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mariusvniekerk/Conda-forge timelines.ipynb

Last active June 28, 2019 02:40
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Conda-forge timelines.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"arches = ['linux-64', 'win-64', 'osx-64', 'noarch', 'linux-ppc64le', 'linux-aarch64']"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"!rm *.json"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 36.9M 100 36.9M 0 0 71.3M 0 --:--:-- --:--:-- --:--:-- 71.3M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 28.6M 0 28.6M 0 0 23.9M 0 --:--:-- 0:00:01 --:--:-- 23.9M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 27.8M 100 27.8M 0 0 84.4M 0 --:--:-- --:--:-- --:--:-- 84.4M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 23.9M 0 23.9M 0 0 24.1M 0 --:--:-- --:--:-- --:--:-- 24.0M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 36.0M 100 36.0M 0 0 91.2M 0 --:--:-- --:--:-- --:--:-- 91.2M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 27.9M 0 27.9M 0 0 25.2M 0 --:--:-- 0:00:01 --:--:-- 25.2M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 6496k 100 6496k 0 0 26.4M 0 --:--:-- --:--:-- --:--:-- 26.4M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 3935k 0 3935k 0 0 13.0M 0 --:--:-- --:--:-- --:--:-- 13.0M\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 613k 100 613k 0 0 3715k 0 --:--:-- --:--:-- --:--:-- 3715k\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 1789 0 1789 0 0 9221 0 --:--:-- --:--:-- --:--:-- 9221\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 611k 100 611k 0 0 4665k 0 --:--:-- --:--:-- --:--:-- 4630k\n",
" % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 146 100 146 0 0 626 0 --:--:-- --:--:-- --:--:-- 626\n"
]
}
],
"source": [
"for a in arches:\n",
" !curl https://conda.anaconda.org/conda-forge/{a}/repodata.json -o repodata-{a}.json\n",
" !curl https://conda.anaconda.org/conda-forge/label/cf201901/{a}/repodata.json -o repodata-cf201901-{a}.json"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import glob"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"packages = []\n",
"for f in glob.glob('*.json'):\n",
" dat = pd.io.json.loads(open(f).read())\n",
" df = pd.DataFrame(dat['packages'].values())\n",
" df.loc[:, 'filename'] = dat['packages'].keys()\n",
" packages.append(df)\n",
" #packages (df['packages'].items())"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"df = pd.concat(packages, sort=False, ignore_index=True)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"df = df.drop_duplicates(subset=['subdir', 'filename'])"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/srv/conda/envs/notebook/lib/python3.6/site-packages/pandas/core/indexing.py:543: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
" self.obj[item] = s\n"
]
}
],
"source": [
"df.loc[:, 'timestamp'] = pd.to_datetime(df.timestamp, unit='ms')"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"198710"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Almost 200 thousand artifacts. Due to us only pulling from master packages that got deprecated during the compiler migration are excluded from\n",
"this analysis."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"97318"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.timestamp.isnull().sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Around half of the packages do not have a creation timestamp in their metadata. thus we kinda have to ignore them"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"has_ts = df[df.timestamp.notnull()]"
]
},
{
"cell_type": "code",
"execution_count": 39,
"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>arch</th>\n",
" <th>binstar</th>\n",
" <th>build</th>\n",
" <th>build_number</th>\n",
" <th>depends</th>\n",
" <th>has_prefix</th>\n",
" <th>license</th>\n",
" <th>license_family</th>\n",
" <th>machine</th>\n",
" <th>md5</th>\n",
" <th>...</th>\n",
" <th>app_type</th>\n",
" <th>constrains</th>\n",
" <th>features</th>\n",
" <th>icon</th>\n",
" <th>summary</th>\n",
" <th>track_features</th>\n",
" <th>type</th>\n",
" <th>app_own_environment</th>\n",
" <th>sha256</th>\n",
" <th>noarch</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ppc64le</td>\n",
" <td>{'package_id': '5a5e1013000a2711ef15d445', 'ch...</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>[]</td>\n",
" <td>False</td>\n",
" <td>MIT</td>\n",
" <td>MIT</td>\n",
" <td>ppc64le</td>\n",
" <td>04788aad2e35bb2aad48c6f06bd7aff9</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ppc64le</td>\n",
" <td>{'package_id': '5a8ef48d82e5d2123f7134ac', 'ch...</td>\n",
" <td>0</td>\n",
" <td>0.0</td>\n",
" <td>[anaconda-client, conda &gt;=4.3, conda-build 3.*...</td>\n",
" <td>True</td>\n",
" <td>BSD 3-clause</td>\n",
" <td>NaN</td>\n",
" <td>ppc64le</td>\n",
" <td>2951d30c96b57f062b17ded6cb009ddf</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ppc64le</td>\n",
" <td>{'package_id': '5952cb319cf1641271f72e97', 'ch...</td>\n",
" <td>h14c3975_1</td>\n",
" <td>1.0</td>\n",
" <td>[libgcc-ng &gt;=7.2.0]</td>\n",
" <td>False</td>\n",
" <td>MIT</td>\n",
" <td>MIT</td>\n",
" <td>ppc64le</td>\n",
" <td>2b543f5fcdcf3cdbec3e3667c41139b9</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>x86_64</td>\n",
" <td>{'package_id': '57826f8590f99a56c159197a', 'ch...</td>\n",
" <td>py36_0</td>\n",
" <td>0.0</td>\n",
" <td>[certifi &gt;=2016.09, python &gt;=3.6,&lt;3.7.0a0]</td>\n",
" <td>True</td>\n",
" <td>MIT</td>\n",
" <td>MIT</td>\n",
" <td>x86_64</td>\n",
" <td>0f8096d32b2c2c7f06d6fdbd601bdd48</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>x86_64</td>\n",
" <td>{'package_id': '5aaa76d50b42f311f7874ace', 'ch...</td>\n",
" <td>h81701ea_1</td>\n",
" <td>1.0</td>\n",
" <td>[terraform &gt;=0.10]</td>\n",
" <td>False</td>\n",
" <td>MPL 2.0</td>\n",
" <td>NaN</td>\n",
" <td>x86_64</td>\n",
" <td>b13d007300776a02c98d7a666bab670d</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 31 columns</p>\n",
"</div>"
],
"text/plain": [
" arch binstar build \\\n",
"0 ppc64le {'package_id': '5a5e1013000a2711ef15d445', 'ch... 0 \n",
"1 ppc64le {'package_id': '5a8ef48d82e5d2123f7134ac', 'ch... 0 \n",
"2 ppc64le {'package_id': '5952cb319cf1641271f72e97', 'ch... h14c3975_1 \n",
"3 x86_64 {'package_id': '57826f8590f99a56c159197a', 'ch... py36_0 \n",
"4 x86_64 {'package_id': '5aaa76d50b42f311f7874ace', 'ch... h81701ea_1 \n",
"\n",
" build_number depends has_prefix \\\n",
"0 0.0 [] False \n",
"1 0.0 [anaconda-client, conda >=4.3, conda-build 3.*... True \n",
"2 1.0 [libgcc-ng >=7.2.0] False \n",
"3 0.0 [certifi >=2016.09, python >=3.6,<3.7.0a0] True \n",
"4 1.0 [terraform >=0.10] False \n",
"\n",
" license license_family machine md5 \\\n",
"0 MIT MIT ppc64le 04788aad2e35bb2aad48c6f06bd7aff9 \n",
"1 BSD 3-clause NaN ppc64le 2951d30c96b57f062b17ded6cb009ddf \n",
"2 MIT MIT ppc64le 2b543f5fcdcf3cdbec3e3667c41139b9 \n",
"3 MIT MIT x86_64 0f8096d32b2c2c7f06d6fdbd601bdd48 \n",
"4 MPL 2.0 NaN x86_64 b13d007300776a02c98d7a666bab670d \n",
"\n",
" ... app_type constrains features icon summary track_features type \\\n",
"0 ... NaN NaN NaN NaN NaN NaN NaN \n",
"1 ... NaN NaN NaN NaN NaN NaN NaN \n",
"2 ... NaN NaN NaN NaN NaN NaN NaN \n",
"3 ... NaN NaN NaN NaN NaN NaN NaN \n",
"4 ... NaN NaN NaN NaN NaN NaN NaN \n",
"\n",
" app_own_environment sha256 noarch \n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
"[5 rows x 31 columns]"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"has_ts.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f69a806ca20>"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x648 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fill_val = '2018-03-01'\n",
"df_has = df.fillna(pd.to_datetime(fill_val)).sort_values('timestamp').set_index('timestamp')\n",
"df_has.loc[:, 'package_count'] = list(range(1, len(df_has)+1))\n",
"df_arrival = df_has.groupby(df_has.index.to_period('M')).package_count.max()\n",
"df_arrival[df_arrival.index > fill_val].plot(\n",
" title='Number of artifacts across all platforms',\n",
" ylim=(0, df_arrival.max() * 1.1),\n",
" figsize=(16,9)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f69a80d60b8>"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x648 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fill_val = '2018-03-01'\n",
"x = df.sort_values('timestamp').fillna(pd.to_datetime(fill_val)).groupby(df.name).first()\n",
"first_date = pd.DataFrame(x.timestamp).reset_index().set_index('timestamp').sort_index()\n",
"first_date.loc[:, 'package_count'] = list(range(1, len(first_date)+1))\n",
"df_first = first_date.groupby(first_date.index.to_period('M')).package_count.max()\n",
"df_first[df_first.index > fill_val].plot(\n",
" title=\"Number of packages over time\",\n",
" ylim=(0, df_first.max() * 1.1),\n",
" figsize=(16,9)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [],
"source": [
"arch_df = {}\n",
"for arch in arches:\n",
" fill_val = '2018-03-01'\n",
" x = df.sort_values('timestamp').fillna(pd.to_datetime(fill_val)).loc[df.subdir == arch].groupby(df.name).first()\n",
" first_date = pd.DataFrame(x.timestamp).reset_index().set_index('timestamp').sort_index()\n",
" first_date.loc[:, 'package_count'] = list(range(1, len(first_date)+1))\n",
" df_first = first_date.groupby(first_date.index.to_period('W')).package_count.max()\n",
" arch_df[arch] = df_first"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f69a7e58390>"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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8r4tqm3C3tncpH2JQxJmNxFmMJEWFMTbZis3/umN9nMWIzWzEZAxG/bL740pY7QW33HILL7/8MlFRUWe9T11dHffccw/79u1DKcWqVauYOHFiYPvy5cv50Y9+RGVlJTabrTeaLYQQQgghhLiMedvacXq8NLp9D6fHi9PT2uV1o7sVp9tLtauFotpmimqaqHG1dKnHbAwmOSaCNJuJqUPjSI6JIDkmHEd0BPEWI9bwEJRSF9xeCau94K233jrnfRYvXszMmTNZu3YtLS0tNDU1BbYVFRXxzjvvMHjw4IvZTCGEEEIIIcRlxN3axtHqJvIqneRVOH3PlS7KGtw43V6aW9vOWIchSGEJCyYqPITkmAhmjExgsD+MDo6JIDk6gqiIixNGz0TC6nl48sknCQsLY9GiRSxZsoTdu3ezadMm3nvvPVavXs3WrVvJzc3F6XRy8803M3nyZD7++GOSkpJ4/fXXCQ8P71JfQ0MDH374IWvWrAEgNDSU0NDQwPYlS5bw5JNPctttt13K0xRCCCGEEEL0M1r7JirKq3SdEkqLa5u6XBeaFBVOepyJUUmRWMJCMBuDsYQFB5471pnD/K+NIYSFBF2SIHo2Bn5Y3fAolO29uHUmjIabl5128/XXX8+KFStYtGgRubm5eDweWltb2bp1K1OmTGHr1q2BsocPH+Yvf/kLf/jDH7jjjjt49dVXueuuu7rUl5+fT1xcHHfffTe7d+9m/PjxPP3005hMJtavX09SUhLZ2dkX9xyFEEIIIYQQ/VJTi5eS2maKa5sprmumuNZ3nWhxbTNHq13UNbUGyhqDg0iPMzPGYWXuVUkMiTeTbjORHmciInRgx72B3fo+Mn78eLZv305jYyNGo5Fx48aRm5vLli1beOaZZ/jVr34VKJuWlsbYsWMD+xUWFp5Sn9frZceOHaxcuZKcnBwWL17MsmXL+MlPfsLSpUvZuHHjpTo1IYQQQgghRC9pb9c0erw0NLdS39xKRaM7EEKLa5sCAbX6pGtEQw1BJEWH44gO55bRg8iIMzMk3syQOBOJ1nCCgvpHT+jFNvDDag89oL0lJCSE1NRUVq9ezXXXXceYMWN4//33ycvLY/jw4V3KGo3GwLLBYKC5uZmioiJmz54NwAMPPMCcOXNwOBzk5OQAMH/+fJYtW0ZeXh4FBQWBXtXi4mLGjRvHtm3bSEhIuERnK4QQQgghhOhOfVMr+VVOCqtd1LhaaWhupcHdSkOz1//cSoPbG1jv9HjR3dy+JTQ4CEdUOEnR4UxPtOLwB1PfI4I4s/GyDaQ9GfhhtY9cf/31LF++nFWrVjF69Gh+8IMfMH78+LMa352cnMyuXbtOWXfw4EGysrJ47733GDFiBKNHj6aioiJQJjU1ldzcXJkNWAghhBBCiEukY9Kigion+VUuCipdFFS5yK9ynTJLLoDFGExkeAiWMN9zUlQ4wwdZiAwLITI8hEj/+siwYOIjw3BEh2MzXZlh9EwkrJ6nKVOmsHTpUiZOnIjJZCIsLIwpU6acd30rV67kzjvvpKWlhfT0dFavXn0RWyuEEEIIIYToibu1jS9KG9hXUk9+pT+YVrkoqWvu0hsabzGSZjMxY2QC6TYTaTYTqTYTcRYjZmMwBgmdAd52L7XuWqqaq6h2V1PVXOVbbj6xXNVcddr9le6uH7ofmTBhgs7Nze2ybv/+/acMtxX9i3xGQgghhBCiv2rxtnOovJHdxXXsKapnT0k9h8obafNPpWsxBpMW5wui6TYzaXEm0v2h1Gy8svv7tNY0tDR0CZsdYfTkEFrrrkVzat40hZiwhduIDYslNjyWp258arvWesLJ5a7sd1oIIYQQQghxWWtr1xypcLKnuI49xb5guv94Ay3edgCiIkIY44hi2rB4xjisjHZYSYgM6ze3b+lNre2tNLU20djSiKvVhbPVibPFibPVGQiknQNoR++ot917Sl2hQaHEhscSFx5HojmRMXFjsIXbsIXZfME03BdMY8NiiQiJ6LLvUzzVbfskrAohhBBCCCEGvBZvO0W1TeRXuiioclJQ5eJwuZMvShtobm0DwGwMZlRSJHdfl8poh5VsRxSO6PDLJphqral2V1PqLPU9XL7nquaqQAjtHErdbe4e6wtSQcSExQTCZkZUhi+A+l93fraEWC76+yhhVQghhBBCCDEgtLdryhvdFFS6yAtMduQLpkW1zYFhvACxplDSbCa+dnUyYxxWxjiiSLeZBvRERh1htMRZciKQOkspcfleH3cePyWAWo1W4sLjMIeYiQ6LJtmSjCnEhCXUginEhDnEjDnUjDnE3GW9JdRCtDEaQ5Chj85WwqoQQgghhBCiH2lwt1Jc47/vaN2Je5Aeq2mmsMoV6CUFCAsJIs1mZmSildnZiaT5JzxKs5mIigjtw7M4d1pr6jx1lLnKKG8qp8xV1u1ya3trl/2ijFEkmhPJiMrg+qTrSTQnnniYEjGHmvvojC6chFUhhBBCCCHEJdHWrqltaqG8wU1JbUcQ9YXRjucGd9frIcNDDIF7jk5Mjw1MdpQeZ8JuCeuXPaWeNg/OFt+Q28bWRlwt/qG3/uG3Heurm6u7BFFPm6dLPcFBwdgj7Ngj7IyOG82XTV8mISIBh8VBoskXSE++/vNyImFVCCGEEEIIcd6aWrxUO1uodHqodrZQ7fRQ7WqhyumhquO1s4Vql4caVwvtJ00OGxHaEUYjmJAaHVhOivIF1BhTaL+5prSj9/Now1GONR7jWIPvUdRYRJ2nLnA96Mm9n93pmJAowZTAiNgR3DT4JhJMCdgj7CSYEkgwJRATFkOQCroEZ9Y/SVjtJ/bs2cP9999PQ0MDQUFBfP7554SFhQW2f+UrXyE/P599+/b1YSuFEEIIIcSVqsbVwqHyRg6XN3Ko3OlbrnBS42rptrzFGEysOZRYs5FUWwTjU6OxmUKxWYzEmY04oiNwRIcTFRHSb8IonD6Qdiw3tjYGygapIBJNiSRbkkmxpviu/zzpGtDOrzuWTSEmQg0Da5hyX5Cw2g94vV7uuusuXnzxRbKzs6muriYkJCSw/R//+Adm88Aday6EEEIIIQaOuqaWE2HUH0wPVzRS5TwRSs3GYDLtZr483E6KLQKb2YjNHIrNbCTWbCTWFEpYSN9NzHO2WtpayKvL40DNAQ7VHgo8N7Q0BMp0BNLBkYO5Nf1WBkcOJiUyhcGWwSSZkwgxhPRwBHEhJKyep9/85jesWrUKgHvuuYd7772XO+64g+LiYtra2vjpT3/KzJkzueaaa1i/fj1ZWVl84xvf4KabbuLee+/tUtfGjRsZM2YM2dnZAMTGxga2OZ1OfvOb3/D8889zxx13XLoTFEIIIYQQA4LWmubWNqqdLdS4WqhpaqHG2UJTaxue1jY83nb/ow1Pa6dlb7v/9YkypXXNVDaeuG7SFGogw27hxqx4htotZNrNDLVbGGQdePchrXPXcbD2IAdqDnCw5iAHaw+SX5ePV/uukQ0PDiczOpMZqTNIs6aREplCsiUZh9khgbSPDPiw+uttv+ZAzYGLWuewmGE8cs0jp92+fft2Vq9ezWeffYbWmpycHNra2khMTOTNN98EoL6+HqvVyu9+9zsWLFjA4sWLqa2tPSWoAhw6dAilFDNmzKCyspKvf/3r/PjHPwbgpz/9Kf/2b/9GRMTle+G0EEIIIYQ4VWtbO8dqmiiodFHp9F3v6QukHmqaWn3PzhaqXS14vO1nrM8YHOR7hBhOLAcbMIb4lq3hIWTEmRnqD6SZdjNJUQPrHqQdt3YpaiyiqLGIwvrCQI9peVN5oFx8eDxZMVlc77ierJgshkUPI9mS3Ke3aRGnGvBhtS9s3bqVuXPnYjKZALj99tsJCQnh3Xff5ZFHHmHWrFlMmTIFgC9/+cv8/e9/53vf+x67d+/utj6v18vWrVv5/PPPiYiIYNq0aYwfP57Y2FiOHDnCU089RWFh4aU6PSGEEEIIcQnVN7WSV+Ukr8JJXqWLvEon+ZVOjlY34T1pNiJTqIEYcygxJt91n1n2SGLNoURHhBJrCiXaFEqM/2E2BgeCaKghaECFzp60trdS5iwLBNLAw1lEcWMxzd7mQFmDMpBmTWNCwgSGRQ9jaMxQsqKziA2P7eEIor8Y8GG1px7Q3qK17nb99u3beeutt/jJT37C9OnT+dnPfkZ7ezv79+8nPDycmpoaHA4H69at4/HHHwfgj3/8Iw6Hg6lTp2Kz2QC45ZZb2LFjB2azme3bt5OamorX66WiooIbbriBzZs3X6pTFUIIIYQQF4G3rZ2Sumby/WG0cyjtfC1oiEGRGmsiM97CzFEJDIkzk2YzkWANIzpiYFwHeiG01tR6aqloqqDcVU55UzkVTRVUNFVQ5vIF1OOu47TpE/daNRqMOMwOki3J5CTkkGxJDjzkmtKBTZ0uePUXEyZM0Lm5uV3W7d+/n+HDh/dRi2DHjh0sWLCATz/9NDAM+LnnnmP8+PGEhYXx2muvsWbNGl577TVWrFjBwYMH+da3vsWSJUv45JNPukyeBFBbW8u0adPYunUroaGhzJw5kyVLlnDrrbcGyhQWFjJr1qwBMxtwX39GQgghhBCXmtaaSqeHgkoXBVUu8qtc5Fe6KKhycqymida2E393R0eEMCTO7HvEmxgSZyY9zkxydDjBhsvvViVur5s6Tx31nnrqPHXUuGt8gbRTGO14nHzbF4XCFm7DHmH3XUNqcXQJpHERcVf07V0uB0qp7VrrCSevH/A9q31h3LhxLFiwgGuuuQbwTbDkdDq55pprCAoKIiQkhGeffZZDhw7xxz/+kW3btmGxWLj++uv5z//8z0Cvaofo6Gh+8IMfcPXVV6OU4pZbbukSVIUQQgghRP/hbm0jv9LF4YpGCqpcJx6VLho93kC50OAgUmMjyIg3M31kAmk2E2k2XzCNMQ3s25Z4272UucoocZZQ0VRBnaeuSxjtvFzvqe8yNLez8OBw4iPiiY+I56r4qwLL9gh7YNkWbiM4SGLLlUh6VkWvkM9ICCGEEAOdx9tGQZXLd+uW8kb/rVycFFa76LiUVClIigonzWYi3WYi3T9sN81mIjEqHEPQwLxOtGM4bnFjMSXOki7Pxc5iylxlXYbigu8WL5GhkUQZo7AarUQbo7EarUQZo4gKizqxbIwi2hhNvCkeS4jlsrmWVpw/6VkVQgghhBCiG61t7f5Q2tglmBZWN9HmT6WGIEVKbARD7RZmjRlEpn+23NRYU7+4jrRdt+NsdVLvqaehpYF6Tz0er4eW9hZa21tpbWv1PfuXO69vaW8JbK92VweC6cm9oTFhMTgsDsbEjeGWtFtwWBwkmZOwR9iJDovGEmqR4bjiopKwKoQQQgghrhju1jb2H2/gi9KORz0Hyhpp8d/6JUhBSqyJzHgzN48aFLivaHqcCWPwpQul7bqdiqYKihuLKXWVUuuuDQTRBk9DIJDWt/jWNbY00q7PfPuak4UEhRBqCCUkKISQoBCsRisOi4NrB10bCKMOs4NEcyIRIXIrRXFpSVgVQgghhBCXpfrmVv7lD6QdwTSv0hXoLY0MC2ZUkpXvTExhRGIkQ+0WhsSZL1lPab2nvssQ25OXT55oqGOYrdVo9T2HWUmOTMYaaiXSGHnKc1hwGKFBoacE0o7l4KBgGYIr+jUJq0IIIYQQYkBrcLdS6J95N7/KxeHyRvaV1lNUc2IYqz3SyMhEKzNHJjAi0crIxEgc0eG9HtacLU4KGwopqC+goL6AwobCwHWfjS2NXcpajVaSzEkMjR7KjYNvxGF24DA7SLIkERMWgynEJMNsxRVFwqoQQgghhOj3PN42imqa/LeCcZ14rnJR5fQEyikFg2MiGJMUxdevHszIxEhGJlqJsxh7rW3tup0yVxmF9YUUNBQEgmlBfQGVzZWBcgZlCNx6JTsuG4flRBhNMidhCbX0WhuFGIgkrAohhBBCiH7F5fGy/Wgtn+ZX86/jDeRXuiiubQrMwAtgM4eSZjNx07A40mxm0uN8s/Emx0T02jDeZm8zRxuO+npI6/29pQ2+ZXebO1DOEmohzZrGdYnXkWZNI82aRqo1lWRzMiGGkF5pmxCXIwmrA4TZbMbpdPZ1M4QQQgghLjqnx0tuYQ2fFZw3cXwAACAASURBVNTwaX41e4vr8bZrgoMUmXYLYxxW5oxNJC3ORJrNd2sYa3jvhD6tNZXNlV3CaEc4LXWVBsopFInmRNKsaVydcLUvlEb6gmlMWIxcCyrERXBWYVUpVQg0Am2AV2s9QSkVA7wCpAKFwB1a61p/+Z8A3/WXX6S1ftu/fjywBggH3gIW6/5+o9dLyOv1Ehwsvx8IIYQQ4vLm9Hj5vLCGz/L94bSknjZ/OM1OjuK+69O5Nj2W8SnRmIy987eR1poyVxmH6w5zuPYweXV5gXDqanUFyoUHh5NmTeMq+1XcHnk7qdZU0qxppESmYDT03tBiIcS59azeqLWu6vT6UeA9rfUypdSj/tePKKVGAF8HRgKJwLtKqaFa6zbgWeA+4FN8YXUmsOEinMclV1hYyM0338zkyZP5+OOPSUpK4vXXX+fgwYM88MADNDU1MWTIEFatWkV0dDR/+MMfeP7552lpaSEjI4MXX3yRiIgIFixYQExMDDt37mTcuHE8/vjjPPTQQ+Tm5qKU4uc//znz5s0D4D/+4z944403CA8P5/XXX8dut/fxuyCEEEII0TNvWztHa5o4XO5k57FaPi2oYZ8/nIYYFNmOKB6YeiKcRoRe/HBa564LhNLDdYc5UnuEI3VHcLaeGLUWHxFPujWdrwz5yomhu5Gp2CPs0ksqRB9RZ9Ox6e9ZndA5rCqlDgI3aK2PK6UGAZu11ln+XlW01r/yl3sb+AW+3tf3tdbD/Ou/4d///p6OPWHCBJ2bm9tl3f79+xk+fDgAZf/1X3j2Hzirkz1bxuHDSPj3f++xTGFhIRkZGeTm5jJ27FjuuOMOvvKVr/Dkk0+ycuVKpk6dys9+9jMaGhr47W9/S3V1NbGxsQA89thj2O12HnroIRYsWEBVVRWvv/46BoOBRx55BI/Hw29/+1sAamtriY6ORinF+vXrmT17Nj/+8Y+JjIzkscceu6jnfTF1/oyEEEIIcflzt7ZRUOXiSIWTwxVO8iqcHK5opLCqiZY23/0/QwyKsclRXJseS05aLONSoi5aOPW2e6lqrqLUWcqxxmO+YFp7mCN1R7pMchQZGklmdCYZURkMjR5KZnQmQ6KGEBkaeVHaIYQ4d0qp7VrrCSevP9v/O2hgo1JKA89prZ8H7Frr4wD+wBrvL5uEr+e0Q7F/Xat/+eT1A1ZaWhpjx44FYPz48eTl5VFXV8fUqVMB+M53vsNXv/pVAPbt28djjz1GXV0dTqeTGTNmBOr56le/isHgmwjg3Xff5a9//WtgW3R0NAChoaHMmjUrcKx33nmn909QCCGEEKKT9nZNldNDcV0z+ZW+YHqkopEjFU6O1ZyYACnIPyNvRryZG4fFkxlvISPeTJbdQnjo+U1+5Gxxctx1nOOu45S5yjjuOk6pszSwXNFUQZtuC5Q3GoykW9OZmDiRodFDyYjKIDM6k7jwOOkpFWKAONuwOklrXeoPpO8opXrqyuzuv37dw/pTK1DqPnzDhRk8eHCPDTtTD2hvMhpPXKdgMBioq6s7bdkFCxbw2muvkZ2dzZo1a9i8eXNgm8lkCixrrbv9H2hISEhgvcFgwOv1XoQzEEIIIYQ4obmljZK6Zko7PUrq3JTUNVFa5+Z4fTOtbSf+fAsxKNJsJkYmWvnK2CQy4s1kxvsmQLqQGXlLnaV8dvwzPiv7jMO1hznuOn7KPUmDVTB2k51BpkFMsE8gwZRAojmRQaZBJJmTSLYkYwjqnVmBhRCXxlmFVa11qf+5Qim1DrgGKFdKDeo0DLjCX7wYSO60uwMo9a93dLO+u+M9DzwPvmHAZ386fctqtRIdHc2WLVuYMmUKL774YqCXtbGxkUGDBtHa2spLL71EUlL3ncrTp0/nd7/73SnDgIUQQgghLpTWmmpXCwVVLgoqffcoLahy+gOqmxpXS5fyQQoSIsNIjApnbHIUt4weRFKU73WazcTgmAiCDUEX3K4adw3byrb5AurxzyhqLAIgJiyG0bbRjIsfFwiiCaYEBpkGYQu3SRgV4jJ3xrCqlDIBQVrrRv/ydOAJYD3wHWCZ//l1/y7rgZeVUr/BN8FSJrBNa92mlGpUSl0LfAZ8G1h5sU+or/35z38OTLCUnp7O6tWrAfjlL39JTk4OKSkpjB49msbGxm73f+yxx/je977HqFGjMBgM/PznP+f222+/lKcghBBCiAGuqcVLfqXLF0r9j/wqFwWVThrcJ0ZnhRgUg2MiSI6JYIwjiqSocJKiwkmMCicxKgx7ZBghFyGMntK+1iZyy3MD4fRg7UEATCEmrrZfzTeHfZOcQTlkRGXIkF0hrmBnnGBJKZUOrPO/DAZe1lovVUrFAn8DBgPHgK9qrWv8+/wHsBDwAg9rrTf410/gxK1rNgAPnenWNWeaYEn0T/IZCSGEEL1Pa83xeje7i+rYVVzH3uJ68itdlDW4u5RL8veEBh5xJtJtJpKiwi9Kz2hP2nU7Za4yCusL2Vm5k8+Of8beyr14tZfQoFDGxo8lZ1AOOYNyGBk7kuAguY2fEFea855gSWudD2R3s74amHaafZYCS7tZnwuMOpsGCyGEEEKIruqbW9lTXOcLp0X17C6uo7LRA0CoIYhhgyxMyrCRHncimKbGms57UqOzpbWmzlNHYUMhhfWFHG04ytGGoxQ2FHKs4Rgt7b7hxUEqiJGxI1kwagE5g3IYGzeWsOCwXm2bEGLgkp+uhBBCCCH6IY+3jf3HG9ldVBfoOc2vdAW2p8eZmJJhY+zgKLIdUQwbZMEY3HuhtLW9laqmKsqayihzlXGs4ViXUNrQ0hAoGxwUTLIlmZTIFCYnTSYlMoWUyBSyYrLkFjFCiLMmYVUIIYQQog91d3/SIxVO8qucgZl34yxGxiZHMW+cg2xHFKMdVqzhIRetDR33KC1zlVHWVEa5q5wyVxnlTeWB5Sp3Fe26vct+9gg7qdZUbk67ORBIUyNTSTQnynBeIcQFk/+LCCGEEEJcAk6Plzx/ID3d/UmV//6kmf77k2Y7rGQnRzHIGnbBEw25vW6KGos41niMYw3HujxXNlV2uUcpQHhwOAmmBOwRdq5Lug57hJ0EU0JgXZI5iYiQiAtqkxBC9ETCqhBCCCFELzlU3siLnxzlvf3llNafmPSo4/6kIxIjA/cnzYgzkx53YfcndXvdFDcWc7Tx6CmBtMxV1qVstDGawZGDmWCfQKI58ZQwGhkaKTPxCiH6lIRVIYQQQoiLqLWtnY1flPPCJ4V8VlBDaHAQXxoez52JVl8ojTeTchHuT9qu2ymoL2BP5R72VO1hT+UejtQd6TJUtyOQXm2/msGRgxlsGUxKZArJkcly7agQot+TsHqezGYzTqeT0tJSFi1axNq1a/u6SWelrq6Oe+65h3379qGUYtWqVUycODGwffny5fzoRz+isrISm83G5s2bWb58OW+88UYftloIIYTo/8ob3Lz82TH+su0YFY0eHNHhPHrzMO6YkEyMKfSC669117K3ai+7K3ezp3IP+6r24Wx1AmAJtTDGNoYbk28k3ZougVQIcVmQsHqBEhMTB0xQBVi8eDEzZ85k7dq1tLS00NTUFNhWVFTEO++8w+DBg/uwhUIIIcTAobXm0/waXvy0kLe/KKdda6YOjWPZxBSmDo3HEHR+w2ibvc3k1eV16TUtaiwCfLd/GRo9lFvSbmFM3BjGxI0hJTKFINW790sVQohLTcLqBSosLGTWrFns27ePNWvWsH79epqamsjLy2Pu3Lk8+eSTwImeWIC1a9fyxhtvsGbNGm677TbmzZvHt7/9bZ577jk+/PBDXnrppVOOMXPmTHJycti5cydDhw7lhRdeICIigtTUVL72ta/x/vvvA/Dyyy+TkZFBeXk5DzzwAPn5+QA8++yzjBo1ig8//JA1a9YAEBoaSmjoiV96lyxZwpNPPsltt93W7bm6XC4eeugh9u7di9fr5Re/+MVpywohhBCXs0Z3K+t2lvDiJ0c5XOHEGh7Cwkmp3HVtCimxprOup6Glgfy6fArqC8ivzyevLo/8+nxKnaVofLMu2cJtZMdlM3/ofEbbRjMydqRMbCSEuCIM+LC65W+HqCpyXtQ6bclmptwx9Lz23bVrFzt37sRoNJKVlcVDDz1EcnLyacs///zzTJo0ibS0NFasWMGnn37abbmDBw/ypz/9iUmTJrFw4UL+53/+hx/+8IcAREZGsm3bNl544QUefvhh3njjDRYtWsTUqVNZt24dbW1tOJ1O8vPziYuL4+6772b37t2MHz+ep59+GpPJxPr160lKSiI7O/u0bV26dCk33XQTq1atoq6ujmuuuYYvfelLmExn/4+yEEIIMVBprdlbUs/fc4v5x45iXC1tjE6y8uT8MXwlO7HHiZGqm6vJr88nvy6fvPq8wHJlc2WgTGhQKKnWVEbbRnPbkNsYEjWE0bbRJJgSZKIjIcQVacCH1f5m2rRpWK1WAEaMGMHRo0d7DKt2u50nnniCG2+8kXXr1hETE9NtueTkZCZNmgTAXXfdxTPPPBMIq9/4xjcCz0uWLAFg06ZNvPDCCwAYDAasViter5cdO3awcuVKcnJyWLx4McuWLeMnP/kJS5cuZePGjT2e28aNG1m/fj3Lly8HwO12c+zYMYYPH362b48QQggxoHjb2tlWWMPGL8rZ+EUZpfVuQoODmDVmEN+emMrY5KjT7tvY0siGgg28evhV/lX9r8B6U4iJdGs6ExMnMiRqCOnWdNKt6SSZkzAEnf9MwEIIcbkZ8GH1fHtAe4vRaAwsGwwGvF4vQJdfRN1ud5d99u7dS2xsLKWlpYDv2tHZs2cD8MADDzBz5sxTflHt/Pp0yydzOBw4HA5ycnIAmD9/PsuWLSMvL4+CgoJAr2pxcTHjxo1j27ZtXfbXWvPqq6+SlZV1hndBCCGEGLjcrW1sPVzF21+U8e7+cmqbWjEGBzElM44lXx7Kl0fYiYrofsIkrTW7Knfx6qFX2Xh0I83eZoZGD+UH439AVkwW6dZ07BF26SkVQoizMODD6kBht9vZv38/WVlZrFu3DovFAsC2bdvYsGEDO3fuZOrUqUyfPp20tDR27doV2LewsJBjx47xySefMHHiRP7yl78wefLkwPZXXnmFRx99lFdeeSUws++0adN49tlnefjhh2lra8PlcpGQkEBycjIHDx4kKyuL9957jxEjRjB69GgqKioC9aWmppKbm4vNZuPAgQOB9TNmzGDlypWsXLkSpRQ7d+7kqquu6u23TgghhOh1De5W3j9QwdtflLH5YCVNLW1YwoKZNiyeGSMTmJoVR0To6f9sqnHX8H95/8erh1+loL6AiOAIbk2/lXmZ8xgZO1LCqRBCnAcJq5fIsmXLmDVrFsnJyYwaNQqn04nH4+Hee+9l9erVJCYmsmLFChYuXMimTZtO+Udt+PDh/PnPf+b+++8nMzOTBx98MLDN4/GQk5NDe3s7f/nLXwB4+umnue+++/jTn/6EwWDg2WefZeLEiaxcuZI777yTlpYW0tPTWb169Vmfw09/+lMefvhhxowZg9aa1NRUuaWNEEKIAava6eHtL8p5+4syPs6rorVNE2cxMueqJGaOTODa9FhCg08/w267bufT0k959fCrbCrahLfdS3ZcNk9c9wQzUmfIJEhCCHGBlNa6r9vQowkTJujc3Nwu6/bv339FXSfZecbhk3XuBe1PrrTPSAghxMDQ4m1n04Fy1m4vYfPBCrztmpTYCGaMTGDGSDtXJUcTdIbbzZS5ynjtyGusO7yOUlcpVqOV2emzmZc5j4zojEt0JkIIcflQSm3XWk84eb30rAohhBDisqa1Zl9JA2u3F/H67lLqmlqJtxj57pQ05oxNYliCpcdhulprDtcdZmvJVraWbGV7+XbadTs5g3JYMn4JNw2+iVBD99ewCiGEOH8SVgeA1NTUbntVwdfrKoQQQohTVTS4WbezhFd3FHOo3ElocBDTR9iZP97B5AwbwYbTD/F1tjj57PhnbCnZwtaSrZQ3lQOQFZ3FPaPvYU7GHJItp5/tXwghxIWTsCqEEEKIy4a7tY1395ezdnsxHx6qpF3DuMFRLJ07illjErGGh3S7n9aaI3VHAuF0Z/lOvNqLOcTMxMSJTE6azKTESdhN9kt8RkIIceWSsCqEEEKIAa2tXbPjWC2v7Szh/3aX0uD2MsgaxoM3DOH2cQ6GxJm73a+ptYlPSj85pfd0aPRQvj3y20xOmszY+LGEBHUfcIUQQvQuCatCCCGEGHAa3K1sOVTFe/vLef9gBbVNrYSFBDFzZALzxyczcUgshm4mSmpta+Wj0o94M/9NNhdtxt3mxhRiYuKgifw/x/+T3lMhhOhHJKwKIYQQYkA4Wu3i3f0VbDpQzmf5NXjbNdbwEG7MimPacDs3ZMVhCTu1F7Rdt7OzYidv5r/JxqMbqffUE2WM4raM25iROkN6T4UQop+SsHqezGYzTqeT0tJSFi1axNq1a/u6Seds8+bNLF++vNt7pWqteeyxx/j73/+OwWDgwQcfZNGiRYHtn3/+Oddeey2vvPIK8+fPv5TNFkIIcYXwtrWz/Wgt7x2o4L395eRVugDIiDfz3SlpTBtmZ9zgqNNOlHSo9hBv5r/JhoINHHcdJzw4nBuSb2BW+iwmJk6UgCqEEP2chNULlJiY2O+DaltbGwaD4Zz2WbNmDUVFRRw4cICgoCAqKiq61PfII48wY8aMi91UIYQQV7D2dk1+lYs9xXV8cKiSzQcrqW9uJcSgyEmL5a5rU7hpWDwpsabT1nHceZw3C97krYK3OFx7GIMyMDFxIovGLeKm5JuICIm4hGckhBDiQkhYvUCFhYXMmjWLffv2sWbNGtavX09TUxN5eXnMnTuXJ598EjjREwuwdu1a3njjDdasWcNtt93GvHnz+Pa3v81zzz3Hhx9+yEsvvXTKcebMmUNRURFut5vFixdz3333AfDggw/y+eef09zczPz583n88ccB3+1uFi5cyMaNG/n+97/PhAkTeOCBB6isrMRgMPD3v/8dAKfTyfz589m3bx/jx4/nf//3f1FK8eyzz/Lyyy8TFOT7tTo+Pj7QlpUrVzJv3jw+//zz3ntjhRBCXNba2jUFVU72ltSzt7iBfSX1fFFaj6ulDYAYUyhfGm5n2vB4pmTauh3e26GooYitpVv5Z8E/2VGxA4DsuGz+PeffmZ4yndjw2EtyTkIIIS6uAR9W31/zPBVH8y9qnfEp6dy44L7z2nfXrl3s3LkTo9FIVlYWDz30EMnJp78P2/PPP8+kSZNIS0tjxYoVfPrpp92WW7VqFTExMTQ3N3P11Vczb948YmNjWbp0KTExMbS1tTFt2jT27NnDmDFjAAgLC2Pr1q0A5OTk8OijjzJ37lzcbjft7e0UFRWxc+dOvvjiCxITE5k0aRIfffQRkydPJi8vj1deeYV169YRFxfHM888Q2ZmJiUlJaxbt45NmzZJWBVCCHFW2to1eZVO9pXUs7ek3h9MG2jyB9OwkCCGD4pk3ngHo5KsjE6yMtRu6XaCJPDN4ptbnsvWkq18VPIRxxqPAZBmTeP7Y7/PLem3yD1QhRDiMjDgw2p/M23aNKxWKwAjRozg6NGjPYZVu93OE088wY033si6deuIiYnpttwzzzzDunXrACgqKuLw4cPExsbyt7/9jeeffx6v18vx48f517/+FQirX/va1wBobGykpKSEuXPnAr4Q2+Gaa67B4XAAMHbsWAoLC5k8eTIej4ewsDByc3P5xz/+wcKFC9myZQsPP/wwv/71r895WLEQQogrR2tbO7uK6thyuIpP8qrYV9JAc6svmIaHGBiRGMkdE5IDwXRInOm0152Cbx6Fw3WH+ajkIz4q/Ygd5TtobW8lzBDG1QlX883h32RS4iRSIlNQqvuAK4QQYuAZ8GH1fHtAe4vRaAwsGwwGvF4vQJd/PN1ud5d99u7dS2xsLKWlpYAvjM6ePRuABx54gGHDhvHuu+/yySefEBERwQ033IDb7aagoIDly5fz+eefEx0dzYIFC7rUbTL5runRWp9zex0OB/PmzQNg7ty53H333QDk5uby9a9/HYCqqireeustgoODmTNnzrm8TUIIIS4jWmsOVzjZeriKj45U8Wl+Na6WNoIUjHZE8bWrkxmdZGW0w8qQOPNpe0w7q/fU88nxT/i45GM+KvmIimbf3AkZURl8c9g3mZQ0iXH2cRgNxjPUJIQQYqAa8GF1oLDb7ezfv5+srCzWrVuHxWIBYNu2bWzYsIGdO3cydepUpk+fTlpaGrt27Qrs+/rrrxMdHU1ERAQHDhwIDBVuaGjAZDJhtVopLy9nw4YN3HDDDaccOzIyEofDwWuvvcacOXPweDy0tbX12N45c+awadMmFi5cyAcffMDQoUMBKCgoCJRZsGABs2bNkqAqhBBXoPIGNx8dqWLr4Sq2HqmiotEDQGpsBHPHJTE5I46J6bFYI7q/1lRrTa2nluOu4xx3Hvc9u45T5iqjuLGYg7UHadftWEItTBw0kUlJk7gu8ToSTAmX8jSFEEL0IQmrl8iyZcuYNWsWycnJjBo1CqfTicfj4d5772X16tUkJiayYsUKFi5cyKZNm7r0xM6cOZPf//73jBkzhqysLK699loAsrOzueqqqxg5ciTp6elMmjTptMd/8cUXuf/++/nZz35GSEhIYIKl03n00Ue58847eeqppzCbzfzxj3+8OG+EEEKIAUdrTVmDmy9KGvgozxdQD1f4Jg2MMYVy3ZBYJmfYmJRhIznmxGy7rW2tbC/fTlFjUSCIljpLKXOVcdx1HE+bp8txwgxhDDIPYpBpEPeNuY9JiZMYZRtFcJD8uSKEEFci1dMQ0f5gwoQJOjc3t8u6/fv3M3z48D5qkTgb8hkJIcTAo7WmvMHDofJGDpU3crjcyaGKRo6UO2n0+C4TMQYHcU1aDJMybEzOsDFiUCRBnYb11nvq+ajkI94vep+tJVtxtjoD22zhNgaZBpFgSiDRlMggs295kGkQiaZErEarXHMqhBBXIKXUdq31hJPXy0+VQgghxBVGa02l0+MLo+WNHCp3ctgfUBvc3kC5GFMomfFm5lyVxFC7maF2C9nJUYSFdJ1kr6ixiA+KPmBz0Wa2l2/Hq73EhMXw5ZQvM9UxlczoTBJMCYQaQi/1qQohhBjAJKwKIYQQlymtNVXOlkAQPVThC6WHK5zUNbUGykVFhDA03sLs7ESG2i1k+oOpzdz95EXtup29VXvZXLSZzUWbOVJ3BIAh1iF8Z+R3uCH5BsbEjSFInX6GXyGEEOJMJKwKIYQQl4Fqp8fXQ1rR2KW3tLZTKI0MC2ao3cLNowYFekoz7WbizMYzDr+t99Szo3wHm4s380HRB1S7qzEoA+Ps4/jRhB9xQ/INDI4c3NunKYQQ4goyYMOq1lqua+mn+vt10EIIcTk4Wu3iw8NVbDlUyfajtVS7WgLbLMZgMu1mZoxMINNuCQTTeMuZQyn4ek7z6/LZXbmbXZW72F25m4J632zw5hAzk5MmMzV5KlOSpmA1WnvtHIUQQlzZBmRYDQsLo7q6mtjYWAms/YzWmurqasLCwvq6KUIIcVlpcLfy8ZFqthyuZMvhKo7VNAGQFBXOjcPiGZZgYajd97BHnl0o7dDY0sjeyr3srtzN7srd7KncQ2NrIwBWo5XsuGxmp89mbPxYxsaNJcTQ/e1ohBBCiItpQIZVh8NBcXExlZWVfd0U0Y2wsDAcDkdfN0MIIQY0b1s7u4vrA+F0V1Edbe0aU6iBiUNs3DMljSmZcaTGRpxTMHV73RTUF3Cg5kAgnObV5aHRKBQZ0RnMSJtBdlw2Y+PGkhKZIj8MCyGE6BMDMqyGhISQlpbW180QQgghLqrSumbeP1jBlkNVfJRXRaPbi1IwxhHF/7thCFMy47hqcBQhhjNPXORp81BQX8CRuiPk1eUFHsXOYtp1OwCWEAtj4scwPXU62XHZjLaNxhJq6e3TFEIIIc7KgAyrQgghxOWisMrFhn1l/POLMnYX1QGQaA3j1tGDmJIZx3VDYok2nf6WL23tbYFAGgim9XkUNRYFQmmwCmZw5GCyYrK4Nf1WhkQNITMqk1RrqszYK4QQot+SsCqEEEJcQlprDpU7+ee+MjbsO86BMt+1oWMcVn48M4vpI+wMiTP3OPRWa82h2kO8kf8Gb+W/RUVzBQAGZSDZkkxmVCYzU2eSEZXBkKghpEamynWmQgghBhwJq0IIIUQv01qzr6SBDfuO8899ZeRXuVAKJqRE89itw5k5KgFHdMQZ6ylzlfFm/pu8kf8GR+qOEKyC+f/s3Xl8FdX9//HX5CY3NwvZFyALIQlhJxD2VQFxK4rivtWNutal1larrf3Wfqu2/X1tq3W3brVqrTtUqIoiorJDgLCGJJAEsrBkvzd3m98fc9lBwAI3y/v5eMxj5s7MnXxGHubed86Zc8alj+PuHneTF59Hz9ie2G1HboUVERFpTxRWRURETgK/32T51t3MCXTxrdjtxBZiMCo7gevH9eSsfqmkxBx95PRGdyOfbfmMWSWzWFK1BBOT/OR8fjnyl5yZdSbxjvhTcDciIiKnnsKqiIjICVDb2EpheR2FFXWsLK+jsLyOBpeXMJvBuNwk7pzUizP6pZLwHc+f7uHxe/i68mtmlcxiXvk8Wn2tZHbJ5NbBtzK151QyYjJOwR2JiIgEl8KqiIjIcWpu9bKmst4KpRV1FJbXU1nnBMAWYtA7tQs/GNSdUdkJTOyTQozj6M+LmqZJYW0h/y75N3PK5lDXWkd8eDzTe01navZUBiYN1BQyIiLSqSisioiIHEX5rha+2rRjb8vpxupG/KZ1LCMhgiGZcVw/Nov8jDgGdI8lwm475mtv3L2Rj0s+Zk7ZHCqbKgm3hTMxYyJTs6cyJm0MYSEaGElERDonhVUREZHvsKqijsueW4jT4yM+Moz8jDjOQS84MQAAIABJREFU6t+VwRlxDEqPJTE6/LivWd5YzuzS2cwunU1xXTE2w8aobqO4Nf9WJmVO0lynIiIiKKyKiIgc0dadLdzwyhISouy8cv1wclO+e0qZ71LbUsucsjnMLp3N6h2rAShIKeDBkQ8ypccUEiMST2TpIiIi7Z7CqoiIyGHsanZz7cuL8fpN3rphBLkp0cd9jfrWej7b8hmzS2ezuGoxJiZ9Evrwk6E/4Zysc+gW3e0kVC4iIhJk3lZw1e+31B30+qDlCBRWRUREDuJ0+5jx6hIq65y8MWPkMQXVOlcdxXXFbK7bTHFdMcV1xaysXYnX76VHTA9uzr+Zc3qeQ3Zs9im4AxERkePg94HXZYVMr8taPE5obQRXA7Q2WNt714HFVb/f64Z953pd3/3zQkLBEQeOWHDEHPE0hVUREZH9+Pwmd721ghXldTx9ZQHDshIOOF7fWr83kG6u27x3e6dr595zosKiyInL4co+V3Ju9rn0S+inkXxFROTk8XmhuRaaqqBxv6WpChqrwbn7oDAaWPvc1trvPfafZYRAeBcIj9m3jkyE+CzrdcSeEBoL4bH7tvdfwiJg/8/Fmw//GamwKiIiEmCaJr+ZWcQna6v59Xn9OGdgN0zT5O9r/878yvmU1JVQ66zde35kaCQ5cTmMTx9PblwuOXE55MblkhqZqnAqIiL/HdO0Wimbaq0gumdpqj4ojFZZ+03/odeITIIuXSEi3mrBDA2HUMd+a8dh9u13zBETCKV7gmkXsEcdGDRPIoVVERGRgOfnl/Dat1v40fieXD+2JwCvFL3C48seJy8+j9HdRx8QSrtFdVMoFRGRQx2uW+3BrZoel/UsZ3MtNNVA844DQ2lzrdXyeQgDogIhNLordB1kbe953aUbdEmFqBQItZ/yWz+RFFZFRESAD1dW8ujs9Uwd1I1fnNMXgE/KPuHxZY9zdtbZ/H7C7wkxQoJcpYiInHR+f+D5yzqr+6wzsD7s68DiqgNPy74gejzdagFsditcRiVBVDKk9IPoZGv7kCUJbJ1jDm6FVRER6fS+2byDe/9VyMieCfzfpfmEhBisql3FAwseYHDyYP533P8qqIqItFdeN7TshJYdVutly05rad5h7WvZCc0792237ALTd+TrhToC3WrjrHVcBjgGgj3yKN1qA2ubfV8324g4K3yGx5yyrrXticKqiIh0auurGrj578vISozi+WuGER5qo6Kxgjs+v4PkiGT+MukvhNvCg12miIjsz+exwmZTtdWFtql633ZzzX77aqxW0sMyIDLBGhwoMgmSekHkKGs7Ij6wxB0YTCPirMGB5JRQWBURkU5re72T619eQkSYjVduGEFsZBj1rfXcNvc2vH4vT5/xNAmOhKNfSEREvj/TtKY+ce6yWjX3rPffdu6yWj33hNCWnYe/VngsRKdAdKr1LGd0ihU+owKBNDLRasmMTLKCZ4jt1N6rHBeFVRER6ZQaXB6uf3kJjS4vb988mrS4CDw+Dz+d91PKG8t5fsrz9IztGewyRUTaDp/3oHk2A9vu5kMHDzpkipTWA/e5mwOBdKf1/Kffc+Sf64jb1wKakA2Zo6wwGp1iPee5Zzs6Ra2eHYzCqoiIdDpur59b/r6M4pomXrl+BP26x2CaJg8vfJhFVYv43bjfMbzr8GCXKSLy/XjdVpB0NwdGnW2xRp71tIDHeYR9Tmvtbg4MLnSYUOppOb46QsKO/OxmWCQk5ULECCuIRiTst07ct63Wz05NYVVERDoV0zT5+TuFfLN5J49fms+4XkkAvLj6RT4o/oBb82/l/Jzzg1yliHRKpmkFQlf9fkuDtW6ttwLjASFyT5BsOPCYr/X4f7YtHMIcYO+ybz7NyASI7xF4vd9cm4795twMj91vYKGDAqlCpvyXFFZFRKTTME2T38/ZwAcrt/Gzs3ozvSAdgNmls3lixRNMzZ7Krfm3BrlKEelQWhuhbivUlVvr+vLAtCf1gRbM+gOXo015YtgCYXG/8NilGyTl7RcqA2t7pNUtNjTCWodFWoE0LBAu97wOdShYSpuksCoiIp2C2+vnoQ/X8NaScq4cmcltp+cAsKJmBb9c8EsKUgr4zZjfYGjqABE5Hq6GQBjdui+M1m3Z99q5+8DzbXare6sj1loikyAhZ9/rQ5a4feHUEWMFS/2ekk5CYVVERDq8Xc1ubn19GYtKd3H7xBx+OqU3hmGwtWErd35+J92iu/GXiX/BbrMHu1QRCTaP88jzbzYfvK6xWkP3FxoBcZnWkjZ033ZcD2sdlaywKXKMFFZFRKRD21TdyI2vLqWqwcWfLxvMBUPSAKhz1XH73NsBeHry08Q54oJZpoicKi27YHcp7CoNrMusdX25FUw9zYd/n2Hbb9qTREjtD1GnQ1zGvkAam2kdVxgVOSEUVkVEpMP6YkMNd76xgvAwG2/dNIqCzHgA3D43d8+7m8qmSl4880UyYzKDXKmInDB+HzRu3y+MHrQ+uCU0OhXie0LGKKvV83DzcUYlWgMJhYQE555EOimFVRER6XBM0+Slr8v43b/X0rtrDC9eO4y0uIi9x379za9ZVr2M34//PQWpBUGuVkSOic8LzbXQVAWN+y37v26qthbTv+99hs1q9UzoaXXLTehphdOEnhCfBfaooN2SiHw3hVUREelQ9h9I6cx+qfzpssFEhe/7uHum8BlmlczijiF3cG72uUGsVEQOYZpWq2jVGqhaBVWrrdbQxiorqO4fQveITLJGw+2SCl0HQHRXiOm+L5TGZoBNX3lF2iP9nysiIh3G4QZSCgmxnh3z+X08vuxxXlv7GtNypvGjgT8KcrUinZzPAzs2WYG0erW1rlptDVy0R3wWJPaCbvlWCO2SagXT6K7QpStEp4AtLGi3ICInl8KqiIh0CEcaSAmgxdPCffPvY17FPK7qexX3DrtXU9SInCxeN7ibwNMC7hZrwCJ3C7ibrVbSqlVWy2nNOvC1Wu+xhUNKX+h9LnQdBF0HWgMYOWKCey8iElQKqyIi0u4daSAlgKrmKn4898cU1xXz4MgHubzP5UGsVKQdME1w1Vmj5h4whUtgvWdpbbRCqbvlwGDq93739SMTrTA68qZ9wTSxl7rqisgh9FtBRETare8aSAlgzY413PH5Hbi8Lp6a/BRj08YGsVqRIPJ5rdDZVA1NNfsGImqqsZbmWiuc7gmmRwqcYZGBkXITrFbPmHSwR1r77VGBdSSERVmvD94Xm2Z141XPBhE5BgqrIiLSLnl81kBKby4+/EBKn5R9wgMLHiApIokXz3yRnLicIFYrcpL4vNZouA3boL7CWu8fSJtrA+sdgHno+8NjAtO1JFsDEqUPO3DKlsjEA6dysUee8lsUkc5LYVVERNqdRpeH2/6xnK827eC203O498x9AymZpsmLq1/kiRVPMDh5MH+Z9BcSHAlBrljke/D7rKC5N4hWHrrduP3QEXJt4dbcodEpENcD0ofvex2dGliSISpF4VNE2jSFVRERaVeq6l1c9/Jiimua+MPFg7h0WMbeY26fm//55n+YWTKTqdlT+Z8x/0O4LTyI1Yocht9ntXQ2brfCaON2aKw+9HVTNZi+A98bGmF1pY1Jg56nBba7W91x93SxjYhXN1sR6RAUVkVEpN1YX9XA9S8vocHp4aXrhjMhL3nvsd2u3dz9xd0sr1nO7YNv5+ZBN2vEXwku04TaDbDhYyhfHAihVdBcc4T5QhMD07KkQko/a2qWmEAw3RNQFURFpBNRWBURkXbh6+Id3PL3ZUSG23j7ltH07x6791hJXQm3z72dWmctf5zwR87ueXYQK5VOzeeFrd/ChtlWSN1dau1P7gOxGdB1wL5A2qVbYK7QQNfcUHtwaxcRaWOOOawahmEDlgKVpmlONQwjAfgnkAWUAZeaprk7cO4vgBsBH3CnaZr/CewfCrwCRAAfA3eZpnmYp/1FRET2eXdZBfe9u4qc5Ghevn443fcb8febbd9w77x7sdvsvHTWSwxKHhTESqVTctVD8VwroG76xJr2xRYO2afB2Dsh72yrq66IiByX42lZvQtYB+yZnfl+YK5pmo8ZhnF/4PV9hmH0Ay4H+gPdgc8Mw8gzTdMHPAPcBCzECqtnA7NPyJ2IiEiHY5omf/28mP/7dCNjchJ55uqhxEaE7T3+9oa3eWTRI2THZfPXSX+le7QCgZwiu7fAxjlW62nZ1+D3WN14+/wAep8D2RMhPDrYVYqItGvHFFYNw0gHfgD8DrgnsHsacHpg+1VgHnBfYP9bpmm2AqWGYRQDIwzDKANiTNP8NnDN14ALUFgVEZHD8Pj8/OqDNby1pJzpQ9J47KJB2END9h5/tvBZnlr5FBPSJ/CHCX8gKiwqiNVKh2aaULcFKpdB5XIomQfVa6xjSXkw+jbofa416m6ILailioh0JMfasvpn4OdAl/32pZqmuR3ANM3thmGkBPanYbWc7lER2OcJbB+8/xCGYdyE1QJLZmbmMZYoIiIdRVOrl9v/sZwvN9Zyx6Rc7pmSt3ewJNM0eXLFk7yw+gXOzzmf34z5DaEhGoJBTqCWXVYorVwGlUutdctO61ioA9KGwZn/C3nnQFJucGsVEenAjvrpbhjGVKDGNM1lhmGcfgzXPNwQdeZ37D90p2k+DzwPMGzYMD3TKiLSidQ0uLj+lSWsr2rk0ekDuWLEvj9amqbJ/y39P15d+yoX9bqIh0Y/RIgR8h1XEzkKjxOqVkNFIJRWLts3KBKGNTBS73Mgbai1pPQDW9h3XlJERE6MY/lT9FjgfMMwzgUcQIxhGK8D1YZhdAu0qnYDagLnVwAZ+70/HdgW2J9+mP0iIiIAbKpu5LqXl1DX4ubFa4cxsXfK3mN+08+jix7lrQ1vcWWfK7l/xP2amkaOX1MNbF1ojdi79VsrqPq91rGYdEgrgKHXWcG0+2AI7/KdlxMRkZPnqGHVNM1fAL8ACLSs3mua5tWGYfwRuBZ4LLD+MPCWj4A3DMN4HGuApV7AYtM0fYZhNBqGMQpYBPwQePIE34+IiLRT327eyU1/X4ojzMY/bx7NgLR9U9P4TT8Pf/sw7256l+v6X8c9Q+9RUJWjM03YVRIIp99Y653F1rFQh/WM6di7rG69aQXWNDIiItJm/DcP+TwGvG0Yxo3AVuASANM0iwzDeBtYC3iB2wMjAQPcyr6pa2ajwZVERAT4YEUlP39nFT0SI3n5+uGkx0fuPebz+3jom4f4aPNH/Gjgj7hjyB0KqnJ4Pq818NGeVtOtC6Gp2joWEQ+Zo6Hgh5A5Brrla15TEZE2zmjr05wOGzbMXLp0abDLEBGRk8A0TZ78vJjHP93IqOwEnrt6GLGR+54H9Pg9PPjVg8wum82PB/+Ym/NvDmK10ua0NlrPmpYvsoJpxRJwN1nHYjOhx2jIHGWF06Q8CNHzzSIibZFhGMtM0xx28H4NnygiIkHh9vp54P3VvLOs4rBT03h8Hn42/2fM3TqXe4bew/UDrg9itdIm1JVbwXRPOK1eA6YfMCC1Pwy6DHqMsQJqbPpRLyciIm2bwqqIiJxy9U4Pt76+jG827+TuM3px1+ReB3TtbfW1cs+8e5hfMZ/7R9zPVX2vCmK1EhR7uvTuCabli6Ch0joWFgXpw2D8vZA50nr21BH73dcTEZF2R2FVREROqfJdLdzwyhLKdjbz+KX5TC84sAXM6XVy1+d3sXD7Qh4a/RCX5F0SpErlpPC2WnOWNu+Alh3WnKZ7tpt3BI7VWqP07unSG5MGGSOtFtOMkZA6AGz6CiMi0tHpN72IiJwyheV13PjqUtxeH6/dMJLROYkHHG/xtHD73NtZXrOc3479LdNypwWpUvmv+H1W2Cz7ymoVbawKhNGd4G48wpsMiEyAyCSISoLBV1rBNGMkxGUc4T0iItKRKayKiMgp8Z+iKu56awXJXcJ566aR5KYcOH9lo7uR2z67jdU7VvPouEc5N/vcIFUqx83vh9p1UPqVFVDLFoCrzjqWkA3xWZDQMxBEEyEycV8o3bMdEQchtqDehoiItC0KqyIiclKZpslLX5fxv/9eS356HC9eO4yk6PADzqlvreeWT29h/a71/PG0PzKlx5QgVSvHxDRhxyYom78voLbstI7F9YC+50HPCZA1DmK6B7dWERFptxRWRUTkpPH5TR6eWcSr327h7P5d+dNlg4mwH9h6tq1pG7d8dgsVjRX8aeKfOD3j9OAUK0fmcUHteti+0mo1Lf0KmqqsYzFpkDvFCqc9x0NcZnBrFRGRDkNhVURETormVi93vrmCuetruGlCNvef3YeQEOOAczbs2sBtn92G0+vk+SnPM6zrIVOsyalkmtaIu9VF1jOn1UXWsrMYTJ91TlSKFUqzxlsBNSEbDOO7rysiIvI9KKyKiMgJV93g4oZXlrBuewO/vWAA14zqccg5S6qWcOfndxIZFskr57xCXnxeECrtxNzNULMeqvcLpdVrwFW/75y4TGvk3X7nW+vUAZCYo3AqIiKnhMKqiIicMK1eH3PX1fC/s9ZS5/Twt2uHM7FPyiHnzSmbwwNfPUBml0yenfIsXaO6BqHaTsLjhB0brWBau27fevcWwLTOsUdDan8YcJG1Th0AKX01d6mIiASVwqqIiPzX1lTW886yCj5YWUldi4eMhAjevnk0A9IODTuvr32dPyz5A0NShvDEpCeIDVcgOiE8Lti56TChtAxMv3VOSCgk9oLuQyD/ykAw7W8NihQSEtTyRUREDqawKiIi38uuZjcfrKjkX8sqWLe9AbsthCn9U7lkaDrjeyVjO+j5VL/p58/L/szLRS8zOXMyj41/DEeoI0jVdwCmCeWLYfW/oOQL2FWyL5QaNkjMha4DYeClkNIHkvtaXXhtYcGtW0RE5BgprIqIyDHz+vzM31TLv5ZW8Nm6ajw+k4FpsTw8rT/n53cnLtJ+2Pd5fB5+9c2v+HfJv7ms92X8YsQvsGlOze+ndgOsetsKqXVbINQB2ROh//T9QmkuhB7+30JERKS9UFgVEZGjKq5p4l/Lynl/eSU1ja0kRtn54egsLhmWTp+uMd/53mZPMz/54id8u/1b7hhyBz8a+CMMDdBzfBq2wep3YPXb1ii9Rghknw6n3w99poLju/8NRERE2iOFVREROSyXx8fMwm28sXgrK7bWYQsxmNg7hUuGpTOxdwr20KM/47jDuYPbPruNjbs38vCYh7mw14WnoPIOwlkHaz+0WlDLFgAmpA2Fsx+zWlG7pAa7QhERkZNKYVVERA6wvd7J6wu38ObicnY1u8lNiebBc/tywZA0kruEH/N1tjRs4eZPb2aXaxdPTHqCCekTTmLVHYTHCZs+sbr5bvoEfG5IyLFaUAdeYj1zKiIi0kkorIqICKZpsmzLbl7+pow5a6rwmyZT+qZy3ZgsRuckHne33dW1q7l97u0A/O3MvzEweeDJKLv983lh23Io+RJKv4TyRVZAjU6F4TOsgNp9iOY1FRGRTklhVUSkE3N5fMxatZ1XvillTWUDMY5QbhzXk2tG9SAjIfK4r1fnquPdTe/y3KrnSHAk8NyU5+gR0+MkVN5O+f1Qs9YKpiVfwpZvwN1oHes6EEbcBLlnQM8JoAGoRESkk1NYFRHphKrqXYGuvlvZ2eymV0o0v7twABcOSSPSfvwfDRt2beDN9W8yq2QWrb5WRncbzSPjHyEpIukkVN+OmCbsLoXS+YHW0/nQssM6lpADgy6BnqdB1niISgxurSIiIm2MwqqISCdhmibLt+7m5a+trr4+0+SMQFffMd+jq6/X72Ve+TzeWP8GS6qW4LA5OC/nPK7ocwV58Xkn6S7aMJ/Hmuu0dgPs2GCtty6C+q3W8eiukDvZCqfZp0FsenDrFRERaeMUVkVEOoFlW3bx6MfrWbplN10coVw/NotrRmWRmXj8XX3rW+t5d9O7vLX+LbY3b6dbVDfuGXoP03tNJzY89iRU38Z4nLBj04GhtHYD7NoMfu++82IzoFs+jL3TCqhJvfTsqYiIyHFQWBUR6cBKapv4w5wNzCmqIrlLOA9P689FBelEhX//rr7/Lvk3Lp+LEV1HcN/w+zgt4zRCQzr4x8mSF2HjJ1Y43b0FMK39RggkZENSb+hzLiT3gaQ8awmPDmrJIiIi7V0H/3YhItI51Ta28sTcTbyxeCuO0BDumZLHjPE9j/t5VK/fy5flX/KP9f/Y29X3B9k/4Mq+V3aerr6LX4CP74XEXtbIvPlXWGE0uY81lUzosU/nIyIiIhbv7t20rluHa926I56jsCoi0oG0uL28+FUpz325GZfXz5UjMrlzcq/jmh8VYHvTdt4vfp/3Nr1HdUs13aK68ZOhP2F67nTiHHEnqfo2qORLmH0f5J0Nl7+hEXpFRESOk2maeGtqcBWtxbVuLa6163CtW4t32/ajvldhVUSkA/D6/LyzrILHP91ITWMrZ/fvys/O7k1O8rF3RfX6vcyvmM+7m95lQeUCTNNkTNoYfjHiF52jq+/Bdm6Gt39otaJOf0FBVURE5ChMvx9PeTmutYFQunYtrnXr8O3aZZ1gGNizsogcUoDjqr44+vYlvG9fSEg47PU62TcPEZGOxTRNPl9fw2Oz17OppomCzDieubqAoT0O/0v/cCqbKnlv03t8sOkDapw1JEckM2PgDKb3mk5adNpJrL4Nc9bBG5dZz6Re8SY4YoJdkYiISJtjejy4iopoXryElsWLca5cib+pyToYFkZ4bi7RE0/H0bcfjn59cfTuTUhU1DFfX2FVRKSdKiyv45GP17GodBc9k6J49uoCzurf9ZimoPH4Pcwvn8+/Nv2Lbyq/AWBc2jgezHuQCekTOl8r6v58XnjnBmt+1B9+CAk9g12RiIhIm2C63TjXFNGyxAqnLStWYLa0ABDeK5eYqT8gYsAAwvv2JbxXL0Ls9v/q53XibyMiIu2Px+dn3oZa3l5azqdrq0mMsvPbaf25fEQmYbaQo76/orGC9za9x/vF77PDuYOUyBRuzr+Z6bnT6Rbd7RTcQTvw6a9g81w47y+QNS7Y1YiIiASNFU7XWMF08RIrnDqdAIT36kXchRcSOWIEkcOHEXqErrz/DYVVEZF2YO22Bt5ZVsGHKyvZ2ewmKdrOnZN7cdOEbKKPYRqaTbs38eSKJ/mi/AtCjBAmpE3g4ryLGZs2tnO3oh5s2auw8GkYeSsMvS7Y1YiIiJwSvoYGPJWV1rJtG57KSlwbN+JcsRLT5QIgvHdv4i66iMgRw4kcPpzQ+PiTXpe+oYiItFE7mlr5YEUl7y6vZN32Buy2EM7ol8JFBelMyEs+5pbUp1c+zaySWUSHRXNL/i1c1OsiukZ1PQV30M6UfQ3//inkTIIz/zfY1YiIiJwQpmniD4RR9wGBdNvegOpvbDzgPUZkJPasHsRdeglRI0YQMXToKQmnB1NYFRFpQ9xeP5+vr+adZRXM21CL12+Snx7Lb6f157z87sRFHtuzHzucO3iu8Dne2fQONsPGdQOu48YBNxIbHnuS76Cd2l0Gb18D8T3g4pfBpo9HERFpn0zTxFNeTsvixTQvXkzLkqV4tx84TUxIZCRhaWmEpaUROXTo3u2w7t0JS0/DFhd3TGNgnGz6NBYRCTLTNFlT2cA7y8r5sHAbdS0eUrqEc+P4nlxckE6v1C7HfK0GdwOvrHmF19e9jtvnZnqv6dw86GZSo1JP4h20c62N8OYV4PfCFf+EiE40j6yIiLR7pmni2bJlbzBtWbwYb3U1ALbERCJHDCfimmsIS7cCqT0tjZDY2DYRRo9GYVVEJEi27GxmZuE2Ply5jU01TdhDQzirf1cuKkhjXG4SocfQzXcPp9fJG+ve4KU1L9HgbuCcnufw48E/JjMm8yTeQQfg98G7M6B2A1z9LiTlBrsiERGR72SaJu6yMmvAo8WLaVmyBG9NDQC2pCSiRgwPDHo0HHt2drsIpUeisCoicgrVNLiYuWo7HxVuo7C8DoDhWfH87sIBTB3UndiIsOO6nsfv4f1N7/Ns4bPUOmsZnzaeOwvupE9Cn5NRfscz92HYOAfO/X+QMzHY1YiIiOxlut14tm3DXV6Oe+tWPFvLcZeX41y9Cl/tDgBCk5OJHB4IpyNGYO+Z1a7D6cEUVkVETrK6Fjez11Tx0cptLCzdiWlC/+4x/OKcPkzN705aXMRxX9Nv+pldOpunVj5FeWM5Q1KG8MfT/sjQ1KEn4Q46qJVvwtd/hmE3wPAZwa5GREQ6IV9TM57yrbi3lu9du8utYOrZvh38/r3nGg4H9ox0okaMDITT4dizOlY4PZjCqojISdDi9vLp2mpmFm7jy421eHwmPZOiuHNSL87L705uSvT3uu4O5w5mbZ7Fe8XvUVpfSl58Hk9NforxaeM79IfVCVe+GGbeCVnj4Zw/gP7biYjISWS63bSWltK6YQOuDRtoXb8B18YNe1tI97DFxRGWmUnE4MHEnH8e9oxM7JkZhGVkEpqS3Ok+6xVWRUROEK/Pz5cba/lw5TY+XVuN0+Oja4yD68ZkcX5+GgPSYr7Xh4zX7+Xryq95b9N7zK+Yj9f0Mjh5ML8f/3vO7nk2IcaxP9sqQF05vHUlxHSHS18D2/F1vRYRETkS0zTx1tbSumEjrRs34Fq/gdYNG2gtKQGvFwAjLAx7r1yix4zFnpMTCKMZ2DMzsXU59kEVOwOFVRGR/9KWnc38c0k57yyroKaxlfjIMKYXpHF+fneGZyUQEvL9/gq6pWEL7296n482f0Sts5YERwJX97uaC3MvJDsu+wTfRSdRt9Ua+dfbCtfOgsiEYFckIiLtmGmauFatovHTT3GuKaJ1wwZ8u3fvPR7atSvhvfOIPu00wvv0xtG7N/YePTDC9IfSY6GwKiLyPbg8Pv5TVMU/l5TzzeadhBgwsXcKlw3PYGKfFMKOYyTf/bV4Wvh0y6e8t+k9ltcsJ8QIYXzaeC7sdSET0ics4EDjAAAgAElEQVQQFqIPt+9t9Tsw6x4w/XDpq5CiQahEROT4maaJa80aGmbPoXHOHDzbtkFYGI6+felyxmTC83oT3jsPR14etjhNh/bfUFgVETkOG6oaeWvJVt5fUUldi4eMhAjuPTOPi4dm0DXW8b2uaZomq3es5r1N7zGnbA7NnmZ6xPTgroK7OD/nfFIiU07wXXQyrY3w8c+g8E1IHw7TX4CEnsGuSkRE2hHTNHEVraVxzmwaZs/BU1kJYWFEjxlD0p130GXSJGwxMcEus8NRWBUROYrmVi+zVm3jrSXlrNhah90Wwpn9U7l8eCZjchK/Vzdf0zRZu2stc7fMZe7WuZTUlxARGsGUHlO4MPdChqYO7XSDKJwUFUvh3Rut7r+n3QcTfg42ffSJiMjRmaZJ67p1NMyeQ8OcOXjKyyE0lKgxo0m6/Xa6TJ6ELTY22GV2aPrEFhE5gsLyOt5cvJWZhdtodvvITYnmlz/oy/SCdBKi7Md9PZ/fx/Ka5Xy+9XPmbp3L9ubthBghDE0dytX9ruacrHOItn+/UYLlIH4ffPU4zHvUGkjpuo+hx+hgVyUiIm2caZq0rl9Pw5z/0DBnNp4tW8FmI2r0aJJuuZkukyera+8ppLAqInKQyjonv525ljlFVUSE2Zg6qBuXj8igIDP+uFs7W32tLNq+iM+2fMa88nnsbt2NPcTOmO5juDX/Vk7POJ14R/xJupNOqq4c3rsJtn4DAy6CHzwOEfpiISIih+erq6P5m29oWvA1zQsW4K2psQLqyJEkzphBlzPOIDRen9XBoLAqIhLQ6vXxwvwS/vpFMQA/nZLHdWOz6OI4vkGNmtxNfFX5FXO3zuWriq9o8bYQHRbN+PTxTM6czPi08USGRZ6MW5A178LMn4DpgwuehfzLNYeqiIgcwPT5cK5aRfOCr2la8BWu1WvA7yckNpaoMaOJHjeO6IkTCU3QiPHBprAqIgJ8sb6G38wsomxnC+cM6MqDP+hLevyxB8pWXytfbP2CmSUz+Xbbt3j8HhIdiZybfS6TMyczousI7Lbj7zosx6i1ET7+ORS+AWnD4KIXIEHT+4iIiMVTXU3zggU0LVhA8zff4q+vB8MgYtAgkm69lejx43AMHIhhswW7VNmPwqqIdGrlu1r4zcy1fLaumuzkKF67YQQT8pKP6b2mabJqxyo+LP6QOWVzaHQ3khqZyhV9rmBy5mTyk/OxhehD76SrWGYNorS7DMbfC6ffDzZN8SMi0lmZpomnshLXmiKchYU0f/01rRs3AhCanEyXyZOJHjeWyNGj1b23jVNYFZFOyeXx8eyXm3lm3mZsIQb3nd2HG8f1xB569PlRq5qrmFUyiw+LP6SsoQyHzcEZPc5gWu40RnQdQYjx/eZYlePk98GCP1mDKEV3hev+DVljg12ViIicQqZp4qmowFVUtN+yFl99vXVCWBiRQ4eS8rN7iRo3jvC8PI22344orIpIp2KaJp+tq+HhWUWU73IydVA3HvxBX7rFRnzn+5xeJ3O3zuWj4o9YuH0hJiZDU4dyw4AbmNJjikbxPdXqK6xBlLZ8Df0vhKl/ggj9dVxEpCMzTRNPefneUOosKsK1dp3VpRcgLIzwXrl0OXMKjv79cfTvT3heHiHh4cEtXL43hVUR6TTKdjTzm5lFfLGhll4p0bwxYyRjcpOOeL5pmqyoWcGHmz/kP2X/odnTTFp0Grfk38J5OeeR0SXjFFYvexW9DzPvAp8Xpj0Ng6/UIEoiIh2Qv6UF56pVtCxfjnP5CpyrVuFvaLAOhoXh6NWLmDPP3BdMe+cRYtf4EB2JwqqIdHgen58n5m7iuS9LsIeG8Msf9OXaMVmE2Q7fXdc0TT7b+hl/Wf4XtjRsISI0gjN7nMm03GkMTR2qbr7B0toEs++Dla9D9wK46EVIzAl2VSIicoJ4qqtxLl9Oy/IVOJcvx7V+Pfh8YBiE5+YSc9ZZOAYMCLSY9lIw7QQUVkWkw3v561Ke/LyYCwZ354Fz+5IS4zjiuSX1JTy66FEWbl9I7/jePDLuESZnTtZUM8FWuQzenQG7SmH8T+H0X2gQJRGRdsz0+WjduHFvq2nLiuV4t20HwHA4iBg0iMQfzSCyoICIwYOxxcQEuWIJBoVVEenQXB4fL3xVytjcRP58+ZAjntfsaea5wuf4+9q/ExEWwQMjH+CSvEsIDdGvyaDy++Drv8AXv4PoVLhuFmSNC3ZVIiJyjEzTxLt9O62bN9O6eTPuzSXW9oYN+JubAWuE3oiCAiKvvZaIggIcffpghOkPkqKwKiId3HvLK6ltbOVPlw4+7HHTNJlTNof/t+T/UeOs4cLcC7mr4C4SIxJPcaVyiPpKeP9mKPsK+l0A5/1ZgyiJiLRRpteLu7wcd0kJrcWbcZdsprV4M62lpZgtLXvPs8XFYc/NIXba+UQMGULEkALC0rprhF45LIVVEemwvD4/z83fzKD0WMbmHho+i3cX8+jiR1lctZi+CX15fOLj5CfnB6FSOcTaD+GjO8HngWlPweCrNIiSiEgbYZom7pISWpYtw7lsGa6163CXlWF6PHvPCU1NJTwnh7iLLiI8J4fwnGzsOTmEJiQEsXJpbxRWRaTD+nhNFVt2tvDs1QUH/MW2yd3EM4XP8Ma6N4gMi+RXo37FRb0uwhZiC2K1AliDKM25H1b8XYMoiYi0EabHg2vtWlqWLd8bUH11dQDYEhOJGDiQ6NMmYM/OITw3B3t2NrZoTekm/z2FVRHpkEzT5Jl5m8lOjuLMfl337ptVMovHlz3OTudOpveazl0FdxHvUNfSNqFyeWAQpRIYdw9MfECDKImIBIG/uZmWlStx7gmnhYWYLhcAYT0yiZ44kchhQ4koKMCelaUuvHLSKKyKSIc0b2Mt67Y38IeLBxESYrBh1wYeWfQIy2uWMyBxAE9OepIBSQOCXaYAmCYsedFqUY1OhWtnQs/xwa5KRKRDM00Tf3097opKPBXleCoqcJdX4FqzZt+UMSEhOPr0Ie7SS4gsGEpEwRDCUlKCXbp0IgqrItIhPfPFZrrFOrhgcBoLty/klk9voYu9C/8z+n+4sNeFmiu1rfC44N8/teZOzTsbLngGIvU8k4jIieBvbcVTWRkIouV4AsHUCqgV+BsbDzjfFhdHeF4eSTffRETBUGvKmOioIFUvorAqIh3Q0rJdLC7bxUNT+2EPDeHplU+THJnMO+e9Q2x4bLDLkz3qK+Hta6w5VE+7D067H0L0RwQRke/Du3MnrqIiXEVFOIuKcK1du3fe0j2M8HDC0tOxp6cTWVBgbWekE5ZuLXrOVNoahVUR6XCenreZ+MgwLh+RwfLq5ayoWcH9I+5XUG1LtnxrBVWPEy77B/SdGuyKRETaDW9trRVIi4pwFa3FVVSEt7p673F7VhaRg4dgv/hi7OnphKVnEJaeRmhysp4vlXZFYVVEOpR12xv4fH0N90zJI9IeyourXyQ+PJ7pvaYHuzQB6/nUpX+D2fdBXA+4dhak9Al2VSIibZLp9eKpqKC1pBTX2rV7W069NTXWCYZhBdPhw3H074+jfz8c/fqphVQ6DIVVEelQnv1yM1F2Gz8c3YMNuzbwVeVX/Hjwj4kIjQh2aeJttZ5PXfF36HUmTH8BIuKCXZWISND5Ghtxl5biLi2ltaQUd0kJraUluLdshT1zlxoG9uxsIkeNxNGvHxH9+xPet5+eKZUOTWFVRDqMrTtbmFm4jRvH9SQu0s4jS/5GZGgkl/e5PNilScM2+Oc1ULkUxt9rTUujeW1FpJPx1dXhXFOEu2QzraWluAPB1Ftbu++k0FDsGRnYs7PpMnEi9p7Z2Htm4cjLIyRKwVQ6F4VVEekwnpu/mdCQEGaMz6a8oZz/bPkPP+z3Qz2rGmxbF8LbP4TWJrj0Neg3LdgViYicdKbHg2vjRlyrVuFcWYizsBB3Wdne4yExMYT37EnUuHHYs3sSnp1tBdOMdIwwzTEtAgqrItJB1DS6+NeyCi4amkZqjIOHv30Zm2Hjmn7XBLu0zm3pS/DxzyE2Ha75AFL7BbsiEZGTwlNdbYXSVVYwda0pwnS5ALAlJhKRn0/shRcSMWgg4Xl52BISNNiRyFEorIpIh/DSgjK8Pj83TcihtqWWD4o/YFruNFIiNXl5UHhbYfbPYdkrkHsGXPQiRMQHuyoRkRPC73bjWlOEc8UKnKtW4SwsxFtVBYARFoajXz/iLr2EiPx8IvIHE5bWXcFU5HtQWBWRdq/e6eH1hVs4Z2A3eiZF8fjS5/CZPm7of0OwS+t8fF6oWAKfPgQVi2HcT2DSr/R8qoi0a95du3CuXIlz+XJalq/AtWYNptsNQFh6OpFDhxKRP4iI/HzC+/YlxG4PcsUiHYPCqoi0e68v3EJTq5dbT8uhvrWef274J2f1OIuMmIxgl9Y5tOyC4s9g43+stasOwqLg4pdhgKYMEpH2xTRN3KWle4Opc/nyfc+ahoUR0a8f8VddRUTBECKHDCE0KSmo9Yp0ZAqrItKuuTw+XlpQyml5yQxIi+X5Vc/T4m3hhoFqVT1pTBOqVsOm/8DGT6wRfk0/RCVD73Mh70zInqhpaUSkXfC3tOAqKqJl5Uqcy1fgXLECX10dALa4OCKGDCF2+nQiC4bgGDCAEIcjyBWLdB4KqyLSrr29tJydzW5uOz0Hp9fJ62tfZ1zaOPok9Al2aR1LaxOUfmm1nm76FBq3Wfu7D4EJP7fmTe0+BEJCgluniMh3MP1+3GVbcBYW4ixcibNwFa0bN4LPB4A9K4voSZOILBhCREEB9p499aypSBAprIpIu+Xx+XnuyxIKMuMY0TOBN9e/ye7W3cwYOCPYpXUMrgYoeg+KPoAtX4PPDfYukDMR8s6C3CnQJTXYVYqIHJGvrg7n6tV7p45xrlqFv6EBgJDoaCIGDST6ph9ZAyENGkRoQkKQKxaR/Smsiki7NbNwG5V1Tn5zfn+8ppdXil5hSMoQhqYODXZp7ZffD1sWwIrXYe1H4HVCYi6MuMkKqBmjIFQDh4hI22P6/bRuKsa5YjnOFSsPnNc0JITwXr2IOfvsvQMh2bOzMdQbRKRNO2pYNQzDAcwHwgPnv2Oa5q8Nw0gA/glkAWXApaZp7g685xfAjYAPuNM0zf8E9g8FXgEigI+Bu0zTNE/sLYlIZ+D3mzz75WZ6p3ZhUp8UZpXOZHvzdh4c+WCwS2ufdm+Bwjdh5T+gbiuEx0L+5TDkakgbCuoGJyJtjL+lBeeqVbQsX249a1pYiL+xEQBbUpI1r+n06Var6YD+hERFBbliETlex9Ky2gpMMk2zyTCMMGCBYRizgenAXNM0HzMM437gfuA+wzD6AZcD/YHuwGeGYeSZpukDngFuAhZihdWzgdkn/K5EpMObu76GjdVN/PmywWCY/G313+gV34sJ6ROCXVr74W6BdTNh5etQOh8wIPs0mPQQ9J0KYRHBrlBEZC9PdfUBI/S61q+3njU1DMJzc4k599y9z5qGpafrWVORDuCoYTXQ8tkUeBkWWExgGnB6YP+rwDzgvsD+t0zTbAVKDcMoBkYYhlEGxJim+S2AYRivARegsCoix8k0TZ6eV0x6fARTB3VjXvk8SupLeGz8Y/pycjSmac2DuuJ1KHofWhsgrgdMfNBqSY3LDHaFIiKYbjeuDRut50xXrKBlxXK827YDYDgcRAwaROKPZhBZUEDE4MHYYmKCXLGInAzH9MyqYRg2YBmQCzxlmuYiwzBSTdPcDmCa5nbDMFICp6dhtZzuURHY5wlsH7xfROS4LCzZxYqtdfx2Wn9sIQZ/W/030qPTOSvrrGCX1na5W2D5a7D0b7BjI4RFQr9pMPgq6DFWo/iKSNCYpom3qsoKpoGBkFxr12K2tgIQmpJCREEBkddeS0RBAY4+fTDCwoJctYicCscUVgNdeAcbhhEHvG8YxoDvOP1wzRrmd+w/9AKGcRNWd2EyM/VXfhE50DNfbiYp2s4lwzJYUrWEVTtW8atRvyI0RGPGHaK1EZa8CN/8FVp2QPpwOP9J6HcBONQSISKnnr+lBeeaNbhWrdobUL21tQAYdjuO/v2Jv+IKIgYHRujt1k29ZkQ6qeP6ZmeaZp1hGPOwnjWtNgyjW6BVtRtQEzitAsjY723pwLbA/vTD7D/cz3keeB5g2LBhGoBJRPZaVVHH/I21/Pzs3jjCbLy4+kUSHYlMy50W7NLaFuduWPQcLHwGXHWQMwnG3wtZY4NdmYh0cKbPh3fnTrzVNXhrqvFUV1vb1dW4Nmw4YF7TsB6ZRI4eRcSgfCLy83H0zsOwa8RxEbEcy2jAyYAnEFQjgDOA3wMfAdcCjwXWHwbe8hHwhmEYj2MNsNQLWGyaps8wjEbDMEYBi4AfAk+e6BsSkY5rU3UjM15dSmKUnatH9aBoZxHfbv+WuwvuJtwWHuzy2obmHfDtU7D4BXA3Qu9zrZCarul8ROTEMH0+XEVFuMvKDgiinprAdm3t3jC6l81GaHIy4dnZdLn5JiuYDhpEaHx8cG5CRNqFY2lZ7Qa8GnhuNQR42zTNWYZhfAu8bRjGjcBW4BIA0zSLDMN4G1gLeIHbA92IAW5l39Q1s9HgSiJyjNZU1vPDlxZjCzF486ZRxDjC+NvCv9ElrAuX9b4s2OUFX8N2+OZJWPoSeF3Q/wIY/1PoOjDYlYlIB+Crq6Npwdc0ffklzV99ha+ubu+xkKgoQrt2JSw1hfBRowhNTSU0NYWw1FRCU6zt0MREDJstiHcgIu3RsYwGvAoYcpj9O4HJR3jP74DfHWb/UuC7nncVETnE8q27ue6lxUSHh/KPH42iZ1IUpfWlfLblM2YMnEG0PTrYJQZP3VZY8GdY8Xfw+2DQpTDuHkjOC3ZlItKOmaZJ68aNNM37kqYvv8S5ciX4/dji44k+bQJREybg6NuX0JRUbNGav1RETg6NRiIibdrCkp3c+MoSkrqE848ZI0mPjwTglaJXsNvsXNX3qiBXGCS1G+Hrv8CqtwADhlwFY++GhJ7BrkxE2il/SwvNCxdaAXX+fLxVVQA4+vUj6ZabiZ4wAcfAgWohFZFTRmFVRNqsLzfWctNrS8lIiOQfM0aSGuMAoKq5io82f8TFvS4mMSIxyFWeQi27YM27UPgWVC6FUAcMuxHG3gmx6Ud/v4jIfkzTpHXTJloWLqJp/nxaFi/GdLsJiYwkauwYon98O1HjJxCWmnL0i4mInAQKqyLSJn1SVMWP31hBbko0f79xBInR+wZQem3ta5imyXUDrgtegaeK1w3Fn8LKN2Djf8DvgZR+MOVhyL8CovUlUkSOjWmauEvLaFm8iOZFi2hZvATfzp0A2LOyiL/iCqJPm0DEsGGEaEReEWkDFFZFpM35cGUl97xdyMC0WF69fgSxkfsmf69z1fHOxnc4t+e5pEWnBbHKk8g0oXI5FL5ptaQ6d0FUMoy4CfIvtwZN0pyDInIUpmniqaigZdEimhctpmXRIrw11kyDoampRI0dQ9TIkUSOHIk9Xb0zRKTtUVgVkTbl7SXl3PfeKoZnJfDSdcOJDt/3a8rj8/Cbb3+D0+vkhgE3BLHKk6SuHFb90+rmu3OT1c2397lWC2rOJLDpV7aIHJlpmni3baN5yRJaAuHUs82a0t6WmEjUyBFEjhhJ5MgR2LOyMPRHLxFp4/TNR0TajFe/KePXHxUxvlcSz18zjAj7vkE83D43P533U+ZVzOO+4feRG58bxEpPoIbtVjffVW9D2QLAhB5jredQ+00DR2ywKxSRNsTX1IynsgJPeTnuigo85RV4Kiqs7cpKTJcLAFtsLJEjRpBw4w1EjRyJPSdH4VRE2h2FVRFpE579cjOPzV7PlH6p/PXKIYSH7guqLq+Lu7+4m6+3fc0vR/6Sy/q043lVva2w9Vso/gyKP4eaImt/QjZMfMCaeiY+K6glikhw+V0uWjdswLVhgxVGKytwB0Kpb/fuA84NiYoiLCMDe88sosePJywzg8iCAsLz8jBCQoJzAyIiJ4jCqogElWma/OmzTTwxdxPn5Xfn8UvzCbPt+4LV4mnhjs/vYEnVEh4e8zAX9rowiNV+D6YJu0qgeK4VUMu+Ak8L2OyQOdoaKCn3DGvQJLV6iHQ6fpeL1vXrcRYV4Spai6uoiNbiYvD5rBNCQwlL6449LR3HlCmEZaRjT08nLD2DsPQ0bHFxajEVkQ5LYVVEgsY0TR75eB0vfFXKpcPSeXT6IGwh+750NbmbuH3u7aysXckj4x9havbUIFZ7HFobofQrK5xungu7y6z9Cdkw5GrImQxZ4yA8Oqhlisip5Xc6ca1fvzeUuoqKaN28eW8wtSUk4Ojfn+jTT8fRvx+Ofv0I69ZN85qKSKelsCoiQbGyvI6/fLaRLzbUcu3oHvz6vP6E7BdU61vrufWzW1m3cx1/mPAHzso6K4jVHoPGKlg3E9Z9BFu+taaYCYuCnhNg9I8hd7IVVkWkUzH9fur++U92v/GmFUz9fsAa8MjRvx/RkycR0b8/jv79Ce3aVa2kIiL7UVgVkVNqcekunvx8E19t2kFcZBgPnNuHH43PPuALWp2rjps+vYniumIeP/1xJmZODGLF36G+0gqoaz+0nkPFhKQ8GH2b1bU3YySEhh/1MiLSMbWWlLL9oV/hXLqMiMGDSbrlZhx7gmlqqoKpiMhRKKyKyElnmiYLinfw5OfFLC7dRVK0nV+c04erRvU4YGoagB3OHdz06U1sqd/CE5OeYFzauCBVfQT1FVY4XfshlC+y9qX0g9Pvh34XQEqf4NYnIkFnejzsfOlldjz1FEZEBN0efZTYC6YpnIqIHCeFVRE5aUzTZO66Gp78opjC8jq6xjj49Xn9uHx45gHT0uxR01LDjE9msL1pO0+d8RSjuo0KQtWHsXvLvoBaudTalzoQJv7Sml4mOS+49YlIm+EsKmL7L39F67p1dDn7bLo++AChycnBLktEpF1SWBWRE87vN5lTVMWTnxezbnsD6fERPHLhQC4amnbAlDT72960nRs/uZGdzp08c8YzDOs67BRXfZDmHbDidVj7AWxbYe3rlg+TH7JaUBNzglufiLQpfpeLHX/9KztffgVbQjxpTz5BzJQpwS5LRKRdU1gVkRPG6/Mzc9U2nvpiM8U1TWQnR/F/l+Rz/uDuB0xHc7CKxgpmfDKDhtYGnj/zefKT809h1Qep3QgLn4LCt8Drgu4FcMZvrBbUhJ7Bq0tE2qzmxYup+tVDuLdsIfbii0j92c+wxcYGuywRkXZPYVVETohPiqr43cfr2LKzhT5du/DXK4dwzoBuB0xFczhl9WXM+GQGTq+TF856gf6J/U9RxfsxTWv+02+fgo1zwBYO+ZfBqNv1DKqIHJGvsZGaP/4/6t5+m7CMDDJffomo0aODXZaISIehsCoi/7WPCrdx91sryEvtwvPXDOWMvqkHTENzJKtrV3Pn/2fvvuOrLO83jn+enOxNgAwSICSQsGRPEQUEcW9wVQQZKm5rS7W29te6WnFbFwoWBwpii1tARGRD2IGEEVbIIoHMc5Kc8fz+OBEBWQkhJ+N6t+eVk2d+Y4mcq/f9fO8fH8Blupg+cjrJEcl1UO1RnHZI/S+seB2yN0Jgc7joT9B3AgTrGTMRObmSRYvI+dv/4cjPJ2LcOFo+cD9eAQGeLktEpFFRWBWRs/LN5mwe/nQDfeIjeH9cXwJ9T/2vFdM0WZ2zmulbprM8azktA1oyfeR0EsPr8BlQWyGkvA+r3oaSLPdyM1e9At1uAh992BSREzNNk8rde8h//TWKv/kWv6Qk4v79OgHnnefp0kREGiWFVRGpsfmpOTwwaz09W4czY+ypg6rT5WTR/kW8t/k9UgtSae7fnAd7Pcjo5NGE+obWTcGH98DKN2HdB2Avg3YXwlUvQ/sR4HXyZ2pFpGkyHQ7K09KxpazFujYF67p1OAsKwMeHFg/cT4sJEzB8fT1dpohIo6WwKiI18sO2XO79eB3nxYUxY1xfgvxO/K+TSmclX+z6gvdT32dv8V5ah7TmLwP+wjXtr8HP4lc3xVoPwVcPwbYvwfCCrjfCwMnu7r4iIlVcNhu2jZuwpqzFlrIO24YNuKxWAHzi4gi+YBABvXoTfMEgfGJjPVytiEjjp7AqItW2OD2Pez5cR6eYUP5zZz9C/H1+c0xpZSmzt8/mw60fctB2kE4RnXj+oucZ0WYEFq8TL19zzix6CtK+hkEPQr9JENqqbu8vIvWSs6gI69pfRk1TKE/dCg4HGAZ+ycmEXXstgX16E9CrFz7R0Z4uV0SkyVFYFZFqWbojn0kfpNAhKpgP7uxP6HFBNd+Wz4dbP2R2+mxK7CX0j+nP0xc8zYCYARjG6Zsu1brDe2HdTOg1Bob/re7vLyL1irO0jNJFP1D8zbeULlsGdjuGry/+3c6j+Z13usNpjx5YQuvo8QQRETkphVUROWMrdhUwYeYaEloE8eH4/oQF/hpUs0qzeHfzu8zbOQ+7y86ItiO4s+uddGnhgaVojrbkX+6pv4Mf9WwdIuIxLpuN0p9+ovjrbyhdsgSzogLvmBgibr+dkGFD8T/vPLz86uixBBEROWMKqyJyRlbvPsSd76+hTUQgH03oT7OgX5uKZBRmMO77cZRUlnBN+2sY22UsbUPberDaKgW7YMMs99TfMD1fJtKUuCorKVu6lOKvv6Hkxx8xrVYsLVsQPmoUoZdfTkCP7hhqrCYiUq8prIrIaaXsPcS4GatpFe7PRxMG0Dz41xGIPUV7GD9/PAYGn131GQnhCR6s9DiLnwNvP7jgYU9XIiJ1wLTbKVu5kuJvvqVk4UJcJSVYwsMJu+oqQi+7jMC+fTAsdfzMvIiI1JjCqoic0vp9h7lj+hoiQ/2ZNXEALUN+Dar7i/czfv54XKaL6SOn16+gmrcNNs+BQQ9ASJSnqxGRc8i2JZXCuZ9R8u13OAsL8QoJIWT4cEIvv5ygAf0xfDbi9vAAACAASURBVH7bBE5EROo/hVUROalNmYWMmb6aiCBfPp7Yn8hQ/yP7MksyuXP+nVQ6K3lv5Hskhid6sNITWPws+AbDoIc8XYmInAPO4mKKvvqKws8+o2LrNgx/f0IuvpjQKy4n6IIL8NL6pyIiDZ7Cqoic0JYDRdz+3mrCAnyYNWkAMWEBR/ZllWYxYf4ErHYr7418j6RmSR6s9ASyN8HWeXDRFAiM8HQ1IlJLTNPElpJC4Zw5FH/3PWZFBX6dOxH95F8JveIKdfAVEWlkFFZF5DfScoq5/b1VBPlamDVxALHhvwbVnLIcxn8/nuKKYqaNnEbHiI4erPQkfnwG/MNgwGRPVyIitcCRn0/RvHkUzvmMyj178AoOJuz66wi/8UYCuni447iIiJwzCqsicowduSXcNm0Vft4WZk0aQOuIwCP78qx5jP9+PIcrDvPOiHfo0rwefkjMXAvbv4Vhf4GAcE9XIyI1ZDqdlC1fTuGczyhZtAgcDgJ69ybmrrsIvXQkXgEBp7+IiIg0aAqrInLEzrxSbpm2CouXwccT+9O2edCRffm2fMZ/P558Wz5vj3ibbi27ebDSU/jxaQhsDv3v9nQlInKGXJWVOLKzsR84QOWBA1Tu2UPxt9/iyMrGEhFBxJgxhN94A34J9aiJm4iInHMKqyICwO78Mm6dthIw+XjiQBJaBh/ZV2ArYML3E8i15vLm8DfpEdnDc4Weyt7lsGsRXPIU+AWf/ngRqROuigrsWVnu14ED2A/88vUA9qwsHHl5YJq/nmCxEDRgAFF/nELIsKEYapYkItIkKayKCPsKrNw6bSUOl8knkwbQPvLXoHe4/DATF0zkQOkB3hj+Br2jenuw0lMwTVj0FARHQZ/xnq5GpEkzKyspW72GkoULKF2yBEdW9rEHWCz4xMTgExtL0Pnn4xMbW/VqhW9sLN5RURje+ogiItLU6W8CkSZu/yErt0xbic3u5OMJA0iKCjmyr6iiiEkLJrGveB+vDXuNvtF9PVjpaWQshr3L4LLnwTfwtIeLSO1yWa2ULl1KycKFlP64GFdJCUZgIMGDBuF3ww34xMbiWxVKvSMjFUZFROS09DeFSBOWVWjj1ndXUlJu5+OJA+jc6tdlH4ori5m0YBK7Cnfx2rDXGNhqoAcrPQ3TdD+rGhoHve/wdDUiTYazsJCSHxdTsnAhZUuXYlZUYAkLI2T4cEJGDCfo/PPx8vc//YVEREROQGFVpInKKSrnlmkrKSyz8+GE/nSNDTuyr7SylHsW3MP2w9t5ZegrDIod5MFKz8CO+ZC5Bq56Bbz9PF2NSKNmz8mhZOEPlCxciHXNGnA68Y6OJnzUKEKGDyewT2+NmoqISK3Q3yYiTVBecTm3TltJQWklM8f3o3vrX5d4cbgc3L/ofrYWbOWFIS9wYdyFHqz0DPzyrGqzeOhxm6erEWm0HAUFZD7wILaUFAB8ExJoPn48ISOG49+1K4ZheLhCERFpbBRWRZqYgyUV3PruKnKKy5l5Zz96tWl2zP7X17/O2ty1PHPBMwxrM8xDVVbDti8hZxNc+xZYfDxdjUijVfj559hSUmjxwP2EjhyJX2Kip0sSEZFGTmFVpAk5VFbJ795dReZhK++P60ef+Ihj9i89sJT3trzHjUk3clXiVR6qshpcTvjxGWjeAbqN9nQ1Io1ayfwF+HftSsvJkz1dioiINBFeni5AROpGobWS295dxZ6CMqbf0ZcBCc2P2Z9blsvjPz9OUrMkpvSd4qEqqyn1v3BwGwx9DLwsnq5GpNGyZ2VRvnkzIZdc4ulSRESkCdHIqkgTUGS187v3VrHrYCnvjunD+e1bHLPf4XLwxyV/pNxZztSLpuLv3QC6dzodsPhZiOwCna/zdDUijVrJggUAhF4ywsOViIhIU6KwKtLIFZfbGTN9FdtzSnn79t5cmNTyN8e8seEN1uWt49nBz9IurJ0HqqyBTZ9CwU646SPw0iQRkXOpeP4C/JKS8I2P93QpIiLShOgTnkgjVmSzc8f01aRmFfPGbb0Y2jHyN8csO7CMdze/yw0dbuDKhCs9UGUNOCrhp+cgpgd0vMLT1Yg0ao6DB7GtW6cpwCIiUuc0sirSSBWUVnD7e6vZkVfC67f2YnjnqN8ck2fN4/Glj5MYnsiUfg3kOVWADR9C4T644kXQchki51TJwoVgmoRoCrCIiNQxhVWRRii7yMbv3l3FgUIb08b0YUjyb0dUHS4HU5ZMweaw8cKQFwjwDvBApTVgL4efnofW/aH9cE9XI9LoFc+fj298PH4dOni6FBERaWI0DVikkdlXYGXUWyvILa7gP+P6nTCoAry58U3W5q7lLwP+QkJYQh1XWUP2cvj6ESjJgqF/1qiqyDnmOHwY6+o1hFxyCYZ+30REpI5pZFWkEdmRW8Jt766i0uni44n96RYXfsLjlmctZ9qmaVzX/rqGsZ4qwKHdMHsM5GyCC/8ACRd5uiKRRq900SJwOvW8qoiIeITCqkgjsTmziDHTV+Ft8eLTSQNJjg454XEHrQd57OfHSAxP5LH+j9VxlTWU9jX89x73SOotn0LypZ6uSKRJKJ4/H5/YWPy7dPZ0KSIi0gRpGrBII7B69yFunbaSQF9v5tx18qDqdDmZ8rP7OdWpF02t/8+pOu0w/y/wya3QPAHuWqKgKlJHnCUllC1fQciIEZoCLCIiHqGRVZEG7qftB7nrg7W0Cg/gown9iQk7eQB9a9NbrMlZw1ODniIxPLEOq6yB4mz4bBzsWwF9J8DIZ8Dbz9NViTQZpYsXg92uKcAiIuIxCqsiDdh3W7K5f9Z62keG8MH4frQIPnmYW5m9krc3vs01iddwTftr6rDKGsj4CeaOh0orXP8udBvl6YpEmpyS+fPxjowkoEd3T5ciIiJNlKYBizRQc1MymfzROs6LDeOTiQNOGVTzbfn8acmfSAhL4PH+j9dhldXkcsGS5+GDayEgAib9qKAq4gEuq5XSn5cSMnw4hpc+KoiIiGdoZFWkAfpgxR7+Mi+VQe2b887tfQjyO/mvstPl5E9L/kSZvYx3L3mXQJ/Auiu0OqyH4PNJsHMBnDcKrnwZ/II9XZVIk1S65GfM8nJNARYREY9SWBVpYN5YvJN/fZfO8E5RvH5rT/x9LKc8/p1N77AqZxV/P//vtG/Wvo6qrKbMtTBnLJTmwhUvQp87tYaqiAeVzJ+PpVkzAvv09nQpIiLShCmsijQQpmny/PfpvLF4F9f0aMXUUd3xsZx8ep5pmry16S3e2PgGVydezbXtr63Das+QacLqafD94xAaA3d+D7G9PF2VSJPmqqigdPFiQq+4HMNbHxNERMRz9LeQSANQ4XDy2NzNfL7+ALf0a8NT13bF4nXykUe7087/rfg/5u2ax9WJV/O3gX+rX0tPHNoNW+dB6n8hewMkXQrXvgmBEZ6uTKTJK1u2HJfVqinAIiLicQqrIvVcobWSSR+ksHr3IR4ZkcT9w9qfMniWVJbwyOJHWJm9ksndJ3N397vrR1At2AVb/+cOqdkb3dta9YQrXoDed4KauIjUCyXz5+MVEkJQ//6eLkVERJo4hVWRemxPfhl3vr+GzMM2Xrm5B9f0iD3l8TllOdyz8B72FO3hqUFPeX6Jmvwd7oCaOg9yN7u3xfaBEf+AztdAs7aerU9EjmHa7ZT8+CMhw4Zi+Pp6uhwREWniFFZF6qk1ew4xaeZaAD6a2J++8aeeIrutYBv3/nAvNoeNN0e8yYCYAXVR5m/lpblHT7f+D/K2ure17g8jn4FOV0N4a8/UJSKnVbZqNa6iIk0BFhGRekFhVaQemrfhAH+Ys4nYZgHMGNuX+BZBpzx+SeYSHv3pUcL8wph52Uw6NOtQR5VWMU1Y+x6segfy0wED2gyES/8Jna+G0FZ1W4+I1EjJ/PkYgYEEDRrk6VJEREQUVkXqE9M0eW3RTl5csJ1+7SJ4+3e9aRZ06ql4s9Nn88yqZ0hqlsTrF79OZGBkHVVbpSwf/jcZdnwPcf3g8qnQ6SoIia7bOkTkrJhOJyU//EDwRRfi5e/v6XJEREQUVkXqi0qHiz99vonP1x3gup6xPHfDefh5n3wNVZfp4pV1rzB9y3QGxw5m6kVTCfQJrMOKgYyf4PNJYDsMlz0P/SZqfVSRBsqakoKzoIBQTQEWEZF6QmFVpB4otFZy94cprMw4xEPDO/DgxR1O2cG3wlnBX5b+hW/3fMvopNE81v8xvL3q8NfZaYcfn4GlL0GLDvC7zyD6vLq7v4jUupL5CzD8/Ai+8EJPlyIiIgIorIp43N6CMsbNcHf8femm7lzXM+6UxxeWF/Lgjw+yLm8dD/d+mHFdxtXt0jSH98DcCZC5BnqNgUufA99TP1MrIvWb6XJRsmABQRdcgFeQfp9FRKR+UFgV8aC1ew4x6YMUXKbJhxP606/dqTv+7i/Zz+SFk8kqzeL5i57n0vhL66jSKlvmwpcPAQbcOAO6Xl+39xeRc6J80yYcubmEPvKwp0sRERE5QmFVxEO+2JjFo3M20irMnxnj+tHuNB1/U/NTmfzDZJymk2mXTKNXVK86qhSoLINv/wjrP4S4vnDDe1ojVaQRKZ6/AHx8CB461NOliIiIHKGwKlKHXC6TRWl5TF+2m+W7Cugb34x3bu9z2o6/y7OW89CPDxHhH8Gbw9+kXVi7OqoYyN4En90JBTth8KMw5E9g8am7+4vIOWWaJiXz5xM0YACW0FBPlyMiInKEwqpIHSgpt/NZSibvL9/D3gIrMWH+TLm0I3deEH/Kjr8A32R8w5+X/ZmEsATeHP5m3S1NY5qw6m1Y8BcIbA53fAHt1HhFpLGp2LYNe2Ymze+a5OlSREREjqGwKnIO7S0o4/3le5izNpPSCge92oTzh5HJjOwSjY/F67Tnf7j1Q/655p/0jurNq8NeJdS3jkY9jl47NekyuObfENS8bu4tInWqeP588PIi5OKLPV2KiIjIMRRWRWqZaZqsyChg+tI9/JCWi8UwuLJbDOMGtaN76/Azvsar61/l3c3vcnGbi/nnhf/Ez+J3jiuvcjAdPrgeyvLgsn9Bv0laO1WkESuZv4DAvn3xjjh1gzcREZG6prAqUkvK7U6+2JDF9GW7ScspISLIl/uGtud3A9oSFep/xtdxuBz8fcXf+e/O/3Jj0o080f8JLF6nnipca/avgY9HgZcPjJ8PrXrWzX1FxCMqdu6kMiODZrfd6ulSREREfkNhVeQsZRXamLV6Hx+t2sehsko6Rofwrxu6cXWPVvj7VC9k2hw2/vjTH1mcuZi7u9/N5O6T624N1R0L4NPbISQabv8cIhLq5r4i4jHF8+cDEDJ8hIcrERER+S2FVZEacDhdLE4/yKzV+/gxPQ8TGN4pinGD4hmY0LxGAbOoooj7F93PhrwN/Ln/n7m54821X/jJbPwE5t0LkZ3hd3MhuI6aOImIR5XMX0BAz574ROl3XkRE6p/ThlXDMFoDM4FowAW8Y5rmK4ZhRACfAvHAHmC0aZqHq855DBgPOIEHTNP8vmp7b+B9IAD4BnjQNE2zdn8kkXMn87CV2Wv28+na/eQWVxAZ4sfkIe25qW9rWkcE1vi6uWW53L3wbvYW72XqRVO5JP6SWqz6NJa/BvOfcHf6vekj8NfSFSJNQeW+fVSkpRE5ZYqnSxERETmhMxlZdQC/N01znWEYIUCKYRgLgLHAD6ZpPmcYxp+APwFTDMPoDNwMdAFaAQsNw0gyTdMJvAlMAlbiDquXAt/W9g8lUpvsTheL0vKYtXofP20/CMCQpJb8/Zo2DOsYeUZdfU8loyiDuxfcTXFlMW8Of5P+Mf1ro+zTc7lg4V/dYbXztXD9O+BdR02cRMTjSqqmAIdeoinAIiJSP502rJqmmQ1kV70vMQxjGxALXAMMqTrsP8BiYErV9k9M06wAdhuGsRPoZxjGHiDUNM0VAIZhzASuRWFV6qn9h6x8umY/s9fuJ6+kguhQf+4f1oHRfeKIa1bzUdSjbTq4iXt/uBeLYWHGyBl0at6pVq57Wk47fHE/bJwFfSfCZf+EumriJCL1QvH8Bfh37YpPbKynSxERETmhaj2zahhGPNATWAVEVQVZTNPMNgzjlwdeYnGPnP4is2qbver98dtF6g2708UP23L5ePV+ft5xEAMYmhzJLf3aMCS5Jd5nOYp6tKUHlvLI4kdo7t+cd0a8Q+vQ1rV27VOqLIM5Y2HHfBj6BFz4qJamEWli7NnZlG/aRMtHHvF0KSIiIid1xmHVMIxgYC7wkGmaxadoIHOiHeYptp/oXpNwTxemTZs2Z1qiSI2VlNv5dM1+pi/dTVZROa3C/Hno4iRG940jJiyg1u5jmiab8jfx8baP+X7P9yQ1S+KN4W/QIqBFrd3jlKyH4OPRcCAFrnoFeo+tm/uKSL1yePZsQFOARUSkfjujsGoYhg/uoPqRaZqfV23ONQwjpmpUNQbIq9qeCRw9RBQHZFVtjzvB9t8wTfMd4B2APn36qAGTnDPZRTbeX7aHj1fto6TCwYCECP5+TVeGdozE4lV7o43ljnK+2/Mds9JmsbVgK8E+wdzS8Rbu7XEvwb7BtXafUyrcDx9eD4f3wuiZ0OmqurmviNQr9qwsDk2fQejll+MbH+/pckRERE7qTLoBG8B7wDbTNF88atcXwB3Ac1Vf5x21/WPDMF7E3WCpA7DaNE2nYRglhmEMwD2NeAzwWq39JCLVsDWrmHd/zuCLjVmYwOXnxTBxcDu6xYXX6n2ySrP4NP1TPt/xOYUVhSSGJfJE/ye4MvFKgnyCavVep5S3DT68ASpK4fb/Qvyguru3iNQreS++BEDk7zUFWERE6rczGVkdBNwObDYMY0PVtsdxh9TZhmGMB/YBowBM00w1DGM2sBV3J+F7qzoBA9zDr0vXfIuaK0kdMk2TpTvzeWdJBj/vyCfQ18KYgfGMGxR/VsvOnOg+q3JWMWvbLBZnLgZgWOth3NLxFvpG963RGqxnZd8q99Rfbz8Y9w1Ed63b+4tIvWFdv57ir76i+T13q7GSiIjUe0Z9X+a0T58+5tq1az1dhjRglQ4XX23K4p0lGaTllBAZ4sfYQfHc1q8tYYE+tXafMnsZX+76kllps8goyqCZXzNuSLqB0UmjiQmOqbX7nDGnA5a/Aoufg7DWcPvn0Cy+7usQkXrBdLnYc8stOLKySfzuW7yC6nB2h4iIyCkYhpFimmaf47dXqxuwSENSWuHgo5V7mbFsDznF5SRFBfP8jd24ukcr/Lxrb5mWjKIMPk37lHm75lFmL6NL8y48fcHTjIwfiZ/FQ+uW5m6FeZMhaz10uQ4ufwGCmnumFhGpF4q//pryjZuIefZZBVUREWkQFFalUVqy/SBT5m4iu6ic8xOb8+wN5zEkqWWtTcF1uBz8tP8nZqXPYlX2Kry9vLk0/lJu6XgL3Vp2q5V71IjTActehp/+CX6hMOo/0OVaz9UjIvWCy2olb+oL+HfpQtg1V3u6HBERkTOisCqNSkm5nWe+2cas1fvpEBnM3HvOp3fbZrV2/XxbPnO3z2XO9jnkWnOJDormgZ4PcH2H62ke4OGRy9xU+N9kyN5QNZo6FYLqaEkcEanXCqbPwJGbS+yLL2B41d560SIiIueSwqo0Gst25vPHzzaRXWTj7osSeWh4B/x9zn66r2marM9bzydpn7Bg3wIcLgcDYwbyeP/HuTDuQry9PPxr5LTD0qrRVP8wjaaKyDHsOTkUvPsuIZddSmDv3p4uR0RE5IwprEqDV1bh4Nlvt/Hhyn0ktAzis3vOp1ebsx9NtdqtfJXxFZ+mf8r2w9sJ8Qnh5uSbuSn5JuLD4s++8NqQmwr/uweyN0LXG+Cy5/VsqogcI+/FF8HlIvL3j3q6FBERkWpRWJUGbcWuAv44dyOZh21MHNyO31+SfNajqRlFGcxOn828nfMotZeS3CyZJwc+yeXtLifQp/aWuDkrR4+mBoTD6A+gs55DE5Fj2TZsoPiLL2l+1134xmmpGhERaVgUVqVBslY6+Nd36by/fA/xzQOZc9dA+sRH1Ph6J2qYdEnbS7il4y10b9m97tdGPZWcLe7R1JxNGk0VkZMyTZOcZ5/F0rIFzSdO9HQ5IiIi1aawKg3O6t2H+MNnG9lbYGXcoHj+OLIjAb41G02t1w2Tjmcvh2WvwJLnNZoqIqdV/FXVUjVPP40lWEvViIhIw6OwKg2GrdLJ1PnpTF+2m9bNAvlk0gAGJFQ/UB5pmJT+CQv21sOGScczTdgyFxb+HxTtg643wuXPQ2DNR5JFpHFz2WzkvfACfp07EXadGq6JiEjDVM8+lYuc2Jo9h5jy2SYy8ssYM7AtUy7tSJBf9f74NoiGScfbtwq+fxwOrIXo8+CaLyDhIk9XJSL1XMH06Thycoh9/l9aqkZERBoshVWp1/YfsvLcd2l8vSmb2PAAPp7Qn/PbV2/t0N1Fu/k0/dP63TDpeIcyYOHfYOs8CI6Ga96A7jeD19kvxSMijZt7qZr3CBk5ksC+fT1djoiISI0prEq9VFJu543Fu3hv6W68DHjw4g7cdVECgb5n/kd2Tc4a3t70dv1vmHQ022FYMhVWvQ0WHxjyGJx/P/jqeTMROTMHX3oJHA4i/6ClakREpGFTWJV6xekymb12Py/MTye/tJLre8Xyh5HJxIQFnPE1yuxlvJTyEp+mf0pUYFT9bZh0NKcd1rwHPz0HtkLoeRsMfQJCYzxdmYg0ILZNmyia9wXNJ07ENy7O0+WIiIicFYVVqTeW7sjnqa+3kpZTQt/4Zkwf25duceHVusbK7JU8uexJssuyGdN5DPf1vI8A7zMPunXONCHta1jwVzi0C9pdBJc8BTHdPF2ZiDQwpmmS+8yzWFq0oPldkzxdjoiIyFlTWBWP23WwlGe+3sYPaXm0jgjgjdt6cVnX6GpN1S2zl/HC2heYs30O8aHxzLxsJj0ie5zDqmtB1nr4/gnYuxRaJMGts6HDJVBfpyiLSL1W/M032DZsIOapf2AJDvZ0OSIiImdNYVU85nBZJa/8sIMPV+7F38fCny7ryNjz4/H3qV4ToRVZK3hy+ZPklOUwpvMY7u95P/7e/ueo6rNUehBS/wubZ0PmGghsDpdPhd5j3c+oiojUgKu8nLypL+DXqRNh113n6XJERERqhcKq1LlKh4sPVu7l1R92UFJu55Z+bXh4RBItgv2qdZ3SylJeTHmx/o+mVpS6p/pungO7FoHphMguMPxv0OdO8A/zdIUi0sAdmjEDR3Y2rZ57DsOiruEiItI4KKxKnXG6TL7YeIBXFu5gT4GVwR1a8MQVnUmODqn2tZZnLedvy/9GTlkOY7uM5d4e99av0VSn3R1MN82G9G/AboXQOHdn326jIaqLpysUkUaiYvdu8t+ZRsiIEQT17+fpckRERGqNwqqccy6Xydebs3l54XZ2HSyjU0woM8b2ZUhyy2ovIVNaWcrUtVOZu2Nu/RtNNU3Yv8odUFP/C7ZDENAMut3kDqitB4CXl6erFJEGyjRNHHl5lKemUr4llfLUVGxbU3EezMfw9dVSNSIi0ugorMo543KZzN+aw0sLdpCeW0JSVDBv3taLkV2i8fKqfhOh5QeW8+SKJ8mz5jGuyzgm95js+dFU04TcLVXPoc6Bwn3gHQDJl7kDauLF4O3r2RpFpMExTRNHbq47mKamYktNpTx1K878fPcBXl74JSYQfP4g/Lt0JmjQIHzbtPFs0SIiIrVMYVVqnWma/LAtjxcXbGdrdjEJLYN49ZaeXHleTI1Cak5ZDq+tf40vdn1Bu7B2zLxsJt1bdj8HlZ8h04TsjbB1nvt1aBcYXpAwFIb+GTpeAX7Vn9osIk2TaZo4cnKOCqVVwbSgwH2Alxd+iYkEX3AB/l26uF8dk/EKDPRs4SIiIueYwqrUGtM0+Wn7QV5asJ2NmUW0bR7Ii6O7c3X3Vnhbqj/9tbC8kHc3v8ustFmYmIzvOp57etyDn6V6jZhqhWm6l5rZ+j93QD28BwwLtBsM598HHa+C4JZ1X5eINCimaeLIyjoyUlq+dSvlqak4Dx1yH2CxuIPphRdWBdPO+HfsiFdAPV4vWkRE5BxRWJWzZpomy3cV8OKC7aTsPUxseAD/uqEb1/WKxacGIdVqt/Lhtg+ZsWUGVoeVqxKu4t4e9xITHHMOqj8F04QDKb8G1MJ94OUN7S6CCx6BjldCUPO6rUlEGgzTNLEfyDoylbc8NZXyrVtxHj7sPsBiwa99e4KHDMG/S2cCunTBr2NHvPzrUbM4ERERD1JYlbOyKqOAFxZsZ/XuQ8SE+fP0dV0Z1bs1vt7VD6l2l53Pt3/OW5veIt+Wz5DWQ3iw54O0b9b+HFR+Ei6Xe/3TX6b4FmeClw8kDoWLpkDy5RAYUXf1iEi9YLpcOIuKcBYWul+HC399f/zr8OEj70273X0Bb2/8OnQgeNhQ/Lt0cQfT5GQFUxERkVNQWJUaSdl7mJcWbGfpznwiQ/z4v6u7cFPf1vj7VH99P5fpYv6e+by2/jX2leyjV2QvXhzyIj0je56Dyk/g8B7IWAy7foTdS9xdfC2+7uZIw55wN0sKCK+bWkTEo5ylZVTu3k3lnt1UZGRQmbGbyowMKvfuxaysPPFJ3t5YwsOxhIdhCQ/Hp20b/Lt3wzs8HJ+4OPy7dMEvKQkvPw88wiAiItKAKaxKtWzcX8hLC7ezOP0gzYN8eeKKTtzWvy0BvjVbhH551nJeTnmZbYe20aFZB/598b8ZHDu42kvaVIv1kDuUZix2vw7vdm8PiYGkSyFxGCRdAv5h564GEfGYXxoaHQmju3dTsdv93pGb++uBFgu+rVvjm5BA0IWD8YmKxtIsvCqY/vryCg4+t//OEhERaaIUVuWMpGYV8dKCHSzclkt4oA9TLu3IHee3JdC3Zn+EUvNTeWndS6zKXkWroFY8c8EzXN7ucixeNQu9p2Qve5lrZgAAIABJREFUd69/mrEYMn6ErA2ACb4hEH8BDLgHEoZAiyTQB06RBs00TVxFRdhzc7FnZ+PIycGek4MjOwd7bi6O7GzsubmY5eVHzvEKCcE3oR1BAwfim5CAX0I7fNu1w7d1awxfLT0lIiLiKQqrckrpOSW8vHA7327JIdTfm9+PSGLsoHhC/H1qdL1tBduYtnkaC/YuoJlfM6b0ncLo5NH4WmrxA6FpQt422PUD7FoEe1eAw+bu3hvXF4b8yR1OY3uDpWY/h4h4jmmaOLKzsaWmUpGWjj0rC3tO9pFAatpsx55gseAdGYlPdDT+XToTPGwYvm3b4pvQDr927bC0aKGRURERkXpIYVVOaGdeKa/8sIOvNmUR7OvNgxd34M4L2hEWULNwtz5vPe9seoelB5YS7BPM3d3v5o7OdxDsG1w7BdsOu0dOd/7gfpVkube3SIbed7jXQG17PviH1s79RKRO/Gapl6quukc66np54d2yJT7R0fglJxN80UV4x0TjEx2DT3QU3jExeLdogWE5B7M2RERE5JxSWJVj7Mkv49UfdvC/DQfw97EweUgiEwcnEB5Y/ZFP0zRZkbWCaZunsTZ3Lc38mvFAzwe4qeNNhPqeZWh0Od3TeXcudI+gZq4B0wV+YZA4xN0cqf3FEBZ3dvcRkTrjXurlAOVbUo+sP1qemoqzsNB9wC9LvQwdqqVeREREmgCFVQFg/yErry3awdx1B/CxGEwcnMCkCxNoHlz97pUu08WP+39k2qZppBakEhkYyZS+U7i+w/UE+gTWvMiSHPe03p0L3Z17bYcAA1r1hMGPusNpbB+w6I+1SH1n2u1UZGRQkZZG+bY0ytPSqNi2DWdRkfsAb293ML14mJZ6ERERaaL0qb6Jyy0u5/VFO/lkzT4Mw2DMwLbcMySRyJDqfyB0uBx8t+c73tv8HjsLdxIXHMeTA5/k6sSra/5MqtMBaV/Cyrdg/0r3tqBISBoJ7Ye7p/cGNa/ZtUWkTjiLi91hNC2N8rR0ytO2Ublj55E1SA0/P/capCOGE9Cli3upl+RkLfUiIiLSxCmsNlH5pRW8tXgXH6zci9NlclPf1tw3rD0xYQHVvlals5J5u+YxffN0MkszaR/enucGP8fI+JF4e9Xwj1h5EaybCavegaJ90KwdXPxXaD8CorqCl1fNrisi54zpcmHPzKQ8PZ2KtHTK09Oo2JaG/cCBI8dYIiLw79SJoDG349+xE/6dOuIbH4/hrb+ORERE5Fj6dNDEFFntvPPzLmYs20O53cn1veJ48OIOtI6o/vTcCmcFs9Nn8/6W98mz5dG1eVf+0PcPDGk9BC+jhmHyUAasehvWfwiVpdD2ArjsOff6p+diWRsRqRFnSQkV27e7g2n6dirS06nYvh2X1eo+wDDwjY8noHs3wm+6Cf+Oyfh17Ih3y5bqvCsiIiJnRGG1iSitcDBj6W7e+TmDknIHV3VvxUPDO5DYsvrdeJ0uJ1/v/prX179Odlk2faP78tQFTzEgZkDNPoSaJuxdDivfgLSvwcsbut7gXv+0VY/qX09Eao1ZWUll5gEqtqcfE0yPHi31Cg3FPzmZsOuvxy85Cf/kZPzat8cr8CyeURcREZEmT2G1kbNVOvlg5R7eXLyLw1Y7IzpH8ciIJDrFVL8br2maLD2wlJfXvcz2w9vp3Lwz/xj0D/rH9K9ZcY5KSP0vrPw3ZG+EgAgY/HvoOwFCY2p2TRE5I6Zp4iouxp6biyM3D0de7q/vc3Ox57nfOwsKfj3JYsG3XTwB3bsTPnq0O5h27Ih3VJRGS0VERKTWKaw2UhUOJ5+s3s/rP+7kYEkFFya15PcjkujeOrxG19uSv4WXUl5idc5q4oLjeP7C57kk/pKaTfe1HoK102H1NCjNca+FeuXL0O0m8NVIjMjZMu12HPn57tBZFT4debnYc3KPCaJmeflvzrU0a4Z3VBTeUZEEdOmKd1QUPrGx+Ccn4ZuYqKZHIiIiUmcUVhuZQmsls9fu5/1le8gqKqdfuwj+fWsv+rWLqNH19hXv45V1rzB/73wi/CN4rN9jjEoahY/Fp3oXKi+G9G9hy1z38jMuu7uT7zX/hsRhapgkUg2mw0F5aioVGbtx5Ob8ZkTUmV/gnl5/FMPHB+/ISLyjovDv3BmfIUOPhFKf6Gj3+8hIvHxr2LlbREREpJYprDYSW7OKmbliD//bcIByu4t+8RH888ZuXNC+RY2m5+Xb8nlr41vM3T4XH4sPd3e/mzs630GwbzWeca20wo7v3QF1xwJwlENoHAy4G7rfClGdq12XSFNVmXmAsmXL3K+VK3EVFx/ZZwkLqwqeUfh16ohPZNSvQbRqu6VZM03VFRERkQZFYbUBsztdfJ+aw8zle1m95xD+Pl5c1zOW2wfE07lV9Z9JBSizl/Gf1P/wfur7VDoruTHpRu7ufjctAlqc2QUcFbDzB3dATf8W7GXudVF73QFdr4e4fhpFFTkDztIyrKtXU7Z0KWXLllG5dy8A3tHRhIwYTvCgQfh36YJ3VBRe/tVfF1lERESkvlNYbYDySsr5ZPV+Plq1l9ziCtpEBPLEFZ0Y1bs1YYHVnJ5bpcJZwdztc3l709scKj/EiLYjeKDnA8SHxZ/+ZKcdMn6C1M9h21dQUeRultRtlLurb9tBWnZG5DRMp5PyrVvdI6dLl2HdsAEcDoyAAAL79aXZbbcSNGgQvgkJGiEVERGRJkFhtYEwTZN1+wqZuWIP32zOxu40uSipJc9e35aLkiKxeNXsw2tRRRGz02fz0baPKCgvoHdUb14b9hrdWnY7/ck5W9yNklL/C7ZD4BcKna6CLtdDwkVQ3edaRZoQ0+mkPC0NW8o6rCkpWFeuxFlUBIB/5840HzeOoEGDCOjVU8+RioiISJPUIMKqy2Vi4g5s7q9gYh7pH3L098cfx3H7OMF1OHLeCa5zmnv8so9j9h11bHVqPfq4X441TfYWWPlg5V42HygixM+b3w1oy+0D2pJQgzVSf5Fdms3MrTOZu2MuNoeNQbGDGNdlHP2i+5161MZph7Sv3J189y4Db3/oeAV0vRHaXwze6hQqciKu8nJsGzdhW5eCdW0Ktg0bcJWVAeDdKobgYcMIGjSIoPMH4h1Rs4ZoIiIiIo2JYR7XMbK+8YvpYMbc8bKny/C4pKhgxgyM57qesQT51fz/Y0g/lM77qe/z7e5vMTC4tN2ljO0yluSI5FOfWJoHKf9xj6SWZEF4G+g7EXr+DgL1wVrkeI7Dh7GtX481JQXb2hRsW7eC3Q6GgV+HDgT07kVg7z4E9u6FT4zWFRYREZGmyzCMFNM0+xy/vd6PrEaG+PHQ8A4YGBgGGOD+WjX659523L6q7937jaO2V31f9Z5j9h11zlHbOPq8I/c+1T2OrYVjvv/tNX654W/2H3VeiL8PXWNDa/ycmmmarM5ZzYwtM1iWtYwA7wBu7XQrt3e6nZjgU3xINk04kAKr3nZP9XXZ3cvMXPkidLhEz6GKVHGWlFCxfTvl6elUbEvDun4dlTt3Ae4lY/zPO4/mY+8goHdvAnv2xBIW5uGKRUREROq/eh9Wo0L9eWh4kqfLaJAcLgcL9y1kxpYZbC3YSoR/BA/0fIDRyaMJ8zvFh2V7ubtZ0up3IGs9+IZA3/HQdwK06FB3P4BIPWM6nVTu3UfF9nTK09KoSN9ORXo69qysI8d4hYUR0L0bYVdeRWCf3vifdx5efpoeLyIiIlJd9T6sSvWV2cv4YtcXzEydSWZpJm1D2/LkwCe5KvEq/Cyn+NBcuN89zXfdf8BaAC2S4fKp0P1m8Aupux9AxMNM08RZUEDFzl1VI6ZVwXTHDsyKCvdBFgu+7eIJ6NGD8Jtvxj85Cb/kZLyjotStV0RERKQWKKw2ImmH0piTPoevMr7C6rDSrUU3Hu3zKENaD8Fysim7dhukfQ0bPoKMxe5tyZdDv0nQ7kLQh25pxEyXC0d2NhUZGVTs2kXlrl1U7MqgcteuI515ASzNmuHXMZlmN9+MX8eO+Ccn4ZuYqBFTERERkXNIYbWBszlsfLf7Oz7b/hmb8jfhZ/FjZPxIRiWNonvL7ice4TFN2L8KNnzsfha1ohjCWsPg30OvMe7mSSKNiOlyUbl3769hNGOXe9R0925Mq/XIcZbwcHzbJxIyciR+7RPxTUjEPzkJS4sWGi0VERERqWMKqw3UzsM7mbN9Dl/u+pISewntwtoxpe8Urkq86uTPoxbuh42fwMaP4VAG+ARC52ugx63Q9gLw8qrbH0LkHDGdTsq3pWFduwbr2rXY1qbgLCw8st87Ohq/hATCb7gBv8RE/BIT8E1M1JIxIiIiIvWIwmoDUuGsYMHeBcxJn8O6vHX4ePkwvO1wRieNpndU7xOP/FSWwbYv3dN8d/8MmBA/GAY/Cp2v1rOo0iiYlZXYtqRiXbsW69o12FLWHVnD1Kd1a4KHDiWgV0/8k5PxTUjAElzzNYpFREREpG4orNYjpmliYh7z3sQksySTudvnMm/XPAorCmkT0oZHej/CNe2vIcL/BCNBLhfsWw4bZsHW/0FlKTSLhyGPQfeb3O9FGjCXzYZt40asa9a6R043bDjS+Mi3fSKhV11JYJ++BPbpjU90tIerFREREZGaqPdhdXfRbm79+tZjwptpVgW6qve/2X6KY48/70THm5i4/2ue9thfrnfa448672THnoq34c3QNkMZlTSK/jH98TJOMGU3NxU2zYYtc6FoP/gGQ5drocdt0GagmiVJg2WaJhXbd1D28xJKl/yMdf16sNvBMPDr1JHwm0YT2KcPgX36aCqviIiISCNR78Oql+FFqG8oGGD88h/jyLsTb68KZSc69kTbT3h81VfgpMces+8Ux5+szuPPP1LDcccH+wYzMn4kLQJa/PYfUOF+2DwHNn8GealgWCBxGFz8V+h4BfgGnZv/YUTOMWdpKWUrVlC25GdKf/4ZR04OAH5JSUSMuZ2gfv0I6NkTS2iohysVERERkXPB+GV0sL7q06ePuXbtWk+XUb9YD7mn926a457uC9C6P5w3CrpcB0EnCLUi9ZxpmlTs2EHZzz+7R09TUsDhwCsoiKDzzyfowsEEDx6sab0iIiIijYxhGCmmafY5fnu9H1mVKpVW2P6tO6DuXAguO7RIhmFPuEOqnkOVBshVUXEknJb+/DOO7GzAPXrafOwdBF14IYE9e2L4+Hi4UhERERGpa/U/rFoPwfqPqr4x3WuEnug9VH1/svcc97665x9/rdPVcqrrVvNnKc6CtK/djZJCWsGAu+G80RB9np5DlQarMvMAmZMnU7F9e9Xo6UCCJt+j0VMRERERARpCWC3cC/Mme7qKc+SXh2iNU7/3C4au17sDatvzwcvigVpFak/Z6tUcePAhTKeT2FdfIWTIEAxfX0+XJSIiIiL1SP0Pq5Gd4cEvOeNgd+Q97u9P+/6446t1jxrcTyOh0sQd/uRTcp56Ct82bWj9xr/xjY/3dEkiIiIiUg/V/7Dq7afnMUUaAdNuJ/fZZzn88SyCLrqQ2KlTsYSEeLosEREREamn6n9YFZEGz3H4MAceehjrqlU0nzCelg8/jGHRdHYREREROTmFVRE5p8q3bydz8r048vJo9a9/Enb11Z4uSUREREQaAIVVETlnShYtIuvRP+AVFETbD2YS0L27p0sSERERkQbCy9MFiEjjY5om+W+9Tea99+GbkED8Z3MUVEVERESkWjSyKiK1ymWzkf3nP1P8zbeEXnklMU/9Ay9/f0+XJSIiIiINjMKqiNQae3Y2mffeR/m2bbT8/SM0nzABQ8s1iYiIiEgNKKyKSK2wbdrE/sn3YtpsxL3xb0KGDvV0SSIiIiLSgCmsishZc5aUkHnvfXj5+9P6/Rn4tW/v6ZJEREREpIFTWBWRs3bwpZdxFBQQ/+mnCqoiIiIiUivUDVhEzopt0yYOz5pFs9tuI+C8rp4uR0REREQaCYVVEakx0+Eg+69P4t2yJS0ffMDT5YiIiIhII6JpwCJSY4dmfkBFWhqxr76CJTjY0+WIiIiISCOikVURqRH7gQMcfO01gocMIWTECE+XIyIiIiKNzGnDqmEY0w3DyDMMY8tR2yIMw1hgGMaOqq/Njtr3mGEYOw3DSDcMY+RR23sbhrG5at+rhhZfFGmwTNMk56mnAYj+yxNaS1VEREREat2ZjKy+D1x63LY/AT+YptkB+KHqewzD6AzcDHSpOucNwzAsVee8CUwCOlS9jr+miDQQJQsXUvrjj7S8/358YmM9XY6IiIiINEKnDaumaS4BDh23+RrgP1Xv/wNce9T2T0zTrDBNczewE+hnGEYMEGqa5grTNE1g5lHniEgD4iwtI/epp/Hr2JGIMbd7uhwRERERaaRq2mApyjTNbADTNLMNw4is2h4LrDzquMyqbfaq98dvPyHDMCbhHoWlTZs2NSxRRM6Fg6++giMvj7hXX8HwVo82ERERETk3arvB0okeXDNPsf2ETNN8xzTNPqZp9mnZsmWtFSciZ8e2eQuHP/yIZrfcTED37p4uR0REREQasZqG1dyqqb1Ufc2r2p4JtD7quDggq2p73Am2i0gDYToc5Dz5JJbmEbR8+GFPlyMiIiIijVxNw+oXwB1V7+8A5h21/WbDMPwMw2iHu5HS6qopwyWGYQyo6gI85qhzRKQBOPzxx5Rv3Ur0449jCQnxdDkiIiIi0sid9oEzwzBmAUOAFoZhZAJPAs8Bsw3DGA/sA0YBmKaZahjGbGAr4ADuNU3TWXWpe3B3Fg4Avq16iUgDYM/J4eDLrxB04WBCLlUjbxERERE59wx3c976q0+fPubatWs9XYZIk5Z5//2U/ryUhK++xDcu7vQniIiIiIicIcMwUkzT7HP89tpusCQijUzJokWULFhIi3snK6iKiIiISJ1RWBWRk3KVlZHzj6fw69CB5mPHerocEREREWlCtEiiiJzUwddex5GdTezHH2P4+Hi6HBERERFpQjSyKiInVL51K4dmziT8ppsI7NXT0+WIiIiISBOjsCoiv2E6nWQ/+TcsERFEPqI1VUVERESk7mkasIj8xuFZn1C+eTOtpk7FEhbm6XJEREREpAnSyKqIHKNsxQry/vUvggYNIvSKyz1djoiIiIg0UQqrInKEdd169t97H77x8cS+MBXDMDxdkoiIiIg0UQqrIgKALTWV/XfdhU9kJG2mv4clPNzTJYmIiIhIE6awKiJU7NjB/vETsISE0GbGdLxbtPB0SSIiIiLSxCmsijRxlfv2se/O8Rg+PrSZMR2fmBhPlyQiIiIiom7AIk2ZPTubfWPHYdrttP3wA3zbtvV0SSIiIiIigMKqSJPlOHiQfWPH4Swups1/3sevfXtPlyQiIiIicoTCqkgT5CwsZN/4Cdjz8mjz3nsEdOni6ZJERERERI6hsCrSxDhLS9k3cRKVe/bQ+u23COzV09MliYiIiIj8hsKqSBPistnYf/fdlG/bRtyrrxI0cKCnSxIREREROSGFVZEmwlVZSeZ992Nbt57Yqc8TMmyop0sSERERETkphVWRJsC02znwyCOULVtGzNNPE3r55Z4uSURERETklLTOqkgjZzqdZD32OKULfyDqz38m/IbrPV2SiIiIiMhpaWRVpJEx7XbsOTnYMzOpzMykbMnPlCxYQMuHHybi9t95ujwRERERkTOisCrSwJimifPQIez791OZeaAqlO7HnnkA+/792HNywOn89QQfH1rcdx8t7prkuaJFRERERKpJYVWkHjNNE3tmJrZ167CuW49t40Yq9+3DtFqPOc7SogW+sbEE9OxJaFwsvq1b4xMbh2/rOLyjojC89asuIiIiIg2LPsGK1COm3U75tm1Y163Dtm491vXrcB7MB8ArOJiA7t0J6t8Pn9g4fOLcYdQnNhavwEAPVy4iIiIiUrsUVkU8yFlUhHX9emzr1mNbtw7bli2Y5eUA+MTFETRwIIE9exLQqxd+7dtjWCwerlhEREREpG4orIqcQ67ychw5Oe6GRzk57vfZ7q+V+/dTmZHhPtDbG/9OnWh202gCevYioGdPfKIiPVu8iIiIiIgHKayKnAXTNKnMyKA8NRV7dg72nGwc2TnYc3NxZGfjLCz8zTmWZs3wjonGt107wq6+yh1Ou52HV0CAB34CEREREZH6SWFVpBpMu53yrVuxpqzDmpKCLSXlmEBqCQvDOyYGn+hoArp3wyc6Bp+YaLyjoqu+RuHl7+/Bn0BEREREpGFQWBU5BVdZGdYNG7D9Ek43bvz1mdI2bQgeOpTA3r0I6N4dn7g4jY6KiIiIiNQShVWRozgOH8a6eg22dSlY16ZQnpbmXrPUywu/jsmEjxrlDqe9euETqWdKRURERETOFYVVadJc5eXY1q2jbPlyypavoHzbNjBNDD8/Arp1o/mkiQT26k1Azx5YgoM9Xa6IiIiISJOhsCpNiulyUf7/7d15kJz1nd/x9/fpY6Z7Lo2EBJI4ZIMwRjICSYDBBzhrNq61w2HswuzG1zpxbHa9ccpOlWs3cbY2tUet16lssk65WMdZb8oxdgzrNY6TOPZi8IGRQYBAIAQGLAkJc4gZzdUz092//NEtIcSlsy+9X1Wt5+nf8/TzfJ95nmk9n3muBx9k6qc/Zfr225m+8y7S3BwUCpTXrOGET/wuA2+8iNLqVUSx2O5yJUmSpOOWYVU9b27Hjn1HTqd/9rN9N0TqW7mS0WuvZeDiiyivX082MNDmSiVJkiTtZVhVT0kpMb9jB9N33sXMxruYumMD89u2AZBfsoTBSy9l4E0XU77wQq85lSRJkjqYYVVdLdVqzG7dyvSddzG98S5m7tpI9amnAMhGRiivXcvC97+fgYsvovja1xIRba5YkiRJ0sEwrKqr1GdnqWza9PxzTu++m/rkJAD5pUspX3AB5fXrKK1dS98ZZxBZ1uaKJUmSJB0Ow6o63vzOnYx961tM/ejHVO6/nzQ/DzSuOR1+1zspr1tPed1aCsuWtblSSZIkSUeLYVUdqT43x+T3v8/YN29k6vbbASidcw4LP/gBSuvWUT7vPHILFrS5SkmSJEnHimFVHaWyZQtj37yRPTffTG18nPyypZxw3XWMXHUVxZOXt7s8SZIkSS1iWFXb1fbsYfw732H8xpuobN5MFAoMXfZ2Rq6+moE3vpHI5dpdoiRJkqQWM6yqLVK9zvSGDYzdeBMT3/seaXaWvrPO4sQ/+AOG3/VO8qOj7S5RkiRJUhsZVtUy9elpZu69l6kNG9jznf/F/PbtZENDLLj63Yy8+2r6V53to2UkSZIkAYZVHUO1iQlmNm5k+s47md7wc2Y2b4ZqFbKM8vnns/j3PsHQZZeR9fe3u1RJkiRJHcawqqOmunt3I5g2X7NbHoJ6HQoFSqtXs+jDH6Z8/npK551Hbmio3eVKkiRJ6mCGVR222tgYUz/9KVMbNjB9553MPfILAKKvj9K553LCxz9O+fzzKa05h6xUanO1kiRJkrqJYVUHLaXE7NatTN56G5O33srM3XdDvU42MEBp3VpGLr+C8vr1lFavIorFdpcrSZIkqYsZVvWK6tPTTP3sDiZvvZXJ226jumsXAP1nn82if/FRhi65hP43vMHHy0iSJEk6qgyrepG57duZ/OGtTN56K9MbNpDm5sjKZQbedDGDv3MdA295K4UTl7S7TEmSJEk9zLB6nEv1OvPbtjGzeTOVTZuY/NGPmXv0UQCKK1Yweu21DF56CaV168g8tVeSJElSixhWjyOpXmfu8V9SeeABKps3N14PPEB9chKAKBYpn38+o++7hsFLLqF42mltrliSJEnS8cqw2qMawfTxRiC9vxlMH3yQ+tQU0AimfWedxfA/eRelVavoX7WKvjPOIAqFNlcuSZIkSYbVnlGbnGTmnnuZ2biR6bs3Url3E/XpaaDxKJm+s17HyBWX0783mJ5+usFUkiRJUscyrHahlBLVnTuZ3ng3M3dvZHrj3cxu3Qr1OmQZfWeeyfAVl1Na/Qb6VzeDad5VLUmSJKl7mGC6QKpWqWx5aN9R05mNd1P91a8AyMplSueuYejjH6e09jxKa9aQGxxsc8WSJEmSdGQ6PqxWtmxh65ve3O4y2qo+NUWqVADIL11Ked06SmvXUl57Hn1nnulRU0mSJEk9p+NTTm54mKHL3t7uMtoq6+un/5w3UF67lsLSpe0uR5IkSZKOuY4Pq4Vly1j6h3/Y7jIkSZIkSS8hpcTs1BQzE+PMVSrMz1aoVirMz84yP1thbmaGmakZKhPTzE5NU5meYW6m0T7fPIP0pXR8WJUkSZIktVZ1fp6ZPeNMj481Xs3+qfExpsfGmNj9HFNjY8zsGWN2eoJUrx3klHMQBYgCQaP7cgyrkiRJktTDUkrMV2aYmdjD9J5xZvY0uxN7moF0nKmxMabGG22VyT1UZ2deZmp5yMpElIisTMRysmKZiDKF/kGK/f0USyX6Bsr0D/TTPzBAabhEaWiAgZEB+gf76B/I01cuNF4DeT71tS+/3JwkSZIkSe2UUiLV69TrdVK91uiv1ak3+/cOq87NMjs1xezUJJWpKab3TDAzMUFlcorKZKNtdnqKuekp5mammatMMV+Zol6rvsycc5CVGuEzShALiGwp+f4yZGXyxUFKQyMMLFjA4Ogog6ODDCzoozzcR3m4SHmkSGmoSHmoSK6QHdWfiWFVkiRJ0iFLKVGdn6NePdjTP9shUatWqddq1GvVRvirValXq9Re1NZ4X6vVqM7NUp2bY75SYa4yy9zMDHMzs83rMRvt1bk55mdn942b6rVGsKzVSen5cLm3P6U6pHozlNZIKQGN96Q6kI5wWTOIPiL69usOELGQyPeTL5bI5QfoKw/SNzhMaWiE8sgI5ZFBSoMF+gcKlAYL9A0U6B9s9JeGihT72xcZDauSJElSi8xOT1Odm31hgKpWqdfrLwxQ1UbwaYSp2iHnmESPIJ1bAAAPb0lEQVTzKF21Rq1aawayWmP69Tr1+WZIq9ebdTQCW3VuvnHjm0rjxjeNMFZpBrJZqvOz1ObnqFVnqVfnOPKA1U0yIA+RJ6Kwr5/IE3v7KQDRHDeILCMiI7KMXNboRpYj29efNfrj+feN/lxj2P7tzVe+UKRYHqCvNECxPED/wAD9A0MUy30U+nLkCznyxYx8MUe+0OgW+3P0DxTIF3Pt/AEeMsOqJEmSdAxMj4/xq0cfYfuDD/HElod4dsdjzE491+6yDkLz5jex9+Y3e/v7IYaIKJArFimWi+TyfUSWg4h2F/2ysixHlss1QmJu/1f+Bf25fON9Lp+n0NdHoa+PYqmPYqm/+SruC3/5YvZ8KGx2c4WMXC4jywe5fEaWC6KDfy7dwLAqSZIkHaGpsed48tFH2L55C088tJXdTzzG3PTYvuGRjRK5JQwsOpdCf2lfUMrlcmT5PLlcnlwhT5bLyBUK5PJ5cvlcoy2fI4tDvxYwsmgEtXyOLMsRuawxv1xGLp8jmv1ZlmuGqxz5YoFCX/6FoeyAo3SGMLWKYVWSJEk6SLXqPGNP7uLpbdt44qFfsOvhh9m98zHmZ8b3jRPZKFn+JIZPOp/Fp76WU85+HUvPWMyik4foK7n7LR0sf1skSZKkA8zPVtj9xA6efPRxdj38GM9s38aep55gZvKZ5s1wGiJbSFZYxoLlb2TJitM5ddXrOOn0xSxaNtB11wdKncawKkmSpONSSomZiT08+8QOdm19jCcffZzdO7Yz8exO5mbGeP7mQUFkC8jyixhctJKRJcs54dRTWbryNZz02kWMnlgmyx3dR3ZIMqxKkiSpx81XKjz35E6e/uU2dj3yS57Zvp3xp3YxPf4r6tXKfmPmiNxC8n0nsWDZuYwuPZklK05j2ZkrWLR8mKFFJbLMazWlVjGsSpIkqWc8u2MbW26/g6ce28Zzu3YyuftJ5ivjLxwphsjyo/QNrmJo0UksXLacJa85leWvO42FSwfpHyi0p3hJL2BYlSRJUldLKfH4pk386H/cwNOP39dojD4iGyVfPJkFS9ex4MRlnHDaySw9YwWLTx1l+IQSubyn7kqdzLAqSZKkrlSv1bjvH27lZzd9k8nd2yBKDJ94CWsuewfLzlzOwqWDlIYKPmZF6lKGVUmSJHWV2Zlpbv/mzWz6/neYrzxHZAs46XVX8pb3Xc4pr19sOJV6hGFVkiRJXWHP089wy99+g1/c9Q+kWoVccTlnXnwVb7n211mwZLDd5Uk6yloeViPiHcBfAjngSymlP2t1DZIkSeoeT2x5hB/+9xt48pGfAzX6Bs9izWWXc+GVF1Ps99iL1Kta+tsdETngC8BlwA7g5xHx7ZTSA62sQ5IkSYeuXq8zuXuC3U88xVylQq1aI6VEvVYj1ev7urVanVTfvy1Rr1dJ9URKiVSvP9+f9mvb15+ARL1WZ9t9G9nz9BYgz8hJ67no6qs5+82vJ3yEjNTzWv2nqAuAR1JKjwJExA3AFYBhVZIk6RhLKUGiGQqBBPWUqEzOMf7UGM/teobxp55mzzPPMvXcs0zvGaMyNc7czDjV2Qnq1Qmg2tKaI0osO+sdXPJPr2bZyqUtnbek9mp1WF0ObN/v/Q7gwhbXILXdrkfG+PZ/vrfdZUiSWmB++j7mZ+5pzcxS2ttDohFMG/+kFwx7/gWJOtRneMkQGgXyxSEK/cOUR06jNLSAwQULGRgdpVjqJ8vlyLKMyHJElhFZ1mjLZWSRI3JBlmVkuXxjWJY1johGRpY1hhFBlkXz881uBJEFWWQsWDpKeaj/GP/gJHWiVofVlzpfI71opIiPAh8FOPXUU491TVLLlUf6WP2WZe0uQ5LUAs9se5JnfjnauhlGNO6Gu7fLC9/HvuEZjeaM/sFhhhYtZPiEExg5cTELly9m9MTFFEvl1tUtSQdodVjdAZyy3/uTgZ0HjpRSuh64HmD9+vUvCrNStxtZXOJN71nZ7jIkSS2xErim3UVIUtfJWjy/nwMrI+I1EVEE3gd8u8U1SJIkSZI6XEuPrKaUqhHxu8D/pfHomi+nlDa3sgZJkiRJUudr+YOpUkrfBb7b6vlKkiRJkrpHq08DliRJkiTpVRlWJUmSJEkdx7AqSZIkSeo4hlVJkiRJUscxrEqSJEmSOo5hVZIkSZLUcQyrkiRJkqSOY1iVJEmSJHUcw6okSZIkqeMYViVJkiRJHcewKkmSJEnqOIZVSZIkSVLHMaxKkiRJkjqOYVWSJEmS1HEMq5IkSZKkjmNYlSRJkiR1HMOqJEmSJKnjREqp3TW8ooiYAB5qdx0v4wTgmXYX0QFGgPF2F3EU9drygNsq9OZ67cVlOhy9tn334nrtxWU6VL22nULvrddeW57D1Wvbai+u115bpn5gR0rpHQcO6IawemdKaX2763gpnVxbK0XE9Smlj7a7jqOl15YH3FahZ9drzy3T4ei17bsX12svLtOh6rXtFHpvvfba8hyuXttWe3G99toyvdI252nAOhpubncBR1mvLY8aenG99uIyqTfXay8uk3pvvfba8qihF9drLy7TS/LI6hHo5Nqk/bmtqpe5fasbuJ2qW7itqtW6/cjq9e0u4BV0cm3S/txW1cvcvtUN3E7VLdxW1Wovu811/JFVSZIkSdLxpxuOrEqSJEmSjjOG1YMQEVdFRIqIs9pdi/RqImLyVYb/MCK8FkVdJSJOjoi/j4iHI+IXEfGXEVF8hfE/GRHlVtYowat/B0udwH1bdQvD6sG5Fvgx8L5D+VBE5I5NOZJ0/IiIAG4CvpVSWgmcCQwCf/wKH/skYFiVpJfmvq26gmH1VUTEIPAm4CM0f6Ej4tKIuC0i/i4iHoiIL0ZE1hw2GRF/FBF3ABe1r3Idz5rb6Hf2e/9XEfGhNpYkHYl/BFRSSv8NIKVUA/4V8NsRMRARfxER90XEpoj4RET8HrAMuCUibmlj3TpORcRgRPwgIjY2t80rmu0rIuLBiPjriNgcEd+LiFK769XxxX1bdRPD6qu7Evg/KaWtwO6IWNtsvwD4FPAG4HTg3c32AeD+lNKFKaUft7xaSeo9q4C79m9IKe0BtgH/DHgNcF5K6Rzgqyml/wTsBN6WUnpbq4uVgApwVUppLfA24PPNMwQAVgJfSCmtAsaAq9tUo45f7tuqaxhWX921wA3N/hua7wE2pJQebf6F/2vAm5vtNeDG1pYoST0tgJe6dX0AbwW+mFKqAqSUdreyMOllBPAnEbEJ+D6wHDixOeyxlNI9zf67gBWtL0/HOfdt1TXy7S6gk0XEIhqnn62OiATkaOwwfZcX7zjtfV9p/pJL7VTlhX+M6m9XIdJRsJkDjj5FxDBwCvAoLx1kpXb6LWAxsC6lNB8Rj/P89/DsfuPVAE8DVsu4b6tu45HVV/Ye4G9TSqellFaklE4BHqPxl6YLIuI1zfP5r6FxkbrUKX4JnB0RfRExAvxauwuSjsAPgHJEfAD23eDj88DfAN8DPhYR+eawhc3PTABDrS9VAmAEeKoZVN8GnNbugqQm923VVQyrr+xa4O8OaLsR+E3gduDPgPtp/JIfOJ7Ucs0d9tmU0nbgG8Am4KvA3W0tTDoCKaUEXAW8NyIeBrbSuCbw94Ev0bh2dVNE3Evj+xngeuB/e4MltdLe72Aa37vrI+JOGkdZt7S1MOl57tuqq0RjH0CHIiIuBT6dUnpXu2uR9hcRa4C/Tild0O5aJOl443ewupX7tupUHlmVekREfIzGDRH+TbtrkaTjjd/BknT0eWRVkiRJktRxPLIqSZIkSeo4hlVJkqRDFBGnRMQtEfFgRGyOiH/ZbF8YEf8vIh5udkeb7Yua409GxF8dMK1rImJTczp/3o7lkaROZFiVJEk6dFXgUyml1wNvBH4nIs4GPgP8IKW0ksZjlz7THL8C/Fvg0/tPpPncy88Bv5ZSWgWcGBE+bkySMKxKkiQdspTSrpTSxmb/BPAgsBy4AvhKc7SvAFc2x5lKKf2YRmjd32uBrSmlp5vvvw9cfYzLl6SuYFiVJEk6AhGxAjgPuAM4MaW0CxqBFljyKh9/BDgrIlY0n9N6JXDKsatWkrqHYVWSJOkwRcQgcCPwyZTSnkP9fErpOeDjwNeBHwGP0zjFWJKOe4ZVSZKkwxARBRpB9asppZuazb+KiKXN4UuBp15tOimlm1NKF6aULgIeAh4+VjVLUjcxrEqSJB2iiAjgvwIPppT+w36Dvg18sNn/QeDvD2JaS5rdUeA64EtHt1pJ6k6RUmp3DZIkSV0lIt5M47Td+4B6s/n3aVy3+g3gVGAb8N6U0u7mZx4HhoEiMAb8ekrpgYj4GrCmOY0/Sind0KrlkKROZliVJEmSJHUcTwOWJEmSJHUcw6okSZIkqeMYViVJkiRJHcewKkmSJEnqOIZVSZIkSVLHMaxKknQQImJBRFzX7F8WEd88hvM6NyJ+41hNX5KkbmBYlSTp4CwArgNIKe1MKb3nGM7rXMCwKkk6rvmcVUmSDkJE3ABcATwEPAy8PqW0OiI+BFwJ5IDVwOeBIvB+YBb4jZTS7og4HfgCsBiYBv55SmlLRLwX+HdADRgH3g48ApSAJ4A/BR4D/mOzbQb4cErpoUOY9w+Be4ALgGHgt1NKG47NT0qSpKPDI6uSJB2czwC/SCmdC/zrA4atBn6TRhj8Y2A6pXQecDvwgeY41wOfSCmtAz4N/Jdm+2eBf5xSWgNcnlKaa7Z9PaV0bkrp68AW4K3NaX4W+JNDnDfAQErpYhpHh798ZD8KSZKOvXy7C5AkqQfcklKaACYiYhy4udl+H3BORAwCFwP/MyL2fqav2f0J8DcR8Q3gppeZ/gjwlYhYCSSgcLDz3m+8rwGklG6LiOGIWJBSGjvM5ZUk6ZgzrEqSdORm9+uv7/e+TuP/2gwYax6VfYGU0sci4kLgncA9EfGicYB/TyOUXhURK4AfHsK8983qwFm/wvJIktR2ngYsSdLBmQCGDueDKaU9wGPN61OJhjXN/tNTSneklD4LPAOc8hLzGqFx/SrAhw6vfK5pzu/NwHhKafwwpyNJUksYViVJOggppWeBn0TE/cDnDmMSvwV8JCLuBTbTuFkTwOci4r7mdG8D7gVuAc6OiHsi4hrgz4E/jYif0LiZ0uF4LiJ+CnwR+MhhTkOSpJbxbsCSJPW45t2AP51SurPdtUiSdLA8sipJkiRJ6jgeWZUkSZIkdRyPrEqSJEmSOo5hVZIkSZLUcQyrkiRJkqSOY1iVJEmSJHUcw6okSZIkqeMYViVJkiRJHef/AydXpbt9LTx6AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1152x648 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot_df = pd.DataFrame(arch_df)\n",
"plot_df.ffill()[plot_df.index > fill_val].plot(\n",
" title=\"Number of packages by architecture\",\n",
" figsize=(16,9)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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