{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "169709ec",
   "metadata": {},
   "source": [
    "Close to \"Spatial_Join\" notebook, but using PostGIS database instead of simple (geo)pandas.\n",
    "\n",
    "Start Docker with:\n",
    "\n",
    "docker run --name some-postgis -e POSTGRES_PASSWORD=mysecretpassword -p 5432:5432 -d postgis/postgis\n",
    "\n",
    "docker logs -f some-postgis\n",
    "\n",
    "Wait until \"LOG:  database system is ready to accept connections\" (might take several minutes)\n",
    "\n",
    "Requires : geoalchemy2\n",
    "Doesn't work for geopandas 0.8, only for 0.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c2d6845",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dafa799f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:50:56.253380Z",
     "start_time": "2021-10-01T13:50:55.683021Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas.io.sql as psql\n",
    "import pandas as pd\n",
    "import psycopg2 as pg\n",
    "from sqlalchemy import create_engine\n",
    "\n",
    "import geopandas as gpd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70f48289",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:50:58.973225Z",
     "start_time": "2021-10-01T13:50:56.256431Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2ebdd42a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:51:01.106294Z",
     "start_time": "2021-10-01T13:50:58.974578Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d0ab32e3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:32.217881Z",
     "start_time": "2021-10-01T13:54:32.210855Z"
    }
   },
   "outputs": [],
   "source": [
    "pg_host=\"localhost\"\n",
    "pg_port=\"5432\"\n",
    "pg_dbname=\"postgres\"\n",
    "pg_user=\"postgres\"\n",
    "pg_password=\"example\"\n",
    "\n",
    "pg_schema = \"gistest\"\n",
    "connection_string =f\"host='{pg_host}' port={pg_port} dbname={pg_dbname} user={pg_user}  password={pg_password}\"\n",
    "engine_url=f\"postgresql+psycopg2://{pg_user}:{pg_password}@{pg_host}:{pg_port}/{pg_dbname}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c85f1540",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:35.542323Z",
     "start_time": "2021-10-01T13:54:32.682463Z"
    }
   },
   "outputs": [],
   "source": [
    "crs =     'epsg:3857'\n",
    "osm_crs=  'epsg:4326'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "07bbe1c3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:38.514533Z",
     "start_time": "2021-10-01T13:54:35.546877Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_request(query, params=None):\n",
    "#     with pg.connect(database='postgres', user='postgres', host='localhost', password='example') as connection:\n",
    "    with pg.connect(connection_string) as connection:    \n",
    "        connection.set_session(readonly=True)\n",
    "        return psql.read_sql(query, connection, params=params)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "894493c6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:40.829157Z",
     "start_time": "2021-10-01T13:54:38.519817Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_geo_request(query, params=None):\n",
    "#     with pg.connect(database='postgres', user='postgres', host='localhost', password='example') as connection:\n",
    "    with pg.connect(connection_string) as connection:    \n",
    "        connection.set_session(readonly=True)\n",
    "        return gpd.read_postgis(query, connection, params=params, geom_col=\"geometry\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9f294110",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:43.300166Z",
     "start_time": "2021-10-01T13:54:40.833664Z"
    }
   },
   "outputs": [],
   "source": [
    "def run_request(query, params=None):\n",
    "    with pg.connect(connection_string) as connection:    \n",
    "        psql.execute(query, connection, params=params)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1812e7d7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:54:45.953909Z",
     "start_time": "2021-10-01T13:54:43.304282Z"
    }
   },
   "outputs": [],
   "source": [
    "def add_basemap(ax):\n",
    "    \"\"\"\n",
    "    Add a basemap on a plot. Tries first default (Stamen) basemap. If errors, tries OpenStreetMap.Mapnik\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    ax: matplotlib axes\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "        None\n",
    "    \"\"\"\n",
    "\n",
    "    try: \n",
    "        ctx.add_basemap(ax)\n",
    "    except requests.HTTPError:\n",
    "        print(\"Default basemap doesn't work...\")\n",
    "        ctx.add_basemap(ax, source=ctx.providers.OpenStreetMap.Mapnik)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c11b8539",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9fe1361b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T13:58:12.525363Z",
     "start_time": "2021-10-01T13:58:12.511300Z"
    }
   },
   "outputs": [
    {
     "ename": "OperationalError",
     "evalue": "could not connect to server: Connection refused\n\tIs the server running on host \"localhost\" (::1) and accepting\n\tTCP/IP connections on port 5432?\ncould not connect to server: Connection refused\n\tIs the server running on host \"localhost\" (127.0.0.1) and accepting\n\tTCP/IP connections on port 5432?\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-21-581c0efec994>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mrun_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"CREATE SCHEMA IF NOT EXISTS {pg_schema};\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-17-04433aff6fd9>\u001b[0m in \u001b[0;36mrun_request\u001b[0;34m(query, params)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0;32mwith\u001b[0m \u001b[0mpg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconnection_string\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m         \u001b[0mpsql\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/gis/lib/python3.8/site-packages/psycopg2/__init__.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(dsn, connection_factory, cursor_factory, **kwargs)\u001b[0m\n\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m     \u001b[0mdsn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_ext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_dsn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 126\u001b[0;31m     \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_connect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconnection_factory\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconnection_factory\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwasync\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    127\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcursor_factory\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    128\u001b[0m         \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcursor_factory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcursor_factory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mOperationalError\u001b[0m: could not connect to server: Connection refused\n\tIs the server running on host \"localhost\" (::1) and accepting\n\tTCP/IP connections on port 5432?\ncould not connect to server: Connection refused\n\tIs the server running on host \"localhost\" (127.0.0.1) and accepting\n\tTCP/IP connections on port 5432?\n"
     ]
    }
   ],
   "source": [
    "run_request(f\"CREATE SCHEMA IF NOT EXISTS {pg_schema};\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "id": "dbbdfbc9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:31:52.179032Z",
     "start_time": "2021-06-23T14:31:50.544633Z"
    }
   },
   "outputs": [],
   "source": [
    "run_request(f\"DROP TABLE IF EXISTS {pg_schema}.nis_boundaries\")\n",
    "run_request(f\"DROP TABLE IF EXISTS {pg_schema}.zip_commune_boundaries\")\n",
    "run_request(f\"DROP TABLE IF EXISTS {pg_schema}.zip_commune_boundaries_filled\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e5653585",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-04T07:37:34.000670Z",
     "start_time": "2021-10-04T07:37:33.976678Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "OperationalError",
     "evalue": "server closed the connection unexpectedly\n\tThis probably means the server terminated abnormally\n\tbefore or while processing the request.\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-25-01e98343f77d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m get_request(f\"\"\"SELECT * \n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mFROM\u001b[0m \u001b[0mpg_catalog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpg_tables\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m WHERE schemaname = '{pg_schema}';\"\"\")\n",
      "\u001b[0;32m<ipython-input-15-8127170786ba>\u001b[0m in \u001b[0;36mget_request\u001b[0;34m(query, params)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m#     with pg.connect(database='postgres', user='postgres', host='localhost', password='example') as connection:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0;32mwith\u001b[0m \u001b[0mpg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconnection_string\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m         \u001b[0mconnection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_session\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreadonly\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mpsql\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_sql\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/gis/lib/python3.8/site-packages/psycopg2/__init__.py\u001b[0m in \u001b[0;36mconnect\u001b[0;34m(dsn, connection_factory, cursor_factory, **kwargs)\u001b[0m\n\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m     \u001b[0mdsn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_ext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_dsn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 126\u001b[0;31m     \u001b[0mconn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_connect\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconnection_factory\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mconnection_factory\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwasync\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    127\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcursor_factory\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    128\u001b[0m         \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcursor_factory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcursor_factory\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mOperationalError\u001b[0m: server closed the connection unexpectedly\n\tThis probably means the server terminated abnormally\n\tbefore or while processing the request.\n"
     ]
    }
   ],
   "source": [
    "get_request(f\"\"\"SELECT * \n",
    "FROM pg_catalog.pg_tables\n",
    "WHERE schemaname = '{pg_schema}';\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "912a9d6d",
   "metadata": {},
   "source": [
    "## Zipcode list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "354b5650",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:00:40.976213Z",
     "start_time": "2021-07-08T14:00:40.039659Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1190 unique zipcodes\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>zipcode</th>\n",
       "      <th>locality</th>\n",
       "      <th>is_sub_commune</th>\n",
       "      <th>main_commune</th>\n",
       "      <th>province</th>\n",
       "      <th>is_special</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>1000</td>\n",
       "      <td>Bruxelles</td>\n",
       "      <td>Non</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>1005</td>\n",
       "      <td>Assemblée Réunie de la Commission Communautaire</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Assemblée Réunie de la Commission Communautaire</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>1006</td>\n",
       "      <td>Raad van de Vlaamse Gemeenschapscommissie</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Raad van de Vlaamse Gemeenschapscommissie</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>1007</td>\n",
       "      <td>Assemblée de la Commission Communautaire Franç...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Assemblée de la Commission Communautaire Franç...</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>1008</td>\n",
       "      <td>Chambre des Représentants</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chambre des Représentants</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>True</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2608</th>\n",
       "      <td>9988</td>\n",
       "      <td>Waterland-Oudeman</td>\n",
       "      <td>Oui</td>\n",
       "      <td>SINT-LAUREINS</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2611</th>\n",
       "      <td>9988</td>\n",
       "      <td>Watervliet</td>\n",
       "      <td>Oui</td>\n",
       "      <td>SINT-LAUREINS</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1450</th>\n",
       "      <td>9990</td>\n",
       "      <td>Maldegem</td>\n",
       "      <td>Non</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9991</td>\n",
       "      <td>Adegem</td>\n",
       "      <td>Oui</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1568</th>\n",
       "      <td>9992</td>\n",
       "      <td>Middelburg</td>\n",
       "      <td>Oui</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2765 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode                                           locality  \\\n",
       "384     1000                                          Bruxelles   \n",
       "92      1005    Assemblée Réunie de la Commission Communautaire   \n",
       "1964    1006         Raad van de Vlaamse Gemeenschapscommissie    \n",
       "91      1007  Assemblée de la Commission Communautaire Franç...   \n",
       "424     1008                          Chambre des Représentants   \n",
       "...      ...                                                ...   \n",
       "2608    9988                                  Waterland-Oudeman   \n",
       "2611    9988                                         Watervliet   \n",
       "1450    9990                                           Maldegem   \n",
       "20      9991                                             Adegem   \n",
       "1568    9992                                         Middelburg   \n",
       "\n",
       "     is_sub_commune                                       main_commune  \\\n",
       "384             Non                                          BRUXELLES   \n",
       "92              NaN    Assemblée Réunie de la Commission Communautaire   \n",
       "1964            NaN         Raad van de Vlaamse Gemeenschapscommissie    \n",
       "91              NaN  Assemblée de la Commission Communautaire Franç...   \n",
       "424             NaN                          Chambre des Représentants   \n",
       "...             ...                                                ...   \n",
       "2608            Oui                                      SINT-LAUREINS   \n",
       "2611            Oui                                      SINT-LAUREINS   \n",
       "1450            Non                                           MALDEGEM   \n",
       "20              Oui                                           MALDEGEM   \n",
       "1568            Oui                                           MALDEGEM   \n",
       "\n",
       "               province  is_special  \n",
       "384           BRUXELLES       False  \n",
       "92            BRUXELLES        True  \n",
       "1964          BRUXELLES        True  \n",
       "91            BRUXELLES        True  \n",
       "424           BRUXELLES        True  \n",
       "...                 ...         ...  \n",
       "2608  FLANDRE-ORIENTALE       False  \n",
       "2611  FLANDRE-ORIENTALE       False  \n",
       "1450  FLANDRE-ORIENTALE       False  \n",
       "20    FLANDRE-ORIENTALE       False  \n",
       "1568  FLANDRE-ORIENTALE       False  \n",
       "\n",
       "[2765 rows x 6 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zipcodes = pd.read_excel(\"data/zipcodes_alpha_fr_new.xls\")\n",
    "zipcodes = zipcodes.rename({\"Code postal\":\"zipcode\", \n",
    "                            \"Commune principale\": \"main_commune\", \n",
    "                            \"Localité\":\"locality\",\n",
    "                            \"Province\": \"province\",\n",
    "                            \"Sous-commune\": \"is_sub_commune\"}, axis=1)\n",
    "zipcodes[\"zipcode\"] = zipcodes[\"zipcode\"].astype(str)\n",
    "zipcodes[\"is_special\"] = zipcodes[\"is_sub_commune\"].isnull()\n",
    "zipcodes = zipcodes.sort_values(\"zipcode\")\n",
    "zipcodes[\"province\"] = zipcodes.province.fillna(method=\"ffill\")\n",
    "print(zipcodes.zipcode.nunique(), \"unique zipcodes\")\n",
    "zipcodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "3d2c9f55",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:00:46.431987Z",
     "start_time": "2021-07-08T14:00:44.191838Z"
    }
   },
   "outputs": [],
   "source": [
    "engine = create_engine(engine_url)\n",
    "zipcodes.to_sql(name=\"zipcodes\", con=engine, if_exists=\"replace\", schema=pg_schema, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "589a203d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:00:48.664127Z",
     "start_time": "2021-07-08T14:00:48.609342Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>locality</th>\n",
       "      <th>is_sub_commune</th>\n",
       "      <th>main_commune</th>\n",
       "      <th>province</th>\n",
       "      <th>is_special</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>Bruxelles</td>\n",
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       "      <th>1</th>\n",
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       "      <td>Assemblée Réunie de la Commission Communautaire</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>Raad van de Vlaamse Gemeenschapscommissie</td>\n",
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       "      <td>Raad van de Vlaamse Gemeenschapscommissie</td>\n",
       "      <td>BRUXELLES</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
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       "      <td>Assemblée de la Commission Communautaire Franç...</td>\n",
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       "      <td>Chambre des Représentants</td>\n",
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       "      <td>BRUXELLES</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2760</th>\n",
       "      <td>9988</td>\n",
       "      <td>Waterland-Oudeman</td>\n",
       "      <td>Oui</td>\n",
       "      <td>SINT-LAUREINS</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2761</th>\n",
       "      <td>9988</td>\n",
       "      <td>Watervliet</td>\n",
       "      <td>Oui</td>\n",
       "      <td>SINT-LAUREINS</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2762</th>\n",
       "      <td>9990</td>\n",
       "      <td>Maldegem</td>\n",
       "      <td>Non</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2763</th>\n",
       "      <td>9991</td>\n",
       "      <td>Adegem</td>\n",
       "      <td>Oui</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2764</th>\n",
       "      <td>9992</td>\n",
       "      <td>Middelburg</td>\n",
       "      <td>Oui</td>\n",
       "      <td>MALDEGEM</td>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2765 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode                                           locality  \\\n",
       "0       1000                                          Bruxelles   \n",
       "1       1005    Assemblée Réunie de la Commission Communautaire   \n",
       "2       1006         Raad van de Vlaamse Gemeenschapscommissie    \n",
       "3       1007  Assemblée de la Commission Communautaire Franç...   \n",
       "4       1008                          Chambre des Représentants   \n",
       "...      ...                                                ...   \n",
       "2760    9988                                  Waterland-Oudeman   \n",
       "2761    9988                                         Watervliet   \n",
       "2762    9990                                           Maldegem   \n",
       "2763    9991                                             Adegem   \n",
       "2764    9992                                         Middelburg   \n",
       "\n",
       "     is_sub_commune                                       main_commune  \\\n",
       "0               Non                                          BRUXELLES   \n",
       "1              None    Assemblée Réunie de la Commission Communautaire   \n",
       "2              None         Raad van de Vlaamse Gemeenschapscommissie    \n",
       "3              None  Assemblée de la Commission Communautaire Franç...   \n",
       "4              None                          Chambre des Représentants   \n",
       "...             ...                                                ...   \n",
       "2760            Oui                                      SINT-LAUREINS   \n",
       "2761            Oui                                      SINT-LAUREINS   \n",
       "2762            Non                                           MALDEGEM   \n",
       "2763            Oui                                           MALDEGEM   \n",
       "2764            Oui                                           MALDEGEM   \n",
       "\n",
       "               province  is_special  \n",
       "0             BRUXELLES       False  \n",
       "1             BRUXELLES        True  \n",
       "2             BRUXELLES        True  \n",
       "3             BRUXELLES        True  \n",
       "4             BRUXELLES        True  \n",
       "...                 ...         ...  \n",
       "2760  FLANDRE-ORIENTALE       False  \n",
       "2761  FLANDRE-ORIENTALE       False  \n",
       "2762  FLANDRE-ORIENTALE       False  \n",
       "2763  FLANDRE-ORIENTALE       False  \n",
       "2764  FLANDRE-ORIENTALE       False  \n",
       "\n",
       "[2765 rows x 6 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_request(f\"\"\"SELECT *\n",
    "FROM {pg_schema}.zipcodes;\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9750a8c6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T12:27:47.612346Z",
     "start_time": "2021-06-22T12:27:47.607514Z"
    }
   },
   "source": [
    "## Zipcode boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ae326da7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:01:19.707996Z",
     "start_time": "2021-07-08T14:01:16.703568Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        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>zipcode</th>\n",
       "      <th>is_special</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000</td>\n",
       "      <td>False</td>\n",
       "      <td>MULTIPOLYGON Z (((4.38334 50.87982 0.00000, 4....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005</td>\n",
       "      <td>True</td>\n",
       "      <td>POLYGON Z ((4.35137 50.84458 0.00000, 4.35158 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1006</td>\n",
       "      <td>True</td>\n",
       "      <td>POLYGON Z ((4.35156 50.84513 0.00000, 4.35099 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
       "      <td>True</td>\n",
       "      <td>POLYGON Z ((4.36790 50.84690 0.00000, 4.36802 ...</td>\n",
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       "      <th>4</th>\n",
       "      <td>1008</td>\n",
       "      <td>True</td>\n",
       "      <td>POLYGON Z ((4.36582 50.84691 0.00000, 4.36469 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>9982</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON Z ((3.57643 51.27498 0.00000, 3.57666 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1183</th>\n",
       "      <td>9988</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON Z ((3.61271 51.29793 0.00000, 3.61273 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1184</th>\n",
       "      <td>9990</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON Z ((3.44165 51.24318 0.00000, 3.44176 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>9991</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON Z ((3.49864 51.22072 0.00000, 3.49942 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>9992</td>\n",
       "      <td>False</td>\n",
       "      <td>POLYGON Z ((3.38394 51.27384 0.00000, 3.38423 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1187 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode  is_special                                           geometry\n",
       "0       1000       False  MULTIPOLYGON Z (((4.38334 50.87982 0.00000, 4....\n",
       "1       1005        True  POLYGON Z ((4.35137 50.84458 0.00000, 4.35158 ...\n",
       "2       1006        True  POLYGON Z ((4.35156 50.84513 0.00000, 4.35099 ...\n",
       "3       1007        True  POLYGON Z ((4.36790 50.84690 0.00000, 4.36802 ...\n",
       "4       1008        True  POLYGON Z ((4.36582 50.84691 0.00000, 4.36469 ...\n",
       "...      ...         ...                                                ...\n",
       "1182    9982       False  POLYGON Z ((3.57643 51.27498 0.00000, 3.57666 ...\n",
       "1183    9988       False  POLYGON Z ((3.61271 51.29793 0.00000, 3.61273 ...\n",
       "1184    9990       False  POLYGON Z ((3.44165 51.24318 0.00000, 3.44176 ...\n",
       "1185    9991       False  POLYGON Z ((3.49864 51.22072 0.00000, 3.49942 ...\n",
       "1186    9992       False  POLYGON Z ((3.38394 51.27384 0.00000, 3.38423 ...\n",
       "\n",
       "[1187 rows x 3 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zipcode_boundaries_filename = \"data/zipcode_boundaries_shapefile_3812.zip\"\n",
    "\n",
    "zipcodes_boundaries = gpd.read_file(f\"zip://{zipcode_boundaries_filename}/3812\")\n",
    "zipcodes_boundaries[\"is_special\"] = zipcodes_boundaries.CP_speciau ==1\n",
    "zipcodes_boundaries = zipcodes_boundaries.rename({\"nouveau_PO\":\"zipcode\"}, axis=1)[[\"zipcode\", \"is_special\", \"geometry\"]]\n",
    "\n",
    "zipcodes_boundaries = zipcodes_boundaries.dissolve([\"zipcode\", \"is_special\"]).reset_index()\n",
    "\n",
    "zipcodes_boundaries = zipcodes_boundaries.to_crs(osm_crs)\n",
    "zipcodes_boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "367285d5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:01:37.741459Z",
     "start_time": "2021-07-08T14:01:28.690328Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "engine = create_engine(engine_url)\n",
    "zipcodes_boundaries.to_postgis(name=\"zipcodes_boundaries\", con=engine, if_exists=\"replace\", schema=pg_schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "65526a2d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-10-01T10:09:44.116114Z",
     "start_time": "2021-10-01T10:09:44.068933Z"
    }
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'get_geo_request' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-30137593fd0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m get_geo_request(f\"\"\"SELECT *\n\u001b[0m\u001b[1;32m      2\u001b[0m FROM {pg_schema}.zipcodes_boundaries;\"\"\")\n",
      "\u001b[0;31mNameError\u001b[0m: name 'get_geo_request' is not defined"
     ]
    }
   ],
   "source": [
    "get_geo_request(f\"\"\"SELECT *\n",
    "FROM {pg_schema}.zipcodes_boundaries;\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04e6b9c5",
   "metadata": {},
   "source": [
    "## Zipcode centers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "724a2bbd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:02:57.790743Z",
     "start_time": "2021-07-08T14:02:57.630467Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1145 unique zipcode\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>locality</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Saint-Gilles</td>\n",
       "      <td>1060</td>\n",
       "      <td>POINT (4.34567 50.82674)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Molenbeek-Saint-Jean</td>\n",
       "      <td>1080</td>\n",
       "      <td>POINT (4.32278 50.85436)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ganshoren</td>\n",
       "      <td>1083</td>\n",
       "      <td>POINT (4.31751 50.87124)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Neder-Over-Heembeek</td>\n",
       "      <td>1120</td>\n",
       "      <td>POINT (4.39049 50.89780)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Wavre</td>\n",
       "      <td>1300</td>\n",
       "      <td>POINT (4.60774 50.71642)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2752</th>\n",
       "      <td>Dikkelvenne</td>\n",
       "      <td>9890</td>\n",
       "      <td>POINT (3.68945 50.91767)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2753</th>\n",
       "      <td>Lovendegem</td>\n",
       "      <td>9920</td>\n",
       "      <td>POINT (3.60761 51.09568)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2754</th>\n",
       "      <td>Zomergem</td>\n",
       "      <td>9930</td>\n",
       "      <td>POINT (3.56424 51.11958)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2755</th>\n",
       "      <td>Waarschoot</td>\n",
       "      <td>9950</td>\n",
       "      <td>POINT (3.60617 51.15153)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2756</th>\n",
       "      <td>Assenede</td>\n",
       "      <td>9960</td>\n",
       "      <td>POINT (3.75681 51.23004)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2757 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  locality zipcode                  geometry\n",
       "0             Saint-Gilles    1060  POINT (4.34567 50.82674)\n",
       "1     Molenbeek-Saint-Jean    1080  POINT (4.32278 50.85436)\n",
       "2                Ganshoren    1083  POINT (4.31751 50.87124)\n",
       "3      Neder-Over-Heembeek    1120  POINT (4.39049 50.89780)\n",
       "4                    Wavre    1300  POINT (4.60774 50.71642)\n",
       "...                    ...     ...                       ...\n",
       "2752           Dikkelvenne    9890  POINT (3.68945 50.91767)\n",
       "2753            Lovendegem    9920  POINT (3.60761 51.09568)\n",
       "2754              Zomergem    9930  POINT (3.56424 51.11958)\n",
       "2755            Waarschoot    9950  POINT (3.60617 51.15153)\n",
       "2756              Assenede    9960  POINT (3.75681 51.23004)\n",
       "\n",
       "[2757 rows x 3 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zipcodes_centers = gpd.read_file(\"data/zipcode_centers.geojson\")\n",
    "zipcodes_centers = zipcodes_centers.rename({\"column_1\": \"zipcode\", \"column_2\": \"locality\"}, axis=1)[[\"locality\",\"zipcode\", \"geometry\"]]\n",
    "\n",
    "zipcodes_centers = zipcodes_centers.to_crs(osm_crs)\n",
    "print(zipcodes_centers.zipcode.nunique(), \"unique zipcode\")\n",
    "zipcodes_centers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "c8a38386",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:03:09.973342Z",
     "start_time": "2021-07-08T14:03:09.968354Z"
    }
   },
   "outputs": [],
   "source": [
    "# zipcodes_centers.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "852da91d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:03:12.244305Z",
     "start_time": "2021-07-08T14:03:09.977055Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "engine = create_engine(engine_url)  \n",
    "zipcodes_centers.to_postgis(name=\"zipcodes_centers\", con=engine, if_exists=\"replace\", schema=pg_schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "75bfee3b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T14:03:12.400115Z",
     "start_time": "2021-07-08T14:03:12.254950Z"
    },
    "scrolled": true
   },
   "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>locality</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Saint-Gilles</td>\n",
       "      <td>1060</td>\n",
       "      <td>POINT (4.34567 50.82674)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Molenbeek-Saint-Jean</td>\n",
       "      <td>1080</td>\n",
       "      <td>POINT (4.32278 50.85436)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ganshoren</td>\n",
       "      <td>1083</td>\n",
       "      <td>POINT (4.31751 50.87124)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Neder-Over-Heembeek</td>\n",
       "      <td>1120</td>\n",
       "      <td>POINT (4.39049 50.89780)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Wavre</td>\n",
       "      <td>1300</td>\n",
       "      <td>POINT (4.60774 50.71642)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2752</th>\n",
       "      <td>Dikkelvenne</td>\n",
       "      <td>9890</td>\n",
       "      <td>POINT (3.68945 50.91767)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2753</th>\n",
       "      <td>Lovendegem</td>\n",
       "      <td>9920</td>\n",
       "      <td>POINT (3.60761 51.09568)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2754</th>\n",
       "      <td>Zomergem</td>\n",
       "      <td>9930</td>\n",
       "      <td>POINT (3.56424 51.11958)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2755</th>\n",
       "      <td>Waarschoot</td>\n",
       "      <td>9950</td>\n",
       "      <td>POINT (3.60617 51.15153)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2756</th>\n",
       "      <td>Assenede</td>\n",
       "      <td>9960</td>\n",
       "      <td>POINT (3.75681 51.23004)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2757 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  locality zipcode                  geometry\n",
       "0             Saint-Gilles    1060  POINT (4.34567 50.82674)\n",
       "1     Molenbeek-Saint-Jean    1080  POINT (4.32278 50.85436)\n",
       "2                Ganshoren    1083  POINT (4.31751 50.87124)\n",
       "3      Neder-Over-Heembeek    1120  POINT (4.39049 50.89780)\n",
       "4                    Wavre    1300  POINT (4.60774 50.71642)\n",
       "...                    ...     ...                       ...\n",
       "2752           Dikkelvenne    9890  POINT (3.68945 50.91767)\n",
       "2753            Lovendegem    9920  POINT (3.60761 51.09568)\n",
       "2754              Zomergem    9930  POINT (3.56424 51.11958)\n",
       "2755            Waarschoot    9950  POINT (3.60617 51.15153)\n",
       "2756              Assenede    9960  POINT (3.75681 51.23004)\n",
       "\n",
       "[2757 rows x 3 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_geo_request(f\"\"\"SELECT *\n",
    "FROM {pg_schema}.zipcodes_centers;\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06bc07d7",
   "metadata": {},
   "source": [
    "## Statistical sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "539afeb8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T14:38:30.627873Z",
     "start_time": "2021-06-22T14:38:19.901103Z"
    }
   },
   "outputs": [],
   "source": [
    "statistical_sectors = gpd.read_file(\"zip://data/stat_sectors_2020.zip/sh_statbel_statistical_sectors_20200101.shp\")\n",
    "statistical_sectors[\"CNIS5_2020\"] = statistical_sectors[\"CNIS5_2020\"].astype(str)\n",
    "statistical_sectors = statistical_sectors.to_crs(osm_crs)\n",
    "statistical_sectors.columns= statistical_sectors.columns.str.lower()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "17d9e1af",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T14:39:52.828353Z",
     "start_time": "2021-06-22T14:39:52.097533Z"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "98487f76",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T14:40:16.620139Z",
     "start_time": "2021-06-22T14:39:55.589755Z"
    }
   },
   "outputs": [],
   "source": [
    "engine = create_engine(engine_url)  \n",
    "statistical_sectors.to_postgis(name=\"statistical_sectors\", con=engine, if_exists=\"replace\", schema=pg_schema)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81f080f2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T11:37:09.241396Z",
     "start_time": "2021-07-08T11:37:08.089425Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>cs01012020</th>\n",
       "      <th>t_sec_nl</th>\n",
       "      <th>t_sec_fr</th>\n",
       "      <th>t_sec_de</th>\n",
       "      <th>c_nis6</th>\n",
       "      <th>t_nis6_nl</th>\n",
       "      <th>t_nis6_fr</th>\n",
       "      <th>cnis5_2020</th>\n",
       "      <th>t_mun_nl</th>\n",
       "      <th>t_mun_fr</th>\n",
       "      <th>...</th>\n",
       "      <th>t_regio_nl</th>\n",
       "      <th>t_regio_fr</th>\n",
       "      <th>t_regio_de</th>\n",
       "      <th>c_country</th>\n",
       "      <th>nuts1</th>\n",
       "      <th>nuts2</th>\n",
       "      <th>nuts3</th>\n",
       "      <th>m_area_ha</th>\n",
       "      <th>m_peri_m</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11001A00-</td>\n",
       "      <td>AARTSELAAR-CENTRUM</td>\n",
       "      <td>AARTSELAAR-CENTRUM</td>\n",
       "      <td>AARTSELAAR-CENTRUM</td>\n",
       "      <td>11001A</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>...</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>Flämische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE2</td>\n",
       "      <td>BE21</td>\n",
       "      <td>BE211</td>\n",
       "      <td>53.158103</td>\n",
       "      <td>5248.0</td>\n",
       "      <td>01030000A0E6100000010000009300000027AE79B5E491...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11001A01-</td>\n",
       "      <td>DE LEEUWERIK</td>\n",
       "      <td>DE LEEUWERIK</td>\n",
       "      <td>DE LEEUWERIK</td>\n",
       "      <td>11001A</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>...</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>Flämische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE2</td>\n",
       "      <td>BE21</td>\n",
       "      <td>BE211</td>\n",
       "      <td>67.114679</td>\n",
       "      <td>3935.0</td>\n",
       "      <td>01030000A0E6100000010000006C000000BF3A94433093...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11001A020</td>\n",
       "      <td>BUERSTEDE</td>\n",
       "      <td>BUERSTEDE</td>\n",
       "      <td>BUERSTEDE</td>\n",
       "      <td>11001A</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>...</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>Flämische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE2</td>\n",
       "      <td>BE21</td>\n",
       "      <td>BE211</td>\n",
       "      <td>28.084365</td>\n",
       "      <td>2202.0</td>\n",
       "      <td>01030000A0E61000000100000034000000D4F1B29DEA82...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11001A030</td>\n",
       "      <td>YSSELAAR</td>\n",
       "      <td>YSSELAAR</td>\n",
       "      <td>YSSELAAR</td>\n",
       "      <td>11001A</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>...</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>Flämische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE2</td>\n",
       "      <td>BE21</td>\n",
       "      <td>BE211</td>\n",
       "      <td>42.811849</td>\n",
       "      <td>3403.0</td>\n",
       "      <td>01030000A0E61000000100000031010000A292C6F2CA90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11001A042</td>\n",
       "      <td>KLEINE GRIPPE</td>\n",
       "      <td>KLEINE GRIPPE</td>\n",
       "      <td>KLEINE GRIPPE</td>\n",
       "      <td>11001A</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>...</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>Flämische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE2</td>\n",
       "      <td>BE21</td>\n",
       "      <td>BE211</td>\n",
       "      <td>25.561955</td>\n",
       "      <td>2166.0</td>\n",
       "      <td>01030000A0E6100000010000003A000000BF3A94433093...</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19789</th>\n",
       "      <td>93090G191</td>\n",
       "      <td>BOIS DE NISMES</td>\n",
       "      <td>BOIS DE NISMES</td>\n",
       "      <td>BOIS DE NISMES</td>\n",
       "      <td>93090G</td>\n",
       "      <td>NISMES</td>\n",
       "      <td>NISMES</td>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>...</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>Wallonische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE3</td>\n",
       "      <td>BE35</td>\n",
       "      <td>BE353</td>\n",
       "      <td>1507.153385</td>\n",
       "      <td>24359.0</td>\n",
       "      <td>01030000A0E610000002000000D702000085D1D1CCC163...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19790</th>\n",
       "      <td>93090H000</td>\n",
       "      <td>DOURBES-CENTRE</td>\n",
       "      <td>DOURBES-CENTRE</td>\n",
       "      <td>DOURBES-CENTRE</td>\n",
       "      <td>93090H</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>...</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>Wallonische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE3</td>\n",
       "      <td>BE35</td>\n",
       "      <td>BE353</td>\n",
       "      <td>19.381890</td>\n",
       "      <td>2569.0</td>\n",
       "      <td>01030000A0E610000001000000470000007C617990215B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19791</th>\n",
       "      <td>93090H012</td>\n",
       "      <td>DOURBES ROUTE DE MARIEMBOURG</td>\n",
       "      <td>DOURBES ROUTE DE MARIEMBOURG</td>\n",
       "      <td>DOURBES ROUTE DE MARIEMBOURG</td>\n",
       "      <td>93090H</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>...</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>Wallonische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE3</td>\n",
       "      <td>BE35</td>\n",
       "      <td>BE353</td>\n",
       "      <td>19.369718</td>\n",
       "      <td>2411.0</td>\n",
       "      <td>01030000A0E610000001000000410000007C617990215B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19792</th>\n",
       "      <td>93090H063</td>\n",
       "      <td>LORET</td>\n",
       "      <td>LORET</td>\n",
       "      <td>LORET</td>\n",
       "      <td>93090H</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>...</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>Wallonische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE3</td>\n",
       "      <td>BE35</td>\n",
       "      <td>BE353</td>\n",
       "      <td>24.865501</td>\n",
       "      <td>2559.0</td>\n",
       "      <td>01030000A0E61000000100000032000000538EA3F3385D...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19793</th>\n",
       "      <td>93090H091</td>\n",
       "      <td>ROCHE A L'HOMME</td>\n",
       "      <td>ROCHE A L'HOMME</td>\n",
       "      <td>ROCHE A L'HOMME</td>\n",
       "      <td>93090H</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>DOURBES*</td>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>...</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>Wallonische Region</td>\n",
       "      <td>BE</td>\n",
       "      <td>BE3</td>\n",
       "      <td>BE35</td>\n",
       "      <td>BE353</td>\n",
       "      <td>903.007902</td>\n",
       "      <td>18791.0</td>\n",
       "      <td>01030000A0E61000000200000074010000178F5339D67D...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19794 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      cs01012020                      t_sec_nl                      t_sec_fr  \\\n",
       "0      11001A00-            AARTSELAAR-CENTRUM            AARTSELAAR-CENTRUM   \n",
       "1      11001A01-                  DE LEEUWERIK                  DE LEEUWERIK   \n",
       "2      11001A020                     BUERSTEDE                     BUERSTEDE   \n",
       "3      11001A030                      YSSELAAR                      YSSELAAR   \n",
       "4      11001A042                 KLEINE GRIPPE                 KLEINE GRIPPE   \n",
       "...          ...                           ...                           ...   \n",
       "19789  93090G191                BOIS DE NISMES                BOIS DE NISMES   \n",
       "19790  93090H000                DOURBES-CENTRE                DOURBES-CENTRE   \n",
       "19791  93090H012  DOURBES ROUTE DE MARIEMBOURG  DOURBES ROUTE DE MARIEMBOURG   \n",
       "19792  93090H063                         LORET                         LORET   \n",
       "19793  93090H091               ROCHE A L'HOMME               ROCHE A L'HOMME   \n",
       "\n",
       "                           t_sec_de  c_nis6   t_nis6_nl   t_nis6_fr  \\\n",
       "0                AARTSELAAR-CENTRUM  11001A  AARTSELAAR  AARTSELAAR   \n",
       "1                      DE LEEUWERIK  11001A  AARTSELAAR  AARTSELAAR   \n",
       "2                         BUERSTEDE  11001A  AARTSELAAR  AARTSELAAR   \n",
       "3                          YSSELAAR  11001A  AARTSELAAR  AARTSELAAR   \n",
       "4                     KLEINE GRIPPE  11001A  AARTSELAAR  AARTSELAAR   \n",
       "...                             ...     ...         ...         ...   \n",
       "19789                BOIS DE NISMES  93090G      NISMES      NISMES   \n",
       "19790                DOURBES-CENTRE  93090H    DOURBES*    DOURBES*   \n",
       "19791  DOURBES ROUTE DE MARIEMBOURG  93090H    DOURBES*    DOURBES*   \n",
       "19792                         LORET  93090H    DOURBES*    DOURBES*   \n",
       "19793               ROCHE A L'HOMME  93090H    DOURBES*    DOURBES*   \n",
       "\n",
       "      cnis5_2020    t_mun_nl    t_mun_fr  ...     t_regio_nl       t_regio_fr  \\\n",
       "0          11001  Aartselaar  Aartselaar  ...  Vlaams Gewest  Région flamande   \n",
       "1          11001  Aartselaar  Aartselaar  ...  Vlaams Gewest  Région flamande   \n",
       "2          11001  Aartselaar  Aartselaar  ...  Vlaams Gewest  Région flamande   \n",
       "3          11001  Aartselaar  Aartselaar  ...  Vlaams Gewest  Région flamande   \n",
       "4          11001  Aartselaar  Aartselaar  ...  Vlaams Gewest  Région flamande   \n",
       "...          ...         ...         ...  ...            ...              ...   \n",
       "19789      93090   Viroinval   Viroinval  ...   Waals Gewest  Région wallonne   \n",
       "19790      93090   Viroinval   Viroinval  ...   Waals Gewest  Région wallonne   \n",
       "19791      93090   Viroinval   Viroinval  ...   Waals Gewest  Région wallonne   \n",
       "19792      93090   Viroinval   Viroinval  ...   Waals Gewest  Région wallonne   \n",
       "19793      93090   Viroinval   Viroinval  ...   Waals Gewest  Région wallonne   \n",
       "\n",
       "               t_regio_de c_country nuts1 nuts2  nuts3    m_area_ha m_peri_m  \\\n",
       "0        Flämische Region        BE   BE2  BE21  BE211    53.158103   5248.0   \n",
       "1        Flämische Region        BE   BE2  BE21  BE211    67.114679   3935.0   \n",
       "2        Flämische Region        BE   BE2  BE21  BE211    28.084365   2202.0   \n",
       "3        Flämische Region        BE   BE2  BE21  BE211    42.811849   3403.0   \n",
       "4        Flämische Region        BE   BE2  BE21  BE211    25.561955   2166.0   \n",
       "...                   ...       ...   ...   ...    ...          ...      ...   \n",
       "19789  Wallonische Region        BE   BE3  BE35  BE353  1507.153385  24359.0   \n",
       "19790  Wallonische Region        BE   BE3  BE35  BE353    19.381890   2569.0   \n",
       "19791  Wallonische Region        BE   BE3  BE35  BE353    19.369718   2411.0   \n",
       "19792  Wallonische Region        BE   BE3  BE35  BE353    24.865501   2559.0   \n",
       "19793  Wallonische Region        BE   BE3  BE35  BE353   903.007902  18791.0   \n",
       "\n",
       "                                                geometry  \n",
       "0      01030000A0E6100000010000009300000027AE79B5E491...  \n",
       "1      01030000A0E6100000010000006C000000BF3A94433093...  \n",
       "2      01030000A0E61000000100000034000000D4F1B29DEA82...  \n",
       "3      01030000A0E61000000100000031010000A292C6F2CA90...  \n",
       "4      01030000A0E6100000010000003A000000BF3A94433093...  \n",
       "...                                                  ...  \n",
       "19789  01030000A0E610000002000000D702000085D1D1CCC163...  \n",
       "19790  01030000A0E610000001000000470000007C617990215B...  \n",
       "19791  01030000A0E610000001000000410000007C617990215B...  \n",
       "19792  01030000A0E61000000100000032000000538EA3F3385D...  \n",
       "19793  01030000A0E61000000200000074010000178F5339D67D...  \n",
       "\n",
       "[19794 rows x 30 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sectors = get_request(f\"\"\"SELECT *\n",
    "FROM {pg_schema}.statistical_sectors;\"\"\")\n",
    "sectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "853c0240",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T11:36:43.491889Z",
     "start_time": "2021-07-08T11:36:24.334249Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>cnis5_2020</th>\n",
       "      <th>t_mun_nl</th>\n",
       "      <th>t_mun_fr</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11001</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>Aartselaar</td>\n",
       "      <td>POLYGON Z ((4.37085 51.11013 0.00000, 4.36937 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11002</td>\n",
       "      <td>Antwerpen</td>\n",
       "      <td>Anvers</td>\n",
       "      <td>POLYGON Z ((4.35607 51.20341 0.00000, 4.35595 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11004</td>\n",
       "      <td>Boechout</td>\n",
       "      <td>Boechout</td>\n",
       "      <td>POLYGON Z ((4.52182 51.14748 0.00000, 4.52177 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11005</td>\n",
       "      <td>Boom</td>\n",
       "      <td>Boom</td>\n",
       "      <td>POLYGON Z ((4.38839 51.08384 0.00000, 4.38832 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11007</td>\n",
       "      <td>Borsbeek</td>\n",
       "      <td>Borsbeek</td>\n",
       "      <td>POLYGON Z ((4.50235 51.19112 0.00000, 4.50213 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>93018</td>\n",
       "      <td>Doische</td>\n",
       "      <td>Doische</td>\n",
       "      <td>POLYGON Z ((4.62817 50.09562 0.00000, 4.62770 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>577</th>\n",
       "      <td>93022</td>\n",
       "      <td>Florennes</td>\n",
       "      <td>Florennes</td>\n",
       "      <td>POLYGON Z ((4.76349 50.21722 0.00000, 4.76339 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578</th>\n",
       "      <td>93056</td>\n",
       "      <td>Philippeville</td>\n",
       "      <td>Philippeville</td>\n",
       "      <td>POLYGON Z ((4.58440 50.10740 0.00000, 4.58441 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>93088</td>\n",
       "      <td>Walcourt</td>\n",
       "      <td>Walcourt</td>\n",
       "      <td>POLYGON Z ((4.52308 50.27092 0.00000, 4.52305 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>580</th>\n",
       "      <td>93090</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>Viroinval</td>\n",
       "      <td>POLYGON Z ((4.66348 49.99385 0.00000, 4.66340 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>581 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    cnis5_2020       t_mun_nl       t_mun_fr  \\\n",
       "0        11001     Aartselaar     Aartselaar   \n",
       "1        11002      Antwerpen         Anvers   \n",
       "2        11004       Boechout       Boechout   \n",
       "3        11005           Boom           Boom   \n",
       "4        11007       Borsbeek       Borsbeek   \n",
       "..         ...            ...            ...   \n",
       "576      93018        Doische        Doische   \n",
       "577      93022      Florennes      Florennes   \n",
       "578      93056  Philippeville  Philippeville   \n",
       "579      93088       Walcourt       Walcourt   \n",
       "580      93090      Viroinval      Viroinval   \n",
       "\n",
       "                                              geometry  \n",
       "0    POLYGON Z ((4.37085 51.11013 0.00000, 4.36937 ...  \n",
       "1    POLYGON Z ((4.35607 51.20341 0.00000, 4.35595 ...  \n",
       "2    POLYGON Z ((4.52182 51.14748 0.00000, 4.52177 ...  \n",
       "3    POLYGON Z ((4.38839 51.08384 0.00000, 4.38832 ...  \n",
       "4    POLYGON Z ((4.50235 51.19112 0.00000, 4.50213 ...  \n",
       "..                                                 ...  \n",
       "576  POLYGON Z ((4.62817 50.09562 0.00000, 4.62770 ...  \n",
       "577  POLYGON Z ((4.76349 50.21722 0.00000, 4.76339 ...  \n",
       "578  POLYGON Z ((4.58440 50.10740 0.00000, 4.58441 ...  \n",
       "579  POLYGON Z ((4.52308 50.27092 0.00000, 4.52305 ...  \n",
       "580  POLYGON Z ((4.66348 49.99385 0.00000, 4.66340 ...  \n",
       "\n",
       "[581 rows x 4 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Niss boundaries \n",
    "\n",
    "nis_boundaries= get_geo_request(f\"\"\"\n",
    "SELECT cnis5_2020, t_mun_nl, t_mun_fr, ST_Union(geometry) as geometry\n",
    "FROM {pg_schema}.statistical_sectors\n",
    "GROUP BY cnis5_2020, t_mun_nl, t_mun_fr;\"\"\")\n",
    "nis_boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "69d00191",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T11:40:32.864661Z",
     "start_time": "2021-07-08T11:40:03.478713Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>c_provi</th>\n",
       "      <th>t_provi_fr</th>\n",
       "      <th>t_provi_nl</th>\n",
       "      <th>t_regio_nl</th>\n",
       "      <th>t_regio_fr</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>Brussels Hoofdstedelijk Gewest</td>\n",
       "      <td>Région de Bruxelles-Capitale</td>\n",
       "      <td>POLYGON Z ((4.29740 50.81001 0.00000, 4.29735 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000</td>\n",
       "      <td>Province d’Anvers</td>\n",
       "      <td>Provincie Antwerpen</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>MULTIPOLYGON Z (((4.93579 51.40930 0.00000, 4....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20001</td>\n",
       "      <td>Province du Brabant flamand</td>\n",
       "      <td>Provincie Vlaams-Brabant</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>POLYGON Z ((5.10784 50.72285 0.00000, 5.10736 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20002</td>\n",
       "      <td>Province du Brabant wallon</td>\n",
       "      <td>Provincie Waals-Brabant</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>POLYGON Z ((4.14575 50.63660 0.00000, 4.14578 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30000</td>\n",
       "      <td>Province de Flandre occidentale</td>\n",
       "      <td>Provincie West-Vlaanderen</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>POLYGON Z ((2.84230 50.73559 0.00000, 2.84250 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>40000</td>\n",
       "      <td>Province de Flandre orientale</td>\n",
       "      <td>Provincie Oost-Vlaanderen</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>POLYGON Z ((3.49165 50.75792 0.00000, 3.49161 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>50000</td>\n",
       "      <td>Province du Hainaut</td>\n",
       "      <td>Provincie Henegouwen</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>MULTIPOLYGON Z (((2.91167 50.70400 0.00000, 2....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>60000</td>\n",
       "      <td>Province de Liège</td>\n",
       "      <td>Provincie Luik</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>POLYGON Z ((5.35148 50.38838 0.00000, 5.35144 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>70000</td>\n",
       "      <td>Province du Limbourg</td>\n",
       "      <td>Provincie Limburg</td>\n",
       "      <td>Vlaams Gewest</td>\n",
       "      <td>Région flamande</td>\n",
       "      <td>MULTIPOLYGON Z (((5.89564 50.74545 0.00000, 5....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>80000</td>\n",
       "      <td>Province du Luxembourg</td>\n",
       "      <td>Provincie Luxemburg</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>POLYGON Z ((5.01249 49.99737 0.00000, 5.01249 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>90000</td>\n",
       "      <td>Province de Namur</td>\n",
       "      <td>Provincie Namen</td>\n",
       "      <td>Waals Gewest</td>\n",
       "      <td>Région wallonne</td>\n",
       "      <td>POLYGON Z ((4.51394 49.94892 0.00000, 4.51385 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   c_provi                       t_provi_fr                 t_provi_nl  \\\n",
       "0        -                             None                       None   \n",
       "1    10000                Province d’Anvers        Provincie Antwerpen   \n",
       "2    20001      Province du Brabant flamand   Provincie Vlaams-Brabant   \n",
       "3    20002       Province du Brabant wallon    Provincie Waals-Brabant   \n",
       "4    30000  Province de Flandre occidentale  Provincie West-Vlaanderen   \n",
       "5    40000    Province de Flandre orientale  Provincie Oost-Vlaanderen   \n",
       "6    50000              Province du Hainaut       Provincie Henegouwen   \n",
       "7    60000                Province de Liège             Provincie Luik   \n",
       "8    70000             Province du Limbourg          Provincie Limburg   \n",
       "9    80000           Province du Luxembourg        Provincie Luxemburg   \n",
       "10   90000                Province de Namur            Provincie Namen   \n",
       "\n",
       "                        t_regio_nl                    t_regio_fr  \\\n",
       "0   Brussels Hoofdstedelijk Gewest  Région de Bruxelles-Capitale   \n",
       "1                    Vlaams Gewest               Région flamande   \n",
       "2                    Vlaams Gewest               Région flamande   \n",
       "3                     Waals Gewest               Région wallonne   \n",
       "4                    Vlaams Gewest               Région flamande   \n",
       "5                    Vlaams Gewest               Région flamande   \n",
       "6                     Waals Gewest               Région wallonne   \n",
       "7                     Waals Gewest               Région wallonne   \n",
       "8                    Vlaams Gewest               Région flamande   \n",
       "9                     Waals Gewest               Région wallonne   \n",
       "10                    Waals Gewest               Région wallonne   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON Z ((4.29740 50.81001 0.00000, 4.29735 ...  \n",
       "1   MULTIPOLYGON Z (((4.93579 51.40930 0.00000, 4....  \n",
       "2   POLYGON Z ((5.10784 50.72285 0.00000, 5.10736 ...  \n",
       "3   POLYGON Z ((4.14575 50.63660 0.00000, 4.14578 ...  \n",
       "4   POLYGON Z ((2.84230 50.73559 0.00000, 2.84250 ...  \n",
       "5   POLYGON Z ((3.49165 50.75792 0.00000, 3.49161 ...  \n",
       "6   MULTIPOLYGON Z (((2.91167 50.70400 0.00000, 2....  \n",
       "7   POLYGON Z ((5.35148 50.38838 0.00000, 5.35144 ...  \n",
       "8   MULTIPOLYGON Z (((5.89564 50.74545 0.00000, 5....  \n",
       "9   POLYGON Z ((5.01249 49.99737 0.00000, 5.01249 ...  \n",
       "10  POLYGON Z ((4.51394 49.94892 0.00000, 4.51385 ...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Province boundaries \n",
    "nis_provinces= get_geo_request(f\"\"\"\n",
    "SELECT c_provi, t_provi_fr, t_provi_nl, t_regio_nl, t_regio_fr,  ST_Union(geometry) as geometry\n",
    "FROM {pg_schema}.statistical_sectors\n",
    "GROUP BY c_provi, t_provi_fr, t_provi_nl, t_regio_nl, t_regio_fr\"\"\")\n",
    "nis_provinces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "39e3abad",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T11:43:54.435951Z",
     "start_time": "2021-07-08T11:43:54.038826Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nis_provinces.assign(label=nis_provinces.t_provi_fr.fillna(nis_provinces.t_regio_fr)).plot(\"label\", legend=True, figsize=(10,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ab4bbc6",
   "metadata": {},
   "source": [
    "## Views"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "id": "6684a7a7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:32:12.624397Z",
     "start_time": "2021-06-23T14:31:55.869332Z"
    }
   },
   "outputs": [],
   "source": [
    "run_request(f\"\"\"\n",
    "CREATE TABLE {pg_schema}.nis_boundaries AS\n",
    "    SELECT cnis5_2020, t_mun_nl, t_mun_fr, ST_Union(geometry) as geometry\n",
    "    FROM {pg_schema}.statistical_sectors\n",
    "    GROUP BY cnis5_2020, t_mun_nl, t_mun_fr\n",
    "    \"\"\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 476,
   "id": "953a9b5a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:32:45.900454Z",
     "start_time": "2021-06-23T14:32:19.556454Z"
    }
   },
   "outputs": [],
   "source": [
    "run_request(f\"\"\"\n",
    "CREATE TABLE {pg_schema}.zip_commune_boundaries AS\n",
    "    SELECT main_commune, ST_Union(geometry) as geometry\n",
    "    FROM {pg_schema}.zipcodes zp \n",
    "      JOIN {pg_schema}.zipcodes_boundaries zp_bnd \n",
    "      ON zp.zipcode = zp_bnd.zipcode\n",
    "    where NOT zp.is_special\n",
    "    GROUP BY main_commune\n",
    "    \"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "id": "81f8f7e6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:33:57.033580Z",
     "start_time": "2021-06-23T14:33:56.804800Z"
    }
   },
   "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>zipcode</th>\n",
       "      <th>is_special</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000</td>\n",
       "      <td>False</td>\n",
       "      <td>01060000A0E6100000050000000103000080070000009E...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005</td>\n",
       "      <td>True</td>\n",
       "      <td>01030000A0E610000001000000090000003D373065CC67...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1006</td>\n",
       "      <td>True</td>\n",
       "      <td>01030000A0E610000001000000080000008B1D8563FE67...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
       "      <td>True</td>\n",
       "      <td>01030000A0E6100000010000000600000006897794BA78...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1008</td>\n",
       "      <td>True</td>\n",
       "      <td>01030000A0E610000001000000060000008CA2FF469876...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>9982</td>\n",
       "      <td>False</td>\n",
       "      <td>01030000A0E610000001000000470100001278574E869C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1183</th>\n",
       "      <td>9988</td>\n",
       "      <td>False</td>\n",
       "      <td>01030000A0E6100000010000000C0200005B5F448AD4E6...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1184</th>\n",
       "      <td>9990</td>\n",
       "      <td>False</td>\n",
       "      <td>01030000A0E610000001000000EC020000FF9BE0508288...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>9991</td>\n",
       "      <td>False</td>\n",
       "      <td>01030000A0E610000001000000B0020000007CE0DE34FD...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>9992</td>\n",
       "      <td>False</td>\n",
       "      <td>01030000A0E610000001000000B4010000AB849FE24C12...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1187 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode  is_special                                           geometry\n",
       "0       1000       False  01060000A0E6100000050000000103000080070000009E...\n",
       "1       1005        True  01030000A0E610000001000000090000003D373065CC67...\n",
       "2       1006        True  01030000A0E610000001000000080000008B1D8563FE67...\n",
       "3       1007        True  01030000A0E6100000010000000600000006897794BA78...\n",
       "4       1008        True  01030000A0E610000001000000060000008CA2FF469876...\n",
       "...      ...         ...                                                ...\n",
       "1182    9982       False  01030000A0E610000001000000470100001278574E869C...\n",
       "1183    9988       False  01030000A0E6100000010000000C0200005B5F448AD4E6...\n",
       "1184    9990       False  01030000A0E610000001000000EC020000FF9BE0508288...\n",
       "1185    9991       False  01030000A0E610000001000000B0020000007CE0DE34FD...\n",
       "1186    9992       False  01030000A0E610000001000000B4010000AB849FE24C12...\n",
       "\n",
       "[1187 rows x 3 columns]"
      ]
     },
     "execution_count": 478,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_request(f\"SELECT * FROM {pg_schema}.zipcodes_boundaries \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "id": "efc2d9d2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:34:38.753485Z",
     "start_time": "2021-06-23T14:34:36.172795Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Fill holes left by special codes. Only for zone fully included in a \"normal\" zone\n",
    "run_request(f\"\"\"\n",
    "CREATE TABLE {pg_schema}.zip_commune_boundaries_filled AS\n",
    "    SELECT main_commune, ST_Collect(ST_MakePolygon(geometry)) As geometry\n",
    "    FROM (\n",
    "        SELECT main_commune, ST_ExteriorRing((ST_Dump(geometry)).geom) As geometry\n",
    "        FROM  {pg_schema}.zip_commune_boundaries \n",
    "    ) s\n",
    "    GROUP BY main_commune\n",
    "    \"\"\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e76786e",
   "metadata": {},
   "source": [
    "# Queries"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5ffbff7",
   "metadata": {},
   "source": [
    "## Join zip centers-boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "id": "54c8192b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:34:48.380114Z",
     "start_time": "2021-06-23T14:34:47.843253Z"
    }
   },
   "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>bnd_zipcode</th>\n",
       "      <th>ctr_zipcode</th>\n",
       "      <th>locality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1060</td>\n",
       "      <td>1060</td>\n",
       "      <td>Saint-Gilles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1080</td>\n",
       "      <td>1080</td>\n",
       "      <td>Molenbeek-Saint-Jean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1083</td>\n",
       "      <td>1083</td>\n",
       "      <td>Ganshoren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1120</td>\n",
       "      <td>1120</td>\n",
       "      <td>Neder-Over-Heembeek</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1300</td>\n",
       "      <td>1300</td>\n",
       "      <td>Wavre</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2752</th>\n",
       "      <td>9890</td>\n",
       "      <td>9890</td>\n",
       "      <td>Dikkelvenne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2753</th>\n",
       "      <td>9920</td>\n",
       "      <td>9920</td>\n",
       "      <td>Lovendegem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2754</th>\n",
       "      <td>9930</td>\n",
       "      <td>9930</td>\n",
       "      <td>Zomergem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2755</th>\n",
       "      <td>9950</td>\n",
       "      <td>9950</td>\n",
       "      <td>Waarschoot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2756</th>\n",
       "      <td>9960</td>\n",
       "      <td>9960</td>\n",
       "      <td>Assenede</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2757 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     bnd_zipcode ctr_zipcode              locality\n",
       "0           1060        1060          Saint-Gilles\n",
       "1           1080        1080  Molenbeek-Saint-Jean\n",
       "2           1083        1083             Ganshoren\n",
       "3           1120        1120   Neder-Over-Heembeek\n",
       "4           1300        1300                 Wavre\n",
       "...          ...         ...                   ...\n",
       "2752        9890        9890           Dikkelvenne\n",
       "2753        9920        9920            Lovendegem\n",
       "2754        9930        9930              Zomergem\n",
       "2755        9950        9950            Waarschoot\n",
       "2756        9960        9960              Assenede\n",
       "\n",
       "[2757 rows x 3 columns]"
      ]
     },
     "execution_count": 482,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sjoin_zip_center = get_request(f\"\"\"\n",
    "SELECT bnd.zipcode as bnd_zipcode, ctr.zipcode as ctr_zipcode, locality\n",
    "FROM {pg_schema}.zipcodes_boundaries bnd, {pg_schema}.zipcodes_centers ctr\n",
    "WHERE ST_Contains(bnd.geometry, ctr.geometry)\n",
    "\"\"\")\n",
    "sjoin_zip_center"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "id": "a3cf25d2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:34:51.526071Z",
     "start_time": "2021-06-23T14:34:51.193812Z"
    },
    "scrolled": true
   },
   "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>bnd_zipcode</th>\n",
       "      <th>ctr_zipcode</th>\n",
       "      <th>locality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1130</td>\n",
       "      <td>3700</td>\n",
       "      <td>Haren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1541</td>\n",
       "      <td>8600</td>\n",
       "      <td>Driekapellen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000</td>\n",
       "      <td>2030</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000</td>\n",
       "      <td>2060</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000</td>\n",
       "      <td>2018</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2000</td>\n",
       "      <td>2050</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2000</td>\n",
       "      <td>2020</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2000</td>\n",
       "      <td>2040</td>\n",
       "      <td>Antwerpen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2180</td>\n",
       "      <td>2223</td>\n",
       "      <td>Schriek</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2180</td>\n",
       "      <td>3400</td>\n",
       "      <td>Laar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2490</td>\n",
       "      <td>1910</td>\n",
       "      <td>Berg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2490</td>\n",
       "      <td>3700</td>\n",
       "      <td>Berg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2560</td>\n",
       "      <td>3840</td>\n",
       "      <td>Voort</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3202</td>\n",
       "      <td>3540</td>\n",
       "      <td>Donk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3300</td>\n",
       "      <td>3470</td>\n",
       "      <td>Sint-Margriete-Houtem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3700</td>\n",
       "      <td>3840</td>\n",
       "      <td>Kolmont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3770</td>\n",
       "      <td>9660</td>\n",
       "      <td>Elst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>4000</td>\n",
       "      <td>4020</td>\n",
       "      <td>Liège</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>4120</td>\n",
       "      <td>4480</td>\n",
       "      <td>Ehein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4122</td>\n",
       "      <td>4120</td>\n",
       "      <td>Neupré</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>4141</td>\n",
       "      <td>4920</td>\n",
       "      <td>Louveigné</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4400</td>\n",
       "      <td>6831</td>\n",
       "      <td>Noirfontaine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>4852</td>\n",
       "      <td>4850</td>\n",
       "      <td>Plombières</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4910</td>\n",
       "      <td>6661</td>\n",
       "      <td>Mont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4910</td>\n",
       "      <td>5530</td>\n",
       "      <td>Mont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>4910</td>\n",
       "      <td>4800</td>\n",
       "      <td>Polleur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>4960</td>\n",
       "      <td>6834</td>\n",
       "      <td>Bellevaux</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4987</td>\n",
       "      <td>5600</td>\n",
       "      <td>Neuville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4987</td>\n",
       "      <td>5080</td>\n",
       "      <td>La Bruyère</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>4987</td>\n",
       "      <td>4821</td>\n",
       "      <td>Andrimont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>5541</td>\n",
       "      <td>5540</td>\n",
       "      <td>Hastière</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>5576</td>\n",
       "      <td>5570</td>\n",
       "      <td>Honnay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>6640</td>\n",
       "      <td>6642</td>\n",
       "      <td>Juseret</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>6666</td>\n",
       "      <td>6997</td>\n",
       "      <td>Mormont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>6681</td>\n",
       "      <td>6680</td>\n",
       "      <td>Sainte-Ode</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>6724</td>\n",
       "      <td>6720</td>\n",
       "      <td>Habay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>6820</td>\n",
       "      <td>4800</td>\n",
       "      <td>Lambermont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>7141</td>\n",
       "      <td>7140</td>\n",
       "      <td>Morlanwelz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>7624</td>\n",
       "      <td>7620</td>\n",
       "      <td>Brunehaut</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>7811</td>\n",
       "      <td>7810</td>\n",
       "      <td>Maffle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>8301</td>\n",
       "      <td>8300</td>\n",
       "      <td>Knokke-Heist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>8620</td>\n",
       "      <td>3700</td>\n",
       "      <td>Sluizen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>8755</td>\n",
       "      <td>9420</td>\n",
       "      <td>Bambrugge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>8952</td>\n",
       "      <td>8950</td>\n",
       "      <td>Heuvelland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>9120</td>\n",
       "      <td>9130</td>\n",
       "      <td>Kallo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>9130</td>\n",
       "      <td>9120</td>\n",
       "      <td>Kallo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>9180</td>\n",
       "      <td>9500</td>\n",
       "      <td>Moerbeke</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>9180</td>\n",
       "      <td>9112</td>\n",
       "      <td>Sinaai-Waas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>9220</td>\n",
       "      <td>1785</td>\n",
       "      <td>Hamme</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>9620</td>\n",
       "      <td>9660</td>\n",
       "      <td>Sint-Maria-Oudenhove</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>9620</td>\n",
       "      <td>9520</td>\n",
       "      <td>Oombergen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>9790</td>\n",
       "      <td>9700</td>\n",
       "      <td>Ooike</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   bnd_zipcode ctr_zipcode               locality\n",
       "0         1130        3700                  Haren\n",
       "1         1541        8600           Driekapellen\n",
       "2         2000        2030              Antwerpen\n",
       "3         2000        2060              Antwerpen\n",
       "4         2000        2018              Antwerpen\n",
       "5         2000        2050              Antwerpen\n",
       "6         2000        2020              Antwerpen\n",
       "7         2000        2040              Antwerpen\n",
       "8         2180        2223                Schriek\n",
       "9         2180        3400                   Laar\n",
       "10        2490        1910                   Berg\n",
       "11        2490        3700                   Berg\n",
       "12        2560        3840                  Voort\n",
       "13        3202        3540                   Donk\n",
       "14        3300        3470  Sint-Margriete-Houtem\n",
       "15        3700        3840                Kolmont\n",
       "16        3770        9660                   Elst\n",
       "17        4000        4020                  Liège\n",
       "18        4120        4480                  Ehein\n",
       "19        4122        4120                 Neupré\n",
       "20        4141        4920              Louveigné\n",
       "21        4400        6831           Noirfontaine\n",
       "22        4852        4850             Plombières\n",
       "23        4910        6661                   Mont\n",
       "24        4910        5530                   Mont\n",
       "25        4910        4800                Polleur\n",
       "26        4960        6834              Bellevaux\n",
       "27        4987        5600               Neuville\n",
       "28        4987        5080             La Bruyère\n",
       "29        4987        4821              Andrimont\n",
       "30        5541        5540               Hastière\n",
       "31        5576        5570                 Honnay\n",
       "32        6640        6642                Juseret\n",
       "33        6666        6997                Mormont\n",
       "34        6681        6680             Sainte-Ode\n",
       "35        6724        6720                  Habay\n",
       "36        6820        4800             Lambermont\n",
       "37        7141        7140             Morlanwelz\n",
       "38        7624        7620              Brunehaut\n",
       "39        7811        7810                 Maffle\n",
       "40        8301        8300           Knokke-Heist\n",
       "41        8620        3700                Sluizen\n",
       "42        8755        9420              Bambrugge\n",
       "43        8952        8950             Heuvelland\n",
       "44        9120        9130                  Kallo\n",
       "45        9130        9120                  Kallo\n",
       "46        9180        9500               Moerbeke\n",
       "47        9180        9112            Sinaai-Waas\n",
       "48        9220        1785                  Hamme\n",
       "49        9620        9660   Sint-Maria-Oudenhove\n",
       "50        9620        9520              Oombergen\n",
       "51        9790        9700                  Ooike"
      ]
     },
     "execution_count": 483,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sjoin_mismatches = get_request(f\"\"\"\n",
    "SELECT bnd.zipcode as bnd_zipcode, ctr.zipcode as ctr_zipcode, locality\n",
    "FROM {pg_schema}.zipcodes_boundaries bnd, {pg_schema}.zipcodes_centers ctr\n",
    "WHERE ST_Contains(bnd.geometry, ctr.geometry)\n",
    "AND   bnd.zipcode != ctr.zipcode\n",
    "ORDER BY bnd.zipcode\n",
    "\"\"\")\n",
    "sjoin_mismatches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "id": "1dbfadb0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:35:07.534111Z",
     "start_time": "2021-06-23T14:35:07.279303Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>st_area</th>\n",
       "      <th>st_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000</td>\n",
       "      <td>1.467467e-03</td>\n",
       "      <td>0.674274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005</td>\n",
       "      <td>2.059788e-07</td>\n",
       "      <td>0.001768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1006</td>\n",
       "      <td>1.366610e-07</td>\n",
       "      <td>0.001785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
       "      <td>1.863360e-07</td>\n",
       "      <td>0.002019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1008</td>\n",
       "      <td>5.448798e-07</td>\n",
       "      <td>0.003302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>9982</td>\n",
       "      <td>1.714060e-03</td>\n",
       "      <td>0.216499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1183</th>\n",
       "      <td>9988</td>\n",
       "      <td>3.844306e-03</td>\n",
       "      <td>0.378281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1184</th>\n",
       "      <td>9990</td>\n",
       "      <td>8.137429e-03</td>\n",
       "      <td>0.566609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>9991</td>\n",
       "      <td>3.352091e-03</td>\n",
       "      <td>0.338254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>9992</td>\n",
       "      <td>8.082315e-04</td>\n",
       "      <td>0.175120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1187 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode       st_area  st_length\n",
       "0       1000  1.467467e-03   0.674274\n",
       "1       1005  2.059788e-07   0.001768\n",
       "2       1006  1.366610e-07   0.001785\n",
       "3       1007  1.863360e-07   0.002019\n",
       "4       1008  5.448798e-07   0.003302\n",
       "...      ...           ...        ...\n",
       "1182    9982  1.714060e-03   0.216499\n",
       "1183    9988  3.844306e-03   0.378281\n",
       "1184    9990  8.137429e-03   0.566609\n",
       "1185    9991  3.352091e-03   0.338254\n",
       "1186    9992  8.082315e-04   0.175120\n",
       "\n",
       "[1187 rows x 3 columns]"
      ]
     },
     "execution_count": 485,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_request(f\"\"\"\n",
    "SELECT zipcode, ST_Area(geometry), ST_Length(ST_Boundary(geometry))\n",
    "FROM {pg_schema}.zipcodes_boundaries bnd\n",
    "\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e106462e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T10:00:29.411452Z",
     "start_time": "2021-06-22T10:00:28.007730Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-28-99aaeb574896>:1: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
      "\n",
      "  zipcodes_boundaries.area\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0       1.467467e-03\n",
       "1       2.059788e-07\n",
       "2       1.366610e-07\n",
       "3       1.863360e-07\n",
       "4       5.448798e-07\n",
       "            ...     \n",
       "1182    1.714060e-03\n",
       "1183    3.844306e-03\n",
       "1184    8.137429e-03\n",
       "1185    3.352091e-03\n",
       "1186    8.082315e-04\n",
       "Length: 1187, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zipcodes_boundaries.area"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "524a101d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T12:31:53.620170Z",
     "start_time": "2021-06-22T12:31:53.616094Z"
    }
   },
   "source": [
    "## Province boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "9836bf66",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:34:43.638866Z",
     "start_time": "2021-06-22T13:34:43.630487Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'epsg:3857'"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 486,
   "id": "bb26e33a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:35:27.092461Z",
     "start_time": "2021-06-23T14:35:24.502503Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>zipcode</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000</td>\n",
       "      <td>MULTIPOLYGON Z (((151026.522 174383.511 -42.83...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1005</td>\n",
       "      <td>POLYGON Z ((148775.482 170463.452 -42.857, 148...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1006</td>\n",
       "      <td>POLYGON Z ((148788.927 170524.548 -42.857, 148...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1007</td>\n",
       "      <td>POLYGON Z ((149939.927 170721.301 -42.865, 149...</td>\n",
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       "      <th>4</th>\n",
       "      <td>1008</td>\n",
       "      <td>POLYGON Z ((149793.162 170723.079 -42.864, 149...</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1182</th>\n",
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       "      <td>POLYGON Z ((94708.930 218639.620 -41.791, 9472...</td>\n",
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       "    <tr>\n",
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       "      <td>POLYGON Z ((85260.390 215211.179 -41.745, 8526...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>9991</td>\n",
       "      <td>POLYGON Z ((89209.935 212664.039 -41.811, 8926...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>9992</td>\n",
       "      <td>POLYGON Z ((81275.299 218673.470 -41.669, 8129...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1187 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     zipcode                                           geometry\n",
       "0       1000  MULTIPOLYGON Z (((151026.522 174383.511 -42.83...\n",
       "1       1005  POLYGON Z ((148775.482 170463.452 -42.857, 148...\n",
       "2       1006  POLYGON Z ((148788.927 170524.548 -42.857, 148...\n",
       "3       1007  POLYGON Z ((149939.927 170721.301 -42.865, 149...\n",
       "4       1008  POLYGON Z ((149793.162 170723.079 -42.864, 149...\n",
       "...      ...                                                ...\n",
       "1182    9982  POLYGON Z ((94708.930 218639.620 -41.791, 9472...\n",
       "1183    9988  POLYGON Z ((97266.682 221166.886 -41.785, 9726...\n",
       "1184    9990  POLYGON Z ((85260.390 215211.179 -41.745, 8526...\n",
       "1185    9991  POLYGON Z ((89209.935 212664.039 -41.811, 8926...\n",
       "1186    9992  POLYGON Z ((81275.299 218673.470 -41.669, 8129...\n",
       "\n",
       "[1187 rows x 2 columns]"
      ]
     },
     "execution_count": 486,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prov = get_geo_request(f\"\"\"\n",
    "SELECT zipcode, ST_Transform(geometry, 31370) as geometry\n",
    "FROM {pg_schema}.zipcodes_boundaries\n",
    "\"\"\")\n",
    "prov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "8bb12a38",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:45:40.646383Z",
     "start_time": "2021-06-22T13:45:07.662619Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>province</th>\n",
       "      <th>geom</th>\n",
       "      <th>prov_area</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ANVERS</td>\n",
       "      <td>MULTIPOLYGON Z (((4.94163 51.45557 0.00000, 4....</td>\n",
       "      <td>2876.169790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BRABANT FLAMAND</td>\n",
       "      <td>POLYGON Z ((4.03636 50.69643 0.00000, 4.03315 ...</td>\n",
       "      <td>2118.372560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BRABANT WALLON</td>\n",
       "      <td>POLYGON Z ((4.17736 50.66342 0.00000, 4.17700 ...</td>\n",
       "      <td>1097.193392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>POLYGON Z ((4.47027 50.78976 0.00000, 4.46491 ...</td>\n",
       "      <td>162.422254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FLANDRE-OCCIDENTALE</td>\n",
       "      <td>POLYGON Z ((3.40308 50.74162 0.00000, 3.40303 ...</td>\n",
       "      <td>3182.506707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>FLANDRE-ORIENTALE</td>\n",
       "      <td>POLYGON Z ((3.67751 50.77070 0.00000, 3.67760 ...</td>\n",
       "      <td>3007.122573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>HAINAUT</td>\n",
       "      <td>MULTIPOLYGON Z (((4.35320 50.85014 0.00000, 4....</td>\n",
       "      <td>3813.106963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LIEGE</td>\n",
       "      <td>POLYGON Z ((5.42193 50.43061 0.00000, 5.42058 ...</td>\n",
       "      <td>3857.181214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>LIMBOURG</td>\n",
       "      <td>MULTIPOLYGON Z (((5.89564 50.74545 0.00000, 5....</td>\n",
       "      <td>2427.453160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>LUXEMBOURG</td>\n",
       "      <td>POLYGON Z ((5.84859 49.59720 0.00000, 5.84877 ...</td>\n",
       "      <td>4459.322510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NAMUR</td>\n",
       "      <td>POLYGON Z ((4.60032 49.98642 0.00000, 4.60025 ...</td>\n",
       "      <td>3674.880647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               province                                               geom  \\\n",
       "0                ANVERS  MULTIPOLYGON Z (((4.94163 51.45557 0.00000, 4....   \n",
       "1       BRABANT FLAMAND  POLYGON Z ((4.03636 50.69643 0.00000, 4.03315 ...   \n",
       "2        BRABANT WALLON  POLYGON Z ((4.17736 50.66342 0.00000, 4.17700 ...   \n",
       "3             BRUXELLES  POLYGON Z ((4.47027 50.78976 0.00000, 4.46491 ...   \n",
       "4   FLANDRE-OCCIDENTALE  POLYGON Z ((3.40308 50.74162 0.00000, 3.40303 ...   \n",
       "5     FLANDRE-ORIENTALE  POLYGON Z ((3.67751 50.77070 0.00000, 3.67760 ...   \n",
       "6               HAINAUT  MULTIPOLYGON Z (((4.35320 50.85014 0.00000, 4....   \n",
       "7                 LIEGE  POLYGON Z ((5.42193 50.43061 0.00000, 5.42058 ...   \n",
       "8              LIMBOURG  MULTIPOLYGON Z (((5.89564 50.74545 0.00000, 5....   \n",
       "9            LUXEMBOURG  POLYGON Z ((5.84859 49.59720 0.00000, 5.84877 ...   \n",
       "10                NAMUR  POLYGON Z ((4.60032 49.98642 0.00000, 4.60025 ...   \n",
       "\n",
       "      prov_area  \n",
       "0   2876.169790  \n",
       "1   2118.372560  \n",
       "2   1097.193392  \n",
       "3    162.422254  \n",
       "4   3182.506707  \n",
       "5   3007.122573  \n",
       "6   3813.106963  \n",
       "7   3857.181214  \n",
       "8   2427.453160  \n",
       "9   4459.322510  \n",
       "10  3674.880647  "
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prov = get_geo_request(f\"\"\"\n",
    "SELECT zp.province, ST_Union(geometry) as geom, \n",
    "    ST_Area(ST_Transform(ST_Union(geometry), 31370))/1000^2 as prov_area\n",
    "    \n",
    "FROM {pg_schema}.zipcodes_boundaries bnd\n",
    "    JOIN {pg_schema}.zipcodes zp \n",
    "    ON bnd.zipcode = zp.zipcode\n",
    "GROUP BY zp.province\n",
    "\"\"\")\n",
    "prov"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "bee3532d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:23:20.895195Z",
     "start_time": "2021-06-22T13:23:16.090630Z"
    }
   },
   "outputs": [],
   "source": [
    "statistical_sectors = gpd.read_file(\"zip://data/stat_sectors_2020.zip/sh_statbel_statistical_sectors_20200101.shp\")\n",
    "statistical_sectors[\"CNIS5_2020\"] = statistical_sectors[\"CNIS5_2020\"].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "72fb065d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:26:13.293383Z",
     "start_time": "2021-06-22T13:25:31.051509Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "prov_nis = statistical_sectors[[\"T_PROVI_FR\", \"geometry\"]].dissolve(\"T_PROVI_FR\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "97968718",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:26:57.203212Z",
     "start_time": "2021-06-22T13:26:55.730755Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>ar</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T_PROVI_FR</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Province de Flandre occidentale</th>\n",
       "      <td>POLYGON Z ((83489.530 159995.491 0.000, 83488....</td>\n",
       "      <td>3196.622714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province de Flandre orientale</th>\n",
       "      <td>POLYGON Z ((98736.032 158867.058 0.000, 98719....</td>\n",
       "      <td>3007.110723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province de Liège</th>\n",
       "      <td>POLYGON Z ((276506.515 96694.991 0.000, 276514...</td>\n",
       "      <td>3857.173434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province de Namur</th>\n",
       "      <td>POLYGON Z ((193240.987 54915.334 0.000, 193226...</td>\n",
       "      <td>3674.826625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province du Brabant flamand</th>\n",
       "      <td>POLYGON Z ((126516.330 154035.693 0.000, 12651...</td>\n",
       "      <td>2118.387343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province du Brabant wallon</th>\n",
       "      <td>POLYGON Z ((150959.609 139257.480 0.000, 15088...</td>\n",
       "      <td>1097.197952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province du Hainaut</th>\n",
       "      <td>MULTIPOLYGON Z (((154103.564 70323.214 0.000, ...</td>\n",
       "      <td>3812.900166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province du Limbourg</th>\n",
       "      <td>MULTIPOLYGON Z (((205615.858 154477.589 0.000,...</td>\n",
       "      <td>2427.449046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province du Luxembourg</th>\n",
       "      <td>POLYGON Z ((234354.943 23041.209 0.000, 234310...</td>\n",
       "      <td>4459.336047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Province d’Anvers</th>\n",
       "      <td>MULTIPOLYGON Z (((158434.326 187398.708 0.000,...</td>\n",
       "      <td>2876.168816</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                          geometry  \\\n",
       "T_PROVI_FR                                                                           \n",
       "Province de Flandre occidentale  POLYGON Z ((83489.530 159995.491 0.000, 83488....   \n",
       "Province de Flandre orientale    POLYGON Z ((98736.032 158867.058 0.000, 98719....   \n",
       "Province de Liège                POLYGON Z ((276506.515 96694.991 0.000, 276514...   \n",
       "Province de Namur                POLYGON Z ((193240.987 54915.334 0.000, 193226...   \n",
       "Province du Brabant flamand      POLYGON Z ((126516.330 154035.693 0.000, 12651...   \n",
       "Province du Brabant wallon       POLYGON Z ((150959.609 139257.480 0.000, 15088...   \n",
       "Province du Hainaut              MULTIPOLYGON Z (((154103.564 70323.214 0.000, ...   \n",
       "Province du Limbourg             MULTIPOLYGON Z (((205615.858 154477.589 0.000,...   \n",
       "Province du Luxembourg           POLYGON Z ((234354.943 23041.209 0.000, 234310...   \n",
       "Province d’Anvers                MULTIPOLYGON Z (((158434.326 187398.708 0.000,...   \n",
       "\n",
       "                                          ar  \n",
       "T_PROVI_FR                                    \n",
       "Province de Flandre occidentale  3196.622714  \n",
       "Province de Flandre orientale    3007.110723  \n",
       "Province de Liège                3857.173434  \n",
       "Province de Namur                3674.826625  \n",
       "Province du Brabant flamand      2118.387343  \n",
       "Province du Brabant wallon       1097.197952  \n",
       "Province du Hainaut              3812.900166  \n",
       "Province du Limbourg             2427.449046  \n",
       "Province du Luxembourg           4459.336047  \n",
       "Province d’Anvers                2876.168816  "
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prov_nis.assign(ar=prov_nis.area/(1000**2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b663c8f9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T13:35:41.384058Z",
     "start_time": "2021-06-22T13:35:41.349249Z"
    }
   },
   "source": [
    "## Commune boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "id": "6f8b70fd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:09:43.478867Z",
     "start_time": "2021-06-23T14:09:41.817260Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>main_commune</th>\n",
       "      <th>geom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AALST</td>\n",
       "      <td>MULTIPOLYGON Z (((3.99584 50.93822 0.00000, 3....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AALTER</td>\n",
       "      <td>MULTIPOLYGON Z (((3.50421 51.07037 0.00000, 3....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AARSCHOT</td>\n",
       "      <td>MULTIPOLYGON Z (((4.90238 50.99611 0.00000, 4....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AARTSELAAR</td>\n",
       "      <td>MULTIPOLYGON Z (((4.40142 51.14983 0.00000, 4....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFFLIGEM</td>\n",
       "      <td>MULTIPOLYGON Z (((4.13900 50.91693 0.00000, 4....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>ZULTE</td>\n",
       "      <td>MULTIPOLYGON Z (((3.52661 50.94769 0.00000, 3....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>577</th>\n",
       "      <td>ZUTENDAAL</td>\n",
       "      <td>MULTIPOLYGON Z (((5.59532 50.97730 0.00000, 5....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>578</th>\n",
       "      <td>ZWALM</td>\n",
       "      <td>MULTIPOLYGON Z (((3.72545 50.91205 0.00000, 3....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>ZWEVEGEM</td>\n",
       "      <td>MULTIPOLYGON Z (((3.39176 50.75286 0.00000, 3....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>580</th>\n",
       "      <td>ZWIJNDRECHT</td>\n",
       "      <td>MULTIPOLYGON Z (((4.32988 51.18561 0.00000, 4....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>581 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    main_commune                                               geom\n",
       "0          AALST  MULTIPOLYGON Z (((3.99584 50.93822 0.00000, 3....\n",
       "1         AALTER  MULTIPOLYGON Z (((3.50421 51.07037 0.00000, 3....\n",
       "2       AARSCHOT  MULTIPOLYGON Z (((4.90238 50.99611 0.00000, 4....\n",
       "3     AARTSELAAR  MULTIPOLYGON Z (((4.40142 51.14983 0.00000, 4....\n",
       "4       AFFLIGEM  MULTIPOLYGON Z (((4.13900 50.91693 0.00000, 4....\n",
       "..           ...                                                ...\n",
       "576        ZULTE  MULTIPOLYGON Z (((3.52661 50.94769 0.00000, 3....\n",
       "577    ZUTENDAAL  MULTIPOLYGON Z (((5.59532 50.97730 0.00000, 5....\n",
       "578        ZWALM  MULTIPOLYGON Z (((3.72545 50.91205 0.00000, 3....\n",
       "579     ZWEVEGEM  MULTIPOLYGON Z (((3.39176 50.75286 0.00000, 3....\n",
       "580  ZWIJNDRECHT  MULTIPOLYGON Z (((4.32988 51.18561 0.00000, 4....\n",
       "\n",
       "[581 rows x 2 columns]"
      ]
     },
     "execution_count": 451,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commune_boundaries = get_geo_request(f\"\"\"\n",
    "SELECT * from {pg_schema}.zip_commune_boundaries_filled\n",
    "\"\"\")\n",
    "commune_boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 452,
   "id": "c2650c6b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:11:24.023709Z",
     "start_time": "2021-06-23T14:10:05.419367Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cnis5_2020</th>\n",
       "      <th>t_mun_fr</th>\n",
       "      <th>main_commune</th>\n",
       "      <th>nis_geom</th>\n",
       "      <th>zip_geom</th>\n",
       "      <th>geom</th>\n",
       "      <th>overlap_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>23002</td>\n",
       "      <td>Asse</td>\n",
       "      <td>AALST</td>\n",
       "      <td>01030000A0E610000001000000D41000000B68248EE2F5...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000070...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.13900 50.91693 0.00000, 4....</td>\n",
       "      <td>2.082180e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23060</td>\n",
       "      <td>Opwijk</td>\n",
       "      <td>AALST</td>\n",
       "      <td>01030000A0E6100000010000002C0C00006EBC1BD2C0B1...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000070...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.16236 50.93238 0.00000, 4....</td>\n",
       "      <td>5.367030e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23105</td>\n",
       "      <td>Affligem</td>\n",
       "      <td>AALST</td>\n",
       "      <td>01030000A0E6100000010000005A0600009D748D540775...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000070...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.07424 50.89940 0.00000, 4....</td>\n",
       "      <td>2.153376e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>41002</td>\n",
       "      <td>Alost</td>\n",
       "      <td>AALST</td>\n",
       "      <td>01030000A0E610000001000000981200008C8EF1323792...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000070...</td>\n",
       "      <td>POLYGON Z ((4.14279 50.92387 0.00000, 4.14275 ...</td>\n",
       "      <td>9.939421e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41011</td>\n",
       "      <td>Denderleeuw</td>\n",
       "      <td>AALST</td>\n",
       "      <td>01030000A0E610000001000000480800003D74A8D45A36...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000070...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.04152 50.90451 0.00000, 4....</td>\n",
       "      <td>8.348838e-05</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3797</th>\n",
       "      <td>34043</td>\n",
       "      <td>Espierres-Helchin</td>\n",
       "      <td>ZWEVEGEM</td>\n",
       "      <td>01030000A0E6100000010000007A050000A109BF1663DF...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000006...</td>\n",
       "      <td>MULTIPOLYGON Z (((3.35986 50.73748 0.00000, 3....</td>\n",
       "      <td>9.206079e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3798</th>\n",
       "      <td>11002</td>\n",
       "      <td>Anvers</td>\n",
       "      <td>ZWIJNDRECHT</td>\n",
       "      <td>01030000A0E610000001000000D8160000C572B9609E6C...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000EB...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.35607 51.20341 0.00000, 4....</td>\n",
       "      <td>1.526778e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3799</th>\n",
       "      <td>11056</td>\n",
       "      <td>Zwijndrecht</td>\n",
       "      <td>ZWIJNDRECHT</td>\n",
       "      <td>01030000A0E61000000100000084020000BAE752DADE4C...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000EB...</td>\n",
       "      <td>POLYGON Z ((4.32507 51.18663 0.00000, 4.32501 ...</td>\n",
       "      <td>9.999781e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>46003</td>\n",
       "      <td>Beveren</td>\n",
       "      <td>ZWIJNDRECHT</td>\n",
       "      <td>01030000A0E610000001000000530800003FF65CDB94D8...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000EB...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.29132 51.25214 0.00000, 4....</td>\n",
       "      <td>5.230534e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3801</th>\n",
       "      <td>46013</td>\n",
       "      <td>Kruibeke</td>\n",
       "      <td>ZWIJNDRECHT</td>\n",
       "      <td>01030000A0E6100000010000006E0600006598E4FC4B3A...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000EB...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.31977 51.19676 0.00000, 4....</td>\n",
       "      <td>1.334699e-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3802 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     cnis5_2020           t_mun_fr main_commune  \\\n",
       "0         23002               Asse        AALST   \n",
       "1         23060             Opwijk        AALST   \n",
       "2         23105           Affligem        AALST   \n",
       "3         41002              Alost        AALST   \n",
       "4         41011        Denderleeuw        AALST   \n",
       "...         ...                ...          ...   \n",
       "3797      34043  Espierres-Helchin     ZWEVEGEM   \n",
       "3798      11002             Anvers  ZWIJNDRECHT   \n",
       "3799      11056        Zwijndrecht  ZWIJNDRECHT   \n",
       "3800      46003            Beveren  ZWIJNDRECHT   \n",
       "3801      46013           Kruibeke  ZWIJNDRECHT   \n",
       "\n",
       "                                               nis_geom  \\\n",
       "0     01030000A0E610000001000000D41000000B68248EE2F5...   \n",
       "1     01030000A0E6100000010000002C0C00006EBC1BD2C0B1...   \n",
       "2     01030000A0E6100000010000005A0600009D748D540775...   \n",
       "3     01030000A0E610000001000000981200008C8EF1323792...   \n",
       "4     01030000A0E610000001000000480800003D74A8D45A36...   \n",
       "...                                                 ...   \n",
       "3797  01030000A0E6100000010000007A050000A109BF1663DF...   \n",
       "3798  01030000A0E610000001000000D8160000C572B9609E6C...   \n",
       "3799  01030000A0E61000000100000084020000BAE752DADE4C...   \n",
       "3800  01030000A0E610000001000000530800003FF65CDB94D8...   \n",
       "3801  01030000A0E6100000010000006E0600006598E4FC4B3A...   \n",
       "\n",
       "                                               zip_geom  \\\n",
       "0     01060000A0E61000000100000001030000800100000070...   \n",
       "1     01060000A0E61000000100000001030000800100000070...   \n",
       "2     01060000A0E61000000100000001030000800100000070...   \n",
       "3     01060000A0E61000000100000001030000800100000070...   \n",
       "4     01060000A0E61000000100000001030000800100000070...   \n",
       "...                                                 ...   \n",
       "3797  01060000A0E61000000100000001030000800100000006...   \n",
       "3798  01060000A0E610000001000000010300008001000000EB...   \n",
       "3799  01060000A0E610000001000000010300008001000000EB...   \n",
       "3800  01060000A0E610000001000000010300008001000000EB...   \n",
       "3801  01060000A0E610000001000000010300008001000000EB...   \n",
       "\n",
       "                                                   geom  overlap_ratio  \n",
       "0     MULTIPOLYGON Z (((4.13900 50.91693 0.00000, 4....   2.082180e-06  \n",
       "1     MULTIPOLYGON Z (((4.16236 50.93238 0.00000, 4....   5.367030e-06  \n",
       "2     MULTIPOLYGON Z (((4.07424 50.89940 0.00000, 4....   2.153376e-05  \n",
       "3     POLYGON Z ((4.14279 50.92387 0.00000, 4.14275 ...   9.939421e-01  \n",
       "4     MULTIPOLYGON Z (((4.04152 50.90451 0.00000, 4....   8.348838e-05  \n",
       "...                                                 ...            ...  \n",
       "3797  MULTIPOLYGON Z (((3.35986 50.73748 0.00000, 3....   9.206079e-06  \n",
       "3798  MULTIPOLYGON Z (((4.35607 51.20341 0.00000, 4....   1.526778e-06  \n",
       "3799  POLYGON Z ((4.32507 51.18663 0.00000, 4.32501 ...   9.999781e-01  \n",
       "3800  MULTIPOLYGON Z (((4.29132 51.25214 0.00000, 4....   5.230534e-07  \n",
       "3801  MULTIPOLYGON Z (((4.31977 51.19676 0.00000, 4....   1.334699e-06  \n",
       "\n",
       "[3802 rows x 7 columns]"
      ]
     },
     "execution_count": 452,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overlaps = get_geo_request(f\"\"\"\n",
    "SELECT cnis5_2020, t_mun_fr, main_commune, \n",
    "    nis_bnd.geom as nis_geom,\n",
    "    zip_bnd.geom as zip_geom,\n",
    "    ST_Intersection(nis_bnd.geom, zip_bnd.geom) as geom,\n",
    "    ST_Area(ST_Intersection(nis_bnd.geom, zip_bnd.geom)) / ST_Area(nis_bnd.geom) as overlap_ratio\n",
    "    \n",
    "FROM {pg_schema}.nis_boundaries nis_bnd\n",
    "JOIN {pg_schema}.zip_commune_boundaries_filled zip_bnd\n",
    "ON ST_Intersects(nis_bnd.geom, zip_bnd.geom)\n",
    "\n",
    "\"\"\")\n",
    "overlaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "a7df4fec",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-22T15:04:08.669091Z",
     "start_time": "2021-06-22T15:04:08.428397Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 261,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "overlaps.overlap_ratio.hist(bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "id": "559212e5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:14:47.731014Z",
     "start_time": "2021-06-23T14:13:27.385517Z"
    }
   },
   "outputs": [],
   "source": [
    "overlaps2 = get_geo_request(f\"\"\"\n",
    "SELECT cnis5_2020, t_mun_fr, main_commune, \n",
    "    nis_bnd.geom as nis_geom,\n",
    "    zip_bnd.geom as zip_geom,\n",
    "    ST_Difference(nis_bnd.geom, zip_bnd.geom) as only_nis_geom,\n",
    "    ST_Difference(zip_bnd.geom, nis_bnd.geom) as only_zip_geom,\n",
    "    ST_Intersection(nis_bnd.geom, zip_bnd.geom) as geom,\n",
    "    ST_Area(ST_Intersection(nis_bnd.geom, zip_bnd.geom)) / ST_Area(nis_bnd.geom) as overlap_ratio\n",
    "    \n",
    "FROM {pg_schema}.nis_boundaries nis_bnd\n",
    "JOIN {pg_schema}.zip_commune_boundaries_filled zip_bnd\n",
    "ON ST_Intersects(nis_bnd.geom, zip_bnd.geom) AND \n",
    "   ST_Area(ST_Intersection(nis_bnd.geom, zip_bnd.geom)) / ST_Area(nis_bnd.geom) > 0.5 \n",
    "\n",
    "\"\"\")\n",
    "\n",
    "# Convert geometry columns\n",
    "overlaps2.nis_geom =      overlaps2.nis_geom.apply(     shapely.wkb.loads, hex=True)\n",
    "overlaps2.zip_geom =      overlaps2.zip_geom.apply(     shapely.wkb.loads, hex=True)\n",
    "overlaps2.only_nis_geom = overlaps2.only_nis_geom.apply(shapely.wkb.loads, hex=True)\n",
    "overlaps2.only_zip_geom = overlaps2.only_zip_geom.apply(shapely.wkb.loads, hex=True)\n",
    "\n",
    "overlaps2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "id": "e508ef64",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:15:24.988123Z",
     "start_time": "2021-06-23T14:15:24.807826Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 454,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "overlaps2.overlap_ratio.hist(bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 457,
   "id": "11ab1654",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:16:04.587871Z",
     "start_time": "2021-06-23T14:16:04.311580Z"
    },
    "scrolled": true
   },
   "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>cnis5_2020</th>\n",
       "      <th>t_mun_fr</th>\n",
       "      <th>main_commune</th>\n",
       "      <th>nis_geom</th>\n",
       "      <th>zip_geom</th>\n",
       "      <th>only_nis_geom</th>\n",
       "      <th>only_zip_geom</th>\n",
       "      <th>geom</th>\n",
       "      <th>overlap_ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>35029</td>\n",
       "      <td>De Haan</td>\n",
       "      <td>DE HAAN</td>\n",
       "      <td>01030000A0E61000000100000002060000DB122286B17C...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000045...</td>\n",
       "      <td>01060000A0E61000007D00000001030000800100000004...</td>\n",
       "      <td>01060000A0E61000007D00000001030000800100000076...</td>\n",
       "      <td>POLYGON Z ((3.06089 51.23242 0.00000, 3.06079 ...</td>\n",
       "      <td>0.910084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>31043</td>\n",
       "      <td>Knokke-Heist</td>\n",
       "      <td>KNOKKE-HEIST</td>\n",
       "      <td>01030000A0E610000001000000E70200001D7A82782242...</td>\n",
       "      <td>01060000A0E6100000010000000103000080010000007B...</td>\n",
       "      <td>01060000A0E61000001E00000001030000800100000019...</td>\n",
       "      <td>01060000A0E61000001E00000001030000800100000007...</td>\n",
       "      <td>POLYGON Z ((3.27612 51.30119 0.00000, 3.27534 ...</td>\n",
       "      <td>0.917736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>21004</td>\n",
       "      <td>Bruxelles</td>\n",
       "      <td>BRUXELLES</td>\n",
       "      <td>01030000A0E610000001000000B20C00006AC51F94E885...</td>\n",
       "      <td>01060000A0E61000000600000001030000800100000015...</td>\n",
       "      <td>01060000A0E6100000D8000000010300008001000000F9...</td>\n",
       "      <td>01060000A0E6100000DC00000001030000800100000037...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.38068 50.83864 0.00000, 4....</td>\n",
       "      <td>0.937348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>13002</td>\n",
       "      <td>Baerle-Duc</td>\n",
       "      <td>BAARLE-HERTOG</td>\n",
       "      <td>01060000A0E61000001A00000001030000800100000020...</td>\n",
       "      <td>01060000A0E61000001700000001030000800100000053...</td>\n",
       "      <td>01060000A0E6100000DB00000001030000800100000020...</td>\n",
       "      <td>01060000A0E6100000E000000001030000800100000010...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.93579 51.40930 0.00000, 4....</td>\n",
       "      <td>0.942526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>23088</td>\n",
       "      <td>Vilvorde</td>\n",
       "      <td>VILVOORDE</td>\n",
       "      <td>01030000A0E610000001000000C1090000C994A61B9BB7...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000C2...</td>\n",
       "      <td>01060000A0E61000008800000001030000800100000007...</td>\n",
       "      <td>01060000A0E61000008800000001030000800100000013...</td>\n",
       "      <td>POLYGON Z ((4.42930 50.92045 0.00000, 4.42702 ...</td>\n",
       "      <td>0.952227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>35011</td>\n",
       "      <td>Middelkerke</td>\n",
       "      <td>MIDDELKERKE</td>\n",
       "      <td>01030000A0E6100000010000008909000058DC49A5A21D...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000AF...</td>\n",
       "      <td>01060000A0E6100000B50000000103000080010000000E...</td>\n",
       "      <td>01060000A0E6100000B500000001030000800100000005...</td>\n",
       "      <td>POLYGON Z ((2.76342 51.13898 0.00000, 2.76296 ...</td>\n",
       "      <td>0.959975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>23098</td>\n",
       "      <td>Drogenbos</td>\n",
       "      <td>DROGENBOS</td>\n",
       "      <td>01030000A0E61000000100000039040000554BAE8DC546...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000B3...</td>\n",
       "      <td>01060000A0E61000005D00000001030000800100000008...</td>\n",
       "      <td>01060000A0E61000005D0000000103000080010000005D...</td>\n",
       "      <td>POLYGON Z ((4.31911 50.77989 0.00000, 4.31371 ...</td>\n",
       "      <td>0.961104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345</th>\n",
       "      <td>23047</td>\n",
       "      <td>Machelen</td>\n",
       "      <td>MACHELEN</td>\n",
       "      <td>01030000A0E61000000100000052020000AA8B37B78AD3...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000A3...</td>\n",
       "      <td>01060000A0E61000003400000001030000800100000007...</td>\n",
       "      <td>01060000A0E61000003400000001030000800100000005...</td>\n",
       "      <td>POLYGON Z ((4.45658 50.88892 0.00000, 4.45632 ...</td>\n",
       "      <td>0.967020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>25068</td>\n",
       "      <td>Mont-Saint-Guibert</td>\n",
       "      <td>MONT-SAINT-GUIBERT</td>\n",
       "      <td>01030000A0E61000000100000065050000B272269D2388...</td>\n",
       "      <td>01060000A0E61000000200000001030000800100000062...</td>\n",
       "      <td>01060000A0E61000007500000001030000800100000015...</td>\n",
       "      <td>01060000A0E61000007600000001030000800100000004...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.63315 50.63093 0.00000, 4....</td>\n",
       "      <td>0.976050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>56086</td>\n",
       "      <td>Ham-sur-Heure-Nalinnes</td>\n",
       "      <td>HAM-SUR-HEURE</td>\n",
       "      <td>01030000A0E610000001000000C2080000433EBD436E90...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000C2...</td>\n",
       "      <td>01060000A0E6100000A200000001030000800100000008...</td>\n",
       "      <td>01060000A0E6100000A200000001030000800100000048...</td>\n",
       "      <td>POLYGON Z ((4.39092 50.29246 0.00000, 4.39090 ...</td>\n",
       "      <td>0.981030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>91142</td>\n",
       "      <td>Hastière</td>\n",
       "      <td>HASTIÈRE</td>\n",
       "      <td>01030000A0E6100000010000009B0800005B38C049A97C...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000EE...</td>\n",
       "      <td>01060000A0E6100000C30000000103000080010000000B...</td>\n",
       "      <td>01060000A0E6100000C300000001030000800100000048...</td>\n",
       "      <td>POLYGON Z ((4.87174 50.15364 0.00000, 4.87167 ...</td>\n",
       "      <td>0.983296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>23096</td>\n",
       "      <td>Zemst</td>\n",
       "      <td>ZEMST</td>\n",
       "      <td>01030000A0E610000001000000CE0B0000925CC420BA0D...</td>\n",
       "      <td>01060000A0E61000000200000001030000800100000020...</td>\n",
       "      <td>01060000A0E6100000F700000001030000800100000018...</td>\n",
       "      <td>01060000A0E6100000F800000001030000800100000006...</td>\n",
       "      <td>MULTIPOLYGON Z (((4.51406 50.97949 0.00000, 4....</td>\n",
       "      <td>0.986310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>31005</td>\n",
       "      <td>Bruges</td>\n",
       "      <td>BRUGGE</td>\n",
       "      <td>01030000A0E610000001000000670B0000B6997E37C8F7...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000D7...</td>\n",
       "      <td>01060000A0E61000000301000001030000800100000006...</td>\n",
       "      <td>01060000A0E61000000301000001030000800100000009...</td>\n",
       "      <td>POLYGON Z ((3.24599 51.18533 0.00000, 3.24596 ...</td>\n",
       "      <td>0.986770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>572</th>\n",
       "      <td>33037</td>\n",
       "      <td>Zonnebeke</td>\n",
       "      <td>ZONNEBEKE</td>\n",
       "      <td>01030000A0E610000001000000AE0D0000283057EFB0FD...</td>\n",
       "      <td>01060000A0E6100000010000000103000080010000001E...</td>\n",
       "      <td>01060000A0E61000002E01000001030000800100000034...</td>\n",
       "      <td>01060000A0E61000002E01000001030000800100000014...</td>\n",
       "      <td>POLYGON Z ((2.99939 50.81591 0.00000, 2.99938 ...</td>\n",
       "      <td>0.987621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>52011</td>\n",
       "      <td>Charleroi</td>\n",
       "      <td>CHARLEROI</td>\n",
       "      <td>01030000A0E610000001000000310800009FA3814DA6F0...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000B9...</td>\n",
       "      <td>01060000A0E6100000C000000001030000800100000005...</td>\n",
       "      <td>01060000A0E6100000C00000000103000080010000000E...</td>\n",
       "      <td>POLYGON Z ((4.48501 50.37882 0.00000, 4.48495 ...</td>\n",
       "      <td>0.987639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>HOTTON</td>\n",
       "      <td>01030000A0E610000001000000010B0000EB09268F1295...</td>\n",
       "      <td>01060000A0E6100000010000000103000080010000008D...</td>\n",
       "      <td>01060000A0E6100000030100000103000080010000007C...</td>\n",
       "      <td>01060000A0E61000000301000001030000800100000007...</td>\n",
       "      <td>POLYGON Z ((5.39558 50.24181 0.00000, 5.39558 ...</td>\n",
       "      <td>0.987869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>541</th>\n",
       "      <td>25110</td>\n",
       "      <td>Waterloo</td>\n",
       "      <td>WATERLOO</td>\n",
       "      <td>01030000A0E610000001000000E9030000F837D4FF3585...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000091...</td>\n",
       "      <td>01060000A0E61000005400000001030000800100000004...</td>\n",
       "      <td>01060000A0E61000005400000001030000800100000007...</td>\n",
       "      <td>POLYGON Z ((4.38009 50.70478 0.00000, 4.37983 ...</td>\n",
       "      <td>0.987917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>53053</td>\n",
       "      <td>Mons</td>\n",
       "      <td>MONS</td>\n",
       "      <td>01030000A0E61000000100000066040000F4059494CBC0...</td>\n",
       "      <td>01060000A0E6100000010000000103000080010000002E...</td>\n",
       "      <td>01060000A0E61000006800000001030000800100000013...</td>\n",
       "      <td>01060000A0E61000006800000001030000800100000005...</td>\n",
       "      <td>POLYGON Z ((3.96914 50.39137 0.00000, 3.96879 ...</td>\n",
       "      <td>0.989514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>57093</td>\n",
       "      <td>Brunehaut</td>\n",
       "      <td>BRUNEHAUT</td>\n",
       "      <td>01030000A0E610000001000000CD07000087D9B11DC06D...</td>\n",
       "      <td>01060000A0E61000000100000001030000800100000035...</td>\n",
       "      <td>01060000A0E6100000A500000001030000800100000004...</td>\n",
       "      <td>01060000A0E6100000A50000000103000080010000000B...</td>\n",
       "      <td>POLYGON Z ((3.42859 50.50468 0.00000, 3.42843 ...</td>\n",
       "      <td>0.989773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>23023</td>\n",
       "      <td>Gammerages</td>\n",
       "      <td>GALMAARDEN</td>\n",
       "      <td>01030000A0E610000001000000701100005C9D5ED00E07...</td>\n",
       "      <td>01060000A0E610000001000000010300008001000000C7...</td>\n",
       "      <td>01060000A0E61000006901000001030000800100000010...</td>\n",
       "      <td>01060000A0E61000006901000001030000800100000012...</td>\n",
       "      <td>POLYGON Z ((4.00689 50.72922 0.00000, 4.00687 ...</td>\n",
       "      <td>0.989833</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cnis5_2020                t_mun_fr        main_commune  \\\n",
       "119      35029                 De Haan             DE HAAN   \n",
       "280      31043            Knokke-Heist        KNOKKE-HEIST   \n",
       "89       21004               Bruxelles           BRUXELLES   \n",
       "34       13002              Baerle-Duc       BAARLE-HERTOG   \n",
       "524      23088                Vilvorde           VILVOORDE   \n",
       "368      35011             Middelkerke         MIDDELKERKE   \n",
       "138      23098               Drogenbos           DROGENBOS   \n",
       "345      23047                Machelen            MACHELEN   \n",
       "377      25068      Mont-Saint-Guibert  MONT-SAINT-GUIBERT   \n",
       "214      56086  Ham-sur-Heure-Nalinnes       HAM-SUR-HEURE   \n",
       "218      91142                Hastière            HASTIÈRE   \n",
       "569      23096                   Zemst               ZEMST   \n",
       "87       31005                  Bruges              BRUGGE   \n",
       "572      33037               Zonnebeke           ZONNEBEKE   \n",
       "98       52011               Charleroi           CHARLEROI   \n",
       "248      83028                  Hotton              HOTTON   \n",
       "541      25110                Waterloo            WATERLOO   \n",
       "374      53053                    Mons                MONS   \n",
       "88       57093               Brunehaut           BRUNEHAUT   \n",
       "181      23023              Gammerages          GALMAARDEN   \n",
       "\n",
       "                                              nis_geom  \\\n",
       "119  01030000A0E61000000100000002060000DB122286B17C...   \n",
       "280  01030000A0E610000001000000E70200001D7A82782242...   \n",
       "89   01030000A0E610000001000000B20C00006AC51F94E885...   \n",
       "34   01060000A0E61000001A00000001030000800100000020...   \n",
       "524  01030000A0E610000001000000C1090000C994A61B9BB7...   \n",
       "368  01030000A0E6100000010000008909000058DC49A5A21D...   \n",
       "138  01030000A0E61000000100000039040000554BAE8DC546...   \n",
       "345  01030000A0E61000000100000052020000AA8B37B78AD3...   \n",
       "377  01030000A0E61000000100000065050000B272269D2388...   \n",
       "214  01030000A0E610000001000000C2080000433EBD436E90...   \n",
       "218  01030000A0E6100000010000009B0800005B38C049A97C...   \n",
       "569  01030000A0E610000001000000CE0B0000925CC420BA0D...   \n",
       "87   01030000A0E610000001000000670B0000B6997E37C8F7...   \n",
       "572  01030000A0E610000001000000AE0D0000283057EFB0FD...   \n",
       "98   01030000A0E610000001000000310800009FA3814DA6F0...   \n",
       "248  01030000A0E610000001000000010B0000EB09268F1295...   \n",
       "541  01030000A0E610000001000000E9030000F837D4FF3585...   \n",
       "374  01030000A0E61000000100000066040000F4059494CBC0...   \n",
       "88   01030000A0E610000001000000CD07000087D9B11DC06D...   \n",
       "181  01030000A0E610000001000000701100005C9D5ED00E07...   \n",
       "\n",
       "                                              zip_geom  \\\n",
       "119  01060000A0E61000000100000001030000800100000045...   \n",
       "280  01060000A0E6100000010000000103000080010000007B...   \n",
       "89   01060000A0E61000000600000001030000800100000015...   \n",
       "34   01060000A0E61000001700000001030000800100000053...   \n",
       "524  01060000A0E610000001000000010300008001000000C2...   \n",
       "368  01060000A0E610000001000000010300008001000000AF...   \n",
       "138  01060000A0E610000001000000010300008001000000B3...   \n",
       "345  01060000A0E610000001000000010300008001000000A3...   \n",
       "377  01060000A0E61000000200000001030000800100000062...   \n",
       "214  01060000A0E610000001000000010300008001000000C2...   \n",
       "218  01060000A0E610000001000000010300008001000000EE...   \n",
       "569  01060000A0E61000000200000001030000800100000020...   \n",
       "87   01060000A0E610000001000000010300008001000000D7...   \n",
       "572  01060000A0E6100000010000000103000080010000001E...   \n",
       "98   01060000A0E610000001000000010300008001000000B9...   \n",
       "248  01060000A0E6100000010000000103000080010000008D...   \n",
       "541  01060000A0E61000000100000001030000800100000091...   \n",
       "374  01060000A0E6100000010000000103000080010000002E...   \n",
       "88   01060000A0E61000000100000001030000800100000035...   \n",
       "181  01060000A0E610000001000000010300008001000000C7...   \n",
       "\n",
       "                                         only_nis_geom  \\\n",
       "119  01060000A0E61000007D00000001030000800100000004...   \n",
       "280  01060000A0E61000001E00000001030000800100000019...   \n",
       "89   01060000A0E6100000D8000000010300008001000000F9...   \n",
       "34   01060000A0E6100000DB00000001030000800100000020...   \n",
       "524  01060000A0E61000008800000001030000800100000007...   \n",
       "368  01060000A0E6100000B50000000103000080010000000E...   \n",
       "138  01060000A0E61000005D00000001030000800100000008...   \n",
       "345  01060000A0E61000003400000001030000800100000007...   \n",
       "377  01060000A0E61000007500000001030000800100000015...   \n",
       "214  01060000A0E6100000A200000001030000800100000008...   \n",
       "218  01060000A0E6100000C30000000103000080010000000B...   \n",
       "569  01060000A0E6100000F700000001030000800100000018...   \n",
       "87   01060000A0E61000000301000001030000800100000006...   \n",
       "572  01060000A0E61000002E01000001030000800100000034...   \n",
       "98   01060000A0E6100000C000000001030000800100000005...   \n",
       "248  01060000A0E6100000030100000103000080010000007C...   \n",
       "541  01060000A0E61000005400000001030000800100000004...   \n",
       "374  01060000A0E61000006800000001030000800100000013...   \n",
       "88   01060000A0E6100000A500000001030000800100000004...   \n",
       "181  01060000A0E61000006901000001030000800100000010...   \n",
       "\n",
       "                                         only_zip_geom  \\\n",
       "119  01060000A0E61000007D00000001030000800100000076...   \n",
       "280  01060000A0E61000001E00000001030000800100000007...   \n",
       "89   01060000A0E6100000DC00000001030000800100000037...   \n",
       "34   01060000A0E6100000E000000001030000800100000010...   \n",
       "524  01060000A0E61000008800000001030000800100000013...   \n",
       "368  01060000A0E6100000B500000001030000800100000005...   \n",
       "138  01060000A0E61000005D0000000103000080010000005D...   \n",
       "345  01060000A0E61000003400000001030000800100000005...   \n",
       "377  01060000A0E61000007600000001030000800100000004...   \n",
       "214  01060000A0E6100000A200000001030000800100000048...   \n",
       "218  01060000A0E6100000C300000001030000800100000048...   \n",
       "569  01060000A0E6100000F800000001030000800100000006...   \n",
       "87   01060000A0E61000000301000001030000800100000009...   \n",
       "572  01060000A0E61000002E01000001030000800100000014...   \n",
       "98   01060000A0E6100000C00000000103000080010000000E...   \n",
       "248  01060000A0E61000000301000001030000800100000007...   \n",
       "541  01060000A0E61000005400000001030000800100000007...   \n",
       "374  01060000A0E61000006800000001030000800100000005...   \n",
       "88   01060000A0E6100000A50000000103000080010000000B...   \n",
       "181  01060000A0E61000006901000001030000800100000012...   \n",
       "\n",
       "                                                  geom  overlap_ratio  \n",
       "119  POLYGON Z ((3.06089 51.23242 0.00000, 3.06079 ...       0.910084  \n",
       "280  POLYGON Z ((3.27612 51.30119 0.00000, 3.27534 ...       0.917736  \n",
       "89   MULTIPOLYGON Z (((4.38068 50.83864 0.00000, 4....       0.937348  \n",
       "34   MULTIPOLYGON Z (((4.93579 51.40930 0.00000, 4....       0.942526  \n",
       "524  POLYGON Z ((4.42930 50.92045 0.00000, 4.42702 ...       0.952227  \n",
       "368  POLYGON Z ((2.76342 51.13898 0.00000, 2.76296 ...       0.959975  \n",
       "138  POLYGON Z ((4.31911 50.77989 0.00000, 4.31371 ...       0.961104  \n",
       "345  POLYGON Z ((4.45658 50.88892 0.00000, 4.45632 ...       0.967020  \n",
       "377  MULTIPOLYGON Z (((4.63315 50.63093 0.00000, 4....       0.976050  \n",
       "214  POLYGON Z ((4.39092 50.29246 0.00000, 4.39090 ...       0.981030  \n",
       "218  POLYGON Z ((4.87174 50.15364 0.00000, 4.87167 ...       0.983296  \n",
       "569  MULTIPOLYGON Z (((4.51406 50.97949 0.00000, 4....       0.986310  \n",
       "87   POLYGON Z ((3.24599 51.18533 0.00000, 3.24596 ...       0.986770  \n",
       "572  POLYGON Z ((2.99939 50.81591 0.00000, 2.99938 ...       0.987621  \n",
       "98   POLYGON Z ((4.48501 50.37882 0.00000, 4.48495 ...       0.987639  \n",
       "248  POLYGON Z ((5.39558 50.24181 0.00000, 5.39558 ...       0.987869  \n",
       "541  POLYGON Z ((4.38009 50.70478 0.00000, 4.37983 ...       0.987917  \n",
       "374  POLYGON Z ((3.96914 50.39137 0.00000, 3.96879 ...       0.989514  \n",
       "88   POLYGON Z ((3.42859 50.50468 0.00000, 3.42843 ...       0.989773  \n",
       "181  POLYGON Z ((4.00689 50.72922 0.00000, 4.00687 ...       0.989833  "
      ]
     },
     "execution_count": 457,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overlaps2.sort_values(\"overlap_ratio\").iloc[0:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "id": "5c13e3ad",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:17:06.519854Z",
     "start_time": "2021-06-23T14:17:03.558057Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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elgFPAmO3mMMYtO2Yphm5xa40C4ua3XsWEdnPZGzY2GhYWV5nZWWVixcvY4yhqiqWlvawa88uRFbZvXsRrb0WgJwwSnx3uO5nhET/FZHbtm6slRbHiKl8AyZ6HvqhVKrTGBMBrwf44b05oQ002o9b4IbDuHTG0LUdIsLaZIa5Qcfe+TpK/r4HkZu2Wfvjdhd3r/HXghAtCIu7Bjz91GXWVifsPzDLnj1DtFZunYkgSjEoF7l4oePZZ09w5Mghbrx5L019EWNbTDdi9+4Fjh8/RVMrBA20AXYi8XaNyySZOAY2a1v6vfWMrsHQmo7GNDSdY6KatqU1LY3p3PgY49aQdfsoj7OXyRV+fOh9J1sHWInMUl/ys6AUASt7wJvd0pPdfB05HQ5EVol4xlh6Co1p4TSMTXjflnWUfc6Z6HQ9v2+r1HZV0PbrJaz1tGfA2owhyaTT/N1Z8OZeG5JwsLUNYb/k+3Jrff5zRkOtMRhj0UXQQiq00g68RHlQtnTWUuoBuweHePqpUywd2MeGvURTrsLmEDMqsdXEL4m0gHLF4HbjZgPlLFv0YgetphtXjC5amnJEWQ1QQ+i6hs40nsInbW2Yu+kxjN8js27iHAtO4FOescz3NPl4ewYXz4CJlfh7LtVbY+k6gzWgCpVJ41mxaY2bzvRouPKMAgZm5obML84xHDqmQStNoTWVLqh0SalKCuUYgUJfG9ZfjKR/My4wyX/0R94eBL7FxxrPy+u8l/wZ4O9al2LyKC4QRiingNds846vBd6dfb9JRD6OC6bxT6y1vzv9gLjUnl8PcPjwfpRyauzAQYlxwxu5Wxw4W2sxSE/y7zoDAzdpgYvtmhZdaKxxqm0MlGVBWZWUZeFAK3B4QSJUikIKD8bKMQ0qEZmuq7hyZYXrrz9K0667epRQFNotKCsYDF3jaiyUchJZBo4GR8gDoVBKohQcSgDWnHiE69DSmoa62UQrjSoK9uwbsG9pAVhitNmyvl6ztrrJ+fOXOH36eay1bKwfZGF+EdSYrtuI4L+VUw9g7wYnaEy6uKBBa+37YrzUkbQGpdZem6B6jI8xdgvRC9fDZ8l2qCUjqgGY/LgEjY1Sis5oLm9UXLdvjJYOE4hvIIIC+Gth3BVu7q1xc2Ns2qzGwpXLYy5dGgHCvqUZ9u2bQcQxb2Feq3KO1dWCT33qcfYt7eWWW/fTdlcwtnXSRzthz94lPvWpCaNRx2BGY03jx8H2QDJKub7dJnBPJOnTYqNmqzUdrW1puo62a9x3D/yt/+uMcSpFwe8TsonOx3sKlHuf3djF9kliqJKGgB6jFaQoT649iId+BSJscXRWPHgHZiyh+xTe9/ZprkGzFpTOSLGkac/72Lshq6MPrvnvdptnMubM5tox6TU0542mgTGtfdt7h/FMzzY938IcbMeURBCW2EKnzVQOYEov5Re6QCuFFk1nO5pW2LNwmLVLY6yFhb1Djq88idUdam6MWR+iqw60o0e9+We679PFz5hYKFt0ZWFDMVkX5vZaWjPB2I7OtJl03V+BPU2O5MwqtE0bNQKhTVH4sDYbpymmAclmye9/klk3vlMcJpSlpih1ZMpzjVDsqc3HH4rSmV6rQYm1lqJwdSjlMMrNSUmhHOhXuqTUJaUutuDBdHkxoF8Ar8CFs/2wiHwP8A+A/z275w+AG6y16yLyZtw5+Nu29Mz3L/8iIv8YF+XsXf7SWeB6a+0lEXklLovWPf7cfarEpfb89wB333OrbVsnuSvlOFNj3IZSIrRd5yRwlUmHytm1HanoKLSKANS0XiXdeRVn51TwulBUg4pCu+csFikLJ7l6ZqFAJ04tcJTGIrpkfdVtjN2750CP0cUQsElt64em8yaKxq/iQrs6A1fqNqKKm9KNI0DiNN190tMeAB7oTFxgXdcABmM2aNqOtjFYsRw4tMCx625j+cqIM2fO8/RTz3H61JDrrjvM4SN7qdsrWK9KmyaMfXVoIq65ei9Xl4oEk0Hog2MewnJJKro+BQzMhNaBi3Z28iipGw8Onq4YY2mbFmuh9IzW5Y0KY2B+0MS+BNIZ7Nq+FVhrENEJQP1ODetqc7Ph3LkNmqbjwMF5lpdV0rj4Prj1WVFP5nj00ceZm5vj9juOYuwKpmsi4epMy3CoqaqK1dUNDs5VWDuOxMgRK4ngEcfZ/9sDRgydDYDeUncNbddGsG9N68bSGjrrtQPWeqlHbSHMPelzGuT7KBuvOckwaImITEAYF9MZr7pP0joSmFtXiVK+y8bVZyBbG/Gt8T9Rxe8B35pMGjO5D0/WLxtZxinA7fcz0eekIreAEhul9gSyHpBCW40b26D1ATKt4ta9su37s7Yb0zeJ9KYjk3gjmE9rDwKvFEwn7sFIS52Er6mKkko505sohTKCKjV7qsM8euYZ9h/cx2pznvFk043PoEPqDrsxRO0aERmaIPGKXHMtJVh1/+noUMNNpIHNFc1wj8LSYUyLsR3Ork+2fwMzE1jIAMrut6Z2yReVUlixkYl07u2+bVPt68nqGaPtaI2NYx5+cFq9sKIks+n73kVGxGC6DrFOui8KjS6dmSG03Y2bo/1aOaGyVIUD+6KkVAVa6auuhVBeDOifwuWM/rD//rM40E+DkQGytfZXROQHxQW9OYVLWBLKMZwmIAzOV+NCkX6e9TNjXWjMif/8oIg8jQue87GrNTCqjP0iDSr9AHwaPBhA27WJWIuhaVoMDuyVKNA4EBkUlEVBYQytatGljioVrVVUybgN5CbGAlqpbLMHjs8yqOY5fXKN4XDI3HzBaGJRaDrT+bY7sDfxz1EJrTVkDnd4ZqLPVXoinY0FEKX9ntrMJtWdkxo9g9G01LWz61pr6Qy0ZszepTmWDtzA5kbH6VMXeOKJZ2nbG7j+xj2Mxhd8G5QHxDizfQ4bos8BONOLIjEHTpXlNkMAtaSWVPFzmONQbxecWzJVf1KtOdW0WOW1LU7SNtZQFIWTvA2cW61YmOmoCq/CjhsRuqDCNKFvkrQoJkjBms5YLl3Y4NLFEbv3DDhydA6thbU1aJqOtuk8o2UZDIYo2ctDf/gUIsJdd9+EUqu0Xe3qx0Q8VLpmYWGe5SurHDl6CFjtqRCtZxiVBysTiExGuzsMbdfSmJambWg6Z8NvPOh3pnPq/M5EsM3BKBIwm63nnDgnlM3QPJNo/QcrmQkk64Nbp35uUVGyD0xcKEF1H5HAM9M99bXfA2GuMlnXt9/GvRLAx5l+8ABEBO9tpZUgSdoEsrm25WrMb2QKPLPRkzilL43aDK22ag8yiTxnO4KAkd3ba0c+GZJ1JLuUbODWMz7O30KLcvZjDyqF1hSqiK/ZPbvE5fNriMDi0gzPXn4i7h8ANTfBrMxgxwUybKe0cqF9lkJKbtx1P8NyIcfS9CG7KAfEi9EgKtnPe13cMgr90bEQhYP+tKXGXxs6+yV/X3zHdAfk6nXa/gNXvb/vvAfW1hh1kcIzZ5Jv/quUFwR9a+3zInJSRO6w1n4K+Dzg0V5DRA4B56y1VlzGKQVcApaB20TkJlymrbcBX+GfeRPOce+N1trNrK79wGVrbSciN+M0BteOlidglUWUd+RyLfftzwhg19LUTrUbgLFrvYShJNpdHPPgJGnrJR9tk8QNyWwA2nsj2bRpyVVNbuMXep4rl09y6NABrB17AuXVk96E0LYdRaEJ4KKipEVs11Z1ox8A32NjEvj2NjKJ6zfG0pkOWsdoKGWcqssaz9RoirKgMx2j8SqwynBmlrvvPYp+rOD48ZMsLN7EzKznYjPVWgCdaftW/j0wLSqTJJNE4sYySrJ06dmsxyaT1CJIeCk/EMYg+YcxEBGKwhEuBNbGBWvjgiO7N5KzXk5Uo8hANOUYzxSJuPWxvlZz9uw6Fst11y8wM1skDUShmIwc0IoIShfMDA/w2CMn2dhY55WvuoeiXHP+FsH5Mb0SYycsLi5w7twFuk75deGdTzNGD8/4qbz9SrDG0HnJvuka6ral6RraztnyO2NoO6fJCkMfpNKE9UFKymlJosIOiN0DPZAlk9IjEfXzjO3X528K9wZbpmRvCv3FJolU8J/jC6Y8zGNbc1DObP7+BYFJcFWEyc7GIFt4CaRzm3Hmld0btT5TENvoNSfBWXW65Or4rSCZmJykNdtSRR8/cibB08O++SFvZxpzrTVlUVDqglLpqD7W4rSipa5YKA/w5OnHOXrsMKvNOep23G+rtsj8BLs6gyoNVhvInJ9DuXHX/Rw7fCPzi3O9+csZH7GS5kZbbKcc6KvpXFVZv7fl3tw/xpj0rnycp8B2O0Dv/TYNstL/0dpEF69WciYkrvFe0zxdJdMiA6srG1y6qFFyMbb9hcqL9d7/ZlwmqQoHwH9NRL4BwFr7TpwT3jeKSIvLGvY2L7m3IvJNuAh4GvgRb+sH+H5gAPy6XyThaN5nAd/u6+qAb7DW9lLmThdrLZ3tUFYhngg1TQs4cO9Mh1KK1jibqvaqfGdbrQDriYxEz3PjiWHbdNR144+3aa8yD9JIbAHQty+HdlksZTFkY6NlMpmwb98idbvsJlkcQ1E3TZQgB4MK0xnK0oFTYEBCfduBfpQ+bVI1W29nztWF+f2B+OYEpNSOg++MAW/vKpRCF5qua2i7NRYW5jh16gzPPnuWg4cK9i3NYW3yrs/BPXeSCdfE26TCO0N72s6Bu/bjG6RNC+hwb5BwPUPk+pXGx21iyCUgEcF0HUimAcIiKDbGJVpZZqtuamxtdJbMHdaMd6LUStG2ljNnVlhbq9m/f47FPRUKm45FWigLxUbnzEjDqmI4PMCzT1/m/PkLvOzl9zA7VzOpNx32mAD17h9jDXU9YvfueU6ePM14bECJ0wxZ61XEKh77C302cd6dur7tOpq2YdxOnCq/c456jdcwRW2JwnswZ4Doy/Q6z1ZSvKEP0ZBTPoFI+MK1INAijsCJ49LiHpuWSJNU5oHLM4FRLc703nOnK1yTEjgnDAkSfviP3ULAM5zG2tyW7pmDSGN7VL7X3tjmbMxE+ir2VIRg1nLga6NEF9rhZJWMvboq4GeCR+x0YkCCMOHvRKxEfxEnpCgq7xQW7fnKn0xSCtsZ9s7v5/nTy2ilWVwa8MzF864P9EFdSoMdNHTrA/Su0VZB1MKwnGd+IQF+X5uknI+WgBVDOBiFNtgucP3biLfbIXePRwzro//M9JD22a1+nbGdYS1nK8KG/1zjCHCPoQiCz1WBOzn5BfDfs3uRy5cu9ejUCwH/iwJ9a+0ngFdNXX5n9vv340B8u2d/BfiVba7fepX7fw6XmvJFF2stTdshhVflGn+8zjq1tSCUA9fVsnD/zgwH7viSMRDUw37RN03bk1DLsmAwqKKnfWDO86MwQLSzu3lzG8tYS1XOcvrEFWZnZxnOwLiZZKpNE53dghSMVlRl2duYoS3b9T2YBIKDXNu2PdW+9hoKay1t60Aj+CVo5VTdlOIlWad6x0LhfQaUvxA8dquq4tZbb+TZZ5+kbS0HDs5FYpFMC+4IW972aU1FMk3gHSuTE01gVsLYuvudk5o1lqLIwd4xetHZ0SbnwED8lVJeMnZMh7XC+kQoFBR6mrMWlBCBP8wTCpTVXL4y5vy5debnK265dQ9K4T3fvZOlEjRCVSmsgUIVDIf7OH1yjePPneCuu25n35JiMtmITKb1TI6xuFMFSmjaCfML+7HWsrE+YX5XAdRoJd5XQfrj6D9bb59v247NeszmZERrWueRb53ZI5dSg5YElYAikK++/C59Ypz/GsAzgFVoG8Q5DXxBknxsRFallbMTJyTqrfEkjedapQTkOdsR1mC4J4xRZDR69QaQIWqJcjNGroYnPO8/53b4vPQ0A0Er4fdfEC6uVrZjm/L2BoZ32pwVJMEA+EEASTxOYry1Vr0XiJXouOnolXMKc0f0ivinfWwPQRhWFSV7OH3qYW66+TpW6/N0pnF7K0yy740SkPmG7kqBGZXITDoWS2p9skWHR62AcTTXKuPO65OvD0/gjIC+OrDGvua3TDMBPaZ0+kH3QKximpnydeQM2vY19Chiv0FxTU/vMXdvEOLDnsyBv/fcVfuRyouV9P9/XYy1TNraLYjCYo3QWedcpwtNVRZorf3RNzfYAcCUl6axFoM7XqH9taBGLdBRJZwPtNI4j+e2i/4EeNqmlIY4CbNcvnyaffv2ILqGpk8oikLTNA4w2raLIJ0ToFwy3q7kgB8kVa1UvO5s4M5xK3x378HfG2y5HjRVUt13BrRKUjbA3FzFDTft5sTxZdrWcPjIPFqT3ZN207SK35V80QdVsCE4QSmlHBEOd1j3uTPG+024DW+MAdP5HaWSRoDwL3F+nYTliYiFSavQ2lKoKaJNYubCEVARYXOz5eyZNYyxHD4yz/x8xaSe0LSt0+ioEpQzA2mlKI1gUQwHe7h4oeGpp57lphuv5+ixeSb1BYLK2hpvriA5WIZ+KN0yPz/PyvIae5cWadpRBKu4DgV/6sBRywD443rMuJl4oHeHmtxhvTQFSXLASb+R6ARKGG69NiHJJbScMFsbmGNLOMaaa4Xi3Ab1p4Q1RCJ0mYnGRqYhe7PXmLlxzPwRwgqbeqa/Dn2r/Q1hz8UTEFu67ZmhbYYjMDciJIfSHNhCh6aqTk1J6z0wOUGFnzM72703gajEa/13hDWd+b/gxsxaS9ca7zMjPs6IZF77hT//nRzIFmaWOPnsRcqyZPeBGZ69cNkJRYT4FqEv4WgusFDTrVagDTJo+wCahgCMOF8ccGAeJeU06JPW8OzFMZt1x2xRcNOBIYPy2ms0F4Lt1K3bqfWnWhZbELeaZPti22ev0ZC8vv6leATQXe6r9QPYk32PL7dhTq/NAL0kQN8Bk3PS6jqBjqj2LIsiSvfOdpnOeutCR0ceEwgNpCN0xh0r6zntBC4f8cshSQJ9YA5H7QrqibCxscGdd95I0yx79a9zEAs+Bk3T0LUdk7phMAChJNi9r7bZQwkEs+ty735/OsH6Y2XBWcs4Tr8oHNdurUVsUEs7ct91hkLpJFH19lzqX1nC0evmOX1ynSuXRuzbPzvVLhAfLCdJZxln6sG062wihIJnuDqCIt6aTDL1c2Uy5kWUjlQ4/Dc0VcK8WYtWOm6OzkDdCGXhiUrmNS6Ij+vg2td2hgsXNrhyZcyePQMWFyu0FkbjMePJxJlhtPJBnVT6XhvKYsDKiuVTjz/NwYMHuPnW/Uwm56O0neJEhOOmbpzC6YDObLK4OM+VKysoDmTybJqSpB0xNKajbVtGkzGTuqUjqYgjaOL6nAeUDHMR52iaEk2vuQAuQR0dRZVQn5/TTEpPzEWvCwnwp4AYknRss/UB9CTmoCnqOh9TQEvSEFm27J/cvh7ek4BcYtvz7vcemR6LjIno2W6DdJ9fo191X/PQHw8b2259JMftCUGYLjeHNl5DpDeDks1Nbibp2i4yS9Gnpygo/XGwQeFOLGlxUn6ph5hmlrNnn+XmW25go7mIYChUgdClGCl+QVvlzWVVBzMt3UaFaINo4wHU98uI+4Ooxu+Jyb78wYk1Pnlqg8abprDCB59VPHDdLK+4fsF3dtuhSlXZtAxl+rfp8d3ue0YLt3tVztBsvan/Vpm6GhgSiYxvH+CDhmu6TW4NbG8CzstLAvQDYoQFbDuLaO+yLU7Fb4zzYg4TURSF8wj2xCIs1NxJwuC430IVcSCD1BKYeGuJUfiiU1EmqQwG85w9tcxwOGRmrmRjNInRnyaT2kneFiZ1TVM3DAYVZVFkx/G8lAQ9wjJdcntcfnqh6xzYh8hq4RRAsv0n+74IWANN3fhN7jQlweHI9taqe3Yw0Bw6MsfpU+vML1ZUlY7EM3dSMtbQNoauNczMVrE/AbCU7t+bR9TqTJdJEcYfveuiJsKNide0RPEwHJkMEflUXCrGWiaN0BhhVrdx/NSUit90htX1CeefX0drxbFj85SluBMgrdMmDYcVVVFirdMMhNDGIKytNYxGLU8+cZyFhQVuv/ModX2Rtmu9BLw11kE4ehpUdVqPWFyc5fz5i0wmlqIoads6bnC3br0N3xiapome+bqAwiqawNAF4moTUepJiVOSS3+H2S3ft0j/mUSaS7yA19p4IN9OEslAKDYzglNmWIhAHdpAPO0SpDV3yoWoHQqq/TjY4Zp1+1jrtKdsNjg5U5Eo+Na95+rJ7e9C2H/bahjye0g+Dz1zw9QQhX5sq2HIm7flmem2EhnAwGyGvVaW/lheWTIsBwyKikoVlB7wnTZTMzPcy3NPX6AsS/YdnOf55VNUunR7zvT3ZBhTYzqwFpmz2A7M6hAGrVt7nUqArwITnnOkqf1/cHKNjz235juXRqDpDB87vg6QgP9FlG1hO6Kv+3eaMeg/O/3txbAN29/XE1jCBf/nlfnRCVr6AxAbnH67enmJgL6XzjovvXhVddcltRXKHT8RxKn8qxLE2U+73Bs6SjsObExnKYugNkw25ByAleioWRAk414VhZrh/Pnn2b17EWTsiHPXUTeNU+WXmmbi/A+GwwFzszMxHG/sW6YGDZJ8KMFOHzZyup4iD7ZtFymD0orOWBAXgz8+4u+f1A3j8SQGIdKekTHGONOBTccTQzvm5irm5krOnlnjyNF5rylxGoOm6dhYb1hbmzCZdCwsDJiZrWJfguYld8YLUq4S763eOS/bDkNrWu+c1vrf8Q6HOobyjSc4MmKbq1ZFoDVCZ6DUSRKLzJQkHFxdnrBr9wwLi4UHVgfKWinKsqLwPhzhJELox+Zmy/NnN1lbnbCwMM+dd92A5QpdV6cB95vZmUWgaZ3TXeelfq00TTNmbmEPxnRsbk6YmVd0XYfSmhjiOJweCbonH1XMiEI6srGOccvcvGdMQCQWCVPzJThVPHhHgAxXbd/hzu+DXIvQYx6yd+UMSfiuVALv+EDAzMAweokY66OehXeHiU5DncwMedemiHqQtPqEM6n/M+4h9ZMgjeXMRPZMaEamrQoj4Rg814lwYiFHnVhFtqCT5swzP1O+RdNaiT7j4f7tOr8eYrRPF8K1KkpKrSliSNcCpTRKHPNfFUOaccm5cxe46abr6cwypdJQDlCdpvXg7gAoqfuND5vdGYMsdrSbQte4hR99E7XJRqY3zIBT6X/y1MbW9Sj+Rit88uQG9x6doyq2D1CTM0jWz1uO1+/+6f/MD37fOxER7r7nLv7RP/n7fMs3/W0uXbzEvqV9fO8P/F8cu+4Y3/SN38LMzJAnn3iKUydP8T0/8H/x7p/6z3zsox/jFa98Bd/3Q/83ADceu5Wv/bqv4f3v+112797FP/6n/5Bv+6ffwelTp/mOf/XtvOnNX8h4PObv/e1/wCc/8Um0Lvjn/+L/4DPf+AZ+6l3v5r2/8t8Yj0Y8e/w4X/IlX8w//45v63c7ND3XNP13OKf///si4o5iKZNUIMm254i6AzAngenCqXnbtqPzwBjuLbwpAOs2gtZC4SPnhahxYXMHiTloBiQnMiJoPWB93bK6usYNNxxlPF5xkljTRg99EWFsDLOzQ4bDAYOqiqrvaYCHwKEnR6W2derccF9RpAh4dd3EmAQimX0afDjNFBu/rhtGowmTxkmRIalDIC5N26K18ue509G10Kal/UOee3aVtdUJi7sGdC1cvjRifb2mrDRz8xWHDi1QlG6cg3RmQnIfX1eImd9ZQwcplKxYHx62o+4a6qZJtmELaIvuXBwD0coR1ByA/Ly49kLdKDqjGJSm70mdERmthMNH5h2T0HWYztk5C28yyiUvpVR8VKmCjXXL6uqI4WDInXfdRFGt0zRj53Hvx8ytxhDO1KCVpSxKCi8NKq+9CEF61tdGzC9WWNadeQDvd+BFdgvusKzBM75dBJ8oJdtsECI2SlSXeyjK5Not8se2Ur/7v0MXoe8g590oonweJO/Q93zcc+0TkuYwtN323uvqVf7IbQous037PHF370y/RZPD1PdpSTuMQC6Zp2UT1oHd0p8gsSYJO/2bmBmb8wbpHnyze9K/7U3htPavpymBGBcgBCYK96TZcOMXzH0hxKsSp+krvF3faRA1w2oXzzx5gaosOXhoN2uj45S6cKYtpSNTHEZMRCLoa+ViRYiA0i6SXmeMb5zN2pbPW1p7z1wc0bQmDHl/nP21prM8e3HMHYdme/zrdrys4xOSRufxxz/F//1vv4dffu8vsW9pH1euXOGbv+FbeOvbvoy3fcVbeddP/BT/6O//E378P/0oAMvLy/zCf/3P/Oqv/Bpf+fav5j3v/SXuvOu7+PzP+SIefuhh7r3/XjY3Nnn9G17HP/32f8LXvONr+Vff8a/52V98N596/Am+6Ru/hTe9+Qv5kf/H1ff+3/9tnnrySb7sL72Njzz4+4jAww8/zPt/77cYDoa86hWv5Ru+8eu57tjR/hhk899nkrcvLxHQxye4wS9w46R6v5MKXUSntWDn6trOHcszXaAHng56IqcUVaEQkio8qFacRJlJkL4Eaarz5z+H1W4+9fQp5ufnWNxVcmV1HRfPWvvwjAVN21IWBcPhkOGgzLg0O0UYXAlAF2zBk0ntvPELB+Rd19G2Tiq3eLuaEmfyEEFp6TkqOufBlkldM6lrnEe/BosPSuOS4AgasfNcuHAcheXkc6fZtaejHGjnAKksi3tKzp8f0XaW1eUJulAcObbAcFgkL3XrNTBd50MMmwjqCmcPbzp3XDAbCRoDTefOnNedM4vY1m1YPVBomyJXBYfKEBExdzKz1qn3R42gxDI/6CIoSHZPmE+t3boqC8GolM8hSAi90wU4wLdmkfPnnqPQBXfddSvzix11Pe4xcD0TjXE+IoRTFj3ZE6Bm9+5djEZjBoPrsAjjehWsm+POGh+MyNJaH0/fuPC6ISBR9GXxWB/XWSZBbl+m2+Lvn6YrfpxddaGfNo1qEl7jfgu149sT2AuHbX2tQc9TmjRbks1xYkJJv/W+B8nOJmbnKirz2C2B/LheVG5kUvT0SEVGKxyrzO53zyTtx1bQziT7beLxh1DEgXEMY5KDfXwmmPzoawt7Y2rd2AfnU6W024fKq/Oz47VVMWQ80ly4cImbb74ewzLgtGzKCkZZjC0IZpWwjoOQgBVE5/MnWNqew+6W8c9WymZt0mrcZv2Faxt1t2198ZbeOkx3/t77f48v+dK3sG9pHwB79uzhYx99kB/9yR8G4K1v+zK+/Z99R3zRF77pC6JGYP/+/dx9z10A3HnnHZw8cZJ777+Xqqr43M//HAS46567GFQVVVVxz713cfLkSQT48Ic/wl//+q9FBG6//Xauu+46nnn6GQThjW/8LHbv2oWI+HpPcd2xYz360eurnaIt25SXBOgD1G2DaQxVUfoz+BrbGRfsRpyqPiz0YOsOAXgAbGfjxiKT4iFsfK+GsiDizrUGGh7qDcdeus4wGCxw4cKYS5cu8cDL7mFjdB5rLcNhRcgAWJUlIXlFCK0I9EDHxazv9zX5F3Te+c7G44JN3VLXNZ0xFGUB4s+p47ILOglVxbPwWJfxzoaoaCpJ+CEdLKJYnDvM008+z+bmiDvvvImV9XM8d3yDvUsDZhad2g5l2Nys2VivOXR0lj37hpQ6OZGFMW/alqZp6XCmjrAJdaldCmDTOQ9eHEFqOudoVDcNrWmZeNA3nUWLYlBWmMLEsLEBYXLuF89AWWNpWsWVzZKl+Zpds6a38bHJ1i6IO6anBDzzF2zVMaRrfM45bWq9j4cfOc7lyyvcfvuN7NknNM1KTz27lRMPquAgaXpJWBRlMU+hZ7jl1r2srq5x/uwGRTFkcc+QK6snsUIMo5vi6aesea1x4+w895MNeTuqmJzxpEdYt0j5AfiCtiDukS0Vxn8C+OTAmBjsvoOfZM/EyvPfgwaP7N7Q+quNbehHJjm/AG0kSdUZgY0fZfrO2BbT2Rj1svAaoOQrYbGedrg5dr8En4SwTnrMRDaOgu3NR+iXk1gzxqPnN5GY3sB8O6df92vIdSE+O2ipvA3fKpROJrOqWuSpZ89TVSUHDi2yMT7ljuiJRaxCeeY9jQh+rRhaoNThhIAPNyspZ8VUh2K/0tgKc5WmN/y2f38oc5WerqpfbJqv3mVr43xM3R7/zdtaDZxvkhLFwH+2OIExnJJyWmKn01NKMRgMUAJKF3Rt6wWUdBonvd2t7sGgir9p7ejjdAuTUinlk7lWuXZk/j8jxRjL+toGm6MRm+MRdV3TtK07uiQOLEbjMaPRmPFownhSJ49VBOWHwXm1FzHynkgKH6uidJ/UrjkRj57Y1qB1gWaRZ55+jgMH9jMz29E0m1717pwNQ8hEV4tn3XOJJtadPNejXda4oCtd5yTRsvSe+J0H7pARSxwAKlHMDCsGgyodLfQErW06Qq52EWFQlszNzVJWBVioygG752/kU4+d5sLFS9xx583M7GqY3dOxuKQ5f36D08dHnDk+4sK5EbOLQjFwDned7RzgeCdCi5fWm4bG+khxpmXc1YxNzaSpGTc1k7Zh3E0YdRNG7YRxO2FzMmKzGTPu3H11U1O3DZ31kqwEQMrD5qYS7M2dgTPLAzYnmsN7apTyNm5PpMJRx57pINSQbU6lxWuVrNeiaMpiP48+fIoLFy5x5103c+TYLE27smW9Biktzqft4aerH5gZ7mWyucBHP/IEv/beX+f3P/D7nD37PH/4yGMIQwf4XUtjGsZtzahx5plJW9P4KHyt7byjanh3WLf5X+pjuCdIh1sISGCeMpWsu76VVDrXvcQkBIYpmJksicgmgOiryLfY4YMUPE343AvimEJgNF2K2HwP55VdjT5ufz2NWaAFSQPgHOLa2mkQg2NoDPObjV/Owwh96X6r5iHz1SCATs6ESIxeGbT2uVNvv63iBQ5XnxJn6iy0otQp4l48oldoxBuhymLI5ppw4fxlrrv+CIbVBFYkWhmC9yilkrYVCUPkGISkqiA4FFo/90H6lqk+InDT0pCySFlJtyxfoNSKm5eG209qGFE7pa7xnz7rjZ/FL/3Cf+XyZRcL7sqVK/yFV7+KX/y5XwLg537m53nNa199zbrzkpopyXwjDnEiwyuK17/hdfzcz/w8ShRPP/UMp06d5o7bb4unH3JmIJngtnlZxoBfq7wkJH1jDXXXOG7VKpwPh3P0cmp8i2kNA+24pkJpBoMybgKDxQo9Yp+ry/KFLTjJpPNSspP+TExiIyLMDPdw4vhl2rbj5puPsDE6SVkVtK1xAOsBKkRIy4OluBL4dUHr4EvQB/2ckzfGBxQic4hr20iwi9L7MHSdYwQ84e18NjURx+wMK0s5KEGcyr8shlT6IJ/8xFNMJmPuve8OTHWF8ysXAVADy54jmvFa65JDzLjjedVEuHhhBGJY2DVwHsBF4VK5+lCwnXVOeU417frSSfJqjwksxEXCa7uOpmuwWCZ17ZwglcKooNb3CXWkczbGKekQoO4UZ64MOLM8ZP/ihIWZdKYbHIAn71hAS9q5NgRlyswAJphMCspiiUcePsnzz5/j/gfuZmm/om6Wt6zVHJDc+nPe9+KZviABunFomJ3dza233spkMmZjY4OZmVlWV9fc+vFaj7praTvntd/5LHomBOHxEn5cVlHuTFJU+NExHnaLRGOz54NGIoT8ddczQiSSNAH0pc/c5t4DN68msH4O8hLSIpPRegdweT6EtIas9YF+srGejlqYWmvjtWmlgrX9a4FhyVuRnz4JAaKCGttai676fh8B3PHjGxi+0Kr8nqA5sb1r7p4QoKpvtghRJB34BzqQMzohK2QYQ0QolFDowudnV5RSxMicAXyVCMNqL088c56ZmSH7D8yxOTnb74t/r5VwjC4xh8aGZE4+k2PnzE6RHrQdYdH0mMwp8BqWipcdm+Ojz61xtfLAsfkX58QXmaL0mjvvuoO/9Xe+hS/94r+MVpp777+Xf/mvv4Nv+aa/zQ987w95R77v3g5yr1lEErOdGDdXlAj/89d/LX/rW/4ub3jNG9FFwTvf+X0MhzNTz75AsQGnXkR7Xsjo/2eh3Hz7dfZffP/fRnDn8oMtKnh329YB21w1Q6k11cAds4rOZD45i1beqz8QwCDVqQT6YeG0XlWtlcQjceH+meogn/j4s+zbt5cbbpplbeMi1jiQDznVg1reemZhfn6WqnRe+8mbfPvF23XOZt91xmeNSzEHrLGM69pJ7ZXzklfe1u8cHjVFEc7vG2qfacpYS+OjGI7HE2Zmh3TtAmdOrrKyssoDD9yLmlvl/OoJt8BQifAbNx7h4LcSoR7B5jLsOzBgcXFIUWiX0Md2NKalo4vakc4aX1cKEIQl2qiD/b/tWpq2ZVI3WGMYDgYMBwN2zc4zN5hlphgyKN2RxxBExGIxBlY2Nc9dGrK8UTIsDXcf22DXTAj1m4MiiWNmm998CR7auigp1D4efeQU586d5/7772bfftkC+P3jcongdF0XhjDV6xkBpUrmZ27kg7//IPMLCxw6eIDV1TUOHV5iYs9xYe0MTdtQty6efmvb6CNhrA/C49uZMDpjhvzvgQ0IatSwBmPbvZjmMaUH5BGdQomgn6TTBK1EkJRMAg5gH0A0eaGnKIvkGoF4P1FzIJKYiuQ/kt6pdS4Wpvb27f4J4KdLOk3iR2TqFuNjZEQ1vRLKUm+pP3/3tB0+aA/TkGb1STJN5s9HhpE+c5BjZxjz8JfMG0JVBI/9goGqqHTFoKoo0C6zqFbMDpcY6IMsL68xPz+DkfOMJys5D+nNNcRQ1cYnpOr8iZdJ2zBpJy7DY9syaRuatqVuW7q241XXfz433nLD9gA3tWT/4MQan8jP6eMk/AeOzvOKY4uI3j4Wf9QmxclOUviWl/Wf6l/J9sG27+jVFITFJLFHCT7elPW6x/P03yD9H2N58sln0OXZLCsm3HXbFz1orZ2Oogu8RCR9a21MamI7C4YYXMYYixioVOkk4cKpn9KRGrdR4pn0KbV9/z2BAAbi3NG2Xj1lDLrQiCja1tnCZ2YGtN0kBscJBKXrnO1fFxqlC6rSnY2NwSzob8xQktd+apcudZROm7ZlMq4xxlBWLg+zxUntkTHQKUrfZFJH1ZltOneqwLfdWmH5yhXuuPNGHn/sJCdOnObWuw5jOmFcjygKHVWB4iW/rrNYcelZ9UAYzCsuX6yphprCdDR1i9VJXWmtiZ7nHW7elFKIDkcuHXMTchPUbRud0wIzFk9OANED2BiMKMaNYmVTc3m9YHmzpDOwZ67h6J6axaHNiIlEohWHV3IpmC073EmUJVr28uijpzh//gL33X83+w4Idb28FTiihN+vL/oJ9FSd2fiYjnvvvZe9e/eyubnJ7OwcM7OK8xcuJcfG1qUW7WxHF4h7vlK2AHXWyYyUJLszPQYgH4MIvNYSHfamJOAeOk8RRwljYIkWgQhmmSScF2NxsflVn8EIwns4oujqtOmZ/KU9cJT4fABX9/0agbByzsV3MN+bulDRFKGLTK19lWqiJmEb4IkahPiMza733xtA3jmd9kc6pzdJKg8nkLydWGknIOFUTF3TYZRBPMOipEDsAh/96INsbGzywAP3s//gIUDYHF/p7b+gtTOYCP6Nz+jYdI0zy/mET3XTeL+caS1nGqk45La/iF5x/QL3HpnjmRCRr9LctDSkEr1NPWnce9+tX99bpmhqg/YW89XrTvuC7abdC5/us5mKxa+U+4vm3qlNEHxhXPXb7EuSgNrrwlXKSwP0gUlTOy7fO+aFdKMa55GqlUrRw6yl6/oOEdp7r8Y6p7lokiTSNC1N03gbsZPaq6rw5/M7hqWbABcD30sBuJgBTvJ0dvfQ3qoqMyexFL4y97i1NoB38twPyWusNUzGNZPaHYcpCo3pDLV1YKnEReArtNvgIWBP07b42C7OG946pmhQaIaDkiPHKmbmO26//RYefPATNOMjlMWAjck6tk2ikcY5EepS07Wds7W3Fj2wMIbV5ZqFPRqr3TiGoEetMVGKx/hTA14DYvxvTdsyrmuvlWjS/PoQw4U/OmeBzig2J5pRM2B1XLE2Kpg0LjrhrtmGA7sads00MY0u9MOxXmW/esm1j21FUWHNIo8+epJLFy9zzz13sP+AYlJfSaBt8rrT5xQoKFF2AawIIcudW6MNyJjJpOX9738/Sml2797FHXfeiqiCrnMxC4LatLOmRxxCSfbAXGuxjdSwDbHoS0X+o3Vt7T2U08prAGf+U1LJB/U48VRBqN7hqHXv822J7Qhhr2PcJUtgmp0GQ3zmzT5x79PUpMGYRvzkMOvBzPet7/Uf9qirV+mkqdjKwARBQ2L7k9mAOBY5uAcGCcl0JxmzGpwa81Mkeb+CFiSElA51KyWURfDOV0kCFpeXo9AFAlTFDGJLJpMJg8GAoqg4deIih47sZTxZ9nOUmDZLyOJpaK2jBZOmZtLVvcBRTdPGgGH9PRhA7eoOda5dijsP9SOAWhd6ZIu0Hb9nDJ6bn+1Af/pt17qS3nGta7YT55isPbj7GwLv7fY6cc5FMn+QaUnkxbzwBcpLA/Stz6pnoZu4c9ei3Nl90YIWxyy2tqU1JdoHewlJVpSolN2LxIXnR+RdcBoPlk3rzsAb5zFelaVPies2clG5QDsbG2MOyKJL+qO8U5IQueuqKnuAH9Z+voEjETAu0E1gHpQWxBI94UebYxChqgpn2247ilJnQW9sDLDTGWcWwHru3I+fO/WQUt7Oz+1jNBpw/PgJZmZmUAWMNzZxdMh6NbJFSQpdLNaNq7vHYBdhY7llsOAkEYMLCFK3Ppd748ZRaU3po+mKFZrOZSXcHI2dCtATiEGh0UozqEoGZYVWA9pujisbu6ibGUbNAGMUSllmBx1LCzV75zoWZloKHw502mxis/9uEU3T1ViUKsHu4vHHTnHp0hXuuutWDhzSDvADYQ1MIglPHPHNIw964t57jwcamwJGnThxgv3797O0fz+T8ZjRaEKpZ1wCHWO806TJZaOphiepvtfVfACkL2Ekhzqb0UobWyjhQZvuF6ci6FedMzXWmVpyFXpc974NgdBFHOhxCWEC0g3hvTaK9tYRf4KJLHkvXI0y9gQkm33PtDPWutTFeSrfXK0e64qAn+/h1PjgTZGD2/R7c2Yirs7IqFmwEs1SNhuoMLZ5Sb4jQeL3Er5WsS1ahFIVlKqklKB5HKBVwdzMQbRa4Nix63ns8Uf55Cc/wZ69ezhweNZr6Yg+I9ba6E/S2DaanurOOd3WrTt1EwB/++V67c33gtiWrzeYXo5X1+T0nnqBItt98f4rPbQXbOfXYeEnR6YeFX8U3F8IuRBM5xwuXZRPolbrWs2LtGQ7dVlWXhqg7x3ZgqqoKFySCItzBgue5E3XUkrrA04USbWd1xUF2MQAhLj1de1VUsbQtR1lVVBVJYNBRVG4iG3Ol8CwsDDPlSvLWLuPrusYlBVKOa2A1h60BlXGgfffO9VDR+Bj9CzX6I3NEeNJ7aT6pqYoChe9ztfhvG+FpmmdSaPrfA71jrZx5pBgf2u9I2BVlswv7GY4OMTzZzY4fvxZBoMBt995IyNzkdYkDYmHNu+o0znA187a31mXo10NLFYZ1tcsw/mUoKjtOppJ44J1IBSVP9+rBDEwnkwYj2uaNhvvsvAZwAoG1SzG7GV1Yx+tmUNEGJYd+xYaFgaG+UFLVRoK5ZJ9eGVCDn0Ozvw+NJ2jusH+Fn8Hf49P0KRKsLt57NGTXLp0hTvvupmDh0omzYoPJGQIOe9NAIvoE5Ik/AT47p0hiFIuoRtjGNUrXH/D9Xz84w9x+coyuxYX2L17F1Ux9PkmuhjWOTIYGcD0Ff1RVM2X1tRK66Os6X/NpOqMsNqgqQhMgGX6QJTzX4mLPD4bP3mwz0NI901cU7ZXCQGsSAxA7GrmIR7eM6UiTvenizE00TZDFY5CXes41LT0n/c+ZX7M3pYBVBTiesyCjf0OGoHwjI2/E/gAb3FRLgFT5rBnSd+FzMveB98plKYsCgZFRalKBuUMuxZuAFNw4rlznDr1EAcPHuQz3vAZ7tjZjGVjdNYH1nLpnsExqp1xPjvO7NR4db4/qdN1NHUT0zkHgWurn0I2DtcQbvsjnAZSfDpbmf49K2F9XLvea9UwfT1DZCtY42i0aJuq8UKAhTiX6RBrWP+JThjjwL9pnMCkr269SK2xlj8XEfmstQ60umS3BpxEaS1GWR/pzXn5a6NRSMw9DiE5hCI4vlkbEuK0Xh3uw9niFkxZFszMDH2sfI2bPreRrK2ZX5jl9OmzQEVZOu/YSe1U6FVVMhwOPOCnnPPuLzMxmGCTd+Fxw9lPgPX1DZavrHqq5CLmOcZCUVYFZVk61fh4Quej/xlraep0xr3rTEy6Y4GqGDA3u0Sp9vL4o6dZWVnl6NFDHD66myubp1hZv4yyxBTDWDfGhi560xelprPGh5N1GpViKGysGrqipvOBg1wkQae5KLRGTAcdaNFMxjXjunZz4RPYlIWhLEqqskKzi0l7HXW7QKkN++Y32DvXMDeAYZU0NgKecyYTdjNAz/drtsFtjxoT71e6BPby6KPPceXyMnfdfQsHD5bUzUrUyITjlEHiARDjiawtKPz6CWaXUHskGTYwKJbWGjZGKyztPcBnv/EzWV1dY2VlxTtaLkSv6PCeLfvC9zF2c4sEeTUQcyhi4zOpgtydzrU3ky4yQOoxVjasZZcMJzZm2nkvl7jjK7eIgsQ0Z/HdxJMUsZ2BobdbpncbG3IG/NOSWGxDkma3GzPp3dsv0X5MYjyT+j4drQvMDhDt8OGe+J7MNJSi7fkgQBlTkR7xmgGIWgrB0btCFx70i/i5KjRlOctow/KHD32CCxcu8OpXv5rl5WUef/xx7n/gPhpzgbYbuf1vgv3enRpputaBvWni8dy6aZj42CEhKVjuJI03tfX34x+jiPVjuL2wO83Eb/+afH9kzEi/oqyNadFaK5778kxHliHQ9urNGGWSIBL+lG9fUPFbC23j4z5oJ1htWYe+omsxpaG8JEA/bA5VCNXAx9SPUrFFtDtiVzcNyipsYXxCEufAEhJ0hGJ84pK6aWnqxp379+rvQVUxHA4YDgdUVUGhQ2ALCJV0XcNwOOvs1Z2hLEtG4zGmswyGlXPay1T6wTaXVL/BOdC6DTRxIXKNdaaF8WjCpUsr1HXDzFxFCF5dFS6R0HBmBsGF0uyUT5OpSypVMj9bIEpjOsfkiIQAQc4PYHV1g6fOPs1wOOD+B+5kZt5yefU8o4lFSUVZgDKdl+rciYSudUF9qrLAdjZqE8IcGISuLqgnLcZ01P7EAUGyCwtZ3HG8SVMj4FPo4kODVpTFPFYOMar3UxSapYU19syPmC0NlXbHAoNTY5gNUV6KzopL4KPjdUWWlS3OgAvAFIpSJcI+Hnn4OJcvX+Gee29n/wGdnPasU3N2xtCYNtouwfq85NqBnpQxLG14U/zkNQNRe2I6xu2EcbPGc09d5uzzzzMejdmzZzd33XMrVTHDuK0xWS3TknqQCJPD1XYR/7K7p/Cwb7qXHgj1Y747QmcBhYrzG+lscLrMruXvmM4fELQBcS6CTBQYixwIw/1KtlQfBf4pKTl7TSZB56C5VYIL6Xa3nvfPpOrt9MfZzeJBOp44kECvbTb/4d7kdOe+51EHbRwP8bE3whoOprzABPRNhyl1uBIXFKz0gK/9qaemWWfP4iEeeOABHnroIZ5++mluueVWbrnlFkS3rGxsuHC7OPOgMY7JrY0D/MZL+U3nIn3WtcszEpkobz7MTarbAtY1JPGuaVg+c4ZmMqEcDNh15Ai6LF3CnpC4Z3qKesz/VSreptgtHwAj2OiJ6tdI2AbK+PrtVC3SZ8byhRmqCF+z/SoKykrRtV7qt8Yn9dq+Gy/UtZcE6CPSs6k7T9YY7xEr+DPpDqxaa4AOZQRdKArthiFIa03ruNN60sZwtlVVIUoYDirKoiQ42YQjEthEKJRWLnKS+ChKnZNsB4OK2ZkhWqv4Lne/Wy0x25+1NE0XN0zj4+J3pmNtbYP11RGt6dizZx8H9u9nZrhIWQwpixmUTx9rjPHSfEfbGdqmYdS0TMYTJvWErnO+AE7qbp1jo7iIUYePHGVh/xHOrG+ycXkTkb2IbbHsAekQarSsIHYNa1oH3tplnWsbB/SdNyUkNXeBacU577UdRaVjvO8QGTEwCTqEubWgC82gmsHafYzbwyhbsWdhg6XFTWYq6xgaKVz8AZwpJuTiDjEUgiQp4tLkvu9pw2uut8yWPv6BjxqY79GY6tY6CV/pfTz0iWe4cmWZ++67k6UDKgJ+AFbrzRxtJH7OZFIojS1KBIXRFmXCuvRg1nPAI5OcWuqupjNOs/PKV76SRx5+hPF4wqCaRVSxPchMgfq0w1Jf7Z8xCjZ9joCbqZjjHiEBfpRSM7rnt2R8W++MfRKM4vM5fEep2BPC2L2p+P3pHRJfL57xCJK0tVud+ALgR0k7v0jGGESmIEmPvYHpjU8g1HkdSYORPxKluwx4Athnlfo5sx4IJEr0oaVBmu1JzH78bIz2FL4nxk9yG7K4ePrumotRYnC+C5Nxy+nT5/jMz/pMlpev8OSTT6MLYXahZtysR4bZ+ZW4GBp1UOO37nPTtjEQWtCggmc6skyfcYx6a/Tq5fknnuD8U09ivObVAvqRhzlw620cuu0OJ1V7aTvNrB9abDhsfI1it34yQYqfaqByIai2gvy16wWnGRCCk2poXWLuwvoUf60oBaWtk/q7jjJmNM2q7+2n7ctLA/Rx4BBAwnH9gEmEQURAC63taE2DLpyE6QKw+KH1o+Wi5jlHk6IoqIZljC4VNohWKkbu83y6k0hEUGqGy5dWmZ+fQ1QN1tnK52ZnfbjGoIJKM1bXdYyZ747eNdSNy8g23pywvrFJ3TRsrI2Zm1vknlsfwBrN+vomK5c32dy8yGQyyTh86W2qoihdopjS/TszO0tRDhkMh1SDitmZ0jnaWcu4m7CycZY9M4b9cx1aG0w3wYh1x+A2KlY3j2LNiJnyPMNqBModzwknFcJRPNN5wqUE0zgJVoxQ6RIVEnxo5dW/LnCSLryTkdIovY/GHMQyy575TfbMLzNbufCmLvOX6p26cMVLZt504vaTINby6DnLyRVYfdLyBbdb5gaJANgwL/6bIKBKimI/D33iGS5fvsIDL7ubfUswqZd7CJGr95u2i9EGsb7PotDaBWMqdWIaJSNMueOc8eal1nSsjC9w1923MTc/x8tecR/1uKVtDUVRuaOOW4qkNQZs4WjwALltsWCd1iWqYUOdgSmIgCh98Ip1J6YjWPdNqMs/nnvuu5Js+dP96M+qjRJW+J7rBHrPWptlzLPkn6K0F8RlcqBPTEHejvw4b15MVLNn1zrn5BtP2UbBwLcz12T4I7+BggcNQN6d3kkQ79QazJiJcbJRwxLMAMGsIkqSCQAXEy7QtOgvgPM9KMt5VlfGrKysoBQsLMxxz913o8qas5efc0m5/HvcGm0zu72nX01DXTd0bcrip7ywk45GM3XM8OpgH1bU8088wfOPP751DtouXj94013bq/jDWrgm4k+tNyvQ+QfEgk579pu+8Vv5gjf9D/zFL33LtSq8al+m2/Yff/jHmJ2d5R3veFum3enfppRQVpquNdSTliIEIsrW8tX3tisvCdAXiJxjUXqJX1wCiCABKK08GLmz4Z108TxpZxIRbL2Eao1Fly7FpBaXPUpwnvrVoKKKMZWJm0ZQtJ2zPa+srLK4awFrxxSFS/gT2hZmSMR5HddNkLoNo80xTde541iNC8CzvrnJeKMBhBuuu4WlfTfw3IkzjMdj5ubnmJub5fDh/SwszvnEQpmNGAMYRBl8mncubVRc2hiwOLvOTDFhfbLO2csN65OOjdqw0Sheez3smdWEMMC1Z1KKqmOo11kcrrG6Ocvy+Caqeo1hdZFCNmiVD1yEgCow4iIjGgGxikFRIoXzFrYGp5LHMWOVqjAYVFHS2gXq7gCdGbIws8numfPMD33yJFFOrSniiZt3iCMAkYrtNh5I286yWVs+ecYNzMpY+PUnDV94hzBb5sFcgvOaIKpEqyUe+sSzXL58hZe//B527zVMJqsRzGz484AfIg2GaGNY66R7UehWkEK8Ld+dkbaoBKQROGxsf2cM55dPslYu01xp2D23n/VzwmRUs+f63WBPZxRkW3JCUI1vV3IQD0yPykAvEpBMwk+R9cJSnjYqZMBvg9oar3KVCBh55rfwYCDKObMRmSE/2Jlg1EsclAnscShS7dkngWDn7mkT6Ncr+f3ZHek8vzfDEfmGWILjX2DC84iBTuolrqCc2YhvmdLghLC+7niXiRlD+zaL/Nk09iGOgTu+6H/yIN/6lLetMRjbMqhmGZYHmNlT8dTTT/Mbv/7bFIVm77697D2sWR2tOgfSwOjgMkS6wFmNA/umcTE5bJ8xEXFhf4OmU3nzXTZdW0qUdHEq/fNPPbnlnvy5808+xdKxW9FSguqzxH9kwDeSTAViufrj0+L2tfuz3dNi4Wu/7muiRhKm9kZ43mvCitJlgG0a4xiAtmFmtsDtl2v18SUC+ohLf6u18t7FQueDzAAUIalOWKC2QxnlJDFAG410liY4l1lHpKuy8J7xLeAczlTIhDZFKRyB7ugMtK1zvhsOKjpTo7V2aXSR7EiX4xjbtqWpXSjK0WiCxVBoxWTcOT8AY8FqDhxcYv/SMcZjeOLJZ1lcXODue26mrFq6boxlTGfWGG1OKCt3xtYY6x34DOORZnlzyNqkYrOG/YvrzFfr/O5xy9nVjGCKZljA7pkgc0I44qNEobGUqkBLy0w1ZjAynFvZx2Rzgd2zp5kp12mUk/jbtmOmHKCloLEwqDSDoTvpEHIcaO2SU1ixFKpgbTzD+mQvnZ1hz9wGe+YuU6nOq/FdNq/g9JWrNfsg4dP/4mLTA9St4YMnFJM2qTeXR8KvP9HxhbfbGLozTKtWFUr28vAfPsuVK07C37PXUDdrRHIdAc3G43PxdEcwJ/m51qqlbj0DKT5roVgEE9dPWKPWEqPqWc9EXNm4QGs7jIXdszdw8fxljpY3pPUX5iotyWx5bk8FAuAb65MOSSYdi2x5VsCjRth2W9/meYB4rj4yDz74SA7K1hisn8OQFCqX3AMzBZ4ZCvVkPZ1uQfCvgOzo69UobexHeDYJTLnuKDAtlvy0YIoZD45Tin33fZ72JQn3BsLu6nMOxjYysG5c8mI64+tSMSlWBPIMGKwlxv0XCWYng+CEjaDet35tdV2HEqHBMXOFLtg1f5hTz50D4HM/93M5dfIEaxtr7No35Pm1Jxm1E+/YnNJ5G+sciUeTSdRY9s0enoaUGe2c8nO4Ghbn16+cORNV+lcrXduxfP40+47d4Dzop2z72+Bor/zg9/87fuonfxqAd3zlO/iit7yJt7/1K3jNa1/NRz/yMQ4fPsSP/6f/yMzMTHzm/e/7XX743/8IP/auH8ECv/Pb7+NHf/jH+dGf/OFt2AG48eitfP03/HV+/b2/wXBmyE/+1I9x6OBBvvNf/Z8szM/xLd/6zfzgD/47fuSHfxRdaO668w5+7Md/xLc/GzclVF7Ff+rEGgcOzrF79wCZVnxOlZcE6MdzpzGRjHdkwdmalVb+6J5FjONKo7c8zgHL1oZ64vLPl0WBFBLD5cb0qv48fuS4/QIMtmvnra7olJPUdOFsDO7cpfOUd3GzHSA2TRtt33VdM55M0EpT1zWj8ZiynGFxYYlhtYfRZsPx4+ep64Zjx45w3fV7qNvLjOsRgjNDaGUYDkvK0oUSDn3cGFtOXFmg6TSLsy2H9ozYO99ybk1xdi1zA/ML6uiiRSnd25yFLiIR7Yxh4HdqoVsG5TInL+1hZXSMpfnnmRtsxIAmSmk2lztmZmDf0izDsnKZp3zSohgf3gpXNua4MtrFbGk4umuFxdmaUimsSUk8JCNcSgSltQMP1wEgxA/wxwNNx6QzvO8ZuLgR7GQK7cn65U3hN57s+LxbjEvmARTFAGEPjz5ynCtXVnjggbvZu89SN6uRmIXoa5Zkgw8hR1vbJY1RYPBax5wEgo2AGIkOnflatli3XoN0bX1+CGsZNescXNR0XYttNVUxoG4n7uFMvAjg5YI4bS814HsQtUIZ2JgMPKNPgDgTie1X0Gcwwvco3hPtyiJJZR7MIXnQmODbEqT3mBpWkjd+6FzsjW980Lb12jwFJQncA0DbeD0H63yo8hwXPQJugykiMRbhzthe60dXnJQZTI3hnUrSs6F7lrAGiJJ6eB7wa171UhGHSqIfg/bMlQWik18SfIw1iBXn29R2tGIQU7Mwu8j8zD66xYZHHnmE8XjMTTffgMxOeO7Cw4yaTaLvilOPOgncuhTfdV1HJ8KYw0J5gUG7AGExoJJkUvwLIbHvSjuZvOB9WGgn4+TQ5yX0LRO4TfnkJx7ip9/1bn71v/0K1sAXfeEX8brPeA3PPP0s7/wPP8j/9b3fxdd9zd/gl//Lr/BlX/6X43Of+Vlv4O//3X/IhQuXWFrax0+/6928/R1fHts9XTY3NnnVq17BP/7f/yHf9k//OT/xYz/J//a//Z04n4Lw3f/2e3j0sU8wGAxYXl65eqPFaZUOHZ7j/LlN2tawtH/m6vfzEgF9hJhUIzrHqUBkk+rW4DKD1V0idmJB2c6rcaDAcaOmM9StoRwU8VxrWRYx0l8MjOKDTBjrI/MVC6ytuIQwi7vmsVwCvAQX4lF3hkldx+N0TefiT3eNy0qniyGHDh6jUHMsL29w5uQpAPbt28uhw/uYmW2p2wsY2zpnOO8J2zv6hyf6Fs6vzQCKO45sMjfo3JEQgRPLmSoqk8yOLG5VLwVv0Vi8ek4pRak7FMucuLSby5uHOLR4iYWZGsHS1JbV8ZiDB2dYWBhQ6iLa4EOozs4ozq7McXFthj2zE47t2WRQdhTa5Q7AE46rEodI7G30jA5Jeuqu5UPPwdlVEJxqWgugXOhlAS5sCO87LnzeLZaqnMHa3Tz66HMsL69y3313sHcJ6nq1/8qMgIf5DUxG66X8rnMmJG01BBOQOHtqCI2irQsW5PIEmAgm7sx/kPYTg9F0DZ1MGAyGbK5OmB0sULfjNF8RA6JISm7TDm0N45WrPC0S8xUAW877OtWiH+5wn682F96EFIt9etCcyjupncNxuMDQheZEAM1CLcfK+0MftVTGm0ZUz8cjnVWwNggFqT/xefITHNL7PVf1hxpdf8N45irZUDepbyK9SLL5WKUoeST/Do/0lrTOAjOSTgolzUFoVYjSGQHVMxbB2ThctzYOlk+LC4JiYfYQVy6OaGvDa17zGs6cOc3Jk6dZOjrPZr1B3daxrZ01Lh25Z7idhtS1JGTvExHKqvCm10RTQhipnEl9MaUYDK75SBiJcsZJuyFIk+MyXrj+D33wI3zRF38Rc7NzoC1f/CVv5kMf/DDX33A9991/Lxa4/2X3ceLEyX51IvyVt34ZP/szP8fb3/HlfOwjD/ID7/zeq76yqiq+4E1fgAAve9n9vO93fjcyqQH47733Hr72r309b/mSN/MlX/LFU53sa0oAFhZczJfz5zadH9U1yksD9Kf6KNCzO/aPsAjWm9aVcvGyNYqqKN3RKtHesQbGY8t4s6UohcXFISLu6J/pnINVSM9L0Bh0lrnhHMfPXmDPnl3MzBhG4walvRe/t4WZ1gXDaTt3NLDtXIyB4XCeXYuHaOqCixeXWVk5QVGUHD58kKWleaRsaOoLTGooCuVzUucOe1k2Pj8WVzZK1kYFx/aNWBim+P/PXe546qJX/0Xi5crSnB9H6TNS7lp/rLUPBrJ7tkWrNU5cWuD82hLHyhUWqpbNlRGzswP27J7tSRxunhzYnV2ZZXlzwLF9I5YWxlQarE1OktPH6aKKMzbGM3b+fwEsW9NwcaPl2cvaMXwIyijnCW5BWZcdTCl4fs3y1OUBdx/YzWOPPsfKyip333Mre5eEul6JoxPGI0iGQbPgjuq5c8qtz3YXkgoB2BANzQN+koRKCglAkgJJubXSpX5Zd09rWhrGLCzMMx7VzO1bZHnzQoaF2VjYBAhpq+SbJX8qgE46dy9bns4+R2CyPjV1eleA+9wZLjA84Z5ceg/Osdu8JTIleVeCRJ8E7aRmlxjnNNUT/RDyknMWUQpPP+SS/zTSTAcZCgxdXnKGwmT350ftwrFca60/dRS0IkE7k9oTTVph6DPmBRGMB+DcTj4dDjhndqy4NYsShsWQUlfMlXt59LEnnSDyWM0999zLgUNLPH7mI9RdE/M6hGBZIYdI8JcKjI4qnRCiC5VOVeVqaYIi4oWdzsIYAuw+coQzjzx8dRW/BV0U7D58GDyDb42AvjYIujGRGMaXPGGP4J2vXdFaMx6Nt0jwb//KL+cr3/bVDIcD/uL/+BaKopxqfSpFEB5F0EURT3pJtm5//uffze994Pd5z3t+lX/9nd/Fxx78IEUR4Hr7MZubLzlaLvD82Y1r9vUFtP9/dkr01PYsrpJMchCfdtUnlXEpbTufzMXlHjfWgIayKhFVsrEOm+uWrlOMNi3nz024fGnMaNQymTT+z8fWb90iKasKS8loNOLAgX0Yuwkk1Z61YH28gKbtnAlAa7QqWFzYz66FGzjx3BWefPI4dV1zw43HuPOe69m7BJP2HF23zGCQYvWLqCnw649H3cCZywMWhi27ZmqCCvD8uuV3n02OUQQAsxathNnSt3pKFWutz/DXdT0C4s7ol+yZ67jl4AaF0pxd3sOoHjLetCztn3HOO4SjcOGcrmJ9MuDi2pBjeycc3VP7vAU+HjhBwzDNePTb5XIRBFu6U7W7qGAtVzY7H8DGRjV8yESXGAUQ0fzBqZKPfPK4A/y7b2Npv6ZpVrDW9N4fipPurZfuHdgHJ77OusBDhuRH0nata5dpGDc1rfH3eFV+dIjq0jn/kC7X2d0V++YOsmtmiZtuuokjR46wNH8YLToSzx6oC1NgBpEI9ZaMl4T8X8S4ANjxL4Bcv7rA/ERAyqT87QAnvy6p1unBnf7gQMVfMiFNrHUEWxTOO/1q1QRgl+AXkCTP0D93v42AFJ73XfLrP3O8ywcne1eQ3gOou8hqJiaRCpFDA4AG0I+M5VTM9bi/bWiHzTQENh2fVAF8My1L3Cv5PLhrBsv8zC7uOPxqbj34CnbN7eW+e+9j/9ISe/fu5ZlnnmZ9fIUL62e9814KDR0WSpiHzqfHdep8B/g5g5/TECS63U7N0bWLLksO3Hrb1W+wwoHbbnXn9YF0VKQ/x9s9Rye87nWv5Vd/9b1sbm6yvrHBe375V3nd614D2z071ejDhw9x6NBBvvu7voe3fcWXk1bOVR/xvkUS95ZvNNZaTp0+zRvf+Jn8i3/xbSyvrLC+vuHrsNtXhhNiZ2ZLjh1buFpPgZeKpI87GpZLrUAiWkpQlhgatu1MJCBiFVaD6hpMK6xfHlNPLPPzBUcOzlJVmq6zjEYta8s1ly9tOvIWzQguve5gKOw/MEc9cZtjZq6i6zbcBrYO5EpRtICo1qfYdemVdu86RFfP89hjTzM7O8Ndd93CcFYYjS+zun6OYVVSVQWDqvLqV/AyXeh+b1Uan6531Ajrk4K98xMni1nL5Y2O33pS6LwqdFpEqTQ8tyzMDwwH5lUiEhYX8tUmYpeO+wSVo2FxpuOmA5s8dW6eE1cWObYEs7OOwcHSy/LXdoqzyzNUhWHffOPbHuy4ROC3PitQOH4UCGFgokKyICcJJ3CdtA1zgw6L7qlU8+J1CVg74PS5K6wx5u2vv4V9XsLPHeR6NlxPo43PD9748KONV+8nImejRNPaDlp/nNIoms6FR7bKuvTEvs2Tpo5BTjrbxRMnSwsHOTxzO0/+4XNMJhOUUrz8Vfdz2+GXcWH1NJfXzyXmxCbHLUjaHzd325FZ2yMkQY7vS8R9CTwAJDY4rvnfMsRPDm1Bes7G3jMlYU5T01NbglRMdo+dfk+UlBMY9aj0lBTfK2Er28BMBqDIh8ZGx0SvfPKMfEhHnKR5g3Omg6RhiNK8P+cdpHrBn+P3gXJ6fYpjJImpsP05yMcxFNP1tR3xFEUYZ4l6HcAyN9jFhbPLfOqxJ3j5y1/B9dcfY2Njk4ceeoi7772L08tP03ZNT9MSPhvrcoBYr0UtShfaPJ7BV1tPjeTHOZPy5eqwn/8iwKHbbweE8089gWmTd77WBQduu42Dt9/Wf0DohWAOwlfsi5G4yO5/+b287Sveyps+74uxwDv+6tvZtXv3dHWJ2cuug/Blb/2fuHTpMnfcefu27Q93O94z/EvcJ6Gyruv4uq/9elZWnQ/RN33TN7J7967s6W2WeOiihaq6drxe2U6C+bNWbrztqP1H3/2/0nUdRVH4jZSGJEgfkUv1G1wrhbLiz9wX6K5CupLde4cMBy40ZThu47yxDfWkA+uPRRgHGG1rqUcGrWaoynmeP3eB173+furmjH+/96L3Zoa68RGqrGZmuI+VKx1PPPEM+/bt4bbbj7A5Os/maA2tnR/BYDDwiRcC55yOMYV+REkGoiR++sosJy/PcNvBdfYv1qyNO977Kcu4vQqHbR3BdSE6hbfcYZkfZkcgfa77qErt2RcToRaluLRe8dS5WQZFxw17V5itWsrSJcsJDMOoVvzhyXkO7ZpwbO8YrI1xvJ2PAl5LYzLThX+3B50gPTlp2p0RbnywkNa0XFiH339uNhI7JS6+QqGUj5RXoNQ8585dYTIec+DAPt5074BjuzYJx2OQ5HRlfV8dA2Ko25ZRM2HS1mzWIzabsTPZ2MyRz+9QrRSFaAZlxaComK1mGBQlhffHqFt31nnS1IzbiQN+00bNxC0H7+XKcw27du3muuuO8YlPfILV1RVuuOFG9h6d5ZMnPkDnTysEopCDfoj/3pPS44pKzyTmYOq+/IYI+PQc7yIzmIXFnXaYCy9UU4DWU6eHN0zX7+tTui/V99qXX8w0CrG4NIFJmjfJ3JCME2lswjqI7fNjEG3kPsGVZOszqv7DWCii6l0pycakT6vw45BAaooLsElqTpk53d4Mv+f+TX2tQRwAAEpdsntuPzftvZcP/96DbGxusG/vEnfccQcHD+7n1MqTPHn2Idqu8VK+62DQVhjjNJVt21KURVTl97WPnn30fQoAOS0637f/jdx0yw3kjNn0nOaPdE3D8tmzNOMxRTVk98Gj6EHhg+Vk/bRgO0EVJO7RCrbDaYicnY+k88smPoz/1ub29k349Pf/3j/kvvvu5Su/6h39PmS9CsyiINFXLD8ae1W/pcDPemKS3/bkk8+gy7O9OBL33PnmB621r9quqpeIpO8i6yWVmY2pa6OkFripEA3NuhCy+WZWZUM1q2hsjeqcKhvljoAZY0CBGgTwcEfICuXcspRVrFzpOH/ukvdcF4aDOUaTda+CdgYjEReAZmZuF123yLNPn+bcufMcPXqEW27dz8raabquZm526EIK40FdxJ+xdZPqnDXcbzIFSCKKS2slZ64MEaBQlro1/OaTllGbiFHgDHPJSrz41bSWj56Cz7k1eTQHpiN6CWdhP4O/Q3Aa2js34bq9luMX5nnu0iJ3Hln32aISEGixDIqkagc3b7mDF/hQvdY5h7lkQ34XGmLb+vG/XaKPzhjqTkXA1x7otTeNaNFoNc/zz1+hrmsOHdrPcMbygePrfOndwrBMG7Ev+DmtUjAZhGROrWcMDSE+QMqkpzLJOATdaU2LMiqq9p2pqWXS1dEvIGQytNYyacfsP3iIjz/4CY4fP86ePbu54447md89y5XR6QQWATO2oVQhCuCUYB8JrInSbA6+ianLNU1uPacx6b1S+uvK3UMf4KYAOgJzDg7xTdljV4ngNj1HQBZ7LRk+wrMCLlqdsUiRPe+ZkyCphz5Hp8cAvDgp19nTk99ACBAWK1R2ixmuxwhl7Y4OkFPgH/ZruKbC/ogaAn/jlgiA/UUQmGUtitsOPYBMZthYHXPDjTfw5JNPcvPNN3HixHMMZyvOXDnupHwy1TwJuLQ/vuyOS7v8I0F7kw+0TM2BhHUhsqV9cXymvk/fpcuSfddfjw3Bc5RFVM71pfFFHMgHDQsGZ+LxsfGjqc8kYaI3ptPtyl4TPn7eG7+A2dlZvv07/lmv9dMMZIBlJX5tSj4CVwH8qZ+21ViKRM3o1fiGUF4aoO+li6J00qHpXMCC8Fs4zxq4YRcdzsSEM51YCnEeqY3nat0ZVu/16o+WhRKkkqqsKJVmWAzoTMeuvQP27j3Co488yyc/8SluvfVG5hZ2oVTnQdNFcuu6BtPN88mPuwhS9953F/sPVKytnUXEuDPsZRFDZPpuIKJikqCQiCEAUnQcMi5q3rMXZ5m0iqowKNXx5AVYrZNqKZSQHrO/kh1hObUCv/Ypw8sPw+HdBRYP8BAdrxxD08a2ZloqDu1qqLsxpy7NcGZ5lpsPjjJRz+VFqArD+rjC2JpCJVW4m6t+YonEZBhHWL3/mCVk+PK2/LahsW0yPeAlfKV9WmNBqwKtA+BPOHR4P4OBoTMulv0Hn7N8zi3Es9M5qIiI814PyUaiXb+LNtowNs5JLXH3Fh+rvBPqrsHiCHhnTFTpOzu+80XIx+vS2lkOHb2RN3/xFzEZT1heXmFhYZ6JXuHZc49hbN/ByVlFQltyhivcMLWHFCnfQAS37JY8EE60I6fQuVFWinp+PAXyErtsJW+5St8RxEysslPSf7a+rloscQ2JZzysTWAXzEKhTcmeniRya8X56Uh4LjU6OnGGI5ueMQsSu+CZ1HyMMv+iLeOerSzjzY42DFs21iE+QBhrE7Uq/mlJAN/TkIQ+BBOL13IoVTBTLvD4I0/zyCOPcfDgQfbvX2Jubo67XnEzl9bOsD5ejkeMc9APwlWYT3eyJmjkhOgqliFdoFO9I582Wyf9Dy+ySDx1FeKzpBdnavTCXbLGJ7Mpw1z2qJ5jDnoLPoxrum+a2Qx3/+b7fi1+D/d+4ed9MZPeMUPhh/7993PvPXdHxqnH3L6I7l/L8TFnZq9VXhqg74vgnHSwQtt2hBS01oj33g73paK0G6Wg3nHZ0Sz1pKaoXPKeQit3RCU7s9s2LuJaoQvasqMQF+J2dqbhgQfu4MknTvDxjz/snNyqChGYn5/nxhsPMxhWPPGpEwC88lX3UA02GE8uopQwKCqMccAfVMrGmyZCFwKBCXEEwkINjmwKmClbRrVGCWhluX0/rE6Epy6lvjvaly37sGCCVIHlwgb8t6fgut2GW5dgvjSIUuwaelDxakY1paYU5UKCHNk94cp6ydnlAbtnW/Yt1FkDOirdcWGzYNKAHtg4Fz2AyAheThFFxMc5cMk8uizrXADf1kgy5fijcYWuUMxy7vkr1HXD4cMHqAYtXdfEjXNqxfLxM/CKY0QpPQf+MH4hNXHu7GfoO3v1VexglPf2b9tIxIO2IPSnzZymgvZqNNngysY5nj9xiRPPnWB9fYOlpSXuvO9WhtUsm5O12K4keSeCkhO4hMvpahQsE06npWHTWsyJlLE2AmB+VBQSMKaJxEtZ25ClbGqjwiIwT9ADmQTr/RLWbOhSTCcbmQX3jMnMBPH13kFPIXEuXWTHNCZx/dlMw4FngCXsS9VnfMiYHTvV8qwDIa5FBMgA8J5BMV4jYWxiaHpHE22Qo7d/Z/5Ci2XSTnjmwsO87FWv4eabb+X48Wdd/7Xi0upZnjz7kFt/JuXTCPkoggNizG+SrYekdczfOcVdxjU3tT5SV6Y+bPMbxPC4osJaT++QjEaEooqEiL2536bypG184ZL3Jr/2a7/5nuxKxoTkf+HXa72rx5mE9veZhNx36IW4h5cG6PekBe9I4naNywCnHXeri6BikxgmM6jHwzi52OmNG0RPCFrrYsOHePKCT46DQSY1DCwzAwGxjOsVBlXL/Q/cwGQirK2OmNQ11lguXrzMH/zBIz6gjOWuu26lGmzStusx6EbIfOUC+ZhsJWULFos1KXtcfo451HNwV8OVzQFKnBq9UMJrb4Ab9grLY8tCBWtjw0dPkgiibMNH+munViwnl919M5Xlr9znufvwzsDJT6kwq8JwcNeYp8/P89zFGWYHLTNVkByE1qgMPFN880BcgspKeQnMnXXyRDsexVRgnE1VkZg4BOq2v7EKXSHMcv78Mk3TcPjwEtWgw5gGL45GgvDw85a9M4abl/S2BCiN0VaydrUHrLF0ON+ItpMI7EFTEXxHYlTBnoQFoFhfW+fVr34NDz74IE1TUxUuCZSdEMEzrol8QiNmBbtn5uiX3zqF03kfQ5Cd0J6ejVHI2mp7hCkQ0b7q170sJISJYBdaE7mHZGLymNtvl009MOGGcJ/K2hAkXskampWgSQrgl5jgcPtUDANLCgPtiTg2MeHxGoGLSSr6nnbEWq+VSUBujckoe5qjeJxP6dSxHMDiOIaFkM+la3P4bVjOcvK504w3ax54xX1cunSJleVlZvbNZ4DvIoYqFRJiJXgr/Fn8flyEAED+ncGDPjNHBEYmQXWc6KyS7IN1cQ56JeSrL8JY96XgbaXoTJjJlpYfE3rCRs7ATrfumpCadyFbd712Zap492u/xmkGYruyHa7nPkjXKi8N0CdwwSY6irnQntafo1eooAq2yaHPHZdznqbKE8AYVxpofNY3aQ0e8t0+tI45aA0oIxTi0tjWTQMFiGzSdhOKomT3vhJrXWrbY9ffzsMPPcva2ir3PXAnu3ZB3awQlmHUTJABunLIGgHVpsmNHqBexRpsbCJQaIsSy565hlInMD2yaDm6S3luXfGJM64fiaEgfrAQ1XGetCMCk6bvXKcyFTgkE4CTtgxLCzUbkwnnVgacujzDzQc2UViaThg3mkr7PNEivU3Xo8tBwlIuGQwkcFA+10B4XuHs9RbL2iQ5Iha6BDvDhQvLtG3DwYP7qAYGY+qeSj4fhw88Z1gYCktziYT0AV4ioxY0CWFutisdIZiTX2vebOTs+l0MLJQTTjxBM9awNr7EjbfcznC24uWvfIDOx96uiqHvZx8QE0NM7J81IHmik+yZ6TGPxNZfjwCa4aZM3RPqEcnAfnogQrsitknywPdgHTuQPx8B1VcRcxWEBqcG5dK4X8wJFPGAbfv1Owc5SfdkoJ0DRKABeV9TcJxMyvTPWy+EBEbJ2sDIBnOB8SG+fdycsJa9B7zbv85XSFRyoI1zaomalRixLweuHGgtVOWQ3YODPP3UaQ4cXOL45UcYNevsntvP8fNnXCySpmM8rjGt8T5Tfk4F77hXxGD+IZtlmAul+7Z8v1Li5zRdfXjrXY+P2Smzk4ARRNsXBPvshy2tmX73C0n200zAtu2Oaiq2ALBktGG63Vvq2lJxMk9t164QNdYv82uWlwbo+3FwDnzJKSMGj/B2ptwOWWjtYr+Hs+44kNHizk03XUs5paoKhNiSjuUIirppUEqxOS4wVbARtjSdO4aGJ2rzs5qyKllYWGBxUTEaX+hpG8I7nDRgItFwdMMDqfKccqR6QRpJUlTTCWeuDFkYthzZM6bw4U2no6Qle3OgwLm9rb8ppp0FGyNUKqUO7YGK9Z4yXqKpCsuNSxuA4eLqgGE5YHHYcHG9YmOiObJ7TFWYLYQssBo9VZzNpKowO9aNQiAzSgnaKp65XHBipaJQQqkrxM5w8eIKbdty4MBeBkODMU2v/tBHjzV0Bn7n6Y4336mYrRJzE8ZOaUVhNIUpKHRLa1R0zttC0CJDEbRGxhMzS2cT2AeGz8Y6EnCcXznj+roJu+b2snbeUtc1c0cX+tH0Mqk0rpHsi2y5yJZ7g0Yp3Z/W3LSgHFMRZ6MYIvz1iG3oTt4WyYk16SyXb2RkMDIJ2oI/CjddaabiDOOYmcB6nbThaGif2c3HKIBP2PN5yGcndTuBItdiRGZIhXHAEW3bb0e+Z0S5vCHWPydW4hl4EehadxZehZj7Kj2bxsCiCu3WZxyPxK14vgOwHFg8wuqFMUqEub0Vx6+cYdKMuLx+3jma+jDhwUtfOuczpbQLQ16UxZYoqEFj6GjCNPeZTzj+AEUwDUkC04TI2e1xMtxfJ9RieWbcsNlZ5rTi1mHJ0PsW2N5kToO9Z77CvNqta6Onds+uvwCWbn9jTkx8ff35CTtle6Ei00lsyySk5wQCE/kCov5LA/R9carTLiMIgesNcacdILgjW5pSa+eAZoVmwxHqYhaQLjrnTAOfWHzAFUspPmQvTi07qicgznbkJMCUQc0l1rB0bUM1KDGmjQCG+PZmzAXWS2Oec8ylx85aH3ciszN7QmiM5fnlis1ac/vhdWbKLtYZADGpUWGmgnpMIpD+Yw66bhMEZsQtvnFrGRTETR/WdlBHByEqEIBSW27aP6LUcOryEJih7YRdsw2Hdtc+NLDrX5KgEpEPandFn+BbwIiNserxqrONVnjy0gwKodQDtMxx6eIqbdtx4MAeqoGh6zL/gtC3sOGzfbNRCx84bvncW008SZEzF4XSVLqgUQWF6lxCHc/V24zA5NWGJCtpzJIGKrYHYta98HRnWp5fOYEATTdmYXA9ly9fYY8soZSLyY9kxGKLsBWhLJOeU1/jevIA0Ver25hzIMxLz6s7AoBsBUHJ5tOmdwBTGe2uQrD8MyLSO7oXpM+taG3Tc7YvIVlr097cwmhmDIbt/xYZ/SDNSwK6XsmaEPZMLgXHOfbZdGPiHD9OYRxd/hCn2jY+1r0zO6T3heetBXSKXhmbNQ2iWKpywJ7BYZ54/jkOHz3A8uR5xvVmfGdTu7DgTd2mpGVlQTXwmUVFUnx//46eWlyCpmQKTHOgC9K7IvlK5WMzNZ7xXyN8bH3Cx8c1rU1z/nsy4ZULA/7CwiCOs5uHKW+cILhl+673KmFqOnNmsl+uxgTk2qEgTwWg7wss9PjVvJtbGKAt7dqecd9WqzZVXhoR+WyKyBeiYAXpwdnx3WYpC01VFJTaZXgri5JKlZiNkm5UUA3ccCkRqsq7fGZF4c5Zl0pTSEpkUVUlutAR+DcnY8bNhFEzYVS7f+uuoTUNZVkxGdcoVSTp2dgIlm3rgr2EBdkZ21sYFhe8oWmd05fxxNlltTOsbCqeXxlwbO+IXTNt9OAFIkHJy2xhI1EKTmmdjyjXeqeyEI2ryxwHnWk9JRoKdumoAwWCvS8kjikLuH5pzLG9IxaGDYszDcf2jqiKLsZjN96WGYijMYamg5UxnFkxPHbO8LvPtPzSww0X1lzwms600eO96SxrY+GhM0OsVQzKIZVe4NKFBPjloMOYrYCfyjQBgzOrlscvJLAMdjmnKdIuA6FS8TigyndyRsxyxiaNnYmgGLAmAk8276GdgeFZG60yv2uG8XhMYYdoKSLDOP2XMsJNEYZEb9NfoDierhvrmSzvQ5HXFUA3qObT99R9j48Z4+q/hR/CXMd570F4Gr8c17NlnJuCYvjtxEUQTAfOFh78eYhSoZmun9DXxFwE1b3SKbtd8PpPHSUCfhicPguX5jAIf32HVYm/d50zA4mX3pD++fcwH/mcBq2K+H6HluRrWxAO7bmBeh2qQcXsnoJLa8/TdR2Tcc1oY8xoc0LTdC5JWKEZzg6ohiW6KBCtnOpeEqMS7fphUF8IdXw7ohSfRn2LBind7/4+tlrzkc0JTei7v7+2lg+tjvnI2jhq2ZxGLdTr/gzEz3FceoB6tcZvvf7N3/it/Ndf+uX0a28+g7bD0Ylo+hPZ0mcQ/pdv/Js89tjjvfpzxj0+0xsf2fJxO0ZgurxEJP20QZXP1YwNZ2NdoJcyqPK1C8RTaE0hBfWa0I2FXQeEjo7NiYmUKqhZnZ3Yq+HxCUAKH40PxbAaoAoVtQub47FLzqOyiTZC3Y0ZDCpWVlYxRkXpO2OY3eYOmyiCj2+PcSFn67px/gjeBmitpeng4vqA05dn2DXbcGBxnDkF2S2A74i5Ye8snFn1gE/K4R42hfIRBY1ftMFhr9QGYxQiKS922rDiJTObjkn6naWV5ejuEYd3T2g7S1WQxsEfgXviguXkCmzU7i8dl+xLww8/3/Gq6x3Yj5uG45fh0fMVdSdYKwyKAZVe5ML5ZYwxHDi4l7JsMV0zpYp245uPzjRzJCJ8/JTl0IJh32zKjBdt+qKSU6hy8z0NZr0YLB5YTZBUgzTYY/czCcWkvos4wjtpJ0jZobVmstkyrOZi8p0ebZgSglP9fXANuBelV2O9qBLAI0mlAbB1lOqI6yWqMqdEijCk0XyRjXnUBqTBiQ3OT804/EsaheBDluzwaa3365pieGOsBxvHOkSNjPsevNe8cWCXaTJSpYmhiRLmNmOfq8Fj8qi+LjoS+SC0BJoS6glBx/J3pGOBSYK00Dsalztb7lk4wNGFWxlR87KX3c/Jtcep2wlN3VLXTQxUVJYaqoKqKrwJI2luoiQb5iPMdxgZmwFWHKOrIVEyCzkV9fZqbIBxBx/fbLYOb6AfIjy4VnP/bEkVx8lg4+z4UQ7ty947bQrLVn129cUWS+xxWB+ZBiQvQaj4oR/63sh0Z7/69trYqMgyXE0j9iLa+tKQ9JEYsU77mO4iQqk1pS6pisJJ+EXJoKiYKQfMlEOadUW9pth7sGI40NjOxkQ4prMxzrZb2CpKcwrFQFcMS5c1riwKKh9ZrVAuo1rXdjH1bljEbVdTDQoXla/u6IyNceEDpx4dC4MKOTAA1uWsbpo2pqvUyjECa2PhqXNzPHthjpmq4/qlEUoSsQC2XXAAM2XiioO0bmzKB9/6QDLGdikRjO2wmQYgxDVouzZK6m3n8xq0KaJczmErDKV293ZesxGC65xaNpxaMVwZGZoutSkASwhm8+wVy/Ko4fRqy289rXnwTMWodYaIshgwKHZx/twVjDEcPLTPAb5pesQr/r2IVWYQPvCsoemSA1eUIKakqVhsCIeb3WuCp36mZTGmTyht+tf6MXKMg0JrH6gJy0azwvz8PJvrIw4sHmXX3D6USmE4pwmcnao/qsrJJEKLd4INXIGNzIBSKnq2p3ckzVrwlg+n2x1zyZQWIYz/VJvIpeSsjp4Qnpi+TKjqjVs0X2UxE9JYZs94yu6IqPvB+A0vEMFOF+70Rtd2PgZIFz9PmxoAr1Xwf5LWvOl83RKk3Aywg43e87eB6Q9zEM0lljjW02PX08CEccueFVHcfPBuHvzwJ3n00Uc5c/osN+2/m+v33QbGvbMalMzMDhgMK4ZDnwZb9+MMWBPCnqdJSMx4oiU5YzxdgrbD2CwhUX6vpL/w9NObHU3OJGXv8MuUxlqeGrduxUbNURaAx8a7M2YtlR/6gX/HZ77uc/is134O7/zB/4cTz53k9a/+LP7W3/w7fMZrP5u/8pfexmg06j3z/vf9Ll/9jq+N33/nt9/P1/zVr/ONFNL2E97znl/lda/9LF732s/i5S97Nffc/TIE+MIvfAt/8ODHEeDA/mP8g3/wT3jD69/IF7/5S7lw/mJ62QsQqkBLrlVeIqBvo9pOaaEqCgZFSak1w7JkWFYMygHD0gH1oKxo1jXjZRdNb7Lpwmi6zFGdl9zEO9ZkYTmtdeEbOxwDUVYMh0NmBkOGZeUZjJKZwdCF8PX/Cxt5tDlmfX3NJfqZNGjlnG7ytKJKu6hx4SyziMQkN07dpiiLEqU0TQdnlwc8fmYXGxPNDftWuPXgCqVqe4C0XQlqpsblydhmRPGSujtCFpMUmY5h0VHbmklXx+Qxo8mYSdMwaV0I2XFbU4fkMd5LvfN1NF1L3TqGYNI21J0PP9vWnF+bsN60Tm1vXdS6cP6+l7bWdLTW8ttPa973TMnlUTo6VRVDBsUuzj1/GWsthw4vUZYNxjbbbprtxuhqY3dlBH9w2ift8WYQ1xbHIIXkOLk6P4C5kpRSNyeiSTJIBMJpTkNGM2f81VrFRCaFLtk7t8TszDz33Xcfx44eY87s57a9r+TgrmNJpZ4zOCSsC2YhwjWvcgiCuqhMIp1G6/BsBnKxIqT3vkiNbTIPJDDwAIkPU5tL6r4hoQ/5sVSbEfM4fNk8brf2Jf/dkJLeBMbLpDpFkgmA2H3vbCepfzFlbC74qzSHqU4PvtG0kEuepAx7ZgrE4jj0mfbcv8fFx+hHYgugHF5cFhW3Hr6PWw/fy+65vS44VNuyf/9+nnrsOPvmjjIczjAYlFRVSTVw5sp4CiDUnTMUoe1hjK5CZyITkBGZqHr32fpy5pKw/kh/7iFhszMk13TbG3fXGPfbhjeNbH1j1pLsd+u/fPITD/HT73o37/2N9/Arv/7L/OSPv4vl5WWeefpZvvavfw2/96HfYXHXLn75v/xK77Wf+VmfwRNPPMnFCy4Iyk+/6918xVd8uZ+rXLiAt3zxm/ngh97PBz/0fu67716+5Vu+qUd+LbCxscHLHrif3/vAb/MZn/EGvvM7/82UpuAayP8ipJeXiHrfOeeJdYRK4TZsodyxklK7uNAu7KpmvGbZXG45fOMMAOfPjFhba9HzJi70ELkKElcdihJhdmZIobVPyeskHy3ae762OC7daQxM19FMDGsXa+aGA8ARHq21YzI8oQhBPoK9Dk/s3AkeRVU5gm+BtZFw4tIM62PN4uwG++ZXGZYGS0HXuXP+MYxodqQuVzMiMG5zQBBcultAOc/14GCWnAdhoA3r48ZHt1NxTEScY1uoO2mlnOlAiY95jYkLvbNdDDjS2Y6Pn1U8v9bnVJVN6YshEWFjLRu1S5wdCOGgmKFUc5z3gH/kyH6UHmNM+0dS0F2rPHbOcnDWcGDBUHctk84xL03bJO1HZiqBjGiLoLFI5wmQZPHwPcA6gugG2xqit7SO9gHhuqVb2cVRTnzqBB89/SjWWo4dO8rNt95Iqas4B+IlvXzwcmYApKfODuPbCwyVMTDxWhZ2NgffQEAJtvVYp18JNqmpo8oyV0vT/x4Js838BbYV8YkAFSXQjFBGadKGsZ2CIb/fdHbcLWcmQmIcayxaZSdIQjfCv4EhIUSTdCaw2OZ8/xEAP/kQiL8n9rCnoZtmFPPOC7kWJIw1CHvm9rMoBzlz6hzrxYQ3vOENfPCDH+L3fu8DHDt2lFG7imgXiz+X5vMxIGga/BgKErMaWvonajLezwtNNl7ot296HrafV9ceYVbnMqr03pM/N6fT2qLHbtCbUyCeIBARPvLhj/Lmt3wRc3NzWCxf/JY386EPfpjrb7iee++/Fwvc/7L7OHHi5NTQC3/lrV/Gz/7Mz/H2d3w5H/vog/zAO7+XYPoLzGKeAOu7v/t7GM4M+Rvf8D9v6atSir/8ZX8JEeFtb38rX/H2r+pj0LUw37/nWuUlAfpKhFIXDvS9arMQTaVLNAW2VmA0KGFzw7JyueHIDbOUlbC+6j1UlcGKcR7z0l8oUfWNSRMpPoVkthCFkNK2ddKUV3WPNgzjNcXuvXPsW9zDyvI6uhC6ro0bPRDaoOZ29YVTB0LTKjqr2aw1qyPN5fWCQdFw3b4rVOUIwdIZhVLuqJ/GEdc8T/n09hIJxwUtyr9PyKKNSYJnaxMAdO2Yi6sTKm0piyKNCeKZEh/NzPet9Gd6w1lSYyyTxlIbQ2ccU2OM0BjD2gSn9iZJXclJqQ/8EMDLMSqlHlLIHBfOLQNw+PASoicY02azmctYVy+JTGXXMmL9oZPw+bcZrG19qmQX7z+YOELM/NDi0P7QhhBW1RC0Aak/Adyw4hIDee0PKhO4fQOPHj3K0tJ+Ll+5wmte/WrGk0022EWhClrT9juRSz82vCvMbwLxUH1cm0E0iuOQSZXZONkABj3Vs+3dFABf8vb436e97MO7etfDAIXipzMG1snmKYBycMQLxfiscIHZCsd6g0peZfMR7g0gY0nMR2KeE6CFPBTp/VnAlHwcMxDNYxUo1e9/73sGpOE0QS9PRe/W9GWzXkftc5qp3/rN32L//v3cdNNNHD5yiE2zzGOnPwpi+rsrixnS00yE5qtwjqbPIKW5t1mT+n0KTGOYk2AGdcM01d9svd8yq/nAhtBkc9kvllKEW4ZFXxM0VVfPgc8mxirazqfKYFDFz4XWTEbj6dfy9nd8OV/59q9mOBzwF7/0LZRlmaTzuCdc5b/92+/jF37+l/hvv/6ebUanX65mlr1qsfSiz25XXhKg7yS8EmvxmfMUpS7pRsL6mlB4NZwFilKoKs14s+PKpZbRqEbPNlC1tF2H0oKRbMFmGy3aYLEM2sZLEOl4Wdt21HXLZNIiaNrG0kwsXQvzey0LeyuaTXecqygVk7ah0DoufkPi1I1RrI0r1sYFo0ZRN8K4UTSdYli2HNy1wfzMOtbWtJ3X0fsAREkwmJKESMQoOM/tm3V2R69k7dUTjKkuBryJfT+1WnFytQRrGWrDoLQMCsuwsAx0x0BbZoqWUhkqaalKF+9+OCgplEYp+MBzAy5sFFGN7Xa8IoRADe/CMxR4r3iRoJEIdm2nHSmLCjEzXLywDMDBg3tReoLtAT5MA35PDW8DOvVNOtMOkBbYaCwfPml42aEmZvSLpxx8yOYotYk4zaMHpwQcXt0vxCOb0TfAWMQIReFOmTiJ0DETHYaLa6c5duMt0JScPnWGZ55+htWVFebm5rntnhso9cCBfoa5jmi7bxbr1NxZQJkosFubARhxXHLcTffbKJnaAG6+P7ngFrE6SLGSAD0n7GEf5IxCZPxUHBqvLt8yna6/mZo/5ahIzIr2Z9lD6dusUwjcae3CFl8C/76Qyjq+w+WxjhEm8zUU5iFJze4/SklKwTutJQl1e4bCWItpuy3Z+XJ+KGdMVteXubh+mvmFXdx+++1cf/0NPPTQJ10o3T0jxvVm4DJxQWD8x7gvXcvFr8/ckS+WKcAWQhCtxOx6Vh7rTVbJWTglxdqCbwK2c20YaHj5XMlH1mq2LRZeMV9RSe6Ytw37nvNI2by87vWv5W/+r9/K3/zWb8JYy6+851f5gXd+Lz/xY+/a/n1ZfYeOHOLQoYN893d9Dz/7Cz/d/zkbmxMnTvC3vvXv8ku/9LPMzsxsK34YY/jFX/gv/JW3/mV+5t0/y+tf/9prv993042u6c3DduUlA/qVdqBfKI0ymtGK0NXC7n0lC/MVRakx1jnDXTo/4cL5EdWcoVioMSolONGicXrsuOQJDm62dUdplNFUesBk5G1HBtoG2to7uBhBKYuuLMVQmJkx6NKidcXmeOLS7NLQmZZChyQ6KgLduNacWx2yNi4ZlB2zVcv+BUdYOguzZUOpJ4y7lsbbkHNYciEe0/n57TjFIF0eWpRs4Vtvc/YaBuUkfWUEg0ICB+nzG1ixjI0wmoBMgJ5qyVGgJBWKV08n9sKRAffJ2L6kYQkZx9wyViQTBFboOutTD2sKVWG6iksXVxCEA4f2oHWNsVdX6W+VKBNhTgKCl+3sFAX2QHViWdhdwdJ81zvx4AQlx8RE6YIU6Q0LWuczBiLOsQ/Eq+QVulReQ+K0V8akTW2spakNn3r4UZQSXvGKV7B//xIULadXnqbuskQflmRQsWl8sSGiWboxaHQCiPQkjUztHPHdx2FwffBSrZeYImMQxiUttR7RDWNmp/ZcIJXRiS2bK9PZGEUz61ZiVvx9Ng93GtTsU5gVzC6+sbFNuaf+tIkjLAURemp5FcdjSnOS80B5QCtJdZoQYjeLOZsYL3eztS5RWBoXX1eUVt0enU7fWxYDDhw6zCc/+RAPP/yHtG3HzFzFhc2TTjLM0ccDfn+PBEbKhtF0Wxzby1efl+3AJ7wmOADHVOgkOhGYwgBkLvqeW8GvWnBS98c3mp7EXyrhFXMVr1yo4lpIFdGfb1J7JbvngZfdz9u+4q184ee9GYB3/NWvYNfu3du2v99PV77srX+ZS5cuc+edd/SZViT++5M/8VNcvnyZL//yrwTg8OFD/MIv/udefXNzczz22OO84fWfza5di/z4T/zHbd7aL8avXScYXdtVT67ugPFnp9x2x432+37kn3rJqWD1YodWir37K4rCOT+JEkabDZfOj5jUHYMFg1Qt4/GEznY+sqNFaR8YIxuXkC/bNpZurNHtkEGZFpf4LE9FKejSUpQuDKUulbeNO1A4uvsWzp+YoLXi8HUzdHaVQVExqErnvCfQdpanz81Sasuh3ROqAgoXWTiq19uuo2kbxm1Na11KV8GdVhgUAwZFRZE5A4aczUHl5rdv7N/PPtSxUScgyD3kc8969/6QCMaPjbX+UEzg1DOHE5ucZnLp0Fqb1PXetpurmcP7cqJVKBfquGss9dg9PxgWzC/MYNqKC+eXESUcOLCHoqjp/jva8HujlY1PazqsrXn99atURUfdtXStS4mbS2sBytIYZUQz9DdLsCP4GBAi0W/CaZqMD93bYRFuOngvR3fdxrnnz3P58hVmZobsO7yLh09/gM16PXH/gTiGOcmk4TAv7gvR+SyGf5XEPIa1HkoEHJvWQ/5btO9LujcfzwB8uQd8vkb6bZMoubqTNV06SWDx422jH014mS5UvtT75/jDdSEGQeqpeknAHniZoCkJs6pEoko/3Cc5w531K7yrJ/naNH7W2uhTkDMwCcCT/V98ZD6EnjkiNDgf26qsuHXfy7lydsRNN9/Axngdawx1scYz5x+h9UGqQnuD9odsmMLcRTOJ0DMdbukXW0E/MFJd29F6lb7Szgz4qus/n5tvvTHSkFCMAdsBun8SozaWp8ctG8Yyp4VbhwXl1BoL2ovIBEyXiP2BMYgSSqYp2Paxbcvf/3v/mPvuu5ev/KqvQKw/6aJUpL8vpKYPv+7ff4wLF09f8968PPnE05TD8z1G8I7bvvBBa+2rtrv/JSHpdy0MygEKxeVzNWWh2XegQimhblrqFkYbHStXalRlmNtnMapl0jS0dCDW++z54D5kUoixtLXBjAsYl2glFLMd5XztN6DxTlY+BKTB2bsKwSrrAN8H09GqYrS5wv4D+5g0Y3RBdLQTcaA+aRWjRnNw1yazVVLnBaIZTACOE08EU7wYJRI8evu2tnzDJPnalRv3CI+cS2dd8f1XCNYfF1ReurRW9Zgii0XbRD2js0pGVANRUxlBzRPr5KrikE7WesIt4FMcKyabBtsJ8/MVVakpywFdW3Lh/GWUUhw4sAddOA3KH6XkksEfhVEQETqjefTCPH/h6KaTwFURhiJGUUvz4CThENcgpNQNRxKz24Jo5yJGgnM4EotFRQ/4Ub3GU08/zYVzF7jhhhs4ffo0oi3zw11sTtb7ZMsDppBU3luyzUXewK0lRSLUaXDEawgkaRCyeQ7PRsKfRLh+eyw+0lyQUHKGMcfj5AZmbQDnnHnCa54yjYwETYsQYh1EYA4MjyXul9BOa8P3JO3nkGe9Gl9rSZK75FEuXb3GJEfVXnCG0LhsXGN8kUAHMsAPa8dmYKTERejbzg4tfoVhbdzHAMNqFlMrLlw4z4Hr9nB89Q8x1jBuNlyGygh9rq9T+XN6/FFkKPL2bQeQNmkL+qr2VI9pOzcOXaJhyRjgnzOAyp93v1ZKuGuu3OadiXaH1guBvqcmBA1FLgBJ1tfpWbNTn6fv+7w3fiGzs7N8+3f8sx4tCWtkukw1J6v3j0KBsvoypusa/ArwEgF9gMkqTCYthdbsOzhgc7NhY61ltNk4yUtbhgugh+7oV9M01G3r7E5hkffWpDtq121ozEYFWOxgQjknFIVCtDcodhZRFivGERgtMQay6Uw8YjaeNGAK6nrCYFgxaa4w522L1lpanz9+Y6wptWVu4LOseUciiwu/GwJ3hBXlCFni+EP++GAvztdQZ00WtSttxtuWhMfO517cbkkrfMhNcW1RNjEcIY5/AOtIpAPhthAc+YOtstDp/HgA/LhzAuGyDghR1gOhoMQFVhIMZaUZDgsKXdG1FefOXUJrzYGDe9Deae/Fbhvrx76pXdyEmdmCQm+vGss3qQXmK9gzA7tmYKFSFKqk1IWfL3+fDse80tnZMFfWj29MriNBsgvHAf08B+9ugobB+JjsziQ0GdcsLCwwGo3Z3NxkdmaOhnnHkLRdJoFngBwZigRAW0bGpsyHbl7TmhHSefZcG5PXH4ldLt1k1DKE802ZFXOpOp0UyZdwyqroIm0GybfvqxIANFfRE5mdNKEJXMLGd/4kiRiEsLsq+g54QMwJbG+BeMAN47UNsyOeoYjgk/lUJIEzgWWcq/jb9DvzYU3qfffdAfPizD5WL28wOzfH2KyxOrri75FePT1iEcY/0zA4ehNiTXqfmwhw/fGwBD+h7RHI+AiALlJqEWlWmhPA+PmNyhqJ0zW9rHolk/inGc0tJTKK2zCmeZXb/Jb3+Dff92vpLmsBxf/wuW+irvvBhH74h9/JPffe03tX7LOv8I8i5W9tZ5/mb1deEqBflpqL5yYs7qqYWyw5d2rEpK3RA4Oaa6kqQbTFiGHShTzrzoY/7S0bJeqJ0K0N3DnScoSeMVSVpixcAJ6w+LsIoWmTWv8OxGVGq5sW20EzcVx1UVo2JmNmzIxLCqTSsa4rGyV751t3LAiJNtPOmLjw3P7rq4vSJ4vFE69MpWStRYvyz5tYLxZ2zwjX77EcvxykffByniM2VvstnsBJ9zZdkhiDt2pkSkggN63idTck5beVwNnTA5MQ7W52VrO+1iAUtG3F82cvogvNwYN7EDXtpX/1YnFS+HjcMRq1gGU4LLc96pJvTK2EN9wg7Js1DLRzthzXwri2TMaauu5oGsWeAyW6kHj23VqXxCmMESSTS+tTAiOOKevajta2ULgxa41xgZGMs+U69bWhtR3nl89w142v4fK5VZQoXvWqv4BSMKdvYVRvcur8s5ExxFpESwTbcIwzt9/HWZEcMNM8gJN2w9E18Q3vEWAv5Uav5TB42XjajNCGZ3MTQXhtHpPfeCZ6Grx9Es1Ea6HHRPjXTHfQO6cn1OxioB0PuF6bkvaY8wnI93pvgYSNiW93DyWCzwM9wAeydN+hD0ErYXvtTyYW77PT45gTE5aPM9ZpimaLRc6urLB7zyKrk4sZIPoRmOauQndCuMhMrRGYFonevvkz6XscI5sYAuvHuW07JqOa0eaExcU5hoMqgXlQM9g8iVNiPAPN6LPh02Valxkqpz9fkha+pBdsW+fVmIEtb431W37jt96LUrqXUG26vmnAf1HFxv+kdoXlKIkJvlp5SYC+UsLMTMHGRkPddMztFmYqRWM7xnVHY43zgAsE2J2iBiFKrCIpzK6pLd3K/0ven8TqtmT5fdgvInbzdae953bvvvu67IrVV1FsqkyqKMmkDNuAJzIgeGIbBgQbtuCJAckDeyZAIwMCZEPQwIYHFgRBIGTaoiiRpmSJFJtSUUVlNVnZvu72pz9fu/eOCA8iVkTs796XmdbwcWe+e875vt3Ejlix+vVfE3QzwHxDpRVNM0nY6gLj65xnu91RNcGC9ZD6okurycFaur6n1hO6XYBMVdqhlEuEEDKTNeuuYtMbPph1I3dntsx0jnVSWAvRnVdmHHvn8UYYeqEgpHOFCYWPHywUn13tWWnyjLhZJM47ysz2Bfml50TmGMcplmra/nvXimch/IyYBzGhKVj6ofRQN5q2hZubgdXyDVVV8fjRPVCbYOG/Q2iXhyS/bdY9fe+oas3BQUPdZMAUWcd0FK7t3/5I8eTA8+b1hperjr4La61UUDybtmLT9fQrxfSkKZiKgD8FoW2q0OFRchvQKiYy6lgypvHK07sBb4cI+hOAgDwerz3ewd3mhsvNCx4/+gZffvmc3//9/5rvfe9P+O3f/m3O3nuPL/lJEvigIopasJxSgliy5MftWoUuS9op3fxiyY6Fdk7cHCXf7clHpbPIKJUALZpksQDpey/7REXPSaGM+EKRiPQVoR1GYxchLgmlFB4UGVeYriDwjc41+0mm+7FAkXu6Ugnas3Jln4W9EO9RKLVJgMu+dRGXovASOStYAaoYZ5yhiPomDXoyWJJi0kzQtmG32zE/nPLl+jqNrpxjEHd3wV9iMxyZi5FkSu/69p4TBV7uJ/NgY+e+vgvgZHVlmE1b5rMpvdtwe7vk+PiAlNTsQRlCkqLQnjw80V2eu/EL+bRuMtz9N04itzROvB/d6uc9Cjmcx1nylHK992br/+8jzr13nuvrG1D93nv+9Df4Wgj9vgtJIQ8eTZnMFZ3v2PbBMgo9ykPMFAWZRrLgUjpYkxqNd4r+pkK3lubA4gn1lk1dU5mqgOJVDM7RRLeuJVphcb4FNnaISXyzpmXoXKhVD3gyI7x25xWfX0yYNo62zm1mXbKcyJaE0qjoY/AO+q2jnoDTOsH6GjJDKi0WpVQOkZE18tOZGmnl4cvyRNngwWJU8f7CsIQRZvE9tgCVSApfEKWiiKvFsIMKuQRonYBlJA7eVBNcq3n58g3GGB49Og0C39uxJUdUwGwos7TW0XeWrgselem04uCwCaVa7yKoIoYqP//UA8WHx4ovPr+l6x33zuY0jaaqYlMnoO8HvvjiDm8Vja6SpTpYm5RMU+mo+MWZNrls0TrLoBS9NBCywRslMMc29SyP7l6jOVnc57/8u3+Pb33zm/zpf+pP853vfJt7Z/f47PJ7GGMYhiEx0NATRZKKCkuYbE2mcRUMS+Bdc0tXVQgymabC8is+T8Iy/lVWSIxCA8GlhHPx3QqLWJRYkY9i1Eryno90kuLjKuTTlOXcEtPXJsdxcw5CdOEj/es9qsrKa3qJkpcqEYjk8wBVeHRG7ycTXShHqZyPIr9CxhkTEF20jAGULkoNZa/GcUgb3rIqRCvFyeIBZ0ePUN9omB5ptjfrqPjnFxEPRna1yFpFQnN5UX+ay16uHfFWYi6QdXRdz9AP9L2lrism05Z20tJUNdfdp5jXmsvzKaixgjryqqjxT783mnI/lwZTMbxMpsUYPcUX5bl79/z5jmi+FAl8ebqz+vHfNn4/epLqqZvr5KX8J8a9X1WaDz5eoAz0Qw+2sBAi4crmLF2HJk6URmGUQXnD7tZQ11AfWqqmidaYTl35AnBv8Ai0k5BUY72jtz2ddJvDhf7ozoVGKd7T6JbdtqOua1A9wgCryqC15vyuZrk1fOfxCu8t4sxPtbtKgZQceRcyQ73GWbh63XP8MJS+OGew2mG8A69BefZF27uSb05nMKkDQl+pOCdlgfhZAT6SBYMesYLCaxaNzCxIgFEbYVEl8gYEfPgslE+GzVNXE/qu4vz8gsmkpW1rLi4vaFtDXQeLzDnP0Acmaa2n72wUsvpnWvUjS6B0+QHvHSl+833Fxfma7abno09OaBopowuKRNdZvvx8iVJwem+aQJtcLMOrKgOVQRFAneTeKakuJvJJYtxbsMN7/QeE713cveC3f+u3mM8X3Nze8PLVK/7gD/6Q3/wzv87R7HMubt8kYRes5MKiV6LXBWkqlnFKSIuC2buAVCnrqURgRoauCuG1H8eW84O0VoVVXnibikNlDYR4ZUaHU2Oc9tKdLXkOANYGhU8669kYbhu1nUWNQMjL+LaUzMn74QurOs5TQNp00R2txvRO6YmIQivStADx6MIaT8NRCl8AF7mosAY6KQVIQbWFAAueiby+k2bKw/lHfO+P/gTvPb/y+Bf59Q//Ij9+/Qdcrc4TTyknX8WX8MR9jCh68f0KvqH5KkuapIxJuGKIFr54t5oI+Sv9SozybOwXdBHf5NWXG6ZHHt3YwE9tKGnVJnpTvU8ImL0L1QBG61jlEzqqKk1ASC07gYo3xHtqHZuiVRqHDz1XpGqoUC501HAlXFEaUSlZ0Xm0C+BwFQEY7mhxwGIyCwZjBI0T8LiEkqoyEms5j6V3a1+JHh9x3yZIyLdOeOv4Wgh9bUJXKOsDc9Jep0xY7TTeW0zR61OYTmK8SmMw9HcVlTLM73m8Dxac8z4QpQ4wvpUOjXdUtArQsO07eisEHrHYbWy4E62UeXvI+m7LdDbBui6g1Jkg8LtB8+xqwpOTLQdTaawSCM1iEfc/5Kx5pRQGTV1r6kazXXnallTW5SNx/TSlT7R2haIx8DvfMPzH37OxL/1YE/U+5ymMXFSF1p32SSk8VGHpUGjmQpyJoYSrRVM18f0VUFUTup3m9esL6rri4cNTPGu2W8duZ9nthmTJVlWo3Z9MNEu/YzKpmc1zG+N3zYdYA/IqpeA6bOEvfAib9cCrl0uefnhI05jCne1Z3nW8fLFivqg5uz9Da5+FUGFRSeMd0crLrG/vwmfO59K8hOsf/0szGIWQ856L21fcn3zMP/jbf5vDw8MQw53NqRpNP/SpOVNOtIt3cZKQF6zT5Ikp6SMsQfIOpFXyMclNRVyGbNiltS1pQYRT6eEh+obUviBWuYpEnqWKMccFK5DowjnW2qTMpxCYIiXjhVI4jbjnfVGbvu96HbvsVRqv9/l9ZYJUMW3jMEgU+FL+psbPSR44xmVwcmFy8yP9OHQBqT22QUcei2INZ82C9c2O1WpNVRm81Vw8W/LwwVOu1uck7T5dUngsGD0iSiISX5BpyWl9IcneC5qpD3PsXG4+Vgq4cG0QVkb4a+Sxy2VH3RhmcwWqCoIbC5VPFVHKWqzWAWPAhmfoOoClmQhVnh0EPikfkrftHOhaZ2XK72cBxBBF+WFSsIpJKb0OJc/0Ab1vlOBq3VjRlP2j3npEGIHKG2vfm5GqNHDy4Kwk/IzjayH0wxFjXT53w6u0wekIZoKLwloYpiuu1AyrCmUrjh9W1I0OTU4IFGKUQaNTzD/EY4EIU2u9S41kehviVt0wJIbjnWM+PeBye87p2THdcB2R6YKV8PKmZlpbHh71aEL6gZCPikxXIHrxWTBqbairitlBzc3VjsWxofK5K53xpqDJnOCxb+XL348ONI8OLM9uS8ANHzXPOFMiCcix/303ZmkxKxGoUUAGq4sEd5rcUcnizM/WymDMhO3G8ebNJU1Tc//BMegtOEc7qWjbKlu+sumECeuW25sdk4nBVGNn2tgqIWvThcBvDfzOJwqc44vPbji9N2E2q6K7OzC0y8stV5cbzs5mHJ9McM7RC6woRGXTp3JFqXuXEq2scLhYjhnd+TEsJe2GSzelwJgCWDcw2I5vfvObfPDBB+x2O5RS3NlzdnZDVZuRwBbLNb16bBsrL53XjjETKficE+8T5GtlveNkfiWzLBixINehosUYlcQ0IwWaqCidEqctby9w11qb3AAnKpsxRQTJNcnu+Ey3wStAstjKsZTnpd728WvvfCyN8yk8kXRZrRjlHYzmRyxE2VfZ4yMubSFK6V2fUAPfdaiswMvftWlYTI55cPSALz9/zosXL/i93/s9Dg8PUX03On8/L24sYHz+ghhqi3OrfaF44XEqKJHhHiEx0g6WoY8WviSPDiGfSRqUNVVNpUPZM16xXlqOThraRgU8Bu/QVeC/gx/oPAzKpvmzgwtlfzVpLKFNsop7Kk1/UPxcSMo1xmRaiQxAeIAiC/B9j9S+V0esfxO0PCAkeotCIevq07qrrPgV81/yTik59b58ULkSezxM9pbiq+kkHl8LoT/0jpvrHcenLU654Ip3Fb4SjT0w1NLNbX2Gz93dKnxXcXK/Zj5t0ErRMyQmFRKPNDiPjgqA8w6vYLADQ8Rc7/uerh/Y7Xah/tq6BB5SmRZrHXVdM7iI8e893aBYbg0fnW2oDNGdF61IfBL4nuymFOFmtKbyhvmi5uaip996mmoMpBOLen++ifSeP/+h5v/1R56hYLhJGCbmQrbkeZvIVHE/5+J4rLjdXSzTMShj3jk0pRTGNHhXc30VEnzatuH+g2OUztC6onR8FZE3TXD9r1Y9B4dN2szjd0akwui7e7Mg8KcVfP7ZHcvljoePZum9u87y5vWa7dby3pND5vMaH5U/4roZHZOxyNanvF85f0GIj4eU3MTF76UVLRbydljj6g3T6Zy/9/f/HgrFYAd+4Ze+ycHskLvNtXjKo6AaW89l5ziZ0/S8qGCO3JlCf8aMS+20CAiVnrU3vUkxy3I3W7spYJGN+aKpzxgsRzAe7BBzX3xQjCXJrWTSyZMSJrpwl4YTBIhmv3xRzvOjcAIpidXHZN1kunlSbbxkuHgfwHbKecr184WCYPKk6MKDIR2SJQdjFJbzhQLvicpN+F6j+OTBL3JUP+T8/Io//+f/PKv1it12x+Sw4vc/+8/jWhczvy/ZfKwSKAhDBL5WGqNUwJAQXAF8gqC2OPrBMfQhL0XKLJVSiSe2TRPCdHVDravkll+vQlnxbFETqR+UoqoqvHf0QzTaYnhFcFVMFYCaNIqqNkFgOkdM5RrReAC9Usnr4HzZ1rpQzHyei5EyXExKuK2EuIJhpiPIG3G9QlvsWIbqwjhzYimgdBT8qlCMo/EjRhein0QaKOg+rVcc034ew/7xtRD6zsHFmy1VpZkdVGGSqkAsRptoKYXtubqzmErRtmGS1ncOt4WTBzWLRUtb12Fje0XT1LH1Y3AFDoPD1LFBhFFYHN0QBP1qs2Gz3dEPQ0YLi/8559j1a9q2YbfdMTuZ0g93WOfZdBqjYNo4nCuBPQK1ah21VZfL7LRg1NtAJHWlmS00y9uBdqYxLjzTaR/cVoX1DJnhves4mmj+6U88/9mPctQ9HJmQfpoKIW405zz9YOn7gLM9DC5aPhqtPUoNGBPWoq5CeMaYkDFhzJTtxnF1dckwWA4PFxwdzUBt8c7+lKfvW/Ce+aLh+mpL37sUh9+/onTnK+CTe/DnnoZZevN6xdA7nn5wxIsXS9pJhXfw/Pkdda15/+kBbWtwztJHsJHKhCQ+QVnM5Wh5LqWe30XvRwa5yR6QZPlFi3skHPOd2A1bnv3wBY8fv8ejR4/4/d//fdbLLU01CZZQ9DgFz0FhaeisgOybDmUm/mhyEAZa0FPUvlI6Zxx30srk1tG1nioHCqt3tHpRuJZNdMTdrqO17V2I8crwBOBqT26NmOtY4Of3K8Me4rpGvc08y7yBoJDk1rojS9uHJMIk8KNJKrSQ5YvMe05G3M+3kYqF8XiKRUmn+kQzAI2Z8KPvf8r3v/8Dvv3tb3F6eo/NZs3D2TGbblWseSn4Kd4tz0k5L0Fg6hDqNLnLZmgvHYwp1zv6XZ/mShsTFyPcqW0appMJ00bQQ6uY1GxY3u6YH1QRuCqcH50o9DYYDaJIiMdNKYWug+dUC4R4ovPw3OR1Se8SO5oiCKBehkfOcvRpipUXZa4gshJMwkudQvZyWWfphmAwVlG5Ni523NM6wmv7vFd8HFuk3aCK5CZvo7WI+2+k1AKj7NWvOL4WQr+qFZvNwBef3fHNXzimrsNkKqVT5r5kgftm4Oay4+xJy3Zt6W4Hjs8MB1HgC+SpqSoqrelVqMX3gNE+tMP1Fq89wxCyrDfbLavNJmTZKqjqkCBiKh01To81OybTKevVhsOzCdvO4oHVrsKYHB8Wpp4EvOid0eJPm1vpYPnb4OqdzAzLm4Gh81Q6uoe9QXv9lnvqnUdB1E+OFP/sNxR/51PHbkhfU7o8M2Mv4vU+JLSt1z1dZyOT1lSVYTKd0NQ1CoP3KoRAup71qsPZnsmkoZ0o7ODZ7W7YbndMpxPOzo5pWo/zm7DBv3r4eRCFO7WqFNNpzWrZUx/Htsnp1EKtidbsn32q+NZZ+O76esf11ZanHx6hFHz5xS2ff3qL957D45qzsznOW7Y7mxQ9ydMQC8Cm2GwATgnMJSeWlR6nlEuhQpKpRsX4pI+CwY2Zf3zN5eaGR+894vPPPucnP/mUk5Nj3n//KbfPn9N3Q5HgFqwsaUCV3YxxPlRW2kQZGgujbOlH07YQpEKZoh+IYPV5zMnEH1v1I9fAzzjK05SKwh5SjL9M9BMPhUKBLly2ipFnBeTvQgHcY56iQCCKgtbB9R73qSTr5Yz+Qjnae/VU9eIKRSDOQ1ZSRhpVtjZ9cX/BA1D5WgjW5vXmnF//jd/kG9/4Bn0/cH7+hrquWPd3ScgoPwYwGrmeye8lj5DS2SDwK5qqwhBc5IO1KHrsEISydy7lVXnvo1dG0TQVs+mE2WRCW7cpyc1ojR083dZyetZEyzUrQc650Jbb+2yZx/dOnhIb9tbgHLqIpyunktKhVaiMMCbwaOvCWL10xIpHAtMS+kn6XBHWdD6Nz8d7h5BB+KwfBpQBtMHGFtmS8yBKfAhB5ftn9iq8SRR0lWknjsOLwihXhBv/VKMMviZCf+gd9x9O2awHtmvL0VELGrQKriaUp9IVKGhPGu4uLdevLH3nOL3fsjisA+iOMoAKICaRUIN7SIWsUZe1K0vopd7bgc1uh3OeqglxKVOb1NbWxnjj4DbMZve4vrpDccAwOLxX3G5qTucZtUmrjNecrI/IeLM9JAtMYEJe0zQaUys2a0vdaAZrqbTDxJIXcaKWJJGyURGFI3yKh8dH8D/4U4r/5Puh3W1+YGbmialF4bZa9qzXXQCImbc0zRStKvrBst10XC/X9H2f3H2ycQDu7jbc3YX3apqG+/dPmc4qnNswWJ82SR77+A8RjEL05bmzWcVuN7Bc9szmRYOPdH3eSKfTEEterTpev1ry+PEBdW349MdX3DubsrzrmM4qTk4nOBcwGATrITQP0YBjsON2rp7QMwFFKjFULuNEeEJLzNLVKEmpSrm0uTOzy+/++vZLfv2jj/jog7/AarXm9u6WVy9e8eDwKZ+/+lHKHdA6eFS0MW+jwyIWdLaeBCQm100H5it5CcHSBZH6Kv8aFQSSUFKxQZOsYiHL3jKuUs17eZIIXJ3xKjQ5C7p0/2d5WSglyQ1NYQ3la/Lv2epm9HgR+EFoZNohKnFyblDwynCBzw+Rge0x8BzTF3NbPEOFt3ek7CVhlJ0F6T2UUiwmx3z+2Re8ePGC4+NjHjx4wOHpjP/qx//pSFEpwxlJ4Sis/LxeApJVRYFf05rQM0SjGLQNP7EYNG3dpHsMLlQjtXUdrPx2Qls11BHvxKggoDfrARNLYPe9HSoJzEJJthHmPCZM21i21dQVWmIjbnyfqqqoiyZWMtc5jBbWP7Rb1qlyIbFbP15KmT9tivwkFcC4OtuDCpDBgU9Xce3knmFvlbSWlYtQjZE2k6y7H1v2SonCrEjVXT9D6n8thL6pNPcfzri93oXY/vGESgUr1yifXFLWeq5uN/S9Z1ZXPP7ogCrOgJbYeST8oR9wNtTYG2MY+lA2hRuw3tG5nl2/Y7PZMgxDKL2L6FpVhNdVKFwU1uvtmrP2caibtgalQpLdYKGupA5XMrxzq0kgMcuUDCLaJtA0oe2qU475geHmumMyi2WIxlA5SW4Sss1apPdEWNecyRwShsKfs1rxz31T8x/9iWM3jKkyx6Wh7x3X11vAM583TCZz7KC4vlqx3W7x3tM0DW3bcHS0oGnrUDNOiIPZwm3nPcwXLd5vGYaV0HJM9S0UltJNWihBe3snzevBYcvqruPqYks7CXkQpcvMA98+UxxNApzzqxdrTk9nzOY1n392Q9saHr23YLcb+OKzW7Yby2xWUVV5CxkdrHlblGsBASvAWbyKrXG9DUlqhVWX3IwxUz+23yneYmx5Ury+tSGE8o+/913ubm85PDzk8vKKX/mNX+BgccRqE7wTBhPquNX4rgpxXRfjcRmv3jmb/vaxXFQphRFI2ndoY8lSTqVpkNq2FpZpGT5wewwafLKc95PiRBAoMuOVtZZ9PJ6voPgKfv7oGpU9Bcj9kjnnUya9jlnhYqGVQjtdFy1PUaDefbwdQhBlYz+bO0+Xigpt3sf5vEIyKEVdNSzaY6aPD3nw4AEvX77k937vH/Hn/+KfxvqhUBZkc8ntJXGM0f21IsXAjdbUuopx+FDtpOLaDgwYr5lULRjJm/J0fU+lDNNpS1M1tHXANqlNFZKkIy9Z3vYsDusADeChMhqriTgVRLd+nq+h79ltd3gEQyJ0W61UUEQSvgABXMhQZOsrhbO5FbY0MxuRTLG25Tw7H4xBWStRqEVuYAw9A6VnR8oDrXdo7zFicEWaUdEAEi9Q4k3C14Q2IzBXSSeZbhl7ib7i+FoIfW3AK8d0XnFxvmUYfABN0TqB1NzcdLx5taaqNd/45gmzWcj67ro+Nj3xydVKXDxtgms64Z8rT+cGuqGndx1d32O9o5nEjntR00pNZwBDsLqX6zsengYBhwvxsIx1H99DRbfr3q5Pwt/7ZJ1LzFgiSbWvmM0rbi56ht5jK3knTwTmCyGooi7Xpb7vqrAe8uG9Z9HAX/mW5j/5gaezhTYcv9/tBm6ut9S14eBggXM1lxd37HY7JpMJ9++f0k5qlLJ4P+B9j/e7lJntCVqyNoomar3W3RXCMGacWx+R1MKMZOIuBH4af9LLk3CsDBydtNjBc3e7Y7XsWSyCNVIbxW99oPj4nubmZsuLZ3ccHU04Pml59sUdWsHDxzOMUbSt4cnTBZNJkwSouLJTDXwZ+42NctChFK+3oSuiJIKqOFwfOYx1LiSFuiF21Bu3PS1jxyJUBnput5f8+q//Gsu7JW/enPPy5UuUN7R1y2qjkhtZmsokhuZD/NnFxivZmvHZQiZ2irTi8vSZeZaeo3SdSmsijoAkR+U8MoMTH5YIHqE9N2QLOnfHGws8EZZZGBfeE6Ehn+lBPAHJKiM/Ux6mRSkRD1gMz5TPcy4umsrVGClU4vP9S5jjcI0k6CmZiIwfkMg752+MBHR8y7e8dbJy0Spt6gmNbvmD7/4B19fXTKdTZrMp235NN2zjPBSUtLd/xKckwkiJW1+bIOhNlYwqUAE50zkMFdNmQquakMc0dIGnGvAGmqoJ1+pYrizud6XwDnZby+n9SeAJ4ip3QQGVkkXjDQ4beKXRNE2NMSYhpdYmeFt1pWNMvQ+teaWqSwXhP6rScKF2phSeoV1y6G+R9l7B1yHzYpnCYbCxBpb0DnawwVNbK4wdGGzIgzA+9kjxEu6LdCTK3T5tFmMoAZjeOr5KzyyOr4XQ9z5YUnVbUVWa9arj+GSCtZ7VauDizRo0PH7vgMVBg9Eqtbu1znF7swOvWBxEq9kGZltXNV4F7PzeWbpIxIO3DG6I8VkfwB28lARmaz0woaAZrjdrdBWYa987lDL0w5DWKMeBi/cqiErarwIpLh3KgoQNqNCMZmHYLh2TWcQM8BbndIwnMWIYWimU0cmmLC1fSSjUWnE6V/wz3/D8zR84HLHdpQ8Z7DfXWybTioODI1bLnuvrC5qm5uHDe1Q1WLfDum1ibkqpBPQSXzK8qc/QxVBYdESPiQ8hhJScg7jHVEZwywSBNB4ZMTWgqoLVf3O9pW8dj44Nv/MNw7x2XFysef1qxdn9GYeHNXd3O7bbng8+OkguZY9nNqvj3DtKNmm0ShaDVG2EtsMB+6C3QWEcorcoCIMct/Qul3+GUjybyi+F1hJJ7G3u9e6W169f8flnX7I4WPDrv/7rTCczqmUTrYhQ2qRqsYDGdCbJRc6FfgvSh14+g5CYZiKYlDF6b8qT5EhGclAu/MjiCsqxKsxjklI9akfs8zW5IY1PSkoJCS2eieTCd1nD2OeBo7DBvlEtCki8H2TFSlzeY4EbFASJu4rgFMWCNAyfLGipLpAyQ4l/jCxtld9LHuRVgGkWJX9vASnzPQ4mRxhV8/HHH4ccJGdRleX58odFB8rxPcr3UmmioseQGMdXhsZUNKaKnwV3P8pTqzq5pL3y9P2A1obB9vQEGqqp0n00OlZCBV653Q5B8a/D9UbAa+Lcehvmq24MuDrQrFe42gcvq1LUpkJFwe51yJpXqLCPVPDYSs6NYGjYmAz9LmH5lmgdKUc5lq+iphxIK95LcDCcA50VHKEJ712AQw+aIajCnV8+0hcbInlX99au3Ig/3cgHviZCf+g9283AdKKZzWrOzzes16HDntKKe/emHB5N0DoIXec1g3Uslz0Xb0LZFR6qRjObVaAVpjKgoesHtt2O3dCz7baoSiXIXRsb1wjQh5T2GaVTVisE7S9k4Xe0bctmvaM5CEWlKv0z1iTFfS1CxNoQAvAEN60y2ab1UXhorZguNJcvBw6S2yq7rgKG9fh5ezfJz47jEnjVBweK3/lY85/+KLjEhsFxe7ujnVQcHBxzdblivV5zcHjA4eEE6zYMdkjeC8i1p2KzCOP3xVg8jEDCgIjjHevDKd2s2U2a9e/8OskKUkUMXymqWjGd1Rz6LX/5mzPqyvHm9YrLyy2PHs+ZziqsDcrgfFEHdL1krRaWqM/ZvGJZCnqdMK3BWoa4foOz9C5Y+il+SuIlOIJiN1ibrH3nxkw+KAeMlBylFRfL1yzOjjn5oGLa1lw8u+DFy5fMHx3yhucF8yCZxOLqhhgbVyQBq4RmfIhvKhX2RFUVZZblpI+UNCEemZM9kJM9DpsFbPguWczFeOSBBZlmHIykEI9LzOQxOVO9/MqTwg0FnXhIcWBZYwFVEs+SzLlGPChFTF4m2Oc9TJweFWvupfth8BDkARcOiWJ+ffG9KH7FCVHgiNdGK83Dgw/5r373H1FXDdvdltPTE+5/cMDrmy/zZXKbyLfCxypZqUCuxxfcE2OodUje04T4uOxvgYquovfRaIP3jl1vqEwAz6pjPL2pauqqjgI4hEKXtz3zRY0yiio1FCLw1iHQhsZQR6veoKl1yI2Rnigqlr6Jgj7o0OtEsEG0ysqbcx4/9EiYSPtc+QCx8sJInf3brn+hfR1pQUo/saR7+kjDOgK6iXdMQnc+evYkYZdEY7y9X4sSzZRfInkjouT+HFY+fE2EPnhefLGhqoLb2A6e6bTi/oMZ80UTN2QoiVMqZPq/erlku7FMZ4a6Ntxc77h4s2P6NBCmw9G7gV3fsbM7dkNgwtrpPPGUNfMZv1+Ad5zzDD60eq2rik23ZDqdstlsObw3Z3BLtHY4F8an4nJIaVCZaGOtixjvKoUAhAF4pBmHpm7D59vtEBEEB2pdpSYeSfCnmRNXvQi1Aqc8GURBqD059vzmo57/4seO9SbgGMznh1xerthuNpydndJMPNau0YaUTLOfiVyGCMb2hS/pu/ACZGGe35tRjTDFJVmRKgRRVDggdD/+rU8qJqsVl+dr+t6x3ViePFkwmcY1gFCD/940oJn5AMQUxl+GcaRbnSC/5ex9G7vCRVsuXSteJjmcs7FqJFgGQ3Tt21iWlJhBwe+TsRyZ/qZb8f3n/5hhsJwdPuKoeZ/z8xvOnr43sm5F2ZJ1hgzx6iMRlJn6LuZamMok5SdNarF0Ip9GK+HFAteFoGV8CLNKwry0WqKwLTwAhfmc5iHNczmmqCRqyQUpFYDiZ1JK9Pj9ZYJFUSytqZxLkIfl0zyIskMKX+Cz4uEdYT4Kz0i5D3xUJFMXzGIvjOcvfydKs1KKST2lMROGfuDjjz6mbVu+973vce+9g7AfbZ8sVNlDWdjnxVEQG15F/qZMBNAJOULiog9TFVzpWks9PRgVPHdu8CHvSAV3fV2HzH+jdKKLoXcslx2PnsxHBoEo0iiCwukcla4C4qoxNCaPt66DAiLvFLxmFusqXBXOE++l946OIdKMJpsEcT8oFao9xHsTFzfxnaTgqgTYFPI+PN76gGGhYifKShIQ4//i7857KS4smiiNNOO8EDDSZ0efF4piykX5GcL/ayH0daU4um84f9bz+OmMxbyhjYRmrePqckc/OM7OQob/ixdLJhPDfGFYr0OS0mxecXfTs1oNHBzVDN6yGzq2/Y7t0DF4Czq6oeNzlQqWvQaICUQBSlJHYAWHUQZfhfKN5fqW6eQxtze3TJoTlus7jHJsOpMYiItuLBhrcILMJeQmlr+LLXc1ouUqdBXiY207YF0ViN/rENeKo0+JK0osHJ+tV+F5hR3qvGO73fHerOebi57fXzYcHR5yc71mu91xeu8ephnwrg8Cf8TMxswrWUujVczSLBk4GgJmecyILpm9JLaKlVNYa/JXIU/iIzxnc8V/50PPQau4u53xox9esThoePL+gqY1SfjsdqGOvpnkFrTeZRhkyBUIqf69Di7LIC98EljaR/x/F6BGtR0YxAMT80l0LBmSMM7gBXN9Lyms8FpIuEbWUTw7m37Jo8OGrusxrqE2Dc7t4hTkOLd4h8bKWLac+z54akzMbRm1oX6X8E4MMit2IbEuni6hcZ/XbYRGJp8pijVVZIZWesKykJf3SN3lvAjCQtmL4QNnx14HpWLYq7DoUka0KlDbivnB5/0zEgAFnRXOshG/QPs4D2HCklKSJibvuXKek8AXxaLYm7KHHx9/yNnsfWbNIb/yK7/Cj370Y/q+4/TeKYPf0g9dXFuyMhXvXeJ4yPukxD3Jste5F0YKd3nwfmDobdJ8FKI4hnvUdY3WAZAr9Z2ISvNmNfDm9Zq2rWgbnb02cV6llbQoNpU2OHRMIg1KmlEmNs8S+vB4A95XIYGWkJMi69sNA5Vx9Davzr7CmZyg4vXBpzwAISkJx4inNRhgea0DOmfwJlSmSvegwMcItDvGDxknmaq3vsthgkJZU2+f+1XHvv7wzkMpdayU+veVUt9TSv2xUuq39r7/S0qpG6XU78f//o/Fd/89pdSfKKV+qJT6V4vPT5VSf1Mp9YP486T47n8fz/8TpdQ//7NH6KkmnvmRZrXssGpgN3Tc3Gz48otbbm52aA2vX615/mwZ3beeu7ueutaYSrHbBib/5vWGbd/T2Z7d0NG5HutDqZWKDDK12JUM1hjnaquGWsVEjRgHa0xNXVWxTjWCMRA0TBQY7bhe11ink3GagX1U0qylG5/SAioRt7yODVyUSqV+zUQz7EKpTEAMFKsxhiWcS7FiJTeL8yiMpLRgrHNsdx3r9Zbbu46HFbx/dsTd3YbtdsfJvTM2vuHizrDpK4IOKxbEmJmMTbIR9x0JtHSZykxdwE7C95lhId6AJOELFuyz1XU8gX/uG3DQhqfMFzXHpxOaVtM0BvEi9L3l8mLDdFrFjPyxgpQTNVWqOhBmnPdd8AJIApSRNY2MUKwSFwdtvWWI+SLWl0lFWYDED9LnWXgWtdRa0w8dVvc0TcNm2TFtF8U0q/RT6szT/QpPxtDbBJBjquotsBbn839JIHlRGLIClrt/sfesounMSFEohCtqxMjGPM2Pzk0hnPJ5SdHMSnTOzM+HLt6tLE8MT9mbfyiAYcZzmmcwK+f5PqNhZ0UlWZpRIIggjWPN7tzsVSy9NqKMzpoFD2cf84e/90P+zn/+X7LZbPi1X/tVvv3tb/PJNz7i1e0XDEPOfk/dFJFXj1YsJHezMSLwqwQ0lV/Dp8qfruuTR0f4i4/NxiQs0NSh0qXcB3ZwvHi+Yr0cePBwmnpEyH61Q2ikMwwWb11scxa8Dk0VeG5TNanWXwBvBMdfmqTVpgp8OCL/iQIzUmITqfhcqeLyHhMhn0JPxYrLZ8aEd61MhTbFXCAg26T1HPOK8fOTkrs3plLJTKGe0bjyfz/t+Hkt/X8D+Bve+39BKdUAs3ec81947/+H5QcqSLn/M/CXgS+B31VK/TXv/R8B/yrw//He/+tRGfhXgX9FKfWLwL8I/BLwHvC3lFLf9t5/JRSb99DbnmahuH45YBoYttDtHAcHDUppri626EpRN5rVcqBpAqPvdjFW7j1Vo+h2lquLLbPTsXYYrAydrHlhaMJDRPsK1o4KMXdrUVpjXdCtjhdnvPl8xdHRAYPboBU0xnG5qth0hklT1tGHbHCtFdaFe4+aVcjzFTED3wViN4a60XRbh7OWrh+ojaXWDqc8ymRN0UQYTcmOTQImIU2JABjYbnas1x031/DcPeTZ+Ypd13Hv7B6q9jT9EmcMN5uG3WA5mAw0ldyn4JojM2v8VWm++fE/yaomMkR8zkfLHpB4Tzm14LQKxe98Am1dZuManjw54Ec/vGK97plMDIN1vH65wVrPg4cziGusI5OWLFulYqmc4L6bEFMEif8WliuAV1ngR+YldOO8T/F8F70JZR5HsAjzvEmJpY/rowAfFVKtYXADnVsxmbSs7jbMTg+4Xl4U+O0imvL8lEuQm9SY1Klu/1CI9R3+Cl6iPOlvWSjFLyXzTG7weIhnY/8eYY0zOmXwgmUFJumuvlz34vklHRa0PXpOHFdKDvRStpjfWnQj8ZCIhVh6YiiVhvixVuR2saW0FUItt8ieMBIFUyzbpBy53Pho3h5x/vKaxWLB48eP+If/8Hc5OjpiPp/zrV/6iE23Ti9eVghJ4uJ4i6pI77G5WKTlULIcIMq9d4HPRXDzqqkQr1PZ1aSqRHkwyZ0flsBze9NjTIDcvbvtuXe/DXtN56qdoQ/lrVrwGQilfNKLRMqxS4EoDCAWOkdwttiwSMWOepLQKHpnoUDLGitVeHKUQpkxuxopBF7FMJmPyKJBXhhTjE1ERBLc4b1EoQjDGeNZ5EdFhicNjX5Oq/5dx88U+kqpQ+CfBv5nYaC+A7qf8/5/Fvih9/7H8V7/LvA/Av4o/vxL8bz/O/CfAf9K/Pzf9d7vgJ8opX4Y7/P3vuohHs9u6NBa0x4qXj/fYrRicVRxd9fjnKepFbb3YKBtDLvOUlWBSVtnqWpF1wdt7PqywyxUSLjCJ2YgWqJolQpFFz0EVa2y9ZZqlAnofdZTUTMxC9brcz748DHe39A2FYf0vLr1XK0bTha7sVEcBUt23Xgk+ShrdD56CxUmChVT6cBgULENZQApqtjTFkVyFIRP/NP5wFC6vsdZx64buLl23Lh7fPfZimEYuHd2hqkGNDvqJkAJb3rP7aZid9dwMLXM2yGXJCGCQn0l0YogkwGVm0xcaNkVO54ruYHEzFTyWCjaKlj4LiavKZVjvvNFzfNnSx4/mXF5vsNax4NHM6paRzCaWLoZH+CiMJB2nZWJ8e7C+hQ3pVSIiOJQmSqglw1DsqwgMxwXG/mkkMFeVYf3jL733oeMellHFfDN77a3zBdn3Fzf8fDhEaHXurT7lZkOQkuUR5zUQrsiMW3kN0FCQaKwlFZIobMV70RBv2+vtVSkkOg5v6cIG8kxUSo2bJKcE632aIsgGGXVC0+CKBgjZUzJlVD+VrYflp/OelC+EPZCw1nYe1HGROjHlw9UnFupBo9dHpuPD8/u6dGwEk3L03z8J7XdVaHx0oNHZ1xfXfPd734X7x2PHj3kG9/8Bufbz9kN61RRMloKtfcz+R3CP6lqSOZNxaRUNLWuqY3C1CYmrmbrVRRXY0wqqSuPvrPc3uw4uz/FVIpnXyyZHRjqJig4MochrBmBqqIQ1VqHhFmlUvfU0sItaTTMbcjmV86Hbn1a3leRSCDpr3KPsfI4ou3ic61VRnf0ofROzhHKNLFPhYKU5C2eXC1Sv1iPfYGvigeLfpjIZ6Ts/HzHz2PpfwK8Af5vSqlfA34P+N9671d75/2WUuofA8+B/533/g+BJ8AXxTlfAn8u/v7Qe/8iDvyFUupB/PwJ8Pf3rnmyPyil1L8E/EsAZw9P6J1F41BTOHio6Vea28serQxVpehcsOwHGxi9qTRdZ6mqDDDjLejKMTkk9jEPrhmJbRkd3PXiOlpdO1ZXcHy/oo1udu88Vtnkth06i7Oeo8Ux2/WAMYbZvMLGeP+8HTg72HC1ahnsDq0LYeWzkJafSgUlRSudy7jwiYEpwJhAiN55XOVSvXcpQqW6QGLvJTiFbPR+GJJ77fa2Z+cP+L1Xlr7vOTk7wyuLdxsoLMh5M9BWjptNxc26ohsUR7OBymQNVYS/93scSBVWHqT2qvJ3aSWm2B/hC59kh0ogMzkUALXJcUiVNozj6nLD7c2OrnP86AdBEfvw4wOaNibjeOkOphKksxcLo65QKXNYtHcRgC4pfz7lggROUFWGiWrRg6YbulBOtwc8EiyLccw9vmrII0mucrF0x5rB3fqas+MPeP7sJfP6SRL4Mm8qWo6GHC4Sl6a4WKEoJS2Y0VuJXz5fi2KEdibfl3ODB6+JeAZRgdBjxUCUsrfKOD0JgEeYYCkhpV99JOQiWXHMGMu/xd2K2jN6kzfC7zXlCeMdldXJoCEldYWPMppkWfaXFJAo9ZUicXKZ57xfswIhbxsYv4xZcbV8Tdt8n1/7jV9ju+5w3nL+5pzLiwt2zTYKQZUsRR9LjMv1SR4zsS9i8vPgPVp7wIWac6/QTqEnEVMeKZ/M/UFEyEuJnNxf9vfNdWifuzhoAM/BYcPrlxsevx/wMJz3MRQgIZCI56FymHPfE5TeofDWpDVAY5VLPXzE2PHsrZ/wjTgREvbyecHyAhSKpFYa5YICrnzIHcEHId80Vcr1SmFasifl5znSHhfPng+WvyB/KpVpeii7pb3j+HmEfgX8JvAve+//gVLq3yC44v8PxTn/CPjQe79USv33gf8A+BZjfVUO/47PRu/381zjvf+3gX8b4JNvP/V93wfich5jKibHsDiusTvN+tqz29kI5mDodkNa2MFatIFh8EwOFZNDw6CG0DhHGvXoYOXXOsSGlDNcv7A4C+9/cEBVh/vUOmT9O20CRG8fhHNT15wdPuD2zYbJdEI70azWDq9DYt3jow0/eNVwu1EczWIyngdbqJqBmMeYkC7FfgurTOmgyACDdWinU3/2wQ7gAlCN5AAU8xmu19kalnKx9WpgvWr47u2E5eqW49N7eA213qaN6YuNVBvH6bxjXRluNzVvbhuOZj3TxoWkLp8T4pQseGHVp826Z8pnlhcOnd49WMilep7KrAjM+tFhRuLyPoAKPfvyjt124P2nAWp3eddxdbXl5Yt1LN0zKTmS6CZMAt9USSDkOcxzmZvKkOrvbYG4ZYwhVBs7fO+xSqNVcJHvxw7FchHh4IpsdqUYQ8zGo7NbTB0YX7dxzNo5q+0ydDocbJ7HpkrPcAl8JyYYGYk7FwKS8ftK1z4Zi1i/TrDGs3kdXMSFpS7vFJKwxnQYfo9emZIm1F64Id2b4joJv+T759PfgdYX30UhXrqsjPqSsOU8xQi7P5VryTN0Ufki446u5ZTMpXJosPhnNMfJW5CEiyg6opFlZUJAt378o09ZLVe8950T+oML7qoNry6/KN5JBEe0hr+CG3sfGmZVVQQ7kk55XoEF7UUA6qicxV4bXpI+834r5wFgux24uel4/GSehOu9+xO+/OyOyzc7zh5M4t7RbJYDVe1opzGREAF8GvOv/aN0oSfeERVE70l7WY3oOSqkMbs0KWpx+VV8bniAbMD4T8zxcNaz6XYYQh6DqUzAI4jj1VpTK1PMR7h5iS3xsyz33Xbg9esVq1UflUvRQigG+tXHzyP0vwS+9N7/g/j3v08Q+unw3t8Wv/91pdT/RSl1Fq99Wpz6PsETAPBKKfU4WvmPgdfF877qmq88xIIJfdoUWI+uYHpoOD1tub20XJ1v6TtHVQVBNWkr1uuOqlEcPlBQ2dDJaRjShlAqZF9XqmJSt2hfcfGqp+88k4mhbUxkOqGlr9MK53ToyIfG1A0Gw6RpWZkQZw/u4goXWy5Wquf+wZbLVcXRLOcRZKt3HNNNlj+ZkaA13sds2yoQ1dA5TGUZzMCuDwEpZ4IgN9rw8uUlXden+UsxuZigMwzB2n/9csN59ZQfvXqDMRWb7RY2a7oqaMXz+TSFSkTQaQXziaWtPTebistlw2IycDgdgMKyKoj0nbQ6EjgUGroIw3BoLaWU8bKiFKk28Ovvhc+tdVxdbXn9csXBQc2T949S3K1uWk7uTbg83/LlF3e8996cxUGLbCoFBTPzWFsm1oTUdIGzlQ5aNgLsWBtK8QYrISNStzKjHVqHvuGSxKdFKBbWYJJVWcNDpH1pdQeFb2DrlsxmM5Y3KxaLI1bbZWpHCn6PaWavkql0YU2PBX2pXJQhFlMIVmtd0r+CYhDMK0GkQwVLGQeqaP4jtA3iOYiMWIsyJ++rItNPXLKwTkVgkhSXssROnlEKf6EjcZs7L938yFgGShAXs8UFMf+heLaEHbwvMAVUFtgyXlXQvCcLnPJIHp9Iz8AI2ne0XzwcNKd8eX3F6dkxl8uXvLr+Mnu1AInf5z2XpZncSxRZT3i28wHgRhGtUudRTie3vfA+fDAWqsok678cX8nPLs+3zGYVk4mJ3rNAjw8ez3j++QqtFO3UcHWxTUBgWilm85rDo4bZvH6LH37VkXyh4lGKn7tI7w4PKvJbV+TgyMlJCc/zjNCKrLsLMNjOerwN+6qZ1DRNSOIOJBPd+qJQK1E+JOcgv0vpGSnnb7eznL9ZcXOz4+RkwtMPjmhbk4wuoaER+Nk7jp8p9L33L5VSXyilvuO9/xPgnyPE5MtJfwS88t57pdSfJShjF8A18C2l1MfAM0KC3v8kXvbXgP8p8K/Hn//P4vN/Ryn1fyIk8n0L+Ic/a5zGBLdKFRGfqioI6WnT0rYNB08000nNi2dL5vOa6azi6nLL6f2Weg6d7ejswGCHDMergis1WPgNdltxfT2wmDecfDDh9cs1z5+tePBgQtM01E0VO+05KqOhrlkuHbNpg1Y9Z/fv8fr1G1ZLx3Q+ZbUKcLOVNhxMej6/bBlcR2MCsRqjUwldMddhM0rTGor4pjcp7tVODMPOYhoLdIXEFKL2/N2/80f85m/8NlVVjTa9VmEFmyqMo3/P8ccv4exsgQh2CBnhV5dXdF3P/fvHBSPLDC5Y/T2rynG3qegGzeG0p61zhvpXbVmflJvyyNeItyBjYJNa1Jbhgz/7xNNqz27nef1qzWrV8fi9OZNZgEL2QxDEIfcj4DtUleb58xWPHisOD9ukGIgHRNYiC7tsGYb4f7B2iRaFI+ZWiJs/xuuNMVTeZ8CeyKRSaWCUBWX2ri/fWzi2E8U3x/vX3R3zxQHLuzVHp4d49yXeZ+ARU4Q8gFGtsNz6XcfIriis1KQ0mNhdUlwB8SqtwgWp7732JJz8qACGd82VJuLS996jDCnHYZ8hKnJYp1TEvFcRfroQvCMjSyUMi8Axg5dt3yOQlRE3fnYxTfstcEURFA9dUkp9mrhibQv9tvRqlIpXoRSoYt6AUEHEnNXqCz761hM+vf3hnjUZH/uWVJP9GpMNkzFRJFpCKJHzHoWhbWqaqkkdIEPJWcgpCtDg4d0l3p7DcCGMul73PHpvHucj0GzwuCpOz1qefbFmtqg4Omo4OmnwPiRlb1bBAFFmw/37swDm8zOsWkUwyn1UHL1ozzEhN+ybyNOM2vN8FEaEfOLzd/iAcumcZ+iiF1UbZtMJk0kTsANiLkKaU1RSMo1SSeCXeSSjEfiAfHpxvuH2Zst80fDJN05o2+qtffDzHj9v9v6/DPw/VMjc/zHwP1dK/S/joP4t4F8A/ldKqQHYAP+iD5Q/KKX+N8B/DBjg/xpj/RCE/b+nlPpfAJ8D/+N4vz9USv17BMViAP7X/qdk7kPUjpwOWlalqXTNpGmZNKGcw0QN/cGDObNpxfPnS66vdzx+OmN2oNnaLsS9hWlEi1e54Na3G83N2lEZy+m9CYeHDUopHj+e8+L5isuLjifvT9J1eDC6Yrmx7Nae+2dT6koxO5jSNA3nb274+PAQuItQuIrWOKxTrHaGejZkFyskQhm/c/oNRINXxHrYivlBxcWbnnoeWzzGeKJPbEoxny/4S3/pn6Ft26+c28E6/p1/+AUfT9+du9k0X3K3fDUaWLCqAgsPWi0sJpam8tysK65WDQfTgXlrc0KKXO/FJgmbUxXMsfQKFDpMKm0uPbE+nvDxsePRArwPaHInJxPunQV0RhvBOsJ4c86EUnBy2mKMYre1qKPMhMV1XDJkGZH3Oa6WPCZE174N7XelIgR8AmjRWnG+mfLiVvELZ3d4HEj+AD6VEL3LuhELpTxEKN9tb3l0+IiryysemfdAhS57Ke/BBWWklFySHFfG70eWfiE3S4u/HJNkXysUXnIJXPSMxPOLPnVFVne2tvat3vzw8dy7KC2dZLITqm5kHXU1vjzIvNLMTpQV7+OKdVYoo4tEwrBvxko4ce/lSLz8q0TBUYWFrsieByhi/3tvqYTefUHbmcYkPCLPPZges7rd0jQtvhrYDdu0buqtdSzmnpz34nysUiELINlHoUZdxSTm4Gr3jlhmp1Pyp4oWbPCUBujgcpcEpNSBm6sdpppQVbHvhq7YbCw31z1n9ycc32tomwrrHUaH8trDw0lCynz1YsV0XnN2fxLKbYv9IIctDSNCuFQ8C6nNtS/mxI+VxoARQubriWbCL6XSZZ0LZdttQ91WqErhlE+4KGFPZSwBU+xlvZefQKQd5zzXVxvevFnTtob3PzhiNqtJLrT/FgIffk6h773/feCf2vv43yq+/zeBf/Mrrv3rwF9/x+cXBK/Bu67514B/7ecZW7gAtAsa9bRpaUzo5NSYKPDJde6Lg4YPPzri/M2am6sd262mWfi45lHLJcypoWZ3q1Gu4uz+jMW8RhuVsmYrbXj0eMab1xtePFvy4OE0xCe1Z7u2XLzuuHdvyqStIxJVx9nZKefnl3z08Rl1XeOsjUTgaSrHxZ1h0fbUJmNPxzkJ75o2u7SfFMKNDJfg8m9nGrzCDkBtA5SlECB6xDQAnj9/zsnJCavVkrpuuLi4oOt2/KQ75MfPXmGt4/j4mNVqSdf1HB8fU9e1DCn+LEp29mhSKWgrx72DjtW24m5T0Q+ag2lI8hOGJlm3Yxuq0GiLTS2MUZEtucTQvedwovgzT31oLxyZV8BoiGEVoyOef7iZlDzKfB8dT9Kz5d289yN3dLn35GdA1Qt9Dzob8kP6CKs7WIvgpOvYAfLz65rvvmxxHiaV55OTZUj+s8KoJNxTitoQl3RWEuHEAgZUaMe73t4yPWnY7ToqP2HSTOiGXY5bF1YHhATQJNzSNGYh9pYgFqNJBGc2HkeCKyhAFG5L9rWGaB3mTH1kPXX2HCQvP6KkjY32/LmKiXf6reoHUToo7hMdL/nm6XyxwLOgz2v/tgDde0oqMRu55PdoNH2WrOpykqNFmqR+HBMq0FBcFOcVB5NTbp4tOTw8YD1cJ+s6gMFk4fXO4cZH1aMSPQmxxIoELdnwntTCNWp/PlaxoEKSMQTlwTkwWgwSxS6WQz94OKPrLC+frbj/cMZ0VrHdDrz4csXpvQlHx81onDomy2oFqtKcnE6YzUJztedfrnjv/Tltm0XZyEMjKyWbQ8X8h0iDSitUkZ/x1WsRz2dsZAQPk0WpkKArbYGdD0qPiH2x9ENycITbVySXf0mkYt2/frVis+55+HDOwUEbc1kKs61UdOKHP4/l/7VA5IOQJTppJixmUypVhdiSCeAqIYEiuFy1NtRVxWRScbfacv5mw+XLnvm9kB0KIZ457GBzVzGbNtx/OKWpDUM/YK2n6waapsJrTVVpHj6a8+rlipcv1zx8OMcYxd3twMnJlMvLLdZ5PvjgiKFac//hKc9fvOLmZsd80dK5TXwDz8Gk5/Vty8PDNfV0DN4iGrQSyy4qKbbwR4krXClFU5tQrbDt0cbRi8AigFuUbl1rLX/1r/5V3n///eSe/uyzz7keKjYPf4XNZsOXXz7j448/4vnzF4Bns3nIBx98MFqDnIsgNKzEkEqbxeA5nA40leN2U3G5rDmYDjRmyIh7CnLS4sh0T0d4z6j4JCurGAuw7OB3v1R8dOJ578DRxcRKEdxB0Evma3bTlwxehhBa5rqUkCNPGSUMIaV8ls6HUFE39EHw24F11/P8xnA266mNwqH49GrBp9cTFMG9+tn1jKNJz0m7wTpIGhSQEttEAUkNmHTJ0xKM8eAsAxsmk5b1csfB7IjLuzcBBS5ac7miIVsuIwEfBfK7LW/5IlcZqL1TxWpXBUMSRSPrceEKyeQPc69BiwDfK6Hz+RrBmRABpJVCxwYsY7bt5f8ZZc2PY/KSoS+KTBbuWZPJPFU+Ky3FZASm98qKoh4h4Mk7CB3KHlHFnPl09r4FmtdEDJWpOeTF7XM++OgJl5tP0z5Mrx5rv0uLv9w1Kgqk8LmO3ggX+Q2hK5zS9N1APanxVnIfPF7nNfXOx7i+GRkWzsHrl2tms5qzB1Oc9Vycb3j1Ys2jJzO2uwGl4OikCS5z7wPOvilzS2RyiK2u57x5teH89YZH781TqE1oWeLmsiTJqxHpZnTf6M3QEerc+6wJeO9H3hkxUPChsdDQ20ivpJ4ozju0V+mZkrmfs/WFV6f6wfSs1bLnxfM76lrz9IND2kkQ06VXqBTuaU2FKH6G4P/aCP26rpm0LbWpaao6dl4qaiEhwU8CMQGtwTrH6tOOm5eWo/sVdQ27lWd7C2dnM45OWhTQ9z27XawQUOF5VWVw1mGM4sGDGa9erXjxYsXhYUPTGNabgYcP56zWPefnK+6dwXR6hNGa27sNs4UpiNMzrTp2w4x117CYuuQiBiIQh0UbuYa0qTJXjqh8LiSITRea6ysDky6U13kfGwINmFjyB6JZdvzu7/4uk8mEX/qlX8Jay0+uHCfHHY8ePebNm3Pquk7nrtfrr1gJ9Xb5VfHTx88njaM2PXdbw/WqYtYoFhObShZHwkOJVl0+poBNlZMix/SRKVoHn13DTy49n5x6/vR7UJnYTz0CEhmjk+WfLVbJWs8xXGtjXbAplQM5x6cY9ECokujkv6Hnet3zgwvDF1cLege/fH/H1hq+uF0wOIO08AzhHMUfvz7kNx521NoGZUBrrCTgeYgZpkBIupMjCFIJ8wSgno29Yz6fs7pdsXh0xNXyPExVIRFKS3asxAhVqZTRjB9XJcheUlq+U2keswQbH299EpUFaRmaBFy0ikOnskJh2LunhDjECs8oimGuykz7/G5ZOVVap3nISuvYnZ8Uo+INVNKQ5L65BW/5efkuIsBl3pIWU2jGYX6zkjIS1PFeGh/2kodpM0fbhq7rmB21fPryKlp/ktdChNn16X5ySKWQvItCJXAZrxROhTp8KUNzEWmv63pUrajrClQwuqrqbaQ7Wb++d1S14vhew+ACguXhSc1gLS+frzg7m9L3jpfPV3S70JCoqjTTWcXBYRvQMY0kXOb5u3d/yrMv77i+2nHvbDriO2UoLgv/uK4u04J3HjvErqKOAJUsc82+opcX1vmAGqh0aEYlXhyxvFXMJzE6VzOEJGo9MhxKRX551/HZpzec3Z9ydjYLSbUyjiJ0mMNvJAvfJUXvKzV04Gsi9LXWTCctTR0mV4hPmDcAvsCDjzO1vO15/XLL4qDGU7G8GDAV4CqePJkxm9cJZrXvLUMfb+XADT3O9QzDgJcN4eHutuPyYkPbVrz/9ICT0wl3dzuefXHH9fUOo9b0fc96tQKOQ9zJhjG2taUynpt1zb2DLcKtvA/Wo2ygUVZ14heixeoEIjSdV9xcduB1sFS9ZVADztmI8Z/n8ODggE8++YS/9bf+Jn/lr/wVHj/9iP/vX/uv+OBgwU9+8mPquubw8IgPP/yQH/zgBxwfHxUrICZm4Zr9irVSkISC1o6DiaU2huWupl8ZDqc9TS0SJ1tZyTWZ3QjpkDUtQyDFDKGU4seXmjdLx29/6Lk3U+jYzzskETkMpPJDGKOxyW2DVZwt6lIAOXy07kPPht4O3G07/vCV4bPrKdblkr9//OqAlK+hAmix17kawznFd1+f8GsPL6gMMQEwW7ZvldHJlETmoTW4OF/r7paDw8ecn19xVB2HMReJVcI+/N68pl9lCXwhdOUqmXOVL/IE5To61sYW6t69Syus5KfZog0rGNr9ZkUwuWDJay7AMzLkksn7t5SPzNQFWpvI/INbPApIleu9gwdl/C5eZcUhNMwav0f5LqUgTy7+kTAZH6JoqURvezkkQuNKcTQ/5e5qxXw+Z2uXDLbPGAcuJIyJfqK87Io4trh5lA8eFaOCJ1COxtTgY/Kqd5gIa1s3NbPJNPUECVbsmDZFkXbeU1WK+w9n+Jjn4mxwZ5w9mPH65ZrPP72jqoMwvP+wpWkMfe+4u+l5+XxNVSuOjloWi5qqzl7Kutbcvz/lxfMVs1nNbFYVNJLHEakivbsjGlU29Jjo+yEpMMBekyeVaDGvV84h0SqjbUY9Mc2vjq1+gzKQx5XGtyefz9+sObs/4+HDeRLm+wZQzh/Jz0nG41cx3uL4Wgh9kCWNBO7jJlQmx7YSQ1RY63n5YsnV1YazswmzRVjsq4stb15uOTmtWC4HLs63wcKypAYvIfNZYYw0gQm7UmvFpDbM3gvgEovFhNmsph8Gpq3h6YcHGG24vnG8em3pdh2KKnViQsG0Ukxry9W6YdttaaqcuS9KTGKyBf0lF60PVouOpXttW1E3Bj/UVFOSoBeNUOjDGMOv/Oqv8sknn/Do0SMePnzI3//BS77zC3+K2WzGMFiqqqLrQsOOjz76kPv3H6S5N3pCZSZYu+MtKv7K9RIGCNPGUlfw5rbhfNlwMh+YNjl3U5iph7ckRrm59zeDgPt453DAXaf4Wz9U/LPfgIcHAVGvtxZrQ6lR6GEQrL5oKMVHufQc78tQQDi++8Iybxz3F6Esb9cP/OTK8o9ftHRD9AREJpPeQRTQ+G7iCBQjZDvU/DevT/j1h9co1aUSxOBFSUkKUcAFWhQtX4QEwN3mhgfH3+Tzz55R+8doDBZbCFafYpRJBpAZSWKc8RsxJMbMJZ6TYtfhhOxizu7phClQeFaSSSvv76KVSn4PaXai9ViolyElvEcZnTH2ZW5FS5PRjgafGW8avXh85NUUb2lBnjwI70lr5+Uaefw4ESEI2HIspXrq88/0rORdiEMtAYEiLS7aY958ecfR0SHL/gLJ9cEz7q/gfGxildfX4VHBP5/V6/gimsBH3OAx3seqoJZp29I0deyoJ8m6bwNUQQxP+lwe6pyKfAp07DN/dNSyWVs++uSQus4taL33HB22WAvLZcf1VQjHzmYVxyct01mNAubzhsPDIfTLmB1k3pCgxX2ea1FUZYp0oH9jdO60SM5PCakTmaelkOhgU8tpUeJE4dGpFFfHEHN4p6oAGyrvJWMbBsdm0/P4vYO3oJh/2lEm0irG933X8bUQ+h6fUecUiQl4H9w2603PdBIE4Gbd88Xnt2ijeBITQKThxr2zGdNJw2rVU1eaxb0JVSQGY4L2rxRJS3UFU1REqEgdwHjquorY0AECcjFvqeqa3RaUuuDo6AjndqmDmezjeTtwu6m5WRvODkKXM2XiJtTBMi0lm2xQaQ8qhyZY+7O54W5pmB5qqMJ4K2Vi/Wg43xjDb/9W6KH06OFDAP7gbsIjvQTgl3/5l9N9Dw4O3pr/8/NbqmrK4eGMqlZAh3V9cjGOLHNf9KEnb8TaeBat5Xpdc72qaIyNnbSKdyVbd6pgl4xPe+t8olXtUVjv+ds/cvzORz33ZmGT11WYj3FcX6FUtJYirnbGYU/imt46vvsSukFxOtN8457nj15VPL+tEihSEPZ+PKbIXILbXCdmoZVCR6a07hq++/qQX3lwSWPqkGmvJJyQBazQu7U20YnEwlfbFd4MOO9Y3e6YNDPsrk89G0YCjqiPkN2heYZl7J7kdInnjowiMrMVa5PifiKcJSQicXMdXex2cGnvStigcODkgUDCnvfxd20kKYqkWGi1RxmekXBSUaB7JwpFzPmodMLAEIta5RlI7VaVKgZUzlZ8r+TqVSXVlDOaL3M+w/jK90q9vRC++L0yNY2fs1q94b0PHvDF6sdpvLpwDcu4SwCmvF75fk65IKQIfCdk6BtMHcBmJpOWymQQeq1IQq2c14T6iA8lwftKZFQEpLbfGMVkUo/HFX+vNByfTDg+mbDbDlxdbXnxfEk7qXjwYM5kWnF8MuGzT2/YrHumszrww0Jz92kG8r2Dh8JQVQ5vVHL1O3xuI61hv8LC+wgy5bMXSNqei7cudCesQ2OgqqZSYlCoxAOFfmRu1qseU4Vy6/JI1KDGf3/V8bOS+b4WQh8Iu1BBmViz21meP7tluxkwRjFftNze7ji7N+HopE2MRbQ+rRTzRcV8XgWEvmkV3D+DxTkbajqjBm0qTa0LiEmgqoMCIchRyP0J9dhtc8xmfUlTN9x/cIh3l2FDRGFtrWPRdDg/5XbbcnbQp3v7aDB4PEbpxEDS28ZEk8Fm1LhaVcwXDXfXFu08dROghGsdOk5tt2v+o7/xH1IZk+7tHWwH+M9farwkynlwMdao9yC8bm/vaNuG5XLF9fUNbduyOJgzn88wxuN9h/NDtNR8AqcoXffyjvOJZbmr6K1icBpj3FvsNCkSCSkrnJEqotR4XhCmG9FWtAfnDX/3c8Vf+bbneBo24z5TSuNSGmNE0NoAtVyc98U1DA688rxZKV7eNfTOopSNRqJKlnxiOiNlMf5URSdFUTqsYtlP+f7lKb/04CaEZ2J2tAwzKKCFti+KIR6iJbLcXbKYL9iuOg7vnbDa3aT3s9al7PgkHgoLVhKxJFYptBp0H0WRl5TnJTL98HeZZJjzMMQSFcErgl4s5eDVCPNhjHgACkKI49RSUmdUYryl0JTS0ahrjL0YunivKLwlEStj46s9jTKKMpWFyeie8lxy6Z+cmG5TWPJJdYsGisxfqcDnREvGY1WwmBzSb8J19VSxulySdkCpJEktenGI0tdZF+hahSqowVgqRVKiKmVom4a2aahiTpN4vCpdttktShtFqCqTaUa8C86lKhljDKYqyqTfIbBKRaFuQuL0/Qczzt9s+PzTW07uTTg+aZnNa66vd8zmTczQz7SarHv5IHqdpGGP9UAs4RX6Ld3wZWKkrLN4rjQq5zMU1WIhzFol2HZTeEP2wzXee66vtxwdTbLFXnyX9xZp/kVhTTRXWPw/7fjaCH0XtSfnPegAAvHsyzum04qnTw+5vdvy7PMlVa2ZLeoEtlIeynu63vPqxYrJtOJ+rej7XFstXe6cD2h7wa0VmII0URDtXuK34cYKYxo265oXL97w5Mlj2rZnsI7KxMzMKMwmjaWpHDfrit1gmImbu5DyEn8tbL3cSAaCImFDjfd00tDUHRWKtq6oVGgO09YNf/63foGuu6UfLN45dhvP+ZstP7htWJl7HB61WLdjuW3YDobFZGBWD8lyATi913JwcEhVTdhtLXd3K66vbri6dEwmUxaLKbPZHFVZvO+D8iQvE+8hxlKlPfN24GZds+s1beVGbuR9onZecbuuGKxKQv9gOjCtBWC7mKtkcQXmN2D4r1/AX/62IAnmTZgFltRt50z3YsR47/ne63jfeG+tNFWs+fQq0KKgfwXlKVr40VvhYx22bF0dccaJvctxcLGe8Nl1z/uHd4UhKV4fUaDCugPBZRmVLIViubvl6OgBy+WS+48WKHT0YPhReCm8U/xZ1JUn4VzWl8fvkrAuGWKcR8lYL0MJsh+S9VTkKHhfAB/pEuu+VHFLCzUwweTZUFmQeeTzMFAVny+ehZKZl4dUA5Rldj6uLTGGX+iaI0VpP6lWFL6AUJitRU/JmHOGf/l3UHpUEi7pGZFWRIk6nN7j+tkth0eH3HYXxTRlz0R6j2KswaOSPR2aCJCDwneeXmla46hVjTa5z72L49JGStAKYUMWSpUpoWZJ1m2K8zuXvANNHRQA6aa3N/Gj9ZE9aIzi4aM5h4ctr1+tuLvdsVg0XF/t6O4P1HUO7SqlQhVC8raF8r/U9jpm2lsUxPr99NTxFAYatTn5Tiuduv4FvcGFFsJKlIBYnZ941hgZUGhk6B3rVcf9+/O8VvJPoTgCeW+LMSM8QAyePZreP74eQr+wLJz3DEPIAp1MKh48nOHxzBc1H3/riOvLLV98dsdsXrM4qJlOK+oqEPVqNfDm9Zr5vObouGHX9dHl41JbUsn0VqhUOpcQxqQ5iHapll/ONeaQ7/3RF9R1zdMPTnH+Irq9SK4iDxgVytdWXcNyq5k2A2K4yTkeYqFn/lw8FSkRTUNNRW2CVt3WNW3Myq1MhVGa03sHsTWsYrfVvHi2omkNxydz6tkZSm+wrmHtJxzPHaeLDh2LWpOr04NSA9YuadqKB9MF1h6yXncslysuLq65vFTMZhPmixnTyRRPSIIMrl9fcEKYt5bVrmLbaw6mjBKPoGSAiuXWoJVP8f+7bc3lsuFw2rNoh5EmnCzIuEE88HKpuN4oTuc5xlZq1VK2ExisToxKjh9fwvmaZJlqVIiZOkCHVqPS5TAwTJeendbR+9C8ZfSWkaGgYy2/5ifXc2bVjqPJJo0VJORDYsLx6tjkJ9x/3d1xdvQR5+cX1P4eCoNzQxZmaT0LmVEI3DS2QriPTkZ4s0pzrClq69nLoBeL24g1X94nI+4ppYoKE1kI8t/JcpNyMfmCkdBMw41Kedg6nkKuv9uai8/LgjcLbnmPQFd+9BwPaS28y4h0ChUSHMkx41KJE+jf/P55XWQXaJ1x/WtT07Lg1fI1j967z83uCzHqMyROHHecxRRWkbbNoQd9oeyqUKliYua5w8VKl+jSrzx1UyNtxkXQlYqe7JFS+CQgHFFwi7k3VegMuln3HB5NRsZSeZTKj/w9nVW8/8EBV5dbLi+2rFc9N1cd9x9MEW+DKLfybKM0lQ680TpH5QMQliDmDc5mpc+Xz86YGfKZWN/OepRyUBXJfCrfwnuPpUjC9rLWYX9vNgNaaybTwggsAE+EFkSRV+Q9MMoDeYciu398PYQ+kbHExT2/XGOt5+RemxCYrHNUNTx4NOPo2LNadlxdbDm3nroJDHO57Dm913J41CQGHyxFg6lMnEydQDeAsSUjYyliQN5C1bRcX1nOzy/4xV/8FlW9xcWMfRuR1+SGRnum9cC6b0JZXvyfxFKJDRbKhU4CrYABFUZVa4NG09Z1sEBdqBm1UgKoa3abmi8+u+Tubs3JyTFPH77Hf/b5km3nWHYtSnmOZn0A2hjZD6Ua7PF+YIhoaPNFxXxxxNDDer1jtVqzXK6p65r5fMps1sY2msH694QmMMpbGtPT2ZrBqlhi55N1E4RmEPgeOJj0Cd61rjquVjW3m4q2djSVT0K2tPK8F4qB7587/txMmF4p8NlDYhsft1vHP/zcJumtotkbBL/E6GO3MOcYlE0VGLaM3UbBEgSOw3nBMFNJkdAqJGf+0fkRv3TmOJjsYsVReJdxNn+2ZIVh7IYN7bwOlSa9oaladv023MHHXgGFta8iUWVrY5+uMzdT4nGKlkaukInlaahUalhat7lMjozCBzFhViW6fqer0oOPsXzppJiEdAo/xLsUJCo8YiSsVXab71N0uoECwfJVMjmQEiBFYc0CNw+0bLcbQo8mo/SlZ1DMjweVuyhmxV7GlCuQ2noCQ0XXd8wOW55d3GT6lR3qo/QRhaZQaoVGhQ5ICppHeRVaQANW5Q6RykgIKhyhVNWHevq9uH75EwpPmcxX2lueg4Oa25uOg8NJEtRv8dW0N0svXCgxvHdvymLR8PL5itev1kymJvbNEIVKY+I+c95QmyrRg1YqdlWV/ezpsYlPJMEePUAj4wBw0rG0TJokInL63Mskd58UD7FKNLK861gsmoxVUtJfIgOf5i4pjqNzyQrOTzm+NkIfwnxsdwOrVceDhzNQjsEFS3qwoSRDGcV0ZphMJhwe1XSdZbXq2ayD5rtaDVjrmM9r2tbglKfSKsVyhXD7vsdUQRkIyoEbucySa7OGyWTOF59dM5lMOHuwwLkLoGxnm6KOKEIy383WMWki/n5M0pMknJLRgCjEe53ElM8bHkVldHC5JaryVGbOzZXj889fM/SWDz98yocf3We9e8PuhwPX2xmDNZzMd0GAsscUIROvTwOJSkyHosfUmsPjmsOjU3Zby2q14fZ2yc3NHU3TsFhMmc4mGOOBntv1ikZ5Omp2g6LSYwJ2XrHtDaud4XTeJWseAs7/0XTgYtmw7QxNNYwUIBCLMQuWH557fvmhZVJlxiqWljG5YkLWSay2f/CZY9tnV3I5BSJwlDKhO1m5k5WK1p9N1q+LyW7aBTFPmtIoSHWwnAdn+G/enPLL9y85mu5SM5LwXlnQS8MbYcLOW3Z2xXQ6ZbXccDA95m5zEzHuQ2Y2e3wiWHAydyLQ1IjpyHki8EEl93dCjFPB2i30hJh0VyROlRDD0XIZMfxS8KVFYuQ2HZWKlUPc539+/Pu7vEgUa/jWuVGAp1DH6KSgnsvhXL67WO5jyFWZrLFwVOXgRUGVOfbp7Vi0x6xuN0zaFmt2dMMOMTN9xHR3HnxhnYraLt7J/biyNGSyUZGt64qqqahqQ11X1FUVcoCQdfbvvI88LyUOSqii7PVQXDM/aLj+/C7D+Y7m3meX+zuUQKVU5OuaDz4+5OZ6F3psLAfunU2oG5PopVJVkHqqCSvsoFImoWX2DKm6w0ahLUq5PL4U+k0VsvOVyUJcMDustQzaUilTpIZEDP4ipGUdrFYdDx8timRhcjVBIgNJIlVj2lZCb8ErY13pVnv7+NoIfe9DZ7HGaM4etqja09khAKYMFo+LCyNlJOBxtK2hbQ3qVDEMnvW6Z7nsWK024BVVrWgaE8+rmEzENRe05Cp6AJwLi2SUoFmppP2bCFzhXCj/C54ClzeMk/hucFcvph5zF2hIkrLGuB8+acpiLI7nQlyTPpXSVKaiqWuUwEL6CS+fb/j88xc0Tcsv/dI3uHe/ZrV+yW67Zl7PeLMyVMYxqe27aAyKdxQLhLg5vYzTWRzBwm0nhsl0xoldsN70rFcbLi9vUFeKyaRlsZjSd5qj44p+Y9l2hrZyKDzWaQan6QZFbzWH0466Gif6KaCtHfN2YNOFHITRvLw1/rDh/vAV/OknMm+wD3drbcZyd87x4sbz5XWwY6XBj0uWVR6NMGpROiQb3IklH925oQrEYb0CP+BC7nSgiZE8Dn//4ZsjfvXRBVPTI+1rhQ7EOyGZ7yInVsMVB4cLlrdrTo8PA0aBiu5mUWwYyxUZtyggyud1VpTMTxSlYqw+02IQWsU6vSNJ7S2LXsWbFPcRr0ZpBSZXalJCilXOMjNZsDAWNqXVKReMhX9JMdk9XsVk3UTr8qDEj8eWroAojV4zCvuUj6Oy9ebziwfh0dsELSyNkubNMa+v7zg6PuRudxGTKsWdTczKD5akhyRsfJyDHKsPdfPhOUMAHNOGSd3QNHUSbBLDp6SPvcz98pDQkFjao3Xec5FPp6Fsere1zOZ1+q6cQ2CEMSH0WdJQVRlO782YzSpev9rwxed33DubMl/EJGtUCL35EALDwKBiJ0Ff+Ggs4GxM7ov0ZsBLu2YVSrfrqkpVW0GHiCFmZzGpoqzIJ4j0KsIcBX1vcT4kju8rT4mcfXjjRIkiM4TOXGjdLQrHTzu+FkLfEyBHtdMYbUH5UA9KmFAIzKKzPb0dYqK/RntFE/HjjdY0jaKqGxYHVbCiHOx2A7d3HdvtgHc7PNDUhuPT0EUJYqIOpIWXhTM6JIkN/YZHj+7xxRfP+NEPn/MLf+oxzl0zuF3Q2uLiB5Q8R1s5auPYdoppZRNBSw25uFDhHQJ/VNKXvwyZ4QZjJrih4Uc/fMnr1xecnd3j29/5gHayZb09Z7ABdfB0avj0Gia1Hbn15YGFrTI2puT7xAQVAuYW4sihmdBiUbNYHGIHxWq1Zblc8+rVBUopjo4OOJ47rlaeq1WNcyGb3wOT2nEy76l0QdiF1NGEKoBtb9j1irbeG3OQ6qWjhD954/no2HM6E+07a1gjhhN///IuJufhYg2+D/20y2mI/4oL0UUGKG78MDs+CYygiIZufxqH17leMSWFxuf3VvHdl0f82sMLJrWsec5CT4ltkTMbrdh2S+r2lNvza+77A+qqoRs6DNmy8E4UkMxeRBlIiy1MpvCcqILmURLfzEopUDRkyYzaCyNTeV32Gf3I8gmnxPfUqYkU0YWa8hJ0gSdQWp3Ro+ABb91ekmGa3iyQ4nsKncgww1xF2i6/HF+e3MGosaJDWvdYcuj9Wz0CxKthBxfgv2NpW+zARVNNMHbCbnfBg/fu8Xr7RX6P5N7NcyoJZXiPMuE+JpahhnJnTz84fOzl0NQVk7ahMlWsuNF5XskNk8RlLfkrad7ivIu3LCVNFu60UsAZY6jrAMiTFbq9vSr3KCa5FPhJGfSOpjU8eX/OzU3Hm9drlncVZw9mNI3GoPEqVEGZusG4IWbbD+gh5GpZbAS7UTgIgtv6iPyYqxaMMTHfq2jX6yxWa6yPPTisw+lcilryaIViveqpI2y6QAe/JfCjspDmzBVKdwL+CsL/bfVrfHxNhL5nsENyvYSMymiB2xw3TEE4p6ioaE3FQIBQdJGQfYwT1XUsXtWas7albRqU1jjrubnZ8eL5GvcQTu9lTH8XuHdIUEomiGewHZNZx7e/8wnf/5MfYYzhW995iLZvsK6wRiOzrYynNp5tpxiagaqussUVra1yY402VVzxYQhNIGyMKSptqKsD1kvFn3zvM1arFd/4xsd88OEJg7ti13XgQ826VoqPTmr+0UuotEsWXDC+xkyfOI6sZ2Tmn0Rf5quJeK3rUfRoozk6rjk6PmW17Hn9+oI3b6548uSM0/kSGwV+N4SNtWgHjCSplTcn893aeOat5XZTM3c6IR2OLTwf3dXhXn//c/jnvwOVAlXGVNNjwvxebyw/uvBBsbQ+ugBdAiFBFXwt0Wdk8Km1bhb4MrMummbeuWCBx9wNoWlXCArvPTtb8Udvjvnl+5cYlSFoBXY6uC6j5eoVV8uOH11pvnzd8GqimLcL7nZL5o1l0WbuIq8RQlkq0eTIvVnMiyCyybuKkM5lWkB072sTznMF75d5VuT7juk638sXdf+l8JXGMEbwLrxP75DyBcqldyJICsKUkl9ZwEKpCb6ZIgYuTBmSIj5Wgn2GzY7Z1SpNXHjTsspAIFxTkpYSZTEnATZNHUoS4zpPmhnDNpzTzA2bNytSu1gySlxQOELFjnLZwg/155KEB15rfO2hCs3B2qahqRuUK1DlfFAeKpOR63zMmSoFtdBpzhvI/R3knHcdQnNvCfh4pOtlyVSmvZJ2Aj5KSGY+PQ2x/tevV3zx6S3Hpy2zeUVda2oT+Kpxmso4BmtAhaZBne2DPKBYCxvc55UJQl+hIsZK3L8+NBsL+B5RmbIWX/m0/73TOGUTep/ynvW6Yzqt09zlF5YXzfQr+U0oKMM2IdHYRuNqPG/7x9dC6ONDO00GcDqUWHVD1hKN1JHiIx6yRlea3g0BAlcFd42N2NQa6LshudOqCEyBUqgmKAR1rXj1csV6PfDeewuMHse3vfd4HZMIrWOwlzx6fA+lvsn3/vgHAHzz2w9w3RucD3Ekyag1CowO1qpze8zJM9pAaQqKDVK6eO0QlIbF7CEX51u+973vU9c1/9Sf+TUOjzyb7StC/C9qq3HDnMw9s1onBh0qj8kM3hOZVP49ayXhkC3qi+EnayyN20Ukvx1KOyaThu22Y7XqmC8atOtosMxaN36OuMveJgWA6OJvuFzVGF3RVJ66clTaM6kC8E/YPOFe11v4Wz+Ev/CR53CS445aa263ni+uHRcrx7MbH+ry41hcbMSTBH94qXeQaC5ZEq08rRfBdW7F8e+D612SF0ulIciNMOa7ruH7l8f84v2bDOwToVQVKjSz9nCzNfzBmynziUNrw7PrHt88ZLlpcXjuz3Z8cHzHvLajBLIsqMr3KJQssXQLrpvc/TBCj1NK5RCVL2L4Jc2ownpJzGw8hrJT38iNGZ+TSv5K9wBRAOmQIR/2kEphOGHq+/eSX1XJdQn169baWDKZ6+ZLX4/3wXpVe16X5PkR5UhlIZ+Vp2IPKUXVVLGFrUrzN6nmbG93TKYtnVvTDwEMyyidQnqC/lYbE+lDp3FoFSzangFf1TjrmNBG+gnX16amNTW1rsHHLpTixvY+egredrcDI7Q+8TTs6V7jN/Vgh6y8umL9fUFD8vNt0KW895LiEW/ctIb3nhywvAsQ6ZcXG5RSHB3XHJ9MAtqpDx6+qqqoXUNl+3EzpviGUtefemVo6ZrnR/H/lB9hYmtt5+jVgCKEgG0MKeCCpf/ocbvnpS0mZ29/CSeVEnLvPYMbYvvuolT8K46vhdD3HvrBhthMZBJa61Qraq2NGZRBS2p0hafC+wzKMlgbrYrQiKaqDU2TXf+SgSlul8W8ZvbJMa9ebfjJj2/44IMj6lZHKyOAhuAiulck0PXmkqPjI95/+j6fffo53nu+9e2HrDcvsD6UiZhYPmi0Z9Npegup231hdYkVIwwjEUU8VZjEdmupqwN+8INXvHj+koePHvCd73wA+pr15i54QjR4Z7EuALUoo5hPHCcTzU2X+2GnmJwPT4r8ZyT8RxaV/FvSsnp748u5zjnaSU1V1Vxf3zJfnKFVQJMble7FNSgTt5BHiztQwdlBx643LHeGblBsugrvFXXlOJgMzFqLLsqtzlfwH/4x/PPftpzMgnD58YXl734avk+lk8VrZoEsvbpzjf8+kSYrMP5O+VOsTcIaCwMt3d2SCZzfWXG5nfLpteWbZ5vUxUulu2g+u57x6c0MpTTWd8zmU9arLSezOdtqhbUDF5sJb9Yt96YbPjhacdDaEZNJuqwnu6vFKpYlFkU3XhdqmX0sQ8tWe6ZhkifBFzSdOu0lbWJkeJfTmfZusvoLZpf0CDWexyCcS2FeKqAFs4xkntpQR6NhvPjxxaNiG/ixTwlVupLmM4qU/U/aOUVvBz96powl8JGiq2Nk/h5oqinrXUfbtmz7dQhdoDLkawSDMaaiMTGerQySxCeHrbKQSHlISgBnqlDei7SdLsBl0pBlfD55NEpXu5HyPb762G0HXjy/4+6uC4nLhdInMergvRrfR1GWAnpZ7NRMKih6MbNew+FRy8Fhg7WO1arnzas1m/WK+49mqFhKGbrhhZ/4XJYtzy09PanZVbZ84pg9Tjl8BDyyLiSSu5hcKeBtRmmGHVgXFJOUN1NY8uX+F49qghf3wmFdCjuI8fbTjq+F0AcfJzUQvvJEl3j4Vhgy3qPQ6Eqx63u8hoY6Em442Six7quioxoZ8jMyNk+Y5PefHnB5vuGzz2548v48YUdDyPTe7SybzcDt7Y7tZsC5c7SuOTic8+zZc7RWfOObj7i9+7J4n1CLu+sNHgFfIGm/ggUvQlCjE/xwckGiaJtjtuueLz5/TtO0/Kk/9W0ePp6y615iuz7OXIQKJlomcdNPG8/ZTHG+0YnjqpL6CwstsU7ZlSozkDjgwpLyozjpPjNwtuf4+JQvv1xFa78C26Ubax1c4Knzbrw/qGAxl7OoPG3d09YD1sFgdQoV3G0q1jvDyTw3+FEEK/5vfD+03P2LHyv+wRd7CrdSCYhHLDilyDG2iPOf5iYJpPy2koksCsNbE6GK870Ip3fkDMR7f3G7YGtbprWn1opaBeZ0sZ6wHhqa2kQm0TOfH7Jarhl2MGsXrLZ3OGfRwOVmxsVmyul0x9OjFceTPo29FOjJcpXv4jjHApiMvkhhecd76EzWI0EZtB2dLHPiPbMFT6Yz8rO8A2UKRbBQCtOYZdJUdpEKry4TrQI1va2dilAXJSdDBI8Vj5CxnhXSIBPkebHO3iiczdd4D8SqhqRAC1+K4xavhELRVC1XuyVHxwcM7i4Kqoz3XlcVla5oqyahw2kT6CArO4pBR+szVgkJPwifmdToyJjcLjcTIKn8UNZsPN9fLX1Eyb++2vH61YrJxDCbVzTRcBKI3lH4kox/kHuqjBNBvc/Kh3gX5JykiBjNYlEznR7y8vmSZ5/fcfZwgmlzmZ2g9ZWcKnhvw99VFRKjK20YvN2bk7ToIYvfWXoV+DSAdhblFbWpWK4cTWOoI5qkzGnUOONElTMX39+7aKhG74OpMLIp/kkQ+g7Pzg4p3mJ0iNH3dkjCMpW7uSHEqaoQ15rUTdCKo8AzOidmCJFIdq38J9acVx7jFWcPZlgHL1+uefL+ATjPxasld3ddaCkZywTv3W+ZzaYczB8w9C3f/e73uLq6BR6BJ5UxBcHt6axh1U9Z+B5BAwOQhg3iapOEF2HGRjcYc8KnP7nkyy/fcHJyynd+4UMm0x3b3RucGyAKK8kEFg4o72q05+GB4w/fqFg77rJFH0YRGWZmlsn9mM8AEv/KOoH3OSegsJyqStMPO7S2zOYzbq7vmE7vBaxvQvc5N0BdKzxbrO1JD4eUXS6afkK/UqCMpzYuzqNl12vOlw03m5qzqosgMmGQ1hOafHSKwZbWn0KibsoLeE5EKRu9dRYj0eP3lsCW796aLAoNXkrdfsYmVgouNy1mKxnWATvdGEMjveVVeKqpHNPplLvbFaf3D+lNR+d2oHOy4fV2wtV2wqLuOJ1umdcdM7OjrbOnZ1SqJmv4lqD96jHLqwdFmph8VsTNs+QLblJf4KGLoC6S/NI+iA9WBb3liVZZId0bjJRPKp2VOrlklM9QeBBGngEpn4w0WNaki+u+JAKtVIirJ6+Q5CbILdSoRXUSCFGgVbpm6Hvqpmbre+oIuBXWvKaRFuO6Sm55E+PQ5ViEXpRSOJVDDvKdPFdc/u9S1ksEu1FC3d555dF3ltevVqzXPe+9twClGPplgc7ok7JBce/kHSs/IxtE4aFeliSNufQehFOCF+rh4xlXV1tePV9zeFpRTT2eXGboVeb3Ajxk0DR18IIordEuKEougo15H5RUiwuJ40phvS1CUwodKwU2q4H5fALyzmV4LTsPEm8v30GU6tKLpVAJqvurjq+F0PfOM8QYPJXBq9jVLCaqhE55wdKvIrypYjxpSgdXVF1VEZ0pLHAS8EHNj26yPG11HRIwHjyY8fnnPT/+0TXeetabnrrWtJPQB3qwnt3Ospgf8JMfX/Dq1RuUUnzyyYcM9i6EAxTpWYftlpu24YvLOc5veXi0Q6siszX9UzIlTV3N6LYz/uB7P+HNm3Pee+8R3/7OE6y7ZrfbJKY3akXqsttY66zwPDocMMowWDDx2VospsLCE0bxLh6f2W2OW46OxEVC+826NixXS46PD3n18pznz94wnU6w7Bt9XwABAABJREFU1rLbhS5/bdvy6PEpStsEfpJfJiduZWEnj1Fp3traMa0lb0KhjCSP5fE+u/GjIYanqEg7weoPcU2N1j70OMejRpn84fdkxJZzEgezH4Pb+/MtZpUSfpLnB1AuCsvg4gvJrFWB5x+OwW45Opnz5lXH1fkd2lR469HtQFVlIBHvHbe7mput0LrndLLl/mzLvdk2QacWnunRGEPYSCWtRxh5viYq1DaHK7QuBH4h2OU7D6nJgi/oLnD1NKF5PIrkKfgqyzMFXaJG71VRWicKTilm4ntIZn7qeki20Izaa0DDODSQVcc8fqV0UKx9HlnqbbCn+FWmBhv6ZZhKMQxd+i5Y5zrhhJgYow8QXXqUiS+GgpThBa+zJyUnKv32nhYDQ8YuQjguiJQHirEk7n1ZY+89d7cdr1+vaFvDhx8dUTeG89cB+jwJxmgYvGXJy3RE+ELrcnhiP2EwJRiXyoqsc2H1n55OUBou3myoZp5qHuVH9OAoH2VE5amiQk3yuhThBeJ4nMcqh1UBJ0TkSVWF8IrWGuM12ml2O8fZfZP3SWz4JAq0TJ9LYbWs/OXOhY6+70c5Kj/t+FoIfYC+66nbOiQyEKAkBS1KJrFSmqqqQjZqZWJGrIngJ1mrlbjXOAMVtDIJXCJh7msdkNY0PHw05+WLO7yDk3sT2lYzDJ7NpsMODjtoPv3JOVeXN3z40Qc8fnzCfK7Z7t4UVn5Y/4Op5ZvNHc+vZjy7mrLcVjw43LKYxOx1QLmc/ayVoa6PuTgf+JPv/TFKwdnZPQ6Pobevcc5m70VMUMSHGvRyI2XGGLreHbQ1/aAw1Z7V+bb0ouRX7/peZrhkEunveM5i0XB9vUWpDfP5lOVyxXa7o2lqTk6O0Fpzfn7J9dWSk9MJvV2j1D6ZhwEMTrPeGawL7nr5TyliU5887ixY82df3shmZiRos5UePSvKEBT3PArJ5k3GXxpZ+VdU8kafjO+TMQOKOY5fuyQAQ8lXOd0lXGtpgXtvgR2n9w558/oSY1ra2uDUFm0cCf/JEZUY0vtebCZcbqeYa89hO3Ay2XEy3TCvA5piSHxSsZZaJehTsdqz0I+lczGzXsabxpiykgsiKoU8I/keFDApByxmb8Tw36WRlrMdBXlo+RoJvRBoooDgpflSEDZGWtTFWKqnCGuIAilZ9YWSXipyYsU5VUDG5iGwH2qodIWPRT/agO2Dl9Pp6E5WFudNKic1Rix6Sf5SqRxN2bHrWxSSpFTJ+FQafFJ8IPAMX7ja08896x9g6C1vXq+4u+s4O5txfDJJqJWrVc/hUTvyJCRhXi52YbmX9x4ZQ8WYvffBqT5SOgW/JO+/2cLgVM35yy1WOWjDvBujcyKyj4qQCtn63noqVUXBTuDxzuI8aO9wUQkUND4XETgkbNINIcYv4EGoAklRCT3H99L53UaloPJekfhSsu9POb42Ql+OsBkzcpqP2VdaBVAL0TwVKiT6QW6BCjAkdTwlUgyDTZnRJVPxXpg7gKeuFI8ezRJgj2hjwxB6T7fNglcvPavlhg8+uI821+y6HT5qgii5d/h32jg+PFsxay3PriZcrQ84ne84qm9Z3wT0nsPDltPTQ6r6hB/98IIvv3jO6ekx3/r2U7788guc2wZLVpUWpUqZqS66rZJlTN5Q0xYOW3iz1kyKevekJECCPU1JJjJ9wu8La2Bsaal3/AZVrTk8bNlutqDg/oMFs+k8utwGtDZYe8Tl5TXz+STCI9uREoHSrDvD7abCuoDqp5RncArvVVy38ORpM4R+AqV5XYwzKzKSVU6aI0WM0xmIXW+Bgbj7pGIu3SUnTOV7y/3KnvZj0ZXpEREAxT1FsImHRr6Sd9Sly5BwvbUdVa05Pjni8uKa6WzCweKAbb8M9cgqWlmKEepfjq0qrncN19uGn1wvmFQD87qjUZam8lTaUVceg8MoR11Bg0MVnhTvKYSbUJNPyZLFtKc5yZ3v8iSKqzrJ2Eh7o9PSZX507xHhKXGnF8+O1rYI/BKGtZwPyNeNXqc8CoVEkjkTzDckJcL7AJJTJs1JHF9eypgKN8R71IphPZArSUJvEBz4SrqBVjl7XxeJuTJMn2kDBd5K05lYPip7WKxoL0mXuStgmacjcyN73vsAevby+RJtFE+fHjKZ1el9vYduZ2nbjDsvqHL7yjY+cIJyLMlbKxbT3lhKhUvuI8BExfLTTDSTmWa9HmgnOWfHxNyNkJYR3fd4VJwDmUJrg38gIzEGQe98EPbeeUjCW7HbOCaTOuXcjLTVgmZ9ZBTi+YCMSxGy9TPEb2iv/dPF/tdD6HtSQxzpQFS6kqUMxSidaoZ9XJzOD9Ta0CuFVo4+LXKVmFI/WCqtcToLyFSb6iVeFIZS11VC36uqkDVbNyGu1jYTrF3HREHoh92eZhdqRMUtplDUFTw63jJvLZ+dT3h1M+VawwfHnrZyXF70nL+5xg5XLJcrPvr4Ke8/PWKwl3T9msm0RWo4VXTthSkTDIOCkYonLio7TWU5mXqe3xlE3JTWky8YUVZYMnMrxdO+uB/Dl+bz8NA0mqZp4v71DG6VFQfbc3i0CN38rpfcf7DA2tD1Rt6lt4rrdWiocTIfqEwYmXXQ9ZrdYBisYtIE9D4RKskdWI5ViQD14oEjuf2UQntQXsfEwoDrrZPgDGiCXloyk5l+Fut7k5eeORYmlHMWx1LWuJcCQpgM+DHoSyFxrd0xX8zpuznL5ZqjowOaqsd1DqdCvNO5kAMhay7C1ctCxWPTV2z6Ks1jGm/pJYnMqtIOozxGeY7aLU8O18waEXwZG0DmRLwYZSe+kimmCdgX5mM+T7F4Y8KMP3Oin3yU1zsJxZLGY6KXNuMENllKAacSxWE8YzlxGEghjPC0LOxG3g+facboCjuEK3QF/dCFZi5oOjdgXECbM9pE/Id3Tk8SnGV1RemFkDJQGQ/kpGjrXKzZD8l9ZdJmsHzDPa11XF5suDhfc3Jvyr17s9TgxwciDn0UPLStSZ+LUpTOi/fM6Jh53Lqga1dY9jJuwU+RNdgP84hBp7VmMq9YrQZUzIY3PgRG5J1KogmCPo5HPERepURAo4Nn2cScsdDW3ITwsNV0azh52KZa/+TRcR5f0pr8XhhtSpHWwUTcAOc9yph/QmB441zZwcY4W5glU0n5SoA1NSbU5xudARUU0A8+IFHFTdY0DcraYEERcOvL5JegsQXCsS64No3RKdtfSjKEGLUSeEbFbhdc1UZ7+j03n7Rd1Tpj/QvzOpz2fPvRwOeXM17fTNnqhg8ettzdvOT5sy85OFjwq7/6C8wPLZvtS5RSTCYVu+1A2R42C/8w5hwDEm4V35Gg1T4+gH/8UpL53ua3I2EFbzGY8JFKazQ6kvY8Xkv5RPDby1iwUh7tdxwdHXBxcYW1hwSJmwl914fa2aNZT62zJl4bRa1DqZ7zIMUZOQGLQqEhCVeihaiVCLBi68dfnJNyM3GdBtQv7wPCQemuLl2RLlmye3Omij0+mmtxiY8v8l7Sj8pOXsKkMlMsz++HDccnc7p+4OL8mvsPjuh0F2h/79lpbfNrJFQ6Ge/+CpehIvl7cIZBBZrYrGtebQ64P9tSa8dmqDidbnlyuE3WWWjjqoub5h+yNqKqiYBOOkk819kwD++K6+f9l0MNZUWFCDlBufPeJ9hVUfxKJSJdG+8TyvLezjD3ewxcAWiF8gEsLDduCS+qo/vAe0+tG4atpaorBh9QRr0DpyyVN4EOIvRrar9RqhyFRbyfTwJlyHA8X2XzMmtdQPYjlkdXVaDnwtXf7SyvXq7oOsv7Hxwxn9ejOZA12+1CeLSqTHpnKT2UZZSKmMoYytj9aHw+5xqIUuCL7+S56bu0ViEpt9Khy11lDNopqlpjdTDCHAKuM26bLvvaqNDUzHpHU4V30RHkS2tDZQy1rqhUhRoMtxeO0+Mpx8eTPGYho8IQS0qjfBQRFK2zSVFRKjRHQgmGwFtLOjq+HkIfsRIoCCEwYO8CpKlASAbXVYBFHOwApoqEpagI2lhlDJXJMVJcEUOKzKgECZHFTS4tskUXzlHgoO892+2Otm3wPmIKlOhJiWhjNLVgcArFpPF88mBD2yw4nhzwR3/wQ16/fs17Tx7zyScP0NWKzWaZXIOLg4ZXL5c4B3UVNVCVW1+mkhaJwfpclijjfnBgef+wZTVsqU2RRBa/z67HsQmVfnN5c/uC2YS/x2tY/imxzXwNcRbAuo754pCLC1gttxwc1RHgJy6XDzH8SolbJ2MlxDfFSKmRCIxC4DuvGCz0VjPYEBs3xkXkO5+SGSXxz0fOagg9FRQRVD/K3NGaMmb+2cIaGeJ78xlvV6zLyCr1pHUQMe9iBDHD6hbnx2djB7xfce/eES9fnHN9tebg5IibzXn0GJRx+OLqGCKRro7v4jH73oCUsFYoPTKq16spAA/mGx7Md6Nr0j6T+4rwVfkcmeOR+EpzGZWHvXkXpSVbvOVTypt5xJ0tirI2OhkWSQEqhWepOJf3FZoJA8cjezDvEfEkJgOjsPBVPL+ppnS7jrZt6Idter5SsWxVqdAND1E8HC6GuAx7Y42H88FdLYJk/5yUMBefZbSKlVLF+UELAuD2puPVyyWHRxOefnBEVem3nilzsNva9N4SMkhQ495j41hSUmqhrOwrUm+ViRYb612KAoTcFaeI3liYTCrsbmA2rQKwjrYMPqDrOR3KeoWmBH8BQnVJbVRM/At73kTIXmMMRhm0rbg6t9w7nfLgwSJUJikJJaRpScaY9+NqCOst5dYKrbUDjRqdEzB/2vG1EPpKKdpJQ1PViMYuG9V7HyATlcbbkFXpjMN6m9D5vAqJcNoE9D1jQuzLKHG5O3RyeeX4kVYxqU8H8Iq8QX3acGIZnr9Z8ebNDdfXKx4+egDEtpBaJ3eMoOGhVGJIKaFDKxSaRXvCvWXP9//wj3HO8Su/+ouc3a/YbC/o+340vrY1sZGGo6lNUa0Q9kKpsQZh50YWptaK+WTgyWLG964MqCExcxH4WfAFKzxZyHtWXjYTx5/G09+SSs6LiCwEXbSKUAqtB+aLGXd3Kw4O76FUF+8VNoB1CoemiufLg9TeBos3RwGDU9yuK7a9TvF/E5lloXeg8RjjqXQoA5SqCm2g8j1eMtKFGXtVMAniW8l7Mfop77Av2OUcpcR0ezfj1p5QveIdztmogqig+JIZqTynHzqcgflixs31LU17zGxyyM368h3PGAtxGc8ojbIQVvm9VEFXhSYbzzfK8dHJHU8OtyHBL9ay55BFQUWSYFu4jlSe1pFyIgiAqf0uhdLg5Z557M4JxO+eYFAKY1SCy02CXva5yvSZ3s0HzI80N370qDx/EEszs/KpVAT7cXvKc8wZbKspV7ueyaRhN6xG10EGkHF7D1WRL0rC4HidJNEvAieNhGkWqtYFHlXXdSylzXOntabvLC9fLAPK3HsLTk6mb1v3Ms74rO22Zz6vwz2Kuc8x/6yMpOd5P9rDyaW99yxZjjznhYmipNog8nOvqTQcHDRcnnsmTZPq4Z13DNoyuAHtTeDPRWtfCU0l2OX4YIEwrnRw6V+8HEYCX5KqVUE42RM4No5szMMysVNXVYXWoNJYSwy3fQjx/eNrIfS1UhxMZzRNnTae8w7b24AMFq0g5wNhmtgaUhJfUIAJ3ZDEXSKCPNRl+mQFpzhX3GQZaCULwvj/kNHZOy7OV1xebvjWtz/h059cslqugRqipmid4+piy8XFOmiLjeHgoA7ZrFExqEyL0ad8/0+e89lnn3P//kMefPBNbvqOdvUKo4NALvtj13XoDHh32zOd1HGThecpMsqYZPJDIDStheAUtbHMW09rDKFZTjHxe9ZA6bIMH1D8nZn02+eDKsg+bkNUgv1K5E8sbsa6HUeHC57dvWK3HWgnFS6mNDe1x28Ug9WhNl+ex1tDSEJwZxVXq5ptZ9A6YPdPG0ulXYxvg/cK54kNgBTWEUr+vEk3c74BLEZtMGqTykff9d5K4n+j6fIj+toXnvHCvRco/lAxbOVUyOb2Dk/oC2EiM5IKFBut2F23ZrP1TKdTrq9uuXf/hEk9Y7W7Gz0iKHb7XoY9GpATi5UVCze8h9o7OShbF8sarTz3Zj2NcQUd59skhDJP7FDoRwx27I3I0+WLP8uQgyhQoaTXpzkvBbuKAj+vAcnaDXwlulNHpP82XZeEl/mEH1FGsPwj9ob3RXJnJhDnHLVp2e2WHB4vWA3nADG0qFI3PDFK3qb4OPbYPS6tqfcMNoRIu51lu3HsdmE/tRNDO9UYo6gqTTOpUyw/u8rh5nrLq5crprOKDz85Sol5X3V4YLCW9brn7P4szU15JDCud1yfMPbf4bnY40TpUF9xfpj3wHfmi5bL8w7XaSazGleFnhmDHRisoXc2eUclH8BJDoAo5dK6RYwVZ3jzsuPs3pT79+fRsCwFfjHqqFCK8ap0roQRTAWlMrx8vkYUu5867V8Poa+UYtpOAkBFdG0753GVS+U1IakktKesqypC3kZXvq4i5KRATcb7Jg2KYH3jk9Uth47W0zC4ULJhPYMNG+butmOzGZjNKr7xzXvM5557p0f88IfXbDaOujE4F8pYbq53PHy0AGC96nn1csVsXlPXFU1zzHbT8L0//j63t3d861uf8OjJMX/yYsXFnWNqFIfTmDSEaOrQdZaus2y3a05OWqrapA2qVE5GLF24QUhEV5GHpgqd7SZVxc7tkJZ50aCmdPdnPutHfD8pRZkFJldhsoDZ36DZS0K0+gNAi3hRHE2raduW29s1D2cHuGFAAW3laCrHujNMmpJhZMUjywfPttdcrWq6wdDWjqNpz6QWr0dYc20i05fJEwsovR/c3PRsd6AnMzp3SGMMTbWOHpWiN7cLiX4BOjWvhdRQI88RuvPlfPi3NvW+EPbxp+CBB7GvivtlXAYiPVetxfeepmm4vrzl5OyQvurZ9ZusEL7D+zBaMZ9nNnmTJAsbEiRq6ajw8dyr7ZTrfsYPLsEoz7wZOJ70nE63HLYWRe5MmJ9V7E8/vrVYp2l+VJ4osfZDrD5cl5r1KLlv9l/Iu8Sr0jU5kTIqNiOmnb0P+bNsXadE46LxTooY+Hxh6QlykfEbVTP0A3VTMdguGSomGgjJWNlDyRN5YAfHMDiG3rHdWLqdox8szoJSPpYzaxaHFd5Dt3PcXHXYIezhqt7RtIbptGY2a9AaLi7WrFc9Dx7OOTpqo5X7tisdYqg0efIUdggYHTI3spC6eHlfflfMrfD25Novvy+O0kW+H9OXq2LpP3VlOD5uef18y3sfzGknNca7hL9ghuDmDzRdeHyjO1/yp8R7olBcvNpxsJhECz9j9+8foviP4agj29HZY6Z19rKIsSds4x06zej4Wgh9rTXTZkJdBVQq78Frj6pl+wZitrGOWMr2xJVuIpBJpQsXOATCLDX0+K+zwc3lfWh9eXOz5eZ2GzZNzOLcrCxKeT7+5JT5okZrxTDsODo+wjnH+Ztbnn64YLu75Pq64+nTI2azsByTqeH2dou1hoPFfV693PCjH/6Aum74jd/8RWaLju3uJYdtxcXdMauu5mjWRys9uJ5ubne8frmmnRg2m4H1uufwcFwiBJmhSR5EGZJQWmEIzWtmVc16qzCxiUsxIcnyQYmlx9iwz5I+fK9kTUhEPSJ/n5WG5N6L54yttZ6DgxmXlzf0/UEsw7Eo4HA6cLmq2XaaSSP2VByYj4oLnk1nuF7V9DZ02jqZ97S1S8JdNp4qmJFMnCrf0XmGfqDSoO0dupqzs3PmjcewK0BvPF4TPSwyZz501RtxLMmXyMz6Zx3CMCJkCN47vNfRWojWQ5HFjLhPcejas+3XTKoDnHPcXa85ODlhsH3IfSmt2Xc9N/5T6ESpkkYpleFa80AL5qQSrLIi5FTcdTV3u5ovbmbFuY5p7Tibbrg36ziaDG/Rj4cklMMy5dyN3F2v0Kmkvn+PWL0QcEmLb3Uve1vYl+swNu9JTV1kjvAF/r7zeJ0z0X2M06qinNZhaeoWQX3VRuEHFzLCTQTfiYljtanQyoBV9M7Trwe6Xc/QBYEv7uimrWinhoOmCW1nKwG5cSn7P4P0BOhgMSY2656LNxu2m4Hj05YPPzpmMslld+XrJyGrSmVMx9bnQehLMqqK35XXJqOL7KHMce8wV9oUMMF7R4mGVyoPonCJBykoX57Do4bXL9e8+HzN/cczFosq1sorbKUTRkby/PpQvmsqwUGIQh/NdmPZrCwff3IQavQFB6KkpL1xiUKR/tZFngN+7Anzma51TCD+acfXQugbpZk2bapHddF9HXCsVbLYXdS2xQWS3PNKhY2jTax3zBntSSBGQeG85/z1iuubXWKak2nF/ftzptMaYzTWOj779IYHD+YsDprwbOdxrmM6hQcP7vHpp19SNx9hzIRJ2zKftzgf3EZaK9pJy2bVcv7qDS9fvub+/Xt88o1HoG5YrpZ475k1jrYa2HQ1qFAqNvSO169XLJcd9+/POTxqgifhZsd80ZBYUiIwjSqazqR8hUhkzjsOpj1H7YIXq5q66pM7UzTk/aTDUVe90tIolAFVMGsRapnvhvku0ba8ErS2fD/reubzGVdXt6yWW46O6wCUpIJ3YtEO3G4qjO6pjMuKHDBYWO9q7nYVGs/htGdSW2rjYrOYoBgNg4vVFNEVJ7Xcwoicp+tsYt4nJxNub3fgtigWDK5l1jg8GShKGvOE94p1vVosjzxJyTLEJ9r9qiN7A2IClwvKRZpfh5iQcd1U0f87ljo1lt12zeHRMbfXd2yXA4fzU27W5wn0451KXZb6WeAnxi7u8jGTk3NSjkm5/vl2cew50W4zVHxxd8CXdzCvez44WnF/3knUJ+3J9Oy0930eps6CRTxfiOWdzHSV7qVigtT+9ItSJoqk3N+ne4xxCdLUqdjVM7qtJRFOE0pAIfAqEz5Jz611xayd4fpgWJgKTK9o6ybkjaCh17hes7WKrQPlQkfJug5hw+m8om0NdRMbyxTgM0SvUHonRUg+K/KEVKOYzkIjsr53fPHpDfceTHny3kFuQJMvHx2yznkePdttj6lUzHZXUZkWq3UsBGWdMuRuXutsEWeLvqSpxMLTq2aApXI95ahrw3RWM51WXL7e0O9ajk8aahM8KAMW531UruTFQv6MTsqbwju4ON9ycjoJClFh6JRH6XUQgS+0H9AoY1hWSNRLXoMop8KHS3/qu4+vhdDXStPqJrm0vA4uGhWFVukmgrz4moCJ7D2pt3KIJQcAkgRNS8RVju6a45MpB4dtWoymMSNN8epqR1UpDo6a6NYNpX0KRT/c8I1vvkffD/zxH/0QrRUPH57RtvdZb16CUsymJ7R1xQ9/8AVVVfGtb3/Mg4dTNts3uKEHRSgBqTQHU8tyG1DzbNfx6uUKlOfp0wOm0xoPHB62fPnlHX3vAm69lxrYrHGLJi4Z04GOAkM8aAcOWsdhM2U9WNoqW86lEIiTHCyUxO2+et32mbxUpkhWbBJY4rPyeY7DJnYYY5nNJixXaw6PThEvAnjm7YD3ipt1RVs7tAq1+tYpdoOmHzST2nI4G6iNY7sZuFvb6MURbbsUYkH417WhaTV1pdluh9AdTKsAuVypiCq4o2k6BttgdERRjIRno9UvoFCh0bkkLeV5NTHj30XbXZqBJNXgrb0tHipA4oVaF0ygTGTyiVGIV8D2Cud6OlYcHi24ub6jqhYsJkfcbq5G1v6eCM+/edIGE0tlP3HS++KaQhB4VTyiUBzS2+298LKr+ePzYz69sTw9XPFgsY0x1XDfEfMv7l12LyOucVKWIuOUe+T2pYU1lrwHcvO4AZIVr/LzkwJC0oY1oGPFh0rexTCG7abj2Y8uqKtm9M6e4L5u6x0X6o+4vrpjtbtl1Z2Hlqq9xnahNwUetHH88m98yNHxlKaqUtiydLmX7W4VIXmw7Dsg8er9w/uQVPby+ZK2rXjy5BBjcnwf4N2CJ+dfyH12W0tVmVTuvJ9AOWIrI3jrqMgV3iSx/otLRs/OmqR/i7aKR6ZzZ7MAof7e+wtev1zTdQNn96ehFFzFagc0ykuCd8yeDyYnKMXd3Q47eO6dzZD9B+TScvYV3vyOQeEca41iSLn98fsiRPRTeC58TYQ+EFzzWqdOUIKK51wWbhJvya4nhY5QrCFG4sebVTZ6ZJCyMAFEIiYD2pgUJ4voPKtlz/ygAe+xsWGLxN2s7aiqGz786H7oDGg9z5+/pmlaPvz4DKU8r191PHv2msPDBd/81lNm84HV5mVMJFRUySPhOZhYrlYtby4HNtd3HB23nN6bUFcmqbftxNDUmrvbjntnAawn1bpCnB8R+JnJ4MPfbe14cLDlejPlu+cVteneJq5yrsikW2qi4YvCnRaPgh+OPlBaBzhLG+OABehE6B3gY/nejNVqzWrZsTiY4Nw2bgDP4axnsDoIeavphog5oDxH8555M2AKCOS6NUyNDl6iwlpxUREYBhfzJHqaxuAiEt9sXtO2EQ/dhMqJbtihdE1vK5oqN8EwXuO1j8lBweIT17u4LtO0+uisV07qDeNq7UnfZDVnuNXyp3wujFT5TNDeQb/VCYN/3d9STatQHXG74uT0gEndselW42emZY3iUoZdMOt35wH4d/wqSkh6nZEn4F1uW/lo0xu+f3HIpzcLnh6uebRYUxWwyMmzUSgjKY+kWOSgMJUm6lcorsk/P34n8WSFUwQvROgoGx7Kg/IqNMOJDcLwIRmvWw48PPiEf/Yv/XffKXB/3uP//df/A9qJYjqtA8S40qlxkYoJy9JgSQwdkMY6gh8xLheTw1rLi2dLPPDk6dEIbCcpEXvXlHF0H+fQe9jtBhaLdjSfyfiQa2CUuxpythzDMETcER16oKBG15f3kyPkcWQApLGSGX6R8c8XDZcXWx48rHny9IBXL5e8fL7i7P6UutG4iOSpYh4FKtOaUophcFxebsP5VfxeQLf2MuzLbRDYtlg3hZeKTEej/Kj4ScgJ8W8rBHvH10bohwYjJiNEpRhOAJIQMANFju+IxSuZrk5qfNL+FA47ZrAl0cp95DKlFe1Es930OD9J+QMh0zIkyr1+fcX5mw2P3zvg4YP3+PKLO37wgx8zmXwbrTXf+96PuH//jG9+8xHdcMHt3RrnHE0b3Gomwgd7VESU8+xsw5OnB0wmJteku9D1SSlYHDTc3mw5OW3DJt3bCALgE5itw+g8D+C5t9hyupowvWrY9pZZY9NcZJleWMgjTlr8/EobYO9vJQmwGoy4xD3eutgJLWxO5wYmk5b5PMT2tTllNmsZ7BZxFdYmwMLigxUvQimE1nLcfjqrR0qJj5ZEyOAGpTXN/4+8P4u1LVvzO6HfaOacq9392aeLOBH3Rt4mnZm+aWe6BAWFqCo/1RvIUPBmkChZQlY9wgO8IIFUSEhVb8hQghcEZZUlI0AqhAoJQcl2qUzaLmfe/sa9ESfinH3O7lc/5xxj8DDaufY+cS8SDyg8Qyf23mvNZswxvvF9/6+vvdmv7yyrVUvbeiC2XLS0rWIyrVBSMJ5o2tsdWnXs+oppY1MtfAc+pdGKULkrvFthDXDk0qzSWazz51oR2/q4xEQJ94vCUcYWq6G7mrM+I0LqUtPytG0NtGs/33rsi5AYa1lsbjmaPKHuau5uVxydHdPbjs60Q2azp5GXmlKinodKSflX0TZXDK4vfZ9DbegR4nHQ9pJfXs/4ze2Ez04WPJ1u/ToGLRGgTG96SHhFvr4rgVXQIB8Buf7ZMVaFZNaVUiQrQQwwEwjP9K0CJ6gbD+BFKIVZ1xV94zg4PeWzzz4bdJgbzl+erw8dB/MDv/7kFLLoJsI4qsoDQJckqgu80b9nbvRiPfgWuY7H27crjIFXnxygdY4Timlz6gNgpfSfu/B321pOz7yC9sFI/EjnyVKb6V4GZa8MKH5M1d2PZSrnT0ACQKX0HTWKvjP0xlJVkhcv51xdbrh4s+HwRDMee5kzqFVQ3PfmeodSgvlBk+RDqQw9UHwK4O6BQ/wyxspka0rZj8DzyrA+yRX24eNbIfSF8BH50cQyLNAgcRiMsVTaa6I+DcQTUSys41w0y+whsAKdSgQu9eIuEHySfB5lTSYVi/s2bB6RmJq1fsMs7ne8eHnAwWGDsTe8+uQJm80L/vzPf4IQghcvnvP9Hzxnu7tgvVmFcqgwEk1CpxHEjCrDuDIYMWI06gDvThBJ8/LPns0011ebkBNbh80ugt/cFlq+GArDcHhtf82L+ZifXnXUyvhAND/LJPY80GqKNfKLMZzb4SmDc1NRHqIgE6nfNxYMAZgAxmw4OZ1jLbx/d8X50zPG4xG92RbWDP9En9kUUXTxjiWaLpiBz8Heexl8d7P5QU3XWpbLFhApwGk6rVBa0veWWrW0VrHYVsyaLjxfDDXzkAPiIJVCds75qn7OV+ASznmQIKKe75KbIE6twNNztHopqehb2G58i+npzFsj4lr1rWO7sigtkLVvOyFcjEY23G+vOTp8wu3VkuXthqPjM66Wb4nBaHkV87zFJY6Ngh41ow4Y+D4hiERDiQR+CxOLQ4i37a3kp5cHaAln012mo6jhP7hftjL4YZWalX+X5A6JWmRxj2iVGARoOU9mSkqEU7hOYVuBbTXCCZqpYFIHgREAna40W91R1JnCWsvnn3/ORx99xMXFBYeHh3z55ZcIKfj+977PZrPh6uqKjz/+2OdtD6Y5B7lZ0jSkfHI/tSIpQqUrQVAU8yqEzWZj2Kx6Pv3sGF3JAX90zqUCOuUYIAKkCG/8RJvep1TXYR7i+Vnw5SNeX0brJ1dkAQbiTxkWr+RiKSi4THWLip3wsV5ZqxYo7ddltzXQ+NTOw6MGqQSX79bMDjTnT5v07uVzlouO29sNL1/OEp+CANyNRahHeKEoLFDldzYojR/YTy40VnJu2LjqQ8e3RujHVL2HrxsQocgLHWvq55rNxaIVSkr0FxlnkSTun06Ld/fmMJe0iem0wdolNzdbjo7HVEEAfPHFHX1v+c53j6lrle4kJczmc4wx1HXFdFax2ryl73d0fZeCOeKRgsCcQ2CYNj2364pdD5X0kdrWuAEBVLVmOqu4vdkyHlfhpbN/PxFcEHCDeRR+jMfTDZ8cVfzqpmK5MxyMu+Kc4roBxebv09Q+ah7dXzZHDGj3nbhEmOeg/VqJCef5yPQVZ09mXL53vLu45NmzM5pR4yv1RSZB1jIK3pxQtoNB3qyLTKO4Po4/gpim0VS1ZLvpWS47nHPc3XltuKqlty7sVtzbA9q+5mjSh6BCX54XAm3iX7YUKnGT+6Avk2jYa2w2F3Upxh4LrGAFm613jczn3j+8vO/A+a5em03PbmcYTzVCO4wFZ6JU8EK9Ny3L9pqj41Ou3t+il5qjySk3q8sMnB4uW6LN0mqyz5iF8IVRED7g9oEkDrz4UYW8WLdHSQe/bj+5POCP5BUHI/PNAr/YzfukGRm6EILUv0yUwDDcswA8AoGwAuE03X2NsF4jHE0ko0NJVQmEhLqq/HpoRUzh0kphiwF0Xcff+Tt/h3/1X/2v8utf/4Yf/vCH/Cf/yf8LrTV/42/8N/iH//Af8OLlC169+vjBe7nUSEzEkaJTbrj/24ZmJI8KCkcIhvaHlD4SfTypqWuVrIKxMI9+xDKRwECkyzif+CY7WotkLSgttI/dxxpvXYypqDEWRQZikWXEf1qouDxDYTrkbwHshjinVIlS+Op8V5dbdrs+XWOdo+8dF19vub/rmU6qAcAwxtL1lvOnEybT2tOFIxWWGgDl4q9Eia5Mp/ZUl5N7IrAhKKvhPtGK/QFrSXl8K4Q+eJ+rKtBTFOwpkj/MvBC5A54I+lWOtg0Xh5WIUda+gUIuATkQ+OGnK0yUuhI8fz7n3bsV79+v+fjjQ96/W6KU4tWrAx/4JwVaNUhxzE9+/JZf//o3NE3NJ5+esFpdcntnefKkpu99CprWVdL6/GaM4cowbTreLxraXlMFs3s0EZUa2cFhw9evl7S7nqpWRN/eB/Z7/t3zb2oFTw+3/OB0zj+7MIyqnlp/gMAi8ycH17hHvn+Mc7vwzMBLE8oXEjBeWLS2S5u5qnTI/V1z9uSA9+/g7dv3PH9+Tj1qMP0uCem4oRMDKocTHlzWvk4WgLQJXdLUpcjZH5NJxWik2Wx8sZHdtmc6qxhPKuzNlmbcsmwb3t3XHE06xrUP7Iylo2M3N8L4coEigZA5stxa54NPjUPLWKs8a7I4cEbSbn3E9sFRhY5BUoewXPSs1z6O4eCwRoTYAhw46VILAx8AC7tui5L3HJ0ccn15w2l9zGw0Z7G5319RotCEnD+9L51FXNQAcrJFLtyh5IkiEsJDIon77jHBHz8zVvDn7475kxfXNFXwX7v96zKqEC6mgBVv5HLFMz/0/dz3IKzIZnyswBmFuR8xOVBMDiVNHWq6Cx+Tb4uqjUp4374UAi0U7d77TKdT/uP/+P+O1po//uMf+U5qCL766jV/9mf/hPfvL/m9z77Hxx8PBb8MsT9l+psObsa4wR5TlLIAjnOTz5nMNLODOp0HLjREkml/uHKvwIPP47HbGZTO5ak/eBSWBIfD4CuqRjNQzJWXOO/OwLsaYiArAXD01ia+Mrw/iVajV9MF7WU0Vnz15ZJPv3vIfF5hjaMzuc7B26/XSCUSsPbvCKOJDgHee6JFiOw7oZAd4bk2nB1lUuzYVzYRylsiWK5FEZvwOxzfGqEvRCwFqbJZ0GZ/oYwpV8RypQKLLZB6ZkAExtP3vlpfDACURQCQo4guj/m7hVZyeDxiftjw/t2an/74kidPJ7x8OQ+RwoKmPmS1qPjxj3/GYrHk/OkZz19MmEwN6/WI33x+T9/rMCaJc8FSURBo1KImdYcUjuVWM2vagTCC7McajTRV5VtHHo/0YAPGd/ow5Xhino9aXh113Gwa3qx6TqZtwZMDebsi3oGS0ZO1v2K+0tVZ7U6bJf6SSotaH/2+27XUtRdoycQnHLDl/Okh7y5cEvxV7TCmTQK1BG15jAUjdzEf2CNsSRY86bw9q48I1pDprGIy0axWHdtQKbCuFd12w+HEsu4arlc1s75nNurQseBGeG8X1lfG+SiegZDepeKidSCsWgImPo2q38EkpBvF6n7gQcDRUeheWDYb8iSGcwonIWZJxEJNq+091bTm4GDOzfUtp+fHtFXLdrcOYIvh/vnGI89+tGiUV5VMcn9dyoV7jEwfe3xnFb+5nfL9J0t/XYEW4vwBg4I4aY8VJyZQKHhAt2n9oyJhNGbRcHCsmR0pKl2l+AqBD/qNMUQWl6vo8bjGPZ1N+Zf/S/8yf/c/+LtcX19zcnrKbrvj/n7Bq1evGI0aLi/f7wn9YHkIFjJHLnsbQaKM55BBWvlvoDGGEyeTamilGWSH5GM/3a4smxszYbbbvrB4Dq9LQIGo2fuqeP6nSem8Lrggom/dCR/HIPcEqwjvb0XxjHKAkYWXfMDC/W3Lx58c+IJDeHmtKhnibfwevbnecXDYBIvk0P2Q3qnkF/uWFUFRdj2PwQWeG2ljUHo4vkfpDnEPA4EfO741Qj8HMQhwKpnc/SRGAhgy7nItRJpYm8z6CJLbQBXmwcRkYdBfW4psHgIf6b1c7Dh9MuHFy3nI9dZU1TFvv97w85//nLqu+ZM/+UNG05bF8j19L2i7Hq194QyH4ur9lulUMZtlYoko3FrfrnRc9ax21ZCYcINNJCUcHNbc3m45Oh49yiTjXDqXfUTOxXuBlpYn8zWfbg55s6zZdD2T2uaspYLoIkSK/DPNWoCuw5Ey3IWeU/jnisG+TMJQimCmFBlYOGdwrHlyfsjFW8fbt97UX9XeXD3YcKXJnrzhgvxNwC6/ycMjhUiVTE7AdOqDLleLjvlBzW5nWC+3VFWPqkesWl8Q6HDSh8j+rK1HbdeDsHI+/VlJeMRvCpAlKsd4JKkqWdBrnrdBlcl4vfUCy/uf8Q1FArhwxucj32+uOZ49pW4b7q4XHJyc0nYtfdcGOSiy4Hcxt52sTUYhm/8HH5zTvW8fEApEHPZbdEScgzfLMS/ma6aNIcCppDlmnhDPz0Vf0hxFECCGNAGZMmQEYrsKu6o4PNEcHNW+YJj02j1B4Ke1Ej5Gowze2n9drTV//V//63z22WccHx3z7PkzmtGIuqr5oz/6I46Pj2jblu9//wf7bz7YtzEYz3/lAXKZqBD5375AKi0B2Srz+HnlzzL4LlrXhMgZFDZULT05ycHOMXBVhNJ48R69Md66JaAznf/bGlzgtUoqHBZjBJWuUKqOgxrMp5ASUTQOkkoEnjEEGvG4u9+BgKOjZviezssUh2Uy1Vy937BYeMEfaQKRQVYcSgomL58TATOE4mLlM8CRsxjSHAdmGd1NWfgHOViCtUeOb4fQd2Q/zF7rNt+itmA8LoN155zPZ06oMiMljx7zZn8YvBOYYtJK4/cCrKNte16/vkdXio8+OkAqgZINuEN+/rN3vPn6LefnZ/ze914g5IL15o6+61FKsl52jMaaptE+OGznOD/3QsRaS29s6MHsCUspmI97rpcNvZVoaYhmyrI+tXNeE7252dG2JpmfHkxnIURsMD1FUKWk5GBsOJ11vJzXfLnoGektMe0/pUWFSc5CNaPSBxr+IwsaFUggNbJyzgs8kzR7gvvFa+MiajK2R8oNT58e8fbtDRcXVzx9eoKuwdquWL/gfBBiMA8BauTNW+TThovJL+nSRyLmMQZGOZ1WLGzL/b0vjHRQNWw2HWa7ZFKN2NkxV8uKeSMY1T1KFJs40Giskx8joLxwieMRQXvNLhStCwHs4lA9Z0kAN41aBBoCh68Fbsr9Y33gqhM+avt2dcnJ8VOu39+xWbQcTc9Y7xaMmjGbdknbt3le4m2GSk4xi+Ih7e3/7fZ+fuDr33Y4J7hYNny3XuO7IELsORvnIs9TuGbPejf0k2YQ6M36oV13V9HdVxycKA6OahpdoUPxlrgXoxLinMWZIV+JGt2ubVksFklb/c53voO1lu9973sA/Omf/KkfhRD84R/+EeDT6O7v79MI+65PgrkMdhu+QwGgP9CkJX26p62yr60O5ruwPlmbrI4RoArhg3JN72hG1RAwF9bY6M7sbJ80/c50dNbQdW3YZwIrfTCyFt59YpQNne4e0piUEmPMADA/sGrgLWY3l1vOn00GczOwEliHMT3zI83luw3TWZUATARQzvnYCqQIxXWKlsxkYJ/3y14go8jgJ/K3NB5HCm6O81sqoR86vh1CP2xWrXVqe1mmZkDW4pKQ3psX57KwSxu6KN2I2ENbZAGHEIM8UmMsb75eUGnFi5fzUHxiznql+fnPPme5XPF7v/cpL17OaftrbN+GYi0G5yx959s0rlc9t7dbmpFiNPZLZUJ+qgvNgyqtAV+I5uJ+zLYVTOoYqZB0bWKnuKpSPH02Saiw1Drii0WXCJD9vc4V82E5maz46OCIX99pVq1m1nQly4RYSaxg/pGv7m/EJITSeAq/qiu1K0JUemia5HwdBK0tSOk7ITqSxo/c8vTZCRdvr3j37obzp8dUFd7UH4mCh+OJFoBSqKfXGvwdN1goDFLICYffnLN5zWbTs1zs0FoyGmm0tljbMRtLljvNYqfZdJJKOSrlm/z4joW+DHLUCF0U+Anxl9paoXX5oQ0QvwiAdBjQlOdroN1Gw5jDpwiG3uzGdizbGw6Pj7i9vmc2P2U8m7FerjmZPeVqdUHXt8P9lYTmQy15cHxI4O9/vEdThYKcrknnFLT0+n7KrDE8nbcDYffw0SJc49K+9ozb/13GDQnhTeRaKLTSKCpcreh3EmE0uvYVQr232aXSrM452s5XjkxBdaHUY91UvL34Nf/H/9PfLV7LD1YKTd9Ltpsts/kE63bkwLCSlgWL1RVVdZoFf6GBD95WFDDsQ6a/Rz4vP3lMyGQl7HFjc99bhPT8aBgjEcz51tCHf63tMPFv09Nbw65rU+Cqdb5csJGhzLrxlTN9jKJM9PhYjEH8u6RZB9zd7KhqxWzWZAWArAxEKwPAdKpZLQzLRcfR0SjdL/70iprx8kPnOYsZSZCBR5yrgbbusjJQzlWq8IlNnTydA2tzTZDHjm+H0BcildCNUxL7wks1RLmCUvj7z60rSr56KBW0LL8jSg2uTPUQktT9KPrDhRCsNx271vKd7xygq5q6PuLi7Y6f/fQnNE3NX/7RDzg4dOzaS4zpsdayazu22x1NXTOeSG5uOtrWMps3HJ94f5ExoZKbMal5UBSC49qgpGPdVUyaLiHdGO2eEaoIACKiR78xIDO36JeCrFVa/8r4VpOWRvWcz9ecjmuuNhWjqkfLwIAciGS+f8gwHFFgDY3mgbSjHHpwTTTRKCVpmoq27VKNAT/W2BggbFDbI+WW86de8L9/d8P50xOU8gJsICtKxC+iFvQYgyyYZyHYRKEhu7RJvRY9nVQ0IWJ+ucypnM7tmI0sk1qxbv0/5zQiafw+h7/SllpZKmU9IIjzU2CSuJYegPi3ynPoT3zoongIegShFa/wVcdUEPoWi7CO9WZJNRtx/vSMdtdx+/4WIXwt8tnsgNvl5YOFS+OJFggeOX5HtT2OdXB6wawzmCm1N8+q/+LdAavdildHy5zWu2d5ytYRwIUeG8HalRqlhJlUocFKJTWVqqhrzWxcsb2H64sO8UQynUmEyoLXkYOLtVbI4IuOL3ZwOOWv/Rd+L8dKEMrF4qiqGfdXmouL9/zeD15wt35Nb30nPCWlL5kbNPtPf+/3GI9rIiTYD17OwPrhgkTAm/hkmo6hFuoKYRQj+OMdjLUh2l4kXhq/l0Kw2/VUlUIXpXujado4gzE9rTV0fce2b+lNH4pZmQQARDCXG+v7BCjh5zVW9/M16BWxOc3Aghb+DurJ4Gh3hru7lmcvpmlPlWN0ZFeyr6XvOHsy5vpqy8FBMwCGUghctC6IfI/o6khdNgtQUmaCMXw8OJeAQgS3SqikgNhBOu3jx7dD6FMyAxcqT8XWhyG/MeQy9r2lqXUwMXlGZq2/xhiLVAItc25qQsKPoV1RNHwAj7SsY7c1jBrNZDIHDvj5T9/x5ZevefrsCd/73kdItWCzXWKMoe8NXdez3e4wxqKVojmsOT6Z+WpdKvggC5DSG5OIpKl8SoiWhknVs221N3nFcQVAUlrnUl3oqKW67Now1oYUQYlWMVgsRrXmJjBKwazpOGhGvF+LAaE9CL7aI8L0refNWRtw+drEngqQFe8tlUQLaNsO2M/dzY/0a9whlQiC/5p3Fzc8fXqMUuBCK94BARVAZB99Z2YR3iHkZQfdkIG6sAdoqkqidYWxGme9prPb9SwWW+bzhqOJZVr3dEZiQutea32qYtcrdp0K6+ColKPWhkqZQevgsjDHPrPyArcYUQQ3YbKSWyb+F4W+VNkPi0MpRaNHbNZb3r694OTkGCkVbdcxE9XDdU/rX5haRZy1DJZ/61ECnLQ+e+e4KODKs8Ln4bvf3M1Y94rvnyyo9N7FFBqg8P533+Nd5kBgEQrvOJGadNW6plE1ja6plOJgolgvDFfvd7Rby8nZODViifQRhaDcewkpJZPp6MGL9cYwHs3Z3PXMplOm84aVkcjAwmN3PS21/53Q+rZ4u31LmsP5WKXSnExeNoD9KS4DHON5uZd9ehCm7zPPEvk943N2W+PjTgoQZ51/z56etu9oTed/9h2d6X0F04Fwc0gnfVAkDqSisz2q98WPrPJCVQcrpcCnwNnA82PKbOwoGmnm9mbHaKwYj1XIYskW31iSfT/gsWkU11dbFvctR8fF+gWNP/aEiUpVLryU6W4Y+BfrCQRlK7R+jgAu2XEDPQpkUIBAiKGVe//41gj9LMSygEwC33mT++X7NTfXW07PppyejXAuB3WAn9zYXjd3NIp3JwlTAYlI4mJC1v76zjIeH7FaTPjpT3/GYrnk+z/4jI8+OmDXXrHZbDHGsNu1GGuCr0cwnY4Zj0fIwfOHiE8pb4Vo257e+LrzIlR2s8Co6vGmxKzpGOMbNUihHmxwILkWYudAX1LY4kKf+ChAYtCR7zng76OlQAqLFAUwEY+xjH3OnqVzAiTpOeEKmxdmcMfwDlWlg/XDAcYj75CCWD7Zlz6Gp09PuLi44t27W54+PUGqLdYWgj+ONELoPYSNKLXoR/TVDwj88iulfAleKX1b4PW64/5+x/ygoaoElS6QehJioReEhW0v2XaazaZG4BhVhkndo5UZCEGvDNikYYqCnuM+ie6ICPh8Jzf/7h7P+B7jTilsKFc9mxzjOsVut+Hw8JDFYsF8PufZs3NuN++TxBCQw2seE857ef4lKH0MKGaLRqaV+Hs6tRA66bug6uaAObhcj9n0NX90fuP7SLj8kOTyCsJFShlqreeAURm09EoqKlXR6JpaVSklT0nFwZGmqhWXF1t2uzXnz8bUTdGD3jqc993s0cnDF/emZIuUmrbdUNU1ne3YmR0xC185hY73dDq9qxQqdIjco90AvMoo933NPnz4gQUaHsmKEEF8AHoeMMlUKTXeqm1NatyTNHxr6KwX9ru+Y9e3dEnge+umxRZuVXK6m/DVKq219LZPKdpWBCHrY/q9Hz5YdVMb3HgvJ9hsOlbLjpcfe6UrKldloGLq5BrmxIZ7nZyOuXq/YTavqaoclFcGa+7aNlThVIUVNmaIZQUszlPUjJL7UIArs87iecKvlbcgPsKbiuNbI/RLE3bMPY+Ev1q1ycf+6pND3n695OZmzfnTcUprUqHpw2MFJjJazmI4aSilM98J6mqKMYa3b2742eo18/mMv/anP2J20LPevPVE3PX0nUeuWmuqqkIphda+jHAJz0tTcdSElVIYu6Pve2/aco7FpmK907w8Wg2KuGQ5lOsMlIc3p3krR/RbxgYYxli6zgvFSutBFy2BwDhJb31Ev4wd3CItxrlxUaNLMn2wZvGapMlTEDvwgCmGn1J4vz6OwBAc0CNCDW4xuL/X+HUF509PuXh7xcXFNc+enyLlBmP7YucUeoxjqL2nhRjywEfgzCNjzlIo9mkQwuf3g2Bxt2N2UFNXOZCpay1KCZT2nRCRUGnfPbDtJbtes+kUm5WmUpZJ3TOqegQ2BOeJtMYiavZ7oyynOnftCkJTCpTzPSZkSI10tmMyO2Y2m/Gb33zBZ599RlVplssVB6Njdt2aXZ8rIbrHl3F/Oh+bsMRYP+RrTlaNwXv41RPh4VnAxdv6i9ad5p9cnPCXz29CF0SSsMpKg0Co3DFNAMKA0MJrmFZSVTqVu5VpTv19mpHk5SdTbq9bvvpiyemTMfPDOqVCCvEQHPphFAGvjiI4S9O2Hc2oZtOt2fadL68MKGmDwPflliFYE5zLdScSWBVpn+6b6h9brMcC3dJ8he9jmnAOOvNzrfRQ0XB4JaNrDSen42DKtvTW0LmeXd8W/zq6vvOuAmuTwE/phQgMLhdeczFI0NILbw0VWKyUqFg3wuSMpEqqgQWi6wyX79ccHDS+WZmLgGI4FyU1xUBpY30k/82V4P6+5fR0HLZ7qVQK+r6nEhUuWKLjGjgH1vnaHbH0t4tBfMEiYXGhiFCoqilFzjQLdGuMpe2KommPHN8qoW+tDcUovJDre7+INzdbzs5GnD2Zsd10OBy7bc/rL5Z8/MkBB/MaXeW89WGwU77/QPMXwbQftFGlGip9wtu3S15/eQUQtPsjuv6a9WZL13UYY+l7Q9v31JVmNGpCWqAcaLtJypMD6yIz8UUngmhzgraHd/cjam19L/g0aNIGfMwPl0z6RrDcjdmZGiVBSWh0x7juqGu/4dVebISfb8fV2neoi5v8MS3goVik2FADFEB664SpsnRNf/sF8HmxUqLC2htr0UGoOsFAw/XMpqOq4OmzUy7eXvLmzSUvnp8hxRqLSWOI9/dMI2rbxXsU43mgGe29owiCPo0jvE5k+EIKptMKIWBx33JwUFPVkvWyZ7vpUw9vXUnqxndWlNKXRR5VLdMGul6y7jSLbcVyW9FUPeMqaP+UQrFwVZSaf/leLte2iEhNIYMrw2Fcz3J7yVgfB9O+5Msvv0IpxdNn55zOn/H+/it601OsZrh/QQ4uAnWygCvWvpy/xywAjiGlDbZN8RhZIM0chO1vtOsV//TihD98dsu86kP75gA24nnhdyl9UJ8UAuUk0slg3vdldePDvMk+iP+gvZ2dj5lMK96/XbNc7Dg88d3bnLVYEVl/IppMJHmxwneatt0xP5yybW9pTYezsYS2DxRz0mcM5HgeCdHVGczF0Zo9mD/x0MxfHlmZ9HM3xAhZ4IMHKSr40WNtFBEEoxSCvvcBuEpHzdzQmY6dadl1Xti3fcuu733MUxD2g0C8MFcyeOSTMBSRL/oiPjiHsQKtrLd6GJAylmz3499sem6uvWl+Mq04ORsNQM6+XPCPDnzV5aBFpSRnTya8u1gFmRIDOD0oMqY04ZO6OyZaRSTaC7MMwqVAUByJtspSwvupgR/qfRCPb43Qj4EkEcWtVy1v3iyRUvDJp4coBRdvl1xfrTk5HfPy1YyvXi/ZbnqOjsYDJBoZ+WM+3UQKkQiFpKmPWK80f/6f/4qbm1uePTvnu5+9ROol6+3XgKPvTWamArRWjMcjqkqnBUxmZYYAIx0ua/pSyOQnvFmNWGxqXhyvUcIWBBD94rF0r0gMJvrhtp3iq5s5d9sxYLnbdtztYNvVfHzU8YcvNhxPMvOOjNoYy/UKrjc9J9NHokXT/nAPPowQJm7OuIHDoPOPyHApmFSx8WLQjpTCx0b0vQdWUlHXOo033tARTP2V4OmzM96+ueTNmyuevzhDshqY+gtZkcbzILCJR0BLKbWIm3FPc3qwKR3jsWdY9/c7RiPNbttzcjpCSN+tq+sM203HyjjqRjGdVMFMCKq2jOqW3graTrHpFLebBiUco6qnqSxK+OZLEWy5CGj2rBg55VI8+OnwpnBrOwwbDo+Oef3l10ynE8bjMV9+8ZoXL54zHR2w2NxgosYSnzF4VBlnsi+C/N8DgV9cP5CJrrw+a+pp7A+sG56Rxnv1VjBSfdaqB0DNn+Mr5YlQREdRCR+4N6qbpOXHAL8UC+QHkK6fTivqT2a8f7vm4usdp09G1HOZmH7kJy5orkPLROivEDT9utYs+y3GGr+vTYjTcYCCziiEBGUVPcZbJaQk1m+MBXtK69pvO/J2flhUyRSd6xwkn3U5D+W+ads+FIeydMZ5k34w52/7lraLJn2v5bsY2EqhOUfgHIS8D2SUCCvQlSqsnZ5XOQdagnRxLILFouXmakvXWuYHNR9/Mve9KQoeNMBgbqiEWestoQ6CK8AxnWmqa8n19ZbTJyM/Xyq7A6KyCAz3XtT4hLfcJAAW+jLEeU8pgQFo5eZxIYhRqt8q1b8dQj8JQ4m1cHW54uZ6w8nJmKOTMdttx9dfrXAOnj6fYo3jqy+XGOOYzZsQCFEQFcDettvTWTDWIWVFXZ3xm19f8Ztff8l4MuZHf/z7HB5KtrsLTEgrgdCCNxCRUj7VrqqqlHPpg0xc6t8eGXTily7XhJZKoitvdr3fNrxbHDAfdzyZrwejtPH6wBA8kcQpczgneXM3Z7kbUeklv7jZsu0tvRWsO83brzR/9nbM7531/P55z4u5Q0nHppV8flXzD75U1NqkUrz7ptgBcIkbtZjVB0w7MRKRPou32xf4/k9fNMlZh5U2xS74dfTzwyPai7PegvH02Slv31xy8faap0+PEGKNdbl7IC4/Mprg9l4n/+2GtJPOL4FDfIf9i8O3o5Gi6zSLRcvx8chrg4DWkiqk+5nesVp13N3tvCCJFc0EPuVP9ozrnt4Kdp1i22mWO1+7oakMI20CMIxGw2E6EsS0wFzLPA7XuhDIhKVtV2hZo5Tk7u6eu7t7zs+fYK1lLA8RY8Xd+jL1iSjnaagpRibskoB2ezSUQJbLdJKvL4DWnnaWy8iWDx+aA6yTfH0/5tXhhmj5Ki0PMQhLK+1T86QOAXsVTVWhhQaErwwpcmBaSXcR92ktOXs6Ynnfcf1+R7dznDwZ+TiPOEyXwUqUOHHYUki6rqNuKtrdNiskwpvwo9ugtwYttTcXWxAqF7uJ5cTju+Fc6ND4zaJ/aBkarkn0bcc5jgFmSsqQhZC/d86xWOyoGomRhr7v2IWAvV1X+PCtpQ/WO1mYsa0j1fGPbaMjjosCv9Z1mj5jDdb02N7S4wNR29ZyebHBGsfxyZjDo4a6yhH+JdiM71fufYgxCLGYUAErheD0bMzXXy9xznB4XAde5HL6p3O+lHJh7fMtjT3YM9aFngc5cFqk1M4MSIZpmBkc7AeH7h/fDqEvQjOIreHtmyXOOV68nPtAmvcrbzY9rBFCcPlu4zff2YT5wShEkIqCsWXtpPw8fhf9e1U1o92O+af//Ffc3d3z8auXfPTRMcgF6+2KGERVxhrE6HglvS9w6OtyCRHva0TGGDpj0iaVSlJXFW1fc3F/hJSCl8fLQSQ3hApX+E2C8MFdZXT+7WbEzXpMo9f89GZNZ7x2o6Vl3hjGVc+m0/zsneIXl4pGOWaNYNcJlq2l0j1Hkw6tCj4amYh/qUeFYwCwgahD6Fj4O6ifiVEGxeSh4A6qavR9QcF3QnSuj5DOG8MrN/6m1rY0Tc3Tp2dcXFzy/v0dZ2cHKLlLBXyGVtdsMdj7arB+SbMJn0YhM7AKFFpSApPhs6ZRbLe+hW8CHvFOwvd1ODis2W0Ni0XrW/2OtU99isoCjkpBpXqmjV/D5bbifqPZKMusaal1jyhWZxj/sScEklnAv18EA12/5vz8hOVyy2g05urqisViQV3XnD87o6lGbNtNetkyPiUy1sCuiu+HWlaco+GmKGc+aq1+fHGdBwL/AfrM1yLg13cHOASvDlYepAtCt0GvOVUhD7+SmpGuqXVNrSu08G1xY9e6cs4+JESVFBwc1YwnFZfvNnz9esn50wl1oxJQSDxHxKwKh0DSh9x+oUjukxjIFn/vrUFbX8HOOB/EJ6XFEluIiwfje2i2fvidgwdxIc75aPuSXmJ6Yb5HXkSHN+uvVx2TA0Xbt0nDj1H6MQ/fOF+PxCsu3tYnhETFXhUDpuLXUivFqPJrE83v1im0VF7pCgWZbt7v0Epy/nJM0+giOr+kfU84UmbNvtT8pfCpmLH7nQw+k67vEcpyfFpzebFFSsf8wLtwjfWFxCLcjs+qhCLuAptNcCBiZP6exYu8h+K+FbFut8v1ZT50fDuEvoPb6y2XlxsOj0Ycn4zYbDrefbmgqiRPzqfc3W3pWsOT8wkHhyOfI7tXhcrPd2YWJbKNHwpZoeUhFxcbfvHzH6O15kc/+n0OjmCzfU+39X0xY0lez/MDKgxoT2uVKur557rBGGLr0thDvjeGvut9poCz1MKbdp2saE3FfNwy0n1mqn6kRPM+BI0FR29yTu31csy6dfzkeouSOUwx3qdSBq0s48oH7VkrWHf+85Mp+KjUvBEGC+IK4fiAYPcEaClk3JCgiWAgcsICRSSlKvzMpYmjDuuywB0OwQcE9TuaUcP5+Qnv3l1zcWE5PpnTNBXW7vw65GE9DjyKEZTjiecPrANBimfNOvyv0IR0JVPRjsSgy6cExjSe+D4K203P4r71hX8mmkrHEr0E4QfTpkdJx+XClwntrUI7F0BiGbyW6ebBkTRQUiEQ63o6s+Dg8ID7+w1d1zGdTtjudiihmTYHtN0Oiy3maujXfPRBDGkqj2c4rhIYxMkUUVo+PD2d9uBj5/jybsL5eMW4ITBOkTR3nyIqqXVFXdXomBoX+3GE8sUPOPPgEUMrRDOSPH855eZ6x5vXK06fjJnOfWxHAr15eAip2W47X5RKWKwzKc87BRCGOhnpP+dSlkTZcXMQjV6AlYeZA3nspdvDQvBRmxRHVbpUog/bxUVwXhV31tHuetrWMKsFm7b3vvwo7I0X9iZo+GXQXsrKKflE+C+mtyW3Zyp7HFwNwmfMOAvbjaHdWT56NaFpdBq7f79oqRlmgqV/e3OUzP3OoV0Iig5FeMYTxfyg4u6uZzZvvDvVeSuvCoEj0R2dAFO4X+r1UlqKIu0kGirl1T6Y/jAdwrdE6Hed4fPP73j2fMbx8YjL9yvW656TkzFSCt6+WQCC73z3iLqRISjtkRsVnz2cOEGlx/TdhJ/+6oI3by44Pz/je9//GKnu2e6W3p8c00GED1QR5LaRMW2lqirfY7lE2LG6UohUdWThFcejVOi9HTSQaeMYVy2btmKxq5k1WwiAIRJTtDakYh8ud4dzOBatoTWWUQEOM+F4wq81xJz2xGjD12X1vtyjO7wTUfksta4ohKNQHxJpFPR51gtVLarEeaAk8yfDJjTxR9l4KH0TXsDh6M2W0XjE06enXF/fcfH2itl8yuHhBKV6rO18UGB5PeVGfKBKJnNnFPKlPl3+licyv6UAXw43lFpOV+yBHYc3F8/mNcY4NpuOxd2O8aRiNFJZVQzX1spSax/hP2ti7IJPBYya5D5DyVPuP0gkUdCHMR27bolA0TQNp6cn7HY7ttstQiqmzZz1boFJqVbfzJD25U7W6jLwe3iHAnyV3+/LMMEg2SZPLBgnebsc8Z16W2h8fmViDnwVc+CLf4/G30ehvQduS4ufAJSWnJ2PaUaKy/cb1quO49MGrcNER+zsvFl+t+tQSuOESRaAgMay1i/zczzoi0Ld/4sCbFhMp5jrR37PrxVb2oJxvrZJyWcGVr7w/nl3+DEuVy2ycjjhq+p11ufkx/iE2FynD210U3BeIfAdhKZFfncJKXw78eDekERzucA5r2ELBT2WVbD6jkZVKubmiveLpvwImjzwcLgARnD5vDiYlGIdBHlV+SJhxyeSzesV241lMlUoLVN+vnMxZVAkXOTLMMtH3VIu8L5UuCsCk/IFEt3+CyD0+95xcNBwd7fl6nLNbFbz7NnUB2pcb2lbw2e/d8JorHNTng8cj30nhKLSh9zeGH7+s1+w27V8//vf5dmLKV3/nr7rcKEDlK+YZ0GDFiqZ36rKt9ZMCsH+c9LixYXMWq6UMvWdhmBaEgKlHKeTO94sTvjN1ZyTieJ4uqWSLc6EFBUhgjk//B4Yr3CORhueTEYIpbnZmT3xlX2JUe/IWn38IjOx+DMymFI4Jr0zEG5ROjowi7B54+uHX/x4ipK4xUaL50Z0HJG+tTb0I3dZp45MWOyx6PAexmxpRjXPnp+wuN9wd7dkvdpwfHzAbDbBssPZfqglJgDi8r0KQR+XsCCiobQqNUNXggCCSZHh8+JtyjUKXyotmM5qqsqwWnZY53w3tGKYUvic/s5IL+L3pF8J15KMHarb6ezsMxShLn/HZDqirmuUFoy14uZqw3K55vTJEabu2exWBZAsprB4SWfzmogiuprBVcV1g1n5RkX74U327TIO1p16sDd9d8d4fw+NcjjscCwi0FlZJTJeF4H4/uMFMJtXVJXg8t2Wt1+tOX3S0Iy94HDW03ita1a7zgNB4ctwJ4RTAjTPMYLwKDpQkgUZLueN7wt6t7enAwsBRGqIAzE+SIa2ttktIQf3C/UiwtZ3zrFcttQjiXGG3vq0ZdN7k34EMta6wPf8w2V4q+F2CxaHBNpyG3Qnhu8XrQ/trmO3NTx5Ok/CNypDQoiUARQf4t0RvhOitcbTp80kE3/Ge0U3T4xlqGs4PKq5vt5ycHiI1gobLAFSyrQewnolrsx0iOAjlm4uHxrTHOOiJ5BKnptvOr4VQr+uFVUt6XrDZKJpO8OXX9ynvOPzp1MOj5qQXheJORPnINp3cAjqao7px/zql+/58ouvmM9n/PEf/4Cq2XK3+Cr5mJzzTS4cPlpUBmErokYgZGomMWBmxQIZYwYm1swjXDI3en+Z9w0aC0eTHZW+4nY75Xo15mY94Wiy4Wi8opYdQgR0GiIErY3BfILjyY7b9ZgXeoaSLZdrW4wraiSZ4fmR5PziGHD1cN4C406zzd5vWWsL0zwsf0ri/YU5z6VzS1NxvI8X+h6RI4b3d5A2UIoiFqR3Q4jgx+85PGqYTM+4vVlyeXnNYjHi9PSQuqmxdkt0vUAspRlftyh+Eta5pKsHGK8YW0QIcZzWOJQaRj4PeF45d3laaBrvslouWkAwnehCk/CR/Derhl0vGVUmgaZC1OdxlouRNH0xIF6X5t/R9Quk1Gx3BusMB0cH7HYtdzcLDk8P6U0HfYtNt4/MtsC6hdbjQedw0vbjXaKAHtJZnpbHMIBzDNfC5V9utyOMW6FTpcVI8zbXs3AWrKCXBmVzk5y0/sGCFsdro+YZW34jBoIxmrCrWvLs5YS7m5aLNxsOjmvmB9oHZ0nQqmK3bT2wpceU9dWFB0xZqOMLdrlsvxGBH8W98k1a/pAf+tm11hbA1qWiOx/SLCMAib/5UuM+DfXgifSWgmiBDHMYOzoS4p5k6EcgRF60rASE2vPSz7GzNqyP8dVVlQ0xF4S1EdzdbZnOa8ajajBWEfaHsaFCqjEhJsgFvBf2XyzLHmkjEJk1FgtUoSZBNMIopTg+GbNcGFbLnsMj/72MQZ9464dMMmKf3gP1PJhel8acovv/vzi+FUJfa8mn3zni/bslN9dbzs8nXL5bs152PH024/mLua/RHIoflIdzLhVLKX1dVTVBcsCbr+/5/PM/Z7dr+fTTj/n41TGb3Xtubu+9ub2ugt+pMMc7h640OkbnB4aWBObeKnrNwC+krxMdTUouRT8nH3ccd/hX1xqte0b6kn5Sse6n3Kwm3KzGHI43HI6WNKrFYTJxhap+81HLq5Nbvrg+5LPjGR8d3vPj9462D7r5nrAaBMMVjGE/+CcKgsh2H5hsydpDPCEyYxsJuRD4Wa6KobBIZszSVSCR0uYWss4zCg921GAMXuDGMfqn9P0GKRVPzmfMN1Ourm756qsLDg/nHB3PkLLFmF1i8gIimiCo1JnC9hD4YKx5UvNcAtudwQFaR+ZRrHnCKFni7wu7qpLMD2ru71ucdczmVRJslXI0lWW5raiVL6gUmWIy3yOyFhmZXTgnBfuFd0raF960amybgEDXLzk9O+Li7SWrux0HRyfcrS/prY89SWAnrFHGdp7J+2mJtB/HtW+lExEvDeenuPX+URgpEtqITLpzin/29pinsx1SgBKO06lhikEJQ9/7Sm9OkIpo2WL9imEl7VJEE2x6fnS52bS+SSMFTk4bxhPN5cWGzarn9EmDqHxRlrbt0FWFcV3SumO8kLQCb8P2xXl0KKZUAmuHCz5vyWBjMxyfFGJw/zRd4Zror3e+5ismgv8wwaW1oLQObDbeIooigRYhgnUguD77rsdF64oNmm4Yr8OG8rn+aVLmNbci0qAPAJRIr+iEsbU7w3rZ8/LjecF24jhJ/AMhcMLS2o6+60H4udQ6lF+K7owo+KNbwTkUvmZI5FVSCrSqOHsy9rn7h3UK4HYu7h+Xs2QKOoqZVy6Aiuj/B9/zIZ4T5zz2mvldjm+F0I9i4ezJhL5zvLtYM53WNJO65KmhZO5wYoQQOREc0HqEVoe8f7/l5z/7CxaLBc+fP+OP/8pH1M2O9fpr2s6bUBvfezf4lki5qaNGUTdVqgyY/NQfKI+YLRCeE+WAPJ/f7035cWNlJBk+IHbbk6ZnVC04Hq9Ydw1Xqwlf3JwyqTuezDbMxj0SH5wWWzIejHe8Ornlzd2c84Mx3zle84trxz9/CxS5rgPsHgm7+Jz9Twaadv5DDM72VJ3etjCjRiBdmpiTa0IUsjJJ9iJq28rk33fpa5e1/CLXNWpnce79hjT0/Yq6qXj58pT7+y3XN7csl2tOTg6ZzedYt00mf8r5GGhDWVNKaz2YTfI4nMMYWK065vM6aRXlkQV0nsN9jR88CD48ari/27Fc+Ba/MR182vgWzJtOMW169iFJMalJyHowFkFfoVkP1Gbh1c0wRGt7pN5wenbM3e0SzZjj2TmLzS1SKta7ZdZW94aAi75LMQCEZdBTns+Hf6StsS/9XRx5/tC5LLwEcL9ruG+bdEZ14/jT57ccjXtEKL+K9jEXEps06KhlK6mChupBpiT7iT3t5menYLry9YXP6W9e+XatX3+54uiJZjbWdF3HZDqm61aJ/q2xWON8y+XKCzkZhWRhGUmBahR7oRDicb4iPcjoKitSy+IRrRNxwZzzNCeEQJi4piIJfW8Rs6yWLfXYC1VnihbHDqQLefZKpAyAODnJ3G0yzUceEMG/C25VIw2d7NFKFz054PpqQz1SNKPcd6UknBxc7ECCVKH9r+3pnS/IpFA+1VpGsBsDCfGtc7EBqITqjNYDxNm84vK9YHHfcXpaBSCdo2kiRXqLRVwXv3Yx1Xtoiclr5XC4UIcg8sx/QYrz5JSZj14dcrbpubndcHe7QwC3Nz6qv67Vo4xDCB+VX+sjbm8Mv/jFL7i9vUVrzbPnJ/z+X3pCb6/YtW0KFqkq39jGR+Nrv+HH3vtEscGGz/E/y4CR8pxscnPJAuEcoRdALq0bNayYpQEEU1vwtWEZ6xXPpgu2Tc3t5oBfXx8yqS1n8zWzZudztQO6nY93CBxv7g+4EiNORy3/5U/W/CdfuFBgBUaV4GwCnxw7TkaOm43jH3ypHmia5REjwhMrEcP3jcQetQgRz/ScKQn5JOjyXkg3Kq0OkQZiwwmx95yAMQZV/tLC7AkMz7R6jPMIfTZ7ztXVHe/fX3N/33B6esho3IArNFdc8c7x73jXgrFQLFz41jpCCp6krnM98PTSiXhI2nQxJQ8UN60FB4cNd7e+/epsXiOASlrGdc9y60v31jHNsxRGfrR7+yTnX6f53H9otAyFE/q+ZTyeoNUJt7d31HXFyfwFpjfUesTV4l24b3GL4n9Zw/+gYprOd/uf7R9pHdIk7o1736rlz+uM4MeXM/742RJndzjt50srvx9r7TNpZArAigI0BpKR712seSrKE7R+G7p1+r4WPk7j/NmYppG8v1hzOLW0bcvRyQFtvyNGw5vYTbQozUro/hlTWREMot+TPz5ZHaLLbkgD3hSdo9sB+t4DRetiIKBfP2ssUuWgZcL1MY7J9o71yjA9UVgXS+s6MM5XNSSOQwagAUL5hfVlwk2y/ERlIBZii5DbxToFvaFXhipUJmx3va+n/9E8FdGJ5dZjlgDg4wyc74XSO4MVBoPBOeiNQIXSvjgQ1hO6cTHlWFBJhQ69FyQyPN9/9+R8wps3S6bTitFI4+JaJ6AskYE/RStvipeQhaIT974La239+XHulfhAcGlxfDuEfhKmAI7RWPN8POfJ2YTFsuXudsfV1YbZrObps1kuaBIurqs5203Nf/4Xr3n//pLDwwP+8A9/yNu3X/P0WUXb3QyiSp31RR6EyrnRUcvH4f2XiRQfIvsU7Be159iuMyJal89XRWSoCFpQeb/S/Ka0yvys7+lsRy3WPBlv2dkRt9s5X1zOaKoJp9M189HWp205x7ja8PzA8fruiK9v5zw7lHxyfM+vruCvPHd8/wloFedZMBsJLjeOn13uZXtHOU0+N79nEOtZfiUiLlGBs3ZwzwgESuafmCmx7a8ILhogZEzEe3qQkLWqJIhF1lrT5svQI74BxuwQouf8fM58PuX65o43b94zHo9C6mVOvYnlimWoESCkTCZKLxQM0GFMTwxkcM6x3fQYY5kfjJKwy5NYaNfxheMrJdT/UOtVSnB45AX/dtMzHmsQMKkNm1Zzu6o5nLTU2qZ7uQJEFb96pixI85p8lwyfHbUPgUDpinZrefv2guPjY+7ubnn37j0vXj7DqdKd8E3QMUcsP8rLCjk+AAYir6IrRud/ZMaZbiCKU4rPnXPcbDT/6VcH/OjpHUeiRzjhGboWWKdRca0fNGkthhOtSvvDdyFYLGirChU6a3p6np9U9Lbh9ReXtF1LPapY2TZdG5+rpI8Zktrni8esFU+Huf59BGtlkFsUojEVL4/LDM4zxgvESmtfCKeIRPetdEOL6yDMfNtZmfpIWON8tUnbA6HCYS2zZpo3vSdz54WqtN5d53mFDUF7DmccxE6gAfiZ3tJjcFUG34v7jtFIM55WiVBiPf9yHRzer+8b/rS0pvP8Hm+18+DEAwU/vpxpJYWkl4paVVTK+UqNTqYyveOJYjJR/OqXN5yeTTg5GaPqGKIoBuPwvEQma190q5UxGz72obDSkOHzvxCBfPFIzBKShnx8POboaMxu1/P+3ZLPf3nDi5dzZvMarWqUPOLt1yt++ctfopTkD/7g+5w+GfHrX3/FZOaYTGVYXEfX9Sn6X0rhi94UhTmiWSaaAYvhhDEFtGx8sInvmFfmtGYhEE3cisIH7DLiS6ad4uVFYBQOFxr52JQ3OhIbTuoVO9Ww6A55fTNlXE+Yj1om1Y5KtYzqjvP5ki+uj1luK0ByPHH88DxvoAxMHH/pieAXVy4UnBhGj2bgUiyOGyrtA0HlSDnFiWZFuC5p4iVXKLTdgZk0a1V+nlwarytu6cBHW4cJTYBiT3pmE6Kht2uakeb5syOWy47lcs1muwtjjivohn8XP4UQjEZN6KY4DoGHHV3bstn0zGZV4cZJ0zIUZlHoxmEGAUx813SiP0MpwWxesbhvaRqfNlQpx8G4425TcbuuOQqCP96/XJNyHHEyHosbeozRaNVwebVgNpsS98Wnn37CaNxwuViihPSBcd90CJdo/YE6v/938Uced3GdCG9SCPwSPOaJHr6Lc7BqFT+5nPPXXi7okXS2QzmJxviAuQJ8PTAZiCGw8fToy6bGcthCUPCSaAXw95vMNBdfL+haQ9NUdItdtvAFDV6mgK7AFWSw/oX2vVIU/ezjdBQaeRyXiVqvtfRdH+qZyAQCsulYJPCAc6gwWFF8FivpCWC97qlGAqF8gKFSMsUrxc6lCRiJCEJc+g9B0maN2YuVCGPDgZJ9KE/up94Yy2Kx49mzWQKPvnxuB0KkALooUI2zoXZAS2f6XGwI4YMGnUUHt5QJQC1axbTSPpDQVVhV+c97mRSAJ0/HbDeWm6st61XHy48OfCXA+L5h7j3oy5QoIs2EObLODuYr8S27j3wfP741Qr80VUWmm3NIYTTSvHx5yM31htev7zk7O+L46JRff/4V799f8eT8jM8+e46u1lxdfcVycc93f+8kaxl4YvHtM4MGruSewM+yab80YzxM7wV+jNqMqyrwZhrrbNxPmeNHme8lY/rdmGxa8g/KAkBJ33pWa5W0CSF73HbFoV4y0zOW/SHv7qfABK0MjWoxTiaG+HJm+eTAb0nT9z41JXZgI3T2cjkIxViH6R1ta0LgnC8tm7rzuYKIS002vmswE4j88gONO56bfJXpfUuO61Jzv0FWGvgGJ1KiolYbsXF43h4f4YH66BzWdTjXM5vXzOeHieZiWIZzGfREP/hmvaVteyaTEavVhuubO7iGpmmYTke+apiuvLuAQvjum03I8xf/iI2Xyla1OdDIH02t2dWW9bpnPq9BwLg2KOm4D4L/cNLR6LKHQp5PnxPsP1WPCXwyqIlA1GevdBwfH/L27Xvquufp03Pu7u65uuo4OTuiNy3bdu3fOK5rpId0Y7KZev+h+39H5jcAP3snlaCSGDCaH5qxRPFb4CG3W822tyhpfd92K1HGF4KxCTjI8gGJflI8if9j8AqyiDER8ftk0hLUteb4+JA36ytfw8GGDnIlSIlrHniRLL8rnmvh0Ujx+HxvhTTsus7zKut5SNRoK61TCrDMk4dUwza96Z4hQHpx3zKbVym9D0KuvzUPgFmcvtj6PEb5W6JgDCAgqPemtzjR+6A6VNqTvTXc33SeD0102vOxSVG0zmYt3zf/MdZbdE1vsCH7SQhBb4L1Qfh9En3wNgI47XsQGGupjfWxBVKjlUQ5b/Kfz2vms4a3b1a8/vKOj18d0QTLc0qtHqyJn5SyMqOUe4V7otJS0NE3Hd8KoZ8ZdUByzvHYewspOH0y5/DoKT/+89f84md/jpSSH/zwM54+ndCZW9abLRdvF5w/nVFpibHGm1qEQUpBXVcDhPzYBCfGvPdV7FvvF1YS/WsRyXkrwh7TCM8pNckoZAaKTuQRxbVlIQipfEaBlILttgW3YVzt6Ixm5yYYq7FOIIxjpjbM1I7jZoNUkr6XgQF4P1OsFX6/NnSdo+0cXWcxvd+MSvlz+t6yuO+YzHz1ON+vfSiQHvc/laF/JLAQJmpP8qUbRYmbgFecmDS/ziGs77a1JyXS6eX85W/3D4sx2wHgEkmAhDSpggDW65abm2vadoIQmr7rWa1WKdBISkFV12w3Dca2RABSBtJ5YWU5e3JI0/iUo5ih4MjvncZcgkYc06nm9nZH11nq2mtCTWU5lm0W/OOWWmXBb51v3tL2is74rIhJ3Yc4gBxfEuch+YfDY43tqOuajz9+AULy1euv2Gy2zGZTFvdrpoeH7LoNUgzLXz8qsR+X4mHNHlHSBQ+vcXF9y5MjYPa/Z4Ef75GFNggWO82o8kLBM/XeC1ErvHadpnxoPRB5g/q5DbEySdCndXtIcUrVnJ+f8PbrK1brBUL4mAIRyg77rnYyWB8VSqiUElZSsN3jKymAcc8SYYzB9N662VsDfag6F9vkqsD3CgvJY+V9cxyAbxh1Nh1jhUmWm9hhLwrO4kLP36KVJ/UUsMUa+tXz2QH+M1VJrPDd9TrTQyu5vdlycjre0yv82OMznfMgrrM+FdKE5zmR+50k95Z1GCIfDkGNziCFxHY2WHB7jDJUsqKpwCLRDkah616lFS9eznnzZsnrL+/46KMDmkbzqCwJzCwHBpO1/LDXrCv2T1zXbzi+FUJ/n2HHBjrlBhJCotUIY2d89eUFy+Wa2WxK01RMph1td4mxvhVvVSsODuvk84l3UVINTC9lEEx5SJk11TwukVwDIpbodVEjKg3138S1/GED9cogEBw5jcPfIQZdBaEqBCKkYanxiKqq6LoeIWDsALH1ZqoAPCJDMiZuKpcqxEklgYquM6xvt5w6yefbCqkF9cRnGcSgocoq7m9alouO2YFvJyqFzEUo8Oq4GLxrjgvIunieB+eK94sfhJ8uanFJS84FUUoXSvRLy/AMBhp+wfZ/SxRsyVKjwcHfLAsuax2bzY6+dzx//vFvReHfdPzmi9+w3bVe6Iti1ooxDwLtikNpSVVJ2tZQ1fm9lLQcjHestr41rxCVL3gioDMSYwVKOGrdY6zkdj1iUnWM6g4l3MDCUFJrnIu2XSFVh+19Js3Lly9C3MwhyklG9ZRtu8rg5bcdBTkUuO7h8YFbeYBQWHVKdD64Jr5X3o8Oxy+upxw0t97aZyWt6fyaqkgNIaguNMHZH5oLA1ahemX0hwspUNHaUFgH/P0027bn7a6m+vKS0VHoUx9820KSKgZq5YuAxe6TkRiiclEW6ym7PSaLVQCiVaUwVlKp2DSHACwKPhOAtPyAhhnvudn0KCloGs3OlGnLLmnGxpqk5bu9BY5pesb4tGMTS1QLkutCuGBlkg6L7z2wW7TJnx7fzYZ8fke0IPjPOtMHH74vFFQGW6d3xSZlK1paoyBOQMGBQyGcB0c+JitG7ItEbrqSvHg55+3XC7788o5Xr46o6lCQqaBDG1I7I0CM9J+tiSHdO9BVdBt90/GtEPpAKjzxmPYdK+rd3zp+/JOfstu2fP8Hn/H06Zg3b1/z+edf8fTZDCHg/m7Hx6/myawS066EkPg077gxA1HbQmKQn++jai1aZ7OS3wQZEORADS8nhIipMN+waA6sMbkADFlbzugvB1P5SzIVSSmpqyJy11qkVFlbdLHmf9ggnW9Zu912jEY1da0xwrC4b2lby1/6RPD1b6Km4Bt7uLApbWoGYlmvOsZTFWr8h/ahSRPNWk4SvilIZV/sl9psqRm69GWMBM739hswagQplWfgggkCYSBVXC5A9OEVyfNPMZRwQQRRo1HD8fHxoybQgTU3/R6YYvH3u3fvcG4X6CWY3Slz7fP8PByjL2K13fY4q1PksweejtmoZ2Qty13lfaY4amWQlWNc9WhpcAjWrWa1q2mNYta0VNoMha7IJv5IE6bf0VQjxmP/75NPP2KxWHF9ccPp+RF939LZbqBtDl7Cffj3D2GoAUmI4d/pMdGKsnfBvuwXIn96v9O8WTS8Ou6QIZI9/+c7EWod0raS2k9SDqKQsLg0kFLbz4/NY9G6Yrtt2aopv9iN+O7tPZMTjVQ23VcJRaViIFkVigENd463KsnsatjnlVGR0BrlfM+PGKwHhNr2YlATHxiY7B87Fvc733RGKqQ1KJFtfZ4EbczcS4Bc4LvNQdgJLpfDtdYidR5XYiPScyDvlzfc3/QcHo3QlUzuVkMo4BOsDL31Efu99XUYWuODbHPaoEvr57Vol4W7y5zVW1EkqmgDLEOZ5lgfJVVIDO+uteTFiwO++uqer98s+OTVIUKG7IqBNTkoLS5yhexuAzK4i9rSb9ErvjVCHx4X+JUe4+wBv/zFO774zWsODw/40b/0Q0bjLbvumtOzEVUt+Or1HX3vePHygPGkBmIUahbWw00kBj+g1BLjeUGQkoWNcy4t/t7gEUhyYZKHnC6iO+ci0yfVmC5dDr8tetO/W6jQF95BxnfEB5IYY+gdOOWg98U0emNwnd+M61XHeKaox4bTccvFyscCSOErkFnAGI+W67Gg3Th2O0M9AmkdArsHrPL6RRFqiUpzBlpRoEbBFzXEKGcFeH9+1D7i/6JVxPlxwRAMxfO8gIiMOsx93Eu/TUsXcbwuNaWJc1Bqb2/evOX8/Ak3NzdMp1Pev79EKcXZ2Rnv3l0gpeTp02dcXLzFWsuLFy/QOlYRc6nWRMIsIg2WRJAuBzJGGtRaYow3nQ57CfjgvEZbarUrZmWodQgck7qjUobFtuZu03A43qbo/3huYuiJ9g2dWXJ6NgdaNu2S0WjKjbWsFjtms0Pu19cBZOX1HAjpsPblEvwuAj9qj4jyw4JXiP0LBsaEAQCLBHixavjoYEdHl9437mctFMopnHBhP2XBHm8YBZgUEiH36CpPYgLiUil22xWd0PRK8rPFhN/XayanoT49Ai0VtappVOVTx/CguvT/AgNhXVqI4mTKmMpmzECYR+ucMTZpzEoNLZ8fOlbLjucvZ97SEPlcANje5SfBGRLPRBT1VEoAmS00XgDblOKIiDFRjh6DWbX0RjGNVQ3DnaKvf6jZe0tD5HF96FIYTftR2GeNJIK4OKexq6cFlO+iqhW1rqi0ptaaWulQZVCkewjh9+TTpzM+/9UNy1XLdFKHWLS8RIPtXcyKnz+ZLdJSpGyBbzp+J6EvhDgC/tfAH4b5/u865/7BI+f9NeAfAv+mc+4/DJ/928B/zy8L/yvn3L8bPv8PgB+ES4+AW+fcHwshPgV+DPw0fPcPnXN/67cPcrh5BJK6PmZxB3/xFz9hs9nwve99xqtPjmj7Kza7bSjdKjk8bLi5rr1pX4cUucRx/L39Qqg9rSybtoyxLJcttzcblJLMDyqaRmGlv08ZfCOCiTsLZ/+Q0i9aIt5A7iEYL0u+/XaexToM1BU3+H2o7uwTYVKcyVqBVgpd+ZzTru9pu55d16MNdM7w6qjjzWLsxy1kMGsGESwA4ajGsFv5d1I6I9jkfhD4ildJ+wppUK5gPEGQlsw0zl6G+67kz5k4wsIJMp04W6LyknbyvaLgL7MTBhJu79sSgIDPl28aTdu2iU7+7J/8Gd//3ve4vr7h/PyM16+/RmvNdrvl9vY2gcPPP/81SikODg44OjoGvCnYOBNo9JGc3DwFCezECVLam3y71qBC+t6eLCyAC5m5kbUw6xxaWg7HluV2zP12xOF4RxViAby+E5ZDygROjelY99cIIXxpWr3l5PSIy/dXjMenjOoJ63YZcfJgUAWJDuZ2sP6DD+J+Kr5PWvX+lSVyyp+L8jMx/P5u17A1khEWQe817V6CwhfFsz3SKSod90C+NvrRB3u3ZCqioOwA3KSTtF1Hj7fIXbuKX9yO+KHaMT32grPRFVUQMkoqcL70b2wKFPlZAtYFCEWItE4yWP8iI4gxAzHIL9WqlzL7+D+AviK9GGuRwdImnFdUal2levmxpoAv1lQK/OG9Ij9yYT/70sAFcBIhrbrr2d1KDuY+GyZG5Xvw68ez61varqVzXtCX1k0byi6n2KkQYLevKljrcCZ0zxOCWlaMmoZR1VDLilpXNFVFrWrveknKnhgEejeN5vjEV+377LMm8SIb5n5gkUrUOgQy0YJgH+6GB8fvqun/e8B/5Jz7G0KIGpjsnyCEUMC/A/xfi8/+EC/w/yWgBf4jIcT/xTn3c+fcv1mc978A7orb/dI598e/49jiPdLvWo0QHPHLn1/wxRevOTg44E//2h8xmxu27YVP7wiHtc435dkZXrw84OuvFkynFVr7oAtPXzmgqtT+nPMq02rZ8vVXC6yD45MRu23Pr355x4sXU07PVMrB1VqnZjnp+VHAQ7IGSCHJoVL+cTamY7hgZivQ4IcEf9x0EZVm4ZhOSr/aEH5urE0d/7ymakAKqlB21FnrI3utpe0FGMNh0zNvFLcbHcxbsSqYf6BzIJRDjRzbVZhLBVI5pBIIGZtVlFq/RNospGOrSRECq2LbU/9uRa17kYVwtszEeXTZGkBRQlUIcBGgZHbvwYvX2PyS76mahSDI2vwwW1tKwXxes1516bPxaMxXX33Nrt3x4sXzFDE9P5hzdXXF9c01L1++RAho29a7iNKYPXPCSZAuaPt5nrxClBn8AEAKn8WyXvehUBXpvnke8tj3Bb5LawFawOF4x32h8Wtls3wM43ggYPBpqMbsGE9qxuMJtzcLjp/M2fU7jO3JpdeKaXb7M/7YKmTAOhD4fjHTGc7FcI1Ia8Xe2HveIzfHAe9WmhfzrU/Xs4Zd3+XceCR1YX4emkseCl0HuVd9VDgCwnGAtYp219GLGmF7rLC86Wvad5IftC3n56po+esD+WL6H3iaEUKw3fTc3/vS5CrV3Mj8J44pa7gu7R4BCKUgaPlxzqQYrsi+ldGF5jlayZSmV+uK0NoeKSRbtyv4jYXUsttlwbd3/7KkdhyzDCYs0wtsLxlNCx4BGBHalNuervctfTvT50Y9ZL98Wi4y6cS5stZX3ouuRa0Uo6pmMhkzqmoqVTHStQdiqvJrEuooxDWOPRu8qxPOziZcX29YrloO5k14tkgFitI7kl23kU4+BIY/dPxWoS+EOAD+K8DfDC/e4gX4/vG3gb8H/LXis9/Ha+rrcK//B/BfA/7nxf0F8N8E/rXfccyPjxMvKCp9yOJO8OMfe+3+u9/9lI9fHWPdHdud75EeD+cc63XLu4sVT59N6Y1lve54+2bBi48OsqlWxECVrORZ5zC95eJixeJ+x+nZmNPTCVJJ1uuW5aKlbrxlwFmLUjqn95XL4zwhKpmrWSXzjCNEmObiPFHY/fYj+p4K8xR7VoCEJP0H1rok8B0uZ48FP1ZMkQEH0tH3DtH7ntgfHyy5WR8SYxeiti4kvjqrdAjtUGPrO8hZQd+Da73AFWGjSyVQGlSVy09KIZHCprmTqVCH586pxIUQe4TvkXrk4SUEiKZAGa55LCAzLrogu1zSE+J1YTr2lP+h4Ih/h5+j0YhXn7zin//zf85ms2U0GmGtZdQ0vHjxHCklTVOjqyr4c3fMZvO0ZjaoTElQpLfNDI4o8MMz46uNRt6vv9uFYj0uWzYSg4sCVuQ7u73z/FeWebNlufOC/2C0pdaZaWY6yJOQAqRw7Lo1p6eH3N0tafSUs1mNsT3Xqwtasyvo9OEcfkih2VPKC+tMuVZB4ojyVhHQDSkl3SFc7D9xLNoK5zYhjczS2x4BdEIitUC6UJwl7NlvYslxXodH1pKdk2zaDqTE2D6Y3iU3ouIfXVb8cLfjDz6FZiaTUhFBbTTR++A8yW5ruHiz5PmLWTZ7FzTT9z1t2xHjbqTw6YiJngLNJa272DdxXcuYmhhIrkPRKu3NfJ6HCkOPQQuFlRohLEL0SETSzMultqZwjwqBUMpblWJ3xmCN6BcV46lE6az4xHUyLvjynU1mfetsiLFI6sGDI4KPmO4nhQceWnnANW4aRtWIUeUtLrXSaKHQSqf4itK6uc+pqlpxejrm/bsVB/OG2CwuAouhFXtI4EL87gIffjdN/7vAe+B/I4T4EfCPgX/bObdKzxXiJV6Y/2sMhf4/B/6nQohTYAP8G8B/tnf/fwW4cM79vPjsO0KIPwPugf+Rc+7/uT8oIcS/BfxbAC9enKP1CCmO+PWvrvjNb75kNpvxV/7qX+LgENruvc8HjdpHCGKyxnHxds3BYcNsVvP69R3Pns9Y3O+4u90ymVZUWiaTusB3VbPWsd32fP16Qd0oPv3uEU3jg6OsddzebBmNFaOxn14p1WDzAURLQd4kQBRowawXGznEBR327x6i331tKloowIXIVkimwygMCu3NHzbxu1RDIDyqrqpQRbD3Uala0ncGaQ3GGI6anpHuaG2TmQFeo4qb0jrro72lw+VihsHs57tnWAdmJ2ErkAp0LZAq9+322v4QBDhBdgUUFQujECQI5Ki7DPyFYT1lqGYYJdagjkA8N/zMVcviU/KaRASeoon3BJeSkh/84PscHR0xHo0YjyfMZlO01kynU/q+5w/+4C8xGo349JNPATg+PioJ30csk1uaJo21pIpSMy7oTijBeKzZbPpQh7y4WuQaB1GDyO+Z6aSUT1LCtOlo14ptX1HrNllYoiFlcISLaz0GGrrWR0p//dVbuq7l4GDOeDqjXe/YP9JjH9PIi2N/DuJjs3DN8/XgooHgf3jEKxc7nXLQjbMIJ+itQYRofh+8JRBU+Dr8j2vEUUDvv1+kVz+XmlVrUFrR2j4JJycdslH8ZDVh84stP3rpOHkikTI8z3kXUESkUglefDTjy9/cc3m55uzJJFmDEN6s3/c91jmUzNUl4znetdT7sVqvxEQ+Et8pASg8OLI21B1JJWWD9UFalPBla43QOAlKGDoj6G2fhR45m8ib2SVVpVO2kgeqDiFCW+ReYXeK8WkQrC5YI8I+91UFTRD2JoGBfTKKcRcDS6z1io9WCiUkla5odEVTN4yrhkprGlX5DAqpUrvcWM/AU96Qr4iCFufzhqurDV1nfZGuwLciv5FiuPdwDwO2BUOA8Njxuwh9DfxV4G875/6REOLfA/6HwP+4OOffBf4HzjlTPtA592MhxL8D/N+AJfBPgX7v/v9t4H9f/P0GeOWcuxJC/Anw94UQf+Ccuy8vcs79HeDvAPzlv/z7bruZ8bOf/pK7uwWvXr3k1adnCLFgu1uncpKxQ1ac9XfvljjneHI+oess7c7w/Pmc0Ujxy5/fMJ3VjCea2axmNqtpGo11lvv7He/erjg4bHj6bJZrQFvHdtNxf7/l2fOp3/TheVmeDIV1KbCTeRZB7HTm8PcYCvxSHykWvdx8AeHGuiZe/uec1ngXLxNF6vTnfV4GFfyHUWhKJb0v1ki00Ght6HYh3cYYLpYV61ahE0V5EpdSYEwALuHZsd51YsLOeZQfiylp377UGkm7CffRDlX5GgC+ZoJMJjIpJdLJDApEFv4D10kAQUlrjdp7wXjLtUkyJQnQUrsvzN3ldYntRWYRAKb1tdOFkMxmc/reJO399PQM8KbN+FnX9ZycnAD4WuK9B1e6EkmbS89OAi0abQq6S++azRFN47X97aZnMqmG6nDUeJJGHiagoNE4h/EKKRxN1dMbDYkWefTwQFBS11N+9YvXNE3NZDLh6dNzjDFc39xwcNDksTy4uvhs7+sHwvNR3ifyfD044q4SmUD2zwzz0NtYAyM3oBFSYJwPElNCeg0PgRaxBnuRLleONykCLv8rH+cky51BzSVmaxKYFDHVr5J82Y/ZfbnjR+2Kkyc1upJooZAyRPcHX7JS8PzFlNdfLKlrzeFRk9IHTch5r7XPGY+gJvaT98FtIYUXRyOqtO/88IcAW+LT63Akq0KkW6UUja6T5q6NYmdaXxvAget99lMOSvPXae0FLjYrS0r6VGLhBP2uohkJ6lqilW+Qo5XC4N1iJhTfSS6MROMFDQWBH0sLx/nzMWCh6Y7WVErT6IaRrmiqhkrFgD01LNoWrWjWDbtwxjnD01DTKJQSLJctR0ejYCWKlsiH1Jh4vygUvw8A4fL4XYT+a+C1c+4fhb//Q7zQL48/Bf4PYfHPgH9DCNE75/6+c+7fB/59ACHE/yzcj/C3Bv7rwJ8Uk7ADduH3fyyE+CXwfR5aCNLRdo7/9z/+MXVd8aMf/ZDDY0HfX2Kdb9IQS1BGDUwI383s7ZslL17OkVJwf7+lrhV1rTg6HnF00mAN6MovwvX1Bq19Gs5q1fH8+Zyj41FOfcJr5qtVi9aSyaQO+brxvYZjjkgyyIXUUAdybrxzzqe37CG3SKbZzZ/RKI4k3KIgiCUqo8VCJrNeILrwz5vsLH0IrImEFP3zQvjKb852ID04EK2ht5Yv7iYFo4zr6zXwrs9oNUa6QqxoZbNQFaKooigQlYVKgBWYXmDWwVyqQVfGxwMIH+jk83VD2dGB0AvafWF9iL6x5C6gLH5U4OZC2y0RetLSyHssrtBDMeHzqLt+y89//hP22P1grkDRth1973GxUoqqqpDSFwBZb1aczw48yEkQpLD9RIEvh4/Yf5qUgvG4YrVqGY/1oN66D1yyg2vinCStsLyf8PpYJX1LZusEilxadp/u036wPVVdcXR0xGQyoW1bbm5uaeraF7CClFmSfQ45xmVfmYn76IHA/wYG6B75bbCCrvh773mVzPELzoHBgbO+jz09OyOQJgB1CULoEFTGQBA8Np4khsK7296yNYR0ORN3v6/XEVxnWsE7V/Nn71p+f7fm+KxiPPHWx0ppfCSFACTNSPH0+YR3b5doLZjOfLaSdwHoQZCxj38KroYiol0Kz6eQfrQxbincyF9rDX1n0gLFZGRB6ASntS/iZQ27vkW0PgW6Fz1OKrACgaWzBhvKiWNCNUAlUSKAKh2sLr2g2ykOzhXj0YhGVyilsHiTfms6OtvTBxdJLPOb5j8oBtbkTCshhQcOwZSvg2CvlEZLTVPVjKqaWmqU1IPUvDinJSnKRFKev5jI/wKvPDwacXu74eholHB6PKLwL6bYU4ItitH9FoEPv4PQd869FUJ8KYT4gXPup8C/DvzF3jnfSQMT4n8L/J+dc38//H3unHsnhHiFF/D/xeLSvw78xDlXAoEnwHWwGnwX+B7wq28a42674/z8jO9+9gwh79nu1hSsClm0pY0rcHW5ZjqtuL3dslp19J3h+GScNPIn51O+/OKes8mYw8MRfW9ZLlqurzY4B7udYbftqRuNlFlL3+0MTaNSK9P4uQgCUYTY5sRakiCJgj4Llf0gmWRqSpLGkcvyFv+LzNZlcCFlgTgJmlxBLGXgXzximeGY5iOERQmJ2zkQzqe+hYYUr45XLLY9UjW8W6l0TxG4twiCOAIBwPv2Cyr1pkCZNNPUYSoE+wkszgiM8QBASoIFwJsulXSIWJxCQPSJpdiGQuuXUiJtCPQRuR1lKdRKLd8F0/c+s07WmwLduT1pV2nNJ5+cZ6tCWOd9k6+UFV2nub6+Y7PeEN0zJydHIFusHVFVqghiLDa/CFq+fLj7RTGe+GlVS+RGsN0aJpMqAKMs8MWQODP9foC7COFz1KPwjXOTdOc9Dbc3W56en3Fx8Z6rq2sA5vMZ41nN9eot0VoR52C4KPnXASMsB/TIeY/r9/tcUuz97oZ/h/U2CHoLWkWaChU3hUCE9qqd6VF44C9trIP/8DkZsBfAPdCsVDW7tvcmcLz2GzV9F0p2eyTr5/i9q1jfwKtVy0dnHeO5ZDppUjBfhdfi5wc17c7y/t2G0diXit0vsuPCHrTgW8z2JlU79VYNS9t1PmZBFGvscgCgt4DEWfS6aeQ/UkoUMl0fLSbOOTqhEKbzvUNCFTwhBU1dU1e+DkEVzOgx0HV9axmPBAcHDXUU+AGs7LqWtu9o+46u95X39uO7oCiFjrdI6Up5/3z4V2tNJXWIxtc+YE9VXuCHJjlSDOcxUVlUPIQY0GyycErB0eGIX13dYEJvlpIs0p4In6VgPq/RJYVvX27sH79r9P7fBv53wkfu/wr47wgh/laYrP/lb7n27wWffgf8951zN8V3/y2Gpn3wQYP/EyFEj29J9recc9ff9IDxeMQPfnhO11/Rdi3RFBQFTTzihG+3PetVx3e+e0zb9vzm1/f4wFRLb8BYiaxHnJw63r/bMJ021JXi9HTC8cmY9arj5mbDF7+5o2kURyfj0LNc0LaGyXQ4rZ7A/WrFOuLJfJbc6EMz0yA4Jgmu8A6FZpoQtoi1sMFZBhkKmb/4Z8QmPBAsDNZvtq733a8QxfwVY7WhlWff9xjb4UJbRyfhbNTybGKYjCx/9qbhdqvCe4fAPmJxklyLQEiX80qzmpMtGYCwORLfCefTorQAa0MwoKDvPDNVlUFWMb0yvnjYFkl7DYLLZnpAhjQyKKpb5ckrA53yooap2tMU/GYsYiUCk6xqvYcNslshi1GHUpZRoxFiRKWbkMa35OnTExDrDPoonhPHE+8STxHCB/sVY4+fS0nS9puRygJWhOyDEsQUhJTEoGM4Hwis9Zp+BkaF1B+c6VP46qrm1auP2W5bjOmDVrbFuv5RK0Ec1h65PJTN5XeuuFCUc12OBmIZ3jTm+AZ72lY8Np3i3WrEi4Nc18A4B9akeyml6ESHNBIjTBL8EaHlQK0hQIvBW845tKxYb1p6UWGJpv1sIbQ4vxdE3F+OeyT/bN3w6y8N3520vDxzTOaKUaORVSgpLgSHxw13d1tWy47DoyYBqMF0CpF71VuTgwOdoO29wK+rKvn/Y4yDJTfTicDYA6PMl6JbQQKV0/TSQD3yrjm7xQqvaaOh0t6039S1L0QkNXUVAua0xnSOu/WW47PadwGUwmv4xtCZjm0Q+lHgW5etqTFIrzTnx3TumFuvhKSSikpo796U2ufhy5CRVZBSVDhduffckL9Ht0LkrZHXjsc+zfD+fsfx8TjQugu8QyQXbCTiZN2DXNjtm2X+7yb0nXP/BG/CL49Hhb1z7m/u/f2vfMN9/+Yjn/09fBbA73wo7di1l1hng4l3+NaDoBnnuLpcM5vX1I3i5nbNbK6pK8VqZZgfS4zwzGt2PGGx2HJ1ueb86cSbkJVkNquZTCu61nB7u+XirY9pnM8bthvD2dk4mY/Tft5nfnHjBrNXzBP1R9LHkwbhP41BN5mhuZjCZfF17aXwiDxWnbMWVSl2W6+ZjyYypQVGFN0bk1B82crX/xM46cBA27cst2s22y3bjReUPuKWZJJftnC98ULYBcHg+Vr2v0cidjhEjLx1WTNwJmx2F0JTEkOLAsV5xqoFQuFLDFtJ10loPZhQGmQVOZhL2oUHxSJZjGPAnbRFlkBhKRAJWuMDBkUpBMIfLtJYNq0HGUOKDEiEkMThAzDhrGOx2CCk5eR0xGrRMRo3bDc77u/XHJ809Gab6CfdTWRgkh8jBueUTDweVeU1ia611E3JuB7jGoXAxxWnFEGkeMCc0j6KKwekH35KUfHll6/pjWHUjJjNplTjHBfgh5uFb9wPj43QPTbkcKIofu5jg8fxQv40WcLiJwWYvN3WvDjYhXfK8+87BxovFAl0ZSVSGrDg+1bJot/9nkZYPFBJRbvb0Qsd3JXDcUYLjcCBDXs1XH+H4M8WI77YWL4zaXn+xHB8IhiLOsWFzA9qbm92HBw0RQ2Q4glhX2slsahgnvP7NJYl10ol/7/Da9axe6JQPlalbfsUpBxb7sbqfvGolPYZQrUfhugkvenQUvmWweD3qRShCJGmkhW1qrhb7NBaMj9oMKHCXvThd6b3efl9R9v3aXwxUM9am3qLyNBXILXGdiGuqvhPSZkar1kCWBAOFawXTkikyNFWPgRhmL5amv33HT1Pzie8fbtgOqvRWhT7K2ccRcwdaqwl8KLkhzZCPr4VFfmSmcvCIEn6kaNtDXe3W77z3WMANuue6ayiqSsWb1a0bTDPCq8Fnz494OKrWybTmoMDX4/fb26HrgSnZ2NOTsds1oarqzXbbcdXr5eMJ5qm0dS1QleSqlJJ6GSN2dCbgKKNC6lxQ03Gb/RgsnFB23UinduMJTrUeFYSkL4FsMOnvwkEfed4+9UWpeD8ZZO0WU9Akt5YHBYVaxOEgCTwVgNnPXpfbTas1xu6ztFvatR4HZpSAHhB/fquSUzI+bJbXv5YQIkABnKxkFLzj21GnXO+VzYlEs7KpSMGqIVZkiCkQWqDs8G3t1VIA7L2eb/JDI9vg5oAVvhdSJH9/IWlQ0qZg+MAoRVR5KRNK0gbfPBF/M4NmWnCf8XGd85nhLRtz3GIFamOa5Qec3dbsVquOTycpHML4h8SeFJYC2tDPK+wHuF8UORopNlue+qmTpaH8hVi/XgRQdLgTTLDigprb3PqadROPsiGQjWxs7NTT2OmZyTGKKEw9OzPWolnHtzqsftHheiB8rOPwOO5JZgpnr4v+MNftxvPD6JZ3JFr3GMNxko62yONyIWnlECEfgbxPqUZOPrQgQCqNdvNml4oYh65vyYrBcT9hSNW1XQ2AE8luEZyvRzzZGP47GrDR08tJyeSUVNxejrli1/fsVp2zA+zb5+0hp5WpJQoJxPfEUIk87pU2TUWA+XiXpahOM5m0zGZVKigQUfAgnO+rDgi1RhwDlzl24P3pqczffJ9a+kr3Y1qXwRHK4W1sLzzJXeds77KHj6Nsu/99f6f8SV2g7Uktg8u26VnwSx8kUAV1j0sUQzQ82maHuB5wS5SNcZKar9vhEBI6YsTCV8YKwvmEugVhAocHY25ud7y/t2KZ89ne9bBuKfLLKIYrxSUov8fmff///6I5pLHikVkX67v+OQFttdsqkrRtZbDQ4VUcH255PjJQULtzahmfjTm4mJFVfsKa9GnKsJCCuDgUHFw2LDdzmh3xlet2xlu7zr6zgt1nAv+GzyokB4FIj1B98YyqDnh4sYHk/iPj+w3FhY3xmtoMS0ubEiEQ9eCqoa68TmiFoPWgm23S93yRLifDQTUhs0Ve3SXHcbarmOz29JuFf1aIsY7aAwmaOcRxV9vVLRRJGIWylsZfP/4TOQiWCai9UJEgCDlsCqXKJitcwPGA177TpqecDgNQlvsVmONRDQ9qUWyKDpSBdeBBz59EmBe2AfEbz2DksIzJV8+lWxxgMFY4t9prCQZPBBWUcA6PKharToW9zsODkc+BiVscGtb5rMJi/sl63XLdFZhTFveKAlWF54pGArbQZxC8tn7b+tasVn3WOvpcVCeNymiWepl5pIXp4wFkeID9Q725safYZjOZtzfLRiPRzRNg1Lam8CNyBNXXOOK55aNjR6q/ml6Ho4n3iRoY6V6nQX7B0wKxQNaI1nsKg7HfTrdEuiRmMIX3Ywy/J7XRhL6viemH9bckerDCxRt29K5CpGqehLGXYJZkiUz0pVM0+dL5t6Iiv9sUfN6a/jO5T3PT8ecnU84PGq4vtownVVZYw/znmvQe24RAY4SPpI9net8OlzX9Rhsuj72IOj7wFeK2v/WxRQ6hy6Ag/fXV9TS0RuNDoWPwLsEal0xqX3jMCEEN9cbrIXxTHpB70wovNPRhZr6sXueDcDJWEvXdnRt762boZmYlCLF94hIZhHYCkfvDLa3uchaBAN47V9LhVGWWnmAE8GT38sxNuYRzTTwxQg+Xr484Je/uubgwKeTx/X19BnlmYsDDPwkWpvcw/sXx7dC6McXHdbK3zNT4U2v00nNbNYEFDVnNFbc3+0QAs6fTnj95YL50YjRpMZZv6KHx1M2yx2X7zc8OR8h9F68QDLju6Td43wqVOqsB8H0ZVNzB4NHxLu2Y7cxuG0PRTZA9ONnd0WIlJUhcK12yMoymgdfWuewPfSdpevwJnjjTYJV46ASLBbB3xSEoPQmDQiC3eE3nRQCgunI9g7TO3ZbhelAHWzpZZvLaEaBJkAHThN9j/4hDts5ROUyoRaCP6Jn6SRK2hB8k31u0Q0CzlseIogT0dcfb5fnCQFi1OF2GrfTUPcgXRbEWTIHJmAoObx0WdsHb2aN5kslfW/s2BsgAijI4DNt4kJAuuJ/8e373qeAWutdK3UTmYkIlb8MVeUYjcYsFmumsyNcqI213/EsWkI+LKhI1oUYBKRCkKTpLboJgC3MuRB5niKgiPcYPDesaazfnzwLgdlR3qMYXt9vOT05YbVa0XU9y+UKqQSVqmm7bV7/weQ9UNsfHsUwc3fF/OyHLHFP8x+cJB47Ix2X64aDUZ/xScAQHggF83KgcWlkLiutQg2PEIAV5zdqyn3oBmeNYrHegRrT21Xx5ALIuQwiS9ASXUvOBWsW3iJ4LRruN2PevjO8vL3jcCTZbDoO7xsODmuMzfPuNWeT/c7RPC1lcKeKFHzXhzgib7aPayCpG4XpQy8Ta8O+JbghTQrYjYHFSgiskqFWAIzqLPSccyENz2cZ9L3h9mbL4VGFVND1LkXqt323l5efCx71nQ9MlEpS1ZUH+UVFUM93CQV9PHjrhAfoYk9Tj4K9UppKVYlua+X7ZSgpCQVPUYNGQRm0pp4IwtePqWvJ6cmYt2+XfPqdI5+37zwgTLFbxSiEKOJ3fsvxrRD6kR+IYsOVUZJJQIfJmkwrlssW5xyTSc311RZjLOOJ5vikYXm7YjzR2Jj7LQWnT+e8++qW2cxweKgTU0toO2irHvRmgeaj533byN5Zut6XsO36ns2mZ3nfsdsEc5gyPq3HgsBru9GcPzTPhhx+A7tbyXbnQMRe02HbRyGovCmwt477mzA2ESFIEErWWw9im8xCByW6FJQGoXvUpKO3LZ0xIeXQJVDSGcf9ViV2lAS/cFgDxBKbxYaJgjVWJLROEMt4mZDkI6JLA78Rw1SX/wv3Cs8tpItoelynsFuNaAxCRX9ztIpkv2LZctUhklk/ZkA45Q2s2jmU8FHHKhQxcsFyAI7ewGbd0XUGpSSjkUZXMtUB9+6daM43jEY+nWuz6X3lMgqNWoJzHfP5hPfvr9ltDVWtsaFISkkXSU/dk1DpT7enhVvPiH1vAJ91Ei8oBVwUSI49i0YU+ELSGo2SFiWLFMy0MKWWU9pHHG3bstlsUgT2Zr1lNJ2wbdeYvk0AJGmOMqxNoM2k7T/C7yJ4StaLpE1lyDkc6CO3KZhLHndg+sLxbjXiu8drkOVtspvOWovBB5PFipYx9xqlfUBpuMIGod8bQ296kArTKa6XO5pJzc32yp9ZMndRjNFBLOWVQZoI7MODECkF1gioNVe24mY35sj0HBuL+dUtLz6aMjv0QafRdA0+LRZAUoKo0hUGTVWD8C6KPgYLC8FoVLHd9KG4l39/Ywxd36W6Gj7OSGCiAA359Z5kSrM76RrnHMtFh7WO+UGNoQ9m9yDoo8B3Pq041rroO+/vV0pR1RW6Uuk9k8IoIs0J3/oYg+sdRuSGRTlWzE91J3sq2WFri6ui4lPhlEpW4VLQZ70jIuxSkgvOzqYsFjdcX2948mQyVDTTbVy65+8m8r8lQj8e2WxdmDySc6sQDpKUu6+17w7XdQYpfQ3ktjVojBcwwZQ/m9R0JxOurzbM5w1ahwYHLvv4k3AoWEofUmy63vuXdp1htWhZL7w/X9Q9curQlcUFgvL3lMh9jXn/cODuKpxy6FnnxxMD+FzU6EnR+V55z+ek24SWlTIIX5xDKpmEp1QCEbIbut6XsLRhbDHSFQRXm4pd52vqC+ECDnH4VCPf4Q1pU7RrGqfMJjRvYXBgZbzSAxkRxYXIaU/ioeYWQV5aawGiNljhcDuFqAFtEzgUkJpUJCEfNdwIHK3zAVI21L6XIYhJSBDauwCcpess201P31uqWjGd1hjj+4mbpU1BNjEYR1eKw8MGXUk2656IS/PY/dtZ1zOeNGitWS43nJ6NcUV2xlC7y1pf/C4LbJkZTGRseC1fhX2QTM1RWy+4yWOarhACYwVtL2m0QQiX3ScMF8c/OgtNazuakeR8/MQXZel6X8DICk5nz7m4fe1jL1x+Vhy0f5988z2cQ8oUGXwWQgyjpWgwg8VRTt5g77kHv+56xeW65nzWEV1aEad7MOnH7037HRBcRia8i/IzbkIgb/Y/d0zHp9zfrlkywkkPBCKYeMATojVxDxCkN3OELB8VCsQE95WS3Nmaa6epdi13X6z45IlifqK8YJQSLRUu1AmQWvkIdwcIhwkuMqWKUrOQcv0FgukULt9vSJTqPM/RIaCPcH4MMJZ1cCHEin/ETNThOt3ft7x/t+L0yZiqVjljyUWelnmyDXEGsd13pTVVpdE6pxcPprNYaAf0zoTuoKagQze4ou97dhEUicArlKWhplIaayVW+qTFZDGJKlbaM1mR0lpyfj7lzdcL5rOaSej+Sjw//J5iEr7BrVYe3yqhH4ku1pm3IUIzalhxYkeN5vLdGtP7oBmtBduN17i0Do0hgpCMayslHB+P2Kx2XF1uePpsRslqfdUqm0zAJkTamtDFab3pWN/3rFcGi0GNDVVjvcYmSL5xR26QQXiC3Stg4/ACCOewlcWua2gsqGBqD0xRIgam8hiLYEVW5WLLSF8e3OfDOmNRXiXxQjHMaW98kExZmlKEQhkOx9Foy3dPlvz6bo61WainKOXQZSMFeg2Qa+5Y6E/3jX9w0QsXN5gbSkb2WMEH+DfB7Gxb5U3y2lsRbHG7uJq5/EGOQZAWrAh9A6LZOeTj2l7QtZ65jBrNbF77YKVw37HVWOPoOh+wVNUy1E3I2rnWkrV1tK2ljhp3gWiE6JnNJtzd3WPNLGdBDDS7eI0bzm38vZjreOp2a+h7y2xeZ4YT0UAy5z+c2DIjxgQfeVOVUfvZRZBvIQa/CyHpOsPbNxe+iFPXs9lsODk55uhkHsyiMsS1iOw2eGSBB8LdQ+YHZauTW4jMNB+HDWki8xq4fboL5wjHL2+mHI1vqCRJu4256t4FFApZIZDCB/bFF7H4dTSht3tnet9RzxqOpmPe39yzUVNas0nrU8ZllEGTH9L0SrN87O2uVOz0GcSacGyl4i+2U95/ueaH6x0HJ5LRuMIBSoCQCuEESmrPF5K/P/NeACElMdzVAXXt6PuY5eOtpyqWB2ZIS37fZG07NphxaXn8i97c+EC3sydjDg4anHBJkZPBCgdB+IciaDH9TkidspTicwfz9YjwdM5h8Gso9ua63DPCwrZvPU9XBqMtsVmYSvFLAXQV94ixYV7WZLA6nzfcz3a8e7fi1asqWwsC7/DW2Qwg4JE9snd8a4R+2Tyi9EfFz8p93Iy8eX6z7ahrSVVJ2s6mVBJjYkSu37bGQ2ukspydj/n69YLJVDOd+twS52JDB185rQ8b2IQGPqtFz2bdIyuLnBl05QNKok8cyNdb+4C/OIIvm6K4SyBkqR2oCrNT2KZLTEAIgYtzErpPIRymeAYioPe4yfCm/JhjSyTNgJBTqd7iGTKao63X2D893jKu4CeXB4Xm6BDK59ULnW5NDKSKy1PW045RSC5GKaemGuHyAhTta/vEUwuB43Be0AvnffxWQJVzqkue75WYKPBt+szXWIfksAR26w6QjEcV40kVLEDl2nktRWo5TL/ZMw1WlWQ6rVgsdhzIhkpnrVzg89qn0xF3d4LVasfhUU3fb0lm5yiD4rrFdykEnadoUfzfZ7PUjXcv+ODJYvQiM5J0QSF445nG+sJIjS66VwZBGTsgFlVpBofpvRn49PSMtm25u5Ocnh2x2Fx5a4hSqTa6B8OP3qYccmCwMsemBDr0bVy9oIoxDQ8P9+iv8YPEWAutddtpPr+e8b3TxR4zFwG0e8uXN/P7M5wjlbVG+Op1renoOt/5TakK5cZc31+zlk/YdTdp75WrVNLTfrGnaA4WBRBUoZSsLMo2Jm3Y+Qp7b/qa+7fwl9sd588FoxEhWFiAUCFtVfgsJ7JWH8cTA+H8PLnkkvMCLVgDghZfXheFnSO6QAphJnJxsrubLe/erXj6bMZsXqW5kIhQ/tgH1ale0gcAqCWBl4i0Tz4UcLpvRUm8JE18pp1kDSt4R9/37AJPlULQWY12EoXKILWImHVh7OV6Rku/VILz8ymff37L3d2Wo6NRelZM5U7KSlAI/4WI3o8b3fut/GcxlUaKjIziaivlta3NumM0GjGZVCyXXdI+UyEdPHBwIX3NOsdopDg4qrl4s+Tlq1nSclPQju3pOsNm1bO869m1BtUYqiMD0jOcPgj72P1JhnubFP2S3yOZkrAFQYgEcqQUuHGHXdZQBdeA8Ob52BwoBp9YHDakCMqIdAVRGvj56wMIcYDzKDUVtglIPEbWJ9oKO8I57844n22wwE8u54nhoi2uVQhCKmBExyKAmggOhEQE7cdGc6EbsugkdIqNFj+PaS2l8Cq3sFAOMep9gF8rEHWfxjBAECJrGN4s7BDW+AA+AdI5rHBIDeORZlR7wflbZNJg/MUEIoRjPK4wxrG4a31NdFW8g7PoyjGZjFguVxwenhGqVYcbRm0oefbTgwYAcg8AJ6FQnBdlhNif4H10Fb43RlJri5KlKyqUSy1uuq+BOOetGqNRw8XFBQDHJ8c40WNci9YKGRrZxGqNEeHkp7g4gx5kILI2GzS+mCeN9YzfRWpy5buJD6jKEUm5R7XpSB/rLltnCtmQwIWNznsbeYmltzLtAWN91bjYs/5wes723vB2I1FTyW6ZAxsHoyuExACZxZmxnscI8IVkwtw8UCqwwQRucFgWUvNPb+Ev2y1PnsJ0KpDOr3GMSfA818+7C2MpwUjc4xl8RCUkV32UATzIMtL9kfeL97q53vD+3ZpnL2bM5nXxfYj/QaRWtnXlA+n6MnL/t6nBxbruH758N4mW874ZAmUTsjZiRlRtDEZajPD1G6roUiCR8wBrpxuFeW0azdmTCe/eLZlOK6paJX4tUgxWVJgE/0II/XikQg+CVMJwoK24vJiTacVmYzgKxR52O5+2pLXAOek1EMImc6FudGCQh0cNi0XL1eWaw9Ma42IUfs9q0bO69wUg9MTQzCxOmGBiDxqHjY0kkqjLAouhjyceIprm4zlFZT9XGV8Du1XIJnefM71NFbCEixWzfARp7BkgBOG8fL+IBbzp2wMmJcO4YgVBaxFSFVzQE6kNuV9O5LLC4DKwKGopRI0LF0GPRSX/vkh+KhetFo7kq/M2+kJikZ/lQqvecuMOWIl00HTQhsj+xgv+lGUhSg0k3D3cywkvPKzw1QZV5U2lUX4MNnLC4FHnK7JKxGMAwTGZaIzxJZ9jlbT4nbUts9mE5XIduuSpomCLSNpLnpFSE8lSN71TeGdrsxCN13VG0lvP1B25xK4SjroyyGDjbHvJrlfMRzGNUCStqExpIs1NKZQExu44f/qEzXpL3/dhzTW1rumNN3On0YXKc/vrGrVfSWG+LrqcRVBkY2dGl83v+Y33B+r2fo8rW4w//Jrmh6yx5Tv7+/i+M76IlrOOXppcF0IKrLG0fYcFtNIcjJ7w5W8uuVGHbPuVzy4pAVtB91kxKKBQ3LuB58SmNGld9hCccxEYxfs51qLiz1eSH77Z8uQMDg8ESpqkhfv4G6+1Z8tbBkdphMHVF7X89ExrUwlsj1ke2REFH4wC/6OP50ymVRK+1voIexe6hAoBSml05K892R1K3tvs/T44ClAcj6HP3IGLFjURlMNAj4IUR+WcS6DDWItW2vNwOyyy4/dqEWsVJjB6Ro+ORtzf7bi8XPP8+bxwExTzFnnUbwE23wqh7/BVn6IvPJqJyoCm6COKwVqzac3Pv7pmtewAx2RahepGfrHavg8+RZsmOGqyVhiOzirefLlBjnyqyvKuZ7vuQVnkuKeqvXbSBlQbtdlYcjY1xRFiQIhx00Rh6PY2ZrkJoq/f4RBNh1vXiJEZNFzZR6EibLIUxGZsKt8oQyqKCPUDhM33yEFgZEQeiTWUAc7jdHxxOxpU2/JV9QArQZg0n45gwncOa72/TKiECvLl4Xy/0W0aysOM1yxovgnxCgk0Pa5VuG2FHBW5/PHaYv5FoJ0IlGJTjUpX2ayaBEnJUAOMi4CikCVxrsotKqUILTbXGOMCCI10aWhGDXVdcX+/5Ol4jrWhz0TU+NJ9SXSXDKVCJKxUPs8Ym+ZX4Oit5HZd+yuT4PBm/N5KtLRUIQui7RWNNlQ6+/M9Fgt7MI6neNecJeHQasSXX/jWG00zYjRqkEIlv6yUDhmq1znxMBW3tCz4CGnfiCWujyQGZroBPQ2U4v3DlSftr2fxncjBVIu2wjo5qFOQVtZFcO9pV+KBYwS1wnr+1RnfTOdoeoZZaV7f97hRzWpzlSe22P/7Fq08J8Uog4BWoWGMTAI6A4Ko2Pj0XRWaanm6WaP4Z2vNp19v+G7fcXamqXS+twwBfJGfRD4ReYIQgt5Y36xM5LygUqJG2ihnWe7xk8v3ay4v13z8ySHTqdfgvbvRhCY63qXadh27vvNNdZL71GUF5BHBaF2xwi6byf2ffs5LwOKKTex/tR7YSBGyb+KOy+dba3EqWDSLalHCv2wGDHFaRAQQftxaSZ4+m/HrX99wcDhi1AQQt7f87oNEnY9vhdDH+ejXrJVFIR0ZthhsRCFEyqd/+mzKwWGIxhc+lWS38/mdoq7ojQkE6AV2jK41dKjK8vpXa6R2VBNHfdJjRUfX+4ITvc3Isxxr6viWhHcWFaSFdun88vDR/Q7nfJ1olD9H1D1iUyM6jRj5lBTfaEhhTajkVOSXZlbpNf8k5FwOqCuFSblJYs+AuIniu5QVojZdTt1Lr68Nrpfev+/A+/QLYRAbXcQoeaJ1JD4/A6XI2RxZuD/MyH6cXee5BNEYXOt8Sl/dI3S0JOydHG7i/cW+CEelK186NNv50qOjBhovzAI/b/iB/HJkZhw2rkhMMm5kB/TM5lMu31/T94ehlnuZRuRvVsZd7AO/8lepBP061BwP9LHaaRxwOtuhZYCrjhClL2iNou0Vzglmo45p0yPjayXtY2/qBosQg/JcEgx13aC1ous6rHFB4Euk9b9bYfmmIwZxqST4vcBHkOJh4u+D4fx2HlmcLdLyldvT/y3onUALl4CWP8ElYRIhmCMLyTgXPrLcopTmbPaCt7+45EYe0rH1haOS+WRvaCKOwe1/7EVPqCgZ68grpZJwSfFPzgtrrUSIS7I4GeJorKCzir9YT3i72PFX11tevdJMJgqpCoshRd2IPZrbbX2QdKzSF9crnlLyjaispZl38O5ixe3Nhk8+PaQZeZFlg+bc2Z7W9LR9S9v7rIfOxDooJsUqpGqGghToXR7RBZIAiChiFR5VHjKcdda7jH22iPCgFYEOQYXChoDEYKWMcVCU7xriDQaiIq2PN+OPx5qjozFfvb7nu989fnRYv4uD8dsh9MlCJ6bsZTNTZoBp/RzoSvq8ZOFRlDdzWna7lq4LEfUh37MXoT69McGEb1nddTgs4xOHHBmcCAF8vRe4CHwTDIYEXFob4hF/izX4XdS8VbF5wiY1odhOTrsTKfJeTjrsuoF6FSrHBaaHG0S0puppCQQM5+ZRK0HxDjKa+hPjCHFaIm+YJ5Mdb5bj/N44b1bvhvMRQrQQiFAP2yIDkokbNhYAcsW4RDD3pxsl7efhfH/oSICgMl4ItRrnDKieWLUtzYl1oW2vT2FSSqFDAZFIb6XQc+liP5A0B4V2k/4OcxalZe5kliYvfC9wrmc6GXGjFKvVloPDvQp9aV0YFA167HBAUyu2WrJYthweNOx6yXqnOJx0SeBHWaOlLwY1ro3XgBjG52XQkuc2vnaqPR6FnQiFabCcnp6yWq38nGrttUezbygfjnsAQoMlKgEFkXuZR+AVC7NEfjDwjwcA+vjDis/FHjnt0deuF4w0QdAXKlsEqC5/F4G+LFKMpZIczU5wm5q39y1bfcRq+y4J9rSuEXVEU9veRJXr4IPuZLB+FnuG7D93jtCky/niNp1vL+tpOrSzVoKFnvBn97D65Ypnx5qnz2ZMJlWmzbAuMY+e8Pdq5StJpiBk5wOKyxa0wwBFP0hjHBdvV6xWHZ9854jRKIsr6xyd7diZjl3bsu13tH3nixqFuvvDbKq441yayzDsPAcF2JbhwwEIKSwtQoQsMSdQwpfgjcWFpPDlgiuhqYSmrurUpU+FNuV5+dwAEKdo/DQev35+LQVPz6f8/H7L7d2GJ2fTOGL/bnvy5kPHt0PoB4EffasRQUcU5oWGzd8E4htPNJtVhzmskc7XSDbOa8/GWZwNqNEaNuuO5V3PZmNAGaq5RdY++rsLvkZjvHZqA8G4EHsEQcAlyZUXJuZY+oItJi2akCTtOwruLOOiGyOjZSEE1D1uqaFVoCxC5WCavelCioBiA3F5PpG5WqmtuIJpxY0SN3g0XaUKdmFuPz5c8mYxKt5VIGQMLhIIlSk9bccQdKgSn3TFpogbQOwxv3yX3y2MLs6hg8SEABVqnncaZ0BUfRbQgZHFyODU1lPpxLBjOnkaQcGT4/uJMInpPFGOOP/e7kzKAihFkScri9KO8XjEcrnm8OgE2Pm7x/WICmFa2wIIDX7xf81mFbc3W7Zbw9rUVNoxqkyqI5/pLv6WXRZpbHsAMTHWgl96EhNJeOpqirM+xXE8GbNcLLm5uQEcupE484iAjvMQZ0zkYjfJJSBE8q17vDa8T9pJhcVoeOfh7/k9XAI7yYoTi0YJeLcac9gsswUjzHGamlAAwlpPwNE8G4GykJKz2Udc/vqG98wwsqUz7QDcxn2ZaajYYQXIiXvVA3LPX3prEc5iel8sq+9jVk4GljIEOSspUTqnmTlCnJRS/NTU7FYtm89vOToa8eR8SlVll+r+0e4Mxycjf5/YPCwEE6apGUy03+MXF0s2656PXx0kDT/ynZji2PYdu771ZXdD4bPUQY+o5celygBWiBis7H9XQhQcpKTrPLeRLgT47J8Ehn1sk5IKhXcv1VVFo2uaqqLRFZXW1EqnjJIyziweJSW6vbmMLgetJa8+PuLzX98wmdRMJ1U438sbJxyPLMHg+HYIfcjFZIoXjgvvN0BsipF0LMYTxeXllu2uRmsZ8mQ7XyrXeKa3Wvas730tfdlY6iODk1HY+0p7kanEfPKhW4H0vMQdwjiEGy68krk9pQhdnlxMowpMR4T82ow+/fWJcYx779s/6DKjLOckMbLcSjKa6BIdpjr1LgmzpK0WGvaAIacxeMHf6AJ+Fc8X0oGRIM0AYIRHeCtJ2FB5HKQUxczYhi8m4n3KnVOcsy9AB2dE5K0tyB52CroK6hw85edcopQuqoVljUaIQqiLbL4eikmXxjJkjoVQdrDd9slvmYJ90vcOazvm8ylv3ryj64oLyVkf/qMAdMPLRw2xkPcgvGlyOqtZLltsPWba9GG08clRA4pvAgOOnZ/4wUkWQyIMd9S8efMOEKzXK6SUnJycMJlMaPs2mZpjpsu+dp9nTqSGJlHwJ9eIywWzIi/IwKfcH0NgJCLfEOy9Z5LAA1ADjjf3Iz6erxhVZaRJFmtCkOpXCCUGtOyAaT1HdiPe3V2ykOes2+v8VJfjgcp99vA5cbZz5Lwz0O4cOEsrfa15rSVVrZCSkLMfdlBAC4OAUJdT7aQQOKX4oh3zlWs43mz53uaez75ziNKF1h7eq+99tlBdx+yGXL8/Wh7zEuR3Wq1aVsuWjz4+HGj4/v5ei++MF/qt6elCY52yZW4ZkBsnueTNkgyQ0/vGvZLKcD9Ydj92KcBlJQCDbzEsJFppRnWNUr797qjy7X4lMs1jBGWBkvw6BUuBB7Mu/Sx5CAKm04qz0wmvv7zju5+dhAJzoQOfXzy+6fjWCH3C5i79oBGMCxH8TS4LO2MNQnotddd19OBbMLYt7c6wWVu2K18Du5oYmrmvmBcbYVjjMGSBmRiKKyokFVq+swVKL5lNgTSJCN5FoZFxgkhV6UTKew13D8IumJgbL/Rdq6AxaaMO2mY670NMRYwS0vfBUPHBPgo1oGKbEaQPJLbJxZDwcRKAPtSgUpbO7oXaaYvrJFT55eLIrIumtwwC4v3i2jlXMLtCqCaxn67JgrcM6CzvG88bMAZpESOHazW0GlEZH6UftPum8qg91jfIa5iBk6BgfHvMJL5Q0mwoXAMIus5rX1U97OZXakLO+YA+rTWL+xXHJw3GtDggluyJgjX62iMDHMxpfH/hmzPZRYcI61YemflFGs3jTRahBAiGa7e3PGSIJzBmzfnTE7Ybn57nnGO73aH1mmZcEdtNJ039kfuKoNWroihLaX7drbwVTtb5+Q8HVozNFX+mMyIBMny3NIf+D+sEP7+e8wfndylVOBkTIm0IEj1mOOXPeXLwkus3d1y5CU73tNtt4ClDcJ2avQyOzH9E0mgFdqfA+i6fo7Gm0pKq0tn158q4HT+iYRyPCPwzC8D40wjJezdh+W7N0aEvFRtXOM5Z2/rsIa39VTmN+uE6xmda63j/bsXhUcN4rIfjCd/31oYOfJ3vqheC+WKPgX0FYD8AdH+N4xgi35Bkd2jk2T5jSSYeLIVv/qOEQlaSRldopaiDkI8AQKdqhcVDB4gxKgSuKLqVRjUA/CKs2/n5lOVqx8XbJS9eHAzG/0HtJhzfGqHvIBFxZJCRoeVazTbVt+76Hqkdx08qDD1ta9lsOpZ3Hdu1Be2r5tW1L1jRh8C5VHmPiL5JrWrLTSQLM1XUWGJzDRypwYQNWn3qNheYTzQ9DYBC0DoiqIkBOYTnWed8FNxoh2gbRLPxk5NoSxBNhHEMuMx0kgC0IlkOIiOJ1zvna2uXpXylykwoWzYcjTJ0Rg5pUPr7+2T3cG7BjMvI2ayt+XcQoW1oBnak1KuM4P0LlzyxZGzFNAyOgRlPEAL8FK7VVGPfjbEKGzgG7CTCi6As6oiDScsLICjSSguAIIrx7nY9da2CrzybkzMzjoy5YzRqWCxWHBxMkco3L4kwgsBk9oVDer+90Xk3mEABUiTvZtB0ywkr0AQlGH2gDA1fsnh+XCtjW6ToGY0V4+kYJccs7jfUdYVxK6LVLFnsEuXHcfv/UqR+MO1HxrfbegBVTwQmbh8hEDYK9wwe44+HStLwgwGtkuktnna1GfH5reGz41W+52BOin1SkMionjDmkN9cf8GNfMq6vUmFu8q5S4qcCxzgAaLEl7+2EtsplBbUE8GoVlSVDk1sZALMpQVGphd6OMZyFiJQiacv5Yifvl4ynVQ+lS6egOD2dpvS68rjQyVjnXPc3m4xxnF8PE6fpaDnwEuNi410bEiHtmmwQ6E5PAZ8oPgs/vMAUqWA0FiBMDDytAcFUFfapwaGlsCNrnxpX6WT5cn78OP+Fw/HIcgxXlFeOwbzFfl1AjIChITnz+Z88cUd06kv2pN44yMApzy+NUI/RZ8HLcRF4RgEqcWGghiWXb/zkZ+mx2JZ3fesFoZ21+OUQR34YC4nHJ1zYBhoHKlBC9lv59KKDaNR4xjSZ7hUWCdXVHIJDJQLvM+ERLhXZHbpvclbXkiBmhjMTQO7KuSgR6ZWmEhF1jqiVrRvgSiZiXPO+1iL+tXx+fuaS5oHWag4cZQCPx4rPUAp3k6I8k32hkIMWMw+1CDe9vlJMWfl+OO9HzKbxzaKFPjSxp3CbBVN2MyD+S5UvgEYccOgvigTLKTqiNI3HBiMxhjHbttzcDhK1qNoTNgPUDSm4/TsgK+/arm6uuP86SGwyoBpOBGDv8tVyeblrL9DDGB6CLzibdKZBfYpf5YgzT1yQsISBIbddwituLu7YzIZM5o94oMvjmziloNiPNHy1O4M3c7QTKS36MUWt3HvFPcVxXul+6dVjXNU0lEh7HkIer68m1BJw0cHawQi13RMed3lxHmA/2T+gpt3S67smF4Ztt3mITBN48lzWH7r/++tda7TKC3QtfcD59KufqQlbwSRq+w9mOm9HRmtTcW3Sgt+sW548tWS737ngKrypvyus9zf7njx0SxdZ0MqXwrgS7f1v3Wt4er9mqfP5uk+8ft4bhL8IeMh1j1Jq1RM3GMxBsWXKRA1xoUoIX1GDp6eYpZOpLF4e4nwxaNiS13llQIl1aAjod8re0wc/1mc/6wwPSawPyzAx+OKp89mXLxdMhppxuPqw+9aHN8eoQ+DZnTZdG1zL+VQInfXdbShkM56aXzDkbFFHXZY0Qdfd/YJRYuJsbmiU4k8y+0XN7/Y+9tvMm96ItyXiDDJiz38mYGC/ywy5yLkJGjr1oT0QIQ3UU+23rffKxi3obFHjG/InarsHpE9KGdcjsflrIHyH+T3jfMupE9fCp+m+z+KQiPTdPGcR05JTDbMSBld/zsdQwb/ITCcMHmwnqiRgF7SrqDWpIj4CP6yL1AkYFEK+oFACJP/mLYNsF536FCuN82ZIzGR8ObpO6U6njw54c2bd9zfNRwcNrh+k95z//5R+CZgTMG8/z/k/VnMdc2SJgY9kbmGvfe79zt90z8PZ6qqU1Vdjd1tmwujlmn7whcgAxLcYDUGDBI0vuCCQUJCshrJFoN9BbKx4AZkIVuykEG2QGISxt2i21Wnq85U5/znn4dveqc9rSEzuMiMzMi19/v9f1U3F/56nfN/795rr5VjZDwRkZERnNfORFRIg5WEDzWISpxTE6iEijz0qchDQ3HsGYcomsPoMENVvKYNJEnwJZpE3gtzNg4+5NJY1Kjq4JSbQj94hk/NL9dyAsQky8kaQBocsXwkqp+Oc3z3o5crgBnvnO3AHvj0ZoGHJx2WrVjafBTePJqqwVn9GD979jFe0BPshtvAK9TwlxawULduS24RAWPwNzF1OLUTghRlgUPlMEp9SoAvFgDR+CnHwpiK8ABiQkyGryr80bMB56c7PH5yAhDh7q6DrSho+rrd4rsEDhEDORPfixc7tLMaq1MdbS8zhrDuYqpc+JRXRBFH8ms5PFlyOOd5KyD4g9SmDpo7LBpbo6nCf1adNCBQCihEJIGghP5M6ieET09BYXJpS0bRTsrzVOAEhzaQAS7O59isB3z11RrvvXeGqjo8uz+9XhvQ98wJcEIKxxDMpJdz9RyO03X9iPX1gM2dA6xHdeLQNsHrfhiDt74QZJDSOSau8YnZQGWFk0uktALwKaRlTBq8MG51XCc8iDyRUg4rp454afNOKD981Of+xSRKszGci1+3oNsFsOxA9Zgy2iUwlwh6scAgMOX+6L8gJG2XmVMO6qTtFyZ2YO8m+/mJgtW4HZ3NIw/q3xhIMfO/jcI1hE2YfQZ+AbUsSBgyeU+urtCDsV07rE4NYLLmkXrIHDIyqopEW9QMNqVVTbUGmhpGj24/YnXaKiZQeuIWHgwUtP35vMLZ2Smurm7Qzh6haVp4n6PjHQhcgsJCPKxFKYIxrCxAMkaEnB1PtYfzmGq+prM757WgJ6Asij2jHzz6/RrDMEQgq9WLiG3htAbFpyKczyeECOsE74DdxqGd2ZgqmEMgHBPGz8QAOmwYYJMFYVJ0QFm48C4PkGjDGuxFHpjOEgH49csVHBO2Q41nmxnu+ga//+QmC9Q+hMV+cPEEty92uHENugro9iEjXeIBGuRRfk6CGCMGXiK40cBWjNpaVNHxNIAWJRDSgoImsgz4aooyIWQBKQkHiNYW4M7P8bMv1lguG8zmNV482+H8cqaif8b9cgW4IITAScZg6D3ubnq8/+F5iqiqlYQE+DEb4eiyed+LQI3soCfvTLX9DKRxzJhSNkEB+spYzOoWja1DCl5bQbRyEydF+HOh2cvAxXWThFzKtKH7pRW4sp8iUGufGRTvyHi+8eYSv/nNFZ4/3+Dx45wI7r7r9QD9KCg6H3O8wyfzfR+9OvfbEbfXMWpePaA+Y1Dl4MHohzFp8Z6UJ2WczLCPz3mCKSltAKCc+SIRIAshIeBGON+dmhsJUcBamIns62vvXBEMmJCYV+zyvaYr0eJH40BnO5ixgV+3QFXBLgew9YnpjKODtUgALhKmXnQ5mAWlo4QJ3ITBiwQax+dqX2Pbx2M2Clw1CN6vpSvhiMrnROua+hAckAQfr+NQw8/MLEQcNrBRg6xkv84YLJaE9e2IzXrEYmkhWyZOMY2oMEjE4YMKtUCQTVLh2e1mQNNaVHUW718lzgTs9hjGLS4vV+i6Di+eX+HNtx7CGBfDLysxQY1bolVhLEpgqw0nZlLOkxJkOBVY3NddJiXIHshmMgSesd2FNUkEzBdzzOdz9H0PQzk+eXZOSsQGxOOT4rxnDQFM2K5HVBVhNrMgyt7ywTErWBIkbBSp/BdqVJPFRvpOouGlPoR+58dKIVL4AzPw8dUy0eqLbYOrXYWztk+lVLbCk9P38cvffIqb+hG6cQMfc30cA/uSfpUQ5RMUwFqgacOxscradCoogdCRRXOvmK0AX81A4j+appvG4jfdAm98scGjhyEi5+lpU4T4lkBnDAqOcRFADRG++XqD84sZ5vNDWBKTfjhhFWKmDG6McUtUYjWp5wjwpd/jfwY5oE5FFq1tMKsbtHWDtmqihp/DOSfH3ThgNBlLtUyOLl4++MxFm3Vf85YwlXVowTn2qaoM3nxjiU8/vcZsXmG5zCl4j12vBegze3R9F8/JMzxiisp+xN1tj/XNiGH0qOYOzYMRbGIsfB+PrUWJGoaStEwq2QlY0tJqZpgl+uR0x5y83AWwDdnMqxTAQKRMZRIS7ULAU8Llgiidb1XwG5732c/AKopjDg52xhBgR9jaw28quKs5MOvB8y4QljXpqI28K74nfGwskCV2aU/qlzIhfnGzmLwDHHL/Y3MZxzYB3+SdbHstv07q0ow31z99EHlAY19t2h8OzjkESvO0XFVY3w3YbjzaRR4zQwaGuQiOoZmjro6AZCWQBg5DyMZ4etrGtpYMQJJ8yHikd2PDnd/i4aMLfPXlU7x8cYuHj5bwfgvtfc2ilSRhKW9H6DG1NlsXSP1TaFyqZ8zCwtMwIuU+lxTOnIWD9BIR9p3Dfjtiddagrg0qWwPM2O52oMiMRehkx0VI7HQ8z4iXNWG7CUG1ZouqEGQIlPIMZA1JCVeJluVebi+lFMjqwTT+EcAUAy6mRj8a/3708gR/4XEXBJIxaPnrFz3uBuC2Jmz7ddKg80kVVWDxlVMuDABJWzWVjWCfvcZFecj+Rrk8XWThs5L6m7cW0nxPAF8G0jY1fno14P3ba3zw4Tmq2ha0Kqsgvxvat14P2O8GvPPuaZ6bJB8H5WmMx/RC1L0xJAcSq8kE5LXlUftWyTgZCpEKjTWooil/3syCdh/P1VdWJyiK1kxkQVnDvZYHMzJopCgvcQYXLCi3PfOWsvALFL9yWtuImDObW6xOW7x4vk3Hfe+7XgvQ98zYdjtI7vi+c7i7HbBdh1CM1YlDI9nUmDE4V+4FAYkpACXT1XvvAAriCU5ZJEsfYJU6UogkEmW5suKfiWncx2N0MtlifShM7MhlJGKnXG9RPihJ2SAHnDigceBNAwwWtNiDzJj7NmFaB2YxZYFQNxNgSjudZ9x2dWrI/Rp9Wcz0Oqgr/4CCKxSf853769DPhoVTJmox0VgMJNU9jvP8xGJzN4C3QDsLAGxMEPwMC7NWNJNMdaRiHymGwGEvv20tdtsBfedwsqxhKzrSLe1AlceA2aGuHS4fXOD5s5do2wbLZQvPHXSNedzUMBbCU3ZsStgHIGaFnwAO5fcnmHSoN2b6SkKLZ+x3IxYndTrDzWBYa1WkM4PBZ6ZNEMHMRguMTfv5Y8dwI3B6VkdrGEeZiuMUexQgkKXKyKgPOp36l9av6hGriSmU4Ulbdd+ZGbf7Gi/WFS5mHQwZvHH6Pj79+TPctQ+wHzYhQFexvKJQlqY7AgwjhCuO1kgjtGvDmCSnRmkDH67D4nviL5R6J/KaKDNCAhQFyCQM6csQng4NtncWl3cdVqd1yD5JlAKClWs6CHTffLXG4ycn4cy5sgwAiEf0QrjdbuixH/oQfc+FJDsSH+VVVx6+2JbY8spYVLBBw49n6puqSbELdFTT3OLU8skdfR3emwrO2k/D4dhvOcU5lFVAyEFwh2NW1qq2wVpy2b5yLF4L0Gcwdv2Abu9wdzOg7x2ocahOPYx1GDmY7wlIoV2nAAocgv1R54pQYRr1wvRiyufFOz/9fg/6CeDL81kI4EMGgDDpkhxInj8GkNkZTy3WZoQ3A3hXg27nQNvDLwYgJQqROkqAONaHAwk01nezb9A7O30VaeCSBH/sd0AAZaJEROUqg1TZXU7vFUXhyHORcWrhRkyPEs1NtEIT9l7CfIABCkfA9psAhHVDUcO/X7iZ7tmJEgwi9IODd4yzixaIAsD1dYf5vMJsHo5YiUZUFEEyR+GnkIFvjv3uBC9f3sBWl1gs5nBuXwyGwqbyfrR2mSI9rqrPHPZhasYQIafQIimJxEUPmJGDtnDWXmQMvc9hWi1MBH6TLGApvj4ZwAO7bRCWjKUE4uxd9i9gTibiFI4XnImgEHjL1hZrsBgETXNRAEMGfBEavPPJgsfE+PR2ifNZh8uzR/C7Cut9jxdtjW33PM0FB+0iySGkhPqUJtgzTDQ9VzEHRAD8rOGLShIOjYjgVvav9EUqtUjxeUj+TIR0Vv0YXfl4AoWbU/w/Px/x4/UNfvy9FRbzGmm4pV8R3K6v9wCA8/N5HnpmeB+EtdGPGGLgtN716IceoxvhvUuJy47h7pRXmSh4BIE+rO2KLKqY1TFo+DXq2uI+fgoZp3vW+ne5jprri4qm5U+3AWT0wtz0vceLZzvc3Q04v1zgqy83r6z/tQD9cfT4+ouYlWzh0V54eBMIZYwmIPE6L52ksiYuyRWmjiMa8PW7QAbaKbgfY5oAkiZvYvxlbYICc/JAlrqsOv8u7wMRvI8IJMf2h/Tz0laGA7cObEeYbg6+q0CLHqgdkmZIWcoX5pW02HuuwKgJeyfmpbSCpSV5jHBs3ci8QL0n2mz5pG5XHD6E7G2HpR4KCMWv6vx/BpJsNg7M1YOTtkgWaOeEfhvmrKlVII+DijIoSG9SXxnY7x2a1gZwB7BcNmgah80maP3LVROAsXAUmOKtCIl7XD5YwTmPZ09f4vLBOVarOZzbhfrjOHCaSz1+BDIhBHKiyyj4aGZXDi8fzKxEjZNlIsAqWpa0d4yRIMNJhSwsBCfcaLlygLU2xLiIeQBE088Bagj7nYOtggCWGxrbTwJqYf6KiG0iHBS0xardMl65P8fnNq4vIEVjlJ6y98GMTAZxnwh7v8CeB7x5/h6+/vVzbGYPsBu2cH7UM5rHViyCsQnsPBD9SCR2RAgAY1KkSEBvSVIC7Lx9qOiIJF7ppJNKaLCWkHjefSuXGft98M9YLCowKvztK4uv/u4W/9j3azy4nEf5laRi9L3H8+c7vP32aXZsjnMivlkjh7gq3TAkLd95ryKg4l7eB+TfOPabEIIE1aZCRRXaqolm/aaItDktS05IJWvLn/E65MvHhQqOjb1PSZT1OY4ed7c9nj/bwtgKb737AFVN+OLTl0ffk+u1AH3nGDQfMJsFJ74Qk3lMWZ2mgJiBawLy6vy5fjYTVcGyAc7pbY+9F6sIhOkz48uEL9rBISrlTHco+nBMStS/TZ87RjjW2uCwWHlQuwPvG2A7B9cDMOtDqNzY+KSpvYIIpQ3TfNl5UI4ziSOlFEB++BQXcyRaWbGo6b6FL8VpLb/UEJKGNskPLlkNpQgDgq0NaM7o94y2AajNWQZ1pUlTEwaqaIU55GtoZ3WhMzWNga3aYLm661HXBotFHY7j5McmYxU8mw3t8ejRKV6+JLx4fgU3nuLsfA7vdxDnw9xM7STGhU8GiallCnRKExPmFN/O6CmLQ74oJinj6hwHnxUAiNq3NQbDMIaIcdFh1JKBtzYDlmhrcR/fj4y+81ie1mlOhWmb6LEfbud4A2JVSLBaYJ0c4eKQJ+DgUhqvIkTZmz0YKw7pVpNQGONzfbN7BOxbXN9+hZfzS2z2X5Yicpxb8Y9I7ILDPr4lCvvOVRXPhwftNfkBcbZeHQC1bmrBu0S4o1T/9N4rWAC8DyGkFzEePAGYzWt8tSf83362wz/5u4Tz81kx3i+ebzGfVzg5qZPFQdZzMOu7FB69H/t4wipE3wtr06c51daHQsuXbsdxIAS6MkwhTG7TBh8IHTnvyDW15P75r8M6knUntfgeDsnBAnxz3eP5sw28B87OFzi9OIExDbx3WJ7OXln7awH6ZD247dFFb/lhHGM+Z0RpP4MjMAF3ziCdouZNLvEOTU5aAurKTKYXVdIkVCB0AcWISoXgUZQ57ZuY9FQEPG2x0ALNFPyPWQPkszBVADAnA3h08JsGuJsDix5UO1HA4vPHpdJpHYMDPr8tnfj+bNf9xJ4YtchfMQudTMN9puRcSMmYWZOBZ3D0mJN7IVlHzs4mtAIOGRDbmYE1wHYzoqps8uAXrCxjIGStk2LI5NGFQEeVNSLex0cJ1oQY221rsduNuLnpUFUGs1mFpjEqTXIpuHoeQOTx4MESVWVxfX2LcXR48HAJoIPX2iTlsWMOEflGT5Aw6Ui0FR7wMmhJ9ZXm6iBJEn72SKjVUCiYETR9S4XQbKjCMOxR1zWIfAR3ho1aso9bUMkaQ4R971E3BnVlDmgxrLNwfJfizBJRjqsuGr0mEbWe0s5K/jXNo9BBGMCYHMln8BcdQZzG5DQMKGaI43P8ycfX6KoVbocdBjdkyJI2JDNDng9Eq4GNx/Fs9CqXff00CwYK8I9ORPFZ5pmErJRwrH0TtMQ9IQPsdiMMEZpG5TnhcJLgqpvhJ7/Z4B/9cYW2rQAKFtqffjHg8tESdMtoDcMaD+eBbgT2o8d6cFh3Hjc74O3ViIocRhf297XTtIx5zixZKmgC+OyD814IwhPM+QL4cqzxlZINypDkfz4BIPNrfaWiOAsnmj69Y9ytB1y92GK7HTAOjA9+8BDtrIbnCo4JRAaL5T8AoM8A+nEAA3Cjg3OuSEpzuD/OiZj1XqU26WgQZg6gp7VvZk5HefRFILgxBI4QkDBWcnvrs+yHwoguQz+jgfyg75N70u8pKB8TCLIZF0DlgOUW2IfjfaYdgVkPY0OL9Bgdq1Ou31wtsRsSagCHLOfIL/JNSWIo69V9FROlwsgs3B2pLimgMSZ5fjXoB5qpivAnZm1GZl56DCQoTD0Pi/Putsf5eZtPQrDy8tUAKVV5hht9PCqZx0Aeleqq2mBVN3Cjx243Yr3uYS1hPq/RxHPoetQoAp2nPc4vZqiqGs+fv4RzHo8en8GYDsxjqVVwSLqD0aEfatQGMUy0T+1nzgF9Qj8yuGtNHuD7s9TKPxxMpdYapUESAIu+H7BcLgD4CG4MzybKa9HvIB7XAxPGwWG1qiPdywhzqlCDvfhssAnOYoSgEQsdcExABaDgH2rmk8VGBIewfCKDjhnOJK21MQQre+1G0lpHYYYb/OTrOzx+cont9nnS5LWyQAjWhiRQRHoylpJJX0z4KfgOhzbYov1Ks0xmhCngZEEpCa5JKtbbQXlg9eg4F0z7y5hCN5EWAcSMprH407sWP3y5xxtvnMAYi3F0+M2mxhdkYF7Glcay7jiGTCf0Dlg2jO9djOhHH4RzT0ixOoTHoVS0picWRAiT6HlVdAitY2KcqrJpLPQWkHMe+92I/X7EMLg0v3VjUdcWTSPJi2RbYDKm3+WKQl4QlsP4ikXKe8b6rseL5zv0vcP5RYvHbyzw6ce32G97tLMahhiABxmH+ojiqq/XAvRFXhcitZU9skcfwlMKuYeFcnh2Xj7LX9bS5JFn5UqEAjEbUjr7biKTgX5vomWQWlViqpL2ewl9G5mstbZo5zHi0kKF5JU+1l79u2cGtfvg7LdpQcMCWO4B61PdeTGUFgphgM+2Wsq8h+hJmO30uXvQAgz2yhkqApURQWEqnGuMFlmCp0xLAoYgffZiLvQaqLMAYqJX/9RZanFSwzPj9rYP5kt1xu5Qy6LEmIbBhxS6wiRUtL/ckdA/aw1WqxaLE4/93mG97kGbEIqzbcUHQbWYPbzvsDqdwdqHePr0Ob7+yuHx4wtUtYFzXdTyw/zVtYE1Pbb7sGdeVwxCLjPrTzmqZA64yMUE3CfC5TEIDFkEcVmPPqbSresKgJxTtmALELm0vsVY3Xce1lB0vJpWkuedEBO9sIFhH4CFKPyFT2CrT8tkZUALEXL6QEA5gL+1AUgQ16w3HiQpfqNwGMYhvD+rF+g2PfaosWagH7tIn5z7OBEWGXHZcLlXL0cXM2hnISSSW54Rkr6oGSnkazGQ63S7sSQuaVnWuxSy2w2oqgCEmcnGNgOorIGrW3x9s8Ebb4SVu9uN2I2Edjp5hAj4YavWeY/3zncYxjH4fBAlC8c0/bP2r2If5kosLXXcAjEgGFhUpkJlTApeFKcYw+Cw340hF8tdj2EIdNbOKtSNQdNYOOex3QwY+i7STaDpuhZrnEXdWDSNRVVLYCSkQTzg2VoxUDjUdQ7ffB1SDF8+mOH8fJX8YB4/WeLZsy1W5/OQBhkx/4Apfcym12sB+gL4iVn6cJADQALPpAG7rL3Ilc31IZlMCG1bEj5Qmtj1/WPWARM1fFmcuT3S5gzsGUxL8NJ7W9o64ZWvgvzVAsx95v9cbvluLj80wFQedLoH9jX89Ry03INal55PVpKJILQZKgzTKHzFLMXLeGC0gfqK/ur+q5GK4CSLRsZN5jHJUZqBaUDCtExKGlGuLwhXzrjk3ZuaGzVEGzVMEo2PMhgulw3ubnvc3nY4PW1CwCZkZi1jpIWQvvdYLKpCPMjCVLiX9ioj57XG4GRhMJ9Z7PcjttsBmw3j5KSJGcnUu8wYxy1m8wZvvfUEX3/9HF999RyPHz9A07bRsz/0wFpC2xh46rHtZ+BemGbogzUMaxiN9WgqRkXSjaiBsuxJlto/T+ZAZNumrbC+7cCoIyhbdJ2LoG/DcUNCyqAX0jxn2gOHPO2zuY1CoKzB7EcRvsvWQwRLGKQjiGoy0rib0jeDYzwP3Z+UzY8D6NZVBWPsgf4sDnzJqgaGpQq1meFqe4PlcoH9uA7viYCS6JyK8kiE1ggu4VhpjENIlGgkrXtN7UIUXG59sQCzanPmF+X6loeYS4spEMz0u+2I07P24DcZUyIDWwHPNoHfWEvY7DNf1paEpOwgAH9jR1zO9ti/tBj2FjAM046g2sNYD7ISrIDgTfB4TT5UjHwiJ3bCxPgbbdOgrhqwJ9ytQyrf9W2PzWbAbFZhuWrw4OEigHhrjyp/QLByjKPHOHoMfRAYbm46jIPkawnbqXVtsTptcHE5T1kH85iW4+094/pqj2++XmO5avDh98/R1DYlaAOAs/MGL1/ssL7Z4uLBIo64x2Qn9uB6LUBfLnYeiMxWguyIqSQNqDobL5fsKwbP9rjnKotBIcqxsdSAWoArlfcOLAUHBd0vROQwlqVQMH32WHuylp/PYGuQ1FaLdJ5WpN7FALIO2MzBwwgsuhCCeEL8UtdJPeJs1uFmLxGhCt0gfzJA6WWvBZ4CsRMjKLYjDq7wTiEwpXbpPmeWl8ZNNLdIK977GGY52RGi1qb2Tin+wgCTjC3h9LTB9XWH9brHatVGRhZBSEn4BGAbU44GE31kenI6I8b1ZmbFqqT1sT4TTPyzWYV9N2K/HbDd9JjNa8znVdiWid31fkDdAG+//QjffHOFp0+fx8h9tsjkNp/XWN/1uDwNk+w8hWNTIIwufN8PFts+0OOscThpQuphPdDSRxHG9XjL96Yx8AyMI6OuAiiMQ2hLXVt4EYqJYWDAXmLoh7Hqu7BmU572OMZBds+a+NTMkE2mPlmPErBzsAYKIXkv/cpbAwFsbdTibUrKkpqgAYyQrDehL4S6mmG/DUmG5icNrncvQWRA4nuQ1oA0Pa6BSAuGDOqY3rlwPJtIHHmrSwVzOkB5VtSl5+cQ8KfLLgM0sNkMSavVaxaqOmaGscDX2wrX13s8eDjHejfAVm16J22nRaujpFZ+93SL/g5wA1Bd7MGO4HuC39aAA8B5a0WsGbZxMA3DVAyyoZ/WGFRUw/gKfrS43o4YuhEUaW6xrCEnW958e4nFST6+V/a9pOmqotLJVj3nfQi+NQ4OXe9wc93h5fMd3n53hZNlc4BFAND3I778/A5d5/DWOysslyFugMaNYPE1ePR4ga+/WmN1WqOuzdHyptdrA/p+DGc2jSJO0UJIPFpxqKGmiwTMlGQeE25E+2OidAFK7xyIYvxulWhGtIX7tgGOfU9aoEcOhzttIlHx31RC5En7jvVZP5usEio29sFvrQfXW/jbFrhdwKz6sP+vOIw8e7MzuNnXBxaLY2OdPwiTSaXF97lgNNoCIIvJEGLmvUMtX2vMuZxcn24LRymRgeSpn4LARhAodCRpTGSqwqLJEE7PWtxc77HZDDEylu6jjG8Iu7tY5LzmUqB8FQZoirkNznSBtrLWNZ9VWMxr9H2I7Pfy5Q7LZRPDmYYynRsAODx6fI4vv3iGu9sdzi9asN+l6oODYDC7LhYVKoO4VeHRVnHsI1Dc7SvcbCvse4PzxYim8gVTSsIO6/HWHtaEtrXo9g71sgJgMQx7VFUV5jQFgwnPb9Yj+m5EFRnbOPog3KQTBzILgkYhs2a5P+zkpwQsQkvZeuaDuCehd6MZWfwIkmMemXBGPoplB9Y+4iQocgJuwFCD9d0NFosFPPUQgULyXeQr0z9zyP9hYsQ9OaYX9u1F00eKCBnam8fkALFlURzRWg8AP9ty1FrKvzsfgqFdXAavfLHG6CUm69kQsLctfv3lBifLGtfbsL0lFiIG0vFYyaJnMOJx3aG7IVTnHajxIA9QywDGYAFxFvCUnRfZgIYG48ZAZtw0Hs4bjL7CQAazxuLsvMHy0QyLkyZp3nerDi+fW3z95SaeKCE8fLzA+fksxIDQI3NEoZvetzaAM7cWJwAuzmd4+bLDZ5/e4u13VlidloF0dtsBn35yg5OTBt/7wSmsLa21NKljddrg6qXFzfUejx6foGAn91yvB+jzIV2Ldn8M4DPY5QhRzNkxb6pVyjlZjr8lp8A4wof7gME7mRA8RaVO0aC1v0HS5rQWy/l5TUBGtU+3E8j78seEgCngy2XUPtYxs1WqnzzM6R7YN3BXc3zhgXbR4Y3TAf0IfHU3B4HxdLtACeD3XYEpHqhhhcaP2Ob0KX7nrIGJVUeXW2Tfy+qPMB6tRQm4BkECMQZ7EBw9ODIQD+8JZEwM6mQT2OpUqVKeNcDp2Qw313sQERaL7Bwk3e06BzCHhDCkWpk0lfB3qjuIFivaqoyLvNI0BnXdYt+N2KzDXuRyWcd5ZjCPqCqP5XKB9XqL07NFiJIWFxAZitsUXdiLrJSIJMASGfSyHQAwbrY1rjaEB6sBleWirSIUyQQ5z9htBwxDYMXjGHwJwgMGXTfE/XyX+sXMQcsfPU7P2rB/6hmzedZsNP0kMoBoimG8JNOmCNcmSowhaFfYm090o9ZLoeFTBnxLVj2TnQhDm0V4k+N/4Xtla/SdxziOuHxwimG8y86F1gRHQsXIpG8GAThCaOi4PywOfHptM5IDYTlfeR7EcuTjPOrFVgrIJe9Iq5XkW7jvRgbZUKek3ZZftaVFqmtbi482NR59tcaLHaGqhTYVbUMUD4+3TzqMa4PqJJwoEvqTUpkAqp2al7jlIr5UjuB7A++Aigxm8xrLkxaLts2JiKxJwuJq1YZolp4xDA6bdY8Xz7d4/myL+aLGatVgvghRJKd8bqqoBWEyOOyOLlimjK1wdj6HMRZffXkHIoPlqgXgcXO9x5ef3+Hy4RyPHp9EZWyqpGSsEL798NECX35xh/OLGdq2Oqow6uv1AH0gmGTjWVxtwWIxa03A8H5Tcbi0Q0ixFeB8zEw3NemJBuoxjg5gJG9QeeZgn120NTn/WTQ8a9xTDf4YsAMohAK97z99VjsFavDI9QQGUPgwEIMWPW56i4++ukR95zH6W3x+N8N+1NH3vhXxJ1c5B8I8897hkfLymi818El5pdAzmevpa8hMx3sOZntCOKvNPuzfRkbEMEFnNRqx40ciVJaxOm2wvuthDDCbqfFhxmbdY76o8/EiosLjfSrICKNL3UhkMvFnCLwes1mFyhqs1z2urvZYrdoIriFy32LR4u5ug6EfUbcFpw8OfZVB1znYStgDlUNFAc6WswDON9sKt7sK5ycjbLSYCHhmPZEx9B673YDFInh4t61sbwSgHMcB8/kSoNIRaYwe9XVj0EShKzajAAENHOII5uTYpQ+ZNEUQ0Il2DvgAIyWWCoBvk0OePi6YBfF8Hj71HZkpi4WjsjNcv1yjaRtUNdDtx+RgyJ5TXAAd4IhA6eSQaPuSlwDK8hLGQxQPSuOhO5WFkDxmaUonf6W8Y2tRCwfj6FHZIPT42F8t62XhOq/tDRr84WcdruwJ6rmat9Q04XkeT2wHgoeZTwEfcawk1wMnXlrFcMSVrWBrg2oR9vArY9E2LWpboY7phvWci6IIcNTQK7StxXLVYLcbsV33ePZ0A+/DaYTZrE7t8T7wVW3hcj5kafQO8YROUC6sJdRVDYLBJ7+5xbvvX2AYBjx7usajJyd48HBxVHHSOEQkp2uAk2WN2bzCyxd7PHlygq4fDl9W12sD+mn/Pqje4Qit7NOZzLRevTecwTkBLBRYxnCa05CkArLeebj4jLE5vzemkzUB/fxj+KOFAy+eoRNt/VUCiwbvY/VK3nJdV343/MMQTV/dB6M96TFb9tjvavzq+Qqw/sBSEOrT7x2McvjvGPAmjfxoz9LrMt9aQxP5LtVfmA0OV1ECysRIwjwGEyngrQ8MOc6DI9EIvdLupAzFS4nQNBYnJw026x7GhDP9QHDe8z5q+RwhMWqfmd6gHLv0mOlhCA+wsjYkQwczqir4GOy2I25u9lgs6ph5LpyPTxYr1fswbsEbfhx9OrmiPYP0PBsClrNw7v92Z1Fbi9V8VBNQNpk5RJlcLOoSFMjAuSBs1XUFTXTMjHGIbUZZdHZeywKyj1HcnAv7wR4+bdmkELws4XiDYOtGVwAmERKwG2XSzxn9bOHXEVVsPTmlJQYBQMaR0HU9Li/PMLp9oDMEZ7wQgyAcdzTgGNkvbx2IJk8acVkELMUbkiA8pUlkfiPjJ32Aeoj0HEeBRd3Tawwg9L3LfimQIdEHO6fkEHjjJ3ctzs8rNWKU12y8Gu9ReaA6dXCUeXI5vrktIoQZEzzz25gWt4rzVZsKta3jeMbYGGJOU4qBxgdmoKoMVqsGy2UN78PRxPVdj34YEQSEYHWpGxN3hUJbqsqUx/kQ/GLGntB3wRei26/x0Z++QDuzePu9cyyX1WS8ZcAP+Vf22wAePFjg049vwomC4R8g0JdL6a4F87kPKDXIS6jcPKB68JE88qVOkbi8Dh9q1JnNeyLrxS9FMKBjACyAaqscD7rY41HEUQgrkYj1uX39V29t6M9Jd1ZIEsoL51Xv9hUGD1A9JoZyTCp95RUFizy+iivF63iZ0bGRCL4IS6tBSTRjCtkBJ1M+FUYKTNWaBqJFxIj5l8v6UkGqrQWHDRo3M2O97sN+bEXYbIao5YtmxFkwTAx70vkST5TmpepL0kJ+zRjC4qRC3Vjc3fUYBoflsk0aTsguaUDsokUjlG0MYRwdnK/CkUI91ArMgAz8zMB6b1Fbj7Z2JeOUMWUknxeOAhlxiB+/74KwEPZ4M9MihKONdW1iT/VpBqQxY4RkW86FCG4+OsaJB7gAfSC9APh63cqakbj+KU67ivNvSVKsmjRWslbER0DWCzMSowcB1ra4vt3BWot2ZtENQ/TNiAGIwNGB1MNz3tpIJvLo61PwgCQUHIOEkmYoEWsJagX9YAr4qohiHYV3Ak+IwaXCyIZ/VSKyg+Yw0Hcj6trCVrn9Uq6LJOwc0DqPZuWAiuEmp9CknmRZQBYxvPdgyyAj5/LzmfwqZh4UoZ2SUhboMx0j5dKJWP4aAywWhHaWLU4iHE6jqKa06GrsbGUxnzWwdgbCDMN7jKfPrvD86TMY1LCmBmiMVtby3QN8iIUTERYnNd5+bxV8IvgfgIQ7AAIgpxCUSICrgX6qxet7Yo4RUDFW9rNz+VoC0/UmZkblopxKpcyck28g7veL9B1XVjBOZLO6tTaZ97TJvigzWgOEACCmSaXNy1+9NSD9n176GfnsGfjjZxe42h0jqMMyDuWr49LqYd3f+kgAC+DAVElRiCi0Y9LAk1txoEGnBR55LHM058fxU+vZKI1cSjjaOwrA7xzj9jYk0RlHj9PTJo8PI2dqlPan5pSafJRlCho/0KgFTFWrmsbg/LzFej3g+nqPumJ47+BGD6Ia3vdwjtH3DsPg0fcOfecAdJjN6nCsUNdDJUM3BKzmDoMjXG8rPDr1sIUsp9bbZIhC9w3GIQgKVW0QYgEgCiLhONRsVk+cHpHmhjkCPjuMHAJjSa6EnGQnH5+SvfMsKCMCc9bis/NezFoX/0p/ciY45Vegxp5IBYWBAXuL7WaH1eoEoCHu18b1SQx2gdeEs+cqtGyi2Zxd0KRjoxSPkKKoP9EkT4Ei0lKi31KAOhAk1Vcmobk8i2LVrCpKcvx0dlmVAQRQ7TqHxUmNkoqUfYKBfufxvUuHagYMY+wDKwVHHD1JXsnOfzAB+EfnYU20vIpVRYQ2xcszHyn7fsyqEMp1YdvH5mN8BInTEnFChLVYtioB3nsY8rAVYT6f4d13FmiaBl998RWMOcdyVQPoi/gqMrWl4pp9oAhIqbn7rp9ORHG9PqAf6UcGykI5UKm/00s0e1BgBiEHfRnYRxaG1trzZATtIZ83pQMiyUd/1CLkuHfsS01Dst2Jdj0ts7AUQBNBRiBNrNP2TAWfaXn60gzjm3VTAP63g/PxMgEGe0oLtZRbs4Sl+JcqSzSgSXkKsF/ZEv37ERAKa5TSnBIHJzLh9Qf94OhJPymDJuO5WFRgBm6uOyxXMfUrH7b3ePPLcUkAmqY9FCSCa2hTKNurOowN5v4QUcyirmvc3NzB+wWGoQeD41lig+WqxhpA21ZBAOgdVqsmOd2lfctJO0/aEc/vGmz2FU7nY252FE4CQzykR6DGdrtBXYc0rM5x6tvoggZtVRCjxEsjoLvI7J2PgB/vcYzXIVo4i2OVdwV5hsh5VgG+8tJX9wBATjjKdoAE/CICWOWeYEWXVVVjc9eBmbE4aeH8Fml/nQiGDWwSTjnQYBRaKFqsKtmjpgz45cmFSCfxI0tZlJ+Rv5pWOG4pZEnTx2e1RbJ8X9bgOGq/hSwwZ8uVfj9cQzyW2dRHsnDG59zosbIDvv9kwEhZoDjQt1S7GSFM8+BGsLdwxgXnTWfhKUbxE2FY8UipV3x5popd6oKiWYmTIFaGQqiCCCAM4myRyyV6eB7hfA9yBswG1rR448ljVNbgs08/w7vvXWB2YsHsVDv8REiC4gVZeNXKyH3X6wP6jJRB65imOjWHA1ljEiIQEzqAGMQHSYyShSbluOidD5QhO0XzljIYAfgLz31E0yoOnfQkA1/RNdWnqQVhKtRM+y7Xsa2B42CfTYv6+vT6JK3jcvHdj/6HxUeO6Q1gtIm6LCO/92rJ4sBEefjEYRsUfoownvhd/ic8FrmKtuCIRC+RwJDmIr6bEEBvwQRnG+dCAA8wcqrU+1bo5D4zUk5zSzmORNJ2PUM7dekxJALkhaapYGyFpr7A06cv8fLlDebzOR49vkBVjXB+AHMIO2ot4eSkxWYTLATnF7MU4z71N44eAWhrRlsz7vYWs3pEbXOgHhlzzQQJgDE1dluH/b7Do8cPwDzEbYfA7L3jqFURdJUc146c5fYxcpuT7+yTuV0YomeGc65YN8aaFJqVyMCanNAnaPcEQzYdkyQgH8mFXn+lFlyABLVYr19isZjD2HBmO/Q/OgCKP4AnOHY5oaIJx/KCtc/kkLsC+lqblKrVUshavAgiAJVqp7JGlH+FxsW6MgV8IPDAcYhHpWOPUlRInqyt+N5+P6Jtq0kuD07/Mhj7vcPvPxxgquAIp59JF+UWyyVAy9Zg8A6VDyHZnXFxDdzjEyBCEoftrhIrhFfG8TKSmjcPWRpyGfcU2ln4pbK7MQAaQ54LZ2C5gjEVjKnx6NEjgB0+++xzvP3uOebzEEhKLDI87XOUsqQeTq19dRjeV//6H5tLwqceAn7xVJKIFOhRBkQBZu/j/hxR1NKjhhI/p31AQweWAbE0OOdCgBGKz8T/kkUB0VlIRe0LPckm5Wlbp3s6x0B9qknp54ThMedog1pSN5JwYvLupiNsh+oIPr0KlLWZXcYfWUstnPUyuR4s7gM9OhcWDamT9hxK6UUdfFiD/p0h4yE+GZlhCp25ZJ1BYj6y6LNZT7UpalunZ8Gsf3c3lF2+p7ehD5y8gkNplHoqH4ReD6wjLD2SFwK9ezfA1h3eevsBHj16gGEY8MUXT3F1NcC7BQxOwByzjhnCclljNguBe3L7skAj34iAZTvCecLdPgQ6SVYIJeDmhhKIZri6usFs1mKxqOD9UND1MPoi8ImysMOxxxjNrY412Ofz+VnL9yn4ljHBybaqgvNhSFxjURkB+rz/a43NWh2VOTjEUiczkgWuPDbWVtjvRozjiOVyjtHt42+U1psIHZW1qKsqZ8+rqhyIJwoeBmHbUiI+6tmQPqc2KMwnUrRjtKVAnfVPz4UCZeNA/57XVNgOGkePbjdC/EwyAAkfizTISFHrmjbGNlE04SPPGwYHHhzee+zhoil8ulhkjcqJCT0K020kjj4zYZsHSdFjz/m/SJ/WmIJn5TUn867G6IjQUfCBg7YJyctTIxg9GDs4v41hsUc8eHiKt9++xGcfv8D6rst8/RVh9hhBeJ61F5i374D9o3ufBV4jTV+YYybeUqorzTMqupFQKnJkPmMoHcmTxFXMwSHIxAmtbD4ed6Axc1gokllrapZJR+tMMO0xOJ3n/7ariC19RAhgzzmuACvnxDQ+nJ4BCI4J247wYtfCEuGt012S1rvR4NdXK7zY5vCaLGJ7qlPfP7w03ee9T5qAfr5EgxQp+7DcKFeTaLBi1mJovJX1pRWhgDUMMZ8Ke9DG6iSxpwUaApDII5aAytosohxMPZezTbnfBGC5qnFz3eFuDayWzcEYgcXBTph41tOmAhmAg5TNmeZjYYLGk4rCFsYWq7MWy9UbuHp5h+urG1y9vA6mbmtxfn6GygLOdVgsGC9fDPBOcqsfCtUEYNZ4tLXHrjdYzQyadPzuUFi1tsb6rkPX9XjrrccAOhTMnRn73RiDHOn6WIETp7WpAV/O53MUiNLJG9GSjUEle/hGgu2IA18+D29g0vqXdxHLDhaInNlOgBcQvw9CXc3x8vkt2rZF3QQhJh3vE4E+9s2akO4VahRE4BArQ6YHFM+BBcylIfE2ac0uCFupnKlUnvrBEUhEMJP5kF+DCX67HUDG4Pq6w7x3OIlBbkSwVzMOz4zNXY9x9NjcDZifVNE3IeOgZ4/dzuHdiwHGOgwu+GmE7ZtDU/khqMq+vQAuoTZ1EuhqOUItoDwdQ2R+LnKpBv5j1/1QLCxEGh1M+TopTzg9MgK8hyMHawgMj7PzGZjP8fnnV3iTlzg9a1NDWTeaDGw1Q1OvsN9ZfPLRU3z55a9xt757RateJ9D32Tx+LCOeXAKC2uyozaJT07mW2PKEHUbbS5YAIIfepLx/Jk6FpETEVLaZtGvS7mld9/VLpPvpvXFwaR9ZMLtzFpUB/vDrC2yHWkrEbjT44YM1AODXVys828yKRX9cez8+J5lNyWfdtin7mr5X9u9Qa1efPAfmVq7eWBJFJyTZpyzfl1KkH1nLz7+6qCE659HUSDnL08lnYSCpq5S6LsAUmhkY19lZi9ubHls7YjGfLkHh2LKdgKQxHYx9HCpxLJxeiXFJs/R78aYbOzB6VBVjuZxjuTrBbtths9nhqy+fYbVa4vT0BOO4TfXl8rNQogWbReNw6yrI0UsR4HRQq7BN0uLq6imWyxO0MwqWKGSA3e+CWTbEPT8U4GW9E4t1zWcP/fi/pOVzEJqIEY/hxTC6ot0bk8z4yVEu0UFc86T2TonS2Wv5N4F+4hcG42Cw2+3x6PElPJcOVmFYJhq0aNSeUzTANGskfGUyETIWRTnyh4r5jqL0EVop7Qb3aZbhyJrDZtODCDg9bdDUFqPzuLntUMUMkFUdgwRFrfr2toexBg8eNOg6h/XdkKwDiCYJQyEE7Y9+MGBwA/phwDCMcMiC45QXURpIitbTIKiJIBd4rGhuIgTRZPgy/y/mpnjinotRLPvpvVyeAcHCUpWwh8BwfgTRCHgX3VcdiDwuLucAAV9+eQPPhPPzzIetrWHtHAYnuL3p8OsvvsLTp89QVTXeeOMxfvzgB/e1FsBrBPpkxJuyNO+XezdyrEa+KlBFWCD3hcCdCgHHHOqS/6lqQ9YyyzKnxzumpnwtMCThRP2usOGoxJt9DxyYPYgtvt7OcdvV2PQNNkNdMpt4fXE7R2tH7AaLF7u2eOYYs4nDeu91AFaMqfpxcJUL+4g8LlwsIlrwco7qQuS+ud5yBeq2BKueFpTo4BkfC/MIQl0KlJKYYt7fy1K9FJXFSWmCMcEx6/S8xe1NB0OE+UKfV0Zk/JTv8aG2LD/q/UL2PoGwKPiaDtMetEgSCEz89rYHM8dUvCMWiznOL5a4u93j9vYOd3cbVHWFy8sVDI0T2hcGpvoY5WkTBbspUAOAtQ1ub3ZwzuH8fAnvO4gDJRAC8mw2A1arJo81T+YSQTv2HBi8pxA1UbR/id+u17cxlDT8wqSf9szTji3ES0JC2uptlnTkK09F4gGy125ti6uXa1RVhXZWYRh3xQyygBgjhdBNtJQUl9LaRepffS+vTdFM6Sj9F+QzAXpVGsR3Rda/nE/f7cL2y3LZhLDNIqSwDWGVu5D+Weja2nBMlQhxLkO66MWiTmPsxnBCYxhDpMrnt8CTS4/RjSnAUvCFyqtJhDKxmoTP0XJgKJ+4kDgLcUvHGCqGb6ooHYyP0k2KeVAKYx7LiA1pDvSoUgTrBhIjgOWUhvfwGEAw2brAhNOzEwAVvvz8CoQajx8/ArjBdtPj+fMbvHj+OdbrNRaLBX7www/x+PE5qqbHMN4e71C8XhPQp+Tsku4o4Ev7OJwlWPGaBwcTIJKDUgnc03tSnnj8h9qVoKAJSpnRdbum11FfA2SNRz+T2oR8Bn9a9lR4sJXFbd/iVy/PINJy2YxCRcZHV6v0WZiOmfTju11THTNe1qvftOCUFw/AqZ1T8M9LCjEjoha0OJnADoWRKcsN8ocwLnkmtyDOiQ93mfNZcGdMOmonmc4Ouy5MPEtOclyoqQPj3Kz7kOFOItNNRyVKLyTDf48AI6wwROmKP8icKZVfa30C+ECwPlhL8N7Bcwgcc3be4GT5EDfXa9zdbeDdCnZm4VwHrXVpawIIcJ5QmRBrXe/b5jYT2Ne4vr7CcnWCugk+MCAKjlgIMcjr2qBpC+N0+iCaLRD2w5k5WHQcogd3sM6IcBz2zimc2a4qdRQvh9alNMjlimAOpmcf2wiGCuqSHz6wGPoK67uXODs/BXMXI3lmQBXBLPQ779tmQU3p5EesOUlAUKKHFryU+BeoIy0oqPu5jyIkakF/HB26zmG/H2GIcHKSwV46LtaPkASqiuAfhDY3etSNxelpA4mHE6ct9oFgaoKtgMoDZGv87c+Af5R6nKwiUEcPNgHEMJcWlQqYpPf4K2PRVDWaqoI18Yx+xIdj/FeORYJyX6ZKRlqXWiE7chWKoPruGdhterBjVFUFkAXBwxiAjAfDI5zgtgCCcFChxcMHBkPX4svPnuLmCri+usF+36Gua5xfnOG999/GxeUCZHYY3XO4fizbfuR6TUC/BEX9nTns54kmls93iuk075XKnr4+cz+tQ8zwYX8/m+eBuFg1UVB+T8fRP2YlEEZ28EyxqBHbyWrfqmyfrkfaREQ4awes2hF3XV2A4VTaL7/qNMTfFfBLED9YY8Sg2iVNWD+rmQipsYsvQliGFlrKtTeRsCm/mX7V9aj38nl4LhZ5Sq8s5QrwS8x2I9sGVGh+ukWSBz3x4Xh/NrPwPjjIEbWo6zzTpPqWgARBSLlHlII4/IjwZBlZu89cLTFe74G6MpgvahgzBToP5zpYa/Dg4RLMwPPnV3izfoSqdvBynGgiYIKB0QOVVaALEYwBEMGaBjc3O3jvcX6+hPO7AtzGPgDN2XmryETmjNNkEEVAYMBbho3OvA4EJgJ7gOFTKF1xktOaffov1h36IXvNYWE75zCK13+c8+yxHi7nsyBLIFRVEOgA4OSkxeju0joS4cDEtV2K3BP6UbpE4klaGJDn4tpNHvfIIXdF0CosUUmZKOkHQMoMt9uFPAmVNTg5qdG0VbmFgAySMi8Egq0Iixiad7MZsBRrTRKOVEfl3Xivqgn1zODvfH6Cf+wH23Bqw1O2UMXxNVGzr2yF2loYEyJcGgqCXWNrWKqKPAnQ60H1OVlpJ4Mq/Zzu638nwFfrwjNAnvHZJ8/BvkLd1PCOwRxiU9StwXxW4/LyAt4Tht5gs9ng9vYb3N2u0ffB7+X58ytYa/G973+Ad999CFs7DMMG/fhNdIAFrLGvdPoDXhfQJxyV4jia94RBIErsFM3Lx85l6q0BXY7+C0Y6ajMVDgJ/Opx8uXz0Ik5n96PEbMgUIJkkRBUhSoQTM6n3mCUiCCeBvdiYLfS07XHXhXjRBwStFzNrjWGi0R3Qe6kx6O4LsymvEhnL8pRGou+meg8FHaISpLWMMHkysMEoEeg2Hkj2R/sRnpBsbc5Hpy+WIE6MfI4uvmeQAJh0Qeqaz8OpiLu7DqdnbfJULxKvJMDLe/zTYY14CgOCU9oFEGRS8WfIvJNCStClzgQYBy6NdQB/oMODByv0w4Cnz17irbcewtAO3quojGnMGM4T2mpMgmwp/Fp4V+Hm+iVOT1eoKofBueTX6TxjvR7QtjZG55OjrSg1adV3MfNaY8DGojISHZPhvUlJVSobMtRJZD2K9CROd2GKchIbRgBzEfySKVkUhgIoJDqcHPlrcXd3hcXJAsY4kEcKkZwbX9KL1Akl9GZ+lN5IQYsEZJlLIYAZcInIs3BR0ArKS/hF3zvsdgPcGOLLn57OUFU5nLjQMiMDvsyBtpZ5ZnR7h+WyQV3ppDpxrJj00MXywl/TANvO4rOXc7z38A5Qc05xnsV8XxuL2tbJapMcM41BRRaNrVKYXE2Hx7BCxk7YllYcg3U1j1WywKo5KsvzORY/AzAjrGUsz1d49PgRDCz63mGz3uLpN8/x9RfP8MlvXqbtKWMM2raFc+HkBxFhcbLAe+++jbffW2HffYGx74MSBRfWBlsQN7D8alh/PUB/con5XZhElnzyXhCnpDMGesEfA9NCGgUKIWNq6jkQFhjJT2D633S/dSqBU/yQGPpk+2LaZ2lL+Av84TcPsBss3lptMXiDr+4W05GKZR2WQ/F+2Z97R/y4Vn/vpcfrfiEhf9ftLBvBnM+vy47NsUVYqhnl+9qaoMFZLAqFsQGcBDdnPIgDYFF0FCTFyFk4mbKUJNAWFYyAxUkF7xl3tx3OzmKYXMVoshbNMSkLJ5TP8kooL9CkstgwUjS13AntEKVPMqhH1Dh5P4Joj8ePL/DlF8/w/NkNHj0+BWiLYA1KgxOBMiQdSkIxsgBS2QY3N1sAwPn5CZzfIEEoB2995zxWp7ODKSvmVQFfGCSCJQuOSp1hAxdU/bSnq6Pr6YA72i9CVxFyabioPYZz/Hk9UtEMMTETAGMs+o7RdR0ePDzH6LfF2Oq96ASCpKw8kS4CI5/0XeY6jU1OHCTf03YmosDoTdxqocxTkvUnnLff7x26fQioNJtVaFc2ntKII1MIHwTxM9Fmfm216LpgzZvPq6Kfqd2KmXhpM+J/STqgILHGEyrBzBWFnbhdQzFHQm0rNFXw1Kc4t3U06x/nB+UlPJPiAnVOEjWFthhjUFdzVNUCzHFP3ssIU5rDfJoGIAplMAj7XY+72+cwNOLr4SVurm+x3+/R98GhcblcYrlaYj6boa5rdH2Pp998g3EMPjZvvvUEj58swbTGzd1vQDH2gB5zhoPjPeD/QQjDG3st0fWcC6ZHW9nyKByFTGmv2qeniZkzPBQGV7LT6Us87u/b5yFthhewR3AmosjcWZUjl0H0Fvaydz/p8qQfuYvhnmPCug/OMp/eLKX7B5q1BjY55pjb8arFIvqCEHzqYqqrfO7VV8E8isfzvaQ1K9wTa45ss2SnryPzOC3PK+ZDgs2He6e6TR4hIYpjD0oaKkVLDSctLJWiAAWxvTIiGsyWyxq3t4zbmx6rswbW6LGl1AAC8mkB1aeptSpjBCM5OVCp8aXfoWepnC9OPHhEVVk8evwA33z9DPVVjYvLOcZxm/oFBMBnECo5waIKYia40eDu7hpnZ6cwdsQ4Zg1rGBi77YiTZR0BJ0+izI0WhvQoWkOgePyVCCAHUIz8aMikfV0BieyIl4U0SuMlFp2YfEkJ+CHHYlQc4ljJ9AgDtrbFyxfrcEyvZnQqGE94tgydqzVk3a0gTIhDb6afPHMSuS/ck2OKaRqVMMFkEiCJgDX0HvudCyb82mAZoy6SWmBBLjJp/UG9n/ienGiNgOk5BOFZLOqkqBCy9UrJo7EfQXCRDIjjwGjMiPcut2GeotLkPccwk6Fd7AEQw7BBWzVo6iZq+NmKAxz6ab3qEn7iowNhXc3R1mcY+govnq7x7NlX6Lp9oSyIQ56en+kWbsi+OmKz/grz+RzL5RJP3niE07NTPLx8iNE5bNY7fPnlF3jx4iX6vsdyucAHH76Nx0+WcLjBpvsNvA++FZWcJZ8I8QDDcffKPr4eoD+ZR2GSU1N9Qaic97+1iRvqWXCePDKUwvRqBi5/jwkR01S3PlofdBQuKatoSxJilEn2CLFqq8H0NMB20FaB6Xv53nEtu3xh+uzhJc8fA+2i5tTuVwsCZXnT98XcCoi0Le3MQKnbWjJV9Tvl96T/R1s1ZcrIgY4C0zbwJsfqT0MZ60ggLzSiixYaNYTVqsbtTY/13YDT0wYJiZDB7uD9soPHm1yYYZQjpLJkyXMMJGe6fCg4PDOOHRaLBS4vz/Hy5TXq2uJk2UbHvlDE4MI2lTXl3IUseoS7uw2IDM7OTuDcGut1j/1+xHIVUhG3M4umtdlKdgCI2bqh98YZBnJEcAySWdjnjW8G7d5ksFeAn4YYiGZnDWqIcfJDpcmMHX/XWwFhP91gHA222y0ePryE8yH2gGiSWrQqBZiSNhiHmTVl7oo5Fx4ACdBU8qIY0y2CZUg01HfBhA8mzOYVFidhW0kLi8XAFFcWRLOPQBaBAMCNoQ1ta9PYHWxBxN6E9gawFyfZYc/4/Te3aBrACXgzUBkkS00Vt2maqsLJbI55PYv3wwmMMDQ+W2C+ZZ8byCHcw/adw6y9QLdd4Bd/8hlub25BRDg/P8Xlg4uUYIc5BPUBhZguEuzIEJKwQsakBFDNrEI3bHFyssCiOcPdzRY//dnP8fLFFfb7PU5PV3j77Tdw8eAEHncY3DXW3TNUNmzHAZXiA4ouiuV2L6MG8LqAfrzE8U2i5AFIAC8LwRiTgMKNLk5W8sTLmnK0FnjnwyRKWZM6U/m+BN6p+b8Ik1oIFlFiD2JrWTaQUnbevwdVanly/+lmfg9Iq7Ox0FpGvnf0re9EVFSUJ1p53gfMWp1+Lnwuhab76k7gHAWp9I4Ma1Br7hE8eFIOEoOQ31nFusxLa6KbUBAA2THgAUMjRiMhUiNbFrAtBKly3KZNNMZgddbg+mqP9brHctWohf3tTEuXm7ohxyMDl4U4fMWYM7lVUdYk3feiyaEvzu1wdn6CYTjB8+dXMOYB5osFgAHeO4wuZo0zesSCuXccPIZhwIMHlyDTg8fg4V1ZwmY9xHTEOe0uChopgU87ZEVKBiGafEHxbDdHQKIE8smMzohx50mGJgk9hRIQNe5ECxnnQmuU9koAbNXi5moLay0WJw2GcZ+2EUIr1XjKBHielAkUokBGeogPi0yNjEURlChln4uhjNljcB5D5zEMHrYymEUvewGsJIpw5k/SpqTVsiKH4tI/ULAcVDYFJ9NdEFO+CCk+7n1LpMt+77GsB7xxsU/jThS2V+SYZdjTDx76s6ZFW7dp60a2YCiZ/svkOvddsv/ufAgrvJg/wYuvR/ziF3+M8/Mz/Oi3PsRi1aAbb7Df3aUTBEw+CTzEBqAoBBjGMI7oXY/9vsOu22MYB9T1DG9efIiX32zxJ198jP1+n7T+8wcLMG0xDC/w8u5jGGLM523csiixLC/LUlj8lm4CeF1AX4gyBrQoTOqTy3sf4+qLU0oZaIc5Ru/yinAkTeSB5F1aAmTkp1p3eCkynfh+Ms0nu1kOi5lM1uneRBjQ7x9pDxFhdK+afc3NqWRyBbhw/F1/12VMr/slTAlMkxjXve0qyymFjfC7KXZsYl8S4iNjri4xaVn6rvymBCgBCpJY10kN1gpxeJYBMsEMaNmBOZwZJwA0SfuZ2z+RYOIClljuhginZy1urjpYO6Yz/CJwftuaZkxBKs5hBAvZoUrZ22jSJjXOqUTSWgXg3BaXl0s45/HNN8/Rti2WywVm8xlO2grs9thsRjg3gjlYRO7ueux3LgSscR1evNhhHB3ubvcgAurGYrVqQoji2ITFYoZKRVFLHzinpNabJdkidsSpVwTuyWCxcgSVML2sMhVNQ70yc7on+RdEWDJkwa7Cen2N5eoEZIYUAhZQqXZ1hxSggzK9l63NjF3mTJuOhQcl50+hX88YBkbfB4GgaQwWqypqjCIscNxKPCZoKcA/ciXwSX+zAJ9BKrdPPnsgxVBw7FJQpdF5DB3w2+9sAeOREg6B0hZNWzewpkJtLJq6QVsFJz6DnAQHejv0HlZz3/gRVZjXD/Hpr1/i88+/xDvvvoXzxzW+fPpLbJ7fBYGGDBbzOZqmBlnKER1hUhwOZkY39th1O6z3O/TdgMcX7+By9j4++9OvsN93wbx/scDO3eB2/xmunm+xqCusZg3atkJd2UD/FOJWMDxGH7adoI7mBp8TcWSkZOG673o9QB8I1GkOzTjTvRUASSsMZh9TPCfhOo2kTTSyGLNT4HQ/XW8jHNPIZT8q4FJ2FpSFSUQp6Is28ecAHfdLqscEAGZgP94X/Ybu+Xx8SI9XOxUM8n2956ifywwZQZuGLns6Zve3qdSGRDFR4Tx1i0RxOVLXgSCjNDb5nE23nJSy8LMwV6SEL855OPIwJgprMNFIk0HpkANpyMp0WtkI/DcdjAm5u+XBLKrdc2nVMIE1JYDT2yG6lAyKhyWnfe94hRMxOzx6fIrdboH13RZX1zfgl2HtvHjxEu+99x6ImvTOyWKBk+hHOo4E8ByGgMvL7G8CBnw8CXh1fYXx3OHBg7Mj7Tk2iuXvKa10si4pix9lszwQaMQ7l8zjUkYS0OON8KraNpThDmIbjKmwWYeUqKvVAt5t0vxKPAktkMqrAu/BIpg7WDoYCnGnHwHJMcCyHmI5DuiHsDduDKFtDWxDADGYHUYX3s8pDQzsvRa2idNx8XvufV73gZcNg26bT+GQ5XvQ7IMZfYxraNgDF/Meb5zvkuWTKCdEsun8fYPaVuE0hqnyto0C+6xUHTQ7tNnHvkXLl/cMa2eAP8Uvf/4VXr68wvd+8D7q0z1+/ukfY7PexjTGBlXbgskDlsMpMPIB/InBhuDhMbgBu6HDbujRDw5PLt/H0jzBr375MU7PVnj7g8e4HZ/iF89+isEPaGqL1WyOZtagbVs0tcSdCU6F/eCwGwb08fioXMSAqcI2x7ypMatyJMz7rtcC9AM4Z+eYY8CbAEeYnlq8wgzcGMKAWmsjU+BXChH3adv68t7DjQ7e+5TA5Fg5ui3ZPEVHyz5Wp/786fUc1/vjHpzJsDABZFng8U66f/y6j6j4yO9Z2/z2cu8r8x6hgMRykuvSbPiwnvw7CYDKGT6llct7SVATfV+Pk5jaIGe0x7Cl44IpMjBLisJbhvxSa8wVTgXTqiasVk2IbmZaNG0pvd+/rKfjlUSKWEe0bsVnXwWgeitKSkrPeIfBr9G0FR4vVnDjKUbn0feM7W6P733vw2/VOF51ffrpJ9h3L1QPyh5qXTi0szy9IvNLstVDGfiJ8hl2QGmsyGvxgJdEAVh+kSx+aY8fAFDj7u4ai8UcVcUYxpiMJwmPEr9R1R1Bx6QGS2paJKuSmOpDg1hQFrJdYY0BXEh12+9DnPqmNlgsK1gLMMXsg94na0Dya4JJHu45wY4SRZXgn+l/OjZayMy3xPE5J4RSTnvRnD/G7IjeMawHfvzOVRBOYgtyqmOLxtZobI22boJnPuWAO8cinL5KUAlhyUWSA9pmhf22xS9+8Qn6rsMPf/QBhuYaH3/za6w3awy9w2xWo6lrzOY1TG3gTda2vWc4CnEjmBn9OKLzA/Z9jwerN7HAE3z80ed4483HMMsBv3z6H8FRB2MNamtgLWHkAOi9G0EEVBXBs0c/OmyGAZtuj24YwqmUOEIEwIwGTVUHPtQCM/wDoekf17DTr0obFic//UwG0TD46dlJOdNL9uq19p/ux//G0YVMXNELddq+6T3RRJKWcQ/h3tff7WDxcUyDm387/jlf95ncdR33jQOp30n91QA3ZduvuvJz4hMw7cuBhSAy7WlsfZ4wogNhJJquswQw6Rll+pgyPG3RCKAf06J6nS7VJ69+mc+yq1xyUvkc579tLZiDg9vKtMGzWvVErE8C1QISAmhiuhcNK+ecOOxHEg08H5i0i9FTgxAcnwYAwWxfW4O7voYPycvBzHj27BnOzs6w3W7Qti1ubm7gnMPjx4/x7NkzjKPDkyePcXV1hb7v8cYbb2I2mwEIgV3aNgQIspbieWsR8gU89f5mFgDyHErvMphls3QWcsL2SjjepwYkr2np88RyKAKCNRW6vcMwDLi4PIVzeU86TXV+K4F3Ehoof5bVUpIkp7lNwli0DHSdR98F7a9pLJo2JPtiSCIiCSjl1HxT3I8OtYXtLFOcGsktpkymQmSaJpLgEx6Q3RGGHHk7dDYMaZBd9pTvCT+8WGPWOnhW4XUpB+Fp6hp1VYez+VRFzV6Ek+wsWegYaq4Ptf4ghjXNOa5eOPzpL3+Nqq7xw995H3fuSzy9+grb/R5d32McPJrGhuiBMRfE4MfojsEphDNR8AMb3Yi+72GoxoOTd/CbX36Bt95+A9VZh4+e/hyj62HrHDaeGRi9w3boQQAG52FiWOJ+dNj2HfZjj0HNocyCSbFfPNh7ONdMO1pcrwnol9d9gB9uHH+HiGAtkrn/mHPcsb20wtw3YZTexUALKpuXFgjEKzWbII/XM728Z4xscLVr8cnNCRrr8cH5Hc5nI3754rTQ38piMtML9egBKftb/jYF2/K36ffjmrwG/vxZ491he4/Vc/gMH9yn8kfB9KIP+QsxF47qGUF1hERdP2fAJSSGFqI0epCP4VrFo1w7FhZAT2V1qu0CXvN5PsOfgvewAvmkNYa90qlFU/QBSURTBKJBUiAB1BAAAQAASURBVBoBznvCpsqOZ3rZiKAByPErTuWHMXHoB5PK8d7h5z//OR48eIBxHHF2doovvvgSxhgsl0us12tcX9/gyZMn2Gy2ePbsKZ48eSO1XY6PDb3D3uctMmsMbCWCQPgvZZgTWUDGUI0EI/d3uiUQhMaEvkjkr8l2Yp2TWO8AYEyD9XqDpqkxm1k4t0tlyJxkYMSEFiMdkFq5GrjSW9kHaRgYXe8w9A7GEBaLGnVTHu31zGlLJ1kzVVpoz+LkSIADKlOByKbohIkzpDHgPBZqoJM1TObdcfTa51JIZE5m/ZwGOdCd9YQ3L7fCoSBOeNaEgEpNjLInGn4W+mJbFQPRc88A4NNjxUVk0TQX+PKLLX79q49xdn6Kdz98hBe7T/Dy7hn2fYf9rsNu38E7xhJzWGsB4pTSWU7iG2Sc8ewxDg5dP+Cty+/h9uUWdV1j9ajBL5/+MUwF1LZO7RBrj3MeHffw7FGPIQuh53DUr495CPQ2oPTPgzF4Bg9R0XwFdgCvDeiXoMneJylwuv+e9ssp788DEWhxCNyvAl8A9zoNiilNTPr3Od+x9yn+eyrzFWYpANiMNf7Olw/S991g8UdfX2DVDLjr61cAKJCgZQLq098PP2uAvkdywqGwMH1fGJ9o5MyT8pLWfr8zplKII2DlKnP9GayTpC99EKZ+n/QQP2um5SMdSQ51GQdjjRQWNBZyir4QzMtAOFuf2sCYDpMAKokGRwL8wMlJHYG/TzHMQ/2ZyTMQ20VFPgItIAjgJ4GBszaWzb55DoSnioDDEGuBDAslU3QAFYLncs6MMXj27Bmcd7i4OAfA6PseTdOgadqooTi0bQuA0Pcd5vOQYaxpLZbLwBxDGwH2MS/7EEL15mOt4UiTtcGZqqoMbKU06dQDxNMMJU8Q7Z8pnPlnCu/dXK+x3fYHAu/h9x2ur27RtjN89VUH74f0q/ceq9MFlst5pswJ4Gs6kGbKHMl4ew/0g8N+N8J7iZjXwFhKjqDikCbgU/zng3NcEoARBJeRHeAiPXsCGQuxgmVLh14cUdxMjTXqibAHHYRTpHdF5BKzvvDHkNMAeNL2MJWLYxm2GqwC/fxfraIpZiUttczoBZGbm2XusKataVDXl/jo1y/w6aef4803H+ONd0/xbPMxbjYvMbgB+67DdrNH342oK4umqWGsic50Lmr6MaFTPDUgTondvse8OcFp/Qi/ef4F3vvgHXx9+3E8ujdVKkMERQKDXbDKDDQma4z34R5z7pp+WdbzwA5+ZPiUlfD49VqAPiNq1UnsjIQqi1mOy4n0qkzqsl92H8C8Svs+sCJM6jQCCijP4ZdbDTha5qvasqwH/PajG/z82Zl+E3f9cbOOtiAf1YZzDRDnm6RxqsdeBehlmTz5XD6jg1mIeU6j9rEjtcL88vOqbwfqUdnmV4ttoU1Ja4Y4G2WHStGmBSApqm0cG+aZQfE/512mNSJQjBQXmhZ1EM1MlWCRHLemNECIwXt63N2G4D3GiMk1M9+CdiYaIhTgh/EX7Z9zuFBEmg0NTAg0zUxJccAlxru03fkUOyVdbdvi3Xffwc9+/nN0XQdrKxAZ7HY7LJdLAIztdov5fI6qqrDd7nB2dp6ZdiReimBMFaFuDMA2tCuCocSLH0eHvuecM4GCAFBFy0BVmTR2Qtx6fz8psFHQeflyg0cP38bJyTSa5eH16OGTo/dvbm5xc/Mcy+VcT00UQLVvQvyX0qwBAEYH7HcDui5EB5zNKzStRWUpesFroGd4DjSYQ0bHY3EI1iChN45CuvcEZzyM96CA/rAwh/5MyIJkaqoiNAKw3zuMo8NCZY7MvIejQ1827TMzeDS4vNxnFoDggV7ZCrUJQF/H/XyrTm3ISSehee992uMXAUjmNgm1CMcqDT3En/zxb/D06Ut8/wcf4MGTGs9uP8Z2vw6gOzp0+x5dP8DYEBIXFhjGEbAUHBCdS2BMiD4K/YhhGOFHjw8ev4vbl1s0bYP5OeGTr7KPSgpUxGE9CgkG/wRfxGgQS0Ax3mpOZGwpTCa6YcCrrtcC9AFEqTQfdzMwwZQVB9cY0ciOgCplgoTJA6gZf7Z1lcBcmOrjJeY0AXxdFikmGT8oM9qhQ4q+hMETEd5Ydni66fBy2x6YrVK3SIiqvHekZAQwzu3Izx6C/6uvRIaqvFBO2FPlg3o0TBwXLHTEv8PYAsl6EIOykBEmLmxUI5ESRrSanAQeTomXpI0BLIWOKGr8PlmH4BmePOAYYAs2gPEOxuW47kETCGMgpw1K82dpopy0VAF/l4L3cBorn+hItoyknOxPILSQgUGCRYm2wswxOckYfBFiGwtQVKNK1qQ6AGDbV/A++4cYY/Hhhx/g7Owcy+USs9kM8/kczIzT01N8/fXXeP/9D3B2doanT5/irbfexMOHD3MlsU8+EkayXOi5MRSPcDLq2gCw0eoRnatcSNva90E7jqk44mmZkBxG/HhSTguTT25U1uLhwwdYrU7x572srbD78kUxeqH9UyE1SBzjqNsdjrTVdTjSWDfKr0OZsRjIGj0kul04ThqEOx/niRMtSxlMHp4DkKUIgGppFMstkSuBWK0hEIbeY70OCXaqyhQvJbqL4OhYTNWA8cDl2Q6g6LgXYx7amP2wjqZ9zcP1nr/049CZz2fBIja9qZfw4xl+8nd/ifV6jd//C7+Dk7MBz28/x37oMXqH0Y3Y7zv0XQiRO2sbGGPQ73oQE4wNkRmdxNf38fSOcyF08zBiXi+xNA/w8fMv8f733sY3dx8rFkTJKuBGVyqCCN74QotG+ZhMAT8UVd7zkQ5edb02oJ/N5YEqfQT8oDkhALs/7tEJIGXiEylfFhPihJChGKgnMx9QGdkvN+YwQFCI4Ba1VZTEKtcxD1T5G8x7IsmG30/bEVe7++MsZ/Mbpe+HoDrRmovANt8Z6dUVdeajdek2KOn0/h4U70kbswBBxaMkkSkT4HNR32HxrP5EAOa4uEQmk+BIKOlLTPtacJEQvZ6DV7IhE7QnEzT+lPiEOQT4SUMWAVvaEruWmxW1cEM4PW1xc90F5rqsIfvQSTBJlgnlwCThnpkhx6VESxHAl8t5DxOT1AiDZWEiRCrPAIFTvneG8wabfQVrcmAeYwwePXoMAHj48BEAYLlcpbree+/99Pmdd949NkFRm8+TWOrAlPqbHPjidgqZsC6rimN63ioIEIUw4BK4yjaB3soAQjhZfTk3YrPZYrk8wXq9wXw+x9X1FeazGZbLFbpuj3Eci36maZ6sBe8RwcKjHzzcEDzvwcE52NpwXLNtmhiWOGvOWl6mdAIla46OfQJ+sQZIAYQAWqTKk3e9ZyTn73Sf1fe87jIPC1sut7cdFosKbRPTRCshQwQSF7dz2Iu/AeGiHVE1HomSKQC+iYDfNuGIno0ntEjFO9B+VcUWrh5nZjhizJpz7NYz/Mkf/xREhH/oL/0eqLnB1fo5+rHH6Ad0Q4/Ndo/ddg/vGHVTwcbUzba2qNsKjBCR0zPDu2DZCCe0wnc3MN558n1cPV9jNm9RLx1efv0ckiVBorO6+J4IM8k6OBFoZOzFgvjt16ufeW1APwSzQZKIhBGQ0aEyuSRiZC1cBj0+mJ7V5/jlt7Qvo99Hfl/Mo0a9OwU40Rb196n1QD7L0RepazdYzGuP6/2hOb+k91Kin94/1LgxuX9Q/N/TpevLAsm3Px8+cwK4I/pHoRYzghalFF6l1CsGpsuNgl0uddq2UK9P34TxAbK3LsKCWAGCN3+I9R729k0A+yiMSsM085TxkbalrsbfjCGsTlvcXO/RthZNYwsalmeTkyjlLRtGAINR7UeKJiSdIQ7njj1KK1UwHSJqYBZmQhzb3qJ3hLbyGMcOv/71n6KMdpjHMeerOPJzvG5urnF6Xt0324pmlX9EjC0f2iYCSd4uYg6BncKeP0L8AzUPsbgU1Y4ZWK9LFrnZbPD//g/+A/zBX/gDfPzxx3jzzTfx+eefYz6f4/vf/z4++ugjvP322wegv9uOuL7eZ9mSOXm5W2tQ14TmpArBVWwcGw7KQxIGdV/jWMqSSMIixPchx7IHsiATRWFk2Mxkk8VbDTacNNOCR+bq4L3H7e0eTWMxnx9CSrYu5f9Ey2dHeHjWB/+XuBassSCEo69NXaMymt60RSyXL3xd81lmhmOGJ8K8fYjnX/f41Z/+DKenK/zWj9/Hbvwau80tur7HbuiwHzrsNnts1zv0MS99XVUACKYymM1nsFXYVmLHcOOIYRzDCS1meMcgR/jRu7+LOZ3js5df4sMfvIOXd1/AMiFsngTAH/sgTFZ1lRSLENr3/u3dv1/X6wH6IqHLYBFU6MvyOSEOMwHzApAnAy/PeGbYI2al6ftCmBq4j2XI0+++SlIVwCci/OrlEl/cnqC1Dr3P5zEPXjl4X38XwCrZ6avL+LNcWhM/ZNnC9KRtmuXke8UbR0BCC2667UoTif+wfjpyKgnOkbhrkBRUK7RgUoJyrjfSQQKVrC0az3DkQeSysBICoQemqk6GSR2cmHrWzINwQAWzr+qwr7vdDmia49ah3Is83i5G8xrdGDR9Of4TB5Y4HpGEgY9RcmQ8ktWKKWUyCz4ABs5bbLsKlWGczh1O3n0A57oISHlEDdXY7xjX17d4/PgByOwVo1bPMnD5YIbFIjj3YVKObKvo7RCxwGR/BAUASXDRo6I6JwJSfMaAcra+Y8E1ifDLX/4SANA0TUyOssTTp09xfX2NqqpweXmJpslCua0M2qZS4IZ0FFEE0ekKSD5IxToSnmHy5CpBj+JxNzbhyJ4RIQYMsE9hKbKlEireT0xDXKy1vLgOoCgC/s1NByLCyUlwIpZjbOJX4KOi5KPXfnLrYwY7woPTXV5lijekCHvFoCBHTEzyCOclLNYfiaNgKszsQ3z2m5f4/LMv8cabj/HW++e42n+EcezgmdG7Af3QY7vtcHu3wXq9RT8MsNZiNjNgP8KgDtZaD5gYcc8PDn03wHuPyla4XD7AB49/hGFj8PlXX+Hh40v09iV2uztYScjlOfqfZVqyymI4Bfz/fwgA3wn0iegcwP8awO8hjO0/x8z/nyPP/WUA/yGA/yIz/1vx3r8A4L+OMKf/OjP/K/H+/zjefxZf/x8y8/85/vY/APBfBeAA/HeY+d9/dQOzRiLKURGqNRRaSFSv6OvRe+wZBxblifYumvvBHqgAunpfZ+c7JmAkQSNF7DPwnpM5XwD/1UCdtaHyu/79sIC/P3RWsjCOjIYn5RemyoN3c7uPCS25jGO6IDJj0BYP9VNSk2L7CEgR/PSopDmRDF9p3mJb+NCqEBzkgje/UcKEWJ6K0ZE2cjD7S6xcLQCkXseBmC8qvHyxR9c7NLU4L+UGSOAYEXjExDrGiF7iSBUEHc5jwxTsGZzpWIQWQ0FLZyOaVWj/trPwDJwvBsxqB2rmagpyT61Z4Jv9Lc7Pz/Dg4QrDOGFwOEKNhOQ4WFjo9GAnjZdSGdNy9Nil78VzXDxc6sHldbo6xfn5OT755GNsNhucn59jGAY453B5eYndbpdOKMhVNwazuaR5Len62Bqmgkby/LPS7nNHJelQtC56xNSz2Xk4mNUp/IVYKkMNFiGWfQB8k4tl2QIo45tIi5gZm80A74Gz6FwqdJvXQ97Pd8wx1HGkLU84r0e07ZB4Y3BI9KBK8gZEQdV4VLHNYddf6DODpQgNPgoVVTUH8Rl++Ysv8fLFFd774B2cPTJ4evdreDcmvuwkIqAfsdntsN3uAjhXHlVl4T2jpgoYDep5A2OBcQjBuBpbY7W6wLtPPkTll3j+zTW2my0++OAdzE4ZL9bPUBkDbw3G0cGPwdvVxFMm8vco/1LXVLn8tu+vur6rpv+vAvj3mPm/QCG25oErKxFZAP8SgH9f3fs9BGD/RwD0AP49Ivo/MfOfxkf+F8z8P52U82MA/yUAvwvgLQD/VyL6ETM7vOIqTedQkjuF8LxHBuOolp+Eh+n+SQnG95UlzlmFJpIKz8/qvajpxEmgBaLgEf2b6xUGb0HE2I3VvYzi/mvad2mreoL03z8r6t8DuqkOAf24UJOlIdR1ODUTbfXo7/e3Mc1dekw0v1RiOvYmQDdVKFC0W+33HlgcdD9z+YzAfAzLfqYJWfgmFgpdJ6uCEihxGYVdKjNEmM8rbDcjmou2HLEjliIx5Tt2yeu9EDiVMin0mdYHKKapDQxXNGtjCfvBYDcYnM5HzJuYQlbRs1griCz6zmO/3+Phwwt47g+AV4DkYD9TAZyAZkEBx2VXiCxIekSlj6liKSk7IGoBYTrVbTvDe++9h0ePHmGxmOP8/ALOOaxWK5ydneGrr77CgweX4dihumRcwtrVQv5UPM6BgnQfkt+ClJboOTupGRAQg4CJ1QYctGxLHt5kb35xbiMgpB2OgC+nN5JMPKUTNU/7/Yiuczg7b4vkOvIQx/We/Au8V60F2Bk8XG4AE3rHHBz9PIfz6YMbYzz5aJWNmRIrC3iJH6h5appJoK6X6LslfvbTX2O/7/CDH70Ps9jim5sv4XgMzoIkEe8G7LoO67sNul3IGGkri7qugzAEYFbPMWsXmM/mcH6Eq4DT2QXOV2+g8id4/vUV1ndf4PR0hR/99gdw5hbXm2cgDo6c5B0IFKK91lYpHRxp79ujux67pnj07X5S3wH0iegUwH8KwF+LhfYIAD69/jqAfxvAX1b3fgfAf8jM21jW/wPAPwPgX35Flf9ZAP8mM3cAfkNEv0IQGg4sC5N2HsTRp6hW3mc+Pwa4STJ1Pnnfy/5Y+FJOylEhQJV7TKCQz0aZr6b1ExGu9zV++uwCo1fnsTO3klLvGZHs6V/cvVdo+XsBfP33kJULYCZNGVAa2qFAcp/2H8blHmmHlfbJYS9XMpKFd8vmaQZxrMuxmCTAibaj/Qok50W4n8c7PQI5nkQgBDN/OAdNISOXFng4N4/j+EwXsBYKAEY7q7Db7VNnSh0yF8pJwxLaQ3KGSubwqNXn/VYuwsxqmBVo7Mcam77BonE4mY15GDUiM0cNtMbd3Q5VFbLPebdRfUJxPEx2lfVMc2wXqWfyQyKglOuyFJgyLeR2SVtZP5U0RgHbcRwxjuEYlLUGT548ARHw9tvvgAj4wQ++n+byww8/QKA3j3EMPMO5MZXOSjOVUcXEkiH/ek7NC20hpPkXMmAuj6OJI1zK/2UAZgM2Ymq3MYWtT2MisesFYIWmY0OPCrl957DZDFitWtSVOZAzIxXlDHrKaZQBwBN4DKb9/E4Yg3Bkbiy2aJkZvgpH+OBDmt0YSxdpz4IIRAZNc4rba4Of/vQXMIbwox9/D715gWe3X2FwwSO/iiGiRxe0+xcvbnB9s4ZzjLZtYG0VsvfBom1anK0ucLq4QFVZOO9w+fAtzOgUX33+DLe3n+P0dIXf/p3vo5p73Nx9je3+BsZmwdHGVLwV2eBng5jyWNHs34sp/++3pv89BBP8/4aI/gDA3wbwLzDzRh4gorcRwPyfQAn6fwzgbxDRAwA7AP80gP+v+v2/TUT/bLz332XmKwBvI2wRyPV5vFdcRPTPA/jnAeDB4/MDpzkAKkzjIfjqS78j370PoM8+p9kFUYq8pMudChOSzvHQVO8TgzvqMzBx7PvibgnHZqLZ3+8Zr3p0BPD5cGEqUNHllQLG8fKF40pbSqA+lD7lllHC2XHrS/n9sF3H3hEOqF9Ut8TMkFS88vGM47lPmfUiCXomAVOUzsVakBacGoPY5ZDL3CXhQjQ+eESHJVbtiP0shNLJmMhAU4wgiZgspKKMa/pxn+edKO/3UpyTg3PNyiE2W2miGZQ8yHs0VY3R11j3bQD8dkxR3BIAqykhIjhnsd3ucHq6BNGYxlf7N6BYg7HuOL5ayyU9t1o6YAGb3N8jsiNEC5WXpLlUELIAIvDJJ79BXddFGewJwzCirr89wUnXdWjnNtah2oGgkQul6fWT5gyZLpIAm0YmXDbl8yiKzmMWQcYww/tgHLdG5olTsJuUe14WxD3C8Dh43K17LBZ1SgYlQq+0jRH38ZFPEYggyWCwN1g1DouTUcthgZ4j6FPkoeL133IDbz24qkOimXzAJAguxqJtLvDs6YCf/fTnWJ0u8f0fvo3N+DWu188wujE5rvbRGbsfBtytt9jvO7D3qOsai/oUNS9gXQ1DBi03MGOLiuc4PVliuTjD+rrHr375G8wXc/z4d38Hp+ctNv0V7rYv0XEHUxmYcEo3HGONR/2ci0Ka5pVKHpU50/Nbfsw5F8KYZd5zP78ur+8C+hWAfwjAX2fmv0lE/yqA/z6A/5F65l8B8N9jZjcBs58R0b8E4P8CYA3gjwCI2Pu/BPAvxi79iwD+ZwD+ORxHsoPuMPO/BuBfA4APf/QO36fF32e6l+/6HVV2Yjay7ylZ8I6VC5SALYA/BXZtPSjqOvgP2I4VXmynx/GmwJ3Y28EzUwDOQFYC6BRIv6uwWY7ZfXvu5bgaQyoT1v0V3U/AwuEzpxcrQmyFcMkjpWcAPdpHBTLTckG4f9+taOdEmFRt9OwBTzAIoXoRo/Ux56h2Gr8EwKZ9Z2TNj0wQIEcXQR9TgMxMOOqAIMr7oUxqiwkqsE484ypG5mAlCMeovAtxBnZDg1ntsGyHtJ9MyPPmvdoPBmF9twUzY7mcwfsdAHEEzOOd2swq14FgD6n5nQ67jJBqh36K5MdiXvS6yPUyRAYJPzx54yKcnlFTa02D25sRXdfj8vIUDMkKd1yhIFTBSzvfhFhyUif1O6m/qfUl5SuhSlsxiUpAyKXlMshYGGhLDuJ6yWffj7Yn1uecx91dj6Y+5qnPSaBKFlOft5ZEsAQAHg3eubxFDkSkfVBC3IvBhwRoo8ToZw9fN0GAqBiWPSqyqKyFsTXa5hKffnKLX//qN3jyxmN8+IMnuN19hvX+OsSlQD7KKBaFbt/jbr1B348gTzipLtD6BfbjLWAcFvMZ5qcXaEyFzc0O495gvzD49NPP8fDBA/zOj38IhwHb3S2GsU/04wzAFP1o2KXQw05EognrZsSgVzRd98UsQNaNvi8zfGTqjl7fBfQ/B/A5M//N+P3fQgB9ff0lAP9mJLaHAP5pIhqZ+d9h5n8DwL8BAET0P4nlgZm/kZeJ6F8H8O+q+vSh3XcAfPmqBgpAaxOymXp+qmscx3g8whQAngWH7OxnjCnC6Mb2Tp7Pk6A1f/lNIgLqCZkCPSGYfbvRYN1X+OLu5KDdOspYvo7AWwLVQ+0+/66fK++/WsNXGsVR8M6gzFoVI6gMg8BhYJLvWn75nB4/Jj44SkbFP+UJj1zcRKpWDPfeMTp49ngbw6d43tx7eApH5mLpwSoUTe3TyHe6PWDxE1HN8VO6pwSMaW88liGvUHxG9tozA8riQdELKdsDsAyCweAsnCeczfswj5StbMXfOLRMFKLxVRa2MsG0LG1VYyRzoecoWCGKBgm65/cSSlKykgA4jGyY2pQlPxIxgTSYZvqqawsJpiTNtXaJF8+f4+zsFCcnFYboZ5MlN8YBc87yY+FlTGRKEIAwcJnotCmTAT+9q3lSenPCZ9Ld0FO17uxEQDgaUpzLudlsBhBCoKgiYp8i10Dv8Uw+u0LLBwD2QMMej843ycp0cBHg2IEdR8/3ANiOPdqqAUBoLGLY5QaVfYSf/+xLfPnFV/jwe+/jnfdP8eLuE+z6bQi44104XudcEkIG57DvOnS7ARW3mDdnsJax88/Rux7L9gSnqznOzma4PDvF2fJNfPbxFX71px/h3Xffwe/9/u/C+T3GIYzpMPTY93s434PZwSP4zwxuwOjHYPXj3FtCpmOwtlEpxpIevp8P0mTOv+36VtBn5q+J6DMi+i1m/gWA/zSAn06e+VA+E9H/FsC/y8z/Tvz+mJmfEtF7AP5zAP6T8f6bzPxVfO2fQdgKAID/I4D/PRH9zxEc+X4I4G99h3YW0u/Bb8iAPA4OVZ2/E5Vn5sWMG/wEXg32yRqgfpdgDvIbUfD+F0Fjas4X4ePltsHPni0xeFuYH0NdsW9H+nc4FkDOOAelOSfWn7SpP+tVCgSHoB1+9/lYDUTboXu0bE7t0d9fVX5hCVACmma8CSCL1lKqoRjQY01CHOepjBABJ0T5mwgYR8pKe5jRY3pUR+GSlhYDlUxNewn3I+OVsLcynmMMCBKOfeHgdEkIOCPe0gKQUUgQrUsJuiQSwmQoGEiRwypjsO2Dlk8Uk78rWhWg11AjYX6HfsBuO2BxMg9Z6NJcqM5OLHPHPovVKqxfJQPodV4ORWanPvxSbs8h8VgtMGuBT8ojqrDbhgxqj588gPO7Q+E0EmhBDtNnhF9pgS5xeVJgqwIPqcJCZMeyd2kOk/VA6sjoUZSiY5go4WA6ZiI07juPoXc4O5/lE1BxLvJcRpqLmvSoj+kJ3TmLd872sPckg9Nz6eEBSRo0qPgWDJiGsJidgnGJP/rDX+Pu9g6/+3u/hYuHwIvbT9CNewzjiH4c0Q89uqGHi9tXow8R9IZ+QIUWC3OB3XgNQx61tVhdnOPxg0tcnp3h5GSB5ckpfN/g2bMXePvtt/Dj3/1tONeH469jj37cYuQBHg6ORwzjAPFrSGGQOa5zzrMh9H9gqY6WwDQiSbANdJIEBBHiteD4LXz9u3rv/3UA/zsKnvsfAfivENF/Mzbyf/Ut7/7bcU9/APDfivv2APAvE9FfDD3CxwD+G7G8PyGi/wOCYDHGd17puS8Xg2NYzsMjeYU5mvK9cBTOpwA4iNqdMAUdz1mXUwQ1QWbg+jkiSgKABnwRNqy1+XkQ/uTZGdQRzgTMwuRiRamduuf5nQyKB6BH08909Lfjl97rPnTuSRp3ZKIldIsp93gl2kJTWiEOr/J+focVyhe8cLpuDrt1tD2hLkbh2V9YCSZ1HZShFnZCjJDK1EX2bsik89TZmJ7xzyOHx2WGOkMdah1GH0LJimCaNCnFbKLZWUKfOhZTaWbCifNE9AxHujRNMUY3gtmCrTh89ZG5m8TcSs1dANmg70L88vl8hqdPX+Dxk4eYz5uoEXEi1rT9Bk07R+Yqjn8CGbFokGqBQnLpq+ChKYIwxYJZrd30j9K24gvGtLi+vsZ8PkfTIDnrabAuxg5Z2My0mK02ubclIXqeCB0CDHSc5rSSwFEoFfrTFkJxzMwF5boLq0ohyIUIhptNj8VJg6qiXE8aG06CihyzE74qQp9c5Alvnm3Ucip5WXIgjcJOcGgM/lCDG+OIWVwsLzBsT/F3f/ZzAMAf/Cd+G9Vsgxe3zzH6oNWPXkzrYTw8QiQ87+JploExozPc9c/h0eNydobVyQkePbzE2WqJtgqJoebNQ/ydn/wp5vMZfvt3fgDnt9j3HQwxhnGL3u8w+B6Oewx+xOCDT4KPRyQlKJEWxrRl72A+fRjcxE85CoCEKBEg0Vog1e+I+PiOoM/Mf4hgwtfXUbBn5r82+f6P3/Pcf/kV9f0NAH/ju7QNCN3UgHrfFULhxrC5Psccj3UCzDEaVgbuqam+qFeBt5Qrz+m9NkA5TClwLMxzAM7nA15sajXJZS8pgeJhH/XjGfAz4h2+9+3EUZavLQeHQsexsUnCh2R9KzjWVCLJ7xxv3xEtf8KwjvbokIsdUyrVE4UuNGGQ+kH99DFBLLcZkbl7ABSTaxgQHHtY9sLe0tspEQ77tCca2LhHSjlKIdZ5XWfzsNBN0qo4O045dhhjlrV8ZCv3NTDaPMdJhvJ5b5YoHZSKgVY4h4BFkhnS5RzDmOD4ZS1w8eAcz5/f4sXzK7z9ziMQBkCLC1HuPjYvpNXxdDNUaojuWaeKZuO/xqDgEVlAjf9Ote4o9IXxsOg6xm63w5tvPob3XaKPgvr1GGrySGtI0Y7QvNQTx3NKd0cBn4XlSw9Ce/NQps7JUJVjCOFF5Zik9kegAQPr9YC6tpjNckAwKU5aIPSWsucV/0W69IRT69C0TlXHkzql8LzgvfAYR7CmwuXqLexuWnz0q19gtVrih7/9LgY8w/XmJgi43mFwI5x3cdzjaS7O7e37EXZYoOv24GrEcn6C87MVLs7PcHl+hspaVKZCVbVgX+Pubo0f/egHYNpju7uD8yMYDvthj37cYXB7DOOAYQz1EiGeXOA0loIzOuyziRZlfRVWRqExzjzw8KL4/3u2S9T1ekTki9d9Zn35zJyTHEgMe4k+RcJAJpH6plq+Fiym2wJaSDiIx69+n5bZjcC6bzC6ErzD7/cDver5EdPs9PlXg/wrhM6i3MwgSsYZfqP0TGKzKbMc3UetE6ZzCJy6jsLqAZrUCa3gHe/JPYAvNafgJ7ofGmhkSRVDzZE/lcBfAo5uQ2aMznvAhFMhhkzUAHzOkMY+pMwlgufgdS2pYbtuxMmyzpn/Yus47afmMvIeawZ8LQ+lbYhSGYlx23XOiRHs9+iGCm09wBAngS2p0iAQPPpuRLcLrktn5y1Ae1xcrvDVl89w9fIODx7OMbo9SDF3bV4/NjsKH1La4mJscxPSW5q2CmyTDkdrgUxYAZB52kGmwe3NGk1TY76oMI77Q2sacJy4oImBiue1hQxFe49dlP7NooMqj3S/JoJ0Ua7mZWU/85oLv3fdCOcZq1Wj5ln1K4GpKFJ5/13oTM/Zqhri2fwsHWkfluT7Q0qY9SFXAQ3ASfsEL79w+PSLX+HtNx7hez98jN3wFXbDJkabHOEi7ecUvrm/1oZ1xgPB+hY9vcRiMcPJfIblcoHlYh7j/BPIVCBY2IpwerrC06fP8PiNU4zjFsPQgeEx+gHedXC+h/cDnB+DtczLCYbQt5TNUuhMrbM8RRm89ZQfXRYTOknvvBrzXy/Q15fex0+BITjuoxNiDuqcPnK60IjKbYJif56ziV7v6et39Xv6ea3hO+fx0dUCn10vgLToM0EwfxsDmF5CFd8O+KXGfOzK3F+ey0fWaPLctJ0aJafOcMfad6xedUfAdtJekSOi8JzfZ8qhRXH4zuGlmeZEcEoLTWlnPBm/NE9Ti0dmqsLcPThE4/U+xOImF963NpnzBZxHFUgFCCFvPQdh0sXsmbZS+3mELEwoR6ox5S/Xe6tIjPpgT5AzGMk2VuhvMPMTrjDSY3RjjcpmHwXxNZDhXCwq9F2IGFhXBs6PqOoap6cr3Nzc4fxiBQopimLdWnDAhBseClF6WyQBmGinwgIp/9WXms38LI4oDkAURgzcSNhudzg/P0PYrZw8mNbstJ2TR1n2+6frKfIJ5DFI7TkqzOb1VQrFJdizlKMaImumUBZSvIDcFucY282A5bKBrcp9fP2szEGi38RzZT7ynJ7NeiBlwixHh2AAT6B4jn8cDPadxW6o0PMCg1/gb/2qx+h7/MNvnsJYj2cvPodtx2DNGsewbiQgUGwbxTVqCGAf+tm4JQbTAYZhjcGsadG2Laq6DqeMQGDv4NhhcGt8+L338Md/92d4+eIOq7MGo9uCvQNjhPNDkEyiABx8mHwal5KX5HmleNQ2W4XF/+nP4nMVyk8Wv29B/dce9OWzMIXK2gNv/OmlzfJT7V2DvVwiDMi70/dKL1vCi22Nnz07jfnH4xnpIqlO0RMk6f5bgRqYsoXj/ct/D+vSjEMD7f3lFlp2Udaxd6aCSR6vXN4xU/60zlKwmrbllU04aM99D3PBk6ZDkeu6ry1lkpP8iSIwB+ZGhuC8aFsqB7oyxQOAJw4Q6Rn9FpjNqqhd5THz0bTpVM5yl7ynfQH2GVsV2kcQ8Z4xOpfO+TMQaJQZbHrA36EbLtBWPSojTB/FdqMbg2/AfNFAAuCwH3B6tsDt7Rq3NxtcXDYYx30eP384vml0E0iFGmR/mhOx5PkgaBqZqkjlvIUTCIfElueSYEyD69vQzuVqBuc29zBlBnMG4gMtm7nID1D0D2W+h0MrQh4QjkLSlN51yhHOJKfaptc/qdqzsKSf26x71I1F09qDIWRVpgiSIdxupFv5n15D3uBsHsPuMoGdAZzB2APdUGHXN9gMFpvRYucJW2/hQZi1M6xm57i53WBBwH/+Lz/G5YXDs2ff4Pk3A+rGYHEOsEXS8pPw7KLmHbvLnoFdDXaEvb+Fdw6VrTCbtWiqOm0XMSGcPvADuv4O5xcPcXF5gU8//Qp/8Be/j7reYhh7WHYxwp8FwaIycR1jDEKBxPaGmPHVmEzmuBgrmSst7E4kycIPA98O+MBrA/oZOKYm96lnvXb0OwbgU2Eg+QAoLV2e894nBzS9ADXY7wbCuq/weDmm99d9jdGbtMBl0YA5RAP5TmilJ/c+4QUFE8l9OlB80v1jZZScQ7cv37vPB6F8R9d/nDiTVHzQnpLBFRq+CNJpbjBZCMdHiNW/goavHJekaWldEyD1rzEToU3UDN1wKIAmimZAsQpwPlYk5n9VjGcPHg3AFlQHxzw5+iPbBi46L4mJn5Ed94oRVcKappWQ9jNsgwmTZB/8CSRNtTUdiAZsuwa1DQ5NobBgZWEGNpsBs1mFujJpyBgelXVYLk9we7vGbB6OSYnfRxhdUs/L1DC04FQcs0szEp9ItKC14JIGNQM9RvelwG7AvsJmfY3l8gTWjBi91tYjJXnZvtN1FoXmvklDAdWsTGja9JvvH1LyVHBLPFCsCbEdrBYKs4ie+ehmLiMD0n4/Yhw9zi5mpUVg2tz4Je3f+9KiJMBPBJBh3KxnuNu1WA8W29Fi6wy2PmSghBFw5pDi13qctEssqnPcvFzjUTPgP/OPvIWqvcV2uMXZRY3VqsHNVY+XX3doThjVQhJLSZ4JDz+E1NeoGH5v4Nc11uNT9EMPQwazusHJYoa6DqlzR+9Sel/vR4x+i85c473338RP/vBn+ObrWzx+6wF4fwvnCLOK4FDBUBvX3oDBheC1noc8j4IVehCVvHmgNChw1/NfWOjUdY9nU3G9JqCvASVr9dk0mc/jH3P20wt8ek01+Gk94bfDlIhS30++ucB+tOjGOxgDvLXq8M26PQAGAgLRh7cnJvH7+nufBvPdrtwG4S6ZqO6v/5gzyRTljo/lVIrN9agyEoAfa3Gp1iRtSjLWKSFDlkMSrGi6HOIzrJy9zKvbPKGAA2k9e0aXz6VfBaSSJcmDfGg/g2OwHsYYs9+l/cA4JgwAjsG9QdV4OAbYcQxXygn09f69L0yMx69yiySkCE2mWdbvhu/WGtiKYO2IwbXwTDCUTdMEYOjDccL5oir6DQDej5jNGtzc3OL2dgdjHJbLBlUtHtvlmDNQMDgjzHCiyqaRVhpsmv/4pRDoi2nKv3EE5LQaqcJm02McHVanCzi/L5h2rkN4wkT4nBKRrDXlBKnnAmoupjSWADQ3G5NHFJDn8uV78SwhClMCJLk5zjHW6x6rVQurBdksIaihKx34MuBzjggpFVYeP+tmWYolBBQiP50QAITV7BwNTnD1/BY/PGf81X/4LayHL+E2O7R1g6qxsLVB01rMTgyeP9tic8vgGnCO4EYLP9pEw2Y+wN9ZbN1LjL4DiFA3Ficnc8znc5DJApMhD+9DqmmGR9ffYrGY4dHjh/j8sy/x+Mnvo60J4AZVNcK6AZ4d+rFD7/bYD9uQ90B8c5TMdnhSpMSw+7BKrrx/X2JBUiBfcb0moB8ureUL02JG8tidesxPwV7v4+tnju3Rh5MAMd+1KpcL5sE4mw3Y3VX41cuQX/vL2zk2vUWhdeQVWHzX852ZMiage79kl+e+lBKPjFxYgMosmbXxzAj1toC+5EjQ1Bqi69aS7LTtum9lE49wGNU3miwgaC0qte1Y7na14EBHrQ5cLMTp+1ws4FTqBKyKNkmboaV0pKA9cvpANHVApUQFopbP4MGCPOCNg4vn+z0kZapoWyIASD71w0sPU2YUE1Ospv2oPUq4U6IW/ThDWzlYw/EYXB6nrnMhcApNt6sAYyz6vkdd13j44BS3dze4vd3j9LRF3djiWU3CJgbJEYgPU6DW0cGbWsM9fOKYip8EwFQogVDj7u4K8/kMdR3DciszSfGOoSxF6Ysotz2u7yIXBRIGo/CviC+VIJ+JT4723e8IS1lgLDpJSdZPArLP871e92jbCm1rlVA7HTZO7fFpO0kBfvwt8bfIY2D88aaqhUJkcLZ4CAwVbm6u8Y+8PcNf/r0LfH37K7hxj0UzD8mBrIlle9Qzxukj4O7WYdeN8DRipAFjPYLJwYwz0F2L7XCDnd+AAVTGYHmywMnJLDv4MYNM2Hq1BHDcc/Leoeuv8e57T/D82Qt88fk3+OGP3oO1Mzg3YuYdRj+iG3ew/R2c9xiow6D0b7GuhHEphdwgJFJKE314EUREOyTdcCPg3/2YALwmoC+aTOFUx0jMngBMgVtfx/b3j2n/qQ4XmKk5ohlOr8t5j6/vZlIT1n192Ia0mo5pikf5x5/rul9yVPtywsCStlQKIgoqUts0j5Mx16BcdPUAgA/7pLX/sj2veu+eQYn8rWRYPreJo2lZMUG5z/e0N2lhPj5HFE262lNa1X/YHAjrljPIyTqeXsmAn+4zgUcDqoJHvPMxtj/leckMN54LVuXq8SqbJbUG5yPvQ0KWdOIiDlZlLeqqApkleneOumIsmi6G0lWDDMLJssH1yz32+xHtzIafkuBXYbe7C4lNKuBkWYE2wO1tVwC/9nPRQzohqCMcUJyaOP2davjarF0MTEErDGtq7HYOXdfj8eMHcL5D2oorSghtOIhFwZOPcWGwbDtC+33EpxLNl/Mka4oSBcXTR4rYpu8UL6v3svCpWhHjF+x2I5xjnJ7VxZJnPcWKZ8gJD21dmsYxUZN3dGzkd0sGpyeXWM7PsN8MuL19gX/qRyu8/16Nj579EQiM1rQgxFTPLtDqPkbD2w8duBkB7tD3HfZ9HyOwEowdgXYNjx6zusbQO9RksTxZoK4bMBCP2hEIgQZ9PFJrI49wrkM77/D222/is8++xFtvvon5yQzeBiVpdCPqsQVAGNyIvtqDxg6RWUymRElzsoYU7pRbz+X8HVwiHB7Bsul1f2L5/zhdHL2hY2QbHf3OBDX/QMufOusVxTEX/6X7PgZ28D5lTbLWHoT81e9czHRCQtGmePIdqU1RRInlHFVG1DMZkO+b50NQ1HXmz1nIwcFWhZbsp+2TssvxLbcnDgG9RMZ8j9Rv+XnSiHG8l0Xfiv6p4oLSF4OVSJ9pOi6cFqMcnylKVoCfo7spUYjL/so72os5YXEEpeI8czxLX2rcsV4XT8lX+Ry/g4Q65TLoThLitNn5kJ4yjeWOikAbEk75CH4GdV2hrk/g+Ry1HbFst7DGK1rKlzWE1WmL9XrAMORxIiJ4B/R9j5OTObwfYIiwXDaYzWrc3HToOxfqzTBYCC8C2gUFTNZ3uo+wJ59o1nN0SIy/ynvp+VxP4BsNbm83aJoGs3kF78dElIk2SZ5VUi5l2i7u58LLNkfBbTrvQQbgYq3Jf/K/3HCJ5w9NeEqYVxo4qy0A1X7ngM1mxOq0CUrNlF4w/a62laITaToih+94EVDbBpWtcLF8Arez+OKTb3DeWvyz//gHePL2gF9/8xPs9zsE2SQCPjMGN6IbenRDh13XoRt6bHc73N1ucXe9wW6zh3fBHyUMUchl7z1j7Ee0swanZ0tUVQVmhkPw1k804jnWZ+M6Z2z3V3jzrQtYa/CTn/wxnn5zBT8S6nqOpp5j1swxqxdoqhbWVClzYZjTvOaZvaJFNbsKo5TxI70bfitpniI9TXn3sev1AH1kiTOZqAqguU9LzIOmJdOp+T+/AMgWgJj1tWAwPbMPALVlnM6GgglncJF2xML/3H3X5Rz/TX8/JkhkgskMMv8m7csscapsSRmZ4+gypu9poSO1rCjrgPkVz2lhJd8/xJ5DoUODuRZSpn0RZkhSf2SiCVCjQBGGi7IQodqVeDzz0TGX9uo90cAQUm/KnowGVPmkEJTCqU8BTKbpcUO/FEilenOfRbBi1fAQtSx8rmzILw46RVN1mDfbkN4UerssWC7kci6kl13fdrEcAhmLvg+C82zewHM0lROwOKmwWNS4venQD2XGydzu3L6Mt6VUyapzYUYInsM57yPkkeeomByGIYu+Y+z3e5yengDowzqhnJzmELhDG7JIrgS8xN8lspo6nneMRmIH07ZJEn6lFGUNOgBnOZuOGIiMEx2X7IZV/YztdkBdGzS1eOvrhZi/stTPUpccj+Mj5mlK7x5bB7P6BE9O38ebZx9g2ZxhfbfGm6sKv7fc4NHDOV7cfYlh6IMsBUr5UBiMfhzQux79OGDwI3Zdh9vbDTbbLfbbLsyjAl0/MMbeod8PWMxnOD1domlqMHmMfoRjZSlGzIQZnYZEwPJ+ANke5+fnGIYB280WP//5L9DtOxiqYE2D2taoTAVDNkmGYon2LvznxmClcC5bRhLNCFawwikjdKcm8Jiu9C1Q8tqAfpLWCUcdsqaX1vKnn1/p2GfC4MsEJsB3XpnZynoeL/bIQHisbZkhH9fa75OZ/2yCwmG5VNT96vLUisd9bT0GbopJ8fFnRNMkBWYZPPnoO2WfMgiE8li1LzAcf2SfrMSKzLyD8DN9WNeQhSRhaHl7KQt2uu/ZAnLoHyBtzniW2ypKI7u4VKtsJsxCgwgmpSantcMp2HMxn5GZubw9xmrMjDUhSxwtYM2Ixm4T4zCT/sh89L3DZtPj7LyFsYT1uodnD0MVttsdmqYJgYYU4IDDMcR2VuHutsc4Tvo4maspvTIiwPl8RFHCwHqmGFxYa8Z6BmI9qjyiGrd3G1hrsDhpwDweDSWtW6KtBoqDF8+qgcrCgMZuDfbqJTWFUbApei53U0cSrWkrhKyL+KZnJK18GDz6zuHkRKURLsY4QX1BR9nClGPMl+/rdYBikAmEeX2C3XqPX//px2AGPjyzeI+f4sN338bmqsOb5x9CtiZtBHzHHt3YY9fvsen22Ox3WG+3WK+36Lse7IG2bTBv2+Aj6Biud+j7Hs55tE2Ns7NTzOezkKnSOwzRTysAtMqLkqZR1rjHMG5xcXmGYRzxwQcf4PLyAh/9+mMMwwgJNkVkgw8MTHpvHB3c6MNacyHwVhAEggOt0C8Q1p8IBOV40pQYSuy5Dy7i9XqAftLA6cDU/qqIenIP0IxEFavu3ffcMIx5Uu7BzIeLHQCtlSlA+hagnW4F/Nmvw/cyUJZM//g7WYsrgbe8L4A3LWOq5R63MiAB/mGbsmBS/jaReFWtBQqxBsHJVsrEInTQLt2+9PnQjKwtQtpSMR2zopzcvBSSU/UgfZRu82BAFatz2OVYK51P1VearjPYSwt0H5SgIBasaNoM0ckaeL9EZQZUhlBVFtbYIoCVMHTmcNxLHMGWywbj6LHfe7A32O87zGYtGGOhqQaKIcwWDWxlsb7r4b2ypt03mDIaLCVQBrr4XwgybCDW1DSu03KTdcTAOYvNZovl8gTGuMmYl3WnMovxPwLmxUuH854VN1J3cx3p6GWskCbP6L/FCirInZJVJik8HthtBzStjWmaj/EbsUxEWkF2FtUOpGIFu/eK40IwWM7PsWzPMZvPUdcWv3U64q/9U38Jb77xBD/72c/QDx3udlcwiHlMCOjHHvu+w3a/x2a3w2YXAH+73WEYRlRVhflshvmsRWNrNFWNiizgGBYGs7bB6nSJk+UcVW2T4MLsw5yoXAFaEUAc/9E7jK7HyckMbnTY7fd45923YYzBZ59+EjPtOYRMe3le079RcaRoLRYlI9BLnA+OW2xKgU3s7sjY5jF/1cCH67Vw5AMiE58A/rft38vnacx8/dux8vJCCXv81pbmfl0+EaGxHk9O9vjqbgZIHUc0hm/pYWyDlH34xDEtWwSM+56jI4kaynem2xBcPCfPHGtLFrLiPS/HusoMaaXYekSTommbDi9W3ShAjgGOke50KuVCLpj0uRwRYYCEHG5XASSyd/J943xMvgh1ajZdqkBZACJgDFsuVLm4rg8HYlrXdGxDXXqcy/eyCVgi2wHMHsbUIU4FFmgqh6YCqqpCZaxaG4ftGXqPk1UdTKQVYbGosd2OsDRgGEZcXJyG/fHUIgZzMMMzEeYnDda3HTabActllZ0FYyenYwnVP6FTSdsioZU9KB2LDE5pGjmV4AbA2gY31zsQCCfLFt73CfAOhp/vc5BVwC/FCxNP/EXTUu5i4jEQygifwrweCqv6dS1gFEs03YsWKeS57roR48g4O6+OidHFVxE+QiIZn8I8J/+Rg9fUGoo/WGNwfvIIp7NLrO82cEOP/9pf/QN8/vM/xCefMH70Wz/CdrzGN9ef4JvbTwMwGoSseY5R11VwlOt77HYdNtsd/OhR1xWapgZ5AgwFE7sBYAA/C/EGbGXRNDVmswZE2XkvnA4JQq6lKh6FVbwMnAQDbel0bgQZj3ffewO//OWv0H2yQzO3GHiLoR9yNlUiwGohucwGeUzpnF5ZGCyF/rw2Dqdser02oA8cDpIwML3nLsxfvut9ef1Zvh/bp5ffxcO51HbyO+Ez46u7GZ5tY4ALMokZf3fcPw6EuV3HAFgflSoXXWntmFKJ9DEIBCXgoyhD1w8gSawCWMFZSN2jQKyymA6J/LgwM+1vBlqpp2y+NnHnWA167/W4eHFQdwKPVHB8blInaQ9qfbusRU8RF+2mg/lElNwJiB77McXotM2FfkfqfenAMe8AVnOk+uSTlJT6GOjbwpgGTd2FM/rGpLHJVWem48ZQZ1UZiPrfthbeG7y8ugUzo5018HxXUB9F8CWE+Oir0xa31zvsK8JiUR2MU2pBaqsW2o/tq4vHfJyDgAtJF8tCEgFcY72+xmIxR12HZF2Yzntq9xEhTA1P6lv5kgy8updvqdWVy1JAc5R1xD6lr6xnn4rpAsnaDImbttuQx0HSNE+alN9TbRbrnk/Oe0c89ovxChJTYxssZ2dYzS7xzdfP8P5bj/F49wnq7gZ/8S/+RfzmNx9hfmbxJ5/9LdxsrjCbN6irOhyBG8fg5GkadP2AcRix73rst13Ym0eIBGmNRW0qzNsWVWtDCGHK42FidsvRh5Mz1tqYPdIkny1rwhE+isGWJGNlSHpl0fVhO2A2q9F1d4DxePzmCs+fvcDmeY++H9C7AbSKIpshGM45WcjQNGNyssxlAVPxj0NpSs3toeJw3/Vagf6xawrU3kvErAkrjIOrk4sIaJSWAhXlDyFQyVRgkHcGR/jli1M827Rpsf5Zwf6+yHWveiexMZreBwA+wjAONUANwCVTmzK+0Oec6z0/c0yrzt+PlTmF4mPQnPunBZJUr89MkpWAc5DFSv9LokUdjpuAStFj9VX29Y9r+dMFW7YgCwVHwISiVO8C44H10wKOllsyhlJzT0KMBnyeCAVxbuQ9Yw2qahYYHTzkKFMaPwGj1IDwfRGD8iR6I8JqNcdmPcI0DYzxSAmzmQuxFGAwGdjKYHU6w93tHpU1aFWGt9yd6J3A4Wy3nlNmIIX0YUQmyoVSVA5iuGNMhe2mxzAMuLw8TVq+j7RlYoeL/ftiDnhCuaF3SSCZPq+f0oDPnOYjj/ExK0emU0qSYhYsS3oOLRPntHH02Kx7zOcVWomRwKUcd6y9wbQfsjc6njqixd7HxhEIi/YUla3RjTuczR5it+7Ro8cHj07xTv8JfvTDD/CTn/wR/om/+ldw/k6Ln33xt3F18xy2DhYlzx7dMGDsRxAH7XwYg0l+v+/S1mK/74Gmhq0tZk2N+UkLW1swgr+B8w4MpABYzGENV3H8RdtP8SUUrxI4tsagrk7w5fOXmM9nADF2/Q3AI2w14PGbJ+h6g00PrHc9Oh8DBXkR2uhgTDWlJFqQeSwUrENHdfVjiJxpX71r/9qD/vQiEgelIwOJDHD3CQVxFlJh7GUvWxwuQiKdl/sZfn19jtGbAuTuA/xDjTrV/Mrn7+llemaqIad/OTPjw3KDqfXb6j2Q6iHvlgKOFh4O+1eC0FTjTRnYlGCiBQRdfoihQYlZEihtu5T1T+diutUwlZoP9Z1pWcVQTMb8eGm6T8fei+UOIdzu/QGE8ljo9pW/EySvaOlTEiHZ531YYWxEBFMZVNYC1EB+Ee/1Y6MiAYSIgNnc5j5Azq9XcD7srvf9DraMwxNokgQmAn3WjcFy2eDuroO1s5hKGBHs1XYaKTLRNIrICBNYauc4CUlbjp6hFre3V7C2wnq9hfOEtg2aokG5zzqdj+zECTWhR0SA2O4ULpeSXJIvpfUpUi2eYeU4l4QQNQ/SLgJHK0Au040ed7c92tZiNq/SHB5Q02TNC+CnyI8Tz/PybUJbz3GxeIxuN+Di7CHubrdgzxiefox/8q/8Pm6uHf7oj/4Iv/8XfhdfvPxT/OSjv43tdoOmqVFJWNxxhHeMcQhbQrwPypUhA+980NwdozYVTpenWMxbnCzngAkCwuhd8JRnl4Qaho9WxwySwfnTAVyBKVgl81ZL6M+sPcV2bfD110/xwYfvwvENxmEDzwPG0QHGg2mEtR5VDfR9Xi++GM+Jj9HkOrSu5jmgQkkRBTWsb/stiuI/EKA/9chnzub36TU198s9bQkAHfc0d45x29X49HaJm649qun+ea4C2A6A/N5eq0XP+W/UAI7lcNYgcYzgjgkQh209BNRpO+677jOTKlc0Nea5Dr19kIWNUnjTnsxHe1AwxKziKFyP5U0XYy5N2pr3zycCkCzcI/NXChzxGqN50fqDd0rAV22Y4M2heTDDSOHEFvsqvpjWGgWUcTtG8lYoU7580M0jyncSPRiDYfBw44j5Yo67ux3Oz9v0jLDVAFoeIVBVGLPZzMK5Cre3Hc7OWlgrwkTurByqQu5O+D0NVB54sXDE1GtJmAEAQxa7ncNut8MbbzyCsT1ub7bY7YDlqkHTHNeipk66mUhIUD6PufSXA2iTmQgfEzK4b9nJ2fgsVE1oOvbzmJMye8bdXY+6NpgvqoKwSb+v+xdv5pMRkr1R9vK56C6RweXyEZbtOayp8OXn3wB4gIuLS7jNDX50PsNP/ugP8Vf+yl/BG+8+xNfXH+Onv/qPsNvtQjuMiR7umX85F7zfx34EQGjbOiUwausGy5MFHj+6gK0MPPuw7z+OGP2YAgilpDfxX8Mm3McYVqkl1GAYZgRlLkSRJBDadgkez/GLn/8Sq9USb71zhvXuK4xuiPMRcmHobUU53inWg2yBVOuT8rQXsyA87UCpyNbofC9czh23Csr12oC+Buqj4MFKQ4wjK6Z+vSev9/CP+QjkJDuET29OMHqg9zV2rsJ+sPAw0WR0HMSOt/3V39UvEO3kW0pMa7gw5YZPytx9CKYZfAo2flTTLIH9iJo1ac+3NDkReNn2sj+57mNHxQ7rl9vFs/KU/DOZp/T7dLUpwSuQDOfbMs50FNMn7VQdPvgUL0/g3oJmDrhn7A+FKCrKP7RERLGEMuBLCTq4lZyDluNRgIc1LoK51Ku0UCpGQlkSlNhAFbp9cGqatTXu1jt0nYR5pQROqZ0UaTV24eSkhnMBqE7P2uA/wlnQ0v3ONM+5fTFTUMDB+LxYFhQJWNvi+uYWdV2jnQUt7/yixXY74uZ6j9mswsmyiRHa8sWxIsH7QtiSCQNyHycSZxjbb18nHMffs1cCvCnWg8xLkvGSkMFpsm5ve1hLODmpC6HnWH15XkXLLx34nHO5LvWmNTVm1QpffPY13n33HTx8+AAff/wJvl9/H91+xP/92uEvPVmh9zv84W/+X3h29Q122306Jjf0AwZGzoqKcFrKxaNu1toQMwEGtrJYnJzg7HyJqrYYvUM/DBj9iNE5dEMftGwCjKdMsxxi6w8jY+QRaELr+9ECFUA+WnYIaKolhv0pfvonv0DbNvidH3+AXfcMbhxiaGbEsMBhTqyxqKxBbSuMPiTRgjrmHbl5ogeWeZB079AJdURpYSS7f1pfYaVYG4SNkN3y/uu1A335PD1S5X1mgsYGItIpcaeXMMb7BIjtYPDJ7VIJGaTe/fP14e/NIlBql7rMgsmlADz5Pa09Z+DI3/PfYxyJYEz5vXQAzOWXZtHDffysIej2Hwo5pWBX/piFF8UBSXnJFmbIojnhT1FsHlMgbgtF4ZGVNkflPyhpQeakBOGiP5iAMgjcVaDGgUxOh5vLnAqGxwhHCXTQQrHc5qR1uNFhHByMIdjKwlY2HBcS06bvQMZGsGEQR7OnErS0cKn3HDlyM2aD3W6Lpmng/AAiwt1tj+bRHKSsDUGpi3vzHDzEBZSWqxq3Nz026wHLZX0ArtJXGe80p4hH9oyNQJ+1o+SPE0d+HAx22x0ePryEMQ7OBbpdrhrM5xXW6x4vX+xwcTFT+eW5aMPBfBzKlWnSjcnC07fKxZF2BWRD/00CxDSvaiFR8kDPEutmPYCZcbJsD6xf0oP0ict7ovg4reUzwycizmtgdAN24x0uLi7wi1/8ErNZi3feeRvffP0N3nzrTbSzt/ERjfj6b/1NnPBXcEPIRApm9P2IqrLwzIEeiWLwNR/So1cVmrqGJQPUwMligYuLJdpZG7X7Af04BLO+9+jHsC1gKwsf5zqd4mAXAuYMHmQAF7cNiAgGBCKLtjnBbjPDT//45zg9XeJ3fvd9DO45hiFYJWw6OcaQXUZrCBVZVLaGHUcAQ3qGiJL/kbZG6sFmyuOvrWrFRUBKa0lIxwFfdb0eoM8ZpLX2M72nzfVT5zvNPI59Tua7uP/5xd081Psdwh5+2zV9Pc39ARc4Vo9eaJmZpV+5JKrytwwCxwGpFJzKOvPvidGrOpMc66dOTfEZz4rhKueUzJteKZBlgCmbG4BdCorC2MHCmbBmJfBkjsfF30RH6dG8R3zsSlqqAGKubNKYbBZOd4cKZDlF3yMWOMvjnf7StAWHcyOXzH9+P9O0jQF4JPyuaOluDGZP58NJFDYMMiYNFak6KJ5MUZif5th7Qt/3WK1WODuvsFwavHy5Q7d3Yb88auGBHkh4GBgZ0Kw1OD1tcH3dYbsVZ0ElYMQG5fbImyYJfqCc6CaZZSK92mqG66stjAnBeJzbFCNrK4OzsxlubjvsdiOWq0YNLiI/MPdQROY7eU6FQrK4Ukxh+poFZwF+a0plg4G0Hy8SwSF9h0RIfe9wdtYiG/s4lZE0TmSaEw2fmeHiPr5LmeMYpftPpr9Fe4KKW4CQotddXl6ibVsMQ48BGzy/eYqu6/BktsRbs+fJR8pag6qpYkZHm/OdUDivX1cVmqqCd4yz1QrzxQxNW8P5Ed0wYHBDbiurXBLOh60rCv0LkfFChEg4RtcP8BXQ1DWcr+CMRU0NanuBn330EarK4oc/ehu9e45+2CaiMyYkUQuCSQh0JYtB6iKZF44aOmWhOE/Tq5SDONfFqSAlwAIpH8irrtcD9DEFJRQAXZi+JsDvY2xOo7zw5fcp4LsYlvRm3+Kb7TIhzgH4/D31o/z+7eVOWD5rTVCJ6TQtq6yoBNise5R9O7ZnXLahcGSSquMzRd/kPc2cijK04IXJ52NmUDGGRY56+DP0QtF1Kjgt26E+BF5NyeeHJg3L4KdBfhq3QQlalBdxLsMAQ3SoalwGs+Otym0DH9BJYtr/P/L+LeaWZUsTg74REZk5b/91XfbeZ5+qOlV1qru66pTbbWxLLWEjYSGBBQ8gSzxiW8JqCbX8aCzgBQkkw4st8YAMFrxYAskt9QNIhhbIwAPdElZTty53173OZe+91vqv854ZEYOHiBGXnDn/tardfmBVnrPXnH/OzLjH+MYtxqDi79gP6Y+sa200GGEPqEKVGuEGYA/nFZyPKUpFipS6RuMwagQUKdgh1NXNGgAWKqqWt5seTTMLJ2qiRO6L8VZCGD0DClCacHERHfuMwnxWk7AEqsLwxYGXgDvCTXBeLbGtCt4bPD/fY3WxhNYO1o16FOd11hlsNscK9JNpcXKmMnimORsv4AnOWAB+LMjoNN5ZuStM08kcCMOPMIT73YDlskl+EfJScjATzRyE2ciALyp9F6Vn70XFXwOVIsJydokOK9y/f0LTNHjz9hXeffcBD4+PmC8bbPdrPDy/x/F4hHMe3+5WeNXcoyUH04Rz9G3XxBgo8cQIxbVGCn/wcIMvFz3ezI9oOgMoxrHvkzrfs4cnWb9xKXofjujBgCiEGR56m0O3M2CdQ9u24OjQxwBWi7f4sz/+gOfnNW5fXaJ3d4ArcqrEdolDpfc+kRuJxpf3X1rciflDgTnZL0SYgTxPTCULXFSO7MTnnPg7nL8+G9AHcALSImWW6mcBc3nGxwQckqJxyo6fbPnMWPcNfu/uJqnVpjiyc4zWFIB/jGH4CNM28SyDuQYbWZRjMH/5qjnJ6pe0SKvaK9BLaqxUVnmGOtwTqbBkVLL2YUwFT8np2XFjBkoTBhWgToSRDv/MVVvUAClydOSw4KsYHAlI2ecMtEmiCpQ8gTUzQjARa0IdbYj+dn6Oivanvo3WbfEkM6p46HWfIsgzUnrc8pnQVgfmHkc7R6MOUIohAopS0heRNujEAxwgOB8S82gdHGkJQDfT2O8t9nuL+bIpAD+voVAeJ0kWBLStxnLZYrPuoYjQdjq1Aaid2oT/UwByCh/K4xsfCuGBezjncHW5hPP72P/iGFxoDZqGkjSnNUGSmcruKhd0+prmIhJnXx9TDJ81k5J6xMXR0InVwJxj/iDuu3JdSo/7PpyRbFstKzHNkoB7epVjyuaCOXTsopRfAD/7aj9opXExuwbZFg+Pz+i6FovLFt89/RhXt69gyOB+/R4P6zsM/ZC1XIqw9wusFgc0bYOmMzAmHPuUxGmbocHvvbsEg9A7g/vDHF8s91g2wPcuDui0tDmaGxC3OgG60bCDg7cOLqb2VTGoGhSnPamiaQtxzmbtBbbPCj/5yTf4wQ++j93hGc/PG1xctnl8uWSQMsbEtFgoYSKZmifmEYRkUsuCg6xYKqcr3ZNn5dMNLvgXvHB9HqCfQK2+gr0mq5HLyHtA5M6cT4s63MtgUavFA7H/w6crMEk0sk8D/D+PFqCW0j/2YkHIC8A9BcVTb/y6rpfbM/47A7TcKwGq9NbHqN7ynZf6U7exBDnpXz3+n8rI5LpHPBFOx7qmmknKyChbPJIoZS6RkbTH2ctWjntlZpMJIK8D4GsGtRma6vGY6sdZrqdivCqYp5jWVfoV/4fI0IyrIgoMg3drWMxxVA2UGkK0M61P1qp4p0dYTXtI8pholY9AKSIslk2w7Xeh/8E/LTKu4FSOgBrFNrVtKOfx8YDb2zm0mQbE0AcO3WOOEm1mWkN5CgoNnp8eMZ/P0TQM64pAPhWgBrAgRRhscCbLfidTG6reG7EZgSGQx6ncM5z/k3X+AhkQkMk3MpyX68AzY7+zmM2bpG6eKjjZ6Isoe+PjeeVvst+1Mpi3KyzaJY5bh6enNRbLBbqlwt32OwxDj94eoMhgf9iiP/bwLvoYAfhy/oy3qyPatoVpDTZuAXsM8NQaxtOhwU/WCzBLYK+gufhmMweB8HxU+NHbdYDZxDBRWuchI2ocd/YYBg/N8Uy+MclXoDE6aRPapsOieYPf/p0/xKtXN/j656/xs5894+mxx2LZQMUjp4oILBAvcUIIaezSXqQoRlDGFhTzJ2YnMXmOVg0wEkPGPmzJBHJyFra+Pg/QH10yCOloTwU++SolT2cdSBbGRHlAWGDbvv0npsoPbTj7ywtvFRJjVUYgkQKUL7WzVNmfr2us3p9qVyDQ6S8uTSTn6s6gfr5dI4m6fmp0X0C1LHMKMDMYY6pP6XUuMLwg2hS2XX5u3A/RXpwf+MBwxOc0hWh7VoMaBhmXcDeByLiNJ2VVDU/tpnGX4nd20ds6dkprnTz1J9urglTr/ACln3Gwt9BqQGtC+OnY6yR1jNshoFb6zgTMC2PctgrGEPb7AfNFkPalTz6OgUTNo4j4DGC/D/Ubo/D4eMD1dVdEACxGLI43okOgQgZKYWAVaRyPHsfjEV9+9RaOe5TDOjWbbasw9C6cPkBaMflZFtV8uEkcCHqZdjZl6kuvjNdwMXecYxiU98J6ybBQz0E+z73f2dTuca+iAj8Du6jwmWOKY0RAi0xA7K0wtYo0bhZvYQ+A8wqN0bi+uQSbHnfrdxjsEJPHHELochd0I0rLPBDu3C2aY4c3ncd2P8NPnlcyU9U4UB6sNOIMxnfbDm+3O7xaDQXvlbUlSilQA5Bq4KyDcxZ2Z6G0QtMCpgl+AlqFnBJGGdwsv4cf//EHWGvxSz/8Gsf+PZYXCs9PwG5rcXHZxKbkzHzsYxZMBKYeHsmErBVBeQXrXZ4/Rsx1EJkE57NPTaJ/hRDAuc+iSQoChEffh2iFf2GO7MmVbGsjO4lcpWo/bRoCrHUB8Jvpcj0DP3leVuroqauUcl8G1E+/TiXyvBDGKnb5fSwhTz2TNRnls8WTSVqU9wpJBZkQ5TEux1mIba6XC7V6BVaZoo/6NH7/pInT90dljVVlZ+hq+mFq7vLxsyxJVQdqyjZXwF3/ntcOAYMCrA5e+qOz+PU6ku8yX+N1NZIMKLdPgFfSTovjEmSPaCRtxNRSDcc7GewY7HdgrHC0M2i1rzRhOS9BDboCaiZKUH1v0c40kuEeCOl0n49oWwMl4VKrSS0IHzOsZez3Ay4uWjStwnZDeHo84vpmFhj99D5l/jC1jZO2QMpWqsXz8xZN02A+17B2n2b43EZvW4Ptto90OBL4wvxTrgsiVXQhRq+MppSScUv7KsqNiFJr6EJireoxjs3MjBSPli7BDh6Hg8PFRXPSnXP2eseuiAMg+yLb96V/RrdYzS6huMX6+R7WWnzx5VtQR/ju4T2GYUharUSzVPRLIKR4IUppfDhe4f5+nNqbq8GUrlWsTSDj+P37Fa7n9zA6eN2XK0gRwKSgKJiYlCLshwOsjadWtIrArNAog+vFK+yfNb755jv8lV//FZBeYzgeoDVhddng6eGIZTxB4hwnbjIxtZ5TvgBGPuWgVUj8JOp477hYapTGV+ZuavnJevMuZO2TT2vDsdqPHdn7PLLsFVd9nGtMPFATKoTkITqqKdOC5jzw8vluN8fRmfguMKaQou6W/8a/TV1Tz5577lN+rwFi6vs0+J8ptfjM3/N4SuNrB6XzUm7NgCR/inpPTyzyuvP5GU4bZ9yXSvP/SVfoY+4pV2Nan3o4LZjG93k85iUzET97A7YaqrMJ8D91PVR1l4wCMrMhXtBySqJ09EkpcyUrpVLn+aCIkJ4Z1jmwe8DgDAar81lx5rq/nM/XB9WyC9nbtMZ2e4CipuqraRS6zuB4sFCU97CoRNN3DlLNdtOjbTXaNnjKr1YNupnB48MB1tbx32n0LeJtXCPh6OEwAPv9DpdXKzD3aWCFD6p3QLjCmeiYVtbz6c4SOhNzuafxABV50fNClX0gDJpnH6PIZTs6s69WaepXZLhLBRpBAaThmbDdDZjNNEwzJvdczF8+ipds99EhTpgCUZ2L34VWBm8uvsLK3KLRDTabDRaLBWbdDK2eQZNJ6WNFSyPzCGTAp+KzYtSq8eAkGU/SWgIO1uDPnpYIptzAWBhSMEpBkYKhEF9fUTgRoLSKnvwEOAFljXm3xLL5En/4+3+Gt29f49XrFofjc9KnXFwYeGZsNn2FFXl9MMBUzBTlNM8VPcme/Wm/AjEHhsyLz2sDSNoA5zz6fsDhcAz/7Y/hFILz4I9I+p8l6MslC7nMe19ewc4T/msaAwJh6O2JesQz8CcPF/g4QNb3PpWAnwPr6XpKsJOFnxkZAcVafT+2K477Mf67BPlcPqeFyCijZCWCMwH441ti/xz7S4z7P5Z+pn+XvhagLEDxQhum+j3CrPRHHsuSGBWe6yclpO2Z5qnsLwDgaMCeoGYWUJzpdtHHsn9lP8a+JDJOJUtVzk/mArJ0wFwciTI5W97JWKfP8L5zDsOwA3iLwXdwLjtOyToQ5jkNV6yfyGGxmGG324NZV+CliDBfNLDWYRh86kuIFYA8lmAcjx7Wccj5XjAFq1WLtjN4ejzAWk6gXfVGxo+ExQOUarBZ70GksFrN4FyfpGUevS5/e++Tc7A45OnkBJkfnOY9swNfuVbkEnt5FQCnsKN776v1JApsWTNhL2gwaQAK+50FAZjNo8CSJOA8V4ziKB67ItJelP5T+tyQ38Bog0a3eHv5NebNBb799jscDge8ffsG+/0OP/vZN3BDbicVURxFu6pUBnqhw+G5MZrn9SxrV9aDMDv5Ivz4aYnt0UCTCul4Yz57QxqaFDRUYDZAyZFPqRAHwETG4GrxBt/85A4A8Jf+8s9ju3+fyidSMI3G1XWLx/tjmH9FcC5I2hIW2cfkWBLACEDw4RgJThwZWed8ij4YzA8xN4A86YO2zVmfwN0OLv4dwhDLKZyPwc5nB/rJ7iTxoCtiWkvxcimtUqCNIcZ2Ls0Df/K4Qu/EGpgvkTjHV8nF5b/PXSWglvfqcksAGROzEm8zgFawV2gnCv7zjGRdMwh1O2n011gjUl6lRqTarMgeuTWQnaqzKlXmyW/VX0miqlpd0wTUD3H9E+p7hQKjem6kHx6VgkSE869xtJjAh5AJjGbDCeBn1enUOjstb3yJhM8+r38UUn5K8ZnO5KuTMU1MyrhshPdDlrMNrFcYnArEKu2r8GRiIoryvB+wWMzgnMNhPwAxcqU8qzUwmxnsd0eAgxo0KHp9VGkD7IFdceRMTAeyjkXif3o6Tqo4y7Ub5lvBOY3NZofVaglSw8niKcEl2GizUzBRUM/WJ2OKMRitkdLTGsU4F2xiluZi5E+umICY1Y6n10l6P7an7x2G3mKxbCEmgCl2o3Lek2N4KRN8Xp+dmeHNxffwav41vrr5Acg1+MlPforvfe97eHh4hFIaX3/9NV69ucbj7gP2x10oP/qROOvSvAQpW8M0gfHMoj2qT6IcIbKay5IBJ/GPAAgav393CeIQCa/RDRpt0JoGmsKRU3YM8gwKKAytCG3ToGkatE2LVi1xf/eIr773JTw9gdlVNAogLFcNvGMcjy7E9rcW1tkQtx95PDkyTcxc0SZfMOVy4ockRobODueiqWNGDkE8OAz9gP7YR1+0wEDZ3qI/DOiPA166Piub/hjURc0zlv5rIMnHHpRWUCnqWnjuZ+sZfvy0hIBhDWSplFjWuEXTaH8qvdbJMXJZXNwLpOoUvGlUTUl8EN8ZMxA1mBa/pD7mOsv+cZIpk1bhjDxTlemFgMSnq0Bm9bv12NDE98yw5L5M1Sr/lkxQMWZlRbHDATSRJcKqZpb/oxzjYmqQzqpVYxjXnyNwb4IqvxVHnmKMZCqpvDdeV+LAU89RYhp8Ds8qjfMsKv0gIWTAymu4HMsww1R0LP+WbLw8ANzj6BoYdYRW9TgnxzJGWnueLdpuBmMMtrsDbmczON6nhhKA+dzgeAhA1c1MwZ+F8jbbHsZQcp4rh545EM3VqgXQ4+nxiMurDsZMRHSMn0HKDyrai8sFvMt+CuNLfARST+MaKZN3iRYrqbJH76eooPWA554UTIaAMSKQq9SGoA2gKMXWjUQiB8577Lc9ZjMDY2osLZ1RRYWcGIvEeErNoUytDK7mr/H4foO+H9C2Lb7/c9/HbDbDN998g8VijuPxiPllg/fPP8VmswlrzuW1TggR8XQEfKWLZGQyicWQxNWP5MMigRohfHdBi2S0CVj3LZ77Gb68ANgylCYorWEhEf96eFJotAMT0FBw3lNQ6MwSh21w6nz79hqH43d53VAWcpQiNI3C4TCAjIJLjKEHQaVAVonh5sIBkjOdJaCK7pn7XUYAjbQmmpKstRh6h8M+mKK0UvA+MAOIppKXrs9O0hd1cZYkxxzi6d/CHIhDByNoDL7bdvhHHy5QbuppgJsmFOGdc7/kpZ0JuEgtUy9NebOXzMy5Ok5V5JmhGMkZiRAUJYzAv1Sll7bXKa1BkmrSs7lv02Ad2jGtgUD67bQvY0an/jP1gYEcra9+OEE4YdTHqVYUMlaJd3z6DhEApwLgGx+c9orfMwEQwkUnBSYtiYiHyOr01KJSg0W5bOc8fFQHgmPecKNAZ3JDlFCVfk8ESqKzeRB2sM7AiXMmFUQstkeIdi7DYrGYYb87gKgJ6lwElSlRCAy0WBrsd33wYi7mO0itDstlm86sgyXoCSfcIApx+ttO4+npgH7wuQPVpBAAg/V6i8VijqYB4oE+JKfGciEmgCnnrTgpIyrsEeCn3RXBPGknYmH57/gvFfcpm8LkMwEPpV1brJE4/t5jvz1CK6Cd1SQ+MBPyXgFIPptpwnYpmFoED31ig/3+gDdv3uB4PGL9vMabN29weXkB6xyuble4X7/D4bhPkr0dHLwLzotNa9A0JmiZSsCP9ZU8UM38ShtORYwK8BmAD239s8cLzEyLrmkxazp0usXMdJg1Lbq2DZK90Wi0CWsPBKM0VrNr3N+tsVwu0c0B70eBbiisEyZGOwvmE8ceFhYH2+MgoX/ZhUBBMVhQOc7SWB+ZcdHOZd8KjvkFwn1rLfpjj2Gw4b/eou9DmmFnHQ6HHod9D+c8lCaYvxCpdQuuVQA//VRI7VNETlRpAuhKhUX/YdvgP7u/fEEqnmjGBPCOBcrpa8pLM4NTKenFUpFAjOS50/7VWoPz7SyZjnPtkxeDh+lYeyCEpxZi0ttlch8qnxt3+qVjhrXUWbY75U6feLe+d1ofhAFKZWampH7vdIASWZzIspPgeNDBQ79xKaxuTU6R2zDZzpJpq8c51VGIRgrZwQygIokOgbRG05oq/8KY4RwzfCL9JwZOwAdHMFtY38JzH4+kRUlY9gzlPQlEFf9yhqenNfreoWkUPLuiYkbXafS9w27b4+qqAyFIvNvtgNncwJi8jsYIkbQlKkT7YwbWzz0uL1s0TcVpQakG+72FtQNevboC8zEWVQDIeEbKfRhBKjmClcwxc1SxF9PGSBLY2JlYHiEKyWOYRMuTncGmhIEqW2j8yXnGfjfADh7LiyZJyaMVldohDJpH4SxXMrWxP9b1OPotvvjqC3zzs2/gnMXd3R0eHx/x5ZdfwsyAh+132B42yT7tXPAPMI0JwXaiSUmV9EBalMZvTANKWkNJMj4B/8iQKqWgSWHVMjrdAjoEvHEhPi2Yw9E8OAutYxhnz2hMg0W3QKsWeHz4Mb744g28r8MwV9PJMW3uU8jkN3iLwQ4gj2Aa8QwyVIxvwVQxKkdbETTC3gpzmv0XIvPuPYbjEOJYMKcTOMzhWaKwFk3UoLx0fR6gP7rKwao8KwvwT6oynzdOWIwK1nr8ww9XUWUzDfqlSv7T21X+9bGXC0pe3Kul51zWy2BZZC8bXfV7IrbK5wjco+RTKDk/4Solx6k6p56f5kDGwD6lmZAyKBHOUeWlgAzUwzz6Xil2zkbxqwk30vwQaNCAV6DWAppPikjtLvm31M7QiBLXOHEMhVQnZXnRP0haz/AcMwPRS98YHX1Xaqm16s2IaSudqCStdCjZw+gDBreC9wO0RLglBkiO3Y0lNo+21WiaBpvNDq9ezaINtMRvCkf4no44HB3mM4PdLtgo53OTGAt5trzS6o2S8HJlgA3j+fmIi8sObRP7TgBRi/XzM9q2RTdTcM5W4y2FnciW8asdwpM6ZlUThoPzl8yYpcEsikrjGAql4ptIr0Qh6RGIkvNZHs6a0WcPWMvY7QZoFZIThYBFp2Mk8yqnBDz7LGkWTGbJnIpGQivC2y/e4sP7D7i5uUbXdbB8wP32HY79PglRzoX89UqpKOE36fx52ZrAY2Sus9TcpfUkcy2PpXGsZ0dRAHxFCr/y2qE1TdKW2P4IZg6qcNZw5NE0BojRS7umw3J2gcOW0fcDXr2+RD/c4+SK7fUeUE04rnc4DrAcJHHmEA1Qa4LiOrT72McsrTHK/fUuGAEEo4SBd4OHd5IcywbVf8EsEwW/BzmB8dL1eYA+nQJ8+mlCwq+fre3+wSTg8Xq+xzeb5RlsO58U4c/V7BGB/diVpa3sPHTajszwhDpKpKnbK++WY1F+hjV1XgtxTrKf0m6I1FjfPwegkhBpXO/5saq0IQWApzZOvsej38dSXvl3Lf1U+D0CcwIBgwFYgbrsoT+ut253WVAuTCQbuZXmiqPdV4i1nKZAXttyT2yo2ijQ2A580obTMZa/RYIQWZDQw3nG4A0McuhPGn2msePgxT+bddjvDsCrVSLKJcNlGoXlqsVm00MRsN/bkCBGOIvY6Ip+lmGG46QqIixXLWg34PnpiK4zWCwCAPVHxvF4xKvX12Duk4RVjj6VGpx6WWEYHIxRWduEvMaJpL81s1Cwv6fagRLEOPweACzs88kQyQiOhHbwOB4dvGfM5hqzmT6heeMtUDvulRH4Tle6IsJqdgN3VHj/fIfXb27xva+/xPp5i/mqxTcPP8XgQkAjZz2G3gaVvlLo5i2apM6nk72SxobKVZMl/8S484S2drRuRRtCYHzYGnxxodBqght81j4JbQFBx/j7ulHomgbL7hrffLfGfD7DfKmx3fU4veLoEEMZgJXH8WhhccQwWJAiGGgQhyRBLojmiYljDkcYk++QzGncA8nhtlgfYnpJmiKZPxtyA2it0LRNyp3xMVz6PEA/0QFKn+dU8rWNudiGhfSviPC91QbfbGYIYR/HgPmfD+xzWz7+m3C6pYSfJO4JwM9l5jYz57Gppa+wwSZV8i92cWJTVhqFlxma6bKFLE0h9NjBEAVTMDHXLPfr8TiV4qb7ltsz3cqyvbmfIuER0JtQfmeRgr8XBJ4xGoOTAeGTYagkd/nJ5zVR2nuFKIjEm52mKDX9U1ZwIsOE5CGcTgc4htdBKumdwYxtlFAkwUiupBDM4HnAarXA8/MaQ8/QRp0ALgDMZhrHo8LD/QGLZZPC7o54p9R3zz6Z9VIwHIQz+atlG5Pk9Hh4OGC10tjvttBaYzFvgxq30AQld9UahyoM73uHttUV41zODUHWa7bjp/afYUIj3IEQJXwAItZW0qJn9IOH7Rkuxv+fzTSaNhB9nii8YImSU5mPMfS9z+fxC++WBLSr2RWUbfH0tMbqYokeO/TDAavrK9xv3mGwx2iHdugPPWwEv6Y1aNommpPGjSmFhghUMs4c61Y52yIRpfS1FS08KSd8/qM7g7u9wn/5FwY0xImJ8swhu5APzJUxGp1p0JkWRs3x8PAt3n7xBsy70wmSGln8DxhNRxiODKuDip+YoO0ANqF9zkfnyEIYK08wIK4T7yL2xJgZot737CtVf3hehWRAcX4kHbZpdDyCe7bpAD4X0C+uEsynJPxzV2UGADAzDl+vNvjp9qpQM/2TAfuPX6XUEv6WhU4ovTMLWeqkb9Mqf6qoTvZ3+Ji24VQyrdVv47EZMxCn759KtWdhmM+N/biPU50IjEk27aDKvFsLGLkdQSphlI5/laq0INwi4SkQ+GgAzSFL3mgeC8xFhbwfGfsEmGNsjJINR1Vfshm6DPii0k9OqJ+whGvtDKd75VHA4Bgo41JKqwJbp70IP3t0nYYxBpvNHje3LZw/TAxCcKq1NqRCTeNHafQqn8ysFs9XuaONIVxddbCWsVkPWK93uLxcATRUzERgyEaMZNp7sbccpOvlQsKwFqcmCtV8HkuaGHquPko+IAAUJeCVx+zgw+mGwUMpQjfTWDQqaRxScWd45+SbgWBqcfDpHLmEBq7GjYBld4mWl7h/eMJytYCZezzuPsB5j+1hDbE32yGonV1MXRvMSaYIQoRiAPKaOncF5ia8UjplE+o9nNpcclrxejwA/7c/0Pjr37eYt2H9EwATnfcazTDKoDMtFrMLbNcOw2Bx++oCg306uy3LfdF0hN0j4BcR2h2H8/rITLgEVwrxHRRYC8BnRpoI6XejNbwKMWNs75LPmUTeY2aYRpIRUfwePk2jP7rFPyvQnwL5kkMeXzX3VG7y8N7PX21x369wdIRpNfd/EdeplCtSq4Dcy6aF/BxQMg1l+8s6zgHty9J62abMQBQlFm2stQvjOqcKLynWNODX41CXUTrITDlxjkuvXy/Hiar7pzhdhDL2Ctw3oMYDTZ3lKkv2UsA0czJ9USImUxJcCUgCWEAg5I0JalUUgP/nXcLZIQ8Ahwh2co+IQAw02iOT1MiIRIqcJP7Yf2YGaYfFYo7tdo+bmwUIFIl47t/x6LDfDbh9Ncd2O6BpVIgbn8BJ2lU4Ko5HM/7jizUwn89wPAxQag9rLQ6HfYxHH7P/5YVVSKTlGgxhgBkMbSglVBFtWgK5iikUzUdMdpRk+jxmHJ8DyxyG784Dx4PF8egAEJpW4eKyhTH1mk4aMNkvXLJfLDsUjHzWPwTgGTvw5b4u2hXm6hJ37x+xWMzRLgkP2w/RZhy0PSHuwhF2sKE3Em1QqXLI6kaOLqEP0lKRpBURtKJgmlIKhGxOYXD0Y/Fprk9OCIGx6YH/5E8M/vrPM646H47mEaU+Nyac4Z+3F/iznzxiNuuwXGps9ocKP9IlyyN+qpbhLULWRQSAJ2/hrIrMKkfzSZDwtQkBgQiINvgoPKngkyCBkYbeRjOJBPaRI5+UAvFICmKR8E1zataZuj4r0J8C+XP3Sgm6XCiAnI8FjFb44c0zfuf97ScA/n9RmoDI2fI5MDrTmrS/zoGqEJmkzAy/0Hhv5n6RSHJcl1PXdzoSU2aIuh1jpoAT4TuvgRgzeLntSdXKk4+eSt2pz8UYCxGKD1Dxbvi9EPOdBgYTjuNVHvrloyXiUvo3y3HnpLQYvjM6RZXSLqI6NqndOavehTio1KFQ8Jkh+eglntEU+0MI5TMzGu0Qjt2VvcqJcqq2EsG5HquLqOIfuGCEQquG3mO9Ds53s3he/+npiOvrDk0RSjalzo5UuAa+PKClFoC5xXr9iNVqhfnCYLPZ4Oqqg9Z5/Gk8H8JgxL9Dng4JoIIkJGR+gfN7GcpAjJhEaGQ+KC+iEPSldzgegsOWaRRWFy2aRiUgLxnAEqhllqWtnjzA2YtctBIuqvTLJDqxAQADXTPHytziw/sHdLMOs0uDh907OHYAhyNl/XHA8dDjeOjDcWejw1pXIcY9c86omDnfkcBBMS0wx/98XF8qHD3TSgWgjuFzpe/eezjlA12U0pLNO2pevIJnj70F/p9/0uCf/z7wc1cEzznYT2MaNKYBYYEPH36Mr773Fp53RYNKGped7AQvdBOww3sVPOythWo0NMX1yShO04S+p0RVFE2QiqsARodDj34/RNt+2Gtl/A2tFdpZg7ZtogklhJKXIf2Y2vYzA31AOPPSRj/FsZU2oaA2zc5QRABFp4hXZsCbfY+7XVe+jWnQOQf8kad/AVDz30htyJe8y5moxPvyXrYXFtLWWbU4o9qLE20ZawrOmwBqYBawrh1zpq7zgC9jKXWXYHyqfagZOOlKGaDi9GjUmRa9wFRx/U9KFQtrAKdBnQNGSXPSH+PiZF6K+yXgJxrIGciJqIhPHn+TRnMOwMM+BCMRO1927CkG55OZRukrR24qvKp0OAkg/uSl1kXWXQL8UXXhnkPXRhX/do+rqwbOHQEw7MBYP/dYLJoYhCckLrHW4+npiJubWSKascZRu2swLFXtSjXYbo9wzuHycglSe+x2wVFwuTTTQHwyVCEKmwQIIiAls88++OWeymPDMUKbSMQljxSiu1kcDw4uJmuZzQ2aJsZUQFmHMCVFXyXUq9wveFJGPs0hmfRE3SzSvzwLAtqmw/XsNe7ePaFtWiyvOzzu3oUTDnGtHQ89+mOfGCAVVfoC/rJG8hrM41GOLSEybZTV3BRV+SLhK1LpKB44SNRMIaKeJNYRpsYjgKP3PhzVi6px6xX+3k9a7I8O378GrlfZ9DBrFlg/HcDscfvqAr19mpz8knFK1I0A3RDsALBGOF/PHiEmESXQZ+aUhplS2siYlpcpSfEUNRvtPJTvhnAKwlBgfhnAbNZivpzBxHFOR9Qj4L8M+Z8Z6I8ldrnCgGYOLSyoaG+xOZ41gDSApUf/D19t8HDocujE8y148ddT0JyiMPzC73UZpZPf6eNTbc3lCxPxUvkvM4yfIoULA3JabnkUcGxKOG8KOP29BCcR2Rmihi6LmbIzn6nzBKRzHYJhBAL3GmCqPPTL5oyXIo/+quZyVK9I9CHIXynZZf8OxE9rXYq2J449pgT8El1euLhqdySiKW9FKCdpEBCkMBddFxLjBWDoHZxjzBdNknVT5zg+RRbz+Qy77QFXV9dAPAmwWfdoWoX5IuTCcN5jvQ5n7a3l9L1k6kqGO5sWBPDLMW3x/PSA+XyGpmVY57FYNlg/hwQ+pjmzRkbDZq3HYmHSxFEaW5HCM4Dmnst8i29DkPqtddjvLYYhZHtrW41FdMhLe5RROBFm9XdYb6Gv6e9qU3LSLMgRvaBuDhn0JDxsLo/R6AD4j3drKKVwebvA4/4drAu+D94xhn7A0A8gUpEpCSr9EN5ZgF5CbKvUlqlLGEcgMOoKGnJ8WiudTCaaStW1B1OIZ+BYmKncRx/NNOR9VI9TzPJo8NvvG7w7EP5rv5KxomlWeP/+A5arJVarBpv9AIzWTvKnIopMFKf2N3OPft0Cah/j4jNI+aj9EsyJ6xTFdkyjwjAmmgO8Qde1YQ3FNLk5Ml94tu3aoMovTnSkRVWxntPXZwP6pWQv3zOHn585eU8RKHroU1y449C9c+Pxg6st/vB+eSKVjhFiWpr/x+pR9VepmZDfs2kiv1NLq7nuMZBOOf6VdQW1JSKhR9IyyH1xFCsXdI2eNVEuepJA5HQsceadMSBJORN1pf6eOcFBubBaW5AZFOl3/Xv2wgarAPhA9NAva8/jXjq0cfVP+cwLrKL0uZD0yt/S8R7keRAJKXgGU5IOis6fq+20+jjXScsA2VuhKK0UDBjWaxhtU0+0UdjteljL4bw45bwVHMGOhyMWixk2my2GHjBNi+fnTQqsE6YpMAHGBCaAfVDzb7YDVstmYn5FrZ0ZAOm2Io3jweNwOODLL9/A+5AWtzEKXaex2fS4vu4y81mMP5DXv2SYoyTd53opVz2eqqSZYc+wntEfHfo+zF3bKlxctCktcHWV6z32LaivayDPJ3tKDVlRbwH8IuF78SyPzxvV4Gr2CuvHA5zzePXmCo+H9+htH9dakVWQOXmfGxNi6BuxV1dAf269ZU2H+H0II6mSdE8gSZBD+Xmwyurugh656NEOxDULCsloEJgIT8EB8mbGsC6sU00a7GZ4uH/CL/zgawx+jRSZcXJnnt7TDQBvIGvOWQcVk7iBEMw6RQz9TBeKPsU25xi5DIZGA05aRWEaquA7CezTYKI6ZjJxfR6gH/soUvpYnV8yBOMrqKSkmCzNVMUT4ftXO3y7mWErxH4iIl2o+7SOU+n15Inq3VqFjyTZjcugcsWc/D3V36w6j29gHJc/imIFS5rbJcAeBZZC1RxLS0dzznd2LNXndp1jEsZ9yxJTvl+/k6R8Go1GokEZ/EomrWQoKmBO7xDABD5qQDGocUB5eiGd6/40UH/xt2oQKBX50gkURCm/PKt77vGq9KlGpDGhQroPHsRkEIky0CmPgzWYNT5FXjSacHnZYb3uk6qewRh6xjB4DDb0XNEAIsKHDw+4uFjCDoTrmxm0DgRyv7ewg8fldTCtKUW4uGjx/Nxjr2zUBsh41R2iagEDSneBqSCC831yRgOA+bzB0B+x39sowcvY5TmUyzs5UpdDVEWf0fB3OvGRX2QOWoX+6HA8OjADxigslw2MISgd2lqCt/xbAfgIuMXz/vS9+t0sLmQGgctfKMbWn73Cfh1Cvt6+vsJzf4fjsI/0J5YhJzg8A4pT8iZRNWfa+fL6JypITAR+sd8bJZoCmcXRvipSGUeKEMbE5cA0ighG6xD7X6lqHP/RncbeMf7Zrz2uVis83IXIe1fXCxz79xCHTpa6c6vTv8lZE0G9TyBoDidlQmAih7ZrqvfZM5gkgh4VzHzsl+TuAIr2ls6JxWhWg1pgQEn0zlyfB+gjb9Bz3otTwF+G6516XsoNqh3GL98847ff3aRNcF4l/cmtTu+/dJ0H0hIE63LLRfNyG+ubIqmcc6QTe9TJ5mZgKvALRttTvtcgPuXvULY311U+U5aR74kq/BySCZlAIQWPtQKZynHZfC9H8nw8kle2b7QhGWkwazKeC81KETqpr2JEKNzIzF9h142pOBWFI27aBLWfEBBZBuUa4tTr8G+5NlJTii6JupU9wzoX+JvYRqMdwA16p2FU9mnQEfg3W4vHxwGWFTwMSAXVZKM9iAzeXF7i6ekRd3ePUErB2RXaVuNw2GK77XF52QUmhgEQJ7AMucxDZj6V8+/kPo0IobMK2+0Ol1cr7LZ7eK8wmwc7qdbA8qLB+ik4pM1m5gRIKS4WLxouhUQHUj3lmkZgEPohgP0wOChNaDuNrpVjlEjSW64ndTWtGB+l++yEV6e+HdM1senzSeEC/OUqAFrd4mJ2g37D2O/3uLm9wt4/Y3/cxnnOa83a4FHumWGK1OSZ4a9pTjEppxdl5b5I8wH4s506gVg8o+clNgVzcpQTaVfGCBSTQ3HYBwmgRWNFwE+eFd5vgX/hlzv07+6wWi1hWov9/hDWLxW28oI+pDHlxI5A6Uh3XMgWmEwNzmfnQmbYwcLAAAgCnIonHGR/jUN21jSbR5+nAzt28Dx3fR6gHxe4eBOf/MzZnv8Sc1AfgTkt53Yx4M3ygHebWVX5lMSdX5+Spsu2xQ6k+uuJL8uU52sVdw3mped6jOCZnpleRHXby35NE7Qx81A6cp2Wca68MWEoQe4lJko0HvVY1Veh1c0SvhCEs9zyRMtLqmUVeDBBuje+fCq1Pzlycnm/ZEhy9VXVXH4Ug1RMnOTpBiPEZi/S5RIRdBMlrVFELgJX9uBqXMZEYzQeJHUjpqyO3faO4cgG04L26BqLw9CA4NDFsRmcRu8UeurgWkajGG0DdMaj0Q6KPBiBSXjz9gaH/YDnpzXevbvHarUAg7FcSSKcmnlqW4XVqsV+N+BwsGhbhW5m0JjieGLRS60bPD3uQES4vl5hf3BYP4dY+7NZyEXQNhrLVWAmtFbRvh8mSuAHQDg7HoumYoGVoDDECHl9H0w/baOxugjH7NIJCNlPBXM2dkKsUt6mnPYZ8JN6vpR8Kb8vSygJLoqKUQn1z9sFls01ts9HHPYHXN1cwKodtvvnzDzHMoZ+wDAETYWKgC8+JDSxoCuyWNlNiscoDWHw3NcEil76FY2m3BcgBL0JNJ/gWWzt8f1i/WqjQ6CjRBMl/oHHwA3+7/9wAD9s8d/4p7/Ern/A4GwwRynE5D2qmtvEWHDdEd05YKcBg8RkOOdBXtZNeF5pSsyKc2KaA1jLUb5MmwgZu6qbkwNZ3PmIFPl5gP7oOiftl5tKiOXHgH5c5i/fbHC3a+E5c4Gn9XxKKzMIftzTXX6bUvEXHGh5LwJQCfin5U3UclK+vFuPkxCtU2k8PVW1+7w2Yly3MElUPRvqRfrMUkXNJDCngirAF5ua2L4robyUiMqWR7GLnQYGHaR7ndXCSSsyAmpO5Y56XDEzpXajZh7qhyml1CwbmBhYkgyRBcEQFKEgPdQ8Ked7oyuNL8RpicEkjkuI0gmFCG6eIJJjowcoAnpn0FsN6xU8E7RizFuHVjsoFTz6VbHWw8o4AjxgPjdYLG6w3Rzx8PAM7z1m3Q2MaeH9AZ5ztjNShLZTaNsQbOdwsFg/9dAmSO9tm48LEgHsNdbrRyxXCyhlM9Owt9Fzv8FsZpKE//x0xPVNV50SkJERL+sw75TGylpG3zscDsGu3MRjdsYUeaSpHHdK/wqD6Tkf5RsDfBlEp8yIF2zyPjEN2bmrZCAQQTPMJwHQqsFqdgnjZ3i628B7xu3rKwy0w/P+EXJqRJjl5FAWyxKPfJrSlhJQJaGiop/l7WK5AtFzXWUb/tTaFNJGCP5XTAy2dQa74FgYGEBiZFNBogshcqRRK3z33T20XuI/+cbjV/onfP+aEeLrEhTF/iP3G8xpTvK4A2rmgHUD6KK/hQAm3VQqMBQpyl5sk7PB6VAC7dR7thAqEn0rCV41UqfzMbo+G9CfAvoTtVch8f/jXMyMzjB+cL3DHz3klLvFE9Ka0XsiBcpvXC3iaQCuN66Uk985V5Y8O6GyRm07T6WcMAVl3RNerAXg57q5em98f3zS4FSyl3drO6bUmbpA8myuq1Sr1poMGZ+sassEO74tBtlR72MPwVYDgwLNood+Ubp8qfbhuDjK8FbcqMuQooQxkScph9Utiyjvi9d0CulZ9QB1XyFzUc/3yd8nGgAK4XI9g12QslQM4ao8gTShMRZdE85NexZgmWIOi/5GwAzS8RGmGXBxOcNi8Rb3D2u8f3+PzWaON2+uYXQP53qI6lr61jQKTdPCLRnHg8N202OLAbOZQTfTaJsWu/0AawdcXb2Gc1sQQtjabqZxPDhsNkOIX94EpsE5xtNTcOxT6RB5YKD7Psbcj+0frMduO8AODNMQlksD04g0X85DPSd5BOq1MLbbW3ZZsufsRJf+x0GTk9YJn67n0laslcZqdoWOltitD3jaPmI2n+H6ao7N8IDdcZv3m6wzjkfRUrPFPEZx3WW6QtU6PZ3z0QJIizOkhNUgUU+mqvLKlfHycZMlc4dz6QRLANV4okBRcg4MZ/3zzu6aC9x/WMOzx6tXV7jfP+D3Pzi8XVkoE5xUyyaG7z6depBjjy76VpDx0MpA+QZO9fDeoykmNmjKikBSpJAVBsF10NuQoleAP2xerqiHjP+0zDaNP+PrswL9pMYiGnk1h0Eobfjj5/889Xz/ao9vN3PsBhm+lwb7lDEYg3QJpKfvZTBMvxSAOiVNnqt3iuDX73z8SpLy6J7UUQJ43aeCKIzaJ1L7KRDVdruaYSu3Y3qrLps5ES2xm0XhvSqi3GCRmgBM8L0BPIHmQ+FVCwRJeWLj8ehrBPxQZzGPE+PNUWRQJExBHq+wnpGXQsFcqNKBagJg08opBvdkZYxu1MxccFqD0bBDcFCSyzqXTroQkNTHjapmN1Vazr1ISERBql2vg7p9uXToZgavXy+xWi3xcP+In/zkW7x9+wrzxRzW7utOxOQ2WhEWC4P5XGMYPHY7i/1+QNcB280R8/kCTRNU77llwX7vXMjEd30zg1bActnAuR7Pz0dcXnZpffa9Q9873NzM4D2w2fQ49g6LeYPVSkNpYe+KPS7/jJZrgvuShylokgB+iI0/dtrLA5ApA6GKbUFUVEtomw7L7hINzbB5OuBpe4emMbi5vQJ1Hg/77zDYfqy1Dj4jzgU7vnUBuIhgYvY8OSWS9++plFpNV/yMCnwQQkx8o3U8x47EVGQTRWZorAvMpnPh2KHlkK9ektQwwh6SjHtaaWjSIeWsihn12iW2zz32uz3efHGL7fCIY7/HV68PGBygSaPRnEc4BuVxMi/OwXqHwVlYtuHUABjUWqhDC9sc437OTItSmTEPDJMCkWggAyPAimCHkDgpO0bK3JYDWRCBk+vjQu1nA/rVsRWMAWL6kk02peofl10xDwT88NUav/XtTfFMBq/xip8C2kodnUuRXyfufew6leLHEvOYI+dqAaWWxd+mF1VpTgiANP49lHlegyHtmH631AQkzVgB+GMtxyRFLfpeBr0o5eCS0EqbcsUqeOgTAuBXhU71aWKsivUwHkuu/0lFi6o0rQ0A4sAk0jdHqS2NR5RoThi5yb/O74damzPqWlSTyoSE41EegxuS1KIQiJgiiTpXqvJP15j4VzDCfrq67qLU3WO77bFYDOhmc7z+4g0e7x/x3Xchu9tyNYdz+5FmItQh95pG4eqqBajF00OPvu/RtAb7wxa6cPqTcZnNNax1eP/uGbNZmAPvQ0yA3W4fUvoC2O8HMAPrdWin94zVqkU/OBx7TtL9YjlLtvs8zXntlbVnSTaMh4TFdaLal0A6LMfrOHi46xalzwVQ0sAw3lppNLpDZ+Zgq7B93ON+f4e2bfDq9TVUy9j2T9hvdkkNLfuaGVmKHiSda/Qf0SHkq4pOfKHuYo0XtO2EpHLec4wA/iqCs0RWlPEojyQCQcMkKXs9cwLfsHcI5DMHFdZr4PBzUCtCY2YYDgoPDw+4ub1Gzxvsj1sQgH901+F7lwd4Lf4z0bzFnELsWm8xsEXvBvS2x+AiYwYP33jQtoWLKXZAyLZ8paK/Qrkdggd/yJURxt5aC9eHwEJlgKPkLIk4RtUGp2phfcyZ77MB/XR2VH2aBJ+OrnCWKqeuyhZUlHk7H/B2ecC7be3UV3/KIs4bMZSZ25Cfq1o3UnkjLQpp02mHkCXV9P7Hif3Uby9L/tOA/VJ5U+Wfvj99rDID/ZT/QE1COX9N9eRyzrcl7RkG4MMZfFIMJA/9ErTkhZE4PXmVc3/apqn2laaKsh+k8hr3Ptt+07n5omk1e1EUfIbxPL24/lqoprSRI6tA39tAsLUOKk5PQbWaqhsfuQoFJpgrMEJRiEDXzQyOB4vtdsB+Z9HNe1zdXEErhbsPD/D+GpeXCwwcgKoEVik3aCc0mFscDmtcXKwwn2s8PmzRdhrLRZMj4iGM4Xxh8NOfvMfXX38/MDEauL6qx2m1zMNyeYGa1sYvH+4+wHnG1dUSznOIyc4e3gPGhKBg1UhzDXDBfu8y4EcJn5TG3HTozAIGLWzv09EvFG3I/jyAd4A9Wjwet3DOoetavHpzC2octv0TjptdDDkuI5cLYg75263NiXQARCdHCf4UcxZUC1WOuuV/R0OU1oRI48aYZHfPS64Yj+jDYG0eF1lJpAiKARcBv/QL0DF5jajqtW5Afob7u3ssV0vomcPD9gmyTza9wrcbhV96FecESOBv2cN6h37ocbQDenvE4CwGZ+McMTwNIDIg34BVH7QjSTOSGQ+UeEOIp1ZijAEKsQX6YQDAUFrDtAZNE/5Tiqpz+olupH2Oj16fDegHqVMVdpvzIFlqBUqJ17swQePgPLmO+t4v3wanPjeRjKeU/JPaiwS8S+I+DeLjiHV1W6cGIPxTOquNpbdSu3CunPKZ88cfc9tfQLyJayR/Vv3ik/5lnodGddblTaunQyepuFnKWsmrnYtSxUPfOKDxGbOBFCI0FVe2gtI/6Z166MThqxhf1GBYsQdczj2nF+SoFJDVhXWQmI9cn0wXTueWKBB8NjpJl865IG1ZC9JBRamiA5ckRznZF6l7occEwNqgbWtbDVII4N9pHA4Ou00IFLO6ugYpwsP9I7y7wOqig/MHkI5rFXlmw9GvOT582AAAbl9dAthCmw6b7YDnpx7LVQPTpDegiDBfzPGDH/zSi0d5P3Z57/G8vgOhCcfLZKYJmM81uBb1EuDXIBcBQCl01KI1cyhuMPQeu/URfb+rQBI4L7QYozFfzNDODLwasO3v0G8OIbjNxJW1laEvISZ8BHxJ36qz5z7S43HR0/T6Khksiup3BQWjTVC9k0pPlT4NjsMa885jGGzSdiiV65I9QQCM0lFroNJ/RIBSGoYWuPvwDGMMVlcd7rffpfj2mgiNZrxeOjAHWPTsQaCkYeh9j4PtcbR91DKEdLrOeUABTB7e9Gj7JQ40YL87RqfTBkpTXFcMcPTgj9igY1IsohA5EAz0AIbjABcjIXJsgxkF3iq1fRLM6GMb/DMC/VoiL6Vy+Z5UaYW6PqkZuZbnpMzyGmsPOuPxC9fb6NSHVE5J7KZU6FlyndqoBUE42chT9nSpJxJRKpkDSm3KfQBEGjrVckyoiQvmaPqY3CfBTd0OLm26wvjk9p4Wnwlnbl9WiZ0CLPJ8ihr8jFYg1WsVeFBAYwHDVb2lX0Am1lVxqLmH6gckMZSK2T1hDPLj1dGt6Ggo+coBymFOK8A/ZSDKMfnUWTrpQVwkRCFimuLoZxEztDnrcMQAagnaGHhiaNDkWsmrDIkJAoLadr+zyQEOCAFr5gsDYwjPz0e03TNWlxcgIjw9PWOzVdAauLzs0HUhEY1UoFWH7XbAbrfDq9e3UKrHEDOcXV622O8s1s9HzBcNZjMd56Vc58B2u8VsNkff9zBG43A4wnuHi4sL7HZ7WDtgtVphswme78vlEl3XBYbDGDSzFqSATINDrA/nfJTuZCTCf6QUNAgGQUtBpOAsYHuP3eaIvt+DiNB2La5vL0GGEaLv5X6nPY3M5HtyGNweT/0B1vWFOWHEuPpMG4GYxnWwMUw5o2lNFeudBMAgNGSKnjHKjUZROArQlCVxORYntIghGo8ck8A6h8HawrdGFW1GzDkR/AIkTr+Jse5BCo1Z4flhD+ccbl9f4vlwB+uHSkHaW8K+J6y6wEhIoB/rHQY74GiP6O0QbPneBXW/C4yRQtR6tEegn8MMCxzoGd28Rdvm6JE+nohw1qUZSEKPCuGG5fy+sy6ZJ53zcNbDKpv3o4qBkbQGdIjhr2o/yMnrswH98hpL+C/Z+su/KR7RmLLvnzMX1E59ArICUqeSbQlupTZg1IMK3MYMw0vq91J6LttS/vbSVY9d+cJLKylvvtMhKqXxTHCSYJDGI/9++n0CQKq+FA56UVwOxY79AIqSy7kYNNiqGENfPOaKBwtNQ6rn/DBUbSznKxPcac1QlurrgeQS8GOY6ITs5fjJ6+nVPz/Un7CZaW8QlIr5wOERrLHRztrHs+3OBButFkCYGCwafaeQzdJFidIYXf3ctMGrvj8MaMwWF5cLKKXw9PiE/mjhHeHt22uYhmPSHoK1Gg8P91gsFlgsDKzbpPYoCmF+tSbsdhbDEOLoj5v5m7/5W/jqqy+x2+2xWq3wzTffwDmHH/7wl/Gnf/Zn8M7j53/+5/D0/Izvvv0Ov/qrv4ovv/wSIGA2n2G+WFTSLeL8prTPXuY8NC0ciXOBsNtDcFSLoNZ1La6uL6BawPojtsMD7L5PoWjHtCl9J8CLzXs89jI9jOJIaKY7w2Bhh6Bx0DpIoEHC14WUz2kJJuAfryehR0W9hCD1SuQ9yQYpKvVses3HFUWFriJzK34lUgkheNwL2Jso7YMIXbPEYWOx2+1xc3uJg1/jOByq/SjHdrcDcOt9yDWgNLxn9K7HYC2Oti/U+TEwko/mNhW0D6bTONotzH6FluYgFbMYOg+KcWSIEII1jeiT0Tr0yQPGmOi/4pN5xTsPSCwKZviILyqGkvcDw7L76Lb/rEC/BKypTfAxx746fOmppmDyHQJ+5dUav/ntDQRxRBWcFhOEoajBa8wA5Htln+p74+fGku/43fKqASj/nTfmKYWuVbTTY3Cu7TVjM352TIHG13ic6r5mMC7memQbkLPaoQ0TdXAEfK+KpDk1KjFkLidaOjneImJxQRKL/siamigjaZ5Sn7JGIhFHXZdH40LKuoqfON7+NDYgr1UZt9CawHR4FOs5SvvDYKGph+oCQfdMUAhJR8pmJYexsh4KYWl3W4vVhYKOEye972Ya+50F4MF+i8VyjqZ7i91mg+1mi2+/fcDV9QWWyyUO+z0eH+8BANfXK1i3i9ISAOakXp/NDJpGY7vt8fR0RNMQSo33MAz44z/+ExhjsFgs4rEwi91uh8Y0uHp1hf3hgJ/7/s9hv9/jWhwAGOgPHvv1AB+dzgTAS7Pi+FPmV2uNpmkwm3VQhqAMwaLHbnjAsOvh2RXvhgq5ONlBgsD5Y3L/yfcMsIXDnPPRi9xHZk+nY6Ep4mO1t0uhqd7XcRVlb32ipHbXWkOTKnYIJRrECM5zOS5BzAhISIGqvPMx3W40Pagg6SfAB9DoDq7XeH5+xMXlCmwG7PbrYmfJmIU673cK37u06B2DfEhtPNgBvRtgnYNjBwaSLwQpgHyQ4EOSIIJqAW8P6PpLwPbgwcMbhpjiJWuljxrPoPlRIU4DEVTKYWDgncfhQFCDAzec1glHnPHew1oXRy560XxEuPusQN85FxaB+jTS9rFr7LV/zoZ2Mx/werHHu42k363dWEI5dWQnKa/0tq0ZFTFRyN/jtlV/vQD4NQE4fSbWA0SCeO6a+m20cSaeGWsmpj3wTxmU8t0M2jUg57KL3ygQj1RuCmoj7woKRvs9A6qzwSt+gmk55Vrq30spPq2XRFLqELegkZGhlNJoXHb+HUAB+Hk+i9EvGhcLmjp9UQZMOXMJuGc+qnR4C09Uc03B3ODZo7cWWsXMgw3AFB0ihYHxqPaNqDUBxmJpsN1YbNYDVhdNNeRaqeAQ5zmoxXkHUIN2eYHZ4hKH3TMe7p/w/KQjEbR4+/YVlBlCVLxijCgSWqJwNny5atD3DrvtUAVA6roOq9UKf/InfxK8/5sGWmsMg8UwDDgcDlitVvjw4QMuLy7RdV0cL8Z2s4OiCJSkYEwTHbAoZaQLqn9KWhtmB472fMc9ej/As8OwD59pmQtl4SyZp3V3NvdFbVpLRUHOj3OKEeGcT8573vt0jC6MV/aZYp+TDk2tXcT9EAA+m9iSWt+YKImXr2TAlzb5MtMchSA2zuXQw0HCDolztFJotEl0VCsDhTne3z1gNuvQLghP+8fkA1CyzByZzG/WBj98tUHjG8iRusFbWGejdM/JBBHqV9CmdkI2WmPoLLzaQ/sOat8Ee39rg3MwuUyxItPMKkcaVSYfgwRC4h5FctIs1K2VgkM0KzDAHDQJ56LSltdnA/oiQZB+maqNAXdKjS+f536bKvOXbtbBqc9nwiqPjyNMlRJ+vHMG1Gn0fPp1BHjnQbcs70Ri54IYEJ20K9cxXW4t4Z8+I3WWwH/KV1Dqz7idJaBOjdG4vPr3iVMcwll7Ag0m2Adndjy01VeueI0CVJHHXzy0y5Cd4SOvtdTXIlCK/JaaJ9hf9RuZKSgaWkpZmQEo6kn1STM+wv6Xb5a8gbQtekeXNn5hqOQoEYPR2yG1uzHx2F4F9NNryWgVk+kccTyEZDpggud4Pn4IZ+RnXchcZtQA9gN2dgY1u8br1RXWj3fYbrdQpGCdB3iOpmFYe5xii9La6LrgO7Be71N7Xr9+jS+//AKz+QwXqwsMwwDvPb73va/gnMMwDHj79g2+++47fPXVl0mjQUS4fnWBq+sVPAfbr2cL5y0GdlFK9WBbRNtLMUVOx2Vq6kqpXOZoHN/h7CVrBgB7n4HVxkAzUaUfnOVUUusbY6LpJY7eJCNc7w05L08Uw9lyacePjGC9pRIT431MoDPk2ASS+8EHD8mUxrfRBm3ToNEmMCkI9bbNBe7ePUMphdX1HM+HD3DeVV3I1Yc0xJte4cdPCt+/6tNYO+eCSh8C+KUwQjG0b2ac5ITLQD1YWUC3oEEDxxbYd6BmADUOHuF0kBxtZYQAPYyc2p2IYJpwumEYLOBdTHYEaK2B4JIStTHj/T99fTagn89i/+NdY3W+fI6l/an3mBmd8vj5qw3++H4V7p9tF1efH1Odj2qLdX78vbEUXDefc7zuuOprYM2L57zwzx9pQ8lNj6XtUVuK/tSAP3ZCLMeO0nPTbRxRSinfKaA3oIaBZmT/4tGXqnJE4bluAzNy/u7K6Tu2cZLJKSuLLm0Vc3GewSwUGqn8qScrmjwBBueYsEog5GIdBUEr/Beliez8lm2T1tr4nkrhgVWlxeIEkImpiWVoDSwWDTabAd4Dx6NN5a8uWuy2Aw57i6bV0Docf7voDtgcHSxfwBgDrTRmsxmeHp/x/LTG1dUFVheXIGXhffSGBkDF+AqolIP8wx/+EADww1Vw0v3iiy/Sr3/lr/yV9P0XfuEHo/FjbA/3wG5XxMsXT20+WRZcv5yZrOrHsq312ki06SV6X9YZOUspxw4hkp2cfxd6pxShaZvkwKdNGV+2ZuRrWoDgsAeO5++jFz2ocAKkNCYq+oaouEaDp3qek8gbpKN6AvihjQptkwHfKJOOEc66Szze7TAMFq/f3mA/PMK5YXK7l86NDMaPH1t8uVonxrBObHS6p0WLwSoyBZTLC3SBwWqAb47wPaD2C2i7AnVbeOXySQwO9bvBwRHSPIAIpglmFW802AezmdIUmSEvm+jsybPy+jxAPwFG6ZFfX1Pg/bHvsvCybat+prSFOefxveUGP35cwLJOhCwXW0qHRdNHv09dXFOAM5IzYUwc6r6UBdbMeWm+eHm9FHwxj6W2DOylx3+qO+7guv91n8djMwVMZdnnyyqAuZQkrAasCTH0jQcmbJDjdlAxrIKdmSAF5kkJtz9ixk7nJg/8udlOUr5IhJ6Tmrh6kYr+5dZO8hkvTWk5AgIEAu7iEShBU4gICsGu6r0PlJrEsz8QPuc9LDyAPmh5EIK5qJgXvV6nkdFU2ZukbTWMsdjvBlxddyHkbWRsZjODoXew1uPQOzjHIRLfEnD9GuvnNV69vsXF5Rxu8Fivd3h6WuPx8Rnz+RzL5Qyz+RxEDkBm+NgztGIM/R3+4A/+EESU4tvnPT9aq0BaA+U0PDzcwyyDt7nYpcsxLeNncf1PZP4EWKb2xkidL/NL4wcpr4/EHgqR5AT2drDoj8OJNkGCwjStgWlMDMBTL6xTpjyxoWHcKAQHkqA7KmatC3MZnPTACKc9SIW1xATngpkDiAyjVyD2cfxiSmMKkrAxGk1jYHRg9kS4mrUL7DYW2+0Wr9/cYsAWgz3EsaJivsa7MPTn8aixPTq0JrisQiT8Yr5l3IlGme1keUcJPbwEsAvrjJWHnT9D9TM0xyv42R6gIQxvDBss2oUwPlFojBoEpQjOZS2AIoQ8GMzFDLx8fR6gHzdCSsc4Av7yt49dY7t9KfmW6lYJEAHE5Alg/Pj5ApZ1xRyE98pya/DO5dIIMMbShzwTVtUp6OW6xuXXdRX3ij7XEv65KzMQJ5qDdK/m+rO2pO7H6ffz7ZRjaxnA8zYL40DVu/J+SrLDBDgNWA1qLaCnAHhqvE+vkhFhRrKjTmkchJhWMRekxyWxLIA+O7rFvO06xxFP9Z+Ze8nlfpJeIT188kP8PyViHRKUFE5X4lkd+8ck55dj6FApuajCe4ejt0kCaoGYiISSDVKaFdZ56QcBtJ2GcxyO8BV7WWuCnmsw6zRO3hs8P/XY7zdxnxsc+gEKB1xed7i4fIvd9oDtbo8PHx7AzJjNZmjbJrYhjHk4dneBvu/Tf13X4eZ2BWu3yXGLWSLmOVgXMgXmqHEMswLaziAog0P5Zd6HijXlmokdT031vVzzsg+BMG4T6/90vjND611I8zoMNjs5Uo6017QmHwudpAuU563Y8xT9P0ipkHZX6XwkL67fMthOcJL1YFIgT0Gln6KjIkSq8xy1RrEMG06MNI1BY0w83ph9BhrTwQ0NHu4/4Pr6Crq12O93YR+KliOORaJCieiED+cZdweDL1ZDNRXJuVb4qolJK1laHY/RydogRfAu0DLfHeGYofsF4Ax4fszmstgf51zQgJGGsz769eicoyOOqdbZjq/UNG0or88D9DE1AXlDTd0fO+dNPSsEJxPcWhIsy/nZeoE/e76AnJV9ua1lW15+ruSkT4/Rlb9Pca1TIF7wpTT2zp+SoMuyyzHLYF4C3hRDULZ7UvOQ+id15efF0ag8WRF+4Cx6xzpKiYV9VlViMAAXHvrSsgKQk+quAP/kJ5JOyVCS2qBK0ltw/akRdDolZQ9SF7P0JmAfRwNQKAhvUdzUmimZqtHvXPxDxZiVTzAoAD6Fc+JKETRUspGmlkXQd5RjwQNISV9UJEDe+nCuGgATw7CJR7S4yrSnELL4lSFYjaGYu93DGJHx8poDghRpzAyHPeN43KBtW1hrcX9/h1evX4NMg37YQymN+arF8uIKzgaTwW67T3nTswYvgJ61Fk3T4PLyAtc3FwDtYO0cop534mznXTqrnQLdxPkTsHfew7vgtKWKYEUy39WumtCaJUYr/k5yU9WbrgJmkUSLzSBfRXvhBodhCMcDwQyKx/BMjPqmJTMg1eXIzdAmgioWM0UGWELqhiA54bvseRePBorZQ/aSg08An8P6BsdsUFT9KxWc6GxgJpvGxDP50TESBK0MNC3w3ft7zOczLC4abI8PAABFGlA+m+IgZjUuuyaTiPXR4O2yz7iSNmGtDS33KyfBTJhZYfo4SfGKKHrpA456cOcD8G8X8O0WaEJAIF+YWiQeRnV6wleNLvDvFCPG12cD+uNLBkE4x6nfxvfGwH/OW38MYKQUjBzTPykX0z+8eOW6ahDOEnWpXivrKJ+fAvD0N6dXTkB73I6sqchkalKynbiXQZ5GdZxKOFnqyUCcvO+F6KVNiMkrEVVEQjs04WYE/DENG49jBcAFUyO/JylE2pC85ClJAJ/iJV8Bvq8niaIq9cTcwtmsMrGEx0XncZqYl/GVmk2BiJpEuHUMEsNQBjBdSK0btF3ZNivHqHSM2KfiIA3OgYagGbNyhtoYyNGtrMTJY6AUQTcKQ+/QNE2czzAnijS07sDe4Olxj6enNRaLOW5fXeDuwwO22yPu7+7x+vUNdNPCuR7O7QO4KaDtGujuEpqARocInIONEpPy2O926GZzOCZs+x5GuYixUcJ3AvYSnMXB+5yEyHNO4+y9j1qa7MPAPvc1reeC4SkZz7R/C6kuPVvRFa6+ypewtnzUegWvfO/C6QZnA6iE7II6AX7OUZEBLPGRsgeKtieWLGqHVDonb6CLqIGeRSsiDoxh3fgY6IkQ1pyAXPBGz/uIXYxI6TmG1tU5DS+CJqAxCzw9bAEAN68ucByeQh/Fo53jsUyWxZ7nYUwX7nctfvF6U4e8RW5PMcoYzWjSkIU5D0+JlkwbDYqCDBGByWFo11D9DLRdAvM9rO7TGHkbTVEQ574gCHChPSyx62Oe+8BnDPpylZL8S854U/dKH4EpT/7swMT4+rLH0e7w4+dFkvhOAZ+L90tCPNWufK/kGsfP1t7ip+9Pg3luDmOqnXUbT9s5QpSqP+NyMrjXWonp5wBGDFcd+kuA2PKmkKuau6JYioDPxKA22MzqjV3PRSpLOIa4uSpWpwBbQtkfKurNbTidrkzQx97X0qTSKe6krz48RGpiLISJSOWMqk2cSt2e3B9KTleNjnZSKAw9MBw9jFHoDw5Nq0MccfZwcKDoROSDriD6NjCMMRlg2MHbYKd1LoClqH3DueNAEcX5iwhoW4XjwWGxRFpcxnRg1+D56YDN5gnMHpdXF7i+nsO6HZYXGqTm2G4OuL9/xJs3N1DKw7ljlnZxBPOAvVPYMeA5mBtmrY2R5wDvdxEYFLZHA0UerbZQKvQ1BEvKgO89p9SuLo6H0A3T6CCcg1KkNUohm7NttpzI02Vzjj7UnHtmYEPcfGE8mBGd9XyM8pYzkGpjQnz3KEGWEiNJPZQWWGoPFU+IpE0Vs1gfUS4TB7lCQ5R8J+IaAkrVP1UR+ay18bifmB5UAHySRDrAdrPDq9c3sLyD8zYG/TnpEcanaGTs5doODe4PLV4vhrMcc2XL52LeiPLYpMiLSIANAIMdkq+Oh4M1O7A/otlewnU9vIr9HoKj32I1S1o04PSY7zlftqnrLwToT0nw5zijP5/En8MqAsAPrtfYDhr3+9knSfilRB6/TT2VvxVBfypOvHp3HJa2rC++7+tXKG3qE3HhhXZNPVfeHzNJ58srmYtSIxAEGEogN818iAYgS+TwBOoNoBnU2PTKyXMnzeZUDwFJhf/yrIyvDOwTPU0KV2Eak0c3AHGAmjZVyYCMWjTRkFNNH5X0oW5q/JUScxVV+kzY7zzAhIvLFtoo7LcDDluHbqZBWkGrTPA9MRxcPiesAB8rKHPA99ZjcBa752M0I+hUd/4kOMc4Hh12u0CilFLQao71eou+D2rX5XKBrmP0dhPDAoeodre3l1iv97j78ITXb64A5eC8Td1W5NEZDg5Q8FAqLAjnAjMiknOjLRQ5HAaNzbGDVg6NDnZopQiao7+DChK8Y5cYxZQkZnDQhkHQcFFDIgRbYgaMJ1NMVcKrTU5auSaiFiIFa4ke+VXZsX9lRtFwFE8iPFJVA1EJ6zUDK3NUfpdseWVgnCBUiDo//yf3mRF8Hzgw+p4ZDZnspU+ZSRTHNkn2U0r6WhtozHD3+IjFYo5uTtge9wmIkwe+jwF+RuN9Orahsz95XuDV/Km4y6ePVSwFF/eR5lLGSikK/XUhRbBiBiEyzd6jd0eQ6+CPQK+GNI+L1RzdrM3ZNMu5msCOj4H/J4E+EV0D+N8C+FHs0r/OzP/vief+OQB/F8B/l5n/o3jv3wTw34+t+t8w878b7/8vAfy3EHIL/CGAf42ZH4noBwB+D8A/jMX+XWb+G5/SzvIad7x0wntpUEpm4CU/gaR6TsAZvvzq6yf85ncau6GBEP+Kez5x0EN6ppaG829VvcXNesJribtSD1bjQQCVyV9KhEg1jMqfviphNT3Lo8+COGFqsU59jycjkM+r1m1MT6MM2kMEwBG4N4B2oNZNSNu5npLpks1EcWDqVwjTG716Ij2Q9+WpBCevyrlqkfqTY87EhhbCBZpiCEbjOtVRjOZg3DYqfooEvN8zhp4xm0UpkIDFsgG2wHEfiLc24SiRMgStkLKZSVs9BRWtgI04zFnnsNs4/OjXfu3PndymODmHb775Bo9P97i9vYTzHtv1gLbVmC8J3ewa79894P27R9zeXqFrAeYe1g9AZH5JZbAUybIckhD21WNmLBplsR9abOwSjWqgVI+msQhu2SHdbduYKPVbDNYmgCEQbMyiJtKeSNVEWTV+MoGTZCoCWQqdizSu7D2G3sIONs0BkP1CiIJ6WRGltLgm2vDHJ5MEzEsXy7BsqDrNQQxQcTSvtOEnP4go5TtRWRfOjxKWWNorZhPpm5gDxMclZc5LQX8UGj3H8/Me3jtc3Vxhd3yM4YdF+R6cS9PxyagVCfuqGPO0x8OXh32HdxuNtytXkQAx6WU+vJQo8hwJW5S1wkjRK1WMOhniBgQbvncOHhbWOhxs0E51sxazRRfO5EdmNFF7Tk0F4bxz9/j6VEn/3wPwHzPzv0JELYDF+AEi0gD+HQD/l+LejxAA/59HAPf/mIj+z8z8+wD+DoB/m5ktEf07AP5tAP9WfPUPmfmf/sS2SV2T90qAP6fe/9TyKukMYWoJIc64OJwZrfCrr+7xW+9ew3o9Kic7ItV1SfknNZ78RZFLPjU3SPmInHRRXm1LiItUJOdzY1IgwSdetYo/MyG1937d39yPgilJknCWOs5PXfGDjWlx25g0Z9ST+kZRZtrQExRgtMkmAX/Uto+NaK4wqMSTc1HBbFTjmAT8CA5lh6rGUV15LeoVX0sGENGngIpTAsEGv4rR6o5Hh8XcAERYrlrMo5Nd3zsMB4+ePZQhNI2G1oAkTHMxPKwyBOfj2f6o/m7bBq9fv4ZSeqqxqZnj9VR2cLPZYHc4gpmx21poTZjPNZzroTXw5u0N7u+e8e2372OEvTlm8xV0AzCHM/vwDiEVjmRUC7uaWcGzgvOAVozGOGh9hPUKvVOwbh7aBw+FHvCHAIBR22GMSapY61w8ihYZN3hQimev4xSHwSp1Mi4yJIlBiL9IytZ0rh4xQcwQAEUYCQEkWZ8qxs6XyHpaa2hTZusTmKJkKweFwDpJC4bMFAQclhS5onIvAN9HwGeX4tUnwE3miELAotDnMq6Bcx7sfTj6F8fVxKh7BEKjW7heYbPe4vrmAoPfobfHpEngUhOComyhlVM0TrY+E/748Qq38w8wWuUVKPb04tWSaatKLProfXDIE0fEYbDwg8/j4QmKWxzsY/BdaDQurpaYzdtUUJ4hzjwGaublP7ekT0SXAP5FAP9qLLBHAPDx9TcB/C0A/1xx768gSOq7WNb/A8B/G8D/gpn/r8VzfxfAv/Kxtrx0nbO7lxL+S9fHGIQkjdHYzp/vKx02ybIFfu3NI37n3StkHy1ZZFMS/TSDASASyYJbhJRBVf2cd9BpOF1RxRXahOnxGBPW6WdGPIRUO7pXQNwJ4Et7pgh9tkUGUX+iCVOXJM2ZhaQ5LI0CVRsi1J5Bt2puIGnp76o7Y8DPbP5pH6rqYhuKx2WTg7PTVwm4lTkJ8R2UgH/ajnr8RwxU0SiSdVgWxcGsIEf1ENdp0yo0rcZ2PaBrNYyJzloq2NzbVgUVrQf6o0N/dDi4oPpuZyF+uFEEzwqko6SfGM6sbgeA5+c1jscDlssVNps1uq7DN998iy+++AJXV5d49+4dVqsVVquL6j3ZD0PvsVw1IcUpM/rhAKUs3nxxhePeYrs94OHhGf7OoW07LBYzzBfzkOyHCYN1OPQOgw3E1PvAqHgmzBqL1ayHIg+jGIocvLbwnnC0DfbDJYAltHLQ1EPjCGCA90PQiHgNHYHfixTrw9E5Ue/WPkKUQIkI2fwcFw8zx3C0LoGJLxL0SEIcHbPiCd0Q6T4UVTL+xbpJTqiBGTXK5LDBxdpM5hiiGD9fJ29+D2SVOrtklxdnyFLBnpiIyKQkxgCc4v/LsdEk5cvZf6XR6AU+3D2jm3Vo54Tn/TpJ9YjtkBqTcS2p+Mbr6FQ4ONgG73YLfO/iUPLgeQw/comAxj445YW+IOUMCH4vwdfCuDkGfUQ/HKAjQ9h2TZqzKaZe9rA4iWacOX99iqT/SwDeA/jfEdFfBfCfAvg3mXmbxoboawQw/6+iBv3fAfA/I6JXAPYA/mUA/5+JOv51AP/H4u9fJKK/D+AZwP+Ymf9f4xeI6N8A8G8AwO3b67MTkB3d6s9z6v+XrrIMsV2mjVluWGbczB1+7e0TfvfdFcJRr7IuKa9qAcqlJ+AnnHz11ARHJwxAJb6etH8KnKsnPjICGcTLPhT8xmgeBPjrsR+XKcAjvRGtSfYkLtt9KvFxb4IdP2bJS6CK3NcTfqT8UiDyS6zQ6RKpwfmEJ0jewXzC/ot5iDkn0aCysdL+k5qm25fGhss2FRJJejAzXjI7Kq5nYopnmcOkBolEw80Zj48HNI1G1wVvb5KjhAxoHRLmzBcG1joMg0d/CGlHSQGmCQ5jiOp+YX7L6/HxAb/zu7+LH/7yD/H8/Iz5fIanp2dYa7HdbvDTn/4Uv/Zrv4bRQAIUnKWWqwa7rYVpmsgkeQzuiN4doYzBxW2LG3qFoWfsdnus11vc3z/CGIO2bdF2LZazGczCgCjGvbcDessYrMLm0Jbom4g/g8IpABCYNTzmIJoFoFEM5gGKejTqCK0GWHuEp6guTuFbEZl1kXgjSMd1kWZTTgUkc0lYJnK8SyIgNm0DbbJUH6Y7AzaXyDW+CtrCjqGMSrbzJOlH8ClNAMIKBGbFFyccXLLli+ajrJqBdDLBpVMhYqYImeh0E5z2jNYw2sBEJ76uWWC3HWCtw5vbC2yP97DeVkJQ0ijQ2H9CGlAwxiecfmjhh90MX632WdD6ONYXdYeS5VRHYnAgcxdiJtjBYdWusB0eYnAkVZhdZKeW4nz4CEJDuMEchMSPIdmngL4B8M8A+JvM/PeI6N8D8D8E8D8pnvl3AfxbzOxGTm+/F1X3fwfABsBvAqhYfCL6H8V7/2G89Q2An2fmOyL6LwH420T068z8XL7HzP8+gH8fAH7wl77/Yj+npPZPuUotwTmmogyMUL5HRHg1P+JXXz/iH7y7Grcog3R4o3w7Sk9enkxlCgPAVDibFdL7mGmoJfsSOM+t2lNALe+X5eR7NbBPlzd9vwTnNNbx55SYRFo0BmoAYAIfg3qYuiERszHgf9o1AvCTPk33JeN48fwEXciMWs08iIYoO2/RZFXhtwK1C/F9FPJl/NLJ2JW8hahnJW+AIpXSvso6mi8Mmlah7x22Wwtmi6ZR6DoN06gYhCRIduIcNpuFMuzAOBwctk8DlCa0s6gxmJibWTfDn/7pn+Li4gJdN8N+/x1ubm7w05/+DM45/NEf/zF+/dd+HcZksiXj2bYazsrMSQCdeDzM9mDeBkBULRaXHVaXl/AuaAiOhx677Q7PT08gUmjbFrNZh9m8hTYWNOwwWA8Xs6Op6MTYNIEoSxwHQFTIgHUE6wDrFAY/A7AEaYZRPdjvAN7D+yGPczFfgQGWBCuBDngfUquKf4QEeQmSv09+Ak3boG2b2C41sW+4+HYqBFS+BbF8QpCyS5aYQBXjxyzj7pPjnWOXwF7s6WNwEufklDoWwPHQ43gcoLUKuegVwWiN1jTRZ0CFZDrcYf18j9XFApaOGFytgBaY5ALwC34a46iHmWkunyY8HkJOFQ2uzCbFzBUlFIw2y9hwihtimhDOODH9CCp/Qy2U0mBjQT4wfKYxCQsyLc/zJ8GMvGOI0CQC00vXp4D+TwD8hJn/Xvz7P0IA/fL6ZwH8H+JAvAbwLxORZea/zcz/AYD/AACI6H8ey0P8+78H4L8J4F/iSKmZ+QjgGL//p0T0hwD+EqY1BOHiDLTjq5TsP+bE9497jRid9Lf3Hm+XPY63a/zh/WXx/EcKTACYubpJGTT1rXr5RArPQH8OnE/fG98bNa2Q6kttR2xseo6L5+S3WutRlyENzkdbSsm0unx02FM+OuyNTBzx5amUxgmgKY/K6diUwHo6VvJs3c9U7Atv5BvZxis1nrAKSbospmT0ZUx08q1Tc0sN+MFpLxBzLXZZIniHJDXKZQyhMQ0W8wbOhSQ4u11IrmO0QtMFMNcSTKeYMzp6tF2Lrmuw3x+hmU/6qpTCl199CWcdNpsNDocDrq4u0fc9lssl+l4ilo3mQ/pDjNlCJcCXlKyuSHJjvcMACxx32QnMdJhftlipFcgr2MHjcOix3e7w9PQMZg+tDS6vLtB1GowewxCky/4Yj+hFJjXknQ9mEWU8tPJoNKP1kWGAAcNgcDdwbgWy70Pe9rjmS8c5Zg9rM/PvIygGyS7HnwfCGgz2eZ2C69Q0KS24qYVxOpjxu0RcFD8kIlWsnyzfc1ygMs7Bhu/SCQbH2f/A+XB8s+wzEBzcvOM4rj2YgWZmYIxBY5oQbteYlKyna+ZYP4UESfNFi+1wH9dxGD8fGZAT2jje4/F+/Qzi+GZ69Xjs8Gp+iOYGSvRqWjeYh1mkeXlejt0RUwTpbLaNuyUwP1RG4eSUupcIyWTsXY694CRpknXTjSmuj4I+M39LRD8mor/MzP8QwL8E4B+MnvnF3FH63wP4PzHz345/v2Xmd0T08wD+OwD+erz/X0dw3PuviM0/3n8D4D5qDX4JwK8A+KOP9mR0vSTdf6pD39gUMH7vU5gMAPj6Yo+Da/Cz58VZpoPjIgscsxRWlMmFR2hZR/GcLFAhuDwq6Fy3p9tUA34pqQIoFmSZk4CrZ4T419JGINwlwUrPx8afHlvL7WdGAPyjAYwDNeIcxEUYSyTOWOqsmZ+aAQqCsxAwFBOQVXK5f5Tmqryq+sqY/kJnC5CufU3CP/XcFGWzqOHL96uqR5IaUNOhPObl+iAQiBW8VTANYhQ1A4KG7R3aJgRXEUeotBYVYBTBGBOd5sLRusPegjmo+dtOozEGw+Cx31t0XYfr63k4dmc0nh6fUUSxBgC8evUK19fXaJoGu90ebdvg4eERNzc3UErh/v4OV1dXlZQvQxVlxirBTUhRK8BTRoCj9AkAve0BliOBGo1pMb+YYXW5gncK+90Rh8MBz09rtG2LxaLDcrkAyGKwx+Al7hnOhf+s9VCaw1lyo8LZ/2JfeHZo/B7b4wJGL0D9DoMd0vwKGIJDxjUfj5n5qGUQdXWVhU0rtF0T6tRTgI9qBVGx9k/XUdBUKPYgqHBKACLdZsaUqNxHUZqFeOqLp7xPgC9SvHecJNTxEpXgR0GTotE2TQR9E2JHmJBQxygD9g02m2dcXV2AqQchrGEglEPsA7/MEtmuYH5wZsOU2saKyybc7Vq8WfaVZB9YiBEmRKYt9EloT/EOx6dUDEKlFZxSGIZQtuIGzMeR4EUhzgKQzDXO+WAWSAGXHIbjAM8csyGevz7Ve/9vAvgPKXju/xGAf42I/kboBP+vP/Lu34o2/QHA/4CZH+L9/xWADsDfiYtUjub9iwD+pxQ8fRyAv8HM95/YzpOrBOxz2oBPeR8o1SyFfWyCIaikToTN8ss3a/RW4f22O1GpCSedn6fiv1h3wdln08C5jTsF8gJ84/d49K60aVzeWBMQ7pWAmDdV+L2W0LOUNiYYAKINX73Q/tgmq8CDBowNSXMgnHCWuGjqGNgJGp7jgGJfYpskjWVuN+f5Yo5n+QsmpezWSftzytDTOabi3RETNR4DjBi1Ut1PL8keUWITxocBtgRSGk1nAK9x2Hu0bYvVqkVw2nZnGVWlFZQGTKOw8A2sY/S9x25j4VyPtu1wdXmFbtaBEI5jtW0g3M569P0ApYJkorWB1oEcLZdLAMDbt29TXW/ehO99P6R71tp0pEskfMlJbwV80tnsmliP58lxcLTr7YAdtokB6JYLLC8uYQdgs9nh4eEZT08Ki+Uci8UMs1bB8wDPQ4wVEJnaIMaClOy3uP/Yg8BotAPzAl03QBFgRSOR5jy2mSiGRwaYCJqy07A464UseDXYC3koGe4XSR9REjiIJdFMAE4VTyhBVg/VK5Nje8ujecJoSVAgAfkQSyAkS5J1r3WMwhefaZomOu2ZkEXPBMDXMVtfo+d4uN9Ba4X5ssHR7mGUBsdkNYHhIMATlGKwH2t4ZRPRBIM8GsD4/X7fwfk19DivSjEu4+LTmMWwuUrlUxDMMZGWUWmuD3aLmV5i8PukBRCsEF8OO9gK8Nkz+uOAYbBg54Mm4Z+Aeh/M/P9FUOGX1yTYM/O/Ovr7Xzjz3A/P3P9bCKcA/rGuEthPwffPB/jyTrKnn0igdX3n2iOc5l9+/YjBX+Pp0BW/n9YHcFIhnUrbsnmn3NoDVyjPZpDm6v36d0IdOyBTw2mJIddV97MGoincrZmdQGFKCX1CTK3/Fg/91oKVAH6ut7RjpqYk6WSakThpYFGmzJvMCVHwVE+MQPygXHw9LmMGIm5ckdRCe8LLmZAWZYwZPZECKWeBkwano11pzEqiRSd3wMGBsJkr2IPC0Cu4wWO5XGCxmMcxdAgn1VPs0jwrioqVwiBNaFRMtkMOy+UCF5cXMKaJUlwInLPfHWMo2yN+9/d+CwCgVQP2galuGoMcR0LHpDDhvhA0a0P0vMNhj7dfXUXJ3ibgSXZlLx7tnIU5yv1P2gtkh7TwU0io4/o9jv0hgE87w+V1B+86PD/u8PT4jPWzQtd1WK7mmM8XUI2HtUfkqHJZOpbvYAUiRmsY+77FvGlhtA4R55yF9S4m8KJovw5jLJIyUYyNEEE/fFbLtwD7CeFgvP55/CmOtfFNE472UXRcqIUA0UzWAXgS8HrxQRD7dVRJDy6eVtFxzxK8cwCCSUnr4LTXdg1aY9A0TQz6E0wMzAbb7Q43t1dAkvLDkTpmhmKGi+3SHELWej7jyJc6P2IA8gF4AITeaTweWrxa9MUg5gGvbPmxPKHfIShPuC9OfHYIRxHBiGfwgaPbYma+CMdYOWh6RCjQce33/YDjvk8CBFGQ+hUR0AQTz8dw7rOJyDcG3zHgZ2/7min42AC95MxXMgJjaYgoBCWp1HAE/OjtM37zu2tsjm18DsiJccafWSUpZZ6VUJFBtWQW6s1fPyt1CPCPtQ11f6q/zrahfnfMNAhTIpuiUHWXdGkknTAD3GvAq+ShP+amk/d7xRh9cpMzzgoTwWI6yWPPjBQzm0CAKubkDFMkxC457nCRDXKcPQ8yRgIWEgo4O/Gk7igNSZPqY5Aoccar11TuflIGcHjWGINGaWhW2G8G3L6+wmqxAikV48kTGAqapD+SOU7GKgZacQ5DH7z2nWVcXV1iNpuBSMez2g7D0GO92WLoj5gtCK+/vMBx2EOrBov2AuvnHbquxfXNEr3dgAjo2jn6o8L93SOYga6bYbfdhehsIHRdB01ztI3B8+4eQOG8Vxz9Sv1GRZ7DOhlhosw1lKiiHdzg0Ns+SP9Ni26lwYrgBuBw2GO/30dzxwyr1SLY9BWD2cF7Cx8D+AAMilqi1ngchhZaddBqSMfSlFUY2EYwCGpg7zilWFWkUm71uFrq9ZOwK34ZOaaNZdlyYTAD8Ax2geYoHZLayBFAVTLPsXxGXoPlmHufA+GARNrNREl8EBJDrQgGCp4IjTZo2wZd06LRGo02cc+ELHrb9QFKKcwXLZzfxN8iLUEMCuUoa1sofsp4VYA+HhCg6GZ1fbOeRdDn0fOceEihH0nxpwBvI86onDVS/DOAGDBJE4Y+pBVuqIP3PawN64Z08LdhZjS+AQnTH/M4aK2hmzBPKgbDeun6bEB/CpBLiWr8nKjqz9nrS6bhpahh5XulCaGWEvOnUYzfePOA3/zuFrvh5eGvJNZwZ+IeMEacaS5/CvXK904Zg7od538H8niJswlOyUvgTNNPcXyFySYqxiu3mxnBfs8AdRYMn4iU/F6q1isP43Ksin06ZggKgbnutHxQ3szlsJ7YNYsCKwZMxCbkaGxFFdW4JmYt+kpoAfJCEiFCFcCEIhgT8lhIJrvSkkvMIRc5UTzvrKCURrtowOxgB586rJQBswcVBCzNB0dAYw8Fhd1+wPE4YD6b4fJiDq2baLN3cM7ieDxgs9kBysHMGM6FeTTaYNFeYb8NaWzfvL3G4LZo2yBZEllcXC4wn3+J9+/usdlsMJ/N8OrVNdpZi83zFs9PGyxXr+GjGUJsyQnQZIbyFCRJlkgmCZGZ8TmxDQeCnaRsjvHrvYsaEoNmpsBWw/ZBjb1eb7DZbIPDmdHouhaz2QxNozC4A6zrAQK0ZmhiKGI4b9AaH0EpSLJKEZwOGg/PIbyxMSGtqsTvZ+lnWotp4Z4u7PF9WXEF2It3OVzYp5pUjLQYT3aMJeGyLI6uc8WadFFjkZzUlIq5GiiBU3n+XKnwLsWTCF3bZrV+YnwJilqs1/eYL2bQKvhsJCYnbBzAj/ditukTJlJPT3TshNoRcL/v4H2JKSUzxZXWsUz0xgjmmYQjLPSO4vcwPkp5HHiDhb7Blj+AIwOrWKX92jYcfT0Yg7OwvYUjCpEVtQoMO/8FAf2x+r0GkelLpLdTEJhW5481A2PVP5A1CvJ7+a58Nhr4p754xN//9gZHWzpdlFy7SOAYbd4SzKac7agiAPWrJStbfp4Dc66eye0qGYv4qxeZSqHeRJw4WqkyAXtkuimq9YjqctnHI3mKg4c+MiM2Ho9QStmfGlgnXqt7OqGpKYchnX+NIE5pnAvAn2Qe8n2qVPqhceN2SZHBsSyGNqX6DD8B2UM9RncrNULgzPwwRtosilJ+8tYP57kvLls83R+g1SaedacYFz/0U5wr08iSSsdVvUcyCwRwjclC7IDNZofD4YC2A1hZ9DHgineA5hl26yOU0rh9dQXrd2C2xVogWLuHMS2+/v7bmJfewfoDnD9isVzg6WmNw+EAZqRELiULRuM1zogntcJalfFXDJDWSaOSCCeJsBzWv3cW5BDSBSsN1SosZsEfoj8AQx9NEUphvz/i6WldrCmgaQyurlsowzDKoXcNZo0NWp0Isk7rlGXNeZck7Qz22Ueh2i/CzcgiHNMDqsFQPlImPslfj6ByDv3QBSMvTCSlb1lbVwbWyfspaSQ8pyRAYW2plMEuMFX5t7Zp0LVtBHydGAetDIYBGIYBb97cwLo9JFFT5u2jpkHMDamd+Mg1po2nrICHws42uOjcyRMS3iLQCs79QgHwZU0UT8hoCgyy8J+mB/OAC36LvbrH0Mf9oMPJBW0IaAOwO+vgWgvnGErH8vVfIEn/pStzX4XapZTkJp4tzQFTv5d/lyr+EtxDnTG8pnCakZjNGsZvfPGI3/r2BkerUvty2+pFUsEoo6orb3xKv59qBAqu9AQIR1KAqCKL58o6S01CSVAKioLAcIg0HxqUGbFYt0gBE8wZu+ChT8YDjUttAouttGa+6j5McO4n41GOQSYZQeqQ8jL3zkBW7Y82cTlu6bckGGUiCRqZgfjkS9BOUWiDigfqRNJKTn8EkA+JX4gDAxDs4JHxEaoCjlnG4lyBqhSooeyYvES3uLhUuL9bY76YJaejUnoRjYVnD+dsTJEL9McBShH2h0OUxgj9YLFZbzEMA0wD9H0I1gNWUMpg3sww9MFX99XrG5Du4VzMPDaSKq3rQTFhjutjtDUK5jIigjEt4KlKfjWeezkFIVqbNI/xf0rnPVw704VnPQLQwzMcM8haePLBlqw5HGe80HBW47i30KbD5dUlmqbBMDgc9kdstzscjz0eH4FXr1ZojcPxEOIWKxU0MSF+vQ/haL0DeYChA5AVkeZiz9K6S/uSUWizSmag3hWJER+tRwJFJ8YmS9mkqnJkTIU5yv9JVr8cIIaj46rzwfkMCAxFCshjXYwuGOzSbdtiPuvQGJO0VRQ7pHWDp+c9mqZB0xJ6W4Nb0DDkLH4pzr787xTXq76nLyxsxKmZ8Ltth1W3OS0kCgPis1OOsYnxHMq9lASBuNeZOSTVMQqOt+DeYc63GLZrEAbM2y75NRgdxoZbEQDCeCem9yMczucB+hOgMSnhF4AxZc+vVDIjCf60qFHYzBNmAABE1Z+lW3nee8bCWPzG2zv81ndB4s+e3HU5kpzlpNvFxj41T4T6i6eLd166TiWIyacq8J8e74rwpHsBtU4ZlgKYXYyh3zjAZIc1FoAr6pt8/0w/K+G92OTlsTwpr5Qd0vtlkpRUWCFBjuav1nDkcRpL3ij8HCQ6nopAoGIyk5TIhAP4iGtQiOIaE9sShah6KqtlkcaMk9+DgF0IbapBpEFQWCwWOB4sulmHy8uLQkqOVXGw3z8/P2GwjMWiCZnpDMHaI47HPZgpnSVnZpQn7LpOo+s6LGaX2O8HHPZPuL29RtN69MMRyW48uXULVXYcrcSgk6RZlQFFWgzVUMtPCgXzI2p1SiBfTGni2QLDFFMIR1DwHDKmsUh3bROczhqFoe9xf7+HMQoXlzOsLltcXr3C89Mej4/P+PB+g1dvLkFEcF6jNZmZUaRBzCGLOiElqhHQyGCGTNNQpJAd0UP2QLA7nzIBLEdCbTDVKEVoTFQVx/6HxGK1tO99VuWnTxYpm1NcAReDCoWTMIDSMf4DA25wSSrVWqExDeazLiR4isxrMBxEv1nZ29FpjxDmIwlYIuWnY4P5qCaPJ/ZF+pbFrDGf8O16hl+8WoewxPEx8dXh6McgQkN2sswYEJ6LZyNY/HHCGpwtsoP3we8ByzD9BTztcWx6mLlC03VodRuzQSL3Ozqvej/KrjhxfR6gj7zIzwE1c05cIVcJ8mU5UxL7uJ4yUEVZb2nPl02WbVdIgM8xycqicfirX97jt797haM7nY4pJuBUygfG0mLdrxrwzzOC58oUqTeq/7RI6GNpe8wsRA0HAoyWQJkBeiT9Jw99h6+uN3g8NNj1Jm+WClwzIRp/nu1h1XdhAse95UwfuCSip/4KmZgUREIIdJmFcQrMInqlvgjok9gvVUw0EqTxIKX6CEAhTztHYk5SAoWc5lprkfsLsMxzlPtDkOR+RITLyxUeHp8xm83RNk3dVgAgxrEfsFiYGF43BKNxvoGYGKyNeeYRpL4wPAaL2QXYN3i4X6PvB1xfX2G+VDgcN5HBKdbTGfAvlbkmgtNmvcPl1Q0edu8TcxCYhwgcHE8DSBkqS16ylsb7Kk0PAWL696BwOiRw4iFkMVBlheMGaE0TwxUrHA4Wjw87LFcDmvaA5cUMbfsK79/fYb8bsOhW6O2AVrtUp8wJEJPxRPCr+EzKmguZY5LJHU/aaBzTPoxSOMfMSI3RIdRt9EkIXvthAAKwCx1AYnrkpITnkENAhJwUOCZGjBN/H7kkjLD01xiDrm2jhC/mjLwXkpZQUdxf44x50YHTF5oHnxP8nGiA8patxyr9KIiePwBg8Bo/fV7i+9c7iE9S6ZSXx7imifLdx+RWzBwYxpRhMHrxR5rQdgbeDBgOG3TDBfbPO3TGoVk0mLezEGKZKe7/bF6xzv7FsemX1xTwh0WnIuhOD8o0iH1aIp7xPWCcFrb8rS5v0TD+qS+Dc19vS6fBKcm/VrHn32tAHb2FzG1O9TxL0qFNSH8HglikwBTGIHKz2WExMELnyh63sQR7gII6f9Aphv5Xlxv84uUTjkuF335/i32vk7QhhKJkGsr2l33I41a3KY0F5/1fkcu03ykR1vOSQV1JkshishBApPPavkrF6Ij0nTQCwgRERiALsCpJOAoUvLqF0US2vUsfklkAZb018xKcsBAT6bSYz2bYrNcxMI7Ehw+x6LfRe14bE9OXRlWqiz1RAFFIu6ugAQ5R7xTNsN0csV7fo21bfPHlKyhtcTiuQUQpLW/JnOTZEkCTASOAPRzvcXN7jQ/v72HMBS4XN1jvH8AyDkCO9Z8k43JcQnEZPPLezPMdPDgYxW+yr2X9xLkebCDqop0hEOZzg6Py2G4sFkuGb3boZktcXFxgu93h1eoKD70OAWUKmiPtVFDQiqsYIXKkUf6RuS+l8fLKDHYhxDDAzsP2IVZ92zQ5k504eRZq/ZTAJtGKHHynPC0h0qaTLIDxkwBwVE/L/pPcAkaFWANiw1cqa7mqtQuuvpfAn45pSps4HxusKFC5kBJRKBjMEZ1IvxfXHz2scLvosWhyCuOovEjzN844mIuUo4zRCVERXO+Sf0M4rQN4r8HeosceGi1au4KGhiGDhnQIQ1zsfTFfOGVGJqDT67MD/RKky89SE/CpZYzfP6dBmALTE+cNUeVg2iwwNw6/8fYBv/ntDXorv0+3tVYjTwHRBLdfvV9KqPmZFBFwzBRLkBrkY2H1GJwyQ2NGYtyO9LhXYKvCcTzlgZnDV5db/OLlE4iAmfH40es7/NZ3r3B002dQy/ZyJAxlvIKpK9/nQsKsmRZJX/nSlddWBpXSL6T21J8myicSmWC/SAjFz+WaEaYg52LIrAshMw41MytvStkFgMVnVxdL3H24x+G4x2w2gx0GbHdbHPYHKANcXrZQKkRPE2Lz/NSj7RQWS5NStyrS0HqG44Hx8PgM5xyuby6xWnWwbofB9nE91cNQz4+Mc/0bgzDYA5pugdvbG9zfP+DN7BazZo7BHhNg5eQmgbsLMRYCcGYnNJ/NRjIucYzEX6KWDDlpT7xovxAkLfgQhIiZE3C2XfCP2G4t5gsNYIfFcoX1egM3HGG0gWdCo0YHCqnwOUA0+RAnNXY5NlOmwRrBCqkylikWoqZpMJt10bcjJuohlcAEzHDIUrOo88dx9YOk6VKUOJHIpW1ah4iMIWtfOLZnpE6K35Vk0VPSSiTmiwPTW9H3gmGrEvz4bN/OTKNw8pk2hTFjTLj0yyyUqrLQEiL8yeMcv/52AwBQGkA0a0ncgcSqEJJGCEAKziUZEpNJQPY6ACjRBgNd26BRA9C34P0CWCl4QzCUExFB+gDAK/1RjPvsQF8mO9vSw/1PsvnHq7Tnp01SMA213R+V+uZUzV8yG6cnDErmYq4H/PrrO/z2u1dwCXzrzfwy2Fe9qJ4RoK8WegL7WsrPDEHRPsqMTN6IKPoyHkMRy+p2pMsT2GrAEaAZ1FqQYvzizRpfLdZBsonc79z4wBC9u4EtgL+u8+WFPqUNyMzKGBTHfSj7W/4egSSZRagIBUwFeNfEq5QqTphFiBQaHQoVMumbWLNiB5e1IvfSsydrR7iJqleRUZKgMArL1QLPT2vsd3v0Qw9jCKsLA23CmnAxlatnhu3DPmgaSdqj0TQzuEHh8X6H3W6Pbtbh9etrKGMx2E2KA0CUZejxmfmKLx2NkliwB7vDYnWF7bbD5nmPy5sV2LsTyZfjuHuE43FJuvceXFVSh4FWAmjw4Zh5EY9dJHxRXYfR8xichSYFQKf+mC7kit9uBriFx2rp0HUdtusNZle3IYJcrD8T7ciQKskpEM7/Kx/aUu/LcrJrhoCT+YHjkTMO7GIMpzzrWrRtU+wHTscxowwZ8xjU3vnJhh+laUkKlJzZosQrmhfTmJTTQUcpXwBfi++KHgsV5R4sNLgsfhixvT5HBAxzFRmWSlNQU6NJ+kFUMAA8+j37TXzYzbE+7rBqXXosxWQpm16WwDkFsqTUlrUjGpDMZAQmqeuasORUD+89Ht95rM0RxgzoumCCmc01lssm+EvQxwWVzwP046DnTRiBGDihqlOagPK3KQ/gDBiZGZDnE9eP8nx+XYe0i5ATLgBxk/hAeEQiuZx5/OjtPX77XUkIasl8DNqjpVx9ngO7avh4fH+q/1k7gaL+lyTpcXTAAJIEOANYBWgfg+0AWjH+8usnvJ4fYAdOgWvE0WXROvzGmwf8zofXcFwDdVVvQSSm2lYyP+cuPtk3ocxpRpELvoCCkxhUxvcx/TpbaXxEFXbMQlIfv5rMAUwJAqffO6MV4mgiCGgPDw8Fh2Dd9ei6BtsNsD/scX09hzaBKQhH8Rz6GIzHe45MQoNu1qAxMzir8HC3w263g9Yat7fXmC8NnNuF0KEFEReHMAIAFdP/yBzJPBZMikxQZKEBMAa3w+XVCu/f3eHyaonWdPDexsHPTCtzkPKzdBqOdGXuIkppEYCAKOmzj1JxBNvIQHA8apXsxtHRz3kHTz5EgpN1E99zjrHbWGizxXK1xN2HB1zeMHpLkRGSpZAl1NK/I5kBuKY71SKKXzlK9xL7nlNfVUwOpEFtkLh93BQx10sIvRujxora3MY8A8Ichm4xrITYLaTuclkTBbqntYpx9XOwn6C9iMF6klkhr/ekbQBizIhRVtPEfMgRPV+ptwVLK/h+aV8WUn0JwNXwUlh7f3B/gd94c18Jfbn8stKcVY+Ugoo2d6UIlrlQ0wddo9Ea3ASbv6S8bmcGFyvCogmOt+yBRrcYeo+nhx4Pd0fMFwarixaLxcuw/nmAfinNFARaOK+xjT9L2GHyy6N8cpUgm++dmgnOaRLkXql5mFKLJ1+D4gz3RTvg198+4HffXcOzqkAq27JfBrXp34WMnErftXNgaSePEitzdf8lwJe+VW1ggK0GOR0k+86Gw9FgNJrxo7ePuOxCqlGxb3FMMkKRSFwtGH/1qyf85rfXEwxRyeR8hNUdPVcyRokBEtLLozKLvcyMZDOWFKFZxV5wDomLLwco/1YROKnwBaZEJpkQgvd4ikMZ6xftAiaHglG2Rgh4AHwPYgeikP5zdTHH06PFYC0YhONxCJnlHENrQteGlLvBHtvBO4PH+x02my20Vri+vsJy1QI0wNpNQawJEkRFnI48GDr2vQT80/GKfUT2a/HeYzYPgVy2mz0ubxY49huI6UFot3h6l0fMSgBRsex0qgHIwV8osCbi5Hni5xO1B4QAnHL5mLjG9QQ3MEzH8J6wXR9xe7OCUgqH3Q7tvIXz26whKuY6tIlTzAZHFDSBPjAtEteg2pMESGx5YXKIKDGVoNDhQE88BudSfHgDAyKCs4yh96DWJyleTBeMcp9mb3QJuyvPA0gSvti6xbtdNGUAkikkmGVKxi/Pv5jbSuOGmBrSPhUmLLFO01e1rydofZ5c1I0oNtTTocPvfbjEL109oWtKHy4xk9YYIaYSIDjtDf0AZx10E50XGSDH0I0GGcCTB5jQRDOIMRrd3IBAMEphseigiGCtx+HgsHke8P67/WQI9PL6PEA/Xsyc8h2XTnTnVPlEiM4mDG3UiDkQSbYuZ0pTMGYoxs+UZdT3UamzEjdIwM1swI/e3OEffMjOfZ+i1n5Jgj3VBsg7PknhkX4hbcpC7TUFlB+tlwlsFXgIkgO1FtB5y75d7vFLN2u0mmMUN07Elj2nYy/CxF20A3709hG/9d1t7tWfg/koGYSPtf+cRqS8KjU6i2STfj3DfxSUpHxHCB0HN71c/ohJi9RQxoVYpTLCp8pPC+ghEs14qwKtYLGNUQAV4hkvNA2wumjx8LADgWGaYJ9uG0nwAhBpNGaBzXrA/f0HEBFubi6xupiB0Sewl/6VUjWQQZc9g88kB8twy8k+mp2kgsXb+QGXlxd4fHzExeUCpDS8G+IZ5hyT/9SOXwQ1gqiedVTPI+VYYERnRa6lPyq8+IXBd94nk4tSCnxUYHjozgMh1hRcz9hu95jPO+y2W8yXrzH4XWTmwmTqaK8VNbUiSsBIJN7+IkUiHCMrgL8UAEJ+dp2mwDNjKJIXecfBc1/2tyIMfZDiTWRqk2pf+hrnIRzRyw5qkhjGex8z41FiOKjciAKMiVmtNVuZ9w19Eq1A3jqcPhPMy3pPjFfJOcRlV4v25xYdQKN3ZT8XTMCH7RxP+wZ/7at7zLuiAcWLJc0vMwwm59dYLHlAaY2GNJwiUEPwvYcmhUY32dkSUTvjPZhCjIn5wmC5bOA9Y/2c53Xq+qxAfwzOH3tWbJPh/Gh9BK90tgNqIjl+Zvx7OcnjEL7CBJSR++R+iDgWOF2lFG6XwD/TBIl/OzRnpNgJKXKyv2UbqhalvpQbogT8rL56eUwrcQwIQG9DYBG0IWY+x4191R3wc6tnXLR9sB1GR5iQSxrZNg4Z59Cmo1X4w/vLqh/npnqkBZwci/xbCazlZqST9+p6g9R6cnCB6PzMVOpP8UimqvZgw41moQnWvVoLFGzjAKXjZWWJZRsE/JNWQtrJ2S4biGyos20VVqsWh8OAq6sumi/CWtGqBXOL9+/W2G53uLhY4vb2AkzHBPZ5L0QiTkjn3EPT8xEvVarUkUMJey61KDhZ8gFoLZYXKzw9PYcjfNdL7HkNZy2Yc7CbdLQujXJcY1I2F3tfACidbw8PWEdJ+qd4YFvKTcdxYxPV0QBkoVoHz4B3EbwbYN9v0OkVhiFIfKAOzHsQigh80qbYLsk+Jz7pKRANOMTNj+uhOv4Y4zaECIqIEfg8nKS5dS7GdBCHxAaATuNCicNE1M7E2Bbx2HE+hx9AsswkKdoAbSSGf57AcNIhC1cqqFoS05MYoHgp1WK326U8BWmVj4UhLpeIFDhinKureKaiBSN6kL4W6xpA7zT+s7tb/NUv70G6pllSvhxdFO2SRONrjA4nNCh45s+7DherJVwM09crC/KErmlgIjNvGl2Ye7ImGQj5Gq6u2zP9DNdnCfof814sHeiE2+Lg4ZIA7hyIT9VXXqVNfwzsU5qH8nnm7MUpzyxaxl/73iN+7/0l7vczeQv1ghwt+qo958ehUremNlY9PHnnHMCGPRqoFNsI9sRAM4B0JLAMvJof8Qs3W8zVIar/oo3Vh8ZWKr8YS5pIBVsjPO73LbaD+YhGo+x3yXlPzde4r6UEfI5BGL8z/l6UlKh2/XJVTgS+iMFJMiU44QACoQOl9XlSlxfGLUqjlCXkupXFWIw4wbzuM8MHMGZzjcNhQN87zOYGRApGz7HbOtzdfQAAfPHFa8wXhCGp8UcRHRHbhSyhJaaKgkSp2MNzmTwleyZzajvKKYrDR/GZAdfXl7i7e8AwWKwu5miNxu64hmNRS/NoT+bpk/lORDvVqaCJAcVg1lBKtFIFm0vF/EXJ2x80oH0E/EBrAnATtAFUa3E87AAwHu8f8OrNG/TOgzlkcqvZEyQmJEn8WgEecJ6hkCVIMMNJPwlgx9HMUJw2kLWCQhOpMkgLMMm6Er8CTyzO71nTCQr2fx8y6DkbpHytg1TaNCaE9E10jdKJB/HRHzO+9QQxtGpxOACbzQZv374C0IeodJEpC+UohCiV9SmINMHjOU+X7Jma7U6pdzkzy4lpKl8F4+lg8A/eX+NHb59AorGqTJDRHwzBoVPCEgetUlDZt6bBxXKFRTcPmSithWo0NMKxRiINZy26rk0ZGIO2xEMrE5n2cu9OX58H6HMxqKMZHavgKzAXO6wQXe+BiSMPY1v+OXV9eZWAL0c5TiT7wgHGO4a1HtrUOk4iglGMX3/7hB8/9fiTx4u64y9I36fAF77X91NNFWdaptud1jCM6vIAnA7SPTHQWhAF1aoi4PV8h68vdriYORAR7ICk8gsOLrm/AFdZuA6Dwt/9yWto8nD8ab4Epwt/vC5O+z/13Kdf1WC9wG0Jg3b6u4CjpOF03oGJI+CjkCyztB1U3gj22apfmZSWQ5I0AiRrOSQ/Swxp2Zh4KQUslg122wGL5QLgDu/fPWO73WG1WuLmdgWiHsPQ11qF4g9Rz5ejwMhENezhYANXI7VJCQtToxkYCo/B7rFYzWCaV3i4f8aH90949foGs9ZhfXhORFf8JupgQEgauDFzrgAwKTAFh1OQgSeXIuUlT+yUgVGBfBs0EHQAu2jHZkDi03jHUOShZxbsNfq+x9PDAy5vrzHYRyA59XEGnWIIMkMS9qpoR8QhTyR45hDqVqTusB+DH4bQMsnQZrQJwXFEs6TEVh5ODXgOWUPDKYJMc4Wx6I9DzPce6jPGYDYLJwN0EUGOEOJLBO/9YKsmlSMqMhCzEYZFFH7rcH93j8VigcWqQd+v0zgItyX+GKwo5O2I6/tkqxeXaKDSWiLUG0aAmxlOYpWUOFPMyd2uwx/cr/CXXkuY3kxDZY0Mg00RC7VWIYMgK3RNi9ViiUU7Q6sNPGkY0mDNMWR2DCgFpFgGMpaiD9FKwbL7qED0eYB+vF6SpMffJaGFREESpxMB3bFtvqzjJdPB1O/jx12MVCVXirl/xgGDiKAJ+IXrPW7nR/zB/RWejy0+FaBKgDuVcqj4nt6YfOZs2VaFwDrEhc2e0WmL763WeLM4oFGyiYssYZ7T5iYVVI/BuqGqvNCbaNrwyCaYqP37hGuqf5M9Qc34TPSzerb4xkI8xtBUUBAJ7ZYISUldohzBnIiO+NMj5qH3FIPd1N1KUo2KoCrMgHxO9iNqA4TB+tjQKFJYzFsc98DTw4Dd7hneM169usbqooVz+1H4T64orRBeKiX9AuxTgBUXjtopU++hSSfZxEQUjonex+h+Gq/fXuPhbo3NeouL2y6ABxhyokSk5bI8QjSPFP+TKwcPMiDvYKX50d2dOfqfMIGGQFOc6WNqXA+jDKhIfUoUHbWUg2oY7BvsdjuYxmB+cYFheIT3QwEuQZotbelhPjmp00XqCw2L2gaf49qLVKqMCuFvCdmjPqrfoSg6dAJBfEca4yTxqwA07GTePPrjgP7Qp33QNg1msxazWZc8932pxYs5440O8f11dS6/nnOj53h82MFaiy++uIWzu2IhlL4OHp7CTgh7UTQRqCT2ah1lLhfjdNRyP4zz9Ptg8R8Lf/70eYFVO+CriyOA7Kfkvcfx0MN7hjEKIIXWmHBcERqLbobVfIGu6aApah26EBGTOPSP45FEgmwoBMdMrv3CzjHIaTxf/PX/X64krdeSdPp5imhETpOjOoQZKVNR5VhXqD2nAF04xSkNQ7ZpBg9ZZqRNAuQUjUSIauzzTIX053LG+GtfPeLHT3P80cMK50BN2pUZZjkyUpZfnlqoWNxK7T0FhMwIMfKtCgDSOkCHfl10A76+2OC22wOx3y6F4gzj7ZxPYxPifEcvYh/GoYmV7gfCH94va6mR6s/p6/y4vHSVnP/ps9kr98ThM9VVjGMSHeJzL6YnLohLhLN4MCprk07aWsKsAOypBCIEolT3F7Qu6YGkNAJihj0NIgNnCdvtEYfDgGHY4+JihevrJZS2sG53whjnK5d60nORgDg4f/XDgMYHchSCw4RHUiz+URWJwQHH72LPZlgXNA6L5Rz3d4/QFLzkffTEl+yBdcQ3yXsQg8fIhKa5DlHX4BG0L+TBpOAVA67QRlgTJG/Tp5DKADAMDgQPE4UKJbGPGXA8QLcE9Brr5zW0NmjmKxz7x9h3sbWXfutIc8kS3z4yLEqHdnM8j6+7mGu9YHK89zGIUgQMoU1yPFFJ8xjeAay4qlUkanhgGCyOhx5OpNemQdOErHDieKgiGHN0jiPSUXrNeSVKBifQ5wZEDTbrHs/PG1zfXEEbi2FwCdyCFqbIWcEevghLXZ7COV2bo8VY0T+u3pE1rgSQi3vCEEjz/+GHSyybu5iNL9D74WjhnUc3a8ORRQ7prRUrLNoZlrM52sbAlHNCMREUwr72nqCc+L2EOAolZnzMj02uzwP0i+uclF/ey5HxMh0moS0TavpSKj+V/E8ZjvK5bK8v2hSPzSitMtFN6/20veM+MTO+vtjAecafPF5E2jSe8FPOVVR7wgxk57zM+OTfcv9GhQTV2aAD2JuQFAcE3Mx6fP9yi+vumLjSlGYyhhF1TtRPcoRIJfWeIsLv313j8dDiq4sDNr3GfjAYvEYC14+s65d+nzZ3pDdfeLcmHPUcUWI65XumIWM4naoXJ8+IQESIZo8ix7u8LmvqpM1T8wVGPIA/0twkViGDPDQABWsZ/dFiu13jeOxBRJjPZ7i57TCfa3g+wDmH02vMoFBxj1N7ZB9a6+Ccw2BtIPQ+ZzKpupIktZrRKd0lSfYyAGZXmNTyEbzKUk8STChCdgwaU+uE47oQkCE5Jhns2wrxbxC4V4BmqNYBHO3hIEAB/b5PID2bdZjNOoj/ilWh763R2G89np+ecGNu0TQrDHad1kQ5FiWhD6Fzcy6BaAyCUoBqCNAKROKc5wA+gkOmJqR9iGga8B4SrVCc7LwnSOC3hHkR6Fz01GeEtMFd16KNKXnbpkXbNDFAD0dmSaPRMzRqBrCCNgzmHsndnsK8aL3Abmux2Txjv99juVzi8rKFtds413l1hKiUCgSH7EA3zWAXlPTsM/JkMnHGeZrCE1J5nWaaD3y7meOi2wCczbtd16I1JpxKgoIhjdmsw6KdoWvayOyG3BmgYPbUpCEmUlIaijjRaNGcUJzrZE7+iGTz2YB+dndBmks5vhcCU2RAE1sPUEv1PpyoSYlSSs/7U8UtRecVTsRM6g5OKpTaxZwz5SmSJBYlJ5rVslU5iVNAltbSRBN+/nKHbd/g/W4GErftuEhr0hvekdCauTdFnzjJxudV3J5CQhxPIO0B4wDyeLs84ueudrhobZAMxO6VABFA9EhOGhOV7adKSXpJwtE3ACn8bL2I8zMGqk+7JrCv0mokAI/9PSEBxb45VZVPEYw8biP277QlqT+hjDTuiEAWGQhhiiZmaxLwJzVECTDymgyEUUGRAZGB94AbgL4fcDiE9K/C6HZdi9vbK8wXLZTy8L6H88eTemQHFkOcgDMsyezhLqp8AQznHOA8VCuSMVXrt/RN4BP047rCuGCIVPL6lzjuKoZHJao/k4NZYgCQBrcEkHJeUkhc8iCrgUHFrJCBEVJM2VdCtqbzOB4GNNoAHYpc8aEu02kAGrtNj8f7B9y+vkVjPPphC4kEGHA6yLhKMZTT4T8fNG4i/zJpaG1ApgGrJv4WwFerPRq1BfOQwF9MBD4uLkm249iAHEHrfCROtIYhLa4DkULXaTRGo2vbJOG3bYOu7UAArHcwukOjFthveqx3a3jPmM1mePXqAh7bOMYKWi1wf7fBZrPDbNZhdbEEe4/tdo2mzZoqlqmRpUD5j0oRV14n+zjupfSbzHV+mOUhFMAf60sxD7jg8QF8t5njB9cbmIgjug0+C8QET4zOtFjMZmibFp1p0eomps7NGTaDtiWsIzCSVkM0OuVeK7HiXG4ZuT4b0A8XFbG1UaQ8BICQBztnMKOKiMjmdNYnIJqS3lMCFeQzwyKBSBnpeWROrFS7lvHAKarISFE6rkZStyyi0QJOGgJm/OrrNfbfNtgOpqi3anROlsEcU68iI0ayTxS3UO6N0Kd81t6DWgdtPL5c7vD15Q6LJjI+iuBtPq6TxhWAUh5EKpoXAgMijA8I6C3wp09L7IfC4WcC56e0KtXvUy9PPp8lnHLcKgIwAlaqnuGKkTjLKEkZMp1jXkEYIymk2NCEIEUqZFBK3SnXxIgpEpCvxyQAodEzMBsMvcfxeMThEGylLs5Z17VYrhbougZda6A0g3mA91tYWwN7roGLeuoxlj2WTV3hb+dCnHYhUFqHDG9N2ySz11hTRYRkI2VGPj6YGGZKc61JwfocuMYoLaOQJXsB+1R+bVOuNUOj0YwSJbGCHwDVWbDOudSD41yeR9MYOHKwvcWx76EPOjnNiXSuFWGxJBBm6I8OD3cPuH19g8ZoHPoengmedVRfMwAHNxzAXkE3DaAMGBqKfJDyFaDIAziA2IFh0PsG1i0x+BmM3sOoHdhbMEJwnsGGJDLGxDm1ClZ5WIRY+incrXMYBgv2DBN9AowOAZIkhn5rGmgKjIZRDVq1xId3T2BmrFYLaK3x+PiMhwfCqzdLOLeHUUvc3YUjoK9e32C5NLDuiP3ugM2mRzfTWCyaKMBlhq+ct6lr8m5iyArhKsWCLgk5Z1olDMHJxq/vOyb87HmOX7jawch6C8YqaKOxWiwwn83QKI1GNTkzZuFkKcIegZKVsGR4Eo0t80tAdt356/MAfUZwKgFDcogLkfESV1Js2kYCXiCdK03FcHC4ME04EkYF8Szl4ykP49SOUqISgh6JS6UeKqQA4dS899CNTm1PUkCUmpmCWkg83sNZT+DX3j7g739zC+vEozO3uuTOAWTAFw4VaXjGXQl1WwXfZ4/8trH4+nKH713s0ZrYbmmfz/4KCeyIwhlkqcd7KJNTSDKFfv7x/Qo/2y6KzSuf5301zl4lQ4M8xVNEvLyVIC2BcPnb6bvTknWuK2uUqNqGJXMYGEPh3rlgNHKYUko20am+5oaW/cvMS2BgtW5ANMP6aY/1+hHOBfty13VYLGboZi3aVgNwYDiwt/B8hLdjEsJJN3EqRp3eLTVT1S8UAoygzfuq7dpM8HAyjel9jtKMlkPRyMF7EjOnVDh/Hr3CA+iPPPaFaGJ6LnP9IwAomDJvo9ZLl23OeT+kbAmMMwwWznscjn2ag1nbhRj0UaBYXSoYdYX7+zXu3t/j9vUbNM0Mh/6AlAYZDPYE5wjdrIFuFIy2UDTE6H1xroTuKQLRgDlbWG+xH1oMbgnPHTTtoGgXvPVj0Jdw9h5QnuGODvY4gDlnz5NxFk9yTeFYmTCpjQkMACHE35i1l7j7EDIqvv3iBqAeWht4v8JmswPhEkYv8eH9GtvtFq9f32KxVBjsFsyMbqahNPD4cIQxKq7V8Xzl+czMZrkiqdhf+Va28aIA/ryH89ITKb9m/MAI/g1cr9k/fVrhi8UBC8PQ0MFpTynMZzNcrBZodIOGTHImV8jj6WNOCB9jL4iQSmW9aUlmZjoxCy9cnwfoA2nQABSUN9pTtIR/RJpYifktZ1GlDIoISCpKomkyKcXPl2fFXh3+LGahBCw5xiOBzkbXiaNgJF5iq5NFWUn+QGVLWnaMH719wm99dw3nT1Y0xFtaUllWCyZJLqO3HIH7yPy0DlAOX19s8YObDYxoUiInKhsrq5yDh3I4R1xBQO5jNKE8Hwy+3SzwbjubBrWJSyTdWiobE+ZTAC77OTbXCClP3HraSOOnPta4EbEo6iFhAFnuRwYxzm/a1NFb1yiTEpGcgFIUdaeAKTkdKYOuvQDBwHngm599B2stLi9XuLhYQpsgLTI7eD5gsC+rBfM4jcdB1tnpNUlTKThvss8ZDgOAlMe24r6IfR3zeoRsr5d2VSYbKHhv43rnZNOv+wFAGOvx4hubEeRefFSYXW8BMvV6K2thYdqDegvaBBttf+wjMw847SLgR1MTezhs8fr1Je4+POPu/Tu8/eI15kuPwR4SQ2ctg5XHcmaDViGBXt6fBAJMZrqYgE5ZNGqA9QpH26B3F/C8/P+R9yexti1pYh72RbPW2t3p7rn3vibfy8qmktWw2IgSSxZkUSI948QNbMszyxYsGDBoDSkPPKQheWBIM0O2YHtgQxIkQxZsQHIDWHDBJMVi0WyKWcysqsyqzNfc9nS7XWtFhAcRf0Ssffa975UID/xqPbx7ztl7rVgRf/zx9w1G7+nMBh/62CnPewIjOI3xXRTuvUcxEsvHgUnWFomgVyjatqVrG6RO/qxdsb4/0B96PvjwGhe2jENP28xSi2YPNLx+/Yb1esOz59cslopx3KVzEZnffh999uuHgfNLhTFCFys8SPfX5z0I/SRMz9FEIHjH1uf99xUeyMclbkpk7yzsKQDN4BpM42i0pWs65l38v7UtrYmxD7pKtxULc1EUfenNImNXwdiiLGal6ytM+/ANYvoZEEJwPckcn8x5CbAxijxFukqIMMemPpUJtBBw+Zlz632YAD4zbqZIFdIJleYcETGOXAGJGuZsAkVuzJMZRBI8avpUS36Xi5FfeXrHb7+6fITHte/8EdyOeYnTMGiCV+jGo3QkLCHAm13HJ+drbDro6XjFamqmBDxKfnDw1UGReWjF6BU/v19ws2u579t3m+ROmPJPMfzJ9wWclQSccOFdBD49mcPCjqT7MmIRcCoWdvT5FLYiBCkVfXIKwcVjAkK2HpkU0WytREAf4aYwWDV9bwgBYxpm7Xm6U/PixVseHh54/vw55+dnzOcN2g6M4wNuCJwGxykAFQ13el8d03IsKIVCjxOxEsI0EZiVShUxVV6XqoipCApFsJT0RBLTrrScBHdUDBoVTb/W8MWq8jj48nj/6pMmt1SZOC7Nx/ijJ6dw8yFlYhhFM7O4PgYu6lRv3lmHMybDMQDeDTh3x5OnZ9y8Ubz48hXPP3jKouvoxx3ej/jRYRsdU8Aqphedv8X3XNL1ynK0VnQG2mbAuZHDaNgPc8YwRzFgzR6vDzjV4/SAG4ZYxsQaWmVRWMSCo4i14FvbMJ+3zOczrDZIV4fDXnF3d8/Tp0+wjaPvx+Qmje6XcRz57LMvGPqe5x88ZTaHvt9mQTiEwDjEJk9XTzr2e8fDXc/qvEXS/4sLKSl0vrg1j7XiQgNCUezL8cq4EGpJkuqexH3l7E1dRBXjR/F7N2eoyw3fujDM245520UN3xgaY2OapJJSynGTJOiZkJpoSan2SosXV3PuaJjWYoxhPBlgW65vBtNX1QFVZHOWmPongroi54QXEzLkYFaiVu69TwV2hElXLxPIq3jwJ5QwEbcsGE55QyFogRio4acMfUI98nOhjHt0ZZ6hFM+WA99za37/bSngE5nNuxhddaWI/Oi3D6jG40cNXqGsQ7WO/Wj5R68v+FMf3mGSwFSEn5DKe1YalyqtNUXoGJzm77+84KFvs+RaX+/y2U/26yuWUs5qAWgW6k48LPdmOSyfran1YkoATs0ivi8zeoTZqCycxSAdXQlzoXymVK6rnTXfdwhEmdlVCKO1oWvOePtmzTg6nj17ynq9ZrFYst/v+fCjZ+z2bxgGR4U5J0SY9101koas8ao8nylcJ5kDRIbpUq/1OGedgzqPz9GpPwS2WbNN78g4k2iBJo7p3HgEQ4XKVL4WvI5x7ngyIa9XGJEbAWllepLrF3zI89aaYAK2sXgfYgle55g5F89qgkdUMEYO/RvOL68AxYsvX7JYLDg7X9K1ip2/ZzYrwvyx5UOaZNWrUzAp66wIKBMweqBrBvrRcBgaRn8enzEBawa06YEDipHgR5RyNLrlcvWU+7st+/0BPwRc7zlsB5Qa8zu221jEaXXWMIybXKhH69gvXprPPP/gmrbz7PbbLIILr+t7T9tqtFEsl9Gnv77vWZ41ifEnfErnXEEuSxwq/hBCKn4VhCbI9k8F1mImLy7SbAWk0KliaTviJ+nMb8aWv/eq49UB/vQHI4t5VELbpsEaOz1NQuvzBjJRDkN5faS1SZk1qNxFcWplPH19M5g+IFCaamnksyslX5UWBgRSMMUnCUul7k8+55TXABSk8IWBJIKjpFwjaasr065OgSzCGIXxTCL+gVT6Om90reGklT0myOmBTNO04pOLHQ+HhlebWWFW1fWYqarotz+kQKfOEXpD6E006wNh1KgQ03KUjkEqOkmm8lk0TYm2FrIwUHJO4z3/8NUF677lxNQeza3+fXqgyr2nEDx3TczwTC+r3pfJeEUY6wOYdqt8Iub3auL5AMJkLyNxJ2tCEQ8Kwzc61TZIU8oVtkJKI9NFSHg84+OlJCuCtjR2iaIlhDVvb97ywQfPmc/nDEPP9fWHScOyse3se69T7P+xOOCzNjW1cIXqkdqykuNspHMdiWF7iG5NEYBrsWI6aq5ImEzHwVfEjiLgBjxNY9lud3hv0NqkAkIlW6Ied4oHJXAqz/IEnrkeVCNd+KYyYU0PgnCE9I6ma2gbUu/5wDA4/HaftP9YyS4KfjElbhhfMV+s6GaXbDcHXr18GzVEYLm8oGssPgz4EAWIHECsCv0QZUNwuMZZ8VPbENCNozUjPsDoFAc3i7Sn1YSwYPQt3ivO5wHjA3d3W7zzLJfLbJo+PpfL1ZLr6zNGVzotyvk1duBbn3wQaak6sNuvs5k7442Hofeszpp0X2A+t6m5TM/5RYtK2RRKe0zQeKPRIZQuiRUaZU06ZTzVltzjgGxZi05ZNNPz/y4RWc52+e/tvuH//dmcf8Yqvn8d8fH4EgWhPi+TUTM8iuAplV+V1uB8Kt/7x0HTDyTzeciajxAjMTP7ELtIqSQdAblJhPPSfetIZA8iGb+bcWailrT2iWYjTCdVP8uEzD8mID75N5WWrILqffGlj94f6oOdpE6rFL/8bM12bNj2pbrgO0E3aMIh5txjPDiFsp7gVNT+RwWtw2rH968eeDrfY02xoIjpUCmQiiqTg01gHDyvdh0Pfcftvj2tJH+NK+tn7xggm7kmbpbCXE/dXxna091UQeA1w69SttKNU2yRYDJVOoFVTN9ok832xd2ksmAEUyJ9muEffxbva+wcreZoDF9++YLr62ucc9zd3fHhhx/y+edf8Pr1G54/f0JQRz4/0XAewTTkf4+w/4hhlLnIE5UD4vGrapk8hFydTimbGOdUW60F6PK++p1RaMjChDYEHXB+YDZfcHenuL1dc/VkTu/XebeVgqlQqSYwr9dc3RXPnYOxj38bq5D2Olql9KpaQA8kk7NkKWgUGqVj45QQwA4ON8YugG4IHIYhNmLRKe1w6Dn0B1bLMy6vV+BXrB927PcHXr28SeVuO+bzjraLDX6c7/F+TAKAqA0FloLnuR9Cqs0vCpEKsQBRY/ccxibljw+gPEaf43vH7c0Nbdvy/NkVtp3GXYg7TSxSo9syJqtLtlEFGIYdqENqhlQyp3RFo/e7kabRNI0ptDcBeOw9Q+9pO5UtaTnwVac6/KEUbxKrUAw+Lvs7EQFPKB4iEIiwXuNJpusBjo9tTUd8gL/1c8vBKf7sRymofIJr1aEK1W6JuUME2mQdVNX8pC30ICmw77m+GUwfKiVINM3IeeWwZQ1KNPRQqsJlX3Qy6WuTciqTNUCaUMhzYn5TIUbUi2Z2SsOR/RJzkQTV1Z8rFNJ+MkAJ/hNt4ZF2XgjocRKBUorWwq99cM/f+vlV5Z44IuqBaM4/WFABPYuafDjUkfVAO3C92vKLV/e0pjTIibEH8cbadBaFrOJ77Uf42d2Szx7OIgF4D8Ov51kLDvm7o/uP35vhEr/MP46FJrkx86vKRnfE6+u3Ualv5NsEDJW1QIRFSIVGdKqxnYN2igkyCxJZeBO2WoSRekmi6YYQsKZDqxZr59ze3BICzOdzbm5uuL6+5mc/+znDMPDJpx8xjnsCe5x73HYzwNSvefTe6e+hmlDRZiYfHt0mNFpM43L51NJaqsUlbJpAfGJtkblyvDdyh8pE3XlHawcur855++aW+ayjm88Y3akaA+8RikOskz8OnmHwMXguxJoe7Tz6W12IqYSBUtAmJMk9CgnFOpgFokRgjFEYq2MHttSv3g8u9revtHatRlDQD3tWixVnlx0XLBgHz/4wsNvu2Wy2KCVpl3Nm8xnOH/B+mDLkyS8h70/EQxHaSOdVYbTjMFpcsJzNWu5vN6wftqzOVlxeLQlhm1xGZWA5/yIcS4bPBK4hdecj1TbQitxhMDHpYYwwv7jsJnVTQBpyqSgUtA3p6ZKWnbRg53xpkCRM3Ht8rdTV55diDfBHtPgRfhz9FUKEYRCrSlq7D57YO1rxD18aDqPin/52oLH6Ma2rRhTsD4ESzHdUEEj4gzTpOWGUmlzfHKY/pQ0ZgLraUCAzXp/LwNZSfkilKYWZTDUuYfhAkSCF4VcKlDD8nOtfif3SWGKi7VcEvxYORBCQOdZS5zG6HTP1Vev4ztWGn7xdVs8UJuN7DX1s7q26MWn1ieE7Bd1IMxv43sUtzxY7UCVwxbuQf4/rTJqWk3cU89yP317wdj+fCCfv8tsfr0dMa7UWVn9WB+pNn02wVqKVP2b4AkF1/NlJk5oqDUDSsuVHLZjFDVSJgUaffNNYrI65y6VJBlONPtTjpPfJjWluCk1j5yiaaP40ATdqvvgidrl79uwpL1++5MmTJ7x585bLyws+/fRjfHAM4z3O9UVbqdedfxdtsHx2ks6J4JrvE79ofcaqNE5KMJ9EWhdBN8KnziiprTIC36kF7pHoF2cdqribdOTG8cBiueSwX/D27R0ffnSN1g7nxuMhJqPKOXRjoO8dQx+ZUtMalkuL0iG2tMXFbJlQiHuJLxCTMVl7LYwl4S0hMx6SOyj4KMiPY9T+Ix3QNNYwpnkfhii8NbbBNJazruX84hI3Bg77ke12x+tXN8xmMy4ulzRtw+j2+NTEp5ZsxbKiJge0picKowKzZiTQEpxls95xfn5Gszhne1jTWffI7F1rvUIC61dMYjCYxr9EAhnhetg7FssmBStOr9nMMPSG7XbkcPC0nWRAxPoWQQVCKqAkisoUd8v8stiYGH0JCvSpJfBk8ojCMx2p5htxb3X6oFouAD+5gd0I//z3PE3RKSdXzmyJf0QcQ9LSK81EqdgMKMQKl6csyfX1jWH62aKaNbgkZSbzlQQbAYjGLreV4Bmog2KEeed8ftmc3CBH5YhkVLIUqGOTTZHGMsNPxCATYJX80MT3S9lGjsY4WjGlGtnp69sXW15tOtaHqnBPgHAwUaMHlI0pOT4JAADaer51seFbT+6wSkpbFitJHisxVu98Lu4i0jfAdmx4u5+nNb5bmzr+/qsEgvqecmuBpTS0mTD82mQHR0RJBK3jOUHeySNp/5H1xEMhXyHnKje6waRUyToKv8SEQK62pgoBKnQoftc0c/ZbePPmBePo+PTTT9hut7HNpjHc3NxwcXHBy5evWC4X2Mbgwhbnexh94eJfDdoKmnmxWUApEeZS6KrWHMue5HWEkIM5ZWUKMDbFN5j3BCuSQZ+Finxn2melQnRNZOFJ5e8DgdHtubxacTj0vHp5wwcfXoNe4xIDPNY+gw8cDo7+EBsIWauZLxusURM3nwqaXOYjFddSSaMLIWSGowixBn7W4kQLrAWEms9FZjEMI250UQlJEd7eexxRm8OkiqEh4PyY+wYsVpbl2Tn93nNz88DLF29YrpZcXCwxto99CSoNpbY05ZmcwBEFGD2ikjLStg37cWR0is7mFVR3VzAt5rfJGYqMXudHVbW5MZg6WlSsLYHXU16nWJ21hACbh4H9NtJr0yhUEysWGgIEg8PjJf8+tVGvu5xKC2HBTyXFw5TJ8RPCvGMoWHhEE2SstNGVAD91IYq28WIN/9cfBf6F78GyK/QgF46rICk/RfSoLZqiAI3OMfTDpKPhqesbw/R9Jd2cpGuCfCJxiSWgzm89RXsC2f8jHc2y2UpVBXdCMQNFQl7eI8w8b1Q+6CqW8pU5iRWB6RypH3s/fZxcRit++fqe3/z8Kj4YVAnSMz7WzB9N1KSSP/+j5Z5fuL5ndtbnlKesdobiC8tWj3T4Yv18lbW20cHvvl19JUH/ute7IvoL964IsihVx/A7+iXDXT26Q0aajll/k19ChkHcZ01wgcZYGtMkP76eCk6P1lWztHoOVXCZ0hwOO9q25fx8xu3tLU+ePOFnP/s53/72p/zhH/4sBu4tOrTxDO4e74spvyY7WcOp/z5hDZH5lF+P4DOVgvKYj7NdqAq+BIy1WHucilivusgo9d+TVx9BSv4+Fsa8d2iz4/kHT/jyi9e8ennDs+eXBNZR861kwnHwbDaxs918YTGNjkVu0gSOmZdWGovCq+iP997jvMqaJbGZWp6Xl1S/iZZd1lijsk+ZMNJtMj4bvxzGqPEbk85cet65MWnzPaZt+OCjSzYPB+7uHthudlxcnrFYLvF+H/39Rzj96IBULEelDpHGeqxt2O0O2NWC3SEG/ZmK3sWfR5vz6FJZaHz3PaIQxeS/CWElCZAaVucNWsN+73BjEqp60FbHjo1WoVNcVwiBIMFvSH0MsQAo0caKKzgFfguNFzm8wK4gUKgISu3OkWZAQjNE0CLAzU7xcg3fm6UCaIGYXZbOS12sKuO2ikKR8z4HATvnORwGvA/M581pYKbrG8P05VIKpLukqqTMEDzeR8YnlhqdovVP+ZKzZi+bWyNCffmAp5gsPeExcVdTghSI/iyFilqCqnz6wkyZEoX8t4dTqXvvus5mjm9fbvnDmxXhYGNTEBtQszHm4DeesLfMtedXnj9wfrEFU/nnkhkreJ8bFYkUahLm56C0FIDjA/zWF0/YDrFRzinCPgmGPPr+vYGHpyS6+rDJlN83xomvy7A1q4mE4BG4K2YPJU3IaBML69jYQctoqaNdCq/Ic6LlVXyEyPzjoc7aWABtYrOU8/MLPvvsM+4fHrDG8vTpU66uLvnpT/+As7MVgR4f1oyDT88faSK1FazC80fEPy+taPUS+Z2F2fRLSOMKfhN12xTUFlX+MXeBi+6taNKv/Ns1/EWjO9qNU1e9DKVK/nzsFCcdyGD0A1bDBx9e88Xnr3jz+p6nz84Zwjq2kQWGwbO+75kvLLO5TWMXf3cdOCvzEqFdBY1K51IrHYWArF2kIj7eTRZZC5y1tSog9CC19Evv9j4GazmfcvzReONwKELCPaFV0cwbc+wXqwVd94wvvnjB61dvae9arp9e0c0Cw7hLvuaj90+wQHBIZcWpaSzDMNKkj7Oyk1MepmdIrF8TkvgVJCy78XTcm6YxCTZhco/s/fKsYb60HPaO3W5kNo+lpsddFBhsF7DWFxeMixYYEQQynCUFu1pX9qEnl0GEAwUuAjc5SDKENFZDp+BEXQk60aZwOYdfuBKapx7BSKV5OOfLh+mnaPTOuSTsBeaLjq5r3wvbbwbTV6ktrmyGxKIl+5tLREf5dJhEKFBHhIOEopNNnzLifAVykREfQqqapJPZstY0EvKGaUSqCBUS1JWXUgkfxZRV/PtBhWrfT2tKx9eniy0vX56x6TXKOvTMReRN65gbz5/75A3tYur3FYEopB7e2qhYtEer4i4R+KmQy4juBpMY/v9vrgmhPD4k8sv7nn/HmHG9Uy1STW/InwlPLr28YylSrXUup5mFuSw51gPU745ExZqOxq4Az2F4wJoGRctuO/Lq9g1N0/Ds2TM+//wLnjy54ic/+SmffvoJV1fnuNAzDGt8cJWwKIFFnNTSVQgVvU/kXu7NgonAtIJ7FoSrMUMtrJUMlIBorQFjYyBj6U1PaU5VyVHqMYi+8srR+yIxqGo+AUbX01jNBx8+5cWXr1g/dCxXLYPbE0Jg6B1tp5nNH+OtwCGISbcsuQKnSt3eQjLPRs3ehRItnmNxVA6VSy4Ff4Sz5TuXXDOxlW2EW2MtgRigprUnoPE+sN2MLFcNxggE47D7/R7vPW3borXmyy9eslotubw6w9ohVfnzaUvUBA2ofkZZWjMMA7ZpGFzAap+DFyt+VDHSuB59SmFKG3VKuQkJn4zROBeKcKKo8EWwJDF/rejmsYxwv/fMV5oQkvCpEmNIeC2cT8rdSgaI7E+2Cic8EreWWHwiPkhhnKhIKlOey4pQovuikSuhMWkJv/SM4j6o1h+VCMnqKZaG/HAo85Ro/cZamsZO6jCcur4ZTB8eEVFJx8vVmZzHVHX3H1GUfJIjoRS+LRqKtqVLHFQChfNxU0V7mZgWpTDHUblUVaqvKX2aR02QJzP3qRz+tcAyaNTdjF9se/6eUzEPX+biFKY3/NpHb7GzPSGoaV6rImv4kkd+PAeVEF4QdHCK3355/mgt/zhm/trnfnoYNWX4x3b72oxaHThJQJjMLWutPGbYofwqaXdG6o2rKMUHX1VAVKVGQU0whK2JxC9M35iGh/stSmkWywtub+7YbO5wzrNYLLi8WtF1lsurCwB+8IPv43zPfrjBSe79hFCHDI4szKYvJ2DMWxo4LgksRPaYJ52yDrzryvUckjSdRY1EMOXfdLKyblgt5/GYaX0hCd9ujD546ahXCyDyc3QH2s6wOltxf79msXyCUj3eO8bRM5/bfP9E+xazMOQsh4AIA1IfvQ7gi/c6H6PxnY+af2ZP1fKzcB98bjXsXVpPIAbvKbA2FbRJtMBnc3UcZ7tNJn+pMqoiPo2D4e7ulsvLC66eLEHBdjNw8/aWzz/bcX5xxvn5GZ4DozvUZHAC/YgDmuBjkOFiuWTrPEbHl0ngZm0hybh9fMaqUaF8d8qF1zaa9XpI1tuoicfux9NYkALLQNNp9rsIv1i8hoJT6gizTuTLy1i1tCNCn/c+BgcmPlHPfzJAelCrZPVTOqVuFwXD6MC3L06vPcqu6bwEifUi17gIIVnTJDtNa5q2mcRUvev6ZjD9QBU5rjKj9lLyM2nqsbFBMjYlLcMnbqLjwwUBAVFzxE8tEaA1AVeKrMHI+2UDa42/EHsqksYjLjbZ/CNNPkt77wNFzeAGg7tr0bORJybwiQ18PjRxbR7oDb/87JbF2bY8G+qjHrLgolPQonAR5ckHWhtNQPFwMPzkZskm1ewXSq4yrKZrfZcgcNLsX/Peo3nm8BtFjrKPBLr8/ugdaXq5NG+6XCLc4o+rTXiqurcutCNpeYQo7Uctf1r6VV5REziFQhuDVgZjGrSasdm8Zrfb8YF+zna75+xsxXI5x1jP6Lbse7i+Psd7RT/eM4w76sCsAlsm5tZTdKkw2np/agYt2t1jSXnKHI4GphBIOX+ilTzGgaNnZV+r/ZZwnXcJx4EkHAfpL3G03kruGoY95+dLNustD/c7lmcNh32PdyHXcpdzXdMQsdpI/Y+8xlD5iisBwXlfgvrETJ8FA5KGFrVXiboeDkN2ici6xnFEKY1JjXCUNpEGGUo+ewA3BmwT8/rj+jVWz3n1+h5rLReXcw7DPYRAN2v56OOnPNzvuL9fs9lsubw8Z75Y4dwu5dML6MpGaK0ZhwgPbTuGnafrfNm0o7zPx/792npZ9nSiKFUCaSCuyRjF4eCYzUyMkVD1WAXuIgTtdw5jQenH+KqOPsn+9brT3uTGKk5L9ttXAZuhZBLVQr5UajU67p1OyoEI/ADPV4pZO9XKZSyxEOeurgkvMv3wKVg00UJjDDrB7mQzuOr6ZjB9KmUlne7HSHVU6tOHvJFSia++RIMVjI3CeJH85LDqE9HHx38LMsqkRJc5zu+f0L8QU+GOr6+jMYcADBp330I3oOYDeM0vADc3LZtRc2VGvvvshrPLbSXohFSbIL7HueJKqHNkc5/yZEYcveZvfXbFfjiacGYUU2n2ZPDWCWHmncF7FGm8BFVO76uZUj1KxockjEy0woAE/pc+2TJW7nRXAvaM1hhlslYv90q9d5lU/j2E3GNdKU3bLFBY+oNj1i55+/YmWo2MoWkaPvr4KdAz+k3W/CBE4o3C+7Hg/GTVstYj7YEpLIoyW+NlIUtiFam/O4awvEO2WsygbnTFtZWEV2HIWYiqOftk+hI8eMw0pveK9qWVAmNKOeBHZgny7F1wmGZgdbbk7u6BfuhQOrBYNamypMSuFMElE/K8zsTYQwrgqxhAZj41gxcQB3JtEDf6kgvuPMMwMhyGSVvt2OM+pMZIEVfFhNs2LY212Yq4WBl2W8fD3UDbac7OVmzWPYfDgafPnuDDPmuFw3hAqYHV+YzF8il3t2vevL5hNuu4uDyjawOj26UAT/UnAAEAAElEQVQKhnHyWhmMnnO7XscAQtMw+gNWe6qtKtsz+buw3GxCZyoAy09VfS6ko5tZtpuBrjMpeLhUgizWFp9jq/qDx3aK/uDxDtHdQCm0DmgbCxCl5AeUChJDd4w2yeIbgyXRGo0m6GQ9xmchDUrVzUgEmOC8tMeucfN68ZgWxriChBu6KJCKVPNNleBDYfAeyRoTd9z7ecQ3hunnso1p57RS+BRkI8RBApKgMI+aaWcNPW1cBKCYcSr9N8iBVgXYCdQTTbvSckVgyHdWZn1VjSvPTVIHvwajr68waNxdh5olhq8h4GhWe355b9HWs7zcgBWTY5lzXjvFNFxbL0Sgql0ZP3275DCavNZyo4zzGLHfF8j3aD3Hml7++92mw3D0MymxJCVhwrg1Zb9l/bLjYnpXyXwvB02apehEdKfR8cKspOBMyH9bbdF6htEW7zU///lnhADL5TY22LENl5cz7h/uuXoyox92RaNJP70fMr4dw++EUi4rmcBfZlqIcGXxUAXmeQPCESxlzIQkxc8ZJimcSqlc+2Lqu5wKvFloOJr8I8Egf14LkenOetKBCV4XXI7+/dVqwWa9wWjLxdWS0W2Pzm4qz61UTudFFabuU5vZU5p+DXUqLdS7QH8YMlEXLHNjLJ/qnEd5cQuWTYgdF3XuXjfrutiIqeocaIxiubIED4d94P52YLvdsVgu6DpFP/YTPAjBM4w7jDY8uV6wXM25u40pfqvVgvOLJdoeGMceMFiz4PZ2x3az48n1FdveRdqoEodjGqhXw7zelHheNVOcDNUZjzil8vOBptWYvWK7HZkvIg5lKxKV8CXtaJXisCPGdumquE5QuFER+nhItIlw0zZhfiguGDkWKsFWUky1KARGYzAp1qAwfSEedXMvsRgKPZBlX82FFpLWFOOnXLYsTYqb5DnKd0K7pQiRKLZf1WnvG8P0gSgBuqS5Z1qhsokxmkTIkvSxDz6bb1VU+UJW/cJE6oLEHDSpbG7ICCNasjB3iSkQAhRCShN8h9+lBJA8JtJfyRwB32v8fWT4zPok6CTksY6z6y3+oU3rEv+QSLXF3yoBhpHB68kBrlNQ/vB2xs/uZo8OfLkef/FHEWKKrnRU5QwyU5kIJfWzx8KCMAdFFXxnjnzAJKZXRbpDltTFd1/M/+V30XKjr3+GVrHksA/79LvFe8XLF28wRnN9fY33gY8++pCXL1/y9OlTXrx4wXy+iMFS5oJ+2CCMo56gTvNUFaF5BNWKrhYTe/V5+iMTp3doaxPI5vGSll/z2aRxOSE6KpodTWVhU8fjpUvqVMg5zbzkSKCqlxWJH1OGkYURIIjPM1D7gEPwmMZxdrbi4WHDxeUy9SSIjAydTNjp/SFRf+clOM/HsrGhmHnjvCQATc5UyGW+vfOMo6M/DKliZUjWNJc7D4q/VgLYgg+YlBNvraVtGrq2i0V50npKvER8rps1zLo5L1+8RSnNxcUiCTQngE7M8fdhQ9O1PP/gks26jyl+231M8Vuc4T28ef3Afn/g6skFi6Xl7iZW+bvddLTW01jPoo0/lUAjUMH8eAKPGX5A0Y+WfoxMrDGBxji08iyWDXe3B6yNzHr0jtGNsYQ6cU+EzgYTosKXauuLuyNX6otaEH5UDCOEIQVWSqBKpVwoBUMf8aptPe3MoFUy5SdLX70axVRoyVxIzlcFhos5iPXP59gplfa/lByexC5U1hDnUkZIKo4m2QHuVA/36vrGMP2aMdZMIB8mkfTjzdlk9+iSjTpFbMR8mIh9IZyJ0acoXCH+2U+kiGYhQkG86jAUpBc/b57IZG1ftXbfa9xdi5r1qPmQpNBSCEShoBlhBn7bos63FYxCbI5NFYimNSFE851PkoFKmo9ScLsz/F6Vi3/MmKL8dBzUMxWyitXksTAgCF7rTiEPXfy29XsnhQ4fbbEE/KVudqkWvgrJJ5bXIW8qb1dKJUJbTPeRPpSXiEvTmo7+oLm9ecv19TWL5SU3b+9x7sDV1RWXlxf87Gc/5+LigtlsxjiOdN0M7z0ffPCc3X7Ps2dPYuncR7BRqGP/Y/pdYFNr3vVcj61QhJCjjDPOVtsnGk9+c8XwT13ZxwnolIcvJa2zplKGzz99CKUmRL2sI62fyZ7LnDSKqtOfmj4rc0rhPPka3YHV2ZL1esvD/ZaLqxlD2GRhMgZJFcadmX3SKDPDT3ArbD/OzfuAG138P2n23nmcdDhUKgcgRgKeArJMsSChwRpL20SGv5jP6NpYjCmumiqFLGBtg9ErXr26BRTXTy9B9dmNUGuVAlWV/nCuxzGwPOuyyf/tm1vWD012STx7fp1S/TbADGsUjfFY43Fec7c1ifk7GiO9xIsFqN4/wRe5BqfZHixKBVobXVmHUbM5tLTWMW8G5ovowpgtVabr4zgy+rG4UCtrjFx1Wd5JkSxbzvDEWic/VKQTAMEFDvu4r22nMSbWJhBhUuAo5GDC8Kt/Q/XPqj3NzGWONcOPwnCxAoQQGEYXLZVVGrdzDvfHpSIfFIaEIve6rj/XRjawYrxHnEFVVCVL0RQNON5ELpuJShpyErezRUBVhClhgrgCRJMsVzJ3pxKcp6WR01c2qyYNP7QH1Gwo5qmaCCbMDM0AuxZGRTBVq1NT9SdIlw8e5QS5i9Y/esUPX51nzaaGjRhuSznImtmU378qkK/8HaX2mtDHn4hlrRaRqJl7LZjJ3OKhT/74xPyttoXpy3wrYi7Pka1BE4UgrVglpj/ns5df8OzZM+bzOd4F1us1q9WKpmn47LPPWC6X3N7ecXl5wX6/5/nzZ/gwgjrQdJbB3zHphlcxzRygp47hqzIDEBNxCEwKzFTDRS1IqQlvrdcr+FMTrYir1Fua3ydESh+lrSZlJG/Yo+mEmCUjwXIxUlly1EnR2gmnJu3vCpFW+cCVPfS1FlxFtcdxPMqMnJ0vubt94Ox8Qezc58iMCgnIi6Z8lxm+T8y9WPBkrqT3jsPI0I+TWAyBkeCkd9LzI8LENDZlgAQIAaMtXdfSdQ3LxZzZbBYLPR1BwHtP03Q0ZsnLF29xzvPs+RW2GRliZ6Bqsyp41QJA+qcf9mjdc/lkznI54+3be/q+Zz6f0zYWwgECXMwPaB2wOnZIDCiGUbPeW96uG5adY9mNiOB1rK3Wl/OK9d6y7ByNdVlAbUxgGDXbocX7hnnr2O8ch51DN5EBjt4xjC7V8ScVQ6oE5QAjCbd8gFRhVPLm4xkAgmjnaoLbinSv0diZot9Fpjqbx5uMUVmonSC2ADWfr1DhCPy5jwNG+E/6MAvIROYtZ977SKMjQ/dYY3KTOCsVG4lZFUnC4n3XN4rpZ2ZaMTylNcfZZlKFT5lqg9PGyxWS2lQHQ8UI4YrgVxJejdhT32jSshNShFRk45Tp5mTxH04zx4kU2Jvow5/36FmsKOZ9CTIMPuSxY2YDKKcJXoPxuY2nMSYfGB9i2095VoixCE4/er1il3LxJ4c4lEM34co8RsTHzP2YgJJrBGQpKmlzWXNI8Mn7INpEfXbzvpS/5XBrlVqZJumaeqaVrTZQpVlWAp2Mq9KexiY4sT5+0zTc398zDAOXl5fc3d3x9Ok1zvv8rsVyTjczuLDGuQM+uEeH9nGgqIB6Cl/JG65xTle4mIXX/NF03MzwhdgI859CpQhD6SPRqkRDQaVUVqXye48nf5xZoSWoNURTfPFTVjfJJp/U+OM/x/Qu7/xEOo2EeHQHlsslD/cb7u82XD6ZcfCbrMVHRu9K2l0y5RctckrIxb0xjg43uMzUI76kdsvJUuTTuUqB/di2oWltSj2MJZxnXctqtWTWdnRdQ2xGU+1BEvi1thi94MWXb+n7gQ8+vEbbnn7o0/sLXcrVRY9UfhFG4twcvV9jmoYPPnzCZtNzd3vPZ5+94MmTS5arBUpt8/0i1DTGcbFw7HrDeh973i+74ci6J7tShHifUtlaW4qCRQHJ09jASvfc7zoao+lmivWDRzmHC2Mqp1xcflJcJwudia5L4GWZQ0rk0wEnLtyCMBm+ArdYQVJjZopxH9g+BNou0M5C/A49sd7WCCrjCj9WSvHtq7QXzuXPpAS7T3n3UkdjdJ5hHBmHMReAgpjGabRJFoCIs1rpP0Zd9iAV+iCb17RWk2LFWZuog/cSYYv4UAJoaoIjaTF1MGA0J8WqeplZC55VTEExZeaT+t3ymQgATJn5V10+BDgY/H2HXg7Rjy+BZUZlC0SOJ/DRjOpHhfEa5Sy685U/Ka7beYeoczmApSLo93vLl/ezvNb6mgboVfzrSNN811XuL0E1qvpCZRiXSNniYyevN1QSb5G0VelVH6JWYKypGL6Y+6p/VBEkjjvRicartMGaDucMtzcblLpluVxwe3vL5eUl9/cPzGYzQggcDgc+/fQjhmGk6yyH/gbnBzjyw9UCy7tAJ4JnYTowDmPG73odRVCqnhbBaALoCj+PF3vEqCfxH7rcH0JqmWs0YvUpjSvq94RKEI8Bt3jQNp2NqlOZCNjHoqMwEWE8ajLl4j4q/tLyvQ8eowfOL864eXvD2fkyavupzesxw/cTnCpuK4G9cy4H5QkMJoxRVSmFrrgNlFap26BYngyztqXrWhbzOY0xVRqWHICAQtN1MzQtb9+s8d7z5PqS3W6NMqY6h3HdPuNJqBTT4gIRf7S8x7kRxz2zect8ds3t7Zo3b2/oZs+z608gUPcOWXYOowPrfYM1ms76Cn0eY7Lz09r6Mm+jTYqPga7xDM7S2p52rthvNT751VUAcWLKZnih57IaPVWyfGQSKYg34mFdnW8CahS+l94iBjOL7+xH6O8CTeuZzW2MpB8Dw+AxRtG0BmvrGi3xn8s5zExgHEMOPrTGRhxNOCLzyK4h71NAbJxvY2KxnzHhKiHWhUDH9M33Xd8opg/pCCZJTxmVU/OyHx5Sg5xIiDKSTRSarFsmtTz+obJZNf0eSKaVSDWDFNZSVfW9rIlMkf1dfuw/UpDbXuMfWtQi+vDraPYcXJRPeuW7JxWkGCwhHHIkcYwwTuYvpWJcizDUxCCCC8wbR2s9gyvRpce++rxG+TxFQAszVlVntSlMhBTFSZfYiTK2+OBy+dvcQzsefecrM2wlrSM4ECKRtdam3Nl0xzHo1clf0zzA6AatW4ZB8frtmvV6gzGGy8tzLi+f8NM/+BkQmcEwDHz88YcERobxgYBnuys+YbFgHF8TtHzn58LYonZamL6a3lwz9AqsIWm2RZOcPhcQgSdR5QlxVnksFDlwLXiP1wqjKtFBBFBfdhjIrZhhKiDXDFMdL+W9VxFy5H/npHGUnuDT6A4sFise7hvubtdcXc/oh0NMx6rqDISjHZCAQ2EU4rMXS1rOs67Pgo/CeCy+I8IBtI3FWhtT8BqF1Ya2beiaFpvq65d1KRrboWjpe8/6bsdm84ZxHLm6usD7gd1uwNhA00pGja/oEEhwssQsCNGUoNBjK8put2O3XaNoCD7wcL/l6knHMO4oGnu00Mheddaj5wMPe4tvHfPWV3tSzQXF4GKhmprh62ShFfxrrGd3MFhrmc9B64H9tsE5A7pPOesuMVEynoqSJ0pdpuw+4FXBD3lPDiKl0FKpuApgjKexBmPBzgIEjR9gfT+gVQzAtE2sInh46AFJD0w0xyiWq8Bu6zFWEfBI46RsgWSK90KPY52ZQpPHMQqlqnIbew+vX+3fezq+MUy/ZjSSvhcSoRI/mSBVCLGRAbLBqjTSmWgTx+b2pLAouT9nCUyJ6fuu9wXlfV2GHwKws5HhLw+o2TgpDiRX3YTIh+JTDEPABGKnvd7kwx58QJnY+SxA7gtAmBLe9cEy+selI0+tYfJnAq4PIZmuCuuqCYHsk66IndwqkfYaCXiR8rdJMgM0HqdiR7KcZ005PBK1Lzn2qprn6T2QycV/rGlQqmO/G7m7e2C329E0DdfXVyxXHageHzZ8+smH3N9vuLw6Z7lsGdwdzo/JZVG0q2hyFYGnwib1mNk/nlrRZIHUm36q5WdmmwbNRP14X3Kq0NHGCdcvii4ikNXMP4TE+BLBlbKjWShOY5U1lep/+ZOa6OXP3i38VENVXwouRmjWGiBH58/7wMiO84sVb17fcH6xxGgbW5ROoVatIQkugaryZyraUsWxSCR2DiROn4t/FuJ+NYnpt20T3U3a0jRNZPhZyI2uI0XHw92O9fo14+iisNBYILDbr2lnhqbV3N8O2NbRzTRtV2IsJC6lMDv1+IweXTFwTWFMS9u1PNyvubhcJIGxYO3UygKN8VwsBh52DT5olp1LTKzc55ziMGjOF2NFwx/TUaMCPmiUNjSZLAwc9oGxb6NSoQIh1Vp41AYgH4gS71IUpLgvtbVBSqxL/fysj3hPGALae1yqtNe0lnZmsckiKuW4Qcz1MULfucDh4PntzwL/8OeeufX8+kcDn344o1nGiq7xqB3jLxOBIJrwoxsprqtYDO7eHnIr6Hdd3ximf3wFSYNV8ajWBTRyreI2LV9Ni7HkNL0JIYnETeVUvsfvnNDJirhkM2P+stybMwLew/Af+br3Br9ODH/uTloRctBQejRqIDFaGGdihz0PPCxjxz0CqnWotodUrKLWuoRoDE7xw1dnpanR0bTFXVKvewqk+qGQTV5ifg3V4SOPI4+qnKoklfCsNpQI2tLsRXuJwC4+TPlfIvfl0EfmU1bwrrgKYzoIsVDI/f0Nfd/Tti3Pnl+nEq49o3sAsS2pkfPLhpgT/YBkQsh4wkhEqo+CTs27Klb3aI/TvvqCzxKwKhH5E1U54YW8caI5qyhAudQFzyOFoU5bH1AlGyWb8itGolSsA17n5Yf8T82fa7xO+1ZZBuS+rxKFQ3VvCIKD8dJGJ3ecZKF4mAQDBobhQDdraduo7V9eLziMh8xs66kWIaDyjWtQvtAM0fSFobjR5xa50m0z6CKkGWNom4bWxq6M1trUsCn5kY3FmjnbzcjtzRtCCCyXcxbLOU0Ti+3cvBlZndtYlU8YjQ8Mh0B/GGnbyPwxUwFKis/k85YFxOquENvbKu1YrZY83K9ZP+xYnXeMY9QqH9GBhLJWhcj49w33O8uiG1PKWwzg2xwM1gQaU+izvLsmHUb7lNqmMMmvba0hdB6lE+MPGtuMuOBSTJKkavvMNOWc1a7euvGapFiPY3TRGK3BxoA/lQRb55MrR8foeR8C3gRUQ+QPWYFIcGsKjOX9w+B40jmulp6XX+yYzQeeXM/oZqWVbwipXe4wIvpPdL8mK1Ham3GMqYvbtePuduDJB39cuuwdaQxZUwyFsQplCD6g7JTRijIDFVHKhzd+7kNAe3KjHIhjkd5T04djQhUKtfhqKvaey281Yddizg6EZswVqkBVhBdRruoZ5HuUNmD7mNqnNF7Fym7K6KKRJIZ4XEr4d9+sOIymwPKYH020ysmry++UFEAZN5qYSXB8zOwU0qJSRS1dm1igRDR/KYQTAj4ogtIYah+dmKGLtp8Zb3VIj6OMFVHDUbRsHnru798yjo5u1vH8+TXdTAMDo1szJZeBEEacG6eabP6n/KGRBi1F4KnnFUJlgaoooTD8iOtH9f6rVwgLVPU6maKIwMVLvnOuMCirKfs4iZ8IkUBKLwKtCnOb2M0SXjzej3jl9L6jM3TqqEzOUh6+RNwHKaqjpJJkSEz5eCOIAoDyeH/g4vKMVy/fcH6xwpomzzXZZZIw4QlKxfi7ZLFylTVJGG4IMZA2dkDzNK3FWOmEV8y1xmjm3Yy2aWgqZh8ZfYvVM/qD4+bhgf1ux2KxiHUFjMO5Lf3o2W4GTKOwTdQuhz4qAjFOIFahG3rP0HsWK4u1EfCqFiqnppJH+xZ/92gz0rYNt7cPNO0TZvMFLjUtCtXZlQBopaKWfj4fWO8tt5sY4Gd0wHmF1Z6z2UA2GVTzORbEtYqpfUbH9M4GmwSzEW0c48HivcWYAafG1PJYyh1XxcZQOYjbOxECVW7qI/eb7ENXGb8J5A6KPgSkRE60/hakndIBleAhOOLp+55f/VbP5VXH+UXL/V3PZz9/YLlsubxqk7U1MLqRWFeiidkKY8zNPxxGhiFw2Ethp+gyWJ4ZvPrjkqcv/1QAL52T4neC1lrrFIVemZVRUq8mI3k21SmVmiWE4l9LxE985hPTFo+ZRxY8UoGgr9Lu5bkSh0BsjbtpMBcDNDG1RYXM8yfP5RSWTOgTkU0ZCD44tBmjSudDLPCgUmBiYjhqwvBjmt7r7fwk7N8p5FQfiDlUmvrU63POY6UTVR4sbmbdulYnht8Ym5r8JK1djpgK6BRoaeSQH9GzWuvPIsURw4fos1eqY7cbub25YRxHFos519cL2k4RQp8a3QQZ5QgqJ+UdmUSenErCTSkVrrKSLn8KgtdMU1xSEDXGOhArDi8ER7ZgOsMaLLIXsdJX/jRFqueIiMyIi8bkGIcxaqzKpBKnEjtRMW8FBJWF7wm7UdO1yBeTpj5ZTaogmYVGEdDKrXUsCojwGvL9tWiqlWL0A7NuHnvFb/fMVl3c2wAq1TmXJisheIJW6GQsUyTrik+WJBPXqo1GJY3S2KLBoUClYjvWGLpUYS8yfEtrZxBadpuezSbiXdO0KU9e4/yOYRwT/AP9wbE8E+0usN855osG0xjGwaGUp2mjv70OZgwU+iiWSHGB1UgisR6K2LRIW48ZDa9evuXy8pzV2RJlRkIYMXoWYUSPc/3E+rPqBuatZhgVLsDMxuh8lfclYZk6ph+R4TfGMzjDvB2zJcqm+KRIHzzD4Bn7JgpOdowlarXHp3Q3RaFrHtHqS/E28nkyOYhZyrTLmTIV7RahIKiAWJSlsY6IBErwOUSGPwwjT9sN541CqY6uMzx7vmB1NnB7c+DzzzYZblrHYGqjx+iKcg7vAoeDw1gPpgSsm3lgveu5f3g/X/nGMH255LAfVc4tGooqkcJu9CkdLZXS9VPmJZKdMMFcV1nek+455m8nzcMpalyIxNe9YpQp+J0lbFvU+R6a0lEsBHLsgUjbse65JwbWFO1TTFfKaYKJJuEcyZsRuXJfiCYfF8XP7xf4XKCgusLxJ9UHaanibvA+4FLqSfSZSa/pUuXvEZNGZV+Z1SYKB1IHvzqARWCJGthEEqulwvRTTzhrxfiUReuWwz5we3vHfn9gPp/x9OklTRvwoWd0brLO2jhRjxcJ6+S1iQhUHEupR/OdiA8hVMS5EuCEoeuyd1OCWb2UKThkqnUQUxGEKi0vBFCiRcfKhBIYNo6Ovh9zZHHcj9rSUCGBAn0C7WW+4oZBlRTAiak04XadLlczhhKTI2t97GOuRQ0RQOXyweHDQNM09P3IQnfFeqRF+EkuAlR284n1og5A8z7m5epUvjUEk2It4njaxKJQot03NnZHa0xLY5fsNgN3dzd471ks5lw9uaDrDC7sGcaBGo/73qONwloxCcf/jY1R76rReA+KGNkd88ozUIt1JAScj5YtW2U3qXQYQ4jnCmKho7OzBSHA3d0DDw8bzi9WnJ+vuL/bcH+/5unTS9quox93BZ+Imr1ppkF7NX7W2v3x51Y7Nn0xXUv8iSUWgorpe6C1Z+g1YWzRZkQZh0uwEfeX9z77zqN1RoojqeRy0TlaPrfJFbBV8UPp2KUUz+RqDSoqj0oqQZL4SGTa4zDw7as1cBYFhoS7bad59sEMNwYOh4FhcOkMxvTCcfR4PJiBrnXYRjGGMVUJguAc/tAzDH9MNP3JVSFUUagq5l73Zq6i7GtaVQcGTrT6QDapB0pzjLpRy7E/Hwq50ZPDVE356JlMjF2AQ0PYRpO+mvl4iI+1oiAHt6TgGRNyZL74gWIRCkNQ0opVIumL4FALJRLIsukVf3i7OJp7RXgfqfblY4lsRlFJ0yoXTIqpOQL/kDXSHLWqTS6gU/s6xUxaH8j40qJR1nsbqG+aMvy4Lo3WLWOvub/fsNlsaduG58+fMF9YnN/HVqfHa6QMJWw2JKEprSgLjzLXorCGDDt1NKbsq/OS+lULOSHvz7EQOUWtE5xW8PXomUycBPcpuDim6PeSpKWy6TrHWFRBhLUFbWK5yVPITof4VwhpThE4scJeKRIkWlkt7NbBo9IDIV6PM0PgMYrGiP4ixPoU4Hs49GgijgURIlNalGh0aVrUnTwzcNOqYvfFAJaMqyZr9LGpUmur4D275ObNhu12x3K14OJiiTYe5w/0o8tj5/V46A+ObmYoZ1GgGhEwlqIVISe2AZ+UFE97HiCbt6msLtI8SmlpbxewjeKw23L99JLV2TNub9c83G9ompabm1vOzs948eI1v/Cdj9BqX3HzJDxU6FCsCtPUUzmzol2DwhoRfKPmH5SUCQ+EoNE+0rFBjSjlcYNiHCzKKKxWmNbECoaA0wpcheMptkLarwtOFWXxCI9V/i3NKQqGY+rwE3RRSqS7nlKKvh/47mrNwo6ZJktNf7HWae0AUxoMKRiGkb73qNHTuyhgDIQYrOykEp/jMPSPlNDj6xvB9LO0nSRVRal9nzWYpLVrHYNBoBBm6RpHxcTj94XhZ41OTEPi668grPIzavL31zHj14Nkhu8h7BvCpsVcHKB1U0aS5isaSx1BPCk9rMR3JURYp5SkKkI+VIdeOkRV8/75/QKfAxynufjx8SQIVZYFSCVWU8c1nYhN0eql4ZHOVopIYCoiqaN2b4wpWn4256fDdwzeEwxN1jjV+MplTINixu3Nhru7B6y1KRq/JYQ9w/juNBhhcol9ZQJQOQ/SPIq5WZGYXBBcrbVYsvAl8MqwqQiPUl+BWycZnzClMicxd4Mw46k1R2rHZy1WKYJ3jKmErG0MTdvkrBk4hvMjcWbC8DPTTylt0YohxL9U5itriONHppzGSsBR9VvkzFavl3Mh2p0ImzFtytM0hu3WZfzzlWCrtMqxKBIg5sYxl6mNDXqOtkDF1DOjNdbYbMa3xmYXlVaarj3n5s2G3W7H02dXzOaa0W1wYxX8OdmVyPCB6KMXYXKiPEeGn2WpoLJVRWhbhq3QicS4pG5Ftn5RGHRjNfvguL+7Z3XWcfVkjlZPeP3qLX2qRBizD2YERsZxl7ErwqTsflY08tzLPeWzeL81IgSowndVcWEZrVG2ifny1uObQN87+oPC2pTOm6orxjiaZLpPPRa0VCRNSDM9a2kehcvHH2lTPEAqFDSKpTGkxm9KZ/7z8fyej+frnOESLQ8lTiBIWnX6LhA7Qw5hZFSOYKMC4AcPOjCMY6b3kqdvteF91zeC6Qt+UyGq/BkZfrpPQ6iyGbyPXa0k+CkHwcmzqEc+fIJoq/GlSusJLvzjLkQEFu8DYZc0/PPI8EWgkFQSiUKtm3YorfPfJbio1PXGa/AKZUIpFKKKkCQMf0ooA7fbiCr1wZxcCeYCC2kqInnMKiFxbliTTGS11qaSaF8YftLwTUyvE4avkcp4xxp+YV2nI/BPgFxpGrtgt/O8eR3znS8uzri4XKJUnwP03rdnsn4/wZ/a1Hz6wcz4fbEOZKFAlXHKXAuxE+tVYQXvRsJiNfB57ONb4/uLtip74lwsc6qIUcKjiwwRVSLPjdFYIxHONVDePZ/JtonWnrTKkM5sqFLgsoWjIsRyXr7qkvfJerTWsZaAkngR8hmw1qb0pyQNhCyWpAwgXxropG6Czse8e6r3GGPi3EPAGkNjm5iap00Vna/RyjDrzrl5s2W93vDs+TWzeaxvnzN7Tq3Jx/Sv2dyWugwq0abMOOOvUtrbyllLa4nfJXqTJaSUrobgr0KhCc4RJGhWK1ZnDfd3PSiYzR2NsWw262hmd46PPv6Ih4cNbdsyny0YhnUSnItFoiYl7zb1V1YHJcKxwlZluanGUSpW2Iw01OOdwhtP18aOeMOowI9JIy/7LspWrLj6GOblbB5hb4JntAJFAdmlsr8qWRwHwCjND54c+KC5RyoEehXb8/bjGOsG5OqjIc/NhVgkamRkxDEGx348sO8P+LRvWitGKR+tFYP/Y5Gyp3KpWMQ0hDD8hPmh+K/q/PV604CK2FZ/HF2BOlr6tDkfKo1dpLoTx7c2UUZhJT2zawi7BnN5gCYiqJRplHlLw4ksuccBI/LqqdUiVyF0sW+47QrDTxCMxEFMWdWcAA7OTuBT5k9h+Gmk+lcFuaiEyUExE2AiQVh1sR2TIvOttLDV0uymFsIeDcVjlvLuK0blz3j96oH7+wfm8znPP3iCtQ7n1tSrenRlTlJr9xXencSd4/FExCNpij6Z+GSBTAm/EgYkS1QFb0+8TYQDqE3j8tbqOZEbQsFfSXmKgUMOUEkAGGmbJqWSGYw1OZipiB/v34OTc60EuCI4SMR8nQ6YYFHqmZwW8AQ8aV05ihs5FyGme07w0WOswXmX69/Lvrjks/U+wmRM5lSpmCYZFIRQBNsA1ja01tJ1HY21yeQf8bmxLdYseftmw/rhgafPrpnNYRj3j1wRUGFPgN0uxsW0rcQZJXfjEYSPhYYaVO/bJYnl8EGj8LnwVdyLGMNxdtFwf9vTNB1uGLi6umK323F+fo5C8erVaz755Ft8/tkrvvXJxzRNzzBsGcZdFDqqOXqpbqrk/XGGUzdmdFeI+T+EqMk7Fze5bWMZcWN0tGoAQ++YLyy21fhUyKaGiJfS1QkiPrlAQqhoo54c9nonKliGNA8m54hksfPW8GbnudCBzsT0w94P7CQ1NLVUroM9/RBxzeEY/MjgRvaHnu1uxzC66BptTVxr4lfjYaDvh3fsary+IUw/SbOZcDEJtqAiGt4FxnHMTBtIxNZMNwuQTY5brrL2XPc5Dken89icn4nre07YxLwaIGwbws5izg4xn14Id1BZg4bUYIFp2Ub5WymV6p+DbWz+WzkDphQLESYFFQFNAopondvR4MLU5JuXowphyQwm7UE0v2YAUveXz8KCms5ZzJ2Sjy/R+tGPX+YJ0dSaC2cQqvWchnNmkNpgzZzd1vH69UtCCDx7ds3yrMG5XSrMcrRd7+DhQfYsFKHl3S8Xtlg+qwPpqk/zIxm2R8OqfO/p+dU4VTfDEY0kKTd53EkmRdUKdkzma611LFubNPscbCfa8tfS8U/foVSpAyF7KpdWOhX8EaYQ8VNTabfveK+4B2Q98V06n+NCmEkarqOxUVLwAVzwjG5MbVxdZv7jOCbYuKzhi9k+zrkUjupSOV2bs01Iny8Zes0XX77BOcfTZ9csFoo+Vbmb7OMRSdqsB9zoWZ41pZFQWTBCCLM1KFQ49Y490QpiUdqYkhitAVG7jjijsqAtLiGtFavzhu3mwOXFkvnFGa9exoJBt7e3nJ2tWK83aK3YbXd8+eULlssFT64v6Mc149hnITGusxbsCv2emv2jph/nFwMZY0R81K6bVvznge0m1ieYzWzBEasyvqlhSJarmNoXqvNSS9M6pFK9MsZUMsnKZFEcZd5JmTEaPHz+YPj89oKPlxt+4WLH3h1gHwguBsgaY2h9gzYKr6IFYBhHBj8yupFD37PZ7WIQcYDGNpmOKqXwqfLnODyOO6qvbwbTFy1aCIAqCANk03fwsftVSCk4JVq8yH45SKqiB6KNZjystIuJxiTvqzX/90y7RHeHPGe/aQh7gz47oDo/1eyDdOwimWpDFkBEyqyJt9apUYQUXgmgg8G0viqDm4hoPtS13zni97a3E4Fokh6FEIHie443l6jVBNgJvOSzYrorEfpaipIkH74Rzane02qd2TXxXsIWJ2tMh3cNr1/FsrmLxYIn12doMzCOm3yQ1VcNV30vMBMcPPXcFGJp1kKj02O1MHkcAFoNFH98NXfN2lDx45d3Zfw+0lzEN+hGR98P2ZUVe71H02ncJ0XT2FQv/o92TcEj+x8FV+c9Sphn0riAVPY6TM7jJPD0aD2xdGqpY+CcWFFEODwKZpO/U8R11OADg4sujXGM9RZEuyeNYVNaV9PYEp2vTDx7xtC1HU0T88ljIF+DZs7d7Y71w5rZbMYHH16jdE9ftVLOE5sSFnbbETd6VmdNLgEekiQnqJdlACKdEBdbyPdWZ9mXewXjRMCrXy2kL/HmdHPAGEU387x5+5JF33F5dYG1Lbe3d3jv2Gxu+O53v8Pv/u7vslqtuL29Zblc4lxL03U4v2N0Qzpv5Y2F1kwxxqjYxhei5XC5avDes9+NHA6Otou4s93EdMv5okljS2ZOdBsSdbxUvz4F1UnJ5aN3SvCfzOeUtfOdsj4xPdrrZGXygZ/eL3ixbfnnunv6sUcT013bpkF10dLpk1m/dwPb3Y5df6DvB4ax6q2hVKlJQYydGgc3tWSfuL4ZTB8yRubWtFmxqupip+A7k+pZx8CjKkij+nE0bPy9YozH98CRLlchwvH9j4QCrQge/LYhHGwM2rM+p9jlZ9J66tgDcX5l4UWK9VTmVgleimkogGhJ6d5HJneZP5EYbw5NFgqO15jXUa2xPrAy7VOcsGaWujLjG2H4qcxlFs6QNKnp+/SEQJy+ohVhwWY9cHv7GlA8e/aExdLi3JZxnKa51Chx8grHK0rwSYA5iSNZ45LY6riXpWXvO1/1jg8FyU49md9QhDhdBNykIOTRo/k/MsfROYZ+KBaxpGE3jaVpm+ymMdo8JnahZiBUnOIIFvW96QOfJiW4XgTRqkdG9ZCqBirCcAlklZiXYpWY1gMQN5iYrsUCJTEogxsi0x9Txzw9bcqiVGwKY20so6tIGlsKPJVSutF6ZbFmRr8PvL69xY2OqyeXrFYto9+kCmsngFLBy/mYn71ctZHhTwTMIhDJ89HlFOHgpENgKtc6KeIkZ7RSgCZWuqDwDsY+4McRScAxOmrW2ihmC81mvce5gdm84+p6xX47slwucG6kbVu6WUfXdYzjyJs3N9jGcn6+pJvNGN0O51ORMGVQypDbHBc0xejA6CpakKSWrrMM/RDz9Meo+a/O2ljhMu2Xjio+WX2oZKrAGK0HHgIlb1+0eMliECWtTvcsRaWO3FBKQaoEKfCFKMzuh8Ddes9ylioxzgxBB3o/oEIq4DNG7f4w9IxJ65csqLZrkPiKQLT6DkN0S9WVME9d3wymH8hld1Wl3ShFMue73HBDTOGSupLobSYARZVKY9dES03fGX+kEyBEKTFQMYN9nUuhYh7+wWDO9zGHPlAF5xUNUtYW+brOyCRFN+riKiEEQtLwo+9VwagIY6VRHqUsiuYkB/+Lhxk/v19idCm76pPeGqo5TbajIsASfJgbtiSoTRi+UtnXaXUx54upv2aHE7/fCTieBrnC6Dl3t3vu7h9YLhZcXi3RZmR0m9xuVDTAr9o1sdCU0cu/5abHH+U9JJR9rOD1SIOQNaaxaoEi/n4i4ChOsDDJzCAfr0wIlU9lR32Irq/+0E8F08Tw27ahaZojZjuF+WRPjs/LCXhE67GcmQiPWOlMTYrzxAZQBX8y7HwRburzEcGQ4hiUxPykAjUivKoSYyJ1LUYXMk3oh55hkODFZG3wJY1QK03TtFgrQaYSqBrjHWKFPYs1Hd4Zbt/u2Gy2zGYdT59eYuxIP5ZA0cxUCNLqIH0W92j9MNI0mkaKz9cKgJjhiTn6AhPvPZ5QugV6l2siSJyMtPfNWTVCE3xg7BVukGYzscJfZ2OpXzdGE7pSYBtN22p22xEfPE3X08zmGG2TUqJZLpZ0M8Nh3HF1fc76Yceb1ze0bcv5xYrZ3BB8KfADe/pxi5jDosDm8cGW85MkEGNifMP6vkdrxdlFizFQaGUJYC10P50JrQg5g9nFwFp/lI5pmMDFOz/BdbEQC72W2IciRMa/xaI7OvjbL57y5z6+46oFj2fwIy5txjgO9P3IYeiTmd+l1roRt6y1mS+4YaQ/jDmz5qv4zjeD6VMTuMjolVaZ4Q/JpG+MTgUTkmapS9nZKGHyiDgVbUidfFctENS+yHcBviChfKDwW4vfW+xFTzC+EC+K+V58WCEQN/5ocyXyM6fdqUIAxQ+rtSK0HrdtCINGtZl9R2JY+RxNakrz09tVPLikpj2xNEkhrFnAKAATRl9bIMgaJxmWUbCoCKUWk75FWvlmP26Ga4HlIx7yDly3Zs7D/cDd3QOXl+ecXbRJu48ktvZHV3zlMR+vVY5qDrV5OVuNjiWSo4FqjUAGippouUeld9YyZ5ZF1RT9KoVvMt9M7NS74TOOI8MQg3+GfkjFdlLmhDUYa+naJuNQGT+rlY+XmP75Krk3zz8JgCYJ5Z6A8lrQCKUpXbJJUejJDRE7KiZtrspIieec/PspQVwyTHzwzJslD7cx39yFaEodxD+qSMwx1X5PFqnZrIu/a1OEgWQFaZsZRs24v9+xfrjDOcf5xRnnFzN8qqoHJS5BXpTpEBLH49msR4xRLJZCssUyEfLaCZExzVemMPyQ4hC8S+VaXWKW5BoZeSNSJpNtojuv30UYt524CYtyYVB0M5NcKIphcIyDx7vA9sExD4GhuSMEmLcrPvzoKVorNoc7Nod7GtNyfrXED3PWDzsO+wGFYbM5AAeMMZxftlU8SlyjUamLoQjKVWGqpjM83A8slqn6oRyeikapdCZCEvi01iiXTOViFVZJGoWK/lQqgSoWonxmE26JtVL2TgyvIrSUoxI4OMvvvL3kn5zfo1wKdPYxqPHQj4zDyG5/YDgMsdS1VnSzhrZrMDY2Yxr6gcPukAmCUimG4D3XN4TpFyJKiIFIOpSmBWIC0SYSsYwomUCHaiSy5BsPetJUM1EX3191D8Iw3k3hjrXh+GH04fu9wVwc8NplS4UwEoXK/kmFysUjaoNE0W6KCVcQWCmNtsWUF8wIc/APM9TlHlKjC4n2zww4mdhRMc0owsUjyJygnpcixFkAleErZutQfS7PhKkv3yibA/YkT7is8jGxztJ/3pfJlgBg7ZztxnFzc8f5+Yrziy5q91VK4+QdIYOWypWXNbD6UtW/j6566uVHkvynt5aYhHJTYeblu/cHYxUcE8JUd148jkHJga3eM/Qjw+Dy/U3TZGavdSkoc+wGkiCx42W/f5aTheeHpA68pNPFGJwhZX6ojFsqPxfynjjnUgBgJRmksyPaa50lU8PLh6gFG93gBstmc8eT60setm8ZhqEIZiEpCkbnnHtplCOCK0Qt0FhL1ywYe82rNzc45+i6FpRjsVQM46ZWIQjZpCHCcmIsKMbRs11HP+5yabNmIkqBCCyiKEgFuOBjIOIgzD61nc1JYUp6zrs4ZuKijmg+Hg8GQsB2UQAbnEOHyJTErSMKVDsztLMYcDkMnsPOcdh5ZlqhdGDbP2D0jhhMHE34o+vZ+IHGznjy7BzlW37+2Wecn53x6tVrfvEH30fhMKZjdIe8f0an+XlNY+oMAFJ8gWHoE53K/wnzpqLXouV7LDGdz+pYt96pgCK6RCVLJKZfekyir8YWxqplAqRCZ5BjJYDcRVNRxe0k6+y6b2JWjIJRe/CBQz8wpCj87WaPd562a+hmHU3bIC6YcRizD1+bJIS0UUB/3/XNYPrChLwUqPE5QjczUB2j2GM6R8hFGGpXgETHZ+KWJOdK9Abez9xPTi9IO8fybAgQEsPX5wewLudrR8aTDmFKnVKK2A6YQqwIVTc90oFPVE9qpmvxWaaULe89oetRQePvO9TZDkTYF80sxGYh694Sgk0ELUTsTg2H6vr5x1cGj6pYWVq7MEph1DoF6k3M+bUZV7RmVYotkXejcI16GvKrtR37veL16xtWqyUXl3NGt50IbYWhTpni8VgTAaf6N98nAketfqfb4lb5yd6e0jiz1UXGO4lmajr+0URLAKAE+TxmdCHV8HZjDEobhiGZMaOW0rZNTsWTVr0nfQ+1XEbBnxzoVTF1jowCWTkV83S1CBFSXAiodG5y5z8lvtwCD6U1RgAWAlIeM9egCNP9kXeGxPB9gM4sePvqntmsI5ie7XpNNBvH9RtbGjwJ09cq1pCIpYnj+61taJsV64cDt7dv6boZzz94wnqzxvuREIYsDJ+sFZ7nGNe528bUvOXKZr/ExH1RMX+EDiTBNaYYukhD0vnPG5R6jLgQc9PzTEIq9zpqmqUHFcvz+lHSajXGuBJ/Y2IlPGmY1CU//3Yz0u8ds2UKnkxByLGSXklLda5ndAc2d1uePHmCd45nz54yjo6btzcsFjNW5+fsDndxbSpW5htGQ2tEhCnCrdQPcC5kq4SAm8qKIvQjuhc1Vhmc8Rgf/0cblNaxZr8TGqxSI6qowYsyWM5XVetFqUr+nN4XUt0U4Qmxu6XL9G273tH3A4ddzzg6ZrOW+aKjm3fxLHjPOEgvgYjn+cwmF8z7rm8G0/caRovS0UQ5iWyEHHQkFeHEpyMNeWoNRoL7IobCI5X+PdcpbSJ/lywGQvDDrsEfDPrigGpip6fi86k1sXSQdcx1zyl7IZVnDWKajwQqR9IrRdDTufhQghnVvCe4GX49w5wf0AkpRWtZ9w2/+dl5NrkD6OBRyjFKL/FQWqoW1fSYOfIIJqr6zIhVIdW5LmlvJdgmw7BWwzn6PI8dT7XRFu9aXr54wWIx58n1ksGt81xlOhOmXjNuSrBdfZ1i+PJMXvoRI0SYVGKSGoVKEbrxHmHOkdiLaT8PNnld4ZyTmakiwDyalDBYRfLfx6ppY2raEk2+YG1qNCLBZ6b4qR+h9PuOw6kjc+J+CTSbCiwhw9ykKH6UFJjSSJ62SkQ1aEUM+iJJHTXISu2L4ElBXYXpu5Rv37VL9tvo4ri6fsKb9eegVI66t8k9ZrSJkdapOiSKHLEPisZ2SN2H3W7H5eU555dzDv2a/W7LctUgSF0LLcfgEYYUkt/87LyprCpFmYlm7mi+z3nvKbZJYOuDYHF2xAmwK+voVCHxLoCK0eNZ/FaRFo3eoVLbaqNKEyFjSqVMBczmhs2D57ANGEveFIWKVRBNYcjRzerZbLbstlu+/e1P+clPfspiseDu7oHV6oxZe86hfyB4T6NHNn3LLMQ2vTXktInjexczC06muWQJpygXSius1niT6ty7lLIpNDiZ8SPuRQHdSFxYGieWpZ7SCx8k9z9ZaJMbVjqGfutsh7UaNzpC8AyDY7c90B96xmFkNp/RzVvaro1ZFanhTn+IHVKb1qIaS9M1mf5/lU76zWD6OsDDHM48tlGZAHgVMkEtXch4xPCznJu5TFZ5OVarjgOc6s+F+R5fSqmy8RAL7+wbzMWBYKKEJ345aW0qSJJ992o6XmFekRA2rSVKsirW65elUBG62tqgAvp8j7+bETYd6nxApXQlozX7Q4NSiQGk6mRigg0hEHQKogmK0rU0HQ7R+CoBRqYjfk+lFAadtKVo1o+5+bos9avlrBOXxGws+OLztzRNw9Nn54wuVTg7OW5h/T5pinEbi5m9WC0KoQiynmq62VpydMmzE40jj1OZ91W1v1RjVagoTCxH4pdHHwkegYJTgWgSHMaR/jAQaqEDUi+EVIpU62zK/LqGrT+KAUzuNcqks1P1FzhhDQk+llAtvvrU+U1FwWBSHrdyXdRxEyFp1hLg50OILWzVjLd3N1xcnLEf1zjvStR9qggpKaRSP6K2qCil6Nolh13gzZs3AHzw4TO6macfHtjveoxRKcBOdiU9/Q6YBcjMRjRWOceyXp+YfbRWhGJNkjGCmP8r0fZIaM5ULkjpaEB7lPKxAY/gWIhmfgkCdAH6MKCVzgWb2qZJKZxxzvOF5f52gKAnQotkQBijsK3iwJ6r6yu2654nV1f0fc9yuYxWFwLb7Yb1esuT63O82qHDgMKy3rcsux6jxXIDhEDTGIbBY6343AOpvdYJy2R8UBP7H2AL3XJDj9BUY3RWuKKvXk3wwDufWypD6TfiUs8Gm9oqS3qnaQwXc8cPnu9id0qtcKNj2OzZ7/a5GZxtovYeiCl5pVOgLgKXjbhaz+d919di+kqpS+B/DfxawpH/fgjhr5+4788DfwP4F0MI/0H67F8F/gcJv/5XIYR/M33+BPj3gO8APwX+2yGEm/Td/wT4lwEH/I9DCP/p+ycYUPMB1kvUxQaUR3oY54A9I5pjYebCgIKqtb8TqiRV8N2k32d9B1UkfKUfhqk1IRws7NpYac+WcomlbK2USlVTeaMi+AqVI0slcCnS7xAbgqRxsqYkc5J5CEPWoM72hIc5ft1gzwY00eQ+OFvlyCeEStwl5/2qkLSK1P2JIslTTX2iucPERGqPzPqnmfLRdr9jl+Rba5bcvF0zDAPf+uQDnN8SstZyevCasdfENcPqxLOPRoqy1PQjVZjNo6fSYiV7PNfrPx44kDU2wpGpMP1TsDoRHZcijNNeiTYfi+24zPClmp4xGtvanI6XafQ7IfaPd4WkaclanKtMzBSmDaUD33G3M7mixag6e6GyIlT3yHNytpRStM2c7aaPfe1XDW8f3tAYm6yDSbtPpZ9NskSV+YO1FqMX3L7d8vCwTsVnzvFhy6Ef8D61ul3ahAshPx8tD0e4Ibb5EAuJacWjWIoMQ2LNdh98Lh4ExHNNTYsk6E+emo6RD53ATnsJK8hCUx5DLC0pUNr7EXeIwdJ9M9CmbAYx/8/mMeBssbLVC2NdkdhNznHYHdg+vGQ+n9MYsMrGoMfzc5pOs9/t8d7z5RevefrsCW1nWbHn4M7oXUsTNlgT/fgoYhT/w5DenU6YqgTiNA8XfA7si/8H0CUqHgVqGGOxHB9iXfwgvUNS3NQYhYaQrAUEJhZmKSIV298qmrbh2Wrkk8sNl7MRa5LrNT2jtWI263K569miyzUgohAbg6+7rsU2Nses1MrCV53Xr6vp/1vAfxJC+G8qpVpgcXyDiiL3vwH8p9Vnv0Zk+L8O9MB/opT6v4QQfgz8a8D/I4Twryul/rX0919VSv0q8N8B/iTwMfB/V0r9iRDCuwsKK2DWg9P4uzmcbQkqMs+suaj6cCUApY9E8z2+6mCMLBW8A6JZIs7PJs0jmem892jXErZdqrTnCMnU40LMj451waUdZzLIJWafNWTUhCCKSUfuCUkarwu9iOABKpvgdPL7eBswFwPursNvFeYimjNfbTtU9l9V5l2lCdpkRIdA8AqVekfXgXUFbMUEFt0HqV571Sa3yp79yutdDF8B1rTsdj6197xCm5jj+v6rSFZaqcn4hcEcz63SQuu/3rUENf2uBIhFoTMWnyn3qESlfCLUtcB5bGGCVHWPiuGl8rBeGL405UjxIdpEYqxTW85jRj+d6x9Ni/86V02Es2YeUoERFxvZCBy8DzEAN6jUHOXdQI5CRPxdh1K2+nEMRSwta3XHfnfPfD5jcIdcbEgp9SjOpBbEVYCmmRN8w8tXtwzDyPXTK5bLhsE9ZAK9244Yq2kanTXq7A4T4T4BRBEmZ9V7CgOKs87/xr32WZOX/Pt4g8q/F7//9MoybW01TAvLjEMXN4QYmqAIlkKn8FH46FNsiHW2CPWdYffg6GY6B78pwNqYetjNY4+CoXfs9xvWmzWXV2d88NE1KMfd5g2jH3ny7IL13Z5XL99wcXnO+cUFM6fxXrEdz+n7NTMbrZUmafjD4Ok6M1mvADPTKZ0OZkLyOitKtmZw4HXAO5Xa8RYBKviQrUwirMqllUaZkPlPa+FXn9/ywbnL8SYFdUWRE/inRlaNzYGoLtH8pjF0s/admv3j3Z5eX8n0lVLnwF8A/qUIvNATGfjx9VeA/xD489VnvwL8jRDCNo31nwH/deB/DvxXgX8h3fe/A/6fwF9Nn/+7IYQD8BOl1O8ShYZHloV8BeIpXOzgYQabOWq5S01l0qEJoq0X/+okaO+UekVlRv2KNAi5CvFXmeGHEAiDIWxnqMUAzRhNQemQl5SjgDYlWE8QqHQTK8RRqeJHi++Vdca5h0DRzKUBhJIqZzLFhOTaoy8G/F2L7zS70HK3t0j9j0yXktBgKZpUiCH4uQjIMRxz+hT6UdU9o0u5XQli+cfhLVo3ONfw5vUblssFy1XDMK6rcU+N/viAvJvR/xe74niSxpN12SyI5oZIYiKZwDEcD1QRsEKRg3yeGH4s1RlyCVrR9qOp0qBM4o6q+HtjBLwID2Eyx3fB4r9IUGt9uRR061wsa3s49Pm+GC2fzPmmpHWSifL03XGm5bO41iMNV6QNRYpVUXjvUpragSY6oHPlNi1MoZq7Cpq2XbLfOm5u3tA0lg8+vMY2jn5McSPEErH9wbE6bzJMI1FP0fZVKeGS3VLOsnM+CmWiPCD7XNLxgpy7JOjku4QPJe03kcC8lhIbUZ4TZlOsTUn7reblUzBvtPRFHFJWFesEnmEcGFVs/GWtRVvN5mFkeW5LRkn6N9ZQANVpjLVsN467+we6xQalFaOLGRRr/4blxQVte852e2AxX/Dq1SueXF+hleJ+3zJYzaI9YHRgNjfst46m0Tlts+BgOZNZ+FQki1ucl9FRGLEpuyk2aAqoUDURE6wKFFO+wEoUMRXX2NrArzy748lsJAQ7ocEC7ujXT/RdR/ruUjls4Qdt26SA7nefu/ez/K+n6X8PeAX8b5RSfwb428C/GkLYyA1KqW8RmflfYsr0/wHw15RS18AO+MvAb6bvPgghfAEQQvhCKfU8ff4tootArp+nzyaXUupfAf4VgCfPLivGv4ftHHYz1PIwhU2tvaQUOJWJwGMiKwLcu/z0x5eQxkwoVTTvBK9h36EXI8ymzRDEb2e1BpP8N0lrO9YMA9LaM+beP9ZexExUS5CR+SujinaZiXm8tFKYFtRlYHjQfLFps/9SfEVxzSmzR1XlLFE4H03n4vkQwlQHBkqQXvRfpep7lQXgaHumQH3Xl6J1KYXRHW40vHl9i9aaJ9dnjG7z7nGPX1Fr2Y+eep9t4etdilhRzVfBmnHoFAuSDn9hiuHE8GHya216jW1gK80u+x+TNuOj7882No6bKpWNTnzpRTh8rCl8Nf7XvvP3wqGyAPlU+cyHwDDEnHjnXE7Ti2mDJYsgrqUQ6sfaWy2wyb6WOIqCMGSLlzFRCBr6kdW8JXoUqUy+Ku9RPHctVi+4u9my2Ww4O1txcbnAhz3DOGQB47B3bDcjs4VFGXJQncQZBAJK/LNZY4uuHqWLK01awoplLQQZK/UUqGlFpSg8tmcfwWYiS0YYpYxcJoeh/qlIeOYJrn5XlhFycTIIjN4z7g+0TcM4wm4b6GYp6l+XoMz4tuhOmS9gfR+j003KPNMqKhWbwx2L2RnPVk958eVLzs5WrJZL+nGPD577rcV5zbI70HYwDp7tZmS5agqDriwgxe2YZpCsfNIdT2hcMBAY0cHjMowq0iTMvdLe855qxbPlnu89eWDVxlgZkvBV30sSxrtZOynC4wVHUGiradoGlMI7XywtaYwS58V7r6/D9C3w54C/EkL4m0qpf4toiv+fVvf8m8BfDSG4I9PjD5VS/wbwfwPWwN8Fvq6ttb4eUd0Qwr8N/NsA3/nBJyEzNwucHWA9h10HZiDkVochE9Zy0KZQyvw/REAnC/ej2QhhPMn8s+k2AAa/7tCdi1r+0WqUThrekcyRfbZyqKnNNvGURc2MwjhFYhXtWteDlrztfEhJ2n9iyu0iFqp49YVFzyRYamp0V+n/mKurUMolE2xM75nwLNHs0zjZv6VSARUKgymHcgrn05doCAatmmjiWw/c3t5hrOHZ8ytgn+ZUb9/7bAnH302ljWPdW03ugXfFepTRhAknYVNSRlGYunQ0nGS8NV7miOwAuVlJ1VhmGMZJ4KjWOlcU00blIDDpHFcKQPEemJcrE5jq73edA/k+f5YCCqPAEXFHtPys3af52MbGCPp0llJgenrpdK4nCd3JBYUkHER4u9Azn8/YbHZcPrnC+UMmCcX0LiWiLW60vHp9h3Mj10+fMF/oFCRafIHOBbbbkfnSpMDiZHEJPlvExOQuAoki0i9jDDrVBGhnOheZSTJHafrjS9T+tFNcBv4JgNRXBKDgEErcO+EIv6duy2wtTNG7Yt6XPRWFIK5Lov01poH9XhNIrg5jMDZVWhTBlOiubFrDMIwYq5I3pzBHYxrevolV/K6vr9lut9ze3nH15AKrD9xuFXe7OWezA7NFbE502Dtm86l2nBm+SgkPcvZEqQkxgFPeLdq91zHNMQvVlPPcaJsRUSloteMXn9zw/MznnhWFb1RblQKsm9bG+IzRx6qLaQ+NjanmtolCcEgCv/d+yjuoirO95/o6TP/nwM9DCH8z/f0fEJl+ff1TwL+bAPQU+MtKqTGE8B+FEP4d4N9JgP6fpfEAXiilPkpa/kfAy+p9n1ZjfwJ8/pWzrLQ+QoDVHn8/w28CLPrYnzsJxDkt73gIKekpvlMDmbocE3WhQBPtLFkGEkHBp1x44zGrIUvqmRgK804EuiamYrKrswsUqcITItFVE0rMv9a4suDAlIiJCU9phUGhUtqc1YY3YcbNTnNmwXZThi+rFEQTidjoyqc40ZiL4FBX15sKEmoiRE1eVN0i4xnT4p1m7APOwXa35bA/EIJnsVhw9WRJCHtGN+YDGSZD1cz8iGskJhGUenT/I7mv1ogSgXtfTIJPhNv7gNKhMiVO97HWhGtQiLCQ4zkSoQyBKu9+jNaExExjMJrKfuGgQmL0SVN0MYcbKtdCVtmyoXdyVP6o5vwpzArDd97l1YVQqkY676vWs7YIJIFoas6S1/spm+zPxIgna0jbFvcjpkXd3z8wDtA282QdEMal8R7cCNt1z/39DU3T8MGHT9Gmj21wJzgS2G9judy2M9l1J0LWpAFOLTilCeVOhsRiQ5GZC4ONAbOR0bvKxF8Lle/T9KanWSkRwiozfiUlC8zrWYqWKhbJyd4KbmqF9PcwjY5BviGgrOGwT+7MxmNDyAqBqbJ2mlbRH1TGcRAFwmBVx3r9hu9//3vc3d0xjiOHQ09/GJl1Hderke1Bcdae8Xa3Zr6sceUxzghPmJzBJAwoYs57IPntVYTZqFUKnIz8QmhpKbwDz5d7vn95R9cojK1TLqcwjuWMHSYVUHNDLLfbdbGhUtNYrDU0XRPHD+RgyriiQhdAcv7ffza+kumHEL5USv1MKfVLIYR/BPxXgH94dM93M8CU+t8C/+cQwn+U/n4eQniplPo28N8A/pl0638M/HeBfz39/D9Vn/8flFL/C2Ig3w+A//wrZpm1hMw4rUevDrj7Dt263E62nAg5+WkDTpjClBLzSc34M5aUe6mUikDs4BTArxsIAXPeZ4Zfvycfksq0O7VCkJl5zeQnmhMVIazuJck1OS+/inwWcm5yRLKhMRbnO354s6DtYLd1tG0qCHJkKlQiMwUdtRPAa1/Wl+4XrV6EsVO0SHhMfS4FkeWBWBCkI3jLdn3g/v4ul0dtmobz8xWLRYdtAoPbxoDIU8xB1XEDofxbTlDZzK/gbUXAqZi9oFQo64rD1+b2orXldVK0g+k7iiAXialOxadS4RHqNrhj7gEvleO0rWrLB5+1ROdKX/i4VcW3nHEkT+uEcPxHMOWLH7usqHwnhNCm2BQ/xgyDpmlSnXc9eaoIWnmUo7/fO5lySFX5CAJtF2uZrx+2rFYLNpvdhImJ20EpxepsycXFHBe2DC6V0a3mN/Sp2ct5kzVB0cb9kbY/mV4aJTNyazFZUC+xPJKiJx3hSkperVDU+HQs8SQQKLJyE83CKoNILEo1rayFiWydMOQa9eJCijADj4sxO8lE7UJA60AwgX5vo9BCyNk7NW3WGrSB1nsOKdo6BhU7XDjw6be/xTgOvHr1OjfwUUrx5ReveHI+51/8Jz7g7dbwdz/TvN7dMmvGx3DIxFoEXFlykXhiLJXHaENjqnTnlNoqrhWjYdU5tHJ01vHhas+TxQDBJnhVNLlSHiOsUlOhqs5/rlmidUzHsyV2S3BFrIEytsTs7Lf73HL9XdfXjd7/K8D/XsXI/d8H/ntKqf9hmvj/8iue/Q+TT38A/kchpeURmf2/r5T6l4E/BP5babzfVkr9+0TBYkzPvHcVmZeqwgQVEBqHmg2EdUcwuxi8lJ6IAXqhaFSZIBQ/8/RgPiZytSZd3xYC+E0Do0ad7Sc+sLpMbjykJBMeE5PsZPwsjuYpAqqk6NTTq6XJapxCzCOzjz60GD3f2oZ+bPnxmwVgWSxiystuO3J21qJQucmO/KMojUsgthPNKWfVnIupb0qgQyDfX8thU7O2wpqW4Ftu325Yr28IIcRiO08uaDtLLCPq8H5Ln6oGVfLSlI8nypU1bJlIPTNh5LUcoKb4UKEKIkIlXYu6GEjcX18ad0y2qsSUiEAkoxffb/rblWC/IOtTZIYUm3+EnM+bg1fTefAntHvRQBW5IGOem+zhMcb/UbX8EALrhz4y1SaZqZPwarRJOBJQyhBGlyxP0Yypj96VA83y5yeEkUe/FF6vQg39pNUqjTUtShm0NtzfP/DwsKZLhVBIQutqtWA271IE/sChv09uv0LMZa+GwdPNTPTjez8x68d8evHpy0QL8mfG71z8XJOzSbLgEKR5jssMX3DimMln68ixJFv3hpffQsgWBSGgIuuHCrC5QmYF4Gwk0pWl0gfG4Aq9UKn6n4oK2egMjA6vHCblsAtt9AS6eeDPrh743buWzw8W23iUg3v/lraZsWgvmc1nbNYbPvr4AzwDz88sbf+Wn/zwLd///g/453/wjL/zc8/r/YDWin6IqbvV5CcYIUxUgvQiY5XSzjbjYFABZWDRjjxZHPj0fE1np/wip2A7n4XwWpEhiFYezfcQCGN8Jvrt43wk+Hm6AyLUFbo0DAP7Xc/9zQNfdX0tph9C+P8QTfj1dZLZhxD+paO//7l33PeGaDU49d1fA/7a15lbfCABPJWInfiyu54wGNymwZz12bSXW/BWYroqJ6c8X0lVZO3u0Xwn2p7fNYS9QV/sQfskxcXna0lPqdSWEbI5Fsi+aI0ur5M1JolYfP3ZfC5R+arcJ9kJWYurGL5Slre7GZu+Zd133OwbrLbYVFv84txwe7unbT1dJ2dXZZ9XdjkkyiBTE0FAELIm3kJqhEUKw68VbbmUUlgzZ78LvHnzGoDz8zPOzudo7RjdntHvTu6HzBUqYn9q3yb3yT9pjgmOopHLuDJclvorQhnXVMh5CJRgq1ARWqWStp5HxYfC2EQzFm1TCnzUrp/gimYgbVbl90g4fRE4Ki0zM6GcyiYZAxQzccLziKr5l8neHP9+rLmWuUJ/cDSNSUy0hn36JwnDRlt00rCKNkSeTwm8Knsy0UCr/cnCUbpJxGOd3tnYDq1mbDcH7u5e0/c9Wmuef3Adu72FKmILh3M7+nHMJb5NSluFFIybJtzNdKp8WAlaScASf7lgSMQRifhOk02pvt57xqzIJAsAtcWgWI2me1PvQc34Bepq+gDxe2HmkfGVQeX3U66DfBbk31Stm0AOFI2WxiLKx58jSjnGUeGUxib6qVNDJx885/OBiw88f+p8yydv4ItNx5eDZQjg/AbnR66fXfP8+VP24wOuf8Vf/CXN89W3efn5LT/64W/z4Ucf8pf/5C/xf/wbP+JnD57rp2cc+rsEc5UrNGZlSmBQwT26VGOjNq0MCs+vPN3ydL5B4XDxpKVn5PlC6eQ8nrqMMTEGDQiSXpqUgFz2NwO7xPKoStsKPnA49Ow2ew77WLb3j0drXdIRUhwRJGK1vvke1gvoPaEdT26Cqghw+gRB5xKAJR9VhK5Gch8Iuwb2FnPRg03+tkR4RevN7RpVqew0mUtFSGt/fxRKooSogDroKZv2avqsVGG6QXp9x4Ijb7cz/t4XZ7ktqETq56hmC2fnHfd3B66ezLC2RJ1GPpDWngmZaKAqa9TTEKD4bE2wj7dBCIzRFqMWvH59z3odI6SvnpyhdM84PjDWPqvT52k6qEgkAqijl0/n9HjAum9C1u5PvFeK7AgxnqbxJLFQl/KnejJOyAc7M9AQYp3uBGfnIkUS024eU0kapwQm+UoTLH3Ua5NwDpozKj3vUUHhQ3IhaKlh9jiVchx97KgWKo0mnYUQYnGUbhaL0XQzy/qhZ+7DpCZ4FGQztU0VMwus67MozZHyiazQSkz0lY0p7oWOaaEi1OQASmUgNKzvdzw8vMJ7x2K54OnTS+7u7/FsOfRTnK0vpWJ9j2wZpDBWHwIhVbKbRNgnRh2CnJSpP1/GEFjEtsJxjMEJfH2xFqmK3tXzPMLxCY4eI2wFPylkJkyurK24eqbTDdWzUzApyE19ioaqqj2Llf3wHhdiPJDcYnx0SfkQsPpA7w6EJrC8HvnOYsvH64bXhzmv+hkPfeBw+IKmsYx+4E8/v+N2u+d++5KPnn+HX3n2A6zu+PHv/Da/YHe8DZbNQ0s7bxjHQ2H4UIrpKJX3KGrlKguSsVJp4MMLz/cuHLtepb1JZcl0xIG6NTGADnKGprR8uneV8EcMbAWDcj4WBErxUiFpEsJ3YhCsZ+zHHFNgUhnh913fGKaffdlAMSOmjTSe0B7w6xn6SgKIhBkUTW36s0YCskZbriIOlmp7Tay2d9HHevrETZHDJKbl7AuqGHnRZIQ1MtHkM8VLG6/q+IUsoae5J/99nROb0+S0wSjD67VN3fQMWmX9PwswAF2rYynNuwOXl7O0zvAIp7LZtWKoteCRidCjPUtQzLdEDWwcGl6+ess4jlxfX7I6bxnHNUFg+VWM/vgSCwVC2CaTz3Jb7RIJpBS71N8gRsAf16CfCjUesgVG8rFlT0yOkI+4Gf2YMTWkZsQh++xF202mUZcYuHwvrZLTmOK6GquIbu+nfl+xOGSBoSj5mbE4H+esgyZ3BzsC+JgqqdWCkNEFj7fbkf3esVw1WBvxcBj8JM00VNxCKZWVRK0Ls/GSD14JNGnLjnYxllm1xqKURWFxLnDYDTkrQNbu/cBud4P458/OFhjrGMYtSo/0B8Vsbqs1l/2VKet0DmL2TCmIFd0mrjB6ElPIWnm1z0dMNCqJqUlLyhjK1TV9pd0rCbo8FqgLBocpoI7W8Zj5qwTBae5++vJEQSgZOltYqtofctakWqe8MscmUFvRUgpclBRwwWNSHJUJPYehz5augZHePvB82fGxbnFjx9uHjrd9g2k8Zww4B4M68Nnb3+fXPv2Yz//gFX//7/8D/syf+TP84voFL+dPuB0cjzpCTYTIx84tlSB7OYM//QFo1UYNv/e4IVa3jMqdL5ZVLfFMBW9Pu43ju3MxLRcLaNXK3DjEQL9ctS8hSEj4FeEXkqY//uMH8v3/xaXILXOBrF2LtqkNuNkAvo115s/2pPqLZYgJMYpIUTP8MD0NCLHyeJRXqfhOG10IbfEb6XSYvYoE3flS+lQrXc1ZIs3LYVHVgRPiV881M3tUPlTCcEVCF5N+XTv8Zm347G5G0yQtPzcPURXSx2s+t/QHx3rdc3bWZuGjJjlTnzSFIiQxOVSfyQGagDIxQaPnbDYjb9+8pGkaPvzwKaYZGcdtLql6OhzwPddkLsJHH49xzPCjPy6mkjWtTWa6cnd9rwiZpaGRaEhazmOaSonriBaV1DClKpcrQoOYsrWOmmNOCVOxYqMytcAYcjlWmUMIIZn4RdAIRzhUrSMEQsYxj/cKrzzeaxJqZEINMJsZZjOT/86uqzTn2bxhtx14uI8154chMt6uM0egj0Ffh71jvrDVvKaEUR/hZMa1tHyjW7Sas1kf2B929IdDNnNG4lncW0prLi7PmS8atBlx7oExafZNozkcHPO57GyRtMv5lL/J5zWEkNMfJchOLC2i2WdckTVUOkfMj0+MvzrbEz1Eq4JI8uWRql3fPhWza0H9SOwVujHhE2pyX036ROCqi/Y8EkAUuc5AjllJA4hl2qNLnBDxHGgULgl6rRlxyWbgVSBYCDqwPWyxtmexdDyf7/jAWdyg6B80hBbVGD769Ds83OzZ73d8+9vf5u7ujn/yz/4pVlfP+ff+zue8fgh0ti8pzGFKwyK9rSChoDOB/9KnnlVn2fdN3udxHAkpTmYcXWXRiXReak0oFWOwBCdrIcqlCpTDMNL3Q4zRseQYiRACylXwVyFbKoZ+ZLves13v2O8OqV7/+9n6N4LpZyZygmCI2V6bgF4e8HcLQmdR3TQ28HHQXjlMjySz+IS8mTBo/EOHWQ6ozuXjEonv9B31AcilT0PxowohLwS1+HZ09ZyMJ/9FwqwmjFurmBuvpZOd0lht+b2bFdY2NDb2BBeiWiOir5jD6qzl/u5AP3jaVk+IixCekH6fMNU0Rg6MyeCtCAKgMITQ8vbNmof1hvOzFReXSwI7Rjc+six8rWsK+CIFveOeYyEkWnA0tlG5iUihr0Iki+bmE8POxCN/H//wqZRm8B4VNKSAIhEwapOvrkzSo+Sw+xjV61XCG00yAVfMPhRzfo4PqGh8LdgWU2HSsKn9zTUgToEzPRcE92R3izl4uWroZpahd7SdYbcd6Q+O2dwms7tl6D33dw9oDbNgpxpm2pOsvx5zfaLGY+2MoVe8fP0W5xxt27JaLWm7BmMAlTRukqbsPSH07Pp1SReT/gNW47djsVxVwr8Q21DLAqS2syExAAmw82U/IpiLwJbZ8JEOIUW38hlO9fPFVZT/DyGV5+VU5fAJiHJMaThG7vpnEWzqex7pOI/AX9eSCJMjnyPLqZQP5Lwrgo4WJK0LnRP6LaudNWN2jUF0/7SLln7XM4wjh76PgrgZwSho05EaLOv1lu9/8j0++ugjfuP/9Rv8s//sf5mXL1/yo7/5G/z68w/57fYpv/vyNctuKF36JnJPSX0OwLKBv/AdOJtZXFBAh3Oevh/QaNyQ2lMrscrENDwRhI012col9fKN0alQT8jBuN5FS0E3bzPN8d5HoUGrKsLfMxItANuHHTdv7xn7iLfdrMWaOjT38fWNYPpQyaUitVU1qwXhgvGoxSEy6GYX/f3vGqkm8I+0y5oCavx6Bt0Aswj4PISfMnPR8LPk70P2fxU/bmkwEgKMo0tlF4lEI50gQa6s4Jvi9xcmHjX8mO7RGIv3mv3YcQhtZPiSLvPu1aGAttHMZpb9bqBtu6ObhbAFJn3XheFnS4QMqPLhj9aFhnGwvHx1w9APPL1+wmJlYsGTOjshzSbIltQTnNxSaz/V3++iYoHJ5xMNMmVV1C8NkHuRTwLrouoXfxdTZiCuQQSjxDGyf04V4qKI2rVSpFLMATdGwiL+90y7RVtKWoWrCr5QMeNav1SKFHdCDiyV7omBlEmhACM6YhFOIw5Xv1drlhahE5CmdVqjsHObx9vvPfPFHDcoNps9Dw8bnBtZrWZ5rDDZ0JCZV6WzopTG6gZFy8P9nvu7B7qu49nzK4z1eD8w+h29GxncwJj6yotgljuqNU0hkCHGHIQAows0VTBwDpibZGZU6XNVGl1OuRNIZRyhEj6r9VQ8OO9bLaRV/FhVZytIXX5BiHcwaNn7UFDh6KoErFy9sAqCPCVvyTSkx42uvxWrCIWTI/Eh8R6hB0pR5b+X2JGgFLPGJ+24iKJaK9pZixvTXjpPbLGScFMFaEZe7H/K+HnPDz76M3z3u9/l888/54svPucHf+IH/M4Pf4e//E//Av/xGPjDmxs6u49NbzgCYVr3sg38xe8GljOd6JEh6EDXtIyzZNUZ436PLmYrBBVN7sHFs0lIrX5TLr7QByW8Ir1POupBpPvOexrIvvrYZTLijHOOoR84HHqC97Qpr3++nDFfzN6NDHyDmD6QiV4dSKEqwhpCiMz5YPCbFn3WT/hAqE/gSTFXJOD4nR8h3HeoZiTMDhH7UwZBxJrC8MWbHP0+MSp/dFEajCVG47szYdIxHkCwIkBqkjMtt6iIQT/SbU8YiCY2trnfN3y5nvNkodkOls/uZ6WRiFbVIVaZgQvcysGF2cxyd7vHjQFrVZ6TwE1g0vcDr17ekryTed31ewS08fC3PDzsOBwOLJcL7u7f8ubtAVTg2bOL2Bimgn/8Nx2aY0p3irJlO506fU/W2o4u9Wj0JMhNzfGT3gfpnhpuSA5yIEr26XXSRCPIHhKZXtQIUhcyHzV8bWIJzjysKn76GJc+Nd1nGE/k10xSk2DpYjXIHK5XNDEpCSw4IamVgh2K1Ja2CiSVq2QqJK1VK4xumc8N64d7XnxxyzjGnPeua9lsBubzBY11+OAmqZITXVRptG7QyjKOit1mYL2+ox96Ls7POL+YRUY/RCHJE3KKnPjZZf7OB7T2FUqUuhC20YXJQzkTITEVisDjvEvafSq848WqIBa+IFyMXHI2KwVFsYgCmSpNuoKksx4xXNmTiVxb8DpUfyoBYoWTofyT76+ZeJGXK0nj+FLlF0VSWqq+AfVkBY10oskiJEhAs9I6potqBGoZdzrrM21zrlhItVGPUgODm2ZA+OB5+fAzGtvwq9/+p/jN//xv893vfp83r99wfnHGojP8xU81v3v1IX/7s7fMWo3zPeO4rywTivMu8Be+4zhLriwvuKIUjW1YZqADh8D2cGAcAl6lfilGQfbzV3xAhBnncgyAnPvsmnM+jlMV/AlEWDjnYhvepN23s5b5vMNYw/JsHlP+3nN9Y5h+CCFXyatYfjpkIZ8SpUGd9dHM3zroSmWw46sO5BOGn7U8D2E9Q6loPYiUML1fDnQoBD2a6op2HlKglQTkaYTJS1McifZUmXhmzctLMJHKJ03rUv5SE2vcN8by5XrFl+uO19vou7em1MIv5nyVp1+ogZqcYmtjsZTDYcTaJj0lGmIREA77ATe2fPrpp7xX/aiu588ff/bjH/8O7kndHrhi9Jl45a2pfxxdsdqXMR1aN4xuj3N9JQwUElcpN/XjRbhJjWGGIZrmtYpESXyAxkhHwjii94WpCwUPgdgGNgtACfYBtNWpznhgGMfUcCXmrSstlcFEy4z+98JgqkqJFJ/+MWwUyQrmhcnEoFCTYj5UVFWy5plL3yqqktCPg51q+meMRWuLVhbvNJv1gYeHO/phoGtbnlxfMJ83aG04/KyP2SjagmhKoR4wVWIzCzbrnvVmTZ+a8sxmMz64ekrbBfpxPcWAytIU5GcSqI0u8BT4yd2zRartX9VVyKsOZRzR7kc3ZktL8eEz2ZcM+cSJQyhuu4m770izP76K/FrHxFTCXP5TvWuIcl/h/VkxiYJazfjL3B9PqjLuV0K/AFMElNo1I1aWWGwrFp4BsptKgh5Xbc+ssblMcwnm1HnSOilOqFgPIMZwxXVIUNwfvPwRXTPn4299xI9//GPOL875wS/+gN/4jd+gsQ0fPXvOf+3XPuU/+/u/z5/9wXPuN5/x+289m0HxnavAP/ERtKnng0DBaJNjpCDQtY7BtfTDgFUjox8JLilyRGtrqbmRyEBdJl1JGfT4t9zrkwXBOQcqugPGwXHY9xz2Pd55+kPsaqhNbFY0m7c0TfNIED++vjFMn1C0jxphxZQZtbIEaB0wyx6/aVHNPpn55fBUz05OrUpSf5KSN7OIfOc9YrKWYB95Npu2K3aSUzq8itqLqoJGRBoULdLEQBDR4uO46V5dNL965gqdiu5YjG65PcxobGlhW7sAIthCcVFDlq7TistRV9DNDPv9yHzRFCl+aioBYLlccn39NBOSr3+Vsf7gD9oT30wkuvTO+keyxCTAGNNgVMc4BN7ebhmGNRcXK+aLJf2woaJO9VCPh6+sMJDM/omIi4QuWr9C9pAsgFER6RCSwBZIucyiyZIlfSFaSlW+PzVlIirZ65XgmWRzUPz80oSnWHAKYRQh0ruA0VHTkEBPrXSFtypFIou2WpiD9E8QLUQFaNoVw0Hx8LBjv98xDD3eBxaLBdfXlzQdEAZGt0GpBcYYRudR6lg7SVYC0+Jdw4sv79jv98znc548uWQ+b0B7vD/QjwPHV40PtURSE1sffBR+koUjCwghlJg5yGceyBH5Us7YJe1e3DfhERbV4iQZbwqjJ//MjHMqb3/F9Z4b1eM/w/RUV7eF6d/C/EPRbjNUk0CYgxvFLZGtGGlBIcY8GK2TJcOjraGxFmtSHfkKX32IDbo/PAs0ukGhY7lmK+9Le5ZgJWcNA47IHMXvPY6xCdgfvP4dvnP9y/zyr/4Jzs7P+b0f/R4ffvAhv/wrv4IbR37rt36LX5l7/tTHn/L6xvFLzzzeKaypO5Im33zueAghuUydaWn1SGsahmaMjN7FLpZZMI9IVVXYK/RD0q5V8iQqp1L8jknMP6DTesQFF+lEtCC0TYNtLN2sSXX5A8f7e3x9c5i+SmajiUacmFfStiTVRilNmI/QG/ymQZ/1ZNWc6nlpXjAxDSvYteAs+mKHskK4VdYkKhUhExGtVSo8QSIQ8QZJzxIBQwqxSICRqYo7xPHJv4sgkH3piZkbpbndz/jR6xUuiABQWthOiI5QBtHWQyFSx6hjrM5pVBKpXUv8p8hPCIG3b29YLpccDnuapuX+/p5h6Pnww48IwXN/f8/l5RXWPkbHY5IpHxT9ptJ0kgZgTYciRpDf30dm0bax/vXr12/58KOnsexr8BQoZLZYGMXRpZQ0GvJ5HwSW+b8i301gXdxMRaOTvyFqkV5q6DuX+t6r3FUu4qXgZ7VvuaBH/DPiT4yLFhFULLoCQKWjJWgSk5DcCCY1SNKI1UDepZJlg/LJEWdSWjP2is8++xJrLV3XcXF5znIxw1jH6A7TEqHJLeWqz5TSWNuiaBgHuL/bcn8XOyd++OEz2pnC+QPDuCO4x+mEj/as+jf/mrTy2C4VfML9EGoGH+Eqpn7BtRK4WRrekL4rmu+Uadc+7vK5qqTqItCVc/l4LOG75TNVDXO0FxQFIWvax7B5F+iq99VnIVQ4JJp1PnpJAKhdq8KkTZIgrDFZuNQpij0KCh6tDd7HIjifXmpmTcvgRkav0S6Ww/Uh4MY4wWzBhegjT+V+A2QLVtCKfuj50c9/m9n+S37w/V9ivV7zySefEHzgiy+/4O3bt7Rty4svH3DtU4J7RWcqd0IVNC37I0qk0Ya2bViEGUpF19C233MYhhiAG2K+PZAbbOnUY0JScieCXoj474NLgoBn7FNg6K6nnTXM5l0WxpRyNI2l6SymicLE+4oByfWNYfoCVKg0dCFaR6ZqYeZqecDfzgnWoOZFQhIimM1tNevZtdA3mMt9CnqamueymS9r64rgErKEGKEJJQhLa50IdSm1GqVKm19ZV2gr6yrvlMA9MetrDD9+PWc3GKx0ucv3k3W4yRXew7wnFo9Q3RNqyJy8vPf8+Mc/RmtNN+s4Ozvj889i/6SmaXj16jVt23J5eXXyeSG2Uagip71MxY2A0U3UCkfD3e2W9cMt3nsWizkfffSM2dzinOKzn7/gsB9ZrEzeiwk5DNMVBUopVC2M2ydvZog9sMV6k0Sw9G9kkFOtbpp6WX4mc16uiR/nZXTs9CX52hpd6tkI860seaGYF7KFItLm4+jqSFzqwL/RORprs/CitZpYhiradPKK5WxnvHgVG9J865PnKD0QvMP5Df0gLULLIFpFq8k4jmjV0DQKN5rUtvaOvh+w1rJaLbm8WuLDjn7o074cMSI5qkcssKIKGY+kOEyssjbFbQmiLfRCzP+hOt/TIkeiC9R4VI5MwtSK8U+4bSWQTZi7fP0upS2kLyWt9x23PZpPHTSRP6/N8zLHghvTOYV8RDJeJMtV7aqoAz1DGkAyhWq6pqBYyEyE8+WswarUc8M7tBpzgKRpTHS9uFjP33uPDnXFwBghH83jDtVYdAuu3/P27gU/+OUf0O892+2GH/7wh/ylv/QX+et//W/QtS2XTz/hfnPF/f2XKL2nazyNTkF5IpxRaEKszR+YNV10V7QGNhrvN4yDy9o4UFomR4ZUeIvAkhLX48Xsj2I4DEivDdsYtFbM5i1KQRtKdoA1BmtSavH7rfvfIKZ/TFhFEg2PvyMKl6B8ZPzbFm1dYuJhqoUF2ZdA2DeEQ4M+36cGPrU4L4yc3K2vaPAlOAMk8t4XIuJ8sgREU66CicQcJ0/RJAMp11slNU6lansxQO9h37A+GNqmmPXr8rinCMRJ2hKmnx4/l5nMV1zWWm5ub/A3jqvLS7TW7Pd7hmHgxYsXLJdLzs/P+Oijj08+r4imss3DAIpYL4CkFZoWRct+N/L2Yc1ut8cYw9nZirPzeSy8MuzpBwg+RrUamwIq86reL7ycEoaiRSC2wTTJVIkGk+s8VwJnvZb0t5eAwAjInN4lbKppGqyJknsp4TplSDWdrjWRKBykuyWYlMgKlSLjJEk7I+F6cAGvPK1tcvGgCQOS85PXEV0oipbtduDu9g37/YHrp1eg9oxjYtCVVSrDLwRCcMznM16/fsvrVw+EENhut6AUq9WCZ8+exBajamRwD1koFigJf8pnOquo5HNRTT4JtvFeT6pAqKoMkUAqTjTdtxI4qzJtyJUTVdy/OsZkuuVqAjfZ35B3rt5LVTT58nhhxLVQAbl09ImQ1hPzqB98dOfR1+ERQTgiBYUWUZh/bQnwVXCdWGDlNc67JET52GxJiaAMMxs4axt8iBq+Irpugo7Bp+PoGMaAd5HOaqXxyqPRdJ2JbpfR52JUkh7n53tevX3Bzt/wg+/8KsMw59f//K/z4x//LpeXV9zf3/Nbv/V3ePr0Kd/6/q/wO5/fQhhYdiOLbmDRDiyaAYVPMTlJ0EFjbQxSbLxn1rYM48DgRlxftVKW6lOqnMGiVCYKlARHnXz7wzCmoFfwPgoASqvYda9taBobxxH3mykug/dd3wymXyHf5PIiocebJpqySVjaORgdbFvUWYwaR6RXlRh4UIS+Iexb9NkhVtsTAiI6ry/+5KBKBTznXJZ6RVp0LuVd2+gPFpeE9FuuXQSZsFEOV7EkKIwqUqdWsevd3aHFqMTw6yh9JsJlvrIJU031InFZ1CaoKdxLAF/WZE5c1lp++Zd+iX/wD36bvu8xxrBYLOj7nvPzc4wxHA6HR8+JVB18bNwSgNWqTWO2EGas73es128YR0fXtTx79oT5oiHQM45rxj7WSm/bFTe3O4zRdJ2NfdPzW+qlqenPStOJ5sqQ/O4uE5fYKKbk8tdmeIGv+ERDiMU4MtM/OvxKESV3WxFDJTCuIVMz4eLvzP9XdpB6ZfKZz9YEYY6qKuWryt7W+1FR/nGMOLrfeu7v3zIMA13XcXa2YLmyOFf2s9b+6jPq/MDqbMlut+D+/oGmaVitllxcLtF6xPk9Qzo/wtIFd487XWe4qCQIqyrtbLKGeF8OSAyTp8n9yJWUVS5rjzQ5rYUiQGTGn4FcCxsyrYrVP2K80/uPw/AyI67Gm3xX8egp8320+skPuf/RXSdl+VpoKQJqFOjKO2vrERCzV7TQLZ+srJFxGW1SXAUZ7z5cRZzUwZS3hhhnNHpid80xzsLoaCoPOgW0akVwI4MfiwUhBfx5MxJmD6wPmh///O/y6fMf8O3nv4zWhqurM37zN3+Tp0+fcnNzww+M49Mnc37yyvFmPeP1eoZWgSfLHR+eb5i3kqtIYtAhNy7zjWPsJNB3z64/ZMaviMpGEAHIF0FSkML7wDiM7LcH9rsDQz9AIGv5Yz9mC4ltot8/Fv7TWVj942PeP9aoJikwhdhIE5r0UATUYsTfdXBooOsRMiiMnN4SNi16Na22J+MVJI+nRQrkiEaQmyckC0Qup5j8teJvz8EwkI+V9FBW1D78xOhT329N1O4Mmp/dzPjJ3Tz7zGrSHXFLzJEnig6FwmhF8ahPfx7rBNF516W15tvf/jbL5ZJf//UFXTdjsVjinOP582ecn1+w3+94/vyDk88759msB5RSnK0arG0wesZ2M3B7+xrvPcvlnNVqjm0VPvQM4wFfddOytmE4wHa75erJJaihWHIyZOqFVQSu0mJk/9w45upbsTWxguDJQW7JHx7hGfKzYuEZx9JOMxCZfLHepKhfKYVXcYii1dYaQhREJLCsrvd+zPYFv0TgUBD7mCfiZUwV7PnuLWUcAvd3A8PoGYeRxWLBk+tzuk7j/IEQ9uWd1dmrmX8ey21ZnWmca7l+eoE2jhC2DKPP862Z/WNBRPbvsQpb8+H68gnRj/hnBaP4Rc6Xrz/nBGN99HvBn+nf8vuRYFkkh+rz8tkxDT/2DpCFdgih8ncL3Kf/TN4zPQcVFEIRWuP4KY5D10sq6xIcB0qRqqTQBAr+EyLOuSBWTqkWGn8+nfUQDBpotM3nwrmYftmYWD4cnVKYjcL5WMhn8GOek7EGnZWnNE8Tx9rut/z4p3+f/X7Dd777K/yjH/6UX/3VP4m1hr4fuLu94Xze8Msf99yttwQMPmhutnN++qbh48s1Z91hYnzRxAyY1jbMuxSPY2PBp34cUkJMyIV7iktQZVdg8J6hH9k8bLm/3cQKffsebRQru2QcHOPgsY2hae2kHPeE2b+f539zmP6pq2hCxax/8jIetRzw6zYSHZuqpQWFcoawjdX26IbUkreSaHM/lCMCW5v+EvJny0P2lwLVZmWikrIMsu9dxda1Okly0fcTCzZoVAxuUYYX2yU/fjuL0bFaCvock5BTknxxG8j9OQZA1pPXlf5HtB+Vn5E7nRvp+z6va7VaAXB2dg7A06dP890XFxdcXFwA0Pd9/lxSVvZbH5F+1dE2M4ZB8/b1A/v9nsViwdnZnBBGtrs1Yevo5qYyJUcBzOo5b27vaNuW5aJhdJu8R0VYDPkzWXeuTR+KBjgmhu+S2S0yb4cLAVKdedQURpG4xejbrN3LDMUKoxWNLdpNthIolTsFZgzLDD9GB5ciMVINLpQAsxDKngWy0Omdy6lC0SqUIqrrJinvuHa7gfl8yXC/ZrFY8vz5OZ49zo8TmB4LlfXftZVC64AyntFtscmiUbT7SkM+mtV0+Cxl5e2c8LnyVPXbe6TV6l4/OS8nhAt4VMNLLApTAfLkhB7NK0/8vdOrOI4sPb2zLggVv49jqckkMzUoDL4W5ovqPhVJ8j2B4COuS8ZJ/VwdRxVCyNXqQKF0dO0EH8uTa+UJGIxyXDQ7vCtKS0OMMxmAoGKBm9G72N8uVaeTaojDGLVgMXuX3gWR5gYXGNxIGGJ8zIs3P0Ph+eTT7/H61R3f+/736ccdv/Pbv8fDesOv/elfpL24J/g9BMX5rOfnNyv+4M05n1w9cLWIjF8riTGKcVhBE30VQ0TC0JPbWUMUuAk+B8s6VYSB/e7AdrNnv41d85zzdLOWcRgzLZmrWS7YNqXjaafebeoBvkFM/7HWGgGQoy9zwvHpS7UjqtH4dYM+dzH/OtiYiz8fUbMRKQ6V5YdAFWVdgC2+bkXS5kNI5hef/fCixRhd2qLGc6Jza0RZkUjBOmmeaNDacLPreLGe8WLdRuk3xB4EjbVZWzvWKSAiikq/TASCr5AQY0FBRd875hJpr+qZxsCs+/sbfvSjf5gEGo0bo39KqViQJeAKrE68x7vAZrNlvu5YLDtWqzladdzd7nh4WAOK1WqJsYr7hzsCnsZqnAus7weWKxv7txPdAJvtyOHQ8/yDa3zYZ1iHyv0jBLNmxjK/bKEJcR1D38eYDBTea7yX7laANQiB9yl9SCnpnZ0In1K5v7YykTiWBjxFs8y/VwS8DgaU6HEp/yp/Z3cSYvYvGn6pDS4BQDYHDFpjclDVI6SprnGE4Eecc1xcLPHs8Ynhw/uZfaFLlQCQfJISH5EZvjCNmpC9V81OcAtJIDpxR8Wz4u9VO+U8H1WE4zxqvLkQ2SwrFnP3sShQpnykhWXJe/reSDbU5DZ56LFGXs+73Fnn/8tapldh4cUgMI0LKEKXymmqx5fUJCDdmwMgZVaVtTOQ/PghuQIS7fMhNlgKIebCX8163NAzjA0NpVxtIOBJ0fkpVsu7kPF+9I7RxWI1KJUr2wUVcm0NrWO+vErWuNgS13Nz/4rFbMnzD6958ep3Gf2Gjz/9gB/+g3v+4Cdf8ou/9JTt9gUoWLQ937pc8/uvL3lxv+RsNtBan/fHGpNktVi4aXBjPFfa4EefcUhPSupGQbzvBw77nn4f2+Tu9z1udNjGonQ8G+BRSmMbS5Mq8NUCtvegsrT77usbw/QnVxATXUAZEOmy/j5LoaUbCmo5EG7nMWCvGwgPLapxqHlfLKpCc0Ih6troiaQv2o5WmqATAfalQ9o4xvr8Uo9Z/DoSNS2XQsXo+5TPr3XU7EcPv/3inFebWKO5LrhjdRozjSXM/ZT0N9GajkF4AqZKK5bLhs2mp+1MbpVaE7zZvOPTb1/H9emGcbS8evmWmOriWS4XzBeB0fVJeAr5hd4H9vuRw97zwUdPuDhf0nZz9lvH7e3bFA+gaRqD83tUgLbTaGNpm2gW321HNuuB84suRfnPuL15zWIxp5tFTf144eLLPjJZZIIlJnlpiuGk6lwi3N57htFhjaENFqVdZLYpWFB+l7Eb20QrTZVeKq4emVPergkHLsxcNAcXKoZfl4DNYC3mfJ+KnWilUVbRpnxpq2MhJ3EzfRXVMMayflgzm81oO41z49fQmo/XU32kqCpQimuk4NbksbQnWaut8FrEyCL0eI4FkON7p9MOJ389zXTTrBLPPfVdUXYLAy4WgFqTrxl3dZoqfMiWH/l9Qoyqt1aumXdbFsLk/gyHd2j7mUZl4Tdk4QKqvgGmuBPrYDKp6KhMTCMtQmiIMrKWLnMjg49BcNHiFAXA0RUc793A6Mao2btYg38cxypwL3ajE3WmH6JwKtq/aUwsWuUC+8OBoR/Rr/6AmX1BY6KypC9avvPdT/jRP/p9vv0LH2JMSwjRt77oRlZdjwuR/tXp1oRQMqiSkpZjrfKMQk4X9i4wjiP9YWDoRw77PgouAj8Li+UM29is2bddw2I5o50103RCoRmpZ8P7rm8M05/k1qsq2ETK4lY+9ayVh2PEDqjlnvAwh0ODsh69OmRtIGoRcvryP4lx+MnHtup+qZSKPmAXmcc4utSEoQS5KEogBpBb3UqxFGsMCsvP7jv+4GbG4AyN0dkPG/1idXpVxfCP4VSm/Ue+2k6z32u2m6F03aPQDKUUbRcLA41jw5vXN7RtxwcfPuPm7S3r9Zbzi2fYZhMLbyR6c9iP7HcOrQ3XT+fMZnPcaHj9MpryrTWszmbYJmAbhbVxreMQ2KwH3Mwwm1sWC8vaBdbrgSdPznm43+G94/JyhXO7QnSFIuf9h5rKirYTQmAYBobE9H3Kg/eT6olRW8LoyLhcFO5i69VC6OsqiKJJRYF0GnwTJv+qitH9f8n7j1jdsizPD/ttc9xnrn33uTDpIiszKqsqq6rLdHe1EZoaCQIEEoJIARqQgkD0pCVoJA0kENBMgASIM4EQIA4oyDUFQqIIqQlqwHZV6rJZLrPSRoZ59vrPHbP31mCbs89373sRas6iT+DF/cz5jtln72X+a63/ih5SJIaZevhThR8MFmMZel/7LwKiIAMCo0Kb5ZgQlZfn3VVihPvVVJXk5nrDcjnHufaLK/y3bFpL781EqHk/USTTeslYdC55ojGxbhwjNxpBLmbb58cL/0vr2MXD723TWP7k5/FXE2Xp3+wr+8kRwznTOhUTP2TPFtnTxHeuYO/TN8n7Owo9XX2Y6zaxfI5gxJjY6UNUdvI7GOdkzGMaZYtLwypExtwpfIXEmN0fb1hQa8N211Jq3xsk0hv3pmdwhs729ENPO3T0/cCu7djtfEhQSlABfez7IRknwxBh8XFsrfHJg7fbNRqNFgox86EuLRTb7RVnp6c0TcPPP3rOtz48Y7t7GUJzhnnVcds26f73w1lSeOdLCZWUffwX5YoxPn7fdR3dzpfl9d0QrtePi9aKui5R2sfwpZQUlaasS8/SGbVc5iRM5tEbti+N0r8LKYYXYaSdI8VTpdvviw5xcYvSQjXgNgXiaOs/D63KPDI7NocgE5LGjF6HUmObX4jxaZ9sMvQmMe3ldIxjDF0khS+VpJAKIRSrtuInlzWXuxIpFIUWaXIh7rbFTaORhGL2/vNmRf6DqduAEILZXHNz3dH3hqIc+z678L1WNV2rePnyHCkljx6fItWOBw+O+Pjj51xe3PLgbI61a4yzbNY9XWuZLTRlUYCruLxoWa/WFEXB6YNjdGl8khgudRl1g0UXkvmi8IrfOOaLgtlcc/F6x+rWcHV1w+HhElUY+kACM4E+M0GVK/voMQ6DCV2wDEM/BIFl0nOOxytCJ63kaUbvWsSSpWycIolIqKzIEz/TJsaErH1lZhKsGVvp2gBWRm3hwrxzqW0nQvgSwJQrIgItsxoT+Bjn4Zs2JSu2mxVVVdHMpln6/9Kbg6KU7HZDSE5KInJvv2heuPQ6IhlJuTN6kd4ImvazT8Mbjx5T3zMHezxdMCwiZ8d+GW36SZZvf0+DLjd5sW/MvMn43v90X2vH04xGRoSP7z3W2HJvYtBGx0ekKo4xHOSsC02avPK0xnd8i1583kbW4feLPQMko4Ebk5kjIU1smCPF6CVrZXlcr9hufQ8OJwJEPgz0zjDYgX4Y6IaetuvZbHf0XZ96zwup0vUYE3OySGWeXdfhrKOXA92u96+3PXVZsW1LtPYlskLDMHS0/SVPnj7ih3/1Y77y1YdIpem6LcYaFvXA9VbQD6CKbE4Fa1kKX7FUFgWt6VIll3ODT9YLOUFD7x3BaKD6Si+ScVVW2lNzq8jkp9BaB3IfkSZPpJSeXMdbti+N0t9fJELGRRI8pVygRoERKHrHDMiweGY7XCtxrUY0fdAOLsW0k+WfzuM/T72S5SjEB2PoW8/QFOHgovAlWaMVKELZnUiLZdNKPjlfcr3S7FpJazVFoZjN9aTRSaTBvdPhLlPuib6RSDm6N1rRc7pnE5MWZ34vrX3XvdWq5+ioymwIgVYNm43j9avXVFXJg7MjhNgBKpHOtG2HlKdYs+H6qqUPLXu3a8NtP9B1t2itOTk5op4rdv2Kbd9lIQuJs3B721M3iqbRLA9Lbq87utZ42FCXXF/dIqXk4LBhGFbhOcUnN7lJP06BES+6Wo6QgGcMXdf7XtfOx/LLski5F95uCFUaMvTHTuV48XwB4hSMdJxZ5m02NZOSjwxjMDbYiW1cc+8+1vHHhxm9tBjDh7FEKsL7VVFQFiVa65BUKkOi6J7QyHSYz8+QrFZrzs5OcHT/1b388HMVaoz7wVApzf563nfB0z1mne6SR5+PX0QDMuTgHv0+QdTTSLoRzka86YfhdwnximbA/Tp+XJaTM6X3CTXau+1p//rwm1CaGN/G4465FfF309LOZDyFuTYiTS4keWY9Qox/n3KXRK7wx/P5uZ7lxERDFjcyJwo8n/xg/P3qiNrA1xZXCLdDaJ+Z39sei2VwvhHTEPoc9Gbwyj7kxuhCjWvVgXC+O2WM//f9MDbICqHcvhswg0EJSVWU3tsuOjpdoKVGKsXlxSWrG89j//L5Ne99dclqvUIimJWWsjC0pqApx7LbGFaF4O0r7el51UCvBszO0rUDXe+TnKWSOOuRt37wOQ8qOIRVUyaCrAjjCwIFeJqLfl5GpPhz7PW0fWmUfoRLp0ZOgF0CdazMrFnwE0XGkiuipwpCgVjucLczXGEg6/hkw6QSxGPKIFgdpIYnIxw2dD4O7Cl43SjkhY9xedpT7yFqqTFGcbkq+LNPZmy7gqIUVJVmJgS7rQEXGqNEXSz2fLOoAIIiigYFcV93V0y7JGzuHdl42MnWzDRtO7DdDszmOvQ2n3Fz3XJ+ccViPuf0wQHQIkTFZj3w8uXzYAgcs1pdcXW1RkrFYjHDGri9XeGc4+BwyfKwoTNrbrab5D146tjAjqdgsSw8YY+DeqapG8V61SOlYnlwwMsXrzl9cIyj3VPA4+yICUmRlnUIzwrAGkPb9Ww3O7quR+BrY1Wg0oyKJSafOeGwZkzek8IbgNFIE9GzD3z692e5ewEa4fvk5UfFn2XnR0/Ne3nJ1fM0oZPS0FF4yFBWVBZFYmuMhua9BlG2aVVx/npFUWjmiwpjV/kUufvTtyjJyS5hLutC0nWGqgpVDFMXeW/e+oZCng7XZYjH6KXmLYcnbWj3jxgUXrzeN3XTnqa73b/dQdr2v09rMciJ9EX+LO+uxYg2TD9307HP+iJM4d4MKQoJqATjLvaGiOeIjlA0/mKYKqGSSZTEsIQfrOjwREMr/+evw4WOXv7mYqjLOUcpdhxWt6iyZNbU9LZn2BrqqkzlqP3QM8TSPGNwITEWKRJcLxA+lBW6U1pjadueIcTJrQlrKjTEaQ7mqFIl5MMOBj3TbNew3XR8/esPmc8OePbsBe++/2FqsqOk5aDquFpXHNaewj0aQSLen/Pc/EWhUb3ybXYHy9AO7HZtygfruyHlR+QIikSiipGV1RHKELVKFUL5FBD3Ttr7ty+H0ndkneem2xh7jVzH0YJn9MpD4DXY0t77Dgl8dlUhD3dE2tW4MGLfY9Ii3VuQLvRENsYvCCUR1ocVdKH9P+lpcmNMHhR//LMFr1YVRSFYHKoAG/vv6ypAUJnllzaR3UOaCPdPAm+wxGuftuC485M96ZVEp4T5omB12zOfz4CKVy9vWa3WHB4uOTqeIaVlt9VcXV2z2Wwpy5LT00PW6xvatuP4ZIlWNddXa1arNVVVcXS8BNWx2p0z2D6NbTRi/CU5nBMoLZgtNOvVgC4lSnshdXAwZ7P251ssKvrhlvs0UGyIATlDnksQfNf3tLuWru28FV7oZNFbG38rSE0zwgCO9LUkRe8XtUBEwqTMK0hDnbz5kKDnzAi1ZtB19NrS80rtUjPDwGRJbBHdcXioMMQbpcxg/aDwRSZMyGxkX6lQsFqdc3R8CPR7xsobJtrnbCKeCyhLb7RZ62O0E6W8N08J95PGK4P48/h+7GWRUXPcvTiXzw2XIRvC5wOFKo+Jjv2CXtV0cb1hn/ygyTjdO0z4bF/5p/WRHz81W4hzmQmcH9nxotIVboT8o8Gal7ImVDEYrPF6Y6KrIBwzPa7RmI3x9NFY8Ax2kXkU4PFs5dHPSiOkpO17T7OLSWiBV/qW7a6l6/oUIrO9n/cxOc7hjYGhGxh649euHQ0hgaCsC6q6Yj6boYVvMlWWmrKsWd+CUvD+Vw8pq44nTx/y0Ucfc3PdUjVzhn6DFILDWcf1tmLVlizrNhjZI1mXwKOvGk0hFIXUVGVB3w5orWl3LZvVNvWiiPLBh30lZeUb6Wil0aJCa683Yu5NjiIlh3ditb55+3IofRiVcNxchLIYlT3gBydyp7vEejZ6zJln0PTQKuxa46o2a5oQhHqY6Cq0X0wKwbnExKdCGQd4CFNrRRGyMWOSnhKSbV/wez8/ZLeWzJeaohgJK5KSUCM0P8quMJsz0z4v+yHfb/L+DQPppsfPJ1f+UiCo64auVZyft+x2155c4+yE+UJjzZa2Vbx8cZ1ibMPQc35xQVWVnByfsN31vL46RwjByekhZS3Z9de03W5ksRJjDHrMWYgJLA6pvILYbX0CTFEqyrLk4vyWo+ODVKI3ufqkI20SdoMJitI6DJ6AZ7dtaXdB4QeWPF9iGZW4V+BjjC2cQmY5Fnv/UuOjPQjdkWXkp6z8qfeaPwPvpfmb8Vzy4TjWw6n7CUYuzA0V55OKPRni1Hi7DytVxe31BoDlosbY9fR67plHaazfsDmXfy1SNYhJ8d/MZc1ejyZPUMT3GEb5JaRzTQ7n0uf5+zg5ckM+OqijEQXk5DVvuPVs18l79r//AuiBGydtcjTuuHvpfkYDMFUnhS06Oil0EUxpGyihY1JemjNCoEJlRRIx96AiLuSP5KGLmNUfzpyuLVYCIASns5b3TnqU0jjh6EznY93O4vrAeIdvNd13A9v1jmEwqQV1NGJiExwz+JazfTsw9H1qV14WhV/HQjGb1VR1SRm4KeqqppQLuk3JwUHFo8dzilJh7EBVdhwdHfHpJy/48DsP2dgWhKDUjuN5x2dXDadzwbzqg9K1COtDHdGDL8uSefDetVDUXclKbRCx7a4JvAoqhHiVoKp99ZEuCsphibIapTqkzBR8RKii5nIR1XnrdPqSKP20ZkZFHz2dNCROjpZ7SMaLXlQSwM75xRwOaKzBNS1uXSFUjyinkdPYTEKE2W+tN6vjBIznixUDUkrKsqQM8dXo4V/vSv785ZKhVxSFoCzVKJyFDF7PKJQnIiK/R97s3d87E3LhmOms/O+doRYSKTU4z7e+WXcMQ89yueTwaIaUJmXJ73Ytw+Dr85WSHByWLBYL+k5wfn5D1/XM5o33xt2Wm63P6E/tMyPqIkLPaZEpfueZ1axzSO1otwalBc1cE0Q/Wius83HniUoLAtGTZARijIzu1QyG7dbXyloTGLAKTVmOZTIRIk284lESB6GZLlxEd9n/m3SBDP9LsWmXZeTHuL0dmfXGc8rsvICxKOFwoZ2nkB5ejKyUQvhrUlKl5hzT8rzxeu5zhAUCnOb29orlcoFUA2bIePBHx/KuVouf7WvCvV28Mhg/iEbKfZr1zidp7rrJnI4eax7QimEe56IhlgvJ+9aOSH0r4rX49RyPcc9P3nC9+0M0njbcsJvOC7L9JrZ9YHIc74/MyRmNmUgolcuE6KhEpR9LaaPCdg6sZOzlEwyAIZFReWN5TMqzSQ6awScp5+hhnKfO2UnYIP57vGxR2qNNg/Hxfhvmlg0dk21A3frWE2MNoR5fCB/TF0Kkyqh226YseDPYxFqKBOEERVVQqYpaldR1TaFKpGlQruH08Yyjo8p722FSd/0NT995xA++/yPa9h2KosRan/dzPO8wznG5qXh+M0OGnDCJDY2cBhAGKSyWHlW1zIuWot9R1ztOjntfQoylKCTd0NHtWpywFIUOjH4KKSxsBe62wS1aRJlZyy7M4TBRPk/hw5dF6UPIMA1Zm9YmGCwq3zQB3SgsRYQQnRiZyJz39CIFr5M9TgPbCqt2IKKSFSm5JTJS5fGrEc71JBFSSspCUxXal3IIwW4o+N7zJZ3RCFFQlbDdWIST4WFn8XiYuirxvtN36X9v3EfsffgWOXxn8yVeBc4VbNc9NzdXdF1HWRY8fnJGWYE1W4xxDINjuxkYBpjPZ6zXG46ODzk4aLi6XHN9c0tV+iQ/1MC6vaQ3XYDn4vVEwSAnCj9eaUxgM87nXBRzENJ5pq4g7Nq2p25qhqH3it/hn19Q9DGz1zmbFvnQG3athxCl9FZ6HazuKNxyrztm5cdBHFEWkXT+CL+O1x8fQg5Pj0rfe/oxiSwpfTHW/Y70vySvfTADNghjG5ikHKQsfa09XKgiMVA+ZfYNI0ZPXOqSzapnGAwHh3MGsx718Zvm0Z6mm9gD6TfuXi/3rdnHuTKMnmN2dnfnatwEzYiOwRgDFePrO9o4vxdx3/K7d9u3ce4ocbH3xd79pg6f3PnKfx8v957rnd69H484z2MN+6TGPnE4TBuI5WXNJnCMyFCd4n83wtmEWL4JZcm5QSKLkYtEBGs9vq/UwFGxxgyaWCnR7rqUfKp6mfJs+t7z6ZvBK/ei8OQ9yQgX4MI9VHWJGhQihDVs75tIFUXBwWJJUy8oVY0WFYUsODiuOD6pqKuC2LEUvIxpd7ccHJ5QFJrVTcvTd59izEA/XNF2ax7MB05mLYNVtEbRdopuEGxawa4vsfg8JCkNShigR2pLIR3GOqSz3g+VBuUG6tmAFFuc2wBbEL7JmNU9ZqWxlzPkQesTzNMqCv9z7s7UvW/7cih95yFBn4QlJ5PaWYfUIkHwMa4FmRANjGTC4S3CwcdTnYPBOah7WJfYrcYWWwCMiAQU3ku0xiaYSwgResOHciztz1HqAiUUu0Hzw/MF55tyLJuSCqkEpjd0O0tV6qmyCIti35kS97xCiETd+l918559gbMFq9uW29sL+n6gbmoePjqlqgSOLmTMwnZraFtDVVWcHs6RUvPpp8+5vVmz23ZsNhuOjg9o5ppdv6LdbX3CVRTXwcOX2bPJCS6ioowKcpK9bv34b3r/jFa3a5bLEmPNRKGlzPbAPx8TBR2kchohBFVZUJY6hWhScMWNgncyVlP32H8iRmUhk+AjoVDpPmxk1huz8ifHFWNjJZUIm7yCl843I4nj5XuamCBsPDyrdCzNyw2PEdVKn+7dlxASZzRXVxfM53O0tnR9NJbGe0nj8wYFdJ9ZMT3VtCHW9KcTXz0piMnnmabNROFocISTRV4F8t/F696/9717SPJj7yLvsxH29fr9pvf+L0fUQezvGi8m/J0aRuMXmQOYSuhG738vTLT3Ohq+KWclwtQuckwwqWbwBqUnxRoTAINLpDJEy415CC4zrp7Mb32y7HaMa3dtj9KBha+3qceFECNCEZPelPLrAAjd52wiy5GhSY/pDUppjg6PaMpDmnLOrK6YL0oWy4qqVmjtiXT8mhTJ/vNxetCF4Tvf+RBjHH/xZ5/Q9R2/9EtfpRc7nLAoAQWG2g24ytHuDC9vdyzrgqPjBhCh6magHzofVhSBlQ+BMS6se7BOs+tndOYBxhq0fIEQNzg7+NmiLHZdIssBoTKUyt2dTW/avhRK3+EhWWttmAwqePmeLU8X2tf+Ov8ZwZpTudeEQgULVGnP2tQNPTLAq2bW4m4rHB1O9WniRmUfLsRPxFDLGiF9pXz3O2cdn6xqfnK1wDpFbKcbY/dKShYLxfV1yzA4ymLquU9k0htdAKKZnX12jxfH/YlRo50hUbLE2iIk2l1jjWfUO31wRFkKnOuw1uAQtDvLZtNT6IKT42PKqkoL/ezhKeevLzHG8ODshKIyrHeX9KYPMVibXfpYtiiDchNimuke4913lb6gbwXonqOjA66ubhIKI7NWYDH84jKlIQJdMs4hlY/fezhfJpc2mVxJO4a/UQhPlGXuGfpjiiwJJ153UvbOYrP7SceJHA6OlP+Rz1uAwca65KSF/TXhL1epMXkwmSa5ZoLsvkYPXwBK1VxebLHWcnyyYDCbO9MuKos4KvvzKt/ufp7Nard3D+FvGukMNUitiLPHANG7jQaTIEHnU5s4v+upkZDu3KUhiY2UYgw8rSWR/TazPib3OJkr+XXExTYdkYRIiOwHmTWW22wTtCWsoRiv3x+Xsaxumk/iYf6QPZ74EQTOmpGfIHwcEbIot6KXbYbIWyHT/omHJKw7Fy44Ku9C9jxsPKV2RGjBy1OfM+XDd1IKVKAV9zJ+lA069IwAPJ219cnTdjD0rQmhEFjMjzisH3F6uuTkwYy61p5NT+RseoHXwg1ehiuFVgUHp1/h/PWGn/7kxzx//opvf/tb3NzcsFoN1LOawfjmUrE81hrHi+drtJacHmuqKso3Rzc4tJDeGA85aEPoyWEd2MHSmw21clix4WZ3wKb9ClXxEYor+kGhlj65HCM8x39mDIrP41EP25dC6fsHZtMEj5PG2ZHxLi6QqEA8XWL0nBTKq32ccxRlgROeS3lwhq7vfeleMyDbBaa8xWETbBZjRpE4IbXKVWMC2qbT/ORyyXXbJLga4voNsWsEqvAlervtQFGU2T1muQe51Mo09T3O572T4Y5/kcbGj49WNcYorq823N5eYq1jPm84PFqiC4e1rU/OExKH8pz3tx2HR0uapkFJj3LgLMYOlJXgydMTBjPQDRtWu7WHot00SS0l7QkRlJvKYP2YqT2y0CXqWRzOCFwrEdKhmqC8Q0Zvft8inkd4j0/rUYikSouQsKmC4RYhCBfcwbzmN/Ie5CeI95C8LzF62R5uHXnzJyQ7bgwRxWPkxkqeBxJj8rEeOYYFxpI+H9tX2fiNEGtMjUxTZHr9Yb0opelaX0p5fHyIUr6z3nQW3TlKHCXEG76/Owuj6owxX5fi5Y6pR+rzOPay9ON/LjPM4lmTsfh2O/meb9JxJqrZAfLOLvf+zmvjzIjIbzsLA02Njuw68wcz8fJJqEM8clLQ+Q0JgZThu4zbw9+3S7C+R0O9BkmlrSKEPbJz+uMFzoeg4E0o0ZPSU45HIqpIG5tuSABOJOTh/YMb30JXSrT217PbtAy9z63R5djbw6O3/r6k9FS+UgrfWEypNJsHO3iacicw2lLogtmsplGnPHp0yKMnC4roEIYxkBPZ4kmIjJHUtUTpGmsqPvv0ZyyXhzx79pKbm1u2mx1FkYc6Qptqpbg890bxoydzikKN4WXnKLXGKpVyG7wnrxBSe+dRQe1cmuNaXoOz7IZHaLH1PVzANzpa1VC3iHpIa5ZsXrxt+3IofUgevtIKX/YufCvF5NaMAsA3QRK+bE9LpPWKXwehWpQF1lkPnw4dvev95Kh77KCRbQOzXTpe4lEPCmLskgeDFfz8es6n1zMEyid4iFEsJqEmxsVeVYrbmxZrIjsZuQs+uW8HnwPlT72Ju6LWH9JnoteYQXL+esVqtUYIWC6XHBzOELLHmDV97yfsgRzYUtM7wXbTUVaaMixU52ucQsvLHmM7hqHzmblmCPXTo4cevacI66ckRrkH6QdPOLWRtb5Gm0FgO4UoLGiDFA2mtyglsc73OfChHJEWYExcysM+zvoEGh/vN+NKimLZjiVxPpQZ4vaZZ5YnKXnPLJRrCpmEc+yGF2P3NiZ/Mho/KbxBLDUVfn7KmHUvErdAbzy/uLEj+5wQY9vcMVwS/snsGt10PsTZ5fdtuLi4pCxLlgf1G0sfp1s0WsK7qEQmv5nu4/cDLzv3jIcMknaM4x/LGeO/eJD9lZAAL5uhOhPv+d7Lv/NRHKqpERGU+r41sW8lCEFeRjfulN18+t10vU60ff6sguHpZDQs82sVPl/J56lmFUqkZz70Q0IpvcwcM+DTZYrRo4919TFPSYic4nls8uMgMVbC6P3Hxjc4mJc9j+YtMvCNOBdoygOKoLUnILPOZvv45mROOJxwlMqHSp0NxGR2LN8zg6UuK46PDjk7O6ZdaQ4OGoqAeEVjKUc8pPChXM9LMNAPEms3zA86fvVXv8t/8V/8f/jN3/wNyrLk1379V9HFLZutpwCO9z4MluvrltMHTVL4aUrE9WZ919A0XqE3i9JjLk4KP2rL8eyWV6sznDtCFheY28pPqbrHritfWl6Mc+Rzy2j5kij9mMUZIXX/IUnA55tXKj6hT0nl6zTxdZRa6vSZFaH3OTJASIYBg5u1cDtDGAO6H2uwhRw9laD8X25qfnwxpx2iNWq9/xMWtnTgxN3FrAuPEnSdoW50vJ24Q7zp8fNg4Yvs8+yAyfvJBXHclCyQsqJrHefXKzbrDVprjo8PWSwbhOjoh1vv2To4kVseta9Zbi74g5PfwhjLbteyPKwZbD8aS8Jh7YC1PYPtfcmNHbB57fm+lx8VnYwxfIgK3yaFH6H9oOA6iRskohxAhSQiKX1Zj1RjCMCKFJv3nolAqYBIBCknUmgokOtISazjj2V9EBuFSA/Z515lxGtinX4gw4l10ZZpst5g41jY9PtknCASd3cey49wv3WWwXiWMmNGZR+xeZERReUJgCJr/hEnUEJ6grAXUqLVjKvLNX3f8ejRA6zdMlVG9yn+u9/n7HJv2qJyTyVfmWJ16a8fpxEhyVgJ7VipMzFKghIVQuDEmJ2+ZwePVzsxBMbY/36uQawgcZOfjFDCePjcGCSFCdLNQcBD9gz5fVQiv7d4eXvG2uilT5Gn+PyjMo8KZQh5K9HoNUMG50svwyJFc0RL4737/S1d55M7EzMlPrcqeuXRSPCGgE0D8XC2TYo8UkUrpWhmVUCn/DwfjCfSiXF9E0h4Sl0kI0KFsJmzUBYlAkFZWg4OFjw4PubwYMnrtqeI+iEz/CdhDuEoUIkieLdrUUpxs3qN7Ry/8iu/zHvvv8erl6+4vLjiwcN6dA7CzbftwHYz8PrllqKUzGZlCoHsoywQHM9gTEb94bsOwoBHmmsBs8qy2h5QzF5hXIdTBldZ2GlwChjwCp8vtH1plH5ZFICH/2D0EPIHq6IXGXrRF9Jn0hdCUagytRaN7HnWxeIvkKbH9Q4KH99nUyMPDJHLPFnRwNW24CcXC267glgGll9rLNESoR1ulDhxsUsRIP7dQFmpVLIH9/hZ92GWYcvJMcbiBH8tSpVIUbHbGq6ur9ltd5RlwYOzY2azEugx1sfEK9HzxFxyuHlB1W9xwLY5wRjDdtMjNSAdven89RP7S4fkldAVy2beWbJKJ4opWMDZHcYM/RjzNjYzGlpv6YuqB+kyIT0dA2NMptC8QkwNZuJ+XjT5IZUCYaLl7LVhHEvviciUAT/qF+/xxXvI6ZgRI6wfPfzBGp8PkWy46IUHxeyipy6yvAa/r3Gep9uYrNlOmKnWubEjZJgfedhkzE7OjJX4UngjEGpevbxhs9lyfHxIWfk66WxUJ+M8evLZaGaK8u7MHZWfS//LlGtYd/G5pPwH5yaG39hMxybDYLyp8doiKpO8c/Z2yy2gcGljKd8oT/LbdxPW0+kx3WTHcPd3bfFwfdm47EttR7qG9FXy6KdybnrsMe/AMSr75EHaaBiOnrmzft7HPvaJUGxqfWCtS6Q31liPlIaxjUqcaFQLi3MSO5gwD/1RZkWHsTZB60oHllHn17sKKFk/DHRd73tfhPBtVfo24v2uB6kpi5JKV6hKsJzNUNKX1y6XM+bzGVoVwIBSowM4ReMYP0NQlo6u79lstggpsfaKpw/f4eoS/vN/9J/TNDO+/vWvU5VLNrsCFyoNpHD0nQ0JggWffbLm4SM4DDTl0SCPY+QBl8CYGlupZyWUBKPfCkutd6xFgyoLlPMl0tggY3P1IvhCcf0vhdKXQlAqnXVtywQKfp1EXnsPmSoKob13LzSF8pNHZ5ag9WYy9GGhYFBW4ZzBVgP0BW5bIw5HiGfTK35yMef1ugpn3hcYIz2vlL69qRCRpjUqDP8rXUhubw19Z6nrMT5255EGxRku4g3jMyICSpYISrabnuvrS7qupaoqHj46pa41jpbBrHA4GjHwjnnO0c0zCAI26EJudE0/9Gx3Lc08jH0OX4bZGBWcp5SdljX6+4leqH8+WEARfjvlVo+Uq8457E55NVINxDLKuBlr0Lpiu21RskwKV0rn8zdkHM9gZYUfJ4PPSgQmeOC+KiEqjjEDPnvEQbF77z4LTeRNl5LCslmI464Qisl6UnmuBj93vYaJyIiN5X0Ej5csPJAZn/7ZhxBEbkxlAjjtJxVK1rSt5fz1BcYYzs5OaGaCwWwnt+ufG3uf7cXwo0RyTPMe3rJFLzwZL25U+DBWbcQGO5HDwO8X59T03vJ54R/1F7mW5KcnFCK/cYcLPSkyy+K+E+5/IAQ5VW6u1Cf7ujCawcOfZL879kqER69VSoEzwYsMhDUw8uTHkEBMeAaP7ggpkYE4LBGPJWtoNPBiWd7Q+WYxMlDg2kBPOwy+tE9IycNqxdoUbHqVmoxFo3kwoSlPblS4UBo4WIRUDGZgvdrShi56ulBUdUWpC2zviXvKRUFT1dRVSak1UirqsqIsC6q69DS+IUo3aUMb/mqtMlRFhLwslWr8lYahb9nsLvnRjz7l3Xff4fDwmOfPnzMMHacPj1kNr/G5TZbNZsNspkOXUMWrlxva3cCDh7OQWxFKycNc8CGMLKk4PCPfV4AkD0rdIeUcKSuKosUK5wm4rEDIMWcpzpf43N+0fSmUvhACrUI82RniPUchJIP3KT3GSuIid2PCmFb+b/yhcC7FxEbhHBcJMG9x1zMYBnrh+Oh6wWc3zZ6X6f8Xu1UJAOeVu5YKrTSFUlnC2rj8tRY0TcHtbUdR1h5CexN+ExXPG8ZGBGXvXMF61XFzc0Hf99R1zaNHDygriaNjMJ69rpE97/YvObz5jJhmFIvqYszpmpJ+6NAahIrw8uhxuVArH5P17L7CFx7eKpTgpOk5X1dJOSHIYrdZJznnk45sGxZrNZASxoLCEMBgemZVwc3NCuwBhSqxLibpyWxsotBxyWv3127SsEYlokIsPSITyQ91TLz76CmNMf3ozcYFOSqqPJs6KmUV2ijLe5IYo0CIRlT8F5P34vMeBUbuzdw/dzzqUTH0isvzFev1JvRHOEFrwzDsJh60yI6U5HV8rmIcGRHeT+ds5gNPrIdRCQrGZ28ZqZHDaJNyQVwMD0294XEZZB50jL2Pn3yxzd8EMYXTWJvCeZPt3nUpJgbl/jHH15mn7kbvLzeek9ceuEOMMWNIIyEGAudGbzaWE5PmwGjgJrhekJSPVCJVPfnjTZWHMRbTD6lFeLTQXJCHxrhUBVBpx9PZNSvTIOWOn94sGZwMaALcdDMe2GuEGccyGiQxvGBakxLkmqbyLKaFxg3Os9otK5bzOXVR+pp9oairkmZWI/BryFrH5UWLDgZNki9pvCICKpKs9iEPn6ioQvx/s7nigw++zu///h9yenrLO+885eHDh0jVIfU6cGoMgKTve6z1Hr/Wipcv1jz77JbHTxYIsuTgOHUSV4ifAOm5pCkk0cpS6AHnZmi1pjMDsd1Lkn/hGJGR823bl0Lpe0/fEytIK30ZRCzbEWOpExaEFSgnEQakVhRFbD6iMnvb+W5OxvdvTqQxYrT8hbYeAhwE11bzyXUTT+ePERdkWDh5mZWWvva7UDqEFPagJvyknM8L+t7QtYZmJnOJNm73fRakn48nF1ijub1pub29YRgMdV1zcnpIVQmsaxmMV54z0fHO8IKDi2eZWhs9zLyG/OTmZzybfYis1KSxSQ7dx7HKM6297PFirNSC33y6Zq4F//jnDYhYajkma01gXAu2DYZZ1U+9oOz2e9NCPVBVJTfXtxydLNl21z6j3YZuiZNfRCgkNsyJwnT0kpGxvGdUariQpbGn8L3AHYVnbuzc6esOE0Ht70WmOD4iempjtn/+L96/2p8LyYHy5xuTJgkGiM9pkbLh5mrH9fUFUkpOT4+YzQuc6xhMP73O+15PPgwiaDK04s5uRCUNeZO4ZHSBNzITSVFS4FMFme4v+zwlDo4/IT3fPac7XPI4Xi7b/46HHoz3O+ttDAPkXuOY5JcdJv4is8Py63BMqZPjJYhkHGTryYE18YKFL1kLP0jJc9EZcA4RmD294TxqFaVjrkeOkMTj27Qeo8KPuT1xdOJcdyEJs9GGbx9dUQvLsmmRWnFY9TzfLXi9qeiM5vV2xruzSwrpu1pGxlIlfc380FuGYfDvZ5r5rMY5L0OtsDRNTVWUIaTrYfCqKpkvZiHs5u/n6rLl9cstZaW4udlxdFRPUJH9+41GOQLKqkyoyHZ3w8MHj/m7/7W/jZIFf/VXf8WPf/wTHj16yPtff8T17jUOy/Ko4dnHLetVz/KgpG4U77y35PLCO1NSTRsNpeovQuJlRG3Ck5T4xEUlJZU2bLrK6xAEg7AIbXHbAuZdWkhCCERb87btS6H0BZKmqOiMQpoeKWQSiBBpS0OzG61RQlLogsVs5lnKZGjPaK3nfx4G2q6jHXq6oceITKlFy6yXWANSWja7KihacDGGFxYHzi9CrfRIrCK9wo/1+cm4E2KSia+UYDYr2O0G6lpPLMS3jodUSFFijOT2asft7TXDMDCfz3hwdkxZgrEtvRnAwULseLJ7xnL1AjLFnQtLR6Z0nEXvbnlYPuNj9dgzFcGk5GwiiCFJ1+jVFtLxW+9sOG0EF5saKXUKq+wrfM8hHhS+sFDE7OBpzkbcnHPc7C45PDrj9csr2q1FVw1m2KZwwghxj8onQscQ4EARcxPCvezBcIjYE1zQtqA11E0UoBmiEHMFwjWPyWeM0ONoJ6RxQmTZvC523suMIBPpnTPPIUiv/QTR8Tsf8/edGmecv75lvd5wcLDgMFZp2M0dzvY3+g5Tp5TP7fblRhUu9jSvDLTB1sX8hLxt8GiSJ0ggO2/01CauksuvPEc87ru+u5+n2Ru+iglr/px7RkZQ9HEMnIuKfzz3JNx659qmED6OkZRmcq8jiY5XJLGh09gURymfFIbNjOLgWBjGpEclo3c/jqELSFQMH+RGSPTCESHfJJy7lB1n9RUHcsXxTDJrKgQ+9q6Voi4lx/Mtu4MbNp1CYamUwhqHG1xStCiHMzINT12XKK18CbV1KOcN6yLIbGcdqlDUdUXTeJjfj4Hk+qpjddPztW8ccXm5Y7XqOTgoRyPFZWytzqX+IOFJUlclXT8wtAY79Hz62fd5dPYBf/WDT3j9+pzFYsEnn3zK+199Fy0Vvekpq5Lj0xmvX25oZgVlKSkKyYOzZiKnIpNhjvTFMXbJKYpzQSKxNEXHejdD6BJBC8Jhmw2sagQaMeuT4SC64p75PW5fDqUvBHVRhbikoDMDgwnc+tYh8YlZWmrKoqBUBXVdUWjtodqwn8XXae7aHZ3xCr8zPU44BmvoQ4ar65Xn4696emf59KZJ0FmiACaEFUL4QEmFJMD6WgcvKyRn7bsd2fuqUmw2A11vU8vRyX7Za0+oUzEMkqubDTc3K4wxlGXBycmSxbICWvphwDnHsdjwePeM2fp1Eq6xh/sIm4uk9BLcHgTD2fVHvD4+YEUdZOMUds1VRUofE4JCCn77nR1nc0khNacL/9yMi4lGeb94hzXguqjwh0xUZguJXDY62mHHrlyzXM65vrnlwYNjnBxCCV/oHZ/hGZYwV2SevBTUTaQcJfbqdqm8zJcbObQWbLcGXUjqerroBMLTP0f0hTHxabz6cUuKO1dwsVzQxYTA4NVl82hEEsK/N2TOS6kQNJy/vmG73fnY/VxizMY3/5hc0RvV/eTrN+61D2u8ZfMJtCFm7UZUye3No/z5+zma9zR/ywmCciYaCTmUmt1Qsh1cvryCN50pexcT4jJP7f7zu3Teu886Ktox2TAaXEkhZB5+/nlElUYq2pCPlGjImXzvGOfWuD9pLlrjE0T9MUaPGPCVKtKm0kffaRTen7/mSNww9ANaSspqRtPUSOtDrlVTgoLeDCgtmVVhXrsCLFRV4dlUTcgTENKz+Rlfhy+USJU2wnqjUEvt6/uVpi5LysobB3FM1quei9c73nlvyWJRcn3d+jJuIZLSj+GLaFjlLK6Rq6PvB5yz9J2h77f0g6FtW377t3+Lv/qrH3J6ekLfDVTVjKHf+ZnpwNhReedJlqlqIHs/nQvh+RIqDMJrHwa1IGq6/gQl1/5pSgvzHaxmHnFsem9oFgNv274kSh8KpT2EFZSfFspnSAvrIX2tKLSmUiVVVaCDwo8dpSyO3vRsdjsP61tD73qs8IQwgzE+UWVXwK6EukPMen70+oBdL73gwcuQSYlVgFFjrDZyn4+Q2qi6Li5u6Xuzd3eO3Xbg9haapkif7UsrKRVaNazX16kcp6pLjo7nzGZ+wVq38wltGD7oP+Xo9llQrqOyTpS4e8LaQRLCxvmAknPwldsf8Wfzb2OjItv7rRB+0kbrVUvBb73XcjYXPpFSaQoB7x32/PhCBiRh5J23BmwrQRrQYWyi15F5RfF6IHbgE9ysLzmdP6bYFdzcrDk5XdB2t8lYSJ6cwCcQCpEUqDWOfgg9sE0UiCGGnwR8aCR0oChKSdtaVrd96KIYPBbn0jyL/2K83eZPMRPGYRTHTNzMk43zS0g/nz1hz8j34IhhGJ/bMqmKEAKlCpSY8frVDW3bcnZ2QtU4+v4u017+7CfKW+QKLO8Jn/43+W0yxsKbFLPOkSBAyGBuRlTNuQl6lLze7ODJO2JUYnfOvofWTy0VkV37eHv7typGSZ2eRTLOZITQ77UiwomisZAdK15/eBsz3126r9ClM9uiokj15mHORmM5HscnknqP3xh/0oSuCELysExGhrXWK7kAtftzj+eI9+ZEqIuXjoXecqpv6TuDVpJZUzOra6qyROM98LIqsMLR9i2FTsQpgRQIzOB59QdrEbUf36EbGPBNdWzv54DSvpyuLArK0jtuVVn6jnlVmWLwm83As8/WPH1nwXJZYYxX2vOlHp9nRM2MScbzaPCPz8LhkbzBtvR9T9tf8cE3v4aUgt/67V/h+nrDH/7BH/HLv/JtqrLg1ctLLi/WPH56QFFWoaFXKBVl9Ozj847PMBpcLk6OTCcAATEx1MWGm+2SSmu0UPTWYMWAnG8R6xlOWGzZI8S/Ckof78ULEaBZJAMDWniWIy8oJUppKl2glcrWvZ8A3dCz7VravsNJh8+J9n8HazEDuFUDVsByiygsQsLZvOPlqvGCwYXFpKJ370vylFJURekTRIRMtat5Vj3AixfXfOX9b0zZrACOvvhYbLc9w7DjnXcfUtcShAE3YK2jYOCJPefk+mOE7T0ZhYuClgTfxxKoXB5GpZJiwwEPrNpbnpbP+Ll6kjyyHIiIekAIwUFl+LUnHaczRaGKhLQYZ/naccuPzstkhFhnMQbsToEyAdLPFU984SbQbvTQvOI23GzOOTp8xPnrK7brinreYG1LYnyLFjkusdztdgPbdQ8ilOcF9i8hfYKlEDkEJ9Lzq2uJGSI7YU32Fb5ePKPPdc6HcgQp3JCMmEwrpMQjKVBENjGZUINIrZtQlmBkDI7E4BVZJ6tihhYNr15e0/c9Dx96SuS+341m5J7A2d9yc3NP5cenwRuPIMZ9Jr/JlL8Lnn6OUiTUKUOL4lvhYlvttyn4z7uj7GD3ABMRvo9QvhRe+VkYmyLZKK+Df5YZCRPjIhmnbuLVx3HLFf5k3O54juP3sdY99Y2Pn4eEu0gURlDeWusMTHSpBj4l2KpQNaLGkmLnXIYe+Dlnrb8erRR1U7FczHwmvdJURUVTVyjlnS8jPW9GMmaQID15mVCSQgUmOmswCApVeD6ByLRqHUWhmTcN82ZGoTV1VVHXVSq13qwHPv35iodPZhweekjdDJa+t5SlSk/AWI8sRENJybGEN5FmpdJGgTUOXWg2m3Pmc0drbnl5vuVw+ZSqqvnB93/C6YMln356yTvvHTFf1DiXGYJhLse23M65lFAcUZmo8EeULpbuhZwdKVnWG9btEYIGrTqG2FNED9DsYF3jDAj7drX+pVD6LipbJxAOhujBM3paQMiYHwlVYoZwbw1t39KbHid9XXjMkO6twWwl5rZClAax3IF0aeI/Wva8WA1c7apUZy0Z+fRjM58ixPRjF1bvYIpoegK+5/OTJ4/R+u0xmbdt1lqKcqCZOZz1yn4uWh4PLzm8eQaR5MZmXlVc1MGL388mTsd2jsgjPXoojkc3H3N9vOCKRfKKIoIRldM7y4HvPmqZlYX37iOftvOMclp2fPus5dlK8fxGYwfhPXwdPfwRMhu9pqngFMK/Ts1VhKBtd2z1rYf5r2+p6hOUtiHbdlSq0epe3Xb0vWV5UFGU0VsnO2fuCUZhOo7/YllyebGl7yxllVGbhr21UqkGPeZvJO+drGzTucB85g+uhEIon4SaIGWRAO7wfCIULkaeeCFoyhmVXrBZD7y6OkcIePT4AVJ1dH3IznfjM7tX8Yd5mt36VEGGuTKBLF3W32FvLmUjmsY3UibbHG3KnfIcQQoKPmapp12zZzXq+9HTHUc8vwg3Ptig+KPccHsjEY1hQSiREy596JKlPBoayah3IIXFuJE6edLa+01efabwY16HYKzmiI2j4nEiLG8w/ph6JKUBUhvb2EraGhugbRLnSOzpELvyOedS2Cd6/c45HjW3qZa8qnxzqkJrisJ74YKx5e3QDR6CVp5YCgum82x+UkiwvjkOOIpQidXbnkJrZnVDGY45axqaqkI6SVEUFFphDTx/tuL2tmcwJitxduzaASkFVaVSaMxZiw1evnOBlVXIkfTJ2LS+nHU+B6xU7LqW1eZjqqJkebCg68/51re/wr/4//4pUkqOjw+5ud5xdOJL9NrOoISlbvz1iAyd2c8Rmzzf4ITYiLKE+V5py7zest0dINwNwgIhj8QVLTQOuas97P+W7Uuh9PveQ69K+VrvQgukkSlBxNO5kjy5WAZkBoMRnoxhMGaM3ZveK33jMLcldqcQsx2iGkJCTORnl1xsawwlhdZIAjzM2AlNK5Vqt6MSHP2at2/Pnj1jGHoWi0Wixf3ss2d84xvfYD6f8emnn/Lw4SOWy+Xkdw6Ds5ZjueHJ6ueUm8s0idLEjhY0oyK12TVFRTDG6SGW5OV8+f4A8LWbH/HnB9+ho0Ck/zzq8nBm+LXHLZUuUEqH8kqRxrodBgbT83A+cFgN7LaHvFrVNE3LNspvN3qE0fK3brxGgfB9xl3IVA5LxTrLZnfLg6M5bVdyeXHLo8dHGNbBufYLrO8tq5sOXUiOjmtUoD/2Vnn0wBL6Nt76vtZH0DQ1u52lbuZI4XDKE/GIlHHv94wLPj6DyEFI3v45nERKkEyVgkevCqQogOhFWaz2pEgCh5Qlu43h2Qtfe79czjk8WoDY0Q27VO4X4dz43+gKhv9lNz0aMVNFO4Wu45xJsyk8v/z1eLw4PxMcrXJ+fTJHPir43AAY58hdNGiqtHOU4s1bssqTzTA91og9SCnAec8/hmPGOeHSj9893PCVwxV/+azm2W01GqwT+NyMyM5k/MMYxTUr/KyNuQ8RkgcCu50c6+8z7pF43JxGOlc6MRnQWkdTDAwUnv8gKw+MHuiDesOJXk1CDAjh+SW0r4QaArf/drdj17U+6VCLkBtj6Ha9T3Au/HmLskArydB7pslZ01CVBbP5jKosUUjKskyOW6E1tzc956+2VI3m3feXfPrJbZiHftxvrjtmC43SMpU6dp2X90qqFMIYnDeCUk6BGFkvpVYMg+FmvfZGyKxBSjC2Y74wfPVrX+FHP/wxi8UCIS277UBZal58dsvZw5q6GauS4hZLLscqCxecgpFieyR+CxwmbqDRa9buFCHOwbW+I2gkAqs6XNXdScLd374USl8IePV8y4OHdYq3xoxWX74R9guwqpSSwZrg4drA5ubpHnvjJ0TfOcyNJ3YRhxuQ3hqONKi7oeBHr5dc7aoUV9VSZRn5WaKNkL5HR1x42euoAe57TDc3N/z0pz/h3XffxTno+56+77m+vubZs2d0Xcfjx4/ZhzAXds2Hu1fU69c+fhW57q3PT4gJc/GkKZYVlXw4TlT4k7po9j02B05QmJ5v7H7K9+tfSBCoEIJSwrdPWwoZ+7n7bOHBGfqQKBnHvDM9w9bxC8WWs6crHiy3/PR6wcfXc4iKPQh2E6sjMq/LczBEmtmA7ihNWWgGs+XoaMmrl5fcXG85OpkxDJtAuenh/Nm8pG6m0GcuLJMHLu7SeMZ9tGrY0XNzfclm7eP7Sod+9oVG64pZtWCwG9p+m7KG05wJbIGxXC/3vuP9SqmRosBZxWbdsV7f0nZdymdJXOlS0rXXGGOYz2ccHi3Q2tCbNWYYJhwIQMpr8LH1UeEFP3acF/FFNmfSXIge78Rg3JtDySAYjUeXKXNjLULuZ+/7w1uy9Mv4e3Hf+tlT3NMZO7ne8a27//MoP6ZLdvTlxUi4sp8LA4JCGr56eIMdDO/O1pxvHtMa39UxN4AikpXnLohQ0bAP+adETiVxIYRpnW8gI5VMneLG3BeXFE1U4JHkR2Twow3rykrHu4srfnZ96Pc1o6FwXPd8cHSD7TxfRqk1VVGkslUHdF2HsGP2jFYeqbIhlh7nSFV6BNQFg8E5i9aKpq5CsnVBXfkW5M46Cu15TayF559tGAbHo8cL5ouC16/WVKWiaca25EUhmS+KlEOTK9s0NuCRhuBlxzyvdtex2fpcF2d8CGU+KygLneD5trviq197xNAPHB4eopTi4HCGtY6vfe0YoS6ILJCTBm3hbzKEk8E86gjhQr6Gs0G2KOrCMit3rNuHVNUG2wUyH+d8F8/g6Lxt+1Iofa0lfee4ON/x4OHMg3IuiP7cY4IE3eFi8xMvkAZr6a1PKum3YFYlrhgQTesZ4sIBrHV8crPgk5sFuFh372lSY0OUmMiXBDCZ5R4WVy6IkgDcuy8pJfO5Lw15/PgxRVGwWq0YhoHLy0uapuGnP/0ZH374IUopDtXAQfcR3fmfUsmDFB/3DV7GpCi3JzRj56p0MYxCJm+KM/G69q9WwMHumverl3wqnwTuBPitp2tO574FZux97Sshetqo8K1PlOy2FnNTo2YtZ3WPEIKvHq0wTvDpdYMQjCQ0iECpO8Lc42SPLYsVSkuKQiOwqMJweLjk+vqGZlahC83tzYZhsCwPK8py9KRHQTzG3/aNgMntC4mSDdfXLZcX1zRNQ1XpwLPQs7PtZLyXBwvq5pBB7rC2T0s9GktKKZQsQcRw1JjZ3e4G1ustm41nyquqiqPDAwgK0wb+c2MsTVOxPJhTFBZjt/R7yn6Itf7gjaZQ7pXE9YiJJwOAoMQlMs3dHPZNc4ux4mAk1fF9wz2SlOWUhN9YBBiQKoYqMnRnj3nREYiTJ/NRZH/ekp/g9l9kXvzbHaW072ga5F59eB8FuINH8y2xwqAuJd84vuEvz49BCkSA1uOcnVyfmM7DiAzExjWxXM9Fb9yOJZypHhzn2dtcRsFLRGs8/C6UQMmRN19Kwa4XnHJBMd9w2dZc2BIrCt452PDVwxXCOnr8XKmq0nvpWvmEQNPTbbpUqQSeHEcXmr7vcdbRm5isS+pR4ZyX23VVMm9mPuE6MWj6UIoUkr53vHqxpSwU771/QFlKum7g+qrl8dPlZBzPHnqHwcQkxzCOnsMkVDfg5/nYfto7WLu2xQ429eyY1zXzZoZWOlv/Fsear37tff7g9/8Y5xyz2QxrLd/91W/TDTcMpg0GdNLsfsZEWSamCagTFIwxEdiXejuW9ZZNd4ouDnFc0wUuGQiyMJ9H92xfCqUvpeDJO3M++fktN0XLbClHutRsNAX4HsTGheYnJiTqeXi57wz9jWZoJWLW+iYu2cOwFt8Ix2icFSFjVPlSwcDnH/nSRfZwJ9Aobvp5/uD37qsoNE+fPknCfTBDylQ9PDyk73uKouBQDXzFPGd++Rmfrl/xOtxTXueeZ0H78wfBNSKQozEQrjPC+G9X+GL0tgW8c/MJm9NDdmrObz/dcNLIUFnhF60xht4OwcMfMGbw7Ys7h13VUPWBeMefQwr4+tENxsCL9QwilJmhCYKQbd8PaKkotU+c9BUaJIYtXM/yYM52W3H++oqqLhBCcHgUEaLpgiMIpP3tbimOQsmGq8sN19c3HBwuOTqagRi8NBESZ0VoZepYr3dcX91ycw2HR0tm8wZrd8SuYoVq6Hu4vd7RdUMQ1pGFbZwbR0cHNLOSohA4F8csWqgR7XBYu5v0LHeOFLuMvAgCQAmPfLlQ550gsvDEvaQa506wAvIhi2hInHN5nkjuue+jAem1ELhegnapGUl+Dd47zjxhkZ8/+/zOU5vM2HuQgYhS3P8blw9HgMX2EY/Jsdw4Ro/mm+StAzxodpzWa863s2AEqoTq5Ma2IMTVCcauc6F8dCwtjQl2vmOeSGjPqORzJszpORJ64B95gIV9eKwRO/ph4KjoOFA7vnmsqesKVSr61lPp+vyZwIZqPW/E0HaYzmB7m+rri6KgqRpUoeiVZjCG9WaLUxYt/VqNBlShfTm1X7++zBkxJjjuNobXL3YcHFU8eDBDa0HfG1693FKUitmsmKzNaBQldsqwpgutgmE9JcuJ4V8TqNKbWYMMn5VVSVlqjLWoweK0Dy3P6gP++e/9Pu+//z5KKf74j/+Yv/E3/jq6HGgHv7aElFhjUlfmOJmk2If9o3GXzVchGJlcNXXZMau8t18W2xSWnnCMvGX7Uih9gKpWPHzS8NknK05FxeHh2Dc5rth9XzpPhBo6aK98X2O53PnksYy5zQXoTEvBtx+s2PUFmz7E8UNMKy/D2+dnj2Qpjvu8RIEUCsTUQnvy5Gn63pgBEGw2aw4ODrHWILfXfFiuOb74HhkJXGi3GuPHuaAN6iDChyKcMgjzURAEQyGR77In1KZSTsCkLO+b7UfMP/gKxzNFWRRJCPWx+Y7xHfci0U/fWR9KEQZTbpE2IDTJq4dvntxgnOBliIfiwPpmfknpu5BlW1cVZVH6FpaQYndeBLecnB7w7LNX6EHz8NEBxrb7N+jPu8fXnR7nxEJXCGrOX9+yWm04PjliuSwxdkNETMYpKFCF5Oikpq4LXr++5vLihq6bcXQ0o9AWXMHV5Zrb2zVSSu9FFb4TYgwXlaUK1MkD1rYMxkyuLcHPYlRW0ZAbn6+vTckTM4UQGCGRLiRXZUoi5j6kqSD2NV2E54M3mrohmonROV7DOKlG5AnfahSB6YRvlRwVf3T4BcR66MkEzHzuL7Tdq/kj0c5U6MZ1s/9b8ZaTxed+ULbUcghxaoMLCuVp9ZrXq8dYI1PCnJgeIMkDF4wyJwQIn3sRQwkuGAJCiOT5g8+LEIKU2Bc3rwRHVMZiUy2/lSIgpI536leeCa4sEE7QzGuk9uiakR5NkkjvjTuF7R3CWoZ+wBmfQOgdAUVT18znM1/7bry3j4VZXTNrmkB36xOZtVKhUibIkwzoub3puXjVcvyg4ujYs+vd3LScv95ijOPJ07nPfUnCMK5TEvLnlEAIG8Jpvsm6UmPJo5TSK3wlqaoKaw1dN6CUot3BetX65D6pgQ7n4JsfwHa7A+Cjj37O3/gbf5OiVKyuDc3ilF33OtHtkjuEuTOYITrxOyHGfby4lljhuQwW1ZrV7hTnaiRd8PDFHd1y3/alUPoOHy9R2rE81Fy+7qjrgqoO1lRoDEFQdkL4+Dsa3ODoN5L2UqPLHlX3GMBaMdXBcaEASjh+5dGK339W4tzY/jQfbm9dZh4SuYwZgUEpNVJWdB2YwSVyDGBSuqeUZ5sqyyMW0vBe/5JF/xliIMSq/H7WmgCXD6HJzTQW6BjDDUJK396X6J1NPTLr7khFyAR/lLU+0xWK5YzycE5zekSzKDzroJLBCOnpbR94o0fGvX6wPlnSWc8wRShRic8KkRCHD44u6bpDLnd1stpdgLWcxZfx1L7hhgpQXWpvG7xAaw1FaTk6OuDq6gZjjhCyx9qxtjX35Pch6/gZCKTQOFvx8vU17a71HQrnkmHYsK9R/CP1JUnObrHOcXg0Q8qCq8sb2l3HwcGCzeaa3W7H8fEBy4MGIcZSRUfkR+gSXHk3hjw+p9jKNbKPxT4IkWApcTSEFE5nTJrLLvYpDxM4JtBFpRInQTx79MSiIpm0D44e5x2z++47J4DS4FoFyFCqKcY9QtIc2adpjN8wEm8+4+fvK+55fQcOcNOP41gAvH9wQ2xl2/eDb1jTDwgHT/RLPuoeYmVm3GQH8nk4UU7IoJSmaIRnc/Tx8GiHmcFgBpM1z/FfRKMxxfctIMduejF/4KS4ZlkMVGWVKMoXc18H3g0D2A6BRBcyVRyUysf0jbO+IYzzSbweqm+oC1+OiwMkqMbD/WVRJNQzet0RofWGjm/je3XecnvTc3LWoAs4P9+xuu7oesPBQcHJg4qqViMRkXNEoLfvLTfXLatVT9eZNNBCeMP+yZMFuvBr2j+3wK2ivKmspGQwjtvrgcXS5/2UlaKqCt+oqNjwG7/5a/zlX/yAX/qlX+KHP/whL16+ZDGf8+u/8V3KuqY36wlfRrzG/G9ueOTx/Whgei6okK8WUD1jdDL8Uo+Xz1H8Xwqlj3O0XU/X9RwelQg38Or5lodPG4pSeoUoxvpSlIelBmO5vbBsVo7ZocBVgsEqusH3vY+LKDL7IXyZvpWOUg98cLLlr871HVHGaKQnYQ+CsV2nQAiNlCVdBzfXvtHJbrfjRz/6cdhv6gUBVK7j3e45rJ/zcTzR3rZerxG1L4NzboyZ7qMPI/jrEvVp3s3M4kY3MZ0rjB9TASuUoHnvjNmjEwqpKVRBqYuQhGLobU9rumSMDMEYsQ5cq3FG4Jqdj9ETUZM8zuc9lkIJvvPomj9/pbjelcHj916oUoKqKFMp4NimdnLZ3gsdWpYHc1brDRfn1zx8dIC1q/C8pnDbHaXq/JgppbG24uWLS4ah5+GjU6rKMoTWw2mM7qw/P6ZFKShxFKWiqR9wfn7Nq9fnFFrz6PED6gbPkGffnpRz3xYFRooDE404E/JYDGO3Oq+KQz44xhmEEUjpPbk4BRIq5mSaAdOx8cfxfPmebCU2AzJR4QeXORpgb9ykRZR+bqBsSizMhzDB/fcN8Ru2qVK971dioizGT6NhHJ/p/SiHP/QoyE9nLYdV71GoQNIS56tQgtN6w43dseYgNYOawvL+2L7HfMiuFy7wLwiklukKBaQkORsUgFABXUod7iQTY1aMOQDJZXGWR8WFV/Y6UIcH73swBmkMWmhU7ZuUWYeH48syGBKxLaz2MfDFjLqqQrtqP2yF1Kgy5NqE5Or4SGK5YHw+pre8fL7l5spn4V9ebD0ltzO0W8vpo5LlgaaufZLwOC+9sbtedbx4sfZhvMOSB2cNSo4P+Pz1lh/98JLDw5KikBjraHeGvvdkRWePvGJ3vaMoJA8fNZ5WXfsWvtY62v6Co5NH/J2/+9f59JNXrNdrTk9OWK3WmB7KxSlDv8NhJnMExsTCOC0jgdeYwCoiEOtHRUp2u5qLzQxQVKWl7STYISh/UuXRm7YvhdJ3zse0ysoTvpw8ULx6seP85Y6Hjxt04WHYKHCcdXQ7w8tnvkb59EmJkwOtcTA4nHL4StcQ8zSj4ozejXWOJ8sdn97MaKO1lZT7KFcSFXmQnkpppKhod5br61s2my1aa05Ojnj0+Jh+2GDsMCpiHNr2PO2fcXLziffKqindKpAkU3noELJgGHw+gnVZIhouKX7rLMKN9aCxi53fbzQ2RPok/hWT86l5Tf3+A6rl3CeaaG+9S4SHxgKk73u/m5S05wCsxG0KRL0D6b0YKQTKxXGOxor0GfASCmf5lSe3/PFnB9xsdfo+sh3GDPicXWv00OIfixAdpydHPHv2ku1mTt1UGNuNQjFTCpNsXwheSM2rV1e0bcti0VCUA/3QBeGed/LLlKMf2PE5CDBmh9SaR4+PuLmp6LqOshpCOOeuEbI/7z/PqveKOFfyNsHuE06GsHkEYUA6iRChhhuRylFVKBv08P+I+kAgd3LG12U7M0L6YhTqe7Po7hb1qQrPwd1VsNOd33bv//98GyHXt1zT3inHEMUotKNzAI6vHNz6sFbvQ3MJKSx8gqkqFB/UV/xgdYgJhEsx6S6iBalOW8RkrxEalipm9pPQBKIcykKb8TiRhCd6/vHGnA3oj7HU7LBC0RqBHAxl4eWHNRY7WLRSzGdNouwtlKSpaqQTGAezcoYuPKRfFgVV4MMXwGC9PCyqwvMHxDCjkwGxmw7w0Fuef7ZmuzHMlwX1TFGWAqUcl+feA5/NfXVOob0MHowfA2Md56+23Fx3nD5oODltEgqQw+ZnD5vQEMefWmvF7KQEYXn2yYpuZyhqgemhKFQ2diQDTSnJrn3FoDYYAwcHB3z44Ydst1vOzy94/qLjW996zGb3PKB1o+KPpdPR0LQuduLcm6dCsOk0l5s5zhmWTc/R/ILBgDXatwO2oUrr7Xl8Xw6lD1CUOis9Ezx8POP5Zxtev2p59KRJXqRzjpvrjlcvtiyPCg6OC0/QYyJ9a+Sc9/v3w+Dfx3jJiHgihOUXHuz43osyECl4SD/foq2mtO9jv1kPXF9f0raxj/0DmkZj3Y5+2KELUCiME5TO8Kh/zvH6M2/JVRITBIvMJl48T/Q4hsErVWfcJBHNhf2jMEhJPeRJe/dtYir4wsH040P0o0NiYkAOHw7OJxP2pqcPyXsjnOwtUrfRnl63HHCDDzwoIbG9Jyqpy9Jbv0qCdD450TgKYfmlsyu+9+KY1lQoMTYwylvgOpjmVjCKlMG01M2C+WLO+fkl77x7hmBMINzXJ6NyFGjZ8Pr1LW3b8fDRA9brG25uVjSNQgg5URzT0AohJj0KbgBrBxxrmhl03cDN9ZrFsrz3SUyvaVRS+wZAAEHuKPn43oZY+2iqkpAVLNhQN5xIflygeiZmE4ds4TBWOaxvRea9hHnj7eX9SfSGLYYVJs8gzsEv8Ps3j1g6aBq7idfuRsPQZacfbb3p0aLRHZGHwFiHE5zNNjSqo++N7xinVIJhVRFKeRUUCD4orvj+xSm4kazFw+aBoInR+EvKX4z3kdPJSiVxxiJDYp4TLtTjj/H/1IxJBHrpcD/WWFa25M+v3qXSht9+dJk6gTrry+6UUvSdzxZXQtFoH06TVkAo2ysr3+5Wx2RqRuejKHRq8pOMDqZGNgK61vDi0w1VrXj63gJw7HYdfd/TdbBZWc6eVJSlRioZHBdvaG7WhlfPdugSHr/XUFeawQ4IG3lUxrUnBBwcligpeHDWJPnVdT1FqVhvdhRGs752PH7qDYcYO7eRE0EIrDF05pYn7zxlsVzSzBX1TNB2FX/x5x8hhOAXvvWQ9faFN3Dc6GxFVs3Uyng/VAzcbEpe3i44Xew4bNYMtqPteza9r+GXkWPBOdzwr0DJXixxSl5JiDM9ejLn2acrLl63nJ41GGs5f7ljvep4/M6MulE4HENo4oCOWZ5epUprQPpQgBW5AnXJgj5pWmo90BmJ2hNovld5Ca5kdbPj+vo1wzDQNA2PnzykqgTGtbT9elLWVLkd7/XPOLh5BpmHliAfN3riuZr2nkaouw0CfwKluijMx6S+UYZGyRzhP8i9+iTcwwfF+6eo41kwaMaGL95jIJRB9gnONzYSGwevzwpcqxDzHQgfeomxRaUFs6pOLIZCCLqhw0lfFyyspVHwq4/X/MHzOrXDFWpkHvOJl/ut66bC3Ngtp6cHfPLxC64u1xyf1DizvXeOuWDpFcWMq4stm/WGs4en1I3DWMnqtqOqNFrHmOtIvJEBBN5zvceb9KiGZ/S7utxRFIaqVnd3nMyveG2ZAZhNwViWFxV+bFVr7Ajtx+P4V36+WGx2neMMs9Zhh7DGAtwvg4EFEdofaUVTiIj8st5SRseebRmzNHMDIF7sW+GCe44VP9mf344kZF2E5rx1HHIHRFoaSUm56b/oTMS4OFi+erQew0/JWvD7Db0naFJaIbXgSK05rSpebZqUte89P/mGZNIRTRw59/1+ZhjpdH1obMx8H0NdAeEzlr4bkiEREU0lDd9cvKYua6QAYw10ntEUA64HYQVVVVAVFbUObKRK+az4wAIYLjyNk/eUxzUaxzw9Uudl025jeP7ZhsWi4PSsBhx9yFMoCh3ys6BuNEXpZXg7dLSt4fJ1x2bdsTxRLA9KjOjZ9gORsEvKjC01dNFcLAtePFtzdFKhtTeM+sGgC8vthUN3hrPHM5YHGusshdBeaUNonR4RV8e2fU7VNKy35zjX8eDhCd+23+Qv/vwHlKXiK187o22vKIoF2911MJ5H3oWIRkQKYIDbXcn1rua941vqwhtcUvhug56OuPSSVfgw978SdfrgJ1DObQygC8GjJzOefbrBmg273YAuFO9+dUGhQzOKQNtaKM/N7JWkF2p9hFgZGFK7z9GDifX93QCxhtjhk24KVeFcwe31juvrl1hrmc1mnu+8dBjb0vZDgEC9AG7cliftZyxuXwBjbX1e5nRf/sD4J1jNYVHfqf9MBkOQffc4Tfcq+zAuLuxQfPUUMa+8MJSxO5rnObBDUHZBAcSEQhOu3zpvPMUWmkJHISySoCtqXxXRdwOzpvaZwBKUb7fneyMIy1LALxzf8hcvlt44y9CY/XuP951/Zq1B64Hj40MuL69YLBpUofeS+nzYwDmNGeDqYsP19S2np0c0DfTDLrXQ3G0HlssyGUYxKWjigefeJOO9x01rwWJZcHvboYt6Gp9zpOea/86P975yDd639cmhBpeMAJfoeqOxEK4XF5jl8kk1KumY/5GfJPKe74eJpvX3aRLlznT67I7uDkahL57e88InnrkgPzSTb8Y1McIN+yeanjK/MJf9L+UCMSrauFNCbRjn29PlllIOdO3gjfDo7RqLCaWTQgow/naMdTwpX3C+foqx+g6kIODe2uscfRrpeAOdbgxFOpfyQoSUCYq0xmfaR+55r24tx8WKr8yvWRYaZxx9N9Aa4zn164JCFpS1v/5Z01CWRcq2jxVMTKasRytUXI+ZFTz6G95LF0KwXRueP9uwPCw4PqkSZD/0QyKtamaSuhnYbAZUKehaw81lz+q2Q9QD84cSWTg2g89PieEpnyDsu/MVgRlUSV8JI6XwTHq199o3my1FZTl77OmF60DjqwJSEFHR+HxFcpgcg1mnZ7NrL3j85AFD/w1++MOfMJ/NefzkfZ4/u+DkwWP6/uc4F4ySTOFH+WWs5HpbczzrmJW91y+BMdM6G8odgxwJSXxd3795ovMlUvp7mGowlUEXkqqWnL/a8ejpjOOTGh+OjFY6yVuRUngrTowlaMmjNh6eTjSgQYHdtpreCgolAszcgNVcX+24vb3COcdiMWOxnKG1J0jxyn4Uwgu2PNl9ymz1EueyrOo9ZT+Fc9PNTt7nCkTETF+bC7xx/0m9dRrCfYUflDE+27/4yimiKf3EDJPMWt98CBvRhZEbPCWNuVFpCCFwg/RUq8Kla/Wekr8iYw12CD3nHb5hkTEgPPQ5GJ/38O7BwG078GpbpntJ3tcU5LgzPQDMsOPgcMFqVXJxccOjx4eB2UoBiq41rLYd2+2K3a5FCMHR0QGLZUE/bDyiIAWzecH1VUvT2IR8vEnLuHAROSqRP7eqUvSdZb3qWB5U49QWd/3k+8I7E6HrYujG3uFqGD1X/9u8619+mFxnxj4NuDEJSRdqkmMyYdF78whk13DPHr1C6DzOGw2RfRc/3vkbNHrS3mLvtPvXd/d6M+CLOE6RN3/cZ1xDAs++9+7smr7r6XYdqlCeEXIwSVHIQJsa4fyh8/Xb7zUv+dHt49BAKFsTYS5N5/KIJFnrjQkbSs3ivboMcYlJfRFWjrXo8fiH6prH82vm2tBUFZUuPWzvfIno0XLBYj5PRh6ClKAX+5zEv+OQ+mTdPIZOMjZHQRZLTjfrgZfPtxyflMwWyle6uMAaGBWr9OOyPPJVWtvNwHbTgzaUR771dmstXSuSIhUiKH08gZo2BqMspXY4Y1jfDpjBz9lhMGx3Lev11nfzK8tQIkkKHbo0B9PNpQkzrfDx97vrLnjvKw9w7usoVfJ7v/snHBwc8PSdx8B7bNtXWOtL/mxg1/PDI7nZVSAEi7pLjZNceLZSSApV+DUpkon9OWvvS6T0U4vcTKK3W8P5qy3DYHn/awvmixIhRypIGD1Cn1wlccLH1J1zKGcplB497cFhDUSeZCkEx42l1AV1scAOiuvLls3mChBB2dco7RiGDd1gEoxvrGXJmkebj5mtzgE78YaTos+MjFEI7S3/bB1NEruioo0Gzr73KyZ/iJo+9+69ASSRWjH/hSe4MjTKCX0NfLcxh4fxQnQweGPWhs5ZQGzqkUIkg0Ior9ETd3hwqGIDEWsd/dCjQ2azco5CaIQNdcXBaPvldzp+9+OGzhh8YzFHocWYRBnNl/v0ggDnWk5ODnnx4jU31y1Fodlud2y3O4wZAvTmmM0blsuGqpIMZgu4MO+8h17XmvW65+CwunOaPEN3TBYkxWr3Ff9srhkGy0RAZseZKqT4Xe79+WdvsenzqYEw+WXYJ3gL4QT+zDky4U8SVXBqEBLyYfKQ04hyTC5/HPS3bVaAFYjShOcTf5NduchfTBXJXT85Qwu4+3Ky3/5psnGOxk4+xnmsHSF4b3GFs31SxoUs0nOVMvaGjy3AxwVoBsvc3vKomXExnIzeOvH8mSiPRppz2NCH3gwmfR7bfFtj0++/tXxN2VT88PIAkMHDh5PimrPikpLeV78UmqaumDczDuZztNK+wcxinkqIZfC4dQijChHWYqb04uDJfYQijmdoVBQNqPVq4NWLLScPKuZLnWhvh8Gk0tvoIFhrUZWjmFl2fUdxaHF68A5G+E1ObqSET6AutU8wHgbB9rZj2PVYI6hrxenDCsfAet0y9Ia+G3xzLGOT0RLXenoI0W6xdkRi3FTl+jGxdP01X/3aV/jH/+XvcnNzzW/+5m/y/NkrdrsdT989ZbX5LJEDJTnoFDfbkpPZBpmZ5HGME+V7RAgiA+vnVPx8OZR+rvDxSWI31x1Xly3NTHH6aEZZ+Ox9n+UayhuC8k4Wc/RUbDAIYEQDRFyoXhlqpVjUB5wdvMPj84KPX+3YbG4RQrBcLpgvaqQasHZL10cvyyv7Q9Y82vycZnORqFAhiq4sXhjOfz/+eY/gzLx54S96lId7O02E8T2Fz3FconGjy4JqMSc2gzEhO9vHiEN7TmyCFeNlJgXgNdwoGIyAIms4E9oNW+uVvUR4fn4zUNoCGfpv+2Y9A4KxYkJJ+JXHG37v40Uwkn2tK1IGxMZfjJs0RMlG01maxjOAnZ9fBt5yTdNUSDlju91QNz5TWIqOkdwub54kmM01V5dtaOUps+Nnxln4RS7U9/eL30da4P0M+1EJxfsig9P9/HcRLQlGZswHttPJsKfgxGiAxXPkaElSPn5MZTDUkmHxNg8jfnXPtHX594AbFELZ5I2PUypqjP35L7KDiL1zZJNRiLsn2z+Wu8+YcndeT55dWEuLouWkWiMgMbrpEN+WSib6XAgx29DAqu/60ChH8ZX5DdvVku1QgolZ/9wxRvwxfFnZ0A/puTnniXmily+VpJEtS7mm0R0fHq64aOe0ZsVS3lIIi0RQlAWzpmbRzDiYLzg4WLKofWKbloqyKtM6LpROnj2M1Njcc5nJcLF2T+jE8YTVTc/5qx2nZ5WPw4eYvc9PsAilw7lDExw70NsetRjQpscYXwock5ENHi3FOoSTFCGsYZ2i2zl2lz6kUc/wXPqVwtqBzaYlIiTd0KOMopKVb/KjPZolwSv4YAg4CGQ93B2LDKIrizP+6A//lPl8zsHBkn/yT/4J1jl+7dd+md6s01jEIRIIjBNoZWlKM/IzBMNTSekdKudQzrOeVkWZWDDftn0plH4+0frO8frllr43nD6omS10Fh/xPOgxk1TK6LGMfeSNHWlru2EI5WX+PyEEZVEyqxacLd+hMAte/fya7vUFXVfza1854le/NuOT2y3fe7bGDGOrUOMsC7fmaVT26Vy+Z3SC7eOdJBxnvM80n4RXN7n8criQfHXPpMvl056HKNjX+WOJUKyVV4Xm8OvvUBWVP4fEUxc7AwMY0U+MlD0cIl1Luh7nPbnYAjI2MXLW+VCusSBjj2vP1U/vr6zUBc75mJaxJln/B1XPBycbfnQx820ybaS/jHcWcwbGsfHQfAGu4tWrK4bBoLXm4GDO8qChbXesbrfMF5Jmpsd7mYz7iIgIIWhmBetVh86ofafzVNxP+fsFt9Fr3zcQ42cjsVIKFQXUZYzlk+nATBEm42RkpvOG276mzsIIkvFasu/vh1X2x2LcPSlfK7xBWJk9I3Qy+m8+1nike/cbkYN04uk9ERQmUQhn5Ex2pGqN3n2E9aXw5FFKxCQsqGc1utDjNbpxHeQNr8CXsVVVgS4031AX/OmrMw85Z0aGY8wvsNZ6b3gwaa57sp04r3z8udSOry9eISWe114a3pndcNtvfO6RLj0z3qxh2cxYzOYsZjOaugqNwsY2u0S5mT1bF64tOkj3zejJPHdjQrRzvgvexeuWBw8bZguVxiSOk9a+UQ+O0Ia7p7M93eBpvH1FT1aJEq5BCAGhW54TozPRrxyqEByeSIR1WNunmvwxKdOXJlZFyXzWZA2J/OXFHBYgdWyN6HC837uhO83JyTHf/OY3+eijn/PJJx/zO7/ztzg4OGAwCqNbrF1NkFyBoy4sYtLuOY63iMsP40AgKVVN0cw4mt1FGvPtS6H0vXVrWd30XLzeMV8UnD2q0VqmRR6tYt+C1zdb8Arf140PxmBj/BmXmO1sgMqUVCzqI05mj5D9nBcfX3B58VPqpuZ3PnzK4WlDU27o+wvEjfGKKVzbgg1PNh9TrV7hnPFJgS5jvosxccQdATbRoPHLzBZIkGpmEYxr0t2RvW9UM36lpKzsqPTL5YzDD96laprUeAIXG664ZJXGeKHLzhGzl/1l3fWmhDIpthmv3xqbblkVCiscwzBgRRBirgjWu392ApGs268et1zuSi62RbD0/XhIKVByL6nRgVY1Q6959eqcYTA8eHCMY2C12jAYHxZaLEuq6h6P+649BUBdKbYb38dhP/t+HJd942sUllP/NcspyYw7m42XF3SjoZr3Wffevk3hrBF1Gc27GC9OSs+NcVj/2IKpEu01N07EPJ49ucG9sRnn9FQd3+O8+lwPabMEPib736vN08HCESNrn9v7nr25mVCvMYSWc+QDnmMgxsZThvV4DCklTjjeP1gzKwwh99cnuJWFN7xCTFopSdmUgMMMPvfD4cuNi7II3pxjrjrenV3x06tleibxep0cFRiM1+Sv3/rOdgFWXxSGDxYvqeTgk9a0z3RHCJqm8mx584blfE5dVCyame9drwtUqGCK1l0kzYlKJ96/cyP3RxzRsSpETOZpJpawDq4udlxfdjx8Uqe10g/Go0jKE27F9AlfVu1JvrrQnXMI3B/W2kk+ip8nOb9BqJoYLEPrWJzGASN8PgRGO597JJXiYLGgmVVhnbpk1MQwZCQMs2403vJ5MzLrCawdaPsXfOXrZ9ze3vKDH/yA3/mdv83FxTl/+Id/yMHBAd/91Q8wqgv8HL4CRmBpB0FvJFL49StFaIglBZjI96EoygOUOmR1tePq8vb+NRK2L4XSt9bx6c9XOAtnjxrmiyLVIUshcdakxV4UEq11qinuh4Fu6P3ryGqEC0l7IIRkWR9yPH+C2RY8++lrrq+esVgs+IVvfYPDk5LeXNH1l2w2vmGKDgtEOsP7/accXn3sSUsyJrR4ngTL3pthLLxA8i/vbgKEHTP137ztScCp/k2LxDN6RitSUJ0ccPzBu1SVr4WP8SbrPBQ5DEPmpb351M5bV8RuE3YQ4Dy5SPw+MR6GbGIIGcYm0hH7hWcH65sbBbjNC4PB1zMLD/P/s4+W9Mb3TvBle9PrE0Ki1YzVquf89UuKouDJ0zO07tm1vtOilJrDo8objnwBrzwaYgLf9as3lJXKlOU4To7glZGFcPaeS8AmkuCN+0XFnXgV9pW9G42A+F0MZUUPlgS1OmAv6TBaI8k4CMomKkUXGev8Fd7rNO8br278/PPGECMRlSeWyk2EfaPo/qdx36d3rd7oTcXbmzwbN/2LG+vgPSGOnMSphRDMSsM7Byvc4H+jVIT0BUNPapBTlAUqHEtJh1Qiy9T21xkbIT2a3XKxq+icZtf7hk3WWIZhrO32c36EciO5lRCCk2LL1xbnlAqKqqJuSopaY2wBDmZVRd3U1GVJU9bMSt9BriwKVCAKimszpxifKPxsxO8b+XEMXZovCG9Unr/esrrpefR0RlULbIjhO2t98x+Towk+2S96+F7hj7wfNrsWwRh2iOHYSCdtA1qoAqlRoQt/j8YhpfPseWVBUejQ3lmw23XoQhM7F8ZEvrgWoxLeb9m7bxx17S3WDtTle/zO7/xNXr16zWefPeO3fuu3+cM//AP6vuBg/gHG7tjuPqPrd0jh0MJyvW04W66T0SvC4oi5Dk19zOqm4Ac//AnrzYbFfHHP0xi3L4XSH3rH0XHNYll4Eyx6LcELilafyjimrfGKvR96uqHz7HsZtC+F5GB+ysn8Ke2N4KPvv+D2dsXh4SG/+J1vMT8UbPtLrlYrT8uoNM536GGwcCQ2vH/7Y3S7YhARXvXWZIRZkwrYU8JwVzxG32xiLpP7iOHTYJm/zQYYwaNgke/9J7Vi/s4Z88en1GXtIfWoJ2I3rrTYwlKL0N4diC9CfzYpOqxONMWRM9oMxmfWSuWFBDAMA6UqfX9wfB9tiYcki9LzbA/OIHvJgDfy6hJ+5cmW3/9kngYzHzKpCiQ1r1/dslqtWC6XnD5YYuwGYw1KCZpaU1TKC4fPU/bcBTOqSnN72416c/K8mAgNbwB4NCl5/2J8RgnccWPcPCr3vFfCJGvexRr5eK4wCsK7WA7GbnV4THhS9SHyZi4QWcTSDQgm4dlcwb953mWe9f5X0UuPHZTu8fKT8XHns+yIeUzinovJlfv43n+WjJps3PLNJ+Cp4EWLyTP/xskNEhhyoZ8hZgg8lW5YJ7ERlFcSNijzIQs5CUqt+MWzK5xUbHeW5+s5r9Y1w+Cz0p3zxnc0KMAbG1oqzqoN31zeoHVNWWuKqkAogSwkZWS9DJnflS6ZlQ1N5de5kmMvEfA5IJPS0BwFybz8XMnFUc6Rvth0q2sdl+db2nbg8dOGovSxe4JHba310xQC6Y5HqZKHP/QYOyR0z7hc3Y9zIceTJNI7eTtJUYCS/v7LqqDvfIgA5+eW1gqEoOt6yqLAWqjqQGOchNaIZMREvdzAiXHElDwbPuv7Lcb8jOX8Mc+ePePBg1N+/OMfcXBwQLvr+X/83/9T/t7f+3scnS4ZTIe1lgfLlmfXc663FSfzdvIsBAKtG9ptxZ//2V+yXC751offQJctb9u+FEq/rCRHx1Xiq57An1mLy8SKFb4zgX7SWJMakUghOVk84nT2DutLww9//Bnb7Y7T0xO++2u/SDUzrHavuVxtfLw7JLokL0AI3mu2FOd/DjgGogDJhHz85/acqjcJzLh27pQZZY52bjjcUfzj78Yl4YK9MRoSxaKmPjumPlx4OF8oClmglcZKT8oSO+X11i8WnzQyeqCjyzsKWRuZASM8ZhXIwNMtR69WhcSnoTcIK9FC0pQVpSpSfW1VVlSFz4hWhWKwg889MCJlrb57KLneDPzsWo9xa0Drhr6TPH91jjGGs4cPmM8VgxnhMCGgrBRdZ3CNTp+9bcsdZRi5r2Nv8vG5kJXPTT31MR4aH6b/O0Kno2JKSp7xODgPgeKmhmCceaPHHr6TueIZ58tdG8fdeTnmZkwV8dsVfvjrwGWe42QQrfAKP83zz0MG9q2OPeGf/zw5AXuHyOQBjpHvwI3KVEqP2Pj3U3TmbN5yVLaT/ZOXjFfwhSiSJxiTwWSQRUIKdKHp2t7HlcOcKcuCWe3XxLyEs4Mdm3bFyxvJs9s5V1sfDhClSpVLWmkezTs+mN/iBkHdVJRNgVD+WmL2vZKKQioKVVIXvo1tEdrMajHeQ67U01hlw51XIOS5BxKS9z0YS9daNuvel8YZSzPTPHrSoLRIFSoiOg7hdzZ4/L3pQ0JvaMUdwqMe0h/nfjQ6UlgqUe4GowuF6yXFQXgu2hsCgx3YbHcIYNd1OHwrYA/dj8mR8a5jVQCM9fRx8gh8czCypml+/gR0wDoGu2O7O+fbH36DH3z/pxwcLDk7e8Af/uEf8bWvf5WqqnBmzrypWW8/Q2I5W+54fl3TlIamGCbHLtQJf/nDn9A0DR9+5z027TOu12vetn0plH7KokzeyZ7F7iKdZe6TkJSQkJJSaRbNKcvijNvzlr/8q4/o+4GHD8/49ne+gS53rHfP2a52PsFEKVRoz5hnuQOUwqb4nD/PaJmJ8dTE2Ro/vSviojB2k/t7E5Qv9gXdPXvkr2U4t5CS+p1T5o9PqIsKLTWF9Gx4VRW6Z1nhk2asX4BDbOiDw2SKJ54jxZWtzyBWauT/dwZQBoRDOq/ydWjwofDJFp7gqKAsSipdUmjfdjO233SAdBaEwlEgkBjhF5sSku88tNx0jrXxhlmh59zedlxeXFNVJQ8fHaN0T9/v7oxZUSq2W1+qd6d5xZ4OzPVfHgcXImZox7kZFfdeh7t98qXkZYYEsaxvQn6MO8l8mckwXmDU0ntfxGvOfnCf1xtuZpyzmdc3fv1FFPQEC3jjN74yxE2+cfurY89bZ/L2bdcwon/5HN1fU9Os/KBE7Lhf+CHOOUoNXz++Sb8TGTKUjkdobCPiOxLaGNkmrbUphNV3oQTP+DBW3w/oQqMLxVwKHrsdJ8Ur1p3itT3lYrfwBp91nDUd35id43qDLhV1XSI0voonkGgJBFrKVMKmhUcHlFTpevLrv3s/wVB80yg7R9cZNpuB29uO3dbTmM/mBQ8eNlS1DGGN0FBobz5FSl0nYXDeuehtn1pyR0bJEUkI5xUx7CSTEyFENnd6j444MWCcdxassWy7lvVu40mI+p7FcoaQUDelZ3kNeQNCCHonEMbnCsX17amJY3c1UhKxcy51IMxmoD/OsKEoBN/99a8wdA3/7J/+Lt/97nd5/Pgx/+Jf/At+8pOf8K//G/9NlCqwpqUuBk7mLeerhseHKwrlB6ws57x+teb2dsUv/8q3sFwBJlQ4vXn7Uij9BJvjY2JSiJR1GnnYI7xEltkNUOmGo/ljCg65erXhB88/whjLw0dnPH56jNBbNu2nmE2PFGTtHwPHO2PSG/jFUc4aVFnQt62H0mTsTR5IJlxQ5BPWk6mfkgvVhGAxQkp+p+B3THX5XePmHqNCADiBrEuW33xKPZtRh1aahfQCQQhBoYvQdsgr66isUrOWyXWNdJLRudRaJbKRdB9W+oYq2TgKJ9BOeYUuHVoqmqqiLErqug6MiR4JiAbWYB0YEl2vdSo9C+kMf+Mrjn/6SYWxNa9fr9isNyyXC46OG6zb+QYle+MCsZwOhsHes3Dj/Ybxj8reZU8v/LE2KnOSgRQrOWLlxh0SpgzGF4hQnxt13VTR+8/3wimZK5vPp3jNqabXjJUT/h72994TqrhMiO5vn2NsCsgz6/Z3TZ4TDmHDvnvXM/7aZWMed9k7Yojh+u9dWltTxc8kae9OGCfeq4tz2mVf+TX4sLmhEJ5SN/Lb40glU9FLlMKHzJwLCV5Bufp14cCGenKlsNrfjk8A9G1yY2Je13aB8EdzWAqO9S1/9rpi3RYclTu+Xr3G9VBVBfWsompKUHGOuKSUZAijqUBFq0Kv+ftav4q9e05hJOtQWiUDqG0N69XAetXRdQapfAnr8qCmqjVaB4MiM1BVaOU7hg49StAPsROnDV6+L91NJahEg42Eloz/kVgBZfzMQb+TqNKBslgsnbFY41i1G1rrw7tKS5xyOOm8AScsfehMiSMxtNrBpb4CSgXZLsVkfeQGZdysc6gwhl23wpgeJR5xenrK0dEh3/ve91itVnzrW9+m0BVaVXS2R+BY1D3doHh5M+PRYYsWBq2WPH/2KUdHBywPJbvdLuiafwWUPhA6DLkgsKdlJUkWJx0rqMqGWX2G6Spev7jh5YufIQQ8fHTK2aNjpN6yaT/DDgNCgBK+zlaHZA4RKH9zDz8uFqkV87Njrj95kQwEi/MZscKFhheez38ikGy8yFEIuZCWmuKDZPcShOl9iWCjmBR7AjKMgfCEO8uvPmZxcECpCuqqCo1rfLMMQSzVASt8WaE1DtN6QZjgfeHjnMZYXwbjXKipV4Hic0xQcs6BcSgFCm8QSSexg6OoC0qtwUBZlMyrGVVRUBQh4SZLelLSJ/JppRBSotUYVxMIdFVwNn/Ad1vNf/bHL3x87MEx9UwwmHXI2xDsD1zycl3m9YWxiwpj9IZIiv+OBxs8OJv1snfOoyIjR70ZhWiu+ONzw+HsdD6EmZJ5x3tKf29LHlF2XbnBINifHN4gjfeVe3oixCrzozuX7b9nFExMz6T43+Tzg1AO1ynvTampMZsbPdFrJg9LvOnuo9GSKfgYkzeB/SweM2Zbk851F1WL604Ly5O5L7Fy1jeLwrk0xyPcnxq0SIF0AhtgfWs9e96+GaW1DMmj4TlZzxKHELQ7X8+vS79uOhp6W3Jc93x7cY0W3lhfLGZUsxJVKN/vItIiO5KCV0Hxa60yDhJx537zdrzOObbbgVcv18zmBSenDc46zl9vub7qqGvNfFlw2tToIvTjCH0BxvJhkQxOgoFuw7Ty5cuhE2do0NUPPYPpfYlwNJRxqbvgvmzLS43Tx0Zie0lx4MtAu6ELJDaGwQ2g8QrfwrZtcTgGNyCkb78uAuHXEAiQzGBo6pq6qigpsEL6fI1wT3GNGRNCF+J+Ai5jWlR5xa989xf44V/9lKura/7W3/pbvHz5kj/5kz/jvfcfU1aCtr1G4Diet3xyMeej13PeO93BWnB5dckv/uI3MWaVpEIeUrxv+0JKXwhxBPzvgF8KQ/zfd87983v2+03gd4F/0zn3D8Nn/2PgfxB+96fAv+Oc2wkh/s/At8JPj4Ar59yvCiG+Cvwl8IPw3e865/7+514jTDpSib3J6tupSgpdUxUHtFvFZx+f8+rVJyilePr0EacP5zi5Ydt9hguJNTrE84xxYH0cOdJQ7i/Y/KEWdeknIAInBAqJmhWUjWb96spbt6EcMAnuKGT3PffcaCGyn2ViOjcGCAdCjO+CFxpwCaRS1I+OmD0+paprZpUv06mKMjBYybR4HJnFLAQYwfZK0g8KagXalxs6C87YxM1eKN9il8CA6OlGe4y1qKGmqLzilnilr5WkKWsKqahUSVPVFFqH5h0i1T5HASWFoNAaY2N2vkwCXqmCqjjh1YuWz378Ywq95PD4JMD5Y5KLu+cZAnSdQUhS85zo8YnxIUyfj4vKNR05zBmv9McOYG7S4naadR8SHcU0bpqnrrnJi89R9m76Os2hcA9JmLtx3/HWvOce2renz0QciMwIug8h2Bueu9f/pk1ZRIGn4BWE+H663b1rfMNpXT564aOQLJr/Pk8y88/rLplSjAdLKfD8CuNifO/glkq7SYOboR/ouyGdXmmdDAzhxnNa63nvpRS+CiXRGXu6Xt+9za9fJ32Sn2cQ9ZDx0A+oquTBEn5DXbMoHK4rEQ6WyzmLxRy0TzCTduwZIghKXygfMlM6rfX9LfUXALbbgfWqZxgs281AWUmuLluGzlcTdL3h0dMZs5kvUYwD7UIp3ZRdMBrmUWYLwNIPJjTmCqXTeO++N33q0BnvwxtNGZyfFL0IIdcxkRIcQyd8GagyGAR2MPRDYHvEpuRkJ2E3tFhpKSm8QZKFdrZbT95jh7D2hEMrSVUCSnu0MmMpTI6oiCHgUU/FcRiGFb26ZHkw4+joiJ/97Gd89NFHPHhwxl/8+Q/5zd/+Dn2/wdoeJRyPDzc8v55ztTlmuHpFoTXzpWYwt+kcb6fm+eKe/r8P/L+cc/9tIUQJzPZ3EEIo4H8J/L+zz94B/ofALzrntkKI/wvwbwH/oXPu38z2+18D19nhfuyc+9UveG3AaKV7uGfKiuI9w4q6PGa7Efz4p694/fqCsix47/2nPDhb4NSaXfuCoe9BBIpDKUPCs0MKz+PvJ2mw7Pc26xzbV5dcf/KS3XVMDhPMTw6ZPzlFHjRcPXvB9vXN2GM8bpmsioL5nrVI7r3cMQ7Sh5mAC15otOSLwwUHX3+C0ppSl5TaJ/P4WLlOgiEuUp94FGBAoWiakuMzx+2tpV0rhm2BrHuc6hONcaEUVVmhS++NGxEEmRhDLr68yB+7Kkq09IKoKgrK0ocWIl85SJQcqT7js5b+wScBJaRAqwpnl/zkh+f8yUfnPBMPOD1rGOzGlxhmg5bnWOTD2+4MVaXvFYb7mmvifwfl6pyfK207oAdCeWhQ8sHL3/fsnYt0xuFYe4/3LZfw1i1VTeS9xCGxNbpM8aW540aBnEJQGUwUcYgYz889rv0mgi6bq/fP5737UdZ3YNxpRD0kxX930udjdfca42atS17+JB/BjWO8D2lPYvzRAIqDB8x0z4Pimu22D2MqMINhs27HxjDat5gFXw5mw2/7wWBD2Z5HCcJYRiKZYCBHb81YS7frscZSNSWq8JVHzjqGtmdZaCpdMBif/Hd8eIgudDIqB2EyB8UhhYf1ffKe9vHpbPhzZe+cY7cbePbpirr2eQUPH8+Zzwtub1t+9pNrDg8r3n1vidbhesOZIh16LAHO55kQHhUyIZRljKUfhlTWPLiQLJx16Iz0suPzic9t9O5V7AMQThWV9rCVCDVgMQgUvTF0XY/UQaYokeZ0b3psFwh3gnOX+ogwMBiLHRx2bemGjnbXs1zMmDdzihAicTanwp22RI5OXr61/RUPzk4o9DH/2f/zX/B3/s7f5aOPfubDmvqARfMOm/YZ1nQ0FTxa3PDy+YqriytOHzzkcley3tbUhWFW9hTK8Lbtc5W+EOIA+DvAvx0mQgd09+z6D4D/GPjNe87RCCF6vLHw2d7xBfDfAf7e513LW64xSLMAo0QlICSlbiiLA9a3jh/+5BXn5xdUVcnXvv4+Zw8XGG7Ztc8Z+j5ZZeAt86jwY7KbepPUwj/My598wtXHLwBvhNSnx7jmkOZwxuJI0ZuB2eEhl+JT3+JWOKSz2Hs8e0cuxu4KswyNnbyN70T2KsYP5+8/ZP741NfhutC+Vhc+jq9GJZcLQREWr5Ke6lEgEDMoa0W3HFjfKrbrAmMHysZSNN7LLwrfeavrPU1mFDSiFJheo7WlCAmDpS4oZUFVFtRViVI6QaXxlr0B5iYQbFL8QgSovwZ7yF/+2c/4i1cd1/VjFnNFP6yw1iQ2sTwaEr3INMKZUBmf7eerYO80j4ZcUQp2W8duZ1Dl1MPPk/fy38Y3Du9Bjz7Rv+w2Il3eIc9mxT1TKg8VRFQp9+RjGGO0qcc2wiPMH7sx7l/HF7gPB67TnpHPSq/4m/2OYZmZlRAMd+e7+HRzYh2fgiMgktvkEEj4Say7xsV+ERGa9e9rPfDV5jmb261PwCu9CJXSK/6hNwhItLtCjDHmvA2ukGPDorj13cDQm+Ttm8HQ7jrarXdEpJaUZYHWPmNpfbvl+PCAoiiY1yXzpqGZ1aHxlZcgOvTIiHIk8rUXocNcbJoVRyEpfSHoe8tnn644PKp5cDZLQ9V1hsuLHccnNY+fzBOXhXeOsmTGcBz/KNwon4OxGZXpEJn1Qgw/su3lLaFTpn7YIjOhV/jRgJcBsYnMer723vYgFwMOkuE9YJA2EN3YaUdM5yzSDAw2lGfG1alijoBj17V0Q8fKbtm1LeJM0JTVpK25ZzT0nn1cW5NQWxgfaw3b9hypKs7OzvijP/ojyrLkww8/5J/903/O6ekJX/vGY7btM6wdKLTm5uqC7XbLg4dHXPdrtp1k1SoG45X/27Yv4ul/HXgF/O+FEN8F/gD4HznnUl1A8Oj/dbziTkrfOfepEOJ/Bfwc2AL/yDn3j/aO/7eBF865H2affU0I8UfADfA/c8794/2LEkL8u8C/C/DkyUOUjNzW3qoqipqqOGF96/jxD55xcXHJfN7wzV/4OicParrhitvtxzhs8Dql94ogyKjYOWokqnhTGhP4Bzg/O+H601csnj7E1gest4ZZVTBfeKhIS5gtFyxOjxiEZXt5Q9/1CGuxwiYB+kW3u7Ds+D75KUFhH3zwDvXpIRofyyvLkjpkxRdaJ7hXRUpcxoVJGAcdJr2SEm0GCjlQVgPzQ8Nupdlce6hs8cAjBw5HqXp2fUvb90grQChaNHVp0UpQKG9wVLryAi1mngqBVjLkApgReZncf1BqQKFndLsZP/jLn/CnrwY2swfM5tD3a2ISmo/hjwpvH2gB792WlWK3M577PhpV90ACudU+UdwAwlE2kvVqoBA+Rp1D+vnvo4EXPxsF0N1nff+1vGmLFz+eK3kcUd/JTBAz0nzeHaH8vFM0KaIBk/k4sR7ebiynF4OnYRV1j+sVrtewKxB1f+8h3j4OQdmbrLugUKigDJJaElMDOcbb49zy3ei8ED2qWj6Yv0Yagwt1+wktieiVFBR1SVEodID3IzoY93VurEkY+iGdx2ftG4ZuYJCCoRvYbX0DGKXlGOKSAmsIMWa/hpaLBU1ZIqXC4XNrPG9+eOZyvEeP5IW+c1kYz1nLYAyF1ljrePViQ11rTh804Tn7zPzPPlmhtODJOwu0GisQ8pmRlH/2kHzlSvTYLYQeHoM19NbQ2x7jjI/jB6Y9kxkHo8ccnZKxMiYaL0BKTrTOYnsH2oAyeHtLhUx/4ROUbbRJfAiuiCiJ8DCMsSNCFg0vKSXDMLDddUjnHYnL6xs4OPAhHZfLqozXwU0Nl7QQAecM290rfvXXv8nQaYwR/MEf/AGPHj/k1atXLA8WnJ4dsN6cs1yeUNc7lNYcHUma7pazhcE6yaZT3GzKty2ML6T0NfDrwD9wzv2eEOLfB/6nwP882+d/A/xPnHNmmmwmjoH/FvA14Ar4vwoh/nvOuf8o++1/F/g/Zu+fAe87586FEH8N+E+EEN9xzt3kF+Wc+w+A/wDgl375206JCiu2aFUya05pt5rv//knvH59zsHBAb/4nW9xfFrS9pdc3b7AYdFKJ7amEQaP0FSm8D9nixaurGtmX/06tztokDx9d0YTar1jL2aE5vGvfJN26Dj/0cfsrm9pbzfeOg9kki78/z71P0FjR4DSj3f4X4SthfAZwctvPGH24BiJoFIlVVFRFt7SL7SO4zkm8+ydS4qxo51WCuv8uGilKG1BVRjmteXgwHH+rEO5kqb0DTq0VKlcUiEZWoktfLvOQisKqX0bz6LwxDx+3nhrPOQIKLWHPjAqC+schZ6xXVX8+Z/9mD+9AHN4RlVZ+qFL4xA91/H/4zBGZee/893y2l3Lrh2oG72nb8b8C8gJcbLHEj6X2qFL6LYO1fh+g5O2s7nCd3tKM86CeybBvoN635YUO2NmuU8uU9kxM2VEfnLvsY/Xsn/w/LcjGjBmLN99Xvdtbu+Ns0Ax4KSDckAWBtdrn9xXDm+4mLsDFO9vVDDjeKdLDzHhfDBj8pVz0cMPVQ4OCmX44PAVWjhkMEzNMCRiGal8vb3SiroJuTFaJkMi8vYPIeavtWboBvoQcho63xMkMtMN24G27em7zhvuWqVrGnrfdroqy9TPviy0ZwIUEicFLhjKEOvp8zyk0QjMw6J5+Gy1atltDV//4CiFGrbbnmefrmhmBWcPm9T90s+TTIGRtdl1jkhF7CCV8TrhcMbXyXehLK8dupFpj6myj2jNWEJ7vyMmc0Mgorbe2hqdqlDCGNewlBJjvIFopEcEnbW4EG6JxkaE7rtuYLtr6TvDydEBSmm2m5ZK7yhCbpTXJTJG1cYxigMUjCgTWzULMGZN133E6fG3+OM//Cs+/PDbWOv47LPPKIuaoVOUxQ5BxW6349GjMxCtn6+AxLAoDctqHx2bbl9E6X8CfOKc+73w/h/ilX6+/Qbwfwo39QD4bwghBqAAfuqcexVu+v8G/E3gPwrvNfBvAH8tHsg51wJteP0HQogfA78A/P6bLlAIRVkumKlD+q7mRz/4jGfPnjGbzfiV736bw+OCtr/iZvMS3/7VE1l479YGCJyUfSykY/K0yGCZ+zx+B5dXOy5e7WgazTvv+/arbk9iiwD3FEqDgJMP3qVrW17+yY9x6w0gcdhMcIYThvPflXl34/5jNYGgOlyw/PoTyrqmkJpalzR1jZY6ec55L2x/ngR0eGGhZFIeUdmqgB6kBUngoK5ADAW3lx3L+dhwxjkf53fOcXNp0M3Asq6QSlIWmkIXoZRopHsdjEltLQnGVxRi+ahW5Zy+PeD7f/l9wDKfV9yqzrP+JkGXfGiiURUfXLLAg5JyeCU5m2vWqz7QNstx/3BD0TMeM+9tGrvkZTqLKh19D6YFyr3EzfTMYGTHG0faz4Fo2P1LblEYx9ufHM5N/0avNfMMp/Mws2xihp8YP5siBPFzkeL8+0p+8kIQFDvpvf/M4LYaXMgqFPcc5D7r+A5KEXJBgkCPCnRU8NHjGgcohgl1oXi62FCXKoScnO/j0XsFURQ+nIUQKCH8a/xa9BS+FjN4WLnvBpRWdKbHDMbXpRvPyidCiKBre9pdS995LoyqrlLjnr4dwDqqquBguaBpKorCr5+09oXAKpe8zeQdB+TPZ/J7eSKV8uPB+Pycg4vXOx4+mqG1X+frdc9nn644OCw5Oa196ezUwUvevbepglcbDB6v6P1zsSLkGxjDbuiSwu9NH4wgvOGSz6O3bPl0jueI1+T/ellnA6e9E5690Bjj5XxAvxAkg2RwNnToFMkABo/IdG2HcJK6UCwWMySSfutDEuvbLWrhqd5l6B9kTaxJHGVRruy9HgqOoXKst8/4a7/5y/z8Z8/44Y9+yG/91m/w2afPefnyFb/+176NDu3NtZZJmnkx+cWc1M9V+s6550KIj4UQ33LO/QD414C/2Nvna+kBCPEfAv+pc+4/EUL8NvDXhRAzPLz/rzFV3v914PvOuU+y358BFwE1+DrwTeAnb7tGJTV1+ZCf/vQTfvbT76OU4he+9QFnD+d05pKb9SpcqFfwvlQmni9vJOEnfCJESfSowRI2BqX1RPA457h4vePmquPRkznzRUEED8ZzjGl/1gjW14ZtOzBbFjSV4uEvf4PzH/yM3dUK40BicaPhnAmkvRsPwjjKZD9J/b01j445/OrTwL5V0FQVTVln9aUjO2G09nMPP7ewCQp3FOne6vaZuRnkLgQPHpTsNobrq46zs1mgKFZp6Zq2ZXOrWM7mnpo08zQm9+dc4rtOpvvka4fWDaY75E//5PtUVckvfPsbnH7yc373RUcv6nS1U0U6bR6TDJq9tVKWilYbttuBxaJEiLsKfz8TP36ejh2MIVU5+o3PC0GZN4qx+5T8eL37Rujne/vx/v2cDkl5+/ZqRBtydrEgOEWOgqXruu/qR60+8k9kv3PeoM4gkvFYuR1x3+ULhyit9/brYdw5v47Ps4ucj7HL0LVxBFoy8y+8Tt3vsv0EltNyRd/2DIPBDJau7X3eSinSg5DCV8ZY61LnNxPi8+2287FpY9EhXo/wssj0Ywx2t219YltQ+CqQvzjnMN2ADPSxs6ZhVtcpIW9acicodJQLI3oXDXslfEVRfApxn2jkrNc+U//o2K+hm+uW589WHB5XnJxWCdLfT37Mn4qN5ZCQrQuf0e5ZPXs6M9D1nU+I67tUzprks5su+xhiyJMs/SoL8kOMKFp8zkoIbHguznqeEcCXUTqRJXl6OYUgzXsXZGpEBayxuMEikShZo/oaRYnW4Apv2LRdx2Dq1N8FF8Y+kLg5SK3dpRx5EhLa5mCzucL0P+Xg8JS/+Td/FcsNT9855uXLV/zZn/2E3/hrv4rWmrYbEKIJ9zP2CPk8sfBFs/f/AfB/CJn7PwH+HSHE3w8n+d++6UchHPAPgT8EBuCPCJB82P4tptA++KTB/0VACgzw951zF2+7uK7r+ef/7PfZbne89947vPv+GdZdsdp+QozTC+IECovbORRMPHeH1wB+Go2LOdwLFjcZMF+jumN10/H03QVVrcL5ooU5LgxjHLc3HVeXLQJQWnD+Wcfxw4K6aTj58Gvc/PwZq09f4xCpmUysr92vSd5/sDI0ThFA9fCI5Vef+FpcFLWuqHTps4qz1pjR+4mwZ+7VxdKbvE43jpENbdiiIZM3IJFa8PDRnE8/ueXgwHeaU0omNKGpHOubIeQRiPQsomEUjSy0RkibyI3igoybUjXYI/70ez9EKcWH3/kaTlzw8GHJdza3/PGmQCg1KqA7WxgDzxl6xwMWApqZ5vbGk40U5bio4lwwKbM4i9VPxsp7kk44RAmmlcj6/g5yEQJGerh8zKsYp+GbVO7bt5h4F494dzxiHDsZf7mRkTvvIrc07hlXARHuT3Za/Mk9RtuduSymx0k/1gb6AgYJ2u4dJ/sJ4/+cI5XpSeW9oogkDcOQPGsZKLRTXHrveIqeb85fIfuW1bZNSlxIQVEozGBpXYdzNpXfxTi9c76kzwTUKuYKDL0nr1FaMQTPXoTS1r7zdLxD71GPaJwrJambikJrFssZB4sFs6qhKqpgyMuE8EHmuIS1nUJ0Ec0k94STFYy1lt124PRBg5SCi/Mtz5+tefCwYb7Q3oPN5Fo8R1TGcS6ZYawaMPG9FHSDz/HZ7VraoaMdvDE0WOOTm0NO0b0T3QuHO1MufmWdQ0QUJ3rRSoIL+RciInBZTkeYpEIEAiVrJwd1Ye4KBKb37YyFFUhtURJ2V5LZESihPFCnCNXDLvS1ip+8KAABAABJREFU8s5RMiTCWCmlktMzCbEEY2m1uUDrLb0F53qa+oDv/NIH/Mkff5/vfe8vcM6yXq2R4oFHMTLkwLq3S4kvpPSdc3+Mh/Dz7V5l75z7t/fe/3vAv/dF9g2f/cf4KoAvvG23W+bzBb/8y79EMxNsdi9o+9ukuJLFifOWW3Tv9jYxig7/Pp9ggqx8z8dIL17vWN30PHl3QV1Pef3j4jKD9fSv5y1SwclpzXxRAI6L8x0XL3YcnWnqqkJ97V2KRcPVjz7FDYboQ/ue8SPEHG4pXJYjJuUIPE943cwopUahqMuauip93E/rBGtOPK0EbceDxkSjMelJME6mRKnrIuNYPoqS+bzi6Mhw/mrHu+8fZNnevjnSONEjQ9lUiPiXitjNL4YgovWvdQXulO9974dYZ/nlX/4mUt/QdS11U/D0UcPrn2/42C7Hc6fnEs+SefwiO3g2ykoJ6kazuu04OKrw9tHY1c5YmzKMU7JYtrkgUKxzoPAc6J0au8hNdt+7vqTz/MVNkPO9n+1/dBcBuE9Ru/H4LjNQxX2/i+tl7/d3YIO9X77RShnvJxL7iP1D5zciHKIccJ03BJFTVOi+sXHZXI3kODFmP/S+FLRQ2je/yccg0mcLgbOGrzafUbmBofdeupSepTLydZjBx6WVkqk80Aw+8S7qLiUllBoREgIjNbUx1sP1xOcQ0KFAXqOkopnVNPPKt8A9XFBpTdM0NGVNrXyJq5Y69f8YBcNUoRvjuL1tWfz/yPvPJkmSJE0TfASoqiHHgRMV6uqq6eqe3Vui+w33s4/uyxEN0cCemerq7gIJIgN6ODQzBQLuA4uIqpp7ZvXeftocrYoMDzc1BQIYvMz88nGd5IQ+2HexeKInZzVGa7bbgW+/vuX4tOboWJwGxcP1NTWaYsq2d94nfSr7RBlwfqDrO2639yOXfu6qlzzsPF8ZUZvd50F77NFC8zGCChCiEHepiAoRJY0HMDnBMRMDTffbFLWYrb9xgcWQqomCUIdXlWa5UGgHuyvN6thia5Ua9oyVH3ldRbJBrzDWJul6YMBkxEhLY6AQWmI0aG1wfs/6qOY3v/0V/+O//0HeBU3XStVCjNnI+uvHT4KRb7Va8r/9739P39/R9rcMzpUFCBQvU6vMEnWg0GfH47/P8ismyO7yY8duO/DyszV1oydxMpUWCdzcddxcCxnM+RNR9ibX48bI8WnNfjfw4fue558vWNQanpyjm5qbf/mOfteiyZCVtKQsGyFtKK01prIsX16w2KyoFg3L9RqjLMu6KQrfpnafkCzPYu+Pm1gnTGyEvEaYTM4b0QT5xVTwjxC9MRXPnl/wlz+95/Zm4OJiSUh0ltdXe04vFunaaqTQVGOYIsr+kI0a0/NGuZfRFVqd89//8c90Xcff/8OvsfU9fb8rxsjJ6YLPP3W8v3UMD5b4+ELl6ZWabPY4O3PRGIbes73vWa0tIPG+mBo1FaUf5h7oeKU43q0KxNYeeKyjhFE63zXP82R8R/usrIFxLUzcU9Sh3J+fO3+4ogBG2HSaS5DPyBbIg1f8kWNU2D/00ey9HpyUrZk0HjpIk6bBQO2Yjtv8/UajW5o5ZQ8rtWpO3A/FyCljGQvakj2uM3tN7Xd4YzFa0SxqTMre1kbj07VsVWFry9AOE24JBKlK6ELxxJDnGPpM5KOwVSagksRbbTxVbVksF5w/OWGxalgtFqyWQljVVA2NqahtjU2d9ZSezFN6n2nI7ua6ZXs/sDmqxfmZQPP5yCRSyii6zvH623sWS4s2mf46j9N4nzyO0yTObFg5P3YOVCi2bcuu3bPb7fGJFEdZJRwF+Xn14XwyzieQIf3pqsmJuFHQ9LEsElDRjD9n4ZURuRgLfW5GhrKRHQU6IOqcm0CC5BVYoRevrME0Yuzvrg2rI9BHMXXtixgyhbckPU+ZXTIjY0YD8lxkB0faM+fkavlOP9zx5Ok5v/zVz/mn3/8zIQxstwOb44YQJomuj8ii6fGTUPoS37ih71tpSRilW9LUS5rGK1USBv+WpId8aG0wRspkri57ujbw4tWKuhmzV5WSUpr7u56bG2FvOjlr2BzVs8Yt3gd2O8f1pxY3RDZHNZfvOs6fViwWC8yJwf59zc2/vmZ/eVvixWRFjMJebLBHS+GoPz9huVhKgh6aqqpYVClpz+hZFUIGOWYgxuQfObtcly5scvLM24YZApCFTSS3IK2p6obnL5/x5vv3HB9vqCq43+4JMXJyvBgNsDgKn2kXM60VFULuU8oGdUVln/JP//M7bm/v+Pf//rcsVnu6YSsKMxsGRnF62nC6G/gQcnVCfucpUpIUchH+h5JG/lptLLfXPV3rsTXCGJY59JPCL9HEA+Uz+9fUYzVxZjQpNSePGYVxhsHHORoVf5z/Iso9snXwwyjfXIFL58P8KOMHD5NHx/pnMvQ1e1U1+TufM7FSZudMjCt18J3pc2blAlB5YldJ7wYdOJzLR02HbMBGVeD1w3h0yBTRIeCc/G2V46n5KIiANdjGpkoSSQbMSWtVXdEsapSCqrLlGplgJ4SUFZ7QBed8omcV6ldTWSprSn13hvKXqyWr9YLTsyMqK0hgU9XSaXKi8I0yJXmPmJDISUJXBFwfuL7quXi2mE1bDulkhe0yaVDwvH29o1lolquK+7tBDPFZx0hhOD3Mi/Dp/Ur/AZXi+F3Pvm3pho4hOInbWyXerwbFSEkcJ9/N1y1/H8jyvAAikjAqujpKpzsUuRfOdAUWo3jCFKiAMCFMm+YOlCPpDa3BBU/bt9jKEisY+sj1Vc1yMPjjyKK2giRFU8jG8l6ICf3I76LjAdKQ3v1Bh8Poafsrvvjic775+jvu7+9p256zixXO7clt5B+B+mbHT0Lph+AZ3Jbe7fGhBZXKVVRKTnkAH/+fclnKEaPi6rJn6AIvP1uXOG+OId3dDVxfiWd/ctokSEwVKFgpRbf3XH7c0/ee4+OGZy9WaKO4+rTn04eOi+e19L/WCv2br7Cv33P/9Tv5foyYzZLmZ0/R1mKUYVFLF7pFLd3xrJJGNU1dpyQ5eCAMJ5vpcGPJRpGOX+mty1emCYXTTZTrzsmGlFIoLKenp2zvWt69uePp8xUfP+w4PV1SVZmpem5s6JhLY9Jj6jH72RpLbc/547+848OHj/zud79ldRTY7e+QLi0Uq1glxf+q6fnYLoVCGfFQpu/x6OY4UFJKCTy72ljubwcWWhF0LCQfOb5PjAdq/vFLY6KwzvUGGjf9dDLeD6/0+JIdPa65FZeuMUIZj3wv32v04h+7x2yoIsxSJB7o2ceU++TZZq91qPyzIZIuGqfnyO+jitKdcdDESqpw1DTqNRXaYV5vL8o9piZI2fCV6+cYtCTrylo6rbdUxqOVoVnW1E2V1vUYL69qKwo/GatEUqKf1NuLwpU5NpVJrJRgrOS5GGuwtcUYjRs8fTuIR60rVpsFm82K5UL63NdVRW3GZljW2MSUmcrxHszbONi3tx2mUiyXJinUkSI2Z/MXWRA1H963aKN4/mJNCHBz1UloY0ZVPPf2QdgDnZP2wMGH1JFTuuMNiT/fE1CVQlmB8fNsjAp/AusnsqcpkjDK7tFQj6Rcu4MlP7U1c1jOJwOdPI+R2b8zXz6HuUBp3lQUOTMMQsRkk1e/dx3aVrj7Dd2uZnU8sNmIXNa2KcZliDnJU2L3JpVM53DAgzwLefiSqFdVKz5+uKHrOo6Pj/nTH//CYvErjk429P3tgYH9+PGTUPoxeobhHh9alE7eyIHl9H/18D5y+X7P0Eeef7YW4pb8mQt8/NCy3w6cP1myPqqo7Dzxy7nA7fXA3U3H5qjm4tmCprapUY3n9KwheHj7zZ7jM0uzSlS2X76k2iy5+ZfXmNMV9fMTfIzCn21qltWCRS1KvjKi9Bd1XRirJqM0/pSqEiJynQLNkcrcpsqgbMfxp4yS5YQYEaB6dj/JZK559dkrvv7Ld3z952uurnY8fbbi8uOO1apisbSJRGNUmuVeWRiljVJXp7z5/p7Xr7/nb3/za84uFmx3H9Izj8JYKUXfez5dtnz2dMHVTeDPn0YvfyYYpsdjkoJRBdtKUy807c5jV5kHPJTNGw++A8yQ7dGCp8D8KsP8U3g+zn74wWO0TQ6Vp5r9boTq1aE9M7vPNLY7v//jHvTs97PHTffU818/fKPD645CXAwANb9m/sl48JboNMpmeGJEWTIUK+x3cfwsNYIKqUwue3nFy0/f04l0p9XHLNe3WGNYb1YpRi8DmDtJ6jih5U7XyvF6GCFc4dSXmn4bBFLWJnfaU0QfGbohIQmGurGs10tWqwV1JXXftRHWSmsMtakmybPZfJZNqaeTrBTt3nFz1XH+dCGKykWWS1uaPU0rd5yHy/eCPn725YamqfBe0J5hCFTVhEcjhjJeAN6PdLl939N2PSAVLl55ghaoXAGVrVJ1Upx4s6NxNiYWzhfPo54/4hyk1y+ySSktPUF8FA6UjMbFMe9qamDmhOmMDk+PbHRIp0RJ1NZRJ2MmQoh0rocwYE3P0K3oP6wwKlLXIa3BiJ9wNWijwKa1m96574OgStW8D0RW+MbU+H7FH/7we54/f5ri+//M7//nH/m7v/sVm5MTun+D4v9pKH08gR6tpwtmOrn/F68fIzdXHW3rJYafFH5ODHr7egfAqy82NAs7u69SiqENvHuzAwUvPztisUztffXIZOWGyP1tz+l5gzaK208DPniOLjRH56c0/8eaECPOSSxw2TQ0lcT6apvgvtz5r6zZUbDmspQsoA7RjjH+l72hOEEK0rXShspwavaqp9apUoZc+WCMZblY8Le/+QUfP37Eua85PVtyc7Pn44cdT56ueZLYvjJHd5ZZPmTYHFaLE+5vNX/817/wxRef89lnT9juL0FJYqZJgkcrhQ+R9++2NI3m9Lzh11Xk6+sDxRgP/paHn3+sHp5SN4q+h6EF3UyMqB9aOI/bXMIDUXlpLGPGvJOMzP9bj0MlPlXw+YTZI8RHvhcPrzOaePMQw6FRQFkP+ecfA1BmoxUf/vbBv8utR9IYuXiUxjzeiIE/MdbGr4zCvRio6ZqihE0RpD61WAWFNmCMxLA9lmp1xKIK2Hpak66Iud0qUwU0svfpxG0xDI66qakqi3eWYZBSLUn2yjz7ojC00Sw3C6rGslw2rFdL6TBpLDbRVWfqXK3nbb3nCccJvfCeYYi8+U6IU2+vO7o2UNWal5+tZO9MmtX0Q+Ttmx0KxVc/OyqKR6mIrQz7nWO1Go2NnARYiJ/S7Yfe0badQOFKlXLC1nUok1kMM/LJZC1FYnjwGhQQkSkyk3+Z1kWK5QsqJ7I5N/kJLhDQ+OjxuRoqXUNrVbL1MwmPrYRqfKQjzmhDnv2Rr18j6E0gCrtg8MQQacMnjNtSXb2gXigWiSwn4xk3145mYTg91WU+Y5TE8OXacn6+LEZkNmS0VtT2lN//82tCCPzN337BEN7w27/7Gf/jH//E//gf/8rf/8Pfsj6K7NsZj92D4yeh9OFA2DFaZzBhh/r/89htB26uW168WlM3o8Lv+8D3396xWlU8ebYU6y3m8jfxeK4vOz5dtpw/aTg9X6TEnlhK5frO8+lSkgJPzxtOzoTJ7uJpw/Wnnu1tx+mLGqKSxBgNdSNtcJtamOxEIIylR3FiFcOkvzfj738oxJEV/vxzNfmvjHUII8ypMsSoKrSqMGaJVhaFpaoanLO0O2jbwNMnX3J8+oG+kxg5pNhV8gKmAiTGyKLZEP0pv/+fv+f09IRf/OpL9u0NwTtiDOicrIUIiE+Xe/a7gS9/doJSimcbxcUqcrmjnDM94uQ/ec5yvHaW5JSEwmKl2G3BO1CGR4/HRzbfKH1qA8prGAzUHpU9ZHmSR7zy+fMXIVSE4zyz+QAdfPiM+foTZ52D76jJd2OcXDMbf/M3ml18cmr24dIFDjz4ct25W1eU6dRbB1TQRGdQUaPw4/fSjTLRTSR7kjp5wKCqcb3GGBlS/Lm0v1WqoABaaXZxw1G1f7BXtDGi+H1I3d4kvSwEgY9zZQpRlIl3AvWb5PXr5OkTpdzYVmbMFdAqceKPylwrlRS9KcmqwvA5f67peu1az+tvtwx9YH1UsVgaTs8byUFKpXFSfeC5vh24/NhydFxz8WSBMiPcHGKkWWh2257j05rEESTKOyNnGc0cHM65VCIpfCam1uxdBC8eeeJGK+svJ+HJxGSDMK8qlWTNdB/G0cCLo6xSShBDF/yMOCik7nw+pjDc5JCQDmnOdUkmBMbxz9Z4Xrf5wdOa8nHCDZDXUVAE1bPr7rm9OqZq9qwXUFnpxNc0mutPPUdHDU0zIjZVZWh3Ds7LhEKiTK7sEe/f7Xj75gN/97vfELnG+xZlP/K7f/g5//W//JF//G//xD/8+9+wWP0v4OmDeIaHiQ8UJTiVWD98jNWb47l95/nwds/FkyWLTKkbxCv/8G7P2UXD2cViFncKMdLuHR/ftwB8/rMNTSPWvQ8epTRuCFxd7rm9GTg+qfnq58eFwQkyY+CASjB+DALFYyR80TS1xPa0kZ7yE8ubyUaUq02TcGQBlwxXlYWgfKqUKt3wYCxRzOfK2DJxJhVaVyhdY3SD1gsqu4Joub/f8/3rv/Dm7Vu29/fEGPnnf/qe3/7uJZX5xPFRhkG9tOXNz5o0UNWsUPGUf/wff0RrxW9++0va9goferQeqNKzi8BX3N91XH7Y8erzI6oqJTPpyK+fwv/368m6kMsfeMGx1LlmhZEVn2Q1Z4se6iW4KF3xHtteh4r50Bsvq8066MSzjCbDgFnBjury8BqPHYf3+rHzHxg+cWYup+uVnOgDhzzjQZP3SL+feW4H33hIGZJjt2OuxfT300x6pRR4hfJWzrVBmvIUsqHkvSWYPsPr+bvT32Wa3QznmwKzZ+78MQ/mdljyynajUZnfVJG8+fRWMY7kQ5FiNFS1tModBodC7tEsRMFIiV8o8f2pMT52uRw9eZMSX3Uq5C217AfDGkOk3Xvefr9nc1xxdt5QNcIk6IOXjo8uEINiv+24uxmwVnHxfMnp8YIItF0nOQeJaMhWittraUdr0zjldQPitbdtz/1WLGuT5JEuZYujETb+Lw1XyIm7k+SM1LRpbrhOV1z6d5rDXBevyURrwjMitMYKVCLRUuN6IArlsU78DYfVAY+brUmm5m2hKMyCSivJsdAKVVmCC9z3nzB3NbrymKdG0BkPy7X09vh02bNYVOn+0qRru/Vp7cvzWxR1dcLNleaf//AHnr94zpNnFbv9FdZqQujph/dYA7tdy3/7r3/g3//vvz3cgrPjJ6P0bc5CPfi9UmPzmPzv6TGP75QvAeCGwLs3W9abis2xNDFoW5fiXoHnr1aJgW9cNO1u4NNlR9d6Ts9qTs4W0lErTaT3ge1dz/WnDms1r77YsFrZMZkGRddF3l3eM/SBi6cLjFFU3hZyHZSiMgZrJCZ+mLAnTFD5XShiIostNX/N8v6HCAGMLF6HNtMI71mUarBmSWU3aFXz7u0n/vKXb7i6uqKuK548ecq//4e/5/b2lv/xP3/Py1fPOH9yzH6/pes6NptGoMDqiBgqYiqcv7ne889/+CeGwfG7v/81Pt7RDzuMBa3FZfBBPJ6+d7x9e8/5xZL1upo961en8J9fQ+vmyjSPxSjMRYlk+HAaW1RK8ot9FMWvArPG1eO15r+b/St7NnksdQAbCIOW+nNGY20Kp5cOdnlCecRLf/SYa4USwTjYJBPnZTx9YidP7JRHbjgxtKf/KUJ0flacPMC4ZucjV7zAGCFoVLCSsW8DqnLpPRR4DXreUSzHymcMg4gidoN0scvGsTKjwM/c9lPj6bqtUejZmEyfMSt+YkIScvlXkDVirClOQEgkPW7wmIoi6IVYRToAZs8yj4gsRzWq+bznJvJmWkWjUFxfd7z9fstioTl/Il3f7u96Lj90xTMWAhhFVWuOzyybI+ncN/jU/Cd3g0zXHwaPsckQjLIepyGUYXAMTrqUGi116lpLsbFLSY3Z45ZhjMVAeuzIn2fZLBUFoayJkjuRZL4OKuVJSCkdSd5Kw52KqD2R1HBn4pWb3B1wwukfD2Nsk4WbSy5Vct5cSuYr3RgTKZXzHjc46VNi9mxvDat1h1WSCGgry9nFgg9vpaT75LQRhMfqkl8SfKCqlzTVBa+/vebPf/qW09MTfv23r+j79yiV0Uf47ttr7rcdX371ivu7Pf/tv/zT4wObjp+E0s/eakmmYYTwRMbEEVKfHMXejPOLSeJd5O3rLdZqzp4siCFyfd1xe92zPqp4/nKFsRkCingf+fB2x243sN5UXHyxoW6E5zt4udP2ziVGPsXZRS2lfEkweOfpusDNVU/feU7OGp6/bFBasj1rW1FVNjW8SR20zJyFS141vY96WPIxg10fgfllHAHm2bI/ZHHLvxXW1NTVMbc3Hf/6L3/g4+Ulpycn/P3f/z1Pnz5hsVxA9Jyfn/H992/405++YdH8Dd+/uWaxqLg4f0LXKv74z2/5ePkJ7xzOeZxznJ2d8pvf/gpTtdzd31DX8nwhjnF/HzTv3t5T1Yaz81SWpMbwjjWKX11E/vs7HmpmeXMyZBgLs5WafZzfPbfGLeZlsRmTZzyfjgdHQRCy4K4CsdPEQUNqiakm8zgaKQ+Vo/w4cttPnzV/9vBZHtPmk+s+uFU2OLL/E4uH/ehQ/pAkf3BM32v+DDF7zMGgXIWqAjRDmtd0topEr1FVNiRyG9TJZadDlTLKY4iYKifgpXnQB2W96fq919wPhk3tHhjDeV/kbP9cepoTc1XqvmatGPSO8RrBB7zKtePy7DFCzqGdpc4m6NqkRNkYgrBVqrFnRggBlGa/c1x+aDk9bdjvByLQ7TyX71vWx5aq1uKVKqgbjTYp5h2FSi4re5dIc2z0EODupqdZmBLnLohmCmfkNrIKIafRWuOCtMj1hER9e5BEl6zMjObozMSnmJ1X4PyYqiy8L8q3PItK303EONmwDDESBkXQPv9yNn/o0bgsob0Ufp3lhqX1k581IlUZQy9MisYYnHMQR+fOGE1VVwR6+q7l/sZCuGezXFFXiqYxXDxZ8OH9nk+XLc+fn1JXZ9R1YNEcQ6y5v4N/+tOfuLvb8vLVC375q+c4/xEfRv6D9+927PeOxULz/KXl5z//Bf/43/742IYrx09C6R8eh4l0RXnxAyLpYEO7QZLzbK04v1jQ7h3Xn6QU7+mLFau1LdfNUNHtTUfbDTx9saBpDErFUm7Wt4Gb64G+96mUr5Ls5iQg9ruB2+uB3c6xWluev1qyWGZvVVFXVYH88nsoeKDwgdIN74FI/YHwxqjYf8RffICSyJWVslR2Q/Ar/vD7r/nuu9fUTcPvfvd3fPbqM6yVpMZs6RsNv/jFL/iP//E/8h/+w38mxshisaDdBz5+vMQ5z/Pnz1ksGsliri2rjaXtrthvt0QcqAqUKUIghMDtTUfXeT7/4kg6m00Ufn7cX15E/vu7AwNv8k/5Tublzo19YoH0fPC4kOry46S73sFxOIrx4MO8CmPMYxhRlRemPhsFQsiCa9QKyVDId4gPbpJ1/PxejzwDowceH5wwte4ozxdzI4gp/36kGDmzJ/qhdTa9RbmxeuwMufZgxJOvHKo+HGclpY9uKsvTAB3Ef1VWLOl7OX4rqNp0XWcjYLymUnC5q1lXQgZUEBGVFTyErMiTsSiOh1QJkMryjHR4KYiC3CqWUtLcTMdqk1pwGypTSYKusSP5Tox4IjoGIjlpVxDAvgu8e3PL+ZMVWgW2u4G+9Vx+6Dg6rjk6s+KJxjGUV6BqwAeP0aL4pdudR3vF0MG+9RydrkrJGWn9O+eK7IhI5YFUKnj6fmDwQ8mjmDr2oz2a1nYqpTw0vEAQlFwdmMdHEjvTfKZQikn5ELIv0x4NkeCAhrJIM9oVQzYosuGQx2Ia3M3Ghij8XI6pcxt3pUqZX0hVDt6FslcjEY8n2pb97YZ+2LH+fAkKhkHmv6o0rm94/e0e5+6x1vDt1z03Nx+5vbljs9nw9//wt5yeGQb3Eef74pzd3Q7cpmqwGCNV7VHmht/+u6/4seMnpfSnomHGg65GXvfx3MnORqY6BEmse/t6S9d51tpKZr6Co+OK49OmMOqNF5Lr7Lee5dJS1aO09S5ycz1wfyc1m0+eLSURMObEl8D1VcvtjcR2nr9Y0ixTss5E0WYq2vzvkSZnlNpJhUweK8UbJ98rMbUJTPVAQU6OKYQ4NZ60brBmTddavv3+hu++/Ve893z55ed89bMvWa2WEPVYx57yB+7v77m8/MjFxRkXT56wWq347rvv+frrb3n+/Dm//vUvaRYVg2sZho5h2HO3vSSEXtrralWoQDPa0bWem6uOl6+kcmJ0y+dzvaojX5zAN9dZS8XZ56NXlTiwmXgzcUK3m6HPSYOdqeKJs1kYf09eZWpyboKBlYkoE1ML2TjrFHZ4DRGwD99xpvknH/+AWv2BX0xBADX7XVaaDy4QJ0myk4+zIXD4DPObPfIcUQnq4ZUw75kDNKD8mH4fYEZ1lk4JXubOaOn7IKVP5UVK/H4aMlOT24jlBZ/2C7463Y0ITVonpPiwsYbg/Yzlcwp9h5CM8AzNp/KykOh6QxSCH6M1lTaSrKc1lbHUpqIxtfxejSRbWhmMrlDKEmNFu3e8e/OJ1XrN8XHDbrfDu8D7ty1HxxVnF4308ZA3T+8pc6cSrO0Sr8DgHZ0f6Lse7yLttcXWAedbtltR8lVVzebUp/bD2mj6bsB5R+8GAkHCrj6S8yhKRCwtEJ3abueQmsxLSgxO81zmTwmh0Wh4xdRzIHcLHY1xaSWdYnDaJZmnikIuLX4niGaG+wUoiDPPPYYo7zY4qjo7M5Kk6QYJYfiURGoSe6HkNiCJkUOEvsKHyN2tY3vbYWxi5EOx3W6x1tK2e/rBcXJ8xK9//XOePFsT1R37bjeT6X3vefvmnmfP16xWFTGNXddtsXYe8jo8fjJKP3vAfvLvKZw9ltZkZT/5LgrvI9eXLddXHSFEjo5rlivLYmmoKoOxo/KEA6MhXXMYAt5FlIXt1nFz3WGM4sWrNcuVLQvJucj9nVhpWimevVixWqVs1ySA8iMetr8dmfHmbl3WY/N48HhMs6HztWYKKI6CSSmDUO5qwEgmvrIoNM7Dbut58+aSjx8+EULg4uKUn/38c05Ol8ToGIYOrWskoUbs3atPV3z77WvOz0/52c8/w1byTKvVVygCv/ntLzFWsd3e0vU7nGtBD2jtMFZhrQI0VQ5vIGWO79/uODtfsjmqDxYERcCnYkB+dRH45nr8fVbROXknj1OJByYyDx99Uf6SezGW/uT/Fk886d75FBwo0MxCmLtwqSjQ/mCIvYXaHXx/nJ+ZEp14pbN7jK/4bzzi3IZ85CIlkznOrz3mGsAU9j+4+vwoFkGc/AIISjz8ANQD2kyeabInCqqhIgSVGhhlVILU3W5kxRuh+JiMxdxmVwmqk65VGmVNnvOurxiClFRnzziX28p1ZeJ1Up4Z3YOxAUyIYw+AIA9I30ljHZWgaZsUfmVsYd1rbCM8/+kzrav0d413mvvbnpubG2IILJdrjk4WoBxVrXn2osFWFat1JfkCUaFjlGS2PCkKWdvJuO2Gnnbo6LqO3a5l2CliH8A62j1UdWDlFwQzNncpIdUY6bp+gh4IghGSAh6RscmcZ29fg8p9C3wkRk0Wg1HJs+dwTFkKatzXc8wtjusjpAvYUCB/kAS+/G+p8JjnSOSQAoz5Pc57+rZP54hHPwyOmKidhxTbN9aA9xChCkGSGaMiqIHoNJdvHVp7zk5rjk8amsWK208NHz9+Yr1Z8erzY7788nNi7HF+y+A+EKKnCJiEJH379S3rdcXJqeRDeR9p2wGtIiHuDnfc7PjJKP3pUaD8JMCzZz05oSx6hSTeXH9qub8bePHZimZhZdFNS2IKJFb4SoFc2iJNKt6/2/H2+30hvDg9a1hvBH7z3kNU7LYDV59alJLmO5nPHZX4llPpCYhitibVnSrNxFGZeGRZCo8e51QxPITmVWohPTViNMZYrFmiVEPXKvoh0PeO3bal7W7Z76QzlnOOvu9pmprPPn/Jy5dPWKzAuR3XN1uWyxWVyc07FF3X8fbtO64+3fDFl19wfnaKCx1dv8W5ln5woAK7/S0xBIahJyqHrYIYWmqsC87Pq4Gu93z7zS2rVcXFxfKB4p6+d/73k1XkpIHrdmQCk8Q6NcJ8xJmyz011Shc9xmtniL4skTQPRbE/4qBOl2ARNFmAJpif3qamPOOcZjNh2p9+vg4Orn/w8w8ZAVMoO12+6P94+MV0UfUA4cgG5Hw8Zl8vQnd683x6Ut69lYtno2eGqJGd79GYM4EYNBAKrB5DnCVXjd3mxmfK2eUzIrt8YXVY3qu4a2vOlh2Z50LYI8czcq26Qrzd7OFlD1XkkEJ52av9MLDfthgjbH9GS3a+NQLrV6aisVKdI3X6FVpXaL2ksguur/d8eHtFXTdcPD1ns27o+z3d0KKixOzXRw11ZeV9ojTFmthHY4w6KWQfAvu+Zd933O92tPsOdsdUK4fSkbquWW+WLBZNotkdS5Odd/TDgHNOOgdGh21sMnIckVBkcZwvCBlhlbL31bgHZavNHaxDJCbtRkEK8vNMLh8HzXSzTL37vOdzHwWVTst9A6ZNf7z3dG3PkLx80nne+XRd2fN1XWGsLt/PTZn0YFHG490A1GyODcu1wVjNerWhvZeFuFobzi5gu/+uXLdKoZ+cewKK7X3Hh/c7/t3vnqQcksC7t1suP+744sujhw7QwfGTUvpTGBqmmy6UxZaVhzUNdb2iMg2fPt3Qbge++vk5tg4E7yRZYirQR/eQKYtKPmOxNHz25Ya2le81jUFpEp91kFr/qwHnIidnFSeniwTvyIYw2ojAii7V6+qDxEPZrdM4ft5Iqnw6MXiYKvzJCUjnKUkEXGLtkmGw7LYDl5c3XH78nu12yzD0gKKua5qmoa5rNpsVzaLh6GjFydkCVEcMN/Q9OB/4+i8fePr0lIsn58QY2e16vv76NRD4m1//jM36JMX7Ova7Fh9a9m2LcwP79i69k6eqFdoEjImALp6TWLSBm5uOd2/vOTlZ8OLlekYQMo+8TAWLwIa/PPf8h2/lJGNMERIZJZHEo1HZ5w562cOPk2uL8T2O8eg9JA8wuxwPNH5ai5mbvcB2CDf/UBE7UfxKZUU/vd+omA4vfXj8tfPyc0+vXb43ff7JQI2CVURubt2bbzJTmo8p+8lHCoheQ2fARlSVqYnV5F6PGRVRNJjLnO3ZU5TQy7QxToxRWqJqgcaLl/7Yk02toPTjbZ+V/gScQBRn7soXQyypClVliwfsE5+9D0NBvryTZLRmXbNcNKn+Pit8y8IKC1+O7Vd2TV2vMGZNZZa8+fYvnByf8ez5OdpEfOjohz1u2GFMja30QefL8XmzQg3pufphgBgZoscFj/OeruvxPlAZQ9MoFrW09W2qOoVETFH27dCza1v6oS8oSEQ6GPooLXMzU9/U0y/IWDHmmVVclDDK4fHYezHuiVH2R+gqYt0DoqCH1PK4GH5pkIKXig4fwSUCpejkZ6WUtAHe9ylkgFAmd0PJno9RlHPmULCV8O0vFg0MBuOXOH2PokZph9EWWwnjamWPubl+gzGaZ89OsLYtlNBTXaaTIQlQ1YZnz9Y0jZU57B373dgf4YfCtfn4SSl9eLyXsFJCbFFXK+pqTQwNu+3A92+uub29pG1bqrri7tqyWi1YrZYsGyVlVGpAaZ/4/Xu8H/BhIEQ392k0aCKLhcScPA4/RIY2cHM10HWe49Oap8cVttJEAkPvE8yYSCRSGYpRara28yT6OM2mz92rRms3VxLI5otynZwVC2hdUy/k/ftO8fbdDR8/SvOatm1ZLBacnp7w6rPnnJ5uqCqpTYsMhNgTGPDB4d0N9+2HxBFQEakBz8WTBa9fX2KMpe8/8f7dJ87ONjx99hRtA/v2nmHwbLf3RDyDG/jw7pqjkwatW4FJlaKptTS18ZmLX97t7r7jw7sdIcCrz444OmqYsZHGA0VfFNh4na9O4T9+53DBzkDBLDoyP7uPU4Wf4/dTxc5EAB2qjxGOP/R+J6syrc05MoFSqHogdrYo/sfshvFOo2f+f+YowxSnBstj+QjTO40CNj/UD57/Q4KnWBkKvCI4DV6jaicwLKPhFgqodmC6ZAspua1TqBakVK50DmQ06IwZaWSLkfX4Q87+te3njHzTsZgqppzslTvS5c+c8zOv0Va28PnX1ci2l+P4VfLwKyOJslV1TFMdY0yD1jUnJ+e8f/+WwR2j8Qzujra7g9QEJ8fFSwyYcY0VON8LmtV1nbDJpdasMQpcrbXGWk1lDatVnRgAx3cKMTB4z67ds+33hPRexprEaBgYgpTyuYSU5T1UdP1EwY9jmbJiHliO47l57MtncXq6hAjUYFBDDUfbFGIIJX8jrxM3SGe6LDdDiKV3QPbilVK0u46+G7CVlRh+lDJFZustlQ0qhaksjVphtmui0/Rs8aFlqTdUK+FvWC2PWdQv+Nc/vOfdu/d8/sXnHJ8sGFyHUgoXBBlWYcw1yu+3WlX88tdn5LwCpeHzLzaEALZSHFapHR4/EaWviizJ2Z0ARmmWyyOMPqbdRT68ueHT1ffc3d4xDAOr1apkrcYQ+e7bNwzDwDD0KKVpmoaqqoQIp6lZLRcslmsWi5rNshbebBwx9kQcLvT0Q0c/9LT7PdeXHe3Oszo2PL2opMTPjNZ2Xih5cxqjEylPqsxNf5fwRISoRsU/6nhVMpLT6RgtbHjWNBAXeGe4vtry8eMnrq6v2d5vqaqK4+Mjvvrqcy6enLBYaowZcH7H4N7TDrJhRVCkFJwkla3OzIQeN+xQWnN8XNH3C/7p918TQuTlZ6ecP12A7hlcIISKoRPPtqpq3r/7yHJV8+z5iohPqiSidZYO4sW1reP92y1d53j6fMXp6VIeZCYb5qWF8qjy6TT+XhnFL87gnz+NnkWcCHGIxbMfPXz5bLxKLmNTo0M49QAnPx/C71lBT53oWSVIPmoHvRWO/sYlxqJDRTr3+vP1+ZF/x8kDTiHvx55z5rmnF52NsToUzo/d+eCEmD37BOUbD9ZBit+PSopZq+EHR5mTiAqKmMJxJiFDpXaacR0UlrWZsXb4jKr8N39vVbnieRUDaTJ2BSVyHj84bCWkNigYBs/QDwVKV1qhG03TjCW4Wmuh2jUVjZXGOrWpqesVdXVCXR1jzRKtpWrl6HjD27eBoe8xYcC5PUo54bZXQRL9UngtrWjxuqPDeZ/CVWKgbHetNAXDE+1IXGOshNEUGm21VMUkWSWNdAb2Q0fnemk/S5TySR1xMRKGQerVvZN9lAZLTRb+1MQs5Xpl8sskJ2M7pSHmHIxxEczmMJIYNbcLWHZEI6iKVkIWlNGWkGB+CbuORkXuikgK/7hB4vPNopZWuH5cW5lkyVojn6f8K200Nlii6XCmp+9bGrWhMpamNiwWSxbVM/7rf/4X7u7u+OWvfsbPfvGErnsv75A2n6xjXRIMD9dsMaKUQleaSmmk++GPuwA/EaWfFB+yUY221NUxxBXv397y3Xf/wna7ZbFYcHS04Vd/8zNOTtZ47/j66295+dkxJydnxKAIXhOiot33tG1Hu+/Z7/fsdy13t/fs93upFU2QTl03LBYCfzeLhrpe0nXw6dM9Fxev+NlXa9COEAdidEmhBfmD9K8umcQzWH/SEnfSPMcYi9YmKQoNUacSM/k5pEt7r7i+3HN7c8/V1Wvu7u5QClarNU+enPPb3/6KzVFNVXlCaBncJYPz9EMcO0ERcMEVASaGiMIog1VjU5FsKd/etny63PLs+Yp6Ybj8sGWxgNOzNSF0xFiDsmgD+/0e5x1ffH6CtdIIRNrL6nQvTdc6Lj/uud/2nJ4u+OyLxAk+dQcnHjNM4L0DT7OEOrTiby4if7xm8l6j4pwpbBQzBp7ZjSBjLOXsAyro6fPNnmX2k5o/e0zhAR1F8Q+W2FZQealXf3DtucJ67AnmRklk9s+pApwI08cY9OZXTqOWkApx0ubXmD9n/l0UyuXlIEr1AL0q5+V5mQEoD+c04gXibyS3xifvJ3ucQPGUFBNmyhmCcDg+8/tmpZ6NMz2B9EPawyBjINztcpWhd7T7jm43hgaqRj6vGou1JsX/RVkYpRPSZzFmSV2d0NQnVFZyVpTStH3H5eVl4vgXaD9Gn7x8JbJhag3H7GSkZDQ34MJQkh33/R4QBKJZNyUZTWkFPhCjJjhhEdVGFJELns4Ncq3o8amXuwue6J3MckjNdsidDg/QmscWKtO9mE6YLCmhV44jSjBFWSYGQNxVRB1Qi0EQDSf7xrtRIQaf5RZjqCEdOSQkRpzHpth8NiaJQnimtZRT17XQoucHkOz9lKTpA5WuqOOGk/MVz54852TzlG//cknb7nn69BwX7tjuBjL5EWTyJi0cCHGs5soOoxhfY2e+TOv+Y9VY+fjJKP0IaGNZ2GO6tuLbrz/x9u2f8T5wcX7Gr3/zM5pGoZSj7bdc3V7y8f2Oo2OLNnvutvt0pQQfGcXmtOHkosaac7Sy9F3gz396y8XFGcvliq7rafc9u92etu3YbreFVGYYBrbb73j/rqFuahaLhXDlNzVNU7FYVDRNJUQhCLQmfPUicAbnCZ7SnUuyQyPDMBC8K325nXOpXET+DMNA13UJzrRUdcXx0RFffPGS45MlzSKi9ID3W0K4pu0mhBtJOJQkthhGga4kmdAojdG2kILkGuePH3d8/LDn5csNJ6cNIFwZlx92bO87njxbQRxA1UQUd/d3bI4aFo0hBKmDDkERvKf1jqtPrRAdrSu++uqEZpEMnRz3S+s6xHHhTxP5ZuWGTESOUqxqxb97Gvjv70YLuqhuRQkFBAUqjj5fuc7Bnsr6LrsqY/z54SLNjo78e2qwjM8LkejF09W1BxOIvREymtqNJWrzF0vXTMGemed+aGaM389+7dxpf0Qa5xdX89+JF5YfYfKCavpwk+um9TQq/Ac3Obj2D1WjpB90THOU3gM1CwnJ0I6c+g/f6bFj/sF9P2V4VCX5bYrA5fK9mKDzYXBcfbxl6Afc4KkboVs1xmAqQ2WFTVOjCwdHbpNrdIU1DZVdY80CraRE7NOnK7755htCCHz2+UuMDfjOk0wPrLIFhk+jXRoN+UQX66JjCCI7hmGg7VuIMk4NNcoq6qYihsjgHU0w4kiZXAcfilzwwRMReaGtKMr8eWYY9aWj5ziuo06arMaJ558Rmul05ES2gpKOMSk5JXnuOEPcVXC8xUeZh+BlrkKMif44pk6jEaLCVraQqI3PKOdk8h1rDUPvAEVtLTYRJNVWaLQrawlDRFfZSSO1UtZYveRkccKvf/7vePv9J9785Tuurq757LMXvPx8xV/+8pqPHxznF8tibgtqoKX0MQRhAo2TdZfGCVLFV/pMHxhDjx0/GaXf1Kf4Yckf//Udb9+8wxjDs2dPOTpe0w973r9/Td937Ha9wFkhUtWazVFVslFjECUSUkKQosWnel/voWuFRtcuNMHcUa8NzabiTK+IcUOICu+EECIE+blre7qup297Pm13BR6SJJCQSGjqEp9x3iV4aSTfGUvpVFFKSmVoydL3A227xxjN+cUZq9UTTo6PqRpD02gRDn5PiJf0Lsw2Sz4Kv3yJ+4VRoWqhAlXoUkcswlgzDJ7373bc33V8/sUxm6MalUIsm+OaZmHYbiXsEQI0dUAbi9aB3bbj/l5xd9ey2w5prCWvYbOp+OKrY+p6TByCcaFPIfFZ8uYj75Z/kyE9peBvLzzfXCvuh1FIaqWISmNUJKqIVlEoPUNAM80XOfBamCvSeCixDtzqh+pQFcMKn2O/oXgTGFALRxyS4s/Us3FEgA7fOMbHN/7UEVdqev7kjB+VGfnps1s1dbqmHr0az43T342nRCGSm3x3ohSS+zWNZx7iD4KCMdbppstkSt1cm68Y103x6mYT8JiBMh63XcXY112S80DmyFbz9egGT9cNbG933FzdUdW2KA1tNHVTS5Z3qk8vnprKLW5ViqfXGF2hlWEYHN988w03Nzc8eXLBYtEQ1UDX3SSylljCgtN9ItwziUUyGfIuhOLxd11P5wfpE2AtYVJ+6HzA9QF7rGnqhtx7PgSfiGky6qfQAWpt0MYwhAHnc8XCWPGSrcr8z0ywM107k7RNSjVOnO/pkkCbyyfiZO0GBfcLWPYoO5LpeB9Kb4WY5JzKRobOG1ahjBj5pdVyGkeRfPL8i7pmmcZDacV6tSxzOSQqbZeaMZloaJoG2jVHR0f86V9ec3N7y/HREUdHK159cUZU1zx9tuTt91tQkZPTRvoepPWQ+6pkpZ47OQIsGtEbYxl3ft4fP34SSl9hefO645uv/0SM8MWXn3F8vOL27pa3777F1I6q0qyOFYODptGcnDd8eNvy/XfbAr3FJJwishb0JAaotSRJHJ1UDK6jHXyJDaFkon2U5BUXfApLaYypWZwsOXq6prEnWKTmPXiFS2VxfddDmmBbpQY6WmOMKqWD1kpGrpQEaawVJXZ5ec/bN+85PV/z5Okxm81S4D7uiTEw+MgQRvaxfGThl6GiGASKC1lIxNR6M8VJMwFGIc2Ikbvbnrff37NYWT7/ckPTJAs3jIYNBJqFKt3MtIlo5Tk5rbn8cM8ffr9jc1Rzdr6gaTRVJTEyW81b2M2TWabvkcl/ePTzg7MTZanU/f8/Pov8f74m6SOFyh6F0mgdMVDIX3Kby2xlTxX4g/WoEPX0ABaICQyYejdTJ1qEUPFaoiLzsqMUqi4sFAf3Orh5es4fHoWDf09smFF8TJR0PHiH9NcPIwOH/x4rD/KlMrKUI8ePfX2avHR41fzeSitw43kKpPvcbC0cvM+D55wjDIcWnEfoeE+qEX51JcM6PYwC14vC329b2l2L1qLkc41+VVcs1w1VbSee/ajkpt5+5sro+p4//fHPaK35zW9+jdKKq6v39MOOfrgHHMYGFoumoG6i6CnInezp0fMenKPrOrquxzmPMVAbBamGX2mNcz1+CITgZJ5SKfGQQpuQkmNR4COVMlRVRRwizgc8kgdRWtOm2ckoj+LAQE/jrpBKlfkH8mFBlPTEKMjT5CHualABtRzSHInTIvLEFgNiigLGso5jYQYkMSpmJWsNeBTWWJaLJlVUVDRVw7JZEL3B9QGf0FjlPVoFKmvRXoNasL1z3Fzf8pvf/pph2BPwhPiJEDy2gpOzig/vdiyXls2mKuvfGEkKzVVnnkSkFCOVFT2Rjdg8pv9LxPR3u44//fFrnj1/xosX59zeXfPNd3/G1p6TJwZdmwInHl8YLt8OrI6E7jbzrGe4J8dHFKJgc0mdICiyKAbnRgs6RqKGEDN0NtAP8scnS7MyFZWyNHXD0XLN0fqIRd2wXtYcaYtWDbkGWGqOJd6Z7y0ukdzfRwheqDHfv9+yvR94/mLNem1R2uHD9tExGiFY0gKR9ri5lW6cxd9GpiydOMRHpS/W8u1dz+tvpczu+fPliEAwimhBDWTjVcmYEaKQyNAPNAvDyWlNu3cYC6tVhUqGjTzrPD6VqxSmxzRxc3o8lhw3elXiQb86Vvz8DP58xQgDSxmGNNRRkDKPJIHy4BlGcfTwmPuOD8948Juil9Q4BuUdRm/oh/dzhB/w7h+eetCM5oGOPkQ0pg89VaBxriCn15kYPPkdJhdJ983v8wD3SKdN4IgDwKB8bVI+GyfjN3sYxb95bObzGctr3vY1J8tuZHEr5WWS8JUhfe+kRNfWVv5Yi/eeqpaM/WZRyz4oe0qQM6sNRhm0ymRYBtB8//p7vPf8zd/8DcYq9vsdw9BJtj49NjXvqRLcnN/dh6RUY1b8AhH77OkPTjxaBA3JNewhRnzvGDoPqdRQK4GPJSkv5WBEndA/Mdsaa6griw+e3qnJfOXRzEmQk5BOzE5CHOWSOlxEo4IWT51xzeR1HCDsDXEwqKMWlIRYtFLoyhKRMrqYEAhj9IhshjH8F0Jy5GKcoIJKyuuqmqaqqfQC7Wr0UBM6w+01VJVhsbYsTmQR7u+hbwP0sD6t+Pyzz3n/Zo8bPJujBV9//R2vPk/Jy0ryKepGYSxcferZbBbzpTvZ2jnM4gapnqiAaDSjdDowph45fhJKXynF3/3uNwzDjr98/Ud05Th5YtFW4cJA20nMmCiW09G54eO7Voh4Gkl+C2mDl37VSeHGAvePmd4hBoEVdYL7UmZs712ywsQrjCFSmaps6MZW0veeQAyDlPJAgfSypTt3sEbqxbHUJPL2zRbvA68+37BcpPKzH5JrYYx9j/K85KqnWvFQ+Kc1KXyQPRA95bNX3Ny0vH2z5enzFZcfdzgXaBo70pnmm0ZKlr9SFAQjxsjNjXSXevpsxdWnPe/f7vBD5PSsKZDvIaz3uLOmipKKMaM0o8LPHk4ez+JNpff69y8jr++UCKqp96L1uDmSt6+j4+m656Tp2DvFbVexGwydM4RHlMrU4zc64BMc/4h/OX4nfXFKxRwniu4BePADcx4fvdOBx/uYBfED4ZG5bp6adpOz4vT68z7oh0cuzxqF+OEdJ8+XrzuxRcobicwX1rb0kBlVeICIPLjX9JzxnQ6XmVJw2zWEsKfY4EqlHIGYSryEgtUnNrbsVUocOFI1o8I3KV5rUltsYeEzqWOmRZsKo2uIiuvrG/b7PX/5y19YLBtWq9RQSoO1GluNoSGlpNOcONgxjVOWYaHA/DEGqZgkoqwmatn/bkj5Q60jtAqrNYuFpbYGSE2+oiKKQCmQd11ZamOwJiUjTzzpPK4z3z3KeKvJ0M9k6+H0x8yxkMo4J2tIKUUYNLQ1et1CleDuqArpDjF1GtVAlO5/KgRp1COQLDFS8iFCCgcoBbauWDQ1jW0w3Zq4q9CNolkYqkrKq7u9wrvA5shC9BhluO5hvbG8+vyU1eKEy8vv+OpnX/H+/XvOLmrqxpb3E7kZaJaR66s9T5+tUv8WNRohPq3hkEjbrCmwvksGzqG8+6HjJ6H0q8ry5s23+Ljn9GmFqSuGMNA6x+CldETGV2GjoVnVVNYQCQxDKJamNWIt56S40kyheEZSeiKxr2Q1B48LDuddIqLwZdCVUlJrqy3L5YJNs2JRN9S2EqGulGyeSRlK3iaHGc1ZiXWd5813W+pG89nnm1TzH8uXc2ldSW6LYzOLrBRVglZDhOTfl37Qisz+N00uSmo8wvXVnnfvtjx/sWaxNFx+3Mk1tUrlQCl+OCEdyhUJue1pux9o945nz9YAnJ4tqCrDm9f37PeOF6822FmZyng8yMo/UCzqkXPH+QCldEouEmNqUcH/9jIWwh65hgiYrPjPV56n654nqz0KaUYiCUv7Mi6D1+wGw94ZGhNYNz1WRbaDZd9rNrXnP789w4fJE04eXams20bjI0ssUTQxdWGbC9GSxKYOrILsBT8Ylfk/HzjnjwjpuRYcFfXD7yZFk5SMyoJ9soZ+WNH/2PG4EJuhBBFKg40YmdLtqdn5P3ZtVUIQ8eD8u65Kit2n88Z3ygm1zjlc73CDSwlkgaq21E3FctWwWNTifaKKwrfGUmuh3rXaYo0k8RnTYIzl5PSEqqpYLldcXn7k5hpOTjfUdklkJwa6niBgyeBIUqPE1UtyHZKvMgySbAxSVhhUgAAqRELvUGFBszJsNkupSFCyJ3x2apQiOAfOs1o0kvxHLhGcmIJJqaqJtSrJtepwlRX+/DEEJN/Ja200IlXp6hedIt7VhKrFNsIFEBISIwZZkoUkAq/UVTBqSjgvVwQoo4VnwRjMQvIwrLXYsEDvF1hrMccU2e/byPrIcPQErt5FdtsBUwWa2nDxrOH4uObk6IJv/3yJsZaTkw13r7/n6fFmEpZUpaeINpGqUXz4sOOzz44eVeIxhsQFYEpDsyzXS2nyj+v8n4bSd77n6NxTLWtpGOEcnesZsiL2I8tX0JIhX1mL94oYRLhWKWHCB49zQqMoiUYKq8Tq8wRi8AQlzFXDRNE7L3BZyECLF0u4risWtuFouWJRL6i0LQpfyHjmmeePyaU86fu957tv7ji/WHDxZDmWH5EWb8hxUpWs17xgJlI7LySEh7vAdaRkvfQzUBS+UrJhPn3a8+H9jpev1myOarbbrsBuzsmY5NIW+f1BMko67u96moWV5kOIpbveVHz582PevL7nm7/c8vkXR1S1/tH4VBYoRDUT0GNVQR6DcYxEIs6v+fMz+PY68uYuFQwpxVEd+fIs8vmxx2pP76D1hn5ISYWFT1zyPxobqK3ndOZUR45rx0nKdfjNkzv++/uT6RtMTh6PCXhRnllIg7LhMsJ+RbHPyuXKVP8V+HwiICYGwyGaMB2uibM94ggHQiYL9QfZ8hOBnm9YDNtHDJFiv0SmvylnjQbywQPMDKBDzz2vgYPLTc6ajn9+v/2g6XuH1pIzEEJExcTB3g84F4q3n/NZjNGs1ktWR0uapir7wSRSq8pITX6VOunlJFljRqj+2bNn/OGf/sDTp+ecnB7xj//tH1mtG6q6wgdheJuPPTOl6UOGqrMxJvu03bWpLbAY65U2VGhMUEQfqe2aJ8/WLJYLcX4ys15KCIxE2r7HEFlvVmL0J7g8M1fGhHbMoaJsjsSD0NU483lNTBG6mBCVnNVukMRCt62J2hHrFqWqokijeDTlqq4TgyzEOHbkCwHMWPKWaW9NZairCh0q1G6BVob6xFMthlJeTQxED0EN9E5hGmlbHICjozVNXbNerXF9zdu37/jqZ1/QLLe8/GxBLs2LMUpNvxL5uFw1LBrF29d7jo5qjo7rAydHEFhrRwKeLG9VQi3+ir4HfiJK31YK20RR9n0nXaJcL9aYlwWaLWBPwA+BpqqpDTTWYpOn7UOy5NXYmzsn8rkwKvnBO0nY8y5tBo8PMfXRRuLCMVJbgYWWdUNTNdIacpJklNtCwiigpxmrxcMOkatPLR8/7Hj5asPxSfNAGWYFqNXcQ57GtmUjhtGaVkJskuP32bMv30sP5n3kzff3bLc9X311wnJlcSHQ7n3KSpZSHq2V8IinTN4xfq6Fj0DpQqN78XSFMVkxy/3q2vD5l8d8eLfnL3+64dXnG9abahJakJNL69vscSpmnkOuHnhsDIixICn50Erx//wc/t9/ghdH8NVZ4GQhFrUPBhcqYhSK3lzhIImOuTnPqAqnHvhcMUaerFq+OLZ8e7NKnzxi0KipkCwvQJIzaZwTV3hGAkgqMCv+mcIaBedoJMY5YpAFc1K+E4Dp4XFgM+WvUQS4eC3ZSxunLU6MgfJiTH+aGhTjD3F2nTQc+aJiYmeEJMHJU5bGmczM13ug8H/wVQuSZJQnT4zIFUEJSzJv8i6V1sQQsUYIW9ZHS5brBVoLYY5JsH5lDLWx0jo3eflGGZSqkEZMYphv1mtW6zW///0/0fdCtfru7SWfffGUyq7QekApT4yO3BdESTsCgvd45yRsl8a/HxztrqfvB4iUxDWzsClhFxb1hqZacXa+whiDj562bROpliWEQNt3qBipKmlI5kKgc47eOXziIBnnXQyzEb3M8zhHIvM5B6tAjgRrVymxzSiNuxPOA73pCEH2k4mCKvoYGYIjBuSZfEBFqGpLVVn6QfhHNArTjHX4ytZoX6PuGjQau/Y0a4dKxoGPoXTTCyESekFIKivJ2dZWWCtJ2Iv6lK//fInWhpcvz9h23yYOACRRezIYMfVeUFax3li++csNP//VKcvlqKJDmDSLmjg1uV4/xgc76NHjJ6H0Y4zsXSddovpOlLOXxeeTp6s8YyzNyACb1O9aG10UUkyLL6ixfC+k1qqDH6H8ISn8IaEI2apVqYjamopF3SQ6zWqE30DqP5UQaeSjxK9IsFNKWtnvBz5+2NN3ni+Twj1McPshb/hBdixjzWxUER1VYZHK9J3TWCvAvnV8980t1iq++tkxdWMlrOE8d3c966MqwXK6UArnHIXR0Bhpgtu9w/vIZvN4Uwit4fnLFYul4fV3d1w8WXJ+sZi84xTdYLb4RyNgtHrz++R8hqKU1VwpL+vI/+tvU50rkhiTYUxjDFWs5PtmtNIzH392KabKKitnsiGHhAF+dnrPXW+53jePvn/xgMk6TBUlLMmEY26FGvXceOM4F5q5q2J+/7LOpobK5MEfjPOhO3+w1LL+LCjK5NTxfuWs2VotP6uJfp9eOF/rQOHHyckqhdpiSCVXh8832VcHly7H+P5j3ktGc/L4Lk2fNrkgGG4QrgxtdEHYgJIBbitDvaypmgpb20SJneP4mXp39PJH499Lvo/fI1n8FTF4Pn264ne/+x22snz/+jUfP1zz+ZfPqSz44HBuiw97YgiSi6MkuTiGKCx5CY3su55230mnubTOtNFUaCqjqU0F/oTT8wp0ZPADPgR22z0oiSWLMRRSOaIuCr8bBnrv8CnwrpWCJAdyt7rDeVGKsVrlB3oiKEjlgblwWBGdwbcGe9LhfBSkBIUyGj94hj4hr0mGa6WoGstiUcs2CRFdVaAQmNwbfGtRvkJXgeokYBqXepQk9lEFeBIlu6PvHe2uQwfNarmmMRaTiNOsrXFDxft3H/niy88I6lZkxUQvPygBTojG8UnF1WXHd1/f8dXPj6mbRLikUkmzGsuUM6pUaKfVAaHVI8dPQumHGNj1Lb0bJIafve9MHZs89xJbTj07R4EgmyIgCXo+We2ZsjL3Uw9BSvKysneph3KhXjTS91oFxbKRBhVNXQvzlsqNQVJmvBrj+JlwIT9QiLC767i6bIWz/7jh5as1NhFgjLB9QiTC6L3E2QLKbzf/W2ziHLPXZPBBzwR+5Pa25/vXt5ycLLh4skj1u54YAn3v6TvPs+crgcq8GEdSkpg9QFWIR7JS/vhhx/FxPfEG50dE4PLTs4a61rz9fkvXOp4+X6deAIzvy9ywEYUQy3XG308VoSo/ZaE3Da2UkAGgUs0+UZIQIxGXGpMY7fFRaqEVqnj/Kl9JjdefPh/Aby+u+U9vLuj8nHt2FHbZUJlOxyTeHONcaOa3SxajmlwjTi4xKnwZAVGo8cEzzCdk7tqr8qv5006sg3LmqPDTv/X0+5MLzm/IoRUwc9bD5J3Sy5eQVnm38ZWmxsRjtvF8DWaFn7uxlSfn6Wpf1pFP5VzZacihrOAS4YsSroBmUQtcnHJkbMrUr1Ly3qjwVUGsYvSJf11KGT+8u8U5x9OnT/n48SPPnl/w4sVTvv3uO969uebLL19ga8mfCL3Hhy7lo8xnJnunPkgYIitao0TZWyXPZXRDjBXNWrNruzTmwh9irQTCfeo7knt7uBDoXWb7cxNkcSqrpusue/1JEhkzn+VsuOd9EFUiMkoNkxT4rUVXgag92qXxC0jYbRCUNRgpoUNL9r5NczH00g2wspVQQrcNOMtyFdALB0ZQS6IuDkze4y5mtNfT9j2D81gNLjia2iaOCGjqE95890ka6Tw/Yt++TWt5dKoy8iGcGgFrjSASxrM+sgy9583397z6/IimsaliJDkbIaNBWW7Hsg7/CvX+T0XpR9q+LZ3R3EThZ+IEk/rS5qWklFiP6NGjd1GYrbzPndZ8SYDJSl8S9iSBL3dZ0omkwihR7iY3yzAVtbGy4a1Olvu03WeyzHKwNki8++pTi/eBk9OGFy8lWY+JQssSQmXjeerNTKTYqIRmonj8qUC82diQ5wghlHDCsxdrzhLXvc8LLUZ29wNVZWQxRsllIE4hZAoMn++y3znaduDFq9OioA9RipwRjILVuuLzL49493bL629vef5izXJVTbXjQ12T1sPhtcfYvhhYMWmfUGLiozKajhHZs8iwrLZ47QjalpJNcfRzHDPOlV2JtY8PWJnIv3t6zX95d1482ajGu2YlP/vn9KeYoT4xTBQTY2CiwHOr2TGklDV7nDyOSkI2j1P+eTKg0zX1yE/zf88nJHvmh7Bu/mx+hbnnM5uvg1tMUYI8co/da7znoYJ//LxiDDGGIYwKPNu0RCeELyEEqkoodCXXIsW6k0FcV5YmZevnEqvcOtdqm7rniVcoJCzJIVA5RCWJop+urvnw4TrV5xt+//vfc3kZefLkgs8+e8WbNx/4859f8+WXL1FqAbFl0Vi8bwlhrDPPbHyRiOsdg3OJcErRVBW1zTk3mr6zHJ2BiwPtvkMrVZISja0lbp+S+UjP7nxOaA4TdE/m60HZbYbbHszVZA4ROWDSM+lUly9ljgoVFF2n0CtX6umzwscL1J6b48REsGWsEeQmxOToWFS3AGdZbAzVKhAN+DCWOyokv0FX2VrN7KVSK+8GV6Rn8E7QhFQ7b1TD5cfvefrsCcrsCL0vIYzpOhwVv5CQOe/p+57jU8vVR8d+6/jwbsfzl+vE22JmhlTeFjkMNS+Pffz4iSj9II0fICn+xLiUa8uzqk9OXFVZqtQZyYUUBsitVDMFbSaYYaScdIkxz08S8IyWDH2dlKjGiEWvJGaXk3OEL18/KvyCh7u7jtubnhgjJycLjo5rqpSZP0LX6U2yFkjeZHHu0y7KyXuPKdVs9uTNdbh4hs7x8eOedu/47HPpZCcxcvF2JfFP07Y7NkfV5DNZSkbrSbXD6BGGEHn79p7ziyWLRTW+wFSBQzFuBO1T1I3h5WcbPn7Y8fq7e56/WHN0VD/iIfLAsyi/L55GDm+kZKPI/Pxifau58leIt6E0lbGEUEsVB2N2bZj0uT+4O4U5b2IQHC89v7644w8fj+enMV7gcah6JC8JPqLNyGyWB6V4VNkrPriQ2BTJ+C1cSxPr8cE7TH/xuFadD3mcNDM6OD2vi8cuPRm9WZJXNowjY1vcYsSLp6RM+CsKf77IZkjJ5N3Knsm2k4JnqxajIvvBl3Uh7XOFxKbvBoZukHa0tRCrVI2lrqvEpZ9gfT3C+hLDHxNnjbapi55Bm5p2D+/eXPHFF1+wWq/wPvLVV1/wr//6JyDy5Mk5n332jMvLG/78p+949uwJzXKFNQPOd3jvafcdbd8RK5GRzgXatsc7j0HR1BXrppkoDAtYbOPZ7wdcN8h1uoHlsiFCys2R565qoRZ2Mab2uQnpmCxgBYVRs6yxNIYj0jr+J8P7uoyLUBWHVDKtjCL0UpeorAcvAdUYcpKb5BgEFQlaWtLmufRBmhFVusLvGpqFZXWhME3EhcjgR3lQqk/I+UGjbPEhiPHUOepKZGDm9TdWkjSHXgicNpslzrcz40ZNjNaQnIZcppxbEy9XFi4Mnz4K4rtYGc7PlzN5VfoBJGQ6y/+/pvV/Eko/xpSEx+g96qnnhCSjaaUlbqRJCRlRSHUmij579D6xyUmeSxAu/EyWA2RmOoOW2Dia2lZUWuryl5WU5mmtqdLCmE52jJFhCNzd9txctwCcnS84OmowdiK5ktchYN90l4zCUoznUbEV0qAwZtBrNR2NrGGm7FSw2w58fL/DVoYvvzoZY0npZlOl5F1ktRLK3cpWRbCKkB8Vfqa8vLvtGfrA2fly9uwcKl6mxohcxxrNk6dLqtrw7s2WvvOcXSwevNNjNapTD1+Uc+qgx5iQd/idTESki5GWFZV0F/TGYKPBa43TGhU0OmfkHmw6eY1RCZIvF+HFUctdX/H97Wr6xOV+syN5/0rF0lyjbHaVQ0ajh5yHr1D5Tjzw4kFP7lOYFqeYwoEiz5BAUc3TSXxwPnJuHr+psXtw1emX517Q6A2qZOwUoyxdKQ4pL8YcNiOaDFs2IPKjTLdXPPg5Ts+RE59t9qmEN8XKc8JejKm2Xerbq9qWioXcZtZqI/z6atJNT1usGctijamw1RJrVhhdM7jA2++/5/z8lIsn58icDSyWmhcvTvnw4ROb44pmseTFyzM+WsWbN+/56mcv6Hsv/d7dQO8coXBeBCEMC57oA1ZpbEo41ioZMXFBtYiEMKT+8V4qFhQslxKmtLmvu1ZCxhMj0blUojsZwwdLYfTkH6yHibUmpXgUGlqjDASwObauFLu9plo7dCXPEpXBh0BtK2prwVD2o06yNAao6hrfWkJvObuoWR7rJP99kQ2550jf9dInwZjSUCg3GxLa855hcCyaBq1kLZjEtVBVNf1exmO5avD+Pu+QZEbIIosRut7x4e2excKyXIsh29QNxhiGoSejerdXHcfHqZNfRlNjagMePCXXJ6NiP3L8NJQ+Y2OHUp9Olq2xxF1lgUj8XjHyzE/LUUrDiJR44hMcla2oXK9aGLUS4U+tK1l0qS3mommobCbcmGdb9n3g9qbj9qbFGM3Z+ZKj47pks09eDBiFVJz+Mv2YU4gyo2AgNcLIhoHPdLq68JCTF56SUEPXeT593LLbOc7OFpxfrGbPktvMKlQyiKJY3olBdQrpzx4/PYRzgffvtjx9tpK4fEIncmy+QGnloYs/Xt5Ta8XpWUNTG9693dIPnqe5AkCNvQPmCMP4HLmXQM7PEANvTDrK60WnTmfFy0iehioaSBSsyUlZ2hB0IjxB4bOnGCmoAiGOz5RoSWOC+X55dsd9b7lthd89abgfPbInqtUI4T/MjB73whxREcNBIko5UU09uGVea1PvOYeLZGvEpODyn1g0dPGU1fRq4z0eOiLx4X8na7/8zGRoooJeqFVV40BN2RonV4qT+003UvH+x+/ItE1zESRpaqla2Udapzp9ecDcwS0G0EaV1rOLpfDr27JOEsRPjpubtM7Ew7dmQWU22GoJwfLuzfc09YIXL58RoyCMPnT4sGe5hlfNMUp1uCGgVeTsfMN+v6cfOmLsJOeoHwjBgw7ixQ4D7a5l6BzBBXRtJGwVI0YrrGrwg6ZZDQy9vFsMAauitBavKpSRRF0xfixR5Va7qYohTsY9T1ySUeNazMtR5RX2AJ7JPCE5HBJ96i1gNK4XoppmBS5EopdeJ1YblssFlTWE6BmCK/S7Smtwiv21Bq95+qphsTQpJBNTTwKfErQ9/TDQdp2EaCtRkTr1a+m7gX4/MLTSLlml92uqWlgRtcaahvt9j1KwWGi2XV/W5OGeuLvp8S6y2w3c3jrOnzQ0jcG7yPZ2wFhFP0C7D+y2TlDOdIyJxGlvpv34V8THT0TpR+F7lnj56O377AFHqBI07ZyjM0OCbcSyy7WnOQYWJ9edCjKTlFtJKtGa6ClJOU3d0NiKxtbUtsZkKHLiTd9ed3z4sKOuDU+fr9ms6wTtPIx9HcZoZzZcElhZ4fuk1FzwI6tV8vANKRkmjs8j34PLT3uuPrWs1hVffnXCYmHLvTK05X0oHkyS90RSIpMeFWL20DNkmXMlbq4kIej4ZDF6XCDKOuczTJV8/pCip4qts1xbPvvyiLevt7z+7o7nL9dU9VizOh0/SP2x8SORUq7ACNJtLKSkLaA0FhK2NAnJ5Bpaq3PjC3kgRSYI0YUoJBtT+Zkz+ccBvl0+y7MqiX3nDMGQYwSPbtyJ90nMSp1kQIWS/ZxP1jmZa+KaP9B/ReYeaOI4/Wz+HRmrMVQ1AgcThZ+f8we86qlifmBwxHEdPRiAfO3Oys9J4R8eh4jB41DDw1GeGjjEyLpuiYnrPKa9kGu6h95N0INUtqpSU52mKuvIGkttaxa2oa5qqkzDi6wxYxK0T8Xb9x/Z71t+8cvPQQUGd0cIjsH1DMMe5/bS5907cC3gUKrh5LTChz3etwyup+2HBOk7Bjxd33N/v8P1jrquWNYNVWZ9VArvapoFVLXC+0hTG2JQaF0J33xlUNaUYYsIutp7T+9yv5Expj+bsnGBzBX+bEGMlp1SUlFgbUWlDcrmBjSw3ztM7WVPu4DrPVZbmtQIBx3xQaNSQp0Yaor724jvIquNYbm0BRkUuRBK+bXzQqwEKXznA157fJAEzqEXo8kaS11pmqah0ob1ajV2UlQN9/d3rNYr0H58N0YLNnv597cDT58vqRrN9WXH5Ye+1OHbSnPxrOHju5b9znN91bE5qouDZ1J8P+sI0X//i7TWjVFqUqVGNv07M8IZnWpNs3C3DE6YqLL3l2ut/QS+j0mQ5szI5O8lRTdpBpOpa6Om0rZATKWeEhGEfe9591Yy0Z+/XKdY+UNlP77TxAD4gc+yyBK4erRYpw1zUAalpW42hkg08v3tduDD2x3GKD77/Ij1up4L9aTwQwizBiZGa0IqbaoSFSQwxogz/JuE5DB4PnzY8uzFmjnbmSrPTggolegxJ+8bOUxKEcFRVZrPvjziw7st335zx4uXK1brafvTcZwCYeRW8I4+kTYJz4In5wHkSoYsKHQ0GK+pVErYil4yhxmRD4m/5TUz9WSz15kF3YhYjBZB1tZC7PPbpzf847vzmRJ8aAJNfpfhUC12QvDZ408fCaxVbiPPRUkazWuvQBIHynlq8OYPi6OmDp5m4pVPpunhS5QPxtrsmYUz9cqn14NidKqoib2Vlrr1VKDKBab6Zfb8j8jBqYLPp+bQR87eX9u2oH7SelWexadYqjIalRBCnct1Ew99bkNdzerxTTEWQbLRwQCBq+srPrz/wJdfvUTrgba7IwaH946+76QJjh/52iWJ0KHUjhDAe0fX7XGpVbUY98K+t9u1tG2HUYr1YkGlR5pnlWL5y01k0VQMTvhGQggsVwtsVRFNohwPkbEKH/rB0TvZXzl5uqz8LBvIRtxDE29MTp7aYmMelmIkDQsh0m2hOgm4fiA6QQVylZROa95UqcrARXZXkW4fWa0tJyeau2uXKNVHeemTE5Bzu5SCqhmb3uQXCi4QXBAIf7GgsjXH6xV1VbFcLKTBTtRo3XB/94bTs1N8aNOLqnG/JZm/33kWS8tiadEanjxbcnRa0e4c775vWR9pqlrx6osVfR95+3rHuzdbnjxbIrMw6g5zQID2Y8dPQukXiy6xpOWWiihSnCUI/KYUVBCcSBefkrnIyijE0lYxW02KkVBDKQVBrGzpfGcg00GOsjE9U1ZqgfvrgbdvthwdNfz8F6cPOsg9/k4TT3dyjMJ44iup5O2nTGIfBYKMPse0rIQ4FOzbgY/v9/Rt4PnLtbRy1NN47vy+eiIc8ge5Y55JYyr5A6F4/GFy7vWnlqo2bDb2AZIBlA550kC+qBcRwGEiiJOXnRWaMfDsxZrrK+mUeHrWcHLWYK1ialD41DvcB88wDPRhSKWdjr7vAeEgl2ZAY/5D5kb3WuL3AslKtm4MiMBI6FCG2XJm8kNBNmq1vN5Kcmka3tOl48uTLV/fbB71fn/4yDfJiXvC8nVADVTGfPxt0eAPvPoY8r5gHHMeRwXi9H2Z69gD8Z7OD6XJ1YNrpLEcyUdGY0MMqVHhU+XSsHRWsW4mhky6+PjcqtxPHZw2e9I4Og4bvSWGiLGaSCgGfyHtsVqYPZORW1U2Qfu2kPCI0q/KGhO5IsF2cU4G7u/v+eYv73n64piq6emGLd73QrDjPX3foRSp9Tb0iUI3xkBVWdwgteP7Xvab1oropfNf27Xs9i2EmDziiuiEPW5R18SwYrMxrFay2SqTKgq0pl7UqNSgxgdZrDG9v4+RPt33r2aN/9CCzmsMJshV3h+MhqAG15Ey8SOu1VgjWfXLpqFZNFhraXee7aWXFucRlmvD+QvNYmmIAbZ3jvu7geUGyXvwQ2okFAr5jartaM+m0m2jNcZa1raSHC5lqKxltVwI70suvdSa4DRd16eOp93k/TN+Ki+9ObIsltkpkN9VlUZvKqq6E04WpBx80Sis0WzvHcOw5eLZyNaX11UZ0r+i/H8aSp9k46vR35rG0IVLX07MvZWnViVQvKSYiA4kXk/hya6ULRs2QmlOAyn5ZNK3Owuxrvd8eL+n3Xlefbbh6LgRa/TAq6J8bxRQE6A4nTg2zQkxjh52LO5jUrjzLNn8sRsCl59a7u8Hzs4XfPHlmqoyaeRyTB3xxtMXi5OoRjURlTT8ye1CQxpfIiPTWvrZB6n1f/p8OYe5IyPCkpR+iClHgBEoL3B6ut40VyM/1tn5guXScvlhz9d/atkcVRwdN1SVAjMlVnL0qcY2x/VdahzioyTDqeBHsiKU1OJrg8vrIXUzCUFInCSxJ7EyJiOSUVxBnsOY3krlJB6KfhpFQOSzk3ve3C/pvZaEwOmJs2NinCVlUxI501rOCat5feX8iTH2n4X0Q88r5ByBye+m67UYYmm95niimiremL296ROrYnjoooRHgztmDR4Pof1IieEb8fAzCx4gKFNenJPnzM8+GgXZ4xyfb/buYVRoMUasDmyqvnDPey8+bi69tVaXnIoQIo01rFYLGiOIX2UrGltRW4n3SlLf1IOFmNjuvvn6muOTBUdHMLg9MAh6qUCpkGhjpbGPcwHvXaoIUvS9o+uk8scNqXKp0olAZmC/7/CDT6WCRkp1laKpLOv1mna34OisRldivFekpMMcE09D60PEBxk4l3qSmFR+KJS+yfCdGnSPm1XkKSlpbYpxbJKMLKs6BJTX7G8jq41GGUtTg0FQk9VySQiK6/cO7yIn5zXYiDagjAiQXFG0OtbcfBqgjnhcKcHOaGle92GytkS+CXspSthGl3Ujxp1NvCRKkFVjK7ZbUfR1Y3Cun731JA0WreXP1NjVwM1tR1SR5dqKYwl8uupYbSxPn634/vU9775vef5yQdNIFUk2xv4t3v5PQumjVGk+EEKkioaQ2NAKM1wWKlFgGiAJqiykZLFqI41htAejDY2tU0yuwhpbLP7B+xSPTkp/IkAjkb53vPl2x3JV8fNfHVHXZhSveR/MlH8sIYrHrIKi21WOXY/Kvjg16T8ZohQOgMjt3cD9jWO5rPjyZycsF7YkHRV4aBIPVpNrlptnhasUbecwVrivfaoH1snYyRnOKnnjy6Wl7zwc1RNDK232lHzpg5Mq99wuPibCCTVh4QpaIF01ZZySAVksLa++2NDuPTfXHe/ebCW8YaBqFNUqEvSYqBkSU6NSiqCRZKCJ8ZERnhACwQRcyHH7oYxOiQmW5jsRl9ZVGQNGb3W6VslKOoxjoVBUBr48uedfPh1LRvNkjUzU7sHaiNOlML/bxPuKpK5oh9D89B6RAmHnZ817Jl8jfzUmZCEbl+aH1mxGIuL4/UwjPFXMIR7QI89eRKGGpPArNxoa6S30gwX7+GvOT8j2xYHRwWgYnC36gmb5FNeXahxDjOCctIju+wHnHMYsaZoaYysqa5PCl+RemxtPFUchv3vg44cbrA2cXVh86ICI1ilUo3VqcetxQ8D5IOFJFRNZlbS8NVaJQsYRsMTgGfzAEDxt1xcElFr2uo+KuqqoqgWxqdCVVDRpLZn8Vo/MpXkYNdJudxgCYYhCabuouO9giA4VVJnH+TGG0LKGz4Z93iKjmZwA/ShGTlARi8YN4AfYnCt8NEK2k8In27tAu41sjio2pwZ0zsTPCYbSVow0Z94LmVBQPsmvsZLnMHSllSIgBERu70QPrCxRi6IPyXGIKuJS/f9+16OUyKV2GGTdqIlRXATYhLlULA2cD1xd9pw/aaisJBK3+0FaqL9agY48e7ngw9s9775vefFqha0j1oxcD3/t+EkofYWUdRHBq0jUulj3ObM8hDFBT1pgjt0YBGYdO8oZpdGVZlk1LKtG6DKtLUlrg/co5Uppn0qdnDKXvkJze91SN4ZXnx/NkitynA2UZH7GcRFo8zjsX2SnGuF0GD0wrRRByQIyQZdF3O4Cu1tPVRmev1yzXufufpQxUagHjVGKnMySORsDSuFc4P6u5+JiWcbOJEg8GwX5alqLN9T3oYxtVq4ZoYipz19mP8w+bE6Okwze1JgnirEzhWrHR1UsloamWRLikmHw7HY99/cdt28HTBMxy0gwMRkVEJRKYYnJe8dITMl0HjHEtAqlLCcr89xsJ6Taf5XeV8JD8nxCETs+55ixXDCAyYiLuHtx1PLt7YrO2elDPWaJTV5+XFfT3guSzzlRpj8kEJLSy+RLBSXL9LJxXGvT58jXHBszpcvF6ezMXeoxsTUha3H8WSfKPkH2J5PSWxmfyj0wBh4YQRPLch7OgGwIT58zw/j5HVXuh6HgtNmPnyOOhdbCIOcG8a7bbcuQOPGttRLL11KiZ1NtvkkcHbnsdjpHfR+4vu742c+PZb3EjDiKAWpyMt7gIQayT5AZPZ1z0mbXGFwn4Sef+EWSy0rfD1KCBjSVxVph4WsWNcFXNKtkUCMVK/kdYkE2RFa5EHH9gHcRrStW9YKgIvuhRU1HebJW8gxl21EhRkdG06ZTGZOxn6tmEsMyyij294FmqamsQnmFCpq+he0uUteGZ69qqloRELa8GAMulWFnJMx1cH8F9XHAI43YSniRcQ/FEBNyIY5hCBKScs4L7bB3DF4TVcQmdMMiqIvSFft9K8aficReIOaY+nNPl69SOSwtORQ+eK4/9VSVYlV6jsD1Vc9iZbA1yZlRPHu54vqy583rLU9fLFivq5nx9GPHT0Lpw7jfs3Wss5IEIC2ypHy91jIh2VPOHm9EFrpW1I1l2SxSU4yaJtXaRxKUOcCANG2QjSI82kLzGLi7Hfj8i+Pi9U0X/QTknQljBbNFKLpDlbKQH4JuxDYWytioNb3T3F0NBKc4O19wfFInpiiKjJyVykwk4zT7Vs28KbG8P7zbYozi6Hje9CcbI9Mn3N73bLcDrz7bFGE/jbfHGBmCZP/2bigefxaMQvRTEQ2JVpQitPXoNJQFkOFhQS0M2ljqJSw2mturnt1HhWoMehkk+5xUhpWkfzYU8zhkx0S4GnKp1mTNHc6D1kzNtqKDDqet/DKWsRCjQWM1fHW6458zaU/+wsx7nszVZO2iKJB+QbdIyEMeI0ahXHIwolC0yjunOmCV6tHLWIyKvSyXokDnAr9k8I8ODfOzpkeabzPtDaDGdTpInTb1MBn0kXt8vPIY1hKbIs4Ha3K/bGhkaH42NUlmGOU5rXblGsaMito7T5cIeaQJTmSxaISBzwq3RUkMZUS+xtmUn32IfHi/l/1Z68nelDCk956gNH03EKNnGKShzeCFEz52IRnGln3f0fUdbTeggscsDCHV5ned5AYYnVrkGiGZquuGbqtZHysqKwqpsYbaCtPgkLkJjCqsg9YYmtpSWUlka93AFLLOayDvn5mFlcYi0xIrlZOdKbZhLodVYnVjlSTVDq3n/HmFIjJsI90erFWcnlcs1wZlBI0ZvMPhCSnkFlLelveR/RXoJqJrX/hYBHWIRR07lzlaICcPKvFCwCCUw35AOSm79dELUmilpNGaJdv7D2w2a0LsyN78D8mNSPbyoescdzc9T58vRL5F6FpP13qevlyUdUWUfX7+RAiTPr7rUM8lb0Hr+Vp77PhJKP1cUkXyzEjCS7xQmc6YNl5I0FlQI5xbWNV8KrmppC41Z4NqEr+9ntwr0UXbWhI66sSypVDcXEkJ3HJVzZ5RlZ+ZeEvMnKES20//fiz5TX4ezxVHUBEHxe21Y3vnWG9qjs9qmkosUPEaFEFF0Z+xOALkNZmVRRGWaUPmx738uGe3G/jiy5OxQ95kHqZkOX0n1QrnF0tWa6ktLR5n8vI9EhPvfU/n+hIbJ6YmINpKg5syWECQOaUI4fEJpnkcoqCkcmO9UlS1YruFu2tFd6VQtUMtI0aP0fBR6SRffIJyHM7BmGg5esLZ4JzB4Pn8ZIbnz8ZIfrkdOS/lxablm5s17WDSVIQyJcVzyvSvSblrI2VNWZGNglfGIa+pouTShUpeRYKutdElfKSgNH6aesg/dIznHWr5A+0/OX/666Lw82legTNQ98nly8ZADsvBL44/8XZ/wq63xQgZ13G+9qFxO/fmpkc2cl6u79BKkrvsZF1JJ87UTneQ3IKqtizWC6wdWTdjGtegx7mIkzUTo2K/c+z3jq9eHBfOhWyYO+9x/UAI0PYtvZMM/CHkJjAa51xiiAz0fS89IVIveF0p2iEwOIdSSkrLEmNdXdUsmgqtK5RWrNaWqhIP22aK8AnXR14nCoWxmkVTU1cNBEUchKPi0AIOYVT8Knv1MWLQI0+BmiiphK5ZdGFb1FYQk24LtpLy6Kv3DmNF4S3WJjXWknkZgit/fPTJ0ZIH6+5EgS/WqWInOW8mZswtknMSRpg/UVjrRLcsXiGDy8ZvIMZUFm0MRDCqYbfb8/zFUwLDbC8UpK9setmPOSfk+lNPszBU9bgH2r2jWRjqWpf3ETRCjPmLpwtuTMf7tzvqJtOiP1jWs+OnofRRLKo6xWP92Kc+e/hKj4I1ezYp6Uf4onM7XS1xuEpqbAkKW+XMyFRXm0vLbFq8uZVs2jDeRfZ7z6vPjyZeaEIg0tPKEgsjvKWysGGyeeb24NQzzL/Lk+t95Pam5/qqw9aKl682NAtdkIJ8iZIhrUeYKaugpFEngzoKUIXi5rrl6tOezz4/omlSnO8HVlcIkXfv7lksLOfnywL9Z+i4lBjmXgleyDQG5woJkAqKoMfyw/y0Eoox46MmY2oO28YCEyqFvK8W69jUsNtFtjeW4UZhTzqM9oQHfmjREPPjRxTfLC49eZaYhPkDC38ilKaHVoovjrf884ejmWdevhulRrrwCySIHSWhq9LACQk5BR/KOOXzS/JfGitVFH5eC5TA8whGqfn7H87/RLA9HLeJ4s3vfmDEAqUpDyiisygbwGQja4QPYlT87PSGF8uW50eOf7o84apdpAS/2SMdzNmk1fSBAadSkq7B82x5VxgtSXMgzaYm3w2Srb9cL1gsa4ydKPwYGILHBE8IOsH7UuUTYsB7uPzYcn7eUNkx+TeXHA+DoAghBoZh4H63p+27YmT4kBRG3aBIfeIrQ7WwBCX3btuOrh3QkRKCqyoJUSxXDft7y3ptWTQmQe46ITyh8NxPD50SdzPS5nPzF1TemaNzYwS2zqVqRmt0EFSisc1Ij65U8bKz4oQxMdS1Au0vN5qry4H1iWZ9ZCRRl7G1tY/SMM3FMVG3rCkFwRlMHVFGFplOXs5od4oEMEbkZvAetDx3CLHkdIQYGZwTBzBXdxmLVor18pjd3UAIgfVamPgeM5TzXsp7MITIbufY7z3PXy0xqa9DcSa0zLUy0guARJAk+QCBk/Oa1dqy3ab8gUkm/2PHT0PpK1lMEqOGqJEM1bSJBJ1JDRe0wPGSjZpIN8gIgC4L3SiTGmIY4cq2Eqsvm5qIMhaIhcVNa0U3SOMFyao8nHFV/vsg3eUHrLMxcS0LuznM74bA+3d7+tZzfrFgfTS23lXZW8uw0PgIcyUweQAFxcPPx27X8/bNPS9ebmb18DFt9cP3vLzc03aOL788GeurITP/FlQl17r7mAgygih9krE285LTqBkl3e58DMWgy4JDlVpYVXI45DMSw5elrgJhHYiVo+s8IW/AuTbLvj4cztPkd1OFPYebx4GdGnqZrGfMZxi90ewN5Ws+Xe74i1myH8RayN5PYISktUmCU+dks5SsGHLJ6ahYS7grJQ6N6IRK19JjbofKoz5JBBTrb8KD81Caydey0j0wUidreKzRH5VyfuZyllcQFGrhxpOKpap4ut7xar1Lhn3glyef+E/tM4aQ0Kn0n8ikUkBlxZp6osdJglW6fPCBnx1foVJ+Se6xMTUS8nybSqDwxbKhbqoytj4GVPBI/k82yFIJsCxK7m6lZe3xaUPumuacL3MgnBJCm9t2Pd3QS4lo8LheYvcGU4zkqqrRGvro6YeOtuu5vrrl7uqeoRuIVcXy+EjyDYyhqhtuusDJqSlJYNNtrIzGpnVSch7S2JPW6SgPx9i/TohGNhoiAudX2oAWIrPGVNKAyEozspja/FprSulcTElt9zcOU2l2955mDdVKGAbjILIgy2Mh3PKlB0BeSOJc5bqAbNRGVOLcyJVKIdXo1xa0crTeE3zEK0nW7Nq+IH8h/61ApxCaMYaT5RO+++Mlm82axRp27fBXfQejNb0PXH/qOTquWCwkaZy0l0pFM9k4miBYcdyfy1XFYlmRc8t+7PhJKH2NojE1Xge8S8ksQ2rAESUZzBhTyFeUJfWA7vBeAz4xsalCl6mVYXsd2TpH00SOThrWa10Ws1FzpzwL9/3O0yxMgb8fc5AgexejVzKTpRNYbXqUBL7Etz70gbevt2itePnFusQFQ07KSoaMmXjDTCxrkkIke1GMwjI/yjA4vv32louLJccn8zg+zOP0MUa2255PlztefnaErXRJfhEJOvHuikeUSuBS7C0TocSJt5whh4iUUZnc8jKhM1oJtC3xwaQky6BPvMN8X8Sj1JVQesb8gUrp9FGNCuwHjkkAhkwspEviwWTu1AjkT54ijx7TXI0pokEIvNxs+dOno3GswogkTFGkEIQONiSlr41O3d306H2X85MhpeeJVNP8l/n8xvK1adnf41bqRJM/UPzj28+X0CREVSI2CgYD1pPJr2SvyBfX9cCvzq5R2esOEasif/f0iv95eUEIYzhDlVeOSbgLyU6yYQqSohDCnbXZcVrdMww+jWMaqyiecEi1+sZIZUe9kG56VS2JVD4Gcg5dHozsFBil0FiiD1xd7jm7aIh4+lSCp1BCPqTEs+z9QNf37LtO4sgmIWZK9orzDtcNojgtDL0idJHe9ez3Lfe3O7q2pzKGzWbF2dma9XrFar0gpJr71Tr31xgVSJ6oknib0fuYs8RHR2L87oFRxChvrJaeAypAbaR8sdZV6UlSEMCQeqEQ2O0d91eB/TaiK0+9iZg19EFQixAls19yQTKzni+OhEprRqHxvcZ1sDpXVEanHJ0w5hOQ0Q0/LrUoSn7oBtq2wzlPs6iLoo0xVe54RWUiVdWg4pqrq2/59d/+ksHdEWOY7bHpMXGxuLsdUERWmzGUBrDfe7b3AydnNYpcYZSYUkMkFm9/TFA9RNAeO34aSl9r1s0K7x2DcqnNo09d0SqxbKuRwMDh6Yd+FDZqzNDVGFQUoXl6XmOipe8ilx/2XH3sOLtYcHRUSbJYfgA1euT7dmCzacbkqSx0J0JyNiUKfmyOcrxpmphFQho+vt+jDTx7sRTEO5mFLni8T7X0k+uUOuSk5EfWwPQo5VkFqnY+8O03txxtap48XT3w6PWBsgoh8vbNPadnS8kmTXeewd0zdTl70fJZDkNEHccyPiPvXGrmkyJTSmGVLVTIuThBqbFHd94ImegkN1fK2enzhLBx0z0+LQ83cUY8xKCIk9+l85PdUXIEJsyEc30ci3IPIfB0ueUvakXEFtKo4q2WB8zni/dsrcGk2uriGKhYarNLToEaE/NOlwML0/F2u2LytQNnXQyAEXWaJPGpAzsn/Wfi3B+M5dTAJCl8NX7JJ+FnE7nGZINYHfjNxRWakUjLGE1lDeeLwP/RXPJf357T9nq8bwllUO6bhWX2wEOIrE3Lz48u0TESVEoI1brkT2TjQKo0xCtfLGtps5tCA1LfHVBBoZQnaIMLnioEsMgYKhKJVKK4RsqDUUrgae/Z9S3b/Z62bXFugErCLyD7zA1COmWtwWjweKIXGdC1Pbtti+8ci6ri4vyEi/MTzk+PJPfAGG6vI8u1wVpF5m9XyTPPsiavq1EqSBc5ae+aVnkUEpw8tuFg7VskLBqDGMVVZiisquSpywLwMdC1jrtrR997ut7TbALLhaCCduMZQnIwMiOqkjI+SajLzKq5/Xd66qjpbwzNWrFMTlskEuJY4aVQMn5RMF+p4FJ4EhnSpKdHcRxSjN8gaOPx8oyPb2+pqprj05p2+JQibONY5DUo4lD28u5+4Pam4+yJJYRcFio5ZJcpyfPouKLvB7JhZq0d9yAj/fhojD9uaJQ99KOf/t/k0EqzrBu8t6jYY1VAV6K4szLQRo+xNueIKhCrZLGi8EoEjNWGyhoqLdBdbS1HR4YnT5bstp5Ply1Xly2vPl/TLMzouiiFGwJ9F1g9r0Y4dDYB43YoEG/MBsNjKmai8GOOn0kmuRsiu+3Ak5cNXjmchwJTebEwtbEpdyE1y0nXyU8kUJ8l6yIgfU/iWN+/vkNrw/OXmwcKf+qdZsF6c9vifeTsfFGgvSJcmSia9GoFXcl/ZMsV5S+c/5T4feY2LzHY9D+jB4ENE6eClEklTzpGYswhBEcfhJAjK/9ZtcLBZnnMSs/e+WgwKg6meERkRpChKPlMCyFzPjb7Ic2NGxzOSbMTozUvVre8vj9N3lC+VpzFrgUaTd6k1cUrz8aOiowoS3rmTHb04mjP3zy5TUaU5t39ojzPfL4hZlrfclcZDVJbYRmfMgzza8ztqvHniWdTznMGVfnireVjXQ384vSKhR7KvsloRh6XRjk+X1/xL935bN3l5ykZ4wppOpS4Or5Yf+LCXpNBqTRJEGPqIT92rnSDF7KbFHtVKuf8jO8cVTZgx66XIXgxZIlUDbQ7x2plwQiSMHgn3r3rubm7p+s6uqHDGKGaDVE82f2+o+sHic+HJDu6XvKTVEyx/J6qshxvVlycn3B0tGK9WUqyoTbs7weePrPFoDFWFHBuYTzz3GMqOEuwsfdOSM6UxgdHDD4pwonBjpI1V4xSR10vMWisMiUHJcvkDMsH49BLz+YsEpQjegchMCTjv2T2J8syy1H5vtAyl8RAYLg3uFZz+sTSWBEmPkRJnMzyJKa1HSSGj7IsFwv2XUebncFUFlmchbSvtFYQYFWd8/3lW0L03N5/QOm+KOOSGKuy/BC5NQyBD+/3LFdiICqVQi1KsduLHDg6qSbOQHjg0ccYC0dNWev/K3j6SinZFEb4r3OdJ0osaEUaoOTxBB2lI1KUJCevUs9lrahMRV3VCcIzRckYrTk61qyPKi4/7Hn93T2ff76hrpNHqRRd6zFWUVV54Edvv0xDVt6TiTmM05ffJ+98Wmua+aHv7gaiDkTtaVOMDwReFH5og4++cAwIcp2UoJI4m2yaUBRIJKKNIQyBDx/2dG3gZ784Kdn9irmyL+MvI8Dlhz1PnqwS0x8ps5YkBObCvXQpLOU7mQAnjN4+pGz+QPQRH8ca56yQtRLiHuHRhyoEvA7S/yAnJmUGvsyg50dCjvBXNshjc8LEs5n9Po9H8QryiaM3PHV9iwGRPao4QqxaS4z91eaeq3bFfV8VumQxKGMRziYn4anRK83PUYySOK4zlYyOv7m44+XxviA2f3txR+cMV201mVXmPxetrshDcaizRVdPByhr9zw+jO8xhxMgiCGtbJh9/+dnd3x+tE3n6nL5wzh7JHLe7Hm+2fN+u5rM17jnrImsK8dKt2yagZVtsaFL3fI0ITWYynTA+fW8D4QU6zXW0CxSNz2jS7ikhJ2UGdd2jBiV4OOkHPsusN5YfPSooKVv/SAwfjv09F6y8QNRjIvaMOwGunagH4QGXBudIG0pr4vEUldeNRXrTc350YajoxWrpXT9BEVwgmys1jVax2S4SHKonxg3eUJ9CHIOkvOQWznHJF+t1oTBM7hB4tx6NOxzmE7Y6gzaCv2wjxGCK+E9Hzxee+qNJCE670sTnIzIKBQqRIJONOMh30RosbNlrZT0YOnvNMpZTs4M95eB3bXn+MJgGum0SjKOxQhISY5ocIOExzI5UczGy0ThI0aAiopa1+i44H57j7WKtt0lRT7KAdFBWWEHuj7y/s0OrWG11mgNy8WiKPCba2EXzU5cppmfSJCy//La/7cePw2lj7RWjEpjGsmoPxRIPhHRkHoPGy1czFYboqnwJve2tiW2r0vsNHsK8tPZRYP3ge9fb/nsi6z4pR/9YmEFVs8WV6YLy7KndMQTJa7i2M4VDjzoIBnDPoay6Fzw7PeO68uB5gha1xEkvavE+qMX48dqI2iGUsmalbEQaz+xD44ufhLkY/3y518ekan3i6Am5+lOvDklbGDCCdBMJkaVz0cPMCmeZJjZhMQMic5WR4WALqoYC0J7Kxa1ZpJUlISJRmFNRDtNMGlDq5jqkmUsnU8efhn/UJCTAnkfePYzRY6a/FvmLhsVDxZj/jGOm37MLZpcIxs2bpppLBUjGaVYVJbfPLnmv75/KtDp5DxR3qnbnVJMuyuSkSalRrsjr2sDf/f0iovVWFIkCYHwu2c3/Ke3p2x7W7ylMtcTUKOMzOH7Zy+P0QAYUa/pabHkCABln+E12LlF9ep4xxcn22S4TFASNZ8z6agWMApeHO2pdMRYIAQq5aiNZ105rPJojTDURfk7eIkP53wIgbE1bvDE5OlLwlyFXmgWi5q6qUvTKVHwY/xeKUOlJYZsgvSpMImz4+ZW+D1WR9lDCyURzUWPS3zwLreHNRrvHLt9S9cPyTjXBDXKEVOJAqqUxi6k2+fResnJasly0ZQSZG00N9eB1cqyWDRpfgIhuuSqMynTzHt8ZJlMC5sMv2kVC2lZ9EkSJYNJo9MSithK5GLUkSEMqKAKCuBjUvJR2l1noq7RMA/FmIqkeLbypRM1aX9lI1ejabcKNRievGxoFhbvIteXPbs7z6ZKWfBIOMYqI1n9pCTCydIW9Ex+HgY3hnhI6yQaTk8uuLvZUdmK1brCGIohNeY8ZXkm4YqrTx0ex/pIY62mrivqWnIcnJM2us9fLqVqIIgzpnLxftkHI5qZ7/NDDuT0+EkofRJkF0KQWBljbApGD2fMBk+TiTRayQhAkk0imNUI40YViDFlGUXxLp8+W/Hh3Z7vv9vy2ZcbqsrQd/4BaU1WUNmjLLzv3pcFZBPqkFnf8h9pAysWvAuernfcXg3s7h3VMkAT2bsRBchC1rsgFqiRHu02MYQppYVZMJVm5Q0jzT8mHpuR98tkRnkMZ1KAzOhHQkIUFxerH5miUblktWBSAp5NLWydNmNtM5GYBQOCGmSLuzjaMaIPSh9DFAIRhkhlciwuSle9MLJwTXMLpsfMAJi8a9F/xZj88Y1VvHhGTz5Og5+Mlw9+9MC10UVYeB8wSrNWgV8cf+Jfb57Im+oEJaOKwp9m5Of4vqzpkSRFjNrI3z275WzRlyedHtZE/uH5Df/lzSl7l2KnOTZRZi7Pafr+CCak06fGUZ738VI5G3wyCvIuEcnYr3xZa0dNzy9ObydezVzJZ6MuG1UoiTufGsdJc1dIpTLCpqBkRCvEGQghlCTCHLNXqETC08sa19JVUvKDLMtFU9otZ0KZMWFPfq6McO3jB6wRgd13jutPAyfn0lJb2sMGOj+w71r2Q8tu17LdtZiUpNamxlD7thNkpzJioGiN0rLrm0VFpQxWWZZ1xcJWrJdNYuCTLm4ASgtb6NNnS5SSOvOE4aWx06ksLykPDcSc9Z7yeFJIRAxIJT0G6kq4NgaXEkoj2kRBGI3I2d4PkiuUGOgEuRyVfibM8TFnBsxleIwSho1B0ImpUZudERUV/VaLwn/RSEa7lgqP1ZHi0/vAMCDhreR5C2oxyucpCiiVYXKvdt+JAlaKaCPBBWpbc7Q45d0311RVJQ2XGo1Omd4qj23eMOmapxc1zgl6UlcWnZrmxAj3tz3agLEQgkq+mDgZYWLsjlB/LLLg3+Lx/zSUPnnZJgEz814pHnqJjXAYI0+fkchqENgn6rkSKDoPySV59nLJm9c73n6/5eWrTbo3B1nO4zHWlOY4n2yi6ANRycLLMa68+H3KQbi/7bm9dkTtqc88GE8fYvHuioESxXPM1LVWSxzKVjaFLHRiF5t631OhLKQ5kShZyEqhoyqbaoyhJqtajQv6MJ50mKlf5qp4RCIMbLBUthrVuU/CWI+Wt7zfBAlJWiCTDfnoCU449n0UUh8fc0+AmGL6IljE24+joJgo6MdX1uPH7PtxqtDnCn8Glx4ozayUc4ydvH5SI458PF213Lkt77brka62jO04rjkRqMwHorCUhvNFx6+ebFlVGVl4+G6RSGM9//D8hv/05pTBz8+ZL+lR28f87UjZZyKUxtWVFX4MGe2ZjoWCkNaWlqudLnt++/QqsZPNE0Kz91SWX2oZrRMbYz6c8wXhyP0BlI7FUApBSsVyEy5b2QLfOidKaLGoRZkbaZlb18Kpb3Qq69XSjEmqenQiuTEC8nkP1hBDZHAe7xUhQN0oqcUfxBjtwsC+79i2LV3bCazroN1vCVH4AHI7XVNL0xdjs/eXKIC1/DlaLamNYb1sHpRvDX3AuchyhSQIplUbgkcxUu7qjFa6UGjElVYzunIQ+VVZw6Kp6b0jAr1zCaV0uCDVBcEFejNIxn6CD5UeZW92gqIalW2+ft4F2ViUKobkDiRqbpHxhv7ewGB49mqZyqbTuosBZSOmFqPPJjpjrQV9mBoeuUFXSF5gDpkNvXj6NtEwWwzVomJRnXB7+0fOzk5RZou1q7I35a/RgVRKoYzCaumal1FloVWWzXT1qePouBoN2hgx1iZEhmKExrSnpkis7LPH5Nh4/GSUPsjEznrd56O4ITJQWfAPQSgtfeq8BmmRRT0KbRi1oirzUs598WrF29db3r3dEiNS+52eo2S3k4VaKB6H89KoQVmISpc4bBaMPv3ZbgduPnV0vaPaBHTjcFGsaZ88Vvne2ABGpXirMQavgsCABLQKoMwYE87ebMrKzhauSxa3CNHUUUyPHPi5KmBq1Dy20LLCmX5eYp9qbGFbaUuwmQ1L5knhhIAkxSXGzw7uEcULdyGgyAlTYlRVZkQBYvIoDi8xhism4wGzLoqTt3m4pA6fJcaSAzHaAIrHliUIFWuGUyU5KGWJh7kBpbTmy801n/YNLlbluoRY+kgUeDOX6iVP4Mmq45fntzRWEpiSXwCTvw9HZVk7fpc8/jDxoh+8fUYA0t9h0rxIJ+My37EkEibFMXkYOSvo1BVNjJy/fXKT+YFGj24CZZaxeeTngnBAaQNrUseyQmySjI8YIra2RZnlcIRznqqyNIsapZQ00amke57VNvWFyFz78kfl0jyliG5s29p38kxGy9wNzuPCQNsP+Jg7QDpRZEahvKLrOpz3pdNajunahNZJ5r648DlpuTZWqKDTfgk+E92IgtveeapKoU2UJLyJw2MzCVlCGNzgyyrJqGQO32Sq5hhlLOuqYr1cimOgerquZ3AO70TmDd2AVgpbSWljDqUolTzZINTYOeG0zHHiTpHf6YQupGS+mJKF0//oK2KrefH5knqRCcRIStwTCaxO8rZJyXwEYkDCK5MQ4JAQCwn9SKXEMDiIcj9B0zSb5RGuHxsyrTc2yf0sL0ZsMo1cMlAyz8a452JU7FMC32pji0yQhGstFVmTvB6lsxE8l0R/Ref/dJR+hMTyNP3NXBll6zDkTG7Xi9JPHrUCMGOpV1ZO6UJkqsipi2yM4vmrNR/e7ri77ZLSWSTBnxYvFOtVodBR2PvEGMjFydlyk+zS3c5xdbVnu+0xC8/ywuNwDCnG78I88zzGWOq0TSa5SB67Cx4bROn74AnpOWIhUsmNY1K9a4mpieA02lJpQ7CWilGZ5KHJjG+Z2r9A+RMBnP89j42n2Jg2VNES7TQanBd8THkQikyTOUpzmQufM5CNEfrQVOqXN5lOmzzDh4/79FPlN27Y8ffFbJ8ozPkay14syshn6X1/6MhUpfmWucY+XzOjA9kb0irws+Nr/vXmafk88xqUnJDk1WdP+HzV8Ztnd9KXIR4IhClqwsQASOecND1/e3HD7z+czMZiGrXPgqmM3MzLH9dBXp8oEZqjx56/qCAoqD2V9vz6yTX6kSlRk7nPiXv5ebNXl43EDKVOERdilJLGBGWbVE6WDQKfenBnNr6qEorVyhiaamyRK1VBFZWpirGQE/cIHoLE5su+VNKdT5A2zzBEvAq0rsMjnfMkeU1K9lzKiC/PlQwpaw11XbFc1NjKFk+0oA3aEJwgX1oNWKtZLKsyD+0+st4If4ZC8kDmVRAi52IQhNEaU+Y72WxkwEWMpoBWsKwqKq2pjWG71SgfiT7irCe4kJqUSSaAUqCiBicXVTmfqhJjNzsa06P0MSiMkcl0jcngoWa7Fdh8sZKSwkxW5aJ0HHTeJzSVRK5mki7ISYMiX/thYOhTQzXvcYNn6Af84AsRltYSKj07ueDTuxuapiHEgeXqB6z7mENylD2gJgyo2RG7u+lZrCQ8kGWaNrroEjMxpAuiXPq7/BVtn46fjNJXRGmiUiBmVSCW7LXmWLqP4uX33jH4oSTKSaatLnCJKt79XMmUI2k5axUvXq1Zb2revdnx6bIjhBaQWl9jNOtNJaQ92VvWWkr82kAXPDFKMtHgPPutE89+FTh6qvA60meBEL3QQBb8KBb+9WL9IYs6hCAdoZzF4OSeiWksC+eiYBkVo0uLPyZ2PGucxNtpEOKasRMWSIZ9rlP+azGlDHOVDPM0FqhxKWbhEkJKYlGRqBRBTcr/0jPPONRLCHqkzZwmuJSQTrnGROkVxTHCiT92CKQ/3i8ne2mjS8vgzP71QxfMvNtqAp/mZJ2YeYIS1JwZH59tei7bLR/3y6LUVC5jYvT2jYZfnN/w6qhLnpJA7aO5NVf45ac4XRHwbN2yGzRfX2+yPpjN02QQypUyf/8hEpQ9/ZC6FpYlDMSQrYDI6bLD6hEZGMd8cl9+RMgpAbJyCoVCoatJqafKiEyqAlBj58eYqyjSja0Rb9oaS2WzohePujLSbjsrT5sYPKMWLzT4ITVAitSNZPkbY6hrR9951DJz86dYshIZlj19yHkzghQtFzWLxYLTow11UvhSkRKIe0PrNK1LvUKiorKB41OFtVBVsi76PlI3jOVfec5jLNAxRHxOdEuDmCF5lCL4yNVtz2qti0istKbSmmVdsawqmrrmfrcX1NB7kV8pSz+3JM8ywJDL7BhzFdQsGj5ZoROEKoqjV5sKv9cYrTg+FQNHqL5DoffOxD2CDMg9fBSlPqSKHh88vRsKHTgZsUmGW1b4xkj/gc16xbI+45vr1yyXC5TqqevlZLXG9P8xBCuOZOaQyNlncnjnubsbuHhaJ6NWl1yMkpcSRiQxhCjkUWqSePkDiOj0+Mko/eKblTcevbCs2nK83KWYTZ+yZH2izEQjXmJx6lSyyNTEvJ3cdOLxK0hWXi63qDGJq7rdDnz8uGO5smw2Nc4F7m573JA4/40SmtRsIBxZzlcVQ+zZDS394AtM6BNdZ074mrzqHEpPJR4uSCmNUQoT9IzEIv+Z5iD4EAr6kevIfbAMUw9Lg1LVGPPPHnyCRWW8xueaen/i0ebEyuRlADF5/DZGggn4aOiVRonLPr5nWtRKa0jJRtI6IW3Ocmq6Z4RsncW08R62WZmuoB9dXeWcrBTc4Ir3I++K1DorQSZGg2OyJlPLW0IsgiSq5K2HOEOFkpQq/3bO82rxgav9K7yyI7OeosQGT5Y9nx+3PFv35XlLfD8/x8Gr5uebGo8ZSXi5vOWuNVzulxNjgQd/K0CZEXHIH0znv6wDxuGOERg0KDG+zxbD6FlmJCGO+5kZijBFlOR62ujS5zyfY0xW8MyEohj2+V3HEFOG/q011LYqCr82FY2tqW3KkUmlrz4orJLmW0pZQhzwbiCGIfWlH3ntZZ16YnJCSntmrYk4YgTXO7p9n5KT5d7HGym/O96sQCkJEdwH3K3EietVYLkKLOucvKi4u3Hc3XqOjy0npxWDC8lvT1nwESnbiyYp3bGFdIaSQRJ18yK/vBzY3QfWm0Wid9bFMEVBZTS1tazrmiF4huDpBkfXdWz3LV10RQbIH10M3rnCHz1YHySpFaVKjoHBUNsaqy3bbeT0vEIbqSTywRenzkU/cpQkOR6RUrjBDyXXx2U4P+UO5IZWrnfi+ftAVVlWywXHRxtOjk/A12y3W7788te8+/CXcY9PtljOHSmx+0eOiGK7lRDIamXLXjVGwrEuhRi8c2mcFU09xv1H+TbZlD9w/DSUfhpUM8MDJ95d8KMC9K4o/H7oC4xtjE792pPCyFeZwpAix8nbZqRrlXHe7x31wvDFV0fSylaNmcD94Lm+arm769BacfFkyWJphNO/CD+5qw+ezg0MThULMXvH0nJztDrzDGchnT0YkzZGtnhdDHQpcUeUvi/9031KKszPkYkyyvNoIYpRgwhOY3TiPziIIR96zpHCK57fT54xzN539L6TV5GToZTGoWHSFzuEVLMas6eSIa/xerFY5/JSGj8q3+mymbmRh15/tqTkP3ObXARq5rk3SaBHBX7IsOwUdUpLJyUlll7diLDOCkY8rDGXIodqQASQG6S9qgmeX5ze8MebJ+McGFmgVgd+fX7Hpnmsg9xIfDTJr3vwGSQl6AUxGbqBn28+0g7P2LomDdUk5yAmD6bsv9FDn4YpSs6Bnfd2kPOU1OYrOE6VBTkLfGooSPnSaGBmATjaETlpSt5PpSzqbDxMDYQQvAjhtK6CnzgKUbg8rJUk08YmhV/VQgKVFL5Ka0cr6f9hjCJ4cIM0wvJ+kqgGBKfYt4HFWWQ3SNy7T2V4kch+2zL0ju12T/QRbaW//Wq54ORkw8lmxbKuxTjfa4atoznr0U2kMRbtfDKEAraC0ycKo2vubj03f/a0beDsoiqKVEITBmP1uAfKvJIaRSm0kXX46ePA/Z3ni6+Wpbog5/oUcaQ0jYV6vQQlMHvbD9xb4ZXf9R37rpN9qkb5NW0UM5qWI6KW+yCoFCeoK8uirunuFVUF66MqoZuebujFQcrESMTUwVDyO2KIgvJmhR8lBOGcQPn7XVeU//Zuj///kfcnsbpl2boY9I0551rrr3Zx6nMiIiMjsrzv5r33PaP3DKJBA/foIEtI0ABkGzBI8IwQDQoJGclyA2QKt0AGCTcMssAghCyELfpg9ODZfrfKzMjIzChPfXb5//9aa845aIwx5pz/3jsi0oZW3HVvxjln779Ya1ZjjG984xspoe8Cjo7WODndYL1e4mR9DxdnV+j7Hqf3V/jquTRbW62lK5+diaUXxi2DT/aEYGacv5tw70GvDiofOEZdQcQc9uOovUfW6PoAZOszolVifxOMvkAdVUtZIspcIBAz+MImTZW0cQD5yGVsdQ0AiiGr39WURMHMlAz09dWMYXAgZaA6W7AEdJ3Hw0cr3H+wOPi8WnZhRkFw3QOWuj6k5ajs37W5CkpEZfXv8uFysM1Z4EKTmizOgElWts+nv5eUh5bkZQf4gJlmeJKWntFJrsk1QXAh++hlPbjtBlMWUQ1DLG7eS8qSukgQD5ucRBjJOQR4EeqwCA/FHgtMiwrzV3KjwMgM+hYRHq5eebn1Om/VjNV5AKg4RURU0yuNcbsFsxEKROqDr4hFg5BYExhrFsTMQNRqg5iK9GrXeTxaTng3TziflmWtPFjt8dMHV1h0egh8I3LRzFVBIatzQq6qN4qGAGMIDn90/y3+vdePEFMovAF7TtPov7mObE6MtFUQDJsj/Q8BgGMMPmHhRUbaiGtFT4KayB9KKHW2HghFsMjSJuqIEFTd0Ta13KCS3KpzRNSS5YQdLxF+QB/E2A+hQ+ek/JV1rh1cqe8nANM0YbcfEVOG8/JZotvPuDhjuA7ILmG/n3C93WG3GwGITG3UWvA+BFAgLBcDVssBx8cbHK2WWA0Deu9xeZVw/TZhcY/BXTUqKU4Y9ZwQh8UhdMDjpwFpBr74/YxOA40QvDrNdt7IvBT5XQeArYEL4extxPlZxLMPBvS9zGO2tY36F1tDBIHfvZIbhy5gXCVc7Udc7XbYTiOmFEuUb+cgwGWfQ9E676RiwVrngCUvztFhe5FEipwIkxLuMjMSNCWqa5g8obM8vvImcq5iQLbep/2MOEVZB52UOzoKODre4HizxrJfoA89VsMJvnrzGqenpwj9iAePBzz/6hqPniyx2XTl3PCNauTBugfgdPHnmDFNCcvV0o4YXe9G0nXogoxlyhl5kiZM0Hm077KGRd92fS+MPmDyjPUSEQfJS2eIRGPkpHC3CEDEOZU2hQDKgURUc6QpS923BaIVpiUt/avRyDhGbI47zCnC5YzgAgCN+JpormSriFBRUP0s9cCTKlKVPCg3efDCnNW645RLnbIEvZKfKwS2lDABcGxSxAZlamcQdXRYF5ndA8FYrmpCyCF5bRkaE7wTMR2XqThYVkLEDVLAnEtLUWQgIRdVPGaUPF9kITQd1O2qQaRi3NGgCmZoGQb5HnIKZJxbxwwH75d/FPeKcQAb16PMyIfFL6/RI4SwZE6Ptac1JEbGGcXI188WNAAMxFgdBitROsiH5+r1d10Qvffe4+ePr/BXrzqcLGcsQ8R7R7uSQgFQoqgCWqjhJG5KiNo9Uw4LLc9UkRrvPbohIDDwi0cX+PdfnILZHTiMbO+3MWGUNEeJ0EypjYDSchH2d7k3T9pblg41C2xMiG0tykC2xkZ82KpbIekTcfoABjlf5rnwX7giCaT6B84LkSo4V8ryOlWeM70LI61axCBdOD1SShinUdBDF+ADoe+9OkCE/X7G8pRxrc109td70dB3DsMQ0HlFEPSeTu4doe86rBY9lr2Q5eaJ8e5VRH+U4RcZo0pwxxgRpxmZhSOwXAxg+PJ8Pgj/yLmq+GjpOZvFGJNWg7CK+XgADpfnCWdvZzx+1mO5dCoEpp5xQY3q3FT5aVkjPoiGQM9S8jYEj24fcLXbYWYl2GXbh1w6fRI5ETbyVf/AUgKdD9hfZazXPdbrAZGlFbE02RVCdIrSmdDpPCZGgfOztuGNyfZodbytr4GkLh26LuBks8FqscTQ9The3sN47XF+cYGf//wnGOdrHJ30AIDXL/aIMePktG+4LXwwHpbatP04zaIV4YM6XhoI1fZGds4BfacVINOEudEYyI3c+Ldd3xuj3yraVZIaSs27NeGZ0yz/ixLtS6OLpmsb5LBiM/DmuaIEeSCQRJ1oJF5nxjQnhEGao5CyL+We5I0CucsGKxCO3muFABmRY1GoK95bCYdQDnY7vFLiEgkB2sSDCJlIDTbAScvAgIMo2+o9DyJa/VzWwzYjI+eElFwZT4Y8tyNCZis5lGiF9R5YjbHpjxvL3sbMFnbZhJqLS6ZTYEhMgwy0xrhEw2iji/okYizywdPV91ZUQqoYGgD/psEvIbuWMsVUIkVZY1Y90JQUNVFwiXgZJTJ13lenQI2jrQliiWzbOnZb4947dEMnfxLwdz94Vx+tMeEHkXxzEQRSPYDz9T4NLTO43Nk61TXnHOHeKuFH9y7xydvj8jyVcMdVV0GdFK8ERLjGQOuesIPWfkwAtnOH7RywGVK550JyLIb+1kPpjNYIxxwlrx9s8HTSunMZTyrOcnEYvWEk1Ii3qMKcEwGVUillBk+GEClH7HcTCITFMCDGGV3w6HunJV/aUCU40CjvCz5g6B0WfcBquQSnykXou4D7pycQboF8/zRlvH4RQV1Gt0oYo+wRylBi8FTy70nJel6RkinVdWbCRq1zaalDG1SnZYkXFxFvXk14+LjDauXKuq5eD1XxH4JFRu3UgkjTgkxAr5VW+qbtNGKMWq7YzLk5EK1cN1gNfheA5DFuM5590AMk6S85n5KW4mX9Xg+nTWpSU6JtRjJr6iVFRQX0rDGd/2U/YLmQPP56IbD+OjzDL//y9zg+PsaDRytc79/BgXB0LPD865c7EAin9wcQTBPG8u7VyWBdd9Jvo3ZHnaKmfKgGiXaOpKgBoRdS7JyaDoPMiFz3zl3X98Lo3ywRA/Sg1UiWUVsvppwxzbOW5mifdYWfAD0s2ghJ93UxhmqEYzIJG/ns7S4CJHkjkZf1cGSRBTfedHVQOFeDnpIgESYMMSnBJCrr1WByi8aMcJKtXEejkxIF2RhAPNtKimlz6ADS3eNX0wtAiaQaD9QgeqIEsN4LuIn6zVDnA0Gi1BhzI8rYXCXLvzV/mqCRfbfBuOb/1jQZHfyB5lmAm9F6faFFhXTHe2rUykUOMyrMbikFAspBGTrplGYojCFAnPR+fc3pCZSYEaMymF3tc196uINVzhRwLAItEn1b/3NDHQ5TNIfD8S2GX6PtxECOsh9kydZD2/nawAdO0Jxnmx2upg4vrqsCY8mjQ9EKh4p6lHG1hYnD+83qUusf13OHzSIpTC/12y2OV1w3an7SfqAFRVSdEudEYS+lBOfk2COi6pyLZ1NTY7k6ywdX8+XiaIohGscoZW7zjMViEPEcT+h6qEGM8E6+Z9rKzXk4LIZOcvahx3q5xDzNyClJdL9aYDX0sv2cwxwz3ryYEXPGcCLM9ATZS4iirjfOM1bDoOWGHfo+FEJeTnIGhN5p5YKm0aD7IFfiqcHy2+uMV88nPHgcsDlucu63zgwuUaxNhiNRlQQp34GCVljZ/5r6f+wxZSExOqcOl63VLNB8fb0w8C/PI4ZFQOgUzZxnTGnCrD0LovIbQgjCt8l2ZjYGX8/QlBLG/YSoktjWsju4gOXxgKPVGidHR9gMG9xbvY9Pf/0cOWf8/I9+iHF+CWbh8jhy2Gx6cAbO3o44PunAjmrw1iDDUKfLESH0ABxw9m6P5UaaL9l7DH0GtPwTGdCWz5EFtZ5mQUgBaPeSb76+F0b/my458GRR5sazi3MEE0rNrTV8sdcbHJ+Z4cmiXgiElgX+ihxL7ew4Jpy/jVhvPCw1ZpGRI1/yMgCK8beFV+pIY+0ANyvr1P40z9Q2ZoGhWQxN1wUUDfbmssjYDFs5vIFiMDhLGqA0yShjh/I6ZxFWidqNBJSKcYspCllG32joSkpZ1PIaZ6Ho3hfno0E8YM4KF+g1631Y+ZN0jbNYy5UI764c9uHyl2cm01so46Rzdgh5FGMfZ4kAQIR5inJfvt4/M9D3XS1hjLUxR26iqxuTI5A9ahRa7lLnRkiCigw5p/lFS0EdzlarflDGQh21O1/RRmOKGkmzGXWCGqQCgDb90NIgR/jx/QtcTx6XU998pxpBkkO5kk3pYFzLXdntMKmcrGzXqyngsRptSw/YvFUHrfwHxVsoX8FVAEjHUxAnFHjY9qiRJgtipI4xA2DHinIZusUapdU0gbSmZYz7CX3fYRgGrFYLLRf0IBcxxxEMRj843H/Y4c2bCbu9A/GA1VLU7DaDSObOiiQsVwsMg4gCJZamMOdvM3ZjwuoBI+a5aHZwZsQpwTOVeVqtFlgue8n3mgOTUSsJGogio0beHqZ8Rzh7F/H2zYx7Dzw2x76McElB3ViHdftUFEm4BZ32NOkag1/JtxaQ5aiQtvYxkHQOaetkea+lbcZ9RpwcHj6UzppzjuKwZnFssqEqKpwvSKVG+BqoCVdG9mhUdr6VvwXnEbx0WT05OsLReo3NYo37R+/j688vcX52ib/1i5+A3RnGaVeWo+27YeEkvZAYznEJguRZtSQQFcXwzmF9Qri6GOEWwpvKxJizMyCrMPlBYs8M2UiqqTCneGBrvun6Xhn9lp1rmJI1PRHCjeV9ZXELUcwdHARct7Z4TpGRNZecUio1nPJ7yaW/e5mwWBNWJ04ZgU0kDRQYqyAHXBdBVL2AKUraYdJGG6IOJd8ndaS5fJYx850nbexQD9UCWdtY2Iox5LrxzNtoqNzrHeOauZTAa9Su4iH6SDlnjPMkG9bVFsal7j8pHF6igTo+5d/2d/15A/QVA9FC9+XMogamvxHxHR5IXN/XICH6lxq5oKaHpERG2fRqtDtVbrPDClBxkL6D9cFupXcZVQq45Mwbg2ObuF0blhKo40HwQRj6h8a+Ne53z93B1dp8iANX+6ZnKXdK6gE0+ygr7GsRo9P987ceneHfff4Q+1nnx7WG3j6Cis1vtkSzHgFmV6R3AeA6BhXHkUj8IM3RZmsOPsuQLC5zYhUtEoFZzr4aLHutddZjfXTW5zfujOl6hKSdGx2BiuMtRsN7UiOtUSIIznmkXGeGOUu07B3enhEu3yzR04zVELAYOhCA1WqQVrqDOFMpS9rw3ZuIy4uI/mRGJOHVJK1qGXcT8j6iZ5H77TrRFBCjlku5WEoVhrfUY2GIG08oM+YZePNyRoyMJ886ZaPrGlDSGKEuEVso7sa/mUUjX1DPAO861Y/XveQTsrYvD8HDZQKyzJEpmnrnBSVolOiQGNfXDqenPVarTqR7DXcl7czplC1PXESPrB5/Tk3EnxnzPCtyKuhAjlnasWsZ8XJYYL1c4XTzBOdvM7766gU++ugHWB7NuLh+q6kwI5vaAq3nMGcZb0Nwk84doO9z8pzUMxYnGZPNrT4rgNJvwKkDm1JELAFVLjYp49D23HV9r4x+e5HGNnYgeCXlOAgZyhZxuVg8YdF+FlEbgLUsh4o3JVG/RkLEuL5gUGAsj90tqLkQiqCHvJ58VlZiBn+ME6Y4YYwzpjiXnLccNjXPZD2vW4PRGnz7TvlCLs9lt0QKYZa7vAHRtXuW7X8NWlDyZVoNYXl5E7UwNTOQPbcR2QRwsnwVms9u/0T7fTg8mMsPm/uT+aUDw4/yzXdH/eUIbiFxjUYLXI5KmvShKeXMjNDJQW9lkyaaUwx++2VAccrmaS7lNBW+l/sgbRdWpixXgM7y7Abp4xue7WCev8X8FwBWnZCUpBWzaVVY5GufBbbIr3HUlCC37IA/fvAO//D5Kbghv5YhbSJ85pt30LyG7bCUK6ZD1IraSL7lbRhqYJPa7Imi3GZKhGgi/ixdG63rHNSAkzo4DDlgbb3kRo9d8spAIK8pGXnfsOiF9Ki5con01alwhJjEoMwxgXPEMGSMCyBNwigXJMdL8y1I6ieBMU0Zb15G7MaI/jSCXcScaovt/XbExdm1ODOuUwcT2O8n4WMM1ovBIyaG88ZBaYISW/9g7EfG119MWK48nrzXIQTRhpDIlOAN/SG6dW7Ymhafievnkhl9DVAykCkViN+UVEX5ukL/3gUEHxAK21lIdXGWbqjH9waQoyaCFmOZVc3Q1kbMQhCespTjzdobABCnZ9xPgpbMCfMkdfDOi/PRdx3WqyXuHz9CGtf49JNf4vHjR7j3uMe7yy8Kr8mRpnRLIoqb/4ojIkHdVATiZDkTKDt4itLqnXRf6llryquAELGNQmopYSvJ5oPzDN96fX+Nvi5K57QELxI8iX5833XYTyNSShioL4eKQO1cooIAp3XT0InSnBORQH+RsT8Hjh5rFNGwS+tRpQapHFA1yp9TxH4esY+j5qNmNaCxQNxGjLL8aDujZVndmG1hhjYQXvP9NjZ3rYxb/qEaelLDahs65QSK8mym1Z+0i51F23ZMJxMeAUr+0P4EakRv7xMjp4dzeWd7QGmUmjUaIxuC+qxUnvGuq36qfXLpkWCphlIb7g4OsMwoIi4F7s5S95tzRRFitHaYojVg8y0Gv2mjDDkM7OCrEHPNXRaCWfmZjksJxCtsz0DpXvZNG5+AEv1ZZCff6UokbKgGGCXHebMywoh1x8uInz28wifvTsu9mzG/4aeVeaTynxs3Zk9043cF0r/xNhO6qShJ83E2GNA1o4RJQ1JkHVbnymD9nJJEsyTfy5D17dTgW0OdsooI8CHo74Cg4jA5MVxgZFWEm+eIaY6YVN4VDIQuYXfV4/JdwLQgLBYOPojiWkwJ+33C5XnCjIjhNCIiltLTOUZsr/fYXmxxdbHFerUE+gDvPWJKpfKiC0GDEdEPCEHTHl4V9g4cM8LbVzPWG4+HjwVtmaaEcZrRd0GqTUoE36SrDn0woNmLYrg7OKoBi50/ut0UNeMCMJkR9d5rO2InDoFzQCZcXmY8erLA0At0n1IqSKmlR40PY+etQPpJy56F1Q/I+k4xSfCgDu/QCc9is17j6aOHuHd8it7dx5//xW+wWq/w/g/v4fXFbzHFHXJmVW30APXoPJVonDQYkSBO7ismbeajRHA7CzzJs5muRMqxSKIX7hBntDvKiOBZ/24O7/9fIn0iOgXwvwbwJ/qt/wwz/z/ueN3fA/D/BPCfZeZ/Q3/23wLwX9b3/SMA/zQz74nofwjgvwLglb79v8/M/1d9z38PwH8JQALwzzHzv/WH3CeAgwe22lUHmXyL9oPzpSmNefvSREGJfzqAs9Z3eq3tNDYvMyNNjKszwHVANzStNWE5V1v/6lGCy6FT6tKNY5ASpjRjp6ILxlY242PNLeyZynOW865GufKaqqRlR1dzpn7z2DW/ZggsZu+xvtjQzVPId4WFnypDVV9qz8ooisXNXd70hRuDB43ib96sGRPIBxYlweJbm8xlY5xu4BflUy1KadMMXO9IDH5WvW13wLLPWtJEcEXg5ABtaFIY0zRXzXkv0QAgh3rOubLbYZoSjXARA07ryDkyYLXuzlVUwKozbDTtHG/1cqmuFYPqnRfmuvMOrqtQbF0AWp2g32PRs8kG2xA77/D+yYRt2uH51QpmRA5dNdzxA52DLBuFHJcqvqupQ2KHYM9mCAqhQOr2LDVNhLpXAGTp3FLEjgzZsOoKEJDmDN2ZIGhpYePwlDRPTogQCHbmiJC1rM5Tkei1ygq53wzW5k4pJ+QUi+MoMLus76PjgPv3ArzrMc+MeWJcX0mjqRhVcpt28KuEmauzl3PG9mqP83cXmPYziAhDCOi6Dt6RcAv6gL4PCJ1HieM5oV/cPACq03R9JeI97z/uVQGuGhLnpFMeO00rojpKh3OKwr2QKdYo3/vDQET/kKCBq46GGn5zyonqeYoM7K+Boe9xctzDkRM+VJb06KTGf4qzVhVxOcfmJKp6cY66JsT4y7+l+U5QbYRVN2C1XOLevRMcHx3jZP0h/uLf+x1SzPjRH7+PV5e/xeX+XJz5KFU7i36o53+wk8C4IqwqgVXnv+jDaOkeQ3gUXs9u6QSqxYdsgaN8VuFj2ZBp6bOd83xrox1ef2ik/y8D+L8x83+GiHoAtxqnk/Sz/B8B+Lean70P4J8D8MfMvCOi/z2A/xyAf1Vf8j9j5n/pxuf8sb7mFwDeA/B/J6KfMX9HHYJe7RHYOgCSS6pEM3LWJ1kQALBt/Nr5KeYIytJhrgsBOQHjPmG/zZj2QL8gLO/lsiAzcmlik5LUptvGkPuRAzzmKhKUVE8/pVTyUigHaklS6E1XwybPYM9srPYKfbYT3+pGUwMD3RUNFxOsp6xzhzK7xmOQXtzaxEYXZgtvG0zfRtTcfr7do1qpmyg+l2G4ewFbhHtAVmRUKeL2fWVzyN+Nx1ccJyVUVodKXm9wnzhguUTFzFbKppKdXkVOgjxtomrMuUGOCFQ+q2iqa+RfDapMakypwvrkaj6fbHD0YK0VVvVRlUtQX297QV7kg9Zo+xqVG7GooAlm70lIhE41BajRRjcEAGA8XE94fr1ub6WJ+mwhUPMzvbVM6lTaApB5fLPr8fRoKmsnp4wcWStUap25a/oxmP2y/5bKkFzb+caUEUhy2yaCBEidvVPRpKI3r4aD2OB0LSFNjLAI6LogkWzwVQEz28LNdU07Akd9DgAJsiaO1kupyHDiVYvT45CJsZsYV/sZ784mxMyg7EFO1uTueo/L82vsr0d0PmC9WmA1LLBcrtB7wmLoMQzS49439fhdzxh3LTpSE0YpZrx9PWNz5OAoY5qjpC4AdWZkTYWmeyhQfOcyn9Yi1pAyyeOHsirMkcpsjYVMCjwXpy6DRbSGUXQ4iBzS6DBeAR/+cIPlYgFWUnaMgo5OcRKdD03fQAOqcZoxTyK4IylGFdfKDNZ6fOuYSAD6vsd6s8RqucD9ow/wu09e4OrqGn/0ix/h9f53ON++LXt4mmYEL+2YHcRWeDsHNTCCljjHFEVLweB93VuCSnk4R6VnihFHbcxKRRkAsnOoxhh1DxDuUP47vL7T6BPRMYD/BIB/Sm9gAjDd8dK/D+D/CODv3fEdSyKaIc7CV9/xlf9pAP86M48AfktEnwD4xwHcQhZuXmbojRwlm1CEH8jLws6aDwMBvrP2i7LAgvfwPjQeeYL34kHHPePi1YyuC9isCeE+QF2qkZkyNYVxOcN5jz4A3Hi9Rv6ac1TvNBZyicWgpXf1QbTaHNrUGDQ7x5uguES7jckkEDiJNx26b+gCdeMiIpXZtM+ujlQpheRacljIa+183La7d33TrTk0I0UK89dXNgx0NVacswWLjVZ4/bAScdwINVukBIQCBbIeNMxZlLlilK6FelhIpFjJZSJ57Eptfkqa41NDyZml9lsNnjgoQsA0PkAhnEGqMcyYCkQbbpS9yQybw9MOLNHhU7bGUISTUOD3u1I8df7ss+VfziSFweWeAXOwRAjqs7NVeT1bZAZbf9XI3Jr3TFUVr3mWF5dLPN1MUses45xTqnX2rkKjdi/MKkjVtBr22nfepKDjnCrMbMQ+ZiGS+ZbFb2hdRtIeE4L2SWTfhx4h9PBUm2pJ2keiOiO/Sqwin5lSwqQoWQiir55UOAaQtRO6IEGDIo0xRojQFiPPjP12xPZqh3k/S1nfcoH1sMBqtcZqWCI4h8Xgsd4MwtxvHLPjE4/PPp2x32csFg52eDCAq6uEOGeB9aHGG1mJeOJ4irDP7SohmU2B4Z2qFZrgknfSBrh9T1aYOnFVCLXGWc5K+izYYV370eHyHePxkzWWaylFTCnCRYmSLa9ta8h6GsyzyBzPcxLUTh1Mg/d9H9D3HTrv0bkAyoTlsMTx+hgPT3+AV1+P+Prrl/j53/oxRvcaZxevhX1fUFvpmDiPMxycNmTysJg76z7KuQqUVTRUnplA0CrSJh1REaobXvRhUKRnc+F54eauvn39IZH+jyAQ/P+GiP42gP83gP8mM1+XCZeI/p8E8J9EY/SZ+Usi+pcAfAZgB+DfZuZ/u/ns/wYR/RcB/AMA/21mfgfgfUiKwK4v9GcHFxH9swD+WQB4773HBR6yUjjLNxdt5ZSkpjGn0lbSxFCYJS/TeYWhoIdCIGmhGTqcX45Yb3rcfzQASvZLKWNKEWlOmsu3CJ8xeK9kDC5Qk+SVhME5RhMJmhX2UbEbf7ut5J05mjZ8ri8EcCi+AuiBmPjgQPvuqxz/NUJmRnKKbLAZ/dvGp7772y8yJ6Z5PgIQk7Y5dmas774kWjvMYd1mt9f/2l/tZ0ysaQcpdcopIWeANZc2TTPiHNGxoC6h8yrry8Wwk7Pe4oSsuXI7SpMygiXaQu3SpciJ76RELkVZk+IAmBqbL9oLNk4Ga5dImejWOJtBZ6gjOhuKAWFGF6NdHWPOKCkLNLn7QvYqntjNyE6M2+/frXC+75vfVejx9inUOm0AJwJCxs0nebfvMSVgCPXn0m4U9b71vorYji1MHS+nTg5IatQ5SxdEc3wD+4NoHDBHgpvcc0WrvHNiHEKQ4AAm3ENl7CXKlcguqw4HWODaKWXsxhkuM8LQw1pG14oXxhQT9jFiux9xvd1hnGdJ1URgv5uw344ixRwCFv2A9WKJ1WKJ5bCBp4DjowHLpRdHSoVsCGJsggfWR4R3r2c8eVbb7abMOHsbcXTi4dUidN4B5NVg67opMCluXURW2y4sfXtR8EEdCB0XbtKCxsnQKzMDieGDOr0AXJZnuDrPWC57nJwMQpVjgMhrNZODd5B25eSUzV8j4OA7DGGJsJE0DFgQokW/wrJfYuiWGIYlhjDAUxA4hj0uXs34/e9+jw9/+AF4eYmX777UrqypcHhMxXTeR+z9iEXoMXQ9HHtkluoL53JJNdj4eXO6uXHWzYY15FML2mDPc8dBq8BfRSq/4/T9Q4x+APAfAfD3mfnfIaJ/GcB/F8D/oHnN/xzAf4eZ00GESnQPErl/DOAMwP+BiP7zzPyvAfhfAPgX9Ln+BQD/EwD/DO52VG49BTP/KwD+FQD4xZ/8lE3uVEodak1mMfia77HfOa395MxC8POhSDWWjEwQqcfOeXTBCRRZFpKWx8BrJAaQk9eXUh+LLhSuSao+N2Wpv5/ijP08SVc7FX+Bwy35VDnD6GBkSI3W7dGSlcglj6swu6NbB+u3XQfxMSv5jggkeYzDr7tt8/9DXQY1o/lDvuIuj0KjUEeIcz4o67qJBtRfkBhOEoNlJJt5jIXQY9F6LWNzGBZdU8utwiXB19SNeuxW51u+Th2AkgM3JEGRkqyMbu9cEd4RA+KkEqJEzs0Al6XR/Mzy3HoIlV8xFxEqUta5ODT6NkuFaJmhyNJm5Ky6FkmFcSw9UdIfrDwHxm/PNvjicn1n9Ffn9I4flHukUqN/ML0gvN4u8P7xXg8/btAnrukcNbTl3nLznXrf0LVbi6lkLwmCUw28icDcdQRJLXUoTXc6nX/JVdsdMpgjABGtYo3WEmeMU8RuHHG93aIjjy6orG/wGKdYFDd3+z3244ztOGI/ToA67LvtqNEkMAwDFsMCx5sjbBYbDGGBoV9iMXRYrQJi3mO3G9GFgKHv4HwGp4jEEet1h7dvoqaRxKRcnM3IibE5Eh5R11kDnZqW8i4Uh0iM900JGAfAwTlJeQAtomSIjAlvJaQkYkbguvacd0Y/ge1Q5whp70CZ8P6HJwidlCwbidaROCgdpD8IgeC1LXHnezw7+QDHy8eg6JWEC6nN18qVuIvYns24iNeI8VxRVxmaaZpw7/4pVg8In735DWKakTRtYxE8dLUk1fyf4qw9RtRx1mdNXPdz2QZMJXgA1JEFN+v7kMDKICX+opxtJR1cfN3vDuj+EKP/BYAvmPnf0X//GxCj315/F8C/rhvvIYD/FBFFAB2A3zLzK3lQ+j8B+I8D+NeY+UUdAPpfAfg3m+/7QfPZH+A7UgLTlPD69RZHJx2YcqltN/32WYkTo3bVk/yL065YrrAvTYWKUesuTSji9N4CL77a4vxswtGxhwtyCFDIIKRqWBXGFRKcGnEWacTE0mZyUoM/mdeoIZTBqADKZN6KVO3Q1whCopKKWNjGrAkfeXsbubS8gG+6DCmoUZ8agCaydlTRhHLP+OaF921IQxslOnfX+/VBuH7TwdiUcVH/mG7wG/jwo6wnwTxFjHvRRDUyFrM0TSLqEDqPfujADMxzLOOYVS2OdRwsGmJ9FqnwUAhZ0ySSV5Y7N8EZKdPydRPrQVge1+ZYn9WMuaV7jOTJXIltbQ+EQsLKDYRuED/0ffo7y+XfnMOcs5Qi+doxbDs5fPL2GOf7/tCyNw5Z+09zetq1zLOmmm4YfXv219sB7x3v673ZCiMSXf1iVGx+D++DzQE2xMIIY1TXh3PVcTMEobDL9ROJRD1v8D2W3YC+60pzHaK6rkXQK4ERwaiCVOM4Y7sfcXW1x3Y3YugkhRiHhL7vME1RhHaQcb3dY5o1CNC0wzSJXsjJYonFaoHlconFsMLp0QmGsIaDfN52K7n+cZyELEgJXZew2Xgs1h6hc+h6BpfyTODiLOLdu4h7953cOwOeq+K7IKJaY+8CgIzMETnPqMhTNe4OxtKv6QP5s3JGaspD3u+8E4QrS62/V/2UQA6IHrtr4P33TrBaSyvfoFr8KSd4Jz0SBh/Qd0Fq8HnAo/4EK/8IV2cRX/3mTVHnQ3O/XSf7e7HsEboNuuDR9R28B1Ik/OqXn+Dxkwd4cfEJdvO+wufNvkQGOLGKqXVClM1W2pzBIBFdUzVYEIraIJyMmJFTc3GKboQ5pGkoYnCmW1B+QQD47rP15vWdRp+ZnxPR50T0c2b+JYB/AsBf3njNx81g/qsA/k1m/j8T0X8UwH+MiFYQeP+fgED5IKJnzPy1vu2fBPDn+vf/C4D/HRH9TyFEvp8C+H992z1673B1MeHqasL9xz0SpIf8rCpMU5qFwaktLL1z6LTNY+87dIpp2QYX1j+BUDuDLRYODx4t8PLFNfp+gb6XhRecR3KuGJLMLFrOxCXazlpvH9URmbS0JClZw2RLucC4JcbGwSGpxqAcMjbmUINS9ll9rx2KFpUUh4Caz6xz1xx6zVebDbqRZrCF1wBXf4Cf+U0Xwdz8cpDb/TX3IdFCPZgBNE1+6msJt50bi95FTldYvHGOmOeEvtdIhkTHIeWMABRtBEMCvHeYG/5CFzyo0drPsZZ8Oc31y0Fnh54aYl9hZJP0LURB1Fpz8QUOHRt7wlauF6hdGK1ckEAKiUufcGOXl7QAs5bvHWpAABIRSTpACXvqiM0R+PXbY5xNC0hy5K4Zt9FHs15J/18OLsxB8vlDvP0evd7tekwR6NU3aNcmlwoCQx+aYbJIKQNOYXbo3rSyVye/aT63zTtbekw+35NH5zssux7LoRfhFqqpAPsMgawjMkewGtAYE6Y5YT9H7OYJ+2lCzAnbccRyuUDwHtudGJTr7R773SgIowrsdN6jg8OwWODhvWNR6lsM6MICq26DaSScne+w3e0BSjg6HvDoZIO+X8L7NcZ9xNu370TedeWxXHXImZAiYbuLePNKFPeWazlDvAkPqTPpnEfwHbzrEFwH5ixseyRIcZWpHLoGDbh5aQe7LKVr1k8ja5AiXABrp12V8DoO2F6LYNHxyQLeoSAsMmeCGhAyhs7Dhw7Bb9C5ezh7O+G3X75AjBGPnzzEyekKIRC63gMuadVAxDjtEPOM/XyF63lC7wNC6HB/9SMwMxbrAddvtqX3B9DIqANyjo8J0xyxXLJKVWfEkQFnnf6MvFcbiDGgTc64OE+FEN0ER5Zq9lTXa2oQAVu01SZ8d0D3h7L3/z6A/y0Jc/9TAP80Ef3X9Mv+l9/0Jk0H/BsA/j8AIoB/CIXkAfyPiejv6Nj9DsB/Vd/zFyQs/7/U9/zX+TuY+yE4/OCHx/ji8wu8/GqL44cemYTEN2ukL3KqIrzQL3v0vkMfOiw66Y3NjdJXYbxmoB4qjM1Rj3GMePtqxLAI6BVq8q4rPIKUMqL2rzexiGhd41T0JyrcI05Cc8ijmTyDcdqo6QaOLqlkPciNna8e4WHUU62m/ObG79vPby5j7LeZZHvFzb/b6/9DXXT49xrBW/he7rBEsW2e2wyfGQUZtvaejSiUiswsQAhK8JIWq6Y2J99eSHYkBNA4V5lOaa4jOfegxpJZO5RFbVpTInA+KC2TzzZHjMrnWfkhoE5PQ7qrg2JheB3pliRqDoS9l5kxT7EoqRmELSQmc0hFwa1NV+TEVQESVJT2nHP4+mKBt+PqwECW8OdwslBuvSBMACcCTwHkGLSIzdzz4fpjQvCMQEpczM0GJQWMidrFV8ahIq8MKxYlEk5Gcaib5VVXM5V0gfnNRCLJuuwW2CzW6LsB3kszGkkFzWrQZsQ0Y46TlK8qTJwzIzsgNmIrOcrBHJKwznfKLt9ud3BEGEKP5SAtdZddD+SMvutw72QD7wM4SzvZt9fnSCljGAgn9xyGhbD2gw8Ifongl1gtOiyXPcbpGhfn13jzaofdNuH1y4irqxn3H/Y4PtExctXIyFqQMkVPYvBlTVVnu54iBCnN880c5rI+K6IUNQJOKrdLABF67zCEAE9CvOzJofcBaQqY54xnz5ZwjpRQKN/HnLRMeEbwHsvhFJ17gLdv9vjN519hHEc8efoIz96/DwpXmOZXYE7YJynDjSliTAnX44hpmrHb7zHPGcfHGwz9gONuj77vsb8e0fsBO97i1sU6v2CE3sMHaZ88c8Q4EtglzJm1jXusJc0K27M62Baplz4jzKViylt6zdJzJCmD2npYl7/tMQv+vuX6g4w+M/+7EAi/ve409sz8T9349z8P4J+/43X/hW/5vn8RwL/4h9ybXd47PP1gjedfXePVV3ssTwHXA+VQUuJF7zsshwV6HzD4Dp16p4W0Q82i11rwOSmsC8bRSY/dNuLV8x2evb9CMEifCFnzk8QOnC3FYB3zasmP1bYXjw4o8Iw+P4yAVAfFDlEu0GR5M9qD9dBwl0jEhoK5NCG5RXq7Axq6eS83P11u4Q8z9t/0+fLL259s9anVszfHpr6+nPkHn03V0Gt9/YERI4F1JdJPytB3YM3bG9IDaOetnEutPfRg6vqgkfRhPbjdqyl7ATU1YqIu0zhr/l4cC6sMEPGT4q+UZ6kGiupasdc10DJplGZwteUtrdc7IM6hRy0vC1YyqPedYi6cBusDTgTsJ8Jvzk7wblzgzmCuWIDWmpLW4SuKkwiYPahLQEiVf3AzutH1dn85FiJjdq44xRaFm29rY9Lm+Q+QIKqfmxvnqozwIe7biDWJE9h5CQ6WvUTm9byw/TyL0c8T5jjJOKpssfN6NiBLVzRmcEog7zDOs1a/SPVO33fYrJY4OlrhaLXCqu8xdKFUh3DyOHuTMI8Z/YJwdMroOkFzrESUwPDOI+cZiSZkRBDNWCwdFosVHjzq8dnvzvDuzYQPPhqwObJyPCqrC4rGSFtlgfWN0yLByqHGOxVUtCk3JTNkWbeN0yg/ap26RvmQHigrVg4NETqSioF35xnHRwOOj5foOq+VAaQogeyrRX8ChxO8eTXh888/w3a7w6NHD/HHf/oRKFzhcv875HlGp06Dgygg5uDQ6Z41ATY5JyLGCYjYYrlc4vJ8i/X9Y5xv3x0gS9C16BwBwRWnfEoRIc6YJg8Ql0qttrMfCyAAKmWdMvqmLAgA8F5KS1XwrcyQnYElHsplfZdGPnxjgd+4vjeKfOQIfQh4+t4Kr18x3r0ZgcDojwHKBE8Bvg9YDgus+gU6lXh0KpxocGjpZqSQLINrIwbIof7g0YCvPt9h3GcMx3QrAm/YKCq3qzX5uVYVtPmw9roZbR88Y1l0Nw5WeScOTzO+47U4yEcd5Pm5Rsrtv+U95iR8xyT8/3TZfd6I8NUY6coGUfPcbIbdnsXexiWizVq1YNG5wdQpJkzjhHmOxUDnzOiHTgVNqJDZTMylCxIRM9cImPUe7JaTcjlyEoidIZG9Z1PyE5IPOREGsTRB33fF2OdkqoS62Zuyz+Ib6otzbog9LAhFSglZiUUgrbNviFsF0WI+aAOck6ISKmIjbOqMMXX463f3sY1dJUweLqvmxiBzlQg8htuvHSLghY/C5ZCyt1F5FgJwsoj6sYf7xRxkyVJppUKBnuqatfEx54ipSiADqOJOVPOkxaHQ7+pcQO86LHyPvvPN+xnWJptVcS3FCEMsfBAUaI61xXQmQlIjGMhhP07gnNAPPZYLgfJPTo5wvFphvRyw6AKCc4iR8ebVjOurGSenHo8ee5BjjOOk8HtAF3qEYMY5Y447gOR+Yp5VIEjaez95NuCLz2b0fXVuzHDIUAn3xHL6ZsxTjsh5Qs513dYJbk8iEcypAC2VvZGy1KozC5/FARichycgzhGAVlVlj3Gf8eGHax13cSpYO3oGv0TnH+Hly2t8+pvfY7vd4fHjx/jFL36MfrnH1fgFrq+3iDkLU94I2vqcjoEOhN4ZMVA4K6bBv50vcXJ6hDev3+G9J6cA/74AWoZeWJqOmUFZHLs5zpiiR0KG66n2Ucm1iyhQW0govgRQFeZyymcozmXjHEO/20GbU4KKk88MQWbu9Mrr9b0x+o4I0EE6OR2w3nR4/WqPq1cThrXH6kgW/NANGEIvcpqkXfEUxgI0QtLDnrnWVRIRkDXHC4cQmsNS4RjWnun1EIOWy+VSnmJb5bAX0mEEJxcf/AHdfPXwr145+JB0xAfHltzITcTfnhW4HYHfleeXnwM3XvqN1x/y2XLDtuzp1iEiQi2HaEg9WLgaDf0JYEZYvPZSckYyb5Y7txK5GCvjXtaBGurMRTEPqHXfCKFI7GZf0wEmK1zEfIau5EQJqh9AWufthEAkUVMVBSo5OnO+lGFWnq44YVRSOa1+ehkjrjLCgDgqLmjJYIP7MUPbnOq/M+uhrE2TdPwmN+DP3zxEZF/y4QcGHge2Vq7kgNEDfQKF3LyqOsjleRo/RDgpNd7Md6AAjdfaHIQa6Si59aCSQ4WKclYjYxUL3Bh8NKTVsk9YxZG87HXvkJIaQ7JmNbVhkVVkGIokUaxEpWBrhKIiQd413+GRpoTFIuB4s8bxaoWj1QKLPoDgcH6W8O71jMWS8Oz9AN9JKeI8i0M79B2GYYHgengPKTllKRNjnhDzhKQGmJykBvqFw/HpgNcvZzx9f2jOnrb6hOo+Y5OvNb6Cjh0fIiqZTakzqWOQymvBUs0U56gOuBEhRd3PaTWDzKXDxZmU6G3WQ6mOss/r+3s4PyP81V/+GldXV3j0+BH+5E9/jOV6wm76EttxL+WZdj7regeZcI0R8qoDaP0IYowIIeB6d4bHp0/w2e+/wKr7ARy5gvhaia4NFTkH56vtGOcRbvBwXSgEPumAxyXgsjFuj0dmbaoDOnROuaYA7K1ZAw9mITbmxAAJJ8N/xyH9vTH6BO1L7DzYM0JgPHlGODnt8eblHru3jHsPeyz6DkOQOlJH9s46wFbixPKrIkUqEyJQy9nZHiknhF7K8cRvkPdbO90AMRxKp9LFlqXkAof2NzfQzbddbP5hgcTr6+sW/e6RKn/c8eLbeX35nrvSAd94nzc+465/3zpczLGwha1RXKvfKyWNcjCnUh5Xo39zUG4afKsxZgA5SgQcYwIyi4jSIAxeclLDLaI8Ei2nWEt4okpu+uBgHbpEmU/u2QhxXS810PYaadEsXdfgRBOgMP81yuCmptt6h+uAaMUJ1KChPTMazX6BeeOcYCp/wfTSNTJt0zAFztfo3voJcGbMcdYopsOn5/cROTRLjct/2xksUH10AuH3GtE3ry20TzPWdoCpKAu4fhYBiFp61R7OADc81MMKE7sZW1/MlUDZlhy2aIA5fKVFc4EN1GlnOVhjitiOI7oY0AWvkRlAlJDypOuk6dsAgcLnlDFnqSiyec8AyIijEUjTDOoXWIYOm77DohOS44vnIirz8KlD35Oouc1At+gFPfIePvQwZ2qeuVlTJCx7ngCYIFEqZLhHj9b43aeX2F8HbI4dMo8HC0ucIzH0yZxptui97i2oM5M5ihKkGn1ma9KD4hgZeRZ1iPXes65ZM2QO11d7nJ6uEYIrr/W+B3CC3/z6JX77289wenqCv/v3/gSL9R778QtcXI8FsXD6v4JelHvW9ZcZc0qYcxYxpSwkupgynM8Y4x6uFyM87masl8c4u3qrzZpcOZ/K+nGETNBGOBrVIzfOPwmvK6bimN4kyXJmJVFCUo2KEMlezSWFmHISm+IlVUEEJEipLQG3goGb1/fG6Jvn6dXoZ86g0GFx0mO16HBxPuPdqxHTlpBPPBaLANd5JcM18B4Zs1k+1tTyvMItF2cjzs72ePBQPeScJdfEKDnbAEhOxgd0qQN7zdlwAmle3w4nQHqP16pXy0s2ZDU0i5br7+WxD8vm7OYPUIGDqx7X7WHZRvTtz+y0/w9i8NtUwbemKxqDXyCz+gj6GvlP1oPDEURoKGdYvVUrvZuzGHVrrdp6zDnmkr/zSsKrWvdiQnKSvJtrmO4mMRwUZjQinA9BcvsKEZrRLKp6LhQ0wpwIEEqLTEJlAieVG3VE0m1LYXtpdRprzbyr82E68m1qAyTKkjDtiAP3UlcEV8NbG+5Q1eV3hH7o8MnZKc7H/m5ikNlsnTACAVFKrDBEwN043PVZWJ0gm+cSKB7abRkTNBGVLltzfrhZ/wSqiIk+E5mapEZTvvMHkVNu6/lRP6ticbInI0eMacJ19MgjS7XP7FVFjxG8OEkxzuWzW7StdICLCfM4Y5pkbfZDhxQTHJNEud4pkc2BM/DmpTimD584gDMyV2ElmW+Pru/h4JEThCmegL53CB6ImcFJpGEV5in7wZHHYljgwQPC2bsdTk5WIMrIPBceDTOkAomTrk2J5A/RJ5t/MThMEjBllZ0FG1IgJFoxhlz05W28WveRCIiRkWbg6GgoZ3PXHWG3HfAXf/4Jzs7O8NHHH+AHHx5jzi+w3W/L/BPVzwneIWSF38tZA428M7bTLNUU2qAnQ/gWPjrJ7edLbDZrnL+9xvr4CO/4TeliiMxgV5EdzmK8GQx2DCTGNFej77yDz05+Z8+eRXBKUgQo+iylj4tz1dknB++UK0K+aVmsssVOzj4LNL/t+v4Y/WoT4bwHZQLlLPX3C4eh73B8vMDF+YSztyPmeYdh4XH/wQKrZQfTkrf/WYMcIlJ5Xo/rqxlv34x48HBA17fRAkp5lRw00m+89wHUC/vXxUm6QJHDnGcQsyov3YSwD3PTd10HkFAb9qHClhqywI7Fm6+z9xLuVrT7NmNd3n/Hayy6Vc/koOa+jdhuORHMqpcNmK/DqF6rQakp1zw2GzlPv4u4Ms9bmVuQsb9xULZWamqjiqmwA7z8LgQHBF+Y905RgBjl4PNaXy/pHiplg/CoPcdtLMEq06pRcq6Oiq0bIi4VI0apgj6rIQFgRoy5GBbvPTxrnXPjvBoCUKbb9gao+Wf9l+X/p3GWCLLrcD13eHG9QpF9wOG81AkHwASOHmCSEjxXdefrujAHg4szUpwSZ8iDjpY2tiJuxEn0MC8OZV1UqOWQCp8WB176DIBRequDqTh6NxGCW/AFgJgTdvMemTP2k2jd90FEeogJxFEMZs5KqPMwXzkDiBo9bq932F7vRQAKsnaD81gtBuQxYtX36LsAB8L5u4Rxn/HwaVCYnlQpVAzWOEYAIg+eIoNzQugIwXfoug6ECE4RQNJ1Sc36gCxSDHj06B4uL77Efk9YrnvkGCFEQIKNMCv5rCQgua4f+T0AygDLfRraQboGc5Z7zjY3zCKw4xujpgNu0zHus9TPDx2870B0jK+/3OPXv/4VnHP4s7/9M2xOJuzmz5FSbNZHM50kxrMPUlFgee6UMqaYsJtnXO722E8T9vNcSvLinGQPOsJuvMJytcJ+t8fm/iCZyBtVNeU8s8BDo31yIvLF0aJ1CSZLB0toszdn3CD5mYeUDHe+kwDWiH0kTrDXce86a2JU90RMCZRn4E6dk3p9f4w+auRAENIMORHeyeyQkLBeB6xWvUz8FHH2bsTzL7dYrjxOTgeBba3LHSBRUxCDnxPj4mzC8UmP9SYoI1u+Q79UL9keHg4IouQWQoCfPcboMcUJFAlZS/msXaId9EVJ78bBhpt/N5uu/7AITu7gMDSzSJqLoMnt0O0uA/6HRvftZ5TDXYeksqarsbr5fYV1rX+3vBsaJ0wMRo3oylCotTAOhpVmmsQyVPiDG8iLoES+aRZYtsC5GehDOTCyoghGjrGouu+7snlrjhhlc5NGVfZsBELogkLRKDBca/gkne3AydJFppcvB6mDEeu0FIy5qPbZuBI1yolUkQKgoiemZU8kZWlJ5YancVZnR2Dn67FDzdcWr6EYA/lsAmYvjCLPAunfWjIyt9ZOFmbwb9TZl2XNkjeXcjGGhfn2FDdXaeWbMG4u4ZtpAXuzcw0KUH4nC5Zargyo5GSnNINYZHiHrpMe6CAgRqyGTsseOxAk35qTwPgpJux2I66v94WdLukmj6ELWHYdpilj6DsshgFXl8D1Zcb9hw7OyZhJ5AekJFUhzIQudEJSzQywtKHtBw/vgKhImNxLKh4boeaUnfNYDBusVmuMY8Rm0yFqFFsQGBsJQ+KafdeOtfyegIaNbihHCTv0jAxOpH1vIoj2mUSkqooO3q8Q5w1+85vn+PqrF3j48D5+/NMnYPcau/FSnb3WS2tQUiLIFnUVkYDUuO9jxNU44mrcYT/NRbU1xYQ4JVAQNVb5LHnQ4IXXIchi85U31pmsQ3WmWf83p1LF0aYDnaYJbIxEXVBk3zsXhGfmUVOBYMBJENCHrowjs1SYlcDvG4JFu75XRh+NUXHONbW8dRByFu93GAIePw2IU8a7d3u8erlDjE0UQYIen95bYH1EGPcJ05Tx4NFC6nRNk5pqiY99HVnHLFXzc1qT6p2I+Xg3YZwncFLjSLIYbceVI05vu1DcDg5UvuNvbS6YD1/Lh4uzQJnNoVmf4duNfUueuu0ssI5dLQW7+70oEPPt+mA+2FDOCSwmP3dlKExKNDd9BWKMxfEgp3KZRr7jXEl8cyriPIAgBD5Ivt4Y8LYZgzoOPkhTjmpYG7PBTXVDi1gYHGjGDrKuHInghpB2XCnNKctVHajMWXK5rDlj50ReupH8Taqbb/nkfqjzb0MmdAFBHKR9rETI8yTkJKlaCHDe42xa4dOL04pemCEAAeyATGLwswP5DAxJVfX44IAF6ffaulbD7CzoNpt+y4mTt4vfVNdnQUAskjFf5BsMfvunmSUcGK/DubN0mn0Ul73IqgCoMH2O4CgwdWAqvAzru1EcFYY0e0kRofPIkIjZO3HuELi0xnXOY7/12G0ZD590AE0Yp4i+76sjUfQchCnU9Z30LmBgMfSiO6HEwbaJE/m6v2RKI0AzmCNWqxW2u3MQLeBIFE2/9Wr2JZuzVJzZZs3pIWpnadZo27T8SwBwEM+IjO/x8YCztzt89rst3rz5Gvv9Hj/56Q/w9L0V9tOXmKd9mX7jZQEo5ZhtoFvFgmw/cZFkH6M01LK0oJwhsoeCFwLnrFot1pXVeAoADhG7JuK2ksKyjuTwLeuk/LS+AJauCy5IV1cfSvc+Jk06BSopbIH2tclXljRRcB6zc4gp4tuu75fRbwy8+evWOxkwY0La/1wOnsUi4OnTNWKSDS01pgLF7ncRb17vcHUZEDpC1zn0vRInFG5laJBgtZElONINpjgfOYLr3EHLVWmCI9GREF/QbIYaoRW2bBt1AeWAJftxWezyD4ua0EBnBwZdvXJbfNVLv234vwvuN1iflRxnm9vee6AvzW2ZnaYfmlI81rKmel/yl6JAp2OUS1leLiV53nn4QerofRAwjLOQqqb9rKxnqW2VPGMqjkVbImOG3QeH0HcgqgeI03k+GCFqDA1qpAR1rupv6n9N5rnzXSMF7WQtkUUK4qTMejgl7SORXMI4i9JXIaDJbGIa51KmR07WnxleSedIwylLXfS9VBu4EPCPXt7H5dTLHRbjTqDsygEPB9HL7yLIcS0kQV231TjUCO7gsMdhRGlvIhSLoeXPakD1T3NsrJKgpkduLEi6vYbb7UONQ3Fj8zRbjA8RIpI7mXOCEKsIDI9RORcbMLreOsBxQXyMAExcyVspJQQssOh7bJYr8LzGGAnP3hsAN+PycgID6HvBeZJ23JPUVQdHDsEFwDtZ89blz1TfoEQyoDiTrqztiJT2yH7Cer3E2bt3AFbwbgJzAquC3l2puGrQgVoP3nhKZc7rOWLNaVpIv+ULySd4eLfA0J8guFN49xl+85vPcO/eCf723/kpFutrbEeB8w/uDYecptvLoJ6aLZqUuRJY7T7JGwLlyhnVfiLZmsptYMbl5xbEGP/ILq9zdIAM6JlnnAZP2pZXz4HgAwLJexKlIuzjnCuVZ6IZQcjZI7mMmKMGC9/uuH2/jH4DBwNovLcKw1qJVfHKHJWIipHgPOCdkOuOhx7LVcDZ2wlvX+9xdCys7NS83/tGilQPPiPDSHST9ZwU8k1p6MFCqMG4k2YMjsAxSlqAxLOXT+MCyd5a0tQYk7IR678LfFrt6a2rKNwRfScB5OCrb0T5WRXvXOPNy5S0qIWNW/2MdvPK626yexs0gKQG2QzzPEltNDO0HE6+O3S+1NMDYvTnSRn7EKIdETBPc1HW61QP3e4nBI8QQiHvHSIrArdXtww3jEOdj9JyuMyhPKtjgLT/wxBECjqoCIqJcYClgdTsIjofkVhKfzoW4x9CVFa4iT2hCj/JF92ep5TBsQo0WevZ64nw1eUJLqdB7nv2QswjBhxL6Z3jEtHbA/Lhf75xrRgkytYqtTgq1Jz9h4esd3XhFmjaEDEY0gKgeUb7hANyY1kIB3dV55MtpVD/XRx6Vr6ovVZTZFLiJfn5/TwhwWG16KtzZaqe5Bqx4tYR8Dhar3G6OUIaOyQK+OCHS6Q84vJyh5Sz5PhJNOaTqkkSpCbf+x7OqZIitBwuRYQAEKnBV29I+jzo2OhcxbTH5dUZri4IV9d7EAb03TGAiJi3yOoYfvt1IwCx04hsmipPytrrMvg2OgqCdwssF08xjwv8xV/9Bm/fvcMPP/oAP/zoFJneYLu/QisIZGvC0rHA4Xli/755b+XnrHsBde865yTlmhOur/YYxwnAUue76uYz3dDO0EsEv+wszA3R1jWOV1MmCwj2QyiG3KtRvzny5TlJKmIdOzAcGG3DHqeBw7cK2H6/jH7UCA5AYWGjGZTCbiQSuIwzAruyIUBKBuMqg9j1Hk/fX4uRmU1gJ5cN4TQCJyLASS/sQASQQ84zHEeQKXExg+DAzoO6XuR+AcwxIlLERKTQbaqeJGoOFmgibl2A9fDEHUadbnnC8pl3HNDNeftd8P6h518dIIvwb310431y42S0h715vBZJtEafNCJuv894AuQc0hxLmVJhw8dUPO+kKE4wgp0jxClWtAFVWpeI4DuPvrecmd2i5tTBAln7OsLya52pA+cLxXgXt40IngEi4Zv0vsMQenShQ3BB10Sd68wZgQImTMhgdF77sKtIScpZ2ePCZYjZiWgHoTGQKCxfCQLrfTpHGGfCX7x+gIheoPtRIgwh5bVr5fDv32jrb4xBTdvIwSjPRqhCS+3VREiu2QeNUUdzuLecD7kfFRxq5GLF8T3U3j+43YP1XIlTBCqoHJU1WgV/pC3yhEgOm36Qs2UidCFI9YRYFNE7GGfEKUnu33mslgusVyuM2x7B9fjhRwuAIra7SdEX0d5nMkSQ4FyHbljAQZ1DT8hpBjOEi2HOFDGcE+5IMcSQ5xmnjOvLiPPzPTiOWK026LuAODush1OJ9OcM5t0dc3M4RdvrhH5Q0itBHeGKnrQGtUhX29w1Y+79gM3yGV6/yviLP/+H8N7j7/ztP8b9hz22+y8xz9carVP5cgtoCo+IWQi0bI7g3Tde0r+670Ugq6KI4kATQKk4fwYRHaCd5dy3NVTXtEX5prppUrrW28DWHDPgNHAztr53vtor1YiJyjkQXkVGVuarS3pelnVc2yB/2/W9MfrJupMZZOyodIQjqt6XRI3Ss7zzXpj+oMYrlbx/ypKfM9nNk9MBX34+4foyYn3kSw6GSMp3nDPvu4MjrxDahDjvkfIMIoHaikYVSY5os1xhitJqt/cd5hQxRlGKy9ZigRq4DAZ2NpGWWezDNVn/e6cRbyJT8SDK53wXlN/yACzPaGzyAoHp76W5TTog4NnC128rtbvOoeaRi8UocZ4iJ0bWEQarVQpYnXfNMzZRNnOFP1MGz4xpnDDuJ5XRnTEsOvSD/K/ra9TfQufVjsp32O/tezJnZeP6w/fpGVc6N+pB0Gvv7T70CvGbPiTpdMqzBefhIFF3sh4PKuuZUkLnA+YQMbkJXhs5zTlpHrjCj2CAYgcXA3i9V0NJ+Ms39zHGAA8vEX5QmVydhjYysTG4ed101No11i6/lpRZ0ai7P7tz+cCYW0nhQUSnTp2RRw0+bnkhtm7qXdW5aZFBW/tEWhFR1p8YUOusKPnyjN1+xLSdsOx6LFzAOEY4cpgm0YOfOWO/G3F5udWGOECAx6LrcLTcYHsWsFp6fPjRBhkTpnEq8rTWeZFZApQYM4Z+UdqBOwdM4x5EJOI83oEhEt9kCKCiS5yB8/OIs7cRMUpK89GjDY6P7mG9vo/Pf/8Gu92Ek5Mj5LxGSlukvC/zx80asD931wlffT7iw48XYK/zr6NoJFM5S1V7ws7lG2dRHzYI7hn++i9f4vPPv8TTp0/wt37xM/iwx258iZjECSqfnTOcV+ddJ8f2ts1j0qAN5gTpqwECsQNRQHs2FjKupSedEG9D6DA3Z11dL+2ZSvUPrudyu7acU9Knh5YrkiJtuaDChe9FEukzFLUDa6+WSoS2AAnM8Nmrs0fasKemLL7p+l4Y/RL9qT60efVJPavCHHcEx04NVBMtqBfHqJMrRA5rqpF0QQBff3mNxdLj5HSBk9MlvB/g/QJ9t4F3PYJfyHvyjDleyw1qJ7OM9tCrUE8fNN+WFA50Dp2PEsGpfGNufGhLHdQe90pYs82pXqwt+btNuC16++eh01BzWnznhs05I8W60XxQ2KpxUFLKmKdZDA+klM237YMzF1jaDnxq5qBFA6pHb2NYnQ7zbKd5RuCgpXSuGDzMEvkXDoDl3Fjzbd5jc7wuEryw5zBHozHsdgDedAgAi/yyQKwKqTqyQVYYzzk459F5j96HIgcdnEdHvs6L/kcQBAcXnDSRsn7e2swp+9q9bPIBU5oxTjNonhCJkSnDONS+c3DskaM4ref7AZ+8O8V+6kApSOe6W9F9Nci2ohp7W4yi3XSxs1yNhRnqQwNQl11djdV58C5jFWZ91hphl3vSfgUHOVklhVsZ1E1jT0Say21Il/a5ihBAz5F6MyjGa9pLLX4/dJjGGdN+AhFh0XdY9B264DDHiK4PiDljN87YjhPmWLs4DsOAzfIIvF9huenw8GEH0FwMPtRJDspHSSomlRKw0gBkmqeip7DZrLEYpPtdyrV3gwUGMTJev5gw7hweP72Po6MeXecAODi/gnMDFosl9ru96I2QB+BAGrjcvAjSj/7F8wn3H/Xohya9CRlv22N2D86TltBS+RmRw3J4hN3VGv/+X/4a2+0Ov/iTn+O99+9hml9j3l8iph0yz7CYROrRfd0hFquQtY8WlMP2Zj1LdL2xGlwW5HDoOmRkpCROyrifwBApbhdaTQSq6pDNc9b125yljuDUUctJEGFijfrhit4LiGCNh6BG3ztf1l7boyW3njDLuEZtF+9dLgiLLJ+EOf0NgvfNcwKgAioAFFbJORe4jhr4o+b8XVFlMgIUEWGeMl6+3GJ7PePBoyXWmw773YyL8xlXlwkf/egIQ3+MPhwh+A7OdWBkuByQOcHnCTnP0KJrZGhDDC3Vk6/XfJdjZLji7Tly8DlVT8905A0S0sVWFf2Mu0BlMTJnuBr86gFenZ0Dz7uNjBQZaY10O2YVZjcYq0b3UAMdZymDcWpYfXC1Qx7qhnTO4K72c6k4MIX8p2V5htzEKIQqGU/7LB0ThfSJSKDVORaYHxBDFPqA5XqBvu+x2iyq0E0ZBCqHWLtOnLUoRrPpieBDdUQIdmioJqNKPQcXlJkr7Vo73xUPHzY2BVKUufIkYjOq5C8OoHNIyYPJjL7WyWs3LiLAZW1p2kKTREAGzq8W+MsXD8DJi7HsMyjcfVg0R3qzhm5E8Aevq/uqVFa0QZcN2TfUExMBj9dTUWNzJGvf1jbri1phIXIo8weFTlvYwNawGfyDtJcafOdUp+HwSZCSyCvPsxh0+2gfPBahx2IxoOs7WKrIERXpVeu30Q89nHNY9QvQvMLRvR4nx7KO5nnGrIb8+nqHmJKw/RMjqnMaXA8CYRxF/S90HULXw/t6hFe0UlDPcc948fWMxWKFn/3RY/T9GqUrJxG8k4DFOY/MJtebQWTO/g30Rs+Rs7MIzsC9e6E4UgQUYlxh0TMVzYrCi2Gg65bo/SN89fkOv/30L7HZrPH3/vE/xXI94Xr7e5H6xQxT/2ODnFrIoVksrcNYF2ZdG3IOOmR2+tnKgO8CXI7InJCmhHmO6LsOcOIfSCWGOHyB5FlLCaytbxV5InOLqa5HU3OV/2m6WEvtGIxI0pNDggNqzh49R9TA63apKU6d65wkXV2GAkDijGl3d5hn1/fG6MecikZ6SxZDo3sfXIWFiEzelAU6PVA6c5hjwsXVjLdvdhgGjw9+cISuk9d0fY+j4yXevIn44vNz/Pynj9F1CyHmAQA8iDKIAhwFONdpBE8gEoZsyrHca0oC5cMJo5qyeqPBIeSE6L0c7M4IPfJa59UomeY/ocDHBNEiZys5YdZUAR9u5FvHtf1UD8eS1r75GioKX97XvgV2Pzmm0uGt64IcyBZ9GXqgBt8sQoFluRoEc9ikGYxsASIUQ+zIFSausYNzzmLo1ejPo0QLhkwwC5mv6wLWm5UQ/3xVbNOHAaN2qiOiQuoTYp5F49VJMKRJIhIqilnm5pQ+4b5DFzpt7xykuYayu4mE/JPbw4VMMlqJjPodIMnTW5UBAFDU6gfn4JOIjnh7FmbEucPLywV+uV2Jal4/g3wdbxuBJ0d7nCz2eH61wn722M/u4MxtRaRsGVm0YfNWUJ8S1et3OELNrd91QBEerceCdkinHDXUuR6CxT9CNfhtqZoZi0ocrHu8vU9rG9wSMMt6ztp5MKaCCoFN+EdQoSmKsFHnnTSH8cK2z2BMug+MwT30AUcrj9UGyFmQvLxn7Pd7jFPENM3ogi/lpEzSujuEgL0iC6vlEv0wKMvb6dwKAS3lGZkTttcZL7+OuHfvFM/ee4JFfwTnO5EB5gRHkpJ0FDCNE0IgxHiNmK4U2q8oXhkr9XYENW3tLxftE2d6Fjre1u9C9rtD358gzaf4q7/+Cm/fnuODD57hhz96iJhe43p3CVV7Ahpks6wKqkiGVSXV39lZUtcQkdeP8mrFJQ3kSSLrLnToo1RegKVFe+gFYaEMXG8vcG/zAGfvzvHMP5XWwUjledrUUBuoyJ9chLtSTALZZ8APQtgTRELTEvp5JqmdbOx12cqyrFyfzKJs2JYZGvKRc8a8+xuQ0885Y7vbgWC1lFyMhzVQsaYnICgBJmOao3ZgMtVQGfTdPuLViy1SZDx8tMLmqAPQkNGYEYLHs2fHePVih1/+8rf4+KOPcXR0VMRNHAkbO7kewWtUD4LzCxBEm1pg44wY94h5gs8OyTECexUFkZrgoLnb5DIiJWRnOXCFdQjiNDAkIlQVupQSPAmqIPC/LBaDvixCPbhKQEiGTd8ecHMGynnewK6WviAq2u/mFNxEElpoLB9EbbahlIsRrTd5LlEF65/zHIunbAY/qrpcSllY+SqFaSiDyaCGTmR0S7VBe39AgfQJKChFy61ox678m1ly85qjs7I8IkLvpS/5EDSP7xqDTxak0IFxLS5XDWPEmUIGk2irZT0MO68HEDEQZzFMWfN8rG2Co0e/yvijk3cYwgSHhFUPnM1L/PL1MQDgaDHh49NrLLqMp+szvLl2+KtXp5iywqM3lg03894aeSdeqNy7pUYasqWg53TL7nvHOF2MGjFWSWIiqoRJNGuI1MlwKIb9tsFSQ8IZnCtBkzQVUOa/3AuL1Ko6nVBDIV0IpXsmM+N6u8PIe/AygjyhGzokMGbO2I4TpjghpoSuFzGeYdmh7zNynFUMjLHbCofHOcJ6vZD0lJZchhAAOKQ5wTkR8FmtVspnkXlFTMioBn8aM149j3jw8BRPnz5B363BAFIakbLkyL3rQM4hZ2CaR6zWDtN8hpguEfOI6oTnxqAJytL3hBQ1fUoAZ5S5Mp0LUTMVESJHASH06Pw9vHmd8JtPfgMiwh//4ie4/8BhjF8gxr1UDBBh3DPO3kWkWFM3XU9Ybxz6wcH7O84ktr1i+1Oqo0SoSAXSOIqIEffqNGtQETNS32v7Yi2L5YSzi7f46OM/xaefjEDs0fkBMV0Xg38XAmoLqzRcUkTSQ+yS8XoYBEciJW5prwxWddEaQNVnqe2v5fzMJWi1BB4A5MiI4+L2+DTX98Lop5yxG0c4iGKW103jVYIxUy3ZA6jAIjEm+L6DtW2MMeL83YizsxGbTY+HH6zQddpHOtfUgR1iPng8e/YYf/GPPsXvfvc7eO+xXC7x8OFDnJwcg8jDux6AhyOLJBmiS53AkP7NRB6UHOYoHrbXUq7MGSFJqVlEQqYM6g7DK4tGATnvOIsuAQPITlTg5hQRc1ReAtVywGbRHvrVrfiMjFm5CLW7ltYct7lWizoPeADtLTefKU4Ulzlxrr42xlTEiwCDu7LCss1rmBG6IPCiGvykTPaUcjHqAEBBPr/rghJ1fHEWDi898NSIhT5oPawJCaFYvXLMMFRBRRyEAF9K8Lzm8DsfEBDE6HcdvPYgJ6BGmqiHh/yzcYbIGL+EDAdHSmpTR86QLOMaeHLILiu/JWHce3hP+MGDERQYORM4S7vhRc5Y+Cu8ug742YNLcRA1nbLporCMy/3dGC4cpmXKwCgKYmtAELb6+zJuMAdAPnzwUaKy+jElYjTH3KKzarCbtcw3lCENp1YPwZy3ukbr+9ptkFlY9/Ms3IKkNFwiQpozck643u7QOQ/yDos4I8wz9jlhihEX11vEOQEEVczrJW/LTiuEtJthEkW+XpX9QISUGaxImWYCsVousFgMWCwCCIQpy+siRxBJM5wUGc+/mrA5WuHhoxM43yHGEYxJInieADhwGMAxAnnANO5xcm9ASjvEvIXpZLROEDfjM46MrncIoROLX8ZFX5sZRB7B9/C0xGI4BmGD33zyNb788gXu37+Hn/z0GcJwie34FlACWoyMi7OIi7OIYekxLHyZi3FMuPgyoh8cHjzsMCxciexl7ZTVUtacBAeGKHqIyl/A7CM6Rdw8XEGI9zNwvd8hR1n302rCjGusVitcnm2xWZxiO141e/Rwr1aSna6fJGmpHDM8RSXj2rlrZd3Wbj0bwHGINkH2cXmeg/+p4Jg6ZhkMjlSI0d90fS+MfuaM7bgXMlS31gmVCG+aBS4z8kR7YnUhiCfNwPX1hNcvt2AGnjxbY7UK8J5Kjiop6axGLRI19F3AarXCj370MZzzuLq6xJdffokXL2VxW99rg7tBwGazwdGRlMokP6FYQgYSJnEKCMiZxJEhVl16aw2aClOTFQoilkhUtK61nAsRc4pKBsmSGyXCrTMbtlVQRHLqEmsjTd1cBJT8MarWNlCN1yFU3n5R4zip4c8qkGMfIt3ttBNdM1+tURQCn25mp81urCseV/Ekm3LjH5Scr7J0Sx7Ynq18F0AKU1ouDTfK8swmi08v4+WCL9rZwYs+dmdiG87Dk5d1p06goxo9l+G6FenfnjGrlpCOW4cOVmaWTpOqIEYgxBQxT8ByldEvXZkH+6wNCPeWGT84nTHFgJiiNmsB4DJWPTCPLQJTG6q0sP3NKMiMatHTOwiO7B4O12TvK4HMDtXyvSmXKpzabKgeumgP4caXI3+bm1LXKZdzoV1vKWqrYYX0LWXEmaU8ck7Sr2DhMHPC9TwiX8s4xJiw3e/F6GeGYxLkYE5IiIB3iEmQya7z6IYOi146PUbOiIryxShngKETrL0ZMpthS5hShHfSLe7F1yNCIDx6soB3jJy2yHlE5h1ynsFIADswz0DXIc2MOY5wjhDz/sDgG0nuwJi1+g600IU6gvMEpgRiVa70KyyHewCOcHke8etf/xrX19f40Y8+xHsfbDCnV9iPV3qmAnHO+OrLCWDGo6c91htfyiVlXgLiLAjA11+OWCwdlktfkB4CIfSE1dpSm1Lh4F1N5QSvEts+oM8dFt0CwflS2bUfR6RZAomu69CFgF06x8nJMS7OL3Hv5AQv0hdgV+V/CxpIOOCotMTVQiT3pAQ9czyhZ5UQcU3/X9ayq+cD1c+UJIlxf2opeNGOiTf32O3r+2H0c8YUJyB0In7jhEhhHn/QXJxNhHMOAULmSJHx5tUWFxcTTk4HPHiwALRjEZJA5zHHajjMPOYk6lAhw3tpe/no0X2cnJzg0aPHePHyBV48fwVmqU/teyH8pJTx/OtXePXyDX72s5+i80twBwAZOc3CVs21LCP4AN8PUhXgAsTITohxgqj5MQRJCGBl3gLAFEeMcYc8XiHtonAI+m8fxwM2enH1m9/JX8pl8Hxbb20Rn5BVbr++nKm2uGFsa6fzw2XxCyRZG+UQUYFVK0RM4iCgqeDIWTa786Wcy6B9IRVWAZ/WEBRyFzXkIDv9KuhQHCTTaPBO1dY6h0AefdephnZfWLmSR7QmQA6F6GeHR2PoD5sUSbRSx1aG1HLiRgi1S/K8rC06qWhORMq4zCOO7/UIC6uaENjaeAdg4cZ0cS6dxxJneJ/wi8c7/IOvesyJtCyIyxwZEbOO48010vyMb7yoDV/0l+s+3UA9UL4vxiiOlpJHiz9mTiNrjh6HUVfLIbAfU/1R+frDPK3wMMiREPmmiGkvhLt5jgC4cFXmOeL6ei8/d4RpmrG73pdxTV1CnCJmllLi0El+PygHwLpCCjKXsBtHTHMEIqFDBweHFAkRtS+7dwIuEQTJefV8h2lifPjRAs5FxHSlzxvlXNFdzJxBOcKlCdOcwZxATlOO0i7uwHliPkRKu95jt3XouwfwvkeMW8zuGilP6LsFhu4I477D119t8fVXv8Ll5RXW6xX+sX/sF9gcT9iOXyGlsezZGBnPv57gPeHZ+0OprCKdpKyCXF3v8OhJh+PTgLO3M66vqxYHM7BcOiwWXWmKw5xV9c4jpblIoTvvAe9LymeMM7b7PTQMR3Ae6/UCXQi43l/g3oMf4/XrN3hK90FwiHFGkRi3IBAoqQJTYTQYnpUX5ChjijP6AJD2DM/a0MjElRJXwrlzHl4rdjK74oRblF8O0OaM5ejhurvCunp9P4w+S2kSEzCnWSa765Gj5O2JqCiuCUwo77k8n/D61Q5d7/DBBxsMiwBykq/LbPCJiCNkiy7V8w0E5DQj5Rmn947w9u07PHjwEN57DMOAH3zwA7z37H1YU4jQGJh5nvHLX/0Kb9+d4cnjR/BOUwzOwWVCVjKSI4cuLNF1Gwz9EbzrBcJLI2JnVQEAUQfvAogCSMmE07zD9XiOcR8xXuzhNodRzM2rKUYpP6sUtRoJ2W/avxbdccHEC3x6E/Yv86WMZFCNtLPCnEbKgxor6kIZ85SNcCNwfmnoYQRBMlKbB2fGuJ8wj7NwC7wv5L3OhHdu3NeNx5eDo6Ad7bjgQFXMO9Hk9+QRyGPoB4nmtVEPQVrvSkSubH6yf1tErF+v43bT8Nu4HUTWJPeRWFuoKuoAEi6FvdERIe4jgk842gyARykXcjjkM+TMRS8iaUOoFDKGPuFPn21xsWN8edHjaq9tiVtInOoN1+dBAbIOT6d2NOsoA8CySyV6Y7XGWYltMaUDiWGL1o0dbmyVwyoQKl9abtUs/o0tUXkJdfynccZuu8f2aqekWa2esS5nmRE5YZrFWZImOxM4Z3ROGvR4EDwrX8M7uM7Ddx5d3xWjEVNCYsZ2HHF+dY1pTOjYY3CMo/WqDCarAyoghRiOs3cTLi4SfvjxUqtIZiQWx8REpWysxZgKM37cj+h6gvO1fLY45MXxryiIcw6r5RqX7xjjboGcGd4fw/sTBJ9xfbHHJ1+9xJs375BzRt93+OEP38fHP34P0/wKr9++weXlDrutls6yRPmhB97/wUKEfspaoIK0VUeNMAyEp88Gu6s6dxaX2HMgKQk3A8SICcjspMpKidXee3Shk7MuK4ve1hUI2/0Vnj0S/kTaA6t+g7PrN+p4ymuhPpLplXAWfX87x1LMknKGdsJTeyAOjTnP3Kx5WQ9S5q02h6X1MhR1SaolY3ydupUIGX8TSvZIZSg5Yrvfo3MB8yRCGV6FLlq25X4/48XzLcZ9xOMnaxwfD4AA5ULisMgRGVHrHs0js88Ubu4ePkw4vXcPv/nk97i6vsTJ8Wm5LdskNw1L13U4PjrCbrtVxyIqKcOYoVLPTeQRQo++W6IPa+EHEJBzVEKONFt0LpSclRwKGd71uLzc4ez5hH5FwIIwxRtu4c3r8IQ+gLvbsT6IlvR1SWFPQMmTJhupH2mesR0qIO2C1YT/zFx63stBTiXCz8m8/VCchKAEQZOhJSK4IJt1ypN43EFKc5arQTaed3fOycEwoBHZaIyTwciVkS/Re+87BIiCWhc6DBrpO1XiciS69QZBf9t3A0103LyuEtGMOYzyeUYUhNX8ms47mVYAYbyesNn0GLpO1jb5xoGgYkDYA8kH9E2p6Jwiphzx3tGEB4sJnU/4i5dHcHAlfdAMngZMVIN3bqijN32sxpm0iohNHzX6PkzPmNMHqHFuVBjt+8pzmGPVGvx2OXODbOlhCwcgQVAnQMleVcgJBPR9ADkntfizkM1MbU60KyBNnJgx9B2Ww4BV1+PkaIPFYhAtACJwIExghBThIPtjHGdMWaL8/X5Cmln4J8HW+Qz0XRnflBLOznd4/vUVYkx4/weD1s2XmL6ZlHZyysQgxqwRZQ/mGUVcuk2TkDirwa8wdPdwvie8ffMJvv7qHwCQenPnamXLyckxfvzjD/Hw8REuLt7g+fM3+NWv3uH6WjhLiyXh6Ni67QlStFjW/gCsqUOTo2ZNY4oDcwMxvLVvZL5Np0WQXXOWCNMsny1dLDN20x5TnCQNqu0vU0oYdxP6vkPMM3bpHMcnx7g4u8KDB49xvn2r5GCqiFdqOEeGTqm+S3YQgrU6CUxSWleQAK4Ol81ayixEPwAxVwEfT3V+GfKMKaeygSgR0P8NMPoEkSVN2WE/jYiU0IcOq8UCw9BrVCcsyrdv93j9covjkwFPPzoWMRYrIc2MeU5S+8ziRMxJ9c21kYUnU04KIO1U1fcODx7cxxeff4nVzzfqmR7muW9e3jtst6Oo9sUdYtwipyimxEmJCblOxH/cAt5LNA8A3gV47srimqeI16/f4s3rN2BmPHh4D7vdHi9evMTxgzVyl3A1trKaFlkdSvTKPmepmoFBpvYO/dmBsUeRGM2ZyyGbU5YmQ3bQu5quMPi1fJ95urkiAxZJe+1uZ7tB8o0ylj74UkrVwv3MUvcs96SpHI3wD0qzyijUh2sJZ3ctMmeRuUZaHh6D79GHDr3r0HdC1JIo30h6tcnKTcbvXcb/mxwCO3idcjiMWAhGMe5SApRgT2AkQYCw3UY8fW+N4CXlQb7OreVuAZmH4D2SFx6CdezKnBAV3Xj/aMLCv8Nn5yu8uh5KpGqHbgvpH5zN3wCq3HzkdVdz+qbCF6PIZ7veVyPfOgzmOCoqZTyMgtaYZLX+YY7dTa0Aq9ZgMyBcSzaXK9FyyCkrfybXbps6H6LnzlguBhxt1jhaL7Hseqw3SzhHmOaEmROQgetpFM6A+hv7vXR+G+MsiAakhaow9Qmh62QtZeDicoevv77APEccnRJO7g3ou0bXvQErCgvc5lj3EvOM5arH27cE0JE64TtwjsUhDK5HCGsEf4KLM8Yvf/sVXr9+A+89/uzP/hSPHj1CSgn7ccSnn36Kx49P8OjJgJjOMc2v4YeE0I/oBo/373foF1TSWoZKtukW3woE6WRlROQsREXi9v7btI2tKI2Ydb/ZGZWdKBVK+bTA6fsp4nK3xeXuGmOakLWbXeaM7X6E6zxccDjfvsLp6VM8//oVPnh2H/3QF0PLRfBLDs2ca76fCAiDtOHuC6G4qYRgtTM5Nj0zKuaVbC1CeFpzjFr6aYp9wuCPcxJkjwlIBPi/AUQ+Upg4g8E5So6sc4ATbz3GhO1VxMsX12AGnr63wnrdlSYQNrDMWdtfClNX2i9OYvR1kp1ziM6jcxkeAVPcY5r3ePjwPn799lO8ef0ajx49Eq/V+W+85xA6bZYyIfEeOUet41/A+x5S498hhAHeBUzTjLN3b3B2dlYOMqcVB+M4YVj0ePLkMYgcPv30U4CAH/3kQ+zyGc62V2IAVDCi+v3cuMzlNASKtypqcO2eqjlvORCtRW3V1JbXJVUVI9UIbwFe0jljriQXTloWpYp4Vu8rr6mwNpk8KqN0ybMqDXHaIsb9hP1uBJixWi8lHeAOD/jDdMbd1si8aUAPEdJGOSwpht53WHQDhr7HEHrJ/0Lysw5VsEjW6Dcb9JvX7QjfjL4Z9lwOjVaF0l4rEqSupDD2OzGiw0IQr6DNiOyezCEBqNRfU9aDyUlVwAyvDowwz++tMu6vrnC222OfHH7zdoX9rMcJMU6XE5Y+YR+B19cLEHEN5b/l6n0SxyZLdYaJKTnd4+S0IZVyPRII7A+dPlmfMq3tPJtTwsbRuDHOJtOsby0aDVajH/qAeYxFoTPNGaFT1KnrYDK9w9Bjs1ri/r0jbBZLad7UBcwpYUwRSYm6nOSz4hwhVZYR0SK4lJUIqmil9xj6XjtHMnb7GUcnAUdHHZhiKZWTZ2m2LNvT4OBZRchsRt+tEWfG+VvG6ekTLBeQ/D975CROytt3e3z91Rd49+4MR0dH+PjjD/Hq1WssFh2WK0FJt7sLOLdHv8y43s8lFRoC8P4PBhwSYEmRgQBC7bpXfq7KlESShhLYPCE33e1qt0U7Y6sDSIB4UVl4D0VNExkEMdAxMfZxxHba4Wp3Lf3onYq0pYxxHDX9EnC5PcP90x9i/myCSwNWizUut+f1vhtEycjNTqvHQvBFha+kH0gidIauOf1f1omz2SKyfh+yJzMY0xxLt0SrYmlL+0zL49uu743RJxDSnND3op3OJFKF85ixvwLGXcbJ6YB796WG0VFzkBDp4SLRVIaU9E0pYoozpjiVwXfZSd09M4KbMM7X6MIVNosF7j84xddfP8fp6Sn6vi/3dtfVDx3iLP2cpZSkBzAgqKyvIxH0IfLY7Sb89tNP0HUBJyfHTYQkm+T4+Bir5arUw19eXSDliOVyiXF3AauX9eTBjkUQpMDF9mHy99qq9DZED9QDpbaF1AXnqKQ/7NDq+u5A0a/tt12+u3y+RfYEBK1SUMNuX2Md8ST6S+XzjEmd1EgUsY2+w2I5FBixzaE3q+cOm18RgBYyJACcRP8w+ICh6zEMYvA7Jx3R2rr8m/N/GHF992X5/RKhGbapTplrERNAy36UyNY0PspZIiLv2sMJzb3UXGQR6XEODgwPp+RDlVLNCc4U20B4sBIFt2ebC+wjY44OEYxNH8v9v1iO+NXbk1uQbDXMdQp6F0XOOCVM0yzGVitsQBpZNdGN01pzkPY9MIe0Xdvt90FEnmTcsn5XroZcK0lYx9/ytETSpGmeZnF2i/gUSUlncKDMCN2Ao80K69USy9USfd/DO8KcM/bzjJkjkjrXkhYTqWpyDjFLJIssana9tlcNwWM59JDtneGI8eDhgJgImWfkdBudqs51u57M4Cuz3fcYxwFn7y7x8sUbeB9wdLRB6AL2uxH7vejvex+wWi3xJ3/6czx6fIRXr95it1/h8y++wsXFFcgx3rx5hYePO4SuMtANMqkZFhtL0THx1JfqFefqHi1r36RolX9SatSBg0CjphqbKhBuRsEGgklJwhFzytjNe+xnhfYhjrTvJICYp4hxN+LaEfohAGFC3/fYXk44Wt7D9f6yjKfvPDx82U8E6D7SFNOBMScVSFISH2pX0fp8DOuMWE6jgmrYugRyTAAZX8yBsjxfzn8D4H0wMO9mEBO6pdRUx5ix3zG2F4zNasB7H2ywXIYKCxbomrQcL5eBTSmXdpYxRW1uYlGUelFM8G7CdrwGXA+wx+Zog7N3F3jx4gXee++ZqKI5f+chv1quARBevz7Ho8fHcH2vcNoC3vWaVyRcb7f43e8/x8npCZ49ewyQ9MIGmUcs9dpz2iLlAOdkg372+RdYrQaJsrlG12KY1FtuQwIcMpwBNfxqbAhVJKWtZ7ZnExWyXKJtOzAPIO0DOBb1e1xt62uQHTMXcY6kynqkEV6cRblsGmetyU9FQAXgUk+/WPQYln1DorzNUmjJii3y0UYmNULRY4Qh2u+s3bGKsVeiXuP5fxt5sr2+yyG4Se4DKkRYSGuoJKSSTtHJF7QEhXx4MAYlD1X/bVoM5ZB2Di5Lr28pEa0MayKCd4wucBGMYZaINBPjveMZi/4Sf/XqCHO6+QyoyAozSjc7Fua8ybhavpW1usN5V8SfDtMyFVHKbeWGwBrFIMn64rJ25inq6yR1JBC+tFqVVJKsM04Z4ySyzuQcFsu+VGSEQbokLlaDyLkSMOUEjhnTPGM/z9I/oawJxpy0WiXpGo4MysAQBgQnJcV9L1rwMSc5n5SNn1lIy+QOYf0a9dYFTLBSXlb0oIPjU/zqV7+VwOHkGM+ePcNuu0OMEfdOT7FcLtEPHsNA6BeMzFcYp5e4OL/C4yenONps8ObdO+Sc8OTpGqtNBGNsvvHQ6YAaZQLApTUtlbVsVzX0olya0gzL6eubS1WKjaP8t7qPlie3PcGscHgCchSeyn4eMecIdocRe2bGNM3FeZ5jwuX0Fsenx7g4u8Cj+/fw8vyLgv4a5+ImZmjrjJnhM8N1HpmT6GOYqh7XrirtGXBwNKvz7LylkfT80XSlC3J68qwVC39TjH7nOvRdh0AB8w7YXmQQe5zc73B6OqAPh3nA4nUxa/MO+aEYFi6epuWFuIkcEicQE6Y4S+MXeCATjlYe9x8d4+XXL3B0vMHR5ljYl99A5ltvNvjs919gt7uPZ0+fous7MDyYHJAJ4zThs8++wGa1xgcfvI/ME6Z5iylKb2lHAifL53fwvkdwC9y7d4LdbofPP/sKm3uhdBJ0IIFDWzi3WXA1g4RaCqUSqKZ+dlcjE4vKzeCCIYI5/obxI8nIV/U93Wwm8pOyfm89vMUBE9JejBnTOKniXkScZkSFXwHAd5VNvVwtJAfbqq3ZYmm2ZiHtNWmOJrgvP7GN6ZTkFY3olpJWjvhSKvRNa/SbtOaNbVwPbr71+8PI/OZ7Vf3MnDZzcBT2HwZBTq4uJhyfDt94j4d8A5l70mhFSg8FZgazKOOaw6erSKLjXCpdmGvDnyebiKPhDH/9eo0326HMcImqdXyn7EsZnGMpe5pG0bIIwQOO0JnB9/KsdX7atVaf6ZvIk6yoCLEc7s4bxEyQWva6Tg3m3+1GTNOsokso7+v6oA17dBw8xLBMk6h/qiQyaV7Xzh5xTDLmWQ/qyOicF56I77Bc9IJ0kPAq5NxJisJJK3G2cWyWzc3Iv1TFkDhTi/4Zfv3XL7DbjvjjP/4jvHz1EvdOT/Gzn/5ExzIhpp2q9F1gP+3AnJCTx26/x8PHEaGf8OTJGkRJJHxzLGdp63vYfrIpyJwgXbAyMiWFxDv9XqlZF+Mo/0sq4lUcf5Yy7Or0ouh2lD0EQy6lrHGOEXNKiBngTJjShHGeJZ+ucxtjwn43YtxN2iynRuDb6RpHy/s4f3eBgB6BvGqaNGdZgzBZs7Kyr/UsNAKfRfpRU3Wguv8Kr6SdTbI/Cc7JuvXFMdfjK0unxSnOt9Z6e30vjL7zDvdPTwEGtpcZ+yvGYu1xcn9A1xNAUnYHyAL03hevv5RMFLhF/l4621G7gDUXY5EOtA563gL62mV3jGEV8NVXX+LHP17CsUNAV/JtKSWM44jz83NcXFzgJz/5Mba7LX77u8+LYRB0QCRmN5sNPvzwQxAxUhwxx2ukuEXKEZbDAZGQ+3yP5BcIYYXHT05BPuLLL79Gt0jolj0yJSTlLFiUVjr/6fPdOiDt8FdjbAQaNO/zWvOatEY1dAFdd5twZRF8NWq6yFX5rR7U8qfkWAWuTyS9r8fdVCB8Bmo9LGo7zWHRY328EqY11UMWN7bSbQegGqKbVzlE5QVgiNLhOE8qranyml7IhjdJZn8oY/+un998761/g0r+vjoIdhiIbv/pvQGvX+2wPuoRwrffi30HkRl8URfstfuedxXKBBeAQI5sdUKYjVyrZKMcsQoZf+fJBc7HgMupwxg77GeP7eyxnR0yE2IWtnpKSSNxSd10fafMd2i+1BWX9SZ+Y45cSXE0TupNh4pIG6p0vij4mbZDSuJkjrsJey3/nLRr5LCwbo4q/MUoEq4pJyEAJ6ntt1SUcw6OD41X1pr/GJOUlTqHoe/RhYBhGNB1Xanjl14aWchaaIjCOg/FWeWKfEibJgemLCJAYYmhv4+vv9jj+fPX+Ft//Ed4/OQhnHf44osvMQw9jo43ovSXJqQ0IVsZNBOmMSKnGc5tMatxccRIbA1ydAaKE1sd7na3MSeVDpe0as5SXgjSpj2mMpdlPZW5ZQlA2vVuAmpOic72vsyiATCnhP08Yz/HwgWY5hlzTtIeeZJ53V7vCzG4X/QIfSjNlkwUSoIU1lSZlvKxEJfhdA8ot4N1fTlFe4umvj6HcUi8b9GOO9JSZCFqO69oJlycbU4OKUfVkPjm63th9IPzGGiJN6/3AAKevN+hW6BGAaxGn6KoyRcAAFoTSURBVKHkEnnsZHK1SXIriesBVQhmGrlmttyKAE0G7djhmCBwzRwTlpsjvHp+htdvXuHB/QcAO0zTFm/evMH5+TlijAhdwONHD/Dg4T089g+19KcxdFly4kPfA5QxR4nwY9wL3KWLykjJ7CbEPEoNf5rgXYfNccAznOCrL16DJyCsBJ7tCZhzrDlg4KDzIL7BJtTNVT1sa2NqbHkxCLUtrwW3LclPCHoV/i9fq4vbWnPOU0ScI3bbEf0g1QpJGyiBqrNh7zW53GExYLkapOGNSfuaV3HwbN8QeVv0f/P5IQClNffMnDFOoxB1WNs1ZyG/EdV0yHdd32TU73IWbhstOpy7W5/J2G0j3r3dY7UKd8L733JnIDh4YgQXgEDw7A/voUEoABxE+TNnxDTrfWcZFwZOhoj7S4Z3sVS6MBOmpI2EmAr7Oms07oI1bLoxpsW6WNSlB2i9PUUguBhyM/Ss+20cZynPirGszRQzpv2E3fUe0zQXpUdyhKHrsFwt4L2T7nqoa9o4QuYc1G6PGo2yU26KnDvWvQ8AXKCi2rgIPbouKALHyjOaJb2oeXKBlQkHDmkzLM55BL+Cd2s4WmCegevLiN+9fIcXz1/iwx9+gA8+eAoAePToIVJM+N3vP8Mf/dHPQE0K8PIy4vpqwjQztteiShjzBMqznH1ZInRuoOq7V1N1ubkgUVlxhflWugqK4JT35Fwrf/Q/phVhBnOOGTFlTKqXEFkRl3nGGCMYGXNM0q0wZVxd70CEIt9tdlQqJhhxnJFjRu/60vLYe4dFv6gOXoyILIRMiy3I1ZJRI79S1pSqrmFzCoozpP9xpdNjM2LVWyprXDYf6x4kcCawiw1qeff1vTD6KQGvnot+9OmDHhlJhS6qnrFE5pByOEjEzSSHQWQhihTvPMkkWgckthq25oRLzMgpwpPDhEmFTNQz7QjrowW++PxLLBYLnL39Cm/fnuH09ATvvf8Mw9AhBACUkfI1Mks5Xt/1IATIYs9q5PYCs8VrTPMVUh7F8y1ytrKBMpPkBVOEixOkxS8wDAlP31vixfOE7ZnHcNKD3CReZxLjxuXMaKNeLjvLDk3AovWaAgEAYhHCiXNCr68RNAVl8wIsrYH19wJ11QUrzyKH+qTKZ/aZKWUslkPJkTmtuhA51IR+0WOxFBg0dF76YTt3cAiW+UN91sMDSuPGb7GJlupxmpdNlME5ws8zchKNfiICsrULvvFs3/CZ5Q6+xfjffh/qeLjb32F58cuLCc+/usbp/R73HiwOpGm/6yJSJURlTRMRghKWDkESBde1FXGGkGgpJ5iuespOco0FkhQypDUgAQO9zypyI+SupGIp8NaAhgDrVtkYOvPpuMyfuW0KuGobUiv/s/HJOcsaU+Qo54x+6IqzOe4nzHOS7oh9p2MtzZq6phTLELqUs3RT02gUaPgWRlhTwxanhP1uEkfDiXNKCit2LggRmIBEjBzF8DASevKgoOJAOiZMh46XpTqCX2LRvYfXr7f44vMvcXV1hWmacHx8jJ/85GN89KNnyHkP53o45/H02ROcX1zixfOXePrefcQ448XX53j37hJHxwPW6w4nx0u8e3eNz3+3xdGxx7B0GAbS8wwwqWpq14YZJVs3aNZOmT9zFuvy0hahMK4HFFmV6FohcM11SwCRMMaE63HCdhpVZM2Ek7T0OmdMY8R+t0dKMv+L5SAoJapzyGDEKSLPGZ4d1sMJzt+OGBYDvCOs+kFSizkh+IgxTlLtrAa/7jN5QHFmuaJOFoMQtdtI3tGUIYoJMy2MJnBp/FwGJCLJAJwhwN98fS+MPjPjhx+foO8dEmXkWQy+1fYCDAchFhWvi6R0JyWD4mbMWQ1+Et1rq53MJdJntC0dBc40ZamsE0TI7HA0PAA5xl/9xS+xOdrgF7/4Y6xWS6Q0YYpXmKLIVmYV0vEuCIGPhImZclQRnhEx7ZGiRPFZCS2HZRooP8uckJDg8qT3l+G6jNNHHb763YzL54TuxMENBAGiCfnmeLb+eAONAgJdUfOaGBPAXIhNMsa+GPDaDrchUZHUsBsBxuYwZzH4o0ZY8ySEwH4QUlTOrBoCUqqWFJbdHC3F0HutjXdWm20z1Zwwd62fG8b+NhPaNqvE+jFn6XHPBFDGmIRnsFgMIt4U2HRyvjWfXCJ5G2PlBJhhaJ2tg05zBd045IqU3+l6fftmj7M3ezx5tsT6qCtS1BJQaHqHuVlB7RjIa8zQBQTVd5dIufQj4OoMWW4xafTFrG2r1XWux5b8nyeRLfY+gFWN0aEqFoIJFAnJ5aLZQODD2eEmapSBPZw31NK70paXRM552s8Y97OuU4Fuo3eYpxlxSkhR1tcwdKKnP0V5SJ2nQhDVG6rCT+qI2/da9ApGku0iaYNxEmIkMggeOWaEvpc8fq8teiHNe3KO6B0he4C5IS9Sa2Dr5VyH7ZXHn3/y17i4uMbJyQk+/vgjPHp8H8MiI/Me+/E1nAvwbgnvezjX4f33H+GTX3+KbmB89dVXYB7x8Y9OsVr2il5lHJ14nJ9vcXkx4vLlhHlKWCwd3vtwKLP9bQhVIZ02YW77ejHs9jn6XhKDv58iphgBEIJzCI7gkzhcMSZs5wkX2700ziGtzNDmUTYX427E9eWukAFTF8r8T6NwL0RSN2mVzgKb7h4+O/stPvr4BwDvse5XiDlhnKfiXDpS0TYup/ThOlX5atthzCZCZkTMA0+6XeBFGZnoBrSma55BYJ8AYnT07Wb9e2H0+95jueiQOB0eljZAWnPsqfY3t5Iz60A2p4gpiYzmbIz9nMtn3lzE0gZR/54ZcFLywxODPBC7NVZHA96+fomf/uynWK6WyDliTjtM8yWm+VrbSQoJy1pdOlJCCwuhJaYRQJZ/ly5zXKIb6ctsRsSOVzYnGYDkKM9eT+gWwHLlcPnWg7cd+CjqOOAQe0P9rHYdsuaqoGzlpLAlkcOwGADSKF8PQ+tmWFrXqmUQSNqIYArhRcY8zZjGCfM0F+KgV+h6fz2K4dfOY4B0s1uuBgxalmdEtkrq4jpGesjYRix/ts4TNREk6vPX19rYsDZAispmnwEKAvVbeRt5eByG1SaiU4xAZsCJspodGsYetu8q7z0otztci14doJL+SBlXlzPO34344KNjLBb+4H2mnGaOmXEvkhFauda928+C98jZgSgdlFcxoGWMfBCBmNL7AW8G1eh678VB8kFUxnTuyHfIYIzTBMQtiAhzjNKwRkekzll1Su9CRQqkb7X+vvJqbH1ZCahUfDTlnzonwTtplBIz9vtJ75vgFtXoWzrDO1+coaz8AKkG4pIrjkTISSoBiAlpikiO4DtxVhfLAf1igO8cmFjIZmlGjgnDMMD30qTHe+35cIfBjzPh7O2Ml1+/wn4/48/+7Bd48t49pLjFNL/Ddr9D1va5QgDt4f0Sjjp0Q4/T+0v85pNPce9+h8dPN3COkfJc6uf70OH+vTVOTxfIHPH1V9eYp6Rwtt1FQzAr81IVIOt+as1ccwiROa/qSKaEKSVc7XbYzTMcicEPJPK0MWecXVzharsXkq2mGgr/R4MKELC93OHqcisSvH3AtJ9KGmmeaj58GHos+gGPHjzG9mqGc4TT+2vs87lwLZIvfB6R4yXMcUYiKKHRzhs5j1q/1JT4nK9r1tC7dkTa98jQ3XSm5H+ZM/JiDzcDyN8O530vjL5ELHZgWbTkCrxMJBKIZnwK05Urec9K9OYknnVMkp/JzSFyM1Nomd8MiUCZMogiopsxpx06EinWL7/8Eg8e3AdRrT2NUXpbp6Sd8mAEPiMYSqctgfJRjIJ9OwrULMbUEhFV2cnkYoHrq4jrqxlHj4HsZwwPJow7022WUjdqFpc5Sy0b1RacCx6aWgWXJjnStx4QQ8xc294SoGSnanCKE6HGICvMNk0z4qylUeqJMIB5nIv0qeVRfXDSmWzRluTJYiDLV8g/UJGZNpa9a07vQgIY7dtkWWmJDMm6I3Zgr8S+SaI30kMZqNG7PbN590w1xxyUXJq0xXAb2Vt0zqhOkK2B1pDHKKSxcZ/x9s2IZ+9vsF51jcDHbdShVYss+f7mNU4VEeW7AVNRK98LIHsTHlGIluRwTZyRkIpDagQUi04dOZD5CuTQhU7K43ICZWAkUUmLOQqznlyJ2mqUZNUZtihR9o81HGLoGlSHCsygvivvszbMpVRUa/VJvzPPNUIbFh2W6yVWmyWIRJe/CPo4B2IpBWQWCd3sCON+EgPtHBwDUwJ6L+1xE0clvgasl0ts1ms4ku6gcxQdDwDoGBj6IE16gi9rqsU94pzx7m3E+buM46MnSOk1Hj95hEdPNtjuXiDGHZgngCKYI/TQgnTguwZRB6KABw8d7j24B0BekzkhM0lgAvkz+A4pi9zz7ppx/2HXrC2uAYNhbQRY46jqDPDB2rb/kkY0hhrNMWIfI3bTjOtxj/0kksguC/8HGdjt9ri4uAY5Qr8eSuWQVYLklOECkKJyLFTim1kcAwbQ+65UADlH2KxW2GzWePbwI3z+67c4Pj5B6Gek7Qyw7Jehl5JNSgSeGrExolLmbWNgzjYAsLtxFjXO0XfB8xb4mQ0T5zZrqsN9Y5WQXd8Lo8+QxeG9l3aSqExuMaYinRucltUcHP7mWZIaf63R51xKkW4BLnzj3SytDUOBTxlZN9fmaAXmjBfPX+LZe08QXAdHQT1sjRQsF9qwnWszBSMUVs13FPhQUQLvIeI64igYQ1XIJA7UMfoVsNsmhI2UmNEiaRtsUuenGvaDaJcsnrODnsuutc00jXMhuJBziNOMeZae1VZL2toag1mNMDXuJ2yvdtJBL+ZCghr3EwBp47lcL9DpgbdQOdSgilfQxyh5+vbvoMPphr28vrZ8ABp042BtlCVSfs7NOiDHYAft0yB5w+CaxjjN9xbjjyqzafleKzsq38HVWWgNdkmdNJ9tyE+cM9682uP+gwWOjoZygLaOR51LKDmqkazlw8EqEr/QtaCRf9lfJT2gfBZNmcUkhNg5paZrIldNA0gJoIeDd9K3oA/SS94RIQcp05ziDAIpe5/EIc9RnUpFQICiTJizoGHkLCJWdTQj2pn3AmvN7ApUb+I8oQtlmUuEJk7+sOixPlphWPQAM6Yp6RqV73dO8sI5Sg01R8kLB3ishoU4oIkx+K6SUJlFKpwcVqslgvflMCcw+uDRkUMXPJYLNTClPFMWUoyM87OIszcz+sHh4x89BPF9fPnFCzx9+hDTfI5pPheDr6ihRaAWAEkZ3STRPFsqxdaWooccAfJFEdLWYT8Q3ryekDlgvQ7wASU0NQNfzg79REcNgoa7r5QzdtOE7TRhO4643o/YjyPmGMvZwUqWnMYZc4rCE9Fqh64LBi7K65hLDp+AQrocVGshdL7scUfy7w+efoj9hcPl5RX+5M9+huv9m0LMFA0I1WjIHp33iFnkwWF8snaDogYZB+mMXAmQ5efcvN48YxyezfYyQ7cBiKz8d1zfD6OvcKToigOZGMEHJO02FBR2c645RFlgJtEzl58LoUYYxcGrychNhrvAMI1HapcdomQbJIExgRl4+uwxvv7ya2yO1livFwh+Ae8HId4ZWQVCOIk5CUSkhp9hIhO6edrn1qXiklPRDmH+G4HRmdEH0J1IBYN1DLSIs9Vdt6iWD79EH6/miw1B4ZyR1XMuXaNyLUtJKZVWt5mh2vcaiWl5k+Xvd9f70rJUGM/y52K1wGojkVW/6Irionnjdm+31oQ9i8HK3ES1zYFTpg+3of/yWU0uuESCToyeGUxrj8k+Y55ndM4jI8PD34KfmbnIbprR5FyNmHEHwMDr1zscH/dYLLsDo21ITmG46+H97s2ExTLgwcNVWZ83R+fgXgDtKVHH8q4KAX3DgRNS7t3uiVkrYERPXJQfjRBb5W2lBNCj8wGUJbffhVD4Nma8p/0ETtLvwjspWUOuqZqUElJq1rL+z5QHzajaHBVkSRuxzJPwd6xahDPDB6dKfxUZZMh6tZ/FmAqjXxjfhH4QFj9YjH4XPHoXEHqHQRsdWZGhle8xZ3TeK0pGCKFHzoJGUCIsuwHBC7rTBV+MlD0LGLi+Tnj9UiokHj0dcHy0wNHmMX71V6+xWAw4PhmwG79EylsAuaBHNbRsF4icW4A5o8I3KOOGRjypzHnE46cdzs4Y795EvH0949GTHqv1oSgZMw72QXHMuTrPcgLJ+MwxYzuOuNztcHZ5je04YpzmojYXUwZH0T2Q7osRPngMi17EjByhGzpdq/r9jcCV8YQsiDBkwaq1GMDJ8Qmenf4Iv/xHn+Hp08fg/hrn128FObLeDvnQkTantgRGzbliaeWDqBF0e8+xjXGVjL5ZdVOjfXmfc8LNuhlg3XV9L4w+oR6ARFL2wpB2o5wl1+adx83RkIIk6Vzk4RDIIZI4DzFb1yQUKIW5DnK7eGtUUG8oc0LGjJQA7wkPH97Hbz/9LT7+0Q/hQ4BzPZB2qr2spR85Ys4i/RtzEj5BBkpOutyNTTrk3+aMAKVulPWAPogsDxAEXYpNJGheY4XH9ZvK7/SntjG4LUHR12UTuxF41xOVvFroAgBxAlKSiH63lTrZWUtmpnEu87g5XuPewxOsNkvpO04amTX5bTuwbkH33EQSSqgKweBqNIdOE80LbFPOwNaDNkfHuqoRV4g+c0aKBO+1/IiTNO9ogAY7WyUdopCiOmfee2i6UbTGWdaMICmM519d4/0fHGEY6nYtAYRF/Tnj/N0eMWY8fbYpTY5aY3jXdcAeBg4On5uOiqUlAJTo/XDIBW0So2/iRVIO2zpeQVsRkxU26/NIG+uIaZ6x243Y7vdwQWR4uZBlxUFh55FdRkoqOgM64JMwM9IsLXqDpkusQdM4TYhTxDRqydmc1KABzoXanVFr8HPOyJ4BKyON1VGIMaLvhJfgMoFThgdhETocL5dY9J2iYFKBwNaa1znMUwZnh3lHmCPA2RxIia6JCCenhOFIdC+8q+nJODPevplxeRFx737AyWmH0HVYL57g9csZz5+/xEcffwhye0zzNZhnrW03pw22CW6sB0MSvO7x3PyPQJQhsL+tDdlXDx72OD1lnJ3NePH1hEdPOhwdhyYybQImOzOb32V1xmLKGGPEbppwPY64ut7icrvFrPXyTp2wVEjacuaRc1isF1gse/jOV6Ge4qSyrhGHvpc0hZVOd31FdgQpAoZugZ/84E/x/IszOOfw+P1jfH3xK1UHlH4UhhLVNCiXPe6IkKmqnhbj35zVzX9AZS4E4ZNzFwLMlMmRPdY6Eva6W3bpW67vhdGHGkDrdEQgeO0TTh4qU0klQmgjdtNK73yHOSXRp/cN8UhhHIsQiBq52sbgHHh0BDAyUp6RGdhNl7j/8BHmOOHTT3+Lp+8/gA+xGPvECZETxjhjTjOmFBWmT4eTW76tbN2ygex+W6ZwBODJF1fBjL0ZfIMtbRnagpV/td9Zx6Cc82pokuo/l056jBKtgaweuulEpqVRcY6Yx7nkogB7LWNY9lhtlrj38ATrzbJIsR7M+F2LuwzVoeFyztWUQjHqh971gYFvPs502lstbB153ZSmdMbIBn3628ayHdvMudRm+ybnWJm81bg+frLC119e4dWLLZ6+tyn9xu2yXPP11YyLswmPn63RD76B3fGtRv+uun2755tG/eb7UvN8+kWFGJu4pqcyS3rKVP10NJDmpCVu1g8iY44ztvs9tuMOCYwuaPMsANCy2xy57IKcuJTHZThQ1m7i6gy1RL04RxHZmWZMe1H5E6OuB7N2HixIVUzYz2PRpjA1RqdNn+YpYtH3WC4XWPQ9oIHG0HmsFgvc26ykqgSSW+YsZZ67a8Z2C6To0fcO/cLh+JTQ9Zpi5AzPhP014+I84voq4fSew+ZI9t+0Tzh7JxD30/cHrFfSvGa5eIrnX0b88pef4uTkCO+9f4Jxeo55GlWcZyiIUJ1rGSqCNbsxQStChgjusNbSt4YNOGwGAwA+EO4/6BBnxsVZxNFxONhTNw2dLVCJ7KXefYoJuxixm0bspgm7aSoOGemxm2PVySdyWLhBIvb1okS6sn++eW3bBxpM7700yFkugb7r8dGjn2N65/Hm9Uv87I9+hDf7L0RyHdD0nUisO1vPzVeRGWzGjT1UI/hyDzfGQm8MFiY0ODMsSispTDJHhcv5yvhuIbDvhdE/zIcofEZOlJO8h/U5vjkW1uGIFW7rQwdywBj18IrSlankeRpJ19YEa7Bc1nPOLEQNn7G575HzDrvpDCcPltjPW7x48TXuP9LyvaQ5StZIP82llW/KqTHwkL8VYpo+M0udbuk13qw/eUWU1+i9GrmkNfgHsL19OuOwKx3X1rctK5qZNY/U3CWpcA6qMpqJ+EDzgQyI7rnpo0MY3d1Rj4dPTrE+WqIfeh37+mB3kVwOnZdq82swo+IuqJwIe3FxUBpPuXVurFqgtE1VaJg0EsqZIWqwNQpz3ox7QmKZI4PQjbjYcgccuaL/bQdCMcae8PjpGl99cYXXr7Z4/GRdIEqD9ecp4/XLHe49XGK97g6i9287AO76HVElux2+hqrgkvtm9MBmojifXJ/zoC9BZsxxBvkeQEaeJsQs9c7jPCEiolt4kHbPRJKeDuJoilyzAzAMHZhDmTNbZ6zWTESeJlG9m2aMOyPPSimo8X9lbgHnhZvivUOcoiKFBN8JiZRA8ExwvYNbE7ogfIRV3xe54vWyF2dAYWNbv2PMOH+XMU+Eew8CVuuAvvdwTuZyigkpMzry8ERYrQjrY4fdNuPqMuHd2wgHwHlgcxRwer9DCARHAUP3BF99PuGTX/8Wq/UaJ6cLTPElxvlKasmD9aevUW+dPgIhyP9MZ4BF+94Mvu3lansODX6ZfwbizAidK45/WY3qWDvUPcYs8xpTwjyrTkOKGKMEP+xUKMcrSQ2E3HNxALz3hbPRNpm6tSh1juMscrvzJJ0JvffCtA8eDoT1coX37v0IuF7hyy++wI9+8hHScI63b18ouiUVSbO1WPdtxF8DT0DXYWzO1oIUt300DImoc1EOrrL/2jO/Oaib61bK5luu74XRPyRFyMLy4u7JhHCFOttoNGXJvxLJ5nUguEQFZix5RD6cmAPDY+OskJ1tkAwGHCMsMvbpAvFqhA8d+iPJgV+P54h5QsxziYxSSphVETAqzNvOIJfvbrw/gnBGzGXnw1fLvrsjitXFR6UiwN7fRPNAgahNU7/NlYMEBrUyNYGus5KUkh4ShpIAotoln5vmRi/fCVHLq7DOyelG+kM3T1odmcpuvf1U8gYRKzlwvUu9ePuhOecSBRrxUQx53bgNtFEcIadta52y0Z0XMpq0Etb1k2JBkSRPKbBh6c5mazFX49i2h5U+6yrz7IHHT5f48vMrrFYBR8dDM4fA86+usF53uHdvccMB/g9+Gd8izhlzzJjnjHmM2O8TYpTubItFQDc49L1HCIQQHGLM2O0nbHcTxpRAS+ghX+/HIkRoDbaD5M8zhMQq6z4K0dRZm2Uu85RSQo4Z3hHCIIppmVgIoOaIJuGZgCXaE111gfINmhfCpCsowbgfNf3j4Ttt2KXSuERAp3X6fQhCCIZwEDrvwSlhvVzi+Gijap8OvX6GlVISO1xfJbx+FeED4+l7Pdab7nBhix62pBq99KhgZvSBMJwGPHgQEGcpKxRDL8bBO4+he4LPf7fDb37ze3z8ox/i3v0lvv76c0xzjxQn+CC9ClrXuJocAlEAwYNZygsZCcwRjNScb4ql2HlhZ5N4EWVfXV9ljPuM9z8c6nlkrWTLPvMydxAnOmp6pusCkAk+pWLbLGCQquhWUls+3voSlDXPFREoh4HuP0sjWirRuEFEwitZdAt88OAniOcDfv+7L/DBD95HfzLh89e/KyqtmQWJiUqa7iggsPEXqHAOwFVA6SZRL6eMmE0JtRp3IaDaPdf54TJhdr5zCTBbVNCe/85zsbm+F0YfqOVpheGsME/JXTWX5Ga1VlZFYrzzABMCMnzWHshKymjWtP5Zoxf5PPseM3AJKUXMJPXaKe1AaYc8kUrIMgArA6ptFmOB+ysMX+/fJroNY6F231T1buZ7av7/5vNXWFYch4NyrfblZIZAmeX6rAelXk6blRBBRNfkeMmGBkC87H7oS31qVknNrutKjb3pq5O3krUb0WS74Mv91X8RoCqLh1G+wWHVWamTaa2EWWF8kRrOGvGkKkJDShBTRULnlADqgOBDzf+yNFdpBUmZxemYOWIaJy1xFFRJHCpxMoxhXlAVVw17P3is1h0uL2ccHQ/l5y9fXCOljIePjxSRyM2x+IdfzIzddsbZ2Yiry0mMpncIHWG5CLh3f4Gu80hZXre7jjg/G4VBbYiFA1xguIWiMrqHMlXjkVNCAmmPecmbx5yQiQDt3Ccqcw4OAs1PcSryy0wMeHEWPBGmOZZ8f4qSNpnHGdZp0dbPrLX38xwVyZIbinPCbjfh/9vee8dZVV59399rl9OmF4aZoQ0zAwgoCiqWkAgqVjASe4lY0MSGvJYkYEyM5uVOTMTokyeJ0SR37iQWjEhUfNURCxYUiDTpbRiGmYHpM2dO2+V6/9jlnMGSVz958sp41ucznM0+e+9zrb2vvda6VvktPZCRKCed+eqtBDXdgS8OhYLoQiOoqQRUHcWWBHM0QuEgkUjQv+deGW1fLEUiBtEeZ74XFKrkFSh+yZ3nBPCS5HzXNBnvqJswqiigB0GQTtQSQiWol7Nvb4Jdu/ZSWFRA7egKOjobSSZTpJI2iuaUDqpu1ZK3whbuOJ3VszMRTcttyyoMvMpaP/jn5p9INcPodgWf53y0paSr0yC/UEMPKD5vlpsL4SVSHxr2cYwl1Vk0mQKRSvrKTPEWJ9LFPDDTHeSUjETL/kml7vhs6e8xUmnURdtdsXuJmZqmkRuKUDVoHD2tFvv37WPI0EryBys0tm13yrf7iXxHyFjYqLaNqUiEdEI+Hq6FPyZBRn6Ne7YifAPIU/CO0e8s4PqvV4Q/J/GMGZkpwPCV/2eF4zJpwCh9wHWHp7uCyUNuDOBbQoZbix8KBtOAG4pAka7CV1QUYbqK3xFsXnMa5zIZsyBDAUth4zQOscAERfEUh9cEws4YigTpgZekrUj/GJGh4g5ReH6ynUiPybd4D1nbf+rqOEPPA74Q6l9eQ9rVLzyNKlxMfdfCdGFRbbcjnu2WaTmrZum3xlVUgWk7tc1ec4tQOIiW4zQW8TuVuWPzRywPvd/pOHl6mN7LIfvdh0zyRIDsl/GtoCjS9yzYigCpOsfZbre3DOXheQWkLV3MgnQtsIXTn9108biNpEFK1R2D0sSP2weDulPK6GalQ7oZETguS4GbVa94gs0RjmpGTL8vatDTnaSquhBdT9fPe5jfnyQIPinhJx43ONDSRyJuUFAQYujwfIJBp4udZ5Bkriby8wPOc3Xx650MehtUG9MySRgp+pKmK6OcVZQlbTccpCCE7UoezzgQ/vNUFAVVaCgynbjnz03HqnegVFOm34BHD2p+Yp3izlPbdrwCltfFzm2aIlyIaFVT/CSr3Lww4ZwQAkHQbUft9W0QbumWpqiEg0ECqkokGCSkaU4PBgGGAb09pmssSExDYiQhEbcJ5+iUlumEws4M9JWUPyNdLAEPttdyEmC9oLCH8icz5j4IFKESCQ6jfk8ve+v3UTa4BE23icXbUBQDVYVYzCK/UPVXk55307SccKeiqug4gEumiyMvkCjC8t8NLxyWOQZvcS8yV/3uvdRUga6LjHCg9J+hny/kGvS4z0u4RqCXI+LNUwfgxnvw6URSL/fHRiKE7YcahfudVw9vGqZfEWKZ6RbKfjg3GCCoa+RHChlRMpaWvT10dHRSXVtFuNCkuWs3COcdxPaQWfEXSbYE07ZRpEAR6Vi647mSeD1C+hlJ3jvqNzBL77dc+ZBenIh+ZaU+iUzZ5q84/z/TgFD6ppnO/PRq5S2vlvSQY6V0Mm79un5X4QO+4tdUDd1WMUwXLxuB5SpoP6FPwVfmvgvcdyfZSMsFbrHSCsOz/jxN5T1wDx3Q+39/WFx35eHVfXp8ZLiLfGvP2y8yJkTGHfiY20dKtyGX4NCv8AyHTCWRoUC8sQoc69TyVxHST/BJ5zvIdCKTaWGkDBclC3/lLJH9lOshd8D1Zki/cqD/gxVpA+kQR4UfRxN8LBnRw+y2LQsh3ax0084wCDylmfnSum471U0CwlVOZjrm6Chexx0djyWcFrG24xEIBQJYlorpxhQ9o8FTqt58FEKQmb5o2zamaZOT69QUJxKmm9VfQCik+2PNLL3L/PRmQGYil5GyaGuN0d2dpKgozLDh+X73Ms/wk25ozAs3eNUH0jVInEWihbQFCNVpqoO7knFltrSl40mRuCVItvtQ03PLmzOO29oZg2nj10HjVkZ4AjJlmggPaVNz6spVVcE0QNMUNC3od0iz3LlmecrMFaSKEITCqtM0x12FBt0yL6dNrvRXp07Zr+PidxSJQiIu6e2ySKWcVZqiCnRVoKkQCCkUD9KdJkeuMvKEuRAiIzdEccrPnBfK91Z6wt6ry0+/CU6FQVgfyu6d3TQ27mf06BryCjT27duLZfUiRJJIrqC7yyInT0V35773rqUMC8O2UYWGrjnvlmmbOCWETl8+KRWCAaXf6jbDuefIJNcQF57hBpQO1jPeO9t/vpr28fbizr50nofnPgdHjJruIsLrpOm92F6oUbiK1UyZvhHoGRSm6WDQq27HRk9OqqqKGnD6J0QiQUpyyqjMq2XPjhYSiSRHjKvFDvVwoHu//74IoYBwQhBCgOryJFxZZx/yfkjSOU9C9dzvntzJvKNpYZUZdrYtZ644iynFyQ+TGYpeZnoS0vLfkxP/igaE0jdSFsl4iFDERLgvtudC9t2z0C9zXXVLvzInlA8YIhQHstfNzJQybSWDO8kzVIvngpfuiyClE2tUD4FD9JRo2nYlQ0F+Ovkr9YzFtj9okTl5Mk1xoN8kyYRySSttrwe457LK/FXXvsbv2+1d3hVYno3jmxiZE9Zzk0rbt1S9+mhFVfymOJGcMJqm+vG1jFhJmryVu7PcTS/Z/4WFm1mB4f9furFz10NiuatBxb0fhmE6rvp+yg9/1eIrDZGGsnVqvW10TcPr5KsKB0sdE3ShoQrVaW0a0NF0zSkbEviVJX5HLvHJho9lOW1Cg0EV07Rp3t9LUUmIvLzAJx7/SfcC95ZZlqSrM057W4xwWKequpBQSOt3nUM9BJZlIVTNn69e+VcmGI5074/q9oOXUpIyIWlLFE1xBbVAkU5oBCHc0tQ0CBU4YRTLE+y4gtp2mqxIK+0m9Vy9Uqr+M1Ld5jjguFoDQUfxp1IuiqKdngNeG2gvc1vTVbSA6j4/Z7xOjbwby1dUJIJkQtLWZiAUiR6yieRLUGx0RSWkaqgSNE2iqC5gkW35c1VKwMYtY8TBsLC9fgZup0bXIPGUTObjdRT+EHbv7KKpqZna2pEMHR6muaUJoVggUljSpKBQIZWyadlvUD4kgK7hNKBBYEhJwkghMdBNw5VDlmMwCh1h2ijB/pn3mesIz/j6JHeyAysLXgKvZwT77yLe6+jJro9NVLwCZV/JW5Z/VjKZQkoH0Mj5ziaZMEgmUgQjgbTscX/CspzSPkVzKmvUoIPoGQwGGJQ3mEHBGrZtakBRFI4YX02CVrp7W51556G6KmkZ7OgP28VOSS9qwPEEeMJJuvNRSJCK0z7XS/DNzBFzbT1XtqYNciEyEWTTd43MTW/R6FeXuDkZn6VMGCBK37YlO7cf4Pjjj6GishLbNmk+sAXLNhhSfiRCKLS176Yv1ubXrvs3NPNCQjg4/c6UpabyKBAqWxvWMnXiLAYVVJAyEmhagM17/8mqrcv7vZGeW91zd8kMN/T04y6hrHAI7295jW371vlIZ4euv71rCARHjpjMuBHHkhvOZ39bPbuaPiIvUkRPXwe7mjd7J+Behn4TI9MwIOMFdd8lbyL5Z/iGTMbLKQVfG38GpQUVKIpKe/cBGlv3sL1hA1K6eRSKM5ltWzpKzvM6CMG5Uy5l1LDxvLfxNVZvWeErfE1obh20Riji4OZ7RornHci8HwEtyITqE6mpGEcokMOO/RtYt2sluaE8jqo+keFltXT3dbB57z/Z2rAWiWTYoBqOHDmZSDCXlJkkluglFIhgWiZvrHseXQ1wytHnEk/28ebaZSSNBJOPmMrYqmMIBSPsad7K6m1vEk304MU9Rgwew+QjphIKRNiw+wM27V2NdAGFjJTh5ywI8EE7IoEQiqYypGwko0dOAiQNjesJBsMMqRiHIgQH2naQTHZ/9hx3QxKqqtDdlQBg0KAcwqEChlUehy0t9ux9D8tOpVf5CAoLhyMQdHTtJRFP0duToqfHiZlWVOYRydH9d6GosIrBpWPojR6k+cBHlJbUUpBXDkKhs3MfhQWVaFqQvY2r6Yu1peeVUBhcWktx4XAQgoPte6hv2ti/DarilNoJWzhQxq7hZdkOpoElnT4XtpQotkJQD3N07fFUlY/Fsk12NW2msXUPRXmD2LHvI9q7DvguVG+V5YBEaQRCAbyVlZOwpRM0AwwuHkJ15Vh2Nm5GQeGkCadiS5t3N7yCHghw8lGnowiFdTvfo7W90cHu0FSCAd03EiwXzU4vsBGqs5pNWTZ2ygI9gO4tEEzh51gEAzoC6WAKuM9Quu1xcyODyc+toKN7L8lUl7+6z4kMonrYVOedcLuA7m9eg2Ho7NrZTnPTQWpqRjB0WISU0YFlGVRWVDGouIjWju1YpkFZuU7bQZOW/SkGVwRQNOd3kQLDkphmioQwXJllE1AdiO2Q6lTjfFpraN9D6T5dD2xI+CtOx3AX8uMn++mcrnfAMyBc6HpXPuN7WGxwsTGc3hy2lE6OhVtRI21JKmWQShkOQJLiJAT6c09KVA9t0XR+U9c0ckIRynNr2bKhnkhOmKraCqJmM7F4dxqF0g2/qVJBtZykTNsrsXZDyUKmJbi3Ws/8lLZ0MT3UdEg0U38LV/Zm3Kt0dcyny4O0rvFku+uVVtPlyZ9GA0LpRyJhnMSrAI88/Dt6e3u5++47SRkxfvfbP9PW1sYP77kDSxoE9BxSqQTdvQdQFI283BJUxUHE6o21YVoWiiIoKaggR1RSX1/P6cdfhBGXzJ07l0ceeYSzzjqLF5e9yD+3r6CiZDgBLUhL5z5iiSjFeYMoyS/HsFK0dDSQNBJoqk5+sISLLryIJUuWkEjFaOlooCivDMsyaO1uJieUS1HuIA72NJMyEhxTczLRZsnsu68hGAxSWlrKI488wpIlS5g6dSoIaO1qprSgAoCWzgbiqRjlhUMJ6CF0NUB7zwF0TScvUkhLZyPReDcBLUhF8QgUodDcsRcpJWVFQ9Dc2HNLxz56Y90IAQU5JWipPK667FqKiooIBoNcdtllXDh1Ds++9UdywnmUlwwlZSXY17wbBAyrqCUUiNCX6GbUsPFceuml/PrRh/lo1z+pqqwFIGUmae1sprSwnHA4TEAL0tbdRFdf+8csf1XVufAb3+GPj/+J+994ECEERx99NAsWLKC5uZl777mX7m5HYd5+++2MGjqBbfvWceTIySz88S9oa2vDtm1OO+00jj32WFasWMFFV55Pfk4RDyz8Jddffz2FkUFOWVMyj6uuvBrbthkzZgz3/uTH/O31R7CxGVJaxfiKk7j1xv8LwzCYN28e40ccz5otb7tlQKbrKXAaDElbEgroSAVQYeTwI/nFzx+hqKiIOTdcTiAQ4WcLFxGJRLjpltl0de8jEMjBNJP0xdrRtADhYD5C0QBJItGCu/ikpztJSWmEvNxSBpWM4n//799SW1vLhIlDQFooqk4i2U0omE/L/iSpVIqqkUewfu+HlJQOoqIighRxTDPqCw1VDZAXGcacOXP4/e9/x8jhX+eBBx5gw4YNSCmZPn06s2fP5pprruGPf/wjG7cuAxxjZHTNN/jH0pdYuvQeAM466ywuu/wi1m9/neK8CAjhvA8HG7AwiQTzGDxoKKaVorWrET0QoTBU6MRkLYsDnfs45ZgLePih/8XatfcCcNFFF3HRRRfx+OOPM2fOd1j69n87GPCKhqrq7GvZTVHJIEKhMO3RZpJmjGAgRHnRMEDQ1FrPZWd81z3/RrqjHSz6xcPous5V11+Koij88bd/xbZtrrrhYraYFiUFg7GMBD2xFjQ9REF+GYqiYVoWTW0NxFJRB3fflmhCoTBvECW5g4jForS17yMvr4BBxcMRwqK9swmh6BTklaLrAQSCnmgLR9ROd8c0h+2761C1AJqqU1F2NA899CumTJlCa2sru3bt4rrrrmHt2nUcPNDGhAljGVyRQ1/ffjQ9QlFhPoMHjebNN9/knHNPZ2f9G6iKRsmYYtpaoxxoaWHI8BLyI/nk5tjkJuJ093WSGykiaSRo6WwgYaRc8CQFHenG+IWf7OpRxvrB9wd6K3RHgWUqPk+xfRxTvt91PIeccJSt4uUTgI/UmUykiOSEfKUuLbsfUBI45X2hiFPd4rnaBY7hoLoLPl1VGVo0kgP7HTlXM6qS3tR+Eqled0HkrOE1p7E9qm2jCtUFnBJIC7z22v4qXIJw4XKlm8ycmWToJe0dGmL1PXDOgCHTgBDCX4gh02f6CzbPg+J/4RgPXwnsfVWDY48bSzgcYuvWrezatYvvfe97RMKDeP311xFCkJdbRnNTF6+/uZJhw4YxdeoMTDPJ2rUbEcJm7969nHfeeeze9z5dva2MGn4sT/z177zzzjskk5cxbdo0rrvuOv83NVXjqum38+abb3KwtZWZ515Nb7KDVFTyxhtvUFBQwCUzb+Z/li/yz5FS8uqrr2IYAS4/Zy779u1DURS2Bj7g1ImzWLVqFUccOZHX1i5h1JCjmP7ts3j11VfJy8ujp6eHWCzGY489RmdnJ8cffzwTjppCXV0dADPPvZruRCudLX0Eg0Hee+89TjvtTKLRKGvWrOG8865k4773OGHM6bz66qvE43EunnkTmqaxatUqgmqQLZu2cN55s6lb9wwHO5uwJfT19TFkyBD/d6+66iq++93vcv43ZqPZIerq6hg+fASnnn0+AS3IG2+8Qf2OeiZPngw4iri0YDBXnnErL7zwAjU1NdiazYxzL2fNmjUUFRTx3nvvceaZ32RT00p2t2zJ7JHDkVXH88Rfn2Tr1q089dRTKIrChx9+iG3bXHrppfzqV79i4sSJJBIJdu3ahSUcA0AgWLduHa+99hqapnHKKacwa9YsPvjgA0455RQ2tGyhr6+PotICdr61hcL8IsacPJpnnnkGIQRXXHEFmzdtoThvEG3dLYwfcSwLvreA22+/ndraWs455xxWrFjB+xvfBKRbOpT2IKHgVoSkcxU2btyIaZrMmzePeDzOihUrqKqqojB/CI0NnaxZs4ZRo0ZxwgmnIITKmjUfkkrFaGtrY+bMmXR3vkIyYSBtOHLc19myeTcr33mFRMJZ+ZeVjKWuro6Ojg5OO+00KgdX8tjvfkJHRwfnn38+p3zjXJYvX87G9XuYNm0aofwEB9p2IKWkOLeCv/3tb8yYMQMhVP7rv+4nHA7z9NNPI6Vk7dq1BAIBqqur+eCDDyirHERv9CBFhUNY9cFann32WZ566imEEMyePZvBgwdz6qlnsHXrVhobGwkEApwz7Rq27FlFVfkEXn75ZcrLyzn769eRTCbZtm0bzY3NWBacf8532LJlC2vXrmXx4sUA9PT0sHPnTn7zm99QUVHBlBNmsGvXLsLhME1NTVw78w6WL19O5/5OLpxxA+t2v8vkI6bxyiuvkEwmuXyG87555x9zzDFs2rSJzs5O7rjjDmzb5s0336S0tJTqynEkumD16tVUV1cz/aSzkVLy4YfrSVkWzc3NnHfetby65gnaew4igZOPPhuSEd555x2qqqqYeeb59Pb28tJLL1FRUcHJJ1+MqgZYvXo18Xic9vY2vvnNC9i9e7c/psmTJ7N7925ycnLYtP4tZs6cSUlJCa2trSQSCV588SVqamq45JJL6erqoru7m5KSWpKJMCKU5IMPPuCxxx4jGAwyffrZ9PT0UFdXR21tLadNOxmkwvbt22lqamLYsGEUF9fwzjvvUFpayqwzr+ep1x8BL8TkJkSqioLilQQjUFXn7fI9g27SobPAd/M53GMdF7edgSTonJuZrOcrTQECJ6yhqe4KW1X9ckzL60zoXUeC7SJ42raNpioEQwHHC6CkG9t4cXIvpKsIhdxgPmFK2NG8jTFHVJGS7RhmAk2ooKZDk14nSMuFkzZsB6LY9IwhV0ylQxGeF8PNV8pI7ksfnVby/YKpfjRDZJyXERL6GGWibfq78C/+GfTZPfgOE5K2IBCEwoIcAC655BIWL17MsmXLmDFjhn/c9u3bqa6uZsWKFTz66O8JBCJcffXVvPvuuyQSCa677jpGDDnGd3BrmoaqqgSDQbq6unjooYf6/e6PfvQj1q9fTygU4qqrrmJw0VCuvvpqRo4c6daFpvzYL8CKFStob29n/fr1/PSnP8UwDH70ox9xytEzqaur47XXXqM35iitWDLKkCFDWLhwIStWrCAcDrtxHpVAIICmadTX11NQUICu61x77bVUllTx6KOP8stf/pLi4mLOP/98nnnmGaSU3HbbbZw87kxuvvlmWlpaMAyD73znOwghuOGGG3jrrbdIJpPMnTuXCSNPdGLzGW6irQ1rWb1zOffccw9PPvkkYTWPK664gsLCQp577jmW/P05nn/+eZYtW8YRRxxBa2urf48AZs+eDcDbb7/NnDlzALj//vv57//+b/Lz8/n2t7/NSePOcGKuXuAQGFw4hMWLF3PnnXfyj5V/4o+v/BxREGfv3r3k5+dTMaKUP7z8M55773F6RBM7Gj/qF2tcvHgxf/jDHygpKaGwsJBHHnmEO++8kwcffJCFCxfy5MuPomoKcaOPdze9ypYtW3j00UcxTZNRo0Y57n0hGFw0lG3btjFx4kR6U+1EIhF6e3tRFR1FURlXfQzHjDqR48d9g8njT+G4cV9jXO2xhMKRdCwPmDFjBsuWLWPx4sVccskl/eZmTU0Nzz77LM899wKqqnP++eezdetWWlpamDdvHkeMmUh3V5KqkdWsXrWBRYsWUVRUxBNPPAFAe3s7iUSCyspKZs+eTSKRQNM0dF0nEAjQ3d1Nb28vQ4cO5brrriMUKMfrmpcTKeGll15i2rRp2LbFc889x7x58/ho28ts2LKM0jKFxuaNTJs2jRdffJHcnBL3vGKeeeYZbr31VvY2rmH33g+47bbb+Pvf/057eztnn302qVSKN998k9/+9neMHn4cl156KTk5Obz++uv8/ve/p729nW9+85tEo1Hq6ur4y1/+Qmlpqf8stm/fTn5+PpqbRBcMBlEUhVtvdQzJkpISvv/977Nt2zZ0Xeeaa67hpPGnc+ONN3Lw4EGSySQ33nijD6QSdCt2AGbNmsXSpUtZsmQJF1xwwcdkxbJly3jyycXoeoiLL76YdevW0dXVxU033cTxR5xGUNMZWTGGrgMpbr75ZoYOHUprayu2bfOtb32LQCDAiy++yG9+8yi2bTNz5kwaGhr46KOPWLRoUb8xKYrCbbfdxnPPPUdpaSlPPfUUW7ZsAeCJJ56gqKiIBx98kLfffpv169ezZMkSgsF8Vq5cycsvv9xPXiUSCb71rW9RUFDAo48+ygvPL6OtrY0ZM2bQ3d2NqqrccMMN1NbWEovFUISCaVkkDYNoMkFPPElvIkk8ZZAwTAyvMsfLbaG/Ejct20kQtCxsb6X/sQCmIEOXZSgnF8RLcVbhuuKUY6qkc7M8REWvwY63+rcsJyE7ENTRg7oLFObG1aX0QbXslIWVsrFSNsW5ZbQd7CYUClFYHCJl9qGrGgE9kP7TAmiKhqaqBHQNzW0B7Xkg/ORsP1fGi5tyyAo8Xd2DIF1G6h7nxeK99rx+4iDpZM+P506kb6LiYqR43gTPw/JZNCCUfl9fnA3rG4i7Ha+mT59OXV0dS5YsYdasWf5xwWCQp556ipaWFt555x0ACgsLmTdvHpdddjHNzc2EgnlIabNz3z+pra2ltraWIyaM/MTfffbZZ+nu7mbt2rVs3bqVnp4ewuEwL7/8MsOGDSMcDmO5WbEAEydO5JuzZjB//nxef/11ampq6OrqItrbxx//+EeuvfZatu5bB8Ca7W/xxBNPMHnyZBYvXsyUKVMAGDp0KFOmTCG3NEBxcTGvvPIKb7zxBuvWrfPHddNNNzFjxgxyc3P5/ve/z5VXXsn+/fsxDINXX32VhoYGtm7dysqVKwEoKiritttu4+qrr6axsZHSgnL8enaXpISu3g5ycnLo7e3ljTfewDRN3n//fYQQPP/88wwePJj169ezfv16JkyY4J9rGAbd3d2cM/NM5s2bR15env/dnXfeybkzzgEgFAj7cTDnR0FTdaLRKLm5ucRTMZDQ3LY3vS/Zh7QlfYledjdvIWUm+j2j3NxcioqKME2TAwcOYIgY06ZN46qrrmL11reIGVE0XXMTDS1CoRBFRUV0d3fT3t5ObigfIUDXAv7LZ1qmL1hVFGqHjqMsUMPat7bTXh/H6gryzze2YbSHGDfyOISajuPNmjWLJUuWUFdXx/Tp0/1xKorCU089RXt7uz83q6qquP7667nxxhvZtGkTg8sq6elJMai0jCVLljB//ny+/o0TufDCCwHIz89n/fr1LF26lI6ODnbt2kVtbS3jxo3jyAnV5ObmsnnzZp577jm6u7vZunUr4WAuiqKg62Ha29spKCgAnAoXTdOwLROkpCd6gL5YG+Xl5ezfvx9NDYIERVH9Z2GYKUwrSW5uLr29vQB87Wtf46yzT+e+++7j+eef5/3336e3t5c1a9Zg2zYvvPACACeffDKzZp3Pddddx4YNGygrK+PVV19FSsktt9zCvffeS1VVFSUlJZw05QSKi4sJBoMsWLCA448/nqVLl9LW1sb69etZt24dPT09vPbaa+zdu5dt27axcuVKKisrKSkp4fTTTyeU4yT7zZw50zdWzznnHP956LrOU089RWtrq/88Kisruemmm7jm2mvYuXMnZUVDyQkGqSgZxtNPP82CBQuoGBbg2Mm17NmzhyFDhnD69CksXLiQ5557DoDx48dz5ZVXcOONN7J+/XpGjBhBSUkJU6d9nZKSEnRd54c//CHjx4/rN48vvPBCTpl6MvPnz2fp0qV8EtXW1jJ06FBOPXUq69evZ8qUKUw79WTuv/9+nnnmGQCmTJnCzG+exahRoxBCUFdXx5gxY9BUHQmYtkXCNIgm4/TE43TFYvTEE8RSKRdHxElY893WwlH4iaRBImWQdFsNexn2nlLz5QjpVa//6a2GBWiq4nQW1FwXvm1jGE75paY77nbTsknGU5iG5eIoOAmyql8F41zXAWayMA2TeCyBmTIJagHyAqW0tbVTXj4Ii5jv8veSNb0GT76HAuF/euOU8uPhCp9B6KeInZPcrzOUc7piy72fduZ+B8/Fy/H4pHMzZUc6cVr+ywz+AeHet22bpv3NdLQ7q2RVVRk9ejRdXV3k5OT4xyxcuJC6ujrq6+uZP38+AIlEwnEPaUEfnU8isSwTIULYtk1JQQWd7V0f+92ioiJuvvlmVFVl7ty55OXl8eKLL7JhwwYWLFjA/fffT1lBJe09BwHHVR4J5TkeAPdBzp49m1/+8pdORmquSnesHYDq8rGgSKafdSqzZs3ikksuYefOnXilLSPLarn88sv52c9+xrBhw5g0aZI/rmAwSCwZJRAIoOu6v19RFAYPHsytt96KEIK5c+f6x3vkZV976HQejR0xkZEVR/DIr/4XU6dOJRQKMWnSJP8auq6Tm5vL0qVLWb58OZdccgmvvfaa/zySySR5kUISiQSxWKzfWDt72/wX/6JTbkACyz98lu5YJ13Rdk488USWL1/OKVNn0NXXTm35Udi2zdatW6koquL4MVMZUjqSvFAR72x6iT0tW/3rn3POOQSDQTZs2MDKlSv5+qknEQ6HCYVC9PR1+fH3wrxSjhx5PKqq8q0LZrFnzx5WrVrFRRddQ1+iF1XRKCwspLOzk+FltbS1tVFaWoopDWxhMXjwYE488UQKCwsJh8Pouk5ZWRmdRoPfSREgJyeHgoICCgsL/dVmNBrl97//PS+++CKrVq3iz3/+sz9f0jW8Tqa6bUkQNqFQiL6+PoKBHKLRKACPP/44Rx55JBdffDHXXnstqVTKny8FeRU89thjjBgxgh//+MfccsstpFIpnEQBiWEmyMvLIxaLIUkwfvx4Vq9ezagxE5HSJjcyGInB+nWbHL7NJKZlkUj0csIJJ7B8+XJuvuV6bGnzP//9FCeeeGJ6zofziUaj6LpOKBTiqKOO8ueNpmn09PQQCoVo7z2Apmk+r0UlhVx97VVcd911HHfccdx7773OPQw5RmMkEvHnTUlJCbfccguKojB37lzC4TDl5eX+73ifHhXmlfjzr7Ky0qnbDjgZ4clkkl/96le8/PLLbNy4kYcffhjAuTeusPfGGHYx98PhMNFolBGR4YRD+SSFcJ5PMJd4PO6/h6FQiFi8ox+fgGNEZfC0bdv2fuPt6+tD18L09fURCoUIBAIkEgki4RK6urr8d9epU9f8+aFrIfr62giFQv78i/Z1ECnJp66ujg8//JB58+bxhz/8gcLcErqi7W7HRyem73REVAhqOsggluok/Ak39m7bNoarWG0pQVWwheK4qwOav4r1cfp9V7hDHsyvA2jklLfpqkpA09BVt9zRslFUQTgY8lfRyYThgOtoTqM0VcusPvHCAW4LZsuJyYfDIQYPqsBIClIpg/KKYmKpBlTX25XpR/e9EzLDhY+jeD3o7rQvwz8pY8MzZlw4dxcWPrNsWHhNucgIAwjvPM+TIv1tL4HSo3QeQNrTIOw0XPqn0YBQ+gCBQMAv1QH46U9/CuAneSmKg7y0aNEi32Xm0bx581AUhVNPPZWunmZs2yaWiHLEmGP54Q9/iGma3HjjjR/7zZtuuolbb72V448/nn379rFw4UInwWv8eCzLYtCgQeypT/gPdP/+/cyfP5/6+nrmzJnDpr2rOffcc5k7dy6PPvooG+tX+dceMXg0c669nqqqKpLJJO3t7YwePZoTTjiBH/7wh1x00UWMHTuWRYsWIYTwX/zPIlVVufjii7nrrrsYP348XV1d3HfffR8/0LdKnc/33nvPDwuUlZWxaNEidF3n8ccf56GHHiIQCDBq1CgCgQAbN25EURSqq6v9yymKwnnnnccVV1xBTk4OkUjkU8e4ZPHz6LrOyIkj6O7r5KP61SxYsIBvf/vbvP322+Tl5bF378P85S9/4f7772fGjBlMmTKFxsZGTjvtNGqOGdzverfffjuGYbB9+3bmzZvH3tYdaTYFfvbv8ME1vPPG+6xZswYhBCtXrmTJkiU0NDRw991385e//IU77riD2bNnU15ezvnnn8/upi0EQjrNHfWsSCxFmgqyx0bRFUKBIAeaNxONdaJnlLoB/PrXvwZg165dgKMIotEoDz74IGvWrKG4uBhwlMwdd9xBT08PF154Ifsad2HbNr29bVx77bXMnTuXqVOn8tprr/GNb3yD0aNH89hjj7F582ZWr14NwIQJE7j55pvp6uriuOOOY9GiRTQ0NPDOO+9w2WWX+auGWKyT0047jXfffZeJx47i5z//Oddddx2TJk1CCEEqleKhhx7i3XffZfr06fT0tmGZJk0HdjJnzhyuuOIKvv+9BnRdZ8+ePTz55JN0dHSwY8cO7rnnHjZv3szNN9/M5MmT+c1vfsMvfvEL8vLyqKys5PTTT3cnXPq5bdq0ifvuu49jjjmGtWvXcvnllwOON+N73/se3/nOd/xjN+9Zy/XXX89tt93GpEmTaGlp4YEHHuCCCy7grrvuYuzYsfT29nLvvfcybNgwbr/9dj/cBPDggw8CzvsJjgFrGAaLFi1i3bp1vjGQSqWYN28eqVSKmTNn0tqxG01RaO3Yy5w5c7j66qs544wzSCQS3HPPPeTn5/OTe3/Kli1bPmZ0ZFJhYSF33XUXN9xwg7+vckhZv2Pq6urIy8vjzTff5OGHH2bIkCH84Ac/QFEU3nrrLS644AIqKirYtm0b8+fP5+6776ahoYGFCx/g/fff98NsAAE9TGtrG/fddx+jRo1C13UKCwsx6lPuc5BulYIDFGRYwnftazgdBIVwYuSGaWIZDuqmrqtoAQ1V84Cn3AS3DH+yp7xEhoyRHvqkm7CmCEFQUwm6pZJCgKY73Qrdqzi5ApqGprsdDN0SW8ty2yS7fTJw+7CEwgFCoSBFuWU07W6nuLgIVU9ip+x0xRU2lgcchPR7loCL1EmGwhefVLKYoZCFZ4R5C0iQrrHkMW57HVRFhrfD84D4KQDpbEhFSf8X3N4bpBP7wAkf/Cv3vfikWsvDjUaOHCkXLFjAkUceyfjx4xFC8I9//IORI6uYNOlYUqkUlmURiUTYvXs3NTU1JBIJCgoKOPPMM3n66afp6Ohg6LBKNmytozfRTdxIMnLIBEYNmUhXVxfFxcVEo1Hy8/Pp6uqiK3EAVdXI00tobGykurqaSCRCe3s7TU1NVFdXs71lHet2vgvAN0++BtUOEI877XTVsO3E7YurOfvss6mrq+Ovyx/CtJ3uaxNGnsjEmins2LEDXdedXISNLzKh+iQCIoxt2+Tm5rJz505KSkpQFIXCwkJ6e3uxhUlj+y6GFNSSlFGSRpz8wCC6kwedVZKh09LSwqhRo/x8hba+/WiKTmG4jObu3by17iU0oXPp6TcS70ui6zoFBQXsb61n+aoXCIfCXHTaHOrr67Ftm+rqaqSU7N69G4CamhoMM0WsL05hYSGxWAwhBE1NTSxYsICnn36a7u5uUjJGU3s9I0rGUlhYyO233878+fNZsXUpndE2pA1DSqo4+4RLaW5uJhqNUltby7ubX6Y4r4xRFRPYvXs3paWlqEF46YMniCWjHD9mGlWlYzEMg2AwSH5+Pi+9t5i+WC9nnXgxIHnhvb9yoKOJVMKgctAwrjznZnbv3o1lWdTU1LBiw0tMqp0CtsLOAxsoyiulMDiYWCxGfnEOz7/7PySMmB83tEyn8kPz+nm7iUCaqnFU9YkMLToCoVl8tGM5IT3A2JrTMFI2ekAibZ36+npqa2sdr0heHmeeeSZ/+9vfiMVilJeXsG3Hu2zfdoCR1UWMGDEeTSmmra2NiooKNzZsc/BgB1JKCgsL0TSNlNFJKFhCNBqluLiYpqYmTNOkpKSEQCDA9j1vYFkpNDVEeekkFixYwIOL/ou2jj0MqzyGhoYGpJRUVVUhpeTKK6/kr3/9K+s+esEVZoKcnGJGV0/h4MFWLMtiyJAhbN7xDoU51dxzzz3cf//9TntcPcGmPR9w6qSLaGhoIJVKUVNT4xodMTY3ruKIYZNQ0f0QQX19PeXl5YiAxUd7VnHK0TPp7OwkNzeXWCxGR6yF5WuWctaJF5OrF7F//35qampobN9FYU4JwtI5cOAAtbW17G/fw8iKMXR3O/HcZDKJ0Cw++GgJuqpx3NjzsS0FiwQhPY89e/ZQU1NDMpkkPz+fM888kyeffJKenh7KK0pZt3UZsVQf0WiMIWVjOWrU19m5cycVFRUomkF+7iD27NnjeHX0GLqWg5FSiKf2kZ87FNNQUBSbnJwC3ysZi8XQA5KOrh0U5Y8lGHS8jZabQFhaWkrCaMIw4xTkjKK5uZkRI0Zg2zYHWvczbMhIOjs7KS4uRkrJnj17KCsrA9GLrhdgGpKW9q0MrRhLb3eMgwcPUlNTw8a9K/mofnU/97GXbCZsp0+CgkAXKpFwCFVR0FwXuqoIwqEAwaBOMKi7GCheg6vMmL5H6ZWr7SJ4eiE2L2kvbph0xeJ0RKN09fQ6BohloalOB8lob8xJ3NNUAsGAA9CUUePmYHBYpBIG2JLcnAj5OXnUlh/Ftk0tlJYUM3iYIBrvcowc28OK8MoRpQ/aJoSCaZkkrRRxI0nKSGJKF1/CTnOX6R1AgmGabpMfBzhIVVX0gFMO6eUt9U9kFN7t6edZAJlhKKXRDm3LMba8JlMetgMC5pw9/59SyuM+SV8OCKVfU1MtF/7XfxGPxVBVjcohlUjbZv/+JoqKCqkaWUXD3gZ6eno49rijSdktGGacY8adw/e//wN+8YtfsGHLK8STvRiWQdIySJhJ4qkEpmUhFI2EEUdVdVJmkqAWImHEAQjqYXKCuUQT3RhWilAgh3Agh75ED4aZ6jdOXdXRVacRRdKMc+HJ3+W73/0u3/72tykdGWbdrvf6Ha8IhdxIIba0iMZ6kNJyM2o1J/HGNsiPFJNKJbCkRcpMoKsBLMvAljYBPUTKSLrjdMYsbSd2HlRD9MS7sWwDXQmRMuPYliQSziGRimOaltsrPICmBrBti3gyhpE0HF4COrqmUVRYChJ6op2gQH64CKEIemKO8glqIY6qPYHGLR0sW7YMRVGYP38+HzWupKltL1KYCFUQDkYYNeQojh19CruaNvHupped8hc7bVHnhPLRNZ1oost5r2yJIlTycwqJJ2P0xRzhYLulPLoa9PHsDSvlv0DhUNgB9TBSJOJJjKRBKBJEICgtKkNRFHrjXe6Lr6DrQSyZQigKkWAEVdHpS3T7yHSWaWc0ExFouqPsvax9zQWryQnloAmFkB4koGkE1ABBPYQiJJqmo2khLCOOFILR1adz1113sXDhfezbvxrDjGNLSdP+HkxDMmx4ProeRFUDmEbcBYWy0bUw3Z0J2tt7GDYi3/Peo6k6lpVCKA6ErmEkkEg0f4VkM7RyAkYySH5BiF317yAlBAMRB27UTFIz4uvE40mi8Qba2uv7IQk66HIBDMMgGu9B0wOMGTaVP/3pT1x9/eWs2voq0XiP2zLaJhLKR6DSHW93MqUVHcNMus2MNFJGCl0LkhvKI56MkTBivjLShE5vbx+RcBipWCSTKZCSvNwCIsEceuPdGIbT4yAcynX3dWHZJiCJBHMI6RoFkVwCGgQ0FU3VwJbEEwbRRIyEIYnk5hFNOLkJF0+7hbvuuov/e+H9vPHhYjDjDlCQrhCNJ0jEk5hJi+K8EvJydFTNJicSJhTKRUoLy0q6sWENTQujK6UcPJBk5449KIrCqFEjKSkLYslOkslOJBJVcbpMegpCVUMkjRjJVMLBM1CcOZMyYoBC8944gwblUFych2kl0VSFUDAX6TbzSqZMDMukO9ZN0kyg6yEUJUBntIO+ZBTLSis/M+W466XlzBFFClQhCAUC5ITDSCRBxWm2lZMbJhTU0bzKFd813V+RZaoaLy7uQBA77m8PktfpOGjSHYvT0ddHV7QX07RIpUxUtz4/kUj6PQzCkZCbwJd2jzvGg02yL4muqhTk5xEKBBleNoZ923vQNI3qMfl0RQ84fRtsyweK8kI4SkY8P2WZJI0kKcvAtE1X4dsONPsnZc65itnJJ0g6Cl9XCYQC6dX+oTn8GUaLr/S9pGY/xyqd3OjJHS9B0OthIiVcf+6Cga30xxxRLRf+7CfYhk40GgME48aNJRQKsX37dlIpg7KyQbS2tqGqKhOPHUU82Ux+fjklhcNo79xLa2cDtpQYvsJPkjCTbn97q39im0y7ogAQ6fhNZsCq34Nzz7Ol7UKNCibVfp2R5WPY3byFdbtX+gl/medn/o6EfnGrj9VmSP8ff2gealzmp6eovFpXMso+hBCYhoMdbxpOJypvv2eF67rud/ny8Mw9bG7btvpZ3IpQiERyOXb0FIaV1dDR3crarSvZ1bgNgGDYCcv4XfUyEmF8+Mo0W97txpv8XnmQaZoOiIeL++8pI08wGCnD7wegaQ62frwvgZFyXG/BUNDpYOauOLwGOpm/qfruRS+pBv/ltiwHlEdxUUYcnHzneFVx2jYHNI2QFiSoBdAVByAkpAUcrH33GXizqLigipycUjq79hKNtYEbQ0wlTRr39ZKXF6BscC5ePFC6Y0omLfbt7aaiMpe8vHQ3Pu/5GVYao97J31DclqEezn8A00ykXYtunNjJNHb6tqdSCQT4AtiWNoZp0hePO0ay5iDOVQ+dRG64kI27V9La3ZRWKLaTfU00jAgZoJv+bPbuo5dT4sFpA37Wtum22A1FQmiqQl9vvB8oiwdz6/HtZUp7r6iuquRGIhTn5BAJBByPjOJopVg8SSJl0memMGwLQzq49KOHHs3wstHs3LeeA+17UFEQEsI5IfoSCZKJFLZlE1I1ivJyCEeChENBPGQ1EOhaBFUU091pU1/fRDwWp7KynGEjikHpJJHqxpbp7oyOonTuv9OFU7rKyS0JI41HrwhBZ5sNtqCsPOS4xDUHXVRRNQQKyaRJLJWkN9aHIQ3XtexAGqcMp6U37lw2DMvtEOgYviqCUEAnGAwScI29sLvSDgUDbrfNQ2vHZUbDKu+9Sb9PmfFxD9LcK7dLmRY9sTjt0Sjd0T5SpunnXKXbYYNpmOTkhdEzQrv+GGyJbVgE9ABBTSeoBakcNJxUdw6N+5o5dvIRHOje5nc19RqeOcNNo2Pa0u3VYpuOgeAaCbaUPhRxJo+eLJZSYhoWiXg6xBvJDX8sXypTpvWzA9wVf2YlhJfVb7kgYI4Mdr5TVK+rKtww8+6BrfSFEK3A3v/gT5YCbf/B3/tP00DmL8vb4UkDmTcY2PxlefvP0wgp5aBP+mJAKP3/NAkh1nyaFTUQaCDzl+Xt8KSBzBsMbP6yvH25aEDU6WcpS1nKUpaylKV/TVmln6UsZSlLWcrSV4SySv+L0e///x7A/2EayPxleTs8aSDzBgObvyxvXyLKxvSzlKUsZSlLWfqKUHaln6UsZSlLWcrSV4SySj9LWcpSlrKUpa8IfeWUvhCiXgixUQixTgixxt13tBBipbv/BSFEvrtfF0L82d2/RQgxP+M6x7r7dwohHhEu+oIQIiiEeNrd/4EQoirjnNlCiB3u32z+zSSEKBRC/F0IsdUd70lCiGIhRJ37m3VCiKKM4+e749wmhDhzoPAmhJguhPiny8M/hRCnfpl5+7z8ZZwzXAgRFULc+WXm7wvMywnu+7jJ5SU0EHgTA0OeXOQ+F1sIcdwhxx828uTz8icOQ5nyqfTxVn8D+w+oB0oP2bcaOMXdvha4392+HHjK3Y6451a5/18FnIQDgPT/AGe7+28CfuduXwo87W4XA7vdzyJ3u+jfzNufgTnudgAoBB4AfuDu+wHwc3d7HLAeCAIjgV2AOkB4mwhUuttHAvszrvOl4+3z8pdxzrPAM8CdX2b+Puez04ANwNHu/0sG0LwcCPJkLDAGeBM4LuPYw0qefAH+DjuZ8ql8/6d+6Mvyxycr/R7SSY3DgM3u9mXACziCqATY7j6oCmBrxvmXAY+6268AJ7nbGg5ak8g8xv3uUeCyfyNf+cAej4+M/duACne7Atjmbs8H5mcc94o7cQ973g45RgDtOMLoS8fbF+UPOB/4BXAvrtL/MvL3BeblOcBfP+E6A4G3w16eZHz/Jv2V4mEjT74If4d896WXKZ/195Vz7+OAGL/qumi8XpYfAee52xfhKH6AvwN9QDPQAPxSStkBDAEaM67Z6O7D/dwHIKU0gW6cF9zf/wnn/DuoGmgF/iSEWCuEeFwIkQMMllI2u+NpBryenZ82noHAWyZdAKyVUib5cvIGn5M/97vvAz855DpfRv4+77MbDUghxCtCiA+FEN8bQLwNBHnyaXQ4yRP4/Pxl0uEgUz6VvopK/2tSyknA2cDNQohv4Lj0bxZC/BPIA7z2eJMBC6jEcVndIYSo5mOdboBPbruQ+d1nnfPvIA2YBPxWSjkRR7j84DOO/yLjPFx4A0AIMR74OeA1X/8y8gafn7+fAA9JKaOH7P8y8vd5edOAKcAV7ucsIcRp/2KchwtvWXmS3v9Fz/l30UCXKZ9KXzmlL6Vscj8PAs8Bk6WUW6WUZ0gpjwWexIlHgRODe1lKabjHvwsch2OZDc247FCgyd1uxPUUCCE0oADoyNz/Cef8O6gRaJRSfuD+/+84k/qAEKLCHU8FcPDQcR4ynoHAG0KIoTjP9yop5a6M63zZePN++/PwdwLwgBCiHpgHLBBC3MKXk78vMi/fklK2SSljwEvu8QOBt4EgTz7r+MNFnni//Xn4O9xkyqfSV0rpCyFyhBB53jZwBvCREMJzmyrAD4Hfuac0AKcKh3KAE3HiN81ArxDiRDdT8yrgH+45zwOz3e0LgdelE7h5BThDCFEknGzeM9x9/xaSUrYA+4QQY9xdpwGbDxnP7EPGeambYToSGAWsGgi8CSEKgWU4McZ3M67zpePti/Anpfy6lLJKSlkF/ApYKKX89ZeRvy8wL18BJgghIq6gPAUnx2Yg8DYQ5Mmn0WEjT74If4ebTPlM+k8lD3wZ/nDiOOvdv03A3e7+23CSarYDPyOd1JeLkx29CWdC3JVxreNwcgF2Ab/OOCfknrMTJ6uzOuOca939O4Fr/g/wdwywBif7eSlOZmgJsBzY4X4WZxx/tzv+bbgZpwOBNxzDrQ9Yl/FX9mXl7Ys8u4zz7qV/9v6Xjr8vMC+vxHnnPgIeGCi8MTDkySyclWoSOAC8knH8YSNPPi9/HIYy5dP+sjC8WcpSlrKUpSx9Regr5d7PUpaylKUsZemrTFmln6UsZSlLWcrSV4SySj9LWcpSlrKUpa8IZZV+lrKUpSxlKUtfEcoq/SxlKUtZylKWviKUVfpZylKWspSlLH1FKKv0s5SlLGUpS1n6itD/C7AOOacquNgdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "i=248\n",
    "rec = overlaps2.loc[i]\n",
    "gdf = gpd.GeoDataFrame([[\"only_nis\", rec.only_nis_geom],\n",
    "                        [\"only_zip\", rec.only_zip_geom],\n",
    "                        [\"common\",   rec.geom]], columns=[\"name\", \"geometry\"])\n",
    "gdf = gdf.set_crs(osm_crs).to_crs(crs)\n",
    "\n",
    "ax = gdf.plot(\"name\", legend=True, figsize=(10,10), alpha=0.5)\n",
    "ax.set_title(f\"{rec.cnis5_2020} - {rec.t_mun_fr} - {rec.main_commune}\")\n",
    "add_basemap(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "id": "ea6cc586",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-06-23T14:17:50.224211Z",
     "start_time": "2021-06-23T14:17:49.543485Z"
    }
   },
   "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>cnis5_2020</th>\n",
       "      <th>t_mun_fr</th>\n",
       "      <th>main_commune</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>overlap_ratio</th>\n",
       "      <th>geom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>MARCHE-EN-FAMENNE</td>\n",
       "      <td>6900</td>\n",
       "      <td>0.012117</td>\n",
       "      <td>POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>HOTTON</td>\n",
       "      <td>6990</td>\n",
       "      <td>0.987869</td>\n",
       "      <td>POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>HOTTON</td>\n",
       "      <td>6990</td>\n",
       "      <td>0.987869</td>\n",
       "      <td>POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>HOTTON</td>\n",
       "      <td>6990</td>\n",
       "      <td>0.987869</td>\n",
       "      <td>POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>83028</td>\n",
       "      <td>Hotton</td>\n",
       "      <td>HOTTON</td>\n",
       "      <td>6990</td>\n",
       "      <td>0.987869</td>\n",
       "      <td>POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   cnis5_2020 t_mun_fr       main_commune zipcode  overlap_ratio  \\\n",
       "0       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "1       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "2       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "3       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "4       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "5       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "6       83028   Hotton  MARCHE-EN-FAMENNE    6900       0.012117   \n",
       "7       83028   Hotton             HOTTON    6990       0.987869   \n",
       "8       83028   Hotton             HOTTON    6990       0.987869   \n",
       "9       83028   Hotton             HOTTON    6990       0.987869   \n",
       "10      83028   Hotton             HOTTON    6990       0.987869   \n",
       "\n",
       "                                                 geom  \n",
       "0   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "1   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "2   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "3   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "4   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "5   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "6   POLYGON Z ((5.37387 50.27889 0.00000, 5.37398 ...  \n",
       "7   POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...  \n",
       "8   POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...  \n",
       "9   POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...  \n",
       "10  POLYGON Z ((5.41258 50.31572 0.00000, 5.41385 ...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 462,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nis = 83028\n",
    "zip_overlaps= get_geo_request(f\"\"\"\n",
    "SELECT cnis5_2020, t_mun_fr, main_commune, zip_bnd.zipcode,\n",
    "\n",
    "ST_Area(ST_Intersection(nis_bnd.geom, zip_bnd.geometry)) / ST_Area(nis_bnd.geom) as overlap_ratio,\n",
    "zip_bnd.geometry as geom\n",
    "\n",
    "FROM {pg_schema}.nis_boundaries nis_bnd\n",
    "JOIN {pg_schema}.zipcodes_boundaries zip_bnd\n",
    "    ON ST_Intersects(nis_bnd.geom, zip_bnd.geometry)\n",
    "JOIN {pg_schema}.zipcodes zip \n",
    "    ON zip.zipcode=zip_bnd.zipcode \n",
    "   \n",
    "WHERE cnis5_2020 = '{nis}'\n",
    "    AND ST_Area(ST_Intersection(nis_bnd.geom, zip_bnd.geometry)) / ST_Area(nis_bnd.geom)  > 0.001\n",
    "ORDER BY overlap_ratio\n",
    "\"\"\")\n",
    "display(zip_overlaps)\n",
    "zip_overlaps.plot(\"zipcode\", legend=True, figsize=(10,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5823dd3a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T11:57:07.673714Z",
     "start_time": "2021-07-08T11:57:07.668933Z"
    }
   },
   "source": [
    "# Tests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d1d1c30c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-08T13:29:55.559196Z",
     "start_time": "2021-07-08T13:29:55.481582Z"
    }
   },
   "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>locality</th>\n",
       "      <th>locality</th>\n",
       "      <th>st_astext</th>\n",
       "      <th>st_distance</th>\n",
       "      <th>dist</th>\n",
       "      <th>st_distance</th>\n",
       "      <th>dist_corrected</th>\n",
       "      <th>st_distancesphere</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Balâtre</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.377856</td>\n",
       "      <td>0.377856</td>\n",
       "      <td>60220.074695</td>\n",
       "      <td>38048.097741</td>\n",
       "      <td>38134.345601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Moustier-Sur-Sambre</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.437830</td>\n",
       "      <td>0.437830</td>\n",
       "      <td>68020.978469</td>\n",
       "      <td>42976.845352</td>\n",
       "      <td>43089.000477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Saint-Martin</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.380737</td>\n",
       "      <td>0.380737</td>\n",
       "      <td>60201.952678</td>\n",
       "      <td>38036.647933</td>\n",
       "      <td>38121.847291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Ham-Sur-Sambre</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.442193</td>\n",
       "      <td>0.442193</td>\n",
       "      <td>70418.685388</td>\n",
       "      <td>44491.758571</td>\n",
       "      <td>44618.069937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Mornimont</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.450833</td>\n",
       "      <td>0.450833</td>\n",
       "      <td>70049.784058</td>\n",
       "      <td>44258.680251</td>\n",
       "      <td>44379.139044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Spy</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.429590</td>\n",
       "      <td>0.429590</td>\n",
       "      <td>65946.306841</td>\n",
       "      <td>41666.031486</td>\n",
       "      <td>41768.067932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Jemeppe-Sur-Sambre</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.416430</td>\n",
       "      <td>0.416430</td>\n",
       "      <td>66630.555134</td>\n",
       "      <td>42098.351540</td>\n",
       "      <td>42209.589491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Auderghem</td>\n",
       "      <td>Onoz</td>\n",
       "      <td>POINT(4.4331389 50.8156571)</td>\n",
       "      <td>0.400612</td>\n",
       "      <td>0.400612</td>\n",
       "      <td>62579.259317</td>\n",
       "      <td>39538.671898</td>\n",
       "      <td>39630.807359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    locality             locality                    st_astext  st_distance  \\\n",
       "0  Auderghem              Balâtre  POINT(4.4331389 50.8156571)     0.377856   \n",
       "1  Auderghem  Moustier-Sur-Sambre  POINT(4.4331389 50.8156571)     0.437830   \n",
       "2  Auderghem         Saint-Martin  POINT(4.4331389 50.8156571)     0.380737   \n",
       "3  Auderghem       Ham-Sur-Sambre  POINT(4.4331389 50.8156571)     0.442193   \n",
       "4  Auderghem            Mornimont  POINT(4.4331389 50.8156571)     0.450833   \n",
       "5  Auderghem                  Spy  POINT(4.4331389 50.8156571)     0.429590   \n",
       "6  Auderghem   Jemeppe-Sur-Sambre  POINT(4.4331389 50.8156571)     0.416430   \n",
       "7  Auderghem                 Onoz  POINT(4.4331389 50.8156571)     0.400612   \n",
       "\n",
       "       dist   st_distance  dist_corrected  st_distancesphere  \n",
       "0  0.377856  60220.074695    38048.097741       38134.345601  \n",
       "1  0.437830  68020.978469    42976.845352       43089.000477  \n",
       "2  0.380737  60201.952678    38036.647933       38121.847291  \n",
       "3  0.442193  70418.685388    44491.758571       44618.069937  \n",
       "4  0.450833  70049.784058    44258.680251       44379.139044  \n",
       "5  0.429590  65946.306841    41666.031486       41768.067932  \n",
       "6  0.416430  66630.555134    42098.351540       42209.589491  \n",
       "7  0.400612  62579.259317    39538.671898       39630.807359  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_request(f\"\"\"\n",
    "\n",
    "SELECT a.locality, b.locality, ST_AsText(a.geometry),\n",
    "    ST_Distance(a.geometry, b.geometry), \n",
    "    a.geometry <-> b.geometry as dist, \n",
    "    ST_Distance(ST_Transform(a.geometry, 3857), ST_Transform(b.geometry, 3857)),\n",
    "    (ST_Transform(a.geometry, 3857) <-> ST_Transform(b.geometry, 3857))*cosd(ST_Y(a.geometry)) as dist_corrected,\n",
    "    ST_DistanceSphere(a.geometry, b.geometry)\n",
    "FROM {pg_schema}.zipcodes_centers a, {pg_schema}.zipcodes_centers b\n",
    "WHERE a.zipcode='1160' and b.zipcode='5190'\n",
    "\"\"\")"
   ]
  }
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