\ No newline at end of file
diff --git a/examples/credible_intervals.ipynb b/examples/credible_intervals.ipynb
new file mode 100644
index 0000000..c1495c5
--- /dev/null
+++ b/examples/credible_intervals.ipynb
@@ -0,0 +1,1223 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Calculating credible intervals\n",
+    "When we combine datasets, by default, we assume that each one is from the same population and that there is no sampling variance. If these assumptions are violated it would lead to overly tight confidence intervals. In reality these assumptions are rarely met and so by default `HLAfreq` does not supply credible intervals.\n",
+    "\n",
+    "However, if we model this variance we can obtain accurate credible intervals for the combined allele frequencies. We can do this using `AFhdi()` from the `HLAfreq.HLAfreq_pymc` module which we import as `HLAhdi` below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import HLAfreq\n",
+    "from HLAfreq import HLAfreq_pymc as HLAhdi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 pages of results\n",
+      "Download complete\n",
+      "2    64\n",
+      "3     3\n",
+      "Name: allele, dtype: int64\n",
+      "Multiple resolutions in AFtab. Fix with decrease_resolution()\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download dataset\n",
+    "country = \"Mongolia\"\n",
+    "locus = \"DQB1\"\n",
+    "\n",
+    "base_url = HLAfreq.makeURL(country, locus=locus)\n",
+    "aftab = HLAfreq.getAFdata(base_url)\n",
+    "aftab = HLAfreq.only_complete(aftab)\n",
+    "HLAfreq.check_resolution(aftab)\n",
+    "aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "caf = HLAfreq.combineAF(aftab)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
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+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:06&lt;00:00 Sampling 4 chains, 2 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 7 seconds.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>allele</th>\n",
+       "      <th>allele_freq</th>\n",
+       "      <th>lo</th>\n",
+       "      <th>hi</th>\n",
+       "      <th>post_mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>0.102965</td>\n",
+       "      <td>0.069354</td>\n",
+       "      <td>0.14193</td>\n",
+       "      <td>0.107</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>DQB1*02:02</td>\n",
+       "      <td>0.062476</td>\n",
+       "      <td>0.025963</td>\n",
+       "      <td>0.078963</td>\n",
+       "      <td>0.052</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>DQB1*03:01</td>\n",
+       "      <td>0.271881</td>\n",
+       "      <td>0.220663</td>\n",
+       "      <td>0.329699</td>\n",
+       "      <td>0.275</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>DQB1*03:02</td>\n",
+       "      <td>0.045532</td>\n",
+       "      <td>0.022769</td>\n",
+       "      <td>0.068847</td>\n",
+       "      <td>0.045</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>DQB1*03:03</td>\n",
+       "      <td>0.128528</td>\n",
+       "      <td>0.066764</td>\n",
+       "      <td>0.142278</td>\n",
+       "      <td>0.103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>DQB1*03:04</td>\n",
+       "      <td>0.001752</td>\n",
+       "      <td>0.000164</td>\n",
+       "      <td>0.009574</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>DQB1*03:13</td>\n",
+       "      <td>0.001752</td>\n",
+       "      <td>0.000164</td>\n",
+       "      <td>0.009965</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>DQB1*04:01</td>\n",
+       "      <td>0.038527</td>\n",
+       "      <td>0.016768</td>\n",
+       "      <td>0.060056</td>\n",
+       "      <td>0.038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>DQB1*04:02</td>\n",
+       "      <td>0.021780</td>\n",
+       "      <td>0.013736</td>\n",
+       "      <td>0.04914</td>\n",
+       "      <td>0.03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>DQB1*05:01</td>\n",
+       "      <td>0.060791</td>\n",
+       "      <td>0.034938</td>\n",
+       "      <td>0.09162</td>\n",
+       "      <td>0.062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>DQB1*05:02</td>\n",
+       "      <td>0.039710</td>\n",
+       "      <td>0.021234</td>\n",
+       "      <td>0.064176</td>\n",
+       "      <td>0.042</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>DQB1*05:03</td>\n",
+       "      <td>0.020403</td>\n",
+       "      <td>0.004785</td>\n",
+       "      <td>0.032304</td>\n",
+       "      <td>0.018</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>DQB1*05:04</td>\n",
+       "      <td>0.001170</td>\n",
+       "      <td>0.000052</td>\n",
+       "      <td>0.008706</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>DQB1*05:42</td>\n",
+       "      <td>0.001170</td>\n",
+       "      <td>0.000037</td>\n",
+       "      <td>0.008818</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>DQB1*06:01</td>\n",
+       "      <td>0.065409</td>\n",
+       "      <td>0.035625</td>\n",
+       "      <td>0.091283</td>\n",
+       "      <td>0.063</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>DQB1*06:02</td>\n",
+       "      <td>0.071234</td>\n",
+       "      <td>0.03369</td>\n",
+       "      <td>0.089428</td>\n",
+       "      <td>0.061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>DQB1*06:03</td>\n",
+       "      <td>0.029325</td>\n",
+       "      <td>0.018317</td>\n",
+       "      <td>0.061218</td>\n",
+       "      <td>0.039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>DQB1*06:04</td>\n",
+       "      <td>0.018674</td>\n",
+       "      <td>0.009669</td>\n",
+       "      <td>0.042506</td>\n",
+       "      <td>0.026</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>DQB1*06:05</td>\n",
+       "      <td>0.001165</td>\n",
+       "      <td>0.000121</td>\n",
+       "      <td>0.009128</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>DQB1*06:07</td>\n",
+       "      <td>0.001743</td>\n",
+       "      <td>0.000073</td>\n",
+       "      <td>0.009962</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>DQB1*06:08</td>\n",
+       "      <td>0.001165</td>\n",
+       "      <td>0.000088</td>\n",
+       "      <td>0.008865</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>DQB1*06:09</td>\n",
+       "      <td>0.012848</td>\n",
+       "      <td>0.001863</td>\n",
+       "      <td>0.023532</td>\n",
+       "      <td>0.012</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        allele  allele_freq        lo        hi post_mean\n",
+       "0   DQB1*02:01     0.102965  0.069354   0.14193     0.107\n",
+       "1   DQB1*02:02     0.062476  0.025963  0.078963     0.052\n",
+       "2   DQB1*03:01     0.271881  0.220663  0.329699     0.275\n",
+       "3   DQB1*03:02     0.045532  0.022769  0.068847     0.045\n",
+       "4   DQB1*03:03     0.128528  0.066764  0.142278     0.103\n",
+       "5   DQB1*03:04     0.001752  0.000164  0.009574     0.004\n",
+       "6   DQB1*03:13     0.001752  0.000164  0.009965     0.004\n",
+       "7   DQB1*04:01     0.038527  0.016768  0.060056     0.038\n",
+       "8   DQB1*04:02     0.021780  0.013736   0.04914      0.03\n",
+       "9   DQB1*05:01     0.060791  0.034938   0.09162     0.062\n",
+       "10  DQB1*05:02     0.039710  0.021234  0.064176     0.042\n",
+       "11  DQB1*05:03     0.020403  0.004785  0.032304     0.018\n",
+       "12  DQB1*05:04     0.001170  0.000052  0.008706     0.004\n",
+       "13  DQB1*05:42     0.001170  0.000037  0.008818     0.004\n",
+       "14  DQB1*06:01     0.065409  0.035625  0.091283     0.063\n",
+       "15  DQB1*06:02     0.071234   0.03369  0.089428     0.061\n",
+       "16  DQB1*06:03     0.029325  0.018317  0.061218     0.039\n",
+       "17  DQB1*06:04     0.018674  0.009669  0.042506     0.026\n",
+       "18  DQB1*06:05     0.001165  0.000121  0.009128     0.004\n",
+       "19  DQB1*06:07     0.001743  0.000073  0.009962     0.004\n",
+       "20  DQB1*06:08     0.001165  0.000088  0.008865     0.004\n",
+       "21  DQB1*06:09     0.012848  0.001863  0.023532     0.012"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Calculate high density intervals\n",
+    "hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)\n",
+    "# Add to the combined allele frequency dataset\n",
+    "caf = pd.merge(caf, hdi, how=\"left\", on=\"allele\")\n",
+    "caf[['allele', 'allele_freq', 'lo','hi','post_mean']]"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Above, we have calculated the 95% high density credible interval and added it to the combined allele frequency dataset. Note that by setting the `credible_interval` argument you can calculate any credible interval.\n",
+    "\n",
+    "This has also added a column `post_mean` which is the mean of the posterior distribution for allele frequency estimated by the model. In general this is very similar to the `allele_freq` estimated by default. The difference is that it takes account of the variances mentioned before. However, the difference can become large when there is heterogeneity in the dataset, which we will demonstrate below."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# How heterogenity affects credible intervals\n",
+    "As we saw in the [multiple country example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb)\n",
+    "Guinea was an outlier in our Sub-Saharan Africa data. Let's see how this causes the default allele frequency estimate to differ from the one accounting for variance."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cameroon\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Cape+Verde\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Ghana\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Guinea\n",
+      "3 pages of results\n",
+      "Download complete\n",
+      "Guinea-Bissau\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Kenya\n",
+      "2 pages of results\n",
+      "Download complete\n",
+      "Sao+Tome+and+Principe\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Senegal\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "South+Africa\n",
+      "3 pages of results\n",
+      "Download complete\n",
+      "population               loci\n",
+      "South Africa Natal Zulu  A       0.935\n",
+      "Name: allele_freq, dtype: float64\n",
+      "1 studies have total allele frequency < 0.95\n",
+      "Uganda\n",
+      "1 pages of results\n",
+      "Download complete\n",
+      "Zimbabwe\n",
+      "1 pages of results\n",
+      "Download complete\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Download and combine country datasets\n",
+    "countries = ['Cameroon','Cape+Verde','Ghana','Guinea',\n",
+    "    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',\n",
+    "    'South+Africa','Uganda','Zimbabwe']\n",
+    "cafs = []\n",
+    "for country in countries:\n",
+    "    print(country)\n",
+    "    base_url = HLAfreq.makeURL(\n",
+    "        country, standard='s', locus=\"A\",\n",
+    "        resolution_pattern=\"bigger_equal_than\", resolution=2)\n",
+    "    aftab = HLAfreq.getAFdata(base_url)\n",
+    "    # Drop any incomplete studies\n",
+    "    aftab = HLAfreq.only_complete(aftab)\n",
+    "    # Ensure all alleles have the same resolution\n",
+    "    aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "    # Combine studies within country\n",
+    "    caf = HLAfreq.combineAF(aftab)\n",
+    "    # Add country name to dataset, this is used as `datasetID` going forward\n",
+    "    caf['country'] = country\n",
+    "    cafs.append(caf)\n",
+    "cafs = pd.concat(cafs, ignore_index=True)\n",
+    "international = HLAfreq.combineAF(cafs, datasetID='country')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
+       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:28&lt;00:00 Sampling 4 chains, 163 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>allele</th>\n",
+       "      <th>allele_freq</th>\n",
+       "      <th>lo</th>\n",
+       "      <th>hi</th>\n",
+       "      <th>post_mean</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A*01:01</td>\n",
+       "      <td>0.047888</td>\n",
+       "      <td>0.023436</td>\n",
+       "      <td>0.051125</td>\n",
+       "      <td>0.037</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>A*01:02</td>\n",
+       "      <td>0.005929</td>\n",
+       "      <td>0.003708</td>\n",
+       "      <td>0.015222</td>\n",
+       "      <td>0.009</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>A*01:03</td>\n",
+       "      <td>0.002433</td>\n",
+       "      <td>0.000601</td>\n",
+       "      <td>0.006494</td>\n",
+       "      <td>0.003</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>A*01:06</td>\n",
+       "      <td>0.000412</td>\n",
+       "      <td>0.000031</td>\n",
+       "      <td>0.00343</td>\n",
+       "      <td>0.001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>A*01:09</td>\n",
+       "      <td>0.000711</td>\n",
+       "      <td>0.000155</td>\n",
+       "      <td>0.00465</td>\n",
+       "      <td>0.002</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>A*69:01</td>\n",
+       "      <td>0.002848</td>\n",
+       "      <td>0.003376</td>\n",
+       "      <td>0.012452</td>\n",
+       "      <td>0.008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>81</th>\n",
+       "      <td>A*74:01</td>\n",
+       "      <td>0.044785</td>\n",
+       "      <td>0.029114</td>\n",
+       "      <td>0.059715</td>\n",
+       "      <td>0.043</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>82</th>\n",
+       "      <td>A*74:02</td>\n",
+       "      <td>0.000286</td>\n",
+       "      <td>0.000042</td>\n",
+       "      <td>0.003404</td>\n",
+       "      <td>0.001</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>83</th>\n",
+       "      <td>A*74:03</td>\n",
+       "      <td>0.004867</td>\n",
+       "      <td>0.000736</td>\n",
+       "      <td>0.007195</td>\n",
+       "      <td>0.004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>84</th>\n",
+       "      <td>A*80:01</td>\n",
+       "      <td>0.006667</td>\n",
+       "      <td>0.00722</td>\n",
+       "      <td>0.020887</td>\n",
+       "      <td>0.014</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>85 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     allele  allele_freq        lo        hi post_mean\n",
+       "0   A*01:01     0.047888  0.023436  0.051125     0.037\n",
+       "1   A*01:02     0.005929  0.003708  0.015222     0.009\n",
+       "2   A*01:03     0.002433  0.000601  0.006494     0.003\n",
+       "3   A*01:06     0.000412  0.000031   0.00343     0.001\n",
+       "4   A*01:09     0.000711  0.000155   0.00465     0.002\n",
+       "..      ...          ...       ...       ...       ...\n",
+       "80  A*69:01     0.002848  0.003376  0.012452     0.008\n",
+       "81  A*74:01     0.044785  0.029114  0.059715     0.043\n",
+       "82  A*74:02     0.000286  0.000042  0.003404     0.001\n",
+       "83  A*74:03     0.004867  0.000736  0.007195     0.004\n",
+       "84  A*80:01     0.006667   0.00722  0.020887     0.014\n",
+       "\n",
+       "[85 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Calculate high density intervals\n",
+    "hdi = HLAhdi.AFhdi(cafs, credible_interval=0.95, datasetID='country')\n",
+    "# Add to the combined allele frequency dataset\n",
+    "international = pd.merge(international, hdi, how=\"left\", on=\"allele\")\n",
+    "international[['allele', 'allele_freq', 'lo','hi','post_mean']]"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Below we plot default combined allele frequency estimate in orange and the individual country estimates in small blue points. The variance model results are plotted in black with a horizontal line representing the 95% credible interval and the mean of the posterior distribution as a verticle black bar.\n",
+    "\n",
+    "In this plot we can see the three alleles with anomalously high frequency estimates for Guinea by the three very high blue points. For these alleles we can also see that the default estimate (in orange) is away from the variance model's estimate and actually outside of the 95% credible intervals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(cafs.allele_freq, cafs.allele, marker=\".\")\n",
+    "plt.scatter(international.allele_freq, international.allele)\n",
+    "plt.scatter(international.post_mean, international.allele, color='black', marker=\"|\")\n",
+    "for interval in international.iterrows():\n",
+    "    plt.hlines(\n",
+    "        y=interval[1].allele,\n",
+    "        xmin=interval[1].lo,\n",
+    "        xmax=interval[1].hi,\n",
+    "        color='black'\n",
+    "    )\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This separating of the two allele frequency estimates is caused by the heterogeneity. The variance model is able to account for this variance and so the posterior mean is not as strongly affected by these outlier values.\n",
+    "\n",
+    "The default estimate (`allele_freq`) is simpler and faster to calculate. Whereas the variance model's `post_mean` accounts for variance and is less effected by outliers, but is slower and potentially suceptible to issues in convergence. Fortunately, in most cases they should be similar.\n",
+    "\n",
+    "In cases where the default `allele_freq` falls outside of the 95% interval, like here, we have to make a choice. You could say one of:\n",
+    "1. \"I want to capture the variance in the data\" and so use the variance model to estimate `post_mean`. \n",
+    "2. \"After looking carefully at the sample sizes and where those data points come from I think they are anomalies\" and so exclude those datasets and recalculate. Note that you would exclude the whole dataset (in this case Guniea) not merely the outlier alleles. The choice to exclude datasets could be based on small sample size (although small studies shouldn't have a large effect on the combined value), domain knowledge, or details of how that data was collected. These details are available on [allelefrequencies.net](http://www.allelefrequencies.net) if you look up the population.\n",
+    "3. \"After looking at the model validation plots I think the variance model has failed to converge on the correct answer\" and so use the default `allele_freq`. Or dive into `pymc` to try and fit a better model."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Model details\n",
+    "\n",
+    "This section describes the variance model in more detail as well as how to access the model and assess convergence.\n",
+    "\n",
+    "The variance model used to estiamte high posterior density interval and `post_mean` is a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).\n",
+    "\n",
+    "In brief, the global allele frequency is modelled as a Dirichlet distribution,\n",
+    "and each population (defined by `datasetID`) is a Dirichlet distribution draw from\n",
+    "the global Dirichlet distribution, and the observed allele count data of that\n",
+    "population is multinomial count data drawn from the population Dirichlet distribution.\n",
+    "\n",
+    "The observed allele frequencies are transformed into allele counts using `weights`.\n",
+    "The variability of population allele frequencies around the global mean is defined\n",
+    "by a latent, lognormal variable `conc`.\n",
+    "\n",
+    "## Fitting the model\n",
+    "If you suspect that the model is failing to converge you can fit the model and check it directly. The code to fit the model below is the same that `AFhdi()` uses internally. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+       "</style>\n"
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+      "text/plain": [
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      100.00% [8000/8000 00:28&lt;00:00 Sampling 4 chains, 138 divergences]\n",
+       "    </div>\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Format data and fit variance model\n",
+    "c_array, allele_names = HLAhdi._make_c_array(cafs, '2n', 'country')\n",
+    "idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Validating the model\n",
+    "Once you have fit the model you can validate it as you would any other PyMC model. A basic overview is available [here](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/pymc_overview.html#model-checking) and a more detailed check for biased parameters is described [here](https://www.pymc.io/projects/examples/en/latest/diagnostics_and_criticism/Diagnosing_biased_Inference_with_Divergences.html#diagnosing-with-divergences).\n",
+    "\n",
+    "Some basic checks are shown below. It's a good idea to check the `r_hat` values are close to 1. Higher `r_hat` values indicate that some chains have failed to converge and `pymc` will also give warnings for high values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sd</th>\n",
+       "      <th>hdi_3%</th>\n",
+       "      <th>hdi_97%</th>\n",
+       "      <th>mcse_mean</th>\n",
+       "      <th>mcse_sd</th>\n",
+       "      <th>ess_bulk</th>\n",
+       "      <th>ess_tail</th>\n",
+       "      <th>r_hat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>frac[0]</th>\n",
+       "      <td>0.037</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.023</td>\n",
+       "      <td>0.051</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5490.0</td>\n",
+       "      <td>2580.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[1]</th>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.015</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4089.0</td>\n",
+       "      <td>2460.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[2]</th>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5394.0</td>\n",
+       "      <td>1994.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[3]</th>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4160.0</td>\n",
+       "      <td>2185.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[4]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3872.0</td>\n",
+       "      <td>2148.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[81]</th>\n",
+       "      <td>0.043</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.029</td>\n",
+       "      <td>0.059</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5169.0</td>\n",
+       "      <td>2694.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[82]</th>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3996.0</td>\n",
+       "      <td>2170.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[83]</th>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.007</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4565.0</td>\n",
+       "      <td>2570.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[84]</th>\n",
+       "      <td>0.014</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.021</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3645.0</td>\n",
+       "      <td>2511.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>conc</th>\n",
+       "      <td>50.870</td>\n",
+       "      <td>4.441</td>\n",
+       "      <td>42.025</td>\n",
+       "      <td>58.678</td>\n",
+       "      <td>0.083</td>\n",
+       "      <td>0.059</td>\n",
+       "      <td>2854.0</td>\n",
+       "      <td>2962.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>86 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
+       "frac[0]    0.037  0.008   0.023    0.051      0.000    0.000    5490.0   \n",
+       "frac[1]    0.009  0.003   0.004    0.015      0.000    0.000    4089.0   \n",
+       "frac[2]    0.003  0.002   0.001    0.006      0.000    0.000    5394.0   \n",
+       "frac[3]    0.001  0.001   0.000    0.003      0.000    0.000    4160.0   \n",
+       "frac[4]    0.002  0.001   0.000    0.004      0.000    0.000    3872.0   \n",
+       "...          ...    ...     ...      ...        ...      ...       ...   \n",
+       "frac[81]   0.043  0.008   0.029    0.059      0.000    0.000    5169.0   \n",
+       "frac[82]   0.001  0.001   0.000    0.003      0.000    0.000    3996.0   \n",
+       "frac[83]   0.004  0.002   0.001    0.007      0.000    0.000    4565.0   \n",
+       "frac[84]   0.014  0.004   0.008    0.021      0.000    0.000    3645.0   \n",
+       "conc      50.870  4.441  42.025   58.678      0.083    0.059    2854.0   \n",
+       "\n",
+       "          ess_tail  r_hat  \n",
+       "frac[0]     2580.0    1.0  \n",
+       "frac[1]     2460.0    1.0  \n",
+       "frac[2]     1994.0    1.0  \n",
+       "frac[3]     2185.0    1.0  \n",
+       "frac[4]     2148.0    1.0  \n",
+       "...            ...    ...  \n",
+       "frac[81]    2694.0    1.0  \n",
+       "frac[82]    2170.0    1.0  \n",
+       "frac[83]    2570.0    1.0  \n",
+       "frac[84]    2511.0    1.0  \n",
+       "conc        2962.0    1.0  \n",
+       "\n",
+       "[86 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import arviz as az\n",
+    "az.summary(idata)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An energy plot can check that the sampler performed well, if it did the two distributions should be similar.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot: >"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "az.plot_energy(idata)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "Trace plots can also be used to check convergence and mixing. In the left hand plots we want the different chains to have converged to the same distributions. And in the right hand plot we want to see no trends or evidence of chains getting stuck.\n",
+    "\n",
+    "With large numbers of alleles you may have to increase the max_subplots to see all alleles and avoid warnings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/dwells/miniconda3/envs/hlatest/lib/python3.10/site-packages/arviz/plots/traceplot.py:217: UserWarning: rcParams['plot.max_subplots'] (20) is smaller than the number of variables to plot (86), generating only 20 plots\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([[<AxesSubplot: title={'center': 'frac\\n0'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n0'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n1'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n1'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n2'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n2'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n3'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n3'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n4'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n4'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n5'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n5'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n6'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n6'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n7'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n7'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n8'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n8'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n9'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n9'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n10'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n10'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n11'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n11'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n12'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n12'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n13'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n13'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n14'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n14'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n15'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n15'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n16'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n16'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n17'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n17'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n18'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n18'}>],\n",
+       "       [<AxesSubplot: title={'center': 'frac\\n19'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac\\n19'}>]], dtype=object)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x4000 with 40 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "az.plot_trace(idata, compact=False, combined=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "hlatest",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index 8a98518..a8b95e4 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -216,7 +216,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -238,7 +238,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -253,7 +253,7 @@
     }
    ],
    "source": [
-    "# Plot specific alleles and zoom in on frequencies\n",
+    "# Plot specific alleles\n",
     "# Select alleles to plot\n",
     "hifreq = international[international.allele_freq > 0.01].allele\n",
     "# Must be a list\n",
@@ -266,6 +266,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -274,6 +275,7 @@
     "It is also clear that the international average allele\n",
     "frequency for A\\*24:02 is being skewed by this country. We can view the\n",
     "`cafs` dataset to see which country this is, Guinea.\n",
+    "For more info on dealing with outliers and this skewing, see the [credible intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb).\n",
     "\n",
     "This method can\n",
     "also be applied to individual countries to identify studies which\n",
@@ -283,7 +285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -458,7 +460,7 @@
        "99                  Guinea  "
       ]
      },
-     "execution_count": 15,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -468,11 +470,12 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Weighting countries by population size\n",
-    "When combining allele frequencies across studies, larger studies are given more weight. This is handled by the `weights` parameter. (Specifically the `weights` is multiplied by the allele frequency to calculate the \"concentration\" of the Dirichlet distribution before adding the prior). By default `weights` is double the sample size as two alleles are measured for person sampled due to diploidy. However, alternative `weights` can be specified. The interpretation of the column used for `weights` is that $n$\n",
+    "When combining allele frequencies across studies, larger studies are given more weight. This is handled by the `weights` parameter. (Specifically the `weights` is multiplied by the allele frequency to calculate the \"concentration\" of the Dirichlet distribution before adding the prior). By default `weights` is double the sample size as two alleles are measured for each person sampled due to diploidy. However, alternative `weights` can be specified. The interpretation of the column used for `weights` is that $n$\n",
     "samples were observed with allele $x$.\n",
     "\n",
     "If estimating allele frequency for a region, it may be important to\n",
@@ -485,7 +488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -515,7 +518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -549,105 +552,6 @@
     "    datasetID='country')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Fitting model with PyMc, make take a few seconds\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Auto-assigning NUTS sampler...\n",
-      "Initializing NUTS using jitter+adapt_diag...\n",
-      "Multiprocess sampling (4 chains in 4 jobs)\n",
-      "NUTS: [frac, conc]\n"
-     ]
-    },
-    {
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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "HLAfreq.plotAF(\n",
-    "    international[international.allele.isin(hifreq)],\n",
-    "    cafs[cafs.allele.isin(hifreq)],\n",
-    "    datasetID='country',\n",
-    "    credible_interval=0.95)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index fa71604..3e06fdc 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -589,13 +589,14 @@ def plotAF(
     if credible_interval:
         assert not AFtab.empty, "AFtab is needed to calculate credible interval"
         from HLAfreq import HLAfreq_pymc as HLAhdi
-        print("Fitting model with PyMc, make take a few seconds")
+        print("Fitting model with PyMC, make take a few seconds")
         hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval)
-        for interval in hdi:
+        for interval in hdi.iterrows():
+            # .iterrows returns a index and data as a tuple for each row
             plt.hlines(
-                y = interval[2],
-                xmin = float(interval[0]),
-                xmax = float(interval[1]),
+                y = interval[1]['allele'],
+                xmin = interval[1]['lo'],
+                xmax = interval[1]['hi'],
                 color="black"
             )
     plt.grid(zorder=0)
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 04cf1c2..a073fe8 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -5,7 +5,7 @@
 import pandas as pd
 import HLAfreq
 
-def _make_c_array(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
+def _make_c_array(AFtab, weights="2n", datasetID="population"):
     df = AFtab.copy()
     df = HLAfreq.unmeasured_alleles(df, datasetID)
     try:
@@ -50,7 +50,7 @@ def _fit_Dirichlet_Multinomial(c_array):
     return idata
 
 def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
-    """Calculate high posterior density interval on combined allele frequency.
+    """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
     
     In brief, the global allele frequency is modelled as a Dirichlet distribution,
@@ -69,12 +69,15 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
         credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
 
     Returns:
-        np.array: Pairs of high density interval limits as a 2 by n array.
+        np.array: Pairs of high density interval limits, allele name, and posterior mean.
+            as a 4 by n array.
             In alphabetical order of alleles, regardless of input order.
             This way it matches the output of combineAF().
     """
-    c_array, allele_names = _make_c_array(AFtab, weights, datasetID, credible_interval)
+    c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
     idata = _fit_Dirichlet_Multinomial(c_array)
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
-    hdi = np.column_stack([hdi, allele_names])
-    return hdi
\ No newline at end of file
+    post_mean = az.summary(idata, var_names='frac')['mean']
+    post = pd.DataFrame([hdi[:,0], hdi[:,1], allele_names, post_mean]).T
+    post.columns = ['lo','hi','allele','post_mean']
+    return post
\ No newline at end of file

From 1e0ff536b8ace12461b95fd4892b774c69f6350f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 13:57:58 +0000
Subject: [PATCH 084/192] Update read me with CI info

---
 README.md | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/README.md b/README.md
index c9dcd56..032c072 100644
--- a/README.md
+++ b/README.md
@@ -18,8 +18,6 @@ default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-A note on credible intervals... **(to be written)**
-
 When selecting a panel of HLA alleles to represent a population,
 allele frequency is not the only thing to consider. Depending on
 the purpose of the panel, you should include a range of loci and
@@ -56,6 +54,7 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 - [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
 - [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
 - [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
+- [Credible intervals](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb)
 
 ## Docs
 For help on specific functions view the docstring, `help(function_name)`.

From 738a67d600af1b69ace8ada0680b91094b906f22 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 14:20:03 +0000
Subject: [PATCH 085/192] Allow prior specification for pymc models and plots

---
 src/HLAfreq/HLAfreq_pymc.py | 13 ++++++++-----
 1 file changed, 8 insertions(+), 5 deletions(-)

diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index a073fe8..b31fdd0 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -29,7 +29,7 @@ def _make_c_array(AFtab, weights="2n", datasetID="population"):
         assert math.isclose(a,b), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
     return c_array, allele_names
 
-def _fit_Dirichlet_Multinomial(c_array):
+def _fit_Dirichlet_Multinomial(c_array, prior=[]):
     # Number of populations
     n = c_array.shape[0]
     # number of alleles
@@ -39,9 +39,11 @@ def _fit_Dirichlet_Multinomial(c_array):
     # for the multinomial
     c_array = np.round(c_array)
     effective_samples = np.apply_along_axis(sum, 1, c_array)
-
+    if len(prior)==0:
+        prior = np.ones(k)
+    assert len(prior) == k, "For k alleles, prior must be length k"
     with pm.Model() as mod:
-        frac = pm.Dirichlet('frac', a=np.ones(k))
+        frac = pm.Dirichlet('frac', a=prior)
         conc = pm.Lognormal('conc', mu=1, sigma=1)
         y = pm.DirichletMultinomial('y', n=effective_samples, a=frac*conc, shape=(n,k), observed=c_array)
 
@@ -49,7 +51,7 @@ def _fit_Dirichlet_Multinomial(c_array):
         idata = pm.sample()
     return idata
 
-def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
+def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[]):
     """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
     
@@ -67,6 +69,7 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
         weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
         datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
         credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
+        prior (list, optional): Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
 
     Returns:
         np.array: Pairs of high density interval limits, allele name, and posterior mean.
@@ -75,7 +78,7 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95):
             This way it matches the output of combineAF().
     """
     c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
-    idata = _fit_Dirichlet_Multinomial(c_array)
+    idata = _fit_Dirichlet_Multinomial(c_array, prior)
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
     post_mean = az.summary(idata, var_names='frac')['mean']
     post = pd.DataFrame([hdi[:,0], hdi[:,1], allele_names, post_mean]).T

From 12aad0ff969aa0eb46cf3cb839f017f0576cffee Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 14:23:02 +0000
Subject: [PATCH 086/192] Update docs and remove docs/ from .gitignore

---
 .gitignore      |   1 -
 docs/HLAfreq.md | 195 ++++++++++++++++++++++++++----------------------
 2 files changed, 105 insertions(+), 91 deletions(-)

diff --git a/.gitignore b/.gitignore
index b6da47c..f1b1575 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,4 @@
 data/
-docs/
 writeup/
 *__pycache__/
 *.code-workspace
diff --git a/docs/HLAfreq.md b/docs/HLAfreq.md
index ca11030..a1048fc 100644
--- a/docs/HLAfreq.md
+++ b/docs/HLAfreq.md
@@ -1,6 +1,6 @@
 ---
 description: |
-    API documentation for modules: HLAfreq, HLAfreq.HLAfreq, HLAfreq.HLAfreq_data.
+    API documentation for modules: HLAfreq, HLAfreq.HLAfreq, HLAfreq.HLAfreq_data, HLAfreq.HLAfreq_pymc.
 
 lang: en
 
@@ -24,6 +24,7 @@ links-as-notes: true
 
 * [HLAfreq.HLAfreq](#HLAfreq.HLAfreq)
 * [HLAfreq.HLAfreq_data](#HLAfreq.HLAfreq_data)
+* [HLAfreq.HLAfreq_pymc](#HLAfreq.HLAfreq_pymc)
 
 
 
@@ -49,36 +50,6 @@ global HLA frequencies.
 
 
     
-### Function `AFci` {#HLAfreq.HLAfreq.AFci}
-
-
-
-    
-> `def AFci(caf, credible_interval=0.95)`
-
-
-Calculate credible interval for combined allele frequency table
-
-
-###### Args
-
-**```caf```** :&ensp;<code>pd.DataFrame</code>
-:   Table produced by combineAF()
-
-
-**```credible_interval```** :&ensp;<code>float</code>, optional
-:   The desired confidence interval. Defaults to 0.95.
-
-
-
-###### Returns
-
-<code>list</code>
-:   Lower and upper credible intervals as a list of tuples
-
-
-
-    
 ### Function `Npages` {#HLAfreq.HLAfreq.Npages}
 
 
@@ -161,40 +132,6 @@ Given the alpha vector defining a Dirichlet distribution calculate the a b value
 
 
     
-### Function `betaCI` {#HLAfreq.HLAfreq.betaCI}
-
-
-
-    
-> `def betaCI(a, b, credible_interval=0.95)`
-
-
-Calculat the central credible interval of a beta distribution
-
-
-###### Args
-
-**```a```** :&ensp;<code>float</code>
-:   Beta shape parameter <code>a</code>, i.e. the number of times the allele was observed.
-
-
-**```b```** :&ensp;<code>float</code>
-:   Beta shape parameter <code>b</code>, i.e. the number of times the allele was not observed.
-
-
-**```credible_interval```** :&ensp;<code>float</code>, optional
-:   The size of the credible interval requested. Defaults to 0.95.
-
-
-
-###### Returns
-
-<code>tuple</code>
-:   Lower and upper credible interval of beta distribution.
-
-
-
-    
 ### Function `check_resolution` {#HLAfreq.HLAfreq.check_resolution}
 
 
@@ -623,67 +560,75 @@ Generate a dataframe from a given html page
 
 
     
-### Function `plotAFprob` {#HLAfreq.HLAfreq.plotAFprob}
+### Function `plotAF` {#HLAfreq.HLAfreq.plotAF}
 
 
 
     
-> `def plotAFprob(caf=Empty DataFrame
+> `def plotAF(caf=Empty DataFrame
 Columns: []
 Index: [], AFtab=Empty DataFrame
 Columns: []
-Index: [], datasetID='population', concentration=[], log=False, psteps=1000, ncol=2, xmin=-0.05, xmax=1.05, ci=0.95, alleles=[])`
+Index: [], cols=['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'], datasetID='population', weights='2n', credible_interval=None)`
 
 
-Plot the posterior density function of all frequencies
-    for all alleles based on concentration for Dirichlet
-    distribution. Supply AFtab to add empirical values to plot.
+Plot combined allele frequencies, individual allele frequencies,
+and credible intervals on combined allele frequency estimates.
+Credible interval is only plotted if a value is given for <code>credible\_interval</code>.
+Credible interval is calculated using HLAfreq_pymc.AFhdi() and PyMc.
 
 
 ###### Args
 
 **```caf```** :&ensp;<code>pd.DataFrame</code>, optional
-:   Combined allele frequence data produced by combineAF(). Defaults to pd.DataFrame().
+:   Combined allele frequency estimates from HLAfreq.combineAF. Defaults to pd.DataFrame().
 
 
 **```AFtab```** :&ensp;<code>pd.DataFrame</code>, optional
-:   The uncombined allele frequency data used by combinedAF(). You must use the same dataframe as this function doesn't have the error checking that combineAF() has. Defaults to pd.DataFrame().
+:   Table of allele frequency data. Defaults to pd.DataFrame().
+
+
+**```cols```** :&ensp;<code>list</code>, optional
+:   List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
 
 
 **```datasetID```** :&ensp;<code>str</code>, optional
-:   The column used to define datasets. Defaults to "population".
+:   Column used to define separate datasets. Defaults to "population".
 
 
-**```concentration```** :&ensp;<code>pd.Series</code>, optional
-:   Dirichlet concentration parameters, if not set calculated as caf.alpha + caf.c. Defaults to False
+**```weights```** :&ensp;<code>str</code>, optional
+:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
 
 
-**```log```** :&ensp;<code>bool</code>, optional
-:   Plot log pdf instead of pdf? Defaults to False.
+**```credible_interval```** :&ensp;<code>float</code>, optional
+:   The credible interval to plot. Defaults to None.
 
 
-**```psteps```** :&ensp;<code>int</code>, optional
-:   Number of increments in pdf calculation, higher values make smoother plots. Defaults to 1000.
 
+    
+### Function `plot_prior` {#HLAfreq.HLAfreq.plot_prior}
 
-**```ncol```** :&ensp;<code>int</code>, optional
-:   How many columns to arrange subplots in. Defaults to 2.
 
 
-**```xmin```** :&ensp;<code>float</code>, optional
-:   Set x axis min. Defaults to -0.05.
+    
+> `def plot_prior(concentration, ncol=2, psteps=1000, labels='')`
 
 
-**```xmax```** :&ensp;<code>float</code>, optional
-:   Set x axis max. Defaults to 1.05.
+Plot probability density function for prior values.
 
 
-**```ci```** :&ensp;<code>float</code>, optional
-:   Central credible interval to plot. Set as 0 to hide. Defaults to 0.95.
+###### Args
+
+**```concentration```** :&ensp;<code>list</code>
+:   Vector of the prior Dirichlet concentration values.
 
 
-**```alleles```** :&ensp;<code>list</code>, optional
-:   List of alleles to plot. Plots all if none supplied. Defaults to [].
+**```ncol```** :&ensp;<code>int</code>, optional
+:   Number of columns. Defaults to 2.
+
+
+**```labels```** :&ensp;<code>list</code>, optional
+:   Labels for elements of concentration in the same order. Defaults to "".
 
 
 
@@ -804,5 +749,75 @@ Data loaders
 
 
 
+
+    
+# Module `HLAfreq.HLAfreq_pymc` {#HLAfreq.HLAfreq_pymc}
+
+
+
+
+
+
+    
+## Functions
+
+
+    
+### Function `AFhdi` {#HLAfreq.HLAfreq_pymc.AFhdi}
+
+
+
+    
+> `def AFhdi(AFtab, weights='2n', datasetID='population', credible_interval=0.95, prior=[])`
+
+
+Calculate mean and high posterior density interval on combined allele frequency.
+Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](<https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html>).
+
+In brief, the global allele frequency is modelled as a Dirichlet distribution,
+and each population (defined by <code>datasetID</code>) is a Dirichlet distribution draw from
+the global Dirichlet distribution, and the observed allele count data of that
+population is multinomial count data drawn from the population Dirichlet distribution.
+
+The observed allele frequencies are transformed into allele counts using <code>weights</code>.
+The variability of population allele frequencies around the global mean is defined
+by a latent, lognormal variable <code>conc</code>.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Table of allele frequency data
+
+
+**```weights```** :&ensp;<code>str</code>, optional
+:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   Unique identifier column for study. Defaults to 'population'.
+
+
+**```credible_interval```** :&ensp;<code>float</code>, optional
+:   The size of the credible interval requested. Defaults to 0.95.
+
+
+**```prior```** :&ensp;<code>list</code>, optional
+:   Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
+
+
+
+###### Returns
+
+<code>np.array</code>
+:   Pairs of high density interval limits, allele name, and posterior mean.
+    as a 4 by n array.
+    In alphabetical order of alleles, regardless of input order.
+    This way it matches the output of combineAF().
+
+
+
+
+
 -----
 Generated by *pdoc* 0.8.1 (<https://pdoc3.github.io>).

From 33c2df768aa481f568ae3056e9424cf0c5b5a5cc Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 14:46:01 +0000
Subject: [PATCH 087/192] Update paper code and add label to plotAF()

---
 examples/paper/basic_use_case.py | 4 ++--
 src/HLAfreq/HLAfreq.py           | 1 +
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
index 5207868..9f4869f 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/basic_use_case.py
@@ -1,11 +1,11 @@
 import matplotlib.pyplot as plt
-from HLAfreq import makeURL, getAFdata, combineAF, plotAFprob, population_coverage
+from HLAfreq import makeURL, getAFdata, combineAF, plotAF, population_coverage
 
 base_url = makeURL("Mongolia", standard="g", locus="DQB1")
 aftab = getAFdata(base_url)
 aftab.population.unique()
 caf = combineAF(aftab)
-plotAFprob(caf, aftab, ncol=2, xmin=-0.02, xmax=0.5)
+plotAF(caf, aftab)
 
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
 plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(population_coverage))
diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 3e06fdc..9024fdb 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -599,5 +599,6 @@ def plotAF(
                 xmax = interval[1]['hi'],
                 color="black"
             )
+    plt.xlabel("Allele frequency")
     plt.grid(zorder=0)
     plt.show()

From efc070faa911ff0b19c5a108e245934ce89821ac Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 16:29:46 +0000
Subject: [PATCH 088/192] Fix global PCA plot overlapping text

---
 examples/paper/globalPCA2.py | 60 ++++++++++++++++++++++++++++--------
 1 file changed, 47 insertions(+), 13 deletions(-)

diff --git a/examples/paper/globalPCA2.py b/examples/paper/globalPCA2.py
index d369912..72e29dc 100644
--- a/examples/paper/globalPCA2.py
+++ b/examples/paper/globalPCA2.py
@@ -25,10 +25,10 @@
 AFeatures['pca0'] = pca_embedding[:,0]
 AFeatures['pca1'] = pca_embedding[:,1]
 
-umapper = umap.UMAP(transform_seed=1234)
-umap_embedding = umapper.fit_transform(AFeatures.loc[:,'A*01:01':].values)
-AFeatures['umap0'] = umap_embedding[:,0]
-AFeatures['umap1'] = umap_embedding[:,1]
+# umapper = umap.UMAP(transform_seed=1234)
+# umap_embedding = umapper.fit_transform(AFeatures.loc[:,'A*01:01':].values)
+# AFeatures['umap0'] = umap_embedding[:,0]
+# AFeatures['umap1'] = umap_embedding[:,1]
 
 # Add region to countries
 AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
@@ -40,13 +40,43 @@
 
 # plt.style.use('fivethirtyeight')
 
+# Define offset values for each country label
+offset = dict(zip(AFeatures.country, [(0,0)]*AFeatures.shape[0]))
+# Customise offsets
+offset['Zimbabwe'] = (0,5)
+offset['United+States'] = (0,5)
+offset['Georgia'] = (0,5)
+offset['Germany'] = (0,5)
+offset['Italy'] = (0,-5)
+offset['Czech+Republic'] = (0,-4)
+offset['Poland'] = (0,-7)
+offset['France'] = (0,-2)
+offset['Bosnia+and+Herzegovina'] = (0,4)
+offset['Russia'] = (0,-5)
+offset['Ireland'] = (0,-5)
+offset['Netherlands'] = (0,-6)
+offset['Austria'] = (0,-7)
+offset['Romania'] = (0,4)
+offset['Wales'] = (0,-5)
+offset['Cameroon'] = (0,2)
+offset['Ghana'] = (0,-3)
+offset['United+Kingdom'] = (0,-4)
+offset['Sao+Tome+and+Principe'] = (0,-5)
+
+
 regions = AFeatures.largeRegion.unique()
 regions.sort()
 for region in regions:
     mask = AFeatures.largeRegion == region
     plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
     for i in AFeatures[mask].index:
-        plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['pca0','pca1']])
+        # Label each country
+        plt.annotate(
+            AFeatures.loc[i].country.replace("+", " "),
+            AFeatures.loc[i][['pca0','pca1']],
+            offset[AFeatures.loc[i].country],
+            textcoords="offset points",
+            fontsize=8)
 plt.legend()
 # Arrow shows change of Venezuela with prior
 plt.annotate(
@@ -55,13 +85,17 @@
     xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
     arrowprops=dict(arrowstyle="->")
     )
+# Open point to show updated Venezuela
+plt.scatter(vwp.pca0, vwp.pca1, color="tab:blue", facecolors="none")
 plt.xlabel('1st principal component'); plt.ylabel('2nd principal component')
-plt.show()
+plt.gcf().set_size_inches(10,10)
+plt.savefig('writeup/globalPCA.png')
+plt.close()
 
-for region in AFeatures.largeRegion.unique():
-    mask = AFeatures.largeRegion == region
-    plt.scatter(AFeatures.umap0[mask], AFeatures.umap1[mask], label=region)
-    for i in AFeatures[mask].index:
-        plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['umap0','umap1']])
-plt.legend()
-plt.show()
+# for region in AFeatures.largeRegion.unique():
+#     mask = AFeatures.largeRegion == region
+#     plt.scatter(AFeatures.umap0[mask], AFeatures.umap1[mask], label=region)
+#     for i in AFeatures[mask].index:
+#         plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['umap0','umap1']])
+# plt.legend()
+# plt.show()

From 9140645b9ceae2113e0045ba206040e053588c87 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 25 Jan 2023 16:29:57 +0000
Subject: [PATCH 089/192] add CI to basic use plot

---
 examples/paper/basic_use_case.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
index 9f4869f..c453090 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/basic_use_case.py
@@ -5,7 +5,7 @@
 aftab = getAFdata(base_url)
 aftab.population.unique()
 caf = combineAF(aftab)
-plotAF(caf, aftab)
+plotAF(caf, aftab, credible_interval=0.95)
 
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
 plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(population_coverage))

From 7806b62b16a7c9da907daafa8ffccb73b3935d2b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 9 Feb 2023 09:36:22 +0000
Subject: [PATCH 090/192] 0.0.1dev2 release Improve release workflow

---
 HLAfreq.egg-info/PKG-INFO                |  57 -----------------------
 HLAfreq.egg-info/SOURCES.txt             |  14 ------
 HLAfreq.egg-info/dependency_links.txt    |   1 -
 HLAfreq.egg-info/requires.txt            |   6 ---
 HLAfreq.egg-info/top_level.txt           |   1 -
 README.md                                |  15 +++++-
 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl | Bin 14842 -> 0 bytes
 dist/HLAfreq-0.0.1.dev0.tar.gz           | Bin 15839 -> 0 bytes
 dist/HLAfreq-0.0.1.dev1-py3-none-any.whl | Bin 15602 -> 0 bytes
 dist/HLAfreq-0.0.1.dev1.tar.gz           | Bin 17215 -> 0 bytes
 dist/HLAfreq-0.0.1.dev2-py3-none-any.whl | Bin 0 -> 18298 bytes
 dist/HLAfreq-0.0.1.dev2.tar.gz           | Bin 0 -> 19855 bytes
 setup.py                                 |   2 +-
 src/HLAfreq.egg-info/PKG-INFO            |   9 ++--
 src/HLAfreq.egg-info/SOURCES.txt         |   5 +-
 15 files changed, 24 insertions(+), 86 deletions(-)
 delete mode 100644 HLAfreq.egg-info/PKG-INFO
 delete mode 100644 HLAfreq.egg-info/SOURCES.txt
 delete mode 100644 HLAfreq.egg-info/dependency_links.txt
 delete mode 100644 HLAfreq.egg-info/requires.txt
 delete mode 100644 HLAfreq.egg-info/top_level.txt
 delete mode 100644 dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
 delete mode 100644 dist/HLAfreq-0.0.1.dev0.tar.gz
 delete mode 100644 dist/HLAfreq-0.0.1.dev1-py3-none-any.whl
 delete mode 100644 dist/HLAfreq-0.0.1.dev1.tar.gz
 create mode 100644 dist/HLAfreq-0.0.1.dev2-py3-none-any.whl
 create mode 100644 dist/HLAfreq-0.0.1.dev2.tar.gz

diff --git a/HLAfreq.egg-info/PKG-INFO b/HLAfreq.egg-info/PKG-INFO
deleted file mode 100644
index aee4b47..0000000
--- a/HLAfreq.egg-info/PKG-INFO
+++ /dev/null
@@ -1,57 +0,0 @@
-Metadata-Version: 2.1
-Name: HLAfreq
-Version: 0.0.1.dev0
-Summary: Download and combine HLA frequency data from multiple studies
-Home-page: https://github.com/Vaccitech/HLAfreq
-Author: David Wells
-Author-email: david.wells@vaccitech.co.uk
-Project-URL: Tracker, https://github.com/Vaccitech/HLAfreq/issues
-Classifier: Programming Language :: Python :: 3
-Classifier: Operating System :: OS Independent
-
-# HLAfreq
-
-The aim of this tool is to be able to estimate the HLA allele
-frequencies at large multi population scale, e.g. combine data from
-several studies within a country or combine countries.
-Allele frequency data from
-[allele frequencies.net](http://www.allelefrequencies.net/).
-This gives frequencies by population, which can be combined across
-studies. Estimates are combined by modelling allele frequency as a 
-Dirichlet distribution which defines the probability of drawing each
-allele. When combining studies are weighted by 2 x sample size by
-default. Sample size is doubled as each person in the study
-contributes two alleles. Alternative weightings can be used
-for example population size when averaging across countries.
-
-```
-import sys
-sys.path.append("/home/dwells/work/tools/scrapeAF/code")
-import scrapeAF
-```
-
-When selecting alleles to represent a population, all supertypes
-should be represented.
-
-When combining estimates of allele frequency larger samples should
-weigh more heavily. However, when combining estiamtes that disagree
-the uncertainty on the estimate should be larger than when combining
-equivalent samples that agree.
-
-When combining studies we must weight averages by sample size but
-when combining countries are we not better to weight by national population?
-Should sample size also have an effect?
-
-IEDB provide reference sets of HLA alleles designed to cover the
-majority of the "general population". However, all populations are
-not likely to be equally well covered by them. Using population
-specific allele frequencies we should be able to select more
-appropriate HLA sets. However, allele frequency is not the only
-determinent when selecting a pannel of alleles. The pannel must
-also contain representatives of commonly shared binding specificities
-(i.e., supertypes).
-
-# Dependencies
-scrapeAF
-umap
-maps
diff --git a/HLAfreq.egg-info/SOURCES.txt b/HLAfreq.egg-info/SOURCES.txt
deleted file mode 100644
index a5314ae..0000000
--- a/HLAfreq.egg-info/SOURCES.txt
+++ /dev/null
@@ -1,14 +0,0 @@
-MANIFEST.in
-README.md
-setup.py
-HLAfreq/HLAfreq.py
-HLAfreq/HLAfreq_data.py
-HLAfreq/__init__.py
-HLAfreq.egg-info/PKG-INFO
-HLAfreq.egg-info/SOURCES.txt
-HLAfreq.egg-info/dependency_links.txt
-HLAfreq.egg-info/requires.txt
-HLAfreq.egg-info/top_level.txt
-HLAfreq/data/HLA1supertypes_Sidney2008.csv
-HLAfreq/data/countries.csv
-data/HLA1supertypes_Sidney2008.csv
\ No newline at end of file
diff --git a/HLAfreq.egg-info/dependency_links.txt b/HLAfreq.egg-info/dependency_links.txt
deleted file mode 100644
index 8b13789..0000000
--- a/HLAfreq.egg-info/dependency_links.txt
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/HLAfreq.egg-info/requires.txt b/HLAfreq.egg-info/requires.txt
deleted file mode 100644
index db17ae5..0000000
--- a/HLAfreq.egg-info/requires.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-bs4
-requests
-pandas
-numpy
-matplotlib
-scipy
diff --git a/HLAfreq.egg-info/top_level.txt b/HLAfreq.egg-info/top_level.txt
deleted file mode 100644
index b260130..0000000
--- a/HLAfreq.egg-info/top_level.txt
+++ /dev/null
@@ -1 +0,0 @@
-HLAfreq
diff --git a/README.md b/README.md
index 032c072..bbb5c85 100644
--- a/README.md
+++ b/README.md
@@ -63,8 +63,19 @@ created with pdoc3 in pdf mode.
 
 <!-- ## Developer notes
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
-Build with `pythom -m build`.
-Run tests `pytest` -->
+
+Run tests `pytest` 
+
+# Clear old build info
+rm -rf build dist *.egg-info
+
+Build with `python -m build`.
+
+twine check dist/*
+
+# Upload to test pypi
+twine upload --repository testpypi dist/*
+-->
 
 ## Citation
 *In prep.*
diff --git a/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev0-py3-none-any.whl
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diff --git a/setup.py b/setup.py
index ac0b840..987e488 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.1dev1",
+    version="0.0.1dev2",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index afaa5d5..e7840ed 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: HLAfreq
-Version: 0.0.1.dev1
+Version: 0.0.1.dev2
 Summary: Download and combine HLA frequency data from multiple studies
 Home-page: https://github.com/Vaccitech/HLAfreq
 Author: David Wells
@@ -9,12 +9,16 @@ Project-URL: Tracker, https://github.com/Vaccitech/HLAfreq/issues
 Classifier: Programming Language :: Python :: 3
 Classifier: Operating System :: OS Independent
 Description-Content-Type: text/markdown
+License-File: LICENSE
 
 # HLAfreq
 
 `HLAfreq` allows you to download and combine HLA allele
 frequencies from multiple datasets, e.g. combine data from
 several studies within a country or combine countries.
+Useful for studying regional diversity in immune genes
+and, when paired with epitope prediction, estimating a population's
+ability to mount an immune response to specific epitopes.
 
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
@@ -27,8 +31,6 @@ default. Sample size is doubled as each person in the study
 contributes two alleles. Alternative weightings can be used
 for example population size when averaging across countries.
 
-A note on credible intervals... **(to be written)**
-
 When selecting a panel of HLA alleles to represent a population,
 allele frequency is not the only thing to consider. Depending on
 the purpose of the panel, you should include a range of loci and
@@ -65,6 +67,7 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 - [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
 - [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
 - [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
+- [Credible intervals](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb)
 
 ## Docs
 For help on specific functions view the docstring, `help(function_name)`.
diff --git a/src/HLAfreq.egg-info/SOURCES.txt b/src/HLAfreq.egg-info/SOURCES.txt
index 8984b0c..f5e2d3a 100644
--- a/src/HLAfreq.egg-info/SOURCES.txt
+++ b/src/HLAfreq.egg-info/SOURCES.txt
@@ -1,9 +1,11 @@
+LICENSE
 MANIFEST.in
 README.md
 pyproject.toml
 setup.py
 src/HLAfreq/HLAfreq.py
 src/HLAfreq/HLAfreq_data.py
+src/HLAfreq/HLAfreq_pymc.py
 src/HLAfreq/__init__.py
 src/HLAfreq.egg-info/PKG-INFO
 src/HLAfreq.egg-info/SOURCES.txt
@@ -11,4 +13,5 @@ src/HLAfreq.egg-info/dependency_links.txt
 src/HLAfreq.egg-info/requires.txt
 src/HLAfreq.egg-info/top_level.txt
 src/HLAfreq/data/HLA1supertypes_Sidney2008.csv
-src/HLAfreq/data/countries.csv
\ No newline at end of file
+src/HLAfreq/data/countries.csv
+tests/test_single_country_caf.py
\ No newline at end of file

From 1fa707d3d6e4b747c9c23198daf4e490c1c09045 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 9 Feb 2023 10:23:33 +0000
Subject: [PATCH 091/192] Add more dev instructions to readme

---
 README.md | 11 ++++++++++-
 1 file changed, 10 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index bbb5c85..258a74d 100644
--- a/README.md
+++ b/README.md
@@ -62,12 +62,15 @@ Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/bl
 created with pdoc3 in pdf mode.
 
 <!-- ## Developer notes
+# Install in dev mode
+pip install -e HLAfreq
+
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
 
 Run tests `pytest` 
 
 # Clear old build info
-rm -rf build dist *.egg-info
+rm -rf build dist src/*.egg-info 
 
 Build with `python -m build`.
 
@@ -75,6 +78,12 @@ twine check dist/*
 
 # Upload to test pypi
 twine upload --repository testpypi dist/*
+
+# Install from test pypi
+python3 -m pip install --extra-index-url https://test.pypi.org/simple/ HLAfreq
+
+# Upload to pypi
+twine upload dist/*
 -->
 
 ## Citation

From 2df29e1b8ca7538984a0837407b4f09e6667bb2d Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 9 Feb 2023 10:24:15 +0000
Subject: [PATCH 092/192] 0.0.1dev3 add pymc to required

---
 dist/HLAfreq-0.0.1.dev2.tar.gz                | Bin 19855 -> 0 bytes
 ...hl => HLAfreq-0.0.1.dev3-py3-none-any.whl} | Bin 18298 -> 18444 bytes
 dist/HLAfreq-0.0.1.dev3.tar.gz                | Bin 0 -> 20207 bytes
 setup.py                                      |   3 +-
 src/HLAfreq.egg-info/PKG-INFO                 |  26 ++++++++++++++++--
 src/HLAfreq.egg-info/requires.txt             |   1 +
 6 files changed, 26 insertions(+), 4 deletions(-)
 delete mode 100644 dist/HLAfreq-0.0.1.dev2.tar.gz
 rename dist/{HLAfreq-0.0.1.dev2-py3-none-any.whl => HLAfreq-0.0.1.dev3-py3-none-any.whl} (80%)
 create mode 100644 dist/HLAfreq-0.0.1.dev3.tar.gz

diff --git a/dist/HLAfreq-0.0.1.dev2.tar.gz b/dist/HLAfreq-0.0.1.dev2.tar.gz
deleted file mode 100644
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diff --git a/dist/HLAfreq-0.0.1.dev2-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev3-py3-none-any.whl
similarity index 80%
rename from dist/HLAfreq-0.0.1.dev2-py3-none-any.whl
rename to dist/HLAfreq-0.0.1.dev3-py3-none-any.whl
index 8ec6f191d0834c635fdc0a907b1afdfed2ed9aac..b371265ad8235f4a4f31029a33b116f1d904c26a 100644
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literal 0
HcmV?d00001

diff --git a/setup.py b/setup.py
index 987e488..f6aaa0b 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.1dev2",
+    version="0.0.1dev3",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
@@ -19,6 +19,7 @@
         'numpy',
         'matplotlib',
         'scipy',
+        'pymc'
     ],
     classifiers=[
     "Programming Language :: Python :: 3",
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index e7840ed..8cea7ce 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: HLAfreq
-Version: 0.0.1.dev2
+Version: 0.0.1.dev3
 Summary: Download and combine HLA frequency data from multiple studies
 Home-page: https://github.com/Vaccitech/HLAfreq
 Author: David Wells
@@ -75,9 +75,29 @@ Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/bl
 created with pdoc3 in pdf mode.
 
 <!-- ## Developer notes
+# Install in dev mode
+pip install -e HLAfreq
+
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
-Build with `pythom -m build`.
-Run tests `pytest` -->
+
+Run tests `pytest` 
+
+# Clear old build info
+rm -rf build dist src/*.egg-info 
+
+Build with `python -m build`.
+
+twine check dist/*
+
+# Upload to test pypi
+twine upload --repository testpypi dist/*
+
+# Install from test pypi
+python3 -m pip install --extra-index-url https://test.pypi.org/simple/ HLAfreq
+
+# Upload to pypi
+twine upload dist/*
+-->
 
 ## Citation
 *In prep.*
diff --git a/src/HLAfreq.egg-info/requires.txt b/src/HLAfreq.egg-info/requires.txt
index db17ae5..baff9c3 100644
--- a/src/HLAfreq.egg-info/requires.txt
+++ b/src/HLAfreq.egg-info/requires.txt
@@ -4,3 +4,4 @@ pandas
 numpy
 matplotlib
 scipy
+pymc

From e20139a2da0bb5b33cbc55026b9cc38ff925976a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 23 Feb 2023 15:28:00 +0000
Subject: [PATCH 093/192] Compare default and compound model estimates

Warn if they disagree.
Also lets you specify the priors on the conc in the compound model
---
 src/HLAfreq/HLAfreq.py      |  4 +++-
 src/HLAfreq/HLAfreq_pymc.py | 35 +++++++++++++++++++++++++++++------
 2 files changed, 32 insertions(+), 7 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 9024fdb..94ad174 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -546,6 +546,8 @@ def plotAF(
     datasetID="population",
     weights = "2n",
     credible_interval=None,
+    conc_mu=1,
+    conc_sigma=1
     ):
     """Plot combined allele frequencies, individual allele frequencies,
     and credible intervals on combined allele frequency estimates.
@@ -590,7 +592,7 @@ def plotAF(
         assert not AFtab.empty, "AFtab is needed to calculate credible interval"
         from HLAfreq import HLAfreq_pymc as HLAhdi
         print("Fitting model with PyMC, make take a few seconds")
-        hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval)
+        hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval, conc_mu=conc_mu, conc_sigma=conc_sigma)
         for interval in hdi.iterrows():
             # .iterrows returns a index and data as a tuple for each row
             plt.hlines(
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index b31fdd0..7ba0917 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -29,7 +29,7 @@ def _make_c_array(AFtab, weights="2n", datasetID="population"):
         assert math.isclose(a,b), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
     return c_array, allele_names
 
-def _fit_Dirichlet_Multinomial(c_array, prior=[]):
+def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
     # Number of populations
     n = c_array.shape[0]
     # number of alleles
@@ -40,18 +40,18 @@ def _fit_Dirichlet_Multinomial(c_array, prior=[]):
     c_array = np.round(c_array)
     effective_samples = np.apply_along_axis(sum, 1, c_array)
     if len(prior)==0:
-        prior = np.ones(k)
+        prior = HLAfreq.default_prior(k)
     assert len(prior) == k, "For k alleles, prior must be length k"
     with pm.Model() as mod:
         frac = pm.Dirichlet('frac', a=prior)
-        conc = pm.Lognormal('conc', mu=1, sigma=1)
+        conc = pm.Lognormal('conc', mu=conc_mu, sigma=conc_sigma)
         y = pm.DirichletMultinomial('y', n=effective_samples, a=frac*conc, shape=(n,k), observed=c_array)
 
     with mod:
         idata = pm.sample()
     return idata
 
-def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[]):
+def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True):
     """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
     
@@ -70,6 +70,9 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, p
         datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
         credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
         prior (list, optional): Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
+        conc_mu (float, optional): Mean to parameterise lognormal distribution of `conc` prior. Defaults to 1.
+        conc_sigma (float, optional): Standard deviation to parameterise lognormal distribution of `conc` prior. Defaults to 1.
+        compare_models (bool, optional): Check that default estimated allele_freq is within compound model estimated credible intervals. Defaults to True.
 
     Returns:
         np.array: Pairs of high density interval limits, allele name, and posterior mean.
@@ -78,9 +81,29 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, p
             This way it matches the output of combineAF().
     """
     c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
-    idata = _fit_Dirichlet_Multinomial(c_array, prior)
+    idata = _fit_Dirichlet_Multinomial(c_array, prior, conc_mu=conc_mu, conc_sigma=conc_sigma)
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
     post_mean = az.summary(idata, var_names='frac')['mean']
     post = pd.DataFrame([hdi[:,0], hdi[:,1], allele_names, post_mean]).T
     post.columns = ['lo','hi','allele','post_mean']
-    return post
\ No newline at end of file
+    if compare_models:
+        compare_estimates(AFtab, post)
+    return post
+
+def compare_estimates(AFtab, hdi):
+    """Does the defaul estimate of `allele_freq` sit within the compound
+    model's estimated credible intervals? If not, print warnings.
+
+    Args:
+        AFtab (pd.DataFrame): Table of allele frequency data
+        hdi (np.array): Pairs of high density interval limits, allele name, and posterior mean from compound model.
+    """
+    caf = HLAfreq.combineAF(AFtab)
+    caf = pd.merge(caf, hdi, how="left", on="allele")
+    mask = (caf.allele_freq > caf.lo) & (caf.allele_freq < caf.hi)
+    if mask.sum() > 0:
+        print()
+        print("WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!")
+        print("There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb")
+        print("If you have set `credible_interval` to < 0.95, this may be a non-issue.")
+    

From cbf11467cb314f0571bec61f379d436eeaa88ec2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 23 Feb 2023 15:40:32 +0000
Subject: [PATCH 094/192] AFplot takes hdi rather than calculating CI

---
 src/HLAfreq/HLAfreq.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 94ad174..e24fe36 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -545,14 +545,14 @@ def plotAF(
     cols = list(mcolors.TABLEAU_COLORS.keys()),
     datasetID="population",
     weights = "2n",
-    credible_interval=None,
+    hdi=pd.DataFrame(),
     conc_mu=1,
     conc_sigma=1
     ):
     """Plot combined allele frequencies, individual allele frequencies,
     and credible intervals on combined allele frequency estimates.
-    Credible interval is only plotted if a value is given for `credible_interval`.
-    Credible interval is calculated using HLAfreq_pymc.AFhdi() and PyMc.
+    Credible interval is only plotted if a value is given for `hdi`.
+    The plotted Credible interval is whatever was passed to HLAfreq_pymc.AFhdi() when calculating hdi.
 
     Args:
         caf (pd.DataFrame, optional): Combined allele frequency estimates from HLAfreq.combineAF. Defaults to pd.DataFrame().
@@ -560,7 +560,7 @@ def plotAF(
         cols (list, optional): List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
         datasetID (str, optional): Column used to define separate datasets. Defaults to "population".
         weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-        credible_interval (float, optional): The credible interval to plot. Defaults to None.
+        hdi (float, optional): The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
     """
     # Plot allele frequency for each dataset
     if not AFtab.empty:
@@ -588,11 +588,11 @@ def plotAF(
             zorder=3
             )
     # Plot high density interval
-    if credible_interval:
-        assert not AFtab.empty, "AFtab is needed to calculate credible interval"
-        from HLAfreq import HLAfreq_pymc as HLAhdi
-        print("Fitting model with PyMC, make take a few seconds")
-        hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval, conc_mu=conc_mu, conc_sigma=conc_sigma)
+    if not hdi.empty:
+        # assert not AFtab.empty, "AFtab is needed to calculate credible interval"
+        # from HLAfreq import HLAfreq_pymc as HLAhdi
+        # print("Fitting model with PyMC, make take a few seconds")
+        # hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval, conc_mu=conc_mu, conc_sigma=conc_sigma)
         for interval in hdi.iterrows():
             # .iterrows returns a index and data as a tuple for each row
             plt.hlines(

From f682316c35770fc29728fa8a8071ea60ed9b2e6b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 6 Mar 2023 10:31:29 +0000
Subject: [PATCH 095/192] Improved examples on CI and priors

perks prior and single country outlier example
---
 examples/credible_intervals.ipynb  | 1347 +++++++++++++++++-----------
 examples/working_with_priors.ipynb |  184 +++-
 2 files changed, 1006 insertions(+), 525 deletions(-)

diff --git a/examples/credible_intervals.ipynb b/examples/credible_intervals.ipynb
index c1495c5..3be97a1 100644
--- a/examples/credible_intervals.ipynb
+++ b/examples/credible_intervals.ipynb
@@ -73,54 +73,11 @@
      "text": [
       "Auto-assigning NUTS sampler...\n",
       "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
       "Multiprocess sampling (4 chains in 4 jobs)\n",
       "NUTS: [frac, conc]\n"
      ]
     },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "    <div>\n",
-       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      100.00% [8000/8000 00:06&lt;00:00 Sampling 4 chains, 2 divergences]\n",
-       "    </div>\n",
-       "    "
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stderr",
      "output_type": "stream",
@@ -161,176 +118,176 @@
        "      <th>0</th>\n",
        "      <td>DQB1*02:01</td>\n",
        "      <td>0.102965</td>\n",
-       "      <td>0.069354</td>\n",
-       "      <td>0.14193</td>\n",
+       "      <td>0.070885</td>\n",
+       "      <td>0.141614</td>\n",
        "      <td>0.107</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>DQB1*02:02</td>\n",
        "      <td>0.062476</td>\n",
-       "      <td>0.025963</td>\n",
-       "      <td>0.078963</td>\n",
+       "      <td>0.026928</td>\n",
+       "      <td>0.080378</td>\n",
        "      <td>0.052</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>DQB1*03:01</td>\n",
        "      <td>0.271881</td>\n",
-       "      <td>0.220663</td>\n",
-       "      <td>0.329699</td>\n",
-       "      <td>0.275</td>\n",
+       "      <td>0.216031</td>\n",
+       "      <td>0.325208</td>\n",
+       "      <td>0.274</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>DQB1*03:02</td>\n",
        "      <td>0.045532</td>\n",
-       "      <td>0.022769</td>\n",
-       "      <td>0.068847</td>\n",
-       "      <td>0.045</td>\n",
+       "      <td>0.023916</td>\n",
+       "      <td>0.069979</td>\n",
+       "      <td>0.044</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>DQB1*03:03</td>\n",
        "      <td>0.128528</td>\n",
-       "      <td>0.066764</td>\n",
-       "      <td>0.142278</td>\n",
-       "      <td>0.103</td>\n",
+       "      <td>0.065484</td>\n",
+       "      <td>0.140824</td>\n",
+       "      <td>0.102</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>DQB1*03:04</td>\n",
        "      <td>0.001752</td>\n",
-       "      <td>0.000164</td>\n",
-       "      <td>0.009574</td>\n",
+       "      <td>0.000079</td>\n",
+       "      <td>0.010115</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>DQB1*03:13</td>\n",
        "      <td>0.001752</td>\n",
-       "      <td>0.000164</td>\n",
-       "      <td>0.009965</td>\n",
+       "      <td>0.000117</td>\n",
+       "      <td>0.010007</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>DQB1*04:01</td>\n",
        "      <td>0.038527</td>\n",
-       "      <td>0.016768</td>\n",
-       "      <td>0.060056</td>\n",
+       "      <td>0.016878</td>\n",
+       "      <td>0.059678</td>\n",
        "      <td>0.038</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>DQB1*04:02</td>\n",
        "      <td>0.021780</td>\n",
-       "      <td>0.013736</td>\n",
-       "      <td>0.04914</td>\n",
-       "      <td>0.03</td>\n",
+       "      <td>0.012336</td>\n",
+       "      <td>0.048523</td>\n",
+       "      <td>0.031</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>DQB1*05:01</td>\n",
        "      <td>0.060791</td>\n",
-       "      <td>0.034938</td>\n",
-       "      <td>0.09162</td>\n",
+       "      <td>0.035718</td>\n",
+       "      <td>0.09095</td>\n",
        "      <td>0.062</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>DQB1*05:02</td>\n",
        "      <td>0.039710</td>\n",
-       "      <td>0.021234</td>\n",
-       "      <td>0.064176</td>\n",
+       "      <td>0.020024</td>\n",
+       "      <td>0.065927</td>\n",
        "      <td>0.042</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>DQB1*05:03</td>\n",
        "      <td>0.020403</td>\n",
-       "      <td>0.004785</td>\n",
-       "      <td>0.032304</td>\n",
+       "      <td>0.00555</td>\n",
+       "      <td>0.033167</td>\n",
        "      <td>0.018</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td>DQB1*05:04</td>\n",
        "      <td>0.001170</td>\n",
-       "      <td>0.000052</td>\n",
-       "      <td>0.008706</td>\n",
+       "      <td>0.000059</td>\n",
+       "      <td>0.008448</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td>DQB1*05:42</td>\n",
        "      <td>0.001170</td>\n",
-       "      <td>0.000037</td>\n",
-       "      <td>0.008818</td>\n",
+       "      <td>0.000095</td>\n",
+       "      <td>0.008946</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>DQB1*06:01</td>\n",
        "      <td>0.065409</td>\n",
-       "      <td>0.035625</td>\n",
-       "      <td>0.091283</td>\n",
+       "      <td>0.03638</td>\n",
+       "      <td>0.091338</td>\n",
        "      <td>0.063</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td>DQB1*06:02</td>\n",
        "      <td>0.071234</td>\n",
-       "      <td>0.03369</td>\n",
-       "      <td>0.089428</td>\n",
+       "      <td>0.03162</td>\n",
+       "      <td>0.088836</td>\n",
        "      <td>0.061</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td>DQB1*06:03</td>\n",
        "      <td>0.029325</td>\n",
-       "      <td>0.018317</td>\n",
-       "      <td>0.061218</td>\n",
-       "      <td>0.039</td>\n",
+       "      <td>0.018884</td>\n",
+       "      <td>0.062921</td>\n",
+       "      <td>0.04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td>DQB1*06:04</td>\n",
        "      <td>0.018674</td>\n",
-       "      <td>0.009669</td>\n",
-       "      <td>0.042506</td>\n",
+       "      <td>0.010062</td>\n",
+       "      <td>0.04377</td>\n",
        "      <td>0.026</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
        "      <td>DQB1*06:05</td>\n",
        "      <td>0.001165</td>\n",
-       "      <td>0.000121</td>\n",
-       "      <td>0.009128</td>\n",
+       "      <td>0.00005</td>\n",
+       "      <td>0.008732</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td>DQB1*06:07</td>\n",
        "      <td>0.001743</td>\n",
-       "      <td>0.000073</td>\n",
-       "      <td>0.009962</td>\n",
+       "      <td>0.000112</td>\n",
+       "      <td>0.009819</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
        "      <td>DQB1*06:08</td>\n",
        "      <td>0.001165</td>\n",
-       "      <td>0.000088</td>\n",
-       "      <td>0.008865</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>0.008881</td>\n",
        "      <td>0.004</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
        "      <td>DQB1*06:09</td>\n",
        "      <td>0.012848</td>\n",
-       "      <td>0.001863</td>\n",
-       "      <td>0.023532</td>\n",
+       "      <td>0.001486</td>\n",
+       "      <td>0.023908</td>\n",
        "      <td>0.012</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -339,28 +296,28 @@
       ],
       "text/plain": [
        "        allele  allele_freq        lo        hi post_mean\n",
-       "0   DQB1*02:01     0.102965  0.069354   0.14193     0.107\n",
-       "1   DQB1*02:02     0.062476  0.025963  0.078963     0.052\n",
-       "2   DQB1*03:01     0.271881  0.220663  0.329699     0.275\n",
-       "3   DQB1*03:02     0.045532  0.022769  0.068847     0.045\n",
-       "4   DQB1*03:03     0.128528  0.066764  0.142278     0.103\n",
-       "5   DQB1*03:04     0.001752  0.000164  0.009574     0.004\n",
-       "6   DQB1*03:13     0.001752  0.000164  0.009965     0.004\n",
-       "7   DQB1*04:01     0.038527  0.016768  0.060056     0.038\n",
-       "8   DQB1*04:02     0.021780  0.013736   0.04914      0.03\n",
-       "9   DQB1*05:01     0.060791  0.034938   0.09162     0.062\n",
-       "10  DQB1*05:02     0.039710  0.021234  0.064176     0.042\n",
-       "11  DQB1*05:03     0.020403  0.004785  0.032304     0.018\n",
-       "12  DQB1*05:04     0.001170  0.000052  0.008706     0.004\n",
-       "13  DQB1*05:42     0.001170  0.000037  0.008818     0.004\n",
-       "14  DQB1*06:01     0.065409  0.035625  0.091283     0.063\n",
-       "15  DQB1*06:02     0.071234   0.03369  0.089428     0.061\n",
-       "16  DQB1*06:03     0.029325  0.018317  0.061218     0.039\n",
-       "17  DQB1*06:04     0.018674  0.009669  0.042506     0.026\n",
-       "18  DQB1*06:05     0.001165  0.000121  0.009128     0.004\n",
-       "19  DQB1*06:07     0.001743  0.000073  0.009962     0.004\n",
-       "20  DQB1*06:08     0.001165  0.000088  0.008865     0.004\n",
-       "21  DQB1*06:09     0.012848  0.001863  0.023532     0.012"
+       "0   DQB1*02:01     0.102965  0.070885  0.141614     0.107\n",
+       "1   DQB1*02:02     0.062476  0.026928  0.080378     0.052\n",
+       "2   DQB1*03:01     0.271881  0.216031  0.325208     0.274\n",
+       "3   DQB1*03:02     0.045532  0.023916  0.069979     0.044\n",
+       "4   DQB1*03:03     0.128528  0.065484  0.140824     0.102\n",
+       "5   DQB1*03:04     0.001752  0.000079  0.010115     0.004\n",
+       "6   DQB1*03:13     0.001752  0.000117  0.010007     0.004\n",
+       "7   DQB1*04:01     0.038527  0.016878  0.059678     0.038\n",
+       "8   DQB1*04:02     0.021780  0.012336  0.048523     0.031\n",
+       "9   DQB1*05:01     0.060791  0.035718   0.09095     0.062\n",
+       "10  DQB1*05:02     0.039710  0.020024  0.065927     0.042\n",
+       "11  DQB1*05:03     0.020403   0.00555  0.033167     0.018\n",
+       "12  DQB1*05:04     0.001170  0.000059  0.008448     0.004\n",
+       "13  DQB1*05:42     0.001170  0.000095  0.008946     0.004\n",
+       "14  DQB1*06:01     0.065409   0.03638  0.091338     0.063\n",
+       "15  DQB1*06:02     0.071234   0.03162  0.088836     0.061\n",
+       "16  DQB1*06:03     0.029325  0.018884  0.062921      0.04\n",
+       "17  DQB1*06:04     0.018674  0.010062   0.04377     0.026\n",
+       "18  DQB1*06:05     0.001165   0.00005  0.008732     0.004\n",
+       "19  DQB1*06:07     0.001743  0.000112  0.009819     0.004\n",
+       "20  DQB1*06:08     0.001165  0.000012  0.008881     0.004\n",
+       "21  DQB1*06:09     0.012848  0.001486  0.023908     0.012"
       ]
      },
      "execution_count": 3,
@@ -376,6 +333,26 @@
     "caf[['allele', 'allele_freq', 'lo','hi','post_mean']]"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "HLAfreq.plotAF(caf, aftab, hdi=hdi)"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -383,7 +360,7 @@
    "source": [
     "Above, we have calculated the 95% high density credible interval and added it to the combined allele frequency dataset. Note that by setting the `credible_interval` argument you can calculate any credible interval.\n",
     "\n",
-    "This has also added a column `post_mean` which is the mean of the posterior distribution for allele frequency estimated by the model. In general this is very similar to the `allele_freq` estimated by default. The difference is that it takes account of the variances mentioned before. However, the difference can become large when there is heterogeneity in the dataset, which we will demonstrate below."
+    "This has also added a column `post_mean` which is the mean of the posterior distribution for allele frequency estimated by the variance model. In general this is very similar to the `allele_freq` estimated by default. The difference is that it takes account of the variances mentioned before. However, in some cases the difference can become large and a warning is produced. Below we discuss when this can happen and what to do about it."
    ]
   },
   {
@@ -391,151 +368,123 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# How heterogenity affects credible intervals\n",
-    "As we saw in the [multiple country example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb)\n",
-    "Guinea was an outlier in our Sub-Saharan Africa data. Let's see how this causes the default allele frequency estimate to differ from the one accounting for variance."
+    "# Explaining differences between `allele_freq` and `post_mean`\n",
+    "`allele_freq` and `post_mean` are two different ways of estimating the average allele frequency for a set of studies. Because they are estimating the same thing they are very similar in most cases. However, in some situations they can diverge, in this section we discuss why that happens and what to do about it.\n",
+    "\n",
+    "In no particular order the main causes are:\n",
+    "- Inappropriate prior\n",
+    "- Heterogeneity in estimated frequency for a single allele\n",
+    "- Issues with model convergence\n",
+    "\n",
+    "## Inappropriate prior\n",
+    "Sometimes the `post_mean` and credible intervals are clearly too low. We have seen this when there are many alleles (usually >100) compared to the amount of data and many of these alleles are very rare. This is covered in more detail in the [working with priors example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb). Fortunately the fix is quite simple; instead of the default prior (a vector of $1$ s) use a vector of $1/k$ s where $k$ is the number of alleles. In simulations this resolved this issue even in extreme cases. Alternatively the default estimate of `allele_freq` is far more robust to this issue."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# When k is the number of alleles\n",
+    "prior=[1/k]*k"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Heterogeneity in estimated frequency for a single allele\n",
+    "Below we calculate and plot the allele frequencies for DQB1 in Italy. DQB1*02:01 at the bottom of the plot shows that one study reports a much higher frequency than the others. This draws the `allele_freq` estimate (shown as a black open point) up and away from the other studies. This is analagous to an outlier skewing a mean. Whereas the credible intervals (the black horizontal line) and `post_mean` estimates remain centered on the majority of studies."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cameroon\n",
-      "2 pages of results\n",
-      "Download complete\n",
-      "Cape+Verde\n",
-      "1 pages of results\n",
-      "Download complete\n",
-      "Ghana\n",
-      "1 pages of results\n",
-      "Download complete\n",
-      "Guinea\n",
-      "3 pages of results\n",
-      "Download complete\n",
-      "Guinea-Bissau\n",
-      "2 pages of results\n",
-      "Download complete\n",
-      "Kenya\n",
-      "2 pages of results\n",
-      "Download complete\n",
-      "Sao+Tome+and+Principe\n",
-      "1 pages of results\n",
-      "Download complete\n",
-      "Senegal\n",
-      "1 pages of results\n",
-      "Download complete\n",
-      "South+Africa\n",
       "3 pages of results\n",
       "Download complete\n",
-      "population               loci\n",
-      "South Africa Natal Zulu  A       0.935\n",
+      "population   loci\n",
+      "Italy pop 4  DQB1    0.574\n",
       "Name: allele_freq, dtype: float64\n",
       "1 studies have total allele frequency < 0.95\n",
-      "Uganda\n",
-      "1 pages of results\n",
-      "Download complete\n",
-      "Zimbabwe\n",
-      "1 pages of results\n",
-      "Download complete\n"
+      "2    206\n",
+      "3      1\n",
+      "Name: allele, dtype: int64\n",
+      "Multiple resolutions in AFtab. Fix with decrease_resolution()\n"
      ]
-    }
-   ],
-   "source": [
-    "# Download and combine country datasets\n",
-    "countries = ['Cameroon','Cape+Verde','Ghana','Guinea',\n",
-    "    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',\n",
-    "    'South+Africa','Uganda','Zimbabwe']\n",
-    "cafs = []\n",
-    "for country in countries:\n",
-    "    print(country)\n",
-    "    base_url = HLAfreq.makeURL(\n",
-    "        country, standard='s', locus=\"A\",\n",
-    "        resolution_pattern=\"bigger_equal_than\", resolution=2)\n",
-    "    aftab = HLAfreq.getAFdata(base_url)\n",
-    "    # Drop any incomplete studies\n",
-    "    aftab = HLAfreq.only_complete(aftab)\n",
-    "    # Ensure all alleles have the same resolution\n",
-    "    aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
-    "    # Combine studies within country\n",
-    "    caf = HLAfreq.combineAF(aftab)\n",
-    "    # Add country name to dataset, this is used as `datasetID` going forward\n",
-    "    caf['country'] = country\n",
-    "    cafs.append(caf)\n",
-    "cafs = pd.concat(cafs, ignore_index=True)\n",
-    "international = HLAfreq.combineAF(cafs, datasetID='country')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
       "Auto-assigning NUTS sampler...\n",
       "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
       "Multiprocess sampling (4 chains in 4 jobs)\n",
       "NUTS: [frac, conc]\n"
      ]
     },
     {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
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-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 11 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!\n",
+      "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb\n",
+      "If you have set `credible_interval` to < 0.95, this may be a non-issue.\n"
+     ]
     },
     {
      "data": {
-      "text/html": [
-       "\n",
-       "    <div>\n",
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-       "      100.00% [8000/8000 00:28&lt;00:00 Sampling 4 chains, 163 divergences]\n",
-       "    </div>\n",
-       "    "
-      ],
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",
       "text/plain": [
-       "<IPython.core.display.HTML object>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n"
-     ]
-    },
+    }
+   ],
+   "source": [
+    "base_url = HLAfreq.makeURL(\"Italy\", locus=\"DQB1\")\n",
+    "aftab = HLAfreq.getAFdata(base_url)\n",
+    "aftab = HLAfreq.only_complete(aftab)\n",
+    "HLAfreq.check_resolution(aftab)\n",
+    "aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "caf = HLAfreq.combineAF(aftab)\n",
+    "hdi = HLAhdi.AFhdi(aftab,credible_interval=0.95)\n",
+    "HLAfreq.plotAF(caf, aftab, hdi=hdi)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this case `allele_freq` and `post_mean` diverge because by modelling the sampling variance `post_mean` (and credible intervals) can better estimate the country allele frequency without being overly influenced by unusual studies.\n",
+    "\n",
+    "What to do about this difference depends on your study. The `post_mean` estimate is probably the better estimate of average allele frequency for these datasets but it is important to check these datasets to make sure they are relevent to your study population. Below we look at each study estimate for DQB1*02:01."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
     {
      "data": {
       "text/html": [
@@ -558,134 +507,109 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>allele</th>\n",
+       "      <th>loci</th>\n",
+       "      <th>population</th>\n",
        "      <th>allele_freq</th>\n",
-       "      <th>lo</th>\n",
-       "      <th>hi</th>\n",
-       "      <th>post_mean</th>\n",
+       "      <th>sample_size</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>A*01:01</td>\n",
-       "      <td>0.047888</td>\n",
-       "      <td>0.023436</td>\n",
-       "      <td>0.051125</td>\n",
-       "      <td>0.037</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>A*01:02</td>\n",
-       "      <td>0.005929</td>\n",
-       "      <td>0.003708</td>\n",
-       "      <td>0.015222</td>\n",
-       "      <td>0.009</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>A*01:03</td>\n",
-       "      <td>0.002433</td>\n",
-       "      <td>0.000601</td>\n",
-       "      <td>0.006494</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Germany DKMS - Italy minority</td>\n",
+       "      <td>0.1898</td>\n",
+       "      <td>1159</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>A*01:06</td>\n",
-       "      <td>0.000412</td>\n",
-       "      <td>0.000031</td>\n",
-       "      <td>0.00343</td>\n",
-       "      <td>0.001</td>\n",
+       "      <th>17</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy Bergamo</td>\n",
+       "      <td>0.0910</td>\n",
+       "      <td>101</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>A*01:09</td>\n",
-       "      <td>0.000711</td>\n",
-       "      <td>0.000155</td>\n",
-       "      <td>0.00465</td>\n",
-       "      <td>0.002</td>\n",
+       "      <th>54</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy Central</td>\n",
+       "      <td>0.1730</td>\n",
+       "      <td>380</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>69</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy North pop 3</td>\n",
+       "      <td>0.0730</td>\n",
+       "      <td>97</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>80</th>\n",
-       "      <td>A*69:01</td>\n",
-       "      <td>0.002848</td>\n",
-       "      <td>0.003376</td>\n",
-       "      <td>0.012452</td>\n",
-       "      <td>0.008</td>\n",
+       "      <th>102</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy Rome</td>\n",
+       "      <td>0.1200</td>\n",
+       "      <td>100</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>81</th>\n",
-       "      <td>A*74:01</td>\n",
-       "      <td>0.044785</td>\n",
-       "      <td>0.029114</td>\n",
-       "      <td>0.059715</td>\n",
-       "      <td>0.043</td>\n",
+       "      <th>144</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy Sardinia pop2</td>\n",
+       "      <td>0.5900</td>\n",
+       "      <td>1129</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>82</th>\n",
-       "      <td>A*74:02</td>\n",
-       "      <td>0.000286</td>\n",
-       "      <td>0.000042</td>\n",
-       "      <td>0.003404</td>\n",
-       "      <td>0.001</td>\n",
+       "      <th>159</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy pop 2</td>\n",
+       "      <td>0.1980</td>\n",
+       "      <td>53</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>A*74:03</td>\n",
-       "      <td>0.004867</td>\n",
-       "      <td>0.000736</td>\n",
-       "      <td>0.007195</td>\n",
-       "      <td>0.004</td>\n",
+       "      <th>171</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy pop 3</td>\n",
+       "      <td>0.2300</td>\n",
+       "      <td>179</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>84</th>\n",
-       "      <td>A*80:01</td>\n",
-       "      <td>0.006667</td>\n",
-       "      <td>0.00722</td>\n",
-       "      <td>0.020887</td>\n",
-       "      <td>0.014</td>\n",
+       "      <th>185</th>\n",
+       "      <td>DQB1*02:01</td>\n",
+       "      <td>DQB1</td>\n",
+       "      <td>Italy pop 5</td>\n",
+       "      <td>0.0780</td>\n",
+       "      <td>975</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>85 rows × 5 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "     allele  allele_freq        lo        hi post_mean\n",
-       "0   A*01:01     0.047888  0.023436  0.051125     0.037\n",
-       "1   A*01:02     0.005929  0.003708  0.015222     0.009\n",
-       "2   A*01:03     0.002433  0.000601  0.006494     0.003\n",
-       "3   A*01:06     0.000412  0.000031   0.00343     0.001\n",
-       "4   A*01:09     0.000711  0.000155   0.00465     0.002\n",
-       "..      ...          ...       ...       ...       ...\n",
-       "80  A*69:01     0.002848  0.003376  0.012452     0.008\n",
-       "81  A*74:01     0.044785  0.029114  0.059715     0.043\n",
-       "82  A*74:02     0.000286  0.000042  0.003404     0.001\n",
-       "83  A*74:03     0.004867  0.000736  0.007195     0.004\n",
-       "84  A*80:01     0.006667   0.00722  0.020887     0.014\n",
-       "\n",
-       "[85 rows x 5 columns]"
+       "         allele  loci                     population  allele_freq  sample_size\n",
+       "0    DQB1*02:01  DQB1  Germany DKMS - Italy minority       0.1898         1159\n",
+       "17   DQB1*02:01  DQB1                  Italy Bergamo       0.0910          101\n",
+       "54   DQB1*02:01  DQB1                  Italy Central       0.1730          380\n",
+       "69   DQB1*02:01  DQB1              Italy North pop 3       0.0730           97\n",
+       "102  DQB1*02:01  DQB1                     Italy Rome       0.1200          100\n",
+       "144  DQB1*02:01  DQB1            Italy Sardinia pop2       0.5900         1129\n",
+       "159  DQB1*02:01  DQB1                    Italy pop 2       0.1980           53\n",
+       "171  DQB1*02:01  DQB1                    Italy pop 3       0.2300          179\n",
+       "185  DQB1*02:01  DQB1                    Italy pop 5       0.0780          975"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# Calculate high density intervals\n",
-    "hdi = HLAhdi.AFhdi(cafs, credible_interval=0.95, datasetID='country')\n",
-    "# Add to the combined allele frequency dataset\n",
-    "international = pd.merge(international, hdi, how=\"left\", on=\"allele\")\n",
-    "international[['allele', 'allele_freq', 'lo','hi','post_mean']]"
+    "aftab[aftab.allele==\"DQB1*02:01\"]"
    ]
   },
   {
@@ -693,39 +617,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Below we plot default combined allele frequency estimate in orange and the individual country estimates in small blue points. The variance model results are plotted in black with a horizontal line representing the 95% credible interval and the mean of the posterior distribution as a verticle black bar.\n",
-    "\n",
-    "In this plot we can see the three alleles with anomalously high frequency estimates for Guinea by the three very high blue points. For these alleles we can also see that the default estimate (in orange) is away from the variance model's estimate and actually outside of the 95% credible intervals."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.scatter(cafs.allele_freq, cafs.allele, marker=\".\")\n",
-    "plt.scatter(international.allele_freq, international.allele)\n",
-    "plt.scatter(international.post_mean, international.allele, color='black', marker=\"|\")\n",
-    "for interval in international.iterrows():\n",
-    "    plt.hlines(\n",
-    "        y=interval[1].allele,\n",
-    "        xmin=interval[1].lo,\n",
-    "        xmax=interval[1].hi,\n",
-    "        color='black'\n",
-    "    )\n",
-    "plt.show()"
+    "The high frequency estimate comes from the island population of Sardinia rather than mainland Italy. Depending on your study question you might choose to remove some studies and recalculate estimates. Note that you should remove the entire study, not just the alleles with different frequencies. Another study you might remove is Germany DKMS-Italy minority, as these are registered bone marrow donors in Germany who assigned their origin as Italy. Details about how data was collected are available on [allelefrequencies.net](http://www.allelefrequencies.net) if you look up the population."
    ]
   },
   {
@@ -733,14 +625,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This separating of the two allele frequency estimates is caused by the heterogeneity. The variance model is able to account for this variance and so the posterior mean is not as strongly affected by these outlier values.\n",
-    "\n",
-    "The default estimate (`allele_freq`) is simpler and faster to calculate. Whereas the variance model's `post_mean` accounts for variance and is less effected by outliers, but is slower and potentially suceptible to issues in convergence. Fortunately, in most cases they should be similar.\n",
+    "## Issues with model convergence\n",
+    "If the model fails to converge the `post_mean` and credible interval estimates should not be used. Fortunately this appears to be rare and we have not observed it. However, if it does happen you could either use the default `allele_freq`, or dive into `pymc` to try and fit a better model.\n",
     "\n",
-    "In cases where the default `allele_freq` falls outside of the 95% interval, like here, we have to make a choice. You could say one of:\n",
-    "1. \"I want to capture the variance in the data\" and so use the variance model to estimate `post_mean`. \n",
-    "2. \"After looking carefully at the sample sizes and where those data points come from I think they are anomalies\" and so exclude those datasets and recalculate. Note that you would exclude the whole dataset (in this case Guniea) not merely the outlier alleles. The choice to exclude datasets could be based on small sample size (although small studies shouldn't have a large effect on the combined value), domain knowledge, or details of how that data was collected. These details are available on [allelefrequencies.net](http://www.allelefrequencies.net) if you look up the population.\n",
-    "3. \"After looking at the model validation plots I think the variance model has failed to converge on the correct answer\" and so use the default `allele_freq`. Or dive into `pymc` to try and fit a better model."
+    "The following sections describe diagnosing convergence issues and details of the model itself."
    ]
   },
   {
@@ -769,7 +657,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -778,65 +666,22 @@
      "text": [
       "Auto-assigning NUTS sampler...\n",
       "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
       "Multiprocess sampling (4 chains in 4 jobs)\n",
       "NUTS: [frac, conc]\n"
      ]
     },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "    <div>\n",
-       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      100.00% [8000/8000 00:28&lt;00:00 Sampling 4 chains, 138 divergences]\n",
-       "    </div>\n",
-       "    "
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n"
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 12 seconds.\n"
      ]
     }
    ],
    "source": [
     "# Format data and fit variance model\n",
-    "c_array, allele_names = HLAhdi._make_c_array(cafs, '2n', 'country')\n",
+    "c_array, allele_names = HLAhdi._make_c_array(aftab)\n",
     "idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)"
    ]
   },
@@ -846,14 +691,14 @@
    "metadata": {},
    "source": [
     "## Validating the model\n",
-    "Once you have fit the model you can validate it as you would any other PyMC model. A basic overview is available [here](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/pymc_overview.html#model-checking) and a more detailed check for biased parameters is described [here](https://www.pymc.io/projects/examples/en/latest/diagnostics_and_criticism/Diagnosing_biased_Inference_with_Divergences.html#diagnosing-with-divergences).\n",
+    "Once you have fit the model you can validate it as you would any other PyMC model, in particular I recommend [posterior predictive checks](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/posterior_predictive.html) which can show that your estimates are being overly influenced by the prior as can happen with small datasets and large numbers of alleles. A basic overview is available [here](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/pymc_overview.html#model-checking) and a more detailed check for biased parameters is described [here](https://www.pymc.io/projects/examples/en/latest/diagnostics_and_criticism/Diagnosing_biased_Inference_with_Divergences.html#diagnosing-with-divergences).\n",
     "\n",
     "Some basic checks are shown below. It's a good idea to check the `r_hat` values are close to 1. Higher `r_hat` values indicate that some chains have failed to converge and `pymc` will also give warnings for high values."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -891,172 +736,645 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>frac[0]</th>\n",
-       "      <td>0.037</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>0.023</td>\n",
-       "      <td>0.051</td>\n",
+       "      <td>0.144</td>\n",
+       "      <td>0.025</td>\n",
+       "      <td>0.095</td>\n",
+       "      <td>0.189</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>5490.0</td>\n",
-       "      <td>2580.0</td>\n",
+       "      <td>5064.0</td>\n",
+       "      <td>2570.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>frac[1]</th>\n",
-       "      <td>0.009</td>\n",
-       "      <td>0.003</td>\n",
-       "      <td>0.004</td>\n",
-       "      <td>0.015</td>\n",
+       "      <td>0.020</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.007</td>\n",
+       "      <td>0.034</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>4089.0</td>\n",
-       "      <td>2460.0</td>\n",
+       "      <td>4900.0</td>\n",
+       "      <td>2553.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>frac[2]</th>\n",
        "      <td>0.003</td>\n",
        "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.006</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.008</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>5394.0</td>\n",
-       "      <td>1994.0</td>\n",
+       "      <td>4228.0</td>\n",
+       "      <td>2307.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>frac[3]</th>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.003</td>\n",
+       "      <td>0.209</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>0.152</td>\n",
+       "      <td>0.264</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>4160.0</td>\n",
-       "      <td>2185.0</td>\n",
+       "      <td>4433.0</td>\n",
+       "      <td>2760.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>frac[4]</th>\n",
-       "      <td>0.002</td>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>0.004</td>\n",
+       "      <td>0.072</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>0.042</td>\n",
+       "      <td>0.104</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>3872.0</td>\n",
-       "      <td>2148.0</td>\n",
+       "      <td>5285.0</td>\n",
+       "      <td>2477.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>frac[5]</th>\n",
+       "      <td>0.042</td>\n",
+       "      <td>0.011</td>\n",
+       "      <td>0.021</td>\n",
+       "      <td>0.063</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4996.0</td>\n",
+       "      <td>2143.0</td>\n",
+       "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>frac[81]</th>\n",
-       "      <td>0.043</td>\n",
-       "      <td>0.008</td>\n",
-       "      <td>0.029</td>\n",
-       "      <td>0.059</td>\n",
+       "      <th>frac[6]</th>\n",
+       "      <td>0.015</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.025</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>5169.0</td>\n",
-       "      <td>2694.0</td>\n",
+       "      <td>4635.0</td>\n",
+       "      <td>2491.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>frac[82]</th>\n",
-       "      <td>0.001</td>\n",
-       "      <td>0.001</td>\n",
+       "      <th>frac[7]</th>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.015</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
+       "      <td>4582.0</td>\n",
+       "      <td>2966.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[8]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2501.0</td>\n",
+       "      <td>1628.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[9]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2900.0</td>\n",
+       "      <td>1691.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[10]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2636.0</td>\n",
+       "      <td>1445.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[11]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3434.0</td>\n",
+       "      <td>1832.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[12]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2833.0</td>\n",
+       "      <td>1737.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[13]</th>\n",
        "      <td>0.003</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.007</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>3996.0</td>\n",
-       "      <td>2170.0</td>\n",
+       "      <td>4053.0</td>\n",
+       "      <td>2244.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>frac[83]</th>\n",
+       "      <th>frac[14]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2968.0</td>\n",
+       "      <td>1520.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[15]</th>\n",
+       "      <td>0.002</td>\n",
        "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2586.0</td>\n",
+       "      <td>1530.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[16]</th>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3245.0</td>\n",
+       "      <td>1888.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[17]</th>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.003</td>\n",
        "      <td>0.001</td>\n",
+       "      <td>0.011</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3413.0</td>\n",
+       "      <td>2071.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[18]</th>\n",
+       "      <td>0.040</td>\n",
+       "      <td>0.011</td>\n",
+       "      <td>0.021</td>\n",
+       "      <td>0.062</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4816.0</td>\n",
+       "      <td>2444.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[19]</th>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.007</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>4565.0</td>\n",
-       "      <td>2570.0</td>\n",
+       "      <td>3833.0</td>\n",
+       "      <td>1695.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>frac[84]</th>\n",
-       "      <td>0.014</td>\n",
-       "      <td>0.004</td>\n",
+       "      <th>frac[20]</th>\n",
+       "      <td>0.089</td>\n",
+       "      <td>0.019</td>\n",
+       "      <td>0.055</td>\n",
+       "      <td>0.123</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5406.0</td>\n",
+       "      <td>2574.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[21]</th>\n",
+       "      <td>0.070</td>\n",
+       "      <td>0.016</td>\n",
+       "      <td>0.042</td>\n",
+       "      <td>0.101</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5408.0</td>\n",
+       "      <td>2315.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[22]</th>\n",
+       "      <td>0.052</td>\n",
+       "      <td>0.013</td>\n",
+       "      <td>0.029</td>\n",
+       "      <td>0.077</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5539.0</td>\n",
+       "      <td>2855.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[23]</th>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.010</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3347.0</td>\n",
+       "      <td>1889.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[24]</th>\n",
+       "      <td>0.027</td>\n",
        "      <td>0.008</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.043</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3708.0</td>\n",
+       "      <td>2691.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[25]</th>\n",
+       "      <td>0.048</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>0.071</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>5204.0</td>\n",
+       "      <td>2544.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[26]</th>\n",
+       "      <td>0.049</td>\n",
+       "      <td>0.013</td>\n",
+       "      <td>0.026</td>\n",
+       "      <td>0.072</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4751.0</td>\n",
+       "      <td>2326.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[27]</th>\n",
+       "      <td>0.044</td>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.022</td>\n",
+       "      <td>0.066</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>4116.0</td>\n",
+       "      <td>2295.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[28]</th>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3708.0</td>\n",
+       "      <td>2002.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[29]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2600.0</td>\n",
+       "      <td>1636.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[30]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2956.0</td>\n",
+       "      <td>1951.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[31]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3457.0</td>\n",
+       "      <td>2407.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[32]</th>\n",
+       "      <td>0.012</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.004</td>\n",
        "      <td>0.021</td>\n",
        "      <td>0.000</td>\n",
        "      <td>0.000</td>\n",
-       "      <td>3645.0</td>\n",
-       "      <td>2511.0</td>\n",
+       "      <td>3938.0</td>\n",
+       "      <td>2234.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[33]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2976.0</td>\n",
+       "      <td>1941.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[34]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3412.0</td>\n",
+       "      <td>1919.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[35]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2827.0</td>\n",
+       "      <td>1542.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[36]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3072.0</td>\n",
+       "      <td>1448.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[37]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2261.0</td>\n",
+       "      <td>1217.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[38]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2664.0</td>\n",
+       "      <td>1623.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[39]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3466.0</td>\n",
+       "      <td>2163.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[40]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3012.0</td>\n",
+       "      <td>1648.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[41]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3740.0</td>\n",
+       "      <td>2475.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[42]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>2703.0</td>\n",
+       "      <td>1464.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>frac[43]</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>3380.0</td>\n",
+       "      <td>2648.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>conc</th>\n",
-       "      <td>50.870</td>\n",
-       "      <td>4.441</td>\n",
-       "      <td>42.025</td>\n",
-       "      <td>58.678</td>\n",
-       "      <td>0.083</td>\n",
-       "      <td>0.059</td>\n",
-       "      <td>2854.0</td>\n",
-       "      <td>2962.0</td>\n",
+       "      <td>19.339</td>\n",
+       "      <td>3.001</td>\n",
+       "      <td>13.982</td>\n",
+       "      <td>25.118</td>\n",
+       "      <td>0.054</td>\n",
+       "      <td>0.038</td>\n",
+       "      <td>3001.0</td>\n",
+       "      <td>2386.0</td>\n",
        "      <td>1.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>86 rows × 9 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "            mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
-       "frac[0]    0.037  0.008   0.023    0.051      0.000    0.000    5490.0   \n",
-       "frac[1]    0.009  0.003   0.004    0.015      0.000    0.000    4089.0   \n",
-       "frac[2]    0.003  0.002   0.001    0.006      0.000    0.000    5394.0   \n",
-       "frac[3]    0.001  0.001   0.000    0.003      0.000    0.000    4160.0   \n",
-       "frac[4]    0.002  0.001   0.000    0.004      0.000    0.000    3872.0   \n",
-       "...          ...    ...     ...      ...        ...      ...       ...   \n",
-       "frac[81]   0.043  0.008   0.029    0.059      0.000    0.000    5169.0   \n",
-       "frac[82]   0.001  0.001   0.000    0.003      0.000    0.000    3996.0   \n",
-       "frac[83]   0.004  0.002   0.001    0.007      0.000    0.000    4565.0   \n",
-       "frac[84]   0.014  0.004   0.008    0.021      0.000    0.000    3645.0   \n",
-       "conc      50.870  4.441  42.025   58.678      0.083    0.059    2854.0   \n",
+       "frac[0]    0.144  0.025   0.095    0.189      0.000    0.000    5064.0   \n",
+       "frac[1]    0.020  0.008   0.007    0.034      0.000    0.000    4900.0   \n",
+       "frac[2]    0.003  0.002   0.000    0.008      0.000    0.000    4228.0   \n",
+       "frac[3]    0.209  0.030   0.152    0.264      0.000    0.000    4433.0   \n",
+       "frac[4]    0.072  0.017   0.042    0.104      0.000    0.000    5285.0   \n",
+       "frac[5]    0.042  0.011   0.021    0.063      0.000    0.000    4996.0   \n",
+       "frac[6]    0.015  0.006   0.005    0.025      0.000    0.000    4635.0   \n",
+       "frac[7]    0.008  0.004   0.002    0.015      0.000    0.000    4582.0   \n",
+       "frac[8]    0.002  0.002   0.000    0.005      0.000    0.000    2501.0   \n",
+       "frac[9]    0.002  0.002   0.000    0.004      0.000    0.000    2900.0   \n",
+       "frac[10]   0.002  0.002   0.000    0.005      0.000    0.000    2636.0   \n",
+       "frac[11]   0.002  0.002   0.000    0.005      0.000    0.000    3434.0   \n",
+       "frac[12]   0.002  0.002   0.000    0.004      0.000    0.000    2833.0   \n",
+       "frac[13]   0.003  0.002   0.000    0.007      0.000    0.000    4053.0   \n",
+       "frac[14]   0.002  0.002   0.000    0.004      0.000    0.000    2968.0   \n",
+       "frac[15]   0.002  0.002   0.000    0.005      0.000    0.000    2586.0   \n",
+       "frac[16]   0.003  0.002   0.000    0.008      0.000    0.000    3245.0   \n",
+       "frac[17]   0.005  0.003   0.001    0.011      0.000    0.000    3413.0   \n",
+       "frac[18]   0.040  0.011   0.021    0.062      0.000    0.000    4816.0   \n",
+       "frac[19]   0.003  0.002   0.000    0.007      0.000    0.000    3833.0   \n",
+       "frac[20]   0.089  0.019   0.055    0.123      0.000    0.000    5406.0   \n",
+       "frac[21]   0.070  0.016   0.042    0.101      0.000    0.000    5408.0   \n",
+       "frac[22]   0.052  0.013   0.029    0.077      0.000    0.000    5539.0   \n",
+       "frac[23]   0.005  0.003   0.001    0.010      0.000    0.000    3347.0   \n",
+       "frac[24]   0.027  0.008   0.012    0.043      0.000    0.000    3708.0   \n",
+       "frac[25]   0.048  0.012   0.026    0.071      0.000    0.000    5204.0   \n",
+       "frac[26]   0.049  0.013   0.026    0.072      0.000    0.000    4751.0   \n",
+       "frac[27]   0.044  0.012   0.022    0.066      0.000    0.000    4116.0   \n",
+       "frac[28]   0.003  0.002   0.000    0.008      0.000    0.000    3708.0   \n",
+       "frac[29]   0.002  0.002   0.000    0.004      0.000    0.000    2600.0   \n",
+       "frac[30]   0.002  0.002   0.000    0.004      0.000    0.000    2956.0   \n",
+       "frac[31]   0.002  0.002   0.000    0.004      0.000    0.000    3457.0   \n",
+       "frac[32]   0.012  0.005   0.004    0.021      0.000    0.000    3938.0   \n",
+       "frac[33]   0.002  0.002   0.000    0.005      0.000    0.000    2976.0   \n",
+       "frac[34]   0.002  0.002   0.000    0.005      0.000    0.000    3412.0   \n",
+       "frac[35]   0.002  0.002   0.000    0.004      0.000    0.000    2827.0   \n",
+       "frac[36]   0.002  0.002   0.000    0.004      0.000    0.000    3072.0   \n",
+       "frac[37]   0.002  0.002   0.000    0.004      0.000    0.000    2261.0   \n",
+       "frac[38]   0.002  0.002   0.000    0.004      0.000    0.000    2664.0   \n",
+       "frac[39]   0.002  0.002   0.000    0.005      0.000    0.000    3466.0   \n",
+       "frac[40]   0.002  0.002   0.000    0.005      0.000    0.000    3012.0   \n",
+       "frac[41]   0.002  0.002   0.000    0.004      0.000    0.000    3740.0   \n",
+       "frac[42]   0.002  0.002   0.000    0.005      0.000    0.000    2703.0   \n",
+       "frac[43]   0.002  0.002   0.000    0.005      0.000    0.000    3380.0   \n",
+       "conc      19.339  3.001  13.982   25.118      0.054    0.038    3001.0   \n",
        "\n",
        "          ess_tail  r_hat  \n",
-       "frac[0]     2580.0    1.0  \n",
-       "frac[1]     2460.0    1.0  \n",
-       "frac[2]     1994.0    1.0  \n",
-       "frac[3]     2185.0    1.0  \n",
-       "frac[4]     2148.0    1.0  \n",
-       "...            ...    ...  \n",
-       "frac[81]    2694.0    1.0  \n",
-       "frac[82]    2170.0    1.0  \n",
-       "frac[83]    2570.0    1.0  \n",
-       "frac[84]    2511.0    1.0  \n",
-       "conc        2962.0    1.0  \n",
-       "\n",
-       "[86 rows x 9 columns]"
+       "frac[0]     2570.0    1.0  \n",
+       "frac[1]     2553.0    1.0  \n",
+       "frac[2]     2307.0    1.0  \n",
+       "frac[3]     2760.0    1.0  \n",
+       "frac[4]     2477.0    1.0  \n",
+       "frac[5]     2143.0    1.0  \n",
+       "frac[6]     2491.0    1.0  \n",
+       "frac[7]     2966.0    1.0  \n",
+       "frac[8]     1628.0    1.0  \n",
+       "frac[9]     1691.0    1.0  \n",
+       "frac[10]    1445.0    1.0  \n",
+       "frac[11]    1832.0    1.0  \n",
+       "frac[12]    1737.0    1.0  \n",
+       "frac[13]    2244.0    1.0  \n",
+       "frac[14]    1520.0    1.0  \n",
+       "frac[15]    1530.0    1.0  \n",
+       "frac[16]    1888.0    1.0  \n",
+       "frac[17]    2071.0    1.0  \n",
+       "frac[18]    2444.0    1.0  \n",
+       "frac[19]    1695.0    1.0  \n",
+       "frac[20]    2574.0    1.0  \n",
+       "frac[21]    2315.0    1.0  \n",
+       "frac[22]    2855.0    1.0  \n",
+       "frac[23]    1889.0    1.0  \n",
+       "frac[24]    2691.0    1.0  \n",
+       "frac[25]    2544.0    1.0  \n",
+       "frac[26]    2326.0    1.0  \n",
+       "frac[27]    2295.0    1.0  \n",
+       "frac[28]    2002.0    1.0  \n",
+       "frac[29]    1636.0    1.0  \n",
+       "frac[30]    1951.0    1.0  \n",
+       "frac[31]    2407.0    1.0  \n",
+       "frac[32]    2234.0    1.0  \n",
+       "frac[33]    1941.0    1.0  \n",
+       "frac[34]    1919.0    1.0  \n",
+       "frac[35]    1542.0    1.0  \n",
+       "frac[36]    1448.0    1.0  \n",
+       "frac[37]    1217.0    1.0  \n",
+       "frac[38]    1623.0    1.0  \n",
+       "frac[39]    2163.0    1.0  \n",
+       "frac[40]    1648.0    1.0  \n",
+       "frac[41]    2475.0    1.0  \n",
+       "frac[42]    1464.0    1.0  \n",
+       "frac[43]    2648.0    1.0  \n",
+       "conc        2386.0    1.0  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1075,7 +1393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -1084,13 +1402,13 @@
        "<AxesSubplot: >"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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BP/C6nE2cKYToLmSaoxCdwF+/ycbtD9Z7/DRXDv38ZbiN0R3SelBH1XRyylyMTY5HoW48Qh/KC/L5fuWHXHrz7FNauz8S3PbqDh1saY2JlX0tOhlFUfjkk0+4/vrrGz3m9ttvp7q6mk8//bTD6uqsJCAIEWFlDh/LtuTVm7VgUX1MrklDw4CqdOyvqg5Uuf1UOH30javdJtdoMhEdn0DW9u8ZMHwk4390WYfWdCrc9mr+88fn8Dg7rvUjOi6O6+Y90eyQcPvtt7N8+fJ6j0+fPp01a9a0cXUdY9q0aZx55pn86U9/inQpABQXF4cWOMrLy2PEiBHs3r07bCfLxYsX97j1DhojAUGICFuyOZeAWn+GwHjnQeKCThymyG2clFvuIinGgunoOs/W6BgCXi/b/7uSvsNG0G/o8IjV1hI+twuP04nJZMZoNp/8hFOkBgJ4nE58bleLWhGuuuoqli5dGvaY1Wpt4+rC+f1+LJaO6746ka7rqKqKydT+X0fJycknPSYxMbHd6+gqZAyCEBFU4w2wvIHWg9igk3HOTAIGM3oLl1NuS0FN50ilO+yx2KRe+FwuNr2/HL/H3ciZnZPRbMZstbb7rbUhxGq1kpycHHY7fklfRVH429/+xs9//nNiYmIYPXo0n332Wdg10tLS+OlPf0pcXBwDBgzglltuoby8PPT8tGnTuO+++3jwwQfp27cv06dPB+Czzz5j9OjRREVFcdlll7F8+XIURaG6uhqXy0VCQgIff/xx2Gt9+umnxMbG4nA46r2X22+/nY0bN7J48WIURUFRFPLy8vjmm29QFIUvvviCKVOmYLVa2bRpE9nZ2Vx33XUMGDCAuLg4zjnnHNatWxd2zeHDh7Nw4UJmz55NfHw8Q4cO5e233w497/f7ue+++0hJSSEqKophw4bxwgsvhP386roORowYAdSuoKgoSmgnzNtvvz2sC8Ln8/HAAw/Qv39/oqKiuPjii9m+fXvo+br38/XXXzN16lRiYmK48MILycioP125q5GAIEQEfbjtCB6/Wu/x02v2E6V68Rgiv6OircaL+7ga68YjlOXnse0/H0tzbAd7+umn+dWvfsXevXuZMWMGs2bNorKyEoDq6mp+/OMfc9ZZZ7Fjxw7WrFlDSUkJv/rVr8KusXz5ciwWC5s3b+bNN98kNzeXX/7yl1x//fXs2bOH3/72tzz++OOh42NjY7nxxhvrtW4sXbqUX/7yl8THx9erc/HixVxwwQX85je/obi4mOLiYoYMGRJ6/tFHH2XRokUcOHCAyZMn43Q6mTFjBl9//TW7d+/mqquu4tprryU/Pz/sui+//DJTp05l9+7dzJ07l3vuuSf0Zfzaa6/x2WefsWLFCjIyMnj33XcZPnx4gz/Hbdu2AbBu3TqKi4tZuXJlg8c98sgj/Pvf/2b58uXs2rWLUaNGMX369NDPvM7jjz/Oyy+/zI4dOzCZTMyePbvB63UlEhCEiJCgqvG373Lq7cDYy1/Fae5cfAZLhw5MbIwCHK4IH9xnNJmIjo0n8/vN5Oza3vCJosVWrVpFXFxc2G3hwoVhx9x+++3MnDmTUaNGsXDhQpxOZ+jL7vXXX+ess85i4cKFjBs3jrPOOoslS5awYcMGMjOPzZIZPXo0L774ImPHjmXs2LG89dZbjB07lpdeeomxY8dy4403cvvtt4e97l133cXatWspLi4GoLS0lM8//7zRL8LExEQsFgsxMTGh1hCj8djuoM888ww/+clPOO200+jduzdnnHEGv/3tbzn99NMZPXo0zz77LKeddlq9FpIZM2Ywd+5cRo0axfz58+nbty8bNtSu0ZGfn8/o0aO5+OKLGTZsGBdffDEzZ85ssL5+/foB0KdPH5KTk+ndu3e9Y1wuF3/961956aWX+OlPf8qECRN45513iI6O5u9//3vYsc8//zyXXnopEyZM4NFHH2XLli14vd4GX7urkIAgRIRsyCijxOGr9/jpjnTMmh+foX37nptLB6o9AWq84bMsrLGxaJrKD5+soKa8NDLFdTOXXXYZqampYbe777477JjJkyeH/h0bG0tCQgKlpbU//z179rBhw4awgDFu3DgAsrOPrWExZUr4BlwZGRmcc845YY+de+659e5PnDgxNJDyX//6F8OGDeOSSy5p1XudOnVq2H2n08m8efMYP348SUlJxMXFceDAgXotCMe/f0VRSE5ODr3/22+/ndTUVMaOHcsDDzzAl19+2ara6mRnZxMIBLjoootCj5nNZs4991wOHDjQaF0pKSkAobq6KgkIQkTIP7fmhW21DNDXV85Qz5EOWxSpuRQgv7L+FMH4Xn1wVlWwecW7aGr9rhLRMrGxsYwaNSrsduJftuYTxjcoioJ2dBlsp9PJtddeWy9kHDp0KOyLPDY2tlX13XXXXSxbtgyo7V644447Wj3d9cQa5s2bxyeffMLChQv57rvvSE1NZdKkSfj9/rDjmnr/Z599Nrm5uTz77LN4PB5+9atf8ctf/rJV9bXU8XXV/Uy0Lr48uQQEISLgSKWb7w6Vh+3WCDDBcQCTFuzQRZGaQwcc3mDYCosAisFAbGIvCvansW/92sgUJ0LOPvts0tPTGT58eL2g0VQoGDt2LDt27Ah77PiBeHVuvvlmDh8+zGuvvcb+/fu57bbbmqzHYrGgNjM4bt68mdtvv52f//znTJo0ieTkZPLy8pp17vESEhL49a9/zTvvvMOHH37Iv//973rjBepqA5qs77TTTguN1agTCATYvn07EyZMaHFtXY0EBCEi4MPtR+o1EPT1lTHEW9DpWg/qKEBhtafe42arFZPFwp4vP6csP6/D6+pOfD4fNpst7Hb8DISTuffee6msrGTmzJls376d7Oxs1q5dyx133NHkF+Fvf/tbDh48yPz588nMzGTFihWhloLjWwh69erFL37xC37/+99z5ZVXMnjw4CbrGT58OD/88AN5eXmUl5c3+Rf16NGjWblyJampqezZs4ebbrqpxX+Bv/LKK7z//vscPHiQzMxMPvroI5KTk0lKSqp3bP/+/YmOjg4N5LTb7fWOiY2N5Z577uH3v/89a9asYf/+/fzmN7/B7XZz5513tqi2rkgCghAdTNV03t+WX29q48RO2npQRwfsngBOX/0VH2MSEvG53WxZ8S4BX+cdmKUGAgR8vna/qYHAyYtpwJo1a0hJSQm7XXzxxc0+f+DAgWzevBlVVbnyyiuZNGkSDz74IElJSRgMjX/cjxgxgo8//piVK1cyefJk/vrXv4ZmMZy4DsOdd96J3+9v1ij9efPmYTQamTBhAv369as3nuB4r7zyCr169eLCCy/k2muvZfr06Zx99tnNfOe14uPjefHFF5k6dSrnnHMOeXl5fP755w2+d5PJxGuvvcZbb73FwIEDue666xq85qJFi7jhhhu45ZZbOPvss8nKymLt2rVh00+7K0Vv5RylmpoaEhMTsdvtJCQktHVdQnRbGzJKuWNpePNtH38FV5V+SVAx4Td0zoAAta0IveMsjOlff1qbGgjgrK7k7J9ex5SrG/6wbW9er5fc3FxGjBhBVNSxKaJdYSXFzub555/nzTff5MiRI2GP//Of/+Shhx6iqKgoogssiaY19rsAzf/+lpUUhehgH+04gtGgoB7XhDDecRCTFsRtio5gZSenAxVOP97eGlGm8L/KahchiiJtw5cMPX0y/YaNiEyRDYhJTOK6eU/IXgxNeOONNzjnnHPo06cPmzdv5qWXXuK+++4LPe92uykuLmbRokX89re/lXDQA0hAEKID1XgDfLW/JCwc9PJXMdRzpHZaYycce3AiBbDZPQzvU3/QW3R8AvayEr5f+QEz7p+H0dT+yxo3V0xiUpf6wu5ohw4d4rnnnqOyspKhQ4fyP//zPzz22GOh51988UWef/55LrnkkrDHRfclXQxCdKAVO47wyMd7wx47r/IHxjkzqTHFd4mAAGBQFKYO71VvmiZA0O/HXVPN+b+4kdMv+0mH1tVUs6oQPUlbdDHIIEUhOtAnuwoxHPedGhd0MMJ9uHbcQRcJBwCarlPWwCJPACaLBYPJROqXq6kpL+vgyoQQbUUCghAdpLTGy/e5FWGzF8Y4D2HVfHg7yaqJLVFs99ZbJrpObEIS7ho7O1d/Kns1CNFFSUAQooOs2lscdj9K9TDKlUPAYO5SrQd1vAGVGk/D0/kUg4HouHhyU3dSlHGgwWOEEJ2bBAQhOsgnuws5/k/u01y5RKueLtl6ALWDFUtqGl/zwBIdgxrws/PzT2UZZiG6IAkIQnSAI5Vu9hXaQ/nAqAUZ48xEVYzoStf8NdSBSpefgNrwaneKohCb2IvS3Gyyd/zQscUJIU5Z1/xkEqKLWb2vOGxw4nBPPvGqE4+xa4+014EyZ8ODFaF2wCIopH65ulOvsCiEqE8CghAd4D+phccGJ+o6Y5yZAGiKMXJFtRGb3dfoYEWA2KReVJcUk/n95iaOEk3Jy8tDURRSU1NP6TrTpk3jwQcfbJOaRPcnAUGIdnak0s2BYkfofrKvhD7+SjyGrt16UMcXVHF46+/PUMdoMmEwmti3/kv8HncHViZOtHLlSp599tk2v+7evXv50Y9+RFRUFEOGDOHFF19s8vi6wFN3s1gsjBo1iueeey5s1stTTz0Vdlzdbd26dWHPX3XVVfVe46WXXkJRFKZNmxZ2vTPPPLNN3nNj8vPzufrqq4mJiaF///78/ve/Jxhs/PcDYNeuXfzkJz8hKSmJPn36MGfOHJwnLAv+wAMPMGXKFKxWa7u/hzoSEIRoZ5+f0L0w2nkIo64RNHSeVQZPhQKUOpruPohNTMJRUSatCBHWu3dv4uPr76NxKmpqarjyyisZNmwYO3fu5KWXXuKpp57i7bffPum569ato7i4mEOHDvH000/z/PPPs2TJkrBjJk6cSHFxcdjtkksuCT2fkpLChg0bKCgoCDtvyZIlDB06tG3eZDOpqsrVV1+N3+9ny5YtLF++nGXLlvHkk082ek5RURFXXHEFo0aN4ocffmDNmjWkp6dz++231zt29uzZ/PrXv27HdxBOAoIQ7ey/e4pC3QvxAQeDvUX4OvGGTC1Vtz+D2sR6BwajEYPRRPrGrwl4ZSxCQzRN48UXX2TUqFFYrVaGDh3K888/H3ZMTk4Ol112GTExMZxxxhls3bo19FxFRQUzZ85k0KBBxMTEMGnSJN5///2w80/sYhg+fDgLFy5k9uzZxMfHM3To0GZ9sR/v3Xffxe/3s2TJEiZOnMiNN97IAw88wCuvvHLSc/v06UNycjLDhg1j1qxZXHTRRezatSvsGJPJRHJyctjt+H0g+vfvz5VXXsny5ctDj23ZsoXy8nKuvvrqFr2XU/Xll1+yf/9+/vWvf3HmmWfy05/+lGeffZa//OUv+P3+Bs9ZtWoVZrOZv/zlL4wdO5ZzzjmHN998k3//+99kZWWFjnvttde49957GTlyZEe9HQkIQrSnwmoPaUU1ofsj3TlYNH+3CghQu7JieRODFaF2S+ia8lKydnzfQVV1LY899hiLFi1iwYIF7N+/n/fee48BAwaEHfP4448zb948UlNTGTNmDDNnzgw1X3u9XqZMmcLq1atJS0tjzpw53HLLLWzbtq3J13355ZeZOnUqu3fvZu7cudxzzz1kZGQ0u+6tW7dyySWXhH1pT58+nYyMDKqqqpp9nR07drBz507OO++8Zp9TZ/bs2Sxbtix0f8mSJcyaNatVG0rFxcU1ebv77rsbPXfr1q1MmjQp7L/b9OnTqampIT09vcFzfD4fFoslbEvq6OjaTds2bdrU4vrbkmzWJEQ7+mJfMYoCul47tfE0Vy5BxdglF0Y6mdIaHwPiGx9XYTSZUBQD+7/bwJjzL8Zoko+fOg6Hg8WLF/P6669z2223AXDaaadx8cUXhx03b9680F/FTz/9NBMnTiQrK4tx48YxaNAg5s2bFzr2/vvvZ+3ataxYsYJzzz230deeMWMGc+fOBWD+/Pm8+uqrbNiwgbFjxzardpvNxogR4Tt31n1B2mw2evXq1ei5F154IQaDAb/fTyAQYM6cOdx6661hx+zbt4+4uLjQ/QkTJtQLPddccw1333033377LVOmTGHFihVs2rSpXndFc5xsIGhTexfYbLZ6oe74n0VDfvzjH/Pwww/z0ksv8bvf/Q6Xy8Wjjz4KQHFxcYPndBT5DRWiHa3aWxxaHGmIt4A41YnLGBPZotqJ0xfEE1CJNjc+MyMmIZGqokLy0/Yw4swpHVhd53bgwAF8Ph+XX355k8dNnjw59O+UlBQASktLGTduHKqqsnDhQlasWEFhYSF+vx+fz0dMTNP/vx1/TUVRSE5OprS09BTeTfN9+OGHjB8/nkAgQFpaGvfffz+9evVi0aJFoWPGjh3LZ599FrpvtdZfWMxsNnPzzTezdOlScnJyGDNmTNj7aolRo0a16rzWmjhxIsuXL+fhhx/msccew2g08sADDzBgwICwVoVIkIAgRDsprfGy50h1aArgKGc26N1jamNDFKDM4WNo78a/kEwWC7qusf+7DQw/42yUbtiS0hp1TconYzYfG9ha97PTtNqFql566SUWL17Mn/70JyZNmkRsbCwPPvhgo33fDV2z7rp112yO5ORkSkpKwh6ru5+cnNzkuUOGDAl9IY8fP57s7GwWLFjAU089FdqBsG6Gw8nMnj2b8847j7S0NGbPnt3s+k90fGtFQ26++WbefPPNBp9LTk6u17rRnJ/FTTfdxE033URJSQmxsbEoisIrr7zSoeMNGiIBQYh28uX+Yx+aSf4q+vvL8Bm75rLKzaEDpQ4fQ3rH0NTXfnRcAiU5WZTmZjNgZMf+tdZZjR49mujoaL7++mvuuuuuVl1j8+bNXHfdddx8881AbXDIzMxkwoQJbVlqPRdccAGPP/44gUAgFDa++uorxo4d22T3QkOMRiPBYBC/39/i7bonTpzIxIkT2bt3LzfddFOLzj3eqXQxXHDBBTz//POUlpbSv39/oPZnkZCQ0Kz/DnXdEUuWLCEqKoqf/KRjt0s/kQQEIdrJ58eNPxjhPoxZC+AxdY+1DxoTUDXsngBJ0Y1P4TRHReF22Mn4fpMEhKOioqKYP38+jzzyCBaLhYsuuoiysjLS09O58847m3WN0aNH8/HHH7NlyxZ69erFK6+8QklJSbsHhJtuuomnn36aO++8k/nz55OWlsbixYt59dVXT3puRUUFNpuNYDDIvn37WLx4MZdddlmTX8JNWb9+PYFAgKSkpFadD6fWxXDllVcyYcIEbrnlFl588UVsNhtPPPEE9957b6hrZNu2bdx66618/fXXDBo0CIDXX3+dCy+8kLi4OL766it+//vfs2jRorD3kZWVhdPpxGaz4fF4QkFmwoQJrRqM2RwSEIRoB9VuP9/n1G7tbNSCjHDnElRM3XJw4vHq1kRoKiAoioI1Ooa81J1MmXEdsUkt+yuzu1qwYAEmk4knn3ySoqIiUlJSmhwxf6InnniCnJwcpk+fTkxMDHPmzOH666/Hbre3Y9WQmJjIl19+yb333suUKVPo27cvTz75JHPmzDnpuVdccQVQ23KQkpLCjBkz6k3tbInY2NhWn9sWjEYjq1at4p577uGCCy4gNjaW2267jWeeeSZ0jNvtJiMjg0Dg2E6o27Zt4//+7/9wOp2MGzeOt956i1tuuSXs2nfddRcbN24M3T/rrLMAyM3NZfjw4e3yfhS9lZu119TUkJiYiN1ub3XaE6K7+vfOAv7noz0ADHXnM63iW1zGmG47/uB4CjB1eG9MhsbDkK5p2MvLOP8Xv2Ly5fVXwWstr9dLbm4uI0aMaHETtRDdSVO/C839/pZ1EIRoB5+nHVs9cYQ7D0XXe0Q4gLqFk5peE0ExGDCajGRs3YR6kmVohRCRIQFBiDbm8gX5NrMMTYfYoIuB3mJ8hu47OLEhJY6mAwLUDla0l5ZQeLDhBWSEEJElAUGINrYxs4yAWttzN9RzBIse6HYrJ56M6+iaCE0xWSzoqsqh7VubPE4IERkSEIRoY1/sK8ZoqJ2+MNKdi4bS7QcnnqhuTYSTscbEULA/DWdVZfsXJYRoEQkIQrQhX1Bl3YFSVE2nT6CSpEB1j+tegGNrIpxsBLQ1Jha/x01e6s6OKEsI0QISEIRoQ1uyKkJN60PdRzBpQQJKz5xNXLcmQlMUgwFFMXBo+1ZaOaFKCNFOJCAI0Ya+SKvtXjDoKsM9h7vtxkzNoQAlNSff2jkqLp6q4kJK83LavyghRLNJQBCijQRVjTVpNlRNZ4CvlLigs1svrXwyOlDl8hPQmm4ZMFutBP1+Du/d3TGFCSGaRQKCEG1ke14VNd7aOf1DPEcw6BpqD+1eqKMD5ScZrKgoCmaLlZxd2wgGmu6SEEJ0HAkIQrSRtek2jAYFkxZgmOcIAUPjyw33JCU13pMPVoyNw1lVSVHGgQ6pqavJy8tDUZSTbiR0MtOmTePBBx9sk5pE9ycBQYg2oGk6q/YWoWo6KV4b0aqnx6190BhPQMXpbXq1RJPZjK6q5O3d1UFV9UwrV67k2WefbdNrer1ebr/9diZNmoTJZOL6669v1nmKooRuJpOJoUOH8vDDD+PzHWtxWrZsWdhxdbe//e1vYc+PHz++3vU/+ugjFEUJ26dg2bJlp7SRU3NUVlYya9YsEhISSEpK4s4778TpdDZ5TnZ2Nj//+c/p168fCQkJ/OpXv6q3hXZmZibXXXcdffv2JSEhgYsvvpgNGza051uRgCBEW0gtqKbc6Qdquxd60tLKJ1O3gdPJmKOiyd+bit/jbv+ieqjevXsTHx/fptdUVZXo6GgeeOCB0OZLzbV06VKKi4vJzc3ljTfe4J///CfPPfdc2DEJCQkUFxeH3WbNmhV6PjY2ltLSUrZuDV9w6+9//ztDhw5t/RtrpVmzZpGens5XX33FqlWr+Pbbb5vcuMrlcnHllVeiKArr169n8+bN+P1+rr32WjRNCx13zTXXEAwGWb9+PTt37uSMM87gmmuuwWaztdt7kYAgRBtYk1bbvWDW/AzxFuKX7oUQHSh3+lFPMo3RGhuLx+mg4EDPXHpZ0zRefPFFRo0ahdVqZejQofV2NszJyeGyyy4jJiaGM844I+xLsaKigpkzZzJo0CBiYmKYNGkS77//ftj5J3YxDB8+nIULFzJ79mzi4+MZOnQob7/9dovqjo2N5a9//Su/+c1vSE5ObtG5SUlJJCcnM2TIEK655hquu+46du0Kb0VSFIXk5OSwW3R0dOh5k8nETTfdxJIlS0KPFRQU8M0333DTTTe1qJ5TdeDAAdasWcPf/vY3zjvvPC6++GL+/Oc/88EHH1BUVNTgOZs3byYvL49ly5YxadIkJk2axPLly9mxYwfr168HoLy8nEOHDvHoo48yefJkRo8ezaJFi3C73aSlpbXb+5GAIMQp0nWdVXtquxcGeouxar4euThSUzRdp/wkGzgZjSZAJ3dPz1w06bHHHmPRokUsWLCA/fv389577zFgwICwYx5//HHmzZtHamoqY8aMYebMmQSPbnbl9XqZMmUKq1evJi0tjTlz5nDLLbewbdu2Jl/35ZdfZurUqezevZu5c+dyzz33kJGR0W7vszGZmZmsX7+e8847r8Xnzp49mxUrVuB217Y+LVu2jKuuuqrez685Jk6cSFxcXKO3n/70p42eu3XrVpKSkpg6dWrosSuuuAKDwcAPP/zQ4Dk+n692C3Trsc+MqKgoDAYDmzZtAqBPnz6MHTuWf/zjH7hcLoLBIG+99Rb9+/dnypQpLX6PzdWzh1gL0QbSi2oostc2oQ/2FKDoOroi2ftEJXYfA+Kb3oLZEhVN4cH9eJwOouPatim8M3M4HCxevJjXX3+d2267DYDTTjuNiy++OOy4efPmcfXVVwPw9NNPM3HiRLKyshg3bhyDBg1i3rx5oWPvv/9+1q5dy4oVKzj33HMbfe0ZM2Ywd+5cAObPn8+rr77Khg0bGDt2bFu/zXpmzpyJ0WgkGAzi8/m45ppreOyxx8KOsdvtxMXFhe7HxcXVa1Y/66yzGDlyJB9//DG33HILy5Yt45VXXiEnp+Vra3z++ecEmphNc3zrxYlsNhv9+/cPe8xkMtG7d+9GuwLOP/98YmNjmT9/PgsXLkTXdR599FFUVaW4uBiobUVZt24d119/PfHx8RgMBvr378+aNWvo1atXi99jc8mnmBCnqG5xJLPmZ7C3SLoXGuHyB3H6mh6saI2JxedyUbB/XwdV1TkcOHAAn8/H5Zdf3uRxkydPDv07JSUFgNLSUqB2LMCzzz7LpEmT6N27N3Fxcaxdu5b8/PxmX7OuOb/umu3t1VdfJTU1lT179rBq1SoyMzO55ZZbwo6Jj48nNTU1dNuyZUuD15o9ezZLly5l48aNuFwuZsyY0aqahg0bxqhRoxq9DRo0qFXXbUy/fv346KOP+O9//0tcXByJiYlUV1dz9tlnYzDUfkXrus69995L//79+e6779i2bRvXX3891157bShEtAdpQRDiFOi6zmdHuxcGeW1YNR8uY2yky+qU6lZWjOsX1+gxBqMR0Dm8N5XR517YYbVFWlN/lR7PbD4WPpWjK3TWDWR76aWXWLx4MX/605+YNGkSsbGxPPjgg/j9/mZfs+66xw+Oa0/JycmMGjUKgLFjx+JwOJg5cybPPfdc6HGDwRD6d1NmzZrFI488wlNPPcUtt9yCydS6r7eJEydy+PDhRp//0Y9+xBdffNHgcw2Fq2AwSGVlZZPjM6688kqys7MpLy/HZDKFxmaMHDkSgPXr17Nq1SqqqqpISEgA4I033uCrr75i+fLlPProoy19m80iAUGIU3DQ5uBIpQeAwd7Co7MXpGGuIXWDFYf10TEZGl9+2hIdQ1HmATyOGqLjEzquwAgaPXo00dHRfP3119x1112tusbmzZu57rrruPnmm4Ha4JCZmcmECRPastR2ZTTWzvzxeDwtPrd379787Gc/Y8WKFbz55putruFUuhguuOACqqur2blzZ2hswPr169E0rVljK/r27Rs6p7S0lJ/97GcAobEVdS0KdQwGQ7uGOQkIQpyC1XuLMSoKiupnsKdQFkc6CU3XKXP4SElsfCyCNToGR2UFBfvTGH1ez2hFiIqKYv78+TzyyCNYLBYuuugiysrKSE9P584772zWNUaPHs3HH3/Mli1b6NWrF6+88golJSUdEhD279+P3++nsrISh8MRWtDpzDPPbPK86upqbDYbmqZx6NAhnnnmGcaMGdPgugbNsWzZMt544w369OnTqvOhtouhtcaPH89VV13Fb37zG958800CgQD33XcfN954IwMHDgSgsLCQyy+/nH/84x+hsSFLly5l/Pjx9OvXj61bt/K73/2Ohx56KDQO5IILLqBXr17cdtttPPnkk0RHR/POO++Qm5sbGpPSHiQgCNFKuq7znz1FqLrOYF8JUZoXlzEm0mV1esV2L8mJUTTWhlDXzZCfvqfHBASABQsWYDKZePLJJykqKiIlJYW777672ec/8cQT5OTkMH36dGJiYpgzZw7XX389dru9HauuNWPGjLBm+bPOOgvgpDt03nHHHcCxsQ+XXHIJCxcubHX3QHR0dLO7a9rLu+++y3333cfll1+OwWDghhtu4LXXXgs9HwgEyMjICLUKAGRkZPDYY49RWVnJ8OHDefzxx3nooYdCz/ft25c1a9bw+OOP8+Mf/5hAIMDEiRP5z3/+wxlnnNFu70XRW7nHak1NDYmJidjt9lCfiBA9yf6iGma89h0A51X+wDhXJjUm+V1ojvEpCSRFN97a4nHUoBiN/OrJhUTFNj5m4URer5fc3FxGjBhBVFTTMyaE6M6a+l1o7ve3dJYK0Uqr9xWFtnYe4i0k0MM3ZmouBbDZm15ZsW42g+zNIETkSEAQohV0Xec/u2tnL/T3lRGtevDL3gvNogNVbj/eYOODqwxGI7quc2T/3o4rTAgRRgKCEK1w0OagoLp2pPVAb5Fs7dxCdVMem2KJiuJIehoB78n3cRBCtD0JCEK0wuf7ijEooOgawzxHCMrGTC2iUxsQmtqfwRoTi9fpoOjQwY4rTAgRIgFBiBbSdZ1Pdhei6dDHX0Fs0IVf9l5oMVWrnfLYGKPJhK5pPXbzJiEiTQKCEC2UXlRDQVVd94INI6q0ILRSUbWHpqZRmSwW8tP2oAYbX7hGCNE+JCAI0UKrji6OhK4z1HMEDQMoja8MKBrnC2pUuRtfCtgaE4vbXk1pbss33RFCnBoJCEK0gK7rfLq7EFXXSQzaSQzaZWvnU1RU1fiyukazGTUYoOBA++15L4RomAQEIVpgT4Ed29HR9wO9NkyaKusfnCKHL4jD2/Auj4qiYDKZObwv9aSr8gkh2pYEBCFa4LPU2sWRAIZ4CtAVpHvhFClAYXXjrQiWmFgc5WVUFDS9bXF3lpeXh6IooT0OWmvatGk8+OCDbVKT6P4kIAjRTKqm85/UQlRNJybooo+/Ap8sjnTK6hZO8gTUBp83W60EA35ZVbENrFy5kmeffbZNr/nNN99w3XXXkZKSQmxsLGeeeSbvvvtuk+fUBZ66m8ViYdSoUTz33HNhLUVPPfVU2HF1t3Xr1oU9f9VVV9V7jZdeeglFUZg2bVrY9U62gdSpeuCBB5gyZQpWq7XZr+X1ern33nvp06cPcXFx3HDDDZSUlJzydU+VBAQhmml7XiUVrtoBdSk+GxY9QECR3RvbgkLtjIYGn1MUFMVAftqeji2qG+rduzfx8fFtes0tW7YwefJk/v3vf7N3717uuOMObr31VlatWnXSc9etW0dxcTGHDh3i6aef5vnnn2fJkiVhx0ycOJHi4uKw2yWXXBJ6PiUlhQ0bNlBQUBB23pIlSxg6dGjbvMkWmj17Nr/+9a+bffxDDz3Ef//7Xz766CM2btxIUVERv/jFL075uqdKAoIQzbRqz7HuhUGeItB1dEV+hdqCDpQ5fPgaWX7ZGhNDeUE+joryji2sA2maxosvvsioUaOwWq0MHTqU559/PuyYnJwcLrvsMmJiYjjjjDPYunVr6LmKigpmzpzJoEGDiImJYdKkSbz//vth55/YxTB8+HAWLlzI7NmziY+PZ+jQobz99tstqvt///d/efbZZ7nwwgs57bTT+N3vfsdVV13FypUrT3punz59SE5OZtiwYcyaNYuLLrqIXbt2hR1jMplITk4Ou1ksx1ru+vfvz5VXXsny5ctDj23ZsoXy8vJ23Qq5Ma+99hr33nsvI0eObNbxdrudv//977zyyiv8+Mc/ZsqUKSxdupQtW7bw/ffft/q6bUE+3YRohqCq8d+9xaiajlnzk+Kzyd4L7aDI3nArgiUqmoDXQ1Fm9+1meOyxx1i0aBELFixg//79vPfeewwYMCDsmMcff5x58+aRmprKmDFjmDlzJsFg7QBPr9fLlClTWL16NWlpacyZM4dbbrmFbdu2Nfm6L7/8MlOnTmX37t3MnTuXe+65h4yMjFN6L3a7nd69e7fonB07drBz507OO++8Fr/e7NmzWbZsWej+kiVLmDVrVliQaK64uLgmby3Zgrs5du7cSSAQ4Iorrgg9Nm7cOIYOHRoWACNBhl8L0Qzf51Ri99Qu1pPsLcGq+XAZYyNcVfdSu/yyj0FJ0ViM4X+7KIba+wX70xh7wY8iUF37cjgcLF68mNdff53bbrsNgNNOO42LL7447Lh58+aF/ip++umnmThxIllZWYwbN45BgwYxb9680LH3338/a9euZcWKFZx77rmNvvaMGTOYO3cuAPPnz+fVV19lw4YNjB07tlXvZcWKFWzfvp233nrrpMdeeOGFGAwG/H4/gUCAOXPmcOutt4Yds2/fPuLijm35PWHChHqh55prruHuu+/m22+/ZcqUKaxYsYJNmzbV665ojpMNBG1qe+TWsNlsWCwWkpKSwh4fMGAANputTV+rpSQgCNEM/91b272gajoDvUUo6GjSvdDmdF2n2O5lWO+Yes9ZoqIpOnQQv8eNJbr+813ZgQMH8Pl8XH755U0eN3ny5NC/U1JSACgtLWXcuHGoqsrChQtZsWIFhYWF+P1+fD4fMTFN/6yOv6aiKCQnJ1NaWtqq97FhwwbuuOMO3nnnHSZOnHjS4z/88EPGjx9PIBAgLS2N+++/n169erFo0aLQMWPHjuWzzz4L3bda6687Yjabufnmm1m6dCk5OTmMGTMm7H21xKhRo1p1XnckAUGIk/AHNVYf7V4w6CqDvYWy9kE7stm9DEqKxmQInz5qiY7BVV1J8aFMhk0+MzLFtZPo6OhmHWc2HxsUqxydXqtpteM2XnrpJRYvXsyf/vQnJk2aRGxsLA8++CB+f+MrVZ54zbrr1l2zJTZu3Mi1117Lq6++Wq8VoDFDhgwJfSGPHz+e7OxsFixYwFNPPUVUVBRAaIbDycyePZvzzjuPtLQ0Zs+e3eL66xzfWtGQm2++mTfffLPV1z9RcnIyfr+f6urqsFaEkpISkpOT2+x1WkM+5YQ4iU1ZZTh9tf28/XzlRKtevLJ6YrvRdB2b3cvgXuFfmrWbN+kUHkzvdgFh9OjRREdH8/XXX3PXXXe16hqbN2/muuuu4+abbwZqg0NmZiYTJkxoy1Ib9M0333DNNdfwhz/8gTlz5rT6OkajkWAwiN/vDwWE5po4cSITJ05k79693HTTTa2uoaO7GKZMmYLZbObrr7/mhhtuACAjI4P8/HwuuOCCNn2tlpKAIMRJ/Cf1WPdCircYo66iyuZM7arI7iE5MapeK4LJYiE/fS/nqzdiMHaf/wZRUVHMnz+fRx55BIvFwkUXXURZWRnp6enceeedzbrG6NGj+fjjj9myZQu9evXilVdeoaSkpN0DwoYNG7jmmmv43e9+xw033BDqN7dYLCcdqFhRUYHNZiMYDLJv3z4WL17MZZdd1uov4fXr1xMIBOr157fEqXYxZGVl4XQ6sdlseDyeUOCYMGECFouFwsJCLr/8cv7xj39w7rnnkpiYyJ133snDDz9M7969SUhI4P777+eCCy7g/PPPb/Z124MEBCGa4PGrrE23oWo66DpDvIW14UBWT2xXqqZTUlPb1XA8S3QMbns1Zfl5DBhxWoSqax8LFizAZDLx5JNPUlRUREpKSotGzD/xxBPk5OQwffp0YmJimDNnDtdffz12u70dq4bly5fjdrt54YUXeOGFF0KPX3rppXzzzTdNnls3ct9oNJKSksKMGTPqTe1sidjYyA8cvuuuu9i4cWPo/llnnQVAbm4uw4cPJxAIkJGRgdvtDh3z6quvYjAYuOGGG/D5fEyfPp033nijRddtD4reygXOa2pqSExMxG63t3mTixCdxeq9xdz7Xu287KRANVeXfEFAMRMwyAJJ7c1oUJgyrFftzplH6bpOTVkpU3/2C86afk29c7xeL7m5uYwYMaLFTdRCdCdN/S409/tbhmEL0YRPUwtDiyOleG2YtKAMUOwgda0Ix1MUBYPRQP6+PbJ5kxDtTAKCEI2o8QbYcLC0tnsBGOwpQFcU6V7oQIVVHtQTgoAlOpaq4kIc5WURqkqInkECghCN+Cq9hODRcBATdNHXX4FfkdUTO1JQ0ymt8YU9ZomOIuDzUtiNV1UUojOQgCBEIz5NLaRuEH3d5kx+GXvQ4QqrPWjHNSIoRxeoOpK+N0IVCdEzSEAQogGVLj+bs8pDX0wDZXOmiAmoGuXO8LEIlqhobNmH8LldEapKiO5PPu2EaMDn+4qp6/o2awEG+mzSehBBBVUejh+JYImOwe92UXzo1DYVEkI0TgKCEA34T2ohHO1eGOArwar5ZffGCPIFNSqcx8YiGE0mNE2jMEPGIQjRXiQgCHGC0hovO/KqQi0IyV4biq6hyeqJEXViK4LZYuVI+h40VY1YTUJ0ZxIQhDjB5/uKQ/9WdI2hngKCsvZBxHkCamjLbahbVdFO2eHcCFYlRPclAUGIE3yaWhT6dx9/BTGqW7oXOgGF2nUR6pgsFtRAgKIeMN0xLy8PRVFOupHQyUybNo0HH3ywTWoS3Z8EBCGOU1TtIfVIdagpe6DPhhGVoHQvRJxO7eJVdTtryqqKLbdy5UqeffbZNr1mRkYGl112GQMGDCAqKoqRI0fyxBNPEAgEGj2nLvDU3eq2dH7uuefC/ls+9dRTYcfV3datWxf2/FVXXVXvNV566SUURWHatGlh1zvzzDPb7L035IEHHmDKlClYrdZmv5bX6+Xee++lT58+xMXFccMNN1BSUhJ6vqKigquuuoqBAwditVoZMmQI9913HzU1Ne30LmpJu6kQx/l8XzGKQu34A11nsKcADYOsnthJKNSGuDED4oHaboYqWxGO8jIS+vWPbHFdwMl2V2wNs9nMrbfeytlnn01SUhJ79uzhN7/5DZqmsXDhwibPXbduHRMnTsTn87Fp0ybuuusuUlJSwnawnDhxYigQNPQ+UlJS2LBhAwUFBQwePDj0+JIlSxg6dGgbvcuWmT17Nj/88AN79zZvrY6HHnqI1atX89FHH5GYmMh9993HL37xCzZv3gyAwWDguuuu47nnnqNfv35kZWVx7733UllZyXvvvddu70NaEIQ4zn9Si6hrPkgIOkgK2KV7oRPRgQqXH29QA2rXQwj4vBQdOhjZwtqApmm8+OKLjBo1CqvVytChQ+vtbJiTk8Nll11GTEwMZ5xxBlu3bg09V1FRwcyZMxk0aBAxMTFMmjSJ999/P+z8E7sYhg8fzsKFC5k9ezbx8fEMHTqUt99+u0V1jxw5kjvuuIMzzjiDYcOG8bOf/YxZs2bx3XffnfTcPn36kJyczLBhw5g1axYXXXQRu3btCjvGZDKRnJwcdjt+e+P+/ftz5ZVXsnz58tBjW7Zsoby8nKuvvrpF76UtvPbaa9x7772MHDmyWcfb7Xb+/ve/88orr/DjH/+YKVOmsHTpUrZs2cL3338PQK9evbjnnnuYOnUqw4YN4/LLL2fu3LnN+hmfCgkIQhx1pNLNvkJ7qHsh2WfDrAfwK7L+QWeiADZ77VgExVD7EVZwIC2CFbWNxx57jEWLFrFgwQL279/Pe++9x4ABA8KOefzxx5k3bx6pqamMGTOGmTNnEgzWdrl4vV6mTJnC6tWrSUtLY86cOdxyyy1s27atydd9+eWXmTp1Krt372bu3Lncc889ZGS0fn2JrKws1qxZw6WXXtqi83bs2MHOnTs577zzWvyas2fPZtmyZaH7S5YsYdasWWFBorni4uKavLVkC+7m2LlzJ4FAILT1NcC4ceMYOnRoWAA8XlFREStXrmzxz7ilpItBiKO+SCvGoBBaPXGwp7C2q0G6FzoVHSip8TG4Vwwmg4IlKpriQxn4PW7ooitdOhwOFi9ezOuvv85tt90GwGmnncbFF18cdty8efNCfxU//fTTTJw4kaysLMaNG8egQYOYN29e6Nj777+ftWvXsmLFCs4999xGX3vGjBnMnTsXgPnz5/Pqq6+yYcMGxo4d26L3cOGFF7Jr1y58Ph9z5szhmWeeadY5BoMBv99PIBBgzpw53HrrrWHH7Nu3j7i4uND9CRMm1As911xzDXfffTfffvstU6ZMYcWKFWzatIklS5a06D0AJx0I2tT2yK1hs9mwWCwkJSWFPT5gwABsNlvYYzNnzuQ///kPHo+Ha6+9lr/97W9tWsuJJCAIcdR/UotC4SBK9dLfVybdC52UpuuUOrwMTIzGEh2Dq7oKW/Yh+o9q2ZdaZ3HgwAF8Ph+XX355k8dNnjw59O+UlBQASktLGTduHKqqsnDhQlasWEFhYSF+vx+fz0dMTEyzr6koCsnJyZSWlrb4PXz44Yc4HA727NnD73//e/74xz/yyCOPnPSc8ePHEwgESEtL4/7776dXr14sWrQodMzYsWP57LPPQvetVmu965jNZm6++WaWLl1KTk4OY8aMCXtfLTFq1KhWndcRXn31Vf7v//6PzMxMHnvsMR5++GHeeOONdns9CQhCUNu9kF50bERwss+GRffjNMZGsCrRlOJqLymJ0RhNJnRNpSjzQJcNCNHR0c06zmw+1t2lHG3Z0rTa8RgvvfQSixcv5k9/+hOTJk0iNjaWBx98EL/f3+xr1l237potMWTIEKD2L3xVVZkzZw7/8z//g9HY+AygIUOGhL6Qx48fT3Z2NgsWLOCpp54iKioKIDTD4WRmz57NeeedR1paGrNnz25x/XWOb61oyM0338ybb77Z6uufKDk5Gb/fT3V1dVgrQklJCcnJyfWOTU5OZty4cfTu3Zsf/ehHLFiwIBQW25oEBCGA1fvCuxcGeYpQZHOmTs2valS6/PSJtWA0W8jft4fJV10b6bJaZfTo0URHR/P1119z1113teoamzdv5rrrruPmm28GaoNDZmYmEyZMaMtSm0XTNAKBAJqmNRkQTmQ0GgkGg/j9/lBAaK6JEycyceJE9u7dy0033dTSkkM6uothypQpmM1mvv76a2644Qagdupofn4+F1xwQaPn1YU4n8/X6DGnSgKCENTuvVAXDkxagEHeIgKyOVOnV2z30CfWgjUmBmd1JdXFxSc/qROKiopi/vz5PPLII1gsFi666CLKyspIT08Pm/LXlNGjR/Pxxx+zZcsWevXqxSuvvEJJSUm7B4R3330Xs9nMpEmTsFqt7Nixg8cee4xf//rX9VonTlRRUYHNZiMYDLJv3z4WL17MZZdd1uov4fXr1xMIBOr157fEqXYxZGVl4XQ6sdlseDyeUOCYMGECFouFwsJCLr/8cv7xj39w7rnnkpiYyJ133snDDz9M7969SUhI4P777+eCCy7g/PPPB+Dzzz+npKSEc845h7i4ONLT0/n973/PRRddxPDhw0+p3qZIQBA93uEKFweKHaH7/X1lWDUfbmPzmn1F5Di8QVx+lRiLFbfdTmleDtaBQyJdVqssWLAAk8nEk08+SVFRESkpKS0aMf/EE0+Qk5PD9OnTiYmJYc6cOVx//fXY7fZ2rLp2GuIf/vAHMjMz0XWdYcOGcd999/HQQw+d9Ny6kftGo5GUlBRmzJhRb2pnS8TGRr5L8K677mLjxo2h+2eddRYAubm5DB8+nEAgQEZGBm63O3TMq6++isFg4IYbbsDn8zF9+vSwsQXR0dG88847PPTQQ/h8PoYMGcIvfvELHn300XZ9L4reyiXIampqSExMxG63t3mTixAd6Y1vsvjj2oxQC8LUqp1MdOynxiz/X3d2CtA/IYqRfWOpKS9j0OlnMPySKxgxYkSLm6iF6E68Xi+5ubkN/i409/tbOlhFj3f87AVF1xjilc2ZugodKHP4CGo61ugYqm3FaJrs7ihEW5CAIHq0vHIXGbZj3Qt9/BXEBl0yvbEL0XSdcqcPc3Q0Ab8XNRCMdElCdAsSEESPVjd7oc5Arw2jLpszdTU2u7d2VUUd1EDT0/qEEM0jAUH0aP/dc6x7AV1niLcATZHNmboaT0DF6Q1itloJHp1eJ4Q4NRIQRI+VX+Hm4HHdCwlBB4kBOz7pXuhyFMBW48VsjULXdYL+9psbLkRPIQFB9Fhr0k/sXijGrAcJyOZMXU7dLo+6wQi6jt/rjXRJQkRUW7SiyVBt0WP9d0/xse4FYJC3sHYnR+le6JJ0XcdWVkWKx43NVoI5OgaLxRJakliInkDXdfx+P2VlZRgMhlbtaFlHAoLokYqqPewrPLaATJTqoZ+vDL8i3Qtdma3aTcGWjXjGnw5GA0aTtAaJnikmJoahQ4diMLS+o0ACguiR1qTZUBSoWyYsxWvDogVwmiK/EptoPbdfxeX14/h2Hf379GHURZdGuiQhOpzRaMRkMp1y65kEBNEj/XdvUW3H9VGDvEWgIJszdXEKUOb001cxkL9vN2dcPj3SJQnRZcmnoehxSh1eUvOrQ/nApAUY6C0mIKsndnl1Kyuao6OpLDiCo7I80iUJ0WVJQBA9zpfpJWH3B/hKidJ8snpiN6HpOk7ViN/joSjjYKTLEaLLkoAgepzVe4vDJiqkeItRdA1NVk/sNkqdAVCgYP++SJciRJclAUH0KNVuPz/kVpywOVOhbM7UzdR4A2COoujQQfwe98lPEELUIwFB9Chf7S8JW/tANmfqvmpUAz6Xk+JDmZEuRYguSQKC6FE+TyvGePzqiT7ZnKm7KnUG0TSNgoPpkS5FiC5JAoLoMZy+IN8dKkc9bnOmwR7ZnKm78qsaAUzkp+1BDcoW0EK0lAQE0WNsOFhKUD3Wv5AQdJAkmzN1WwpgV4247dWU5mVHuhwhuhwJCKLH+CLNhvG43ZmSfTbMekA2Z+qmdKDCoxEMBCg8uD/S5QjR5UhAED2CN6Cy/mAJ6nEjFAd7CtF1RboXujEN8KoKh/emouv6SY8XQhwjAUH0CJuzyvEGjm1/alW99PeX4TdI60F3VxU0UFNeQmVhQaRLEaJLkYAgeoS16eHdCym+EiyaX6Y39gD2gILX46VQZjMI0SISEES3F1Q1vkizhXUvpHiLUHRdNmfqCRQFd0Ajb+9u6WYQogXk01F0e9vyKnF4j01zM+gqg7xFBKR7oceoDBqpLDxCTVlppEsRosuQgCC6vTVpNkzHdS/095URrXqle6EHcWsmnE43BQfSIl2KEF2GBATRrWmazuf7igmGdS8UY9A1VFk9scdQFAWXX+XwvtRIlyJElyEBQXRrewqqKXf6jz2g6wzxFko46GF0oDpopCQ3G2dlRaTLEaJLkIAgurW16SVhsxd6BaqJDzqke6EH8ipmahwu6WYQopkkIIhuS9d1Vu0tCpu9kOwrwaQFCcj2zj2PouDyBcnbuzvSlQjRJUhAEN3WoVInBVWesMcGeQrRFVk9saeqUU0UHsrEWVUZ6VKE6PQkIIhua22ajeN6F4hSPfTzl+NXpHuhp/IZLNhrnBTs3xfpUoTo9CQgiG5r1d5ijutdINlXglkPyPLKPdnRbobcPbsiXYkQnZ4EBNEtHal0k1HiCHssxVssqycKXLqZ/IwMHJXlkS5FiE5NPilFt7Q23RY2zKB29cRiWT1R4DdYqHG4OJIu3QxCNEUCguiWVu8trp38flQ/X/nR1RMlIPR0+tFFk7J3bY90KUJ0ahIQRLdT6vCSeqT6+HxAsteGQVdRkQWSBHgUC/mHsrCX2iJdihCdlgQE0e18mV4S/kBo9USDTG8UAAQUMw6nS5ZeFqIJEhBEt/P5vuKwHJAQdJAQrJHVE0WIrii4AzoHf/hetoAWohESEES3Uu32831ORdj0xgG+EsxagIAi4w/EMV6DlaL8I5Tn50W6FCE6JQkIoltZd6A0LBwADPQW1f5DuhfEcQKKCafLI0svC9EICQiiW/liX3HY6olmzU+yr1S6F0R9ioJHU0j/fitqMBDpaoTodCQgiG7D5Quy8VDZCd0LpVg1v0xvFA3yG62UlZRSlHkw0qUI0elIQBDdxsbMMoJqeP9CsteGomtoikxvFPUFFRNuj58sWRNBiHokIIhu44t9xRiP71/QdQZ7iwhKOBBN8Com9m/fgdfpjHQpQnQqEhBEt+ALqqw7WIp6XP9C70AVsapLxh+IJvkNVmrsdg7vk8GKQhxPAoLoFrZkV+Dxq2GPJftsmHSVoGKKUFWiK9AUA56ARvrWzbImghDHkYAguoW1abbw7gVgkKeodrllmd4oTsJrsHI4M4vKooJIlyJEpyEBQXR5qqazJs0W1r0QpXro66/Ar0j3gji5gGLG5XKRI4MVhQiRgCC6vJ2Hq6j2hM9jT/aVYtYDMr1RNI+i4NGN7N30HQGfN9LVCNEpSEAQXd7a9PrdCwO8NhRdR1fkf3HRPD6DlYqycvLT9kS6FCE6Bfn0FF2aruus3lsc1r2g6BqDvUUEDDI4UTSfqhhx+4Ic3Lop0qUI0SlIQBBd2oFiB7aa8Cbhvv4KolWPjD8QLeYxWMk5cFAGKwqBBATRxa1Nt2E8YZJCsq8Eo66iygJJooX8ihmn003W9u8jXYoQEScBQXRpn+8r5oTVlRnsKURTDDK9UbScouBUFQ58vwW/xx3paoSIKAkIoss6UunmUGn48rixQSdJgWqZvSBazWOIoqKsnNzUXZEuRYiIkoAguqy16bZ6jQTJvhIsekDGH4hW0xUDTl+Qg1u+lZUVRY8mAUF0Wav3FcMJn98pXpusnihOmQMrhTk52LIyI12KEBEjAUF0SWUOH6n51WH5wKQFGOgtJiB7L4hTpComHC4PGd/LlEfRc0lAEF3SugMlJzYe0N9fhlXzye6N4pTpioJdNZG3ZzeOyvJIlyNEREhAEF3S5/uKMZw4/sBrw4COJtMbRRvwKBaq7TUy5VH0WBIQRJdT4w2wJbsC7fgmBF1nsLcIVf6XFm1FUXAEIGPLdwT8vkhXI0SHk09T0eVsOFgatrQyQFKgmvigQ7oXRJuq1sxUlZVxeM/uSJciRIeTgCC6nDVp9TdnSvaVYNKCMkBRtClNMeLyBTiweaNMeRQ9jgQE0aV4AyrrG2hBGOwpRFcUmd4o2lylaqYsL4eSnKxIlyJEh5KAILqUzVnl+IJa2GNRqoe+/nJZHEm0C49mxOn2krH1u0iXIkSHkoAgupS16TZMDXQvWPWALK8s2oWiKDg0I3l7dlFTXhbpcoToMBIQRJcRVDXWpNkIntC9MNBbDLqOrsj/zqLt6UCF34jH5eLQD5sjXY4QHUY+UUWXsfNwFTXeYNhjBl1loLeIgLQeiHakKwoe1UDG1k2yy6PoMSQgiC5jbXpJvdkL/X1lRKtemd4o2l2FasRVXUXO7h2RLkWIDiEBQXQJuq7z+b7ierMXUrzFGNBQZfVE0c5cAQioGgc3b0TXtJOfIEQXJwFBdAn7i2uw1XjDH9R1hngKUJFwINqfQu0ujxUFRyjM2B/pcoRodxIQRJfw1f6Sensv9ApUEa86pXtBdAgdKPPqqIEAGVtkyqPo/iQgiC7h833FnNC7QIrPhkmX1RNFx1E1HZ/RypH9+6iyFUW6HCHalQQE0ekVVLnJLHHWe3ywpxAdWT1RdKxynwG/18OhbVsjXYoQ7UoCguj0vkwvqZcBYoNO+vor8Un3guhgNb4gmCxkbdsiUx5FtyYBQXR6n+8rru0APs5AbzFmLSDLK4uIcOhmXNXVMuVRdGsSEESnVunyszO/6sR8cLR7AeleEBFR6gyioJCx5VuZ8ii6LQkIolP7+kAJJ+6yG6V6GOArlb0XRMT4VY2AJZqKgiMUHcqIdDlCtAsJCKJTW5tef3rjQK8Ni+aX6Y0iYhSgwqMRDPg5tG1LpMsRol1IQBCdljeg8u2hsnrTGwd5CkBBNmcSEaMDle4ApqgY8vel4qyqjHRJQrQ5+YQVndZ3h8rxB8P7dy2qj4E+GwFFuhdEZOlAjWbC53KSs3NbpMsRos1JQBCd1lf7bZhO6F8Y6CvGqvlkeqPoFMqcfgwmExnfb0INBk9+ghBdiAQE0Smpms7a9BKCJ/QvDPYUoui6dC+ITsHtV9EssdhLSyg8KPsziO5FPmVFp7Qrvwq7JxD2mFnzM8hbJLMXRKehABVeDV1VZbCi6HYkIIhO6ct0G8YTuxe8td0LfoM1QlUJEU4Hyhw+zDExFOzfh6OiPNIlCdFmJCCITkfXdT7fZ0NtpHtBk+4F0Ylouo5TN+PzuMnZtT3S5QjRZuSTVnQ6mSVOCqs9YY+ZNT+DvYXSvSA6pTKHH6PJROYPm9FUNdLlCNEmJCCITufLdFu9xZEGeYuOzl6Q7gXR+dR4AxiiYqkpK6Eo80CkyxGiTUhAEJ3OF2m2eosjDXEfAWRxJNE51Q5W1FGDKtk7f4h0OUK0Cfm0FZ1Ksd3D/uKasMeiVC+DfMWyOJLotHSgxOHDEh3N4X178DhqTnqOEJ2dBATRqazbX8KJ+zMO8hZi1fyyOJLo1IKqhkex4HM5ydu7O9LlCHHKJCCITuXzfbZ6OzgPc+ej69K9IDo3BSh1+lEUhaxtW9FP3IZUiC5GPnFFp2F3B/ghtyJs/EFs0Hl0a2dpPRCdmw5UuwMYo2IpP3KYioL8SJckxCmRgCA6jfUZJfUHJ3oKsOgB6V4QXUZlQCHg85GbujPSpQhxSiQgiE5jTZoN4/H9C7rOSHcuGlCv30GITqrU4cNkNpOzcxvBQODkJwjRSUlAEJ2CN6DyTUYZ6nH9tr0DlfQKVOMzREWwMiFaxh/U8JuicFSWU5QhayKIrksCgugUNmeV4wtqYY8Ncx/BpAUJKKYIVSVEyylAmUtFVzVydsvSy6LrkoAgOoW1J2zOZNBVRrjzCCom6V4QXYoOVLr9KFYrR9L24HE6Il2SEK0iAUFEnKrprE0vCducaaC3mFjVhc8oSyuLrskeNON1OcnftyfSpQjRKhIQRMTtPFyF3RM+mGuY+zAGXUNVjBGqSohTU+r0A5Cza1uEKxGidSQgiIg7sXshWnUzxFsoax+ILs2vagSMVkpysrCXlkS6HCFaTAKCiChd11m1tyise2Go+whW1SdrH4guTQHKvAp+r4fDsvSy6IIkIIiISi+qoaTGd+wBXec0dw66osjSyqJL04FqbxBNMZK143tZell0OfIJLCJqTVp490Jffzm9A9V4ZO0D0Q0ogEMzU20rpjQvJ9LlCNEiEhBERK3eVxzWvTDCfRijFqyd3ihEF6cDJW6VoN8v3Qyiy5GAICImq9RJbrkrdN+i+RjhziNgMMvaB6LbUHXw6AZydm2XpZdFlyIBQUTM2nQbx/UuMNRTQLTmxWuQtQ9E91IRMOKsqqA4U5ZeFl2HBAQRMav2Fh3bvVHXGeXMQgcZnCi6HUcAfP4geXt2RboUIZpNPolFRBypdHOg+NgStH395fQJVOKVwYmiG1IAh2rg8L5UfG53pMsRolkkIIiIWJtuCxtmMNKdJxsziW5LB8p8Blw1NRQc2BfpcoRoFgkIIiJW7S2u/dQELKqP4e7DMjhRdGuaYsDpDZCbujPSpQjRLBIQRIcrqfGSeqS6Lh8wwnOYaM0jgxNFt1cVMFJwcD+u6qpIlyLESUlAEB1ubbqNunYCRdcY5cxCQ1ZOFN2fGxN2u4P8NNnhUXR+8oksOtxnqUXUJYQUn43egWq8hujIFiVEB9AVAw5vkJxd2yNdihAnJQFBdKhSh5edh6uoW5b+NGcOBl0jaJDBiaJncOhmjmRlUV1ii3QpQjRJAoLoUGvSjn0oxgUdDPYWyq6NokcJKGaqa5yy9LLo9CQgiA712Z5j3QsjXblYNL8EBNGj6IqCK6CT/v0W2eFRdGoSEESHKXV42ZlX271g0gKMdmUTVIwytVH0OF6DlcL8AtnhUXRqEhBEh/li37HuhWGeI8SqLrxGWTlR9DxBxYTL7SVz145IlyJEoyQgiA7zaWph7T90ndHOQwBoijGCFQkRIYpCACM7N22RHR5FpyUBQXQIm93L7vzaxZEG+Evp66/AI/suiB7Ma7RiLy/nyIH0SJciRIMkIIgOsWpvUWiowShnFkZUgrLvgujBNMWIpqp8s/67SJciRIMkIIgO8cnuQtAhPuBgqKcAn2KRwYmix/MbzBzem4rH6Tj5wUJ0MAkIot3llbtIL6pBB0a6co5ObZR9F4TwGaxoPjfffLMl0qUIUY8EBNHuPttThEEBs+ZntDu7dtVEaT0QIrT/yGbpZhCdkAQE0a50XeffuwrQdBjuPkys6pbBiUIcx2ewoJUeZu/B3EiXIkQYCQiiXaUX1XC4wo2ia4x1ZqKB7NooxHH8igWzHuDf/1kX6VKECCOf1KJdfbK7EKNBYZC3iF6Bajyya6MQ4RQFDQNVB3Zjq3ZFuhohQiQgiHYTVDVW7ipAVTXGOA9h0DVU2bVRiHq8higSgnaW/3dTpEsRIkQCgmg33x4qo8odoE+gkhSfTZZVFqIRQcWIUVPZu/V7nL5gpMsRApCAINrRRzsKMBoURjuzMGlB/Io50iUJ0TkpCgGDmUGOPN77LiPS1QgBSEAQ7aTa7eer/SVE+Z0Mdx/Gb5CFkYRoitdgJUr18vnab/EHtUiXI4QEBNE+PttThKrpjHJlYdV8eGVhJCGaVDe7p19FJp/sKohwNUJIQBDt5L0f8msXRnJl1+65IK0HQpyUz2ilv7+c5Wu2o2l6pMsRPZwEBNHm0ovsHLQ5GOHOI0Z145HBiUI0i18xY9ICWIoO8uV+W6TLET2cBATR5j7YdgSzUrswko4iCyMJ0VyKQlAxcZo7j798dQBdl1YEETnyyS3alDeg8u9dBQx0HSEpYMdjlIWRhGgJr9FKrOrEkXuQLdkVkS5H9GASEESbWrW3GLcvyFhnJug6qmKMdElCdCmaYgQdRrmy+fP6Q5EuR/RgEhBEm1q+JY9kfyn9fWWyMJIQreQzWunvKyXjYDZ7jlRHuhzRQ0lAEG0mrdDOvkI7YxyZGHWVgCLLKgvRGn7FjFkLcJonlz+vz4p0OaKHkoAg2sw/tx6mT7Cawd5CvEarTG0UorUUhYDBxAhnLhvTj3CoxBHpikQPJAFBtAm7O8AnqYWMqsnErAXwK5ZIlyREl+Y1RBGjeRjpyecvG6QVQXQ8CQiiTXy08wgWbw0j3HmyrLIQbUBXDOjAKEcm/00t4EilO9IliR5GAoI4Zaqms2RzLqOcsqyyEG3JY4imd6CaFF8Jb27MjnQ5ooeRgCBO2boDJVRUVDPalU3AIMsqC9FWggYTBl3lNMchPtx+BJvdG+mSRA8iAUGcsrc2ZjPGnUOM5sFrkKmNQrQlr9HKIG8Rib5K3v5WWhFEx5GAIE7JniPV7MsrY7QjExWDLKssRBvzKxbMWoCRziz+9X0+FU5fpEsSPYR8motT8va3OYzy5BKvOnHLsspCtD1FwW8wM9Kdh8Xv4G+bciNdkeghJCCIVjtS6Wbt3iOMrTmIJpsyCdFuvIYoolQvpzmyWLo5l0qXP9IliR5APtFFq731bTYj3YdJCNZI64EQ7UlRCBpMjHFlofg8/O27nEhXJHoACQiiVUodXlb8kMe4mgPoKLUbzAgh2o3HEEWM5makM5slm3OpklYE0c4kIIhWeefbHIY6c0kKVkvrgRAdQFcMqBgZ58xA93v52yZpRRDtSwKCaLEql59/bclhvOMgOkjrgRAdxG2MJi7oYqQzh79vklYE0b4kIIgW+/umXAY5cukVqMJjjIl0OUL0GLpiQFUMteHc7+UtWRdBtCMJCKJFqlx+ln6bxfiaA+iAKq0HQnQotzGa+KCT05zZLN2cR5lD1kUQ7UMCgmiRNzdmM7Amm16BKtzSeiBEhzvWinAAxe/hDdnpUbQTCQii2UprvPzjuywm1OyXsQdCRFDdWITRjkz++f1hCqs9kS5JdEMSEESzvfb1IYY5s0kM2qX1QIgI0hUDQYOJ8c4MooJuXv0qM9IliW5IAoJolrxyFx99n834mv2y7oEQnYDbEE206mGs/QD/3lVAZokj0iWJbkYCgmiWF9ceZJQr++iqidJ6IETEKQp+g4XRrix6Bey88PmBSFckuhkJCOKkUo9U83VqHuNr9qNiRJM9F4ToFLwGK1bNx6TqPWw4WMoPORWRLkl0I/JJL5qk6zrPrtrPROdBYoMuWTVRiM5EUfAYoxjiLWCwz8bTq/ajaXqkqxLdhAQE0aS16SVkZuUzxplJwGCWHRuF6GQCBgsGTWOyPZWDhVV8mloY6ZJENyGf9qJRvqDKs6v2M9mRRpTqw2OIinRJQogGuE0x9PVXMMaZxcLPD+D2ByNdkugGJCCIRi3fkkew5DDD3Xl4jFZQlEiXJIRogKoY0TBwuiMdj72av34jSzCLUycBQTSo3Olj8VcZnGnfg0kL4lcskS5JCNEEtzGa2KCLSfa9/PWbbA5XuCJdkujiJCCIBv3hi4MMrM5mgK8UlzFGWg+E6OR0xYDPYOU0dy79vTae/E86ui4DFkXrSUAQ9aQeqeY/27KZZN9buyGTwRTpkoQQzeAzWDDqKmdW7eK7DBtf7i+JdEmiC5OAIMKoms7/frKPyY504oOO2tYDIUTXoCi4jTH081cw3nGQJz5Jw+ENRLoq0UVJQBBhPtx+hJK8XMY4D+E3WGRaoxBdjKoYCSpGTnfsJ1BdxktrMyJdkuii5NNfhFQ4fSxancbU6p2YNT9egzXSJQkhWsFtiCZK9XJ21U7+uSWPHXmVkS5JdEESEETIoi8OMqRivwxMFKKrUxTcxmgGeYs4zZPLQx+m4vGrka5KdDESEAQAOw9X8uX36Zxek4aKUQYmCtHFBQ1mAM6o3kNlRQULZTMn0UISEAQBVePRj/dwbvUOolSv7LcgRDfhMsYQF3RyRvUe/rk1jw0HSyNdkuhCJCAIlm3Ow5y9gxRvce1WztK1IES3oCsGvMYoRrpzGeIt5MEPUymt8Ua6LNFFSEDo4YqqPfz9v1uYXJNWO/pZuhaE6Fb8BgsGXWNK9S4Cbif3v78bVXZ8FM0gAaGHe/Lfu5ha/j1WzYfbIF0LQnRHTmMsiQE7k6pS+SGngle+kqmP4uQkIPRgX+wrxvHDl/TxleM0xUrXghDdVG1Xg5XR7hwGewv5y4Zs1qbbIl2W6OQkIPRQNd4Aby3/hDGuLLxGK5pijHRJQoh25DdYMegq51TvJFr18rsPdpNZ4oh0WaITk4DQQ/3x/Q2MLdmGTu0HhxCi+3MaY0kI1HCWfTeBgMZtS7ZR4fRFuizRSUlA6IG2pOVh/2YlUapX9loQogcJzWpw5TLYfZhSh4/bl26XRZREgyQg9DBOl5sVf/kLSYFqHKY4GXcgRA/jN1hQ0JhavQur30l6kZ1739slMxtEPRIQehBd03jzT2+SWHMElzFGNmISoodyGWOJCzo5t3oHuqax4WApj63ch65LSBDHyDdED6HrOp9/+DE1+7fjNUTJUspC9GC6YsBtjGaop4AxzkPowIodR3hu9QEJCSJEAkIPkb5pIzvW/JegYsZvsES6HCFEhAUNZlQMnFmzl17+KgD+vimXP6w5KCFBABIQeoTc3TtY+69/4Q/qeIxRkS5HCNFJuI2120JfUPUDJi0AwJsbc3hpbYaEBCEBobs7kr6XL5cvodrplk2YhBDhFAWnKZZ+vjKmVO+Co6HgjW+yeeELaUno6SQgdGPFhzLY8M8llFTYcRllpUQhRH2aYqxdZdGVzWnu3NDjb3+bw5P/SUeT2Q09lgSEbsqWlcn6pW9RUlpBlRKDLuFACNGIusXSplbvpLe/MvT4P78/zIMf7sYf1CJVmoggCQjdkC37EF8veZOqikqKglHSciCEOCmXMYYo1ctFlVuxqse2hP7v3mLuWLoNpy8YwepEJEhA6GZs2Yf4+u9/xVldTb7fKuFACNE8ioLTFEdvfyUXVP2AQa9dXVHXYWtOBb/86xZKa7wnuYjoTiQgdCN14cBdU02ZHk1Q+g6FEC2gHV0fYZjnCGfa94QGLWo6HCp1cu3rm8iwyQZPPYUEhG7ClpXJ10tqw4HXmkiFO4DEAyFESwUNZnyKmQmOg4xxHQo9rmo65U4/1/9lM18fKIlghaKjSEDoBooyD7JuyV9x2+2YE/uQV+GOdElCiC7MZ4xCR2Fq9S6GeApCj6uajjegctfyHby1MVumQXZzEhC6uIIDaaxf+iaemhpi+/Qls8Qpv7RCiFPmNkZj1INcWLmVAd5jLQb60dsLXxzkdx/slp0guzEJCF3Y4X2prF/2Nl6ng/i+/cgtd+MJqNK1IIQ4dYqC0xiHVfXxo8rN9PFX1Dtk1d5irv/LJo5USqtldyQBoYvKTd3Jxn/+Hb/bTXyffpTU+Ch3+iJdlhCiO1EUHKY4YlUX08o30tdXHva0pkNWmYufLv5OxiV0QxIQuqCs7d/z7b+W4Pd6iO/TlxpfkLwKV6TLEkJ0R4pCjTGeONXFtIpv6e8rDXta1XRcviB3Lt/B86v3y6JK3YgEhC5E13UObPqG7z5YTjAQIL53X/yqTqZMOxJCtKejISEm6GZa+bcM8hSGPV3Xrfm3Tblc/8ZmcsvlD5buQAJCF6HrOqlfrmbrx++jaxpxvXqj6nCguAZV1jsQQrS3o90NVs3LJRWbGOXMCq2TUEfXIcPm4Ko/fcs/vz8sA6a7OAkIXYCmqny/8gN2rv4Ug9FIXFJvdEUhs8QhgxKFEB3n6MBFo65yftU2zrKnhlZcrKNqOr6gxoJP05j1tx8oqvZEqFhxqiQgdHJ+r4cN/3iHtA1fYYmKJiYhER3IKXNi9wQiXZ4QoqdRFFymWIKKkcmOdC6p2ESU2vASzD/kVnLFKxt5f1u+7ArZBUlA6MSclRV8+dafyd7xA9HxCUTFxqEDhytclDlkxoIQInJ8xijchiiGufO5snQd/Xxl9Y5RNR23X+Wxlfv45ZtbSC+yR6BS0VqK3spOopqaGhITE7Hb7SQkJLR1XT1ecVYG3723nGpbMXG9e2MyWwAoqHJzpEqa7IQQnYOia8SpLgKKmb0Jp7M/fjy6Uv9vT6NBQdN1Zp03lP/5yVh6xVoiUK2A5n9/S0DoZDRVJe2br9i9ZhV+j5v43n0xGI0AFFZ7yJcFSYQQnY2uE615MOkqhVED2ZZ0Dg5zfIOHGhSIsZj4nyvHMOu8YVhM0pDd0SQgdEE15WVs/fg98tP2YrKYiUlIQlEUdKBQWg6EEJ2cSQsSo7pxG2NITZxMVuxpDbYm1BncK5r/nTGen56ejCJb03cYCQhdiKaqZGz5ll1f/BdXdRWxSUmYrVEAoTEHxXbZh10I0QXoOrGqGwMaRVEpbE+agt2c1OChilI7NXLCwAQe++k4Lh7VV4JCB5CA0AXouk5R5kF2rf4UW04WRqOR2KReKIbaxK3pOodKnVS6/BGuVAghWsakBYhRPfgMVvbHj2N//HiCBnODxxqU2mWbpw7rxbzpYzl/ZJ8OrrZnkYDQiem6ji0rk30bvqTgQDpqwE9sYi9MlmODdnxBjQybA5c/GMFKhRDiFOg60ZoXsxagytyLPYmTOBw9tLbpoAFGBVQdzh3Rm4d/MkaCQjuRgNAJBfw+8vft4eCWbynJPkQw4Cc6PgFLVHRYs5rdEyCzxIGq6bIIkhCiyzPoKrGqGx2F4qhkUhMmU27t1+jxdUHh7KFJPHjFGH40Wroe2pIEhE5C01TK8nLJ27ubnF3bcFVVousQHR+P2RoV9j+9puscqfLIymNCiG6prtshaDCRHz2E9PjxVFoabyWo63qYODCBB68Yw+Xj+mMwSFA4VRIQIkhTVUrzcig4kEZu6k4c5WUEA37MFitRcfEYTaZ65zh8QbJLnXgCagNXFEKIbkLXseh+olQfAYOZgqhBHIgfR5mlb6NdD3VBYUTfWO69bBQ/O2OgTI88BRIQOljA68WWnUlhxn4O703FVV1FMODHZDJjjY3FZLE22EQWUDXyK92UysqIQoie5LigEDSYKLX041DcKI5EDUY11P8jCkChdmZXvzgrd/1oBDeeM5TEmIYHPorGSUDoAM6qSoozD1JwMJ3Cg+l4XU50VcVosWCNjsVksTTabxbUdIrtHoqqvei6jDUQQvRQuo5ZD9bu56CAyxhLbswwCqIHU2bp2+g6CooCFqOB/zd1MLddMJzRAxpemEnUJwGhHWiaSnn+YYoPZXAkfS8VBfn4vR7QwRwVhTUmBqOp6TTrCajYaryU1vjQZCtUIYQIMegqUZoPkxZEVYy4TLEciRpESVQyZZa+eI1R9c4xGhRUTeec4b249YLhXDlxAFaTMQLVdx0SENqIu8aOLTuT4kMZFOzfh6u6GjUQQDEYsETHYImOxmBoui9M1XWqXH5KanzUeAOhZjIhhBAN0HVMuopF82PSg+iKQkAxU21OosTaj0pLb6pNidSYE9CU2jBQN04hPsrEDWcP5udnDWLy4ESZ/dAACQitpAYDlOcfxpadScGBdMqPHMbv8dT+D2uxYImObnQ8wfECmk6120+ly0+VO0Arf8xCCNHjKbqGRQtg1gMYdA1QCBqMBBUTNaZ4qs1J1JgScJpicZri8JjjcGNhcO8YfnHWIGZMTmHsgHgJC0dJQGgmXdepthVRkptN8aEMig9l4HXWoAaCR1sJorFERYc2TGqMqus4vUHsngDV7kBogSNpLRBCiDam65j0ICZdxXj0pisKCqBiQFWM+A1mHKZ4asyJOI2xWBOSOHPcMC44fQQXnj6cmKieu5ukBIRGaJqKvcRG2eFcSnNzKMo8gMteTdDvqx1LYLViiY7BaDY3mjZ1wBtQcfmCOH1BHN4gLl8QHQkEQggRMbpeGxhQMeoaRl3FoGu14UHX0QzG2gBhMGGOS6J3cjJDhqQwevhAknr3Jjo+gej4BKyxcViio7tti0Nzv78bnkvSjXicDioLC6gqKqAsPw9b9iG8TgdBnw8dMFssmKOiiEmo31elUzvbwONX8QSCuP21ocDlU0MDDE8MBBIOhBAiQhQFVTGhNvTVpusYqA0NRk0Feyn26mKqM1JJA0wGBYvFjMVsJspqJtpqJjomBnNUNCaLBZPZzBlXXs2gseM7/G1FSrcICLqu43U6cFZW4Kgop6aslOqSYioK8nFWVRL0+dDU2gWITFYrZquV6IQEdBQCQR2fquFwBwioGr6ghi+g4gmo+AIa6nENLA21DkggEEKILkBR0DCiKUYCDT2v6xgDGopfxeAKYNB1jEoVVqOC2aBgUn0UWZMZqfemX1wUfeMt9IqxEGU+tRkTuq4f/d7R8Kkq/qCGptV2W+u6zvA+sRFbPbJTBgR7qY2q4iLQdTRNo6TaxeEyB1owgBbwEfR5Ub0egs4agk47QVcNejCAHgyiqQFAQdd1VIMRzWAiaDCh6maCOgS9OqrmQdXcDX65N9VFIGFACCG6KUVBxQhK+Be+SwdFhbign29SC0nL2RH2vMmgEGMxEmWuvVlNBkxGBYOi1C4Mqde2RAdUDX9Qw6/WhgH/0ftBrelvlsdnjOc3l4xs63fbLJ0yIPzw6Ucc3rsbqE1X5Q4fvmBtP1JdR7+i6+iKgoYBVTGgKbV9S5oSdWy5zqOrFutogNas15YQIIQQ4nhNfS8ENZ0ab5Aab/vsvFvjbbC9o0N0yoCgqSpBv//oSoQGNJTacAC1f+JDaMSqEQ2jroEu2yILIYRoHwo6RoOC2dhxzf0BVSeSwyQ7ZUA444qfkjJqbOj+oVIH2WXOCFYkhBCiZ1M4f9BYzo/r1YGvqPDzswd32OudqFMGhJTRY0kZfSwgnBHBWoQQQoieSPbLFEIIIUQ9EhCEEEIIUY8EBCGEEELUIwFBCCGEEPVIQBBCCCFEPRIQhBBCCFGPBAQhhBBC1CMBQQghhBD1SEAQQgghRD0SEIQQQghRjwQEIYQQQtQjAUEIIYQQ9UhAEEIIIUQ9rd7NUdd1AGpqatqsGCGEEEK0r7rv7brv8ca0OiA4HA4AhgwZ0tpLCCGEECJCHA4HiYmJjT6v6CeLEI3QNI2ioiLi4+NRFKXVBQohhBCi4+i6jsPhYODAgRgMjY80aHVAEEIIIUT3JYMUhRBCCFGPBAQhhBBC1CMBQQghhBD1SEAQQgghRD0SEIQQQghRjwQEIYQQQtQjAUEIIYQQ9UhAEEIIIUQ9EhCEEEIIUY8EBCGEEELUIwFBCCGEEPVIQBBCCCFEPf8fNstjWHo/H+AAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1116,14 +1434,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/dwells/miniconda3/envs/hlatest/lib/python3.10/site-packages/arviz/plots/traceplot.py:217: UserWarning: rcParams['plot.max_subplots'] (20) is smaller than the number of variables to plot (86), generating only 20 plots\n",
+      "/home/dwells/miniconda3/envs/hlafreq/lib/python3.10/site-packages/arviz/plots/traceplot.py:217: UserWarning: rcParams['plot.max_subplots'] (20) is smaller than the number of variables to plot (45), generating only 20 plots\n",
       "  warnings.warn(\n"
      ]
     },
@@ -1172,13 +1490,13 @@
        "        <AxesSubplot: title={'center': 'frac\\n19'}>]], dtype=object)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1200x4000 with 40 Axes>"
       ]
@@ -1191,11 +1509,18 @@
     "\n",
     "az.plot_trace(idata, compact=False, combined=False)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "hlatest",
+   "display_name": "hlafreq",
    "language": "python",
    "name": "python3"
   },
@@ -1209,12 +1534,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+    "hash": "46d2d82dbc865cefb79a4a45cbcd8ead329d89ff6c8b099bf15de0f92559257f"
    }
   }
  },
diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
index dbb44c7..59f5f0d 100644
--- a/examples/working_with_priors.ipynb
+++ b/examples/working_with_priors.ipynb
@@ -16,9 +16,18 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+     ]
+    }
+   ],
    "source": [
     "import HLAfreq\n",
+    "import HLAfreq.HLAfreq_pymc as HLAhdi\n",
     "import pandas as pd\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt"
@@ -60,7 +69,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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YMEHp6elatWqVbr31VqstQA04yyu0bneePD1sCvDz1sHPNujEj3mKfmim/AOC1NzXqc/zCrX72wL1799fiYmJWrlypZxOp7y9veu6fABAPWE5GK1YsULt27dXRESEEhISNHHiRCUnJ8tmsykxMVF9+/ZVz549JUlZWVlq1aqVpNOP3zp16qTmzZu71urXr5+SkpKUk5NTZfCpqKhQUVGRmjRp4hpzOBwaOXKkDMM4a40FBQVux5xtTocOHc45p6SkRCUlJa7twsJCSVJZWZmlxzxn5tbnR0PfFZzSd8d/UoCfpyqMCuXv36VGTcMUHN5WFUaFfL1sKikr1xd5BeoY2lBxcXGaN2+evvrqK7Vr166uy7/o8T1mDf2yhn5ZR8+sqe1+WVnXcjCy2+1KSEiQdPpuTUFBgTZu3KioqCgtXrxYc+bMcb17NGTIEI0bN04JCQnKy8tzC0WSXNt5eXlVnmvmzJkqLi52exE3KChIERERZ61v3759euGFF1x3i6qyYsUKffrpp3r55ZfPea3Tp09XSkpKpfH09HT5+/uf89iqZGRkWD7mUlFQKhUUeOqkh6GTXtLJU6fkLC3RkSNHZLPZZBhS8Smbdu3cKZ/D2crKypJ0OlDv27evjqv//ajP32M1Qb+soV/W0TNraqtfJ0+erPZcS8EoNzdXWVlZrnc/vLy8NHToUNntdkVFRSk/P18ZGRlauXKlJGn27NmaN2+elVO4LFmyRCkpKXr77bcVEhLiGh80aJAGDRpU5THffvut+vfvrzvvvFMPPPBAlXM2bNigkSNHat68ebr66qvPWUNycrImTZrk2i4sLFR4eLhiY2MVGBhY7WspKytTRkaGYmJi6u1jIcMw9GnZbu39rkghTRqo/Lo++ipzpSqOfqMWHbqr6JRTzRqU656bO6ltSCMtWrRILVu21N133y0fH5+6Lv+ix/eYNfTLGvplHT2zprb7deaJT3VYCkZ2u11Op1NhYWGuMcMw5Ovrqzlz5riFCEkKCAhwjYWGhrruApxx5MgR176fW7Zsme6//3698cYbio6OrlZthw8fVp8+fXTDDTfolVdeqXLOxo0bNWDAAKWmpmr48OHnXdPX11e+vr6Vxr29vWv0B1fT4y4VA7teri/zc3X0RJlatO+hy1pFaMuCp/Wn8f/USf/m6t0uRFc1D9CLL76oVatWKSkpST4+PvW6Z1bV9+8xq+iXNfTLOnpmTW31y8qa1f5UmtPp1KJFizRr1ixlZ2e7vnbu3KmwsDAtXbrUNTcxMVGJiYlux0dGRmr37t3Kz893jWVkZCgwMFAdO3Z0jS1dulQjR47U0qVLz/rjAH7p22+/VVRUlLp3764FCxbIw6PyZWVmZiouLk7/+Mc/NHr06OpeNn5DN3UIUcL1rWQY0sGjP6nD8KdULk+te/IefbUoWbnLn9VVV12lCRMmaMKECYqNja3rkgEA9Uy17xilpaXp2LFjGjVqlIKCgtz2xcfHy263uz6BVpXY2Fh17NhR9957r2bMmKG8vDxNnjxZY8eOdd2VWbJkiUaMGKHnnntOvXr1cr171KBBA9c5V69ereTkZH3++eeS/huKWrdurZkzZ+r77793nfPMnagNGzbo1ltv1YQJExQfH+9a18fH57wvaeO3Y7PZlHD9Fbq+zWXamPu9vjneTLdct0aFORv1743v6uv/O6C+fftq9OjRuvbaa7Vu3bq6LhkAUM9UOxjZ7XZFR0dXCkXS6WA0Y8YM7dq1S507d67yeE9PT6WlpSkpKUmRkZFq2LChRowYoaeeeso155VXXpHT6dTYsWM1duxY1/iIESNcPzCyoKBAubm5rn0ZGRnat2+f9u3bp8svv9ztnGc+ubZw4UKdPHlS06dP1/Tp0137e/furczMzOq2AL+RtiEBahsS8N+B27pKyRPc5vBJDgBAXah2MFqzZs1Z9/Xs2fOcH58/o3Xr1ue8C1CdkPLLx3RVPbb7pbP9JG4AAICf45fIAgAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYPKq6wJwafmxuETr9+Zr05ff60SJU43Ljytv21vatn6diouL1aFDB40ZM0Z33XWXPD0967pcAADc1OiO0bZt2+Tp6am4uLgq9zscDjkcjkrjhw4dUlxcnPz9/RUSEqJHH31UTqfTtX/VqlWKiYlRs2bNFBgYqMjISL3//vvnreeZZ57RDTfcIH9/fzVu3LjKemw2W5Vf+fn51b5unNuBH07okTd26qWN+/XlkWJ9sfvfmjN+sFYue12tuv1JEyc+LD8/PyUkJGjIkCFuf/YAAFwMahSM7Ha7xo8fr02bNunw4cOu8dTUVBUVFbm2i4qKlJqaKkkqLy9XXFycSktLtXXrVi1cuFAOh0NTpkxxzd+0aZNiYmK0bt06bd++XX369NGAAQO0Y8eOc9ZTWlqqO++8U0lJSVXuHzp0qL777ju3r379+ql3794KCQmpSQvwC87yCs1Kz9XBH0+qVRN/tWjkqR0L/q7LwtvqlqfflN+fRqnrbSOVkZGhd955R++8847rewMAgIuF5WBUXFys5cuXKykpSXFxcW53hoKDgxUTE6PNmzdr8+bNiomJUXBwsCQpPT1de/bs0eLFi9W1a1fdfPPNmjp1qubOnavS0lJJ0uzZs/WXv/xF1113na666ipNmzZNV111ldasWXPOmlJSUvTwww+rU6dOVe5v0KCBQkNDXV+enp768MMPNWrUKKuXj7PI/vq4vjxSrBaBfvL0sOng9g366fgPunHk47osuLFskt7dnaeKCkMDBgxQQkKC5s6dq4qKirouHQAAF8vvGK1YsULt27dXRESEEhISNHHiRCUnJ8tmsykxMVF9+/ZVz549JUlZWVlq1aqVpNOP3zp16qTmzZu71urXr5+SkpKUk5Ojbt26VTpXRUWFioqK1KRJE9eYw+HQyJEjZRiG5Ys9Y9GiRfL399cdd9xxznklJSUqKSlxbRcWFkqSysrKVFZWVu3znZlr5Zjfmy/yClRWUSFfb5sqjArl79uloBatFRjaShVGhQL8vHTo6AnlF5zQZY18NWDAADkcDn399dcKCwurtF596NlviX5ZQ7+soV/W0TNrartfVta1HIzsdrsSEhIkSf3791dBQYE2btyoqKgoLV68WHPmzHG9ezRkyBCNGzdOCQkJysvLcwtFklzbeXl5VZ5r5syZKi4u1pAhQ1xjQUFBioiIsFp2pWu455571KBBg3POmz59ulJSUiqNp6eny9/f3/J5MzIyLB/ze7E736biIg8dKSuSzSb9dKpEpSWndOTIEdlsNp10ShUVNn24fr0aeksff/yxJCkzM7PK98LOuJR7VhvolzX0yxr6ZR09s6a2+nXy5Mlqz7UUjHJzc5WVlaXVq1efPtjLS0OHDpXdbldUVJTy8/OVkZGhlStXSjr9aGzevHlWTuGyZMkSpaSk6O2333Z7D2jQoEEaNGhQjdaUTt+52rt3r1577bXzzk1OTtakSZNc24WFhQoPD1dsbKwCAwOrfc6ysjJlZGQoJiZG3t7eNar7YnfFd4XKXpWjhn6eauTrpdLronRwyzuyFR1RSNvOOnT0J117eZDuuO1q2Ww2zZ8/X506ddLdd98tm81Wab360LPfEv2yhn5ZQ7+so2fW1Ha/zjzxqQ5Lwchut8vpdLo9+jAMQ76+vpozZ45biJCkgIAA11hoaKiysrLc9h85csS17+eWLVum+++/X2+88Yaio6OtlHhe8+fPV9euXdW9e/fzzvX19ZWvr2+lcW9v7xr9wdX0uN+DzuFN1K1VsLZ99YN8PD0V3ukGNW7ZRh/Nf0o9Rs+Qb9OWGtjtcnl6eio1NVVpaWlyOBzy8fE557qXcs9qA/2yhn5ZQ7+so2fW1Fa/rKxZ7ZevnU6nFi1apFmzZik7O9v1tXPnToWFhWnp0qWuuYmJiUpMTHQ7PjIyUrt373b7eHxGRoYCAwPVsWNH19jSpUs1cuRILV269Kw/DqCmiouLtWLFCl66rgU2m02TYtupa3iw8otKdPDoT+o44mmVOSu04ZlhOrz077I/84jatGmjRx99VI899piGDx9e12UDAOCm2neM0tLSdOzYMY0aNUpBQUFu++Lj42W32zVmzJizHh8bG6uOHTvq3nvv1YwZM5SXl6fJkydr7NixrrsyS5Ys0YgRI/Tcc8+pV69ernePGjRo4Drn6tWrlZycrM8//9y19qFDh3T06FEdOnRI5eXlys7OliS1bdtWjRo1cs1bvny5nE6n6x0p/LaaNvLVs/GdlHXgqLIOHFVxSTMlRKXr2O4PtSl9rfbv36/Y2Fg9+OCD6tGjR12XCwBAJdUORna7XdHR0ZVCkXQ6GM2YMUO7du1S586dqzze09NTaWlpSkpKUmRkpBo2bKgRI0boqaeecs155ZVX5HQ6NXbsWI0dO9Y1PmLECNePBSgoKFBubq7b2lOmTNHChQtd22c+4bZhwwZFRUW5XcPgwYPP+bIvfh1fL0/98apm+uNVzf47GHO1/jZpfN0VBQBANVU7GJ3rZwn17NmzWh+fb926tdatW3fW/ZmZmeddo6rHdGf7Sdu/tHXr1vPOAQAA9Re/RBYAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABMBCMAAAATwQioJ4qKivS3lGlq2SZCfo0aK7hlG912/yPKyv26rksDgItGjYLRtm3b5Onpqbi4uCr3OxwOORyOSuOHDh1SXFyc/P39FRISokcffVROp9O1f9WqVYqJiVGzZs0UGBioyMhIvf/+++et5+jRoxo2bJgCAwPVuHFjjRo1SsXFxa79p06dUmJiojp16iQvLy/dfvvtlq8Z+D37/vvv1aV7T/3j6SflDLpcrfsMlX/YVVq78Hn1/dONem19dl2XCAAXhRoFI7vdrvHjx2vTpk06fPiwazw1NVVFRUWu7aKiIqWmpkqSysvLFRcXp9LSUm3dulULFy6Uw+HQlClTXPM3bdqkmJgYrVu3Ttu3b1efPn00YMAA7dix45z1DBs2TDk5OcrIyFBaWpo2bdqk0aNHu/aXl5erQYMGeuihhxQdHV2TSwZ+10beP1qH847o+v83X3EPTdf/xN+v/mOf1qCpS+Us+UmPPJSkL44UnX8hALjEWQ5GxcXFWr58uZKSkhQXF+d2Zyg4OFgxMTHavHmzNm/erJiYGAUHB0uS0tPTtWfPHi1evFhdu3bVzTffrKlTp2ru3LkqLS2VJM2ePVt/+ctfdN111+mqq67StGnTdNVVV2nNmjVnrWfv3r167733NH/+fPXq1Uv/8z//oxdeeEHLli1zhbaGDRvqX//6lx544AGFhoZavWTgd+3rr7/WurR31DomUe0i2stms7n2BYW20nV3/Fn5ez7WkoysOqwSAC4OXlYPWLFihdq3b6+IiAglJCRo4sSJSk5Ols1mU2Jiovr27auePXtKkrKystSqVStJpx+/derUSc2bN3et1a9fPyUlJSknJ0fdunWrdK6KigoVFRWpSZMmrjGHw6GRI0fKMAzXuo0bN1aPHj1cc6Kjo+Xh4aFPPvlEgwYNsnqJLiUlJSopKXFtFxYWSpLKyspUVlZW7XXOzLVyTH1Hz6w5V78+/vhjGRUVCun0P5IMVZj/7pzR6trekl3atGWryob+6UKUW+f4/rKGfllHz6yp7X5ZWddyMLLb7UpISJAk9e/fXwUFBdq4caOioqK0ePFizZkzx/Xu0ZAhQzRu3DglJCQoLy/PLRRJcm3n5eVVea6ZM2equLhYQ4YMcY0FBQUpIiLCtZ2Xl6eQkBD3i/LyUpMmTc66bnVNnz5dKSkplcbT09Pl7+9veb2MjIxfVU99RM+sqapf2dnZkqSiguPKz/eutL+kuOD0/sIirVu3rlbru9jw/WUN/bKOnllTW/06efJktedaCka5ubnKysrS6tWrTx/s5aWhQ4fKbrcrKipK+fn5ysjI0MqVKyWdfjQ2b948K6dwWbJkiVJSUvT222+7BZ9Bgwb9qrtAViQnJ2vSpEmu7cLCQoWHhys2NlaBgYHVXqesrEwZGRmKiYmRt3flv5hQGT2z5lz9uv766/W/s2ap8PMt6nzNA/L0sLnt/8+OD2Tz9NI9dw7WLbd0v5Bl1xm+v6yhX9bRM2tqu19nnvhUh6VgZLfb5XQ6FRYW5hozDEO+vr6aM2eOW4iQpICAANdYaGiosrLc32E4cuSIa9/PLVu2TPfff7/eeOON874sHRoaqvz8fLcxp9Opo0eP/ur3iXx9feXr61tp3Nvbu0Z/cDU9rj6jZ9ZU1a/mzZvr3ntHaOHChdoZ1lZdbugjb09PSdLX//lEO96ap9Y9Y3Vn7871rtd8f1lDv6yjZ9bUVr+srFntYOR0OrVo0SLNmjVLsbGxbvtuv/12LV26VGPGjJEkJSYmVjo+MjJSzzzzjPLz8113gDIyMhQYGKiOHTu65i1dulT33Xefli1bdtYfB/DLdY8fP67t27ere/fT/2/3ww8/VEVFhXr16lXdywMuaXNfeE5ffnVAH736N331/lVq1KKNTuQdVNE3uQqJ6K6F81/S5cHWHw8DwKWm2p9KS0tL07FjxzRq1Chdc801bl/x8fGy2+3nPD42NlYdO3bUvffeq507d+r999/X5MmTNXbsWNddmSVLlmj48OGaNWuWevXqpby8POXl5amgoMC1zurVq9W+fXvXdocOHdS/f3898MADysrK0pYtWzRu3Djdddddbne29uzZo+zsbB09elQFBQXKzs52vXsBXOr8/PyUmfGeVqx8W106RsjnRL7CW4XrsVl27fpkk/7UMbyuSwSAi0K17xjZ7XZFR0crKCio0r74+HjNmDFDu3btUufOnas83tPTU2lpaUpKSlJkZKQaNmyoESNG6KmnnnLNeeWVV+R0OjV27FiNHTvWNT5ixAjXjwUoKChQbm6u29qvv/66xo0bp5tuukkeHh6Kj4/X888/7zbnlltu0f/93/+5ts98Cs74xSd0gEuVh4eH7hx8m+4cfFtdlwIAF61qB6Nz/Syhnj17VitgtG7d+pyfesnMzDzvGomJiZUe1TVp0kRLliw553EHDx4879oAAKB+43elAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYCIYAQAAmAhGAAAAJoIRAACAiWAEAABgIhgBAACYCEYAAAAmghEAAICJYAQAAGAiGAEAAJgIRgAAACaCEQAAgIlgBAAAYPKq6wLqs7LyCm3d/6M+2HNE3xw7qaAG3vpTu2a6qX1zfbJ5g1544QV98skn8vT0VL9+/TRhwgR169atrssGAOCSVaM7Rtu2bZOnp6fi4uKq3O9wOORwOCqNHzp0SHFxcfL391dISIgeffRROZ1O1/7vvvtO99xzj9q1aycPDw9NnDixWvWcOnVKY8eO1WWXXaZGjRopPj5eR44ccZvz0EMPqXv37vL19VXXrl2re6m1psRZrv99P1fPrN2jrft/0PdFJdrzXaHmbNinPnePUb9+/fTNN99o3LhxGjlypDZu3KjrrrtOS5YsqevSAQC4ZNUoGNntdo0fP16bNm3S4cOHXeOpqakqKipybRcVFSk1NVWSVF5erri4OJWWlmrr1q1auHChHA6HpkyZ4ppfUlKiZs2aafLkyerSpUu163n44Ye1Zs0avfHGG9q4caMOHz6swYMHV5p33333aejQoTW55N/c2zsOa/3eIwr299EVlzVU80A/hQf7y+ObndrxzqvqnTBR27dv15QpUzRt2jR9+eWXSkhIUGJiog4ePFjX5QMAcEmyHIyKi4u1fPlyJSUlKS4uzu3OUHBwsGJiYrR582Zt3rxZMTExCg4OliSlp6drz549Wrx4sbp27aqbb75ZU6dO1dy5c1VaWipJuuKKK/Tcc89p+PDhCgoKqlY9BQUFstvt+uc//6m+ffuqe/fuWrBggbZu3aqPP/7YNe/555/X2LFj1aZNG6uX/JsrcZZr3X++k6+Xhxr5uj/N/GLDGwpu1V7+PQYp90ixa9zLy0tz586Vv7+/XnnllQtdMgAA9YLld4xWrFih9u3bKyIiQgkJCZo4caKSk5Nls9mUmJiovn37qmfPnpKkrKwstWrVStLpx2+dOnVS8+bNXWv169dPSUlJysnJqfa7M5mZmerTp48OHDigK664Qtu3b1dZWZmio6Ndc9q3b69WrVpp27Ztuv76661eoktJSYlKSkpc24WFhZKksrIylZWVVXudM3PP/O83R08qv/CUAvw8VWFUuM3N3/8fdYgeqlNl5friuwK1bdrAtc/Hx0cxMTHasmWLpfP/Hv2yZzg3+mUN/bKGfllHz6yp7X5ZWddyMLLb7UpISJAk9e/fXwUFBdq4caOioqK0ePFizZkzx/Xu0ZAhQzRu3DglJCQoLy/PLRRJcm3n5eVV+/z+/v6KiIiQt7e361gfHx81bty40tpW1q3K9OnTlZKSUmk8PT1d/v7+ltfLyMiQJP14Sios9FTJCUN+nu5zDElFBcflXXxC2dk7pK8Nt/2HDh3SqVOntG7dOsvn/z060zNUD/2yhn5ZQ7+so2fW1Fa/Tp48We25loJRbm6usrKytHr16tMHe3lp6NChstvtioqKUn5+vjIyMrRy5UpJ0uzZszVv3jwrpzivnj176vPPP/9N1zyb5ORkTZo0ybVdWFio8PBwxcbGKjAwsNrrlJWVKSMjQzExMfL29pazvEKfrNilr344oZDgBm5zL7/meuXt3qL2tyVpWFw3tW7y3wD2ww8/aOfOnZoyZYpuueWWX3+BF7Ff9gznRr+soV/W0C/r6Jk1td2vM098qsNSMLLb7XI6nQoLC3ONGYYhX19fzZkzxy1ESFJAQIBrLDQ0VFlZWW77z3xyLDQ01EoZbkJDQ1VaWqrjx4+73TU6cuTIr1pXknx9feXr61tp3Nvbu0Z/cGeO8/aWbu92uVI/+ELHTzoV7O8tm80mSWrbZ4i++iRDee/OUcsHX3Od54cfftCwYcPk5+en0aNH15t/0Wra6/qKfllDv6yhX9bRM2tqq19W1qz2y9dOp1OLFi3SrFmzlJ2d7frauXOnwsLCtHTpUtfcxMREJSYmuh0fGRmp3bt3Kz8/3zWWkZGhwMBAdezYsdoF/1L37t3l7e2t9evXu8Zyc3N16NAhRUZG1njd2tb/mlDddV0rOSsqdPDHkzp09KQO/HhCRrMrFTc2Rdnr31LLli11zz33aPDgwbr88sv173//W2vWrFHTpk3runwAAC5J1b5jlJaWpmPHjmnUqFGVPjEWHx8vu92uMWPGnPX42NhYdezYUffee69mzJihvLw8TZ48WWPHjnW7K5OdnS3p9Kffvv/+e2VnZ8vHx8cVnrKysjR8+HCtX79eLVu2VFBQkEaNGqVJkyapSZMmCgwM1Pjx4xUZGen24vW+fftUXFysvLw8/fTTT67zdOzYUT4+PtVtw2/GZrNp5I1X6Ma2TbXpi3wdLjilQD8vXd+mqXpc8Ucdmni3Xn75ZX388cfy8vLSk08+qfvuu08hISEXvFYAAOqLagcju92u6OjoKj9GHx8frxkzZmjXrl3q3Llzlcd7enoqLS1NSUlJioyMVMOGDTVixAg99dRTbvN+/um07du3a8mSJWrdurXrZ/ecPHlSubm5bm+Yp6amysPDQ/Hx8SopKVG/fv304osvuq17//33a+PGjZXOc+bTbXXBZrMpIjRAEaEBlfZdeeWVmjFjRh1UBQBA/VXtYLRmzZqz7uvZs6cMwzjr/jNat2593k9TnW+dqKioSnP8/Pw0d+5czZ0796zHZWZmnrc+AABQv/FLZAEAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATAQjAAAAE8EIAADARDACAAAwEYwAAABM1f7J1/jvT+UuLCy0dFxZWZlOnjypwsJCfstyNdEza+iXNfTLGvplHT2zprb7debv7er8lg6CkQVFRUWSpPDw8DquBAAAWFVUVFTl73z9OZtRnfgESVJFRYUOHz6sgIAA2Wy2ah9XWFio8PBwff311woMDKzFCi8d9Mwa+mUN/bKGfllHz6yp7X4ZhqGioiKFhYXJw+PcbxFxx8gCDw8PXX755TU+PjAwkH9BLKJn1tAva+iXNfTLOnpmTW3263x3is7g5WsAAAATwQgAAMBEMLoAfH199cQTT8jX17euS/ndoGfW0C9r6Jc19Ms6embNxdQvXr4GAAAwcccIAADARDACAAAwEYwAAABMBCMAAAATweg3MnfuXF1xxRXy8/NTr169lJWVdc75b7zxhtq3by8/Pz916tRJ69atu0CVXhys9CsnJ0fx8fG64oorZLPZNHv27AtX6EXESs/mzZunP/7xjwoODlZwcLCio6PP+z15qbHSr1WrVqlHjx5q3LixGjZsqK5du+q11167gNXWPav/DTtj2bJlstlsuv3222u3wIuQlZ45HA7ZbDa3Lz8/vwtYbd2z+j12/PhxjR07Vi1atJCvr6/atWt3Yf6uNPCrLVu2zPDx8TFeffVVIycnx3jggQeMxo0bG0eOHKly/pYtWwxPT09jxowZxp49e4zJkycb3t7exu7duy9w5XXDar+ysrKMRx55xFi6dKkRGhpqpKamXtiCLwJWe3bPPfcYc+fONXbs2GHs3bvXSExMNIKCgoxvvvnmAldeN6z2a8OGDcaqVauMPXv2GPv27TNmz55teHp6Gu+9994FrrxuWO3XGQcOHDBatmxp/PGPfzQGDhx4YYq9SFjt2YIFC4zAwEDju+++c33l5eVd4KrrjtV+lZSUGD169DBuueUWY/PmzcaBAweMzMxMIzs7u9ZrJRj9Bnr27GmMHTvWtV1eXm6EhYUZ06dPr3L+kCFDjLi4OLexXr16GQ8++GCt1nmxsNqvn2vdunW9DEa/pmeGYRhOp9MICAgwFi5cWFslXlR+bb8MwzC6detmTJ48uTbKu+jUpF9Op9O44YYbjPnz5xsjRoyod8HIas8WLFhgBAUFXaDqLj5W+/Wvf/3LaNOmjVFaWnqhSnThUdqvVFpaqu3btys6Oto15uHhoejoaG3btq3KY7Zt2+Y2X5L69et31vmXkpr0q777LXp28uRJlZWVqUmTJrVV5kXj1/bLMAytX79eubm5+tOf/lSbpV4Uatqvp556SiEhIRo1atSFKPOiUtOeFRcXq3Xr1goPD9fAgQOVk5NzIcqtczXp1zvvvKPIyEiNHTtWzZs31zXXXKNp06apvLy81uslGP1KP/zwg8rLy9W8eXO38ebNmysvL6/KY/Ly8izNv5TUpF/13W/Rs8cee0xhYWGVAvmlqKb9KigoUKNGjeTj46O4uDi98MILiomJqe1y61xN+rV582bZ7XbNmzfvQpR40alJzyIiIvTqq6/q7bff1uLFi1VRUaEbbrhB33zzzYUouU7VpF9fffWV3nzzTZWXl2vdunX6+9//rlmzZunpp5+u9Xq9av0MAOrUs88+q2XLlikzM7PevexpRUBAgLKzs1VcXKz169dr0qRJatOmjaKiouq6tItKUVGR7r33Xs2bN09Nmzat63J+NyIjIxUZGenavuGGG9ShQwe9/PLLmjp1ah1WdnGqqKhQSEiIXnnlFXl6eqp79+769ttv9b//+7964oknavXcBKNfqWnTpvL09NSRI0fcxo8cOaLQ0NAqjwkNDbU0/1JSk37Vd7+mZzNnztSzzz6rDz74QJ07d67NMi8aNe2Xh4eH2rZtK0nq2rWr9u7dq+nTp1/ywchqv/bv36+DBw9qwIABrrGKigpJkpeXl3Jzc3XllVfWbtF17Lf475i3t7e6deumffv21UaJF5Wa9KtFixby9vaWp6ena6xDhw7Ky8tTaWmpfHx8aq1eHqX9Sj4+PurevbvWr1/vGquoqND69evd/t/Bz0VGRrrNl6SMjIyzzr+U1KRf9V1NezZjxgxNnTpV7733nnr06HEhSr0o/FbfYxUVFSopKamNEi8qVvvVvn177d69W9nZ2a6v2267TX369FF2drbCw8MvZPl14rf4HisvL9fu3bvVokWL2irzolGTft14443at2+fK3RL0hdffKEWLVrUaiiSxMf1fwvLli0zfH19DYfDYezZs8cYPXq00bhxY9dHMe+9917jr3/9q2v+li1bDC8vL2PmzJnG3r17jSeeeKLefVzfSr9KSkqMHTt2GDt27DBatGhhPPLII8aOHTuML7/8sq4u4YKz2rNnn33W8PHxMd588023jwcXFRXV1SVcUFb7NW3aNCM9Pd3Yv3+/sWfPHmPmzJmGl5eXMW/evLq6hAvKar9+qT5+Ks1qz1JSUoz333/f2L9/v7F9+3bjrrvuMvz8/IycnJy6uoQLymq/Dh06ZAQEBBjjxo0zcnNzjbS0NCMkJMR4+umna71WgtFv5IUXXjBatWpl+Pj4GD179jQ+/vhj177evXsbI0aMcJu/YsUKo127doaPj49x9dVXG2vXrr3AFdctK/06cOCAIanSV+/evS984XXISs9at25dZc+eeOKJC194HbHSr8cff9xo27at4efnZwQHBxuRkZHGsmXL6qDqumP1v2E/Vx+DkWFY69nEiRNdc5s3b27ccsstxr///e86qLruWP0e27p1q9GrVy/D19fXaNOmjfHMM88YTqez1uu0GYZh1O49KQAAgN8H3jECAAAwEYwAAABMBCMAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAvCby8zMlM1m0/HjxyVJDodDjRs3trSGzWbTW2+99avq2LJlizp16iRvb2/dfvvtv2otAPUDwQhAjWzbtk2enp6Ki4ur61LOatKkSeratasOHDggh8NR1+UA+B0gGAGoEbvdrvHjx2vTpk06fPhwXZdTpf3796tv3766/PLLq7xjZRiGnE7nhS8MwEWLYATAsuLiYi1fvlxJSUmKi4ur0d2Yt99+W9dee638/PzUpk0bpaSknDOkfP311xoyZIgaN26sJk2aaODAgTp48GCVcw8ePCibzaYff/xR9913n2w2mxwOh+sR37vvvqvu3bvL19dXmzdvVkVFhaZPn64//OEPatCggbp06aI333zTbc1169apXbt2atCggfr06SOHw+H2uPDJJ59U165d3Y6ZPXu2rrjiCrex+fPnq0OHDvLz81P79u314osvVqp71apV6tOnj/z9/dWlSxdt27bNbY0tW7YoKipK/v7+Cg4OVr9+/XTs2DEtWrRIl112mUpKStzm33777br33nvP2lsA/0UwAmDZihUr1L59e0VERCghIUGvvvqqrPw+6o8++kjDhw/XhAkTtGfPHr388styOBx65plnqpxfVlamfv36KSAgQB999JG2bNmiRo0aqX///iotLa00Pzw8XN99950CAwM1e/Zsfffddxo6dKhr/1//+lc9++yz2rt3rzp37qzp06dr0aJFeumll5STk6OHH35YCQkJ2rhxo6TToWzw4MEaMGCAsrOzdf/99+uvf/2rxa5Jr7/+uqZMmaJnnnlGe/fu1bRp0/T3v/9dCxcudJv3+OOP65FHHlF2drbatWunu+++2xUas7OzddNNN6ljx47atm2bNm/erAEDBqi8vFx33nmnysvL9c4777jWys/P19q1a3XfffdZrheolwwAsOiGG24wZs+ebRiGYZSVlRlNmzY1NmzY4Nq/YcMGQ5Jx7NgxwzAMY8GCBUZQUJBr/0033WRMmzbNbc3XXnvNaNGihWtbkrF69WrXvoiICKOiosK1v6SkxGjQoIHx/vvvn7XOoKAgY8GCBZXqeuutt1xjp06dMvz9/Y2tW7e6HTtq1Cjj7rvvNgzDMJKTk42OHTu67X/sscfcrvGJJ54wunTp4jYnNTXVaN26tWv7yiuvNJYsWeI2Z+rUqUZkZKRhGIZx4MABQ5Ixf/581/6cnBxDkrF3717DMAzj7rvvNm688cazXnNSUpJx8803u7ZnzZpltGnTxq13AM7Oqy5DGYDfn9zcXGVlZWn16tWSJC8vLw0dOlR2u11RUVHVWmPnzp3asmWL2x2i8vJynTp1SidPnpS/v3+l+fv27VNAQIDb+KlTp7R//37L19CjRw/XP+/bt08nT55UTEyM25zS0lJ169ZNkrR371716tXLbX9kZKSlc544cUL79+/XqFGj9MADD7jGnU6ngoKC3OZ27tzZ9c8tWrSQdPrOT/v27ZWdna0777zzrOd54IEHdN111+nbb79Vy5Yt5XA4lJiYKJvNZqleoL4iGAGwxG63y+l0KiwszDVmGIZ8fX01Z86cSn/JV6W4uFgpKSkaPHhwpX1+fn5Vzu/evbtef/31SvuaNWtm8Qqkhg0buq0tSWvXrlXLli3d5vn6+lZ7TQ8Pj0qPE8vKyiqdZ968eZVClqenp9u2t7e365/PBJqKigpJUoMGDc5ZR7du3dSlSxctWrRIsbGxysnJ0dq1a6t9HUB9RzACUG1Op1OLFi3SrFmzFBsb67bv9ttv19KlSzVmzJjzrnPttdcqNzdXbdu2rdZ5r732Wi1fvlwhISEKDAysUe1n07FjR/n6+urQoUPq3bt3lXM6dOjg9t6OJH388cdu282aNVNeXp4Mw3CFmezsbNf+5s2bKywsTF999ZWGDRtW43o7d+6s9evXKyUl5axz7r//fs2ePVvffvutoqOjFR4eXuPzAfUNL18DqLa0tDQdO3ZMo0aN0jXXXOP2FR8fL7vdXq11pkyZokWLFiklJUU5OTnau3evli1bpsmTJ1c5f9iwYWratKkGDhyojz76SAcOHFBmZqYeeughffPNN7/qmgICAvTII4/o4Ycf1sKFC7V//379+9//1gsvvOB6KXrMmDH68ssv9eijjyo3N1dLliyp9Em8qKgoff/995oxY4b279+vuXPn6t1333Wbk5KSounTp+v555/XF198od27d2vBggX65z//We16k5OT9emnn+rPf/6zdu3apc8//1z/+te/9MMPP7jm3HPPPfrmm280b948XroGLCIYAag2u92u6OjoKh+XxcfH67PPPtOuXbvOu06/fv2Ulpam9PR0XXfddbr++uuVmpqq1q1bVznf399fmzZtUqtWrTR48GB16NBBo0aN0qlTp36TO0hTp07V3//+d02fPl0dOnRQ//79tXbtWv3hD3+QJLVq1UorV67UW2+9pS5duuill17StGnT3Nbo0KGDXnzxRc2dO1ddunRRVlaWHnnkEbc5999/v+bPn68FCxaoU6dO6t27txwOh+s81dGuXTulp6dr586d6tmzpyIjI/X222/Ly+u/DwCCgoIUHx+vRo0a8RO/AYtsxi8figMAziszM1N9+vTRsWPHLP+6kwvhpptu0tVXX63nn3++rksBfld4xwgALiHHjh1TZmamMjMz3X54JIDqIRgBwCWkW7duOnbsmP7xj38oIiKirssBfnd4lAYAAGDi5WsAAAATwQgAAMBEMAIAADARjAAAAEwEIwAAABPBCAAAwEQwAgAAMBGMAAAATP8f9g7kB0TXzd4AAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -89,7 +98,7 @@
     "allele. Note that `combineAF()` uses the first value in the prior for\n",
     "the first allele alphabetically and so on.\n",
     "\n",
-    "By using a more informative prior we can see how a prior can moved the\n",
+    "By using a more informative prior we can see how a prior can move the\n",
     "estimate away from the observed study."
    ]
   },
@@ -100,7 +109,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 6 Axes>"
       ]
@@ -113,7 +122,7 @@
     "manual_prior = [1, 10, 1, 1, 1]\n",
     "\n",
     "# View prior distribution\n",
-    "HLAfreq.plot_prior(concentration=manual_prior, labels=cafV.allele)\n"
+    "HLAfreq.plot_prior(concentration=manual_prior, labels=cafV.allele)"
    ]
   },
   {
@@ -123,7 +132,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -133,7 +142,6 @@
     }
    ],
    "source": [
-    "\n",
     "# Combine Allele Freq of study with Manual Prior\n",
     "cafMP = HLAfreq.combineAF(venezuelaAF, alpha=manual_prior)\n",
     "\n",
@@ -200,7 +208,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 60 Axes>"
       ]
@@ -227,7 +235,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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6nY6cnBx+/PFH2rRpA8C6detwcnLiwIED+Pr6MnjwYK5fv067du3IycnBysqK0aNHM23aNNRq/TePZcqUeeVn1YH+YZ8rf/2VjRtzsDVVYWeqYmGwjs93RtG9nh0xD7IZ2qoSlhZpmDXrxzs13nnWyykRREtFOZGVciIr5URWyomslCvxrTpHR0dUKhVqtRpJkvK16lasWEFwcDBeXl5YWlrKC4+8u0GjR48mIiICKysr3n//fUqXLs3t27cB/Z2cQ4cOodFoMDU1pXnz5pQvXx7gsaNS8vYpeXh48ODBA86ePUvt2rWJiYmhdu3aAFy/fp2PP/6Y4OBgUlNT0Wq1xMTE4Ojo+MTrLc5W3e0rf5OTk4OTlSGzOzjxjms6YXEqhmxJ4uejcfh5WFDHJgXKNMCg2jsg/qXLR7RUlBNZKSeyUk5kpZzISrkS2apr2LCh3Kjbs2cP586dw8XFhUGDBpGSkgKAl5cXXbp0ydeou3LlCqB/DlNYWBh79+6lSZMmxMXFUb58eSIiIujYsSMtW7bk3Llz7N27l4SEBMaNG0fjxo2xt7cv9LwsLCywsLCQ23mgX1meOHGCxo0bk5aWRps2bVCpVOzfv5/PPvsMSZJo3749Op2uKCNSLPTsWfYcPsHsTmWp6mJN79V3KPVNPM2WxnE7WYujhYrs7Cyo6gt+34CxsqHEgiAIgiA8vSK945TXqktNTWXlypXk5uby119/MXnyZLp06cL69evx8fGhZs2aACxevJihQ4cC+kbd/PnzadKkCdu2baNdu3ZYWVnx22+/4eHhQYsWLdi6dSu5ubmULVuWnJwc1Go11tbWJCYmMnv2bPk8IiMjadWqlbyI69u3L/fu3WPmzJmA/unj06ZNw8XFhXfffZfDhw9z8+ZNtm3bRk5ODjqdDhMTE0JCQliyZAm9e/fGwsKi0Gsurs3hv636BXtLQ0b4VmVM51JcuJPM0bA7OJSypGUlczaevsfgVeHct6yBraEliI2FMrHZUjmRlXIiK+VEVsqJrJR7WTaHq6QnVcb+o/bt23Pr1i2MjY0JCQlhx44djBkzhqtXrxISEkKjRo3YtWsXH3zwAZC/Ubd+/Xr69u3L/Pnz+fTTT3nw4AGGhoa0bNmSJUuW4OrqSkREBO7u7ri6uhITE4MkSVhYWFChQgVOnDgB6Dd4u7m5AXDgwAG8vb0BfTNu9OjR/PTTTxgZGdGsWTMWLVpE1apV2b59O506daJHjx6sXr26wHU9/DmPmjZtWqGbw9euXftMm8OXL/6RK2ePcmh8bbSagl8FHricQM+lF9j+/VC0Vfye+jiCIAiCIOg3h/fs2ZPk5OQn7lEu8lZd06ZN6dq1K/BPo+7QoUN4e3uzatUqpk6d+sRG3dy5c/n999/lRl1ERIS8z8jNzY2goCC6du1KZmam/ADLwIfaZIaGhri7u8t3m/KoVCrGjRvHTz/9xIkTJ+S9TQCenp6Ym5tjZ2dHWloakiQxceJEFixYwJAhQx67aILi2xx+81o4gUEHSM3WEXw7lfXHI0hMycDd0ZTB3uU5F5mOlYmGFu90xqjK48/vdSQ2WyonslJOZKWcyEo5kZVyJXJz+MONuuPHj+Pl5YWrq2uhjbrg4GA++OAD7t+/D+Rv1EVFRfHJJ58QHh5OdnY2Xbp0Yfv27URHRzN48GDeeustLl++zPXr1wkJCaFq1aqcOHECNze3xzbqJElizpw5gH4IcLNmzfD396dKlSrY29uzYcMGPvroI3788UckSUKtVqPRaNizZ88Tr7m4Nof3HTCYSZ99Tt2vT5OUoaNZeUNcrdTsD3/ALydCMdbA4BYVMK/aHAzEv2yFEZstlRNZKSeyUk5kpZzISrkStTn84Tl1TZs2RZIkbt26xR9//EFycjLjxo1j2bJlZGZmAmBqasrgwYOZO3eu3KgLDg7ms88+Y+LEiVy8eJFSpUrJrbmFCxdiYmLC9u3bad++PX///Tfbtm0jNjYWP78nf101a9YsVqxYAcCqVaswNzfH19dXPpc2bdowa9YsrKys+OGHH7h06RI2NjY0bdq0KCNSzMbGhjJOjiRl6KjrrGFoIwv61zenV20zzAwhSwtlrQ1Bm/1Czk8QBEEQXkdFtnB6eE7dsWPHMDExYevWrfj6+mJmZsa6desAsLW1lRcwD49cyVugfPfdd6xcuZKePXtia2tLUlKSPHIlPT1dnjH31VdfUalSJfkrtytXrjx2Y5ckScybN48RI0YAULVqVVauXElUVBRbtmyRz3/06NH88MMPjBs3jrt375KQkMCUKVOKKqL/5MSJE1y7dZfpfo6YmJjSa30ivssTmH8slX6N7OhS14Elh26ju37ghZyfIAiCILyOiuyrurxG3cCBA9m4cSM1atSgffv2qFQq+vTpQ0BAAEOHDqVfv360bNmy0JEr9evX5/Tp0xw8eJDBgwdz7949LCwsqFy5MgBt27Zl7ty5qNVqvv32W3x8fJg0aRJmZmZ4enpiaGhIZGQkb731Fjdu3JA3dZ89e5bo6Gj5rlZ4eDigH6mSN3Jl+vTpREZGyo8+uHPnDuXLl//XXfbF1aoLDAzEzsKIye0q8XkvF6LiU7kbFU2Nii6Ym5ux+3w073wfTPiJPVQWm8PzES0V5URWyomslBNZKSeyUq7Eterynnm0c+dOeYP46NGjyc3NpXTp0iQnJ3Pu3DnOnz/PggULqFGjBgBhYWHyBvFp06bx5ZdfolKpMDc3p27duuTm5hIXFyePXPntt9/44osvuHbtmjxDrnbt2hw4cAAbGxu5Vefq6soff/xBw4YN+eyzz+RHETysevXq1KxZk99//52OHTuybds2QP8gzm7duhEdHU1QUBBXrlyhVKlShV53cbXq1qxZw5HdW7k42YMsQ5sCPz9+PYnOi86z8/O25NQf/NTHEQRBEAThBbTq8ubUFTZypXfv3iQnJ/Pmm2+yd+/ex45cMTIyQpIkdu3aJY9ciY2NzTdyJa/h9vHHH9OjRw9SUlL44osveO+99wgKCqJChQoFhvK2bduWmTNnEhUVVWBWXZ5u3bqxbds2fv75Z4YMGQLo7yaVLVuWDRs28OGHHxZ63cU5cmXDhg1cvZ9F/ToOSJJEbGwsIVG5LNhznQMX76MCfg6OZkxLK7y8vB7/QdpsVDcOoLqyC1XSLTC2QlepFVJVPzAv/KGhrzLRUlFOZKWcyEo5kZVyIivlSmSrDvJvENdqtahUKlQqVb6RK6Df3wTQr1+/AiNXLly4wMcff8yVK1ewsrLC2NhYHrmycOFCAA4fPoy/vz8mJibUr1+fXbt2ceLECTw9PQuck5OTEwBTp05l+/btJCUl0bRpUx48eEDjxo0B/eMK8t4zevRoXFxc6N27N25ubvKxC1Ncrbp27dpRsVwZhm+MZHfZ0tjYO/PdnzeZt/c2Hi6WSJJEs6qluB6TRsuWLVm4cCHDhg0r+EG5WXD4G7gaBJIERmaQkYD6xCK4ukv/1HG7Sk99ni8z0VJRTmSlnMhKOZGVciIr5UpUq+7hDeIdOnSQx64EBQXh4uLCunXrmDt3LikpKXh5eeHl5UVKSoo8diVvg/jMmTOZOHEiYWFhbNy4kaysLLlZd+/ePa5du0bLli0JDQ1l9+7dJCYmAjx2PIqbmxuWlpasWrWKxYsXc+LECYyMjDh16hT16tUD9He71Go1PXr0ICwsjLlz5+Lv709YWJh87OdJo9Hwx+ZtRCRB5c9P0GVWEPP23qaakylX7qXQ3L0Uu7f+zt9hFxk9ejQjRozg4sWLBT/o/Hq4shvMSkMpN7BwBOuyYFseEq7DwW/hBY2VEQRBEIRXTZEunPI2iHfr1o2goCCmTJlChw4d+Ouvv+jSpQsBAQHY2tri4+NDcHBwvlYdgL29PWq1GktLSypUqEBGRgazZs2SR64AlClTRh4anLdQys7WV/LzRrlERkbi4eHByZMn5XOTJEm++5X35+Gv9Lp06cLIkSNZv349165dw93dnQoVKpCZmcn7779flDEpVqduXc6eD2Ngnx7svpKGWgVmpib4f9KNwH3BmHi0RqVSMWvWLBwcHPD398//AbnZcGk7aIzA+JGRMWoDsHSG+xfh3tnnd1GCIAiC8Aor0q/qAgICaN26Nbt378bDwwN3d3d69+7NmDFjWLNmDbNmzaJu3bqsX7++0FZdUFAQBgYGlCtXjmbNmiFJEi4uLmzcuFG+hdavXz++/vprfvnlF77//ntMTU0xMjKiSZMm8p6iiIgIwsPDOXbsGA0bNiQiIoLU1FQGDx7MkCFDSEpKwsvLS27x9e3bF4Dvv/8eAwMD+vTpQ0ZGBqVLl8bDw0Ne2BWmuFp1eZycnZn5UwDrduynSZMmrFixQs4i7/NVKhW+vr6cOHEi/zGTI9GkRIOxVeF3lTQmkJuF7n44ksObz3yuLwvRUlFOZKWcyEo5kZVyIivlXpZWXZGPXAH9V269e/cG/hm7kpGRgSRJrF69mgULFjx27IokScTExBAYGCiPXfnggw/kVp2bmxv79u2Tx66kpaXRuHFjdu7cKZ+Hm5sb7u7uNGnSBIDo6GgApk+fzpIlS+T3de3aVf4Z6L/fnD17NrNnz+batWvUq1cv3/DgwnzzzTeFtur27NnzTK26R+Xk5JCVlUVQUFChPw8PDyc+Pp5Vq1ZhZ2cHgEl2Ag2TH6BVZ5CrSS/4S5KEeXYql8/9TdRt86c+N4PcNAx1GeRozMnVmD715xS1x2UlFCSyUk5kpZzISjmRlXLFlVV6eiH/nSxEkW8OL6xV161bt0LHrkD+Vt3DY1fyWnXr1q3L16rLG7vywQcfFNqqU6lUjx27olRkZCR+fn68//77DB785Kp/cbbqHtahQwc2btzIr7/+irn5P4ucO3fuMGHCBHnI8cCBA2natClTpkyh5du90Gw9AjEXwMah4IdmJkGuI7Xf7kftUhX/+0nFX0P99++obh4BbQ4YmiJVbInuze5g5fKUV/rsREtFOZGVciIr5URWyomslBOtupesVQfw9ddfs3nzZs6cOYOBgUG+u1OPU1ytukeNGDGCFStWMGjQIAICArC2tub27ds0bdqUhIQETExM+P3330lLS+Onn37inXfeYf369XSp1Q32XYb0OP2jB/7fHiQ7DTISoKofakf3/35CMRdh16fwIBJMbcHYEnLS4cJ6NFGnoO0PYFOuyK7/aYiWinIiK+VEVsqJrJQTWSknWnUvSasOIC4ujtu3b1O1alVMTU1Rq4s0nmdSvXp1Pv74Y3bu3ImLiwvvvvsunp6eREdHY2pqyp49e+jQoQM9evTgyJEjdOrUiQ8//JBM17eg4YeASt+iS7gB8dcgPR4qvAXNJ/z3k5EkOPojpETpH2VgXlq/+dzCAWwrQPx1OPnvi05BEARBeNWIVt3/RUZGsmPHDt58800+/PBDJEkiOjo63x6oF83T05PLly/z6aefkpKSQnR0NB06dODGjRs0a9ZMfp9Go2HmzJnEx8ezafNmqPcBvLcMGg0Fj3ZQqye0nQPvfA8m1v/9RGLC4H4YWDiB6pH/C6kNwMwObh2DB1HPeMWCIAiC8HIRrbr/t+qCgoK4du0a165dY9++fcA/Xx0+aSpNcbfq8uR9lr29PZMmTcLPz49GjRoxadIkLC0tCxzLzc0NZ2dnLl++rP+ZpSvU6Zf/Q3US6P77OaqS7qLJTkcydyy8rWdojio1Gm3iHSTT5/9kctFSUU5kpZzISjmRlXIiK+VEq+4la9X169ePfv36AbBixQrGjBlDUlLSv17z82jVpaelER6yn9z0JKLPH8Cphhf37scBsHXrVmJiYgr8TkZGBvHx8URGRhIYGFgk55HHLvUyb6ank5F9D0ld8P9CGm0mhrp0zhw/TYrpi7tjJ1oqyomslBNZKSeyUk5kpZxo1b2Erbr/ojhbdTqdjukTRvDTkl9JzfxnJVyn/K/4z5pCnTp1OHnyJNOnT5dHxuT56aefyM3NZfLkyfIdvSKT441mw1Es0uLAqpC2XtItsK9Ds3cHgFpTtMdWcnqipaKYyEo5kZVyIivlRFbKiVbdM7TqrK2tcXBwoFu3bty6dQtbW1tiYmKeuVXXoUMHQkNDuXfvHlqtlj59+vDdd9/h4vL4an1xtupGD+7LgoBVTGjlyIc+HqikXMLu5zBlQxhtPpjAzPEDGfH1EoYMGcKMGTNwdXUlPT2dX375hYkTJzJo0CAqVSqGOXSG1lCnNwTPhbQYfVtPbaB/JEFqDBiYQL2+qI1Niv7Y/+U0RUtFMZGVciIr5URWyomslBOtuv/YqktPT+fOnTssW7aM2bNnc/nyZX799Vfg2Vt1LVq0YP369XzzzTeYm5tz/fp13nvvvaKMSLEbN27wU8Aqvu9Yhm/6NaOciz3Ghhr86pTj4NQ2lLYwIHjvTn4NWMKmTZuoUKECbm5uODg4MGrUKD744AN++umn4jvBN96HxiPA0AySbuvbesl39RvDm38ClVsX37EFQRAE4QUp0jtOD7fqpk6dyqlTp8jNzc3Xqhs+fDg+Pj5yA27x4sUMHToUUNaqq1mzJjExMXTt2pVq1aqRmJjI3LlzKV++PHXq1AH0DblWrVqxcuVKeRP6v7XqQD+vLiEhQf6es2vXrowdO5bExMTHjl0prs3hK5ctwspEw5BWVdBJ/2xQlyQJc2MNw1pXZtKGi/j7O9Hu5k3++OMPrl+/jo2NDV26dMHNzU0+j2JTsytU8kF1+zhkPQAzOyRXz/8/0+nFbXQUmy2VE1kpJ7JSTmSlnMhKuZdlc7hKelJl7D9q3749Op2OLl264O/vT0hICDt27JBbdZ6enpw7dw4bG5tCW3Xr16+nT58+eHp6EhwcnK9V16hRIwBmzZrF3Llz0Wg0REVFoVKpKFu2LL///rv8NV1wcDDNmjVj7ty5jBkzhhs3blCpUiUGDx7Mtm3b5FZdcnIyTZo0Yf78+YD+a8O8u1cPO3DgAN7e3oVe87Rp0wrdHL527dpn2hz+y6I53Pj7JPvG1UanNirw8/2XE+i19ALbZg9HV9nnqY8jCIIgCIL+G62ePXuSnJz8xD3Kr1yr7saNGyQmJlK7dm3WrVuHVqtl7NixTJ48mf379wNPP6tuxYoVODo6smDBAtLT0/H09GTHjh3y7LfCFNfm8POnjrP/0FFMjIxIwoJVR25yI/I+ZW2M6d3Injvx6RgbqHirtR9m1X2f+jglkdhsqZzISjmRlXIiK+VEVsqV2M3hxd2q0+l0ZGVlsXLlSqpWrQroN6TXq1eP8PBw3N3dn6lV98knnzBw4EBu3brF9OnT6du3Lzt27CjQWstTXJvD+w0ZzrSZs+j402mO3EjH1AAqltKwMUnLl39GYmEE779phXX52iD+ZSuU2GypnMhKOZGVciIr5URWypWozeGQv1WnUqlQq9X4+/uzceNGkpOTGTduHJaWlvKTwy0tLQtt1b355puYmJhQo0aNfK06Z2dnDAwM2LZtG1WrVsXY2Jh27doByO951MOtOmdnZ0xNTWndujU3b96Uf3bz5k0GDhxIgwYNqFWrFkOHDqVBgwYEBgby119/FXVM/8rV1RXvpp4cvJZGXWcNQR9YEdjXjp86lMLRQk1qNpgbqmD/V5Cb/dzPTxAEQRBeR69cq65p06bk5uayaNEiuVX3ww8/AMjveZSSVt3ly5fR6XT8/PPPhIWFMXfuXFatWgWQb/P385Kdnc3fl6/RqJorEYk6Gi9NpuysGPquj8fdwZgP33Jh1dlUkq6HwO1jz/38BEEQBOF19Mq16sqUKQOAnZ0drq6uJCQkMH/+fHx8fOSv7p6mVWdra0u9evVwcHBAo9FgYWGBhYUFycnJ+Z719KjiatUdOnSI2NhYdo19Gw9TZw7fkbgfG0+9Ks5Uq+BEZGImPx/eya6wBN6vexSda9OnPlZJI1oqyomslBNZKSeyUk5kpdzL0qp75WbV7dy5k4oVK5KVlUW9evVQqVRUqlSJNWvWyOfxNLPqzMzM2LRpE1OnTiUtLQ1nZ2fs7OzkB3A+TnGNXMkbUGyQGUeWOovaZWygTFkA7sfGotbpF31xKZncCL/AxdSiHatSEogRBsqJrJQTWSknslJOZKVciRq58rxadZGRkdSuXZtDhw7JrbrBgwc/U6vujTfekH8f4Nq1a9SrV4/Zs2c/8ZqLq1VXpUoVZs6cyfm00qiyb+EfcpcTV2MxM1LTrpoZFW31o0xqlzGlYh1vKtR/56mPVdKIlopyIivlRFbKiayUE1kpV+JbdZMnT0aj0eDn51doq27s2LGAfuX4aKuuXbt2fPLJJ1y5cgULCwsSEhIKtOqaN28ut9+srKwIDQ3911bdrFmz+O233+SRK0ZGRlhaWso///rrr9m5cydnz54lOzub/v37M3jw4Cdeb3G16qpXr06rVq0Yv+I49+OTcLY2olVFQ9KzcvgiMBmtDiqXUtPUIR1VZgIaAwN4TPPvdSVaKsqJrJQTWSknslJOZKVciW3VtW/fHkmSCAwMzNeqK6zWn/daXqtu9erV8ubw/fv3Y2Vlla9Vp1ar2bp1q7w5fMuWLcC/t+qWLVsmbw43NzfnwIEDlC5dWn5fdnY2bdq0wcTEBI1Gk+/u1IvQq1cv7scnYWlqxPCGpnSvrsLLzRgXK/3dprh0iVRDe7i0DcL/fKHnKgiCIAivg2Jp1c2cORMTExO2bt2Kr68vI0aMkFt1tra2+Pj886RrHx8feZxJ3obx8ePH07NnTypVqkTZsmVJSUmRG3Ourq7odDp++uknOnTogJubGxYWFsDjW3UVKlRArVbj7e1Nx44defPNN1mwYAGZmZloNBr5fUOGDGHt2rW4u7tjamqKWl3k68r/ZMOGDdSsWZPO7f2YceAB7dakMuHPZBqWNWLXkHI8yJJYHW4Ekg4ubITHzOoTBEEQBKFoFEurztLSkho1atC+fXtUKhVjxoyhc+fOBAQEEBISQsuWLQvdHB4REYFarWb+/Pn5FjaVKlWSW3VxcXEYGxszdOhQed+UVqvF29tbbtX99ddfNG7cmEWLFvHRRx9x8+ZNdDodhw4dYtu2bbi5uTFlyhRMTEzQarWAvonn7e1N+fLladu2LVOnTpX3P+XdsSpMcbXqJEli3759fPXVV4xtXZYFDW4TnmRI5bL2WJoagtqAtw5nEPR3DB82rQHx19Am3gUr56c+ZkkhWirKiayUE1kpJ7JSTmSlXIlu1a1bt67A5nA3Nze+//57Zs6cybZt2x67OVytVpOamopWq0WtVmNsbIxWq5UfHXDz5k0kSSIxMZHMzExMTExQqVTk5uY+9rzyFkADBw7M16rz9vYmLi4O0O+1unbtGteuXWPfvn3AP18dPmmcX3G16vIWhFeuXOFc6Viq5mTgYmNBRnoqGf/f+C9pc0nP0JGQkIhGl8XJ/XvJNHr8eJjXjWipKCeyUk5kpZzISjmRlXIlrlUXHh5OzZo1C4xcOXbsGJIkMWfOnCeOXMnNzWX9+vXyyJXY2NgCI1eys7P5+++/5TtMZ86cyTdyxdPTs9DFzoQJE+SHbYJ+0ZanX79+9OvXD9DPrBszZgxJSUn/es3F1aoDaNy4MX///Te/pJbit21XSUgPp2IpAwZ4lqJH00ocv5HMjPdqUMpMDbbVaNmhB6iLfL//K0e0VJQTWSknslJOZKWcyEq5Etuqe3jkilarlR82aWxszIIFC+RFRnBwMKBfsOS9ltdw69OnD0lJSTg4ONCxY0fs7OwKjFz59ddfWb16NdHR0Tg6OgL6zeHu7u4Fzinvq7YxY8awd+9esrKy8PX1JSoqSv7KEGDUqFEcPXqUc+fOPfEu08OKq1UH0KFDByZMmEBYqIaPGpriZi1xMgpm7L7PrH2xGKpVDPAsjZpUqNkZtbHpMx2vpBEtFeVEVsqJrJQTWSknslKuRLXqnnXkiqenJ6CfKXflyhVWrFjB7t27iYuLKzByZefOnQQEBBAeHs5XX30FPHnkipmZGbt372bDhg0cOnSI27dvc+LEiQJPBR8wYACNGjUqylieik6nI2DZEhwsjUjN0rL/tobINANsTMDSWM2DLAmvcmpKS3FQrSPU6PyiT1kQBEEQSrwiXTg9PHIlKCiIKVOm0KFDh3wjV/JadXlDfh9u1TVo0ICOHTuyaNEiIiMjcXR0xNjYGI1GI28Oz83NRa1WY25ujp2dHfHx8SxatKjAyBUPDw/56dsPHjwgMzOT3NxcUlNTMTIywtraGkmS5H1MAB9//LH8fCeA0NBQQkNDSU1NLcqYFDlw4ADhV66xoX95Aj9ugpOtOctOZ7AlXEu32laMbmrN4VtakiyqgvdE0Iiv6ARBEAShuL1UI1cAVq5cydixY+XN4wYGBrRr106+hbZjxw6aNGnC/fv3qVevHmq1Gg8PD3nPFMCRI0cIDw/nxo0bNGzYkNOnT6PT6Rg2bFi+zeHOzs6cOXOG5s2bA/DFF1/w66+/yp9Tp04dQL+I8fb2LvSai6tVFxISgpW5MV4VzcHOhTZvOhMbG4u9vT0qlYrzt5OYf3QvYTfu0DBXCyrxKII8oqWinMhKOZGVciIr5URWypXIVt2zjlwBsLKyIj09naysLDIyMmjfvj3r1q2Tj3Hjxg1CQkJo3bo1q1atIi4ujmHDhvH555+zfPlyACpWrIi7uzvNmjUD9K06IyMjZs2axaxZs+TPatiwody4A/2m8BUrVjBt2jS2bNlCaGjov15zcbXqrl27RlZ2LvHJqWi194lLzeZuYhal4lJwK2XE7Sj97v+M9AwCAwPFU8MLIVoqyomslBNZKSeyUk5kpVyJatXBPyNXHm3VPTpypbBWXZ65c+fK+5zyWmuLFi0C9Ht/VCoVa9aswdraGoA5c+bw3nvvsWjRIkxNTWnYsGGhI1eKQ3G16ipXrkxAQAC/nMnkxN0rbDsbg/b/g30bljXExlRDWWsNzdp0QO3T9pmvoyQRLRXlRFbKiayUE1kpJ7JSTrTqCmnVxcfH06tXL86fP098fDwODg40aNAAf39/pkyZgrOzM87OzpQpUwZra2uOHj1K8+bNqVy5MpIkcffuXapUqVLgnJycnMjOzub9999n9+7dqNVqunTpQnR0tNy4O3jwIHPnzuXkyZPExcVhYGDAmjVr6NWr1xOvt7hadTVq1MCndWsmbd2Lo6WGue9Y0qiMmogHGj7bncTJuzn0rWWMcXwYZCWBhf1TH6ukEi0V5URWyomslBNZKSeyUk606h5q1anVajp27Mi2bdvkVt2pU6cA5H1ETZs2JSoqirt379K3b19atWpFVlYWarWasmXLFnpe9erVQ6VSERISQlBQEDt27GDv3r3cuXNHbtUdO3aMN998k40bN/LRRx9RqlQp+vbty44dO4oyov/E6P+LsugULUtOpjHjQDrjdiRyPUFLFTsDdlzNJfN+BISufWHnKAiCIAivk5eqVXf8+HFMTEwwMTFBkiQyMzPJzs7GyMiIChUqANCzZ0/s7Oxo3LgxPj4+uLi4EBUVxYABAzA11T/H6OTJk3h4eBAZGQlAVFQUkiSRlZVFeno6pqammJubA8gb0ydPnswHH3yAmZkZ2dnZWFhY0KRJE5YuXUp2dnZRxqRITEwMf/75J7MnfsiuYVWp42ZHrtqQznXsOPdZXXZM8CYhXcuWS9lwdTdkPf/mnyAIgiC8bl6qVp2pqSlLly5l7NixZGVl4ezsjJGRER07dpSPYWFhwUcffcR3333HypUrMTQ0xNramh9//FF+z6ZNmwgPD5d3yB8/fhxra2s6d+5Mly5dyMrKok2bNoSHh3PixAk6deoEwKBBgzh06JD8OVeuXAH0C6+8hdujiqtVd/36dXQ6HZ4ejtSxs6K15xv5WnUA9pbGXEvIRZeVgjblPqgLfmX4OhItFeVEVsqJrJQTWSknslJOtOoKadW1aNGCY8eO0aNHD7Zu3UpERATt27dn5cqV8jGuXr3K/PnzCQkJoWrVqnIDLu9uE0CjRo1wd3eXFzt5TxdfuHAhCxculN/n4OCQr1V38OBB+a/Xr19Pnz59OHPmzGMXTVB8rbqoqCgADvx1DkfrJHYeTyQ1M4uKpaNoXMWe5GwVSenZGOkySXqQxolDx8g2sHzq45VEoqWinMhKOZGVciIr5URWyolW3X9o1Wm1Wnr27Mn06dPlh10WplOnTvJdpKdx4MAB+vfvz9KlS6lRo8YT31tcrTpJkliyZAkLNx1lanQk6TmgVoFOgkqlbuLtbo0E9KlvjXXN1rT26fbUxyppREtFOZGVciIr5URWyomslBOtuqdo1ZmamnLq1ClOnTrFRx99lP9CDAzYs2cPLVu2LHBOTk5O3L59myZNmhAaGoqRkRFxcXEkJCTIrTrQP3Tyww8/5OzZs5iamrJmzRpq1apFrVq1Hnu9xTmrrmIFVzaFhlLdwZClHc2pV8aIQ7dVfLQljoDj8XR70wxnJyeo0xuN+BeuANFSUU5kpZzISjmRlXIiK+VEq+4/tOqsrKxYv3493333HZs3b2bXrl20atUKlUrFZ5999tgZc40bNyYzMxNPT095wbV//350Op38O6mpqbRq1Yq///6bKVOmEBISgqWlJb6+vi/ku+d79+6xbUcg79W2ISoVvJYlUWF2HO1/jeF2kpbSZiri0nKhTm9wfvO5n58gCIIgvI6K9I7Tw626qVOncurUKXJzc/O16oYPH46Pjw81a9YEYPHixQwdOhRQ1qp7//338x3z+PHjnDp1ihs3bshNuc2bNzNp0iT5IZjVqlXDz8+PgwcP0q5dO3JzcxkxYgTdu3fHxcUFgNWrV5OSksLw4cMZNmwYAMOHD2fjxo3cunWLypUrF3rNxbU5fO3atRioYEnPihiWKsemkEguRERTxsaI9+qUYk94KgNWXCLy1nUc3hSbCh8mNlsqJ7JSTmSlnMhKOZGVciVyc/jzaNU96t69e6Slpcnz5gB27txJeHh4vvetWbOGESNG8P3335OZmYmXl1e+Jt6RI0cACmwgNzMzeyGbw48fP469hQHocklNTqBNVVPaVHWTf25vqf8HfPZ0CFpN4FMfpyQTmy2VE1kpJ7JSTmSlnMhKuRe9OVwlSZJU1Adv2rQpXbt2ZfTo0eTm5uLs7MyGDRvw9vaWW3V5m67DwsLyzaoD5FZd3qy69evXY2Jiku8YZcuWJTY2ltzcXKZNm8aUKVPknz16x+lhK1asYMyYMSQlJRX42YULF3j33XeJiIgAoEqVKuzevZvy5cs/9loLu+Pk6upKXFzcM20OX7JkCWNGj+L2l2/iWK4ymdm5rNh/mdAo/bGycrSsOXabyK1fU+qtwahuHkaVGo1kYIpUzhNKVX5t59eJzZbKiayUE1kpJ7JSTmSl3PPYHF66dGmSk5Of+N/vV6pV97AjR46QmprKX3/9xcSJE6lcuTI9evQAnq5Vl5GRwcCBA2natCnr1q1Dq9Uye/Zs2rZtS0hISL7HHTysuDaH9+zZk08+Hse3e6Lo19KK9vNCiEzM4E1Xa7SSRNjdB5gYqLgbn4bjxg8gLVb/i5IEZ3+Fyj7w1ngwLPy8Xwdis6VyIivlRFbKiayUE1kpV6I2h0P+Vp1KpUKtVuPv78/GjRtJTk5m3LhxWFpayk8Ot7S0zNeq8/Pzo27dutSqVYvhw4fj7u6Ov78/9+7dA/RtvKZNm1K/fn0aNmzIDz/8QKNGjZg2bdoTzyshIYFevXrx0UcfkZyczMCBA0lN/edp23PmzOHs2bP8+eefNGvWjJ49e1KlShUiIiLYunVrUcf0r2xtbZn51Vf8eOg+jb88gqUxbPywGhPergjaXKxM1FQpUwrf4bOIjrkPNuWgVEX9HwNjuLgFjs5/7uctCIIgCCXZK9WqAzA3N2fEiBEcPnyYS5cu8fnnn7N3717i4+OfeG69evUiLCyMjz/+GAsLCw4fPsyQIUPkn2dnZ2NmZsaePXsIDw9n3rx5BAQEkJOTg06nK8qYFBsz/hM6dWhPtlbicnQGXX6+RO8lZ3GwMefoyq/Z/1UnMnJ0LDmVCer/3zxUqcDUFkxt4MoeSL77Qs5dEARBEEqiV65Vd+zYMcqVK4eRkRE5OTlkZWUhSRLOzs7yeTy6x+nSpUvs2rWL1atXc/36dQDGjBnDiBEjmD59OlWqVKFHjx589913LFmyhJEjR1KpUiXs7OxISEigRYsWj73m4mrV5bl1N5L3u3blw/69CTmwg3f82uDh2QayUtCs70WXeo5sPhXJ5+9Wy/+LxtaQdAvdzeNI1d995vN4lYiWinIiK+VEVsqJrJQTWSknWnVP2arT6XRMmjSJiIgIDAwMcHFxwdTUlJEjR8rvebRVd/z4cQwNDfNtQB8xYgQAv/32G1OmTMHDw4Pt27czffp0GjduDOhD7NOnT75F2aOKq1WX5/79+7i4uJCSpcOjyTvceAA39uzHNDuOBokJWBhKpKRncf/+/QK/a5aVxtUzIdy9afTM5/EqEi0V5URWyomslBNZKSeyUk606p5Dq27mzJn8+uuvBR5R4ODgwPTp0/M9hbxJkyacOXOGrKwshgwZgr+/P2r147/RLK5WXZ4ePXpw8eJFQkJC+OmnnwgNDeXixYuYmZrQwTWF1Udv4VG2FH+M1i/2kLSQHo8q9T7kpKGr1hFdvYHgUP21admJlopyIivlRFbKiayUE1kpV+JbdZMnT0aj0eDn51doq27s2LGAfuWY16rLG7ly9uxZcnNzsbOzIzg4mBEjRrBs2TJAvzn8008/lTd229vb8+233/5rq06r1dKrVy+2b9+OWq2mS5cuPLxmzMzMZOjQocTHx5OTk0O9evXYuXMns2fPZsKECY+93uIcuQIwbNgwWrVqRceOHdm3bx+VK1emTZs2xMfHM3XjH+TmahnVppR+cZeTAbGXITMFpBzQGKO5dRRN9Hmo0wcaDHxtFk8gWir/hchKOZGVciIr5URWypXYVl379u2RJInAwMB8rTpVIf/hznstb3P4zp07uXr1Kr///jsWFhYEBATIrbq8zeFHjx4lPDyc2bNnk5OTIy/ECuPk5MStW7cICwsjKCiIHTt2cOjQIeLj4+VZdVqtFlNTUz7++GN8fHwoW7Ys3377LdOmTUOr1RZ1TIq1aNGCNm3asG/fPsqVK8dnn31G06ZNyczMJDdXi721KTO2XiIr9hbEhEFGIiCBkQU4vQF2lUGtgdO/wLV9L+w6BEEQBKEkKJZW3cyZMzExMWHr1q34+voyYsQIuVVna2uLj4+P/Ds+Pj7Y2toC+gr+Rx99RP369SlfvjytWrXi3XffBf5p1dWpU4cePXpQo0YNKlSoQO/evalcuXK+Rws8ysHBgdzcXMaPH0+jRo3w8vKif//+SJIkP9zS3Nwcf39/Bg8eLC+mdDrdC23VgX5RGR8fT82aNVGr1fTv359evXoRERFBQEAAhw8fISo5lz/C0iE7DQxMwLoMONYEE2v9HSZze9DmQtgm/XOeBEEQBEF4KsXSqrO0tKRGjRq0b98elUrFmDFj6Ny5MwEBAYSEhNCyZctCN4cHBgYSExNDgwYN5EcGBAQEYG9vL7fqFi5cSLly5fDw8AD0M+YuX77M22+/LZ/HyJEjWbBggfxV3P379zEwMGDu3Lm4u7uTk5PDr7/+ikql4tatW9StW5c1a9ZgaGjIG2+8QUpKCpGRkUyaNIlu3bo98fZdcbfqUlNTOX36ND///DMODg40bNgQAwMDbGxs5Dt1tWvXZl+0BT1raJBKVQTV/9fDDy/4jK3h/mW0KbH6xxWUYKKlopzISjmRlXIiK+VEVsqV6FbdunXr5M3efn5+JCcn4+bmxvfff8/MmTPZtm0bbdu2BaBr167y5vC8Vt2HH34oX0DlypXlOXLwT6vu4sWL8sKoXbt2T3xIZXR0NOXLl8fDw4NWrVrJe5wSExOJjo7WB2FgwHfffceVK1fIzMzE1NSUSZMmPfErQCj+Vl1GRgYAFy9exNHRkZCQEEB/d0+lUqHRaEhJSSEhMZvUdC1p2rhCP8cwNw0VWk7s+ZNsA+vXYq+TaKkoJ7JSTmSlnMhKOZGVciWuVRceHk7NmjWJjIzEwcEB0Ff/k5OTWbVqFXPmzGHw4MHyyJUuXbqwdOlS+enhoF/oJCUlySNXmjdvXmDkSkRERL6RKwsWLJA3hz/qv7TqAPr160dSUhJbtmz51+st7lYdQP369SlbtiyDBg0iOjqan3/+mXPnzqFWq2nSpAnBwcEsmzWZAWb7kMzswPCRBVtuFqr7F0GlRrIpB5ZO6Kq+jeTeFozMi+QcXyaipaKcyEo5kZVyIivlRFbKldhW3cMjV7RaLSqVCpVKhbGxMQsWLJAXSMHBwYB+kfLwyJVevXpx/vx54uPjcXBwoEGDBvj7+zNlyhScnZ3ZtGkT/v7+hIaGkpWVRY0aNWjXrh3Tpk177MLJycmJmJiYfK26Tp06kZCQIO9nymvVnT59mrCwMBwdHRVdb3G36kD/sM4BAwZw7do1rly5QseOHRk1ahRxcXHMmDEDgAdqW1SONVDdCwWbCqD5/z/a7DSIPq9v3Fk66280JVxHfWwe3DkGvt+ASdEs8F42oqWinMhKOZGVciIr5URWypWoVt3zGLly+PBhfHx8CAwM5PTp07Ro0YLVq1eTkpLy2PNq3LgxycnJhISEyK26PXv2oNVqadSoEfBPq27UqFFPfODli9CvXz9atmzJlStX5K8cjx8/ztdff42BgQFdu3bl4wmfcq1CbyjtDsm3IfGmftxKVKh+0WRTHuw9wMxOP9fO0gVu/wVnV73oyxMEQRCEV0aRLpweHrkSFBTElClT6NChQ76RK3mturwhvw+36pSMXKlSpQrVqlXDxsYGgEqVKsmv59m8ebO8eTzfxarV8h2wRx+LYG5uzsiRI2nQoAFqtZrc3FxCQ0MJDQ0tyoieikqlIiMjAzc3N9544w3Wr1/PsWPHGDlyJH///TcrVqzA2tqaJev/hHcXQvNPoWwDMHcAQxOwr6Yf/vvwNRua6B9ZEP4nZD1+0SkIgiAIwj9e+ZErlSpVwtrami5dusjvKWzkipWVFXXr1pU3h3fq1IlVq1Zx4sQJ+WGZ77zzDrdu3ZJ/r06dOgA8aRtYcbfq8pw/f56uXbuyYMGCQm8nent7c/bsWXIMLMCjI3h0RHV5B+qDX+kXUJJU8FEERpaQkYg24Q6UrlLgM19VoqWinMhKOZGVciIr5URWyr0srbpXduRKnlmzZvHtt99y+fJleTP6s4xcgf+2OXzatGmFturWrl1bJK060C/cevXqRdP6bzCgeyfMnCsjqfKveadMmYKJiQmfffaZ/Jpj8llqRP5GmpH9P48oeIiBNgMDXRYhbiNIN3YoknMVBEEQhFdReno6PXv2fHEjVzZv3qw/gIFBoSNX8lp18+bNk0eu5Jk7dy5Tp06VW3Xjxo0r0KoD/eJk+vTpbN26VV40QeEjV4pL3vnlyWvVtWnTpkhadX/8vpYZUyaSnp5O0OET7D18grZ1Xfh+2qdU8v0QVGquX7/OhQsXWLRoEe+8884/v5xSF80fRzBHB2alC3540i1wqI33u30LXVi9qkRLRTmRlXIiK+VEVsqJrJR7Hq06JV65Vt29e/cYP348Bw4cIDo6mg4dOtC6desnnpOTkxN3797F29ubM2fOkJKSQmxsbL5WHUCFChXyfVWnUqn45ptvmDhx4mM/uzhbdUsX+zPko2G0q2HNiO4VGbMhgpplLPn7Zhxv9RzP8YB4smt2o2u3bpQtW5Y+ffrkP2YpV6jWFkLXgsbonyeJSzpIvQ8aQ6jVA7VRwfMvCURLRTmRlXIiK+VEVsqJrJR70a26Il04PdyqCw4OxszMjE2bNrFjxw6GDBnCunXryMjIYNCgQXh5eQGQkpLCsmXLGDt2rNyq++qrr7C3t+fatWv0798f+KdVl5WVRUJCAvHx8bi5ueHm5vav59W4cWPS09N544038PPzY9KkSRw+fBidTie36vJ8+eWXXLhwgeTkZFasWIGlpWVRRqTYgwcPGDd+PIOa2LNkUAMkQzPMTU0ZtuYyuToJFdCw/0wS0r+kfPny7N69G3PzQp7J5DlM/0iCq0GQHgf8f4O4qQ00+hCq+j7HqxIEQRCEV9sr16o7duwY+/btY968eTg5OZGWlkZ0dDTJycnyeTzaqqtWrRp+fn4cPXoUa2trACZMmED37t1xcXGR35ednc2DBw/IyMggKyuL6Ohorl69WpQRKfb777+TkZnJtLddUBlbAOBb045b89vyTbc3qF7GisT0XH6e0J3w8HCqVatW+AcZmkDLz6HTYmg0FGr3BK+x0HWl/q9fgyeIC4IgCEJReeVadUuWLCE3N5fhw4cD+sXWsmXL+OCDD1ixYgUAJ06cIDw8nJs3b8oLrjVr1jBixAjGjx8PgKenJ4sXL853/vfv32f27Nny37/IVt3169cpY2uCc2krdDqdfA625oaM8atCo0ql8PryAA3Lm6FWq//9WKWq6P88rIS2OERLRTmRlXIiK+VEVsqJrJQTrboiaNV5e3tTu3Zt5s2bl+/1kydP0rdvX/bt20eZMmXy/ezgwYO0aNGCxMRE+VlQeebMmUPdunUpVaoUx44dY9KkSfTv3585c+Y89lqLq1W3ZcsWfluzkqufVSHD0I49F+JISkmjjLUBPtVLsSUsnRFrwznwzfskV+v11McRBEEQBEF5q+6VnVUHj184PcmTFk6P+uWXX/jwww9JTU0tdAM4FN+surt371KlSmV83S04fD2VtGwdZoaQlg12piqsTTW42hqzd8+fSK6eT32ckki0VJQTWSknslJOZKWcyEo5MavuGVt1p06d4urVq/n2Nj3JkiVLWLt2LSdPngQgOTk538Lp5s2bzJgxg/379xMdHY2Liwtt2rQhNzeXmzdv4u7uXujnFlerzs3NDc+G9Qk8fpImrgYs7mhDVXsTdl/P5aMtcdxIyOWD+lYYGJmA+JetUKKlopzISjmRlXIiK+VEVsq96FbdKzerLisrC3t7ez7//PPCW2SPkZ6ejp+fX76vBB92+fJldDodP//8M2FhYcydO5e1a9eiUqnyPSPqeUlNTeX8hUvUKWdBSFQudRYl4DjzHh1X3keSoEE5U9aGpiGdXVvwieCCIAiCIBSLIr3j9HCrburUqZw6dYrc3Nx8rbrhw4fj4+NDzZo1AVi8eDFDhw4FlLXqKlSoID+iIG+GW2hoKEZGRlSvXh0ofI9T9+7diY6OZs2aNYB+b1ViYiLlypWjVKlSWFtbU6tWLRwdHQH9YxK0Wi3m5uZy668wxbU5fOvWraSkpLD54zcwtnFhy6k7xMQlULOcLe3quREckUrrbw5z6vhhaje5A1Yv12DiF0lstlROZKWcyEo5kZVyIivlSuTm8Pbt26PT6ejSpQv+/v6EhISwY8cOuVXn6enJuXPnsLGxKbRVd+DAAT777DMuXrwot+pyc3Px9PRk/fr1/5x0IRX68uXLc/PmTUD/NPKxY8dy5MgR+XlRj9vEvXz5cvr168eZM2cYNmwYly9fJisrCzc3NxwdHUlOTubMmTOPvebi2hweGBjILwHLSJhRlbRCxqHcTcykwVcn+aNfeWz8JpBqUqaQTxEEQRAEQYkXtjkcXt1W3cOuXbtGvXr1mD17NoMHD37s+4prc3hgYCDvvvsupyfUICbLmM2n7pKUmskbZS3p36Iqx29n0PXHvwib3ogqo7eAmd1TH6ukEZstlRNZKSeyUk5kpZzISrkSuzn8ec6qe5yGDRvKA36fRmRkJH5+frz//vtPXDRB8W0Ob9u2Lc7OTrT+KZzEjFzcS2twtFATeCmF6YGRuFgb0sTNnOpN3gFrp3//wNeQ2GypnMhKOZGVciIr5URWypWozeGQv1WnUqlQq9X4+/uzceNGkpOTGTduHJaWlvKTwy0tLfO16vz8/Khbty61atVi+PDhuLu74+/vz7179wC4d+8ePXv2pGrVqhw6dIhDhw4pOq/MzEyGDx9Ohw4dAOjTpw8xMTEF3hcVFcVbb71FVFQUAQEBJCUlFU0w/5FGo8Ha1IjEjFzqOBvwvZ8lizra8GP7UtiaqriTlEPnN62h3gcv5PwEQRAE4XX02rTqxo4dy/bt25k2bRqgf1ZU586d870nMjISb29vsrKyaN68eREk8vSOHjnC5Ru3+fKdMugMTOmwOoma82MZuDGeGo6G1C1jzOYLqWBQMgf0CoIgCMLL6LVo1SUnJ7Ns2TJmzpwpf285evRo+vTpw+7du/H19ZUXTRqNBldXVwYOHMiuXbuIiYl54l6o4mrVbV6/irK2Rkx6twaTu1ty4U4SN25HUr1caaq42LL6r3t88PMpos/txa5Rt6c+TkkkWirKiayUE1kpJ7JSTmSlnGjVPcdW3f79+2nVqlWh59y9e3fWrVvHihUr5AXZo54UUXG16pb7z+NK6HEOfVwbrbrgXaV9F+PpHRDGth9GoKvU+qmPIwiCIAiC8lZdkd5x2r59O6Bv1eW15Pz8/EhOTiYjIwNJkuRWXdu2bQHo2rWr3Kpr0aIFx44dk1t1ERERtG/fnpUrV+Y7Tt5C5nGtuiZNmuDu7o6bmxug/1rOyMgo350h0G8iz1u09ejRg7lz5/LJJ5/Qu3fvfO27J8nbvJ4nr1XXpk2bZ2rVRd+9yfY9B4l+kMPea6msO3aThNQs3EoZMcjLieMRmThYGtKqY08My9V/6uOURKKlopzISjmRlXIiK+VEVso9j1adEsXWqps8eTIajQY/P79CW3Vjx44FICgoSG7V5Y1cOXv2LLm5udjZ2REcHMyIESNYtmwZgKKRK49r1Q0fPpzffvuNrKwsfH19892WGzRoEElJSUyaNInBgwdjb2+v6HqLq1XX64OBfDJhIo2/PUuWVuLdasY0K2tESGQu3ZffQKOCj30rYObWCNRFvse/RBAtFeVEVsqJrJQTWSknslKuxLbq2rdvjyRJBAYG5mvVFfY1W95reZvDd+7cydWrV/n999+xsLAgICBAbtU9zeZwJycnsrOz2bp1Kxs2bODQoUNERUVx8eJFnJz0Vf5Dhw5x584doqKiyMnJ4e7duwDY2dkxderUoojmPzE3N8fZxYW0HIny1moalTPmDSdDKtsZYKgGnQQ52RkQff65n5sgCIIgvK6KpVU3c+ZMTExM2Lp1K76+vowYMUJu1dna2uLj4yP/jo+PjzzSxNbWlo8++oj69etTvnx5WrVqxbvvvgv806qrUKEC8+fPp2/fvhgYKLthVrlyZUC/n6lly5bUq1ePL774guzsbCwtLQH9/qrz589z7tw5QkNDCQgIAKB27doMHz68SPL5L06ePMmVazeY06kMdSrYMGn3A/pvTGbf9SymvVOGUT4VWP5XHBnntjz3cxMEQRCE11WxtOosLS2pUaMG7du3R6VSMWbMGDp37kxAQAAhISG0bNmy0M3hgYGBxMTE0KBBAywsLDh8+DABAQHY29vLrTqA0NBQALRabaGtOn9/f4YNG8bx48fx9PTk2rVrAPz++++0bdsWKysrZsyYgZGRESkpKQBUqlQp37XExcUBUKZMmScO+S2uVt2BAwewMDVixFv2jO5cmZycXCLvxVCujBNqjYaT1xOYH3ST83/tp27rz576OCWRaKkoJ7JSTmSlnMhKOZGVci9Lq65IF04BAQG0bt2adevWFdgc7ubmxvfff8/MmTPZtm1boZvDTU1NWbp0KR9++KF8AZUrV+bIkSP5jlOnTh35r8PDw6lTp06+Vt2joqOjMTQ0pEOHDnTp0kXe41S9enWio6ML/Z0LFy4A0K9fvyde8zfffFNoq27Pnj3P1KoLDw9Hp9ORlpZGpu4+AGYmhsTFxwOQkKBfoCUmJskjaZTegVNMktDostGpNUiqIt8OV+yCgoJe9Cm8MkRWyomslBNZKSeyUq64skpPT1f0viKfVRceHk7NmjWJjIyU79SMGDGC5ORkVq1axZw5cxg8eLA8cqVLly4sXbo0XzMtOjqapKQkeeRK8+bNCx258rhW3aPWrl1L//79C23VtWjRgu+++y7f6xcuXKBFixaMHj2azz///ImfXVyz6k6dOkWTJk3YOrgS7bzeQFJpiI2Nxd7eHpVKxdCAU6wMvoWRoSEpGdmYmJjQrVs3Pv30U/mryaeWm4UqfCfqyzsgJQrUBkgVmqGr3glKV322z34OREtFOZGVciIr5URWyomslCuxs+oeHrmi1WpRqVSoVCqMjY1ZsGCBvEAKDg4G9Hd0Hh650qtXL86fP098fDwODg40aNAAf39/pkyZgrOzs6JW3aPyNocPGjSIzZs3y3ecoqKi5M3hAKNGjWLv3r1cunQJBweHf100QfG16ho3bkwTz0aM3HSeao4mVKqiX7CoVCqWH4pg6cGbmBqqGDGoD3Wa+RIeHs7PP//Mtm3b2L9/P7Vr1366A+dkwsEv4fpBfVvP2Aq02XBxM5pbwdB6OpRr9NTX9TyJlopyIivlRFbKiayUE1kp96JbdUW6cHp45EpwcDBmZmZs2rSJHTt2MGTIENatW0dGRgaDBg3Cy8sLgJSUFJYtW8bYsWPlVt1XX32Fvb09165dkx9KWdjIlWHDhik6r3r16qFWq9myZQsbNmzA2tqagQMHEhkZSePGjeX3xcfHc/fuXapXr/5S/B/4t/UbaOXdjGozL9K2xl3KWqk5E5nDXzdTMTVUE7bDH7c2Q+T3jxgxgpYtW9KvXz/Onj1baIPxX13cql80WTiA0UOtRXN7SLwFh76DbqvB6Om/hhQEQRCEV1WRtuoeHrkSFBTElClT6NChQ76RK3mturwhvw+36v7LyJU333wz38iVixcvyudx8uRJPDw8iIyMzHd+eXe/8v76YRcuXCAoKIiOHTvy9ttvk5OTQ3R0NLGxsUUZ0X/i6urK6dC/mf/9N8SqHNh9LQcTC/3tw/nffZlv0QRgY2PDN998w7lz5zhx4sR/P6BOq184qTX5F00AKhVYu0DyXbgZ/LSXJAiCIAivtGLZHL579248PDxwd3end+/e8siVWbNmUbduXdavX19oqy5vc/jYsWPlkStGRkZ07Ngx33H+bXP4sWPHCA8PJyIigjJlynD69Gl0Oh0dO3bMtzk8NjZWbt798ccfxMbGsnr1avmznZ2dn7jpHIqvVZfHxMSEISPH0X/oSIKCgtBqtRzs0oVWHXsU+vne3t6oVCrOnj1LvXr1/tvBMhLRpNwDI0vQ6Qr+XGWASpLQJUSge4kbIKKlopzISjmRlXIiK+VEVsq9LK26It8cDvqRK127dmX06NHk5ubi7OzMhg0b8Pb2lkeu1KhRA4CwsDC5VZcnb+RKRkYG7du3l1tjj3rc5vBHh/z+183h06ZNY8uWLfJjD56kuGbVPerevXvEREeTcPcKPwasY8GsLylb9c0C73vw4AF9+/ZlzJgxeHt7/6djaLRZNLn+HUgS2QaWBd8gSZhnx3DNsS237Zo/5ZUIgiAIwsvnhcyqg39GrmzevFl/AAODQkeu5LXq5s2bJ49cyTN37lymTp0qt+rGjRtXaKvucR43cqU4FNesujznz59n/PjxHDp0SH5No4Kty+fy59wR6OoPAKsy8s9mzZqFsbExEyZMoHTp0v/5eOq9oaiv7kaytdd/PfewzAeQ60BNvwHUtHd/6msqbqKlopzISjmRlXIiK+VEVsqV2Fl1xd2qAzh48CDjxo0jNDSU0NBQateu/cTnLeW16t5//312796NWq2mS5cuREdH52vV5UlISODvv//GxsaGpKSkJ15vcbXqQL/vqmXLlpRzLMWq/h7UKp3NfakUI9deJuhSIj0m/sTK0Rcx6fwjuWYOrFq1ii+//JIhQ4bIWf1ntd6Hu3+hSokEKxdQG4AkQVYKZMRBVV/UzjUKLqpeQqKlopzISjmRlXIiK+VEVsqJVt1/bNVFRETQtm1bhg4dioGBAebm5gwaNAhnZ2d8fX0LPa969eqhUqkICQkhKCiInJwcevXqxZ07d/K16kC/ov3jjz8Uz8ErThMmTKCMizPHxlTCPDee+5lG1HB05EKtCrw5aQ8bQpPYN3wL1X44zfW4TKKjo+nVqxc//PDD0x/UpQ60+AyC50LSbf1rkgSGplC5NTSf+EosmgRBEAShOLxyrbrFixfj5OREnz590Ol0uLi40KpVK2bMmCGfx6OtuqioKCRJIisri/T0dExNTeWFUd7GdIBr164xePBgLCwsMDc3R6vVEhoaSnZ2dlHGpEhUVBS7du3i477tsMyNBQsnecGiVqvZ8XEzAJpWtqGiZTa9ur/P2bNnWb16NUZGRs928MqtoPsa/QKqXj/wHArvLgK/b8Hk2b9+FARBEIRX1SvXqjt+/Dg3btyQm3WnT58G8j9eYNOmTYSHh8s75I8fP461tTWdO3eWW3Vt2rQhPDycEydO0KlTJwDee+89zp07l++a6tSpQ0RERL5ZeQ8rrlbdzZs3kSSJWm6l0MVJSGr9PypJktDpdJSzM8Xe0pgGFUvxma8j2i6jwaZc0bUNNGZQtW3+13Jzi+azi5loqSgnslJOZKWcyEo5kZVyL0urrkgXTtu3bwf0rbpHZ9VlZGQgSZLcqitsVl2LFi04duyY3KqLiIigffv2rFy5Uj5GdHQ0M2fOZNKkSfJrgYGBtG3bloyMDExNTWnUqBHu7u7yYic6OhpHR0cWLlzIwoUL5d9zcHCQZ9XFx8eTkJDAoUOHeOutt1ixYgVjxoz51z1OxTWrLu+89gSfoWqZFNKzouH/Y1fO300hKCye+NQs7ickk5hszonDf5FjcOGJn2mSnYBNegQqSUu6sQPJpuVL9NduYvaTciIr5URWyomslBNZKfeiZ9WVyFZdp06d5LtISg0ePJiePXvy1ltv/affK85W3YoVK9h+6jbj33TFXJvBhZhsRv5+jcOX4zDUqNBJsODwfY5Gqlm9rQ5VqlQp/IOy01D/tRDV9b2osh4goYIMYySjGuiafQy2bs90ni8b0VJRTmSlnMhKOZGVciIr5USr7ilbdU5OTpw+fZq6desSFhaGq6srzZs3x8rKClNT00LPycnJiZiYGHr16sX27dtRq9V06tSJhIQEuVW3Z88etmzZUuCZTgYGBixZsoQBAwYU+tnF2aqbOXMmbdq0oZNBDSY3ymHQmuskZsC79VzYcjqKz9s48dYbrozcGoevry9nz54t+AgCSYIDsyF8F5jaQKmKqFBBdhpEnUYT9Bl0WACWjs90ri8j0VJRTmSlnMhKOZGVciIr5V50q65IN4c/3Krr0KEDvXr1wsTEhKCgIFxcXFi3bh1z584lJSUFLy8vvLy8SElJYe7cufqT+X+rbtu2bVy5coUVK1Zw6tQp4J9WXbVq1di0aRMtWrQgNDSUMWPGsHz58sffbUE/MDc5OVlu1e3YsYM9e/ag1Wpp1Eg/sHbQoEEMHjyYVatWERgYyDvvvAPA/Pnz//Pdq6LSokULNm/ezPlb8XjNucjlmCxiHmQR9Hc009u58uWgt/EZv4x9B48QHx/Pzz//XPBD7oXqZ8+Z24OZHajU+q/njC3AtgIk3IDL25/zlQmCIAjCq6lI7zg93KqbOnUqp06dIjc3N1+rbvjw4fj4+FCzZk1A35IbOnQooKxVl0ej0aBSqVCrC679Nm/ezKRJkwo8BFOtVst3wB6dVffo08djYmLYs2cPp0+fZvjw4Y+95uIeueLr68uVK1fw9PQkPj6WGaP60qF5HaycK5Hr9Aao1Dig39i+du1aJkyYkO/31TeOoM5JR7JwKmSMiho0xhC+C23tD575XF8WYrOlciIr5URWyomslBNZKVciN4c/j1bdpUuX6Ny5M0FBQcyfP5+yZcvSv39//vjjD/k9O3fuJDw8XP7748ePY2VlRd26dWnVqpX8Vd2qVavyteoeJUkSpUqVeuI1F9fm8EelpaVRvXpNSrk3JjgaiI4E/hlinJOTw7179wgMDMz3e1XvnaVsWhppuYUPKzbKzUBKu0Xwzp0lbqO42GypnMhKOZGVciIr5URWypWozeHPq1X39ttv51soBQYG8ssvv8iturZt28p7qPJ+x8nJibVr1+Y738DAQLm99igzMzM0Go38AM7HKe6RK3lWrlxJSEgI165d4/jx40iSxFtvvUWvXr2wtrbG39+fatWq6b9ilHSookJR3T2BKi0TVYoOc1srMCw474+kTHCswTtt2xb82StKbLZUTmSlnMhKOZGVciIr5Urs5vBXtVX3sAMHDtC/f3+WLl0qDyN+nOLcHP4wT09PNm3axCeffELz5voBu+PHj2f69OlMmzaN3bt3s3z5cgy16bBvBtw+DrmZoM2BzGRUUaehdBWwfGjETE46qCSo3h51CfwXVmy2VE5kpZzISjmRlXIiK+Ve9OZw0ar7f6suMzOToUOHcvjwYSIiIqhVqxZ9+/Yt6nieyt27d5kxYwbW1takpqZSo0YNevbsSWJiIsOGDWP06NF4eXnRq2dPODANbhzQP2nc2EL/AUbm+k3g9y+BLhdMS0Fmsn7hVKEZVPV7odcnCIIgCK+KV25WXbVq1eR9UGvWrGHfvn2MGjWKunXrPva8Hm3V5eTk0K1bt3ytOq1WS0JCAlFRUVSrVu2xTwp/ERYvXgzATz/9xPXr1/H395cf5GllZYWhoSGNGzfGMDkCbgbrG3R5iyYAa1f9JvD4q5ByT7+XycwOPPpA7Z76OXSCIAiCIPwr0ar7v5MnT7Jv3z7GjRvH9evXSU5OJjo6GiMjoyduEC/uVh3oc+3YsSNWVlZMmDCBTz75hLCwMHQ6HdWqVWP06NHs2rWLmd1roc5OAzOHgg06c3tQaSA3A63fbLD30N+J0p9skZzny0K0VJQTWSknslJOZKWcyEo50ap7yVp1v/76K+np6XzzzTfy7zk7O9O8eXMOHjz42Gt+Hq26+Ph4efTLo22CmJgYEhISSEhI4O/Q01RKTSM9p/AGnYE2HY2Uw4lT4WQZxhTJub3MREtFOZGVciIr5URWyomslHvRrTqVJElSUR+8adOmdO3aldGjR5Obm4uzszMbNmzA29tbbtXlbboOCwuTW3V58lp1GRkZtG/fnvXr12Niom+EVa1alf79+xc6qy49PR1TU9MCd5xmzpzJr7/+mm8xBfpZddOnT+ejjz7K93q/fv1ISkpiy5Yt/3qthd1xcnV1JS4urkhadZF3btHWtzVXb97BztyAmhUcGNy3Gx0HTURtao1Op6NmzZrUrVuXNV8PRbNrIpKFAxgU0qBLvgs25dC+twLURb697aUhWirKiayUE1kpJ7JSTmSl3PNo1ZUuXZrk5OQn/ve72Fp1kydPRqPR4OfnV2irbuzYsYB+5ZjXqjt37hzffvsthw4dQqvVUqZMGUJCQgq06o4fP061atW4efMm5cqVo127dvnOobBWXXJyMt7e3pw5c4aUlBQSExMLnHtCQgIjR45k/fr1AAwcOJD58+djYWFR4L15irNVd/rEX7TxaUlGViY5uRJV7AzJSEmi2/gf6Ll5Myu3H2HOz6u4du0ay5cvx6BCQyhdGVVsOJRy0z8lPE92KkhaqPEuauPXY0+TaKkoJ7JSTmSlnMhKOZGVci+6VVekI1fgn1Zd+/btkSSJwMBA/P392bhxI8nJyQX2FgHya6dPn8bBwYF169Zx6dIlvv32WxISEvD39+fevXuA/qGUu3btYtq0aYSFhTF9+nQWLlyImZnZE1t1Dx48wM/Pj8mTJwP6jewPt+oAevXqRVhYGG3atMHT05PDhw8zZMiQoo5IkezsbDp1bEvlUmruzm7JlHerceRGGioDYwa8VY51wTeoWq06EydOZMqUKfrN9gZG4D0JrFz0LboH9yAtDhJv6v+3cmuo2fmFXI8gCIIglATFMqtu5syZmJiYsHXrVnx9fRkxYoQ8q87W1hYfHx/5d3x8fLC1tQVgwIABzJ8/n+bNm1OxYkV69+4tz4zL+zosPT0da2trunXrRsWKFenevTsVKlTAyMjosefVuHFjMjIy8PHxwdPTE4DDhw+j0+nkVt2lS5fYtWsXy5Ytw97eHjs7O3766Sd+++03oqKiijImRbb8sZ47MQkE9KlCKTs7pnWpwfL+1THQqFlx5A4AUXEP2Lj8R7788st/ftGpJnRcCPUHgFkp/VdyzrWg5efQehoYFLw7JgiCIAiCMsXSqrO0tKRGjRq0b98elUrFmDFj6Ny5MwEBAYSEhNCyZctCN4cHBgYSExNDgwYNsLCwICwsjP3792NnZye36mxtbbly5QoTJkxgwIAB7N+/nytXrqBWq8nJycHQ0JAZM2bwxRdfEBERQYUKFahWrRp+fn4MHjyYwYMHAzBhwgS6d++Oi4sLoP/6z9LSEgMDAxISEkhJSaF06dKoVKonjmUprlbdkQN7cHc0pbqbMzqdDkmS8KtZmj4tqiFJsPV0JO/9+Bf1Xc0KHsfcCeoPgXqDAemfr+wkSlyDrjCipaKcyEo5kZVyIivlRFbKlehW3bp16wqMXHFzc+P7779n5syZbNu2rdCRK4+26uzt7UlJScnXmOvQoQOLFy9m69atzJ8/H3t7eywtLXnw4AFxcXE4OzvLF//w95Vr1qxhxIgRjB8/HtA/iTvv+UigH8uSkZFBnTp15NcaNGgg/+xxiqtVFxUVRXaulvj4eLSaNPn12Fh9Yy4xKRmAsAsX+Ct+M2lpaVhYWDzxztszkyQMdBmAily1yUs/2060VJQTWSknslJOZKWcyEq5EteqCw8Pp2bNmkRGRuLg4ADAiBEjSE5OZtWqVcyZM4fBgwfLI1e6dOnC0qVL8817A7hw4QItWrRg9OjRfP755/LrGRkZDB8+nFWrViFJEo6OjvTu3ZtZs2YRHR2No6PjE8/v4MGDtGjRgsTERGxsbOTX/2vzLk9xtep2bt9Gpy7v8dcnNWnwpgeSJBEbG4u9vT0qlYr35hzi77sp1PNqzaYdu8nJycHU1JRu3brx2WefUb58+ac+dgGSDtXV3agvbdPvnVKpkBxqIlXviFTe66VbQImWinIiK+VEVsqJrJQTWSlXYlt1zzJyJa9Vd+DAAWJiYrCzs8PS0jLf55uamlKvXj2OHTvGzZs3MTc3Jzo6GktLS+zt7R97XpmZmYwfP55Vq1YB0KdPH5YtWyYvtHJycoiIiJAXPRUqVGDw4MEFNpA/qrhade07vkvV8s70X3WNP8fa4OqsP09JgsV7LrP5bCymRgbknr3A119/TbVq1QgNDcXf35/AwECCg4OpUqXKUx9fJklwdB6c/x10Epha61+7cwzunQHPYVC7x7MfpxiIlopyIivlRFbKiayUE1kp96JbdS/VyJXTp0+j0WjIzs5m8ODBvPXWWwwZMgSNRsOIESMA8Pf3Z9KkSSxdupQGDRpw8uRJevXqhZeXV6FPEc8zduxYdu7cybRp0xg/fjzR0dF07tyZo0ePAvonkefk5DBlyhRat27NsWPHGDhwYL4N5M+TRqNh25978fFuSuVJR3mnuhWlzFQcjcjgamwWpa1McHWrysHDR+SVcbt27fjwww9p2rQpH330EXv37n32E7l9HP7+A4ytwNT2n9fNSkFKNJxcCq4Nwa7Ssx9LEARBEF5yRdqqe3jkSlBQEFOmTKFDhw75Rq7kteqCg4MJDg7O16pr2LAhe/bsoW3btnz55Ze0bt2abt268dtvv8nHWLJkCc2aNaNu3brExcWxZcsWjIyMSEv7Zx/QyZMn8fDwIDIyEtA/w2nZsmWMHDlSXmSMHj2aY8eOsXv3bgA+//xz/Pz8WLx4MXFxcbi5uWFqaoq9vb28gfx5c69Wnb/DI5gz/RMS1aU4FSXRoGYVFn85hrgHmXzz3awCtxPt7e354osv2LdvH1evXn32kwj/E3Kz8i+a8lg4QlYyXN3z7McRBEEQhFfASzVy5Y8//iA2NpbVq1ezevVq+XMf3mSdlZXF6dOnqVWrFoaGhrRo0YJ+/foREBAgt+qOHTtGeHg4ERERlClThtOnT5Obm8uECRPkz+nTpw8AK1aswNfXF/hnA3neWJbSpUvzxhtvPPGai3tWnZm5OUM//YqB46bK3+2uWbMGgLfeeqvQYzRv3hyAv//++5mHFWtiw/VPIX909l0elQYp7hq6l6gRIloqyomslBNZKSeyUk5kpVyJbNVt374d0I9cebRVl5GRgSRJ8siVwlp106ZNY9q0afLnHTt2jObNm7N582b5tXfffZfly5dz5MgR6taty+nTp2nXrh05OTlyq65Jkya4u7vj5uYGIA/rfXiBA/o7XHmLNoBSpUqxdu3afMf29/d/4jU/j1l1kiRx9epV0mNvEfP3QW7f1zfqfvvtt0IHEEdERAD6DfYajeaZjl0vNhnLzEQyMgr/HPOsB9y7fY9LgYHPdJziIFoqyomslBNZKSeyUk5kpdyLbtUV28iVvMWOgYFBoSNX8lp18+bNk0euPOzChQt07NiRqVOn0qZNG/n1KVOmEB0djaenp9yq++CDD5g1a5a8x6lhw4bynLqn8bhjF2bSpEn5GoF5rbo2bdoUyay6nTt3MvGT8YRfuyG/5uFogrGBmuun99N77i8FfmfkyJGULl2acePGFbpx/b9QhSagPr4ASxs7UD+yeMrNQpWaTsUWvXGr7FP4B7wAoqWinMhKOZGVciIr5URWyj2PVp0Sr0WrzsnJiezsbAYNGsTmzZvJysrC19eXqKiofI25UaNGsXfvXi5duoSDg0O+xyA8TnHOqtu6dStdunShdXU7Fo2ojLONGbczzfluxxXCYzL5ZtFqHG2tGfzZbExMTEhNTeXHH3/k559/ZtasWU+csadYtXYQvhMSI8CqLBj+f3hwdhqk3AOnWhhUbgEv4b/woqWinMhKOZGVciIr5URWyolW3XNo1dWrVw+1Ws2WLVvYsGED1tbWDBw4kMjISBo3biy/Lz4+nrt371K9evUX/n9grVbL2LFjebt+Jbb1MAe7ityPjcPdwYFWb5bB99tDnIlIYNRXC5m2aB0VKlTg2rVrpKSkMHHiRD7++OOiORELe/CdCfu+hPhr+kHBkqQf3VK2IbSaAoavx9BgQRAEQSiWkSvdunVj6tSpnDp1itzc3HytuuHDh+Pj40PNmjUBWLx4MUOHDgX0X7FNnDhRbtUBcqsub+GktFXXt29f9u3bR5kyZeTX8+5+5f31wy5cuEBQUBAdO3bE0dGRP//8k+joaDQazROfD1VcDh06REREBOu61UNtYYtO9c+i0ECj5vN3a9By5kF+71+JCxZexGQZ8+6779KnT59n3hBegH1VeO8XuPMXxF3Rj3BxehNc6sITHgEhCIIgCCXNa9Oq0+l0dOzYkS5dushf1cXGxnL8+HE8PT3zHTuPs7Mz5cuX5+bNm4+95uJq1eUd801nQ3QaE/Ie8C5JEjqdjjfL5e2fkvhiUHukah3k3y2exoEKyjbW/8mj1er/vGRES0U5kZVyIivlRFbKiayUe1ladUU+cgX0rbquXbsyevRocnNzcXZ2ZsOGDXh7e8utuho1agAQFhYmt+oeldds27lzp7xJe/LkySxfvpwdO3bka9XFxMQQFRWFs7NzgTtOa9eupX///oW26lq0aMF3332X7/Vp06axZcsWQkND//Vap02bVmirbu3atc/Uqjtz5gxffvklh0a7Y2yo5s+wZNKzcqjqYEqbWi6cj8qk/U+hBA4uh3WzIcRa1XzqYwmCIAjC6y49PZ2ePXs+/5ErJaFV918UV6vOx8eHJUuW0Gf1HW7Hp2NupMLGREXkAx122+5Q2cEcNztjWnu+CZ2Hg5F5UVxOiSBaKsqJrJQTWSknslJOZKWcaNU9Q6vO398fBwcHVq1aRWxsLMuWLcPExORfW3VeXl6cP3+elJQUEhMTiYmJkVt1ecN/H5a3D+rkyZM0aNCg0M8urladoaEhrg62hJyPpmFZAxa2s6KGkxG7r+sYtiWOEzdTmeFXGsNGA8Hc5qmPU5KJlopyIivlRFbKiayUE1kpJ1p1/7FVB/qHZsbExPDrr79SuXJlOnXqROnSpZ/YqtNoNFSoUIF27doxadIkrl69yu3bt+VWXZMmTbh37x4As2fPZteuXTRu3Jh9+/ZRv379ooxJkfPnzhFy/hJDmpRm64UHNFicIP/MxVJNeRsNx+/kgNtbz/3cBEEQBOF19cq16pYtW0ZQUBCHDh1CkiQmTpzI7du38z1d/NE9TtbW1gwePJjAwEDq1asHwPDhw2ncuDGenp4AGBkZkZqaKv/Jzs5m48aNdO/enZycHIyMjAq95uLaHL5u5VLsLQ35sU8t5ptYs/v8PW7cvkcVZ0t8qtuz/GQcw349T9zfe7Gu2+mpj1MSic2WyomslBNZKSeyUk5kpVyJ3Bzevn17dDodXbp0wd/fn5CQEHbs2CG36jw9PTl37hw2NjaFtuoet9HazMxMftxAjx492LFjB5mZmWi1WszMzOjatSsLFy7E1FT/PKF58+YxduxYjhw5It/ZyszMZPz48axatYqUlBTatWvH0qVL8z0A09vbm0OHDhU4fkRExGMr/sW1OXz5orlcO3+C/eNro1MXXLTtv5xAr6UX2DZ7BLrKrZ/6OIIgCIIgKN8c/sq16vz8/Dh48CCtW7fmiy++IC4ujmHDhtGiRQuWL18OPP45TvDPXqbExERsbGweew3vvPMOAIH/MoOtsDtOrq6uxMXFPdPm8B9/+I7JU77gzreNKe3ogiRJ3L9/n79jYfXR2wSHx3I3IYMdK+bg3XVYgedSAfoHVcZcQH3rCGQkgXlpdG7eYFcFCnt/CSE2WyonslJOZKWcyEo5kZVyz2NzeOnSpUteq06n06FSqVizZg3W1tYAzJkzh/fee49FixZhamr6zK26u3fvsnv3btavX/+v7y2uzeEfDBrKZ19MZ9rmKywc4kBGroq+AWHsvZRAJQdzIhMyMDM2wLfPWLpuP87q1avzHy83Cw5/D1d3Q046oAIkNH+vhxqdoMnIgrPnShix2VI5kZVyIivlRFbKiayUe9Gbw4v8sc8Pt+pUKhVqtRp/f382btxIcnIy48aNw9LSkuDgYIKDg7G0tMzXquvRowdOTk688cYbSJJUoFXn7OyMi4sLs2bNonz58hgbGzNy5EgkSeLu3buPPa/MzEyGDx9Ohw76B0X26dOHmJiYfO8ZNWoU9erVo0KFCqjVavm9L0Lp0qWZN+sr/I/G8fY3+3h39gGOXEmkZyNHHqRnUc7OlMuHt7J27Vo2b97MZ599lv8DTi6Fi1v0jykoVQnsKun/V2MI59bC+X9fFAqCIAiCkF+RLpwebtV16NCBXr16YWJiQlBQEC4uLqxbt465c+eSkpKCl5cXXl5epKSkMHfuXIACrbp58+YxadIkFixYIB+jadOm3Lp1iz179hAQEEB4eDijRo1CrVZTtmzZx57b2LFj2b59O9OmTQMgOjqazp07F3hf//79MTU1xdbW9oWv/oeO+ZQ/Vi0jMsucvZeSyNJKbDoTS7vG1QneuxOnem/To0cPJkyYgL+/PykpKfpfTE+AyzvA2AJMrP/5Wk6lAjM7UBvBhT8gJ/PFXZwgCIIgvIJeuVadvb09Op0OFxcXXFxcuH37NgEBAQwYMEDeHP7oHqfk5GSWLVvGzJkz5e8tR48eTZ8+fdi9eze+vr4A/Pjjj+zbt4/U1NQCe6Mep7hadXk6dOtLms6QDz74gNlTP6bXB/2xK1tFPgZAz549+frrrzl48CB+fn6oIkPRpMUhWbuCTlfwQ01s4UEU2uiL4PTGM5/jy0a0VJQTWSknslJOZKWcyEq5l6VV98rNqgsKCqJRo0acO3eOmjVrotFoqFWrVr6xKYXNqsvNzWXChAnye/r06QPAihUr5IVT3jW4urpiYmKi6Jq/+eabQlt1e/bseaZW3cNOnz4NgGv1Bpw4fxXOX83388TERACOHz+OTqfD/sEF3khNIS07vtBN4CpdLqa5Dzh75BBJ5neK5BxfRkFBQS/6FF4ZIivlRFbKiayUE1kpV1xZpaenK3pfkS6ctm/fDui/Tstryfn5+ZGcnExGRgaSJMmturZt2wL6h1nmteqmTZsmf5UG/7TqHn5G040bNzh79iytW7dm/fr1cqtu/PjxcquuSZMmuLu74+bmBui/ljMyMip0Vl3eoi3P2rVr5Vl1ShTXyJWHOTk58eOPPzJy5Ehyc3Oxs7OjR4/ufNS2LvZxx1l6OAi1SsWgxqVwbdYAcmqg2bQHc7URmNoU/MC0WNCUoUnbnmBWqkjO8WUiWirKiayUE1kpJ7JSTmSlXIkduZLXqps8eTIajQY/P79CW3Vjx44F9CvHvFZd3siV4OBg7t+/j1arxdfXN1+rLj4+nqysLHbu3MnOnTvl13/99dd/bdX16tWL7du3o1ar6dKlC7qHvsbKzMxk6NChnD59mrCwsAKb0h+nuFp1eR48eMCoUaMASE5OZtSoUSTExzN71res+EnFr70rMGPTTTq8aUPFm7/Bg7/A9xso3xiuBoGJBWgeeg5UTiZkPYDavVBbOz7z+b3MREtFOZGVciIr5URWyomslCuxrbr27dsjSRKBgYH5WnWFPW8o77XTp0/j4ODAV199haWlJW3btuXAgQP5NoeXKqW/QxIeHs69e/e4d++e/BTxx7Xq8mbVnT9/nqCgIHbs2MHhw4e5dOmS/ABMrVaLqakpo0aNomLFikUdy1P7+OOPCQ8PZ9OmTVhaWrJ48WKM0+8xqbUDSRlaWi24grmpEf5DvMC2AiREwP4Z0Hikfv9S0h1Iug2p9yHxFqREQTlPaDjoRV+aIAiCILxyiqVVN3PmTExMTNi6dSu+vr6MGDFCbtXZ2tri4+Mj/46Pjw+2trYADBgwgCFDhjBhwgQGDBjA1q1b6d+/P5s2bZLfn7ep3MzMDCcnJ5ycnEhMTHxiq87CwgLQ72tq1KgRXl5efPrpp6Snp1O5cmUAzM3N8ff3Z/DgwfL7X7TExERWrVrFp59+Srt27Zg9ezbDhw9je9BhvvwzChMjA3QSLB5QDycbU/1zmazKQNwVSLwJ7eZBs/FQugoYmYFjDfCeCO98r2/bCYIgCILwnxRLq87S0pIaNWrQvn17VCoVY8aMoXPnzgQEBBASEkLLli0L3Rx+4cIFWrZsia+vL+PGjSM6Opro6GjMzc3lY7Ru3Zo5c+bg7u6OmZkZ5cuXJyYmJl+r7osvvmDGjBncvXuXMmXKcOHCBYyMjFi4cCENGjTAysqKgIAAQL/Yy3Pt2jVSU1PJyMhAq9USGhoKQPXq1Z/7rDrQ34HLzMykbdu25OTkYGNjw5SPR/C12wlQG6A1ssZi4GbC7ibjXc1e/0saY1TaXLQxl5DKNIQa7+n/PKoENzhES0U5kZVyIivlRFbKiayUK9GtunXr1hXYHO7m5sb333/PzJkz2bZtW6Gbwx/XqnN0/GcvTsWKFZk2bRqBgYGcO3eOS5cukZGRQf/+/eX35H1PmRdCdHQ05cqVo02bNnTp0oWsrCx8fX2xs7MjOjpa/r1Bgwblm1VXp04d4Mmz6oqzVRcWFgbAvn37OHf6JNr0JPb9eY+mSclIqHggZaDV6UhPS+X+/fv6X5IkzLNTuRZ2kdvRTx4XU9KJlopyIivlRFbKiayUE1kp96JbdUU+qy48PJyaNWsSGRmJg4MDACNGjCA5OZlVq1YxZ84cBg8eLI9c6dKlC0uXLs3XTAP93acWLVowevRoPv/88yces3nz5pQrV45Vq1YV+vOZM2fy66+/Eh4enu91BwcHpk+fzkcffZTv9X79+pGUlKSoWVdcs+pA/w+xbNkyWJkYEBWXDICViYZ+jR34orUtW2+aMXDpKS5/70sVp/9vZs9OhawHaNvOA+faz3T8V5VoqSgnslJOZKWcyEo5kZVyJXZW3cMjV7RaLSqVCpVKhbGxMQsWLJAXSMHBwYB+kfLwyJVvv/2WAwcOEBMTg52d3RPbbUePHqV58+aUKlWK7Ozsx77PycmJe/fu4ePjQ0hICBqNhk6dOpGQkCBvDgcKbFxXqVSsW7eO7t27P/azi7NVt3X9GlJT00hLhWFvOeNdxZwzkdksPnSX7aH3ScqCjvVccHf5/36l3ExIuw/lm6B2rV+iB/kqIVoqyomslBNZKSeyUk5kpdyLbtUV6cLp4ZErwcHBmJmZsWnTJnbs2MGQIUNYt24dGRkZDBo0CC8vLwBSUlJYtmwZY8eOLTBy5a233mLIkCFoNBr5yeF5kpKS6Nu3L61ateLYsWM4Ozs/9rwqVapESkoK1tbWnDhxggcPHtCvXz+0Wi2NGjXK997ly5fz559/kpyczIoVK7CxsSnKiBRLSkrio1Fj6Vvflgy1KYsOR7HvihmNKtvj5mDJ2VvJOFmqWf6enX4juE6r3xxepi60+Py1XzQJgiAIQnEo0lbdwyNXgoKCmDJlCh06dMg3ciWvVZc35PfhVl3Dhg3Zs2ePPHKldevW8siVPPPmzWPr1q306tWL1q1bk5ycTGpqKsOHD5ffs3nzZjw8POS/Dw8Px8jIiBs3bpCcnEx2djZpaWlAwe80ExMTycjIICsri+jo6EKfB/U8rF6+lJycHL7r6sHvo5qyZ2Izqjubcy0mFVc7czrUcSQjB8xrvA0VW0D1juD7NbT/CSxL9vOZBEEQBOFFeeVGrmRnZzNkyBBiY2OxtbXFysqKSpUq0apVK/k9O3fuzLefKSsri9KlS+Ph4UGrVq1Qq9X4+Phw69YtgoOD5UcSAPn2WuVtDn/SNrDiatVd/Pss1ZxMcShdCkmSaFndgTfsVdjb26NSqfjz3D22nY0h0rgiZVsMyP/Lr3k7Q7RUlBNZKSeyUk5kpZzISrkS2ap7HiNXOnXqxA8//MDly5epWrVqoeNR2rZtK++hAmjZsiXjxo2jTp06rFixgrS0NAYPHgzAvXv35Pd9+eWXtGzZEjMzM/bs2cPUqVOZNWvWE6+5uFp1CYlJRCdnE3s/mjTJhBNX40jPyqaKQxxVy9px5XYMAFevR3A+4/Vuzz2OaKkoJ7JSTmSlnMhKOZGVcqJV9x9adVqtFk9PTwYOHMjQoUMB5IVT3jOXHmft2rWMGzeOuLg4NBoNo0aNYtWqVYwdO5ZPP/200N/54osvWL58OXfuPH4QbnG16s6cPo1n48b0qGvNrkspJGb8Mx7Gs5wRKdkqnGzN+fN4GJjZPfVxSiLRUlFOZKWcyEo5kZVyIivlRKvuKVp1KSkpnDp1irNnz8qbxbVarf5CDAzYs2cPLVu2LPS8Jk+eTExMjPw7s2fPRqVSyeNVpk2bVuidI9AvjgprzkHxteoaeXpSsawj687E4FfZkFnv2ONgrmbb5Sw+CUwkOUtiQjcvDK2d/v3DXlOipaKcyEo5kZVyIivlRFbKvehWXbGMXPnhhx/o0KEDvXr1wsTEhKCgIHnkyty5c0lJScHLywsvLy9SUlKYO3cuQIFW3bx585g0aZI8q87Kyoq///6b0NBQDh8+jLOzM2XLlsXY2JjQ0NACDblHffnll/J8uzlz5mBqaiqPf/n444/ln+X9sbe3x8jI6LGLpuJ0+/ZtIiJjcLc3ZNe1HFoui8V72X2GbklAJ4G9uZrdJy5BVupzPzdBEARBeF29Uq06tVpNzZo1qVmzJj/++CP9+vWjUqVKqFQqatasKY9mebRVB/pbcElJSTx48ICNGzfy2Wef8c0338iPGzhw4AA7duwgLi6O1NRUfvrpJ2JjY+nZs2dRRqTY6uVLMDfScOqLJpyZ0ZIPvcvSoqo1C3tUInL+23zaoTobQu6ReunACzk/QRAEQXgdvXKtOtA/a+nGjRusXr2a1q1bFziPR1t1oG/jzZ07lzlz5mBiYkLHjh0ZNmyY/HNDQ0MWLlzI2LFjkSQJU1NTHBwc5Jl2j1NcrbrI27dwszPGzMycWjZmvFm+AbGxsXKrroarDTlaiZjICIxriDbGw0RLRTmRlXIiK+VEVsqJrJQTrbqnbNVdvXqViRMncuTIEQwMDPD29iYpKSnfeTzaqgP913R169alVKlSHDt2jEmTJjFhwgTmzJkjn6efnx8AmZmZuLi48Mknn6BWP/mmXHG16lIyMomIz+Ru5F1uJGvYde4e6Vk5VHUwpW1dF05cuo+hBm5G3edCoGjVFUa0VJQTWSknslJOZKWcyEo50ap7Tq26R/3yyy98+OGHpKamFtjDtG7dOvr27cvdu3fzDRguTHG16m7duoW7e1U8Shtw8X4OtqYq7EzVXE/UYmkEJoYaWlR3YNW+C2D8+LE0ryPRUlFOZKWcyEo5kZVyIivlRKvuObfqKlSowK1btwq8fvPmTdzd3QkPD2fo0KFcvHiR2NhYTE1N+emnn5g6deoT/wEVV6uucuXKuLk4cPGuvlX3Qzs7HC1UbL6YxceBidxP1fJO4xoYWpR66mOUdKKlopzISjmRlXIiK+VEVsqJVt0LatUtWLAAtVot3xUzNDSkb9++LF++HNA/QXzp0qVMnTq1KCNS7Mzp01y/G0PXWlYcv6ulxrxoSn91j8GbEqhS2ojqjsas2XsW0hNeyPkJgiAIwuuoSO84Pdyqmzp1KqdOnSI3Nzdfq2748OH4+PhQs2ZNABYvXix/7dawYUMmTpwot+oAuVU3YsQIuVUH0L17d/r168eRI0eIi4uTXwd9q27SpEnynLnjx4/z4MEDHjx4QHp6OsePH2f69On07t1bbvRVrFiRihUrMmXKFJydnZk2bRppaWkcOXLkiddcXJvDf18VgKOVIas+akiWxpx95+4QE5dAvcoO1K1aloCDNxjySyix54Owqdf5qY9TEonNlsqJrJQTWSknslJOZKVcidwc/rK26oyNjUlLS+OHH35g9uzZGBsb06JFCxYtWpTv93Q6HStWrKBfv35ERESwa9cuOnd+8qKkuDaHh1+6SGkzDckpKWjV2Xi6WYCbBQD3Y+Mw1+QC8NfRYHQxJk99nJJMbLZUTmSlnMhKOZGVciIr5Urc5nDQt+q6du3K6NGjyc3NxdnZmQ0bNuDt7S236mrUqAFAWFiY3Kp7VF6rbufOnbRp0wbQt+q8vLw4cuRIvll1D28Of/SOE8CcOXMKtOr69+8vt+ryNGnShDNnzpCVlcWQIUPw9/d/YrOuuDaHL5z3AxMmTeby9AYcuJ7BppO3eZCeRXVnc4a0rMT603H8fPAWkWeCMKrk9dTHKYnEZkvlRFbKiayUE1kpJ7JS7mXZHI5UxC5fviwZGBhIO3bskNRqtfTOO+9Iw4cPl3r37i1JkiT98MMP0oMHD6SBAwdKAwcOlB48eCD98MMPkiRJUmhoqNS9e3epbNmykpGRkaTRaKR33nlH/uzc3Fypfv36kr+/vyRJkhQcHCypVCrJxMTkX8+rffv2kqurq2RsbCw5OTlJnp6ekoGBgZSZmZnvfbdv35YCAwMlY2NjSaVSSd99991/uv7k5GQJkJKTk//T7z0qISFBMjEykKyMVRIgtXAzkrq9YSyVtVJLgGRigDTKt4ok5eY803FKouzsbGnLli1Sdnb2iz6Vl57ISjmRlXIiK+VEVsoVd1ZK//tdpJvD4Z9WXfv27ZEkicDAQPz9/dm4cSPJycmoVKoCv5P32unTp3FwcOCrr77C0tKStm3bcuDAAXlzeF6rbsSIERgYGODl5YUkSWRmZmJgYMD+/fsfe14tWrRg/fr1hIeHs3HjRjIyMsjNzeXmzZv53ufk5MQXX3xBy5YtMTExYdq0aXJz73mytramtK0VD7Ik6rsYMKiBOQPqm9OnjjmmBpCZC+6u9qAp8mKkIAiCIAiPUSytupkzZ2JiYsLWrVvx9fVlxIgRcqsub+RKnodHrgwYMIAhQ4YwYcIEBgwYwNatW+nfvz+bNm0C8rfqWrduzZAhQ6hfv76iVt3YsWPx9PSkfPnyNGnSRH5sQd6x83z++ed4eHjQtWtXQH9rUKfTFWVMiuzds4e7MQl818EFQ2Njeq1PxHd5Agv+SqW/Z2l8q9nw865zSHHXnvu5CYIgCMLrqlhadZaWltSoUYP27dujUqkYM2YMnTt3JiAggJCQEFq2bFno5vALFy7QsmVLfH19GTduHNHR0URHR8sz6PJadcuXLychIYEdO3bQunVreVZdnpEjR7JgwQKk/2/fOn78OCdOnKBFixZYWloSFBTEokWLsLe3lx9HsGbNGsLDw1mzZg07d+7k559/JjMzk549ez7xu9TiatXt2r6R8qWMGd++Jh+/b0VUfCp3o+5Ro2IZzM3N2HDiDt0XnCDy/AEcm5V/6uOURKKlopzISjmRlXIiK+VEVsqV6FbdunXrCoxccXNz4/vvv2fmzJls27at0JErj2vVPfz07kdHrihhbGzMb7/9xsSJE+VFjqvr/9q77/gaz/+P468zsjcRCUKM2ivUSGnFiJWGorWitlRrK/1WS43WaGgpWv0ZNYvaatSoSjViEypI7ZlIIhLZyTnn/v1xmruOBDdykojr+Xh4fOuM+77uzzfq6n1f7+vjyeHDh+XPpKWlMWPGDLRaLU2aNMHJyQlLS0sWL178xGObK1V37epVLDUQfz8BvSYdLeBV0omUlGRSUpLJTE0C4HR4OLok0XIlNyKlopyolXKiVsqJWiknaqVckUvVFeaWK3FxccTHx3P9+nUmT56Mk5MT27dvR6VS0blzZypXrsyMGTMAWLZsGSNHjszRB+9R5krVrV29it59+7Pjwypsi0hi08m7JGcYqOpmSVCzUhy6ms4fF+7xz8m/0JT2fu7zFEUipaKcqJVyolbKiVopJ2qlXJFN1Y0dO1YCJI1GIwGSSqWS1Gq1ZGNjIyUkJMify07VPSw7VVeyZEkJkIoXLy7NmTNHfv/+/fvysbN/AfJr+/bte+y4vvrqK8nHx0eysbGRnJycpJs3b0qAFBYWJkmSJNnY2MjHevTX7NmzFV9/XqXq0tPTpeJO9pJaheRmp5LGvmknBbexlzpUtZZUIKlA+vK92pJkMLzQeYoikVJRTtRKOVEr5UStlBO1Uq6wpOry9FHdwy1XQkNDsbW1ZdOmTWzfvp2goCDWrFlDWloaAwcOpGlT495DSUlJLF68mFGjRuVoufLWW28RFBSERqNh6NCh8uLw7Jlht27dAIiNjeX48eOUL1/+sWPLzMzkvffew8fHhyVLlsgLvrPvFh08eJDExET587t27WLWrFl4e3vTp0+fvCyTYgaDARWglyBLDzoDZOglJEAFGPJ+Cy5BEARBEJ4gT1N1D7dc2bt3LxMmTKBDhw4mLVeyU3WhoaGEhoaapOoaNmzInj175JYrrVq1kluuwH+Lw2vWrMncuXPp27cvFStWlBeHZy8i37x5M1WrVpXHdeTIEUqUKEHz5s3x8PBAp9PRo0cPKlasiI+PDwDe3t74+vrKv0qXLo1er2f48OE5knf5YcMva7iflMquodXp1bg06yMy+PqvFBIzVCx9vxL9mpZi4e+R6G+dyPexCYIgCMKr6pVouZJ952vixIk8ePAAvV5P7dq1GT9+PFZWVrley8GDBwF49913n3jN5krVHTkYQlV3G1rULUeLhnZ801ciNjaWEiVKoFKpKH7qDj+F3uHmuaOUdq/z3OcpikRKRTlRK+VErZQTtVJO1Eq5Ipmq27ZtG2BsufJoqi4tLQ1JkuSWK7ml6iZNmsSkSZPk42W3XNm8ebP82qOpOl9f3xwLuP39/QkNDZV/X6tWLXlzzOxF3wsWLHjitZw5c4YPP/wQGxubJ37OXKm6O3eiSE7XcS8uFr02hTsJ6SSnZpCcmoa9rQ1RMfEAXLgQyel0karLjUipKCdqpZyolXKiVsqJWilX0Km6PN92OjIykqNHj8qTHa1WS7du3ViyZAm+vr7ExMSwd+9eOVU3Z84cFi1alOM4Z8+epWPHjkycOFHuU6fX6+nZsyeTJ0+mcuXKjx1Dp06d6NSp03Nfw6FDhzh//jwrV6586mfHjRtnkgjMTtW1bt36hVJ1VpYWbNy+h6VhUWz9+wFhV4zbD1hpoXtdR24+kKjraUeL7kNQFXv82q5XkUipKCdqpZyolXKiVsqJWimXH6k6JfJ84pTdcqVUqVLo9XpUKhUqlQorKyvmz58vTzKy7wj17dtXfu306dPMmDGD/fv3c/fuXYoXL46Dg4N87OyWK6dOnWLo0KEAcjsUrVbLnj175B3BHzV16lR27NjB8ePHH3s77tF2MK+//jpr1qyhe/fuj71eKyurXB/3WVhYvND/sa3btMWrtBv/23obbw8Nq7s64+GgIfSmjq9DHpCcKTG3Vy0sSz5+Avmqe9H/D14lolbKiVopJ2qlnKiVcuaqldJjmqXlyjfffEOHDh0IDAzE2tqavXv3yi1XZs+eTVJSEk2bNqVp06YkJSUxe/ZsgBypujlz5jBu3Di5V93DLVcOHDiAh4cHZcqUUdRyJTtV97iJVbYFCxZgZ2fH1KlTiYqK4p133smz+jyL9PR04hOTcbRScypKzw9HUph/OJnvw5JIzpSwt1Rx7OJdEC1XBEEQBCHfvBKpOoABAwbQvHlzec1SeHg44eHhJCcnm3zu7Nmz6PV6PvroI9zd3bG2ts7LEim2fv16klJSOTKmGquC6lLcyZ74dDXv1ivO35N9GN+pButOxJIYvq1AxicIgiAIr6JXIlUH8MUXX7B8+XL5997ext229+/fj6+vr/z6woULUalUtG7dmsGDB9OvX78cj/AeZq5U3fnz5/EsZkPlMsWoXLUk3ZtWNEnVJervkaGTuHbxHNWbiTTGw0RKRTlRK+VErZQTtVJO1Eo5karLx1QdGNN02b8e10plypQptGjRAltbW/bs2cNHH31EcnIyw4cPf+w1mytVFxUVRVxSJndjYkmO1xN6IYbUjEwqu8VQ08uVc9fuARB3/z47d4pUXW5ESkU5USvlRK2UE7VSTtRKuYJO1b1SvepAeQ86MN6lWrp0KTdv3nzsZ8zVq+7y5ctUr16d1lVsOXg1leSM//5vquthgUprgZVGxV97fkXyevO5z1MUiZSKcqJWyolaKSdqpZyolXKFpVfdc91xOnToEE2bNqVt27bs2LHD5L3sVJ2Hh4f8iEuSJCwtLUlNTeXo0aN8/vnnODs707x5c5NUXbZz587x1ltvkZCQwIYNG+SJU26pOoPBgCRJqFQqLC0tsbGxeeKkKDk5mQcPHqBSqbh//z7Ozs4AbNq0iQULFhAeHk5GRgY1atSgXbt23Lp1i4yMjMdulGmuVF3VqlWpWrEcuy9co3VFLd8FFMfDUcvmc+mM3hHP/bQsfuxTC235pqAVf9hyI1IqyolaKSdqpZyolXKiVsq9lKm6JUuWMGzYMA4cOMCdO3fk12fNmsXy5cvp3r07kydP5uDBg4wePZrTp0/j6OjI/fv3WbVqFREREcycOZMtW7bIiblsERER+Pr6YjAY8PPzM3nv4VRd9q/BgwdTvHhxxo4dywcffPDUsf/0009oNJocrx84cAA/Pz927tzJiRMnaN68OZMnT8bR0fGxkyZzunLlCucvXaOBpw17Luto8EMMdedGMWDjPfQGKGGnJuR8HBjEc3FBEARByC/PfMcpOTmZX375hePHjxMdHc2yZcv47LPPALhx4waxsbFYWFhw7do1RowYweDBg6lZsyZ9+/bljz/+oFmzZgBUqFCBQ4cOsWnTJvnu0dmzZ+U1RoGBgWg0Gm7duiUvis5O1T3Mzc2NMmXKEBwczLJly1ixYgWbN29m3LhxXLhwQf7cjRs3+PHHH4mPj8fCwgKdTsfff/+Nt7c39vb2tGzZkrt372JjY4NKpcLT0xNJkuRF5I9jrsXhKxb/gJONhj8+aURUuhUbDl0mNj6B6qWd6PpGBRb9dYdx68+REPEHdjXbPvd5iiKx2FI5USvlRK2UE7VSTtRKuZd2cfi6detyJObGjRuHSqXi6tWr+Pr6smfPHsA0MdelSxeCg4M5c+YMtWvXBiAxMZFixYrJx85O1YFxR/FsDRo04Nq1a4BxjVK/fv140tKsxMTEHKm64cOHs3XrVpPX3nrrLTlVZ2Fhwffff8+oUaOQJIlKlSrh7OxM586dn1gPcy0OP3XiGJ7OFqSmp+OgNtCvSSmgFACp6Rl4OKjI0kv89cduDDcMz32eokwstlRO1Eo5USvlRK2UE7VS7qVbHN6kSRO6du3KiBEj5LVM69evx9fXV07M1ahRAzA+dstOzD0qOzG3Y8cOuaXKxYsXadq0KX/99ReVK1fOdeF3bneTsj1u4XdGRgYNGzZk7Nix9OrVi5CQEJo3b26yxulRwcHBzJgxgwsXLsiL3HNjrsXhM6ZMIHjmLG4HN8G+mBuSJLE//Cq/X0zhQaqOW/eS2XM2hrvHf8W2ehuQJIg+gyr6DEgGKF4RqUwj0Lx6z8zFYkvlRK2UE7VSTtRKOVEr5V7KxeEvax+6cePGUa1atVwncLlZvXo1kydPZuvWrU+cNIH5Fof3DRrCpGnBzNtzkZGditHzh6P8evIObo5WuDpYcu52EmoVrD98k4EVE+CPL+H2SdClg0oFKg0UrwQtJ0CJKs89jpeZWGypnKiVcqJWyolaKSdqpdxLtTj84T50Wq0WrVbLggUL2LhxI4mJiYwePVruLXfp0iWcnZ3Zt2+fyTHOnTtHy5Ytady4MWXKlJFfz07MffTRR3J/u8mTJ3P69Gm0Wi1//PFHjvEcPHgQrVZL3bp1nzjuP/74g3Xr1snHbd68OQCurq5MnDjR5LNr165l4MCB2NjY4Ofnp2jbAnPw9PTkk2FBjN8RRe3/7WTv39HM7FKR2d2rgj6LYrZa3m37FoMGf8S2qe/DtYNg7QTFKhh/2ZeE2AuwaxwkRRfINQiCIAhCUaN44vRwH7qHU22nT5+W+9Bl69u3L9HR0TmSdxERETRq1IgePXrQpUsXALlXnaOjI5MnT6Znz5789NNP7Ny5k5YtW6JSqfjkk09y9KFLSEigd+/etGzZ8qlj37hxIx988AFjx46ld+/ectuVv/76iyFDhsifW7NmDf369aNWrVryzuYFadrsBXz8UX+u3MskLcvA2I2XCVx4GlcXJ0I3LWLtjhBa+Hjz1ZpQcCoNVvbGu00AFtbg4gUJ1yHytwK9DkEQBEEoKhQ/qsvuQzdgwACcnJxM3svuQ5e9KWVuybsOHTrQokULatWqxYEDB4iJiQFg3rx5DBs2DLVazRdffGFy3CNHjhAeHs7hw4dN+tCNGzeOunXr0rNnTzQaDevWrSM8PJwbN26g1+vlNVGVKlXC3t6eihUrsmDBAsC4Dir7UWK1atXkNU6rV6+mT58+dOnShRs3btC/f39+++03EhMTH7sOCsyXqsvm4FYWR0dHls//mrMnDvF2QAdqNPUHtQadTkdQq8p0//IUNxL1lCn26CJxFWgs4eLv6Osoe0xZFIiUinKiVsqJWiknaqWcqJVyL12qLrsP3aOTJsiZmMsteZeRkUFsbKycmjt16hQAZcqUoW/fvo89r8FgMEneZSfmHB0dWbVqFV999RXR0dEm2wY8rg/dkyxcuBCdTscvv/wCwHvvvQcY10etXr36sd8zV6ou25kzZ4xbJDh6UKt5Z64nw/Vdu+X39cnGel6/HYOlLuf5rLJSyUy7zuFXsC2LSKkoJ2qlnKiVcqJWyolaKVfQqTrFE6fsPnS5adiwocn2AEuWLMnRqy57Q8ncknerVq3KdeF269atmTp1KkFBQfJrTZo0wc3NjVWrVqHVGodftmxZ4uPj5c9k35V63KRJq9Xm2M5g9+7duSbvfvjhhyfWZdy4cSY7n2en6lq3bv1CqbpscXFxbN68GS8vL1avXs3Zs2eJiYmhVKlS9O7dm/MJ1thZqqn7WinstAZUKbGQmQwqNZK1M6pMDYYKjWjfpv0Lj+VlIVIqyolaKSdqpZyolXKiVsrlR6pOiTxt8gv/Je8+++wzNBoNbdu2zTV5N2rUKMA4c8xO3p0+fZoZM2YQGhpKTEwMer2eNm3aPDZ5d/DgQaZMmZIj1ZZb8i4+Pp5hw4axadMm0tPTGTBgAN999x329vYAfPDBB0RFRfHxxx8zcOBAXFxcgKffujNXqi5bjx49GDNmDC1btuTevXv4+PhQt25dzpw5w7vvvouFhZbeDUvikHIN0u6DPsu4zkkCVfJdUGvRlK6H5hX8AylSKsqJWiknaqWcqJVyolbKvVSpOiWyk3cBAQFIksTOnTtNknfZ/eselv3aiRMncHNz46uvvsLBwQF/f3/2798vt2XJTt4NHToUrVZL06ZNkSSJ9PT0xybvsgUGBhIREcGYMWOwt7fnwIEDJneyjh49SlxcHPfu3UOn08lrsEqWLJkjeZefbG1tqV27Nvfu3aNUqVLyOqyWLVtib2+PTqdH71Aaku5CVppx3ya1BagwbkmgsYQL243vCYIgCILwQvJ04pSdvJs2bRrW1tZs3bqVNm3aMHToUDl55+LiYtKDzs/PT767079/f4KCgvjkk0/o378/W7dupV+/fmzatAkw7VXXqlUrgoKCeP3117GysiI8PDxH8i7b+fPn2bVrF4sXL6ZixYpoNBrmzZvH2rVr5cTftm3bOHPmjJwWXLx4MQC1atUySd7lt9u3b3Pw4EGGDh1KyZIlGTx4MO3ateOHH36gf//+fPbZZ6z9I5x4HMEue88pCSwdwPU18KgN9y7DtdACuwZBEARBKCry9FFddvLOwcGBGjVqEBAQgEqlYuTIkXTu3JklS5Zw7NgxWrRoIcf9H27Lkt2rrk2bNowePZro6Giio6PlRF12r7qlS5cSHx/P9u3badWqFSqVyqSH3bBhw5g/f768junQoUM4Ojqi1Wrl5J2rqysqlYqQkBB69uxJxYoVTa7l9OnTgHFi96w7h0Peper++OMP9Ho9n3zyCSdPnqRBgwZkZGRQokQJrKysuH7tGlOnTuWvO5YE+FQFg874RbVW3ppAZdBjuB2Owcv3hcfzMhApFeVErZQTtVJO1Eo5USvlXrpUnRLZybs1a9bkWBxevnx5Zs6cybRp0/j111/x9/cHoGvXrnJbluxedatWrWLVqlXycUuWLCn/88WLF/n000/566+/5MXhTxMdbdwA8uHkXYMGDQA4duwYPXv2lF9/4403OHnypDwZym5g/DjmTtWdPHkSMG72aWNjw7Fjx0zevxcXB0BScgox/yYWH2WXkcytyPP8k/iEZJ0k/bcHVBEhUirKiVopJ2qlnKiVcqJWyr00qToltm3bRmRkJDVr1szRliUsLAxJkvj2228f25Zl0qRJTJo0CTDefWrevDkjRoxg/PjxQO5tWXx9fXPs7j1v3jzmzZtn8pq7uzuJiYkmr7m5ueVo7/LLL7+QlJTE6dOnGTt2LIsXL+aTTz557DWbO1VXpUoV5syZw4MHD+TdzC9cuMCcOXPYvHkzycnJAFyLz8S5mCuW2keevhp0qBJTeO2NDlSq+kiyTp+J6tLvqP7Zier+NbC0Q6rQEkPVt8Gx1AuPvaCIlIpyolbKiVopJ2qlnKiVckU2VfdwWxa9Xi+3ObGysmL+/PnyJCM01Ljmpm/fvvJr2am6/fv3c/fuXYoXLy63cIH/FocfP36cDz/80PRCtFr27NlDixYtcozJ3d2du3fvEhgYyLZt21Cr1XTq1In4+Hjc3d0BSE9PZ/DgwZw4cYLz58/z9ttvM2PGDIKCgvj444/RaDS5Xq+5U3VVq1alffv2TJo0ifHjx7N//366dOmCh4cHvXv3ZsWKFTg72DLptzuEXt3Pr5+0wNLi37FKBnhwG5w90VZuCQ+PR5cBB6bDxX9n7pZ2kBILJ39Cc3kvtJkGJau/8PgLkkipKCdqpZyolXKiVsqJWilX0Km6PJ04PdyWJTQ0FFtbWzZt2sT27dsJCgpizZo1pKWlMXDgQJo2bQoYJ0OLFy9m1KhRnDhxAo1GQ2ZmJoMGDeKtt94iKCgIjUbD0KFDcXR0ZN26dVy9epXKlStjY2PDzJkz+eOPP/j8888fuzjcx8eHxMREjh07xt69e8nKyqJbt27o9Xr5O3q9HhsbG4YPHy7fDTMYDGRlZWEwGB47ccoP2Vs5DB8+HLVajZeXF7Vq1WLhwoXUrFmTfb//Tvj6YNoNm8msDYf4zL8CSHrj5MixFLSYAFYOpgc9uwn+2W1cUG5l/9/rBj3cvwYh0+HdpaDJ87m1IAiCILy08jRVl704vFu3buzdu5cJEybQoUMHDh8+LLdlyU7VhYaGEhoaapKqa9iwIXv27MHf358pU6bQqlUrunXrxtq1a42DVat57733+OSTT3jnnXdo06YNTZs2xdHRkStXrpi0ZalatWrOi1Wr5Ttgj26LsGXLFpo3b07Tpk2xs7Pj9u3bjBs3jm7duhX4fwW4u7tz8OBBGjduTFZWFvfv3+fatWt8++23hIaGUqx4cVp8MIP33+vIj0dTMDh6gmsVaPwRvPMjlK5nekC9Ds5vNW5b8PCkCUCtMU627l2Em0fy7yIFQRAE4SVglsXhu3fvztFy5eeffyY4OJh69eqxbt26XFN1j1sc/qRF1lFRUaSkpNCsWTP5tR07dhAZGSn/PjtVV69ePVq2bCk/qlu5ciVHjhyhU6dOaLVavv76a/755x/S09OxsbFh3Lhx8kadj2PuVF02GxsbHBwcqFWrFidOnDB5L/s87br0YsmaLdx5K9hkQT2PjiMpGs2DKONdKMOj/e0AjRXo9RhiLyKVLvhmx89KpFSUE7VSTtRKOVEr5UStlCuSqbrstixNmjTJkapLS0tDkiS55UpuqbqHF4cDhIWF0axZM3mh+cPKlClDbGwsOp2OSZMmMXDgQPk9f39/eQ0VGFN17u7uOXrO7dy5U07cdevWjW7dugHGdVcJCQmMGzfuqdds7lQdgCRJ3L15mfTEOGKio9ixY0euG4n+9ddfAPz555/yjui5sdQl0SjxARIpZGnTczshdplJ/HP2HLfuvLw97kRKRTlRK+VErZQTtVJO1Eq5IpWqg/9arjyaqnu05UpuqbqHnT17lo4dOzJx4kS55crD/vrrL5KTkzl8+DCffvoplSpVokePHkDuLVfMxdypunUrFjL9qy+JuHZXfu2HKSNZvPD/8Kjz30J4SZL47rvvaNy4MV27dn3yQSUJ9c7DqG4eAZdc9qhKTwSdG7Xb9qW262svfA35TaRUlBO1Uk7USjlRK+VErZQTqbpcUnUAw4cP5/fff+f8+fO4ubnJWxFkyy39NmrUKCZNmiRPnB7l7u7O7du3ad26NSdOnCA+Pp5jx46ZpOri4+OZOHEie/bs4dKlS1hZWTF8+HC+/PJLnJycHnu95kzVzZv5FcM/mcDbNRyZMaQmlhqJfisusS/8Oj5+HTn5+yZK1m9PamoqkydPZv/+/WzevFnZeet0hegzkBwNDu6g+ne5W2YypN2D11qjdq/2Uu/tJFIqyolaKSdqpZyolXKiVsoVdKrOLC1XvvnmGzp06EBgYCDW1tbs3btXbrkye/ZskpKSaNq0KU2bNiUpKYnZs2fLx7h37x63bt2ievXqeHh45DjHw+m3Vq1aAcb028PrjB7l4+NDSkoKFSpU4OuvvwaMG18aDAY5VXfnzh3u3LnDrFmzeOedd/D29mbXrl0MGDAgL0ukWGxsLGM+n8Swt0rw6/9a0r5xVWqXK86hyS2pVNKeOwkZ1G7RmYC3/SlTpgwzZ86Ux65I+begyXDQWkH8FWNblnuXjI2CyzeDZv97qSdNgiAIgmAOhSpVd/bsWfbu3UvHjh1p164dWVlZREdHE/vQjtjLli2jffv2+Pr6Ymtry/Xr15k1a5a8pgpypuqqVatG27ZtOXr0KK6urgDMmDGD7t27U6qUcaPHmjVr8uWXX+Lp6UlWVhaWlpYMGjSIrVu3otPp8rJMiqz6aSEqSWLiO1VQaf6bBZcpZsvZr9vS5XUP4pMzkFITCAoK4uLFi3z88cfPdpJa70LXFdBkJNR6D+r3hYC50H4m2Djn5eUIgiAIQpFQaFN12Tw8PChXrhzXrl0DjHeXxo0bx9WrV8nKysLW1pavv/6aDz74QP7O5cuXiYyMJCQkBF9fXwB+/vlneRE6GNuvLFy40GT87du35/r16/LvQ0JCjEV6QmsXc6Xq/jl/liolrXFxdsJgMMh99yRJQqNW0b95RTYej2Lep70p07y/fM5nZlMCanU3fU1vMP56SYmUinKiVsqJWiknaqWcqJVyhSVVp5Ky/0bOQ02aNKFr166MGDECnU6Hh4cH69evx9fXV07V1ahRA4CIiAiTCU22SZMmsWXLFsLDwx97nuz025YtW0xev337Ni1btmTFihXyBC3btWvXKF++PKdOnaJu3bqPPXZcXBz169enV69eTJ069bGfmzRpUq6putWrV79Qqu6XFYvZs/s3/h5fB5VlzoTcyrDb/G/TZeaP68fZ+9ZotVrq1Kkj31HLK1p9Ks6p11BLOlIti5NsVUo8whMEQRCKnNTUVHr27EliYuITw12FNlX3IkqXLs2FCxee+/sPHjzA39+f6tWrm2yPkBtzperKli3Lmk3b2X32Hr3blEfCuO6pRIkSZOklloQew8lGy5BpS1GpVMY7URoN3bp1Y/78+U/cjkARgw71qZWozm1GlRIHkgHJ0hbJvQ4GnxHg4vVixzcjkVJRTtRKOVEr5UStlBO1Uk6k6p6Qqjt48CDh4eFYWlrmOP7DqbqIiAjTjR6fQJIkJk6cyIIFCwD44IMPWLVqFa+99l/cfurUqfz6668cP34clUpFcnLyU//PMVeqztvbm24Bfny4bh9pOni/ubFv3Lmb9xm18iSRd9PwdC/G8jVLad++PWlpaaxYsYJPP/2UmJgYdu/ejVr9AkvYQr+H8NVgYQMuZUGlQZWRBDcPodl717gWyjHn4v3CRKRUlBO1Uk7USjlRK+VErZQTqbpHUnUA/fv3p2bNmrme4+FUXW6pu8cJDg5m7ty58mM3Gxsb2rRpQ3r6fxtAJiUlcffuXUqVKoWdnR3W1tbPUYW8s2zdr3QN8GPIuuu4DdtNnYkHqf35Hxy+moSttSVHjp+hQ4cOaLVaHBwcGDJkCOvWreP333/n999/f/4Tx1+Fc1vB2tG4VYFaa3w8Z+1ovNN07zJE5NyUVBAEQRCKujy94/Rwqm7ixIkcP34cnU5nkqobMmQIfn5+8sToxx9/ZPDgwfIxhg8fTnJyMkuXLkWSJHmNU/Xq1bG0tMTOzo5hw4aRmZmJWq0mMzNT/kz2mqVH1zhJksS3335Lv379KFOmDAB9+vThgw8+YNmyZQwePJgHDx4QEhKCo6MjvXr14quvvpJ3FS9RosRjm/yas+WKRqNh8dptfH4pki3L53Pln3O81cSHsd+s4J1OnXF1c8txjpYtW1KjRg2WL19O8+bNn+u8qsshqDOSwNkrl5YsarCwg8jf0Nfrb+xtV8iIxZbKiVopJ2qlnKiVcqJWyhXJxeEBAQEYDAa6dOnCggULOHbsGNu3b5dTdY0bN+b06dM4OzvnmqoD8PX15c8//8xx7KtXr+Ll5QWAl5eXSfotW/alhIaG8uabbzJ79mxGjhzJlStXqFixYq5jbtiwIUeOHCEkJOSxE42Hz/0ocy0Of5J3332Xfv36yW1rHjVjxgzS09Ofuj7rcSrG/Ea5uBBSrHJ/DGqhS0aFRFilT9Frcj6mFARBEISXTYEsDn/RXnXw3xYAT0rVZW9N8LhUXfny5alSpQpvvPEGgHzn6M6dOyaP97p27Sr3fPP19ZUnXsuWLWPkyJEkJCQ89ZrN3XIFICEhgRUrVrBr129U8nCihLMdmbf/xr9KF6Ryb4D2v0eKBoOB0aNH06xZM9q3b/9c51P9nYz64HHsnF3/21H8YQ+ywMGDNm93zP39AiYWWyonaqWcqJVyolbKiVopV2QXhxeFVN2zMGfLFTDubdW3b18yMjKoUcqOa6cziIpLZ8Vvh+n/2gjealgHmn8OHrUBWLFiBVeuXGHVqlXPf/5KLeDkUkiNM65xepg+E/QZUO1t1JaF+26TWGypnKiVcqJWyolaKSdqpVyRWhwOpqk6lUqFWq1mwYIFbNy4kcTEREaPHo2Dg4O8c7iDg4PJHZsbN27g7+/P1KlTOXv2LGPHjjXZuTs0NJQmTZpQvHhxVq5cyb59+3IsLn9Udj+6AQMG4OjoiLOzMwMGDODOnTvyeyEhIXTs2BEPDw8++OADkpKS+Pnnn/O6PM/k0KFDdO/enbf923P9h/f4a3BJLkz3ZfuYpmhUKlrO+4c5Gw9x7efRnD30O5988gn9+/enV69eNG7c+PlP7OgB9foYJ0kJNyAzFXSZkBIH96+De22o3jHvLlQQBEEQXhKFKlWn1+vx9/cnMzOTAQMGUK5cOZYtW8YXX3whn8POzo6hQ4dy4MABOnXqROXKlRk/fnyOXcAfVr58eaysrAgPD2fv3r1s376dkJAQDh06hI+PDwBhYWHUrl2bjRs38uWXX2JpaUnv3r3Zvn17XpbomQQHB1O1alVWTQnCI+MyaRbFUFnZ4+9dik2j3kBnkBiz5Rblx+6j1ht+LFq0iHHjxrF06VL5EeRz8+4FvuPApbyxf11ytPGxXK33jC1ZbIvlzUUKgiAIwkukUKXq9uzZQ0REBHPmzGH9+vVotVqCgoL47rvv+Oyzz7C3t8fb2xsrKysyMzPJzMzE0dGRRo0asXXrVoKCgoCcqboLFy6QkZFBcnIyd+/epXz58pQsWZIrV67Ii9Q/++wzbty4QXx8POnp6Wi1Wl5//XUWLVqEr6/vYzeUNFeqTqfTsW3bNmbMmIHq9lEkQxYGtQOSJGEwGGhfx53qpR2pU9aJXt52WDqVpMH/tmJra4skSXmTOnitHVT0g7iLxsdzTp5gW5x/L/DFj28mIqWinKiVcqJWyolaKSdqpVxhSdUVql51hw4dwtbWllatWsnHnDZtGgB//vmnvKD80Z5yj1qzZg2RkZGkpqbKx3VycmL48OEEBQWRkJBAkyZNUKvVnD59mgoVKgDwxRdfsHz5cvk42Zt0Hj9+XO5596jp06fnmqrbs2fPC6XqMjIy0Ov13L59m8u2MXikpIKVg0nDYydrFenp6fiUdSFLmykvrDefO2Y+ft7au3dvQQ/hpSFqpZyolXKiVsqJWilnrlplzxmeplCl6qKjo2nSpAm7d+82uRA7OzuTXbCvXbtGmTJliI2NRafTMWnSJCZMmCC/X7FiRapUqSJPdqKjoylZsiRTpkxhypQp8ufc3NzkxB0Y03TLli0DYN26dbz//vucPHlS7quXG3Ol6iRJonz58sTFxVGhRwvUh86TopMo4eaGSqXifkom4TeTGd+xGk42Wv5M9WTt2rVERERga2tLx44d6devH8WLF3/uMTzfwA2o7pxEdWkfJN0BG2ek8r5IZd8Abf4sJhcpFeVErZQTtVJO1Eo5USvlinyq7rPPPkOj0dC2bdtcU3WjRo0CjDPHh1N16enp+Pv7s3//fuzt7enZs6fJ8UNDQ/nf//5HcnIyYNyccsaMGVSqVIkePXoA0KlTJzp16mTyPb1eT2BgINu2bUOtVtOlSxce3sLq4VYu586dQ6VS8dNPPz1x0gTmTdUNHjyYCRMmENTzHZrYumB9LwYVboCKz9adRaeX6NeoGGO2/sPsP05SpUoVWrVqRWxsLJMnT+a7775jz5491K5d+4XGoZg+Cw58Axd2gC4DNJbGBeaX94FnI/CbAjbO+TMWRErlWYhaKSdqpZyolXKiVsoVdKrObL3qAgICANi5cydqtVruVZfbouXs19zc3Fi5ciVNmzYlLCyMqKgoAgMDgf+ScdmLw2vXro2dnR2hoaH079+fUaNGyROnR7m7u3P9+nXs7e3Zu3cvWVlZ9O3bl3v37snHzW7l0qZNG86fP0/NmjXp3bt3XpfnmQwfPpxdu3bh1ymQnu2b0sw2iYzTx/jpSAJHrj5gcU8v9oTfYvYf0cz97juGDhsm1zI6Opr27dsTEBDApUuX8ucP5JlfIGKLceG4U5n/Xs9Kg+sHIXQO+E0y/zgEQRAEwUzMkqqbNm0a1tbWbN26lTZt2jB06FA5Vefi4oKfn5/8HT8/P1xcXACwtLQkPT2d2bNnU7duXdq1a0e7du0AqFSpEmBsftujRw9q1KiBl5cXvXr1olKlSvIdqNy4ubmh0+n4+OOPadSoEU2bNqVfv35IkkS5cuUA44SsW7du/Pjjj7z++uuP3Sk8P1lbW7Nz506++OILfj/+D31/vs4Ha2/gYK1lz6i69O/cijknIODttxk2fLjJpNTd3Z0VK1Zw48YNeU8ts8pKN/av01iCtZPpexY2YFMMrh6AhJvmH4sgCIIgmIlZUnUODg7UqFGDgIAAVCoVI0eOpHPnzixZsoRjx47RokWLXBeHZ2ZmYm1tzccff0xwcDDR0dHyeqdLly7h7e3N999/T9myZalatSoAq1at4sKFC/IEC2DYsGHMnz9ffhQXExODVqtl9uzZVKlShaysLJYvX45KpeL69evUq1eP/fv38/bbbzNixAguX75MYmIi0dHRWFpaUqzY46P35uxVB8Z+dWPHjmX48OFs3ryZNm3a4GJvDQYdsSlZhJ93Z9SnE3M9V5UqVahRowb79u3L8egyz8VeQpMUDdbOufS3A6wcUSVcQ3/nNJKde87385BIqSgnaqWcqJVyolbKiVopV6RTdWvWrMmxOLx8+fLMnDmTadOm8euvv+a6ODwmJoYGDRqg0Wjw8fHBzs6OwMBA5s6dKy/iNhgMjBs3jnPnzskTo7fffputW7c+dlzR0dGUK1eOqlWr0rJlS3mN0/379+XjLl++nNTUVKZPny5/z8PDg2bNmj0xrWauVN2jDHo9ttYWHAoLg3/vLCUlJQFw5swZnJyccv1eSkoK169fZ+fOnXk2ltw4pN2ifuIDMlP06NW53P2TJOwyk4k4fpy7F/VmHUs2kVJRTtRKOVEr5UStlBO1Uq6gU3V52uQXjIvDa9asye3bt3FzcwNg6NChJCYmsnLlSr799lsGDRokt1zp0qULixYtYvTo0QQFBXH9+vVcU3U7d+40uat09epVkpOTOXz4MJ9++inz589/7BqnadOmsXz5ciIjI01ed3NzY/LkyXz44Ycmrz+uB15ucrvj5OnpSVxcXJ70qjt1NIxvpnzKlj+OkqkzUKGELYPe9eOjz4KxdvOibt26VKlShXXr1uX4bmRkJLVq1WLZsmU5Ftnnuaw0NOvfh9R74OCR8/20BDBkou+0GFy8zDsUkVJRTNRKOVEr5UStlBO1Ui4/UnWurq752+QXTFuu6PV6VCoVKpVKXhyeHd3P3iOpb9++8mvu7u4cPHjQJFXXsWNH+T2ATZs2sWDBAsLDw43922rU4O2332bSpElPXBweExMDGCc6jRo14vTp02g0Gvm4165do3z58ibfU6lUHDp06IntS8yZqtu5dQOd3u1GORcLpviXxt5KxdEb6Uxc+Cs7/whl1579jBw5kg8++ICff/6ZPn36yOuc7t+/z6BBg/Dw8KB79+7m/wNpYQE13oFD30NWClg5/PeeLh3S70HldqjdXjPvOEyGJFIqSolaKSdqpZyolXKiVsoVqVTdwy1XQkNDsbW1ZdOmTWzfvp2goCDWrFlDWloaAwcOpGnTpoDxcdPixYsZNWoUDRs25Msvv8TV1VVO1XXt2hUrKyuqV68OwIEDB/Dz82PatGk4OzuzdOlSvv76a0qWLPnYcfn4+JCQkMCJEydYsWIFpUqV4vTp0xgMBho1amTy2d9//52FCxeSmJjIsmXL8n8fpH+lpKQQ+H5v2lR1YMPIN9FaWRMTE8OHAW4MvhhHy+l/MuPjPkxae4xjx47Rr18/5s+fj5+fHzExMfLO67t37851YmcWdXtC/FW4tAeSY8HCytjjDqB0A2g6+snfFwRBEIRCLk9TdQ+3XNm7dy8TJkygQ4cOJi1XslN12U1+H07VyYNSq+UGwWDcDDL7Tsprr71GtWrVcHZ2BoybXWa/nm3z5s3y4nGAatWqyftJbd26VX5s1aZNG0qVKmVy7ri4ONLS0sjIyCA6OpqIiIi8LJFiv6xaTmJyGvN6VMHSxnStlE8VN/q/WZaFe85iuH2KhQsXsmPHDkqVKsUvv/zCkSNHGDlyJGfPnqVBgwb5N2itFbT8AtoFQ+XWULwSeDWFVhPh7W/BrmAmoYIgCIKQVwpVy5WjR49SrVo1bGxs5MXh3bt3Z/HixURERODt7S0vDr969SparZaKFSvi5OREly5d5HHs2LEjx3qm2bNnU69ePVQqFR999BGAyW7j2bp37y7/s7e3NwBPWgZmrlTdiaMHqeFhi6eHKwaDQR5Ddq+6tt6l+f6P69yKPElpjzr4+fmZbPOQrUCSGmV8jL9yDiZfTi9SKsqJWiknaqWcqJVyolbKFclUXV60XPH09DRJgKWmprJ48WI5/TZs2DCGDRsmvx8cHMyMGTNMJjz+/v7yGiowTjZGjRrFZ599xvjx4+X1TA+n3uzt7fnmm2/kHnYbN24kODj4qQvEzZWqi4mNIz4li3uxMWSpbbgQ9YC09Ey8EpMp7mTP9ag4ACL/ucjpVPMm5l5WIqWinKiVcqJWyolaKSdqpVxBp+rM1nIle9NFrVaba8uV7FTdnDlzTFquPIvVq1czefJktm7dKif4IGfLlXnz5pGUlMS4ceMeeyxXV1eTnnMNGjTgzp07zJw5kw4dOjz2e+bqVedgb8eGbXv4evd1tp55wKU4410tjRo61rAnKlnCp4IjLXoMBwfz7ov0shEpFeVErZQTtVJO1Eo5USvlimyvuvxK1R05coSkpCSqVKmCXv/kfYH++OMPwsLC0GpNL/f1118nMDCQ5cuXm7x+79496tSpw+3bt5+46BzMl6pr3qIl5Txc+eaPWHy9tCwIKI6rnZp9VzKZ9HsiyZmwZIgvFsU8n/scRZ1IqSgnaqWcqJVyolbKiVopJ1J1z5GqK1GiBJmZmfzwww/cvHmTgIAAjhw5Iq9JetTcuXPx8PDAwcGBu3fvsmHDBlJTU/nll19ypOoABgwYQO3atRVNnMwlNjaWO7HxlLTXEHJNR+yOREraqTh2R0daFjhYqjh09ir9s9LBwrpAxigIgiAIr5qXLlXXsGFD1q9fz7fffkunTp0YPnw45cuXZ/369fL3H03VlS1blgULFhAcHEzz5s3RaDSAMZFXpoyxGe3y5ctZs2YNEydO5M6dO3h4GDdxDAoKyssSKbbyp4VoVPD3pMbsGNWIBhVccLKzZlQLD67O9GWsfxVWH7pJ2sU/C2R8giAIgvAqeulSdQsXLkSn0zFkyBCGDBkin3vfvn3yP+eWqlNi/PjxXL16FXt7e7mdSWBg4BO/Y65U3ZWLkVQqYU1xF0falrSjjXcZYmNjKVGiBCqVitcr6UjNvMCdq5GUfa3Fc5+nKBIpFeVErZQTtVJO1Eo5USvlRKruOVN1j/aNy07VZZ8bcqbqHqVWq3NsMdC9e3e+/fZbVqxYQa9evQgJCaF58+ZPvWZzpeoSHiRz634G0dFRqK3/W2R+9vIt9p6L588L8aiAy9dvc/YxfejUhkxcUq5goU8hU2vPfduKSOo8X9ZWaImUinKiVsqJWiknaqWcqJVyIlWXD6k6JcaNG0e1atXkCd+zfM8cqbqKFSuyesMWtp25xyD/imToDHy0+DCrjkRjMEhIgAR8OPMXlixtR5MmTUy+r/pnF+oTa1A9uAWSAVQaJMkTQ4MPkCr4Pve4XgYipaKcqJVyolbKiVopJ2qlnEjV5WOqDmDq1Kns2LGD48eP53o7bu/evZw9e5ZffvnF5HVXV1c+//zzXO8qgflSdTVr1qRP1w4M37iN5Aw4dkfH5hPRfNSiPKev3ePw1Qcs+Kw/y0Iu0r59e8LCwqhbt67xy//sgb9mgiELHEuD1hJ06agSb6L+cxpYWkH5t557bC8LkVJRTtRKOVEr5UStlBO1Uq6gU3V5ujj84VRdhw4dCAwMxNramr1791KqVCnWrFnD7NmzSUpKomnTpjRt2pSkpCRmz54NGBd+nzt3juTkZMLCwli+fDlr1659Yqquc+fOBAQEcOrUqSeOLTMzk/fee48WLXJfD7R8+XLGjx/PmjVr2L17N2PGjAGgRYsWJmup8tPClevp370z//v1Fr8cjUKtgrl7r3DlXgY75n1Cv4kL2bVrF2XLluWrr74yfkmXCSd+An0mOJc1TpoAtNbgXA4yk+HEMjAYCuSaBEEQBOFllqd3nB5O1U2cOJHjx4+j0+lMUnVDhgzBz8+PmjVrAvDjjz8yePBgk+M8LVXXp08fvvvuO/lx3MaNG1m/fr28HcHmzZsZN24cFy5ckI85YMAA4uPjOXDgAADh4eEAVKpUCXt7e+rVq0e9evXkz1taWjJr1iwiIiJMHgM+ylyLwwFUKhVzf1qDxnEEy5YupY+/Dy1936Rdz4/Q2hcjS69Hq9XywQcfMHbsWO7fv49D4j9o4q8h2ZXIfXJkWwJiI9FHnQW3ai80vsJKLLZUTtRKOVEr5UStlBO1Uq5ILg4vzKm6L774wmSjy+xJ1v79+/H19c1xLXFxxpYmj64depS5Foc/7PKVq5T0KEXrXiOMxz5w2OT9+Ph49Ho9mzdvpoplNLUfJJCSbgmqnM9rVZIem6z7hIfs4b791TwZX2ElFlsqJ2qlnKiVcqJWyolaKVfQi8NV0pM62D6nJk2a0LVrV0aMGIFOp8PDw4P169fj6+srp+pq1KgBQEREhJyqCwoK4vr16+zevdvkQuzs7Ni5cyft2rXLca7sVN2FCxfkO0O53XHKtmzZMkaOHElCQkKuY+/Rowdbt24lLS2NgIAA1q1bh7X14zeYzO2Ok6enJ3FxcS+0OPxhU6dOZfr06TRq1IgypUvhW7MMPRq5Y2ttgeRahckr/2T2d/OIiorCOvEymm1DwMoJLO1yHiz9AejS0HdeDC7l82R8hY1YbKmcqJVyolbKiVopJ2qlXH4sDnd1dSUxMfGJf3+LVN0jZs+ezcSJE/nnn3/kxNwPP/zw2M+ba3F4tiNHjjB//nwyMzM5d/YMmVHnWftLHBPstWwdWJGyxa1ZOP8CgZ074ODgAPZ1oGQNuH0SrCrAv484AWO6Li0OvN5EXeI10/eKILHYUjlRK+VErZQTtVJO1Eq5IrU4HExTddnrlBYsWMDGjRtJTExk9OjRODg4yDuHOzg4mKTqbt26hb+/P7a2tri5uTFixAj5PTCm6vz8/HB0dCQwMBBPT0/Fqbo33niDoKAgEhMTc/3M8OHD8ff3p06dOnzxxRf83//9HwsWLCAqKiqPqvNsoqKiaNeuHVWqVGHksI+4dz+RCo561nxYD09XB1rMv0jDbyKxVBv4on4SJMcaJ0ONPwQ7V4i/DGkJoEuHtPtw7zI4eECjD4r8pEkQBEEQzEGk6h7Rv39/unXrBoDh38XVDz+Ky0//93//R2ZmJtu2bWPmwBbM7VSSsOvpdP/hJCeu3icty4CDtQUHJ7aitDoWLv373LeUN7SfCRWaG9N1KXGg10Hl1uD/TZFdFC4IgiAI5iZSdf+m6nbu3Im3tzcNGjTg4sWLPHjwgMGDB9OkSRO8vLwee83mTNVt3bqVTp064eDggHQ9jD4NXPigYxPCryeQnKFjwd7LXLybTBlXOwwJGqTLIRhqvGf8cvGq0Ho6PLhtvOtkUwwcjf33KOLpDZFSUU7USjlRK+VErZQTtVKusKTq8nRxeEBAAAaDgS5durBgwQKOHTvG9u3b5VRd48aNOX36NM7Ozrmm6r744gs2bNiAl5cXISEh2NnZ8c4777B48WJOnjyJt7c3vr6+/Plnzsa2DRs25MiRIwAMHDiQJUuWmLRV6du3r0mqLlt2qm7//v18/vnnnDt3jpSUFNRqNaNGjeLTTz/F2dn5sdc8adKkXFN1q1evfuFU3dChQ/H29mbAgAHUufETLimXSLN0ld+fuPUy+87HE/ppA6wz40m2dudE+aEvdE5BEARBeBWlpqbSs2fPpy4OF6m6XEyaNIktW7bId6WexJypusDAQE6dOkWvt99i66YNJKWkUM3dhiBfL9o2qEjtz/6gRhknfhnaCFXCVQzVO2N465MXOmdRIFIqyolaKSdqpZyolXKiVsoV+VTdZ599hkajoW3btrmm6kaNGgUY92N4OFWXnp5u0nKlZ8+eJsfPbrkSHh5OcnIymZmZfPXVV09N1cXHxzNs2DA2bdpEeno6AwYM4LvvvsPe3h7I/c6RSqXC1taWlJSUx16vOVN1bVu3Yv369Uyde5lu3o64lbEg5Go6Ad+fpVHZS5y/k873feujTo8HSzs01dqjEX/wZCKlopyolXKiVsqJWiknaqVckU3VBQQEIEkSO3fuNEnVqXJJc2W/5ubmxtGjR8nMzJQXh69YsQL4L1V34MAB/Pz8GDlyJABdunRh4sSJT10cHhgYSEREBGPGjMHe3p4DBw4QFBQkvz9mzBiioqKIiori448/pkaNGlSvXp333nsvL8ryzHQ6HV9OHI+bvZYsg0R0hhVe7sUY3MiOmm5ajtxIp2UlG5p7JBvbrNTrCx51C2SsgiAIgvCqMEuqbtq0aVhbW7N161batGnD0KFD5VSdi4sLfn5+8nf8/PxwcXEBjG1O0tPTmT17NnXr1qVdu3by47lKlSoBxn2fPD09+eqrr1i7di3r1q3jtddeY9u2bY8d1/nz59m1axeLFy+mYsWKaDQa5s2bx9q1a7lz5w4A9vb2uLu74+7ujr29PVlZWZw7d44BAwbkZYkU+3XzJq7diWX3sOqsGdqYpDQdwzfdIWhLIrbWFvh4WnA9PgOpZG1oOw1e7ye2GBAEQRAEMzNLqs7BwYEaNWoQEBCASqVi5MiRdO7cmSVLlnDs2DFatGiR6+LwzMxMrK2t+fjjjwkODiY6Olpe73Tp0iW8vb1ZvXq1nKpr1KgRd+7cISEhARsbG3kcw4YNY/78+fLi8EOHDuHo6IhWq+XGjRvo9XpcXV1RqVSEhITIjwMvXbpEcnIy0dHRxMTEULZsWRwcHMjMzMTS0jLXazZXqi5k73Yqu1lTu1Jpalva8V7D0ty8c5cSrq7YWGnZfPQm7847ws1ib+BRxgd0uuc+V1EjUirKiVopJ2qlnKiVcqJWyhWWVJ1ZetWtWbOGXr16AdC2bVsSExMpX748M2fOZNq0afz666/4+/sD0LVrV3lxeExMDA0aNECj0ci96gIDA5k7dy7R0dEAj+1Vd+LEiceOK/u72dsVADRo0ACAY8eOyROngQMHmiT2EhIS8Pb25urVq4/dksBcvepu3bqN3mDg3r176DUpZOoMZOh0JN6PI0mtJuHfCdrZs39zKnnnc5+nKBO9n5QTtVJO1Eo5USvlRK2UK+hedXk6cdq2bRuRkZHUrFkzR8uVsLAwJEni22+/fWLLFRsbG3bu/G8ikJqayty5c+Xfh4SEyP+8evVqBg0axNatW2nVqpX8+rx585g3b57J2Nzd3XPsGO7m5kblypVzHHvNmjX07t2bW7duUbJkySdec3ZblmzZqbrWrVu/UKouKyONzb/9wZ5z8Wz5O5Etp2LRGaCEnZoBPsW5EKOjSkkbWnX7AFXxSs99nqJIpFSUE7VSTtRKOVEr5UStlMuPVJ0SeZ6qe7jlil6vR6VSoVKpsLKyYv78+fIkIzQ0FDDur/Rwy5WDBw+apOo6duwovwf/peqOHDlCUlISVapUeWrLFXd3d+7evUtgYCDbtm1DrVbTqVMn4uPj5eOCcaPNb775hi+++AK9Xk+9evX46KOP+Pzzzx97bHOl6t7p/C4erh/y/rJLlHdRM721A6UdNRy8kcXs/bFk6GFWz1pYuotdwB9HpFSUE7VSTtRKOVEr5UStlCvoVF2eTpwebrkSGhqKra0tmzZtYvv27QQFBbFmzRrS0tIYOHAgTZs2BSApKYnFixczatQoGjZsyJdffomrqythYWFERUXRtWvXJ7ZcuXnzJgEBARw5csTkUdzDfHx8SExM5NixY+zdu5esrCy6deuGXq+nUaNG8udGjBjB9u3bSU9PZ+HChXh7exMfH5+XJVJMr9eTqTNgoYHbDwwcv53FjQQdB65mkaEHSw1cuhkLCTfAuWyBjFEQBEEQXjV5mqp7uOXK3r17mTBhAh06dDBpuZKdqstu8vtwqk4e1FNarqxfv55vv/2WTp06MXz4cMqXL8/69evl72/evJmqVavmvNh/j5v962Hnz59nwYIFtG3bFg8PD/r160f9+vVNEoD5acuWLdxLeMD+oa8x5Z3XuJKoZu9lHa+52bJnRG0+8a/MqqMxJJ/ZXiDjEwRBEIRXkVkWh+/evZuqVatSpUoVevXqJbdcCQ4Opl69eqxbty7XVN3Ro0epVq0aNjY28uLw7t27s3jxYiIiIvD29n7s4vB9+/bJ/7xjxw4iIyPl32en6urVq0fLli3lR3UrV67kyJEjdOrUiW3btlG+fHlWr14NQMWKFWnVqhXBwcEUK1bssddsrlRdeHg4ZYrZ0LhqSRq/7s7HHWsTGxtLiRIlUKlU2DjG8dWv/3Dl3Cmq+Yg0xsNESkU5USvlRK2UE7VSTtRKuSKZqsveS6lJkyY5UnVpaWlIkiS3XMktVRcdHY2np2eOxeGLFy+Wk3EPLw6H/1quPLyPk7+/v7yGCoypOnd3d3lSlG3nzp3yca9cucKNGzeoW7cuM2fORK/XM2rUKN59913++OOPx16zuVJ1N2/eJDE1k3tx99Cn/ndj8O9Lt/jnbipnbiUBEBMbx9Wdj6TqJAP2GXdRGzJJt3Ah0+LFWr+8rERKRTlRK+VErZQTtVJO1Eq5IpWqg/9arjyaqnu05crjUnXPYvXq1UyePJmtW7c+teXK0xgMBjIyMlixYoWctFuyZAn169cnMjKSKlWq5Po9c6XqypUrx88//8yuf1IJ9HPlZnwaHy45yu6z9zD8211Qq4ZTySUY0a6d8dGjJKG68gfq06sh/goY9GBph1TeF0P9vmD/5IRgUSFSKsqJWiknaqWcqJVyolbKiVRdIUvVZW+gmdsE6caNG4+dOJkrVVe3bl06+rdh6IZ96A0qJv4WjU5vILhHbS7cus/iAzd5s5o7nwQv4p6qGDNmzICzmyB0Nugzwc4V1BaQkQTnNqG5Fwn+34J9iece08tGpFSUE7VSTtRKOVEr5UStlCvoVJ1ZWq588803dOjQgcDAQKytrdm7d6/ccmX27NkkJSXRtGlTmjZtSlJSErNnzwaMC7/PnTtHcnKy3Ktu7dq1T0zVde7cmYCAgCf2qns0Vbd9+3b27NljkqqrX78+ACtWrJB71v3++++A8e5PQVixeh2NGzag38/XuHU/HXd7FZM2nmVp6E1m9WnEH2EnmD59OsHBwVw+ewKOLQIkcPECS3vQWhknUC5eEHMOzm4okOsQBEEQhKJCpOr+lb09wpw5c4iKiuL27dt8/vnn+Pn5mWySmZ8cHR3Z8fsB7OzsqFutEqXLlmPM++25FraVj5eEgmMphg8fjrOzM8vmfw0pcbk/jtNYgKUdRP4Guoyc7wuCIAiCoIhI1f2bqsuepJ0/f5769euj1Wp58803Wbt27ROv2Vypumz3798nJSWF0Z9Nwt7eXn62m2WQwJCFhYUF1apV4/qNm0g1QEINBkPOA2lsIP0B+uR4412oIkykVJQTtVJO1Eo5USvlRK2UE6m6Qpaqs7e355tvvqFJkyao1Wo2btxIcHAwoaGhdOjQ4bHXbK5UXTadTodWq+X7ObOoU86FM78tpYHPm2Q4VQSVCr1ez4ULFyjfoCLJyUmkZEaDKueNRKusRPRqCw7tD8Wgzr1hcVEjUirKiVopJ2qlnKiVcqJWyolUXSFJ1bm6upqk4xo0aMCdO3eYOXPmEydO5krVgTHp9/mnY9Hr9Rw6Hs6FCDX30wwUW7WDeUHNeG/c/7Fq+wHi4+MZMW4VdpEzsZMMYPfIAnDJgOp+EoZa79K26TsvNKaXgUipKCdqpZyolXKiVsqJWiknUnWFLFX3sEuXLuHt7Y1Op8PZ2fmJxzZXqg7gk7FjmD13PsPedGXp0XjKudowu11Vdp66ReDsfew76cfPh+/QvXt3GjRrB9Y34PhPkHLXOHlSaSAzBZKjwdkTTZ2uaF6hP5gipaKcqJVyolbKiVopJ2qlnEjVFZJUXbasrCx69OjBm2++iV6vx8PDIy9LpFhMTAxzvvuOie1L813f19n3mS+pmQb6LjzO5pN3Afjpz6v08fdh2bJlxi81GAiNPzIm6hJuGPdyykiE0g2gXTAUK18g1yIIgiAIRUWe3nF6OFU3ceJEjh8/jk6nM0nVDRkyBD8/P2rWrAnAjz/+yODBg02O87RUXZ8+ffjuu+/kx3EbN25k/fr1cpPfzZs3M27cOC5cuJDrcXNL1S1fvhxLS0v27duHh4cHlpaWZGVlMWzYsCdes7kWh69fvx7JYOCjN1wwWNhRz8uWkLH1uRCvIuLWAy5EJfH93suMfMMetVr937lq94TKb6OKCgddGpJjaXCrASoVvCKLD8ViS+VErZQTtVJO1Eo5USvliuTi8Jc5VQfw6aefcvPmTRwcHHB1dcXW1pZ+/fo98ZrNtTj88OHD2FlrsSKTmJgYAFQqFdWKQ7Xijpx30/D9Xrh69Qr/PNpyxcSNf3+9esRiS+VErZQTtVJO1Eo5USvlitTi8Jc5Vff2228zYcIEQkJCeOutt1i2bBkjR4586jWba3F4cnIyq1at4k6KGgd7B5YcuMbhyGgcrLX4V7PlQaoOlQpq1aiOe/v2z32eokgstlRO1Eo5USvlRK2UE7VSrsguDn9ZU3WDBg2iZ8+evPXWW8/0PXMtDu/SpQsjhg+j7+pbnLhxHq1Gg4+nJfcSdPQ+dhetGnzLafHUXYELW6HWu899rqJKLLZUTtRKOVEr5UStlBO1Uq5ILQ4H01Rd9jqlBQsWsHHjRhITExk9ejQODg7yzuEODg4mqbpbt27h7++Pra0tbm5ujBgxQn4PjKk6Pz8/HB0dCQwMxNPT85lSdY6Ojjg7O9OvXz+TVN2ePXsIDg6W1z/169ePxMREtFotP/30U16X6amsra0ZOWo0h68mUczWgoWdXJjpZ0m/enaUddIgSfDPfUiXLOHgd3AlJN/HKAiCIAivmjy94/Rwqi40NBRbW1s2bdrE9u3bCQoKYs2aNaSlpTFw4EC5xUlSUhKLFy9m1KhRNGzYkC+//BJXV1fCwsKIioqia9euT0zV3bx5k4CAAI4cOSIvDn/Uo6m6rKwsunXrZpKqGzhwIGlpabz55psUL16c+fPns3PnTpNF6Pnt9OnTeHp64man4v1fjOuU1Crwr2rLjz09ab8gknXnDfSukQFn1kP5ZsZF4IIgCIIgmIVI1f1rzpw5Jr+/e/cue/bs4cSJEyaL0B9lrlSdJEns2LGDzz//nE/aV+TyhilcTVRRq7wbpUq4gFrDG7/Hse3kHXrVrwZ3I9DfvwUOOfeletWIlIpyolbKiVopJ2qlnKiVciJVVwhTdY+SJIlixYo98ZrNlaqTJImMjAxu3rzJmfBEKtsbcC5eEjAQE3cPAGuNgaSUNOLvJ6AxZHB0317SLYs/9zmLGpFSUU7USjlRK+VErZQTtVJOpOoKSaruUba2tmg0mqduR2DOlit169bl+vXrnHmtPqOW3OZy7GWK2WroXteOnq+X4MjVB3zcvjLF7LTg4EmLgG6geTX60D2JSKkoJ2qlnKiVcqJWyolaKVfkU3WfffYZGo2Gtm3b5pqqGzVqFGCcOT6cqktPTzdpudKzZ0+T40dFRfHxxx9z/PhxLl68iFar5bfffntqqk6SJIYMGcLatWvJyMigTZs2GAwG+f3Tp08zY8YMQkNDuXv3Ljqdjh49elCjRo0nXq85W64EBQUxePBgdu3aRavXbOlfV8v1RPhybzzT98WTqYegWgbU+kyo3gG1td0Lna+oESkV5UStlBO1Uk7USjlRK+WKbKouICAASZLYuXOnSaru0bVFgPyam5sbR48eJTMzU265smLFCuC/VF1GRgYlSpSgVatWqFQq2rdvT6tWrZ44Jnd3d65fv862bdtYv349f/75J7dv3+bevXvycU+cOIGbmxtjxozBwsKCvn37snnzZubPn5+X5Xkmly9f/nddFthYanB3tqKWhwVeLlpSssDDQU0pTRw4eULtbgU2TkEQBEF4VZilV920adOwtrZm69attGnThqFDh8q96lxcXPDz85O/4+fnh4uLCwCWlpakp6cze/Zs6tatS7t27WjXrh0AlSpVAsDLy4vGjRuzdOlSqlevTvnyT++/VrNmTTIzMxkyZAgtWrSgfv36DBo0CDDuMwXQv39/OnXqxOeff05wcDA//fQT/fr1Y9OmTXlZIsXS0tJYtGgRowYFsiiwEreSVAz9NZHP9yZTraQl37Z35kaigdAYe+PjOXWe3zwUBEEQBOERZknVOTg4UKNGDQICAlCpVIwcOZLOnTuzZMkSjh07RosWLXJdHJ6ZmYm1tTUff/wxwcHBREdHs3v3bgAuXbqEt7c3q1evllN1q1atIiUlhejoaGxsbHBycgLgyy+/5IsvvuDq1at4eXmRnJwMGDfMbN68OVlZWXz99dfY2tpy6dIlAPbv38/bb7/NiBEj6NKlC9HR0URHR2Nvb//EazZXqu7vv/8mISGBzk1eo3HCOfr61SY6JpaSbiVQq1QYDBKTQ7YRGmVJk6Qo9Am3wLH0c5+vKBEpFeVErZQTtVJO1Eo5USvlinSqbs2aNTkWh5cvX56ZM2cybdo0fv3111wXh8fExNCgQQM0Go2cqgsMDGTu3LnyIu6HU3VgTMwtXryYPn36sGzZMpOLz35eGR0djYWFBTVq1JBTdV26dOH06dPycZcvX05qairTp09n+vTp8jXVrl37iddsrlTdlStXADh/IZJa9smkZMaiUauIi4sDQG+Q0OsNpKenkpiYyNE/9pNu+eQE4KtGpFSUe2ytJAmtIR2Q0KltxD5hiJ+rZyFqpZzSWkmSRHJyMnq9HkdHR3nbnldFhh62/rYXa41xX8O8pDRVp5IkScrLE0dGRlKzZk1u374tL9geOnQoiYmJrFy5km+//ZZBgwbJLVe6dOnCokWLGD16NEFBQVy/fl2+y5R9IXZ2duzcuVN+bJfN19eXunXr5tiD6VGrV6+mX79+JneGwLgnVPPmzfn6669NXj979izNmzdnxIgRjB8//onHzu2Ok6enJ3FxcS+UqsvMzKRChQq869+SeQ1vImltiX2QTokSJVCpVGw9cYfOc8I4MrY6r9evj/6dhaDWPPf5ihKRUlHuSbVS3QhDdW4LqugzIEng4oWhagekym1fyZ818XOlnKiVcs9Sq19++YXZs2dz8uRJAMqXL8/gwYMZNmyYvOykqDpzK5FfT9/mz7M3cHRyxsPJmrY1StK6ekkstXkzeXzw4AGurq4kJiY+8e/vPK/0wy1X9Hq9vNmklZUV8+fPl6P72dsF9O3bV35NpVJx9OhReeLh5eXFe++9B/y3OPxhiYmJzJ07l5CQEMLDwx87Jnd3dzIzM3nvvffYvXu3fMcpe5sCMG5zMHv2bMLCwoiLi8PNzU3R+ilzpeosLCwYOnQokydP5q0SbXmv1G3UBmtUKhXn7yQxbPkp3nzNmYZeDlD7PdRW1s99rqJKpFSUy1GrvzdA2FzISgNrZ+N/2sVEoI45B/H/wJtj4BX7L91s4udKOVEr5Z5WqylTpjBx4kTatGnDzz//jI2NDVu2bOGzzz7j8OHDrF+/Ho2maP4HzR8X7vLd7xd5kJ6FBGg1Kq7eS+WHP69y4W4KY9pUwULz4v8+UvqzWqhartja2pKYmMjSpUupXbs2YWFh9O/fH2tra7nlSraEhAQuXLiAp6fnU8dVv359VCqVScuVwMBAbt68iY+PDwBhYWF4eHig1+sZNGgQNWrUoHfv3jg5OfH222/nZZkUGzduHOfOnaN78FqmexWjnpuB2w/OsTfyAVXdrFk7oDJ4vw9VC2Z8QhF1/zocXmD852IV/nvdxgXSEiBiC3g2ggrNCmJ0gvDKOXPmDBMnTmTKlClMmDBBfr1Tp068++67dOjQgZ9//pnevXsX4CjNIz4lkx9DrpChM1CumA2xsck42VjgYmtFcoaO/ZExeJd1oW3N/Ouakaf/yfhwy5W9e/cyYcIEOnToYNJyJTtVl93k9+FU3axZs6hRowYLFiwgKSmJEiVKoNVqcXNzM7mrEx4eTrdu3XBxccHJyYm0tDTOnTsnv3/06FGqVq3K7du3Abhz5468E3dqaio2NjbY2Rn3PMpemN6hQwc2bdqEv78/U6ZMoVu3bjRv3jzHppn5SavVsnr1anbt2kVF77cIi7FBZ12MRUNacnzlREr1WQyNPxLrToS8dWkvpCeAfcmc79k4gyETInfmfE8QBLP4v//7Pzw8PPj0009zvBcQEEDr1q358ccfC2Bk5nfgn1jupWTg7midYzsjeystkgS7I3LfyNpcClXLFY1Gw/bt2/nwww/lxeFeXl5UrVrV5DwPN/ONiooCoH379ly7dg2ATZs2ERkZKS8SP3ToEE5OTnTu3JkuXbqQkZFB69atiYyMlFuubNiwgdjYWFatWsWqVavk4z9tnZK5UnUPa9GiBW+++WaO5+BZADpdnpyjKBEpFeVyq5U67goqVCABkiHnl7S2EPsP+lesvuLnSjlRK+WU1CoiIoK33nrrsZ9r3rw506dPL5L1vhWfgsEgoVJJSAbjkmzJIGFQG//dZGup5vq9FNLSM9C+4OO6AknVvWjLFYBy5crJLVfCwsJo1qyZyeLvixcv4ubmxl9//UXlypWZNGkSW7ZsMVnj1KhRI6pUqYKXlxdgTNWVLFmS77//nu+//17+nJubm5yqmzRpEpMmTZLfW7duHe+//z5hYWFPvGZzpeoeJ69TKiqDDof026glHamWJci0eLE2MS9CkiSuXbtGbGwsDg4OVK5cOddn9gYJotMgUw9OluCSc4kZIBI9z+LhWlWJuk3p5GRSsmJy/axNZjwpaRYc2/lq3nUSP1fKiVop96RapaSkcO7cOZN2ZA87fPgwGo3mse+/zC5HqUhJURNjSJZfi42Llf85MRNsNLB7164XfvhSIL3q4L+WK5s3bzaeQKvNteVKdqpuzpw5Ji1Xsp09e5aOHTsyceJEWrduDYBer6dnz55MnjyZypUrP3YMubVceRb79++nX79+LFq06KktV8zZq+5heZ5SkSRU57eg/ns9PLiNyqBHsrJH8noLQ4NBYFfixc/xDA4dOsSoUaPktAgYEyOTJ0+me/fu8muhl+6x7sQtrsWlojMYsLbQUK+sM70bl6VsMeNEVSR6lMutVqortmj2nsfO3hG0j4QODHpISMK+UXfa12tfACMuOOLnSjlRK+WU1Oru3bsMHjyYihUrUqVKFZP3UlJSCAoKokePHrRvX/T+TJa6mcD5reews9Fia6EhNi6WEq4lUKlVGCSJ1HtpdKxXGv+3nh7mepoC61X3Iqk6gBs3btCrVy/++usvebG4TqdDq9WSlJTE8ePHOXHiBB9++KHphWi17NmzhxYtWuS8SK2Wa9euUb58eaKjoylVqhQ9e/YkPj4+R6ouNDSU+Ph4ypQpoyihYM5edbnJs+Me+wmOLQJUYOcKag2q9AdwfiuahGvg/w3Y5s++UIcPH6ZNmzbUqVOHbdu20aBBAy5dusQ333xD79690ev19O3bl73n7vLdvotkZBlwtbfEQqMmJUPPgYv3uHovjanv1MSz2H93+USiRzmTWlV8CyLqoLp9EhzcwcLOuI5Olw6Jt8GlHFQPQPOK1lb8XCknaqXck2rVq1cvgoOD6dSpEytXrqRRo0aoVCouXbrEBx98QGpqKqNGjSqSta7v5Up9r2KEXb6Hq51xZxSVWoVOD1GJ6bg5WvN2ndJ5cu0vZapOr9fTsmVLbty4QZ8+fejWrRu9e/fGwsKCadOm4ejoSGBgIG5ubjRs2BAHBwcmTJjAqVOnWLNmDY0aNcp1XM7OzmRmZjJmzBjatWvH2bNn5b+Qs78TFhaGo6MjaWlpTJw4ERcXlwJP1ZlN4i0I/9l4N8H+v+bI2LmCtSNE/w3nt0H9PvkynLFjx1KzZk1CQkKwtjbe4ShZsiRvvPEGffr0YcyYMXTo/C7Lw66SpZPkO0sAzrZqHKy1XL+XwvoTNxntV+VxpxGU0lqB31ewbwpEhUPSXePESaWGEpWh+XjjhEoQhHxha2vLnj17CAgIwMfHh0qVKmFjY8Pff/9NiRIl2LFjh9yWrKhRq1WMbVOFb/f+w7Fr8dxLV5Een4ZapaJMMVtGtaqMl2v+Nrg3S8uVbt26MXHiRI4fP45OpzNJ1Q0ZMgQ/Pz9q1qwJwI8//sjgwYMB467gly5d4t1332XGjBkAjBkzhq+++opJkyZhaWlpsnAb4NixY5w7d47z58/Lez5t3ryZcePGceHCBQCCgoLYvHkzS5YsoUGDBhQvXhwLCwvs7OwoVaoUAD4+PkydOpWRI0fK49m2bRtr1qwpehOnK39CeiIUy+XWpsbSOKG6sB3q9TZ7Yu/ixYuEhoayfv16edKUTaVSMWHCBFauXMm8pb8Qra9EKaec+1Vp1CqcbC04ePEeA5pkYVv0/qMr/zmUhA7zIOoURJ0BSQ/FK0HZN0BrWdCjE4RXToUKFThz5gy7du1i9+7d6HQ6Pv74Y7p27YqNjU1BD8+snG0tmdyhBn/fvM/qXaFUre6JVwkHGlcojrVF/u9dVahSdWvXrgVgw4YNbNiwweTYERERJmm6bJIkYTAYKFbsv8dKO3bsIDIy0uRzP//8M0OHDpVbrnh5eZlsVf+4litlypR54jXnR6ou+3gP/++LUCfHoMZ4yzP31JQVpN5Hn5YEFub9A3n9+nUAatSokeu1eXl5YWdnx5Vr15DKVESjBkMuY7bSqklK1xGXlIqHw7+pwyKYMMlrT/25cqtt/JVNAl7RuoqkmHKiVso9a61at24tr/t99BhFXSVXa3xKSvjV8/j3sZqBrKxc/g57Ti9lqq5KlSpYW1vn2nIlO/32KDs7O+zt7enatav8mr+/v7yGKluxYsXkPZkuXbpE/fr1mTVrlvz+smXL5F538F+qbteuXU+85vxO1R3YuYFiKRfRGDJIt3Ah3u41DOpnu8VSNu4GlZKTSMm8m+sdJeus+2RqHTi0Z5/x8cwL0Ov1HDt2jKtXr6LVaqlfvz4VKvy3qeLNmzcB48S2QYMGAMSkwa0UFQYJtCkxpKSkkJaaQnJyMlFZSWhyuQmWkgUSKg7/FYL9v+UQiR7lRK2UE7VSTtRKOVEr5cxVq1eiV93q1asZNGgQW7dupVWrVorGd/v2bZo1a4avry+LFy/O9TP79+/n7bffZsGCBU/didVcveoelZWRxuU1n1JdikSdkYiECpVKjeTsieGNEUiejZUf7P5VNJuDjJMi2+Km7xl0kHAdqUEQhtcHvNCYDx8+LO/Q7uHhQWqqsSFx69atWbFiBcWKFUOSJBo3boy9vT3rt2xnYegNjly7T2qmcX+qy1vnEXViD3+eiGD2n7dJSs/C/ZHHdQZJ4vq9NPyqufFJm8oi0fMMRK2UE7VSTtRKOVEr5cxdq5eyV527uzsHDx7E39+f/fv3Y29vT8eOHeX3wLi55YIFCzhy5AhJSUlUqVIFvV7/1HFNnTqVzZs3c/LkSbRaLQsXLjR5f9myZfTr18/ktT59+tCnTx/u3r0rTwIflV+pOvXR/8Mrbj+qYiVRuXihUmtAl4Eq4QbqP6YYU3AetZ9+IAC3ylCzE5z6GSQd2BpTdWQkQUosuL4GtTq/UGoqMjISf39/6tSpw9atW/H29iYrK4stW7bw4Ycf0qVLFw4cOIBarSY4OJi2bdvyhp8/zk164FWlNla6e0TsXs2N0M1UCviIJUdj6FC3NKsOXycqMQNXeyssNSpSMvXEJmXg4WRDt4blTGouEj3KiVopJ2qlnKiVcqJWypkzta5EnrZceThV16FDBwIDA7G2tmbv3r2UKlWKNWvWMHv2bJKSkmjatClNmzYlKSmJ2bNnA9CwYUPOnTtHcnIyYWFhLF++nLVr12JlZSX3qjtw4AAlSpQgMzOTH374gc6dOxMQEMCpU6eeOLa4uDhu3LhB5cqVsbGxMVnfBNCtWzc2btyIra0t06ZNIyoqijZt2tCsWbPHTpryTdJdVOc2k6W2Nu6vlN2ZXmsFLl6QFg+n1zzbMRsPgcYfgpWjMWUXf9XY0LWCL7SfaZq2ew6zZs3C0dGR3377TV6bZmFhwXvvvcf69es5ePAge/bsAaBVq1YE/98q7ly9xMl5Q9g09E02jXuPa8f20ajnx/h0fJ8rcSlYqFUMa/EaJR2tiUlK59q9VJIydNQt68wXAdWp5Gb/QmMWBEEQhKcpVKm6bGq1GpVKJU9uJEmSe9Q0bNiQPn368N1338mbXG7cuJH169fLf0E/mqq7ffs227dvp3bt2vj7+zNx4kR5zVT2nazDhw/z/vvvM2LECPr160dcXBz79u1j7ty5T7zm/Fgcrrp2EHVaAplae3kxvAlrZ7hxBH1idM5Hb09SpxdU7Yjq7t+gy0Ry9gSXCsZ1Ty8wdkmS+OWXXxg+fDhWVlY56tCkSRNq1KjB6tWradmyJQCast40+t9KrGLPk3wvGit7J0rXbITW0vhYzkKtYn9kDPO616FZJRciopJIzdRTwt6SyiXtUalUORZZvioLJl+EqJVyolbKiVopJ2qlnLlrpfS4ebrGKSAgAIPBQJcuXViwYAHHjh1j+/btcqqucePGnD59Gmdn51xTdV988QUbNmzAy8uLkJAQ7OzseOedd1i8eDEnT57E29sbX19f/vzzzxznbtiwIUeOHAFg4MCBLFmyhOxLy+0xXLbsz/Tt25fly5fneP/NN9/kwIEDj73mSZMm5bo4fPXq1Xm2ONzzXiiV7m4n1Sr3u0AafTpaQzrHKgwnzdI1T875IvR6PV26dJEnybn58ssv0Wq1jBs3DoBfr6s5ex9cc+42AMCDTLDVwkfV8y5BIQiCIAjZUlNT6dmz51PXOOX54nAw3lHo2rUrI0aMQKfT4eHhwfr16/H19ZVTddmtTCIiIuRU3bMuDgcIDg5mxowZXLhwQX6k9ugdp4ctW7aMkSNHkpCQ8MRrqF69Or6+vvzwww9P/Fx+LA5XXQlBveczYjMscS3pkaNDNMl3wcoBfdefwTJ/NwJ7nCpVqvDmm2/mugA/IyODChUq8P7778v7da08fIOVR25QrphNzusDbsan8Xo5F77sWP2p534pFlvGX0Z95U9IjgYrB6RyTZA86r5wivFZpaenExwczMWLF7l//z5ly5alX79+vP766yb/PySl6zh4+R7/3E1CBVRxd+CNisWxt8rzZZKF1kvxc1VIiFopJ2qlXJFdHJ5XveqUWL16NZMnT2br1q0m65BetFfdoUOHOH/+PCtXrnzqZ/NlcXiFNzE4e2Jz6wIqPEzXZ+kzISsFandFbeecN+fLA0FBQUyaNIkRI0ZQr149k/dmzpxJbGwsgwYNkmvUvJo7W05HcT9Vh6u9aT1TMnSo1Sra1PR4ppoWysWWkgTHlhh3bk9PNE6UJAkiNkKFZtD883yb/D548IAOHTrw559/UqtWLV577TX27t3L4sWLGThwID/++CMajYaIO4kE74rk1v1UDP/+d9aOs3dZf/IO/2tblWoeBdcYuiAUyp+rQkrUSjlRK+WK1OJwME3VZa9TWrBgARs3biQxMZHRo0fj4OBAaGgooaGhODg4mKTqbt26hb+/P7a2tri5uTFixAj5PTCm6vz8/OT2K56enopSdfHx8QQGBvLhhx+SmJjIgAEDSE7+r9tyeno6ffv2pVatWjRp0gQnJyfq16+f1+V5PhbWGHyGodNYo7p/FdLuQ2aysRXG/evgXhvq9CjoUZoYNmwYtWvXxtfXl88++4ywsDB27dpF165d+fzzzxk/fjxVq1aVP1/e1Y5uDTzJ0Bm4EZ9KUnoWKRk67iSkEZucSbPKJWj6WsE/hnxh57fB8SWAyrgTd/GK4FoJrJ3gnz0QNi/fhjJw4EBOnTrF5MmTOX78OBs3buTy5cssWrSIn376iRkzZhCXnMH0nRe4dT+VMs42VHC1p4KrPWWcbbh5L5XpO88Tn5KZb2MWBEEoaK9Mqi4wMJCIiAjGjBmDvb09Bw4cICgoSH5fr9djY2NDUFAQarVaXndVWEjlmvK35/sYKvga91rKSAJLW6jfF9rPArtnWBSeD+zs7Ni3bx/9+vXj+++/p0mTJrRr147w8HAWLVrElClTcnynZ8OyjGldhaoeDqRlGUjO0OHhbMMHzSowtk1VLDT5+xgrz+l18Pd6QAL7Eqabj1o5gI0zXNwLD+6YfShXrlxhw4YNBAcHU6dOHfmxnEajYeDAgXz00UfMnTuX3WducichDU8XW7QP1V+rUeNZzJZbCWmERMaYfbyCIAiFxSuRqjt//jy7du1i1apVXL58GYCRI0cydOhQJk+ezGuvvYadnR0LFixgyZIlAHh6eiq65vxsuZJgW4GMFh9gkZlg3DrAthhY2md/IM/OlVesra2ZNWsWU6ZM4fLly1hZWVGpUiXUajU6nS7X7zR7rRhvVnThblIGBkmihL0Vllo1SHqysp5+ZxEKcUol/jKa+GtgXQweTUYCWDmhSriO/uYJpMolzDqU3377DY1GQ5cuXTh48GCOWgUGBjJ//ny27wtFY+eFSiXJj+myqVTG//I6cuUeAbVKmnW8hUGh/bkqhEStlBO1Uk6k6vIxVffTTz8xePDgXIsyZcoUJkyYIP/+jTfeIDo6mtq1a7Nly5anXnN+pOqEosE+/TavX11AptYOvTrnujgkCbvMGM6Xeo8o59fNOpbt27ezYsUK1q5dm2NPM4Bbt24xdOhQ3ho8lSyPWrjkMlyA+AzwtIPASiLtKAjCy01pqq5Q9aqLjo7G09OTnTt3mlzI4sWL5X2XQkJCTM6ZnarLPjfk7FUXHR1N+fLlczT+dXNzw9XVdN1MWFgYffv2fWrqLtu4cePkNVrwX6qudevWedty5TFpgqR0HX/+E8ufF+NISM3C3dGaFlVL0KRicSy1ak6fPs38+fPZs2cPOp2O119/nQ8//JC2bdvm2dhMxF9B/c8uVDcPg6RH8qiLoXI7KFnTPOfLRaFNqWSmoFm/E9ISwSGXrSUykiDTFe9W7+HtVs2sQ3FxcWHx4sVoNBokScpRq1mzZmFlZcXbrVuy41IqJYrnTDtKkkTKvTRa1S9D+yZeZh1vYVBof64KIVEr5UStlMuPVJ0SZkvVffbZZ2g0Gtq2bZtrqm7UqFGAsVnfw6m69PR0k5YrPXv2NDl+VFQUH3/8McePH+fixYtotVp+++23p6bqJEliyJAhrF27loyMDNq0aZNjI8nhw4dz8OBBwsPDsbdXtgt1frVcye24MUnpTNl2nvNRD9CoVFhq1dxKSOfEjQTCKt2nUvLf9OvzPqVKlaJPnz7Y2tqyZcsWOnTowCeffMLXX3+dt4O7EgL7p0FqHFjYAirj46lLe8BnKNR6N2/P9xSFLqVi4QzVAuDoItCn/1ujfxl0kBoL5d5AXapWrs2X89Kbb76Jt7c348aN43//+59Jrc6ePcusWbPo0aMHnZrUIPROOLHJWZR0sJInT5IkcTcpE2dbS1rVeLa048uu0P1cFWKiVsqJWilX0Kk6s/WqCwgIAGDnzp2o1Wq5V11ue/Rkv+bm5sbKlStp2rQpYWFhREVFERgYCPyXqsvIyKBEiRK0atWKS5cu0b59+6c2+HV3d+f69ets27aN9evX4+TkxJAhQ7h375583Gz9+/fn22+/JS4u7oVrYW4/7L9MxJ0HlHG2Ma4D+ldqpo49x84x9es+dO3alWXLlsk/EOPHj+e7775j1KhRNG3aVP7/6YUlRUPI15D+AIpV+u8vfkky7lV06HsoURXc8+/OU6Hk3QtiI+FaqLFGFragzwBdJrhWhrfGmn3SBMY/cz///DO+vr4MGTKE48ePU6VKFY4dO8batWupUqUK3377LS4u9gx6swIL/7zCtXup2FlpAYmUDD321lqC3qpAhRKi1Y0gCK8Os6Tqpk2bhrW1NVu3bqVNmzYMHTpUTtW5uLiY7Cbt5+eHi4sLAJaWlqSnpzN79mzq1q1Lu3bt5E0vK1WqBICXlxeNGzdm6dKlVK9enfLlyz91XDVr1iQzM5MhQ4bQokUL6tevz6BBgwDjPlPZ5s6dy5AhQ3BwcMizmpjL1bgUTly/j6udpcmkCcDWUkvcsZ2g1vLNd/NNZtEqlYqRI0fSuHFj5s+fn3cDurjX2CDY2dP0L36VCuzdIeMBRO58/PdfFZZ20GYatPgcSnkbk5Eu5aHJcOgwH5zzL81ZrVo1jhw5QqtWrdiwYQOjR48mLCyMSZMmERoaKv+5fLt2KaZ2qkX7Wh44WmtxtLGgfS0Ppv37miAIwqvELKk6BwcHatSoQUBAgPwXdefOnVmyZAnHjh2jRYsWuS4Oz8zMxNramo8//pjg4GCio6PlXcQvXbqEt7c3q1evllN1q1atIiUlhejoaGxsbHBycgKM7Ty++OILrl69ipeXl7xf0+rVq2nevDlZWVl8/fXX2NracunSJXn8586dIzMzk7S0NPR6PeHh4QDUrVv3sdecn6m6h/83MiqB5PQsihe3wSDlXJj74EYExV6rx710ieK5jKNDhw5Mnz49z8aojvobFSqQgFzGg9YGbp9Enw/JkcKfUtHAa+2Nvx6Vz2N2c3Ojb9++/PzzzzluUz9cv6olbalaskKO7xfeGue9wv9zVXiIWiknaqVcYUnV5enEacmSJbRq1Yo1a9bkWBxevnx5Zs6cybRp0/j1119zXRweExNDgwYN0Gg0+Pj4YGdnR2BgIHPnzpUXhy9cuBCdTseQIUMA4y7fixcvpk+fPixbtszk4rP/IoiOjsbCwoIaNWrQsmVL1Go1Xbp04fTp0/JxAdq3b8/169fl32dvb/Ck4OH06dNzTdXt2bPHLKm6vXv3AhBxX0VKipq7+mTUuTzZ0en06HVphP71F5dyGcbff/+NwWAwWYj/Iqrfuk7J5CRSs3Lf08c6M5GUdGuO59H5lMiulfB0olbKiVopJ2qlnKiVcuaqVWpqqqLP5XmvusjISGrWrMnt27flBdtDhw4lMTGRlStX8u233zJo0CC55UqXLl1YtGgRo0ePfuZedb6+vtStW5c5c+Y8cUyrV6+mX79+JneGwLiFQfPmzXMskp40aRJbtmyR7zg9SX70qoOcaYLoB+kMXWMcXzE7yxyfP7R1JRe3/x8XL17Cs0wpk/cMBgN16tShZs2arFmzJk/Gpzq3Gc2Br5GcyoL6kfm4JKG6fwVDvb4YGn2YJ+d7EpFSUU7USjlRK+VErZQTtVKuyPaqe7jlSjZJkuTF4Q9H94EcLVeOHj1q8v7du3fl956Xu7s7mZmZJCQk4OzsbHLsFzkuFFyqzrO4Bb5VSrLt9B1sLAz/Lto11johLQv319tyO+Rn+vTuxcaNG+VJbHp6OqNGjeKff/5h6dKleTfGyn7w9y+o7l8Hl3L/TZ4MBnhwE+xLoKkegCYf/8UgUirKiVopJ2qlnKiVcqJWyhWpVN3DLVdat25t8t4777zDmjVr5F3C+/btm+P7Pj4+TJ06lZiYGPkv+r179+Lo6Ci3XHke9evXx8LCgn379tGlSxfAeGfsxo0b+Pj4PPdxC9qgtyqQkJbJ4cvxxCRloFGr0BkkbC01dG1ala+a76BDwNuULVuWtm3bYmdnx65du0hISGDRokV5e+02LtBqMvw+ERJu/Puiyrjeyd4Nmn8GxZ6+kF8QBEEQCjOzLA4fMGCAvFA7W3bLlUfbqzysdevWVK9enffff19eHD5+/HiGDBliclcn+xFacnIysbGxhIeHY2lpKU+ujh49Su/evdm3bx+lS5fGycmJAQMGMHr0aIoVK4ajoyPDhg3Dx8eHxo0by8e9dOkSycnJREdHk5aWJp+nevXqWFrmfBxW0OyttEzwr86pmwmEXYojIS2Lko7WvPVaCap5OKBSVZLvLO3atYv4+Hj69u3L4MGDee211/J+QO41ocsSuPwH3DkFkt648WWlVsbJkyAIgiC85MyyOPzRSRMYJ07BwcGcOXOG2rVr5/p9jUbD9u3b+fDDD+XF4X369MnREDZ70TbAiRMnWL16NeXKlePatWuAcV1UZGSkyQr52bNny4vCszfA/OGHH0yOO3DgQJN2LtnnyU7nFUZajZoGXsVo4FUs1/ddXV0ZO3YsY8eOzZ8B2ThDzc7GX4IgCIJQxJil5UpuGjZs+MR0WrZy5co9Nen1tOP4+vrm+Iy1tTXff/8933///WO/92g7F0EQBEEQhIfl6QaYgiAIgiAIRZmYOAmCIAiCICgkJk6CIAiCIAgKiYmTIAiCIAiCQmLiJAiCIAiCoJCYOAmCIAiCICgkJk6CIAiCIAgKiYmTIAiCIAiCQmLiJAiCIAiCoFCe7hwu/Ler+YMHD/L0uFlZWaSmpvLgwQPRQfspRK2UE7VSTtRKOVEr5UStlDN3rbL/3n5adxIxccpjSUlJAHh6ehbwSARBEARBeFZJSUm59tzNppKUNJATFDMYDNy5cwcHBwdUKlWeHffBgwd4enpy8+ZNHB0d8+y4RZGolXKiVsqJWiknaqWcqJVy5q6VJEkkJSVRqlQp1OrHr2QSd5zymFqtpkyZMmY7vqOjo/jDpZColXKiVsqJWiknaqWcqJVy5qzVk+40ZROLwwVBEARBEBQSEydBEARBEASFxMTpJWFlZcXEiROxsrIq6KEUeqJWyolaKSdqpZyolXKiVsoVllqJxeGCIAiCIAgKiTtOgiAIgiAIComJkyAIgiAIgkJi4iQIgiAIgqCQmDgJgiAIgiAoJCZOhcj333+Pl5cX1tbWNGrUiKNHjz7x8+vXr6dq1apYW1tTq1Ytdu7cmU8jLXjPUquIiAi6dOmCl5cXKpWKOXPm5N9AC4FnqdWiRYt48803cXFxwcXFhVatWj3157AoeZZabdq0iddffx1nZ2fs7OyoW7cuK1euzMfRFqxn/fdVtrVr16JSqXjnnXfMO8BC5FlqtWzZMlQqlckva2vrfBxtwXrWn6uEhASGDBmCh4cHVlZWVK5c2fx/F0pCobB27VrJ0tJS+umnn6SIiAhp0KBBkrOzs3T37t1cP3/w4EFJo9FIwcHB0rlz56Tx48dLFhYW0t9//53PI89/z1qro0ePSmPGjJHWrFkjubu7S7Nnz87fARegZ61Vz549pe+//146deqUdP78ealv376Sk5OTdOvWrXweef571lrt379f2rRpk3Tu3Dnp0qVL0pw5cySNRiPt2rUrn0ee/561VtmuXr0qlS5dWnrzzTeljh075s9gC9iz1mrp0qWSo6OjFBUVJf+Kjo7O51EXjGetVUZGhvT6669L7du3l0JDQ6WrV69KISEhUnh4uFnHKSZOhUTDhg2lIUOGyL/X6/VSqVKlpOnTp+f6+a5du0r+/v4mrzVq1Ej64IMPzDrOwuBZa/WwcuXKvVITpxeplSRJkk6nkxwcHKTly5eba4iFxovWSpIkydvbWxo/frw5hleoPE+tdDqd9MYbb0iLFy+W+vTp88pMnJ61VkuXLpWcnJzyaXSFy7PWasGCBVKFChWkzMzM/BqiJEmSJB7VFQKZmZmcOHGCVq1aya+p1WpatWrFoUOHcv3OoUOHTD4P0KZNm8d+vqh4nlq9qvKiVqmpqWRlZVGsWDFzDbNQeNFaSZLEvn37iIyM5K233jLnUAvc89ZqypQpuLm5MWDAgPwYZqHwvLVKTk6mXLlyeHp60rFjRyIiIvJjuAXqeWr166+/4uPjw5AhQyhZsiQ1a9Zk2rRp6PV6s45VTJwKgbi4OPR6PSVLljR5vWTJkkRHR+f6nejo6Gf6fFHxPLV6VeVFrf73v/9RqlSpHJP0ouZ5a5WYmIi9vT2Wlpb4+/szb948/Pz8zD3cAvU8tQoNDWXJkiUsWrQoP4ZYaDxPrapUqcJPP/3E1q1bWbVqFQaDgTfeeINbt27lx5ALzPPU6sqVK2zYsAG9Xs/OnTuZMGEC33zzDV999ZVZx6o169EFQXhpzZgxg7Vr1xISEvJKLU59Fg4ODoSHh5OcnMy+ffsYPXo0FSpUwNfXt6CHVmgkJSXx/vvvs2jRIlxdXQt6OIWej48PPj4+8u/feOMNqlWrxv/93//x5ZdfFuDICh+DwYCbmxsLFy5Eo9FQv359bt++zcyZM5k4caLZzismToWAq6srGo2Gu3fvmrx+9+5d3N3dc/2Ou7v7M32+qHieWr2qXqRWs2bNYsaMGfz+++/Url3bnMMsFJ63Vmq1mkqVKgFQt25dzp8/z/Tp04v0xOlZa3X58mWuXbtGQECA/JrBYABAq9USGRlJxYoVzTvoApIX/76ysLDA29ubS5cumWOIhcbz1MrDwwMLCws0Go38WrVq1YiOjiYzMxNLS0uzjFU8qisELC0tqV+/Pvv27ZNfMxgM7Nu3z+S/PB7m4+Nj8nmAvXv3PvbzRcXz1OpV9by1Cg4O5ssvv2TXrl28/vrr+THUApdXP1cGg4GMjAxzDLHQeNZaVa1alb///pvw8HD5V4cOHWjevDnh4eF4enrm5/DzVV78XOn1ev7++288PDzMNcxC4Xlq1aRJEy5duiRPxAH++ecfPDw8zDZpAsR2BIXF2rVrJSsrK2nZsmXSuXPnpKCgIMnZ2VmOob7//vvSp59+Kn/+4MGDklarlWbNmiWdP39emjhx4iu1HcGz1CojI0M6deqUdOrUKcnDw0MaM2aMdOrUKenixYsFdQn55llrNWPGDMnS0lLasGGDSRw6KSmpoC4h3zxrraZNmybt2bNHunz5snTu3Dlp1qxZklarlRYtWlRQl5BvnrVWj3qVUnXPWqvJkydLu3fvli5fviydOHFC6t69u2RtbS1FREQU1CXkm2et1Y0bNyQHBwdp6NChUmRkpLR9+3bJzc1N+uqrr8w6TjFxKkTmzZsnlS1bVrK0tJQaNmwoHT58WH6vWbNmUp8+fUw+v27dOqly5cqSpaWlVKNGDWnHjh35POKC8yy1unr1qgTk+NWsWbP8H3gBeJZalStXLtdaTZw4Mf8HXgCepVaff/65VKlSJcna2lpycXGRfHx8pLVr1xbAqAvGs/776mGv0sRJkp6tViNHjpQ/W7JkSal9+/bSyZMnC2DUBeNZf67CwsKkRo0aSVZWVlKFChWkqVOnSjqdzqxjVEmSJJnvfpYgCIIgCELRIdY4CYIgCIIgKCQmToIgCIIgCAqJiZMgCIIgCIJCYuIkCIIgCIKgkJg4CYIgCIIgKCQmToIgCIIgCAqJiZMgCIIgCIJCYuIkCIIgCIKgkJg4CYJQIEJCQlCpVCQkJACwbNkynJ2dn+kYKpWKLVu2vNA4Dh48SK1atbCwsOCdd955oWMJglD0iYmTIAhmc+jQITQaDf7+/gU9lMcaPXo0devW5erVqyxbtqyghyMIQiEnJk6CIJjNkiVLGDZsGAcOHODOnTsFPZxcXb58mRYtWlCmTJlc73hJkoROp8v/gQmCUCiJiZMgCGaRnJzML7/8wocffoi/v/9z3c3ZunUr9erVw9ramgoVKjB58uQnTmJu3rxJ165dcXZ2plixYnTs2JFr167l+tlr166hUqm4d+8e/fv3R6VSsWzZMvkR4m+//Ub9+vWxsrIiNDQUg8HA9OnTKV++PDY2NtSpU4cNGzaYHHPnzp1UrlwZGxsbmjdvzrJly0weR06aNIm6deuafGfOnDl4eXmZvLZ48WKqVauGtbU1VatW5Ycffsgx7k2bNtG8eXNsbW2pU6cOhw4dMjnGwYMH8fX1xdbWFhcXF9q0acP9+/dZsWIFxYsXJyMjw+Tz77zzDu+///5jaysIgpGYOAmCYBbr1q2jatWqVKlShV69evHTTz/xLD3F//rrL3r37s2IESM4d+4c//d//8eyZcuYOnVqrp/PysqiTZs2ODg48Ndff3Hw4EHs7e1p27YtmZmZOT7v6elJVFQUjo6OzJkzh6ioKLp16ya//+mnnzJjxgzOnz9P7dq1mT59OitWrODHH38kIiKCUaNG0atXL/7880/AOGnr3LkzAQEBhIeHM3DgQD799NNnrBr8/PPPfPHFF0ydOpXz588zbdo0JkyYwPLly00+9/nnnzNmzBjCw8OpXLkyPXr0kCeV4eHhtGzZkurVq3Po0CFCQ0MJCAhAr9fz3nvvodfr+fXXX+VjxcTEsGPHDvr37//M4xWEV44kCIJgBm+88YY0Z84cSZIkKSsrS3J1dZX2798vv79//34JkO7fvy9JkiQtXbpUcnJykt9v2bKlNG3aNJNjrly5UvLw8JB/D0ibN2+W36tSpYpkMBjk9zMyMiQbGxtp9+7djx2nk5OTtHTp0hzj2rJli/xaenq6ZGtrK4WFhZl8d8CAAVKPR1m+OwAABRFJREFUHj0kSZKkcePGSdWrVzd5/3//+5/JNU6cOFGqU6eOyWdmz54tlStXTv59xYoVpdWrV5t85ssvv5R8fHwkSZKkq1evSoC0ePFi+f2IiAgJkM6fPy9JkiT16NFDatKkyWOv+cMPP5TatWsn//6bb76RKlSoYFI7QRBypy3ISZsgCEVTZGQkR48eZfPmzQBotVq6devGkiVL8PX1VXSM06dPc/DgQZM7THq9nvT0dFJTU7G1tc3x+UuXLuHg4GDyenp6OpcvX37ma3j99dflf7506RKpqan4+fmZfCYzMxNvb28Azp8/T6NGjUze9/HxeaZzpqSkcPnyZQYMGMCgQYPk13U6HU5OTiafrV27tvzPHh4egPHOUdWqVQkPD+e999577HkGDRpEgwYNuH37NqVLl2bZsmX07dsXlUr1TOMVhFeRmDgJgpDnlixZgk6no1SpUvJrkiRhZWXF/Pnzc0wCcpOcnMzkyZPp3Llzjvesra1z/Xz9+vX5+eefc7xXokSJZ7wCsLOzMzk2wI4dOyhdurTJ56ysrBQfU61W53hcmZWVleM8ixYtyjEJ02g0Jr+3sLCQ/zl7wmMwGACwsbF54ji8vb2pU6cOK1asoHXr1kRERLBjxw7F1yEIrzIxcRIEIU/pdDpWrFjBN998Q+vWrU3ee+edd1izZg2DBw9+6nHq1atHZGQklSpVUnTeevXq8csvv+Dm5oajo+Nzjf1xqlevjpWVFTdu3KBZs2a5fqZatWom64YADh8+bPL7EiVKEB0djSRJ8mQnPDxcfr9kyZKUKlWKK1euEBgY+NzjrV27Nvv27WPy5MmP/czAgQOZM2cOt2/fplWrVnh6ej73+QThVSIWhwuCkKe2b9/O/fv3GTBgADVr1jT51aVLF5YsWaLoOF988QUrVqxg8uTJREREcP78edauXcv48eNz/XxgYCCurq507NiRv/76i6tXrxISEsLw4cO5devWC12Tg4MDY8aMYdSoUSxfvpzLly9z8uRJ5s2bJy/aHjx4MBcvXmTs2LFERkayevXqHElCX19fYmNjCQ4O5vLly3z//ff89ttvJp+ZPHky06dPZ+7cufzzzz/8/fffLF26lG+//VbxeMeNG8exY8f46KOPOHPmDBcuXGDBggXExcXJn+nZsye3bt1i0aJFYlG4IDwDMXESBCFPLVmyhFatWuX6OK5Lly4cP36cM2fOPPU4bdq0Yfv27ezZs4cGDRrQuHFjZs+eTbly5XL9vK2tLQcOHKBs2bJ07tyZatWqMWDAANLT0/PkDtSXX37JhAkTmD59OtWqVaNt27bs2LGD8uXLA1C2bFk2btzIli1bqFOnDj/++CPTpk0zOUa1atX44Ycf+P7776lTpw5Hjx5lzJgxJp8ZOHAgixcvZunSpdSqVYtmzZqxbNky+TxKVK5cmT179nD69GkaNmyIj48PW7duRav97yGDk5MTXbp0wd7eXuyYLgjPQCU9+sBdEARByBMhISE0b96c+/fvP3M7mfzQsmVLatSowdy5cwt6KILw0hBrnARBEF4x9+/fJyQkhJCQEJPNNQVBeDoxcRIEQXjFeHt7c//+fb7++muqVKlS0MMRhJeKeFQnCIIgCIKgkFgcLgiCIAiCoJCYOAmCIAiCICgkJk6CIAiCIAgKiYmTIAiCIAiCQmLiJAiCIAiCoJCYOAmCIAiCICgkJk6CIAiCIAgKiYmTIAiCIAiCQv8PbLS3ki+FSaUAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -237,7 +245,7 @@
     }
    ],
    "source": [
-    "# Allelel Frequency TABle with Study Prior\n",
+    "# Allele Frequency TABle with Study Prior\n",
     "AFtabSP = pd.concat([venezuelaAF, study_prior], join=\"inner\")\n",
     "\n",
     "# Combine Allele Frequency with Study Prior\n",
@@ -258,7 +266,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -277,6 +285,154 @@
     ")"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Alternate priors\n",
+    "As the amount of data increases, the choice of prior has less and less impact on the posterior estimates. However, priors can have an unexpectedly large impact when working with large numbers of alleles (because the sum of the prior also increases). Fortunately this mainly affects the compound model (fit using `AFhdi()` to estimate credible intervals and \"post_mean\"), but if you are using this it is important to check your results and see the impact of alternate priors.\n",
+    "\n",
+    "We can diagnose the problem easily using `plotAF()`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 pages of results\n",
+      "Download complete\n",
+      "2    80\n",
+      "3     3\n",
+      "4     2\n",
+      "Name: allele, dtype: int64\n",
+      "Multiple resolutions in AFtab. Fix with decrease_resolution()\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 19 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!\n",
+      "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb\n",
+      "If you have set `credible_interval` to < 0.95, this may be a non-issue.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "country = \"Oman\"\n",
+    "locus = \"A\"\n",
+    "\n",
+    "# Download dataset\n",
+    "base_url = HLAfreq.makeURL(country, locus=locus)\n",
+    "aftab = HLAfreq.getAFdata(base_url)\n",
+    "aftab = HLAfreq.only_complete(aftab)\n",
+    "HLAfreq.check_resolution(aftab)\n",
+    "aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "caf = HLAfreq.combineAF(aftab)\n",
+    "# Calculate high density intervals\n",
+    "hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)\n",
+    "\n",
+    "# Plot data\n",
+    "HLAfreq.plotAF(caf, aftab, hdi=hdi)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above plot clearly shows that the credible intervals are too low. This is an example of how our defult prior (all $1$ s) can be a problem with many alleles. It's important to note though that this is a very small dataset (one study) and this will not be a problem for larger datases until the number of alleles is much higher.\n",
+    "\n",
+    "We can solve this by using smaller values in our prior, e.g. $1/k$ where $k$ is the number of alleles. This is known as Perks prior. Unfortunately models with this prior take longer to fit (minutes rather than seconds). It is also particularly important to validate models that use this prior with [posterior predictive checks](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/posterior_predictive.html) and as described in the [credible intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb).\n",
+    "\n",
+    "Using this $1/k$ prior we can see that the credible intervals are no longer dragged to zero and better reflect the observed data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 299 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!\n",
+      "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb\n",
+      "If you have set `credible_interval` to < 0.95, this may be a non-issue.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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wtm/fDiAfH+aHJR0oe1trzJKElVqNGpCstKi01mDU41S1MSprO+xtrbGxsaF169Z4eXlx/fp1KlSoIH45EZ6BUkROyhA5KUPkVDgiI2UUSQdqypQpTJw4kVWrVjF37lyqVKnC1q1bCQ4OlpsJ5z4h16ZNG1kiz/3c559/Tq9evQBISEggNTVVXsRERUUhSRKTJk2Sn7obMGAAx48fR6/X5zuvsmXLolaradmypVxIc86cOZQuXTrPDhTA9u3b2bVrF3/88Qfbt29HrVbj6elZ4D1b2oFysdOSkW0iTW9Cn3gPU0YK1sVKc3PxSOy8yzNloytLnbRcvXoVs9mMvb09GzZsoFq1ak819suM8AyUIXJShshJGSKnwhEZKaNIO1COjo7UqFGDTp06oVKpGDp0KAEBAQQGBnLy5MkCJfLIyEjUajU///wzc+bMISsrC41GQ4UKFfD19QXgrbfeYsuWLQQEBDB16lRiY2MZNWoUtra21K9fH4Bjx47RqFEj5s2bx4ABA4iKisJsNhMSEsKmTZvkHShbW1u5jMHRo0fZs2cPc+bM4bfffmPXrl0AtG/fXq5PlR+WdKAiItVIesCkwmgEfVYmALqKDTAk3iMjOoKMaLj9/+9v2LAhERERXLx4UThQCM9AKSInZYiclCFyKhyRkTKKnAPl5+dHcHDwY82Ey5Urx/Tp05kyZQqbNm3Kt5DmjRs3UKvVJCQkkJ2dLQvijo6O8pHcO++8w7Zt21ixYgUbN24Ecrbd1qxZk6fS+MPkVh2vXr16HgeqQYMGxMfHA2Btbc2ECRMwGo1069ZN3pn65JNPnnjPlnSgIg9c5+KfUZgw46DT4ODtwz0ra5KPrcWpVis8fd/ng7b1GNi0FMuWLWPo0KEYDAa6dOkiHCjhGRSKyEkZIidliJwKR2SkjCLrQF27do2aNWs+1kz4yJEjSJJEly5dCiykaTabMRqNODk5sWDBAho2bMjt27dp3bo1+/fvp23btpw4cYLg4GAaNmzI6NGjiYuLY8SIEfTu3ZuUlBRUKhWvvfZaHgcql8uXL+dxoPbu3Uu7du0AOHz4MD4+PixdupRSpUoRGhpK9+7dGTNmDB07dizwni3pQLnY2WA0S2jVarRqNZKNLWobO0xmEx5N3kTl6IGrvQ1OTk7069ePuXPncvnyZV599VXxy4nwDJQiclKGyEkZIqfCERkpo0g5UPB0zYRzd2zmzp0rF9KsUKECxYoVkyXyadOmIUkSR44ckR0ojUZDv379OHz4cL494HILaX7wwQd5mgk/XEhz37593Lx5kxYtWuT52vPnz/Puu++ydOnSfO/Xkg7UjftpONlakWkwkaE3Yk6Lx5SehJWTB5FBw3F/pQ3b0puQfBwWLFjA7du3sbW1Zf369VSsWFHxOImJiWzevJm7sfGonIvzSqOWVCjuTAUP+wLrZb3ICM9AGSInZYiclCFyKhyRkTKKpAP1bxTSzO1ft3DhQrmQ5rp16wDkBdU/KaQ5a9asPCUMrl27Rvfu3alSpQrfffddgfdsSQfq6nU1GhMU00KyQUVyWs7irHSnIRhuXyDm1C42Hd/EVo2Ghg0bMmDAAL777jvOnDmjyIEym80EBwezYePGnL6CVtaYDdloHd2o2HkQdV6tj38pM66Pb7C9FAjPQBkiJ2WInJQhciockZEyipQD9bTNhHMLaf70008UK1aM+Ph4Nm3ahEqlkgtp9urVi6CgID7++GM+/PBDIGfbrUSJEnL17YIKac6bN4+FCxeSkZGBk5MTtra2ciFNs9nMjBkzWLt2bZ5z0NmzZ1OqVKkC79miDtT+69w/d48y7jpUKhUZbjbctNLimhVLrT6fE9XhE1qWd2DE6zXl+/38889p166dIgdqzJgxrF27luZvfoShqj/uHp6Y70dybsNvXA2egtZ+GnbuTZnsXwM3+/ybKb+ICM9AGSInZYiclCFyKhyRkTKKpAP1tM2EcwtpqtVqUlJScHBwoFatWhw6dEgupOng4IAkSeh0OsxmM1qtlszMTJKSkrC1tQUosJBmfl5ULrllABYsWICbmxtbtmxh5syZ9OnThzt37hR4lGVJB6p1dW92X71PSqYJV3tr7Jyc8KrZmEu7g3Gr3gQrB3da1ygJQGZmJqNHj8bZ2ZnOnTsXWNIhl9jYWGbOnMmHg4cTVcofVxsNjloJSpSlxScT2fXjp0TvCSK8TDV2nL9N97o+T3Uv/wYPV5UH4RkoReSkDJGTMkROhSMyUkaRcqCeVTPhxYsXF9hMeNq0aQCkpqbKR3YLFy7M40A9Wkgz14EaOHBggc2E27VrJwvlAK1bt8bOzo4pU6bIZRHyw5IOVBVPHZ1qefHHmbukZhlwsrUi+mwIALsn5tTJ2jPq8a97Ut2qR/l99o/AjwW+fnBMew4Cff7GvJ8XuYtG4RkoQ+SkDJGTMkROhSMyUoZwoF4yByo/chdDDy+QHsWSDhRAcQmauag480BFXMLLJ3T/mzzqfQnPQBkiJ2WInJQhciockZEyXmQHSiU96UzrH7BhwwZ69uxJnTp1aNSoEbNnz8bf35/Q0FD8/PyIiIjgs88+Y86cOfIOlF6vlx2oqVOnMnr0aDQajexAmUwmVCoVKSkp2Nvbs2/fPvz8/FCpVJjNZiBn283Dw4OIiAh0Oh2hoaE0adKEX3/9lb59+3LkyBGaNGmCjY0NOp1OdqDS09Np3749a9eu5fjx40yaNIlbt25x7do1VCoVBoMBNzc3bt++ne8xHeS/A+Xj40N8fPxTO1APYzZLxCSls2vXLjr5+2JrY01qair37t3D0dFRboOjlODgYAYNGsSkpTvYEWXEx02XZ1EZ/udmTgTPoPGXS6lVsQxTA2o+9T2kpqbi7+9PQkICX331FZ06dSI7O5vVq1czffp0XnvtNVavXi3X4Loak8LUHWEkpOtxd7DGVqtBbzQTn6bH3lrDZ60r0rCcm3z93CM84RkoQ+SkDJGTMkROhSMyUsbzdKCKFStGcnJyof9+CwfqIezs7Lh48SJxcXEYjUZMJhNVq1Zlz549BS6ewLIO1KOUcFPh6WSLu5srWq0WFxcXfHz+mZv07rvv8uWXX3J26zKcG31EukmFu0POfegz0ri6dw0lazVB516SjvXK4+Li8tTzDwoK4saNG5w7d46qVavKnx83bhyNGjWiXbt2HD16lI4dOyJJEhv33SLZaEXFEk7y4s4OcHaUuJ2YydoLCbT+X1msNOp8xxOegTJETsoQOSlD5FQ4IiNlCAfqJXGgatWqRWRkJNHR0bz66qskJCRw6dIleYznTbbRROT9dG4mZJGQlIKDnS3R0dHcuHEDZ2dnatas+bdqNqlUKqZOncrAgQP5X9Rt1NX9iXXxwhR7jau7g8lMSaTSW2Oo7W3Laz4Ock5PQ1BQEF26dMHHx+ex6zVt2pRXX32VBQsW4Ovry+0HGZy9EYOLVoNRn/XYtdyszdy494AT4dHU9snbasdgMJCVlUV6evp/6i+pRyV5gUAgEDwfhAP1CHfv3sXX15eyZcuSmZmpaPFkSYkcwGgys/HcPbZfjCU2JYudw9/is6e+al7OHz0ARw889vlTP/fnFPDTMxzr0qVLrFmzpsDXT58+jYODg+Lr7fvyWczq5aCwJyv/LkJoVYbISRkip8IRGSnjZZDIX2oHSqvVyv+gqFQqnJycuHfv3j92oO7evUuVKlUwGo3yEd4bb7zB119/TZ06dQq853HjxuUrka9YseKpJXKzBDtuqziboEajkrC3gj1jOj/VNQUvLxs2bHjeUxAIBIL/LBkZGfTq1eu/60BVr14dnU5HdnY21tbW2NraolKpKFGixFM5ULt3737sWOmPP/7gjz/+eOLXWbKQ5plbSdyMvEwpDw1OOi2SWaJ4zUakRd+gxfB5ZGns+LJdZeqXdUOSJIYNG8batWu5fPnyMxXYnxWzZ89m0qRJ8s/Hwxw4cIBu3bqxfPly2rdvjyRJjN9yldO3Eh8T3CVJIjoxi9LudvzQvRbaRxwog8HAvn37aNWqlTjCewJCaFWGyEkZIqfCERkpo0gW0vw3HKjx48eTkZHB1atXqVKlCgB37tzBx8eH48eP89prr/0jB6pPnz706dMHgEWLFjF06FCWLFlC165dMRgMBX4TLSmRH7qegN4kUdLOBglITU0g7vIJ6vf4FK+SPlyPjmfHyWvULlEXT09PJk+ezLJly9i5cycfffTRU41tCT777DOCg4Pp3LkzEydOJCAggOzsbJYvX863335L69at6dmzp/wU3oetqjNu8yXupenxcLRB9/9P4cWlZeHo5MhHrari4e722DgGgwFbW1tcXFzEX1IKEEKrMkROyhA5FY7ISBlFSiL/NxyoS5cuYWtry5YtW2jXrh2SJNG4cWMAuazBs6gDJUkSy5cvp3Hjxk8M1ZIO1J3EDLRqFXEpWcSlZpNwJxLJbCJB48ru+ROIPrWHEH0WP30MzZs3Z8yYMZQqVYqIiIgX8oxdp9Oxa9cu+vfvz0cffZSnFc8777zDjBkzMJvN8vexiqcdo9tVZvHRW4TFpRGfmo1Wo6JCMXveaehDw7LO+d6n8AyUIXJShshJGSKnwhEZKUM4UBZyoDp16sSWLVtwdnbG1taW+Ph4zGYzGo2GlJSUf+xARUVFMWrUKLZu3SrvSnl4eLB8+XIaNWpUoNhsSQdqQ6Sak/EqDDnrCcxpD4iY3QeNnROgwq1eR2rXrE4NbRzbt28nPDwcjUZD79696dq161ONbWliY2MJCwtDo9FQvXr1J5ZJkCS4lwnpBhU6KwlvO9CImqICgUAgeIb85x2o3IKRmZmZZGdn4+LiQpkyZTh9+jS3bt2iSpUq/7gX3qlTp/J4UPfv38ff3599+/bh6+ub79dZ0oF6cOwWh3eEYa1VYWOlBp03VvauGDNTqDjgN1TO3nRrXZGPmpVj6tSp1K9fn4sXLzJy5MjHHKOihPAMlCFyUobISRkip8IRGSlDOFAWcqCsrHKmff78edmByszMxM7OTl5A/dNeeBEREXnuZ8yYMUyZMkWW0/PDkg5UcpYRays1JrMZo0kCfTrGrFSQzNzb+RterfqQkl2OlJQUfvnlF65cuQJAaGgoVatWRW8yo5Ik9NlZ2NnZvTA1rf4thGegDJGTMkROyhA5FY7ISBnCgXrGDlRu6YJFixaxcuVKJEnilVdeAZDf82/2wrOkA3U7IQMvJxuyjWaSMvWkJ8SByYiX34cknFjP9fmDGLvEnjH6TKysrPj0009Zu/YPth48yf4kV/avWsCd0F0YszNxdHKmz/vvMWLEiL/d9uVlQ3gGyhA5KUPkpAyRU+GIjJTxMjhQz3wBtWXLFhITE4mKisLPz4/atWvj7+9PVlYWTZs2JTAwEAcHB+bMmUPlypUB6NGjh+xAZWVloVKp+Omnn2QHatOmTahUKpo0aQKARqNBpVIxY8YMnJ2defDgATdv3sTW1la+Znx8PNbW1kRGRtKyZUtiY2MBmDdvHgsXLpQdKFtbW/nR8IJ64Xl4eNCoUaMC79mSzYTj76lJTYNitmBrDUn21kQCHh7FqDPqd25cOIVdejRNStvRoEEDrG1smTPvF0Iu3iJ+xTuo1Rq8G3VG6+aD4X4kgQsXsWLFCqZMmSLvyv2XEQ07lSFyUobISRkip8IRGSnjRW4m/FI6UJIkIUmSLI27urpSrVo1/vzzT65du/aPHah/2gvPkg6U9nIcP+4Jx8XJBmsrNSWLexBeqhL3z+ymlm8nsuu25rNWFWlfywuALybPwJCdRcbtizi4FqPdqF+wdXDOqZuUlI1N+3c598tnrFu3js2bNz/V3F5khGegDJGTMkROyhA5FY7ISBnCgbKwA3X69Oln6kD90154lnSgWlYrzrZLsVyKTqG4ow22WhXlmgdwdsX37P31W1q+NZAGZRxJTU1l5cqVzJnyDW6V65MQdpKWA6egtbbFpM85XvTQwZ0sazq8O4BfJ3/JtWvXHltgPk8s0edNeAbKEDkpQ+SkDJFT4YiMlCEcqJfIgXrReuFpVTCqbSUmbLnCmdvJpGcbubriewBiT+9h1ek9rBqZ92sSwk4CcGDe6HyvefD//79WrVpPNbdnzbPs8yY8A2WInJQhclKGyKlwREbKKPIO1EcffURqaipDhgxBq9USEBCQx4Hq0KED4eHh+Pr6Mn78+DwO1MyZM5k6dSp2dnYMHDgQs9lMjRo1gL8cqGnTpmFra4ter+fWrVvodLpCHajAwEBOnTpFaGgoer0ejUYj7x7dvXuXFi1akJGRQWpqKikpKbRr145Fixbh5eVV4D1b0oECuJCg4tptNSYj2KqeadmuF4pt27Y982sKz0AZIidliJyUIXIqHJGRMoqsA7V582ZGjx7Np59+yrx582QH6uzZs3Tp0gVXV1dUKhVvv/02t2/flqtQS5KEr68vEyZMID09HXd3d+7fv8+xY8d44403ZAeqZs2aXL9+HRcXF3x8fDhz5gwTJkxg7NixBTpQrq6uHDlyBLVaTe3atbly5QpnzpwBcr5R169fz/P+nTt34u3t/dx64d1KyGDh2gvYOZko72QDEiQ17cLt4zuo88Ekilf8HxO71KB8MXuSkpJo7t+R2Lg4TBnJ1GjXm1rt35WvlaU3kZhhwPXSGvZuWcelS5eeyQLvWfEsj/CEZ6AMkZMyRE7KEDkVjshIGUXegSpRogQmk0n2oA4fPkxSUhLOzs4sWrSIiRMnUrJkSQAuXrxI//795WrUCxYsYPPmzaxatYqxY8fSunVr7ty5A4C3tzdWVlacP39eHjfXgTp4MOeA6lEHKncH6ebNm5w8eZJ69eoBOcdYFy9eJDo6+rFeeB9//DHt27dnw4YNT7xnSzpQByMSSM40Us7dLuepQH0Wd0/vo6pvAP9r0JzIBxmERmfxasWSuLi4MGvOXLq1bUmxGo25uG0Jzp6lqNCoHVkmuJ+RhubaftYtX8i4ceMoUaLEU83tZUB4BsoQOSlD5KQMkVPhiIyUUSQdqB9//JG0tDRWr14te1BDhw5lxYoVDBgwgD59+sgeVFhYmOxBhYWFATnHXxMmTOD48eOcPXsWAB8fHwCaNGmC0Wjk+vXrVKhQAYBNmzYB5PGdFi1aRN++fZEkiXLlyuHs7Ex2dra8eEpJSSE8PByVSsXx48fp1q3bP7pnSzpQl+4mo1WDRM6uW0rsXQwZqZSq0wwJCRUSG8/c5XJ0Mikxt4k+ugGNRkNy5EWsnT34M3ACx9fMxd6jFNnxt8lITqB///6MGjXqP30GLzwDZYiclCFyUobIqXBERsp4GRwoi/XCi4uLo1mzZly8eJHXX3+djRs34uTkROnSpbl69SrLli3j22+/pWTJklSqVIlLly4xePBgXn/9dapVq8b9+/dRq9V4eHgAOX3T4uLi8PDwwGw2y2L53bt35cazHh4exMXFATk+U8OGDdFoNNy8eROANm3asHfvXuzt7TGZTLi4uKDVasnIyJBLKfTt25djx44RHh6OyWSiZcuWzJgxg4oVKz6XXnirbqi5kQLu/18IPT0+mpAf+lO/3zhsy9blXgaoVUDUUcJXT0NtrUMyZFGydDlSkhNJfnCfUpVq4lnMldLF3WndurW8EBUIBAKBQPAXz70Xnp+fHzExMVy8eJEPP/yQ4OBg4uLi6NChA2vXruWLL77Azc2NESNGcOrUKerVq0fFihWJi4tDrVZTrVo1tFotaWlpZGRkyE/m5W6t5S6soqKisLa2RqfTUbJkSW7evElwcDBvv/02BoOBu3fvsn//fnluycnJ8nX0ej3p6elUqFCBzMxM+T3Hjh3j6tWr8scHDhzglVdeeexpvoexpAOVfSaaXw7ewN1Vh0atwuzmjp2bF7EXjuBUqiEqtRlPTSpH1vxA6TrNKNuwDSHzRlO1x0gWjXiT6ZO+ZebMmSxfEPLEYqD/NYRnoAyRkzJETsoQORWOyEgZRdaBAhg6dCiSJBEUFITZbJZ3PXQ6HeXKlWPJkiXUrFmTsLAw9u/fzzfffCP7R8nJycTExMhlBnJ3mIoVK8aYMWNo1KgRx48f58aNG7i5ucljT5o0iXHjxvH2228/5kAlJydz+vRp7OzsSEhIAHKaB1erVg2NRiM7Urm95MaNG8esWbNo3rz5c3WgWlf3YtP5GO4mZVLKRYfaSkPpxh24uiUQd8dSeDfsyIPjm9FYWVGlZQB/LhiPR4VaZDl4c+BqDBMmTGDr1q3MmjWLunXrPtVc/g6WqOn0TxCegTJETsoQOSlD5FQ4IiNlFCkHCnI8qIULF1KqVCm2b98u14Hatm0b3bp1Q61Ws3r16nzrQAH88ccf8q5QXFwcAwcO5Nq1a/z5559UqFCBcePGUa9ePaZNm8bSpUuxt7enc+fO6HQ62UU6cOAAvr6+REZGUrZsWU6dOoXJZCI9PZ1Tp05Rt25dqlatioeHB/Hx8TRs2PAf368lHSgnGzVf+Ffku+3XuBKTSrbBxNUtgQA82BfEg31B8nt3/TgEgMzkeO5/3YE/H7pOeHg4f/zxx1PN5e/wLGs6/ROEZ6AMkZMyRE7KEDkVjshIGS+DA2WRBdSWLVtITU3lq6++ylMH6sGDB7zxxhtMmzaNRYsW5VsHCsDFxYWmTZsSExMD/LUiLFmyJJ6enty4cYOQkBCSk5P5+eefOXnyJNOmTQNgzJgxQE5blhIlSuDn50dERAQxMTFYW1vTrFkz2rRpQ3Z2NiqViszMTCpXriw/kXbgwAEmTJjA0aNHycrKYs+ePUyZMoX27dtTp06dfO/X0nWgbqfBgwdqsrJUGM1Pfbl/BUvUdPoniForyhA5KUPkpAyRU+GIjJTxIteBeuYSOYCvry8hISHExMQwevRoHBwcmDdvHp06dWLUqFE0bNiQIUOGUL16dUJDQ6lbty5JSUnY2toybNgwEhMT+e2336hYsSJJSUl8/fXXxMbG8sYbb7B27Vr8/f3Zv38/lSpV4ubNm2RmZmJra0tmZiZpaWny8dHDT+GtWLGCvn370rRpU06fPo1er5cXUJUqVZK9pylTpjBt2jTZl3qYgqLKbwfKx8eH+Pj4p3agHqRlM3zNBWJSsinpaosGOL7+d65uDcK91Qd41W+P+ew6wkPW4zvoew4FjsferTjV+n3Px83K075mcRo0aEDt2rUJDAx8qrn8HZ73EZ7wDJQhclKGyEkZIqfCERkp43k6UMWKFXs+EjlA/fr1OXDgwGN1oDZv3kxQUBCSJBVYBwpyil1++eWX8vWqVq1Ks2bNOHLkCJBTB6pMmTJcvnyZt956i0qVKpGQkMC8efOIjo6mUqVKAHnqOnl5eaHX69m3b1+eOlDFixfn2rVrREdHU6JECUaPHs3o0aMZN24cGzZs4OzZs3To0EHupZcflnSgDt2IJSYlm9JudmjUKkwmIzePbqV0g7Y4N3uTLIMJ7wZdCNu3lrD9f9Cw1wgOzPsSXVoM/rV9mThuDNevX2fZsmVyja2ihPAMlCFyUobISRkip8IRGSmjSDlQT1sHKj9ySxPkOlNNmjRhzZo1/PLLL9y4cYNly5bJx3+lSpWSv+7hHai6devKbVtyF0/Xrl2Tn/x7Uh2o5ORkqlWrVuA9W9KBOhn5APX/14GKT9MTdzuSzIRYvOu2wc6cxPmQDcQmReNcrha3zh3i7tVTqK203Nk2l7rLxnH37l1+/vln6tatW6TO3IVnoAyRkzJETsoQORWOyEgZL4MDZdE6UO3bt6dHjx589tlnGI3Gx+pAzZkzR+5vl1sHys3NjdjYWOrXr89XX33Frl270Ov1uLq6Eh0dja2tLWlpaVSqVInExETWrVuHg4ODvPh58OABkCOmBwQEYGNjI7dnadiwIadPn2bXrl04OTkxZEiOdB0REcH48eMZMGAAERERpKWl8euvv7J//34++OADxowZw8mTJwt0oCxZByr4uprrKZBlUqE3QXb8bW7+PhCn2m1JObcLjY0dDiUqYEqNJy0+GgdXdzKSk3BwsKdhw4a8/vrrlC9f/qnmIBAIBAJBUeCFqQN14sQJRo8ejUajoV27dnIdqPPnzxMXF8fu3bsZNmwYkCOK/f7775QsWZJffvmFjz/+WK7/ZGtri9lsZvDgwSxYsACdToe7uzsuLi50794dR0dHEhIS8hyjZWRkcPfuXSIjI+XPtW/fnqtXr9KuXTv0ej1WVlZ0796d8PBw+T39+vXjzz//en5t1KhRAE88/rJkHag7B29w7kAkkmTGztYKO28fblvbknJuJ26Ne1Cs6Vt80qoqg30rsGvXLnr16oXZbGLJkiW0b9/+qcZ+mRGegTJETsoQOSlD5FQ4IiNlFOk6UCNHjsRoNNKpUycg56kstVqNTqejTJkyco2nh1GpVPj6+rJz505WrlxJ/fr18fDwICIigr59+xIYGMjEiRPR6XRcunQJjUYD/HXEl52djZWVFbt27aJVq1aPSd8+Pj5kZGRQo0YNfvvtNwwGA3369OHBgwdyHajt27czYsQI7O3tmTlzJjVr1pRbyRSEJR0ona01ZknCSq1GDUgaLSqNFlTZOFWsC1pb7Gy0WFtb07hxYzw8PEhNTaV06dLilxPhGShF5KQMkZMyRE6FIzJSRpFyoOAvD2rKlClMnDiRVatWMXfuXKpUqcLWrVsJDg7G1dWVNm3aULNmTSCnzcrDEvmAAQPk65UpU4auXbsye/ZssrOzKV68OBcuXABgxIgRlClThtOnT3PhwgVCQ0MpV65cvvPy9PTEaDTy+eefy3Wf+vbty9dff02ZMmWAnKfHevbsSceOHalXr568sHoSlnSgrsem4GpnRYbeTIbBhCk5BlNmKjbFyxG19CtcqzRgRVRDLq41smLFCtRqNQ4ODmzatEnO9p+QlpbGmjVruHz5MnZ2dtRq4oeqWHnMElT0sOd/pZzRqB9fBL8oCM9AGSInZYiclCFyKhyRkTJeBgfKYnWgEhMTcXR0pEaNGnTq1AmVSsXQoUMJCAggMDCQkydPyhI55C2muW3bNtmDcnBw4ODBgwQGBuLh4UHZsmUBqFmzJgsXLiQhIYEtW7bg5+eHSqXKs2gYMmQIc+bMkXei4uLisLKyYsaMGVSpUgWDwcDixYtRqVTcvHmTV199lf3799OxY0c+++wzrl+/LldFt7a2zlP1/GEsWQcqIlKNygge1pCqh4TsnAKjZdp+gCrlHndO7OTYHwu46mhHixYt6NChA1999RWXLl36x7WYjh49yuzZs8nKyqK4dwkSklLI/u47nCvVo8IbX2Cjs8PLTqKDj5litk91exZH1FpRhshJGSInZYicCkdkpIwXuQ6URRZQuR5UcHAwTZo0QaPR4O/vT3JyMuXKlWP69OlMmTKFTZs2UblyZQB69OjB4MGD6d27N3q9nuHDh5OUlCRf08nJicOHD8sfBwcH88knn2BnZ4ejoyMqlUp2pgoiJiaGUqVKkZCQIO9AVapUCTc3N7lo56xZs8jIyOC7776Tv87b25vmzZsTEhKS73Ut6UDdOxTFqlN38HHToVKpMHg6ctNGh21CBK90+4Sbjd+gax1vBrasAOSUg4iPjycgIOAfOVCHDh3ihx9+oGvXrkyYPIVfQlM5fzsR/fWjnFo+jZgtM2g66AfiUvUczrDn+3Y1cbF78bahhWegDJGTMkROyhA5FY7ISBlF0oGCHA/q2rVr1KxZk7JlyzJkyBACAwPp3r07R44cQZIkunTpwrp16xg7diwAEyZMYMCAAfTu3ZsWLVowZcoUypUrh1ar5ciRI0yaNIn27dsTHh6OyWRi0qRJvPvuuwwfPhx7e3uGDx/Ohg0bmD9/Ph9//DEAs2fPZvbs2XnmFhcXR6VKlVi1ahUGg4G+ffuSlpYmv/7jjz/SuXNnXn31VSZOnMidO3eIjIykSZMmBd6vJR0ovxpebLsUy4M0A55Otmh1OkrUacGVvWtwrPQajiXK0aScM3q9nszMTIYPH46Xl5csyv9dvvvuO2rWrElgYCCHrj/g4q37eDvZYF2vBTYaFSG/fUNK1AW8S1fl+r0H7Ll0h861Sz7VPVoCg8FAVlYWer2+wAKo+fG8C4A+L4SPoQyRkzJEToUjMlJGkXOgIGcXymjM8XJyC2kuXrwYW1tb5syZQ7du3QgICMDa2hqAgICAAh2o1q1bEx8fz6xZs7h37x46nY7Lly9z7do1Fi9eDOQ0HJYkif79+1OxYkVatWr12JzMZjMZGRksWLBArgU1c+ZMOnbsKM+jfPny8mP/Dg4OeHl50bhx4zxP5j2KJR2oMq62vNvQh4VHbhIZn469tZpbx3cAcHhGTl47vnj861xdXZ9q3Cc9dbjj+7++NwefapQXj+fdw+/fRvgYyhA5KUPkVDgiI2UUWQcqVyLv0aMHly5dkgtpTp06FRsbG4KDg+nfv3+BDtSjREdHy8dnj0rkuUyYMIF169bxzTffyMdzDxfSfJiHnwBUq9VPvJf09HR27NhBQEBAge+xdC88a6CNG5x9oOZW6lNfTvAEXpQefv82wsdQhshJGSKnwhEZKaPIOVC5EnlUVBR+fn7Url0bf39/srKyaNq0KYGBgTg4ODBnzpx8HaiVK1cyefJkwsLC5B0BrVZLgwYNZIk8KSmJUaNGcfToUXmB5OjoyLfffivP48qVK/LOEiCXUXi4mXBudfLccbKysnjrrbfYsWOHvKsUEBDwxAWUJR2oR8nMzmZLhZW0ad0KrVaLJElkZWVhY2NT6GIwMTGRuq81IdMINboOpMIrr6FGIvL0Ic6snYuNvQPqrBR6v9OLSZMmsehwFOvORsv+VVZqEutH9+CVrh9TtXV3bidk0LKyB8P8Kj3Te3wWGAwG9u3bR6tWrf7WlmxRO8ITPoYyRE7KEDkVjshIGUXWgQoMDKRRo0YcPnyYihUr5nGgYmJiCA0NZcGCBQU6UHZ2dqSnp8uhOTo6kpiYyP379+Ux7O3tGTx4MGPHjkWSJL766ivOnj3Lhx9+yIIFCwCoVq1avkcyD+9ISZKU52OTycTevXvzHMmtW7eOdevWFejSWNKByg+NKu+1H14kPonZvwWRnBCP71eLKFHyr5Y3lRu2pljJsmyd/AFVX23MkiVLeP/992lZzYedV+6TlGHEzd6ac5sCUalUVHitLWlZJqw1GlpX93oufwkUttAxGAzY2tri4uIi/pJSgPAxlCFyUobIqXBERsoocg7U5s2bGTlyJCEhIfk6UElJSaxfv75AB6pz58507tw5zzU/++wz2YHy9vbmlVde4ZVXXpFfb9euHdWrV2f16tXyAurhZsKQ40BlZmZy8OBB2YHaunVrHgfK3t6e1NRU+euTkpLo3r07H3/8sdwY+VEs6UA9TEK6nmv3knnrrbee6jp7J75T4GtXT+U86Zh7tJofq0f89b3Z82WBb7MohblKwjNQhshJGSInZYicCkdkpAzhQFnIgcqPM2fOcOvWLWxt/ypM9CwcKMhZeBkMBsxmc74LKEs7UNkmOBij4lKiigzji1u88t9EqaskPANliJyUIXJShsipcERGyhAOlAUcqI8++oiTJ09y/vx5eYGk1WoZOnSoPI9/4kCNGTOGnTt3cvPmTbm/3sGDB+nZs2eBW3uWdKAMJjPf7bjGpYwHODpZUdLWCumTqZwO+hY7r3L49xrAj4O7Ex97j/nz5zN//nxGjRrFl18+vjXUqKUfsekSbYf98FgVcUmS2DzpI5w9SnB230Y0ahVZWVnExsai0+nw8PAgMcMAkoSLnTXq51yFXMkRnvAMCkfkpAyRkzJEToUjMlKGcKAs6ECFh4fLFcI1Gg1WVlakpKSg0+nk9/wTB+r69evcvXuX9PR0VCoVZrOZpKSkJ0rklnSgTt6M53hkIl5OtthZW2GWzEQdWIOjZynajPyFRL2KyHQrWtaty2+//YanpyfTpk1j+PDheHp65rnW4AH9Gdz/IyKvXKRG3dfyvBZxYi+p0dcZMOJr3N3+KoHwcCubp6yM8FwQnoEyRE7KEDkpQ+RUOCIjZQgHygIO1IEDBx4b19PTkxkzZjBmzBjgnzlQK1eulN+f60AZDAa2bNlS4CLKkg7UgauxGE1mbLVqzJKZjKQH3A87TeP3vsTeXseDrEz2X42lSfmc1c3gwYOZPn06K1asYNCgQXmu1ffdXswPWsTJ374gpnl3KjZsjVoyE3F0J1EH11GhQWu+6Nf9P3E2/1/2DJKSkjh37hxqtZpXX331qZ4cfJY5SZLE3aQsUrIMuNpZ4+38gvf5+Rv8l3+eniUip8IRGSlDOFD/ogNlNpvJzs7GyuqvW3pWDlRycjLVqlUr8HVLOlBnI9RkZkCcKadaemrMTZAkJHtX4uLiyMqG82GpbOOG/DVOTk4cOnQo36bKo4d/yuyFyzkesp6be5cDoLVzpF7bNxj8Xg8OH9j7VPN90fgveQaZmZksWrSI/fv3yzurdnZ2+Pv788477zzVf6U9bU530uFwjJrb6SpMUs6TomUcJJp6mfF+eg3wheG/9PNkSUROhSMyUoZwoCzoQN26dQu9Xo+NjQ0pKSlP7UDl1oG6ePEi169fx9HRkczMTIYNG1bg/VrSgbq8K5z4K3F4uuccTTraWIFKDakP8PT0JPNBJrUrudO+fVUA4uPjSU5Opnnz5gX2wgsI6EZKSir7j5/GZIZmDV/Fw8Xxqeb5ovFf8wyysrJo27YtFy9e5Ouvv6Zr164YjUZWrlzJzJkzMZlMrFmzRtF/EDzMs8jpwt1klm6/xgOTHs9iWmytNGQaTNxJN7Av2YaxTatSxevl/vn6r/08WQqRU+GIjJQhHKh/wYHKzMwEICEhAZVKRe/eveX3PE0dqNz+eLklDbp37/5c6kD5VivOgbD7ZOrN2NtYoXN2w7NqPS7vWUmJem3QaKzy1GKaOXMmKpWq0B0Jd3c3urf3e6q5vQz8VzyDRYsWcezYMY4ePSpX2gd45ZVXaNq0KZ07d2bPnj106NDhH13/n+YkSRJLjt0mId1AuWL28u6urdYKZ501UQ8yWHbiDt8F1Mqz8/uy8l/5ebI0IqfCERkpQzhQFnSgVq5cSb9+/diyZQsjR45k69at1K1bF3i6OlAhISH4+flRo0YNzp49a4mYFFGvjCvNKnmw71oc9noTzjoNFfze4cT8L9k5bQAd3h9CZZeanD9/ntmzZ7NgwQKmTJmCu7v7M5+LJEncuHEDvV5PuXLlsLW1xWgyE5+mR6UCDwcb+em89PT0Zz7+3yG3mfDDC/GXmd9//5127dpRs2bNx7L19fXllVdeYf78+bRs2fJvXfdpc7oak8LlW/dxs7XCqM967HVXrYmzkTFcvuVF2WIvb5X3/9rPUy5FrfK+QPAseakdqODgYPr168fKlSt5/fXXGTBgAG5ubvLr/9SBOnDgAB07dqRu3bp5nkIrCEsX0vysVXk8HLTsuXqfmORszO7laf7ZLG5sms2qKZ+yasqnwF8S/cCBA5+peCdJEosXL+aHH34gLCwMyGk23Lzjm7g17839zJw8S7vp6FjLG79qHjg4ODyz8QV/8aRcz5w588LmvjOfhteC58+zbp4tBOnCERkpo8hK5LkO1MWLF7ly5QqjRo1i48aNjBs3Lo8D9e2331K5cmUqVaokO1Cvv/46/v7+XL9+nZSUFHnxY29vT6NGjShbtiz37t3jjTfe4OjRo/J4oaGhpKSk0K5dO3kejzpQZrMZKysrGjZsiFarpWHDhty+fTuPAxUQEMDGjRsBuHr1Ki4uLnK5hIcXZw9j6UKaAF7AGx4Q6wBScfC09cC+8QRu3LhBTEwMdnZ21KhRA61Wy/bt25/JmLksX76cNWvW0LhxY3r06IGtTsfa/afYsmopdiF/UrffRNRaG04nJnHmegy7j5if6fgCgcAyWKp5thCkC0dkpIwiJ5HnOlAHDx7kww8/JDg4mLi4OHr27Mn169cJDQ3lxIkTjBgxglOnTlGvXj0qVqxIXFwcarWaZs2aYTAYiIyMJDs7W64EnvskXHZ2Nrdu3ZLHy23dAuQ0wV20CHjcgdq6dSuSJNGiRQuOHTvGoUOHcHd3x9HxL8H1ypUrmM05C4Dk5GR27tyJt7c3LVq0yLd0Avy7zYT/bbHuypUrrFmzhgkTJsjFOU9EJXBQ14Tmr7Tl4IzBpF85SM12Oe1hEtL1hOkljl65RdXnKA7/02bCLyo///wz3333HcePH6dMmTJ5Xjt79iy+vr78+uuv9OzZ829d92lzMpjMjFh7gVsPMijppsvzmiRJ3EnMompxR77rVuO5F199Gv5rP0+5POsjPCFIF47ISBlFViLfvHkzQ4cOJSQkhKCgIMxmMz4+PkCOcD137lyWLFlCRkYGYWFh7N+/n2+++Ub2lWbOnJnnerNmzWLSpEkEBQUxadIkypYty507dwCoXr064eHhbNiw4TGB9mEHKjk5mVOnTmFra8vevTmP6l+9epVq1aqh0Wjko7orV64AMG7cOGbNmkXz5s3ZsGHDE+/3324mnJWVhV6vL1BqV4IkSTxITMZklvB0dylQ8P3999/x8PBg8ODB8mJ0z4U7ZGdmULpCVcq82pKwkI1Ua9UdACcriVspGRy9kUgtn/x37P5NntX34Hm7Ip9++ilLliyha9eu/Pjjj3Tu3Bmj0ciaNWv4/PPPqVu3Ln369Mn35/BJPIumy31bVuOHXdeIyzTj6WiDjZWGLIOJuNRsXJwc6etbDTe3l7AK60OI5tR/DyFIF47ISBlFTiI3Go0sXLiQUqVKsX37dtl/2rZtG926dUOtVrN69WrF/tO6deuoXbs2e/bsecyBunbtGu3bt39s8XTgwAF8fX2JjIykbNmynDp1CpPJRHp6OqdOnaJu3bpUrVoVDw8P4uPj8zzZ9Hf5t5oJ517zaZsJ/xMKOr7MZWn/Fnk+PggMz/+tLyXP2hX5uzg4OLBr1y769u3LG2+8gZWVFZIkYTKZaN++PYGBgajV6r/98/YsPIMm5V0xtKrA8uO3uZuUidEsoVWrKO1mx3uvlaauj9NL73sIb0UZIqfCERkp42VwoFTS02xjFMCGDRsICAhgypQptGjRgiZNmqDVatm5cyfbt29nzZo1eHp6UqNGDcLDw7l79y7jx4+XSxCsXLmSTz75RF6IaLVa7O3tqVq1quw9rVixgvfeew8rKyv0ej2lS5dm2LBh9OnTB2dnZ06cOEG3bt3Q6XRERESwYsUK+vbtS7NmzTh9+rRcByozM5NKlSpx9epVef6XL19m1qxZLF++nMzMTHQ6HX/++Sd16tTJ937HjRuXrwO1YsWKZ+ZAPUzXrl2f+TUFT6awXch/kxs3bnD16lXUajW1atWiZMmSz3tKABjNcDMNMo0q7LUSPvZg9ffKUgkEAsFzJSMjg169epGcnFyogmORBZSvry8hISHExMQwevRoHBwcmDdvHp06dWLUqFE0bNiQIUOGUL16dUJDQ6lbty5JSUnY2toybNgwNm3axJAhQ4iPj8dgMCBJEhqNho4dO7J27VoAXnvtNY4fP/7Y2H5+frJ09vBTeLkLqKZNm3L69Gn0en2BC6iyZcty8+bNx65dUFT57UD5+PgQHx9vEQdq8+bN/8jFWL95K/3e603VN4bzauuOeY7tzu0I5uLG+Yz/NZhPe/4l4m/bto133nmH7du389prOf3ztl+M4deDNyhmK7F9Qh9K/q8RDXvl7DfpjSbiUvQMb1OJ5pWKPYM7/mc8a2fleR/hWQrhYyhD5KQMkVPhiIyU8TwdqGLFiilaQFnkCK9+/focOHCAEiVKYDKZ5DpQmzdvJigoCEmSWLRoERMnTpT/6/nixYsF1oE6dOgQzZo148iRI/LnWrRoQVpaGsWKFaNOnTrMnDmTt956i6SkJPk9DztQXl5e6PV69u3bx8mTJ+U6UMWLF+fatWtER0dTokQJAKKiomjSpAlXrlzhp59+YujQoXmu+yj/tgP1T68997cFOJaqzCutOqF5pHxDnbZvE/HnJpYtXszwd/5aXHXs2JF69erx3nvvMWvWLNq3b0/Lal6s2n2MPb//gCErg+qte6BCRXq2kfh0Pf8r6UKTSp5otZpndr8Po2QxI5yVv4fwMZQhclKGyKlwREbKKFIOVG4NqB9//JG0tDRWr14t14EaOnQoK1asYMCAAfTp00euAxUWFvZEDyouLg5AdqYAjh49ip+fX54il23bts3TyuXhHai6devKbVtyF0/Xrl2Tn/w7fvw43bp1A2Dfvn1cvnxZFt8L499woC7fS2H35ThO30ok+JOnc6CCB/kW+Fr40R15nkp8mLfffjvfz28a926ej/8E5v7j2RWOEh9JeAbKEDkpQ+SkDJFT4YiMlFEkHagNGzbQs2dP4uLiaN++PfXr12f27Nn4+/sTEhJC6dKluXr1KsuWLWPOnDlynSa9Xs/gwYNxc3Pj+vXrrFy5ktDQUPkfSxsbG27duoWnpycAZcqUoW7duuzYsYPs7GxKlCiBr68vS5cuJSMjgwsXLhAQEICNjQ3Xr18HoGHDhpw+fZoWLVpw9OhRsrOzcXd3x2w2y61k1qxZwzvvvINKpcJgMODs7Ex6ejqJiYkF7nxY2oE690DFnrtqskxgo5E4NLZz4V/0H+ZF8pEEAoFA8N/huTpQnTp1wmw289NPP1GzZk169OiBh4cHgYGBtGjRgq1bt3Lu3Dm++eYbfvnll8d64Q0dOpRRo0Zx8eJFTCYTHh4elCtXTq5/Ex4enjPxJ/TVysjI4Pjx43mewgMYP348kyZNQpIkuTnxrVu3uHfvHjNmzJArmScmJj52zQEDBjBv3rx8x7OkA3XzQQafr72A3miiuJMNSBCy8Dtun9zFqx9+R7Fy1ZnYpToVPBxISUmR+w2ePn0aK6u8G4yffjGa4GVLaDt2OS6uznleS0+8z8ZvetG29yCCZ457qjlbGqVHeMIzKByRkzJETsoQORWOyEgZRdKB2rx5MwAjR47EaDTm6YW3bds2dDodZcqUoVu3bvn2wvP19eXEiROPXffRXnilSpUiIyODBw8eyO9p0KABZ86cQafT0bJly8ekb41Gg9FozONAPdoLz2w2o9H85e5IkoTZbOaXX36hXr169OvX77G5WdKBOhiRQGqWkbLudqhUKvT6TO6e3ke1Vm9Qs15joh5kcPJuNnUrlcLFxYVff/2VunXrcuTIkcf6CU78ehSrg5dx6PdvaNz3G7xKlUGlUhF/K4L988dibe/Mt6OG4uLi8lRzfpEQnoEyRE7KEDkpQ+RUOCIjZRQpBwr+vV54j+5CqdXqPIumf9IL7+jRo5hMJvnjoKAgfv75Zz744APZkXoUSzpQl6OTsFKDhIQkSaTG3sWQmUap/zVFQsLaSsWl6CR5nNzH2o8ePcrrr7+e51olSpRgw4YNdO/+JtvH9sChZCUks4n0ezewcyvOr0vXUrdiSYueOUuSxL59+/j11185f/481tbWdOjQgf79+8s7hQ9zLzmLfdfuc/pmImYJqns70qqqJxU8nrwLJTwDZYiclCFyUobIqXBERsp4GRwoi/bCi4qKws/Pj9q1a+Pv709WVlaeXnhz5syhcuXKAHIvvN69e7Ny5UomT55MWFiY7EDlHrnl/iNrZWVFcnIyxYsXJzExEWdnZx48eIAkSXLtpkd74anVanQ6HW3atJHrQOWK5bnjxMbGMmPGDLZv3y4HaWVlxa+//ppv42GwbC+86LtqUlJBa0gFIP3/F2cP7segdosjKQtiTSls25ZTmd1kMpGSksLNmzcL7HMV+NsvbNl3iHOXriCp1FTr3I0uvq/hICVbrDcWID99uXHjRtlhy8jIYP78+cybN48xY8ZQq1Yt+f2RqbD5lppUvQqNWkIFHA9XsepwGK1LmqntXvjps+g3pQyRkzJETsoQORWOyEgZRbYX3uHDh6lYsSJDhgwhMDBQ9nNCQ0NZsGAB69ate8yB6t27N3Z2dqSnp8tbaY6OjiQmJnL//v0840iS9MR2Jo/2wnv46wq6xpEjR/jf//5Hnz590Ol0TJw4kSNHjvDBBx+wcOHCfMexZC88/dlo5oXcwN1Vh0atwuzmjp27N/cvHaFak3ZkJmbStUk52tfNKQexadMmUlNT+fTTT6lbt26B1w0IyH83zZKsWbOGjRs38tNPPzFo0CB5JzAtLY0333yTH374gYiIiJzFcLqe4FXnUdlkU83LFvX/v1eSJGJTsglNV/OGfw0qF8//iUHhGShD5KQMkZMyRE6FIzJSRpHuhTdy5EhCQkLyOFCLFy/G1taWpKQk1q9fn68DBY/XgYLHHSij0Yizs7Nc4gDyOlCQtw4U5PhNmZmZHDx4sEAHavTo0XnGbdeuHXXq1GHp0qUsWLAgjx+ViyUdqNbVvdl8Poa7iZmUctWhttJQpnFHrmz+HbVbaV5t15NGZR3R6/WcPHmSgQMH0qxZM2rVqvXc2488yuzZs2nRogUff/xxnm1Sa2trfv31V6pWrcrixYvp378/+y7d5d6DJEq52iEZ9Jgeuk4xW7iVkMb2c7cp27JivmMZDIZn0jPwefJvFu8UPoYyRE7KEDkVjshIGcKBeokcqPzIyMiQZfL8FlCWdKAcrVV84V+JKduvcSUmhSyDiSubfwfgxo5AbuwIZO3QvF8TFxeHg4PDU41rSZ40txEjRjBixAhF1zkIfPGM5vQi8m8sgIWPoQyRkzJEToUjMlKGcKBeQgdq4cKFLF68mLt373Ljxg3Kli3LjRs36NChQ4ErU0s6UJDTX+z+fTXZWSpML+luiuDvY0kf7VGEj6EMkZMyRE6FIzJShnCgXiIHSq1Wc+nSJVJTc6TtGzdu0L17d5YuXVrgOJZ0oOLTslm55gKSbTa1vWxRA6Z273Nt5xIqdxlC9eYdmfpGLYo72XL16lXefPNNvLy82LVr1xNrZT0POnXqhNFoZPv27Y+9duvWLV555RV++OEH+vbtK/fbK+GS4349jCRJ3E7IpGvtEvRrWjbfsZ51L7znwb9xhCd8DGWInJQhciockZEyhAP1EjpQ77//Pu+//z4hISH4+flRq1Yt1qxZ88T7taQD9ef1GGJTsinjZodarcJoMnDr2HYqNH6dxp3f4eaDDELvZfNOaS9ee+01fv/9d15//XUuX75MkyZNnmrsZ83IkSPp3Lkzs2fPZvTo0fJx6IMHDxgwYADu7u589NFHODg48Pqrdmy/lszdpEx8XO3kRZRZkriXnEUxV2e6NKyIi0v+x4GiF97fQ/gYyhA5KUPkVDgiI2UIB+olc6AOHDhAx44dqVu3Ll5eXoXeryUdqFNRCWjUOQuHB6nZxN2JJDMpDvf/tSIxOorIvev5dnUsu6r50L17d/z8/ChWrBg7d+7M0zvwRaBdu3Z8++23jB07lqCgIPz9/UlOTmbTpk3Y2tqyefNmbGxsMBgM2GtVDPeryPRdYdxMSEejUqFSgdEk4WpvzcAW5SjtYlNgvsIzUIbISRkiJ2WInApHZKQM4UBFRfHRRx9Rs2ZNqlatyrhx4x5zoDp06ADkdaC2bdtGbGwsq1evZv/+/WRnZ+Pg4ECjRo3yOFApKSmMHDmSfv36sW/fPk6ePCnvMhXkQNnZ2fHRRx/x66+/YjAY+Oyzz/I4UPv376djx4589tlnXL9+neTkZGJiYrC2tsbNzS3f+7WkA3XzlpqkFIhJTCPbBPrEdACuHNrOiQt7sdI54l66EgcOXGfJkiVUqVIFo9HI1atX/1WHRimvvPIK06dPZ8eOHezatQtra2sCAgJo06YN8fHxj825vStcUamISlVhkqCUk0R1V4n0iHi2RRQ+nvAMlCFyUobISRkip8IRGSmjSDtQY8eORaPR0K5dO3r27Mn169cJDQ3l7Nmz7N69m2HDhgE5If3+e87TZdHR0Xz55ZckJCQgSRIajQZJkqhWrZo8hlarpV69esyaNYvp06ej1Wpp06YNO3fulN+TnwPl5eVFWloaDRs2BHKaEj/smsyfP5+MjAy+++47+XPe3t40bdqUP//8M9/7taQDdefPSM7tv44kSdjbWmHvXZrb1jpSL+ylWPN3cG38JgN8KzOoZQVCQkLo3r07KSkpvPfee7Rt2/apxrYkn332mUWvLzwDZYiclCFyUobIqXBERsoQDlRICJ06dQJynihSq9XY2NiQlJREUFDQY1+Xe7SmVqt55513CAgIwMfHRy5kGRQUxKRJk/D29kaSJEJDQ1m6dCn169fnxIkT9OnTBzs7uwIdKC8vL+7cuUPx4sXZu3cvzs7ODBo0iJs3b8pHdfPmzaN58+bUr1+fqVOncu/ePR48eICPj0+B92tJB0pnbYVZAo1ajRqQNFagsQKVCjufGqg01thaW2Ntbc0rr7yCm5sbKSkplChRQvxyIjwDpYiclCFyUobIqXBERsoosg7UlClTmDhxIqtWrWLu3LlUqVKFrVu3EhwcjKurK23atKFmzZoAtGnTRpbIH23YW758ef744w82bNggu0YZGRk4OzvTs2dP+T3jxo0jNja2wHnVrFkTvV7PoEGDaNWqFQAfffQRx48fx8oqJwpXV1cGDBgA5NQr8vDwoGfPnkyfPr3A61rSgboel4qrnZYMvYkMgwlT4j3MmanYeFXg1vLROFeqx/KIBpxZYWDlypXY2tri5OTEho2bSNaVIPTCFY7v3owmO4malcrxzjvvPHEx+F9BeAbKEDkpQ+SkDJFT4YiMlFHkHShHR0dq1KhBp06dUKlUDB06lICAAAIDAzl58mSBEnmuA1W/fn0cHBy4dOkS+/btw93dXXagXF1dCQsLy+NAhYWFoVarMRgMaLVaJk6cyNixY4mMjKRs2bKkpaUBsGLFCnx9fTEYDHz//ffY2dkREfGXUHP58mX0ej0JCQnEx8ezZMmSPD3aHsWSDlREpBqVETytIUUPicYsAMq27YcmLY7bJ3YSumU5N5zsaNeuHa+//jrDR3zBioOXmL/9Q2JPbkVja4+tS3HWrV7Jt9+OIyCgG717937hyhxYAuEZKEPkpAyRkzJEToUjMlJGkXSg/Pz8CA4OpkmTJmg0GvmJq3LlyjF9+nSmTJnCpk2b8i2k+agDZWVlhdFo5I8//pDH6Ny5Mz///DM///wz06dPx8rKCltbWzIzM4mPj8fb21teSeZuycXExKDVasnMzMzjQFWoUIGYmBgAzp07R+PGjf9WiJZ0oGIOR7Hy5B1KuetQqVQYijsSZWuP9f1rvPrGADwbdiHglRL0b1EegF2HjpOU8ABtfCzxlw5T/62hVG7RhWxJS8yDZFSXtvLHynk0aNBA9s/+iwjPQBkiJ2WInJQhciockZEyirQDde3aNWrWrEnZsmXzFNI8cuQIkiTRpUuXAgtpPuxAZWRk0LNnTzIzM4mOjpbHKF68uNznTKPR4OjoKO8w5ZYmmDBhAhMmTMgzN5PJRFZWluxADR48mIsXL8qvnzp1ig8//JAWLVrg6OjI9u3bmTlz5hNrKlnSgfKr4c22i7HEpxko7mSL1lZHiTotuLJvLY6VGuJcqhJNyjuh1+tJT09n6GfDsHZ0IyHsBDXa9qJqy5ymwTqVieJOtiTV6UxXKYXp06fz4Ycf5jvv582zLCApPANliJyUIXJShsipcERGyihyDhTk7EIZjcZ8C2nOmTOHbt26FVhIM9eBunz5Mr6+vgwZMoSkpCTWrVvH4MGDAVi1ahVDhw5lypQpxMbG4u3tTdu2bTlw4AAeHh75zsnBwQGz2czEiRNlB2rhwoVUq1aNrKysPGPn0qZNG6Kioli/fr1cxPNRLOlAlXax4f1GpQk8HEVkfBp2Wg23juU86n/k50EAbC+gIdzFHcu4uGNZgdd2d3d/qrlZimfRA054BsoQOSlD5KQMkVPhiIyUUWQdqGdRSPPSpUu0atWK999/n8mTJ9O7d+88dZiys7OxtbVFq9VSqlQpAMLDwzGbzZhMJtRqNQcOHMDX11d2oHJ52P1R4gHltnV5eJH0MJbuhacB/N3gfIKayNSnvtwLz7OsXyU8A2WInJQhclKGyKlwREbKKHIOVK5EfvHiRa5cucKoUaPYuHHjY4U0v/32WypXrkylSpVkB6pWrVp8+eWX7Nq1C4D169eTmJjIypUrWbFihTyGTqdj8uTJfP/993h5eeHk5MTt27eRJEl2oCIjI7G2tiY+Pp6yZcuSkJAAQN++ffnkk09o1KgRqamp2NvbY2trC+S4VefPn+fu3btUqlSJfv36sWfPHmrUqJFnEfYwlnSgHkWv17O5wkoaNGnGpB0RhMel4Wxl4tDPn6HPSMHT7yOytQ7ErPyaOt0+IfLYTvQZqbw+ej7WDq7cTcqkZtZlfpn4BSdPnqRixYrPdH7PgmdxhCc8A2WInJQhclKGyKlwREbKKLIOVG4hzYMHD/Lhhx8SHBxMXFxcnkKaJ06cYMSIEZw6dYp69epRsWJF4uLiOHXqFAkJCZjNZgAiIiLkJ+RGjhxJjx49+OWXXzhz5gz29vakpaVx+/ZtIOe4bffu3bIDVa5cOfR6PcWKFQNg2bKc46yOHTty4MABQkJCcHFxoVKlSn8FYmWFWq1GpVJx9epVRo0aRbNmzdi0aVOB92tJByo/VCo4EpXC9fvplHK149bJXSTfi6TDmAWYXUoTEZdGokdZIk/uo+WAyWyd/CHhBzdRvNnbOEhZ7FzxG82bN89TmNRS/BsNcZ+E8AyUIXJShshJGSKnwhEZKaPIOVCbN29m6NChhISEEBQUhNlslmsP2djYMHfuXJYsWUJGRgZhYWHs37+fb775Ri56+agDVapUKZydndm3bx8AS5cuZeDAgUyfPh2DwUBsbCw//vgjmzZtwtHRUXagWrZsKffBS05O5sCBAwAsXrwYFxcXrl69SrVq1bC2tpYLaa5btw6AQYMGMX/+fEaOHMnkyZOfeL+WdKAeJj4tm8t3k3jrrbfyfX3r5A/zzgvYOPYdAC5sXcyFrYvl125cj8DBIf9GvM+SZ+Ez/ROEZ6AMkZMyRE7KEDkVjshIGUXagVq4cCGlSpVi+/btsv+0bds2unXrhlqtZvXq1U9sJPywAxUdHS1L3vCX/wTIDpS9vT2RkZH06NEjX//p1KlTmEwmtFote/fu5Y033qBq1ap4e3tz7949GjVqlGfsxYsX4+rqWujiCSzvQGWZICRaxeUkNZnGp77cv8rz7scnPANliJyUIXJShsipcERGyniRHSiVlLtF8wzZsGEDAQEBfPLJJ8yfPx9/f39CQ0NZs2YN27dvZ82aNXh6espP4On1erkG1Llz5/I4UN7e3kRHR7NixQpat26Nh4cHo0eP5vfff6d69eqEhYVx//59TCYTAMePH6dBgwacOHGCN998E61WS0hICCEhIfTt25dKlSrJTYYbNWrE8ePHcXFx4e7duwAsWLCAAQMGyCL6J598wldffYWNjU2BT/fltwPl4+NDfHz8UztQeqOZyduvcvR6Ak46K5xsrLgWeoDQoHHYeFWgrN97ZF7cw4ObVyj1vyZc3buGGm3fwbVZL7rV8abbKyXp2/ttEh/Es3379meyoPs7PK8jPOEZKEPkpAyRkzJEToUjMlLG83SgihUrRnJycqH/fltkB+rnn3+WJ/JwDajAwECGDBnCtGnTmD9/PitXrgTy1oB61IHKXdi8/fbblClThqioKL755hsWLlzIwYMHgZwn6UqVKsWdO3coU6YMAA0aNGDx4sVyxXHI2RlLTk7O40CpVCq6du0K5BTR/OSTT+SxTSYT8+bNY968efLY+WFJB+p4VDyhN5PwcrbFztoKs2Qmcv8aHD198O49Fay0lHSy52boXjzKVkPX5SPObllI62Zv0qFuRe6En+Xggf38/vvvlChR4qnm8jIiPANliJyUIXJShsipcERGyihyDlT9+vU5cOBAgTWgFi5cyNdff11gDah+/frJ/tOHH35IUlISV65ckR2okJAQMjMziYmJwWAw4O3tzfz58xk1alSeXaKHHajz589jNpuZNGkS77//PoDsQOX2wVu1ahWvvvoqJ0+eZNy4cWzYsIGJEyfSo0cPLly4UOD9WtKBCrkWi9FkxlarxmAy8eB+HPHhZ2j43mi0Lg7cirxOVmoiXjVe48+gSXjX8wckpLMbWPDjIebOnUuLFi146623itSZu/AMlCFyUobISRkip8IRGSmjSDpQ/0YNqE2bNlGvXj1mzJjB0qVLsbe3JzMzk9dff11+Au+f1IB62K3KRafTkZWVxalTp2jZsmW+92xJB+pchJrMdLiank6KAdJjc544vJ2UReovn5F6868q6hobO+5fOIhkMrF37SKO2dvTtm1b3n77bfbs2fNU83hZEZ6BMkROyhA5KUPkVDgiI2W8yA7UM19A5daAioqKws/Pj9q1a+Pv709WVlaeGlBz5szJtw/eH3/8wTvvvINGo2HWrFmsWLGC6Oho+bgP4MKFCxw7dozw8HCysrK4d+8ekiRx/fp1+T2P1oBKS0tDrVYzaNAgBg8ejMFgwM7ODjs7O3nR1LZtW2bMmEGFChW4ffs2JpOJbt1yWqHklkrID0vWgbq8K4xroXcwGM2oNSocXT1BpeLetrlYu3pR+o2v6NrOl6YlVCwLnM+mdWtQq9V8/vnnjBkz5l93nl4UhGegDJGTMkROyhA5FY7ISBlFsg5Ubg2ow4cPU7FixTwOVExMDKGhoSxYsKDAPnhLlizJcxyW60ANGDCAHj16ADluktFo5Pbt2+h0Ovz8/KhZsyYzZ84kMzMTnU73WA0ogEd9+Uc/bty4MSqVihs3bsify+2v9+DBgwLv2ZIOVAlXezINZmw0amys1EiOzljZu2DKSKFMr8lI9q7UqFSeN1tU4M32frz66qucOXOG/v374+zs/FRj/xcQnoEyRE7KEDkpQ+RUOCIjZRQpB2rz5s2MHDmSkJCQfB2opKQk1q9fX2AfvI0bNwLk60DlYmdnh1qt5v79+/LR3pUrV5gxYwZ37tyhUqVKefwnyOmDJ0kSc+bMecyByi2RcPXqVcxmMzdv3sTKygpXV1d27dpF165dHyuz8G8Rm5yFTqvGYJTIMpqRslIwpiWhstJyM/gbPBp147DtXTwTL7B+/XrOnDmDWq1m165dcqYCgUAgEAieLS+lA2U05hRDmjRpEqtWrcLe3p7q1aujVqvlvnj/xIGqUqUK7u7uBAUFMXr0aEwmE1OmTMHKyooOHToUeM+WlMhjUjLxcLAhLcvAg3QDmQ/iAAnX5u+Scmwtdzb+xJKNsISclXP//v3Zvn07kZGRRVpSFKKmMkROyhA5KUPkVDgiI2UUSYn8YQfqo48+IjU1lSFDhqDVagkICMjjQHXo0IHw8HB8fX0ZP348vXv35uLFizRv3hwnJyeWLVvGzJkzMRgM8q4R5LRbMZvNBAcH89prr7F//37Cw8OxsrIiODiYfv36FehAff3116xbt479+/eTlpaGRqORa0g5OjpSr149xo8f/5gUbmtrS2xsLJ6eno/dsyUl8sQYNfcSVRjNoJLA1j7HqUo8vBKNtQ73Rm9QxsOJqg7ZnD9/nl9//RWNRkN8fPxzL2L5IiBETWWInJQhclKGyKlwREbKeJEl8mdeSLNTp06kpqZy+PBh7t69y+jRo3FwcGDevHk0adKEAwcO8Pnnn+Pu7o6rqyuhoaHUrVuXpKQkbG1tSU5OzncxolKpmDVrFoMHD8bf35+QkBAcHR1JTEzE3d2d//3vf+zdu5e9e/fSqlWrx3agVqxYQZ8+fahcuXKeQprHjh3D1dWVu3fvkpmZSfHixcnKykKlUlGuXDmcnJy4cuUKderU4c8//8z3ni1ZSHPpsVtM3RGGtUaFjTbnCcPz37+FMTOFSoMDwcGDoX4V+ahpOcxmMw0aNOD8+fNcuXKFChUqPNXYLzNC1FSGyEkZIidliJwKR2SkjCJZSPNhB6pEiRKYTCbZgzp8+DBJSUk4OzuzaNEiJk6cSMmSJQG4ePEi/fv3Z9iwYYwbNy6PAzV58mQGDRrEunXrGDx4MN7e3ri7u5ORkSF7UFeuXKF69epyz71HHSgvLy8MBgPXrl1j1apVdO/eHYASJUoQHR3NsWPHuHTpEjqdjqSkJLkcwt27dylVqhT/+9//CrxnS0rkiZlGbKzUmMwSBpOElJWGMTPniPDuxp/wbNGbm7ftiIyEoKAguV7V0aNHqVq16lON/V9AiJrKEDkpQ+SkDJFT4YiMlFGkJPJcB+rHH38kLS2N1atXyx7U0KFDWbFiBQMGDKBPnz6yBxUWFpbHg3rUgYKcZsC5HlSTJk1YsWIFTZo0Ydq0aSxduhRJklCpVLi7u8tzeXgXqm7dulhZWWE0GvHz8wPg2rVr3Lt3j+LFi3P06FGsrKxQq9V53Kjly5cDOcVBC8KSDtTdxAyKO9qQkm0kMUNPZnwMmE24texD8rE1RC0ZybQlMA3QaDT06dOHvXv3cu3atSJ9xi48A2WInJQhclKGyKlwREbKeBkcqGd+hLdhwwZ69uxJXFwczZo14+LFi7z++uts3LgRJycnSpcuzdWrV1m2bBnffvstJUuWpFKlSly6dInBgwej0+nkOlAmkwkfHx9atmzJwoUL2bZtG/7+/qSlpVGsWDGys7OxtraWHSYrKyvefvttFi5cyIkTJ+jRowcajYaDBw9SsmRJWrVqxf79+3F0dJTrQJUvXx6VSoWvry99+/alTp06NG7cmDt37hAVFYXRaESlUnHnzh28vb3zvedx48ble+y4YsWKp3ag1kWqOf1Ahd4EZgmMqfFEze2LxsENsyELxwp1Ke7iSGldNmFhYURHR6NWq+nVq5dcw0ogEAgEAkHhZGRk0KtXr+dzhBcYGIifnx8xMTFcvHiRDz/8kODgYOLi4ujQoQNr167liy++wM3NjREjRnDq1Cnq1atHxYoViYuLIyQkJM9uTkREBBEREeh0Ovz9/YGckgR2dnby+zw9PWnRogVVq1Zl/PjxzJs3j4yMDG7evElkZKR8TFhYHaiqVavy/vvvs2jRIqysrLC2tsZgMDBkyJACF09g2UKa8UdvcmxXOFZaFbZWarArwW17F0wZyVT45BfUriUZ2roSHzUri8FgoH79+ly+fJkvvvhCLlRaFBGegTJETsoQOSlD5FQ4IiNlFMlCmps3bwZg6NChSJJEUFAQZrNZdpNyi1wuWbKEmjVrEhYWxv79+/nmm2/o06dPnoVIrgdVqlSpPEUhd+zYQVpaGuXKlctT9PLKlSuMGzeOO3fuPOZAJScnyxL4rVu3cHFxketAeXl54eXlRWJiIkuXLmXbtm20bt2aDz74gNOnT8vNkQvCkg5UmsGMlUaF2Qwmk4RkyMSUlQ5mM3EHllC8VV9Ss8uRnZ1NYGAg4eHhQE7vvxo1ajzV2P8FhGegDJGTMkROyhA5FY7ISBlFyoGCHA9q4cKFlCpViu3bt8t1oLZt20a3bt1Qq9WsXr26wDpQkNeDio6OlotdQk4vvAoVKhAREYG3tzeOjo507tyZBg0ayLWgHn0K79SpU5hMJrRaLXv37uWNN96gatWqeHt7c+/ePRo1asTu3bsxm83cvXuXKlWqEB4eTp06dbh9+7a8AMwPSzpQN+PT8XKyISXTSFKmgczYaDAZcG36FknH15N65RBfzoUvyXlSsXv37hw7dozz58/LonxRRHgGyhA5KUPkpAyRU+GIjJRRJB0oyPGgAgICmDJlCi1atKBJkyZotVp27tzJ9u3bWbNmDZ6entSoUYPw8HDu3r0r14EC8vTDy12EvPfee/zwww94eHjQrl079u/fj1qtpnjx4qSkpJCYmIhKpaJp06YcPHiQEydO8Oabb6LVagkJCSEkJIS+ffvy/vvvExwcjEqlkq/t4eHBvXv3mDp1KmPHjs03wKVLl8rzexRLOlBrI9Wcf6Ai6/8dKENSLDd//RAr1xIYk2OxK1EZFycHPLR6bt68SVZWFpIk8eabbxbpBZRAIBAIBH+X5+pAAfKRV79+/Rg9ejSffvop8+bNY/bs2YwaNYpp06bRsWNHqlevjkql4u233+b27dvMmDGDYcOGPdYPD2DJkiVs2bKFBw8eYDabUavV1K9fn3PnzpGdnY2rqyuJiYl89dVXADRo0IDFixfj6+ubZ0GU33ox93Nms1l+b4UKFfjf//7HhAkTqF279hP7ylnSgbp/9CYndoVhZaXCVqtB0pXijp0zxqQYyvb9Ea1XZT5rXZGPm5UjLS2Nhg0bEh4ezueff16kj/CEZ6AMkZMyRE7KEDkVjshIGUXSgYKcR/4PHDjwWB2ozZs3ExQUhCRJBdaBgpx+ePnVgcrth+ft7Y2rqyvnz58nMjIyTx2oihUryvN42IO6ceMGer2eRYsWERwcnKcO1L179zh27FgeUfyHH36ga9euABQrVoyYmJgC79eSDpTeJKFRqzFLYDYDJj1mQxZIZpLO78PDtSTZJgm1Ws3u3bvl5stRUVHUqVPnqcb+LyA8A2WInJQhclKGyKlwREbKKFIO1MtcB+rhfneDBg3iww8/pHTp0ty/f/+JzYQt6UDduJ9GcSdrUjKNpGQZyYy7g2TIxrleF5JObyHp1Ba+mKlmJGAymWjTpg2XLl3i+PHjT+zf919HeAbKEDkpQ+SkDJFT4YiMlFEkHaiH60C1b9+e+vXrM3v2bLn9ysN1oObMmYO1tTUAer2ewYMHU6dOHbkXnl6vJyEhgWLFihEdHc2OHTvkOlAeHh7o9XpKlSpFamqq7EA1btyYQ4cO5VsHys/Pj71799KlSxe5F56LiwulS5fG39+f77//nq5du3L06FHGjx+PtbU1n3zyCUajkcmTJzN69Oh879mSDtTqG2ouJ6rINIJRAkNiNLd++wQbr4pkx0Rg7VYCezs7nDQG7t27h06nw2Aw0KVLF3r27PlUYwsEAoFAUJT4Ow6URXrhmc1mfvrpJ2rWrEmPHj3w8PAgMDCQFi1asHXrVs6dO8c333zDL7/8wtixYwGYMGECAwYM4JVXXsl3MQIwe/ZsBg8eDOTsQh05cgSVSkWxYsXo3LkzpUuXZty4caSnp3P8+PE8T+EBLFq0iL59+6JWq+VeeMnJyYSFhTFw4EC+//57UlJSGDZsGOvWrSM9PR03NzdiY2MpUaKEfDz2KJbshbfo6E1+2BWORgU6aw2SJHF+6puYstLweWsCuvJ1+dS3Ah83L0dcXByNGzfm1q1bHD16lLp16z7V2C8zwjNQhshJGSInZYicCkdkpIwi2wsPYOTIkRiNRlasWCE7UNu2bUOn01GmTBm6detGQECAvAMVEBBA//796dOnD+PGjQPI40ElJSXJvfAgp56UWq2We+FBTh2ob7/9Nt86UID8vqCgIN5//30AuRZUbpkEJycnAgMDqVevHqtWrWLs2LG0bt2a6OhosrOz83WdLOlAmVGhVqkACUkCyWTEbDKCJJF1LwJdmf9hknLGunHjhnx8mJycLH45EZ6BUkROyhA5KUPkVDgiI2UUKQcK/vKgevTowaVLl2QHaurUqdjY2BAcHEz//v1lBwoerwX1qAfVu3dveQGUOwbApEmTWLVqFfb29lSvXl2uAwU8Vgsql4d73T3851wuX77MhAkTOH78uFyo08XFJd9FEljWgYqIScXD0ZrULCNp2UYy799G0mfiUMOX+wcWE//nCr742ZrRakhPT6du3brcvn2bgwcP0qpVq6ca+2VGeAbKEDkpQ+SkDJFT4YiMlPEyOFAWWUBt2bKFxMREoqKi8PPzo3bt2vj7+5OVlUXTpk0JDAzEwcGBOXPmyO1GevToweDBg+ndu3eeOlCzZs1ixYoVREdHs3Llyr8mbmWF2Wxm/vz52NraEhsbS3h4OMWLF0en0wEQGRmJtbU18fHxlC1blrS0NNRqNYMGDWLw4MFyPzw7OztsbW2BnGO+/v37o9VqqVixorxDlrtjlR/fffddvseOu3btemoH6s4dNWnpkG3MqUbO/y/4TBlJAKitbbGy1WGjMpKRkcGdO3fIyMjg+vXrbNu27anG/i+we/fu5z2FlwKRkzJETsoQORWOyEgZ/3ZOGRkZit9rkQVUYGAgjRo14vDhw1SsWJEhQ4YQGBhI9+7diYmJITQ0lAULFrBu3brHHKjevXs/Vgcq1z0aMGAAPXr0AECtVqNSqVCr1aSlpeHp6UmFChU4dOgQmZmZcssYvV5PsWLF5GsV1g9v7dq1qNVqzGYzWq0WZ2dn0tPTuX37doH3a8k6UDGHozizJwKVGpxsNWBbmmhbezIjz+DdaTgOtVozxLcC/VuUJywsjNatW5OWlsYnn3xC06ZNn2rslxnhGShD5KQMkZMyRE6FIzJSRpGtA7V582ZGjhxJSEhIHgdq8eLF2NrakpSUxPr16/N1oCCnDhQ87kDl1oGCnKKXKpWKqKioPA5U9erVuXPnDpUqVXrMg3JwcECSJObMmVOgA3Xnzh2ys7Plo73c+k/r1q3j22+/zXenyZIOlJVGA6qco0aVBBL8///k/EEFqNRqtFotVlZ/fTs1Go345UR4BkoROSlD5KQMkVPhiIyUIRyol8iB+uOPP8jMzJQ/3r17N8OHD8ff359Bgwble7+WdKDCYlPxcMhxoFKzTWTF38GcnY5d+brc2zyD+3sW8NVvdkzWqoiNjaVixYryyr1Ro0ZPNfbLjPAMlCFyUobISRkip8IRGSlDOFBRUXz00UfUrFmTqlWrMm7cuMccqNxijw87UBcvXqRVq1a0bduW4cOHs3nzZlauXMmKFSv+mvj/O1DBwcHMmDGDW7duMWbMGCpUqFCoA/XNN9/g4+ODk5MTQ4YMwd7eXnagKlSoAMDbb7/Nxo0b5cXU4sWL8fT0zPd+LelA3bylJjMTDAYVJjOYzTkLR2zsATDps8iWzJhUZiRJwmQyYTKZCAsLEw4UwjNQishJGSInZYicCkdkpIwi7UCNHTsWjUZDu3bt6NmzJ9evXyc0NJSzZ8+ye/duhg0bBuSE9PvvvwMwZ84c7t+/z7Jly1i2bJl83ZEjR+ZxoKytrbG2tqZXr15IkoROpyM8PPyJDpRGo8HJyYnWrVsjSRIlSpTIszt17tw5pk6dSkhICCaTiWLFihEfH8+YMWMIDAzM934t6UDdPRTJuX3XkVQSTjorKFGaezZ2ZFw5iIfv+7g2DKC/b2UG+1bgyJEjdO3aleTkZN5//33atGnzVGO/zAjPQBkiJ2WInJQhciockZEyhAMVEkKnTp0A2LZtG2q1GhsbG5KSkggKCnrs63KP0xo0aICNjQ2vvvoqn3/+OU2aNGH37t2MGDFCfq+3tzdWVlZ4e3sTGBhIxYoVOXr0KL169SrQgfLy8sJgMJCYmMiePXtwdnZm8ODBnD59Gi8vLwBOnTqFp6cnwcHB+Pj4cOTIET744AOCgoKYNGlSnn55uVjSgdJptZglsFKrUQOSWgMqNahU2HpVAI0WG2srtFotVatWxdnZmaSkJDw8PMQvJ8IzUIrISRkiJ2WInApHZKSMIutATZkyhYkTJ7Jq1Srmzp1LlSpV2Lp1K8HBwbi6utKmTRtq1qwJQJs2bWSJvF+/frID1a9fP6ZNm8agQYPyFNJ0dnYmIyOD1atXy+7UuXPn8jhQj5LbaPitt96SaySNHTuW9u3b4+joKI/9MOXLl+ePP/5gw4YNeTynh7GkAxUem4K7vTVp2UYyDCaMifcwZ6VhW6IKt4PH4lSuNkuuNOD4wmzWrl2Lk5MTTk5ObN26tUg3E34ZPIOEhASWL1/OpUuXsLOzo0uXLjRv3jzf2mSWwmAwkGWCHRejiUszYmOl5hUfZyp5Ovyr83jReRl+nl4ERE6FIzJSRpF3oBwdHalRowadOnVCpVIxdOhQAgICCAwM5OTJkwVK5I86UDExMcTExGBvby+PkZmZiY2NDf7+/iQkJGBjY0N6ejrvvfee7ED98ssvDBw4kKNHj/Laa68REREBwKpVq+jQoQNOTk5MnDgRa2trUlNTgZydstjYWOrXr4+DgwOXLl1i3759uLu75znqexhLOlDXo9RIBihuDSl6SDTmPC1Yts37aDIfcPvELs7vXc8955x/gNu2bcvnn3/O5cuXhQPFi+sZhISEMHfuXMxmM2XLliU5OZk5c+ZQrVo1vvrqq6c++lXKtWQVe+6oSb5wAf7/KU9rDVRykmjnY8ZW869M46XhRf15etEQORWOyEgZRdKB8vPzY/78+Vy8eJEOHTqwceNGkpOTKVeuHNOnT2fKlCkEBgZSuXJlKlWqJEvktWrV4p133snXgSpevLj855s3b2IwGAgPD8dsNstOVO7Teflx69YtVCoV9+/fp1WrVmg0Gtq2bUv16tXlcgULFixg165dpKeno1Kp5GbFa9euLfC6lnSgYg9HEXzyDiXddZRSqTAUdyTS1h6r2CvUfXMgxep1oPurJfmkeTkAzpw5w4MHD+jRowft27d/qrFfZl5kz+DAgQP8/PPPvP3220ydOpXixYsjSRK7d++mb9++/Pbbb+zbt8/iO0CX76UQtPEyKYYkKnm7odXm9FpMzTYSmWYgwtqTL/wriZ0oXuyfpxcJkVPhiIyUUaQdqGvXrlGtWjU+/PBDgoODiYuLo2fPnhw5coSffvqJrKwsRowYwalTp6hXrx4VK1YkLi6OU6dO0bp1a+bOnYuPjw+rVq1i9OjRdOjQgS1btshjnD17FkmSWL9+PbVr1+bevXvs37+fr7/+mvnz56PT6RgwYAADBgyQv2bZsmVIksS2bdtk/ykpKSnPN6dUqVJ8//33HD9+nOPHj5OQkMCECRMICAgo8H4t6UC1qVmCbZfiuJ9qoLiTDVpbHT7123B1/x84V2+CW7ka+Nf0RqvVkpqayvDhwyldujRdu3bNUxfqWZOenm6xaz8LDAYDWVlZ6PX6x4qlPm++//576tSpwy+//IJarUav1wPQsmVLfv/9d7p27cq+ffto1qyZReexITSKxJRUnFRZYNZj0qsBsFeDWWvmzyt36VTDnQqejhadx8vAv/Hz9PAO+8uO8HsKR2SkjCLnQEHO8ZkkSQQFBWE2m/Hx8QFyFhuNGjVi1apV1KxZk7CwMPbv388333xDnz598lzj8uXLzJw5k1dffTXPttqOHTtISkqibNmydOnSBYCyZcvi4uLCmDFjZIn8YZKTkzlw4AAAr776Ki4uLixcuJBq1arh5eUlS+SzZs2Sx75x4wYjR47k66+/fuK9WtKBKuVsTb/GpZn/ZxTXYnOOGZ2a9EJ3M5wjPw+mYrVafLrFk+zsbC5fvkxWVhZbtmxBkiSLnh07ODhY7NpFhSftTr7++uv/4kwKZufI5z2DokPuQvplRvg9hSMyUkaRdaCMRiMLFy6kVKlSbN++XS6iuW3bNrp164ZarWb16tUFFtGEvIU0o6Oj5UrhAJs2baJChQpERETg7e2No6MjnTt3pkGDBrJE/mgRzVOnTmEymdBqtezdu5c33niDqlWr4u3tzb179/IUnbx06RKLFy/G1dWVyZMnF3q/lnSgIMd90mSpSUlTkWUC0OFUx5/06HDCL54h/OJf723cuDGxsbHCfxIIXjL+S7+zwu8pHJGRMl5kB0olWWA/esOGDQQEBDBlyhRatGhBkyZN0Gq17Ny5k+3bt7NmzRo8PT2pUaMG4eHh3L17l/Hjx9O7d2+APM2Ec3dx3nvvPX744Qc8PDxo164de/fuzdd36tWrF8uXL+fEiRO8+eabaLVaQkJCCAkJoW/fvvTq1YvVq1cjSRIajYasrCw8PDyIjo4GYOHChfTv318uSFm9enUGDhxIjx498PDwyPd+89uB8vHxIT4+/qkdqEy9iTEbL3HhbgrFHKyx16q5fGQ3oYvG4/G/Fvi/9ymzP26LypjNokWLGDVqFO+88w6//fbbU41bGC/DEd6+ffto1arVC7VNbjKZqFGjBh07duSHH3547PX79+9To0YNJkyYID+VapF5mCWGrznPnYQMrIxpFHMvhkr9l+tkNJmJSc5meJtKNK9U7AlXKhr8Gz9P/4UjPOH3FI7ISBnP04EqVqwYycnJhf77bZEdqJ9//hnIKQkwevRoPv30U+bNm8fs2bMZNWoU06ZNo2PHjlSvXh2VSsXbb7/N7du3mTFjBsOGDXusmTDAkiVL2LJlCw8ePJClccjZcTl9+jQ6nY7ExER57AYNGrB48WJ8fX3zbMndvXsXnU6HwWBAr9djNpvzHEctW7Ysz1b65cuXGTx4MBMmTCA2Njbf+7WkAxUSnsCVmDRKueqwsdJglsxc3xdM8Ur/w2/gZO6lZnM8Kol2Nb0ZOnQoVlZWfPrpp4wdO7bApwafBS4uLha79rPAYDBga2uLi4vLC/eX1CeffML06dPp378/9erVkz9vNpvl7+HHH39s8Yw716vAvP0RmCUj1jo71Kqc3ylJkohNzKR0cTf8apfFztpyLt3Lwov88/QiIvyewhEZKaPIOVD169fnwIEDlChRApPJJDcT3rx5M0FBQUiSxKJFi5g4cSIlS5YEckoXPNxM+OFGwpMnT2bQoEFyM2Fvb2+KFStGdHQ0W7duxcXFRW4knJiYKFcef7iQ5o0bN9Dr9ezevZuTJ0/K/3AVL16c8PBwoqOjKVGiBHv37gVg3LhxbNiwgbNnz9KhQ4c8TwA+iiUdqEPhcUhmM1qNikyDkfvRd0m8eZVGH47HSgMJYaH8dHUXsU2r0L59e959912+/PJLgoOD8xQeLWq8yJ7BsGHD2LlzJy1atODdd9+ldevW3L9/n6CgIM6cOUNgYCCOjo4Wn7t/tWKcioxn78U07iRk4qizwmiSSM0y4mKnpX/zcmhVlnXpXhZe5J+nFwmRU+GIjJTxMjhQz/wIz2g0UqpUKUaOHElaWhqrV6+WmwkPHTqUWbNmyU/G3bp1K18P6mH/adq0aQD07t2brKws1q5dy/z58/n000/Jzs6mTJkyZGdn4+npycWLF0lLS5PrQC1atIi+ffsiSRLJycm4u7vL9aIArl27RtWqVVGr1axdu5Zu3brJ9/HwAqpp06a89tpr+R655L43PwdqxYoVT+1ALY9QcysNTJKKNANkxN3k1oLBeLT5mOTQTegTY1Cp1UhmMzY2NnTp0oX9+/fTokUL+UhU8OKRlZXF+vXr2bVrF4mJiQDUqVOHN954g1q1av1r8zCY4ewDFeceqEgxqFCrJCo5wSvFzJR4en1PIBAIXioyMjLo1auXoiO8Z76A2rBhAz179iQuLo727dtTv359Zs+ejb+/PyEhIZQuXZqrV6+ybNky5syZg7W1NZDzBMrgwYOpU6cOzZs3x8nJCb1eT0JCgrzbtGPHDvz9/UlLS6NMmTIkJCQ8Nv7OnTvx9/fnxIkTBAQEYGNjw/Xr1wFo2LAhp0+fpkWLFhw9epTs7Gzc3d0xm81MmDCBAQMGcOnSJb766isOHTpEYmIi1atXJywsjJMnTxZY2duSDtTMveEsOXoLg8mMtZUGlT6D89+/CZKEXZlaFG/1Pv26+PFeHWfmzp3LtGnTUKlUzJ8/n/fff/+pxn6ZeVk8A5PJRGJiIra2ts/lycbcnFr7+aE3q7DWqLHRiuqZj/Ky/Dw9b0ROhSMyUkaRdKByi2jGxMRw4sQJypYty5AhQwgMDKRVq1Zs3bqV8+fPs2bNGtatW8fYsWMB5AVMREQEiYmJ8n+VQ463BBAWFoa/vz8ODg7MmDGD999/H1tbW9zc3OjUqRNnzpxhyZIl+Pv7k5GRwd27d4mMjJSv0759e06fPs2BAwfQarU0adKEW7duce/ePfk9/fv359ChQ/LHly9fBp7s/FjSgfJ00pFtkrDRqLHWqJF09mh0TpgyUyjZeSg4FMfDWUfp0qX57rvv2LlzJ+fOncPX11f8cvLiewZarTbf/or/NjbW1ji8wDm9KLzoP08vCiKnwhEZKaNIOVCbN28GYOTIkRiNRlasWCE7UNu2bUOn01GmTBm6detGQECAvAMVEBBA//796dOnD+PGjQPI40ElJSXl6YWXe9x37949eXHzxRdfyIufRxsJA2g0GoxGYx4HauvWrXTs2FGex59//gnktNrw8/OjRo0anD179on3bEkH6lZ8GvbWarKNEhl6I6b0REzpiahtHYhcOALXmi1YdcuHO3scCQkJ4fz582i1WjZs2MCnn376VGO/zAjPQBkiJ2WInJQhciockZEyXgYHyqLNhHv06MGlS5dkB2rq1KnY2NgQHBxM//79C+yFB3k9qMmTJ9O7d2/c3NweG6tOnTpkZ2dTs2ZNkpKS5IKdkNeBepiHW1PkPs33MAcOHKBjx47UrVtXLrD5JCxZB+pChBprM0ioSDFCdnLOzpxzox6kHF/L/aPr2H8U9pOzQGzXrh2hoaEcPXpUbp5clBG1VpQhclKGyEkZIqfCERkp40WuA2XRZsJRUVH4+flRu3Zt/P39ycrKomnTpgQGBuLg4MCcOXOoXLkygNwLr3fv3nnqQM2aNYsVK1YQHR3NypUr5TF27dpF//79adu2LadOnWLSpEkAfPDBB/J7rly5Iu8sQc5iSavV0qJFC4xGI1ZWVpQoUQIbGxu5dMH+/fvp2LEjn332GZcvX2bHjh2oVCpu3LhBuXLl8r1fS/bCu7IrjGsn76CXzOi0oHPzJFqlJunPpVi7++Dt/zGt61ajWy131q1bx5IlS1Cr1fj6+opeeMIzKBSRkzJETsoQORWOyEgZRbYXXmBgII0aNeLw4cNUrFhRdqC6d+9OTEwMoaGhLFiwIF8Hqnfv3o/Vgcp1oAYMGECPHj2AHCdp9erVLFq0CL1ej6urK5mZmRw+fFguh1CtWrXH2iM4ODhQtmxZLl68SHp6Ok2bNpWPHQEWL15MRkYG3333XZ6ve/fdd/O4UQ9jSQfK29WOTIMZGys1NlZqJK0zVvbOGDNSKPv2eMx2bjRuVoUuLSrQuXNnLly4wJkzZ3j99dfFLyfCM1CKyEkZIidliJwKR2SkjBfZgXr8/OoZsHnzZho0aCA7UHPmzCE9PZ3FixcTEhJCUlISffr0ISAggLCwMMLCwggICJDLCGzcuBFJkrh06RKenp6MHj2agQMHUrt2bXmMkSNHEhERQZcuXeRinY6OjkRERMjv6dOnT57jOy8vLyRJ4vTp08yfPx9nZ2fmz59PYmKifFS3aNEiJEli3rx5FC9enMaNGwPkaWT8b3IvOQs7azUmSSLLaCIzNQljWhIqjRWRy0aTfnYb+3duZfny5bz99tucOXMGtVrNjh07nst8BQKBQCAoCrzUDtTChQu5ceMGy5YtY9KkSWRmZuZ5oulRB6pRo0YkJSVx6tQp+T379u3DbDbTsGFD+XOXL19mwoQJNGvWLM8TegVhSYk8LiULDwcbUvVG4lP1ZCXcByTcmr9L8tE1RG+by8ptsJKclfPAgQPZunUrN2/eLNKSohA1lSFyUobISRkip8IRGSnjZZDILdYLr2fPntSpU4dGjRrJdaBCQ0Px8/MjIiKCzz77LN86UI86UCaTSa4DtXLlSvkIb8yYMcydO5c1a9YQExPDe++9B8CePXto3bo1AKNGjWLmzJl5FjeVK1eWmxObTCYqVapEvXr1WLFiBQDR0dFUqlQJtVpNeno6VlZWGAwGtm3bxuuvv57v/VqykObGKDXH76swmAEJzBmJXJ/1HiprHRqdIy61WlPey5nqDlmcO3eOM2fOoNFo6Nu3Lx07dnyqsQUCgUAgKEo810KaAJ06dSI1NZXDhw/LTXgfdqB27NhBixYtWLFixWMO1MaNG+nSpQubNm167Lpubm48ePAAk8lEmTJl0Ov1pKamotfrsba2xmQy5XGe8nsKb+TIkezZs4fz589jMpno27cvs2bNkosYDhw4kMDAwMfcKeCxp/lysWQhzaXHbjJ1RxhajRpbbc6J6/lpb2HMSKHykCAk+2IMbV2Rj5qVQ5IkGjRowLlz57h69Srly5d/qrFfZoSoqQyRkzJETsoQORWOyEgZRbKQJuQ4UCNHjiQkJCRPHajFixdja2tLUlIS69evz7cOFOQ4UPB4HajcXnipqancvXtXvi7ktMYAsLKyYteuXbRq1Yo+ffrQp0+fPHPLbQ3z4YcfEhgYSFBQUJ7Xjxw5gtFoRKPJqcYsSZI8xrfffpvvTpMlJfKEDBO2Wg0Gk4TeKCFlp2JMTwEV3P7jezxbvE34dTUXXdNZsmQJ586dQ6VScejQIapUqfJUY/8XEKKmMkROyhA5KUPkVDgiI2W8yBL5S+lAOTk5ceHCBdavX8+qVatYtmwZH330ERcuXCA0NFQuN1BQHagn8ccff5CZmSl/vHv3boYPH46/vz+DBg3K92ss6UBFJ2VQ3MGGlGwDCRkGMu7HgmTCrWVfko+u4eby/2PvvAOqKv8//rqDy5ah4M6Fe+dOLTTcWjnSMveoXDlypGmamZnfX7nTTNw5cosrLRX3wIWggoqCIgjKnned3x/ESQS9p+iWyPP6o+SO85zzhiuPz/M6n8805v8M88maPA4ZMoSDBw8SGhpaqPfYhWegDJGTMkROyhA5WUZkpIyC4ED9rQnU6dOnadGiBe3bt2fv3r25nh83bhyPHz/m7t27DB06lFq1apGZmUlsbCxqtZrhw4czc+ZMdDodnTp1AnLWgQoKCqJly5YkJiayd+9eWrZsyaZNm2RPSa1WY2try+LFizl+/DhbtmwhJCSEzMxMWrRoQUJCApCzDtQnn3zCyZMnuXr1KhUqVKBGjRoAcpXxqKgoOnbsSI0aNQgMDKRPnz7s2rVLnkx17NgRT0/PPPOwZiHNx1FqohNV6E2ABLYOWVuNied2YJbApXZrSrg7U9FBz/Xr11m5ciUajYaYmBj27duXr7FfBkSxOmWInJQhclKGyMkyIiNlvHSFNH19feXaTg8ePKBUqVIAzJs3jyFDhnDs2DEqVarExYsX5QnSlStXqFq1KnZ2dpw7d4569epx5MgRMjMz8fHxYf78+fz0008ArF+/Xp4EXbt2jbfeegvI8pd69uyJyWSid+/efPnll1SpUgW9Xo+Hh0euC3+6DtSgQYP4/vvv5dIJAPXr15fPHSAsLIy1a9cyb948pk+fzrZt25g6dSpbt25l9OjReeZhzUKaj86Ec/rXUHQ2WXWgcChJhKMrpvRkvIYtQ+VSik/+cKCMRiONGjUiODiY8ePHy0VKCyPCM1CGyEkZIidliJwsIzJSxktZSDMlJYXNmzcTEBBAdHQ0q1evZsqUKQC4ubnRpk0bGjZsyLlz5zAajXz55ZfMnDkTyPKJbG1tSUhIwMXFhREjRnD48GF8fHxwdnaWJyF3795l6tSpxMXFsXz5ciZOnMjXX38tn0NycjIBAQFcunRJ7o1nNpuRJInExEQOHz6cy4FauHAhALGxsezcuZMxY8YwZswYeaJ29OhRAEaNGsX06dPp3bs3JUqU4PPPP+ebb77hxIkTREVF5dn41ZoOVHKGCZ1Gg8ksYTRJYEjDlJ4CkpnoQysp/mZ/4lNKk5KSwk8//URISAgAly5dombNmvka+2VAeAbKEDkpQ+SkDJGTZURGynipHKhffvmFatWqUbVqVfr06cOYMWOYPHkyKpWKAQMG0Lp1axo1asSjR4+YOnUqvXr1yvH+d955R3agEhMTqVmzZg7RO7u20+TJk2nevDlubm45Jk/ZXtPVq1dzHPeHH35gx44dpKSk5Kjp9FcZM2YM69evZ9GiRYwfPz7Hc096Tk8/brVmwnFpFC9iS1K6gYR0A+nRUWA24tbiAxLPbuP20tNMXQpTyerx995773HixAmCgoIK9R678AyUIXJShshJGSIny4iMlFEQHKi/XMagefPm9OzZk9GjR2M0GilZsiRbtmzB29ub9evXs3jxYpycnDhy5Aj169enU6dOzJo1S/alJk2axOHDh1mwYAFvvPEGo0ePplatWgwYMICbN2/SokULpk6dyoQJEzCZTBiNRry8vOjXrx8ff/wxJ06cYPLkydy4cUM+p5MnT9KyZUu0Wi0ODg7yqtKOHTtyvfa1117j0qVLGI1GjEYjly5dAv50oDZv3swvv/zCrl27UKvV2NnZkZycTKVKlbh582aemVizDtTWO2quPFahN4PJDIakGMJ/GIzWtQTG5Mc4lq2Om7MTJWz1hIWFkZqaCsC7775Ljx498jW2QCAQCASFCavVgQoJCaFWrVpERkbKQvXIkSNJTExk3bp1fP/99wwdOpSWLVsiSRInTpzAx8eHZs2a4evrS0hICPfv36dJkybY29vz6aefUqlSJSBrZapOnTpMmTKF/fv3P7cO1JMkJCTQoEEDAO7du5djApXXXXglSpTg4cOHuY49b948xo4dy44dO+jduzfp6eloNBqKFy/OgwcPaNu2Lb/++mueuVizDtTaMxHM/TUUrRrsbDRIkkTgt70wpSdTYfB8tJ6V5DpQaWlpNG7cmNDQUC5fviyL8oUR4RkoQ+SkDJGTMkROlhEZKeOlqwPl6+uL0WiUpXH402tavHix7DCNGTMGyNpSunbtGmvXrpV9qXfeeQdPT08aN27MoUOH5FYpixcv5t69e7LTlF3jSZIkNBoNnTp1Ijk5Odc5ffzxx/Tu3RuNRsPKlStzCGB51YH6+OOPn+tAGQwGMjMzWb58OWPGjOH8+fN4eXlx7NgxuWDn01jTgUo3mNCqVZglCbMZMGZi1qeDZCb+wn48vPuSbsiqU7V7924iIiIAuHXrVo7egYUV4RkoQ+SkDJGTMkROlhEZKeOlcKCyazt99913tG3bNsdzT3pNgDxpWblyZQ5favjw4SxYsID+/fszd+5cIiIi5DpQZ86cISUlJcdxf/jhBw4fPszWrVuZNWtWrgt7uhfe0/ydOlDnz5+ndu3aDB06lJ9++okvv/wSrVZLcnIywcHB8l17T2JNB+ruo1Q8i+hISjeSlGEkPSYSyajHpUk3Es/vIuHSfiYsUDORLJG+Q4cOXLlyhYCAAPnuxcKI8AyUIXJShshJGSIny4iMlFEQHCjFE6g9e/YQHx/P4MGDuXbtWo46UN27d8fX11eeQK1evRrIWrHq06cPAKmpqdy7dw9bW1sWLlzImjVr0Ol0tG7dGnt7e9577z25DhRkeU3Lli3D1taWpKQktm3bxt69e2Wvyc/Pj88++4zjx49z7do11q9fz/3795EkiXfeeYeJEyei0+nkatwLFy5kyZIl3L59G5VKxYYNG+TWLzqdjgMHDgDw888/U6tWLQDmzJlDu3btMBqNAERHR+eZjTXrQEVHqolPUpFhBEkCjSbrW5Z+9zKS2YRtsbI4OTrgqjUSGRnJiRMnMBqNREREiDpQiForShE5KUPkpAyRk2VERsp4KepA+fr64uPjg4uLS646UN27d2fu3LlMmDBB7m0XFRXFuXPnaNeuHYBcBDN7pSYmJgbI2nZavHhxjjpQCQkJ9OvXjwoVKhAZGcnbb7/N9OnTadu2LatXryYkJCRHHajSpUvz4MED+Vx37drFrl27OHLkCDdu3GD//v25ajhlf1MePHhA+fLl5cefrGvVunVrXn/9dQ4fPvzcbKxaB+p0OOcP3kSjARedBsn+FSLti6CPucMrfWZjV64en7SuxIctK/D48WOaNWvG3bt3GTNmDPXq1cvX2AUZ4RkoQ+SkDJGTMkROlhEZKeOlqgPl5+cHPLsOlCRJrF69mjZt2lCrVq0860BlVxCPiorKUQcKyFEHKttryq4D9eGHHzJ16lQga3vwnXfewc3NTa4DZTKZUKlUsi81a9YspkyZIheSXLduHT169GDLli3y9fTp04cNGzZQrlw5AKpVq4aLiwsVK1bk2rVr8uu2bduGm5sbkCWg54U1HSijpEKtUiEhIUkgmQyYTXqQJNLCg7ArXQOjOauNS1BQEHFxcQA8evRIfDgRnoFSRE7KEDkpQ+RkGZGRMl4KByqbF60O1Pbt2/m///s/+vTpI/tSZcuWZerUqZw9e5auXbuSmZmZayvNxsYGSZIIDw/PsQI1btw4+vbti6+vL4MHD5Yfd3R0fOZdbdZ0oG4+TKa4s47EDCMpmUbSY+4j6TNwruPDo+MbeXzqF8bPt2GyGtLT02nSpAl3797l+PHj+Pj45GvsgozwDJQhclKGyEkZIifLiIyUURAcqAJfB2r27NksW7aM+/fvY2trK/eu8/T0pGvXrvj7+zNu3DjGjh3L7t27KVq0KJ988gknTpxAkiRatmzJnDlzCAwM5LPPPuPx48cULVqU5ORkdDodWq2WlJQU3n77bXbu3JlnJtasA7XptpqQBEg3qTCYITMukvvLP8auXB0ywgPROrpia2ePg9rI48ePcXd3Jz09nS5duvDee+/la2yBQCAQCAoThaoO1LRp0/j2228pW7YsDx48yDGBat++PevWrcNsNvPZZ5+xcOFCMjIy8ry2SZMmsWzZMi5dukTVqlUxmUxoNBocHBxITEykUqVK3Lp1K8/3WrMO1KpTd/n+0C1UKrDXacBs4sqcnpgzUij1zkQca7zBqNaV+Pj1ity5cwdvb2+ioqI4evQor732Wr7GLsgIz0AZIidliJyUIXKyjMhIGaIO1L9QB+rXX39Fo9HQt29feYXIaDQSFxdH165dWbt2LQDffvstffv2pXbt2pw6dYqEhAQ6duzIxo0b6d27N8WLFwfgwoULSJLEN998w4IFCzh//jylS5fm9u3bGAyGPL+R1nSg1CoNqLKyVElZd+IhZdV9MuvTUKkkVCo1NjY2ZGZmyncMms1m8eFEeAZKETkpQ+SkDJGTZURGyngpHKgXtQ5Ueno6GRkZOe7CO3z4MGazmbt378pyOcC5c+dwdXWlWbNm9OvXj2bNmtGjRw/69OlDWFgYAA0aNECtVlOkSBHUajVz586VH39WsFZ1oGKS8HDSkZxhJDnTSMaj+5gz03D0akz0vsXE/r6SSUsc+FKbJY5Xq1YNs9nM77//TosWLfI1dkFGeAbKEDkpQ+SkDJGTZURGynipHKidO3fSq1cvYmJicHFxyfFcttd0/vz5HI83b96cRo0asWjRIpo1a8apU6fw8fFh7dq1bN26lZUrV6LT6dDpdOj1erkO1JUrV5gzZw579+4lJSWFsmXLcv/+ffbv309qaqpcB6pFixYcP36cfv36cfbsWXQ6HYcPH2bgwIE0bNiQd999l8mTJ3PixAm2bt1KSEgIW7duxcHBgdDQUBwdHenVqxe7d++mQ4cO7N69mzFjxuTpM+l0umc2E7a2A3UzEdKNKjLMkPnoHpErhuNQ9TXSQk6h0tpio9NhozKTmprKK6+8QkJCAu3bt6d37975GlsgEAgEgsKEVRyoLl26YDab2bt3b67nzp07R5MmTbhy5Qp16tQB/vSlevbsiYeHBz/88EOeMzsnJyd69erFzJkzGTZsGLt27WLlypVcuXKFxMREjh8/TmxsLOnp6cybNw8nJyd5gjR48GDee+896tWrx6NHj0hNTaVIkSJ0796dhQsX4uTkBGStzHTp0oWLFy+i1+txcnJi/vz5VK1alYEDB3Lv3j169uzJ7t27uXDhAm3btqV9+/Z06dKFDz/8kHv37uHu7s6jR49QqVS5rsGaDtSKE3dZePgWSBL2Oi2YjVyZ8y7mzDQ8fYbg2uhtPvb2YmSrSgQEBNC5c2fi4uLYv38/b775Zr7GLsgIz0AZIidliJyUIXKyjMhIGS+VA5VdByovGjdunKtdSrYvtWHDBtlnUqlU2NnZERUVxY4dO1i2bBk6nY7Q0FC6desmbwEOGjQIgGvXrrF//35GjRpFQkIC27dv5/DhwznqQA0fPhxAHj81NZU+ffrIkyeAYsWKcfr0aWbNmsW0adM4cuQIDRs2BGD+/Pl07tyZN954g7Vr1zJt2jTc3d1ZsmSJfN316tUjLi6Os2fP0rRp01zXb00HSmejQZKyamipAEmlRqVSAyps3UuBWoOtjRYbGxteeeUVHBwciIuLw93dXXw4EZ6BUkROyhA5KUPkZBmRkTJeCgfqr5DtS/Xs2ZPg4GA2bdqEv78/c+bMwdbWVvalWrduLTtQ586d45VXXpGPERwcTOvWrenfvz9ff/01ffr0wd3dHYAiRYpw9epVduzYwebNm1m/fj1Dhw7l6tWrBAQEUKFCBeDZvfCeXEVSq9U5nktLS8vx2IoVK6hYsSJhYWGYzeY8r9eaDtSth8m4O+pIyTSSojeR+fg+powU7MpU594vM9G5ePDFmiLMt1dz9+5dPDw8cHFxYe/evXn27SssCM9AGSInZYiclCFysozISBkFwYGyygQqu2/e3bt3GTp0KLVq1aJatWrMmDGDFi1a4Ovri5OTE4sXL6ZTp04A9OzZU3aggoKCaN26Ne3atWPcuHH4+fmxadMmuR1MdkXzxYsXc/z4capUqYKjoyMqlUruYwdw/fp1dDqd/LVarcbBwYGhQ4eybNkyDAYDo0ePxtbWFr1eD0CnTp2YN28eM2fOpFu3bqxZs4aSJUtSrly5Z05IrNkL7064GkMmmI0qTCYw/vHN1RYrD/dvoE96THxqAolIGI1G3NzcyMjI4Pr166IXHqLflFJETsoQOSlD5GQZkZEyXopeeH8FX19fmjVrxsmTJ/niiy/QaDS0b9+eXr16cfv2bQICArh8+TKHDh1i7NixQFZI2b3wFi9eTGxsLOvXr2f9+vXycSdOnEjPnj0xmUw5euGdPHkSf3//XH5S9erV5YlRNp6ensTFxdGkSRMAKleunGO7r3Xr1vz8889MmDCBGTNmIEkSer2ejz/+GHt7+zyv15q98O4dC+PK0TtImHG21+Jc6hWibOxIubwft6bdKNayNx+9WYOR3hXZu3cv/fr1IzU1lffff5+OHTvma+yCjPAMlCFyUobISRkiJ8uIjJTxUvXC+yv4+fkxceJE/P396dKlCwD79u2TV44SEhJYuXJlrvdlT4AaN26Mra0tr776Kp9++inNmzfn0KFDjB8/HoDk5GQCAgJy9MKDLA9Kq9Vy8OBBWrduzYABA3K0iSlRogT379+nZs2abN68GYPBwIABA4iLi8vR5+706dM4OTlRu3ZtSpQowezZs+Uec3lhTQfK0U6HWZLQqtWoAUlrg8pGB0Y9Raq9hkrngKOdDltbW958801KlCjB7du3qVSpkvhwIjwDpYiclCFyUobIyTIiI2UUWgdq9uzZfPXVV2zevJklS5ZQtWpV9u7dy8aNG3Fzc5MbDwO0adMmh0Se7UANGjSIuXPnMmLECLZv387IkSNlBwpg/PjxlCtXjosXL+ZyoJ7G09MTo9HIp59+Kq9ADRw4kKlTp8pNha9fv87SpUs5cOAAbdq04euvv6ZBgwbPvV5rO1CuDjakZZpI0ZvQx0dhSktCV+wVwtdMxKFkRWbvcmNdERtu3LiB2WzG0dGRnTt3Ur169XyNXZARnoEyRE7KEDkpQ+RkGZGRMgq9A+Xs7EzNmjXp0qULKpWKMWPG0K1bN3x9fTl//vwzJfKnHajo6Giio6NxdHQEslymWrVqsWrVKuLi4tizZw8+Pj65HKhRo0axePFiWSKPiYlBq9Uyb948qlatisFgYM2aNahUKsLDw3n11Vfx8/OjYsWKzJkzB7VazYgRI9i5cydz586VJfansaYDdeuOGkkPmFQYjaDPyGpVY+/VGEN8FGkPbpH2AO798fomTZpw69YtgoKChAOF8AyUInJShshJGSIny4iMlFEoHSgfHx82btxI8+bN0Wg0tG3blsTERCpUqMD//vc/Zs+eze7du6lSpQqQUyJ/lgOV3W4F4ObNm3z22WccP36cs2fP5ulAPU10dDRlypTJ5UC5u7sTHR0NwJUrVwgNDSU0NBSAiIgIfH19uXz5MgEBAXke15oO1J2jtwk6fhcTZpzsNTiVLEuUVkfima0Uqd0az1b9GdyuIcNblGH9+vWMGTMGg8HA22+/LRwo4RlYROSkDJGTMkROlhEZKaNQO1DZhTTLly/PqFGj8PX1pUePHpw6dQpJknj77bfZvn07X3zxBYBcSLNPnz6yA9WtWzfS0tLo1asX6enpTJ06FSCHRO7p6UmHDh2oWLFijnYuAIsWLWLRokU5HouJiaFy5cqyAzVw4MAcLWSySxWsXr2adu3aARAYGEi7du0ICQmhatWqua7Xmg6Uq4MtRrOEjVqNjVqNZGuH2tYBk9mER/N3UTl74OZoS5EiRRg0aBBLlizh2rVrvPrqq+LDifAMlCJyUobISRkiJ8uIjJRR6BwoyLuQ5po1a7Czs2Px4sV07dqVbt26yWUGnlVIs1WrVjkKaY4cOTKHRP50Ic0nJfKnMZvNpKWlsWLFilyFNLPPw9PTE4C6devKYnl265qIiIg8J1DWdKDCYlMoYqcl3WAiJdOIMSkWU2oC2iIe3Fk5DufydVh0woPfPe25ePEikZGR2NnZsWPHDry8vPI1dkFGeAbKEDkpQ+SkDJGTZURGyii0DlRBLqSZLYx37NgRo9FIlSpVePfddwFk0fxprOlA3bitRm0EjVlFuhEyUpMBcKrXgaQzW0gMPUtiKAT/cV3e3t4EBQVx6dIl4UAhPAOliJyUIXJShsjJMiIjZRQ6B+rJQpo+Pj7UrVuXtm3bkpGRkauQZl4O1LZt2/jggw/QaDQsXLiQDRs28ODBAzZt2gTkLqQZGxtLQECAokKa9vb2tGnThszMTFQqFRqNJkchzfbt21OmTBk8PDzo3bs3kydP5uTJk9SrV08+16expgN18/Atrp0KxyiZcbTT4OhZkgdqLQnH1+NYoT6erfrSp00TBjUpga+vL19//TWSJNG+fXvhQAnPwCIiJ2WInJQhcrKMyEgZhdaBerKQppeXVw4HKjo6moCAAFasWPFMB2rt2rU5tsQiIyMBGDZsWK5CmtkOlKurK4mJiTnOI69CmkCOFSlJknJ87enpydmzZxkxYgSTJk1Cq9WiUqnydJyysaYDVczJDoNJwkajRqdRIzk4obV3xpieROlOI5CcS1C6hAfly5dnxowZ7N69m8DAQN544w3x4UR4BkoROSlD5KQMkZNlREbKKHQO1JOFNPNyoBISEtixY8czHahdu3YBfzpQQ4YMISEhgevXrwModqCeLqRpNptJT0/n2LFjsgO1d+/eHA4UQKlSpahSpQq9e/fmzTffZNiwYYSHhz/zeq3pQEU8SsFRpyHTaCZNb8SYEo8xNR6NfRFur/wUtxotWH+zNDf9HDlx4gRBQUHY2NiwY8cOxowZk6+xCzLCM1CGyEkZIidliJwsIzJShnCgCqADBXD48GG2bNnC5cuX2b59OyaTiZIlSz7zeq3pQAXdUmNjBhMqUgyQkRQPQJGmPUg6s4VH5/04cR5OABqNhjZt2nDx4kXOnj0rHCiEZ6AUkZMyRE7KEDlZRmSkDOFAFSAHatq0acyZMwd7e3uKFSuGjY0NBoNBXunKC2s6UDcO3eTGuXsYJDP2OrArVpwHKjUJx9Zh61meUp1G0aFpbbrXdmfLli2sWLECtVrNm2++KRwo4RlYROSkDJGTMkROlhEZKUM4UAXQgdqxYwe2trYYDAbs7OxwcHAgLS2NsLCwZ16vNR2oEq4OZBjN6DRq7LRqJJsiaB1dMKUlUa7XF5gditKgURXavl6JNm3ayI2a27VrJz6cCM9AKSInZYiclCFysozISBkvsgOVe//qH8DPz4/GjRvLdaAWL15Mamoqa9aswd/fn4SEBAYMGEC3bt3kqt/dunWja9euQJYDJUkSwcHBeHp6MmXKFIYPH07dunWBPx2okSNH4u7uzp07d0hISJCbCR8+fBiAAQMG5JgcZTtQhw4dIjU1lZSUFDZu3Iher5dXqu7fv09GRgYGg4G0tDRiY2OBrG26vBogW5uohHQcbNSYJYkMg4nM5HiMKfGgseHO2s/ICP6NoOshHDlyhO7du3P58mU0Gk2h3r5LTEzk1KlThIaG5piI/x0MJjO3Y1O4FZNMmt74D52hQCAQCAo6woF6yoE6ffo0JpNJ/nrlypUsWLCAwYMHyxO8p7GmRP4wKQNPZ1vUahUxSZkk/uFAvfLWWFKCf+feru9ZtOt7FgFeXl6sXr2a6dOnc+/evUInKSYlJTF58mTWr19PenpWz8DsRtSfffYZGo1G8bEkSWJ/0EP8AqOITMxAkiRc7XW0qeFBj1dL46CzWg3afxUhtCpD5KQMkZNlREbKKLQSeUF2oB4+fMi8efPYv3+/HKRWq2XZsmV5CudgXYk8KUZNQpIKD3uJ4jpwdHckTKXCSUqm5oCp3I+KoYQhmnaV7KlQoQIpKSlERkYSFxdXqFahMjMzmTZtGvfv3+edd96hadOm6PV6jh49yldffcWxY8f45JNPLPZLBJAk8I9ScTpGjUol4agFFXA/GX6MesyRgOu8U96MjVXWb/8bhNCqDJGTMkROlhEZKaPQSeQF2YE6deoUderUYcCAAdjb2/PVV19x6tQpBg8ezKpVq/K8XmtK5O5hcczcex0nRxscdFokDw9CqjQg8sw+qnl3xaNsJSZ16EjLysWALAlerVbz5Zdf4uHhka+xCxKLFy8mLCyM48eP06BBA1lAHD58OBs3bmTIkCFMmzaNFi1aWDzW7dhUVmy9SvGi4O6oy/Fcut5EdIoe+4petK1R/BlHKDgIoVUZIidliJwsIzJSRqGVyAtyHagpU6bkuJb27dtTr1491q1bx4oVK/LcBrKmRN7Uy4PmXo84FhqLk62Ei70Gr7YfcO7HKRz8v5F06j+K+qUbcPv2bRYtWsQPP/zA559/jouLS56Tx+cRGxtLQkICdi5FsbVzwN1Rh1ZTMJZZVq5cSefOnalduzZ6vR6DwUBGRgZ6vZ6ePXsyZ84cVqxYIW8ZP4+j1yJJSkmmnLsjJn1Oh0oHmPQZHAy8j7eXm5Wu5t/jyZye3urOL46Ojv/o8V4EhPirDJGTZURGyniRJXLhQD1jW+5J0tLSkCQJs9mc5wTKmg4UwNg3K+LhZMPhG7E8SMjAVNSL5iO/5/bOBWz6ajibvsqaRGbn8/XXX/P111/ne9yCRlBQEE5OTs98/tatW2zYsEHx8Y4/57mjwMJ+ig9VKPmrE/gXGeGtKEPkZBmRkTKEA2VFB+rq1at89dVXODg40KxZM1QqFSaTKd8O1KpVq1izZg2RkZGEhYVRvnx5wsLC6NSp0zNnptZ0oLIpA3T3hOgsN5ri9iVxbPkNN2/eJCoqCkdHR2rXrk2vXr3+kfEEgvzyMjp4wltRhsjJMiIjZQgHygoO1KxZs+jbty/jxo3D0dGRDh06cOPGDZYvX86HH34I/D0HSq1WExwcTHJyMgBhYWH06NGDdevWPfN6relAPY2lfeH4+HjFx8rMzKRWrVrUqdcA27ZjMEoqPItkbUWmJcRyYM5wilaqTeUeE/iktRfeVV9cp2rWrFksX76c8+fPU7x4cQwGA4cPH6Z169ZcvHiR9u3bs2bNGt566y2Lxwq8n8DMPTdwttfiaJvzI2IymYlMzGBw8/K8XbeUtS7nX+PJnP7pZfKXaQtPeCvKEDlZRmSkDOFAWdGBunbtGiEhIaxZswbI8psAPv74Y7y8vP62A9W/f3/69++Pv78/Pj4+1K5dmy1btjz3eq3pQD2N3mgmJe1PZ0WSJFJTU7Gzs0Or1f6l8Xbv3s2jR4/w6fsJB+5LlHW3R/3H9qaTW3FqtOnJpR3LKdfxY47efEybWi/uhGH48OFs2LCBt956i2+//ZbXX38dg8HAnj17mDBhAk2aNKF3795otZZ/5JsXceH1O2kcDYkBrQ2uDjaogJRMI7HpemqULc7bjbxwddBZPNaLTnbBWFdXV/GXuQKEt6IMkZNlREbKEA6UlRyoJ5k5cybbt29n2rRpNGnSBPj7DtTRo0fp3LkzDRo0oESJEhav19oOlCRJBIQncCA4mquRiewc+V6+j/kkU/p3eu7zJ2f14iSw4B8d1TpERUXlqtfVqVMnfH19kSRJ8fdjdOsKOOnU+N98RPjjVADsbTQ0reDGsDcq4mijeikcBuFjKEPkpAyRk2VERsoo9A5UUFAQ169fZ9KkSezatYsZM2bkcKCmT59OlSpVqFy5cg4H6oMPPuCXX37BbDazd+9eWrZsyaZNm2QBWK/X83//939cuHCBoKAg1Go1ZrOZEiVKMH36dPk8nnagVCoVNjY2NG3aFLVaTe3atXn8+HEOB+rIkSN07tyZESNGsHz5cs6ePctvv/3Gq6++Kk/gnsbaDtS5GBX+0Wr0JrDX/rN3Sr3sLFmyhNKlS3PmzJm//N5KQFFPuJ+mQpLAw06iuCaeSyfvcumfP9X/FOFjKEPkpAyRk2VERsootA7UsWPHGDJkCBs3biQmJoZevXpx+/ZtAgICOHfuHOPHj+fChQs0bNgQLy8vYmJigKy7pYzGrLYZ165dk72ViRMnyg6Uvb09n3zyCevWrUOr1eLo6Mj+/fvZuHEj77//PpDbgTp+/DhGo5EWLVpw4cIFrly5gp2dHc7OzvJr1qxZQ1paGv/73//kx9q0acMbb7zB0aNH87xeazpQt2JSWLE9CFcXCQ9nWySzxJ0m7YkOPE7jYd/hVKICM7pUo1qJIqSnp9O7d2+uX79OYGBgjsljXkRERFCvXj1GTJzGNddmuDrYYK/LustQkiSOLJ5EeuJjan28kA+avMJ7jcrm61r+TbLdni5duohl8ucgfAxliJyUIXKyjMhIGYXagRozZgz+/v6sXLkSs9lM2bJZv3xtbW1ZsmQJa9euJS0tjdDQUI4cOcK0adNkX+ns2bMA8irQxIkTc9yW7+joyNKlSwE4efIkCQkJ7Ny5k1mzZjFjxgx5AvWkAyVJEqdPn8bOzo5jx44BWT3TPD09SUtLk7fqVq9eTa9evRg3bhxVq1Zl165dXLp0iXr16j3zeq3pQB2/FUdqponyRR1QqVRkGlKJuuxPzbbvU6VWfe4+TuP8g0yaVnPF1dWVxYsXU6tWLfz9/Xn33Xefe2xXV1cGDRrE8nlzaD1wIrHlWlJcZ48mPYFLu34i6tp5avX/kvIli/FO48q4utjl61r+TbLdHuEZKEPkpAyRkzJETpYRGSmjUDpQq1atokyZMuzfv1/2n/bt20fXrl1Rq9X88ssvz/SfIMuBWrNmDW5uboprGpnNZtlFunv3LhUqVODIkSN4e3tz584deWZ54cIFGjRogIuLC1WqVCEoKEj2ph4+fMjQoUPZuXMnc+bMUTSuNR2o0IdJaDV/CMzJmUSH38SYmY5UsgaXD27h1vFdnHgcybdF3ejRowcjR46kbNmyXLx4kXfeecfi8RcsWIDBYGDtj7OwdXBG6+RK2qMHqDQ2VH/3U5q/2YFPWnlR1EFToPbshWegDJGTMkROyhA5WUZkpIyC4ECppH+6/DCwc+dOunXrxkcffcTy5ctp27YtAQEBbNmyhf3797NlyxY8PT3lLSa9Xi/7T4DsQBmNRmxtbbl79y4AGo0GDw8PMjIy8Pb2JioqioiICIoVK8acOXMYO3Ysn3zyCbNmzSIyMpLGjRtjY2PD3bt3OXXqFM2bN6dcuXJERkbKDtT169cpVqwY4eHhSJJE8eLFSUtLQ6/Xo1Kp0Ov1/PDDDzRr1uyZq1AzZszI04HasGFDvh2oLWFqguJVZJrAJIExIZo7S4ei8yiP/lEERao0pkKVGpSVYvD390eSJIxGI927d7e4AvUkDx484MSJE8QkpqJxKUH1xq9T1t2R8s6gsdw+TiAQCASCAk9aWhq9e/cmMTHRooJjlQlUq1at8Pf35/3338fDw0OuAWU0Ghk1ahRNmjTh0KFDcmHM7BpQ2eULmjRpwrlz53Idt1y5cty9e5fU1FTatWvHnTt3iIqKAqBevXoMHTqUjz76SL6z7sm78LInUE5OTtSvX58LFy7IflSnTp3YuXMnCxcuZP78+aSnpxMdHZ1r/GdFldcKVNmyZXn06FG+Hag1p8P538GbaNRZd4FJkkTgnJ6YMlIo128OtmVqMapVJT56vQLx8fE0a9aMsLAwzp8/T926dfM1dkFGeAbKEDkpQ+SkDJGTZURGyvgvHahixYopmkBZZQuvUaNGHD16NM8aUIsXL2bVqlVMnTo1zxpQ8KcD5e3tzdmzZ0lPT89xfEdHR06cOAGAl5cXqampXLx4Mdd5POlAFS+e1fh1yJAhzJs3D8hyoNzc3OTJz+HDhwkPD5crlAOYTCYAeXUsL6zpQBnMoFZl3QUmmUEyGzAb9SCZSb55HtviXhglCa1WS0BAALGxsQBER0fLta4KM8IzUIbISRkiJ2WInCwjMlJGoXKg/okaUP8ETztQ2TxZA+rJPwMsXLiQWbNmyV+HhITQo0cPqlatyjfffPPMsazpQN2OSaG4s46kDCMpmUbSY+4jGTIoUq89cae3En9mO+PnaflMnXUeLVq04NatW5w6dYp27drla+yCjPAMlCFyUobISRkiJ8uIjJRREByof3wCld8+eAD9+vXj/Pnz3LhxA5VKxeXLlwGoUaMGOp2OjIwM3nvvPYKCgrh9+zY6nU5+Tban9OjRI3Q6HXfu3MHb25uHDx8C8MMPP7Bq1SrS0tIoUqQIdnZ2cssJs9nMvHnz2Lp1a45bGRctWkSZMmWeec3WrAP1IFJNYgpkGFWYJVD9sT2Z+egeSBIaJ1fs7e1xVBuJjY3l2rVrZGZmcufOnZeyF9lfRdRaUYbISRkiJ2WInCwjMlLGi1wH6h93oLp06UJycjInT56kZ8+eORyo6OhoDhw4wBtvvMGGDRty9cHLdqDKlCkj9797kjt37lC+fHlSU1MpUaIEKSkpuV6TfTlPr0BlO1A6nQ4HBwd5ApWamkrHjh3ZunUrBw4cYPPmzXTs2BF3d3f27NnD/PnzKVWqFPfv38+1YpWNNR2oVafC+f7QTdQqsNNpwGzmypx3MWekULr7FByrtWBkq4p8/HpF7t27R8uWLWUhPHuFrzAiPANliJyUIXJShsjJMiIjZRRKByq/ffAA7t+/Dzzfgcpu9pvtQGXL5NmUL18+h/Sd7UANHz48lwOVmprVqqN9+/a0b99efs+bb76Jg4MDs2fP5syZMzRr1izPa7ZqLzyVGpUKJMj6T5YIBYAxJQ4kEyqVGhsbGxISEmQxPiMjQ3w4EZ6BUkROyhA5KUPkZBmRkTKEA1VAHKi8yN7Ke3KF6Wms6UDdepiEh5OO5EwTGUYTGbH3MWem4VytOQ9/XUbC2e0sOlKfjapkTp06Re3atYGsljSvv/56vsYuyLysnsG9e/dYsWIFZ86cQa1W4+3tzcCBA/H09Pxbx/uncjKbJYIeJHE67DFxqQaKOel4rVJRapR0VvQ5e9F5WX+e/mlETpYRGSmjIDhQ//gW3s6dO+nVqxf16tWjWbNmLFq0SK4D5ePjw61btxg9ejSLFy9+Zh2opx2o7DvsnudAZd+5l+1ABQQE0Lx5c5YtW8bAgQPlLTxbW1vs7e3z3MI7e/Yss2bNIiIigpCQEFSqrIax7u7u3Lt3L89VJrBuHahNt9XcSQZXW0gxQEJ0JME/DKPmgK9wdnAg7OxBpIQHVCzmQIsWLWjSpAlDhw6lffv2ckV2wcvBqVOn+P7777GxsaF+/foYjUYuX76MRqNhypQp8uT538ZghgP31FxLUP1x16iEWVKhU0NtdzNtS0tocvfsFggEgheOv1IH6h9fgcrug3fy5Em8vLwYNWpUDgcqICCAFStWsH379lwOVPYE6vDhw7IDJUkS9evXB/50oEwmE7///rvsQOn1evk12fPBYsWKodfrqVChQo7ze9580cHBgaCgIGJiYjAajZhMJqpVq8Zvv/32zMkTWLcXXtL5+6w8dZfi7vaUVKkwFXfjVhF3DGEBVO3/GXbl69Ov2Sv0aZK1gufv709iYiKDBw/OsfJW2HjZPIOgoCDeffddunXrxtKlS+X+jY8fP6Zv377MnTuXoKAgSpYs+ZeO+0/ktPLkXcJu36eUhw4nWw0qlQpJkkjKMHIzzchrxV/h/QLURzEvXrafJ2shcrKMyEgZhbIXXkF2oGrXrs2dO3d48OABr776KnFxcQQHB8uFOZ+FNR2oNjVLsudqNA8SMinjZo/GxoZyzTpx89AG7MrXp3LTNvjUKImNjQ3h4eGMGDGCOnXq4OPjY/Wtk+zcXkQMBgMZGRno9frnTpoLCosWLaJYsWIsW7YMnU4nu27Ozs6sXr2aqlWrsnz5ciZPnvyXjpvfnBLTDBy4cg87TDioNZgNJvk5Jw2kSnr2XAynQ/WiOOisUnbuX+Fl+XnKvuPY2gi/xzIiI2UIB6oAOVCRkZG0atWK8uXLk56ebnHyBNZ1oIo6aPikdUXm/36bu49S0apVuDXtRrHo+wSunUHmxR18F+LNvXv38PPzo1SpUuzcuROj0fjMYyYmJvF/S1dy9PgJJFQ0ea0l4z8eQMmif221zMnJKV/XJvjruLu7P/O5r7/+WnHfyH+bLaP+6zMQAPLE21oIv8cyIiNlFAQHyqp1oIYOHUqtWrWoVq0aM2bMyFUHqlOnTkDuOlC3bt0iJSWFlJQUJEnKVQcK4Nq1a+j1ejIzM2UXBCzXgVq5ciXe3t5UqFCBadOm4eDgIP+rLDIyEm9vb8qVK0enTp2YPn263NKlRIkSz7xma9aByqazOwSrVYQnq3B31tDio08w3H2N00cOsm3bNhwcHOjbty+tW7cmNDSU0NDQPI9z/vJV/vftt+gz0nAqUxXJbObcoV38+P1sPvz0c3zqVfpHzlcgELx4/Fu14USNI8uIjJRRaOtARUZGcvv2bVq0aEHZsmWpXr06Bw4c4NNPP2X69Ols27aNEydO0KBBA9LT02WPyNvbG39//1zHvnnzJl5eXgCULFnyuf3qnlUH6uOPP2b16tVkZGSg0WgoUaIETZo0Ydu2bXLvvLx4XkzWrAP1NPnZFw4LC6NOvVdxKFON5gM/x6NkaQDioyI4suwLMuKj+PX4OZrXrGDhSFm86Ft4hw8fpnXr1i/FMnn//v0JDQ3l1KlTuVZOMzMzqV27Nl27duXbb7/9S8fNb04PkzIYtyUQlQpcHXS5no9L0aPVqJjfsy7ujrmfLyi8LD9P1t7CE36PZURGyij0daBKlSqF2ZxVsyg8PJyHDx+SkJCAi4sL8+bNw97eHgB7e3v69OnDvHnzGDt2LL///jv16tUjNTUVGxsb5s+fT79+/Vi5ciWzZ88Gsv4ldePGDTZv3kxaWhr9+vXjo48+Yvny5Xz44Ye5HKjsFaTAwECqVq3Kjz/+iMFgoE2bNgQFBQFZvfMePHhAeno6ZrOZRYsW8dVXXzFu3Dj27NlD586d87xmq9aByoO/62LMnDsPSa3h9Q9n4lLEGZM+a9JXpGhx2oyczfbPezH7+8XsWPrstjVP8l99+JX8EjAYDNjZ2eHq6vpS/CU1btw4vL29WbJkCZ9//rk8iTKbzXzyySc8fvyYMWPG4Orq+peOm9+cXF3hjZoJ7A+KwlVrj632zy3vDIOJdKBb3dJULP33yiy8KLxsP0/WRvg9lhEZKaNQOlDfffcdLVq0wNvbm82bN7NkyRLOnz8vO1Bubm4sW7aMWrVqceLECZYtWyaL5AcPHuTatWuMHTuW3377jQ4dOvDVV18xadIkZsyYgU6no379+tSvX59ff/0VyGr2u337do4fP86HH36Y67wqVKhAsWLFOHXqFOfPn6dhw4YkJSVhMpkIDQ3lwYMHlCpViilTpgCwevVq1Go1o0eP5uDBg2zfvv2ZEyhrOlBPYzAYeO+99/J1jN0T874OgEPrFuG0blG+jm9tlHgc9x+ncPGRisSz4Xi62NOkgjtOtgVXYn7ttdeYPn0606ZNY+vWrXTt2hWDwcAvv/zCrVu3WLJkCV5eXn/55+2f8AwGNCtLZHwaVyMT0ahU2NqoyTCYkYAGr7jwQaPSBd73EN6KMkROlhEZKaNQO1CDBw9m27Zt1KxZky5duqBSqejbty++vr58/PHHDBgw4Jki+d69e/Hy8iIlJYX09HQuX75M2bJlSUpKIjg4mPr168sOVFxcHMnJybKsnr2FERkZScOGDYmOjkaSJFQqFW+88Qbbt2/nwYMHXL16lWnTplGmTBnCw8M5e/YsXbt2JSIigri4OCIiIjCZTFy+fJnIyEgqVXq2G/RvOFCCP9m2bZu8evk0JgmORam49FhNulGN6v4NAIrYSHiXlKjlXnDvoKpfvz5ffvkle/bs4bvvvkOlUlGnTh0GDx5MqVKl8uW35NczaG4Lbm4qghNUJKeCuw5quUlU1yZy/HBEvo79IiG8FWWInCwjMlJGoXOgzGYze/fupXnz5jRq1Egupnn69GkSExO5cuUKgYGBzyymWapUqVxlCbLZt28fHTp0UOxAlS1bloiIrL/Av/76a7777jvS09NlB+qdd97B399frkXVt29f1q9fn+u4K1eufKYf9W87UH5+fn/LxWjbpTvXwyLoOHkZNlpNjufMZhM7Pu/NKzUbcsZv/X9aPfro0aN0796dbt26MWPGDEqXzlrB2LlzJ+PGjaNVq1Zs27Ytz/euPxvBz2fvYW+jxpiWSHEPD0ySREyyHhuNms/aV6FJhWffyVbYED6GMkROyhA5WUZkpIxC60ABhISEcO7cOcqXL5+jmKbRaKROnTpMmzbtmcU0O3XqxKZNm2jatCn/+9//iIqKom/fvjx+/FgeJ9uBcnd3R5IktmzZwsqVKxkyZAgrVqzI5UBBVtmCzMzMHA7UwIED5ZpSAMuWLcPJyYlXX32V5cuXc+nSJVauXEm/fv2eec3/tgP1d489dtQwevd6l8u/7aJx++45JkmX9q4lIyGGQYOGyJPa/4rvvvuOhg0bsnLlSrmMhI2NDb1790ar1TJo0CAuXLiQq/J2fKqeXRfuopPMuOhsiE3MwGjIQK1S42kP9+JS2HL2DvVKOb4U7UXyw9MemfAxlCFyUobIyTIiI2UUKgcqG19fX4xGY57FNBcvXkzXrl2fWUwzNTWVlJQU1q9fT/HixalXrx5jxoxh2rRpFC1aFEB2oLJp3749p0+f5pdffmHFihV5npPZbCYtLY0VK1bQsGFDAObPn0/nzp3l83B0dGTp0qX4+/tz+fJlatWq9dzJE/x7DlREXBrXHiTk24EK3bWI0F15e06fDe7GZ4Pzdfh/jOfN/p/V2NkS/sDCv3k+LxPZHpnwMZQhclKGyMkyIiNlFEoHCv65YppPrhJkr0Q8a8fx0qVLREREYGdnJz+WXZYgr5Wop4/7JEePHqVz5840aNDgufWfsrG2A5VqgEORam4lqcg0WX69QGCJp30p4WMoQ+SkDJGTZURGyniRHSirTKCeLKbp4+ND3bp1adu2LRkZGbmKaVapUgXIWUzTwcEBBwcHatasSXJyMnZ2dvK/mOPi4gAYOnQo58+fJzAwUJ4g2djYMGbMGPk8rl+/nmM7KjExEY1Gw2uvvQZk9cvLyMjA1tZWPv6RI0fo3LkzTZs25ezZs5w9e5YSJUowePDgZ1Z5tmYvvEyDiS/8rnNHn4BHURucdRrMA6Zzce0s3Ko0wKf3SOZ91AF9Wopc5mHQoEHMnTvX4rHT0zMwSeDkYGfxtf8WGRkZVKlShaFDhzJt2rRczz948IA6deowd+5cBg0alOO5wPsJfLnnBm4ONthq1Tx6/IhiRYuhUmdNmB+n6LHVqln0Xl2c7Qr30nn2Fp7wMZQhclKGyMkyIiNlFMpeeJD/hsLZK0TZd89JkpRrFenmzZtER0ej0+nQaDRotVqSkpJy3J1VvXr1HLe8x8bG4uDgQIMGDTh//jwJCQmYzeYcK1Jr1qwhLS2Nw4cPy489fPiQPXv2PHMCZU0H6kRYPIGRSZR2tcfORoNZMnPHfxtFy1ejzZjviEkxEhRrpG3N8sycORMXFxcmTpzIF198QZkyZZ577L9YMuhfY8CAAaxatYqPPvpInmDDnzWP7OzsGDJkSK7JafMiLlS9EkdIdBJlnOzQ6uzQ2TugVqkxmMxkING5blnKlvD4ty/phUf4GMoQOSlD5GQZkZEyCp0Dld+GwqmpqaSlpREWFiY3AZ41a1YOB+ro0aO5xvX09GTevHl8/vnnQNYv4gEDBsjPv/766+zatYsjR47Ij82ZM4fJkyfLW3WTJk3i559/JigoiG+++YaEhAR27tz53Ou1pgN1LOQhkllCp1WRaTARGxNF3J0gmg2ejs5GS0J4IIt/PEmKd3XefPNNBg4cyLRp09iwYQNjx47N19j/FVOmTOHQoUM0bdqUDz/8EG9vb6Kiovjpp584c+YMq1atwt7ePs9sP2xRjtn7Qwh/lIZkAPt0A+kGM2l6E9VKONO9fknhHjyB8DGUIXJShsjJMiIjZQgH6l90oMxmM5mZmWi1f17S0w5Us2bNSEhI4MKFCzRo0ADIqkwO0KRJEyBr8lexYkX27NnD1q1bMZvNDBkyhLlz5z6zkas1HajgW2pSUyE4JYVkA6TFPADgzoNHXJ78Pukxd7kA+C3K2pbp3r07Tk5OnDt37l/re2UNpkyZwqZNm1i4cKFc26tmzZpMnz4dV1fX516bjysEGNSE6uHh4wTsNBL13CQa2idx1j/yX7qCgoXwMZQhclKGyMkyIiNlCAfKig5UREQEer0eW1tbkpKSnutA2dvbU7p0admBcnV1JTY2loYNG1KqVCkArly5QmhoKOPHj5ff5+vry6lTp7h27Vqe12tNB+rGoZvcOHcPg8mM1kZNkWIlQKUm+tdl2JeqQvk+s+n7Tlveq27PDz/8wJIlS1CpVLRp04aOHTvma+z/mvfee4/09HSioqJwcnLC01N5O5A+BgN+Bw7RtPnrFHW2x9ZGY/lNhRDhYyhD5KQMkZNlREbKEA7Uv+BApaenA1kTK5VKRZ8+feTXPO1A3bhxg9dff52oqCjOnj1LbGwsarU6xy3x2b37nub69euEhIRQtWrVXM9Z04Eq4WpPhtGMrUaFrUaN5OCM1tEFY1oSZXtMQXIoSulirtSoUYlFixZx8uRJLl++jI+Pz0vx4bSxsfnbk1A7DZRyd3opcrA2wsdQhshJGSIny4iMlCEcKCs6UJs2bWLQoEHs2bOHiRMnsnfvXnl77mkHqn379rRv354HDx7g7e1N06ZNqVmzJj/++CMLF2ZVB8pe5bh06RL16tUDID09HQcHByIiIvKcQFnTgbr/OBUHGzV6k0S6wYQpLQFjSjxqnQN31kygaP12+CWUJ+2iC4cOHeLy5ctotVr8/PwYMWJEvsYuyAjPQBkiJ2WInJQhcrKMyEgZwoGysgO1ceNGBg0axKZNm+jQoQPDhg3L4SnlVQcqMjKSVq1a0aBBA1atWsX06dNzvCd78tWxY0eMRiNVqlTh3XffBaBcuXJ5Xq81Hagrt9TYSQAqkg2QEZ9Vjd21RW8Sz/xC9OE17D0MewGNRkPHjh05f/48J06coEKFCvka+2VAeAbKEDkpQ+SkDJGTZURGyhAOlBUcqLFjx7JgwQIcHBz44IMPcHV1JT4+nvbt28vn8bQDdebMGdq1a4deryciIoJXXnmFR48e5Zj8tG/fnjJlyuDh4UHv3r2ZPHkyJ0+epF69ejluqX8SazpQwb+GEnrhPnrM2NmAzq0oD1Qq4o+vw6aIJ8Vf702zWpXoUM2NvXv3smPHDjQaDa+//nqBd6Dyg/AMlCFyUobISRkiJ8uIjJQhHCgrOlBbtmxBkiRSU1MB5P+PGzeO3bt3A7kdqC1btuQI58GDrDvaJk+ezGeffQZkbeGdPXuWESNGMGnSJLRaLSqVKk/HKRtrOlCl3R1IM5ix1aix1aqRXNzROrpiTEuiQp+vMTsWpU3bqgx+oxKDBg2iQYMGXLp0iS5duogPJ8IzUIrISRkiJ2WInCwjMlLGi+xA5e5j8g/g5+dH48aN5V54ixcvJjU1lTVr1uDv709CQgIDBgygW7duhIaGEhoaSrdu3ejatSvwpwMVHBxMeno6iYmJcm2nbAfq/v37SJLExo0bsbe3Z8+ePdSoUUPucQdZDtSTE6/vvvsOSZKIjIykcuXK9O3blzlz5uTa6ipVqhRVqlShd+/e/Pjjj9ja2hIeHm6NqCzyMDETOxs1Jkkiw2gmIyUJY0oCKpWau5tnkhFynIBzZzl06BAffvghly5dQq1Wc/Dgwf/kfAUCgUAgKAwIB+opBwrg8OHDbNmyhcuXL7N9+3ZMJhMlS5Z85vVaUyKPTkqnuJMtyZlGHqfqSXv8EJBwf6MfiWe2cG/bHFZsgxVkzZw/+ugj9u/fT1hYWKGWFIWoqQyRkzJETsoQOVlGZKSMQiuRF2QHavTo0SxduhQHBweKFy+Ora0tBoOBUaNGPfN6rSmRx0eriYpXYTCDSgI7B+esx0/9gkprg3ujLpQpVoQqjpkEBwfz448/otFoePToUYEupPlPIURNZYiclCFyUobIyTIiI2UUOom8IDtQW7duRavVylXNsyube3g8u3+aNSXyx2ciOHkgFJ2NClutGhxKoHF0w5yeRKWhK8DZk4/e9GJoywqYzWYaNWrE1atXGT9+PF5eXvkauyAjRE1liJyUIXJShsjJMiIjZRRaifzfqAN1//594M86UFu2bGHixIm5HKgn60B99913fPfdd3nWgcomNTVVnnQZDAZ5NvrWW2+xYsUKBg0alOt6rSmRJ6QbsNWqMZrNGE0Skj4VU3oSSBKRexdS3Lsf0bGuREXZsWLFCoKDg4GsLdHq1avna+yXASFqKkPkpAyRkzJETpYRGSnjRZbIhQP1lAN1+vRpTCaT/PWuXbuYPn06ffr0kSX3p7FqIc34dIo725KUaSA+1UB6TBSYTbi/0Z+EM1u4s3IsX62Er/7IqG/fvhw5coTr168X6j124RkoQ+SkDJGTMkROlhEZKUM4UAXQgapQoQIff/wxFy5c4Pr165QtWxaTycSECRNwc3PL83qt6UA9jlITk6hCbwIksLHLOl7Spb1IZjPOVZpSzNWJMraZ3L59m59//hmVSkVUVJRwoBCegVJETsoQOSlD5GQZkZEyXmQHSiU9LRf9A3Tp0oXk5GROnjxJz5498fDwyOFAHThwgDfeeIMNGzbkcqB27drF0KFD2bBhA/b29qSmpqLT6dDr9WRkZLBv3z46dOhAmTJliIyMzHPsbAfq6RWoTz/9lO+//z7Pc85+TWpqKuPHj+fVV19l+fLlXLhwQT6PZ5HXClTZsmV59OhRvh2otWfC+fbXm9howE6b1RD3yre9MKUnUemjH1C7lWXMHw5UZmYmTZo04dq1awQGBlKtWrV8jV2QEZ6BMkROyhA5KUPkZBmRkTL+SweqWLFiJCYmWvz9LRyopxwoR0dHli5dir+/P5cvX6ZOnTpcvnz5uddrTQcqNVPCRq3CbJYwmSUkQwamjFQwm4k9vhnPVv1J01fEYDCwbt06bt26BcC1a9eoXbt2vsZ+GRCegTJETsoQOSlD5GQZkZEyhANVgBwoyGpU3LlzZxo0aECJEiUsXq81HaiIuBRKFLElKcNIQrqB9IeRYDLg+lovEs/tICnoCBMWwcQ/7lbs2rUr58+f5/Lly3Tr1i1fYxdkhGegDJGTMkROyhA5WUZkpAzhQBVAB+rIkSN07NiRYsWKce7cOXQ6HdOmTWPs2LG5JlrZWNOBehip5lGiigwTSBJobbKuJzXkFJLJiH2pyhRxcqSYjYGIiAgOHDiAJEncu3dPOFAIz0ApIidliJyUIXKyjMhIGcKBKkAO1AcffMCGDRtyPV+lShVCQkLyfK9VHajTEcw9GIpWDXY2GiRJIvDbXpjSkynX/3/oSlVj9JtefNiyAklJSTRp0oTbt29z4cKFQr2FJzwDZYiclCFyUobIyTIiI2UIB6oAOlAtWrRg//79REdH8+GHH5KQkEC1atXYuXPnM6/Xmg5UpklCo1ZhlsBsBkwGzIYMkMwkXz9JsWLl0BtBo9Fw/PhxoqOj5XxeffXVfI39MiA8A2WInJQhclKGyMkyIiNlCAeqADlQp0+f5vXXX8+x9deuXTu+/fZb4uPj8yxlYE0HKiw2GU9nHUkZRlIyjKTH3EMyZFLk1U7EndtJ3LmdjJ+vYZIqazxvb29CQkI4ffo0HTp0yNfYBRnhGShD5KQMkZMyRE6WERkpo9A7UEFBQVy/fp1Jkyaxa9cuZsyYkcOBmj59OlWqVKFy5co5HCiz2YxGo6FkyZK4uLjQunVr/P39gSwHavv27UyfPp2goCBsbW2ZOXMmmzdvJikp6bkO1KRJk1i4cCF6vZ7o6GjOnTvHggULmD59uvyaa9eucefOHRwcHDCZTBQvXpzY2FgAoqOj85xAWdOBehCpJjFZRboRzBKoNVmlDDKjb4NkRufiib2DA05qAw8fPuTy5cvo9XrCw8OFA4XwDJQiclKGyEkZIifLiIyUUWgdqGPHjjFkyBA2btxISEgIs2fP5vbt2xw4cIBRo0ZRvXp1Lly4QMOGDYmPj8fW1pbRo0fj4eGB2WymVq1aBAQEoNfradCgAQEBAezbt49ff/0VPz8/wsLCco3dv39/Vq9eDeRegXr77bdlP+ppJEniypUr1K9fHxsbmxw99LK5du1anu1RrOlArT4VzneHbqJWgb1Og2Q2EzjnXUyZqZTp+QUOXk0Y1aoiH71ekaioKFq0aMG9e/c4efIkjRo1ytfYBRnhGShD5KQMkZMyRE6WERkpo1A7UGPGjMHf35+VK1diNpspW7YskOULLVmyhLVr15KWlkZoaChHjhxh2rRpDBgwgP379xMfH0/NmjU5ceIEAMuWLWPChAkAlChRgvnz5zN//nzgTweqWLFiDBkyRJbSIbcDtWvXLgDmzZvH+PHj+eCDD1i9erW8Pbh582bc3d1p0aKF7Dz5+fnRvXt3DAbDM0saWNOBMqMieydTkgDJjCSZQZLQP76PQ8UGmCU1NjY2REVFyQU/09LSxIcT4RkoReSkDJGTMkROlhEZKaNQOlCrVq2iTJky7N+/X/af9u3bR9euXVGr1fzyyy95+k+nT5+mQoUKXL9+nZiYGDw9PWnXrh3Dhg3DycmJGjVqyONkO1AbNmxg9OjRFv0nyHKgvv32WzQaDatWrZInT5C1kuTq6sqxY8cwGAzY2Nhgb2+PwWCgbNmyz2zlYk0H6nZMMh7OtiSnG0nJNJIeG4E5Mw3H6i2J+c2XR/7rmLjQjmmarHHr1q2LRqPhyJEjvPHGG/kauyAjPANliJyUIXJShsjJMiIjZRRqByo5OZnevXvnqAH1+PFjunfvzty5c1m9enWeNaCio6MpU6YMsbGxsgOVPRHo2LEjtra2uRyoUaNGER8fj7e3N4mJibi4uODi4kKpUqWoVq0aN27cAP50oDIzM5EkSXabIGtlq127dsybNw+1Wo2joyM6nU6egLVt2/aZ12tNB+rePTWpqZBpVGE2/7EKBUj6jKw/aGxQabSoVFkNkGNjY8nIyOD27dvCgUJ4BkoROSlD5KQMkZNlREbKKHQOVKtWrfD39+f999/PUQPKaDQyatQomjRpwqFDh9i0aROQuwbUpk2bqFu3LoDsQEmShJ+fH507d2bMmDFWcaBSUlLw9PTEYDBgNBoB0Gq1GI1G1q9fzwcffJDne63pQK08eZd5v91C9YcDhcnElTnvYs5MpUTHTyhSry0jWnkx7I2KXLt2jbZt2xITE8OhQ4cK/QqU8AwsI3JShshJGSIny4iMlFFoHahGjRpx9OjRPGtALV68mFWrVjF16tRn1oBKSUlh27ZtuWpAeXp6AsgO1NM1oHr16qXIgRoyZAi+vr65tvdu3LhBeno64eHhaLVa3NzcOHjwIO+88w729vbPvF5rOlAajQZUoEKFSgJJBfzhRKl1toAKjSbLgXJycsp6PWBnZyc+nAjPQCkiJ2WInJQhcrKMyEgZhcqBepFrQFmiatWqFC1alJUrVzJlyhRMJhOzZ89Gq9XSqVOnZ77Pmg7UzYfJFHPUkZxpIiXTRMaj+5gzUrEvX48HO/+H9tBypqxwYo5OxYMHDyhXrpw88WvSpEm+xi7ICM9AGSInZYiclCFysozISBmF0oF6sg/e0KFDqVWrFtWqVctVA2rx4sXypOTpPnhOTk707duXuXPnEh0dzbx584A/++Bt2LCB/v37s2DBApo0acL06dMt1oACiIiIIC4ujsePHwNw+fJlALy8vHBycsLZ2Zn+/fvj6+vLzJkzgaxJ248//pjnClM21nSgwiPUZGaA0ajCaAaTKWtrUe2YNVk0paeSZtSTiRmz2YxWq0WSJG7cuCEcKIRnoBSRkzJETsoQOVlGZKSMQuVAPdkHLzIyktu3b9OiRQvKli1L9erVOXDgAJ9++inTp09n27ZtnDhxggYNGpCens64ceP48MMPuXHjBhqNhmPHjmE2m7G3tyc9PV12oLy9veXCmk/i4+Mjh53XCtSAAQNYs2ZNrvcdOXIEb29v0tPTcXd3JyMjI89re/jwobyN+CTWdKCWH7/D4iO3kSQJe50WTAYC57yLWZ9Osdc/wO21dxnWqgojvCvh7+9Pjx49SEpKws/Pj3bt2uVr7IKM8AyUIXJShshJGSIny4iMlFEoHagn++CVKlUKs9kMQHh4OA8fPiQhIQEXFxfmzZsne0X29vb06dOHefPmUaJECc6dO4fJZKJ169b873//49KlSwwaNIjt27fTuXNnjh49ypgxY4iJiWH79u0sXLiQu3fv8n//939cunSJ+vXr5/KfIGtSVa5cOUJDQ9mxY4fcly+bDRs2UKRIEW7fvi1vG+r1eipWrEiVKlXynDyBdR0oe50WswQatRo1IGm0oNGCSoVD2ZqoNDrsdDp0Oh3169fH3d2dpKQkSpUqJT6cCM9AKSInZYiclCFysozISBmF0oH67rvvaNGiBd7e3mzevJklS5Zw/vx52YFyc3Nj2bJl1KpVixMnTrBs2TI+/vhjqlWrxtdff40kSfz2228UL16cc+fOYWdnx9atW1m2bBk6nY4mTZowaNAgNm/ezNtvvw1kSeJ+fn7Ur1//mef35Zdfsnr1alkof5K0tDTUajUlS5aUHayoqChMJtNz72izdh0oNwcb0vQmUvQmMuMeYE5PxrZEJSJ+noKdR1lmbnbhR0cNt27dwsHBgSJFiuDn50ft2rXzNXZBRngGyhA5KUPkpAyRk2VERsoo1A7U4MGD2bZtGzVr1qRLly6oVCr69u2Lr68vH3/8MQMGDMhTJDeZTBQtWpT09HSio6O5fPkyU6dOZeDAgSxdupTg4GCuX7+ew4GKjo7GbDaTmJgoi+Q7duxg+PDhREdHy9t42Q5UREQEkiRhMpm4fPmy7EC1adOGCRMmMGLECEaNGoXZbKZfv34AciX0vLCmA3XrjhqzHsxGFUYjGPRZEzXb0rXIfHiXjNh7PHwcSQxgNpupWrUq4eHhBAcHCwcK4RkoReSkDJGTMkROlhEZKaPQOVBms5m9e/dSp04dgoKC6NChA7t27ZL3Fa9cuUJgYCDTp0+ndOnSVK5cmeDgYFkkf/vtt9m/fz8GgwGVSkWDBg349ddfKVq0KPv27WPChAkEBwfnGlun03Hv3j08PT1lB6pq1apyIc1XX32VS5cu5XpftgMFWd+sESNGcPv2bXn7sUKFCnnWnMrGmg7UUv8wlh27g9lsxs5Gi8qUyZU57yIZMnF9tSMe3n0Z2qYuI98oz5YtW/joo4/IyMhg8+bNdO3aNV9jF2SEZ6AMkZMyRE7KEDlZRmSkjELrQAGEhIQQFBQkNxOOiYmhT58+JCYm8vvvv5ORkcH48ePlZsJeXl7ExMRgMpk4fvw4zs7O/P7770RFRdGvXz+++eYbeQwfHx/69etHq1atcHV1Zfz48ezevZsFCxbInlJeDlSXLl3o27cv9+/fZ+nSpeh0uhwOFMDVq1dJTU1l3bp12NjYyHcIPg9rOlBF7HWYzBJajRqtWoVZpUNtY4vJaMDt1fao7F1wttdhb29P9+7dmT17NiEhIdSoUUN8OBGegVJETsoQOSlD5GQZkZEyCpUDlc3SpUuRJCnPZsLNmjVj8+bN1KpV67nNhOvVq0e9evX46quvcjUTzmbTpk0cOnSIsmXLEhMT89xzyt5my65U/jTx8fFMnToVPz8/3nzzTQYPHky9evUYN27cc49rVQcqNhkXexvS9Fm98AwJDzGlJWHjVoq7qz7FsWx1vvvVnZ1Fbbl69SqJiYnY29uzc+dOqlatmq+xCzLCM1CGyEkZIidliJwsIzJSRqF0oODFbib8PA4dOoTZbCYyMpKqVaty8+ZN6tWrx7179+QJYF5Y04EKua1GZQS1WYXBCBnpqQA4Vn+dxPM7SLkbyK27cOuP17ds2ZLr169z5coV4UAhPAOliJyUIXJShsjJMiIjZbzIDtTfmkCdPn2aFi1a0L59e/bu3Zvr+XHjxpGUlMTkyZNzFNK8du0akiQxfPhwNBoN1apVo2HDhvI2mYODAytXruThw4cAVKlShW+++YZSpUoBfzYThpzFNBcuXEhkZCTjx4/n888/lxsKP9lM+MnK5tlIkiQX0zxz5gzDhg1DpVIxe/ZsOnbsyA8//ICDgwOvvPIKBw8epE2bNnnmMXny5ByrVNkOVNu2bfPtQIUduU3wybuYJDNO9hoci5ciSmNDwqnNOFVrRvFWA+nfvhHDXiudo4J6586d6dixY77GLsgIz0AZIidliJyUIXKyjMhIGf+lA6WUvzWB8vX1ZdSoUfj6+vLgwQN5gjNv3jyGDBkizxh79uzJvHnzGDt2LD179uSjjz6iSpUqhIWFMWfOHGbMmEG5cuU4dOgQP/30ExEREZQuXZoyZcowZ84cBg8ezPDhw3F1dQWgb9++8jksX74co9HIiBEj5McyMzNl8btr164kJiYycOBA+flVq1axf/9+fvnlFwAyMjLkkgeTJk1CrVZjNpsZNGgQO3fupEePHnz55ZdUrlyZS5cuPXMCZU0Hys3JFqNJwkajxkatRrJ3RG3niCk9mZKtB4JraTyKOFGsWDHGjh3LunXrCAoKomnTpuLDifAMlCJyUobISRkiJ8uIjJTxUjlQKSkpbN68mYCAAKKjo1m9ejVTpkwBwM3NLcdssVKlSqjVaiZMmIAkSZjNZn7++WcqV64MQGBgIL/88gu2trbyCs4XX3zB7t278fb25vbt29SsWZO2bdsyf/58SpcuLZ/H0aNHczQT7tSpE6tXr2bMmDHya54WyV1dXdm8eTMdOnRgzJgxOQTy1atXY2trS3p6Ohs3bpTv1st+zfP8Kms6UHdiknGy1ZBhMJNmMCGlPMKUmoDG0Y3bK8fi0agT+42vcfNYJrs3reVO6HW0Wi1Tp07liy++oFq1avkav6AiPANliJyUIXJShsjJMiIjZbyUDtQvv/xCtWrVqFq1Kn369GHMmDFMnjwZlUrFgAEDeP3116lcuTJOTk5s376dkiVLArB48WJWrVrF77//Lk+gZsyYwdq1awkODpZXgpo1a8bXX39NTEwMxYoVIzk5mejoaIoUKUKNGjVkt2nDhg1yM+HnNfp9khEjRjBkyBCKFCmCXq9HkqQcW3sajQaAa9eusXXrVnr06EF8fDwAxYsXf+ZxrelAXb+txsYMjjpI0qtISk4EoOxbn5AZdpGH5/zYfXwzoMLGyRWTyQxIbN26la1bt1K3bl0++eQTihYtmq/zKKgIz0AZIidliJyUIXKyjMhIGS+yA/WX60A1b96cnj17Mnr0aIxGIyVLlmTLli14e3uzfv16Zs6cye3bt+nduzc3b96kXbt2zJo1i9KlS6PRaChWrBjnz5+XT9TR0ZGxY8fy/fffA2AymahXrx7u7u6Eh4cTHh6OSqWicePGnDhxAj8/P0aMGEFMTAxeXl7ExsaSmZlJ1apVadasGevXrychIYEdO3YwefJkuQbUV199RY0aNfjll1/49ddfSUxMRKfTcfbsWby8vNi6dStjxozB29ubkydPYm9vz9q1a2nfvj2ZmZns2LGDd955J89MrFkHauHhW+wJjKZ8MQckSSI1KZFt4ztTv+swtPXf4lFCKk6mJB7snEti1F0qtn6PkH0r6fTx57zbtDJTP5+CnZ0dp06dkrdCCwPCM1CGyEkZIidliJwsIzJSxktXByokJIRz586xY8eOrDdrtfTq1QtfX1+8vb2JiYmhUqVK2Nvb8+abb/LDDz/g4+PDqFGjWLJkCbVr1yYgIIDAwEB+//13evfuLR87OTmZFStWMHbsWHbt2kXNmjXJyMjAycmJtm3b4u/vzxdffMHs2bNZsGABUVFRhISEyO+/ePEily5dwtHREYDExMQcz2eXScj2nyCrz139+vU5cuSI/NjatWsZMWIEP//8Mz4+Pri7uxMbG4tW++yorOlAvVmjJL/deERyhgkXexucXFwpXrMp137bREnP+uic3dDF3ORRWBBtxi0g7PR+tDo7Ukq8SqVGDdi/fz8NGzbkxx9/ZOzYsfk6l79C9vfhv0Z4BsoQOSlD5KQMkZNlREbKeGkcKF9fX4xGoyyNQ9adbLa2tixevJhx48Yxbtw4uc6SSqXi2rVrrF27lkOHDhEVFSWXFbh48SLt2rUDICwsjDZt2vDxxx8DWYJ4RkYG69ato0+fPgAsW7aMSZMmMWPGDI4ePZrn+ZUuXZq4uDgg70Kaq1evls9t7NixzJ8/n4yMDGxtbeXHixQpwrp160hNTWXv3r0sXryYXr16PTcXazpQNYo70L6GB36B0SSm67HRqIgOPAHAnR8G5Xjtoe9Hy3/2n96VltP/fG7atGlMmzYtX+fyV9Dr9f/aWHkhPANliJyUIXJShsjJMiIjZbxUDtSTTYLbtm2b47l33nlHbhIMyBOXlStXyr7Uu+++y5dffsnDhw8pXrw4AwYMIDo6msDAQE6fPs358+d55ZVX2LhxI9999x3ly5eXJ0+AXAvqSV/qScxmMxkZGTmcpufVgoqIiEClUuW5cnTt2jVOnTpF0aJF5dW252FNBwqgpAncJTXB8Sr0pnwf7l/hRalBJTwDZYiclCFyUobIyTIiI2W8yA6U4gnUk02CXVxccjzXvXt3uUnwk/j6+tK8eXM0Gg1t2rRBo9HQuXNnVqxYwc8//8y8efMoU6YM5cuXp2fPnrz66qv89NNPNGnSBJPJhI+PDydPnsTR0VGeTG3fvp3333+f2bNns3TpUi5fvkx6ejrOzs6kpKRgY2Mj13bS6XRUrVoVPz8/Hj58SNOmTVm5ciU7d+7kzp07eV7ngwcPaNKkCRqNhpSUFDZt2gRAamrqM7OxZh0ok1ni+99u8ogYXimmxk6rpsiw77m8ahoap6KUee0tkoOOkJ7wmKIVqhNx4Qivdh+GY/3OvFWnJENaVmDAgAGEhYVx7NixfJ3LX+G/3sITnoEyRE7KEDkpQ+RkGZGRMl6qOlC+vr74+PjkmjxB1gRq7ty5BAYGUqdOHeBPX6p8+fJyzaiuXbty6tQpmjVrhslkYvDgwej1etRqNTNnzqROnToYjUZOnjyZ4/gtWrRg/fr1QNZEJiQkhGPHjtGmTRtmz57N8OHDCQgIAP70miCrSfCNGzc4cOAAS5YsYezYsWRmZuLh4UGNGjW4du1armuZNWsWVatWZdmyZbi7u/Paa6/x8OFDfvjhh2du5VnTgbp8N45jNx9TzMkOZzstZsnM6WO/YOfsSun+36Gxc6R4qVc4s2wizfpOwMm9OFd2r6RVg860q1+RiIhw9u7dy/fff1+oJPJshGegDJGTMkROyhA5WUZkpIwX2YFSK32hn59fnlXHARo3bowkSfLkCf70pTZs2MDixYtJTU1l27ZtxMfHExUVxY8//sjly5e5desWoaGhdOvWjf/7v/9DkiTef/99AKKjo5EkiUOHDsn1nd577z0kSWL+/PlMnDiR27dvExwczJ49e6hRowZffvklkiQhSRLe3t4AtG/fnkuXLpGcnIxerycyMpJmzZrluIYBAwaQkJDAqVOnuHTpEk2bNqVKlSrExsYCcOzYMaZPn86/jX9ILAaT+Y/Jk0RifDwx189Rq21vPIq6kZmaRAL2FK/agMNLJpNuBJPRgM3N3/h96ypat25NrVq1GDRokOXBBAKBQCAQKMJqvfDWrl1Lz549CQ4OZtOmTXI/PFtbW9mXat26dZ798LJ50mdSq7Pmek/6TNm98DZt2kSHDh0YNmxYvvvhbdu2jfT0dPnrQ4cOMW7cONq2bZuj6vmTWFMif5CQhkalIjoxnYfJmSRE3kUym4k12ZH2y2xiAo8hmYwA2Di5En58G0hm9q+axyGtlnfffZf58+ej0+kKlbQoRE1liJyUIXJShsjJMiIjZbxUEvlfIduXunv3Lj4+PtStW5e2bduSkZFBixYt8PX1xcnJicWLF1OlShUAuR9enz59cHBwwMHBgZo1a5KcnIydnZ18V1f2XXZjx45lwYIFODg48MEHH+Dq6kp8fDzt27eXz+P69evodLoc5zZhwgQOHjxIUFAQgOxLeXl54eTkREpKCnPmzGHXrl05JlJr1qzB09Mzz+u1pkQeH60mMk6FMatDDWrbLLfo7o7v0ejs8Ww9gDo1qlOWWE4c2kvotauo1WrefPNNevfujZubG6dPn87XORRkhKipDJGTMkROyhA5WUZkpIyXQiL/K/j6+tKsWTNOnjyJl5eX7ED16NGD6OhoAgICWLFiBdu3b+eLL74AYObMmQwbNow+ffrIK0/ZlcKzt+SeZMuWLVmFJf+Qu7P/P27cOHbv3g1A9erVc91Of+jQIQIDA+Wvn/SlvL29uXDhAp6enqxfvx5nZ2eWL1/O1q1b6dq16zMnItaUyB+fieDkgVB0WhW2NmqwL47W0Q1jehIVPloCTh684+PF0BYVMJtn0LhxYwIDA1m4cCGVKlXK19gFGSFqKkPkpAyRkzJETpYRGSnjpZLI/wp+fn5MnDgRf39/NmzYgEajwWw2s2bNGuzs7ORK4d26dZNXiLp16ybfxZeamkpaWhphYWFyC5VZs2Yxbdo0uSXJ/fv3AXL0w5s4cSINGzaUzyOvWlDZK05DhgzB19c318TsaVeoTZs2dOvWjR07dhAVFSW3pnkSa0rk8elGbLVqTGYJg0lCykjBmJ71DY7c9T2eb/Qh/J4Dd+5klY24evUqAKdPny60ffCeRIiayhA5KUPkpAyRk2VERsp4kSVy4UApIDk5GSCH5/Qk1nSgIuPTKO5sS1Kmkfg0PemPosFswt17AIlntnB37UTmroW5ZPXyGzBgAL///jshISGFeo9deAbKEDkpQ+SkDJGTZURGyij0DlRQUBDXr19n0qRJ7Nq1ixkzZuRwoKZPn06VKlWoXLlyDgfKbDaj0WgoWbIkLi4utG7dGn9/fyDLgdq+fTvTp08nKCgIW1tbZs6cyebNm0lKSnquA/X111+zfft2goODMZmyKlI+7UC99dZbBAYGEhkZSeXKlRk0aBC//fYbNWvWpHz58nlerzUdqMdRah4m/lFAUwIbuz9a1QTsxixJFKnRkuKuzrxin0loaChr165FrVYTHR39whSz/C8RnoEyRE7KEDkpQ+RkGZGRMgqtA3Xs2DGGDBnCxo0biYmJoVevXty+fZuAgADOnTvH+PHjuXDhAg0bNsTLy4uYmBhMJhMHDx7EycmJWrVqERAQwPbt22nQoAGPHj0CskoKZF9kZmYmFy9e5OLFi0DWVl92W5anHSi9Xo9Go8mxWvS0A6XValGr1ahUKm7cuMGkSZNo2bKl7FXlhTUdqEenwzlz8CZaGxV2WjU4lOKeoyumtEQqfbQUtVtpxrxZmaEty2MwGGjUqBHXrl1jwoQJsqBfGBGegTJETsoQOSlD5GQZkZEyCoIDhWQlRo8eLQGSRqORVCqVpFarJbVaLdnb20tLliyRmjRpIg0ePFhq2bKlVLFiRWnVqlWSJEnSvn37JECqWbOmfKylS5dKTk5OEiBdvHgxxzgbN26U7O3tpbJly0pffvmlonNbtWqVZG9vL7m4uDzzNcOHD5e0Wq00ZcqUv3ztiYmJEiAlJib+5fc+zfzfQqQaX+yXqk3dL9WdfkCqM2WHhMZGApXkXL2F5DXCV5qz75qUnJwszZ8/X7KxsZEAacOGDfkeuyCj1+ulnTt3Snq9/r8+lRcakZMyRE7KEDlZRmSkjP8qp7/y+9tqDtSqVasoU6YM+/fvl/2nffv20bVrV9RqNb/88kue/tPp06epUKEC169fJyYmBk9PT7kPnpOTEzVq1JDHyXagNmzYwOjRo/8x/yk4OJg1a9bg5ubG119/bfH11nSgwh+lUqKILUnpRhLSDaQ/fAAmA24t3iPh7A6Sr5/gsyXwGVnOWI8ePThz5gyBgYH06NEjX2MXZIRnoAyRkzJETsoQOVlGZKSMQu1AJScnM3nyZJKTkxk1ahQ2NjY8fvxYbvuyevVqOnXqxM2bN2nVqhVffvklffr0ITo6Gi8vL3Q6nVwHKvsOtw4dOsh/frIOVK9evTCZTNjY2JCYmIiLiwsuLi6UKlWKatWqcePGDfncJkyYwKZNm0hPTyc9PT2XAxUUFIS3tzdqtZrY2FiKFStGz549mTZtWp534IF1HajYKDWPElRk/OFAaW2yrj85OKuApkOZ6rgWccLDRk94eDh+fn5IksT9+/eFA4XwDJQiclKGyEkZIifLiIyU8SI7UCrp7yzRWKBVq1b4+/sTHR3NlClTcHJy4ocffqBLly5MmjSJJk2aMGrUKGrUqEFAQAANGjQgISEBOzs7rl+/zt27dwkPD+fx48ekpqai0+lISkqiR48ebNmyBYAyZcoQGRmZa+wuXbrIvlJeq1D16tXjypUrud6X7UB98cUXfPXVV7med3FxISEhIc/rzWsFqmzZsjx69CjfDtSa0+H872AoWrUKOxsNkiQR+G0vTOnJlB/4HTYlqjD6TS8+bFmBlJQUmjRpws2bN7l06RI1a9bM19gFGeEZKEPkpAyRkzJETpYRGSnjv3SgihUrRmJiosXf31ZZgWrUqBFHjx6lVKlSmEwmuQ6Un58fK1euRJIkVq9ezVdffUXp0qUBCAoK4uOPP6ZEiRL8/vvv3L17lwcPHlC8eHHu3LlDxYoV2b9/P3q9Hp1Ox/3793PUgOrUqRM1a9ZUVAdq9erVDB8+HJ1Ol2tS1KxZM9RqNWPHjuW3337j8uXLLFu2jEmTJsljP40160DpTRIatRqzBGYzYNJjNmSAZCYh8DAebqXJNEmo1WoOHTokTyrv3r1LvXr18jX2y4CotaIMkZMyRE7KEDlZRmSkjEJVByq7BtR3331HSkoKv/zyi1wHasyYMWzYsIFhw4YxYMAAuQ5UaGio7EHt37+fWbNmUb16dbmI5qFDh+Q2K8HBwdSvXz9HDahOnTphNptJTk7Otwd1+vRpateujZOTk/xYtoOVPfbTWNOBCotNoXgRHUnpRpIyjKTH3EcyZOLS8G0SLu4h4cIeJsxXMxEwmUy0adOG4OBgzp49S6dOnfI1dkFGeAbKEDkpQ+SkDJGTZURGyigIDtQ/voW3c+dOevXqRUxMDB07dqRRo0YsWrSItm3b4u/vzyuvvMKNGzdYv349ixcvlld09Ho9I0eO5P3338fDwwOAmjVrcu7cOQwGAw0aNCAgIIB9+/YRHx9Pv3798PLyIjY2lszMTFxdXUlISCAsLAxPT0927NjBqFGjcHJykh2oiIgI7ty5w6hRo+SK3W+//TbLli2jRIkSAPTq1YtLly4RFxdHXFwcxYsXp3v37ixZsoR9+/bRoUOHXNc8Y8aMPB2oDRs25NuB+iVMzbV4FelGMEpgiH9AxI8fYVvCi8zoW+jcS+Ho4EARjYGoqCjs7e0xGAy8/fbb9OrVK19jCwQCgUBQmEhLS6N3797/zRaer68vPj4+REdHc+7cOcqXLy/3wmvdujV79+4lMDCQLVu2PLMXXtu2bdm6dSunTp2iSJEitG7dmqNHj8pjLF++HJPJREhIiPxYamoqKpWKyMhIPD09SUxMJDIyMsfq0xdffMGaNWtynO+uXbtITk7m999/B7JWu+Lj4+Xno6OjWbJkyXOv2Zp1oGJOhxNw8CYaDbjoNEj25Yi0dybz4W3Kvv8V9hUb8EmrSnz4egViYmJ47bXXiIiI4JNPPqFBgwb5GrsgIzwDZYiclCFyUobIyTIiI2UUhDpQ//gEys/PD4CJEydiNBpz9MLbt28f9vb2lCtXjq5duz6zF55arcZkMhEdHZ1nL7wnJ1NP98Lz8/Ojfv36efpPkyZNYs2aNZw/f56goCDGjBnDpk2b6NixIw8ePKBUqVKUKlUKs9mcw43KXmHKPpensaYDZUaFWqUCJCQJJJMRs8kIkkRG1C3sy9XBJGWNFRYWJn/zExMTxYcT4RkoReSkDJGTMkROlhEZKaNQOVDw4vbCO336NK6urjRs2JCgoCAAfHx8UKvVnD17lq5du+Li4sK1a9fkGlQAYWFhADg6OuZ5vdZ0oG5FJ+PhrCM100i6wUxGbCSSPp0itVoTe3QNCed3MduvBl+nPiLmbihuxYqj0WoZOHAg3bp146OPPiqUTYWFZ6AMkZMyRE7KEDlZRmSkjILgQFm1F97du3fx8fGhbt26tG3bloyMjBy98BYvXiy3G3myF56DgwMODg5yHSg7Ozu5JUtcXByQsw7UBx98gKurK/Hx8c/thRcdHU2RIkXo2LEjv//+O3q9nh49euDs7Mzdu3cB6Nu3L6dPn6ZixYqYTCa0Wi2pqak5xn4aa9aBun9fjT4dPG0hFUjQmgF4pYE3ulY9CDtzkJSEKDQqe1QaLfEJCaglFWqdHevXr2fp0qUMHz4cHx+ffJ1HQUXUWlGGyEkZIidliJwsIzJSxotcB8qqvfBOnjyJl5eX7ED16NGD6OhoAgICWLFixTMdqOyVJ0mSUKlUSJKU6066LVu2IEmSPLnJ/v+4cePkOlBP98IDiIyMJCIiQv56165dAPJjbdu2RaVSkZaWJo/v7OxMUlKSvAr2NNZ0oFIvRLLixB083e1Rq1SYSrhz09WDlNAzOLUZRbE2QympTeP0t/0oXbMxlVq8hf8Pn1Gj1yRWftqTmVMn8cMPP/DBBx8UKidKeAbKEDkpQ+SkDJGTZURGyiiUDhRkeVATJ07E398/hwO1Zs0a7OzsSEhIYMeOHc90oFJTU0lLSyMsLCxPBwrg/v37QG4H6nl1oMxmMyaTifPnz8uv27t3L507d6ZWrVoAXLx4EbVaTVpaGjExMXh4eDB79my+/PJLypYtm+f1WtOB8qlZAr+r0UQmZFLG1R6NVssrTToQenAdHkUq4PlqG+LO7wGgdqf+HFs+Hfdy1cgsUpaTtx/xf//3f/z2228sWLCAFStW5Otc/grP2u78txGegTJETsoQOSlD5GQZkZEyhAP1gjhQzztuNg0aNECtVrN27VoGDBhASkoKq1evllvD5IU1HSg3Ow3j3qzE/w7e5HpUEnqTidBf1wIQ++sSYn/98w7B/d98BEDq42iOTe3EsSeOc+fOHTZt2pSvc/krPL3y928jPANliJyUIXJShsjJMiIjZQgH6u5dhg4dSq1atahWrRozZszI5UBlF3t82oFycnKib9++zJ07l+joaObNmwf86SFt2LCB/v37s2DBApo0acL06dNJSkp6rgOlVqtxcHBg6NChLFu2DIPBwOjRo7G1tZV/4Ts7OzNixAgmTpzIhx9+iNlsRqVSPXcf1poOFMCDNEiIU5OeoUJvzvfh/hVelD58wjNQhshJGSInZYicLCMyUkahdqC++OILNBoN7du3p1evXty+fZuAgAAuX77MoUOHGDt2LJAV0k8//QRkTXRq1KjBpUuXqFevHiqVivr16/Po0SN5jNmzZ2M0GhkxYgQjRoyQH581axarV68G8nagPD09iYuLo0mTJgBUrlw5R9XxL774gqVLl+Z4jyRJtG3bFqPRmGP1KhtrOlDxaXo+3XIVgy6dOp52aFUqNG9/xLVdP+Le4gNKNH8H04WthJ3cQ8uhMzi1ajZFSpanav9ZDG5enrfqlKRZs2ZUrVo1Vw0sa/Jfb+EJz0AZIidliJyUIXKyjMhIGcKB8venS5cuQNaKhFqtxtbWloSEBFauXJnrfdmTE09PTwIDA2nRogX/+9//iIqK4oMPPgCQK4b7+PjQr18/DAYDs2bNokuXLuzcuZPRo0fLx3vagSpRogT379+nZs2abN68GYPBwIABA4iLi5OP6+zsTN26dTlw4ID8vtdff52bN29y9uxZmjZtmuu8relAnQqLITIxg3LujmjUKkwmI3dP+lGmQWtcW/cl02iiRNN3uHlkG+HnD9Okz0T8l06mbupDOr7amu/nfk1ISAjLly/H1dU1X+dSEBGegTJETsoQOSlD5GQZkZEyCq0DNXv2bL766is2b97MkiVLqFq1Knv37mXjxo24ubnRpk0bWd5u06aNLJHrdDoyMjKYN28etWrVol69enTo0IENGzbg5eUFwPz583M4UG+//TY1a9aUC2nmhaenJ0ajkU8//VRegRo4cCBTp06lXLly8rnb2trKE6orV65w8+ZNIEtCzwtrOlDnwh7xh/1FXKqemPvhpD16QJ0eY3CwSSfw+G5iEx7gXrUhYWd/5V7wedRaGx7++iPNt3zDzZs3mT17Ns2aNStUe+7CM1CGyEkZIidliJwsIzJSRqF3oJydnalZsyZdunRBpVIxZswYunXrhq+vL+fPn3+mRK7X67Gzs+PTTz+VHahff/0VgFu3blG/fv1cDtSDBw9ISEjA3t5ePo9Ro0axePFiWSKPiYlBq9Uyb948qlatisFgYM2aNahUKsLDw3n11Vfp1KkT8+bNY+bMmbz//vvMnj0bBwcHPDw8njkxs6YDdfuumsRkiElIIdMEGY8TAbgRcILE5VNArcbBsxwZKY+RzGZsNWA0m7h1/SoNGjRg0KBBVK9e/YVxkv5thGegDJGTMkROyhA5WUZkpIxC6UD5+PiwceNGmjdvjkajoW3btiQmJlKhQgX+97//MXv2bHbv3p1nIc2YmBjq1KmTy4F6/Pgx0dHRwLMdqAsXLjzzvKKjoylTpkwuB8rd3V0+buvWrfn555+ZMGECM2bMQJIktFot77zzTo7J2ZNY04GK8A/j6rE7mCUzDnZaHEqU5Z6NLQkBu3Ft9BYer3/Ahz61GeldgZ07dzJ48GC5ZMTbb7+dr7ELMsIzUIbISRkiJ2WInCwjMlJGoXagQkJCqFWrVo5mwj169ODUqVNIksTbb7/9zEKakiRx7do1mjZtKjtQffv2zTFGtgPVqlUrjh8/zmeffYbZbGbSpEnyaxYtWsSiRYtyvC8mJobKlSvLDtTAgQNJSUnJ8ZrTp0/j5OTEuHHjWLBgAXv37s1THs/Gmg6Us70Ok1lCq1GjBiStDrWNLSajAbfarVDZOeNkb4OdnR2dOnWidOnS3Lx5k6pVq4oPJ8IzUIrISRkiJ2WInCwjMlJGoXOgIGsV6ulmwtmFNBcvXvzcZsKpqamkpKSwfv16ihcvTr169RgzZkyOQprz588HsgppTp06lR07duRoJpwXZrOZtLQ0VqxYIRfSnD9/Pp07d5bP4/r16yxdupSgoCCGDx9O586dadu27XOv1aq98GKScXWwIS3TSJrBhCkpBlNaErqiZbi7egJutVqy7WFT7uwzsW7dOlJTU3FwcGDnzp356oGXmZnJrl27uHbtGo6OjtRv2YYMh+JIQCUPR6qXcH7upPK/RngGyhA5KUPkpAyRk2VERsootA5UQS6k6efnR8WKFVmzZg2HDx/Gw8ODIUOGMHfu3BzHfhJrOlA3w9SojeChgyS9iviMrNWyVzoOQ3p0m8jzv/L7Sn/OOjrSvHlz3nrrLaZPn87Vq1f/tvd08eJFFixYQGJiIm7uRUlOTcOY+TluNVtQ4a3R2NnZUcZRokNZM265F95eKIRnoAyRkzJETsoQOVlGZKSMQudAvajNhNVqNfb29rRp04bMzExUKhUajSZHIc0rV64QGhrKN998A0BsbCy+vr5cvnyZgICAPK/Xmg7UvWN32HYxkleK2qNSqdB7OhCus8Mp6Q51ewwlvFUfutQpwajWWXcn3rhxg9jYWN566y06duz4l8c7f/48c+bM4c0332TmrNn8fNPMhduxpF0/ypUtC4g9sIimH87mYbKe0xlOfNOhJs52L94ytPAMlCFyUobISRkiJ8uIjJRRaB2oF7mZcPZxn/zzk19nlypwd3enT58+TJ48mcDAQNq1a0dISAhVq1bNdTxr98L79VoM8WlGijnZonNwpGSdFlz77RdcqzdH516K5hVc0Ov16PV6Jk6cSLFixejYsePfaqfy9ddf4+Xlxc8//8zZ8ESuhN2gZBFbbFt0wN5WxwnfmdS+d52Spb0Iuf+I34If0Kl2yXxdozUwGAxkZGSg1+tz/ew8zX9d9PNFQPgYyhA5KUPkZBmRkTIKnQP1IjcTTk9P59ixY7maCWefh6enJwC///479erVA8DFxQWAiIiIPCdQ1nSgKrrb8W6DUmw4d49bMcloVHA/4DcAjs4ZCMDBibnfl53T3+VZ25UA+2YPlf/sn69RXgz+6759/yXCx1CGyEkZIifLiIyUIRyoAuhANWjQAICOHTtiNBqpUqUK7777LoBcbPNprN0Lz8YATgYV95PUZJjyfTjBUxTWGllPInwMZYiclCFysozISBnCgSpADlT79u0pU6YMHh4e9O7dm8mTJ3Py5Enq1asnn+vTWNOB0hvNfLX3Oo+Ip1IJDU46La6DZ3Fp9Zc4l6uBz/sfMaN3KwyZ6axbt4758+czcuRIZs6c+ZfHMhgMeHl5MXDgQGbMmIHvibvsuvKAsu5Z/lVmahI7Jr9LnS6DqNGmF/fi0njdqxifts07l/8Sg8HA4cOHad26tcUl2cK8hSd8DGWInJQhcrKMyEgZwoEqgA6Up6cnZ8+eZcSIEUyaNAmtVotKpcrTccrGmg7UmbuxXIhIpJSLPfY6DWbJzF3/LbiWrkCb8Yt4lG4mRu1G6/rVqF+/PkWLFmXGjBlMnjyZkiX/ups0aNAgVq9ezciRI+nwakWOhCWTZlbj5mDDpW3LkMxmqr3xDnp02Nmr6dCg4gvZY89gMGBnZ4erq6v4S0oBwsdQhshJGSIny4iMlCEcqALkQAGUKlWKKlWq0Lt3b958802GDRtGeHj4M6/Xmg6U/42HmMxmbG1U6I0mHsc+5PGtKzQbOA17Ox3Jt4NZuvoixtY1adGiBR999BGzZs1iw4YNfPLJJ395vIkTJ7J3716aNWvGyJEjqelRgwMBIUSe3sPjG2ep13MMj012GFP1tK9RnFfLFHkh9/KFZ6AMkZMyRE7KEDlZRmSkDOFAFUAHCuDw4cNs2bKFy5cvs337dkwm03NXc6zpQAXeUpOWCtdTU0kyQNrDrInj3dgkrn4xgJT7NzgHbP0W3Nzc6NmzJ87Ozpw+fVpuvPxXmTp1KuvXr2f27NnyCl6RkuWp1nMSTrVaYKNPolFRiUqZifx6IDRf12dthGegDJGTMkROyhA5WUZkpAzhQBUgB2ratGnMmTMHe3t7ihUrho2NDQaDgeHDhz/zeq3pQF0/GErI+fvoTWY0GhXO7sVBpSb6wA/oipbllZ7T6NnpTd6tZs+SJUv48ccfUavVtGrV6m/Vgcrm/fffJykpifDwcBwcHChXvgKxKVklATycbbHR5J54vkgIz0AZIidliJyUIXKyjMhIGcKBKoAO1I4dO7C1tZUdGgcHB3k78VlY04Eq6eZAusGMrVaNrVaN5FQEraMLxrQkyr//JWYHdyqXK0PjxpVo1KgRV69e5dKlS3To0CHfYxctWjRHOYRX7F7wsuN5IDwDZYiclCFyUobIyTIiI2W8yA6UVZYR/Pz8aNy4sdwLb/HixaSmprJmzRr8/f1JSEhgwIABdOvWjdDQUEJDQ+nWrRtdu3YF/nSggoODSU9PJzExkc8//xwghwMlSRIbN27E3t6ePXv2UKNGjVwO1NNFMtPT0zl06JDcb2/jxo3o9Xp5per+/ftkZGRgMBhIS0sjNjYWyNqmW7lypTXiei5RiRk46NSYJIkMo4nM5ASMKQmoNFrurJ9Cxg1/gm/eZsve33ir27tcunQJtVrNjz/+KE8qBQKBQCAQ/LMIB+opB+r06dOYTH8WW1q5ciULFixg8ODB8gTvaawpkcckZeDpbItKpSImOZOkpDhAokyX0aQEHuLe9rks3D6XhYDW3gkbO0cMGanMnTuXZcuWMXDgQL788st/pB5VQUKImsoQOSlD5KQMkZNlREbKKLQSeUF2oB4+fMi8efPYv3+/HKRWq2XZsmV5CudgXYk88aGahCQVHvYSJXTg5OZAGOCiysCj90ycHj6AxChSL+4mLvQSHvXf5FHgUep5d6Kiqw3Lli3jt99+Y8aMGYVyuViImsoQOSlD5KQMkZNlREbKKHQSeUF2oE6dOkWdOnUYMGAA9vb2fPXVV5w6dYrBgwezatWqPK/XmhK56+3HzNp3AydHHQ46DZKHBzeq1Cf81B5KVm6Ng0dZ3G3SOR16kZZDppMUc59HgeDeaiAz+rVk5MgRtG7dmsePGOOuEwAAIVNJREFUHzNo0KB8nUtBQoiayhA5KUPkpAyRk2VERsootBJ5Qa4DNWXKlBzX0r59e+rVq8e6detYsWIFGo0m1/VaUyJv5uVJs0qPOH7zES52WorYa6no3ZPzK6cTvvYzKvj0ITL4MM7FShEbFsyNw1up1b4PBpWOw8GRDG7ZiPbt27NixQr69OmTr3NRyotU2VuImsoQOSnjn8hJkiSio6Mxm82ULFnymSvbBRlr/DwlZRgwGM242NugfcHvAlaC+Mwp40WWyIUDpeAvr7S0NCRJwmw25zmBsqYDpQLGvVmJYg42HAmN5X58OueWT84a98ENbqydKr/2xuGtAAQdWA8H1nMMGP3EsZycnPJ1Lkp5EZrzCs9AGSInZfwTOUmShK+vLwsWLCAkJASAChUqMHz4cEaOHJnn3y0FDWv8PF2+l4BfYBSBkUmYzVllVNrVKE7HWsWxtSl4mYnPnDKEA1UAHahVq1axZs0aIiMjCQsLo3z58oSFhdGpU6dnzkyt3UwYoBzQvThEp6k48o8c0Xq8SM15hWegDJGTMv5uTpIk8dNPP7Fv3z5ee+01Jk2ahEaj4dSpU0yaNIndu3czduzYl2Y16p/6eQqOV3HgXlYTdQethFoFsfEQFB7DnlOBvF3OjLaARiY+c8oQDlQBcqDUajXBwcEkJycDEBYWRo8ePVi3bt0zr9eaDtTTGAwGytpuIqN4TVaeiqCkix0RAb9xevU3dJiyHPeylcnQm4hL1fNZ+6q8Yq+nYcOGjBw5ks8+++wfPZdn8SJs4QnPQBkiJ2XkN6fjx4+zb98+Fi1axEcffZTjua1bt9K7d29Gjhz5zDt9Cwr/5M9TQpqB9RsvY+ekp6KLXY6dgzS9iQcpejTlKtGxdon8nva/ivjMKUM4UAXQgerfvz/9+/fH398fHx8fateuzZYtW557vdZ0oJ7GbJbQ2drh82pFzt7P5Hp0MsXreONWZgtHl0ymTo8x2FZuwmuVS2GOuUW3sWNwcXFh3LhxL2TTX2tTmDyDv1P3y2AwkJGRgV6vz/WPFMGf5DenZcuWUblyZQYMGJDrH3VvvfUWTZs2Zfny5XTq1OmfOuX/hH/y5+no9Shi4xIp7eaA2ZAzM1tAMmSw71IEPlXcckyuXnTEZ04ZSnKyxj/WhQP1B3/XgTp69CidO3emQYMGlChh+V831nSgsrl0L4Ffgx9y+V4CcfFqzqRdIeXMDi5uXkfSo2hUWh029k6c9Z2Gzs6eSzob5iQlUadOHQ4ePIibm1uh2nMvjJ7Bv+W4Cf4+zs7Oz31efA//GoeBn4b812ch+K+whm9bKByoJUuWMGrUKIoVK8Y777xDo0aNSEpKsuhAOTg40L59e/R6PXq9Hq1Wi06nk4+/YsUKPv74YxwcHDh37pxcymDEiBE5JmdPYm0HKiBWxZEoNXoT2GkljBlpLJnQj/SYCGo1eZ263d/l/sPHXDr+G5KNjtbeb+Dp6UnVqlWpUaMGt27d4tatW/k+j4KI8AwEAoHg5cQavm2hcKDWrVuHJElyq5Xz588DWVt9q1evBvJ2oDQajXxXnUajwd7envT0dPn5VatWYTKZZAcqLS2NL774grVr13Lz5s08r9eaDtTt2FR8t13FxUXC09kWySzhv3I2+vgoXhv7Ay5lqjCha02qlXAmLS2Nt99+m8DAQG7evFlotq7yojB6BvHx8X/5PQaDgcOHD9O6detCk9PfIb85LVu2jGnTpnHhwoVcK+1xcXHUrVuXYcOG5SqjUtD4J3+ebkQnMW3XdZxsNTja5fxVZZYk7sel07l2ST58vUK+xvm3EZ85ZSjJyRpbeIXCgTpz5gyQ5UB98MEHdO7cmV27duU4j6cdqCJFipCcnMyWLVvo0aMHAEFBQdSuXZvExEQATp48meP9CQkJlC5dmuvXrz/zeq3pQB2/9ZiUTBPlizqgUqnQG9K4f+F3avi8S+XqtbnzOA3/m4+pXdYdFxcXFi5cSN26ddm/fz/du3fP19gvA4XJgfo7jlt202xXV9dCk9PfIb85DRs2jB9++IFevXqxevVqGjdujEql4sqVKwwZMgQ7OzvGjBlT4D3Ff/LnqYmLCy1qJOMfEotW0uFsp836O9BoJiYxnZLF3Hj3tSq4uv73N638FcRnThn/VU6FzoGqXr06FSrk/lfI0aNHadWqFXfu3KF8+fLybLVYsWLyax48eABARkbGM68nMTHxmdt3YF0HKiQ6Ca0GJLJW4ZJjH2DMTKN0rWZISNhqVYREJ8njVK9enTJlyhAQEMBbb72Vr7ELMs9zoCRJYvv27SxfvpzAwEDs7e3p0qULI0aMkLeU/y7JGUb8Q2M5dvMR8WkGShSxo3U1D5pXKoruBbzfujC6Yn+H/Obk4ODA/v376datG02bNqVChQpoNBpu3brFK6+8wt69e/Hw8Cjw34d/+udplHdF1JLEmbtxPE7NBFSoVVDGzZ5RrSpRxkVX4DITnzllFPo6UEFBQVy/fp1Jkyaxa9cuZsyYkcOBmj59OlWqVKFy5co5HKjsgpUlS5bExcWF1q1b4+/vD2Qtd0dFRdG9e3dOnz4NwOPHj0lNTSU6Ohp7e3tcXFyArEmZTqeTZ5TZEzIfHx9sbGxo0qQJ9+7dw93dXd7G++STT/jtt9+4efMmDg4OVKpUicDAQBYtWvTM67WmAxUdqSYxCWz0WVuKqX9sLcY+jETlVoqEDIgxJbFvX9ZdiSaTifj4eCIiIl6oekz/FU87UGazmUWLFnHkyBFq1KhB+/btSU5OZuPGjaxcuZIpU6ZQt27dvzVWkh6231UTmapCrZLQquF6BBwNvkdlF4m3XjGje0Hr/glXTBn5zembb77h4sWLXL16FUmS6NatG40bNyYqKoqoqKh/6Cz/e/7Jn6faEnh6QHiKCpME7rZQqUgi9wOjuR/4jw3zryM+c8ootHWgjh07xpAhQ9i4cSMxMTH06tWL27dvExAQwLlz5xg/fjwXLlygYcOGeHl5ERMTg8lk4uDBgzg5OVGrVi0CAgLYvn07DRo04NGjR0DWik9ERIQ8XnR0NCtWrGDFihX0799fdqA8/7+9ew+Lqs7/AP7mOghyM0QuIhcNAZOLN6T9FRgoKGuamK6alxWpyGwXpVWfVHRdxUyDVbELoiNtalamJWq6PI4p4tq6oj5IJISpKd5CLo4gl+/vDx9OTgwyozMMl/freXiEc77zPd/vx+Ph4zmf+Y6jI+7fvw9XV1cAwL/+9S8AQGhoKE6cOIFjx47hqaeegoeHh8r4r1+/jrq6OlRUVOD06dMAgDfeeAPx8fFq56vPGqiGs9ew/nAxutlbwNTYGA1POaCroxtunPkOvv83Csqye4h5zgujglwAPFhT5u7du0hISHjsRKAjaK4GKiMjAwqFAnK5HJMnT5a2K5VKTJgwASkpKSguLm7x3VLqLM8qQBlu42lXC5W7Tcr79bhSWYOK7m6YNtT9ySamY52xVuxx6DJOo0eP1tGo2h6eTy1jjDTTqdeB+utf/4ojR45g8+bNaGhogJubG4AH9UJpaWnIzMyEUqnEjz/+iMOHD2Px4sWYMWMG9u/fj7KyMvTr1w/Hjh0D8KAA8+233wYAODk5wcPDQ1oHKiwsDEVFRRg/fjxSU1NVxvFwDVR5eTkUCgUA4Msvv4SdnR1++OEH+Pr6wtjYWFquYN26dVi3bh1mz56Njz/+GH/729+wYsWKR85XnzVQL/g64+uzpfj5thKudl1gamIMr9AYnP08FUc/+wCDoqdgqLs1ampqoFAo8Oabb2L48OHNLiLaWTS3hsiGDRsQHR2N8ePHq8TH1NQU69evh5+fHzIzMxEXF6fV8S7euovvi67D3swYJg21qH8o9DIAMlGLb89cxuh+3WEl08s/u8fSHtakaQsLszbqTDV1T4JxahljpJlO+Vl4W7ZsQc+ePbF//36p/mnfvn146aWXYGxsjJ07d6qtf8rNzYWnpycKCgpw48YNODo6IjIyEvHx8ejatSv8/Pw0GsPv659OnTqF+vp6mJmZITs7GzExMfDx8YGzszOuXbuGkJAQ6bX5+fnYunUr7O3tW0yeAP3WQFmaAQsivfHewR9x8bYSdfUNkPmFw3NEOUoOyXHxUCa++Kvqaw4dOsT1ZB4hPz//kfFJSEhAQkKCXo79+Ry9dNuhtYX/CLBuRTOMU8sYI8106hqoyspKLFy4EM888wx8fHywdOlS3L59GzExMVi9ejXkcrm06u7D9U+lpaXo06cPrKysMHXqVKxevRoXL14EAIwaNUrlTk9eXh6qqqpQW1uLmzdvIi8vD+bm5vDz84OlpSV69eqFiIgIHDlyBKWlpTA3N8fMmTMxd+5cdOvWDTY2NqioqICLiwuGDh0K4MG78l544QX07t0bdXV1KC0tBfBg+YPu3burnW9rfBZelC1QBCNcVQLoCjhNGgvrF4fgrTfVP1Yk6ijaUi0f61Y0wzi1jDHSTFuugTISerhvP2zYMClpcXR0BAC8+eabKC8vx5w5cxAcHIzjx49Ln0geExOD9PR0zJ07F6+++ip+/vlnfPzxx4iPj4dCoYCVlRVu3bqFb775Bn/84x9/G7ya5fvd3d2lhOvhu1DHjx/Hn//8Z5SXl2PevHnYvn07ampqYG5ujsmTJyMtLQ0AsHTpUrXJ0MP9/p66O1Bubm64deuWXj4L7+Hnwo/z8R2dQXNriIwaNQrAg4/w+f35U1BQgGeffRbp6enSMheaulFRjYTPH1S02luZN9lfWl6NHjYWSHnZv029G689rEnTFh7hsW5FM4xTyxgjzRiyBsrBwQHl5eUt/v7Wyx2owYMHQ6FQwMXFRdomhIBMJsOGDRukWovGBMra2loqwnZycsLJkyfh7u4u/c+zpKQEXl5eUjH4w32GhYUhMDCwSf0T8KA+qvFYP/30E+7fv4/q6mqkpaVJCZO7uzv69OkjvWbp0qXS1+7du5GXl9fifFvzs/B+33d7XzdGX5pbQ2T+/PkYO3Ys3n//fSxZskTad+nSJbz22mtwd3fHtGnTVFaw14SdHTDcvwJfn7kKayOZVOckhMCde7UwMjNCTHBvODo0vxyGIXBNGu2wbkUzjFPLGCPNtOUaKJ3/V7hxDai1a9ciLy9P+jpz5gxcXFywfft2qe3vF7oEgJCQEJw7dw43btyQth06dAg2NjYa1z+pM3DgQKn+qVFhYSEuXbqkUv9EHduYMWOQnJyMf/zjH1KyFB0dDS8vL/z666/IysrSOnlqFPe8F57zdkCZshYlt+7i0q9KXLytRE1dA14KcsWYQNeWOyEionZB53egGteAio2NldZjahQTE4OMjAxpxXF1RowYAT8/P6n+qbS0FIsWLcLs2bOb1D8BQFVVVZP6J+BBYfq0adOQnZ0NV1dX2NraIjY2VqX+ac6cOQgJCZHqnwCgqKgIVVVVKC0txb1796Tj+Pn5PfYvVmpbFixYgFGjRuGjjz6SFtL85z//ialTpz7RI1crmSkWR/vh9OU7OF50C3fu1aKHjQWef7o7fJ2t29UnxhMR0aPpPIHKyMhAREREk+QJgFRAfvbsWfj7+6t9vYmJCfbu3Yv4+HiEhITAysoK06dPx9///neVdkFBQdL3p06dwrZt21TqlJRKJQoLC1Uq6lNSUmBsbIyYmBjU1NQgMjISGzduVOl31qxZ0qKdDx+n8d181DH4+/tLj3F1ydTEGIM9umGwR9t6VEdERLql8wTqm2++aXbfkCFDNFpr5uH6p+a01M/D9U+NLCwsVOqf1GlcK4qIiIioOW3n7UBERERE7QQTKCIiIiItMYEiIiIi0hITKCIiIiItMYEiIiIi0hITKCIiIiItMYEiIiIi0hITKCIiIiItMYEiIiIi0pLOVyKn31ZJr6io0HnftbW1UCqVqKio4Cd5PwLjpBnGSTOMk2YYp5YxRpoxVJwaf29r8qkpTKD0oLKyEgDg5uZm4JEQERGRtiorK9V+pu/DjIQmaRZppaGhAVevXoW1tTWMjIx02ndFRQXc3Nxw+fJl2NjY6LTvjoRx0gzjpBnGSTOMU8sYI80YKk5CCFRWVsLFxQXGxo+ucuIdKD0wNjZGz5499XoMGxsb/uPTAOOkGcZJM4yTZhinljFGmjFEnFq689SIReREREREWmICRURERKQlJlDtjEwmQ1JSEmQymaGH0qYxTpphnDTDOGmGcWoZY6SZ9hAnFpETERERaYl3oIiIiIi0xASKiIiISEtMoIiIiIi0xASKiIiISEtMoNqAtLQ0eHh4wMLCAsHBwTh58uQj23/++efw8fGBhYUF+vfvj3379qnsF0JgyZIlcHZ2RpcuXRAREYELFy7ocwp6p+sYzZgxA0ZGRipfUVFR+pxCq9AmTvn5+YiJiYGHhweMjIyQmpr6xH22F7qO09KlS5ucTz4+PnqcQevQJk7p6el47rnnYG9vD3t7e0RERDRp3xGvTYDu48TrE7Br1y4MGjQIdnZ2sLKyQmBgID755BOVNgY/nwQZ1I4dO4S5ubnYvHmzyM/PF3FxccLOzk5cv35dbfucnBxhYmIiVq9eLc6fPy8WLVokzMzMxLlz56Q2q1atEra2tmL37t3izJkz4sUXXxSenp7i3r17rTUtndJHjKZPny6ioqLEtWvXpK9ff/21taakF9rG6eTJkyIxMVFs375dODk5iZSUlCfusz3QR5ySkpJEv379VM6nmzdv6nkm+qVtnCZPnizS0tLE6dOnRUFBgZgxY4awtbUVV65ckdp0tGuTEPqJE69PQhw+fFjs2rVLnD9/XhQVFYnU1FRhYmIiDhw4ILUx9PnEBMrAhgwZImbPni39XF9fL1xcXERycrLa9hMmTBDR0dEq24KDg8Vrr70mhBCioaFBODk5iffee0/af+fOHSGTycT27dv1MAP903WMhHhwgRozZoxexmso2sbpYe7u7moTgyfps63SR5ySkpJEQECADkdpeE/6d19XVyesra3F1q1bhRAd89okhO7jJASvT80JCgoSixYtEkK0jfOJj/AM6P79+zh16hQiIiKkbcbGxoiIiEBubq7a1+Tm5qq0B4DIyEipfUlJCUpLS1Xa2NraIjg4uNk+2zJ9xKiRQqGAo6Mj+vbti/j4eNy+fVv3E2gljxMnQ/RpaPqc04ULF+Di4gIvLy9MmTIFly5detLhGowu4qRUKlFbW4tu3boB6HjXJkA/cWrE69NvhBDIzs5GYWEhnn/+eQBt43xiAmVAt27dQn19PXr06KGyvUePHigtLVX7mtLS0ke2b/xTmz7bMn3ECACioqKQmZmJ7OxsvPvuuzhy5AhGjhyJ+vp63U+iFTxOnAzRp6Hpa07BwcGQy+U4cOAAPvjgA5SUlOC5555DZWXlkw7ZIHQRp/nz58PFxUX6BdfRrk2AfuIE8PrUqLy8HF27doW5uTmio6Oxfv16DB8+HEDbOJ9MW+UoRG3Mn/70J+n7/v37w9/fH71794ZCoUB4eLgBR0bt0ciRI6Xv/f39ERwcDHd3d+zcuROxsbEGHJlhrFq1Cjt27IBCoYCFhYWhh9NmNRcnXp8esLa2Rl5eHqqqqpCdnY25c+fCy8sLYWFhhh4aAN6BMigHBweYmJjg+vXrKtuvX78OJycnta9xcnJ6ZPvGP7Xpsy3TR4zU8fLygoODA4qKip580AbwOHEyRJ+G1lpzsrOzg7e3d6c8n9asWYNVq1bh4MGD8Pf3l7Z3tGsToJ84qdNZr0/Gxsbo06cPAgMDMW/ePIwfPx7JyckA2sb5xATKgMzNzTFw4EBkZ2dL2xoaGpCdnY2QkBC1rwkJCVFpDwCHDh2S2nt6esLJyUmlTUVFBf7zn/8022dbpo8YqXPlyhXcvn0bzs7Ouhl4K3ucOBmiT0NrrTlVVVWhuLi4051Pq1evxvLly3HgwAEMGjRIZV9HuzYB+omTOrw+/faampoaAG3kfGqVUnVq1o4dO4RMJhNyuVycP39evPrqq8LOzk6UlpYKIYSYOnWqWLBggdQ+JydHmJqaijVr1oiCggKRlJSkdhkDOzs7sWfPHnH27FkxZsyYdv1WYV3HqLKyUiQmJorc3FxRUlIi/v3vf4sBAwaIp59+WlRXVxtkjrqgbZxqamrE6dOnxenTp4Wzs7NITEwUp0+fFhcuXNC4z/ZIH3GaN2+eUCgUoqSkROTk5IiIiAjh4OAgbty40erz0xVt47Rq1Sphbm4uvvjiC5W331dWVqq06UjXJiF0Hydenx5YuXKlOHjwoCguLhbnz58Xa9asEaampiI9PV1qY+jziQlUG7B+/XrRq1cvYW5uLoYMGSJOnDgh7QsNDRXTp09Xab9z507h7e0tzM3NRb9+/URWVpbK/oaGBrF48WLRo0cPIZPJRHh4uCgsLGyNqeiNLmOkVCrFiBEjRPfu3YWZmZlwd3cXcXFx7TopaKRNnEpKSgSAJl+hoaEa99le6TpOEydOFM7OzsLc3Fy4urqKiRMniqKiolackX5oEyd3d3e1cUpKSpLadMRrkxC6jROvTw+88847ok+fPsLCwkLY29uLkJAQsWPHDpX+DH0+GQkhROvc6yIiIiLqGFgDRURERKQlJlBEREREWmICRURERKQlJlBEREREWmICRURERKQlJlBEREREWmICRURERKQlJlBEREREWmICRUQGo1AoYGRkhDt37gAA5HI57OzstOrDyMgIu3fvfqJx5OTkoH///jAzM8PYsWOfqC8i6hyYQBGRXuXm5sLExATR0dGGHkqz5s6di8DAQJSUlEAulxt6OETUDjCBIiK9ysjIwJw5c/Ddd9/h6tWrhh6OWsXFxXjhhRfQs2dPtXfAhBCoq6tr/YERUZvFBIqI9KaqqgqfffYZ4uPjER0d/Vh3d/bs2YMBAwbAwsICXl5eWLZs2SOTmcuXL2PChAmws7NDt27dMGbMGFy8eFFt24sXL8LIyAi3b9/GzJkzYWRkBLlcLj1a3L9/PwYOHAiZTIZjx46hoaEBycnJ8PT0RJcuXRAQEIAvvvhCpc99+/bB29sbXbp0wbBhwyCXy1UeUy5duhSBgYEqr0lNTYWHh4fKtk2bNsHX1xcWFhbw8fHBxo0bm4x7165dGDZsGCwtLREQEIDc3FyVPnJychAWFgZLS0vY29sjMjISZWVlyMzMxFNPPYWamhqV9mPHjsXUqVObjS0R/YYJFBHpzc6dO+Hj44O+ffvilVdewebNm6HN55cfPXoU06ZNw1/+8hecP38eH330EeRyOVasWKG2fW1tLSIjI2FtbY2jR48iJycHXbt2RVRUFO7fv9+kvZubG65duwYbGxukpqbi2rVrmDhxorR/wYIFWLVqFQoKCuDv74/k5GRkZmbiww8/RH5+PhISEvDKK6/gyJEjAB4kb+PGjcPo0aORl5eHWbNmYcGCBVpGDfj000+xZMkSrFixAgUFBVi5ciUWL16MrVu3qrR75513kJiYiLy8PHh7e2PSpElScpmXl4fw8HD4+fkhNzcXx44dw+jRo1FfX4+XX34Z9fX1+Prrr6W+bty4gaysLMycOVPr8RJ1SoKISE+effZZkZqaKoQQora2Vjg4OIjDhw9L+w8fPiwAiLKyMiGEEFu2bBG2trbS/vDwcLFy5UqVPj/55BPh7Ows/QxAfPXVV9K+vn37ioaGBml/TU2N6NKli/j222+bHaetra3YsmVLk3Ht3r1b2lZdXS0sLS3F8ePHVV4bGxsrJk2aJIQQYuHChcLPz09l//z581XmmJSUJAICAlTapKSkCHd3d+nn3r17i23btqm0Wb58uQgJCRFCCFFSUiIAiE2bNkn78/PzBQBRUFAghBBi0qRJ4g9/+EOzc46PjxcjR46Ufl67dq3w8vJSiR0RNc/UkMkbEXVchYWFOHnyJL766isAgKmpKSZOnIiMjAyEhYVp1MeZM2eQk5Ojcsepvr4e1dXVUCqVsLS0bNK+qKgI1tbWKturq6tRXFys9RwGDRokfV9UVASlUonhw4ertLl//z6CgoIAAAUFBQgODlbZHxISotUx7969i+LiYsTGxiIuLk7aXldXB1tbW5W2/v7+0vfOzs4AHtxJ8vHxQV5eHl5++eVmjxMXF4fBgwfjl19+gaurK+RyOWbMmAEjIyOtxkvUWTGBIiK9yMjIQF1dHVxcXKRtQgjIZDJs2LChSTKgTlVVFZYtW4Zx48Y12WdhYaG2/cCBA/Hpp5822de9e3ctZwBYWVmp9A0AWVlZcHV1VWknk8k07tPY2LjJY8za2tomx0lPT2+SjJmYmKj8bGZmJn3fmPg0NDQAALp06fLIcQQFBSEgIACZmZkYMWIE8vPzkZWVpfE8iDo7JlBEpHN1dXXIzMzE2rVrMWLECJV9Y8eOxfbt2/H666+32M+AAQNQWFiIPn36aHTcAQMG4LPPPoOjoyNsbGwea+zN8fPzg0wmw6VLlxAaGqq2ja+vr0pdEQCcOHFC5efu3bujtLQUQggp6cnLy5P29+jRAy4uLvjpp58wZcqUxx6vv78/srOzsWzZsmbbzJo1C6mpqfjll18QEREBNze3xz4eUWfDInIi0rm9e/eirKwMsbGxeOaZZ1S+YmJikJGRoVE/S5YsQWZmJpYtW4b8/HwUFBRgx44dWLRokdr2U6ZMgYODA8aMGYOjR4+ipKQECoUCb731Fq5cufJEc7K2tkZiYiISEhKwdetWFBcX43//+x/Wr18vFXe//vrruHDhAt5++20UFhZi27ZtTd55GBYWhps3b2L16tUoLi5GWloa9u/fr9Jm2bJlSE5Oxrp16/Djjz/i3Llz2LJlC95//32Nx7tw4UJ8//33eOONN3D27Fn88MMP+OCDD3Dr1i2pzeTJk3HlyhWkp6ezeJxIS0ygiEjnMjIyEBERofYxXUxMDP773//i7NmzLfYTGRmJvXv34uDBgxg8eDCGDh2KlJQUuLu7q21vaWmJ7777Dr169cK4cePg6+uL2NhYVFdX6+SO1PLly7F48WIkJyfD19cXUVFRyMrKgqenJwCgV69e+PLLL7F7924EBATgww8/xMqVK1X68PX1xcaNG5GWloaAgACcPHkSiYmJKm1mzZqFTZs2YcuWLejfvz9CQ0Mhl8ul42jC29sbBw8exJkzZzBkyBCEhIRgz549MDX97cGDra0tYmJi0LVrV67ATqQlI/H7h/FERKQzCoUCw4YNQ1lZmdYfU9MawsPD0a9fP6xbt87QQyFqV1gDRUTUCZWVlUGhUEChUKgs0klEmmECRUTUCQUFBaGsrAzvvvsu+vbta+jhELU7fIRHREREpCUWkRMRERFpiQkUERERkZaYQBERERFpiQkUERERkZaYQBERERFpiQkUERERkZaYQBERERFpiQkUERERkZb+H/zlMxvWhrR9AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "k = caf.shape[0]\n",
+    "perks_hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95, prior=[1/k]*k)\n",
+    "HLAfreq.plotAF(caf, aftab, hdi=perks_hdi)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -287,7 +443,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.6 ('hlatest')",
+   "display_name": "hlafreq",
    "language": "python",
    "name": "python3"
   },
@@ -301,12 +457,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+    "hash": "46d2d82dbc865cefb79a4a45cbcd8ead329d89ff6c8b099bf15de0f92559257f"
    }
   }
  },

From 936db020a935818d9d32df8ad9addb25809ada57 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:39:18 +0000
Subject: [PATCH 096/192] Update checks and plots

Fix bug in compare_estimates logic
Add formatting checks to AFhdi
Add compound mean to plotAF
---
 src/HLAfreq/HLAfreq.py      | 12 +++++++++---
 src/HLAfreq/HLAfreq_pymc.py | 27 +++++++++++++++++++++------
 2 files changed, 30 insertions(+), 9 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index e24fe36..6d07e06 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -544,10 +544,8 @@ def plotAF(
     AFtab=pd.DataFrame(),
     cols = list(mcolors.TABLEAU_COLORS.keys()),
     datasetID="population",
-    weights = "2n",
     hdi=pd.DataFrame(),
-    conc_mu=1,
-    conc_sigma=1
+    compound_mean=pd.DataFrame()
     ):
     """Plot combined allele frequencies, individual allele frequencies,
     and credible intervals on combined allele frequency estimates.
@@ -601,6 +599,14 @@ def plotAF(
                 xmax = interval[1]['hi'],
                 color="black"
             )
+    if not compound_mean.empty:
+        for row in compound_mean.iterrows():
+            plt.scatter(
+                y = row[1]['allele'],
+                x = row[1]['post_mean'],
+                color = 'black',
+                marker = "|"
+            )
     plt.xlabel("Allele frequency")
     plt.grid(zorder=0)
     plt.show()
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 7ba0917..91567ed 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -51,7 +51,8 @@ def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
         idata = pm.sample()
     return idata
 
-def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True):
+def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True,
+          format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
     """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
     
@@ -80,17 +81,30 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, p
             In alphabetical order of alleles, regardless of input order.
             This way it matches the output of combineAF().
     """
-    c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
+
+    df = AFtab.copy()
+    HLAfreq.single_loci(df)
+    if unique:
+        assert HLAfreq.alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
+    if complete:
+        assert HLAfreq.incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+    if resolution:
+        assert HLAfreq.check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+    if format:
+        df = HLAfreq.formatAF(df, ignoreG)
+    if add_unmeasured:
+        df = HLAfreq.unmeasured_alleles(df, datasetID)
+    c_array, allele_names = _make_c_array(df, weights, datasetID)
     idata = _fit_Dirichlet_Multinomial(c_array, prior, conc_mu=conc_mu, conc_sigma=conc_sigma)
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
     post_mean = az.summary(idata, var_names='frac')['mean']
     post = pd.DataFrame([hdi[:,0], hdi[:,1], allele_names, post_mean]).T
     post.columns = ['lo','hi','allele','post_mean']
     if compare_models:
-        compare_estimates(AFtab, post)
+        compare_estimates(AFtab, post, datasetID)
     return post
 
-def compare_estimates(AFtab, hdi):
+def compare_estimates(AFtab, hdi, datasetID):
     """Does the defaul estimate of `allele_freq` sit within the compound
     model's estimated credible intervals? If not, print warnings.
 
@@ -98,9 +112,10 @@ def compare_estimates(AFtab, hdi):
         AFtab (pd.DataFrame): Table of allele frequency data
         hdi (np.array): Pairs of high density interval limits, allele name, and posterior mean from compound model.
     """
-    caf = HLAfreq.combineAF(AFtab)
+    
+    caf = HLAfreq.combineAF(AFtab, datasetID=datasetID)
     caf = pd.merge(caf, hdi, how="left", on="allele")
-    mask = (caf.allele_freq > caf.lo) & (caf.allele_freq < caf.hi)
+    mask = (caf.allele_freq < caf.lo) | (caf.allele_freq > caf.hi)
     if mask.sum() > 0:
         print()
         print("WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!")

From 8b19902ec5dc7ff2cc596239f61a608f3d27bee7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:39:41 +0000
Subject: [PATCH 097/192] Add hdi plot to basic use case

---
 examples/paper/basic_use_case.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
index c453090..7ee9004 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/basic_use_case.py
@@ -1,11 +1,12 @@
 import matplotlib.pyplot as plt
 from HLAfreq import makeURL, getAFdata, combineAF, plotAF, population_coverage
+from HLAfreq import HLAfreq_pymc
 
 base_url = makeURL("Mongolia", standard="g", locus="DQB1")
 aftab = getAFdata(base_url)
-aftab.population.unique()
 caf = combineAF(aftab)
-plotAF(caf, aftab, credible_interval=0.95)
+hdi = HLAfreq_pymc.AFhdi(aftab, credible_interval=0.95)
+plotAF(caf, aftab, hdi=hdi, compound_mean=hdi)
 
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
 plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(population_coverage))

From 27b9875490cb2cd56701a25bd06a1c9f385dc9c4 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:40:20 +0000
Subject: [PATCH 098/192] Plot cumulative frequency of IEDB panel  vs country
 specific alleles

---
 examples/paper/select_hla_panel.py | 54 ++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)

diff --git a/examples/paper/select_hla_panel.py b/examples/paper/select_hla_panel.py
index 90f31da..b36958d 100644
--- a/examples/paper/select_hla_panel.py
+++ b/examples/paper/select_hla_panel.py
@@ -11,6 +11,8 @@
 
 # The IEDB reference panel
 iedb_ref = ['B*35:01', 'A*30:01', 'A*02:03', 'B*15:01', 'B*57:01', 'A*68:02', 'A*23:01', 'B*53:01', 'A*03:01', 'B*40:01', 'B*44:02', 'B*51:01', 'A*33:01', 'A*01:01', 'A*68:01', 'A*24:02', 'B*07:02', 'B*08:01', 'A*02:06', 'A*26:01', 'A*11:01', 'A*30:02', 'A*31:01', 'B*58:01', 'B*44:03', 'A*32:01', 'A*02:01']
+iedb_refa = [i for i in iedb_ref if "A" in i]
+iedb_refb = [i for i in iedb_ref if "B" in i]
 
 regions = pd.read_csv("data/example/countries.csv")
 countries = regions.Country.tolist()
@@ -85,6 +87,58 @@
 plt.grid(zorder=0)
 plt.show()
 
+##############
+# Plot cumulative frequency of IEDB panel
+# vs
+# country specific alleles
+#A
+country = "Indonesia"
+afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
+afa = HLAfreq.only_complete(afa)
+afa = HLAfreq.decrease_resolution(afa, 2)
+cafa = HLAfreq.combineAF(afa)
+
+cafa = cafa.sort_values('allele_freq', ascending=False, ignore_index=True)
+plt.scatter(cafa.allele, cafa.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+# plt.tight_layout(); plt.show()
+
+maska = cafa.allele.isin(iedb_refa)
+cafai = cafa[maska].sort_values('allele_freq', ascending=False, ignore_index=True)
+# Add unobserved IEDB ref alleles
+missing_iedb = pd.DataFrame([[i, 'A',0,0,473,1,0] for i in iedb_refa if not i in cafai.allele.values], columns=cafai.columns)
+cafai = pd.concat([cafai, missing_iedb])
+plt.scatter(cafai.allele, cafai.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+plt.ylim(0,1.05)
+plt.tight_layout(); plt.show()
+
+#B
+country = "Indonesia"
+afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
+afb = HLAfreq.only_complete(afb)
+afb = HLAfreq.decrease_resolution(afb, 2)
+cafb = HLAfreq.combineAF(afb)
+
+cafb = cafb.sort_values('allele_freq', ascending=False, ignore_index=True)
+plt.scatter(cafb.allele, cafb.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+# plt.tight_layout(); plt.show()
+
+maskb = cafb.allele.isin(iedb_ref)
+cafbi = cafb[maskb].sort_values('allele_freq', ascending=False, ignore_index=True)
+# Add unobserved IEDB ref alleles
+missing_iedb = pd.DataFrame([[i, 'B',0,0,473,1,0] for i in iedb_refb if not i in cafbi.allele.values], columns=cafbi.columns)
+cafbi = pd.concat([cafbi, missing_iedb])
+plt.scatter(cafbi.allele, cafbi.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+plt.ylim(0,1.05)
+plt.tight_layout(); plt.show()
+
 #############
 # Plot the cumulative allele frequency of HLA-A and HLA-B
 # a single country, with alleles coloured by supertype

From fd0874022c7687ffa49e3fea5773915d0a4b171e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:49:49 +0000
Subject: [PATCH 099/192] Explore high dimensions issue

Small datasets with many alleles had very low hdi for all alleles
This update uses simulations to explore the cause
It shows that one common allele and many rare leads to underestimated
frequencies for the common allele
This problem is made worse by increasing numbers of alleles
The prolem is much worse for the compound model
We have seen that we can fix this with perks prior (1/k)
---
 examples/CI_simulated_data.py | 155 +++++++++++++++++++++++++++-------
 1 file changed, 125 insertions(+), 30 deletions(-)

diff --git a/examples/CI_simulated_data.py b/examples/CI_simulated_data.py
index 715d9bf..3aeff5f 100644
--- a/examples/CI_simulated_data.py
+++ b/examples/CI_simulated_data.py
@@ -9,6 +9,8 @@
 import arviz as az
 import pandas as pd
 import scipy as sp
+import HLAfreq
+from HLAfreq import HLAfreq_pymc as HLAhdi
 
 def simulateAF(k, concentration, n, samplesize_lo=5, samplesize_hi=200):
     """ Simulate allele frequency dataset for k alleles and n populations.
@@ -20,7 +22,15 @@ def simulateAF(k, concentration, n, samplesize_lo=5, samplesize_hi=200):
     The range of posible sample size is between samplesize_lo and samplesize_hi.
     """
     # Global AF
-    alpha = sp.stats.dirichlet(np.ones(k)).rvs()
+    # Flat prior
+    # alpha = sp.stats.dirichlet(np.ones(k)).rvs()
+    
+    # prior with one high freq allele
+    alpha = np.ones(k)
+    # alpha[0] = 5*k
+    
+    alpha = sp.stats.dirichlet(alpha).rvs()
+
     alpha = alpha.reshape(-1)
     # The Dirichlet distribution which populations are drawn from
     dd = sp.stats.dirichlet(alpha*concentration)
@@ -30,36 +40,72 @@ def simulateAF(k, concentration, n, samplesize_lo=5, samplesize_hi=200):
     allele_counts = np.vstack([sp.stats.multinomial(n=samples, p=af).rvs() for samples,af in zip(sample_size, popAF)])
     return alpha, popAF, allele_counts
 
+def serialise_aftab(allele_counts):
+    aftab = pd.DataFrame(allele_counts)
+    aftab['sample_size'] = aftab.apply(sum, axis=1)
+    aftab['population'] = aftab.index
+    aftab = pd.melt(aftab,
+            id_vars=['population', 'sample_size'],
+            value_vars=range(allele_counts.shape[1]),
+            value_name='allele_count',
+            var_name="allele")
+    aftab['loci'] = "X"
+    aftab['allele_freq'] = aftab.allele_count/aftab.sample_size
+    aftab.allele = aftab.allele+1000
+    aftab.population = aftab.population.astype(str)
+    aftab.allele = aftab.allele.astype(str)
+    return aftab
+
+
 results = []
-for i in range(100):
-    print(i)
-    alpha, popAF, allele_counts = simulateAF(k=15, concentration=10, n=5)
-
-    # Key data derived from simulated data
-    # Number of alleles
-    k = len(alpha)
-    # Number of populations
-    n = popAF.shape[0]
-    # Sample size for each population
-    sample_size = np.apply_along_axis(sum, 1, allele_counts)
-
-    # Define and fit model
-    with pm.Model() as m1:
-        frac = pm.Dirichlet('frac', a=np.ones(k))
-        conc = pm.Lognormal('conc', mu=1, sigma=1)
-        y = pm.DirichletMultinomial('y', n=sample_size, a=frac*conc, shape=(n,k), observed=allele_counts)
-
-    with m1:
-        idata1 = pm.sample()
-
-    # Store results
-    result = {
-        'lo': az.summary(idata1)[:k]['hdi_3%'],
-        'hi':az.summary(idata1)[:k]['hdi_97%'],
-        'alpha': alpha,
-        'popAF': popAF
-    }
-    results.append(result)
+for k in range(10, 110, 10):
+    for i in range(1):
+        print(f"{i} for k={k}")
+        alpha, popAF, allele_counts = simulateAF(k=k, concentration=100, n=5)
+
+        # # Key data derived from simulated data
+        # # Number of alleles
+        # k = len(alpha)
+        # # Number of populations
+        # n = popAF.shape[0]
+        # # Sample size for each population
+        # sample_size = np.apply_along_axis(sum, 1, allele_counts)
+
+        # # Define and fit model
+        # with pm.Model() as m1:
+        #     frac = pm.Dirichlet('frac', a=np.ones(k))
+        #     conc = pm.Lognormal('conc', mu=1, sigma=1)
+        #     y = pm.DirichletMultinomial('y', n=sample_size, a=frac*conc, shape=(n,k), observed=allele_counts)
+
+        # with m1:
+        #     idata1 = pm.sample()
+
+        # Store results
+        # result = {
+        #     'lo': az.summary(idata1)[:k]['hdi_3%'],
+        #     'hi':az.summary(idata1)[:k]['hdi_97%'],
+        #     'alpha': alpha,
+        #     'popAF': popAF
+        # }
+
+        aftab = serialise_aftab(allele_counts)
+        caf = HLAfreq.combineAF(aftab)
+        hdi = HLAhdi.AFhdi(aftab, prior=[1/k]*k)
+        caf = pd.merge(caf, hdi, how="left", on="allele")
+
+        # Store results
+        result = {
+            'lo': caf.lo,
+            'hi': caf.hi,
+            'post_mean': caf.post_mean,
+            'allele_freq': caf.allele_freq,
+            'alpha': alpha,
+            'popAF': popAF,
+            'k':k,
+            'total_c': caf.c.sum()
+        }
+
+        results.append(result)
 
 # View summary results
 def alpha_in_hdi(result):
@@ -90,3 +136,52 @@ def popAF_in_hdi(result):
 ax[1].hist(pih)
 ax[1].axvline(np.mean(pih), color="black")
 plt.show()
+
+#               #
+#   k/c_total   #
+#               #
+
+plt.plot([r['k']/r['total_c'] for r in results]);plt.show()
+
+def reduction_vs_kc(estimate, results, ax):
+    # post mean reduction vs k/c
+    for result in results:
+        ax.scatter(
+            [result['k']/result['total_c']] * result['k'],
+            result['alpha'] - result[estimate]
+        )
+    ax.set(xlabel='k/total_c', ylabel=f'{estimate} reduction')
+
+def est_vs_true(estimate, results, ax):
+    # post_mean vs alpha coloured by k/c
+    ax.scatter(
+        pd.concat([pd.Series(r['alpha']) for r in results]),
+        pd.concat([r[estimate] for r in results]),
+        c=pd.concat([pd.Series([r['k']/result['total_c']]*r['k']) for r in results])
+    )
+    ax.plot([0,1], [0,1], c='black', linestyle="--")
+    ax.set(xlabel='alpha', ylabel=estimate)
+
+def kc_effect(results):
+    fig, ax = plt.subplots(2,2)
+    reduction_vs_kc('post_mean', results, ax[0,0])
+    est_vs_true('post_mean', results, ax[1,0])
+    reduction_vs_kc('allele_freq', results, ax[0,1])
+    est_vs_true('allele_freq', results, ax[1,1])
+    plt.show()
+
+kc_effect(results)
+kc_effect(results[:100])
+kc_effect(results[100:110])
+kc_effect(results[110:120])
+kc_effect(results[120:130])
+
+fig,ax = plt.subplots()
+# post_mean vs alpha coloured by k/c
+ax.scatter(
+    pd.concat([pd.Series(r['alpha']) for r in results]),
+    pd.concat([r['post_mean'] for r in results]),
+    c=pd.concat([pd.Series([r['k']]*r['k']) for r in results])
+)
+ax.plot([0,1], [0,1], c='black', linestyle="--")
+ax.set(xlabel='alpha', ylabel='post_mean')
\ No newline at end of file

From b2ed199870fe41d1ae37b5d37335c67e4ac5b29b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:50:18 +0000
Subject: [PATCH 100/192] Update plot and access the underlying model

---
 examples/CI_empirical_data.py | 24 +++++++++++++++++-------
 1 file changed, 17 insertions(+), 7 deletions(-)

diff --git a/examples/CI_empirical_data.py b/examples/CI_empirical_data.py
index 58003b9..e8697d0 100644
--- a/examples/CI_empirical_data.py
+++ b/examples/CI_empirical_data.py
@@ -31,12 +31,6 @@
 aftab = HLAfreq.decrease_resolution(aftab, 2)
 caf = HLAfreq.combineAF(aftab)
 
-#           #
-#   Plot CI #
-#           #
-
-HLAfreq.plotAF(AFtab=aftab, credible_interval=0.95)
-
 #                   #
 #   Calculate CI    #
 #                   #
@@ -44,4 +38,20 @@
 hdi = HLAhdi.AFhdi(aftab)
 # Add to caf
 caf = pd.merge(caf, hdi, 'left', on='allele')
-caf[['allele', 'allele_freq', 'post_mean', 'lo', 'hi']]
\ No newline at end of file
+caf[['allele', 'allele_freq', 'post_mean', 'lo', 'hi']]
+
+#           #
+#   Plot CI #
+#           #
+
+HLAfreq.plotAF(caf, AFtab=aftab, hdi=hdi, compound_mean=hdi)
+
+#                           #
+#   Access model directly   #
+#                           #
+
+c_array, allele_names = HLAhdi._make_c_array(aftab)
+idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)
+idata.posterior.frac
+
+az.plot_trace(idata); plt.show()
\ No newline at end of file

From 2c6f2e75e4079d1ba54cef92a9ab974b17240b09 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Mar 2023 10:55:53 +0000
Subject: [PATCH 101/192] Update single country example plot and description

---
 examples/single_country.ipynb | 143 ++++------------------------------
 1 file changed, 15 insertions(+), 128 deletions(-)

diff --git a/examples/single_country.ipynb b/examples/single_country.ipynb
index c77a055..93defed 100644
--- a/examples/single_country.ipynb
+++ b/examples/single_country.ipynb
@@ -164,59 +164,16 @@
      "text": [
       "Auto-assigning NUTS sampler...\n",
       "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
       "Multiprocess sampling (4 chains in 4 jobs)\n",
       "NUTS: [frac, conc]\n"
      ]
     },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "    <div>\n",
-       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      100.00% [8000/8000 00:14&lt;00:00 Sampling 4 chains, 0 divergences]\n",
-       "    </div>\n",
-       "    "
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 15 seconds.\n"
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 13 seconds.\n"
      ]
     }
    ],
@@ -227,20 +184,18 @@
     "# Calculate High Density interval\n",
     "# This takes a few seconds and can be skipped if not needed\n",
     "hdi = HLAhdi.AFhdi(afloc, credible_interval=0.95)\n",
-    "hdi = pd.DataFrame(hdi, columns=['cl', 'cu', 'allele'])\n",
-    "\n",
-    "# Add low and high credible interval\n",
+    "# Add credible intervals and posterior mean to caf\n",
     "caf = pd.merge(caf, hdi, how=\"left\", on=\"allele\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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83+Veent7GQCb8RBCCCFkZprM326BMca+9GySTJu+vj54eHigt7eXZuwIIYSQ+8Bk/nbPyHfsCCGEEELI5FFiRwghhBAyS1BiRwghhBAyS0xrYpeZmQlBECAIApycnKBQKLB06VKUlZVhZGSE1wsODub1XFxcoFarsWvXLlFbTU1NvI4gCHB2dkZkZCT/qnRUc3MzkpKS4OfnB0EQcOjQoXHHt3jxYpuy6upqxMXFwdPTE4Ig8KVM7o67cyyCIOD555+f8PeoqqpCeHg45syZA7VajWPHjvFrn3zyCfLz86FWq/Hggw/Cz88P6enp/OtcQgghhJBpX+4kISEB5eXlouVOcnNzsX//fhw+fBiOjreHWFRUBKPRiMHBQVRVVcFoNMLf3x8Gg0HUXnt7O9zd3TE0NIQjR44gKysLoaGh0Ol0AICBgQFoNBqsWbMGK1assBlPTU0N/Pz8RIsUV1RUQKvVIiwsDAMDA1iwYAFSU1NhNBrHvS+j0YiioiJ+7uLics/f4dSpU0hLS+NLvezduxfLli1DW1sboqKiMDg4iLa2NvzsZz+DRqNBT08PcnNz8b3vfQ+tra0T/9B3iSqswwPSe4+JEEIIIfa5/EridA8BwAxI7KRSKd9dwd/fH1qtFjExMdDpdNi9ezffD9bNzY3Xy8/Px+bNm1FfX2+T2Pn4+OChhx4CAKxduxbbtm1DW1sbT+wMBoNNzJ1CQkKQl5eHmJgY3Lx5E6mpqZDJZIiLiwNwe6FgALh8+fI978vFxYWP1x5bt25FQkICTCYTAOCll15CfX09tm/fjh07dsDDwwP19fWimO3bt+M73/kOurq67FqDjxBCCCGz24x8x27JkiXQaDSorq62uTYyMoIDBw6gp6cHEolk3DYYY6itrUVXVxff0sseERERqKurQ0dHB86cOQO9Xo+dO3dCLpdP6h5+//vfw8vLC1FRUSgoKMDg4KDoenBwMDZu3MjPW1paoNfrRXXi4+PR0tIybh+9vb0QBIEnsmOxWq3o6+sTHYQQQgiZnWZkYgcA4eHholmx/Px8uLq6QiqVIiUlBTKZjM/m3WnevHlwdXWFRCJBYmIiCgsLsXDhQrv7bW9vh8FggEqlgkajwfHjx5GdnY2enh6721i1ahV+97vfobGxEQUFBdizZw9+8IMfiOqEhobCy8uLn1ssFigUClEdhUIBi8UyZh+3bt1Cfn4+0tLS7rmmTUlJCTw8PPgREBBg930QQggh5P4y7Y9ix8MYgyAI/NxkMiEzMxNXr16FyWRCdnY2VCqVTdzJkyfh5ubGtxTLycmBXC5HVlaWXf1euHABxcXF0Gq1aG5uRmVlJfbt24fr169DJpPZ1cazzz7L/61WqzF37lzodDpcunQJoaGhAGCzL+xkfPLJJ0hNTQVjDG+88cY96xYUFGD9+vX8vK+vj5I7QgghZJaasYnd+fPnoVQq+bmXlxdUKhVUKhWqqqqgVqsRHR2NiIgIUZxSqeSPJiMjI3H69GkUFxfbndglJSXZlKWlpU39RgD+KPjixYs8sbubr68vuru7RWXd3d027+mNJnUfffQRGhoaJlyBWiqVQiqVfobRE0IIIeR+MSMfxTY0NODcuXNITk4e83pAQABWrlyJgoKCCdtycHDA0NDQlMbR1NQ0pbi7jS6JMnfu3HHrxMbG2szi1dfXIzY2lp+PJnUdHR04fvw4PD09P5fxEUIIIWR2mPYZO6vVCovFIlruZHTJj/T09HHjcnNzERUVhdbWVkRHR/Pya9eu4datW/xR7J49e5CSksKv9/f34+LFi/y8s7MTZrMZcrncri9Lb9y4ga6uLr5+XHt7O4DbM26+vr64dOkS9u7diyeeeAKenp44e/Ys8vLysHDhQnzzm9/k7eh0Oixfvhw5OTn8fhYtWoQtW7YgMTERFRUVaG1t5evwffLJJ0hJSUFbWxtqamowPDzM37+Ty+X3/JBkLO9tiqe9YgkhhJDZhk2jjIwMBoABYI6Ojszb25vp9XpWVlbGhoeHeb2goCBWWlpqEx8fH88MBgNjjLHGxkbe1mh7SqWSbdiwgfX39/OYu+uNHhkZGXaNuby8fMz4wsJCxhhjXV1dbOHChUwulzOpVMpUKhUzmUyst7dX1E5QUBCPGVVZWcnCwsKYRCJhkZGR7OjRo/xaZ2fnmP0CYI2NjXaNnTHGent7GQCb8RBCCCFkZprM326BMca+xDySTLO+vj54eHigt7eXZuwIIYSQ+8Bk/nbPyHfsCCGEEELI5FFiRwghhBAyS1BiRwghhBAyS0xrYpeZmQlBECAIApycnKBQKLB06VKUlZVhZGSE1wsODub1XFxcoFarsWvXLlFbTU1NvI4gCHB2dkZkZCT/qnRUc3MzkpKS4OfnB0EQcOjQoXHHt3jxYpuy6upqxMXFwdPTE4Ig8KVM7o67cyyCIOD555+f8PeoqqpCeHg45syZA7VajWPHjk26b0IIIYR8dU37cicJCQkoLy8XLXeSm5uL/fv34/Dhw3B0vD3EoqIiGI1GDA4OoqqqCkajEf7+/jAYDKL22tvb4e7ujqGhIRw5cgRZWVkIDQ2FTqcDAAwMDECj0WDNmjVYsWKFzXhqamrg5+cHrVbLyyoqKqDVahEWFoaBgQEsWLAAqampMBqN496X0WhEUVERP3dxcbnn73Dq1CmkpaXxpV727t2LZcuWoa2tDVFRUXzs9vRtj6jCOjwgvfeYCCHT4/IridM9BELIfWraEzupVMp3V/D394dWq0VMTAx0Oh12797N94N1c3Pj9fLz87F582bU19fbJHY+Pj5854m1a9di27ZtaGtr44mdwWCwiblTSEgI8vLyEBMTg5s3byI1NRUymQxxcXEAgNWrVwOAaB/bsbi4uNjsGnEvW7duRUJCAkwmEwDgpZdeQn19PbZv344dO3ZMqm9CCCGEfDXNyHfslixZAo1Gg+rqaptrIyMjOHDgAHp6eu65KC9jDLW1tejq6uJbetkjIiICdXV16OjowJkzZ6DX67Fz507I5fJJ3cPvf/97eHl5ISoqCgUFBRgcHBRdDw4OxsaNG/l5S0sL9Hq9qE58fDxaWlom1e/drFYr+vr6RAchhBBCZqcZmdgBQHh4uGhmKj8/H66urpBKpUhJSYFMJuOzeXeaN28eXF1dIZFIkJiYiMLCQixcuNDuftvb22EwGKBSqaDRaHD8+HFkZ2ejp6fH7jZWrVqF3/3ud2hsbERBQQH27NmDH/zgB6I6oaGh8PLy4ucWiwUKhUJUR6FQ8N0lpqqkpAQeHh78CAgI+EztEUIIIWTmmvZHseNhjEEQBH5uMpmQmZmJq1evwmQyITs7GyqVyibu5MmTcHNz41uK5eTkQC6XIysry65+L1y4gOLiYmi1WjQ3N6OyshL79u3D9evXIZPJ7Grj2Wef5f9Wq9WYO3cudDodLl26hNDQUACw2Rf2i1JQUID169fz876+PkruCCGEkFlqxiZ258+fh1Kp5OdeXl5QqVRQqVSoqqqCWq1GdHQ0IiIiRHFKpZK/YxcZGYnTp0+juLjY7sQuKSnJpiwtLW3qNwLwR8EXL17kid3dfH190d3dLSrr7u6e1Ht6Y5FKpZBKpZ+pDUIIIYTcH2bko9iGhgacO3cOycnJY14PCAjAypUrUVBQMGFbDg4OGBoamtI4mpqaphR3t9FlSebOnTtundjYWJtZvPr6esTGxn4uYyCEEELI7DftM3ZWqxUWi0W03Mnokh/p6enjxuXm5iIqKgqtra2Ijo7m5deuXcOtW7f4o9g9e/YgJSWFX+/v78fFixf5eWdnJ8xmM+RyOQIDAycc740bN9DV1YUrV64AuP1OHnB7xs3X1xeXLl3C3r178cQTT8DT0xNnz55FXl4eFi5ciG9+85u8HZ1Oh+XLlyMnJ4ffz6JFi7BlyxYkJiaioqICra2tonX4Jup7Mt7bFE97xRJCCCGzDZtGGRkZDAADwBwdHZm3tzfT6/WsrKyMDQ8P83pBQUGstLTUJj4+Pp4ZDAbGGGONjY28rdH2lEol27BhA+vv7+cxd9cbPTIyMuwac3l5+ZjxhYWFjDHGurq62MKFC5lcLmdSqZSpVCpmMplYb2+vqJ2goCAeM6qyspKFhYUxiUTCIiMj2dGjRyfVtz16e3sZAJvxEEIIIWRmmszfboExxr7MRJJMr76+Pnh4eKC3t5dm7AghhJD7wGT+ds/Id+wIIYQQQsjkUWJHCCGEEDJLTGtil5mZCUEQIAgCnJycoFAosHTpUpSVlWFkZITXCw4O5vVcXFygVquxa9cuUVtNTU28jiAIcHZ2RmRkpOjjAwBobm5GUlIS/Pz8IAgCDh06NO74Fi9ebFNWXV2NuLg4eHp6QhAE/sXrWBhjMBgME/YDAP/93/+N5ORkfq+vvfbamPVef/11BAcHY86cOZg/fz7eeeede7ZLCCGEkK+Oaf8qNiEhAeXl5aKvYnNzc7F//34cPnwYjo63h1hUVASj0YjBwUFUVVXBaDTC39/fZt/X9vZ2uLu7Y2hoCEeOHEFWVhZCQ0P5XrEDAwPQaDRYs2YNVqxYYTOempoa+Pn5QavV8rKKigpotVqEhYVhYGAACxYsQGpqKoxG4z3v7bXXXhMtsnwvg4ODCAkJwfe//33k5eWNWecPf/gD1q9fjx07dmD+/Pl47bXXEB8fj/b2dvj4+NjVz6iowjo8IHWZVMzdaKNyQgghZGaZ9sROKpXypTr8/f2h1WoRExMDnU6H3bt3823D3NzceL38/Hxs3rwZ9fX1Nomdj48PX6B47dq12LZtG9ra2nhiZzAYbGLuFBISgry8PMTExODmzZtITU2FTCZDXFwcAGD16tUAINrubCxmsxlbtmxBa2vrPdevG/XII4/gkUceAQC8+OKLY9b55S9/CaPRiB/+8IcAgB07duDo0aMoKysbN4YQQgghXx0z8h27JUuWQKPRoLq62ubayMgIDhw4gJ6eHkgkknHbYIyhtrYWXV1dfOcHe0RERKCurg4dHR04c+YM9Ho9du7cCblcbncbg4ODWLVqFV5//fVx15cLDg7Gxo0b7W7zn//8J/76179Cr9fzsgceeAB6vR4tLS12t0MIIYSQ2WtGJnYAEB4eLpoVy8/Ph6urK6RSKVJSUiCTyfhs3p3mzZsHV1dXSCQSJCYmorCwEAsXLrS73/b2dhgMBqhUKmg0Ghw/fhzZ2dno6emxu428vDw8+uijeOqpp8atExoaCi8vL7vb/Mc//oHh4WEoFApRuUKhgMViGTfOarWir69PdBBCCCFkdpr2R7HjYYyJ3k8zmUzIzMzE1atXYTKZkJ2dDZVKZRN38uRJuLm58Z0ncnJyIJfL7d4r9sKFCyguLoZWq0VzczMqKyuxb98+XL9+HTKZbML4w4cPo6GhAe++++496929fdgXpaSkBJs2bfpS+iKEEELI9Jqxid358+ehVCr5uZeXF1QqFVQqFaqqqqBWqxEdHY2IiAhRnFKp5O/YRUZG4vTp0yguLrY7sUtKSrIpS0tLs3vcDQ0NuHTpEh/DqOTkZDz22GNT3n/Wy8sLDg4O6O7uFpV3d3ffczuxgoICrF+/np/39fUhICBgSmMghBBCyMw2Ix/FNjQ04Ny5c0hOTh7zekBAAFauXImCgoIJ23JwcMDQ0NCUxjGVJOzFF1/E2bNnYTab+QEApaWlKC8vn9I4AEAikeDb3/62aKZvZGQEJ06cQGxs7LhxUqkU7u7uooMQQgghs9O0z9hZrVZYLBbRciclJSV48sknkZ6ePm5cbm4uoqKi0NraiujoaF5+7do13Lp1iz+K3bNnD1JSUvj1/v5+XLx4kZ93dnbCbDZDLpcjMDBwwvHeuHEDXV1duHLlCoDb7+QBgK+vr+i4W2BgoGgGUqfTYfny5cjJyQFw++OI999/n//7448/htlshqurK3/kvH79emRkZCA6Ohrf+c538Nprr2FgYIB/JTsZ722KpySPEEIImW2+2G1r7y0jI4NvZO/o6Mi8vb2ZXq9nZWVlbHh4mNcLCgpipaWlNvHx8fHMYDAwxhhrbGzkbY22p1Qq2YYNG1h/fz+Pubve6JGRkWHXmMvLy8eMLywsHDcGADt48KCoLCgoSBTT2dk5ZruLFi0Sxf3Hf/wHCwwMZBKJhH3nO99hf/7zn+0a96jJbCRMCCGEkOk3mb/dAmOMfYl5JJlmk9lImBBCCCHTbzJ/u2fkO3aEEEIIIWTyKLEjhBBCCJklKLEjhBBCCJklpjWxy8zMhCAIEAQBTk5OUCgUWLp0KcrKyjAyMsLrBQcH83ouLi5Qq9XYtWuXqK2mpiZeRxAEODs7IzIyEm+++aaoXnNzM5KSkuDn5wdBEHDo0KFxx7d48WKbsurqasTFxcHT0xOCIPDlTMbCGIPBYJiwn1FVVVUIDw/HnDlzoFarcezYMdH1O3+v0SMhIWHCdgkhhBDy1TDty50kJCSgvLxctNxJbm4u9u/fj8OHD8PR8fYQi4qKYDQaMTg4iKqqKhiNRvj7+8NgMIjaa29vh7u7O4aGhnDkyBFkZWUhNDQUOp0OADAwMACNRoM1a9ZgxYoVNuOpqamBn58ftFotL6uoqIBWq0VYWBgGBgawYMECpKamwmg03vPeXnvtNdHuGfdy6tQppKWl8aVe9u7di2XLlqGtrQ1RUVE2v9coqVRqV/t3iyqswwNSlynFfpEuv5I43UMghBBC7lvTnthJpVK+7pu/vz+0Wi1iYmKg0+mwe/duvh+sm5sbr5efn4/Nmzejvr7eJrHz8fHhuz6sXbsW27ZtQ1tbG0/sDAaDTcydQkJCkJeXh5iYGNy8eROpqamQyWSIi4sDAKxevRoARPvYjsVsNmPLli1obW3F3LlzJ/wdtm7dioSEBJhMJgDASy+9hPr6emzfvh07duwY8/cihBBCCLnTjHzHbsmSJdBoNKiurra5NjIyggMHDqCnpwcSiWTcNhhjqK2tRVdXF+bPn2933xEREairq0NHRwfOnDkDvV6PnTt3Qi6X293G4OAgVq1ahddff33cJCw4OBgbN27k5y0tLdDr9aI68fHxaGlpEZU1NTXBx8cHX//615GVlYX/+Z//sXtchBBCCJndZmRiBwDh4eGiWbH8/Hy4urpCKpUiJSUFMpmMz+bdad68eXB1dYVEIkFiYiIKCwuxcOFCu/ttb2+HwWCASqWCRqPB8ePHkZ2djZ6eHrvbyMvLw6OPPoqnnnpq3DqhoaHw8vLi5xaLBQqFQlRHoVDAYrHw84SEBPz2t7/FiRMn8Oqrr+Ltt9+GwWDA8PDwuP1YrVb09fWJDkIIIYTMTtP+KHY8jDHR+2kmkwmZmZm4evUqTCYTsrOz+VZbdzp58iTc3Nz4lmI5OTmQy+XIysqyq98LFy6guLgYWq0Wzc3NqKysxL59+3D9+nXIZLIJ4w8fPoyGhga8++6796x3556v9vqXf/kX/m+1Wo1vfvObCA0NRVNTE3/UfLeSkhJs2rRp0n0RQggh5P4zY2fszp8/L9pb1cvLCyqVCo899hiqqqqwdu1avrfqnZRKJVQqFSIjI/HDH/4Qq1evRnFxsd39JiUliT6cAIC0tDSEhYXZFd/Q0IBLly7hoYcegqOjI//4Izk5ecyvbEf5+vqiu7tbVNbd3X3P9+lCQkLg5eUl2vv2bgUFBejt7eXH3/72N7vugxBCCCH3nxmZ2DU0NODcuXNITk4e83pAQABWrlyJgoKCCdtycHDA0NDQlMbR1NQ06ZgXX3wRZ8+ehdls5gcAlJaWir5mvVtsbKzNLF59fT1iY2PHjfn73/+O//mf/7nnxxlSqRTu7u6igxBCCCGz07Q/irVarbBYLKLlTkaX/EhPTx83Ljc3F1FRUWhtbUV0dDQvv3btGm7dusUfxe7ZswcpKSn8en9/v2iGq7OzE2azGXK5HIGBgROO98aNG+jq6sKVK1cA3H4nD7g943bncbfAwEDRDKROp8Py5cuRk5PD72fRokXYsmULEhMTUVFRgdbWVr4OX39/PzZt2oTk5GT4+vri0qVL+PGPfwyVSoX4+PgJx3239zbFU5JHCCGEzDZsGmVkZDAADABzdHRk3t7eTK/Xs7KyMjY8PMzrBQUFsdLSUpv4+Ph4ZjAYGGOMNTY28rZG21MqlWzDhg2sv7+fx9xdb/TIyMiwa8zl5eVjxhcWFo4bA4AdPHhQVBYUFGQTU1lZycLCwphEImGRkZHs6NGj/Nrg4CCLi4tj3t7ezMnJiQUFBTGj0cgsFotd4x7V29vLALDe3t5JxRFCCCFkekzmb7fAGGNfdjJJpk9fXx88PDzQ29tLM3aEEELIfWAyf7tn5Dt2hBBCCCFk8iixI4QQQgiZJSixI4QQQgiZJaY1scvMzIQgCBAEAU5OTlAoFFi6dCnKysowMjLC6wUHB/N6Li4uUKvV2LVrl6itpqYmXkcQBDg7OyMyMpJ/VTqqubkZSUlJ8PPzgyAIOHTo0LjjG2vduerqasTFxcHT0xOCIPDlTMbCGIPBYJiwn1FVVVUIDw/HnDlzoFarcezYsXHrPv/88xAEAa+99tqE7RJCCCHkq2HalztJSEhAeXm5aLmT3Nxc7N+/H4cPH+YL/BYVFcFoNGJwcBBVVVUwGo3w9/eHwWAQtdfe3g53d3cMDQ3hyJEjyMrKQmhoKN+ZYWBgABqNBmvWrMGKFStsxlNTUwM/Pz/RIsUVFRXQarUICwvDwMAAFixYgNTUVBiNxnve22uvvSbaPeNeTp06hbS0NL7Uy969e7Fs2TK0tbUhKipKVPfgwYP485//DD8/P7vaHktUYR0ekLpMOZ58+S6/kjjdQyCEEDLDTXtiJ5VK+bpv/v7+0Gq1iImJgU6nw+7du/l+sG5ubrxefn4+Nm/ejPr6epvEzsfHBw899BAAYO3atdi2bRva2tp4YmcwGGxi7hQSEoK8vDzExMTg5s2bSE1NhUwmQ1xcHABg9erVACDax3YsZrMZW7ZsQWtr6z0XEB61detWJCQkwGQyAQBeeukl1NfXY/v27dixYwev9/HHH+NHP/oR6urqkJhIf+gJIYQQ8v/MyHfslixZAo1Gg+rqaptrIyMjOHDgAHp6eiCRSMZtgzGG2tpadHV1Yf78+Xb3HRERgbq6OnR0dODMmTPQ6/XYuXMn5HK53W0MDg5i1apVeP3118fdEiw4OBgbN27k5y0tLdDr9aI68fHxaGlp4ecjIyNYvXo1TCYTIiMj7RqL1WpFX1+f6CCEEELI7DQjEzsACA8PF82K5efnw9XVFVKpFCkpKZDJZHw2707z5s2Dq6srJBIJEhMTUVhYiIULF9rdb3t7OwwGA1QqFTQaDY4fP47s7Gz09PTY3UZeXh4effRRPPXUU+PWCQ0NhZeXFz+3WCxQKBSiOgqFAhaLhZ+/+uqrcHR0xNq1a+0eS0lJCTw8PPgREBBgdywhhBBC7i/T/ih2PIwx0ftpJpMJmZmZuHr1KkwmE7Kzs6FSqWziTp48CTc3N76lWE5ODuRyObKysuzq98KFCyguLoZWq0VzczMqKyuxb98+XL9+HTKZbML4w4cPo6GhAe++++496929L+xE/vrXv2Lr1q1oa2uz+709ACgoKMD69ev5eV9fHyV3hBBCyCw1YxO78+fPi/ZW9fLygkqlgkqlQlVVFdRqNaKjoxERESGKUyqV/B27yMhInD59GsXFxXYndklJSTZlaWlpdo+7oaEBly5d4mMYlZycjMceewxNTU1jxvn6+qK7u1tU1t3dzR/lnjx5EteuXRPtZzs8PIx/+7d/w2uvvTbuO39SqRRSqdTu8RNCCCHk/jUjH8U2NDTg3LlzSE5OHvN6QEAAVq5ciYKCggnbcnBwwNDQ0JTGMV4Sdi8vvvgizp49C7PZzA8AKC0tRXl5+bhxsbGxNrN49fX1iI2NBXD7o4272/Xz84PJZEJdXd2kx0kIIYSQ2WfaZ+ysVissFotouZPRJT/S09PHjcvNzUVUVBRaW1sRHR3Ny69du4Zbt27xR7F79uxBSkoKv97f34+LFy/y887OTpjNZsjlctFs2Hhu3LiBrq4uXLlyBcDtd/KA2zNudx53CwwMFM1A6nQ6LF++HDk5Ofx+Fi1ahC1btiAxMREVFRVobW3l6/B5enrC09NT1KaTkxN8fX3x9a9/fcJx3+29TfG0VywhhBAyy0x7YldbW4u5c+fC0dERMpkMGo0G27ZtQ0ZGBh54YPwJxYiICMTFxeHf//3fRQv5jiY5jo6OCAgIwHPPPSf6+rS1tRWPP/44Px99/ywjIwO7d++ecLyHDx/GD3/4Q37+L//yLwCAwsJCUT8TuXTpEv7xj3/w80cffRR79+7FT3/6U/zkJz/B1772NRw6dMhmDTtCCCGEkPEIjDE23YMgX56+vj54eHigt7eXZuwIIYSQ+8Bk/nbPyHfsCCGEEELI5FFiRwghhBAyS1BiRwghhBAyS0xrYpeZmQlBECAIApycnKBQKLB06VKUlZVhZGSE1wsODub1XFxcoFarsWvXLlFbTU1NvI4gCHB2dkZkZCT/qnRUc3MzkpKS4OfnB0EQcOjQoXHHt3jxYpuy6upqxMXFwdPTE4Ig8OVMxsIYg8FgmLCfUVVVVQgPD8ecOXOgVqtFH4V88sknyM/Ph1qtxoMPPgg/Pz+kp6fzr3MJIYQQQqZ9xi4hIQFXr17F5cuX8dZbb+Hxxx9Hbm4unnzySXz66ae8XlFREa5evYr33nsPP/jBD2A0GvHWW2/ZtNfe3o6rV6/i/fffx3PPPYesrCzR+nADAwPQaDR4/fXXxxxPTU0N2traRGUVFRW4cOECj1+wYAFeffXVCe/ttddes3uXiFOnTiEtLQ3/+q//infffRfLli3DsmXL8N577wG4vf9sW1sbfvazn6GtrQ3V1dVob2/H9773Pbvav1tUYR2CXzw67kEIIYSQ+8+0L3cilUr5um/+/v7QarWIiYmBTqfD7t27+X6wbm5uvF5+fj42b96M+vp6GAwGUXs+Pj5814e1a9di27ZtaGtrg06nAwAYDAabmDuFhIQgLy8PMTExuHnzJlJTUyGTyRAXFwfg9kLBAMbd6WGU2WzGli1b0Nrairlz5074O2zduhUJCQkwmUwAgJdeegn19fXYvn07duzYAQ8PD9TX14titm/fju985zvo6uqyaw0+QgghhMxu0z5jN5YlS5ZAo9Ggurra5trIyAgOHDiAnp4eSCSScdtgjKG2thZdXV2YP3++3X1HRESgrq4OHR0dOHPmDPR6PXbu3Am5XG53G4ODg1i1ahVef/31MRcrBm4/Xr5z3buWlhbo9XpRnfj4eLS0tIzbT29vLwRBsNm+7E5WqxV9fX2igxBCCCGz04xM7AAgPDxcNCuWn58PV1dXSKVSpKSkQCaT8dm8O82bNw+urq6QSCRITExEYWEhFi5caHe/7e3tMBgMUKlU0Gg0OH78OLKzs9HT02N3G3l5eXj00Ufx1FNPjVsnNDQUXl5e/NxisUChUIjqKBQKWCyWMeNv3bqF/Px8pKWl3XNNm5KSEnh4ePAjICDA7vsghBBCyP1l2h/FjocxJno/zWQyITMzE1evXoXJZEJ2djZUKpVN3MmTJ+Hm5sa3FMvJyYFcLkdWVpZd/V64cAHFxcXQarVobm5GZWUl9u3bh+vXr0Mmk00Yf/jwYTQ0NODdd9+9Z72794WdjE8++QSpqalgjOGNN964Z92CggK+uwZwe5FDSu4IIYSQ2WnGJnbnz58X7a3q5eUFlUoFlUqFqqoqqNVqREdHIyIiQhSnVCr5o8nIyEicPn0axcXFdid2SUlJNmVpaWl2j7uhoQGXLl2yeTyanJyMxx57DE1NTWPG+fr6oru7W1TW3d1t8yh3NKn76KOP0NDQMOEK1FKpFFKp1O7xE0IIIeT+NSMfxTY0NODcuXNITk4e83pAQABWrlyJgoKCCdtycHDA0NDQlMYxXhJ2Ly+++CLOnj0Ls9nMDwAoLS1FeXn5uHGxsbE2s3j19fWIjY3l56NJXUdHB44fPw5PT89Jj48QQgghs9e0z9hZrVZYLBYMDw+ju7sbtbW1KCkpwZNPPon09PRx43JzcxEVFYXW1lZER0fz8mvXruHWrVv8UeyePXuQkpLCr/f39+PixYv8vLOzE2azGXK53K4vS2/cuIGuri6+flx7ezuA2zNudx53CwwMFM1A6nQ6LF++HDk5Ofx+Fi1ahC1btiAxMREVFRVobW3l6/B98sknSElJQVtbG2pqajA8PMzfv5PL5ff8kGQs722Kp71iCSGEkNmGTaOMjAwGgAFgjo6OzNvbm+n1elZWVsaGh4d5vaCgIFZaWmoTHx8fzwwGA2OMscbGRt7WaHtKpZJt2LCB9ff385i7640eGRkZdo25vLx8zPjCwsJxYwCwgwcPisqCgoJsYiorK1lYWBiTSCQsMjKSHT16lF/r7Owcs18ArLGx0a6xM8ZYb28vA8B6e3vtjiGEEELI9JnM326BMca+vDSSTLe+vj54eHigt7eXZuwIIYSQ+8Bk/nbPyHfsCCGEEELI5FFiRwghhBAyS0xrYpeZmQlBECAIApycnKBQKLB06VKUlZVhZGSE1wsODub1XFxcoFarsWvXLlFbTU1NvI4gCHB2dkZkZCT/+GBUc3MzkpKS4OfnB0EQcOjQoXHHt3jxYpuy6upqxMXFwdPTE4Ig8K9ex8IYg8FgmLCfUVVVVQgPD8ecOXOgVqtx7NixKfdNCCGEkK+eaf8qNiEhAeXl5aKvYnNzc7F//34cPnwYjo63h1hUVASj0YjBwUFUVVXBaDTC39/fZt/X9vZ2uLu7Y2hoCEeOHEFWVhZCQ0P5XrEDAwPQaDRYs2YNVqxYYTOempoa+Pn5QavV8rKKigpotVqEhYVhYGAACxYsQGpqKoxG4z3v7bXXXhMtsnwvp06dQlpaGv8ieO/evVi2bBna2toQFRXFx25v3xOJKqzDA1KXz9QGIV+my68kTvcQCCFkxpv2xE4qlfLlQfz9/aHVahETEwOdTofdu3fzbcPc3Nx4vfz8fGzevBn19fU2iZ2Pjw9fHHjt2rXYtm0b2traeGJnMBhsYu4UEhKCvLw8xMTE4ObNm0hNTYVMJkNcXBwAYPXq1QAg2u5sLGazGVu2bEFrayvmzp074e+wdetWJCQkwGQyAQBeeukl1NfXY/v27dixY8ek+iaEEELIV9OMfMduyZIl0Gg0qK6utrk2MjKCAwcOoKen555rtzHGUFtbi66uLsyfP9/uviMiIlBXV4eOjg6cOXMGer0eO3fuhFwut7uNwcFBrFq1Cq+//vqYa9oBtx8vb9y4kZ+3tLRAr9eL6sTHx6OlpcXufgkhhBDy1TYjEzsACA8PF81M5efnw9XVFVKpFCkpKZDJZHw2707z5s2Dq6srJBIJEhMTUVhYiIULF9rdb3t7OwwGA1QqFTQaDY4fP47s7Gz09PTY3UZeXh4effRRPPXUU+PWCQ0NhZeXFz+3WCxQKBSiOgqFgi9CPFVWqxV9fX2igxBCCCGz07Q/ih0PY0z0fprJZEJmZiauXr0Kk8mE7OxsqFQqm7iTJ0/Czc2N7zyRk5MDuVxu916xFy5cQHFxMbRaLZqbm1FZWYl9+/bh+vXrkMlkE8YfPnwYDQ0NePfdd+9Z7+7tw74oJSUl2LRp05fSFyGEEEKm14xN7M6fPy/agsvLywsqlQoqlQpVVVVQq9WIjo5GRESEKE6pVPJ37CIjI3H69GkUFxfbndglJSXZlKWlpdk97oaGBly6dImPYVRycjIee+yxcfef9fX1RXd3t6isu7t73Ee59iooKMD69ev5eV9fHwICAj5Tm4QQQgiZmWbko9iGhgacO3cOycnJY14PCAjAypUrUVBQMGFbDg4OGBoamtI4xkvC7uXFF1/E2bNnYTab+QEApaWlKC8vHzcuNjbWZhavvr4esbGxkx7DnaRSKdzd3UUHIYQQQmanaZ+xs1qtsFgsouVORpf8SE9PHzcuNzcXUVFRaG1tRXR0NC+/du0abt26xR/F7tmzBykpKfx6f38/Ll68yM87OzthNpshl8sRGBg44Xhv3LiBrq4uXLlyBcDtd/KA2zNudx53CwwMFM1A6nQ6LF++HDk5Ofx+Fi1ahC1btiAxMREVFRVobW0VrcM3Ud+T8d6meEryCCGEkNnmi9229t4yMjL4RvaOjo7M29ub6fV6VlZWxoaHh3m9oKAgVlpaahMfHx/PDAYDY4yxxsZG3tZoe0qlkm3YsIH19/fzmLvrjR4ZGRl2jbm8vHzM+MLCwnFjALCDBw+KyoKCgmxiKisrWVhYGJNIJCwyMpIdPXr0M/d9t8lsJEwIIYSQ6TeZv90CY4x9iXkkmWaT2UiYEEIIIdNvMn+7Z+Q7doQQQgghZPIosSOEEEIImSUosSOEEEIImSWmNbHLzMyEIAgQBAFOTk5QKBRYunQpysrKMDIywusFBwfzei4uLlCr1di1a5eoraamJl5HEAQ4OzsjMjJS9FUpADQ3NyMpKQl+fn4QBAGHDh0ad3yLFy+2KauurkZcXBw8PT0hCAJfzuROzz33HEJDQ+Hs7Axvb2889dRT+OCDD+75W/z3f/83kpOT+b2+9tprNnVKSkrwyCOPwM3NDT4+Pli2bBn/MpYQQgghZNqXO0lISEB5eblouZPc3Fzs378fhw8fhqPj7SEWFRXBaDRicHAQVVVVMBqN8Pf3h8FgELXX3t4Od3d3DA0N4ciRI8jKykJoaCh0Oh0AYGBgABqNBmvWrMGKFStsxlNTUwM/Pz9otVpeVlFRAa1Wi7CwMAwMDGDBggVITU2F0Wgc856+/e1v4+mnn0ZgYCBu3LiBjRs3Ii4uDp2dnXBwcBgzZnBwECEhIfj+97+PvLy8Meu8/fbbeOGFF/DII4/g008/xU9+8hPExcXh/fffx4MPPjjxj32HqMI6PCB1mVTMnS6/kjjlWEIIIYR8MaY9sZNKpXwNNn9/f2i1WsTExECn02H37t18P1g3NzdeLz8/H5s3b0Z9fb1NYufj48N3fVi7di22bduGtrY2ntgZDAabmDuFhIQgLy8PMTExuHnzJlJTUyGTyRAXFwcAWL16NQCI9rG927PPPsv/HRwcjJ///OfQaDS4fPkyQkNDx4x55JFH8MgjjwC4vcjxWGpra0Xnu3fvho+PD/76179Oaj9cQgghhMxOM/IduyVLlkCj0aC6utrm2sjICA4cOICenh5IJJJx22CMoba2Fl1dXZg/f77dfUdERKCurg4dHR04c+YM9Ho9du7cCblcPqV7GRgYQHl5OZRKpWgrr+DgYGzcuHFKbY7q7e0FgCmPjRBCCCGzy4xM7AAgPDxcNCuWn58PV1dXSKVSpKSkQCaT8dm8O82bNw+urq6QSCRITExEYWHhpGaz2tvbYTAYoFKpoNFocPz4cWRnZ6Onp2dS4//Vr34FV1dXuLq64q233kJ9fb0oEQ0NDYWXl9ek2rzTyMgI1q1bh+9+97uIiooat57VakVfX5/oIIQQQsjsNO2PYsfDGIMgCPzcZDIhMzMTV69ehclkQnZ2NlQqlU3cyZMn4ebmxrcUy8nJgVwuR1ZWll39XrhwAcXFxdBqtWhubkZlZSX27duH69evQyaT2T3+p59+GkuXLsXVq1fxi1/8Aqmpqfiv//ovzJkzBwBs9oWdrBdeeAHvvfce/vSnP92zXklJCTZt2vSZ+iKEEELI/WHGJnbnz58X7a3q5eUFlUoFlUqFqqoqqNVqREdHIyIiQhSnVCr5O3aRkZE4ffo0iouL7U7skpKSbMrS0tImPX4PDw94eHjga1/7GmJiYiCTyXDw4MEptXW3nJwc1NTUoLm5GfPmzbtn3YKCAqxfv56f9/X1iR4JE0IIIWT2mJGPYhsaGnDu3DkkJyePeT0gIAArV65EQUHBhG05ODhgaGhoSuNoamqaUtzdGGNgjMFqtX7mdnJycnDw4EE0NDSIEt/xSKVSuLu7iw5CCCGEzE7TPmNntVphsVhEy52UlJTgySefRHp6+rhxubm5iIqKQmtrK6Kjo3n5tWvXcOvWLf4ods+ePUhJSeHX+/v7cfHiRX7e2dkJs9kMuVyOwMDACcd748YNdHV14cqVKwDA15Hz9fWFr68vPvzwQ/zhD39AXFwcvL298fe//x2vvPIKnJ2d8cQTT/B2dDodli9fjpycHADAP//5T7z//vv83x9//DHMZjNcXV35I+cXXngBe/fuxR//+Ee4ubnBYrEAuD076OzsPOHY7/TepnhK8gghhJDZhk2jjIwMBoABYI6Ojszb25vp9XpWVlbGhoeHeb2goCBWWlpqEx8fH88MBgNjjLHGxkbe1mh7SqWSbdiwgfX39/OYu+uNHhkZGXaNuby8fMz4wsJCxhhjH3/8MTMYDMzHx4c5OTmxefPmsVWrVrEPPvhA1E5QUBCPYYyxzs7OMdtdtGgRrzPWdQCsvLzcrrEzxlhvby8DwHp7e+2OIYQQQsj0mczfboExxr6cFJLMBH19ffDw8EBvby/N2BFCCCH3gcn87Z6R79gRQgghhJDJo8SOEEIIIWSWoMSOEEIIIWSWmNbELjMzE4IgQBAEODk5QaFQYOnSpSgrK8PIyAivFxwczOu5uLhArVZj165doraampp4HUEQ4OzsjMjISLz55puies3NzUhKSoKfnx8EQcChQ4fGHd/ixYttyqqrqxEXFwdPT08IggCz2WxT57nnnkNoaCicnZ3h7e2Np556Ch988MGEv0dVVRXCw8MxZ84cqNVqHDt2THR948aNCA8Px4MPPgiZTAa9Xo/Tp09P2C4hhBBCvhqmfbmThIQElJeXi5Y7yc3Nxf79+3H48GE4Ot4eYlFREYxGIwYHB1FVVQWj0Qh/f38YDAZRe+3t7XB3d8fQ0BCOHDmCrKwshIaGQqfTAbi9d6tGo8GaNWuwYsUKm/HU1NTAz88PWq2Wl1VUVECr1SIsLAwDAwNYsGABUlNTYTQax7ynb3/723j66acRGBiIGzduYOPGjYiLi0NnZyccHBzGjDl16hTS0tL4Ui979+7FsmXL0NbWxrcMCwsLw/bt2xESEoKhoSGUlpYiLi4OFy9ehLe396R+96jCOjwgdZlUzGRdfiXxC22fEEIIIWLT+lVsZmYmbt68aTNr1tDQAJ1Oh1//+td45plnEBwcjHXr1mHdunW8jqenJzIyMvDLX/4SwO0Zu8cffxw9PT185wkAUKlUeO6552AymWz6FwQBBw8exLJly3jZ+++/j7y8PMTExOCPf/wjwsLCIJPJUFJSArlczutdvnwZSqUS7777Lh5++OF73ufZs2eh0Whw8eJFhIaGjlln5cqVGBgYQE1NDS+LiYnBww8/jB07dowZM/qVzPHjx3niOpHRmIB1lZTYEUIIIfeB+/6r2CVLlkCj0aC6utrm2sjICA4cOICenh5IJJJx22CMoba2Fl1dXZg/f77dfUdERKCurg4dHR04c+YM9Ho9du7cKUrqJmNgYADl5eVQKpWirbyCg4OxceNGft7S0gK9Xi+KjY+PR0tLy5jt/vOf/8Sbb74JDw8PaDSacfu3Wq3o6+sTHYQQQgiZnWZkYgcA4eHhuHz5Mj/Pz8+Hq6srpFIpUlJSIJPJ8Mwzz9jEzZs3D66urpBIJEhMTERhYSEWLlxod7/t7e0wGAxQqVTQaDQ4fvw4srOz0dPTM6nx/+pXv4KrqytcXV3x1ltvob6+XpSIhoaGwsvLi59bLBYoFApRGwqFgu8uMaqmpgaurq6YM2cOSktLUV9fL2rnbiUlJXzfWg8PD9onlhBCCJnFZmxixxiDIAj83GQywWw2o6GhAfPnz0dpaSnfautOJ0+ehNlshtlsxq5du/Dyyy/jjTfesLvfCxcuoLi4GEVFRXjooYdQWVmJxx57DNevX5/U+J9++mm8++67ePvttxEWFobU1FTcunWLXz9x4gTfTmwyHn/8cZjNZpw6dQoJCQlITU3FtWvXxq1fUFCA3t5efvztb3+bdJ+EEEIIuT9M+8cT4zl//rxok3svLy+oVCqoVCpUVVVBrVYjOjoaERERojilUsnfsYuMjMTp06dRXFyMrKwsu/pNSkqyKUtLS5v0+EdnyL72ta8hJiYGMpkMBw8eHLctX19fdHd3i8q6u7vh6+srKnvwwQf57xATE4Ovfe1r+M///E8UFBSM2a5UKoVUKp30+AkhhBBy/5mRM3YNDQ04d+4ckpOTx7weEBCAlStXjpvM3MnBwQFDQ0NTGkdTU9OU4u7GGANjDFarddw6sbGxOHHihKisvr4esbGx92x7ZGTknu0SQggh5Ktj2mfsrFYrLBaLaLmT0SU/0tPTx43Lzc1FVFQUWltbER0dzcuvXbuGW7duwWq14p133sGePXuQkpLCr/f39+PixYv8vLOzE2azGXK5HIGBgROO98aNG+jq6sKVK1cA3H4nD7g94+br64sPP/wQf/jDHxAXFwdvb2/8/e9/xyuvvAJnZ2c88cQTvB2dTofly5fzx7G5ublYtGgRtmzZgsTERFRUVKC1tZWvwzcwMIDi4mJ873vfw9y5c/GPf/wDr7/+Oj7++GN8//vft+enFnlvUzztFUsIIYTMNmwaZWRkMAAMAHN0dGTe3t5Mr9ezsrIyNjw8zOsFBQWx0tJSm/j4+HhmMBgYY4w1NjbytkbbUyqVbMOGDay/v5/H3F1v9MjIyLBrzOXl5WPGFxYWMsYY+/jjj5nBYGA+Pj7MycmJzZs3j61atYp98MEHonaCgoJ4zKjKykoWFhbGJBIJi4yMZEePHuXXhoaG2PLly5mfnx+TSCRs7ty57Hvf+x5755137Br3qN7eXgaA9fb2TiqOEEIIIdNjMn+7p3UdO/Llm8xaOIQQQgiZfvf9OnaEEEIIIWTyKLEjhBBCCJklKLEjhBBCCJklpjWxy8zMhCAIEAQBTk5OUCgUWLp0KcrKyjAyMsLrBQcH83ouLi5Qq9XYtWuXqK2mpiZeRxAEODs7IzIykn9VOqq5uRlJSUnw8/ODIAg2+9TeafHixTZl1dXViIuLg6enJwRBgNlstqnz3HPPITQ0FM7OzvD29sZTTz2FDz74YMLfo6qqCuHh4ZgzZw7UajWOHTvGr33yySfIz8+HWq3Ggw8+CD8/P6Snp/OvcwkhhBBCpn25k4SEBJSXl4uWO8nNzcX+/ftx+PBhODreHmJRURGMRiMGBwdRVVUFo9EIf39/GAwGUXvt7e1wd3fH0NAQjhw5gqysLISGhkKn0wG4vWyIRqPBmjVrsGLFCpvx1NTUwM/PD1qtlpdVVFRAq9UiLCwMAwMDWLBgAVJTU2E0Gse8p29/+9t4+umnERgYiBs3bmDjxo2Ii4tDZ2cnHBwcxow5deoU0tLS+FIve/fuxbJly9DW1oaoqCgMDg6ira0NP/vZz6DRaNDT04Pc3Fx873vfQ2tr66R/96jCOjwgdZl03L1cfiXxc22PEEIIIZMzrV/FZmZm4ubNmzazZg0NDdDpdPj1r3+NZ555BsHBwVi3bh3WrVvH63h6eiIjIwO//OUvAdyesXv88cfR09PDd54AAJVKheeeew4mk8mmf0EQcPDgQSxbtoyXvf/++8jLy0NMTAz++Mc/IiwsDDKZDCUlJZDL5bze5cuXoVQq8e677+Lhhx++532ePXsWGo0GFy9eRGho6Jh1Vq5ciYGBAdTU1PCymJgYPPzww9ixY8eYMX/5y1/wne98Bx999JFda/AB/+/LmoB1lZTYEUIIIfeB+/6r2CVLlkCj0aC6utrm2sjICA4cOICenh5IJJJx22CMoba2Fl1dXZg/f77dfUdERKCurg4dHR04c+YM9Ho9du7cKUrqJmNgYADl5eVQKpUICAjg5cHBwdi4cSM/b2lpgV6vF8XGx8ejpaVl3LZ7e3shCIIokb2b1WpFX1+f6CCEEELI7DQjEzsACA8Px+XLl/l5fn4+XF1dIZVKkZKSAplMhmeeecYmbt68eXB1dYVEIkFiYiIKCwuxcOFCu/ttb2+HwWCASqWCRqPB8ePHkZ2djZ6enkmN/1e/+hVcXV3h6uqKt956C/X19aJENDQ0FF5eXvzcYrFAoVCI2lAoFLBYLGO2f+vWLeTn5yMtLe2e2XtJSQnft9bDw0OUXBJCCCFkdpmxiR1jDIIg8HOTyQSz2YyGhgbMnz8fpaWlUKlUNnEnT56E2WyG2WzGrl278PLLL+ONN96wu98LFy6guLgYRUVFeOihh1BZWYnHHnsM169fn9T4n376abz77rt4++23ERYWhtTUVNy6dYtfP3HiBN9ObLI++eQTpKamgjE24b0VFBSgt7eXH3/729+m1CchhBBCZr5p/3hiPOfPn4dSqeTnXl5eUKlUUKlUqKqqglqtRnR0NCIiIkRxSqWSP5qMjIzE6dOnUVxcjKysLLv6TUpKsilLS0ub9PhHZ8i+9rWvISYmBjKZDAcPHhy3LV9fX3R3d4vKuru74evrKyobTeo++ugjNDQ0TPisXSqVQiqVTnr8hBBCCLn/zMgZu4aGBpw7dw7JycljXg8ICMDKlStRUFAwYVsODg4YGhqa0jiampqmFHc3xhgYY7BarePWiY2NxYkTJ0Rl9fX1iI2N5eejSV1HRweOHz8OT0/Pz2V8hBBCCJkdpn3Gzmq1wmKxiJY7GV3yIz09fdy43NxcREVFobW1FdHR0bz82rVruHXrFqxWK9555x3s2bMHKSkp/Hp/fz8uXrzIzzs7O2E2myGXy+36svTGjRvo6uri68e1t7cDuD3j5uvriw8//BB/+MMfEBcXB29vb/z973/HK6+8AmdnZzzxxBO8HZ1Oh+XLl/PHsbm5uVi0aBG2bNmCxMREVFRUoLW1la/D98knnyAlJQVtbW2oqanB8PAwf/9OLpff80OSsby3KZ72iiWEEEJmGzaNMjIyGAAGgDk6OjJvb2+m1+tZWVkZGx4e5vWCgoJYaWmpTXx8fDwzGAyMMcYaGxt5W6PtKZVKtmHDBtbf389j7q43emRkZNg15vLy8jHjCwsLGWOMffzxx8xgMDAfHx/m5OTE5s2bx1atWsU++OADUTtBQUE8ZlRlZSULCwtjEomERUZGsqNHj/JrnZ2dY/YLgDU2Nto1dsYY6+3tZQBYb2+v3TGEEEIImT6T+ds9revYkS/fZNbCIYQQQsj0u+/XsSOEEEIIIZNHiR0hhBBCyCwxrYldZmYmBEGAIAhwcnKCQqHA0qVLUVZWhpGREV4vODiY13NxcYFarcauXbtEbTU1NfE6giDA2dkZkZGR/OODUc3NzUhKSoKfnx8EQbDZzuxOixcvtimrrq5GXFwcPD09IQgCzGazTZ3nnnsOoaGhcHZ2hre3N5566il88MEHE/4eVVVVCA8Px5w5c6BWq3Hs2LFJ900IIYSQr65p/yo2ISEB5eXloq9ic3NzsX//fhw+fBiOjreHWFRUBKPRiMHBQVRVVcFoNMLf3x8Gg0HUXnt7O9zd3TE0NIQjR44gKysLoaGh0Ol0AG5v8aXRaLBmzRqsWLHCZjw1NTXw8/ODVqvlZRUVFdBqtQgLC8PAwAAWLFiA1NRUGI3GMe/p29/+Np5++mkEBgbixo0b2LhxI+Li4tDZ2QkHB4cxY06dOoW0tDT+RfDevXuxbNkytLW1ISoqio99or7tFVVY97nvFft5oP1mCSGEkKmb9sROKpXyRXj9/f2h1WoRExMDnU6H3bt3823D3NzceL38/Hxs3rwZ9fX1Nomdj48PX6B47dq12LZtG9ra2nhiZzAYbGLuFBISgry8PMTExODmzZtITU2FTCZDXFwcAGD16tUAINru7G7PPvss/3dwcDB+/vOfQ6PR4PLlywgNDR0zZuvWrUhISIDJZAIAvPTSS6ivr8f27duxY8cOu/smhBBCyFfXjHzHbsmSJdBoNKiurra5NjIyggMHDqCnp+eea7cxxlBbW4uuri7Mnz/f7r4jIiJQV1eHjo4OnDlzBnq9Hjt37oRcLp/SvQwMDKC8vBxKpVK0T2twcDA2btzIz1taWqDX60Wx8fHxaGlpmVK/hBBCCPnqmZGJHQCEh4eLZqby8/Ph6uoKqVSKlJQUyGQyPpt3p3nz5sHV1RUSiQSJiYkoLCzEwoUL7e63vb0dBoMBKpUKGo0Gx48fR3Z2Nnp6eiY1/l/96ldwdXWFq6sr3nrrLdTX14sS0dDQUHh5efFzi8UChUIhakOhUPBFiKfKarWir69PdBBCCCFkdpqxiR1jDIIg8HOTyQSz2YyGhgbMnz8fpaWlUKlUNnEnT56E2WyG2WzGrl278PLLL+ONN96wu98LFy6guLgYRUVFeOihh1BZWYnHHnsM169fn9T4n376abz77rt4++23ERYWhtTUVNy6dYtfP3HiBN914otUUlLC96318PAQzRoSQgghZHaZ9nfsxnP+/HkolUp+7uXlBZVKBZVKhaqqKqjVakRHRyMiIkIUp1Qq+Tt2kZGROH36NIqLi5GVlWVXv0lJSTZlaWlpkx7/aCL1ta99DTExMZDJZDh48OC4bfn6+qK7u1tU1t3dzd8rnKqCggKsX7+en/f19VFyRwghhMxSM3LGrqGhAefOnUNycvKY1wMCArBy5UoUFBRM2JaDgwOGhoamNI6mpqYpxd2NMQbGGKxW67h1YmNjceLECVFZfX09YmNjP1PfUqkU7u7uooMQQgghs9O0z9hZrVZYLBbRciejS36kp6ePG5ebm4uoqCi0trYiOjqal1+7dg23bt2C1WrFO++8gz179iAlJYVf7+/vx8WLF/l5Z2cnzGYz5HI5AgMDJxzvjRs30NXVhStXrgC4/U4ecHvGzdfXFx9++CH+8Ic/IC4uDt7e3vj73/+OV155Bc7OznjiiSd4OzqdDsuXL+ePY3Nzc7Fo0SJs2bIFiYmJqKioQGtrq2gdvon6noz3NsVTkkcIIYTMNl/orrUTyMjI4BvZOzo6Mm9vb6bX61lZWRkbHh7m9YKCglhpaalNfHx8PDMYDIwxxhobG3lbo+0plUq2YcMG1t/fz2Purjd6ZGRk2DXm8vLyMeMLCwsZY4x9/PHHzGAwMB8fH+bk5MTmzZvHVq1axT744ANRO0FBQTxmVGVlJQsLC2MSiYRFRkayo0ePTqpve0xmI2FCCCGETL/J/O0WGGPsy0wkyfSazEbChBBCCJl+k/nbPSPfsSOEEEIIIZNHiR0hhBBCyCxBiR0hhBBCyCwxrYldZmYmBEGAIAhwcnKCQqHA0qVLUVZWhpGREV4vODiY13NxcYFarcauXbtEbTU1NfE6giDA2dkZkZGRoq9KAaC5uRlJSUnw8/ODIAg4dOjQuONbvHixTVl1dTXi4uLg6ekJQRBgNptF12/cuIEf/ehH+PrXvw5nZ2cEBgZi7dq16O3tnfD3qKqqQnh4OObMmQO1Wo1jx47xa5988gny8/OhVqvx4IMPws/PD+np6fwLWUIIIYSQaV/uJCEhAeXl5aLlTnJzc7F//34cPnwYjo63h1hUVASj0YjBwUFUVVXBaDTC398fBoNB1F57ezvc3d0xNDSEI0eOICsrC6GhodDpdABu792q0WiwZs0arFixwmY8NTU18PPzg1ar5WUVFRXQarUICwvDwMAAFixYgNTUVBiNRpv4K1eu4MqVK/jFL36BiIgIfPTRR3j++edx5coV7N+/f9zf4dSpU0hLS+NLvezduxfLli1DW1sboqKiMDg4iLa2NvzsZz+DRqNBT08PcnNz8b3vfQ+tra2T/t2jCuvwgNRl0nGEEELI/eTyK4nTPYQv1bR+FZuZmYmbN2/azJo1NDRAp9Ph17/+NZ555hkEBwdj3bp1WLduHa/j6emJjIwM/PKXvwRwe8bu8ccfR09PD995AgBUKhWee+45mEwmm/4FQcDBgwexbNkyXvb+++8jLy8PMTEx+OMf/4iwsDDIZDKUlJRALpfzepcvX4ZSqcS7776Lhx9++J73WVVVhR/84AcYGBjgierdVq5ciYGBAdTU1PCymJgYPPzww9ixY8eYMX/5y1/wne98Bx999JFda/AB/+/LmoB1lZTYEUIImfVmQ2J3338Vu2TJEmg0GlRXV9tcGxkZwYEDB9DT0wOJRDJuG4wx1NbWoqurC/Pnz7e774iICNTV1aGjowNnzpyBXq/Hzp07RUndZI3+h7gzqQsODsbGjRv5eUtLC/R6vSguPj4eLS0t92xXEARRIksIIYSQr64ZmdgBQHh4OC5fvszP8/Pz4erqCqlUipSUFMhkMjzzzDM2cfPmzYOrqyskEgkSExNRWFiIhQsX2t1ve3s7DAYDVCoVNBoNjh8/juzsbPT09EzpPv7xj3/gpZdewrPPPisqDw0NhZeXFz+3WCxQKBSiOgqFAhaLZcx2b926hfz8fKSlpd0ze7darejr6xMdhBBCCJmdpv0du/EwxiAIAj83mUzIzMzE1atXYTKZkJ2dDZVKZRN38uRJuLm58S3FcnJyIJfLkZWVZVe/Fy5cQHFxMbRaLZqbm1FZWYl9+/bh+vXrkMlkk7qHvr4+JCYmIiIiQjQ7B8BmX9jJ+OSTT5CamgrGGN5444171i0pKcGmTZum3BchhBBC7h8zNrE7f/48lEolP/fy8oJKpYJKpUJVVRXUajWio6MREREhilMqlfzRZGRkJE6fPo3i4mK7E7ukpCSbsrS0tEmP/3//93+RkJAANzc3HDx4EE5OTves7+vri+7ublFZd3e3zR6wo0ndRx99hIaGhgmftRcUFGD9+vX8vK+vDwEBAZO8G0IIIYTcD2bko9iGhgacO3cOycnJY14PCAjAypUrUVBQMGFbDg4OGBoamtI4mpqaphTX19eHuLg4SCQSHD58GHPmzJkwJjY21mYWr76+HrGxsfx8NKnr6OjA8ePH4enpOWG7UqkU7u7uooMQQgghs9O0z9hZrVZYLBbRciejS36kp6ePG5ebm4uoqCi0trYiOjqal1+7dg23bt3ij2L37NmDlJQUfr2/vx8XL17k552dnTCbzZDL5XZ9WXrjxg10dXXx9ePa29sB3J5x8/X15Und4OAgfve734nea/P29oaDgwMAQKfTYfny5cjJyeH3s2jRImzZsgWJiYmoqKhAa2srX4fvk08+QUpKCtra2lBTU4Ph4WH+/p1cLr/nhyRjeW9TPCV5hBBCyGzDplFGRgYDwAAwR0dH5u3tzfR6PSsrK2PDw8O8XlBQECstLbWJj4+PZwaDgTHGWGNjI29rtD2lUsk2bNjA+vv7eczd9UaPjIwMu8ZcXl4+ZnxhYeE92wfAOjs7Rfc0GjOqsrKShYWFMYlEwiIjI9nRo0f5tc7OznHbbWxstGvsjDHW29vLALDe3l67YwghhBAyfSbzt3ta17EjX77JrIVDCCGEkOl3369jRwghhBBCJo8SO0IIIYSQWYISO0IIIYSQWWJaE7vMzEwIggBBEODk5ASFQoGlS5eirKwMIyMjvF5wcDCv5+LiArVajV27donaampq4nUEQYCzszMiIyP5V6WjmpubkZSUBD8/PwiCYLNP7Z0WL15sU1ZdXY24uDh4enpCEASYzWbR9Rs3buBHP/oRvv71r8PZ2RmBgYFYu3Ytent7J/w9qqqqEB4ejjlz5kCtVuPYsWOT6psQQgghX23TvtxJQkICysvLRcud5ObmYv/+/Th8+DDfX7WoqAhGoxGDg4OoqqqC0WiEv78/DAaDqL329na4u7tjaGgIR44cQVZWFkJDQ6HT6QAAAwMD0Gg0WLNmDVasWGEznpqaGvj5+UGr1fKyiooKaLVahIWFYWBgAAsWLEBqaiqMRqNN/JUrV3DlyhX84he/QEREBD766CM8//zzuHLlCvbv3z/u73Dq1CmkpaXxpV727t2LZcuWoa2tDVFRUXzs9+p7MqIK6/CA1OUztTGR2bDxMiGEEHI/mXJid/PmTezfvx+XLl2CyWSCXC5HW1sbFAoF/P397W5HKpXy3RX8/f2h1WoRExMDnU6H3bt38/1g3dzceL38/Hxs3rwZ9fX1Nomdj48P33li7dq12LZtG9ra2nhiZzAYbGLuFBISgry8PMTExODmzZtITU2FTCZDXFwcAGD16tUAINrH9k5RUVE4cOAAPw8NDUVxcTF+8IMf4NNPP+WJ6t22bt2KhIQEmEwmAMBLL72E+vp6bN++HTt27LCrb0IIIYR8tU3pUezZs2cRFhaGV199Fb/4xS9w8+ZNALcfFdqzG8RElixZAo1Gg+rqaptrIyMjOHDgAHp6eu65KC9jDLW1tejq6sL8+fPt7jsiIgJ1dXXo6OjAmTNnoNfrsXPnTsjl8indCwD+efKdSV1wcLBo/9iWlhbo9XpRXHx8PFpaWqbcL3B7AejRRZLvXCyZEEIIIbPPlBK79evXIzMzEx0dHaLtsp544gk0Nzd/LgMLDw8XzUzl5+fD1dUVUqkUKSkpkMlkfDbvTvPmzYOrqyskEgkSExNRWFiIhQsX2t1ve3s7DAYDVCoVNBoNjh8/juzsbPT09EzpPv7xj3/gpZdewrPPPisqDw0NhZeXFz+3WCxQKBSiOgqFgu8uMVUlJSXw8PDgB+0TSwghhMxeU3oU+5e//AU7d+60Kff39//MicgoxhgEQeDnJpMJmZmZuHr1KkwmE7Kzs6FSqWziTp48CTc3N76lWE5ODuRyObKysuzq98KFCyguLoZWq0VzczMqKyuxb98+XL9+HTKZbFL30NfXh8TERERERIhm5wDY7Av7RSkoKMD69etFY6LkjhBCCJmdppTYSaXSMR/pXbhwAd7e3p95UABw/vx5KJVKfu7l5QWVSgWVSoWqqiqo1WpER0cjIiJCFKdUKvk7dpGRkTh9+jSKi4vtTuySkpJsytLS0iY9/v/93/9FQkIC3NzccPDgQTg5Od2zvq+vL7q7u0Vl3d3d/L3CqZJKpZBKpZ+pDUIIIYTcH6b0KPZ73/seioqK8MknnwAABEFAV1cX8vPzkZyc/JkH1dDQgHPnzo3bVkBAAFauXGnX+3wODg4YGhqa0jiampqmFNfX14e4uDhIJBIcPnxY9Lh6PLGxsTazePX19YiNjZ3SGAghhBDy1TOlGbstW7YgJSUFPj4+GBoawqJFi2CxWBAbG4vi4uJJtWW1WmGxWETLnYwu+ZGenj5uXG5uLqKiotDa2oro6Ghefu3aNdy6dYs/it2zZw9SUlL49f7+fly8eJGfd3Z2wmw2Qy6XIzAwcMLx3rhxA11dXbhy5QqA2+/kAbdn3Hx9fXlSNzg4iN/97neiDxa8vb3h4OAAANDpdFi+fDlycnL4/SxatAhbtmxBYmIiKioq0NraKlqHb6K+J+O9TfG0VywhhBAy27DP4OTJk+z1119nr776Kquvr590fEZGBgPAADBHR0fm7e3N9Ho9KysrY8PDw7xeUFAQKy0ttYmPj49nBoOBMcZYY2Mjb2u0PaVSyTZs2MD6+/t5zN31Ro+MjAy7xlxeXj5mfGFh4T3bB8A6OztF9zQaM6qyspKFhYUxiUTCIiMj2dGjRyfVtz16e3sZANbb22t3DCGEEEKmz2T+dguMMfblpJBkJujr64OHhwdfgoUQQgghM9tk/nbb/Sh227Ztdg9g7dq1dtclhBBCCCGfD7tn7O78QvWeDQoCPvzww880KPLFoRk7Qggh5P7yhczYdXZ2fuaBEUIIIYSQL86UljsZ9c9//hPt7e349NNPpxSfmZkJQRAgCAKcnJygUCiwdOlSlJWVYWRkhNcLDg7m9VxcXKBWq7Fr1y5RW01NTbyOIAhwdnZGZGSk6KtSAGhubkZSUhL8/PwgCAIOHTo07vgWL15sU1ZdXY24uDh4enpCEASYzWabOm+++SYWL14Md3d3CILAt1y7l6tXr2LVqlUICwvDAw88gHXr1o1Zr6qqCuHh4ZgzZw7UajWOHTs2YduEEEII+WqY0nIng4OD+NGPfoTf/OY3AG4vTBwSEoIf/ehH8Pf3x4svvmh3WwkJCSgvLxctd5Kbm4v9+/fj8OHDfH/VoqIiGI1GDA4OoqqqCkajEf7+/jAYDKL22tvb4e7ujqGhIRw5cgRZWVkIDQ2FTqcDAAwMDECj0WDNmjVYsWKFzXhqamrg5+cHrVbLyyoqKqDVahEWFoaBgQEsWLAAqampMBqN4/4+CQkJSEhIsHvvXKvVCm9vb/z0pz9FaWnpmHVOnTqFtLQ0vhzM3r17sWzZMrS1tSEqKsqufkZFFdbhAanLpGI+q8uvJH6p/RFCCCFfNVOasSsoKMCZM2fQ1NQkWnxXr9fjD3/4w6Takkql8PX1hb+/P7RaLX7yk5/gj3/8I9566y3s3r2b13Nzc4Ovry9CQkKQn58PuVyO+vp6m/Z8fHzg6+sLpVKJtWvXQqlUoq2tjV83GAz4+c9/juXLl485npCQEBQUFKCwsBA3b95EamoqGhsb+b6uq1evxr//+79Dr9ePe0/r1q3Diy++iJiYGLt/h+DgYGzduhXp6enw8PAYs87WrVuRkJAAk8mEb3zjG3jppZeg1Wqxfft2u/shhBBCyOw1pcTu0KFD2L59OxYsWCDazzUyMhKXLl36zINasmQJNBoNqqurba6NjIzgwIED6OnpgUQiGbcNxhhqa2vR1dWF+fPn2913REQE6urq0NHRgTNnzkCv12Pnzp2Qy+VTupfxLF68GJmZmZOKaWlpsUko4+Pj0dLSMm6M1WrliyTfuVgyIYQQQmafKSV2169fh4+Pj035wMCAKNH7LMLDw3H58mV+np+fD1dXV0ilUqSkpEAmk+GZZ56xiZs3bx5cXV0hkUiQmJiIwsJCLFy40O5+29vbYTAYoFKpoNFocPz4cWRnZ6Onp+fzuC0uMDAQc+fOnVSMxWKBQqEQlSkUClgslnFjSkpK4OHhwY+AgIApjZcQQgghM9+UErvo6GgcPXqUn48mc7t27frc9jZljImSRJPJBLPZjIaGBsyfPx+lpaVQqVQ2cSdPnoTZbIbZbMauXbvw8ssv44033rC73wsXLqC4uBhFRUV46KGHUFlZicceewzXr1//XO5r1G9/+1uUlJR8rm2OpaCgAL29vfz429/+9oX3SQghhJDpMaWPJ15++WUYDAa8//77+PTTT7F161a8//77OHXqFN5+++3PZWDnz58XrZ3n5eUFlUoFlUqFqqoqqNVqREdHIyIiQhSnVCrx0EMPAbj9aPj06dMoLi5GVlaWXf0mJSXZlKWlpU39Rj5Hvr6+6O7uFpV1d3ffc59YqVQKqVT6RQ+NEEIIITPAlGbsFixYALPZjE8//RRqtRr/9//+X/j4+KClpQXf/va3P/OgGhoacO7cOSQnJ495PSAgACtXrrTri1MHBwcMDQ1NaRxNTU1TivuixMbG4sSJE6Ky+vr6z22WlBBCCCH3tynN2AFAaGgofv3rX3/mAVitVlgsFtFyJ6PLeaSnp48bl5ubi6ioKLS2tiI6OpqXX7t2Dbdu3YLVasU777yDPXv2ICUlhV/v7+/HxYsX+XlnZyfMZjPkcjkCAwMnHO+NGzfQ1dWFK1euALj9Th5wezZtdObMYrHAYrHwfs6dOwc3NzcEBgbyjzDS09Ph7+8vehw7uiZef38/rl+/DrPZDIlEwmclc3NzsWjRImzZsgWJiYmoqKhAa2urzVp99nhvUzztPEEIIYTMNsxOvb29dh/2ysjIYAAYAObo6Mi8vb2ZXq9nZWVlbHh4mNcLCgpipaWlNvHx8fHMYDAwxhhrbGzkbY22p1Qq2YYNG1h/fz+Pubve6JGRkWHXmMvLy8eMLyws5HUKCwvHrFNeXs7rLFq0yKbPsWKCgoJEdSorK1lYWBiTSCQsMjKSHT161K5xj+rt7WUAJvXfiRBCCCHTZzJ/u+3eK/aBBx6Y8ItX9v9/8DA8PGx/Zkm+VLRXLCGEEHJ/+UL2im1sbPzMAyOEEEIIIV8cuxO7RYsWfZHjIIQQQgghn5HdX8WePXvW7sNemZmZEAQBgiDAyckJCoUCS5cuRVlZGUZGRni94OBgXs/FxQVqtRq7du0StdXU1MTrCIIAZ2dnREZG2nxY0NzcjKSkJPj5+UEQBBw6dGjc8S1evNimrLq6GnFxcfD09IQgCPyDhzu9+eabWLx4Mdzd3SEIAm7evGnX79HU1AStVgupVAqVSiXaUm3Uxx9/jB/84Afw9PSEs7Mz1Go1Wltb7WqfEEIIIbOb3TN2Dz/8MARBwESv5E32HbuEhASUl5eLvorNzc3F/v37cfjwYTg63h5iUVERjEYjBgcHUVVVBaPRCH9/fxgMBlF77e3tcHd3x9DQEI4cOYKsrCyEhoZCp9MBuL07hkajwZo1a7BixQqb8dTU1MDPzw9arZaXVVRUQKvVIiwsDAMDA1iwYAFSU1NhNBrHvKfBwUEkJCQgISHBriVZgNtf5yYmJuL555/H73//e5w4cQLPPPMM5s6di/j4eABAT08Pvvvd7+Lxxx/HW2+9BW9vb3R0dEAmk9nVx52iCuvwgNRl0nHT7fIridM9BEIIIWTGsjux6+zs/EIGIJVK+TIh/v7+0Gq1iImJgU6nw+7du/m2YW5ubrxefn4+Nm/ejPr6epvEzsfHhy9QvHbtWmzbtg1tbW08sTMYDDYxdwoJCUFeXh5iYmJw8+ZNpKamQiaTIS4uDgCwevVqABBtd3a3devWAZjcOng7duyAUqnEli1bAADf+MY38Kc//QmlpaU8sXv11VcREBCA8vJyHnfnIs6EEEII+Wqz+1FsUFCQzTEwMIDz58/jzJkz/JjMo9jxLFmyBBqNBtXV1TbXRkZGcODAAfT09EAikYzbBmMMtbW16Orqwvz58+3uOyIiAnV1dejo6MCZM2eg1+uxc+dOvv7c52Xx4sXIzMzk5y0tLdDr9aI68fHxaGlp4eeHDx9GdHQ0vv/978PHxwff+ta3Ppe1BAkhhBAyO0xpgeIPP/wQy5cvx7lz50SPZ0eXQ/k8ljsJDw8XJYn5+fn46U9/CqvVik8//RRyuZzP5t1p3rx5AG4vfDwyMoKioiIsXLjQ7n7b29uxbt06PPLII9BoNDh+/DjMZjOKi4un9MhzPIGBgZg7dy4/t1gsUCgUojoKhQJ9fX0YGhqCs7MzPvzwQ7zxxhtYv349fvKTn+Avf/kL1q5dC4lEgoyMjDH7sVqtsFqt/Lyvr+9zuwdCCCGEzCxTSuxyc3OhVCpx4sQJKJVKnD59Gjdu3MC//du/4Re/+MXnMrDRNfFGmUwmZGZm4urVqzCZTMjOzoZKpbKJO3nyJNzc3PjOEzk5OZDL5XbvFXvhwgUUFxdDq9WiubkZlZWV2LdvH65fv/65Jna//e1vJx0zMjKC6OhovPzyywCAb33rW3jvvfewY8eOcRO7kpISbNq06TONlRBCCCH3hykldi0tLWhoaICXlxceeOABODg4YMGCBSgpKcHatWvx7rvvfuaBnT9/XvT+mJeXF1QqFVQqFaqqqqBWqxEdHc232xqlVCr5O3aRkZE4ffo0iouL7U7skpKSbMrS0tKmfiN28vX1RXd3t6isu7sb7u7ucHZ2BgDMnTvX5n6/8Y1v4MCBA+O2W1BQgPXr1/Pzvr4+BAQEfI4jJ4QQQshMYfc7dncaHh6Gm5sbgNsJ1+i+qUFBQXzv1M+ioaEB586dQ3Jy8pjXAwICsHLlSru+OHVwcMDQ0NCUxjGZjx8+q9jYWJw4cUJUVl9fj9jYWH7+3e9+1+b3vXDhAoKCgsZtVyqVwt3dXXQQQgghZHaa0oxdVFQUzpw5A6VSifnz52Pz5s2QSCR48803ERISMqm2rFYrLBaLaLmTkpISPPnkk0hPTx83Ljc3F1FRUWhtbUV0dDQvv3btGm7dusUfxe7ZswcpKSn8en9/Py5evMjPOzs7YTabIZfLERgYOOF4b9y4ga6uLp7MjiZavr6+/Ktdi8UCi8XC+zl37hzc3NwQGBjIP8JIT0+Hv78/SkpKAADPP/88tm/fjh//+MdYs2YNGhoaUFlZiaNHj/K+8/Ly8Oijj+Lll19Gamoq3nnnHbz55ps2a/XZ471N8ZTkEUIIIbPNVDajra2tZQcOHGCMMdbR0cG+/vWvM0EQmJeXFztx4oTd7WRkZPDN7h0dHZm3tzfT6/WsrKyMDQ8P83pBQUGstLTUJj4+Pp4ZDAbGGGONjY28rdH2lEol27BhA+vv7+cxd9cbPTIyMuwac3l5+ZjxhYWFvE5hYeGYdcrLy3mdRYsW2fTZ2NjIHn74YSaRSFhISIio/qgjR46wqKgoJpVKWXh4OHvzzTftGveoyWwkTAghhJDpN5m/3QJjE6w4bKcbN25AJpOJPnggM89kNhImhBBCyPSbzN/uKT2KHcvnvc4bIYQQQgiZnCl9PEEIIYQQQmYeSuwIIYQQQmaJaU3sMjMzIQgCBEGAk5MTFAoFli5dirKyMoyMjPB6wcHBvJ6LiwvUajV27dolaqupqYnXEQQBzs7OiIyMtPlitLm5GUlJSfDz84MgCDh06NC441u8eLFNWXV1NeLi4uDp6QlBEGA2m23qvPnmm1i8eDHc3d0hCAJu3rxp1+/R1NQErVYLqVQKlUqF3bt3j1v3lVdegSAIfF9aQgghhJBpn7FLSEjA1atXcfnyZbz11lt4/PHHkZubiyeffBKffvopr1dUVISrV6/ivffeww9+8AMYjUa89dZbNu21t7fj6tWreP/99/Hcc88hKytLtD7cwMAANBoNXn/99THHU1NTg7a2NlFZRUUFLly4wOMXLFiAV199ddx7GhwcREJCAn7yk5/Y/Tt0dnYiMTERjz/+OMxmM9atW4dnnnkGdXV1NnX/8pe/YOfOnfjmN79pd/t3iyqsQ/CLR8c9CCGEEHL/+dw+npgqqVTK13/z9/eHVqtFTEwMdDoddu/ezfeDdXNz4/Xy8/OxefNm1NfXw2AwiNrz8fHhO0+sXbsW27ZtQ1tbG3Q6HQDAYDDYxNwpJCQEeXl5iImJwc2bN5GamgqZTIa4uDgAwOrVqwEAly9fHreN0Vm0ySxwvGPHDiiVSmzZsgXA7R0l/vSnP6G0tBTx8fG8Xn9/P55++mn8+te/xs9//nO72yeEEELI7DftM3ZjWbJkCTQaDaqrq22ujYyM4MCBA+jp6YFEIhm3DcYYamtr0dXVhfnz59vdd0REBOrq6tDR0YEzZ85Ar9dj586dn/tXv4sXL0ZmZiY/b2lpgV6vF9WJj49HS0uLqOyFF15AYmKiTV1CCCGEkGmfsRtPeHg4zp49y8/z8/Px05/+FFarFZ9++inkcjmfzbvTvHnzANze0WJkZARFRUVYuHCh3f22t7dj3bp1eOSRR6DRaHD8+HGYzWYUFxdDJpN99hv7/wUGBmLu3Ln83GKxQKFQiOooFAr09fVhaGgIzs7OqKioQFtbG/7yl7/Y3Y/VaoXVauXnfX19n33whBBCCJmRZmxixxgTLXZsMpmQmZmJq1evwmQyITs7GyqVyibu5MmTcHNz41uK5eTkQC6XIysry65+L1y4gOLiYmi1WjQ3N6OyshL79u3D9evXP9fE7re//e2k6v/tb39Dbm4u6uvrMWfOHLvjSkpKsGnTpskOjxBCCCH3oRmb2J0/fx5KpZKfe3l5QaVSQaVSoaqqCmq1GtHR0YiIiBDFKZVK/o5dZGQkTp8+jeLiYrsTu6SkJJuytLS0qd+InXx9fdHd3S0q6+7uhru7O5ydnfHXv/4V165dg1ar5deHh4fR3NyM7du3w2q1wsHBwabdgoICrF+/np/39fUhICDgi7sRQgghhEybGZnYNTQ04Ny5c8jLyxvzekBAAFauXImCggL88Y9/vGdbDg4OGBoamtI4JvPxw2cVGxuLY8eOicrq6+sRGxsLANDpdDh37pzo+g9/+EOEh4cjPz9/zKQOuP1xilQq/WIGTQghhJAZZdoTO6vVCovFguHhYXR3d6O2thYlJSV48sknkZ6ePm5cbm4uoqKi0NraiujoaF5+7do13Lp1iz+K3bNnD1JSUvj1/v5+XLx4kZ93dnbCbDZDLpcjMDBwwvHeuHEDXV1duHLlCoDb7+QBt2fcRr/atVgssFgsvJ9z587Bzc0NgYGB/COM9PR0+Pv7o6SkBADw/PPPY/v27fjxj3+MNWvWoKGhAZWVlTh69PbSI25uboiKihKN5cEHH4Snp6dNuT3e2xRPe8USQgghsw2bRhkZGQwAA8AcHR2Zt7c30+v1rKysjA0PD/N6QUFBrLS01CY+Pj6eGQwGxhhjjY2NvK3R9pRKJduwYQPr7+/nMXfXGz0yMjLsGnN5efmY8YWFhbxOYWHhmHXKy8t5nUWLFtn02djYyB5++GEmkUhYSEiIqP5YFi1axHJzc+0a96je3l4GgPX29k4qjhBCCCHTYzJ/uwXGGPsyE0kyvfr6+uDh4YHe3l6asSOEEELuA5P52z0j17EjhBBCCCGTR4kdIYQQQsgsQYkdIYQQQsgsMa2JXWZmJgRBgCAIcHJygkKhwNKlS1FWVoaRkRFeLzg4mNdzcXGBWq3Grl27RG01NTXxOoIgwNnZGZGRkXjzzTdF9Zqbm5GUlAQ/Pz8IgoBDhw6NO77FixfblFVXVyMuLg6enp4QBAFms9mmzptvvonFixfD3d0dgiDg5s2bdv0eTU1N0Gq1kEqlUKlU2L1795THTgghhJCvnmlf7iQhIQHl5eWi5U5yc3Oxf/9+HD58GI6Ot4dYVFQEo9GIwcFBVFVVwWg0wt/fHwaDQdRee3s73N3dMTQ0hCNHjiArKwuhoaHQ6XQAgIGBAWg0GqxZswYrVqywGU9NTQ38/PxECwFXVFRAq9UiLCwMAwMDWLBgAVJTU2E0Gse8p8HBQSQkJCAhIQEFBQV2/Q6dnZ1ITEzE888/j9///vc4ceIEnnnmGcydOxfx8fF2jX0yogrr8IDU5TO1QT5fl19JnO4hEEIIuc9Ne2InlUr5+m/+/v7QarWIiYmBTqfD7t27+X6wbm5uvF5+fj42b96M+vp6m8TOx8eH7zyxdu1abNu2DW1tbTyxMxgMNjF3CgkJQV5eHmJiYnDz5k2kpqZCJpMhLi4OALB69WoAwOXLl8dtY926dQAmt8Dxjh07oFQqsWXLFgDAN77xDfzpT39CaWkpT+wmGjshhBBCvtpm5Dt2S5YsgUajQXV1tc21kZERHDhwAD09PZBIJOO2wRhDbW0turq6MH/+fLv7joiIQF1dHTo6OnDmzBno9Xrs3LmTLyz8eVm8eDEyMzP5eUtLC/R6vahOfHw8WlpaPlM/VqsVfX19ooMQQgghs9OMTOwAIDw8XDQrlp+fD1dXV0ilUqSkpEAmk/HZvDvNmzcPrq6ukEgkSExMRGFhIRYuXGh3v+3t7TAYDFCpVNBoNDh+/Diys7PR09PzedwWFxgYiLlz5/Jzi8UChUIhqqNQKNDX1zflLdEAoKSkBB4eHvygfWIJIYSQ2WvaH8WOhzEGQRD4uclkQmZmJq5evQqTyYTs7GyoVCqbuJMnT8LNzY1vKZaTkwO5XI6srCy7+r1w4QKKi4uh1WrR3NyMyspK7Nu3D9evX4dMJvvc7u+3v/3t59bWvRQUFGD9+vX8vK+vj5I7QgghZJaasYnd+fPnoVQq+bmXlxdUKhVUKhWqqqqgVqsRHR2NiIgIUZxSqeTv2EVGRuL06dMoLi62O7FLSkqyKUtLS5v6jdjJ19cX3d3dorLu7m64u7vD2dl5yu1KpVJIpdLPOjxCCCGE3Adm5KPYhoYGnDt3DsnJyWNeDwgIwMqVK+364tTBwWHKjzIn8/HDZxUbG4sTJ06Iyurr6xEbG/uljYEQQggh97dpn7GzWq2wWCyi5U5KSkrw5JNPIj09fdy43NxcREVFobW1FdHR0bz82rVruHXrFn8Uu2fPHqSkpPDr/f39uHjxIj/v7OyE2WyGXC5HYGDghOO9ceMGurq6cOXKFQC338kDbs+4jX61a7FYYLFYeD/nzp2Dm5sbAgMD+UcY6enp8Pf3R0lJCQDg+eefx/bt2/HjH/8Ya9asQUNDAyorK3H06NHPbex3em9TPO0VSwghhMw2bBplZGQwAAwAc3R0ZN7e3kyv17OysjI2PDzM6wUFBbHS0lKb+Pj4eGYwGBhjjDU2NvK2RttTKpVsw4YNrL+/n8fcXW/0yMjIsGvM5eXlY8YXFhbyOoWFhWPWKS8v53UWLVpk02djYyN7+OGHmUQiYSEhIaL6n8fYGWOst7eXAWC9vb12xxBCCCFk+kzmb7fAGGNfUg5JZoC+vj54eHigt7eXZuwIIYSQ+8Bk/nbPyHfsCCGEEELI5FFiRwghhBAyS1BiRwghhBAyS0xrYpeZmQlBECAIApycnKBQKLB06VKUlZVhZGSE1wsODub1XFxcoFarsWvXLlFbTU1NvI4gCHB2dkZkZCTefPNNUb3m5mYkJSXBz88PgiDg0KFD445v8eLFNmXV1dWIi4uDp6cnBEGA2Wy2qXPr1i288MIL8PT0hKurK5KTk23WqBtLVVUVwsPDMWfOHKjVahw7dmzSfRNCCCHkq2valztJSEhAeXm5aLmT3Nxc7N+/H4cPH4aj4+0hFhUVwWg0YnBwEFVVVTAajfD394fBYBC1197eDnd3dwwNDeHIkSPIyspCaGgodDodAGBgYAAajQZr1qzBihUrbMZTU1MDPz8/aLVaXlZRUQGtVouwsDAMDAxgwYIFSE1NhdFoHPOe8vLycPToUVRVVcHDwwM5OTlYsWIF/uu//mvc3+HUqVNIS0vjS73s3bsXy5YtQ1tbG6KiovjYJ+rbXlGFdXhA6vKZ2viyXX4lcbqHQAghhMxo057YSaVSvv6bv78/tFotYmJioNPpsHv3br4frJubG6+Xn5+PzZs3o76+3iax8/Hx4TtPrF27Ftu2bUNbWxtP7AwGg03MnUJCQpCXl4eYmBjcvHkTqampkMlkiIuLAwCsXr0aAET72N6pt7cX//mf/4m9e/diyZIlAIDy8nJ84xvfwJ///GfExMSMGbd161YkJCTAZDIBAF566SXU19dj+/bt2LFjh119E0IIIeSrbUa+Y7dkyRJoNBpUV1fbXBsZGcGBAwfQ09MDiUQybhuMMdTW1qKrqwvz58+3u++IiAjU1dWho6MDZ86cgV6vx86dO/nCwhP561//ik8++QR6vZ6XhYeHIzAwEC0tLbwsODgYGzdu5OctLS2iGACIj48XxUyF1WpFX1+f6CCEEELI7DQjEzvgdjJ058xUfn4+XF1dIZVKkZKSAplMxmfz7jRv3jy4urpCIpEgMTERhYWFWLhwod39tre3w2AwQKVSQaPR4Pjx48jOzkZPT49d8RaLBRKJhM8ajlIoFLBYLPw8NDQUXl5eojiFQnHPmKkoKSmBh4cHPwICAj5Te4QQQgiZuab9Uex4GGMQBIGfm0wmZGZm4urVqzCZTMjOzoZKpbKJO3nyJNzc3PiWYjk5OZDL5cjKyrKr3wsXLqC4uBharRbNzc2orKzEvn37cP36dchkss/t/u7eF/aLUlBQgPXr1/Pzvr4+Su4IIYSQWWrGJnbnz5+HUqnk515eXlCpVFCpVKiqqoJarUZ0dDQiIiJEcUqlks+WRUZG4vTp0yguLrY7sUtKSrIpS0tLs3vcvr6++Oc//4mbN2+KZu26u7v5O4Ljxd395exEMfaQSqWQSqWfqQ1CCCGE3B9m5KPYhoYGnDt3DsnJyWNeDwgIwMqVK1FQUDBhWw4ODhgaGprSOJqamiYd8+1vfxtOTk6iGbn29nZ0dXUhNjZ23LjY2FibWbz6+vp7xhBCCCGE3GnaZ+ysVissFotouZPRJT/S09PHjcvNzUVUVBRaW1sRHR3Ny69du4Zbt27xR7F79uxBSkoKv97f34+LFy/y887OTpjNZsjlcgQGBk443hs3bqCrqwtXrlwBcDtpA27PuPn6+sLDwwP/+q//ivXr10Mul8Pd3R0/+tGPEBsbK/oiVqfTYfny5cjJyeH3s2jRImzZsgWJiYmoqKhAa2uraB2+ifqejPc2xdNesYQQQshsw6ZRRkYGA8AAMEdHR+bt7c30ej0rKytjw8PDvF5QUBArLS21iY+Pj2cGg4ExxlhjYyNva7Q9pVLJNmzYwPr7+3nM3fVGj4yMDLvGXF5ePmZ8YWEhrzM0NMSys7OZTCZjLi4ubPny5ezq1auidoKCgkQxjDFWWVnJwsLCmEQiYZGRkezo0aOT7nsivb29DADr7e21O4YQQggh02cyf7sFxhj7MhNJMr36+vrg4eGB3t5emrEjhBBC7gOT+ds9I9+xI4QQQgghk0eJHSGEEELILDGtiV1mZiYEQYAgCHBycoJCocDSpUtRVlaGkZERXi84OJjXc3FxgVqtxq5du0RtNTU18TqCIMDZ2RmRkZGijw8AoLm5GUlJSfDz84MgCDh06NC441u8eLFNGWMM//7v/465c+fC2dkZer0eHR0dojptbW1YunQpHnroIXh6euLZZ59Ff3//hL9HVVUVwsPDMWfOHKjVahw7dkx0vbq6GnFxcfD09IQgCDCbzRO2SQghhJCvjmn/KjYhIQHl5eWir2Jzc3Oxf/9+HD58GI6Ot4dYVFQEo9GIwcFBVFVVwWg0wt/f32bf1/b2dri7u2NoaAhHjhxBVlYWQkND+V6xAwMD0Gg0WLNmDVasWGEznpqaGvj5+UGr1fKyiooKaLVahIWFYfPmzdi2bRt+85vfQKlU4mc/+xni4+Px/vvvY86cObhy5Qr0ej1WrlyJ7du3o6+vD+vWrUNmZib2798/7u9w6tQppKWl8S+C9+7di2XLlqGtrQ1RUVF87AsWLEBqaiqMRuNn+t2jCuvwgNTlM7VBCCFkZrj8SuJ0D4HMENOe2EmlUr5Uh7+/P7RaLWJiYqDT6bB7926+bZibmxuvl5+fj82bN6O+vt4msfPx8eELA69duxbbtm1DW1sbT+wMBoNNzJ1CQkKQl5eHmJgY3Lx5E6mpqZDJZIiLiwNjDK+99hp++tOf4qmnngIA/Pa3v4VCocChQ4fwL//yL6ipqYGTkxNef/11PPDA7QnRHTt24Jvf/CYuXrw45m4ZALB161YkJCTAZDIBAF566SXU19dj+/bt2LFjBwBg9erVACDaao0QQgghZNSMfMduyZIl0Gg0qK6utrk2MjKCAwcOoKenBxKJZNw2GGOora1FV1cX5s+fb3ffERERqKurQ0dHB86cOQO9Xo+dO3dCLpejs7MTFosFer2e1/fw8MD8+fPR0tIC4Pa6fBKJhCd1AODs7AwA+NOf/sTLgoODsXHjRn7e0tIiahcA4uPjebuEEEIIIROZkYkdAISHh4tmpvLz8+Hq6gqpVIqUlBTIZDI+m3enefPmwdXVFRKJBImJiSgsLMTChQvt7re9vR0GgwEqlQoajQbHjx9HdnY2enp6YLFYAAAKhUIUo1Ao+LUlS5bAYrHg//yf/4N//vOf6OnpwYsvvggAuHr1Ko8JDQ2Fl5cXP7dYLPdsd6qsViv6+vpEByGEEEJmpxmb2DHGIAgCPzeZTDCbzWhoaMD8+fNRWlo65mPNkydPwmw2w2w2Y9euXXj55Zfxxhtv2N3vhQsXUFxcjKKiIjz00EOorKzEY489huvXr9sVHxkZid/85jfYsmULXFxc4OvrC6VSCYVCIZrFO3HiBN914otUUlICDw8PfgQEBHzhfRJCCCFkekz7O3bjOX/+PJRKJT/38vKCSqWCSqVCVVUV1Go1oqOjERERIYpTKpX8HbvIyEicPn0axcXFyMrKsqvfpKQkm7K0tDQA4B9ydHd3Y+7cufx6d3c3Hn74YX6+atUqrFq1Ct3d3XjwwQchCAJ++ctfIiQkZNx+fX190d3dLSrr7u6e9FZhdysoKMD69ev5eV9fHyV3hBBCyCw1I2fsGhoacO7cOSQnJ495PSAgACtXrkRBQcGEbTk4OGBoaGhK42hqahKdK5VK+Pr64sSJE/9fe/ceFsV1/w/8PYAsEC6yIiyLIAsrWi4uv5WIpN4iq0CVaJRKbX4RtKLB+AhSEUkNGL9Q8rWJ8sWaoDEQ9WlEURMviRjkEsw3BIMGNEVXTDGm1V204SIX14Q9vz/8MXVcQFBwkXxezzNPOzPnnDlzgvJxZs7n8Meam5tRUVGBoKAgg/pOTk6wtrbG/v37YWFhgZkzZ3Z7raCgIEG7AFBYWNhlu30hEolga2sr2AghhBAyNBn9iZ1Op4NGoxGkO+lM+bF48eJu68XFxcHX1xeVlZUICAjgj9fX1+POnTvQ6XQ4c+YM9u7di4iICP58S0sLrly5wu/X1dWhqqoKYrEYbm5uPfaV4zjEx8cjLS0NY8aM4dOdSKVSzJs3jy/317/+Fc899xysra1RWFiIxMREvPnmm/yTRAAIDg7Giy++yL+OjYuLw7Rp0/D2229j9uzZyMvLQ2VlpSAP348//ohr167h+vXrAO59Dwjce9rX1yd7374RQkEeIYQQMtQM6Kq1DxEVFcUvZG9mZsZGjhzJVCoVy8nJYR0dHXy50aNHs61btxrUDwkJYWFhYYwxxkpKSvi2OtuTyWRs7dq1rKWlha/zYLnOLSoqqld91uv17PXXX2dOTk5MJBKx4OBgplarBWVefvllJhaLmbm5ORs/fjzbs2ePQTujR49mqampgmMHDhxgXl5ezNzcnPn4+LBPPvlEcD43N7fLvj/YTk/6spAwIYQQQoyvL7+7OcYYe+LRJDGaviwkTAghhBDj68vv7kH5jR0hhBBCCOk7CuwIIYQQQoYICuwIIYQQQoYIowZ20dHR4DgOHMdh2LBhcHJywsyZM5GTkwO9Xs+Xc3d358tZWVnBz88Pu3btErRVWlrKl+E4DpaWlvDx8RHMKgWAsrIyhIeHQyqVguM4fPzxx932b/r06QbHGGNISUmBs7MzLC0toVKpUFtbKyhz+fJlzJ07Fw4ODrC1tcXkyZNRUlLy0PHIz8/HuHHjYGFhAT8/P3z66aeC8xs3bsS4cePwzDPPwN7eHiqVChUVFQ9tlxBCCCG/DEZPdxIaGorc3FxBupO4uDgcPHgQR48e5ZMCb9q0CTExMWhra0N+fj5iYmLg4uKCsLAwQXtqtRq2trZob2/HsWPHEBsbC09PTwQHBwMAWltboVAosHTpUsyfP9+gP8ePH4dUKoVSqeSP5eXlQalUwsvLC5s3b0ZWVhZ2797NpzsJCQlBTU0NLCwsAABz5szBmDFjUFxcDEtLS2RmZmLOnDn47rvvuk1L8uWXX2LRokV8qpcPP/wQ8+bNw7lz5+Dr6wsA8PLywl//+ld4eHigvb0dW7duxaxZs3DlyhWMHDmyT+Pum3oSJiKrPtUh/3H1zdnG7gIhhBBiwKizYqOjo9HY2Gjw1Ky4uBjBwcF47733sGzZMri7uyM+Ph7x8fF8mREjRiAqKgpbtmwBcO+J3fPPP4+GhgZBvji5XI4VK1YgMTHR4Pocx+Gjjz4S5KCrqanBmjVrMGnSJBw5cgReXl6wt7dHRkYG7O3tIZVK8cc//hFr164FADQ1NcHJyQkffPABfve73+HWrVsYOXIkysrKMGXKFADA7du3YWtri8LCQqhUqi7HIjIyEq2trTh+/Dh/bNKkSfD390d2dnaXdTpnyZw6dYoPXB+ms45r/AEK7B4DBXaEEEKelKd+VuyMGTOgUChw+PBhg3N6vR6HDh1CQ0MDzM3Nu22DMYaCggJcu3YNgYGBvb62t7c3Tp48idraWlRXV0OlUmHHjh0Qi8Woq6uDRqMRBGd2dnYIDAxEeXk5gHsB59ixY7Fnzx60trbi559/xo4dO+Do6IgJEybw9dzd3bFx40Z+v7y83CDoCwkJ4dt90N27d7Fz507Y2dlBoVD0+v4IIYQQMnQZ/VVsd8aNG4fz58/z+0lJSdiwYQN0Oh1+/vlniMViLFu2zKDeqFGjANxb0UKv12PTpk2YOnVqr6+rVqsRHx+PZ599FgqFAqdOnUJVVRXS09Oh0WgA3Fsq7H5OTk78OY7jcOrUKcybNw82NjYwMTGBo6MjCgoKYG9vz9fx9PSEg4MDv6/RaHpst9Px48fxu9/9Dm1tbXB2dkZhYaGgnQfpdDrodDp+v7m5uddjQQghhJCny6AN7Bhj4DiO309MTER0dDRu3LiBxMRErFy5EnK53KDe6dOnYWNjwy8ptmrVKojFYsTGxvbqupcvX0Z6ejqUSiXKyspw4MAB7Nu3Dzdv3ux1v1999VU4Ojri9OnTsLS0xK5duxAeHo6vv/4azs7OAGCwLmxvPf/886iqqsKtW7fw3nvvYeHChaioqICjo2OX5TMyMvDGG2880rUIIYQQ8nQZlK9iAeDixYuQyWT8voODA+RyOaZMmYL8/HysXr0aNTU1BvVkMhnkcjl8fHywZMkSvPzyy0hPT+/1dcPDwwUTJwBg0aJF8PLy4ic+aLVawXmtVsufKy4uxvHjx5GXl4df//rXUCqVeOedd2BpaYndu3d3e12JRNJju52eeeYZyOVyTJo0Ce+//z7MzMzw/vvvd9tucnIympqa+O2HH354+CAQQggh5Kk0KAO74uJiXLhwAQsWLOjyvKurKyIjI5GcnPzQtkxNTdHe3v5I/SgtLRXsy2QySCQSwdO25uZmVFRUICgoCADQ1tYGADAxEQ6tiYmJIIXLg4KCggye4hUWFvLtdkev1wtetT5IJBLB1tZWsBFCCCFkaDL6q1idTgeNRiNId9KZ8mPx4sXd1ouLi4Ovry8qKysREBDAH6+vr8edO3f4V7F79+5FREQEf76lpQVXrlzh9+vq6lBVVQWxWAw3N7ce+8pxHOLj45GWloYxY8bw6U6kUik/szYoKAj29vaIiopCSkoKLC0t8d5776Gurg6zZ/9nJmVwcDBefPFFrFq1ir+fadOm4e2338bs2bORl5eHyspKPg9fa2sr0tPT8cILL8DZ2Rm3bt3C9u3b8a9//Qu//e1vez/g/9+3b4RQkEcIIYQMNcyIoqKiGAAGgJmZmbGRI0cylUrFcnJyWEdHB19u9OjRbOvWrQb1Q0JCWFhYGGOMsZKSEr6tzvZkMhlbu3Yta2lp4es8WK5zi4qK6lWf9Xo9e/3115mTkxMTiUQsODiYqdVqQZmvv/6azZo1i4nFYmZjY8MmTZrEPv30U0GZ0aNHs9TUVMGxAwcOMC8vL2Zubs58fHzYJ598wp9rb29nL774IpNKpczc3Jw5OzuzF154gZ05c6ZX/e7U1NTEALCmpqY+1SOEEEKIcfTld7dR89iRJ68vuXAIIYQQYnxPfR47QgghhBDSdxTYEUIIIYQMERTYEUIIIYQMEUYN7KKjo8FxHDiOw7Bhw+Dk5ISZM2ciJydHkBrE3d2dL2dlZQU/Pz/s2rVL0FZpaSlfhuM4WFpawsfHh59V2qmsrAzh4eGQSqXgOM5gndr7TZ8+3eAYYwwpKSlwdnaGpaUlVCoVamtrBWUuX76MuXPnwsHBAba2tpg8eTJKSkoeOh75+fkYN24cLCws4Ofnh08//ZQ/99NPPyEpKQl+fn545plnIJVKsXjxYly/fv2h7RJCCCHkl8Ho6U5CQ0ORm5srSHcSFxeHgwcP4ujRozAzu9fFTZs2ISYmBm1tbcjPz0dMTAxcXFwQFhYmaE+tVsPW1hbt7e04duwYYmNj4enpieDgYAD30oYoFAosXboU8+fPN+jP8ePHIZVKBUmK8/LyoFQq4eXlhc2bNyMrKwu7d+/m052EhISgpqYGFhYWAIA5c+ZgzJgxKC4uhqWlJTIzMzFnzhx89913BgmHO3355ZdYtGgRn+rlww8/xLx583Du3Dn4+vqira0N586dw+uvvw6FQoGGhgbExcXhhRdeQGVlZZ/H3Tf1JExEVr0uT4veE0IIIYOfUWfFRkdHo7Gx0eCpWXFxMYKDg/Hee+9h2bJlcHd3R3x8POLj4/kyI0aMQFRUFLZs2QLg3hO7559/Hg0NDRg+fDhfTi6XY8WKFUhMTDS4Psdx+Oijj/gcdABQU1ODNWvWYNKkSThy5Ai8vLxgb2+PjIwM2NvbQyqV4o9//CPWrl0LAGhqaoKTkxM++OAD/O53v8OtW7cwcuRIlJWVYcqUKQCA27dvw9bWFoWFhVCpVF2ORWRkJFpbW3H8+HH+2KRJk+Dv74/s7Owu63z99deYOHEivv/++4fm4OvUObPGNf4ABXaEEELIU+CpnxU7Y8YMKBQKHD582OCcXq/HoUOH0NDQAHNz827bYIyhoKAA165dQ2BgYK+v7e3tjZMnT6K2thbV1dVQqVTYsWMHxGIx6urqoNFoBMGZnZ0dAgMDUV5eDuBewDl27Fjs2bMHra2t+Pnnn7Fjxw44OjpiwoQJfD13d3ds3LiR3y8vLzcI+kJCQvh2u9LU1ASO4wSB7IN0Oh2am5sFGyGEEEKGpkEZ2AHAuHHjcPXqVX4/KSkJ1tbWEIlEiIiIgL29PZYtW2ZQb9SoUbC2toa5uTlmz56N1NRUTJ06tdfXVavVCAsLg1wuh0KhwKlTp7By5Uo0NDRAo9EAAJycnAR1nJyc+HMcx+HUqVP45ptvYGNjAwsLC2zZsgUFBQWwt7fn63h6esLBwYHf12g0Pbb7oDt37iApKQmLFi3qMXrPyMiAnZ0dv7m6uvZ6LAghhBDydDH6N3bdYYyB4zh+PzExEdHR0bhx4wYSExOxcuVKyOVyg3qnT5+GjY0Nv6TYqlWrIBaLERsb26vrXr58Genp6VAqlSgrK8OBAwewb98+3Lx5s9f9fvXVV+Ho6IjTp0/D0tISu3btQnh4OL7++ms4OzsDgMG6sH3x008/YeHChWCM4d133+2xbHJyMhISEvj95uZmCu4IIYSQIWrQBnYXL16ETCbj9x0cHCCXyyGXy5Gfnw8/Pz8EBATA29tbUE8mk/GvJn18fFBRUYH09PReB3bh4eEGxxYtWgQA/EQOrVbLB2id+/7+/gDufR94/PhxNDQ08E/S3nnnHRQWFmL37t1Yv359l9eVSCTQarWCY1qt1mCyRWdQ9/3336O4uPih79pFIhFEIlGPZQghhBAyNAzKV7HFxcW4cOECFixY0OV5V1dXREZGIjk5+aFtmZqaor29/ZH6UVpaKtiXyWSQSCSCp23Nzc2oqKhAUFAQAKCtrQ0AYGIiHFoTExNBCpcHBQUFGTzFKyws5NsF/hPU1dbW4tSpUxgxYsQj3RchhBBChiajP7HT6XTQaDSCdCedKT8WL17cbb24uDj4+vqisrISAQEB/PH6+nrcuXOHfxW7d+9eRERE8OdbWlpw5coVfr+urg5VVVUQi8UPnVnKcRzi4+ORlpaGMWPG8OlOpFIpP7M2KCgI9vb2iIqKQkpKCiwtLfHee++hrq4Os2f/Z2ZpcHAwXnzxRaxatYq/n2nTpuHtt9/G7NmzkZeXh8rKSj4P308//YSIiAicO3cOx48fR0dHB//9nVgs7nEiSVe+fSOE1oolhBBChhpmRFFRUQwAA8DMzMzYyJEjmUqlYjk5Oayjo4MvN3r0aLZ161aD+iEhISwsLIwxxlhJSQnfVmd7MpmMrV27lrW0tPB1HizXuUVFRfWqz3q9nr3++uvMycmJiUQiFhwczNRqtaDM119/zWbNmsXEYjGzsbFhkyZNYp9++qmgzOjRo1lqaqrg2IEDB5iXlxczNzdnPj4+7JNPPuHP1dXVddlvAKykpKRXfWeMsaamJgaANTU19boOIYQQQoynL7+7jZrHjjx5fcmFQwghhBDje+rz2BFCCCGEkL6jwI4QQgghZIigwI4QQgghZIgwamAXHR0NjuPAcRyGDRsGJycnzJw5Ezk5OYLUIO7u7nw5Kysr+Pn5YdeuXYK2SktL+TIcx8HS0hI+Pj78rNJOZWVlCA8Ph1QqBcdxBuvU3m/69OkGxxhjSElJgbOzMywtLaFSqVBbW9ttP+7fvv766x7HY/v27XB3d4eFhQUCAwNx5swZwfmdO3di+vTpsLW1BcdxaGxs7LE9QgghhPyyGD3dSWhoKHJzcwXpTuLi4nDw4EEcPXqUTwq8adMmxMTEoK2tDfn5+YiJiYGLiwvCwsIE7anVatja2qK9vR3Hjh1DbGwsPD09ERwcDABobW2FQqHA0qVLMX/+fIP+HD9+HFKpFEqlkj+Wl5cHpVIJLy8vbN68GVlZWdi9ezef7iQkJAQ1NTWwsLDAc889hxs3bgjafP3111FUVCRIy/Kg/fv3IyEhAdnZ2QgMDERmZiZCQkKgVqvh6OgI4F6OvNDQUISGhvYqh19PfFNPwkRk9VhtEEIe7uqbsx9eiBBC+onRX8WKRCJIJBK4uLhAqVTitddew5EjR3DixAl88MEHfDkbGxtIJBJ4eHggKSkJYrEYhYWFBu05OjpCIpFAJpNh9erVkMlkOHfuHH8+LCwMaWlpePHFF7vsj4eHB5KTk5GamorGxkYsXLgQJSUlcHBwAGMMmZmZ2LBhA+bOnYvx48djz549uH79Ov/kz9zcHBKJhN9GjBiBI0eOYMmSJYIl0h60ZcsWxMTEYMmSJfD29kZ2djasrKyQk5PDl4mPj8f69esxadKkPo4yIYQQQn4JjB7YdWXGjBlQKBQ4fPiwwTm9Xo9Dhw6hoaGhx6S8jDEUFBTg2rVrCAwM7PW1vb29cfLkSdTW1qK6uhoqlQo7duyAWCxGXV0dNBoNVCoVX97Ozg6BgYEoLy/vsr2jR4/i3//+N5YsWSI4znEcH7jevXsXZ8+eFbRrYmIClUrVbbu9pdPp0NzcLNgIIYQQMjQNysAOAMaNG4erV6/y+0lJSbC2toZIJEJERATs7e2xbNkyg3qjRo2CtbU1zM3NMXv2bKSmpmLq1Km9vq5arUZYWBjkcjkUCgVOnTqFlStXoqGhgV/pwcnJSVDHycmJP/eg999/HyEhIRg1apTg+NixY2FnZwcAuHXrFjo6OvrUbm9lZGTAzs6O31xdXR+rPUIIIYQMXkb/xq47jDHBq8vExERER0fjxo0bSExMxMqVKyGXyw3qnT59GjY2NvySYqtWrYJYLEZsbGyvrnv58mWkp6dDqVSirKwMBw4cwL59+3Dz5s0+38M///lPnDx5EgcOHDA4d+nSpT639yiSk5ORkJDA7zc3N1NwRwghhAxRgzawu3jxImQyGb/v4OAAuVwOuVyO/Px8+Pn5ISAgAN7e3oJ6MpkMw4cPBwD4+PigoqIC6enpvQ7swsPDDY4tWrQIAPiJHFqtFs7Ozvx5rVYLf39/g3q5ubkYMWIEXnjhhR6v6eDgAFNTU2i1WsFxrVYLiUTSq353RyQSQSQSPVYbhBBCCHk6DMpXscXFxbhw4QIWLFjQ5XlXV1dERkb2amaoqakp2tvbH6kfpaWlgn2ZTAaJRIKioiL+WHNzMyoqKhAUFCQoyxhDbm4uFi9ejGHDhvV4HXNzc0yYMEHQrl6vR1FRkUG7hBBCCCHdMfoTO51OB41GI0h3kpGRgTlz5mDx4sXd1ouLi4Ovry8qKysFaUTq6+tx584d/lXs3r17ERERwZ9vaWnBlStX+P26ujpUVVVBLBbDzc2tx75yHIf4+HikpaVhzJgxfLoTqVSKefPmCcoWFxejrq6uy+8AgXvfEGZkZPCzcxMSEhAVFYWAgABMnDgRmZmZaG1tFUy60Gg00Gg0fP8vXLgAGxsbuLm5QSwW99j3B337RgitFUsIIYQMNcyIoqKiGAAGgJmZmbGRI0cylUrFcnJyWEdHB19u9OjRbOvWrQb1Q0JCWFhYGGOMsZKSEr6tzvZkMhlbu3Yta2lp4es8WK5zi4qK6lWf9Xo9e/3115mTkxMTiUQsODiYqdVqg3KLFi1izz33XLftAGC5ubmCY9u2bWNubm7M3NycTZw4kX311VeC86mpqV32/cF2etLU1MQAsKampl7XIYQQQojx9OV3N8cYY086mCTG09zcDDs7OzQ1NdETO0IIIeQp0Jff3YPyGztCCCGEENJ3FNgRQgghhAwRRg3soqOjwXEcOI7DsGHD4OTkhJkzZyInJwd6vZ4v5+7uzpezsrKCn58fdu3aJWirtLSUL8NxHCwtLeHj44OdO3cKypWVlSE8PBxSqRQcx/FLgXVl+vTpBscYY0hJSYGzszMsLS2hUqlQW1vbZX2dTgd/f39wHIeqqqqHjsf27dvh7u4OCwsLBAYG4syZMwZlysvLMWPGDDzzzDOwtbXF1KlTH3nWLyGEEEKGFqPPig0NDUVubq5gVmxcXBwOHjyIo0eP8rnjNm3ahJiYGLS1tSE/Px8xMTFwcXFBWFiYoD21Wg1bW1u0t7fj2LFjiI2NhaenJ4KDgwEAra2tUCgUWLp0KebPn2/Qn+PHj0MqlUKpVPLH8vLyoFQq4eXlhc2bNyMrKwu7d+/mZ8WGhISgpqYGFhYWgrbWrVsHqVSK6urqh47D/v37kZCQgOzsbAQGBiIzMxMhISFQq9VwdHQEcC+oCw0NRXJyMrZt2wYzMzNUV1fDxKTv8blv6kmYiKz6XG+ooQXaCSGEDCVGfxUrEokgkUjg4uICpVKJ1157DUeOHMGJEyf4tVQBwMbGBhKJBB4eHkhKSoJYLEZhYaFBe46OjpBIJJDJZFi9ejVkMhnOnTvHnw8LC0NaWhqfZuRBHh4eSE5ORmpqKhobG7Fw4UKUlJTAwcEBjDFkZmZiw4YNmDt3LsaPH489e/bg+vXrBk/+Tpw4gc8++wxvvfVWr8Zhy5YtiImJwZIlS+Dt7Y3s7GxYWVkhJyeHL7NmzRqsXr0a69evh4+PD8aOHYuFCxdSAmJCCCGEABgEgV1XZsyYAYVCgcOHDxuc0+v1OHToEBoaGmBubt5tG4wxFBQU4Nq1awgMDOz1tb29vXHy5EnU1taiuroaKpUKO3bsgFgsRl1dHTQaDVQqFV/ezs4OgYGBKC8v549ptVrExMRg7969sLLq+qkYx3F84Hr37l2cPXtW0K6JiQlUKhXfbn19PSoqKuDo6IjnnnsOTk5OmDZtGr744ote3xshhBBChrZBGdgB9xL4Xr16ld9PSkqCtbU1RCIRIiIiYG9v32Xy31GjRsHa2hrm5uaYPXs2UlNTMXXq1F5fV61WIywsDHK5HAqFAqdOncLKlSvR0NAAjUYDAHBychLUcXJy4s8xxhAdHY1XXnlFkDj5QWPHjoWdnR0A4NatW+jo6Oix3X/84x8AgI0bNyImJgYFBQVQKpUIDg7u9hs/4N53fs3NzYKNEEIIIUOT0b+x6w5jDBzH8fuJiYmIjo7GjRs3kJiYiJUrV0IulxvUO336NGxsbPiVJ1atWgWxWNzrtWIvX76M9PR0KJVKlJWV4cCBA9i3bx9u3rzZq/rbtm3D7du3H7rc2aVLl3rVXqfOySQrVqzgV6P4P//n/6CoqAg5OTnIyMjosl5GRgbeeOONPl2LEEIIIU+nQRvYXbx4ETKZjN93cHCAXC6HXC5Hfn4+/Pz8EBAQAG9vb0E9mUyG4cOHAwB8fHxQUVGB9PT0Xgd24eHhBscWLVoEAPxEDq1WC2dnZ/68VquFv78/gHtLiZWXlxt89xYQEICXXnoJu3fvNmjfwcEBpqam0Gq1guNarRYSiQQA+Os9eL+/+tWvcO3atW7vJzk5GQkJCfx+c3MzXF1duy1PCCGEkKfXoHwVW1xcjAsXLmDBggVdnnd1dUVkZORDn4oBgKmp6SOnAyktLRXsy2QySCQSFBUV8ceam5tRUVGBoKAgAEBWVhaqq6tRVVWFqqoqfPrppwDuzXpNT0/v8jrm5uaYMGGCoF29Xo+ioiK+XXd3d0ilUqjVakHdy5cvY/To0d3eg0gkgq2trWAjhBBCyNBk9Cd2Op0OGo1GkO4kIyMDc+bMweLFi7utFxcXB19fX1RWVgq+Zauvr8edO3f4V7F79+5FREQEf76lpQVXrlzh9+vq6lBVVQWxWAw3N7ce+8pxHOLj45GWloYxY8bw6U6kUinmzZsHAAZtWFtbAwA8PT0xatQo/vi4ceOQkZHBz85NSEhAVFQUAgICMHHiRGRmZqK1tZV/7cpxHBITE5GamgqFQgF/f3/s3r0bly5dwsGDB3vsd1e+fSOEgjxCCCFkiDF6YFdQUABnZ2eYmZnB3t4eCoUCWVlZiIqK6jE/m7e3N2bNmoWUlBT+qRhwb1ICcO+1qaurK1asWIGNGzfy5ysrK/H888/z+52vKaOiogTpVbqzbt06tLa2Yvny5WhsbMTkyZNRUFBgkMPuYdRqNZqamvj9yMhI3Lx5EykpKdBoNPD390dBQYFgQkV8fDzu3LmDNWvW4Mcff4RCoUBhYSE8PT37dG1CCCGEDE0cY4wZuxPkyenLQsKEEEIIMb6+/O4elN/YEUIIIYSQvqPAjhBCCCFkiKDAjhBCCCFkiDBqYBcdHQ2O48BxHIYNGwYnJyfMnDkTOTk5fEJe4F6qj85yVlZW8PPzw65duwRtlZaW8mU4joOlpSV8fHywc+dOQbmysjKEh4dDKpWC4ziDNV7vN336dINjjDGkpKTA2dkZlpaWUKlU3a78oNPp4O/vD47jUFVV9dDx2L59O9zd3WFhYYHAwECcOXPGoD/33yPHcXjllVce2i4hhBBCfhmMPis2NDQUubm5gnQncXFxOHjwII4ePconBd60aRNiYmLQ1taG/Px8xMTEwMXFBWFhYYL21Go1bG1t0d7ejmPHjiE2Nhaenp4IDg4GALS2tkKhUGDp0qWYP3++QX+OHz8OqVQKpVLJH8vLy4NSqYSXlxc2b96MrKws7N69m093EhISgpqaGoOZsevWrYNUKkV1dfVDx2H//v1ISEhAdnY2AgMDkZmZiZCQEKjVajg6OvLlYmJisGnTJn6/u7VoH8Y39SRMRI9Wl5Ch4Oqbs43dBUII6XdGfxUrEokgkUjg4uICpVKJ1157DUeOHMGJEycE6UdsbGwgkUjg4eGBpKQkiMViFBYWGrTn6OgIiUQCmUyG1atXQyaT4dy5c/z5sLAwpKWl8fnjHuTh4YHk5GSkpqaisbERCxcuRElJCRwcHMAYQ2ZmJjZs2IC5c+di/Pjx2LNnD65fv27w5O/EiRP47LPP8NZbb/VqHLZs2YKYmBgsWbIE3t7eyM7OhpWVFXJycgTlrKysIJFI+I1mthJCCCGkk9EDu67MmDEDCoUChw8fNjin1+tx6NAhNDQ0wNzcvNs2GGMoKCjAtWvXEBgY2Otre3t74+TJk6itrUV1dTVUKhV27NgBsViMuro6aDQaqFQqvrydnR0CAwNRXl7OH9NqtYiJicHevXu7faLGcRwfuN69exdnz54VtGtiYgKVSiVoFwD+9re/wcHBAb6+vkhOTkZbW1uv740QQgghQ5vRX8V2Z9y4cTh//jy/n5SUhA0bNkCn0+Hnn3+GWCzGsmXLDOp1ru6g0+mg1+uxadMmTJ06tdfXVavViI+Px7PPPguFQoFTp06hqqoK6enp0Gg0ACBIGty533mOMYbo6Gi88sorCAgIwNWrV7u8ztixY2FnZwcAuHXrFjo6Orps99KlS/z+73//e4wePRpSqRTnz59HUlIS1Gp1lwFwJ51OB51Ox+83Nzf3eiwIIYQQ8nQZtIEdYwwcx/H7iYmJiI6Oxo0bN5CYmIiVK1dCLpcb1Dt9+jRsbGz4JcVWrVoFsViM2NjYXl338uXLSE9Ph1KpRFlZGQ4cOIB9+/bh5s2bvaq/bds23L59+6Hr2N4fsPXW8uXL+f/v5+cHZ2dnBAcH47vvvut29YmMjAy88cYbfb4WIYQQQp4+g/JVLABcvHgRMpmM33dwcIBcLseUKVOQn5+P1atXo6amxqCeTCaDXC6Hj48PlixZgpdffhnp6em9vm54eLhg4gQALFq0CF5eXpBIJADuvWq9n1ar5c8VFxejvLwcIpEIZmZmfPAZEBCAqKioLq/p4OAAU1PTHtvtSucr5vvXvn1QcnIympqa+O2HH37otiwhhBBCnm6DMrArLi7GhQsXsGDBgi7Pu7q6IjIy8qFPxQDA1NQU7e3tj9SP0tJSwb5MJoNEIkFRURF/rLm5GRUVFQgKCgIAZGVlobq6GlVVVaiqquLXsd2/f3+3Aaa5uTkmTJggaFev16OoqIhvtyudKVScnZ27LSMSiWBrayvYCCGEEDI0Gf1VrE6ng0ajEaQ7ycjIwJw5c7B48eJu68XFxcHX1xeVlZUICAjgj9fX1+POnTv8q9i9e/ciIiKCP9/S0iJ4wlVXV4eqqiqIxWK4ubn12FeO4xAfH4+0tDSMGTOGT3cilUoxb948ADBow9raGgDg6enJf/8H3PuGMCMjg5+dm5CQgKioKAQEBGDixInIzMxEa2srlixZAgD47rvv8OGHH+I3v/kNRowYgfPnz2PNmjWYOnUqxo8f32O/u/LtGyEU5BFCCCFDjNEDu4KCAjg7O8PMzAz29vZQKBTIyspCVFQUTEy6f6Do7e2NWbNmISUlhX8qBtyblAAAZmZmcHV1xYoVK7Bx40b+fGVlJZ5//nl+PyEhAQAQFRUlSK/SnXXr1qG1tRXLly9HY2MjJk+ejIKCAoMcdg+jVqvR1NTE70dGRuLmzZtISUmBRqOBv78/CgoK+AkV5ubmOHXqFB/wubq6YsGCBdiwYUOfrksIIYSQoYtjjDFjd4I8Oc3NzbCzs0NTUxM9sSOEEEKeAn353T0ov7EjhBBCCCF9R4EdIYQQQsgQQYEdIYQQQsgQYdTALjo6GhzHgeM4DBs2DE5OTpg5cyZycnKg1+v5cu7u7nw5Kysr+Pn5YdeuXYK2SktL+TIcx8HS0hI+Pj7YuXOnoFxZWRnCw8MhlUrBcZzBGq/3mz59usExxhhSUlLg7OwMS0tLqFQq1NbWdllfp9PB398fHMfxqUl6sn37dri7u8PCwgKBgYE4c+ZMl+UYYwgLC3to/wkhhBDyy2L0WbGhoaHIzc0VpDuJi4vDwYMHcfToUZiZ3evipk2bEBMTg7a2NuTn5yMmJgYuLi4ICwsTtKdWq2Fra4v29nYcO3YMsbGx8PT0RHBwMACgtbUVCoUCS5cuxfz58w36c/z4cUilUkGS4ry8PCiVSnh5eWHz5s3IysrC7t27+XQnISEhqKmpMZgZu27dOkilUlRXVz90HPbv34+EhARkZ2cjMDAQmZmZCAkJgVqthqOjo6BsZmamYFWOR+GbehImoq7Xse0PV9+cPWBtE0IIIaRrRn8VKxKJIJFI4OLiAqVSiddeew1HjhzBiRMnBOlHbGxsIJFI4OHhgaSkJIjFYhQWFhq05+joCIlEAplMhtWrV0Mmk+HcuXP8+bCwMKSlpfH54x7k4eGB5ORkpKamorGxEQsXLkRJSQkcHBzAGENmZiY2bNiAuXPnYvz48dizZw+uX79u8OTsxIkT+Oyzz/DWW2/1ahy2bNmCmJgYLFmyBN7e3sjOzoaVlRVycnIE5aqqqvD2228bHCeEEEIIMXpg15UZM2ZAoVB0ubi9Xq/HoUOH0NDQAHNz827bYIyhoKAA165d45fe6g1vb2+cPHkStbW1qK6uhkqlwo4dOyAWi1FXVweNRgOVSsWXt7OzQ2BgIMrLy/ljWq0WMTEx2Lt3L6ysun4qxnEcH7jevXsXZ8+eFbRrYmIClUolaLetrQ2///3vsX379h6XGrufTqdDc3OzYCOEEELI0DQoAzvg3soMV69e5feTkpJgbW0NkUiEiIgI2NvbY9myZQb1Ro0aBWtra5ibm2P27NlITU3F1KlTe31dtVqNsLAwyOVyKBQKnDp1CitXrkRDQwM0Gg0A8EmDOzk5OfHnGGOIjo7GK6+8IlgR40Fjx46FnZ0dAODWrVvo6OjosV0AWLNmDZ577jnMnTu31/eTkZEBOzs7fnN1de11XUIIIYQ8XYz+jV13GGOC78gSExMRHR2NGzduIDExEStXroRcLjeod/r0adjY2PBLiq1atQpisRixsbG9uu7ly5eRnp4OpVKJsrIyHDhwAPv27cPNmzd7VX/btm24ffv2Q9exvXTpUq/a63T06FEUFxfjm2++6VO95ORkfnUN4F6SQwruCCGEkKFp0AZ2Fy9ehEwm4/cdHBwgl8shl8uRn58PPz8/BAQEwNvbW1BPJpNh+PDhAAAfHx9UVFQgPT2914FdeHi4wbFFixYBAD+RQ6vVwtnZmT+v1Wrh7+8PACguLkZ5eTlEIpGgjYCAALz00kvYvXu3QfsODg4wNTWFVqsVHNdqtfwr1+LiYnz33Xf8vXVasGABpkyZgtLS0i7vRyQSGfSFEEIIIUPToHwVW1xcjAsXLmDBggVdnnd1dUVkZORDn4oBgKmpKdrb2x+pHw8GSzKZDBKJBEVFRfyx5uZmVFRUICgoCACQlZWF6upqVFVVoaqqil/Hdv/+/UhPT+/yOubm5pgwYYKgXb1ej6KiIr7d9evX4/z583y7nelTtm7ditzc3Ee6P0IIIYQMLUZ/YqfT6aDRaATpTjIyMjBnzhwsXry423pxcXHw9fVFZWWl4Fu2+vp63Llzh38Vu3fvXkRERPDnW1pacOXKFX6/rq4OVVVVEIvFcHNz67GvHMchPj4eaWlpGDNmDJ/uRCqVYt68eQBg0Ia1tTUAwNPTE6NGjeKPjxs3DhkZGfzs3ISEBERFRSEgIAATJ05EZmYmWltbsWTJEgCARCLpcsKEm5ub4Mlmb337RgitFUsIIYQMMUYP7AoKCuDs7AwzMzPY29tDoVAgKysLUVFRMDHp/oGit7c3Zs2ahZSUFP6pGHBvUgJw77Wpq6srVqxYgY0bN/LnKysr8fzzz/P7nd+fRUVFCdKrdGfdunVobW3F8uXL0djYiMmTJ6OgoMAgh93DqNVqNDU18fuRkZG4efMmUlJSoNFo4O/vj4KCAoMJFYQQQggh3eEYY8zYnSBPTnNzM+zs7NDU1ERP7AghhJCnQF9+dw/Kb+wIIYQQQkjfUWBHCCGEEDJEUGBHCCGEEDJEGDWwi46OBsdx4DgOw4YNg5OTE2bOnImcnBzo9Xq+nLu7O1/OysoKfn5+2LVrl6Ct0tJSvgzHcbC0tISPjw927twpKFdWVobw8HBIpVJwHGewxuv9pk+fbnCMMYaUlBQ4OzvD0tISKpUKtbW1XdbX6XTw9/cHx3F8epKebN++He7u7rCwsEBgYCDOnDkjOL9ixQp4enrC0tISI0eOxNy5c/uc6JgQQgghQ5fRZ8WGhoYiNzdXkO4kLi4OBw8exNGjR/mkwJs2bUJMTAza2tqQn5+PmJgYuLi4ICwsTNCeWq2Gra0t2tvbcezYMcTGxsLT0xPBwcEAgNbWVigUCixduhTz58836M/x48chlUqhVCr5Y3l5eVAqlfDy8sLmzZuRlZWF3bt38+lOQkJCUFNTYzAzdt26dZBKpaiurn7oOOzfvx8JCQnIzs5GYGAgMjMzERISArVaDUdHRwDAhAkT8NJLL8HNzQ0//vgjNm7ciFmzZqGurg6mpqZ9Gnff1JMwEXW9ju1Qd/XN2cbuAiGEEDIgjP4qViQSQSKRwMXFBUqlEq+99hqOHDmCEydOCNKP2NjYQCKRwMPDA0lJSRCLxSgsLDRoz9HRERKJBDKZDKtXr4ZMJsO5c+f482FhYUhLS+Pzxz3Iw8MDycnJSE1NRWNjIxYuXIiSkhI4ODiAMYbMzExs2LABc+fOxfjx47Fnzx5cv37d4MnfiRMn8Nlnn+Gtt97q1Ths2bIFMTExWLJkCby9vZGdnQ0rKyvk5OTwZZYvX46pU6fC3d0dSqUSaWlp+OGHHwRr6hJCCCHkl8vogV1XZsyYAYVCgcOHDxuc0+v1OHToEBoaGmBubt5tG4wxFBQU4Nq1awgMDOz1tb29vXHy5EnU1taiuroaKpUKO3bsgFgsRl1dHTQaDVQqFV/ezs4OgYGBKC8v549ptVrExMRg7969sLLq+qkYx3F84Hr37l2cPXtW0K6JiQlUKpWg3fu1trYiNzcXMpmsx7VfdTodmpubBRshhBBChqZBGdgB91ZmuP9JVFJSEqytrSESiRAREQF7e3ssW7bMoN6oUaNgbW0Nc3NzzJ49G6mpqZg6dWqvr6tWqxEWFga5XA6FQoFTp05h5cqVaGhogEajAQCDpMFOTk78OcYYoqOj8corrwhWxHjQ2LFjYWdnBwC4desWOjo6emy30zvvvANra2tYW1vjxIkTKCws7DHAzcjIgJ2dHb/1FAQSQggh5Ok2aAM7xhg4juP3ExMTUVVVheLiYgQGBmLr1q2Qy+UG9U6fPs2vpbpr1y78+c9/xrvvvtvr616+fBnp6enYtGkThg8fjgMHDmDKlCm4efNmr+pv27YNt2/ffug6tpcuXer2dXBPXnrpJXzzzTf4/PPP4eXlhYULF+LOnTvdlk9OTkZTUxO//fDDD32+JiGEEEKeDkafPNGdixcvCtZAdXBwgFwuh1wuR35+Pvz8/BAQEABvb29BPZlMhuHDhwMAfHx8UFFRgfT0dMTGxvbquuHh4QbHFi1aBAD8RA6tVgtnZ2f+vFarhb+/PwCguLgY5eXlEIlEgjYCAgLw0ksvYffu3QbtOzg4wNTUFFqtVnBcq9UarA/b+eRtzJgxmDRpEuzt7fHRRx/xfXyQSCQy6AshhBBChqZB+cSuuLgYFy5cwIIFC7o87+rqisjIyIc+FQMAU1NTtLe3P1I/SktLBfsymQwSiQRFRUX8sebmZlRUVCAoKAgAkJWVherqav6pYec6tvv370d6enqX1zE3N8eECRME7er1ehQVFfHtdoUxBsYYdDrdI90fIYQQQoYWoz+x0+l00Gg0gnQnGRkZmDNnDhYvXtxtvbi4OPj6+qKyslLwLVt9fT3u3LkDnU6HM2fOYO/evYiIiODPt7S04MqVK/x+XV0dqqqqIBaL4ebm1mNfOY5DfHw80tLSMGbMGD7diVQqxbx58wDAoA1ra2sAgKenJ0aNGsUfHzduHDIyMvjXsQkJCYiKikJAQAAmTpyIzMxMtLa2YsmSJQCAf/zjH9i/fz9mzZqFkSNH4p///CfefPNNWFpa4je/+U2P/e7Kt2+E0FqxhBBCyBBj9MCuoKAAzs7OMDMzg729PRQKBbKyshAVFQUTk+4fKHp7e2PWrFlISUnhn4oB9yYlAPdem7q6umLFihXYuHEjf76yshLPP/88v5+QkAAAiIqKEqRX6c66devQ2tqK5cuXo7GxEZMnT0ZBQYFBDruHUavVaGpq4vcjIyNx8+ZNpKSkQKPRwN/fHwUFBfyECgsLC5w+fRqZmZloaGiAk5MTpk6dii+//JLPc0cIIYSQXzaOMcaM3Qny5DQ3N8POzg5NTU30xI4QQgh5CvTld/eg/MaOEEIIIYT0HQV2hBBCCCFDhFEDu+joaHAcB47jMGzYMDg5OWHmzJnIycmBXq/ny7m7u/PlrKys4Ofnh127dgnaKi0t5ctwHAdLS0v4+Phg586dgnJlZWUIDw+HVCoFx3EGS4Hdb/r06QbHGGNISUmBs7MzLC0toVKpUFtb22V9nU4Hf39/cByHqqqqh47H9u3b4e7uDgsLCwQGBuLMmTOC8zt37sT06dNha2sLjuPQ2Nj40DYJIYQQ8sth9MkToaGhyM3NFcyKjYuLw8GDB3H06FE+d9ymTZsQExODtrY25OfnIyYmBi4uLggLCxO0p1arYWtri/b2dhw7dgyxsbHw9PREcHAwgHtLcSkUCixduhTz58836M/x48chlUqhVCr5Y3l5eVAqlfDy8sLmzZuRlZWF3bt387NiQ0JCUFNTYzCBYt26dZBKpaiurn7oOOzfvx8JCQnIzs5GYGAgMjMzERISArVazU+OaGtrQ2hoKEJDQ3uV6qUnvqknYSLqermzrlx9c/ZjXY8QQgghA8/or2JFIhEkEglcXFygVCrx2muv4ciRIzhx4oRglqqNjQ0kEgk8PDyQlJQEsViMwsJCg/YcHR0hkUggk8mwevVqyGQynDt3jj8fFhaGtLS0bld98PDwQHJyMlJTU9HY2IiFCxeipKQEDg4OYIwhMzMTGzZswNy5czF+/Hjs2bMH169fN3jyd+LECXz22Wd46623ejUOW7ZsQUxMDJYsWQJvb29kZ2fDysoKOTk5fJn4+HisX78ekyZN6lWbhBBCCPllMXpg15UZM2ZAoVDg8OHDBuf0ej0OHTqEhoaGHtdIZYyhoKAA165dQ2BgYK+v7e3tjZMnT6K2thbV1dVQqVTYsWMHxGIx6urqoNFooFKp+PJ2dnYIDAxEeXk5f0yr1SImJgZ79+6FlVXXT8U4juMD17t37+Ls2bOCdk1MTKBSqQTtEkIIIYT0ZFAGdsC9BL5Xr17l95OSkmBtbQ2RSISIiAjY29tj2bJlBvVGjRoFa2trmJubY/bs2UhNTcXUqVN7fV21Wo2wsDDI5XIoFAqcOnUKK1euRENDAzQaDQDwueU6OTk58ecYY4iOjsYrr7wiSJz8oLFjx8LOzg4AcOvWLXR0dPTY7qPS6XRobm4WbIQQQggZmoz+jV13GGPgOI7fT0xMRHR0NG7cuIHExESsXLkScrncoN7p06dhY2PDrzyxatUqiMXiXq8Ve/nyZaSnp0OpVKKsrAwHDhzAvn37cPPmzV7V37ZtG27fvv3Qb+AuXbrUq/YeV0ZGBt54440nci1CCCGEGNegDewuXrwImUzG7zs4OEAul0MulyM/Px9+fn4ICAiAt7e3oJ5MJsPw4cMBAD4+PqioqEB6enqvA7vw8HCDY4sWLQIAfiKHVquFs7Mzf16r1cLf3x/AvXVuy8vLIRKJBG0EBATgpZdewu7duw3ad3BwgKmpKbRareC4VquFRCLpVb+7k5yczK+uAdxLcujq6vpYbRJCCDGOjo4O/PTTT8buBulnw4YNg6mpab+0NSgDu+LiYly4cAFr1qzp8ryrqysiIyORnJyMI0eO9NiWqakp2tvbH6kfpaWlgn2ZTAaJRIKioiI+kGtubkZFRQUfOGZlZSEtLY2vc/36dYSEhGD//v3dfutnbm6OCRMmoKioiF9zVq/Xo6ioCKtWrXqkvncSiUQGQSYhhJCnC2MMGo2G0lwNYcOHD4dEIhG8rXwURg/sdDodNBqNIN1JRkYG5syZg8WLF3dbLy4uDr6+vqisrBR8y1ZfX487d+7wr2L37t2LiIgI/nxLSwuuXLnC79fV1aGqqgpisRhubm499pXjOMTHxyMtLQ1jxozh051IpVI+IHuwDWtrawCAp6cnRo0axR8fN24cMjIy+Nm5CQkJiIqKQkBAACZOnIjMzEy0trZiyZIlfB2NRgONRsP3/8KFC7CxsYGbmxvEYnGPfX/Qt2+E0JJihBDylOgM6hwdHWFlZfXYv/zJ4MEYQ1tbG+rr6wFA8EbwURg9sCsoKICzszPMzMxgb28PhUKBrKwsREVFwcSk+7kd3t7emDVrFlJSUvDpp5/yx8eOHQvg3mtTV1dXrFixAhs3buTPV1ZW4vnnn+f3O19TRkVFCdKrdGfdunVobW3F8uXL0djYiMmTJ6OgoMAgh93DqNVqNDU18fuRkZG4efMmUlJSoNFo4O/vj4KCAsGEiuzsbMH3cp2TQnJzcxEdHd2n6xNCCHk6dHR08EHdiBEjjN0dMgAsLS0B3Hs45ejo+FivZTnGGOuvjpHBry8LCRNCCDG+O3fuoK6uDu7u7nwAQIae9vZ2XL16FTKZzOBhUV9+dw/adCeEEEII+Q96/Tq09dd/XwrsCCGEEEKGCArsCCGEEPLEXb16FRzHoaqqCsC9TBQcx/Vp5q+7uzsyMzP7rU87d+6Eq6srTExM+rXdJ8mokyeio6P5vG5mZmYQi8UYP348Fi1ahOjoaH7yhLu7O77//nsA9z4w9PT0RFxcnGDlidLSUsGkCAsLC3h4eCAuLg7Lly/nj5eVleEvf/kLzp49ixs3buCjjz7iZ7Q+aPr06QYpTxhjSE1NxXvvvYfGxkb8+te/xrvvvosxY8bwZV544QVUVVWhvr4e9vb2UKlU+O///m9IpdIex2P79u34y1/+Ao1GA4VCgW3btmHixIn8+Z07d+LDDz/EuXPncPv2bTQ0NPA5+wghhPyyuK//5Ile7+qbs5/o9Z605uZmrFq1Clu2bMGCBQv41aGeNkafFRsaGorc3FxBupO4uDgcPHgQR48e5ZMCb9q0CTExMWhra0N+fj5iYmLg4uKCsLAwQXtqtRq2trZob2/HsWPHEBsbC09PTwQHBwMAWltboVAosHTpUsyfP9+gP8ePH4dUKoVSqeSP5eXlQalUwsvLC5s3b0ZWVhZ2797NpzsJCQlBTU0N/7Hj888/j9deew3Ozs7417/+hbVr1yIiIgJffvllt+Owf/9+JCQkIDs7G4GBgcjMzERISAjUajUcHR0BAG1tbQgNDUVoaOhDV7Z4GN/UkzARdb2OLSGk94b6LztCfimuXbuGn376CbNnz+425cjdu3d7XKd+MDD6q1iRSASJRAIXFxcolUq89tprOHLkCE6cOCFIP2JjYwOJRAIPDw8kJSVBLBajsLDQoD1HR0dIJBLIZDKsXr0aMpkM586d48+HhYUhLS2Nzx/3IA8PDyQnJyM1NRWNjY1YuHAhSkpK4ODgAMYYMjMzsWHDBsydOxfjx4/Hnj17cP36dXz88cd8G2vWrMGkSZMwevRoPPfcc1i/fj2++uqrHrOFb9myBTExMViyZAm8vb2RnZ0NKysr5OTk8GXi4+Oxfv16TJo0qQ8jTAghhBhHQUEBJk+ejOHDh2PEiBGYM2cOvvvuu17X/+KLLzBlyhRYWlrC1dUVq1evRmtra7flGxsbsWzZMowcORK2traYMWMGqqurH3qdDz74AH5+fgDuxQEcx+Hq1avYuHEj/P39sWvXLsFs1d5c580334STkxNsbGzwhz/8AevXr+cXNxhIRg/sujJjxgwoFAocPnzY4Jxer8ehQ4fQ0NDQY9TMGENBQQGuXbvW7YoPXfH29sbJkydRW1uL6upqqFQq7NixA2KxGHV1ddBoNFCpVHx5Ozs7BAYGory8vMv2fvzxR/ztb3/Dc889h2HDhvHHOY7jA9e7d+/i7NmzgnZNTEygUqm6bZcQQggZ7FpbW5GQkIDKykoUFRXBxMQEL774IvR6/UPrfvfddwgNDcWCBQtw/vx57N+/H1988UWPKzL99re/RX19PU6cOIGzZ89CqVQiODgYP/74Y4/XioyMxKlTpwAAZ86cwY0bN/jlN69cuYJDhw7h8OHD/PeAD7vOgQMHsHHjRvz5z39GZWUlnJ2d8c477/RmyB6b0V/FdmfcuHE4f/48v5+UlIQNGzZAp9Ph559/hlgsFnxj16lzdQedTge9Xo9NmzbxiXx7Q61WIz4+Hs8++ywUCgVOnTqFqqoqpKenQ6PRAIAgaXDnfue5+/v717/+FW1tbZg0aRKOHz8uOD927Fj+/f2tW7fQ0dHRZbuXLl3qdd+7otPpoNPp+P3m5ubHao8QQgjprQULFgj2c3JyMHLkSNTU1PArM3UnIyMDL730EuLj4wEAY8aMQVZWFqZNm4Z3333XINfbF198gTNnzqC+vp5fSvOtt97Cxx9/jIMHDwq+t3+QpaUln/x55MiRgnXa7969iz179mDkyJG9vk5mZib+8Ic/4A9/+AMAIC0tDadOncKdO3ceNmSPbVA+sQPuPXG7P6dLYmIiqqqqUFxcjMDAQGzduhVyudyg3unTp1FVVYWqqirs2rULf/7zn/Huu+/2+rqXL19Geno6Nm3ahOHDh+PAgQOYMmUKbt682af+JyYm4ptvvsFnn30GU1NTLF68GPfngr506VK3r4P7U0ZGBuzs7Pit818ghBBCyECrra3FokWL4OHhAVtbW7i7uwO49z3bw1RXV+ODDz6AtbU1v4WEhECv16Ourq7L8i0tLRgxYoSgTl1dXZ9e/z5o9OjRfFDX2+tcvHjR4G1hUFDQI/ehLwbtE7uLFy9CJpPx+w4ODpDL5ZDL5cjPz4efnx8CAgLg7e0tqCeTyfiZoj4+PqioqEB6ejpiY2N7dd3w8HCDY4sWLQIAfiKHVqsVfFip1WoN3ps7ODjAwcEBXl5e+NWvfgVXV1d89dVXXf6HdXBwgKmpKbRareC4VqsV/KvhUSQnJ/PLpgH3nthRcEcIIeRJCA8Px+jRo/Hee+9BKpVCr9fD19cXd+/efWjdlpYWrFixAqtXrzY419Xa7i0tLXB2djbIZgHgsTJIPPPMM0/kOv1lUAZ2xcXFuHDhAtasWdPleVdXV0RGRiI5ORlHjhzpsS1TU1O0t7c/Uj8e/I8mk8kgkUhQVFTEB3LNzc2oqKjoMXDs/Jbg/lei9zM3N8eECRNQVFTEp17R6/UoKirq8VuC3hCJRPyjYkIIIeRJ+fe//w21Wo333nsPU6ZMAXDvNWZvKZVK1NTUdPl2rrvyGo0GZmZm/JPBgdCb6/zqV79CRUUFFi9ezB/76quvBqxP9zN6YKfT6aDRaATpTjIyMjBnzhzBgDwoLi4Ovr6+qKysREBAAH+8vr4ed+7cgU6nw5kzZ7B3715ERETw51taWnDlyhV+v66uDlVVVRCLxV3+C+B+HMchPj4eaWlpGDNmDJ/uRCqV8gFZRUUFvv76a0yePBn29vb47rvv8Prrr8PT01PwtG7cuHHIyMjgX8cmJCQgKioKAQEBmDhxIjIzM9Ha2oolS5bwdTQaDTQaDd//CxcuwMbGBm5ubhCLxb0Y7f/49o0QWiuWEELIgLG3t8eIESOwc+dOODs749q1a1i/fn2v6yclJWHSpElYtWoVli1bhmeeeQY1NTUoLCzEX//6V4PyKpUKQUFBmDdvHjZv3gwvLy9cv34dn3zyCV588UVBrPA4enOduLg4REdHIyAgAL/+9a/xt7/9DX//+9/h4eHRL33oidEDu4KCAjg7O8PMzAz29vZQKBTIyspCVFQUn6C4K97e3pg1axZSUlLw6aef8sfHjh0L4N5rU1dXV6xYsQIbN27kz1dWVgoSGXe+poyKihKkV+nOunXr0NraiuXLl6OxsRGTJ09GQUEB/xGnlZUVDh8+jNTUVLS2tsLZ2RmhoaHYsGGD4MmZWq1GU1MTvx8ZGYmbN28iJSUFGo0G/v7+KCgoEEyoyM7OxhtvvMHvd04Kyc3NRXR09EP7TgghhDwpJiYmyMvLw+rVq+Hr64uxY8ciKysL06dP71X98ePH4/PPP8ef/vQnTJkyBYwxeHp6IjIyssvyHMfh008/xZ/+9CcsWbIEN2/ehEQiwdSpUw0mJz6O3lwnMjIS3333HdatW4c7d+5gwYIFiI2NxcmTJ/utH932j93/RT8Z8pqbm2FnZ4empiZ6YkcIIU+BO3fuoK6uTpBHjTx9Nm7ciI8//phPmfKgnv479+V396CdFUsIIYQQQvqGAjtCCCGEDHk+Pj6C9CT3b3/729+M3b1+Q69if2HoVSwhhDxd6FVs//j++++7Xdqzc+kvYxoSr2Kjo6PBcRw4jsOwYcPg5OSEmTNnIicnR7DciLu7O1/OysoKfn5+2LVrl6Ct0tJSvgzHcbC0tISPjw927twpKFdWVobw8HBIpVJwHCdY4/VBXX3gyRhDSkoKnJ2dYWlpCZVKhdraWkGZ9PR0PPfcc7CysupTTpv8/HyMGzcOFhYW8PPzE0wKAYDDhw9j1qxZGDFiBDiO6/Y9PSGEEEKERo8ezefDfXAzdlDXn4w+KzY0NBS5ubmCdCdxcXE4ePAgjh49yicF3rRpE2JiYtDW1ob8/HzExMTAxcUFYWFhgvbUajVsbW3R3t6OY8eOITY2Fp6enggODgZwb906hUKBpUuXYv78+Qb9OX78OKRSKZRKJX8sLy8PSqUSXl5e2Lx5M7KysrB7924+3UlISAhqamr4CPvu3bv47W9/i6CgILz//vu9Gocvv/wSixYt4lO9fPjhh5g3bx7OnTsHX19fvu+TJ0/GwoULERMT0/fBvo9v6kmYiKx6Xf7qm7Mf63qEEEIIGXhGD+xEIhG/uoKLiwuUSiUmTZqE4OBgfPDBB/x6sDY2Nny5pKQkbN68GYWFhQaBnaOjI/+UbPXq1cjKysK5c+f4wC4sLMygzv08PDywZs0aTJo0CY2NjVi4cCHs7e0xa9YsMMaQmZmJDRs2YO7cuQCAPXv2wMnJCR9//DF+97vfAQCfkqQ36VM6/c///A9CQ0ORmJgIAPiv//ovPldPdnY2AODll18GAFy9erXX7RJCCBka7n+TRYae/vrva/TAriszZsyAQqHA4cOH+cCuk16vx0cffYSGhgaYm5t32wZjDCdPnsS1a9cM1mvribe3N06ePInf//73qK6uxsqVK/mFg//xj39Ao9FApVLx5e3s7BAYGIjy8nI+sOsNd3d3REdH8zn2ysvLBUt/AUBISEiPr4p7Q6fTCVa8aG5ufqz2CCGEPFnm5uYwMTHB9evXMXLkSJibmwvWUidPN8YY7t69i5s3b8LExKTH2KY3BmVgB9xbmeH8+fP8flJSEjZs2ACdToeff/4ZYrHYIOgDgFGjRgG4F9Do9Xps2rSJT+TbG2q1GvHx8Xj22WehUChw6tQpVFVVIT09HRqNBgAMEh06OTnx53rL09MTDg4O/L5Go+mXdh+UkZEhSGpMCCHk6WJiYgKZTIYbN27g+vXrxu4OGSBWVlZwc3PrcXGG3hi0gR1jTPAvksTERERHR+PGjRtITEzEypUru1w/7vTp07CxseGXFFu1ahXEYnGPa7ne7/Lly0hPT4dSqURZWRkOHDiAffv24ebNm/12bwBQVFTUr+11Jzk5WfAksLm5Ga6urk/k2oQQQvqHubk53Nzc8PPPP6Ojo8PY3SH9zNTUFGZmZv3yJHbQBnYXL16ETCbj9x0cHPjZK/n5+fDz80NAQAC8vb0F9WQyGf+NnY+PDyoqKpCent7rwC48PNzg2KJFiwCAn8ih1Wrh7OzMn9dqtfD39+/L7RmQSCTQarWCY1qtlv+u8FGJRCLBUmaEEEKeTp0ZJIYNG2bsrpBBbFAmKC4uLsaFCxewYMGCLs+7uroiMjISycnJD23L1NQU7e3tj9SP0tJSwb5MJoNEIhE8bWtubkZFRQWCgoIe6RqdgoKCDJ7iFRYWPna7hBBCCPnlMPoTO51OB41GI0h30pnyY/Hixd3Wi4uLg6+vLyorKxEQEMAfr6+vx507d/hXsXv37kVERAR/vqWlBVeuXOH36+rqUFVVBbFYDDc3tx77ynEc4uPjkZaWhjFjxvDpTqRSKebNm8eXu3btGn788Udcu3YNHR0dfL45uVwOa2trAEBwcDBefPFFrFq1ir+fadOm4e2338bs2bORl5eHyspKQR6+zjY7v7FQq9UA7j3t6+uTvW/fCKEExYQQQshQw4woKiqKAWAAmJmZGRs5ciRTqVQsJyeHdXR08OVGjx7Ntm7dalA/JCSEhYWFMcYYKykp4dvqbE8mk7G1a9eylpYWvs6D5Tq3qKioXvVZr9ez119/nTk5OTGRSMSCg4OZWq3u9r7u30pKSgT3lJqaKqh34MAB5uXlxczNzZmPjw/75JNPBOdzc3O7bPfBdnrS1NTEALCmpqZe1yGEEEKI8fTldzctKfYL09TUhOHDh+OHH36gJ3aEEELIU6Bz4mNjYyPs7Ox6LGv0V7Hkyfr3v/8NADQzlhBCCHnK3L59mwI7IiQWiwHc+w7wYT8cvwSd/wqiJ5j30Hj8B42FEI2HEI2HEI2HUH+PB2MMt2/fhlQqfWhZCux+YToTH9rZ2dEfvvvY2trSeNyHxuM/aCyEaDyEaDyEaDyE+nM8evswZlCmOyGEEEIIIX1HgR0hhBBCyBBBgd0vjEgkQmpqKq1G8f/ReAjRePwHjYUQjYcQjYcQjYeQMceD0p0QQgghhAwR9MSOEEIIIWSIoMCOEEIIIWSIoMCOEEIIIWSIoMCOEEIIIWSIoMBuCNi+fTvc3d1hYWGBwMBAnDlzpsfy+fn5GDduHCwsLODn54dPP/1UcJ4xhpSUFDg7O8PS0hIqlQq1tbUDeQv9pj/H4qeffkJSUhL8/PzwzDPPQCqVYvHixbh+/fpA30a/6e+fjfu98sor4DgOmZmZ/dzrgTMQ43Hx4kW88MILsLOzwzPPPINnn30W165dG6hb6Ff9PR4tLS1YtWoVRo0aBUtLS3h7eyM7O3sgb6Ff9WU8/v73v2PBggVwd3fv8c9BX8d4sOjvscjIyMCzzz4LGxsbODo6Yt68eVCr1QN4B/1rIH42Or355pvgOA7x8fH901lGnmp5eXnM3Nyc5eTksL///e8sJiaGDR8+nGm12i7L/+///i8zNTVlmzdvZjU1NWzDhg1s2LBh7MKFC3yZN998k9nZ2bGPP/6YVVdXsxdeeIHJZDLW3t7+pG7rkfT3WDQ2NjKVSsX279/PLl26xMrLy9nEiRPZhAkTnuRtPbKB+NnodPjwYaZQKJhUKmVbt24d4DvpHwMxHleuXGFisZglJiayc+fOsStXrrAjR4502+ZgMhDjERMTwzw9PVlJSQmrq6tjO3bsYKampuzIkSNP6rYeWV/H48yZM2zt2rVs3759TCKRdPnnoK9tDhYDMRYhISEsNzeXffvtt6yqqor95je/YW5ubqylpWWA7+bxDcR43F/W3d2djR8/nsXFxfVLfymwe8pNnDiRvfrqq/x+R0cHk0qlLCMjo8vyCxcuZLNnzxYcCwwMZCtWrGCMMabX65lEImF/+ctf+PONjY1MJBKxffv2DcAd9J/+HouunDlzhgFg33//ff90egAN1Hj885//ZC4uLuzbb79lo0ePfmoCu4EYj8jISPZ//+//HZgOD7CBGA8fHx+2adMmQRmlUsn+9Kc/9WPPB0Zfx+N+3f05eJw2jWkgxuJB9fX1DAD7/PPPH6erT8RAjcft27fZmDFjWGFhIZs2bVq/BXb0KvYpdvfuXZw9exYqlYo/ZmJiApVKhfLy8i7rlJeXC8oDQEhICF++rq4OGo1GUMbOzg6BgYHdtjkYDMRYdKWpqQkcx2H48OH90u+BMlDjodfr8fLLLyMxMRE+Pj4D0/kBMBDjodfr8cknn8DLywshISFwdHREYGAgPv744wG7j/4yUD8fzz33HI4ePYp//etfYIyhpKQEly9fxqxZswbmRvrJo4yHMdp8Ep5Uv5uamgAAYrG439ocCAM5Hq+++ipmz55t8OfqcVFg9xS7desWOjo64OTkJDju5OQEjUbTZR2NRtNj+c7/7Uubg8FAjMWD7ty5g6SkJCxatGjQL3I9UOPx3//93zAzM8Pq1av7v9MDaCDGo76+Hi0tLXjzzTcRGhqKzz77DC+++CLmz5+Pzz//fGBupJ8M1M/Htm3b4O3tjVGjRsHc3ByhoaHYvn07pk6d2v830Y8eZTyM0eaT8CT6rdfrER8fj1//+tfw9fXtlzYHykCNR15eHs6dO4eMjIzH7aIBs35vkZAh6KeffsLChQvBGMO7775r7O4YxdmzZ/E///M/OHfuHDiOM3Z3jE6v1wMA5s6dizVr1gAA/P398eWXXyI7OxvTpk0zZveMYtu2bfjqq69w9OhRjB49GmVlZXj11VchlUr7/akEeXq9+uqr+Pbbb/HFF18YuytG8cMPPyAuLg6FhYWwsLDo9/bpid1TzMHBAaamptBqtYLjWq0WEomkyzoSiaTH8p3/25c2B4OBGItOnUHd999/j8LCwkH/tA4YmPE4ffo06uvr4ebmBjMzM5iZmeH777/HH//4R7i7uw/IffSXgRgPBwcHmJmZwdvbW1DmV7/61aCfFTsQ49He3o7XXnsNW7ZsQXh4OMaPH49Vq1YhMjISb7311sDcSD95lPEwRptPwkD3e9WqVTh+/DhKSkowatSox25voA3EeJw9exb19fVQKpX836Wff/45srKyYGZmho6OjsfqMwV2TzFzc3NMmDABRUVF/DG9Xo+ioiIEBQV1WScoKEhQHgAKCwv58jKZDBKJRFCmubkZFRUV3bY5GAzEWAD/Cepqa2tx6tQpjBgxYmBuoJ8NxHi8/PLLOH/+PKqqqvhNKpUiMTERJ0+eHLib6QcDMR7m5uZ49tlnDVI2XL58GaNHj+7nO+hfAzEeP/30E3766SeYmAh/rZiamvJPNwerRxkPY7T5JAxUvxljWLVqFT766CMUFxdDJpP1R3cH3ECMR3BwMC5cuCD4uzQgIAAvvfQSqqqqYGpq+nid7pcpGMRo8vLymEgkYh988AGrqalhy5cvZ8OHD2cajYYxxtjLL7/M1q9fz5f/3//9X2ZmZsbeeustdvHiRZaamtplupPhw4ezI0eOsPPnz7O5c+c+NelO+nMs7t69y1544QU2atQoVlVVxW7cuMFvOp3OKPfYFwPxs/Ggp2lW7ECMx+HDh9mwYcPYzp07WW1tLdu2bRszNTVlp0+ffuL311cDMR7Tpk1jPj4+rKSkhP3jH/9gubm5zMLCgr3zzjtP/P76qq/jodPp2DfffMO++eYb5uzszNauXcu++eYbVltb2+s2B6uBGIvY2FhmZ2fHSktLBX+XtrW1PfH766uBGI8H9eesWArshoBt27YxNzc3Zm5uziZOnMi++uor/ty0adNYVFSUoPyBAweYl5cXMzc3Zz4+PuyTTz4RnNfr9ez1119nTk5OTCQSseDgYKZWq5/ErTy2/hyLuro6BqDLraSk5And0ePp75+NBz1NgR1jAzMe77//PpPL5czCwoIpFAr28ccfD/Rt9Jv+Ho8bN26w6OhoJpVKmYWFBRs7dix7++23mV6vfxK389j6Mh7d/f0wbdq0Xrc5mPX3WHT3d2lubu6Tu6nHMBA/G/frz8COY4yxx3vmRwghhBBCBgP6xo4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIigwI4QQgghZIj4fymyZ8Ps4JUbAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -262,87 +217,19 @@
    "source": [
     "You can view the combined allele frequency estimates with `plotAF()`. By passing the uncombined allele frequency data we can see the individual study estimates.\n",
     "\n",
-    "The black open points are the Dirichlet mean, the coloured points are individual study estimates, coloured by population, and the black horizontal lines are the credible intervals on the combined estimate.\n",
+    "The black open points are the combined estimates made using the default model, the coloured points are individual study estimates, coloured by population. The combined estimate and credible intervals from the compound model are plotted as vertical and hoizontal black lines respectively.\n",
     "\n",
-    "Estimating the confidence intervals can take a few seconds. If `credible_interval` is not set it is not estimated or plotted."
+    "The credible intervals are taken from hdi, calculated above. This defaults to 95% but other values can be passed to `AFhdi()` and will be plotted. It is important to verify the credible intervals are reasonable but HLAfreq will print a warning if they are too different from the default estimate. See the [credible_intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb) for more details."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Fitting model with PyMc, make take a few seconds\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Auto-assigning NUTS sampler...\n",
-      "Initializing NUTS using jitter+adapt_diag...\n",
-      "Multiprocess sampling (4 chains in 4 jobs)\n",
-      "NUTS: [frac, conc]\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "<style>\n",
-       "    /* Turns off some styling */\n",
-       "    progress {\n",
-       "        /* gets rid of default border in Firefox and Opera. */\n",
-       "        border: none;\n",
-       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
-       "        background-size: auto;\n",
-       "    }\n",
-       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
-       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
-       "    }\n",
-       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
-       "        background: #F44336;\n",
-       "    }\n",
-       "</style>\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
-      "text/html": [
-       "\n",
-       "    <div>\n",
-       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      100.00% [8000/8000 00:13&lt;00:00 Sampling 4 chains, 0 divergences]\n",
-       "    </div>\n",
-       "    "
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 14 seconds.\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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02aq5Kjo79cE2bWxsStXOuHHjKG5RkbGBf//3zZa/StV2ab2w9QXuae+RmpGKRq0xPi4y/GoWudQJ8qlVLnWCfGoVdVaj7NTqnptakjp16lCrVq1S7WNqtuqDKjo7tSbl2sUmxGKhsCBwdyAqharA8zWp1uKIOmseudQqlzpBPrXKuc5qk51a3XNTS/Lzzz+XWVslqejs1Afz3hISEkza32Aw0K5dO5o3b86P33/PvfdnoAsPx8wzZ7C78swZfjh/nn3Dh2OdkIBZLU88Pv0ExSMs8RGSGMJH/36ERqXBxiz/GUMDBqKyo3iy3pM82TR/FJvI8KtZ5FInyKdWudQJ8qlV1FmNslOre25qeTA1W/VBFZ2d+mC7pck8nTdvHi+99BIz585lUr8ALNb+Rsq9aNZFR7Pq7Fn+r3kL3NPSwdwClxHPY+fq+kh9bWPfhq5xXdkXug+VWoW9uT0KhYKM7Axi0mLwsPagf93+Rb5Ocs7wq4nkUifIp1a51AnyqVXOdZZ33WUyiMvNTZ00aVKhz+fNTf3rr+LviaoKuallJTdbNe/yI6Zkq1YnL774IklJSUydOpXvvvsOT2dnomNj0RkMvOzjw6TaXqhsbXF47jls+/R55OMpFArGtRyHudKcw+GHuZtyFxSgUqio61CXcf7j8LYtu/XoBEEQBKGqKvUgrqblpkLOvWtRUVHG45w/fx5bW1vq1KmDk5MTAC+//DJeXl4sXLjQ2HbumnOpqanExMQQHByMubm58WxjSdmqNcX48eMZOXIk69ev5/bt2zjb2fFk3Xq4m5ujsrfHqn27Mk1tsDKzYkLrCQxtMJTzMefRGXR42nji7+qPWinWrxYEQRDkodT/x6tpuakAq1atyjeRIHdixZo1a4xxXaGhoQXqa926tfHfp06dYu3atfj4+BiXMykpW7UmcXBwYOzYsRV6TC8bL7xsvCr0mIIgCIJQVZRqEFcTc1MB5s6dm2/gWJjCLtWa0q/islUrS9bt2yQH7kF7/DhekZHEXLiAfd++7Lp7l5UrV/Lvv/+iVqsJCAhg4sSJmNU1I+huEDcSbmCmMqNjrY70qtNLXLYUBEEQhEpU6sQGEb2V3/79+2nTpg0WFhbUr1+/2EHuJ598gkKhKDKiqyKknThBxIwPSPrzT7LjYlFmZqA9eIjxI0bwzDPPoNfrmT9/PlOnTuXixYt07daVNxa+wZHwI6TqUolNj+X3a78z+/BsgqODK60OQRAEQZC7Ug/iQERv5bp16xYDBw6kZ8+eBAcHM3HiRF5//XV2795dYNsTJ07wzTff0LJlS5PbL2v6xERiVq5En5SEmY8Pajc39La27JMM/HTzJvNbtmTnZ4uZPHkyH3zwAd/u/hafvj6c+fIM9qn2uFi64G7ljo+tD/EZ8XwZ/CWpWamVVo8gCIIgyNlD3QUuordyrFq1Cj8/P5YsWQJAkyZNOHToEEuXLqVfv37G7VJTUxk5ciTfffcdH330kcntl7XUw4fJjonFzMsLhUJhvBz844ULtHZzY7C7B/d27MC9eTMAdl3fRcPnGxJxKILzf53nsdH/JWm4KF0Ijw9nX8g+etXpVeKxra2ty6coQRAEQZCpMpvKJ8foraNHj9LngWUz+vXrV+By6fjx4xk4cCB9+vQxaRBXXrFb6TdvIhn0SEoFkmRAMuQM4o7en7nbMvBvCPwb5hVMizj751nO/nm2wOM7KXhmtTBZWVkP3e+yIOJfaha51AnyqVUudYJ8ahV1VqPYLZBf9FZRsVrJycmkp6djaWnJunXrOH36NCdOnDD5OOUVu+UYEoJdqhZddPRDt/Gw8s5Irkxyjn+pieRSJ8inVrnUCfKpVc51VpvYLRDRWw+6e/cu77zzDoGBgWg0mpJ3uK+8YrfSHByIuX4dtYMDCnNzJINETGwMT9Wtx+noe/zVvgMOAwfi9NqrAHx7/lt2nNvBgXcO8Ngrj9H8yf+WRsk0ZBKfEc/kNpNp49amxGNX9uVUEf9Ss8ilTpBPrXKpE+RTq6izGsVugfyit4qK1bKzs8PS0pJTp04RHR1Nmzb/DXL0ej0HDhxg5cqVZGZmolIVDGkvr9gt244dSanfgMyrV1F7eqIwy3n7x7RswdC/bjL/Zgjf9u5lfC8ec3iMRV8swszGjKYDm2JhndOnTH0m8dp4mnk2o2v9rpgpq8+HU87xLzWRXOoE+dQqlzpBPrXKuc5qEbsF8oze6tSpU4HLhHljtXr37s358+fzPf/KK6/QuHFjpk2bVugArjwpLSxwmzKF6M8+I/PGDaTsbMzStDS2tmFply68e/w4fo8/Tu/evUlPTycoKAhbB1v6fNiHaCka7v9BoVKoaOLUhEltJ1WrAZwgCIIg1CQPNYgT0Vs50Vvjxo1j5cqVTJ06lVdffZWgoCA2bNjA9u3bgZzZuQ+mM1hbW+Ps7FxpqQ3mtb3wXPQpaf/+S2pwMFGXr+DdpzfjundnaEYG3333HcePH8fCwoJly5bx8ssvk2WWxeHww4SmhGKuNKeFawvaubfDXFX0JBVBEARBEMrXQw3iRPRWDj8/P7Zv386kSZNYvnw5tWvX5vvvv8+3vEhVpLSwwKZrVyw6duT4jh3YPfEEajMzvKDI5IrB9QdXaB8FQRAEQSheqQdxInqrYN/OnDljcl8q8nJvWbl06RKrVq3izJkzWFhYMHDgQEaPHl2mk0aqBF063DoIoUdz/u1cD+r3ASe/kvcVBEEQhAomYrfuGzt2LPXq1cPS0hJXV1cGDx7MlStXin0tLl68yLBhw4y1Llu2rMA2CxcupH379tja2uLm5saQIUOMl3Org+XLl9O8eXPWr1+Pr68vVlZWTJs2jcaNG5dq8FrlJUfA5jfh75lweSvcDILjq+DP1+H8H5XdO0EQBEEoQMRu3de2bVvWrFnD5cuX2b17N5IkERAQgF6vL3KftLQ06tatyyeffGK8t+5B//zzD+PHj+fYsWMEBgai0+kICAhAq9UW2W5VERgYyMSJE5k8eTJ3797ll19+YcuWLdy+fRtvb28GDhxYLeookUEPez6EqHNg55lzBs7RD5zqgUEHR1bAnaOV3UtBEARByEfEbt2XN+HB19eXjz76CH9/f27fvk29evUK3ad9+/a0b98egOnTpxe6Td7Lx5BzOdrNzY1Tp06VakHj8pKRkYFWqy10GvSiRYto06YNc+fOzZcWYW9vz48//kjLli358ccfS7xUXZzKXj8OgLCTEHUebD1BnWdpF4UCbGtBXAhc3Ag+nSqvj4IgCILwABG7VQitVsuaNWvw8/PD29vb+Livry+jR48u8d654iQlJQEYZ7wWprxitx6k0+mMkzyKY2trW+RzEyZMYMKECQ/dh4qK4youFkUZfgalPhNJrYE8twQYWdhB+Bn0aclgZlneXX0kIuam5pFLrXKpE+RTq6hTxG6ZpKxit7766iumTp2KVqulUaNGBAYG5ht01qtXDxcXF5Pbe5DBYGDixIl06dKl2CVGyit2qyqq6DiuwmJR/GLO45eqRasrPI7MLDsVBRJHdu1ErzI9eaMyyTnmpqaSS61yqRPkU6uc6xSxWyYoq9itkSNH0rdvXyIjI1m8eDHDhw/n8OHDxsisvPfpPYzx48dz4cIFDh06VOx25RW79SCdTse6devo1atXoZdT+/bti52dHX/++WeB52JiYmjevDmzZs16pDNxFXU5tbhYFMVNK1SBJ7C2sc9/OTVXYjpSrdb0GzQ05xJrFSZibmoeudQqlzpBPrWKOkXslknHLavYLXt7e+zt7WnQoAEdO3bE0dGRTZs2lUmE14QJE9i2bRsHDhwwnnksSnnFbhVGo9Hg4OBQaLuTJk1i5MiR/PHHH/nOoGZkZDBlyhTMzMx44403jO9ddVDoa1ivG5yuhyL2Ojj6gjJPkkZ6Qs73zYeiKuZWgKpGzjE3NZVcapVLnSCfWuVcp4jdKqWyWodNkiQkScp3b9rDtvPWW2+xadMm9u/fn2+QW9WNGDGCQ4cOMWbMGH744QcGDhxIUlIS//vf/4iPj+fPP//E2dm5srv56NQW0GsW/P0BJNwGtTko1ZCVlvNcy+egQUBl91IQBEEQ8hGxWx4e3Lx5k/Xr1xMQEICrqythYWF88sknWFpa8sQTTxjb6d27N0OHDjVePszKyuLSpUvGf4eHhxMcHIyNjY3xsvH48eNZu3Ytf/31F7a2tkRFRQE5Z/0sLav2TfIKhYIvv/ySfv368eWXX7J8+XIsLCx46qmneOedd2jSpElld7HsuDeFIV/DtV1wc3/OAM61ETQaAHU6VfnLqIIgCIL8iNituXPRaDQcPHiQZcuWkZCQgLu7O926dePIkSO4ubkZ9wsJCSE2Ntb4fUREBK1btzZ+v3jxYhYvXkz37t2NZwS//vproOAixHnjvKoyhULB4MGDGTxYBrFbth7QdnTOlyAIgiBUcSJ2C/D09DRpluSDNfn6+pbYr0fpd1V39+5dfv31VyIjI/Hw8ODFF1+kTp06JGQk8G/UvyRnJWNnbkd7j/Y4aYpeUqXKkKScNeHC/oXsTHDwBp/Hwax6zEgVBEEQ5EUWsVuSJDF79mxq1aqFpaUlffr04fr164Xun5mZSatWrYqM53rQl19+ia+vLxqNhscee4x///230O0kSWLAgAEl9r86kCSJ999/H19fXz7++GP27dvHwoUL8fPzY+iYoby15y2+PPMlv176lS/PfMk7Qe+w6fqmqj2gzUzNSW348zU4+Dkc+wp2zYD1L8Ldwt9TQRAEQahMsojdWrRoEStWrGDVqlUcP34ca2tr+vXrR0ZGRoG2pk6diqenp0mvw/r165k8eTJz5szh9OnT+Pv7069fP6KjC643tmzZsnzLr1Rnn376KZ988gnz5s0jIiKC8+fPExkZycvvvszm7zcTvC4YL1svvG29qW1bmyx9Fr9c+oXdd3ZXdtcLJ0nwzyK4sg3UGnCqm/Nl5wWJoRA4G2KqT96tIAiCIA8PNYjLjd3KjdyaMWMGf/31Fzt37sx3qTU3dqtu3bpMmzYNJyenQhfDc3Nzw8PDAz8/P95++238/PzyDcoGDBjARx99xNChQwvtT926dXn//feZM2eOMXZr3759uLi4IEkSy5YtY+bMmQwePJiWLVvy888/ExERUeCM2M6dO/n7779ZvHixSa/D559/zpgxY3jllVdo2rQpq1atwsrKitWrV+fbLjg4mCVLlhR4vKrRarUlfsXExLBo0SLGjRvHxIkTUSqVaLVadAYdZl3NqPtEXa5vvk5mYia6dB36DD0OCgf0mXr+PP8n8cnxJh2npK8yFXMFbu0HaxewdPhvEoPaPGfJEW0MXCi4Vp4gCIIgVKYaH7t18+ZNoqKi6NOnj3F7e3t7HnvsMY4ePWqc5HDv3j3GjBnD5s2bi0xFUCgUxgkJWVlZnDp1ivfff9/4vFKppE+fPhw9+l9YelpaGi+88AJffvmlMUe2JBUZu5X3vzY2Nibvu2rVKlatWlXk82ueXVPo49/zfaGPl1Zp47qKi0VR3DqMMlMLVm6Fx26Z28LNf9B3egdUVXutOBFzU/PIpVa51AnyqVXUKWK3TFJc7Fbukh7u7u759nF3dzc+J0kSo0ePZty4cbRr167ISRmNGjXC3t4egNjYWPR6faHtXrlyxfj9pEmT6Ny5c6lmd1Z07FZ1jER52LiuwmqtG30GX60WbXZMofuYZWtRkMzRHVvJVlXtZWFyVcf39GHIpU6QT61yqRPkU6uc6xSxWyYoLnbLFF988QUpKSn5zqoVJu/gzBRbtmwhKCiIM2fOlGq/iozdyhsVkpCQUOI+Fy5coGvXrvz6668MHDjQ+HhkaiQzj84k+nQ0hz45xJClQ3Cp+1/ObKoulSxDFvM6zcPLxuuR+17auK5iY7euSKj2H8fa3ilnkd8HJd0FRz8CBg0FxUPdgVBhRMxNzSOXWuVSJ8inVlGniN0y6bjFxW6p1Tkl3rt3j1q1ahmfv3fvHq1atQJy0iaOHj1aIOqqXbt2jBw5kp9++qlA+y4uLqhUKu7du5fv8Xv37hkvmwYFBRESElIglmrYsGF07dq1yHSJiozdytuuKfFZjz/+OB07duTTTz9l0KBBxjOTDg4ONHduzrL1y3Bt5IpXi/8GanqDnhR9Cp28OtGsdrMy739pFPoaNugJp75HkRoF9t75F/bVpYGkh2aDUZoXkqtaRck55qamkkutcqkT5FOrnOss77rL7LRCbuzWsGHDCn0+b+xWScoydsvPzw8PD498s12Tk5M5fvw4nTp1AmDFihWcPXuW4OBggoODjZfq1q9fz4IFCwo9jrm5OW3bts3XrsFgYO/evcZ2p0+fzrlz54zt5i5ZsnTpUtasKfyeserg22+/5e7du7Rq1YrPP/+cwMBAli5dyo+v/UhGdAaN/q8RsemxpGalEpsey93Uu9SxrcPLzYpO86hUGnt4fBKYWUJ8CKTFQUYSJIVBShT4dYOmMljsWBAEQahWanzslkKhYOLEiXz00Uc0aNAAPz8/Zs2ahaenJ0OGDAEo0EbuDf716tXLF1bfuHFjFi5caJwlO3nyZEaNGkW7du3o0KEDy5YtQ6vVGtMhcmO9HlSnTp1qlaH6oBYtWnDs2DE+/PBDpk+fjk6nQ61WM2zYMMZPGc918+scDD9IRnYGlmpL+vr0ZWDdgXhYmzaxo1LU7w2WjnD+dwg7kbPYr31taDwImg/LGeAJgiAIQhUii9itqVOnotVq+b//+z8SExN5/PHH2bVrFxpN6Vbiv3r1KklJScbvn3vuOWJiYpg9ezZRUVG0atWKXbt2FZjsUBM1atSItWvX8s033xAXF4ezszO2trYAdKUrLzR5Aa1Oi7WZNRp1NUk88GqT85WRBHodaBxAVaZ3HAiCIAhCmZFF7JZCoWDevHnMmzfPpO2LitMq7LEJEyYwYcIEk/tSpVMLHoKtra1x8JaXRq2pPoO3B2nsy6ddSYLoSznrzlnYgkdLUBV9v0SGTs/FiCQydQY87DX4uVhX2wWjJUniVtItotOjsVRb0sSpCeYlLNeSnJxMYGAgWq2Wpk2b0rZt22pbv1D9SAYDmdevo4+PR2lji6ZJYxRq8UedULXIInZr48aNBAQE4OzsXGyc1tGjR+nVqxfW1tbY2dnRrVu3Eu/N279/P23atMHCwoL69esXGOAuXLiQ9u3bY2tri5ubG0OGDOHqVbH6v+xEBMOmsbBpHOyYAn+9BRtehmt/F9hUkiT+Cg7n/34+yfsbzzPrrwu8ve4MH2y+wO3YMl7ouALcTLzJ3KNzmX5wOh8f+5i5R+Yycd9E/r79d6F/1BgMBmbPno2XlxfPPPMMo0aNon379rRr167UM70F4WGknz9PxNSpREyfTtT8j4ic+QHhEyeRevhwZXdNEPKRReyWVqvl8ccf59NPPy2ypqNHj9K/f38CAgL4999/OXHiBBMmTCj28vCtW7cYOHAgPXv2JDg4mIkTJ/L666+ze/d/8VL//PMP48eP59ixYwQGBqLT6QgICCj71AGh6oq6ALveh/DTYGGXkwJh7QLxN2HfR3A1/2diw8m7fLU/hJiUTNxtNdRxssLSTMXRkDjmbLlIROLDTfqpDHeT7/Lx8Y85de8UVmoratvWxsXShShtFN+c+4btt7YX2GfSpEksWLCACRMmcPv2bdLT09mxYweSJNGzZ89SL/UjCKWRfuEi9z5eSPrFS6hs7TCrXRuVgyOZt24Rs3QZqQcPVXYXBcHooc4N58ZuAcborY4dO9K7d29+/PFH44K+ubFbkLPw76JFiwgMDGTAgAH52nNzczMub/H222+zYsUKTp8+Te/evYGc2K0H98mrbt26TJo0iY4dOxpjtxwdHQkICADgpZdeAoq+xAs5/+N4++23mT59uvGx3Hv1irJq1Sr8/PxYsmQJAE2aNOHQoUMsXbqUfv36AfkvH0PO5Wg3NzdOnTpVqgWNheol3yD98HcQHwmOdUFSQKYBMAPL2jlr0B38Btw7gJmG2NRM1h66jjJbj6udBvSZ6PVgqQBPawW3ouJYf+Q6/9e9XqHH1el0ZGRkoNVqq8SU/vXn1xMWF4a3rTdKvRK9Xo8SJa4qV6LTo1l3bh3tHNtha55zSf7mzZt88cUXfPzxx7z11lsA6PV6unXrxvbt2+ncuTNz5szhm2++qVJ1loXSrn0olD1JkkhYvw59YgLmdXyMl+8VlpaY1a6NLiyMhLVrsX6sA4pi0ocEoaLU+NgtU0RHR3P8+HFGjhxJ586dCQkJoXHjxixYsIDHH3/cuF2PHj3w9fU1XjI9evRovjgvgH79+jFx4sQij5U7McLJyanIbSordqsmq+haC48wO1v0DmP+Mrntg8DkEreqPv7H/wo89v777xe5HNHt27fZsGFDeXerwhUVJSeXz2lVqFN3N4yMi5dQOjohIRW43K90dSEr7C4pZ89h2cr/4Y9TBWqtCKJOEbtlkuJitxwdHUvc/+bNmwDMnTuXxYsX06pVK37++Wd69+7NhQsXaNCgAZCzNEjeBYOjoqIKjd1KTk4mPT0dS8v8y1IYDAYmTpxIly5daN68eZH9EbFb5UdOtQrVS0lRcnL52a3MOi3CwvCIi0NnZwvphcQlSRLmCYncCtqLNiL8kY8n3tOaRcRulUPslimDuNwJGWPHjjWu8da6dWv27t3L6tWrWbhwIQA///yzSf0pyvjx47lw4QKHDhV/T0VlxW7VZBVdqzHCLDkK1eYxoDQrfNarPhNFajT6fh8j1e7A35fu8eX+EDwdLFEpC87EjE3JxMpczdcvtMLCTFXgeZ1OR1BQEL169ar09zQlK4UpB6eQbcjG0aLg5zBbyuZe2j3G+4+ni2cXABYvXsyKFSu4dOlSoWczly1bxieffMLVq1c5duxYlaizrBR1OVUun9OqUKcuLIyooCCwsEBVyKx7Q0YGBr2Bun36oGnZ8uGPUwVqrQiiThG7ZdJxi4vdMkXu2bUH+9WkSRNCQ0OL3M/Dw6PQ2C07O7sCZ+EmTJjAtm3bOHDgQL4FhAtTWbFbclBRtRojzBwcoEFnuB4Ils75s1clCRIjwaMuNO4BanP6+Fux4VwcyVl6POzyL9GiN0hkKuDp1t64uzoXelydTodGo8HBwaHS31MHHOhWrxs7bu7AzMoM5QO5swnaBDycPOhevzs25jkDtjFjxrBw4UJ+/vlnZsyYkW/7+Ph4Vq9ezXPPPYenp2eVqbOiyOVzWpl1qn19sWzRgrRjx1HY2KLIM7FNkiQMsXGY+/pi4+9fJsuNiPe0ZhGxW/eVZeyWKXx9ffH09Cyw9Me1a9fw8fEpcr9OnTrlm0ULOadTc2O3IOeDP2HCBDZt2kRQUFC1TmoQHlK7V8GuVs5s1IwkMGRDlhYSboOZBh4bC+qce0WdrM15oUMd9AaJsIQ00nV6svUGEtOyuBOvpZ6rNYNbeRV/vCpkcP3B1LatTWhyKMmZyWQbsknPTicsJQwFCp5r9JxxAAfg4+PDlClT+OCDD3jrrbe4ePEicXFxbNiwga5du5KWlsbs2bMrsSKhJlMoFDiOGIHa1RVdaCj6lBSk7GwMWi260FCU1lY4vfSSWC9OqDJqfOwW5PwFHxoaSkREBIBxsJYbi6VQKJgyZQpz5szB39+fVq1a8dNPP3HlyhX++OMPYzsvv/wyXl5exsur48aNY+XKlUydOpVXX32VoKAgNmzYwPbt/y2bMH78eNauXctff/2Fra0tUVFRANjb2xc4WyfUUK6NYMBncPwbiAyG9IScy6vuTXMGeH757/8c2toLK3M1f5y6S1hCOnqDhJW5it6N3XnlcT/c7arPIspeNl580PEDfr30K2djzpKsTUalVOFr78vTDZ6mq1fXAvssXLgQJycnFi1axMqVK42Pd+vWjT/++IN69erV+BulhcqjadQI9w9mEP/Lr2RevowuKRGFmRmapk1wfP55rNq3r+wuCsJ/pFIaNWqUBEiApFarJVdXV6lPnz7S6tWrJb1eb9zOx8dHWrp0aYH9+/XrJw0YMECSJEnat2+fsa3c9vz8/KT33ntPSk1NNe7z4Ha5X6NGjTKpz2vWrCl0/zlz5uTbbuHChVLt2rUlKysrqVOnTtLBgwfzPd+9e/cCx9y3b5/UqlUrydzcXKpbt660Zs2afM8XdlygwHbFSUpKkgApKSnJ5H1MkZWVJW3evFnKysoq03aroipRq8EgSbE3JOnOMUmKuihJeT4vhcnU6aXzYYnSydtxUnhCmkmHqBJ1FiEsJUw6c++MdDnusqTT60rcPj09Xdq9e7f0559/SpcuXcr3XFWus6zJpdaqVqfBYJAybt6UtKdOS+lXr0qGEj6vpVHVai0vos7y+/93LlnEbo0ePZrRo0eXuN306dPzrRP3oMIu1fbo0aPYVeQfpd+VJTIykri4OLy8vFBZ2pCcrsPe0gxbTc2/p6FcKRTgXC/nywTmaiXNvcopAqwSeNl44WVj+qVgjUZjXOtRECqaQqHAws8PxB0wQhUmLuwLRgcOHGDOnDnGwapKbUYt/+40eOJ1HGt583h9F55pWxtvp7Jf5kQQBEEQhNIR2al59svbF4VCwbhx40p8PX7//XcaN26MRqOhRYsWxa71NG7cOBQKBcuWLSux3Yq2fft2evfuTVpaGku++p6Aad/iO2AMcTfPc2TZGyRH3WXL2Qg+2HSeW9Uwv1MQBEEQahqRnZrHmDFjiIyMNH4tWrSo2O2PHDnCiBEjeO211zhz5gxDhgxhyJAhXLhwocC2mzZt4tixY3h6ehbbZmXQ6XSMGTOGfv36cejQIWLc25Pl0oCuQ0YxZO7PmGusuLblK3ycrLibkMaaw7cqu8uCIAiCIHsiOzUPKysrY39NsXz5cvr378+UKVMAmD9/PoGBgaxcuZJVq1YZtwsPD+ett95i9+7dDBw40OT2K8rGjRuJjIxk1qxZXAmP50xIFI7mKvS6DNQWGpr2fZ5/f1tKakwY9hb2nLgeyZVQd7ydTb+sKnIhBUEQBKFsiezUPP73v//x66+/4uHhwZNPPsmsWbPyxVz5+voyevRo5s6dC+Rkp+ZNVoCc7NS8l3sNBgMvvfQSU6ZMoVmzZib1o6KzU3MHuR07dix2+z+n/7cG4K4ppTtWUbmQFUVk+NUscqkT5FOrXOoE+dQq6hTZqSZ51OxUgBdeeAEfHx88PT05d+4c06ZN4+rVq2zcuNG4Tb169XBxcTF+X1R2au5acACffvoparWat99+2+R6Kjo7tSKUlAtZUeSc4VcTyaVOkE+tcqkT5FOrnOsU2akmeNTsVCDfmbsWLVpQq1YtevfuTUhICPXq5SwJ8WA6Q0lOnTrF8uXLOX36dL7XpSQVnZ164cIFWrduzfTp0xn/9kQm/36OqKR0ajlYIkkS/3z9ASkxEQyavYbIxAy8naxY/EwLzFSm31JZ2ZdTRYZfzSKXOkE+tcqlTpBPraJOkZ1q0nEfNTu1MLmXc2/cuGEcxD2oqOzU3PvqDh48SHR0dL5UCb1ez7vvvsuyZcuKvEevorNTGzZsyPjx4/n444+xt7fnma6D+fZIBBHRcYTt/Ynw80fpNvYjErJUaKxseLFrQ1ydncq8HxVBzhl+NZFc6gT51CqXOkE+tcq5zvKuu8wGcbnZqZMmTSr0+bzZqX/99VexbVV0dmphcpchqVWrVpHb5GanTpw40fhY3uzUl156iT59+uTbp1+/frz00ku88sorZdLPsvLZZ5+RnZ3N1KlT0WhmY+PgTExUBEq1GY2fmYxZgy7YWZrxYkcf+jRxq+zuCoIgCILsiexUDw9CQkJYu3YtTzzxBM7Ozpw7d45JkybRrVs3WrZsaWynd+/eDB06lAkTJhjr6d69O0uWLGHgwIGsW7eOkydPGte5c3Z2xtnZOV9fzMzM8PDwoFGjRiX2uyKp1Wq++OILpk6dyvr164mLi6OWtw8+7fqgU2lwsDTjsbpOIrVBEARBEKqIhxrE7dq1i1q1aqFWq3F0dMTf358VK1YwatQolMqi75Nq2rQpAQEBzJ49O9+N7rkDGrVajbe3N2PHjjXOAAU4efIkPXv2NH6fe7/YqFGjTIoA27JlS74zX88//zwAc+bMYe7cuZibm7Nnzx6WLVuGVqvF29ubYcOGMXPmzHzthISEEBsba/y+c+fOrF27lpkzZzJjxgwaNGjA5s2bad68eYl9qqq8vb157733KrsbgiAIgiCUQGSnkjNw+eeff0psp7Cann32WZ599lmT+1LSWnWCICt6HdzYC1e3Q/xtsLCB+n2g8UCwNX3NRqHqSM3MZu/le+y5fI/YlCxcbM3p08Sd3k3csbGomkmPBw8eZOnSpezZswe9Xk+nTp146623GDx4cGV3rVxk6bM4GH6Q/aH7idBGYGtuS1evrvSs0xMnTfW83/lhZFy7RkrgHtJPn0aSJCybN8O2Tx8s81yBq+pE7Fae/co6dkun0zFt2jRatGiBtbU1np6evPzyy8bLuoIga9mZsPdD2DMXQo9DViokhsKxr2DLBIi9Xtk9FEopXpvFrM0XWLH3OlejUtBmZnM1KoUVe68za/MF4rWVu15kYVatWkX37t25fv0606dPZ968eaSnpzNkyBCmTZtW2d0rc+nZ6Sw5uYQvTn/BudhzaHVa7qbc5ceLPzL78GzCUsIqu4sVImXfPiJnziJp21b0CQkYkpJICdxD1IcfklTCfftViYjdyqOsY7fS0tI4ffo0s2bN4vTp02zcuJGrV6/y1FNPFduuIMjChT/h2m6wcgYnP7BxA/va4OgH8bdg38dg0Fd2L4VSWH3oFsF3E/C0t8Tb0QpXWwu8Ha3wtLck+G4Cqw9Vrci+K1euMH78eCZMmMDZs2eZMWMG7777LocPH2bp0qUsWrQo39WjmmBryFaORBzB2dIZb1tvXCxdqGVdCy8bL24n32bV2VWPdOWrOtCFhxP37XdIGRmY1/FB7eaG2tUVcx8fQEH8L7+QcflyZXfTJCJ2K4+yjt2yt7cvsPjfypUr6dChA6GhoSZNyhCEGkmvg0t/gco85xJqXkoV2HpCzFUIPwXeHSqkS1qttkKOU1o6nY6MjAy0Wm2VXqYhOjmD/RfvYqMEhT4TXZ7xtwKwUer55+JdhrV0wc1OU2D/yqjziy++wMnJiblz5xZYEeH111/np59+Yvny5XTt2rVMj1tZ72lGdgY7r+5Ena1GrVMXSBNwUDhwMeIiZ8LO0Mjpv8l3lb3OZ1lLPXAAfUICZnXqFFjDVeXiQlboHVKC9qFp0qSSemg6EbuVR3nEbj0oKSkJhUJhHLQWpqJjt2p6JArIp9ZqU2dyBKrkKDC3hTy3YRipNaDPwhB9DcmjdYGny6NOGxubkjcSHtm2dyu7BwU9uIrAg+T2s7GZzfm+f9jYxKr6+yjtylUklQpJAZJU8PePwsKC9MuXTe63iN2qwbFbeWVkZDBt2jRGjBhRbPJCRcduySUSBeRTa1Wv00KXyGPJSegVaWSrClkTUpKwzkrl6rnzhIfZFtlOVa9TEGqCR41NrGqfU5fwMKyTk9FFF34WVJ2YRJaFBWdKWbeI3aphsVt56XQ6hg8fjiRJfP3118VuW9GxWzU9EgXkU2u1qVOSUG49jCLiDDgWsnh0RhJku+E/YBT+zg0KPF0edSYkJJRJO2VNp9MRFBREr169qvR7mpqZzcT150jJ0OFqVzBxJiY5E1uNGcuea1noLNXKqHPZsmV88sknXLhwId8f6JBz9ql169b07duXZcuWlelxK+s91Rv0zD02l1vJt6hlVXAh++SsZPSSno86f4SH9X+3Fj3s5dSq+vsoRakk/suvUDs5oVDn/1mUDAay09JxePJJ2jzxhEntiditGhq7lSt3AHfnzh2CgoJKHIhVdOyWXCJRQD61Vos6/Z+D6Eugjc6Z1KC4P88qSwvpcdCwH0r3JlBM7nBZ1lncLQ6VSafTodFocHBwqNLvqQMwtEM9Vh++RbrBHHtLNQqFAkmSSErPJlsFQzv4UdvdpdD9K6POCRMmsGLFCl555RU2bNhgTOhJTEzkrbfeIjY2lvfee6/MfzYq8z0d2nwoK8+sJFWZipPGyXjiRavTotVr6efTj8Zejcv0mFXt95F99+5ot20jK/QuZp6eKO73TcrOJjsyEjN3d+x79y51nysjduuhZqcWJjd2a9iwYYU+nzd2qyTVLXYrr7yxW/DfAO769evs2bOnxHsvBEE26vWCTm+CUg3xNyE+BOJuQFoc+HaDblOLHcAJVc/w9t485e9JRraeW3Fp3I7TcisujYxsPU/5ezK8vXdldzEfFxcXtm/fzqVLl6hTpw79+vXjqaeewsvLiy1btrBu3bpqvXh7YXp69+S5Rs8BcCflDqHJodxJvkNyVjJdPLvwaotXK7mH5U9lZ4fblCmY+/igi4oi8/Ztsm7fRhcejtrNDbd3J2NWzP/7qxIRu1WOsVs6nY5nnnmG06dPs23bNvR6vfF+OScnp2IneQhCjadQQKsXwKcLhOyFpHAwtwafzuDVDlRVc2FYoWhmKiVv925AQDMPDt+IJUGbhaO1OV3qu9DYw7bATMCqoFOnToSEhPDTTz8RGBiITqdj+vTpvP7668X+EV9dKRQKnmv8HJ08O3Ek4gjRadHYmNvQzr0dzZyboVKqKruLFcKifn28lixGe+wYGZevIBn0aOrXx7pLF1T29pXdPdNJpTRq1CgJkABJrVZLrq6uUp8+faTVq1dLer3euJ2Pj4+0dOnSAvv369dPGjBggCRJkrRv3z5jW7nt+fn5Se+9956Umppq3OfB7XK/Ro0aZVKf16xZU+j+c+bMkSRJkkJDQ6Vu3bpJTk5OkoWFhVS/fn1pypQpUlJSUr52fHx8jPvk2rBhg9SwYUPJ3NxcatasmbR9+3bjc7du3Sr0uIC0b98+k/ouSZKUlJQkAQX686iysrKkzZs3S1lZWWXablUkl1pFnTWPXGqVS52SJJ9aRZ3l9//vXCJ2i/KL3fL19a3xiyYKMpCdBaFH4PYhyEwBhzo50ViujUrel5wJT7eSbnEo/BAxUTepcymO9OAYdp4L4bZWi72nJ8+OGMGIESMeavZ1YloWB67Hcj4sEYDGHnZ0b+SKi03B+0oFQRBqEhG7lWe/so7dMvXYglBlpcXDtkmwcxpc3AQ398PJ1bBpLPz7PZTwR4okSay/up4Zh2ZwdO8v1P98CxsW/sao1es5cOE8HklJaC9dYsyYMbRu3ZrQ0NBSde9iRDJv/3aG5XuuEXQlmn1Xovly/w3eWnuak7fjH6FwQRCEqk/EbuVR1rFbpTm2IFQ5kgT7P4HQo2DjDs71wdEXnOoBypzB3LXdxTbxT9g/bLi6AZuUbIbu1XLoeix/RMYxpqUvSwOa8naXJvzYujWBTz5J1v28SlPPXqfqYPHf1wlLSMfb0QpfZ2t8nK2p42hFTGoWn+2+Snjiw02QEgRBqA5E7FYeZR27VZpjCzVHZcY3lWmcT/RVuHEYzJxAbwb6//5AQ+0IqXfg5G/g9Xihs0gNkoHNlzaTlZ5F00tKlDFa1kbE0MnTmf5+tdAbsrmXnoC9Y0PcomL5ZMQLPL/oU3bs2FHoGfUH6zx7L5PQpHi8Ha0x6DLIu+66hxXcjUtkx+lbvPCYz6O9DpWkpkUdCYJQ9kTsVh4VEbtlChG7VfYqslZ5RfScAn4ucavtef4doc1g2F9H8zxy/yz63j0ADBo0qMx6dwAo/W+CqiE36kgun1O51AnyqVXUKWK3TFJdYrdMJWK3yo+cahWqtwfvr5XLz65c6gT51CrnOkXslgmqQ+xWaYjYrbJXkbVWZnxTWcb5KCKDUe6aBhp7MCvk0l5yODjUQT9kVc6CvQ/2xaBj5uGZRGgj6HMqm8aHwxlx+grtazky1r8ueoOebCmb+nb1sbgXT2j7Djz5yUJ++eWXEs/G6XQ6PvptH6dTrPF2skL5wOVcSZIIjU9nqL8nrz7u+ygvQ6XJvZwql8+pXOoE+dQq6hSxWyYdt6rHbpWWiN0qPxVRa2XGN5VpnI9dN7jsD+GnwNY2/0AtMxnMgXbDwanwGCWAQU0H8f3577npb0+LCwkM9XTl59uRdPFyppmLJS5mdjilZpFia8e8nTuoU6cOzz//PGp18b+adDodrT0sCFM7EJeRjZeDpfEPSEmSiErOxMnBjqc61MPBwfbRXocqQi6fU7nUCfKpVc51ititUqpqsVuCUG0pldBzBrg0hIQ7kBgKKVE5EVnpidDkSWg2tNgm+vv1p3ed3ty1zWJXN2uerutKewcb5hy+zKcHb7AzOIwPL16k555AQu7eZePGjSUO4HI5WsD4HnWxtlBzKy6NyKR0opIyuB2XhplKwbhu9ajvVjMGcIIgCIURsVvlGLtlyrEFoUpz9IXBX8K1XXBjb85iv46+0GgA+HYtMRrLTGnGm63epL1He/Z77OdInauMaetDwOFwtt64y0+RUdg6OvJ/b77JhAkT8PYuXbZm1wYu+LraEnjpHifvJCBJEv7eDgQ09aCRhxjACYJQw5U24kHEbs3J91hxsVumHNsUInbr0cmlVlFnzSOXWuVSpyTJp1ZRp4jdKtV2Rams2C1Tjl0dSJLE0aNH2bJlC+np6fj7+/P888+XOFM2K9vAydvx3IlPQ6VU4F/bgYbuNlUyBFsQBEEQqhsRu/UASZIYMGBAiccBuHjxIsOGDTPWumzZskK3+/LLL/H19UWj0fDYY4/x77//FttuVRIbG0vPnj3p0qULP//8M4GBgbz++uvUrl2b7du3F7nfxYgkxv/vNHO2XOSHgzdZtT+EyRuCmbf1EklpNXvNIEEQBEGoCCJ26wHLli0z+UxRWloadevW5ZNPPiny/rb169czefJk5syZw+nTp/H396dfv35ER0ebdIzKZDAYeOqpp7h06RJbt24lLCyMS5cuERISQteuXXn66ac5efJkgf3uxqexYPtlbsam4m5ngY+zNb7OVlibq9h/LYZFu6+gNzz8mVVBEARBEETsVj7BwcEsWbKEkydPFjsrNVf79u1p3749ANOnTy90m88//5wxY8bwyiuvALBq1Sq2b9/O6tWri9ynohUV0bR3716OHj3K1q1b6dmzp3HGsJubGz/++COPPfYYCxYs4Ndff82335aTtwiLSaCOkxVKfRY6fc7jGgU4mxs4fi2C49cc8fd2FNFCgiAIgvCQROzWfWlpabzwwgt8+eWXRZ5VezB2qyRZWVmcOnUq37IqSqWSPn36cPTo0SL3q+jYrZIWRC5sHb5c169ff6iYqb33x6+50ULlTcS/1CxyqRPkU6tc6gT51CrqFLFbJimL2K1JkybRuXNnBg8eXOQ2D8ZulSQ2Nha9Xl9oNNeVK1eK3K+iY7cq04PRQuVNzvEvNZFc6gT51CqXOkE+tcq5ThG7ZYJHjd3asmULQUFBnDlzptjtamrsVnR0dKGXUz/77DOWL1/OpUuXCj3u22+/bVzkOe/7PnPzRS5GJOPlZFlgH4NBIjwxnVe7+DLY37PCLqeK+JeaRS51gnxqlUudIJ9aRZ0idsuk4z5q7FZQUBAhISEF4pKGDRtG165dHzoFwsXFBZVKVeporoqO3SoqounNN99k0aJFLFmypMCEjxMnTvD7778zc+bMAgPlp9rX49rfV9EpzLGx+O9HTJIkopIzcHF0YECbujjYasq8lpLIOf6lJpJLnSCfWuVSJ8inVjnXKWK3SulhBlzTp0/n3LlzBAcHG78Ali5dypo1ax6qHwDm5ua0bds23xk8g8HA3r17q0U0l5eXF0uXLmXFihX07t2btWvXsmvXLiZOnEiPHj1o1aoVkyZNKrBfj0Zu9GjkRpw2i7CENJIzdCSkZRnXi3v9cT/cKmEAJwiCIAg1iYjdyvP1oDp16uQ7s/hg7FZWVhaXLl0y/js8PJzg4GBsbGyMl40nT57MqFGjaNeuHR06dGDZsmVotVrjbNWqLjcK6ZNPPmHkyJFAzhnGt99+m5kzZxZ6j565Wsl7AY1oWsuOnRciiUrKQKlQ0LmeC0+18qS9r1NFlyEIgiAINc5DDeJ27dpFrVq1UKvVODo64u/vz4oVKxg1ahRKZdEn95o2bUpAQACzZ8/Od0N7o0aNcjqjVuPt7c3YsWPzzQA9efIkPXv2NH6fe7/YqFGjTEqP2LJlS75B0/PPPw/AnDlzTJ5pChASEkJsbKzx+4iICFq3bm38fvHixSxevJju3bsbzwg+99xzxMTEMHv2bKKiomjVqhW7du0qMNmhKhs8eDCDBw82DrZr1apV4ilic7WSIa29GNSyFknpOtQqJfaWNf90uiAIgiBUFBG7VYTCjvdgTb6+vib1a8KECcazd9WJ3iBxOTKZpHQdDskx1MlMwsbcDKWTM5h4nV+tUpKeGMOBAweQJIlOnTpRt27dQrc1SAauJVwjMTMRW3NbGjk2Qq0s09s2S5alhajzkJ0JDt7gVHhfBUEQBKGyiditB5Qmdgvg999/p3Hjxmg0Glq0aFFgyYy8r1fuV//+/Utst7IdvxnHW7+dYf6P/3Bm+lzC3pnEuSkfcPP9mYSNH0/C+vVIedI5CpOUlMSIESPw9fVl5MiRvPjii9SvX5/BgwcTExOTb9vg6GCmHZjGzEMz+fjYx8w+PJupB6ZyIupEeZb5H4MegtfCuhdg60TY8R788SrsmAKJoRXTB0EQBEEoBRG79YDSxG4dOXKEESNG8Nprr3HmzBmGDBnCkCFDuHDhQr7tcl+v3K/ffvvNpPYry/GbcXy88zJhtyMYfnQDrcMvgJkZEZaO3JCsSI1LIP7nX4grZtJHVlYWTzzxBDt37mT58uXEx8eTlJTE999/z/Hjx+nVqxepqalAzgBu8cnFXIm/gp25Hd623jhYOBCSEMLnpz6vmIHciR/g8HJIiwe7WuDoCyoLCAnKGcilRJV/HwRBEAShFETsVh6ljd1avnw5/fv3Z8qUKQDMnz+fwMBAVq5cyapVqwp9vao6vUHi56N3SM3I5snoS3jEh5Nk74pBpYbsbJKzDVwzWNDQ0kDG9u2ounTB3MenQDsbNmzgyJEj7Nmzh44dOxoff+6552jZsiUdO3bkm2++YezYsfwS/AtxSXF423ijyFaQnZ2NGjXuanfCk8P5+czPNHy84SNdWtXpdGRkZBQeMZYUDif+B5IGLF2wVt0/jqUDWNhA3A24uAk6mrbkjSAIgiBUBBG7dd/DxG4dPXo036K8AP369StwGXb//v24ubnh6OhIr169+Oijj3B2di6yLxUdu5W3zUuRyYTEpOBibUa9G6fRqczQq1SAxPC//yjYyF9/FXuMPn36FPnce++9x3vvvWdSX1ey0qTtyoL+l2fyfKcEtRVc2YG+9Wio6Hv0SknE3NQ8cqlVLnWCfGoVdYrYLZNUVuxWVFRUoZFaUVH/XXrr378/Tz/9NH5+foSEhDBjxgwGDBjA0aNHUalUhR6nomO38kaFXE9SkJCoRGWejSolkQwUFZZvWlVER0fn+94sOx1Fipaj2/8iW1UwhaIqknPMTU0ll1rlUifIp1Y51ylit0xQlWO3cpczAWjRogUtW7akXr167N+/33i5+EEVHbuVNyrkSlQKe+PPY6NRkW3niF1SLLr7Z083BAxDb5DINkg0cbfBLDoS+xdewP7poQXaHj58OMnJyflmI+f1wgsvEBMTw3d/fMeHxz/EUm2JtbpgBFe6Pp2UrBQ+6PABDR0bPlKtQUFB9OrVq8DlVMXFP1Ee/QIcfAAl1poHPhYpkWDlRMDAwdXiTJzcY25qGrnUKpc6QT61ijpF7JZJx62s2C0PD49SR2rVrVsXFxcXbty4UeQgrqJjt/K228zLkfrutlyKSOZGg7Z0OL4DlV6PQaVGozYjPUuPq7UZjtmZKBwcqNWnN+YPvG4AY8aMYfjw4Zw5cybfGn+Qc+/h7t27+eqrr/Cv40+zu804G3MWRyvHfH8ESJJEVEoUjT0a0863HUrFwweM6HQ6NBpN4RFjLZ6Ay7+BIQlsHli/T6+D7HRo8iRKi+pxFg7kHXNTU8mlVrnUCfKpVc51ititUqrI2K1OnToVODsXGBhYbKRWWFgYcXFxJk2cqAxKpYLRnf2wtzRjr2sTIly8sUuKwVybTGZGFpaSntr6FKS0NOwGDcK8iMSMoUOH0rNnT5588kkWLVpkTMzIjfBq3bo1L7/8MgqFghFNRuCocSQ0JZRUXSrZhmy0Oi2hKaHYW9gzssnIRxrAlciuFrR6MWdtuKS7oEsHfXbOTNXEO+DaGJoOKb/jC4IgCMJDELFbjxC79c4779C9e3eWLFnCwIEDWbduHSdPnjSuc5eamsqHH37IsGHD8PDwICQkhKlTp1K/fn369etXYr8rS1sfR2YNasrPR+/wh+o5OgXvoUnEFWplJeNgY4GtZy3sBw3CrpAzoLnUajVbt25l4sSJzJ49m2nTphkfHz58OF9++SWWljlntpo5N2Nah2n8dvm3nMV+MxIxU5nR3KU5zzd+Hn9X/wooehRobOHsekgOy1k3ztwaGg3MmZVq41r+fRAEQRCEUhCxW48Qu9W5c2fWrl3LzJkzmTFjBg0aNGDz5s00b94cyDmjeO7cOX766ScSExPx9PQkICCA+fPnF3q5tCppXceRVt4OhMTUIym9I3baZLwyElCYm2PRoD5KE/pvbW3Nd999x8KFCzly5AiSJNGhQ4dCz0I2c27G/C7zuZ18m6TMJOzM7fCz9zN5zb5HplBA82HQ+EmIvgT6LLCvDXaeFXN8QRAEQSglEbtVBFNitwCeffZZnn322ULbsLS0ZPfu3aU6blWiUCio72Z7/zsnwPeh2nFxceGpp54y6Xh+9n4lbkd2FmijcyYZ2LjnDMDKitocPFsBoNVpSUqNwNrMGnW2mtu3b2NtbY2Pj49xcKnTG4hJyUSpAGedFrKyUDk7mzTIFQRBEIRHUbWn2glCXroMuPAHXNoCqfdAoQTXRtDiGajXu8wGc/e099h8YzNHIo6QFJ/Epf9d4s7+O2Sl5yy10qpVK6ZNfx/zBp3ZcT4KzdULtLl6jLqJYThqVDi4O2Pbuzf2gwejsrEpkz4JgiAIwoNEduoDyjo7Na9x48ahUChYtmxZie0KD8jOgr3zcqKxksNz7ldTW0D4aQicC2fLJsosMjWS+cfmszVkKymJKfwz4x/uHLqDz1M+PLH4CVb+vBJ3d3dGPP8c73/0GbbBxxlyeD31I66Smi1xJ10iNiyGhF9/5d6Cj9GnasukX4IgCILwIJGd+oDyyE4F2LRpE8eOHcPTU9xj9VBu7IGQvWDjlnOvmoUtaOzByQ+Uqpzs0zIIql93dR23km/hbevNrU23SItL45kVz9D39b4o6yq563OX6ct+wvvxp7mx5SseO70dc302yY7uYGNHtrklt5VWZDm5kh4cTPLOogf1giAIgvAoRHZqHuWVnRoeHs5bb73F7t27GThwYIntypVWW8xZq+DNkKkHSw1kZOd/Tu0ECbfg/A5o81KhuxebnXpfTFoMR28fxVZhS3ZaNpd3XaZxQGNsXGzIzsjGQeHAlagrJN09iHeP54g8tpW9t67Qv1ErJL0eAAlI1+kJT1fhoVQSvXMnZgEBKNQVc+eCKXUWxdq64GLLgiAIQtUlslPvK6/sVIPBwEsvvcSUKVNo1qyZSX2pzOzUymRj0v1jp4p57o37X2Xn3KZznNt07oFH/8uL/f7uLb6/e6v4RopZa7AqqU7xalXtZ7c8yaVWudQJ8qlV1CmyU01SlbNTP/30U9RqNW+//bbJ9VRmdqogX8Xdz1lVyelnVy61yqVOkE+tcq5TZKeaoKpmp546dYrly5dz+vTpUq13VpnZqZUpISGhyOeUZ35GcfKHnHxThSr/kzotpCdi6LcQyattofsXl52ayyAZ+PDYh1xPvI6XtRd/L/iblHspDFkyBJWZiuj0aOwt7HncbiJLv/uDK+sW8rl/e+rZO5GpyTmLqJdylh1p4GqFVUwUNgF9cRo79uFekIdgSp1FqU6XU6vaz255kkutcqkT5FOrqFNkp5p03KqanXrw4EGio6PzpUro9Xreffddli1bVuQ9epWZnVqZHnz982k3HMIP5Nz7ZusJ5lYgSZCRBNlx0LA7NOmRM8mhEMVmp+bxvP/zLDu1jDhDHG1GtmHLe1sI+iyIJqOboKmlYUjDIdw7fJaQzStwavwYmlbdcbp2ggxlBqkW1kgGCU8LBS5JCZh5euLx7HAsiqurjJlaZ01RVX52K4JcapVLnSCfWuVcZ3nXXWaDuNzs1EmTJhX6fN7s1L/++qvQbXJVRnbqg5d5W7RowdKlSwsdIObKzU6dOHGi8bG82akvvfQSffr0ybdPv379eOmll/IlSAgmsPWA/gth30KIvQKpUTmDOAsbaNgfuk8tcgBXGp08O5Genc7ay2uJrRNLu2ntCF4RzJ037uDq5cq+1H0kJSXRb+BT1Ht2Gjti0knJlmh+5zwO6dFozNU4m1tg4euLyxvjsKhrwuLFgiAIgvAQRHZqOWanOjs74+zsnK9NMzMzPDw8jFFjQim4NIBh3+WsDRcfkpPY4NkanOuV6WF61elFx1odOXnvJAnNE7B4yYKwo2HcunYLKysrhg4dStOmTTEYJM6HJxHSqxFSfAyesbdws1Bi5uWJVatWKIqZxCMIgiAIj0pkp5ZjdqpQDpQq8G6f81WOrMys6FY7z+SahoV0RanA39sBf28HoDbQulz7JAiCIAh5iezUIpRFdmphSlqrrjKFhYWxbNky1q5dS3x8PC61auPTeRCeHQfj4WJPnybu9G7ijo2FSGsTBEEQhMomYrceUJaxWzqdjmnTptGiRQusra3x9PTk5ZdfNl7WrUouXLhAmzZtWLNmDYOffoaOz79DtpMfR9d/ReBnb3DhViQr9l5n1uYLJKZVn/XEBEEQBKGmErFbDyjL2K20tDROnz7NrFmzOH36NBs3buTq1as89dRTJrVfUSRJYsSIEdSqVYurV6/iO+hNFM0H0PeNj3hq9hrS4yKI/PsHatlbEnw3kdWHSljcVhAEQRCEcidit/Io69gte3v7Aov/rVy5kg4dOhAaGmrSpIyKEBgYyIULF9i+fTvJWQoOXgrDVgkKfSZ27t406TOcCzt/pdWQ17FWmrP/4l2ebumKq23BZVBKUp3WIhMEQRCEqkzEbt1XXrFbD0pKSkKhUBS7JlpFx24NGjQIoMRc1/WT/nt+6+RiNixGZUU7ifiXmkUudYJ8apVLnSCfWkWdInbLJFU5diuvjIwMpk2bxogRI4pNXqjo2K2KVNnRTnKOf6mJ5FInyKdWudQJ8qlVznWK2C0TVNXYrbx0Oh3Dhw9HkiS+/vrrYret6NitI0eO0LlzZ77++msGDnmGievPkpqVbbxcenzt54SdPczQj9cTq9Vjb2nG8udaYmVe+h+fyrqcKuJfaha51AnyqVUudYJ8ahV1itgtk45bVWO3cuUO4O7cuUNQUFCJA7GKjt1q164dgwcPZsaMGTRu3JjB7evx09HbpOtVRP67nRuHttHumfFkKizRq3QM7eCHp5tLyQ1XQXKOf6mJ5FInyKdWudQJ8qlVznWK2K1SqkqxW/DfAO769evs27evQIJDVfHjjz8yaNAgevbsSatWrTHYuHH00lnS46Pw7Pgk1u2GkpltYHArL4a3867s7gqCIAiC7InYrXKM3dLpdDzzzDOcPn2abdu2odfrjffLOTk5FTvJo6I5ODjwzz//sGPHDtauXUtcXByNnuhPg66DcajTGCcbC7rUd6aRu63JS7AIgiAIglB+ROxWOcZuhYeHs2XLFgBatWqVr619+/YVujBxZVKpVDz55JPFnn0UBEEQBKFqELFbRSiL2C1fX99H6rdQwXTpcOsghB7N+bdzPajfB5z8Ct08OjmD/VdjuHYvJSdHtbYDXRu6YKep3Hs/7ty5wzvvvMP58+fRaDQ8+eSTjBo1Cnt7+yL30el1nLx3kpP3TqLVafG09uTx2o9T175uBfa8YumTktAePkz6xYugN2DRqBE2XR9H7VI97/cUBEF+ROzWA8oydqu0xxYqUXIEbH4T/p4Jl7fCzSA4vgr+fB3O/1Fg8yM3YnnrtzOs+ieE/Vej2Xv5Hp8HXuWd385w7V5KJRSQY8mSJbzzzjts2rQJX19fLCwsePfdd2nSpAnnz58vdJ+EjATmHZvHpyc+5e/bf3Ms4hgbrm1gxsEZ/H719xr5h0jGlSuEv/suMV+sJHXfflIPHCDu228Jn/wuaSdOVHb3BEEQTCJitx5QlrFbpT22UEkMetjzIUSdAzvPnDNwjn7gVA8MOjiyAu4cNW5+K1bLksBrJKRl4eNshY+zNb7O1tR2sCQ0Po2FOy6TklHxi1tu376d999/n2HDhhESEsIvv/zCtm3buHnzJu7u7gwcOJCMjIx8+0iSxFfBX3Em+gwuGhd87HyobVsbH1sfFChYd3UdB8MPVngt5UmfmEj0Z4vRhUdg5uWFeZ06mNepg1nt2mTHxRG9fDlZYeGV3U1BEIQSiditPMo6dqs0xxbKX0ZGBlqttuCU77sn4E4wWLlBtgry/CGCmSvE34RT68ClJQDbTt0kJiEJHycr9FkZ6PM05W4JtyLjCDwbSr/mhSd/lJdFixbx2GOP8cwzz5CVlWU8g+bk5MTq1atp06YNv/76a77ld24k3ODU3VPYqe1Q6VT5Vhe3w46wtDD+uvQXbRzaVKkJLTqdrtD305R1CFMPHUYXEYFZ7dooVCrj4wqVCjMvL3ShoaQE7cW5mElagiAIVYGI3bqvomK3TFHRsVs1PRIFcmrMndDycIKBFfkeKe781D8fPMKhHlFxaySOGTOGMWPGlKq9Hezgcz5/1G5VCFNi3bTBZ5AASalAkgz5n1QA5uZoT57CrhRrTZYnuXxO5VInyKdWUaeI3TJJdYndMlVFx27JJRJFqPlMiXVzvXkTK60WXXR0oc+rU1PQhYdzppIj4h4kl8+pXOoE+dQq5zpF7JYJqkPsVmlUdOxWTY9EgZxa161bR69evQrUqrh1AFXQh0g27qAqmJRBUiiShz+GJ5aAQsFX+0PYdfEe3k6WBS4x6g0S4YnpvNbFl8H+nuVZUgHdu3enVq1avPLKKwXqjIyMpGXLlixYsCDfWeqLcRf59OSn2JnbYamyLNBmVFoUtW1qM7/zfNTKMv118Uh0Oh1BQUEF6jTlcmpSejqJET+idnFB8cCSSJIkkZ2ejm3vXrR+4oky7/fDkMvnVC51gnxqFXWK2C2TjlvVY7dKq6Jjt+QSiaLRaHBwcChYa4t+cOU3iL0Ojr6g/O8+KdITwNIc2g2H+38QPNW+PkfvppOkk3CztTAO5CRJIiwxHU8XRwa2rYeDTSEDwnI0ceJEXn31VRo3bszTTz9trDM9PZ333nsPKysrxo4dm2+pkU72nWgS3oRLcZewsbTJN1BLzUpFpVExqOkgXJyq1rIbOp2u6PezBPY9e5K6dRv6qHuY3Z/xDjnvnz4mBpWtLfZ9+lS5z4RcPqdyqRPkU6uc6yzvuh9qdmphcmO3hg0bVujzeWO3SlIZsVvnzp0jODjY+AWwdOlS1qxZU+R+ubFbeT0YuyVUA2oL6DULHLwh4TYk3YWUSIgLgSwttHwOGgQYN2/uZc9rj/uhUCi4HZdGVHIGkUnp3IpLw87SjIl9GuJSwQM4yFn+55VXXmH58uX06NGDBQsW8O6771K3bl327dvH77//XmCtOKVCyYTWE/Cx8yE8NZyI1Ahi0mIITQ4lKSuJ3nV608+3X4XXUp7M3N1xHf8mKhsbsu7cQRcVhe7ePbJC76BQqXB+9VU0DRtWdjcFQRBKJGK3yjF2y5RjC1WEe1MY8jVc2wU390NWGrg2gkYDoE4neOCy6ZDWXjRwt+Hvi/e4EJGEWqmkg68jfZt6UMe57O9bNIVCoWDVqlW4ublx4sQJli1bhkaj4emnn+btt982JqM8yNvWm/ld5nMg7ACHww+jzdbibetND+8etHdvjyrvmckawrpzZ8w8PUnZt4+0k6fAYEDTvDm2fXqjKeJ1EgRBqHKkUho1apQEOZO71Gq15OrqKvXp00davXq1pNfrjdv5+PhIS5cuLbB/v379pAEDBkiSJEn79u0ztpXbnp+fn/Tee+9Jqampxn0e3C73a9SoUSb1ec2aNYXuP2fOnCL3AaRNmzble8zHx6fAPhs2bJAaNmwomZubS82aNZO2b9/+yMd+UFJSkgRISUlJJu9jiqysLGnz5s1SVlZWmbZbFcmlVlFnzSOXWuVSpyTJp1ZRZ/n9/zuXiN0qQmHHK23s1sMeu7xJkkTmtetoz57FPjiYNBcX7Nq3R1HM8i959923bx+7du0iKyuL9u3b88wzz+S/h08bB7cPkK1NICRFzUXzlmRbOuNf24GG7jZVar0xQRAEQaiuROzWfWPHjqVevXpYWlri6urK4MGDuXLlSomvR3GxWzqdjmnTptGiRQusra3x9PTk5ZdfNl5arQz6xETufbSAiOnTSVi9GoeDB4n5eCFhkyeTcf9Sb1HCwsJo3749vXv35rfffmPXrl28+OKL+Pj4cODAAZAkCF4L60aQ+fd8ogOXYnnoExruG8vtwG+YvP4M87ZeIimtZq8ZJAiCIAgVQcRu3de2bVvWrFnD5cuX2b17N5IkERAQgF6vL3KfkmK30tLSOH36NLNmzeL06dNs3LiRq1ev8tRTTxXZZnmSsrOJ/vxzUg8fRmllhbqONzoXZ1SuLmSF3OTeJ5+ii4wsdN+srCz69etHdHQ0e/fuJTQ0lCtXrnDlyhWaNm3KwIEDubbjKziykqyMNC5lOHHH4E6cuSfWaj0jDFvpYzjC/msxLNp9Bb2h5uVxCoIgCEJFErFb9+VdO8vX15ePPvoIf39/bt++Tb169Qrdp6TYLXt7+wKL/61cuZIOHToQGhpq0qSMspR+7hzpwWcxc3NDaWWF4f5q9UoLC1Te3iTdvIli2zacX3ihwL4bNmzg0qVLHDlyhJYtWxoXMKxduzbr1q3D378liz5bwvLBrtw12BOfloGVuZKMbIjCHsfsGDoZ/uZfu1YcvxbB8WuO+HubthAzmLb+lyAIgiDIiYjdKoRWq2XNmjX4+fnh7e1tfLwsYreSkpJQKBQF1qTLq7xit1JPnsSQmYnKUoNBMiDdPxsmGSRQKmi5dw/s3QPFvHadO3cu8rkfouCHf26V0It9AOydXrq+mxKnVBwR/1KzyKVOkE+tcqkT5FOrqFPEbpmkLGK3AL766iumTp2KVqulUaNGBAYG5ht0PmrsVkZGBtOmTWPEiBHFJi+UV+yW07nz2BYSNxQTG/PQbVYUU+KUTCHn+JeaSC51gnxqlUudIJ9a5VyniN0ywaPGbuUaOXIkffv2JTIyksWLFzN8+HAOHz6MRqMBHi12S6fTMXz4cCRJ4uuvvy522/KK3UrOzCThxg1j3JBkkIiJjcHVxRWFUsHZvgFoWrTAbdbMAvtOnz6dTZs2cf78+ULPpo4c/jThl//l4PQOXElUkpKhx9L8v1suLQ2pmEk6vnWaQnCqPa+WMpbqUS+niviXmkUudYJ8apVLnSCfWkWdInbLpOM+auxWLnt7e+zt7WnQoAEdO3bE0dGRTZs2FdmWqbFbuQO4O3fuEBQUVOJArLxit+y6dyd54yYMsXGYubtjUObcE6dQKpC0aVhbWOA2cCC2hVzqfeutt/jmm2/45ptvmDVrVr7ngoKC2LX3H756sze2+lh8nbwIiUvHTKVEpVSgkPS4ZadySdOG65IXLo5qBrSpi4Ot5qFreVhyjn+pieRSJ8inVrnUCfKpVc51ititUnqY2K3CSJKUs55annvTHmRK7FbuAO769evs2bMHZ2fnMunfwzBzd8d51MsolAqyQu+gT0pCmZ6BLiICfUICNj26Y9P18UL3bdasGXPnzmX27NkMGjSI33//nR07djBu3DgGDBhA3759eXXWV+BcD2ddOHXMU1Bnp2KZGYurLpxwpQdrpIGolApef9wPt0oYwAmCIAhCTSJitzw8uHnzJuvXrycgIABXV1fCwsL45JNPsLS05IknnjC2U9rYLZ1OxzPPPMPp06fZtm0ber3eeL+ck5NTsZM8yovdgAGoXVxI2r6d9IuXUGRnY16/Hvb9+mPXLwBFMX81zJkzh/r16/PZZ58xfPhwADw9PZk5cyZTp07FzMICnlyO8twGPK79jWVyEtEZVgQqH+egpid+derzVCtP2vs6VVS5giAIglBzlTbioSbGboWHh0sDBgyQ3NzcJDMzM6l27drSCy+8IF25ciVfO6WN3bp161ahxwWkffv2mdR3SSqf2A6DwSClx8RKW3/9VcpMTy/1vpGRkdKdO3cknU5X+EZZaZKUEi3p0lOl2JQMKTGtcmNXRPxLzSKXOiVJPrXKpU5Jkk+tok4Ru1Wq7YpSUvSVp6enSbMfSxu75evr+0j9Lk+G1FSyblzH/N49smNiMM+zlEphwlPDCU8JR61U08ipUYH7/gowswQzS1SSxPXg41y7dg1bW1sCAgJKNUlBm5nNpchkdNkGvJ2s8HaygqQwiL8JSjW4NwONvcntCYIgCEJNIWK37iuP2C1Tj12RpKws4tf+Rtib44me/xFumzYTNWky9z5bTHZsbIHto9OiWXRiEe/tf4+Pjn3EvKPzeDvobX6/+jvZhuxCjvCf48eP06pVKzp16sSoUaN4+umn8fLyYsGCBSUObrP1Bn77N5QxP59kxsbzzPrrAjN+DeLw12+StfZF2P4ubJsEv42A499C9qOtIycIgiAI1Y2I3bqvPGK3TD12RZEkidjvviPh118xaLWoPdzROTmCWkXKnj1ELViAPs906MSMRBYeX8iBsAOolWpq29bG3dqdlKwUfr38Kz9d/KnIY509e5bevXtjaWnJ33//TUZGBiEhIbz66qvMnDmTDz74oNi+rj58i9WHbpGUrqOWvYZGDhJjtd9SJ3ofoYmZZNl4g50XZGnhxHdwcHFOdqsgCIIgyISI3bqvPGK3TD12Rcm8fp3UvUGo7O1R2dvnxG4plajs7VFb25B55SopQUE4DBkCwLYr27gSdQVPa0/UBjX6jJwBraPCkUR9Ijuv7qSzS2fq2BWcXPLBBx9Qu3Zttm7dipWVFdnZ2bi7uzN//nysra355JNPeO211wq9LBsap2XziZtoFAocLcwhO5Nmqf/gkX6DcJUraWkqDPHpeDlYgZkL6BPh3Hbw6QvuTQu0BzmTTDIyMsrstRQEQRCEyiZitwpRnrFbpiiv2K2UI0fQp6WhdnEuGLulVoFaTfKevVgPHIgkSbzU+qUS2/yTP4t93s3NrcjnClv4uSi/mLLRxA4lbqLVak0+ZnUkYm5qHrnUKpc6QT61ijpF7JZJqkvslqnKLXbr5ElstanoYvLHbOXGbqky0pFCbnBm+3b0GAprotqTc/xLTSSXOkE+tcqlTpBPrXKuU8RumaA6xG6VRnnFbiUmJpF0/QZqV1cUCkWB2C1ddjYWfnVpef9M3JgtY4jSRuFu5V6gLQmJsNQwnm/0PEPqDcn3XEJCAg0aNGDhwoWMGTOmwL4JCQk0adKEOXPmFPoebzwTzo9H7lDbyRLl/Z+n12I/w0t3hzi1Oxk6Axq1kuaeua+FhCLhFoY2ozC0fbXQ2nU6HUFBQbKOf6lJ5FInyKdWudQJ8qlV1Clit0w6blWP3SqtcovderwLqVu2ICUlo3J0zBe7hS4bRbYeu759jMcY0HgAqy+sRqlRYqbKf9z4jHgc7Rzp3aA3DnYO+Z5zcHBg8ODBfPvtt4wdO7bAwPOzzz7DYDDw2muvGd/3vPr6m/PXxQS0enCxyXkdrjt0pVHiHTJVBkBFHWcrbK3unyVNiwc7e2jxBBTSHuR8yDQajazjX2oiudQJ8qlVLnWCfGqVc50idquUqlrsVlViXrcutv37YUhNRRcVhZSZCXo9+vgEsiMi0DRvjk3Pnsbte9XpRWOnxoSnhpOQkUC2IZtMfSZR2ijSdGkM8BuAt13h68vNnz+f6OhounXrxsaNG4mLi+PcuXP83//9Hx9//DGzZs0q8n45bycrnm7jRVqWnojEdDJ0ek5ZPMZVVQMcsqLwUKfiZqWE7AxIjoCMJGgyGFwblcvrJgiCIAhVkYjdKsfYLVOOXZEUCgXOr7yC2smZpO3byY6Jxiw5GTyssHtiAE4vv4zKxsa4vb2FPe8/9j7/u/Q/jkYeJUobhVKhxM3KjYF1BzKw7sAij9W0aVMOHDjAG2+8kW9g7+bmxrJly3j77beL7etLHX2xtzRnc3A4UUkZRBuU/GAzlrGaPXQ0nMFMGwkKJdi4Q/Nh4D8C8lzKFwRBEIQar7QRDyJ2a06+x4qL3TLl2KYoj9gOfVqalHz6tLRr+XIpLTKyxO2jtdHSmXtnpAuxF6SM7IxSHev8+fPSn3/+KQUGBkqZmZml2jc9K1s6dzdROnk7XrqXdD8eLCVakkKPS1LYSUnK1JrUjoh/qVnkUqckyadWudQpSfKpVdQpYrdKtV1RKit2y5RjVxalpSWa5s3JCA1F7exc4vauVq64Wrk+1LGaN29O8+bNH2pfjZmKFrUfiNWycc35EqolSa83poOoXVxQqFSV3COhOtNqtdy5cwcrKyt8fHzyTa57KJIE2tic2zWsXcFMUzYdfYBegsikDCzM9bjaWKBU1qwrCXqDnui0aJINyegNesyo+ffEVYYyndggCIJQFMlgIOXvQJJ37UQXFg5ImHl6YTegP7YBAWIwJ5RKQkICs2bN4qeffiI1NRWAli1bMmPGDJ577rmHa/TOUTi3DiLPg6QHS0doMghaPgcWtmXSb53ewF/BEfx0Vcnq0GCUCgV+LtY86e9J7yZujz4IrWR6g549oXvYfXs3YSlhJKUmcfrwaQbUHUDvOr1RKcXnvCyJ7FRy7lt76623aNSoEZaWltSpU4e3336bpKSkEl+P4rJTdTod06ZNo0WLFlhbW+Pp6cnLL79svD9OEORCkiTiVq8mZuVKMm+EoNBoUGgsybx1i5gvvyLu++8f6Wy7IC+JiYl0796d//3vf0yePJlDhw6xefNmvL29ef7551m6dGnpG72yA3a/D3eOgMoMzG0gLQ6OrYLdM3Ii/h5Rtt7Asj3X+frALWIzwdJcicZMyaXIZD77+yq/HrtTrT8HkiSx+sJqvj77NbeSbqFRaTBTmHEr+RZfnf2KNRfXVOv6qiKRnQpEREQQERHB4sWLuXDhAj/++CO7du3itddeK/Z1KCk7NS0tjdOnTzNr1ixOnz7Nxo0buXr1Kk899VSx7QpCTZNx4QLJ23egsrHBvHZtVDY2Of/28kJla0vyzl2kP/DHlSAUZdGiRdy6dYvDhw/z4Ycf0qVLFwYPHszWrVuZPHkyU6ZMITw83PQG0+Lh6ErQZ4GjH1g6gIUN2HnmfIUeg0t/PXK/j92MZ8/lezhameFkATYWamw1ZtRxskKjVrLhZBghMamPfJzKcj72PLtv78bWzBYvGy9szGzQKDR4Wntia2bL7lu7uRB7oeSGBJOJ7FRy7tn688//4qPq1avHggULePHFF8nOzkatLvxlKik71d7evsAKzitXrqRDhw6EhoaaNLNWEGqC1AMHkDIyUBayrIzK3h59YiKp/xzAqnXrMjleTYpXy8391Wq1NXqtLVPrNBgMfPfdd7z00kv4+PgUeK/fffddvvnmG7799lumTp1q2sEv7oK4SHCoA5n6B540A50SzmyEek+C8uFX5tpx5haZaVpcNZakZGWgy0xHqchpz04tERqfxt/Bd6jVxa/INqytrR/6+OXtYNhBsvRZeFgXXHnB3sKexMxEDoYfpIVri0roXc0kslOLkJSUhJ2dXb4BXFlkpyYlJaFQKApd5DZXeWWnPkguuXYgn1qrap2Zd0LBTI2EVPjlFHMzMkPvmNzvkuq0ybNUjlAzff3113z99ddFPj9v3jzmzZtXylaDi3nuX3i1+KzosnAAGF/M81lZWeXeh4cVmhyKWqk23lqV+1mXJAmDwYCZwow7SaZ/zqsLkZ1aRbJTc8XGxjJ//vwCA8FHzU7NyMhg2rRpjBgxotj4rPLKTi2KXHLtQD61VrU6XWNjsUpMRFfE5AWzhETS4+I5bcIs8byqWp2CUN5MWUmhssSlxZGYnYgyNf/Zypj7ed2JhkTi0+OrdA2PQmSnVnJ2KuSc9Ro4cCBNmzY1nnHL9SjZqTqdjuHDhyNJUrF/PUL5ZacW1ic55NqBfGqtqnWmaiyJW74ctYMDigfOxks6HdkZmfg8N5x2ffua1F5JdSYkJJRJv6uC3NzfXr16Van3tKyVps5Ro0Zx+fJlDh48WCCicMeOHYwcOZKdO3fSsWNH0w4edx3VtomgtgCLB5Y0woAi4TaGZs9g6PyW6QUV4q+zEfxw+DaedhoSEuJwcXbJiT0EMnV6YlOymNa/ER3rOhXZRlW+nKq5q2Hl2ZU4WjpipjJDkiRiYmJwdXVFZ9CRlZ7Fs/7P0tO7Z8mNVSMiO7WKZKempKTQv39/bG1t2bRpU4m/SEzNTs0dwN25c4egoKASB2LllZ1aFLnk2oF8aq1qddp3fZy0v/8m4+JFVC4uKO//j8iQloY+JgZN48bYdeuOqpR9LqrO4m5XqG5yc38dHByq1Hta1kpT5+zZs+nSpQujR49m6dKlNG7cGJ1Ox++//84bb7xB37596devn+nLddi3g+b94NIWQJmztIhCCboMSA4HV2947IUis5lN9VQ7Kw7dTuNGdAoqlQYzjSVKhZKUzGxiMzNp19CTXi19MVeXWSJmherq3ZXAu4Fcib+Cq6UrGqUGSZJIy04jLjOOJk5NeNz78Rr7cyyyU++rjOzU5ORkAgICMDc3Z8uWLWg0JS/waEp2au4A7vr16+zZswdnExbWFYSaRmllhdu0qVh1aI9Bq0V3NxTd3bsYUlOxbNsW9/eno7KpumcYhKqlbdu2bNmyhdOnT9OkSRN8fHxwc3Nj5MiR9OjRgz/++KN0660pFNBtSk6En8EA8bdyvlLvgWtDCPgInOs9cr8drc2Z/WRTWta2Jy1bQWh8Bnfi00jP0tOtoRvvD2hSbQdwAFZmVkxtP5W27m1J1aUSlhpGvBSPNltLO/d2TGk/BSuzsr8lSM5EdqqHh3EAl5aWxq+//kpycrLxFKirqyuq+/fxlDY7VafT8cwzz3D69Gm2bduGXq833i/n5ORU7CQPQahpzNzc8PjwQzKvXSPz2jWQJCwaNMCiceNqv8CpUPECAgIIDQ1l06ZNnD9/HktLS4YMGfLQ6TCYWULP96H1ixB2Ime5EXtv8O6Qs25cGfF2smLR08359o+7eDT0w9xMTTNPO+q52tSIz4GblRtzO83lWsI1rsReIfhsMM90fIamrk1rRH1VTmlzumpidmpR7QPSrVu38tVUmuzUW7duFdnuvn37TOq7JJVf9ppccu0kST61ijprHrnUKpc6JUk+tYo6RXZqqbYrSkn5paa2X9rsVF9f32q/OrUkSaQd/5eUvXvJvH4dhbk51p06YtO7N7vOnOGLL77g6NGjqFQq+vTpw6TxY+nqmox0dQfJsZHczbLmH9py3qYzbRp4E9DUA18XcdlMEARBEB6ViN2i/GK3TDl2VSZJEvGr13Bv4cdoDx3CkJpKdkwM8evW886AAQwZMoT09HTmzZvH9OnTuXblMt379ufrBe+RcPscUTGxWCVe46mk/zH83lJ2HL/IlD/OcuJ2fGWXJgiCIAjVnojdovxit0w5dlWmPXyEpC1bUFpaYe7jg9rFBTN3d44oFXxz6RKzO3TgwO7dvPvuu8yYMYNzK15gQldXJvweSmCYOclqR5I1niSZu9PUcJ3XVDtISNOxNPAaSek1a7FHQRAEQahoInaL8ovdMuXYVVFujM297dtJS0/H3MUF8qw6vebiRZo5OzPMzp7ooCDseveGlHtwZS9zhzbhl5OJbDh2l/cGNSJbbwAUGPTW+CafooFLAJdjLNlzNpT+LQpGszyKqrx+kiAIgiCUNRG7VYTyit0yRWXHbpkaWeS/JxD2FL5i/sZ/w9n4b2EB1DlL0PxjejdNVlwcTVWNoypros6aRy61yqVOkE+tok4Ru2WS6hK7ZSoRu/VwTIlyqSm1lkTUWfPIpVa51AnyqVXOdYrYLRNUh9it0qjs2K3cyKL4r1eRumcP6jre+d7X2YcPczAsjO1dHqfWtKlYtW0LWamoNr5ObGwcjT88zahuPrzS3Q/u72anjyNdYc1yx+mEpapLjJZ5GMVdTq2qcVRlTdRZ88ilVrnUCfKpVdQpYrdMOm5Vj90qrcqO3cp9LzRPDyXyzBmkuHjUHh4olDnzYF5v0oS/rl/nwzu3+ally/vbOxDp24+XP5uNtbmSZx+rjUKpQKNSYiWlYqPQ8691D8KybGnma1dp0TJVLY6qvIg6ax651CqXOkE+tcq5ThG7VUpVLXarOtM0aoTrWxNQ2tqgu3uXrDt3yLp9m/rZer4cOIi/79yhtq8vTz31FP369aPOk1O5HGtgx/hmdHFOxluKxDnrLmSns1vRhQ2GnjStZcf7T1TvaBlBEARBqApE7FY5xm6ZcuyqzqZrVzRNmpB68BBZd+6gMDfH0r8lr7Vvz6C4OL7//nuOHDmCubk5ixcvZtTLL+OQFQE3/4HEe1xPMeeM2p8Uu4ZMr+PIY35OaMxUlV2WIAiCIFR7DzWI27VrF7Vq1UKtVuPo6Ii/vz8rVqxg1KhRKJVFn2Fp2rQpAQEBzJ49O99N6I0aNcrpjFqNt7c3Y8eOzXc/2smTJ+nZs6fx+9z7xUaNGmVSesSWLVt45ZVXjN8///zzAMyZM4e5c+dy+vRpjh8/DlDgnr1bt27h6+sLQEhICLGxscbnOnfuzNq1a5k5cyYzZsygQYMGbN68OV92X0nHrg7ULi44DB1S4PFatWoxa9asQvZwBPdmWAH+978EQRAEQShbInarFO2XNnbLlGPLUVJSEj///DNbtmwhPT0df39/xo0bR4sWLUxuIz1Lz5GQWE7dSSBdp6euqw09Grri7VT2s3fLhCTBvQtwIwhSIkDjCHW7Qe0OoCrTW1MFQRAEmSjVjUk1MXIL4Ntvv6VHjx7Y2dmhUChITEw06fXYv38/bdq0wcLCgvr16xc6uA0PD+fFF1/E2dkZS0tLWrRowcmTJ01qvya6cOECTZo0YfLkyVhYWFC3bl02bdpEy5YtWbRokUlthCem8+6GYBbuvMKui1Ecuh7LmkO3ePu3M2w/F1nOFTwEgx4OL4PN4+HMz3BzP1z4Hba/C7umQ2ZKZfdQEARBqIZKfXd5TYvcgpx1XPr378+MGTNMfh1u3brFwIED6dmzJ8HBwUycOJHXX3+d3bt3G7dJSEigS5cumJmZsXPnTi5dusSSJUseau26miAjI4MnnngCV1dXbt68ybZt2/j555+5c+cOM2bMYNq0aWzdurXYNnR6A5/uvMLlqBRq2Wnwc7amjpMVPs5WZGUbWPVPCGdCEyqoIhNd+BPOrgO1BTjVA0dfcK4PVk5wcx8c/qKyeygIgiBUQ6W+jlPTIrcAJk6cCJRuZuuqVavw8/NjyZIlADRp0oRDhw6xdOlS+vXrB8Cnn36Kt7c3a9asMe6XdwmWqi43fqusrFu3jrt377J582acnJzytf/++++zb98+Fi1aRK9evYps48StOC7euYebjQUKfSY6/X/POVlIhMansflECA2dm+TbT6fTkZGRgVarNf68VYjsrJxBnFKVM2jLy9wGLB0hZA+0Gw12nhXXL0EQBKHaK5ObcWpa5FZhevToga+vr/GS6dGjR+nTp0++bfr162ccEELOpIZ+/frx7LPP8s8//+Dl5cWbb77JmDFjij1WZcdu5TI1fqu02rZtW+zzj3rcA8C8Yp4vLp6rzMVeR5UUlnMPXJ5bDows7FEk3kYfHoxk6frIhxMxNzWPXGqVS50gn1pFndUodqumRG4VpU6dOtSqVcv4fVGRW8nJyaSnp2NpacnNmzf5+uuvmTx5MjNmzODEiRO8/fbbmJubM2rUqCKPJWK3ypcp8VxlxTY9jLZJSWRqDRiUqQU3kCSss7RcPPEv966V3YddLu+pXOoE+dQqlzpBPrXKuc5qE7tVEyK3ivPzzz+Xeh+DwUC7du34+OOPAWjdujUXLlxg1apVxQ7iKjt2K1du/FZZ+fbbb5kxYwbnz5/PNyDONWLECMLDwzlw4ECRbRy4Hsvngddxt7PArJAFg8Pi02nt7cCcJwteTg0KCqJXr14Vezk1S4vq953YpieBrVvB5zOSINuNtv2ez7lf7hGJmJuaRy61yqVOkE+tos5qFLtV3SO3SquoyC07OzssLS2BnHXUHqy3SZMm/Pnnn8W2XdmxW7nKerAzduxYPv74YyZPnszGjRuNrxPAL7/8wq5du/jhhx+KPW5AK1s2X0zgTpyWOlZWKJX//eGQoM1CY6VkyGP1C7Sh0+nQaDQ4ODhU7C8TMwdo8hT8+y1kp4N5nnxXfRakxUH9XijdG5ftYWUcc1NTyaVWudQJ8qlVznWWd91lMojLjdyaNGlSoc/njdz666+/im2rMiK3HkanTp0KXJZ7MHKrS5cuxoSGXNeuXcPHx6dC+ljV2Nvb8/vvvzN48GD8/PwYOXIkTk5O7Ny5k8OHD/Pqq6/mWxi5MBozFe8FNGLBjkvciU/DXK1ErVSQptNjoVbxTNvadGvgUkEVmajNSxB/IyfFIjUazCwhOyNn6ZFaLaHru5XdQ0EQBKEaKvUgrqZFbkHO/W1RUVHG45w/fx5bW1vq1KmDk1POjMKXX34ZLy8vFi5cCMC4ceNYuXIlU6dO5dVXXyUoKIgNGzawfft247EnTZpE586d+fjjjxk+fDj//vsv3377bYG18OSkb9++BAcHs2LFCjZs2EBGRgb+/v78+eefDB06NN8l+aI09bTj8+Gt2HP5Hoevx5KRbaCBmw19m7rT1sfRpDYqlJkl9P0oZ324azshKSxnpmr9vtCgL2jsK7uHgiAIQnUklcKoUaMkQAIktVotubq6Sn369JFWr14t6fV643Y+Pj7S0qVLC+zfr18/acCAAZIkSdK+ffuMbeW25+fnJ7333ntSamqqcZ8Ht8v9GjVqlEl9XrNmTaH7z5kzx7jNnDlzCt1mzZo1xm26d+9e4Jj79u2TWrVqJZmbm0t169bNt32urVu3Ss2bN5csLCykxo0bS99++61J/c4rKSlJAqSkpKRS71ucrKwsafPmzVJWVlaZtlsVyaVWUWfNI5da5VKnJMmnVlFn+f3/O1epzsTVxMgtgLlz55aYY1rYpdoePXpw5syZYvcbNGgQgwYNKqGXNUt2WAhpO/+HPiEOlaMzVgNGoK7doFL7pDPouJV9i003NmGmNqOpc1MaOjYscNbu0qVLrF+/noSEBOrVq2dM26jO9AaJ4LsJXL+XikIBjT3saOFln+9+QkEQBKH6EbFblF/sVmn6XhNIBgOJy6cRNuppYn5YR/ymQGJ+WEfYqGdIXDoFqbB10ipASGIIMw7PYGvaVn658gurL6xm5uGZfHTsIxIycmbgZmRkMHLkSJo1a8bKlSsJCgpi6tSp1K5dm6+//rpS+l0WQuPSmLQ+mA82XeC7gzf59sBNpv95jql/niUqKaOyuycIgiA8AhG7RfnFbpXU95om5YePiN+wDUOWHjNnK8xdbDBztkLSGYj/Ywcp38+v8D5Fp0Wz6MQiQhJDsFHY4G3jTR3bOlirrTkedZzPT32OzqBj3LhxbNy4kR9++MH4cxsWFsYrr7zCm2++yR9//FHhfX9USWk65m+/xPnwJJyszPF1tsbHyQp7SzNO3Unko+2XSMvKLrkhQRAEoUoSsVuUX+xWSX2vSQxpKST+tQ1QYObw34LECqUStb0lSbGpRGz8C8XgMShtKu5G/p1Xd3In9g5e1l7EZcahS9ehVCqxwAJnpTPBYcH8eeBPfv75Z5YsWcJzzz1nTMawsrJi0aJFhISEMHfuXPr371+lJk1YW1sX+/y+q9GExKRSx9EStSrn7zWFQoG1hZraKiVXolI4dD2WgGYeFdFdQRAEoYyJ2C0TPUzs1sOqKrFbpZF5aBu6BC0qG3MKu4OxxbHLOf/w8HrkY5W1bWwDYPLkyfkWWX6Qra1tRXXJJIXFh+V9Tw9ej0alAKUSDFL+S9lqVc5n88iNGHo2rH73/MklzgfkU6tc6gT51CrqFLFbJarKsVsPqzrGbrldOoFLtgGDPhtFZuXc+yY3xcWHBQYGEnJbSVoGROtSCt0mPROuhqSyY8fN8upiuZNLnA/Ip1a51AnyqVXOdYrYrRJU5dith1VVYrdK1ZafK1G7AlEYlKgsC6ZNXOjWHElvwP2zpZg16fBIxyqNz05+xpmYM3haexIbE4uLqwsKcn5OJSTCUsOoG1qXr9//mmPHjtGoUaMCbaxYsYIFCxZw9erVio3sKkFhl1PzvqeXzW7z96Vo3JwL/kEhSRJp8ek87u/FE938Cjxf1cklzgfkU6tc6gT51CrqFLFbJarKsVsPq6rEbpWqjZadsWroTeq526gszVAo/5szIxkMaDL1WDWrg2ungEftbqkMaDKAS9pLZKmzUGvUmFuao7zft+i0aJztnZkyZgp/Lv2T+fPns2nTpnyvRWhoKF9//TXPPfccvr6+Fdr3R2FmZkbfZrX453ocyenZOFjlv5UhTpuJjYWa3s08qvUvV7nE+YB8apVLnSCfWuVcZ3nXXerZqYXJjd0aNmxYoc/njd0qSXWK3co7ixYKxm7JjdOkOVi4WpMVm0Z2cjr69Cyyk9PJik3DzMUa54mzK7xPHWt1pJd3L5KykkgwJJCSlUJSZhKhyaEAjGgyAj9nP9asWcPff/9Nhw4d+O677/j777+ZO3cu7dq1Q6PRFDu7uapqU8eBwa08ScnMJjQ+jaR0HUnpOu7EpZGRbWB4O28auVet+/wEQRAE04nYLcovdutR+17dmDd9DI9l35O0Zinaf89iyMpGYa7GoUsb7Ee/g1nDNhXeJ7VSzRut3sDPzo9f//0VnSFndmpb97YM8BtAh1o5l3afeOIJ9u/fz/z5840TY6ytrXnxxReZO3eu8WelOlEoFPxf17r4uViz41wkt+O0oAB/b3sG+XvSo6FrlZptKwiCIJRSaeIdROxW/mOWFLv1qH3PVR1jt/TJ8ZLuzlVJnxxf5m0/jKysLGnjpo3SveR7UmJGomQwGIrcNj4+Xrp9+7aUlpZWgT0sG0W9pwaDQYpLzZTiUzOLrb26kEucjyTJp1a51ClJ8qlV1Clit6p17Naj9r0qCU8NJzwlHLVSTSOnRlibFb1GmaTXk3U3En1SEqrUbCwa2aFQqfJtc+3aNXbtO0Rihp72nR7n8Zb1sdWU870DCiWOGsfi71HI0uKYchVHfSak68Gybrn2qaIoFAqcrIte4kcQBEGofkp9T1xNjd7KyMhg/PjxODs7Y2Njw7BhwwpMXCjM77//TuPGjdFoNLRo0aLAsg+mHLsqy008eG//e3x07CPmHZ3H20Fv8/vV38k2FFztP+3UKcLffY+I92cQNW8+Ee/PIPzdd0k7cQKA8PBwevUJoFGjRrwz7jXmTPw/BnZuiX/voXwfdAmdvpKWJzHoIXgtrHsBtk6EHe/BH6/CjimQGFo5fRIEQRCEYjzUxIaaGL01adIktm7dyu+//84///xDREQETz/9dLGvw5EjRxgxYgSvvfYaZ86cYciQIQwZMoQLFy7k63tJx66qEjMSWXh8IQfCDqBWqqltWxt3a3dSslL49fKv/HTxp3zbp506xb1Fi8i8dg2VvT1m3t6oHBzIvHade58tJnzvXrp178GJ4HM0fn4GTy35m+eX7abNsPGEngxi2riX+XLvtco5e3niBzi8HNLiwa4WOPqCygJCgnIGcilRFd8nQRAEQSjGQy0xUtOit5KSkvjhhx9Yu3YtvXr1AmDNmjU0adKEY8eO0bFjx0L3W758Of3792fKlCkAzJ8/n8DAQFauXMmqVatMOnZVtid0DzcSb1DbpjZqZc6PilKhxM3KjZjEGHZe3Ulnl87UsauDZDAQ+dNPZCQkYla7NtkKBej1oFYjeXigCwtjzcyZhIWF4T/hK+rV9cPsfhRU015P4+Dhzd4V7/HLuj/oWf916pfxrEmdTkdGRgZarbbg5dSkcDjxP5A0YOkCOgADKGzAUgMRV+HkOugwxrhLSZFXgiAIglDeymyduOocvXXq1Cl0Ol2+GK3GjRtTp04djh49ahzE+fr6Mnr0aOP9c0ePHi0Q09SvX79iL/eaoirEbkmSRNCdIMyV5ihR5rtUDrDhmQ0A/MmfpT7uiSWvcqKI506vmUWrNbNK3Wb5m3T/K0dhkVdVgYi5qXnkUqtc6gT51CrqrEaxW1B9o7eioqIwNzcvsBq/u7s7UVH/XUarV68eLi4u+fYrLHor7z4PoyrEbuklPXdS72CQDESnRpf5Mau74iKvqgI5x9zUVHKpVS51gnxqlXOd1SZ2C2p+9NaDi/uWl6oQuyVJEnsP7CUyNRI3a7cC+77212uEpYbxfKPnGVJvCJkhIUTPmYvSxgalVcHECkN6Ok9t24amfis8nptBLYf820iSxI6PXsfMuTbzlqzk+fbeZVZnbq1BQUH06tWrQK2Ki3+iPPoFOPhQ6G2iqVFg5Yj+mZ/h/mXlqno5VcTc1DxyqVUudYJ8ahV1VqPYLai+0VseHh5kZWWRmJiY72zcvXv3il3ktajorUddGLaqxG718enD6gur0Ut6zFT5n09TpeFo50jvBr1xsHNAatOG7KZNSD9/AXN7+3yDeUmS0EVG8Xzr1nx2/F9sE2JQuDTCXP3fgCn0zAESI27y2ODx9G3lh4ODTZnWqNPp0Gg0ODg4FKy1xRNw+TcwJIFN/jOr6HWQngWthoKTC9WFnGNuaiq51CqXOkE+tcq5zmoRuwXVO3qrbdu2mJmZ5TvTdvXqVUJDQ4uN0arp0Vu96vSisVNjwlPDSchIINuQTaY+kyhtFGm6NAb4DcDbLueMmUKhwOnFF1E72JMVGoo+NRUpOxt9aipZoaGo7O15++OPqVevLue/mczxnesIj4wkISqMk5u/I+jrGbg07cTLzz5JXZcKPstlVwtavQjZmZB0F3TpoM/OmamaeAdcG0PTIRXbJ0EQBEEowUOdiatp0Vv29va89tprTJ48GScnJ+zs7Hjrrbfo1KlTvpmpvXv3ZujQoUyYMMFYT/fu3VmyZAkDBw5k3bp1nDx5Mt86d6bEflVV9hb2vP/Y+/zv0v84GnmUKG2UcXbqwLoDGVh3YL7tLVu2xH3GDOL/t5bMa1fRJyagMDPHsmVLnF4YgaW/P//s389rY8ayffMKrm9cBoDSzIIGXQcze/7HPNexXuVEQbUdBRpbOLseksNy1o0zt4ZGA6HjG2DjWvF9EgRBEITilDbioaZGb6Wnp0tvvvmm5OjoKFlZWUlDhw6VIiMj87Xj4+OTbx9JkqQNGzZIDRs2lMzNzaVmzZpJ27dvL/WxS1IVYreitdHSmXtnpAuxF6SM7IxitzUYDFJGSIikPXVayrhxo9CYp7t370o/rt0gLf3hN+nghdtSelb2Q9dhCpNr1WVKUvgZSQo9LklJ4eXap/IgYm5qHrnUKpc6JUk+tYo6q1jsFtTc6C2NRsOXX35Z5ILCUHhNzz77LM8+++wjHbs6cLVyxdXKtLNRCoUCi7rFx1XVrl2bUSOKft0qjdocPFtVdi/kJ+v/27vzuKir/Y/jr1nZ9x0FBNfcsDS3ypVcS20z00r7mWW7rS6ldq2uXrVszza3a920q6lXS1PRckFccRcVFVRAZIcZlmHm/P4gJkcQQRhgmPN8PHioM9/v+Z7PfGeY43c5bz3oM0DjDC4+9d2bGhFCkJZXhNEk8HdzQK2qtatWap1er+fChQs4OTmZU3bqksFoIKMwA5VChYfao063bWtMOh3G7GyULi6orptJQbJftXpjgyRJUrXoM+HwfyD+NyjKK737t2lniHwMgm+v795VixCC6FNprItL5ny6DoEg0N2JwR0Cua9jsMWNPPUtOzubGTNmsGTJEvLy8gBo3749U6dOZfTo0VbffpGxiA3nNrAlcQsZhRkoURLuHo6PwafR5E3XFkNaGjlr15L/x5+IggJQq3Hu0hmP4cNxbNWqvrsn1TO7yE4VQjBjxgyCgoJwcnIiKiqKM2fOWCxz8OBB7r33Xjw9PfHx8eGZZ54hPz//pq9HY89OlSSr0WfChjdg/6LSAZzWFZQqOLu1NOrs/I767mG1/BCbyLxN8ZxIycVBo8RZq+Zilp4vtyewYMtpSuorF/g6ubm59O3bl2XLlvHKK6+wY8cO1q5dS0REBGPGjGHu3LlW3X6xsZiP9n/EkmNLSNOn4ax2RqPScCzjGJsKNvHbhfLRjPbKkJZG6j9mkb1qNaKwEOVf84Tmbd1K6qxZFBw9dpMWpMbOLrJT586dy6effsrChQuJjY3FxcWFgQMHUlhYCEBycjJRUVG0aNGC2NhYNm7cyPHjx296GrSxZ6dKklUd/g+kHgbPUHALBAdXcPIC7+alg7pdn4ChsL57WSUJV/NZue8SDmolod7OuDtqcHVQ08TTCW9nLVtPXiHmXEZ9dxOADz/8kNOnT7Njxw7ee+897r77boYNG8batWuZMmUKU6dOJSkpyWrb//PSn8SmxOLr5EugSyAuGhfcte40dS2d9H3F6RVc0V25SSv2IXvFSooSEtA2bYra1xeliwtqLy+0oWEYMzPJ+O47xDXfuZL9afTZqUIIPv74Y9555x2GDx8OwLJlywgICGDNmjWMGjWK9evXo9Fo+OKLL1AqS8e1CxcupGPHjpw9e7bCCYqh8WenSlJ16XS6qi1YrIej60E4gUEJhuu+iLT+cOU8nNoKEX3KrV5pFm49+D3uAtl5eYR5O2MospweyVEBxQV6fj10gTuCq5+4Upu1CiH45ptvGD16NBEREeX216RJk/jiiy9YuHAhb7/9do22dSO/xf9GSWEJGrUGQ8nfkUQmkwmnIicyczOJPhvNsBbDrLL9ijTEybtLsrLQ7d6Fyt0dhdryq1qhVKL286f4/HkKjx/HKTKynnop1bdGn5167tw5UlNTLXJRPTw86NatGzExMYwaNYqioiK0Wq15AAfg5FSaKLBz507zIM6eslMbG3uptb7rdHWt3Uma4b5abs+6KjsB/Acwp646chPfffdductbrjV79mxmz55dhz2ytIlNdbq9us5CrsrntCg1FaNOj9LbC5Oo4FS8owMmg4HClBTU102g31DU9++juiKzU62YnVqWY1pZxmm/fv147bXXmDdvHq+88go6nY4pU6YAkJKSYl7HnrJTGyt7qdVe6pSk2lBfWciVfU7VmZkE63SYDMWYHB3LL2A0otHlc/7IEfTX/Ke/IbKX30cyO9UK2alV0a5dO5YuXcprr73G1KlTUalUvPzyywQEBFgcnbOn7NTGxl5qre86s7Kyqryscuu7KM9tR3g1A66b2kKfAQoFxhHfgFtAuXUry8KtD7HnM5mzMR4fVy2OGpXFc0aTicvZhYy/qxnDI4Or3XZt1zp+/Hji4uLYtWsXjtcNDjZv3szIkSP53//+x913313jbVXk59M/s+rsKpq4NkF5zWXZAsHltMuoXdVM6zqN27xvs8r2K1LXp1Or8jkVQpB26hSFR46i9vMrN/1LSdpVlKGhtHn6aVRubnXR7Wqr799HdUVmp1oxO1X917UEV65cISgoyPz8lStX6NSpk/nfo0ePZvTo0Vy5cgUXFxcUCgUfffQREZXMd9bYs1MbI3uptb7q9KzO/FU9n4Ks41CUAm5BoHYAYSodwCkL4I4nIaR1hatWmoVbD/p2cGdrQh77LmTiq9Hi5qBGoVCgLy4hNb+IVk38uL9LCzxdbnw5yY3Udq0zZsyge/fuPPnkk3z88ce0bdsWg8HA6tWree655+jbty9Dhw612pxxw9oNY1/2PlJ0KQQ4B+CodkQIQU5RDoUOhdwbdi/dwruhVDScKVms5WafU+9HHuFKwjmMKalo/P1RaDQIoxFjZiYYDHgOG46jt3cd9vjW2PPvXZmdWk3XZ6eGh4cTGBhocRQtNzeX2NjYCjNOAwICcHV1ZcWKFTg6OnLvvffecFuNPTtVkqwqKBKi3i29OzUvBTLPQ9YFUChLB3DdJtZ3D6tMq1YydfBt9G7lT0GxkcRMPRcydGTrDXQK8WTGfe3wvoUBnDVERkayYcMGjh49Srt27QgLC8Pf359Ro0bRo0cPVq9ebdVJfwNcApjSdQqtvVqTWZRJUl4SF/MuYjAZuE1zG89FPmcXA7iqcO7SBb9XXkbt54chNZXipCQMly+j0GrxenwMng89WN9dlOpZo89OVSgUTJo0iffff5+WLVsSHh7O9OnTCQ4OZsSIEeblPv/8c3r27ImrqyubN2/mzTffZM6cORZHFuwtO1WSrK7ZXdCkM1zcA7kpoHGC0O6lU47YGC8XLTPvb0vC1XyOJ+diNAma+7nSoYkHSmU95AFXol+/fiQmJrJmzRoOHz6Mk5MTw4YNo2PHjnWy/QjPCOb0msOx9GNczLuIWqmmtUdrju44iqumtm+OsW2u99yDc+fO6A8coCQ9A6WrC85duqD28qrvrkkNQXVzumwxO9VkMonp06eLgIAA4eDgIPr37y/i4+MtlnniiSeEt7e30Gq1omPHjmLZsmXl2rHn7FRbZy+1yjobH3up1V7qFMJ+apV1yuzUai13IwqFglmzZjFr1qwbLrNs2bKbtmPP2alVZczXkb9tG3nbtmHMyEDl44Nb3z649u2HyvXGFw/rDXr+uPQH2y9uJ70gHS9HL3o37U2fkD64actftHsxU8/vx1PZeTadohITLf1dGdAukE5Bznz77Td8++23JCQk4OnpyahRo8xHT6UGxmgoTWiI3wCZF0on/G0RBW2G2uTROEmSpLokY7f+cvr0aYYPH46vry/u7u7cfffdbNu27aavx81it959913atGmDi4sLXl5eREVFERsbe9N2bVFJVhaps2aR/tVXFJ05g0mno+jMGdK/WkjqP/5ByQ3uXMwpyuGD2A/46vBXnM46jc6gIyE7gW+PfMt7e94jo8BypvvDF7N587+HWR6bRFpuEfmFJew8m87MVfvp2O0e3nrrLTp06MC8efN4/PHH+eGHH+jWrRsJCQl18TJIVVVSBFv/AVvehaRYKM6H7CTY8yWsexHSz9y0CUmSJHsmY7f+Utb36OhoDhw4QGRkJPfdd1+lc75VJXarVatWfP755xw9epSdO3fSrFkzBgwYUOXpT2xJ1rJ/U3jkCOrAQLRNmqD29S39MzCQwqNHyVyytML1fjz5I4evHibAOYAmrk3wdfKliWsTglyCOJF+gmUn/j5Kqi8u4cPN8aTnFdHMx5lAD0f83Bxo5uNC4u+LSTx7ko+Xr+Wnn37ipZdeYv78+Zw5c4bw8HDmzZtn8R8NqZ4dWwWnN4GzD3iHg6s/eDQFr/DSmxy2/RNMxvrupSRJUoMlY7dGjSI9PZ0zZ87w/fffmy/snTNnDl9++SXHjh274Q0IVYndGj16tMU6H330Ed9//z1Hjhwx19cYlFy9Sv7u3Sg9PFBel8qh1GpRenig2xND9vnhaPz9zc9lFGTwx7k/cBbOKIuVGLCc3doVV2IuxDA8ZDgBLgFEn7zCxStZBHo4YiwupOwr3lBUQOLuDTTpMYz4Yi/y8/PNd9hpNBpmz57NgAEDWLduHUOGDLHqa2FtDTEiqNqMBjixFlTa0lOo11KqwC0YrsbD5QMQ0rV++ihJktTAyditUaPw8fGhdevWLFu2jDvuuAMHBwe+/vpr/P396dy5s3m9msZuFRcX88033+Dh4UFkJVl3thi7VXDuHMa8PNRBgRVGxCjcXClJTsGrknn3KvMzP1dpuaTtK/h0+wo+vcHzI0eOvKXtNySVRQTZTMxNbjKq3FTQukFFR0fVjmAsxpR2GhF4e7mnbabOWmAvtdpLnWA/tco6ZexWldQ0dkuhULBlyxZGjBiBm5sbSqUSf39/Nm7ciNc1t3HfauzW+vXrGTVqFHq9nqCgIDZv3mzRzvVsMXbLMTGJAJ0OQ1oaqCt4W5UY0VQ1HF2qVFUighp6zI2DIZtuuTkYFXpKVBXMCSkELsX5xB85yuVLN56NvqHXWZvspVZ7qRPsp1Z7rlPGblVBTWO3hBC88MIL+Pv7s2PHDpycnPjuu++4//772bdvnznp4VZjt/r27UtcXBzp6el8++23jBw5ktjYWPyvOa14LVuM3TLp9aTs348xLxd1BXWVXL2KKiyMjEuXUF5zOrCgpIApu6aQU5iDn5NfufUyCjNw0jgx5645uGndOJSUxfu/xuPlrMFR+3e8kclkZN30MbiEtuO5t+cwKaqlRTurV69m/PjxbN26lTvuuKNGtda3yk6n2kzMjRAo/7cLRfIh8Krgc1CYAyX+RA4eS6RPy3JP20ydtcBearWXOsF+apV1ytitKm23prFb0dHRrF+/nqysLPMg6csvv2Tz5s0sXbqUKVOmVLjdqsZuubi4mF+H7t2707JlS77//vsbplfYZOyWhwceQ4eQuXQZIjcPpbs7CoUCIQSm3FwoLML94UfwbtLEYjVPPBnedjhLjy+lUF2Iu/bv9fKK8zBoDDzS5hFC/EMAuMfNnY4nc4i7mEWwk6M5p9IkBKF9RnFy9ScUHN+K64jbzft+9+7dTJkyhcjISO65555G/cukjE3E3EQ+CmknQJdWelND2Sz9xTooyIBWA1EG3AaVpAfYRJ21xF5qtZc6wX5qtec6ZexWNd1K7FbZ4c5rw+7L/l3Z3Yy3GrtlMpksrnlrLDwffBD3oUMxFRViSEykODERQ2IipsJC3IcMwevhit8bw5oPY2jEUIqMRSTlJZGUm0RSXhIFxgIGhQ/i4VZ/p3eoVUqmDG5Dx6aepOUVcS5dx4V0HYkZem7r/wgPPvEMc9+dSnh4OA8//DB33nknd911F2FhYbz++ut19VJIVdG8H/R4HpRqyDwHmQmQcbY0O7VZL+j1VqUDOEmSJHsnY7coHYx5eXkxduxYZsyYgZOTE99++y3nz59n6NCh5raqG7ul0+n44IMPGDZsGEFBQaSnp/PFF19w+fLlSicItlUKjQbf55/DLSoK/Z4YSjIzUXl54dKjBw6tWt0wj1GtVDOhwwT6hvRlT8oeMgsz8XTwpHtQd1p5lV8vwN2ReQ9Hsu9CJgeTsigymAj1caZPKz/8n7+LQ69ONE/2GxERwbRp0xg0aBC///57XbwMUlUpFNBpNITdBQlbIecyaF0grCc06QKqWj1RIEmS1Ojc0m/JjRs3EhQUhFqtxsvLi8jISD799FPGjh1b7mjWtdq2bcuAAQOYMWOGxcXZrVu3Lu2MWk1ISAjPPvus+Q5QgP3799O3b1/zv8uuFxs7dmyV0iPeeustdDodzzzzDNnZ2dx9991s3LgRR0dHoPS078aNG3n77bfp168fBoOBdu3asXbtWou7SBMSEkhPTzf/u2fPnvz444+88847TJs2jZYtW7JmzRrat28PlB5RPHXqFEuXLiU9PR0fHx/uvPNOduzYQbt27W7ab1ukUChwbN0Kx9atqr1eS6+WtPQqf/1TRbRqJXe18OWuFuVvELn99tv58ssvLR5r7HdH2TSvMOjyf/XdC0mSJJsjY7f+0qVLFzZt2lRpO9WN3XJ0dGT16tXV6mtDkZOTy5zPvmHNmjXk6XLwaOZJlxHt6dS5FZ38O9EtqBvOmtq/U1aSJEmSpKqRsVt/sUbslsFgYPLkyXTo0AEXFxeCg4N58sknSU5Ovmm79enw0eOEtWjNv2ZOIVWfid4zm9N79rJs4kIWzPmSBQcWMG3nNC7lXarvrkqSJEmS3ZKxW3+xRuyWXq/n4MGDTJ8+nYMHD7J69Wri4+MZNmxYFV7l+mEwGLh30BBKVA70nfURrd9qTotnO9Bl3oM0Gd6Bi6vOkrwzh7PZZ1lwYAEGozxNKUmSJEn1QcZuWTF2y8PDo9zkf59//jldu3YlKSnppjdl1DWdTsfyn37manISPV/9CnzjKS7S4YAfCgShg9uSezKVU78cp809Q4lPjWfH+R10C6p6ukZVNIpYKUmSJEmyMhm7VYexWwA5OTkoFArzoLUi9RW75er6d4bl7gWVz9H3wwOlofQb2FBr/SlTWazUrZLxL42LvdQJ9lOrvdQJ9lOrrFPGblVJQ4/dKlNYWMjkyZN57LHHKk1esMXYrdpUlVipW9XQarUWWWfjYy+12kudYD+12nOdMnarChp67BaUjsZHjhyJEIKvvvqq0mXrK3YrKyuLz7/+nulT36TP1CWYQmPIJR5H/o7DOvX1LgpTcnnw8xFkFaczseNEejWp+oC7KqxxOlXGvzQu9lIn2E+t9lIn2E+tsk4Zu1Wl7Tb02K2yAVxiYiLR0dE3HYjVV+yWp6cnr744kdkfvEfcyk/oOWkCBS6JCArR4MaV2Atkx12m7VPdyFNmE+obSlSrKJuaasSe418aI3upE+ynVnupE+ynVnuuU8ZuVVNDi90qG8CdOXOGLVu24OPjc0t11RUXFxdWrPwvuosn2Tx5KpeWZZG07iSHZm/gzMJd+PYIJnSQD/7O/rx0x0s2NYCTJEmSpMZExm5hvdgtg8HAww8/zMGDB1m/fj1Go9F8vZy3t3elN3nUp/sGRXHg4EGm/3M+0Rs3UFSkwy3Eiw5v3MGdAztwV9Me9A7pTaBLxXftSpIkSZJkfTJ2C+vFbl2+fJl169YBmE/dltm2bVuFExM3FB3atmHN8u9uvqAkSZIkSfVCxm79xRqxW82aNatRv21VSVYW+thYjDm5qDzcce7aFbW3d313S6ojRUVFrF69mr1796JWqxk4cCA9evVg35V9XC24iqPKkc4BnQl2Da7vrlZLQbGR2PMZJGcX4qBW0jnMi2a+NjqnoRBw5TikxIGpBLwjIKQ7qBvm2QFJkiomY7cq6Me1P/v27av09fjiiy9o1qwZjo6OdOvWjb1791o8/80339CnTx/c3d1RKBRkZ2dX2p4tE0KQ/csaLr3wAlc//YzMpUu5+smnXHrhRbJXrbbLAa292b17N+Hh4YwePZpff/2VFStWcO+99xLWLowPNn7Av0/8m2+OfMPrf7zOt0e+tZnEj73nM5m4/ADvbzjJ9zvP8cW2s7z0n0N8+Hs8BcXG+u5e9egz4be3YM3zsOtjiPkCfn0L/juudGAnSZLNkLFblJ4WTUlJsfh5+umnCQ8Pt7h273orVqzgtddeY+bMmRw8eJDIyEgGDhxIWlqaeRm9Xs+gQYOYNm1aFV5Z25a3aROZixdjKixC06QJ2tBQNE2bIoqKyFy6hLxrjsJKjU9CQgKDBg2iRYsWnDhxgvj4eP63/3/0m92PgtwC9s/aT7BDMKFuoShR8r9z/2PZiWX13e2bOpWay79+O8Xl7AKC3B1p5uNCMx9ntCoFG46m8MW2MzdvpKEwlsCWf0DCVtC6gFdE6VE41wC4eho2TYMcmYksSbZCxm6NGoVWq7WYFsRgMLB27Vpeeukli3nvrvfRRx8xYcIEnnrqKQAWLlzIhg0bWLRokXlakkmTJgHl75ptbEzFxWT/sgYAjb+/+XGFSoXa3x9DcjLZv6zBtV8/lBVMn9LQ6HS6+u7CLTEYDBQWFqLT6er8lv558+bh6OjIypUrcXNzIz8/n1XHV6EN0zJ4+mBWvbSK+M3xtOrXCldcMRgNbDq9ib4BfQlwCbj5Bq5RF3WWzVe4Ni6ZTH0x4T7O5t8HCoUCT2ctoOCP0+k81FlHuC2cWr20Dy7tBbfg0kFcGY0jeIVD1jk4uR66T6y/PkqSVGUydmvUqHLtrVu3joyMDPPgrIxCoWDx4sWMGzeO4uJiDhw4YDFlilKpJCoqipiYmCr3vSL1FbtVE4XHj2NITkbp441JlJ+WReHthSElGd3x4zh26FDj7VVXdWu9NoJMqp5r52O83vYF29m+YLvFYz/zs5V7dGuKi4vRF5ewJyEdd0cVAlHukgA3RyVJmUXEJlylqYd1rierzc+p8sJulCVFCLUTVDR9ksoRzmzG2Hl8jbdVXfYS0QT2U6usU8ZuVUlNY7eu9/333zNw4EBzv8q0bt0aDw8PANLT0zEajRW2e+rUqSr3vSK2GLvldP48/jk5GJQKqOgOZZMJTU4OCX/8QcHFizXe3q2yl/gXqeZ+/fVXdAbIyFShVgpKbnBwVleo4EDcEZxSD1u1P7Xx3m2dcoQmOh26krQKn9ca9Jj0l9hlxei7m7Gnz6i91GrPdcrYrSqoaezWtS5dusSmTZtYuXJluedqOjirqvqK3apRW5cvk7pjJ2g1qCroozE3F9QaWg0fgSakaQUtWFd1a83KyqqDXtU+g8FAdHQ0/fr1q/PTqf3798fX15cVK1YAUFhSyFs73yKvOA9vtTc/TfiJsG5h3DXxLgCKTcWkF6TzWufX6OzfuVrbqos6XVxcKDGa+D03jtTcQvw9HMv3w2iiMKeIqLta0a+1XwWt1Fxtfk4VcZkoY47h4uULigr+s5WtRzS9kyFDhtRoO7fCXiKawH5qlXXK2K0qbbemsVvXWrx4MT4+PgwbNqzSbfr6+qJSqaoUu1Vd9RW7VaM2mjXD+Y7byf9zB2pXNxQqlfk5YTQisrJx7tkT54jwSlqxvqrWWvZ+tDUGgwFHR0c8PT3r/Jfm888/z4QJE4iNjWXgwIEADGg1gBXxKzj6v6PoM/V0HNERBxcHhBCk5acR7h9Or+a90Kiq19e6qlOjgSEdgvn6zwSKSwSOmmve10KQlldMkIcT97TyR6Op1V+nFfSlFj7/rQfC4R9Alwbu103xUpRXOrBrez+qevzCtZeIJrCfWu25Thm7VU23ErtVRgjB4sWLefLJJ2/6wmu1Wjp37mzRrslkYuvWreXatRfeY8fh0CyM4otJlFy9ijEvj5L0dIqTktCEhuLz1Lj67qJkRWPHjmXIkCHcf//9TJgwgV9//RVxRHBq/in2Ld5Hm0fa4BDiQGZhJom5iXg6eDKh44RqD+Dq2n2RQXQN9yYlt5Dk7ALyCg1k6oq5kKHH1UHN832b46y17gCu1rgHQ/fnQaGAjAQoyILCHMhOAn06tB4CzfvXdy8lSaoiGbt1jejoaM6fP1/hdXtQes3f7NmzeeCBB4DS5IixY8fSpUsXunbtyscff4xOp7O4ISI1NZXU1FRz/48ePYqbmxuhoaF4N7IJcLVNmxA4axY56/6H7s8/MRUUoHByxHPgADzuuw9NJRe8S7ZPrVazevVq5s2bx1dffWWeF7Jd+3Y8P+d5ijsVk2/IR6VUERUWxX0R99HCq/zlFQ2Ns1bN9Pvasi4umY3HU8nSFaNUKuh/mz/DOzWhfROP+u5i9bR/sHRKkaP/hdQjIAzg0wJuGwbtRoDKRgakkiTJ2K1rff/99/Ts2ZM2bdpU2E58fDw5OTnmfz/66KNcvXqVGTNmkJqaSqdOndi4caPFzQ4LFy60uEmh7IaNsrtcGxtNQAC+E57G+4nHMel0KF1cUDqWv5ZIapy0Wi1vv/02U6ZMITk5GbVaTWBgIAqFAoPRQG5xLo5qR1w0NjAdxzWctWpGdQ3loc5NySkw4KBW4ubYsI8gVqrZXRDWEwqzwWQEJy9Qqm66miRJDYuM3brGjz/+WOnzFfXhxRdf5MUXX7zhOu+++67FgNRWXc6/zOW8y6iValp7t670S1gYjRSfO4cxJweVhwcOrVtbXCNXE0VFRWxZ+xPpSfGENgmi9/DHUTp71UrbtyI1p5Bz6fmoFAraBLrj4WzDX+y1SKVSERISYvGYRqXBx8mnnnpUOzQqJb6uDX+ewypRKEoHb5Ik2SwZu3WdoqIiOnXqhEKhIC4u7qavx81itwBiYmLo168fLi4uuLu706tXr1u+5q+upenTmLtvLm9sf4P397zPrJhZvBz9Mj/H/0yJqaTc8voDB7j8+hskT51G6qz3SJ46jcuvv47+JvFlVfHNpx8SGujDfY+OY9ybs+k3+mVahTfltwUvQ0lxjduvjmx9MfM3nWLi8gNMX3OMd9Yc4+ll+/huxzkKDTYWwyRJkiTZJBm7dZ233nqL4OCqBXNXJXYrJiaGQYMGMWDAAPbu3cu+fft48cUXKz3t3FBkF2YzO3Y2f176E7VSTVO3pgS4BJBXnMfyk8tZenypxfL6Awe4MncuRadPo/LwQBMSgsrTk6LTZ7gyb36NBnJfffoRz77yBkNaO3Ds3e4ULX6AXdN70cLXgfvf+IzNCyaWhnrXAV1RCbPWn2DD0RQUQIiXM8EejhQZTPy4N4mPt5zGZJI5sZIkSZJ1yditaxIbfvvtN37//XdWrVpV4WDzelWJ3Xr11Vd5+eWXzf+Gv68BbOi2JG3hbPZZmro2Ra0sfasoFUr8nf3JKszit/jf6Onbk1D3UITJRMrSpRRmZaNp2pQShQKMRlCrEYGBGC5dwrBsGcFt2qCo5gBWr9fz9jszGNfNh8+f7gFKLQYTRDbzZcWk3tw3bztvfLKSXQ9ORBHYrsI2ajOmaePRVA6eTSHQwxGt2ojpryNvnlpQm4xsPZpEnwh3OjT1NEc3SZIkSVJtk7Fbfw3irly5woQJE1izZs0NUxGqG7uVlpZGbGwsY8aMoWfPniQkJNCmTRs++OAD7r777hvW0xBit4QQRCdGo1VqUaK0OFUO4K5xZ+F9C1nFqqpvcPPv8Pnnt9zfJbE6lsSuv+Hzbi2q/p6xti2TS/8sLq7b07wy5qbxsZda7aVOsJ9aZZ0ydqtKahq7JYRg3LhxTJw4kS5dutzwpozqxm6dO3cOKL25Yf78+XTq1Illy5bRv39/jh07RsuWLSvcTkOI3TIKI4n5iZiEibT8iiN6pJv7tZ7ii+w55qaxspda7aVOsJ9a7blOGbtVBTWN3frss8/Iy8u76UTE1Y3dKjt69eyzz5pPud5+++1s3bqVRYsWMXv27ArXawixW0IItv65lZT8FPxd/MutK4Rg4A8DGdV6FCOaj6AoIYG0me+idHVF6exUbnlTQQGmvDz8Z87E4QaD1xtZt24dY8eO5cDkdrRsUX7dDXHJPPbFXmK/f5NWD067Ya21FdM0Y+0Jjl7OoYl3+TqFEFzMLGB4ZDDj725W56dTZcxN42MvtdpLnWA/tco6ZexWlbZb09it6OhoYmJiykVddenShTFjxrB0qeUF/GW13Sx2q2x719d72223kZSUdMN6GkrsVlRYFIuOLcIojOVm1c8szMTL3Yv+Lfvj6e6JuOMOStreRsHRY2g9PCwG80IIDCmpOLZri3+XLhbPVcXIkSN57ZUX+WRbKktua45C8/e8c8UlRj7dGE/XZm50ve//4AZxWbUZ0zSkczgn0uMRKkeLGCaAnAIDrq5qBt4ejqdn/U0Ca88xN42VvdRqL3WC/dRqz3XK2K1qupXYrU8//ZTDhw8TFxdHXFyc+RTYihUr+OCDDyrcTlVit5o1a0ZwcDDx8fEW654+fZqwsLBbqq8u9QvtRxvvNlzOv0xWYRYlphKKjEWk6lLRG/QMDh9MiHvpXGAKhQLvxx9H7elBcVISxvx8REkJxvx8ipOSUHl44P3449UewAE4Ojoyf+5clu3N4NGP/yT2aAKZOTp+P5RE1HubOZCYy7zXHge/urlhpHcrfzqHeZOSU0h6fhEGo4niEhNXcgvJ0hcT1dafdsG1d8RUkiRJkioiY7egXBuurq4ANG/e3Hy9HlQ/dkuhUPDmm28yc+ZMIiMj6dSpE0uXLuXUqVP897//rbTfDYGHgwdTu03lhxM/EJMSQ6ou1Xx36tCIoQyNGGqxvFPHjgRMm0bmDz9SdDoeY3YWCo0Wp44d8R79GE6Rkbfcl3ETJqJRKZg2bQrd5xwwP96hqTubvphCr/GzSicvrQNOWhVv33cby3ZfYNupq6TmFqIAfFwdeKxrKCPvDLmlwaokSZIkVYeM3aqGW4ndmjRpEoWFhbz66qtkZmYSGRnJ5s2bad68ebW2XV+8Hb156Y6XGKUfxeX8y2hUGlp4tsBBVfGs9U4dOhA8+58Unz+PMTsHlYc72oiIWhnUjPm/Zxk19ml2bd7A1cQThIU0oXP/B1E41P00Hu6OGl7s15LR3cK4kKFDpVDQwt8VFweZOylJkiTVDRm7VYFmzZpVuL1bid0CmDJlisU8cbbIz9kPP2e/Ki2rUChwiIiwSj9UKhW9Bg0Dhlml/erydtHi7XLjaXPKKcqHgkzQuoKzt9X6lVWYhbHIiJejF47qyv+zUmI0kZ5fOhWKp6OSC+fPoVQqad68OapaikurS8bsbEw6HSovL5RWuJtbkiSpoZCHDSSpLuSlQtyPcGYzGPSg0kBoT+g0Gvzb1NpmjmccZ71+PT/98RMmYcJV60rfkL7c3/x+PBwsb7QoMZr47Vgqvx5NISk9j7O//5uLu9dSkJMBlF5m8PLLL/Pqq6/aRMJIYfxpctauQX/gIJSUoHR2xqVXLzwffAC1j21ntkqSJFVEZqdep7azU/v06WNRo0KhYOLEiTdtV2pEcpNh/atwaDmUFIJD6TWXxG+ADa9B8qFa2cyelD38a/+/OFtyFiVKnDXO5Bfn81P8T/wz9p/kFP19KYDJJPjqjwQ+3XqGhCs5xC2ezpnfl+HT/h46P7eAV+YvoV+/frz55puMHz++RkfC60LB4cOkzvoHedHbUCgUKJ2dMRUUkLNqFanvvktJFacbkiRJsiUyO/U6tZ2dCjBhwgRSUlLMP3Pnzq1S+1IjsX8xXI0H73Bw9f/rVKoPeEdAfhrs+gRMxhptQm/Qs/jYYvQlerwV3ng4eOCiccHP2Y9gl2BOZJzg1/N/X4d6MCmLX4+k4OGkwXA2huQjO4l6aR4Dnp5GaLs7OaOJ4LX3Pmbx4sUsWbKE6Ojomr4KViNKSsj49juMWdlow8JQeXqidHFB7euLpmlTCs+cIevnhn8jkSRJUnXJ7FQrZ6cCODs7m18HyTbodLpaaigDTm4FpTsUA5RYPq/1g8snISEGgm+/5c3suryLSxmX8HPyI7soG0OBwXwKVIECTYmGTac3MSh4EFqVlt8OXUCv1+Hn5MLObasIaNWJwDZ3YCgqwEUlyMjRs+nwBSY+9BD/+te/+PLLL+nevfutvw617NosXMPx42SfS0Dl5W3xn8gyJU7OXN2+HYcHRqCq5mTZMvtWkqSGTGanWjE7tcwPP/zA8uXLCQwM5P7772f69OmVxmc1hOzUxqa6tZZNM1NnXr2nTjazlPITV5f598TeFv/+E3jzr7+fPHmS1atXW69jdeHnldVepa6zbytiL59Te6kT7KdWWafMTq2ShpqdCjB69GjCwsIIDg7myJEjTJ48mfj4+Eq/EBtCdmpjZU+1SjVXX9m3FbGX96691An2U6s91ymzU6ugoWanAuYjggAdOnQgKCiI/v37k5CQcMO54hpCdmpjU91as7KyamfDQqDc8CqK1MPgGQZcN19efio4uGF88HtwcLvlzVzRXeGdmHdAgCHXgK+fL4q/tiUQXMq/RK8mvXg+8nkANh2/wpd/JBDk4cjJjf/m+O8/Mfy9H3By96a4xERabhGT+rcgRJ1L165dmTt3LuPHj7/l/tW2a7NwlXo9qW++hamwALWvr8VyQghKLl7CsVMn/N6eVu35ChvC6VR7+ZzaS51gP7XKOmV2apW221CzUytSdpr47NmzNxzENZTs1MaoqrV63iCD9Zbc/TT8/g4UXwG3QFBpS29k0F0FjYBuT0BASI024enpyaDWg1hzdg0l2hLUjmrUKjXFxmLS9Gn4efrxUIeHzHUN6ezCH+fzOZmaR7NeD3Nmx//Y9tlkOo16E5N/SzqGB6DNOs/IF54jPDycZ599tu5PMVfCIgvXzw/lQw+S+e/lKHPzUHl5oVCpEAYDhqtpOHl5ETB6NM5eXvXd7Rqxl8+pvdQJ9lOrPdcps1OrqSFlp1akbNqSaweUUiPX7G7oMw1cAyD3MmSeg+xEUDtCt2eh05ha2cyTbZ9keMRwUMBl3WUu5l0krSCNpq5Nea3La7T2/jtb1s1Rw/T729KlmRcGrTsdJ8ynqKiIbfOf5cDsR/nPK4MZOnggnp6ebNmypUEN4Cri+fDDeI0ejUKjxnD5MsVJSRhSU9H4++M36RWc77j1m0YkSZIaKpmdivWyUxMSEvjxxx8ZMmQIPj4+HDlyhFdffZVevXrRsWPHSvstNTKtBkCzuyAxpvQInINr6WS/LrU3Ca1GpWFs27E4nHPAt6MvBgwEOAdwu//taFXlbygK8nBi7kMdOZGSy+kr4YhR/ck8vY8Lxw+iUqno378/99xzj03kwCpUKrxHP4b7oIHoDxzAlK9D7euLc5fOKJ2c6rt7kiRJViGzU6uhutmpWq2WLVu2mAd3ISEhPPTQQ7zzzjvV2q7USGhdoGXUzZerIXelO1GhUVU6jK9QKGgX7EG74L/SHDqHAA9at4NWpPb2xv3ee+u7G5IkSXVCZqdWoLayU0NCQvjjjz+q11kbpzPo2H5xO9svbiezMBNvR296h/Smb0hfXDQ3vkjcpNORt307+dHbKElPR+XtjVvfPrj06cP66Gg+++wz9uzZg0ql4t5772X0+OfIdotg59l0ikpMtPR3ZUC7QHpE+KBU3uKRo+yLcGo9JGwrTVbwbQlthkJ4b1DaXoaoJEmS1LjJ2K3r1Hbs1rPPPkvz5s1xcnLCz8+P4cOH39JdrrYguzCb9/e8z9eHv+Zs9ll0Bh1ns8/yzeFveC/mPbIKK77j05idTcp775P+xZcUxsdj0ukoPnuWq19+xYv9+vHAAw9QVFTErFmzmDJlCoePneDh+wYw9+PPScstIr+whJ1n03lv/Qm++uMsJtMtDPiT42Dt87DvO8hLhqI8OP8nbHob/pxf40QFSZIkSaptMnbrOrUdu9W5c2cWL17MyZMn2bRpE0IIBgwYgNHY+AYFy08u5+jVowS6BNLEtQm+Tr40cW1CoEsgxzKO8e8T/65wvczlP1AQF4c6IABt06alcUlNmrDTaOTrAwd4f8QIdu7cyeuvv86kN96ix5uLaNpzBGd++QSngiv4uTnQzMcFVwc16+JS2H46rcLt3JChELZ9UBpS7x0B7k1K47G8I8DRA078AvE3T/CQJEmSpLokY7esHLt17TxxzZo14/333ycyMpILFy7ccIoRW5RekE5McgwuwgVFsQIDf89SrUCBi8mFned3MixkGH7OfubnSjIyuLp9O8LZGaNSCdfMbr3k1Enae3kxQqEk+9w5NAEBRJ+8wqWrOfR4ZCLrDkdzYstKujxSejrbWQkZhXrW7j9P16YuFhfkXxvTVO5asbPRkHoOPIKhyASYrnnSBQrT4dAqCOkDtXCRf0OYe0ySJEmyfTJ2qw5it8rodDoWL15MeHg4ISE3nhfMFmO3zmWeI784n3UPr6t0uZ/5udptt/9lNfxSccLFya0/c3KrZZvbgU+rvRWAg5U8dwBYckutXs+aUU4y5qbxsZda7aVOsJ9aZZ0ydqtKGnLsFsCXX35pvkO2devWbN68udLBrC3Gbl0suUi+Pr8WetP41UWUkz3H3DRW9lKrvdQJ9lOrPdcpY7eqoCHHbgGMGTOGe++9l5SUFObPn8/IkSPZtWvXDac4scXYLb1Bz8E/DzJixQh8HX3LPZ9emI6r1pU5d82xuEvV9FdkkjEnG7W/v8U603fuZNfFS/x2//2EfDgflZsbh5KyeP/XeJyM+fz27mgih42n7b2PAqXvv0tZBfRt5cekqJblai2Labq+VkVyHMpNk0uvfyt3B61AkZ2IKaIPpn4za/AK/c2ap1NlzE3jYy+12kudYD+1yjpl7FaVttvQY7c8PDzw8PCgZcuWdO/eHS8vL3755RdzH69ni7FbHhoPBocP5t8n/02huhB3rTsKhQIhBLnFuRi1Roa2GUoTvyaWK3p6onxgBBmLF6PSF6D08DCvN755C9adPct7F5NY5O6Oh4cH97i5E7HrDCvn/gO1gxO39X0QB0cXTEKQmlOIp7s7D3Vvhaenh8VmLGKarq/VvRec7gIX94CzI2j+mhxWmCA3Bdw9oOsYqM0oLiuz55ibxspearWXOsF+arXnOmXsVjU19NgtIQRCCItr3hqLES1HMCR8CEXGIhLzEknKTSIxL5EiYxGDmw3moZYVvzc8RozA4/77EcXFGBITKU5MxJCYSGtHRxaOe4oNhw4RHBzMsGHDGDpkMEteHkpx+iUix88muVDDhXQdiRl6XBzUvNSvJR2aelS4nRtSKiFqJjTpAvlpkHEWMhNK47G0znDP69C0y83bkSRJkqQ6JGO3sF7s1rlz51ixYgUDBgzAz8+PS5cuMWfOHJycnBgyZEil/bZFGqWGZzs+S7/QfsSmxJJZmImXgxfdgrrRyqvVDeObFGo1Ps8+i2u/fuhjYijJzETl6YVLj+481bo1g95/j++++46YmBi0Wi0ffvghj415gtNZRg4mZVFkMBHq40yfVn74u1cvhcPM1R+GfVZ6NO7i3tJpR7zCoEV/cK/alDOSJEmSVJdk7FY1VDd2y9HRkR07dvDxxx+TlZVFQEAAvXr1Yvfu3fhfd/1XY6FQKGjl1YpWXq2qvZ5jq1Y4tiq/XnBwMDNmzCj3uJ8P3NWi/PV3t0ythfBepT+SJEmS1MDJ2K0K1FbsVnBwcJ3ciVhdxnwdupjd6A4dwvf0GXL0ejz69kVzzbV8OTm5zPnsG9asWUOeLgePZp50GdGeTp1b0cm/E92CuuGsqf07ZSVJkiRJqhoZu3Wd2o7d+uabb+jTpw/u7qUX+mdnZ9+0TWsqvnCB5Lfe4uqCj9FFb8PldDzZS5dx+bXXyPvresLDR48T1qI1/5o5hVR9JnrPbE7v2cuyiQtZMOdLFhxYwLSd07iUd6lea5EkSZIkeyZjt65T27Fber2eQYMGMW3atCq1aU2mwkKuzP+QovPn0AQFoQkLxeDjgzqkKaZ8HelffkXesePcO2gIJSoH+s76iNZvNafFsx3oMu9BmgzvwMVVZ0nemcPZ7LMsOLAAg7FxT+IoSZIkSQ3VLQ3iymK3yiK3pk2bxtq1a/ntt98sTrWWxW5FREQwefJkvL29K5wMz9/fn8DAQMLDw3n55ZcJDw+3GJQNHjyY999/33xDwfUiIiKYOnUqM2fONMdubdu2DV9f33KxWx07dmTZsmUkJyeXO6JXFrs1f/78Kr0O18ZutW3bloULF+Ls7MyiRYvMy0yaNIkpU6bQvXv3KrVpTfrYWIrPnUMbFIzimtueFUolxb6+5GdlsWj2HK4mJxE5egr4nqe4SIeqyA2FURA6uC1urfw49ctxPBU+xKfGs+P8DnQ6Xa38SJIkSZJUdTJ2qw5jt6rKWrFbuuPHESYTQqNGCBPCVHqNnzAJblu8yGLZ3Qsqn6PvhweWAbCBDbfcn+vJOKqak3U2PvZSq73UCfZTq6xTxm5VSUOP3aoua8VueZ88hXt+PsXXnO4FuJpetWQLa5NxVLVH1tn42Eut9lIn2E+t9lynjN2qgoYeu1Vd1ordylepyTh7Fg8fHxQqFcIkuJp+FT9fP0489RSGpIuscnBg1m+/0mfqEkyhMeQSjyN+5jZOfb2LwpRcHvx8BFnF6UzsOJFeTWpnSg4ZR1Vzss7Gx15qtZc6wX5qlXXK2K0qbbehx25Vl7Vit9x79yJ31SpKUlLRNGkCytIBt0KpwDE7Hwc3N158/TXm79hJ3MpP6DlpAgUuiQgK0eDGldgLZMddpu1T3chTZhPqG0pUqyibmmrEnuNfGiN7qRPsp1Z7qRPsp1Z7rlPGblVTQ4/dqk8qNzf8J72C2tub4qQkSlJTUefkYkhMAqMRr1GP4nvXXaxY+V90F0+yefJULi3LImndSQ7N3sCZhbvw7RFM6CAf/J39eemOl2xqACdJkiRJjYmM3cJ6sVsAqamppKammvt/9OhR3NzcCA0Nxdvbu9K+W4NTZCTB/5pDXvQ28mNiKEm+jOvd9+Ax4F4c27dHoVBw36AoDhw8yPR/zid64waKinS4hXjR4Y07uHNgB+5q2oPeIb0JdKnZEUdJkiRJkm6djN2qhurGbgEsXLjQ4iaFshs2yu5yrQ+a4GC8Hx+D26MjOfTrr3QaMqTcId8ObduwZvl3N2hBkiRJkqT6JmO3KlBbsVsA7777rsWAVJJs0cVMPfsTMykoNuHv5sCdoW4k7vuVHRv+x84jZ1C6edFrwP2MGfO4+Uh2gyAEJB+CK8dBmMCvDTTpDKpavRxYkiSpXsjYrb8MGzaM0NBQHB0dCQoK4oknniA5Ofmmr4etxW5JUnUUlRj5PPoML/54kM+iz/L9znN8tWo9yx7rz1MPPsWLHy5j0/Z97Nq4leefe47goCB++eWX+u52qdwUWPsirHsJdn0Cuz+D9ZNg9TOQea6+eydJklRjMnbrL3379mXlypXEx8ezatUqEhISLK7Lq4itxW5JUnV9v+M8vxy6jFKhIMzbmeYuhYzY+x2L/jzKaV0BU7u2Zun93VjYN5L/dG5NRy9HRo4cya5du+q348V6+P0duLgHnDzBOwJ8moOLL6Qeho1TQZ9Zv32UJEmqoVs6p1AWuwWYo7e6d+9O//79WbJkiXlC37LYLSid+Hfu3Lls3ryZwYMHW7Tn7+9vnmLk5Zdf5tNPP+XgwYP0798fKI3dun6da0VERPDqq6/SvXt3c+yWl5cXAwYMKBe7BbBs2TICAgJYs2aNObHh1VdfNbcXFhbGlClTGDFiBAaD4Ya3CF8buwWl179t2LCBRYsWMWXKFKA0dgvK3zUrNQ4NLS7MYDBQWFiITqer8a3tqTkF/HroAk4KcFMrMRYb8Y//H8kJKcTl6ni5Uwtu83bHYDRhUKvQBLgzRa3iFaHmgw8+4Oeff66lqsq7aZ2nN0NiHLgHgckBiox/PaEFp6aQfBqOrIMOj1itj5Wx5pyIkiTZDxm79dcg7lqZmZn88MMP9OzZ0+ILwtZjt65nL5EoYL1aG9T1X3Xs07izN3zu3KXfbOC1eeqvn7pXnYg5e/mc2kudYD+1yjpl7FaV1DR269r+fv755+j1erp378769estnrf12K0bsZdIFLCvWqWG61Yi5uzlvWsvdYL91GrPdcrYrSqoaezWtf0dP348iYmJ/OMf/+DJJ59k/fr15ppsPXbrevYSiQLWqzUrK6vW2qoNBoOB6Oho+vXrV+M6Y89n8q+N8fi6OaBVl14+23b3R5zdHsvyy1eZf09H3BzUuDtqUCgAk8D5aj6fFhs4cCmbEydOoFKpaqGq8m5Wp3Lv1ygP/4jwCgcU5Z5XZJ/H1HIQpt5TrNK/m6nO6VR7+ZzaS51gP7XKOmXsVpW2W9PYrWv76+vrS6tWrbjtttsICQlhz549FSYw2GLs1o3YSyQK1H6tZe/bhsJgMODo6Iinp2eN6+zTwY2fj2RwIUNPqIsTCoWCq7f1ZcCZBP596SprziXzQqfmOGlKP2PqXD0XjCVsP5nEa6+9jo+PT22UVKGb1tlpOFz4DUy54Opn+VxBFri4wO0joIHtv8rYy+fUXuoE+6nVnuuUsVvVdCuxWxUpmy7l2mvTrmWLsVuSVB0OahXP9WmBp7OG8xl6MnTFXPK8k1MdOvJCRBDbLl7l3Z3H2H76EsfiL/HtyYtMOnyOtm3bMXny5PrtvF9ruGMsGIsg83zpwK0wB7IuQGEutH8IQqp+3a0kSVJDJGO3gNjYWPbt28fdd9+Nl5cXCQkJTJ8+nebNm1sMyBpD7JYkVUfnMC8+GNGBNXGXiT2XQbERErq+zN23tWX6+tWsPnCGeUcvAODu6szzL73MjBkzcHNzq9+OKxTQeRx4hMDx1XD1FAggoD20GwGth5YuI0mSZMNk7Bbg7OzM6tWrmTlzJjqdjqCgIAYNGsQ777xjcVqzscRuSVJ1tA50Y/KgNuQXlVBoMOLuqEGr7oHplbeZlHaR9PQMtK7eBAcHV3r3eZ1TKKBlFLToX3okTghw9paDN0mSGg0ZuwV06NCB6Ojom7bTmGK3jHl5FBw/jlNCAobUVDQhIeWWyc3LZ/HKtVzNyKLtbW0YOaQfalUVzsCbjHDlWOkXp5NX6dEPpXUucJfqjquDGleHv39lKJVKvAPD8A4Mq8deVYFCUTp4kyRJamRk7NZfPvjgA3r27Imzs3O1Llb/+eefadOmDY6OjnTo0KHc1AGrV69mwIAB+Pj4oFAoiIuLq3Lb1iCKi8n88T9cev4F0t57H/9f1pD66mtcmTefkvT00mWE4Lk33sEvMIhJTz/OB5NfYsywewkIb82iXzZVvoHEGFg1HtY8D7++Ufrnf/8PLtTzDP6SJEmS1MjI2K2/FBcX88gjj1T5jliA3bt389hjjzF+/HgOHTrEiBEjGDFiBMeOHbPo+913382//vWvKrdrLUII0r/9lqzlyzHpdKgDAzB4e4FaRd6WLaR+8AHG3FyeeuF1Fn74AQFdBnH/+//lia930GfSJ5QotTwzagQ//vpHxRtIjCmNOrpyvPQInFc4OHlD2gnYPF0O5CRJkiSpFsnYrb8SG8quW6vKqeIyn3zyCYMGDeLNN98E4L333mPz5s18/vnnLFy4EIAnnngCuPHp5bpUdOYM+VujUXl4oPLwwCRMoFRS5OyMQutA1rHjXFn+A8u++ZSw/o9zz8NPl86RJ0yEtOlE4Gsfse79Cbz99jsM6/WbxZyAmEyw4yvIzQLPZmBSQJGJ0pijEMi+UPq8T0e4wXWTMopIkiRJkqpOxm5VELt1I82aNWPcuHHma9xiYmIsJuUFGDhwYKWne6vCWrFbebt3Y9TrUfv6YBImhKn0Gr+2ixf/vdCW0hmnE7cuJ3Hr8grbuXD14k3uPjxUyeM/3HCt6kQRVZeMf2lc7KVOsJ9a7aVOsJ9aZZ0ydqtKait262aaN2+Or6+v+d+pqam10u71rBW75b1/P266fAzVTLKoK7cSRVRd9hz/0hjZS51gP7XaS51gP7Xac50ydqsKait262auvU7PmqwVu5WdnUPOmbOo/fxQKBQIk+Bq+lWOjx2HQqnAkJLC0swcPj64nyGzfsLDq/wdfUe3rOLoL1+yZU8cd7S85o7W9HhU6yeBgytoKgg+N+igKBfj0I/Br02F/bPm6VQZ/9K42EudYD+12kudYD+1yjpl7FaVtltbsVvVFRgYaFOxW+5330X+unWInFxUXl6YlKV3E7s4aMFQQgkKJj4/kY/Hj+follX0e/wVi0F5sT6fM3+soXmXPvTt0t7ymjiPrhDaAS4fBHcvy7m4hCidbiQkElp0q9d5uuw5/qUxspc6wX5qtZc6wX5qtec6ZexWNdVW7FZV9OjRo9zRuc2bNzfY2C1tRARugwZiys/HkJqKKCoCoxFjZhYlyck4tm9PxEMP8sykt0iM/pGNX8/iUsJJ8nOyOLVnK2ven4AhP4s5H7xvOYCD0oFZ12fB2Qsyz0FRHphKSv/MPAdOnqXPy4lWJUmSJKlWyNitvyQlJZGZmUlSUhJGo9E8n1uLFi1wdS09Pdi/f38eeOAB8+S+r7zyCr179+bDDz9k6NCh/PTTT+zfv99inruyNpOTk4HS6/eg9CheTY/YVZdCocDnqadQe/uQs2EDJVfT0OTmQqAz7kMG4/3kk6hcXfly3vu4ubnxxYJ5/B67wbx+UMsOfLfoNx6KusEgtWlnGDQH9n4LV06APgNUDtCkC3R9Gpp2qXg9SZIkSZKqT1TT2LFjBaUphEKtVgs/Pz8RFRUlFi1aJIxGo3m5sLAwsWDBgnLrDxw4UAwePFgIIcS2bdvMbZW1Fx4eLt544w2Rn59vXuf65cp+xo4dW6U+m0wmMX36dBEQECAcHBxE//79RXx8/A3ruvZn27ZtFjXNnDnTYr2VK1eKVq1aCa1WK9q1ayc2bNhg8fzixYsrbPf6diqTk5MjAJGTk1PldW7GqNeL3IMHxcZPPhH6lJQKlyksLBRLVq4VcxcuERu2xwqTyVS1xk0mIdLihUjcI0TaqdJ/17Pi4mKxZs0aUVxcXN9dsSpZZ+NjL7XaS51C2E+tsk7rfH9fS8Zu/aUqdVVU0yOPPMIjjzxyw3XGjRvXIDNSlU5OOLZvT2FSEmofnwqXcXBwYOwjw6rfuEIBfq1q2ENJkiRJkipTa9fESZIkSZIkSXVHDuIkSZIkSZJskBzESZIkSZIk2SA5iJMkSZIkSbJBchAnSZIkSZJkg+QgTpIkSZIkyQbJQZwkSZIkSZINkoM4SZIkSZIkGyQHcZIkSZIkSTbolrJTpbpVllaRm5tbq+0aDAb0ej25ubloNJpabbuhsZdaZZ2Nj73Uai91gv3UKuv8+3u7JqlTlZGDOBuQl5cHQEhISD33RJIkSZKk6srLy8PDw6PW21UIaw0PpVpjMplITk7Gzc0NhUJRa+3m5uYSEhLCxYsXcXd3r7V2GyJ7qVXW2fjYS632UifYT62yztIjcHl5eQQHB6NU1v4VbPJInA1QKpU0bdrUau27u7s36g/YteylVlln42MvtdpLnWA/tdp7ndY4AldG3tggSZIkSZJkg+QgTpIkSZIkyQbJQZwdc3BwYObMmTg4ONR3V6zOXmqVdTY+9lKrvdQJ9lOrrNP65I0NkiRJkiRJNkgeiZMkSZIkSbJBchAnSZIkSZJkg+QgTpIkSZIkyQbJQZwkSZIkSZINkoM4G/bFF1/QrFkzHB0d6datG3v37q10+Z9//pk2bdrg6OhIhw4d+PXXXy2eF0IwY8YMgoKCcHJyIioqijNnzlgsk5mZyZgxY3B3d8fT05Px48eTn59f67VdrzZrNRgMTJ48mQ4dOuDi4kJwcDBPPvkkycnJFm00a9YMhUJh8TNnzhyr1FemtvfpuHHjytUwaNAgi2Uawz4FytVZ9jNv3jzzMg19nx4/fpyHHnrI3M+PP/74ltosLCzkhRdewMfHB1dXVx566CGuXLlSm2VVu0/Xqkqds2fP5s4778TNzQ1/f39GjBhBfHy8xTJ9+vQptz8nTpxY26WVU9u1vvvuu+XqaNOmjcUyjWGfVvT5UygUvPDCC+ZlbGGffvvtt9xzzz14eXnh5eVFVFRUueXr7PtUSDbpp59+ElqtVixatEgcP35cTJgwQXh6eoorV65UuPyuXbuESqUSc+fOFSdOnBDvvPOO0Gg04ujRo+Zl5syZIzw8PMSaNWvE4cOHxbBhw0R4eLgoKCgwLzNo0CARGRkp9uzZI3bs2CFatGghHnvsMZuqNTs7W0RFRYkVK1aIU6dOiZiYGNG1a1fRuXNni3bCwsLErFmzREpKivknPz/fZuoUQoixY8eKQYMGWdSQmZlp0U5j2KdCCIsaU1JSxKJFi4RCoRAJCQnmZRr6Pt27d6944403xH/+8x8RGBgoFixYcEttTpw4UYSEhIitW7eK/fv3i+7du4uePXtaq0yr1Dlw4ECxePFicezYMREXFyeGDBkiQkNDLfZX7969xYQJEyz2Z05OjrXKFEJYp9aZM2eKdu3aWdRx9epVi2Uawz5NS0uzqHHz5s0CENu2bTMvYwv7dPTo0eKLL74Qhw4dEidPnhTjxo0THh4e4tKlS+Zl6ur7VA7ibFTXrl3FCy+8YP630WgUwcHBYvbs2RUuP3LkSDF06FCLx7p16yaeffZZIYQQJpNJBAYGinnz5pmfz87OFg4ODuI///mPEEKIEydOCEDs27fPvMxvv/0mFAqFuHz5cq3Vdr3arrUie/fuFYBITEw0PxYWFlbhLyJrsUadY8eOFcOHD7/hNhvzPh0+fLjo16+fxWMNfZ9e60Z9vVmb2dnZQqPRiJ9//tm8zMmTJwUgYmJialDNjVmjzuulpaUJQPzxxx/mx3r37i1eeeWVW+nyLbNGrTNnzhSRkZE3XK+x7tNXXnlFNG/eXJhMJvNjtrZPhRCipKREuLm5iaVLlwoh6vb7VJ5OtUHFxcUcOHCAqKgo82NKpZKoqChiYmIqXCcmJsZieYCBAwealz9//jypqakWy3h4eNCtWzfzMjExMXh6etKlSxfzMlFRUSiVSmJjY2utvmtZo9aK5OTkoFAo8PT0tHh8zpw5+Pj4cPvttzNv3jxKSkpuvZhKWLPO7du34+/vT+vWrXnuuefIyMiwaKMx7tMrV66wYcMGxo8fX+65hrxPa6PNAwcOYDAYLJZp06YNoaGht7zdmvapNuTk5ADg7e1t8fgPP/yAr68v7du3Z+rUqej1+lrb5vWsWeuZM2cIDg4mIiKCMWPGkJSUZH6uMe7T4uJili9fzv/93/+hUCgsnrO1farX6zEYDOb3Zl1+n6qrvKTUYKSnp2M0GgkICLB4PCAggFOnTlW4TmpqaoXLp6ammp8ve6yyZfz9/S2eV6vVeHt7m5epbdao9XqFhYVMnjyZxx57zCK8+OWXX+aOO+7A29ub3bt3M3XqVFJSUvjoo49qWFV51qpz0KBBPPjgg4SHh5OQkMC0adMYPHgwMTExqFSqRrtPly5dipubGw8++KDF4w19n9ZGm6mpqWi12nL/Ians9aoJa9R5PZPJxKRJk7jrrrto3769+fHRo0cTFhZGcHAwR44cYfLkycTHx7N69epa2e71rFVrt27dWLJkCa1btyYlJYV//OMf3HPPPRw7dgw3N7dGuU/XrFlDdnY248aNs3jcFvfp5MmTCQ4ONg/a6vL7VA7iJLtmMBgYOXIkQgi++uori+dee+018987duyIVqvl2WefZfbs2TYTIzNq1Cjz3zt06EDHjh1p3rw527dvp3///vXYM+tatGgRY8aMwdHR0eLxxrBP7dELL7zAsWPH2Llzp8XjzzzzjPnvHTp0ICgoiP79+5OQkEDz5s3rupu3bPDgwea/d+zYkW7duhEWFsbKlSsrPJrcGHz//fcMHjyY4OBgi8dtbZ/OmTOHn376ie3bt5f7fVMX5OlUG+Tr64tKpSp3Z9KVK1cIDAyscJ3AwMBKly/782bLpKWlWTxfUlJCZmbmDbdbU9aotUzZAC4xMZHNmzdbHIWrSLdu3SgpKeHChQvVL+QmrFnntSIiIvD19eXs2bPmNhrTPgXYsWMH8fHxPP300zftS0Pbp7XRZmBgIMXFxWRnZ9fadmvap5p48cUXWb9+Pdu2baNp06aVLtutWzcA8/u7tlm71jKenp60atXK4nPamPZpYmIiW7ZsqfJnFBrmPp0/fz5z5szh999/p2PHjubH6/L7VA7ibJBWq6Vz585s3brV/JjJZGLr1q306NGjwnV69OhhsTzA5s2bzcuHh4cTGBhosUxubi6xsbHmZXr06EF2djYHDhwwLxMdHY3JZDJ/0GqbNWqFvwdwZ86cYcuWLfj4+Ny0L3FxcSiVynKHwGuDteq83qVLl8jIyCAoKMjcRmPZp2W+//57OnfuTGRk5E370tD2aW202blzZzQajcUy8fHxJCUl3fJ2a9qnWyGE4MUXX+SXX34hOjqa8PDwm64TFxcHYH5/1zZr1Xq9/Px8EhISzHU0ln1aZvHixfj7+zN06NCbLttQ9+ncuXN577332Lhxo8V1bVDH36dVvgVCalB++ukn4eDgIJYsWSJOnDghnnnmGeHp6SlSU1OFEEI88cQTYsqUKebld+3aJdRqtZg/f744efKkmDlzZoVTjHh6eoq1a9eKI0eOiOHDh1d4S/Ttt98uYmNjxc6dO0XLli3rZDqK2qy1uLhYDBs2TDRt2lTExcVZ3MpeVFQkhBBi9+7dYsGCBSIuLk4kJCSI5cuXCz8/P/Hkk0/aTJ15eXnijTfeEDExMeL8+fNiy5Yt4o477hAtW7YUhYWF5nYawz4tk5OTI5ydncVXX31Vbpu2sE+LiorEoUOHxKFDh0RQUJB44403xKFDh8SZM2eq3KYQpdNRhIaGiujoaLF//37Ro0cP0aNHD5uq87nnnhMeHh5i+/btFp9RvV4vhBDi7NmzYtasWWL//v3i/PnzYu3atSIiIkL06tXLanVaq9bXX39dbN++XZw/f17s2rVLREVFCV9fX5GWlmZepjHsUyFK7/wMDQ0VkydPLrdNW9mnc+bMEVqtVvz3v/+1eG/m5eVZLFMX36dyEGfDPvvsMxEaGiq0Wq3o2rWr2LNnj/m53r17i7Fjx1osv3LlStGqVSuh1WpFu3btxIYNGyyeN5lMYvr06SIgIEA4ODiI/v37i/j4eItlMjIyxGOPPSZcXV2Fu7u7eOqppyzeuNZSm7WeP39eABX+lM1XdODAAdGtWzfh4eEhHB0dxW233Sb++c9/Wgx+Gnqder1eDBgwQPj5+QmNRiPCwsLEhAkTLL7shWgc+7TM119/LZycnER2dna552xhn97ovdm7d+8qtymEEAUFBeL5558XXl5ewtnZWTzwwAMiJSXFmmXWep03+owuXrxYCCFEUlKS6NWrl/D29hYODg6iRYsW4s0337T6nGLWqPXRRx8VQUFBQqvViiZNmohHH31UnD171mKbjWGfCiHEpk2bBFDuu0UI29mnYWFhFdY6c+ZM8zJ19X2qEEKIqh+3kyRJkiRJkhoCeU2cJEmSJEmSDZKDOEmSJEmSJBskB3GSJEmSJEk2SA7iJEmSJEmSbJAcxEmSJEmSJNkgOYiTJEmSJEmyQXIQJ0mSJEmSZIPkIE6SJEmSJMkGyUGcJEmSJEmSDZKDOEmSJEmSJBskB3GSJEmSJEk2SA7iJEmSJEmSbND/A6HdCGTGqxIRAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -352,7 +239,7 @@
     }
    ],
    "source": [
-    "HLAfreq.plotAF(caf, afloc, credible_interval=0.95)"
+    "HLAfreq.plotAF(caf, afloc, hdi=hdi, compound_mean=hdi)"
    ]
   },
   {
@@ -366,12 +253,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -402,7 +289,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.6 ('hlatest')",
+   "display_name": "hlafreq",
    "language": "python",
    "name": "python3"
   },
@@ -416,12 +303,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+    "hash": "46d2d82dbc865cefb79a4a45cbcd8ead329d89ff6c8b099bf15de0f92559257f"
    }
   }
  },

From c8b22f1d1b51ea55b2d1bd8817eb11c3c3c1ffe8 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 12:26:26 +0000
Subject: [PATCH 102/192] Multicountry compound model weighted by population
 size

---
 examples/multi_country.ipynb | 1430 +++++++++++++++++++++++++++++++++-
 1 file changed, 1404 insertions(+), 26 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index a8b95e4..f055ee2 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -16,14 +16,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [],
    "source": [
     "import HLAfreq\n",
+    "from HLAfreq import HLAfreq_pymc as HLAhdi\n",
     "import pandas as pd\n",
     "import numpy as np\n",
-    "import matplotlib.pyplot as plt"
+    "import matplotlib.pyplot as plt\n",
+    "import arviz as az"
    ]
   },
   {
@@ -35,18 +37,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 76,
    "metadata": {},
    "outputs": [],
    "source": [
     "countries = ['Cameroon','Cape+Verde','Ghana','Guinea',\n",
     "    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',\n",
-    "    'South+Africa','Uganda','Zimbabwe']\n"
+    "    'South+Africa','Uganda','Zimbabwe']"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
@@ -90,14 +92,13 @@
     }
    ],
    "source": [
-    "\n",
     "for country in countries:\n",
     "    print(country)\n",
     "    base_url = HLAfreq.makeURL(\n",
     "        country, standard='s', locus=\"A\",\n",
     "        resolution_pattern=\"bigger_equal_than\", resolution=2)\n",
     "    aftab = HLAfreq.getAFdata(base_url)\n",
-    "    aftab.to_csv(\"../data/example/multi_country/%s_raw.csv\" %country, index=False)\n"
+    "    aftab.to_csv(\"../data/example/multi_country/%s_raw.csv\" %country, index=False)"
    ]
   },
   {
@@ -109,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [
     {
@@ -151,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -170,12 +171,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -193,12 +194,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -216,12 +217,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -238,12 +239,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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S/a+xb98LaJr4F6ognA1KRQVHnvwj9R98gOp0IhmNaG43DXPnUfHkEwQPHT7bQxQuQKeUGBUWFjJ58mRWrlxJeXl5ePu0adNwuVzhn10uF9OmTYs49q677mL8+PHN9quqKjabjd/+9rcMHTq01eN5/vnneeWVV5gxYwbr1q0jKiqK4cOH4/f7w/sEg0Fuuukm7rvvvlb3eybtWbeGA99vxhYbRyhoB8mKxRaD2Z6ErgfxNazFGqVzuLiefRubLwaqKxqupWVo3hDGJCuGaDOyzYgx3oIh1kxwvxPv5sZjl9Y5WVzjJNFkJNtmJt5kJNFkpIPFhOKu4g37FVQl94Lo1MY7RLHtIC4HjmyG72b95wLzI47V2Hv00UcpKiriF7/4BWPHjqWwsJCFCxfyxRdf8Pe//73V/SlKPQfK3kLVAthsHTCbEjGZ4rBZszCbkqitW0FNzdIzeEWCILSkbtYsAiX7MGdlYUpNxRAbizE1FVN2NsH9B6htw991QWitNidGbrebuXPnct999zFq1KiIO0MJCQkUFBSwevVqVq9eTUFBAQkJCeH2V155hd/85jd07Nix2b6joqJ44403uOeee1pd50zXdV566SUee+wxxowZQ+/evZk1axbl5eV88skn4f2eeuopHnzwQXr16tXWSz7tdF1n9/qvkWUZVTGgKhqSrIPUuJ6R0RxLKOAk6N2PLEvs21SN3syco8B+B6G6AIZYc5MFICWTAcko49tegx7S+KLGga7rxBgjH8tJQRcZ/ipqTfEss3aOPIHRDJYY2LME/I7THodT8dZbb5GUlMTjjz/e5JqHDRvG6NGjefPNN1vdX23daoLBGqyW9Cb9GY2Ndcaqqpf89IELgtAmypEjeL/dgDE+AckYOetDMhgwJCbi37qFYFnZWRqhcKFq8xyjefPm0a1bN/Ly8pgwYQJTpkxh6tSpSJLExIkTGTx4MH379gVg/fr15OTknNYB79+/n9zcXJYtW0Z+fj6lpaVUVFRE3GGKi4ujX79+rF27lltuueWUzxUIBAgEAuGfj1XnVRSlzY9rIvr1enHV1mK02ggFVHTgaNVYkCQk2YAOBP0N2BMMeBwBPC4/FnvkrytY60XXNXQDzU4W1s0yqlvB3+Bln8ePXZbQfzhJOehF0lR0SeKQHNN0ErMpGvz1qPWHIdl+ytd8qo7F+dj/btu2jSuvvBKDwdDs72DQoEH8/ve/b/Xvx+s5hK7r6EjNxlCW7fi8ZQQCnnNqrtEP4yIcJ2LTsvMpNr5Dh1C9XozpaWjNvQwRZUetr8d38CBSRsZPPt/5FJv/pAslLm0Zf5sTo8LCQiZMmADAiBEjcDgcrFixgvz8fGbPns306dPDc49uvvlmJk2aFN7/dDCZTOTl5WG3N35JV1RUAJCWlhaxX1paWrjtVD333HM89dRTTbYvWbIkfP5ToasqDofjaJJiR1VlJAMEjr5toes6ekjB7fbh1+qRJJ0vv1qC9IM52AnVZjJcVgKKszGx+gGDIiEBG5YvxR2XggsZVY+cr2QJuYhRQ6iqiuJqoKoq8rGdUfVi0IJ8u+prfJbIeVv/SUVFRUBjclpfX8+iRYua3W/NmjWYzeYW23/IZNqL0eTG5aqkuSBKkhNdt7B4cVGz7WfbsbgITYnYtOx8iI3l0CHSPR5ClZXozVRGl0IhjF4v+zZsxF9Tc9rOez7E5mw43+Pi9XpbvW+bEqPi4mLWr1/P/PnzGw82Ghk/fjyFhYXk5+dTVVVFUVERH330EQAvvfQSb7/9dltO8aPatWsXLiB7pk2dOpWHHnoo/LPT6SQ7O5thw4YRGxv7k/pe63eyZ93X2OMTqD3sQQ0pWKxmkCTUkB9dspHSrgcBbzS5lyTRd3TTWmahOj+OeXuIkSXkH9xN0nUdrTaAuUscnUblcuBQDe9X1JNiNSGf+MhIjcdb4cIuhcg3NzQtIlu/Hz2zH4NG3wGnqV5bWyiKQlFREQUFBZhMJhwOB7/85S/JyspqUpfP5/MxefJkbrrpplaXO3G5stm9ZydGYzQGQ1REm65r+P1e0lJHk5PT/IsGZ8sP4yIcJ2LTsvMpNnowyJEtWwhVVGBsprh1qKICQ8eOdL/rTmSr9Sef73yKzX/ShRKXY098WqNNiVFhYSGhUCiiar2u61gsFqZPnx6RREBjPa4fbjvdjs1FqqysJOOE26mVlZXNvvnWFhaLBYvF0mS7yWT6yR+QHgPyObxzOwFXHRabDY9TQlV1IICmeLDHdyHoj8cWbSSvb2az5zOlmQh2S8K3tbrxEZzNiCRJ6KqG5lSQ7UZiLsvAZDIxOj2RpQ0eDgYVMi0mzLKMrut4JBOVUe34We1GLnduR7bFgSSDFgJXBZht0Oc2DGe5GvuxmI8fP57nnnuOG2+8kffee4+rrroKSZIoLS3l/vvvp6amht/97net/v0kJFxCfPwV1NWtwWIGgyEaSZLQtCDBQAUWSyoZGdees/9BOB2fxQuViE3LzovYmEwkjB1LzRtvoNXUYkhKQpJldE1DrasDTSNh7PVYYmJO82nPg9icBed7XNoy9lYnRqFQiFmzZvHCCy8wbNiwiLbrr7+eOXPmcO+99wI0KfJ6JuXm5pKens5XX30VToScTifr1q07Z95Aa05yTgeuvu2XfPPxPBzVVaC7CQUMgAlzVGcsMQOISbBw2c87kJwV3WI/sflZoOv4i+vR6o6/hWeINRMzMBtzduN/NHJsFp7onMlfSyso8wU49sTeKksMSMvk/+SNGGsVqCs9fmcoKgX63Qsd889MEE6BxWLh3//+N6NHj+bqq6+mY8eOREdH8/3335OQkMBnn31Gjx49Wt2fJMl06vgQkiTT0LCBoFLLsUdmNms7cnMfwG5verdOEIQzL2bECDSvl4YP/4Vy8GDjf5t0HTk2loTbbiP22mvP9hCFC1CrE6OFCxdSX1/P3XffTVxcXETbuHHjKCwsDCdGLdm7dy9ut5uKigp8Ph+bN28GoEePHuFF+Xbs2EEwGKSurg6XyxXe51jSc/jwYYYMGcKsWbPo27cvkiQxZcoUnnnmGbp06UJubi6PP/44mZmZEesglZWVUVdXR1lZGaqqhvvt3Lkz0dEtJx5nUlb3noz5386Ubv2OtStW0Dm3O0ZzFraYNGKSbGTlJWCynHxxR8lkIG5YB+yXphHc70BXNAyxFiyd4pCtkb/ei2PsvHNRB75xuCn1BTFJEpfE2Lgo2obUfTL0ug4OrIGgpzEpyr0G7IlnMgSnJCcnh02bNlFUVMSiRYsIBoM88MADjB8/nqioqB/v4AdMpji6dnkCt6cYp3MLuqZgtWWREP8zDIaffoteEIRTI0kS8ePGET1wIJ5161AbGjDExmLv1w9TM4/XBOF0aHViVFhYyNChQ5skRdCYGD3//PNs3bq1ybyPE/3P//wPK1asCP/cp08fAEpLS+nQoQMAI0eO5MCBA0320fXG19UVRaG4uDhiItXvf/97PB4Pv/rVr2hoaGDAgAEsXrwY6wnPnZ944gn+8Y9/NOn32NttZ4vJaiW3zxXsPFJN35EjT/lWpSnZhinZ9qP7WQ0y+Ymx5DfXmNC+8c95QJZlhg8fzvDhw09Lf5IkERPdjZjobqelP0EQTh9jcjJxLSwoLAinW6sTowULFrTY1rdv33DicjLLly//0X32799/0vYOHTo0OZckSTz99NM8/fTTLR7X0mrcgiAIgiAIx4gisoIgCIIgCEeJxEgQBEEQBOEokRgJgiAIgiAc1eaVr4Vzi8ezj5qaZXi8ezHIVuLjLycx8RpMph9fgFLXdaqqqtizZw+1tbWYTCY6dOhAp06dKK0LULRsM3t2FGN2VHOpeohBnWXSrr0JufMAkE/+tpwe0giUOvDvaUDzKhhizFjzEjDnxCLJErW1tRQWFjJ//nw8Hg8XXXQR9957L9dcc02TmmVBPcjyQ8v5rvo7PIqHdtHtuCbrGroldovYV9d1asr2U7JpAw0V5ZgsFrJ79KZ970sw2+zsr/GwdFcVxRVOzEYDl7VPYGDXFOLtJnZ5/HxV62SfL4BdlukfH01+YgzRxpNfZ1spAZWDO+s4vLsexa8Sm2ylfc9kkrOjm1y3IAiC8J93SonR2rVrGTBgACNGjODzzz9v0n5skvOJ6xnNnDmTO++8s9n+Kisrm6y4vGbNGgYOHEjPnj3Dr9a3pK6ujsmTJ7NgwQJkWWbcuHG8/PLL4dfw/X4/9957Lxs3bmTnzp1ce+21EQVmz1cVFZ9y8OBMlJALWTah6xp19WuoqPiULl0ePen6O7qu891337Fx40YCgQAGgwFN09i3r4TCZTv5vgK8TjcmVUKV0llvSGfR9iqmrH2cS267CuPopxqLzDZD84dwfFFKYL8TNB0MEqg6/p11WLsnciDVwfCRI6ivr2fMmDGkpKTw1VdfkZ+fz5QpU3jxxRfDSUK1r5r53vm4N7tBAqNkZFPVJr4q+4rrOl3H7d1vb1zUUtfZ+uUXfL90CUGfD4PRiKapHNi6mZ1rVkDf6/j7lgYcPgWzQULTYc2+Gj7edJje/TMp8nhwh1RMsoyq66ysdzG/sp4nO2eSY2u6yOep8DgCrP5wD7WH3OiAQZY4sq+BfZuqyftZOhcPzhbJkSAIwll2So/SCgsLmTx5MitXrqS8vDy8fdq0abhcrvDPLpeLadOmATB+/HiOHDkS8Wf48OEMHDiwSVLU0NDAHXfcwZAhQ1o1nttvv53t27dTVFTEwoULWblyJb/61a/C7aqqYrPZ+O1vfxtRbPZ81uDYSFlZIbquYbd1wGbNwm7LwWrJwuMtZe++51HVQIvHl5aWsn79egASExOJj48nMTGROmMSKw7ruH0+2vmryNAcZGkNpGtO9sdk8Fr0cCr+uQj9u1kt9u1aeQj/vgbkKBPGJBvGeCvGJBuS1YBj8xFGj7qW9PR0SktLmTt3LtOnT2fHjh28+uqrvPTSS+FlFXRd542tb1CulpNqSyUnJofM6ExyYnIwySY+3vMxyw8uB+DA1k1sLlrUuO5JegaxKanEp2UQk5zC4ZISVn8wi6CikJtkJyvBTk6inZwEO7uUIG+WVaFrkGuzkG0108FmoZ3FzE6Pj+dKjhDSfvyNyx+j6zrrPi2husxFdIKF+BQbMUlW4lJsGIwyO9ccoXTL6av3JAiCIJyaNidGbrebuXPnct999zFq1KiIV+ATEhIoKChg9erVrF69moKCAhISEgCw2Wykp6eH/xgMBpYuXcrdd9/d5Bz33nsvt912G/379//R8ezcuZPFixfzzjvv0K9fPwYMGMCrr77KBx98EE7aoqKieOONN7jnnnvCJUTOd1VVi1FVHxZLasRdBlk2YrNm4vWU0uD4ttljdV1n27ZtqKpKdPTxRzi6DttdFnRNxyKHCJkt4VWwjWikhhzsj0lnozeH4Kp/NS4E+QOqI4B/TwOyzYRsjnwMJVuNLN65grIjh5hZ+G5ECRdJkpg0aRKjR49m2rRp6LrOzrqd7KjdQYwUg9lgjtg3wZqApmss3r8YTdPY9fVKtJCKPS4+Ih4GoxGPMQqbu5JcrfYHsZJQ020EVA1Z0SLaTLJEpsXMLo+fjc6m19lWNQfdVJe5iIozYzAe/2snSRK2aBO6Dns3VrVq2QtBEAThzGnzo7R58+bRrVs38vLymDBhAlOmTGHq1KlIksTEiRMZPHgwffv2BWD9+vXk5OQ028+sWbOw2+3ceOONEdvfffddSkpKmD17Ns8880yT4449kjv2BbJ27Vri4+O5/PLLw/sMHToUWZZZt24dY8eObeslhgUCAQKB43ddjhWhUxQFRVFOud8fOtZXa/vU9RAOx2ZkQxSarjXdQTKh6SGcju3ExvRr0hwIBKisrMRisaBpx48PanDEI2FVA+gyBI0mLMFQuN2qh1BlA3utGfgObkSu3AXpkQt6Bg470XwKcqKl2bF9vf878tI70iWlQ7PXe9NNN3HHHXdQVVXFroZdBNQAFiyNRXG1yP5iTDHsd+znUNV+ag6WYbbb0ZpJLBwKmHQNi7sKb0JWeHtIAo/ZgEHRcPkVkqMiF9e0ShDUNLY5PVwa9dMep1WVOQgpKrY4U7NjtNgNNFR6cNZ5scf+eF26tn5m/puI2LRMxKZlIjbNu1Di0pbxtzkxKiwsZMKECQCMGDECh8PBihUryM/PZ/bs2UyfPp1RR1covfnmm5k0aVJ4/x/2c9ttt2GzHV+tec+ePTzyyCOsWrUKo7H5ocXFxZGXlxf+uaKiosmjOKPRSGJiIhUVFW29vAjPPfccTz31VJPtS5YswW63/6S+m1NUVNTKPVVstjqQNHRdbXYPSfKwc+dOtm5d1PRoVaW+vh4g4tFnUJNQQhbko1/czSUjuq6j6Rp+n4/Nq1fjsB+KaI+tN5HlthEIOY+VHIvg8/nQdVi9ajW+qKZj37p1K9AY473WvXj8HiySherq6ib7+nU/IUIsX7EcZ0M9SDIGj6/JfsEgGDQVl9NJVVXV8TjIEkpSCqoGHo+HStXd5Fi3bGTbtiMs2tS0rS08h4y43WZ8qovmphFpCuiaxFdffoXB2vq7Rq3/zPz3EbFpmYhNy0Rsmne+x+XEahk/pk2JUXFxMevXr2f+/PmNBxuNjB8/nsLCQvLz86mqqqKoqIiPPvoIgJdeeom33367ST9r165l586dvPfee+Ftqqpy22238dRTT9G1a9cWxzB27NifdBeoLaZOncpDDz0U/tnpdJKdnc2wYcOIjf3xt75aS1EUioqKKCgoaHVJkL37tlBfvwabrWm9IE0LEgwG6Jg7msTEa5q067rO559/zuHDh4mPjz9hO2SGZA6oFiyaF7MWQpaPP/YJSEYM6HQMVhHXqR1Xjf4FWCIrW6uOAA1zdhMjS8j2ph+va7r2Y976haR1zaLHxRc1af/HP/5Bt27dGD9+PDvqdrD1m60oboV2Ke2aTEwu95TTNa4rN195G19V11O5bw9xaU3j4dbqcQdNmDM7kppwvF0HqjQDNWaJ1FgrqdGRd4X8mkZQURnbqSv949peg+1EVQdcrJyzB4vd2Gz9O1etn4R0O0Ou74Yk//gE7FP5zPy3ELFpmYhNy0RsmnehxOXYE5/WaFNiVFhYSCgUIjMzM7xN13UsFgvTp0+PSCIAYmJimmwDeOedd7jkkku47LLLwttcLhcbNmxg06ZNTJo0CQBN09B1HaPRyJIlSxg8eHCTvtLT0yPuAgCEQiHq6up+8nwii8WCxdL0EYrJZDojH5C29JueNgqn8zsUpQ6zKemEeUIqgUAFUfZckpOvwmBovr+ePXty5MgR/H4/NpstfHyvOIUyp5FAyIApEACDASRQkagyxpHrLOcK8wGsV9+LFN20wKwp2YStcwK+7TVIZiOS6XhipQVUru05mD8nv8avJ93LokWLSExMPDpunX/84x/Mnz+fGTNmYDab6Z3Wm7yEPL5xfUOanobFcPx34Qg4kCSJn3f8OVaLle5XXkPNgVICbhe2mONJq6aqRKseaqKTKTOkkoIUvlZN0zFW+THn2JEsBpCOt4V0nSNBle7RVvonxmFqRbJyMpkdE0jJjqGyxIEx2YrBcDwufo+ChETXK9IxW378MdqJztRn8UIgYtMyEZuWidg073yPS1vG3urEKBQKMWvWLF544QWGDRsW0Xb99dczZ84c7r33XiDyNf0fcrvdzJs3j+eeey5ie2xsLN9//33Ettdff52lS5fyr3/9i9zc5l8979+/Pw0NDWzcuDGcaC1duhRN0+jXr+n8mgtFfPwVZLW7ncPlc/D59iPLVnRdRSeEzZZNp06/O2ll+M6dO1NbW8vmzZupq6vDaDSiaRpJqkb/tHR2VtkoV1Iwh4KEZAOaJJPlruQ+x7/JGD8Y6fLml14AiBmYheoOEjzoAiQkg4Qe0kCWiOuZzqcLPmXEqJ/Tvn17brrpJlJTUykqKuK7777jf/7nf8JvFMqSzP0X30/p4VIqPBUYZANG2dg478hgYVTHUQzJaXxzMbfP5dSXH2LHqmXUV5RjNJnR1BCappPRvj3Jl49m53Y3pbVerEYZTddRVJ3OcVa6t0tmpc9HqS+IVZYI6TqqDp3sFh7tmPmTkyIASZbod11HVn+4h7pyD5IsYTBASNEwmgx07ZdG7iUpP/k8giAIwk/T6sRo4cKF1NfXc/fddxMXFxfRNm7cOAoLC8OJ0cnMnTuXUCjUZN6RLMv07NkzYltqaipWqzVi+/z585k6dSq7du0CoHv37owYMYJ77rmHGTNmoCgKkyZN4pZbbom4s7Vjxw6CwSB1dXW4XK7w2kiXXHJJa0NwTpEkiczM8cTG9qa6Zilezx5k2UJCQj+SkvIxm5N+9Ph+/fqRnZ1NcXExdXV1mEwmcnNzubtTJ/bWBvn3V9+xt7gEs7Oay5UDDOkUIvPa/8PQYyi0cCcKQLabSLi+M/49Dfh316N5FAzxFqx5CVhy47nC0JHvv/+eN998k48//hiv10uPHj14+umnGTlyZMQjs4yoDG6w30B0z2g2VG3ArbjJjsnmmqxruDjl4vC+kiRx6ajradftIvZ9t576I4cxWWzk9OxNh0suwxYdQ+/uLr7aWcnOCidmg0zf3EQG5aWSEmNhs8tHUY2DEl8AmywzICGawUmxJJhO3xqoMYlWBt/RnbLttRzaVU/QHyIu2Ub7Xsmkd4wVaxgJgiCcA1r9X/3CwkKGDh3aJCmCxsTo+eefZ+vWrfTu3buZoyP7ueGGGyLmtrSFw+GguLg4Ytv777/PpEmTGDJkSHiBx1deeSVin5EjR3LgwIHwz3369AE4r1+PliSJmJgexMT0OOXj27VrR7t27Zq0XRwVxcV3DgFat5ZUk75NBmw9krD1aD5By8zM5Kmnnmp2cvsPWSUrw9oPY1TnUSc/pySR3rkr6Z2bn6OWlx5DXnpMs219Yu30iT39E+p/yGIz0uXyNLpcnnbGzyUIgiC0XasTowULFrTY1rdv31YnGF9//XVrT8kf//hH/vjHP0ZsmzhxYpNHdYmJifzzn/88aV/79+9v9XkFQRAEQfjvJIrICoIgCIIgHCUSI0EQBEEQhKNEYiQIgiAIgnDU6XvlRjjrgvv349u6FV1RMLVrh/3SS9EMBg4dOkRtbS0Gg4GMjAxSUlJa/waUpwb2r4aAE92WyF57H7bW6KiaTm5KFH2y4zGesCaPotRTX7+eUMiB0RRHQnw/TKb4cLumalSUOGmo8mIwSKTkxJKQYT/peHRdZ/ny5SxduhRVVenXrx/XXXcdAUnm6wY3NcEQUUaZn8VFk2Y5s+ts6LrOfud+ttVsI6SFyIrJ4pKUSzCd5C29k6k/cpgje3ejhhTiUtJp1607DX6NdaV1uPwKCXYz/TomEWf7z60forqDBEod6H4V2W7C0ikO2Sr+UyEIwn+HU/qv3dq1axkwYAAjRozg888/b9J+rLBsc+sZzZw5kxdffJHdu3cTGxvLTTfdxGuvvRZu//e//82TTz7J9u3bsVqtXHPNNbzwwgt06NChxfHous6TTz7J22+/TUNDA1dddRVvvPEGXbp0ARonXv/pT39i6dKlVFRUkJmZyYQJE/jDH/6A2dy2BfXORZrHQ82bb+H5eg2a1wtIIEt4O+Sy7eLe1CtKeLFMs9lMdnY2+fn5Jy9rommw6T3Y/D746lF1qHMH8KkxbDOOZKXxSowGA51So3ioII9OKVFUVHzM4fJ5KEp9uBuzKZF27W4lLe066iu8rP+shPpKL7qmo+tgNMtkdo7nimtzsUY1/fI/ePAg//u//0tJSQmZmZlYLBb++te/ktIui15/eZlg5+5A4yrWcUYDY1LjuatdCsbTsPbQD7mCLt7c8ibfVnyLN+RFkiRkSaZ9THvuv+R+8hLzfryTo4I+L998PI+ybZsJ+n2NiaEksyu+Jzuj8/BoBiQkdHSSoy38on97RvXKOKOv9OuajufbCrwbK9F8x2vkyTFmovtnYO8l1lkSBOHCd0qP0goLC5k8eTIrV64MV7AHmDZtWkTtLZfLxbRp08I/v/jii/zhD3/gkUceYfv27Xz55ZcMHz483F5aWsqYMWMYPHgwmzdv5t///jc1NTXccMMNJx3P888/zyuvvMKMGTNYt24dUVFRDB8+HL/fD8CuXbvQNI0333yT7du3M23aNGbMmMGjjz56Kpd/TtF1nerXXsNVVIRkMmPKzsGck0MgPYOvjQYqSkuxyTKJiYkkJiZiMpnYu3cvX375JarafJ01AL6fB9+8AaEAWlwOxcFk9ilJxOBhovoRo+3bSYo2s+uIi6cXbmfPgU85UFaIpvqwWbOw29pjs2YRUj0cOPAWB/cvYvW8PdSWu7HHmIhLsRGXYsVkMXBgey1r5+9DUyPrsvl8Pn7+85/jcrlYvHgxhw4doqSkhH+s/JpgYhIr77uT+NpqOtgstLeaUXWd2eW1zC6vOe1x1nSNV797leWHlmMxWsiJySEnJocUWwqljlL++u1fKXeX/3hHNP7O1sx7n73frsVgMhGflkF8WgbF0V1Y6kqgtqqaDLuB9kl2suJtuPwKry/fx7Liqh/v/CfwbqrC/XU5uqpjSLBiTLJhiLeieUO4lh3EX1x3Rs8vCIJwLmhzYuR2u5k7dy733Xcfo0aNCt8dAkhISKCgoIDVq1ezevVqCgoKSEhIAKC+vp7HHnuMWbNmcdttt9GpUyd69+7NddddFz5+48aNqKrKM888Q6dOnbj00kv53e9+x+bNm1usjKvrOi+99BKPPfYYY8aMoXfv3syaNYvy8nI++eQToLHY7bvvvsuwYcPo2LEj1113Hb/73e/4+OOP23r555zA7j141n6DITERQ1xc+I7CwZgYPFFRRHk8SHWNd3AkScJqtRIbG8uhQ4c4dOhQ850GPbD5n2AwQkw6joCG06dgNplwmNIwEmKAezFRRshJtHOk3sme/XORkLBY0pAkw9HzGbBa0tHROFD6Aa46F7HJNoxmQ3g8FpuR6HgLFSUOKkoja9nMnTuX3bt38/jjjzN48GAkSULXdTYkZ9LtxTeRZZl9c2cBIEsSKWYTNllmflUD9UqI02lH7Q42Vm0kxZZCrPn4YowWg4WsmCwqvBV8eeDLVvVVfaCUgzu+xx4XjzUqGkmSCOgy36lpmIwG7CEPXkfj78xokMmIs6GEND7ccIjQD5LH00ULqHi/q2xckTvGHK7XJhkkjPEW9JCGZ0Mlunb+rvslCILQGm1+lDZv3jy6detGXl4eEyZMYMqUKUydOhVJkpg4cSKDBw+mb9++AKxfv56cnBygsTKvpmkcPnyY7t2743K5uPLKK3nhhRfIzs4G4LLLLkOWZd59910mTpyI2+3mvffeY+jQoeE6J/v37yc3N5dly5aRn59PaWkpFRUVDB06NDzGuLg4+vXrx9q1a7nllluavQ6HwxGu09WSQCBAIBAI/3ysCJ2iKC0maqfiWF+n0qd7w7doPh9ySjKafvxL85DFjFHXkQwGQnV1GLOzOFbW3Wg0EgqF2L9/f8Tq4MdIBzdgcFWgx2SCptHgCaLpOo31ZHUccjwpSjmpwQOUmzuQFX0Qn/8IxtisiDEcYzQm4vQdxhx3GKRuaD9Y88pgllEVlcO760hpf7xY67x58xg4cCA5OTnh2BzyB9nl8pEaH0/uz0dzYMkXXPrgI+FjEo0yBwMK6+ucDE5sfjHHU7HhyAYCoQBWqxVNa3qNVoOVFQdXcEuXW370cVfZju8JBfzY4xPCsTgYsuHQzMRJQTAY8DkbiEtNg6NdJUaZ2F/jpvhIA13TYn7SZ6Y5wQMOQs4gcpyp2d+hFGVEqfbiP+LCmGo7Lec8U053bC4kIjYtE7Fp3oUSl7aMv82JUWFhYbicx4gRI3A4HKxYsYL8/Hxmz57N9OnTGTWqcYXim2++mUmTJjFhwgRKSkrQNI1nn32Wl19+mbi4OB577DEKCgrYunUrZrOZ3NxclixZws0338yvf/1rVFWlf//+LFq0KHx+k8lEXl5eeH5MRUUFAGlpkSsJp6Wlhdt+aO/evbz66qv87W9/O+m1Pvfcc82uzLxkyZKTz885RUVFRW0+Jn7TJuI8HpTq6ojtnpgYVEkiFAoBIZyVlRzNbIDGpG/Hjh00NDQ06TPVuZWeLgeegBUkCadPQlUhEGh89BbSNewEcNdVUCXbSbQ1oKoBamoaCH+TR9DQ1CA+fz3O+uYfB4U8Eju3F1OuHK+Xd+DAAVJSGue1HItNhWykzpZClKai2qMJul1U/qCIsFs2smbDRvwh78mD1wZb/VvxBD1U+6qbbfdoHnySj88XfY4snfxGbP2OLbjdHgLS8b6qJY2gUSWk+0HTUCWoqqoMJ7MhDZxBia9WrGJv9PG+TuUz05zYehPZLht+RWv2VyhpYArKfL98Jd7okzyCPYecrthciERsWiZi07zzPS5eb+u/D9qUGBUXF7N+/Xrmz5/feLDRyPjx4yksLCQ/P5+qqiqKior46KOPAHjppZd4++23AdA0DUVReOWVV8JFaOfMmUN6ejrLli1j+PDhVFRUcM899/DLX/6SW2+9FZfLxRNPPMGNN95IUVFRuITFsTppp+Lw4cOMGDGCm266iXvuueek+06dOpWHHnoo/LPT6SQ7O5thw4YRGxt7kiPbRlEUioqKKCgoaHP1YpdsoG77doxJSUgGQ3h7siRRaTZjVBRku52Y9PRwm67r1NfXc9lll4VLo0SoysXw2b+JMtvBEoPS4MdT78VsMiBJEKX6UYlGSu5CqjEJl8eLyRRNYqIdo7HpXZpQyIGjOoSZLBLSUpu067qOs9pH7yuy6H5VRnj7Z599Fp4LNWLECEwmE46QysLtB1B0Hc+u7cTndiIt9XifPlVDCamM6pPHpaexxIdWorFn+x6So5ObTXwOuw/TLbEb11557Y/2VRwfw/rKw8SkJCMfTVY11YrdI4Fkw6j4MFmtpJ5wx6jBq2DVdcaOuIT0WOtP+sw0R6nw4PxoHzFWA5LF0KRd8yqgw9U/74sh5tx+YeF0x+ZCImLTMhGb5l0ocTn2xKc12pQYFRYWEgqFIh6/6LqOxWJh+vTpEUkEQExMTHhbRkbjF16PHsfreqWkpJCcnExZWRkAr732GnFxcTz//PPhfWbPnk12djbr1q3jZz/7WZMxpR/9wq+srAyf49jPPywQW15ezqBBg7jyyit56623fvR6LRYLFoulyXaTyXRGPiCn0m/c1QNwzpuLVlWNMeP4W0vtg0GqTCYUSSYqJSX8BQyNk+Ltdjtdu3Zt/nyZvSCjNxxcB9YYkqMtVDj9KKqG1QAxmpPv7ANwmVLw+kM4lDTiYnujKFswGaPDc4wAdF1FURqIi7uCaiWVUEDF/INXvz2OINYoM7m9UyPGc++99/L3v/+dzz//nNGjR2MymUg2mRiSHMdbny7gyNpV9P/j/0M6llzoOpWKSrdoK5clxJ7WN9Ouzrmaj/d9TK2/lrSoyLuTXqXxDbWhHYa26vfXsc9lbFv6b7z1dcQkJSNJEhmGAO2MXkqUKOKB6ITE8O8spGk0eBUKLkonOyky8Txdn0VjVhz+zGiCB13IFmPE40Bd1cGrYuuVjDUx6iS9nFvO1N/TC4GITctEbJp3vselLWNv9eTrUCjErFmzeOGFF9i8eXP4z5YtW8jMzGTOnDnhfZurZ3bVVVcBRBSArauro6amhvbt2wONt7pO/AIHMBy9C9LcvA6A3Nxc0tPT+eqrr8LbnE4n69ato3///uFthw8fJj8/n8suu4x33323yXnOV4b4eJLuugvJbEYpK0NtaEB1u0nbf4B2NTUE42LxmEz4/X58Ph91dXXouk7fvn1bLuQrSXDVAxDbDmr3YVPq6BCtEq/VkxA4zEE5iwWWURyq91HnDTK0ezpXXPQbbLYsvL4DBIM1hEJuAsEavL4D2O3t6d77Xtr3SsLnUnDV+gn4Qvg9Cg3VPnSgV34WMYnWiGFcccUVTJkyhb///e/ccsstfPrppyxZsoTNzz5J8cOTiO9/NfaCUbhCKrXBEKW+ACkWI5Pbp5321/WTbcn8oscvkCWZMlcZjoADd9DNEc8Ravw19M/sT35Wfqv6ssfGcfm1YzEYjTgqK/C7XQR9Xvr6dhKrenBZEvEZo3D5Q1S7ApTVeemUGs3EKzuc1ms6kSRJxAzMwhBrQa3xobqDaP4QqitIqN6HMdVOdP+m89EEQRAuNK2+Y7Rw4ULq6+u5++67iYuLi2gbN24chYWF3HvvvS0e37VrV8aMGcMDDzzAW2+9RWxsLFOnTqVbt24MGjQIgFGjRjFt2jSefvrp8KO0Rx99lPbt24cf+Rw+fJghQ4Ywa9Ys+vbtiyRJTJkyhWeeeYYuXbqQm5vL448/TmZmJtdff334mPz8fNq3b8/f/vY3qk+Yj5N+wiOm81XMoEEY4uNxLFiIf/s28Psxp6UxeOgQDnXsyI49e3C5XEiSRHZ2Nr169aJjx44n7zQlD0a/DFvmQskykq0BzMYkVktD+ZdyJbV6Eh2Srfy8ZwajemdgMsh0y3uGiopPqatbiar5MMhWUjNuJD19DFZrJv2u00hqF82+76rwNARAksjoFEfXK9LI6tb8RPi//OUvKIrCl19+Gf59ZmRk8PtHHyVrwt0sdflxqyomSWJ0ajzj0hLpGmVttq+faliHYSRaE1lUuohddbtQNIWMqAwK2hcwIndEmxZ57HzFz7DFxLJz9XIqS/ehq0E6JcfzaM9Mvjdms6akHr+iYjMbGNkrg7GXtiMt9sxc1zGmtCgSbuiM57sqAnvr0RUNyWwgqncyUX3SMMSe24/QBEEQTgu9la699lp95MiRzbatW7dOB/QtW7actA+Hw6Hfddddenx8vJ6YmKiPHTtWLysri9hnzpw5ep8+ffSoqCg9JSVFv+666/SdO3eG20tLS3VAX7ZsWXibpmn6448/rqelpekWi0UfMmSIXlxcHG5/9913dRrXAGzypy0cDocO6A6Ho03H/ZhgMKh/8sknejAY/Ml9herr9WBlpa4FAse3hUK60+nU3W63rmla2zv1O3XdUa7rgcbja90BvdLp05WQ2uzuiuLW/f4KPRTyNNuuhlTd3eDXva7Aj47nWGwCgYB+4MABfd++fbqiKOF2b0jVj/iDulMJtf26TpGmaXq9r16v8lTpQfWn/c40TdO9TofuqqvVQydcl8uv6BUOn+4JKM0edzo/M81R/Yoecvh1NfCfi+vpcqZjcz4TsWmZiE3zLpS4tOX7u9V3jBYsWNBiW9++fdH1H1/fJDY2lsLCQgoLC1vc55ZbbmnxFXuADh06NDmXJEk8/fTTPP30080e09yjvQuVIT6eH06dNRgMxMT8hFfXLTGNf2icC5wYdfI7B0ZjFEZjy3NRZINMVFzTuVsnI0lSeOmHE9kMMjbDf/axqCRJxFvjT1tftpimE/mjLUaiLWevDIdsMcJZPL8gCMLZcmFMtBEEQRAEQTgNRGIkCIIgCIJwlEiMBEEQBEEQjhKTCM5Dofp6QkeOoBkMeCwmdCAmOQVbdAx+RWV/rQdV08lOtBNrbflNqbKyMnbt2oXRaiOp18V4Q2Dwq8RJMtmSjFGSMCZa8ZSX4q93YI5PJLZjbsQaN8FgDYFAJbJswW7PDa9hpOs6RzxHaAg0EGOOISs664xWhj9VPp+PhoYGZFkmKSkJo1H8lRAEQfhvdkrfAmvXrmXAgAGMGDGCzz//vEn7scKyzU14njlzJi+++CK7d+8mNjaWm266iddeey3c/u9//5snn3yS7du3Y7Vaueaaa3jhhRfo0KFDi+PRdZ0nn3ySt99+m4aGBq666ireeOMNunTpEt7nz3/+M59//jmbN2/GbDY3WwrjXBeqraX+n3Nwr17NoYCXg0Ydn8WEFBOLOSWV8ux+fC9lUOMJoQNxNhMFPdK4tW8OUSdMpC0pKWHy5Ml88cUX4YnsxqQU4m76JdnDbia/WmXckRDpkooW8FHh91OuepEljeTklVw08lLie6Rx6NBs6uq/RlV9SJIBu70DmRk3UitnMK94HttqthFUg5gMJronduemvJu4KOmisxS9SD6fjw0bNrBnzx78fj+SJBEXF0evXr246KKLLph1rgRBEIS2OaX/+hcWFjJ58mRWrlxJeXl5ePu0adNwuVzhn10uF9OmTQv//OKLL/KHP/yBRx55hO3bt/Pll18yfPjwcHtpaSljxoxh8ODBbN68mX//+9/U1NRwww03nHQ8zz//PK+88gozZsxg3bp1REVFMXz4cPx+f3ifYDDITTfdxH333Xcql3zWherrqfjTMzg+X0iJHmSXVcJjlDD4gxhqaljmTGDe3iAlZeXEWw0kR5vxBVX+ua6MZxftxK801rc6ePAgAwYMYOfOnYz/fy9w2cdF5LwyG+slP6N2xt+onfs2KzNNvJ0r0+DxEQoayTDG0MUSjckQ4killTUfrmHLuilUVjXWsLOYUzAaY/B49rB99595f/1DfHPkG8wGMym2FKwGKxsrN/L/1v0/ttVsO5thBBrrxC1evJhNmzYRCoWIjo7GbrfT0NDAypUr+fbbb8/2EAVBEISzpM13jNxuN3PnzmXDhg1UVFQwc+ZMHn30UQASEhIoKCigZ8+eAMyYMSO86GN9fT2PPfYYCxYsYMiQIeH+evfuHf7/GzduRFVVnnnmmfC/2H/3u98xZswYFEVpdklvXdd56aWXeOyxxxgzZgwAs2bNIi0tjU8++ST86v+xYrDH7madb1yLFxPYtYtQRgZlgQYMyFhlAxjhiB7NTjmDKIOO2e9A9URhT0omJcZAtMXIutI6Vu6uZthF6fzpT39C13Xe/XIpz9QGMPmCmKQ4uv32SZyJGeye9w5ZQ8awMy2Vb5Os9K/2IkkysdhJNHkxmbwoadtwOveR2K4HBrnxdyJjxmCwU1m3iVwpiCOmPyGp8bV+k8FEtCmaMlcZ7+14j/939f87q4/ViouLOXz4MPHx8RGPzuLj4/F4PGzZsoXOnTuTlJR01sYoCIIgnB1tvmM0b948unXrRl5eHhMmTODvf/97+HHMxIkTmTdvHgsXLmThwoXMmzcv/DitqKgITdM4fPgw3bt3Jysri5tvvpmDBw+G+77sssuQZZl3330XVVVxOBy89957DB16vAbV/v37kSSJ5cuXA413mSoqKhg6dGi4n7i4OPr168fatWtPNS7nFD0UwvXVUiSrlUpCKLqO5YRCpnujcwhgxKb6kWQZT0M9x1Z6spkb5/x8tbOKQCDA+++/z3333cd2gw2vquFxK8hAtAqdrr0Ng8VK7dLGNavWpTUmNqGjv99Y3Y5kULFn7iAUsBDyBCLG6Qv5qFM0YmSdFKk+ok2SJFJsKexr2Mfu+t1nIEqtV1xcjCzLzc4nstvtBAIBSkpKzsLIBEEQhLOtzXeMCgsLmTBhAgAjRozA4XCwYsUK8vPzmT17NtOnT2fUqFEA3HzzzUyaNIkJEyZQUlKCpmk8++yzvPzyy8TFxfHYY49RUFDA1q1bMZvN5ObmsmTJEm6++WZ+/etfo6oq/fv3Z9GiReHzm0wm8vLysNsbK6dXVFQAkJYWWdgzLS0t3HaqAoEAgcDxL/9j1XkVRUFRlJ/U94mO9dVSn6rLRcjpBKsVv6YCOhISx7Ifl8GOjI6k6UhGGTWkoGlq+K6M1ShR3uClsrISr9dL79692eAPIqGjhDRkWcIY0jHYoojKzMFfU0GqCjXWxuRL10GXdEwY0Q0+JKOCqlgIBYOY9OM17IKhIKquI0kSJt2PpkfWt7PIFgJqgGpPNR1jfqQkSStj01a6ruNwODAYDC3W39N1HZfLdVp/x6fb6Y7LhUTEpmUiNi0TsWnehRKXtoy/TYlRcXEx69evZ/78+Y0HG42MHz+ewsJC8vPzqaqqoqioiI8++giAl156ibfffhtoLAKrKAqvvPIKw4YNA2DOnDmkp6ezbNkyhg8fTkVFBffccw+//OUvw7XSnnjiCW688UaKioqQJIl27dqxa9eutgz7lD333HPhR3AnWrJkSTgxO52Kioqab1BVsjxuJL8ff3wUIVnDj9qYHAFmxYtmAUUNoWkakkGmuqqao83U+sEShG++KcNgMPDZZ59hssThMkWjhkKENAjqMqZgCF/1EVIu7kdQhrjg0cRB10CDgB4k4NMxhmQkOYjb48EVCoaHGdADqKEQKiq1bi9V/qqIy1B0BZ/uY+v6rdQaa09PbE6B0+kkGAzi8XiatOm6TjAYZN++fRHz5c5VpzMuFxoRm5aJ2LRMxKZ553tcvF5vq/dtU2JUWFhIKBQiM/N4lW1d17FYLEyfPp2HHnooYv+YmJjwtoyMDAB69OgRbk9JSSE5OZmysjIAXnvtNeLi4nj++efD+8yePZvs7GzWrVvHz372syZjOlYEtrKyMnyOYz9fcsklbbm8JqZOnRpxTU6nk+zsbIYNG0ZsbNMyDqdKURSKioooKChodh4VQH1dHc4P/0VubCI1fgeyJGE++jiti7+c7dGdUS1RGNUAsSlpxKakNPatavga/Nw+qBOje2dwww03sGrVKt764zPsPuLAbwhR3eDDJ8vUL/kExeUgNf9aFBkur2rMsA0GAzISHgJYpBgCVV2xt99KYkYnZMPxAiS6Dkp9Ld5QgEBMe1J/UPT0sPswPWJ7cOeAOzHKrfvotSY2bbVp0ya++eYb4uLiMBgiC6j4/X4URWHkyJGkpqaelvOdCWciLhcKEZuWidi0TMSmeRdKXI498WmNVidGoVCIWbNm8cILL4Tv+Bxz/fXXM2fOnPBE6+Ze07/qqquAxrtOWVlZANTV1VFTU0P79u2Bxozuh69JH/viaumxR25uLunp6Xz11VfhRMjpdLJu3bqf/AaaxWLBYmla08tkMp2RD8jJ+k0YNQr/uvVw8CCZCVEc1ENouoYppJKpVdJJr6FYyyTKbMIel4CEhNMfotYTpGdmHEMvysBkMvHkk0/ys5/9jKnjx9H1Nw9RnNsDgi72ffYR9XPfImPIdfg7daSjw0/faj9G3YxFl/BKfhy6D7fPgrH8YlK6VxEMHsZsTsFgsKPrKopSQ6Ilmu3BOEr9tY1vpBmtjY/PvNXYTDZu6XYLNovttMamrS666CJKSkqorq4mKioKi8WCrut4vV4CgQA9evQgMzPznFx36YfO1GfxQiBi0zIRm5aJ2DTvfI9LW8be6sRo4cKF1NfXc/fddxMXFxfRNm7cOAoLC8OJUXO6du3KmDFjeOCBB3jrrbeIjY1l6tSpdOvWjUGDBgEwatQopk2bxtNPPx1+lPboo4/Svn17+vTpA8Dhw4cZMmQIs2bNom/fvkiSxJQpU3jmmWfo0qULubm5PP7442RmZnL99deHz19WVkZdXR1lZWWoqsrmzZsB6Ny5M9HR0a0Nw1ljysgg/Q+PUvPW23TZtQNDKEi5ScJnNCDFRjPEcpC0pBRKLNmUuxV0XSHaYmRQXgr35XcOL/R40UUX8eWXXzJx4kTe+8XNyAYDmqoimcxEX3szqb/4LZdUK9xWppFmMqESojoUpCzoRZPMxEQH6TnoYpL7jeDAgTdxu4sJBqtBkrCYU+iadQc2sqjZNYdDrkMomoJRNpIVk8Ut3W7hynZXnuVIQlRUFD//+c9ZvXo1hw4dwuPxNBZztdm47LLLwp8rQRAE4b9PqxOjwsJChg4d2iQpgsbE6Pnnn2fr1q0Rr9//0KxZs3jwwQcZNWoUsiwzcOBAFi9eHM7kBg8ezD//+U+ef/55nn/+eex2O/3792fx4sXYbI13GRRFobi4OOJ54e9//3s8Hg+/+tWvaGhoYMCAASxevBir9fijnCeeeIJ//OMf4Z+PJVrLli0jPz+/tWE4q8wdOpDx52cI7t1Lenk5AU3Fabeim03Ep2VwV0Y7aj1BdpQ7UXWdTsnR5CQ1nQvVr18/duzYwcqVK9m+fTua1UrWgEG4jXaMXpX2IYkulza+6i/HG4jbt40MpxlLXCypl16KwdL4tlqP7n/F7Skm4D+CbLASG9MLozGadsDl6Vewo3YHDYEGYs2xXJR0ESbDufOvjbi4OEaOHEltbS11dXUYDAYyMjLOyNwxQRAE4fwh6cfetRd+lNPpJC4uDofDcdrnGC1atIiRI0ee17cqzwQRm+aJuLRMxKZlIjYtE7Fp3oUSl7Z8f4u6B4IgCIIgCEeJxEgQBEEQBOEokRgJgiAIgiAcJRKjc5Cu6+EyKy1NATu2z4n7nrRPTUNvYcmDH9I0rVV9/ug529DHD/eNvL6fPBRBEARBaJU2lwQRzpxA8W4ali7FvWkd7qwa/L1CaKlmLPEZJCcPJiVlGL6GKPZ8V8G2LaXUexw02CvxtqukV5+OFOQOJTP6hMU3NZ3Apl341u9EqQogoWBJcmHr2wnTZUPBEPnr/+STT3j55ZdZuXIlkiQxcOBApkyZwujRo1t9DXWeIP/eXsGXOytxeBVSYy0M65HO0B5pRFsiz+cMqSyucbC42kFNMESCycDlASc527+lbncx9d4QBy0Z7DOns07dwcjemQzonCxepRcEQRDOmFO6Y7R27VoMBkO4JtoPzZw5s8Uq9jNnzqR3795YrVZSU1P5zW9+E9Gu6zp/+9vf6Nq1KxaLhXbt2vHnP//5pOPRdZ0nnniCjIwMbDYbQ4cOZc+ePRH7/PnPf+bKK6/EbrcTHx/f6mv9T4nauYuqp/5Iw5cLqb50N/UXH8SnHyZYXoanYhdlB99l88bfseyDZXyzbCdH6qrwBf1E16aSuvUiNi0+yBOrnqS4rhhoTIpcn31Dw6c7CBxW0VUdTTXjrUinfmEVgY9fAzUUPv9jjz3G2LFjUVWVl19+mWnTphEIBLjuuuuaLYvSnPIGH498tJW3V5ZQXu8jpGnsq3Lz6tI9PPHpNhze47VqaoMh/q/4IK8cqKTUFyCk6+yuquatigZeMiSww6lQ73CRULmdXodWULJ5E3/+fCczVpSclrtZgiAIgtCcU0qMCgsLmTx5MitXrqS8vDy8fdq0aRH1pVwuF9OmTQv//OKLL/KHP/yBRx55hO3bt/Pll18yfPjwiL4feOAB3nnnHf72t7+xa9cuPvvsM/r27XvS8Tz//PO88sorzJgxg3Xr1hEVFcXw4cPx+/3hfYLBIDfddNNPXg37TAhVVpKwbBl6IID3Ghl/tg+jYsOsxGL0m5EOezH543A2lEDSP6k1l6PbFAx2HS3GD1aN7Ooe6GVRvL75dRRVIbCrEu+mCmTcGG0+DJYQBksQg9WDRjTObTFoWz8HYOXKlfz5z3/mL3/5CytXrmTSpElMnjyZ1atX88wzz/DHP/6Rb7755qTXoOs6byzfx54qF9kJNjLjbSRFWchKsJMRZ2VTWT3vrzsQ3r/wUDVbXD7aWUxkWc3YA16stZUk+D0cjkth40VXYIiKRY1KxKSFuKh6PfH4+XTzYdbsbVudNUEQBEForTYnRm63m7lz53LfffcxatSoiDtDCQkJFBQUsHr1alavXk1BQQEJCQkA1NfX89hjjzFr1ixuu+02OnXqRO/evbnuuuvCx+/cuZM33niDTz/9lOuuu47c3Fwuu+wyCgoKWhyPruu89NJLPPbYY4wZM4bevXsza9YsysvL+eSTT8L7PfXUUzz44IP06tWrrZd8xnlWr8bg8SC1S8LTrgY5ZEBWG0uhSGYTqCq+GheKPxZDzAGioqsxyMdrfGmmxjs/7Wt7csB5gM3Vm/Gt2wlqCNkceXdFksBg9qCqsfi/3Qy6zuuvv063bt14+OGHm4xt6tSpdOrUiddff/2k11Ba42HzwXqSoywYDZEfK4vRQKzVxNLiKhq8QaqDCivrXcQbDZiPloDxOhoa50DpYPH7qE5Nw2WPBkkiYIrCEPSQ6SlDUTWW7Khoc4wFQRAEoTXaPMdo3rx5dOvWjby8PCZMmMCUKVOYOnUqkiQxceJEBg8eHL7Ds379enJycoDGyryapnH48GG6d++Oy+Xiyiuv5IUXXiA7OxuABQsW0LFjRxYuXMiIESPQdZ2hQ4fy/PPPk5iYCMD+/fvJzc0Nr1hdWlpKRUUFQ4cODY8xLi6Ofv36sXbtWm655ZZTDk4gECAQCIR/PlaETlEUFEVp6bC2n6ekFGSJkC2Iag4iB0yRE44NBhR/CM0SjWQKEhXlxOmPTHg0g4LNHQshif11+8mpjkGS/OhSM7mvpKNLBpQGFcVdx8aNG7n22msJhUJN9wVGjBjB0qVLT3rNpdUu3IEQSVEmNL3pJO9oi4Fqd5D91S4C0UacIZUMkzE8ITzg9SDJMqoG5lAQT0wsjqhooj3uxmxOB5O7hqjYPHaUOwgGg//Vc42O/S5O5+fwQiFi0zIRm5aJ2DTvQolLW8bf5sSosLCQCRMmAI1fmA6HgxUrVpCfn8/s2bOZPn16eO7RzTffzKRJk5gwYQIlJSVomsazzz7Lyy+/TFxcHI899hgFBQVs3boVs9lMSUkJBw4c4MMPP2TWrFmoqsqDDz7IjTfeyNKlS4HGQnB5eXnh0g0VFY13D9LS0iLGmZaWFm47Vc8991yz82uWLFlyWktHJB08SIymU19XT0gJIYU0JOX4HSFJCaEaVFQ1hKTrKEGNQDAY0YdJMaDLKk6Pk+3btnOZrxdWVSd0QmIXQbXj83tY9eVXBINBtm/fzqJFi5rddceOHQQCgRbbAYobJDxumcqQG7mZfCWogicksXbNaoIxZjy2JCo1FRONCZ6iKGiqhirpqEigaaiBAMFg4/hVNYTb56euoQG7ARYt+oL/4rworKio6GwP4ZwlYtMyEZuWidg073yPy4llxH5MmxKj4uJi1q9fz/z58xsPNhoZP348hYWF5OfnU1VVRVFRER999BEAL730Em+//TbQ+Aq4oii88sorDBs2DIA5c+aQnp7OsmXLGD58OJqmEQgEmDVrFl27dgUaE7HLLruM4uJi8vLyaNeuHbt27WrLsE/Z1KlTeeihh8I/O51OsrOzGTZs2GktCeIwWzi0fTspUipV/nqCsR5MHku4XVc17PF2VPwoWhRubyYWs/l4BzqYgzaqU0tJSkjk1itvJcFQh39TOUZjCOkHb5/pqgFNU4ntksbwa8cyfu0G3nrrLT744ANiYmIi9m1oaGDChAk88MADjBw5ssVruNKrsO79TQRVleRoS5P28gY/efE27hh7MaoEa3aWURMMkWZpXGK+AQ1XbQ0GgxGnbMYWDJDudWM2W1D8XgxGE1JmF0xSNKP7ZDJqYMdTCfUFQ1EUioqKKCgoOK+X6T8TRGxaJmLTMhGb5l0ocTn2xKc12pQYFRYWEgqFyMw84ZVwXcdisTB9+vSIJAIgJiYmvC0jIwOAHj16hNtTUlJITk6mrKwsvI/RaAwnRQDdu3cHoKysjLy8vCZjSk9PB6CysjJ8jmM/X3LJJW25vCYsFgsWS9MveZPJdFo/IDFX9ieYkoJ2pIKYfSnU9fGi2gIYfCZ0fxDMJsypFsyuejwHLkf3JxIwBLEYzKBLmHx2FFOA/SlbuTz9cromdSV0lQdlVyWaLwqD2Yd0dN6PrsloQRsm62FsAwYjmUxMmjSJN954g/HjxzNr1qxwHMvLy7n99tuRZZn77rvvpNecEmfi570ymLO+DJdfJdZqRJIkdF2nzhNEA8ZemkWUrTGe49KTeK2skjpVI9FoIDohEa/DgVsyoJtMZJfswaQoSFoIq+LGF5/JXkM6iTYLIy9ud17/BT2dTvdn8UIiYtMyEZuWidg073yPS1vG3urJ16FQiFmzZvHCCy+wefPm8J8tW7aQmZnJnDlzwvtOnDiRiRMnRhx/1VVXAY13nY6pq6ujpqaG9u3bh/cJhULs27cvvM/u3bsBwvv8UG5uLunp6Xz11VfhbU6nk3Xr1tG/f//WXt5ZJdvtVF87CnOXrlg2acR8E4XuVwhaXYSSVfQOdnSjSmbWcBIst5MmtSPKE4/ksCI5LXgNLvZ2/oaL8jpx/yX3I0kSpvRoYsf0QbYbUIMxKF47IZ8dNWDCZDtC/KguSNmXA5CTk8OCBQv49ttvycnJYfDgwQwaNIicnBy2bNnCwoULadeu3Y9exx39OzCqVwY+RWV/rZfSGg/7a71owO19c7i21/HE9cb0BG7NSELVdUp9QQ6qEp60duhmM5ceKqbf7g0Y3DXgdVJrTua7tAEkxNh5eEQenVKiz9SvQhAEQfgv1+o7RgsXLqS+vp67776buLi4iLZx48ZRWFjIvffe2+LxXbt2ZcyYMTzwwAO89dZbxMbGMnXqVLp168agQYMAGDp0KJdeeil33XUXL730Epqm8Zvf/IaCgoLwXaTDhw8zZMgQZs2aRd++fZEkiSlTpvDMM8/QpUsXcnNzefzxx8nMzOT6668Pn7+srIy6ujrKyspQVZXNmzcD0LlzZ6Kjz/4XbSgxkbTnnkXZsgX/jh0EAw34Ul3QPh6TPYGE+H5ER3cnr5tO9xIn+3aXs7/+AB5rPdYOEmPa30nP5J7IJ0y2tvZsj6l9KoH1mwgdPIhECHM7G+a+NyHFpUacPz8/n/379/Pee++xYsUKJEni5Zdf5he/+EWrHxuajTIPFnRlVO9M1u6rweUPkRRtYUDnZHKSIudkGSSJ+3JSGZ4cx8p6F/VKiDijgb7WHIy7zdSmx1HuDFJhTKS6QeHXV11Kfrd04uzn779YBEEQhPOA3krXXnutPnLkyGbb1q1bpwP6li1bTtqHw+HQ77rrLj0+Pl5PTEzUx44dq5eVlUXsc/jwYf2GG27Qo6Oj9bS0NH3ixIl6bW1tuL20tFQH9GXLloW3aZqmP/7443paWppusVj0IUOG6MXFxRH9/vKXv9SBJn9O7OfHOBwOHdAdDkerj2mNYDCof/LJJ3owGDyt/V4IRGyaJ+LSMhGblonYtEzEpnkXSlza8v3d6jtGCxYsaLGtb9++rVqNODY2lsLCQgoLC1vcJzMzMzx5uzkdOnRoci5Jknj66ad5+umnWzzuZKtxC4IgCIIggCgiKwiCIAiCECYSI0EQBEEQhKNEYiQIgiAIgnBUm1e+Fs4sRamntnYlbs9eJEkmNqYnCQlXYjRGRex32H2YNYfXcMR9BJvJRp/UPlySegkm2cTOnTt566232LZtG3a7nbFjxzJ+/HhsNht+VePrBjebnB4Cmk6u3cLgxNjwQos/1OAN8s/1ZazZU4PP4yFdd9Av2k2XBDPt8rqR1f0iDMamx+qajnLYTaDEgeZVkGPMWLvEY0y1/1eX8hAEQRDObaeUGK1du5YBAwYwYsQIPv/88ybtxyY5n7iWUW1tLbfffjtbt26ltraW1NRUxowZw7PPPhvxOnggEODpp59m9uzZVFRUkJGRwRNPPMFdd93V4nj8fj//+7//ywcffEAgEGD48OG8/vrrEWVCfvvb37JmzRq2bdtG9+7dw6/rn0scjo2Ulb1KIFgFuo4OVFV9gd3Wgc6d/4+oqE7ous7CkoXM2TUHV9CFhISGxhelXzS+rr9U5uknniYlJYWBAwdSXV3NnXfeyTPPPMN7Cz/n3ZCFXR4fqt5Yggwd5hyp47ft0xiaFPla/ndldTwwZzOVTj+yGsQc8rMXnfW6RE9tP9esXUl6bicGTriLqPiE8HG6ouIoKiOwpx5N0RpLneng3VSJrXcKMVdnITVXN0QQBEEQzrJTepRWWFjI5MmTWblyJeXl5eHt06ZNw+VyhX92uVxMmzat8USyzJgxY/jss8/YvXs3M2fO5Msvv2yy9tHNN9/MV199RWFhIcXFxcyZM6fZFa9P9OCDD7JgwQI+/PBDVqxYQXl5OTfccEOT/e666y7Gjx9/Kpd8xklSHaX7pxEI1mCzZmO35xJlz8VqycTrLWHv3v9HKORiXcU6Zu2Yhaqp5MTkkBObQ4fYDiRaE1n06SKefuJpHn30UQ4ePMiHH37I8uXL2bFjB0gSo64dzfcON+kWEx3tFnJtFtrbzLhCKi+UVrDNdbyWTK07wENzt1Dh9BMlhUgO1hKnuYnRA2hIbDLmssPWmYq9u1n9wXvhYrAArjXl+HfWIlkMGJOsGJNsGJOsIMt4N1bh3VJ9NkIsCIIgCD+qzXeM3G43c+fOZcOGDVRUVDBz5kweffRRABISEigoKKBnz54AzJgxI5z4JCQkcN9994X7ad++Pffffz9//etfw9sWL17MihUrKCkpITExEWh8Pf9kHA4HhYWF/POf/2Tw4MEAvPvuu3Tv3p1vvvmGn/3sZwC88sorAFRXV7N169a2XvYZZzR+j6LUYLd1QDphkUZZNmG1ZuP1HaC2bg1flK4lEAqQE5sTcbzNaOPggoOk9k7ll//7y4hSJt27d+f3b7zFrwsGI2/4Gsugocf7lyTaWUyU+oIsrG6gZ0zjQoyfbSnniMOP1WjA5q9H1jU0gwkJsBPCpRvYGEqhT3w1FSW7qSzZS3rnrqjuIP4djUmRbD3+8ZIkCUOUiZCi4d1chb1XMpJRTHETBEEQzi1tTozmzZtHt27dyMvLY8KECUyZMoWpU6ciSRITJ05k8ODB9O3bF4D169eTk5PTbD/l5eV8/PHHDBw4MLzts88+4/LLL+f555/nvffeIyoqiuuuu44//elP2Gw2AJYvX86gQYMoLS2lQ4cObNy4EUVRGDr0+Jd9t27dyMnJYe3ateHE6FQEAgECJ1SnP1aETlEUFEU55X5/SFEUZEMJkmRpXHVS1yJ3kGR0XaOy5ht21+0m1hyLpkXuE/AEqN5VzcWTL2Zb9TZyY3Ij2oOdumHNyaVm7SpyBw5uMoZoWeLrejeBYBBZkli+qwpN0zGZdAyKH12KTGIsWhCHZqHOGIc9WEf53t0ktc8lcNCB6lWQEyxoP7wOQLLLqI4A/goXxjR7k/bmYnPi/wqNRFxaJmLTMhGblonYNO9CiUtbxt/mxKiwsJAJEyYAMGLECBwOBytWrCA/P5/Zs2czffp0Ro0aBTQ+Fps0aVJ4f4Bbb72VTz/9FJ/Px+jRo3nnnXfCbSUlJaxevRqr1cr8+fOpqanh/vvvp7a2lnfffRcAu91OXl5euCBcRUUFZrOZ+Pj4iHGmpaVRUVHR1suL8Nxzz/HUU0812b5kyRLs9h//Um8Lq1XD5XLjdFY12y5JXmrq91HfUI8RI37JH9EecDUmcIqusHnLZgy7DBHtO8yxSBYzHpeLyqqm53BJMgbg8y92YgAqqmQ0XSIYDGE/Ot/pxMdl6DKaplNb14Du8fD991s5GFCJrTeR5bYRCDmhmWlEkgYmRWbrylX4otRWx6eoqKjV+/43EXFpmYhNy0RsWiZi07zzPS5er/fHdzqqTYlRcXEx69evZ/78+Y0HG42MHz+ewsJC8vPzqaqqoqioKLxy9UsvvcTbb78d0ce0adN48skn2b17N1OnTuWhhx7i9ddfB0DTNCRJ4v333w/XY3vxxRe58cYbef3117HZbPTt25ddu3a1Zdin7Nj4jnE6nWRnZzNs2LBW1w9rDUVRWL7iC+JiPNjtqU3adV3D7/eR124E3fZ+y37nflKjIvfTU3Ri0mNwbnMy6pFRXJp6aUR71aZtvLF3Nxm3/IK01Kbn8PmD/CwuitGdLwOg2LSH0jX7kU1GdKMZQyiAJh+/a6ToJqIMGrmxZjRiGDCkgJxelxCq8+OYu4cYo4Rsa/rx0lwKkllm4OifRTxqO1lsioqKKCgoOK8rO59uIi4tE7FpmYhNy0RsmnehxOXYE5/WaFNiVFhYSCgUIjMzM7xN13UsFgvTp0+PSCIAYmJimmxLT08nPT2dbt26kZiYyNVXX83jjz9ORkYGGRkZtGvXLqJIbffu3dF1nUOHDtGlS5cmY0pPTycYDNLQ0BBx16iyspL09PS2XF4TFoslYq7OMSaT6bR/QNRQT4yGchSlFos5Jbxd13UCwQrM5kTS04YyLJTAm1vfxBvyEm0+XvxW1VWyR2Szc9ZOKjZWYLru+Ph8Ph/zHn8Ec0wspsEj0CUJ+YRX5uuVEGZZZnRaYvi6bu7bnnnfHcbpU7CYY7CFAkiahi7LBHWZkGziIlM1Wn0VCRmZtO95MUaTCVOaCX+HOAK765AsRiTD8WRKV1QIatguScUSY2tTfM5EzC8EIi4tE7FpmYhNy0Rsmne+x6UtY291YhQKhZg1axYvvPACw4YNi2i7/vrrmTNnTnii9Ymv6Z/MsXkyx+bxXHXVVXz44Ye43e5wxfvdu3cjyzJZWVnN9nHZZZdhMpn46quvGDduHNB4Z6usrIz+/fu39vLOOk3LIjPzNo4c+ScebylGQxSgE1K9mEzx5HaYjMWSRkGHAvY07GH5weXU+euwm+yEtBB+1c9V46+iXXU7xl4/lhEjRlBQUEBVVRXvvfcedXV1vDRnHkviYtnvC2AzyBgkCY+qYZYkbkxP5JqE44lWh+QoHh7WjWe/2EFDwILPlIBV9RLSjeiSRAetmj7u7UQnJ3PlzRMwms3hY2Pzs2lwBVEqPCBLSEa5MSkCLB3jiO730xJWQRAEQThTWp0YLVy4kPr6eu6+++6IOzoA48aNo7CwsMmr9ydatGgRlZWVXHHFFURHR7N9+3YefvhhrrrqqvCbZ7fddht/+tOfuPPOO3nqqaeoqanh4Ycf5q677gpPvl6/fj133HEHX331Vfju0t13381DDz1EYmIisbGxTJ48mf79+0dMvN67dy9ut5uKigp8Pl94HaMePXpgPuFL/eyRSE8fR2xcd6qrl+BybkOSDKTEX05qyjCiojoDYJJN/OaS33BZ2mUsK1tGmasMm9HGgHYDGJQ9iMSCRGbNmsWMGTN4/PHHwws8Tpkyhe7duzPSF2BxtYPVDW4CmkbfuCh+nhxP//ioJgsvju+bTcfUKN5ZVcJ3B+rR/CbSNSe9pQoujw3Q5ZKRdL78Z8QkJUccZ4g1k3BDF3w7a/HvqkPzKBjS7Fi7J2HrloBkipz/JAiCIAjnDL2Vrr32Wn3kyJHNtq1bt04H9C1btrR4/NKlS/X+/fvrcXFxutVq1bt06aL/3//9n15fXx+x386dO/WhQ4fqNptNz8rK0h966CHd6/WG25ctW6YDemlpaXibz+fT77//fj0hIUG32+362LFj9SNHjkT0O3DgQB1o8ufEfn6Mw+HQAd3hcLT6mNYIBoP6J598ogeDwdPa74VAxKZ5Ii4tE7FpmYhNy0RsmnehxKUt39+tvmO0YMGCFtv69u2LrusnPX7QoEF8/fXXP3qebt26nXT2e35+fpNzWa1WXnvtNV577bUWj1u+fPmPnlsQBEEQhP9uYoU9QRAEQRCEo0RiJAiCIAiCcJRIjARBEARBEI5q88rXwllSvx8qtzeWqU/Jg6TOILVcoV7zevFt2YLqdGFIiMd2ySUE9Tpcru3oegi7rQNRUV3RdZ1NZYf4rs6JZJC5JC2ZzV8uZ92mbZjtVvoO60FmThTRpmguTrkYu6lxxW9N01m7dS/F+8sxyxJX9sqlY252xBh0VSN40IXqUpAtBsw5Ma1a1PEYV52fiv0N+CqM1B/xkJId1+TNOUEQBEE4nU4pMVq7di0DBgxgxIgRfP75503aZ86cCUSuZ1RbW8vtt9/O1q1bqa2tJTU1lTFjxvDss882u4r0mjVrGDhwID179gy/Wt+Suro6Jk+ezIIFC5BlmXHjxvHyyy+H10Javnw506ZNY/369TidTrp06cLDDz/M7bfffiqX/5/lq4dV02D/Kgi4GreZoyC7H1zzMESnROyu6zquoiLq53xAqKoKdA3NDO5BQQK9ZXRb48R1WbaiGPN4p2IwW4khIBlwbVzHkZeeI1RbjcFmQw34ef05SBuUxaX39KZdfAY3dr2RdLUXz36whgMuFeVolZC3vj7IlWkyU+8aSVxcHIH9DlwrDxGq9YOmgwSGaDP2y9KwX5p60gQn6A+x6d9llO2sI+BV8HjMLKsuJjU3jitGdiA6wXpGQi0IgiAIp/QorbCwkMmTJ7Ny5UrKy8vD26dNm4bL5Qr/7HK5mDZtWuOJZJkxY8bw2WefsXv3bmbOnMmXX37Z7NpHDQ0N3HHHHQwZMqRV47n99tvZvn07RUVFLFy4kJUrV/KrX/0q3P7111/Tu3dvPvroI7Zu3cqdd97JHXfcwcKFC0/l8v9zQkFY8jjsWggGEyTmQmJHMNlg31fw76kQcEcc4l66lJo3ZqDW1mJKT8eUk4NjqAdnu8OEjhzB5I/FZm1PSLPxRl0m35mNmGQd844tHHrq/7BmdyDnlb/T/f1Z9H51BFk39KRq2WE2vb6TGl8dr6/9J1Pe/Yq9DhU7CmlmlRSTiobEl0cknnjjE3z763EsKiVU7cMQbcaYZMMQZ0XzhXCtOoT3u+brwQFoqsY3n+xj73eVyBLEplgx2HSMFgOHi+tZNW8Pfs/5XcxQEARBOHe1+Y6R2+1m7ty5bNiwgYqKCmbOnMmjjz4KQEJCAgUFBfTs2ROAGTNmhBOfhIQE7rvvvnA/7du35/777+evf/1rk3Pce++93HbbbRgMBj755JOTjmfnzp0sXryYb7/9lssvvxyAV199lZEjR/K3v/2NzMzM8PiOeeCBB1iyZAkff/wx1157bVtD8J+zfxUc+hbishqToWOscWC0wpEtsG8p9LgOAC0YpH7uPAiFMLVrB4A/wYEvowFT0A4ehdCRIxgTEtjiy2An3UiU6jDK0Wx8/12sWTl0fuRP6CYNj9lOXMLVdBi5HZPZTOk/NxIcfzmB+vbUBWTSTQqGo+U+ZAliZR1Z1fm2zsjmL7aR67VhSLKG7wxJBglDnAXVEcCzoRLbRUnNPlarLHVyeHcD9lgLZqsBTdeRJDDbjJgsBurKPRz4voa8n2Wc4eALgiAI/43anBjNmzePbt26kZeXx4QJE5gyZQpTp05FkiQmTpzI4MGD6du3L9C4SnVOTk6z/ZSXl/Pxxx8zcODAiO3vvvsuJSUlzJ49m2eeeabJcTNnzuTOO+8Mr2W0du1a4uPjw0kRwNChQ5FlmXXr1jF27Nhmz+9wOOjevftJrzUQCITLlcDxInSKoqAop++uxbG+ftinvG8ZsqaiGyxwYmV7ALmx7ou+50u0Lj8HwLdlC8HycozJSWh64/6elFp0g4oUsoJJQvN6CbndbA52RTUYsaAQcJXTsOlbsu/7X2STAZUgsq4TsHbGGthG2jWdOPDRVnYt3UNS52EYtSA6EuiRNxyjJI1qjGw47CE3Mxodven6VtFG1IYg3pJ6LF3im8SibGctakjDaJHRdB396HXrmoYky0gylG6tpuNlyU2O/W/S0mdGELE5GRGblonYNO9CiUtbxt/mxKiwsJAJEyYAMGLECBwOBytWrCA/P5/Zs2czffp0Ro0aBcDNN9/MpEmTwvsD3HrrrXz66af4fD5Gjx7NO++8E27bs2cPjzzyCKtWrcJobH5ocXFx5OXlhX+uqKgg9QfV4o1GI4mJiVRUVDTbx7x58/j222958803T3qtzz33HE899VST7UuWLMFut5/02FPxw4UtLy7bSoLHh09p/tGTNejHU7KDDYsWAWDfvZvUhgaCRkN4YrY/14kaUtGDAdB1JCWEu7oal8WMJGvouo5yNOEzp6aj6Rq6pGPQVEKSmUAgCIApzoqn3ku8KiETIqjoqGjNjMqIK6RQ11CH5mqmGbD4ZPas3UD9nmCTtoZdZvweI4HKyIOrq2sAUAMS3jInixaVNt/5f5mTLYb6307EpmUiNi0TsWne+R4Xr9fb6n3blBgVFxezfv165s+f33iw0cj48eMpLCwkPz+fqqoqioqK+OijjwB46aWXePvttyP6mDZtGk8++SS7d+9m6tSpPPTQQ7z++uuoqsptt93GU089RdeuXVscw9ixY1u8C9Qay5Yt48477+Ttt9/moosuOum+x8Z3jNPpJDs7m2HDhjU7YfxUKYpCUVERBQUFERWA5VXbkbcdJiYxtdnjpHoPMZ2vYOTQkQAEOnakcvUa5JgY5KOJW4MhgMPobizyGlJBkklKSyfZ6UGXZJDAkpiCZDLh3VtMXO9L0JFQZSNWxY3FYibo9BOs9RDfLg6zKUhAs2I2SRjlyI+PpgMKpJhNJMYmIEc1rWashzQ0l8Jl1/TG3KFpDLdaD7FzTQWxKY2P4XRNo7q6hpSUZCRZxlnjJ71jLNeM7HKq4b4gtPSZEURsTkbEpmUiNs27UOJy7IlPa7QpMSosLCQUCpGZmRnepus6FouF6dOnRyQRADExMU22paenk56eTrdu3UhMTOTqq6/m8ccfx2azsWHDBjZt2sSkSZMA0LTGOxpGo5ElS5YwePDgJmNKT0+nqiryjkooFKKuro709Mgq7itWrGD06NFMmzaNO+6440ev12KxYLFYmmw3mUxn5APSpN+84bB7EVLAAbaEyJ0DLjAYMeSNwHD0GONFF2Ht0gX/9u0YchqLwkZXJuPqcATNoiD7VAyJCRjtdvoGD7NO6YWbKOxWGylXD6bmi/kk5w+HpBh0ScMUKAYdyj79HiSJi4Z1xVFegq/q4sZHdT94scwRMmCXglyZlwRHVCS7GUk+vpOu62guBVOSDXtuApKx6dz/3F6p7NtYQ9CrYos2ocmN+0iyjBrUkCToeEnqef0X9HQ6U5/FC4GITctEbFomYtO88z0ubRl7q99KC4VCzJo1ixdeeIHNmzeH/2zZsoXMzEzmzJkT3nfixIkRr+q3RDs6fyQQCBAbG8v3338f0fe9995LXl4emzdvpl+/fs320b9/fxoaGti4cWN429KlS9E0LeKY5cuXM2rUKP7yl79EvLF2Tsu8FLqPAb8DHAch6IGgF5yHwVMNXUZA+6vCu0uyTOLEiRiSkggeOIDqcGCsMRCzIwFN9xNK0pEzklBVH50tZVzFOrxaDNV6HO1+8T+gw84/TKaiaAnS7q9p+O5ztr3yFZVL99D5tp4EbPWkdq2hU7xEnWqmIQjBEPhCEtVBA7qmcX0nK11H9sKYbEet86F6FHRFRfOFCNX6ka1GYq5u12xSBJCQYadrvzQUv4qz1o8SUNFU8DQE8DiCZHdLJKdH4n/qNyAIgiD8l2n1HaOFCxdSX1/P3XffTVxcXETbuHHjKCwsbPbV+2MWLVpEZWUlV1xxBdHR0Wzfvp2HH36Yq666ig4dOgCE32Y7JjU1FavVGrF9/vz5TJ06lV27dgHQvXt3RowYwT333MOMGTNQFIVJkyZxyy23hO9sLVu2jGuvvZYHHniAcePGhecemc1mEhPP4S9ZSYIBD0J8NmyfD85yQIfoNOh+HVx8Kxgif4W2nheR/vhjNHz4L3xbtqD5fMRsT8bWLg9vTx8BuQ4t1IDFEs/9ybmkHbLy74BCfVo6nV6cQeVbr1A94yWqj07etqZHcdGkPlw0rCu9U3oxrus4Ugbl8MqHK1hV0oA7BBI62eYgYy9O5/axQ5ANBuKv74xn3REC+xrQvCGQJawd47BfnoYlp+XHkJIkcfGgbKLiLOz5thJnrQ9dkbBGmeh8aSrd+mdgaCGpEgRBEISfqtWJUWFhIUOHDm2SFEFjYvT888+zdetWevfu3ezxNpuNt99+mwcffJBAIEB2djY33HADjzzySJsG7HA4KC4ujtj2/vvvM2nSJIYMGRJe4PGVV14Jt//jH//A6/Xy3HPP8dxzz4W3Dxw4kOXLl7fp/P9xBiNcfAtcdAM0HGjcFpcNppYXObTm5ZH+2B9QKivRXC4M8fEYk5PRtBB+/0F0XcVqzcRgsPNIZ/iN10dxXQNc3IXuE8ZSW1HJN5u3ExUdwyWXdsSvuYg2RZMWlRY+x1N3/5x6p4d9ZUcwGyR6dM7GaDKH243xFuKGd0D1KGjuIJLFiCHO3KqVqyVZosvlaXTqk0JdhZvly1cw/Poe2KLEwo6CIAjCmSXpTd6nFlridDqJi4vD4XCc9snXixYtYuTIkef1M9wzQcSmeSIuLROxaZmITctEbJp3ocSlLd/f4pmEIAiCIAjCUSIxEgRBEARBOEokRoIgCIIgCEe1eeVr4T8r6PPidToxWSxExSf8+AFtENA0KgMKRkkiw2LCr2jUuAPILgfJkoIxMQlDdBQOh4P9+/cTHR1Nx44dGydQ++rB19BYt83e/Jt9wWAtqurBZErAr9qocwexWwwkR1tQ3UH0gIocbUK2nH8fQ13XcbvdhEIh7HY7FosFNaThaQggyRLR8ZaINZwEQRCE88MpfSOtXbuWAQMGMGLECD7//PMm7TNnzgSIWMuotraW22+/na1bt1JbW0tqaipjxozh2WefDU+EWr16Nf/3f//Hrl278Hq9tG/fnl//+tc8+OCDJx1PXV0dkydPZsGCBeG30l5++WWio6OBxhW77733Xnbs2IHD4SAzM5PbbruNJ5988pydTOZ1Oti2rIjSTRsI+nzIBgPpnbtw0cChpHf6aas++1WNjyrr+by6gepgCD2kYTrsQStzQE0deL109NfSr2EXiw9s45NN34Vrxl3cszuP33Ax47JrIBQAoxk6XA19JkBSJwBc7l0cKf8XDud3BENB6rwy31d3Z3PtVaQFErlWNpOnydgMMpLFgDUvkajL0zBEm0827HPGoUOH2Lx5M+Xl5WiahsVsIcGaAbWJBJyNSw7EpdjockUauRcnt+pNPEEQBOHccEqP0goLC5k8eTIrV66kvLw8vH3atGm4XMdrXLlcLqZNm9Z4IllmzJgxfPbZZ+zevZuZM2fy5ZdfRqx9FBUVxaRJk1i5ciU7d+7kscce47HHHuOtt9466Xhuv/12tm/fTlFREQsXLmTlypURiziaTCbuuOMOlixZQnFxcbhUyZNPPnkql3/GeZ0Ovip8nW3LilACfsx2O7JB5sDWzSx9900Obt96yn0HNY0/l5TzxsEqKgMKdh3qttSwZ0cNJS4/blXBjMombNy/+BO+2LSZBy+9lDWLF/PpezPIkGu58ekPmLH8IFiPzuzf8SksfBCqi3E4t1Bc/CQ1tctRVNhfJ1Hv8dA1dhU3ZMziJk8diZV+yup9eNDRgxreDZU0fLIX1d20dtq5pqSkhC+++ILS0lIMBgMWi4X6ahfbd29lX+0mZIuKySxTW+5h3WclfL/8UNNCuoIgCMI5q813jNxuN3PnzmXDhg1UVFQwc+ZMHn30UQASEhIoKCgIL8g4Y8aMcOKTkJDAfffdF+6nffv23H///fz1r38Nb+vTpw99+vQJ/9yhQwc+/vhjVq1a1eJq1Tt37mTx4sV8++23XH755QC8+uqrjBw5kr/97W9kZmbSsWNHOnbsGHHu5cuXs2rVqrZe/n/E9hVfUX2glNiUNAzhYrpWLFHROKor+XbBx2R06dZY/6yNlta6WFnnItVsJMpgoGJfA75aPzZJIWSQqI+PJ62+htrlswkFfFw14WluOrKKnJJSrszZw+i72/Gbz6J5cN5ebrq6G0kxSY3lSupK0Na+woFcHUWpx27rwP5aL06/js2cgE+NI9NUjiFzOc5DN+ALaZQ6/fRqF4dsN6JUePFsqCQ2P/v0BvM0CgaDrFmzhmAwSGJiIpIk4XMFUX0GLHIUCi6cejnp9s6YbUZ8riC71laQlZdIYmbU2R6+IAiC0AptvmM0b948unXrRl5eHhMmTODvf/97+F/EEydOZN68eSxcuJCFCxcyb968FkuDlJeX8/HHHzNw4MAWz7Vp0ya+/vrriH1mzpwZ8Whi7dq1xMfHh5MigKFDhyLLMuvWrWu2371797J48eKTnvtsCfp9lGxcj9lmPyEpaiRJEjEJSTirqzhcvOOU+v+ixoEORBkM6JpO7UEXEhqyrmHWdUKyRI1BZv+Or+ly8SCCCVlsSe6Ce/mXqCXfIkWn8tSNPdF0ndlrji44KckQlYqrfiNeZzEWcyohXafWE8BkkJElCasqY1Ci8SduB5Mbs1HGF1Rx+hSko4/U/MV1aIHQT4zgmXPgwIHwGhjHPoNeZ+NdLoPRgCwbaQhWoOkqANZoE8FAiLIdtWdtzIIgCELbtPmOUWFhIRMmTABgxIgROBwOVqxYQX5+PrNnz2b69OmMGjUKgJtvvplJkyaF9we49dZb+fTTT/H5fIwePZp33nmnyTmysrKorq4mFArxxz/+kf/5n/8Jt8XFxZGXlxf+uaKigtTUyOrzRqORxMTEcOmPY6688kq++65xvsyvfvUrnn766ZNeayAQCM+tgePVeRVFQVGUkx7bFsf6UhQFX0M9AZ8Xs82O1swjGMloRNM0HDXVpzSGMp8f29Gq9aGgSjAQQpZ1dFVHkgAdPD43ISVASmYnNB1q7XGoNU5CDg9SXBJJZiN5GTHsrXCH691hshNQD6OpBiTZQiCgomo6RoPUWAhY15FUM7rZDaYG5FA0uq7jV9TGgrRmCc0fIujwYUg4vsL1ibE52xoaGtB1HUmSwtetBNXGJEnXkTGgagpBNYDZYAMak1lHtfe0j/9cisu5RsSmZSI2LROxad6FEpe2jL9NiVFxcTHr169n/vz5jQcbjYwfP57CwkLy8/OpqqqiqKiIjz76CCA8l+dE06ZN48knn2T37t1MnTqVhx56iNdffz1in1WrVuF2u/nmm2945JFH6Ny5M7feeisAY8eOZezYsW0ZdtjcuXNxuVxs2bKFhx9+mL/97W/8/ve/b3H/5557jqeeeqrJ9iVLlmC3209pDCdTVFSE6vfhdLnA5cZgaVoCQ9d1Qh4332/fTqnT2+ZzeG0p1EgGNF1F13RCaghCKmZdR9M0dAMYDI0T0h31VdhUFdVRj9vnxxP0o1Yd4f+zd+fxURR548c/3XNPjklCTnIQDkk4RUEQgZUrgICLyD4iC4+CeBs88HFXVv2pe+jq6uKByi5E0UURPFBBVKIIyCEgcggEwn2F3JPJ3NMz3b8/AqNDEki4RLferxcvTXd1VfU3E/KlurrKpxk4Wu1BrwUoLy8HQFYD+KwBvF4/Tt8xFFVHMCihBkGWwa9KaFIQTZVR/DKaP0BIBWetA3ygC0pIqsTGlV8TNNRPCAsLC5t9r+ea3W7H5XIRCATCI0YBRYcWhKAKIRQkoLrSjkzdXLugW+LgETs1S3adouYzdzHE5WIlYtM4EZvGidg07JceF4+n6b8vm5UYFRQUEAwGw5uzQt0vapPJxIwZM5g6dWpE+ZiYmHrHUlNTSU1NJTc3l4SEBPr168djjz1GWlpauEzr1q0B6NKlC2VlZTzxxBPhxOhkqamp4V/OJwSDQaqrq0lNTY04nplZN3+lY8eOhEIhbr/9dh588EF0Ol2DdZ9I3E6ora0lMzOTIUOGnPMtQQoLC8nLy8NgMLDCXcPBLd9jS06q90aTx1GDHG1l5I3jsdrimt2WvbSafx+pItFsQCdJBDJ0lB9wgBRCkyR0QLLBRFp2Z/ZtX0XPbnn0cpWQ2OdqbDm7kez7eGubn2q3wqSBOSQnH987z3GYoK0j5S0MBENuTMZkXDixexVMBh1BTUOlCmNtOyQ1jYBOw2yQaJVmQyeDWuXHeImNtiNanzI2Pyen08n777+PpmlERdXNGXIb/TgqfOgMEpoaIM6URmpU3c9HMBDCq1PoM7wtLdvHndO+XExxudiI2DROxKZxIjYN+7XE5cQTn6ZocmIUDAZ56623eP755xkyZEjEueuuu4558+aFJ1o3Nq/oZCceR/z0cVVDZU51vnfv3tTU1LBx40a6d+8OwLJly1BVlV69ep2yXkVRUFW10cTIZDJhMpnqHTcYDOflA3Ki3i4D8ijftwdnRTnRCS3QGwyoqoq31kHQ7+fSvGuwJSadURsjUhL40u5mv8dPiklPcus4HOVevC4VTVKJ93qICvhpdeVo1i14ioMfPE2oU1sSbriBgLaf/zzzIPe/t4+xvdLp2ioeQgq4ykHWY7z8FtJsXg4fLkBRKkmzxeLyhwgEA8SZHHiDFhKP/QZdAPxAWrwZAxKhGj+6KAMxPdIajev5inlzJCQk0LlzZ77//ns8Hg9WqxWrzYTb4cMbcGPQGWlhykQCAt4gXqdCy/bxZOS0QKc/P2upXgxxuViJ2DROxKZxIjYN+6XHpTl9b3JitHjxYux2O5MnT8Zms0WcGzNmDAUFBRGv3p9syZIllJWVccUVVxAdHc327dt56KGH6NOnD9nZ2QC88sorZGVlkZubC8DKlSt57rnnuPfee8P1LFy4kGnTprFz504AOnTowLBhw7jtttuYOXMmiqKQn5/PjTfeGB7Zevvtt+sSji5dMJlMfPfdd0ybNo2xY8delN/olNZt+c34iWz45AMc5WVomgoamKNj6HT1IC7NG37GdScZDfylXTrPHThGkctHQK9h6hhPqLgGfY0HoytAiWoiLrEV4/r/js/XfMzgz4tpuXULDocDt9vN+N7pzPpdKlTvAySIToYekyB3BC3RQAtxrHQhRrWMNvEh7B6FKl88S8uGkO1tSz8Z2hkMxIYkQs4A+ngzMVdnYsyIOXdBPE969eqFJEls376dmpoaAAwxoPfGEhPIRqkx4dB8GEw6WnVJpMfw7POWFAmCIAjnXpMTo4KCAgYPHlwvKYK6xOjZZ59l69atdO3atcHrLRYLs2bN4oEHHsDv95OZmcn111/Pww8/HC6jqirTpk1j//796PV62rZtyzPPPMMdd9wRLuNwONi1K3K+xttvv01+fj6DBg0KL/D40ksv/XiTej3PPPMMxcXFaJpGq1atyM/PP+3CkT+njA6dSW2XQ8muItz2KvRmM+ntO5zR47OTtbaaeLlDK7Y4vez3+tG1hs79cqiu8HL4aCUcPEBno5/039+H3OnffLxkCUVFRURHR3P99dfTNiMZDn1bt/q1OQ5a9QZTXVIjIZGefiPJycOoqfmOUMgNcjx7HG1JbgVWo45OSTFYK7xoARU5xogpOxbpF5I86HQ6evfuTZcuXTh8+DCKohATE0NmZib2Ei/2MjeSJJGUGUNcyrmfhyYIgiCcX5ImVp9rstraWmw2W/iV7XNFURSWLFnC8OHDL8oRrJ+TiE3DRFwaJ2LTOBGbxonYNOzXEpfm/P7+ZfwzXRAEQRAE4QIQiZEgCIIgCMJxIjESBEEQBEE4TiRGgiAIgiAIxzV7SxDh/PEHVVbsLmPZzmNogc20jdlMlq2aZFsCckw/vixJZmWlF3cwRLq7lquPHUZdvox3inayzV6NKTqaa0aM4L777qNjx46NN+SphuIvYO8y8DshIRvaXwPZfUGuW9PJ4/Gwe/du9uzZg9/vJz42jmxTKknVFvCpKHqZCuBIbQBJkkltG0vrrknEpVjxh/ysPrqab45+Q4WnghbmFvTL6MdVLa/CahBvagmCIAgXrzMaMVq7di06nS68J9rJ5syZw5w5cyKOVVVVMWzYMFq2bInJZCIzM5P8/PyI1ShXrVpFnz59aNGiBRaLhdzcXKZPn37a/lRXVzN+/HhiY2OJi4tj8uTJuFyu8Hmfz8fEiRPp0qULer2e66677kxu+7zyh+Dpz3bx7OfbMXrf5NKYN4iRvqO85ghrSkr4vz0e3nS5OYBElSaxwRrPH75Zw62ffUapvZobE5O4Ji6eRR99xGWXXcYnn3zScEPV++Hje+Cb56FsGzhLYM+X8PnDsPwZCAWx2+18/PHHrFy5krKyMmprHBRvKWLp2q9Zs/d7XMecOLdXYfqhkhYlLpwVHnasKuGrN3dQvPUof1/3d176/iW+L/ueck85Wyq28NKml3hq3VM4/I4LG1hBEARBaIYzGjEqKChgypQpFBQUUFJSEl5Icfr06REbvjqdTmbPns0DDzyALMuMGjWKv/71ryQlJbFnzx7uueceqqureeeddwCIiooiPz+frl27EhUVxapVq7jjjjuIiori9ttvb7Q/48eP59ixYxQWFqIoCpMmTeL2228P1xsKhbBYLNx7773hfdwuNqvLJLa6quiTvoUuCd8TUKMJaFb8msQH6kgqpURSpDIkvQ6lSk/Fxg1ULl5I2i138fvUBP63ogLl8GEe6n0lf6ys5MYbb2T//v2kpKT82IiqwtdPQWUxxGeD/JNvv88BRR+jJV7C8r16KisriYuLQ6fToZS6MakWFH2IfaFSZK+JLCkNg1GihaqhGmWq4k04q/18+eFmfmhfRGKLRMz6H/d684f8bK7YzH92/If8y/IvXGAFQRAEoRmaPWLkcrmYP38+d911FyNGjIgYGYqPjycvL49Vq1axatUq8vLyiI+PD5+766676NGjB61atWLQoEHcfffdfPPNN+HrL7vsMsaNG0enTp3Izs5mwoQJDB06NKLMyYqKivj888+ZPXs2vXr1om/fvrz88su8++67lJSUAHUJ12uvvcZtt91Wb/+0i4HTp7CtWiLaBG1j1wMSilb3yOmwLoMqXQtswWokVQadgmQMceTLz7HldCBx+HWsymqHBxVDWhpSyTGm33ILmqbx+uuvRzZUsgnKd0BMWmRSBGC2gSRz7PvPKS0tJSYmBp1OhxoIoXqDoJcx6oygwlFKkQwaqiyjShJxHgVZA3OcjMcZIMPeISIpAjDpTNiMNtaUrKHCU3EeoykIgiAIZ67ZI0YLFiwgNzeXnJwcJkyYwP3338+0adOQJImJEycycOBAevbsCcD69evJyspqsJ6SkhI+/PBDrr766kbb2rRpE2vWrOGvf/1r+NicOXOYNGkSJ9alXLt2LXFxcfTo0SNcZvDgwciyzLp16xg9enRzbzHM7/dH7NN24rGfoigoinLG9Z5sb5kTT1Ai2+rFqqvEH7KG769cikdFxkAITZOQJBXJoOHYW0zb//k91oCPClsLSiVobdCjhUKYy8rp378/q1atiuinVLYDOegHvaVu9OhkJhsVNU6Ckg9ddDSqqqL6gmiqhqST0NDQa3q8kh8fAayYCUqgVzX0wRB2zUuIIPGuVMrUsnrVxxhiOOo+yu7q3cQZ4poUmxP9P5fx/jUQcWmciE3jRGwaJ2LTsF9LXJrT/2YnRgUFBUyYMAGAYcOG4XA4WLFiBf3792fu3LnMmDEjPPfohhtuID8/P1weYNy4cXz88cd4vV6uvfZaZs+eXa+NjIwMKioqCAaDPPHEExGP52w2Gzk5OeGvS0tLSU5OjrwpvZ6EhARKS0ube3sRnn76aZ588sl6x5cuXYrVeu4mER9xgyTpqLLXoCQHCWngDwUAUA1B0IMGqJqKTgJN05BkmVBQIUTd17U1NZQHghjcbo7u3ElJSQlms5klS5aE28mo/oH2LhfuQBlIUr1+6EMevIoON24CQRVJkjAoMuaQDlUL1vVHVdE0jYBfQYeMTgOQqKqqpgYPqqri8XkoLy+vV7+qqbg1N+vXradC37xRo8LCwmaV/28h4tI4EZvGidg0TsSmYb/0uHg8niaXbVZitGvXLtavX8/ChQvrLtbrGTt2LAUFBfTv35/y8nIKCwvD83heeOEFZs2aFVHH9OnTefzxxykuLmbatGlMnTqVV199NaLMN998g8vl4ttvv+Xhhx+mXbt2jBs3DoDRo0ef1ShQc5zo3wm1tbVkZmYyZMiQc7olSK3HxyevLsevb4mXLBJM+yFYtyddhmRHr4VQJANWnQKaDIpMfMculH+7GuvYibQrPUhOrA1jQCGkBDH2uYrtL0zn+eefZ/jwn2w4W94a3SdriTJaw3ubRag5QOu0TDa7EtHr9ZjNZrSgSvCoGyRAJ+HRXEQHo7CZopGQMARVAnqZmBaxmENBvL4juJMr6yWrAFW+KjJ0GUz4zQRspvp77jVEURQKCwvJy8v7RS9Hf66JuDROxKZxIjaNE7Fp2K8lLj990et0mpUYFRQUEAwGw5OtoW60wmQyMWPGjIgkAiAmJqbesdTUVFJTU8nNzSUhIYF+/frx2GOPkZaWFi7TunVrALp06UJZWRlPPPFEODE6WWpqar3RiWAwSHV19VnPJzKZTJhMpnrHDQbDOf2AxFrhshYaG5xQVNOLq5IPYtbV4ldjaRk6Rqp0jCP6TIxSBfqgEU3RkTFkOFue/Qtlr7/GpNy2WEIaSlk5rlatuOcf/yA+Pp5JkyZF9rNlF8i8AvYtB70JDMfnAWkaeCpBNpB8xXVk7VXZs2dP3X0aDahRBoK1fvxaEJ1OJiuUSsivYjLISEg4rEY0JDz2EDEJZkoSiokJWokx/ph8uRQXnqCHa1pfQ2J0YrNjdK5j/msh4tI4EZvGidg0TsSmYb/0uDSn701OjILBIG+99RbPP/88Q4YMiTh33XXXMW/ePO68804AJk6c2KQ61ePzXH46j6ehMqc637t3b2pqati4cSPdu3cHYNmyZaiqSq9evZrUj4tBzySNpFYpfLVTRlLLuazFN5h0JRj1Om40fMKH8m85GMogGDRCnIbaqx+ZE+/g8Jx/8fSXRlYlJuEzm/h6+ddERUWxZMmS+qNakgQD/gSKF0q+BzVUt26RGqwbQepxC1L7oVyd4SEQCHD06FFUVUXSSQT1fvRBmQ76THItLfGFFIKKyjFZ5ohbQXMHiU4wMeC3vfDbd7PyyEqqfdXoJB0hLYRRZ6R/Zn/GdWg4wRUEQRCEi0GTE6PFixdjt9uZPHkyNlvkY5AxY8ZQUFAQTowasmTJEsrKyrjiiiuIjo5m+/btPPTQQ/Tp04fs7GwAXnnlFbKyssjNzQVg5cqVPPfcc9x7773hehYuXMi0adPYuXMnAB06dGDYsGHcdtttzJw5E0VRyM/P58Ybb4wY2dqxYweBQIDq6mqcTiebN28GoFu3bk0NwXmlk2HKgLYM6dSSlbtbcsTVi3TjFrLjHKTYEhgYl8OasgSWHy7DrSq0DPoY1OsyDDH38p/vv+cHezWWFi348x13MHnyZFq0aNFwQ1GJcO0LcHA17F8FARfEZcEleZBUN3crKiqKkSNHcvDgQQ4cOIDf78cWa6OVNZXoCh2aL4jVrKdKA8nhJ0uWScqKoVWnFpijDeRn5zMwayBrjq6h0ldJvCme3i170yWxC7rjC0gKgiAIwsWoyYlRQUEBgwcPrpcUQV1i9Oyzz7J161a6du3a4PUWi4VZs2bxwAMP4Pf7yczM5Prrr+fhhx8Ol1FVlWnTprF//370ej1t27blmWee4Y477giXcTgc7Nq1K6Lut99+m/z8fAYNGoQsy4wZM4aXXnoposzw4cM5ePBg+OvLLrsMIPz218VAkiS6ZNjokmED2gHXRJy/IQlu6Ny53nWNv9fXCL0J2g6s+9NYkePxb9u2baNlWgDtGzguSzKdEzvTObF+XwVBEAThYtbkxGjRokWNnuvZs+dpE4wBAwawZs2aU5aZMmUKU6ZMOWWZiRMn1ntUl5CQEF7MsTEHDhw45XlBEARBEASxiawgCIIgCMJxIjESBEEQBEE4TiRGgiAIgiAIx53RJrLCzyfk8OPZWkLFtj18a3dRbtSIbtOSdu2SsXgrUJQSAvoDfFZUw9LFG3E7gmRmtOP/bruVQd0u4ciOH6gpO4as05HWLoeUtu2Qm/immLvGz+Gd1XhrFYwWHent44lLaeYK4J7qunWUao+C3gxZV0JK5wZX4hYEQRCEC+2MEqO1a9fSt29fhg0bxqefflrv/ImNZX86Sbqqqorx48ezdetWqqqqSE5OZtSoUTz11FPh9XY+/PBDXnvtNTZv3ozf76dTp0488cQTDB069JT9qa6uZsqUKSxatCj8VtqLL75IdHQ0AD6fjzvvvJONGzdSVFTEyJEj+eijj87k1n82mqbh2VBG7VfFrK1y8B8JqiQDGiq+8iOw4RBt44/SPnszrzy3heoNWzCkpmBISmb/t6tY/tarXN37Ksb36IhOlgGNH5YtJbXNJfT7/c1YbXGnbHvXt6VsW3kUvydYtwq2Btu/KaFNt0QuG9IKnb4Jg4+7Poc1L4G7oq4CTYPv34LsPjDgkYZX4xYEQRCEC+iMHqUVFBQwZcoUVq5cGd7BHuq2+3A6neGvnU4n06dPr2tIlhk1ahSffPIJxcXFzJkzhy+//DJi7aOVK1eSl5fHkiVL2LhxIwMGDODaa69l06ZNp+zP+PHj2b59O4WFhSxevJiVK1dy++23h8+HQiEsFgv33nsvgwcPPpNb/tl5t1VR+9VetpdXMEsK4ZA00ggRI/uJkhWiDU6Kvcm8+Pc91GwrpuNjD9D39X/Q+59/pNe8V0m8cTwr1qzms+37iU9NIz61JZboGI7u2s7Kd+aghkKNtr1/SyWbvzyEGlKxJZqJS7JgSzKj00sUry/jhxVHT38DR76DFc+At6Zu3aSEtnV/jNGwuxBW/KMuURIEQRCEn1GzR4xcLhfz58/nu+++o7S0lDlz5vCnP/0JgPj4ePLy8uh8fK2dmTNnhhOf+Ph47rrrrnA9rVq14u677+Yf//hH+NgLL7wQ0dZTTz3Fxx9/zKJFi8LrDp2sqKiIzz//nA0bNtCjRw8AXn75ZYYPH85zzz1Hy5YtiYqK4rXXXgNg9erV1NTUNPe2f1ZaSMWzqYyQ08lXWhCXZCADjSAqPimITtKwWJyUVjio3bSGtnfdTmqfHoCGqkpEmTVyJozAf/AwX33/Pb/t0wub1YDBbCY6oQVle3dTsnsnGbmd6rWthlR2rStFUzWiEszh45IkYY4yoIY09n5fTm6vVMzRp1hy/YcF4K+tS4ZOPDaTJDDHgqbC/hVQtQcSLznH0RMEQRCEpmt2YrRgwQJyc3PJyclhwoQJ3H///UybNg1Jkpg4cSIDBw6kZ8+eAKxfv56srKwG6ykpKeHDDz/k6qsbX55QVVWcTicJCQnhY3PmzGHSpEnhdZPWrl1LXFxcOCkCGDx4MLIss27durPacNbv90dsR3JiEzpFUVAU5YzrPdmJuhqrM1jmQan04HVX84PRSgwaEhoBKYSGhkHnB1mlqng7ksFIbLffoFH3xEvSNLQQmHVe4oaO4PCaFew6cowel2QCoDOaCAYVju4qIqVt/eUaa8o8OCo8mKINqA2M6Bij9DirfJTss5PZIb7hG/Q50B3eCOa4ulGhk+sxxoCnEvXgOjRbdrNi899KxKVxIjaNE7FpnIhNw34tcWlO/5udGBUUFDBhwgQAhg0bhsPhYMWKFfTv35+5c+cyY8YMRowYAcANN9xAfn5+uDzAuHHj+Pjjj/F6vVx77bXMnj270baee+45XC4XN9xwQ/iYzWYjJycn/HVpaWm9ndz1ej0JCQmUlpY29/YiPP300zz55JP1ji9duhSrtZmTjpugsLCwweMWl47WtRY8AYWQQUPWNFQ0VFlFA5A0NCTUoB/JYEbSGYEAP00/ZEAXWzeHp8bhoLzsx81xFZebHdu3U0r9EZ9ArUytw4zs0ZAamKOtaRDySqz/dj0/7G/4cZxRqeXKmipCkoGgM9hgGavfw97NGzl0pOF5Ro3F5r+diEvjRGwaJ2LTOBGbhv3S4+LxeJpctlmJ0a5du1i/fj0LFy6su1ivZ+zYsRQUFNC/f3/Ky8spLCzkgw8+AOoejc2aNSuijunTp/P4449TXFzMtGnTmDp1Kq+++mq9tt555x2efPJJPv7444jEZ/To0Wc1CtQcJ/p3Qm1tLZmZmQwZMqT+Bq1nQVEUCgsLycvLa3AHYNWtYJ+7E5OrlmRN5ZDOgA0Vg6RDIoimGpA0iErJoMpTi69kD7aMVkjUJUySDCFNh2vjd+j0etq3yiQ5qW5rF1UN4dRCXNGnHzlX9avXtt+j8MWxHQSDKtZYY73zAV8QxRxiwNAcElpGNXyDahDd+4ug5jDYkuufD/qRXF669BtB59aRI4ini81/KxGXxonYNE7EpnEiNg37tcTlxBOfpmhWYlRQUEAwGIzYnFXTNEwmEzNmzIhIIgBiYmLqHUtNTSU1NZXc3FwSEhLo168fjz32GGlpaeEy7777LrfeeivvvffeaSdLp6amUl5eHnEsGAxSXV1Nampqc26vHpPJhMlkqnfcYDCclw9Io/XGGbDktiBU6eBqeylv6Qx4kLBoOvSajBKS0CkG4rI7UxKXxOEFc0ns+n/ozUaQJZCgZL8f+8fv0bF9BzISbciShKZpuKuriYqLp+3lPRps22AzkN01kaI1x9CitIi3z1RVw+tUSGtjIznLhtToK/cG6HQdrJoOQS8Yf5JAaSq4SiE+G32bfqBvOK7nK+a/dCIujROxaZyITeNEbBr2S49Lc/re5MQoGAzy1ltv8fzzzzNkyJCIc9dddx3z5s0LT7Q+eS+zxqiqChAxj2fevHnccsstvPvuu+FHcqfSu3dvampq2LhxI927dwdg2bJlqKpKr169mtSPX4Lo3i1RylwM+MHPLsXHOp1MDTIm1YJXDlDjSSYhqoarpt7Iqqdm8e2d00gZPhhDago1O/ZT88UXxFqtTOjdDcXtJKCq+D0eTFHR9Bp9A5aYxkfAOvVLp7rETflBJzq9hMGkI6SoBPwhbEkWug/LPkVSdKKS66FkE+xbAZJc92q+qoDfCdEp0P+PdZvbCoIgCMLPqMmJ0eLFi7Hb7UyePBmbzRZxbsyYMRQUFES8en+yJUuWUFZWxhVXXEF0dDTbt2/noYceok+fPmRnZwN1j89uvvlmXnzxRXr16hWeI2SxWMJtLly4kGnTprFz504AOnTowLBhw7jtttuYOXMmiqKQn5/PjTfeGDGytWPHDgKBANXV1TidTjZv3gxAt27dmhqCn5UuykDC6PaYWtu455tddK50sVwLUYpCkklH2xQDmSaVljaFri/8Dx+9v5sj/5mPpgTRx8bR67e/55EbrkU+toea0hJkg4H2V/ah/ZV9Sc5uc8q2zVEGfjMuh73fl7N/cwVet4IpykD7K1Npd3kK0fFNSGgMZsj7C+xcXPfHcRQMVsgdCZ1GQ4u25yhSgiAIgnDmmpwYFRQUMHjw4HpJEdQlRs8++yxbt26la9euDV5vsViYNWsWDzzwAH6/n8zMTK6//noefvjhcJl///vfBINB7rnnHu65557w8Ztvvjm8aKTD4WDXrl0Rdb/99tvk5+czaNCg8AKPL730UkSZ4cOHc/DgwfDXJ17/135Ba+fIVgMxV2UQ3Tud8UqIcUGFoCSjNxrQ62RCoRCqqjJWJzN9cgBPUMLt9pJoi8Wgr5s5rWkaIUVB1umQdU1b8RrAZNHTsU9LOlyVRlBR0etlJLmZq1UbzNDld9B5DAR9IBtAJxZfFwRBEC4eTf6ttGjRokbP9ezZ87QJxoABA1izZs0pyyxfvvy0/Zg4cWK9R3UJCQm88847p7zuwIEDp637l0KSJCSjHtmoj/gG6nQ6dMeTHVm2EKuHWLO53rV6Y/1J1M1p22BsekLVSCVgsJxdHYIgCIJwHohNZAVBEARBEI4TiZEgCIIgCMJxIjESBEEQBEE4Tsx8vYgo/hCVhzyElBDRCWbikutW19ZUla071rJnfzGywUS3jleSndkaRVF48/3FHDxSQmZGBjf/bgSGQAD/rp1oShBDRjq7oyT2le3H7A1xeUw28ZkZyCYdKD4o/QEUN8SmQ4t2P+5hJgiCIAj/pc4oMVq7di19+/Zl2LBhfPrpp/XOn3iD7KeTpKuqqhg/fjxbt26lqqqK5ORkRo0axVNPPRVeRfrYsWM8+OCDfPfdd+zZs4d777233sayDfH5fDz44IO8++67+P1+hg4dyquvvkpKSkq4zL333svq1avZtm0bHTp0CL+ufzHQVA33UT1LZ+3A61TQVA29UUdK61jMmcdYVjgfv98EshEkic2rt7Bj314+W7Icd01VuJ5pd8bxaOfOjEqwsS8lnrlDe7M7PhOfbECHSlLlt4zcVst4LZlY11wk52FQQ3UTodO6wVVTxCaugiAIwn+1M3qUVlBQwJQpU1i5ciUlJSXh49OnT8fpdIa/djqdTJ8+va4hWWbUqFF88sknFBcXM2fOHL788suItY/8fj9JSUk8+uijXHrppU3uzwMPPMCiRYt47733WLFiBSUlJVx//fX1yt1yyy2MHTv2TG75vNqx6hjOfUZ8LoUom5HYFmb0Bpk93//Asrfn41ei6xY/lEOAwtZNW3j/nQ/IyEhh5B9f5X//9Q0P/XYSHXQ6/m/tKuYEgzx//Qi2JrTBpAVIVewkqF6q5BjejE5jtrIT59HWEJ0K8dlgiIIDq2HJQ1C9/+cOhyAIgiD8bJo9YuRyuZg/fz7fffcdpaWlzJkzhz/96U8AxMfHk5eXR+fOnQGYOXNmOPGJj4/nrrvuCtfTqlUr7r77bv7xj3+Ej2VnZ/Piiy8C8PrrrzepPw6Hg4KCAt555x0GDhwIwBtvvEGHDh349ttvufLKKwHC6xpVVFSwdevW5t72eeOy+9m9oRxJhqh4E/Lxx1lGiw6nax3BqCgkSY9GAICQqvLl8m/olNue6347Ele8hqG2kmtqjjG425U8/MNGXtq0kWzDvaQHa5CP72avk4Ik46YSM5/Gt2awxUKnkB29vhbMsWCMhuq9sHU+9H/4VF0WBEEQhF+tZidGCxYsIDc3l5ycHCZMmMD999/PtGnTkCSJiRMnMnDgQHr27AnA+vXrycrKarCekpISPvzwQ66++uoGzzdm+fLlDBgwgP3795Odnc3GjRtRFCViT7Xc3FyysrJYu3ZtODE6E36/P2K7khOb0CmKgqIoZ1zvTx0qqsTvUZCNGpqqosp1g3h+TxW+UA2qMQkpqKIZADT27T+Iy+2hd+8r0IUUzJ5yUqrsGBQfrrhkRuZ25S+rl6IVbUFu37quEUlCU1UkCeI1F2V6G2uTfLSpTCfKUPNjZ0w22PMVoR63123ZcRE4EedzFe9fCxGXxonYNE7EpnEiNg37tcSlOf1vdmJUUFDAhAkTABg2bBgOh4MVK1bQv39/5s6dy4wZM8J7nN1www3k5+eHywOMGzeOjz/+GK/Xy7XXXsvs2bOb1b7VaiUnJye8IVxpaSlGo5G4uLiIcikpKeEtRc7U008/zZNPPlnv+NKlS7FarWdV9wmugwbcbgN6K1RUVIaPB3zHUNEACbS6CdgaUOtyA5CYlACqiqYGCTpqCQWDBBSFeFs8AGpVFZBdV9nxxTc1TUOnaaBJOAwqToeCO/jjBrz6kBed6mf9Zx/jMyack/s7VwoLC3/uLlyURFwaJ2LTOBGbxonYNOyXHhePx9Pkss1KjHbt2sX69etZuHBh3cV6PWPHjqWgoID+/ftTXl5OYWEhH3zwAQAvvPACs2bNiqhj+vTpPP744xQXFzNt2jSmTp3Kq6++2uQ+9OzZM7xP2vl2on8n1NbWkpmZyZAhQ8ITxs/Wnu/K2Vh5EJ/qIjk5Een4iFHAq8fhkOqSGgkkWUZCwxYTDUBFWRUt01KQZD16WyI6vR6jwUCVvW4ytpyUDEiAFn7bTJIkQsggacQpMrFxeqzxyT92xl0B+ngGXjPqohoxKiwsJC8v7xe9s/O5JuLSOBGbxonYNE7EpmG/lriceOLTFM1KjAoKCggGgxGbs2qahslkYsaMGRFJBEBMTEy9Y6mpqaSmppKbm0tCQgL9+vXjscceIy0trTldiagvEAhQU1MTMWpUVlZGamrqGdV5gslkwmSqv0GqwWA4Zx+QrI6JbF9ZgqdKQpLl8BwjkyUBsz4eRQmgmk60JdGmdStiYqJZvWYdY/7nenzWVI5Ep3PpllUYPS4+2bWV+NQU5NwuqCEHsgZoGpJOB5JMtWQhXnXSp8yEOb4Y+XgihhoCfy3kjkOOvrhGi+DcxvzXRMSlcSI2jROxaZyITcN+6XFpTt+b/FZaMBjkrbfe4vnnn2fz5s3hP1u2bKFly5bMmzcvXLah/cwaoqoqQMQ8nubq3r07BoOBr776Knxs165dHDp0iN69e59xvRdKlM1ETu9UNBVc1T6CgRBqSMXvCRITfSUGtxtNDQJ60CRkYOjA/uzcvZd573/EjqNejupMfBCTyJ82rWV7dQUPdrucdL+dY/o4nDojIVmHTzZQKkeDpPHb6v1k+Q+gl8pADYLXXvc2WkIb6Dbu5w6JIAiCIPxsmjxitHjxYux2O5MnT8Zms0WcGzNmDAUFBRGv3p9syZIllJWVccUVVxAdHc327dt56KGH6NOnD9nZ2eFyJ9YXcrlcVFRUsHnzZoxGIx07dgTqJnTfdNNNfPXVV6Snp2Oz2Zg8eTJTp04lISGB2NhYpkyZQu/evSMmXu/ZsweXy0VpaSlerzfcTseOHTGexaaq50LOlSls27GVaMWMu8aPqoLBpCO3Vxd6ZLXk88/+g9etA50JJCOdunbE1MLGp4u/Zt8LP47IpSQkM6P/QIYaDPR9/1PeGXol2xJbUWGwotNUWobsjPL4+J+YS4nO+g84qusSI4MVLhkEve4CW8bPGAlBEARB+Hk1OTEqKChg8ODB9ZIiqEuMnn32WbZu3UrXrl0bvN5isTBr1iweeOAB/H4/mZmZXH/99Tz8cOSr4Zdddln4/zdu3Mg777xDq1atOHDgAFA3gWrXrl0RM8ynT5+OLMuMGTMmYoHHn7r11ltZsWJFvXZOvN32c5IkCWtakLwhHXBWBAgFVaLjzUTHm4BL6NqjF7v3bqF4/y70BiOXduhFanIaqqry4WfL2H/kKK0yM/ndsAFISgD/7j2kBhX6ZGRwyAz7yw9g8oboGnM5MS1TkAwyhPKgfAcoXohNg7iG3x4UBEEQhP8mTU6MFi1a1Oi5nj17oh1/86kxAwYMYM2aNadt53T19O/fv14Zs9nMK6+8wiuvvNLodcuXLz9t2z83nV4mKav+pGdJkmjfrhvt23WLLK/T8T8j806qxIylS+fwl22ANjFJDTUGaQ0nsYIgCILw30psIisIgiAIgnCcSIwEQRAEQRCOE4mRIAiCIAjCcSIx+oXQFIVQTQ1qIND8a1UN1RtEDYQijoeCKj63QiionqtunjOhkB9FqUHTgg2e1zSNiooKKisrUUMhfC4Xis9HUNWoUYJ4Q2d2Tx7FQ22g9rRz3QB8SgiHRyHY1LZUtW5phID7jPp2oamqitfrJXAGn7lz076Gw6PgCTT8GRAEQTgfmr0liHBhBe12aj9dgnPZV6guN5LJRPRv+mEbMQLDTxbabIgWVPFur8T7QyVBRwBJAmNWDLSxse+Im0PbqlACKkazjuwuiVxyRQrW2J936QKv9xClpYuotn+DqgbQydHoDakoSh8MhkQ0TePf//43L7zwQngF9KyUZAZccRm2Yb+luHVHFFsCVouFvnHRXJcST/so82nb3VKxhc/2f8a2ym2omkrL6JbktcpjYNZADHLkwmB7yp18tKmEb/dVoagqLaJMDOuUyoiuaUSZGviRCgag6BPY8THUHgVJB5k9ocvvoOVl9cv/zILBIEVFRezYsYPa2lokSSIjI4MuXbqQnp5+3tsPBFU+23aMz34opbTWhyxB91bx/PbSdLpk1H8rVhAE4Vw6oxGjtWvXotPpwnuinWzOnDnMmTMn4lhVVRXDhg2jZcuWmEwmMjMzyc/Pr7dM9/Lly7n88ssxmUy0a9euXj0Nqa6uZvz48cTGxhIXF8fkyZNxuVwRdY4aNYq0tDSioqLo1q0bb7/9drPv+0ILVlZS+sST2OfOJWSvQdLr0Tweaj74kGP/73H8+/c3eq0WUnEsPUjtV4dQKrxIsoSmgXt7NWXzdlG28ggBXxCdTsLvVvhhxRGWv7MTd82ZL7Z5tlyuXRTtfIRjpR8SCvmRMBBQqjAYVrJn758JBKq54447uPPOO+nUqSOP33MHdw4fTAtbDG8u/oK5nxVS4ldwlx3D5XLxUbmdh3Yd5nvHqUdolh1axtPrnmbN0TVomoZe0rO3Zi+vbX6NVze/SlD9ccTi+0N2pn34A5/+cAwlpGKQZY7VePnXyr38edEOXP6TRjeCAVj2Z1j5D6jaA7IB0KD4c/j0Qdj95XmI5JkLhUIsW7aMlStXUlVVFV4Zfffu3Xz66acUFxef1/YDQZV/fLGTl5ftYX+lC/3xz+1XReU8+vEPLN9VfvpKBEEQzsIZJUYFBQVMmTKFlStXUlJSEj4+ffp0nE5n+Gun08n06dPrGpJlRo0axSeffEJxcTFz5szhyy+/jFgUcv/+/YwYMYIBAwawefNm7r//fm699Va++OKLU/Zn/PjxbN++ncLCQhYvXszKlSu5/fbbw+fXrFlD165d+eCDD9i6dSuTJk3ipptuYvHixWdy+xeM/e138O3ciSE9HUNKCrrYWPRJSRgzMwkcPULVrNmNPvLx7azGt6saOcqAPt6MbNGji9LjVEKoikq2LBEbbcBk1RMVZ8KWaKa6xM3Wr49c4Luso2kqBw68hs9XitWSjcmYiMEQi8mUiqbF43Ju5513/h+zZs3i9ddf528PPkC2SaZ/z+5c/cfHSL/nQao//Qjdlu8wBXxI5SW0MuiwK0GmHyzDrzb8uKvSW8mc7XMIqkEyYzKJN8cTa4olPTqdOFMcyw8vZ/XR1QD4gyFmLNuD3aPQuoWVxGgTNouBlnEWUmPNbDhQzcebj0Y2sGsJ7C4Ea2LdWlGWOLC2gIS2dWtIrfoneKrPb3Cbobi4mN27d2O1WomLi8NisWC1WklISCAYDLJq1Src7vP3KPDLojKW76ogMcpIRrwVm8VAQpSR7BZWfIEQM1fspcbz8zzaEwThv0OzEyOXy8X8+fO56667GDFiRMSITnx8PHl5eaxatYpVq1aRl5dHfHx8+Nxdd91Fjx49aNWqFYMGDeLuu+/mm2++CV8/c+ZMWrduzfPPP0+HDh3Iz8/nd7/7XTi5akhRURGff/45s2fPplevXvTt25eXX36Zd999N5y0/elPf+Ivf/kLV111FW3btuW+++5j2LBhfPjhh829/QsmWFWFe+1adDYb0kl7vEg6HfoWifiKivDv3t3g9d5tVaBpyD95tKP4QwR8IYJ6CYOqEeP7cc6RrJMxRxk4usuO23HhR42czm243bsxm5KRpJM/lnp0+mjeeGMh3bpdys0338zu9XXJimSJYnNCGilDRxCVkcXRpZ+hNxgJKQo+l5NUk4FDXj/raxr+Zb766GrsPjvJ1mSk4/vUnRBtjEbVVL46VLfdzHcH7Byu9pAaa65X1mzQYTbIfLGtlMCJOVuaBkXH1/8yRUc2LEkQ2xJc5bDv6+YH7DwpKioK73/4U5IkERsbi9vtZu/eveelbU3T+GzbMSSJeo8kJUkizWah3Oln1Z7K89K+IAgCnMEcowULFpCbm0tOTg4TJkzg/vvvZ9q0aUiSxMSJExk4cCA9e/YE6rbvyMpqeEXlkpISPvzwQ66++urwsbVr1zJ48OCIckOHDuX+++8Pfz1nzhwmTZoUHilZu3YtcXFx9OjRI1xm8ODByLLMunXrGD16dIPtOxwOOnTocMp79fv9Efu4nXjspyhKxMrbZ+tEXT+t03fkCCG3C11iIqrWwGiH1YJaWYnv8BF0rVtHnNJUDaXKA0Y54lolEEINaRhMMigqhmAIVfvxI2Awy7hrAtSUuzBaL+y8fLf7MCE1gFE2R/RZU+u+zzo5in37ahg9ehh+rxdHRTkGswWnzoBbZ8ASChHf9TLsWzfVJR1A0O8jCghpGgc9Xq6MqT/X6Gjt0brPkkaDcbboLBxwHCAQCHCw0kVI0zDoGi4bZdJR7Q5Q7nCTEmuGUACd/SAYousmXtcjIwFq9UHUZn6eGvrMnC1VVamursZoNIb3MWyI3W4/p+2e4FdCHKn2YD3pc3uCJAGaxuEq9ynbPx+x+bUQsWmciE3Dfi1xaU7/m50YFRQUMGHCBACGDRuGw+FgxYoV9O/fn7lz5zJjxozw3KMbbriB/Pz8cHmAcePG8fHHH+P1ern22muZPXt2+FxpaSkpKSkR7aWkpFBbW4vX68VisWCz2cjJyYm4Jjk5OfKm9HoSEhIoLS1t8B4WLFjAhg0b+Ne//nXKe3366ad58skn6x1funQpVqv1lNeeicLCwvD/G8vKSHW7CakqWkN7uYVCGDxu9m3ehNfljDynwSU1MehCoLh/fNSmBiRCIRnVBzokal1+yr2OH8+HQFMk1ny7BuOOC/ummk63A6PJhdNZSkMDmVXVFRiNEtu27eSLpUupcThQlSABRSWUHcCvafiqq5CMJvx+P1owiMvtxltejlPWs3PLUZYEPfXq3efbhyvgotzb8NyVWrWWKDmKzz77jKIKCZdTpkxxctKAEQBuBTQkVn69jCgDoKn0cTjRhXz4XQ28WaVpRAWcHNi1l332Jc2MWJ2ffmbOlqZp1NTUEAqFIubo/ZTf76e4uJiamppz1u4JIQ1qa2QCKigNNK9p4PJJ7NlVxJLaHaet71zG5tdGxKZxIjYN+6XHxeOp//d/Y5qVGO3atYv169ezcOHCuov1esaOHUtBQQH9+/envLycwsJCPvjgAwBeeOEFZs2aFVHH9OnTefzxxykuLmbatGlMnTq13r5mpzJ69OhGR4Ga4uuvv2bSpEnMmjWLTp06nbLsif6dUFtbS2ZmJkOGDCE2NvaM+3AyRVEoLCwkLy8Pw/HHZlowSOnWHwjs34/hpMQPIFhegdwqmw633IIcHV3vvCvmKL7vK5BbmMKPfTRVo+KgE4Iqsk5Giosm2aQLX+Os8hGbbibvfzog6y7siJGi9Gb79o2omoLRmBg+rqkaFZUVxMTA0KFdePPNzfSc24v9ioedq1eQFh9L24CbbSGZ6o3raH3DBAx6PZokkZiahkdvIhWNW3I7kWmun2Cmlaexd8NeYkwxWPSWiHOqpuJz+fhtu98yvMNwutg9bJ6/Fb0sEWeNfLypaRreai9927Xgf0b8OBIprypG/mE+WnwinPyI0O+CQCK5QyeSm9atmfGq/5k5F9asWcOWLVuIj4+v97gwEAjg8/nIy8s7b2+nHbLu5eMtx0hsYUE+qX2XP4jmCzFhWCc6pzf+83e+YvNrIGLTOBGbhv1a4nLyi16n0qzEqKCggGAwSMufvCZ+Yj7CjBkzIpIIgJiYmHrHUlNTSU1NJTc3l4SEBPr168djjz1GWloaqamplJWVRZQvKysjNjYWiyXyl9ZP6ysvj/zXfjAYpLq6mtTU1IjjK1as4Nprr2X69OncdNNNp71fk8lUb64FgMFgOC8fkIh6DQbir7+eipdeIlRegT4xEUmnQ1NVQnY7BALEjRyJ6fgcrpPFdEtB2VOLag8g20xIehlN1oiONhKw+6iVJLwGGVmSUFUNb20AWZboeFU6JnP9ez7fDIZkUlJHcPToPIJKDQZDHJIkE5IUJKkGWY5jypQpvPfeZEaNGsULzzxNVFw8zopyMmrW8Ol7HyNHRZMyMA81qGCOjcVnNFMTDDE6OY42MVENtnt52uV0Te7KxtKNJFmTsOqtSJJEIBSg1FNKclQyQ9oMwWAw0CbZxsDcFBZtLUGWJGwWA5IkEQyplNb6iTEbuL57VuRno8sYOLACqfZI3ZwinbFu6MPvBE85tBmAnNmDBoegmhS3c/tZ7Ny5M/v27cPhcBAbG4ter0fTNAKBAC6Xi9atW5OVlRV+W+1cu/ayDFbvs3O0xk9arBmjXkbTNFz+IJUuhX6XJNKtVUK9pK0h5+vn9NdAxKZxIjYN+6XHpTl9b3JiFAwGeeutt3j++ecZMmRIxLnrrruOefPmhd8wmzhxYpPqPDGP4cQ8nt69e7NkSeQjhcLCQnr37t1oHb1796ampoaNGzfSvXt3AJYtW4aqqvTq1Stcbvny5YwcOZJnnnkm4o21i1n0gP6obhf2ee+iHD3+tpOmIcfEEDf2BuLGXN/otfoWFuKGt8bx5UFCdn/dL2PAYtIRzIjhsEPBU+VHkkADzFY9Xful07pbYqN1nm8Z6RNQ1QAV5Z/j9R0CJDRNQ9PMZGXeTsuW17J06VJGjRpF30F5tG/XFrejhqMVVdji42j3yF9wJqWhN5pQYmOJ1jR+mxTHPVkpjbapl/U8cPkDvLzpZbZWbKXSW4kkScjIZMZkcne3u0mP/nF05K7+bVE1jeW7KjhY/ePQbEqsmTuubku3zLjIBhLbQd6fYfnfoeYQoNV9LwwWaDsIBvzpjJOi86FFixYMGTKEr7/+Ovy4TNM0DAYDbdu2ZcCAAectKQJomxTNtOG5vPjlbo7WeKmb/qVhMejon5PEA3ntm5QUCYIgnKkmJ0aLFy/GbrczefJkbLbIRdbGjBlDQUFBxKv3J1uyZAllZWVcccUVREdHs337dh566CH69OlDdnY2AHfeeSczZszgD3/4A7fccgvLli1jwYIFfPrpp+F6Fi5cyLRp08KL+3Xo0IFhw4Zx2223MXPmTBRFIT8/nxtvvDE8svX1118zcuRI7rvvPsaMGROee2Q0GklISGhqCC44SZKwXXstUX374vn2W4LV1eiio7H27IkhLe201xszY0ic0AH/PgfBah+STsaQEU1yWhSpNQGOFtsJeIOYowyk58T/7Is7yrKB7FZ3kJI8gpqa9QRDbnRyHBs2OElKGgbAZZddxp49e1i4cCErV65EU0N0apNNz44dCJotHGzZEk9MPBadTC9bNG2spx/9ijPH8eiVj7LLvottldsIqkGyYrLontodky7yerNBx4NDcrj+8gw2HKjGp4RIiTVzVdsWxJgb+RdJRg8Y+x84sArsB+pGjdK7Q0qniyopOiE9PZ2xY8dy4MAB7HY7Op2O9PR0UlJSLkhScnlWPDMndOfbfVUcsXsw6GS6ZcWRkxIjkiJBEM4/rYlGjhypDR8+vMFz69at0wBty5YtjV6/bNkyrXfv3prNZtPMZrN2ySWXaH/84x81u90eUe7rr7/WunXrphmNRq1NmzbaG2+8EXH+jTfe0E7udlVVlTZu3DgtOjpai42N1SZNmqQ5nc7w+ZtvvlmjbmAk4s/VV1/d1NvXNE3THA6HBmgOh6NZ151OIBDQPvroIy0QCJzTen8NRGwaJuLSOBGbxonYNE7EpmG/lrg05/d3k0eMFi1a1Oi5nj17nnZvqQEDBrBmzZrTttO/f382bdrU6PmJEyfWe1SXkJDAO++80+g1Da3ELQiCIAiCcDKxiawgCIIgCMJxIjESBEEQBEE4TiRGgiAIgiAIxzV75Wvh4hOsrMS1YiXerVvQVBVLx45EX301hp+sN3UhlZeXU1xcXLc7u6TDKiVAbQzVjhAu7zGyA/tID4JsimFb20w2ZmdQHnBz8MO3OFC4CNXr4JJ2yUy+9X8ZNvS2c9avqiOH2ff9eqpLjqA3msjo0InsSy/HZG14jaNzrdodYPmucr4/aEcJqeSkxjKoQzKtWpy79g/WHmTF4RXsqdmDUWfksuTL6JveF5vJdvqLBUEQhDNLjNauXUvfvn0ZNmxYxKv0J5yY6PzTSdJVVVWMHz+erVu3UlVVRXJyMqNGjeKpp56KWEV6+fLlTJ06le3bt5OZmcmjjz562nWRqqurmTJlCosWLUKWZcaMGcOLL75I9PEVoX0+H3feeScbN26kqKiIkSNH8tFHH53JrV90vFu3Uv78PwmWlYFeD5KEd8N3OBYtJvGeu4nu0+eC9UXTNDZv3syGDRvq1qbSJNwOP6GgihSykOBKprvORqwuB5fRzyuto9hhtOD+dgM7/98Ugk4n8Vf1IqttMts3bmHM9Q8zbtxcxo594Kz7tWPlMjZ9sZiAx4NOr0dVVQ79sJmiVcu5+n8nE596fpPIomO1PL2kiCM1XnSShCzB+gN2Fm0p4c7+bRnaKfX0lZzGFwe+4M3tb+IMODHIBkJaiPXH1vPpvk95sMeDtI1rew7uRBAE4dftjB6lFRQUMGXKFFauXBnewR7qtvtwOn/ct8vpdDJ9+vS6hmSZUaNG8cknn1BcXMycOXP48ssvI9Y+2r9/PyNGjGDAgAFs3ryZ+++/n1tvvZUvvvjilP0ZP34827dvp7CwkMWLF7Ny5cqIRRxDoRAWi4V777233ia1v2TB6mrKp08nWFmJISsLY0YGxvR0DFlZqE4nlTNeIXDw4AXrz8GDB1m3bh2aphEfH0/IbUAOmpElM4rkRIo6SrQOPJrKv9vEsSXOQpzbxd6/PIg5LoqBb7/ApX+ehuHeP3Pf/Md4+OFezJu3jeUrXkXTGthrrImO7tzO90s+AU0jLjWN2KRk4lJSiU1KovroEb55501CwfO3QaLTp/DM5zs5aveSFW8lK8FKRryV1i2s+JQQr369h6JjTV+uviHbq7bzxrY3UFSFrJgsWka3JDMmk/TodA47D/PCxhfwKE3fK0gQBOG/VbMTI5fLxfz587nrrrsYMWJExGvw8fHx5OXlsWrVKlatWkVeXh7xx7esiI+P56677qJHjx60atWKQYMGcffdd/PNN9+Er585cyatW7fm+eefp0OHDuTn5/O73/0unFw1pKioiM8//5zZs2fTq1cv+vbty8svv8y7774bTtqioqJ47bXXuO222+ptE/JL5lq5kmBpGYaWLZF+shqxJMvoW7YkZLfjXPb1BevP9u3bCQaDxMTE4PeEUPxB9AaZQAisqoRbF+CYVENJlMb2eCNxfo3qDavwlJVy6UO3Y4lLJEb2o5M0ViqX8Luxl3L11Rl8tLAIh6PxJRxOp/jb1QQDfqLiIvf/knV6YlokUn30MEeKtp+LEDRo9Z5KDld7yIi3oJN/bF+SJNJsZmp9QZZub3jD46YqPFCIW3GTbEmOuEedrKNldEsOOQ+xvnT9WbUhCILw36DZj9IWLFhAbm4uOTk5TJgwgfvvv59p06YhSRITJ05k4MCB9OzZE4D169eTlZXVYD0lJSV8+OGHXH311eFja9eurTeiM3ToUO6///7w13PmzGHSpEnhdZPWrl1LXFwcPXr0CJcZPHgwsiyzbt26s9pw1u/3h7crgR83oVMUBUU5dyMMJ+pqbp2eH35AkyQ0WULT1PoFTEbc339P7ITx56KbpxQMBjl27BhGoxFVVQl4FTQNVDQ0TcWEDgUVu+zmWEwSXr1EvFti//ZNRGWmYWudDaqGpmpESz7K1WjKQlaGDWvLtGlHOHhwPXFxVzS7X6GgQune3RgsFtQG1tqSDQbUUIiyA/tomXvqTYXP1A9HalBVDVmu25j2ZFajzIYD1c36/v/0M6NpGlvKt2DVWY9voRJ5nzp0hNQQO6t20if1wj1a/bmc6c/TfwMRm8aJ2DTs1xKX5vS/2YlRQUEBEyZMAGDYsGE4HA5WrFhB//79mTt3LjNmzGDEiBEA3HDDDeTn54fLA4wbN46PP/4Yr9fLtddey+zZs8PnSktLSUmJ3NcqJSWF2tpavF4vFosFm81GTk5OxDXJJ+0+r9frSUhICG/9caaefvppnnzyyXrHly5ditVqPau6G1JYWNis8kn7D2B1uVBO2kT3BH2tE+XYMTadtP/c+aCqKna7vW7DT5eLoFcmFJIIaqCpGkgg8eOy42gaGnW/xCVJrjuGhhIIoEgQRKayqgqnq+7R7O7duzl6tPn3oYVC4X45vf4GyyguF0U7dnBM1Z3ZzZ/GnkMybjeUq64GzzsCEHRTb5/ApigsLETTNKpcVQS0ACFnqMFyLtXFrl27WHLw/H8WLhbN/Xn6byJi0zgRm4b90uPi8TR9KkGzEqNdu3axfv16Fi5cWHexXs/YsWMpKCigf//+lJeXU1hYyAcffADACy+8wKxZsyLqmD59Oo8//jjFxcVMmzaNqVOn8uqrrza5D6NHjz6rUaDmONG/E2pra8nMzGTIkCERE8bPlqIoFBYWkpeX16wdgGv9fuyvl6BPTIx4lAZ1E46DXh8xeXlcNnz4OevrqSxZsoRDhw4RHx+Pz6VgL/Ug62QULYhf9aMD4lUrJmcQswo+AyTmXsr+pZ/gPHQIW3Y7jCYDDi2aVMlFbrSJ/6yrJCPDwtVX/46kpL5n1K+vK0s4UrQNW0pyvXMhRcEtafTJG0qrLt3OLgCN+aGU3cv2kBBvRt/A98lT5WVQ5xSGD76kyVWe/JnZvWk3K46sIDmm/j0G1SABT4BrLr2GAZkDzvp2LnZn+vP030DEpnEiNg37tcTlxBOfpmhWYlRQUEAwGAxvzgp1f7GbTCZmzJgRkUQAxMTE1DuWmppKamoqubm5JCQk0K9fPx577DHS0tJITU2lrKwsonxZWRmxsbFYLJYG+5Samkr5SSMmwWCQ6urqs55PZDKZMJnqb0JqMBjOywekufXaBgzAtfhTgiXHMKSnh5MjTdMIlZWhs9mIu4Af5i5dulBSUlI3uhdlwWDSofhCGHQSHkKkqBZaavH43Bq5doXNSTqSr/wNlrcT2fp8Ab3+Po2QOY2QpqOvaQ+fL9rJl18e4p78S2nRotcZ30fuVf0o3bMLX60DS6wtPAdHDYVwVVXSIiOT7C7d0J+nOPXvkMr7m0o4VuMlM8GKfLx9TdModwWINhsY3jX9jO7vxGdmaOuhbCjbQJWvikRL4o/3qKmUekrJiMmgb2bfX/RfbM11vn5Ofw1EbBonYtOwX3pcmtP3Jk++DgaDvPXWWzz//PNs3rw5/GfLli20bNmSefPmhcs2tJ9ZQ1S1br7FiXk8vXv35quvvoooU1hYSO/evRuto3fv3tTU1LBx48bwsWXLlqGqKr169Wrq7f0i6ZOSSLrvXnTx8SiHDqGUlKCUlBA4eBDJbCbxjjswtWl9wfrTunVrevToUfdYrcaOPjpESOdD0zzotWhwtcQTAquk5/Z9djrWeqmOjqXto8/hPlbFl7+/ly1PvUDo33+jYOJfefzxVVx3XXsGD7obWT7zH8jMTl25NG84qqpSU3oMZ1UljvIyHBVlxKWm0ffGm89bUgRgsxh4aGgOybFmDlZ5OGL3UFLj5UCVB70scftv2tA5/ezWGeqa1JX/7fi/SJLEIechSt2lHHUd5bDzMKlRqdx7+b1YDef+8a8gCMKvTZNHjBYvXozdbmfy5MnYbJF/iY8ZM4aCgoKIV+9PtmTJEsrKyrjiiiuIjo5m+/btPPTQQ/Tp04fs7GwA7rzzTmbMmMEf/vAHbrnlFpYtW8aCBQsi1kpauHAh06ZNY+fOnQB06NCBYcOGcdtttzFz5kwURSE/P58bb7wxYmRrx44dBAIBqqurcTqdbN68GYBu3bo1NQQXJWv37qT/41lcy5fj2bQZ1BDmTp2JGdAf4/G4XiiSJNGjRw/S09MpLi6msrISKU0mSmqB5ojFXquyxXuMtkox6arMIwdj2dw2nfW9e3HpR19w6L3XOfjlp5T94KRduyQe+dMUrr/+Xr78cu1Z96vr4GGktr2EfZs2UHXkMHqjkaxOXcnu1h1r7Plf/LBrRhwvjO3Gsp3lrD9QTTCk0TGtboHHS1Jizkkb17a9lpyEHFYeXklxTTEG2UCPlB70y+hHoiXxnLQhCILwq6c10ciRI7Xhw4c3eG7dunUaoG3ZsqXR65ctW6b17t1bs9lsmtls1i655BLtj3/8o2a32yPKff3111q3bt00o9GotWnTRnvjjTcizr/xxhvayd2uqqrSxo0bp0VHR2uxsbHapEmTNKfTGVGmVatWJ+b9RvxpDofDoQGaw+Fo1nWnEwgEtI8++kgLBALntN5fAxGbhom4NE7EpnEiNo0TsWnYryUuzfn93eQRo0WLFjV6rmfPnvVeET7ZgAEDWLNmzWnb6d+/P5s2Nb5mTUOP6RISEnjnnXdOWe+BAwdO27YgCIIgCP/dxCaygiAIgiAIx4nESBAEQRAE4TiRGAmCIAiCIBzX7JWvhQsrWFWFZ8MGVJcLXUIC1iuuQBfT/LeYQiGVsn0Oasq96HQSSa1iiU+1RuyrBaCFVAIHawlW+UAnYcyIQZ9kiSznqYaDq8FrB3McZPcFa8KPfQ4G+fLLL1m48CPKPR5iczrS74YbyUmw0lb7AZQqdLoo4uJ6YjIlRbavaVQfPULZvt2EQkFiEpPR1Aa2O7mAXP4g6/ZVUenyE2XS0zM7geRY8zltwx8M8d0BO0ftXgx6icsy48lOjDqnbQiCIAind0aJ0dq1a+nbty/Dhg2LeJX+hBMby/50kvSWLVv4+9//zqpVq6isrCQ7O5s777yT++67L+LaV155hRkzZnDgwAGysrJ45JFHuOmmm07ZH5/Px4MPPsi7776L3+9n6NChvPrqq+HtRZra9sVEU1XsCxZQ+9HHhBwOOJ6Y6BMTif/fCcTm5TW5rqqjLtYv3k9NmQdN1dA00BtlWl4SR8+RrTFZ69bwUUrdOAoPEqz0glo3mV4yyJjaxBE7OAvZpIMf3oPv3gBP5Y8NWBPg8pvh0nHs2buXCRMmsG7dOgxR0chx8fjfeYe5T/2Z7Kn30jmvEzcaCsmWj6HX20hNHUVG+u+RJB1+j5u1773D4aJtKH5fXTImyfiRqby0C2lt2p27ADfRsp1lzP5mP+VOH2gSGhqxZgPXXtqSm3q3Qq87+0HXrUdqeOmr3Rys8qABqqoRZdLT75JE7hnQjiiT+PeLIAjChXJGf+MWFBQwZcoUCgoKKCkpCa8XNH36dG699dZwOafTyezZs3nggQfYuHEjycnJzJ07l8zMTNasWcPtt9+OTqcjPz8fgNdee41p06Yxa9YsrrjiCtavX89tt91GfHw81157baP9eeCBB/j000957733sNls5Ofnc/3117N69WqAJrV9san58EPsc99GNpkwZGQg6XRowSDBigqqXpuJbLUS3ef0G4K67D5Wv78bZ7Wf6DgjeqMOTdMI+EIc2lZFSFH5zbgc1Fo/NYv2EXL40dlMSAa5bkNSXwjvzmq0kErcJUVIq18ESYa4LJD1oIbAXQ5rXqbKK/H7+6azZcsWLrv3//APHUWsLEHFPg6+OZN9Tz2LHPs33uz9P0w1f0lc6CBHj7yNJOlpmXYDq+a9ycEfNmOJtREVF48kSQT8fpyHD/LN3NcZdvcDxCYmnfaez5V1+6qYXribQDBEus2CXiejahrV7gDz1h/CoJP4397ZZ9XG/ko3f/u0iEqXnzSbGZO+7vvj8Ab5fFspQVVj2jW59Ub2BEEQhPOj2YmRy+Vi/vz5fPfdd5SWljJnzhz+9Kc/ARAfH09eXh6dO3cGYObMmeFFH2+55ZaIetq0acPatWv58MMPw8nJf/7zH+644w7Gjh0bLrNhwwaeeeaZRhMjh8NBQUEB77zzDgMHDgTgjTfeoEOHDnz77bdceeWVTWr7YhJyuan9ZBGSwYA+6cdEQNLrMaSlETh8mJoPPiSqd+96e6SdbO+mCpzVPmITLchy3S9XSZIwWfTIskTpPgflB2qJOuqsS4oSzEg/KSdZ9CBLBPbVoFQsxaipYMv4sQFZBzFp4DjM4kUfsWHDBsbceQ97R4whTg1h0lT0aUY6/+FWvGVVVP3nLWJ7vcrqQDuut3jw+8soK/sEXDkc2bmDqLgEjD/Z/kVvNKKPisVZVcnu9WvoPnzUOYx04zRNY8F3h3EHgmQn/PjIUZYkEqNNlDv9fLKlhGsvbUmc1XjG7SzeWkK50092ix+3CpEkiTirAVmC1XsqKS5zkZN6bhaBFARBEE6t2YnRggULyM3NJScnhwkTJnD//fczbdo0JEli4sSJDBw4kJ49ewKwfv16srKyGq3L4XCQkPDj3BS/34/ZHDl3w2KxsH79ehRFwWAwsHz5cgYMGMD+/fvJzs5m48aNKIrC4MGDw9fk5uaSlZXF2rVrufLKK5vUdkP8fn94uxL4cRM6RVFQFOWU1zbHibpO/Nez6XuUygr0aWmoWv35NXJ8PP79+/Ds2YOx9am3/Di4rRKdQQYJ1JPWmtIZZYI1Kkd2VpFV4kIzSGiSVn9NKqOEWu3D57egT2kBDcz5Uc2JfLTuIFaLBduAIQSRMKohkBQkAiAbyRgxiG3PvErb6lI2JGYxyrQZvSEen6+EgyWfE1QC6M3miH5qqookSegNRvZ9v4GueRdmQ9wjdi+7Sp0kWA1o1I9JvFXPEbuPDfsr6d/+zEaxgiGVlcUVRBllQKv3/YkyyVS6/Xy7t4I2LSJ/Lk7+zAg/ErFpnIhN40RsGvZriUtz+t/sxKigoIAJEyYAMGzYMBwOBytWrKB///7MnTuXGTNmMGLECABuuOEG8vPzw+V/as2aNcyfPz9ijtLQoUOZPXs21113HZdffjkbN25k9uzZKIpCZWUlaWlpWK1WcnJywhvClZaWYjQaiYuLi6g/JSWF0tLSBu+hobYb8vTTT/Pkk0/WO7506VKs1nO/71RhYSEAUUVFJDmdBIzG8Nyin5KCQfROF7u/+gr/T7Y9OZmmQcUxC1pIwu1veAHOoEdix/YaogImJA2CvobLWb1B9HIIb3UNmuSsd15Rwe0LYLVaqFUUgqEggUAAWQ6gN6hoqoSxRRwAodoanLFWyioqkNGQJRdVh/bgdvkJlJXXqxvA6XLj8nr59NNPL8hjpVIP2Gt0WA0a3kYG5VxeiTXrvsOz59SLmzbGH4KKSh1IGpq34TJur8SmrduIq/yhwfMnPjNCfSI2jROxaZyITcN+6XHxeDxNLtusxGjXrl2sX7+ehQsX1l2s1zN27FgKCgro378/5eXlFBYW8sEHHwDwwgsvMGvWrHr1bNu2jVGjRvH4448zZMiQ8PHHHnuM0tJSrrzySjRNIyUlhZtvvplnn30W+fgjo549e4b3STsTjbXdkGnTpjF16tTw17W1tWRmZjJkyBBiY2PPuA8nUxSFwsJC8vLyMBgM+Nu0oWztt8gxMcgNJGAhux2sVnJGj0bfosUp615eU0z5gVpiEy31zmmaRm2Fj0t7ZZBU4kI56kaXYGqwnIoLiy6E1WapexPt5DLeWlqnyny51k6My4E+KR2D0Ygs6ZDQIclQ88NOdGYTUkomWWYnqVFJhEIegsEQ8TlX4i7eiC0pMeLxoKaqVFRUYjWbSGl7CUOOJ93nm8OrsHTuJpSQSovo+o/KvIEQQaPC8P4d6ZYZd0ZtaJrGV64t7K90kxxf//sTUjW8di8DerVjeJfUiHMnf2aEH4nYNE7EpnEiNg37tcTlxBOfpmhWYlRQUEAwGIzYnFXTNEwmEzNmzIhIIgBiYmLqHduxYweDBg3i9ttv59FHH404Z7FYeP311/nXv/5FWVkZaWlp/Pvf/yYmJoakpIYfV6SmphIIBKipqYkYNSorKyM1NfKXyanabojJZMJkqp8oGAyG8/IBOVGvvnNnzDnt8f2wDV2mNTJRCAbRHLXEXHMNlpPuryHtLkum4qCToD+E0Rz57XY5ApijDLTukowuwYKjxAMBre7ts58I1frRxVixtIxBPlQFZlvd3KIT1BD4KpmU15e3lnzLljmzsT72DLU6A3GqhKpG4SvbzeFPCknN64/OYqWPcSsSoCiVREd3ILvdaIqXF+Nx1BCT8GOyp8oyqqIgGfW073XVBfvBTDQY6J+bzIcbjxJnBcNP3j5TNY0KV4CclBguz05EJ5/5CNY1XVry8rI9+BUNi/HHmGqaRrnTT1KMmatzUxq97/P1Wfw1ELFpnIhN40RsGvZLj0tz+t7kxCgYDPLWW2/x/PPP1xtpue6665g3b154ovXJe5mdsH37dgYOHMjNN9/M3/72t0bbMhgMZGTUTfB99913GTlyZHjE6GTdu3fHYDDw1VdfMWbMGKBuZOvQoUP07t272W1fDCRJosXkWyl7+mkCBw+ii41FMpnQvF5Utxtju3bEjxvXpLqyOrWgZHcNB7dV4fcEMVr0aKqGzxNEb5C5dGAm0fEmtBgD/gMOfLvsqF4J2awHVUP1BpEMMtF909FlToYlO6F6H5hiwWABxQv+WojLovuQu5myz8Rzzz1Hyn2TMV13I/akZPybN1Dx6UJ0MdG0mHQLl+n20k37Ho/XjsmUSnaru4iJSaL78FGs//h9akqPYY6ORpJ1+NwuQn4vrXr8hjaX9TjPkY80rmcWRSW1FJU6iTLqsBr1BEIqDq9CcoyJuwe0O6ukCGBY51S+O1jN2r1VGHUyMWY9IVWjxqMQZdZz+2/anNXkbkEQBKF5mpwYLV68GLvdzuTJk7HZbBHnxowZQ0FBQTgxasi2bdsYOHAgQ4cOZerUqeH5PzqdLjwaVFxczPr16+nVqxd2u51//vOfbNu2jTfffDNcz/r167npppv46quvSE9Px2azMXnyZKZOnUpCQgKxsbFMmTKF3r17hydeN6Xti405pz1pTzyO45NFuL9di+bzIVutxI4cgW3kyIi31U5Fp5e58rq2JGZEs3dTBe4aP0gSLdvZuOSKVDJy4gGQ9DK2Ya0xpEXj3VZJyBkAScLU2oa1WxKmNnFAEoycDlsXwO5CUDygN0POjXDpWAxxWfz1r3+ldevWvPTSS+x87i8AyGYLqcNGcPnt4+gbX0Rf+XuMOh3xLUaQmnodUVFtAMjp3Q+rLY6iVcupOLgfLRQiNikZXXo2vW+YgE5/Yf+1khht4i/XdeajTUf5sqgctz+IXicxvEsaoy9rSbvks39TzGzQ8cjwjnyy5SifbyulyhVAliX6XJLIqG7pdG8Vfw7uRBAEQWgyrYlGjhypDR8+vMFz69at0wBty5YtjV7/+OOPa0C9P61atQqX2bFjh9atWzfNYrFosbGx2qhRo7SdO3dG1PP1119rgLZ///7wMa/Xq919991afHy8ZrVatdGjR2vHjh1rVttN4XA4NEBzOBzNuu50AoGA9tFHH2mBQKDB80GnSwuUlmkhj+es2gkFQ5qrxqd5nH5NVdVGy6lBVQs6/FrQFWi8nN+laY4STfM5GzytKIq2Z88ebcuWLdohu0Mr9QU0JaRqwaBX8/lKNUVp+DpN0zRVVTW3o0ZzVldpPq/3lLG5ULyBoFbq8Gq13vPXD78S0socXs3u9p+27Ok+M//NRGwaJ2LTOBGbhv1a4tKc399NHjFatGhRo+d69uxZ/xXvkzzxxBM88cQTpyzToUMHNm3adMoy/fv3r9eW2WzmlVde4ZVXXjnjti9muugodNFnvz2ErJOJstWfM3UySSehiz3N4xtjVN2fRuj1etq2bdvAGTM63am305AkCWts3ajkxfKKqNmgw2zQnb7gWTDq5XO+1YggCILQPGITWUEQBEEQhONEYiQIgiAIgnCcSIwEQRAEQRCOE9t2X8RCQQV7yVFUVUWNMWLHiVFnJENNRfJqyGYduoS6OSn7vQFcoRBJRj1pprr5QR6Ph9Vrv+VgRS0Ws55WFheZKSlkdvkNsq7p82Vqq7z43XWv+scmmpu38rSztO6PMQpatEMDqqqqCAQCREdHn9OFMgVBEAThbJ1RYrR27Vr69u3LsGHDGtxWY86cOUDkekZbtmzh73//O6tWraKyspLs7GzuvPNO7rvvvohr/X4/f/7zn5k7dy6lpaWkpaXx//7f/6u3EexP+Xw+HnzwQd599138fj9Dhw7l1VdfJSUlJVzm3nvvZfXq1Wzbto0OHTqwefPmM7n1C0JTVXat/YaiVSuwVxyjxleDU/KgJceTE9Wdal8WCfp4os3R/JBlYWG6gWJCBDUNkyzRPcqE481/8eZrr+GqdQAgyTpSOndjzO86MXTVX8jJvZn2g28+ZT+qjrrYtvIoZQdqCSkqOr1MUmY0nX6TTnKr0yQ09oOwYTYcXF231pFs4IClCxvpTIVXQlVVDAYDrVq14oorriA+XryWLgiCIPz8zigxKigoYMqUKRQUFFBSUhJeCXv69Onceuut4XJOp5PZs2fzwAMPsHHjRpKTk5k7dy6ZmZmsWbOG22+/HZ1OF7HD/Q033EBZWRkFBQW0a9eOY8eOoTawaelPPfDAA3z66ae899572Gw28vPzuf7661m9enVEuVtuuYV169axdevWM7ntC+b7zxfxw1dfoEoapaFKXLKXZDWRPvbBWNyxVEW5qZFqKbe24g2dhKvKT0qsCbPVgDsY4t9T76Vy6RJSrvwt7Tp3ITYqRHnRdvau/JLXXy6lespYbjr0T1jio/3wOxrsQ9VRFyvnF+Op8WOJMWK26gkqKkd311B9zE2f/7mE1Na2Bq+l5jAs+T+o2gvWFhCdym6Xma8PGQiwj6iENHQxiQQCAXbu3El5eTkjRowQyZEgCILws2t2YuRyuZg/fz7fffcdpaWlzJkzhz/96U8AxMfHk5eXR+fOnQGYOXNmeNHHk0d82rRpw9q1a/nwww/DidHnn3/OihUr2LdvHwkJCQBkZ2efsj8Oh4OCggLeeecdBg4cCMAbb7xBhw4d+Pbbb8OLPL700ksAVFRUXNSJkf3YUYpWLcdgNlMju3G6vJiNZjrK3bESizNQjWwxENDB3ATwGCDTpyKrAYxRJhw7NlH5+SKSf/cQSV2vIEu3Hy2ow9a7H6nt2rNy5nRWfX2Qy8a2xXRwNm3d49FFRUf0QdM0tn59BE+NH1uyJfzoTKeXMZp1OCp8bP3qMCm3xCI1tPLzpv/UJUUJbUDWoagS37rSUXR64rVaJPdhsCWht1oxm81UV1ezadOm8PdPEARBEH4uzZ58vWDBAnJzc8nJyWHChAm8/vrr4XWFJk6cyIIFC1i8eDGLFy9mwYIFjW4PAnVJzYkECOCTTz6hR48ePPvss6Snp9O+fXv+7//+D6/3x63Hly9fjiRJHDhwAICNGzeiKAqDBw8Ol8nNzSUrK4u1a9c29/Z+dgd/2ELA48EcE0OltwqdJBMjxZAkpeKVvCCBzhviUEws5SYDcYqCpJPRAiqqL8iej97HnJxOdOf+BEwmFNUA1CUvMUkppHfuRsXmb9hU1RU11knJuoX1+lBb6aXikBNLrLHefCJJkoiyGbGXeqg86qp/A94a2LccLHHh/dQO+yzUBg3E6INIBhMoPvDaAZBlGYvFwr59+5q1+7EgCIIgnA/NHjEqKChgwoQJAAwbNgyHw8GKFSvo378/c+fOZcaMGYw4vgP6DTfcQH5+frj8T61Zs4b58+dHzFHat28fq1atwmw2s3DhQiorK7n77rupqqrijTfeAMBqtZKTkxPeEK60tBSj0RixgSxASkpKeOuPM+X3+/H7/eGvT+zOqyjKOV148ERdiqLgslejoRFSQwTVILIkY9Is6NDj11xoEkghDadeR0gCvarWfReDGmowhKe0BGvmJUiShCZJKBjQ8+M92NLSOfLDJmqUONBr1FYdqncvTruXYCCEKUqH2sDCnbJBQgmEcNV4iUs9aUFCZzm6gAdMNjj+CNSlyGiahg4N7UQuHvSjHT+v1+vx+Xw4nc56G/39NDbCj0RcGidi0zgRm8aJ2DTs1xKX5vS/WYnRrl27WL9+PQsX1o0y6PV6xo4dS0FBAf3796e8vJzCwkI++OADAF544QVmzZpVr55t27YxatQoHn/88YgNaVVVRZIk3n777fB+bP/85z/53e9+x6uvvorFYqFnz57s3LmzOd0+Y08//TRPPvlkveNLly7FarWe8/YKCwupOXAQt8uFD5mQGkTVVFyyi6AUREJGVYOoOg2934+kgj8UQg4FkFVwOmrQLFY8h3YTq6ro0NBpIX6a27iqKjBYY4jWuSAIhyoq2bNkSUQ/FJeMy2PG7deQG/iEaCEIBSS++34dW/dFzv8yKrX0cnrQnF4Ufd0jOp8SJBhKwKcGkFHRaUGcTjd+bzlQt0ExwDfffNPoDsiFhYVnGtZfNRGXxonYNE7EpnEiNg37pcelOU8kmpUYFRQUEAwGw5OtoW4+islkYsaMGUydOjWifExMTL1jO3bsYNCgQdx+++08+uijEefS0tLCG8Oe0KFDBzRN48iRI1xyySX1+pSamkogEKCmpiZi1KisrIzU1NTm3F4906ZNi+h/bW0tmZmZDBky5Jy+Zq4oCoWFheTl5eHo3JHCf72E3mQipKZyzHMMn85DjVRFspSGK2QnFKXnEq+XhGAQtzUKmw8wySSkRdPh+rF8nT8Z38GtRLdrh1HnB63ukZbPWcuRLRtJ6j6QrgnbkdxWrp7wMAZbQkR/NE3ja+8uKg67Gnw9v7bShy3dTN7YDsi6+k9j5S+LkHd/jhafCJKMTZXZXqLhU63E4gLZii01G2Q9mqZht9tp164deXl5p4xNY0nTfyMRl8aJ2DROxKZxIjYN+7XE5cQTn6ZocmIUDAZ56623eP755yNGeQCuu+465s2bF55o3di8ou3btzNw4EBuvvlm/va3v9U736dPH9577z1cLhfR0XWjDcXFxciyTEZGRoN1du/eHYPBwFdffcWYMWOAupGtQ4cO0bt376beXoNMJhMmU/29xQwGw3n5gBgMBlLbtKNN957s/nY1MUYzNbIZb9DHTm0T8fp4ogxxVBo86EMBRtmDvJ8sccwIKbEmJFki7sq+2HpcSfm7f0U/6CbsXS/BZlEo37mL7V8sQTKauew3nbnUupQW1uuwJqY02Jcu/TNZ/f4eXFV+omxG9EYdQUXF4/BjMOro0j8Tk7mRfde6/y+UbkaqOQgxqVgMVrrHVrGqKoFaTETHpSLrDCiKgtPpJDo6Ovx9PFVsfsk/lOeLiEvjRGwaJ2LTOBGbhv3S49Kcvjc5MVq8eDF2u53JkydHjOgAjBkzhoKCgnBi1JBt27YxcOBAhg4dytSpU8Pzf3Q6HUlJSQD8/ve/5y9/+QuTJk3iySefpLKykoceeohbbrkFi8UCwPr167npppv46quvwqNLkydPZurUqSQkJBAbG8uUKVPo3bt3+I00gD179uByuSgtLcXr9YbXMerYsSNG42k2TL2AJEniyutvxBwVxe7135Lqi6PGV0OFXMJXUcvIjb6C1FAS6VIql9pjSLTq+DjDyDG9RsgbwCRLjH5lFiXP/pnChf/myKcqSDJoKjHp2QyffC03Zq4hwzqarv/zWKP9aNkujqtGt2XLssM4KryoIT+yTiYm0ULn36TTqlOLxm8iuQMMfQrWvAwVO8FZShdJh9yiA9/TiVrNilpdjV6vJzU1lT59+kSsOSUIgiAIP5cmJ0YFBQUMHjy4XlIEdYnRs88+y9atW+natWuD17///vtUVFQwd+5c5s6dGz7eqlWr8Btm0dHRFBYWMmXKFHr06EGLFi244YYb+Otf/xou7/F42LVrV8REqunTpyPLMmPGjIlY4PGnbr31VlasWBH++rLLLgNg//79p10S4ELTGwz0GHk9na4eTNn+vYSCQZzWII6oACbZSFt/a8wBI7JZx7iMGK6XYJPTgysYIslooEuMBd37Czh8+DAffPIpe0uriTJr9Ghlpm1iLJ37/ANDTNxp+5GeE09aOxvlh5z4XAomq4HkVjHo9E14mbFlN7h+FpRuBVc5ktFK55aX0x49JSUl4ZWvU1NTkWWxM40gCIJwcWhyYrRo0aJGz/Xs2TP8yn5jnnjiCZ544onTtpObm3vKSV79+/ev15bZbOaVV17hlVdeafS65cuXn7bti40lJpbsrpedtpwZ6B0XXe94ZmYm99/T+CheU8g6ufGFHE97sVyXIP2EkdOvTSUIgiAIPxfxT3VBEARBEITjRGIkCIIgCIJwnEiMBEEQBEEQjhOJ0S+ApmnheVUnz6/SNA01FDrtHK/T1XvysYbO/WpoGpyjeP303Ok2OxYEQRBOTVPVn/13T7O3BBEunKJjtXy27Rhr91TgcnuI05y0M3vokmKmVUZLDhQfYN+m7/B5vCiWOJI7d2fY8IHkZpziVXqgpszDvk3lHN5pJ6SoxKdacXeKZWOMxvcVTkJuhS4OlUFuiSvS47B2ScSQEnWB7vo8CQVhTyEULYaqPaA3Q9uB0PG3kNC60cs0TcPh2Eh5xRc4a3+oW7DSdjnJSUOJje3C2rVree6551i8eDGBQIDLLruMu+66i1tuuQWdTncBb1AQBOGXSQ0EcH29HOdXX6IcOYpstRL1m37EDhmC4SwXaj4TZzRitHbtWnQ6XXhPtJPNmTOHOXPmRBzbsmUL48aNIzMzE4vFQocOHXjxxRcbbWP16tXo9Xq6det22v5UV1czfvx4YmNjiYuLY/LkybhcP25wunz5ckaNGkVaWhpRUVF069aNt99+u0n3+nNZtrOMhz/cysebjlBSXoXd4WSXQ8cXFdF8ttvF5599QdEPG/E6HaCFMDlLqVm9iFnPv8Q3RSWN1lu6z8Gy/xRRtPYYfo9CKKSy2OnkiSNlLN5biavah9cf5Otojb8lqbx/qAL7B7vx7bZfwLs/x0JBWP4UfPkkHPkOVAV8dtj0Fnx8Dxzd2OBlmqZRUjKfXcVPUlW1AlX1Ewp5qCj/gp27/h+vzXyYvn37snPnTv7yl78wc+ZMMjMzueOOO/j9739PKBS6wDcqCILwy6L6/ZT/4x9UvPQSvh1FaMEgwaoqat6Zx7FHHsG/d+8F79MZJUYFBQVMmTKFlStXUlLy4y/h6dOn43Q6w187nU6mT58OwMaNG0lOTmbu3Lls376dRx55hGnTpjFjxox69dfU1HDTTTcxaNCgJvVn/PjxbN++ncLCQhYvXszKlSu5/fbbw+fXrFlD165d+eCDD9i6dSuTJk3ipptuYvHixWdy++ddqcPHK1/vxa+oRKleTJofm1km2QJGncwPrijKAkZUSxRyi2QkcwxaVAKSNYbY6v3Mf/cj7O5AvXoDviDrF+3D51awJVmIspmoaWFgdbYRPZBRGyRe0UiUdLQKyUiyxLyWevYQonbZIULuX+gmgjsXw85PwRoPCdkQlQQxaZDQBtyV8PXToHjrXeZ0buNoyTxkSY/V0gqjMRGTMQmLpRWVlU7uu/cf/P7317N161b+8Ic/cMcdd/Dxxx/zwQcf8N577/H6669f+HsVBEH4BaldtAj36jXoW7TAmJGBPiEBQ0oKhsxMlJJjVLw8A+34fpoXSrMTI5fLxfz587nrrrsYMWJExMhQfHw8eXl5rFq1ilWrVpGXl0d8fDwAt9xyCy+++CJXX301bdq0YcKECUyaNIkPP/ywXht33nknv//975u0pUdRURGff/45s2fPplevXvTt25eXX36Zd999N5y0/elPf+Ivf/kLV111FW3btuW+++5j2LBhDbZ9MVi+qxy7O0CCRSLg96HT6ZGo26/MIikoGhwkEVnTwKDn+Ck0nQmdwUDUsR2saGDU6MhOOy67n5h4U3j/sy0x4JUhSdFAg5D647PdxBC4ZFiVrEd1KfiKf4GjRpoGRZ8AEphO2t9OksGWDjWHYP839S6tqPyKYNCNwRD5aFKSJJZ8WoMswx8fHlTvkdno0aO59tprT7muliAIwn87LRCgdmkhktGIfNLG7JJOhz45mcC+fXi3/nBB+9XsOUYLFiwgNzeXnJwcJkyYwP3338+0adOQJImJEycycOBAevbsCdRt35GVldVoXQ6Hg4SEyA1M33jjDfbt28fcuXMjVrw+Yc6cOUyaNCk8OWvt2rXExcXRo0ePcJnBgwcjyzLr1q1j9OjRjbbdoUOHU96r3+/H7/eHvz6xCZ2iKBErb5+tE3Wd+O+eslokSSMYUFBVFYNOh0bd/aohFZ2mYpei6mIgyyBLEKqb+BvSmzH6Pew/WIJyaXpEO/YyF5qqgSyhHo/fERPoNdCrgASaenyC8fFky6DCbpOGpmoEyl0Ylfhzdt9NcXJsms3vRFd9EIwx0NDkaEmPpKmolXtQWw+IOOV07kSWzWjUn3S9c2cVXS+NR5aPNNi3a665hrvuugufz3de5hqddVx+xURsGidi0zgRm4adz7goZWUEKyuRoqNQtQb+fjabUBUF74H9GLp0Pru2mtH/ZidGBQUFTJgwAYBhw4bhcDhYsWIF/fv3Z+7cucyYMSM89+iGG24gPz8/XP6n1qxZw/z58/n000/Dx3bv3s3DDz/MN998g17fcNdsNhs5OTnhr0tLS0lOTo68Kb2ehISE8H5sJ1uwYAEbNmzgX//61ynv9emnn+bJJ5+sd3zp0qVYT8puz4UTK34fPCTjdIJeHyQYCoWTGAAtFEJDRtZUVFVDQiUYCKAF6+az6EIBVFXj4KGDLFlSEVG/64ABl9uAr+zHx53BuGgUvRFV05A0UDUIBH58DBcwyYQ8QVxuH4f2VFPqu7CZ+wmnWg39VGQ1wFWOGiRNI+Cs/3gRTSMq4GJf0S4OVCyJOGUyVyLLNWiaVO+yUChArcPHwQMl7C5eUu/8unXr0Ov1fP755+HRufPhTOPy30DEpnEiNo0TsWnY+YiLrraWlrW1aB43qttdv4CmYXC5OPTDNpxn+Q9Mj8fT5LLNSox27drF+vXrWbhwYd3Fej1jx46loKCA/v37U15eTmFhIR988AEAL7zwArNmzapXz7Zt2xg1ahSPP/44Q4YMASAUCvH73/+eJ598kvbt2zfah9GjRzc6CtQUX3/9NZMmTWLWrFl06tTplGWnTZvG1KlTw1/X1taSmZnJkCFDiI2NPcWVzaMoCoWFheTl5WEwGDDtLGff0t0kROmpKC8DTUOnr/tQqCEVNaSSqjmQ9ToIhTDo9KCr+1Ya3G6qolMYfU1/rmqbGNFO+YFaVs7bgylKj8FUV19XDY4YIBAIYQ5q6A0S+uPnQoCkh6s0PdGxetIGduLydnHn7L6b4uTYnAn5y03Iu79Ai0+Ck5OUgAv8LeiYN4GOad0iTh075uTIkTcwWxKRpMinzoMHt+HRR1dhNndn8ODhEedCoRCPPPIIw4cPb/QFhbN1LuLyayVi0zgRm8aJ2DTsfMZF0zTKt23D98M2DCcNcACEHA5ITqb9/07AkJl5Vm2deOLTFM1KjAoKCggGg7Rs2TJ8TNM0TCYTM2bMiEgiAGJiYuod27FjB4MGDeL222/n0UcfDR93Op189913bNq0ifz8fADU4+sZ6PV6li5dysCBA+v1KTU1lfLy8ohjwWCQ6upqUk96zW/FihVce+21TJ8+nZtuuum092symTCZTPWOGwyG8/KDc6Le3+SksHDzMYrLXERZovC4a5FUCU3S4QgZiNZ5aRWqQlNVJJ9SN/9I09D5nQQ0GUP7K+jdLgXDSZu9prVNIDk7lmN7aoiON2Ew6ujq1lhngxKTRKaqYUFCQkJBo0QP6Qr0OaZgTI0m6pIWSE3ZQPY8OKuYdx0Dh9ciuUogpiXIx//lEfCAuwyy+yFn9qiXNKWk5FFZ9QV+/xHMpgxkue7HRVUD9O1nICMjhrvvfokPPhhAx44dgbpHtFOnTqWoqIiZM2ee979gz9dn8ddAxKZxIjaNE7Fp2PmKS/yoUZQV7yZUXoE+KQlJluvWhXO70WocxOTlYW3T5qzbaU7fm5wYBYNB3nrrLZ5//vnwKM8J1113HfPmzePOO+s2LJ04cWKDdWzfvp2BAwdy880387e//S3iXGxsLD/8EPmY5tVXX2XZsmW8//77tG7d8FozvXv3pqamho0bN9K9e3cAli1bhqqq9OrVK1xu+fLljBw5kmeeeSbijbWLkdWo59ERHXl6SRHFZeCWQyh+BdCI0fm5Kt5OrFdPoMKOVmMHCSQNAgYzwY6/4f6bR2BsIIGRZYne17Vl7cI9lB904gr5kYBramU+v8RIZQsjKCqEVCQg06NxX6lGckoMtuGtf7ak6Kyld4er/wCrXwT7ATg+XwudEbKugoH/r/5IEmAypdCu3R/Zu/c5fL6joKlogCTpiI9rz6efPsro0bfRqVMnrrzySmw2G9988w2KovDGG2/Qt2/fC3mXgiAIvzjW3r1pccskque+jXL4ECChoSEbTUT160uLO+644H1qcmK0ePFi7HY7kydPxmaL3G19zJgxFBQUhBOjhmzbto2BAwcydOhQpk6dGp7/o9PpSEpKQpZlOneOnFyVnJyM2WyOOL5w4UKmTZvGzp07AejQoQPDhg3jtttuY+bMmSiKQn5+PjfeeGN4ZOvrr79m5MiR3HfffYwZMybcttForDf5+2KRmWDln2O7seFANduOOqh1ujAHHLS3aSTFtaZNmzbYS8tZvWY99hoXumgbnXpeQZ+u7RpMik6wxhoZMCGX0v21lO2rJRRS6ZFgZlJuHBsVP0U1boJVPtp6VHpbjdi6xGLKjv3lJkUn5FwD6T1g7zJwHAa9CTJ61iVNusZ/DGJjOtOl8wzs9jW43XtBkomOziE+rjc6nYkdO3bw/vvvs3jxYvx+Pw8//DCTJ0+OGFUVBEEQGiZJErZrr8XasyfuVasJVpQjmc1Yu/fA3Kkjknzhf/c0OTEqKChg8ODB9ZIiqEuMnn32WbZu3UrXrl0bvP7999+noqKCuXPnMnfu3PDxVq1aceDAgSZ32OFwsGvXrohjb7/9Nvn5+QwaNAhZlhkzZgwvvfRS+Pybb76Jx+Ph6aef5umnnw4fv/rqq1m+fHmT277QzAYd/S5Jot8lSQ2eT0hIoG3H3GbXK+tkWraLo+VJ84WGYGZIog3anUlvfwGik+DSsc2+TK+PJilpCEkNfBtMJhPjx49n/Pjx56CDgiAI/50MKSnEjbn+5+4G0Ix1jBYtWhTxBtlP9ezZE03TGk2KAJ544ol6+3BpmnbKpOiJJ55g8+bNEccmTpxY79XphIQE3nnnHZxOJw6Hg9dff53o6Ojw+Tlz5jTY9sWcFAmCIAiCcOH9wp+PCIIgCIIgnDsiMRIEQRAEQThOJEaCIAiCIAjHNXvla+HXxx+opLpqBW7PfmTJQKzt0vBbVxeFUAjvd99Rs2ULmseDIS2NqH79MGZknJfm3DV2Dmz5HnvJUWS9nrR27dG1y+Ubp5+DXj9mWeYKWxS94qIwNuGNCU3TWLlyJW+88QZHjhwhOTmZm266iSFDhiCfozcuQs4AvmI7wQovEMCo24uZzUhyCJJzoe1AsJ7dG5jeQIi1+yrZetiBElJpmxzNb9onkRjd9M+J06ewanclRcdqUTXITYuh3yVJ2CwX57oxiqqwqWwTm3buwHdAh8lnIsqgIzbeTFJaPG3atCElJeW8rm4uCMKFdUaJ0dq1a+nbty/Dhg1rcEL2iY1lf7qe0ZYtW/j73//OqlWrqKysJDs7mzvvvJP77rsvXGbVqlX88Y9/ZOfOnXg8Hlq1asUdd9zBAw88cMr+VFdXM2XKFBYtWhR+K+3FF18MT8D2+XzceeedbNy4kaKiIkaOHMlHH310Jrf+q1NVtZIDB14lEKisW8tH0ygrX0JUVDsuaTcNi+X8JB9NFXI4SP7oYyqqq9GCwbrFv1SVmoUfET9uHLbrRp3TX0oHNm/k24UL8NTW1B3Q4IMDR1h7xImWkIhOr0fT4KNyO11jrPy/ti1JNjX+S11RFCZMmMCCBQto3749l156Kdu3b+eaa64hLy+PhQsXEhUVdVZ99hXbqV12CNWlQMiP5q7Eqwbw6KOx2T5Br/8Ivv8PDHwUMq84ozYOVXn425Id7K1wH9+KBjQJ5m84zL2DLqFPu8TT1lF0rJa/f7aTI3YPJ96f+GzbMeavP8xDw3LomhF3Rn07X2p8Nfxzw3Sc6w0klrVBk+3UGJyAinxYh6nYwJYtW+nQIZd+/fqdlz3xBEG48M7on6sFBQVMmTKFlStXhnewB5g+fTpO54/7cDmdTqZPnw7Axo0bSU5OZu7cuWzfvp1HHnmEadOmMWPGjHD5qKgo8vPzWblyJUVFRTz66KM8+uij/Pvf/z5lf8aPH8/27dspLCxk8eLFrFy5MmIRx1AohMVi4d5772Xw4MFncsu/Si7XLvbtfwkl6MBiaYXVko3V2hqzKRWXaxd79j6Lqjawv9gFomka1a/NxLpvH3JCPKbsbIxZWRizsiAUovrNN3GvWXPO2qs8dIA178/D73YRl5xKfGpL7Jd04pucHniDQaIrjpFtMtDGaiLFaOD7Wg9P7TsWsZfdyR555BEWLlzIvHnz2LlzJwsWLGDz5s189tlnrFmzhnvuuees+hws81D75UFUbxBdnA59cA8G+Rg6o4+A2gqHbxyarQ04j8GXT4DjSLPb8CkhnvqsiOIyF2mxZlonRpGdGEVWvBW7J8DzS4vZU+46ZR3V7gBPLyniiN1DRpyF1olRtE6MIiPewjGHl79/tpPyWt8ZRuHc0zSNVza/QtlmH+mlHcFYS9BcAzrQZBlVlQh5dQQ8Ktu2bWPTpk0/d5cFQThHmp0YuVwu5s+fz1133cWIESPCo0MA8fHx5OXlsWrVKlatWkVeXh7x8XW7sd9yyy28+OKLXH311bRp04YJEyYwadIkPvzww/D1l112GePGjaNTp05kZ2czYcIEhg4dyjfffNNof4qKivj888+ZPXs2vXr1om/fvrz88su8++674aQtKiqK1157jdtuu63eNiH/zcrLPyeo1GA2pUfsBSbLRizmlrjdxdTUbPjZ+hfYtw/v998TjI5GtljCxyVZRp+UhKYo1C7+tN7yDWdq9/q1+FxOYhKTwouKbUxIx683kKAqKD4vXldd4m/WyaSa9Gx1ethc2/DmhP+/vTuPr6K6Gz/+mbl7lpt9hSSAIJsoKAVRFEQCYVFrsagVC66PPIK12o3Wn+KjldZqwYpVi1G0VBA3LEgtcQFEkCgCQgLIEghL9uUuubnbzPn9kXAh5CYkkCDgeb9eecGdOXPmzPdO7j05M3O+LpeLl156iV//+tfccsstoZEtRVHIycnhqaee4l//+leTPy7ay1tQje4JYIi1oNRXQaAeTDYUg8BochHwxuOrz4S4LHCXwncftXsfG/ZWsafcTddYW5PJQw2qQtdYGzUeP6sKwidsPmr1rnIO1daTEReB0XCsDqOqkhEfQYnDy6c7y1up4czaXbubbaXbySofgFA1gkYHCioKBlTFgK7qaGgEPQqqaqCgoKBJ8mVJks5d7b6UtnTpUvr06UPv3r2ZMmUKDz74ILNmzUJRFKZNm8aoUaMYMmQIAPn5+WRmZrZYl8PhaHXm6c2bN7N+/XqefPLJ0LKFCxdyxx13hL4MN2zYQGxsLIMHDw6VGT16NKqqsnHjxtNKOOvz+fD5fKHXR5PQBQIBAoHAKdd7oqN1dWSdJyOEoLpmI6ohAoFo3rlQTOh6gNrarURHDzlj7Tpe3dZv0T0edJsVoQt0VW/aRHs03t278ZaVYUxIOK19CSEo3r4Vo9WKaHztV1SKImOxBQMoSkP+Hl9dHbaoaAAiFIUyXWezw82ACHOzOj///HNcLhe33npr2Pf21ltv5Re/+AX//e9/mTJlSrvaGwgEQICvqBbMKgIB9TWNaxsvLaoaQqj4PImYIw+AaoaidWgDp7ZrX1uLq9E0HaMBdKE3Wx9hUlm/t5J7hme1WMfX+6tQAEURYUfYTCps3FfJpEFp7WpbOB3x+7S9fDtqrQ2zLwK/pQYI0vBx2dB2BYUgAbSgGSM23G43R44coUuXLqfd/s70fXzWnCtkbMI7X+LSnva3u2OUm5sb+hDPycnB4XCwZs0aRo4cyaJFi5g/f34oo/jkyZOZMWNG2A/99evX89Zbb4W9R6lr165UVFQQDAaZPXs2d999d2hdTEwMvXv3Dr0uLS0l+YSsvEajkfj4+FDqj1M1Z84cHn/88WbLV61aRURExGnVHU5eXl6H19kygdVWgaIEWhxxUZU6dtbuYNu2lWewXcfYt2wmzuOBCBsVlRXN1qteL0ogQGFeHprdflr7EkJQWVmJ0DTqfA2/QH6DEX/PIKoQ+AM+9GAQt9uNTzk2slGnGvl2eykrN7ua1fn1118DsHHjRvbu3dts/dFf1G+++eaUU9PUVNWgCAjWC+z1HsxBDU0/1pkXwSB1bg/1ohyr302d/yBfr2zf+7njoIK7TqFcD3+5zOkHfx2sbKXeov0qHjeUB5vHCcDtgwMHXaxcebBdbWvN6fw+bfFtwevxogU1AoYAQhGAjmjsdDb8ygiCmobD4UBT/HzxxRdNJpY9m53Zz5pzi4xNeOd6XDye8CP74bSrY7Rr1y7y8/N5//33GzY2Grn55pvJzc1l5MiRlJeXk5eXx7vvvgvAvHnzWLBgQbN6tm/fzg033MBjjz3WLCEtNPyl7Xa7+fLLL/nd735Hz549ufXWWwG48cYbT2sUqD1mzZrFQw89FHrtdDrJyMhgzJgx2E/zi/h4gUCAvLw8srOzz2hW5917vqG2dgM2W3KzdUIE8Xq9dMsaQ1JSzhlr0/Hq09Mp/2YztX4/ieldUNSmN1kHj5Rg6tadi266CcV4+g9YrqkqoXj7FmJSGuIhgC6aj+LIWGIUQRBBbEICUbENl4f9uo7XH2RCj55cExfdrL6BAwcyZ84cPB4P48ePb7b+6O/JnXfe2SxP4MkcPWcS+6YT3OfCkGBFqfVBrQeDyQyKghAKGgbs8UFs9iSUGjfRA7IZP7x5W1oT3FrC7tV7SYizYVCb3+heX+XhqguTGD+ud5itG1RsOMC/8g+SFG9rdrO8EIK6qnquvbQL468Onyy6PTri9ym1PJUdX8xFHNKwCjtetWE0Tmm8+0AXOgZhwmw2EhljwWiKZsKECad9I31n+74+a84FMjbhnS9xOXrFpy3a9W2Sm5tLMBhskiBTCIHFYmH+/PlNOhEA0dHRzZYVFhZy7bXXcu+99/LII4+E3U/37g0fjgMGDKCsrIzZs2eHOkYnSk1Npby86b0JwWCQ6urq076fyGKxYLE0fxTZZDJ1ygnSWfW2JDUlB5dzE8FgLWbTsRELIXS8vlKs1lSSk0diNH4/vwzGQYNwXHABpk2bIC0NVTnWDs3tBl0nJmcs5uPuPzodFw69ksO7CvC5XdiiGzq+l9aUcDAyFpeAaLOZyJgYFFVFF4KSgEZWhJWrE2IxGZrfrpeVlcVPfvITnnzyScaMGdNkpPPQoUP84Q9/4Oqrr2bQoEGn3OaI/om4iz0Ij4YalQzuEgh6EUYbeiAao6kOm/0gqqcCrNEY+k7E0M5z7Jq+qbzzzWFKHD4y4pp2bKrqfFhNRsZdnN7quTumfzofbiujzOknLcYaqkMIQbnbT4zNxJiL0jr0/D+d36fL0i4jIzmdkvjvyCq9BL85El1xITA0DBcJBaMwYY4wEAj66dN3ALGxsR3W9s52pj9rziUyNuGd63FpT9vbfPN1MBjkjTfe4Nlnn2XLli2hn61bt5Kens7ixYtDZadNm9bkUf2jCgoKuOaaa5g6dSp//OMf27RfXdeb3OdzomHDhlFbW8umTZtCyz799FN0XWfo0KFtPbwfpLi4YaSl34Su+/B49uPzVeD1leKpP4DZHE+PHg9iNDYfCTlTFKOR+Pv/F39CAsGDhwiUlBCsrMR/sBittpaoUddgHzeuw/aX0X8AF43MJuj3U1taQl1tDd32FdL/wA78FhvupHQqNcERn5/99X5SzCZ+1z0Va5hO0VHz588nMTGRgQMHMm3aNJ577jnuu+8++vbtSzAYbPLwwqkwdbcTMTgFgjpBJ2jWC9D0WIL1Eag4sdv/g1pb2FD48v+F1PaNTAHER5p5cPSFxESYKKryUOrwUu7ysb+qDr8muHVIBoOz4lqtIzMhgukjL8BsUimq8lDm9FLm9LK/yoNBUbj7qh70Svn+zrUTGVUjMwbOINCvgnL7fsx1yaiBCIQeAF3DIFRUiwbmABkZGfKzRpLOI20eMVqxYgU1NTXcddddxMTENFk3adIkcnNzue+++1rcfvv27YwaNYqxY8fy0EMPhe7/MRgMJDWmLX/hhRfIzMykT5+GjPFr167lmWee4YEHHgjV8/777zNr1ix27twJQN++fcnJyeGee+7hpZdeIhAIMGPGDG655ZYmI1uFhYX4/X6qq6txuVyh5LQDBw5sawjOO4qikNF1GtFR/amo/Bi3eyeqaiYubhjJSdnYbC3fOH+mmLt3p+ynN9FdNVC/fj16XR3W/v2IHjWKyCuv7JBLaEcpisKl464npfsF7PnqSyqL92MwmXggM5nKvt1ZpxnY4/FiU1VGxEczNjGGLtbmN10fLzk5mfXr1/Piiy/y6quvsnTpUpKTk/nlL3/JzJkzQ+f+6bQ56sp0zF2iqC+sIlBiQbFbsZl3E6Gvxmh2Q/qPoc8E6HLpKe9naI8E/nLTJeQVlLJhXxUBTTDsggTG9Evhsqy4Ns0lNaZ/KhnxEawqKOWb4lp0IbimTyxj+6dyUZeYk25/pvWI7cHjIx/l08zP2LppH9aDCdiCdgxmHxFRRpJS4+nbrw+9evUKO7IsSdI5SrTRxIkTxfjx48Ou27hxowDE1q1bW9z+scceEzTcttHkJysrK1Tmb3/7m+jfv7+IiIgQdrtdDBo0SPz9738XmqaFyrz22mvixGZXVVWJW2+9VURFRQm73S7uuOMO4XK5mpTJysoKu//2cDgcAhAOh6Nd252M3+8Xy5YtE36/v0PrPR/I2IQn49IyGZuWydi0TMYmvPMlLu35/m7zn9vLly9vcd2QIUNOOpfM7NmzmT17dqtlZs6cycyZM1stE+4yXXx8PG+++War2+3fv7/V9ZIkSZIkSTKJrCRJkiRJUiPZMZIkSZIkSWokO0aSJEmSJEmNOu6RHul7EygpwbtjB0LTGhKt9uzZoRnnWyKEoKbkCFWHi1FQSMzsRmxKKrquc2DfQYr3lFJVr1MfGUdCWgw9kqPolRyFoihs3ryZ1atXI4Rg+FVXYenTn+LaepQqL5eoRlLiIzCld+4swkJouFwFeL0lqKoZu/0SzOa2zUDtDWh8U1yDwxMgJsLEpZlxWE2tZFcXAkq/hZoDYDA3PCEWlYwQgiJnEUW1RSiKQu/43nSJOrvTSkiSJJ3PTqljtGHDBoYPH05OTk7YlB5H52Y58Sbp4uJipk+fzmeffUZUVBRTp05lzpw5GBsfuV63bh2//e1v2blzJx6Ph6ysLP7nf/6HX/7yl622p7q6mpkzZ7J8+XJUVWXSpEk899xzoen5vV4v9913H5s2bWLHjh1MnDiRZcuWncqhn1U0dx3Vr+biXvcFuqsh1YJizYJ6iQAAVBZJREFUs2K76CISp0/HlHb6eada4nHU8uV7b3Hkux34vfUAmG0RxPXozWGPhdLqWjYHYjmkR+EXJRgNJhLjoukVG2TTa4/z5fp12Gw2UBTqPR7s/S6hx2/nYElMJUaDUd8Kfm6wEXtV+klacmpc7p3s3/936ur2IkRD8k+TKZ6U5Al06fIzVLXlX42PC8t448v9lNR60YVAVRTSYq38/PJujO6X0nyDqr2w5mkoK4BgYwZ5WxyVF4zkZYvGt1UFeIIN09VHmaIYmjaUuwbcRbT57JnXR5Ik6YfilC6l5ebmMnPmTNauXdskM/jcuXNxuY7lQnK5XMydOxcATdOYMGECfr+f9evX8/rrr7Nw4UIeffTRUPnIyEhmzJjB2rVr2bFjB4888giPPPII//jHP1ptz2233UZBQQF5eXmsWLGCtWvXcu+994bWa5qGzWbjgQceYPTo0adyyGcdoWlUPDcPx8r/gKJgysjAlJmJGhFJXf5XlD31FFptbafsO+D18tkbC9i/dRMGk4nYlDRiU9LQDUa27CmipHQ/XwWSKdLjUBWVGCVAhF6Hq6yU1/5wF9t27uafi5eyo7ySCWs30/vJ5whUVrD7t/eS6najGRWWJar8Q/PgXLkfs7djr/h6PPvZvftJ3O4dmE2xRNi6YbNmoOs+Dh1exMFDC1vcdvWucuZ9/B1lDi+pdivdEiJJtVspc3iZ98l3rN51QoZ45xH4z2/h8CawxkB8D4jrTp0I8Oe9S9lQ9BFWo4XM6EwyozMxqkY+Lv6Yv276KwHt3E7aKEmSdC5q9zeO2+3mrbfeYvr06UyYMKHJzL1xcXFkZ2ezbt061q1bR3Z2NnFxDTPirlq1isLCQhYtWsTAgQMZN24cTzzxBC+88AJ+f8Nf7IMGDeLWW2+lf//+dOvWjSlTpjB27Fg+//zzFtuzY8cOPvroI1555RWGDh3K8OHDef7551myZEmo0xYZGcmLL77IPffcc9ppQs4W9Vu/xbMxH1NSEsa4OBRVRVEUDFFRmLt2xbdnL67PVnfKvvd/+w3lRXuJTkzGGtlwaUxRFNxGG5rBRGXQxBHdSqSqEaEKDAYDBlWlYtvHeCoOcdHdT2PrNYyV1S4O+QJcNOAqRj7xMvWVpezP+4AEXcEuYG2igSKvn7jK1idRbK/S0n/j9ZZgs2ZiMDQkA1YUAxZzEkZDFOXlK/F6jzTbLqjpLM4vxhfU6RoXgdnY8OtjNqp0jYvAF2hYH9SOy0BfsAyq90FcN7BEgaKAqvK5zcouo0IXXz3RqKEYxlhiSIlIYXP5Zr4p/6ZDj1uSJEk6uXZfSlu6dCl9+vShd+/eTJkyhQcffJBZs2ahKArTpk1j1KhRDBkyBID8/HwyMxtmT96wYQMDBgwgJeXYpYaxY8cyffp0CgoKwuaL2rx5M+vXr+fJJ58MLVu4cCF33HFHaN6kDRs2EBsby+DBg0NlRo8ejaqqbNy48bQSzvp8vibpSI4moQsEAqHM6B3haF3tqdP15Zfofj+GCBu60JuuNKgIowHX6tVETpzQYe08at/mrxECVKMRvfF9EAKcQVB0KCGGoBCYoWEaTQAUygu/IPGCy7CnZPLJjlJKFTsRAYGqCaK6dCX98msoXvMfLvzxFOw6HDTCpjgDo4pN+OtbTgvTHppWT1X15xgM0Y0zfDaNncEYg9d7iMqqL0lJvq7JuoIjTg5U1pEQZWoecyAh0sSByjq2H6qhf7odhMCw6yMwRQAK6Me2Wae5UBUDRj2AqKtCGCNC6yyqhaAWZMPhDVyaGH626lM5Z34oZGxaJmPTMhmb8M6XuLSn/e3uGOXm5jJlyhQAcnJycDgcrFmzhpEjR7Jo0SLmz5/PhAkNX8aTJ09mxowZTJkyhdLS0iadIiD0+mh6kKO6du1KRUUFwWCQ2bNnc/fdd4fWxcTENEnGWVpaSnJy0+zwRqOR+Pj4ZvW215w5c3j88cebLV+1ahURERFhtjg9eXl5bS6buHUrkZ46Aick0D3KUF+Pvm8v36xc2VHNCynZs5uApx5f2bF9CyBoiwMBPowoQoQ6TUcF691EJ/fA43ax2+emLiWIya8Q1BR0H1gT06j+rgC/r2EEUVNUKgN+FKHwWd6naMbWJxFtE8WNzVZBw9ymWvgiiputW78kGGh6M/UeJ9Q4DCg+gSvMve26gBqvwidr13HADqoe4IqKwyhC4K9v+j5VRNWjGHQ0TaPe6aDO1zSlRL1ez7bd21h5uPX3rz3nzA+NjE3LZGxaJmMT3rkeF4/H0+ay7eoY7dq1i/z8fN5///2GjY1Gbr75ZnJzcxk5ciTl5eXk5eXx7rvvAjBv3jwWLFjQnl0A8Pnnn+N2u/nyyy/53e9+R8+ePbn11lsBuPHGG09rFKg9Zs2axUMPPRR67XQ6ycjIYMyYMdjt9g7bTyAQIC8vj+zs7DZnAK6trsZx4ADGpKSwT6AFfH6sAy7mkvHjO6ydR31eW07R5q+JTTnWIRUC3B4NH4Io3Y9QVBQER5smEFhjknCX7sUSEc3AzFhKkqI45PBi9PvBpOLYt4Oo1K6YLWZ0wGCArqqCZqjnmrHXYrac/iU1XfezveA/BAK1WCzJzdYLEcTr9dK920gSE7ObrNtbUcen1d8SYTYQZW3+q+P2BlFtGhOvvZgeSZENI0bvvNPwJFpM031laToleDAInajYeCKjj4+lwOv2MqTHEMb3D//+nco580MhY9MyGZuWydiEd77E5egVn7ZoV8coNzeXYDDYJDmrEAKLxcL8+fObdCIAoqOjQ8tSU1PJz89vsr6srCy07njdu3cHYMCAAZSVlTF79uxQx+hEqamplJ8wahIMBqmurj7t+4ksFkvY5JAmk6lTTpD21Gu/+mrcH36IqHVgiG/6iLnu8TTcr3LtqE5pZ8/LhnJw2xYC9fVYjo6cKRBnNlDqDZJODXuVrnhRsSkNl4+E0EkdOIrCd5+laucGxoy/k4o4I3+vL8NvUqn55ksqvv2Ky389BwWFKoMgVoPLa3Vq4wOYLeYOOhYTycljOXTodRAaqtq0Tq+vEoslicTE4c321zsthv5dYvh6fw1RVhPqcR1SXQiq6gL8qFs8F6bFHOus9rsB1v0VdD8YraHyI7HzVcCFx2AkMjIRRT12u5/D58BmsnF1xtUnPebOOhfPBzI2LZOxaZmMTXjnelza0/Y233wdDAZ54403ePbZZ9myZUvoZ+vWraSnp7N48eJQ2XD5zIYNG8a2bduadGLy8vKw2+3069evxf3qut7kPp8TDRs2jNraWjZt2hRa9umnn6LrOkOHDm3r4Z1zzD16YL/+evT6egKHD6N7PA3/LysjWFFB5LDLibzqqk7Zd9e+/elx6RDqXQ5cVZUEfF4CXi9GZxXmoI8Ys0JP1YFfKDg0Fa+mEdAVovuMIKH/lWx//TFWvvJnuhzYQ5fDRXz15vOs++ODJA0aRuzw0RwyCHRdMLkkSHJSJDWJ/g5tf2rKdURF9aPeexCfvxJN8xIMuvHUF6OoRjIypmIyNR8RVBSFu4b3INluYX+lh1qPH29Ao9bjZ3+lh2S7hTuHd286gtd3InT9ETgOgasUAvXgczHEUcFVmoEqWzRlPgf1wXo8AQ8l7hJcfhdju42lT3yfDj1uSZIk6eTaPGK0YsUKampquOuuu4iJiWmybtKkSeTm5nLfffe1uP2YMWPo168ft99+O08//TSlpaU88sgj3H///aFRmRdeeIHMzEz69Gn4Qli7di3PPPMMDzzwQKie999/n1mzZrFz504A+vbtS05ODvfccw8vvfQSgUCAGTNmcMsttzQZ2SosLMTv91NdXY3L5WLLli0ADBw4sK0hOKsoikL87bdjSk7GueJD/IcPN1y6iYsjOns0sTfeiGru2Ke5jlINBq6Y/DNiU9P47ssvqHPUoACxiYkMvOxyDtVC5K7dRHiD7NHs1GHBYraSlRbL//z9VXZ8+CqvLPgH8xqncrBF2+k+6Wek/ew+vKqBXh7BdXUKo3skY700EW317g5tv8kUS+8LZ3P4yBKqqtYQCNagKAbs0ReRlvYT4uOvbHHb3qnRPPnji1icf5CvD1RT7fFjNqqM6pvMrUMy6Jl8wtxDlmjImQPfvAG7/gOealBVjMn9mTHgJjIVD3nFH1NdXw0KpEenM7bbWMZ1G3dGJumUJEmSTiDaaOLEiWL8+PFh123cuFEAYuvWra3WsX//fjFu3Dhhs9lEYmKiePjhh0UgEAit/9vf/ib69+8vIiIihN1uF4MGDRJ///vfhaZpoTKvvfaaOLHZVVVV4tZbbxVRUVHCbreLO+64Q7hcriZlsrKyBA33CDf5aQ+HwyEA4XA42rXdyfj9frFs2TLh9/tPaXs9EBC+oiLh3btXaHV1Hdq2kwn4fKLq8EFRdfigCAaOtb/eUy/27iwWuwsPih3FNWJ3mUvU+Y691x6PR3z55Zdiw4YNwu12C2cgKHa6PGLP4VrhLXULrb6h7OnG5mT8fodwu3cLj6dY6Lrerm3LHPXiu1KnKHPUt20Dr1OI8p1CVO0V4rhz2hv0ir21e0VRbZHwB9t2nJ0dl3OZjE3LZGxaJmMT3vkSl/Z8f7d5xGj58uUtrhsyZEjo8fnWZGVlsbKVp6RmzpzJzJkzW60j3GW6+Ph43nzzzVa3279//0nbd65SjEbM3bp9L/s2ms3Ep3dtttxqs9Kjd0aL29lstmaXOntH2SDK1uFtbI3JZA972awtku1Wku3Wkxc8yhINSb2bLzZY6BHT45TaIEmSJHUsmURWkiRJkiSpkewYSZIkSZIkNZIdI0mSJEmSpEbtnvla6jxC0whUVoKuY0xORjlu3gXN56fu8CEUVRDVJQPF1PSJMyEEbrebYDBIZGQk5uOeSKv2uMgvL8FosDAstQuRJiNHjhyhvLyc1NTUJvM9BQK1BINOjEY7JlNsszYGXD5KKj1gM5KaGBnKF9YW3jo3XrcbS0QEtuiOmyBTkiRJkjrKKXWMNmzYwPDhw8nJyeHDDz9stv5oYtkTb5IuLi5m+vTpfPbZZ0RFRTF16lTmzJmD0djQjPfee48XX3yRLVu24PP56N+/P7Nnz2bs2LGttqe6upqZM2eyfPlyVFVl0qRJPPfcc0RFRQENN14fnTTyxOO4/PLLTyECHUsIQdS2bZR+8gna4SOAwJiSgn3sWCJHj2HPfz5lz+YK6jxGFAQxUV56DU6i+4QJKEYThw4dYvPmzZSUlKDrOhaLhd69e5Peszu/2/RfvgqA35wAqIj33oN/vcnhr74GGh77z8nJ4dFHZ5CUtIPqmg3ouh9VNRMfN4z09J9is2XiO+xiZd5eVhZXcSigoSuQZLcycWgGPxmW1WoHyVlRzrbP8ijetoWg34/BZKRr34voP3I0CV1avkFbkiRJks60U7qUlpuby8yZM1m7dm0ogz3A3Llzcblcodcul4u5jXPVaJrGhAkT8Pv9rF+/ntdff52FCxfy6KOPhsqvXbuW7OxsVq5cyaZNm7jmmmu47rrr2Lx5c6vtue222ygoKCAvL48VK1awdu1a7r333mblPv74Y0pKSkI/l1122akcfocSQlD7z3+SkPcx/n37UGw21IhIAocOU/6PBaz+3Ut8s9aFu86I2RjEZNSpckay8dM6tuW+wZ7d3/Gf//yH/fv3YzAYsFqt+P1+Nn6Vz4P/focvSMRnSUcVOv5vN3P4N7+jrKqafr+dxZoNG1iwYAH79n3HtdfewOo1S0AITMZoEIKy8pXs2PkINbu/5dVFW5m/u5S9gSAWg0IkUFrj4eW83Ty9vJCA1jypKkBtWSl5r7zAri/WoGtaaKbsPfkb+CT3RSoOFJ3BaEuSJElS69o9YuR2u3nrrbf4+uuvKS0tZeHChfz+978HIC4ujuzsbC666CIAXnrppdCkj6tWraKwsJCPP/6YlJQUBg4cyBNPPMFvf/tbZs+ejdlsZt68eU329dRTT/HBBx+wfPlyBg0aFLY9O3bs4KOPPuKrr75i8ODBADz//POMHz+eZ555pskkjwkJCaedJqSj+XbtwrXiQ3SLGVOXLqhKQ19VjYykymnisCuJyKg6bFFH+7ACs8lHvc9E4U4DnsBH+BUD8fHxoQkBzWYze31O9ib1wywUCDoRQlAz/2UsPXuQ9Mc/4LClUJCUzn13DmXgoJ3c9rOXmfvX/fzrXwMBMBgiMJli8dQfYP2uRfzbdS0Wo4EEY2NiVQNEmAR1Po3V20u5sm8y1/Rpnntsy3+XU1tWQmxqGmpj2guT1Yo1Kora0lK+XvE+Of/7SzmZoSRJknRWaPeI0dKlS+nTpw+9e/dmypQpvPrqq6E5jKZNm8bSpUtZsWIFK1asYOnSpaHLaRs2bGDAgAGkpKSE6ho7dixOp5OCgoKw+9J1HZfLRfxxucAWLlzY5Et0w4YNxMbGhjpFAKNHj0ZVVTZu3Nikvuuvv57k5GSGDx/Ov//97/Yeeqdwr/0cUe9BO5pz7DgVpq4IoaD6mqfEsJoDONQgNTVO7HZ7k5joQmenzYrXaCHa27Ctb8cuAgcPEX/bzZhMVhAB/llcjMdThKZ9x733XkJBQSW7dlWF6lEUFaMew0anjlsJEm9oerooKEQaVYJ+jVXbSpq10VlZweGdO4iItoc6RcfXHRkbR0XxfiqL97crZpIkSZLUWdo9YpSbm8uUKVMAyMnJweFwsGbNGkaOHMmiRYuYP38+EyZMAGDy5MnMmDGDKVOmUFpa2qRTBIRel5aWht3XM888g9vtZvLkyaFlMTEx9O59bJK80tJSkpObjlQYjUbi4+ND9UZFRfHss89y5ZVXoqoq7777Lj/+8Y9ZtmwZ119/fYvH6vP5muRpO5qdNxAIEAgEWg9UG/kOHQSDERQFoQt09dglqTolGoPuRw/oYSfQ1NUgmqajKAq6fmw7n+bHY2pIs6IKUAT4Sxo6LpZ+DbFTdB+1mk6lu4RgsJ6Bg7oAUHzQQa8L40J1qUErlX4biqqBAoIT2qEoWAUUV7ibxcRRWY7f5yUyLh49TPsNFguBmmocVZXEhpkkEgjV2VHxPl/IuLRMxqZlMjYtk7EJ73yJS3va366O0a5du8jPz+f9999v2Nho5OabbyY3N5eRI0dSXl5OXl4e7777LgDz5s1jwYIF7dlFyJtvvsnjjz/OBx980KTjc+ONN3LjjTe2q67ExEQeeuih0Osf/ehHHDlyhL/85S+tdozmzJnD448/3mz5qlWriAgzwnMqEsvKiXQ6ITGBisqKJuuUSA+aIQodHZ8/TCJdoaILnbKysqYjRugYYxraJwBN6Ci2htf+sgpM6akIoxnd52dz/k4irB5273YDEAx6miT6NQaDWJWuBIMCn9585ErRwacLPM7qZrOa+2qrcdfV4fEHUI3NMxsLTSPorefrTd9QcPBIs/XHy8vLa3X9D5WMS8tkbFomY9MyGZvwzvW4eDyeNpdtV8coNzeXYDDY5L4dIQQWi4X58+c36XwAREdHh5alpqaSn5/fZH1ZWVlo3fGWLFnC3Xffzdtvv83o0aNbbVNqamqTL3KAYDBIdXV1q/cTDR069KRv9KxZs5ock9PpJCMjgzFjxmC3d8zj5nUxMVQ+/RdqAwES09JR1GMdHL+ngt1KGsZIC2Zz07cqoBmI8IMWFYEpKorIyMgm6zMdpRzQg9SbDSiqQsSll6BGRuJe8R9i75uGUG3kJCcz7qJhFO7YwnPP/YfERBujRvXBZDp22avec4iL7fVsKbGgGw3YTrgkFvBp6Gb46ci+jL+s6aiPrmv8t6qUqoMHsKc0v//IVVVJZHIWE382BWMLCW8DgQB5eXlkZ2djMjXvXP1Qybi0TMamZTI2LZOxCe98icvRKz5t0eaOUTAY5I033uDZZ59lzJgxTdb9+Mc/ZvHixaEbrU98TB9g2LBh/PGPf6S8vDw0ApSXl4fdbqdfv36hcosXL+bOO+9kyZIloUtyrRk2bBi1tbVs2rQp9JTZp59+iq7rzXJxHW/Lli2kpaW1WrfFYsFisTRbbjKZOuwEsV9xBe4BAzB98QW63Y6xcX4fva6OuKoyolMz8KgJKMF6TMaGy1H+gJF6v5nMxFpMgy9lS8FOPB4PERERqKpKIBCgp19hd+0R9iSloggrRqtCzOQbqXltEXpkDKk/+Sm/vOoqamsdvPxSDSs/PMJvftMfkxFURUXXg/j95RiMZkZ0u4qte81sCviJMypEqwpCCDxBnSp0eqbFkDOgS5iYmLh4dA7r3lyIu7KCyLh4DEYjuqZR56hFAS6+diy2Ezp14XRkzM8nMi4tk7FpmYxNy2RswjvX49Ketre5Y7RixQpqamq46667iImJabJu0qRJ5ObmhjpG4YwZM4Z+/fpx++238/TTT1NaWsojjzzC/fffH+p8vPnmm0ydOpXnnnuOoUOHhu4RstlsoX2+//77zJo1i507dwLQt29fcnJyuOeee3jppZcIBALMmDGDW265JTSy9frrr2M2m0NPtr333nu8+uqrvPLKK209/E6jms0kPvwQxRUVRNfWEKipBUVBsViIvfQirrnpajav3ExlpRmPTwUUTIYAWekOBk+bgCkpHdUSQWFhIbW1tUDD3ERdU9K4MzOeP1d8h8Oagc8YhXXybUQHFdxLlrD/vfe4MjmZsrIyTCYTjz52Jzfc4MPnO9J4H5GCxZJEly63kZQwll9zmBc+38c3Hi8HG+8XshhVBmXG86sbLyI+MvyIT7eLBxH0+9n80XJcVZXQWHeEPYYB147lwsuHn4EoS5IkSVLbtLljlJuby+jRo5t1iqChY/T000/z7bffcvHFF4fd3mAwsGLFCqZPn86wYcOIjIxk6tSp/N///V+ozD/+8Q+CwSD3338/999/f2j51KlTQ5NGOhwOdu3a1aTuf/3rX8yYMYNrr702NMHj3/72tyZlnnjiCQ4cOIDRaKRPnz689dZb3HTTTW09/E5liIuj4vrruKRvP7S9exouT/bogaVPHxRFYdQl/ancVkDNniIUBZIuzCS2/yXQeF/RFVdcwcUXX8zBgwcJBALY7Xa6du2K0WjkpoCPV7dtYKPDgUGxMHb2bEY+8yzvvfM2paWldOnShcmTJxMXF0cw6Ka29quGma9NMcTGDMZobJgkM/2qDP7v0lS++7aMwnI3wqpyYe8kBmTFnvRR+56Dh5J10SUc2lmA1+XEHBFJ1779sUScfKRIkiRJks4kRYR73EkKy+l0EhMTg8Ph6LB7jKDhGu7KlSsZP378OT1U2RlkbMKTcWmZjE3LZGxaJmMT3vkSl/Z8f8skspIkSZIkSY1kx0iSJEmSJKmR7BhJkiRJkiQ1kh0jSZIkSZKkRu1OCSKdfXTdT3X1F1RWrcbnLcFkiiUhYQQJCSMweuvhu//AvtXg9+DT0nCVRlF/oBYA2yUXEz1qFJYLLmj3fj2azupqJx9XOth72EV9aR1Wj06C7qFu80q2rP6Q2ppqunXrxl133cXUqVNRdI2izV9TtGUT3jo39sRkelz6IzL6XkzwoJv6HdVo1V4UiwHrhXEYL2j7Te5CCPKLqvl4Rxn7KuuIMBu5tJsRQ/QOtld+jSi10aWqN0m+LiTaE8joG0+3AYlE2MNPNdCR/H4/u3fvZvfu3Xg8HqKjo7nwwgu54IILMBrlr6EkSdLZ4pQ+kTds2MDw4cPJycnhww8/bLb+6KP1J070WFxczPTp0/nss8+Iiopi6tSpzJkzJ/TF8N577/Hiiy+yZcsWfD4f/fv3Z/bs2YwdO7bV9lRXVzNz5kyWL18eelz/ueeeIyqq4VHz1atXM3fuXPLz83E6nfTq1Ytf//rX3Hbbbady+GcVTfOyZ+/T1NSsRwiBQbVQ7y3G4dxMxaF3uXBXJeaqw2Cw4C7WqNywDc0HSnQcRCbh37MH18cfk/g/9xE96po277c2EOSxPUfY5HDj3uPAc9CNrgmCtSUceeXXaB4X3Ydmc9tPBrKvcCv/+7//y+sLF/Lgj3OoKy1BUVUMJhO1pUc4VLCNQWnZJKldUQQoJhWhCQKH3Ri2WTHbTj6wqemCl9bsYfnWEgKajs1koF6U8oXrHQymai6vuoquZX3waQrFxhJqKz1UHnSx95tyhv+0F3GpnTd1QF1dHf/97385cuQIiqJgNBqprq6muLiY3bt3M2bMGMwtzPwtSZIknVmndCktNzeXmTNnsnbtWo4cOZbjau7cubhcrtBrl8vF3LlzAdA0jQkTJuD3+1m/fj2vv/46Cxcu5NFHHw2VX7t2LdnZ2axcuZJNmzZxzTXXcN1117F58+ZW23PbbbdRUFBAXl4eK1asYO3atdx7772h9evXr+fiiy/m3Xff5dtvv+WOO+7g5z//OStWrDiVwz+rHDnyFtXVn2M2JRBhy8RiScFmzcBqTsVZtZH9xj0Q1x2/SKHy6yC6MGGKN2EyODBFq5iyshBeH5Uvv4z/wIE27/flgxV85ajDVu3Hf9CNxWggOtpM+dt/ArOFH83+F1k/fgh33+tZ+u57rFu3ji2bN/Pym0uJTkwiJjmFqLh4YlPSyIjog7ncgNfvwphgw2C3YIyzYoi1ECyvJ+2gLWwS3ePlFZbxwZYjRFmMdEuIJMluJBCzEtVcRZeKQaQd7odiBhHjR7P5qDAcwR/pwVlZz5fL9qEF9VbrPx3r16/n8OHD2O124uLiiI6OJj4+nqioKIqKivjqq686bd+SJElS+7S7Y+R2u3nrrbeYPn06EyZMCI0OAcTFxZGdnc26detYt24d2dnZxMU1ZGpftWoVhYWFLFq0iIEDBzJu3DieeOIJXnjhBfz+huSk8+bN4ze/+Q0/+tGP6NWrF0899RS9evVi+fLlLbZnx44dfPTRR7zyyisMHTqU4cOH8/zzz7NkyZJQp+33v/89TzzxBFdccQUXXHABv/jFL8jJyeG9995r7+GfVYLBOioq8zCoNgyGpkltVV8dZl+AWruCxxTAvduBVh/EaDehGBpHJ1ylDSMYqanoDgeu1WvatN8yX4A1NS5ijCqOg26EAJPFgOdAIfXFO0m98X7qIuNJtFvYX1XHV0U1XJjRlbGDL+GLHbvxBYOhuhShkCS6IBRwu2oQ+rEOimJQUaNNRNQZCJa0nABQCMF/tpUgBMTYGubZcLMXLyVYRDwXOC5AF+AzNCTiNaoNI5RV3goi4yzUlnso2eto07G3l8PhoKioCJvN1uySmclkwmKx8N133+H1ejtl/5IkSVL7tPtS2tKlS+nTpw+9e/dmypQpPPjgg8yaNQtFUZg2bRqjRo1iyJAhAOTn55OZmQk0XH4bMGAAKSkpobrGjh3L9OnTKSgoCKXrOJ6u67hcLuLj40PLFi5cyB133BEaQdiwYQOxsbEMHjw4VGb06NGoqsrGjRu58cYbwx6Hw+Ggb9++rR6rz+fD5zuW1f5oErpAIEAgEGh12/Y4Wld766yrK8Lvr8ZojEMXTUc8FJ8bgw4BReBW6wmU1IOqgKIgAFQj+OsQWgBUA5hNeLZvw96GNuxy1uEMBElXDRxy+jCYVAQCd1EBislCXJ8h+IQggEDXdHaVOkg0HOGSrAyWfZHP/pIy+nRrOC/MuhmTbkFT/QSDAfw+LyarNbQvYVRQdAVfqQtTevjLXbWeAPur3ERbDaE41HMEoWiYtQjs3hh8qh+DLjCpDeeNQTVQH6xHKBqaplN12ElKj6h2xb8tSktL8Xq9xMXFoevNR6XMZjN1dXWUl5efNHff8U71nPkhkLFpmYxNy2Rswjtf4tKe9re7Y5Sbm8uUKVMAyMnJweFwsGbNGkaOHMmiRYuYP39+KPnr5MmTmTFjBlOmTKG0tLRJpwgIvT6aE+1EzzzzDG63m8mTJ4eWxcTE0Lt379Dr0tLSUFLa0EEZjcTHx7dY79KlS/nqq694+eWXWz3WOXPm8PjjjzdbvmrVKiIiIsJscXry8vLaVV5VS7FYXQihAU3vUbH5XEQENYKagqO2FtUbIBgMInwNHQNFNIza1FRUIBQVo8OJ70gJ36xcedL9fmewUGeNp/y4DqJAQ9MFCB2ftx7NZKam2kNdvWBHYQHWYBFutxsAR20t5WUNnR8rNrqbAgT1IEERpKqqGtV03GkpwILKtu3bqSn9Jmx76oNQW2tAUQS+xiu5bpubYKRGvd/X2FkSBINBfI19E01ogKCishLhMbK9oID9ri0nD3o7uVwu6urqCAQCYVOn6LpOMBjkiy++OKVzqr3nzA+JjE3LZGxaJmMT3rkeF4+n5asOJ2pXx2jXrl3k5+fz/vvvN2xsNHLzzTeTm5vLyJEjKS8vJy8vj3fffRdouDS2YMGC9uwi5M033+Txxx/ngw8+aNLxufHGG1scBWqLzz77jDvuuIMFCxbQv3//VsvOmjWLhx56KPTa6XSSkZHBmDFjOjwlSF5eHtnZ2e2acl3X/RQUfonfX4bF0rRzSL2ZYHU1VsVI18g0vL3qqKqswGQyo6gKBDSwxZOUnIrQdYL19WRMmMBl48efdL/DAkE+33EQn6YTmwyOsjrMFjNx/YdQ9u8Xce/YQPxlo0mMisRsDvDT0f3oabuMfy5cSJTNyqD+/TAf7fwICHoCWH1WjBYjSelpTToQmieAM+Bg0OghWNPDx1wIwWa9kK+La0mOtwEQST/qla9QbH5qI6tJdqWhm3VMakPd9ZqXGHMMibYkfCaNq3N6ktyt497To+rq6nj77bfRdZ3IyOYjXi6Xi4iICG644YZ2vfenes78EMjYtEzGpmUyNuGdL3E5esWnLdrVMcrNzSUYDIay1kPDl5LFYmH+/PlNOhEA0dHRoWWpqank5+c3WV9WVhZad7wlS5Zw99138/bbbzN69OhW25Samkp5eXmTZcFgkOrq6mb1rlmzhuuuu465c+fy85///KTHa7FYsFgszZabTKZOOUHaX6+JtNTrOHDgZbSgE6MxJtSpCFosBMxmUqs0bEEF04V2nNtrCdYGMEXpKKoK9jTQBcEjJZiSU4i5dlSb9p9sMjEuKZZFJVVEZUThqqonUK9hTelGVJ8hlL7/d1JTs6hM7snAjDgu65bAO28v5eNvvmX84IEYhIaqNOxHICjTDpCpXEh0ZAKqooaOQQQ08Gi4owNY0qJbbdv1g7qy7YiLSneApCgzUUp3IumGU9nN7tjvSPKkYPNHELR68et+VEUl0ZKExxkgrUcM6RfEN3QYO1hsbCy9e/dm69atmM3m0PkkhMDr9aJpGhdddNEpj0B21rl4PpCxaZmMTctkbMI71+PSnra3uWMUDAZ54403ePbZZxkzZkyTdT/+8Y9ZvHgx9913H9D8MX2AYcOG8cc//pHy8vLQCFBeXh52u51+/fqFyi1evJg777yTJUuWhC7JtWbYsGHU1tayadMmLrvsMgA+/fRTdF1n6NChoXKrV69m4sSJ/PnPf27yxNq5LiXlerzeUsor/kOgvgZFMSKEhqIaSUjNIbO2FJy7MCJI/pGgfEOAgFMBWxxUuEG4MCYnk/TgLzCdcKmzNXd0SaTCH2C14sLcw07dPif1Lh9JN/6K0tf/wKa/3Et638tIubQfg57czPbt2/npTZO489qrKd2zEz1YjWpQ0TWdOouVLt37YvVHoVV5G+6F0gWoCqbMaEoMJVwc5jLU8a64IIE7ruzGoi8PUFTlwagq6OSgRNVTlbCLA2YL3Q8NwuC0YFUt2E0xGD02EjKjGHrDBZ3SKTrq8ssvx+PxsG/fPtxuN6qqous6RqOR/v37M3DgwE7btyRJktQ+be4YrVixgpqaGu666y5iYmKarJs0aRK5ubmhjlE4Y8aMoV+/ftx+++08/fTTlJaW8sgjj3D//feH/op+8803mTp1Ks899xxDhw4N3SNks9lC+3z//feZNWsWO3fuBKBv377k5ORwzz338NJLLxEIBJgxYwa33HJLaGTrs88+Y+LEifziF79g0qRJoXrNZnOTG7vPRapqpFu36SQmjqCqai0+fzlGYwzxcVcQE3Mpap8AFH0OB9Zju8BDl6vTqKuIxltcidAFtv79iLzqKoztjIPVoPKHC9IZn+RhTZKLA93rcJa4ifSlkHb529R/t55Nnyxn/57v6N+/P3PnzuXaa69F1zSO7CqkuGAbXreL6IREul1yKYmZ3dAq6qnfVYNW60W1GLH0iEHtGoG2atdJ26MoCj8dnMHgbvF8trOcA9UeIs0pDMx6EkPEXrZXbsFbVUpCZXfSghnER8eS1jOWrr3jMJoNpxr+NjGbzWRnZ3P48GH27t1LfX09UVFR9OzZk7S0tLD3HkmSJEnfE9FGEydOFOPHjw+7buPGjQIQW7dubbWO/fv3i3HjxgmbzSYSExPFww8/LAKBQGj9iBEjBNDsZ+rUqaEyr732mjix2VVVVeLWW28VUVFRwm63izvuuEO4XK7Q+qlTp4atd8SIEW09fCGEEA6HQwDC4XC0a7uT8fv9YtmyZcLv93dovecDGZvwZFxaJmPTMhmblsnYhHe+xKU9399tHjFqbS6hIUOGnHQCPoCsrCxWtvLU0+rVq09ax7Rp05pdqouPj+fNN99scZuFCxc2mW9JkiRJkiQpHJlEVpIkSZIkqZHsGEmSJEmSJDWSHSNJkiRJkqRG7Z75WpJaIjSN+q3f4t2+HaFpmLMyiRw6FDXMxIbnMiEEZWVlHDx4kEAgQHR0ND169Ag7gePxXPUB3swvZtOBGgQwKCOWKZdnYrcdm7W8tLSU1157jYKCAmyqhYmDRzPy4isxxlix9ozFEH2srF/4WXd4HcV1xRgUA30T+nJJ0iWhXHDh+Dx1HPh2M86KcgwmE+kX9iW5+wUoioIQgpqK79i/ezVejxOTMZ6MHteSkpkV/sm5oB+KN0BZASAguS9kXQnG5nN/tcU+j4/1tW6cQY0Ek5Gr46NIs5hPvqEkSVIHOqWO0YYNGxg+fDg5OTl8+OGHzdYfvdH5xJuki4uLmT59Op999hlRUVFMnTqVOXPmhJJrvvfee7z44ots2bIFn89H//79mT17NmPHjm21PdXV1cycOZPly5ejqiqTJk3iueeeIyqqIfeV1+vlvvvuY9OmTezYsYOJEyeybNmyUzl0qQXBigrKnv0rvsJCRCAACqAomNLSSJoxA9t5MlePz+djzZo17Nu3L5TmQwjBV199xRVXXEGfPn3CbrdmVzm/eedbajwBREO2OtbsKmfh+v089ZMBjO6bwoIFC7j//vsxGo0MvOAiKsrLeeWfrzIooz9v3PlXkpOTiRqWjm1gEjurd7KkbgmBzUdTsgiMqpEL4y7kl5f9ktTI1GZtOLBtCxvfX0pdbTWIhkczt326ivQL+zJs8s3s2PYyVdWfgVKPEA1vYdXmt4n49sdcnn03ZutxHxdVe+GTx6FiF+hawzLVAPE9YPRsSOrdbP8tCeiCvxeXs7KyFndQR1EAAW8cqeS2tARuTYuXUxpIknTGnNKltNzcXGbOnMnatWtDGewB5s6di8vlCr12uVzMnTsXAE3TmDBhAn6/n/Xr1/P666+zcOFCHn300VD5tWvXkp2dzcqVK9m0aRPXXHMN1113HZs3b261PbfddhsFBQXk5eWxYsUK1q5d22QSR03TsNlsPPDAAyedSVtqPxEIUPbMM9Rv2YIhLg5zVhbmzCxMqWkESkopf/av+A8e/L6b2SE+//xzdu3aFZoDKz4+nri4OHw+H2vXruXAgQPNtjlQVcfDS7dSVefHZlaJsZqIsZqwmQ3UePz89p1veXXJe9x7773cdddd7Fyaz3vT/s66R9/n/d+8yiFHKXf+67foAQ3X2kOUfLuPeZvnUaPXkBKRQqY9kyx7FgnWBAqqCnjm62fwab4mbag4UMQXby3C46zFnphMbGoasSmpWCIiKd6+hTXLHqSq5j8IzYCipaHqXVD0VBRDEI94i68/fftYZV4HrHqkYaQoOhUSLmj4iU6Dyt3w3z9AXVWbY/rGkUreKavGqCh0t5npbrOQZTMT1AULDlXwn0rHKb9fkiRJ7dXujpHb7eatt95i+vTpTJgwoclj8HFxcWRnZ7Nu3TrWrVtHdnY2cXFxQEPi1cLCQhYtWsTAgQMZN24cTzzxBC+88AJ+vx9oyK32m9/8hh/96Ef06tWLp556il69erU6VcCOHTv46KOPeOWVVxg6dCjDhw/n+eefZ8mSJaFOW2RkJC+++CL33HNPszQh0unzfLMZb0EhptRUVJsttFwxmTB16UKgogLXxx9/jy3sGNXV1ezbt4+IiAisVmtoFENVVex2Oz6fj2+//bbZ1BWvrivC4Q0QZTFiUo/9yplUlUizAac3wONPzuHKK6/k+T/Pw1ocRLEYMESaGd53CC/c8xRf7dnCxpJtCE2n9MvdlNeVEafEYVKPTXNvNVpJj0xnd81uvir9qkkbdm1Yi9ftwp6YjGpomNBSURTMNhtRSTY0y3a0gAFVieHYx4IBRU9ANejU1q3EUVnXsHjvp1C1B2KzwGg9thOjBeKyoGY/7F7VppjWBoIsL68lQlWJNxmPxVRRSLaYEMDbpTUE9ZNPByJJktQR2n0pbenSpfTp04fevXszZcoUHnzwQWbNmoWiKEybNo1Ro0YxZMgQAPLz88nMzAQaLr8NGDCAlOPSTowdO5bp06dTUFDAoEGDmu1L13VcLleT2akXLlzIHXfcEfry2bBhA7GxsQwePDhUZvTo0aiqysaNG08r4azP58PnO/aX99EkdIHjssp3hKN1dWSdZ1Ld5s0Nl88s5sZM9sdRQLFZcX3+OfYpU9pd99kUmwMHDuDz+YiNjUXX9WbrrVYrJSUlOJ3OJrnP1u2pAMCgErqMdpRBVdC8dRQXfM3/W7AA7wEHmieAGmcJxfLqfpfTNSGN/2z+lKE/Hohe6SMlJpFaxY0QoklbjIoRTdfYVLKJockNKXGCgQDFBdsw2SJonB21SRuMdheqKYDuM4CteQdE6HYU8xEO7t5BRMwlqEXrUASgGKBZHFRQDIh9a9D733TSmH5T66bSH6CrxYQIE9N4g8qBeh+7XG4ujLCGqaG5s+mcOdvI2LRMxia88yUu7Wl/uztGubm5TGn8gsvJycHhcLBmzRpGjhzJokWLmD9/fijH2eTJk5kxYwZTpkyhtLS0SacICL0+mqLjRM888wxut5vJkyeHlsXExNC797H7F0pLS0O510IHZTQSHx/fYr1tNWfOHB5//PFmy1etWnXKST9bk5eX1+F1ngnx27cTXVdH4IRkvkcZ3G6E18fWDz+EU7xX5GyITVVVFW63u8VfME3T0HWdvLy8JgkLa50GhA6+xpHRE+l+LwBFRUVsUr8m3W3DF3Q23OTTKMocQY2jhuqaKoKBIH63D2xQUVHRrD6P7mHnnp2sPNwwmaoeCFBdVQ2A2+trVj4yxYEFCAY1hK95GxVVQzUEKSjYyt7yw1xy4DviPB7qA+Hfb6vfg7t4H5tamcz1qG1GKy5LPJXOAOHOjCDgVI18tnYfe/T2fTCfDefM2UrGpmUyNuGd63HxeDxtLtuujtGuXbvIz8/n/fffb9jYaOTmm28mNzeXkSNHUl5eTl5eHu+++y7QcGlswYIF7dlFyJtvvsnjjz/OBx980KTjc+ONN57WKFB7zJo1i4ceeij02ul0kpGRwZgxY7Db7R22n0AgQF5eHtnZ2edk9mKnplGzZw/GxEQUtfnV2YDXh23wYC5uQ1LgZtueRbE5cOAAH330EVFRUaEHBo7ndDqJjo5m4sSJGAzH8q+9U76JDUXVmE2GZjcRC8AQGYvVnkB1dTU/umcYzmX7sNsMKI053I5Ul7K7bD93jL6F+KhYPH4PdTE+FL9KUlJSkzp1oeN1exnRdwTje45v2IcQfFS8m6pDB7Gf8EcEAGYQ+m5MFgMmc/OnwIRahx6IZugV19KlVxfUL/ejbn6d6Lik5h1dIVBqXERfNJLxV40/aUx7eXys3nWISFUh2tg8Z11lIEiqojD5igHEmdr2cXU2nTNnGxmblsnYhHe+xOXoFZ+2aFfHKDc3l2AwGErOCg0fuhaLhfnz5zfpRABER0eHlqWmppKfn99kfVlZWWjd8ZYsWcLdd9/N22+/fdKbpVNTUyk/YaQiGAxSXV192vcTWSyWUILb45lMpk45QTqr3s4WM2IErnffRS8rx3hCUlTN6UQxGokZM+a0ju1siE23bt1ISEigsrKS+PimT0oFAgE0TaNfv35YrU0v+fzs8iy+Lq7B49eJNB/rHAmg3h/EZDJywy238/rrLzP151PplRpL4JAbNd6IJjQee+tZbGYrN/1oAsKnE9E3ERGEep8HRVFQGzujQggq6yuJtcYyMnNkk3j1Hjac9W+/SdDrxXzcfWBCCJyHBabEeMxx9YigjqIe10FR/KB4UANXk9k7E9WgQp8c2LEMxVMJ0U1HgamrAEsUhj7jMbTh/eprNzLQHsH6WjeRJiOG42Lq13WcmuCmlFiSI2yt1BLe2XDOnK1kbFomYxPeuR6X9rS9zTdfB4NB3njjDZ599lm2bNkS+tm6dSvp6eksXrw4VDZcPrNhw4axbdu2Jp2YvLw87HY7/fr1Cy1bvHgxd9xxB4sXLw5dkmvNsGHDqK2tZdOmTaFln376KbquM3To0LYennQajAkJJN57L4rVQqC4mGBVFcGaGvwHD6K7XNjHjSPyimHfdzNPm9FoZMSIEURHR1NdXY3L5cLj8VBbW4vL5aJ79+4MGDCg2XY5F6Uy4eI0AJy+IB5/w4/TG0AXMLZfKrl/fZJLL72UkdeM5Ff/nsMH333Cix+8yshHJrFy0yfMu/UxIvwmLFl2eo8azIRuE/ALP4fch6jx1lDtrabYVYxRNTKt/7Rmj+v3/NHlXHDZEOpdThzlZdS7nNTV1lJbWoIlMoo+F/0Wk6ELmErQlUoEDoRa3vB/b28GXn5XQ6cIGh7FH3IvCB2q9kFdJXiqoHofBH1w6TRIu6RNMVUUhZlZKXS3WTlQ76fUF6AmEOSw188hX4BLom1M7ZJ4Om+bJElSu7R5xGjFihXU1NRw1113ERMT02TdpEmTyM3N5b777mtx+zFjxtCvXz9uv/12nn76aUpLS3nkkUe4//77Q6Myb775JlOnTuW5555j6NChoXuEbDZbaJ/vv/8+s2bNYufOnQD07duXnJwc7rnnHl566SUCgQAzZszglltuaTKyVVhYiN/vD32hbdmyBYCB58n8Ot+3qBEjMCYl4fzoIzxfbwJdx3bxxURnZxM14moUQ/PLJOei9PR0rr/+egoKCti7dy/BYJCEhAT69u1L3759w/5VoigKf7npEvqnx/DWVwc5WN1wrbt7YgSTB2dw55XdUVWFVatWMW/ePF5++WUWFr+BwWBg7MUj+OuURxky4DJs/ROxXZSAajFye9/bqd5djTPJSZGzCBWVazKuITsrmwFJzTtnBqOJK2+eQuoFvdidvx5nRTlGs5kLLhvChZdfSULXTNKcA9i19V1qalej40UEk4mJHEXvH00iPvWEzskltzQ8gVa4DI5saVjW/Wroe33Dv+24lyzLZuGvfTJYXl7DqionHk2ni9XMuMQYJiTFENPGS2iSJEkdQrTRxIkTxfjx48Ou27hxowDE1q1bW61j//79Yty4ccJms4nExETx8MMPi0AgEFo/YsQIQcMVhiY/U6dODZV57bXXxInNrqqqErfeequIiooSdrtd3HHHHcLlcjUpk5WVFbbu9nA4HAIQDoejXdudjN/vF8uWLRN+v79D6/2+6H6/0Lxeoev6add1NsdG0zTh9/vbfZzOer9welreTtd14XQ6G+rWdKH7g83KHh8Xb9Ar/MG2x0fXdRHw+YQWDIZdr2lB4fW4RTCota3CgE+IgLfN+2+NpuuiLqid1rlzNp8z3zcZm5bJ2IR3vsSlPd/fbf5TrLW5hIYMGdLsEeBwsrKyWNnKkyqrV68+aR3hLtPFx8fz5ptvtrrd/v37T1q31DEUkynsE0bnG1VVQ/f3tEe0tfVr3YqiEB0dfdyOWh9tsxjal4JDURSMYW6yDu1ONWCxtSONi7Hj0naoikKE4Ydw9kiSdLaSSWQlSZIkSZIayY6RJEmSJElSI9kxkiRJkiRJaiQf9zjLOTwBdpY60YSgR2IUqTHH5sgRQrCrzEWV20+UxUi/dDuGYABvYSHC58OYnIK5e7c2ZSYXQrCndg9V3ioijZH0ie+DIhRKSkoIBAJER0eTmJgYti69PkigpA4hBKZEG4aYtt/zEgxoVB50E6w6TIQoY/v+HRQ5DcQlp5GdnR12IsXO4ggEKazzNsTaZiHdasZf76H8QBF6UCMmOYWY5JSTV3QWCwRqcLt3AzoRERdgsSR9302SJEk6q5zSt86GDRsYPnw4OTk5fPjhh83WH00se+JN0sXFxUyfPp3PPvuMqKgopk6dypw5c0JffiUlJTz88MN8/fXX7NmzhwceeIB58+adtD1er5eHH36YJUuW4PP5GDt2LH//+9+bpCB54IEH+OKLL9i+fTt9+/YNPa5/tvIGNP715QE+Kiij1uNHF4Joq4kreyZw9/AeHKqp59UvithV5sIX0DCpCteWbWN08VfYXTWgaag2K9aLLiJ+2jQs3bu3uK9d1bt4o/ANvqv5Dl/Qh1Ex0s3bjW7ubhj9RnRdx2QykZqayhVXXEFSUsOXqQjquL8sob6gEr0uAAIUqwFrj1iiru6KIbLlm4yFEOz5upwdnxdRV1LG9r2bWLj6FY7UlITKxMfH84c//IEePXp0XGDD8Os6rx+uZGWFg6pAEB2INqhc6Kzgki8/Rq0qR+g6JpuNLr37Mfi6G4mOP7fm1tG0eg4efIPKqk8JBGoBgdFoJyF+OJmZd2E0Rp+sCkmSpB+EU7qUlpuby8yZM1m7dm0ogz3A3Llzcblcodcul4u5c+cCDXmkJkyYgN/vZ/369bz++ussXLiQRx99NFTe5/ORlJTEI488wiWXtG2COIBf/vKXLF++nLfffps1a9Zw5MgRfvKTnzQrd+edd3LzzTefyiGfUboueO6T3fwrvxhfQCM9xkpGXAQKsHJbCQ+/vZXH/l3A1oO12C1GMuMjuObAV1y65n2q9x/BGWHH1LUritVG3cZ8yp78I/5Dh8Pua0/NHv6U/ye+rfiWKFMUXaO70tXdFdN+E0eqjuA3+omLi8NsNlNcXMzKlSupqqpqmDH54wPUbSxB+HUMMRYMcQ0Z5+sLqqhdvhfdF2zxGHduKGHTh3vwHC6m+ODnPP3vOcRFxfD7SY/zzoPP8/XvrmTyiH48/PDDoRQ0nUEIwV/3l/L6kSo8mk66xUym1Ux9TTWf1AV5O+siDEkNI0UGg5Gib77i01dfwuN0dFqbOpquB9m791lKSt5G6H6s1nRs1q4gBKVlK/hu91NoWvMcapIkST9E7e4Yud1u3nrrLaZPn86ECRNCo0MAcXFxZGdns27dOtatW0d2djZxcXFAQ+LVwsJCFi1axMCBAxk3bhxPPPEEL7zwAv7G5JrdunXjueee4+c//3mzSSRb4nA4yM3N5a9//SujRo3isssu47XXXmP9+vV8+eWXoXJ/+9vfuP/++zt99KEjbDvsYPWuchIjzSRFWzAaVAyqQnykmS6xEXy9v5qDNR66JUQQaTES4XVz6fbPUc0mqqPiOOTW0BUFQ3Q05owMAocP4fj3v8Pu693d71JRX0FmdCaRpkgMmoGoiihMBhN+k5/S+lJ0dCwWC/Hx8TgcDrZs2ULgsBvvrhrUSBOGaDOKQUVRFdQIE4ZYS8P6nTVh91nv9lP4RQlqwEG0Us6i9cvpntSVJ299iMt7ZVAv0hG2a3gxx8SD993JW2+9RW1tbafEeru7no+rnMSbjCRbTJhUBd3vQ6mpJN7r4UhcCjsSuqCoKtaoKGJSUqg6dJA9+Rs6pT2dweHcTHXNF5jNyZjNiaiKEUUxYDbHY7Wk4XB8Q3XNuu+7mZIkSWeFdl9KW7p0KX369KF3795MmTKFBx98kFmzZqEoCtOmTWPUqFEMGTIEgPz8fDIzM4GGy28DBgxocnlr7NixTJ8+nYKCAgYNGtSm/a9evZprrrmGoqIiunXrxqZNmwgEAk1yqvXp04fMzEw2bNjA5Zdf3t5DDPH5fPh8x/6SPpqELhAItJhh/VQcrevov59/V4bXr5Fqt6ALvUlZXdfxBXSMqoJAIISgy4Ed2DwuamMSMSsq3oCGw+MnNsIEqoISFY3788+x3/Yz1IiIUF0V9RVsKd9CjCkGIRrqMteaUf0qmkXDpJjwaT4cXgexllgArFYr+/bto7/WFeHXUKONzdqIAYQCdYUVmPrFNjve4sJKvG4/0VoJpa5ath/8jl9ffy9G1QAIzAYfB9y9GeDJ4xcT+vG3fwR45513uPvuuzss5ketqXTgCeqkGA0IveE4PE4HQtMwW4yoQvBtbAqXVR1q2EA1YDCZ+C5/PX2uHtWm+7c6w4nnTGsqKlaj6wFUg63Ze6WoZkBQUfEZsTFXd0ZTz7j2xOaHRsamZTI24Z0vcWlP+9vdMcrNzWXKlCkA5OTk4HA4WLNmDSNHjmTRokXMnz8/lONs8uTJzJgxgylTplBaWtqkUwSEXh9N/dEWERER9O7dO5R6obS0FLPZTGxsbLO621NvOHPmzOHxxx9vtnzVqlVEHNfB6Ch5eXkAbNqv4vFAebm7WRlvEDRdwevXQnnnulWUEtA0fMGGS1cBDaqqa/G7GybdVL1elECAgn//G81uD9VVrpVTWVdJhBKBT2noAMY6Y7EGrfjVhlG8oAhSVVMVeq1pGrqu8517F2meaHx6+IzFJr9CcL+T9St3N1tXd9CE220kQtRT6awFICUmEZ+/oQ26DsGgiVqXjrtkN1FRUXzxxRdNUrx0lK8ssXiMNspdxy77BdxOgloQ3aegYKBKKJSXHcvxp/m8uD31rFyx4ntPdXL0nGmN2bIFg6Eel6s87HpF8eJwFLD7u5YnXz0XtSU2P1QyNi2TsQnvXI+Lx+Npc9l2dYx27dpFfn5+6J4Po9HIzTffTG5uLiNHjqS8vJy8vDzeffddAObNm8eCBQvas4uTGjJkSChPWmebNWsWDz30UOi10+kkIyODMWPGYD+ug3G6AoEAeXl5ZGdnYzKZOPx5Efs3HSYpwdZsRMIX0DlUX4vNYiA5ueFyo7E2DaPRgMVoQFMM6IpOYnwUMRENncdgZRWq1Ur/669vMmJUVV/Fp2s/RUUlxtJQl9loxug0opgUdHSELkiISQiNGNXV1WEwGOid2Rd9ay32BEvYUROt2oepSyQXjr+q2bqirZV8Vb4fgz+CJHtDvUdqyund5YKGbf02zKYgsdEq7tQLcbvdXHXVVYwfP/70Ah3GocOV7C6tIdliCh2H06Di9HkxWswIi4XEoJfklOTQNq6qSqLjExk/ceL3OmJ0/DnTmv3791BRWY7Nlhx2fX29j9jYAfTq2fHx/T60JzY/NDI2LZOxCe98icvRKz5t0a6OUW5uLsFgsMlf7kIILBYL8+fPb9KJAIiOjg4tS01NJT8/v8n6srKy0LpTlZqait/vp7a2tsmoUVlZ2WnVC2CxWEIJbo9nMpk65QQ5Wu/VvVNYsa0Mt08nxtZ0P4oisJoMGFQFUFAVhcNZ/aiPsBNZ56TSGoPVZCAmwoyqKAhNQ9TVET1mDJYT7ttKNaVyWcplrD64mhhrDKqiosVq6GYd1a/iNXqxGCzEWmNRFbXhMp7Px4ABA4jrnUbNTheKT0c9oY0ioKMAEf0Tw8Yps28i21cfob46lZRoDxdn9eH9/P9yZZ/BmIwW/LqFnjHbsERG8syyLZjNZn760592SsyvSYxlWYUTpy6INTWM/kTaY3BXVeDTdYSicomjDLWxA6QFg+jBAL2GDMPcSlqNM6Ut52JS8kiqqj9B1zwYjVFN1mlaPaqikJx0zTn9oRdOZ/2eng9kbFomYxPeuR6X9rS9zTdfB4NB3njjDZ599lm2bNkS+tm6dSvp6eksXrw4VDZcPrNhw4axbdu20OUfaBias9vt9OvXr80NPtFll12GyWTik08+CS3btWsXxcXFDBs27JTr/T71T7eT3S+FGo+fUqcXX1AnoOlUun0ccXi5vEc8WQmR7K/y4PQGqDPZyB8wgmBQJ8FdRWakiqJpaA4H/uJiLFmZxFx/Xdh9TbpwEqmRqRS7inH5XQTUAI5kBwE9gMVvIdWaCgLq6+uprq4mLi6OgQMHYkqLxNovAd0TRHP6EEEdoelobj+aw4c5Mxpr7/iw+7RGmuh/VReEJRanSOP2K27kcHUpv130NGsKv0MN7KXO8Sm3v+fhpVf/yZQpU5rmDutAfSOtjE+MoTaoUeILNHSGTGaC8cnUWCLpUlVCn/KD6FqQepcTR3kZSVnd6TX0ik5pT2eIsQ8kIWEE/kAlPl85uu5H1wP4/JV4faXExg0lPv7cOR5JkqTO1OYRoxUrVlBTU8Ndd93V7ImxSZMmkZuby3333dfi9mPGjKFfv37cfvvtPP3005SWlvLII49w//33NxmVOTq/kNvtpqKigi1bGkYMjnae8vPz+fnPf84nn3xCly5diImJ4a677uKhhx4iPj4eu93OzJkzGTZsWJMbr/fs2YPb7aa0tJT6+vrQfvr163dW/OV/PEVRmDGqJ8l2Cx9+W0KFy4sAoi0mfnJpF6Ze0Y2SWi8L1xex7bCDWk+AiszLsEVHMvrAV0TXVBAodaBabUSNGEH8z3+OKS0t7L66x3Tn90N/z792/IvtVdtx+BwYo4z06NWDTFcmSr2Cw+HAZDLRs2dPLr/88tCThvZrMjBEm6n/thLN1XAPkmoxYBuUTNSV6ajmlu+/uXBICiaLgR2fm1AMJn7/k0d5ffUrPPvvOaEy6enpvPzyy83uTetIiqIwMyuFZIuJZeU1lPuDCAH2uDiuMOr0L/wOraYal9AxWW1cePmVXDb+BmxR5868P4pi4IIeD2K1pFFe8RE+fzkN8xjFkJ7+U7p2mYKqti8RrSRJ0nlLtNHEiRPF+PHjw67buHGjAMTWrVtbrWP//v1i3LhxwmazicTERPHwww+LQCDQpAzQ7CcrKyu0/rPPPhOAKCoqCi2rr68X//u//yvi4uJERESEuPHGG0VJSUmTekeMGBG27uPrORmHwyEA4XA42rxNW/j9frFs2TLh9/ubrXN7A2JLcY3YdKBaVLl9Tdbpui6KKtzi6/1VYmeJU2iaLnS/X9QXFoq6Td8I/+HDbW6Druui2FEsNpdtFjurdoqgFhTBYFCUlJSIAwcOiOrq6ha31XxB4St2Cu8Bhwi6mx9Da4JBTZQXO8WRrXuE49v14pv/vineeWux+PTTT4Xf7281Nh3NHQyKbxx14utat6jwNZyXAZ9PlO7dLQ7vKhSu6qpOb0NbnWpcAgGnqHVsEbW1m4XfX9M5jfuenclz5lwjY9MyGZvwzpe4tOf7u80jRsuXL29x3ZAhQxBCnLSOrKwsVq5s/cmXk9UzcuTIZmWsVisvvPACL7zwQovbrV69+qTtOxtFWoxckhEbdp2iKHRLjKRbYuSxhaoJa9++7d6Poihk2DPIsGc0Wd6W+7RUswFzxqmNoBgMKkkZ0ZARDVzAoAHDOH7ihjP5iGikwcAge9OnDY1mMyk9ep6xNnQ2ozGaGHvbJ0+VJEn6oZFJZCVJkiRJkhrJjpEkSZIkSVIj2TGSJEmSJElqJDtGkiRJkiRJjWTHSJIkSZIkqZHsGEmSJEmSJDWSHSNJkiRJkqRGsmMkSZIkSZLUSHaMJEmSJEmSGrV55mvp2KzcTqezQ+sNBAJ4PB6cTuc5nb24M8jYhCfj0jIZm5bJ2LRMxia88yUuR7+325KlQ3aM2sHlcgGQkZFxkpKSJEmSJJ1tXC4XMTExrZZRRFu6TxIAuq5z5MgRoqOjURSlw+p1Op1kZGRw8OBB7HZ7h9V7PpCxCU/GpWUyNi2TsWmZjE1450tchBC4XC7S09NR1dbvIpIjRu2gqipdu3bttPrtdvs5feJ1Jhmb8GRcWiZj0zIZm5bJ2IR3PsTlZCNFR8mbryVJkiRJkhrJjpEkSZIkSVIj2TE6C1gsFh577DEsFsv33ZSzjoxNeDIuLZOxaZmMTctkbML7IcZF3nwtSZIkSZLUSI4YSZIkSZIkNZIdI0mSJEmSpEayYyRJkiRJktRIdowkSZIkSZIayY5RJ3jhhRfo1q0bVquVoUOHkp+f32r5t99+mz59+mC1WhkwYAArV65ssl4IwaOPPkpaWho2m43Ro0eze/fuzjyETtPRsZk2bRqKojT5ycnJ6cxD6DTtiU1BQQGTJk2iW7duKIrCvHnzTrvOs1lHx2b27NnNzps+ffp04hF0jvbEZcGCBVx11VXExcURFxfH6NGjm5X/oX7WtCU2P9TPmvfee4/BgwcTGxtLZGQkAwcO5J///GeTMufTeQOAkDrUkiVLhNlsFq+++qooKCgQ99xzj4iNjRVlZWVhy3/xxRfCYDCIp59+WhQWFopHHnlEmEwmsW3btlCZP/3pTyImJkYsW7ZMbN26VVx//fWie/fuor6+/kwdVofojNhMnTpV5OTkiJKSktBPdXX1mTqkDtPe2OTn54tf/epXYvHixSI1NVXMnTv3tOs8W3VGbB577DHRv3//JudNRUVFJx9Jx2pvXH72s5+JF154QWzevFns2LFDTJs2TcTExIhDhw6FyvxQP2vaEpsf6mfNZ599Jt577z1RWFgo9uzZI+bNmycMBoP46KOPQmXOl/PmKNkx6mBDhgwR999/f+i1pmkiPT1dzJkzJ2z5yZMniwkTJjRZNnToUPE///M/QgghdF0Xqamp4i9/+UtofW1trbBYLGLx4sWdcASdp6NjI0TDh9UNN9zQKe09k9obm+NlZWWF/fI/nTrPJp0Rm8cee0xccsklHdjKM+90399gMCiio6PF66+/LoT4YX/WnOjE2AghP2uON2jQIPHII48IIc6v8+YoeSmtA/n9fjZt2sTo0aNDy1RVZfTo0WzYsCHsNhs2bGhSHmDs2LGh8kVFRZSWljYpExMTw9ChQ1us82zUGbE5avXq1SQnJ9O7d2+mT59OVVVVxx9AJzqV2HwfdX4fOvM4du/eTXp6Oj169OC2226juLj4dJt7xnREXDweD4FAgPj4eOCH/VlzohNjc9QP/bNGCMEnn3zCrl27uPrqq4Hz57w5nuwYdaDKyko0TSMlJaXJ8pSUFEpLS8NuU1pa2mr5o/+2p86zUWfEBiAnJ4c33niDTz75hD//+c+sWbOGcePGoWlaxx9EJzmV2HwfdX4fOus4hg4dysKFC/noo4948cUXKSoq4qqrrsLlcp1uk8+IjojLb3/7W9LT00NfaD/kz5oTnRgb+GF/1jgcDqKiojCbzUyYMIHnn3+e7Oxs4Pw5b45n/L4bIEmn45Zbbgn9f8CAAVx88cVccMEFrF69mmuvvfZ7bJl0Nhs3blzo/xdffDFDhw4lKyuLpUuXctddd32PLTsz/vSnP7FkyRJWr16N1Wr9vptzVmkpNj/kz5ro6Gi2bNmC2+3mk08+4aGHHqJHjx6MHDny+25ap5AjRh0oMTERg8FAWVlZk+VlZWWkpqaG3SY1NbXV8kf/bU+dZ6POiE04PXr0IDExkT179px+o8+QU4nN91Hn9+FMHUdsbCwXXnjhOXPenE5cnnnmGf70pz+xatUqLr744tDyH/JnzVEtxSacH9Jnjaqq9OzZk4EDB/Lwww9z0003MWfOHOD8OW+OJztGHchsNnPZZZfxySefhJbpus4nn3zCsGHDwm4zbNiwJuUB8vLyQuW7d+9OampqkzJOp5ONGze2WOfZqDNiE86hQ4eoqqoiLS2tYxp+BpxKbL6POr8PZ+o43G43e/fuPWfOm1ONy9NPP80TTzzBRx99xODBg5us+yF/1kDrsQnnh/xZo+s6Pp8POH/Omya+77u/zzdLliwRFotFLFy4UBQWFop7771XxMbGitLSUiGEELfffrv43e9+Fyr/xRdfCKPRKJ555hmxY8cO8dhjj4V9XD82NlZ88MEH4ttvvxU33HDDOfkoZEfHxuVyiV/96ldiw4YNoqioSHz88cfi0ksvFb169RJer/d7OcZT1d7Y+Hw+sXnzZrF582aRlpYmfvWrX4nNmzeL3bt3t7nOc0VnxObhhx8Wq1evFkVFReKLL74Qo0ePFomJiaK8vPyMH9+pam9c/vSnPwmz2SzeeeedJo+cu1yuJmV+iJ81J4vND/mz5qmnnhKrVq0Se/fuFYWFheKZZ54RRqNRLFiwIFTmfDlvjpIdo07w/PPPi8zMTGE2m8WQIUPEl19+GVo3YsQIMXXq1Cblly5dKi688EJhNptF//79xYcffthkva7r4v/9v/8nUlJShMViEddee63YtWvXmTiUDteRsfF4PGLMmDEiKSlJmEwmkZWVJe65555z7ov/qPbEpqioSADNfkaMGNHmOs8lHR2bm2++WaSlpQmz2Sy6dOkibr75ZrFnz54zeEQdoz1xycrKChuXxx57LFTmh/pZc7LY/JA/a/7whz+Inj17CqvVKuLi4sSwYcPEkiVLmtR3Pp03QgihCCHEmR2jkiRJkiRJOjvJe4wkSZIkSZIayY6RJEmSJElSI9kxkiRJkiRJaiQ7RpIkSZIkSY1kx0iSJEmSJKmR7BhJkiRJkiQ1kh0jSZIkSZKkRrJjJEmSJEmS1Eh2jCRJkiRJkhrJjpEkSZIkSVIj2TGSJEmSJElqJDtGkiRJkiRJjf4/HldHLrXMS6UAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -285,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [
     {
@@ -460,7 +461,7 @@
        "99                  Guinea  "
       ]
      },
-     "execution_count": 13,
+     "execution_count": 84,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -469,6 +470,42 @@
     "cafs[cafs.allele == \"A*24:02\"].sort_values('allele_freq')"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is important to do a sanity check on any apparent outliers. In this case the apparent outlier of Guinea is actually caused by our search returning studies for Guinea-Bissau and Papua New Guinea"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['Guinea Bissau Balanta', 'Guinea Bissau Bijago',\n",
+       "       'Guinea Bissau Fula', 'Guinea Bissau Papel', 'Guinea Bissau',\n",
+       "       'Papua New Guinea East New Britain Rabaul',\n",
+       "       'Papua New Guinea Eastern Highlands Goroka Asaro',\n",
+       "       'Papua New Guinea Karimui Plateau Pawaia',\n",
+       "       'Papua New Guinea Madang',\n",
+       "       'Papua New Guinea West Schrader Ranges Haruai',\n",
+       "       'Papua New Guinea Wosera Abelam'], dtype=object)"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "aftab = pd.read_csv(\"../data/example/multi_country/Guinea_raw.csv\")\n",
+    "aftab.population.unique()"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -488,7 +525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 86,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -518,12 +555,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 87,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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UCsWOiUQi3HDDDdx9990tLvdU8tXW8Oncf7F/87eEgzq6loAsO5H0IEH3WgK16zm4vYZVb+/EXxdutpzAtxV4PilG9UQwxJkxJFmRzAbCe+uo+3APSk19DOqiCg/vKuHjKg9GSaK91UymxYxPUSnYu59Zmzeg1x2obylK7ACWODj0DXz0Z6jY8QtF5afpus4NN9zAvHnzePLJJykrK8Pn8/H222+zb98+LrvsskZLxPyUgwf/l4MH56BEPVjMGdis2ciSiarqz9i5cxqRSM0puhtBEI4n8O13lP9tOuGdOzHEx2PKzsaQkEB41y4q/vEP/OvW/dpVFM5CrU6MfD4f77zzDnfffTejRo2KtQ4BJCYmkp+fz+rVq1m9ejX5+fkkJibG9r/wwgv8z//8Dx07dmyybIfDwcsvv8ydd97Z4nXOdF3nueee4+GHH2b06NH06NGDefPmUVpa2qC1adq0adx3332cd955rb3lU6Loqy+oLS3BmZhGOGhEkiWMFhNGqwtJNhGo24w9PoK7IsCu9eVNlqH6o/i/KUMySBgTLEhGGUmSkK1GDEk21JoQgW/rk4RlVW62+oK0s5pJNBmRJQmTLJFuknEFDrPU2YOdKReAyQqSXJ8YJXUEbxl8O++XDM1xffbZZyxevJi33nqLP//5z6Snp+NwOLjppptYtWoVtbW1vPjiiy0uLxDYT3nFUgxGJxZLOrJsQpJkTCYXNms7/P5dVFZ+fArvSBCEpui6Tu2CBWgeD6bsbGS7HUmWkW02TNnZaD4/tW+9ha6qP12YILRCq1+lvfvuu+Tl5ZGbm8u4ceOYMmUKU6dORZIkxo8fz+DBg+lzpHlz3bp1tGvX7qRWeP/+/eTk5PDZZ58xaNAg9u3bR1lZWYMWJpfLRd++fVmzZg0333zzCV8rHA4TDh9rrTm6Om80GiUajZ5wuZqqsmfDWowWC+GgiqZqSLIOug6ShMHkIBqqIejei9F6Lvs2V5LXPx2DsWEeG9pdg+qLICda0HSt4UUkwGoguLMGy8VpLKuswyyBER1d+8FknMFaEiK17LW2ZZWpPZ0jlQ3LsSVB8RrU2kPgTD/hez5RR+N89H/nzp1Lbm4uI0eObPQ7SE9P55ZbbuH111/n0UcfbVH5VVWrURQfVmu7JmIoI0kWyiuWk5o65qTNPn4y/DguwjEiNs07k2IT2bOH0K5dyMnJ6OiNJhGWU5IJ792Hf+tWLD+zfyGcWbH5JZ0tcWlN/VudGBUUFDBu3DgARowYgdvtZuXKlQwaNIj58+cza9YsRo0aBcCNN97IpEmTYsefDCaTidzcXOz2+r4zZWVlQP2X4g+lp6fH9p2oZ555hmnTpjXavnz58tj1T4QaiVBRdri+ZUZVUVUZyQDhH/SX0RQVd20lJmcdukfioyXLkH+0OHByhZl0n5Ww6mnyOrIqYVAl1i9dzq7ENFSg/Edf/tZoHU5FQVVVSoNqo9dQshbBovhYv/xDfNa2J3zPP1dhYSEAW7ZsITExkY8++qjJ4zRN4/DhwyxdurRF5ZrM6zAZfXi9lU3ul6QgUMxHHy3idByrcDQuQmMiNs07E2Jj3b+f9JoaoroGfl/jA3QdU20tewoLCe7bd9KueybE5tdwpsclEAi0+NhW/Ze+qKiIdevWsXDhwvqTjUZuuukmCgoKGDRoEBUVFRQWFvLee+8B8NxzzzF79uzWXOIntW3bNraA7Kk2depU7r///thnj8dDdnY2w4YNIz4+/oTL1VSV/+zYSNDnRZYc1EWCaChYzGaQJHRdJ6oZcCWlYbC4sNhMjLzyMmTDj1qMttXgW1FMfIIFSW7cmqH5okhGmfxR/XhvTyl7g2HSLT/KroJGqKzEaJDJssmNF5EN1oBu47Lh14Aj9YTv+URFo1EKCwvJz8/HZDKxcOFCvvzyS0aMGIEsN34TvHjxYrKyslq83MnhMj+HDm3Dak1BkhqXFw4fxmJpw7ndrjrtWox+GBfhGBGb5p1JsYns3UvZ558jOxzIDkej/VoggKbDOcOHY8nN/dnXO5Ni80s6W+Jy9I1PS7QqMSooKEBRlAar1uu6jsViYdasWQ2SCKhfj+vH2062o32RysvLadOmTWx7eXk5PXv2/FllWywWLBZLo+0mk+nnPSAmE+f0vpiNHy/GlhSPwSCjRqXY0Hg16sNgtGGP74jfo9H14lQs1sb1MHROIvh1GbpPQXY13K9rOnpYw949FbPDyhVpCTx/oJwoYP5hQmFLpMachFPxMzByoGGyoWsQrIW8K5ETMvk1HY35hAkTeP3111m4cGGj16T79u1jwYIF/OlPf2rx7yc15VLKy/6Nqrgxm5Mb7NO0KLoeJS1tGObTdDX6n/0snsVEbJp3JsTG2KUL1tw8gps2YXA4G/xhous6WlU1lq5dcXTrhtTEH0kn6kyIza/hTI9La+re4qdJURTmzZvHjBkz2LhxY+xn06ZNZGZmsmDBgtixTS30eqrk5OSQkZHBJ598Etvm8XhYu3Yt/fr1+0XqcCLyLrmU5KxsfDUVmO1RdE0jGgoTDdahayr2xPPxe0wktXHQ+aKm+/bIdhPOvvXJoFIbQouo6KqOFoiiVAcxJlux96pvARqR4qKH08bBUJTqiEJU0wlrGqVRFa8jg6t9m+hU+S1E/PXD9UNuqN4Driy44NZfLC4/ZcCAAdxwww3ceuutPProo+zZs4eKigpee+01Lr30Utq0acPkyZNbXJ7Nlk16xjWoWoBQ6DCqGkbTFCLRGoKhgzideaSlDj+FdyQIQlMkSSLpllswJiQQKT6A6vOhKwqq30+0uBiDy0XSuHEnNSkSBGhFi9HixYupra1lwoQJuFyuBvvGjBlDQUEBEydOPG4Zu3fvxufzUVZWRjAYjM1j1K1bt9hf5Nu2bSMSiVBTU4PX640dc7T1p6SkhCFDhjBv3jz69OmDJElMmTKFp556is6dO5OTk8MjjzxCZmYm11xzTezaxcXF1NTUUFxcjKqqsXLPOeccnE5nS8Nw0thdCQy5426+/ehDirduxu+pAsxIhjhsrh44ks6jbZcEzh/cDnt8860VtvNTkcwG/OvLUGvCaJqOZJax5iUR178txoT6lqQ4o4EnO2dRcKiSlbVeDoejyBKkmY1cm9WRG9pcivTt3vpkSIvWz2OUMxAuvhtSzvmFovLTJEnizTffZOrUqTz77LM8+eSTse1XXXUVr7zyCklJSa0qMzvrt5hMLsrK/kM4XA7Uz2OUlnYF7bLHYzIlnPwbEQThJ9nO6076gw9S8+abhHcWodbVIpnMWM/rTtLYsdh+5lsBQWiS3kJXXnmlPnLkyCb3rV27Vgf0TZs2HbeMgQMH6kCjn3379sWOad++fZPHHLVv3z4d0D/77LPYNk3T9EceeURPT0/XLRaLPmTIEL2oqKjBtW+77bYmy/1hOT/F7XbrgO52u1t8TkvUlB3WF8z+l168bZt+eE+NfnhPne6tCbWqDE1R9XCJVw/td+vRmuBxj60IR/Rv6nz6d26/HlDUYztURdcPf6/rB77W9eq9uq5pJ3I7J1UkEtE/+OADPRKJNNrndrv1xYsX6++//76+f//+n30tRQnpbvdmva5ugx4Klf/s8k6l48Xlv52ITfPO1NhomqaH9uzV/Ru+1UO7d+vaKfhv05kam1PtbIlLa76/W9xitGjRomb39enTp9FQyqZ8/vnnP3nM/v37j7u/Q4cOja4lSRJPPPEETzzxRLPnzZ07t8GcS6cTZ1IyttR0Ms4554Tf4UoGGXNmy1q+Us0mUs1NXEc2nHazXB9PfHx8bATkyWAwWIiPPz3muRIE4RhJkrB0zPm1qyH8lxAvZwVBEARBEI4QiZEgCIIgCMIRIjESBEEQBEE4QiRGgiAIgiAIR5x+axwIrRYMHiIYOogsmXA68zAaWzf9QHV1NW63G6PRSEZGRmzqhP1VPvZv2Y2hdDvd4kIk9eyJ1PZ8aOG8IbqqEz3sQwspyA4zpgx7g0na3G43K1aswO/3c+6553LhhRc2W1ZYDbO1dithNUyaPY0O8R2anIla13XqykrxVldhMJlJ65CDyWKN7S+tC7K/2o9RlslrE0e89Vgn9H2BMCXhCBZZppvTisNgaNF9tpYSVak66EOJqDgSLCSk20+rWbUFQRD+m51QYrRmzRoGDBjAiBEjWLJkSaP9R0d//XCSx7lz53L77bc3WV55eXmjpSi+/PJLBg4cSPfu3WNzDjWnpqaGyZMns2jRImRZZsyYMTz//POx+YlCoRATJ05kw4YNbN++nSuvvJIPPvigxfd7ugqFyyg+8Bp17g2oqh9JkjGbU0hPu5I2ba5Hlo//662treWrr76ipKSESCSCJEnExcWR3rEbK3eH+HbrPgIRFVlTSY54GP7W89yYV4frjoeQsi86ft121uL7uhS1JoyuakhGGWO6nbj+bTFk2nnkkUd44YUX8Pv9sXMuuugiCgoKOO+8YyPDdF3n+8j3LF21lIpgBaqmYjVaOTf5XG479zY6uDrEjq0rL2PD4vc5vHsnkVAIWZZxJiXT7bLBpJ5/Ma+t3s/Xe6vxhRVkSSLJYWbUeW3o3yOD10or+dYTwK9qGCSJdLOR6zOSuD49EfkkJS26rrN7QwU71hzGVxtGU3VMFgOp7eLoOTSbxIzGyx4IgiAIv6wTepVWUFDA5MmTWbVqFaWlpbHtM2fOxOv1xj57vV5mzpwJwE033cThw4cb/AwfPpyBAwc2Sorq6uq49dZbGTJkSIvqc8stt7B161YKCwtZvHgxq1at4q677ortV1UVm83GH/7wB4YOHXoit3zaiURq2LlzGlXVnyNLJmzWbCzmDJSoh4MH53Dw4P8e93yPx8PSpUvZs2cPRqORxMRE4uLiqPCEmL58Dyu2HsLoq6NNqJJUzYvbEsdbKZdSsCUF7wv3Qcm3zZYdKqrB/fF+lKoQssOIIcmKZDUSOeSjbsle7rljIn/729+49957OXDgAMFgkEWLFhEOhxk4cCC7du2KlbV432I+D31OZaCSVFsqWXFZ2Iw2vin/hmfWPUOJrwQAb00Vn855hQPfb8JoMpOQlo4zMYmAu46vF/6bZ1+cx/Jt5RhkiexEO21cVgJhhdfWH+DWtTtZWePFIsu0t5rJMBupjiq8dKCceSVVJ+cXBhR9Xcb6pfvx14Wxx5txpVoxmmVKd9byxTs78VQFT9q1BEEQhBPT6sTI5/PxzjvvcPfddzNq1KgGcwMlJiaSn5/P6tWrWb16Nfn5+SQmJgJgs9nIyMiI/RgMBj799FMmTJjQ6BoTJ05k7NixLVrSY/v27SxbtozXXnuNvn37MmDAAF588UXefvvtWNLmcDh4+eWXufPOO2Nrq53pKiqX4ffvwmbNxmRyIUkysmzCYknHYHRSXrGUQGB/s+dv2bKF6upqkpKSsFqtSJKE0Whkr5pETdSInRB2OYrBaMCERprqwSoprEjrTdH3GuqX/4Im5q7SFQ3fmsPoUQ1jkhXJZECSJGSLAWOylaK9u3h13mvMnDmTv/71r7Rr1w6r1cqVV17JypUrcTqd/PWvfwWgLlTHwj0LkZHJcGRgNpiRJZk4cxzt4tpR4i1h0Z76+bV2rF5JbVkprvR0LA4HkixjMJmIS07Br0rIezfQwaaQaDdjkCVMBpm0eCuRNBuHolFSZAMuowFZkjDLMpkWMzaDzLvltRwOR3727yvkj7Lty1IMBom4JCtGk1w/N4vNSHyqDU91iKK1ZT/7OoIgCMLP0+pXae+++y55eXnk5uYybtw4pkyZwtSpU5EkifHjxzN48GD69OkDwLp162jXrl2T5cybNw+73c7111/fYPucOXPYu3cv8+fP56mnnmp03tFXckcneVyzZg0JCQn07t07dszQoUORZZm1a9dy7bXXtvYWY8LhMOFwOPb56Oq80WiUaDR6wuX+2NGyWlqmrutUVCxHkiwgyWi61mC/weAiFCqmqmo1bdq0bXS+qqoUFRXF+hJpWv35qg473AbMaghkCJusGKOh2HkJqp8SUzIbbOeQu2EjtoE7Ialjg7IjxV6iNUHkOFOjegG8v+VjEu0ubr3mN43u1+FwcNddd/HUU0/x4osvsrZyLbWhWpySs37RSK1heU6Tky8PfckNHcaw59tvMFltR+LRMGGrUU2YFS+uugO47ccmsNQAT7wRSdFw+yPEmxv2KUoyyBwIR1lV5ea6tIRG99IaxdurCHojOJOtjeqHBGabgQNbq+l2WQZm60//s2ztM/PfRMSmeSI2zROxadrZEpfW1L/ViVFBQQHjxo0DYMSIEbjdblauXMmgQYOYP38+s2bNis1GfOONNzJp0qTY8T8uZ+zYsdhstti2Xbt28cADD/DFF19gNDZdNZfLRW5ubuxzWVlZo1dxRqORpKQkysp+3l/gzzzzDNOmTWu0ffny5djt9p9VdlMKCwtbeKSCzX4Q0NH1iiaPkCUfW7au47vv4hqfrShUVlYCEAgEYtvDmkwgbMGoKWAAFalRMiLpKm7ZSqDWy3efLKXO0TAxiq81keWxE46qTdbrYGUJWQkZrPtiLUFn42MCgQDhcJj333+fPbY9BMIBrLI1Vt8fCuthInqExR/9B29FOUgy/nDjh98fArumEaitpMJ4LF6KQSKUkoqm6tR5fJij3sbnyka+2lSGtYl9reE/aMTnMxPSmi5HU0BXJT5eWojB+tOzyB/V8mfmv4+ITfNEbJonYtO0Mz0uP/yu+ymtSoyKiopYt24dCxcurD/ZaOSmm26ioKCAQYMGUVFRQWFhIe+99x4Azz33HLNnz25Uzpo1a9i+fTtvvPFGbJuqqowdO5Zp06bRpUuXZutw7bXX/qxWoNaYOnUq999/f+yzx+MhOzubYcOGER8ff9KuE41GKSwsJD8/v0VLgui6ztZtSwiHy7BY0prYrxEKBcjKupg2GSMb7VdVlbfffptgMEhc3LHESdXBETDiixoxoWLQdeQfjEDTACSZBDWIIymeS4ZeCYkdGpQdOejFU7uXeIcJydT4TW371CxWbF1N7wF9iMtMbLT/u+++w2azMWbMGL6q+IrvNn6HFtBIT0tvNHKrOlRNoiGRqy+9juVFewgH/DgSGy8gW6nUoUdlbElpDZJoDTgkG/FJOgkOC+mJtgbnabpOIBylf3YOI39mi9H+zdWsq9yHM8mKbGjcmTvgiWA0yYwYdSkmy0+PhmvtM/PfRMSmeSI2zROxadrZEpejb3xaolWJUUFBAYqikJmZGdum6zoWi4VZs2Y1SCIA4uLiGm0DeO211+jZs2eD4dler5f169fz3XffMWnSJKD+FY+u6xiNRpYvX87gwYMblZWRkUFFRcNWE0VRqKmp+dn9iSwWCxaLpdF2k8l0Sh6Q1pSbljac4uLXQFeR5YbnRKK1mIzxpKZc2mR5JpOJvLw8vvnmG3Rdx3BkWLoMdHWpfBk0YVPCWKMh+MF3eK3RiSMS5KLwLhwXXYiceg78KFkxtk8gmGxDqQoiJ1obJDO6rnNDjyt49qPZvPbOXP785z83OLeqqorZs2czduxYnE4nfU19eXPHm5T6S8mQMhokaaqm4o/6Gdp+KIlxSZzTuy+bCpeCpiH/aJh9ohShzGjFndABg3SsDBmI8yj4Eoy4HGakH01DUBWOkmgyMjAl4Wf/vrPzktnyeSkhbxRnYsNnStN0oiGVTr3SsDutzZTQtFP1LJ4NRGyaJ2LTPBGbpp3pcWlN3Vvc+VpRFObNm8eMGTPYuHFj7GfTpk1kZmayYMGC2LHjx49vMFT/h3w+H++++26jTtfx8fF8//33DcqeOHEiubm5bNy4kb59+zZZXr9+/airq2PDhg2xbZ9++imapjV7ztkgLXU4TmdXgqFDRKI1aJqCqoYJhQ6jqgHSM0Zjs2U3e3737t1JTU2lrq6OQCCAqqpEo1Hay1Ukm1WCWPHqFqKKTlg3UGZwEdFkrihfyznnm5H7T2yUFEH9YrbOS9oimQ2oNSG0sIqu6mghBbU6SMecTtx71yQeeOABpkyZwrZt26iqquLtt99mwIABRKNRHn74YQBcFhfXd67vg1bqLyWkhFA0BXfYzUHfQdrFt+OqTlcBkNd/IElts6mrKCPo86KpKkokjKeyAqdJgi59ORCQqfaHUVSNsKJS5g5hrQzTwWqmSlOpjSoomk5I1TgUihDRdX7TJpl0y8//j4HVYaL7ZfX9vTzVIaIRFU3VCfmjuCuDJKTZye17dgwMEARBOJO1uMVo8eLF1NbWMmHCBFwuV4N9Y8aMoaCggIkTJ/5kOe+88w6KojTqdyTLMt27N1zZPS0tDavV2mD7woULmTp1Kjt27ACga9eujBgxgjvvvJNXXnmFaDTKpEmTuPnmmxu0bG3bto1IJEJNTQ1erzc2N1LPnj1bGoLTismUQG6XRzl4cC41tWsIRw4DMhZLOhkZo8lIv/q45zudTkaOHMnXX3/NgQMH8Hg8yLJM22QXj/TN5Ys9Ib7aqFAZsiOrKqnBWkYGNnLdRQpxt82CjOZXobeek4A0siO+tYdRKgJoqo5klDDnuHBe0pZn73yetPZtmDFjBs8//3zsvEGDBvHhhx/SoUOH2Lbh7YezddNWSpwllAZKUTUVm9HGpW0vZVy3cWQ46pMJR0IiQ+64mw1L/0PJ9q14q6uQZJn41HTOHTiYa867iLlfHeCLXZWUukPIkkRqvIXbemTS79w05pRWsabOT0k4gkGSyLKauT4jkatTE37Or6mBc3qnYTTLbP/qMJ6qIJoGJrNM++7JnD84m7ik1rUWCYIgCCdfixOjgoIChg4d2igpgvrEaPr06WzevJkePXr8ZDnXXXcdCQkJra4s1M+WXFRU1GDbm2++yaRJkxgyZEhsgscXXnihwTEjR47kwIEDsc+9evUCiI1uOxOZzSl06vRHssIVhEKHkCQTDkcXDIbGr/+aEh8fz7Bhw/B4PLjdbgwGA2lpaRiNRgb2gbKRPTlQtA9DSRFdXAnEdbsKKb1Lky1FP2bp6MLcIb4+MQqryA4TxuRjr9YefPBB7rvvPlatWkUgEKBbt24NOtUfJUkSXU1d+cOlf6DYX0xICZFmTyPTmdno2LjkFAb9dgKeqkq81VUYzWZSstthMNa3+NyX34Xf9mvPgeoARlmiS3octiMj0R49py2loQil4ShmWSLPYcXcwhm+W0qSJHLOT6Vd92RqSv0oEQ1Hgpn4ZNtPnywIgiD8IlqcGC1atKjZfX369GlxgvHVV1+19JI8/vjjPP744w22NfWaLikpibfeeuu4Ze3fv7/F1z3TWCxpTXbCbqn4+PgmO5NnuKxk9OkKdD2hciVZwnSc2ZxtNhvDhw9vUVkm2UReUl6Ljo1PSSU+JbXJfSlOCynOphPHTKuZTKu5Rdf4OQwGmdTsxqMFBUEQhF+fWERWEARBEAThCJEYCYIgCIIgHCESI0EQBEEQhCNEYiQIgiAIgnBEq5cEEU5fWiBAaPt29GgUU9u2mLPr5zFyu93U1NQgyzLp6elYra0YFq4qUP49hNxgT8Yd34UdZT5UXScnxUEbV8MRVbqu4vVtR4m6MZkScTpzkaSGEy56a0K4K4PIskRylhOL7acfw7KyMlavXo2qqvTp04cuXbqg6zo7/CGqIgoOo0x3p+2kjyRrij/qp6imCEVTyIrLanKEXEtFQkEq9u9FUxRcaem40jJQVI3th714QlES7WbyMuKQ5Z8eCXiy6KpO9LAPLaQgO8yY0u1Iv+D1BUEQfk0nlBitWbOGAQMGMGLECJYsWdJo/9y5cwGanORx7ty5PPvss+zcuZP4+HhuuOEGXnrppdj+jz/+mMcee4ytW7ditVq57LLLmDFjRoO5bX5M13Uee+wxZs+eTV1dHf379+fll1+mc+fOQP2ItCeffJJPP/2UsrIyMjMzGTduHA899FBsIdUzma6q1C1ciGfxEpSqqvrZn+126Hk+O889lwOVlUQiESRJwm63061bNy688MJm16OL2fMZrC+Amr1oSoTasMx2pQ3vyKPYZuiC02rkko4p/O7SHJKdFmpr13Ko5A0C/n1oegRZtmC355CddRsJCb0JeCJsXFFMyc5aoiEVJLA5zXS6IJVzL22Lwdg4qfH7/bzwwgusWrUKRVFi2/sPHUqXB5+i2JlASNMwSRLZVjPjMpPJT45vtHzIyaBoCgt3LWTZ/mVUB6vRdA2HycEF6Rcw/tzxpNqbHgnXFE1V2fJ5ITu+XEXAXYeuaZhsNtxZPfnO2plDHoWoqmE2GjgnzcEd/XPo1a7xEionW2hXLb6vD6NWh9BVDckoY0yzEzegLWYxkk4QhP8CJ/TndUFBAZMnT2bVqlWUlpbGts+cOROv99gimV6vl5kzZ8Y+P/vsszz00EM88MADbN26lRUrVjQYrr1v3z5Gjx7N4MGD2bhxIx9//DFVVVVcd911x63P9OnTeeGFF3jllVdYu3YtDoeD4cOHEwrVrwy/Y8cONE3jX//6F1u3bmXmzJm88sorPPjggydy+6edmvnzqZk7F9XtxpSWhikri6jVyudlZWzdsAFZ00hISCA+Pp5IJMI333zDF198cfwpFvZ8Cp9Mg8pd6PZk9qmpFAdMtI/sZrIyh0vtBzFIEsu2ljFt0TZKyr9i956/4fPtxGRKxGZth8nowucrYtfuZ6isWMcX7+5k78ZKZFkiLtlKXKKFaFjh+5UlrP9of6P6qKpav2baV1/xzDPPUFlZidfr5W+vFfDt91tYcNtNWPxe2lvNpJiMFIciTN9XxkdV7pMeY13XmbNlDvO3z8cb8ZLuSCcrLgujbGTloZU8s+4Z3OGWX/fbpf9hw9L/EPb7cCYl40pLZ5+Uypv7DGzZU4rLItEuyU6CzcjWUg9PLd7OpoN1J/2+fii0sxb3sv0olQEkuxFDkhXJaiRa6qNu8R4ih37eQrqCIAhnglYnRj6fj3feeYe7776bUaNGxVqHABITE8nPz2f16tWsXr2a/Px8EhPr/8qtra3l4YcfZt68eYwdO5ZOnTrRo0cPrr762AzNGzZsQFVVnnrqKTp16sQFF1zAH//4RzZu3Eg02njVdKj/wnruued4+OGHGT16ND169GDevHmUlpbywQcfADBixAjmzJnDsGHD6NixI1dffTV//OMfef/991t7+6edyKESPIuXINsdmNLTkcz1a34dSkmhzuXC7vNh9HqRZRmDwUBcXBw2m42ioiLKy8ubLlSNwrrZEA1CYnt8qokqfxTVaKfa3JY4zcMQ/2ISbSayEmxsK63l+13/i6L4sFnbYTDYkCQZg8GOzdoORfGwa/scqg56iU+2YnWYkGUJ2SDjcFmwOozs31xFdYm/QTWWLl3Kp59+ygMPPMC9995LSkoKTqcT72XDyHtpLtGKMkoXvossSVgNMtlWM6qu83pJFQFVO6lx3u/Zz4riFcSZ40izp2GSTciSjMviIsuZxa7aXXxS/EmLyqorO8yONV9gttpwJiVjMBrRJANr5XaoJgvOiBvN70GWJOxmIx2S7NQGIsxfe+CUTUiqKxq+NaXoUQ1DohXZbECSJGSLAUOSFdWv4F97+IyeEFUQBKElWv0q7d133yUvL4/c3FzGjRvHlClTmDp1KpIkMX78eAYPHkyfPn0AWLduHe3atQOgsLAQTdMoKSmha9eueL1eLrnkEmbMmEH2kb4wF154IbIsM2fOHMaPH4/P5+ONN95g6NChsQXg9u/fT05ODp999hmDBg1i3759lJWVMXTo0FgdXS4Xffv2Zc2aNdx8881N3ofb7SYpqfFK7D8UDocJh8Oxz0dX541Go80maifiaFknUqb3q69QvV6M7bLR9GPJQLHFjAwYJAmlsgpjRkZsxmqz2Yzf72fPnj0kJyc3KlMq2YChZh+6Iw10nRp/BFXTsZhkkMBjSCArvIeU6CEqTG1Jtx/C799LSkoGOnqjL0+TKZnaml0YnSVIhnPQfrzfaiDojVK8rQpX+rHJF+fOnUuvXr3o2bNnLDblkSjf1PnIbN8B97CR7F30HufeflfsnFSjgdJQhLU1bgYkOFsdz+asKVmDP+In25mNpjVMumRkTLKJTw58wlUdrvrJsvZt/o6w348ro00sFgcVO9WqhXgpiiTL+GprcSalxBbxTXaY2FbiZne5mw7Jjp/1zDQlUuwlWhNEdpqa/B1KDgPhEh+hCh/G03zpkpMdm7OJiE3zRGyadrbEpTX1b3ViVFBQEFvnbMSIEbjdblauXMmgQYOYP38+s2bNYtSoUQDceOONTJo0iXHjxrF37140TePpp5/m+eefx+Vy8fDDD5Ofn8/mzZsxm83k5OSwfPlybrzxRn7/+9+jqir9+vVj6dKlseubTCZyc3Ox2+1AfadcgPT09Ab1TE9Pj+37sd27d/Piiy/yj3/847j3+swzzzBt2rRG25cvXx67/slUWFjY6nMS1q7F5fcTraxssN0TF4emaSiqCmoQT3k5/KBjcjgcZvPmzVRVVTUqM82zme6eWvwhM0ge6oISqgphXQVA0SVSCBKuLqZCNpFkq0JRglRXe4CmXrdoaEqQcLQSn6fxDNsAil9iy6btHAxuim3bvn177Pd6NDaHZSNVtlQcmoqc1oZA5QrKKyoalOWVjXy2bj0eJfCT8Wupb0Lf4A/7qQxWNrk/qAXZ793P4iWLkaXjN8TWbtuE3+8nUnGsrFIphZBRw6aHQNNQVZXyivJYXylVg7qIxEcrVtL+B119TuSZaUp8rYkst51wRG1yv6SBKSLz/YqVBJxNH3O6OVmxORuJ2DRPxKZpZ3pcAoGWfx+0KjEqKipi3bp1LFy4sP5ko5GbbrqJgoICBg0aREVFBYWFhbz33nsAPPfcc8yePRsATdOIRqO88MILDBs2DIAFCxaQkZHBZ599xvDhwykrK+POO+/ktttu4ze/+Q1er5dHH32U66+/nsLCQiRJom3btrEFZE9ESUkJI0aM4IYbbuDOO+887rFTp07l/vvvj332eDxkZ2czbNiwJpfQOFHRaJTCwkLy8/NjLWMt5YlGqd26FWNKCtIPEh+XwUCt0YhRUZDNZuIyjq3crus6tbW1nH/++Vx00UWNypRKM5AXL8VhjweTjXBtEH9dEIvJUN9hWoui6zbMyR1IM6URDtZhMtpJTo7DYGicMCqKj7qKCBZjGonpjZcu0XUdT0WIc3u2ofugtrHt8+fPp6ioCF3XGTZsGCaTiaqIwgfbijEAyuFDONIzSE87VmZE0wlHoww5vwuXJDS/HElrBXYF2LVjF6nO1CY7dpf5y2jrbMuVA6/8ybK22s1sKD+EK+1YWSHFgTUgI0s2ZCWE0WQiPS091mLkDSkYoioj88+nfZL9Zz0zTYke9OKu3Uu8w4RkapzYaSEFojqX5vfGkHj6txidzNicTURsmidi07SzJS5H3/i0RKsSo4KCAhRFabBqva7rWCwWZs2a1SCJAIiLi4tta9OmDQDdunWL7U9NTSUlJYXi4mIAXnrpJVwuF9OnT48dM3/+fLKzs1m7di0XX3xxozplHPnCLy8vj13j6OeePXs2OLa0tJTLL7+cSy65hFdfffUn79disWCxNF5Xy2QynZIH5ETKje/fH8+7/0avrcOQkhLb3j4cocZoRNV1zCkpyD9ImgKBABaLhXPOOafp62VdCCmdoHInJHYgyWGhzBNC0XSMskS8WkeR9XyqTZlEVY3yYFscjk5Eo/swGto3SBx0XUeJ1uB05lIRyEQz6xh/9MUbCiiYbUbanZvSoD4TJkzgiiuu4JtvvmHUqFGYTCbamEz0S3TywfrvKC78iJ6T/18sIdR1nQpFoa3VQt+keEyGkzd0v39Wf/6z9z+4o26SrA1fwUbVKFE9ypAOQ1r0+8s5/wK2flZI2OvB7koAINsYINUQokyxEq9pOBISY78zXdep8Ufpk5NEp7SGI+5O1rNobJ9IINmGUhVETrQ2+h3iV7B0SsCS6jwlI/5OhVP17/RsIGLTPBGbpp3pcWlN3Vv8zaEoCvPmzWPGjBls3Lgx9rNp0yYyMzNZsGBB7NimFnrt378/UN/qdFRNTQ1VVVW0b98eqP/Cln80D43BUD8Hzo/7dRyVk5NDRkYGn3xyrOOrx+Nh7dq19OvXL7atpKSEQYMGceGFFzJnzpxG1zlTmdq0wXXNNWjhENHDh9FCIXRFIbO8nKTaOgJxcYSdTlRVRVEUPB4PoVCIrl27kprazPBygxH6/B4sTqjZi1MKku40YlL8pEQOUScnUOi4kmp/hJK6ED2zkzg/93cYjS6CoQMoig9NV1AUH8HgAUymBLp0vYO09vH4akIEvRE0VUOJavhqw4QDCp16pZLUpmELz7Bhwxg5ciT/+Mc/ePrpp9m/fz9lZWVIS95j+6TbsWS3J230jSi6jl9VKQ5FsMgSd7RNwXoSkyKAdvHtGJkzkkA0QJm/jLAaRtEUakO1lPhK6JrclcHtBreoLFdaOl0vvZxoOIy3uhIlEkHSFPpq+zGqIbzmBHC4UFQNbyjK/uoAyU4Lv+3X/pQlJZJBwtm/LZLFgFoTQgur6KqOFlJQq0PIcWYcF2eeMUmRIAjCiWpxi9HixYupra1lwoQJuFyuBvvGjBlDQUEBEydObPb8Ll26MHr0aO69915effVV4uPjmTp1Knl5eVx++eUAjBo1ipkzZ/LEE0/EXqU9+OCDtG/fnl69egH1Cc6QIUOYN28effr0QZIkpkyZwlNPPUXnzp3JycnhkUceITMzk2uuuSZ2zqBBg2jfvj3/+Mc/qPxBf5yMH7xiOlMl/uZmDPHxuD/8EKWsDF1TMdkdXN6xI7u65rHv8GE8Hg+SJOF0OunevTvnn3/+8b/kci6FYX+F9QVIlUW0N0SodUpsVs7lHXkUu4NtibPKXNszk9suycFlN2EzP8yhQ2/g8+9EV2qRJDPxrp5kZ/2W+PgeXHpjlM2fHeTgthq8tREkCewuM517p5N3cUaj+siyzNtvv83NN9/M3/72Nx5//PHY9vyrruacvzzGLpONklAEkySR67Dy28wULks6NfPt3NL1FhKsCSzZu4TKQGVsHqPhHYYzrts44s0tf73aa/gobE4n21Z/jq+mGl3T6GC1cUdnme8sWeyri1AXDGExylzYIZHxl3Tg3EzXTxf8M1g7JSCN7Ijv68MolQE0v45klDB3iMd5SSbmNifv1aQgCMLpqsWJUUFBAUOHDm2UFEF9YjR9+nQ2b95Mjx49mi1j3rx53HfffYwaNQpZlhk4cCDLli2LNXENHjyYt956i+nTpzN9+nTsdjv9+vVj2bJl2Gz1MyxHo1GKiooadKT685//jN/v56677qKuro4BAwawbNmy2AzPhYWF7N69m927d5OVldWgTmfD8GNJknBdOYq4YfmEd+5Cj0YwZbbFlJ5GO+qnWKitrUWWZVJTU1s+qWX7fpDdF6qKkEIekuzJ9IlrT2KFH1XXaZ9kJ9l57FWjy9WT+PjzCQT2EFXcmIwJ2O0dYwmP1WGiz5Ud6X5ZFp6qIJIskZTpwGQ2NFcDrFYrd911F3PmzGHdunUoikLv3r3JyspC13UOhCJURhQcBplchxXDKWzRMMgGru50NcM7DGd33W6iapSsuCxSbCk/ffKPSLJM10svp3Pf/lQfKkZVosSnpuNMTELXdXZV+PCGoiTYzXRMcfxiLTWWHBfm9vH1iVFIRbYbMabYREuRIAj/NST9bMgMfiEejweXy4Xb7T7pna+XLl3KyJEjz+h3uKeCiE3TRFyaJ2LTPBGb5onYNO1siUtrvr/Pjo42giAIgiAIJ4FIjARBEARBEI4QiZEgCIIgCMIRIjESBEEQBEE4otVLggi/vkhxMdHSUqK6jtdmQTcacaWl40pLxx2IsqPMg6rrdExxkuFqepZiXdfZsGED27ZtA4uVzH4D8GLGGFRpo0mcIxuwGg0YE03U7d9G0O3D4nKRcl4PZJMxVkYgsI9wuAzZYCHO2R2DoX6UmqZr7KzdSV24jjhzHLmJuRjl0+9xq6uri43YS09Pj41kFARBEP47ndA31Zo1axgwYAAjRoxgyZIljfbPnTsXoNEkj0f3Pfvss+zcuZP4+HhuuOEGXnrppdj+jz/+mMcee4ytW7ditVq57LLLmDFjBh06dGi2Prqu89hjjzF79mzq6uro378/L7/8Mp07d44d89e//pUlS5awceNGzGYzdXV1J3Lrv6rIoRJq5szBv+k79kVDlJgkIkYDUpwTQ3IGRWkXssuchSeio+k6cVYT/c9J5ncDOpLoODZEf9OmTUyYMIENGzbEtsk2O3FX30yHG++ibx3cfDBClqqgRyJURSMURwMgH8YVt5nuw/JIvjCd4uICPN7vUdUgkmTAYkmnTZsxHCaLt3a8xT73PiJqBJPBRPv49tycezN92vT5FSLXmNfrZc2aNezfv59IJIIkSTgcDrp168aFF14Ym1hUEARB+O9yQq/SCgoKmDx5MqtWraK0tDS2febMmXi9xxYR9Xq9zJw5M/b52Wef5aGHHuKBBx5g69atrFixguHDh8f279u3j9GjRzN48GA2btzIxx9/TFVVFdddd91x6zN9+nReeOEFXnnlFdauXYvD4WD48OGEQqHYMZFIhBtuuIG77777RG75VxetqKD8r3/F9+WX7DbCXrsJxWjAqqiYatx8GmpDYZlMxeEy0p1GshPtyMDS7w/zxOJt+MMKADt37mTQoEGoqsq42a/T57NvyXl9CfFX3ID733OpfG0G36QbeeUcA1XhMFHVQJrRTp7dgc0UodZjZt2y9Wxaez81tV9jkG3YrNlYzGlEwpXs2P0sH278CztqdhBvjic7LpsESwJ76vYw89uZfFP2za8bSCAYDPLRRx9RVFSEwWAgISGB+Ph4wuEw69atY/Xq1WfF/FaCIAhC67U6MfL5fLzzzjvcfffdjBo1KtY6BJCYmEh+fj6rV69m9erV5Ofnk5iYCEBtbS0PP/ww8+bNY+zYsXTq1IkePXpw9dVXx87fsGEDqqry1FNP0alTJy644AL++Mc/snHjRqLRaJP10XWd5557jocffpjRo0fTo0cP5s2bR2lpKR988EHsuGnTpnHfffdx3nnntfaWTwuej5YR2bePcGYGJbKGSZKwGU0YrFbK7OnsklKJM6hYI17CnjoMskSiw0zbBDubD9XxWVH9CvRPPvkkLpeL5z9cSkmPPhgkE3JcKp1vm8y5t06h9KN/Y91fzN54E9+k2ogSISJFcWAl0Wgj3h7C0GYzPv8hbNZsjMY4JElGls1YrG2oCXvIkUo5Jy4Du8mOJEnYjDaynFkEogEW7FiAoim/aix37NhBeXk5CQkJ2Gw2ZFnGYDAQFxeHzWZjx44dVFVV/ap1FARBEH4drX6V9u6775KXl0dubi7jxo1jypQpTJ06FUmSGD9+PIMHD6ZPn/rXJevWraNdu3ZA/ezTmqZRUlJC165d8Xq9XHLJJcyYMYPs7GwALrzwQmRZZs6cOYwfPx6fz8cbb7zB0KFDYxNL7d+/n5ycHD777DMGDRrEvn37KCsrY+jQobE6ulwu+vbty5o1a7j55ptPODjhcJhwOBz7fHR13mg02myidiKOltVs8heN4v30U7DZqNCiRHUdp2SAI40ae5zZRDGQoITRZBl/XS3OpBSQwGQAWYJPtpVxWQcn7777Lo8//jgbojohVcPrCyNL4FB1Uodey87/e42qz5eQ8Nvfsy7dxGXl1C9EK0GcbsdjqMWWsRM1bCPsDWCJd8bqGYgGqFNUXDKk6NWU6A2XW0myJLHfvZ9tldvomtT1pMTmRGzfvh1ZlpEkqdEafGazGb/fz65du0hISDhp1zzZTkVczhYiNs0TsWmeiE3Tzpa4tKb+rU6MCgoKGDduHAAjRozA7XazcuVKBg0axPz585k1axajRo0C4MYbb2TSpEmMGzeOvXv3omkaTz/9NM8//zwul4uHH36Y/Px8Nm/ejNlsJicnh+XLl3PjjTfy+9//HlVV6devH0uXLo1d32QykZubi91uB6CsrAyA9PT0BvVMT0+P7TtRzzzzDNOmTWu0ffny5bHrn0yFhYVNbpeDIdqWlqIbZGplBdWgEdHV2H6vbkLSNdRoFNVgQFVVKirK4cgyDqEIbN/n5b33NhGJRPD7/WzZuZuA0UowpKIDkmZAMlmwprYhXFuFRYU6c32DoqZpqJKGjERE9mGSI2hRK57aOvTQsaVZglqQiKqgGTVC/hoqgg0bJHVdp1avZcUXK9hn2ndSYtNauq5TUlKCrusNkt4fCofDfP/99w3W1Dtdnay4nI1EbJonYtM8EZumnelx+eEyYj+lVYlRUVER69atY+HChfUnG43cdNNNFBQUMGjQICoqKigsLOS9994D4LnnnmP27NlA/ZdrNBrlhRdeYNiwYQAsWLCAjIwMPvvsM4YPH05ZWRl33nknt912W2wR2UcffZTrr7+ewsJCJEmibdu27NixozXVPmFTp07l/vvvj332eDxkZ2czbNiwk74kSGFhIfn5+U1Oua4rCqXLlqG66/DEOagM+zBLhtj6VfFSBF2WMRhMSLKE0WQmLS0djixvFa4Jcm6Wi+tHDuKee+7BYrHQp8s57KuoQw2HCEdVdFlC8wUJlh+izUWXETZAYri+NUWWZWRJRkPDLMWBakY2RolPSsMSd2xh0UA0QE1tFbKsYIlLJi0urcF9BJUgRGBYv2HkJuaelNiciPfee4/q6uom1/3TdZ3a2lp69OhB7969T8r1ToVTEZezhYhN80Rsmidi07SzJS5H3/i0RKsSo4KCAhRFITMzM7ZN13UsFguzZs1qkEQAxMXFxba1adMGgG7dusX2p6amkpKSQnFxMQAvvfQSLpeL6dOnx46ZP38+2dnZrF27losvvrhRnTIy6l/XlJeXx65x9HPPnj1bc3uNWCwWLBZLo+0mk+mUPCDNlmsyET90CDXz3yQ9MYF9kkQYDatUP3LqHG8xm20dCRmtmJQgjoREZLm+tSYUVQGJod0yiIuL4+abb+bVV19l/m/Hs8ggoztNBGtU/AaJsmXvogQDJF9+JVEJ+pZHADBIEhLglYKgmQgezsPRcQMWpw1ZOtYq5DA7SDIa8CgKVXJSg326rlMdriY3MZduqd0a7PtZsTkBXbt2ZdWqVWiahtHY8J9AIBDAarXSuXPnM+I/AqfqWTwbiNg0T8SmeSI2TTvT49Kaurf420lRFObNm8eMGTPYuHFj7GfTpk1kZmayYMGC2LHjx49vNFS/f//+QH2r01E1NTVUVVXRvn17oP5L6egX+lFHh03/uC/IUTk5OWRkZPDJJ5/Etnk8HtauXUu/fv1aenunvfgrrsByTicspWVkqxKqrhNQoiihEGnhSnK1cryqTNASjynORVTVqPKFKXUH6dU+gYG5qQA8+uijhEIh7h45nPSvPkMJeFArDlD06nR2vDWLtlePI5TVls7uKBdVBTFjxqSb8BKkRgng9ttQy3oQ5+xAMFRMNFqHpiuoapBQqIREawJ79Sz2eMvwRXwomoI/6qfYW0y8OZ5but7S6qToZMvNzSUzM5O6ujr8fj+qqqIoCh6Ph3A4TLdu3UhOTv5V6ygIgiD8OlrcYrR48WJqa2uZMGFCo1cQY8aMoaCggIkTJzZ7fpcuXRg9ejT33nsvr776KvHx8UydOpW8vDwuv/xyAEaNGsXMmTN54oknYq/SHnzwQdq3b0+vXr0AKCkpYciQIcybN48+ffogSRJTpkzhqaeeonPnzuTk5PDII4+QmZnJNddcE7t+cXExNTU1FBcXo6oqGzduBOCcc87B6XT+uLqnHWNyMhmPPErNG/PotG4dpkCAgyYImYwY4uMY7CgnJ7M92wxtqA4o6CjEWUxcd0EWt13SAbu5/ledk5PDF198wcSJE3lryj2x8g1xLhLHTyJl9K1cUh7lhkMayTYbWiRMWSRMSTSAJJtJTQ7TfURfEnuM5uChubjr1hMOHwYM2GzZdGpzPclSJsqOt2MTPJoMJrqndOem3Jvomdbz1wngD1itVkaMGMHatWvZu3cvHo8HSZJwOp2cd955nH/++bHXlIIgCMJ/lxYnRgUFBQwdOrTJfhljxoxh+vTpbN68mR49ejRbxrx587jvvvsYNWoUsiwzcOBAli1bFmviGjx4MG+99RbTp09n+vTp2O12+vXrx7Jly7DZbED9+86ioqIGHan+/Oc/4/f7ueuuu6irq2PAgAEsW7aswSzGjz76KK+//nrs89FE6+jotjOBKT2N9D/+kWh5ORmlpVwoS/itFjQJ4lPTcSYmEYgo7Cr3oeo6HZIdJP1gYsej8vLy+Pzzz9mxYwfbtm3DYLWSdmFffKqMIaSSikwHZMxGGWOimdSDuzinzovZlUBS1zykI616XTo/RChUSih8GINsw+HojCybSAWe7P8k+z37cYfdxJvjyXHlnFbJhsPhiI2gPDrzdVpa2hndVCwIgiD8fJIuZrJrMY/Hg8vlwu12n/TO10uXLmXkyJHii/lHRGyaJuLSPBGb5onYNE/EpmlnS1xa8/0tFpEVBEEQBEE4QiRGgiAIgiAIR4jESBAEQRAE4QiRGAmCIAiCIBzR6iVBhFNLdbsJ79yJpqgomRpanI7B6CTO2RVZrh9hFgkpVB30UuI5TNDmJj7FRtfkrlgMjSejBFDKa1D2FiHpEUw5mchtOjd7/QMHDrB69WokSWLAgAGxte5aQ1E1th324A0pJDnM5GXENTsiTdN1tvmC1EZV4k0GznXYCNRUUVd2mJCqUya72OWWKK0L0j71zO34JwiCIJwZTigxWrNmDQMGDGDEiBEsWbKk0f65c+cCNJrk8ei+Z599lp07dxIfH88NN9zASy+9FNuv6zozZszg1Vdf5cCBA6SkpHDPPffw0EMPNVsfXdd57LHHmD17NnV1dfTv35+XX36Zzp2PJQB//etfWbJkCRs3bsRsNlNXV3cit37KSNEotW+8QeDTTwkay3BfUE00PQpxVkwJyVgd7cjMuJHKXd34/utiyquqCEcjKIYwdYllBLrNZVSP4YzoMCKWhKh1Qbzvf0a42IeuyICOwbgfW9YyHNdehZTcIXb96upq7rrrLhYuXMjRgYqyLDNmzBj+9a9/kZiY2KL7+GJXJW+sOUBxTYCoqmExGuic5uSOATmcn53Q4Nhv3H5eO1TJbn+IsK5j1DRctZX02rqWhD078UVUArKVA/b2fFEbT9/O6fzu0hzS4qxNX1wQBEEQfqYTepVWUFDA5MmTWbVqFaWlpbHtM2fOxOv1xj57vV5mzpwZ+/zss8/y0EMP8cADD7B161ZWrFjB8OHDG5R977338tprr/GPf/yDHTt28OGHH9KnT5/j1mf69Om88MILvPLKK6xduxaHw8Hw4cMJhUKxYyKRCDfccAN33333idzyKaVrGkkrPsHz738TttVRO7yWSDsFOWpAPhRGO+QhFChm25YZbP32/zhYWUKtoYKIw4fRZCC9qiMpG7oz95v5fLD7AwBUf5TaeZ8R2htE0sIYLD4M1jCabsO3PwPvG2+ju+t/d8FgkPz8fFatWsW//vUv6urqqK2t5Z///CeffPIJw4YNaxDL5qzcWcn0ZUXsq/KT5DDTLslOvNXI9yVunli8je8PuWPHbnD7mba7hK2+IC6TgWyTASrL2BvV+KBjL75N6UjA5MSKQm7dVjocWkPh1jKmfbgNd+DMXuVZEARBOH21usXI5/PxzjvvsH79esrKypg7dy4PPvggAImJieTn59O9e3cAXnnlldhs2LW1tTz88MMsWrSIIUOGxMr74YSQ27dv5+WXX2bLli3k5tYvMpqTk3Pc+ui6znPPPcfDDz/M6NGjgfqJJNPT0/nggw+4+eabAZg2bRpwrDXrdBLetg1HURGGNm1wX1CKYotg8tmQkNCtOrrbD/FphKMeLJkfE6i+EqscD0hoBgXNqBLvT6VNeRfe3/U+g7IHYd5QjlIZxmByIxmN1OfAGgZzCFWxEKzOxrZuCab8O5k/fz6bNm3i22+/5fzzz4/V6/e//z29e/emd+/evPPOO9x2223N3kNE0Zi3Zj+hqEp2oi3WauWwGOlgNrC/OsCbaw/wTNvzAJhTUkWdotLBakaSJHw1VeD3kmw0c9hkY2eXc+ngrkHVTWiqTmrtbjq3PZfthyUKt5dz/YVZp/A3IgiCIPy3anVi9O6775KXl0dubi7jxo1jypQpTJ06FUmSGD9+fGw2YYB169bF+qgUFhaiaRolJSV07doVr9fLJZdcwowZM8jOzgZg0aJFdOzYkcWLFzNixAh0XWfo0KFMnz6dpKQkAPbv309OTk5sxup9+/ZRVlbG0KFDY3V0uVz07duXNWvWxBKjExEOhwmHw7HPR1fnjUajRKMnr9XC99VXSNEoarKRYEodctgEuoQOIEmARLDGh2KKR7aWkeAqI+iJB47MzSnpaAaFjMpz2NN2PV8f+pre38mgh8Bg4MczeEqGMGrUQej77XCpn7lz5zJixAi6devW6L569OhBfn4+c+fOZezYsc3ew8biOg5W+0mNM6Oj8+N5Q5McJraUuNlb4SFsNbDDFyTFKINef6y/rg4kCUXTsQUDeOLiqXIlkFpbg2IwY1X9xNfuw5TQk+VbDzO6R/rPjPqZ7ejv6WQ+h2cLEZvmidg0T8SmaWdLXFpT/1YnRgUFBYwbNw6AESNG4Ha7WblyJYMGDWL+/PnMmjWLUaNGAXDjjTcyadIkxo0bx969e9E0jaeffprnn38el8vFww8/TH5+Pps3b8ZsNrN3714OHDjAv//9b+bNm4eqqtx3331cf/31fPrpp0D9Crm5ubnY7XYAysrKAEhPb/hFmZ6eHtt3op555plYS9MPLV++PHb9kyFl4yYcskSVv4KoFkEKGlDVY4vmSppKNBxFkUDSNWTJTzgSaVCGqklIQYmQJ8yaDWvIq+2JRQujRpp+GHTNTsAbYdWS/7B371769evH0qVLmzzWarWyffv2ZvcDbK2VqPPImKJNT6SuaOCJSHy04nMiLgvV1iQ0TcF/ZH8o4AddJwpIGqiShB8JVyQMkoSqqoRrqwiaPOwOeFiyZCmn0Qojv5rCwsJfuwqnLRGb5onYNE/Epmlnelx+uIzYT2lVYlRUVMS6detYuHBh/clGIzfddBMFBQUMGjSIiooKCgsLee+99wB47rnnmD17NgCaphGNRnnhhRcYNmwYAAsWLCAjI4PPPvuM4cOHo2ka4XCYefPm0aVLF6A+EbvwwgspKioiNzeXtm3bsmPHjtZU+4RNnTqV+++/P/bZ4/GQnZ3NsGHDTuqSIFWlpVRs306yPY1yuQxsEobIsRFYuqZhspiJGnU0yYCmO7GYG66BZlStRK1BbPFW+vfsj7Mc1IoIBrPEjzMIXQdVk7G7zAwbdQ2dn3+FQCDAyJEjm6zf888/T5cuXZrdD5B5sI7Pa7cR7zBhNRka7fcEo5gUnVH55xO2yCwtOoRDlogz1h9bEfARCQUxSUbCmoRB13HqGmazhUg4hMFgwJKYitURR06yg1GjerY0vGelaDRKYWEh+fn5Z/Q0/aeCiE3zRGyaJ2LTtLMlLkff+LREqxKjgoICFEUhMzMztk3XdSwWC7NmzWqQRADExcXFtrVp0waAbt26xfanpqaSkpJCcXFx7Bij0RhLigC6du0KQHFxcazf0Q9lZGQAUF5eHrvG0c89e/Zsze01YrFYsFgaD4E3mUwn9QFxXnIJZf/+N4bqCLbKRPyZlRiixvo+Rlp9y5Et2UEk6iYUTKHWnYFF4tgQeE1CVo0cTttJoi2Ri9tejLFXGd7lAVACSKaGv2ZNsSJLAWzn5WC02rn99tuZMGEC3333XaOO7l999RWfffYZ8+fPP+4992yfTPtkB/ur/GQnGhsMz9d0nRq/Qv9zkumQGgfAuXF21rv9xJnqj3UkJBI5HMBogKDFTpK7lmS3GyQwqmF0oxl3Yg6qCsO7tzmj/4GeTCf7WTybiNg0T8SmeSI2TTvT49Kaurd4VJqiKMybN48ZM2awcePG2M+mTZvIzMxkwYIFsWPHjx/faKh+//79gfpWp6Nqamqoqqqiffv2sWMURWHPnj2xY3bu3AkQO+bHcnJyyMjI4JNPPolt83g8rF27ln79+rX09n5Vlq5d8XXrhlbnxvGNFaPfTNQRQCGIFg4hJTrQ4wNY7XbCpSNxhtKIRCIoioIcMmHy2alzllGevpsbcm/AZXFh690JU4YVRUlADcnomo6uyqhhG7oC9tRDGPteDcDYsWPp27cvw4YNY+bMmZSUlHDo0CFmzJjBFVdcQf/+/bnhhhuOew8mg8zt/TtgNxs4UBPAH1ZQVA1vKMqB6gBp8RZuubg9kiQhSRJ3ZKWQbDayLxjBq6iY413ocS6qLHYcSpi8HVuIRkIYgh6MaoSyxM7sjjro3tbF0G7/3f2LBEEQhFOnxYnR4sWLqa2tZcKECXTv3r3Bz5gxYygoKDju+V26dGH06NHce++9fPXVV2zZsoXbbruNvLw8Lr/8cgCGDh3KBRdcwB133MF3333Hhg0b+P3vf09+fn6sFamkpIS8vDzWrVsH1LeaTJkyhaeeeooPP/yQ77//nltvvZXMzEyuueaa2PWLi4vZuHEjxcXFqKoaS+x8Pl9rY3bSSZJEzeDBJPx2HDY9ncTlKVj2W9BNoGfZkNom4IzLpXuPB+nZ7zrat2lLop6GOeggqimUpe/Ec9Eu7uozgVE59f27ZJuRhFuHYM+zg9GCGrGjRk3IBi9xnatw3vZbcKYC9S1jH3/8MaNHj+Yvf/kLWVlZZGdn8+CDDzJmzBiWLVuG+Uev7ppySacUHhzZlW6Z8XhCCqXuEIGIykU5STx+9bl0bXPs9eP5cXae7NyW3i4HflXjcFTFkJpON5PEdfu+o6e7GIcaIChb2Z50Pofa9eOq89vy+FXnEm89c/9qEQRBEE5vLX6VVlBQwNChQ3G5XI32jRkzhunTp7N58+YGw+9/bN68edx3332MGjUKWZYZOHAgy5YtizVxybLMokWLmDx5MpdddhkOh4MrrriCGTNmxMqIRqMUFRU16Ej15z//Gb/fz1133UVdXR0DBgxg2bJlWK3HJgJ89NFHef3112Ofe/XqBRAb3farMxhw3XADSaNHE967F11RUNsYUW0RDAYHTkdnJMlAcgp07JVKTamfCm8lfqsbV9IFdErohElumDAY4sy4xo3AWeurn/maKKacLKSkxkPd4+Pjef3115k+fTpff/01kiRx8cUXk5aW1qrb6NsxmYs6JLGrwocvHCXJYaFDsr3Jma/Pj7PzXF42e4JhaqMqLqOBzvauBC/pSV35YaKaRIUcx5fr1nPTqAtok+hsXUwFQRAEoZUk/cfjqoVmeTweXC4Xbrf7pHa+jkajLF26lJEjR57R73BPBRGbpom4NE/EpnkiNs0TsWna2RKX1nx/i0VkBUEQBEEQjhCJkSAIgiAIwhEiMRIEQRAEQThCJEaCIAiCIAhHtHpJEOHUC4fL8Qf2ImHA6eyCyZTQ6Bhd19nv2U9FoAKLwULX5K5YDMcmo/z222/ZsmULdrud/Pz8BqMJfYrKVl+QqK7Tzmqmna3xJJY/VO4JsmJ7BYGwSgdrhC62EEazhbT2OZh+MPKvUR1VnehhH1pIQXaYMWU0PTpNEARBEE4XJ5QYrVmzhgEDBjBixAiWLFnSaP/RFex/OMljdXU1t9xyC5s3b6a6upq0tDRGjx7N008/3aCHeDgc5oknnmD+/PmUlZXRpk0bHn30Ue64445m6xMKhfh//+//8fbbbxMOhxk+fDj//Oc/G6yf9oc//IEvv/ySLVu20LVrVzZu3Hgit35KRaN1FBe/QU3tlyiKFwkJoymBtNRhtG07DsORxOeA5wCvb32drVVbCSpBDLKBNHsa15xzDW29bfnd737HN998EyvX4XAwefJkHn/iSd6pqOM/FXVURRRUdJwGmT4uB/e0SyfD0nDEgT+s8PiHW1i+rYJwOIJBCWJRI6RoHi6VD9A10UjXSy+n26WXI8kNGx9DO2vxfV2KWhNGVzUko4wx3U5c/7aYs+NOfTAFQRAE4QSc0Ku0goICJk+ezKpVqygtLY1tnzlzJl6vN/bZ6/Uyc+bM+gvJMqNHj+bDDz9k586dzJ07lxUrVjBx4sQGZd9444188sknFBQUUFRUxIIFC5pcCuSH7rvvPhYtWsS///1vVq5cSWlpKdddd12j4+644w5uuummE7nlX0CYvXv/P8orlgASNmsWFmsmmhampORt9u57Dl3XKPWV8vTap1lXtg6r0UpWXBaptlSqglXM/Hgm/S/rTzgcZtGiRQSDQYqLi5kyZQp///vfGXr7BGYfqsSjqLSxmGhvNWOSJFZUe3ho5yGqI0qsNhFF4w8LvuM/Gw8TjkRJiNSQFK3FqEc5bExisdydXR6dbz58j02FHzW4k1BRDe6P96NUhZAdRgxJViSrkcghH3VL9hIp+fUn1RQEQRCEprS6xcjn8/HOO++wfv16ysrKmDt3Lg8++CAAiYmJ5Ofn0717dwBeeeWVWOKTmJjI3XffHSunffv23HPPPfz973+PbVu2bBkrV65k7969JCUlAdChQ4fj1sftdlNQUMBbb73F4MGDAZgzZw5du3bl66+/5uKLLwbghRdeAKCyspLNmze39rZPOYNxBx7vZmzWtshyfcuQBFjMqSiyjZrqVXhSh7No/1pKfCW0i2uHLNXntWaDmTaONnz772/RzBr/+fg/dMjoAEB2djZPPfUUpuRUHr9/Cpdd+xsyOh9biy7BZMRhMLDDH+KjKjfjMpMBWLOniq/3VmOQwaX4MashNIMZM2DUg3gkG+uMHblO3sLWVZ/S6aK+xCWloCsavjWH0aMaxqRjr9kkiwHJbEWpDuFfexjTteeI12qCIAjCaafVidG7775LXl4eubm5jBs3jilTpjB16lQkSWL8+PEMHjw4thDpunXraNeuXZPllJaW8v777zNw4MDYtg8//JDevXszffp03njjDRwOB1dffTVPPvkkNpsNgM8//5zLL7+cffv20aFDBzZs2EA0GmXo0KGxcvLy8mjXrh1r1qyJJUYnIhwOEw6HY5+Prs4bjUaJRqMnXO6PRaNRjMZtgASSCU3XGuyXDXbUSAWHKz7ly5KNOIwO0GlwnBpROfjFQTrf2Jnt/u20jbZtUEabK6/FOO1xqj/6kOxODRf7NQIWCZZW1HJjShySJPHehoNEVA2n2YAp4EeXjjUuyoBVi3BIsROIT8FUVcz+Td+RN2AQkWIv0Zogclzj+wCQHAbCh7yEK30YEpvvn/TD2Pzwf4V6Ii7NE7FpnohN80Rsmna2xKU19W91YlRQUMC4ceMAGDFiBG63m5UrVzJo0CDmz5/PrFmzGDWqfr2uG2+8kUmTJsWOB/jNb37Df/7zH4LBIFdddRWvvfZabN/evXtZvXo1VquVhQsXUlVVxT333EN1dTVz5swBwG63k5ubG5uBs6ysDLPZTEJCQoN6pqenU1ZW1trba+CZZ55h2rRpjbYvX74cu93+s8r+MavNh88XxuutaHK/JAWprNtARU01RoyoHrXB/pA7hBpVMaYY+WrDV0S2RBrs/84cj6lNW2pLDlJe0fgaQUnmALD4o60YgO37ZTRNQo0o6JqKDujasURH1nXCkpHSGi/Jfh/ffrOOvZ4A8bUmsjx2wlG10TUAJA1MEZnNhSsJOps+pimFhYUtPva/iYhL80Rsmidi0zwRm6ad6XH54TJiP6VViVFRURHr1q1j4cKF9Scbjdx0000UFBQwaNAgKioqKCws5L333gPgueeeY/bs2Q3KmDlzJo899hg7d+5k6tSp3H///fzzn/8EQNM0JEnizTffjI2ievbZZ7n++uv55z//ic1mo0+fPuzYsaM11T5hR+t3lMfjITs7m2HDhp30JUFWrnoHlyuMzdZ4bTJd1wmFArRLuYh0/TtCSohkW3KDY9REFYPFQLQ8yoDeAxicPbjB/vL9JcwuOUjSpYNIb2L9MyUcpa3VxJVdL0CSJD71b2b/1nJkswkpZEDSVfQfdLBWdQNmGdomODFqTi7sezG5l1xG5KAXT+1e4h0mJFPjLmxaUAFF57JhF2FIOP5ouKOxKSwsJD8//4yejv5kE3FpnohN80Rsmidi07SzJS5H3/i0RKsSo4KCAhRFITMzM7ZN13UsFguzZs1qkEQAxMXFNdqWkZFBRkYGeXl5JCUlcemll/LII4/Qpk0b2rRpQ9u2bRsMLe/atSu6rnPo0CE6d+7cqE4ZGRlEIhHq6uoatBqVl5eTkZHRmttrxGKxYLE0/vI2mUwn/QFR1W5IrELXIhgMDV8xRVUPBoONzPTBXBaKY+HuhSSRhEE2xI6RLTLtBrajeHkxnf/RuVH9Drz3DqrXQ9LIaxqNIItoGlFgZFoiZrMZgOsvaseKokrCiobV7MAcqkPXAQk0ICxbyDV6sPkqMTjj6NCjFyaTCWP7BILJNpSqIHKitUE/Il3XIaBgOScRS4qjVX2MTkXMzwYiLs0TsWmeiE3zRGyadqbHpTV1b/GoNEVRmDdvHjNmzGDjxo2xn02bNpGZmcmCBQtix44fP77BUP3maEdezRztx9O/f39KS0vx+Y6NWtq5cyeyLJOV1XhFeIALL7wQk8nEJ598EttWVFREcXEx/fr1a+nt/epUJZf4+AsIRw4TiVShaVE0LUI4XE40WkNK8mDi4s7jyo5X0i6uHQd9B3GH3SiaQkgJUeIrocv1XbBIFkYOGcmCBQuoqqpi27ZtTJkyhWcenMqQCXeht8miNBQhpGpENZ3qqMLBUIRuDhsjU44lpP06JjOwcyqaDrWyg5DBDlqUiCbhxUYcYS6K7EFTFLpfno8zsb6zvGSQcV7SFslsQK0JoYVVdFVHCymo1UHkOAvOi9uIjteCIAjCaanFLUaLFy+mtraWCRMmNGjRARgzZgwFBQWNht7/0NKlSykvL+eiiy7C6XSydetW/vSnP9G/f//YyLOxY8fy5JNPcvvttzNt2jSqqqr405/+xB133BHrfL1u3TpuvfVWPvnkk1jr0oQJE7j//vtJSkoiPj6eyZMn069fvwYdr3fv3o3P56OsrIxgMBibx6hbt26xVpJfl5mOHf9CWfkCqqs/JxwpAyTM5mTapN5I28wbkSSJdEc6D138EPO3zWdjxUbK/GUYZANZcVlc0+sasi7L4u6772bs2LGxkhMTE3nyySf5ywMPsLDSzfvltZSFo2g6OIwyV6cl8LusNBJMxx4Ho0Hm2Zt68szS7SzafBiPnoBRsWLRwrRTq7jUcIguKVbOHTiSLhcPaHAn1nMSkEZ2xLf2MEpFAE3VkYwS5hwXzkvaYspw/FJBFQRBEIRWaXFiVFBQwNChQxslRVCfGE2fPp3NmzfTo0ePJs+32WzMnj2b++67j3A4THZ2Ntdddx0PPPBA7Bin00lhYSGTJ0+md+/eJCcnc+ONN/LUU0/FjgkEAhQVFTXoYT5z5kxkWWbMmDENJnj8od/97nesXLky9rlXr14AsdFtpwOj0UlOh3vIavsbAoH9SJIBu70jRqOzwXFtnW35S5+/cNh3mPJAOVajlU4JnTDJ9U2Fn376KUVFRWzbtg273c5ll10WSyxvyEjiqtQEigIhoppOttVMuqXpJkarycC00d25L78LnxdVEIyodIzTyTIEMJrMpLRrj8HY9LmWji7MHeLrE6OwiuwwYUy2ipYiQRAE4bTW4sRo0aJFze7r06dPff+R47j88sv56quvfvI6eXl5x+39PmjQoEbXslqtvPTSS7z00kvNnvf555//5LVPFyZTIi5X4k8e18bZhjbONk3uy83NbXZiTKtB5vy4lo+qS7CbuaZX068yj0eSJdE6JAiCIJxRxCKygiAIgiAIR4jESBAEQRAE4QiRGAmCIAiCIBwhEiNBEARBEIQjWr0kiPAr8VdD5XbQdUjNBWfj2at/SFcUQjuK0LweDImJWLp0QdX8eH070HUFu609Vmv9RJ17yyv5rroWyWDgwjbpFH27kdXrN2O12+k3tBu2OI04Uxy5SbkY5WOPzI79h9mx+yAmo0zf7h1JSUlqWAddR6kIoHojyBYjpjYOJGPLc/GQP0pFsZtQtQF/XZiE1DN3cjFBEAThzHBCidGaNWsYMGAAI0aMYMmSJY32z507F6DBJI/V1dXccsstbN68merqatLS0hg9ejRPP/10k8trfPnllwwcOJDu3bvH5hxqTk1NDZMnT2bRokWxYfvPP/88Tmf9MPfPP/+cmTNnsm7dOjweD507d+ZPf/oTt9xyy4nc/i8r4oe1r8LOZRCsBXSwuqDTEOh3T/3//xH/mjXUvrWASPEB9KgCViOBQRKhnhqqOYyOjtHgwGC9gNdL+/C1YsMvGwgUbefwC38jtG93rCzZZiRrZAd6ju1OTmJ7bsy9kXRy+duClWytDBPWJCR0XB9vZ1iOg3vHXYHFbiNy2I/vi0NEy/zoUQ1kCWOiFUefDKxdk447bF+JqmxZWcK+TVUEvGF8XgvLy7fTrmsSPYe2w+oUCZIgCIJwapzQq7SCggImT57MqlWrKC0tjW2fOXMmXq839tnr9TJz5sz6C8kyo0eP5sMPP2Tnzp3MnTuXFStWNDkpZF1dHbfeeitDhgxpUX1uueUWtm7dSmFhIYsXL2bVqlXcddddsf1fffUVPXr04L333mPz5s3cfvvt3HrrrSxevPhEbv+XoyrwyROw8U1Qo5CQDQnt61uNtvwfLH8UoqEGp/jXrKFixrOE9+7FkJCIMast7v5uatoUETq8D1PEic2aRVSFl8qNfG6QUAwSlr07OTD1D0hGI5lPzODct1+n298HkXppDsXv7ea7/93O3rp9zPjyVe7511LWl0cxoJJqUkg0afh0I//eHeaJV94jVOqhbtEeIsVeJIsBQ5IVg9OMUhvCs+IAoa3Vzd6yrut8s3g/W78oRYmoOBOtGGw6kgS7v63gi3/vJBJSTnXkBUEQhP9SrW4x8vl8vPPOO6xfv56ysjLmzp3Lgw8+CNTPsJyfn0/37t0BeOWVV2KJT2JiInfffXesnPbt23PPPffw97//vdE1Jk6cyNixYzEYDHzwwQfHrc/27dtZtmwZ33zzDb179wbgxRdfZOTIkfzjH/8gMzMzVr+j7r33XpYvX87777/PlVde2doQ/HIOfg37VkJcOph/MMmjIwXMDiheU7+/y3Cg/vVZzfw30YJBTFlZSJJE2OUl0L4Oo2JD8igoVGBwJbIt2JZN9MAl1WGWomx8cw6mpBS6PP4PdKuBgMWKq+1gOv+mCLPTzsEPNtPz2l64KzOpDMikGyMYj7wWMwJJsoZXMfB5GVy3dAuZHhPGZNuxliFTfYuRUhfC9/VhLF0Skc0Gfqyy2Evx1mpscSYsNiOaXp8UWZ0mLFYjFfu9HNhSTefe6ac6+oIgCMJ/oVYnRu+++y55eXnk5uYybtw4pkyZwtSpU5EkifHjxzN48GD69OkD1C/f0a5duybLKS0t5f3332fgwIENts+ZM4e9e/cyf/78BjNeHzV37lxuv/322CSPa9asISEhIZYUAQwdOhRZllm7di3XXnttk9d3u9107dr1uPcaDodj67jBsdV5o9Fog5m3f66jZf24THnXCmRVQTfa4ci6cjEGC6CjF32MljMYgNCWLUSKi5FTktHR0XUdf1o1mlHFGDQjmSVUnw/F52dD5ByiBhM2QkT8XqrXfknWHf+DwWpBJYisW4lYOmMN7yBzaBdKFm9h+4qdJHUYjFGPgCSB3rDB0SmrVKom1h3wcG1GeqwOPyQ5jSjuMIE9NVjOSWgUiwNbq4hGVGwuE5quox+5b13T6vsnSbBvcyUdzk9qdO5/k+aeGUHE5nhEbJonYtO0syUural/qxOjgoICxo0bB8CIESNwu92sXLmSQYMGMX/+fGbNmsWoUaMAuPHGG5k0aVLseIDf/OY3/Oc//yEYDHLVVVfx2muvxfbt2rWLBx54gC+++AKjsemquVyuBjM6l5WVkZbWsCOy0WgkKSmJsrKyJst49913+eabb/jXv/513Ht95plnmDZtWqPty5cvx25v+czRLfXjGb/PL/6WRH+QYLSiyeOtkRD+3ZtZv3QpAPadO0mrrSVikOFIEhfKqUNVFPRIBHQdKargq6ygzmJFkjV0HSLuWtA0LFnt0XQNXdIxaCpR2UY4HAEZTIl2vJV+4rMNyLpCJKqjojVRKyO10Sg17ho0XxO7AUtQZtdX66ndGWm0r26HmZDfSFj3NtheWVkFgBqWCO71sHTpnuOF8r/G8WaJ/28nYtM8EZvmidg07UyPSyAQaPGxrUqMioqKWLduHQsXLqw/2WjkpptuoqCggEGDBlFRUUFhYSHvvfceAM899xyzZ89uUMbMmTN57LHH2LlzJ1OnTuX+++/nn//8J6qqMnbsWKZNm0aXLl2arcO1117bbCtQS3z22WfcfvvtzJ49m3PPPfe4xx6t31Eej4fs7GyGDRvWZIfxExWNRiksLCQ/Px+T6VjHYvnzjcg7SohLbGYEWm2AuJzzGTl8JACh9u2p+GI1cnw88pG10eqMIdxGH0azGUlV0SWZpLR0krwBdKm+BcacmIxkMBA6sA/XeeejI6EYjFiVIBaLGSUQIVITID49DqNBQdHMmE1glBt2gtZ1IApJJhNJrkRke+NO0rqioXmiXND/PCydGncc32g+SNGaMuJT61/D6ZpGZWUVqakpSLKMpypIWvs4Bo1sermT/xbNPTOCiM3xiNg0T8SmaWdLXI6+8WmJViVGBQUFKIpCZmZmbJuu61gsFmbNmtUgiQCIi4trtC0jI4OMjAzy8vJISkri0ksv5ZFHHsFms7F+/Xq+++47Jk2aBICmaei6jtFoZPny5QwePLhRnTIyMqioaNiioigKNTU1ZGRkNNi+cuVKrrrqKmbOnMmtt976k/drsViwWCyNtptMplPygDQqt8sw2PUxUtQPlriGB0cCIMuQewWGI+cYu3fH3aED4d27MWRnI0kSjopkvB0Oo5sVcCsYElwYHXYuDJeyTo0QxIbFZif54kupXPo+KZcPA4cZHR1zeCcSEoeW7UBXNbrmd8Zfvo/Kqu6ga/CjgWVeVcYqRbk4x4VeoyHZpUajzxRfBGOCBUenRCRT4z5GHc5NZe+3VSghFYvdhCbXv66TZBlN0ZCQ6Hh+2hn9D/RkOlXP4tlAxKZ5IjbNE7Fp2pkel9bUvcWj0hRFYd68ecyYMYONGzfGfjZt2kRmZiYLFiyIHTt+/PgGQ/Wbox3pPxIOh4mPj+f7779vUPbEiRPJzc1l48aN9O3bt8ky+vXrR11dHRs2bIht+/TTT9E0rcE5n3/+OaNGjeJvf/tbgxFrp7XsPnDOEPBVgLcMlAiokSOfS6HDAMi5LHa4ZDSS9NtxyE4n0eJiNL8fU40Vx95EVCmAmqBjyExF11S62g5yAd/h0V1Uay7a/XYCqs/Ljkfvp3z9esyVRfj3LGfHnC8pWbSF9qO7orm8JHQ6TFuHTpVqxhsFRdWJqFAdNRBRYWimTLdR52F0WVCrQ2hBBV3V0SIqSnUQySjh7JfZZFIEkJLtJOf8FII+BV9dGFXR0DUIeiN4a8Kkd3TR7tzkX+o3IAiCIPyXaXGL0eLFi6mtrWXChAm4XA1fgYwZM4aCgoImh94ftXTpUsrLy7noootwOp1s3bqVP/3pT/Tv358OHToAxEazHZWWlobVam2wfeHChUydOpUdO3YA0LVrV0aMGMGdd97JK6+8QjQaZdKkSdx8882xlq3PPvuMK6+8knvvvZcxY8bE+h6ZzWaSkk7jTryyAS5/COLbwo5F4DsMOmBLgG6/hT53gtHc4BT7RReR/sBfqH1rAeE9e9BrI7hqE7HY0wn0jKKYAiiRAEajk//JtJJYKrNKU/G2yyFn+iwOz/oHZc88wtHeWcY4Mx3H5XH+mDzOSerETbk3kX7ZOfz9nc/5tjRArSoho5NoiDCyawJ33zwck8VCwjWd8K0uIXLIhxZUkAwSxnQ7zr5tsHZObPaWJUniwis6YI+3sHtDBQF3GDUsIcdL5F2cwXmXZ2OyNJ1UCYIgCMLP1eLEqKCggKFDhzZKiqA+MZo+fTqbN2+mR48eTZ5vs9mYPXs29913H+FwmOzsbK677joeeOCBVlXY7XZTVFTUYNubb77JpEmTGDJkSGyCxxdeeCG2//XXXycQCPDMM8/wzDPPxLYPHDiQzz//vFXX/8WZrHDxROg5Fqp21m9L6gj25hM6+wUXYOvVi8ju3aheH4aEBMw5HdC0IH7/bnRdwWZrh9mcQo9ucLi2jk1VtdAliwtuv4l923fwxTebsTsc9B2Yh8ESxWFy0CmhE7JU38j4/OTRHCitpmjvQcwGiQu7dyQu7tjrPlOqnYRrzkGtCaH6okhmA6Z0O5Lc/MSORxkMMt0va0tu3wwqDrr5cvWXDB99LnGJJ7/DuyAIgiD8kKT/eDy10CyPx4PL5cLtdp/0ztdLly5l5MiRZ/Q73FNBxKZpIi7NE7FpnohN80Rsmna2xKU1399iEVlBEARBEIQjRGIkCIIgCIJwhEiMBEEQBEEQjhCJkSAIgiAIwhGtXhJE+OXouk5NySF8tdWYLFbScjphPImd30pCEfYFwxgliW5OG7XuEIcqvXComC4Whfg2aZg6dmTDhg1s374dp9NJfn4+cQ47lG+FYA1YEyDjvPqpBX5A0yL4fDtQFC8mUwql/jZU+SI4LEa6pjqhIoAeUTHEWzCm2hpNBHm6i0ajlJWVEY1GiY+PJzk5mYA7Qm15AFmGpEwnVseZ21FREAThv9UJJUZr1qxhwIABjBgxgiVLljTaP3fuXIAGkzxWV1dzyy23sHnzZqqrq0lLS2P06NE8/fTTsR7iq1ev5i9/+Qs7duwgEAjQvn17fv/733Pfffcdtz41NTVMnjyZRYsWxYbrP//88zid9SvSFxUVMXHiRLZt24bb7SYzM5OxY8fy2GOPnba97KsPHWT94oVU7N9DNBzGYDAQl5JK90FD6dy3/89KJCojUV4pruSrOh9eVUXzR4ns8WCo9GKp9SBHIyRF/eQeWMPi9R+zpbw8dm6c0859Izrz2CA7sh6pX8w2+Zz6OZU6DEDXdaqrP6ekdAHB4CFC0TA1AYlD3kzWlA2lg6cDQxUD7U1GnCYDkknGlOkk7tK2mNIdJyN0p5Su62zdupWNGzfi8XjQNA2DwYhJcWLzZiFFrCCB1WEip2cq5w1si7GZySwFQRCE088JvUorKChg8uTJrFq1itLS0tj2mTNn4vUeW/zT6/Uyc+bM+gvJMqNHj+bDDz9k586dzJ07lxUrVjSYFNLhcDBp0iRWrVrF9u3befjhh3n44Yd59dVXj1ufW265ha1bt1JYWMjixYtZtWpVg9mtTSYTt956K8uXL6eoqCi2httjjz12Ird/ytUeLuHTOa9QsmMrJouVhPR07AkJeKsrWfP+2+z4cuUJl+1RVB7dVcJHVW4MEmToMoEtNbgPe6lWNaJmSJEilAY8/L3w39RFYc6QIdRt28a+1e9zd/8UnnxvE3/8sAwSc8CWBBXboPBR2P8lVVUr2LN3JsFAMQou9tYmUBc009axl5uz3+FquQR7SGVPIEKNCSSzgch+D3Uf7iFaFTyJUTw1Nm3axKpVq/B6vTidTlyuBIJ1CuVVpZQqWzAnqMQlWlCjGtu+KGXdon3ompgRQxAE4UzR6hYjn8/HO++8w/r16ykrK2Pu3Lk8+OCDACQmJpKfnx+bqfqVV16JJT6JiYncfffdsXLat2/PPffcw9///vfYtl69etGrV6/Y5w4dOvD+++/zxRdfNLuMx/bt21m2bBnffPMNvXv3BuDFF19k5MiR/OMf/yAzM5OOHTvSsWPHBtf+/PPP+eKLL1p7+7+Iras+xVNdSWJ6G6Qja4UZTWbiU9LwVlexecUyOl5wERZ761tYlle5+d4XJNtqwizLHNpdTcgTwSZFUWWJOmccaUqEw2v+D7M9jryxT5C3/2NCi5fQoeMO/jYqldSkBP789mb+MLIbHVId9QlS7T7Ub17h0DnykQkks9lV4SWs6NhNDoKKnTbyYaIZq4hGxqEoKofqQiRnWTEkG1CqggTWl+EakXOyw3nSBAIBvv32W2RZjrVy+o/MzG01OonofmoiB2nr6Io93ozRpFC8tZqOvVLJyGk8MaogCIJw+ml1YvTuu++Sl5dHbm4u48aNY8qUKUydOhVJkhg/fjyDBw+mT58+AKxbt4527do1WU5paSnvv/8+AwcObPZa3333HV999RX/P3tnHh5Vefb/zzln9kwy2TcSCAiGXVAEUVB2UlAR8QUtVHGttuBCf/YVa1/lbautby0uaG0hlVpUQAUVpEpk3zdZJEAA2QnZM/t6lt8fgdEhCSQsCvR8risXzPM851m+c2bOPc9y37///e+jaTNnzuT+++/nlF/KdevWkZiYGDWKAAYNGoQoimzYsIGRI0fWq3f//v188cUX3HnnnWccaygUIhQKRV+fis4biUSIRCJnvLY5nKorEokQ9Hk5vGMbZpsdTRA43f+m1ZGIp6qSwzu307r79c1u68tKJwbACCiyQs1xL6KggqohaQIRUaAKjaP7vuaavncRtCSwLf1q0teuJCxWYkhK4+cDLPzuk13MWn2IZ0d0qKvYlo7Tt5ugLw6TrSXBiIzTH8YoCoCGRQFJsRNJ3IdWVo1JSyYkq9T6wyTHGRGsEsFvnVhcAUTbd7fl97X5sfn222/x+Xw4HI5onD+/OwyAKApIqhFXuIJ0y1VIohGDRcLnDnO4uIqUnAvrtftS0uVSQ9emcXRtGkfXpmGuFF2a0/9mG0aFhYWMGzcOgIKCAlwuFytWrKBfv37MmjWLadOmMXz4cABGjx7NhAkTouUB7rnnHj799FMCgQC33XYbM2bMqNdGTk4OlZWVyLLMCy+8wEMPPRTNczgc5OfnR1+XlZWRnp4eOyiDgeTk5GhMtFPceOONfP3114RCIR555BH+93//94xjfemll5gyZUq99MWLF2OzXfjwFEVFRUS8HmqqqxCNJjyBYIPlIl4vG9auZfeJyma3UWLLIASUayqKrBEMhhBVBTQVTQNN1fD5PWiqQlxCGqosUx7R8NVU4612EkFCE/y0SDRz8EQtFRUVdRVrKqE4NwGfitvvJKRAOCIgCaAqYFMF0IyoUhBZc6FF7MgK1NTWIvtAVEBSRL7+4ivCFrVBbX5sqqur8Xq9MR+wsF9CU0HRQEVFI0J5ZRkGzADIfoHd37goU3ZelD5dCrpcqujaNI6uTePo2jTM5a6L3+9vctlmGUYlJSVs3LiR+fPn111sMDBmzBgKCwvp168fFRUVFBUV8fHHHwNE9/J8n6lTp/L888+zd+9eJk+ezKRJk3jrrbdiyqxatQqv18v69et55plnaNu2Lffccw8AI0eObHAWqCnMmTMHj8fD9u3befrpp/nzn//Mr3/960bLn+rfKdxuN7m5uQwZMuSChwQpKipi8ODBqJEwn+3ehqoqWBPqL7+oiowHlRtu6kNet+ua3dbne45S4guSYTGhqRo11jARfwg0EUEQEUQBe1wComTA4yzHYTCQZdCIS07BnqphcNjxqBaO1ob4WYvk74zSsI9aMYg1Lg6HLRFZNVARdgMaRklEUAAlgKiZMJKEajShCiopSXaS4oyovgiCIDDgJzcgWmNnjE5p82NvlC8pKWHZsmU4HA7Ek0uc1REfYb+MwSQSUUOIgpEMRxaSYEDTNNyVQa7umkH3IbkXtC+Xki6XGro2jaNr0zi6Ng1zpehyasWnKTTLMCosLESW5WjUeqg7pWM2m5k2bVqMEQEQHx9fLy0zM5PMzEzat29PcnIyffv25be//S1ZWVnRMq1b1+0z6dKlC+Xl5bzwwgtRw+h0MjMzv5u1OIksy9TU1JCZmRmTnptb93Dq2LEjiqLwyCOP8Ktf/QpJavjUkNlsxmw210s3Go0X5QYxGo0YbTZade3OnjUrsMYnRB/Ap/A6ndiTkmnVues59eEn6UnsPlRGGDAbJJJz7JSWRJAEEVkQkFSNFA1y2/Vg7/Zl9OkygGvK92Ef0A9T3l44vpk3VgYJhBV+1ievrn+aBr5KErM6YbWLBIOlWCw5JNqMVHrDGCWBgKShSF5MVd0JR5IIywpmo0hinAlBAwIKlm5pmBOsjWvzI38or7rqKjZt2oTf748axnEJZsIBGVXVULQISeYsjGJdP0MBBaNJIq9z6kXr+6Wgy6WKrk3j6No0jq5Nw1zuujSn700+lSbLMu+++y6vvPIK27Zti/5t376d7OxsPvjgg2jZ8ePHxxzVb4xT+zS+v4+noTJnyu/duzdOp5MtW7ZE05YuXYqqqvTq1euM9UYikWgfLiU69xuEIz0TV9kJgj4vqqIQCQVxVZQjiiLdhgzDZD23pbzBKQl0i7dxPBihKiyTlJuAxWHGrxmJqAJJbjdSKEzWjf+FHA6y873n2OKvRRk4gJ2O/vxyfjm//aiYX/+kNTlJJgh5oOYgWBORej5Gbu59iJKZQPAoWQlgNWgoiger4QRuNQWp7GbsQQULArkOK0JQQa4JICVbiLsu8+wD+BGxWq306NEDTdNwOp1EIhHMcRKiWSMoezFqNpKMuSiyis8ZIuCN0KpLCmkt43/sruvo6OjoNJEmzxgtXLiQ2tpaHnzwQRyO2CWeUaNGUVhYGHP0/nQWLVpEeXk5119/PXa7neLiYp5++mluuukm8vLyAHjzzTdp2bIl7du3B2DlypX8+c9/5vHHH4/WM3/+fCZPnsyePXsA6NChAwUFBTz88MO8/fbbRCIRJkyYwN133x2d2XrvvfcwGo106dIFs9nM5s2bmTx5MmPGjLkkLWBHegYDH3yUr//9GSf2luDxVSFIIknZLegyYAitu/U4eyWNYDdI/G+7FhQeq2J5jZsqQcPeNQXLQTfiCTcmRcCJkZZmM8OH3sXCrcv45fLl/PLkacHU5ERevrcX/+8GI7iOgWSCFt2h5yOQ04MUQBAMHC+djd9/kDbJYap9cMjdgQ3lA8gVshlqE2ltNBIngyaoWNolEX9TCwzJlguk4MWjc+fOGI1Gtm7ditPpRFVV7ElGUrVWmNzZhN0SESGMNd5Ehz5pdLwp+7JzXqmjo6Pzn0yTDaPCwkIGDRpUzyiCOsPo5ZdfZseOHXTt2rXB661WK9OnT+epp54iFAqRm5vLnXfeyTPPPBMto6oqkydP5uDBgxgMBq666ir+9Kc/8fOf/zxaxuVyUVJSElP3e++9x4QJExg4cGDUwePrr7/+3SANBv70pz+xd+9eNE2jVatWTJgw4ayOI39MkjKzGXj/o7gqyvHW1mA0m0nNbYXYyLJfs+o2Gvh/rTO5r0UKhwNhJEEgv48FtzfM8WovnDjOVSYFW+btPJeby65du9izZw92u52bb74Zi9kMVfsgUAvWREi9Gr738E9OvomkpBvw+fYjK16MxhSq/Gnc7AthMxlol2pHrfSjRVSkeNNlYRCdQhAE2rdvT7t27aioqIh6vk5MTCTgDeOqCCCIAkmZNkwW3bG8jo6OzuWGoJ1+HlynUdxuNw6HA5fLdcE3Xy9atIhhw4ZdkjNYPya6Ng2j69I4ujaNo2vTOLo2DXOl6NKc57ceRFZHR0dHR0dH5yS6YaSjo6Ojo6OjcxLdMNLR0dHR0dHROYluGOno6Ojo6OjonEQ/NnOZoakakTIf4QPHOFRRSbnFQELb1lzdwoG7popwOIjRWMYJWebDL7dTU6Nxbdu23H9HAXFmI+7KCpzlZYgGifRWrZvlD0nTNGpKffg9YUwWA6m5diSpmba1pkH1t+A+DgYLZHUFY8NOHXV0dHR0dH5ozskwWrduHX369KGgoIDPP/+8Xv7MmTMBYpw8VldXM3bsWHbs2EF1dTXp6emMGDGCF198MbpDfN68efz1r39l27ZthEIhOnXqxAsvvMDQoUPP2J+amhomTpzIggULosf1X3vtNex2OwDBYJBHH32ULVu2sHv3bm699VY++eSTcxn6j0r4qAfX4r0c2lfGB4pKMRoBVJTlxzCbNbqmHqVTy3X87csI299fiuzxAvAO8N/ZLXn41tvokWIkEgggiCI2RyL5vfvSZcCQs7oBqDjsZvvSo9SU+pDDKpJBICHVSqebW9CqU0rTBlD9Lax9A0q3QsQPogTx2XDNPdDlrpgj/zo6Ojo6Oj8G57SUVlhYyMSJE1m5ciWlpaXR9KlTp+LxeKKvPR4PU6dOrWtIFBkxYgSfffYZe/fuZebMmXz11VcxTiFXrlzJ4MGDWbRoEVu2bKF///7cdtttbN269Yz9GTt2LMXFxRQVFbFw4UJWrlzJI488Es1XFAWr1crjjz/OoEGDzmXIPzrhYx5q5+3h2J4T/CUSZpOgYRI0HJKKJCr41AjrXKn87/smtvztM5JvvpGeM16m7+czaffnF9GSEnnjH39j8/6jONIzsCenEPL7+Prfn7Hps485k9eGqmMeVn+4j4qDbkwWCUeaBavdiKvCz4ZPD3Dom6qzD8B5FBb9Gg6tqpshSsoDeyZ4y2H1X2Drvy6cWDo6Ojo6OudIsw0jr9fLnDlzeOyxxxg+fHh0dgggKSmJwYMHs3r1alavXs3gwYNJSkqK5j322GP06NGDVq1aMXDgQH7xi1+watWq6PWvvvoqv/71r7n++utp164dL774Iu3atWPBggWN9mf37t188cUXzJgxg169etGnTx/eeOMNZs+eHTXa4uLi+Otf/8rDDz9cL37a5YCmafg2lBGpcvFV2MsxSSIbjTg0/EIIg6CSFleNPxTm+KfzyL5jOJ0m3oc9JxuDwUSrrtl0/MNvMLVszUfrNxFSQDIYsCclY7bFsW/jWmpPHG+07eKVpfjdYRzpVkwWA4IgYDBJJKRaUWSVb5YfQ44oZx7ENx9C7UFIag0WBwgiGMzgyKnznr11FviaYGDp6Ojo6OhcRJq9lDZ37lzat29Pfn4+48aN48knn2Ty5MkIgsD48eMZMGAAPXv2BGDjxo20bNmywXpKS0uZN28et9xyS6NtqaqKx+MhOTk5mjZz5kzuv//+6AzHunXrSExMpEeP78JkDBo0CFEU2bBhAyNHjmzuEKOEQqGYOG2novNGIhEikcg513s6p+pqrE65JkjoqIuwp4a1RjNWNCQ0/IKMiobREAFJpqpkG5oSIa3fiOi1gqaiqZBo8ZE0cjTHX/kD+0sr6NgyAwBTXByu8hMc3PY18WkZ9dr21oYoO+TCYjeiQb2ZJWuCEU91kNL9tWS1re8VvW5gfqS9i8EcDwhwenw6awq4jqB+uxytw4jYS8+izX8qui6No2vTOLo2jaNr0zBXii7N6X+zDaPCwkLGjRsHQEFBAS6XixUrVtCvXz9mzZrFtGnTGD58OACjR49mwoQJ0fIA99xzD59++imBQIDbbruNGTNmNNrWn//8Z7xeL6NHj46mORwO8vPzo6/LyspIT0+PHZTBQHJyMmVlZc0dXgwvvfQSU6ZMqZe+ePFibLZzC+J6JoqKihpMt3kl8mqt+EN+ggYHRlVFRUMRVTRAEBQ0BCJeF5I1HsmeCISJmjAaiAKYcnMBOF5eQar5u/08Ea+PHVu/5lik/nJa2C3irLUgGTUET71sAGS/wNpVG7DulRvMN0dc9KouQxGMyL6KBsvEhXx8u2k1hw827Fm1MW3+09F1aRxdm8bRtWkcXZuGudx18fv9TS7bLMOopKSEjRs3Mn/+/LqLDQbGjBlDYWEh/fr1o6KigqKiIj7++GOgbmls+vTpMXVMnTqV559/nr179zJ58mQmTZrEW2+9Va+t999/nylTpvDpp5/GGD4jR448r1mg5nCqf6dwu93k5uYyZMiQCx4SpKioiMGDBzfocl2pDeKsKkFyVWMDPKKIiIYkiAiApkkIaBjjE1H8HmRPDRCPcNI0EgTQgNChQwDkZGaQnlGnqaZpuFSZa667ji4DC+q17a0NUXR0F6JBwGyr3zc5ohIwhLnp5rZkXtXYjFEAafYHEPaDPb1+vqoguPx07nkzndoPa5Y2/6noujSOrk3j6No0jq5Nw1wpupxa8WkKzTKMCgsLkWU5GrUe6h6sZrOZadOmxRgRAPHx8fXSMjMzyczMpH379iQnJ9O3b19++9vfkpWVFS0ze/ZsHnroIT788MOzbpbOzMykoiJ2FkKWZWpqas57P5HZbMZsNtdLNxqNF+UGaaxeQ5oBc0sHclUKN7or+MQchwxYNAMeIsiyCaNiIC2/G+VGExVF80jpcB8AmiAiSlDjseGcP4fcVq1pm52GePIEmN/jxmyLo3W36xpsOyndSNZViRwursZiM8ZEitc0jYA7QkKqley2yUiGRrasGY1w9VD4+l0gFcTTbjtvOcSlYLiqX13ZZmjzn46uS+Po2jSOrk3j6No0zOWuS3P63mTDSJZl3n33XV555RWGDBkSk3fHHXfwwQcfRE+Yff+Y/plQT+41+f4+ng8++IAHHniA2bNnR5fkzkTv3r1xOp1s2bKF6667DoClS5eiqiq9evVqUj8udQRBIO6GbMLHXQwOBtmqhDkkSTgAq2rBLYSo8KViM4dpddd/cej9fyGHQrQcOQhzVjplu0o58e4cIqXHGD3qDoyCihyWCXjcKLJMlwFDSMrMbrT9Tn1bUHXci6sigDXBhNEkocgqfncYo1nimv65jRtFp+g6Go6shapvIS6lbr+REgFfZd2U1nXjwZZ85jp0dHR0dHQuMk02jBYuXEhtbS0PPvggDkfsksmoUaMoLCyMOXp/OosWLaK8vJzrr78eu91OcXExTz/9NDfddBN5eXlA3fLZfffdx2uvvUavXr2ie4SsVmu0zfnz5zN58mT27NkDQIcOHSgoKODhhx/m7bffJhKJMGHCBO6+++6Yma1du3YRDoepqanB4/Gwbds2ALp169ZUCX5UTFlxJN3ZHukrA7/aXcpcWWYbAgFNQBNEkswiXRNP0OmuIIXpd7LxX8v5esmK6PUJrfOZNOEJOllVPNXVdcZWUjId+vSjQ99+Z2w7OTuOm8dczY5lx6g84iHok5EkgZQcO536tiAnP+nsA0jIhmF/hvVvw5F14DpW58coqRV0Gwvtbz0/gXR0dHR0dC4ATTaMCgsLGTRoUD2jCOoMo5dffpkdO3bQtWvXBq+3Wq1Mnz6dp556ilAoRG5uLnfeeSfPPPNMtMzf//53ZFnml7/8Jb/85S+j6ffdd1/ULYDL5aKkpCSm7vfee48JEyYwcODAqIPH119/PabMsGHDOHz4cPR19+7dgfqnrC5lTNl2Un52DY7qfK4+fILSikoqrQbi81rRNsuBs6aKcHgUBTdUUf30r/l0WTHVNRo92rZj1OCbMBskfM5aXBVliJKB1NxWGEymJrWd0sJOv7H5uCoCBLwRTBaJ5Kw4BLEZThkTW0LBi3VGkes4GC2Q3hGky3d6VkdHR0fnyqLJhtGZfAn17NnzrAZG//79Wbt27RnLLF++/Kz9GD9+fL2luuTkZN5///0zXnfo5Mbjyx1BEDCmWjGmtqEdbWj3vTxrdJ9WHllA57H1lxLjEpOIS2zCDE8jbSdm2Eisf6q/eThy6v50dHR0dHQuMfQgsjo6Ojo6Ojo6J9ENIx0dHR0dHR2dk+iGkY6Ojo6Ojo7OSXTDSEdHR0dHR0fnJM0OCaJz8YiEFKqO+FEiCvZkC4npdWFHNFVlx6517D+4F9FoplvHG8jLbU0kEuGfHy3k8LFScnNyuO+u4RjDYUIle9AiMsacFuyLEzhQfhBLQOHa+DyScnMQzRJEglD2DUR8kNACUtrW+RPS0dHR0dH5D+acDKN169bRp08fCgoK+Pzzz+vlnzpa//3TY9XV1YwdO5YdO3ZQXV1Neno6I0aM4MUXX4yG1zhx4gS/+tWv2Lx5M/v37+fxxx/n1VdfPWt/gsEgv/rVr5g9ezahUIihQ4fy1ltvkZHx3fGpxx9/nDVr1rBz5046dOgQ9WN0KaCpGr7jBhZP30XAE0FTNQwmiYzWCVhyT7C0aA6hkBlEEwgC29ZsZ9eBb/n3ouX4nNXReiY/mshznTszItnBgYwkZg3tzb6kXIKiEQmVtKr13LrTzVgtnQTvLATPUVAVMFohqxvcOBFS2zXeUR0dHR0dnSucc1pKKywsZOLEiaxcuZLS0tJo+tSpU/F4vos06vF4mDp1al1DosiIESP47LPP2Lt3LzNnzuSrr76KcQoZCoVIS0vjueee45prrmlyf5566ikWLFjAhx9+yIoVKygtLeXOO++sV+6BBx5gzJgx5zLki8qu1SfwHDAR9EaIc5hISLFgMIrs//oblr43h1DEDgYziAoQYcfW7Xz0/sfk5GRw63+/xc/+toqnb7+fDpLE/1u3mpmyzCt3DmdHchvMWpjMSC3JaoBqMZ5/2rOYEdmD53hrsGdCUh4Y4+DQGlj0NNQc/LHl0NHR0dHR+dFo9oyR1+tlzpw5bN68mbKyMmbOnMmzzz4LQFJSEoMHD6Zz584AvP3221HDJykpicceeyxaT6tWrfjFL37B//3f/0XT8vLyeO211wD4xz/+0aT+uFwuCgsLef/99xkwYAAA77zzDh06dGD9+vXccMMNAFGHj5WVlezYsaO5w75oeGtD7NtUgSBCXJI5GsPMZJXweDcgx8UhCAY0wgAoqspXy1fRqf3V3HH7rXiTNIzuKn7iPMGgbjfwzDdbeH3rFvKMj9NCdiJqGmgakiCTjo8qLHye1JpBViudlFoMBjdYEsBkh5pvYccc6PfMmbqso6Ojo6NzxdJsw2ju3Lm0b9+e/Px8xo0bx5NPPsnkyZMRBIHx48czYMAAevbsCcDGjRtp2bJlg/WUlpYyb948brnllma1v3z5cvr378/BgwfJy8tjy5YtRCKRmGCz7du3p2XLlqxbty5qGJ0LoVAoJo7bqei8kUiESCRyzvV+nyO7qwj5I4gmDU1VUcW6SbyQv5qg4kQ1pSHIKpoRQOPAwcN4fX56974eSYlg8VeQUV2LMRLEm5jOre278rs1i9F2b0e8unVdI4KApqoIAiRpXsoNDtalBWlT1YI4o/O7zpgdsH8JSo9H6mKZXQKc0vlC6X2loOvSOLo2jaNr0zi6Ng1zpejSnP432zAqLCxk3LhxABQUFOByuVixYgX9+vVj1qxZTJs2LRr8dfTo0UyYMCFaHuCee+7h008/JRAIcNtttzFjxoxmtW+z2cjPz49Gyi0rK8NkMpGYmBhTLiMjIxpr7Vx56aWXmDJlSr30xYsXY7PZzqvuU3gPG/H5jBhsUFlZFU0PB0+gogECaHUbsDXA7fUBkJqWDKqKpsrIrrpgsOFIhCRHnVdrtboayKur7KRXck3TkDQNNAGXUcXjiuCTK6JtGpQAkhpi478/JWi6tAK6FhUV/dhduCTRdWkcXZvG0bVpHF2bhrncdfH7/U0u2yzDqKSkhI0bNzJ//vy6iw0GxowZQ2FhIf369aOiooKioiI+/vhjAF599VWmT58eU8fUqVN5/vnn2bt3L5MnT2bSpEm89dZbTe5Dz549owFkLzan+ncKt9tNbm4uQ4YMiW4YP1/2b65gS9VhgqqX9PRUhJMzRuGAAZdLqDNqBBBEEQENR7wdgMryarKzMhBEAwZHKpLBgMlopLq2bjO2mJYOCIAWPW0mCAIKIggaiRGRhEQDtqT07zrjqwRDEgN+MuKSmjEqKipi8ODBUWNYR9flTOjaNI6uTePo2jTMlaLLqRWfptAsw6iwsBBZlmOi1muahtlsZtq0aTFGBEB8fHy9tMzMTDIzM2nfvj3Jycn07duX3/72t2RF43w1j8zMTMLhME6nM2bWqLy8nMzMzHOq8xRmsxmz2Vwv3Wg0XrAbpGXHVIpXluKvFhBEMbrHyGxNxmJIIhIJo5pPtSXQpnUr4uPtrFm7gVH/dSdBWybH7C24ZvtqTH4vn5XsICkzA7F9F1TFhagBmoYgSSCI1AhWklQPN5WbsSTtRTxpiKEqEHJD+3sQ7ZfWbBFcWM2vJHRdGkfXpnF0bRpH16ZhLnddmtP3Jp9Kk2WZd999l1deeYVt27ZF/7Zv3052djYffPBBtGxDgV4bQlVVgJh9PM3luuuuw2g0smTJkmhaSUkJR44coXfv3udc7w9FnMNMfu9MNBW8NUHksIKqqIT8MvH2GzD6fGiqDBhAExCBoQP6sWfft3zw0SfsOh7guGTm4/hUnt26juKaSn7V7VpahGo5YUjEI5lQRImgaKRMtIOgcXvNQVqGDmEQykGVIVBbdxotuQ10u+fHlkRHR0dHR+dHo8kzRgsXLqS2tpYHH3wQh8MRkzdq1CgKCwtjjt6fzqJFiygvL+f666/HbrdTXFzM008/zU033UReXl603Cn/Ql6vl8rKSrZt24bJZKJjx45A3Ybue++9lyVLltCiRQscDgcPPvggkyZNIjk5mYSEBCZOnEjv3r1jNl7v378fr9dLWVkZgUAg2k7Hjh0xmUxNleGikH9DBjt37cAeseBzhlBVMJol2vfqQo+W2Xzx738R8EkgmUEw0alrR8wpDj5fuIwDr343I5eRnM60fgMYajTS56PPeX/oDexMbUWl0YakqWQrtYzwB/mv+Guwt/wXuGrqDCOjDdoNhF6P6VHvdXR0dHT+o2myYVRYWMigQYPqGUVQZxi9/PLL7Nixg65duzZ4vdVqZfr06Tz11FOEQiFyc3O58847eeaZ2KPh3bt3j/5/y5YtvP/++7Rq1YpDhw4BdRuoSkpKYnaYT506FVEUGTVqVIyDx+/z0EMPsWLFinrtnDrd9mMiCAK2LJnBQzrgqQyjyCr2JAv2JDPQjq49erHv2+3sPViCwWjimg69yEzPQlVV5v17KQePHadVbi53FfRHiIQJ7dtPphzhppwcjljgYMUhzAGFrvHXEp+dgWAUQRkMFbsgEoCELEhs+PSgjo6Ojo7OfxJNNowWLFjQaF7Pnj3RTp58aoz+/fuzdu3as7Zztnr69etXr4zFYuHNN9/kzTffbPS65cuXn7XtHxvJIJLWsv6mZ0EQuLptN65u2y22vCTxX7cOPq0SC9YunaMv2wBt4tMaagyyGjZidXR0dHR0/lPRg8jq6Ojo6Ojo6JxEN4x0dHR0dHR0dE6iG0Y6Ojo6Ojo6OifRDSMdHR0dHR0dnZM0OySIzg+PpqqE9u1DqalBtMdj6dAewdD0t06uCSLXBhEkAWNWHKLZgKqoVB3zEgrIWO1GUrLtCKJwEUfRdFQ1jMe7G0X2IoqJQP0N+YcOHWLNmjUIgkDX9leTYDIiSBLezFyqEbGIIp3tVixS021/b9hLSW0JiqqQG59Llr1xp6PBiEJxqZtQRCHDYaFNahyCcBb9ag9D7SGQTJDZ+ZLxLt4YtbW1OJ1ORFEkMzOzQWenF5OjNX6O1vgxGkQ6ZiUQZ9a/rnR0dC4+5/RNs27dOvr06UNBQQGff/55vfyZM2cCxDh5rK6uZuzYsezYsYPq6mrS09MZMWIEL774Ykx4jeXLlzNp0iSKi4vJzc3lueeeO6uzyJqaGiZOnMiCBQuix/Zfe+017HZ7tM6pU6eyceNG3G437dq14+mnn2bs2LHnMvwflMA331Dzz3cJfbsfLRRGMBow5bYk8Z67sd900xmvVdwhPCuPETrkRgspIAhIdiPBDBs7T/hxVQZQZA2DUSQp00bXAblktqnvjuGHQtM0qquXcbx0NoHAMTRNRhBMmC1xeL1tSErqSnV1NY888gjz58+Pnk4UBIHO7a8m65e/ojq3AsGeQFxcHNkWE2Oykrk9LfGMRktEjfDx3o9ZfGgxNcEaVE0lzhRHj4we3NfpPlKtqTF9/PybE3y4+RgnXAEUVcNqlOiS4+Chvm24Ks1evwF3Kax9HY5sgLAXBBHi0qHLXdBtbN0JwUsIt9vN2rVrOXLkCOFwGEEQiIuLo3PnznTv3h1Jki5q+ydcAf6+8gBbDtfiC8mIgkBavJnbr8nmrutyMDTD2NXR0dFpLuf0DVNYWMjEiRNZuXIlpaWl0fSpU6fi8Xiirz0eD1OnTq1rSBQZMWIEn332GXv37mXmzJl89dVXMU4hDx48yPDhw+nfvz/btm3jySef5KGHHuLLL788Y3/Gjh1LcXExRUVFLFy4kJUrV/LII49E89euXUvXrl35+OOP2bFjB/fffz/33nsvCxcuPJfh/2AEdhZT/tJLBIqLkeITMObkICUlEzp4kMqpU/GuWtXotYovQu1n3xLcU4MgCkhJFiSHiaAzSGBDGXFHPVjiDDjSLJhtBiqPeVnz0T7KDzY9nsyFpqrqK7498CoB/1FMxhSsllwkyY4kHubbAy9SUbGNwYMHs3LlSt54dSrv/e9veP3Rexl9+zB2Hy1l1Wt/QfJ5sFUcx+Ku5UQowquHyvmwvLbRNjVN4x/f/IP397yPL+IjIy6DnPgcDIKBZUeW8dKGl3CFXNHyH399nDeW7KfCHSQ93kzLZBs2k8T6AzW88FkxR2tOC1Toq4JF/w/2FoFkhKQ8SMiGoAvWvwnr/3qR1Dw3/H4///73v9m3bx+SJJGUlERCQgKhUIj169ezbt26i9p+tTfE858Ws7ykEpMk0jLZRpbDgisQoXD1Qd5Zc+iitq+jo6PTbMPI6/UyZ84cHnvsMYYPHx6dHQJISkpi8ODBrF69mtWrVzN48GCSkpKieY899hg9evSgVatWDBw4kF/84hes+t7D/e2336Z169a88sordOjQgQkTJnDXXXdFjauG2L17N1988QUzZsygV69e9OnThzfeeIPZs2dHjbZnn32W3/3ud9x4441cddVVPPHEExQUFDBv3rzmDv8HQ9M0nHPmoNTWYmrZEtFmq4ulZrFgzMlBDYaoff99tHC4weuDxdXIZX6kJAuizVi3TCYKeAIKEU0jU4Q4UUAQBIxmCUeqhaAvws4Vx87qS+pioCgBjh2bBZqM1ZqDJFkQBBGDIQ5VSyUcruRvf3ue7du389VXX3FT+3YEqyvJzm2FfdRYWv3+LwT27cG7diWSKBKqrSZD0DAIAu+VVlMbkRts94DrAEuOLMFhcpBmS8MoGhEFEYfZQYv4Fuyt3cuyo8sAcPrDzNl0BKMkkJ1oxWyQEAWBeIuRVsk2jtUGmP/1sdgGdn0KlSWQ1AqsSXWzRZKpzqmmOQGK50HNgYstb5PZvXs3FRUVJCYmYrVaEQQBSZKIj4/HYrGwa9cuqqurL1r7i3aWsb/CS8skKw6rEVEQMEoimQkW4swGFuwo5Uh106Nk6+jo6DSXZs/hz507l/bt25Ofn8+4ceN48sknmTx5MoIgMH78eAYMGEDPnj2BuvAdLVs27FG5tLSUefPmccstt0TT1q1bx6BBg2LKDR06lCeffDL6eubMmdx///3Rh/e6detITEykR48e0TKDBg1CFEU2bNjAyJEjG2zf5XLRoUOHM441FArFxHE7FZ03EonEeN4+X07V9f06I0ePESguRkxKQkOrZ6yIqSmEjx7Ds3071m7dYvI0TcNXXIlmAE0ETauLSRf2y0RCCpJBQNQ07EGZKsN3trEl3kjVcQ9Vx90kZtgu2PiaQq1zM8HQCUymDNST/QXQVA0QMEiJfPTRcoYMHUCHDh34dMGHSCYTQYOJXQnppDgEaq/pzonlS8jqPwg5FMLvdpGanMLRUITV1S4KUhLqtbv22Fr8ET8p5pRo7L5TSEgYBANLDy9leKvhrNlXQY03TIskS0wfAQQB4s0SK/ZW8rMbcrGbDaBpSHs+B8kCggSn1Y85EWoPou5fhtY9t1l6NXTPnC+aprF7924kSUIQhHp6mM1mamtr2bdvX8zy94Vs/8udJzAbBESRehonWiWO1ARYtbec0T0aD11zMbS5UtC1aRxdm4a5UnRpTv+bbRgVFhYybtw4AAoKCnC5XKxYsYJ+/foxa9Yspk2bxvDhwwEYPXo0EyZMiJYHuOeee/j0008JBALcdtttzJgxI5pXVlZGRkZGTHsZGRm43W4CgQBWqxWHw0F+fn7MNenp6bGDMhhITk6mrKyswTHMnTuXTZs28be//e2MY33ppZeYMmVKvfTFixdjs114w6GoqCj6f/OxY2RWVxNJiIdAoMHyJqeTg0uX4vveciYAGuSXxoMGcug7g0oNC8iyiKKBQRMIuL1U+L6bSdFUUEICy5asxJx42kP8IiMZtmMyedC0hjf41jp9VFb5adtW5POFC6g4UYqmgU9yElBVTHIES3YOtTu2Eg6FURUZt8tJQFHxigZWfV2KGvHVq3dzYDPeiJfKQGWD7QbVIAe8B/j888/ZUCni9YlUK56GyyoQVgQ+W7SYRDOIaoSbyg6DphEOVjR4TVzIx5FtG9h/IrXB/LPx/XvmfNE0jRMnTqBpGsFgsMEyoVCI7du3U15efsHaPUVEhWNldYZ6RajhJV1vQGDD1m+wV+w4a30XUpsrDV2bxtG1aZjLXRe/v+kzzc0yjEpKSti4cSPz58+vu9hgYMyYMRQWFtKvXz8qKiooKiri448/BuDVV19l+vTpMXVMnTqV559/nr179zJ58mQmTZpUL67ZmRg5cmSjs0BNYdmyZdx///1Mnz6dTp06nbHsqf6dwu12k5uby5AhQy7oL+ZIJEJRURGDBw/GaDTWpR0/TtnSpWAyIyXUP72kBoOoskKbQYOwNBCfrtZZglIbREr8ztAIB2SqAz4kCQwaWOxW0u2mmHw5rDBgUC8c6dYLNr6m4HQms//bNZhMiYjid33SVI3KqkoSE21kpMfh8UQYfuttfLZnO77aGpKSHNhEAdlsJXD0CNaUNExmE5GQhiMxEWtSCoFQhJvzrmJoAzNGnr0evi35ljR7WoMbtE/4TtAqoRXD+w7HvLuCjUV7SU60YmjgBF+VN0SSQeKO4ddiM52cMZr7AbhPQEJ6vfJoKji95HfvzdXdhjVLr4bumfNF0zQ+/PBDXC5Xg/e3pmnU1tbSrVs3rr322gvS5un1L6jZSrknSLrDUi9f1TT8NQFuuLY1w65r0Wg9F0ObKwVdm8bRtWmYK0WXUys+TaFZhlFhYSGyLJOdnR1N0zQNs9nMtGnTYowIgPj4+HppmZmZZGZm0r59e5KTk+nbty+//e1vycrKIjMzs94v0fLychISErBaG35QZ2ZmUlER+2tclmVqamrIzMyMSV+xYgW33XYbU6dO5d577z3reM1mc4NHlI1G40W5Qb5fr6FVK6xduuBfvwEhPh5B/G7JS9M01KpqTHl52Lt2RWigL3GdUvGsOIaggHByucxsNWI0SxCUUQwivpN7OE7VGfTKZLV1kJIdf/aj5xeY5OSeWI63IBQ8gcXSItq+KqqAhiK7GD36Fn7zm/ls27aNq3veyOaF84mLhOnoqmBphZPandvp9MTTqLKMJEnYEhxUyAppZiM3pyZiNNQ/TXVTzk0sOLgAd8RNkiUpJi+shFE0hYGtBmI0GrmxbTqp645Q7Q2T5Yi9HxVVwxtSKeicjSPue3kdboO100CT6/YWfR9fNZgdiG0HwDneTxf6XuzQoQNr1qxB07R6p898Ph8Wi4V27dpdtC/IoZ2zmLHqAIoKxtNOn9X4QiRYjdycn96k9i/W5/RKQNemcXRtGuZy16U5fW/y5mtZlnn33Xd55ZVX2LZtW/Rv+/btZGdn88EHH0TLjh8//qxH7IHoHoZT+3h69+7NkiVLYsoUFRXRu3fvRuvo3bs3TqeTLVu2RNOWLl2Kqqr06tUrmrZ8+XKGDx/On/70p5gTa5cqgiCQdM89GNLSiBw5guLxoMkyqs9H5OhRRJuN5J+Na9AoArB2TsWYbUd2BlF8ETRFBVkjwWrAIAicUMErq6iKRjgg46oMYo030uWWnB/cKAKQJDO5OT9DlEwEgkdRFD+qJiPLHkShCrM5k0ce+T29evViyJAhfLF5K6IjiYPffkv1++9w+H/+H7aOXbHe0JeIpmFMTqNUEUCD+7JTSWjAKALIS8hjaKuheCNeyn3lhJQQsipTE6yh1FtKh5QO9MvtB4DDZmTsDa3QEDha6ycQVpAVFac/wuEaP3kpNkZ2P20mo8PtdT6Lao+AvxqUCESC4DoGYR9cM6ZuY/YlQocOHcjMzKS2tha/34+iKMiyjMvlIhwO06VLF5KTky9a+8O6ZNI+K4GjtQFqfGFkRSUYUSh1BvBHFO7s3oKcpB92/5uOjs5/Fk2eMVq4cCG1tbU8+OCDOByxvm5GjRpFYWFhzNH701m0aBHl5eVcf/312O12iouLefrpp7npppvIy8sD4NFHH2XatGn8+te/5oEHHmDp0qXMnTs3xlfS/PnzmTx5Mnv27AHqvsgLCgp4+OGHefvtt4lEIkyYMIG77747OrO1bNkybr31Vp544glGjRoV3XtkMpku6pf8+WLJzyfjud9Q8+6/CO3eTcTlRDAasXRoT9Ldd2O7/vpGrxWtBhJvb4N3TSnB/U4UVxhEMKdYELqkEj7uI1zuJ+CVkQwCmVc56Novh7SWP57TwdTU/oiiieOls/H7D0b9GMlKW9q2fQ6Hoz1ffvklEydO5Ln/eT66mc4gSVzbqSNZP59IWVwcEbuDSFwcra0m7slKYUgDS2inEASBezvdS7I1mUUHFlEVqELVVOwmOz9p/RPGdhhLvOk7TW7rmoXVKDF381GO1fiRVQ2rSaJffhoP3NSa7MTTZjZtyfCT/4P1b8HBleA+XncyLSEbuo6BznddFC3PFavVyrBhw1i/fj0HDhzA7XYjCALx8fF07dqVLl26XNT2E20mptzeiX+sOci6b6spdQWRRIFMh4U7urXg9muyz16Jjo6OzvmgNZFbb71VGzZsWIN5GzZs0ABt+/btjV6/dOlSrXfv3prD4dAsFovWrl077b//+7+12tramHLLli3TunXrpplMJq1NmzbaO++8E5P/zjvvaKd3u7q6Wrvnnns0u92uJSQkaPfff7/m8Xii+ffdd59GnfvkmL9bbrmlqcPXNE3TXC6XBmgul6tZ152NcDisffLJJ1o4HG4wX1VVLXTwoObb8rUWKCnRVEVpVv2yO6QFD7m00FG3poaVaJ3Vx71a6X6nVnPCq6mqet7juFCoqqx5PHu0WudmzeXar33yyfx62pSVlWmffPKJ9umnn2oHSvZox0t2aWXf7tMOujzaRqdX+8bt0yJK88YUiAS0nZU7ta3lW7VKf+UZy4ZlRdt53KltPlStHa3xNa0B9wlNO7JB045/rWnhQLP6Vq/9s9wzFwK3260dOXJEO378+EVtpzHKXQFt86EabcdRpxYIy02+7ofQ5nJF16ZxdG0a5krRpTnPb0HTfgSnNZcpbrcbh8PR6ObUcyUSibBo0SKGDRt2Wa/hXgx0bRpG16VxdG0aR9emcXRtGuZK0aU5z2/dt76Ojo6Ojo6Ozkl0w0hHR0dHR0dH5yS6YaSjo6Ojo6OjcxLdMNLR0dHR0dHROUmzQ4LoXJrItbWE9+9HU1RMbVpjTG/A0/IPSE1NDU6nE0mSSE1Ox1UeQomoVGkKqu8giVU1ZNjjEdq0Z4/djF/RsIb8lCydh8tVSocO7ejbdxRgOmtbzcFVUYarohzRYCA9rw0myw/r4dsViLDnhBtF02idGlfPUeSF4IT3BEc9R5FEifykfOwm+wVvQ0dHR+dK5ZwMo3Xr1tGnTx8KCgpifAydYubMmQAxTh6rq6sZO3YsO3bsoLq6mvT0dEaMGMGLL74Ys0N8+fLlTJo0ieLiYnJzc3nuuefO6iyypqaGiRMnsmDBAkRRZNSoUbz22mvY7XUPhGAwyKOPPsqWLVvYvXs3t956K5988sm5DP2SQw0EqHn/fbxLlqK4XICGaI/HftONJI8fj3QRgn2eCZfLxZo1azh27BjhcJhwQEENSpgj6aieJNpoflobVSSDzCdpKp+W7eaEzcChuYWc+HAWauC7GF0dO07iL1N/DbQ77365qyrZsnA+x0t2EwkGEESRuMQk2t90C51uGYgoNewA8kIRllXe33CYf+8so8YXRtU07BYDvduk8HDfNqTYG44R1xyqAlX8s/ifbC7fjC/sQxREki3JDMkbwqirR2EUL98TJTo6Ojo/FOe0lFZYWMjEiRNZuXIlpd8LYDp16lQ8nu8CbHo8HqZOnVrXkCgyYsQIPvvsM/bu3cvMmTP56quvYpxCHjx4kOHDh9O/f3+2bdvGk08+yUMPPcSXX355xv6MHTuW4uJiioqKWLhwIStXrozxbq0oClarlccff5xBgwady5AvSTRZpvL113F99DFaOIwxKwtjdp3nZdeif1P+pz+hNhIM9GLg9XpZtGgR+/fvR5IkJMWC7BMJKSFqtIM4zHtpZ7Qh4WBhaipvX5VIqVni2LSXOT6rkJyRP6Hz7PcYUPQxv516O5FIhP+66zdUVCw4r375XU6WvvM3DmzbjGQ04EjPwJ6cQtDrYcvn89n6788ukAINo2kabyzdx7/WH8YfVsh2WMhNsiEJAl8WlzFlwS48wfOLXO0Kufjjxj+y7MgyDIKBnPgcMuIy8EV8vL/nff7xzT/QPXPo6OjonJ1mG0Zer5c5c+bw2GOPMXz48OjsEEBSUhKDBw9m9erVrF69msGDB5OUlBTNe+yxx+jRowetWrVi4MCB/OIXv2DVqlXR699++21at27NK6+8QocOHZgwYQJ33XVX1LhqiN27d/PFF18wY8YMevXqRZ8+fXjjjTeYPXt21GiLi4vjr3/9Kw8//HC9+GmXM4Ht2/GtWYuUmoohNRXBYECQJAxJSRizsghs245vzZofrD+7du2iqqqK5ORkjJIJnyuMKEpomhmDpuI2+vGKAVxSmAW5cahIxB38lsNfzKfDz39K1wfuoXW2FacxidpeI/jHP+4gzm5kztxFhEJl59yvvevXUHP8KInpmVji7AiiiGQwYE9OwWixsnvtSlwV517/2dh1ws3SPRUk2Uykx5sxSCKSKJBkM5GTaKO41MXSPRVnr+gMLDu6jJKaElrEt8BhdiAKIkbRSJotDYfJwZIjSzjgOnCBRqSjo6Nz5dLspbS5c+fSvn178vPzGTduHE8++SSTJ09GEATGjx/PgAED6NmzJwAbN26kZcuWDdZTWlrKvHnzuOWWW6Jp69atqzejM3ToUJ588sno65kzZ3L//fdHf/2uW7eOxMREevToES0zaNAgRFFkw4YNjBw5srlDjBIKhaJx3OC76LyRSCQajuJCcKqu5tbpXrUKNRxGsllRNTU202RE0zTcy5djufnmC9XVRlFVld27d2Mw1N1SAW8YVdEQjSJyWCVRE4mIKsfFWqoTc6ixiKQHZA6sLsJoj6PlsP6g1I0hXgiyI5LNnfZ47hrVgb/9bSvHjy+nTZu7m90vTVXZt2kdkskEooh62qyJ2R6Pq7yMg9u30qnfxZlNXL23An9IJs1urPc+GSQQBVhcfIJhnZq+L+z0e2bp4aUYBAMSUjQG4SnsBju1wVrWHltLy7iGP49XEuf6efpPQNemcXRtGuZK0aU5/W+2YVRYWMi4ceMAKCgowOVysWLFCvr168esWbOYNm0aw4cPB2D06NFMmDAhWh7gnnvu4dNPPyUQCHDbbbcxY8aMaF5ZWRkZGRkx7WVkZOB2uwkEAlitVhwOB/n5+THXpJ+20dhgMJCcnByNiXauvPTSS0yZMqVe+uLFi7HZLnwgy6KiomaVT9+2DWsgQKSi4dkGQzBITfEuNi9adCG6d0YURaG8vByAQCCA7BdRFAFZA03VEAUBBY0IMh5jXZBaSYOgsxprVhqS0YymaURCYQRBxY+VI1Ve0tIkIhGNTZtWs2dP8/dLqbJM+YlS0MAfURosE/H52LZlM4f94XMX4AxsOizi80Ol6m0wPxSGvYc9LFp0vNl1FxUVoWkaB7wHUDSFCl/D94JX9bJ552YSvv1h95z9mDT38/SfhK5N4+jaNMzlrovf729y2WYZRiUlJWzcuJH58+fXXWwwMGbMGAoLC+nXrx8VFRUUFRXx8ccfA/Dqq68yffr0mDqmTp3K888/z969e5k8eTKTJk3irbfeanIfRo4ceV6zQM3hVP9O4Xa7yc3NZciQIRc8JEhRURGDBw9ulsv1msNH8JSVN3oCLRIKY+3Sme7Dhl2orjaKpmnMnj0br9dLQkICPmcIV2UQySgSViMnZ2o0TBiIj2gIgCyAJSkN/7oK5FAQkyUek9lEULNgA1olxbGhTMZkEri+Z1/atG7+ODRN47M92/E5a7CnpDaY79Jkuve4no63DDxvHRqifO1h9m88SlqKFUEQ6uWHawN0yExg2LCmB2g9/Z5Zvmo5h92HSY+rfy9omkbQG+T6/OsZdvXFvxd+bM718/SfgK5N4+jaNMyVosupFZ+m0CzDqLCwEFmWo1Hroe5L12w2M23atBgjAiA+Pr5eWmZmJpmZmbRv357k5GT69u3Lb3/7W7KyssjMzIzOOpyivLychIQErNaGjzVnZmZScdqMiSzL1NTUnPd+IrPZjNlc/7SQ0Wi8KDdIc+uN79sH35Kv0Lw+pPj4mDw1EEAQBBL69//BbuYOHTqwfv16NE3DajfhrQmhqRoGScSrqCRoBnLUZNJrwqQEVWotAi1vHsKej/7J4c+KaPfTu9AAj2ahj+lbBI+bjz7aTb/+GbRoce7jaNezN1sWfYKmKEiG2Fve73ZhibPTutt1F02nm/PT+XT7CTxBhURbrPuBkKygajC4U+Y5tX/qnhnYaiDTd0xH1mRMUmwbtcFa7CY7N+XcdFl/sTWXi/U5vRLQtWkcXZuGudx1aU7fm7z5WpZl3n33XV555RW2bdsW/du+fTvZ2dl88MEH0bLjx48/6xF7ILoX4tQ+nt69e7NkyZKYMkVFRfTu3bvROnr37o3T6WTLli3RtKVLl6KqKr169Wrq8C5LrNdcg/2WW1BqapArKtDCYbRIBLmqikh5ObbrexB3Bu0uNB07diQ9PZ3a2lrCcgirw4iiyggEUQSJhHAcNtWCQzUz8rAHoybjbpVH69vGUFI4l61vzmT/t7Ukuo9jXvoh9903n4isMnr0HZhN5+6X6eobbiI1Nw93ZQUBjxtVUZDDYdxVlURCITrePICE1LQLqEQs+RnxFHTOxBmIUOYKEpIVIopKtTfEcWeQbrmJDGh/fn6n+uf2p2NKR0q9pdQEa5BVmZASotxXjjfiZUirIeQl5F2YAeno6OhcwTR5xmjhwoXU1tby4IMP4nA4YvJGjRpFYWFhzNH701m0aBHl5eVcf/312O12iouLefrpp7npppvIy8sD4NFHH2XatGn8+te/5oEHHmDp0qXMnTs3xlfS/PnzmTx5Mnv27AHqZikKCgp4+OGHefvtt4lEIkyYMIG77747ZmZr165dhMNhampq8Hg8bNu2DYBu3bo1VYJLDkEUSZ0wAUN6Bp7Fi4lUVoKmITkcJA4dQtI9P0VsYMbrYhEXF8ewYcNYv349hw4dQjOEMceDMWjDHM7EHUlgj+alrVFmaI1C8v445uc6MD32FGpWOsc/mMnxeYvYAywFevTI4t13n6O2NvtsTZ8Ra3wCAx94lK8XfcaR4u14qqsQRBF7cgod+/an/U23nL2S80AQBB675SrS7GYW7Cil0lPnxyjeYuSObtmMv7E1cebz87VqN9l5puczvLf7PdadWEeZrwxREEm1pjKszTBua3Nbg8t4Ojo6OjqxNPnbuLCwkEGDBtUziqDOMHr55ZfZsWMHXbt2bfB6q9XK9OnTeeqppwiFQuTm5nLnnXfyzDPPRMu0bt2azz//nKeeeorXXnuNnJwcZsyYwdChQ6NlXC4XJSUlMXW/9957TJgwgYEDB0YdPL7++usxZYYNG8bhw4ejr7t37w5w2ft2EU0mkseNxXHHHYQPfAuahqlVK6TExB+lP/Hx8QwePBi3243L5UKSJFKSUnFVBFFkFbeoEfIeQ6usZHiCg1tbteOA1Yiv94skvDiFvWv/jbP2OB06Xs213QtQFIFFF2DzeFxiEn1/eh/emmrcVRVIBiMpOS0xmC6sZ+3GMEgid/dsye3dstlX7kXRNFol2y6IY8dTJFoS+WX3XzKm/RiOeY5hFI1clXgVFoPlgrWho6Ojc6XTZMNowYLGnez17NnzrAZG//79Wbt27Vnb6devH1u3bm00v6FluuTkZN5///0z1nvo0KGztn05I9njsDZilP4YJCQkxGxQT29VZ4BkAZAUU7bj9/6ff+s9MXmKcmGPiNqTU7Anp1zQOpuDzWTgmtzEi9pGqjWVVGv9jeY6Ojo6OmdHDyKro6Ojo6Ojo3MS3TDS0dHR0dHR0TmJbhjp6Ojo6Ojo6JxEN4x0dHR0dHR0dE5yfmeEdS46miwT3L0b1etFSk7GfPXV53zs2lMTxFUZQBQFUnLsmK0Nv/2yM4hcHUQQBYzZcYinHyVXFSgvhkANWBIhswuIUkyRI0eO8Pnnn+P0+0nu2IWOvW6gldVMsnKIcLgKgyEeu70Doljf6VbI76fy8AFURW3QW/UPjaZp7C33UuUNEWc20DErAZPhwv+mOFLt51itH6NBpFN2AjaT/vHU0dHR+aE5p2/edevW0adPHwoKCmJ8DJ1i5syZADGnx7Zv384f//hHVq9eTVVVFXl5eTz66KM88cQTMde++eabTJs2jUOHDtGyZUt+85vfcO+9956xP8FgkF/96lfMnj2bUCjE0KFDeeutt6Jx15ra9qWGd9VqamfPJnL0KJosI5hNmNu2I/nee7F26dzkevzuMFuLDlO6z0kkqIAgYI030vbadDr2yUY6+ZBX3GE8q44ROuhCC9WVk+xGrF1Tibs+E0ES4ch62PA2VO0DJQSSGVLaQs+HIa8PTqeTxx9/nA8//JBgMBjtg7VNW/J/PZFeHUVuMywjRQxgtebSIvtuUlP717Uvy3yz5Ev2rl+N3+1CU1WMFgshkxXfjb1JTDs/J4jnwq5SN4WrD7CnzEMwomCQRHKSrNxzfUsGdki/IL6BSp0B/r7yAF8frsUXlpFEgTS7mdu7ZXPXdblIou5/SEdHR+eH4px+9hYWFjJx4kRWrlxJaWlpNH3q1Kl4PJ7oa4/Hw9SpUwHYsmUL6enpzJo1i+LiYn7zm98wefJkpk2bFi3/17/+lcmTJ/PCCy9QXFzMlClT+OUvf3lGVwEATz31FAsWLODDDz9kxYoVlJaWcuedd0bzm9L2pYZ35UoqX32V8KFDSMnJGHNykOzxBHbupPyPLxHctatJ9YT8EVbN2cvB7VWIokBCigV7kolIUOab5cf4+otDaJqG6o/g/Gw/wd3VCKKAlGRBcphQgwreNaV4VhxDO7wevvxN3WyRNQmSWoM1GSp2QdH/4N29jPvuu49//etf5A0cSv7Mj+j22TI6/e5FjEaNHU/+N8v3mnhHuZuQ1IKA/zAHDkylsmoJmqax6bOP2frlQkIBP/bkFBzpGQiShO/4EVa8O4OA13P2AV9A9pZ7mLKgmK1HnNjNBlom20iNM3G0xs/Ur/ayeFf52Ss5C5WeEM9/WsyKvRWYDCItk21kxFtw+iPMWHWQf649dP4D0dHR0dFpMs2eMfJ6vcyZM4fNmzdTVlbGzJkzefbZZwFISkpi8ODBdO5cN5vx9ttvR71hP/DAAzH1tGnThnXr1jFv3jwmTJgAwL/+9S9+/vOfM2bMmGiZTZs28ac//Ynbbrutwf64XC4KCwt5//33GTBgAADvvPNONG7XDTfc0KS2LyW0cJja995HDYUw5eZG04W4OEw2G5HDh6mdM5fMF54/64zFwe1VVB3zkpBiic4MSQjEOcwEfREObK+izbXpWI57iZT5kZIsdTNDdS0iJZhQ/RECO6uwls7FGHRBchs41a7JVmcg1R5kxafvsnDhQgr+azSVDz6JpGnEaQqGXu3IuObXbPjlFGrfKeTQH/7IBrUDQ60QCB7j2LH3wN+KfRvXYomLw2L/Lu6bxR6PIc5L1dHDfLtpPZ37D76gWp+J2RuPUOEJkpcSh3hyvBajRG6SjePOALPWH+bmdmlYTdJZamqcRd+c4NtKLy2TbBhO6m4yCGQ6LFR7Q3y67ThDOmWQk2S7IGPS0dHR0TkzzTaM5s6dS/v27cnPz2fcuHE8+eSTTJ48GUEQGD9+PAMGDKBnz54AbNy4kZYtWzZal8vlIjk5Ofo6FAphscR66bVarWzcuJFIJFIXRXz5cvr378/BgwfJy8tjy5YtRCIRBg0aFL2mffv2tGzZknXr1nHDDTc0qe2GCIVC0Thu8F103kgkQiRy4RwPnqrr1L+BrVsJHT+OITUFVVPrlReSkwjs3Eng8GGMLVqcse4D2yoQJRAk4WSE++8wWiUC3ghHiqvIOe5Fk0ATQTutTc0iolb4CAYFpNQ00LS6v++hWtOZ9fleJEki6/a7OCYIpCgREGQEIYDBaiN3xFD2vDWTlp4a1kqtGGwqxmhMJRg8zrfFnxIOBLA6EmP6qakqgighirBv0zry+/Rrsq7nQ4UnxOZDNSRajYBWT7tUu5ETzgAbD1Ry41Xn5jBSUTUWF5/AYhQRReq91w6bgSM1AVbtreCua2Pf59PvGZ3v0LVpHF2bxtG1aZgrRZfm9L/ZhlFhYSHjxo0DoKCgAJfLxYoVK+jXrx+zZs1i2rRpDB8+HIDRo0czYcKEaPnvs3btWubMmROzR2no0KHMmDGDO+64g2uvvZYtW7YwY8YMIpEIVVVVZGVlYbPZyM/Pj0bKLSsrw2QykXhaCIyMjAzKysoaHENDbTfESy+9xJQpU+qlL168GJvtwv+CLyoqAiBu1y5SXS4ixobfHkGWMXi87P33vwllNx5HTNOg8ogVTRXwR9wNlpF9At9s240lbEbQQA437MHc5pcxiOCv9aAJ/nr5ERWq3X4SE+LxCCKKrBAJhxHFMAajiqZK2FpmgaqhVJVTbW1Bmb8SEQ1RcFN9sBifL0S4orLB9n3+AP7Dh/n8889/kJhfZX6orpWIM2qEvQ2XcQcFlq/diLPk3MLKhBQ4Xi6BoFERbLiMLyCw4esd2Mq2N5h/6p7RqY+uTePo2jSOrk3DXO66+P31n1uN0SzDqKSkhI0bNzJ//vy6iw0GxowZQ2FhIf369aOiooKioiI+/vhjAF599VWmT59er56dO3cyYsQInn/+eYYMGRJN/+1vf0tZWRk33HADmqaRkZHBfffdx8svv4wo1i0z9OzZMxpA9lxorO2GmDx5MpMmTYq+drvd5ObmMmTIkJhwF+dLJBKhqKiIwYMHYzQaCWRnU7lmLaLD0WAQWMXtBpOZq2+9FWNm5hnr/qp8N7VlfuJT6sfL0jQNd2WQztdmk3rMg1wTREqs356maaiaB4sIcYl2MMfXLxPykZao4HS7iVdkJIMBIyZEQURAQhDBe+gYgigipmWRapbJtKehqiHC4TAJrbvg27sbR3pajOGjqSqVlVXE2SwkZeVEje6LTZU3xKLqrYiCQKKt/sm5sKwS9oQYcFMHbmhz5pnHxlBVjc9qvqbaGyLdUf/9UTWNQE2A3te1Zlj3+jNG379ndL5D16ZxdG0aR9emYa4UXU6t+DSFZhlGhYWFyLIcE7Ve0zTMZjPTpk2LMSKgLqDo6Wm7du1i4MCBPPLIIzz33HMxeVarlX/84x/87W9/o7y8nKysLP7+978THx9PWlpag33KzMwkHA7jdDpjZo3Ky8vJPM1oOFPbDWE2mzE3YJgYjcaLcoOcqtdwzTW4WuYSPnwEKSennqGg1jqJu/FGbN/bf9QYbbqls3nRITRFi+4xOkXAJ2OyGGjVKRVTogXP8qMICginlVP8EcQ4G5YUEbG6CiwJ3+0xgrqpKX8l427pypwv13Nk3mwsj/0av2TArgpomhXFX8nRT74kvW8vBLuDm0xfIyAQiVRhteaSkzOCfSsPE/Z5scZ/Z3SqooimKGgaXN2z9w/2wcxKMtKzdQpf7S4n0WaK7jGqG65GpTdMdqKN69ukYjSe+x6joZ2zeGf1QRQVjFKs7tXeEAlWEzfnZzQ67ot1L14J6No0jq5N4+jaNMzlrktz+t7kU2myLPPuu+/yyiuvsG3btujf9u3byc7O5oMPPoiWbSjQK0BxcTH9+/fnvvvu4w9/+MMZB5CTk4MkScyePZtbb701OmN0Otdddx1Go5ElS5ZE00pKSjhy5Ai9e/dudtuXAoLJRPLPfoZosxI5ehTV70eTZRSPh8iRIxjT0ki6e0yT6mrdNZX0VvG4q4MEPGFURUWOqHhrQ4SDMlddl05ihg1rpxSM2XYUZwjFF0FTVDRZRXGF0EIy1mvSMN5yN9iSoeYAhDygynX/1hwEayI33zGeO++8kyWffoLrz1NwHjxAldfLkeU72DjpJcIuD0njH+IqqZJeUjGB4FFE0UJuzr2ktGhNfu++hAN+PNVVyJEwqiITcLuQ/R7S8tpwVY9eF1n5WO7u2ZIsh5VD1T7cgQiyouIPyxytDWA2iIy/MQ/LeRhFAMO7ZJGfGc+RmgA1vjCyohKMKJQ6AwRlhVHXtiDLYb1AI9LR0dHRORtNnjFauHAhtbW1PPjggzgcjpi8UaNGUVhYGD2B1hA7d+5kwIABDB06lEmTJkX3/0iSFJ0N2rt3Lxs3bqRXr17U1tbyl7/8hZ07d/LPf/4zWs/GjRu59957WbJkCS1atMDhcPDggw8yadIkkpOTSUhIYOLEifTu3Tu68bopbV9qxPXuTfrTT1M7ew7hgwfQIhFEsxnb9deTNG4slquvblI9JquBvqOvZvuyoxzbXYOnNowgQJzDRLvrM8jvlYkgCAgWA4m3X4V3zXFC+50orjAIICWYsHVLx9Y9HcQcKPgjbPw7lO8CfzVIJmjRHXo+QlxOD2bMuIbU1FRmzZqF56svvxtPpy5cO+039G7rZrhhISYljM1+NS1a/JTkpDoD9rpb78Ca4GDPmhX4amvQNA2jxYq91VXccu9DmG1xF0Xrxrgqzc7/jujEO2sOseOYE2cggkESaZcRz097tqRPu/N3PpkcZ2LK7Z34x5qDrD9QQ6kriCTWnUob2b0Ft1/T+B4yHR0dHZ2LgNZEbr31Vm3YsGEN5m3YsEEDtO3btzd6/fPPP68B9f5atWoVLbNr1y6tW7dumtVq1RISErQRI0Zoe/bsialn2bJlGqAdPHgwmhYIBLRf/OIXWlJSkmaz2bSRI0dqJ06caFbbTcHlcmmA5nK5mnXd2QiHw9onn3yihcPhenmqomiBkhLNt+VrLXTwoKaq6jm343OFtBPfOrWygy4tHJIbLSe7Q1rwkEsLHXVrariBcqqqaRUlmnZ4vaZV7Kl7fRoVFRXae++9p731979rs1ev1zY5vVp5MKT5fAe1WudmzePZo6lqw30Ih4Laif17teMluzRnZUWj2vxQqKqqHaryapsPVWu7Sl2arJz7e3AmTjgD2uZDNdqOo04tGGn8/dG0M98z/+no2jSOrk3j6No0zJWiS3Oe34Kmaed2pOY/ELfbjcPhwOVyXfDN14sWLWLYsGGX9RruxUDXpmF0XRpH16ZxdG0aR9emYa4UXZrz/NaDyOro6Ojo6OjonEQ3jHR0dHR0dHR0TqIbRjo6Ojo6Ojo6J9ENIx0dHR0dHR2dkzQ7JIjOD0fI76fy8AFURcUfp+GyBDGJRq4Kt8QUkhAtBoxZdiKCRrE3iFdWSDUZaB9nQRAEKioq+PyLIvaX1RJn1eiSAa3TUsnvfTtGS9OOvmuqRtVxL0FfBLPVQGqOHVFqoj2taVBZAt4yMNkhsysyImVlZYTDYex2O2lpaT9IiA8dHR0dHZ2mcE6G0bp16+jTpw8FBQUNxhubOXMmQIyTx+3bt/PHP/6R1atXU1VVRV5eHo8++ihPPPFEzLWhUIj//d//ZdasWZSVlZGVlcX//M//8MADDzTan2AwyK9+9Stmz55NKBRi6NChvPXWW2RkZETLPP7446xZs4adO3fSoUMHtm3bdi5D/0FQZJlvlnzJ3vWrcTmrcAZq8YthTMnpdLBfjywfJVFyEG+NZ20LM/NyjByXNCKahkUUaCcJVLz+Jz57/z3kSDhab2KbfG6750ZG7n6Lq7LuoMsdk85olJQdcLFj6VFqy/zIERXJIOBIt9GlXw45+UlnHkT5Llj3JpR9A3IATTBQYujA13TBqZhRVRWDwUBmZia9e/eOea90dHR0dHR+LM7JMCosLGTixIkUFhZSWloaDREydepUHnrooWg5j8fDjBkzeOqpp9iyZQvp6enMmjWL3Nxc1q5dyyOPPIIkSUyYMCF6zejRoykvL6ewsJC2bdty4sQJVLV+hPnv89RTT/H555/z4Ycf4nA4mDBhAnfeeSdr1qyJKffAAw+wYcMGduzYcS7D/kHQNI1Nn37E7tXLwShRJtbitwRpoWZzY2AAJtlKld1HlVDLkYTWzLaJhGsjZCZasMSZ8MkKcyY+gmvzejL7/ZSW13TAYZOp2LWL3V99wZxpn+Ge+AAPWWchzVfodOevG+xH2UEXaz7aR9AvE5dgIs4kIkdUak/4WDd/P73vuIqc9o3ECKvaB188A+7jYM+A+Ax2uWysqkhE5RhxKZkYkrIJh8McPXoUp9PJ8OHDL1lnmzo6Ojo6/zk02zDyer3MmTOHzZs3U1ZWxsyZM3n22WcBSEpKYvDgwXTu3BmAt99+O+oN+/QZnzZt2rBu3TrmzZsXNYy++OILVqxYwYEDB0hOrnvo5uXlnbE/LpeLwsJC3n//fQYMGADAO++8Q4cOHVi/fn3U+/Xrr78OQGVl5SVtGFUfO8K+Teuw2O1U4cbvDWI1WOggdsMsWPGEa5EUI4rJwEdJIhEJWgRBcIYR40x4v95A7doVZI57geT8TqSLB9BkMzldriWlZWuWTfs/Ni/fQ6/sq4kLz+FqzyMY4xNj+qBpGjtXHCfoi+BIs0ZnlYwmiYRUC+6qIN+sOE52u8SGl9W2zgL3MUi+CgSRkCqw2ZOOJokk4gXPcUjIwGw2YzKZqK6uZuvWrWcN6qujo6Ojo3OxabZhNHfuXNq3b09+fj7jxo3jySefZPLkyQiCwPjx4xkwYAA9e/YE6sJ3tGzZstG6XC5X1AAC+Oyzz+jRowcvv/wy//rXv4iLi+P222/nd7/7HVZrXbyo5cuX079/fw4ePEheXh5btmwhEokwaNCgaD3t27enZcuWrFu3LmoYnQuhUIhQKBR9fSo6byQSIRKJnHO9p3OqrkgkwqEdWwkHAlgSHFTXHEASROJJIFlIx6/50QSQ/AoHMxxUmwxkRSIgmdDCCoo/woHP5mNr0Rpb256ETBHCYTNGZEDD6kgkp+u1nNixhm0FT9IzbztH184ld8D9Mf1xlvupOubBEm+scxF+mg9Qa4IRZ7mfskNO0lrGxw7GX4N0cDWYk076F1c57IvDI0skGCJomBDkIJq/Bs1WF1LDYrFw6NAhnE4ncXGxe5++r43Od+i6NI6uTePo2jSOrk3DXCm6NKf/zTaMCgsLGTduHAAFBQW4XC5WrFhBv379mDVrFtOmTWP48OFA3bLYhAkTouW/z9q1a5kzZ07MHqUDBw6wevVqLBYL8+fPp6qqil/84hdUV1fzzjvvAGCz2cjPz4964CwrK8NkMpGYmBhTf0ZGRjQm2rny0ksvMWXKlHrpixcvxmaznVfdDVFUVET1N1/j8/kIVpYTVEIIAIKEKIpEtDBoGpqs4NZUVIBwhLAAoirgrXHiOnEcY1oOoIIgIGsSBk2OtmFPyyCydRNu2Q6Sxu6dm/kmGLu/J1Qr4nJakMwaQgMTQpoGSkBg1fK1WFKVmDxbqJzrayuJSDYUb127FZF0ZEVB0UIogKTKeGurCXrrlkhVVUVRFL788kssFkuj2ujUR9elcXRtGkfXpnF0bRrmctfF7/c3uWyzDKOSkhI2btzI/Pnz6y42GBgzZgyFhYX069ePiooKioqK+PjjjwF49dVXmT59er16du7cyYgRI3j++edjlk9UVUUQBN57771ooNq//OUv3HXXXbz11ltYrVZ69uzJnj17mtPtc2by5MlMmjQp+trtdpObm8uQIUMueEiQoqIiBg8ezC4jbK8sIyEtg8qaKiJKBE2SUQUVE2YiQhAMIomIiIBmMmLCBIpKYko8iS1yOLFpMyCApmEQZL6/v9pTfgJTfCKJBg8oAh079yJnwLCY/jgr/Cw9vgeDScJkrX+LREIKIZPMzf2vJjXXHpsZqEWaM6fOerKl1LXpj8NQKSEZzEioCLKCIymVhJP5p27YgoKCegbn97W5nN3RX2h0XRpH16ZxdG0aR9emYa4UXU6t+DSFZhlGhYWFyLIc3WwNdcssZrOZadOmxRgRAPHx8fXSdu3axcCBA3nkkUd47rnnYvKysrJo0aJF1CgC6NChA5qmcezYMdq1a1evT5mZmYTDYZxOZ8ysUXl5OZmZmc0ZXj3MZjNms7leutFovCg3iNFopPU117Jn1TIifh+p1hSOe0vx4KFaqyBLyEHWgsg2iTyPm9RwEk6rhbigimiSkKwmrhpxFwc+m4dvz1rSOl6DSQqjqRIg4Kup5vg3W8m6cRjdUr5B9NhpOeK/kE4bS2p2Aqm5CZR968JsNcScXNM0jYAnQkq2nYy8RETxtFNtxnRo0w+K59cZRqJIK1uQBKOMVzaSiAeMFgRbMoIooqoqwWCQjh07xrzvDWlzOX8oLxa6Lo2ja9M4ujaNo2vTMJe7Ls3pe5MdPMqyzLvvvssrr7zCtm3bon/bt28nOzubDz74IFp2/PjxMUf1T1FcXEz//v257777+MMf/lAv/6abbqK0tBSv1xtN27t3L6IokpOT02C/rrvuOoxGI0uWLImmlZSUcOTIEXr37t3U4V0yJGfncPUNNxHy+7EFDMQJVkKRILsDWwjIXuymJFRJxKhq3F2jYZHhuFkg7DAho2G55jqS+w+h4qOXqVo6n9KyCD6/h4Ob17H6H29iiE+iV7+2dDHvJSP7Z0j2+jNfgiDQtV8O1ngjrsog4YCMqmiEgzKuyiBmi4GuA3LqG0Wn6D4OklpB7QEIODERoae9DEkJUatYCdtboCIQDAapra0lMTGR7t27X2RldXR0dHR0zk6TZ4wWLlxIbW0tDz74YL1f9qNGjaKwsDB6Aq0hdu7cyYABAxg6dCiTJk2K7v+RJCl6TPunP/0pv/vd77j//vuZMmUKVVVVPP300zzwwAPRzdcbN27k3nvvZcmSJdHZpQcffJBJkyaRnJxMQkICEydOpHfv3jEbr/fv34/X66WsrIxAIBD1Y9SxY0dMJlNTZbjoCIJAj1vvxOZIYs+aFWjVCs6Ikxqhin/Hf0WHuB60CregheDgGm88GYkm5uUYOSSoVAfDWESR+157i5q/v8bswkLKlp8yWAVS23dm5JjrGJ62kbz0R+k4/LFG+5HWMp6+o69mx/JjVB31EPDJSAaB9FbxdL4lh6yrGp/dIbk1DPszrP8rHN8MLiftRQOGbBtb6EJN2IDqcmE0GmnTpg29evUiJSXlwgqpo6Ojo6NzDjTZMCosLGTQoEENLneMGjWKl19+mR07dtC1a9cGr//oo4+orKxk1qxZzJo1K5reqlUrDh06BIDdbqeoqIiJEyfSo0cPUlJSGD16NL///e+j5f1+PyUlJTE7zKdOnYooiowaNSrGweP3eeihh1ixYkX09akZilOn2y4lREmic79B5N/Yl+qjR1AVmbBdwmnwYxKN5Cm5SEEQzRLD0m0UCLDXF8SrqKQaDeRZTQhvvM5rv/8dS5at4EC5E6sF8pNkWqal0bZHAWITphXTWsYz4GftcZb7CfpkzFYDSVm2pnmqTrkKhv8Zag+BpxxMcbRNa09rBCorK6Oer79/KlFHR0dHR+fHpsmG0YIFCxrN69mzZ70j3afzwgsv8MILL5y1nfbt259x93u/fv3qtWWxWHjzzTd58803G71u+fLlZ237UsNoMpN5Vf19VacjAR3s1nrpDoeDO++4/bz6IAgCSZlNCx/SIEl5dX8nkeC8937p6Ojo6OhcLPQgsjo6Ojo6Ojo6J9ENIx0dHR0dHR2dk+iGkY6Ojo6Ojo7OSXTDSEdHR0dHR0fnJM0OCaLzw+LyR9hT5iaiKNhVHwlGjbi4ONLT01FkmV07d3O8wok1MYlru+aTYG2a64FwUKbqmBdVVolPseJIs1IZjrDPF0Lxhmkd0EgzGjBmxSFarqDbpOYAOI+CwQyZXcDUtI3loVAFfv8BQMRub4fRmBTNq66uZsmSJYRCIbp37x4Noqyjo6Oj0zQ0TSN84AByRQWi1Yq5Y0fEH8mVzjk98datW0efPn0oKCiIiXV2ipkzZwLEOHncvn07f/zjH1m9ejVVVVXk5eXx6KOP8sQTTzTYxpo1a7jlllvo3Llz1OdQY9TU1DBx4kQWLFgQPbb/2muvYbfXhatYvnw5U6dOZePGjbjdbtq1a8fTTz/N2LFjz2X4PwjBiMJ76w/zRXE55U4vgUAAgybT0uynl8NHvKRS/e1BQtUVoKooopEvHJnkD76NcQU9MTYU9R5QVY09606wd2M5fndd7DXZKrG1o5U9KRLuQAQ1rJAgQx+3xjifRGrnNOw9MxEMl/EEY+1hWPtGnV+lsA8ECeIzoeto6Ho3iA2PLRJxc+RoITU1q5FlDyBgNCaSljqQ9PQx/PrXzzF9+vSYYMN9+/blH//4B23btv2BBqejo6Nz+RL69luq35lJaNcu1GAQJAljVhaJd95J/NAhTXMRcwE5pyddYWEhEydOZOXKlZSWlkbTp06disfjib72eDxMnToVgC1btpCens6sWbMoLi7mN7/5DZMnT2batGn16nc6ndx7770MHDiwSf0ZO3YsxcXFFBUVsXDhQlauXMkjjzwSzV+7di1du3bl448/ZseOHdx///3ce++9LFy48FyGf9FRVY3XluzjvY1HcHp9GIIu7ISQRJH9oQSKquI5dLSUgEEkYnOg2pMRTWZstUfY+8m7vPXp+kbdJ+xYepRtXx0h5I9gTzRhS7WwIE/iKyFMoNJPhlsmOyKgGgQWpopMTVZxri/FvezoWV0yXLJ4yuDfv4Zvl4LBUuc+ICEL/FWw5jXYNKPByxQlyL79L1JeXmf8Wy05WCzZaGqY46VzGDWqD3//+9/5n//5H0pLS/H5fHz44YeUlZVx8803x3w2dHR0dHTqEz5yhLLf/x7/5s0INhvGnBwMqanIZWVU/fUt3D/Cc7rZhpHX62XOnDk89thjDB8+PDo7BJCUlMTgwYNZvXo1q1evZvDgwSQl1S05PPDAA7z22mvccssttGnThnHjxnH//fczb968em08+uij/PSnP21SSI/du3fzxRdfMGPGDHr16kWfPn144403mD17dvTB9Oyzz/K73/2OG2+8kauuuoonnniCgoKCBtu+FPjmuIvlJRUk24yIIS8CGmaTEbsREg0KJ4JGjskJYDBisNsQBBGMFlR7KnERD/vXLGN/hbdeve6qAPs2l2MyS9gTzUgGkb12+DZBJEOGpKCGABgkgWRVIEOBLfECX6cYCO6uRi5venTiS4qdH0PVvjqP3BYHCCJIJkhoAUYb7JgDruP1LqupWYXbtRWLOQuTMRlBkBAFAyZTKntLRP797528+eb/8Oyzz5KVlYXNZuOuu+5i5cqVhEIhXnnllR9hsDo6OjqXD85584mUnsDUsiWS3Y4giohmM8bsbBAlnHM/RPnehMsPQbOX0ubOnUv79u3Jz89n3LhxPPnkk0yePBlBEBg/fjwDBgygZ8+eQF34jpYtWzZal8vlquf5+J133uHAgQPMmjUrxuP1KWbOnMn9998fnb1Yt24diYmJ9OjRI1pm0KBBiKLIhg0bGDlyZKNtd+jQ4YxjDYVCMUskp6LzRiKRGM/b58upuk79u2pvOcGwgsOoEolEMEgSGnXjFVQZNJWjYip5mgvNINWZt6oGAqgmGwm1h1i+4yB5/WLHd3hXFSG/TEKaBfWkft/EgSqAXa67XpE1JFNdnkUDFViTAD0rFHwl1cSl/LBrvqdr02yUCFLJFyf3EomgqrH51mRwHkL9djlal9ExWZWVy9A0DUE0oWqx1y1adIysLAt9+5rq9S0lJYX77ruPf/7zn/zxj388t36fhfPW5QpG16ZxdG0aR9emYS6mLorHg2/9esSEBDQBtNO+Z8WUZCLHS/GsX09cv37n1VZz+t9sw6iwsJBx48YBUFBQgMvlYsWKFfTr149Zs2Yxbdo0hg8fDsDo0aOZMGFCtPz3Wbt2LXPmzInZo7Rv3z6eeeYZVq1ahcHQcNccDgf5+fnR12VlZaSnp8cOymAgOTk5Go/tdObOncumTZv429/+dsaxvvTSS0yZMqVe+uLFi7HZbGe89lw45fF7yyERvx9qQjKyLKN+72GuKQoSAgHNiCorCJKIHJHRZBkASVFBibB9+w4W+Q/G1O85aMTnMxLSvrO+K5LjIWxAUwENVE0jHFKi+YImclxW8Pr8HN1Rywnn1gs+7qZwJm/oZ8Kg+OldcRwNkYi/osEycSEfh7as5cBRe0y62VKMKAZxe+pfd7zUSYsWFg4c3M6ePYvq5UciEaqrq1mwYAGSJJ1T35vCueryn4CuTePo2jSOrk3DXAxdDLW1ZFdWoJjNaHLDhovR6+XIqlV4/Oe3YuFvxvXNMoxKSkrYuHEj8+fPr7vYYGDMmDEUFhbSr18/KioqKCoq4uOPPwbg1VdfZfr06fXq2blzJyNGjOD5559nyJAhACiKwk9/+lOmTJnC1Vdf3WgfRo4c2egsUFNYtmwZ999/P9OnT6dTp05nLDt58mQmTZoUfe12u8nNzWXIkCEkJNSPSn+uRCIRioqKGDx4MEajkeOrDnJoy3GSbHVxxQyShHAykr0SkVFkFZsQQDz5wDUaDXDy/1JYJoSJ7t2vYdjN7WPaKVlfzraaoySkWaKb2TINUG4CIawgqBqiIGAyf/cgVw2QEzFgjxNJvyaD7r2zLti4m8Lp2jQbVUaa/QH4ayA+vX6+poLTR4ceN9G+87CYrH37N+FybcRiqX9dTk4SK5YfoE3ra2nTZli9/CVLlpCens5tt93W/D43gfPW5QpG16ZxdG0aR9emYS6mLorHw4kvvkRTZKQG4mZqsowcCpN3yy3E3XzzebV1asWnKTTLMCosLESWZbKzs6NpmqZhNpuZNm1ajBEBEB8fXy9t165dDBw4kEceeYTnnnsumu7xeNi8eTNbt25lwoQJAKiqiqZpGAwGFi9ezIABA+r1KTMzk4qK2F/0sixTU1NTLybXihUruO2225g6dSr33nvvWcdrNpsxm8310o1G40X54Jyq9+b8DBZ+U05EEDEZjXXLaaIRAVBFAwgyuWoVGASEsFy33oUAmooQDuBO7UC/rq3r9bFVp1R2rykj5JWxJdQtiXXxaXwTDx6DQEJIQzIKCNQZTX5BwwD0cYFokbC1T/3RvjDOXXMj5A+DTdPrjCDptFveUwnWRMS2A+C0+tPTBuB2bUJTQ0hSbCy6W4fnMHfObr76ys0vfxl73dGjR3n33Xd59NFHL7peF+tevBLQtWkcXZvG0bVpmIuhizE5GXvfPrgXLEBITEI4bXY9UlWNMTWV+F69kM6z7eb0vcmbr2VZ5t133+WVV15h27Zt0b/t27eTnZ3NBx98EC07fvz4mKP6pyguLqZ///7cd999/OEPf4jJS0hI4Jtvvomp+9FHHyU/P59t27bRq1evBvvVu3dvnE4nW7ZsiaYtXboUVVVjrlm+fDnDhw/nT3/6U8yJtUuRTtkJDO6YgSsQQTbZUQSBYDiCJwwuWSLHGiHH4IFIGNnrQ1MUhHAA0VuNz+Sg/c2DaJNa3z9PfLKF9jdkIodVPDVB5IjCVR6NfKdKhQGqrQKKAGFVo0rUqJSgp0ujW42MtXMahrT6gWovCzqPgrR8cB6qmzlSZIgE6vwZKSHo/rO6o/unkZR0E4mJPQmGygiFq1DVCKoaJhSqoG07jZEjr+PJJ//As88+y759+6isrOSdd96hb9++JCYm1vtRoKOjo6MTi2PEHRhzcokcPYLicqHJMmogQPjYMRBFkn56D5LdfvaKLiBNnjFauHAhtbW1PPjggzgcjpi8UaNGUVhYyKOPPtro9Tt37mTAgAEMHTqUSZMmRff/SJJEWloaoijWc4yXnp6OxWKJSZ8/fz6TJ09mz549AHTo0IGCggIefvhh3n77bSKRCBMmTODuu++OzmwtW7aMW2+9lSeeeIJRo0ZF2zaZTPU2f18KCILAhAFtSU8w8/mOE5xQOenHKEIHi5frk/w4jK2o2HeAQNCLpigokpFwWlu6DL2VMQO6N+r3ofMtLTDbDJRsKMPnDKGqcFtAIq+LjZ1pEtW+EGpIJTGiUeDWuDtsILlvFrZrM35wXxIXDHsaDPszrH8bDq8G9zEQJXDkwDV3Q6eGl2YlyUzbtv/NsePvUVW1lFC4jDo/RslkpY1i9uxRPP/875k2bRovvfQSUPfeFRQU8Le//a3e3jcdHR0dnVhMOS3IfP5/qPnnuwS2bSNSdgJBMmDKyyNx1J3Yz3PT9bnQZMOosLCQQYMG1TOKoM4wevnll9mxYwddu3Zt8PqPPvqIyspKZs2axaxZs6LprVq14tChQ03usMvloqSkJCbtvffeY8KECQwcODDq4PH111+P5v/zn//E7/fz0ksvRR9gALfccgvLly9vcts/JEZJZGyvVtzRrQX7K7zIioKdAFZRJS4ujuTkZDRVZf/e/RyrcBKXlMw1HdpgMZ55o68gCFzdM5M23dOoKfWhKhrxyRZ+mmjGLSvs9wVRAhHyAuAwSBgybIimi7d5+AcjIRuG/C+4S8F1rO64fnpHMJz5lJ3BYCev1c9pkT0Gv/8QCAJxtqswGOp+wbz00ks8++yzrFq1ilAoxDXXXEObNm1+gAHp6OjoXBmYcnPJfO43hI8dP+n52oK5XTuERg5hXWwE7bL12vfD43a7cTgcuFyuC775etGiRQwbNkxf2z4NXZuG0XVpHF2bxtG1aRxdm4a5UnRpzvP7Mo7xoKOjo6Ojo6NzYdENIx0dHR0dHR2dk+iGkY6Ojo6Ojo7OSXTDSEdHR0dHR0fnJD/Olm+dS45gsBR/4DCCYCDe3h6DIf7H7lIMaiiEf+dOtFAIQ3oGptZ5F9V9gLuqAmdZGaIkktaqDWabjUOBEMeCYUyCQKd4K3HNCPWhKArLly/n2LFjpKenM2jQoAu+kVF2BpGrgwiigDExjOjaW+fUMrVdg36azgV3MMKeEx5kVSUvJY7sxOb7tqrxhdlb7kHToG26nbT4+k5ULyVCSohdlbtwnggQpyRgE8xYHAJxcXFkZGQgivrvSx2dK4lzMozWrVtHnz59KCgoiIl1doqZM2cCxDh53L59O3/84x9ZvXo1VVVV5OXl8eijj/LEE09Ey6xevZr//u//Zs+ePfj9flq1asXPf/5znnrqqTP2p6amhokTJ7JgwYLocf3XXnsN+0mnUMFgkEcffZQtW7awe/dubr31Vj755JNzGfoVRyhUwZEjhTidG5EVH4IgYjQmk5E+nOzs0Yjij3sKQdM07Nt3UPbZAuSKClAURIsFS6dOJN9/P+Y2rS9oe97aGjYvnM/x3cWEA34EUSSQlsXXPfpz2JGKX9WQBIEMk4FRGcn8V2YS4lkMtE8++YSnnnoqxi1FVlYWL730Evfdd99591nxhPGsPEbooAstKEOwFkkpx2LajN2+HsEaD20GQO9fgDXxnNoIyyofbDzMom/KqPGFUTUNu9nADW1SePjmNqTaz27c+MMyM9ccYsnuClzBMGiQYDVyy9VpPNCnNfGWS+vEi6ZpfHHoCxZvWIW9JBeL34xqcKJJYQxGCXu8lawWGfTs2ZNWrVr92N3V0dG5QJzTT53CwkImTpzIypUrKS0tjaZPnToVj+e7AKUej4epU6cCsGXLFtLT05k1axbFxcX85je/YfLkyUybNi1aPi4ujgkTJrBy5Up2797Nc889x3PPPcff//73M/Zn7NixFBcXU1RUxMKFC1m5cmWMd2tFUbBarTz++OMMGjToXIZ8RRKJONm773dUVn2FIBiwWnIxmzJRZB9Hj/2Tw4f/zo/tzcGzYAEpS5ciV1ZgSE3FmJODYLXi27yJst//vs476gUi6PWybObfObBlI6Ik4kjPQMlowYetr2FtQCZcW0Mri4lMk4GaiMxbRyqYebzqjHUuXLiQUaNG0blzZzZs2EAwGGT79u3079+f8ePH884775xXn9WAjPOzbwnsrkEQBCT1CFLkEKpixBfsjydyJ5oGFH8Mi39T5/G7mWiaxrRl+3h33WH8IZlsh4XcJBuSKLB4VxlTPivGHTxz5OqIovLyFyV8tOUYsqrSItFKTpINVdP4dFspLy7aTTCinLGOH5pP9n/CnJWfkrqtE3afHdlSgWIIoKIhh0QCToVjR0tZvHgxR44c+bG7q6Ojc4Fo9oyR1+tlzpw5bN68mbKyMmbOnMmzzz4LQFJSEoMHD456qn777bej3rAfeOCBmHratGnDunXrmDdvXjQ2Wvfu3enevXu0TF5eHvPmzWPVqlWNhvHYvXs3X3zxBZs2baJHjx4AvPHGGwwbNow///nPZGdnExcXx1//+lcA1qxZg9PpbO6wr0gqK4vwevdgteRGZ4YEQcRsTicScVJZtZj09KHExbX9UfqnOJ24P56HJooYsrIQhTo7XoqPR4yLI3zkMK5PPyXtl7+8IO3t37SOyiOHSEhLRzrpWGxrekuq4pNI87kR/G7kRAcmi5Uss4nKcISPymoZmuqghaW+o0hN03j66acZPHgwn376aXTJpWvXrsyaNQtRFJk8eTJjx47FZDqzo8nGCO2uIXLChyHJjBB2gb8KDEYkMYwqCwTcbbEmHsSYcAKOboJvl0H7+kFvz8SeMg9LdleQZDPhsH43q5NkMxFnMrDrhJslu8sZ2T2n0To2Haph7bdVZCSYsZm++9pJiTNjMxrYdKiWdQeq6Z9/aXgLrw3WMm/vPPKO3IhFjsNn3w8oCBgRBFCIoCgSBMwEjUE2bdpEbm7u5esdXkdHJ0qzDaO5c+fSvn178vPzGTduHE8++SSTJ09GEATGjx/PgAED6NmzJwAbN26kZcuWjdblcrnOGJJj69atrF27lt///vfRtJkzZ3L//fdHZzLWrVtHYmJi1CgCGDRoEKIosmHDBkaObDjcQ1MIhUKEQqHo61PReSORCJHImX8hN4dTdV3IOptCeUURYABBQtXUmDxRiiccPEJV1WpMph9nmcC7fgNyTQ1yvB1N1VDF7/VRANEej3f1ahLGjkWMqx8brrns27QeUZIQJAlV01AQ+CYxA7OiYJBEInIEv9uF0VS3bJQsiRwORVhZ5eKujMR69W3evJk9e/bw+uuvoygKihI7I/KrX/2KWbNmsWjRIoYPH96svp66VwK7qtEk0ETAV4WAiiae/FhLIdSwhaCnBVJKNWgaWskXqFcNblZbq/ZW4A/JpNmN9e4TgwSSAIt3lnFr54xG61ixpxxZUbEYxXp1mI0CmqaxdHcZfdokNatvDXEhPk/rj68nXAsJvjQiZicaYUDilNkjCAIRwhgjRmySmYqKCk6cOEFaWtp59/9i8mN911wO6No0zJWiS3P632zDqLCwkHHjxgFQUFCAy+VixYoV9OvXj1mzZjFt2rTol/zo0aOZMGFCtPz3Wbt2LXPmzGlwj1JOTg6VlZXIsswLL7zAQw89FM1zOBzk5+dHX5eVldWLSWUwGEhOTo7GRDtXXnrpJaZMmVIvffHixdhstvOquyGKiooueJ2No2G1HgBBwe2uaLCEIHgp3rWZbdvO/2F1LiRs2kySzwdWC5VVlfXyxWAIMRxm16efISfWD1XTHDRNo/TwITRVJaDU6REyGPEqGqIcIBwJo8oyHpeL4Pee6z7RwLpvyrBt8dSrc+PGjQCUlpayaNGievmqWldRUVHRuc00aFBTWoWggRzWSAg4MckqivqdMa8pCh63jE+pwBIJ4T+wk00N9OVMbD4i4vNBpeptMD8Yhn1BD4sWHW+0jm37RQJ+qFAaqSME3+zzsGjRwWb17Uycz+dpc2gzsltDDWuELAE0VQUENOreM00DDZVIRMbtCqEIYZYtWxbd13ip88N+11xe6No0zOWui9/vb3LZZhlGJSUlbNy4kfnz59ddbDAwZswYCgsL6devHxUVFRQVFfHxxx8D8OqrrzJ9+vR69ezcuZMRI0bw/PPPM2TIkHr5q1atwuv1sn79ep555hnatm3LPffcA8DIkSPPaxaoOUyePDkmQrrb7SY3N5chQ4Zc8JAgRUVFDB48+Ad1uV686wsCgcNYLPWXLzRNIxj00yK7J9nZzVt6uVB4LVaqNm/GqSikZWQiiLHGg1JdjZCURMcRt1+QGaPP9xfjLCslPrXuV7+CQLwo4DVYMYkQQSPBkUjCyXxV0/CHItyU25ph6Yn16svMzOTFF1+MnkI7ne3btwMwdOhQfvKTnzSrr6fumeScNNSaEFKiGaHag+AJIJ2c0dI0UMIG7AkScSnpUOsnPu8ahhU07/2sWHeYvRuOkpZibdCAC9cGuDrDzrBh1zRax+6ifVTsKic9peEfFIHqAN3apTBsWPtm9a0hLsTnyXzUzN41hxBNAmbBSkgUAQHh5LZMVdMQNBGj0UC8w4omKAwYMIDU1NTz7v/F5Mf6rrkc0LVpmCtFl1MrPk2hWYZRYWEhsixHo9ZD3QPUbDYzbdq0GCMCID4+vl7arl27GDhwII888gjPPfdcg+20bl130qhLly6Ul5fzwgsvRA2j08nMzKSiInbGQ5ZlampqyMw8vyPKZrMZs7n+aRuj0XhRbpCLVW9jZKQP5tDht0GTEcXYPS5huQaDIZ60tL4/2ochofcNOP+ViqH0OEKWEN1jBHUzIarHS+IdgzAnJl6Q9tpdfwMbPvkQTZaRjEZEoKuzjOUZrYkEVURJwpbgQDi5V6g6HCHRaKBfamKDGvXs2ZPOnTvzf//3fwwePBjD9wIiaprGyy+/THZ2Nj/5yU/OWWNrxxT8K0sRFBDiUsFXjqDKIBpQFQuiFMYSfxxRCYIoQn4BUjPbuvnqDD7ddgJ3UCHJFnufhGQFVYOhnbPPOIb+7TNYVlKFP6xiN8d+7fjDMpIkMKBD5gW9187n89S7RW8+SPkAZ3wZybU5hI1VaITQEBGoe/9MmhmDSSSihMjJySEzM/Oy2WP0Q3/XXE7o2jTM5a5Lc/re5FNpsizz7rvv8sorr7Bt27bo3/bt28nOzuaDDz6Ilh0/fnzMUf1TFBcX079/f+677z7+8Ic/NKldVVVj9vmcTu/evXE6nWzZsiWatnTpUlRVpVevXk0d3n8kaWlDiI/vRCB4jHC4BlWVUdUQwdAJZNlLRvqt2GwX9jh8c5ASEnCM/i/QIHK8FDUQQJNlFJeLyNGjmFq2xHHHiAvWXtvrbyCjzVW4qyrwu12oiky3ikOkuaqptsShJqUimMwEFZVjwTAhVePuzGQyzA1/4ARB4C9/+QurVq2ioKCApUuXUlNTw9q1axk5ciQffvghf/7zn8/ry8bcPgljCzuKM4SixqFZM9BkFSVoRlOMWONLMET2grsUWt0IrW9pdhtXZ9j5SZdM3MEIZa4gIVlBVlSqfSGOO4N0zUlkQPszb5q+rlUSN///9u48PooyT/z4p6r6TDrpnCQESLhPObxAFBWRG3XGZQZ1RZFRZ+QnuI7Oziwzrse4KzOOLjrC6q5G0WUE7wsYh8gpgkSRACaAgIRA7rOP9F31/P4ItDY5SDARxOf9evULuuqpp576ptL9zVNVzzMwjWpvkCpPgFDEIKwbVHuCVLiDXNo3lUv6pp5uGDqd0+rk54N/zrGcPfjNHmy+TDA0hAhj6Domw4ymKWANERcXx+jRo38wSZEkSW1rd4/RqlWrqK+v5/bbb8fpjL2fY+bMmeTm5kafQGvJl19+yYQJE5gyZQr33Xdf9P4fTdOiNywuXbqU7OxsBg9u6k7fvHkzTzzxBPfcc0+0nnfeeYeFCxeyb98+AIYMGcLUqVO58847ee655wiHw8yfP58bb7wxpmerqKiIUChEXV0dHo+HgoICAEaNGtXeEJxzTKYEBg54kKPHXqau7hOCoXJAxWpNJzPjOjIzf3qmm4hj6lRqCwtJLTlKpKwMoUdQbXbiL7+clDm3Yu7evdP2ZY2L56o5v2Tnhx9wZHcBntpaNEXhJqWQPRdfxVcJKZQGQ2iKQg+bmZ9npnBdelKbdU6aNInVq1fz61//mquvvjq6vE+fPrzxxhv87Gc/+05tVm0mkq7th/eTUoIHG9BNPcAajxYpJ872MXGWHShmJwybDRffCWZbh/ehKAq/uqIf6Q4b7+8qo9oTxBCCBJuJn4zK4rZLezfrBTqZSVO5f/Igujvt/KOwgkpPAACn3cI1I7sz+5IcLKaza6DEGX1mYDfZ+dC+EcveDOK8GRhaA2ghzFZBfIKJHtlZjB49mh49epzp5kqS1EnanRjl5uYyceLEZkkRNCVGjz/+OLt372bEiBEtbv/mm29SXV3N8uXLWb58eXR5Tk5OdOA7wzBYuHAhhw8fxmQy0a9fP/785z/zq1/9Klre5XKxf//+mLr/9re/MX/+fK6++uroAI9//etfY8pMnz6dI0eORN+fGBbgTI/Tc6ZZLCn06/treva8hYC/BEUxER8/EE3r+BdoV1AUhcahQ8m8916M4mIMfwBzRjfMXfRFFJfo5LJZsxk1eQauqgpUzURqr2zMFivlwRClgTAWVWFwvA1LO0c8njx5Ml9++SX5+fkcO3aMjIwMLr300k4bMVmLN+Oc3Bt9bIhIXQBFUzAnGSgNw4DbIKUvxLX+9Gd7mDSVWRf34pqR3TlQ6SViCHJS49o1sOMJNrPGL8b14WcX9eRQVdNN2H3THDjjzs7ueUVRuDr7aq7oeQUHxx+kvtJHgu7ErlqwJIDdbictLU32FEnSOUYRP/bMoAPcbjdOpxOXy9XpN1+vWbOG6dOn/6Cv4XYFGZuWybi0TsamdTI2rZOxadm5EpeOfH+fXX3XkiRJkiRJZ5BMjCRJkiRJko6TiZEkSZIkSdJxMjGSJEmSJEk6rsNTgkhnH93tJrh/P0I3sPTpjTmj9TmrOltjQz11pUdBUUjtmU1cYtNTi1UVNZQcLKcxJAg4kkhIjaNvmoNMZ9PTbkePHuXjjz9GCMFll12GktGdI54Aan2QoYqJxBQ7pjR7l7ZdCIHfX0wgUI6qWUlwDGv303i6Idhb7sblD+O0mxnSPRFNPcXTSfVHoL4YNAtkngfWBACqfdUcdh1GVVT6J/UnyZb03Q5MkiRJOm2nlRht27aNcePGMXXq1BbnOlu2bBlAs0EeS0pKmDdvXnROoTlz5rBo0aLoiMBbtmzhd7/7Hfv27cPn85GTk8OvfvUrfv3rX7fZnrq6OhYsWMAHH3wQfVz/6aefjs5bFAgEuOuuu9ixYwd79+7lmmuu4d133z2dQz+rGKEQ9StW4v3oIyJ1dSAEqsNB/JgxpPxiLqbkrpvjLOhrZMfq9yje9QVBXyMAtngH3c87n2MejZKyCnYHHRQbCQQxYzJZyEhN4MIsK7tfe4L33307OlcYikL6uAlkz/8DVkcSqWHBdLfCzxIdOMZ+t9HLW+PzHaHk6Au43bvRdT+KomG1dKN7938iI+O6Nh/Bzj9cx8tbi/m6xksoYmAxqfRNczDn0t6M7tPCY/HuMtj6VyjZDiEvKCrEd8M99Br+zxRia/mneMNNj687rU4m9JrAjYNvxGY6O4ZMkCRJ+jE5rUtpubm5LFiwgM2bN1NWVhZdvnjxYjyebybT9Hg8LF68GABd15kxYwahUIitW7fy8ssvs2zZMh588MFo+fj4eObPn8/mzZvZu3cvDzzwAA888AD/+7//22Z7br75ZgoLC8nLy2PVqlVs3ryZX/7yl9H1uq5jt9u55557Wpyz6odICEHN0v+mYeVKDJ8Pc/fumHv0QFFVPHl5VD62CN3b2CX7joRCbFr+Ivs+2YgQBonp6SSmpRPSdbZ9UcDXh/fyWTCZ/UYqumLCQQhbxENteTWLf3MbH67N47+e/itfVVRy45YC+tz3IK7dX3Dwd3eR6gvgtqq8kq7wcoMb96pizMHOHScmEChj/1ePUF+3DU21Ybf1wmrpRihUS/GR5ygtW9nqtp8V1/HYmr3sq3CTZDeTnRJHkt3Mvgo3j63Zy2fFdbEbNNbAmt/AV3mgmSG5NyRm4Q808Jfdz/LhvtcAyHJk0T2+O2E9zFsH3uKZnc8QMSKdetySJEnSqXU4MfJ6vbz22mvMmzePGTNmRHuHAJKTk5k0aRJbtmxhy5YtTJo0ieTjvRZr166lqKiI5cuXM2rUKKZNm8ajjz7K0qVLCYVCQNOgizfddBPDhg2jd+/ezJ49mylTpvDxxx+32p69e/fy4Ycf8sILLzBmzBjGjRvHM888w8qVK6NJW3x8PM8++yx33nnnd54/7WwRKCzCu3kTWnIypvR0FJMJRdPQkpIwZWURKPwS76aNXbLvksJdlO0vwpGSRlyiE1XVUDUNvy2BsMlCXVjlqBGPXdVxqAYmTUNVFeqK1uM5uo/zfvEn+l5+PZvDCkcUE6Ou+ClXPvIs7pKDlG1cQ4auEC/g7900jnoCJNdaTt2oDqio/AC//wh2ezYmUyKKoqKqFmy27qiKlfLytwiGapptZxiCV7YW4wlEyEmJI85iQlUU4iwmclLi8AQivLKtGMP41tBgRe9B9X5IzgF7clNvkWZhmyOB3SbIDDSSrFnRFA2TaiLVnkqaPY1t5dvYU7OnU49bkiRJOrUOX0p7/fXXGTx4MIMGDWL27Nnce++9LFy4EEVRuO2225gwYQKjR48GID8/n+zsbKDp8tvw4cPJ+Nb9L1OmTGHevHkUFhZGR6L+tp07d7J161b+4z/+I7ps2bJlzJ07Nzpi9bZt20hKSuKiiy6Klpk4cSKqqrJ9+3auv/76jh5iVDAYjJmn7cTsvOFwmHA4fNr1nuxEXR2p0/3JJxg+P2p6OoYwYleaTQhFxb1+A3GTJ3daO0/4+ovPMQyBZrFgHP85CAGusEARUEYSYSFwfCs/UFCp+nIzKX1GkpQ9mLWF5VQMScQWMjDpBkn9B5F50TiK171P32kzSTLgqAk+S9K4otRCKND6fHkdYRhBamo2oGnxCBTESbEzmZMJBI5RU72Fbt1mxKzbV+HhYJWHNIcZgWg2anqaw8TBSi+FpfUMzkwAIdD2rQbNBooGxjf7+lj3gKJhMcKIxhpEYs/oOrtmpzpSzcdHP+a85PNaPI7TOWd+LGRsWidj0zoZm5adK3HpSPs7nBjl5uYye/ZsAKZOnYrL5WLTpk2MHz+e5cuXs2TJEmbMaPpCmTVrFvPnz2f27NlUVFTEJEVA9P2JedNO6NmzJ9XV1UQiER5++GHuuOOO6Dqn08mgQYOi7ysqKujWLXYCS5PJREpKSrN6O2rRokU88sgjzZavXbuWuLi471R3S/Ly8tpdNu2LHcT7fYSrq1tcrwUDGF/t54s1azqreVHl+4oI+/wEK6uiywQQtieDAX7MKEIcTx6+2S7kbSA5ZwT+Rg/7jnhpTA9jDilEdAUjCPFZvXEVf0Qo2NSDqCsqlXoI1VDYsHY9uqkTBmlXvNjtFQhhAqpaLqJ4Kdi1lUg49hLeQTfUNWgQEHhbuLpnCKgLKKzd+DFfJ4JqhLms4ggIQSgQu68yRyOqZqDrOn5XA42B2F4xv+Fn11e7WHOs7Z9fR86ZHxsZm9bJ2LROxqZlP/S4+Hy+dpftUGK0f/9+8vPzeeedd5o2Npm44YYbyM3NZfz48VRVVZGXl8dbb70FwFNPPcXzzz/fkV0A8PHHH+P1evn000/5t3/7N/r3789NN90EwPXXX/+deoE6YuHChdx3333R9263m169ejF58uROnxIkLy+PSZMmtXvI9fqqKtzFR5ouo7Vwo3A4FMY6eAgjp0/vtHaesKm2jJLdBTgzvklIhQCPTyeEwG6EEYqKguBE0wQCiyMZX81RbPEJDMtKpCwtgWp3AFMoDGYV79FDxKVlYLFaMABNg0xNwVADXDX5aiy2735JzTBC7PlyFbreiMWS3my9EDqBQIDeOeNIT58Ws+6rSg8f1X5Jgk0jvoVJUxuDEQjoTL3qPAZmHO8xen0FuMshMTZ576EbVNCIJjQczmTiT1of8AQ4v/f5TB/e8s/vdM6ZHwsZm9bJ2LROxqZl50pcTlzxaY8OJUa5ublEIpGYWeuFEFitVpYsWRKTRAAkJCREl2VmZpKfnx+zvrKyMrru2/r06QPA8OHDqays5OGHH44mRifLzMykqir2r/FIJEJdXd13vp/IarVitTafJNNsNnfJCdKRehMvvxzvmr+Dx4t60sS+RjCIIgTOqyd0STv7XTCaY4V70INBzLbjT04pkGRWqTR0etDA10oPgoqKTWm6fCSEQcaIK9n//hIaDu9h8uSfUZVi5n/9VUQ0Hff+Qiq+2MpFCx5CQaFeEyQYMKbeoCE5xACbpZOOxUx62tWUlq0AUlGV2F+BYKga4n/8rgAATN5JREFUiyWZtLRxzfY3tEcyAzMT2FPqwmE1xySkQghqGsOM6OFkaI/kb9YNuRa2LgERaXpM/7grSGBH2ENQNWGLT0X51oSy3pAXq8nKFb2uOOUxd9W5eC6QsWmdjE3rZGxa9kOPS0fa3u6bryORCK+88gpPPvkkBQUF0deuXbvIyspixYoV0bK33XZbs0f1x44dy549e2KSmLy8PBITExk6dGir+zUMI+Y+n5ONHTuWhoYGduzYEV22fv16DMNgzJgx7T28HxzroEEkTLwa3eUiXFmJEQohwmEitbWEy8uxjxyJ44orumTf2eeNoNew4Xgb6mhsqEePRNAjYWw+F+ZIiGSzQW/VS8BQ8OgqYd1ANwTJQyfg7DOcPS8upGD1/3FBwEOO38WOta+y6aF5JPcfRub4qZRrgoCAayp1eiTZqU8LdWr7MzOvIz6uL35/CeFwA4aIoOsB/IFSDBGhR9YNWCzNH7tXFIXbLu1Nkt1Cca0PbzBCRDfwBiMU1/pItluYc2nv2B68Idc1jVlUXwK+WtDDEA4w1tPARRGosMVTG/ETNsKE9BDVvmrqAnVc0eMKzktr+f4iSZIkqeu0u8do1apV1NfXc/vtt+M8qYdi5syZ5Obmctddd7W6/eTJkxk6dCi33HILjz/+OBUVFTzwwAPcfffd0V6ZpUuXkp2dzeDBgwHYvHkzTzzxBPfcc0+0nnfeeYeFCxeyb98+AIYMGcLUqVO58847ee655wiHw8yfP58bb7wxpmerqKiIUChEXV0dHo+HgoICAEaNGtXeEJxVFEUh7Ze/xJSWjvvDD9FrqhGGQEtw4LzuOlJm34zaBfdBAWgmM1f881wK1q7m0I58vHW1oCjYHQlcMeoijrlULCVHsQVDfK0n4sOC2Wyhe7qTf/rrK+x+82keeejf+cPC3zXVZzbT7aqp9PrVv9JgtZARMLjGrfCTbsnYx2QQ2XKoU9tvtXZj0KBHKDm6DFfDZwSD5YCGzdaDrO4/Iz299RvWz89O5sFrh/LKtmL2V3ioa2wax2hUdhJzxvZmZK+k2A3iUmDaX+DT/4bDm8FdCoqKNTGL+4b9lJVakE2lm6n0VaKgkGJL4af9f8rPBv4MVZED00uSJH3f2p0Y5ebmMnHixGZJETQlRo8//ji7d+9mxIgRLW6vaRqrVq1i3rx5jB07lvj4eObMmcMf//jHaBnDMFi4cCGHDx/GZDLRr18//vznP/OrX/0qWsblcrF///6Yuv/2t78xf/58rr766ugAj3/9619jykyfPp0jR45E3594Cu7kJ4t+SBSzmeQbZuG89hqChw6BrmPOyenSgR1PMNtsXHzdTIZPmEJ9eSkAKT16Yo2LB6ChzsXRrysIhAVBh5M4p43eqfGkxFvgmpf4r788zrZt2xBCcMkllyCSUjjaGECpDzJQMxOXbMPktHbZkxA2WxYDB/yeQKCMQLAcTbURHz8AVT31fUyjeiUxsudIDlV7oyNf90t3tD4opCMdJj4EngpoKGkazyh9CPFmG7cDPxv0c4rdxaio9E3qS7w5vnMPVpIkSWq3didGH3zwQavrRo8e3a4EIycnhzVtPCW1YMECFixY0GYdLV2mS0lJ4dVXX21zu+Li4lO274dKjYvDPnz4Gdm3zeGg+4BBzZYnpThJSmmeRJ+Qnp7OddddF7Ms02qGlIROb2NbbLYsbLasUxc8iaIo9O/WwbYmZDa9TuK0OhmZPrLDbZAkSZI6n+yrlyRJkiRJOk4mRpIkSZIkScfJxEiSJEmSJOk4mRhJkiRJkiQd1+EpQaSuozc0EC4uRhgCS5/emL811UljWQX1B75CVQQpgwdg6xZ7w3A4HKaiooJwOExiYiKpqakoioIQgk1H9rG+ogKTycJ1fYYyLNHBunXrqKysJCsriwkTJqBpGkLoeL37CIcbMJuTcDgGoyhadB8iYlBzuIF9FW6wm+jfP5XuSfZ2HZswDKpLivF73NjiHaTn9EHVtFNvKEmSJEnfo9NKjLZt28a4ceOYOnUqq1evbrZ+2bJlAM2eHispKWHevHls2LABh8PBnDlzWLRoESZTUzPefvttnn32WQoKCggGgwwbNoyHH36YKVOmtNmeuro6FixYwAcffBB9XP/pp5/G4XAATU+knRhN++TjuOSSS04jAp3L8PtJ3rSJ8pWvYbjdgEB1JOC47FLifjqTPe9t5lhxhFDYBArYzIfp008wfPZP0RxJFBYWUlBQgNvtxjAMzGYz3bt3J6FfD35/4FNKLZnoWjwQ4unXH8P74kuEamuj+8/OzuaPf5zHBRcew9d4GEOEUBUrcfF96NVzDk7nhbj31PDKRwdYX++l/vhkqA6riXHDuvHLqYObHsNvRfmB/Xzx9/eoPXaUSDiMZjKRlNmdUZNnkDN8VNcGV5IkSZI64LQupeXm5rJgwQI2b95MWVlZdPnixYvxeDzR9x6Ph8WLFwOg6zozZswgFAqxdetWXn75ZZYtW8aDDz4YLb9582YmTZrEmjVr2LFjB1dddRXXXnstO3fubLM9N998M4WFheTl5bFq1So2b97ML3/5y2blPvroI8rLy6OvCy+88HQOv1OJSITaJUtI/OxzRDiEuXt3zFk9AKhdk8e6P77Jwa9UEAYJcX4S7AF0w0TRXjv5z75OweefsXnzZjweDw6Hg+TkZMxmM18dOsif8ndyzNYPodqxRHwE81ZT95cnUIedx6Bn/4djHi+fffYZ553Xm7lzF7J61RbM5iTstmzMZide734OHFxExRcfsfj9Qt6sdRNQmh6rzzKbIKizZmc5D7+xG28w0uLxVRz8io2vvEDl4a+xxseTlJGBPSGRurJjfLziZY7sLvgeoy1JkiRJbetwYuT1ennttdeYN28eM2bMiPYOASQnJzNp0iS2bNnCli1bmDRpEsnHBxtcu3YtRUVFLF++nFGjRjFt2jQeffRRli5dSijUNOXDU089xW9/+1suvvhiBgwYwGOPPcaAAQPaHENp7969fPjhh7zwwguMGTOGcePG8cwzz7By5cqYpA0gNTWVzMzM6OtsmPfFv2sX/m2foic40FJTUUwmFE3DlJxMffog6iLpxAk3dpuBqiqoKsTZwsRZQxwut7F9y8domobT6cRkMqEoCjabjWKzzrHU3tgjChbdjxIJ0/DS34i//FLS/3Ue3j59eelIGRdeeAGPLRrO2LFp/Pd/H0ZR7CiKiqbFYbdlEwm72bxvNZ8EgiSbTaSZTZgVBU1TSbKZyUBhz5F6NuxrPlO9EIKCvDX4vW6SMjKx2JrqNlutONMzCAcD7PzHKgxdPwORlyRJkqTmOnwp7fXXX2fw4MEMGjSI2bNnc++997Jw4cKmeaRuu40JEyYwevRoAPLz88nOzgaaLlsNHz6cjIyMaF1Tpkxh3rx5FBYWRkei/jbDMPB4PKSkfDNv1bJly5g7d250QMlt27aRlJTERRddFC0zceJEVFVl+/btXH/99dHl1113HYFAgIEDB/Lb3/622QCDJwsGgzHztJ2YnTccDnfaiMzujz/GCIcw7HaEITBUI7quSssCIRD+MCIh9n4csymCx9DxuH1kpKZjGN9sZwiDr+1xhDQzjmAQtxV8u/ag19Xh/PlPMSkaISPAOxUV3JUVwO8/zG1zR/DLO9dTsKuCUaO++RlpESc73RYCaphuqoYgdiBPi0lFCUfI21XG1KGxs9U3VJRRVfw19kQnguajjMc5k2moLKf0wD4y+w1sMT4n4txVI2D/UMm4tE7GpnUyNq2TsWnZuRKXjrS/w4lRbm4us2fPBmDq1Km4XC42bdrE+PHjWb58OUuWLGHGjBkAzJo1i/nz5zN79mwqKipikiIg+r6ioqLFfT3xxBN4vV5mzZoVXeZ0Ohk06JuRlisqKuj2rZuUAUwmEykpKdF6HQ4HTz75JJdddhmqqvLWW2/x05/+lHfffbfN5GjRokU88sgjzZavXbuWuE6ah6zbzgLs/gDY7VTXVMes8yeMQCWEHtYJhppPpGsoAl03qKmpiVkeFjqhFCcCgSJA6IJIXT0Aph49MQwBShhXMMjGTz4i0VpHUlLT/VhfH6ogK+ubqS1MIXCFrQgjQqiFE0sRoOmCAyUVrFlTGrMuUFNFQ309Jns8itvbbFshBBGvm483bCB+/8E245SXl9fm+h8rGZfWydi0TsamdTI2Lfuhx8Xn87W7bIcSo/3795Ofn88777zTtLHJxA033EBubi7jx4+nqqqKvLw83nrrLaDp0tjzzz/fkV1EvfrqqzzyyCO89957MYnP9ddfH9ML1B5paWncd9990fcXX3wxZWVl/OUvf2kzMVq4cGHMdm63m169ejF58mQSExM71IbW1BYfwVNRQQOQnpaOon6TlJQHAwREEppZw2qxxmwnBGhhHc2kkpaWhqp+c1XUEAbWkBsFBaGAoimY05p63SIlJVgH9EOoFpLMViZcMJGvvlrH1183AtB/QPeYeIc9bpIsQVBMWMzmZvOBCV0QIcKw3t2YPj12WouGynL+/tWXmKxWrC0kkuFgkIBJ5YoJV5PRt3+L8QmHw+Tl5TFp0qSz4tLn2ULGpXUyNq2TsWmdjE3LzpW4nLji0x4dSoxyc3OJRCIxs9YLIbBarSxZsiQmiQBISEiILsvMzCQ/Pz9mfWVlZXTdt61cuZI77riDN954g4kTJ7bZpszMTKqqYu9viUQi1NXVNav328aMGXPKDNhqtWK1WpstN5vNnXaCJF5+OY3r1qEGAiiqEjOjeje9nDotE2yWZglJKGwiwdAgMR6fzxeTqKmo9PP7KY6E8VrMQAD7iOFo6Wk0vPYWqb//NZiS+FlWFslJfbDb+/Hii8vp3dvJyBEZ0X0JIYho9VyY2JMdx8x4DUjUvmmHAIIRHcwak0f2aBaTtB69yOzXn2NFX2KLi4s5BiEEflc9qT2zyeo/8JSP7ndmzM8lMi6tk7FpnYxN62RsWvZDj0tH2t7um68jkQivvPIKTz75JAUFBdHXrl27yMrKYsWKFdGyLU30OnbsWPbs2ROTxOTl5ZGYmMjQoUOjy1asWMHcuXNZsWJF9JJcW8aOHUtDQwM7duyILlu/fj2GYTBmzJhWtysoKKB79+7tOfQuZR85gvjLL0fzNhKprkaEQohwmEhNDck1+0gzV+NXHPj8GroOug6NfjP+kIm+PQOMHT8eIQQNDQ2Ew2EMw8Dv95MT0ehV9zUBk0FQi8cwmUm+fQ6+7Z9T9Z9Pk7i3kJ8lJ7Bp02Z+fW8+X+yoZ8GCPuh6I4aIEIl48fuPYLEkc/mQn3Kl3UZDOEJVOEJQCMK6QV0gTJUiuKBvCuMHpTc7NkVRGDV5BnHOJBoqygn6fBi6Tsjvx1VZgcUexwVTr5PjGUmSJElnjXb3GK1atYr6+npuv/12nM7YWdNnzpxJbm4ud911V6vbT548maFDh3LLLbfw+OOPU1FRwQMPPMDdd98d7ZV59dVXmTNnDk8//TRjxoyJ3iNkt9uj+3znnXdYuHAh+/btA2DIkCFMnTqVO++8k+eee45wOMz8+fO58cYboz1bL7/8MhaLJXqD99tvv82LL77ICy+80N7D7zKKppHy/+axr6YaZ1k54epqEALN6SR1ymRyrvsphe+tp/gr8AasKIDdEmDIeSaG3vTPqHYHFlscO3fupKGhITqO0bDBQxnXtwe/27uFw6YUIloC1vETSTPZ8L34Evt+fS8Dfn0vAIMGDWLla88wZMhhvN79iEg9imIh0TmKXj1vITFxBPfYa0n7xwHyaj3UBCOgQILdxMyR3Zk7aQBxlpZPpW69+zJh7q/44u/vU33kMAGvB9VkoluffoycPJ2eg4d9f8GWJEmSpFMR7XTNNdeI6dOnt7hu+/btAhC7du1qs47i4mIxbdo0YbfbRVpamrj//vtFOByOrr/yyisFTVdoYl5z5syJlnnppZfEyc2ura0VN910k3A4HCIxMVHMnTtXeDye6Pply5aJIUOGiLi4OJGYmChGjx4t3njjjfYeepTL5RKAcLlcHd62LaFQSLz77rsiUF8vfLt2CV9BgYjU18eU8VXXiPJt20TF9k9FsLaqWR2RSESUlZWJI0eOiPqTtt1R+rV4fMfHYnHBZ+KAyy10XRdbtmwRb775pti2bZswDEMIIYRhGMLrPSDqGz4XXu/B6PITjIgh6o+4RH7+MZG/u1zUeALtPkbDMERt6VFxbF+RqC4pblb3qWITCoXava8fAxmX1snYtE7GpnUyNi07V+LSke/vdvcYtTWW0OjRo5s9it2SnJwc1qxZ0+r6jRs3nrKOli7TpaSk8Oqrr7a6zZw5c5gzZ84p6z7T1Ph4rCNGtLjOnpaKPS211W01TWv10uAFWX24ICt25O/LLrusWTlFUYiPb/kmaGi6iTspO5GLszt+47miKKRk9ezwdpIkSZL0fZKTyEqSJEmSJB0nEyNJkiRJkqTjZGIkSZIkSZJ0nEyMJEmSJEmSjuvwlCDS2UkIQWPjV4RCNZhMCTgcQ1DV4wNahRqh4kuIBMDZk4iSTPDgQRBg7d8PU2rrN3WfSsQQFDX6cYV1At4QtpCB3aTRN8XC1s0bqa2tpXfv3lx++eXR0bn1SJiq4q8J+f3EO5NI7ZWDoihNA0pW+9HdQRSLhiXLcVpxKK71Ud7gx2pWGdrdCWqI/XX7CUQCJPhTSQylYrJopPVyYLZ8f2Mo6bpOZWUlgUCAuLg4unXrFjNiuSRJknTmnVZitG3bNsaNG8fUqVNZvXp1s/XLli0DaPb0WElJCfPmzWPDhg04HA7mzJnDokWLMJmamvH222/z7LPPUlBQQDAYZNiwYTz88MNMmTKlzfbU1dWxYMECPvjgA1RVZebMmTz99NM4HE1frBs3bmTx4sXk5+fjdrsZMGAA//qv/8rNN998Ood/1nG793D06Et4G7/CMEIoigm7PZue3W8ktbQcdr8GngqMYIS6QvCWWtBxgGZGS0jEceUVJN9yK5ojvkP7/aTew0ulNeyv9lJ3oIFwXQCzAcHPV3Ms72WC3oZo2QEDBrBkyRL6pTrZve4fuKuq0PUIZouFtOzeXHDpDMyHFMJlXkTYAFVBS7JiOz8NTv3AIwAltT7+d/Mhdh1rwBfSUVWwOHdhdn6BPQS9vh5JijuLOOEgyZ5EUko8g8ZkMnB0ZsxULF3h66+/5rPPPqOurg5d19E0jfT0dC655BJ69pRP60mSJJ0tTuvP1dzcXBYsWMDmzZspKyuLLl+8eDEejyf63uPxsHjxYqDpr+UZM2YQCoXYunUrL7/8MsuWLePBBx+Mlt+8eTOTJk1izZo17Nixg6uuuoprr72WnTt3ttmem2++mcLCQvLy8li1ahWbN2/ml7/8ZXT91q1bGTFiBG+99Ra7d+9m7ty53Hrrraxatep0Dv+s4vHs5asD/4HbvRuTlojd1guLORW/r5hDhX+gpuBx8NUg4jKp+sJKQ1EQ4WvArNVj7paKMAxc771P1RNPIEKhdu/3k3oP/3GonKJaL+49tejVfswmlerP3uXQO0+TPOwyxv7uZZ7fsJfNmzeTnZ3NNTNm8OITj+OqrCDO6SQpIwOLPQ7XwTKqXy/Ed7AWxaKhpdjQEizoriCNG0pJrrWcsj3lLj8Pvf8lnxyqxWbSyE6Jw5SYT5lYTXVVIwO/nEBmfT+EJqg1l1MuSnC7fHzxjxK+/Lj0lPV/F4cOHeKjjz6iurqauLg4kpOTsdvtlJeX849//IPS0q7dvyRJktR+HU6MvF4vr732GvPmzWPGjBnR3iGA5ORkJk2axJYtW9iyZQuTJk0iOTkZaJqRvqioiOXLlzNq1CimTZvGo48+ytKlSwkd/0J+6qmn+O1vf8vFF1/MgAEDeOyxxxgwYECbYyjt3buXDz/8kBdeeIExY8Ywbtw4nnnmGVauXBlN2n7/+9/z6KOPcumll9KvXz/+5V/+halTp/L222939PDPKkIISkv/RihUi93eG5MpHkVR0TQbdnM6hr+WY6khjMTu+EpDNB5pxJxoxeSMR4n4UHzVmFJSMGVk4Pv8cxrzP2vXfiOG4KXSGry6jrUiQMgTxh5vwWSEqP37MpLG/YRes39LWs++rCqspd/wi3j/3Xfo0z2T1zZ9grNbBiaLBUVRsdjt9EkcgVm34A03oNpMKIqCYlIxJdkQCqRXWjECkTbb9N7OMoprG8lJiSPRbiaiuGjQtmLRrAyovQCrN4FAnBfFamAz2/GJRjyWekwWlf2fVtDoCnbGj6QZXdfJz88nHA6TnJyM+fhEvBaLhZSUFHw+H5999lm7xgGTJEmSul6HL6W9/vrrDB48mEGDBjF79mzuvfdeFi5ciKIo3HbbbUyYMIHRo0cDkJ+fT3Z2NtB0+W348OFkZGRE65oyZQrz5s2jsLAwOl3HtxmGgcfjISUlJbps2bJlzJ07N/pFsm3bNpKSkrjooouiZSZOnIiqqmzfvp3rr7++xeNwuVwMGTKkzWMNBoMEg998YZ6YnTccDhMOh9vctiNO1NXROgOBMlzuPZjNyQhE7JdrYw2WsEHAqtFg8hI66EEYAsWiNl2ZUjXwViGcvcBmReg67k0bsY4Zfcr9fun1c6gxQJqq8nWZF9WkgAoNe7ZghPxkXP3PeCM6lngTda4gW76q4iJzDZNGDmXpqrUcq6ohK73pvibNMJEYSUFXdUKNPsKhINq3JvtT4k2YXAr+Q/Wow1o+XYNhnfX7Kom3aCiKwBACN/uIKI3YjG70cmUTUsMoho5VVVEATdGo89fSPaU73roQRwprGHBxtw7Fvz1KS0upq6sjLi4OIUSzBCguLo6KigqqqqpizvNTOd1z5sdAxqZ1Mjatk7Fp2bkSl460v8OJUW5uLrNnzwZg6tSpuFwuNm3axPjx41m+fDlLliyJTv46a9Ys5s+fz+zZs6moqIhJioDo+xNzop3siSeewOv1MmvWrOgyp9PJoEGDou8rKiro1i32C81kMpGSktJqva+//jqfffYZ//M//9PmsS5atIhHHnmk2fK1a9cSFxfX5ranIy8vr0PlVbUUq60WIRKAQMy6uGA9cWGDsClCjbsWrTaEIXRCxxM9RRhAgPrKCoSqYQr4qd3zJZ+1MTL5Cfs0G3W2ZJRQmIA/iAKEggaB+ipUqx01PolwJEJNnQ9/QLDti12Ew4dw2pouiR0uOYrJ0AGwE49u1gmLEBE9RHVVFepJsyBbUdnz+S7qjrR8qc8bhopqDZMqqPI3LfPYK4jE6RhBBU3XiKhhiETAaFpvCJ0wEapqKhE+Mzs/38WB6s7/xXe73bjdbgKBAIrS/D4mIQThcJh169YRH9+xe7yg4+fMj4mMTetkbFonY9OyH3pcfD5fu8t2KDHav38/+fn5vPPOO00bm0zccMMN5ObmMn78eKqqqsjLy+Ott94Cmi6NPf/88x3ZRdSrr77KI488wnvvvReT+Fx//fWt9gK1x4YNG5g7dy7PP/88w4a1PYHpwoULue+++6Lv3W43vXr1YvLkySQmdnxajNaEw2Hy8vKYNGkS5pOSgrYEguUUFf0DVTVjMsVO7ItHx6ivw6yZSEtMJZTuxVvnxnJ8wl4iAVDNpGdkgqIQDgSJHzmCC6ZPP+V+c7x+/nGgFKeiUmcPEQ7qWKwm7CkZGAEfhqcGc0p30pzx1LmCXHZhXy6w9GTLh01JV9+cbLqlNfWOaEJD86qougVFE6R36xbTY2SEDTzldQy/eBTxQ9NabE8wYvBB7Q48wQjdEpqOz0QmfkVDVQW6KYI5bAGTgdXUdPU4aISwKCa6pWTgrQtxwehs+l/Y+T1GZWVlrF69Grvd3uLPNhAIEIlEmDhxYvSyc3uc7jnzYyBj0zoZm9bJ2LTsXInLiSs+7dGhxCg3N5dIJBKdtR6a/uK1Wq0sWbIkJokASEhIiC7LzMwkPz8/Zn1lZWV03betXLmSO+64gzfeeIOJEye22abMzEyqqqpilkUiEerq6prVu2nTJq699loWL17MrbfeesrjtVqtWE8kEt9iNpu75ATpaL1mczZJzguorfsYs8mJonxzy5iwpxL2fo0tCEkRB/5+Ko0HPIiQjmpWQejg6Imiahg+H4qmkTh+fLv2PyLJxIB4O4VePyk9HJQfqEcYkDTico7a46lY+zcG3vxbggEDp93CFYMyiFdSyNtVxIAemWSlpUR7T4Ri4DbVkRROw55gwWyJjbfuCxI2C+z9klttm9kMVw/J4NX8EgwDTJqKk6FUsZ6Q6qIksYRB1UNAjYDSdM4ahk6qI4NQo4493kzO0PQu+Zn27NmT1NRUqqurSU5Ojuk1EkLg9/vJyckhPT29xR6lU+mqc/FcIGPTOhmb1snYtOyHHpeOtL3dN19HIhFeeeUVnnzySQoKCqKvXbt2kZWVxYoVK6JlW5rodezYsezZsycmicnLyyMxMZGhQ4dGl61YsYK5c+eyYsWK6CW5towdO5aGhgZ27NgRXbZ+/XoMw2DMmDHRZRs3bmTGjBn8+c9/jnli7YeuR4+bsFq74fMfIRLxYIgIEb0Rf6QS1Z5OrzobakMpcVkq8X3iibhDRFyNCC0OYU8jUlNDpLqa+LGXEPet+7TaoioKd/RMx2nS8GfasSRaCHhDhAwTadPvxLV9DcUv/pHqw4VMG+BgxycbmDx1Kkera7hpwhW4qioJBwIYuk6wsZFD7gLCpiAOcxKGP4LQBUZIJ1LXdPmpOjOAam17vKGfjOpBv3QHJXU+GnwhFN1Bkn45IT3MgbTPCSS4sPniIaASCAeIUx04gknoEcGQy7KISzz1k2+nQ9M0xowZg9Vqpb6+nmAwiGEYBINB6urqiI+P5+KLLz6tpEiSJEnqfO3uMVq1ahX19fXcfvvtOJ2xl21mzpxJbm4ud911V6vbT548maFDh3LLLbfw+OOPU1FRwQMPPMDdd98d7ZV59dVXmTNnDk8//TRjxoyJ3iNkt9uj+3znnXdYuHAh+/btA2DIkCFMnTqVO++8k+eee45wOMz8+fO58cYboz1bGzZs4JprruFf/uVfmDlzZrTeE08G/ZA5HAMZNPAhjh59GY+3kHCkAUUx4XAMpufAm0hOaxrHSHEdpduFEerj7HiPWgkLB9TUY0pOInHGdJJvvBGlAxn1xc54/ti/By+W1lA4UqH2QD2hmgDpF84g2Wzl6D9eYvvi9WxvGq2BkSNHsm7dOnolOti9/kPqy0oxdB2TxULG0AFkjB2F6ZBBqMSD4Y+gqAqmdDu2C9JoOHjslO3plmjjjz85j5c+OUz+4TrKXAFU9UJ6J9kxp+zgQMoGen49nNSGXqTp3UmyJJGU5mDwJd3pd0H66Ya/XXr37s3kyZP5/PPPqa6uxufzYTKZ6NWrF2PGjKF79+5dun9JkiSpA0Q7XXPNNWL69Oktrtu+fbsAxK5du9qso7i4WEybNk3Y7XaRlpYm7r//fhEOh6Prr7zySkHTcH4xrzlz5kTLvPTSS+LkZtfW1oqbbrpJOBwOkZiYKObOnSs8Hk90/Zw5c1qs98orr2zv4QshhHC5XAIQLperQ9udSigUEu+++64IhUKnXYdhGKKx8WtR3/C58Hj2CcPQv1kZDgpRulOIku1CuEpFxO0WvoIC4SsoEJHveCyGYYj9Xr/Ib/CKbeX14vPDtWLPsQbR6A+KDRs2iDfffFN8/vnnwjCM6Da6HhFVRw6LY/uKRH15Wcy6cK1fBIpdIljqEUbEOK3YlNb7xOfFTe0IhnURioREUU2R2Fm5Uxw6ViLKDjaIqiNuEQnrp66sExmGISorK8WRI0dEdXV1zHF3VGecM+cqGZvWydi0TsamZedKXDry/d3uHqO2xhIaPXp0u8ZhycnJYU0bTz1t3LjxlHW0dJkuJSWFV199tdVtli1bFjPe0rlIURTi4voQR5/mK00WyBoVfasB9pEjO22/A+NtTW9Ouv97/PjxLW6jqhrp2b1bXGdKsWFKsX2zwOh4m7KS7GQl2b+9R4aktj00w/dBUZRmT1BKkiRJZxc5UZMkSZIkSdJxMjGSJEmSJEk6TiZGkiRJkiRJx8nESJIkSZIk6bgOTwkiSW3RPR6C+/cjIjqWnGzM5+ij6OFwmIqKCsLhMImJiaSmprZrLKIDlR42H6gG4PL+6QzMTIhZL4Rgx44dFBUVEWezM/68S3FY4tAcFkwZcc32UeWrotRXiqqoDEgegNN60h3wLWiorMBdXYlmMtOtd1/Mtm9udtf1IGVHduLzNGC1ptOz7yhMljbGkGqsheq9IASkDwLH6d9cHjEEX3r9eCI6qRYTQ+JtcnwnSZK+d6eVGG3bto1x48YxdepUVq9e3Wz9iSfATn56rKSkhHnz5rFhwwYcDgdz5sxh0aJFmExNzXj77bd59tlnKSgoIBgMMmzYMB5++GGmTJnSZnvq6upYsGABH3zwAaqqMnPmTJ5++mkcDgfQNO3CXXfdxY4dO9i7dy/XXHMN77777ukcutQKEQpR/+ZbeP7+dyL1dWAI1Ph44kaPJnXubZjSWp7O44dGCEFhYSEFBQW43W4Mw8BsNtO9e3cuvfRS0lo5zip3gPtfL+CLkgZCetOjdv+lfcXInk6emDWKrCQ7u3bt4vbbb48ZrDTeGscd427kt9fchS0rEcflPbF0j6ch2ECeP4+VH6+kMdKIgkKyLZmrs69m1qBZWLXmI7a7a6r4/IN3KPtqH+GAH0VViU9KZsjlVzHk8vGUHFrL1weWEzHKAB0hzOwr7EN2r7kMufiy2CQl1Ajb/we++hD8DYAAWxL0nwiXzANbx6bM2VjnZllpDUf8IcJCYFMVBsXbuKNnN85P7Px5CSVJklpzWpfScnNzWbBgAZs3b6asrCy6fPHixXg8nuh7j8fD4sVNI/zpus6MGTMIhUJs3bqVl19+mWXLlvHggw9Gy2/evJlJkyaxZs0aduzYwVVXXcW1117Lzp0722zPzTffTGFhIXl5eaxatYrNmzfHjG6t6zp2u5177rnnlFOMSB0nhKDm+eepX74co7ERc0Ym5p49UTQNz0cfUfGf/4negXlqzma7du1i8+bNeDweHA4HyclNU5UcOXKENWvWUF9f32wbbyDMLbn5fPp1HYYQOKwmHFYNA/jsSD23vridHbu+ZPz48ei6zltL/0bxE1v57N9XcceEm3hm/TL+/d0nCZV4aHj/EJ7SWp7c8SRfhr9EQaGnoyfd47sTiAR4Y/8bPFvwLIaIHeegsaGe9S8+R/GuHWhmE85uGThSUvB7PXz+wdt88sF/cuCr/yKslyJ0J4qRiUI8inU/R0r/ROGn276pTA/Dukeg4FXQI5DUC5KyQRiw53VY++8Qjp3UuC3ra90s+rqcr31BUs0mcmwWEk0au9x+HjpYym5P+yd/lCRJ+q46nBh5vV5ee+015s2bx4wZM2LGB0pOTmbSpEls2bKFLVu2MGnSpOjEmGvXrqWoqIjly5czatQopk2bxqOPPsrSpUsJhZpmTX/qqaf47W9/y8UXX8yAAQN47LHHGDBgQJtjKO3du5cPP/yQF154gTFjxjBu3DieeeYZVq5cGU3a4uPjefbZZ7nzzjubzZ8mfXfBAwfwrluP5nRi6tYNxWxGUVW0pCQsPXsS3Lcfz/r1Z7qZ35nP5+OLL75AVVWcTicmkwlFUbDZbCQnJ+Nyudi1a1ez7ZZvP8LhmkZsZpV4iwlNUdAUlXizht2sUVLr467f/AGn08n6teu43Docq2ahd9/ePDDr1/zxxn/lxU2vcSRSheEJcmhjAYV1hSQpSSRZk1AVFZNqIs2eRrItmS2lW9hbuzemDfu2bqau7BjObpnY4h1NPx+TmYSUVMx2Ey7fanQ9iCoyUBUboKKIOBQ9C9VcT8mRFQT9kabKSrbB15shIRMc6aCaml7xaZDYA45+Coc3tyumIcPgpdIaArpBjt2KXVNRFYV4TaO33UJtKMIrpbXtGidNkiSpM3T4Utrrr7/O4MGDGTRoELNnz+bee+9l4cKFKIrCbbfdxoQJExg9ejQA+fn5ZGdnA02X34YPH05GRka0rilTpjBv3jwKCws5//zzm+3LMAw8Hk/MtB3Lli1j7ty50Q/Kbdu2kZSUxEXfmudr4sSJqKrK9u3buf766zt6iFHBYJBgMBh9f2J23nA4TDgcPu16T3airs6s8/vk2boV3efDlJbarKcCkwYmE+6P1hHfjrnvTnY2xebQoUM0NjbidDoxjOYjT1osFg4ePMhFF10UM/nwql1lCARmTUUQ+wVv1hQaG4Ps2PB3/vPRRzDXGgQagqhOczSWs6+cyRPvP8sb297nN5N/RaSkkaS+DvxK+PiEuN+0JU6Lo9ZfyyfHPmGgcyAAhq5z6PPtaFYbqCrGSUmGvVsA1epHDySg2YCT2ohwotj2cbhwH/1GDkL96iNUI4ww2eHkOGhWMAzEV//A6HPVKWO6w+2jxB+km1lDtBDTVJPKbncjX3t9ZNvaN5/d2XTOnG1kbFonY9OycyUuHWl/hxOj3NxcZs+eDcDUqVNxuVxs2rSJ8ePHs3z5cpYsWRKd/HXWrFnMnz+f2bNnU1FREZMUAdH3J+YuO9kTTzyB1+tl1qxZ0WVOp5NBgwZF31dUVDQbTdhkMpGSktJqve21aNEiHnnkkWbL165dS1xc59/3kJeX1+l1fh9SPt9BQqOXcHV1i+u1gB9x6CA7V6+G07yZ9myITW1tLV6vt9VfMF3XMQyDv//971gs33yJl9dqCANC4ZaH8dYDHoQeprGxkR1b88ny2AlGYst2T8rgSMUxal11REJhNI8CdqhuIeY+w8cX+74g40jT75cRDlFVUQGKgi8UaVY+PqMGq2IQCRsIJdRsvaKCqoXYVfAp+0sPMfLITpJ9AfzhqmZlAWyhAN6Du9mhtz7K/Ql7THYarElYjObtAogALtXEmo2byTaat60tZ8M5c7aSsWmdjE3Lfuhx8fnaf0m+Q4nR/v37yc/P55133mna2GTihhtuIDc3l/Hjx1NVVUVeXh5vvfUW0HRp7Pnnn+/ILqJeffVVHnnkEd57772YxOf666//Tr1AHbFw4ULuu+++6Hu3202vXr2YPHkyiYkdu7m0LeFwmLy8PCZNmoS5AxO5ni0aGly4DhzAlJ7e4lNE4UgEa5++jDjNHqOzJTb79+9nw4YNOJ1OVLX5VejGxkZMJhPTp0+PSYxySz7FXe7BYtZajI/fnohqtmC1WrnostG464tJTDSjmJr20Rj0cayunGsvnkSqMwW/u5FQggERSD8p5kII/F4/F/W7iOlDpwNgGDrv79uFz+3CkZLabP+qPQLiACazisXavFdGqEEM3cqoCy6l7/ABqBt3ou4tIyGllSfQ6n0k9D2f6ZOntx1QIMPtI+9gGU6zhq2FmLoiOmYhuGbMMHp2oMfobDlnzjYyNq2TsWnZuRIXdwfuc+1QYpSbm0skEonOWg9NH8RWq5UlS5bEJBEACQkJ0WWZmZnk5+fHrK+srIyu+7aVK1dyxx138MYbb5zyZunMzEyqqmL/co1EItTV1X3n+4msVmvMJZETzGZzl5wgXVVvV0scdxne999HuNxox+8pO8EIhVAiOomTJn6nYzsbYtOvXz8+++wzfD5fs8TYMAyCwSCDBw8mPj4+Zt11I3uwr2I/YV1gNcV++Qd1A81sYfSEa/jf//1f5t35K0zJNnRXEC256TH6l9a9hjfQyKxLr0P4Ipj6JOC1+FDCCoqixCRp7qCbOFMcl/W87FvxMtP/4kvY+fcPwNBRtdhf+8YqK1p6HOb4IE2X0b7dRgNUN8J7MX2GDsRsNsGASXDgHyjhRrDGDjdAqBFUFQZNQWvHz+vC5ET6xNXytS9Iti02cTSEoDaic0VyAr0dzYcqOJWz4Zw5W8nYtE7GpmU/9Lh0pO3tvvk6Eonwyiuv8OSTT1JQUBB97dq1i6ysLFasWBEt29JEr2PHjmXPnj0xSUxeXh6JiYkMHTo0umzFihXMnTuXFStWRC/JtWXs2LE0NDTEPOK8fv16DMNgzJgx7T086Tuw9O1LwtQpGF4v4YoKjGAQEYkQqasjUlaG7bzzcFx16vtNznZ2u52LLroIIQQNDQ2Ew2EMw8Dv91NXV0dqaiqjRo1qtt0/j8lmYIaDQMSgMRQhYhiEDQNvKEIgpNO3m4Pnn1pEIBDgignj+Xv9p9QFXBQWfcm/vfKfPPrmYuZdfQs9lFRMSVb6jx/FiLQRuISLukAdYSNMSA9R5auiIdTAVdlXMThlcEwbBo29nNReObiqKvF73Bi6TiQUwl1TTSRokJpwPZoWh6FWYAgfiAgCL0Irwwim0qffzVhsxxOqXmOg/9XgrQJPBeihpteJ970vb3q1g1lVuKNnOvGaRnEgRKOuExECT0Sn2B8iw2pmTo80OZ6RJEnfm3b3GK1atYr6+npuv/12nM7YQeRmzpxJbm4ud911V6vbT548maFDh3LLLbfw+OOPU1FRwQMPPMDdd98d7ZV59dVXmTNnDk8//TRjxoyJ3iNkt9uj+3znnXdYuHAh+/btA2DIkCFMnTqVO++8k+eee45wOMz8+fO58cYbY3q2ioqKCIVC1NXV4fF4KCgoAGjxi0zqGEVRSJ07F1NKKq7Vq9FrqhGGQHM4SJw+jZRbb0U7PqbUD915552H2Wxm586dNDQ0RMcxGjBgAJdcckmz3w2AOKuJV24fze/e2sOnh2rxhQxAYDVpXNovhcd/NoI0h5WPP/6Yu+66izm/uTO6bXKck99Pn8+CKXOx9krAcVkPzN3iuC/hPrylXmrUGip9lSgopNpS+Xnvn/PTAT9tlkjEJTq5+hd38cWa9zhatAdPbQ2KqpKQmsbQy69i0KVXcKx4NAf2vkKYEgQuhLCghEbQr88vGDDqm4cb0Exw1QNNT6Dt/QA85U0dTfZkGPZPcPEvwNS+y14A45ITeLC/wsulNRz0BQgZEWyqyiVJ8dzeM50hDntHf0ySJEmnT7TTNddcI6ZPn97iuu3btwtA7Nq1q806iouLxbRp04TdbhdpaWni/vvvF+FwOLr+yiuvFDR9xMa85syZEy3z0ksviZObXVtbK2666SbhcDhEYmKimDt3rvB4PDFlcnJyWqy7I1wulwCEy+Xq0HanEgqFxLvvvitCoVCn1nsm6D6f8O3eLRq/+EKEa2q+c31na2wikYgoKysTR44cEfX19e3e7lidT6zMPyJeyy8RR+saWyyzd+9e8dZbb4m/r/m7aDhULQLFLhGu8QnDMKJlTsSl0l0pCqoKxJ7qPaIx1HJ9J3PXVovS/UWi4tABET4proYREeUlBeLgl5vEsUOFIhKOtF2Zv0GIo581vXx17dp/a3TDEEUen8hv8IpDjYGY4+2Is/WcORvI2LROxqZl50pcOvL93e4eo7bGEho9enS7xhnJyclhzZrWn1TZuHHjKeto6TJdSkoKr776apvbFRcXn7Ju6btT7Xbsw4ef6WZ0OU3T6H4a0530SLZzw8XZbZYZPHgwgwcPbrPMCcm2ZLoldGwajoSUNBJSWh6hW1E0MnuNbH9lNif0vOjU5dpBVRTZOyRJ0hknJ5GVJEmSJEk6TiZGkiRJkiRJx8nESJIkSZIk6TiZGEmSJEmSJB3X4SlBpO+XyxdmX4UbXQj6pjnIdNqi64QQ7K/0UOsN4bCaGJqViBYJEygqQgSDmLplYOnTu11jwAghONhwkNpALfGmeAanDEYRCuXl5YTDYRISEkhLa3k8GcMfIVzeiBACc5odzdl8UMzWRMI6NUe9RGpLiROVfFm8l8NujeRu3Zk0aRIm0/d3irrCEYoaA02xtlvJslkI+X1UHTmMEdFxdsvA2S3j1BWdxcLherzeA4BBXFw/rNb0M90kSZKks8ppfets27aNcePGMXXqVFavXt1s/bJlywCaPT1WUlLCvHnz2LBhAw6Hgzlz5rBo0aLol195eTn3338/n3/+OQcPHuSee+7hqaeeOmV7AoEA999/PytXriQYDDJlyhT++7//O2ZutnvuuYdPPvmEL7/8kiFDhkTHMTpbBcI6f/v0CB8WVtLgC2EIQYLNzGX9U7ljXF+O1ft58ZPD7K/0EAzrmFWFqyv3MLHkMxI99aDrqHYbtvPOI+W227D26dPqvvbX7eeVolf4qv4rgpEgJsVE70Bvent7YwqZomP1ZGZmcumll5Ke3vRlKiIG3k/L8RfWYDSGQYBi07D1TcJxRU+0+NZHGhVCcPDzKvZ+fJjG8kq+PLSDZRtfoKy+PFomJSWFP/zhD/Tt27fzAtuCkGHwcmkNa6pd1IYjGECCpjLQXc3ITz9Cra1CGAZmu50eg4Zy0bXXt/pU19lK1/0cPfoKNbXrCYcbAIHJlEhqyjiys2/HZEo4VRWSJEk/Cqd1KS03N5cFCxawefNmysrKossXL16Mx+OJvvd4PCxevBhommBzxowZhEIhtm7dyssvv8yyZct48MEHo+WDwSDp6ek88MADjBzZ/keGf/3rX/PBBx/wxhtvsGnTJsrKyvinf/qnZuV+8YtfcMMNN5zOIX+vDEPw9LoD/C2/hGBYJ8tpo1dyHAqwZk8597+xi4feL2TX0QYSrSayU+K46shnXLDpHeqKy3DHJWLu2RPFZqdxez6V//GfhI6Vtrivg/UH+VP+n9hdvRuH2UHPhJ709PbEXGymrLaMkClEcnIyFouFkpIS1qxZQ21tLUII3B8doXF7OSJkoDmtaMk2FEXBX1hLwweHMIItTwwKsG9bOTtWH8RXWkLJ0Y95/P1FJDuc/H7mI7x57zN8/m+XMevKodx///3Rufm6ghCC/yqu4OWyWny6QZbVQrbNgr++jnWNEd7IOQ8tvamnSNNMHP7iM9a/+Bw+t6vL2tTZDCPCoUNPUl7+BsIIYbNlYbf1BCGoqFzFVwceQ9eDZ7qZkiRJZ4UOJ0Zer5fXXnuNefPmMWPGjGjvEEBycjKTJk1iy5YtbNmyhUmTJpF8fO6stWvXUlRUxPLlyxk1ahTTpk3j0UcfZenSpYRCTbNm9+7dm6effppbb721xRGEW+JyucjNzeW//uu/mDBhAhdeeCEvvfQSW7du5dNPP42W++tf/8rdd9/d5b0PnWFPqYuN+6tIi7eQnmDFpKloqkJKvIUeSXF8XlzH0XofvVPjiLeaiAt4ueDLj1EtZuocyRzz6hiKgpaQgKVXL8Klx3C9/36L+3rrwFtU+6vJTsgm3hyPpms4qh2YNTMhc4gKfwUGBlarlZSUFFwuFwUFBYRLvQT216PGm9ESLCiaiqIqqHFmtCRr0/p99S3u0+8NUfRJOWrYRYJSxfKtH9AnvSf/cdN9XDKgF36RhbBfxbNTzdx71y947bXXaGho6JJYf+n181GtmxSziW5WM2ZVwQgFUeprSAn4KEvOYG9qDxRVxeZw4MzIoPbYUQ7mb+uS9nQFl3sndfWfYLF0w2JJQ1VMKIqGxZKCzdodl+sL6uq3nOlmSpIknRU6fCnt9ddfZ/DgwQwaNIjZs2dz7733snDhQhRF4bbbbmPChAmMHj0agPz8fLKzmwaz27ZtG8OHD4+5vDVlyhTmzZtHYWEh559/frv2v3HjRq666ioOHz5M79692bFjB+FwOGay2cGDB5Odnc22bdu45JJLOnqIUcFgkGDwm7+kT8zOGw6HCYfDp13vyU7UdeLfj7+qJBDSyUy0YggjpqxhGATDBiZVQSAQQtDjyF7sPg8NzjQsikogrOPyhUiKM4OqoDgS8H78MYk3/zNqXFy0rmp/NQVVBTjNToRoqsvSYEENqehWHbNiJqgHcQVcJFmTALDZbHz99dcM03siQjpqgqlZG9FAKNBYVI15aFKz4y0pqiHgDZGgl1PhaeDLo1/xr9f9EpOqAQKLFuSIdxDDfXn8y4yh/PV/w7z55pvccccdnRbzEzbVuPBFDDJMGsJoOg6f24XQdSxWE6oQ7E7K4MLaY00bqBqa2cxX+VsZfMWEMzaH18nnTFuqqzdiGGFUzd7sZ6WoFkBQXb2BJOcVXdHU711HYvNjI2PTOhmblp0rcelI+zucGOXm5jJ79mwApk6disvlYtOmTYwfP57ly5ezZMmS6OSvs2bNYv78+cyePZuKioqYpAiIvj8xJ1p7xMXFMWjQoOhMuRUVFVgsFpKSkprV3ZF6W7Jo0SIeeeSRZsvXrl1L3LcSjM6Sl5cHwI5iFZ8Pqqq8zcoEIqAbCoGQHp2Qt3d1BWFdJxhpunQV1qG2roGQt2k0cjUQQAmHKXz/ffRvzQpfpVdR01hDnBJHUGlKAJPcSdgiNkJqUy9eRESora+Nvtd1HcMw+Mq7n+6+BIKGu8VjMYcUIsVutq450Gxd41EzXq+JOOGnxt0AQIYzjWCoqQ2GAZGImQaPgbf8AA6Hg08++SRm7rvO8pk1CZ/JTpXnm8t+Ya+biB7BCCooaNQKharKbyY/1oMBvD4/a1atQtG0Tm9TR5w4Z9pisRagaX48nqoW1ytKAJerkANftT4q/Q9Re2LzYyVj0zoZm5b90OPi8/naXbZDidH+/fvJz8+P3vNhMpm44YYbyM3NZfz48VRVVZGXl8dbb70FwFNPPcXzzz/fkV2c0ujRo6MTyHa1hQsXct9990Xfu91uevXqxeTJk0n8VoLxXYXDYfLy8pg0aRJms5nSjw9TvKOU9FR7sx6JYNjgmL8Bu1WjW7emy42mhu6YTBpWk4auaBiKQVqKA2dcU/IYqalFtdkYdt11MT1Gtf5a1m9ej4qK09pUl8VkweQ2oZgVDAyEIUh1pkZ7jBobG9E0jUHZQzB2NZCYam2x10SvC2LuEc/A6c1nWT+8q4bPqorRQnGkJzbVW1ZfxaAe/Zq2DdmxmCMkJah4Mwfi9Xq5/PLLmT59+ncLdAuOldZwoKKeblZz9Djcmoo7GMBktSCsVtIiAbplfDPthqe2hoSUNKZfc80Z7TH69jnTluLig1TXVGG3tzx1iN8fJClpOAP6d358z4SOxObHRsamdTI2LTtX4nLiik97dCgxys3NJRKJxPzlLoTAarWyZMmSmCQCICEhIbosMzOT/Pz8mPWVlZXRdacrMzOTUChEQ0NDTK9RZWXld6oXwGq1YrU2f/TcbDZ3yQlyot4rBmWwak8l3qCB0x67H0UR2MwamqoACqqiUJozFH9cIvGNbmpsTmxmDWecBVVRELqOaGwkYfJkrCfdt5VpzuTCjAvZeHQjTpsTVVHRk3QMi4EaUgmYAlg1K0m2JFRFbbqMFwwyfPhwkgd1p36fByVooJ7URhE2UIC4YWktxil7SBpfbizDX5dJRoKPETmDeSf/H1w2+CLMJishw0p/5x6s8fE88W4BFouFn//8510S86vSkni32o3bECSZm3p/4hOdeGurCRoGQlEZ6apEPZ4A6ZEIRiTMgNFjsVjaP4N8V2nPuZjebTy1deswdB8mkyNmna77URWFbulX/aA/9FrSVb+n5wIZm9bJ2LTshx6XjrS93TdfRyIRXnnlFZ588kkKCgqir127dpGVlcWKFSuiZVua6HXs2LHs2bMnevkHmrrmEhMTGTp0aLsbfLILL7wQs9nMunXrosv2799PSUkJY8eOPe16z6RhWYlMGppBvS9EhTtAMGIQ1g1qvEHKXAEu6ZtCTmo8xbU+3IEwjWY7+cOvJBIxSPXWkh2voug6ustFqKQEa042zuuubXFfMwfOJDM+kxJPCZ6Qh7AaxtXNRdgIYw1ZybRlggC/309dXR3JycmMGjUKc/d4bENTMXwRdHcQETEQuoHuDaG7gliyE7ANSmlxn7Z4M8Mu74GwJuEW3bnl0uspravgd8sfZ1PRV6jhQzS61nPL2z6ee/H/mD17NgkJXfM4+ZB4G9PTnDREdMqD4aZkyGwhktKNems8PWrLGVx1FEOP4Pe4cVVVkp7ThwFjLu2S9nQFZ+IoUlOvJBSuIRiswjBCGEaYYKiGQLCCpOQxpKT8cI5HkiSpK7W7x2jVqlXU19dz++23N3tibObMmeTm5nLXXXe1uv3kyZMZOnQot9xyC48//jgVFRU88MAD3H333TG9MifGF/J6vVRXV1NQ0NRjcCJ5ys/P59Zbb2XdunX06NEDp9PJ7bffzn333UdKSgqJiYksWLCAsWPHxtx4ffDgQbxeLxUVFfj9/uh+hg4delb85f9tiqIwf0J/uiVaWb27nGpPAAEkWM380wU9mHNpb8obAizbepg9pS4afGGqsy/EnhDPxCOfkVBfTbjChWqz47jySlJuvRVzKzPB93H24fdjfs/f9v6NL2u/xBV0YXKY6DugL9mebBS/gsvlwmw2079/fy655JLok4aJV/VCS7Dg312D7mm6B0m1atjP74bjsixUS+v33wwcnYHZqrH3YzOKZub3//QgL298gSffXxQtk5WVxf/8z/80uzetMymKwoKcDLpZzbxbVU9VKIIQkJiczKUmg2FFX6HX1+ERBmabnYGXXMaF03+C3fHDGfdHUTT69b0Xm7U7VdUfEgxV0TSOkZOsrJ/Ts8dsVLX9g3JKkiSd00Q7XXPNNWL69Oktrtu+fbsAxK5du9qso7i4WEybNk3Y7XaRlpYm7r//fhEOh2PKAM1eOTk50fUbNmwQgDh8+HB0md/vF//v//0/kZycLOLi4sT1118vysvLY+q98sorW6z72/WcisvlEoBwuVzt3qY9QqGQePfdd0UoFGq2zhsIi4KSerHjSJ2o9QZj1hmGIQ5Xe8XnxbViX7lb6LohjFBI+IuKROOOL0SotLTdbTAMQ5S4SsTOyp1iX+0+EdEjIhKJiPLycnHkyBFRV1fX6rZ6MCKCJW4ROOISEW/zY2hLJKKLqhK3KNt1ULh2bxVf/ONV8eZrK8T69etFKBRqMzadzRuJiC9cjeLzBq+oDjadl+FgUFQcOiBK9xcJT11tl7ehvU43LuGwWzS4CkRDw04RCtV3TePOsO/znPmhkbFpnYxNy86VuHTk+7vdPUYffPBBq+tGjx6NEOKUdeTk5LBmTdtPvpyqnvHjxzcrY7PZWLp0KUuXLm11u40bN56yfWejeKuJkb2SWlynKAq90+LpnRb/zULVjG3IkA7vR1EUeiX2oldir5jl7blPS7VoWHqdXg+Kpqmk90qAXglAP84fPpZvD9zwfT4iGq9pnJ8Y+7ShyWIho2//760NXc1kSsCZ2P7BUyVJkn5s5CSykiRJkiRJx8nESJIkSZIk6TiZGEmSJEmSJB0nEyNJkiRJkqTjZGIkSZIkSZJ0nEyMJEmSJEmSjpOJkSRJkiRJ0nEyMZIkSZIkSTpOJkaSJEmSJEnHtXvka+mbUbndbnen1hsOh/H5fLjd7h/07MVdQcamZTIurZOxaZ2MTetkbFp2rsTlxPd2e2bpkIlRB3g8HgB69ep1ipKSJEmSJJ1tPB4PTqezzTKKaE/6JAFgGAZlZWUkJCSgKEqn1et2u+nVqxdHjx4lMTGx0+o9F8jYtEzGpXUyNq2TsWmdjE3LzpW4CCHweDxkZWWhqm3fRSR7jDpAVVV69uzZZfUnJib+oE+8riRj0zIZl9bJ2LROxqZ1MjYtOxficqqeohPkzdeSJEmSJEnHycRIkiRJkiTpOJkYnQWsVisPPfQQVqv1TDflrCNj0zIZl9bJ2LROxqZ1MjYt+zHGRd58LUmSJEmSdJzsMZIkSZIkSTpOJkaSJEmSJEnHycRIkiRJkiTpOJkYSZIkSZIkHScToy6wdOlSevfujc1mY8yYMeTn57dZ/o033mDw4MHYbDaGDx/OmjVrYtYLIXjwwQfp3r07drudiRMncuDAga48hC7T2bG57bbbUBQl5jV16tSuPIQu05HYFBYWMnPmTHr37o2iKDz11FPfuc6zWWfH5uGHH2523gwePLgLj6BrdCQuzz//PJdffjnJyckkJyczceLEZuV/rJ817YnNj/Wz5u233+aiiy4iKSmJ+Ph4Ro0axf/93//FlDmXzhsAhNSpVq5cKSwWi3jxxRdFYWGhuPPOO0VSUpKorKxssfwnn3wiNE0Tjz/+uCgqKhIPPPCAMJvNYs+ePdEyf/rTn4TT6RTvvvuu2LVrl7juuutEnz59hN/v/74Oq1N0RWzmzJkjpk6dKsrLy6Ovurq67+uQOk1HY5Ofny9+85vfiBUrVojMzEyxePHi71zn2aorYvPQQw+JYcOGxZw31dXVXXwknaujcfnnf/5nsXTpUrFz506xd+9ecdtttwmn0ymOHTsWLfNj/axpT2x+rJ81GzZsEG+//bYoKioSBw8eFE899ZTQNE18+OGH0TLnynlzgkyMOtno0aPF3XffHX2v67rIysoSixYtarH8rFmzxIwZM2KWjRkzRvzqV78SQghhGIbIzMwUf/nLX6LrGxoahNVqFStWrOiCI+g6nR0bIZo+rH7yk590SXu/Tx2Nzbfl5OS0+OX/Xeo8m3RFbB566CExcuTITmzl9++7/nwjkYhISEgQL7/8shDix/1Zc7KTYyOE/Kz5tvPPP1888MADQohz67w5QV5K60ShUIgdO3YwceLE6DJVVZk4cSLbtm1rcZtt27bFlAeYMmVKtPzhw4epqKiIKeN0OhkzZkyrdZ6NuiI2J2zcuJFu3boxaNAg5s2bR21tbecfQBc6ndiciTrPhK48jgMHDpCVlUXfvn25+eabKSkp+a7N/d50Rlx8Ph/hcJiUlBTgx/1Zc7KTY3PCj/2zRgjBunXr2L9/P1dccQVw7pw33yYTo05UU1ODrutkZGTELM/IyKCioqLFbSoqKtosf+LfjtR5NuqK2ABMnTqVV155hXXr1vHnP/+ZTZs2MW3aNHRd7/yD6CKnE5szUeeZ0FXHMWbMGJYtW8aHH37Is88+y+HDh7n88svxeDzftcnfi86Iy+9+9zuysrKiX2g/5s+ak50cG/hxf9a4XC4cDgcWi4UZM2bwzDPPMGnSJODcOW++zXSmGyBJ38WNN94Y/f/w4cMZMWIE/fr1Y+PGjVx99dVnsGXS2WzatGnR/48YMYIxY8aQk5PD66+/zu23334GW/b9+NOf/sTKlSvZuHEjNpvtTDfnrNJabH7MnzUJCQkUFBTg9XpZt24d9913H3379mX8+PFnumldQvYYdaK0tDQ0TaOysjJmeWVlJZmZmS1uk5mZ2Wb5E/92pM6zUVfEpiV9+/YlLS2NgwcPfvdGf09OJzZnos4z4fs6jqSkJAYOHPiDOW++S1yeeOIJ/vSnP7F27VpGjBgRXf5j/qw5obXYtOTH9Fmjqir9+/dn1KhR3H///fzsZz9j0aJFwLlz3nybTIw6kcVi4cILL2TdunXRZYZhsG7dOsaOHdviNmPHjo0pD5CXlxct36dPHzIzM2PKuN1utm/f3mqdZ6OuiE1Ljh07Rm1tLd27d++chn8PTic2Z6LOM+H7Og6v18uhQ4d+MOfN6cbl8ccf59FHH+XDDz/koosuiln3Y/6sgbZj05If82eNYRgEg0Hg3DlvYpzpu7/PNStXrhRWq1UsW7ZMFBUViV/+8pciKSlJVFRUCCGEuOWWW8S//du/Rct/8sknwmQyiSeeeELs3btXPPTQQy0+rp+UlCTee+89sXv3bvGTn/zkB/koZGfHxuPxiN/85jdi27Zt4vDhw+Kjjz4SF1xwgRgwYIAIBAJn5BhPV0djEwwGxc6dO8XOnTtF9+7dxW9+8xuxc+dOceDAgXbX+UPRFbG5//77xcaNG8Xhw4fFJ598IiZOnCjS0tJEVVXV9358p6ujcfnTn/4kLBaLePPNN2MeOfd4PDFlfoyfNaeKzY/5s+axxx4Ta9euFYcOHRJFRUXiiSeeECaTSTz//PPRMufKeXOCTIy6wDPPPCOys7OFxWIRo0ePFp9++ml03ZVXXinmzJkTU/71118XAwcOFBaLRQwbNkysXr06Zr1hGOLf//3fRUZGhrBareLqq68W+/fv/z4OpdN1Zmx8Pp+YPHmySE9PF2azWeTk5Ig777zzB/fFf0JHYnP48GEBNHtdeeWV7a7zh6SzY3PDDTeI7t27C4vFInr06CFuuOEGcfDgwe/xiDpHR+KSk5PTYlweeuihaJkf62fNqWLzY/6s+cMf/iD69+8vbDabSE5OFmPHjhUrV66Mqe9cOm+EEEIRQojvt49KkiRJkiTp7CTvMZIkSZIkSTpOJkaSJEmSJEnHycRIkiRJkiTpOJkYSZIkSZIkHScTI0mSJEmSpONkYiRJkiRJknScTIwkSZIkSZKOk4mRJEmSJEnScTIxkiRJkiRJOk4mRpIkSZIkScfJxEiSJEmSJOk4mRhJkiRJkiQd9/8BF+FvPaXkhqsAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -547,11 +584,1352 @@
     "hifreq = hifreq.tolist()\n",
     "# Plot only selected alleles\n",
     "HLAfreq.plotAF(\n",
-    "    international[international.allele.isin(hifreq)],\n",
+    "    winternational[winternational.allele.isin(hifreq)],\n",
     "    cafs[cafs.allele.isin(hifreq)],\n",
     "    datasetID='country')"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Credible intervals and population size\n",
+    "The approach above should only be used for the default model. If you want to account for population size using the compound model to get credible intervals the approach is a little different. A different approach is needed because the compound model accounts for study variance and the above weighting will chiefly affect that variance rather than the total allele frequency.\n",
+    "The solution to accounting for population size when estimating credible intervals is to calculate the country specific allele frequencies first and then weight the country estimates before combining them. In this case, slightly different from above, we weight by the country's proportion of the total population. This different weighting is because sample size is already accounted for when estimating county allele frequencies.\n",
+    "\n",
+    "Load the allele frequency data so that each country is an element in a list. This is the non-combined data we downloaded earlier. This time we're skipping Guinea because the data wasn't actually from Guinea."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "population               loci\n",
+      "South Africa Natal Zulu  A       0.935\n",
+      "Name: allele_freq, dtype: float64\n",
+      "1 studies have total allele frequency < 0.95\n"
+     ]
+    }
+   ],
+   "source": [
+    "countries = ['Cameroon','Cape+Verde','Ghana',\n",
+    "    'Guinea-Bissau', 'Kenya','Sao+Tome+and+Principe','Senegal',\n",
+    "    'South+Africa','Uganda','Zimbabwe']\n",
+    "aftabs = []\n",
+    "for country in countries:\n",
+    "  # Load raw county data\n",
+    "  aftab = pd.read_csv(\"../data/example/multi_country/%s_raw.csv\" %country)\n",
+    "  # Drop any incomplete studies\n",
+    "  aftab = HLAfreq.only_complete(aftab)\n",
+    "  # Ensure all alleles have the same resolution\n",
+    "  aftab = HLAfreq.decrease_resolution(aftab, 2)\n",
+    "  aftab['country'] = country\n",
+    "  aftabs.append(aftab)\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to combine different countries they must have the same alleles. The easiest way to do this is using `HLAfreq.unmeasured_alleles()`. So we will join all the country datasets up, add the missing alleles, then split them apart again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Join them up\n",
+    "all_aftabs = pd.concat(aftabs)\n",
+    "\n",
+    "# Add the missing alleles\n",
+    "all_aftabs = HLAfreq.unmeasured_alleles(all_aftabs, datasetID='population')\n",
+    "\n",
+    "# Split them apart again\n",
+    "aftabs = []\n",
+    "for country in countries:\n",
+    "  # List all populations in a given country\n",
+    "  country_populations = all_aftabs[all_aftabs.country == country].population.unique()\n",
+    "  # Select all data from a population in the given country\n",
+    "  mask = all_aftabs.population.isin(country_populations)\n",
+    "  aftabs.append(all_aftabs[mask])"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we fit the compound model for each country separately. Because we need access to the underlying trace, we fit the model with internal functions rather than `AFhdi()`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cameroon\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 22 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cape+Verde\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 24 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ghana\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 22 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Guinea-Bissau\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 27 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Kenya\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 16 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sao+Tome+and+Principe\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 23 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Senegal\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 23 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "South+Africa\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 23 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Uganda\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 22 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Zimbabwe\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 22 seconds.\n"
+     ]
+    }
+   ],
+   "source": [
+    "idatas = []\n",
+    "for i,aftab in enumerate(aftabs):\n",
+    "  print(countries[i])\n",
+    "  # fit pymc model to each dataset separately\n",
+    "  c_array, allele_names = HLAhdi._make_c_array(aftab)\n",
+    "  idata = HLAhdi._fit_Dirichlet_Multinomial(c_array)\n",
+    "  idatas.append(idata)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As we're not including Guinea this time we have to recalculate the population size proportions otherwise our weights will not sum to one and neither will our allele frequencies."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "population_sizes = {'Cameroon':24348251,\n",
+    "    'Cape+Verde':563198,\n",
+    "    'Ghana':30832019,\n",
+    "    # 'Guinea':12907395,\n",
+    "    'Guinea-Bissau':1646077,\n",
+    "    'Kenya':47564296,\n",
+    "    'Sao+Tome+and+Principe':214610,\n",
+    "    'Senegal':17223497,\n",
+    "    'South+Africa':60604992,\n",
+    "    'Uganda':42885900,\n",
+    "    'Zimbabwe':15178979\n",
+    "}\n",
+    "\n",
+    "country_data = pd.DataFrame(\n",
+    "    {'country':population_sizes.keys(),\n",
+    "    'population':population_sizes.values()}\n",
+    ")\n",
+    "\n",
+    "# What proportion of the regional population does each country account for\n",
+    "country_data['proportion'] = country_data.population/country_data.population.sum()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next we take the estimate for each county and multiply it by the population proportion for that country. Finally we sum these weighted estimates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sd</th>\n",
+       "      <th>hdi_3%</th>\n",
+       "      <th>hdi_97%</th>\n",
+       "      <th>mcse_mean</th>\n",
+       "      <th>mcse_sd</th>\n",
+       "      <th>ess_bulk</th>\n",
+       "      <th>ess_tail</th>\n",
+       "      <th>r_hat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A*01:01</th>\n",
+       "      <td>0.040</td>\n",
+       "      <td>0.007</td>\n",
+       "      <td>0.028</td>\n",
+       "      <td>0.054</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4128.0</td>\n",
+       "      <td>3365.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:02</th>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.014</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4615.0</td>\n",
+       "      <td>3709.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:03</th>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.013</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3747.0</td>\n",
+       "      <td>3452.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:06</th>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5086.0</td>\n",
+       "      <td>3560.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:09</th>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.010</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4828.0</td>\n",
+       "      <td>3588.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*69:01</th>\n",
+       "      <td>0.007</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.011</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5330.0</td>\n",
+       "      <td>3755.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:01</th>\n",
+       "      <td>0.027</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>0.037</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4433.0</td>\n",
+       "      <td>3294.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:02</th>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.008</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5237.0</td>\n",
+       "      <td>3646.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:03</th>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.014</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4620.0</td>\n",
+       "      <td>3717.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*80:01</th>\n",
+       "      <td>0.010</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.016</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3889.0</td>\n",
+       "      <td>3798.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>85 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
+       "A*01:01  0.040  0.007   0.028    0.054        0.0      0.0    4128.0   \n",
+       "A*01:02  0.009  0.003   0.005    0.014        0.0      0.0    4615.0   \n",
+       "A*01:03  0.008  0.002   0.004    0.013        0.0      0.0    3747.0   \n",
+       "A*01:06  0.005  0.002   0.002    0.009        0.0      0.0    5086.0   \n",
+       "A*01:09  0.006  0.002   0.002    0.010        0.0      0.0    4828.0   \n",
+       "...        ...    ...     ...      ...        ...      ...       ...   \n",
+       "A*69:01  0.007  0.002   0.003    0.011        0.0      0.0    5330.0   \n",
+       "A*74:01  0.027  0.005   0.017    0.037        0.0      0.0    4433.0   \n",
+       "A*74:02  0.005  0.002   0.002    0.008        0.0      0.0    5237.0   \n",
+       "A*74:03  0.009  0.003   0.004    0.014        0.0      0.0    4620.0   \n",
+       "A*80:01  0.010  0.003   0.005    0.016        0.0      0.0    3889.0   \n",
+       "\n",
+       "         ess_tail  r_hat  \n",
+       "A*01:01    3365.0    1.0  \n",
+       "A*01:02    3709.0    1.0  \n",
+       "A*01:03    3452.0    1.0  \n",
+       "A*01:06    3560.0    1.0  \n",
+       "A*01:09    3588.0    1.0  \n",
+       "...           ...    ...  \n",
+       "A*69:01    3755.0    1.0  \n",
+       "A*74:01    3294.0    1.0  \n",
+       "A*74:02    3646.0    1.0  \n",
+       "A*74:03    3717.0    1.0  \n",
+       "A*80:01    3798.0    1.0  \n",
+       "\n",
+       "[85 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weighted_country_estimates = []\n",
+    "for i,country in enumerate(countries):\n",
+    "    # Country specific weight\n",
+    "    weight = country_data[country_data.country==country].proportion.values\n",
+    "    # Weighting the country estimate\n",
+    "    weighted_country_estimate = idatas[i].posterior['frac'] * weight\n",
+    "    weighted_country_estimates.append(weighted_country_estimate)\n",
+    "\n",
+    "# Sum all the weighted country estimates\n",
+    "weighted_international_estimate = sum(weighted_country_estimates)\n",
+    "\n",
+    "# Get model summary\n",
+    "summary = az.summary(weighted_international_estimate)\n",
+    "# Add the allele names on to the summary\n",
+    "# these were produced when we made c_array\n",
+    "summary.index = allele_names\n",
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<AxesSubplot: title={'center': 'frac'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac'}>]], dtype=object)"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# This object can be fully explored using arviz like any other pymc model\n",
+    "az.plot_trace(weighted_international_estimate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.02759661, 0.0548428 ],\n",
+       "       [0.00452285, 0.01433677],\n",
+       "       [0.00377304, 0.0129694 ],\n",
+       "       [0.00176486, 0.00881422],\n",
+       "       [0.00231861, 0.01024124],\n",
+       "       [0.00203228, 0.00954437],\n",
+       "       [0.03415686, 0.06497219],\n",
+       "       [0.01573759, 0.03394972],\n",
+       "       [0.00235762, 0.01074451],\n",
+       "       [0.0021822 , 0.00932612],\n",
+       "       [0.01403252, 0.03101837],\n",
+       "       [0.00373039, 0.01356755],\n",
+       "       [0.00196443, 0.00987427],\n",
+       "       [0.00434116, 0.01517492],\n",
+       "       [0.00564147, 0.01691425],\n",
+       "       [0.0026366 , 0.01053915],\n",
+       "       [0.00148889, 0.00845054],\n",
+       "       [0.00176905, 0.00898124],\n",
+       "       [0.00234081, 0.01046179],\n",
+       "       [0.00186188, 0.00876754],\n",
+       "       [0.00203182, 0.00905159],\n",
+       "       [0.00193571, 0.00895337],\n",
+       "       [0.00179998, 0.00900889],\n",
+       "       [0.02321528, 0.04599152],\n",
+       "       [0.00311518, 0.01205201],\n",
+       "       [0.00896835, 0.02769771],\n",
+       "       [0.00189439, 0.00985112],\n",
+       "       [0.00206027, 0.00961964],\n",
+       "       [0.02288719, 0.04653844],\n",
+       "       [0.00210568, 0.0104285 ],\n",
+       "       [0.00180538, 0.00896166],\n",
+       "       [0.00150521, 0.00843743],\n",
+       "       [0.00204784, 0.0101851 ],\n",
+       "       [0.01709138, 0.03842565],\n",
+       "       [0.00212325, 0.01014264],\n",
+       "       [0.00165893, 0.00846217],\n",
+       "       [0.00372449, 0.01475766],\n",
+       "       [0.00152746, 0.00848436],\n",
+       "       [0.00193521, 0.00922991],\n",
+       "       [0.00157473, 0.00838175],\n",
+       "       [0.00378695, 0.01341583],\n",
+       "       [0.01160147, 0.02687958],\n",
+       "       [0.00178218, 0.00884404],\n",
+       "       [0.00191682, 0.00977162],\n",
+       "       [0.00165529, 0.00880991],\n",
+       "       [0.00330384, 0.01207244],\n",
+       "       [0.00703055, 0.01960981],\n",
+       "       [0.0193696 , 0.03994969],\n",
+       "       [0.00181336, 0.0088939 ],\n",
+       "       [0.00228535, 0.01033887],\n",
+       "       [0.00184695, 0.00903161],\n",
+       "       [0.02108054, 0.04292904],\n",
+       "       [0.02220973, 0.04393149],\n",
+       "       [0.0018361 , 0.00901249],\n",
+       "       [0.00890208, 0.02225097],\n",
+       "       [0.00170556, 0.00899271],\n",
+       "       [0.00199869, 0.00952631],\n",
+       "       [0.0020753 , 0.00991832],\n",
+       "       [0.00976027, 0.02484884],\n",
+       "       [0.00276726, 0.01087186],\n",
+       "       [0.00335449, 0.01247954],\n",
+       "       [0.01155675, 0.02631822],\n",
+       "       [0.00185561, 0.00900223],\n",
+       "       [0.0019529 , 0.00912835],\n",
+       "       [0.00216055, 0.01033339],\n",
+       "       [0.00690024, 0.01936623],\n",
+       "       [0.01479347, 0.03303133],\n",
+       "       [0.00246119, 0.01059669],\n",
+       "       [0.01388516, 0.03169402],\n",
+       "       [0.01108828, 0.02599472],\n",
+       "       [0.00311409, 0.0128932 ],\n",
+       "       [0.01510048, 0.03311533],\n",
+       "       [0.00578678, 0.01594144],\n",
+       "       [0.00361539, 0.01296951],\n",
+       "       [0.0160388 , 0.03481026],\n",
+       "       [0.02409609, 0.04690669],\n",
+       "       [0.00162889, 0.00867585],\n",
+       "       [0.00184908, 0.00935288],\n",
+       "       [0.00160451, 0.00851681],\n",
+       "       [0.001937  , 0.00959509],\n",
+       "       [0.00289136, 0.0113081 ],\n",
+       "       [0.01694051, 0.03715183],\n",
+       "       [0.00159336, 0.00858231],\n",
+       "       [0.00447347, 0.0143532 ],\n",
+       "       [0.00440853, 0.01568641]])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# az.summary() gives 96% credible intervals\n",
+    "# but any interval can be obtained with az.hdi()\n",
+    "az.hdi(weighted_international_estimate, 0.95).frac.values"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It's important to check the compound models by comparing to the default model. Below we plot the population size weighted default model estimates against the population weighted compound model estimates. Unfortunately they are not as similar as we'd like. The compound model is overestimating rare alleles and underestimating common alleles. This suggests an overly informative prior pulling all alleles to an average frequency. For more detail on this issue see the [working with priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb) example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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LeHl5YerUqTAzM4OjoyOOHz+OX3/9FUuWLBHtPomIqGSys7MxZcoUrFy5EjY2Nvj7778LjAUlKglRE6D+/fsjMTERc+bMQXx8PFxdXREaGir/4n7w4IFCa07Lli2xbds2fP3115g1axbq1KmDPXv2oFGjRvI6wcHBmDlzJgYOHIgXL17A0dER33//PT7//PNSvz8iIiq5uLg49O3bF6dPnwYAjB49mttZkNqIug6QtlJlHQEiIlK/U6dOoW/fvoiPj4elpSW2bNmCbt26iR0WabkysQ4QERHR2wRBwIoVK+Dt7Y34+Hg0atQI58+fZ/JDascEiIiItMrZs2eRm5sLPz8/nDt3DnXq1BE7JNJBOrcOEBERlV0SiQTr169Hx44dMWzYMO7nRRrDFiAiIhLV/v378X//93/IH5Javnx5DB8+nMkPaRQTICIiEkVeXh7mzJmDbt26YdOmTfj111/FDon0CLvAiIio1L148QIDBw5EaGgoAODLL7+En5+fyFGRPmECREREperSpUvw9fVFbGwsTE1NsW7dOgwePFjssEjPMAEiIqJSs3PnTgwZMgSZmZlwdnbGrl274OrqKnZYpIc4BoiIiEpN9erVkZeXh86dOyM6OprJD4mGLUBERKRRubm5MDR8/ePG09MTp06dQrNmzQpsXE1UmvjVR0REGnPixAnUrVsXly9flpe5u7sz+SHR8SuQiIjUThAELFu2DO3atUNsbCy++eYbsUMiUsAuMCIiUqu0tDSMGjUKwcHBAICBAwdi3bp1IkdFpEjpFqAhQ4YgNTVV/v7vv/9GTk6ORoIiIqKy6fbt22jRogWCg4NhaGiIFStWYMuWLShXrpzYoREpUDoB2rp1KzIyMuTvP/roIzx8+FAjQRERUdlz9epVNGvWDFevXoWtrS3Cw8Mxbtw4bmlBWknpLrD8PVqKek9ERPqtfv36cHd3R2ZmJn7//XfY2dmJHRJRkTgGiIiISuzFixcwNzeHiYkJpFIpdu7cCXNzcxgZGYkdGlGxVEqArl27hvj4eACvW4Bu3LiBtLQ0hToffPCB+qIjIiKtFRMTg969e8PHxwdBQUEAACsrK3GDIlKSRFCyL8vAwAASiaTQrq/8colEgry8PLUHWdpSUlJgaWmJ5ORkWFhYiB0OEZHW2bx5M8aMGYPMzEzUrFkT0dHRqFixothhkZ5T5ee30i1AsbGx7x0YERGVbVlZWZg4caK8xadr167YsmULkx8qc5ROgBwdHd9Z58qVK+8VDBERaa9Hjx6hT58+iIyMhEQiwTfffIOvv/6aqzpTmfTeg6BTU1Oxfft2/Pzzz7hw4YJOdIEREZGivLw8tG/fHjdv3oSVlRW2bt2KLl26iB0WUYmVOG0/ceIEhg4dCjs7OyxatAjt2rXDuXPn1BkbERFpCalUisWLF+PDDz9EdHQ0kx8q81RqAYqPj8fmzZuxYcMGpKSkoF+/fsjKysKePXvg4uKiqRiJiEgEaWlpuHnzJtzc3AC8Hu/TqVMnSKVSkSMjen9KtwB169YN9erVw+XLl7Fs2TI8efIEK1eu1GRsREQkkps3b8LDwwMdO3ZUmATD5Id0hdIJ0KFDhzBixAjMnTsXXbt25TcBEZGO2rNnD5o3b45r167BxMQEz58/FzskIrVTOgE6deoUUlNT4ebmBg8PD6xatQrPnj3TZGxERFSK8vLyMGvWLPTq1Qupqan46KOPEBMTg2bNmokdGpHaKZ0AtWjRAuvXr0dcXBw+++wzBAcHw97eHjKZDEeOHFHYKZ6IiMqWZ8+eoXPnzggMDAQATJw4EWFhYbC1tRU5MiLNUHol6MLcvHkTGzZswJYtW5CUlIQOHTpg37596oxPFFwJmoj0zfTp07FgwQKUK1cOP//8M/z8/MQOiUhlqvz8fq/Vq+rVq4cFCxbg0aNH2L59+/ucioiIRDR37lz0798f586dY/JDeuG9WoB0FVuAiEjXZWVlYd26dfjiiy84qYV0hkb2AiMiIt3w8OFD9OnTB1FRUUhMTMS3334rdkhEpY4buBAR6ZFjx47Bzc0NUVFRqFixIlq2bCl2SESiYAJERKQHBEHAwoUL0aFDByQmJsLV1RUXLlxAp06dxA6NSBTsAiMi0nGpqan4v//7P/zxxx8AgKFDh2Lt2rUwMzMTOTIi8SiVAKkytb179+4lDoaIiNQvNjYW+/fvh5GREZYvX47PP/8cEolE7LCIRKXULDADA8WeMolEgjcPe/MbKS8vT43hiYOzwIhI1/z+++9wcHCAp6en2KEQaYza1wGSyWTy1+HDh+Hq6opDhw4hKSkJSUlJOHjwIJo2bYrQ0FC13AAREZVcbm4uvvrqK0RFRcnL+vXrx+SH6A0qrwPUqFEjBAUFoXXr1grlJ0+exOjRo3H9+nW1BigGtgARUVmVmJgIPz8/hIWFwcHBATdu3EC5cuXEDouoVGh0HaA7d+7AysqqQLmlpSXu3bun6umIiEhNzp8/j969e+Phw4cwNzfHwoULmfwQFUHlafDNmzeHv78/EhIS5GUJCQmYOnUq3N3d1RocEREp5+eff0br1q3x8OFD1KlTB5GRkejfv7/YYRFpLZUToI0bNyIuLg41atRA7dq1Ubt2bdSoUQOPHz/Ghg0bNBEjEREVIScnB6NHj8aoUaOQnZ2NHj164Pz582jYsKHYoRFpNZW7wGrXro3Lly/jyJEjuHHjBgCgQYMGaN++PadVEhGVMqlUioSEBEgkEsybNw8zZswoMHOXiAriZqiF4CBoItJ2giDIf+lMTk7GhQsX0K5dO5GjIhKXxjdDDQsLQ1hYGJ4+fQqZTKbw2caNG0tySiIiUoIgCFiwYAGuX7+OTZs2QSKRwNLSkskPkYpUToDmzp2Lb7/9Fs2aNYOdnR27vYiISklKSgqGDRuG3bt3AwAGDhyIDh06iBwVUdmkcgIUFBSEzZs3Y/DgwZqIh4iICnH9+nX06tULN2/ehJGREVauXIn27duLHRaRSrLzBCy5nAsA8P/AEMZS8RpRVE6AsrOz0bJlS03EQkREhfjjjz8wfPhwpKWloVq1aggJCYGHh4fYYRGVaSpPFRg5ciS2bdumiViIiOgt8+fPR9++fZGWloa2bdsiJiaGyQ+RGqjcApSZmYl169bh6NGj+OCDD2BkZKTw+ZIlS9QWHBGRvvP09IRUKsWkSZMQGBgIQ8MSzV0horeo/J10+fJluLq6AgCuXLmi8BkHRBMRvb+0tDSUL18eAODt7Y3r16+jTp06IkdFpFtUToDCw8M1EQcRkd4TBAHr16/HV199hVOnTqFevXoAwOSHSAO4XCgRkRbIzMzEyJEj8dlnn+HZs2f4+eefxQ6JSKep3ALk7e1dbFfXsWPH3isgIiJ9c//+ffTu3RsXLlyAgYEB5s+fj2nTpokdFpFOUzkByh//ky8nJweXLl3ClStXMHToUHXFRUSkF44cOQI/Pz88f/4clSpVQnBwMNf3ISoFKidAS5cuLbT8m2++QVpa2nsHRESkL44ePYpOnTpBJpOhWbNmCAkJQY0aNcQOi0gvqG0M0KBBg0q0D9jq1avh5OQEU1NTeHh4ICoqqtj6O3fuRP369WFqaorGjRvj4MGDBepcv34d3bt3h6WlJczNzdG8eXM8ePBA5diIiDTJy8sLLVu2xMiRI3Hy5EkmP0SlSG0J0NmzZ2FqaqrSMTt27IC/vz8CAgIQExODJk2awMfHB0+fPi20/pkzZ+Dn54cRI0bg4sWL6NmzJ3r27KkwHf/OnTto3bo16tevj4iICFy+fBmzZ89WOTYiIk24ffs2cnJyAABGRkb466+/sH79ev4fRVTKJIIgCKoc4Ovrq/BeEATExcUhOjoas2fPRkBAgNLn8vDwQPPmzbFq1SoAgEwmg4ODA8aNG4cZM2YUqN+/f3+kp6dj//798rIWLVrA1dUVQUFBAIABAwbAyMgIW7ZsUTqOrKwsZGVlyd+npKTAwcEBycnJsLCwUPo8RETF2blzJ4YPH47Ro0dz0VjSS5reCywlJQWWlpZK/fxWuQXI0tJS4WVtbY22bdvi4MGDKiU/2dnZuHDhgsJgPwMDA7Rv3x5nz54t9JizZ88WGBzo4+Mjry+TyXDgwAHUrVsXPj4+qFq1Kjw8PLBnz55iYwkMDFS4JwcHB6Xvg4joXXJzczFlyhT069cP6enpuHz5MrKzs8UOi0ivqTwIetOmTWq58LNnz5CXlwcbGxuFchsbG9y4caPQY+Lj4wutHx8fDwB4+vQp0tLS8MMPP2DevHn48ccfERoaCl9fX4SHh8PLy6vQ886cORP+/v7y9/ktQERE7yshIQEDBgxAREQEAGDatGn4/vvvuaUFkchK/B144cIFXL9+HQDQsGFDfPjhh2oLqqRkMhkAoEePHpg0aRKA19P2z5w5g6CgoCITIBMTE5iYmJRanESkH86dO4c+ffrg8ePHKF++PDZv3ozevXuLHRYRoQQJ0NOnT+W/zVhZWQEAkpKS4O3tjeDgYFSpUkWp81SuXBlSqRQJCQkK5QkJCbC1tS30GFtb22LrV65cGYaGhnBxcVGo06BBA5w6dUqpuIiI1CEtLQ2ffPIJnj9/jvr162PXrl1o0KCB2GER0f+oPAZo3LhxSE1NxdWrV/HixQu8ePECV65cQUpKCsaPH6/0eYyNjeHm5oawsDB5mUwmQ1hYGDw9PQs9xtPTU6E+8HoRsfz6xsbGaN68OW7evKlQ59atW3B0dFQ6NiKi91W+fHkEBQWhd+/eiIqKYvJDpG0EFVlYWAhRUVEFyiMjIwVLS0uVzhUcHCyYmJgImzdvFq5duyaMHj1asLKyEuLj4wVBEITBgwcLM2bMkNc/ffq0YGhoKCxatEi4fv26EBAQIBgZGQn//POPvM6uXbsEIyMjYd26dcLt27eFlStXClKpVDh58qTScSUnJwsAhOTkZJXuh4j02927d4Vz584plMlkMpGiIdI+WbkyITAmWwiMyRayctX/vaHKz2+Vu8BkMhmMjIwKlBsZGcnH4Cirf//+SExMxJw5cxAfHw9XV1eEhobKBzo/ePAABgb/NVK1bNkS27Ztw9dff41Zs2ahTp062LNnDxo1aiSv06tXLwQFBSEwMBDjx49HvXr1EBISgtatW6t6q0RESvvrr7/g5+cHIyMjxMTEoFq1agBQ7N6JRCQeldcB6tGjB5KSkrB9+3bY29sDAB4/foyBAweiYsWK2L17t0YCLU2qrCNARPpNJpNh/vz5mDNnDgRBQPPmzRESEsKZpESFKNPrAK1atQopKSlwcnJCrVq1UKtWLTg7OyMlJQUrV64scdBERGVNcnIyevbsidmzZ0MQBIwaNQonTpxg8kNUBqjcBebg4ICYmBgcPXpUvl5PgwYNuHsxEemVK1euwNfXF7dv34aJiQlWr16NESNGiB0WESmpROsASSQSdOjQAR06dFB3PEREZcKSJUtw+/Zt1KhRAyEhIWjWrJnYIRGRCkq0GWpYWBg++eQTeRfYJ598gqNHj6o7NiIirbVy5Up88cUXuHDhApMfojJI5QRozZo16NSpEypUqIAJEyZgwoQJsLCwQJcuXbB69WpNxEhEJLqEhATMnTsX+fNGzM3NsXr1alSuXFnkyIioJFTuAps/fz6WLl2KsWPHysvGjx+PVq1aYf78+fjyyy/VGiARkdjOnDmDvn374smTJyhXrhymTp0qdkhE9J5UbgFKSkpCp06dCpR37NgRycnJagmKiEgbCIKA1atXo23btnjy5AlcXFzQvXt3scMiIjVQOQHq3r17oWv97N27F5988olagiIiEturV68wdOhQjB07Fjk5Oejbty8iIyNRr149sUMjIjVQuQvMxcUF33//PSIiIuR7cJ07dw6nT5/G5MmTsWLFCnldVfYGIyLSFnfv3oWvry/+/vtvSKVS/Pjjj/D39+eqzkQ6ROWVoJ2dnZU7sUSCu3fvligosXElaCL9du7cObRp0wZWVlbYsWMHvL29xQ6JSCdo00rQKrcAxcbGljgwIqKyoEWLFggODoa7uzuqV68udjhEpAElWgeIiEiXJCUloV+/fvj777/lZb6+vkx+iHSYyi1AgiDgjz/+QHh4OJ4+fVpgB/hdu3apLTgiIk27fPkyfH19cefOHVy9ehX//PMPDAzK/u+Gmu5qICrrVP4unzhxIgYPHozY2FiUL18elpaWCi8iorJi27ZtaNGiBe7cuQNHR0ds2bJFJ5IfIno3lVuAtmzZgl27dqFLly6aiIeISONycnIwZcoU+azVjh07Ytu2bahUqZLIkRFRaVE5AbK0tETNmjU1EQsRkcYlJSWhe/fuOHnyJADgq6++wty5cyGVSkWOjIhKk8ptvd988w3mzp2LjIwMTcRDRKRRFSpUgJmZGSwsLLBnzx7MmzePyQ+RHlK5Bahfv37Yvn07qlatCicnJxgZGSl8HhMTo7bgiIjUQRAE5OXlwdDQEFKpFNu2bcPz589Rt25dsUMjIpGonAANHToUFy5cwKBBg2BjY8OVUYlIq7169QqjR4+Gubk5fvrpJwBApUqVON6HSM+pnAAdOHAAf/31F1q3bq2JeIiI1ObOnTvw9fXF5cuXIZVKMX78eDRs2FDssIhIC6g8BsjBwYHbQxCR1jtw4ACaNWuGy5cvo2rVqggLC2PyQ0RyKidAixcvxrRp03Dv3j0NhENE9H5kMhm++eYbfPLJJ0hKSkKLFi0QExMDLy8vsUMjIi2ichfYoEGD8OrVK9SqVQvlypUrMAj6xYsXaguOiEhVQ4YMwdatWwEAX3zxBZYuXQpjY2ORoyIibaNyArRs2TINhEFEpB4DBw7E7t27sXbtWgwZMkTscIhIS5VoFhgRkTaJj4+Hra0tAKBz5864d+8eqlSpInJURPS2PJmAx09f4FVGFiLLl0PLWpUgNRBnNrnKCRAA5OXlYc+ePbh+/ToAoGHDhujevTsXEyOiUpWdnY3Jkydj69atuHDhApydnQGAyQ+RFgq9Eodv9l1DfEomACDsHGBnaYqAbi7o1Miu1ONReRD0v//+iwYNGmDIkCHYtWsXdu3ahUGDBqFhw4a4c+eOJmIkIirgyZMn8Pb2xqpVq/Dy5UscOXJE7JCIqAihV+Iw5rcYefKTLz45E2N+i0HolbhSj0nlBGj8+PGoVasWHj58iJiYGMTExODBgwdwdnbG+PHjNREjEZGCkydPws3NDWfOnIGlpSX27duH0aNHix0WERUiTyZg7p/XIBTyWX7Z3D+vIU9WWA3NUbkL7Pjx4zh37hysra3lZZUqVcIPP/yAVq1aqTU4IqI3CYKAFStWYMqUKcjNzUWjRo2we/du1K5dW+zQiKgIUbEvEJecWeTnAoC45ExExb6AZ63SW6Fd5RYgExMTpKamFihPS0vjVFMi0qiNGzdi4sSJyM3NhZ+fH86dO8fkh0jLPU0tOvkpST11UTkB+uSTTzB69GhERkZCEAQIgoBz587h888/R/fu3TURIxERgNdT3Fu2bInly5dj69atMDc3FzskInqHqhVM1VpPXVTuAluxYgWGDh0KT09P+SKIubm56N69O5YvX672AIlIv50+fRotWrSAVCqFqakpTpw4wRmnRGWIu7M17CxNEZ+cWeg4IAkAW0tTuDtbF/Kp5qjcAmRlZYW9e/fi1q1b+OOPP/DHH3/g5s2b2L17NywtLTURIxHpoby8PMyZMwetW7dGQECAvJzJD1HZIjWQIKCbC4DXyc6b8t8HdHMp9fWASrQOEADUrl2bfe9EpBEvXrzAwIEDERoaCgBITU2FIAiQSMRZMI2I3k+nRnZYO6ipwjpAwOuWH7HWAVI5Aerduzfc3d0xffp0hfIFCxbg/Pnz2Llzp9qCIyL9c/HiRfTu3RuxsbEwMzPDunXrMGjQILHDIqL31KmRHbzq2WDasUS8ysjCsIbirgStchfYiRMn0KVLlwLlnTt3xokTJ9QSFBHpp19//RUtW7ZEbGwsatasibNnzzL5IdIhUgMJqlW1Rh1HO3jUFC/5AUqQABU13d3IyAgpKSlqCYqI9M/jx4/x+eefIzMzE126dEF0dDSaNGkidlhEpKNUToAaN26MHTt2FCgPDg6Gi4uLWoIiIv1TrVo1/PTTTwgICMCff/6JihUrih0SEekwlccAzZ49G76+vrhz5w7atWsHAAgLC8P27ds5/oeIVHL8+HGYmZnB3d0dADB48GCRIyIifaFyAtStWzfs2bMH8+fPxx9//AEzMzN88MEHOHr0KLy8vDQRIxHpGEEQsHTpUkybNg22traIiYlB1apVxQ5L7bLzBCy5nAsA8P/AEMbSsj+LTRfvifRTiabBd+3aFV27dlV3LESkB9LS0jBy5Eh5V3rbtm1Rvnx5kaMiIn1T4nWAiIhUdevWLfj6+uLq1aswNDTEkiVLMHbsWK7vQ0SljgkQEZWKvXv3YsiQIUhJSYGdnR127tyJVq1aiR0WEekpJkBEpHGCIOCXX35BSkoKWrdujd9//x12dkWv/MpxJkSkaUyAiEjjJBIJNm3ahKZNm2L69OnyjZSJiMSi8jpARETKiImJwdSpUyEIr/d/trS0xNdff83kh4i0glItQP7+/kqfcMmSJSUOhoh0w6ZNmzBmzBhkZWWhfv36GDFihNghaQy764jKJqUSoIsXLyq8j4mJQW5uLurVqwfg9cwOqVQKNzc39UdIRGVGVlYWJkyYgJ9++gkA8Mknn6B3794iR0VEVJBSCVB4eLj870uWLEGFChXwyy+/yJeqf/nyJYYPH46PPvpIM1ESkdZ79OgR+vTpg8jISEgkEsydOxdfffUVDAzY005E2kflQdCLFy/G4cOHFfbpqVixIubNm4eOHTti8uTJag2QiLTf8ePH0bdvXyQmJqJixYrYunUrOnfuLHZYxWLXFZF+UzkBSklJQWJiYoHyxMREpKamqiUoIipbBEHAixcv4OrqipCQENSsWVPskIiIiqVy23SvXr0wfPhw7Nq1C48ePcKjR48QEhKCESNGwNfXVxMxEpEWyp/dBbzezmL//v04ffo0kx8iKhNUToCCgoLQuXNnfPrpp3B0dISjoyM+/fRTdOrUCWvWrNFEjESkZW7evAlPT09cv35dXtapUyeUK1dOxKiIiJSncgJUrlw5rFmzBs+fP8fFixdx8eJFvHjxAmvWrIG5ubkmYiQiLbJ79240b94ckZGRGDdunNjhEBGVSImnZ8TFxSEuLg516tSBubm5QnM4EemevLw8zJo1C76+vkhNTUWbNm3w22+/iR0WEVGJqJwAPX/+HB9//DHq1q2LLl26IC4uDgAwYsQIzgAj0lHPnj1D586dERgYCACYNGkSjh49CltbW5Ejo6LkyQQ8fvoCt+/HIfLuc+TJ+Esq0ZtUToAmTZoEIyMjPHjwQKG/v3///ggNDS1REKtXr4aTkxNMTU3h4eGBqKioYuvv3LkT9evXh6mpKRo3boyDBw8WWffzzz+HRCLBsmXLShQbkb6LjY2Fm5sbjhw5gnLlymH79u1YsmQJt7TQYqFX4uC9MBx/hkcj7Nw/GLwhEq1/PIbQK3Fih0akNVROgA4fPowff/wR1atXVyivU6cO7t+/r3IAO3bsgL+/PwICAhATE4MmTZrAx8cHT58+LbT+mTNn4OfnhxEjRuDixYvo2bMnevbsiStXrhSou3v3bpw7dw729vYqx0VEr1WvXh1OTk6oU6cOIiMjMWDAALFDomKEXonDmN9iEJ+SqVAen5yJMb/FMAki+h+VE6D09PRCZ3q8ePECJiYmKgewZMkSjBo1CsOHD4eLiwuCgoJQrlw5bNy4sdD6y5cvR6dOnTB16lQ0aNAA3333HZo2bYpVq1Yp1Hv8+DHGjRuHrVu38jdVIhVlZWUhJycHAGBkZISdO3fi/PnzaNSokciRUXHyZALm/nkNhXV25ZfN/fMau8OIUIIE6KOPPsKvv/4qfy+RSCCTybBgwQJ4e3urdK7s7GxcuHAB7du3/y8gAwO0b98eZ8+eLfSYs2fPKtQHAB8fH4X6MpkMgwcPxtSpU9GwYcN3xpGVlYWUlBSFF5G+evjwIT766CNMmzZNXla1alVYWlqKGBUpIyr2BeKSM4v8XAAQl5yJqNgXpRcUkZZSeSXoBQsW4OOPP0Z0dDSys7Mxbdo0XL16FS9evMDp06dVOtezZ8+Ql5cHGxsbhXIbGxvcuHGj0GPi4+MLrR8fHy9//+OPP8LQ0BDjx49XKo7AwEDMnTtXpdiJdNGxY8fQv39/PHv2DHfu3MGMGTMKfL+R9nqaWnTyU5J6RLpM5RagRo0a4datW2jdujV69OiB9PR0+Pr64uLFi6hVq5YmYlTJhQsXsHz5cmzevBkSiXJ7+8ycORPJycny18OHDzUcJZF2EQQBCxYsQIcOHfDs2TN8+OGHiI6OZvJTxlStYKrWekS6TOUWoAcPHsDBwQFfffVVoZ/VqFFD6XNVrlwZUqkUCQkJCuUJCQlFTq+1tbUttv7Jkyfx9OlThTjy8vIwefJkLFu2DPfu3StwThMTkxKNXyLSBSkpKfLtbQBg2LBhWLNmDczMzESOjFTl7mwNO0tTxCdnFjoOSALA1tIU7s7WpR0akdZRuQXI2dm50M1Qnz9/DmdnZ5XOZWxsDDc3N4SFhcnLZDIZwsLC4OnpWegxnp6eCvUB4MiRI/L6gwcPxuXLl3Hp0iX5y97eHlOnTsVff/2lUnxEuk4QBHTo0AG7du2CkZER1q5di40bNzL5KaOkBhIEdHMB8DrZeVP++4BuLpAaKNc6TqTLVG4BEgSh0K6ltLQ0mJqq3qzq7++PoUOHolmzZnB3d8eyZcuQnp6O4cOHAwCGDBmCatWqyRdgmzBhAry8vLB48WJ07doVwcHBiI6Oxrp16wAAlSpVQqVKlRSuYWRkBFtbW9SrV0/l+Ih0mUQiwfTp0zFhwgTs3LkTLVq0EDskek+dGtlh7aCm+GbfNYWp8LaWpgjo5oJOjexEjI5IeyidAPn7+wN4/R/m7NmzFabC5+XlITIyEq6urioH0L9/fyQmJmLOnDmIj4+Hq6srQkND5WMPHjx4AAOD/xqqWrZsiW3btuHrr7/GrFmzUKdOHezZs4fTc4mUlJubi7t376Ju3boAAF9fX25kqmM6NbKDVz0bTDuWiFcZWRjWsBxa1qrElh+iNyidAF28eBHA6xagf/75B8bGxvLPjI2N0aRJE0yZMqVEQYwdOxZjx44t9LOIiIgCZX379kXfvn2VPn9h436I9FFiYiIGDBiAf/75BzExMfIFTdWR/GTnCVhyORcA4P+BIYyl2vfD9s0YxzWSihyNZkkNJKhW9fVYH4+ahkx+iN6idAIUHh4OABg+fDiWL18OCwsLjQVFROoXFRWF3r1749GjRzA3N8e1a9cKrOhORKQvVB4EvWnTJiY/RGXM+vXr8dFHH+HRo0eoW7cuIiMj0bFjR7HDIiISjcqDoNPT0/HDDz8gLCwMT58+hUwmU/j87t27aguOiN5PZmYmxo4diw0bNgAAevbsic2bN3NVZyLSeyonQCNHjsTx48cxePBg2NnZKb3YIBGVvsDAQGzYsAEGBgb4/vvvMX36dNG+Z8vCGCEi0h8qJ0CHDh3CgQMH0KpVK03EQ0RqNG3aNJw6dQozZ84ssIceaV6eTMDjpy/wKiMLkeV1YyaWLt4T6SeVE6CKFSvC2pqriBJpI0EQEBISAl9fXxgYGMDc3BxHjx5lS60IQq/EKazFE3YOsCvja/Ho4j2R/lJ5EPR3332HOXPm4NWrV5qIh4hKKCUlBb1790bfvn3xww8/yMuZ/JS+0CtxGPNbjMJChAAQn5yJMb/FIPRKnEiRlZwu3hPpN6VagD788EOF/0T//fdf2NjYwMnJCUZGRgp1Y2Ji1BshEb3TtWvX4Ovri5s3b8LY2BhVqlQROyS9lScTMPfPa4XuxSXg9ZYUc/+8hg4utmWm60gX74lIqQSoZ8+eGg6DiEpq586dGD58ONLT01G9enWEhITA3d1d7LDeS1keZxIV+wJxyZlFfi4AiEvORFTsC3jWqlRkPW2ii/dEpFQCFBAQoOk4iEhFubm5mDlzJhYtWgQAaNeuHYKDg8t8609ZH2fyNLXoRKEk9bSBLt4TkcpjgIhIO1y/fh0rVqwA8Hq2119//aUTyU9ZH2dStYJym0IrW08b6OI9EZVoFlhhgyolEglMTU1Ru3ZtDBs2TL6bOxFpRuPGjREUFIQKFSqgT58+Yofz3srqOJO3u+s8nK1hZ2mK+OTMQu9Fgtc7s7s7l53ZtO46eE9EKidAc+bMwffff4/OnTvLxxlERUUhNDQUX375JWJjYzFmzBjk5uZi1KhRag+YSF8JgoB169bBw8MDrq6uAKBTv2iUxXEmRXXXdW9ih3UnYiEBFBKG/LQtoJuLViVx7yI1kCCgmwvG/BajM/dEpHICdOrUKcybNw+ff/65QvlPP/2Ew4cPIyQkBB988AFWrFjBBIhEpyurD2dkZOCLL77A5s2b4ezsjIsXL+rcdhZlbZxJfnfd2y0i8cmZWHciFqPbOGPvpTiF7jzbMjSW6W2dGtlh7aCmCgkfULbviUqfsVSCGR8avbtiKVA5Afrrr7/w448/Fij/+OOPMXnyZABAly5dMGPGjPePjohw79499O7dGzExMTAwMMBnn32mkxsSl/Y4k/eZaaZMd92+v+NwdHJbzIx4hlcZWRjWsGzNZitMp0Z28Kpng2nHEnXmnkh/qZwAWVtb488//8SkSZMUyv/880/5CtHp6emoUKGCeiIk0mOHDx+Gn58fXrx4gcqVKyM4OBgff/yx2GFpRGmOM7n7KAEdDt1EQglnminbXXfxwUtUq/o6Xo+ahjqRKEgNJDp3T6SfVE6AZs+ejTFjxiA8PFw+Buj8+fM4ePAggoKCAABHjhyBl5eXeiMlek85Mu3oDlOmW04mkyEwMBCzZ8+GIAho1qwZQkJCUKNGjfc+t7YqrXEmdx8l4PDpvwuU5880Wzuo6TuTIGW74RJTs/4Lnoi0isrT4EeNGoXjx4/D3Nwcu3btwq5du1CuXDkcP34cI0aMAABMnjwZO3bsUHuwRPpCEAScPHkSgiBg5MiROHny5DuTH12QP87ExkKxm8vW0lSpxORd8mQCTsfcKPSz/IRr7p/XkCcrrA3qP8p2w1WpYKJKeERUilRuAQKAVq1acTd4Ig2SSqXYtm0bDh48iEGDBokdTqnS5DiT6HsvkJ6RVeTnys40U7a7rpmTNU5fyXvvuIlI/ZRqAUpJSVH4e3EvIiqZHTt2YOLEifL31tbWepf85MsfZ1LH0Q4eNdU3yDYxtejk503v6uLK764DCvZwcVo4UdmgVAtQxYoVERcXh6pVq8LKyqrQhRAFQYBEIkFeHn/bIVJFTk4Opk+fjqVLlwJ4PaOyW7duIkelm5TtklKmi0uZaeHZecV3pRGReJRKgI4dOyaf4RUeHq7RgIj0SUJCAgZ/OgDHjx8HAMyYMQNdunQROSrd1czJGuZmJkV2g6k604zTwonKLqUSoDdndHF2F5F63P/7HFp8NQBPnjxBhQoV8Msvv6BXr15ih6XTpAYStGpaH4dP/622mWacFk5UNpVoM9STJ09i0KBBaNmyJR4/fgwA2LJlC06dOqXW4Ii0RXaegB8u5uCHizlq6daI3vsL1o/6GE+ePEGDBg0QFRXF5KeU1Kxug46tmqCqhmaaEVHZoHICFBISAh8fH5iZmSEmJgZZWa+bkpOTkzF//ny1B0ikiypUtoUsLxe+vfsgMjIS9evXFzuk95a/svLt+3GIvPv8nVPJxVSzug2OTG6Lbt7N8HGLxtgywgOnprdj8kOkR1SeBj9v3jwEBQVhyJAhCA4Olpe3atUK8+bNU2twRLokNzcXhoavv+XqtfLBZxuPY9mgVjAxLFFDrFYpalNQbd4jil1XRPpN5f95b968iTZt2hQot7S0RFJSkjpiItJqOTLVu8NCQ0NRr1493LlzR17m2KRFoTMqy5r8TUHfnAkF/LeycuiVOJEiIyIqmsoJkK2tLf79998C5adOnULNmjXVEhSRrpDJZPjuu+/QpUsX3L17F99//73YIanVuzYFBZRbWZmIqLSVaCuMCRMmIDIyEhKJBE+ePMHWrVsxZcoUjBkzRhMxEpVJSUlJ6NmzJ+bMmQNBEPDZZ59h7dq1YoelVspuChoV+6L0girGm+OUomKfQ8bEjEhvqTwGaMaMGZDJZPj444/x6tUrtGnTBiYmJpgyZQrGjRuniRiJypwrV66gV69e+Pfff2FiYoK1a9di+PDhAKBTi+MpuymosvU0qbBxSuZmJmjVtD7wQTWRoyOi0qZ0AhQbGwtnZ2dIJBJ89dVXmDp1Kv7991+kpaXBxcUF5cuX12ScRGVGZGQk2rVrh1evXsHR0REhISFwc3MTOyyNUHZTUGXraUr+OKW3U8/0jCwcPv03/nKUotsH2jlYm4g0Q+kEqFatWnB0dIS3tzfatWsHb29vuLi4aDI2ojLJ1dUVDRs2hJWVFbZt24bKlSuLHZLGKLspqLuzNbLzXnc/vcrIQmT50lsxubhxSvnmH7iGLo1sOROMSI8onQAdO3YMERERiIiIwPbt25GdnY2aNWvKkyFvb2/Y2NhoMlYirZWYmAhra2tIpVKYmJjg0KFDsLKyglQqFTs0jcrfFHTMbzHFrqx85Fq8aNPk3zVOCVBuB3gi0i1KD4Ju27YtvvnmG0RERODly5c4cuQI/Pz8cP36dQwbNgz29vZo2LChJmMl0kpnzpxBkyZNMGfOHHlZpUqVylTy8z4rXedvCmpTxMrKAESdJl+Wximpk7FUghkfGmHGh0YwlrJli+htKg+CBgBTU1O0a9cOrVu3hre3Nw4dOoSffvoJN27cUHd8RFpLEASsWb0KUyf7Izc3F/v27cPXX38NMzMzsUMrdUVtCgoArX88VuQ0eQleT5Pv4KK57qeyMk6JiEqXSglQdnY2zp07h/DwcERERCAyMhIODg5o06YNVq1axY1SSW9kZ7zC7u+/wKWD2wAA/fr1w4YNG/Qy+clX2MrKZ+88V3qavKa6n941Tgl43R2n7A7wRKQblE6A2rVrh8jISDg7O8PLywufffYZtm3bBjs7zpwg/RJ79y6ChvdG3K3LkEqlWLBgASZNmqQTqzqrmzZ0PxU3TinfrK6q7QBPRGWf0mOATp48iUqVKqFdu3b4+OOP0aFDByY/pHdysjLh83FbxN26jPLWVXHoryPw9/dn8lMEbel+KmqckrmZCTq2agKfhrYavT4RaR+lW4CSkpJw8uRJRERE4Mcff4Sfnx/q1q0LLy8vtG3bFl5eXqhSpYomYyVSWf7Kv68yshBlbgaZzBIG7/GbvpGJKb6dNx9zF6/GwIXB8GrrpL5gdZAq0+Q17e1xSoNczHA29f2+Hoio7FI6ATI3N0enTp3QqVMnAEBqaipOnTqF8PBwLFiwAAMHDkSdOnVw5coVjQVLpAp1rfz78uVLxN5/CKABAGDAwEFIaNQPBmVolpdYlJ0mX1rdT2+OU3J3liLySl6pXJeItI/Ke4HlMzc3h7W1NaytrVGxYkUYGhri+vXr6oyNyhBVplG/z5RrZRW1Q7l85d+r8Uqd5/Lly2jWrBm6de2M1OcJ8nImP8p71zR5Ta8DRERUGKVbgGQyGaKjoxEREYHw8HCcPn0a6enpqFatGry9vbF69Wp4e3trMlYipSiz8m/A3ivwcbGBsWHRvwNs3boVo0aNQkZGBhwdHfEq6RkqVHr/xT7f7JZT94rImjz3+yhqmrw2xEZE+knpBMjKygrp6emwtbWFt7c3li5dirZt26JWrVqajI9IZcqs/PsiPRstAo9ifq/GBVogsrOzMWXKFKxcuRIA4OPjg02//oZfHlu+d2yFdcupa0VkTZ5bHQqbJk9EJBalu8AWLlyI69ev4/Hjx/jtt98wYsQIJj9UKlTtMlN2SvWL9JwCKxHHxcWhXbt28uTn66+/xoEDB1Cp0vuvUVNUt5w6VkTW5LmJiHSR0gnQZ599hrp162oyFiK1UHVK9dw/ryFP9jqxCggIwOnTp2FhYYG9e/fiu+++U8uWFsV1y+WXvRmHtpybiEhXlXgQNJG2yp96rUwHy5srEQPAokWL4Ovri+joaHTv3l1eL39sze37cYiKfQ6ZisnEu7rl3o5DW85NRKSrSrQXGOmn7DwBSy7nAgD8PzDU2g0W35x6/S6y7EykXz2GhJQmAAALCwuEhIQo1FHHdHpNroisDastU+HyNyTVJbp4T6Sf2AJEOil/6rW1uXGRdXJePkH8b1Pw4vAaRIT8UmgddU2n1+SKyNqy2jIRUVnCBIh0VqdGdjgxrR1MjQv+tvrq3yjE/TIJOYn3YFS+Inq0b12gjrLT6bNzZe+M5V3dchKUfENOTZ6biEhXMQEinWZsaIA2zV0AvE4EBEGGpFNbkRjyLYSsdJjY18fGPUfh3darwLGqTKd/1yyr/G65/Dje9L4rImvy3EREuooJEOm8mtVt0LFVE1gb5SDxj2+RfHo7AMCmRQ/s3B+KQR83LfS495lOXxhNroisa6st548zmfGhkdaONctXlmIlov9wEDTphZrVbdDbvCI6z78IqbEJpn+3GN9O+aLYVpGSTKfv4GJb7Dk1uSIyV1smIlIeEyDSG60/+gi95/wEu3ofIKBvs3cmBu/ayfxNb04196xV/KKJmlwRmastExEph11gJFcam5SWpuzsbEybMhlP7/63Sa9b9yGwr+eq1PFvjq1RFqealx1GBuy6ItJnTIBIJz158gTe3t5Yvmwptk7tj7ycnBKdR5np9G/iVHMiorKBCRDpnBMnTqBp06Y4c+YMLC0t0WlCIKRGJV+4rbjp9Pk41ZyIqGzRigRo9erVcHJygqmpKTw8PBAVFVVs/Z07d6J+/fowNTVF48aNcfDgQflnOTk5mD59Oho3bgxzc3PY29tjyJAhePLkiaZvg0QmCAKWLVuGdu3aISEhAY0bN8aZyPNo0Kbre5/77en0b+JUcyKiskf0BGjHjh3w9/dHQEAAYmJi0KRJE/j4+ODp06eF1j9z5gz8/PwwYsQIXLx4ET179kTPnj1x5coVAMCrV68QExOD2bNnIyYmBrt27cLNmzcV9nUi3fPq1St8+umnmDRpEvLy8vDpp5/i7NmzqF27ttqukT+dvqqOTDUnItJnos8CW7JkCUaNGoXhw4cDAIKCgnDgwAFs3LgRM2bMKFB/+fLl6NSpE6ZOnQoA+O6773DkyBGsWrUKQUFBsLS0xJEjRxSOWbVqFdzd3fHgwQPUqFFD8zelh/I3C32VkYXI8sVPv1alrrKMjIzw5MkTGBoaYvHixRg3bhwkEonaB3PXrG6DRR3t8FXEM041JyIqw0RNgLKzs3HhwgXMnDlTXmZgYID27dvj7NmzhR5z9uxZ+Pv7K5T5+Phgz549RV4nOTkZEokEVlZWhX6elZWFrKws+fuUlBTlb4IK3SzUztIUAd1cCrSKqFJXGYIgQCKRwMjICL///jtu376N1q0LbmuhTpxqTkRU9onaBfbs2TPk5eXBxsZGodzGxgbx8YVvMhkfH69S/czMTEyfPh1+fn6wsLAotE5gYCAsLS3lLwcHhxLcjX4qarPQ+OTMAqsjq1L3XfLy8jB79myFZNjGxkbjyQ8REekG0ccAaVJOTg769esHQRCwdu3aIuvNnDkTycnJ8tfDhw9LMcqyq7jNQvPL5v55DXkyQaW6hV3n8dMXuH0/DpF3nyPx2XN07doV8+bNw7Jly3D+/Hk13ZH+evsZF/bvQESkS0TtAqtcuTKkUikSEhIUyhMSEmBra1voMba2tkrVz09+7t+/j2PHjhXZ+gMAJiYmMDExKeFd6K93bRb65urI+N/flan75krKb3eZHdp7By/2BiLrZTzMzMywbt06NG/eXC33o6/U3S1JRFQWiNoCZGxsDDc3N4SFhcnLZDIZwsLC4OnpWegxnp6eCvUB4MiRIwr185Of27dv4+jRo6hUqfitCfTN2ys+579fcjlXpfMou+rx09RMlerme7vLLO2fMMT/NhVZL+NhaGWLRVv2YdCgQSrFTIrU2S3JTUGJqCwRfRaYv78/hg4dimbNmsHd3R3Lli1Denq6fFbYkCFDUK1aNQQGBgIAJkyYAC8vLyxevBhdu3ZFcHAwoqOjsW7dOgCvk58+ffogJiYG+/fvR15ennx8kLW1NYyNlVvRl95N2VWPVVkdOb/u211mLyM2ISUyBABgVqs5Kn8yGVtuSfCZTOAg5BJ6V7ekBMpt8EpEVBaJngD1798fiYmJmDNnDuLj4+Hq6orQ0FD5QOcHDx7AwOC/hqqWLVti27Zt+PrrrzFr1izUqVMHe/bsQaNGjQAAjx8/xr59+wAArq6uCtcKDw9H27ZtS+W+dNHb09c93rFZqASv18jJXx1Zlbpvd6+Z2NcDJAawbOUHy5b9IZEYKL35KBVOlS5MPmMi0jWiJ0AAMHbsWIwdO7bQzyIiIgqU9e3bF3379i20vpOTEwSBAzjVrahxIt2b2GHdiVhIAIXEprDVkQO6uWDMbzFK1X2amglZdiYMjF+3CJWr2xL2I9fCyLqaQlzcfLTkStItWdbld9MREen0LDBSj+LGiaw7EYvRbZxho8TqyPkbi76rriAICPt9I56sH43clER5vbeTH4Cbj74PTXRhEhGVFVrRAkTaS5lxIvv+jsPRyW0xU4nVkTs1soNXPRtMO5ZYaN20tDSMHDkSO3bsAACkXzkGy5b9C5zn7S4zUp27il2YRES6hAkQFUvZcSIXH7xUenXkolZSvnXrFnx9fXH16lUYGhpi1NRvcDCviVJdZqQ6qYFEpW5JIiJdwi4wHfX2VPeSUnb8R2Jq1rsrFWPv3r1o3rw5rl69Cjs7O0RERGDN/K8QNNhNqe41KhlluyXVgdPkiUibsAWIiqXs+I8qFUxwK61k1wgJCUGfPn0AAB999BF+//13+cKW7+oyo/fHZ0xE+ogJEMnJZALinr1U2KVd2XEizZyscfpKXomu27lzZzRp0gRt27bFwoULYWSkOEuHm49qHp8xEekbJkBlWHaeoLB6s/8HhiXuWrj7KAGnY24gPeN1V9ab2yFoYpxI4r2bqFSjDgCgXLlyOH36NMzNzUsUe3HenvY840P2+hIREccAEYC/rsbj8Om/5clPvvztEACodZzI5k0bsWJAM0Rs/EFeponkh4iIqChsAdJzeTIB3++/Vuhnb26HcGp6u/ceJ5KVlYXx48fLty15fO0CZDIZIJWq4U6IiIiUxwRIz0Xfe1FggcM3vbkdgpuTdYnHiTx8+BB9+vRBVFQUJBIJPv58DrxHzFTY5oSIiKi0MAEqA94c66PsOJ8cmaDw96KOUXb6+vtshxAeHi7f861ixYrY/OtvuFatQ4nPV9ZpcjsGbvVARKQcJkB66M1NTa2tc999AEq+HUJiYiI++eQTvHr1Cq6urggJCUF1R2dcu6zcdYmIiDSBCZCeKbCp6Tvqv7kdQknWU6xSpQqWLVuGU6dOYe3atShXrtx7LcxIRESkDkyAdEiO7L+uss9d/htbs/JKHoA8NJQ+w/htMYWu51Oc/GnueUomLjdv3oSQm40PPvgAADBq1CiMHDkSEknZXVuG0+mJiHQL/xfXE7L/zfZSJfkxkACrP/1QpWnuV4/tQasW7ujRoweeP38uLy/LyQ8REekeJkB6Iu7Zy2JnexVGJgAVzU2Uqpubm4vQlV/htyn9kJqaiho1aiAvr2QrQxMREWkau8C0xNszvXJkwv+6rhS9WedthdXP9yqjZJuVKjP7KzExEf0H+OH4sdcjiiZMnISFC34ssKUFERGRtmACpCfKmSnXkvO2d83+On/+PHr37o2HDx/C2Mwcvef8hAVTP4URd/smIiItxgSoDHtzOns5MxPYVa4Ig/8tTvj2ZzaVrGBrYYqElMI3NX3bm7O/ijN//nw8fPgQtevUwSfzf4dNrYbvf2NEREQaxgSojPrrajy+339NYVyPuZkJWjWtDwDocugGElKyFD4b0MweG0/GFtjUtCjKbHK6YcMG2NnZYe68+dhwn/t5ERFR2cAESAu8vat7UeN/8t19lICfTv9dIIlJz8jC4dN/F3pMekYWNp6Mxeg2zth7KU4hcTKQvB7wnM/czAQ/9GpY6OyvpLgHuBQajElLZgKQwNraGmvWrAEAzCi+sUiOqxUTEZHYmACVMTKZgNMxN1Reyyffvr/jcHRyW8yMeCbf1PTDGhXl7/O70nwaFkxQjoWFYdVAP6QnPcPmxjb4bNTI97sZIiIikTABKmPinr1EeglndOVvbHrxwUuFTU0ByN8XepwgYMGCBZg1axZkMhns67vCu93HJYqBiIhIGzABEtHbXV/5XuXKijympNPZ35SYmvV6lPM7ZOcJmH/mBf74ZiSuHtsDAHDrPhQ9ZqyAk1OF945DWewyIyIidWMCVMaUdDr7m6pUMMGttHfXu379OtYM8UXivZswMjLC0uUrkOLxf1zVmYiIyjyuBF0GyP43pf32/TgIggBT45K3hthamKCZk3KjlR89fIhn92/Bomo1HIs4gVGjP2PyQ0REOoEtQCJIz5EVO8vrTXcfJeB0zA2FcT+G0pLnrZm5Mhy9ngCg8jvrdujYEf3mbUZtj4/h7mHPrigdxn9bItI3bAHSYncfJeDw6b8LDHrOzSt6jNC7JL3KwfhtMbj7KKHAZ2kvE/HblH54/vCOvMy1sx/KW1ct8fWIiIi0EVuAtIRMJiDu2Uu8yshClLEJ7j3JQ9i5yxq73umYG3Cy/y+xeXjlPLZO7Y/khEdIe56AeV1OsbuLiIh0FhMgLfB2N1fYOc1eT8DrhRHjnr2EIFTBhp/X46fx45GXk43KjnXQa/ZaJj9ERKTTmACVssSMXGy48d8yhvndXGJISU7G56NnYvOmTQCAht49EBHyCypXtATweho8ERGRLmICJKL8VZ3FkJf+Eoe+7ovE25dhYGCADl9+C69hU2Fh8d9A2Dc3VI0sXw4ta1V6595gREREZQETIBG9z6rO70MCoLyVNSQmpqhUqRK2bN2Ov6u2VagTeiUO3+z7b7PVsHOAnaUpArq5FLpHGBERUVnCWWClKD1HptD9de/x01K9viAIEGSvp99/5P4BBi4MxtmoaHzcvr1CvdArcRjzW4zChqkAEJ+ciTG/xSD0SlypxUxERKQJTIBEIpMJuBX7pPSul/UKibu/R27Udqz4tClqVreBpU11ODo6KtTLkwmY++e1QjdbzS+b++c15Mk4PoiIiMouJkAiyM7Nw6FTMcjKKbgPmLoZGxmiQSUDJP8+Axm3z+H5ud1oUCG7yPrR914gLjmzyM/zN1SNin2hgWiJiIhKB8cAlbJDpy7i/uNEjV9HgtfJSo3sWBwLmILsjHRUr14dISEhqO3siBlv1c9fBXjvJeXGJD1NLTpJIiIi0nZMgErR2K0X1J78NKnvCJtKVgW2y6hiboTMmBCE7VkHAKjV3BvH9wWjmm3xqzpXrWCq1HWVrUdERKSNmACVkozsPITfUO+gZwmAf+/Hw6NxXTjZV5WvJG1maoxby0fgSOhBAECboZPR8cvvUKXKu5MWd2dr2FmaIj45s9BxQBIAtpamcHdWbkNVIiIibcQxQKWk95rTaj/nmys6GxhIUK2qNeo42qG6TSX0HeAH43LlMXBhMDpPCITUULlcV2ogQUA3FwCvk5035b8P6ObC9YCIiKhMYwJUCgIPXsO1+FSNnf9VRhYEQUDq8/82OP30008xdd8NNPrYV+XzdWpkh7WDmsLGQrHFyNbSFGsHNeU6QEREVOaxC0zDsnNlWHciVqPXMDaQIeSbUbh97ijGbj2HCpVtAeC9dnHv1MgOXvVsMO1YIl5lZGFYQ64ETUREuoMJkIZtOXuv0LE06iABYCVLwr7pvnhy4yIkBga4e+E4mvj0V8v5pf/rVgMAj5qGTH6IiEhnMAHSsPsvXmnkvBIAGXcv4PnhZUhNfonKlSujx3e/obZHO/h/wH9WIiKi4vAnpYY5WpdT+zkFQQbZxd14enQzBEFA8+bNsW3HTvyRZK/2axEREekiJkAaNtjTCfMOXC9RN1g5U2O082iMjKxsmJkYAxIgIzMbNw5swJkjmwAAo0aNwooVK2BgZAIkaX5laSIiIl3ABEjDjA0NMLqNM35SYSB0/irOrd0aoLptJQDAuEZSrLzyeiPTBQsno330PowdOxYjRowAAGTnKaZYxlKJfHVnIiIiUsQEqBTM7PJ6XR1lkyAbS1N80Kgeala3kZedOX0KgkULSCQSVKhQAdHR0ZBKpRqJl4iISNdxHaBSMrOLCy4G+OBDF2e8PZnK2sIcPq2a4OMWjdHNuxkO+7eVJz95OTnYv3gqOnp74dTW5fJjmPwQERGVHFuASpGxoQE8GteBR+M6xdbLn26e+jwB26d/itiYkwCAjJSXGo+RiIhIHzAB0jLjGklhbmQAr8xI9BnaB0+ePIGJeQVs2rQJ92t3L/I4TYz54TgiIiLSVewC0zKCIGDNmjXw8vLCkydPUNW5Pr749TS69+wldmhEREQ6gy1AWubWzZuYMGECcnNz0btPXzSe+BNMypUXOywiIiKdwgSoFBm9MfrZ/wNDGEsL21rCBUuXLkVWVhb8/f0hkfxXZ8aHbLAjIiJSByZAWiA0NBQODg5o2LAhAGDs2LEiR0RERKTb2KQgIplMhm+//RZdunSBr68vkpOTxQ6JiIhIL2hFArR69Wo4OTnB1NQUHh4eiIqKKrb+zp07Ub9+fZiamqJx48Y4ePCgwueCIGDOnDmws7ODmZkZ2rdvj9u3b2vyFlSWlJSEHj16ICAgAIIgwNvbG6ampmKHRUREpBdET4B27NgBf39/BAQEICYmBk2aNIGPjw+ePn1aaP0zZ87Az88PI0aMwMWLF9GzZ0/07NkTV65ckddZsGABVqxYgaCgIERGRsLc3Bw+Pj7IzMwsrdsqVP608i7S62jp0Rz79++HiYkJNm7ciKCgIJiYmIgaHxERkb6QCIJQkn061cbDwwPNmzfHqlWrALzuFnJwcMC4ceMwY8aMAvX79++P9PR07N+/X17WokULuLq6IigoCIIgwN7eHpMnT8aUKVMAAMnJybCxscHmzZsxYMCAd8aUkpICS0tLJCcnw8LCQk13+tq2bdswcuRIZGRkwNHRESEhIXBzc1PrNYiIiPSRKj+/RW0Bys7OxoULF9C+fXt5mYGBAdq3b4+zZ88WeszZs2cV6gOAj4+PvH5sbCzi4+MV6lhaWsLDw6PIc2ZlZSElJUXhpQkymQzr169HRkYGOnTogAsXLjD5ISIiEoGoCdCzZ8+Ql5cHGxsbhXIbGxvEx8cXekx8fHyx9fP/VOWcgYGBsLS0lL8cHBxKdD/vYmBggB07dmD+/Pk4dOgQKlWqpJHrEBERUfFEHwOkDWbOnInk5GT56+HDhxq7VtWqVTFz5kxuZkpERCQiUROgypUrQyqVIiEhQaE8ISEBtra2hR5ja2tbbP38P1U5p4mJCSwsLBReREREpLtETYCMjY3h5uaGsLAweZlMJkNYWBg8PT0LPcbT01OhPgAcOXJEXt/Z2Rm2trYKdVJSUhAZGVnkOYmIiEi/iL4StL+/P4YOHYpmzZrB3d0dy5YtQ3p6OoYPHw4AGDJkCKpVq4bAwEAAwIQJE+Dl5YXFixeja9euCA4ORnR0NNatWwcAkEgkmDhxIubNm4c6derA2dkZs2fPhr29PXr27CnWbRIREZEWET0B6t+/PxITEzFnzhzEx8fD1dUVoaGh8kHMDx48gIHBfw1VLVu2xLZt2/D1119j1qxZqFOnDvbs2YNGjRrJ60ybNg3p6ekYPXo0kpKS0Lp1a4SGhnKhQSIiIgKgBesAaSNNrgNEREREmlFm1gEiIiIiEgMTICIiItI7TICIiIhI7zABIiIiIr3DBIiIiIj0DhMgIiIi0jtMgIiIiEjvMAEiIiIivcMEiIiIiPSO6FthaKP8xbFTUlJEjoSIiIiUlf9zW5lNLpgAFSI1NRUA4ODgIHIkREREpKrU1FRYWloWW4d7gRVCJpPhyZMnqFChAiQSiVrPnZKSAgcHBzx8+JD7jKkJn6lm8LmqH5+pZvC5akZZfK6CICA1NRX29vYKG6kXhi1AhTAwMED16tU1eg0LC4sy8wVVVvCZagafq/rxmWoGn6tmlLXn+q6Wn3wcBE1ERER6hwkQERER6R0mQKXMxMQEAQEBMDExETsUncFnqhl8rurHZ6oZfK6aoevPlYOgiYiISO+wBYiIiIj0DhMgIiIi0jtMgIiIiEjvMAEiIiIivcME6D2tXr0aTk5OMDU1hYeHB6Kiooqtv3PnTtSvXx+mpqZo3LgxDh48qPC5IAiYM2cO7OzsYGZmhvbt2+P27duavAWtpM7nmpOTg+nTp6Nx48YwNzeHvb09hgwZgidPnmj6NrSKur9W3/T5559DIpFg2bJlao5a+2niuV6/fh3du3eHpaUlzM3N0bx5czx48EBTt6B11P1M09LSMHbsWFSvXh1mZmZwcXFBUFCQJm9BK6nyXK9evYrevXvDycmp2O9tVf+ttIpAJRYcHCwYGxsLGzduFK5evSqMGjVKsLKyEhISEgqtf/r0aUEqlQoLFiwQrl27Jnz99deCkZGR8M8//8jr/PDDD4KlpaWwZ88e4e+//xa6d+8uODs7CxkZGaV1W6JT93NNSkoS2rdvL+zYsUO4ceOGcPbsWcHd3V1wc3MrzdsSlSa+VvPt2rVLaNKkiWBvby8sXbpUw3eiXTTxXP/991/B2tpamDp1qhATEyP8+++/wt69e4s8p67RxDMdNWqUUKtWLSE8PFyIjY0VfvrpJ0EqlQp79+4trdsSnarPNSoqSpgyZYqwfft2wdbWttDvbVXPqW2YAL0Hd3d34csvv5S/z8vLE+zt7YXAwMBC6/fr10/o2rWrQpmHh4fw2WefCYIgCDKZTLC1tRUWLlwo/zwpKUkwMTERtm/froE70E7qfq6FiYqKEgAI9+/fV0/QWk5Tz/TRo0dCtWrVhCtXrgiOjo56lwBp4rn2799fGDRokGYCLgM08UwbNmwofPvttwp1mjZtKnz11VdqjFy7qfpc31TU9/b7nFMbsAushLKzs3HhwgW0b99eXmZgYID27dvj7NmzhR5z9uxZhfoA4OPjI68fGxuL+Ph4hTqWlpbw8PAo8py6RhPPtTDJycmQSCSwsrJSS9zaTFPPVCaTYfDgwZg6dSoaNmyomeC1mCaeq0wmw4EDB1C3bl34+PigatWq8PDwwJ49ezR2H9pEU1+rLVu2xL59+/D48WMIgoDw8HDcunULHTt21MyNaJmSPFcxzlnamACV0LNnz5CXlwcbGxuFchsbG8THxxd6THx8fLH18/9U5Zy6RhPP9W2ZmZmYPn06/Pz8ytQGfyWlqWf6448/wtDQEOPHj1d/0GWAJp7r06dPkZaWhh9++AGdOnXC4cOH0atXL/j6+uL48eOauREtoqmv1ZUrV8LFxQXVq1eHsbExOnXqhNWrV6NNmzbqvwktVJLnKsY5Sxt3gye9kpOTg379+kEQBKxdu1bscMqsCxcuYPny5YiJiYFEIhE7HJ0hk8kAAD169MCkSZMAAK6urjhz5gyCgoLg5eUlZnhl1sqVK3Hu3Dns27cPjo6OOHHiBL788kvY29sXaD0i/cEWoBKqXLkypFIpEhISFMoTEhJga2tb6DG2trbF1s//U5Vz6hpNPNd8+cnP/fv3ceTIEb1o/QE080xPnjyJp0+fokaNGjA0NIShoSHu37+PyZMnw8nJSSP3oW008VwrV64MQ0NDuLi4KNRp0KCBXswC08QzzcjIwKxZs7BkyRJ069YNH3zwAcaOHYv+/ftj0aJFmrkRLVOS5yrGOUsbE6ASMjY2hpubG8LCwuRlMpkMYWFh8PT0LPQYT09PhfoAcOTIEXl9Z2dn2NraKtRJSUlBZGRkkefUNZp4rsB/yc/t27dx9OhRVKpUSTM3oIU08UwHDx6My5cv49KlS/KXvb09pk6dir/++ktzN6NFNPFcjY2N0bx5c9y8eVOhzq1bt+Do6KjmO9A+mnimOTk5yMnJgYGB4o87qVQqb3HTdSV5rmKcs9SJPQq7LAsODhZMTEyEzZs3C9euXRNGjx4tWFlZCfHx8YIgCMLgwYOFGTNmyOufPn1aMDQ0FBYtWiRcv35dCAgIKHQavJWVlbB3717h8uXLQo8ePfRyGrw6n2t2drbQvXt3oXr16sKlS5eEuLg4+SsrK0uUeyxtmvhafZs+zgLTxHPdtWuXYGRkJKxbt064ffu2sHLlSkEqlQonT54s9fsTgyaeqZeXl9CwYUMhPDxcuHv3rrBp0ybB1NRUWLNmTanfn1hUfa5ZWVnCxYsXhYsXLwp2dnbClClThIsXLwq3b99W+pzajgnQe1q5cqVQo0YNwdjYWHB3dxfOnTsn/8zLy0sYOnSoQv3ff/9dqFu3rmBsbCw0bNhQOHDggMLnMplMmD17tmBjYyOYmJgIH3/8sXDz5s3SuBWtos7nGhsbKwAo9BUeHl5KdyQ+dX+tvk0fEyBB0Mxz3bBhg1C7dm3B1NRUaNKkibBnzx5N34ZWUfczjYuLE4YNGybY29sLpqamQr169YTFixcLMpmsNG5Ha6jyXIv6f9PLy0vpc2o7iSAIgkiNT0RERESi4BggIiIi0jtMgIiIiEjvMAEiIiIivcMEiIiIiPQOEyAiIiLSO0yAiIiISO8wASIiIiK9wwSIiIiI9A4TICJSSUREBCQSCZKSkpQ+5ptvvoGrq6vGYnpb27ZtMXHiRJWOKUmMN27cQIsWLWBqaqrW+ytJ/ESkGiZARDoqKCgIFSpUQG5urrwsLS0NRkZGaNu2rULd/KTmzp077zxvy5YtERcXB0tLS7XGWxZ/6AcEBMDc3Bw3b94ssCGnOjk5OWHZsmVK1w8MDIRUKsXChQsLfLZ582ZIJJICr59//lmNERNpPyZARDrK29sbaWlpiI6OlpedPHkStra2iIyMRGZmprw8PDwcNWrUQK1atd55XmNjY9ja2kIikWgk7rLkzp07aN26NRwdHVGpUiWxw5HbuHEjpk2bho0bNxb6uYWFBeLi4hReAwcOLOUoicTFBIhIR9WrVw92dnaIiIiQl0VERKBHjx5wdnbGuXPnFMq9vb0BADKZDIGBgXB2doaZmRmaNGmCP/74Q6Hu211g69evh4ODA8qVK4devXphyZIlsLKyKhDTli1b4OTkBEtLSwwYMACpqakAgGHDhuH48eNYvny5vEXi3r17AIArV66gc+fOKF++PGxsbDB48GA8e/ZMfs709HQMGTIE5cuXh52dHRYvXqzU8/nhhx9gY2ODChUqYMSIEQoJYb6ff/4ZDRo0gKmpKerXr481a9bIP5NIJLhw4QK+/fZbSCQSfPPNNwCA6dOno27duihXrhxq1qyJ2bNnIycnR37csGHD0LNnT4XrTJw4sUCrXL62bdvi/v37mDRpkvzZFOf48ePIyMjAt99+i5SUFJw5c6ZAHYlEAltbW4WXmZlZsecl0jVMgIh0mLe3N8LDw+Xvw8PD0bZtW3h5ecnLMzIyEBkZKU+AAgMD8euvvyIoKAhXr17FpEmTMGjQIBw/frzQa5w+fRqff/45JkyYgEuXLqFDhw74/vvvC9S7c+cO9uzZg/3792P//v04fvw4fvjhBwDA8uXL4enpiVGjRslbJBwcHJCUlIR27drhww8/RHR0NEJDQ5GQkIB+/frJzzt16lQcP34ce/fuxeHDhxEREYGYmJhin8vvv/+Ob775BvPnz0d0dDTs7OwUkhsA2Lp1K+bMmYPvv/8e169fx/z58zF79mz88ssvAIC4uDg0bNgQkydPRlxcHKZMmQIAqFChAjZv3oxr165h+fLlWL9+PZYuXVpsPMXZtWsXqlevjm+//Vb+bIqzYcMG+Pn5wcjICH5+ftiwYUOJr02k08Tejp6INGf9+vWCubm5kJOTI6SkpAiGhobC06dPhW3btglt2rQRBEEQwsLCBADC/fv3hczMTKFcuXLCmTNnFM4zYsQIwc/PTxAEQQgPDxcACC9fvhQEQRD69+8vdO3aVaH+wIEDBUtLS/n7gIAAoVy5ckJKSoq8bOrUqYKHh4f8vZeXlzBhwgSF83z33XdCx44dFcoePnwoABBu3rwppKamCsbGxsLvv/8u//z58+eCmZlZgXO9ydPTU/jiiy8Uyjw8PIQmTZrI39eqVUvYtm1bgXg8PT3l75s0aSIEBAQUeR1BEISFCxcKbm5u8vdDhw4VevTooVBnwoQJgpeXl/z928/C0dFRWLp0abHXEQRBSE5OFszMzIRLly4JgiAIFy9eFMqXLy+kpqbK62zatEkAIJibm8tfNjY27zw3ka4xFDf9IiJNatu2LdLT03H+/Hm8fPkSdevWRZUqVeDl5YXhw4cjMzMTERERqFmzJmrUqIGrV6/i1atX6NChg8J5srOz8eGHHxZ6jZs3b6JXr14KZe7u7ti/f79CmZOTEypUqCB/b2dnh6dPnxYb/99//43w8HCUL1++wGd37txBRkYGsrOz4eHhIS+3trZGvXr1ij3v9evX8fnnnyuUeXp6ylvF0tPTcefOHYwYMQKjRo2S18nNzX3n4O8dO3ZgxYoVuHPnDtLS0pCbmwsLC4tij1GX7du3o1atWmjSpAkAwNXVFY6OjtixYwdGjBghr1ehQgWFVjIDA3YGkP5hAkSkw2rXro3q1asjPDwcL1++hJeXFwDA3t4eDg4OOHPmDMLDw9GuXTsAr2eJAcCBAwdQrVo1hXOZmJi8VyxGRkYK7yUSCWQyWbHHpKWloVu3bvjxxx8LfGZnZ4d///33vWIq7rrA67FNbyZXACCVSos87uzZsxg4cCDmzp0LHx8fWFpaIjg4WGFckoGBAQRBUDjuzTFC72PDhg24evUqDA3/+69dJpNh48aNCgmQgYEBateurZZrEpVVTICIdJy3tzciIiLw8uVLTJ06VV7epk0bHDp0CFFRURgzZgwAwMXFBSYmJnjw4IE8WXqXevXq4fz58wplb79XhrGxMfLy8hTKmjZtipCQEDg5OSn8UM9Xq1YtGBkZITIyEjVq1AAAvHz5Erdu3So2/gYNGiAyMhJDhgyRl705KNzGxgb29va4e/euSrOjzpw5A0dHR3z11Vfysvv37yvUqVKlCq5cuaJQdunSpQIJ4psKezZv++effxAdHY2IiAhYW1vLy1+8eIG2bdvixo0bqF+/vtL3QqTrmAAR6Thvb298+eWXyMnJUUgKvLy8MHbsWGRnZ8sHQFeoUAFTpkzBpEmTIJPJ0Lp1ayQnJ+P06dOwsLDA0KFDC5x/3LhxaNOmDZYsWYJu3brh2LFjOHTokMrT5J2cnBAZGYl79+6hfPnysLa2xpdffon169fDz88P06ZNg7W1Nf79918EBwfj559/Rvny5TFixAhMnToVlSpVQtWqVfHVV1+9s0tnwoQJGDZsGJo1a4ZWrVph69atuHr1KmrWrCmvM3fuXIwfPx6Wlpbo1KkTsrKyEB0djZcvX8Lf37/Q89apUwcPHjxAcHAwmjdvjgMHDmD37t0Kddq1a4eFCxfi119/haenJ3777TdcuXKlyC7G/Gdz4sQJDBgwACYmJqhcuXKBOhs2bIC7uzvatGlT4LPmzZtjw4YNha4LRKSv2PFLpOO8vb2RkZGB2rVrw8bGRl7u5eWF1NRU+XT5fN999x1mz56NwMBANGjQAJ06dcKBAwfg7Oxc6PlbtWqFoKAgLFmyBE2aNEFoaCgmTZoEU1NTleKcMmUKpFIpXFxcUKVKFTx48AD29vY4ffo08vLy0LFjRzRu3BgTJ06ElZWVPMlZuHAhPvroI3Tr1g3t27dH69at4ebmVuy1+vfvj9mzZ2PatGlwc3PD/fv35a1g+UaOHImff/4ZmzZtQuPGjeHl5YXNmzcX+RwAoHv37pg0aRLGjh0LV1dXnDlzBrNnz1ao4+PjI7928+bNkZqaqtASVZhvv/0W9+7dQ61atVClSpUCn2dnZ+O3335D7969Cz2+d+/e+PXXX9XW1UakCyTC253RRETvadSoUbhx4wZOnjwpdihERIViFxgRvbdFixahQ4cOMDc3x6FDh/DLL78UWFeHiEibsAWIiN5bv379EBERgdTUVNSsWRPjxo0rMM2ciEibMAEiIiIivcNB0ERERKR3mAARERGR3mECRERERHqHCRARERHpHSZAREREpHeYABEREZHeYQJEREREeocJEBEREemd/weOO5tQ+/j3TQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(winternational.allele_freq, summary['mean'])\n",
+    "plt.vlines(x=winternational.allele_freq, ymin=summary['hdi_3%'], ymax=summary['hdi_97%'], color=\"lightskyblue\", zorder=0)\n",
+    "plt.plot([0,.1],[0,.1], c=\"black\", linestyle=\"--\")\n",
+    "plt.xlabel('Weighted default AF')\n",
+    "plt.ylabel('Weighted compound AF')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The solution is to use a different prior. Instead of $1$ for each allele, use $1/k$ where $k$ is the number of alleles. It's a simple fix but the downside is that it runs much slower."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cameroon\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 272 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cape+Verde\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 285 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ghana\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 308 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Guinea-Bissau\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 319 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Kenya\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 348 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sao+Tome+and+Principe\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 288 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Senegal\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 308 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "South+Africa\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 317 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Uganda\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 297 seconds.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Zimbabwe\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Auto-assigning NUTS sampler...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Initializing NUTS using jitter+adapt_diag...\n",
+      "Multiprocess sampling (4 chains in 4 jobs)\n",
+      "NUTS: [frac, conc]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 277 seconds.\n"
+     ]
+    }
+   ],
+   "source": [
+    "idatas2 = []\n",
+    "for i,aftab in enumerate(aftabs):\n",
+    "  print(countries[i])\n",
+    "  # fit pymc model to each dataset separately\n",
+    "  c_array, allele_names = HLAhdi._make_c_array(aftab)\n",
+    "  # number of alleles\n",
+    "  k = len(aftab.allele.unique())\n",
+    "  # use 1/k prior\n",
+    "  idata = HLAhdi._fit_Dirichlet_Multinomial(c_array, prior=[1/k]*k)\n",
+    "  idatas2.append(idata)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now the models have finished running, weight and sum the traces. This is exactly the same as before."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sd</th>\n",
+       "      <th>hdi_3%</th>\n",
+       "      <th>hdi_97%</th>\n",
+       "      <th>mcse_mean</th>\n",
+       "      <th>mcse_sd</th>\n",
+       "      <th>ess_bulk</th>\n",
+       "      <th>ess_tail</th>\n",
+       "      <th>r_hat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A*01:01</th>\n",
+       "      <td>0.063</td>\n",
+       "      <td>0.009</td>\n",
+       "      <td>0.047</td>\n",
+       "      <td>0.079</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1774.0</td>\n",
+       "      <td>2231.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:02</th>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.007</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1002.0</td>\n",
+       "      <td>1315.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:03</th>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.005</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1903.0</td>\n",
+       "      <td>2290.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:06</th>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1894.0</td>\n",
+       "      <td>1317.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*01:09</th>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1221.0</td>\n",
+       "      <td>1575.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*69:01</th>\n",
+       "      <td>0.002</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1373.0</td>\n",
+       "      <td>1856.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:01</th>\n",
+       "      <td>0.042</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.030</td>\n",
+       "      <td>0.053</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>886.0</td>\n",
+       "      <td>1661.0</td>\n",
+       "      <td>1.01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:02</th>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1240.0</td>\n",
+       "      <td>1675.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*74:03</th>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.001</td>\n",
+       "      <td>0.006</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2653.0</td>\n",
+       "      <td>2560.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>A*80:01</th>\n",
+       "      <td>0.010</td>\n",
+       "      <td>0.004</td>\n",
+       "      <td>0.003</td>\n",
+       "      <td>0.017</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3136.0</td>\n",
+       "      <td>2721.0</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>85 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
+       "A*01:01  0.063  0.009   0.047    0.079        0.0      0.0    1774.0   \n",
+       "A*01:02  0.004  0.002   0.002    0.007        0.0      0.0    1002.0   \n",
+       "A*01:03  0.003  0.001   0.001    0.005        0.0      0.0    1903.0   \n",
+       "A*01:06  0.000  0.000   0.000    0.001        0.0      0.0    1894.0   \n",
+       "A*01:09  0.001  0.001   0.000    0.002        0.0      0.0    1221.0   \n",
+       "...        ...    ...     ...      ...        ...      ...       ...   \n",
+       "A*69:01  0.002  0.001   0.000    0.004        0.0      0.0    1373.0   \n",
+       "A*74:01  0.042  0.006   0.030    0.053        0.0      0.0     886.0   \n",
+       "A*74:02  0.000  0.000   0.000    0.000        0.0      0.0    1240.0   \n",
+       "A*74:03  0.004  0.001   0.001    0.006        0.0      0.0    2653.0   \n",
+       "A*80:01  0.010  0.004   0.003    0.017        0.0      0.0    3136.0   \n",
+       "\n",
+       "         ess_tail  r_hat  \n",
+       "A*01:01    2231.0   1.00  \n",
+       "A*01:02    1315.0   1.00  \n",
+       "A*01:03    2290.0   1.00  \n",
+       "A*01:06    1317.0   1.00  \n",
+       "A*01:09    1575.0   1.00  \n",
+       "...           ...    ...  \n",
+       "A*69:01    1856.0   1.00  \n",
+       "A*74:01    1661.0   1.01  \n",
+       "A*74:02    1675.0   1.00  \n",
+       "A*74:03    2560.0   1.00  \n",
+       "A*80:01    2721.0   1.00  \n",
+       "\n",
+       "[85 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "weighted_country_estimates2 = []\n",
+    "for i,country in enumerate(countries):\n",
+    "    # Country specific weight\n",
+    "    weight = country_data[country_data.country==country].proportion.values\n",
+    "    # Weighting the country estimate\n",
+    "    weighted_country_estimate = idatas2[i].posterior['frac'] * weight\n",
+    "    weighted_country_estimates2.append(weighted_country_estimate)\n",
+    "\n",
+    "# Sum all the weighted country estimates\n",
+    "weighted_international_estimate2 = sum(weighted_country_estimates2)\n",
+    "\n",
+    "# Get model summary\n",
+    "summary2 = az.summary(weighted_international_estimate2)\n",
+    "# Add the allele names on to the summary\n",
+    "# these were produced when we made c_array\n",
+    "summary2.index = allele_names\n",
+    "summary2"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now when we compare the weighted default and weighted compound estimates they are in much better agreement. Remember though that we didn't exclude the incorrect Guinea data for the default model so we should really redo the compound model without Guinea."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(winternational.allele_freq, summary2['mean'])\n",
+    "plt.vlines(x=winternational.allele_freq, ymin=summary2['hdi_3%'], ymax=summary2['hdi_97%'], color=\"lightskyblue\", zorder=0)\n",
+    "plt.plot([0,.1],[0,.1], c=\"black\", linestyle=\"--\")\n",
+    "plt.xlabel('Weighted default AF')\n",
+    "plt.ylabel('Weighted 1/k compound AF')\n",
+    "plt.show()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -562,7 +1940,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.6 ('hlatest')",
+   "display_name": "hlafreq",
    "language": "python",
    "name": "python3"
   },
@@ -576,12 +1954,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "ba8993ce7211adb02205292137dc55b777974e9fe0701bdbbc9cdd66bee34052"
+    "hash": "46d2d82dbc865cefb79a4a45cbcd8ead329d89ff6c8b099bf15de0f92559257f"
    }
   }
  },

From bf2925a69a9e781ec6710fcb2f8a3564f12f3dd5 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 12:37:20 +0000
Subject: [PATCH 103/192] Reorder cells put the CI output at the end so people
 dont miss the 1/k prior model

---
 examples/multi_country.ipynb | 311 +++++++++++++++++------------------
 1 file changed, 155 insertions(+), 156 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index f055ee2..99db3d1 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -16,9 +16,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+     ]
+    }
+   ],
    "source": [
     "import HLAfreq\n",
     "from HLAfreq import HLAfreq_pymc as HLAhdi\n",
@@ -37,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -48,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -110,7 +118,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -152,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -171,7 +179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -194,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -217,7 +225,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -239,7 +247,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -286,7 +294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -461,7 +469,7 @@
        "99                  Guinea  "
       ]
      },
-     "execution_count": 84,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -480,7 +488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -496,7 +504,7 @@
        "       'Papua New Guinea Wosera Abelam'], dtype=object)"
       ]
      },
-     "execution_count": 85,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -525,7 +533,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -555,7 +563,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1211,144 +1219,6 @@
     "summary"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[<AxesSubplot: title={'center': 'frac'}>,\n",
-       "        <AxesSubplot: title={'center': 'frac'}>]], dtype=object)"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x200 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# This object can be fully explored using arviz like any other pymc model\n",
-    "az.plot_trace(weighted_international_estimate)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[0.02759661, 0.0548428 ],\n",
-       "       [0.00452285, 0.01433677],\n",
-       "       [0.00377304, 0.0129694 ],\n",
-       "       [0.00176486, 0.00881422],\n",
-       "       [0.00231861, 0.01024124],\n",
-       "       [0.00203228, 0.00954437],\n",
-       "       [0.03415686, 0.06497219],\n",
-       "       [0.01573759, 0.03394972],\n",
-       "       [0.00235762, 0.01074451],\n",
-       "       [0.0021822 , 0.00932612],\n",
-       "       [0.01403252, 0.03101837],\n",
-       "       [0.00373039, 0.01356755],\n",
-       "       [0.00196443, 0.00987427],\n",
-       "       [0.00434116, 0.01517492],\n",
-       "       [0.00564147, 0.01691425],\n",
-       "       [0.0026366 , 0.01053915],\n",
-       "       [0.00148889, 0.00845054],\n",
-       "       [0.00176905, 0.00898124],\n",
-       "       [0.00234081, 0.01046179],\n",
-       "       [0.00186188, 0.00876754],\n",
-       "       [0.00203182, 0.00905159],\n",
-       "       [0.00193571, 0.00895337],\n",
-       "       [0.00179998, 0.00900889],\n",
-       "       [0.02321528, 0.04599152],\n",
-       "       [0.00311518, 0.01205201],\n",
-       "       [0.00896835, 0.02769771],\n",
-       "       [0.00189439, 0.00985112],\n",
-       "       [0.00206027, 0.00961964],\n",
-       "       [0.02288719, 0.04653844],\n",
-       "       [0.00210568, 0.0104285 ],\n",
-       "       [0.00180538, 0.00896166],\n",
-       "       [0.00150521, 0.00843743],\n",
-       "       [0.00204784, 0.0101851 ],\n",
-       "       [0.01709138, 0.03842565],\n",
-       "       [0.00212325, 0.01014264],\n",
-       "       [0.00165893, 0.00846217],\n",
-       "       [0.00372449, 0.01475766],\n",
-       "       [0.00152746, 0.00848436],\n",
-       "       [0.00193521, 0.00922991],\n",
-       "       [0.00157473, 0.00838175],\n",
-       "       [0.00378695, 0.01341583],\n",
-       "       [0.01160147, 0.02687958],\n",
-       "       [0.00178218, 0.00884404],\n",
-       "       [0.00191682, 0.00977162],\n",
-       "       [0.00165529, 0.00880991],\n",
-       "       [0.00330384, 0.01207244],\n",
-       "       [0.00703055, 0.01960981],\n",
-       "       [0.0193696 , 0.03994969],\n",
-       "       [0.00181336, 0.0088939 ],\n",
-       "       [0.00228535, 0.01033887],\n",
-       "       [0.00184695, 0.00903161],\n",
-       "       [0.02108054, 0.04292904],\n",
-       "       [0.02220973, 0.04393149],\n",
-       "       [0.0018361 , 0.00901249],\n",
-       "       [0.00890208, 0.02225097],\n",
-       "       [0.00170556, 0.00899271],\n",
-       "       [0.00199869, 0.00952631],\n",
-       "       [0.0020753 , 0.00991832],\n",
-       "       [0.00976027, 0.02484884],\n",
-       "       [0.00276726, 0.01087186],\n",
-       "       [0.00335449, 0.01247954],\n",
-       "       [0.01155675, 0.02631822],\n",
-       "       [0.00185561, 0.00900223],\n",
-       "       [0.0019529 , 0.00912835],\n",
-       "       [0.00216055, 0.01033339],\n",
-       "       [0.00690024, 0.01936623],\n",
-       "       [0.01479347, 0.03303133],\n",
-       "       [0.00246119, 0.01059669],\n",
-       "       [0.01388516, 0.03169402],\n",
-       "       [0.01108828, 0.02599472],\n",
-       "       [0.00311409, 0.0128932 ],\n",
-       "       [0.01510048, 0.03311533],\n",
-       "       [0.00578678, 0.01594144],\n",
-       "       [0.00361539, 0.01296951],\n",
-       "       [0.0160388 , 0.03481026],\n",
-       "       [0.02409609, 0.04690669],\n",
-       "       [0.00162889, 0.00867585],\n",
-       "       [0.00184908, 0.00935288],\n",
-       "       [0.00160451, 0.00851681],\n",
-       "       [0.001937  , 0.00959509],\n",
-       "       [0.00289136, 0.0113081 ],\n",
-       "       [0.01694051, 0.03715183],\n",
-       "       [0.00159336, 0.00858231],\n",
-       "       [0.00447347, 0.0143532 ],\n",
-       "       [0.00440853, 0.01568641]])"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# az.summary() gives 96% credible intervals\n",
-    "# but any interval can be obtained with az.hdi()\n",
-    "az.hdi(weighted_international_estimate, 0.95).frac.values"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -1934,8 +1804,137 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.02759661, 0.0548428 ],\n",
+       "       [0.00452285, 0.01433677],\n",
+       "       [0.00377304, 0.0129694 ],\n",
+       "       [0.00176486, 0.00881422],\n",
+       "       [0.00231861, 0.01024124],\n",
+       "       [0.00203228, 0.00954437],\n",
+       "       [0.03415686, 0.06497219],\n",
+       "       [0.01573759, 0.03394972],\n",
+       "       [0.00235762, 0.01074451],\n",
+       "       [0.0021822 , 0.00932612],\n",
+       "       [0.01403252, 0.03101837],\n",
+       "       [0.00373039, 0.01356755],\n",
+       "       [0.00196443, 0.00987427],\n",
+       "       [0.00434116, 0.01517492],\n",
+       "       [0.00564147, 0.01691425],\n",
+       "       [0.0026366 , 0.01053915],\n",
+       "       [0.00148889, 0.00845054],\n",
+       "       [0.00176905, 0.00898124],\n",
+       "       [0.00234081, 0.01046179],\n",
+       "       [0.00186188, 0.00876754],\n",
+       "       [0.00203182, 0.00905159],\n",
+       "       [0.00193571, 0.00895337],\n",
+       "       [0.00179998, 0.00900889],\n",
+       "       [0.02321528, 0.04599152],\n",
+       "       [0.00311518, 0.01205201],\n",
+       "       [0.00896835, 0.02769771],\n",
+       "       [0.00189439, 0.00985112],\n",
+       "       [0.00206027, 0.00961964],\n",
+       "       [0.02288719, 0.04653844],\n",
+       "       [0.00210568, 0.0104285 ],\n",
+       "       [0.00180538, 0.00896166],\n",
+       "       [0.00150521, 0.00843743],\n",
+       "       [0.00204784, 0.0101851 ],\n",
+       "       [0.01709138, 0.03842565],\n",
+       "       [0.00212325, 0.01014264],\n",
+       "       [0.00165893, 0.00846217],\n",
+       "       [0.00372449, 0.01475766],\n",
+       "       [0.00152746, 0.00848436],\n",
+       "       [0.00193521, 0.00922991],\n",
+       "       [0.00157473, 0.00838175],\n",
+       "       [0.00378695, 0.01341583],\n",
+       "       [0.01160147, 0.02687958],\n",
+       "       [0.00178218, 0.00884404],\n",
+       "       [0.00191682, 0.00977162],\n",
+       "       [0.00165529, 0.00880991],\n",
+       "       [0.00330384, 0.01207244],\n",
+       "       [0.00703055, 0.01960981],\n",
+       "       [0.0193696 , 0.03994969],\n",
+       "       [0.00181336, 0.0088939 ],\n",
+       "       [0.00228535, 0.01033887],\n",
+       "       [0.00184695, 0.00903161],\n",
+       "       [0.02108054, 0.04292904],\n",
+       "       [0.02220973, 0.04393149],\n",
+       "       [0.0018361 , 0.00901249],\n",
+       "       [0.00890208, 0.02225097],\n",
+       "       [0.00170556, 0.00899271],\n",
+       "       [0.00199869, 0.00952631],\n",
+       "       [0.0020753 , 0.00991832],\n",
+       "       [0.00976027, 0.02484884],\n",
+       "       [0.00276726, 0.01087186],\n",
+       "       [0.00335449, 0.01247954],\n",
+       "       [0.01155675, 0.02631822],\n",
+       "       [0.00185561, 0.00900223],\n",
+       "       [0.0019529 , 0.00912835],\n",
+       "       [0.00216055, 0.01033339],\n",
+       "       [0.00690024, 0.01936623],\n",
+       "       [0.01479347, 0.03303133],\n",
+       "       [0.00246119, 0.01059669],\n",
+       "       [0.01388516, 0.03169402],\n",
+       "       [0.01108828, 0.02599472],\n",
+       "       [0.00311409, 0.0128932 ],\n",
+       "       [0.01510048, 0.03311533],\n",
+       "       [0.00578678, 0.01594144],\n",
+       "       [0.00361539, 0.01296951],\n",
+       "       [0.0160388 , 0.03481026],\n",
+       "       [0.02409609, 0.04690669],\n",
+       "       [0.00162889, 0.00867585],\n",
+       "       [0.00184908, 0.00935288],\n",
+       "       [0.00160451, 0.00851681],\n",
+       "       [0.001937  , 0.00959509],\n",
+       "       [0.00289136, 0.0113081 ],\n",
+       "       [0.01694051, 0.03715183],\n",
+       "       [0.00159336, 0.00858231],\n",
+       "       [0.00447347, 0.0143532 ],\n",
+       "       [0.00440853, 0.01568641]])"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# az.summary() gives 96% credible intervals\n",
+    "# but any interval can be obtained with az.hdi()\n",
+    "az.hdi(weighted_international_estimate2, 0.95).frac.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[<AxesSubplot: title={'center': 'frac'}>,\n",
+       "        <AxesSubplot: title={'center': 'frac'}>]], dtype=object)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# This object can be fully explored using arviz like any other pymc model\n",
+    "az.plot_trace(weighted_international_estimate2)"
+   ]
   }
  ],
  "metadata": {

From df49de6b0c01b9b9679cb8482a24e0be929f256a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 14:39:11 +0000
Subject: [PATCH 104/192] Plot compound af vs default af

This is a more obvious method to  iangnose high k
---
 examples/working_with_priors.ipynb | 70 +++++++++++++++++++++++++++---
 1 file changed, 64 insertions(+), 6 deletions(-)

diff --git a/examples/working_with_priors.ipynb b/examples/working_with_priors.ipynb
index 59f5f0d..dd2b6d4 100644
--- a/examples/working_with_priors.ipynb
+++ b/examples/working_with_priors.ipynb
@@ -329,7 +329,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 19 seconds.\n"
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 20 seconds.\n"
      ]
     },
     {
@@ -344,7 +344,7 @@
     },
     {
      "data": {
-      "image/png": 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XL6ZatWrs2rWLwMDAXM2E27ZtK0rk2a99+eWX9OnTB4C4uDiSk5PFSUx4eDiCIDBz5kzxybOhQ4dy+vTpfF2aChUqoFQqadmypVhI09fXl3LlypmtQAHs2bOH/fv3s2nTJvbs2YNSqaREiRL53rOlHSgXew1pmUZSdFlPC958woGaM6wHc4blfXy1atUKdP1XiRQ8KCm7AVJBzsi6kfOxfqSckVU4UI6OjtSqVYvOnTujUCgYPXo0Pj4++Pn5cfbs2Xwl8jt37qBUKvnll1/w9fUlIyMDlUpFpUqVaNWqFQC9e/dm586d+Pj4MHv2bKKjoxk/fjxarZaGDRsCcOrUKZo0acKSJUsYOnQo4eHhmEwmgoKC2L59u7gCpdVqxTIGJ0+e5K+//sLX15fff/+d/fv3A9ChQwexPlVeWNKBunVHiaADjAoMBni27nyvJ1LyoKToBkgNOSPrRs7H+pFiRoXuQHl5eREYGJirmXDFihWZO3cus2bNYvv27XkW0rx9+zZKpZK4uDgyMzNFQdzR0VHckvvoo4/YvXs3AQEBbNu2DchadtuwYYNZpfGcZFcdr1mzppkD1ahRI2JjYwGwsbFh+vTpGAwGunfvLq5MDR48+Kn3bEkH6s6RMK7+HY4REw52KlQKBXZfb0DITOXGogEgmGjU/gNW/zKTEiVKiE8kfvfdd5hMJrZu3UqLFi0KNIZXhRS28KTsBkgFOSPrRs7H+pFyRoXuQIWEhODp6ZmrmfCJEycQBIGuXbvmW0jTZDJhMBhwcnJi2bJlNG7cmPv379OmTRsOHz5Mu3btOHPmDIGBgTRu3JiJEycSExPDV199Rd++fUlKSkKhUPD222+bOVDZBAcHmzlQBw8epH379gAcP36csmXLsnr1asqUKcO5c+fo0aMHkyZNolOnTvnesyUdKBd7WwwmAY1SiUapREAABdg4OqNQ24DJSLte/SldujQArq6uDBw4kN9++42IiAjefPNNq/4Bl8KkKS+k6AZIDTkj60bOx/qRYkaF6kBBwZoJZ6/YLF68WCykWalSJYoXLy5K5HPmzEEQBE6cOCE6UCqVigEDBnD8+HGaNWuWa0zZhTQ/++wzs2bCOQtpHjp0iLt37+Zasbl8+TIff/wxq1evzvN+LelA3X6UgpNWTbreSJrOgFql4PoTDtSM/h2Y0T/v4994440CXd/SSMF7yomU3QCpIGdk3cj5WD9SzqhQHahXUUgzu3/d8uXLxUKamzdvBhAnVC9SSHPhwoVmJQxCQkLo0aMH1apV44cffsj3ni3pQN0IU6IyQnENJOoVZEjs51VK3lNOpOgGSA05I+tGzsf6kWJGz+NAKYS89rkKwNatW+nVqxd169alSZMmLFq0CG9vb86dO4eXlxe3bt1i1KhR+Pr6iitQOp1OdKBmz57NxIkTUalUFC9enNjYWIxGIwqFgqSkJIoUKcKhQ4fw8vJCoVBgMmVp1RqNBjc3N27duoWdnR3nzp2jadOm/Pbbb/Tv358TJ07QtGlTbG1tsbOzIy0tDScnJ1JTU+nQoQMbN24kPDycGTNmsHHjRrN90P3799O2bdt87zmvFaiyZcsSGxtbYAdq8eEwtl16SPlidigUCgwGE1EPH+CgEtg6uTdVu33Bxx/3Zei7FUlJScHe3h6NRsPFixdp1aoVa9eupV27dgUaQ3JyMm3atCE1NZV+oyZy1lQRnd5A5u2zXNryKxp7R+oO/hk7+yKMbF2JppWKPfO5pbaFJ2U3QCrIGVk3cj7Wj5QzSkpKonjx4iQmJv7r399W10w4u5CmUqkkKSkJBwcHateuzbFjx8RCmg4ODgiCgJ2dHSaTCY1GQ3p6OgkJCWi1WoB8C2k+bb5448YNTCYTy5Yto2jRouzcuZMFCxbQr18/Hjx4kG/rF0s6UG1qenDgxiOS0o24FrFBrQYbWy0uJUpQskYj7h9dT92vBqDVasV71+l0zJw5kzJlyvDee+/lKtPwvKxdu5Y7d+5w+swZlpxPxfAohbJuzihKtMWtXGV2zhhA5s3jqDy92PzPQ5pVKYFapfz3E/P6beE964RPim6A1JAzsm7kfKwfKWZUqA7Uy2omvHLlynybCc+ZMwfIWhnJ3rJbvny5mQP1ZCHNbAdq2LBh+TYTbt++vSiUA7Rp0wZ7e3tmzZollkXIC0s6UNVK2NG5tjub/okgOUOf5UMZ4EFcGtHBpwHo3LROvsdnF9h8GdSvVy/f904HzAPmcRjwH/TSLml1/NuET8pugFSQM7Ju5HysHylnJDtQFKyZcE6yJ0M5J0hPYkkHCqCkAM1dFPzzWEFMnAJQ4GRMKfB5ZZ6fZ3W2pOgGSA05I+tGzsf6kWJGsgP1gg7U6dOnmTlzJvfu3SMkJASFQoFer6do0aLcv38/z206sKwDlROTSSAqIZWgo0fp/p4XRsP/ZsqJiYlER0fj4uLy1KrpL0L2U4sL/AL4ZvNV7G1UFNH+b+69/6eRqG3tafz596RmGvmhey0queXdeNlSLFq0iClTpvDxxx8zePBgypYty+nTp5kzZw7Xrl1j9+7d1K1bN9/j41J1zNh9g1sxKbjYaXDQqjGaBOJSdZhMAr0alKFXw7L/uoUnZTdAKsgZWTdyPtaPlDOSHShezIGyt7fn6tWrxMTEYDAYMBqNVK9enb/++ivfyRNY1oF6klJFFTjbgNbWBo3D//4yd3FxeWq/voIwePBgPvroI+LvhfDmG+6cC4/HxdYepULBgysneRR2lZbDfiBRr+atCsWpV7n0M63uvSzi4+P54YcfGDt2LPPmzRNfL1euHJ06daJx48b88MMP7Nu3L99zbL8eTniiiTfci5n5W44O8Cg5kz03k+jc0BaXZ8xTim6A1JAzsm7kfKwfKWYkO1Av6EDVrl2bO3fuEBkZSb169YiLi+PatWviNQqbTIORO49SiUqDuIQkHOy14nt3797l/v37FC1alBo1arzUCUyHDh1o1aoVnTp14qPPBqMq4snlexkkXz9B2JENlKjRCIOHJyVsTPSuV+K5lkBfBmvWrEGv1zN8+HAxy5yMGDGCwYMHExoaSqlSpXK9bzQJ7PknHBuTDsGgRG8wf99JI3A/Lo1DV+/T/a3STx2LXq8nIyOD1NRUNBqN5J4ylJGRkZHJQnagniAiIoJWrVpRoUIF0tPTn2nyZEmJHMBgNLHt0kP2XI0mOimD5GQVQ/oUL/B5X4RlvgtyvRZz/QwxkzsDsHnUKx5QDipVqvTU97NbB70oR1/gmNftKcP/AlIWYKWAnI/1I+WMrKKZcHh4OF5eXtSpUwdvb28yMjJo1qwZfn5+ODg44Ovrm2cvvIyMDBQKBT///LPoQG3fvh2FQkHTpk0B6NOnD/7+/gwbNoyBAwcCWZMhZ2dn3nrrLQBiY2OxsbHhzp07tGzZkujoaACWLFnC8uXLRQdKq9WKqwQRERFUq1YNg8HA7du3MRqN9OjRg2+//fap/owlJXKTAHvvK7gYp0SlECiiBnuL1I+XsQRSLRQqBaQowEoJOR/rR4oZFXozYUs7UDVr1sTOzo7MzExsbGzQarUoFApKlSpVIAfqwIEDubaANm3axKZNm556nCWbCf9zL4G7d4Ip46bCyU6DYBJ4FPuIPosPsX/BWNKTEgjYvJ13a5YVjzGZTPTv359Tp05x5coVcatUqsTHx1OzZk0GDhzIjBkzzN7LyMigbdu2FC9enC1btuR7jsAz9wk4e58yLlpUT9SwikvRoVDAvB5v4u6szecMWej1eg4dOkTr1q3lLTwrRcoCrBSQ87F+pJxRoTcTtrQDNW3aNNLS0rhx4wbVqlUD4MGDB+KTV2+//fYLOVD9+vWjX79+AKxYsYLRo0ezatUqunXrhl6vz/cHxZIS+bGwOHRGgdL2tgiAzmTIcmx0KcSGXqT6B1/zT5SORm9kEB0djaurK8WKFWPy5Mk0bNiQgwcP0qVLlwKN4VXxopMNFxcXpk6dyjfffINOp2PUqFGUL1+eEydOMHXqVG7duoW/vz8uLi75nuODd+y4EJXJrZgUitrb4Pj/T+E9Ts1Er7Sl79vlqF7e/V/Hotfr0Wq1uLi4SO4/LFJDigKslJDzsX6kmFGhSuSvwoG6du0aWq2WnTt30r59ewRB4J133gEQyxq8jDpQgiDw559/8s477zz1S7WkA/UgPg2NUkFMUgYxyZmk6Qxcnd5TfP/GhrlM3TCXqfkc36dPnwJd/1VSEF9ozJgxaDQaZs2axdKlS8XXa9Wqxd69e6lbt+5Ts3C2VTK5QzX8j4dz/l4C9+N1qBTg5mhL1zql6FrH45mylLIbIBXkjKwbOR/rR8oZPc89vZZ1oDp37szOnTtxdnZGq9USGxuLyWRCpVKRlJRUoF5448ePZ9euXeKqlJubG3/++SdNmjTBwSHv2kZTp07N04EKCAgosAO19Y6Ss7EK9FnzQlQKuD6rc4HOaa1s3bq1wOfQ6XRcvnyZ1NRUPDw8qFKlynM/kfg4A+J1oFZAKXuwKVgnHBkZGRmZ14S0tDT69Okj3TpQHh4eAKSnp5OZmSnWQLpw4QL37t2jWrVqL9wL7/z582Ye1KNHj/D29ubQoUO0atUqz+Ms6UA9PnWP43tvYqNRYKvOcnNqjNuARqPh6twPEUxGpvjvYnTnBuIxmZmZNGzYkAcPHhAWFoarq2uBxvCqeFm+ULdu3V7KeV4EKbsBUkHOyLqR87F+pJyR5B0otTpr2JcvXxYdqPT0dOzt7cUJ1Iv2wrt165bZ/UyaNIlZs2aJcnpeWNKBSswwYKNWYjSZMBgFVEoQBMhIjMWkSwdg0+9z6Or5I1WrViU6OprFixdz//59AC5evIi3t7d4PkEQyDSY0KiU6HVZ245Pu7dXiZR+EaXoBkgNOSPrRs7H+pFiRpJ3oLJdmRUrVrB27VoEQRDLF2R/5lX2wrOkA3U/Lg13J1syDSYS0nXo9AI35n5g9pmrxw9Qr17ej5P6+PgU6PqvEinUTJKyGyAV5IysGzkf60fKGUm+DpRKpUKhUDB//nycnZ15/Pgxd+/eRavViud8kTpQ+fXCc3Nzo0mTJvnesyXrQMU+VJKcAsW1oLWBDGOBTmfVSKlmkhTro0gNOSPrRs7H+pFiRpKvAyUIAoIgiNK4q6srNWrU4O+//yYkJOSFHagX7YVnSQdKExzDvL9CcXGyxUatRDAJ2E9fTzHXomyf9jF27m+w6NdltPc0f8R+3rx5zJkzh6tXr3IiUs/y43cRokM4unAMb/kMoWbbXpgEgcj4DMoUtaNmwmkmTfiGrVu30qJFiwKN+UWRQs0kKbsBUkHOyLqR87F+pJzRf8aBunDhwkt1oF60F54lHaiWNUqy+1o01yKTKOloi1ajQKXRkmkSKN2yDzc3zuPgml94+5vxuLm5kZaWxvLly5k9ezaDBw+mREl3Dh7+B7VKSdjJXTiVLEstr14oFEqUCnB31hIZn8En7/Wi5upV+Pv74+XlVaAxvyjWtoVXkAmdFN0AqSFnZN3I+Vg/UsxIdqCQTi88jQLGt6vC9J3X+ed+IqmZBoxGBaET2oqfWfb7byz7/bdcxy5evJjFixfnen3NsNxPEx6emPW/wcHB+ZZr+K/xIhM6KbsBUkHOyLqR87F+pJyR1ThQgwYNIjk5mZEjR6LRaPDx8TFzoDp27EhoaCitWrVi2rRpZg7UggULmD17Nvb29gwbNgyTyUStWrWA/zlQc+bMQavVotPpuHfvHnZ2dv/qQPn5+XH+/HnOnTuHTqdDpVKJq0cRERG0aNGCtLQ0kpOTSUpKon379qxYsQJ39/yrUFvSgQK4Eqcg5L4SowG0CsECqcnkRUGcLCm6AVJDzsi6kfOxfqSY0fM4UC+9kGbnzp1JTk7m+PHjREREMHHiRBwcHFiyZAlNmzblyJEjfPnllxQrVgxXV1fOnTtH/fr1SUhIQKvVkp6ezqRJk2jXrh2nT58mNTUVFxcXHj16xMaNG3n//ff5/PPP+eOPP6hduzZhYWHY29tTtmxZcdVqypQpuVagsgtpli9fnoiICJRKJbVr1+b69esUL16cu3fvsmLFCvr375/nfT3ta8prBaps2bLExsYW2IG6F5fGlxuvkKE34u5kCwI8in2Es0MRglbOIebqcVat3cR77zYSj4mOjqZLly7Y29tz6NAhftgbwqk7cSSc3Ejw/kC6fb8WrYMzAMnpejIMJia1KUunlm/z+eef8+233xZozFLhRbbwpOwGSAU5I+tGzsf6kXJGSUlJFC9evHAKaeZ0oEqVKoXRaBQ9qOPHj5OQkICzszMrVqxgxowZlC5dGoCrV68yZMgQsV/ZsmXL2LFjB+vWrWPKlCm0adOGBw8eAODh4YFareby5cvidbMdqKNHjwLkcqCyV5Du3r3L2bNnadAgq/Bk7dq1uXr1KpGRkbl64X3++ed06NDhXytkW9KBOnorjsR0AxWL2aNQKDAJJgy6DPQZEH3xMGVbfUisrYfZdcqUKcPs2bPx8fHh4sWLdH2rClcjkxHqeKM6vImgJRNp2n8SSqeSJKQbeMtVz4SRg1AqlQwePPiV/0JIQR5/Eim6AVJDzsi6kfOxfqSYkVU4UPPmzSMlJYX169eLHtTo0aMJCAhg6NCh9OvXT/Sgbt68KXpQN2/eBLK2v6ZPn87p06e5ePEiAGXLlgWgadOmGAwGwsLCqFSpEgDbt28HMPOdsleUBEGgYsWKODs7k5mZKU6ekpKSCA0NRaFQcPr0abp37/5C92xJB+paRCIaJQhkPXkomAT2T/lfL7zw/Sv5Yv9Kvsjn+NatW+d6LfZOMNumfCT++WiO97K3QF8l1iaPFwQpuwFSQc7IupHzsX6knJFV9MKLiYmhefPmXL16lffee49t27bh5OREuXLluHHjBmvWrOG7776jdOnSVKlShWvXrjFixAjee+89atSowaNHj1Aqlbi5uQFZ21IxMTG4ublhMplEsTwiIkJsIOzm5kZMTAyQ5TM1btwYlUrF3bt3AWjbti0HDx6kSJEiGI1GXFxc0Gg0pKWliaUU+vfvz6lTpwgNDcVoNNKyZUvmz59P5cqVC6UX3rrbSm4nQbEcxcJ3f9OlQOe0Nl5GDzwZGRkZGZmCUui98Ly8vIiKiuLq1asMHDiQwMBAYmJi6NixIxs3buTrr7+maNGifPXVV5w/f54GDRpQuXJlYmJiUCqV1KhRA41GQ0pKCmlpaeKTedlLa9kTq/DwcGxsbLCzs6N06dLcvXuXwMBAPvzwQ/R6PRERERw+fFgcW2JiongenU5HamoqlSpVIj09XfzMqVOnuHHjhvjnI0eO8NZbb+V6mi8nlqwDlflPJL8evU0xVztUSgWCScB7+npcnZzY+m0vitVuydu9RxKTnImHsxYbtZLws4c47j8DgIZj/mBkt6Z0ftODhIQEevfuTVhYGBcvXrSarTNrGcfLQMpugFSQM7Ju5HysHylnVOh1oABGjx6NIAj4+/tjMpnE7Tc7OzsqVqzIqlWr8PT05ObNmxw+fJjJkyeL/lFiYiJRUVFimYHsFabixYszadIkmjRpwunTp7l9+zZFixYVrz1z5kymTp3Khx9+mMuBSkxM5MKFC9jb2xMXFwdkNQ+uUaMGKpVKdKSuX78OZK0qLVy4kHfffbdQHag2Nd3ZfjmKiIR0yrjYoVQqUNtoUWhs8GjcmbuHA7hepjJV326HVpMV59U9q1AoVZSp3QSnkmU5cP0RneqUwc3NDT8/P2rXrs3WrVvF77uwKcwtPEtN3qToBkgNOSPrRs7H+pFiRoXqQEGWB7V8+XLKlCnDnj17xDpQu3fvpnv37iiVStavX59nHSiATZs2iatCMTExDBs2jJCQEP7++28qVarE1KlTadCgAXPmzGH16tUUKVKELl26YGdnJ7pIR44coVWrVty5c4cKFSpw/vx5jEYjqampnD9/nvr161O9enXc3NyIjY2lcePGL3y/lnSgnGyVfO1dmR/2hHA9KplMvRG9XsH1b/7nNl3fMI/rG+blOvb+pWPcv9QegNVDzN8bMWIEI0aMKNDYpMDLnrxJ2Q2QCnJG1o2cj/Uj5YwKtQ4UZNWCSk5OZsKECWZ1oB4/fsz777/PnDlzWLFiRZ51oABcXFxo1qwZUVFRwP9mhKVLl6ZEiRLcvn2boKAgEhMT+eWXXzh79ixz5swBYNKkSUBWW5ZSpUrh5eXFrVu3iIqKwsbGhubNm9O2bVsyMzNRKBSkp6dTtWpVSpUqBWRNvKZPn87JkyfJyMjgr7/+YtasWXTo0IG6devmeb+WrgN1PwUeP1aSkaHAYCrw6WRyYKn+e1KsjyI15IysGzkf60eKGRVqHSiAVq1aERQURFRUlFkdqM6dOzN+/HgaN27MyJEjqVmzZq46UGPGjCE+Pp7ff/+dypUrk5CQwLfffkt0dDTvv/8+GzduxNvbm8OHD1OlShXu3r1Lenq6WEMqJSVF3JbJ+RReQEAA/fv3p1mzZly4cAGdTidOoKpUqSJ6T7NmzWLOnDmiL5WT/L4qS9aBepySydgNV4hKyqS0qxYVWXWgnIoU4eQWP+4dWUuNHl9SqbEXTvZZrXF2Tu9PUvR9Sns2puqHkynlYse8HrWz/KjwcOrVq8cvv/zCxx9/XKCxSYGXvYUnZTdAKsgZWTdyPtaPlDMq1DpQAA0bNuTIkSO56kDt2LEDf39/BEHItw4UgKurK9988414vurVq9O8eXNOnDgBZNWBKl++PMHBwfTu3ZsqVaoQFxfHkiVLiIyMpEqVKgBmdZ3c3d3R6XQcOnTIrA5UyZIlCQkJITIyklKlSjFx4kQmTpzI1KlT2bp1KxcvXqRjx45iL728sKQDdex2NFFJmZQrao9K+b86UNjbEnV6Jx5vd6ZW8/ZEJWVgb6vBRq3izY6f8veyaTy4fAKPNg/o8O67FLGzJS4ujqFDh1K8eHF69+5tdT/4UpLJpegGSA05I+tGzsf6kWJGr3UdqLzILk2Q7Uw1bdqUDRs28Ouvv3L79m3WrFkjbv+VKVNGPC7nClT9+vXFti3Zk6eQkBDxyb+n1YFKTEykRo0a+d6zJR2os3ceo/z/OlCxKTpSMvQcylEHKvLENjac2Jb/8fMH0Wd+7tdLlChRoHFZAinUg5KyGyAV5IysGzkf60fKGVlNHagOHTrQs2dPRo0ahcFgyFUHytfXV+xvl10HqmjRokRHR9OwYUMmTJjA/v370el0uLq6EhkZiVarJSUlhSpVqhAfH8/mzZtxcHAQJz+PHz8GssR0Hx8fbG1tCQsLA6Bx48ZcuHCB/fv34+TkxMiRIwG4desW06ZNY+jQody6dYuUlBR+++03Dh8+zGeffcakSZM4e/Zsvg6UJetABYYpCUuCDKMCnREEIPSHzgU6p7Ui14OSkZGRkSlMrKYO1JkzZ5g4cSIqlYr27duLdaAuX75MTEwMBw4cYMyYMUCWjPbHH39QunRpfv31Vz7//HOx/pNWq8VkMjFixAiWLVuGnZ0dxYoVw8XFhR49euDo6EhcXJzZNlpaWhoRERHcuXNHfK1Dhw7cuHGD9u3bo9PpUKvV9OjRg9DQUPEzAwYM4O+//xb/PH78eACxxUxeWLIO1IOjt7l05A6CYMJeq0apgBrjNqAw6Ahe8AmYjLT/9AtW/DgRW1tbcat08ODBZGZmcuDAAXHFzdqRwhaelN0AqSBnZN3I+Vg/Us7IKupAjRs3DoPBQOfOWaslu3fvRqlUYmdnR/ny5cUaTzlRKBS0atWKffv2sXbtWho2bIibmxu3bt2if//++Pn5MWPGDOzs7Lh27RoqlQr43xZfZmYmarWa/fv307p161zSd9myZUlLS6NWrVr8/vvv6PV6+vXrx+PHj8U6UHv27OGrr76iSJEiLFiwAE9PT7GVTH5Y0oGy09pgEgTUSiXKHK+rbGxRKNUIKKhV/x2zKunNmjXDycmJR48eUaZMmdfiB1wKk6ecSNENkBpyRtaNnI/1I8WMrKIO1KpVq5g1axYzZsxg3bp1LF68mGrVqrFr1y4CAwNxdXWlbdu2eHp6AlltVnJK5EOHDhXPV758ebp168aiRYvIzMykZMmSXLlyBYCvvvqK8uXLc+HCBa5cucK5c+eoWLFinuMqUaIEBoOBL7/8Uqz71L9/f7799lvKly8PZP1F3qtXLzp16kSDBg3EidXTsKQDFRadhKu9mjSdiTS9EZVSwfU5H5h9Zt4XvZmXTzO8p7lb1oQU/CeQthsgFeSMrBs5H+tHyhlZRR2o+Ph4HB0dqVWrFp07d0ahUDB69Gh8fHzw8/Pj7NmzokQO5sU0d+/eLXpQDg4OHD16FD8/P9zc3KhQoQIAnp6eLF++nLi4OHbu3ImXlxcKhUKckAGMHDkSX19fcSUqJiYGtVrN/PnzqVatGnq9npUrV6JQKLh79y716tXj8OHDdOrUiVGjRhEWFiZWRbexsTGrep4TS9aBunVHicIAbjaQrIM0Q+6VOylgqXpMhYUU66NIDTkj60bOx/qRYkbPUwfKIhOobA8qMDCQpk2bolKp8Pb2JjExkYoVKzJ37lxmzZrF9u3bqVq1KgA9e/ZkxIgR9O3bF51Ox9ixY0lISBDP6eTkxPHjx8U/BwYGMnjwYOzt7XF0dEShUIjOVH5ERUVRpkwZ4uLixBWoKlWqULRoUbFo58KFC0lLS+OHH34Qj/Pw8ODdd98lKCgoz/Na0oF6eCycdecfULaoHQpFVi+80tPX42CjYuukXlRoN4DBgwfz+btvmB13/PhxOnXqxI4dO2jWrFmBxpAfJpOJ9957j7CwMBYuXEi7du14lKJn7PK/OL12EQm3/qHdOF9cy1YhNdPI41QdjSoUZUL7qqhVSrNzSWULT8pugFSQM7Ju5HysHylnVKgOFGR5UCEhIXh6elKhQgVGjhyJn58fPXr04MSJEwiCQNeuXdm8eTNTpkwBYPr06QwdOpS+ffvSokULZs2aRcWKFdFoNJw4cYKZM2fSoUMHQkNDMRqNzJw5k48//pixY8dSpEgRxo4dy9atW1m6dCmff/45AIsWLWLRokVmY4uJiaFKlSqsW7cOvV5P//79SUlJEd+fN28eXbp0oV69esyYMYMHDx5w584dmjZtmu/9WtKB8qrlzu5r0TxO0VPCSYtJaUJto8XO2ZGStZvz4OgGqo7tZ3adxMREpkyZQrVq1WjZsmWevtnL4NChQ5w5c4YdO3bQqlUrAA5fiCLFphjew79n9/cDCN6/lncHTcXJToVaqeTSg0RuxKTyVjnz1bzXdQsvv4mfFN0AqSFnZN3I+Vg/Usyo0B0oyFqFMhgMBAQEiIU0V65ciVarxdfXl+7du+Pj44ONTVb1bB8fn3wdqDZt2hAbG8vChQt5+PAhdnZ2BAcHExISwsqVK4Gs1RBBEBgyZAiVK1emdevWucZkMplIS0tj2bJl4pNpCxYsoFOnTuI43njjDd54I2s1x8HBAXd3d9555x2zJ/OexJIOVHlXLR83LsvyE3e5E5tKERslKXrYPbSV+JnuXu/ke7yjo2OBrv8sZD8okBdJ0fdZff6w2WsHv8nnw68hT078pOwGSAU5I+tGzsf6kXJGhe5AZUvkPXv25Nq1a2IhzdmzZ2Nra0tgYCBDhgzJ14F6ksjISHH77EmJPJvp06ezefNmJk+eLG7P5SykmZOcKzJKpflW0pOkpqayd+9efHx88v2MpXvh2QBti8LFx0ruJYNSmhrUa0l+7pYU3QCpIWdk3cj5WD9SzKjQHahsiTw8PBwvLy/q1KmDt7c3GRkZNGvWDD8/PxwcHPD19c3TgVq7di3ff/89N2/eFP+Fr9FoaNSokSiRJyQkMH78eE6ePClOkBwdHfnuu+/EcVy/fl1cWQLEMgo5mwlnVyfPvk5GRga9e/dm79694qqSj4/PUydQlnSgniQ9M5O//jrI+pgYs6VGQRDIyMjA1tb2XyeF+XHt2jVatWmLnccbeHb5nHLVPDFmZhByYi9Xty2ldK1GHN6xgWIOWduVc+bMYdGiRQQHB4srXVO2BXMlIpHSRe04teYnHgafpdv3a1EoFJgEgQdx6fR7pwI+b5Uq+JdhBTy5hSdlN0AqyBlZN3I+1o+UMyp0B8rPz48mTZpw/PhxKleubOZARUVFce7cOZYtW5avA2Vvb09qaqoYjKOjI/Hx8Tx69Ei8RpEiRRgxYgRTpkxBEAQmTJjAxYsXGThwIMuWLQOyHuHPy63JuSIlCILZn41GIwcPHjTbktu8eTObN2/Ot5mwJR2ovFAp8j53zsniizB99k+oi7jw7rAfcXXKmhBp7B2o49UDB0cXTiyfwfKdR5nwcQcgq9fgnDlzmDNnDj/88AMKhQKvWu5ce5hEZNgNws8cwPO9j1Eps+p1PUrKwMXehpbVSr52v3TPK7lL0Q2QGnJG1o2cj/UjxYye535eeiuXbMaNG8fcuXMBRAcKsqqKP3z4kC1btvDbb7+Jf+nrdDqGDBkiNv99klGjRrFw4UIiIyPx8PDI8zM1a9bkwYMH+c4gZ86cyeTJk82aCe/atYtOnTqxbNkyPvvsM7PP9+vXj4SEBHr06MHnn39OcnKyWLwzJ3k5UGXLliU2NvalrkDFpeoIeZjI2XNn+eqTbi/tvDL/zrNK7lL+l5lUkDOybuR8rB8pZ5SUlETx4sULp5ULWN6Byot//vmHe/fuodVqxddehgMFWfK5Xq/HZDLlOYGytAOVaYSjUQquxSv+vw5U7jHIWJbnrVMlRTdAasgZWTdyPtaPFDP6TzhQgwYN4uzZs1y+fFmcIGk0GkaPHi2O40UcqEmTJrFv3z7u3r0r9tc7evQovXr1ynembUkHSm808cPeEK6lPcbRSU1prZrYx7G8N2cv929cIHjlZJo1a8b4ceOoV68et2/fZsmSJfz555/8+OOPYkmHf8NoNFKuwhsUrduW5n2Go3yi9IE+I51N3/Sgbrve/LVyXp7niIqKIjMzE3d3d2xtbTEYTSSm61EqFbjYaSxWTuFV8KxbeFL+l5lUkDOybuR8rB8pZ/SfcKBCQ0PFCuEqlQq1Wk1SUhJ2dnbiZ17EgQoLCyMiIoLU1NQs8dlkIiEh4akSuSUdqLN3Yzl9Jx53Jy32NmpMgglBn0FRF0dO/bUSxzLV+HruH7SomSVl16lTh99//x2tVsusWbPo16/fM/3lr9Fo+KD3hwT8GUBk8y6UK1/B7P2r+9Zi1GUwoN8n+d5T2bJlnzgn2Glzfy/5IZVimiBNN0BqyBlZN3I+1o8UM/rPOlAlSpTAZDIRGxub5/sv6kDp9XpKliyJv79/nue1pAM1d99N/roRQ/liWVuBgklg5cAmBTqntfK6FtPMiZT/ZWZpQkJCePDgAcWLF+fNN9+02Irlq84oXWfkfnzWtkBZV3vsbOQt+Kch/w5ZP1LO6D/pQJlMJjIzM1Gr/3dLL8uBSkxMfGpTXks6UBdvKUlPgxhjyr9/+DVHSv3wpOgGWIqbN2/i7+/PjRs3xNfKlSvHxx9/TMOGDS12XUtnZDDBmUcKLj5WkKzP+m+Oo0agbjGBRm4C6herNvKfQf4dsn6kmNF/yoG6d+8eOp0OW1tbkpKSCuxAZdeBunr1KmFhYTg6OpKens6YMWPyvV9LOlDB+0OJvR5DiWJZW5OCScB7+npsDOnsnP4pNftMomuXzoxrV83suDt37lCvXj38/Pyeuv2YH9Exjzh9KRiVjS3NG76Fk/2zb8W9KFLYwpPyv8wswZkzZ/jwww+pUaMGa9eu5a233uLWrVssWLCAWbNmERAQwPvvv/9Sr/kqMjIYTcw/eIuzSY/Q2isob5d1nYR0PWeTTLiULskYr8qo5Kq4uZB/h6wfKWf0n3Kg0tPTAYiLi0OhUNC3b1/xMwWpA5XdHy85ORmAHj16FEodqFY1SnLk5iPSdSaK2KrFXnjFy5Sj2BuePDi2Ga+JQ3FxcTG7J19fX1xdXfnwww/NvLBnxcXFhWpVqxRo7P9lpOgGWIKvv/6aWrVq8ffff4tP0FatWpX27dvzwQcfMHbsWN5//32LfJeWzOjC/ccE3XxMcQdbHLX/+8+svY2G5AwDQaGxtKnpTqOKRZ9ylv828u+Q9SPFjAq9F96OHTsYN24cQUFBefbCS0hIYMuWLfn2wuvSpQtdunQxO2e2A/Xw4UM8PDw4cuQIAGvXrmXAgAHs3LmTcePGsWvXLurXrw9kOUw5nSqTyUR6ejpHjx7N5UBlj6NIkSIkJycTFBSEl5cXtWrV4uLFi5b4mp6JBuVdaV7FjUMhMRTRGXG2U2EwQWxKJmXbf86VpV8yadAHTPjmG+rVq8edO3dYuHAhGzduZOHChZhMJlJTUwtt/ADR0dE8fvwYDw8PXF1dxdcFQSA2RYfBaKKogw226tffDdHr9WRkZJj9A+BZkMLq2/Ny48YNTp48yaZNm8zKj0DWavHUqVN588032bt371P7LVojh0NiMJhMZpOnbBy1ah6nZnIkJEaeQMnIvMa81g5UYGAgAwYMYO3atbz33nsMHTqUokX/9x+kF3Wgjhw5QqdOnahfvz7u7u7/er+WbCYMMKr1G7g5aPjrxiOiEjNJ0SkorVIy6P12lO9cjU7vtaNr1665jvviiy/44osvCnx9GcsjBYH+ebl9+zaQ9eRoXr8n1atXR6PRcPv27ZfatPRVNEKNjE9Do1JgEkx5vq9WKoiIT5NkM9aCIuVGtVJByhkVejPhbAfq6tWrXL9+nfHjx7Nt2zamTp1q5kB99913VK1alSpVqogO1HvvvYe3tzdhYWEkJSWJk58iRYrQpEkTKlSowMOHD3n//fc5efKkeL1z586RlJRE+/btxXE86UCZTCbUajWNGzdGo9HQuHFj7t+/b+ZA+fj4sG3bNiDrX8guLi5iuYSck7OcWLqQJoA78L4bRDuAUBJKaB9TJPkxhpdydpnCRkoC/bMSFhYGwJ9//kmdOnVyvR8TE4Ner+fBgwcW+X4sKcAmxCiJTwBVZt4+RXw6JCqT2L37vsXG8LojRUFZakgxo0KXyLMdqKNHjzJw4EACAwOJiYmhV69ehIWFce7cOc6cOcNXX33F+fPnadCgAZUrVyYmJgalUknz5s3R6/XcuXOHzMxMsRJ49pNwmZmZ3Lt3T7xedu87yCpVsGLFCiC3A7Vr1y4EQaBFixacOnWKY8eOUaxYMbERLmRNurJLLiQmJrJv3z48PDxo0aKFuG34JK+ymXBe8l58fPxLvUZBMRgM1KlThxo1ahAYGGi2lRX2IIoWrb3QFvWg3ag5ZquBmXojj5J1DGxekU61/33lzxrR6/UcOnSI1q1by1t4/4IgCPzxxx+cPHmS8ePH51oNHj16NM7OzkyaNOmlfj+vQoC1v/mIH/fexMnRBq3GfGs6Q28kQ62jr1dVWlR1s8j1X2ekLChLBSlnVOgS+Y4dOxg9ejRBQUH4+/tjMpnEIou2trYsXryYVatWkZaWxs2bNzl8+DCTJ08WfaUFCxaYnW/hwoXMnDkTf39/Zs6cSYUKFXjw4AGQ1f8uNDSUrVu30rFjR7PjcjpQiYmJnD9/Hq1Wy8GDB4GsFaYaNWqgUqnErbrr168DMHXqVBYuXMi7777L1q1bn3q/r7qZcPa5cz6h+LIxmUzEPI5DY2NLUSeH56rJ89dffxEZGcn69etzrcDdSlZRutkH3Nz6CxkJjylStIT4np2NEpVSz+GQWLq9VcbqK5fn9Ze6Xq9Hq9Xi4uIiuf+wWILZs2fTvXt3Pv74Y7777jtq1arFvXv3+Omnn1iyZAk//fST2QMSLxNL/n42r1qSA9cfcTY8Hld7Dc7//xReYrqe+DQ9jSoUpVnVkmg0r7/3ZymkKChLDSlmVOgSucFgYPny5ZQpU4Y9e/aI/tPu3bvp3r07SqWS9evXP7P/tHnzZurUqcNff/2Vy4EKCQmhQ4cOuSZPR44coVWrVty5c4cKFSpw/vx5jEYjqampnD9/nvr161O9enXc3NyIjY2lcePGL3y/lnagcpJz79nBweGlnvtl06xZs6e+v3niB/m+5z/oZY/m5ZOXtyRlN8ASdOjQgVWrVvHVV1/h6emJra0tmZmZODk58eOPPzJy5EiL/g5ZChUwzrsKf/x9h5O347j7OBUBcLRV413DjUHNK6LChF6ftyP1X0b+HbJ+pJzR89yTRSqRb926FR8fH2bNmkWLFi1o2rQpGo2Gffv2sWfPHjZs2ECJEiWoVasWoaGhREREMG3aNLEEwdq1axk8eLA4EdFoNBQpUoTq1auL3lNAQACffPIJarUanU5HuXLlGDNmDP369cPZ2ZkzZ87QvXt37OzsuHXrFgEBAfTv35/mzZtz4cIFsQ5Ueno6VapUMSviFxwczMKFC/nzzz9JT0/Hzs6Ov//+m7p16+Z5v1OnTs3TgQoICHhpDlRedOvWzWLnlvl3/m1lUubZ0ev1nD9/Xqze37Bhwxcqv2GNxGXCw7Ss1VQPe4Gili+pJiMj84KkpaXRp0+fZ6pEbpEJVKtWrQgKCiIqKoqJEyfi4ODAkiVL6Ny5M+PHj6dx48aMHDmSmjVrcu7cOerXr09CQgJarZYxY8awfft2Ro4cSWxsLHq9HkEQUKlUdOrUiY0bNwLw9ttvc/r06VzX9vLyEsW2nE/hZU+gmjVrxoULF9DpdPlOoCpUqMDdu3dznTu/r8qSrVyeJOfe88t+cmv697P5ZcHPvDXwR6q9WVfcQjOZjBxb/iMRF4NYufsYnRo+vT7U48ePqVWrFmPHjmXcuHFm792MTqLz+x+SGnOXrlNXocjhvZgEgftx6XSrU4rPmlV4qfdmCfLbwpOqGyAV5IysGzkf60fKGRV6K5eGDRty5MgRSpUqhdFoFOtA7dixA39/fwRBYMWKFcyYMYPSpUsDcPXq1XzrQB07dozmzZtz4sQJ8bUWLVqQkpJC8eLFqVu3LgsWLKB3794kJCSIn8npQLm7u6PT6Th06JBZL7ySJUsSEhJCZGQkpUplNeQNDw+nadOmXL9+nZ9//pnRo0ebnfdJXrUDlZGRgU6ne6nnNplMrFy1khJ1W1PtzXpmFZKVKiVv9xrBxn8O88eKNXR/Z9ZTz+Xu7s7QoUP58ccfsbe3Z+DAgTg6OhIVFcUfP80m5toJqvf8muRME052KpQKBZl6I9FJGXg429HxzdJW9Uv5IgKzFN0AqSFnZN3I+Vg/UsyoUB2o7BpQ8+bNIyUlhfXr14t1oEaPHk1AQABDhw6lX79+Yh2omzdvPtWDiomJARCdKYCTJ0/i5eVlVuSyXbt2Zq1ccq5A1a9fX2zbkj15CgkJEZ/8O336NN27dwfg0KFDBAcHi+L7v/EqHKjgh0kcCI7hwr14Agf3finnzJOYKALO7cv37aMBC3EIWPjMp5s8eTKTJ0/O9fqN9XO5sX5unsdsGPnMp38lPM9Kn5TdAKkgZ2TdyPlYP1LOqFAdqK1bt9KrVy9iYmLo0KEDDRs2ZNGiRXh7exMUFES5cuW4ceMGa9aswdfXV6zTpNPpGDFiBEWLFiUsLIy1a9dy7tw58S8vW1tb7t27R4kSWU9tlS9fnvr167N3714yMzMpVaoUrVq1YvXq1aSlpXHlyhV8fHywtbUV6800btyYCxcu0KJFC06ePElmZibFihXDZDKJrWQ2bNjARx99hEKhQK/X4+zsTGpqKvHx8fmuRFjagbr0WMFfEUoyjGCrEjg2pcu/HyTz0pBdJxkZGZn/BoXqQHXu3BmTycTPP/+Mp6cnPXv2xM3NDT8/P1q0aMGuXbu4dOkSkydP5tdff83VC2/06NGMHz+eq1evYjQacXNzo2LFipw+fZry5csTGhqaNfCnPOKelpbG6dOnzZ7CA5g2bRozZ85EEASxOfG9e/d4+PAh8+fPFyuZ51VXaejQoSxZsiTP61nSgbr7OI0vN15BZzBS0skWBHgYeZ9iRYsRtOJHHgWfZPX6zbRr2kA8JjY2li5duqBWqwkKCnrmcgDenbpx404Ebb9ejJ3Wxuy9yBvnOfzLVwyZ+Ss/DLfgCpgV8jxbeFJ2A6SCnJF1I+dj/Ug5o0J1oHbs2AHAuHHjMBgMZr3wdu/ejZ2dHeXLl6d79+559sJr1aoVZ86cyXXeJ3vhlSlThrS0NB4/fix+plGjRvzzzz/Y2dnRsmXLXNK3SqXCYDCYOVBP9sIzmUyoVP+rzSIIAiaTiV9//ZUGDRowYMCAXGOzpAN19FYcyRkGKhSzR6H4X2sIfUYKURcPU75NX6KUJc2u4+HhwezZs+natSsXLlzg7bfffqZrTZkwji6dO3Ns1Rwa9RiGa7HiCIJAxPXzHPf/Htfy1RnxUTeL/sJIpaCkFN0AqSFnZN3I+Vg/UszIKupAvYpeeE+urCiVSrNJ04v0wjt58iRGo1H8s7+/P7/88gufffaZ6Eg9iSUdqODIBNRKEBAQBAHBJLB/Sk/x/Tv7ljN633JG53O8l5fXc18z5p+D7PznYK7XdSnxeFb0eO7zPQ8v8mShIAjs37+f33//natXr6LVaunUqRNDhgzJ92fqyeP/uZ/I4Rsx3I1Lx0Gr5p03itKianEctc/3HwcpuwFSQc7IupHzsX6knJHV9MILDw/Hy8uLOnXq4O3tTUZGhlkvPF9fX6pWrQog9sLr27cva9eu5fvvv+fmzZtm1bYbNWokbsep1WoSExMpWbIk8fHxODs78/jxYwRBEGs3PdkLT6lUYmdnR9u2bcU6UNliefZ1oqOjmT9/Pnv27BG/SLVazW+//ZZn42GwbC+8yAglScmg0ScX6DyvC8/b8yy7Hcju3bupWLEi9evXJzk5mSVLlrBkyRImT54stgDKC5MAf0Uo+OexEoMJNEoBowBB1x6w3F6gewXTC9XtkWKPKKkhZ2TdyPlYP1LMyGp64R0/fpzKlSszcuRI/Pz86NGjB1FRUZw7d45ly5axefPmXA5U3759sbe3JzU1VVxKc3R0JD4+nkePHpldRxCEfGszQe5eeDmPy+8cJ06c4M0336Rfv37Y2dkxY8YMTpw4wWeffcby5cvzvI4le+HpLkayJOg2xVztUCkVCCYB7+nrcXVyYuu3vSnm2YwZs37E561SZsetXr2aUaNGceHCBXHS+TrwvFt4q1evZvfu3SxevJiBAweKq4tJSUn4+Pgwb948QkND8z3vnqtR3LwdhntxtdhuA0BvNBERn8ElkzM/tvdEqXw2j0zKboBUkDOybuR8rB8pZ2QVvfDGjRtHUFCQmQO1cuVKtFotCQkJbNmyJU8HCnLXgYLcDpTBYMDZ2VkscQDmDhSY14GCLL8pPT2do0eP5utATZw40ey67du3p27duqxevZply5aZ+VHZWNKBalPTgx2Xo4iIT6eMqx1KpQK1jRaNgxMeb3fh7sE1xFxog7L+AFQqFYIgcOTIESZPnkzXrl2pUuXpRS+tjefdwlu0aBHt2rXj008/NVt61Wq1/Prrr3h6evLnn3+a/RxkYzQJ7LhwF1NmBg5F7DHq/rcNqwSK2Qpcu/eIf+4+onZpl2caj16vF+t05Te5l4rn9bojRX9DSsj5WD9SzEh2oP6fF3Gg8iItLU2UyfOaQFnSgXK0UfC1dxVm7QnhelQSGXojer2CGH0K4X+tAmDCV2OY8NWYXMdu3brV6vvlvSyedp8jRoxgxIgRL3zuv8a/8KF58rIryMs8H1L2N6SAnI/1I+WMZAeqAA7U8uXLWblyJREREdy+fZsKFSpw+/ZtOnbsmO/M1JIOFMDdFHj0SElmhgKjIKBUmE8kZV4vntfzkrEMUvQ3pIScj/UjxYxkB+r/eREHSqlUcu3aNZKTs6Tt27dv06NHD1avXp3vdSzpQMWmZLJ2wxUEbSZ13LUogUexjyhatBiJLXtx/+hG5vv+yie9e4graxcuXKBnz57Ur1+fdevWFej61o63tzdFihRhy5Ytud4LCwujQYMGLFmyhA8//DDX+yaTwIQt17gZnUzporkb16ZmGkjJMDKjaw2quz9bjnq9nkOHDtG6det8J9zyFl7hImV/QwrI+Vg/Us5IdqAK4EB9+umnfPrppwQFBeHl5UXt2rXZsGHDU+/Xkg7U32FRRCdlUr6oPUplVh0ogy4DfXoSUWd2U/qdrjjUaGa20ta4cWN+/PFHBg4cyO3bt6lWrVqBxvCqeJGJxddff03Pnj1ZunQpX331lbglGxMTw9ChQ/Hw8BAfCMiL99+uzLwDN0k1qnC114iT0EyDiYSUdBpXLkHjamWfuRipXq9Hq9Xi4uIiuf+wSA0p+htSQs7H+pFiRrID9f+8qAN15MgROnXqRP369XF3d//X+7WkA3U+PA6VEkyCwOPkTFIyDRzOUQfqwbHNDGy1mYH5HF+/fv0CXf9V8iJuULdu3fjmm28YP348S5cuxcvLi8ePH7Nz504cHBzYtWsXarU63xxaVinKvcel2PJPJHdidWjUCgxGAYVCQS0PR0a2egODwfDM45GyGyAV5IysGzkf60fKGVmVAzVo0CA8PT2pXr06U6dOzeVAdezYETB3oHbv3k10dDTr16/n8OHDZGZm4uDgQJMmTcwcqKSkJMaNG8eAAQM4dOgQZ8+eFVeZ8nOg7O3tGTRoEL/99ht6vZ5Ro0aZOVCHDx+mU6dOjBo1irCwMBITE4mKisLGxoaiRYvmeb+WdKDu3lOSkARR8SlkGv/9868zL+oGvf3228yePZu9e/eyb98+bG1t+eCDD/Dy8uLhw4c8fPjwqccXF6CDG1yPVxCbqUCrgSpOAlXtEjn394MXGpMU3QCpIWdk3cj5WD9SzMiqHKgpU6agUqlo3749vXr1IiwsjHPnznHx4kUOHDjAmDFZT48dOHCAP/74A8hacfrmm2+Ii4tDEATx8fycBRE1Gg0NGjRg4cKFzJ07F41GQ9u2bdm3b5/4mbwcKHd3d1JSUmjcuDGQ1ZQ459bR0qVLSUtL44cffhBf8/DwoFmzZvz999953q8lHagHf9/h0uEwBEGgiFaNUgE1xm1AYdQTPP9jMBnpNPAr/GeNQ6PRIAgCe/fuZcCAAWRkZHDo0CHeeuutAo3hVVEQN6hDhw5mGRQWUnYDpIKckXUj52P9SDkjq3KgOnfuDGStLiiVSmxtbUlISMDf3z/Xcdlba0qlko8++ggfHx/Kli0rFrL09/dn5syZeHh4IAgC586dY/Xq1TRs2JAzZ87Qr18/7O3t83Wg3N3defDgASVLluTgwYM4OzszfPhw7t69K27VLVmyhHfffZeGDRsye/ZsHj58yOPHjylbtmy+92tJB8rORo1JAJVSSc7NRpXGBoVShQBUrvWW2UpX/fr1cXBwICMjA3d399fmB/x1GeezIEU3QGrIGVk3cj7WjxQzshoHatasWcyYMYN169axePFiqlWrxq5duwgMDMTV1ZW2bdvi6ekJQNu2bUWJ/MmGvW+88QabNm1i69atomuUlpaGs7MzvXr1Ej8zdepUoqOj8x2Xp6cnOp2O4cOH07p1awAGDRrE6dOnUauzvgpXV1eGDh0KZNUWcnNzo1evXsydOzff81rSgQqLScbVXkOazkia3ohKoeD6nA/MPrNgzEcsyF0GCoCaNWsW6PqvEinUR5KyGyAV5IysGzkf60fKGVmNA+Xo6EitWrXo3LkzCoWC0aNH4+Pjg5+fH2fPns1XIs92oBo2bIiDgwPXrl3j0KFDFCtWTHSgXF1duXnzppkDdfPmTZRKJXq9Ho1Gw4wZM5gyZQp37tyhQoUKpKSkABAQEECrVq3Q6/X8+OOP2Nvbc+vWLXH8wcHB6HQ64uLiiI2NZdWqVdSuXTvf+7WkA3XrjhKFAUrYQJIO0o3P9jTY64iU6iNJ0Q2QGnJG1o2cj/UjxYyswoHy8vIiMDCQpk2bolKp8Pb2JjExkYoVKzJ37lxmzZrF9u3b8yyk+aQDpVarMRgMbNq0SbxGly5d+OWXX/jll1+YO3cuarUarVZLeno6sbGxeHh4iDPJ7CW5qKgoNBoN6enpZg5UpUqViIqKAuDSpUu88847z/UlWtKBijoeztqzDyhTzA6FIqsXXqnp63Gw1bB14geU9+7HsKHDGNi8otlxR48epWvXruzcuZOib9Tm+z0hJMbFcW7RcLSOzrz9yXg0bhVJSNdTxz6Jv1fMJiIiguPHj1OiRIkCjflFkUJ9JCm7AVJBzsi6kfOxfqSckVU4UCEhIXh6elKhQgWzQponTpxAEAS6du2abyHNnA5UWloavXr1Ij09ncjISPEaJUuWFPuNqVQqHB0dxRWm7NIE06dPZ/r06WZjMxqNZGRkiA7UiBEjuHr1qvj++fPnGThwIC1atMDR0ZE9e/awYMECmjZtmu/9WtKB8qrlwe6r0cSm6CnppMWkNKG20eLkVgKPt1oRcXQDlb781Ow68fHxTJkyhRo1atCiRQvm7L1BcoaB1ODD6NKS6ThxKfYuxQFQoCDMUIwlywNp26wBq1ev5ptvvinQmF8Ua9/Ce54JnhTdAKkhZ2TdyPlYP1LM6HnuRyE8rZR3ARg3bpzoDWUX0oSsJq8PHz5ky5Yt/Pbbb2KZAZ1Ox5AhQ8yk7+DgYFq1asXAgQNJSEjg+vXrHDp0CIB33nmHpk2bMmvWLKKjo/Hw8KBdu3YcOXIEnU6XZ32n7du307VrV1asWMGnn34KwI0bN6hRowZffPEFv/zyS5734uPjw5YtW4iMjMTDwyPX+3k5UGXLliU2NrbAK1AAOy4/xO94OOk6I/YaFUnJiahsi6DUpXDo264FPr/Ms/EsEzwp/8tMKsgZWTdyPtaPlDNKSkqiePHiJCYm/uvf31ZbSPPatWu0bt2aTz/9lO+//56+ffua1WHKzMxEq9Wi0WgoU6YMAKGhoZhMJoxGI0qlkiNHjtCqVSvRgcomZyHNZ6kwnd3WJb/+c5buhacCvIvC5Tgld5JBrYDyNqnU8RA4VOCzyzwrz+NoSdENkBpyRtaNnI/1I8WMCt2BypbIr169yvXr1xk/fjzbtm3LVUjzu+++o2rVqlSpUkV0oGrXrs0333zD/v37AdiyZQvx8fGsXbuWgIAA8Rp2dnZ8//33/Pjjj7i7u+Pk5MT9+/cRBEF0oO7cuYONjQ2xsbFUqFCBuLg4APr378/gwYNp0qQJycnJFClSBK1WC2S5VZcvXyYiIoIqVaowYMAA/vrrL2rVqmU2CcuJJR2oJ9HpdBw48Bfe3lkz/36d4tl0IYI/T99DpRAo7mRHSvRd9sweikOpSnh2G4pr2aqkpKVzedk44u7dxL1aPVp/MReFQoHeYCI6KZMv21Zh8qAeeHh4EBgY+FLHLBWeZQtPyv8ykwpyRtaNnI/1I+WMCt2Byi6kefToUQYOHEhgYCAxMTFmhTTPnDnDV199xfnz52nQoAGVK1cmJiaG8+fPExcXJ2753bp1S3xCbty4cfTs2ZNff/2Vf/75hyJFipCSksL9+/eBrFIIBw4cELfvKlasiE6no3jxLN9nzZo1AHTq1IkjR44QFBSEi4sLVapU+d8XolajVCpRKBTcuHGD8ePH07x5c7Zv357v/VrSgcoLhQLR/0rTw66r0dioVZRwypoEBu9fi9bBhfdG/0RkqoCNWoVJqaF2p4EELf6aqBvniQ27SonKbxKTrKOUqz0Pzh/i0qVLTJ48WXK/EP+GJeR1KboBUkPOyLqR87F+pJhRodeB2rFjB6NHjyYoKAh/f39MJpNYiNLW1pbFixezatUq0tLSuHnzJocPH2by5Mmi/5RdByrbgSpTpgzOzs6i/7R69WqGDRvG3Llz0ev1REdHM2/ePLZv346joyNubm4AtGzZUuyDl5iYyJEjRwBYuXIlLi4uov9kY2MjFtLcvHkzAMOHD2fp0qWMGzeO77///qn3a8k6UDmJTckkOCKBkEQF3Vxd//Xza0e/l+97++d9Yfbn7DWnHj16FGSIryUvU16Xcn0UqSBnZN3I+Vg/Us6o0OtAGQwGli9fTpkyZdizZ4/oP+3evZvu3bujVCpZv379UxsJ53SgIiMjycjIEN/L9p8A0YEqUqQId+7coWfPnnn6T+fPn8doNKLRaDh48CDvv/8+1atXx8PDg4cPH9KkSROza69cuRJXV9d/nTyB5R2oDCMERSoITlCSbgCB3IK8zItjifpTUnQDpIackXUj52P9SDGj53GgLPIU3tatW/Hx8WHw4MEsXboUb29vzp07x4YNG9izZw8bNmygRIkSZk/gZdeAunTpkpkD5eHhQWRkJAEBAbRp0wY3NzcmTpzIH3/8Qc2aNbl58yaPHj3CaMzqtHv69GkaNWrEmTNn+OCDD9BoNAQFBREUFET//v2pUqWK2GS4SZMmnD59GhcXFyIiIgBYtmwZQ4cOFUX0wYMHM2HCBGxtbcWVrSex5FN4OoOJ7/fc4GRYHE52apxs1cQ+jkWptuXutbMEr5qCa+V6vNW5HyXfqEHSowj2fD8Ioz6Tej2GUbJxV9QqJYt618HZTkNScgq1a3vyab/+DB86BEEQKFmy5DPJ9FLlZW7hSdkNkApyRtaNnI/1I+WMCv0pvOxyAElJSWY1oPz8/Bg5ciRz5sxh6dKlrF27FjCvAfWkA5U9sfnwww8pX7484eHhTJ48meXLl3P06FEg60m6MmXK8ODBA8qXLw9Ao0aNWLlypVhxHLJWxhITE80cKIVCQbdu3YCsIpqDBw8Wr200GlmyZAlLliwRr50XlnSgTofHcu5uAu7OWuxt1JgEEyZ9BkWdHTh5cCVO5WrSeOAM0vWgVKpwdS9PDa+eXNsfyKXt/jSu2YauDd6guFPWStjvv/1KclISnw/8THx60VqQQiHNbKToBkgNOSPrRs7H+pFiRoXuQDVs2JAjR44QEBAg1oBauXIlWq0WX19fli9fzrfffiuuQPn4+Jj1wRswYMBTa0AFBQWRnp5OVFQUer0eDw8Pli5dyvjx481WiXI6UJcvX8ZkMjFz5sxcNaCy++CtW7eOevXqcfbsWaZOncrWrVuZMWMGPXv25MqVK/neryUdqKCQaAxGE1qNEr3RSGqmgf1Tepp9Zs+4vF0no9HAienvcwIY/8R7T2tNU1hYeyHNZ0HKboBUkDOybuR8rB8pZ1SoDtSrqAG1fft2GjRowPz581m9ejVFihQhPT2d9957T3wC70VqQOV0q7Kxs7MjIyOD8+fP07Jlyzzv2ZIO1KVbStJT4UZqKkl6MJgKdDqrRu6FJ/MqkTOybuR8rB8pZlSodaCya0CFh4fj5eVFnTp18Pb2JiMjw6wGlK+vb5598DZt2sRHH32ESqVi4cKFBAQEEBkZKW73AVy5coVTp04RGhpKRkYGDx8+RBAEwsLCxM88WQMqJSUFpVLJ8OHDGTFiBHq9Hnt7e+zt7cVJU7t27Zg/fz6VKlXi/v37GI1GunfvDiCWSsgLS9aBCt5/k5BzD9AbTChVCuw1Sqp/vQF9YgxhS4eDUo1Hxar8NH0Sb731Fv9cC+GP33/jyF/7APD19aVmzZpotVqqVauWZ4V2a0EKW3hSdgOkgpyRdSPnY/1IOaNCrQOVXQPq+PHjVK5c2cyBioqK4ty5cyxbtizfPnirVq0y2w7LdqCGDh1Kz55ZW1dGoxGDwcD9+/exs7PDy8sLT09PFixYQHp6OnZ2drlqQAE86cs/+ed33nkHhULB7du3xdey++s9fvw433u2pANVyrUI6XoTtioltmolAgIqWy32ZSqjtLVHMBr5esFq+nSqB0CNGjXo7dOFypUrEx4ezkcffYSLi0uBxiDz/EjRDZAackbWjZyP9SPFjArVgdqxYwfjxo0jKCgoTwcqISGBLVu24OPjk6cDtW3bNiDvPnjZ2Nvbo1QqefTokbi1d/36debPn8+DBw+oUqWKmf8E4ODggCAI+Pr65nKgsksk3LhxA5PJxN27d1Gr1bi6urJ//366deuWq8zCqyI6MQM7jRK9QSDDYEKlBENGBhmP7mPKTEOhVDNv7Kc4Ro2iZMmSpKSksHbtWu7cuQNkrQhmr6K9DkhhFUpGRkZGRvq8lg6UwWAAYObMmaxbt44iRYpQs2ZNlEql+GTZizhQ1apVo1ixYvj7+zNx4kSMRiOzZs1CrVbTsWPHfO/ZkhJ5VFI6bg62pGToeZyqxygI3PnpA/F9wWQgIvQqgwYNyvP4jz/+uEDXf9W87iK5lOVKqSBnZN3I+Vg/Us6oUCXynA7UoEGDSE5OZuTIkWg0Gnx8fMwcqI4dOxIaGkqrVq2YNm0affv25erVq7z77rs4OTmxZs0aFixYgF6vF1eNIKvdislkIjAwkLfffpvDhw8TGhqKWq0mMDCQAQMG5OtAffvtt2zevJnDhw+TkpKCSqUSa0g5OjrSoEEDpk2blksK12q1REdHU6JEiVz3bEmJPD5KycN4BQYTKASwsV6F6aUgFZFcinKl1JAzsm7kfKwfKWZUqIU0O3fuTHJyMsePHyciIoKJEyfi4ODAkiVLaNq0KUeOHOHLL7+kWLFiuLq6cu7cOerXr09CQgJarZbExMQ8JyMKhYKFCxcyYsQIvL29CQoKwtHRkfj4eIoVK8abb77JwYMHOXjwIK1bt861AhUQEEC/fv2oWrWqWSHNU6dO4erqSkREBOnp6ZQsWZKMjAwUCgUVK1bEycmJ69evU7duXf7+++8879mShTRXn7rH7L03sVEpsNVkzZ7SU5LQaDRcnfshgsnI9NX7GNG+rniMwWCgfv363L9/n7CwMFyfoe2LtfC6b+FJWa6UCnJG1o2cj/Uj5YwKtZBmTgeqVKlSGI1G0YM6fvw4CQkJODs7s2LFCmbMmEHp0qUBuHr1KkOGDGHMmDFMnTrVzIH6/vvvGT58OJs3b2bEiBF4eHhQrFgx0tLSRA/q+vXr1KxZU+y596QD5e7ujl6vJyQkhHXr1ok930qVKkVkZCSnTp3i2rVr2NnZkZCQID6tFhERQZkyZXjzzTfzvWdLSuTx6QZs1UqMJgG9UUClAJMJ0uNjMOnSAQWrf5rMOyWmUa5cORISEvjjjz+4d+8eAOfOnaNDhw4FGsOrRCq/jFKUK6WGnJF1I+dj/Ugxo0KVyLMdqHnz5pGSksL69etFD2r06NEEBAQwdOhQ+vXrJ3pQN2/eNPOgnnSgIKsZcLYH1bRpUwICAmjatClz5sxh9erVCIKAQqGgWLFi4lhyrkLVr18ftVqNwWDAy8sLgJCQEB4+fEjJkiU5efIkarUapVJp5kb9+eefQFZx0PywpAMVEZ9GSUdbkjINxKfpMJrMHSgQuHn+GG3atMnz+OwnF18XZAdKxtLIGVk3cj7Wj5Qzep57eulbeFu3bqVXr17ExMTQvHlzrl69ynvvvce2bdtwcnKiXLly3LhxgzVr1vDdd99RunRpqlSpwrVr1xgxYgR2dnZiHSij0UjZsmVp2bIly5cvZ/fu3Xh7e5OSkkLx4sXJzMzExsZGdJjUajUffvghy5cv58yZM/Ts2ROVSsXRo0cpXbo0rVu35vDhwzg6Oop1oN544w0UCgWtWrWif//+1K1bl3feeYcHDx4QHh6OwWBAoVDw4MEDPDw88rznqVOn5rntGBAQUGAHavMdJRceK9AZwSSAQgGhP3Qu0Dmtma1btxb2EGRkZGRk/qOkpaXRp0+fwtnC8/Pzw8vLi6ioKK5evcrAgQMJDAwkJiaGjh07snHjRr7++muKFi3KV199xfnz52nQoAGVK1cmJiaGoKAgs9WcW7ducevWLezs7PD29gayShLY29uLnytRogQtWrSgevXqTJs2jSVLlpCWlsbdu3e5c+eOuE34b3WgqlevzqeffsqKFStQq9XY2Nig1+sZOXJkvpMnsGwhzdiTdzm1PxS1RoFWnbWtWGPchiwHak5vBMHEt39sZ2y3xuIxaWlpNG7cmIiICEJDQ81W5awd2YGSsTRyRtaNnI/1I+WMCrWQ5o4dOwAYPXo0giDg7++PyWQS3aTsIperVq3C09OTmzdvcvjwYSZPnky/fv3MJiLZHlSZMmVwdnYWX9+7dy8pKSlUrFjRrOjl9evXmTp1Kg8ePMjlQCUmJooS+L1793BxcRHrQLm7u+Pu7k58fDyrV69m9+7dtGnThs8++4wLFy6IzZHzw5IOVIrehFqlwGQCo1FAqQTBBJlJcZj0mYDA7j9/5aMmFShdujSJiYksXbqUyMhIBEEgODiY1q1bF2gMr4rXffKUEym6AVJDzsi6kfOxfqSYUaE3EzYYDCxfvpwyZcqwZ88esQ7U7t276d69O0qlkvXr1+dbBwrMPajIyEix2CVk9cKrVKkSt27dwsPDA0dHR7p06UKjRo3EWlBPPoV3/vx5jEYjGo2GgwcP8v7771O9enU8PDx4+PAhTZo04cCBA5hMJiIiIqhWrRqhoaHUrVuX+/fvixPAvLCkA3U3NhV3J1uS0g0kpOvzcKDg/F/bqF59W57Hd+nSpUDXf5W87v4TSNsNkApyRtaNnI/1I+WMCtWBgiyPxcfHh1mzZtGiRQuaNm2KRqNh37597Nmzhw0bNlCiRAlq1apFaGgoERERYh0owKwfXvYk5JNPPuGnn37Czc2N9u3bc/jwYZRKJSVLliQpKYn4+HgUCgXNmjXj6NGjnDlzhg8++ACNRkNQUBBBQUH079+fTz/9lMDAQBQKhXhuNzc3Hj58yOzZs5kyZUqeX+Dq1avF8T2JJR2ojXeUXH6sIOP/HSiAW7Ol6UDJ/pOMjIyMTGFSqA4UIG55DRgwgIkTJ/LFF1+wZMkSFi1axPjx45kzZw6dOnWiZs2aKBQKPvzwQ+7fv8/8+fMZM2ZMrn54AKtWrWLnzp08fvwYk8mEUqmkYcOGXLp0iczMTFxdXYmPj2fChAkANGrUiJUrV9KqVSuzCVFe88Xs10wmk/jZSpUq8eabbzJ9+nTq1KljtoX4JJZ0oB6dvMuZ/TdRqxVoNSrg/x0otYorcz9EMJkY57uOCb1bicfEx8fzzjvvEBUVRXBw8FP9LWtCClt4UnYDpIKckXUj52P9SDmjQnWgIOuR/yNHjuSqA7Vjxw78/f0RBCHfOlCQ1Q8vrzpQ2f3wPDw8cHV15fLly9y5c8esDlTlypXFceT0oG7fvo1Op2PFihUEBgaa1YF6+PAhp06dMpto/PTTT3Tr1g2A4sWLExUVle/9WtKB0hkFVEolJiGr/tP/l6dCl5aCYNCDYOLs4d2kd30bJycndDode/fuJTY2FoAHDx4UWh+/5yV7C08KEykpugFSQ87IupHzsX6kmJFcB+r/ed46UDn73Q0fPpyBAwdSrlw5Hj169NRJiCUdqNuPUijpZENSuoGkDEOWAzXH3IE6vH4ZpdYvy/P47CcXXydeZxdKym6AVJAzsm7kfKwfKWdkNXWgOnToQMOGDVm0aJHYfiVnHShfX19sbGyArL80R4wYQd26dcVeeDqdjri4OIoXL05kZCR79+4V60C5ubmh0+koU6YMycnJogP1zjvvcOzYsTzrQHl5eXHw4EG6du0q9sJzcXGhXLlyeHt78+OPP9KtWzdOnjzJtGnTsLGxYfDgwRgMBr7//nsmTpyY5z1b0oFaf1tJcLyCdAMY/j+pMIk6UNnILpSMjIyMTGHwPA6URXrhmUwmfv75Zzw9PenZsydubm74+fnRokULdu3axaVLl5g8eTK//vorU6ZMAWD69OkMHTqUt956K8/JCMCiRYsYMWIEkLUKdeLECRQKBcWLF6dLly6UK1eOqVOnkpqayunTp82ewgNYsWIF/fv3R6lUir3wEhMTuXnzJsOGDePHH38kKSmJMWPGsHnzZlJTUylatCjR0dGUKlWKiIiIPMdlyV54K07e5af9oagUYGeT5UClpyShUiq49lMfBJORkT/6MX1gV/GY+/fv06pVKx4/fsylS5demy28bF7nLTwpuwFSQc7IupHzsX6knFGh98IDGDduHAaDgYCAANGB2r17N3Z2dpQvX57u3bvj4+MjrkD5+PgwZMgQ+vXrx9SpUwHMPKiEhASxFx5k1ZNSKpViLzzIqgP13Xff5VkHChA/5+/vz6effgog1oLKLpPg5OSEn58fDRo0YN26dUyZMoU2bdoQGRlJZmZmnq6TJR0oEwqUCgUgIPx/JXIAk0GHYDKCycj9sBAUCgVqtRpBELh165bYUTopKem1+AF/nSdNeSFFN0BqyBlZN3I+1o8UM7KKOlCrVq2iZ8+eXLt2TXSgZs+eja2tLYGBgQwZMkR0oCB3LagnPai+ffuKE6DsawDMnDmTdevWUaRIEWrWrCnWgQJy1YLKJmevu5z/P5vg4GCmT5/O6dOnxUKdLi4ueU6SwLIO1K2oZNwcbUjOMJCSmeVA3X7Cgdr62w+4/PZDnsc3b968QNd/VbzO3lNOpOwGSAU5I+tGzsf6kXJGz3NPFplA7dy5k/j4eMLDw/Hy8qJOnTp4e3uTkZFBs2bN8PPzw8HBAV9fX6pWrQpkNb0dMWIEffv2NasDtXDhQgICAoiMjGTt2rX/G7hajclkYunSpWi1WqKjowkNDaVkyZLY2dkBcOfOHWxsbIiNjaVChQqkpKSgVCoZPnw4I0aMEPvh2dvbo9VqgaxtviFDhqDRaKhcubK4Qpa9YpUXP/zwQ57bjvv37y+wA/XggZKUVMg0ZFUjlyq7d+8u7CG8VA4cOFDYQ5D5F+SMrBs5H+tHihll7948CxaZQPn5+dGkSROOHz9O5cqVGTlyJH5+fvTo0YOoqCjOnTvHsmXL2Lx5cy4Hqm/fvrnqQGW7R0OHDqVnz54AKJVKFAoFSqWSlJQUSpQoQaVKlTh27Bjp6eliyxidTkfx4sXFc/1bP7yNGzeiVCoxmUxoNBqcnZ1JTU3l/v37+d6vJetARR0P55+/bqFQgpNWhYKsOlAqBK7N+wjBZODTCfNY8HV/8ZgrV67QqVMnkpKSOHXqFNWqVSvQGF4FUtnCk7IbIBXkjKwbOR/rR8oZFXodqB07djBu3DiCgoLMHKiVK1ei1WpJSEhgy5YteTpQkFUHCnI7UNl1oCCr6KVCoSA8PNzMgapZsyYPHjygSpUquTwoBwcHBEHA19c3XwfqwYMHZGZmilt72fWfNm/ezHfffZfnSpMlHSi1SgWKrK1GhQCIO44COad+arVaHLMyu1gUoFKpXosf8NdhjM+DFN0AqSFnZN3I+Vg/UsxIdqAK4EBt2rSJ9PR08c8HDhxg7NixeHt7M3z48Dzv15IO1M3oZNwcshyo5EwjJkEg7AkHauWssaycNTbP4xs2bFig678qZAdK5lUhZ2TdyPlYP1LOyKocqEGDBuHp6Un16tWZOnVqLgcqu3hlTgfq6tWrtG7dmnbt2jF27Fh27NjB2rVrCQgI+N/A/9+BCgwMZP78+dy7d49JkyZRqVKlf3WgJk+eTNmyZXFycmLkyJEUKVJEdKAqVaoEwIcffsi2bdvEydTKlSspUaJEnvdrSQfq7j0l6emg1yswmuDldy60DmQHSuZVI2dk3cj5WD9SzMiqHKgpU6agUqlo3749vXr1IiwsjHPnznHx4kUOHDjAmDFjgKwg/vjjDwB8fX159OgRa9asYc2aNeJ5x40bZ+ZA2djYYGNjQ58+fRAEATs7O0JDQ5/qQKlUKpycnGjTpg2CIFCqVCmz1alLly4xe/ZsgoKCMBqNFC9enNjYWCZNmoSfn1+e92tJByri2B0uHQpDUAg42alRKkA7bgMKk4Hgnz8Gk4FuQybwx4yxYhmDQ4cO0bdvXzIyMjhy5Ah16tQp0BheBbIDJfOqkDOybuR8rB8pZ2RVDlTnzllVs3fv3o1SqcTW1paEhAT8/f1zHZe9ndaoUSNsbW2pV68eX375JU2bNuXAgQN89dVX4mc9PDxQq9V4eHjg5+dH5cqVOXnyJH369MnXgXJ3d0ev1xMfH89ff/2Fs7MzI0aM4MKFC7i7uwNw/vx5SpQoQWBgIGXLluXEiRN89tln+Pv7M3PmzDwb81rSgbLTaDAJoFYqUeZ4XalWo1AqEVBRtlI1cdUNoEaNGhQpUoSMjAyKFy/+WvyA63Q6yUyiQJpugNSQM7Ju5HysHylmZDUO1KxZs5gxYwbr1q1j8eLFVKtWjV27dhEYGIirqytt27bF09MTgLZt24oS+YABA0QHasCAAcyZM4fhw4ebFdJ0dnYmLS2N9evXi+7UpUuXzByoJ8luNNy7d29at24NwJQpU+jQoQOOjo7itXPyxhtvsGnTJrZu3WrmOeXEkg5UaHQSxYrYkJJpIE1vRKlQcP0JB2rR1/1Y9HW/PI/P/n5fB6TgQUnZDXiS9PR0NmzYwKlTp1CpVLRq1YouXbqgVlvkPysvjexsUjMyuXz7MWGPUlEoFNRwd+TN0k6oVcp/OYOMJfkv/Q69rkg5I6txoBwdHalVqxadO3dGoVAwevRofHx88PPz4+zZs/lK5E86UFFRUURFRZmtUKSnp2Nra4u3tzdxcXHY2tqSmprKJ598Iq7G/PrrrwwbNoyTJ0/y9ttvc+vWLQDWrVtHx44dcXJyYsaMGdjY2JCcnAxkrZRFR0fTsGFDHBwcuHbtGocOHaJYsWJmW305saQDFRauRNBDSRtI0kG6MXfhT6kgJQ9Kim5ATm7cuMEPP/xAYmIiFSpUwGg08vvvv+Pu7s6kSZMoW7ZsYQ/xqUSnwye/HiYmXYHp/xep1UooZS/QqZwJ17xr5sq8QqT+OyQFpJiRVThQXl5eLF26lKtXr9KxY0e2bdtGYmIiFStWZO7cucyaNQs/Pz+qVq1KlSpVRIm8du3afPTRR3k6UCVLlhT//927d9Hr9YSGhmIymUQnKvvpvLy4d+8eCoWCR48e0bp1a1QqFe3ataNmzZpiuYJly5axf/9+UlOz/lWa3ax448aN+Z7Xkg5U9PFwAs8+oHQxO8ooFAgmAY/p63G01bBlUk/KeX3MiOEj+axZBbPjjhw5Qvfu3dm9ezdNmjQp0BheFVLYwpOyG5DN3bt3+eSTT3jzzTf5/fffqVKlCgAXL16kf//+zJ49m4sXL+Ls7FzII82b6IRUBvn9TbqqCG+U0mKr/v8ekzojUUmZnMp05MeOtbC3se6VNKnyX/gdet2RckZW4UCFhIRQo0YNBg4cSGBgIDExMfTq1YsTJ07w888/k5GRwVdffcX58+dp0KABlStXJiYmhvPnz9OmTRsWL15M2bJlWbduHRMnTqRjx47s3LlTvMbFixcRBIEtW7ZQp04dHj58yOHDh/n2229ZunQpdnZ2DB06lKFDh4rHrFmzBkEQ2L17t+g/JSQkmP0AlClThh9//JHTp09z+vRp4uLimD59Oj4+PvneryUdqLaepdh9LYZHyXpKOtmCEtQ2WrROjrjXaUnE0Y1UHPOp2XUeP37M5MmT8fT0pHnz5nm2q7FGpLKFl5GRgU6ny1WkNT9et4nj77//jkqlYteuXWb/QGjYsCG7d++mUqVKBAYGMnLkyEIcZf78fTuBxxkKqpe1R6NSia8XsVVS1lXFrUepnL2bhFfNkk85i4ylkaJfIzWkmFGhO1CQtX0mCAL+/v6YTCZxSd/W1pYmTZqwbt06PD09uXnzJocPH2by5Mn069fP7BzBwcEsWLCAevXqmS2r7d27l4SEBCpUqEDXrl0BqFChAi4uLkyaNEmUyHOSmJjIkSNHAKhXrx4uLi4sX76cGjVq4O7uLkrkCxcuFK99+/Ztxo0bx7fffvvUe7WkA1XG2YYB75Rj6d/hhERnbTNmpCvY/U0r8TPvt2uR7/HZbpeM9fK6TRy3bNlC7969sbOzy/Xz7eHhQbt27di0aZPoNFobx0NjUSkFlIBJMO+PpFZlFek9FfaIFlWK5n0CGYsiZb9GKkg5o0J3oAwGA8uXL6dMmTLs2bNHLKK5e/duunfvjlKpZP369fkW0QTzQpqRkZFipXCA7du3U6lSJW7duoWHhweOjo506dKFRo0aiRL5k0U0z58/j9FoRKPRcPDgQd5//32qV6+Oh4cHDx8+NNvmunbtGitXrsTV1ZXvv//+X+/Xkg4UZLlPqgwlSSkKMowFPp2MlfG6uV9xcXHEx8fnO+7MzEwiIyOt9r7uRSpRKuBR7KM830/LgBu3Uti9O+wVj0wmJ1L0a6SGFDN6HgdKITzrPsNzsHXrVnx8fJg1axYtWrSgadOmaDQa9u3bx549e9iwYQMlSpSgVq1ahIaGEhERwbRp0+jbty+AWTPh7FWcTz75hJ9++gk3Nzfat2/PwYMH8/Sd+vTpw59//smZM2f44IMP0Gg0BAUFERQURP/+/enTpw/r169HEARUKhUZGRm4ubkRGRkJwPLlyxkyZAhGoxGj0UjNmjUZNmwYPXv2xM3NLc/7zWsFqmzZssTGxhbYgUrXGZm07RpXIpIo7mBDEY2SR7Gx2NhquXHqL0LWz6FP34+ZNOEbSpUqRWJiIn5+fnz//feMHDmSqVOnFuj6Ms+HXq/n0KFDtG7d+pmXgl+3Lbz33nuPjIwMDh8+nOs9o9FIjRo1aNmyJUuXLi2E0f07c/beYNv5u9QsWxyF0nx7WxAE7j5Op0+jsvR7p3whjfC/jZT9Gqkg5YySkpIoXrw4iYmJ//r3t0VWoH755RcgqyTAxIkT+eKLL1iyZAmLFi1i/PjxzJkzh06dOlGzZk0UCgUffvgh9+/fZ/78+YwZMyZXM2GAVatWsXPnTh4/fixK4wDvvPMOFy5cwM7Ojvj4ePHajRo1YuXKlbRq1cpsSS4iIkLcetDpdJhMJhwcHMT316xZY7alEhwczIgRI5g+fTrR0dF53q8lHaig0DiuR6VQxtUOW7UKk2DCqM+giLMDkUcCKVbjbXqMmEL58ln1qYoXL8748eMxGAzMnz+fsWPHUqxYsQKN4VXwuk0i8kOv16PVanFxcZHcf1iyGTp0KD169GDz5s306tXL7L1ffvmF8PBwhg4darX371XTnd3/3CUxw0DRIua/tzEpmTjZaWhd091qx/9fQYp+jdSQYkaF7kA1bNiQI0eOUKpUKYxGo9hMeMeOHfj7+yMIAitWrGDGjBmULl0ayCpdkLOZcM5Gwt9//z3Dhw8Xmwl7eHhQvHhxIiMj2bVrFy4uLmIj4fj4eLHyeM5Cmrdv30an03HgwAHOnj1LgwYNgKwn+0JDQ4mMjKRUqVIcPHgQgKlTp7J161YuXrxIx44dzZ4AfBJLOlDHQmMQTCY0KgXpegMp6Xr2T+n5vw/E3Mfn7Sr5Hl++/Ovxr+jXzQPKDym7Adl06tSJPn368OGHH7Jx40a6d++OXq9n3bp17Nmzh6+//pq33nrLar8DT3d7GriZCE43kJRhwEmrRkAgKd2IrVpJv3fKUc7F1mrHL3X+C79DrztSzqhQHajsIprz5s0jJSWF9evXi82ER48eTUBAAEOHDqVfv35iHaibN2+aeVBPNhKGLAk8u5lw06ZNWbduHQB169YlMzOTEiVK5CqiuWLFCvr3748gCNSvXx+VSoWtra04eQoJCSEmJgalUsnp06fp3r17nveUmJhIjRo18r1nSzpQwbeUpKbC1ZRUUvRglHvhvRZI0Q3ISY8ePXBwcGDXrl1iiY833niDMWPG8M4771h9nq08oGRCEhcfK4iOV6AAShcReKuogG1kPLsfXirsIf7nkfrvkBSQYkaF6kBt3bqVXr16ERMTQ4cOHWjYsCGLFi3C29uboKAgypUrx40bN1izZg2+vr7Y2NgAWSsQI0aMoG7durz77rs4OTmh0+mIi4sTV5v27t2Lt7c3KSkplC9fnri4uFzX37dvH97e3pw5cwYfHx9sbW0JC8uSQRs3bsyFCxdo0aIFJ0+eJDMzk2LFimEymZg+fTpDhw7l2rVrTJgwgWPHjhEfH0/NmjW5efMmZ8+epW7dunnesyUdqAUHQ1l18h56owkbtQq1UkFGShKG1ARClwwCFFRt0IxlP39P7dq1uXfvHosXLxb9k4CAAN57770CjeFVIKUtPKm6AXkhCALx8fEolUpcXFwKezjPRM6M1Go1qTojSgVy3Scr4b/2O/Q6IuWMCtWByi6iGRUVxZkzZ6hQoQIjR47Ez8+P1q1bs2vXLi5fvsyGDRvYvHkzU6ZMARAnMLdu3SI+Pp74+HjxnBEREQDcvHkTb29vHBwcmD9/Pp9++ilarZaiRYvSuXNn/vnnH1atWoW3tzdpaWlERERw584d8TwdOnTgwoULHDlyBI1GQ9OmTbl37x4PHz4UPzNkyBCOHTsm/jk4OBjgqX85WNKBKuFkR6ZRwFalxEalREAABdi5uqG0sUMwGfn0qxnUq1cPgEqVKvHjjz+yb98+7t27R/PmzV+LH/DsLTypTKSk6Abkx9O2t62Z7Iz+/99wMlbGf+l36HVFihkVqgO1Y8cOAMaNG4fBYCAgIEB0oHbv3o2dnR3ly5ene/fu+Pj4iCtQPj4+DBkyhH79+olPjuX0oBISEsx64WVv9z18+FCc3Hz99dfi5OfJRsIAKpUKg8Fg5kDt2rWLTp06ieP4+++/AQgKCsLLy4tatWpx8eLFp96zJR2oe7EpFLFRkmkQSNMZUOTRC29S75ZMyud4a2+p8SSvuwslZTdAKsgZWTdyPtaPlDOyijpQq1atomfPnly7dk10oGbPno2trS2BgYEMGTIk3154kNuD6tu3r+hA5STbgfL09CQhIcFswpDTgcpJzsrc2U/z5eTIkSN06tSJ+vXriwU2n4YlHagrt5TYmEBAQZIBXn7RCevC2t2ZZ0WKboDUkDOybuR8rB8pZlTovfCymwmHh4fj5eVFnTp18Pb2JiMjg2bNmuHn54eDgwO+vr5UrVoVQOyF17dvX7M6UAsXLiQgIIDIyEjWrl0rXmP//v0MGTKEdu3acf78eWbOnAnAZ599Jn7m+vXr4soSZE2WNBoNLVq0wGAwoFarKVWqFLa2tuLKx+HDh+nUqROjRo0iODiYvXv3olAouH37NhUrVszzfi3ZC+/6/puEnH2ATjBhpwG1QknVrzZgSHrE7aXDQKGidJWaTBs3Cnd3dxITE1m/fj3btm0DsiaR2dXaXwde9y08KbsBUkHOyLqR87F+pJxRoffC8/Pzo0mTJhw/fpzKlSuLDlSPHj2Iiori3LlzLFu2LE8Hqm/fvrnqQGU7UEOHDqVnz6xH+F1cXFi/fj0rVqxAp9Ph6upKeno6x48fF8sh1KhRI9eWkIODAxUqVODq1aukpqbSrFkzcdsRYOXKlaSlpfHDDz+YHffxxx+buVE5saQD5eFqT7rehK1aia06y4HSaLU4OFVCaWuPYDTy5bwVfNapnnhM7969qVy5MuHh4XTt2vW1kXulhBTdAKkhZ2TdyPlYP1LMqNDrQO3YsYNx48YRFBRk5kCtXLkSrVZLQkICW7ZsydOBAsTVkycdqOw6UJDlWI0bN47evXtTpUoVVCoVS5Ys4datW+Jn+vXrZ9Zfz93dHUEQuHDhAitWrGD06NEsXboUrVYrbtWtWLGCFStW8OuvvzJt2jQqVarEiRMnzBoZv0oeJmZgb6NEZxTIMBhRKhToMjJIj7mLKTMNhUrNnFEfoQkfjpubG8nJyWzatEmU57dv3877779fKGN/Vl73VScZGRkZmf8er7UDtXz5cm7fvs2aNWuYOXMm6enpeHh4iO8/6UA1adKEhIQEzp8/L37m0KFDmEwmGjduLL4WHBzM9OnTad68udkTevlhSYk8JikDNwdbknUGYpN1mASBOz/9TyIXjAaibt9g5MiReR7/6aef8umnnxZoDJbmdRfHcyJluVIqyBlZN3I+1o+UM3qee7JYL7xevXpRt25dmjRpItaBOnfuHF5eXty6dYtRo0blWQfqSQfKaDSKdaDWrl0rbuFNmjSJxYsXs2HDBqKiovjkk08A+Ouvv2jTpg0A48ePZ8GCBWaTm6pVq4rNiY1GI1WqVKFBgwYEBAQAEBkZSZUqVVAqlaSmpqJWq9Hr9ezevTvfekpTp07NUyIPCAgosES+LVzJ6UcK9CZAAKUSQmZ1LtA5rY2tW7cW9hBkZGRkZGRIS0ujT58+z1QHyiITqM6dO5OcnMzx48fFJrw5Hai9e/fSokULAgICcjlQ27Zto2vXrmzfvj3XeYsWLcrjx48xGo2UL18enU5HcnIyOp0OGxsbjEaj2WpGXk/hjRs3jr/++ovLly9jNBrp378/CxcuFPvhDRs2DD8/vzxXRfL7qixZSHP1qbvM3nsTjUqJVpP1xGB6ShI2NjZcmdMbwWRk+up9jGhfVzzGaDRSr1497t+/z+3bt63egZLSFp6U5UqpIGdk3cj5WD9SzqjQmwlb2oFKTk4mIiJCPC9ARkZG1g2p1ezfv5/WrVvncqAA5syZA8DAgQPx8/PD39/f7P0TJ05gMBhQqVRA1qQp+xrfffddnitNlpTI49KMaDUq9EYBnUFApQSTCVIfR2HSpYNCwfLZE3jL8VvKlStHfHw8y5cv5969ewCcPn2aTp06FWgMlkan00lqEgXSlCulhpyRdSPnY/1IMaNCl8gt7UA5OTlx5coVtmzZwrp161izZg2DBg3iypUrnDt3Tiw3kF8dqKexadMm0tPTxT8fOHCAsWPH4u3tzfDhw/M8xpIOVGRCGiUdbEnK1BOXpsdgFAjP4UAhCNy+dCrfSVLv3r0LdP1XhVQ8KCm7AVJBzsi6kfOxfqSckcULaZ48eZJmzZrRvn17du3alev9sWPH8vjxY8LDwxk0aBCenp5kZmby6NEjlEolw4YNY/r06djY2NCxY0fAvA7U1atXad68OYmJiezatYvmzZuzdu1a0VNSKpXY2tri6+vL33//zYYNGwgJCSEzM5NmzZqRkJAAmNeB+uKLLzh+/DhXrlyhYsWK1KxZE0CsMv7w4UM6dOhAzZo1uXz5Mn379mXbtm3iZKpDhw6UKFEiz+/DkoU0Hz9UEpWoQGcEBNDkrvspCaRSQDMbKRaYkxpyRtaNnI/1I8WMLF5I08/PT6ztFBkZSalSpQCYP38+AwcO5OjRo1SqVIkLFy6IE6RLly5RrVo1tFotZ86coW7duhw+fJjMzEy8vLxYsGABf/zxBwBr1qwRJ0HBwcF06dIFyPKXevbsidFopE+fPkybNo2qVaui0+lwc3PLdeNP1oEaMGAAP//8Mzdv3uTmzZsAvPXWW+LYAW7fvs2qVauYP38+3333HZs2beLbb79l48aNjBo1Ks/vw5KFNGNP3eXkvpvYaLLqQAHUGLcBjUbDlbm9wWRiiv9ORnduKB6TkZFBw4YNiYiIIDQ0lGLFihVoDK8CqWzhSdkNkApyRtaNnI/1I+WMLFpIMyUlhXXr1nHu3DmioqJYsWIFEydOBMDV1ZW2bdvSoEEDzpw5g8FgYNq0aUyfPh3I8olsbW1JSEjA2dmZ4cOHc+jQIby8vHB0dBQnIeHh4Xz77bfExcWxdOlSxo0bx/fffy+OITk5mXPnzvHPP/+IvfFMJhOCIJCYmMihQ4dyOVALFy4E4NGjR2zdupXRo0czevRocaJ25MgRAEaOHMl3331Hnz59cHd3Z9KkSfzwww8cO3aMhw8fmpVJyMaSDlRyhhEblQqjScBgzHKgBBNkJj5G0GUCAlv95vN+3R8pU6YMiYmJ/Pbbb0RERCAIAleuXKFt27YFGsOrQGq/hFJ0A6SGnJF1I+dj/UgxI4s6UOvXr6d69epUq1aNvn37Mnr0aCZMmIBCoaBfv360bt2ahg0bEhsby7fffkuvXr3Mju/WrZvoQCUmJlKrVi0z0Tu7ttOECRNo2rQprq6uZpOnbK/pypUrZuddsmQJW7ZsISUlxaym0/MyevRo1qxZw6JFi/jqq6/M3svpOT35usWaCcelUdLJlqR0PQnpeoxG8zpQAJeC9vDmm3vyPL579+4Fuv6rQnagZF4VckbWjZyP9SPljCxaB6pp06b07NmTUaNGYTAY8PDwYMOGDbRs2ZI1a9bg6+uLg4MDhw8f5q233qJjx47MnDlT9KXGjx/PoUOH+OWXX2jRogWjRo3C09OTfv36ERoaSrNmzfj222/5+uuvMRqNGAwGKleuzCeffMKQIUM4duwYEyZM4MaNG+KYjh8/TvPmzVGr1djb24urSlu2bMn12XfeeYd//vkHg8GAwWDgn3/+Af7nQK1bt07sJadUKtFqtSQnJ1OpUiVCQ0Pz/E4sWQdq4x0llx4r0JnAaAIUcOsHadWBArkWlIyMjIxM4WOxOlAhISF4enoSEREhCtUjRowgMTGR1atX8/PPPzNo0CCaN2+OIAgcO3YMLy8vmjRpgp+fHyEhITx48IDGjRtjZ2fHl19+SaVKlYCslak333yTiRMnsmfPnqfWgcpJQkIC9evXB+D+/ftmE6i8nsJzd3cnOjo617nnz5/PmDFj2LJlC3369CE9PR2VSkXJkiWJjIzE29ubffv25fm9WLIO1KpT95iz7yZqJWg1WaUV0lOS0KhVXJnbB0xGvlmygXE9W4jHJCYm0qRJEx4+fMiNGzcoWbJkgcbwKpAdKJlXhZyRdSPnY/1IOSOL1YHy8/PDYDCI0jj8z2vy9fUVHabRo0cDoFAoCA4OZtWqVaIv1a1bN0qUKEGjRo04cOCA2CrF19eX+/fvi05Tdo0nQRBQqVR07NiR5OTkXGMaMmQIffr0QaVS4e/vbyaA5VUHasiQIU91oPR6PZmZmSxdupTRo0dz9uxZKleuzNGjR8WCnU9iSQcqXW9ErVRgEgRMpqxK5AC61GQEgw4EE8f2bGZYh/q4urqSkZHBli1bePToEQB37tyhTJkyBRrDq0BqtaCk6AZIDTkj60bOx/qRYkYWcaCyazvNmzcPb29vs/dyek2AOGnx9/c386WGDRvGL7/8wqeffsqcOXO4d++eWAfq1KlTpKSkmJ13yZIlHDp0iI0bNzJz5sxcN/ZkL7wneZE6UGfPnqV27doMGjSIP/74g2nTpqFWq0lOTubatWviU3s5saQDFR6bSgknG5LSDSRlGDCaBO7MMXeg/t66irJbV+V5fH7tZ6wRKXhQUnYDpIKckXUj52P9SDkji9SB2rlzJ/Hx8Xz22WcEBweb1YF6//338fPzEydQK1asALJWrPr27QtAamoq9+/fx9bWloULF7Jy5UpsbGxo3bo1dnZ29O7dW6wDBVle02+//YatrS1JSUls2rSJXbt2iV7Tjh07+Oabb/j7778JDg5mzZo1PHjwAEEQ6NatG+PGjcPGxoZq1aoBWU/hLV68mLCwMBQKBQEBAWLrFxsbG/bu3QvAn3/+iaenJwCzZ8+mXbt2GAwGAKKiovL8bixZByoqQkl8koIMAwgCSLQMFCCtWlBSrI8iNeSMrBs5H+tHihlZpA6Un58fXl5eODs756oD9f777zNnzhy+/vprsbfdw4cPOXPmDO3atQMQi2Bmr9TExMQAsH37dnx9fc3qQCUkJPDJJ59QsWJFIiIi6Nq1K9999x3e3t6sWLGCkJAQszpQpUuXJjIyUhzrtm3b2LZtG4cPH+bGjRvs2bMnVw2n7OAjIyOpUKGC+HrOulatW7fm3Xff5dChQ0/9bixaB+rkXc7uD0WlAmebLAeqxrgN/8feecc3Vf1/+EnSpoOWllJKW6jsvZeIoqyyQaagbBkq8kUBkeGPJUsEFBAQVAoFlC1ThiKjrDKljFJmy6a00L0z7u+P2iuhKQol9PZyntcLbXPXuXkn5HDOk8/BTqvl/OweSGYjn85ezqT321rcQ6NGjXjw4AFnz57Fz88vV214UahhCk/NboBaEBkpG5GP8lFzRjapA7Vt2zYg5zpQkiQRGBhI8+bNqVq1qtU6UFkVxO/du2dRBwqwqAOV5TVl1YH64IMPGDduHJA5PdixY0cKFSok14EymUxoNBrZl5o6dSpffPEF5cuXB2DlypV07dqV9evXy/fTq1cvVq1aRYkSJQCoWLEibm5ulC5dmgsXLsj7/frrrxQqVAjIFNCtYUsHyihp0Go0SEhIEmg0mY+bDKlIZiOYTVwLPY0ktUGv12M2mzl79qw8HRobG0vp0qVz1YYXxeNTePm5Q6VGN0BtiIyUjchH+agxo5eqDtTGjRuZPXs2vXr1kn0pPz8/xo0bx7Fjx+jUqRPp6enZptLs7e2RJIkbN25YjECNGDGC3r17ExAQwIABA+THCxQoIC//8ji2dKCu3E+kqKue+DQjSemZDlT4Yw7UbwHf4BHwjdXjGzVqZPXx/EB+dKLU7AaoBZGRshH5KB81Z/RS1YGaPn06ixcv5vbt2zg4OMhr13l5edGpUyeCgoIYMWIEw4cPZ+vWrRQuXJhPPvmEQ4cOIUkSb775JjNmzODs2bOMGTOGhw8fUrhwYRITE9Hr9djZ2ZGUlESHDh1yrFVkyzpQa65puRQHqSYNBjNIQPgM9dWBsoaoDSUQCASCF8lLVQdq/PjxfP311/j5+XH37l2LDlSrVq1YuXIlZrOZMWPG8N1335GWlmb13kaPHs3ixYs5ffo0FSpUwGQyodPpcHZ2Jj4+njJlynD16lWrx9qyDtSyI9f5dvdVNBpw0uvQkFkHSodE6Dc9kcwmBkyYx+xhveRjwsLCaN26NfHx8Rw/fpxy5crlqg15RX6cwlOzG6AWREbKRuSjfNSc0UtVB+r3339Hp9PRu3dvecTCaDQSExNDp06dWLEi8+v9X3/9Nb1796ZatWocOXKEuLg42rRpw+rVq+nRo4dcbPLUqVNIksRXX33FvHnzOHHiBMWKFePatWsYDAarLxZbOlBajQ40mc+lRgL+dqCQzH+XZ5BIS0nGzs4Ozd+CVFpaGiaTKXM3SVL8Czw/dpT+DTW6AWpDZKRsRD7KR40ZvVR1oFJTU0lLS7P4Ft7evXsxm81cv35dlssBjh8/jru7Ow0aNKBPnz40aNCArl270qtXL8LDwwGoU6cOWq2WggULotVqmTlzpvx4Tk+sTR2oqASKuOhJTDOSmG7ELMG1xxyoX2aN4ZdZY6wen5t1AV8U+dF1ygk1uwFqQWSkbEQ+ykfNGdnEgdq8eTPdu3cnKioKNzc3i21ZXtOJEycsHn/jjTeoV68e8+fPp0GDBhw5cgR/f39WrFjBhg0bWLp0KXq9Hr1eT0ZGhlwH6syZM8yYMYPt27eTlJSEn58ft2/fZufOnSQnJ8t1oBo2bMjBgwfp06cPx44dQ6/Xs3fvXt5//33q1q3LO++8w9ixYzl06BAbNmzg0qVLbNiwAWdnZy5fvkyBAgXo3r07W7dupXXr1mzdupVhw4ZZ9Zn0en2Oiwnb2oG6Eg+pRg1p5sxaUBFfq8uBEq6TQCAQCJSATRyo9u3bYzab2b59e7Ztx48fp379+pw5c4bq1asD//hS3bp1o0iRInz//fdWe3YuLi50796dyZMnM3jwYLZs2cLSpUs5c+YM8fHxHDx4kOjoaFJTU5kzZw4uLi5yB2nAgAG8++671KxZkwcPHpCcnEzBggXp0qUL3333HS4uLgA8ePCA9u3b89dff5GRkYGLiwtz586lQoUKvP/++9y6dYtu3bqxdetWTp06RYsWLWjVqhXt27fngw8+4NatW3h4ePDgwQN5muxRbOlALTl0ne/2XgVJwklvh0aT6UBpzEYuzOkNJiNdhk7gx0mfov17nZeDBw/y7rvvkpKSwoEDB6hWrVqu2mBr1DSFp2Y3QC2IjJSNyEf5qDkjmzhQWXWgrPHqq69mWy4ly5datWqV7DNpNBocHR25d+8emzZtYvHixej1ei5fvkznzp3lKcD+/fsDcOHCBXbu3MnQoUOJi4tj48aN7N2716IO1McffwwgXz85OZlevXrJnScAT09PgoODmTp1KuPHj2ffvn3UrVsXgLlz59KuXTsaNWrEihUrGD9+PB4eHixcuFC+75o1axITE8OxY8d47bXXst2/LR0ovb0uswK5VsujXTetzg4NWiSNlqK+r1hcv0SJEjg6OpKSkoK7u7viX+CPTuGppTOlRjdAbYiMlI3IR/moMSOb1oH6L2T5Ut26dSM0NJQ1a9YQFBTEjBkzcHBwkH2ppk2byg7U8ePHeeWVV+RzhIaG0rRpU/r27cu0adPo1asXHh4eABQsWJBz586xadMm1q5dy88//8ygQYM4d+4cJ0+epFSpUkDOa+E9OoqUNWqTRUpKisVjS5YsoXTp0oSHh2M2m63ery0dqKv3E/EooCcp3UhShglJkrjymAP1/diBfD92oNXjs0YE8wv53YdSsxugFkRGykbko3zUnJFN1sJ7GrLWzbt+/TqDBg2iatWqVKxYkUmTJtGwYUMCAgJwcXFhwYIFtG2buQRJt27dZAfq/PnzNG3alJYtWzJixAi2bdvGmjVr5OVgsiqaL1iwgIMHD1K+fHkKFCiARqOR17GDzK/z6/V6+XetVouzszODBg1i8eLFGAwGPv30UxwcHOQP7rZt2zJnzhwmT55M586dWb58OT4+PpQoUcLqQsJg27XwIm5oMaSD2ajBZALzU1Xtyn+oZT08Na4RpTZERspG5KN81JiRTdbCexoCAgJo0KABhw8fZsKECeh0Olq1akX37t25du0aJ0+eJCQkhN27dzN8+HAgM4istfAWLFhAdHQ0P//8Mz///LN83lGjRtGtWzdMJpPFWniHDx8mKCgom59UqVKlbCMaXl5exMTEyN9OK1eunMV0X9OmTfnll1/4/PPPmTRpEpIkkZGRwUcffYSTk5PV+7XlWni3DoRzZn8EEmZcnezQasBx1HowpBM2ry+YTfj3HMzymeNwdnbGZDKxceNGhgwZgsFg4Pfff5dH+fID+X0KT81ugFoQGSkbkY/yUXNGNlkL72nYtm0bo0aNIigoiPbtM78xtmPHDnnkKC4ujqVLl2Y7LqsD9Oqrr+Lg4EDt2rX57LPPeOONN9i9ezcjR44EIDExkZMnT1qshQeZHpSdnR1//PEHTZs2pV+/fhbLxHh7e3P79m2qVKnC2rVrMRgM9OvXj5iYGIt17oKDg3FxcaFatWp4e3szffp0YmJicrxfWzpQBRz1mCUJO62WRycb7Ryd0OjskDQaar/RTP5mpL29Pf7+/nh4eHD//n1Kliyp6Bd4fu8w5YQa3QC1ITJSNiIf5aPGjBTjQE2fPp0pU6awdu1aFi5cSIUKFdi+fTurV6+mUKFC8sLDAM2bN7eQyLMcqP79+zNz5kyGDBnCxo0b+d///ic7UAAjR46kRIkS/PXXX9kcqMfx8vLCaDTy2WefySNQ77//PuPGjZMXFQ4LC2PRokXs2rWL5s2bM23aNOrUqfPE+7W1A+XubE9KuomkjMyO4uXHHKiZH3dl5sfWj69QoUKurm9r8rvz9DhqdgPUgshI2Yh8lI+aM1KMA+Xq6kqVKlVo3749Go2GYcOG0blzZwICAjhx4kSOEvnjDlRkZCSRkZHyaIVWq6Vq1aosW7aMmJgYfvvtN/z9/bM5UEOHDmXBggWyRB4VFYWdnR1z5syhQoUKGAwGli9fjkaj4caNG9SuXZtt27ZRunRpZsyYgVarZciQIWzevJmZM2fKEvvj2NKBuhqhRcoATBqMRrCusedf1OI8PY4a3QC1ITJSNiIf5aPGjBThQPn7+7N69WreeOMNdDodLVq0ID4+nlKlSjFr1iymT5/O1q1bKV++PGApkefkQGUttwJw5coVxowZw8GDBzl27JhVB+pxIiMjKV68eDYHysPDg8jISADOnDnD5cuXuXz5MgA3b94kICCAkJAQTp48afW8tnSgIvZf4/zB65gw4+KkQ6fR4PT5eqT0ZC7O7w+SmVdbvcPKeVPx8vIiKSmJwMBAJk6ciNlsZvPmzTRq1ChXbbAlapvCU7MboBZERspG5KN81JyRIhyorEKaJUuWZOjQoQQEBNC1a1eOHDmCJEl06NCBjRs3MmHCBAC5kGavXr1kB6pz586kpKTQvXt3UlNTGTduHICFRO7l5UXr1q0pXbq0xXIuAPPnz2f+/PkWj0VFRVGuXDnZgXr//fctlpDJKlUQGBhIy5YtATh79iwtW7bk0qVLVqfEbOlAuTs7YDRL2Gu12Gu1SEigAb2rGxo7PZhNtOz+PsWKFQOgUKFCDBw4kMWLF3Pnzh2qV6+u6Bd4RkaG6jpRoE43QG2IjJSNyEf5qDGjPHegwHohzeXLl+Po6MiCBQvo1KkTnTt3lssM5FRIs0mTJhaFNP/3v/9ZSOSPF9J8VCJ/HLPZTEpKCkuWLMlWSDOrHV5eXgDUqFFDFsuzBO2bN29a7UDZ0oEKj06ioKMdqQYTSelGNBq4+JgDNeX9Nkx53/rxpUuXztX1XwRq8qDU7AaoBZGRshH5KB81Z5TnDlR+LqSZJYy3adMGo9FI+fLleeedzA5Llmj+OLZ0oC5e06I1gs6sIVWFDhSo04NSoxugNkRGykbko3zUmFGeO1CPFtL09/enRo0atGjRgrS0tGyFNK05UL/++is9e/ZEp9Px3XffsWrVKu7evcuaNWuA7IU0o6OjOXny5H8qpOnk5ETz5s1JT09Ho9Gg0+ksCmm2atWK4sWLU6RIEXr06MHYsWM5fPgwNWvWlNv6OLZ0oK7svcqFIzcwSmYKOOrQaaDiyPWYU+O5vDCz+nil+k35cfaX+Pn5ERcXx5IlS1iwYAEAa9askacilYqapvDU7AaoBZGRshH5KB81Z5TnDtSjhTTLli1r4UBFRkZy8uRJlixZkqMDtWLFCospsTt37gAwePDgbIU0sxwod3d34uPjLdphrZAmYDEiJUmSxe9eXl4cO3aMIUOGMHr0aOzs7NBoNFYdpyxs6UB5ujhiMEnY67TodZkOlEYLju6eaPVOSGYTPT4dL1dJ9/T0ZPLkyWzdupVbt27x+uuvK/4FLtbCE+QFIiNlI/JRPmrMKM8dqEcLaVpzoOLi4ti0aVOODtSWLVuAfxyogQMHEhcXR1hYGMB/dqAeL6RpNptJTU3lwIEDsgO1fft2CwcKwNfXl/Lly9OjRw+aNWvG4MGDuXHjRo73a0sH6uaDJArodaQbzaRkGNFoNIQ95kCN79GE8Tkc/+i0aH4gv/tQanYD1ILISNmIfJSPmjMSDlQuHCiAvXv3sn79ekJCQti4cSMmkwkfH58c79eWDtT5q1rszWBCQ5JBnQ7Uo6jFh1KjG6A2REbKRuSjfNSYkXCg/uZZHKjx48czY8YMnJyc8PT0xN7eHoPBII90WcOWDtTF3Ve4ePwWBsmMkx50Oi3lR67HlBjNtR8+Bo2WVyrWYPr/fYaPjw/x8fGsWrWKDRs2ALBixQp5OZ38QH6fwlOzG6AWREbKRuSjfNSckXCg/uZZHKhNmzbh4OCAwWDA0dERZ2dnUlJSCA8Pz/F+belAebs7k2Y0o9dpcbTLdKDsHR1xKVgGrYMzksnEsJk/0bPdP8vNvP3225QrV47r16/Trl073N3dc9UGwdOjRjdAbYiMlI3IR/moMSPhQOXCgbp9+zZpaWlAZi87OTkZyJymK1u2rFyj6kVxLy4VZ3stGSaJNIMJO50GY3oaqfdvYE5PQWOnZ8aQd3GP/oI6deoQERHB/PnzuX79OpIksWXLFrkMg5LJ7yNPkPkaDA0NJTQ0lCpVqlC2bFmbXi8qIY3YFANuTvZ4uzna9FoCgUAgsEQ4UI85UMHBwZhMJvn3pUuXMm/ePAYMGECnTp2s3q8tJfL7CWl4uTqg1WqISkgn3Wjm0qx/OkSSMYOom1dz7Ni9//77vP9+DlU2FUR+l8d37NjB+PHj5UWu/+///o9mzZrx9ddfU7169ed6rfDoZNacuM2pm7FkGM3Y22mpUdyN7nWLU9Hb9bleS42oWYBVAyIf5aPmjPJcIs/PDtT9+/eZM2cOO3fulJ9IOzs7Fi9ebFU4B9tK5AlRWuISNBRxkiiqhww7uJCrMyqT/CyPHzp0iG+++YZq1aoxbtw4fHx8uHz5Mps2beKtt95i+vTplCxZ8rlcKzIFNkRoicvQUMBeQq+FJDP8fiae4As36FTSjJ/Lc7mU6lGjAKsmRD7KR40ZPY1ErpEeH555DrRv357ExEQOHz5Mt27dKFKkiIUDtWvXLho1asSqVauyOVBbtmyhQ4cObN26Ndt5PTw8ePjwISaTiddee40BAwbw7rvvUqdOHWJiYoiPj5fXsoPsI1DTp09n6tSpcodJo9Gg1WpJT09n7ty5DB48mOnTp5Oamkrt2rVxcnJiypQpHDlyhH79+rFs2TKr92ttBMrPz48HDx7kWiI/Gh7D5O1heBSwx1lvh2SWuHf3Fp6FPdk582NMkoYVazfSqKK3xXHDhg1j06ZNhIWF5boT9yLIr1N46enplClThoYNG7Jq1SpMJpMsV6alpfHmm2/i7e3Nrl27cn0tSZKYuC2M4PAYShR2QvvISKokSdx4mEr14m7M6lL1XxfWfplRswCrBkQ+ykfNGSUkJODp6Ul8fPy/fn4LB+oxB+qLL76wuJdWrVpRs2ZNVq5cyZIlS9DpdNnu15YS+Wtli/BG2QccuByNi4OEm5MOkwSxKQaKN3+f0GX/xzejPkQ/dozsQGWN2n377bfyOn7PC5PJxK1bt9BoNBQu6kNyhhkXBzsKOOTupZRfp/C2bNlCVFQUX3zxBUajEYPBQFpaGhkZGTg4ODB8+HAGDRrElStX5KWAnrWzePNhCufvJlLExQE77WOvQw0ULejIlahkrj1Mo5JP7jruLwNqFGDVhMhH+agxozyXyPOzA2WNlJQUJEnCbDZb7UDZ0oECGN6sNEVc7Nl7MZq7cWnsndjNYvvBgwc4ePBAtuNGjBhhUV5BYDuyOuQ5UaVKFfnnZ+0sRsYlk2Yw4u7kgFnKXhHM0V5DVKKR+/EplPV0eqZrvAyo2d9QAyIf5aPmjF4KB+rcuXNMmTIFZ2dnGjRogEajwWQy5dqBWrZsGcuXL+fOnTuEh4dTsmRJwsPDadu2bY49U1s6UFkUB7p4QWQq7H0uZxTkFc/qe91NgZQkHffSEnHI3o/HYIbUDA1nTh4j/lIuG/kSoEZ/Q02IfJSPGjPK80KaL6IO1NSpU+nduzcjRoygQIECtG7dmosXL/Ljjz/ywQcfAM9WB0qr1RIaGkpiYiIA4eHhdO3alZUrV+Z4v7YspPk4BoOBYvo1NG3a9IUNne7YsYOePXuydOlSwhwrERweQ/FCTui0GsKP/UFw4Fc0GvI1Zp+q1C/lwf+1qfhC2qUE4uLiqFy5Mh9++CETJ07EYDCwd+9emjZtik6no0uXLkRHR3Pw4EF55PNZp/DMZonzG85x8V4iRTwcs3lOt2NTqejtzMAuNdDb/fvI6suKmv0NNSDyUT5qzijPC2m+CAfqwoULXLp0ieXLlwPI8vhHH31E2bJln9mB6tu3L3379iUoKAh/f3+qVavG+vXrn3i/tnSgHifDaMZozn5uSZJITk7GycnJ6jRjbli5ciV169alQbN2rFsXQuECDtj/fY0y9Vty8c/1hB/+jTp963D+biL3EjJ4pXD+lMKfhLWOj7u7O2PGjGHixIk4OjoyZMgQHB0diYyMZOrUqQQFBbF161YKFSr0XNrQ87USzNh5kbvx6Xi5OuBgpyPDaCY6KR29nY6e9UtQwCnnha8F/6BGf0NNiHyUjxozemkcqEeZPHkyGzduZPz48dSvXx94dgdq//79tGvXjjp16uDt7Z1t++PY2oGSJImTN+LYFRrJuTvxbP7fu7k+57NQqYRXjttib1/lVog/ALs+f1EterHk5C6NGTMGk8nErFmz+Prrr3F0dCQ1NZUiRYqwcuVKWrZs+dxcgXqvuDGsWRlWBN/kTlwqJjNoNeDt5kiPen68VbaQKr2E54ma/Q01IPJRPmrOSDEO1Pnz5wkLC2P06NFs2bKFSZMmWThQEydOpHz58pQrV87CgerZsyfr1q3DbDazfft23nzzTdasWcOqVauAzA+y2bNnc+rUKc6fP49Wq8VsNuPt7c3EiRPldjzuQGk0Guzt7XnttdfQarVUq1aNhw8fWjhQ+/bto127dgwZMoQff/yRY8eO8eeff1K7dm25A/c4tnagjkdpCIrUkmECJ7vnXnVC8B95krtUu3ZtfvrpJ44dO0ZiYiJeXl7Uq1cPe3t7m9S4al8IrttDskGDsx2UcInHcP0+O68/90upFjX6G2pC5KN81JiRYupAHThwgIEDB7J69WouXbrE9OnTuXbtGrt27WLo0KFUqlSJU6dOUbduXWJjY3FwcGDEiBHUr1+f48ePZztviRIluH79OsnJyYwcOZLatWuzcuVK7OzsKFCgADt37mTlypW89957QPYRqFatWvHHH3/QsGFDTp06RUZGBo6Ojjg6OsoOVr9+/eRpwUdp1KgR+/fvt3q/tqwDdTUqiVEbzyNJEkVcHSzqQO39aTIx186yeuMWmtb9R55PSEigc+fOJCYmcvTo0VzXBPrmm2+YPXs2x0+c4utD0dyLS8HHPfNbXskxUWyd0JOaHQfhXvdtvN0c+fad6jio0MH5L+6Smt0AtSAyUjYiH+Wj5owUUQdq2LBhBAUFsXTpUsxmM35+fkCmL7Rw4UJWrFhBSkoKly9fZt++fYwfP172lY4dOwYgjwKNGjWKadOmyecvUKAAixYtAuDw4cPExcWxefNmpk6dyqRJk+QO1KMOlCRJBAcH4+joyIEDmV/5j4+Px8vLi5SUFHmqLjAwkO7duzNixAgqVKjAli1bOH36NDVr1szxfm3pQB28GkNyuomShZ3RaDSYtZmuV3pSHPfPHqR064GEp7vS8pHrFC5cmGnTptGqVSuCg4Np1KhRrtowcOBAlixZwnvvdqPPiC+5RwGi4tMh+irHf5mFo2sh3Ko1Q6PR0KW2Hy7P6ODk12Ka1lCjG6A2REbKRuSjfNSYkSIcqGXLllG8eHF27twp+087duygU6dOaLVa1q1bl6P/BJkO1PLlyylUqJBF5+lJmM1meSTo+vXrlCpVin379tG4cWMiIiJkN+nUqVPUqVMHNzc3ypcvz/nz52Vv6v79+wwaNIjNmzczY8aM/3RdWzpQl+8nYKeDpHQj0YnpxKcaOP1IHahr23/g8+0/kJN21LZt21xd/1EiIyMZPaCr1W37JmU+vicX58+vxTQfRc1ugFoQGSkbkY/yUXNGinCgEhMT6dGjh0UNqIcPH9KlSxdmzpxJYGCg1RpQgOxAGY1GjEYjkZGRAOh0OooUKUJaWhqNGzfm3r173Lx5E09PTwICApg9ezaffPIJkNmL9PX1pV+/fly/fl0+R4kSJSwcqPDwcF555RV8fX2RJIlq1aqRkpLC66+/Lk99BQcHA+Q4CmVLByryjpaoWA23HoBJyhSG1Up+Xg/vcdToBqgNkZGyEfkoHzVmlOcOVJMmTQgKCuK9996zWAfPaDQydOhQ6tevz+7du+XCmI+ugwf8JweqZcuWREREcO/ePSCzczNo0CA+/PBD+Zt1jzpQR44c4Y033sDFxYVatWrJDhRkjtJs3ryZ7777jrlz55Kamip3uB4lp6fKlg7U8uAbzPrjCjotONlnlg5ITUrATqfj/Kz3kMwmhs/5mQl9WsrH3L9/nzfffJPo6GjOnTtH8eLFc9WGF4UapvDU7AaoBZGRshH5KB81Z5TnDlS9evXYv3+/1RpQCxYsYNmyZYwbN85qDSj4x4Fq3Lgxx44dIzU11eL8BQoU4NChQwCULVuW5ORk/vrrr2zteNSBKlq0KJDp88yZMwfIdKAKFSokd3727t3LjRs35ArlkLn2GyCPjlnDlg6UwQxajQZJAskMmr/dbFN6CpLZCGYTYX8dwdTTH0dHR0wmE8eOHSM+Ph6A6OhoeWkbJaKGTpM11OgGqA2RkbIR+SgfNWaUpw7U86gB9Tx43IHK4tFvpD3+7bTvvvuOqVOnyr9funSJrl27UqFCBb766qscr2VLB+paVBJFXfUkpBlJSjdiMkuEz3zHYp9dy7/Dc/l3Vo9v2rRprq5va9TgPT2Kmt0AtSAyUjYiH+Wj5ozy1IHK7Tp4AH369OHEiRNcvHgRjUZDSEgIAJUrV0av15OWlsa7777L+fPnuXbtGnq9Xt4ny1N68OABer2eiIgIGjduzP379wH4/vvvWbZsGSkpKRQsWBBHR0d5FMRsNjNnzhw2bNhgUc59/vz5T5wGs6UDdfeOlvgkSDNqMKuwBJSavKdHUaMboDZERspG5KN81JhRnjpQWTWgDh8+TLdu3SwcqMjISHbt2kWjRo1YtWpVtnXwshyo4sWLy+vfPUpERAQlS5YkOTkZb29vkpKSsu2TdTuPj0BlOVB6vR5nZ2e5A5WcnEybNm3YsGEDu3btYu3atbRp0wYPDw9+++035s6di6+vL7dv386xnpItHahlR27w7e4raDXgqNehIdOB0mkg9JueSCYjgyYvZOYj1cmvXLlCixYtiIuL49SpU5QuXTpXbbAlapvCU7MboBZERspG5KN81JxRnjpQuV0HD+D27dvAkx2orMV+sxyoLJk8i5IlS1pI31kO1Mcff5zNgUpOTgYyC222atVKPqZZs2Y4Ozszffp0jh49SoMGDazes03XwtNo0WhAgsz//N2Hk8zGTClKkkiMeYBOp5Pl+djYWHkYMiMjQ9Ev8Men8NTSoVKjG6A2REbKRuSjfNSYkXCgeDYHyhpZU3mPjjA9ji0dqKv3Eyjioicx3USa0YQkwcXHHKg1c8azZs54q8fn1OlTKvndiVKzG2ArJEli//79LF++nFu3buHp6cl7771Hu3btsLN7/t9zeZEZxaUYOHT1AWGRmf/gq+TtSsOynrg7q+tD53ki3kPKR80ZCQeKZ3Ogjh07xtSpU7l58yaXLl1Co9FgMBgoUqTIEzsitnSgbt3SkpEGRR0gSZPpQqkZtThRanQDbIHRaGTu3LkcOnSI4sWLU6ZMGc6fP0+3bt2oVKkS48aNs9mopK0zupEEv93UEpeu4e8xZDajoZCDRLtXzLziYtPL53vEe0j5qDGjp3GgnnsHKiAggAYNGnD48GHKli3L0KFDLRyokydPsmTJEjZu3JjNgcrqQO3du1d2oCRJolatWsA/DpTJZGLPnj2yA5WRkSHvkzVt5+npSUZGRrav8D9J+XJ2dub8+fNERUVhNBoxmUxUrFiRP//80+oUXRZjx45lxIgR8u9ZDlSLFi1y7UAlnLjN0iPXKerhhI9Gg2SWKDx5HW4FCrDp/97Bp347vvi/cbxbz8/iuC1bttCvXz8OHjxI1apVczi78sjvU3hqdgNswbhx4zh69CgrV66kW7du8qjwgQMH6NKlC7/++qtcL+558SIyikpMZ82Gc5j06VT0ckT3dwVck1niTlwaR5Id6NqmGp4uz7bskZoR7yHlo+aMHv0C2b8hHKhHHKhq1aoRERHB3bt3qV27NjExMYSGhspuUU7Y0oFqXsWH385FcjcuneKFnNBowU7viJO7Bz51W3HnyGbso7pgb/+PKH7p0iW++OIL3nrrLbljmV9QwxReWloaGRkZT+ysP05+7zg+C8nJyfzwww+MGDEiW521Zs2aMWvWLD788EPu3LlDyZIln/v1belvHLp2j/sJ6ZTwcEb7yPIBWh28UsiZGzEpHLwWS7e6fk84y8uNGv0ataHGjIQDxbM7UHfu3KFJkyaULFmS1NTUf+08gW0dqMLOOj5pWpq5e65x/UEydloNSemQ/DCFW4c2AjCwV3cGWjn27t27uLiIeYL8QH7vOD4LR48eJT4+nnfffdfq+6Rbt258+OGH7Nq1iwEDBjy3674If+NExEN0WkAjYX68I60BnRZOhD+kUw1vm7Uhv6Jmv0YtqDkjxThQgwYNomrVqlSsWJFJkyZlc6CyFrp93IG6evUqSUlJJCUlIUlSNgcK4MKFC2RkZJCeno7RaPzPDtTSpUtp3LgxpUqVYvz48Tg7O8v/+r9z5w6NGzemRIkStG3blokTJ8pLunh75/wXnS0dqCzaeUCoVsONRA0eBeAVlySCnsuZBUpALe7X03DmzBkg0z28efNmtu0mk0l2IG3x/NjS37hxU0tSCkQZEq1uT0qHG7cS2bHjhs3akN9Ro1+jNtSYkWIcqG3bthEcHEzDhg3x8/MjLi6OkydPEhISwu7du/n11185dOgQffv2JSoqSj7HwIEDCQr6p3uQNQ115coVypYtC2QO8T+6Xt1/daDee+89unfvTlpaGjqdDm9vb/mY3bt3c/XqVa5evcqePXsA8PHxsTivNWzpQD3Oo3PP/9c99rme+8+9e3mnSxeK1m3Jq10GU9DdDYD7V85xMGAyji7u7N23l9JFXJ/rddWEwWBg7969NG3a9KmGgl/GKbxXX32VadOmER8fb3WEacuWLZjNZvr37/9cp6JfhL9x//B1Vp+4TZHCTtlGuiVJIiUmleZ1/WjzegmbXD8/o2a/Ri2oOSPFOFC+vr6YzWYAbty4wf3794mLi8PNzY05c+bg5OQEgJOTE7169WLOnDkMHz6cPXv2ULNmTZKTk7G3t2fu3Ln06dOHpUuXMn36dCDzX+wXL15k7dq1pKSk0KdPHz788EN+/PFHPvjgg2wOVNYI0tmzZ6lQoQI//PADBoOB5s2bc/78eSBz7by7d++SmpqK2Wxm/vz5TJkyhREjRvDbb7/Rrl07q/ds0zpQOWCL+k4zZs3BtXh53uz1OU6O/5zbp3wNGg2YwB/ffsLi1b8x57M+z/W6+Yl/6+gYDAYcHR1xd3dX3V8szxsfHx/ee+89vv76a1q3bk316tXlbbdv32bs2LG8/vrr8lT/88aW78/mVX3ZGRpFVGIG3gUd5U6UJElEJqTj7qSneRUf8Rp5Amr0a9SGGjN6mvt57pXIjUYjxYsXZ9SoUTRs2JDGjRuzdu1aFi5cyIkTJ5g2bRofffQRgYGBLF68WP6G2Pnz5/noo4/o168fO3fupF27dgwfPpw///yTkJAQFi9ezOjRo4mOjpan8SCz0xMXF8fmzZvp3LkzBQoUYOXKldnaJUkSXl5ePHjwgBMnTlC3bl254qjBYODOnTv4+vrK+wcGBjJs2DDi4uJo27YtRYsWZenSpVbv2ZaVyB8nq+ffsWPH53pewX/j31wlg8HAph27cS5ZgxSDhJuTPfVLeYi6PzkQFxdHixYtCA0NpWPHjtSuXZsrV66wdu1aPDw82L1793OvpP+i/vW8+0IUiw+Ek5hmxEmfuTh5aoaJgk52fPRWafwredns2vkZNY9uqAU1Z5SnlcizHKgBAwbw66+/UqVKFdq3b49Go6F3794EBATIHaWcRPLt27dTtmxZkpKSSE1NJSQkBD8/PxISEggNDaVWrVqyAxUTE0NiYqIsq3/99ddAps9Ut25dIiMjkSQJjUZDo0aN2LhxI3fv3uXcuXOMHz+e4sWLc+PGDY4dO0anTp24efMmMTEx3Lx5E5PJREhICHfu3KFMmTI53vOLcKAEyuBJLo4kwbFoDUejtCSfP59ZQV4CF3uJ14tK1PWU+A+1W186xowZwx9//MGff/7J9u3bKViwIO3bt6d169ZcvHiRixcv2uS6L8LfaO0J52I0XE/MDL6yq0RVD4mMiBh2RNj88vkaNfo1akONGeX5Wnhms5nt27fzxhtvUK9ePebPn0+LFi0IDg4mPj6eM2fOcPbsWRYsWCCPJmVkZMgiua+vb7ayBFns2LGD1q1b4+PjY+FAZfH4Wnh+fn6yoDpt2jS++eYbUlNTZQeqY8eOBAUFybWoevfuzc8//5ztvEuXLuX999+32qa8GIF6/fXXn2vPX5IkylWqgl2xqjQZMFauW5NFanwMm/6vO2+9N4TN8yc9t+vmFcePH6dt27a0atWKadOm8corr2Aymdi+fTuffvop1atXZ/Pmzdn8lSdN4f129h6LgsJJSU6klLcndnZaTGaJB0kZmM0SQ5uWoUXlora+NcG/oOZ/PasBkY/yUXNGeb4WHmTWIjp+/DglS5a0KKZpNBqpXr0648ePz7GYZtu2bVmzZg2vvfYas2bN4t69e/Tu3ZuHDx/K18lyoDw8PJAkifXr17N06VIGDhzIkiVLsjlQkFm2ID093cKBev/99+WaUgCLFy/GxcWF2rVr8+OPP3L69GmWLl1Knz45ez954UDZ4twDBw5i1oyvuBTiT5Xa9eXOg9lk5NjaBWi0Oj4e2E8Vb5i5c+dSoUIFVq5cKd+Pvb09Xbp0wcnJiW7dunHy5Elef/11i+NymsJLM5hYfzwCsyGNAqQhmdIxmTNLYHg6wp3YVDaFRNKiqi/2un8vjSGwPWr0N9SEyEf5qDGjPK0DlUVAQABGo9FqMc0FCxbQqVOnHItpJicnk5SUxM8//0zRokWpWbMmw4YNY/z48RQuXBjI/Nbdo9/MadWqFcHBwaxbt44lS5ZYbZPZbCYlJYUlS5ZQt25dIPODtF27dnI7ChQowKJFiwgKCiIkJISqVas+sfMEtq0D9Sg3Y1K4cDeOszEaOhYq9NzO+zinfxrN6Ry2dW+cvwpz/huFnvA8tmjR4rleq8W3+wm9HUsV3+c7Kil4OtRcw0YNiHyUj5ozytM6UPD8imk+On2SVdAypxnH06dPc/PmTRwdHeXHAgMDef/9962ORD1+3kfZv38/7dq1o06dOk+s/5SFrR2oZAPsvqPlaoKGdBOAGMHIj8QnJLLvwCFuiP6TIlCjv6EmRD7KR40Z5WkdKMj9gsLOzs44OztTpUoVEhMTcXR0lKdOYmJiABg0aBAnTpzg7NmzcgfJ3t6eYcOGye0ICwuz+MZefHw8Op1Onpbx9PQkLS0NBwcH+fz79u2jXbt2vPbaaxw7doxjx47h7e3NgAEDmDZtmtX7tWUdqHSDiQnbwojIiKNIYXtc9TqiHzyg/Td/cPXUAcJWTaVT5y783xdjKVOmDFFRUfzwww98++23jBkzhtGjRz/ztZNTUtHq7HByUNcQrclkolKlSnTq1En+0sGjxMTEUKVKFcaOHcsnn3zyn855IyaZUb+ex1GnJS05Ds/Cnmge8cgSUg1Ido50blUDX3en53YvgqdHzf6GGhD5KB81Z5SndaAg9wsKP1ozRaPRIElStlGkK1euEBkZiV6vR6fTYWdnR0JCglxbCqBSpUoWzkp0dDTOzs7UqVOHEydOEBcXh9lsthiRWr58OSkpKezdu1d+7P79+/z22285dqBs6UAdCo/l7J0Eirk74WivwyyZMRnSKOTmwp19P+NRrg59R39NxYqZI2XFihVj8uTJaDQavvvuO/73v//h7u7+TNd2d3txb4wXXUhy0KBBzJs3jyFDhljUH5IkibFjx2I2m/noo4/+83Pn5uZGnbIxBF99gKO9I3onZ7SazJFCk1kiMTGFJmU9KFFEDD8pBTX6G2pC5KN81JhRnjtQuV1QODk5mZSUFMLDw+VFgKdOnWrhQO3fvz/bdb28vJgzZw7/93//B2TWiOrXr5+8/a233mLLli3s27dPfmzGjBmMHTtWnqobPXo0v/zyC+fPn+err76Sa0w9CVs6UAcu3UcyS+jtNKQbTCSlG/hjQrdH9rhOx/plczy+ePHiubr+i+JFrwU3YsQIduzYQcOGDRk0aBDNmzcnOjqagIAAgoKCWLhwIYUKFXqq/N5v4MeNB0lcvpOMLiEdJ72OVIOJpHQTJQs707u+nyqdgfyGmv0NNSDyUT5qzuildKDMZjPp6enY2f1zS487UA0aNCAuLo5Tp05Rp04dILMyOUD9+vWBzM5f6dKl+e2339iwYQNms5mBAwcyc+ZMPDw8rF7blg5U6FUtyckQmpREogFMz7XohHLIi7XgPv/8c9auXStPeQJUqFCBL774gmLFij1Tm/zdwD1DQ1hcPPFmDXqtRNVCEvVcEjgbHMnZ530TgmdGjf6GmhD5KB81ZvRSOVA3b94kIyMDBwcHEhISnuhAOTk5UaxYMdmBcnd3Jzo6mrp168pVyM+cOcPly5cZOXKkfFxAQABHjhzhwoULVu/Xlg7Uxd1XuHj8FgaTGTt7LY5aDRU/X48xMYariz8EjYZSVeuxYMZEateuTXh4ON9//z2//PILAD///LO8aLOSyau14N555x3S09O5e/cuzs7O8ojns2IwGPDYvZsvezYh3azB1cFOrkItUAZq9jfUgMhH+ag5o5fKgUpNTQUyO1YajYZevXrJ+zzuQF28eJG33nqLe/fucezYMaKjo9FqtTRo0EDeJ2vtvscJCwvj0qVLVKhQIds2WzpQ3u5OpBnNOOg0OOi0SGRWsy7g6Y1W74RkNjFo/Dc0apRZXqBGjRosWrSIw4cPc+PGDRo1apQvXuB52UZ7e3u5I/+8cCvgmC+e95cZNfobakLko3zUmNFL5UCtWbOG/v3789tvvzFq1Ci2b98uT8897kC1atWKVq1acffuXRo3bsxrr71GlSpV+OGHH/juu++ATI8KMssi1KxZE4DU1FScnZ25efOm1Q6ULR2o2w+TcbbXkmGSSDWY0GggbOY7Fvt80e1NvsjheD8/v1xd/0Xxoh0oW6FmN0AtiIyUjchH+ag5o5fGgVq9ejX9+/dnzZo1tG7dmsGDB1t4StbqQN25c4cmTZpQp04dli1bxsSJEy2Oyep8tWnTBqPRSPny5XnnncwOS4kSJazery0dqDNXtThKABoSDWAWDlS+QI1ugNoQGSkbkY/yUWNGL4UDNXz4cObNm4ezszM9e/bE3d2d2NhYWrVqJbfjcQfq6NGjtGzZkoyMDG7evMkrr7zCgwcPLDo/rVq1onjx4hQpUoQePXowduxYDh8+TM2aNXOc5rGlAxX6+2Uun7pNBmYc7UGr0VB+5HqM8fcJ/+l/aHT2ePmV4vP/fYCnpyeJiYls3ryZPXv2AJnTqZ07d85VG14EeeVAPW/U7AaoBZGRshH5KB81Z/RSOFDr169HkiSSk5MB5P+PGDGCrVu3AtkdqPXr11s8OXfv3gUyO0BjxowBMqfwjh07xpAhQxg9ejR2dnZoNBqrjlMWtnSgink4k2Iw46DT4mCX6UBJjo64FCyH1sEZyWRi9Pw1DG/3zxIrH3/8MWXLluX69et07tz5metACZ4dNboBakNkpGxEPspHjRm9FA7U7du3gX8cqPXr1zNq1Ch5jTvI7kB98803fPPNN1YdqEfx9fWlfPny9OjRg2bNmjF48GBu3Lhhi6fqX7kfn46jvRajSSLNaEanBWNaGukPbmNOTwGtjjmf98crfiTe3t4kJibyyy+/EBERAcD27dvp2LFjnrT9aVDLCJRAIBAIXg6EA/WYAwWwd+9e1q9fT0hICBs3bsRkMuHj45Pj/dpSIo9MSKWoiwOJ6UYeJmdgNEtcn/2IRG42cetiiMW3Dx8lp8eVhpDIBS8KkZGyEfkoHzVnlOcSeX52oD799FMWLVok1wRycHDAYDAwdOjQHO/XlhJ5bKSWe7EaDGbQSKDX/Psx+REhkQteNCIjZSPyUT5qzCjPJfL87EBt2LABOzs7uap5VmXzIkWK5Hi/tpTIHx69yeFdl9Hba3CwyxyFqzRqPfb29pyf9R6S2cSkwJ180ra2fIzBYKBu3brcunWLa9euUahQoVy14UWglik8NcuVakFkpGxEPspHzRnluUSenx2o5ORkudNlMBjk3ujbb7/NkiVL6N+/f7b7taVEHpdqwMFOi9FsxmiS0GpBMkNaXDTmjMwiomvmT8G/1DT8/PyIj4/nhx9+4ObNmwD89ddfFqNySkVtb0I1ypVqQ2SkbEQ+ykeNGeW5RJ6fHajg4GBMJpP8+5YtW5g4cSK9evWiU6dOVu/XpoU0Y1Mp6upAQrqB2GQDJkkiYrZlIc2wY/t54403rB7ftWvXXF3/RSEcKMGLQmSkbEQ+ykfNGQkH6m+exYEqVaoUH330EadOnSIsLAw/Pz9MJhOff/55jlNhtnSgHt7TEhWvIcMESGAnHKh8gRrdALUhMlI2Ih/lo8aMnsaB0kiPy0XPgfbt25OYmMjhw4fp1q0bRYoUsXCgdu3aRaNGjVi1alU2B2rLli0MGjSIVatW4eTkRHJyMnq9noyMDNLS0tixYwetW7emePHi3Llzx+q1sxyox0egPvvsM7799lurbc7aJzk5mZEjR1K7dm1+/PFHTp06JbcjJ6yNQPn5+fHgwYNcO1Arjt7g69+vYK8DR7vMRWlTkxKwt7fj3MxMB2rcj5v5rPPr8jFJSUnUr1+fe/fucenSpSf6W0pBOFCCF4XISNmIfJSPmjNKSEjA09OT+Pj4f/38Fg7UYw5UgQIFWLRoEUFBQYSEhFC9enVCQkKeeL+2dKCS0yXstRrMZgmTWUKrAUmCjMR4JEM6IPHH+mX0a1RBrgO1fPlyIiMjkSSJS5cu4evrm6s2vAiyRhjV0pFSoxugNkRGykbko3zUmJFwoP7mWetA7d+/n3bt2lGnTh28vb3/9X5t6UDdjEnCu6ADCWlG4lINmMwSEbMsHajjuzZQtuwGq8e3b98+V9d/0eR3F0rNboBaEBkpG5GP8lFzRsKB+ptncaD27dtHmzZt8PT05Pjx4+j1esaPH8/w4cOzdbSysKUDdf+OlgfxGtJMmSNPulydTfmoxYVSoxugNkRGykbko3zUmJFwoHLhQPXs2ZNVq1Zl216+fHkuXbpk9VibOlDBN5n5x2XstOBo/48DZafTcX72e0gmEyO/W83/9fSXj3nw4AENGzbk/v37hIaG5ospvCzy+xSemt0AtSAyUjYiH+Wj5oyEA/U3z+JANWzYkJ07dxIZGckHH3xAXFwcFStWZPPmzTnery0dqHSThE6rwSyB2Qx/z2RiTEtGMhpAMhNyZC8Z77xFgQIFMBqNBAUFERsbC8C9e/coUaJErtrwosjvnadHUaMboDZERspG5KN81JiRcKD+5lnrQL311lsWU38tW7bk66+/JjY21mopA1s6UOHRiXi56klIM5KUZsRklgifaelA/blqEUVXLbJ6vL+/v9XHlUh+959A3W6AWhAZKRuRj/JRc0aKcaDOnz9PWFgYo0ePZsuWLUyaNMnCgZo4cSLly5enXLlyFg6U2WxGp9Ph4+ODm5sbTZs2JSgoCMh0oDZu3MjEiRM5f/48Dg4OTJ48mbVr15KQkPBEB2r06NF89913ZGRkEBkZyfHjx5k3bx4TJ06U97lw4QIRERE4OztjMpkoWrQo0dHRAERGRlrtQNnSgbp7R0t8ooZUI5glUGkZKEA9/hOo0w1QGyIjZSPyUT5qzEgxDtSBAwcYOHAgq1ev5tKlS0yfPp1r166xa9cuhg4dSqVKlTh16hR169YlNjYWBwcHPv30U4oUKYLZbKZq1aqcPHmSjIwM6tSpw8mTJ9mxYwe///4727ZtIzw8PNu1+/btS2BgIJB9BKpDhw6yH/U4kiRx5swZatWqhb29vdXRkAsXLlCpUqVsj9vSgQo8coNvdl9BqwEn/T8OlE6jIfSbHkhmI4On/cD0j/6pOH79+nWaNm1KbGwsp0+fpmTJkrlqw4tCDVN4anYD1ILISNmIfJSPmjNShAM1bNgwgoKCWLp0KWazGT8/PyDTF1q4cCErVqwgJSWFy5cvs2/fPsaPH0+/fv3YuXMnsbGxVKlShUOHDgGwePFiPv/8cwC8vb2ZO3cuc+fOBf5xoDw9PRk4cKAspUN2B2rLli0AzJkzh5EjR9KzZ08CAwPl6cG1a9fi4eFBw4YNZedp27ZtdOnSBYPBkGNJA1s6UGY0ZM1kShL//GwyIElmMEtE3bmFVqtFp9MhSRK3b9+WO3QpKSn55gWekZGhik4UqNMNUBsiI2Uj8lE+asxIEQ7UsmXLKF68ODt37pT9px07dtCpUye0Wi3r1q2z6j8FBwdTqlQpwsLCiIqKwsvLi5YtWzJ48GBcXFyoXLmyfJ0sB2rVqlV8+umn/+o/QaYD9fXXX6PT6Vi2bJnceYLMkSR3d3cOHDiAwWDA3t4eJycnDAYDfn5+OS7lYksH6lpUIkVcHUhMNZKUbt2B+nXBZH5dMNnq8TmtkadU8rsHpWY3QC2IjJSNyEf5qDkjRThQiYmJ9OjRw6IG1MOHD+nSpQszZ84kMDDQag2oyMhIihcvTnR0tOxANWrUCIA2bdrg4OCQzYEaOnQosbGxNG7cmPj4eNzc3HBzc8PX15eKFSty8eJF4B8HKj09HUmSZLcJMke2WrZsyZw5c9BqtRQoUAC9Xi93wFq0aJHj/drSgbp1S0tyMqQbNZjNmaNQakYtHpQa3QC1ITJSNiIf5aPGjPLcgWrSpAlBQUG89957FjWgjEYjQ4cOpX79+uzevZs1a9YA2WtArVmzhho1agDIDpQkSWzbto127doxbNgwmzhQSUlJeHl5YTAYMBqNANjZ2WE0Gvn555/p2bOn1WNt6UAtPXydOX9eRfO3A6XhbwdKMhP6bS8kk5Feo2bw3ZhB8rcW//rrLzp06EBSUhJHjhyx6m0plfw+hadmN0AtiIyUjchH+ag5ozx3oOrVq8f+/fut1oBasGABy5YtY9y4cTnWgEpKSuLXX3/NVgPKy8sLQHagHq8B1b179//kQA0cOJCAgIBs03sXL14kNTWVGzduYGdnR6FChfjjjz/o2LEjTk5OOd6vLR0onU4HGtCgQSPxz9fwNCABaDQ4ODlZfNuwQIECmcf93bb88gLP752nR1GjG6A2REbKRuSjfNSYUZ46UEquAfVvVKhQgcKFC7N06VK++OILTCYT06dPx87OjrZt2+Z4nC0dqCv3E/EsoCcx3URSugmzJHH1MQcq4MtPCPjyE6vH16lTJ1fXf5Hkd/8J1O0GqAWRkbIR+SgfNWeUpw7Uo+vgDRo0iKpVq1KxYsVsNaAWLFggd0oeXwfPxcWF3r17M3PmTCIjI5kzZw7wzzp4q1atom/fvsybN4/69eszceLEf60BBXDz5k1iYmJ4+PAhACEhIQCULVsWFxcXXF1d6du3LwEBAUyenCllS5LEDz/8YHWEKQtbOlA3bmpJTwOjUYNR5Q6UWvwnUKcboDZERspG5KN81JhRnjpQj66Dd+fOHa5du0bDhg3x8/OjUqVK7Nq1i88++4yJEyfy66+/cujQIerUqUNqaiojRozggw8+4OLFi+h0Og4cOIDZbMbJyYnU1FTZgWrcuLFcWPNR/P395UCtjUD169eP5cuXZztu3759NG7cmNTUVDw8PEhLS7N6b/fv35enER/Flg7UjwcjWLDvGpIk4aS3Q6vJdKA0JgMX5vQGs4l2A0eydPoo7O3tkSSJXbt20b9/f9LS0ti7dy+1atXKVRteFGqYwlOzG6AWREbKRuSjfNScUZ46UI+ug+fr64vZbAbgxo0b3L9/n7i4ONzc3JgzZ47sFTk5OdGrVy/mzJmDt7c3x48fx2Qy0bRpU2bNmsXp06fp378/GzdupF27duzfv59hw4YRFRXFxo0b+e6777h+/TqzZ8/m9OnT1KpVK5v/BJmdqhIlSnD58mU2bdokr8uXxapVqyhYsCDXrl2Tpw0zMjIoXbo05cuXt9p5Ats6UE56O8wS6LRatI88rrPXo9HqkICyVWpZjHTVqVMHFxcX0tLS8Pb2zjcv8PzSzv+CGt0AtSEyUjYiH+WjxowU4UB98803NGzYkMaNG7N27VoWLlzIiRMnZAeqUKFCLF68mKpVq3Lo0CEWL17MRx99RMWKFZk2bRqSJPHnn39StGhRjh8/jqOjIxs2bGDx4sXo9Xrq169P//79Wbt2LR06dAAyJfFt27Y9ccTlyy+/JDAwUBbKHyUlJQWtVouPj4/sYN27dw+TySSXUrCGretAFXK2JyXDRFKGCUmSuPKYAzV3eE/mDrd+/KN1s5SOcKAELwKRkbIR+SgfNWekCAdqwIAB/Prrr1SpUoX27duj0Wjo3bs3AQEBfPTRR/Tr18+qSG4ymShcuDCpqalERkYSEhLCuHHjeP/991m0aBGhoaGEhYVZOFCRkZGYzWbi4+NlkXzTpk18/PHHREZGytN4WQ7UzZs3kSQJk8lESEiI7EA1b96czz//nCFDhjB06FDMZjN9+vQBkCuhW8OWDtTVCC3mDDAbNRiNYM7V2ZSNcKAELxKRkbIR+SgfNWaU5w6U2Wxm+/btVK9enfPnz9O6dWu2bNkizyueOXOGs2fPMnHiRIoVK0a5cuUIDQ2VRfIOHTqwc+dODAYDGo2GOnXq8Pvvv1O4cGF27NjB559/TmhoaLZr6/V6bt26hZeXl+xAVahQQS6kWbt2bU6fPp3tuCwHCjJfEEOGDOHatWvy9GOpUqWs1pzKwpYO1KKgcBYfiMBsNuNob4dOm+lASRmpXJzXDyQzb3Xux4pvJ+Hm5kZ6ejqrV69m5MiRmEwmfvvtt3xTjVw4UIIXgchI2Yh8lI+aM8pzBwrg0qVLnD9/Xl5MOCoqil69ehEfH8+ePXtIS0tj5MiR8mLCZcuWJSoqCpPJxMGDB3F1dWXPnj3cu3ePPn368NVXX8nX8Pf3p0+fPjRp0gR3d3dGjhzJ1q1bmTdvnuwpWXOg2rdvT+/evbl9+zaLFi1Cr9dbOFAA586dIzk5mZUrV2Jvby9/Q/BJ2NKBKuikx2SWsNNpsdNqkDKrP6F3dkFjZw9mMw1bd8bT01O+ZteuXZk5cyb37t2jYsWK+eIFrobO06Oo0Q1QGyIjZSPyUT5qzCjP18IDWLRoEZIkWV1MuEGDBqxdu5aqVas+cTHhmjVrUrNmTaZMmZJtMeEs1qxZw+7du/Hz8yMqKuqJbcqaZsuqVP44sbGxjBs3jm3bttGsWTMGDBhAzZo1GTFixBPPa1MHKjoRNyd7UjIy18IDuPSYAzV90NtMH2T9+LJly+bq+i8KNfhPoG43QC2IjJSNyEf5qDmjPF8LT8mLCT+J3bt3YzabuXPnDhUqVODKlSvUrFmTW7duyR1Aa9jSgbp0TYvGCFqzBoOKHSg1+U+gTjdAbYiMlI3IR/moMSObO1DBwcE0bNiQVq1asX379mzbP/nkE+bPn89XX33FmDFjMBqN+Pj4sGDBAr744gsiIiLQ6XRUrFiRunXrEhYWxv/+9z+cnZ355JNPuH//PmazGVdXV7766it8fX3p2LEj3bp1Y+3atYBlMc3169dz4MAB7O3tcXBwID4+nk2bNvG///0PV1dXLl68aFHZPAtHR0eCg4MBOHr0KIMHD0aj0VC+fHlat27N999/T7169Th8+DB//PEHzZs3t/p82NKBWrDvGksOX8dkMuNgr0MLpCUlIqUncmn+AECiRuO2rJg3HV9fXxITE/nxxx+ZMWMGABs2bKBZs2a5asOLQC1TeGp2A9SCyEjZiHyUj5ozsrkDFRAQwNChQwkICODu3bv4+voCMGfOHAYOHCj3Srt168acOXMYPnw43bp148MPP6R8+fKEh4czY8YMJk2aRIkSJdi9ezc//fQTN2/epFixYhQvXpwZM2YwYMAAPv74Y9zd3QHo3bu33IYff/wRo9HIkCFD5MfS09Nl8btTp07Ex8fz/vvvy9uXLVvGzp07WbduHQBpaWlyyYPRo0ej1Woxm83079+fzZs307VrV7788kvKlSvH6dOnc+xA2dKBKuTigNEkYa/TYq/VIiGh0YK+oAcaeweQzHQaMJwyZcoAmTW1PvvsM3755Rdu375NvXr18sULPCMjQzWdKFCnG6A2REbKRuSjfNSYkU0dqKSkJNauXcvJkyeJjIwkMDCQL774AoBChQpZ9EjLlCmDVqvl888/R5IkzGYzv/zyC+XKlQPg7NmzrFu3DgcHB9kzmjBhAlu3bqVx48Zcu3aNKlWq0KJFC+bOnUuxYsXkduzfv99iMeG2bdsSGBjIsGHD5H0eF8nd3d1Zu3YtrVu3ZtiwYRYCeWBgIA4ODqSmprJ69Wr523pZ+zzJr7KlAxURlYiLg440g5kUgwk7LYQ95kBN6u3PpByOL1GiRK6u/yJRgwelZjdALYiMlI3IR/moOSObOlDr1q2jYsWKVKhQgV69ejFs2DDGjh2LRqOhX79+vPXWW5QrVw4XFxc2btyIj48PAAsWLGDZsmXs2bNH7kBNmjSJFStWEBoaKo8ENWjQgGnTphEVFYWnpyeJiYlERkZSsGBBKleuLLtNq1atkhcTftJCv48yZMgQBg4cSMGCBcnIyECSJIupPZ1OB8CFCxfYsGEDXbt2JTY2FoCiRYvmeF5bOlBh17TYm6GAHhIyNKSr7/UqoyYPSo1ugNoQGSkbkY/yUWNGNnWg3njjDbp168ann34qu03r16+ncePG/Pzzz0yePJlr167Ro0cPrly5QsuWLZk6dSrFihVDp9Ph6enJiRMn5IYWKFCA4cOH8+233wJgMpmoWbMmHh4e3Lhxgxs3bqDRaHj11Vc5dOgQ27ZtY8iQIURFRVG2bFmio6NJT0+nQoUKNGjQgJ9//pm4uDg2bdrE2LFj5RpQU6ZMoXLlyqxbt47ff/+d+Ph49Ho9x44do2zZsmzYsIFhw4bRuHFjDh8+jJOTEytWrKBVq1akp6ezadMmOnbsaPU5saUD9d3eq/x2NpKSns5IkoTBaCby3h1ctEa2TuhBha4jqO//Njej48lIjsercCHMaYnsmP4BxtQkyrfoyfJvp+DpYGLFihV8/fXXtG/fniVLluSqXbZADVN4anYD1ILISNmIfJSPmjOymQN16dIljh8/zqZNmzIPtrOje/fuBAQE0LhxY6KioihTpgxOTk40a9aM77//Hn9/f4YOHcrChQupVq0aJ0+e5OzZs+zZs4cePXrI505MTGTJkiUMHz6cLVu2UKVKFdLS0nBxcaFFixYEBQUxYcIEpk+fzrx587h37x6XLl2Sj//rr784ffq0/CEcHx9vsT2rTEKW/wSZU0a1atVi37598mMrVqxgyJAh/PLLL/j7++Ph4UF0dDR2djk/VbZ0oJpV9uHPiw9ITDPh5mSPxl6DnRZci/jgVaEOtw6sp1i1htg5OONXMnO67ujWHzEb0nEsWIgiDbuzPewhY1pXYvTo0fj5+fHBBx8wbNgwxS0ynJdTeM+786ZGN0BtiIyUjchH+agxI5s5UAEBARiNRlkaB5AkCQcHBxYsWMCIESMYMWKEXGdJo9Fw4cIFVqxYwe7du7l3755cVuCvv/6iZcuWAISHh9O8eXM++ugjIFMQT0tLY+XKlfTq1QuAxYsXM3r0aCZNmsT+/futtq9YsWLExMQA1gtpBgYGym0bPnw4c+fOJS0tDQcHB/nxggULsnLlSpKTk9m+fTsLFiyge/fuT3xebOlAVS7qTKvKRdh2NpL41AzsdRr+mNDNYp+9EztbPTYtIZbDE97mMDD1sW1vvvlmrtqlNp5X503NboBaEBkpG5GP8lFzRjZxoB5dJLhFixYW2zp27CgvEgzIHZelS5fKvtQ777zDl19+yf379ylatCj9+vUjMjKSs2fPEhwczIkTJ3jllVdYvXo133zzDSVLlpQ7T4BcC+pRX+pRzGYzaWlpFk7Tk2pB3bx5E41GY3Xk6MKFCxw5coTChQvLo21PwpYOFICPCTwkLaGxGjJMuT6dwArP279SoxugNkRGykbko3zUmNHTOFD/uQP16CLBbm5uFtu6dOkiLxL8KAEBAbzxxhvodDqaN2+OTqejXbt2LFmyhF9++YU5c+ZQvHhxSpYsSbdu3ahduzY//fQT9evXx2Qy4e/vz+HDhylQoIDcmdq4cSPvvfce06dPZ9GiRYSEhJCamoqrqytJSUnY29sTEhICZK6NV6FCBbZt28b9+/d57bXXWLp0KZs3byYiIsLqfd69e5f69euj0+lISkpizZo1ACQnJ+f43IwdO9aiWnmWA9WiRYtcO1Ams8S3f17hAVG84qnF0U6L94R1ODq58ODGRc4FjMXZqwQVG3eggJsHGalJBK/4GslkpEHfMRSq1gQNGr57twYeBfRkZGRQtWpVunfvzpQpU3LVNjXxvKbw1OwGqAWRkbIR+SgfNWeUNYP0X/jPHaiAgAD8/f2zdZ4gswM1c+ZMzp49S/Xq1YF/fKmSJUvKNaM6derEkSNHaNCgASaTiQEDBpCRkYFWq2Xy5MlUr14do9HI4cOHLc7fsGFDfv75ZyCzI3Pp0iUOHDhA8+bNmT59Oh9//DEnT54E/vGaIHOR4IsXL7Jr1y4WLlzI8OHDSU9Pp0iRIlSuXJkLFy5ku5epU6dSoUIFFi9ejIeHB6+//jr379/n+++/z3Eqz5YOVMj1GA5ceYiniyOujnaYJTMZyY54eXlwJmA5zkVf4c1h32PQ2lHc3QmNRkP8nXDC9m7g1PrvqV++Me1qv0LpYplrBC5YsIDo6Gg++ugjub6W4PmjRjdAbYiMlI3IR/moMSObOFBZiwRb49VXX802TZblS61atQqdTofZbObXX3/F0dGRe/fusWnTJhYvXoxerwegc+fOzJ49m379+tGjRw9Wr15NZGSkXD5g6tSpjB8/nnfffVf+xh5kroUXGhrKb7/9xqhRo+jevTsTJkywaEurVq1o1aqVxWMDBw606EBlOVM1a9bk3LlzvPbaawDyfR04cICJEydanaqzJUGXojGYzH93niTSDGZSU9N4ePMq0VfPUPndsRR103P99j3OXruPl6cnZRt35erR30lPiOHeru95rfk0Tpw4wfLly/n+++8ZNGgQJUuWfOKo2otEDd++EwgEAsHLhc3WwluxYgXdunUjNDSUNWvWyOvhOTg4yL5U06ZNra6Hl8WjPpNWqwWw6KhlrYW3Zs0aWrduzeDBg3O9Ht6vv/5Kamqq/Pvu3bsZMWIELVq0sKh6/ii2lMjvxqWg02iIjE/lfmI6aQYToZP/kcgvrPmKC2u+yvH4qwe30ujVrRaP/fTTT/z000+5atfzRA0FNLNQs1ypFkRGykbko3zUnFGeLyac5Utdv34df39/atSoQYsWLUhLS6Nhw4YEBATg4uLCggULKF++PJC57Mv//vc/evXqhbOzM87OzlSpUoXExEQcHR3lD9msb9kNHz6cefPm4ezsTM+ePXF3dyc2NtZipCksLEwe4cri888/548//uD8+fMAsi9VtmxZXFxcSEpKYsaMGWzZssWiI7V8+XK8vLys3q8tJfLYSC13YjQY/15FWKfN1ekUiZoKaGahRrlSbYiMlI3IR/moMSObSORPQ0BAAA0aNODw4cOULVtWdqC6du1KZGQkJ0+eZMmSJWzcuFGebps8eTKDBw+mV69e8shTVqVwSZKyjSKtX78eSZLkaais/48YMYKtWzNHXCpVqpRtdGP37t2cPXtW/v1RX6px48acOnUKLy8vfv75Z1xdXfnxxx/ZsGEDnTp1khcefhxbSuQPj97k8K7L6O00ONhn9p4qjVqPvb0952e9h2Q2MXnl7/yvVU35GKPRSJ06dbh16xbXrl2jUKFCuWqDrVHTFJ6a5Uq1IDJSNiIf5aPmjGwikT8N27ZtY9SoUQQFBVk4UMuXL8fR0VGuFN65c2cLByrrW3zJycmkpKQQHh6ezYEqXLgwALdv3wawWA9v1KhR1K1bV26HtVpQWSNOAwcOJCAgIFvHrH///ha/N2/enM6dO7Np0ybu3bsnL03zKLaUyGNTjTjYaTGZJQwmCZ0GzGZIjY3CnJEKaFg5ezyve33JK6+8QlxcnLwwM8DJkydp06ZNrtpga7I6uWrqSKlRrlQbIiNlI/JRPmrMyKaLCf8X8rMDZY3ExEQAC8/pUWzpQN2JTaGoqwMJ6UZiUzIwmSUiZj+6mLDE5VOHaNasmdXju3XrZvVxJaIGF0rNboBaEBkpG5GP8lFzRopxoM6fP09YWBijR49my5YtTJo0ycKBmjhxIuXLl6dcuXIWDpTZbEan0+Hj44ObmxtNmzYlKCgIyHSgNm7cyMSJEzl//jwODg5MnjyZtWvXkpCQ8EQHatq0aWzcuJHQ0FBMpsyKlI87UG+//TZnz57lzp07lCtXjv79+/Pnn39SpUoVSpYsafV+belAPbyn5X783wU0JbDT/Osh+RY1uVBqdAPUhshI2Yh8lI8aM1KMA3XgwAEGDhzI6tWriYqKonv37ly7do2TJ09y/PhxRo4cyalTp6hbty5ly5YlKioKk8nEH3/8gYuLC1WrVuXkyZNs3LiROnXq8ODBAyCzpEDWTaanp/PXX3/x119/AZlTfVnLsjzuQGVkZKDT6SxGix53oOzs7NBqtWg0Gi5evMjo0aN58803Za/KGrZ0oB4E3+DoH1ews9fgaPeYAzXzXSTJzLiftjKiY335mJSUFOrXr8+dO3e4cuWKPO2pdNQwhadmN0AtiIyUjchH+ag5I0U4UMOGDSMoKIilS5diNpvx8/MDMn2hhQsXsmLFClJSUrh8+TL79u2TF/vduXMnsbGxVKlShUOHDgGZ6+B9/vnnAHh7ezN37lzmzp0L/ONAeXp6MnDgQIsaUI87UF9++SVffvklgYGBfPzxx+j1euLi4izavnHjRgCGDBnCjz/+yKhRo5g2bdoT79eWDlSSwYydToPZDCaThFYLkhnSE2IwG9IBiR2/LKJng5IUK1aM+Ph4fvzxR+7evYskSVy4cIGmTZvmqg0vioyMDFV0okCdboDaEBkpG5GP8lFjRopwoJYtW0bx4sXZuXOn7D/t2LGDTp06odVqWbdunVX/KTg4mFKlShEWFkZUVBReXl7yOnguLi5UrlxZvk6WA7Vq1So+/fTT5+Y/hYaGsnz5cgoVKvSvnSewrQN140Ey3gUdSEg1EpdqsOJAwak/t1Cx4harx7/99tu5uv6LJr97UGp2A9SCyEjZiHyUj5ozUoQDlZiYyNixY0lMTGTo0KHY29vz8OFDedmXwMBA2rZty5UrV2jSpAlffvklvXr1IjIykrJly6LX6+U6UFmjO61bt5Z/frQOVPfu3TGZTNjb2xMfH4+bmxtubm74+vpSsWJFLl68KLft888/Z82aNaSmppKamprNgTp//jyNGzdGq9USHR2Np6cn3bp1Y/z48Va/gQe2daCi72l5EKch7W8HSpersykftXhQanQD1IbISNmIfJSPGjN6GgdKI+X2K2pWaNKkCUFBQURGRvLFF1/g4uLC999/T/v27Rk9ejT169dn6NChVK5cmZMnT1KnTh3i4uJwdHQkLCyM69evc+PGDR4+fEhycjJ6vZ6EhAS6du3K+vXrAShevDh37tzJdu327dvLvpK1UaiaNWty5syZbMdlOVATJkywusium5tbtum+LKyNQPn5+fHgwYNcO1DLg28w64/L2Gk1ONpndp9SkxKwt9NxbtZ7SGYzoxasZey7TeRjYmNjef3114mMjOTChQs5dvyUSH6fwlOzG6AWREbKRuSjfNScUUJCAp6ensTHx//r57dNRqDq1avH/v378fX1xWQyyXWgtm3bxtKlS5EkicDAQKZMmUKxYsUAOH/+PB999BHe3t7s2bOH69evc/fuXYoWLUpERASlS5dm586dZGRkoNfruX37tkUNqLZt21KlSpX/VAfqSQ5UgwYN0Gq1DB8+nD///JOQkBAWL17M6NGj5Ws/ji0dqAyThE6rxSxl1n/6u5oDGSlJSEYDSGZO7NtBaofXKFiwIBkZGezatUsW7m/fvp2tPISSUcubUY1ugNoQGSkbkY/yUWNGeepAZdWA+uabb0hKSmLdunVyHahhw4axatUqBg8eTL9+/eQ6UJcvX5Y9qJ07dzJ16lQqVaokF9HcvXu3vMxKaGgotWrVsqgB1bZtW8xmM4mJibn2oIKDg6lWrRouLi7yY1kOVta1H8eWDlR4dBJFC+pJSDWSkGbMdKBmWjpQ+9YtwXfdEqvHt2jRIlfXf9EIB0pga0RGykbko3zUnNHT3NNzn8LbvHkz3bt3JyoqijZt2lCvXj3mz59PixYtCAoK4pVXXuHixYv8/PPPLFiwQB7RycjI4H//+x/vvfceRYoUAaBKlSocP34cg8FAnTp1OHnyJDt27CA2NpY+ffpQtmxZoqOjSU9Px93dnbi4OMLDw/Hy8mLTpk0MHToUFxcX2YG6efMmERERDB06lHPnzgHQoUMHFi9ejLe3NwDdu3fn9OnTxMTEEBMTQ9GiRenSpQsLFy5kx44dtG7dOts9T5o0yaoDtWrVqlw7UOvCtVyI1ZBqBOPfSV2b0T5X51QymzdvzusmCAQCgeAlJSUlhR49evynKbzn3oFq3749ZrOZb7/9lqpVq9KtWzeKFClCQEAAjRo1Yvv27Zw5c4bx48ezaNGibGvhbdmyhXfffZcNGzYgSRIFCxakadOm7N+/n5iYGHbs2MHXX38tF9a0uBmNhlOnTlGrVi2ro0/9+vVj+fLl2Y5r2rQpe/bsAcDDw4PY2Fir95ZTB8qWDlRg8A1m/3EFnQac9P84UDqthtDZPZDMJoZ+HcDkgR3kY27dukWTJk14+PAhZ86cyVdTeMKBEtgakZGyEfkoHzVnlKcO1LZt2wAYNWoURqPRYi28HTt24OTkRIkSJejUqVOOa+FptVpMJhORkZFW18Lbv3+/fL3H18Lbtm0btWrVsuo/jR49muXLl3PixAnOnz/PsGHDWLNmDW3atOHu3bv4+vri6+uL2Wy2cKOyRpiy2vI4tnSgzGjQajSAhCRB1uo2ZmMGktkEZhO3rl1Co9FgZ2eHJElcvXpV/iZBQkJCvnmB5/fO06Oo0Q1QGyIjZSPyUT5qzEgRdaCUuBZecHAw7u7u1K1bl/PnzwPg7++PVqvl2LFjdOrUCTc3Ny5cuCDXoAIIDw8Hcv6At6UDdTUykSKuepLTjaQazEiSxMXHHKjNi7/CffFXVo9/8803c3X9F0l+959A3W6AWhAZKRuRj/JRc0aKqAMVGxvL9evX8ff3p0aNGrRo0YK0tDSLtfAWLFhA+fLlASzWwnN2dsbZ2VmuA+Xo6Ch/uMbExACWdaB69uyJu7s7sbGxT1wLLzIykoIFC9KmTRv27NlDRkYGXbt2xdXVlevXrwPQu3dvgoODKV26NCaTCTs7O5KTky2u/Ti2rAN1+7aWjFTwcoBkyKwHpVLUUgMK1FkfRW2IjJSNyEf5qDEjxayFd/jwYcqWLcvQoUMJCAiga9euREZGcvLkSZYsWcLGjRuzOVC9evWSR54kSUKj0SBJUrZv0q1fvx5JkuTOTdb/R4wYIdeBenwtPIA7d+5w8+ZN+fctWzIreGc91qJFCzQaDSkpKfL1XV1dSUhIkEfBHseWa+Eln7rDkkMReHk4odVokMwShSavw93Vlc3/1w2v2i1o0O1j7iWk4V3QAQd7HbdCDnLgh8znte4n3zPinSa0rurN/fv3ee+994iMjOTUqVM4OTnlqm3PGzVM4anZDVALIiNlI/JRPmrOSBFr4Y0aNYqgoCALB2r58uU4OjoSFxfHpk2bcnSgkpOTSUlJITw83KoDBZn1jSC7A/WkOlBmsxmTycSJEyfk/bZv3067du2oWrUqAH/99RdarZaUlBSioqIoUqQI06dP58svv5TX83scWzpQ/lW82XYukjtx6RR3d0KjBTu9Izq9A9712nDr0K9cLFmZUrXfwkmfea1z21eg1dnhXbEOBX1K83tYNG2qF6N48eIsW7aMmjVrsm3bNnr27Jmrtj1vXvQUni07bGp0A9SGyEjZiHyUjxozEg7U3+RUB8raebOoU6cOWq2WFStW0K9fP5KSkggMDJSXhrGGLR2oQo46RjQrw6w/rhB2L4EMkwlDhobQMf8sEHzu5ymc+zn7sXdDj3F3bOaU5vIPLLd9+OGHfPjhh7lqW37HFh02NbsBakFkpGxEPspHzRkpyoEaNGgQVatWpWLFikyaNCmbA9W2bVsguwPl4uJC7969mTlzJpGRkcyZMwf4x0NatWoVffv2Zd68edSvX5+JEyeSkJDwRAdKq9Xi7OzMoEGDWLx4MQaDgU8//RQHBwf5w9TV1ZUhQ4YwatQoPvjgA8xmMxqN5olzvbZ0oADupkBcjJbUNA0ZZtD8+yGC/4AtnSs1ugFqQ2SkbEQ+ykeNGSnKgZowYQI6nY5WrVrRvXt3rl27xsmTJwkJCWH37t0MHz4cyAzip59+AjI7OpUrV+b06dPUrFkTjUZDrVq15OVJAKZPn47RaGTIkCEMGTJEfnzq1KkEBgYC1h0oLy8vYmJiqF+/PgDlypWzqDo+YcIEFi1aZHGMJEm0aNECo9FoMXqVhS0dqNiUDD5bfw6DPpXqXo7YaTREP4imxnd/cuy3lVzfvYIKHYZQvmE7ChZwQJIktk3qTdKDSPxqvUm5d0bj5erInG7VcbDTcuvWLWrWrMmsWbPo379/rtqW37HFFJ6a3QC1IDJSNiIf5aPmjBTlQLVvn1k1e8eOHWi1WhwcHIiLi2Pp0qXZjsvqnHh5eXH27FkaNmzIrFmzuHfvnuzrZFUM9/f3p0+fPhgMBqZOnUr79u3ZvHkzn376qXy+xx0ob29vbt++TZUqVVi7di0Gg4F+/foRExMjn9fV1ZUaNWqwa9cu+bi33nqLK1eucOzYMV577bVs7balA3UkPIo78WmU8CiATqvBLJkxZqShKeBIZPBWfF5tQ5WmnYhOTKeAI9jb6ajWpg9HAr/i5qn9+DTuQ5/XX8fFyYGkpCQ++eQT3Nzc6NGjh+Jf+PlZKlejG6A2REbKRuSjfNSYkWIcqOnTpzNlyhTWrl3LwoULqVChAtu3b2f16tUUKlSI5s2by/J28+bNZYlcr9eTlpbGnDlzqFq1KjVr1qR169asWrWKsmXLAjB37lwLB6pDhw5UqVJFLqRpDS8vL4xGI5999pk8AvX+++8zbtw4SpQoIbfdwcFB7lCdOXOGK1euAJkSujVs6UAdD3/A3/YXMckZJKUZ+XNCN3n7vWPb2Xhse47HH/umP8e+gb6PPe7j45Ordr0I8mNdKDW7AWpBZKRsRD7KR80ZKcaBcnV1pUqVKrRv3x6NRsOwYcPo3LkzAQEBnDhxIkeJPCMjA0dHRz777DPZgfr9998BuHr1KrVq1crmQN29e5e4uDiLr+YPHTqUBQsWyBJ5VFQUdnZ2zJkzhwoVKmAwGFi+fDkajYYbN25Qu3Zt2rZty5w5c5g8eTLvvfce06dPx9nZmSJFiuTYMbOlA3Xtupb4RIiKSyLdBM913R2Fk5/rQqnRDVAbIiNlI/JRPmrMSBEOlL+/P6tXr+aNN95Ap9PRokUL4uPjKVWqFLNmzWL69Ols3brVaiHNqKgoqlevns2BevjwIZGRkUDODtSpU6dybFdkZCTFixfP5kB5eHjI523atCm//PILn3/+OZMmTUKSJOzs7OjYsWOOdZNs6UDdDArn3IEIzJIZZ0c7tBqoNGo9UkYqF797H8wmmnQbxPLZ43F1dcVgMLB+/XqGDRuGwWBgx44dNGjQIFdtyCvy4xSemt0AtSAyUjYiH+Wj5owU4UBdunSJqlWrUrJkSYtCmkeOHEGSJDp06JBjIU1Jkrhw4QKvvfaa7ED17t3b4hpZDlSTJk04ePAgY8aMwWw2M3r0aHmf+fPnM3/+fIvjoqKiKFeunOxAvf/++yQlJVnsExwcjIuLCyNGjGDevHls377dqjyehS0dKFcnPSazhJ1Oy6MFF/TOLmh0dqDRUL9ZG7l8g729Pe3atWPKlClERkZSrly5fPMCz48dppxQoxugNkRGykbko3zUmFGeO1CQOQr1+GLCWYU0FyxY8MTFhJOTk0lKSuLnn3+maNGi1KxZk2HDhlkU0pw7dy6QWUhz3LhxbNq0yWIxYWuYzWZSUlJYsmSJXEhz7ty5tGvXTm5HWFgYixYt4vz583z88ce0a9eOFi1aPPFebboWXlQi7s72pKQbSTGY0Gk1hD22Ft6MDzsxI4eSTuXKlcvV9V8k+dF5ehw1uwFqQWSkbEQ+ykfNGeW5A5WfC2lu27aN0qVLs3z5cvbu3UuRIkUYOHAgM2fOtDj3o9jSgboSrkVrhCJ6SMjQkCLWwssXqNENUBsiI2Uj8lE+aswozx0opS4mrNVqcXJyonnz5qSnp6PRaNDpdBaFNM+cOcPly5f56quvAIiOjiYgIICQkBBOnjxp9X5t6UDdOhDBr3/d4ZXCTpnrApol/Cavo4Cdls3julG67YcMGDCAwY3KWBx37NgxWrVqxaZNm2jcuHGu2pATkiTRsWNHQkJCmD17Nh06dCA+XeKTxb8RvGY+Sbcv0XLUQtx9S5GQaiQ+1cDrZTwY1aICWm32KVE1TOGp2Q1QCyIjZSPyUT5qzijPHSglLyacdd5Hf37096xSBR4eHvTq1YuxY8dy9uxZWrZsyaVLl6hQoUK289l6LbzfL0QRm2LE08UBs9aMnd4RNy8vilZ9g9sH1lN1ZH+L6yQnJ/Pll19SpkwZmjVrluMiyLnl4MGDHDhwgF9//ZWWLVsCsPX8DVIK+NLyk5nsmPo+YbvX0PD9cRQqoENvp+PUjXguR6dQrbh7tvPlpym8f+vsqdENUBsiI2Uj8lE+aswozx0oJS8mnJqayoEDB7ItJpzVDi8vLwD27NlDzZo1AXBzcwPg5s2bVjtQtnSgSns48k4dX1Ydv8XVqER0GkhO1ZAUnUTk2YMAvN2oXo7H53YE7L/QpUuXHLclPbhLxDHLYd4/x9i6RbYnp86emt0AtSAyUjYiH+Wj5oyEA/U3z7qYMECbNm0wGo2UL1+ed97JlLazim0+jq3XwrM3gItBw+0ELWl/O1AOxtRcn1fw7Pybr6VGN0BtiIyUjchH+agxI+FA/c2zOFCtWrWiePHiFClShB49ejB27FgOHz5MzZo15bY+ji0dqAyjmSnbw3hALGW8dbjo7Xjw8CGOLm5o+nzJhZVf0qJlC0aPGoWfnx+xsbEsWbKEH3/8kUmTJlksbfO8mT59Oj/88AMXLlyQp7T+b3MoF+4mUMzDieOr53D7zGE6fbUejUaDWZK4HZNK3wYl6FK7mM3a9SLIaQpPzW6AWhAZKRuRj/JRc0bCgcqFA+Xl5cWxY8cYMmQIo0ePxs7ODo1GY9VxysKWDtTR69GcuhmPr5sTTnodZskMxjRc7Fy4s3clbqWq8fHk73i1si+QuUTLt99+i729PbNnz+bDDz/E1dU1V23IiX79+jF79mzmzZvHxIkTAWhe2YcL9xKJunGNiGO7qdTsHXRaHQAPEtMo6KTnrQpFsz0vahDIH0WNboDaEBkpG5GP8lFjRsKB+ptncaAAfH19KV++PD169KBZs2YMHjyYGzdu5Hi/tnSggi7ex2Q242CvIcNoIjndyB+PrIUH0OFV6yNj8GLWvJs1axazZs2yuu3cjhWc27HC4rHtn2XfLz8J5E9CzW6AWhAZKRuRj/JRc0bCgfqbZ3GgAPbu3cv69esJCQlh48aNmEymJ3ZEbOlAnb2qJSUZwpKTSTCAyfp6xvkeNdWAAnW6AWpDZKRsRD7KR40ZCQfqb57FgRo/fjwzZszAyckJT09P7O3tMRgMfPzxxznery0dqLA/LnPpxG0yTGZ0Og0O9loqfr4eQ0I01374GDQ6ipWrzJyp46lduzbh4eEsXLiQLVu2AJmdyA4dOuSqDf8FSZIIDw8nLS2NEiVK4OLiQrrRzIPEdOx0GrxcHZ64HI5apvDU7AaoBZGRshH5KB81ZyQcqFw4UJs2bcLBwQGDwYCjoyPOzs7ydGJO2NKB8inkTKrBjIOdFgc7LRISOgdHnIuVQevgjGQy8dk3gbzTrjaAXPupbNmyXL9+nQ4dOuDu7p6rNvxXsr7B+ChFPV/IpRWHGt0AtSEyUjYiH+WjxoyEA/U3z+JA3b59m7S0NCCzl53VMfvqq68oW7Ys/fv3t8VTliP34tNw1mvJMEmkGU3YaTUY09NIjbqBOT0Fjc6OmZ/2xCt+HHXq1OHUuYv8uHghERERQOY0Z6VKlXBycqJSpUrodLoX2v6nRS0jUQKBQCBQN8KBesyBCg4OxmT6Z8G5pUuXMm/ePAYMGECnTp2s3q8tJfKohDR5+isqMZ0Mo5lLs/5ZTFgyGYkMv0ivXr2sHv+kqUclkt9lcjXLlWpBZKRsRD7KR80Z5blEnp8dqPv37zNnzhx27twpP5F2dnYsXrw4xyVRbCmRx9/XEpegoYiThLceMnRwIVdnVDZqkcnVKFeqDZGRshH5KB81ZpTnEnl+dqCOHDlC9erV6devH05OTkyZMoUjR44wYMAAli1bZvV+bSmRu197yNQdF3EpoMdZr0MyS7SYvA7Pwp7smPERZp09r380izQT+BZyRKPRELJlCRf+WIPOXk+90T/TvnYJebHhWbNmMX36dP766y9KlSqVq7bZgvw+hadmuVItiIyUjchH+ag5ozyXyPOzA/XFF19Y3EurVq2oWbMmK1euZMmSJVYdIltK5A3KetGgzAMOXnmAm6MdBZ3s0No7EpdqoHjzfoQGjudYwDhqt++Hxr0KCfdvcXHPeiSziZpvD8CjoCtHw+Po+zq4OdszbNgwFi1axKpVq5g0aVKu2mYLlDCF9zw6cWqUK9WGyEjZvKh8TCYT9+7dQ6fT4e3t/cRvCwssyav3kNksEZdqQKsBNyf755pZnkvk+dmBskZKSgqSJGE2m612oGzpQGmAEc3K4Olsz77L0dyOTSU5TcPxsS3lfWKv/MWeb//KduzJ9Qtg/QIAto6w3DZ79mxmz56dq7apldx04tTsBqgFkZGyeVH5GAwG5s6dyw8//MDNmzcBqFKlCsOHD6d3796iI/UE8uo9ZDJL7A6LYlfofW7FpKDRQHkvV9pW9+b10h7PJTPhQP3NszhQy5YtY/ny5dy5c4fw8HBKlixJeHg4bdu2zbFnauvFhAFKAF2KQmSKBrzg+HM5q8Aaz8PDUqMboDZERsrGlvmYTCZmzpzJyZMnady4Mb169cJoNLJ//34GDhzI9u3b6du3r82urxZe5HvILMHuOxr+eqAFJJz+7r0ceBDHkYu3ecvHzGte0hPP8V8QDlQuHCitVktoaCiJiYkAhIeH07VrV1auXJnj/drSgXqcrLnnqKgo7O3tSUg18Om6sySnG/EqmDmNeCTwK+5fOUPbcUuJTIH6pTz4onUFNBoN27dvp1evXuzYsYMGDRo817aphdxM4anZDVALIiNl8yLy+fnnnzl27BibNm2ibdu2FtvmzJnD6NGjGTVqlNXadoK8eQ8di4jhWsRFihXRUdDJ8prRiemEpmnoX78aJQvnTsEQDtTfPIsD1bdvX/r27UtQUBD+/v5Uq1aN9evXP/F+belAPY7ZLGGWwN3dnYyMDArb29OpVnGWH4ngfmwyngWdqdaqJ7dCDvL7vM+p3vEjOnetjslkYu3atYwZM4bmzZvz5ptviiHqHMjtFF5aWhoZGRnZOv22IL9L93mJcKCUjS3zCQgIoEWLFnTs2DHbts8++4yFCxcSEBDAa6+9ZpPrq4UX+R7ad/kBRrOEu3P2z1ovV0ciHqZw8Gos5bzdc3Ud4UD9zbM6UPv376ddu3bUqVMHb2/vf71fWzpQWZy+FcfvofcJuRVHTKyWv6QLTO1c84nHJNy4wKF5n/D6vE8sHt+9ezeurq7PpV2CvEUJ0n1+QzhQyuZF5HPx4kWGDRuW4zXefPNNLly4IF4jOZAX76Hw6CQc7bSYJesLwuo0cONhUq7b9FI4UAsXLmTo0KF4enrSsWNH6tWrR0JCwr86UM7OzrRq1YqMjAwyMjKws7NDr9fL51+yZAkfffQRzs7OHD9+XC5lMGTIEIvO2aPY2oE6Ga1h3z0tGSZwtMvsDP5x5lauzyvI/6ilblZeIBwoZWPLfLRaLceOHcvx/XP+/Hm0Wq14f/0LL/I9FPdAS0wqkGZ9e0Kqhrs3E9mxI+dl1/4LL4UDtXLlSiRJIjo6GoATJ04AmVN9gYGBgHUHSqfTyd+q0+l0ODk5kZqaKm9ftmwZJpNJdqBSUlKYMGECK1as4MqVK1bv15YO1LXoZAJ+PYebm4SXqwOSWSL6QTSlfTy5VbMJD6+e5ucNW2hev7p8THx8PB06dCA9PZ0jR46IqboXiMFgYO/evTRt2vSFDG2LKbynRzhQyuZF5NOzZ09WrlxJYGBgtr+jL1++zNmzZ1m8eDFt2rSxyfXzO3nxHkoueoclhyIoXMgJndbyMy3daCI9IYP3mlXgzXK5W4D1pXCgjh49CmQ6UD179qRdu3Zs2bLFoh2PO1AFCxYkMTGR9evX07VrVyDzXxrVqlUjPj4egMOHD1scHxcXR7FixQgLC8vxfm3pQB28+pCkdBMlCzuj0Wgwa80YM9JIionk/rmDlGz5PjeNbhbX8fT0ZPr06bRt25Zjx47x5ptv5qoNLwo1dAayFqF2d3cXH84KRzhQysaW+Xz66acsW7aMDh068MMPP1ClShUkSeLw4cP069eP0qVL06tXL/H6+Bde5HuoRVUfdodFcSMmBZ+Cjjja65AkiZQME/cTM6hR3I3Xy3lhb5+79V5fOgeqUqVKVqtq79+/nyZNmhAREUHJkiXlD2hPz396qHfv3gWQFxC2Rnx8fI7Td2BbB+pSZAJ2OpDIHIWTzBJ/TOgmbw/f8RMjd/zEyByOb926da6u/yJRg8/ztG7A/fv3WbRoEevWrSMmJoZSpUrRv39/+vTpY7VT/ryJTclg36VoDlx5SHK6ET8PJ5pV9KJ+yULY6f69Rlp+RDhQyuZF5FOsWDG2b99Ot27dqFq1KuXLlyc9PZ0bN25QpUoVNm7ciL29vXiN5EBevIfcHLSMbVWeOX9e5dqDZIwmMxLgaKel7ivuDPcviw4zBoN1R+q/ohgH6vz584SFhTF69Gi2bNnCpEmTLByoiRMnUr58ecqVK2fhQGUVrPTx8cHNzY2mTZsSFBQEZDpQ9+7do0uXLgQHBwPw8OFDkpOTiYyMxMnJCTc3NyCzU6bX6+UeZVaHzN/fH3t7e+rXr8+tW7fw8PCQp/E++eQT/vzzT65cuYKzszNlypTh7NmzzJ8/P8f7taUDFXlHS3wC2Gck5uo8+QE1+Qb/xQ24ffs248ePJzU1lbfeeovXXnuNy5cvM3ToUL7//nsmTJhg007UwzTYeF1LVKoGnVZCp4ELNzX8efYmVQtJtC5uRqV9KEA4UErnReQzb948jh49yqVLl9DpdPTr148aNWoQFhb2xFkHQSZ58R5q7grlgPupGrQaKOYsUVwfx4mDN57L+Z/GgdJINviudfv27UlMTOTAgQMMHDiQ1atXc+nSJaZPn861a9fYtWsXQ4cOpVKlSpw6dYq6desSGxuLg4MDn376KUWKFMFsNlO1alVOnjxJRkYGderU4eTJk+zYsYNKlSrRsGFD7ty5k+3affv2lR2ox7+F5+/vz549e2jatClHjx4lPT2dwoULU7x4cfz9/fn666/55JNP+OWXX2RZ/VFyeqqsjUD5+fnx4MGDXDtQv529x/x91yhWyBE7rRbJLHHv7i083N3ZPP493MvV5evZc3i7ho/FcQEBAYwaNYqQkBD8/Pxy1YYXhVqm8P6LGyBJEnXr1sVoNPL7779bfNszODiYNm3aMGDAAJtVizebJUZtPM/Z2/EU98h8bWWRlGYkNsXAR41K0+Gx15UaEA6UshH5KB81Z5SQkICnpyfx8fH/+vltMwdq2LBhBAUFsXTpUsxms/wh7uDgwMKFC1mxYgUpKSlcvnyZffv2MX78ePr168fOnTuJjY2lSpUqHDp0CIDFixfz+eefA+Dt7U3JkiXlOlCNGzfm6tWrdO3alblz51q041EHKj4+nv379wPw66+/4u7uzsWLF6lUqRJarVb+APvuu+/47rvvGDJkCD/++COjRo1i2rRpT7xfWzpQTSv5sPVsJDceplDM3Qk7nQY7vSNmjQ7f1zsRvnMJV4M2IlX/GL1ej9lsZvv27UycOJFu3bpRunTpXF3/RaKWKbwn1YHK6iQGBQVx7tw59uzZk62D+9Zbb/Hpp5+yYMECpk+fbpOO5ZlbcVy+n4S3myN6neVfAwWd9CSmm/j9QhQdaxVX7VSecKCUjchH+agxI0U4UMuWLaN48eLs3LlT9p927NhBp06d0Gq1rFu3zqr/FBwcTKlSpQgLCyMqKgovLy9atmzJ4MGDcXFxoXLlyv+pDY/7T6dOncJkMmFvb8+ePXvo0qULFStWxMfHh3v37llU5Q4NDWX58uUUKlToXztPYFsHytkexrQsz6w/LnP9YQpGk5mUVA07xjST95kycRxTJo7LduyaNWtYs2ZNrq4veL5kdRIPHz6Mm5sbDRs2tPoaad++PdOnT+fs2bMWxWGfF5cj40k3mnC0d7BaV8XVUce9uFTuxibj4+b43K+flwgHStmIfJSPmjNShAOVmJjI2LFjqVq1KhUrVmTSpEk8fPiQLl26MHPmTAIDA+US+o/6T5GRkZQtW5YCBQrQu3dvZs6cyfXr1wFo06aNxUhPSEgISUmZhbOio6MJCQlBr9dTuXJlnJ2deeWVV/D39ycoKIjIyEj0ej39+/dnxIgReHh4ULBgQRISEvD19ZUrzp4/f56mTZtSpkwZjEYjkZGRQGb5gyJFili93xexFl4rN7iKhrspgAuceC5nFbxosjyvK1eukJ6ezrZt27Czy/42zPIvjh49SlRU1HNvx9loDUlJWu4bk7BW5SLVCAazhv379uKmz75dDQgHStmIfJSPGjPK8zpQ8+bNA6B///6ZF7Gzo3v37gQEBDB06FBmzpzJL7/8wqVLlwCYO3cuP/30k3y8RqPht99+Y/DgwTRo0ECewujdu7fFdWrVqiX/cMT01wAAE0pJREFUvGrVKlatWkWJEiW4fv06r776KsuXL6dJkyYWPco5c+ag1Wrp0qUL6enp6PV6i3L+GzZsIDo6Wq4v5eOT6YBkndcaebEW3vi/18ITKIt/qwOV9VouVqwYgYGBZGRk8Pbbb2fbb8eOHXh7e/PBBx9YFIN9XpSLSuKvDedw0utwdcz+18CtmFRq+rjybodqqqsjpmZ/Qw2IfJSPmjPK8zpQ9erVY//+/fj6+sqPSZKEg4MDCxYskN2QrA6Uq6ur3AHx9vbm+PHjlChRQv7XekREBKVLl6ZYsWIW15EkicaNG1OzZs1s/hNk+lFZ1woPDycjI4O0tDQWLlzIwoULgcyOUdmyZeVjJk2aJP/ZvHkzISEh/3q/L3ItvCxEnSFl8l/rQNWtW5dmzZoxfPhwypcvLy9aKkkSK1asYMmSJUydOtVmYn0lX3fqlirMgctR6O10OP1dO0WSJB4mZ2Cn09KxVnGbdN6Ughr9DTUh8lE+aszoae7nuduhWTWgvvnmG0JCQuQ/Z86cwdfXl9WrV8v7Pl7oEqBBgwacO3fOYtpi9+7dFCxY8D/7T9aoU6eO7D9lcenSJW7evGnhPwkEL4pVq1bh4+ND3bp1adSoEX379qVSpUr069ePPn36MGrUKJtdW6PRMKxZOeqW9CA6MZ2IB8ncjEkh4mEKkgS9XnuFphW9bHZ9gUAgyO889xGorBpQAwYMkOsxZdGlSxcCAgLkiuPWaNGiBZUrV5b9p8jISMaNG8eQIUOy+U8ASUlJ2fwnyBTT+/Tpw549eyhWrBhubm4MGDDAwn8aOnQoDRo0sFhx++rVqyQlJREZGUlqaqp8ncqVK6v6X+OCF4+XlxdHjx7l119/ZfXq1Vy9epV69erxww8/8NZbb9l86qxQAT3TOlbjxPUYjoY/JCndSHF3JxpVKEJZL7HYtEAgEDyJ596BCggIwN/fP1vnCZAF8rNnz1K9enUrR2fK2o/7T3379mXy5MkW+z3qP506dcrCf4JMEezSpUtP9J9atmzJ999/b3HegQMHykU7H71O1rf5BILniYODAz169KBHjx55cn29nZY3ynryRtncrR8lEAgELxvPvQO1bdu2HLe9+uqrORajfJRH/aec+LfzPOo/ZeHo6GjhP1kjq1aUQCAQCAQCQU6os0KeQCAQCAQCgQ0RHSiBQCAQCASCp0R0oAQCgUAgEAieEtGBEggEAoFAIHhKRAdKIBAIBAKB4CkRHSiBQCAQCASCp0R0oAQCgUAgEAieEtGBEggEAoFAIHhKRAdKIBAIBAKB4Cl57pXIBf9USU9ISHju5zYYDKSkpJCQkKC6VbDVgMhH+YiMlI3IR/moOaOsz+3/smqK6EDZgMTERAD8/PzyuCUCgUAgEAielsTERKtr+j6KRvov3SzBU2E2m7l79y6urq5oNJrneu6EhAT8/Py4desWBQsWfK7nFuQekY/yERkpG5GP8lFzRpIkkZiYiK+vL1rtky0nMQJlA7RaLcWLF7fpNQoWLKi6F66aEPkoH5GRshH5KB+1ZvRvI09ZCIlcIBAIBAKB4CkRHSiBQCAQCASCp0R0oPIZDg4OTJw4EQcHh7xuisAKIh/lIzJSNiIf5SMyykRI5AKBQCAQCARPiRiBEggEAoFAIHhKRAdKIBAIBAKB4CkRHSiBQCAQCASCp0R0oAQCgUAgEAieEtGBUgALFy6kZMmSODo6Ur9+fY4fP/7E/devX0/FihVxdHSkWrVq7Nixw2K7JElMmDABHx8fnJyc8Pf358qVK7a8BVXzvPPp168fGo3G4k+rVq1seQuq5mnyCQ0NpUuXLpQsWRKNRsPcuXNzfU7Bv/O8M5o0aVK291DFihVteAfq5mny+emnn3jzzTcpVKgQhQoVwt/fP9v+L81nkCTIU9asWSPp9Xpp6dKlUmhoqDRo0CDJ3d1dun//vtX9Dx8+LOl0OmnmzJnShQsXpHHjxkn29vbSuXPn5H1mzJghubm5SZs3b5bOnDkjvf3221KpUqWk1NTUF3VbqsEW+fTt21dq1aqVdO/ePflPTEzMi7olVfG0+Rw/flwaOXKktHr1asnb21uaM2dOrs8peDK2yGjixIlSlSpVLN5D0dHRNr4TdfK0+fTo0UNauHChdPr0aSksLEzq16+f5ObmJt2+fVve52X5DBIdqDzm1VdflYYMGSL/bjKZJF9fX+mrr76yun+3bt2ktm3bWjxWv3596cMPP5QkSZLMZrPk7e0tzZo1S94eFxcnOTg4SKtXr7bBHaib552PJGV2oDp06GCT9r5sPG0+j1KiRAmrH865OacgO7bIaOLEiVKNGjWeYytfXnL7ejcajZKrq6u0fPlySZJers8gMYWXh2RkZHDq1Cn8/f3lx7RaLf7+/gQHB1s9Jjg42GJ/gJYtW8r7R0REEBkZabGPm5sb9evXz/GcAuvYIp8s9u/fj5eXFxUqVGDw4ME8fPjw+d+AynmWfPLinC8ztnw+r1y5gq+vL6VLl6Znz57cvHkzt8196Xge+aSkpGAwGPDw8ABers8g0YHKQx48eIDJZKJo0aIWjxctWpTIyEirx0RGRj5x/6z/P805BdaxRT4ArVq1YsWKFezZs4evv/6aoKAgWrdujclkev43oWKeJZ+8OOfLjK2ez/r16xMYGMiuXbtYtGgRERERvPnmmyQmJua2yS8VzyOf0aNH4+vrK3eYXqbPILu8boBA8LLx7rvvyj9Xq1aN6tWrU6ZMGfbv30+zZs3ysGUCQf6gdevW8s/Vq1enfv36lChRgnXr1jFgwIA8bNnLxYwZM1izZg379+/H0dExr5vzwhEjUHmIp6cnOp2O+/fvWzx+//59vL29rR7j7e39xP2z/v805xRYxxb5WKN06dJ4enpy9erV3Df6JeJZ8smLc77MvKjn093dnfLly4v30FOSm3xmz57NjBkz+OOPP6hevbr8+Mv0GSQ6UHmIXq+nTp067NmzR37MbDazZ88eGjRoYPWYBg0aWOwPsHv3bnn/UqVK4e3tbbFPQkICx44dy/GcAuvYIh9r3L59m4cPH+Lj4/N8Gv6S8Cz55MU5X2Ze1POZlJTEtWvXxHvoKXnWfGbOnMmUKVPYtWsXdevWtdj2Un0G5bXF/rKzZs0aycHBQQoMDJQuXLggffDBB5K7u7sUGRkpSZIk9e7dWxozZoy8/+HDhyU7Oztp9uzZUlhYmDRx4kSrZQzc3d2lLVu2SGfPnpU6dOigyq+Qvgiedz6JiYnSyJEjpeDgYCkiIkL6888/pdq1a0vlypWT0tLS8uQe8zNPm096erp0+vRp6fTp05KPj480cuRI6fTp09KVK1f+8zkFT4ctMvrss8+k/fv3SxEREdLhw4clf39/ydPTU4qKinrh95ffedp8ZsyYIen1emnDhg0WZSQSExMt9nkZPoNEB0oBzJ8/X3rllVckvV4vvfrqq9LRo0flbY0aNZL69u1rsf+6deuk8uXLS3q9XqpSpYq0fft2i+1ms1kaP368VLRoUcnBwUFq1qyZdOnSpRdxK6rkeeaTkpIitWjRQipSpIhkb28vlShRQho0aJD4cM4FT5NPRESEBGT706hRo/98TsHT87wz6t69u+Tj4yPp9XqpWLFiUvfu3aWrV6++wDtSF0+TT4kSJazmM3HiRHmfl+UzSCNJkpQHA18CgUAgEAgE+RbhQAkEAoFAIBA8JaIDJRAIBAKBQPCUiA6UQCAQCAQCwVMiOlACgUAgEAgET4noQAkEAoFAIBA8JaIDJRAIBAKBQPCUiA6UQCAQCAQCwVMiOlACgUAgEAgET4noQAkEgjxj//79aDQa4uLiAAgMDMTd3f2pzqHRaNi8eXOu2nH48GGqVauGvb09HTt2zNW5BALBy4HoQAkEApsSHByMTqejbdu2ed2UHBkxYgQ1a9YkIiKCwMDAvG6OQCDIB4gOlEAgsCkBAQEMHTqUAwcOcPfu3bxujlWuXbtG06ZNKV68uNURMEmSMBqNL75hAoFAsYgOlEAgsBlJSUmsXbuWwYMH07Zt22ca3dmyZQu1a9fG0dGR0qVL8+WXXz6xM3Pr1i26deuGu7s7Hh4edOjQgevXr1vd9/r162g0Gh4+fEj//v3RaDQEBgbKU4s7d+6kTp06ODg4cOjQIcxmM1999RWlSpXCycmJGjVqsGHDBotz7tixg/Lly+Pk5ESTJk0IDAy0mKacNGkSNWvWtDhm7ty5lCxZ0uKxJUuWUKlSJRwdHalYsSLff/99tnZv3LiRJk2a4OzsTI0aNQgODrY4x+HDh2ncuDHOzs4UKlSIli1bEhsby4oVKyhcuDDp6ekW+3fs2JHevXvn+NwKBIJ/EB0ogUBgM9atW0fFihWpUKECvXr1YunSpTzN+uUHDx6kT58+fPrpp1y4cIEffviBwMBApk2bZnV/g8FAy5YtcXV15eDBgxw+fBgXFxdatWpFRkZGtv39/Py4d+8eBQsWZO7cudy7d4/u3bvL28eMGcOMGTMICwujevXqfPXVV6xYsYLFixcTGhrK8OHD6dWrF0FBQUBm561z5860b9+ekJAQBg4cyJgxY57yWYNffvmFCRMmMG3aNMLCwpg+fTrjx49n+fLlFvv93//9HyNHjiQkJITy5cvz3nvvyZ3LkJAQmjVrRuXKlQkODubQoUO0b98ek8nEO++8g8lkYuvWrfK5oqKi2L59O/3793/q9goELyWSQCAQ2IjXX39dmjt3riRJkmQwGCRPT09p37598vZ9+/ZJgBQbGytJkiQtW7ZMcnNzk7c3a9ZMmj59usU5V65cKfn4+Mi/A9KmTZvkbRUqVJDMZrO8PT09XXJycpJ+//33HNvp5uYmLVu2LFu7Nm/eLD+WlpYmOTs7S0eOHLE4dsCAAdJ7770nSZIkjR07VqpcubLF9tGjR1vc48SJE6UaNWpY7DNnzhypRIkS8u9lypSRVq1aZbHPlClTpAYNGkiSJEkRERESIC1ZskTeHhoaKgFSWFiYJEmS9N5770lvvPFGjvc8ePBgqXXr1vLv33zzjVS6dGmL504gEOSMXV523gQCgXq5dOkSx48fZ9OmTQDY2dnRvXt3AgICaNy48X86x5kzZzh8+LDFiJPJZCItLY2UlBScnZ2z7X/16lVcXV0tHk9LS+PatWtPfQ9169aVf7569SopKSk0b97cYp+MjAxq1aoFQFhYGPXr17fY3qBBg6e6ZnJyMteuXWPAgAEMGjRIftxoNOLm5maxb/Xq1eWffXx8gMyRpIoVKxISEsI777yT43UGDRpEvXr1uHPnDsWKFSMwMJB+/fqh0Wieqr0CwcuK6EAJBAKbEBAQgNFoxNfXV35MkiQcHBxYsGBBts6ANZKSkvjyyy/p3Llztm2Ojo5W969Tpw6//PJLtm1FihR5yjuAAgUKWJwbYPv27RQrVsxiPwcHh/98Tq1Wm20a02AwZLvOTz/9lK0zptPpLH63t7eXf87q+JjNZgCcnJye2I5atWpRo0YNVqxYQYsWLQgNDWX79u3/+T4Egpcd0YESCATPHaPRyIoVK/jmm29o0aKFxbaOHTuyevVqPvroo389T+3atbl06RJly5b9T9etXbs2a9euxcvLi4IFCz5T23OicuXKODg4cPPmTRo1amR1n0qVKll4RQBHjx61+L1IkSJERkYiSZLc6QkJCZG3Fy1aFF9fX8LDw+nZs+czt7d69ers2bOHL7/8Msd9Bg4cyNy5c7lz5w7+/v74+fk98/UEgpcNIZELBILnzm+//UZsbCwDBgygatWqFn+6dOlCQEDAfzrPhAkTWLFiBV9++SWhoaGEhYWxZs0axo0bZ3X/nj174unpSYcOHTh48CARERHs37+fTz75hNu3b+fqnlxdXRk5ciTDhw9n+fLlXLt2jb/++ov58+fLcvdHH33ElStX+Pzzz7l06RKrVq3K9s3Dxo0bEx0dzcyZM7l27RoLFy5k586dFvt8+eWXfPXVV3z33XdcvnyZc+fOsWzZMr799tv/3N6xY8dy4sQJPv74Y86ePcvFixdZtGgRDx48kPfp0aMHt2/f5qeffhLyuEDwlIgOlEAgeO4EBATg7+9vdZquS5cunDx5krNnz/7reVq2bMlvv/3GH3/8Qb169XjttdeYM2cOJUqUsLq/s7MzBw4c4JVXXqFz585UqlSJAQMGkJaW9lxGpKZMmcL48eP56quvqFSpEq1atWL79u2UKlUKgFdeeYVff/2VzZs3U6NGDRYvXsz06dMtzlGpUiW+//57Fi5cSI0aNTh+/DgjR4602GfgwIEsWbKEZcv+v707Nm0YiAIw/AIuDdrCKoQKNQJXQmgETaVWC8QrqFV1K2iSGyHpEpLKByHG+PsWuCt/eI+792jbNoZhiNvt9nXOPS6XS+z7HsdxRN/3cb1eY9u2OJ2+Bw9VVcU8z3E+n73ADoXePn4P4wH4MymlGMcxcs7F39T8h2maommaWNf10VeBp2IHCuAF5ZwjpRQppR+PdAL3EVAAL6jrusg5x7IsUdf1o68DT8cIDwCgkCVyAIBCAgoAoJCAAgAoJKAAAAoJKACAQgIKAKCQgAIAKCSgAAAKfQL2GMKCQpZpqgAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -376,7 +376,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The above plot clearly shows that the credible intervals are too low. This is an example of how our defult prior (all $1$ s) can be a problem with many alleles. It's important to note though that this is a very small dataset (one study) and this will not be a problem for larger datases until the number of alleles is much higher.\n",
+    "The issue becomes even clearer if we compare the default model and compound model estimates directly. In the plot below, the dashed line shows agreement between the default and compound models. In this case, the compound model is overestimating rare alleles and under estimating common alleles. In other words, all allele estimates are being dragged towards equal frequency."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(caf.allele_freq, hdi.post_mean)\n",
+    "plt.vlines(caf.allele_freq, hdi.lo, hdi.hi)\n",
+    "plt.plot([0,.17], [0,.17], c=\"black\", linestyle=\"--\")\n",
+    "plt.xlabel('Default model AF')\n",
+    "plt.ylabel('Compound model AF')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above plots clearly shows disacreement between the default and compound model which indicates an issue with out choice of prior. This is an example of how our defult prior (all $1$ s) can be a problem with many alleles. It's important to note though that this is a very small dataset (one study) and this will not be a problem for larger datases until the number of alleles is much higher.\n",
     "\n",
     "We can solve this by using smaller values in our prior, e.g. $1/k$ where $k$ is the number of alleles. This is known as Perks prior. Unfortunately models with this prior take longer to fit (minutes rather than seconds). It is also particularly important to validate models that use this prior with [posterior predictive checks](https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/posterior_predictive.html) and as described in the [credible intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb).\n",
     "\n",
@@ -385,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -403,7 +436,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 299 seconds.\n"
+      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 293 seconds.\n"
      ]
     },
     {
@@ -418,7 +451,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -433,6 +466,31 @@
     "HLAfreq.plotAF(caf, aftab, hdi=perks_hdi)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(caf.allele_freq, perks_hdi.post_mean)\n",
+    "plt.vlines(caf.allele_freq, perks_hdi.lo, perks_hdi.hi)\n",
+    "plt.plot([0,.17], [0,.17], c=\"black\", linestyle=\"--\")\n",
+    "plt.xlabel('Default model AF')\n",
+    "plt.ylabel('1/k Compound model AF')\n",
+    "plt.show()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

From 743a0817e2065d12d39f03e2d65da5c5ea7dd0c0 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 14:55:46 +0000
Subject: [PATCH 105/192] Filter Guinea from the global PCA

---
 examples/paper/globalPCA2.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/examples/paper/globalPCA2.py b/examples/paper/globalPCA2.py
index 72e29dc..87d7f29 100644
--- a/examples/paper/globalPCA2.py
+++ b/examples/paper/globalPCA2.py
@@ -20,6 +20,10 @@
 AFeatures = pd.read_csv("data/example/globalPCA/AF_features.csv")
 regions = pd.read_csv("data/example/countries.csv")
 
+# Remove Guinea because it includes data from
+# Guinea-Bissau and Papua New Guinea
+AFeatures = AFeatures[AFeatures.country != "Guinea"]
+
 pca = PCA(n_components=2)
 pca_embedding = pca.fit_transform(AFeatures.loc[:,'A*01:01':].values)
 AFeatures['pca0'] = pca_embedding[:,0]

From 6b29ddbe0bffa38225db8ea360437f68bbf9d0c8 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 14:56:38 +0000
Subject: [PATCH 106/192] Move data checks from hdiAF to _make_c_array

---
 src/HLAfreq/HLAfreq_pymc.py | 32 +++++++++++++++-----------------
 1 file changed, 15 insertions(+), 17 deletions(-)

diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 91567ed..ea52a44 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -5,9 +5,20 @@
 import pandas as pd
 import HLAfreq
 
-def _make_c_array(AFtab, weights="2n", datasetID="population"):
+def _make_c_array(AFtab, weights="2n", datasetID="population",
+                  format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
     df = AFtab.copy()
-    df = HLAfreq.unmeasured_alleles(df, datasetID)
+    HLAfreq.single_loci(df)
+    if unique:
+        assert HLAfreq.alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
+    if complete:
+        assert HLAfreq.incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+    if resolution:
+        assert HLAfreq.check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+    if format:
+        df = HLAfreq.formatAF(df, ignoreG)
+    if add_unmeasured:
+        df = HLAfreq.unmeasured_alleles(df, datasetID)
     try:
         df['2n'] = df.sample_size * 2
     except:
@@ -51,8 +62,7 @@ def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
         idata = pm.sample()
     return idata
 
-def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True,
-          format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True):
     """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
     
@@ -82,19 +92,7 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, p
             This way it matches the output of combineAF().
     """
 
-    df = AFtab.copy()
-    HLAfreq.single_loci(df)
-    if unique:
-        assert HLAfreq.alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
-    if complete:
-        assert HLAfreq.incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
-    if resolution:
-        assert HLAfreq.check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
-    if format:
-        df = HLAfreq.formatAF(df, ignoreG)
-    if add_unmeasured:
-        df = HLAfreq.unmeasured_alleles(df, datasetID)
-    c_array, allele_names = _make_c_array(df, weights, datasetID)
+    c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
     idata = _fit_Dirichlet_Multinomial(c_array, prior, conc_mu=conc_mu, conc_sigma=conc_sigma)
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
     post_mean = az.summary(idata, var_names='frac')['mean']

From ba7503d765473203ebf451b36995a2b89664436a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 15:01:55 +0000
Subject: [PATCH 107/192] Improve function doc strings: plotAF,
 compare_estimates

---
 src/HLAfreq/HLAfreq.py      | 3 ++-
 src/HLAfreq/HLAfreq_pymc.py | 1 +
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 6d07e06..292fdec 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -558,7 +558,8 @@ def plotAF(
         cols (list, optional): List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
         datasetID (str, optional): Column used to define separate datasets. Defaults to "population".
         weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-        hdi (float, optional): The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
+        hdi (pd.DataFrame, optional): The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
+        compound_mean (pd.DataFrame, optional): The high density interval object to plot post_mean. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
     """
     # Plot allele frequency for each dataset
     if not AFtab.empty:
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index ea52a44..1f9a0a7 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -109,6 +109,7 @@ def compare_estimates(AFtab, hdi, datasetID):
     Args:
         AFtab (pd.DataFrame): Table of allele frequency data
         hdi (np.array): Pairs of high density interval limits, allele name, and posterior mean from compound model.
+        datasetID (str, optional): Unique identifier column for study.
     """
     
     caf = HLAfreq.combineAF(AFtab, datasetID=datasetID)

From 80cc2a2d3f277b2493a4e72f4913fa389b208255 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 8 Mar 2023 15:19:12 +0000
Subject: [PATCH 108/192] Update to version 0.0.1.dev4

---
 README.md                                |   2 +
 dist/HLAfreq-0.0.1.dev3-py3-none-any.whl | Bin 18444 -> 0 bytes
 dist/HLAfreq-0.0.1.dev3.tar.gz           | Bin 20207 -> 0 bytes
 dist/HLAfreq-0.0.1.dev4-py3-none-any.whl | Bin 0 -> 19268 bytes
 dist/HLAfreq-0.0.1.dev4.tar.gz           | Bin 0 -> 20791 bytes
 docs/HLAfreq.md                          |  60 ++++++++++++++++++++---
 setup.py                                 |   2 +-
 src/HLAfreq.egg-info/PKG-INFO            |   4 +-
 8 files changed, 60 insertions(+), 8 deletions(-)
 delete mode 100644 dist/HLAfreq-0.0.1.dev3-py3-none-any.whl
 delete mode 100644 dist/HLAfreq-0.0.1.dev3.tar.gz
 create mode 100644 dist/HLAfreq-0.0.1.dev4-py3-none-any.whl
 create mode 100644 dist/HLAfreq-0.0.1.dev4.tar.gz

diff --git a/README.md b/README.md
index 258a74d..8d4b302 100644
--- a/README.md
+++ b/README.md
@@ -65,6 +65,8 @@ created with pdoc3 in pdf mode.
 # Install in dev mode
 pip install -e HLAfreq
 
+Update version in setup.py
+
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
 
 Run tests `pytest` 
diff --git a/dist/HLAfreq-0.0.1.dev3-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev3-py3-none-any.whl
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HcmV?d00001

diff --git a/docs/HLAfreq.md b/docs/HLAfreq.md
index a1048fc..43cb623 100644
--- a/docs/HLAfreq.md
+++ b/docs/HLAfreq.md
@@ -569,13 +569,17 @@ Generate a dataframe from a given html page
 Columns: []
 Index: [], AFtab=Empty DataFrame
 Columns: []
-Index: [], cols=['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'], datasetID='population', weights='2n', credible_interval=None)`
+Index: [], cols=['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'], datasetID='population', hdi=Empty DataFrame
+Columns: []
+Index: [], compound_mean=Empty DataFrame
+Columns: []
+Index: [])`
 
 
 Plot combined allele frequencies, individual allele frequencies,
 and credible intervals on combined allele frequency estimates.
-Credible interval is only plotted if a value is given for <code>credible\_interval</code>.
-Credible interval is calculated using HLAfreq_pymc.AFhdi() and PyMc.
+Credible interval is only plotted if a value is given for <code>hdi</code>.
+The plotted Credible interval is whatever was passed to HLAfreq_pymc.AFhdi() when calculating hdi.
 
 
 ###### Args
@@ -600,8 +604,12 @@ Credible interval is calculated using HLAfreq_pymc.AFhdi() and PyMc.
 :   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
 
 
-**```credible_interval```** :&ensp;<code>float</code>, optional
-:   The credible interval to plot. Defaults to None.
+**```hdi```** :&ensp;<code>pd.DataFrame</code>, optional
+:   The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
+
+
+**```compound_mean```** :&ensp;<code>pd.DataFrame</code>, optional
+:   The high density interval object to plot post_mean. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
 
 
 
@@ -768,7 +776,7 @@ Data loaders
 
 
     
-> `def AFhdi(AFtab, weights='2n', datasetID='population', credible_interval=0.95, prior=[])`
+> `def AFhdi(AFtab, weights='2n', datasetID='population', credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True)`
 
 
 Calculate mean and high posterior density interval on combined allele frequency.
@@ -806,6 +814,18 @@ by a latent, lognormal variable <code>conc</code>.
 :   Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
 
 
+**```conc_mu```** :&ensp;<code>float</code>, optional
+:   Mean to parameterise lognormal distribution of <code>conc</code> prior. Defaults to 1.
+
+
+**```conc_sigma```** :&ensp;<code>float</code>, optional
+:   Standard deviation to parameterise lognormal distribution of <code>conc</code> prior. Defaults to 1.
+
+
+**```compare_models```** :&ensp;<code>bool</code>, optional
+:   Check that default estimated allele_freq is within compound model estimated credible intervals. Defaults to True.
+
+
 
 ###### Returns
 
@@ -817,6 +837,34 @@ by a latent, lognormal variable <code>conc</code>.
 
 
 
+    
+### Function `compare_estimates` {#HLAfreq.HLAfreq_pymc.compare_estimates}
+
+
+
+    
+> `def compare_estimates(AFtab, hdi, datasetID)`
+
+
+Does the defaul estimate of <code>allele\_freq</code> sit within the compound
+model's estimated credible intervals? If not, print warnings.
+
+
+###### Args
+
+**```AFtab```** :&ensp;<code>pd.DataFrame</code>
+:   Table of allele frequency data
+
+
+**```hdi```** :&ensp;<code>np.array</code>
+:   Pairs of high density interval limits, allele name, and posterior mean from compound model.
+
+
+**```datasetID```** :&ensp;<code>str</code>, optional
+:   Unique identifier column for study.
+
+
+
 
 
 -----
diff --git a/setup.py b/setup.py
index f6aaa0b..3232a5a 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.1dev3",
+    version="0.0.1dev4",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index 8cea7ce..718ae53 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: HLAfreq
-Version: 0.0.1.dev3
+Version: 0.0.1.dev4
 Summary: Download and combine HLA frequency data from multiple studies
 Home-page: https://github.com/Vaccitech/HLAfreq
 Author: David Wells
@@ -78,6 +78,8 @@ created with pdoc3 in pdf mode.
 # Install in dev mode
 pip install -e HLAfreq
 
+Update version in setup.py
+
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
 
 Run tests `pytest` 

From 1e2a163b4108fb357c1dae29ee28f5ed6a30a324 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 10 Mar 2023 09:06:52 +0000
Subject: [PATCH 109/192] Correct spelling errors

---
 examples/multi_country.ipynb | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index 99db3d1..8280165 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -135,7 +135,7 @@
    "source": [
     "cafs = []\n",
     "for country in countries:\n",
-    "    # Load raw county data\n",
+    "    # Load raw country data\n",
     "    aftab = pd.read_csv(\"../data/example/multi_country/%s_raw.csv\" %country)\n",
     "    # Drop any incomplete studies\n",
     "    aftab = HLAfreq.only_complete(aftab)\n",
@@ -154,7 +154,7 @@
    "metadata": {},
    "source": [
     "## Combine all country data\n",
-    "Concatenate each single county dataset into a single multicountry dataset.\n",
+    "Concatenate each single country dataset into a single multicountry dataset.\n",
     "Combine allele frequencies, using the manually added `country` column as `datasetID`."
    ]
   },
@@ -525,10 +525,10 @@
     "\n",
     "If estimating allele frequency for a region, it may be important to\n",
     "account for the size of national populations. Below we calculate an\n",
-    "individual weight for each country. A county's populaion, as a proportion\n",
+    "individual weight for each country. A country's population, as a proportion\n",
     "of the sum of countries' populations, multiplied by the number of countries is\n",
     "used as the weight for each individual in that country. This means that\n",
-    "individuals from large countries contibute more to the total sample but the total sample size is unchanged. Therefore, the uncertainty of estimates is still determined by the overall samplesize."
+    "individuals from large countries contibute more to the total sample but the total sample size is unchanged. Therefore, the uncertainty of estimates is still determined by the overall sample size."
    ]
   },
   {
@@ -604,7 +604,7 @@
    "source": [
     "## Credible intervals and population size\n",
     "The approach above should only be used for the default model. If you want to account for population size using the compound model to get credible intervals the approach is a little different. A different approach is needed because the compound model accounts for study variance and the above weighting will chiefly affect that variance rather than the total allele frequency.\n",
-    "The solution to accounting for population size when estimating credible intervals is to calculate the country specific allele frequencies first and then weight the country estimates before combining them. In this case, slightly different from above, we weight by the country's proportion of the total population. This different weighting is because sample size is already accounted for when estimating county allele frequencies.\n",
+    "The solution to accounting for population size when estimating credible intervals is to calculate the country specific allele frequencies first and then weight the country estimates before combining them. In this case, slightly different from above, we weight by the country's proportion of the total population. This different weighting is because sample size is already accounted for when estimating country allele frequencies.\n",
     "\n",
     "Load the allele frequency data so that each country is an element in a list. This is the non-combined data we downloaded earlier. This time we're skipping Guinea because the data wasn't actually from Guinea."
    ]
@@ -631,7 +631,7 @@
     "    'South+Africa','Uganda','Zimbabwe']\n",
     "aftabs = []\n",
     "for country in countries:\n",
-    "  # Load raw county data\n",
+    "  # Load raw country data\n",
     "  aftab = pd.read_csv(\"../data/example/multi_country/%s_raw.csv\" %country)\n",
     "  # Drop any incomplete studies\n",
     "  aftab = HLAfreq.only_complete(aftab)\n",
@@ -986,7 +986,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Next we take the estimate for each county and multiply it by the population proportion for that country. Finally we sum these weighted estimates."
+    "Next we take the estimate for each country and multiply it by the population proportion for that country. Finally we sum these weighted estimates."
    ]
   },
   {

From e5c2c43b5cb59d0505c0dfad51a507a41246a67b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 2 Jun 2023 16:18:24 +0100
Subject: [PATCH 110/192] Format src/ and tests/ with black

---
 src/HLAfreq/HLAfreq.py           | 368 +++++++++++++++++++------------
 src/HLAfreq/HLAfreq_data.py      |  12 +-
 src/HLAfreq/HLAfreq_pymc.py      |  88 +++++---
 src/HLAfreq/__init__.py          |   2 +-
 tests/test_single_country_caf.py |  62 ++++--
 5 files changed, 340 insertions(+), 192 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 292fdec..4b7392a 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -19,21 +19,22 @@
 import warnings
 import matplotlib.colors as mcolors
 
+
 def makeURL(
-        country="",
-        standard='s',
-        locus="",
-        resolution_pattern="bigger_equal_than",
-        resolution=2,
-        region="",
-        ethnic="",
-        study_type="",
-        dataset_source="",
-        sample_year="",
-        sample_year_pattern="",
-        sample_size="",
-        sample_size_pattern=""
-    ):
+    country="",
+    standard="s",
+    locus="",
+    resolution_pattern="bigger_equal_than",
+    resolution=2,
+    region="",
+    ethnic="",
+    study_type="",
+    dataset_source="",
+    sample_year="",
+    sample_year_pattern="",
+    sample_size="",
+    sample_size_pattern="",
+):
     """Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
     Args:
         country (str, optional): Country name to retrieve records from. Defaults to "".
@@ -55,22 +56,39 @@ def makeURL(
     """
     base = "http://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
-    hla_locus = "hla_locus=%s&" %(locus)
-    country = "hla_country=%s&" %(country)
-    region = "hla_region=%s&" %(region)
-    ethnic = "hla_ethnic=%s&" %(ethnic)
-    study_type = "hla_study=%s&" %(study_type)
-    dataset_source = "hla_dataset_source=%s&" %(dataset_source)
-    sample_year = "hla_sample_year=%s&" %(sample_year)
-    sample_year_pattern = "hla_sample_year_pattern=%s&" %(sample_year_pattern)
-    sample_size = "hla_sample_size=%s&" %(sample_size)
-    sample_size_pattern = "hla_sample_size_pattern=%s&" %(sample_size_pattern)
-    hla_level_pattern = "hla_level_pattern=%s&" %(resolution_pattern)
-    hla_level = "hla_level=%s&" %(resolution)
-    standard = "standard=%s&" %standard
-    url = base + locus_type + hla_locus + country + hla_level_pattern + hla_level + standard + region + ethnic + study_type + dataset_source + sample_year + sample_year_pattern + sample_size + sample_size_pattern
+    hla_locus = "hla_locus=%s&" % (locus)
+    country = "hla_country=%s&" % (country)
+    region = "hla_region=%s&" % (region)
+    ethnic = "hla_ethnic=%s&" % (ethnic)
+    study_type = "hla_study=%s&" % (study_type)
+    dataset_source = "hla_dataset_source=%s&" % (dataset_source)
+    sample_year = "hla_sample_year=%s&" % (sample_year)
+    sample_year_pattern = "hla_sample_year_pattern=%s&" % (sample_year_pattern)
+    sample_size = "hla_sample_size=%s&" % (sample_size)
+    sample_size_pattern = "hla_sample_size_pattern=%s&" % (sample_size_pattern)
+    hla_level_pattern = "hla_level_pattern=%s&" % (resolution_pattern)
+    hla_level = "hla_level=%s&" % (resolution)
+    standard = "standard=%s&" % standard
+    url = (
+        base
+        + locus_type
+        + hla_locus
+        + country
+        + hla_level_pattern
+        + hla_level
+        + standard
+        + region
+        + ethnic
+        + study_type
+        + dataset_source
+        + sample_year
+        + sample_year_pattern
+        + sample_size
+        + sample_size_pattern
+    )
     return url
 
+
 def parseAF(bs):
     """Generate a dataframe from a given html page
 
@@ -81,29 +99,37 @@ def parseAF(bs):
         pd.DataFrame: Table of allele, allele frequency, samplesize, and population
     """
     # Get the results table from the div `divGenDetail`
-    tab = bs.find('div', {'id': 'divGenDetail'}).find('table', {'class': 'tblNormal'})
+    tab = bs.find("div", {"id": "divGenDetail"}).find("table", {"class": "tblNormal"})
     # Get the column headers from the first row of the table
     columns = [
-        'line', 'allele', 'flag', 'population', 'carriers%',
-        'allele_freq', 'AF_graphic', 'sample_size', 'database',
-        'distribution','haplotype_association', 'notes'
-        ]
-    rows =[]
-    for row in tab.find_all('tr'):
-        rows.append(
-            [td.get_text(strip=True) for td in row.find_all('td')]
-            )
+        "line",
+        "allele",
+        "flag",
+        "population",
+        "carriers%",
+        "allele_freq",
+        "AF_graphic",
+        "sample_size",
+        "database",
+        "distribution",
+        "haplotype_association",
+        "notes",
+    ]
+    rows = []
+    for row in tab.find_all("tr"):
+        rows.append([td.get_text(strip=True) for td in row.find_all("td")])
     # Make dataframe of table rows
     # skip the first row as it's `th` headers
-    df = pd.DataFrame(rows[1:], columns = columns)
+    df = pd.DataFrame(rows[1:], columns=columns)
 
     # Get HLA loci
-    df['loci'] = df.allele.apply(lambda x: x.split("*")[0])
+    df["loci"] = df.allele.apply(lambda x: x.split("*")[0])
 
     # Drop unwanted columns
-    df = df[['allele', 'loci', 'population', 'allele_freq', 'carriers%', 'sample_size']]
+    df = df[["allele", "loci", "population", "allele_freq", "carriers%", "sample_size"]]
     return df
-   
+
+
 def Npages(bs):
     """How many pages of results are there?
 
@@ -114,21 +140,26 @@ def Npages(bs):
         int: Total number of results pages
     """
     # Get the table with number of pages
-    navtab = bs.find('div', {'id': 'divGenNavig'}).find('table', {'class': 'table10'})
-    assert navtab, f"navtab does not evaluate to True. Check URL returns results in web browser."
-    # Get cell with ' of ' in 
-    pagesOfN = [td.get_text(strip=True) for td in navtab.find_all('td') if " of " in td.text]
+    navtab = bs.find("div", {"id": "divGenNavig"}).find("table", {"class": "table10"})
+    assert (
+        navtab
+    ), f"navtab does not evaluate to True. Check URL returns results in web browser."
+    # Get cell with ' of ' in
+    pagesOfN = [
+        td.get_text(strip=True) for td in navtab.find_all("td") if " of " in td.text
+    ]
     # Check single cell returned
-    assert len(pagesOfN) == 1, "divGenNavig should contain 1 of not %s" %len(pagesOfN)
+    assert len(pagesOfN) == 1, "divGenNavig should contain 1 of not %s" % len(pagesOfN)
     # Get total number of pages
     N = pagesOfN[0].split("of ")[1]
     N = int(N)
     return N
 
+
 def formatAF(AFtab, ignoreG=True):
     """Format allele frequency table.
     Convert sample_size and allele_freq to numeric data type.
-    Removes commas from sample size. Removes "(*)" from allele frequency if 
+    Removes commas from sample size. Removes "(*)" from allele frequency if
     `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
 
     Args:
@@ -147,6 +178,7 @@ def formatAF(AFtab, ignoreG=True):
         df.allele_freq = pd.to_numeric(df.allele_freq)
     return df
 
+
 def getAFdata(base_url, format=True, ignoreG=True):
     """Get all allele frequency data from a search base url. Iterates over all
         pages regardless of which page is based.
@@ -160,17 +192,17 @@ def getAFdata(base_url, format=True, ignoreG=True):
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
     """
     # Get BS object from base search
-    bs = BeautifulSoup(requests.get(base_url).text, 'html.parser')
+    bs = BeautifulSoup(requests.get(base_url).text, "html.parser")
     # How many pages of results
     N = Npages(bs)
-    print("%s pages of results" %N)
+    print("%s pages of results" % N)
     # iterate over pages, parse and combine data from each
     tabs = []
     for i in range(N):
         # print (" Parsing page %s" %(i+1))
-        print (" Parsing page %s" %(i+1), end="\r")
-        url = base_url + "page=" + str(i+1)
-        bs = BeautifulSoup(requests.get(url).text, 'html.parser')
+        print(" Parsing page %s" % (i + 1), end="\r")
+        url = base_url + "page=" + str(i + 1)
+        bs = BeautifulSoup(requests.get(url).text, "html.parser")
         tab = parseAF(bs)
         tabs.append(tab)
     print("Download complete")
@@ -182,7 +214,8 @@ def getAFdata(base_url, format=True, ignoreG=True):
             print("Formatting failed, non-numeric datatypes may remain.")
     return tabs
 
-def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
+
+def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
     """Report any studies with allele freqs that don't sum to 1
 
     Args:
@@ -191,19 +224,20 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
         ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
         datasetID (str): Unique identifier column for study
     """
-    poplocs = AFtab.groupby([datasetID, 'loci']).allele_freq.sum()
+    poplocs = AFtab.groupby([datasetID, "loci"]).allele_freq.sum()
     lmask = poplocs < llimit
-    if sum(lmask>0):
+    if sum(lmask > 0):
         print(poplocs[lmask])
         print(f"{sum(lmask)} studies have total allele frequency < {llimit}")
     umask = poplocs > ulimit
-    if sum(umask>0):
+    if sum(umask > 0):
         print(poplocs[umask])
         print(f"{sum(umask)} studies have total allele frequency > {ulimit}")
     incomplete = pd.concat([poplocs[lmask], poplocs[umask]])
     return incomplete
 
-def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
+
+def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
     """Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
     This prevents throwing away data if another loci in the population is incomplete
 
@@ -216,15 +250,20 @@ def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population'):
     Returns:
         pd.DataFrame: Allele frequency data of multiple studies, but only complete studies.
     """
-    noncomplete = incomplete_studies(AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID)
+    noncomplete = incomplete_studies(
+        AFtab=AFtab, llimit=llimit, ulimit=ulimit, datasetID=datasetID
+    )
     # Returns False if population AND loci are in the noncomplete.index
     # AS A PAIR
     # This is important so that we don't throw away all data on a population
     # just because one loci is incomplete.
-    complete_mask = AFtab.apply(lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1)
+    complete_mask = AFtab.apply(
+        lambda x: (x[datasetID], x.loci) not in noncomplete.index, axis=1
+    )
     df = AFtab[complete_mask]
     return df
 
+
 def check_resolution(AFtab):
     """Check if all alleles in AFtab have the same resolution.
     Will print the number of records with each resolution.
@@ -243,7 +282,8 @@ def check_resolution(AFtab):
         print(f"Multiple resolutions in AFtab. Fix with decrease_resolution()")
     return pass_check
 
-def decrease_resolution(AFtab, newres, datasetID='population'):
+
+def decrease_resolution(AFtab, newres, datasetID="population"):
     """Decrease allele resolution to a specified value so all alleles have the same resolution.
 
     Args:
@@ -256,16 +296,19 @@ def decrease_resolution(AFtab, newres, datasetID='population'):
     """
     df = AFtab.copy()
     resolution = 1 + df.allele.str.count(":")
-    assert all(resolution >= newres), f"Some alleles have resolution below {newres} fields"
+    assert all(
+        resolution >= newres
+    ), f"Some alleles have resolution below {newres} fields"
     new_allele = df.allele.str.split(":").apply(lambda x: ":".join(x[:newres]))
     df.allele = new_allele
     collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
     return collapsed
 
-def collapse_reduced_alleles(AFtab, datasetID='population'):
+
+def collapse_reduced_alleles(AFtab, datasetID="population"):
     df = AFtab.copy()
     # Group by alleles within datasets
-    grouped = df.groupby([datasetID,'allele'])
+    grouped = df.groupby([datasetID, "allele"])
     # Sum allele freq but keep other columns
     collapsed = grouped.apply(
         lambda row: [
@@ -273,22 +316,29 @@ def collapse_reduced_alleles(AFtab, datasetID='population'):
             row.sample_size.unique()[0],
             row.loci.unique()[0],
             len(row.loci.unique()),
-            len(row.sample_size.unique())
+            len(row.sample_size.unique()),
         ]
     )
     collapsed = pd.DataFrame(
         collapsed.tolist(),
         index=collapsed.index,
-        columns = ['allele_freq', 'sample_size', 'loci', '#loci', '#sample_sizes']
+        columns=["allele_freq", "sample_size", "loci", "#loci", "#sample_sizes"],
     ).reset_index()
     # Within a study each all identical alleles should have the same loci and sample size
-    assert all(collapsed['#loci'] == 1), "Multiple loci found for a single allele in a single population"
-    assert all(collapsed['#sample_sizes'] == 1), "Multiple sample_sizes found for a single allele in a single population"
-    collapsed = collapsed[['allele', 'loci','population','allele_freq','sample_size']]
+    assert all(
+        collapsed["#loci"] == 1
+    ), "Multiple loci found for a single allele in a single population"
+    assert all(
+        collapsed["#sample_sizes"] == 1
+    ), "Multiple sample_sizes found for a single allele in a single population"
+    collapsed = collapsed[
+        ["allele", "loci", "population", "allele_freq", "sample_size"]
+    ]
     alleles_unique_in_study(collapsed)
     return collapsed
 
-def unmeasured_alleles(AFtab, datasetID='population'):
+
+def unmeasured_alleles(AFtab, datasetID="population"):
     """When combining AF estimates, unreported alleles can inflate frequencies
         so AF sums to >1. Therefore we add unreported alleles with frequency zero.
 
@@ -297,7 +347,7 @@ def unmeasured_alleles(AFtab, datasetID='population'):
         datasetID (str): Unique identifier column for study
 
     Returns:
-        pd.DataFrame: Allele frequency data with all locus alleles reported 
+        pd.DataFrame: Allele frequency data with all locus alleles reported
             for each dataset
     """
     df = AFtab.copy()
@@ -311,19 +361,48 @@ def unmeasured_alleles(AFtab, datasetID='population'):
             datasetAF = df[(df[datasetID] == dataset) & (df.loci == locus)]
             # What was the sample size for this data?
             dataset_sample_size = datasetAF.sample_size.unique()
-            assert len(dataset_sample_size) == 1, "dataset_sample_size must be 1, not %s" %len(dataset_sample_size)
+            assert (
+                len(dataset_sample_size) == 1
+            ), "dataset_sample_size must be 1, not %s" % len(dataset_sample_size)
             dataset_sample_size = dataset_sample_size[0]
             # Get all alleles for this locus (across datasets)
             ualleles = df[df.loci == locus].allele.unique()
             # Which of these alleles are not in this dataset?
-            missing_alleles = [allele for allele in ualleles if not allele in datasetAF.allele.values]
-            missing_rows = [(al, locus, dataset, 0, 0, dataset_sample_size) for al in missing_alleles]
-            missing_rows = pd.DataFrame(missing_rows, columns=['allele','loci',datasetID,'allele_freq','carriers%','sample_size'])
+            missing_alleles = [
+                allele for allele in ualleles if not allele in datasetAF.allele.values
+            ]
+            missing_rows = [
+                (al, locus, dataset, 0, 0, dataset_sample_size)
+                for al in missing_alleles
+            ]
+            missing_rows = pd.DataFrame(
+                missing_rows,
+                columns=[
+                    "allele",
+                    "loci",
+                    datasetID,
+                    "allele_freq",
+                    "carriers%",
+                    "sample_size",
+                ],
+            )
             # Add them in with zero frequency
             df = pd.concat([df, missing_rows], ignore_index=True)
     return df
 
-def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+
+def combineAF(
+    AFtab,
+    weights="2n",
+    alpha=[],
+    datasetID="population",
+    format=True,
+    ignoreG=True,
+    add_unmeasured=True,
+    complete=True,
+    resolution=True,
+    unique=True,
+):
     """Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
     Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
     Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
@@ -353,35 +432,38 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
     df = AFtab.copy()
     single_loci(df)
     if unique:
-        assert alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
+        assert alleles_unique_in_study(
+            df, datasetID=datasetID
+        ), "The same allele appears multiple times in a dataset"
     if complete:
-        assert incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        assert incomplete_studies(
+            df, datasetID=datasetID
+        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
     if resolution:
-        assert check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+        assert check_resolution(
+            df
+        ), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
         df = formatAF(df, ignoreG)
     if add_unmeasured:
         df = unmeasured_alleles(df, datasetID)
     try:
-        df['2n'] = df.sample_size * 2
+        df["2n"] = df.sample_size * 2
     except:
         print("column '2n' could not be created")
-    df['c'] =  df.allele_freq * df[weights]
-    grouped = df.groupby('allele', sort=True)
+    df["c"] = df.allele_freq * df[weights]
+    grouped = df.groupby("allele", sort=True)
     combined = grouped.apply(
         lambda row: [
-        row.name,
-        row.loci.unique()[0],
-        np.average(row.allele_freq, weights=row[weights]),
-        row.c.sum(),
-        row.sample_size.sum()
+            row.name,
+            row.loci.unique()[0],
+            np.average(row.allele_freq, weights=row[weights]),
+            row.c.sum(),
+            row.sample_size.sum(),
         ]
     )
     combined = pd.DataFrame(
-        combined.tolist(),
-        columns = ['allele', 'loci',
-            'wav',
-            'c', 'sample_size']
+        combined.tolist(), columns=["allele", "loci", "wav", "c", "sample_size"]
     )
     combined = combined.reset_index(drop=True)
     # Check that all alleles in a locus have the same sample size
@@ -390,12 +472,13 @@ def combineAF(AFtab, weights='2n', alpha = [], datasetID='population', format=Tr
         id_duplicated_allele(grouped)
     if not alpha:
         alpha = default_prior(len(combined.allele))
-    combined['alpha'] = alpha
+    combined["alpha"] = alpha
     # Calculate Dirichlet mean for each allele
-    combined['allele_freq'] = sp.stats.dirichlet(combined.alpha + combined.c).mean()
+    combined["allele_freq"] = sp.stats.dirichlet(combined.alpha + combined.c).mean()
 
     return combined
 
+
 def default_prior(k):
     """Calculate a default prior, 1 observation of each class.
 
@@ -408,6 +491,7 @@ def default_prior(k):
     alpha = [1] * k
     return alpha
 
+
 def single_loci(AFtab):
     """Check that allele frequency data is only of one locus
 
@@ -416,7 +500,8 @@ def single_loci(AFtab):
     """
     assert len(AFtab.loci.unique()) == 1, f"'AFtab' must conatain only 1 loci"
 
-def alleles_unique_in_study(AFtab, datasetID='population'):
+
+def alleles_unique_in_study(AFtab, datasetID="population"):
     """Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
 
     Args:
@@ -427,23 +512,31 @@ def alleles_unique_in_study(AFtab, datasetID='population'):
         bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
     """
     df = AFtab.copy()
-    grouped = df.groupby([datasetID,'allele'])
+    grouped = df.groupby([datasetID, "allele"])
     # Are allele alleles unique? i.e. do any occur multiple times in grouping?
-    unique = grouped.size()[grouped.size()>1].empty
+    unique = grouped.size()[grouped.size() > 1].empty
     if not unique:
         print(f"Non unique alleles in study, is datasetID correct? {datasetID}")
-        print(grouped.size()[grouped.size()>1])
+        print(grouped.size()[grouped.size() > 1])
     return unique
 
+
 def duplicated_sample_size(AFtab):
     """Returns True if any loci has more than 1 unique sample size"""
-    locus_sample_sizes = AFtab.groupby('loci').sample_size.apply(lambda x: len(x.unique()))
+    locus_sample_sizes = AFtab.groupby("loci").sample_size.apply(
+        lambda x: len(x.unique())
+    )
     return any(locus_sample_sizes != 1)
 
+
 def id_duplicated_allele(grouped):
-    """ Reports the allele that has mupltiple sample sizes """
+    """Reports the allele that has mupltiple sample sizes"""
     duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
-    assert all(~duplicated_population), "duplicated population within allele %s" %duplicated_population[duplicated_population].index.tolist()
+    assert all(~duplicated_population), (
+        "duplicated population within allele %s"
+        % duplicated_population[duplicated_population].index.tolist()
+    )
+
 
 def population_coverage(p):
     """Calculate the proportion of people with at least 1 copy of this allele
@@ -455,11 +548,12 @@ def population_coverage(p):
     Returns:
         float: Sum of homozygotes and heterozygotes for this allele
     """
-    q = 1-p
+    q = 1 - p
     homo = p**2
-    hetero = 2*p*q
+    hetero = 2 * p * q
     return homo + hetero
 
+
 def betaAB(alpha):
     """Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
 
@@ -469,9 +563,10 @@ def betaAB(alpha):
     Returns:
         list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.
     """
-    ab = [(a,sum(alpha)-a) for a in alpha]
+    ab = [(a, sum(alpha) - a) for a in alpha]
     return ab
 
+
 # def betaCI(a,b,credible_interval=0.95):
 #     """Calculat the central credible interval of a beta distribution
 
@@ -508,6 +603,7 @@ def betaAB(alpha):
 #     ci = [betaCI(a, b, credible_interval) for a,b in ab]
 #     return ci
 
+
 def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
     """Plot probability density function for prior values.
 
@@ -518,7 +614,7 @@ def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
     """
     ab = betaAB(concentration)
     pline = np.linspace(0, 1, psteps)
-    nrow = math.ceil(len(concentration)/ncol)
+    nrow = math.ceil(len(concentration) / ncol)
     fig, ax = plt.subplots(nrow, ncol, sharex=True)
     fig.suptitle("Probability density")
     # If labels is a list nothing happens,
@@ -526,27 +622,30 @@ def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
     labels = list(labels)
     if not labels:
         labels = [""] * len(concentration)
-    assert len(concentration) == len(labels), "concentration must be same length as labels"
-    for i,alpha in enumerate(concentration):
-        a,b = ab[i]
-        bd = sp.stats.beta(a,b)
+    assert len(concentration) == len(
+        labels
+    ), "concentration must be same length as labels"
+    for i, alpha in enumerate(concentration):
+        a, b = ab[i]
+        bd = sp.stats.beta(a, b)
         pdf = [bd.pdf(p) for p in pline]
         ax.flat[i].plot(pline, pdf)
         ax.flat[i].set_title(labels[i])
-    for axi in ax[-1,:]:
-        axi.set(xlabel='Allele freq')
-    for axi in ax[:,0]:
-        axi.set(ylabel='PDF')
+    for axi in ax[-1, :]:
+        axi.set(xlabel="Allele freq")
+    for axi in ax[:, 0]:
+        axi.set(ylabel="PDF")
     plt.show()
 
+
 def plotAF(
     caf=pd.DataFrame(),
     AFtab=pd.DataFrame(),
-    cols = list(mcolors.TABLEAU_COLORS.keys()),
+    cols=list(mcolors.TABLEAU_COLORS.keys()),
     datasetID="population",
     hdi=pd.DataFrame(),
-    compound_mean=pd.DataFrame()
-    ):
+    compound_mean=pd.DataFrame(),
+):
     """Plot combined allele frequencies, individual allele frequencies,
     and credible intervals on combined allele frequency estimates.
     Credible interval is only plotted if a value is given for `hdi`.
@@ -565,27 +664,27 @@ def plotAF(
     if not AFtab.empty:
         # Cols must be longer than the list of alleles
         # If not, repeat the list of cols
-        repeat_cols = np.ceil(len(AFtab[datasetID])/len(cols))
+        repeat_cols = np.ceil(len(AFtab[datasetID]) / len(cols))
         repeat_cols = int(repeat_cols)
         cols = cols * repeat_cols
         # Make a dictionary mapping datasetID to colours
         cmap = dict(zip(AFtab[datasetID].unique(), cols))
         plt.scatter(
-            x = AFtab.allele_freq,
-            y = AFtab.allele,
-            c = [cmap[x] for x in AFtab[datasetID]],
-            alpha = 0.7,
-            zorder=2
-            )
+            x=AFtab.allele_freq,
+            y=AFtab.allele,
+            c=[cmap[x] for x in AFtab[datasetID]],
+            alpha=0.7,
+            zorder=2,
+        )
     # Plot combined allele frequency
     if not caf.empty:
         plt.scatter(
-            x = caf.allele_freq,
-            y = caf.allele,
-            edgecolors='black',
-            facecolors='none',
-            zorder=3
-            )
+            x=caf.allele_freq,
+            y=caf.allele,
+            edgecolors="black",
+            facecolors="none",
+            zorder=3,
+        )
     # Plot high density interval
     if not hdi.empty:
         # assert not AFtab.empty, "AFtab is needed to calculate credible interval"
@@ -595,18 +694,15 @@ def plotAF(
         for interval in hdi.iterrows():
             # .iterrows returns a index and data as a tuple for each row
             plt.hlines(
-                y = interval[1]['allele'],
-                xmin = interval[1]['lo'],
-                xmax = interval[1]['hi'],
-                color="black"
+                y=interval[1]["allele"],
+                xmin=interval[1]["lo"],
+                xmax=interval[1]["hi"],
+                color="black",
             )
     if not compound_mean.empty:
         for row in compound_mean.iterrows():
             plt.scatter(
-                y = row[1]['allele'],
-                x = row[1]['post_mean'],
-                color = 'black',
-                marker = "|"
+                y=row[1]["allele"], x=row[1]["post_mean"], color="black", marker="|"
             )
     plt.xlabel("Allele frequency")
     plt.grid(zorder=0)
diff --git a/src/HLAfreq/HLAfreq_data.py b/src/HLAfreq/HLAfreq_data.py
index c040648..bf2dd4c 100644
--- a/src/HLAfreq/HLAfreq_data.py
+++ b/src/HLAfreq/HLAfreq_data.py
@@ -4,10 +4,14 @@
 import pkg_resources
 import pandas as pd
 
+
 def load_countries():
-    stream = pkg_resources.resource_stream(__name__, 'data/countries.csv')
-    return pd.read_csv(stream, encoding='latin-1')
+    stream = pkg_resources.resource_stream(__name__, "data/countries.csv")
+    return pd.read_csv(stream, encoding="latin-1")
+
 
 def load_HLA1supertypes_Sidney2008():
-    stream = pkg_resources.resource_stream(__name__, 'data/HLA1supertypes_Sidney2008.csv')
-    return pd.read_csv(stream, encoding='latin-1')
+    stream = pkg_resources.resource_stream(
+        __name__, "data/HLA1supertypes_Sidney2008.csv"
+    )
+    return pd.read_csv(stream, encoding="latin-1")
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 1f9a0a7..73a70de 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -5,41 +5,57 @@
 import pandas as pd
 import HLAfreq
 
-def _make_c_array(AFtab, weights="2n", datasetID="population",
-                  format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True):
+
+def _make_c_array(
+    AFtab,
+    weights="2n",
+    datasetID="population",
+    format=True,
+    ignoreG=True,
+    add_unmeasured=True,
+    complete=True,
+    resolution=True,
+    unique=True,
+):
     df = AFtab.copy()
     HLAfreq.single_loci(df)
     if unique:
-        assert HLAfreq.alleles_unique_in_study(df, datasetID=datasetID), "The same allele appears multiple times in a dataset"
+        assert HLAfreq.alleles_unique_in_study(
+            df, datasetID=datasetID
+        ), "The same allele appears multiple times in a dataset"
     if complete:
-        assert HLAfreq.incomplete_studies(df, datasetID=datasetID).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        assert HLAfreq.incomplete_studies(
+            df, datasetID=datasetID
+        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
     if resolution:
-        assert HLAfreq.check_resolution(df), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+        assert HLAfreq.check_resolution(
+            df
+        ), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
     if format:
         df = HLAfreq.formatAF(df, ignoreG)
     if add_unmeasured:
         df = HLAfreq.unmeasured_alleles(df, datasetID)
     try:
-        df['2n'] = df.sample_size * 2
+        df["2n"] = df.sample_size * 2
     except:
         print("column '2n' could not be created")
-    df['c'] =  df.allele_freq * df[weights]
+    df["c"] = df.allele_freq * df[weights]
 
     # Sort by alleles so it matches the combined alleles
-    df = df.sort_values('allele')
+    df = df.sort_values("allele")
     c_array = np.array(df.groupby(datasetID).c.apply(list).tolist())
     allele_names = sorted(df.allele.unique())
     # Imperfect check that allele order matches between caf and c_array.
     # caf is sorted automatically so should match sorted AFloc
     # Therefore we check that sorted AFloc matches c_array
     # The check is that the sum of allele i is the same
-    for a,b in zip(
-        np.apply_along_axis(sum, 0, c_array),
-        df.groupby('allele').c.sum()
-        ):
-        assert math.isclose(a,b), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
+    for a, b in zip(np.apply_along_axis(sum, 0, c_array), df.groupby("allele").c.sum()):
+        assert math.isclose(
+            a, b
+        ), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
     return c_array, allele_names
 
+
 def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
     # Number of populations
     n = c_array.shape[0]
@@ -50,22 +66,34 @@ def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
     # for the multinomial
     c_array = np.round(c_array)
     effective_samples = np.apply_along_axis(sum, 1, c_array)
-    if len(prior)==0:
+    if len(prior) == 0:
         prior = HLAfreq.default_prior(k)
     assert len(prior) == k, "For k alleles, prior must be length k"
     with pm.Model() as mod:
-        frac = pm.Dirichlet('frac', a=prior)
-        conc = pm.Lognormal('conc', mu=conc_mu, sigma=conc_sigma)
-        y = pm.DirichletMultinomial('y', n=effective_samples, a=frac*conc, shape=(n,k), observed=c_array)
+        frac = pm.Dirichlet("frac", a=prior)
+        conc = pm.Lognormal("conc", mu=conc_mu, sigma=conc_sigma)
+        y = pm.DirichletMultinomial(
+            "y", n=effective_samples, a=frac * conc, shape=(n, k), observed=c_array
+        )
 
     with mod:
         idata = pm.sample()
     return idata
 
-def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True):
+
+def AFhdi(
+    AFtab,
+    weights="2n",
+    datasetID="population",
+    credible_interval=0.95,
+    prior=[],
+    conc_mu=1,
+    conc_sigma=1,
+    compare_models=True,
+):
     """Calculate mean and high posterior density interval on combined allele frequency.
     Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
-    
+
     In brief, the global allele frequency is modelled as a Dirichlet distribution,
     and each population (defined by `datasetID`) is a Dirichlet distribution draw from
     the global Dirichlet distribution, and the observed allele count data of that
@@ -93,15 +121,18 @@ def AFhdi(AFtab, weights="2n", datasetID="population", credible_interval=0.95, p
     """
 
     c_array, allele_names = _make_c_array(AFtab, weights, datasetID)
-    idata = _fit_Dirichlet_Multinomial(c_array, prior, conc_mu=conc_mu, conc_sigma=conc_sigma)
+    idata = _fit_Dirichlet_Multinomial(
+        c_array, prior, conc_mu=conc_mu, conc_sigma=conc_sigma
+    )
     hdi = az.hdi(idata, hdi_prob=credible_interval).frac.values
-    post_mean = az.summary(idata, var_names='frac')['mean']
-    post = pd.DataFrame([hdi[:,0], hdi[:,1], allele_names, post_mean]).T
-    post.columns = ['lo','hi','allele','post_mean']
+    post_mean = az.summary(idata, var_names="frac")["mean"]
+    post = pd.DataFrame([hdi[:, 0], hdi[:, 1], allele_names, post_mean]).T
+    post.columns = ["lo", "hi", "allele", "post_mean"]
     if compare_models:
         compare_estimates(AFtab, post, datasetID)
     return post
 
+
 def compare_estimates(AFtab, hdi, datasetID):
     """Does the defaul estimate of `allele_freq` sit within the compound
     model's estimated credible intervals? If not, print warnings.
@@ -111,13 +142,16 @@ def compare_estimates(AFtab, hdi, datasetID):
         hdi (np.array): Pairs of high density interval limits, allele name, and posterior mean from compound model.
         datasetID (str, optional): Unique identifier column for study.
     """
-    
+
     caf = HLAfreq.combineAF(AFtab, datasetID=datasetID)
     caf = pd.merge(caf, hdi, how="left", on="allele")
     mask = (caf.allele_freq < caf.lo) | (caf.allele_freq > caf.hi)
     if mask.sum() > 0:
         print()
-        print("WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!")
-        print("There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb")
+        print(
+            "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!"
+        )
+        print(
+            "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb"
+        )
         print("If you have set `credible_interval` to < 0.95, this may be a non-issue.")
-    
diff --git a/src/HLAfreq/__init__.py b/src/HLAfreq/__init__.py
index d2604df..4648629 100644
--- a/src/HLAfreq/__init__.py
+++ b/src/HLAfreq/__init__.py
@@ -1 +1 @@
-from .HLAfreq import *
\ No newline at end of file
+from .HLAfreq import *
diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index 92c9cc8..b8661f0 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -10,44 +10,58 @@
 import pandas as pd
 from scipy.stats import dirichlet
 
-dfa =  pd.DataFrame({
-    'allele':['A*02:03','A*02:05','A*02:07'],
-    'loci':['A','A','A'],
-    'population':['test1','test1','test1'],
-    'allele_freq':[0.1, 0.3, 0.6],
-    'sample_size':[10,10,10]
-})
-dfb =  pd.DataFrame({
-    'allele':['A*02:03','A*02:05:01','A*02:05:02'],
-    'loci':['A','A', 'A'],
-    'population':['test2','test2', 'test2'],
-    'allele_freq':[0.5, 0.25, 0.25],
-    'sample_size':[5, 5, 5]
-})
-dfc =  pd.DataFrame({
-    'allele':['A*02:03','A*02:05'],
-    'loci':['A','A'],
-    'population':['test3','test3'],
-    'allele_freq':[0.5, 0.1],
-    'sample_size':[5, 5]
-})
+dfa = pd.DataFrame(
+    {
+        "allele": ["A*02:03", "A*02:05", "A*02:07"],
+        "loci": ["A", "A", "A"],
+        "population": ["test1", "test1", "test1"],
+        "allele_freq": [0.1, 0.3, 0.6],
+        "sample_size": [10, 10, 10],
+    }
+)
+dfb = pd.DataFrame(
+    {
+        "allele": ["A*02:03", "A*02:05:01", "A*02:05:02"],
+        "loci": ["A", "A", "A"],
+        "population": ["test2", "test2", "test2"],
+        "allele_freq": [0.5, 0.25, 0.25],
+        "sample_size": [5, 5, 5],
+    }
+)
+dfc = pd.DataFrame(
+    {
+        "allele": ["A*02:03", "A*02:05"],
+        "loci": ["A", "A"],
+        "population": ["test3", "test3"],
+        "allele_freq": [0.5, 0.1],
+        "sample_size": [5, 5],
+    }
+)
 aftab = pd.concat([dfa, dfb, dfc])
 
 # Drop incomplete test3
 aftab = HLAfreq.only_complete(aftab)
+
+
 def test_drop_incomplete_test():
-    assert not any(aftab.population == 'test3')
+    assert not any(aftab.population == "test3")
+
 
 # Collapse 3 field alleles
 aftab = HLAfreq.decrease_resolution(aftab, 2)
+
+
 def test_resolution_decreased_correctly():
-    mask = (aftab.allele=="A*02:05") & (aftab.population=='test2')
+    mask = (aftab.allele == "A*02:05") & (aftab.population == "test2")
     assert sum(mask) == 1
     collapsed = aftab[mask]
     assert all(collapsed.allele_freq == 0.5)
     assert all(collapsed.sample_size == 5)
 
+
 # Combine allele frequencies
 caf = HLAfreq.combineAF(aftab)
+
+
 def test_combined_allele_freq():
-    assert all(caf.allele_freq == dirichlet([8,12,13]).mean())
\ No newline at end of file
+    assert all(caf.allele_freq == dirichlet([8, 12, 13]).mean())

From 902ff6fc48550b12c05ceead02266b56a4e58624 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Jun 2023 11:10:53 +0100
Subject: [PATCH 111/192] require arviz and pymc>=3, add nox file

---
 dist/HLAfreq-0.0.1.dev4-py3-none-any.whl | Bin 19268 -> 0 bytes
 dist/HLAfreq-0.0.1.dev4.tar.gz           | Bin 20791 -> 0 bytes
 dist/HLAfreq-0.0.2-py3-none-any.whl      | Bin 0 -> 19365 bytes
 dist/HLAfreq-0.0.2.tar.gz                | Bin 0 -> 20873 bytes
 noxfile.py                               |  16 ++++++++++++++++
 setup.py                                 |   5 +++--
 src/HLAfreq.egg-info/PKG-INFO            |   2 +-
 src/HLAfreq.egg-info/requires.txt        |   3 ++-
 8 files changed, 22 insertions(+), 4 deletions(-)
 delete mode 100644 dist/HLAfreq-0.0.1.dev4-py3-none-any.whl
 delete mode 100644 dist/HLAfreq-0.0.1.dev4.tar.gz
 create mode 100644 dist/HLAfreq-0.0.2-py3-none-any.whl
 create mode 100644 dist/HLAfreq-0.0.2.tar.gz
 create mode 100644 noxfile.py

diff --git a/dist/HLAfreq-0.0.1.dev4-py3-none-any.whl b/dist/HLAfreq-0.0.1.dev4-py3-none-any.whl
deleted file mode 100644
index 441b33036bf4b7b4ba6bd4e8274ca9ae8e29a1dc..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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diff --git a/noxfile.py b/noxfile.py
new file mode 100644
index 0000000..5823ff7
--- /dev/null
+++ b/noxfile.py
@@ -0,0 +1,16 @@
+# noxfile.py
+import nox
+
+
+@nox.session
+def lint(session):
+    session.install("flake8")
+    session.run("flake8", "src", "--count", "--select=E9,F63,F7,F82", "--show-source", "--statistics")
+    session.run("flake8", "src", "--count", "--exit-zero", "--max-complexity=10", "--max-line-length=127", "--statistics")
+
+
+@nox.session(python=["3.8", "3.9", "3.10"])
+def tests(session):
+    session.install("pytest")
+    session.install(".")
+    session.run("pytest")
diff --git a/setup.py b/setup.py
index 3232a5a..b48ca7d 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.1dev4",
+    version="0.0.2",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
@@ -19,7 +19,8 @@
         'numpy',
         'matplotlib',
         'scipy',
-        'pymc'
+        'pymc>=3',
+        'arviz'
     ],
     classifiers=[
     "Programming Language :: Python :: 3",
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
index 718ae53..98edc29 100644
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ b/src/HLAfreq.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: HLAfreq
-Version: 0.0.1.dev4
+Version: 0.0.2
 Summary: Download and combine HLA frequency data from multiple studies
 Home-page: https://github.com/Vaccitech/HLAfreq
 Author: David Wells
diff --git a/src/HLAfreq.egg-info/requires.txt b/src/HLAfreq.egg-info/requires.txt
index baff9c3..a76745b 100644
--- a/src/HLAfreq.egg-info/requires.txt
+++ b/src/HLAfreq.egg-info/requires.txt
@@ -4,4 +4,5 @@ pandas
 numpy
 matplotlib
 scipy
-pymc
+pymc>=3
+arviz

From 80312dfde14b15450fea12b9033dd74e8e99acdf Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 4 Jul 2023 17:01:32 +0100
Subject: [PATCH 112/192] Improve installation guide with conda

---
 README.md | 36 +++++++++++++++++++++++++++++++++++-
 1 file changed, 35 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 8d4b302..62240c2 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@ Estimates are combined by modelling allele frequency as a
 Dirichlet distribution which defines the probability of drawing each
 allele. When combining studies their estimates are weighted as 2x sample size by
 default. Sample size is doubled as each person in the study
-contributes two alleles. Alternative weightings can be used
+contributes two alleles. Alternative weightings can be used,
 for example population size when averaging across countries.
 
 When selecting a panel of HLA alleles to represent a population,
@@ -24,9 +24,43 @@ the purpose of the panel, you should include a range of loci and
 supertypes (groups alleles sharing binding specificies).
 
 ## Install
+`HLAfreq` is a `python` package.
+
+### Linux and Mac
+You can install directly using pip
 ```
 pip install HLAfreq
 ```
+See the [pip documentation](https://pip.pypa.io/en/stable/)
+to get started with pip.
+
+### Windows
+On windows we recommend installing `HLAfreq` with `conda`.
+```
+conda create -n hlafreq -c bioconda -c conda-forge hlafreq
+conda activate hlafreq
+```
+See the [miniconda documentation](https://docs.conda.io/en/latest/miniconda.html)
+to get started with `conda`.
+
+### Troubleshooting
+`HLAfreq` uses `pymc` to estimate credible intervals,
+which is the source of most installation difficulty, see
+[pymc installation guide](https://www.pymc.io/projects/docs/en/stable/installation.html).
+
+You can try installing a specific `python` or `pymc` version
+(as long as it is >=3) and then add `HLAfreq` with pip or conda.
+For example
+```
+conda create -n hlafreq
+conda activate hlafreq
+conda install -c conda-forge python=3.10 pymc=5.0.2
+conda install -c bioconda hlafreq
+```
+If you don't intend to use credible intervals you can install
+with pip: `pip install HLAfreq`.
+However, if you do import `HLAfreq_pymc` you may get warnings
+about degraded performance.
 
 ## Minimal example
 Download HLA data using `makeURL()` and `getAFdata()`.

From 3fe73b87645dc2d6a53c87965d00c3a690309421 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 5 Jul 2023 11:08:54 +0100
Subject: [PATCH 113/192] Update install readme

---
 README.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 62240c2..a2b3fc6 100644
--- a/README.md
+++ b/README.md
@@ -32,7 +32,9 @@ You can install directly using pip
 pip install HLAfreq
 ```
 See the [pip documentation](https://pip.pypa.io/en/stable/)
-to get started with pip.
+to get started with pip. If you do have issues with pip,
+try installing with conda as described in
+the windows and troubleshooting sections below.
 
 ### Windows
 On windows we recommend installing `HLAfreq` with `conda`.

From b42df9b5486426ccf65fc7397dc909b6eed39cf0 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 5 Jul 2023 11:09:22 +0100
Subject: [PATCH 114/192] Simplify HLAfreq import in baseic use case for paper

---
 examples/paper/basic_use_case.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
index 7ee9004..0e0a99e 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/basic_use_case.py
@@ -1,15 +1,15 @@
 import matplotlib.pyplot as plt
-from HLAfreq import makeURL, getAFdata, combineAF, plotAF, population_coverage
+import HLAfreq
 from HLAfreq import HLAfreq_pymc
 
-base_url = makeURL("Mongolia", standard="g", locus="DQB1")
-aftab = getAFdata(base_url)
-caf = combineAF(aftab)
+base_url = HLAfreq.makeURL("Mongolia", standard="g", locus="DQB1")
+aftab = HLAfreq.getAFdata(base_url)
+caf = HLAfreq.combineAF(aftab)
 hdi = HLAfreq_pymc.AFhdi(aftab, credible_interval=0.95)
-plotAF(caf, aftab, hdi=hdi, compound_mean=hdi)
+HLAfreq.plotAF(caf, aftab, hdi=hdi, compound_mean=hdi)
 
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
-plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(population_coverage))
+plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(HLAfreq.population_coverage))
 plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
 plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
 plt.tight_layout(); plt.show()

From 6ae2e6b5348a7465a4b7bcc582aa52ac99c17166 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 12 Jul 2023 15:46:26 +0100
Subject: [PATCH 115/192] Improve install guide

focus on conda, regardless of OS
---
 README.md | 42 ++++++++++++++++++++++++------------------
 1 file changed, 24 insertions(+), 18 deletions(-)

diff --git a/README.md b/README.md
index a2b3fc6..0599237 100644
--- a/README.md
+++ b/README.md
@@ -24,46 +24,52 @@ the purpose of the panel, you should include a range of loci and
 supertypes (groups alleles sharing binding specificies).
 
 ## Install
-`HLAfreq` is a `python` package.
-
-### Linux and Mac
-You can install directly using pip
-```
-pip install HLAfreq
-```
-See the [pip documentation](https://pip.pypa.io/en/stable/)
-to get started with pip. If you do have issues with pip,
-try installing with conda as described in
-the windows and troubleshooting sections below.
-
-### Windows
-On windows we recommend installing `HLAfreq` with `conda`.
+`HLAfreq` is a `python` package. We recommend installing
+with `conda`.
 ```
 conda create -n hlafreq -c bioconda -c conda-forge hlafreq
 conda activate hlafreq
 ```
-See the [miniconda documentation](https://docs.conda.io/en/latest/miniconda.html)
+If you're new to conda see the miniconda [installation guide](https://conda.io/projects/conda/en/stable/user-guide/install/index.html) and [documentation](https://docs.conda.io/projects/conda/en/stable/user-guide/index.html)
 to get started with `conda`.
+Enter the above command into your conda prompt to create and
+activate a conda environment with `HLAfreq` installed.
+Typing `python` into this activated environment will start
+a python session where you can enter your python code such as
+the HLAfreq [minimal example](#minimal-example) below.
+
+If you prefer to write your python code as scripts using an IDE such as
+PyCharm or VScode, you'll need to look up how to configure a conda
+virtual environment with those tools.
 
 ### Troubleshooting
 `HLAfreq` uses `pymc` to estimate credible intervals,
 which is the source of most installation difficulty, see
 [pymc installation guide](https://www.pymc.io/projects/docs/en/stable/installation.html).
 
-You can try installing a specific `python` or `pymc` version
-(as long as it is >=3) and then add `HLAfreq` with pip or conda.
+At time of writing `pymc` doesn't play nice with python 3.11, so
+you can try installing a specific `python` version
+and then add `HLAfreq` with pip or conda.
 For example
 ```
 conda create -n hlafreq
 conda activate hlafreq
-conda install -c conda-forge python=3.10 pymc=5.0.2
+conda install -c conda-forge python=3.10
+conda install -c conda-forge pymc
 conda install -c bioconda hlafreq
 ```
+
+`HLAfreq` requires `python>=3.8` and `pymc>=3`.
+
 If you don't intend to use credible intervals you can install
 with pip: `pip install HLAfreq`.
 However, if you do import `HLAfreq_pymc` you may get warnings
 about degraded performance.
 
+See the [pip documentation](https://pip.pypa.io/en/stable/)
+to get started with pip. If you do have issues with pip,
+try installing with conda as described above.
+
 ## Minimal example
 Download HLA data using `makeURL()` and `getAFdata()`.
 All arguments that can be specified in the webpage form are available,

From 8d2fe5b3f30dc7bcf50a95e966d173b6fddea82a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Jul 2023 16:43:01 +0100
Subject: [PATCH 116/192] list OS

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0599237..3d6fda6 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ the purpose of the panel, you should include a range of loci and
 supertypes (groups alleles sharing binding specificies).
 
 ## Install
-`HLAfreq` is a `python` package. We recommend installing
+`HLAfreq` is a `python` package available on windows, mac, and linux. We recommend installing
 with `conda`.
 ```
 conda create -n hlafreq -c bioconda -c conda-forge hlafreq

From 4595f95ac80f0eaf013abea92abf774665aabfd3 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 17 Jul 2023 16:43:17 +0100
Subject: [PATCH 117/192] Explicity country argument

---
 examples/paper/basic_use_case.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/paper/basic_use_case.py b/examples/paper/basic_use_case.py
index 0e0a99e..90c7956 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/basic_use_case.py
@@ -2,7 +2,7 @@
 import HLAfreq
 from HLAfreq import HLAfreq_pymc
 
-base_url = HLAfreq.makeURL("Mongolia", standard="g", locus="DQB1")
+base_url = HLAfreq.makeURL(country="Mongolia", standard="g", locus="DQB1")
 aftab = HLAfreq.getAFdata(base_url)
 caf = HLAfreq.combineAF(aftab)
 hdi = HLAfreq_pymc.AFhdi(aftab, credible_interval=0.95)

From cd4aaec67a2b692e5efef960a0814ffaa7d8a464 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 29 Aug 2023 11:10:36 +0100
Subject: [PATCH 118/192] Ask people to open issues if they can't install

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 3d6fda6..0b8ed32 100644
--- a/README.md
+++ b/README.md
@@ -60,6 +60,7 @@ conda install -c bioconda hlafreq
 ```
 
 `HLAfreq` requires `python>=3.8` and `pymc>=3`.
+If you do run into trouble please open an [issue](https://github.com/Vaccitech/HLAfreq/issues).
 
 If you don't intend to use credible intervals you can install
 with pip: `pip install HLAfreq`.

From 57c736f9179defb2811661568aa2d6f8faa1c6f6 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 25 Sep 2023 13:21:24 +0100
Subject: [PATCH 119/192] Add biorxiv citation

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0b8ed32..a6dea85 100644
--- a/README.md
+++ b/README.md
@@ -132,4 +132,4 @@ twine upload dist/*
 -->
 
 ## Citation
-*In prep.*
+Wells, D. A., & McAuley, M. (2023). HLAfreq: Download and combine HLA allele frequency data. bioRxiv, 2023-09. https://doi.org/10.1101/2023.09.15.557761 

From a569cc58c55a7ed9df7c2c952403e420b9f06747 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 27 Oct 2023 10:04:19 +0100
Subject: [PATCH 120/192] Add instructions for debugging package versions

---
 README.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index a6dea85..35964cd 100644
--- a/README.md
+++ b/README.md
@@ -59,7 +59,10 @@ conda install -c conda-forge pymc
 conda install -c bioconda hlafreq
 ```
 
-`HLAfreq` requires `python>=3.8` and `pymc>=3`.
+`HLAfreq` requires `python>=3.8`, `matplotlib>=3.5`, and `pymc>=3`.
+Conda should handle this automatically, but if you get errors check
+the package versions with `conda list`.
+
 If you do run into trouble please open an [issue](https://github.com/Vaccitech/HLAfreq/issues).
 
 If you don't intend to use credible intervals you can install

From 84548daaa0e176eca7cb62b6b34a72067c74908b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 27 Oct 2023 10:06:13 +0100
Subject: [PATCH 121/192] HLA supertype data from Sidney et al 2008
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Sidney, J., Peters, B., Frahm, N., Brander, C., & Sette, A. (2008). HLA class I supertypes: A revised and updated classification. BMC Immunology, 9, 1–15. https://doi.org/10.1186/1471-2172-9-1
---
 data/HLA1supertypes_Sidney2008.csv | 946 +++++++++++++++++++++++++++++
 1 file changed, 946 insertions(+)
 create mode 100644 data/HLA1supertypes_Sidney2008.csv

diff --git a/data/HLA1supertypes_Sidney2008.csv b/data/HLA1supertypes_Sidney2008.csv
new file mode 100644
index 0000000..f77d1f9
--- /dev/null
+++ b/data/HLA1supertypes_Sidney2008.csv
@@ -0,0 +1,946 @@
+allele,supertype
+A*0101,A01
+A*0102,Unclassified
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+B*5517,B07
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+B*5604,B07
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+B*5612,B07
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+B*5807,B58
+B*5808,B58
+B*5809,B58
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+B*6701,B07
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+B*7802,B07
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+B*7804,B07
+B*7805,B62
+B*8101,B07
+B*8102,B07
+B*8201,Unclassified
+B*8202,Unclassified
+B*8301,Unclassified
+B*9501,Unclassified
+B*9502,B62
+B*9503,B27
+B*9504,B62

From 2d54e9e3cd264902ac052c5df294d8e84eb59100 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 27 Oct 2023 10:08:59 +0100
Subject: [PATCH 122/192] Countries and regions as defined by AFND

http://www.allelefrequencies.net/datasets.asp
---
 data/example/countries.csv | 248 +++++++++++++++++++++++++++++++++++++
 1 file changed, 248 insertions(+)
 create mode 100644 data/example/countries.csv

diff --git a/data/example/countries.csv b/data/example/countries.csv
new file mode 100644
index 0000000..130ab6e
--- /dev/null
+++ b/data/example/countries.csv
@@ -0,0 +1,248 @@
+Region,Country,largeRegion
+Central Asia,Afghanistan,Central Asia
+Central Asia,Kazakhstan,Central Asia
+Central Asia,Kyrgyzstan,Central Asia
+Central Asia,Tajikistan,Central Asia
+Central Asia,Turkmenistan,Central Asia
+Central Asia,Uzbekistan,Central Asia
+North-East Asia,Japan,East Asia
+North-East Asia,Mongolia,East Asia
+North-East Asia,North+Korea,East Asia
+North-East Asia,Russia,East Asia
+North-East Asia,South+Korea,East Asia
+South Asia,Bangladesh,East Asia
+South Asia,India,East Asia
+South Asia,Pakistan,East Asia
+South Asia,Sri+Lanka,East Asia
+South-East Asia,Bhutan,East Asia
+South-East Asia,Brunei,East Asia
+South-East Asia,Cambodia,East Asia
+South-East Asia,China,East Asia
+South-East Asia,Hong+Kong,East Asia
+South-East Asia,Laos,East Asia
+South-East Asia,Macau,East Asia
+South-East Asia,Malaysia,East Asia
+South-East Asia,Myanmar,East Asia
+South-East Asia,Nepal,East Asia
+South-East Asia,Singapore,East Asia
+South-East Asia,Taiwan,East Asia
+South-East Asia,Thailand,East Asia
+South-East Asia,Vietnam,East Asia
+Western Asia,Armenia,Western Asia
+Western Asia,Azerbaijan,Western Asia
+Western Asia,Bahrain,Western Asia
+Western Asia,Cyprus,Western Asia
+Western Asia,Gaza,Western Asia
+Western Asia,Georgia,Western Asia
+Western Asia,Iran,Western Asia
+Western Asia,Iraq,Western Asia
+Western Asia,Israel,Western Asia
+Western Asia,Jordan,Western Asia
+Western Asia,Kuwait,Western Asia
+Western Asia,Lebanon,Western Asia
+Western Asia,Oman,Western Asia
+Western Asia,Qatar,Western Asia
+Western Asia,Saudi+Arabia,Western Asia
+Western Asia,Syria,Western Asia
+Western Asia,Turkey,Western Asia
+Western Asia,United+Arab+Emirates,Western Asia
+Western Asia,West+Bank,Western Asia
+Western Asia,Yemen,Western Asia
+Australia,Australia,Oceania
+Europe,Albania,Europe
+Europe,Andorra,Europe
+Europe,Austria,Europe
+Europe,Belarus,Europe
+Europe,Belgium,Europe
+Europe,Bosnia+and+Herzegovina,Europe
+Europe,Bulgaria,Europe
+Europe,Croatia,Europe
+Europe,Czech+Republic,Europe
+Europe,Denmark,Europe
+Europe,England,Europe
+Europe,Estonia,Europe
+Europe,Faroe+Islands,Europe
+Europe,Finland,Europe
+Europe,France,Europe
+Europe,Germany,Europe
+Europe,Gibraltar,Europe
+Europe,Greece,Europe
+Europe,Hungary,Europe
+Europe,Iceland,Europe
+Europe,Ireland,Europe
+Europe,Italy,Europe
+Europe,Latvia,Europe
+Europe,Liechtenstein,Europe
+Europe,Lithuania,Europe
+Europe,Luxembourg,Europe
+Europe,Macedonia,Europe
+Europe,Malta,Europe
+Europe,Moldova,Europe
+Europe,Monaco,Europe
+Europe,Montenegro,Europe
+Europe,Netherlands,Europe
+Europe,Northern+Ireland,Europe
+Europe,Norway,Europe
+Europe,Poland,Europe
+Europe,Portugal,Europe
+Europe,Romania,Europe
+Europe,San+Marino,Europe
+Europe,Scotland,Europe
+Europe,Serbia,Europe
+Europe,Slovakia,Europe
+Europe,Slovenia,Europe
+Europe,Spain,Europe
+Europe,Svalbard+and+Jan+Mayen+Islands,Europe
+Europe,Sweden,Europe
+Europe,Switzerland,Europe
+Europe,Ukraine,Europe
+Europe,United+Kingdom,Europe
+Europe,Vatican,Europe
+Europe,Wales,Europe
+North America,Canada,America
+North America,Greenland,America
+North America,Mexico,America
+North America,United+States,America
+North Africa,Algeria,North Africa
+North Africa,Chad,North Africa
+North Africa,Djibouti,North Africa
+North Africa,Egypt,North Africa
+North Africa,Eritrea,North Africa
+North Africa,Ethiopia,North Africa
+North Africa,Libya,North Africa
+North Africa,Mali,North Africa
+North Africa,Mauritania,North Africa
+North Africa,Morocco,North Africa
+North Africa,Niger,North Africa
+North Africa,Sudan,North Africa
+North Africa,Tunisia,North Africa
+North Africa,Western+Sahara,North Africa
+Oceania,American+Samoa,Oceania
+Oceania,Borneo,Oceania
+Oceania,Bouvet+Island,Oceania
+Oceania,British+Indian+Ocean+Territory,Oceania
+Oceania,Christmas+Island,Oceania
+Oceania,Cocos+Islands,Oceania
+Oceania,Cook+Islands,Oceania
+Oceania,East+Timor,Oceania
+Oceania,Federal+States+of+Micronesia,Oceania
+Oceania,Fiji,Oceania
+Oceania,French+Polynesia,Oceania
+Oceania,French+Southern+Territories,Oceania
+Oceania,Guam,Oceania
+Oceania,Heard+and+Mc+Donald+Islands,Oceania
+Oceania,Indonesia,Oceania
+Oceania,Kiribati,Oceania
+Oceania,Madagascar,Oceania
+Oceania,Maldives,Oceania
+Oceania,Marshall+Islands,Oceania
+Oceania,Nauru,Oceania
+Oceania,New+Caledonia,Oceania
+Oceania,New+Zealand,Oceania
+Oceania,Niue,Oceania
+Oceania,Norfolk+Island,Oceania
+Oceania,Northern+Mariana+Islands,Oceania
+Oceania,Palau,Oceania
+Oceania,Papua+New+Guinea,Oceania
+Oceania,Philippines,Oceania
+Oceania,Pitcairn+Islands,Oceania
+Oceania,Samoa,Oceania
+Oceania,Solomon+Islands,Oceania
+Oceania,Timor-Leste,Oceania
+Oceania,Tokelau,Oceania
+Oceania,Tonga,Oceania
+Oceania,Tuvalu,Oceania
+Oceania,Vanuatu,Oceania
+Oceania,Wallis+and+Futuna+Islands,Oceania
+South and Central America,Anguilla,America
+South and Central America,Antigua+and+Barbuda,America
+South and Central America,Argentina,America
+South and Central America,Aruba,America
+South and Central America,Bahamas,America
+South and Central America,Barbados,America
+South and Central America,Belice,America
+South and Central America,Bermuda,America
+South and Central America,Bolivia,America
+South and Central America,Brazil,America
+South and Central America,British+Virgin+Islands,America
+South and Central America,Cayman+Islands,America
+South and Central America,Chile,America
+South and Central America,Colombia,America
+South and Central America,Costa+Rica,America
+South and Central America,Cuba,America
+South and Central America,Dominica,America
+South and Central America,Dominican+Republic,America
+South and Central America,Ecuador,America
+South and Central America,El+Salvador,America
+South and Central America,Falkland+Islands,America
+South and Central America,French+Guiana,America
+South and Central America,Grenada,America
+South and Central America,Guadeloupe,America
+South and Central America,Guatemala,America
+South and Central America,Guyana,America
+South and Central America,Haiti,America
+South and Central America,Honduras,America
+South and Central America,Jamaica,America
+South and Central America,Martinique,America
+South and Central America,Montserrat,America
+South and Central America,Netherlands+Antilles,America
+South and Central America,Nicaragua,America
+South and Central America,Panama,America
+South and Central America,Paraguay,America
+South and Central America,Peru,America
+South and Central America,Puerto+Rico,America
+South and Central America,Saint+Berthelemy,America
+South and Central America,Saint+Kitts+and+Nevis,America
+South and Central America,Saint+Lucia,America
+South and Central America,Saint+Martin,America
+South and Central America,Saint+Vincent+and+the+Grenadines,America
+South and Central America,Sant+Pierre+and+Miquelon,America
+South and Central America,South+Georgia+and+South+Sandwich+Islands,America
+South and Central America,Suriname,America
+South and Central America,Trinidad+and+Tobago,America
+South and Central America,Turks+and+Caicos+Islands,America
+South and Central America,United+States+Virgin+Islands,America
+South and Central America,Uruguay,America
+South and Central America,Venezuela,America
+Sub-Saharan Africa,Angola,Sub-Saharan Africa
+Sub-Saharan Africa,Benin,Sub-Saharan Africa
+Sub-Saharan Africa,Botwsana,Sub-Saharan Africa
+Sub-Saharan Africa,Burkina+Faso,Sub-Saharan Africa
+Sub-Saharan Africa,Burundi,Sub-Saharan Africa
+Sub-Saharan Africa,Cameroon,Sub-Saharan Africa
+Sub-Saharan Africa,Cape+Verde,Sub-Saharan Africa
+Sub-Saharan Africa,Central+African+Republic,Sub-Saharan Africa
+Sub-Saharan Africa,Comoros,Sub-Saharan Africa
+Sub-Saharan Africa,Congo,Sub-Saharan Africa
+Sub-Saharan Africa,Cote+d+Ivoire,Sub-Saharan Africa
+Sub-Saharan Africa,Democratic+Republic+of+the+Congo,Sub-Saharan Africa
+Sub-Saharan Africa,Equatorial+Guinea,Sub-Saharan Africa
+Sub-Saharan Africa,Gabon,Sub-Saharan Africa
+Sub-Saharan Africa,Gambia,Sub-Saharan Africa
+Sub-Saharan Africa,Ghana,Sub-Saharan Africa
+Sub-Saharan Africa,Guinea,Sub-Saharan Africa
+Sub-Saharan Africa,Guinea-Bissau,Sub-Saharan Africa
+Sub-Saharan Africa,Kenya,Sub-Saharan Africa
+Sub-Saharan Africa,Lesotho,Sub-Saharan Africa
+Sub-Saharan Africa,Liberia,Sub-Saharan Africa
+Sub-Saharan Africa,Malawi,Sub-Saharan Africa
+Sub-Saharan Africa,Mauritius,Sub-Saharan Africa
+Sub-Saharan Africa,Mayotte,Sub-Saharan Africa
+Sub-Saharan Africa,Mozambique,Sub-Saharan Africa
+Sub-Saharan Africa,Namibia,Sub-Saharan Africa
+Sub-Saharan Africa,Nigeria,Sub-Saharan Africa
+Sub-Saharan Africa,Reunion,Sub-Saharan Africa
+Sub-Saharan Africa,Rwanda,Sub-Saharan Africa
+Sub-Saharan Africa,Saint+Helena,Sub-Saharan Africa
+Sub-Saharan Africa,Sao+Tome+and+Principe,Sub-Saharan Africa
+Sub-Saharan Africa,Senegal,Sub-Saharan Africa
+Sub-Saharan Africa,Seychelles,Sub-Saharan Africa
+Sub-Saharan Africa,Sierra+Leone,Sub-Saharan Africa
+Sub-Saharan Africa,Somalia,Sub-Saharan Africa
+Sub-Saharan Africa,South+Africa,Sub-Saharan Africa
+Sub-Saharan Africa,Swaziland,Sub-Saharan Africa
+Sub-Saharan Africa,Tanzania,Sub-Saharan Africa
+Sub-Saharan Africa,Togo,Sub-Saharan Africa
+Sub-Saharan Africa,Uganda,Sub-Saharan Africa
+Sub-Saharan Africa,Zambia,Sub-Saharan Africa
+Sub-Saharan Africa,Zimbabwe,Sub-Saharan Africa

From 37c7cb4ff0c659b5e00ef5d0e5eff009c9003f6e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Dec 2023 13:18:00 +0000
Subject: [PATCH 123/192] More specific conda install instructions

---
 README.md | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 35964cd..e45f7f7 100644
--- a/README.md
+++ b/README.md
@@ -52,11 +52,7 @@ you can try installing a specific `python` version
 and then add `HLAfreq` with pip or conda.
 For example
 ```
-conda create -n hlafreq
-conda activate hlafreq
-conda install -c conda-forge python=3.10
-conda install -c conda-forge pymc
-conda install -c bioconda hlafreq
+conda create -n hlafreq -c conda-forge -c bioconda python=3.10 numpy=1.25.2 pymc=5.6.1 hlafreq
 ```
 
 `HLAfreq` requires `python>=3.8`, `matplotlib>=3.5`, and `pymc>=3`.

From d91f51b708bfab3218ae6e39408aaeb03d260bc9 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Dec 2023 13:18:18 +0000
Subject: [PATCH 124/192] Only add missing rows if there are some

---
 src/HLAfreq/HLAfreq.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 4b7392a..cf221cc 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -387,7 +387,8 @@ def unmeasured_alleles(AFtab, datasetID="population"):
                 ],
             )
             # Add them in with zero frequency
-            df = pd.concat([df, missing_rows], ignore_index=True)
+            if not missing_rows.empty:
+                df = pd.concat([df, missing_rows], ignore_index=True)
     return df
 
 

From 97543ee5eeb35ece4e54f0e9816e4a016eccca1f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 20 Dec 2023 13:42:16 +0000
Subject: [PATCH 125/192] Update version number

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index b48ca7d..23c93c9 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.2",
+    version="0.0.3",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"

From cc29826f28d0b367a2c437a69bb3f861c9f33c52 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 2 Jul 2024 16:11:06 +0100
Subject: [PATCH 126/192] Don't track virtual environment

---
 .gitignore | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.gitignore b/.gitignore
index f1b1575..c473d30 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,3 +2,4 @@ data/
 writeup/
 *__pycache__/
 *.code-workspace
+envs/.venv
\ No newline at end of file

From 40f2ce278272688ef58de8ecf8f571c669e9a05b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 2 Jul 2024 16:12:46 +0100
Subject: [PATCH 127/192] Generate html docs with pdoc

Add docstrings to modules and use readme for top module.
---
 README.md                   | 14 +++++++++-----
 src/HLAfreq/HLAfreq.py      |  2 --
 src/HLAfreq/HLAfreq_data.py | 12 ++++++++++++
 src/HLAfreq/HLAfreq_pymc.py |  5 +++++
 src/HLAfreq/__init__.py     |  3 +++
 5 files changed, 29 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index e45f7f7..2664b90 100644
--- a/README.md
+++ b/README.md
@@ -21,7 +21,7 @@ for example population size when averaging across countries.
 When selecting a panel of HLA alleles to represent a population,
 allele frequency is not the only thing to consider. Depending on
 the purpose of the panel, you should include a range of loci and
-supertypes (groups alleles sharing binding specificies).
+supertypes (grouped alleles sharing binding specificies).
 
 ## Install
 `HLAfreq` is a `python` package available on windows, mac, and linux. We recommend installing
@@ -71,7 +71,7 @@ to get started with pip. If you do have issues with pip,
 try installing with conda as described above.
 
 ## Minimal example
-Download HLA data using `makeURL()` and `getAFdata()`.
+Download HLA data using `HLAfreq.HLAfreq.makeURL()` and `HLAfreq.HLAfreq.getAFdata()`.
 All arguments that can be specified in the webpage form are available,
 see `help(HLAfreq.makeURL)` for details (press `q` to exit).
 ```
@@ -83,7 +83,8 @@ aftab = HLAfreq.getAFdata(base_url)
 After downloading the data, it must be filtered so that all studies
 sum to allele frequency 1 (within tolerence). Then we must ensure
 that all studies report alleles at the same resolution.
-Finaly we can combine frequency estimates.
+Finaly we can combine frequency estimates, for more details see
+the `HLAfreq.HLAfreq.combineAF()` api documentation.
 ```
 aftab = HLAfreq.only_complete(aftab)
 aftab = HLAfreq.decrease_resolution(aftab, 2)
@@ -100,16 +101,19 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 
 ## Docs
 For help on specific functions view the docstring, `help(function_name)`.
-Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/blob/main/docs/HLAfreq.md)
-created with pdoc3 in pdf mode.
+Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/docs/index.html)
+created with pdoc3 with `pdoc -d google -o docs/ HLAfreq`.
 
 <!-- ## Developer notes
 # Install in dev mode
 pip install -e HLAfreq
+pip install -e .
 
 Update version in setup.py
 
 Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
+Or html documentation with:
+`pdoc -d google -o docs/ HLAfreq`
 
 Run tests `pytest` 
 
diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index cf221cc..aef77cf 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -1,6 +1,4 @@
 """
-HLAfreq
-
 Download allele frequency data from
 [allelefrequencies.net](www.allelefrequencies.net). Allele
 frequencies from different populations can be combined to
diff --git a/src/HLAfreq/HLAfreq_data.py b/src/HLAfreq/HLAfreq_data.py
index bf2dd4c..a67224d 100644
--- a/src/HLAfreq/HLAfreq_data.py
+++ b/src/HLAfreq/HLAfreq_data.py
@@ -6,11 +6,23 @@
 
 
 def load_countries():
+    """Load dataframe of countries and regions available on [allele frequencies.net](http://www.allelefrequencies.net/).
+
+    Returns:
+        pd.DataFrame: Three columns: `Country`, `Region`, and `largeRegion`.
+        `largeRegion` is based on `Region` with with fewer categories to improve
+        plotting.
+    """
     stream = pkg_resources.resource_stream(__name__, "data/countries.csv")
     return pd.read_csv(stream, encoding="latin-1")
 
 
 def load_HLA1supertypes_Sidney2008():
+    """Load HLA alleles and their supertype as defined in Sidney2008
+
+    Returns:
+        pd.DataFrame: DataFrame of alleles and their supertype
+    """
     stream = pkg_resources.resource_stream(
         __name__, "data/HLA1supertypes_Sidney2008.csv"
     )
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 73a70de..a1e7b46 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -1,3 +1,8 @@
+"""
+Functions using `pymc` to acurately estimate credible intervals
+on allele frequency estimates.
+"""
+
 import math
 import pymc as pm
 import numpy as np
diff --git a/src/HLAfreq/__init__.py b/src/HLAfreq/__init__.py
index 4648629..0892506 100644
--- a/src/HLAfreq/__init__.py
+++ b/src/HLAfreq/__init__.py
@@ -1 +1,4 @@
+"""
+.. include:: ../../README.md
+"""
 from .HLAfreq import *

From 627af1db4627ac4faaf4aeda9be019ef9c9ca1cf Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 2 Jul 2024 16:21:53 +0100
Subject: [PATCH 128/192] Use pdoc's github action template

---
 .github/workflows/docs.yaml | 52 +++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 .github/workflows/docs.yaml

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
new file mode 100644
index 0000000..d96081f
--- /dev/null
+++ b/.github/workflows/docs.yaml
@@ -0,0 +1,52 @@
+name: website
+
+# build the documentation whenever there are new commits on main
+on:
+  push:
+    branches:
+      - main
+      - docs
+    # Alternative: only build for tags.
+    # tags:
+    #   - '*'
+
+# security: restrict permissions for CI jobs.
+permissions:
+  contents: read
+
+jobs:
+  # Build the documentation and upload the static HTML files as an artifact.
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      # ADJUST THIS: install all dependencies (including pdoc)
+      - run: pip install -e .
+      - run: pip install pdoc
+      # ADJUST THIS: build your documentation into docs/.
+      # We use a custom build script for pdoc itself, ideally you just run `pdoc -o docs/ ...` here.
+      # - run: python docs/make.py
+      - run: pdoc -d google -o docs/ HLAfreq
+
+      - uses: actions/upload-pages-artifact@v3
+        with:
+          path: docs/
+
+  # Deploy the artifact to GitHub pages.
+  # This is a separate job so that only actions/deploy-pages has the necessary permissions.
+  deploy:
+    needs: build
+    runs-on: ubuntu-latest
+    permissions:
+      pages: write
+      id-token: write
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    steps:
+      - id: deployment
+        uses: actions/deploy-pages@v4
\ No newline at end of file

From ae85e5d14b2351d5042c0831896bf3c8010231d9 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 2 Jul 2024 17:13:51 +0100
Subject: [PATCH 129/192] Delete docs markdown because it's generated as an
 html file now.

---
 docs/HLAfreq.md | 871 ------------------------------------------------
 1 file changed, 871 deletions(-)
 delete mode 100644 docs/HLAfreq.md

diff --git a/docs/HLAfreq.md b/docs/HLAfreq.md
deleted file mode 100644
index 43cb623..0000000
--- a/docs/HLAfreq.md
+++ /dev/null
@@ -1,871 +0,0 @@
----
-description: |
-    API documentation for modules: HLAfreq, HLAfreq.HLAfreq, HLAfreq.HLAfreq_data, HLAfreq.HLAfreq_pymc.
-
-lang: en
-
-classoption: oneside
-geometry: margin=1in
-papersize: a4
-
-linkcolor: blue
-links-as-notes: true
-...
-
-
-    
-# Module `HLAfreq` {#HLAfreq}
-
-
-
-
-    
-## Sub-modules
-
-* [HLAfreq.HLAfreq](#HLAfreq.HLAfreq)
-* [HLAfreq.HLAfreq_data](#HLAfreq.HLAfreq_data)
-* [HLAfreq.HLAfreq_pymc](#HLAfreq.HLAfreq_pymc)
-
-
-
-
-
-
-    
-# Module `HLAfreq.HLAfreq` {#HLAfreq.HLAfreq}
-
-HLAfreq
-
-Download allele frequency data from
-[allelefrequencies.net](www.allelefrequencies.net). Allele
-frequencies from different populations can be combined to
-estimate HLA frequencies of countries or other regions such as
-global HLA frequencies.
-
-
-
-
-    
-## Functions
-
-
-    
-### Function `Npages` {#HLAfreq.HLAfreq.Npages}
-
-
-
-    
-> `def Npages(bs)`
-
-
-How many pages of results are there?
-
-
-###### Args
-
-**```bs```** :&ensp;<code>bs4.BeautifulSoup</code>
-:   BS object of allelefrequencies.net results page
-
-
-
-###### Returns
-
-<code>int</code>
-:   Total number of results pages
-
-
-
-    
-### Function `alleles_unique_in_study` {#HLAfreq.HLAfreq.alleles_unique_in_study}
-
-
-
-    
-> `def alleles_unique_in_study(AFtab, datasetID='population')`
-
-
-Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by <code>datasetID</code>.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Allele frequency data
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Unique identifier column to define study. Defaults to 'population'.
-
-
-
-###### Returns
-
-<code>bool</code>
-:   <code>True</code> on if no alleles occur more than once in any study, otherwise <code>False</code>.
-
-
-
-    
-### Function `betaAB` {#HLAfreq.HLAfreq.betaAB}
-
-
-
-    
-> `def betaAB(alpha)`
-
-
-Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
-
-
-###### Args
-
-**```alpha```** :&ensp;<code>list</code>
-:   Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
-
-
-
-###### Returns
-
-<code>list</code>
-:   List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.
-
-
-
-    
-### Function `check_resolution` {#HLAfreq.HLAfreq.check_resolution}
-
-
-
-    
-> `def check_resolution(AFtab)`
-
-
-Check if all alleles in AFtab have the same resolution.
-Will print the number of records with each resolution.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Allele frequency data
-
-
-
-###### Returns
-
-<code>bool</code>
-:   True only if all alleles have the same resolution, else False.
-
-
-
-    
-### Function `collapse_reduced_alleles` {#HLAfreq.HLAfreq.collapse_reduced_alleles}
-
-
-
-    
-> `def collapse_reduced_alleles(AFtab, datasetID='population')`
-
-
-
-
-    
-### Function `combineAF` {#HLAfreq.HLAfreq.combineAF}
-
-
-
-    
-> `def combineAF(AFtab, weights='2n', alpha=[], datasetID='population', format=True, ignoreG=True, add_unmeasured=True, complete=True, resolution=True, unique=True)`
-
-
-Combine allele frequencies from multiple studies. <code>datasetID</code> is the unique identifier for studies to combine.
-Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
-Sample size is doubled to get <code>2n</code> due to diploidy. If an alternative <code>weights</code> is set it is not doubled.
-The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior <code>alpha</code>.
-If <code>alpha</code> is not set the prior defaults to 1 observation of each allele.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Table of Allele frequency data
-
-
-**```weights```** :&ensp;<code>str</code>, optional
-:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-
-
-**```alpha```** :&ensp;<code>list</code>, optional
-:   Prior to use for Dirichlet distribution. Defaults to [].
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Unique identifier column for study. Defaults to 'population'.
-
-
-**```format```** :&ensp;<code>bool</code>, optional
-:   Run <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>. Defaults to True.
-
-
-**```ignoreG```** :&ensp;<code>bool</code>, optional
-:   Treat allele G groups as normal, see <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>. Defaults to True.
-
-
-**```add_unmeasured```** :&ensp;<code>bool</code>, optional
-:   Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See <code>add\_unmeasured()</code>. Defaults to True.
-
-
-**```complete```** :&ensp;<code>bool</code>, optional
-:   Check study completeness. Uses default values for <code>[incomplete\_studies()](#HLAfreq.HLAfreq.incomplete\_studies "HLAfreq.HLAfreq.incomplete\_studies")</code>. If you are happy with your study completeness can be switched off with False. Defaults to True.
-
-
-**```resolution```** :&ensp;<code>bool</code>, optional
-:   Check that all alleles have the same resolution, see <code>[check\_resolution()](#HLAfreq.HLAfreq.check\_resolution "HLAfreq.HLAfreq.check\_resolution")</code>. Defaults to True.
-
-
-**```unique```** :&ensp;<code>bool</code>, optional
-:   Check that each allele appears no more than once per study. See <code>[alleles\_unique\_in\_study()](#HLAfreq.HLAfreq.alleles\_unique\_in\_study "HLAfreq.HLAfreq.alleles\_unique\_in\_study")</code>. Defaults to True.
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   Allele frequencies after combining estimates from all studies.
-
-
-*allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is <code>alpha</code> + <code>c</code>.
-*alpha* is the prior used for the Dirichlet distribution.
-*c* is the observations used for the Dirichlet distribution.
-*sample_size* is the total sample size of all combined studies.
-*wav* is the weighted average.
-
-    
-### Function `decrease_resolution` {#HLAfreq.HLAfreq.decrease_resolution}
-
-
-
-    
-> `def decrease_resolution(AFtab, newres, datasetID='population')`
-
-
-Decrease allele resolution to a specified value so all alleles have the same resolution.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Allele frequency data.
-
-
-**```newres```** :&ensp;<code>int</code>
-:   The desired number of fields for resolution.
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Column to use as stud identifier. Defaults to 'population'.
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   Allele frequency data with all alleles of requested resolution.
-
-
-
-    
-### Function `default_prior` {#HLAfreq.HLAfreq.default_prior}
-
-
-
-    
-> `def default_prior(k)`
-
-
-Calculate a default prior, 1 observation of each class.
-
-
-###### Args
-
-**```k```** :&ensp;<code>int</code>
-:   Number of classes in the Dirichlet distribution.
-
-
-
-###### Returns
-
-<code>list</code>
-:   List of k 1s to use as prior.
-
-
-
-    
-### Function `duplicated_sample_size` {#HLAfreq.HLAfreq.duplicated_sample_size}
-
-
-
-    
-> `def duplicated_sample_size(AFtab)`
-
-
-Returns True if any loci has more than 1 unique sample size
-
-    
-### Function `formatAF` {#HLAfreq.HLAfreq.formatAF}
-
-
-
-    
-> `def formatAF(AFtab, ignoreG=True)`
-
-
-Format allele frequency table.
-Convert sample_size and allele_freq to numeric data type.
-Removes commas from sample size. Removes "(*)" from allele frequency if 
-<code>ignoreG</code> is <code>True</code>. <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code> is used internally by combineAF and getAFdata by default.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Allele frequency data downloaded from allelefrequency.net using <code>[getAFdata()](#HLAfreq.HLAfreq.getAFdata "HLAfreq.HLAfreq.getAFdata")</code>.
-
-
-**```ignoreG```** :&ensp;<code>bool</code>, optional
-:   Treat G group alleles as normal. See <http://hla.alleles.org/alleles/g_groups.html> for details. Defaults to True.
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   The formatted allele frequency data.
-
-
-
-    
-### Function `getAFdata` {#HLAfreq.HLAfreq.getAFdata}
-
-
-
-    
-> `def getAFdata(base_url, format=True, ignoreG=True)`
-
-
-Get all allele frequency data from a search base url. Iterates over all
-    pages regardless of which page is based.
-
-
-###### Args
-
-**```base_url```** :&ensp;<code>str</code>
-:   URL for base search.
-
-
-**```format```** :&ensp;<code>bool</code>
-:   Format the downloaded data using <code>[formatAF()](#HLAfreq.HLAfreq.formatAF "HLAfreq.HLAfreq.formatAF")</code>.
-
-
-**```ignoreG```** :&ensp;<code>bool</code>
-:   treat allele G groups as normal. See <http://hla.alleles.org/alleles/g_groups.html> for details. Default = True
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   allele frequency data parsed into a pandas dataframe
-
-
-
-    
-### Function `id_duplicated_allele` {#HLAfreq.HLAfreq.id_duplicated_allele}
-
-
-
-    
-> `def id_duplicated_allele(grouped)`
-
-
-Reports the allele that has mupltiple sample sizes
-
-    
-### Function `incomplete_studies` {#HLAfreq.HLAfreq.incomplete_studies}
-
-
-
-    
-> `def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID='population')`
-
-
-Report any studies with allele freqs that don't sum to 1
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Dataframe containing multiple studies
-
-
-**```llimit```** :&ensp;<code>float</code>, optional
-:   Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-
-
-**```ulimit```** :&ensp;<code>float</code>, optional
-:   Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-
-
-**```datasetID```** :&ensp;<code>str</code>
-:   Unique identifier column for study
-
-
-
-    
-### Function `makeURL` {#HLAfreq.HLAfreq.makeURL}
-
-
-
-    
-> `def makeURL(country='', standard='s', locus='', resolution_pattern='bigger_equal_than', resolution=2, region='', ethnic='', study_type='', dataset_source='', sample_year='', sample_year_pattern='', sample_size='', sample_size_pattern='')`
-
-
-Create URL for search of allele frequency net database. All arguments are documented [here](<http://www.allelefrequencies.net/extaccess.asp>)
-
-###### Args
-
-**```country```** :&ensp;<code>str</code>, optional
-:   Country name to retrieve records from. Defaults to "".
-
-
-**```standard```** :&ensp;<code>str</code>, optional
-:   Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
-
-
-**```locus```** :&ensp;<code>str</code>, optional
-:   The locus to return allele data for. Defaults to "".
-
-
-**```resolution_pattern```** :&ensp;<code>str</code>, optional
-:   Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using <code>resolution</code> and <code>resolution\_pattern</code>. Defaults to "bigger_equal_than".
-
-
-**```resolution```** :&ensp;<code>int</code>, optional
-:   Number of fields of resolution of allele. Filter created using <code>resolution</code> and <code>resolution\_pattern</code>. Defaults to 2.
-
-
-**```region```** :&ensp;<code>str</code>, optional
-:   Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](<http://www.allelefrequencies.net/pop6003a.asp>). Defaults to "".
-
-
-**```ethnic```** :&ensp;<code>str</code>, optional
-:   Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}. All ethnicities listed [here](<http://www.allelefrequencies.net/pop6003a.asp>). Defaults to "".
-
-
-**```study_type```** :&ensp;<code>str</code>, optional
-:   Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
-
-
-**```dataset_source```** :&ensp;<code>str</code>, optional
-:   Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
-
-
-**```sample_year```** :&ensp;<code>int</code>, optional
-:   Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".
-
-
-**```sample_year_pattern```** :&ensp;<code>str</code>, optional
-:   Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
-
-
-**```sample_size```** :&ensp;<code>int</code>, optional
-:   Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".
-
-
-**```sample_size_pattern```** :&ensp;<code>str</code>, optional
-:   Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
-
-
-
-###### Returns
-
-<code>str</code>
-:   URL to search allelefrequencies.net
-
-
-
-    
-### Function `only_complete` {#HLAfreq.HLAfreq.only_complete}
-
-
-
-    
-> `def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID='population')`
-
-
-Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
-This prevents throwing away data if another loci in the population is incomplete
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Dataframe containing multiple studies
-
-
-**```llimit```** :&ensp;<code>float</code>, optional
-:   Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-
-
-**```ulimit```** :&ensp;<code>float</code>, optional
-:   Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
-
-
-**```datasetID```** :&ensp;<code>str</code>
-:   Unique identifier column for study. Defaults to 'population'.
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   Allele frequency data of multiple studies, but only complete studies.
-
-
-
-    
-### Function `parseAF` {#HLAfreq.HLAfreq.parseAF}
-
-
-
-    
-> `def parseAF(bs)`
-
-
-Generate a dataframe from a given html page
-
-
-###### Args
-
-**```bs```** :&ensp;<code>bs4.BeautifulSoup</code>
-:   BeautifulSoup object from allelefrequencies.net page
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   Table of allele, allele frequency, samplesize, and population
-
-
-
-    
-### Function `plotAF` {#HLAfreq.HLAfreq.plotAF}
-
-
-
-    
-> `def plotAF(caf=Empty DataFrame
-Columns: []
-Index: [], AFtab=Empty DataFrame
-Columns: []
-Index: [], cols=['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'], datasetID='population', hdi=Empty DataFrame
-Columns: []
-Index: [], compound_mean=Empty DataFrame
-Columns: []
-Index: [])`
-
-
-Plot combined allele frequencies, individual allele frequencies,
-and credible intervals on combined allele frequency estimates.
-Credible interval is only plotted if a value is given for <code>hdi</code>.
-The plotted Credible interval is whatever was passed to HLAfreq_pymc.AFhdi() when calculating hdi.
-
-
-###### Args
-
-**```caf```** :&ensp;<code>pd.DataFrame</code>, optional
-:   Combined allele frequency estimates from HLAfreq.combineAF. Defaults to pd.DataFrame().
-
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>, optional
-:   Table of allele frequency data. Defaults to pd.DataFrame().
-
-
-**```cols```** :&ensp;<code>list</code>, optional
-:   List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Column used to define separate datasets. Defaults to "population".
-
-
-**```weights```** :&ensp;<code>str</code>, optional
-:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-
-
-**```hdi```** :&ensp;<code>pd.DataFrame</code>, optional
-:   The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
-
-
-**```compound_mean```** :&ensp;<code>pd.DataFrame</code>, optional
-:   The high density interval object to plot post_mean. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
-
-
-
-    
-### Function `plot_prior` {#HLAfreq.HLAfreq.plot_prior}
-
-
-
-    
-> `def plot_prior(concentration, ncol=2, psteps=1000, labels='')`
-
-
-Plot probability density function for prior values.
-
-
-###### Args
-
-**```concentration```** :&ensp;<code>list</code>
-:   Vector of the prior Dirichlet concentration values.
-
-
-**```ncol```** :&ensp;<code>int</code>, optional
-:   Number of columns. Defaults to 2.
-
-
-**```labels```** :&ensp;<code>list</code>, optional
-:   Labels for elements of concentration in the same order. Defaults to "".
-
-
-
-    
-### Function `population_coverage` {#HLAfreq.HLAfreq.population_coverage}
-
-
-
-    
-> `def population_coverage(p)`
-
-
-Calculate the proportion of people with at least 1 copy of this allele
-    assuming HWE.
-
-
-###### Args
-
-**```p```** :&ensp;<code>float</code>
-:   Allele frequency
-
-
-
-###### Returns
-
-<code>float</code>
-:   Sum of homozygotes and heterozygotes for this allele
-
-
-
-    
-### Function `single_loci` {#HLAfreq.HLAfreq.single_loci}
-
-
-
-    
-> `def single_loci(AFtab)`
-
-
-Check that allele frequency data is only of one locus
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Allele frequency data
-
-
-
-    
-### Function `unmeasured_alleles` {#HLAfreq.HLAfreq.unmeasured_alleles}
-
-
-
-    
-> `def unmeasured_alleles(AFtab, datasetID='population')`
-
-
-When combining AF estimates, unreported alleles can inflate frequencies
-    so AF sums to >1. Therefore we add unreported alleles with frequency zero.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Formatted allele frequency data
-
-
-**```datasetID```** :&ensp;<code>str</code>
-:   Unique identifier column for study
-
-
-
-###### Returns
-
-<code>pd.DataFrame</code>
-:   Allele frequency data with all locus alleles reported 
-    for each dataset
-
-
-
-
-
-
-    
-# Module `HLAfreq.HLAfreq_data` {#HLAfreq.HLAfreq_data}
-
-Data loaders
-
-
-
-
-    
-## Functions
-
-
-    
-### Function `load_HLA1supertypes_Sidney2008` {#HLAfreq.HLAfreq_data.load_HLA1supertypes_Sidney2008}
-
-
-
-    
-> `def load_HLA1supertypes_Sidney2008()`
-
-
-
-
-    
-### Function `load_countries` {#HLAfreq.HLAfreq_data.load_countries}
-
-
-
-    
-> `def load_countries()`
-
-
-
-
-
-
-
-    
-# Module `HLAfreq.HLAfreq_pymc` {#HLAfreq.HLAfreq_pymc}
-
-
-
-
-
-
-    
-## Functions
-
-
-    
-### Function `AFhdi` {#HLAfreq.HLAfreq_pymc.AFhdi}
-
-
-
-    
-> `def AFhdi(AFtab, weights='2n', datasetID='population', credible_interval=0.95, prior=[], conc_mu=1, conc_sigma=1, compare_models=True)`
-
-
-Calculate mean and high posterior density interval on combined allele frequency.
-Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](<https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html>).
-
-In brief, the global allele frequency is modelled as a Dirichlet distribution,
-and each population (defined by <code>datasetID</code>) is a Dirichlet distribution draw from
-the global Dirichlet distribution, and the observed allele count data of that
-population is multinomial count data drawn from the population Dirichlet distribution.
-
-The observed allele frequencies are transformed into allele counts using <code>weights</code>.
-The variability of population allele frequencies around the global mean is defined
-by a latent, lognormal variable <code>conc</code>.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Table of allele frequency data
-
-
-**```weights```** :&ensp;<code>str</code>, optional
-:   Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Unique identifier column for study. Defaults to 'population'.
-
-
-**```credible_interval```** :&ensp;<code>float</code>, optional
-:   The size of the credible interval requested. Defaults to 0.95.
-
-
-**```prior```** :&ensp;<code>list</code>, optional
-:   Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
-
-
-**```conc_mu```** :&ensp;<code>float</code>, optional
-:   Mean to parameterise lognormal distribution of <code>conc</code> prior. Defaults to 1.
-
-
-**```conc_sigma```** :&ensp;<code>float</code>, optional
-:   Standard deviation to parameterise lognormal distribution of <code>conc</code> prior. Defaults to 1.
-
-
-**```compare_models```** :&ensp;<code>bool</code>, optional
-:   Check that default estimated allele_freq is within compound model estimated credible intervals. Defaults to True.
-
-
-
-###### Returns
-
-<code>np.array</code>
-:   Pairs of high density interval limits, allele name, and posterior mean.
-    as a 4 by n array.
-    In alphabetical order of alleles, regardless of input order.
-    This way it matches the output of combineAF().
-
-
-
-    
-### Function `compare_estimates` {#HLAfreq.HLAfreq_pymc.compare_estimates}
-
-
-
-    
-> `def compare_estimates(AFtab, hdi, datasetID)`
-
-
-Does the defaul estimate of <code>allele\_freq</code> sit within the compound
-model's estimated credible intervals? If not, print warnings.
-
-
-###### Args
-
-**```AFtab```** :&ensp;<code>pd.DataFrame</code>
-:   Table of allele frequency data
-
-
-**```hdi```** :&ensp;<code>np.array</code>
-:   Pairs of high density interval limits, allele name, and posterior mean from compound model.
-
-
-**```datasetID```** :&ensp;<code>str</code>, optional
-:   Unique identifier column for study.
-
-
-
-
-
------
-Generated by *pdoc* 0.8.1 (<https://pdoc3.github.io>).

From 8efc67bdb4d262ad3112359d2d2a77ed4e4a4db6 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 2 Jul 2024 17:30:50 +0100
Subject: [PATCH 130/192] Add detail about docs hosted on a github page and how
 to regenerate it

---
 README.md      | 19 +++++++++++++------
 docs/README.md |  7 +++++++
 2 files changed, 20 insertions(+), 6 deletions(-)
 create mode 100644 docs/README.md

diff --git a/README.md b/README.md
index 2664b90..bdd6ef0 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,8 @@ ability to mount an immune response to specific epitopes.
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
 
+Source code is available at [Vaccitech/HLAfreq](https://github.com/Vaccitech/HLAfreq).
+
 ## Details
 Estimates are combined by modelling allele frequency as a 
 Dirichlet distribution which defines the probability of drawing each
@@ -101,8 +103,12 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 
 ## Docs
 For help on specific functions view the docstring, `help(function_name)`.
-Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/docs/index.html)
-created with pdoc3 with `pdoc -d google -o docs/ HLAfreq`.
+Full documentation API at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+Run `pdoc -d google -o docs/ HLAfreq` to generate the
+documentation in `./docs`.
+<!-- Documentation generated by pdoc should not be commited
+as it is auto generated by a github action. -->
+
 
 <!-- ## Developer notes
 # Install in dev mode
@@ -111,11 +117,12 @@ pip install -e .
 
 Update version in setup.py
 
-Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
-Or html documentation with:
-`pdoc -d google -o docs/ HLAfreq`
+Update documentation with: `pdoc -d google -o docs/ HLAfreq`.
+Note that github actions will automatically run this when pushed
+to `main` branch.
 
-Run tests `pytest` 
+Run tests `pytest`
+Or allow nox to do it `nox`.
 
 # Clear old build info
 rm -rf build dist src/*.egg-info 
diff --git a/docs/README.md b/docs/README.md
new file mode 100644
index 0000000..530ff0e
--- /dev/null
+++ b/docs/README.md
@@ -0,0 +1,7 @@
+# Documentation
+`HLAfreq`'s documentation is hosted on a github-page [here](
+https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+
+## Build instructions
+Run `pdoc -d google -o docs/ HLAfreq` to generate the
+documentation here.
\ No newline at end of file

From d1af3c279b95eafa66dce3c77edc84441312f239 Mon Sep 17 00:00:00 2001
From: DAWells <49305334+DAWells@users.noreply.github.com>
Date: Wed, 3 Jul 2024 10:03:57 +0100
Subject: [PATCH 131/192] Create python-package-conda.yml

Github action to run pytest in conda in with multiple python versions
---
 .github/workflows/python-package-conda.yml | 36 ++++++++++++++++++++++
 1 file changed, 36 insertions(+)
 create mode 100644 .github/workflows/python-package-conda.yml

diff --git a/.github/workflows/python-package-conda.yml b/.github/workflows/python-package-conda.yml
new file mode 100644
index 0000000..55732e8
--- /dev/null
+++ b/.github/workflows/python-package-conda.yml
@@ -0,0 +1,36 @@
+name: Python Package using Conda
+
+on: [push]
+
+jobs:
+  build-linux:
+    runs-on: ubuntu-latest
+    strategy:
+      max-parallel: 5
+      matrix:
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Add conda to system path
+      run: |
+        # $CONDA is an environment variable pointing to the root of the miniconda directory
+        echo $CONDA/bin >> $GITHUB_PATH
+    - name: Install dependencies
+      run: |
+        conda env update --file environment.yml --name base
+    - name: Lint with flake8
+      run: |
+        conda install flake8
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+    - name: Test with pytest
+      run: |
+        conda install pytest
+        pytest

From d8a2a169c6485121b82715a5435a932afc2fd109 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 10:08:49 +0100
Subject: [PATCH 132/192] Github action to test on multiple python versions
 without conda

---
 ...-package-conda.yml => python-package.yaml} | 26 +++++++++++--------
 1 file changed, 15 insertions(+), 11 deletions(-)
 rename .github/workflows/{python-package-conda.yml => python-package.yaml} (60%)

diff --git a/.github/workflows/python-package-conda.yml b/.github/workflows/python-package.yaml
similarity index 60%
rename from .github/workflows/python-package-conda.yml
rename to .github/workflows/python-package.yaml
index 55732e8..a243cfe 100644
--- a/.github/workflows/python-package-conda.yml
+++ b/.github/workflows/python-package.yaml
@@ -1,12 +1,20 @@
-name: Python Package using Conda
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
 
-on: [push]
+name: Python package
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
 
 jobs:
-  build-linux:
+  build:
+
     runs-on: ubuntu-latest
     strategy:
-      max-parallel: 5
+      fail-fast: false
       matrix:
         python-version: ["3.8", "3.9", "3.10", "3.11"]
 
@@ -16,21 +24,17 @@ jobs:
       uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
-    - name: Add conda to system path
-      run: |
-        # $CONDA is an environment variable pointing to the root of the miniconda directory
-        echo $CONDA/bin >> $GITHUB_PATH
     - name: Install dependencies
       run: |
-        conda env update --file environment.yml --name base
+        python -m pip install --upgrade pip
+        python -m pip install flake8 pytest
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Lint with flake8
       run: |
-        conda install flake8
         # stop the build if there are Python syntax errors or undefined names
         flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Test with pytest
       run: |
-        conda install pytest
         pytest

From a888ba9fc24d75efd200aabf19b47f8d40c0048d Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 10:14:03 +0100
Subject: [PATCH 133/192] Install HLAfreq before testing

---
 .github/workflows/python-package.yaml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index a243cfe..b294a7c 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -29,6 +29,9 @@ jobs:
         python -m pip install --upgrade pip
         python -m pip install flake8 pytest
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Install HLAfreq
+      run: |
+        pip install .
     - name: Lint with flake8
       run: |
         # stop the build if there are Python syntax errors or undefined names

From db27fe05a1c0f8eb980318aac9807818fe4de89a Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 10:40:59 +0100
Subject: [PATCH 134/192] Remove `build/` and `dist/` from version control

---
 dist/HLAfreq-0.0.2-py3-none-any.whl | Bin 19365 -> 0 bytes
 dist/HLAfreq-0.0.2.tar.gz           | Bin 20873 -> 0 bytes
 2 files changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 dist/HLAfreq-0.0.2-py3-none-any.whl
 delete mode 100644 dist/HLAfreq-0.0.2.tar.gz

diff --git a/dist/HLAfreq-0.0.2-py3-none-any.whl b/dist/HLAfreq-0.0.2-py3-none-any.whl
deleted file mode 100644
index e1cae47d7c175391f6f5536a47647621b79ebdea..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From 69e1b42fe7e109688ee1a4faa60571ba68208878 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:08:27 +0100
Subject: [PATCH 135/192] Reformat doc strings to fit line length and spacing

---
 src/HLAfreq/HLAfreq.py      | 187 +++++++++++++++++++++++++-----------
 src/HLAfreq/HLAfreq_data.py |   1 +
 src/HLAfreq/HLAfreq_pymc.py |  35 ++++---
 src/HLAfreq/__init__.py     |   1 +
 4 files changed, 155 insertions(+), 69 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index aef77cf..d238427 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -1,4 +1,6 @@
 """
+Download and combine HLA allele frequencies from multiple datasets.
+
 Download allele frequency data from
 [allelefrequencies.net](www.allelefrequencies.net). Allele
 frequencies from different populations can be combined to
@@ -33,21 +35,45 @@ def makeURL(
     sample_size="",
     sample_size_pattern="",
 ):
-    """Create URL for search of allele frequency net database. All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+    """Create URL for search of allele frequency net database.
+
+    All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+
     Args:
         country (str, optional): Country name to retrieve records from. Defaults to "".
-        standard (str, optional): Filter study quality standard to this or higher. {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
+        standard (str, optional): Filter study quality standard to this or higher.
+            {'g', 's', 'a'} Gold, silver, all. Defaults to 's'.
         locus (str, optional): The locus to return allele data for. Defaults to "".
-        resolution_pattern (str, optional): Resolution comparitor {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Filter created using `resolution` and `resolution_pattern`. Defaults to "bigger_equal_than".
-        resolution (int, optional): Number of fields of resolution of allele. Filter created using `resolution` and `resolution_pattern`. Defaults to 2.
-        region (str, optional): Filter to geographic region. {Asia, Australia, Eastern Europe, ...}. All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to "".
-        ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}. All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp). Defaults to "".
-        study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor", "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients", "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
-        dataset_source (str, optional): Source of data. {"Literature", "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
-        sample_year (int, optional): Sample year to compare to. Filter created using sample_year and sample_year_pattern. Defaults to "".
-        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter created using sample_year and sample_year_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
-        sample_size (int, optional): Sample size to compare to. Filter created using sample_size and sample_size_pattern. Defaults to "".
-        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter created using sample_size and sample_size_pattern. {'equal', 'different', 'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}. Defaults to "".
+        resolution_pattern (str, optional): Resolution comparitor {'equal', 'different',
+            'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}.
+            Filter created using `resolution` and `resolution_pattern`.
+            Defaults to "bigger_equal_than".
+        resolution (int, optional): Number of fields of resolution of allele. Filter
+            created using `resolution` and `resolution_pattern`. Defaults to 2.
+        region (str, optional): Filter to geographic region. {Asia, Australia,
+            Eastern Europe, ...}.
+            All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            Defaults to "".
+        ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}.
+            All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            Defaults to "".
+        study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor",
+            "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients",
+            "Other", "Solid+Organd+Unrelated+Donors", "Stem+cell+donors"}. Defaults to "".
+        dataset_source (str, optional): Source of data. {"Literature",
+            "Proceedings+of+IHWs", "Unpublished"}. Defaults to "".
+        sample_year (int, optional): Sample year to compare to. Filter created using
+            sample_year and sample_year_pattern. Defaults to "".
+        sample_year_pattern (str, optional): Pattern to compare sample year to. Filter
+            created using sample_year and sample_year_pattern. {'equal', 'different',
+            'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}.
+            Defaults to "".
+        sample_size (int, optional): Sample size to compare to. Filter created using
+            sample_size and sample_size_pattern. Defaults to "".
+        sample_size_pattern (str, optional): Pattern to compare sample size to. Filter
+            created using sample_size and sample_size_pattern. {'equal', 'different',
+            'less_than', 'bigger_than', 'less_equal_than', 'bigger_equal_than'}.
+            Defaults to "".
 
     Returns:
         str: URL to search allelefrequencies.net
@@ -156,13 +182,17 @@ def Npages(bs):
 
 def formatAF(AFtab, ignoreG=True):
     """Format allele frequency table.
+
     Convert sample_size and allele_freq to numeric data type.
     Removes commas from sample size. Removes "(*)" from allele frequency if
-    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata by default.
+    `ignoreG` is `True`. `formatAF()` is used internally by combineAF and getAFdata
+    by default.
 
     Args:
-        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net using `getAFdata()`.
-        ignoreG (bool, optional): Treat G group alleles as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+        AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net
+            using `getAFdata()`.
+        ignoreG (bool, optional): Treat G group alleles as normal.
+            See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
 
     Returns:
         pd.DataFrame: The formatted allele frequency data.
@@ -184,7 +214,8 @@ def getAFdata(base_url, format=True, ignoreG=True):
     Args:
         base_url (str): URL for base search.
         format (bool): Format the downloaded data using `formatAF()`.
-        ignoreG (bool): treat allele G groups as normal. See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+        ignoreG (bool): treat allele G groups as normal.
+            See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
 
     Returns:
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
@@ -218,8 +249,10 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
 
     Args:
         AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete.
+            Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported.
+            Defaults to 1.1.
         datasetID (str): Unique identifier column for study
     """
     poplocs = AFtab.groupby([datasetID, "loci"]).allele_freq.sum()
@@ -236,13 +269,17 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
 
 
 def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
-    """Returns only complete studies. Studies are only dropped if their population and loci are in noncomplete together.
+    """Returns only complete studies.
+    
+    Studies are only dropped if their population and loci are in noncomplete together.
     This prevents throwing away data if another loci in the population is incomplete
 
     Args:
         AFtab (pd.DataFrame): Dataframe containing multiple studies
-        llimit (float, optional): Lower allele_freq sum limit that counts as complete. Defaults to 0.95.
-        ulimit (float, optional): Upper allele_freq sum limit that will not be reported. Defaults to 1.1.
+        llimit (float, optional): Lower allele_freq sum limit that counts as complete.
+            Defaults to 0.95.
+        ulimit (float, optional): Upper allele_freq sum limit that will not be reported.
+            Defaults to 1.1.
         datasetID (str): Unique identifier column for study. Defaults to 'population'.
 
     Returns:
@@ -282,12 +319,13 @@ def check_resolution(AFtab):
 
 
 def decrease_resolution(AFtab, newres, datasetID="population"):
-    """Decrease allele resolution to a specified value so all alleles have the same resolution.
+    """Decrease allele resolution so all alleles have the same resolution.
 
     Args:
         AFtab (pd.DataFrame): Allele frequency data.
         newres (int): The desired number of fields for resolution.
-        datasetID (str, optional): Column to use as stud identifier. Defaults to 'population'.
+        datasetID (str, optional): Column to use as stud identifier.
+            Defaults to 'population'.
 
     Returns:
         pd.DataFrame: Allele frequency data with all alleles of requested resolution.
@@ -402,31 +440,45 @@ def combineAF(
     resolution=True,
     unique=True,
 ):
-    """Combine allele frequencies from multiple studies. `datasetID` is the unique identifier for studies to combine.
-    Allele frequencies combined using a Dirichlet distribution where each study's contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
-    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is set it is not doubled.
-    The total concentration parameter of the Dirichlet distribution is the contributions from all studies plus the prior `alpha`.
-    If `alpha` is not set the prior defaults to 1 observation of each allele.
+    """Combine allele frequencies from multiple studies.
+    
+    `datasetID` is the unique identifier for studies to combine.
+    Allele frequencies combined using a Dirichlet distribution where each study's
+    contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
+    Sample size is doubled to get `2n` due to diploidy. If an alternative `weights` is
+    set it is not doubled. The total concentration parameter of the Dirichlet distribution
+    is the contributions from all studies plus the prior `alpha`. If `alpha` is not set
+    the prior defaults to 1 observation of each allele.
 
     Args:
         AFtab (pd.DataFrame): Table of Allele frequency data
-        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        weights (str, optional): Column to be weighted by allele frequency to generate
+            concentration parameter of Dirichlet distribution. Defaults to '2n'.
         alpha (list, optional): Prior to use for Dirichlet distribution. Defaults to [].
-        datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
+        datasetID (str, optional): Unique identifier column for study. Defaults to
+            'population'.
         format (bool, optional): Run `formatAF()`. Defaults to True.
-        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`. Defaults to True.
-        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is important to ensure combined allele frequencies sum to 1. See `add_unmeasured()`. Defaults to True.
-        complete (bool, optional): Check study completeness. Uses default values for `incomplete_studies()`. If you are happy with your study completeness can be switched off with False. Defaults to True.
-        resolution (bool, optional): Check that all alleles have the same resolution, see `check_resolution()`. Defaults to True.
-        unique (bool, optional): Check that each allele appears no more than once per study. See `alleles_unique_in_study()`. Defaults to True.
+        ignoreG (bool, optional): Treat allele G groups as normal, see `formatAF()`.
+            Defaults to True.
+        add_unmeasured (bool, optional): Add unmeasured alleles to each study. This is
+            important to ensure combined allele frequencies sum to 1. See
+            `add_unmeasured()`. Defaults to True.
+        complete (bool, optional): Check study completeness. Uses default values for
+            `incomplete_studies()`. If you are happy with your study completeness can
+            be switched off with False. Defaults to True.
+        resolution (bool, optional): Check that all alleles have the same resolution,
+            see `check_resolution()`. Defaults to True.
+        unique (bool, optional): Check that each allele appears no more than once per
+            study. See `alleles_unique_in_study()`. Defaults to True.
 
     Returns:
         pd.DataFrame: Allele frequencies after combining estimates from all studies.
-        *allele_freq* is the combined frequency estimate from the Dirichlet mean where the concentration is `alpha` + `c`.
-        *alpha* is the prior used for the Dirichlet distribution.
-        *c* is the observations used for the Dirichlet distribution.
-        *sample_size* is the total sample size of all combined studies.
-        *wav* is the weighted average.
+            *allele_freq* is the combined frequency estimate from the Dirichlet mean
+            where the concentration is `alpha` + `c`.
+            *alpha* is the prior used for the Dirichlet distribution.
+            *c* is the observations used for the Dirichlet distribution.
+            *sample_size* is the total sample size of all combined studies.
+            *wav* is the weighted average.
     """
     df = AFtab.copy()
     single_loci(df)
@@ -437,7 +489,7 @@ def combineAF(
     if complete:
         assert incomplete_studies(
             df, datasetID=datasetID
-        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Checkincomplete_studies(AFtab)"
     if resolution:
         assert check_resolution(
             df
@@ -501,11 +553,15 @@ def single_loci(AFtab):
 
 
 def alleles_unique_in_study(AFtab, datasetID="population"):
-    """Are all alleles unique in each study? Checks that no alleles are reported more than once in a single study. Study is defined by `datasetID`.
+    """Are all alleles unique in each study?
+    
+    Checks that no alleles are reported more than once in a single study.
+    Study is defined by `datasetID`.
 
     Args:
         AFtab (pd.DataFrame): Allele frequency data
-        datasetID (str, optional): Unique identifier column to define study. Defaults to 'population'.
+        datasetID (str, optional): Unique identifier column to define study.
+            Defaults to 'population'.
 
     Returns:
         bool: `True` on if no alleles occur more than once in any study, otherwise `False`.
@@ -538,8 +594,7 @@ def id_duplicated_allele(grouped):
 
 
 def population_coverage(p):
-    """Calculate the proportion of people with at least 1 copy of this allele
-        assuming HWE.
+    """Proportion of people with at least 1 copy of this allele assuming HWE.
 
     Args:
         p (float): Allele frequency
@@ -554,13 +609,18 @@ def population_coverage(p):
 
 
 def betaAB(alpha):
-    """Given the alpha vector defining a Dirichlet distribution calculate the a b values for all composite beta distributions.
+    """Calculate `a` `b` values for all composite beta distributions.
+    
+    Given the `alpha` vector defining a Dirichlet distribution calculate the `a` `b` values
+    for all composite beta distributions.
 
     Args:
-        alpha (list): Values defining a Dirichlet distribution. This will be the prior (for a naive distribution) or the prior + caf.c for a posterior distribution.
+        alpha (list): Values defining a Dirichlet distribution. This will be the prior
+            (for a naive distribution) or the prior + caf.c for a posterior distribution.
 
     Returns:
-        list: List of a b values defining beta values, i.e. for each allele it is the number of times it was and wasn't observed.
+        list: List of `a` `b` values defining beta values, i.e. for each allele it is
+            the number of times it was and wasn't observed.
     """
     ab = [(a, sum(alpha) - a) for a in alpha]
     return ab
@@ -609,7 +669,8 @@ def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
     Args:
         concentration (list): Vector of the prior Dirichlet concentration values.
         ncol (int, optional): Number of columns. Defaults to 2.
-        labels (list, optional): Labels for elements of concentration in the same order. Defaults to "".
+        labels (list, optional): Labels for elements of concentration in the same
+            order. Defaults to "".
     """
     ab = betaAB(concentration)
     pline = np.linspace(0, 1, psteps)
@@ -645,19 +706,29 @@ def plotAF(
     hdi=pd.DataFrame(),
     compound_mean=pd.DataFrame(),
 ):
-    """Plot combined allele frequencies, individual allele frequencies,
+    """Plot allele frequency results from `HLAfreq`.
+
+    Plot combined allele frequencies, individual allele frequencies,
     and credible intervals on combined allele frequency estimates.
     Credible interval is only plotted if a value is given for `hdi`.
-    The plotted Credible interval is whatever was passed to HLAfreq_pymc.AFhdi() when calculating hdi.
+    The plotted Credible interval is whatever was passed to HLAfreq_pymc.AFhdi()
+    when calculating hdi.
 
     Args:
-        caf (pd.DataFrame, optional): Combined allele frequency estimates from HLAfreq.combineAF. Defaults to pd.DataFrame().
-        AFtab (pd.DataFrame, optional): Table of allele frequency data. Defaults to pd.DataFrame().
-        cols (list, optional): List of colours to use for each individual dataset. Defaults to list(mcolors.TABLEAU_COLORS.keys()).
-        datasetID (str, optional): Column used to define separate datasets. Defaults to "population".
-        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-        hdi (pd.DataFrame, optional): The high density interval object to plot credible intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
-        compound_mean (pd.DataFrame, optional): The high density interval object to plot post_mean. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
+        caf (pd.DataFrame, optional): Combined allele frequency estimates from
+            HLAfreq.combineAF. Defaults to pd.DataFrame().
+        AFtab (pd.DataFrame, optional): Table of allele frequency data. Defaults
+            to pd.DataFrame().
+        cols (list, optional): List of colours to use for each individual dataset.
+            Defaults to list(mcolors.TABLEAU_COLORS.keys()).
+        datasetID (str, optional): Column used to define separate datasets. Defaults
+            to "population".
+        weights (str, optional): Column to be weighted by allele frequency to generate
+            concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        hdi (pd.DataFrame, optional): The high density interval object to plot credible
+            intervals. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
+        compound_mean (pd.DataFrame, optional): The high density interval object to plot
+            post_mean. Produced by HLAfreq.HLA_pymc.AFhdi(). Defaults to pd.DataFrame().
     """
     # Plot allele frequency for each dataset
     if not AFtab.empty:
diff --git a/src/HLAfreq/HLAfreq_data.py b/src/HLAfreq/HLAfreq_data.py
index a67224d..9fc0399 100644
--- a/src/HLAfreq/HLAfreq_data.py
+++ b/src/HLAfreq/HLAfreq_data.py
@@ -1,6 +1,7 @@
 """
 Data loaders
 """
+
 import pkg_resources
 import pandas as pd
 
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index a1e7b46..708cc26 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -97,7 +97,9 @@ def AFhdi(
     compare_models=True,
 ):
     """Calculate mean and high posterior density interval on combined allele frequency.
-    Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
+
+    Fits a Marginalized Dirichlet-Multinomial Model in PyMc as described
+    [here](https://docs.pymc.io/en/v3/pymc-examples/examples/mixture_models/dirichlet_mixture_of_multinomials.html).
 
     In brief, the global allele frequency is modelled as a Dirichlet distribution,
     and each population (defined by `datasetID`) is a Dirichlet distribution draw from
@@ -110,13 +112,21 @@ def AFhdi(
 
     Args:
         AFtab (pd.DataFrame): Table of allele frequency data
-        weights (str, optional): Column to be weighted by allele frequency to generate concentration parameter of Dirichlet distribution. Defaults to '2n'.
-        datasetID (str, optional): Unique identifier column for study. Defaults to 'population'.
-        credible_interval (float, optional): The size of the credible interval requested. Defaults to 0.95.
-        prior (list, optional): Prior vector for global allele frequency. Order should match alphabetical alleles, i.e. the first value is used for the alphabetically first allele.
-        conc_mu (float, optional): Mean to parameterise lognormal distribution of `conc` prior. Defaults to 1.
-        conc_sigma (float, optional): Standard deviation to parameterise lognormal distribution of `conc` prior. Defaults to 1.
-        compare_models (bool, optional): Check that default estimated allele_freq is within compound model estimated credible intervals. Defaults to True.
+        weights (str, optional): Column to be weighted by allele frequency to generate
+            concentration parameter of Dirichlet distribution. Defaults to '2n'.
+        datasetID (str, optional): Unique identifier column for study. Defaults to
+            'population'.
+        credible_interval (float, optional): The size of the credible interval requested.
+            Defaults to 0.95.
+        prior (list, optional): Prior vector for global allele frequency. Order should
+            match alphabetical alleles, i.e. the first value is used for the alphabetically
+            first allele.
+        conc_mu (float, optional): Mean to parameterise lognormal distribution of `conc`
+            prior. Defaults to 1.
+        conc_sigma (float, optional): Standard deviation to parameterise lognormal
+            distribution of `conc` prior. Defaults to 1.
+        compare_models (bool, optional): Check that default estimated allele_freq is
+            within compound model estimated credible intervals. Defaults to True.
 
     Returns:
         np.array: Pairs of high density interval limits, allele name, and posterior mean.
@@ -144,7 +154,8 @@ def compare_estimates(AFtab, hdi, datasetID):
 
     Args:
         AFtab (pd.DataFrame): Table of allele frequency data
-        hdi (np.array): Pairs of high density interval limits, allele name, and posterior mean from compound model.
+        hdi (np.array): Pairs of high density interval limits, allele name,
+            and posterior mean from compound model.
         datasetID (str, optional): Unique identifier column for study.
     """
 
@@ -154,9 +165,11 @@ def compare_estimates(AFtab, hdi, datasetID):
     if mask.sum() > 0:
         print()
         print(
-            "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!"
+            "WARNING: The default allele frequency estimate is outside of the CI"
+            "estimated by the compound method for some alleles!"
         )
         print(
-            "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb"
+            "There are several possible reasons, see the credible intervals example:"
+            "https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb"
         )
         print("If you have set `credible_interval` to < 0.95, this may be a non-issue.")
diff --git a/src/HLAfreq/__init__.py b/src/HLAfreq/__init__.py
index 0892506..d7149ce 100644
--- a/src/HLAfreq/__init__.py
+++ b/src/HLAfreq/__init__.py
@@ -1,4 +1,5 @@
 """
 .. include:: ../../README.md
 """
+
 from .HLAfreq import *

From 3c4c42d66e51c4e89f469a6bdbeea0fdf9da6ecd Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:08:47 +0100
Subject: [PATCH 136/192] github action test guide to readme

---
 README.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index bdd6ef0..1c37ac8 100644
--- a/README.md
+++ b/README.md
@@ -122,7 +122,8 @@ Note that github actions will automatically run this when pushed
 to `main` branch.
 
 Run tests `pytest`
-Or allow nox to do it `nox`.
+Or allow nox to do it `nox`. Nox will also run linting.
+On push github actions will run linting and pytest
 
 # Clear old build info
 rm -rf build dist src/*.egg-info 

From e2a93e4b81f62d0ed473f26bec08796330a5dc02 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:09:04 +0100
Subject: [PATCH 137/192] .gitignore build/ and dist/

---
 .gitignore | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index c473d30..0c68b5e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,4 +2,6 @@ data/
 writeup/
 *__pycache__/
 *.code-workspace
-envs/.venv
\ No newline at end of file
+envs/.venv
+build/
+dist/
\ No newline at end of file

From d8c89ac04cf9a36e4d09977d4e7a914fd068f051 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:09:34 +0100
Subject: [PATCH 138/192] Update version number 0.0.3.dev1

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 23c93c9..2bece8d 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.3",
+    version="0.0.3.dev1",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"

From 4dd41352e32888a3cd560ae659a517d473a7ae5f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:45:39 +0100
Subject: [PATCH 139/192] flake8 linting

Mostly white space empty lines,
and open excepts
---
 src/HLAfreq/HLAfreq.py      | 29 +++++++++++++++++------------
 src/HLAfreq/HLAfreq_pymc.py |  2 +-
 2 files changed, 18 insertions(+), 13 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index d238427..f694eff 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -15,8 +15,6 @@
 import matplotlib.pyplot as plt
 import math
 import scipy as sp
-import logging
-import warnings
 import matplotlib.colors as mcolors
 
 
@@ -167,7 +165,7 @@ def Npages(bs):
     navtab = bs.find("div", {"id": "divGenNavig"}).find("table", {"class": "table10"})
     assert (
         navtab
-    ), f"navtab does not evaluate to True. Check URL returns results in web browser."
+    ), "navtab does not evaluate to True. Check URL returns results in web browser."
     # Get cell with ' of ' in
     pagesOfN = [
         td.get_text(strip=True) for td in navtab.find_all("td") if " of " in td.text
@@ -239,7 +237,7 @@ def getAFdata(base_url, format=True, ignoreG=True):
     if format:
         try:
             tabs = formatAF(tabs, ignoreG)
-        except:
+        except AttributeError:
             print("Formatting failed, non-numeric datatypes may remain.")
     return tabs
 
@@ -270,7 +268,7 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
 
 def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
     """Returns only complete studies.
-    
+
     Studies are only dropped if their population and loci are in noncomplete together.
     This prevents throwing away data if another loci in the population is incomplete
 
@@ -314,7 +312,7 @@ def check_resolution(AFtab):
     pass_check = len(resVC) == 1
     if not pass_check:
         print(resVC)
-        print(f"Multiple resolutions in AFtab. Fix with decrease_resolution()")
+        print("Multiple resolutions in AFtab. Fix with decrease_resolution()")
     return pass_check
 
 
@@ -441,7 +439,7 @@ def combineAF(
     unique=True,
 ):
     """Combine allele frequencies from multiple studies.
-    
+
     `datasetID` is the unique identifier for studies to combine.
     Allele frequencies combined using a Dirichlet distribution where each study's
     contribution to the concentration parameter is $2 * sample_size * allele_frequency$.
@@ -500,7 +498,7 @@ def combineAF(
         df = unmeasured_alleles(df, datasetID)
     try:
         df["2n"] = df.sample_size * 2
-    except:
+    except AttributeError:
         print("column '2n' could not be created")
     df["c"] = df.allele_freq * df[weights]
     grouped = df.groupby("allele", sort=True)
@@ -549,12 +547,12 @@ def single_loci(AFtab):
     Args:
         AFtab (pd.DataFrame): Allele frequency data
     """
-    assert len(AFtab.loci.unique()) == 1, f"'AFtab' must conatain only 1 loci"
+    assert len(AFtab.loci.unique()) == 1, "'AFtab' must conatain only 1 loci"
 
 
 def alleles_unique_in_study(AFtab, datasetID="population"):
     """Are all alleles unique in each study?
-    
+
     Checks that no alleles are reported more than once in a single study.
     Study is defined by `datasetID`.
 
@@ -610,7 +608,7 @@ def population_coverage(p):
 
 def betaAB(alpha):
     """Calculate `a` `b` values for all composite beta distributions.
-    
+
     Given the `alpha` vector defining a Dirichlet distribution calculate the `a` `b` values
     for all composite beta distributions.
 
@@ -760,7 +758,14 @@ def plotAF(
         # assert not AFtab.empty, "AFtab is needed to calculate credible interval"
         # from HLAfreq import HLAfreq_pymc as HLAhdi
         # print("Fitting model with PyMC, make take a few seconds")
-        # hdi = HLAhdi.AFhdi(AFtab=AFtab, weights=weights, datasetID=datasetID, credible_interval=credible_interval, conc_mu=conc_mu, conc_sigma=conc_sigma)
+        # hdi = HLAhdi.AFhdi(
+        #     AFtab=AFtab,
+        #     weights=weights,
+        #     datasetID=datasetID,
+        #     credible_interval=credible_interval,
+        #     conc_mu=conc_mu,
+        #     conc_sigma=conc_sigma
+        # )
         for interval in hdi.iterrows():
             # .iterrows returns a index and data as a tuple for each row
             plt.hlines(
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index 708cc26..a75697d 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -42,7 +42,7 @@ def _make_c_array(
         df = HLAfreq.unmeasured_alleles(df, datasetID)
     try:
         df["2n"] = df.sample_size * 2
-    except:
+    except AttributeError:
         print("column '2n' could not be created")
     df["c"] = df.allele_freq * df[weights]
 

From ac954237c27bc1804d3fbc76dd3afb9d5b8f51cd Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 11:54:23 +0100
Subject: [PATCH 140/192] github doc page only runs on pushes to main, not docs
 branch

---
 .github/workflows/docs.yaml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index d96081f..23efd49 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -5,7 +5,6 @@ on:
   push:
     branches:
       - main
-      - docs
     # Alternative: only build for tags.
     # tags:
     #   - '*'

From f98fbf9510ca4aa2f994b6bd6262d0223af11f31 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 14:24:49 +0100
Subject: [PATCH 141/192] Detail submodules in readme

Makes it easier to get to function docs
---
 README.md | 20 ++++++++++++++------
 1 file changed, 14 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index 1c37ac8..6661bbf 100644
--- a/README.md
+++ b/README.md
@@ -102,8 +102,16 @@ For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccite
 - [Credible intervals](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb)
 
 ## Docs
+Full documentation at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+API documentation for functions are under the submodules on the left.
+- `HLAfreq.HLAfreq` documents most functions, specifically download and combine
+allele data.
+- `HLAfreq.HLAfreq_pymc` is functions using pymc to acurately estimate credible intervals on allele frequency estimates.
+- `HLAfreq.HLAfreq_data` contains data loaders to get countries available on
+allelefrequencies.net.
+
 For help on specific functions view the docstring, `help(function_name)`.
-Full documentation API at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+
 Run `pdoc -d google -o docs/ HLAfreq` to generate the
 documentation in `./docs`.
 <!-- Documentation generated by pdoc should not be commited
@@ -111,7 +119,7 @@ as it is auto generated by a github action. -->
 
 
 <!-- ## Developer notes
-# Install in dev mode
+Install in dev mode
 pip install -e HLAfreq
 pip install -e .
 
@@ -125,20 +133,20 @@ Run tests `pytest`
 Or allow nox to do it `nox`. Nox will also run linting.
 On push github actions will run linting and pytest
 
-# Clear old build info
+Clear old build info
 rm -rf build dist src/*.egg-info 
 
 Build with `python -m build`.
 
 twine check dist/*
 
-# Upload to test pypi
+Upload to test pypi
 twine upload --repository testpypi dist/*
 
-# Install from test pypi
+Install from test pypi
 python3 -m pip install --extra-index-url https://test.pypi.org/simple/ HLAfreq
 
-# Upload to pypi
+Upload to pypi
 twine upload dist/*
 -->
 

From 2c629c5bba49dad6def07239be81de21f5b53c94 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 14:25:44 +0100
Subject: [PATCH 142/192] update nox and github action testing to 3.10-3.12 as
 recommended https://scientific-python.org/specs/spec-0000/

---
 .github/workflows/python-package.yaml | 2 +-
 noxfile.py                            | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index b294a7c..11c7300 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v4
diff --git a/noxfile.py b/noxfile.py
index 5823ff7..b338db0 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -9,7 +9,7 @@ def lint(session):
     session.run("flake8", "src", "--count", "--exit-zero", "--max-complexity=10", "--max-line-length=127", "--statistics")
 
 
-@nox.session(python=["3.8", "3.9", "3.10"])
+@nox.session(python=["3.10", "3.11", "3.12"])
 def tests(session):
     session.install("pytest")
     session.install(".")

From 210b0ea5be6258893842560db40dd15740925a59 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 14:27:51 +0100
Subject: [PATCH 143/192] Test AFhdi runs without complaint

---
 tests/test_single_country_caf.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index b8661f0..5f1c8b7 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -1,12 +1,11 @@
-"""
-Tests on a toy allele frequency data set
+"""Tests on a toy allele frequency data set
 
 Tests dropping incomplete studies, merging different resolution
 alleles, and combing allele frequency estimates.
 """
 import pytest
 import HLAfreq
-
+from HLAfreq import HLAfreq_pymc as HLAhdi
 import pandas as pd
 from scipy.stats import dirichlet
 
@@ -65,3 +64,8 @@ def test_resolution_decreased_correctly():
 
 def test_combined_allele_freq():
     assert all(caf.allele_freq == dirichlet([8, 12, 13]).mean())
+
+
+def test_hdi():
+    hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
+    all(hdi.columns == ["lo", "hi", "allele", "post_mean"])

From d92b9f4f73a34f205f28f17d1d74b97a12636e53 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 3 Jul 2024 14:39:34 +0100
Subject: [PATCH 144/192] Simplify naming of scripts to reproduce paper results

---
 examples/paper/entropy_map.py                 |  81 -----------
 examples/paper/globalPCA2.py                  | 105 ---------------
 ...se_case.py => reproduce_paper_results1.py} |   3 +
 examples/paper/reproduce_paper_results2.py    | 127 ++++++++++++++++++
 ...obalPCA.py => reproduce_paper_results3.py} |  99 +++++++++++++-
 5 files changed, 224 insertions(+), 191 deletions(-)
 delete mode 100644 examples/paper/entropy_map.py
 delete mode 100644 examples/paper/globalPCA2.py
 rename examples/paper/{basic_use_case.py => reproduce_paper_results1.py} (87%)
 create mode 100644 examples/paper/reproduce_paper_results2.py
 rename examples/paper/{globalPCA.py => reproduce_paper_results3.py} (51%)

diff --git a/examples/paper/entropy_map.py b/examples/paper/entropy_map.py
deleted file mode 100644
index 55c69f9..0000000
--- a/examples/paper/entropy_map.py
+++ /dev/null
@@ -1,81 +0,0 @@
-"""
-Entropy of country average allele frequencies
-"""
-
-# use maps conda env
-
-import code.HLAfreq as HLAfreq
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import geopandas as gpd
-import geoplot as gplt
-from scipy.stats import dirichlet
-
-regions = pd.read_csv("data/example/countries.csv")
-regions.index = regions.Country
-regions['country'] = regions.Country.str.replace("+"," ")
-
-regions['entropy'] = np.nan
-regions['total_sample_size'] = np.nan
-regions['populations'] = np.nan
-
-countries = regions.Country.tolist()
-
-for country in countries:
-    print(country)
-    try:
-        df = pd.read_csv("data/example/globalPCA/%s_raw.csv" %country)
-        df = HLAfreq.only_complete(df)
-        df = HLAfreq.decrease_resolution(df, 2)
-        caf = HLAfreq.combineAF(df)
-        # Recreate the Dirichlet distribution
-        alpha = HLAfreq.default_prior(len(caf.allele))
-        dd = dirichlet(alpha + caf.c)
-        # Calculate entropy
-        regions.loc[country, 'entropy'] = dd.entropy()
-        # How many populations in the country?
-        regions.loc[country, 'populations'] = len(df.population.unique())
-        # Calculate total sample size
-        regions.loc[country, 'total_sample_size'] = caf.sample_size.unique()[0]
-    except:
-        pass
-
-# Drop regions without data
-regions = regions.dropna(subset=['entropy'])
-
-######## World plot
-world = gpd.read_file(
-    gpd.datasets.get_path('naturalearth_lowres')
-)
-
-# Not all countries are in both datasets,
-# Some of this is due to alternative naming
-# Will require manual editting.
-
-# Regions not in world
-regions[~regions.country.isin(world.name)].country
-# world not in regions
-world.name[~world.name.isin(regions.country)]
-
-# Change world names to match region country
-# key becomes value
-renames={
-"United States of America":"United States",
-'Bosnia and Herz.': "Bosnia and Herzegovina",
-"Czechia": "Czech Republic",
-}
-
-for key,value in renames.items():
-    world.loc[world.name == key, 'name'] = value
-
-world_regions = pd.merge(world, regions, how="left", left_on="name", right_on="country")
-
-fig, ax = plt.subplots(2,2)
-gplt.choropleth(world_regions, hue="entropy", legend=True, ax=ax[0,0])
-ax[0,0].set_title('Entropy')
-gplt.choropleth(world_regions, hue="populations", legend=True, ax=ax[0,1])
-ax[0,1].set_title('Populations')
-gplt.choropleth(world_regions, hue="total_sample_size", legend=True, ax=ax[1,0])
-ax[1,0].set_title('Total sample size')
-plt.show()
diff --git a/examples/paper/globalPCA2.py b/examples/paper/globalPCA2.py
deleted file mode 100644
index 87d7f29..0000000
--- a/examples/paper/globalPCA2.py
+++ /dev/null
@@ -1,105 +0,0 @@
-"""
-Global PCA
-
-Calculate average AF for ~all countries and perform dimension
-reduction on that data to 2D (PCA, UMAP, t-SNE). Then plot
-those points coloured by geographic area.
-
-For this each country must have an estimate for the same set
-of alleles.
-"""
-
-# Use umap conda env
-
-import numpy as np
-import pandas as pd
-import matplotlib.pyplot as plt
-from sklearn.decomposition import PCA
-import umap
-
-AFeatures = pd.read_csv("data/example/globalPCA/AF_features.csv")
-regions = pd.read_csv("data/example/countries.csv")
-
-# Remove Guinea because it includes data from
-# Guinea-Bissau and Papua New Guinea
-AFeatures = AFeatures[AFeatures.country != "Guinea"]
-
-pca = PCA(n_components=2)
-pca_embedding = pca.fit_transform(AFeatures.loc[:,'A*01:01':].values)
-AFeatures['pca0'] = pca_embedding[:,0]
-AFeatures['pca1'] = pca_embedding[:,1]
-
-# umapper = umap.UMAP(transform_seed=1234)
-# umap_embedding = umapper.fit_transform(AFeatures.loc[:,'A*01:01':].values)
-# AFeatures['umap0'] = umap_embedding[:,0]
-# AFeatures['umap1'] = umap_embedding[:,1]
-
-# Add region to countries
-AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
-
-# Select Venezuela With Prior
-vwp = AFeatures[AFeatures.country == "Venezuela with prior"]
-# Drop countries without largeRegion, this is Venezuela with a prior
-AFeatures = AFeatures.dropna(subset=['largeRegion'])
-
-# plt.style.use('fivethirtyeight')
-
-# Define offset values for each country label
-offset = dict(zip(AFeatures.country, [(0,0)]*AFeatures.shape[0]))
-# Customise offsets
-offset['Zimbabwe'] = (0,5)
-offset['United+States'] = (0,5)
-offset['Georgia'] = (0,5)
-offset['Germany'] = (0,5)
-offset['Italy'] = (0,-5)
-offset['Czech+Republic'] = (0,-4)
-offset['Poland'] = (0,-7)
-offset['France'] = (0,-2)
-offset['Bosnia+and+Herzegovina'] = (0,4)
-offset['Russia'] = (0,-5)
-offset['Ireland'] = (0,-5)
-offset['Netherlands'] = (0,-6)
-offset['Austria'] = (0,-7)
-offset['Romania'] = (0,4)
-offset['Wales'] = (0,-5)
-offset['Cameroon'] = (0,2)
-offset['Ghana'] = (0,-3)
-offset['United+Kingdom'] = (0,-4)
-offset['Sao+Tome+and+Principe'] = (0,-5)
-
-
-regions = AFeatures.largeRegion.unique()
-regions.sort()
-for region in regions:
-    mask = AFeatures.largeRegion == region
-    plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
-    for i in AFeatures[mask].index:
-        # Label each country
-        plt.annotate(
-            AFeatures.loc[i].country.replace("+", " "),
-            AFeatures.loc[i][['pca0','pca1']],
-            offset[AFeatures.loc[i].country],
-            textcoords="offset points",
-            fontsize=8)
-plt.legend()
-# Arrow shows change of Venezuela with prior
-plt.annotate(
-    "",
-    xy=(vwp.pca0, vwp.pca1),
-    xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
-    arrowprops=dict(arrowstyle="->")
-    )
-# Open point to show updated Venezuela
-plt.scatter(vwp.pca0, vwp.pca1, color="tab:blue", facecolors="none")
-plt.xlabel('1st principal component'); plt.ylabel('2nd principal component')
-plt.gcf().set_size_inches(10,10)
-plt.savefig('writeup/globalPCA.png')
-plt.close()
-
-# for region in AFeatures.largeRegion.unique():
-#     mask = AFeatures.largeRegion == region
-#     plt.scatter(AFeatures.umap0[mask], AFeatures.umap1[mask], label=region)
-#     for i in AFeatures[mask].index:
-#         plt.annotate(AFeatures.loc[i].country.replace("+", " "), AFeatures.loc[i][['umap0','umap1']])
-# plt.legend()
-# plt.show()
diff --git a/examples/paper/basic_use_case.py b/examples/paper/reproduce_paper_results1.py
similarity index 87%
rename from examples/paper/basic_use_case.py
rename to examples/paper/reproduce_paper_results1.py
index 90c7956..0aff080 100644
--- a/examples/paper/basic_use_case.py
+++ b/examples/paper/reproduce_paper_results1.py
@@ -2,14 +2,17 @@
 import HLAfreq
 from HLAfreq import HLAfreq_pymc
 
+# Download and plot HLA frequency data
 base_url = HLAfreq.makeURL(country="Mongolia", standard="g", locus="DQB1")
 aftab = HLAfreq.getAFdata(base_url)
 caf = HLAfreq.combineAF(aftab)
 hdi = HLAfreq_pymc.AFhdi(aftab, credible_interval=0.95)
 HLAfreq.plotAF(caf, aftab, hdi=hdi, compound_mean=hdi)
 
+# Calculate and plot cumulative population coverage
 caf = caf.sort_values('allele_freq', ascending=False, ignore_index=True)
 plt.scatter(caf.allele, caf.allele_freq.cumsum().apply(HLAfreq.population_coverage))
 plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
 plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
 plt.tight_layout(); plt.show()
+
diff --git a/examples/paper/reproduce_paper_results2.py b/examples/paper/reproduce_paper_results2.py
new file mode 100644
index 0000000..221c3f2
--- /dev/null
+++ b/examples/paper/reproduce_paper_results2.py
@@ -0,0 +1,127 @@
+"""
+Download HLA data for all countries and calculate
+population coverage of IEDB set of 27 alleles.
+
+Plot population coverage in detail for Indonesia.
+
+Takes ~1hour with data downloads
+"""
+
+import os
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import HLAfreq
+import requests
+
+# Create folder for data
+try:
+    os.makedirs("data/example/population_coverage")
+except FileExistsError:
+    pass
+
+# Population coverage of IEDB 27 alleles
+# The IEDB reference panel
+iedb_ref = ['B*35:01', 'A*30:01', 'A*02:03', 'B*15:01', 'B*57:01', 'A*68:02', 'A*23:01', 'B*53:01', 'A*03:01', 'B*40:01', 'B*44:02', 'B*51:01', 'A*33:01', 'A*01:01', 'A*68:01', 'A*24:02', 'B*07:02', 'B*08:01', 'A*02:06', 'A*26:01', 'A*11:01', 'A*30:02', 'A*31:01', 'B*58:01', 'B*44:03', 'A*32:01', 'A*02:01']
+iedb_refa = [i for i in iedb_ref if "A" in i]
+iedb_refb = [i for i in iedb_ref if "B" in i]
+
+# Download countries in regions as defined on 
+# http://www.allelefrequencies.net/datasets.asp#tag_4
+r = requests.get("https://raw.githubusercontent.com/Vaccitech/HLAfreq/main/data/example/countries.csv")
+with open("data/example/countries.csv", "w") as f:
+    f.write(r.text)
+
+regions = pd.read_csv("data/example/countries.csv")
+countries = regions.Country.tolist()
+
+
+# Download A and B data for all countries to identify 
+# Countries poorly covered by the IEDB reference set
+for locus in ['A', 'B']:
+    # for country in ['Indonesia', 'Philippines']:
+    for country in countries:
+        print(country)
+        try:
+            base_url = HLAfreq.makeURL(country, standard='s', locus=locus)
+            aftab = HLAfreq.getAFdata(base_url)
+            aftab.to_csv(f"data/example/population_coverage/{country}_{locus}_raw.csv", index=False)
+        except:
+            pass
+
+
+iedb_cov = []
+iedb_country = []
+# Load and combine within country data for HLA-A and HLA-B separately
+# Calculate the proportion of each population with no alleles
+# in the IEDB reference set, assuming no linkage disequilibrium
+# between HLA-A and HLA-B
+for country in countries:
+    try:
+        afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
+        afa = HLAfreq.only_complete(afa)
+        afa = HLAfreq.decrease_resolution(afa, 2)
+        cafa = HLAfreq.combineAF(afa)
+        maska = cafa.allele.isin(iedb_ref)
+        p = cafa[maska].allele_freq.sum()
+
+        afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
+        afb = HLAfreq.only_complete(afb)
+        afb = HLAfreq.decrease_resolution(afb, 2)
+        cafb = HLAfreq.combineAF(afb)
+        maskb = cafb.allele.isin(iedb_ref)
+        m = cafb[maskb].allele_freq.sum()
+        # Population proportion with no IEDB ref alleles
+        # at HLA A or HLA B
+        coverage = 1 - ((1-p)**2 * (1-m)**2)
+        iedb_cov.append(coverage)
+        iedb_country.append(country)
+    except:
+        pass
+
+df = pd.DataFrame({'country':iedb_country, 'coverage':iedb_cov})
+df = df.sort_values('coverage')
+df = pd.merge(df, regions, how="left", left_on="country", right_on="Country")
+
+# Plot the proportion of each population with no alleles
+# in the IEDB reference set, assuming no linkage disequilibrium
+# between HLA-A and HLA-B
+plt.barh(df.country, df.coverage, color="black")
+regions = df.largeRegion.unique()
+regions.sort()
+for region in regions:
+    mask = df.largeRegion == region
+    plt.barh(df[mask].country, df[mask].coverage, label=region, zorder=3)
+plt.axvline(0.97, linestyle="--", c="black", zorder=5)
+plt.tight_layout()
+plt.legend(loc="upper left")
+plt.grid(zorder=0)
+plt.show()
+
+##############
+# Plot cumulative frequency of IEDB panel
+# vs
+# country specific alleles
+#A
+country = "Indonesia"
+afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
+afa = HLAfreq.only_complete(afa)
+afa = HLAfreq.decrease_resolution(afa, 2)
+cafa = HLAfreq.combineAF(afa)
+
+cafa = cafa.sort_values('allele_freq', ascending=False, ignore_index=True)
+plt.scatter(cafa.allele, cafa.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+# plt.tight_layout(); plt.show()
+
+maska = cafa.allele.isin(iedb_refa)
+cafai = cafa[maska].sort_values('allele_freq', ascending=False, ignore_index=True)
+# Add unobserved IEDB ref alleles
+missing_iedb = pd.DataFrame([[i, 'A',0,0,473,1,0] for i in iedb_refa if not i in cafai.allele.values], columns=cafai.columns)
+cafai = pd.concat([cafai, missing_iedb])
+plt.scatter(cafai.allele, cafai.allele_freq.cumsum().apply(HLAfreq.population_coverage))
+plt.grid(True); plt.xticks(rotation=90); plt.tight_layout()
+plt.xlabel('Allele'); plt.ylabel('Cumulative population coverage')
+plt.ylim(0,1.05)
+plt.tight_layout(); plt.show()
diff --git a/examples/paper/globalPCA.py b/examples/paper/reproduce_paper_results3.py
similarity index 51%
rename from examples/paper/globalPCA.py
rename to examples/paper/reproduce_paper_results3.py
index 1d0637d..f6953c8 100644
--- a/examples/paper/globalPCA.py
+++ b/examples/paper/reproduce_paper_results3.py
@@ -2,20 +2,35 @@
 Global PCA
 
 Calculate average AF for ~all countries and perform dimension
-reduction on that data to 2D (PCA, UMAP, t-SNE). Then plot
+reduction on that data to 2D (PCA). Then plot
 those points coloured by geographic area.
 
-For this each country must have an estimate for the same set
-of alleles.
+This script requires scikit-learn which is not included
+with HLAFreq.
+
+Takes ~30 minutes to download data
 """
 
 import os
+import requests
 import HLAfreq as HLAfreq
 import pandas as pd
 import numpy as np
+import matplotlib.pyplot as plt
+from sklearn.decomposition import PCA
+
+# Create folder for data
+try:
+    os.makedirs("data/example/globalPCA")
+except FileExistsError:
+    pass
 
-# Countries in regions as defined on 
+# Download countries in regions as defined on 
 # http://www.allelefrequencies.net/datasets.asp#tag_4
+r = requests.get("https://raw.githubusercontent.com/Vaccitech/HLAfreq/main/data/example/countries.csv")
+with open("data/example/countries.csv", "w") as f:
+    f.write(r.text)
+
 regions = pd.read_csv("data/example/countries.csv")
 
 countries = regions.Country.tolist()
@@ -35,7 +50,7 @@
             aftab = HLAfreq.getAFdata(base_url)
             aftab.to_csv("data/example/globalPCA/%s_raw.csv" %country, index=False)
         except:
-            print(f"Failed to get data for {country}: {base_url}")
+            pass
 
 ############
 # Using prior for Venezuela
@@ -111,3 +126,77 @@
 # Dataframe of allele frequencies read for dimension reduction
 AFeatures = pd.DataFrame(AFeatures, columns = ['country'] + sorted_alleles)
 AFeatures.to_csv("data/example/globalPCA/AF_features.csv", index=False)
+
+###################
+#   Prep plots    #
+###################
+AFeatures = pd.read_csv("data/example/globalPCA/AF_features.csv")
+regions = pd.read_csv("data/example/countries.csv")
+
+# Remove Guinea because it includes data from
+# Guinea-Bissau and Papua New Guinea
+AFeatures = AFeatures[AFeatures.country != "Guinea"]
+
+pca = PCA(n_components=2)
+pca_embedding = pca.fit_transform(AFeatures.loc[:,'A*01:01':].values)
+AFeatures['pca0'] = pca_embedding[:,0]
+AFeatures['pca1'] = pca_embedding[:,1]
+
+# Add region to countries
+AFeatures = pd.merge(AFeatures, regions, how="left", left_on="country", right_on="Country")
+
+# Select Venezuela With Prior
+vwp = AFeatures[AFeatures.country == "Venezuela with prior"]
+# Drop countries without largeRegion, this is Venezuela with a prior
+AFeatures = AFeatures.dropna(subset=['largeRegion'])
+
+# Define offset values for each country label
+offset = dict(zip(AFeatures.country, [(0,0)]*AFeatures.shape[0]))
+# Customise offsets
+offset['Zimbabwe'] = (0,5)
+offset['United+States'] = (0,5)
+offset['Georgia'] = (0,5)
+offset['Germany'] = (0,5)
+offset['Italy'] = (0,-5)
+offset['Czech+Republic'] = (0,-4)
+offset['Poland'] = (0,-7)
+offset['France'] = (0,-2)
+offset['Bosnia+and+Herzegovina'] = (0,4)
+offset['Russia'] = (0,-5)
+offset['Ireland'] = (0,-5)
+offset['Netherlands'] = (0,-6)
+offset['Austria'] = (0,-7)
+offset['Romania'] = (0,4)
+offset['Wales'] = (0,-5)
+offset['Cameroon'] = (0,2)
+offset['Ghana'] = (0,-3)
+offset['United+Kingdom'] = (0,-4)
+offset['Sao+Tome+and+Principe'] = (0,-5)
+
+# Plot PCA
+regions = AFeatures.largeRegion.unique()
+regions.sort()
+for region in regions:
+    mask = AFeatures.largeRegion == region
+    plt.scatter(AFeatures.pca0[mask], AFeatures.pca1[mask], label=region)
+    for i in AFeatures[mask].index:
+        # Label each country
+        plt.annotate(
+            AFeatures.loc[i].country.replace("+", " "),
+            AFeatures.loc[i][['pca0','pca1']],
+            offset[AFeatures.loc[i].country],
+            textcoords="offset points",
+            fontsize=8)
+plt.legend()
+# Arrow shows change of Venezuela with prior
+plt.annotate(
+    "",
+    xy=(vwp.pca0, vwp.pca1),
+    xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
+    arrowprops=dict(arrowstyle="->")
+    )
+# Open point to show updated Venezuela
+plt.scatter(vwp.pca0, vwp.pca1, color="tab:blue", facecolors="none")
+plt.xlabel('1st principal component'); plt.ylabel('2nd principal component')
+plt.gcf().set_size_inches(10,10)
+plt.show()

From 3c266a3841ab4f7976195f649f4e2b8bb77056cd Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 4 Jul 2024 10:29:44 +0100
Subject: [PATCH 145/192] Add bandit to nox file

---
 noxfile.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/noxfile.py b/noxfile.py
index b338db0..6a9b219 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -8,6 +8,10 @@ def lint(session):
     session.run("flake8", "src", "--count", "--select=E9,F63,F7,F82", "--show-source", "--statistics")
     session.run("flake8", "src", "--count", "--exit-zero", "--max-complexity=10", "--max-line-length=127", "--statistics")
 
+@nox.session
+def bandit(session):
+    session.install("bandit")
+    session.run("bandit", "-r", "src")
 
 @nox.session(python=["3.10", "3.11", "3.12"])
 def tests(session):

From 48e3fbd11ecd4d9fe13020ed083c3c761fa52eed Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 4 Jul 2024 10:37:10 +0100
Subject: [PATCH 146/192] Make code complient with bandit

Most changes are replacing assert with if not condition: raise AssertionError.
This is because assert statments are removed when code is optimised and compiled.

A timeout argument is also added to getAFdata and used for requests.get().
If requests timesout the exception is reraised with a custom message.
---
 src/HLAfreq/HLAfreq.py      | 75 ++++++++++++++++++-------------------
 src/HLAfreq/HLAfreq_pymc.py | 24 ++++++------
 2 files changed, 48 insertions(+), 51 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index f694eff..7147943 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -163,15 +163,15 @@ def Npages(bs):
     """
     # Get the table with number of pages
     navtab = bs.find("div", {"id": "divGenNavig"}).find("table", {"class": "table10"})
-    assert (
-        navtab
-    ), "navtab does not evaluate to True. Check URL returns results in web browser."
+    if not navtab:
+        raise AssertionError("navtab does not evaluate to True. Check URL returns results in web browser.")
     # Get cell with ' of ' in
     pagesOfN = [
         td.get_text(strip=True) for td in navtab.find_all("td") if " of " in td.text
     ]
     # Check single cell returned
-    assert len(pagesOfN) == 1, "divGenNavig should contain 1 of not %s" % len(pagesOfN)
+    if not len(pagesOfN) == 1:
+        raise AssertionError("divGenNavig should contain 1 of not %s" % len(pagesOfN))
     # Get total number of pages
     N = pagesOfN[0].split("of ")[1]
     N = int(N)
@@ -205,12 +205,14 @@ def formatAF(AFtab, ignoreG=True):
     return df
 
 
-def getAFdata(base_url, format=True, ignoreG=True):
-    """Get all allele frequency data from a search base url. Iterates over all
-        pages regardless of which page is based.
+def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
+    """Get all allele frequency data from a search base_url.
+
+    Iterates over all pages regardless of which page is based.
 
     Args:
         base_url (str): URL for base search.
+        timeout (int): How long to wait to receive a response.
         format (bool): Format the downloaded data using `formatAF()`.
         ignoreG (bool): treat allele G groups as normal.
             See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
@@ -219,7 +221,10 @@ def getAFdata(base_url, format=True, ignoreG=True):
         pd.DataFrame: allele frequency data parsed into a pandas dataframe
     """
     # Get BS object from base search
-    bs = BeautifulSoup(requests.get(base_url).text, "html.parser")
+    try:
+        bs = BeautifulSoup(requests.get(base_url, timeout=timeout).text, "html.parser")
+    except requests.exceptions.ReadTimeout as e:
+        raise Exception("Requests timeout, try a larger `timeout` value for `getAFdata()`") from e
     # How many pages of results
     N = Npages(bs)
     print("%s pages of results" % N)
@@ -229,7 +234,10 @@ def getAFdata(base_url, format=True, ignoreG=True):
         # print (" Parsing page %s" %(i+1))
         print(" Parsing page %s" % (i + 1), end="\r")
         url = base_url + "page=" + str(i + 1)
-        bs = BeautifulSoup(requests.get(url).text, "html.parser")
+        try:
+            bs = BeautifulSoup(requests.get(url, timeout=timeout).text, "html.parser")
+        except requests.exceptions.ReadTimeout as e:
+            raise Exception("Requests timeout, try a larger `timeout` value for `getAFdata()`") from e
         tab = parseAF(bs)
         tabs.append(tab)
     print("Download complete")
@@ -330,9 +338,8 @@ def decrease_resolution(AFtab, newres, datasetID="population"):
     """
     df = AFtab.copy()
     resolution = 1 + df.allele.str.count(":")
-    assert all(
-        resolution >= newres
-    ), f"Some alleles have resolution below {newres} fields"
+    if not all(resolution >= newres):
+        raise AssertionError(f"Some alleles have resolution below {newres} fields")
     new_allele = df.allele.str.split(":").apply(lambda x: ":".join(x[:newres]))
     df.allele = new_allele
     collapsed = collapse_reduced_alleles(df, datasetID=datasetID)
@@ -359,12 +366,10 @@ def collapse_reduced_alleles(AFtab, datasetID="population"):
         columns=["allele_freq", "sample_size", "loci", "#loci", "#sample_sizes"],
     ).reset_index()
     # Within a study each all identical alleles should have the same loci and sample size
-    assert all(
-        collapsed["#loci"] == 1
-    ), "Multiple loci found for a single allele in a single population"
-    assert all(
-        collapsed["#sample_sizes"] == 1
-    ), "Multiple sample_sizes found for a single allele in a single population"
+    if not all(collapsed["#loci"] == 1):
+        raise AssertionError("Multiple loci found for a single allele in a single population")
+    if not all(collapsed["#sample_sizes"] == 1):
+        raise AssertionError("Multiple sample_sizes found for a single allele in a single population")
     collapsed = collapsed[
         ["allele", "loci", "population", "allele_freq", "sample_size"]
     ]
@@ -395,9 +400,8 @@ def unmeasured_alleles(AFtab, datasetID="population"):
             datasetAF = df[(df[datasetID] == dataset) & (df.loci == locus)]
             # What was the sample size for this data?
             dataset_sample_size = datasetAF.sample_size.unique()
-            assert (
-                len(dataset_sample_size) == 1
-            ), "dataset_sample_size must be 1, not %s" % len(dataset_sample_size)
+            if not (len(dataset_sample_size) == 1):
+                raise AssertionError("dataset_sample_size must be 1, not %s" % len(dataset_sample_size))
             dataset_sample_size = dataset_sample_size[0]
             # Get all alleles for this locus (across datasets)
             ualleles = df[df.loci == locus].allele.unique()
@@ -481,17 +485,14 @@ def combineAF(
     df = AFtab.copy()
     single_loci(df)
     if unique:
-        assert alleles_unique_in_study(
-            df, datasetID=datasetID
-        ), "The same allele appears multiple times in a dataset"
+        if not alleles_unique_in_study(df, datasetID=datasetID):
+            raise AssertionError("The same allele appears multiple times in a dataset")
     if complete:
-        assert incomplete_studies(
-            df, datasetID=datasetID
-        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Checkincomplete_studies(AFtab)"
+        if not incomplete_studies(df, datasetID=datasetID).empty:
+            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Checkincomplete_studies(AFtab)")
     if resolution:
-        assert check_resolution(
-            df
-        ), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+        if not check_resolution(df):
+            raise AssertionError("AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)")
     if format:
         df = formatAF(df, ignoreG)
     if add_unmeasured:
@@ -547,7 +548,8 @@ def single_loci(AFtab):
     Args:
         AFtab (pd.DataFrame): Allele frequency data
     """
-    assert len(AFtab.loci.unique()) == 1, "'AFtab' must conatain only 1 loci"
+    if not len(AFtab.loci.unique()) == 1:
+        raise AssertionError("'AFtab' must conatain only 1 loci")
 
 
 def alleles_unique_in_study(AFtab, datasetID="population"):
@@ -585,10 +587,8 @@ def duplicated_sample_size(AFtab):
 def id_duplicated_allele(grouped):
     """Reports the allele that has mupltiple sample sizes"""
     duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
-    assert all(~duplicated_population), (
-        "duplicated population within allele %s"
-        % duplicated_population[duplicated_population].index.tolist()
-    )
+    if not all(~duplicated_population):
+        raise AssertionError(f"duplicated population within allele {duplicated_population[duplicated_population].index.tolist()}")
 
 
 def population_coverage(p):
@@ -680,9 +680,8 @@ def plot_prior(concentration, ncol=2, psteps=1000, labels=""):
     labels = list(labels)
     if not labels:
         labels = [""] * len(concentration)
-    assert len(concentration) == len(
-        labels
-    ), "concentration must be same length as labels"
+    if not len(concentration) == len(labels):
+        raise AssertionError("concentration must be same length as labels")
     for i, alpha in enumerate(concentration):
         a, b = ab[i]
         bd = sp.stats.beta(a, b)
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index a75697d..c08ce2d 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -25,17 +25,14 @@ def _make_c_array(
     df = AFtab.copy()
     HLAfreq.single_loci(df)
     if unique:
-        assert HLAfreq.alleles_unique_in_study(
-            df, datasetID=datasetID
-        ), "The same allele appears multiple times in a dataset"
+        if not HLAfreq.alleles_unique_in_study(df, datasetID=datasetID):
+            raise AssertionError("The same allele appears multiple times in a dataset")
     if complete:
-        assert HLAfreq.incomplete_studies(
-            df, datasetID=datasetID
-        ).empty, "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+        if not HLAfreq.incomplete_studies(df, datasetID=datasetID).empty:
+            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)")
     if resolution:
-        assert HLAfreq.check_resolution(
-            df
-        ), "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+        if not HLAfreq.check_resolution(df):
+            raise AssertionError("AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)")
     if format:
         df = HLAfreq.formatAF(df, ignoreG)
     if add_unmeasured:
@@ -55,9 +52,9 @@ def _make_c_array(
     # Therefore we check that sorted AFloc matches c_array
     # The check is that the sum of allele i is the same
     for a, b in zip(np.apply_along_axis(sum, 0, c_array), df.groupby("allele").c.sum()):
-        assert math.isclose(
-            a, b
-        ), "Error making c_array sum of single allele frequency differs between c_array and AFloc"
+        if not math.isclose(a, b):
+            raise AssertionError("Error making c_array sum of single allele"
+                                 "frequency differs between c_array and AFloc")
     return c_array, allele_names
 
 
@@ -73,7 +70,8 @@ def _fit_Dirichlet_Multinomial(c_array, prior=[], conc_mu=1, conc_sigma=1):
     effective_samples = np.apply_along_axis(sum, 1, c_array)
     if len(prior) == 0:
         prior = HLAfreq.default_prior(k)
-    assert len(prior) == k, "For k alleles, prior must be length k"
+    if not len(prior) == k:
+        raise AssertionError("For k alleles, prior must be length k")
     with pm.Model() as mod:
         frac = pm.Dirichlet("frac", a=prior)
         conc = pm.Lognormal("conc", mu=conc_mu, sigma=conc_sigma)

From f113d81eccc04bb6ee14f1c932af2a80836a7f85 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 4 Jul 2024 11:02:12 +0100
Subject: [PATCH 147/192] Set minimum python version to 3.10

---
 setup.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 2bece8d..0168282 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.3.dev1",
+    version="0.0.3.dev2",
     url="https://github.com/Vaccitech/HLAfreq",
     project_urls={
         'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
@@ -12,6 +12,7 @@
     description="Download and combine HLA frequency data from multiple studies",
     long_description=open('README.md').read(),
     long_description_content_type="text/markdown",
+    python_requires='>=3.10',
     install_requires=[
         'bs4',
         'requests',

From 6044a4216427f177250d1c02d431456d99b1aa40 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 4 Jul 2024 12:07:29 +0100
Subject: [PATCH 148/192] Fix spacing in paper example code

---
 examples/paper/reproduce_paper_results2.py | 2 +-
 examples/paper/reproduce_paper_results3.py | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/examples/paper/reproduce_paper_results2.py b/examples/paper/reproduce_paper_results2.py
index 221c3f2..ddc0293 100644
--- a/examples/paper/reproduce_paper_results2.py
+++ b/examples/paper/reproduce_paper_results2.py
@@ -64,7 +64,6 @@
         cafa = HLAfreq.combineAF(afa)
         maska = cafa.allele.isin(iedb_ref)
         p = cafa[maska].allele_freq.sum()
-
         afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
         afb = HLAfreq.only_complete(afb)
         afb = HLAfreq.decrease_resolution(afb, 2)
@@ -92,6 +91,7 @@
 for region in regions:
     mask = df.largeRegion == region
     plt.barh(df[mask].country, df[mask].coverage, label=region, zorder=3)
+
 plt.axvline(0.97, linestyle="--", c="black", zorder=5)
 plt.tight_layout()
 plt.legend(loc="upper left")
diff --git a/examples/paper/reproduce_paper_results3.py b/examples/paper/reproduce_paper_results3.py
index f6953c8..7ed41be 100644
--- a/examples/paper/reproduce_paper_results3.py
+++ b/examples/paper/reproduce_paper_results3.py
@@ -187,6 +187,7 @@
             offset[AFeatures.loc[i].country],
             textcoords="offset points",
             fontsize=8)
+
 plt.legend()
 # Arrow shows change of Venezuela with prior
 plt.annotate(
@@ -194,7 +195,7 @@
     xy=(vwp.pca0, vwp.pca1),
     xytext=(AFeatures[AFeatures.country == "Venezuela"].pca0, AFeatures[AFeatures.country == "Venezuela"].pca1),
     arrowprops=dict(arrowstyle="->")
-    )
+)
 # Open point to show updated Venezuela
 plt.scatter(vwp.pca0, vwp.pca1, color="tab:blue", facecolors="none")
 plt.xlabel('1st principal component'); plt.ylabel('2nd principal component')

From b02385d76a11084f5b02c6285a65b37428277150 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 7 Aug 2024 17:08:50 +0100
Subject: [PATCH 149/192] Report pytest coverage

---
 noxfile.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/noxfile.py b/noxfile.py
index 6a9b219..95268e8 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -15,6 +15,6 @@ def bandit(session):
 
 @nox.session(python=["3.10", "3.11", "3.12"])
 def tests(session):
-    session.install("pytest")
+    session.install("pytest", "pytest-cov")
     session.install(".")
-    session.run("pytest")
+    session.run("pytest", "--cov=HLAfreq")

From 8f37ae5c34773a753d33dc36cb3d02b576480adb Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 7 Aug 2024 17:12:59 +0100
Subject: [PATCH 150/192] Host example jupyter notebooks on github pages

github action converts notebooks to html and hosts them.
New examples module links the new html examples in docs. README uses updated urls
---
 .github/workflows/docs.yaml      |  3 ++-
 README.md                        |  8 ++++----
 src/HLAfreq.egg-info/SOURCES.txt |  1 +
 src/HLAfreq/examples.py          | 10 ++++++++++
 4 files changed, 17 insertions(+), 5 deletions(-)
 create mode 100644 src/HLAfreq/examples.py

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index 23efd49..cf281e0 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -26,11 +26,12 @@ jobs:
       # ADJUST THIS: install all dependencies (including pdoc)
       - run: pip install -e .
       - run: pip install pdoc
+      - run: pip install jupyter
       # ADJUST THIS: build your documentation into docs/.
       # We use a custom build script for pdoc itself, ideally you just run `pdoc -o docs/ ...` here.
       # - run: python docs/make.py
       - run: pdoc -d google -o docs/ HLAfreq
-
+      - run: jupyter nbconvert --to html --output-dir docs/HLAfreq/examples examples/*.ipynb
       - uses: actions/upload-pages-artifact@v3
         with:
           path: docs/
diff --git a/README.md b/README.md
index 6661bbf..a73d7d4 100644
--- a/README.md
+++ b/README.md
@@ -96,10 +96,10 @@ caf = HLAfreq.combineAF(aftab)
 ## Detailed examples
 For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
 
-- [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
-- [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
-- [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
-- [Credible intervals](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb)
+- [Single country](https://vaccitech.github.io/HLAfreq/single_country.ipynb) download and combine
+- [Multi-country](https://vaccitech.github.io/HLAfreq/multi_country.ipynb) download and combine, weight by population coverage
+- [Using priors](https://vaccitech.github.io/HLAfreq/working_with_priors.ipynb)
+- [Credible intervals](https://vaccitech.github.io/HLAfreq/credible_intervals.ipynb)
 
 ## Docs
 Full documentation at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
diff --git a/src/HLAfreq.egg-info/SOURCES.txt b/src/HLAfreq.egg-info/SOURCES.txt
index f5e2d3a..e24c0e5 100644
--- a/src/HLAfreq.egg-info/SOURCES.txt
+++ b/src/HLAfreq.egg-info/SOURCES.txt
@@ -7,6 +7,7 @@ src/HLAfreq/HLAfreq.py
 src/HLAfreq/HLAfreq_data.py
 src/HLAfreq/HLAfreq_pymc.py
 src/HLAfreq/__init__.py
+src/HLAfreq/examples.py
 src/HLAfreq.egg-info/PKG-INFO
 src/HLAfreq.egg-info/SOURCES.txt
 src/HLAfreq.egg-info/dependency_links.txt
diff --git a/src/HLAfreq/examples.py b/src/HLAfreq/examples.py
new file mode 100644
index 0000000..be73b5a
--- /dev/null
+++ b/src/HLAfreq/examples.py
@@ -0,0 +1,10 @@
+"""
+Several detailed `HLAfreq` examples are detailed in `examples/`.
+
+- [Single country](https://vaccitech.github.io/HLAfreq/single_country.ipynb) download and combine
+- [Multi-country](https://vaccitech.github.io/HLAfreq/multi_country.ipynb) download and combine, weight by population coverage
+- [Using priors](https://vaccitech.github.io/HLAfreq/working_with_priors.ipynb)
+- [Credible intervals](https://vaccitech.github.io/HLAfreq/credible_intervals.ipynb)
+
+"""
+

From e709fe405160f709f6da10d33039db0f32f67752 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 7 Aug 2024 17:34:30 +0100
Subject: [PATCH 151/192] Correct url links for jupyter notebook htmls

---
 README.md               | 8 ++++----
 src/HLAfreq/examples.py | 8 ++++----
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index a73d7d4..1ba0928 100644
--- a/README.md
+++ b/README.md
@@ -96,10 +96,10 @@ caf = HLAfreq.combineAF(aftab)
 ## Detailed examples
 For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
 
-- [Single country](https://vaccitech.github.io/HLAfreq/single_country.ipynb) download and combine
-- [Multi-country](https://vaccitech.github.io/HLAfreq/multi_country.ipynb) download and combine, weight by population coverage
-- [Using priors](https://vaccitech.github.io/HLAfreq/working_with_priors.ipynb)
-- [Credible intervals](https://vaccitech.github.io/HLAfreq/credible_intervals.ipynb)
+- [Single country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
+- [Multi-country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
+- [Using priors](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
+- [Credible intervals](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
 
 ## Docs
 Full documentation at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
diff --git a/src/HLAfreq/examples.py b/src/HLAfreq/examples.py
index be73b5a..846bfa8 100644
--- a/src/HLAfreq/examples.py
+++ b/src/HLAfreq/examples.py
@@ -1,10 +1,10 @@
 """
 Several detailed `HLAfreq` examples are detailed in `examples/`.
 
-- [Single country](https://vaccitech.github.io/HLAfreq/single_country.ipynb) download and combine
-- [Multi-country](https://vaccitech.github.io/HLAfreq/multi_country.ipynb) download and combine, weight by population coverage
-- [Using priors](https://vaccitech.github.io/HLAfreq/working_with_priors.ipynb)
-- [Credible intervals](https://vaccitech.github.io/HLAfreq/credible_intervals.ipynb)
 
+- [Single country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
+- [Multi-country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
+- [Using priors](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
+- [Credible intervals](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
 """
 

From 2b7df1ef980036a7f556e93f9588d6509b0c4373 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 22 Aug 2024 11:33:30 +0100
Subject: [PATCH 152/192] Update vaccitech references to barinthusbio

---
 README.md                                  | 16 ++++++++--------
 docs/README.md                             |  2 +-
 examples/credible_intervals.ipynb          |  4 ++--
 examples/multi_country.ipynb               |  4 ++--
 examples/paper/reproduce_paper_results2.py |  2 +-
 examples/paper/reproduce_paper_results3.py |  2 +-
 examples/single_country.ipynb              |  2 +-
 setup.py                                   |  6 +++---
 src/HLAfreq/HLAfreq_pymc.py                |  2 +-
 src/HLAfreq/examples.py                    |  8 ++++----
 10 files changed, 24 insertions(+), 24 deletions(-)

diff --git a/README.md b/README.md
index 1ba0928..eed1884 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ ability to mount an immune response to specific epitopes.
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
 
-Source code is available at [Vaccitech/HLAfreq](https://github.com/Vaccitech/HLAfreq).
+Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
 
 ## Details
 Estimates are combined by modelling allele frequency as a 
@@ -61,7 +61,7 @@ conda create -n hlafreq -c conda-forge -c bioconda python=3.10 numpy=1.25.2 pymc
 Conda should handle this automatically, but if you get errors check
 the package versions with `conda list`.
 
-If you do run into trouble please open an [issue](https://github.com/Vaccitech/HLAfreq/issues).
+If you do run into trouble please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues).
 
 If you don't intend to use credible intervals you can install
 with pip: `pip install HLAfreq`.
@@ -94,15 +94,15 @@ caf = HLAfreq.combineAF(aftab)
 ```
 
 ## Detailed examples
-For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
+For more detailed walkthroughs see [HLAfreq/examples](https://github.com/BarinthusBio/HLAfreq/tree/main/examples).
 
-- [Single country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
-- [Multi-country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
-- [Using priors](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
-- [Credible intervals](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
+- [Single country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
+- [Multi-country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
+- [Using priors](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
+- [Credible intervals](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
 
 ## Docs
-Full documentation at [HLAfreq/docs](https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+Full documentation at [HLAfreq/docs](https://BarinthusBio.github.io/HLAfreq/HLAfreq.html).
 API documentation for functions are under the submodules on the left.
 - `HLAfreq.HLAfreq` documents most functions, specifically download and combine
 allele data.
diff --git a/docs/README.md b/docs/README.md
index 530ff0e..a624c34 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -1,6 +1,6 @@
 # Documentation
 `HLAfreq`'s documentation is hosted on a github-page [here](
-https://vaccitech.github.io/HLAfreq/HLAfreq.html).
+https://BarinthusBio.github.io/HLAfreq/HLAfreq.html).
 
 ## Build instructions
 Run `pdoc -d google -o docs/ HLAfreq` to generate the
diff --git a/examples/credible_intervals.ipynb b/examples/credible_intervals.ipynb
index 3be97a1..fcb400b 100644
--- a/examples/credible_intervals.ipynb
+++ b/examples/credible_intervals.ipynb
@@ -377,7 +377,7 @@
     "- Issues with model convergence\n",
     "\n",
     "## Inappropriate prior\n",
-    "Sometimes the `post_mean` and credible intervals are clearly too low. We have seen this when there are many alleles (usually >100) compared to the amount of data and many of these alleles are very rare. This is covered in more detail in the [working with priors example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb). Fortunately the fix is quite simple; instead of the default prior (a vector of $1$ s) use a vector of $1/k$ s where $k$ is the number of alleles. In simulations this resolved this issue even in extreme cases. Alternatively the default estimate of `allele_freq` is far more robust to this issue."
+    "Sometimes the `post_mean` and credible intervals are clearly too low. We have seen this when there are many alleles (usually >100) compared to the amount of data and many of these alleles are very rare. This is covered in more detail in the [working with priors example](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/working_with_priors.ipynb). Fortunately the fix is quite simple; instead of the default prior (a vector of $1$ s) use a vector of $1/k$ s where $k$ is the number of alleles. In simulations this resolved this issue even in extreme cases. Alternatively the default estimate of `allele_freq` is far more robust to this issue."
    ]
   },
   {
@@ -444,7 +444,7 @@
      "text": [
       "\n",
       "WARNING: The default allele frequency estimate is outside of the CI estimated by the compound method for some alleles!\n",
-      "There are several possible reasons, see the credible intervals example: https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb\n",
+      "There are several possible reasons, see the credible intervals example: https://github.com/BarinthusBio/HLAfreq/blob/main/examples/credible_intervals.ipynb\n",
       "If you have set `credible_interval` to < 0.95, this may be a non-issue.\n"
      ]
     },
diff --git a/examples/multi_country.ipynb b/examples/multi_country.ipynb
index 8280165..cf497c9 100644
--- a/examples/multi_country.ipynb
+++ b/examples/multi_country.ipynb
@@ -284,7 +284,7 @@
     "It is also clear that the international average allele\n",
     "frequency for A\\*24:02 is being skewed by this country. We can view the\n",
     "`cafs` dataset to see which country this is, Guinea.\n",
-    "For more info on dealing with outliers and this skewing, see the [credible intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb).\n",
+    "For more info on dealing with outliers and this skewing, see the [credible intervals example](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/credible_intervals.ipynb).\n",
     "\n",
     "This method can\n",
     "also be applied to individual countries to identify studies which\n",
@@ -1224,7 +1224,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "It's important to check the compound models by comparing to the default model. Below we plot the population size weighted default model estimates against the population weighted compound model estimates. Unfortunately they are not as similar as we'd like. The compound model is overestimating rare alleles and underestimating common alleles. This suggests an overly informative prior pulling all alleles to an average frequency. For more detail on this issue see the [working with priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb) example."
+    "It's important to check the compound models by comparing to the default model. Below we plot the population size weighted default model estimates against the population weighted compound model estimates. Unfortunately they are not as similar as we'd like. The compound model is overestimating rare alleles and underestimating common alleles. This suggests an overly informative prior pulling all alleles to an average frequency. For more detail on this issue see the [working with priors](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/working_with_priors.ipynb) example."
    ]
   },
   {
diff --git a/examples/paper/reproduce_paper_results2.py b/examples/paper/reproduce_paper_results2.py
index ddc0293..2a14ec8 100644
--- a/examples/paper/reproduce_paper_results2.py
+++ b/examples/paper/reproduce_paper_results2.py
@@ -28,7 +28,7 @@
 
 # Download countries in regions as defined on 
 # http://www.allelefrequencies.net/datasets.asp#tag_4
-r = requests.get("https://raw.githubusercontent.com/Vaccitech/HLAfreq/main/data/example/countries.csv")
+r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)
 
diff --git a/examples/paper/reproduce_paper_results3.py b/examples/paper/reproduce_paper_results3.py
index 7ed41be..5184618 100644
--- a/examples/paper/reproduce_paper_results3.py
+++ b/examples/paper/reproduce_paper_results3.py
@@ -27,7 +27,7 @@
 
 # Download countries in regions as defined on 
 # http://www.allelefrequencies.net/datasets.asp#tag_4
-r = requests.get("https://raw.githubusercontent.com/Vaccitech/HLAfreq/main/data/example/countries.csv")
+r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)
 
diff --git a/examples/single_country.ipynb b/examples/single_country.ipynb
index 93defed..9f7b72f 100644
--- a/examples/single_country.ipynb
+++ b/examples/single_country.ipynb
@@ -219,7 +219,7 @@
     "\n",
     "The black open points are the combined estimates made using the default model, the coloured points are individual study estimates, coloured by population. The combined estimate and credible intervals from the compound model are plotted as vertical and hoizontal black lines respectively.\n",
     "\n",
-    "The credible intervals are taken from hdi, calculated above. This defaults to 95% but other values can be passed to `AFhdi()` and will be plotted. It is important to verify the credible intervals are reasonable but HLAfreq will print a warning if they are too different from the default estimate. See the [credible_intervals example](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb) for more details."
+    "The credible intervals are taken from hdi, calculated above. This defaults to 95% but other values can be passed to `AFhdi()` and will be plotted. It is important to verify the credible intervals are reasonable but HLAfreq will print a warning if they are too different from the default estimate. See the [credible_intervals example](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/credible_intervals.ipynb) for more details."
    ]
   },
   {
diff --git a/setup.py b/setup.py
index 0168282..c46289d 100644
--- a/setup.py
+++ b/setup.py
@@ -3,12 +3,12 @@
 setup(
     name="HLAfreq",
     version="0.0.3.dev2",
-    url="https://github.com/Vaccitech/HLAfreq",
+    url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
-        'Tracker': "https://github.com/Vaccitech/HLAfreq/issues"
+        'Tracker': "https://github.com/BarinthusBio/HLAfreq/issues"
     },
     author="David Wells",
-    author_email="david.wells@vaccitech.co.uk",
+    author_email="david.wells@BarinthusBio.co.uk",
     description="Download and combine HLA frequency data from multiple studies",
     long_description=open('README.md').read(),
     long_description_content_type="text/markdown",
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index c08ce2d..b12fc6b 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -168,6 +168,6 @@ def compare_estimates(AFtab, hdi, datasetID):
         )
         print(
             "There are several possible reasons, see the credible intervals example:"
-            "https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb"
+            "https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html"
         )
         print("If you have set `credible_interval` to < 0.95, this may be a non-issue.")
diff --git a/src/HLAfreq/examples.py b/src/HLAfreq/examples.py
index 846bfa8..db68b38 100644
--- a/src/HLAfreq/examples.py
+++ b/src/HLAfreq/examples.py
@@ -2,9 +2,9 @@
 Several detailed `HLAfreq` examples are detailed in `examples/`.
 
 
-- [Single country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
-- [Multi-country](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
-- [Using priors](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
-- [Credible intervals](https://vaccitech.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
+- [Single country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
+- [Multi-country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage
+- [Using priors](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
+- [Credible intervals](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
 """
 

From c0146ee2122befa8b9141604f8f4d147d7b9f8fb Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 22 Aug 2024 11:46:26 +0100
Subject: [PATCH 153/192] Update detailed examples link in readme to examples
 module

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index eed1884..190d194 100644
--- a/README.md
+++ b/README.md
@@ -94,7 +94,7 @@ caf = HLAfreq.combineAF(aftab)
 ```
 
 ## Detailed examples
-For more detailed walkthroughs see [HLAfreq/examples](https://github.com/BarinthusBio/HLAfreq/tree/main/examples).
+For more detailed walkthroughs see [HLAfreq/examples](https://barinthusbio.github.io/HLAfreq/HLAfreq/examples.html).
 
 - [Single country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/single_country.html) download and combine
 - [Multi-country](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/multi_country.html) download and combine, weight by population coverage

From a8adab4aeb58125a2d11b7cee27ba362b78615a7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 27 Aug 2024 13:45:53 +0100
Subject: [PATCH 154/192] Pytest coverage

HLAF-8
---
 .github/workflows/python-package.yaml | 4 ++--
 .gitignore                            | 3 ++-
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index 11c7300..a9eebb3 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -27,7 +27,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install flake8 pytest
+        python -m pip install flake8 pytest pytest-cov
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Install HLAfreq
       run: |
@@ -40,4 +40,4 @@ jobs:
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Test with pytest
       run: |
-        pytest
+        pytest --cov=HLAfreq
diff --git a/.gitignore b/.gitignore
index 0c68b5e..2473b06 100644
--- a/.gitignore
+++ b/.gitignore
@@ -4,4 +4,5 @@ writeup/
 *.code-workspace
 envs/.venv
 build/
-dist/
\ No newline at end of file
+dist/
+.coverage
\ No newline at end of file

From 8151d19427b670a3367ded9c299c3d4fbe761b53 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 27 Aug 2024 13:53:41 +0100
Subject: [PATCH 155/192] Specify minimum dependancy versions

HLAF-11
Minimum versions set for numpy, scipy, and matplotlib
---
 setup.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/setup.py b/setup.py
index c46289d..722b310 100644
--- a/setup.py
+++ b/setup.py
@@ -17,9 +17,9 @@
         'bs4',
         'requests',
         'pandas',
-        'numpy',
-        'matplotlib',
-        'scipy',
+        'numpy>=1.24.0',
+        'matplotlib>=3.6.0',
+        'scipy>=1.10.0',
         'pymc>=3',
         'arviz'
     ],

From 7868e97409dbb09f805cc4e41f91eb1c75f3c73b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 27 Aug 2024 15:14:34 +0100
Subject: [PATCH 156/192] gitignore egg info

Delete old egg info and stop tracking
---
 .gitignore                                |   1 +
 src/HLAfreq.egg-info/PKG-INFO             | 105 ----------------------
 src/HLAfreq.egg-info/SOURCES.txt          |  18 ----
 src/HLAfreq.egg-info/dependency_links.txt |   1 -
 src/HLAfreq.egg-info/requires.txt         |   8 --
 src/HLAfreq.egg-info/top_level.txt        |   1 -
 6 files changed, 1 insertion(+), 133 deletions(-)
 delete mode 100644 src/HLAfreq.egg-info/PKG-INFO
 delete mode 100644 src/HLAfreq.egg-info/SOURCES.txt
 delete mode 100644 src/HLAfreq.egg-info/dependency_links.txt
 delete mode 100644 src/HLAfreq.egg-info/requires.txt
 delete mode 100644 src/HLAfreq.egg-info/top_level.txt

diff --git a/.gitignore b/.gitignore
index 2473b06..7eba116 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,4 +5,5 @@ writeup/
 envs/.venv
 build/
 dist/
+src/*.egg-info/
 .coverage
\ No newline at end of file
diff --git a/src/HLAfreq.egg-info/PKG-INFO b/src/HLAfreq.egg-info/PKG-INFO
deleted file mode 100644
index 98edc29..0000000
--- a/src/HLAfreq.egg-info/PKG-INFO
+++ /dev/null
@@ -1,105 +0,0 @@
-Metadata-Version: 2.1
-Name: HLAfreq
-Version: 0.0.2
-Summary: Download and combine HLA frequency data from multiple studies
-Home-page: https://github.com/Vaccitech/HLAfreq
-Author: David Wells
-Author-email: david.wells@vaccitech.co.uk
-Project-URL: Tracker, https://github.com/Vaccitech/HLAfreq/issues
-Classifier: Programming Language :: Python :: 3
-Classifier: Operating System :: OS Independent
-Description-Content-Type: text/markdown
-License-File: LICENSE
-
-# HLAfreq
-
-`HLAfreq` allows you to download and combine HLA allele
-frequencies from multiple datasets, e.g. combine data from
-several studies within a country or combine countries.
-Useful for studying regional diversity in immune genes
-and, when paired with epitope prediction, estimating a population's
-ability to mount an immune response to specific epitopes.
-
-Automated download of allele frequency data download from 
-[allele frequencies.net](http://www.allelefrequencies.net/).
-
-## Details
-Estimates are combined by modelling allele frequency as a 
-Dirichlet distribution which defines the probability of drawing each
-allele. When combining studies their estimates are weighted as 2x sample size by
-default. Sample size is doubled as each person in the study
-contributes two alleles. Alternative weightings can be used
-for example population size when averaging across countries.
-
-When selecting a panel of HLA alleles to represent a population,
-allele frequency is not the only thing to consider. Depending on
-the purpose of the panel, you should include a range of loci and
-supertypes (groups alleles sharing binding specificies).
-
-## Install
-```
-pip install HLAfreq
-```
-
-## Minimal example
-Download HLA data using `makeURL()` and `getAFdata()`.
-All arguments that can be specified in the webpage form are available,
-see `help(HLAfreq.makeURL)` for details (press `q` to exit).
-```
-import HLAfreq
-base_url = HLAfreq.makeURL("Uganda", locus="A")
-aftab = HLAfreq.getAFdata(base_url)
-```
-
-After downloading the data, it must be filtered so that all studies
-sum to allele frequency 1 (within tolerence). Then we must ensure
-that all studies report alleles at the same resolution.
-Finaly we can combine frequency estimates.
-```
-aftab = HLAfreq.only_complete(aftab)
-aftab = HLAfreq.decrease_resolution(aftab, 2)
-caf = HLAfreq.combineAF(aftab)
-```
-
-## Detailed examples
-For more detailed walkthroughs see [HLAfreq/examples](https://github.com/Vaccitech/HLAfreq/tree/main/examples).
-
-- [Single country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/single_country.ipynb) download and combine
-- [Multi-country](https://github.com/Vaccitech/HLAfreq/blob/main/examples/multi_country.ipynb) download and combine, weight by population coverage
-- [Using priors](https://github.com/Vaccitech/HLAfreq/blob/main/examples/working_with_priors.ipynb)
-- [Credible intervals](https://github.com/Vaccitech/HLAfreq/blob/main/examples/credible_intervals.ipynb)
-
-## Docs
-For help on specific functions view the docstring, `help(function_name)`.
-Full documentation API at [HLAfreq/docs](https://github.com/Vaccitech/HLAfreq/blob/main/docs/HLAfreq.md)
-created with pdoc3 in pdf mode.
-
-<!-- ## Developer notes
-# Install in dev mode
-pip install -e HLAfreq
-
-Update version in setup.py
-
-Update documentation with `pdoc --pdf -o docs/ src/HLAfreq/ > docs/HLAfreq.md`.
-
-Run tests `pytest` 
-
-# Clear old build info
-rm -rf build dist src/*.egg-info 
-
-Build with `python -m build`.
-
-twine check dist/*
-
-# Upload to test pypi
-twine upload --repository testpypi dist/*
-
-# Install from test pypi
-python3 -m pip install --extra-index-url https://test.pypi.org/simple/ HLAfreq
-
-# Upload to pypi
-twine upload dist/*
--->
-
-## Citation
-*In prep.*
diff --git a/src/HLAfreq.egg-info/SOURCES.txt b/src/HLAfreq.egg-info/SOURCES.txt
deleted file mode 100644
index e24c0e5..0000000
--- a/src/HLAfreq.egg-info/SOURCES.txt
+++ /dev/null
@@ -1,18 +0,0 @@
-LICENSE
-MANIFEST.in
-README.md
-pyproject.toml
-setup.py
-src/HLAfreq/HLAfreq.py
-src/HLAfreq/HLAfreq_data.py
-src/HLAfreq/HLAfreq_pymc.py
-src/HLAfreq/__init__.py
-src/HLAfreq/examples.py
-src/HLAfreq.egg-info/PKG-INFO
-src/HLAfreq.egg-info/SOURCES.txt
-src/HLAfreq.egg-info/dependency_links.txt
-src/HLAfreq.egg-info/requires.txt
-src/HLAfreq.egg-info/top_level.txt
-src/HLAfreq/data/HLA1supertypes_Sidney2008.csv
-src/HLAfreq/data/countries.csv
-tests/test_single_country_caf.py
\ No newline at end of file
diff --git a/src/HLAfreq.egg-info/dependency_links.txt b/src/HLAfreq.egg-info/dependency_links.txt
deleted file mode 100644
index 8b13789..0000000
--- a/src/HLAfreq.egg-info/dependency_links.txt
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/src/HLAfreq.egg-info/requires.txt b/src/HLAfreq.egg-info/requires.txt
deleted file mode 100644
index a76745b..0000000
--- a/src/HLAfreq.egg-info/requires.txt
+++ /dev/null
@@ -1,8 +0,0 @@
-bs4
-requests
-pandas
-numpy
-matplotlib
-scipy
-pymc>=3
-arviz
diff --git a/src/HLAfreq.egg-info/top_level.txt b/src/HLAfreq.egg-info/top_level.txt
deleted file mode 100644
index b260130..0000000
--- a/src/HLAfreq.egg-info/top_level.txt
+++ /dev/null
@@ -1 +0,0 @@
-HLAfreq

From 2c84b7c64c4abad0586144f058e51483feda00a2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 13:38:38 +0100
Subject: [PATCH 157/192] Tests for simulated data, including failure tests

Tests written for simulated data,
tests that assertion errors are thrown as expected.
typos in assertion error messages corrected
AFhdi test removed for speed
---
 src/HLAfreq/HLAfreq.py           |   4 +-
 tests/test_simulated_data.py     | 137 +++++++++++++++++++++++++++++++
 tests/test_single_country_caf.py |   7 +-
 3 files changed, 143 insertions(+), 5 deletions(-)
 create mode 100644 tests/test_simulated_data.py

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 7147943..d1ecc4c 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -489,7 +489,7 @@ def combineAF(
             raise AssertionError("The same allele appears multiple times in a dataset")
     if complete:
         if not incomplete_studies(df, datasetID=datasetID).empty:
-            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Checkincomplete_studies(AFtab)")
+            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)")
     if resolution:
         if not check_resolution(df):
             raise AssertionError("AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)")
@@ -549,7 +549,7 @@ def single_loci(AFtab):
         AFtab (pd.DataFrame): Allele frequency data
     """
     if not len(AFtab.loci.unique()) == 1:
-        raise AssertionError("'AFtab' must conatain only 1 loci")
+        raise AssertionError("'AFtab' must contain only 1 loci")
 
 
 def alleles_unique_in_study(AFtab, datasetID="population"):
diff --git a/tests/test_simulated_data.py b/tests/test_simulated_data.py
new file mode 100644
index 0000000..a86ca91
--- /dev/null
+++ b/tests/test_simulated_data.py
@@ -0,0 +1,137 @@
+import pytest
+import HLAfreq
+import pandas as pd
+import numpy as np
+from collections.abc import Iterable
+
+@pytest.fixture(params=["Thailand"])
+def country(request):
+    return request.param
+
+@pytest.fixture
+def base_url(country):
+    return HLAfreq.makeURL(country)
+
+def test_url_string(base_url):
+    assert isinstance(base_url, str)
+
+def simulate_population(
+        alleles: Iterable[str],
+        locus: str,
+        population: str
+    ):
+    pop_size = np.random.randint(len(alleles), 50)
+    samples = np.random.choice(alleles, pop_size, replace=True)
+    counts = pd.Series(samples).value_counts()
+    counts.values/pop_size
+    pop = pd.DataFrame({
+        "allele": counts.index,
+        "loci": locus,
+        "population": population,
+        "allele_freq": counts.values/pop_size,
+        "sample_size": pop_size,
+    })
+    return pop
+
+
+def simulate_study(alleles, populations, locus):
+    study = []
+    for i in range(populations):
+        pop = simulate_population(
+            alleles = alleles,
+            locus = locus,
+            population = f"pop_{i}"
+        )
+        study.append(pop)
+
+    study = pd.concat(study)
+    return study
+
+@pytest.fixture(params=[
+    ["A*01:01", "A*01:02", "A*01:03"],
+    ["A*01:01:01", "A*01:02:01", "A*01:03:01"],
+    ["A*01:01", "A*01:02", "A*01:03:01"],
+    ["A*01:01", "A*01:02", "A*01:03:01", "A*01:03:02"],
+])
+def alleles(request):
+    return request.param
+
+@pytest.fixture
+def aftab(alleles):
+    return simulate_study(alleles, 3, "X")
+
+@pytest.fixture
+def expected_freq(aftab):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    aftab = HLAfreq.unmeasured_alleles(aftab, "population")
+    grouped = aftab.groupby("allele")[['allele_freq','sample_size']]
+    return grouped.apply(lambda x: np.average(x.allele_freq, weights=x.sample_size*2)).values
+    
+def test_wav(aftab, expected_freq):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    caf = HLAfreq.combineAF(aftab)
+    assert caf.wav.values == pytest.approx(expected_freq)
+
+def test_combineAF(aftab, expected_freq):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    caf = HLAfreq.combineAF(aftab)
+    assert caf.allele_freq.values == pytest.approx(expected_freq, rel=5e-2)
+
+def test_resolution_check(alleles, aftab):
+    aftab.loc[0,'allele'] = aftab.loc[0,'allele'] + ":00:00"
+    with pytest.raises(AssertionError) as e:
+        caf = HLAfreq.combineAF(aftab)
+    assert "multiple resolutions" in str(e.value)
+
+def test_low_res(aftab):
+    with pytest.raises(AssertionError) as e:
+        HLAfreq.decrease_resolution(aftab, 5)
+    assert "resolution below" in str(e.value)
+
+def test_single_locus(aftab):
+    with pytest.raises(AssertionError) as e:
+        aftab.iloc[0,1] = "Y"
+        HLAfreq.combineAF(aftab)
+    assert "only 1 loci" in str(e.value)
+
+def test_complete(aftab):
+    aftab = aftab.drop(0)
+    with pytest.raises(AssertionError) as e:
+        HLAfreq.combineAF(aftab)
+    assert "incomplete_studies" in str(e.value)
+
+def test_single_sample_size(aftab):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    aftab.loc[0, 'sample_size'] = 51
+    with pytest.raises(AssertionError) as e:
+        caf = HLAfreq.combineAF(aftab)
+    assert "dataset_sample_size must be 1" in str(e.value)
+
+def test_unique_in_study(aftab):
+    aftab['allele'] = "A*00:00"
+    with pytest.raises(AssertionError) as e:
+        caf = HLAfreq.combineAF(aftab)
+    assert "same allele appears multiple times" in str(e.value)
+
+
+def test_multi_loci_allele_decrease_resolution(aftab):
+    aftabB = aftab.copy()
+    aftabB.iloc[0,1] = "Y"
+    aftab = pd.concat([aftab, aftabB])
+    with pytest.raises(AssertionError) as e:
+        HLAfreq.decrease_resolution(aftab, 2)
+    assert "Multiple loci found for a single allele in a single population" in str(e.value)
+    
+
+def test_multi_sample_size_allele_decrease_resolution(aftab):
+    aftabB = aftab.copy()
+    aftabB.loc[0, "sample_size"] = 51
+    aftab = pd.concat([aftab, aftabB])
+    with pytest.raises(AssertionError) as e:
+        HLAfreq.decrease_resolution(aftab, 2)
+    assert "Multiple sample_sizes found for a single allele in a single population" in str(e.value)
+
diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index 5f1c8b7..c8fe7df 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -66,6 +66,7 @@ def test_combined_allele_freq():
     assert all(caf.allele_freq == dirichlet([8, 12, 13]).mean())
 
 
-def test_hdi():
-    hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
-    all(hdi.columns == ["lo", "hi", "allele", "post_mean"])
+# Not a meaningful test but slow
+# def test_hdi():
+#     hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
+#     assert all(hdi.columns == ["lo", "hi", "allele", "post_mean"])

From 7ab5b63b77f166038f924aea8e75bf4564c13dfd Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 13:40:42 +0100
Subject: [PATCH 158/192] Black formatting, mostly assertion error message
 wraps

---
 src/HLAfreq/HLAfreq.py      | 36 +++++++++++++++++++++++++++---------
 src/HLAfreq/HLAfreq_pymc.py | 14 ++++++++++----
 src/HLAfreq/examples.py     |  1 -
 3 files changed, 37 insertions(+), 14 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index d1ecc4c..bb225b6 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -164,7 +164,9 @@ def Npages(bs):
     # Get the table with number of pages
     navtab = bs.find("div", {"id": "divGenNavig"}).find("table", {"class": "table10"})
     if not navtab:
-        raise AssertionError("navtab does not evaluate to True. Check URL returns results in web browser.")
+        raise AssertionError(
+            "navtab does not evaluate to True. Check URL returns results in web browser."
+        )
     # Get cell with ' of ' in
     pagesOfN = [
         td.get_text(strip=True) for td in navtab.find_all("td") if " of " in td.text
@@ -224,7 +226,9 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
     try:
         bs = BeautifulSoup(requests.get(base_url, timeout=timeout).text, "html.parser")
     except requests.exceptions.ReadTimeout as e:
-        raise Exception("Requests timeout, try a larger `timeout` value for `getAFdata()`") from e
+        raise Exception(
+            "Requests timeout, try a larger `timeout` value for `getAFdata()`"
+        ) from e
     # How many pages of results
     N = Npages(bs)
     print("%s pages of results" % N)
@@ -237,7 +241,9 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
         try:
             bs = BeautifulSoup(requests.get(url, timeout=timeout).text, "html.parser")
         except requests.exceptions.ReadTimeout as e:
-            raise Exception("Requests timeout, try a larger `timeout` value for `getAFdata()`") from e
+            raise Exception(
+                "Requests timeout, try a larger `timeout` value for `getAFdata()`"
+            ) from e
         tab = parseAF(bs)
         tabs.append(tab)
     print("Download complete")
@@ -367,9 +373,13 @@ def collapse_reduced_alleles(AFtab, datasetID="population"):
     ).reset_index()
     # Within a study each all identical alleles should have the same loci and sample size
     if not all(collapsed["#loci"] == 1):
-        raise AssertionError("Multiple loci found for a single allele in a single population")
+        raise AssertionError(
+            "Multiple loci found for a single allele in a single population"
+        )
     if not all(collapsed["#sample_sizes"] == 1):
-        raise AssertionError("Multiple sample_sizes found for a single allele in a single population")
+        raise AssertionError(
+            "Multiple sample_sizes found for a single allele in a single population"
+        )
     collapsed = collapsed[
         ["allele", "loci", "population", "allele_freq", "sample_size"]
     ]
@@ -401,7 +411,9 @@ def unmeasured_alleles(AFtab, datasetID="population"):
             # What was the sample size for this data?
             dataset_sample_size = datasetAF.sample_size.unique()
             if not (len(dataset_sample_size) == 1):
-                raise AssertionError("dataset_sample_size must be 1, not %s" % len(dataset_sample_size))
+                raise AssertionError(
+                    "dataset_sample_size must be 1, not %s" % len(dataset_sample_size)
+                )
             dataset_sample_size = dataset_sample_size[0]
             # Get all alleles for this locus (across datasets)
             ualleles = df[df.loci == locus].allele.unique()
@@ -489,10 +501,14 @@ def combineAF(
             raise AssertionError("The same allele appears multiple times in a dataset")
     if complete:
         if not incomplete_studies(df, datasetID=datasetID).empty:
-            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)")
+            raise AssertionError(
+                "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+            )
     if resolution:
         if not check_resolution(df):
-            raise AssertionError("AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)")
+            raise AssertionError(
+                "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+            )
     if format:
         df = formatAF(df, ignoreG)
     if add_unmeasured:
@@ -588,7 +604,9 @@ def id_duplicated_allele(grouped):
     """Reports the allele that has mupltiple sample sizes"""
     duplicated_population = grouped.population.apply(lambda x: any(x.duplicated()))
     if not all(~duplicated_population):
-        raise AssertionError(f"duplicated population within allele {duplicated_population[duplicated_population].index.tolist()}")
+        raise AssertionError(
+            f"duplicated population within allele {duplicated_population[duplicated_population].index.tolist()}"
+        )
 
 
 def population_coverage(p):
diff --git a/src/HLAfreq/HLAfreq_pymc.py b/src/HLAfreq/HLAfreq_pymc.py
index b12fc6b..0adcd91 100644
--- a/src/HLAfreq/HLAfreq_pymc.py
+++ b/src/HLAfreq/HLAfreq_pymc.py
@@ -29,10 +29,14 @@ def _make_c_array(
             raise AssertionError("The same allele appears multiple times in a dataset")
     if complete:
         if not HLAfreq.incomplete_studies(df, datasetID=datasetID).empty:
-            raise AssertionError("AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)")
+            raise AssertionError(
+                "AFtab contains studies with AF that doesn't sum to 1. Check incomplete_studies(AFtab)"
+            )
     if resolution:
         if not HLAfreq.check_resolution(df):
-            raise AssertionError("AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)")
+            raise AssertionError(
+                "AFtab conains alleles at multiple resolutions, check check_resolution(AFtab)"
+            )
     if format:
         df = HLAfreq.formatAF(df, ignoreG)
     if add_unmeasured:
@@ -53,8 +57,10 @@ def _make_c_array(
     # The check is that the sum of allele i is the same
     for a, b in zip(np.apply_along_axis(sum, 0, c_array), df.groupby("allele").c.sum()):
         if not math.isclose(a, b):
-            raise AssertionError("Error making c_array sum of single allele"
-                                 "frequency differs between c_array and AFloc")
+            raise AssertionError(
+                "Error making c_array sum of single allele"
+                "frequency differs between c_array and AFloc"
+            )
     return c_array, allele_names
 
 
diff --git a/src/HLAfreq/examples.py b/src/HLAfreq/examples.py
index db68b38..f21f9ae 100644
--- a/src/HLAfreq/examples.py
+++ b/src/HLAfreq/examples.py
@@ -7,4 +7,3 @@
 - [Using priors](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/working_with_priors.html)
 - [Credible intervals](https://BarinthusBio.github.io/HLAfreq/HLAfreq/examples/credible_intervals.html)
 """
-

From 16bd045be5c494b8adffc24306f234cacead2137 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 13:42:54 +0100
Subject: [PATCH 159/192] Black formatting of tests

Mostly 2 lines between functions,
and changing text wrapping
---
 tests/test_simulated_data.py     | 89 +++++++++++++++++++-------------
 tests/test_single_country_caf.py |  1 +
 2 files changed, 54 insertions(+), 36 deletions(-)

diff --git a/tests/test_simulated_data.py b/tests/test_simulated_data.py
index a86ca91..f4d4049 100644
--- a/tests/test_simulated_data.py
+++ b/tests/test_simulated_data.py
@@ -4,115 +4,128 @@
 import numpy as np
 from collections.abc import Iterable
 
+
 @pytest.fixture(params=["Thailand"])
 def country(request):
     return request.param
 
+
 @pytest.fixture
 def base_url(country):
     return HLAfreq.makeURL(country)
 
+
 def test_url_string(base_url):
     assert isinstance(base_url, str)
 
-def simulate_population(
-        alleles: Iterable[str],
-        locus: str,
-        population: str
-    ):
+
+def simulate_population(alleles: Iterable[str], locus: str, population: str):
     pop_size = np.random.randint(len(alleles), 50)
     samples = np.random.choice(alleles, pop_size, replace=True)
     counts = pd.Series(samples).value_counts()
-    counts.values/pop_size
-    pop = pd.DataFrame({
-        "allele": counts.index,
-        "loci": locus,
-        "population": population,
-        "allele_freq": counts.values/pop_size,
-        "sample_size": pop_size,
-    })
+    counts.values / pop_size
+    pop = pd.DataFrame(
+        {
+            "allele": counts.index,
+            "loci": locus,
+            "population": population,
+            "allele_freq": counts.values / pop_size,
+            "sample_size": pop_size,
+        }
+    )
     return pop
 
 
 def simulate_study(alleles, populations, locus):
     study = []
     for i in range(populations):
-        pop = simulate_population(
-            alleles = alleles,
-            locus = locus,
-            population = f"pop_{i}"
-        )
+        pop = simulate_population(alleles=alleles, locus=locus, population=f"pop_{i}")
         study.append(pop)
 
     study = pd.concat(study)
     return study
 
-@pytest.fixture(params=[
-    ["A*01:01", "A*01:02", "A*01:03"],
-    ["A*01:01:01", "A*01:02:01", "A*01:03:01"],
-    ["A*01:01", "A*01:02", "A*01:03:01"],
-    ["A*01:01", "A*01:02", "A*01:03:01", "A*01:03:02"],
-])
+
+@pytest.fixture(
+    params=[
+        ["A*01:01", "A*01:02", "A*01:03"],
+        ["A*01:01:01", "A*01:02:01", "A*01:03:01"],
+        ["A*01:01", "A*01:02", "A*01:03:01"],
+        ["A*01:01", "A*01:02", "A*01:03:01", "A*01:03:02"],
+    ]
+)
 def alleles(request):
     return request.param
 
+
 @pytest.fixture
 def aftab(alleles):
     return simulate_study(alleles, 3, "X")
 
+
 @pytest.fixture
 def expected_freq(aftab):
     aftab = HLAfreq.only_complete(aftab)
     aftab = HLAfreq.decrease_resolution(aftab, 2)
     aftab = HLAfreq.unmeasured_alleles(aftab, "population")
-    grouped = aftab.groupby("allele")[['allele_freq','sample_size']]
-    return grouped.apply(lambda x: np.average(x.allele_freq, weights=x.sample_size*2)).values
-    
+    grouped = aftab.groupby("allele")[["allele_freq", "sample_size"]]
+    return grouped.apply(
+        lambda x: np.average(x.allele_freq, weights=x.sample_size * 2)
+    ).values
+
+
 def test_wav(aftab, expected_freq):
     aftab = HLAfreq.only_complete(aftab)
     aftab = HLAfreq.decrease_resolution(aftab, 2)
     caf = HLAfreq.combineAF(aftab)
     assert caf.wav.values == pytest.approx(expected_freq)
 
+
 def test_combineAF(aftab, expected_freq):
     aftab = HLAfreq.only_complete(aftab)
     aftab = HLAfreq.decrease_resolution(aftab, 2)
     caf = HLAfreq.combineAF(aftab)
     assert caf.allele_freq.values == pytest.approx(expected_freq, rel=5e-2)
 
+
 def test_resolution_check(alleles, aftab):
-    aftab.loc[0,'allele'] = aftab.loc[0,'allele'] + ":00:00"
+    aftab.loc[0, "allele"] = aftab.loc[0, "allele"] + ":00:00"
     with pytest.raises(AssertionError) as e:
         caf = HLAfreq.combineAF(aftab)
     assert "multiple resolutions" in str(e.value)
 
+
 def test_low_res(aftab):
     with pytest.raises(AssertionError) as e:
         HLAfreq.decrease_resolution(aftab, 5)
     assert "resolution below" in str(e.value)
 
+
 def test_single_locus(aftab):
     with pytest.raises(AssertionError) as e:
-        aftab.iloc[0,1] = "Y"
+        aftab.iloc[0, 1] = "Y"
         HLAfreq.combineAF(aftab)
     assert "only 1 loci" in str(e.value)
 
+
 def test_complete(aftab):
     aftab = aftab.drop(0)
     with pytest.raises(AssertionError) as e:
         HLAfreq.combineAF(aftab)
     assert "incomplete_studies" in str(e.value)
 
+
 def test_single_sample_size(aftab):
     aftab = HLAfreq.only_complete(aftab)
     aftab = HLAfreq.decrease_resolution(aftab, 2)
-    aftab.loc[0, 'sample_size'] = 51
+    aftab.loc[0, "sample_size"] = 51
     with pytest.raises(AssertionError) as e:
         caf = HLAfreq.combineAF(aftab)
     assert "dataset_sample_size must be 1" in str(e.value)
 
+
 def test_unique_in_study(aftab):
-    aftab['allele'] = "A*00:00"
+    aftab["allele"] = "A*00:00"
     with pytest.raises(AssertionError) as e:
         caf = HLAfreq.combineAF(aftab)
     assert "same allele appears multiple times" in str(e.value)
@@ -120,12 +133,14 @@ def test_unique_in_study(aftab):
 
 def test_multi_loci_allele_decrease_resolution(aftab):
     aftabB = aftab.copy()
-    aftabB.iloc[0,1] = "Y"
+    aftabB.iloc[0, 1] = "Y"
     aftab = pd.concat([aftab, aftabB])
     with pytest.raises(AssertionError) as e:
         HLAfreq.decrease_resolution(aftab, 2)
-    assert "Multiple loci found for a single allele in a single population" in str(e.value)
-    
+    assert "Multiple loci found for a single allele in a single population" in str(
+        e.value
+    )
+
 
 def test_multi_sample_size_allele_decrease_resolution(aftab):
     aftabB = aftab.copy()
@@ -133,5 +148,7 @@ def test_multi_sample_size_allele_decrease_resolution(aftab):
     aftab = pd.concat([aftab, aftabB])
     with pytest.raises(AssertionError) as e:
         HLAfreq.decrease_resolution(aftab, 2)
-    assert "Multiple sample_sizes found for a single allele in a single population" in str(e.value)
-
+    assert (
+        "Multiple sample_sizes found for a single allele in a single population"
+        in str(e.value)
+    )
diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index c8fe7df..ef56cc9 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -3,6 +3,7 @@
 Tests dropping incomplete studies, merging different resolution
 alleles, and combing allele frequency estimates.
 """
+
 import pytest
 import HLAfreq
 from HLAfreq import HLAfreq_pymc as HLAhdi

From 6dabdec221b71f34e12f45f3b39cf14dd55174b4 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 16:08:54 +0100
Subject: [PATCH 160/192] GHA python linting and testing for push/pull_request
 on main and dev

---
 .github/workflows/python-package.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index a9eebb3..3ccb771 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -5,9 +5,9 @@ name: Python package
 
 on:
   push:
-    branches: [ "main" ]
+    branches: [ "main", "dev" ]
   pull_request:
-    branches: [ "main" ]
+    branches: [ "main", "dev" ]
 
 jobs:
   build:

From ec1d0bf38119214e49cea1975be22d75f62f33ae Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 17:09:23 +0100
Subject: [PATCH 161/192] Move simulation functions to HLAfreq

These functions will be used for multiple tests so should be available
---
 src/HLAfreq/HLAfreq.py       | 28 ++++++++++++++++++++++++++++
 tests/test_simulated_data.py | 29 +----------------------------
 2 files changed, 29 insertions(+), 28 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index bb225b6..c10aea4 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -8,6 +8,7 @@
 global HLA frequencies.
 """
 
+from collections.abc import Iterable
 from bs4 import BeautifulSoup
 import requests
 import pandas as pd
@@ -18,6 +19,33 @@
 import matplotlib.colors as mcolors
 
 
+def simulate_population(alleles: Iterable[str], locus: str, population: str):
+    pop_size = np.random.randint(len(alleles), 50)
+    samples = np.random.choice(alleles, pop_size, replace=True)
+    counts = pd.Series(samples).value_counts()
+    counts.values / pop_size
+    pop = pd.DataFrame(
+        {
+            "allele": counts.index,
+            "loci": locus,
+            "population": population,
+            "allele_freq": counts.values / pop_size,
+            "sample_size": pop_size,
+        }
+    )
+    return pop
+
+
+def simulate_study(alleles, populations, locus):
+    study = []
+    for i in range(populations):
+        pop = simulate_population(alleles=alleles, locus=locus, population=f"pop_{i}")
+        study.append(pop)
+
+    study = pd.concat(study)
+    return study
+
+
 def makeURL(
     country="",
     standard="s",
diff --git a/tests/test_simulated_data.py b/tests/test_simulated_data.py
index f4d4049..94a6aa2 100644
--- a/tests/test_simulated_data.py
+++ b/tests/test_simulated_data.py
@@ -19,33 +19,6 @@ def test_url_string(base_url):
     assert isinstance(base_url, str)
 
 
-def simulate_population(alleles: Iterable[str], locus: str, population: str):
-    pop_size = np.random.randint(len(alleles), 50)
-    samples = np.random.choice(alleles, pop_size, replace=True)
-    counts = pd.Series(samples).value_counts()
-    counts.values / pop_size
-    pop = pd.DataFrame(
-        {
-            "allele": counts.index,
-            "loci": locus,
-            "population": population,
-            "allele_freq": counts.values / pop_size,
-            "sample_size": pop_size,
-        }
-    )
-    return pop
-
-
-def simulate_study(alleles, populations, locus):
-    study = []
-    for i in range(populations):
-        pop = simulate_population(alleles=alleles, locus=locus, population=f"pop_{i}")
-        study.append(pop)
-
-    study = pd.concat(study)
-    return study
-
-
 @pytest.fixture(
     params=[
         ["A*01:01", "A*01:02", "A*01:03"],
@@ -60,7 +33,7 @@ def alleles(request):
 
 @pytest.fixture
 def aftab(alleles):
-    return simulate_study(alleles, 3, "X")
+    return HLAfreq.simulate_study(alleles, 3, "X")
 
 
 @pytest.fixture

From ec30aa0e5dc01bf7508ef8700562726c84252422 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 28 Aug 2024 17:10:16 +0100
Subject: [PATCH 162/192] Write tests for non-pymc functions of HLAfreq_pymc

---
 tests/test_HLAfreq_pymc.py       | 68 ++++++++++++++++++++++++++++++++
 tests/test_simulated_data.py     |  2 +-
 tests/test_single_country_caf.py |  5 ---
 3 files changed, 69 insertions(+), 6 deletions(-)
 create mode 100644 tests/test_HLAfreq_pymc.py

diff --git a/tests/test_HLAfreq_pymc.py b/tests/test_HLAfreq_pymc.py
new file mode 100644
index 0000000..72ba738
--- /dev/null
+++ b/tests/test_HLAfreq_pymc.py
@@ -0,0 +1,68 @@
+import pandas as pd
+import numpy as np
+import pytest
+import HLAfreq
+import HLAfreq.HLAfreq_pymc as HLAhdi
+
+
+@pytest.fixture(
+    params=[
+        ["A*01:01", "A*01:02", "A*01:03"],
+        ["A*01:01:01", "A*01:02:01", "A*01:03:01"],
+        ["A*01:01", "A*01:02", "A*01:03:01"],
+        ["A*01:01", "A*01:02", "A*01:03:01", "A*01:03:02"],
+    ]
+)
+def alleles(request):
+    return request.param
+
+
+@pytest.fixture
+def aftab(alleles):
+    return HLAfreq.simulate_study(alleles, 3, "X")
+
+
+# Not a meaningful test but slow
+# def test_hdi():
+#     hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
+#     assert all(hdi.columns == ["lo", "hi", "allele", "post_mean"])
+
+
+def test_correct_c_array(aftab):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
+    c_pivot = aftab.pivot(columns="allele", index="population", values="c")
+    c_array = HLAhdi._make_c_array(aftab)
+    pytest.approx(c_array[0]) == c_pivot
+
+
+def test_correct_c_array_alleles(aftab):
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+    aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
+    c_pivot = aftab.pivot(columns="allele", index="population", values="c")
+    c_array = HLAhdi._make_c_array(aftab)
+    c_array[1] == c_pivot.columns
+
+
+def test_complete(aftab):
+    aftab = aftab.drop(0)
+    with pytest.raises(AssertionError) as e:
+        HLAhdi._make_c_array(aftab)
+    assert "incomplete_studies" in str(e.value)
+
+
+def test_unique_in_study(aftab):
+    aftab["allele"] = "A*00:00"
+    with pytest.raises(AssertionError) as e:
+        caf = HLAhdi._make_c_array(aftab)
+    assert "same allele appears multiple times" in str(e.value)
+
+
+def test_resolution_check(aftab):
+    aftab.loc[0, "allele"] = aftab.loc[0, "allele"] + ":00:00"
+    with pytest.raises(AssertionError) as e:
+        caf = HLAhdi._make_c_array(aftab)
+    assert "multiple resolutions" in str(e.value)
+
diff --git a/tests/test_simulated_data.py b/tests/test_simulated_data.py
index 94a6aa2..4c2df1d 100644
--- a/tests/test_simulated_data.py
+++ b/tests/test_simulated_data.py
@@ -61,7 +61,7 @@ def test_combineAF(aftab, expected_freq):
     assert caf.allele_freq.values == pytest.approx(expected_freq, rel=5e-2)
 
 
-def test_resolution_check(alleles, aftab):
+def test_resolution_check(aftab):
     aftab.loc[0, "allele"] = aftab.loc[0, "allele"] + ":00:00"
     with pytest.raises(AssertionError) as e:
         caf = HLAfreq.combineAF(aftab)
diff --git a/tests/test_single_country_caf.py b/tests/test_single_country_caf.py
index ef56cc9..b5e7f1d 100644
--- a/tests/test_single_country_caf.py
+++ b/tests/test_single_country_caf.py
@@ -66,8 +66,3 @@ def test_resolution_decreased_correctly():
 def test_combined_allele_freq():
     assert all(caf.allele_freq == dirichlet([8, 12, 13]).mean())
 
-
-# Not a meaningful test but slow
-# def test_hdi():
-#     hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
-#     assert all(hdi.columns == ["lo", "hi", "allele", "post_mean"])

From 87423cabdaa7ae76264c74ff72798b6e92683941 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 29 Aug 2024 09:36:34 +0100
Subject: [PATCH 163/192] Remove data loaders as they are not working and not
 needed

---
 MANIFEST.in                 |  1 -
 README.md                   |  4 +---
 setup.py                    |  1 -
 src/HLAfreq/HLAfreq_data.py | 30 ------------------------------
 4 files changed, 1 insertion(+), 35 deletions(-)
 delete mode 100644 MANIFEST.in
 delete mode 100644 src/HLAfreq/HLAfreq_data.py

diff --git a/MANIFEST.in b/MANIFEST.in
deleted file mode 100644
index 6961c5e..0000000
--- a/MANIFEST.in
+++ /dev/null
@@ -1 +0,0 @@
-include src/HLAfreq/data/*.csv
\ No newline at end of file
diff --git a/README.md b/README.md
index 190d194..5c67fd2 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ ability to mount an immune response to specific epitopes.
 Automated download of allele frequency data download from 
 [allele frequencies.net](http://www.allelefrequencies.net/).
 
-Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
+Full documentation at [HLAfreq/docs](https://BarinthusBio.github.io/HLAfreq/HLAfreq.html). Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
 
 ## Details
 Estimates are combined by modelling allele frequency as a 
@@ -107,8 +107,6 @@ API documentation for functions are under the submodules on the left.
 - `HLAfreq.HLAfreq` documents most functions, specifically download and combine
 allele data.
 - `HLAfreq.HLAfreq_pymc` is functions using pymc to acurately estimate credible intervals on allele frequency estimates.
-- `HLAfreq.HLAfreq_data` contains data loaders to get countries available on
-allelefrequencies.net.
 
 For help on specific functions view the docstring, `help(function_name)`.
 
diff --git a/setup.py b/setup.py
index 722b310..1f27c6a 100644
--- a/setup.py
+++ b/setup.py
@@ -31,5 +31,4 @@
     packages=find_packages(
         where='src'
     ),
-    include_package_data=True,
 )
\ No newline at end of file
diff --git a/src/HLAfreq/HLAfreq_data.py b/src/HLAfreq/HLAfreq_data.py
deleted file mode 100644
index 9fc0399..0000000
--- a/src/HLAfreq/HLAfreq_data.py
+++ /dev/null
@@ -1,30 +0,0 @@
-"""
-Data loaders
-"""
-
-import pkg_resources
-import pandas as pd
-
-
-def load_countries():
-    """Load dataframe of countries and regions available on [allele frequencies.net](http://www.allelefrequencies.net/).
-
-    Returns:
-        pd.DataFrame: Three columns: `Country`, `Region`, and `largeRegion`.
-        `largeRegion` is based on `Region` with with fewer categories to improve
-        plotting.
-    """
-    stream = pkg_resources.resource_stream(__name__, "data/countries.csv")
-    return pd.read_csv(stream, encoding="latin-1")
-
-
-def load_HLA1supertypes_Sidney2008():
-    """Load HLA alleles and their supertype as defined in Sidney2008
-
-    Returns:
-        pd.DataFrame: DataFrame of alleles and their supertype
-    """
-    stream = pkg_resources.resource_stream(
-        __name__, "data/HLA1supertypes_Sidney2008.csv"
-    )
-    return pd.read_csv(stream, encoding="latin-1")

From 802596e8a496acd6f1cc644c6dd8f9c8038d0f4e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 29 Aug 2024 09:57:18 +0100
Subject: [PATCH 164/192] Add documentation link to setup.py

This should render on pypi
---
 setup.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/setup.py b/setup.py
index 1f27c6a..a1bd88f 100644
--- a/setup.py
+++ b/setup.py
@@ -5,6 +5,7 @@
     version="0.0.3.dev2",
     url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
+        'Documentaion': "https://barinthusbio.github.io/HLAfreq/HLAfreq.html",
         'Tracker': "https://github.com/BarinthusBio/HLAfreq/issues"
     },
     author="David Wells",

From 04ac0ec22860bf32762152e689ffe87b8ed60ec9 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 29 Aug 2024 10:12:44 +0100
Subject: [PATCH 165/192] Update version to 0.0.4

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index a1bd88f..774ef7a 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.3.dev2",
+    version="0.0.4",
     url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
         'Documentaion': "https://barinthusbio.github.io/HLAfreq/HLAfreq.html",

From 7753d576afc7bcc70acc5a4c5b57e9125d4daad2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 11 Sep 2024 11:23:49 +0100
Subject: [PATCH 166/192] Update install and troubleshooting guides, add links
 to specific function docs

---
 README.md | 58 ++++++++++++++++++++++++++++++++-----------------------
 1 file changed, 34 insertions(+), 24 deletions(-)

diff --git a/README.md b/README.md
index 5c67fd2..8b27625 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@ and, when paired with epitope prediction, estimating a population's
 ability to mount an immune response to specific epitopes.
 
 Automated download of allele frequency data download from 
-[allele frequencies.net](http://www.allelefrequencies.net/).
+[allelefrequencies.net](http://www.allelefrequencies.net/).
 
 Full documentation at [HLAfreq/docs](https://BarinthusBio.github.io/HLAfreq/HLAfreq.html). Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
 
@@ -29,40 +29,50 @@ supertypes (grouped alleles sharing binding specificies).
 `HLAfreq` is a `python` package available on windows, mac, and linux. We recommend installing
 with `conda`.
 ```
-conda create -n hlafreq -c bioconda -c conda-forge hlafreq
+conda create -n hlafreq -c conda-forge -c bioconda hlafreq
 conda activate hlafreq
 ```
-If you're new to conda see the miniconda [installation guide](https://conda.io/projects/conda/en/stable/user-guide/install/index.html) and [documentation](https://docs.conda.io/projects/conda/en/stable/user-guide/index.html)
-to get started with `conda`.
-Enter the above command into your conda prompt to create and
-activate a conda environment with `HLAfreq` installed.
-Typing `python` into this activated environment will start
-a python session where you can enter your python code such as
-the HLAfreq [minimal example](#minimal-example) below.
-
-If you prefer to write your python code as scripts using an IDE such as
-PyCharm or VScode, you'll need to look up how to configure a conda
-virtual environment with those tools.
 
 ### Troubleshooting
 `HLAfreq` uses `pymc` to estimate credible intervals,
 which is the source of most installation difficulty, see
-[pymc installation guide](https://www.pymc.io/projects/docs/en/stable/installation.html).
+[pymc installation guide](https://www.pymc.io/projects/docs/en/stable/installation.html) and [tips and tricks](https://conda-forge.org/docs/user/tipsandtricks/#using-multiple-channels).
+
+You may see an error about g++ and degraded performance:
+```
+WARNING (pytensor.configdefaults): g++ not detected!  PyTensor will be unable to compile C-implementations and will default to Python. Performance may be severely degraded. To remove this warning, set PyTensor flags cxx to an empty string.
+```
+
+This means that one of the pymc backends is missing and estimating confidence
+intervals will be very slow. But don't worry, try one of these fixes below:
 
-At time of writing `pymc` doesn't play nice with python 3.11, so
-you can try installing a specific `python` version
-and then add `HLAfreq` with pip or conda.
-For example
+- Set the channel priority to strict, then install as above (using conda-forge then bioconda channels).
 ```
-conda create -n hlafreq -c conda-forge -c bioconda python=3.10 numpy=1.25.2 pymc=5.6.1 hlafreq
+conda config --set channel_priority strict
 ```
 
-`HLAfreq` requires `python>=3.8`, `matplotlib>=3.5`, and `pymc>=3`.
-Conda should handle this automatically, but if you get errors check
-the package versions with `conda list`.
+- Install a conda compiler to handle g++ based on your os.
+```
+conda create -n hlafreq -c conda-forge -c bioconda hlafreq cxx-compiler
+```
 
 If you do run into trouble please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues).
 
+### conda
+If you're new to conda see the miniconda [installation guide](https://conda.io/projects/conda/en/stable/user-guide/install/index.html) and [documentation](https://docs.conda.io/projects/conda/en/stable/user-guide/index.html)
+to get started with `conda`.
+
+Enter the install command from above into your conda prompt to create and
+activate a conda environment with `HLAfreq` installed.
+Typing `python` into this activated environment will start
+a python session where you can enter your python code such as
+the HLAfreq [minimal example](#minimal-example) below.
+
+If you prefer to write your python code as scripts using an IDE such as
+PyCharm or VScode, you'll need to look up how to configure a conda
+virtual environment with those tools.
+
+### pip
 If you don't intend to use credible intervals you can install
 with pip: `pip install HLAfreq`.
 However, if you do import `HLAfreq_pymc` you may get warnings
@@ -75,7 +85,7 @@ try installing with conda as described above.
 ## Minimal example
 Download HLA data using `HLAfreq.HLAfreq.makeURL()` and `HLAfreq.HLAfreq.getAFdata()`.
 All arguments that can be specified in the webpage form are available,
-see `help(HLAfreq.makeURL)` for details (press `q` to exit).
+see the [`makeURL()` docs](https://barinthusbio.github.io/HLAfreq/HLAfreq/HLAfreq.html#makeURL) for details.
 ```
 import HLAfreq
 base_url = HLAfreq.makeURL("Uganda", locus="A")
@@ -86,7 +96,7 @@ After downloading the data, it must be filtered so that all studies
 sum to allele frequency 1 (within tolerence). Then we must ensure
 that all studies report alleles at the same resolution.
 Finaly we can combine frequency estimates, for more details see
-the `HLAfreq.HLAfreq.combineAF()` api documentation.
+the [`combineAF()` api documentation](https://barinthusbio.github.io/HLAfreq/HLAfreq/HLAfreq.html#combineAF).
 ```
 aftab = HLAfreq.only_complete(aftab)
 aftab = HLAfreq.decrease_resolution(aftab, 2)

From a074ebaaf84d45e0e22b613d0012d4fdc65e4493 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 11 Oct 2024 06:14:48 +0100
Subject: [PATCH 167/192] Add `example/quickstart` and link in readme.

This provides a callable script to test download, preprocessing, combination, credible intervals, and plotting.
It also uses main guard and multiprocess spawn method to avoid multiprocessing issues on windows
as described in https://docs.python.org/3/library/multiprocessing.html
HLAF-19
---
 README.md              |  3 +++
 examples/quickstart.py | 28 ++++++++++++++++++++++++++++
 2 files changed, 31 insertions(+)
 create mode 100644 examples/quickstart.py

diff --git a/README.md b/README.md
index 8b27625..7cd6a74 100644
--- a/README.md
+++ b/README.md
@@ -103,6 +103,9 @@ aftab = HLAfreq.decrease_resolution(aftab, 2)
 caf = HLAfreq.combineAF(aftab)
 ```
 
+To add confidence intervals to estimates see
+[`examples/quickstart.py`](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/quickstart.py).
+
 ## Detailed examples
 For more detailed walkthroughs see [HLAfreq/examples](https://barinthusbio.github.io/HLAfreq/HLAfreq/examples.html).
 
diff --git a/examples/quickstart.py b/examples/quickstart.py
new file mode 100644
index 0000000..d296a21
--- /dev/null
+++ b/examples/quickstart.py
@@ -0,0 +1,28 @@
+import HLAfreq
+from HLAfreq import HLAfreq_pymc as HLAhdi
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Windows can have issues with multiprocessing in python
+# main guard and spawn method help to execute everything in order
+import multiprocessing
+if __name__ == "__main__":
+    multiprocessing.set_start_method('spawn')
+
+    # Get HLA frequency data
+    base_url = HLAfreq.makeURL("Uganda", locus="A")
+    aftab = HLAfreq.getAFdata(base_url)
+
+    # Preprocess data, checks etc
+    aftab = HLAfreq.only_complete(aftab)
+    aftab = HLAfreq.decrease_resolution(aftab, 2)
+
+    # Combine frequency estimates
+    caf = HLAfreq.combineAF(aftab)
+    # Calculate credible intervals
+    hdi = HLAhdi.AFhdi(aftab, credible_interval=0.95)
+    # Add credible intervals and posterior mean to caf
+    caf = pd.merge(caf, hdi, how="left", on="allele")
+
+    HLAfreq.plotAF(caf, aftab, hdi=hdi, compound_mean=hdi)

From c3f17ac407fbda7047517375278bc646b2496ed2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Fri, 11 Oct 2024 06:28:31 +0100
Subject: [PATCH 168/192] Describe multiprocessing issue in troubleshooting of
 readme

HLAF-19
---
 README.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/README.md b/README.md
index 7cd6a74..8035f95 100644
--- a/README.md
+++ b/README.md
@@ -56,6 +56,12 @@ conda config --set channel_priority strict
 conda create -n hlafreq -c conda-forge -c bioconda hlafreq cxx-compiler
 ```
 
+When running entire scripts on windows, you may see an error about
+"Safe importing of main module", multiprocessing, and starting
+new processes. To fix this, main guard your code with
+`if __name__ == "__main__":` after the `import`s as demonstrated in
+[`examples/quickstart.py`](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/quickstart.py).
+
 If you do run into trouble please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues).
 
 ### conda

From bff71c4c84328d52917819c47f6be16acb5508f7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 14 Oct 2024 09:35:53 +0100
Subject: [PATCH 169/192] Add long timeout for quickstart.py

---
 examples/quickstart.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/quickstart.py b/examples/quickstart.py
index d296a21..7cda737 100644
--- a/examples/quickstart.py
+++ b/examples/quickstart.py
@@ -12,7 +12,7 @@
 
     # Get HLA frequency data
     base_url = HLAfreq.makeURL("Uganda", locus="A")
-    aftab = HLAfreq.getAFdata(base_url)
+    aftab = HLAfreq.getAFdata(base_url, timeout=120)
 
     # Preprocess data, checks etc
     aftab = HLAfreq.only_complete(aftab)

From 6133e9144b89df044dbaf3d76101f501e55e8e46 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 14 Oct 2024 10:51:34 +0100
Subject: [PATCH 170/192] Simply getAFdata timeout message

Raise a new exception without the full details from requests.
Avoids overwhelming the user
---
 src/HLAfreq/HLAfreq.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index c10aea4..21efd57 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -256,7 +256,7 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
     except requests.exceptions.ReadTimeout as e:
         raise Exception(
             "Requests timeout, try a larger `timeout` value for `getAFdata()`"
-        ) from e
+        ) from None
     # How many pages of results
     N = Npages(bs)
     print("%s pages of results" % N)
@@ -271,7 +271,7 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
         except requests.exceptions.ReadTimeout as e:
             raise Exception(
                 "Requests timeout, try a larger `timeout` value for `getAFdata()`"
-            ) from e
+            ) from None
         tab = parseAF(bs)
         tabs.append(tab)
     print("Download complete")

From a379ce3abd9d877f852e53b496ed173b91976fd4 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 14 Oct 2024 11:12:06 +0100
Subject: [PATCH 171/192] update version to 0.0.5

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 774ef7a..76bfbf0 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.4",
+    version="0.0.5",
     url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
         'Documentaion': "https://barinthusbio.github.io/HLAfreq/HLAfreq.html",

From 484f3cdb8f154ec885bf3b1b8d96bb92bc87e4da Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Jan 2025 09:54:13 +0000
Subject: [PATCH 172/192] Clarify dosctring for `only_complete()`

---
 src/HLAfreq/HLAfreq.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 21efd57..8a4f893 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -311,8 +311,9 @@ def incomplete_studies(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
 def only_complete(AFtab, llimit=0.95, ulimit=1.1, datasetID="population"):
     """Returns only complete studies.
 
-    Studies are only dropped if their population and loci are in noncomplete together.
-    This prevents throwing away data if another loci in the population is incomplete
+    Data is dropped if the locus for that population is not complete, i.e. doesn't
+    sum to between `llimit` and `ulimit`. This prevents throwing away data if
+    another loci in the population is incomplete.
 
     Args:
         AFtab (pd.DataFrame): Dataframe containing multiple studies

From 112687b4a17cb5ad97c9b7ddba8d211deb402d3b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 10 Feb 2025 14:05:32 +0000
Subject: [PATCH 173/192] Calculate coverage of just HLA-A

---
 examples/paper/reproduce_paper_results2.py | 32 ++++++++++------------
 1 file changed, 15 insertions(+), 17 deletions(-)

diff --git a/examples/paper/reproduce_paper_results2.py b/examples/paper/reproduce_paper_results2.py
index 2a14ec8..5c444d5 100644
--- a/examples/paper/reproduce_paper_results2.py
+++ b/examples/paper/reproduce_paper_results2.py
@@ -1,6 +1,6 @@
 """
 Download HLA data for all countries and calculate
-population coverage of IEDB set of 27 alleles.
+population coverage of HLA-A IEDB set of 27 alleles.
 
 Plot population coverage in detail for Indonesia.
 
@@ -52,10 +52,11 @@
 
 iedb_cov = []
 iedb_country = []
-# Load and combine within country data for HLA-A and HLA-B separately
+# Load and combine within country data for HLA-A
 # Calculate the proportion of each population with no alleles
-# in the IEDB reference set, assuming no linkage disequilibrium
-# between HLA-A and HLA-B
+# in the IEDB reference set
+# We focus on HLA-A only, because we cannot accurately combine HLA-A and HLA-B data
+# without an estimate of linkage disequilibrium which is usually high between HLA loci
 for country in countries:
     try:
         afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
@@ -64,15 +65,11 @@
         cafa = HLAfreq.combineAF(afa)
         maska = cafa.allele.isin(iedb_ref)
         p = cafa[maska].allele_freq.sum()
-        afb = pd.read_csv(f"data/example/population_coverage/{country}_B_raw.csv")
-        afb = HLAfreq.only_complete(afb)
-        afb = HLAfreq.decrease_resolution(afb, 2)
-        cafb = HLAfreq.combineAF(afb)
-        maskb = cafb.allele.isin(iedb_ref)
-        m = cafb[maskb].allele_freq.sum()
         # Population proportion with no IEDB ref alleles
-        # at HLA A or HLA B
-        coverage = 1 - ((1-p)**2 * (1-m)**2)
+        # at HLA A only
+        q = 1-p
+        coverage = 1 - q**2
+        assert coverage == (p**2) + (2*p*q), f"Inconsistent coverage calculation: {country}"
         iedb_cov.append(coverage)
         iedb_country.append(country)
     except:
@@ -83,8 +80,7 @@
 df = pd.merge(df, regions, how="left", left_on="country", right_on="Country")
 
 # Plot the proportion of each population with no alleles
-# in the IEDB reference set, assuming no linkage disequilibrium
-# between HLA-A and HLA-B
+# in the IEDB reference set, for HLA-A only
 plt.barh(df.country, df.coverage, color="black")
 regions = df.largeRegion.unique()
 regions.sort()
@@ -92,17 +88,19 @@
     mask = df.largeRegion == region
     plt.barh(df[mask].country, df[mask].coverage, label=region, zorder=3)
 
-plt.axvline(0.97, linestyle="--", c="black", zorder=5)
+plt.axvline(
+    df.coverage.mean(),
+    linestyle="--", c="black", zorder=5)
 plt.tight_layout()
 plt.legend(loc="upper left")
 plt.grid(zorder=0)
 plt.show()
 
 ##############
-# Plot cumulative frequency of IEDB panel
+# Plot cumulative frequency of HLA-A in IEDB panel
 # vs
 # country specific alleles
-#A
+# A
 country = "Indonesia"
 afa = pd.read_csv(f"data/example/population_coverage/{country}_A_raw.csv")
 afa = HLAfreq.only_complete(afa)

From b57b8bd09684293b02d9109f21485bf9b9cf033f Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 16 Sep 2025 00:25:28 +0100
Subject: [PATCH 174/192] Add contribution and community guidlines

---
 CONTRIBUTING.md | 36 ++++++++++++++++++++++++++++++++++++
 README.md       |  7 +++++++
 2 files changed, 43 insertions(+)
 create mode 100644 CONTRIBUTING.md

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
new file mode 100644
index 0000000..acb7720
--- /dev/null
+++ b/CONTRIBUTING.md
@@ -0,0 +1,36 @@
+# Community guidelines
+Thank you for using `HLAfreq`!
+It's great that you'd like to contribute in any form!
+Asking questions as issues is an important contribution.
+See below for particular information to include. If you see an
+issue you can help with, your answer would be greatly appreciated.
+When creating or answering issues please be kind!
+
+## Seek support
+If you need help using this tool, the first port of call is the
+examples and documentation [here](https://barinthusbio.github.io/HLAfreq/HLAfreq.html).
+But if the answer is not there, please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues).
+
+## Report problems with the software
+If the software isn't working or you think you've found a bug,
+please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues). Please include:
+- the version of `HLAfreq`
+- code to reproduce the error
+- any error message/the result
+- what you expected/think should have happened instead
+
+## Contribute to the software
+If you want to add to `epitope_aligner` that's great! Fork the
+repo and create a branch named after the change you're making.
+Make your contribution to the new branch on your fork and add
+tests to verify that your code runs as expected. The tests should
+pass when run by nox before submitting a pull request. See this
+[guide](https://learn.scientific-python.org/development/guides/tasks/)
+on using nox.
+
+When you're happy with your changes and the tests are passing,
+submit a pull request. In the pull request describe the motivation
+for your changes, their impact, and the tests you have written for
+them.
+
+# Thank you for contributing!
\ No newline at end of file
diff --git a/README.md b/README.md
index 8035f95..0f2029d 100644
--- a/README.md
+++ b/README.md
@@ -134,6 +134,13 @@ documentation in `./docs`.
 <!-- Documentation generated by pdoc should not be commited
 as it is auto generated by a github action. -->
 
+## Community guidelines
+Thank you for using `HLAfreq`! Contributions in any form
+are immensely helpful: asking questions, answering issues,
+and pull requests are all great.
+
+For full details see [CONTRIBUTING.md](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/quickstart.py). In short, if the answer to
+your question is not in the docs, open an [issue](https://github.com/BarinthusBio/HLAfreq/issues). If you'd like to improve `HLAfreq` create a fork and a pull request.
 
 <!-- ## Developer notes
 Install in dev mode

From 53f878a3d841c690168cd879d038d3fd41765f9e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Sun, 11 Jan 2026 12:37:39 +0000
Subject: [PATCH 175/192] Add python 3.13 and 3.14 to tests

---
 .github/workflows/python-package.yaml | 2 +-
 noxfile.py                            | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index 3ccb771..fa042c3 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
 
     steps:
     - uses: actions/checkout@v4
diff --git a/noxfile.py b/noxfile.py
index 95268e8..0b10863 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -13,7 +13,7 @@ def bandit(session):
     session.install("bandit")
     session.run("bandit", "-r", "src")
 
-@nox.session(python=["3.10", "3.11", "3.12"])
+@nox.session(python=["3.10", "3.11", "3.12", "3.13", "3.14"])
 def tests(session):
     session.install("pytest", "pytest-cov")
     session.install(".")

From 58ccec839324d6b9153d64690838e29ecd54a3da Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Sun, 11 Jan 2026 13:10:39 +0000
Subject: [PATCH 176/192] Update install instructions

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0f2029d..d15089b 100644
--- a/README.md
+++ b/README.md
@@ -29,7 +29,7 @@ supertypes (grouped alleles sharing binding specificies).
 `HLAfreq` is a `python` package available on windows, mac, and linux. We recommend installing
 with `conda`.
 ```
-conda create -n hlafreq -c conda-forge -c bioconda hlafreq
+conda create -n hlafreq bioconda::hlafreq
 conda activate hlafreq
 ```
 

From 395cec43819297efd773fb9388453ecce8a8da87 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Sun, 8 Mar 2026 19:23:17 +0000
Subject: [PATCH 177/192] git push fix contribution linnk

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index d15089b..ad7136e 100644
--- a/README.md
+++ b/README.md
@@ -139,7 +139,7 @@ Thank you for using `HLAfreq`! Contributions in any form
 are immensely helpful: asking questions, answering issues,
 and pull requests are all great.
 
-For full details see [CONTRIBUTING.md](https://github.com/BarinthusBio/HLAfreq/blob/main/examples/quickstart.py). In short, if the answer to
+For full details see [CONTRIBUTING.md](https://github.com/BarinthusBio/HLAfreq/blob/main/CONTRIBUTING.md). In short, if the answer to
 your question is not in the docs, open an [issue](https://github.com/BarinthusBio/HLAfreq/issues). If you'd like to improve `HLAfreq` create a fork and a pull request.
 
 <!-- ## Developer notes

From f753c9b9cedb73ce525480671534a5a069512479 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Sun, 8 Mar 2026 19:23:47 +0000
Subject: [PATCH 178/192] Remove reference to epitope_aligner

---
 CONTRIBUTING.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index acb7720..67a1169 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -20,7 +20,7 @@ please open an [issue](https://github.com/BarinthusBio/HLAfreq/issues). Please i
 - what you expected/think should have happened instead
 
 ## Contribute to the software
-If you want to add to `epitope_aligner` that's great! Fork the
+If you want to add to `HLAfreq` that's great! Fork the
 repo and create a branch named after the change you're making.
 Make your contribution to the new branch on your fork and add
 tests to verify that your code runs as expected. The tests should

From 1dd3eb1aeb9c5425ec98f97c3dd1ef5cbb6b6c49 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 17 Mar 2026 16:10:00 +0000
Subject: [PATCH 179/192] add asserts to `test_correct_c_array` and
 `test_correct_c_array_alleles`

---
 tests/test_HLAfreq_pymc.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/test_HLAfreq_pymc.py b/tests/test_HLAfreq_pymc.py
index 72ba738..3167b06 100644
--- a/tests/test_HLAfreq_pymc.py
+++ b/tests/test_HLAfreq_pymc.py
@@ -34,7 +34,7 @@ def test_correct_c_array(aftab):
     aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
     c_pivot = aftab.pivot(columns="allele", index="population", values="c")
     c_array = HLAhdi._make_c_array(aftab)
-    pytest.approx(c_array[0]) == c_pivot
+    assert pytest.approx(c_array[0]) == c_pivot
 
 
 def test_correct_c_array_alleles(aftab):
@@ -43,7 +43,7 @@ def test_correct_c_array_alleles(aftab):
     aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
     c_pivot = aftab.pivot(columns="allele", index="population", values="c")
     c_array = HLAhdi._make_c_array(aftab)
-    c_array[1] == c_pivot.columns
+    assert all(c_array[1] == c_pivot.columns)
 
 
 def test_complete(aftab):

From 3357b84d6a3355315738801ca51eea30c68ca9b0 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Wed, 18 Mar 2026 23:48:08 +0000
Subject: [PATCH 180/192] check data type using is_string_dtype to handle
 pandas 3 update  thanks to @usethedata for diving in to this
 https://github.com/openjournals/joss-reviews/issues/10122#issuecomment-4020246959

---
 src/HLAfreq/HLAfreq.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 8a4f893..30b44c1 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -226,9 +226,9 @@ def formatAF(AFtab, ignoreG=True):
         pd.DataFrame: The formatted allele frequency data.
     """
     df = AFtab.copy()
-    if df.sample_size.dtype == "O":
+    if pd.api.types.is_string_dtype(df.sample_size.dtype):
         df.sample_size = pd.to_numeric(df.sample_size.str.replace(",", ""))
-    if df.allele_freq.dtype == "O":
+    if pd.api.types.is_string_dtype(df.allele_freq.dtype):
         if ignoreG:
             df.allele_freq = df.allele_freq.str.replace("(*)", "", regex=False)
         df.allele_freq = pd.to_numeric(df.allele_freq)

From 60e1c0fab3d7bbff5d5a70f8ef4229e2380afbda Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 19 Mar 2026 00:22:28 +0000
Subject: [PATCH 181/192] use https for url links

---
 README.md                                  |  2 +-
 examples/paper/reproduce_paper_results2.py |  2 +-
 examples/paper/reproduce_paper_results3.py |  2 +-
 src/HLAfreq/HLAfreq.py                     | 12 ++++++------
 4 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/README.md b/README.md
index ad7136e..3525159 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@ and, when paired with epitope prediction, estimating a population's
 ability to mount an immune response to specific epitopes.
 
 Automated download of allele frequency data download from 
-[allelefrequencies.net](http://www.allelefrequencies.net/).
+[allelefrequencies.net](https://www.allelefrequencies.net/).
 
 Full documentation at [HLAfreq/docs](https://BarinthusBio.github.io/HLAfreq/HLAfreq.html). Source code is available at [BarinthusBio/HLAfreq](https://github.com/BarinthusBio/HLAfreq).
 
diff --git a/examples/paper/reproduce_paper_results2.py b/examples/paper/reproduce_paper_results2.py
index 5c444d5..c740689 100644
--- a/examples/paper/reproduce_paper_results2.py
+++ b/examples/paper/reproduce_paper_results2.py
@@ -27,7 +27,7 @@
 iedb_refb = [i for i in iedb_ref if "B" in i]
 
 # Download countries in regions as defined on 
-# http://www.allelefrequencies.net/datasets.asp#tag_4
+# https://www.allelefrequencies.net/datasets.asp#tag_4
 r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)
diff --git a/examples/paper/reproduce_paper_results3.py b/examples/paper/reproduce_paper_results3.py
index 5184618..62ec9fe 100644
--- a/examples/paper/reproduce_paper_results3.py
+++ b/examples/paper/reproduce_paper_results3.py
@@ -26,7 +26,7 @@
     pass
 
 # Download countries in regions as defined on 
-# http://www.allelefrequencies.net/datasets.asp#tag_4
+# https://www.allelefrequencies.net/datasets.asp#tag_4
 r = requests.get("https://raw.githubusercontent.com/BarinthusBio/HLAfreq/main/data/example/countries.csv")
 with open("data/example/countries.csv", "w") as f:
     f.write(r.text)
diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 30b44c1..96c8be2 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -63,7 +63,7 @@ def makeURL(
 ):
     """Create URL for search of allele frequency net database.
 
-    All arguments are documented [here](http://www.allelefrequencies.net/extaccess.asp)
+    All arguments are documented [here](https://www.allelefrequencies.net/extaccess.asp)
 
     Args:
         country (str, optional): Country name to retrieve records from. Defaults to "".
@@ -78,10 +78,10 @@ def makeURL(
             created using `resolution` and `resolution_pattern`. Defaults to 2.
         region (str, optional): Filter to geographic region. {Asia, Australia,
             Eastern Europe, ...}.
-            All regions listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            All regions listed [here](https://www.allelefrequencies.net/pop6003a.asp).
             Defaults to "".
         ethnic (str, optional): Filter to ethnicity. {"Amerindian", "Black", "Caucasian", ...}.
-            All ethnicities listed [here](http://www.allelefrequencies.net/pop6003a.asp).
+            All ethnicities listed [here](https://www.allelefrequencies.net/pop6003a.asp).
             Defaults to "".
         study_type (str, optional): Type of study. {"Anthropology", "Blood+Donor",
             "Bone+Marrow+Registry", "Controls+for+Disease+Study", "Disease+Study+Patients",
@@ -104,7 +104,7 @@ def makeURL(
     Returns:
         str: URL to search allelefrequencies.net
     """
-    base = "http://www.allelefrequencies.net/hla6006a.asp?"
+    base = "https://www.allelefrequencies.net/hla6006a.asp?"
     locus_type = "hla_locus_type=Classical&"
     hla_locus = "hla_locus=%s&" % (locus)
     country = "hla_country=%s&" % (country)
@@ -220,7 +220,7 @@ def formatAF(AFtab, ignoreG=True):
         AFtab (pd.DataFrame): Allele frequency data downloaded from allelefrequency.net
             using `getAFdata()`.
         ignoreG (bool, optional): Treat G group alleles as normal.
-            See http://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
+            See https://hla.alleles.org/alleles/g_groups.html for details. Defaults to True.
 
     Returns:
         pd.DataFrame: The formatted allele frequency data.
@@ -245,7 +245,7 @@ def getAFdata(base_url, timeout=20, format=True, ignoreG=True):
         timeout (int): How long to wait to receive a response.
         format (bool): Format the downloaded data using `formatAF()`.
         ignoreG (bool): treat allele G groups as normal.
-            See http://hla.alleles.org/alleles/g_groups.html for details. Default = True
+            See https://hla.alleles.org/alleles/g_groups.html for details. Default = True
 
     Returns:
         pd.DataFrame: allele frequency data parsed into a pandas dataframe

From d984e475180d9064dead9b86ea701f8787056fb2 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 19 Mar 2026 00:43:11 +0000
Subject: [PATCH 182/192] avoid depreciation warning by setting include_groups
 for .apply on grouped data

---
 src/HLAfreq/HLAfreq.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/src/HLAfreq/HLAfreq.py b/src/HLAfreq/HLAfreq.py
index 96c8be2..61452de 100644
--- a/src/HLAfreq/HLAfreq.py
+++ b/src/HLAfreq/HLAfreq.py
@@ -393,7 +393,8 @@ def collapse_reduced_alleles(AFtab, datasetID="population"):
             row.loci.unique()[0],
             len(row.loci.unique()),
             len(row.sample_size.unique()),
-        ]
+        ],
+        include_groups=False
     )
     collapsed = pd.DataFrame(
         collapsed.tolist(),
@@ -555,7 +556,8 @@ def combineAF(
             np.average(row.allele_freq, weights=row[weights]),
             row.c.sum(),
             row.sample_size.sum(),
-        ]
+        ],
+        include_groups=False
     )
     combined = pd.DataFrame(
         combined.tolist(), columns=["allele", "loci", "wav", "c", "sample_size"]

From 9ed2227b3798daf18db88e6f6bd5cb9a32b3d743 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 19 Mar 2026 00:58:03 +0000
Subject: [PATCH 183/192] update to version 0.0.6

---
 setup.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/setup.py b/setup.py
index 76bfbf0..1aba31b 100644
--- a/setup.py
+++ b/setup.py
@@ -2,7 +2,7 @@
 
 setup(
     name="HLAfreq",
-    version="0.0.5",
+    version="0.0.6",
     url="https://github.com/BarinthusBio/HLAfreq",
     project_urls={
         'Documentaion': "https://barinthusbio.github.io/HLAfreq/HLAfreq.html",

From 7d3450453ba4f403f60cc338912a830d9b8c4ed7 Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Mon, 6 Apr 2026 23:48:33 +0100
Subject: [PATCH 184/192] Fix `test_correct_c_array` test

Fill missing values in pivot with zero to match make_c_array where zeros are important.
---
 tests/test_HLAfreq_pymc.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_HLAfreq_pymc.py b/tests/test_HLAfreq_pymc.py
index 3167b06..7bb2532 100644
--- a/tests/test_HLAfreq_pymc.py
+++ b/tests/test_HLAfreq_pymc.py
@@ -33,6 +33,7 @@ def test_correct_c_array(aftab):
     aftab = HLAfreq.decrease_resolution(aftab, 2)
     aftab['c'] = 2 * aftab.allele_freq * aftab.sample_size
     c_pivot = aftab.pivot(columns="allele", index="population", values="c")
+    c_pivot = c_pivot.fillna(0)
     c_array = HLAhdi._make_c_array(aftab)
     assert pytest.approx(c_array[0]) == c_pivot
 

From 3124b9c1e6620eb003e69f93dad64c3c365e5531 Mon Sep 17 00:00:00 2001
From: DAWells <49305334+DAWells@users.noreply.github.com>
Date: Tue, 7 Apr 2026 00:00:25 +0100
Subject: [PATCH 185/192] Create dependabot.yml

---
 .github/dependabot.yml | 12 ++++++++++++
 1 file changed, 12 insertions(+)
 create mode 100644 .github/dependabot.yml

diff --git a/.github/dependabot.yml b/.github/dependabot.yml
new file mode 100644
index 0000000..8593f64
--- /dev/null
+++ b/.github/dependabot.yml
@@ -0,0 +1,12 @@
+# To get started with Dependabot version updates, you'll need to specify which
+# package ecosystems to update and where the package manifests are located.
+# Please see the documentation for all configuration options:
+# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
+
+version: 2
+updates:
+  - package-ecosystem: "pip" # See documentation for possible values
+    directory: "/" # Location of package manifests
+    schedule:
+      interval: "weekly"
+    cooldown: "14 days"

From 3e1a9b819c721d34098678fd90c2f6143234b06b Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Tue, 7 Apr 2026 00:11:09 +0100
Subject: [PATCH 186/192] fix dependabot cool down param

---
 .github/dependabot.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 8593f64..194ab66 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -9,4 +9,5 @@ updates:
     directory: "/" # Location of package manifests
     schedule:
       interval: "weekly"
-    cooldown: "14 days"
+    cooldown:
+      default-days: 14

From 5dbb9f0685d5dde7336f893b5bce3af7ec1b1d3e Mon Sep 17 00:00:00 2001
From: DAWells <david.arthur.wells@gmail.com>
Date: Thu, 9 Apr 2026 02:18:44 +0100
Subject: [PATCH 187/192] add github actions to dependabot

---
 .github/dependabot.yml | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 194ab66..ca9bc34 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -11,3 +11,9 @@ updates:
       interval: "weekly"
     cooldown:
       default-days: 14
+  - package-ecosystem: "github-actions" # See documentation for possible values
+    directory: "/" # Location of package manifests
+    schedule:
+      interval: "weekly"
+    cooldown:
+      default-days: 14

From 0b3200e25e4f9ef82906a0c4ce80602ba7eafb51 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 9 Apr 2026 01:19:25 +0000
Subject: [PATCH 188/192] Bump actions/checkout from 4 to 6

Bumps [actions/checkout](https://github.com/actions/checkout) from 4 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/docs.yaml           | 2 +-
 .github/workflows/python-package.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index cf281e0..515e9b5 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -18,7 +18,7 @@ jobs:
   build:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
       - uses: actions/setup-python@v5
         with:
           python-version: '3.12'
diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index fa042c3..813a55d 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -19,7 +19,7 @@ jobs:
         python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
     - name: Set up Python ${{ matrix.python-version }}
       uses: actions/setup-python@v3
       with:

From 807f7092785de41b27825f411ebc3fc4f444adcc Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 9 Apr 2026 01:19:30 +0000
Subject: [PATCH 189/192] Bump actions/deploy-pages from 4 to 5

Bumps [actions/deploy-pages](https://github.com/actions/deploy-pages) from 4 to 5.
- [Release notes](https://github.com/actions/deploy-pages/releases)
- [Commits](https://github.com/actions/deploy-pages/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/deploy-pages
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/docs.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index cf281e0..ae9da11 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -49,4 +49,4 @@ jobs:
       url: ${{ steps.deployment.outputs.page_url }}
     steps:
       - id: deployment
-        uses: actions/deploy-pages@v4
\ No newline at end of file
+        uses: actions/deploy-pages@v5
\ No newline at end of file

From 7a790ced5c5898e419bd622bff7891e99a824885 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 9 Apr 2026 01:19:41 +0000
Subject: [PATCH 190/192] Bump actions/upload-pages-artifact from 3 to 4

Bumps [actions/upload-pages-artifact](https://github.com/actions/upload-pages-artifact) from 3 to 4.
- [Release notes](https://github.com/actions/upload-pages-artifact/releases)
- [Commits](https://github.com/actions/upload-pages-artifact/compare/v3...v4)

---
updated-dependencies:
- dependency-name: actions/upload-pages-artifact
  dependency-version: '4'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/docs.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index cf281e0..0994599 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -32,7 +32,7 @@ jobs:
       # - run: python docs/make.py
       - run: pdoc -d google -o docs/ HLAfreq
       - run: jupyter nbconvert --to html --output-dir docs/HLAfreq/examples examples/*.ipynb
-      - uses: actions/upload-pages-artifact@v3
+      - uses: actions/upload-pages-artifact@v4
         with:
           path: docs/
 

From 9c0513ead2b37aa4ae22f2c4de37fab72101794d Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Thu, 9 Apr 2026 01:24:41 +0000
Subject: [PATCH 191/192] Bump actions/setup-python from 3 to 6

Bumps [actions/setup-python](https://github.com/actions/setup-python) from 3 to 6.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v3...v6)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/docs.yaml           | 2 +-
 .github/workflows/python-package.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index 32747f6..6229757 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -19,7 +19,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v6
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.12'
 
diff --git a/.github/workflows/python-package.yaml b/.github/workflows/python-package.yaml
index 813a55d..0f7d230 100644
--- a/.github/workflows/python-package.yaml
+++ b/.github/workflows/python-package.yaml
@@ -21,7 +21,7 @@ jobs:
     steps:
     - uses: actions/checkout@v6
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v6
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies

From c3814622febb1ff337f55e5544b60c34fe84a294 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 28 Apr 2026 01:06:17 +0000
Subject: [PATCH 192/192] Bump actions/upload-pages-artifact from 4 to 5

Bumps [actions/upload-pages-artifact](https://github.com/actions/upload-pages-artifact) from 4 to 5.
- [Release notes](https://github.com/actions/upload-pages-artifact/releases)
- [Commits](https://github.com/actions/upload-pages-artifact/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/upload-pages-artifact
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
---
 .github/workflows/docs.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml
index 39b0e64..013798f 100644
--- a/.github/workflows/docs.yaml
+++ b/.github/workflows/docs.yaml
@@ -32,7 +32,7 @@ jobs:
       # - run: python docs/make.py
       - run: pdoc -d google -o docs/ HLAfreq
       - run: jupyter nbconvert --to html --output-dir docs/HLAfreq/examples examples/*.ipynb
-      - uses: actions/upload-pages-artifact@v4
+      - uses: actions/upload-pages-artifact@v5
         with:
           path: docs/