{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The effects of Brexit\n",
    "\n",
    "The aim of this notebook is to estimate the causal impact of Brexit upon the UK's GDP. This will be done using the {term}`synthetic control` approach. As such, it is similar to the policy brief \"What can we know about the cost of Brexit so far?\" {cite:p}`brexit2022policybrief` from the Center for European Reform. That approach did not use Bayesian estimation methods however.\n",
    "\n",
    "I did not use the GDP data from the above report however as it had been scaled in some way that was hard for me to understand how it related to the absolute GDP figures. Instead, GDP data was obtained courtesy of Prof. Dooruj Rambaccussing. Raw data is in units of trillions of USD."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from pymc_extras.prior import Prior\n",
    "\n",
    "import causalpy as cp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "seed = 42"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Australia</th>\n",
       "      <th>Austria</th>\n",
       "      <th>Belgium</th>\n",
       "      <th>Canada</th>\n",
       "      <th>Denmark</th>\n",
       "      <th>Finland</th>\n",
       "      <th>France</th>\n",
       "      <th>Germany</th>\n",
       "      <th>Iceland</th>\n",
       "      <th>Luxemburg</th>\n",
       "      <th>Netherlands</th>\n",
       "      <th>New_Zealand</th>\n",
       "      <th>Norway</th>\n",
       "      <th>Sweden</th>\n",
       "      <th>Switzerland</th>\n",
       "      <th>UK</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>3.84048</td>\n",
       "      <td>0.802836</td>\n",
       "      <td>0.94117</td>\n",
       "      <td>16.93824</td>\n",
       "      <td>4.50096</td>\n",
       "      <td>0.51052</td>\n",
       "      <td>5.05450</td>\n",
       "      <td>6.63471</td>\n",
       "      <td>5.18157</td>\n",
       "      <td>0.114836</td>\n",
       "      <td>1.634391</td>\n",
       "      <td>0.47336</td>\n",
       "      <td>7.78753</td>\n",
       "      <td>10.32220</td>\n",
       "      <td>1.476532</td>\n",
       "      <td>4.61881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-01</th>\n",
       "      <td>3.86954</td>\n",
       "      <td>0.796545</td>\n",
       "      <td>0.94162</td>\n",
       "      <td>16.75340</td>\n",
       "      <td>4.41372</td>\n",
       "      <td>0.50829</td>\n",
       "      <td>5.05375</td>\n",
       "      <td>6.64530</td>\n",
       "      <td>5.16171</td>\n",
       "      <td>0.116259</td>\n",
       "      <td>1.634432</td>\n",
       "      <td>0.47916</td>\n",
       "      <td>7.71903</td>\n",
       "      <td>10.32867</td>\n",
       "      <td>1.485509</td>\n",
       "      <td>4.60431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-07-01</th>\n",
       "      <td>3.88115</td>\n",
       "      <td>0.799937</td>\n",
       "      <td>0.95352</td>\n",
       "      <td>16.82878</td>\n",
       "      <td>4.42898</td>\n",
       "      <td>0.51299</td>\n",
       "      <td>5.06237</td>\n",
       "      <td>6.68237</td>\n",
       "      <td>5.24132</td>\n",
       "      <td>0.118747</td>\n",
       "      <td>1.640982</td>\n",
       "      <td>0.48188</td>\n",
       "      <td>7.72400</td>\n",
       "      <td>10.32328</td>\n",
       "      <td>1.502506</td>\n",
       "      <td>4.60722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-10-01</th>\n",
       "      <td>3.91028</td>\n",
       "      <td>0.803823</td>\n",
       "      <td>0.96117</td>\n",
       "      <td>17.02503</td>\n",
       "      <td>4.43300</td>\n",
       "      <td>0.50903</td>\n",
       "      <td>5.09832</td>\n",
       "      <td>6.73155</td>\n",
       "      <td>5.22482</td>\n",
       "      <td>0.119302</td>\n",
       "      <td>1.650866</td>\n",
       "      <td>0.48805</td>\n",
       "      <td>7.72812</td>\n",
       "      <td>10.37107</td>\n",
       "      <td>1.515139</td>\n",
       "      <td>4.62152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-01</th>\n",
       "      <td>3.92716</td>\n",
       "      <td>0.800510</td>\n",
       "      <td>0.96615</td>\n",
       "      <td>17.23041</td>\n",
       "      <td>4.47128</td>\n",
       "      <td>0.51413</td>\n",
       "      <td>5.11625</td>\n",
       "      <td>6.78621</td>\n",
       "      <td>4.91128</td>\n",
       "      <td>0.121414</td>\n",
       "      <td>1.647748</td>\n",
       "      <td>0.49349</td>\n",
       "      <td>7.87891</td>\n",
       "      <td>10.64833</td>\n",
       "      <td>1.525864</td>\n",
       "      <td>4.65380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Australia   Austria  Belgium    Canada  Denmark  Finland   France  \\\n",
       "Time                                                                            \n",
       "2009-01-01    3.84048  0.802836  0.94117  16.93824  4.50096  0.51052  5.05450   \n",
       "2009-04-01    3.86954  0.796545  0.94162  16.75340  4.41372  0.50829  5.05375   \n",
       "2009-07-01    3.88115  0.799937  0.95352  16.82878  4.42898  0.51299  5.06237   \n",
       "2009-10-01    3.91028  0.803823  0.96117  17.02503  4.43300  0.50903  5.09832   \n",
       "2010-01-01    3.92716  0.800510  0.96615  17.23041  4.47128  0.51413  5.11625   \n",
       "\n",
       "            Germany  Iceland  Luxemburg  Netherlands  New_Zealand   Norway  \\\n",
       "Time                                                                         \n",
       "2009-01-01  6.63471  5.18157   0.114836     1.634391      0.47336  7.78753   \n",
       "2009-04-01  6.64530  5.16171   0.116259     1.634432      0.47916  7.71903   \n",
       "2009-07-01  6.68237  5.24132   0.118747     1.640982      0.48188  7.72400   \n",
       "2009-10-01  6.73155  5.22482   0.119302     1.650866      0.48805  7.72812   \n",
       "2010-01-01  6.78621  4.91128   0.121414     1.647748      0.49349  7.87891   \n",
       "\n",
       "              Sweden  Switzerland       UK  \n",
       "Time                                        \n",
       "2009-01-01  10.32220     1.476532  4.61881  \n",
       "2009-04-01  10.32867     1.485509  4.60431  \n",
       "2009-07-01  10.32328     1.502506  4.60722  \n",
       "2009-10-01  10.37107     1.515139  4.62152  \n",
       "2010-01-01  10.64833     1.525864  4.65380  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = (\n",
    "    cp.load_data(\"brexit\")\n",
    "    .assign(Time=lambda x: pd.to_datetime(x[\"Time\"]))\n",
    "    .set_index(\"Time\")\n",
    "    .loc[lambda x: x.index >= \"2009-01-01\"]\n",
    "    # manual exclusion of some countries\n",
    "    .drop([\"Japan\", \"Italy\", \"US\", \"Spain\", \"Portugal\"], axis=1)\n",
    ")\n",
    "\n",
    "# specify date of the Brexit vote announcement\n",
    "treatment_time = pd.to_datetime(\"2016 June 24\")\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get useful country lists\n",
    "target_country = \"UK\"\n",
    "all_countries = df.columns\n",
    "other_countries = all_countries.difference({target_country})\n",
    "all_countries = list(all_countries)\n",
    "other_countries = list(other_countries)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "az.style.use(\"arviz-white\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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UTCY1MTGhUCg09PeB2RFuAwAAAMCwNZvS7bd7xwBgCFqtlhqNhivI7gxkF8owDFcgbgfcpmnuEb2GO6u2JcLt5arZbGpqaqrrxYixsbFZQ2nLslSpVFSpVFQul7s+bn/nhUJB8XhckUiEyu0RIdwGAAAAAABYBSzLUi6XU7VaHcj+AoGAgsGg6z/9fn/XRfny+bxM0+zau3g1IdxeGer1unPRZSa/36/x8fE5e2PX63XV6/Wuwbbf71cymVQwGJQkNRoNNRoN+f1+xeNxxWIxzoclRrgNAAAAAACwws21YN58fD6fK8S2//tslaiZTEaGYXjCv2KxKNM0lU6nF/QeVoJuVcBU7C4v1WpVuVzO03InGAxqbGxs3gVAK5WKqz93MBhUIpGQtDvc7vZ9t9ttFQoFFYtFRaNRxeNxJwDHcBFuAwAAAMCwJRLS5z7nHQOAAbArtucLtg3DmLUau1/pdFo+n0/FYtE1Xi6XZVmW0un0qgx9WUxyeSuVSioUCp7xcDisbDY77/fVbrdVq9VUr9edsUgkonQ6rXQ6LdM0nXYl3Vr9zGxpEg6HFY/HFQ6HV+VvYbkg3AYAAACAYYtGpXe8Y9SzALBK5fN5TysSwzAUDoddQfZsVacLlUwm5fP5lM/nXeOVSkWmaSqbza66UI9we/kqFAoqlUqe8Wg06txtMB/73LUXoDQMQ6FQyFkw1efzKZFIKB6Pq1arqVwuu6q8Z7LbmwQCAcXjcUWjUc6XISDcBgAAAAAAWKEKhYKn/7VhGBofH591wbxBisfj8vl8njYQtVpNU1NTPVXLriTdejhjtObqNR+Px5VKpXq+yFKpVFxV2+Fw2Lk4NJNhGIpGo4pGo2o2myqXy6pWq55WKNLuBV7z+bwKhYJisZji8ficPb/Rn9Xz1wUAAAAAAGAPUiwWPZWqhmFobGxsSYJtWzQa7VqlXa/XNTk52XURxpWKyu3lxTRNTU1NdQ22U6lUX+1x6vW62u22U4ndarXUbDbVaDTmPIeDwaAymYzWrl3r3M3QjWVZKpfL2rFjh6amplwhOhaOXyAAAAAAAMAKUy6XPf2uDcNQNptVOBxe8vlEIhGNj497gr1ms6ldu3Z17U+8EnVbUBKj0W63NTk56QmJDcNQJpNxFoHsVaVSkWVZajabajabqlararfbMk1TO3funLenvd/vVzKZ1Lp165TJZOZcULJWq2lyclI7duxY0CKw+D1+gQAAAAAAACtIpVLx9LmWdi/yGIlERjCj3UKhUNeAu9VqadeuXU4f45WMyu3lodFoaNeuXWo2m65x+86FWCzW1/5M03QWkrTbjIRCIRmGoWAw6FSI5/P5rq1HOucQi8W0Zs0aTUxMOP26u2m1Wpqampq1bzfmxy8QAAAAAABghahWq8rlcp7xdDrdd6C3EJVKRblcbtaWCsFgUBMTE55e1O12u2sYudIQbo9epVLR5ORk1yr68fHxBd25YFdtVyoVp9VPKBRyAm5buVzu60JNKBRSNpvVunXrlEgkZj1fCLcXju7lAAAAADBs+bz0pje5x/7jP6R0ejTzAbAi1Wq1rsF2KpVSPB4f+vHtYNv+72vWrOnaeiEQCGhiYkKTk5OuENA0TU1OTi55T/BBItweHcuyuvaZl3afc2NjYwteqLFSqajZbGp6elqSnFC723lqt9pJp9NzVmXP5Pf7lUqllEwmValUVC6Xnd+GYRgjveNipSPcBgAAAIBhazSk733POwYAParX65qenva0REgkEn33Fl6ozlCxWq3O2lfY7/c7AffMam074M5msysu0LMsyxNud1aoYzhM09T09HTXOwbC4bCy2eyCLzTU63WnB7b9/dqhdiqVUjQaVaFQcP32Zs6nn0UrDcNQPB5XPB5XvV5Xq9VSOBxecCgP2pIAAAAAAAAsa41GQ1NTU55gOx6PK5VKLckcWq2WpxXDfK0UZmsTYVmWpqenVa1WBz7PYeoMtiUqt5eCXSndLdiOx+MaGxtb1PdQKBSUz+ed/ft8PgUCASUSCY2Pjysej2tiYqJrAF2pVBbcbiccDisejxNsLxK/QAAAAAAAgGWq2Wx2DbZjsZjSS9jaqFarecaazea8i+v5fD6NjY15qrTtgLtcLg90nsPUGW4bhkG4PWS1Wq1rj2vDMJTJZPqqmu6m2Wxqx44dMk3TCahDoZCCwaDWrVvn7DsYDGrNmjVd+9rb4XulUlnwPLBwXBoAAAAAgGGLx6V/+RfvGADModVqaWpqyhOqRiKRJQ22JXWtsrYsS61Wa9bWJDbDMJTNZpXP5z0BYD6fl2maSiaTA53vMNBve2kVi0UVi0XPuN/vVzabXXTf9na7raeeesq5K8G+UGPfEdF5QcYO1EOhkPL5vOvCjmVZzkKr6XSac2MJEW4DAAAAwLDFYtK73z3qWQBYQdrttiYnJ9Vut13jdn/hxVSrLmQus7VdaDQa84bb0u+DQcMwPNXaxWJRlmUtWYuVher8Lggwh8Ou6u92t0AoFFI2m110r3PTNDU1NeX0kbcrwyORiDKZzJx9sGOxmEKhkKanpz2/i2q1qmazqWw229PvAovHrxAAAAAAAGAZmS3YDoVCGhsbW9JgW+reksTWb6/hdDrdtUq7VCopl8vN2+ZklKjcHr5Wq6Vdu3Z1PedisZjGx8cHEmxPTk6qUqk4oXaz2ZTP59OaNWvk8/nmXew0EAhoYmJC8S53YdnvYSW13FnJ+BUCAAAAAAAsE3ZFaWeP4WAwOJJgW+reksQ236KS3SSTya5tVSqViqanp5dtwE24PVz1en3WxRnT6bRT+b8YlmVpampKzWbTCdDb7bYsy1I6nXZC7fnCbWn33QjpdLrrgpaWZSmfz3dtK4TB4lcIAAAAAACwDNjBdme4FwgEND4+PpIwtd1uzxlgt1qtBYV38Xi8a3uVWq22bANBwu3hKZfLXb93n8+n8fHxrhXS/bKD7UajIcuyVK/XJe0+xxOJhLNYpN/v76ulSCQS0Zo1a7r2AK/Vatq5c+eCLgKhN/wKAQAAAAAARszuM9wZgo0y2JbkBIA2wzA8gXS/rUls0Wi0a8Bdr9eVy+UWtM9h6gxeF9seA79fiLFzgUbp960/wuHwQI4zPT3tnM+1Wk2WZcnn8ykcDsvv9/dVtd3J7/drfHxciUTC85jdZsjuLY/BItwGAAAAAAAYoc7gzeb3+zU2NjbSELWzJUkkEvFUtS6mKjUSiXQN72u12rKr3mZBycGyQ99KpeJ5LBKJaGJiYtZFHfthB+gz+3jXajX5fD4lk0lZlqVQKOR8nwsJt6XdF35SqVTX89myLBWLRU1NTXnOIyzO4s8QAAAAAMDc8nnpzDPdY5dfLnXpOQtgz9IteJN+345hEOHeQpmm6QmuI5GIGo2Ga3yhldu2UCik8fFx7dy50zXebreXVYBMW5LBaTQamp6e7hr0JpPJrouOLlQ+n3ddpLFb6aTTaefctQNtn8/Xtb1IP8LhsNasWaNcLue5YFWv17Vz505ls9mBVKSDcBsAAAAAhq/RkL71LffYpZeOZi4AlpXO4E1aHsG2tDuIm9lGwTAMJ5Arl8vO+CD6CQeDQfn9flfY2W63++p9PGyE24NRqVS6tiExDEPZbHbBldPd5PN5T2V4vV5XKpVSIBBQuVx29diORCIDWbTVvuuiVCqpWCy6HjNNU5OTk0okEkomkyNZJHY14VcIAAAAAAAwAoVCwRO8GYahsbGxZRHqdobu4XBYPp/PMzfTNNVqtRZ9vM72K8upfYNlWZ4wlnC7P5ZlKZ/PK5fLzdpfe5DBdqFQcF2EsYXDYQWDQVmWpWazqXA47ATMgzy+YRhKJpOamJjo2lqoVCppcnJyWZ3nKxG/QgAAAAAAgCVWLBZVKpVcY3awvdi2CINgWZanpYId/AUCAU+wu9jWJNLyDre7zYUFJXtnmqampqZmDZsnJiYGekFntt9XNBp17ohoNBqyLMs5r2femTBIoVBIa9as6RqcNxoN7dq1a9n1l19JaEsCAAAAAMMWi0kf/KB3DMAeqVurArslw3Lpw1ur1TwtSWaGc6FQyNUnvNFoKBqNLuqYyznc7gwfDcOgnUSPms2mpqenu1b3x+NxpVKpgX6Wc/2+ZgbejUZDoVDIOe9mVnAPms/nc7UpmfnbarfbqlarisfjQzn2ake4DQAAAADDFo9LF1006lkAGLF2u61CoeBp9yFJmUxmoC0RFqtzgctQKOSq1g4Gg67nrPbKbfptL0ytVtP09HTX/trpdFqxAV/oLZfLKhQKnvFMJiO/3+/0h7fvTJi5cOVS/P4SiYRCoZByuZwr7OcugIUj3AYAAAAAABiySqWiQqHQtf1AOp1edNXzIM3VksTW2Tql2WzKsqxFVb6upHCbMHJulmV1bQ0i7f7sstnswNvv2AtVdspkMopGo67Hms2mDMNwzWGpLi6FQiFNTEyoVCqp0WgoEoksqwtbKw3hNgAAAAAAwJC0Wi3lcjmnYrRTKpVadu0I6vW6J8ztDN86+yNblqVWq7Wovsndwu3FBuaDQuV279rttnK5nOcCibQ72M1mswO/OFCtVpXL5TzjdnW4ZVmuOybq9boikYgMw5BpmgoEAmo0Gmq32zJNU+122/nvfr9fyWRyoD3BfT6fUqnUwPa3JyPcBgAAAAAAGDDLslQqlVQqlTwtGaTfh1uDbsswCN1aknSGkT6fT4FAwNVaodFoDDTclnYHpfYCgKPUWUVOuN1do9HQ9PR016r7WCymdDo98IsVtVqta7CdSqUUjUbVbDZVKpVULped4HpqakqJRELValWWZSmRSMy6qGOz2VS9Xh9KGxUs3uj/OgAAAAAAAKwi9Xpd+Xy+6wJ6khSNRpVOp5dlQGpZlifcnq1lQjAYdL3Hxfbd9vl88vl8rpBxuYTbVG7Pr9tiidLu/trDukOhUqlox44dTpW1HV5Ho1EVi0Wn/3Y+n3funmi1WrIsyzXP+VqkWJbl3IExiIC+1WqpUqmo1WopEokQmi/C6P86rFCbN2/W448/ru3btysajWrdunXasGGD1q1bN+qpAQAAAACAETBNU4VCQZVKpevjgUBA6XRa4XB4iWfWu0ajMW9LElsoFHK1epit9Uo//H6/J9xeDgi3Z2eapvL5fNeFUofVX1uSisWiHn/8cc93E41GFQ6HnfC63W67zs1Wq+WaTyAQ6LlNSqVSUbPZVDab7fuii93Lvlwuu1q21Go1+f3+Zf13YTlbsnC7XC7rvvvu0+bNm7V582bdfffd2rp1q/P4Pvvso1tuuWXB+5+cnHTt++6773bdknDyySfr4x//+GLegkzT1NVXX62rr75aTz75pOdxn8+nF7/4xTrvvPO0YcOGRR0LAAAAwCpSKEh/93fusc98RqLfJrBsmaapZrOpYDDYU5A514KRhmEoHo8rmUwui/7Rc+ms2g4Gg7OGeJ0tSFqtlkzTXFTw6/f7XRXgyzXcZkHJ3VqtlqamprrepRAOh5XNZodyIcCyLD311FNdg+1EIuEa6zynW62W6zl2qOz3++Xz+eT3+51/7ArrmZrNpnbt2qVMJtPTQpDtdluVSkWVSmXW87nZbBJuL9DQw+2vfOUruu666/Twww/P2rtmMd7znvdo06ZNrqB8GKanp3XeeefpF7/4xazPMU1TP/3pT3XHHXfoXe96l04//fShzgkAAADAClGvS1dd5R77138dzVwAzKvRaGhyctJZzNBuGxAKhTzhdKvVUj6f77p4nrS7ujmdTg90Mbph6rUlibQ73DYMw9XeYbEhXbdFJZcDKre97EUcu/WUTyaTSiQSQ7uYUywWu56rncG2XS1tB9eWZSkWiykejztj69atUzgcnnWu4XDY8z5N03T6ds920WpmlXa3z8jm8/l6CsnR3dDD7TvvvFMPPvjg0PZ/yy23qFgsDm3/0u4/zO985zt15513OmOBQEAvfelLdeCBB6pcLmvTpk164IEHnOd/4hOfUDKZ1CmnnDLUuQEAAAAAgMGxe+vaYZRlWapWq6pWq/L7/YrFYopGo/L7/fMuGJlMJofSZ3hYGo2GJ0yORqOzPt8wDAWDQVfLh0ajQbi9ylmWpUKhoHK57HnM5/P1XNG8UHawPFMwGNSaNWucFiN2BbZ9F4AdPlerVSWTSeduBL/fP+9co9GoAoGApqenPRXqpVLJaVNi94u3q7Rn67lvs0PtZDLJnQCLMJKe27FYTIceeqjuvffeWftQLcbExIQOOOAA3XHHHQPZ37/927+5gu2DDjpIl112mfbdd1/X82644QZdeOGFzg/nQx/6kDZs2KD169cPZB4AAAAAAGC4yuXyrKFUu91WsVjU1NSUarWagsFg14rPaDSqVCq14gKrzkrYQCAwb1/hznB7sYtKLsdw2zRNzwWMPTXcbrfbmp6e7tpfPRgMLqgXdb9KpZLnTonx8XGNjY15nlssFl2/T9M0XfPrNYQPBoOamJjo2lu8Xq/rqaeeUigUUrvdnrNKW9p9N0coFFKtVnNalYyNjS37lkXL1dDD7XA4rA0bNujwww/XYYcdpsMPP1wHHnigfD6fTjjhhEWH26lUytmvfYy9995bW7Zs0caNGxc9/23btulrX/uasz0+Pq6vfvWrymaznue+9rWvlWmaeu973ytp9x/0T3/607r00ksXPQ8AAAAAK1g0Kv3DP3jHACwrdng9G9M0VS6XnRC4VqupVCopHA4rEokoEokonU6v2BYD/bQksYVCIVcF72IXlVyu4XanPTHcrtfrmp6e7vp5xGIxpdPprgGtaZoyDGMg4W273VapVHKdZ+FwWMlksutzZ4bgpml6zq9+fqs+n89ZHNPur1+r1VSr1dRqtZze+t3udjAMQ9FoVPF4XIZhaHJy0jm36/W6qtWqYrFYz3PB7w093L744ouHuv/FLELZi8svv9z1g/n7v//7rsG27aSTTtK3vvUtp9L75ptv1v3336+DDz54qPMEAAAAsIwlEvTYBlaAQqHgqbpMJpOq1WoqFosql8ueYM+yLNVqNac3d6vVUrvdXnFV281m01OxPldLEltnL3HTNNVqtRZcvdv5uVmWtehFKherM2D3+Xx7XJVtqVRSoVDwjBuGoXQ63TWYtSzLVek82/P6USgU1Gw2nd+hYRiKxWJdW+F0Wwhy5vN8Pp9CoVDfcwiFQgoEAtqxY4frN2NZltOmJJFIyOfzKRgMOq2MfD6fsxjlMNYl3FPteZeZ+mBZlm666SZnO51O69WvfvW8rzv11FNd2z/4wQ8GPjcAAAAAADA4dvXkTDNDqUAgoHA47AlZA4GAstmsEomE2u22CoWCtm/frsnJSVWr1XlbFCwXnVXbfr+/p0UwA4GA5zNZTGuSbiH2qKu39+R+23Z/627BdiAQ0MTERNfAutlsaufOnapUKrIsywm65+tDPZdGo6Fqteo6vyKRiNMDfybLsjzhdmf1+FyLSHaye+/v2rVLO3fuVLPZnHWh2EajoVqtpnQ6rTVr1igejzvB9uTkpOd8CoVCPV1IQnd7zq9xAe655x5t377d2T7uuON6WhRh48aNrpP75ptvHsr8AAAAAADA4tkL5M1kGIZ8Pp927typer2uQCCgRCKhsbExpVIpRSIRJRIJZTKZrlXKdguH7du3K5/PL7oX9bAtpCWJrbP6dTGtSQzDWHatSfbUcNuuMu48N6Td58fExETXcLdSqWjXrl2eINsOuBfK/o3arUZ8Pt+sVdv1et113liWtaCWJK1Wy7lg1dlr3OfzuarR/X6/EomExsfHFYvFVCgUnAtmcwXb9NtenJEsKLlS3HXXXa7t5z3veT29LhKJ6LnPfa42b94sSXrggQdUKBSUSqUGPkcAAAAAALA4lUrFFT43Gg0ZhtG16tpuw5BOpyVJ1WpVlUpl1opUu093uVxWMBhUNBpVLBZbVgFpq9XyhO/9VJIGg0FXADqIRSVnBpOE20uvUqkon893/Q2kUiklEgnPuB1ez7W+nn2HRL+VyrVaTY1GQ5ZlOb81+66KXlqSdIbbhmHMWcBqmqYKhcK8awUahqHx8XGtXbvWqVKfeczp6WmVy2U1m03PZ2kH23vC+TRMhNtzeOSRR1zbhxxySM+vnRluS9Kjjz6qI488clBTAwAAAAAAAzBzEclWq6VSqSTLspTJZDzP9fv9ngUjE4mEEomEGo2GKpWKarXarP10m82mms2misWiwuGwEonEgnr+DlpnZa7dK7hXne/BDvIWWo263Cu3V1o/9X7YdzHMXCTUZi+o2C0Ubjabmp6e7qntSKFQUCQS6asliF21bVdO+/1+RaNRGYbhOf86F5KU5DlWtxZDtkql4iwYORu7ajwejzvnQzwe1/T0tOviTqvV0uTkpPx+v5LJpPNcgu3BIdyew6OPPurafsYzntHza/fee2/Pvgi3AQAAAABYXorFoprNpsrlshOIZTIZTxgWj8eVTCZnDaNCoZBCoZCzwGSlUvEEbDb7ObVaTePj4z21QB2mbi1J+gmmO4Nwy7LUbDYXHNwvt3C724KSq1G73dbU1FTXyvtQKKRsNts12J+ryjsejysYDCqXy7mOUywWe+5wMPPOCDvcjsfjTvV157nardd953O6tSRptVrK5/Oz/m6l3aF4LBbr+huxe5Db1evNZtMJyU3TVC6XUzKZVDKZpBXJABFuz2Fmv+1AIKA1a9b0/Nq99trLtb1t27aBzQsAAADAClMsShdc4B77+MelZHI08wEgaXeou2PHDtVqNScMi0QirrA2GAwqnU73HNQahqFoNKpoNKpWq+W0LZktoC0UCpqYmBhZ0NVutz09svttGWEvuDmzanc1hdt7QlsSu0d8t2rleDyuVCrlOUfnakNi96O2z6VqteoKjcvlsmKxWNd+9TOZpuncWSHtDreDwaBzQaiXliSd52bn6yzLUqlUcu7a6GQYhlOlPd98DcNw7vrYsmWL6/M0TVPVapVge8AIt+cw88dg3+rQq3g8Puu+AAAAAOxhajXp0kvdYxddRLgNjIhlWSoWi9q6datngTj73+ftNgL95gEzBQIBp1KzXq87bUtmBmjNZlOVSsWTIyyVbi1JFhJKh0IhV4DYaDQW/J4It5dWuVzuutCjHdR2u9gxVxuSYDCobDbrCoLT6bR27tzpnPt2MD4+Pj7n3EqlkvP5t1otmabpqvjuDLfr9bpnTp3fVygUcs6xRqOhXC43azuVaDSqVCrVVyuaRqOhWq2mVCqlQqHgnL+hUEipVEqlUknNZlPZbHbVnUujQLg9h5mBdL+3CHX+DwHhNgAAAAAAo2VZlqrVqorFokqlkqdi2a4kTSQSTtuDQQmHwwqHwzJNU5OTk67WD8Vi0Vkcb6kttiWJrbM1yWIWlewWbi+mh/direZwu9FodA22A4GAstls197r87Uh6VblHQgEFI/HVSqVnLH5FpdstVqu3t+NRkPhcNiZUyAQ8FRSd+ZvwWDQc3EkEonMu2Bkt/76vWg0GpqcnJRlWQoEAspkMk5F+MzPpV6va+fOncpms8ui7/5KRrg9h5m3S/SzkILkDbc7/8cCAAAAAAAsnVqtpkKhoFarJcuyuoZgExMTc/bVHgSfz6dUKqXJyUlnzDRNlUqlnnsQD4ppmp7+wv2GebbOHMSusl3IZ9mtSrbdbs/bEmIYLMta1QtKzmz5YYtEIspkMp7vrp82JN0kk0lVq1VX2FwoFGZd3LFYLHruckgkEs52ZyGqaZqe/C0QCKharXrex44dO2ZdMDKRSCiZTPZ9MWVmsG3z+Xxau3atgsGgp+1Ju93W5OSk0um0YrFYX8fC7xFuzyEcDjs/gH6vOHZe/V3o/zgAAAAAWAUiEenss71jAIau0WioUCi4/j19ZqsDafe/sz/zmc9csoApHA4rEom4grheexAPUmcQaC/QtxCBQECGYXjCyIXsz+fzyefzub6jUYXb3QLQ1VK5XavVPBc3EolE14ssrVZLU1NTPbch6cYwDKXTaU1NTTlj7Xa764WdRqPhCqUty5Lf73ddWOjM2iqViuv8MwzDFVC3221P0N35PjKZTN8FrtLuAtmpqSlPNXskElE2m3V+W9PT065w37Is5XI5BQIBKrgXiHB7DrFYzDnp51optZtutzYBAAAA2EMlk9Ill4x6FsAepdVqqVAoeALcVqvljIVCIcXjcSWTySX/9/ZUKqV6ve7qQVwsFpXNZpdsDoNqSSLtDhKDwaArD7HbSCyE3+/3hNujsFrDbft8m8nuM99pIW1IZhOJRBQOhz2LS0ajUVeoXCgUXK9rNpuu36hhGPO2BI5EImo0Gk47okql0rWy3DAMpVIpxWKxBZ3/vQTb0u6/NxMTE5qenvbkhotZgHVPt/J/jUM080dTrVZnvV2hm5k9gTr3BQAAAAAAhqPdbiuXy2nHjh1dW4SWSiUFAgGl02ml02kFg8Elbwci7a507swKqtWqJ/QalkG2JLF1hnOD7rs9Cqu1JUm1WvV8P52tOOyq4lwu5wlufT6fstms0ul034Fw52ssy3KF2d1+B8Fg0HVRIRQKufbRaDQ8VeWhUEjValW5XE7lclmWZXnO0UgkorVr1y64x36vwbbN7/drfHzc1V5lMXdMgMrtOa1bt05PPvmkpN1Xdnft2qW1a9f29Nqnn37atb3XXnsNfH4AAAAAAGA3u2+1HWJ102w2FYlEXCFuMpkcWWBp9yCeGaAWCgVNTEwM/dgzq8alwQRsne0cFhPUL9dwe7VWbQeDQdfFlkG0IZmNvWjrzDnYi0tGIhHP3AKBgEzT9LQSmqmzatvn8ymfzyuXyzljfr/fOUcXumDkTLMF29FoVJlMZtaw3K4Uj0ajzt0No2i5s1qs/F/kEB144IGu7aeeeqrn13aG2537AgAAAAAAi2dZlsrlsnbs2OFZsM3m8/mUTCYVCoVcYVYgEFA8Hl/K6Xad10ydvYaHpbOqfbZF/frRGW6bptk1HO3Fcgm3O4+7GsLtcrnseV8z716oVCrauXNn1+8uHo9rYmJi0WFsIpHwfMeFQkHFYtFz3Egk4rnIMPNCjGmart+MHZTPDLal399ZEI/HtWbNmkUF27VabUHB9kzBYFDxeJxge5FW/i9yiA444ADX9n333dfzazuf27kvAAAAAACwONVqVTt37lQ+n+/aStQwDCWTSa1du1amaXqCqIW0VBi0botIFgqFWavPB8GyrK79thcrEAh4wt+FtiZZLuH2aqvctu9wmCkcDiscDs/ZhsQwjAW3IenGXlxypmazqR07drjGQqGQ5zMPBAKu30y1WpVlWWq328rn8yoWi/L7/Z5zzw7m0+n0or7HWq2m6enpRQXbGJyV/Yscshe84AWu7V//+tc9va5Wq+n+++93ttevX9+1IT8AAAAAAOifZVmamprS9PR01+pSwzAUi8W0du1aJZNJtdttz9pY9sJ2o2a3KJip3W57AshB6mxJIg0m3Ja8fbcX2pqEcHs4isWi5z2lUimnHW9new9pd4XxmjVrui7GuBidLYIqlYoqlYrrN20vvDpT5++2XC6rUqk4CzWGw2HXPuyLXM94xjMWvWgjwfbyQ937HA477DCtW7dO27dvlyTddtttqtfr8/6P349+9CPX1aGNGzcOdZ4AAAAAlrlSSfrQh9xjH/ygNGNBKQC9KxQKXReLlHYHZqlUylXZmc/nXc/pFiiPkh20zwzxSqWSYrHYUPqBD6MliS0YDLr2P6jKbcuyZJrmkofLq2lByVar5Qmvo9GoWq1W12ptaXe1cyqVGlpoa4fXrVZLtVpNlmWpVCopk8koGo0qEAh4LpDMzOXK5bKnhUokEnHalIRCISUSCSUSiUWfO7MF27FYbFncBbKnWtmXm4bMMAydeOKJznahUNCNN9447+u+/vWvu7Zn7gMAAADAHqhalT75Sfc/S9BTF1iNqtWqpwpb2h1iTUxMaGxszNOyoDMcSyQSy67PbWfY3m3Rv0EYVksSW2dlbLPZXFCLlW5B5Ciqt1dT5XaxWPQsIhqNRpekDcls7MUlZy4E22w2Va/XlUwm1Wg0Zl34tFqtauvWra5g2+/3KxAIqNVqKZlMKp1Oy+/3L/ocr1arBNvL1Mr9RS6RM844w/WH+VOf+pSmp6dnff7111+vO++809neuHGjDj744KHOEQAAAACAPYFdYTqTYRgaGxvTxMSEJ1g1TVOFQsE1Zodpy00wGFQsFnONVSqVBVc+z6bRaHgC20GG252LSlqWtaD3YBjGsmhNsloWlGw2m56FSmOxWNdFWIfVhmQ2oVDI8zm32235fD5PS5JQKCTDMNRqtTQ1NdX1Qo3f71cmk3HO65mB+ELYi1N2C7ZpRTJ6K/MXuYT22msv/dVf/ZWzPTk5qdNOO01btmzxPPeGG27Q+9//fmc7GAzq3HPPXZJ5AgAAAACwmlmW1bVyMp1OzxrOlkolT2g2zBYLi5VMJj1z6wznF6szDAyFQgNtteHz+TxV8St5UcnVUrndeR75fD75fD7PXQ3RaFQTExNLemdDsVhUPB53zS0SiahYLHZtoWP/LejsHR8IBLTPPvt42ux0W5SyV7NVbMfjcWUymQXtE4M19DN169atevnLX971sZl/lLZu3apDDjmk6/OuvPJKHX300V0fu/7663XhhRfOO4/rr79eN9xwQ9fH7rvvvjlfe/7552vz5s3atGmTJOnBBx/UK1/5Sr30pS/VAQccoEqlojvvvFMPPPCA63Uf/OAHtX79+nnnBgAAAGCVC4elv/5r7xiAnuVyOU9IGovFPNXOtlar1XURyUFWKQ+a3+9XIpFwtSOp1+uq1WoDmfewW5LYQqGQq1VEo9FwhZe9GnW4bVmWJ9RcieF2rVbzVEBHo1HPoqWBQGDJK5HttkGhUMjpOx+LxeTz+Zxe+TOD9nA47PTcn/n7jkQimpiYUCQS8fTYX+g5bgfbneLxuNLp9IL2icEberhtWVbPf3xme95cvZlM0+xp//3Mo1MoFNJnP/tZnXvuubrjjjsk7b7q+KMf/ajr8wOBgM4//3ydcsopCzoeAAAAgFUmlZKuvHLUswBWrHK57GmpEAwG5wyY8vm8p1fvclpEcjaJREKVSsWVYRQKBYXD4UWHjs1m05ONDCPc7mxNslIrt7sdb6WF2916t/v9frVaLU/ettTBtmVZroryeDyudrvtnJONRkONRsOpkPb7/Wq32yqVSioUCk5Vvd1qKB6PD6ztTrvd9rRAsuc4iGDbsiyVy2U1Gg1FIpFZL9JhfivrFzlCY2Njuuqqq/S+971Pz3zmM7s+x+fz6Q//8A917bXX6swzz1ziGQIAAAAAsPo0Go2uLRWy2eysQVy1WvVUqsbj8WW3iGQ33UL4VqulSqWy6H13Vm0Hg8GhfCadvc9brZYncOzFqMPtzjkbhrHiwu1qteq5uBAMBj2/j1gs5vnehq1cLru+U7/fr7Vr1zq/62azqWaz6Zy3gUBA09PTyufzzp0BhmEomUwqGo0qEokMrO1O5+Kb0uCC7UajoZ07dzoV6LlczvN9oHeGtZAla/dwlmXp7rvv1mOPPaYdO3YoEolo3bp1OuKII7Ru3bqBHWfffffV1q1btc8++3Tt8Q0AAAAAwGpmmqZ27tzpCTXHxsZmrca0LEs7duyYMzRbCXbt2uXqh+zz+bR27dpFhavbt293fS7JZFLJZHJR8+zGsixt27bNFQ7O9Z3NplaraWpqytn2+/0DzV2W+/EXa7bfgmmaru/G7/drzZo1Sxrcm6apHTt2uC4ghEIhjY+Pa+fOnWo2m5qcnJRlWc7FLGl3H/2ZQbB9Dk9MTMgwDM85nkql+l5AttVqaefOna7PyF48cjHsSvXOdknS7rUDFtK6B0vQlmQ1MgxDGzZs0IYNG0Y9FQAAAAAAVq1cLucJthOJxJwh6UpbRHI2qVRKu3btcrZN01SxWFxw5ehStSSRducmwWDQFc43m82+j9etctuyrCX7Llf6YpKdldG2bouyLvV7KxaLns/X/p2mUinXxRHTNDU5OalIJOIKtsPhsOLxuMbGxmQYxsDO8c6q7UG0NGo0Gsrlcq5e9DZ7AU0szMr6VQIAAAAAgD1CsVjs2mJgrkrjVqvlWSQvHA4rGo0OZY7DFAqFPPOuVCpdw7FedPYsDwQCnt7Yg9TZ4mJm0N2rbu0klrI1SWf4upD2FqNimqbnt2AYRtfwd6mD1W5tdqLRqHPORCIR1wWMVqulyclJV8Wz3+9XKpXS2NiY8710/r0IBAJ9t91pNpue30o8Hl9w+G9ZlvL5vHbt2uX57drterLZ7Io6t5Ybwm0AAAAAALCs1Ov1rovgzdVnW9q98GJnxeUgeuSOSjKZdL3fzgX4+tEZ/A070BzEopI+n88TKi5luN15rJVUud1ZGW1ZVtdK9FH8Prr9Tjsro0OhkAzDcMLhVqvlhM7273p8fNx1ng3iHO+8IODz+fpua2Kze2vPDOUty1KtVlM+n1ez2ZRhGJqenl7wRSvQlgQAAAAAhq9clv71X91j7363RH9NwKPdbmt6eto1ZhiGMpnMnNWNtVrNE26tlEUkZxMIBBSPx12BW61WU71eVzgc7nk/rVbLE54NO9zurNw2TVOtVqvv78PuEW0bZeX2Sgm3u1VGm6bp+f0kk8klrxhuNBpdf6cz59FqtWRZluLxuLZu3apKpaJYLKZWq6VGo6FsNqvx8XHXb6DVankuoPR7jg+qatuyLBWLRdfvtt1uO3+j/H6/67M3TVO1Wm3BIfqebuX+hQcAAACAlaJSkT70IffYO95BuA10sCxL09PTnlAxmUzOGeZ2q2j2+/2rIixKJBKqVCquz6RQKDgL6PWiM7Dz+/2e8HnQ/H6//H6/K4xuNpsLCrdnhpaE2/Pr7Bndbrc950ooFBrJAoadv9NuldF2X+1Wq6VyuSzDMJwguNVqac2aNYrFYq7XdAbmfr+/77Y7nXeL+Hy+vj+jzt7adphfr9dlGIbi8bin7YrkvdMBvSPcBgAAAAAAy0KhUPD0Zo5EIvOG1KVSyVOZnEwmV0wYORefz6dkMql8Pu+M2RWmnQHfbJa6JYktGAy6wuhGo9F3//Nui0oulZUYbndWH1uWpVar5bo4ZN8JsdSq1arn993td1qv19VoNLRr1y6FQiHn4sZc8+48x8PhcF8Lj3arKE8kEj1/5zOrte3WI9Vq1Tlfg8Fg10p5u3d4P3diwI1wGwAAAAAAjFy1WnX1ppV2t+WYL4Rrt9uePrmhUKjn4HcliMViqlQqrgrmYrGoaDQ6b4DXbrcX3a5hoUKhkCswXEjf7eUUbq+ERf86K6Pr9bqnSj+RSCx5u55ud1cEAgHP79SyLFWrVT399NNOG5tgMCjLspTJZJRKpVQul10LUJqm2fWiWD8WU7VtV2vbbUfq9bpz7sxWrR0OhxWPx/sO4eFFuA0AAAAAwxYKSX/+594xAJJ2txrI5XKuMcMwlM1m562czOfzrhYMklb0IpLd2AvuTU5OOmN2qJ9MJud8bWdLEp/PN/SWJLZui0paltVXmLecwu3lXrltB6u2drsty7Jc8w4EAiNp11Mulz3fXSqV8pwLjUZD27Ztc4XViURCpmlqbGzMeX4+n3da83RWXBuG0VcldL1ed31ukncx127swH56erprVXpntbZhGIrFYit+LYDlhk8SAAAAAIYtnZa++c1RzwJYlizL0tTUVNeAer4+tPV6vevidKuxf204HFY4HHaFcKVSSbFYbN6FNmfq1u93WDq/B8uy1Gw2+wrXRxVum6bpOSeXc7htt8WYqVKpeILsTCaz5JXCpml2vbuiW3X1li1bXM/1+/2KxWJat26d60LNzNY8iz3HOz83+5hzqdVq2rZtm0qlkuec7KzWtheGjUajy/ocWqkItwEAAAAAwMjMXHzNFovF5g2XLMty9aGWft+ferVKp9PauXOnE7ralaPZbLbr89vt9qLbNSyGz+dTIBBwfb+LDbcty5JpmkMPCTurtqXlHW5Xq1VX25daraZgMOgKeePx+JJV7c9ULBY9n2e3uysKhYKefvpp11g4HNaznvUsRSIRNZtN17lUKBQ8F3yk/s5xu7/3TIlEYtZwvNFoaMeOHV0vyEm7K+OTyaQCgYAikYjTegTDQ7gNAAAAAABGolwue9pmBIPBntqKlMtlTyieSqWWdQC5WHaP4pm9yavV6qyhZWdFq8/nW/KgLRQKub6nRqPRcy9jafecDcNwBYntdnvJw217HstRZ9W2ZVmq1+tKpVLOmN/vH8mFn1arpUql4hqLRqOeqv56va7f/e53niroZz/72c4ipOl02tWaxzRNTU5Ous6NfluS9FK1bS8QmcvlNDU15fm7Yx83Ho87bUdisRitR5YInzIAAAAAAFhyjUbDs8Ccz+dTNpudN0RsNpueUGq1LSI5m2QyqWq16gpfC4WCJiYmPM/tDLdHsXhdt77b/TAMQz6fzxV6ttvtobee6QxZl/NFk85+1qVSybPYaDqdXvL3YJqmcrmcJ3yeGbpLuwPwJ554wnOha2JiQuPj4852OBxWNBp1Pa8zaA6FQj2/z1qt5qnati8AtFottVotNZtNlctlFYtFT0hvCwQCGhsbUzqd7mmRVwwW4TYAAAAAAFhSpmlqenrac1t/JpOZt9qx3W53bQnQGZitVj6fT4lEwnVhoNFoqFqtOhWu0u7PeJQtSWydFeWtVqvvtiJ+v98Tbg/bSllMsrOfdaPRULvddn3u0Wh0yb97u9K583OMx+OuVjOmaeqpp55SpVJxBdXxeFzPeMYzPEFxKpVSrVbr2hJE6v0ctyxL09PTqtfrarfbarfbzoWUmYvbNptNlUqlrtXa9sW4NWvW0HpkhAi3AQAAAADAkrFDpc6AMpFIzBtMmaapqakpz2tjsdhIegmPSjwe94SBxWLRtZBeZwBoGMZIwu1AIOBpK9JoNPqayygWlVwp4XapVHLmalmWSqWS60KPz+db0gs/pmmqUCh0rXK2L8zYLMvSjh07nOpuu6o/FApp7dq1Xc8Ru71K510ftpmvMU1TrVZL7Xbb85+VSsWzj1Qq5freq9WqyuVy14VFk8mk9tprr5H8puBGuA0AAAAAw1apSJdc4h57xzukPaCFAtCpVCp5FoALh8Pz9gO2LEu5XM7T1iIUCvXUo3s1MQxDyWRS09PTzlir1VK5XHbCw2G0JLEXqDRNU+FwuKeewoZhKBgMuqrIm83migu3O+ewHNjfua1cLisQCLi+l1QqtWRzr9fryuVyXb8fn8+nsbEx10WCqakpp2e2faHG7/dr3bp1CgQCs1ZDz7y4Y7/W7sNeKBScELvboqDS7r8lneF7IBBwXSBrNBquinhpd4udWCymsbExJZNJ2o8sE4TbAAAAADBs5bL0nve4x97yFsJtLAt2VeJSBDX1er3rAm6ZTGbe4xcKBU9ga/e63RNDpmg0qnK57AqNS6WSYrGYDMPwXEBYSIWp3dqkXq+rVqs5x2u32woEAlq3bp0SicS8IXcoFHLNs7NdynyWQ7i9HCu3i8Wi8/ttNpuq1WrKZrPO4+FweEn60FuWpUKh4AraZ4pEIkqn067vsVAoaHJy0gm1W62WfD6fxsfHFYlEFAwGZw3lDcNQOp3Wtm3bVCgUnO8qHo97+nZ302g0PG1G7N+NtPu7LxaL8vl88vv9CgQCikQiikajymQyA+n3bi+0aV/o6WeRVbgRbgMAAAAAsIcqFosqlUpOWDSzZ/OgtdttV6WxtDukymaz81aWlkolT3DWrRJ0T5NKpbRr1y5n2w7lQqHQglqS2K0h6vW66vW6E2zb/zlzn61WS08//bTS6bRT9RoOhxUOhz3fyWIXlRxFuL3cF5RsNptOkGu3I4lEIs5nZf+mh63RaCiXy83akzqVSnkC9nK5rMnJSVcQ3W63lUqlnBYq8/WwDoVCajabTrDdzzk+s2rb7/crHA4rm80qEAjI7/crn88rm826vvNEIjGQau1Wq6VisehqG1Sv1+esVMfcCLcBAAAAANgDzayitvtgm6Y5lApCy7I0NTXlqYZNJpPz9squVque3riGYWhsbKynthirWSgUUjQadYWE5XK5a+uW2cJZO8y2A2zTNF1js7V2kHYHm/ax7EpU+3h22G3/95nsXsi9fn/dwm3LsoZasb/cK7dn/iZqtZpM03SFyMlkcqi/DztQ77wTwxYOh5XJZDzfXa1W09TUlKvlh2VZikQiymazznc6X1BdLBadi3HtdluRSKTrd2QYhvx+v1OB3Wg0FIvFnDH7b4l9vHK57FnwNBKJLLpvud3mpPPuE1ur1SLcXqA9+38FAAAAAGAphELSq17lHQNGxLIs5fN5z3g+n5dpmvP2v+5XoVDwBK7RaNS1uFw3dlVop0wms0ctIDmXVCrlWTyys+3HzKCw3W67KrPtCuWZFdtzBdqdyuWyMpmMa6zRaDhhnmEYCofDajQa8vl8TuDaaDQWHG7b72OY4e1yDrft70na/TmUy2XFYjFnjsFgcKhtLprNZtf+99LuMDmVSnU9frPZ1NTUlIrFouvztSv+7e/T5/PN2fqj2WyqXC7LMAwn0Pf7/U4rE7vv+MwAW/r9ApYzQ+RQKOT8PprNpudCmt02aaHq9XrXdQY6j8HClAtHuA0AAAAAw5ZOS//936OeBeAol8td2whIcoKnQbU0qFarnpYigUBg3v23Wi1NTU25Qltpd5g7zPYpK43f71cikZi1gtb+/PL5vOr1uut7bzabTsX2bK0+DMNw2o7YFeD2fuzK7UajMevFBsuyVKvVVKvVVK/XXSFkOBzuabFDn88nn8/nCkSHGW5blrVsw227v7WtVCrJ5/O5fhPpdHooVe2WZalcLrt6fc8UCoWUyWS6fi/tdltTU1OeOwvi8bhnMcf5Fj8tFAqetjvj4+Pzng+VSsVzntsX8uy7VzrfVyaTWdB3X6vVVCqV5uwvbxiG4vG44vH4slywdKUg3AYAAAAAYA/SbrdnDUJt5XJZlmUtOiSzKzxnsvtszxUYmabZtY1JLBabt9p7T5RIJJzgzrIsV/AsuRcLtR/rDLpnCgQCCgaDCoVCCgaDzmJ6kUhEhmFox44dTkjYarVkWZZTnd0t9LT3aYfo7XZbk5OTarfbCgaDTuVuKBSa9Xzz+/2ecHtYulWuL5fwsVqtOt9rrVZTo9Fw9YKOx+NDuauh1Wopl8t1DWsNw1AikVAikfB8f7VaTblcTvl8XoZhuFroRCIRJZNJz3c5V3uOarXqqYLuZVFTu43KTHbrHGl3YN75e0gkEn21CrEv5JRKpTn7yvt8PifUXi4XTVYywm0AAAAAAPYg3aou4/G4p7q6UqnINE1XH9xeWZalRqOhfD7vOVY6nZ6z5YDdn7szaAqHw0uyQN5KZJqmAoGApqenPQFzPB5Xu91Wo9FQrVbrGmjb1dR2mO3z+Zx+3jMXKbQlk0nnooUdKsZiMY2NjTnBeb1edwV8neGjHYo3m001m02nhYndJiIWi7nOO7/f79rfUofbw+zv3SvLspwLU6ZpqlwuuxYi9Pv9i+4N3U25XPZUS9sCgYCy2WzX37RpmpqenlYul3NC32g06pxryWRSiUTC0yJptkDZNE3Pc+07F3p5D53njP1Z1Wo1z9+/YDDYc3smy7JUrVZVKpVmvWAk7Q61E4mEq4UMFo9wGwAAAACAPUSj0XAW/bPFYjGl02mFQiHlcjlXgGUv/jZfpbUdntrVws1ms2sQFo/HXYveddOtOjQYDC4oZF+t7FDYbvVhf9525bb9nEajIb/f7wnu7J7Gdshoh9fBYNAJtOeqhI1Go54gr1gsKhKJOFXY0u4w0g66O787u8J8ZihqWZbz/Hq9rrGxMeexbotKDku3liTL4dybGdDaCx/OrNoedDuSdrutXC43a7/oRCLhOn6nRqOhYrHo/N2xA/lkMqlUKqVUKuX5rO2WNd109uqWenvP3aq27TsF7Pc4k313SS/7rVQqKpVKc56PdgA/84KNfaGiWq0qmUzO+3cRsyPcBgAAAABgD9FZ9ejz+ZzqxGg0KsMwPH1n6/W6pqamNDY25gTcdmsL+5+5qhVtwWBw3qpSO+yZye/3u469p7KDYjvQ7gz57P69k5OTToW23dfaMAxXmD0zuA4EAopGo4pGoz33sLYXDZyamnLGWq2WqtWqK6Sze0FHo1FnUb5KpeJcAOkMt2eq1Wpqt9tO0DnKcHs5tCQxTdMJaO0qfPv7lORclBiUarXqLDDbKRAI9LSoa7lcVrVadd0xYBiGDMOQZVlKJBLatWuX6zWzVW3bi0jOFIlEenrP9oWAmey/e7lcrmtgPtdvwTRNJ9Sea/HVQCCgRCLh/G2Vfr8A6PT0tHNny44dO/Sc5zyHtQQWiHAbAAAAAIA9gB0qzpRIJFzBXSQS0fj4uKvftb2IXKlUclpczBXodOPz+TQ2NjZnJWSlUvH0AjcMQ2NjY8siXByFmdXZcy1MJ/2+mtvuaR0KhZTNZhWJRBQMBj0tPuzQea4WMXOx9zvznCoWi64gr1M0GpVlWc5/2pXiM6vPZ7IDenvOMw0z3O7c93K4sGIHqTOrkO12HD6fb2Ate+zWH50XmWzxeFypVKqnCvFcLqdWq6VareZ6vR0c5/N5z3ndLdy2LMtzYc4wjJ7e88yLArZIJKJQKKRSqeSpSrdb4sy1L7sKfTbBYFCJRMLpUS/Jab1jB/0z27yYpqlCoUC4vUCE2wAAAAAwbNWqdMUV7rHTT5f4F1ksETs8mSkQCCgej3uea4/v2LHDWXTQDmFKpZLS6XRPYbNhGE4/4FgsNudr6vV61/Bqtl6+q9XMNh724ou9aLfbTs/qiYkJhUIhTyA7s4p6UAsOplIpTU5OuuZRqVS6nlfS7gX87LY4duiXTCaVTCZlmqYmJyddYXmr1XL1k55pqduSjJJd7Sv9vjVJOBx2QuJUKjWQOdqLP862oGYmk+l5gcVWq6Vyuexqg2S3u0kmk/L5fM6iovb5Yvdc71SpVDwheDKZ7Onv0GxV281m03MxzX6PnezfV6VSmXXBVElOH3H7M5q5wKQ9f7sdycw52QtyYmEItwEAAABg2Eol6Zxz3GNveAPhNpbMXL1q2+22Uxk8s8VIKBRStVp1hTntdlv5fF6pVMpz277dxzkUCjn/9FLd2Ww2Pa1QpN2B3SDbLCxXdmWr/R3MFZ51CgaDMk1TrVarazWtz+dTJBJxAu1B9422+2vPrH4tFouexSBnznemVqsl0zTl8/nk8/kUCAQ84batM8i0LMt57aAtp3Dbsizn99FsNlWtVp0WNJKci0eLYV/86uzHb4tGo0qn0319DvbipjM/y0wm4yxWKslZfNSyLMXjcVel88y5dYbQs12Y6/a+OluZ2O13du7c6fmt2fOz2a1QOv8OdgqHw0omk877Mk1T1WpV5XLZ07Kp8w6aUCik8fHxnt4PuiPcBgAAAABgFWu1Wp7Qyl74r1AoeG7Zt9lVjPl83hXQ2AF3NptVPB53guxAINB3eNput10tUGyJRGJVhz3NZlOVSsXpK90rwzAUDoedliClUknVatVzocHuiT1byLwYdqhsh83JZNIVbtuBYrdKVPscmRkUNhoN5yJGMBh0tcOYGQLaizp2XmxZzeG2HWzbFz3s32okEpHf7++5Ncd8x+ismLfZ7U76bZdhh+Uz9xmPxzU2NqZoNOrcRWI/bofH3d5LoVBY0CKSkrr2xE4mk56/adLuvznhcNgJpru1ceoUjUaVSCScizZ2hf1sbUvshTUNw3D6hUciEU1MTMz7XjA7wm0AAAAAAFYxe9Eymx185vN5T1VjJ5/Pp0wmo1wuJ2l3+BgIBBQMBuX3+xWLxXpuU9DJsixNTU15wt1oNDrvwpMrWalU8rSImYvd2sXuE2wYhhqNRtfPzn7+oNu52O0VCoWCisWiWq2WIpGIxsbGnHOh2Ww6IXCpVFIsFvOEwvbCljNbTDSbTSfc7gzpZwaQhmHI5/O53nO73R5K25rlsKCkZVnK5XJOv+pqtapWqyWfz+dUaieTyZ4XAZ1NPp/vGuJGIpGeWxB1KpfLajQarv3aPagTiYR8Pp927drl+pxrtZqq1ari8bgTXNth8EzRaLSnvzkzW7nMfG23i33237SpqSmnknw2hmE4obb92TcaDZXLZdVqtVlfa1/0sSvU7Ys12Wx25G1vVjrCbQAAAAAYtmBQeulLvWPAkNntLmZKJBKq1WpzBtt279tQKKRgMKh169Ypl8u5Qkk7nM5kMn1XdtoVqZ2hWigU6trzdjWwLEuFQmHeCwr2Z29X188ML+1+vaVSqWuI1s9if73Mt1arKZ/Pq1AoqF6vu8LIer2uarWqVCqldrut6elpp72I3+9Xu91WJpOR3++X3+93qrZDoZDrPJr53zuDWtM0Xa1H7P3ahtV3ezksKDlzUUe7l7ldSW23AFrs3Q21Ws0T9NrV4AttdWJXmM8MekOhkHOBRpJisZii0ahyuZzzHPsCydTUlLLZrAzD8PTh9/l8PV/46vyNGIahWCym6elpZ6zVaqlerysajbrGu7Ffby/Ca1mW03pkvsVeA4GAGo2GMpmM67eZSqX2qDUFhoVwGwAAAACGLZORbrtt1LPAHsayLE845Pf75fP5ui7eGA6HXYF2Z0A6Pj6u6elpp5LUPobdD7ifMKxQKLj2I+0OgMbGxgbeRmM5sD+nzvds8/v9TpgdDoe7fgbtdlu5XM5zsUL6fYX9IHqUl8tl5fN55fP5eUO7RqOharWqWCymSCSiWq3m9AC3W2nMDIZ9Pp9arZZKpZJzLrZaLadC2G61MTOUbDabS76o5KjbkuTzeVfobF8QsXvdG4bhCUr7ZZ9PMxmGoTVr1iyqGtxu5zHz3JnZSmfmsdLptHNnid2vul6va2pqSqFQyHPxq9dFJO2LATNFo1GVSiUn0K7Vamq1Ws7ilrOx71CxF8U1TVOlUslZ2HMukUhE8XjcWZi3cz6rufXSUiLcBgAAAABgFSqVSp7wxe6z3amX6mv7FvpcLufqiyxJuVxOpml27bPcqVwue6qXfT6fxsbGVuXt+aZpampqqmtQnEgkFI1G563erNVqzmfcKRQKKZvNLrh1hl1pa1doz9dnuFO5XFYgEFAsFnO1dLAsS5VKxXVO2PPvDOgNw3DCbXvxQLutSavVWtJw27IsT1X8Up6XxWLR9fuwF5KcWeUbj8cXVfFrtzzp1st6McG2ZVkql8tqNpvOeWS31Zl58cs0TTUaDQWDQaXTaRUKBSfclna3YNmxY4dSqZTz2QeDwZ4voHW7s8H+Dc1ctHVmNflMdk/sWCzmtAJqtVpONX233+HM18ZiMcXjcQUCAdXrdc+6BoFAYNG90vF7hNsAAAAAAKwy7XbbE6j4fD5n4baZUqlUz21F7IpRn8/nCagLhYIsy1IymZz19Xabi859jo2NLbp38HLUarU0NTXlqdq0P8f5Pve5WpkYhqFEIqFEItF3BW+r1XIqtO0e2r2wA8ZmsynTNNVut2WaporFojKZjMLhsKs6vVareXpvz2xbYms2m86Y3Q6l1Wopk8m45rYU4Xa3fS5VuF0qlZxw31av15VMJp3w1/7eF6NcLnsuMESj0QW3IrHZ31u9Xnc+x0gkokAg4AqRZx47GAwqk8koEAg4f5vsgDyfzzttWHpdRHJmT+1ms+nMpdlsuv72+f1+z+cYCoWcuxDs79zup915Qa+T3+9XPB53ne92u56ZZv4NxWCsvv/lAAAAAABgD2cHzTZ7IbrOQMUOR/thtxMwDMMToBeLRZmm2bUqsdFodO1rm8lkXFWbq0Wz2dTk5OT/x957h1uSl+XaT+Ww8tqhu6d7aDKSRnIQUIkiIEGQIGCCg4B4FAyo6HfpdwwEBUXF7xxEUETHQwYTcGAYEY6CAwwwIyBhGKZ7uvfeK69VOXx/rH5/XVWrVtipw/De19UX3btXqFWrqpq5f089b2nFRavVWjoULwxD9Hq9UvGsKApardbK+y1NUzGcjwaJ7kZo12o1NJtNUc1QHIqZpikURcGJEyewtbWFKIqE+KYhgVlUVc1J5DKBTQL9Qsvt4vdFgywPm8lkUnpXha7ruffPite9EATBjEBXFOVAksS0CENymbrWqe6IKIp127bRaDTQ6XTguq74+yiK0O/3cezYsZWPdap0IdEOYKbqBoAYbEm1I5Zl5RbY4jjGYDCYWyVE6LouhkRm5fu8dHx2oYI5GFhuMwzDMAzDMAzDMMxtCBr0RyRJgjAMZ1LCtm2vPJytDKoMKAq5yWSCJElyncCUYN5PavxywvM80UWeRVEUtNvtpZUSJDrLhkZaliXSrItIkkQMDByNRnBdd+XKEV3X0Wg0xGDBYmK2Wq0iDENxnEmSJI6zdrs9kzTf2NgQ1Q5xHIthgSTAs9uVFYxRFC2V22maHmhP+8Xo23Zdd+aOBmC6n4sLSPs5X5IkyQ1xJFqt1r4/ZxAECIJAJLcBiLR28e6CotymdHe73cbXvva13N+laQrf9xGG4dzzhtL+w+EQZ86cyf1ddiApUalUxJ0TZYtM9H0sqh+hzux5ono8Hpd+zv2m7plZWG4zDMMwDMMwDMMwzG0EqrEgqDKiKLFN0zyQpCalH4uD6aj+pNVqIU1TdLvdGVFk2/ZtUvRQOrooEDVNQ7vdXtiNTfKxLC1Kifmy6og4joUIJrlIcm3ZUEh6bcMwUK/XV6pLAab9zGEY5uSz4zio1+szSdnxeIxWqyXEdbaCApget+vr6+j3+7k0drb6hFK2ZZ/9ICttLrTcpi7oIvV6vbT7e1nifxGDwWAmsX9QSWKS8HRMyLIMTdNm6j/CMCydBQBM90WtVsttJ6X+O50O2u12blvpekc92MWFNqq7IXRdR7VaxRVXXFF6LCVJInq1y5BlWUjtRcec7/ul6fhmszn3OczeYbnNMAzDMAzDMAxz2HgecPXV+Z89+9lAySArhtkPjuOIFCyJH8MwcqlJGkB4UGlXSvYWE6Ge56HT6YjEbhbDMG6TA9VGo9GM1AKmn3dZOtb3/Rm5S2iaJr4zqlvI/kqSRFSPkNAuS31nkWUZpmmiXq+j0WiUDtZb9vx2u43t7e3ce41Go5nubdd1Ua1WRfK2mMClY1FVVYRhKOQ47YsoikQ9hyzLOQF92HJ7r4M6V8H3/dKEf61WQ7VaxdbWVu7nlmXt+bx1XXdG2pLs3S9hGIrvmypJSFhrmpYT8sU0M1WXRFGE8XgMWZbRbDbR7/fFYEdg+r2Q4KbXowoSALnEOD0+SRKRzjYMA6qqYmNjo/Q7XTS0taxPex5xHM8sVtAwXu7ZPhxYbjMMwzAMwzAMwxw2oxHwkz+Z/9kTn8hymzlQKKUNTMX2aDRCmqY5aUm3/h9kjQMwlW6yLM9Uj5SlhrOi9rZCmqY50ZbFsqxcRUvZc0ejkUi+pmkquqbjOBZSriiR6bE0NM/3/aVCmwb71et11Gq1mYWP3aKqKprNZq5LnWokigyHQ6ytrQGASPVm60iCIICqqpAkCYqiiM8PTOUpJXYVRZmR2wfJhUpuB0FQWtVTrVZRq9VExUeWvVaSRFE0U3tC3e8HcR5ma2gcxxF3AgCYEcJlVR1Afk4ADV0sftd0F0ir1YKiKLnzrXjuJUmCjY2NnFhvNBozCyGU+C47d4HVa4CIsgUq7tk+XFhuMwzDMAzDMAzDMMxtgOFwKETQZDKB7/s5qaooCtbW1g5N1hmGgbW1tdIKEoI6p29LCcYkSdDr9UqFbrVandtrThJ4Z2dHpLHjOBY90rIso1arCdGbfV4URfA8D0EQLOwFliQJuq7DMAyRBt6v0C5iWRbCMMx1Q1PqWpZl8V6UKCfJV5TbWYFNSd5scptQFCX3vIOW28XXO4xjNQzDUrGd7cEvpqxpMONumTfYsNFoHEgqPY5jsa1xHMP3/ZxQrtVq4vdJkswseFHKv1jFQ+dOr9fL/V2apuj1euLzUP2O53moVqswTVP8XXY7LMuaqfRZdLeELMtoNBq7WlAo69k2DOM2Wb90KcFym2EYhmEYhmEYhmEuc8IwFMlDx3Hgui5M0xT1D1QhcZgVC8C05mBtbQ2dTmdGpkmSdEG24UISxzG63W7poMZGoyH6grOEYYjRaITBYIDxeFwqp3VdR61Wy4nVbEK77DmUeFZVFYqiQNM0VKtV2LYN0zQPNSlPSeOsuJRlGb7v5+4cGA6HWF9fF58xm5YNw1DIRzpG6HMuGyp5kBx2cjuKotLzgxLCwFTgFuX2XlPbo9FoRijbtn1gg1wnk4mQ9NS1T9+5LMu5c6BYlyNJEjRNw87OTu41FUVBrVYTdR79fj+3P3zfzyXRx+NxLpHteV6u31pRlFwNElU2FQefEjSTII5jkSjXNA2apom7C4oEQVDas91qtUrfgzk4WG4zDMMwDMMwDMMcNqoKPOABsz9jmAOCRI/ruphMJpAkSUglEkTFnuPDQtM0rK+vo9Pp5MTjhdyGCwGlb4tylfZ3scM6iiKMRiM4joPxeDx3aGSlUhHikXqEfd8X75Md1JeV2YqiiKS2ZVkwTfNQUsc05DEr+egz7+zsiO2k3uxsWjsIAniel1t4ye4f2t6s3KaKFuJyltvzxLZpmrm7LMoWMPYio2mwaBZVVQ+s7z5JkplKkmxauvg9F1PNuq5jMpnMfIf1el3sd6ookSQJjuMgTVPxnv1+H5qmIUkSmKYpzslms5n73rJ910EQoN/vz1S+ANPvul6vQ1EU9Hq90lolSZKgqipUVRXCmx5fTOIXt4M5HPj/TTEMwzAMwzAMwxw2rRbwmc9c7K1gbqO4risGCZLIqlQqQqo0m82ccLoQqKqK9fV1jEYjJEmCSqVywbfhMKFBgGUitN1u5+oj4jjGeDwWifrJZFKavFZVVaRVHccRYk1VVViWJUR2mSwjoU3d54cF9UQnSQJVVbG2tiZkM6VUO52OkHymaaLf7wv5DkyTxKZpCjmeFYJRFAl5SFC9SZIkkGX5gsvtg7rTgFL+xe2lYaPZNHDZ4MfdDs1MkmTuYMODSvGTbM7+OSvhi3UcxQUdWZZn0tOGYcyIfBLcsixjZ2cHURSJ8yOb+HccRyyGDAYD1Go1NBoN6Lo+021fhIZOTiaT0jsxCOq5D8NQfE/D4RBhGArpTV303LN9YWC5zTAMwzAMwzAMwzCXKTQMjaougPNDAwHsujP2IFEUJVcNcFvBdV30+/2ZlCYN6yQJSanW8XgsOqlJmlEimWoZqA+YeqZN05zpBy5CzyPxfdjEcZwT+pRCXl9fF0Jd13XU63VxJ4EkSbAsC8PhUKRvSQpalgVd13Np3iiKxBBBEt9xHEPTNERRBF3XL8vkdpIk6HQ6M2lhXddnBrwmSTIjgfdyDs8bbHhQd09kE9TAVDJLkpTbX9m+7WyHOlEcgipJ0sJUea1WExUmJLcVRYGu6wjDEEEQwLIsSJIkakLa7fbCtDYw/R6ogmS3uK4rjmGq5qHKHc/zcnUm9Pvb0jDdSwGW2wzDMAzDMAzDMAxzmUIDzKgXFpimtiVJQq1WK+18ZvbOeDwuFWAkKWVZRpqmcBwHo9EIcRyLxDZ9P1EUwXEckcLWdV2I3GXpXEpxW5a16yTvfqAhfkU5GUURut0u1tbWhLCrVCoIgkCkWg3DgOu6GI/HQnZSelvTtJzcDoJADJOkQZrZoZJlcjtNU5Hq3i9JkswsWuz3deeJbU3TZsQ2ME03F4XvbuX2ZDKZEeQHPdjQdd3c8VCsJFEUJXf9KVaShGE4I9qr1erC43o8HouBkZRKtywLSZLA931RywOc7/s+deoUkiRBtVrN7Ws6bhRFKa0fyX4OWlwpfodhGM4kz2kQbLaWp/j6WdGtquqBD3n9ToPlNsMwDMMwDMMwDMNchkRRhOFwiMFgINKmhmFA13XYtp1LTTK7I01TkbTWdR2maWIymZQOoDNNUwyNy0rtIAgwHo9zArA4KNAwDFFbMplMRDVCNt1JSXzLsi5aZ3nZUEKCUrHZwXnNZhNhGIqakUqlgsFgIOR8FEVwXXemtiEMQyFySXLT/qPUuyzLM3UmVF2yX8rqYvbzummalg4cpZR/2WsXK0kMw9jVNtB1IYssywd+F0Wx3iMMw9zCg23bOWGble1JkiAIgtzxrCjKQvmeJIl4TxL+VAUyHo9RrVZhGIY4ZgzDwGg0EkI6CAKRXPc8TywszUNVVVSrVZEEp22IokgMdy1b6Mr2hc+DRDl911TjxP3ce4PlNsMwDMMwDMMwDMNchvT7ffT7fSHkSCKapnlgA+O+EwnDEL1eT0gx13Vx6tQpALMD8iqVCur1Onzfx2g0QhiGiOMYk8lkpm5DkiQh+GzbnkmopmkKz/NElUGj0UCz2bzo6XvP8+b2FBOu60JRFNTrdQDTY7HdbmN7extpmorO6MlkIlKro9EIa2trudfJyuXsUEkA4vug6ovsogFVl+yXskqSvSZqSWwXFwUURcl1lWeJ43gm4byb1DYl7MsGGx5kdY3nebkUc9miQFZUU4KZcBxn5vtqNBoL9/VoNBKfy/d90VXe7/chyzIMw0CtVhPd2sUEfBRFOHv2LBRFwcbGxtzjRdM0VKtVmKY5sz0kxKlOp16vi+ocEupZwb4qJLov9rl+ucJym2EYhmEYhmEYhmEuM1zXxdbWVk6gUF3FQQ6M+05jMpnkKl6ynebAVOpRknp9fR2WZaHT6SAIApHKpiF7lE4luQvMVjVkIXGWTW4PBgM4jgPbtg99WGQZURSVDiVsNBoYDoc5qTkej3Ofj4bq9Xo9AFPZ2e/3MRqNRIrY930oipI7juk1ScZma0mI4nMOqne7+Dp73d8kmYuiepHYBmZT25Ikif78VcgeqwQteB0kxcWOotymWiQi260dRRE8z8udB6ZpLtxGqvKh9wrDEKZpCtG8trYG0zTF4+r1urhzIooi+L6PIAjEuTUajWb6x3VdF1J7GdnaFxqAatt2rp4njmOR8qZfcRzPLDwQnNreOyy3GYZhGIZhGIZhDhvfBz7wgfzPnvxkINNPyjCrkiQJbrnllpzEotRsWYcvsxzq8M1WJ1C9Q1F4xnGMJElw5swZABAyjGpMgiBAGIZI01R0Y2uaJmobKKEdx/FMdQNJsHlomiak3rzvmeQZDdqjX7vt6CZBWxSX9Xodtm1DURR0u92crBsMBlAURewTqo4Yj8fQNA26rotBf/V6HaPRCJqmLZTbNHyTfi/L8qENlTyoYZKDwWCm81qW5dzA0TKKcjtbibEMz/NmanM0TRNp+oOirEMaQO44oEUagiQ/1f2oqio+17IhkgByC07UrW0YBobDoUhtO44Dx3FEApzOO6oGqlaruQWTfr8Py7LQbrdRq9Vy27uIMAxLa1+Ki4qKokBRlNzrpmk6I7zTNBW1Q8zeYLnNMAzDMAzDMAxz2AyHwDOfmf/Z1hawsXFxtoe5rLn11ltFipGo1Wrc2boASlJnf5Gk9jwP/X4fURSJgYIkOUnCZcWdLMti/6dpik6nI+SdJElQFEX0Y1OSOdvT63keFEVBs9lEs9mEJEliIJ7v+wvldhzHoi/YMAyYpjlXllKvL21rmexeJE4Hg8HMtlBVw2AwEPU3xWR3r9fD2tqaSKvXajXx2W3bFnLUcRyxb4qfkfYj7XuS2vOGSl5KcpvS9lmopmVRdQodI1lWFZ4ka4vvScfXQVJMbcuyPLPdtm3n9h2dH57nIQzDXGq7VqstrEwJgiC3UOB5HgzDwHg8RpIk0DRNHKs0THc0Gom0OF0XHcfJfb9UIZIkycr7KEmSfdW+SJIkBkkyBwfLbYZhGIZhGIZhGIa5TOj1euh0Ormf6bqO48ePH2in7uVAmqbiVv+iuC7+KqsCSNNUpD3LsG0btm0DOD8oMivB6GeUvqQ0KVWKWJYl5O1wOEQQBJBlWaREsx3DsiyLWhmqUfA8r7TLGJhKNtd14bouVFUVwpqkPcleEmlU40HPoffMyu7sEMuy/RLHMcIwFKLRcRysr6+jVqthNBrl9mu328X6+roQ6M1mEzs7OwCmUtH3fTiOA1VVRcI1W+cgyzLSNIWiKELS04DJMrldFOR7Zb9yezgczqSnSWwvGl4IYGZ/02LEKmS794l6vX7gEpUqRbLouj4j1rN92/T9JUkiPiN9LlVVl/ZMZ1PSdGxTz3UQBIjjGIqiCMlO+58GQtI+oAGTkiTlOu+jKMLOzg6q1SpqtdrSBZ/isbZqlUkp3S7Q7wNHjgDct71nWG4zDMMwDMMwDMMwzGXAZDLB1tZWTtRKkoTb3e52u66cuFyhgXue5+V6fPfyOiSmi8iyLMQg9WhHUYTNzU2EYYhut4udnR3x3KLUpp+RaKOkK4lySZJQrVbnSjRVVUWHL8lk6u4maGAdiX0SbiS6aVtIRMqyLGoaNE2DqqoitZ7tDqbnZasjwjAUKetsQpoqJlqtFuI4zsnZJEmE4KYakVarhU6nA9u2RZJ3PB6j0WiI16fXzVarkBilz00/L36fB0FREO9mwWg8Hs+kmiVJQqvVWqnyYq+VJOPxeKbb2zTNQxlOWJbapmOE0DQtlzinbZtMJiKBT9erZUMkXdfNVaD4vi8WrFzXFWltz/NgmqZ4LC0sZc/HarWKo0ePwvf9XM1J9rP5vo9ms1m6KOA4zsx3pOt6rlt8Zb72NeBVrwLe9z4gCABFAX7mZ4D/9/8FeBjwrvnO+NePYRiGYRiGYRjmYqIowD3uMfszhlkR13Wxs7OTS01KkoQjR44cisS6lCDBS5UG+8X3fVFpUIRkFYlhx3FEV/RwOMRoNBK1CLIsC3ErSZIY/keimwSv7/u5pCqlRm3bXpr4pNQrJZ0nk4mQhZR4Lj6eHgtAbBeJ6qzsI4lOFSWqqsLzPAwGA1EFQqn0VqslUswkFxVFged5SNMUjUZDLDxkt6Xb7Yohe7quo16vi0oTSqZT6js7MDNbC+P7/sxQyeLnpnT+fis49jpQktL5RZrN5kqpXkogZ1mlkiQMw1xqHoCovDloKPmfpVKpzAwWpTsBCKraoWsX/Z1lWQulf5qmM59tOBxCkiRMJhNRX+M4jhDMiqLkBkVSSjvbt62qKgzDQL/fn+kOD8NQpLizC1BhGGIwGOQeW9azvZQkAf74j4Ff/VUguy/jGHjjG4Gvfx344AcBnpuwK1huMwzDMAzDMAzDHDbtNnDDDRd7K5jLFN/30ev1ZlKT9XodG7fB3vYkSUTPblZs7pc0TYUcJilNgprS2tVqFZ7nwXVdyLIMTdPEAETXdYXEo1oR6oEGpmlZ0zRF2jsIAiF7qWda13U0Gg20Wq2cvIzjODdojqR2Nl1KHcHUu037Jk1T8frFfUUp6KyUlCRprrQNgiDXRw5A7INTp04JiayqKur1Oo4ePQrXdWHbtkhmZxcggiBAr9cTErBSqYjtpOQ9fVZN00SdBYnq7ABAAOK1yxLVcRzv+w6GvdaSFKs6gKnYXrUzuyiNKWW/CBr4Wdb/fBjd+5PJZOauEU3TZj47DRuNokicN9lrl67r4nxbhOM4uQqQ0WgkjnPajjRNhYQ2TVP8XpZlIbXL9oWqqlhbW8NkMsFoNMp9LpLqlOJWFGVfPduCr30N+KmfAj7xifmP+Yd/AP7xH4EnPnH112VYbjMMwzAMwzAMwzDMpYrneej1eqIag6hUKtjY2LjNDJDM9kwXKziWoapqTlKX/aJkLSUyi89vNptCYlOdCCWLs5JN0zSYpimkFvWdN5tNRFGEra0tjEajmZoOYCoDadBiv9+H67qiN3xet3YZNKRS13WMRiMh/QDk0uQkjillnYX2bzZ1Son2rFSn1yGBSQnwIAjguq6QijRAsN1uY2dnJyfZPc/DcDhE41zdAu0rwzDE6yZJgsFgIF6HRHVRbpN0p8+Z3W8XU24Xe5izfe3LKC4+0POXMa//eZUKlN2S7csmLMsSCzGEoigiFU2PL1676O6IRWI4m+gHpsdmceEkTVPUajXRrW2aJmRZRrVanRloWQZVldD2Fu8KCYIA29vb0DRtZj9XKpXVe7aTBPiTPwF+5Vfyae15XHcdy+1dwnKbYRiGYRiGYRiGYS5BJpOJqIjIiiXLstBoNFaWZ5cilDYmob2bgYCyLIsUMwmtRYzH45l0JmGaJlRVRbfbFYloktmUHgemUpceS0J3fX0dzWYTaZpiOByK4Y6tVguDwSDXF2yaJlqtVi6ZXJb2XUaSJPB9X6SeNU3D5uamEL1UAZGFJDelw6MomqlScF03V6tB1SPANEFLKd1sXQntt0qlglarJWpS1tbWsLOzkxPFk8kEiqKIZG2r1RLfPw2OHI1GGAwGaLVaYhtIgGZrR7JDJYtyez/QZ8uyV7m9G8lOPdJZliW+Xdedkc2apu2t/3kFHMeZ2cZqtYperyeONzpmhsOhEOxFKW6aJnRdX3rton5uYCqZz5w5M3Nc27YNwzBQr9dFrc7Gxsauq2k0TcP6+rq4TmSh61Tx8ctS54JV0tpFCv3pzHJYbjMMwzAMwzAMwzDMJQTJUqoByPZDG4aBSqWCer2+737hCw0NMCQ5u5u0MsllwzCg6/pKnz2OY/T7/Zlhe9nXJIFN3cWO4+TqPRRFgWmaYhCjaZqo1+uikqCs1oDqRWzbRqPRgKqqSNN0z93oJHhpu3Rdh2mapfuAhhCS+CWBTHIYgBhAGUWRSFWPRiMhJykdbRiG6MrOyloSzCS4d3Z2sLm5iXa7LfZrq9VCt9vN7ZfhcAhFUWBZVq4WwnVd8Rk7nQ6q1SpUVUUYhuK9Sc7T70luZ4XnfuV22fG4au3EfuR22ZDCRe8bx/FM/zMtGBzGNYHqfLLQ8UcLU3Re03dH0DWMakJM01w6RDKOY1Fj4vs+Tp8+PfPd0HWw2WyK11p1AGcZkiShVquJFPe8xbaVe7Z3m9bO8kM/tLvHMyy3GYZhGIZhGIZhGOZSgXp0XdcV3c8k7ahTlhKLlwMkvqhuZFVIqpLQ3m3dhOd56Pf7M1KMxG5WmPZ6PYxGo5zQIpmu67oYfEd92TQMsdvtzkgw6uullLKmaZAkCevr6yKBT3UkZZ9Z0zTRt0zyluR72QDJ7HOpHqR4bFD1CS0qUJXEZDIRlS2yLAtRSbUflmWJhQRZliFJkkg3+74vvttKpYKbbrop1/VsGAaazSZ6vV5uW/r9PhRFEd/t5uYmbr75ZtHjTdUuV1xxhfjuqL85K7fp51kOQ26vIkuzKXdi1eOVFnyyLEo10/Wh+H60iLJXqIpHlmVUKpXcvs1eg4hqtSrS/sPhUKTq6bil1/R9H5VKRYhn27ZzwybLoMUiz/Nw+vRpxHEsBrQCU/nfbDbF4Fdi1X7zRei6jo2NDbG4WGSl/fz1r0/T2v/yL7vfgJ/4CeDBD979877DYbnNMAzDMAzDMAzDMJcASZKg0+mIiousUKpUKrBtG5IkrX5L/EUkjmORhF4V6uslqbyXPvFs6r24PTQk0rIsBEGA4XAoal+IbP2IYRioVqui47pWqyGOY3Q6nblpcM/zxGBJEm8kuYGpPKvX66KHmIZWUq0CME1oO44jpOEiVFWFbduwLGuh+NZ1XdRBDAYDkeYeDAaiikGWZei6DsMw0G63RUI7juPcAE5KYJOUpe/61ltvxfHjx8X7WpaFOI5zdSdpmqLb7WJ9fR2qqqLRaAgJTuKaPjvts2Lv9oWS2yT0l0HbQwsnkiSJbaHXmPc6nufNDGlc1OU8Ho9nFoksy9pXRRH1+tN2OI6DZrMptqN4LlEH9alTp3LHqKqqQlxLkoQkSdBut8V5vMoQyTAM4TgOJpMJtra2EMcxDMMQCX1N03DkyJGZuzfoHDoIJEkSi1j9fl98l9VqdbFATxLgT/90mtbexXVP8DM/A/zhHwKX2R05lwIstxmGYRiGYRiGYQ4b3wf+z//J/+wxjwEuk/Qtc/iEYYhTp05hPB7nJB0NPSPRVK/XV65KuBhQOplqLpZBVR+UjN4PURTlOoABiMGOYRjCMAzEcYytrS1MJpPcftY0TSTEVVUVaVPTNFGpVITUdRxnrnDWdV0kWLOvWxxgSenYLEmSYDKZiG1dxKKU9jyo3mY0GokkPS08VKtVkdg2DEPURsiyjFqtJgZoUv/weDxGrVbDaDSC7/twHAe1Wg2nT59Go9HIfd5qtYo4jnOClBZx1tfXoSgKjh07JtLuRLfbRbPZhG3bQlpeaLm96nlGNS4kQlVVRafTyT2GBmDSfqVfVIFBP7csS2xHUYrTvi9uIw3q3Auu66Lf7+eO6SRJ0O12xfGVPR49z0Mcx6LuJrvPdV2HpmmwbVscL1mq1erSBavBYIB+v49erye+Z1VV4fs+NE3D8ePHRc1PloNIbRcxDAObm5vwfV8s/Mzl618HXvAC4Nprd/9GJ08Cf/EXwKMetfeN/Q6H5TbDMAzDMAzDMMxhMxwCT3pS/mdbW8DGxsXZHuaSgWoGbr311pmKC5KLlLqlTthLlSAIMBgMFspZSZJEOtswjAMT9Y7j5FLYURTBdV0hVVVVFf3O2eQryXVFUcRCQqvVytUnLJP1lMYeDAY5GSlJUq4TuAxKac+rKsmySkq7SJqmQmBOJhN4nid6tWnfKIoiRGar1RI915IkIQzDnGw1DAO2bWMymaDRaKDX62EwGIgk7alTp3CnO90pl6Kt1+tiWCcRxzG63S7W1tagaRqOHTuGm2++Wfx9FEUYjUa5xZys3KYhlFkOI7m9CjR8NNvTXvbaZRU5/X5/5rFbW1u5baBf9LkJ6tneyx0OwPmBtfNwHAdnz56FaZq53m3TNMUg0Ow+t20bV1xxBQzDwPb2du61aMFoEePxGGfOnMF4PBbXQtM0EUURDMPA8ePHoSgK4jie2ceHIbeB5Un6fae1X/IS4DWvAQ5pEOh3Ciy3GYZhGIZhGIZhGOYCQ7JoZ2entH5CURTU63XYtn3JS+0kSUSquQxKpFLdyEEOvaNqDRrKF0URxuMxxuMxwjAUiWxKK9N+pvoNktq1Wg0bGxuoVCpi+5bJevqOLMsS75elUqmIao0iruuWPqfIXlLahO/72NnZwWg0QhAEuWOMvqtshcr6+jrW19dzCdU0TRFFkejrDoIA1WoVk8kElUpFLBZMJhNEUQTTNHHmzBkcP35c7EeSsJ1OJ7ewEIYher0e2u02Wq1Wrr8ZgOhpJ7mYlcNRFM0ITuoD36vsLcrx3cjt7MLUqs8rVttQRU2WMilOVKvVPd/tMB6Pc3UxZYRhiPF4jJ2dHVHXUzsnYYMgyCWr6/U6Wq0WTNPEaDSa2ZfLhki6roubb74Zk8lE7BdZlmGaJsIwxObmpvi+i69zkItku+Ib35h2a+81rf2WtwCPfvTBb9d3ICy3GYZhGIZhGIZhGOYCkSQJHMcRArZsaJmqqtjY2ECj0bikpfYqFSQk5w9DPgVBgF6vJ2oSKJ1M4tO2bTHgkWQbDTIkkVitVrGxsZFLflJPNAnzIpTwrlarIt1MvdWEqqpCBGZJ0xSDwWBpF/leUtrZ/bK1tYXBYDBzNwAwTezSwEtFUWBZFlqtFtbW1ko/q6ZpYl+laQrLsjAYDMQwyTiOxUICDZC0bRvtdjv3Ou12Gzs7O7lt8n0fg8EAzWYTGxsbOH36tBD+NLjSsizRx021L2EYiiGFWWlP/eB7YT/J7exnogWTZUn84iDJ3Sz86Lo+U3ezKsPhcKbeBDi/GEMLOltbW+I4pe71Vqsl6mnSNBXPoTsdihU0AMRdGmVQR3632xV3FhCWZYnXpzsBkiS5IJUkC0kS4E1vAl75yr2ltV/8YuC1r+W09gHCcpthGIZhGIZhGOawkeVpUqv4M+Y7BupUpq7n8Xg8I7cAoFar4fjx45e01AaWp5o1TUOj0dh3j/Y8JpMJut0uXNedkcWGYcAwDJE2zv6M5LZpmmg0GrmkNqXpR6PRXDFpmibq9bqQbSSri48vqyOhCpqy7x3YX0obgBCS3W537mJDmqbi81uWJSpvsiJ6EST2jx49iltvvRVBEIgBnbSA4LouvvrVr+Ie97hHboCgLMtCcGe3z3EcIds1TRPHlCzLYl8piiIEK4lu6qnOpoTjOJ6bll/GfuR2dhtUVUWr1YJhGCJ5TVKWfh8EAVRVhaIo4u9oYOy8Y49S9LSv4jjO9XIvGlxJDAaD0gW1Wq2GWq2GKIqgqip2dnZmFmAURUG/30elUhH92ST16Tgq3oWyaABuHMfo9XrwfR/9fj/3frquY3NzE7quL+xCX1obctBwWvuShOU2wzAMwzAMwzDMYbO2Btx008XeCuYikJXaJLaoJiKLYRhYX1/H2tragdZ2HDSrVJDUajUh6vb6HnEcz/yin49GI4xGo5nhi5Ik5dLaaZqKjmjLssTASMuyZgZzUoK4LOkMTGV9vV6fkc6TyWTmuyyri6CO6bLFgP2ktIHpQsPOzg46nQ6SKIL15S/D/OpXoYzHSEwTqWkClQq0eh2xYUCt1yFXq0gtC1KlgtaJE5DiGFBXU0SqqsIwDCH5wzCEoigiZU2f8atf/SrueMc7otVqiWNBVVW02210Op2cBKWBkrqui2NLkqSZ4ZEkOrM/z4rled/fKuxloGT22Mw+jzrLFUUpfZ3hcJhL9iuKgiNHjgBAToLTr2zaWlEUdLvdudtEkrsou2lBrSjE6/V6buElTVOxCESLC5IkwbIsVKtV0cOerSUhSV9cuKlUKrn+dSJ71wUNOiV0XcfRo0fRarVmRHxR/BuGseek/q5IEuDP/mya1i5ZHFgKp7UPFZbbDMMwDMMwDMMwDHPAFKU2/awoUA3DgGVZWF9fXzpw7WKySgVJmTQukpXU8+T1ouQqDYUsim3qBPY8D3Eci35g27ZFkldV1Zmql2UVJItkPQ09zFJWRxJFEbrd7ox4pYGTe61V8DwPvV5vKjrPnsXaBz6Atfe8B8a3v72n14OmAbY9+8uyZn7W0DTId70rzj7gAWg0GgiCQHx/VFEymUxw6tQpRFGU2++6rqPVas0I2sFgMHPs0HdcNlQy+3NiP0Ml95LcLqa2FwltgoZ8ZskeA9nX8DwPw+EQcRyvfJykaZo7h2ixp9jxDUwT22ma5mpKqA7GNE2oqgrP81Cv19FutyFJEhzHge/7cBwHtm3Dtm0AszUrlDAvMplMRMI7iiJsb2+L7bVtG5VKBe12G5qm5b6TJElmzsELUknyjW8AL3gB8PGP7/65nNa+INwm5fbNN9+MG2+8EWfOnEGSJDhy5Ajucpe74K53vevF3jSGYRiGYRiGYRjmNkySJKJLOyuYoijCYDAQsoYSxZqmiUFslyqrVJCUpZqDIIDrugjDUMjrZT3E88gKuqLY1jRNSLd6vY56vZ7rL6aBkbutILFtG/V6vVRypmmKfr+/tI4kCILSmhCq6NhtbQuJ0eFwiEGvB/Xaa3H83e9G4+Mfh7SP1DIAIAyBwWD6awnWuV/NEyfwX69+Nfq3vz2uuOIKnDlzRixQSJKEwWAA0zQRRVFuf1ItzCDzXmmaimMlK7PTNBXp36zcTtP0QOX2XgZKxnE807dNqe15ZCtciKKkjeNY9JrvB+q0Lt5dQOdEWf0NpbdlWUaj0cDRo0dhmiZ83xcyP4oica3LpvWz1Gq13D6kc4bEfpqm2NraEvUqlPJeW1tDvV5Hv9/PvV6SJLkU+KFXknBa+7LhgsntyWSCG2+8EV/4whfwhS98AV/84hdx6tQp8ffHjx/Hxz72sX29x7XXXos/+7M/w+c+97nSv7/b3e6GF77whXjyk5+88mu+5z3vwa/+6q/uaXt+6Id+CL//+7+/p+cyDMMwDMMwDMMwlw/zpDYwlVmUeKauY1VV9yw4LxSrVJBUq9WcNI7jGI7jwHXdfVVElG1HGIbwPC8n6mg/1mo1NBqNGSFZlianNOyiCpJlfeGO48wIw0qlknuO67qlApyqOcrqGuZBdwKMx2N4N90E8+qrcft3vxtGxqtcDPRbbsGdX/lKXPeWt8A4ehRra2sYj8cIw1AMGOx0OqJuxPd9NBoNmKYphlFmU8O6rsN1Xdi2DVmWRbq3KLcBiP7pLHuV28W0M7C35Laqqku/12JqmwZ20nYsW3RZZVglvVbZopQkSWg0GqXd5GmawvM8UZMjyzJs20az2YTneTh9+rT43PRatOC0ubkpPruu6yLRTY/v9XpiW0h0TyYTUctD15PNzU0As0nwIjRQ9FAYDoFnPQv453/e/XNvdzvgL/6C09oXkEOX229961vxnve8B1/72tfm3rq0X9I0xe/+7u/ir/7qrxY+7itf+Qp+6Zd+CR//+Mfx6le/+pL9PxAMwzAMwzAMwzDM5YPv++h2u6XCyfM8jMdjUT9C8mcvgvNCsdsKkiRJ4LouXNctrT7YKyQuHceBqqoiqWtZFuI4hq7rIjVe/O/7sgqSKIowHA7nSjNZllGv15dKM3qd4vtlB+dNJpNcKpnQNA3tdnvlbu0oijAej+FOJpA++lHYf/3XOHrNNftPaR8gxqlTOP6+96Hz3/6bWOgIw1AMfqTzY2NjAwDQ7XZhWRYajQbq9TriOBbCl4QrCW56LU3TSvu1D0pulx3nq8rt7CKJLMsLz2mSx1kotb3sDgnDMNBoNHLDTOmaQ7+nX9TxblkWLMsSj8uK7bLnBkGAZrOZ++xULWKaJqrVqkhwA9Pvy/M8aJomhk3S0FXC9330er3cPh6PxxgOhzAMA6ZpQpIkqKqKK6+8EpIkwXXd3PU0SZKZ7/rQKkkcB3jiE4F//dfdP/enfxp43es4rX2BOfR/RT/zmc/gq1/96qG+xx/8wR/MiO373e9+uPe97w1FUfCVr3wFn/rUp8SJ8Q//8A9QFAWve93rdv1euxnusJdBEAzDMAzDMAzDMMzlxWAwKBXb1LfdarVy/32o6zra7faFGYS2S5YJNpLGuq4jCAIhi3dTNyJJEmRZFr3CiqKU/jkMQ3S7Xdi2DcdxRCI4SRJRYVAc3jivgmQ8HmM8Hs/dzkqlMlOjMI+yNHaj0RDvNxgMZgbhAVM5mB2uuAjf96fDKr/1LZh/+7dY+5u/gX6RU9qLuOKd78T2854HpVoViwOGYSCKIriui/F4LKpIAIiFkEajgWaziTiOEQSBSD5TSt+yLARBANu2oaoqgiAQlSdRFM3UUlD1zW4TvUUpTsfoMorJbaolmYfneTMi3TAM9Pv9hXdI1Ov1XBKatrHsc0ZRhH6/L76D7Ousra2VJraB8zUh2c9NvdsAxBBJSnW7rgtZlsX3ROdZdt/ROZw9XxzHEQtWdO7KsoyjR4+KPxfT7cVKElmWDyewGobTxPZuxfbtbjft1n7MYw5+m5ilXJQlYtu2cc973hM33HDD3JN3Va655hq8+c1vFn+u1+t44xvfiIc+9KG5x9144414yUtegjNnzgAAPvCBD+D+978/nv3sZ+/q/T784Q/jxIkT+9pmhmEYhmEYhmG+wwgC4FOfyv/se74H4LtJL3uyKUaCqhRM0yxNGxZ7mS8FllWQZDt6qW5jlZSsqqoisZ4V18s+v+d56HQ68H0fo9FI9O9SBQlVGGTlJsnTYgXJYDCYu626rs+taChjMpmU1pEYhjHTKVx8TL1eX/i5qU97MhxCPpfSbn3kI5D20SN9odA6HbT/6Z8w+pEfEVUWYRjCMAzouo7JZIJeryeSusD0mOv1euJ76/V6IvkchqHodc4OlUzTVKR4wzAsHcIax/Gu74jYyzBJ6gjPPldRlIXHUpm07XQ6c++Q2M2iCzAV251OZ+Z4VxQFa2trS8V78XnZgZCUOI+iSHyvjuPkzmdJkqDrOnZ2dlCr1WZqmjzPg+/70DRNfCYarNpqtcQ+WXYHyKFUkiTJdHDk3//97p7Hae2LzqHLbcMwcNVVV+He97437nWve+He97437nSnO0GWZTzqUY/al9xO0xSvf/3rxZ8lScKb3vQmPPCBD5x57D3ucQ+87W1vw1Oe8hRxkvzJn/wJnvrUp17SgzsYhmEYhmEYhrkNMBgAj3xk/mdbW8C52/SZy5eirCLRUyZeqtVq7nb9S4FVKkgMw4CmaWKQ4TJkWRZ1CHsZmNjtdrG9vY0gCBCGoehkVhQF1WpVDJ+jWgJN01Cr1XL/bU8DPOdJsnlp2EWU1ZEoioJ6vY4kSdDtdmfENzAN4WUlYZIkuW1L0xS+7yP81rfQePe70Xz3u6Gf6za+nDj2jndg9PSnA7IshkbSMVWtVhEEAXq9HjY3N2cWIIIgQKVSge/7OQFLiW7g/N3xNHAyiiLI594re+xeKLldHCYJQCzizHsP+s6pbsY0zdL3WqX3vUgYhqWinIY0LmsXyHafA9OFn+z7k9ymxQY6D7NQd3aSJPj2t78NSZLEORuGIcIwhG3bufOoVquh1WqJ/VC8EyQ7YJQ48EqSNAV+4ReAt7999edwWvuS4dDl9hve8IZDe+3/83/+T67y5ClPeUqp2CbucIc74AUveAHe9KY3AQC2t7fxzne+E89//vMPbRsZhmEYhmEYhmGY2ybUNU2QiCsKKeq53Y1IvRBQfUGZkKWErKZpCIJgaZKSKhAsyxIduqtCXb+u62JnZ0dUemSHDVIFCTAVW7VaTQj0bFI2TVOMRqPSwZ60nbZt7yoNS5TVz1ClRrfbnRGdlEjNijgSvHEcT7umx2NoH/sY2u96F+qf+MSBprRj2wYUBbLnQZpTM3OQWDfdhNq112L0yEciSRLxuekcyVZOZGtjgOm5NBqN4Pt+7nuh/QTk5TYwPX6ph70ot3fLXuR2Wd+2rutzj33XdZEkiRi4CiBXGwJAyGDLspAkiagxieNYVK7Q47JpaaoTyv49cF6SUxI++5zi84tVRNkFGVqAAaZym3q9qWtelmU4jiO+c0po0+Mty4Lv+6jX67ku+mq1Ctu2c5K8uGBYrJlRFOXgK0l+7/eAP/zD1R//ohdN09qX2GLldyqX3uSKXfDPhamlz33uc5c+59nPfjb+5//8n+Ji98///M8stxmGYRiGYRiGYZhdk00YhmGI0WiEZrOZe4wkSWi1WpfcHcOTyQTD4VB0IlPSlgS9oigwDGNumpvQNE108O5WFodhCMdx4HmeSLJSOjQrtnVdF4nQRqOBI0eOlEpESpYfVAVJFsdxZgQ/bdPOzk6pHG21Wjl56TgO+v0+fM9DfNNNqLz73bj9e98L/dZbd70980glCaOHPQydpz8dw0c8AlDVqWSvVKBFEbQwhB5FUIMAehRB8X1Irgu47nSQ3qJfN98M/Mu/LHz/I3/1Vxidu0slDEO0Wq2ZIYpxHEPTNCRJUnp8+b4vhkiS3M52LpcNlcyK2YOQ26vMUMuKd3rOvMR4mqbodDrodrvi82iaJhZh6M+WZWE0GmE0Gq287dR9X1x40TQNhmGUDjZdhqqquWuW7/tCaJN0p7+nipGTJ0+KbcmmwOM4huM4aDabCIJALAjQ4lStVhPn8qqVJAfK//pfwKtetdpjT5wA/uIvgMc+9mC3gdkXl63cjqII/5K5qB47dgxXXXXV0ucdOXIE97nPfXDdddcBAD73uc+h2+2i3W4f2rYyDMMwDMMwDPMdjiQB6+uzP2Mua6hmk4SOrus5wasoCtrt9p5k6mERx/FUsPq+2O4kSURys1arLR12qShKaWq6DBJi2UUA13XhOI6QXJTapWGBSZJgPB4jSRKYpgld16EoCiqVCiqVihBnaZqKX5SKLauFoOqQvUqxOI5L60ioW7goFZUwRNtxoN14I3DzzUhvvhnef/0X0m9+E+3Tp6HdeiuUjOw9CMKNDXSe9jR0n/pUhFdckfu7arUK1TSRAgjO/SKoI1nXdWiaNnMM53Bd4ORJYHt77nZUPvc52NdfD+e7vxtRFCEIAqytreHMmTNCBAdBgNFohCuuuAK+7+fqajVNE4MjkyQRXeZRFInjoExuZ9mL3C4+Z6/JbTqnSALTudXv97Gzs5N7frVaheu6om5nL2lk6qQvHoO6ri/teF9ENrUNnK8kCYJASH1JkkSHvmEYsG0bpmliNBpBkqTcNlWrVZHuBqaJ9Wq1KhbHiGJqu+z7PVC5/a53AS9+8WqPPX58Omjy5MmDe3/mQLhs5fZXv/rV3D8u973vfVd+7n3ve18ht+M4xmc/+1k8hjtyGIZhGIZhGIY5LNbXFwoh5vKDxF02NZlNOmqahna7vVIC9ELhui4Gg4FIRw6HQ7iuK6ogbNtGmqaYTCaoVCo5wSdJEkzThG3bC6sXiDRNMR6PMZlMEEURfN8Xidyyx5FcpKoXSZJyXdVU+ZBNdVJfuOu6OZEmy7IY7Fev19FsNvdVY9Dv988ne5MEcqcDa2cH/je/CfuWW6CcOgXl9Gkop09DPXUKcuFclwAccNYUAJDKMsYPfzi6z3gGhg9/ONJzAxezUE3M3Nc4VzeR3a+qquZkt6qq0+oYSQJe9CKYv/M7C7dr8y//Ejedm4/mOA7W19fRbDbR7XbF9k0mE3S7XRw7dgymaYqhn6qqQlVVyLIshHYYhqLu57Dk9l5rSbLvNRwOYRiG+BktumRrSAhJkqCqKmzbhm3be5LQruvO9GQDU3GcTUPvFlq8ypLtCvc8TyTUNU0TtUvAtLpHURS0Wi2xYGVZFgzDgOM4IrVfOzd8sTiDoGwYa/ZzaJp2cIuFH/kI8KM/Ou3bXka7DXz4wyy2L1EuW7n99a9/Pffnu9/97is/9x73uEfuz9/4xjcOZJsYhmEYhmEYhmGY7wwcx0EYhkJsy7IspIthGLkBaRcbGmBI4sh1XYxGIyGVqSub8DwPYRiiWq2KTtx5g++KUOc1pcNpEaCMOI4xmUyEWCShWalUpmnjcwKNen1JclHNheM4pbUWlOCmmpVOpyNkIskxSgjP/UyOA3z4wwj//d9hff3rqGYEtjTn81wo4qNH4fzoj8J59rMRHz8ODcDaub/LHoskHkkOl3WQlxGGoTgGwjBEkiSQJGkqu5/+dJx4/eshl0hIon7NNdC/9S0EJ0+Kup6NjQ14nif61NM0Rb/fh2maWFtbg67roivdMAwxlDCbfgamxwJ1PkuShCiKZuT9hZLblC4HIBaISLTTIFRKdhcXdWzbRqvVWjj4UpIkMTAzK/ApAR1FUa72hhbYaIAj3dVAf5f9ffZ/i5+72WzmhDKltYHz1z3a56qqolKpQFVVTCYTcY2hCqEoiqCqqugap7soqKM/u/3Z4aHztu/AUtuf/jTwtKcBq3TRVyrAP/4jUHCJzKXDZSu3i0L6isJtN4s4duzYwtdaxJ/92Z/h61//Om655RaMRiMx1fVe97oXHvzgB+Pxj3/8JdelxjAMwzAMwzAMwxwcJHCzPbc0RNGyrBk5dDHxPC+XPKaubZKMWYlMqKoKwzBE+tmyrLmfJ0kSIUFJas+T2VmoY5u6vlVVhed50HUdlUpFyDxFUdBoNCDLspDarusKEUbyUFEUsb21Wm1mUF+apmI7i581K7y1MIT8x38MvPrVwHAIDcClUCqTyjL8Rz0Kk+c9D/4jHwlkvjNKtZMsLBOmVO1BdxvQgEFg+h1GUST2Dw1qLBIEASayDPspT8H61VfP3VYpTbHxV3+FU7/xGwCmad7NzU1sbm7i1KlT4viIogjdbhemaaJSqaDRaCAIArHwQMnoOI7F96acS6cnSSK6trPDCIELI7dpCGr2PdVz/eaj0WimY5y2iQaaXnHFFeIcI3mdFdn0e8L3ffR6PfFdKYoi0s8E7cNVKZPdZXeaUGqbevCzsp3qRWihL4ssy8LVnTlzRlQZ0edaltomMZ7lQHzbf/4n8IQnAOeugQvRNOA97wEe/OD9vy9zaFy2cvvs2bO5Px89enTl5xYfe+bMmZWf+653vSv3Z8/zsL29ja9+9at4z3veg9e+9rX46Z/+afzYj/3YJfN/ZhiGYRiGYRiGYZiDgyoVskLMMAyYpnnJiO0kSTAcDkXHLdV/9Pt9eJ4num5JyGuaJmogsrf9TyYT+L6PZrMpHkNyNPtrMpnMiOMikiSJJHGSJGK4I9WLKIqCZrMJRVFEn2+r1YKiKKKbmfq7KYmsKIoQfgBEgtT3fdG/XdbDTVBvsjsew3rXu1B/7WuBXTiCwyY+dgyTH/1ROM96FpLjxwGcl9kktFepaaDkNVWOZLvPKaU9T2oX2X7+87H2v/83pAXDRtsf/CD+63nPQ7y+jvF4DNu20Ww2YZqmqJFRFAWO42BnZ0ccdzQEkaQmdbaTSKbvMY5jUVFSFNH0nN1UAu12oGSxkoR+TwtJ9L1ke6Zt20alUoFhGNjc3Fx52wBgNBqJLnrXdVGpVHJd1bVabUZ2L4OuU8uuVyTqaRto4UiWZTG/rtfrzRw7zWZTLFJQZz5h2/bMcbuskoQqcvbFzTcDj3sc0Oksf6wkAX/919PHHxJ0bNPdCszeuGzldnbgAICZlbpFFB9bfK390Ol08Lu/+7v4v//3/+INb3jDwU9xZRiGYRiGYRiGYS4acRzj1ltvzckwujW/1WpdEmLb9330+/1c9+9wOES320Ucx6hUKkIsVSoV1Ot1UaNCdSLA+VT2ZDJBp9OZSXFHUQTHcXJ9zUUoia1pmqgJ8X0/t5/oruhs9Ygsy1hfX0cURRgOh/A8D0EQwPd9pGma69A2DEOkvUl00y/P88TwO+pzzkpvCYBxzTWo/87vQPvylw/0e9grqSzDe8xj4Dz3ufAf+UhI54S0YRhCAq96nNF3mE1sZ4/drHQkKUyiOwzDnMClfSjd8Y7oP/axaH3oQ3PfVw4CXPHud+OmF74QwDSgSPudFlqI8XgMx3GwubkJ3/dnpHF2MYPkJn0GSnEXBxjuRm4nSTIjZpeJxuIwSTrW6D1pwYjuNlhbWxPn3G49EXXkj8djIZpd1xVVQdlu+oOGjgMa+gog9zksy0K/38/tC2B6RwilrLN3uADT46go4ul9iEOpJNnenorqW25Z7fF/+qfAM5+5v/ecA939Q+eBLMvY2Ni4pGY0XE7cZuT2boZDFG9PWia3ZVnGQx7yEHz/938/rrrqKpw8eRK1Wg2+7+PMmTP49Kc/jb/927/FV7/6VfGca665Br/8y7+MN77xjZfE/7lhGIZhGIZhGIZh9kccx9je3p5JGNbrdbTb7Yv+334ksSeZ2+2TJEGv10O/3xcijLazWq2i3W6LKoMwDKHrOlzXFRUIWUguVyoVBEEAz/PmJn11XUez2USlUhEp4+FwiCAIcvuJtjW7XZIkoVKpoNvtiqRqUZ7RexQToNlUc3YfkIyM41jUmpg33IAr/uiPUP33f9/Vfj4souPH4TznOXCf/WwoJ09OBwOeSwDPO7ZI7sZxPPO/2dqWVcguAAAQneRUCUP7MU1TDF/0ooVyGwCueP/7cfOP/igS2xZdzZqmodFoIAzD3JDCXq8nKmqoq50eT5+Hqj+KQyUpvV2WpF6Fst72ZXI7WzVCx1VWTFJFCQne7Pe3W0kbhqFI2Ge3eTKZ4Morr8wluA8a+o7ozgw6RgCg3W6XDsvUdV3Ia8/zctsNIFc7RBRfg757Irsv98RoNK0i+cpXVnv8//gfwEtesvf3W0AYhuj3+zmZnyQJPM/bVXCXOc9lK7eLK8O7kdvFxxZPtCz3uc998JGPfAQnTpyY+TtN03DnO98Zd77znfGc5zwHb37zm/H6179e/OP+4Q9/GO985zvxzENa6WEYhmEYhmEY5jIhDIHPfz7/s/vcZ9rnyVwWJEmCbreLyWSSE7qapuHYsWMXXWyHYYher5eTmUmSYGtrC+PxGJZlif8WliQJ9Xoda2trkGUZOzs7uefRMLjRaJT7OSVuO52OqGGh16O+a8Mw0G63c8lMEuzF/46noFn2sVEUQZZlnDlzBp7nlYpHqlShNLOiKEKGzhuSlxXeyre/jdqrXw37fe9bef8eFqmmwXvUoxD8xE9A+oEfgGHbqOl6TlpT+pyGKxZF9kEgBkae20+6rpcKXtFd/gM/AO97vgfmpz419zW10QjH/vEfceoZzwAwrezY2NiAbduo1Wq5ag/qbKYqD13XhcwmkUwdzEW5TbUXByW3ZVleej5nk9uULqf9RcNMm80mhsPhvqs1ygSyJEkzFUKHged5uTsg6Byifveynm26gyVJEvT7/Zm/L0uZl32+4n7bc6rZ94GnPhX4j/9Y7fH//b8Dr3rV3t5rAXT9HI/HpdepfVeufAdz2e65Yvp6lYEV8x67aPXnjne840qvKUkSXvSiFwEA/uAP/kD8/E//9E/x1Kc+dVfynWEYhmEYhmGY2xj9PvCgB+V/trUFbGxclM1hdgeJ7TAMc+EoRVFw5MiRiyol5gmTKIpw5swZhGGIWq0mxJskSWi1Wmg0GnMT0cBUtDSbTbiuKzqsKalN9R/Um02CuVariR5vIo5jse+yeJ4nhuvR9pIIm5cGp/oXwzBg2/ZMajtbq5H9RfJS6vVQ++M/RuWtb4W0C4ewX8L1dUTHjiE6fhzJuV/plVciPXECuOc9IZ+TfXEcwxsMhCw9TBRFyYlsShovg6SqrutIfv3Xp2nYBVz57nej8+xnI5FleJ4HVVWRpqlIbw8GA/FY13UxHA4hy7KQ3CT5qZrDNE0xSJIguZ1lv3J7GUEQiOdFUSQGXALT47RarUI+95mz7KVao9hnLUmS6KsfDodYW1vb9WuuQpIkCIIA4/FYXCfoLgLbtkslLXXmA9NBosV9W6/XZ/ZvdrgpvW/xWNxzJUkcAz/6o8DHPrba45/7XOANb5j2bR8gdH0rc5e02Fj0nMzqXLZyu3jbxW7kdnG1+CBv4XjhC1+I97///fja174GYDqs8rrrrsNDH/rQA3sPhmEYhmEYhmEY5sKQpil6vZ6oeCAJQ8MPD6vrdhWozqEojn3fx+nTp4VkI2RZRrPZhGEYuc7jeWTTvGEYolKpzIj8yWQC27axtrYm+oUpaUvVGGX1JpTOpc8wGo1EErsI9ULTED3btksFZLZWIyvD4skE6R//MZTXvAZSIUm6X2LThHf0KPzNTXibm/A3NxEdPw7tjneEesc7QjpxAtKyOoWSQXoHSTGVrWnagXT7yo9/PNJ73xvSF7849zHGrbfi6Cc+gf4P/iCAqfilIYStVgunTp0SgwqTJIHruiKdLcuy+Dn9XaPRgKqqOWkcRdHMcbMbuV187CpyO+uVgiAQFS70GXVdn6nt2Uu1BnVtZ6E+b/p7z/P2V9mx4L2zw0aB83dNhGE4cy3I9my7rjuTxjZNs9S/FR9Hg22JPVeSpCnw4hcD73nPao9/4hOBt74VOMDBjmmaYjKZYDQalS5YaZomhvUye+c2I7eznWLLKD72IOW2LMt42tOehte97nXiZ//2b//GcpthGIZhGIZhGOYyg8Q2iSwSalTbQcLwYjAej0uFyXg8xs7ODizLmhGYlCadl9YmCUqixXVdaJqGer0ukppUy5IkiZB4W1tb6PV6uYT4PKh2JE1TnD17VnwG0zRnBKWiKLBtWwzMMwxjd/UvSYL47W+H9Bu/AeXb3179eQXcEycwufvdIZ08ifTKKxEcOYJ+vQ5nfR2BbSM5tz9o8eBiDBaVJAmyLAsprCiKSGfvZgDlLt8U0i//MvD85y982Obb3ob+4x8PSBK63a6Q25VKBRsbGyKVDUyPOaqjUVVVVM3IsiwkKA2lpH0eRdFMsvcwk9s0pJOgRDnt40qlAkmSSruod7uoUExtU61H9mfD4XD358YK0F0bAHKVMMDsPsv2bMdxnEvk03ZTt3+RYrq9+DlocOauedWrgD//89Ue+7CHAf/7fx9oVdiytHa1WkW1Wr3olVa3BS5buX3kyJHcn8+cObPyc2+99dbcn48ePXog20Tc5z73yf351KlTB/r6DMMwDMMwDMNchhzi0C/m4EnTFP1+X4iXNE3h+76QNCReL7SYiOMY/X5/5o5k2t7JZDIzlCyKIrTb7bm3vdNnURQFQRCg3++LoYuUmiVkWUYYhqKKhN47CAL0ej0hocugxw0Gg1waNdvfTe9RqVTQbrdRrVZXrn2h1w/DEMmHPwzrN38T2oJU8TKC9XXc8tM/DfdHfgSNc/3kk8lEdIVrAAxZFjUp7XYbqqqKLmlK+tMQxr1AAx1JWhcFdvZ/LwrPehbwa78GLFg8sL7yFVT//d8xfshD4DgOHMcRIcNGowHP89DpdMRgSKr/oSGRVNNCxzwdD/T4NE1nzsPDlNvFvu04jnPJW9u2EcfxvlsDPM+bSW3XajU0m030er3c9jiOc6DDCGlhLzs0k3r7HcdBvV4Xj832bAPldSR0zSxSHHoax/HBVJL8wR8Av/d7qz323vcG/v7vD/Tf6MlkguFwOLdbu9lscn3xAXLZyu073elOuT+fPn165ecWRfiqvdqrUuw7yl50GIZhGIZhGIb5DmRjA9jF3abMxWcwGOSSl5S+o1oEYB89sHvEcRwMh8MZcUSd4MV6BqoEOXr06Mxt79RNrWkawjCE4zjwfX9GyGWhW+gVRcFkMplJXCZJIlKklBIHzi8M0EDOLLqui/0oyzJqtRrW19fnVo8QaZqKIZJhGAqprd54I+q/+7swr7lmwZ5cTFypYPzSl8J50Ytg2jbMc59tMBiI44AG6lHVR6vVEsdFmbQi2Z2V3tQtPE9WK4py6ac6NQ14+cuBV7xi4cM23/Y2jB/yEKRpik6nI0SvLMtot9ti0YMS58W0a5IkYp/RvslK5bJzokx6l1F87rJ0dXEQZnaYpKIosCxr35UkaZrODHRVFAWNRgOWZWEymeT20Wg0gmVZB7bIUUxtA1M5HwQB0jTNLThle7YdxyntGZ93rSw+Nju0EpgeH7vuov7LvwR+8RdXe+wd7gB86ENAs7m795jDvMVHolqtolarXfrn9WXGbUZu33jjjSs/94Ybbsj9+aDldvHk5FJ4hmEYhmEYhmGYy4fhcCjSuUQQBKjX6zmBeaEGSdJt/sX/1gSmco2qPUgwRVEE13VhmiaOHz8uhFcURfB9H2EYin7rwWCQE9UkDqmCgH5PgxyJWq0GwzBEXzIAIWrTNIXruqjX60iSBP1+H91udyZNq2kaLMuCJEloNptCahcpimz6latrOH0azde9DtY73wlpjynpVFXRf+Yz4f3yLyPNDHuNogjD4VBUCRiGIfapZVloNptLZRXty9skL3wh0t/6LUiFKoostX/7N5hf/jK87/oujEYjBEEgJKZhGGi1WgjDUAhVSZKEoCaxraoqfN8XlTvZ46koqIHpebPKObrb5DYtUAAQd3PQd0u1PsVajmxtySq4riuOc8K2bXEO1ut17Ozs5D7DaDSaW/2xW3Z2dsT5lR3YSfuU9lG2ZzuOYwyHw9zrkJAvg64Ti9jtfsMHPgC84AWrPfbIEeAjHwGOHVv99Rcwb/ER4LT2YXPZyu273OUuqNfr4sT5/Oc/v/JzP/e5z4nfK4qC+93vfge6bd8u3I5zWJNrGYZhGIZhGIZhmINlNBrNVAEkSQLDMGaqBy4Evu+j1+uVChPP80R9CDCVS67rIooitFottNttxHEMx3EQBAHiOBaJY9d1cfbs2Zn+baohCcNQpE1JKkqSBF3Xxc8URcHm5ibG47F4PL3GYDDAN7/5TUiSVDpUkoZdttttbG5uCumzisjOIg2HqP7pn6L6538OqUT+r0r/MY9B5xWvgHnVVTmZRgsCtVot9/1LkoRarXZRB4peMtRq08F9r3nNwodt/uVf4ubf+z2EYYjhcIj19fXMS9Tg+z5c1xULKpR+TpJEpLRd150rt2kAJbGq3N7tQMns8UzDUUn+VioVRFE0kzzfzfUim9qm91FVVdwpAJy/4yErh6maZL+Lbr7v5yR1FEXQNE3sJzoPDMMQPdsA0O/3S+tI5u1PuiZl36e4ALSru2OuvRZ45jOBVSppGo1pYrsQnN0LixYfgekxUa/XOa19iFy2cltVVXzv934v/v7v/x7AtEf7+uuvx3d/93cvfN7Zs2dx/fXXiz/f9773FcMMDoprr7029+fv+q7vOtDXZxiGYRiGYRiGYQ4eGtKYhQRvVlZJknTolSQkuIqinf4uCAL4vi/6nD3PEynSVqsFwzBEZ24YhpBlWUjq4XBYmpikGgzq4CZRRl3PJGc8z4OqqiKl2mw2EQQBtre3MRgMcmnuMnRdx8mTJ7G+vg5JkhCGYS6puko/tdztwnz3u1H7oz+Cso8q0Ml97oPTL385ogc+UCQrKZVPiwdFWZjdx8wU6ed+Dukb3gCpZHge0fzwh3Hrz/4swiuuQL/fR7PZFPuW0vs7OzuilkWSJEiSJBY8ZFmG4zhot9tQFCWXaiYxWpTbq7Db5Ha2csL3fei6Lp5jmiaGw2HuOJYkSVSZpGla+guA+P1kMsFoNILv++L8r1ar6Pf7UBRFnHeapmEymeTqf4bD4b4cF9XGZPddEAS5ShVN08TwVLomTCaT0o7xRVUsZbVG2WQzDURdic99Dnjyk4EFtUoC0wQ++EFgiT9cBdd1SzvGgen2N5tNvk5cAC5buQ0AP/iDPyjkNgD8zd/8zVK5ffXVV+dO0sc//vEHuk3f/va38YEPfCD3s0c84hEH+h4MwzAMwzAMwzDMwUK3lBdpNpszwpuqNA6LOI7R6/Vm0p/A+WSz7/sIggCe58HzPJHArlQqCIIAjuOIn1mWBVVVRQ0Ava4sy0KSqaoqRP6yvmsAuXS153kYjUZCsFMHcbYzmmpTarUaTpw4AQDodDqrD1qMY2jXXw/zmmtgXHMNtM9/fs/1IwDgnTyJ7V/4BbiPexwq1So2NzdFItX3fQwGg5lUOwDRr32brRjZK8eOIXzWs6C//e1zHyLFMdbf/nbc+spXwvM8TCaTXGWFpmkwTVMkt4Hz9SQ0PJIWZVRVzQnFKIpmROgqcpuS4VlWldsksDVNgyRJmEwmmEwmGI/HuWPHsqyZmpJF20MJaM/zkCSJWGCiz5ztxnddVyw20eIVncN7gQZ+EvQ5sgs8mqblzgGq7cmiKEpu6GTZ5zywSpL/+i/g8Y8HSq7fMygK8M53Avv0dHR3yrzPYNs26vX6xRv0+h3GZS23H/3oR+Oud70rvvrVrwIA3v/+9+MZz3gGHvjAB5Y+/pvf/Cbe8pa3iD9vbGzgR37kR+a+/te//nXc7na3mxm8MY/BYICXvexluf8D8shHPhK3u93tVno+wzAMwzAMwzAMc+FxXRf9fn/m541GA4qizEjOw6wk8Tyv9PZ+4PyQPBJo1F0cBAFUVYVt20J8UbqchF+SJKLPmGpFSFiZpon19XVYloU0TXN1IEXo7+l9SK6TpNY0DUEQCOkjSRIMw4BpmqjValhbWyuV9mXInQ6Mj38cxjXXwLj2Wijd7u53aIFobQ3Dl78c7nOfC0XX0dZ1rK2tQZIk0Rm8SFg1Gg2uF5hD8opXAAvkNgCsve99OPvTP4242cRgMECtVssJQJLbJE4puU0SOgxDUTdCFTqyLJcukqwit8vOs0VCku6EAM5LblVVxaBFADPXi90MknQcR2xTdnGK3qcInfN0HaDXaLfb4i4EWsBatiBDvd3Z83MymeSSx9ShTT8jGV/c/81mc+F+LFYVhWG4t0qS06eBxz0O2Npa/lgAeOtbgSc9abXHzsHzPAwGg9LjixLtu/nOmf1zWcttSZLwile8Ai9+8YsBTE+ql770pXjjG9+Ihz70obnH3njjjXjJS16Su03iZS972cID7uqrr8ZHP/pRPO95z8MTnvAEHD16tPRxaZrimmuuwW//9m/j1KlT4ueWZeEXV53QyjAMwzAMwzDMbZcoAr7ylfzP7nY34AINJGTmQzK5SL1eR6VSmfk7VVUPZSgYVQqQgC4jSRKcOXMG3W4XrusKuUfDIbPVCMX/1o2iCLZti8qHbKVIu90uFbYksoMgEFUJ9L6UGi+Tg7qui9S2ZVlCpi/q3wVwPp39sY/BvOYaqNdfv690dpbEsjB58YsxfvGLkVarkM5tJ1U40Ocr+zySJInjgZmPeq97wX3c42B9+MNzH6O4Lhp/8zfovfSl8DwPjuPkesvpLgO6k4DqR+hYB6Zi1LIsyLIsEt1lHIbcpnoR4HythqqqiKIIpmnOVHNkF5FW2RZaWCGZT+cSgNLgpSRJsG07d3dJFEVwHAdpmua2p1hpUhTe1PNdlPfZ612lUsl9X5PJZGaxqjh8toziAlKSJLnPt9J1ttsFfuAHgJtuWvw44g1vAJ7//NUeW0KSJKXDhgnLspZf45hD4dD/n9SpU6fw2Mc+tvTvsheaU6dO4R73uEfp4972trfhQQ96UOnfPfKRj8R/+2//DW9+85sBTKda/8RP/ATud7/74aqrroIsy/jKV76CT33qU7mVpCc/+cl49rOfvdL2v+Y1r8FrX/tanDx5Ene/+92xubmJarWKIAhw66234rrrrsOtt96ae56iKHj961+PO9/5zkvfg2EYhmEYhmGY2zi9HnCve+V/trUFbGxcnO1hAJwf1lhMHdKgQOqyznIYqe0oitDr9eYmpYMgwNbWFs6ePZtLSSuKAsuyhBCkYY8krw3DEPUG1WpVdElTzQElDGkoXlYu0WfPJrOpjmU8HiNNU6iqijiOc/9tT4MiG42GSHEnSTK3YkDe2YH1iU/A/PjHoX3sY5APIJ2d23+yDPe5z8Xw5S9HcuSI+LmmaWLgZr/fL933wFTs0WdhFqOqKgY/8zML5TYAHH3nO3H2ec+DLMsYj8eoVCri2KDjhGptaFApyV5ZluF5njjmadAkgJnzeC9yO9stX0b2eKcue0VR4Ps+DMMQQpj6wmk76c/ZX9nHSZKEwWAgri9hGMK2bVH/oSgKjhw5kruzgs4tGhCbTYw7jjNzztG2Z69pJLxVVc2JapL4kiQJOa8oiujJp8cUK5tUVV1YRwJg5rqapunMPl+a2r7lFuCpTwW+9KXFjyNe9Srg539+tceW4Ps++v3+3LR2o9E49DkMzHwOXW6nabpyif+8xy3r4HrFK14Bz/Pw9sztL5/97Gfx2c9+tvTxT3jCE/Dbv/3bK21Tdhtuuukm3LTCitAVV1yB173udXjAAx6wq/dgGIZhGIZhGIZhLgxBEKDb7c7892alUkGtVgMAkVLOctACY9FAsiRJsL29jVtvvVUIZYLktWVZMAxDDG+jFDeJtjiOYdt2Th4piiLE7vb2tpBi9Dzq0c6+n+/7uR7vbDKThLllWbBtW/SCp2k6k+BUAJhf/CLMa66B9tGPQrruugNLZxdJnvQk9F/5Snh3vGPu59QZPBqN5iblZVlGrVab2XfMEh72MAT3vz/0666b+xC910P9Ax/A6FnPguu6cF1XSF1agKHebUrBUu+2JElCIBcHSBbPob3K7UUEQYA4joX8pTshqCqFtq1er0PXdWxubq6U3A7DEOPxWOyH8XiMRqMh/kznJpCvOaGaFMMwxLlMKXfHcZbebVBcnCK57bouTNPMiedarSauf/PqSFap7fF9f6aSpLiPFl5nP/EJ4BnPWLmKxP3xH4fz8z8PdDoziwplvy/+LIqiudcJ0zRFfRVz8bhN3AMnyzJ+/dd/HY94xCPwpje9CZ///OdLH3fXu94VL3zhC/GUpzxlpdd9zGMeg263i//4j//AmTNnlj7+rne9K571rGfhaU97Gt+uxDAMwzAMwzAMc4kShmGp2KZOZaJ467xhGAcmMRbVkERRhH6/j1tuuQWTySQngqjDWlVV1Go1NJtNVKtV2LYtRLeiKBgMBpBleUbWGYaBer2O8XgM13VFMjwIAuzs7ECSJFSrVSHSqJKk2CNMcp0Ee61Wy9UIkOAOwxDp2bPQr7kG6kc+AukjHwE6nQPZh/NIHvAA4HWvQ+ee95xJZJOE73Q6c+Wnbduo1WosrPaApmkYv/SlaL/gBQsfd+Xf/R0+84QnwLIsTCYTIXFlWRZVHMWBpFEU5e4GKPbhF0U1hS0XfY/F5yz7zkleU8c2nV+UIifoTopVK0mKAxnjOM4loOdVdNB+ojs2PM+bke9lQzPLoBqT8XgsBtBSKr5SqYh6IWDvdSTA7HU1ux8BiCR5yQYCb3rTNIFdMuy19L2e+ET0/sf/AFbs+V8VSZJyiw/MxeXQ5faJEyfwlWK33CHxfd/3ffi+7/s+fOtb38INN9yAra0txHGMI0eO4C53uQvudre77er1HvzgB+PBD34wAKDb7eJrX/saTp8+jV6vB9d1oWkaGo0GNjc3cdVVV4muLoZhGIZhGIZhGObSJIoidDqd0kR2VmxHUTTTnztPZNDt+XEcwzRN2La9tLe3WENCgyKHwyG63W5pmluWZZimCcuycPz4cWxubsK27VwvLyXSy8RtpVKBLMvY3t4W6Wzf93OSn6Q7vV72dbJCmyRkrVYrFVqS40B785uhveMdwH/8x9x9cZAkt789pFe/GnjGM9Dt9RDOEVpFkUhQL/gqgo4pR9d1jB/3OER3vCPUb3xj7uPsb38ba5/8JHrf//2o1Wqi1gOYnotZuU0DJalfmxZNsklpoLw/e5ncLp4ny5LbVKeRHSaZJElOblOae9W7PGg4a/Zz6LqeS0BrmiYWmaiLnCpR6Pf1eh2+7+cGclL9Du0zqjMJw3BmcY+uCXEco1KpwHVdMZQ2O5w2DMM91ZEA5ZUkRUr3m+cBL33pdCDkiviPeAR6f/zHwAEvUhmGgWazyYtflxC3ieR2kZMnT+LkyZMH+prtdntu7zfDMAzDMAzDMMxCNjamqTPmokFSpexWepIVWZlUTBeSWC7ium7uNYMgwHg8FmnqoixzHAeDwUA83vM8DIdDjMdjkZos9nwD56s0jh49ijvc4Q6l21J8bYKGzk0mE4zHY1GtUEYURfA8T0i0RqMhktz0WTRNQ61WK90GRBHwF38B/OZvAoXZVIdBqqqIHvxgyM9/PpSf/EmkmoZup5NLlVIiVdf1mQQ6MN0/tVot1/3M7A1N0wBZxvinfxrNV75y4WOvvPpqdB7xCHS73VzqNyu3AeTS20mSCElbqVSWVo8s+/vd1JLQXQ70v8D5xDYlpOln1Le9CsXFljRNc+dWEATo9/tL09eU3PZ9Xwhw13WhKIpYBMv2cJPwJtlNC27ValU8hqS1JEnQdX1uHUnx+jmPYt1RGIYzqfSZ/XbLLcAP/zDwmc8sfX0iuO990X3LW4ADXKjiwbKXLrdJuc0wDMMwDMMwDMMwhOM46Pf76PV6Il1NAk3XdbTb7Rkx4zhO7s80TJFYVCuSJIkQ1pVKRUjTwWAAx3EQhiGGwyFGo5FIb3ueh/F4PCNfJUlCpVLByZMnceWVVwrRlGXZtsRxjG63Wyp2ZVmGbdvwPA+DwUAkYrNJzSiKclUopdIuTYH3vhf4tV8DDvnu7fjYMXiPehT8Rz0Kxg/+ICrHjp3bhBTdbjcntoMggOu6qFarpeLSNE3U6/WV6yOYxZCUdp7xDNRe9zooOztzH9u44QbUv/hFTO57X3S7XdTrdWiaBsuycqlkYHoekKgmKUvnAQ2aLOMg5TbVfVCvNTCV+dS3TaiqmlsMWoTrujPVOYZhiFoRqiWaV0tS/CyapmE8Huc+l+d5Oflclvqmc5rmDaRpCkVRUKvVxPN0Xcd4PJ7ZXhpWuwpllSTZ69lM9dMu+7UBILnb3RC///1orq8LkU7pf/p92c8W/b2maahUKnyduEThb4VhGIZhGIZhGIa5TRIEAYbDoRC3JHdd14XneahUKlhfX5+RxTSIMUu2kiSOY/R6vZnO2SJJkmA0GmEwGIhEZTGZHUURHMcR/ddZLMvCiRMncJe73EWkJuk9aeBZkiTo9/s52UdJZdd1F8o90zRhGAY8z4MkSWi1WqWfiURbvV4vT2v/y78Av/zLwL//+8L9sVcSVYX3gAcgfPSj4T/qUYjudjfo59L2JJvSNEWv1xP1DkmSiF7gsoFviqKg0WiUfx5mX2iahtg0Mfmpn0L9ta9d+Ngrr74aN9z73hiPx9jZ2cGxY8dEzQ4loGVZFrUk9L9Uq0FDJUkkF2XpQcptOg/CMBTDLVVVndvrvgxalCo+V5IkOI4Dx3GQpumuhtjSYtV4PM5tt+/74linIZLZ7Q7DMLf4FUURms2m6NyWZRlJkuReFzh/F8cqJEmytEZGnI/n+rXTn/95SCv2awMArroK8j/+I6zjx1d/DnPZw3KbYRiGYRiGYRiGuU0RxzFGoxEcx0EcxxgOhzOpZRrCtrOzA8uyUK1WhcgpprY1TRN/R9UmZWJG07ScMEqSBN1uF9vb20Joa5om+nQ9z8NkMsk9h9LkjUYDJ06cQLVanem3JSgBTttCgyGpdkRVVciyLGRfNrmpaZoQ65TKph5tkuJUZ2AYBiRJEvURIj3+pS8Bv/qrwN///epfzooER49i9LCHYfTwhwOPfjT0tTXxGRqFagAS21R5QPuValWyaUtKwmcTqczBomna9Dv4sR9D9U/+BHLhfMqy/slPwvrWtxDc7W7Y2dlBq9WCaZpiGCMli8MwFHchUBUI3WWQTU7vV24v6lEmqZ0V6/QaxYGIqyyaTCaTme3TdR2nTp3KXa/o2kN/rygK4jgW+6O4KGaa5szC1mQyga7rc+V9cVFL0zRUq9Xcn4uVR5IkrVxHAiyvJBFVLp4HvOQlwNvehl2doc9+NvDnfw5wbch3HCy3GYZhGIZhGIZhmNsENJSRbsuPoqh0MCMNDiQp47ouXNeFaZqoVCoznde2bSNNU4zH41LRTBLVtm0EQYCtrS1sb29jZ2dnZigl1WRQxQFtG8k82rYrrrgChmHMlXOe52E0GolUJgm3IAggy7IQYtlb64GppMrWEgAQHcYEPZ+SllEUiQqDOI4RfO1raL/xjVDe/vYD65JPNQ3+gx+M0cMehs6DHgT/jneEcq7vl8Slruu5tDZ9vn6/D8/zEIahqHaRZXlGbNOiQVYWMgcPCcu01YLznOeg+pa3LHz8lX/3d/jar/wKTNPE6dOncfLkSZimCU3TRHIbON+5TVI3DENxTBJF0bzbTu5FyW3f90XnNz2WtonOJUpOLxO+xRR0kiQIgkDUnmShc7Zer5emuGl/0P/S8d/pdERKOwgC9Ho9mKYprgm07ZSGJxRFmXkf6hrPkl0QXIVVKknkU6eQ/vAPQ9rNEFpZBl7zGuAXfgHgBavvSFhuMwzDMAzDMAzDMJc9NJiRxFAYhrmkoaIoqFQqSNNUJJHLXoPqRmzbFnLNMAx0u90ZUZ2mKWRZRr1eR5qmOHPmDAaDASaTCUajUalYo0qUMAzFkMps//fm5iY2NjbmyjGSuaPRKCecaDCcaZoz6dM0TaGqqhCG8yAxR0PnKAFPUkoZDLD5lrdg7eqrIS+pZFmF9ORJ+I98JCbf932YPOhBGJ6Tc8BU6NXrdZE8nzfwkXrMs3UvNPiNxDZ9R9lqGebwyB5jkxe9CJW3vQ3SAsl85CMfwU0veAGic0NPO50OTNMUyW2q36EKkqzcLi5GFQXsIrldXPgBFsttOm9pQapYiQKcryQp62/O/u9wOEQQBEiSBJ7nwXEc1Go1+L6fS1HTIpRt2+J8zEpp2h/Z32e3he7AoG2l74Yem30OpdGL5wnJ/Oz3Wkx2LyOO45lKkuK5XLnuOqTPex6kXfRro90Grr4aeOxjV38Oc5uD5TbDMAzDMAzDMMxhE8fAt7+d/9mVVwILboFnViOKItGrTfi+LyQQDUujAYk0PHI8HmMymczILUpBB0EghoidOXNGiKhsQpIEz9bWlqgYoK5rAEKie54nOrdpm7LpTs/z0Gq1cPLkydL+WhJXQRCINDhtd1Ya0SA+gnq5qeZhHlTRUhyaqSgKms0mvF4P1pvfjM23vAVKoXN3N6S6juThD0fyuMchePSj0d3cRBTHcBwHXibVaRiGkHnZBHY2XU6ij75HEnQktknE2bYtJDlzYSAhG8cx4hMn4D75ybDf+975jw9DHH/3u3H6Z38WqqpiNBqJRZps5zYtuNCxQAnlrMCmx2QrQ4oJYaKsWmhZcrtsmCS9Fw2H7HQ6C5PbVFcUhqG4i4PS2dmaIlVV0Wq1kKbp3GqiRVQqlZnEte/7SzuyoyjK1byMx2M0m03x97utIwEwczdMEAQwDAPn3gT2294G/Td/c9f92njf+4A73GH15zC3SVhuMwzDMAzDMAzDHDbd7ux/gG9tARsbF2d7bgPQbf1FQe26rrjdn2pGZFmGYRhotVpCXtXrdVSrVQyHQ4xGI1HNQTUmlKikdDUlSYHzvc2GYWA0GgnZTJKdBHh2u6jvlpLl9PeKoqBWq8G2bXS7XYzHY9GBTUP1KHXpOI7YFgBCmlNPMTAVYlQzYBhGrl4gm1RN0xSapsGyLBiGIWpcqMYAABBFsN/5Thz5/d+HcubMnr+r6IorMPrFX4T3pCchrVREV3iwvQ3HcXKS0bIs0ZNu2zZUVUW/3899747jzPT30vdSr9eh6zo0TUOj0Vgo9ZnDg7rbAWD84hcvlNsAcMUHPoBvP//5gGXBdV3RX0/HP4luOjaphqd4nimKIupKiGwnd5ZiqjtbgVKEhrTSOQJM5Tbd5UH1QGV3FxQZj8dwHCeXZKbzNIoisSBlGMa+Bp7SolW2DsTzvIV3cNB703WKuuuzn6lWq+262qdYSULvBc9D/Vd+BdV3vnNXr8f92kwWltsMwzAMwzAMwzDMZYXruhgOhzNyajKZwHEckbgmAWNZFmq1mhgwSb20NIyNkqGDwUBUAniehyiKUK1WEUURxuOxuGV/bW0NURSh2+0iSRIMBgP0+31EUSQEMolpkm8k4yRJEu9tGAbq54YjZsVaHMfQdV2kVz3Pw3g8FhKPBkEmSQLbtlGpVITUDoIAiqLM9E0TJK8qlcpc8ZvEMZL3vQ/yr/865C9/ec/fU9JsYvSzP4vJT/wEcE7Sua6L0WgkkuzZ7aLPoaoqarVabvuTJBHd6EWpTc+v1+swDGNuhQlz4dA0TQjN6F73QvB93wf92mvnPl4dj3Hk7/8e/Z/4CQAQ52h2KCqd79mO6DAMIUmSOLeowiTLPLldfNyi1HYURSIFnb1LgM51Slsvq74Zj8fY2trKHcOGYUCWZVEbkr2DYr/98HT9ov1DSfdWqyX+TPtXlmWoqoputwsAIlme/Uy6rueGua4CdX5n/yzLMuRTp9B8wQtgfvGLq78Y92szJbDcZhiGYRiGYRiGYS4LKFkdFPqe6db5IAhQq9VyaUeS3Nvb26VSFDgvfCk13O/3RVVA8XFpmuL06dOQZRmu62IwGMD3fSHWNE0TQ9uKA+joNWzbRrPZFAPZyqQadXOTTCMB7zgOwjCEpmnY2NgQCVfXdSHLMiqVSmnak6pQKpXKTCd3jk9+EvIrXwn5k5+c/5glJIaByQtegPHLXoa00QBw/jui1GpWLFIfOi0eZOUeJehd1y2tkQAgOrkbjQbq9friz8dcEIrnzujFL8baArkNAFe+613YfuYzoTUaYpGK5CsJ5OwAxOJQyTKBDczv3d6N3A7DUCS3AQiJTkI4e5fHvG0Yj8fo9Xq565AkSbAsC5qmiV/08+xgRzofSEIX/3fe7wGg0WhgMBjktockepHsQhxVoWS3abd1JMBsajsMQ9if+QzWX/pSqOdE+kpwvzYzB5bbDMMwDMMwDMMwzCVNkiQYDodwHGfm70jCyLKcqx0BprfPJ0mSq7WYRxiG8DwPQRDAsiwhkAnbtoXQdhxHDIwkSUTVJ7Isiw5oknGqqgpZValUsL6+jlarJTp7qaIgK71IZJPIp8dqmoZWqwXbtuH7fq5vm7YxC6XYi33aM9x4I/Brvwa8//1L99U8UlnG5Ed+BN3//t+RHj8uEp5RFIkhmNS9S9uZTdln09rZpDZJSHoO7SdalKjX62g0GvuqcGAOlqLc9h/xCCTf/d2Qr79+7nOMs2fR+vCH4T3jGYiiSNSRkKylIYT0ezrHKpVKTm6vOlRyN3K72LdNCejs3RbZc6zRaIhO6dFoJCqFKAVNj6tWqzhy5AgqlYoYjkpYloVWqzV3m1bFPjeoM8r0WQ+HQzE4NguJ7fF4LPYb7dfskNbdkJXbaZLAfPObceT3f5/7tZkDg+U2wzAMwzAMwzDMYbO+DhQH8S25fZ05L3hHo1FpajdNU3HbfFa6SJKEarUK3/dnUt7z6PV6CIJAdGM3m000m02RFB0MBhiNRhgMBrm+Z3r9SqUi+qCpI5uGxNE2NZtNrK2ticoQSldWq1XxWUj+jsdj6LouhlJmh+oB0woWAKUVHsD5vnExtG0et9wC/OZvAm99KzAnGb0K7g/8AEa/8iuI7npXIRrCMIRpmvB9X1StZKtQKpUKKpUKqtUqqtWqSMY7joPxeJzrFy9i2zZqtRqntC9RKNEshKokIfi5n4P5Uz+18HlX/u3f4oYf+iEYpimS0bQwBJyvJCG5TDVAWYFdVktSRvFxi44l13Vn5HaSJNB1XVwjsnUdpmmKO03iOIYkSXBdNyeTTdPE7W53O7EQULxWHVRfPFX2dDMpaUqSF4dLBkGAIAjEdYhqYQzD2HUdCTBd2KI7V+LJBNVf/EW0PvCB3b0I92szS2C5zTAMwzAMwzAMc9hIEv+H+S7xfR+DwSCXNsxCHbzFjlvqbqZ+7SI0TI06sdM0Ra/Xg6IoqFar4nFUbxIEATqdDjqdjhBVhCzL0HUdiqIgTVNYliWeQ1IamErcI0eOYH19fUYmFQnDELfccgskSRLCOooieJ4HVVWh67roCbdtO5e+lGUZlmWJ7uqF3Hwz8PrXA//zfwLnRNae+J7vQfqa1yC86ipE5xZwqJIlCILSOhiSbZVKBc1mE5qm5aT2vO8cON+fvpcEKXNh0XU99116T3oSzJMngW99a+5zKt/4Biqf/CSiRz86l9An8UyimAagArOSOlsZQs8pYzfJbRpSm30t2i6S7dmFJFoEI3zfF5KXrjVUK0TbUjzuD3IYKg2ozPbcj8dj2Ladk/rU709omiYW5vYCvV/w9a9j8yUvgX3DDas/mfu1mRXhfw0YhmEYhmEYhmGYS4YoijAcDnNiKAtVUfi+P5O0pM7byWRSKlQbjUZOhnueh36/nxvWCEDUHZw9e1YkttM0hWmaIomoKIroyCURTkMoSVhRVQrVkCxLUUdRhF6vB8MwoKoqBoOBEPy2bQvZZRgGqtWqkHGqqorqkUWCDsC0fuS1rwXe8Q5gN7UARe5+d+DVrwZ+6IemSflzNRHb29tzhz7SttbrddE5TonW0Wi0UGqbpolarbbvAXvMhaP4XQVpCrz85cDP//zC513xjnfgpkc+UlSSUD0JkJfLWbmdTURnhXPxOVmKP1907lBdSHaYJACRTtc0DaqqwnXdXMc+cP4OFOrXtm0bmqblrkXF1HZ2ceugqNfr2N7ezm3XaDQS4jpNU3S73dx+0TQNjUZjz3dI+L6P6KMfxfGf+zlovd7qT+R+bWYXsNxmGIZhGIZhGIa5DTEYDOC6LnRdR7PZXC47LxGyAwfniVFKRg8Gg9LUpaZppb3ciqKg3W4L2UZShxKKlC6MokhUBziOg+FwOCPAdF1HrVaDJEnQdV0MZSsOSTRNExsbG2g0GjNd4GWEYYhutyu6vz3PQxzHqFarImFOae2s5J43QHKGf/u3qYzeR6c2AOD4ceC3fgv48R9HIsvwzvViB0GANE1h27aoWCmi6zra7bb4Lnzfx3A4nJGBWQzDQK1WO9AUK3NhKMrtKIqQ/ORPQv6t3wIWiM7WZz+LW77wBST3uY+oxSDBna0iIbkdhmHu+JBlObfItN/kNtUN0evEcSxkr6Io8DwPlmVhMplMhyUW7ibxPE+kn0lY0zWEKKsk2e3gxmWQUM9eIx3HEZ334/F45rytVCozn2dV0jRF+qY34crf/E1Ic76DUr77u4H3vpf7tZmVYbnNMAzDMAzDMAxzG8FxHNHFTLeX1+v1i7xVy4njWHRel0HpwSRJ0Ov1SlPZsiznbrknDMPIyeU4jtHv98VjwzDEZDIRNRpBEIgO3SxpmkLTNJEgbrfbUFUV/X4fw+Ew18VLQjubTl6E7/vY2tqaGSypKMrMEDdKf5KQWkiaAh/60FRqX3vt4scuo9EAfvVXEb/0pfBkGd5gIIR2Fuo713VdDKWjbd7c3ES9XkcYhtjZ2VnYh06LCEs7w5lLFqq0yB4joWHAeOlLgd/5nYXPPfpXf4XT5+Q2JbhlWRYDD7O/T5JESG+qCsne+UGd3MX08apymypF6PE0vJL6wOl9aZGmmLhWFCVX65FdFCMOq2+7SK1Wg+d5uc8+GAzQbrexs7OTe6ymaVhbW9vze4VveQvWfuM3dvek5zxn2q/NMymYXcBym2EYhmEYhmEY5jZCMbXsuu4lL7cpsVyWrpRlGfV6HZZlwXVd9Pv9ua9TVmlRrVZzCUnf99Hv9xHHMeI4hud56Ha7mEwmYphjscc7iiIoigLbtoW0Nk1TVGmkaYpqtSq2v1aroVarrVRDQn3fZ8+enZFbqqqi0WgI4aYoikhRLk3jRxHwrndNpfb11y9+7DIMA8nP/Azcn/95eLYNfzRa8WmGGJSpaZoYRtftdksXIYhszQtzeUPVGtlkfhiGMH72Z4Hf/31gwXGw/vGP48y3vgWcPCmGryqKIo4dSZIQRZEQzSSwSTqXDZVcJrfnVW8Mh0PxGsD0vCXhToNjswKf5Pa8AYzFa3Kapp2HEuAAAQAASURBVDN3LxyW3Ka+b/pMwFSsnzlzZua8bLVaex/YGoZQfv3XV3+8LE/rkl7xCu7XZnYNy22GYRiGYRiGYZjDJkmATif/s7W16X/QHxBRFM0I0jiOEYbhJdtTTMK6LP1r2zZqtRpkWcZoNMKoRKpSYrLs+c1mU6Qj0zTFZDLBaDRCEARwXRe+7yNJEuzs7OQqRTRNQxzHiKIIsiyjWq2iXq9jfX0dlmUhCAL0er2cjNd1HYZhwDAMmKaJZrO5UApRzcH29nZOMhGapqFer4uBlVQ9srSmwPOAv/xL4HWvA77+9cWPXUIqSYie+1yMfuEX4G1uTn+4QEYC0/1uGAYsy4JhGELCh2GI0Wg0t0cdmArBWq02k2hlLm80TZuR2zhyBPjxHwf+1/+a+zwpSbD+13+Nzv/z/0BRlNxQSbqmFeV2VlYXrwnFxbOyuzPmLRpRfRElxBVFEVI7juOc3KYKlUajAdM0sbW1lXst0zRnxHXxDgiqPDosaOAuLQjSnSvZbTAMA41GY8/vEf3rv0I9e3a1B7fbwN/9HfCYx+z5/ZjvbFhuMwzDMAzDMAzDHDadDkCCkNjaAjY2DuwtyrqmgWk9yaUot+cJ62w/dpqmGAwGomqFmFczUHw+ACGjKZ1NQsfzPJw+fRqe54kEJlVoZKX22toaKpUKkiTB4FwVBzCVsaZpColLKfNF/bRUgUKp77JeasMwxOusVD0CAIMB8P/9f8Ab3gCsKpQWEDz2sei/8pWI7n73pY+lAZ/0KyvgkyTBcDice2wC0++LpPZBdwwzFx9d13PfvxDdv/ALwJvfPK3OmcPmBz+I0ctfLlLSlMomUZ2cG2IKQNyNkSVJkrlDJYupbWC+3KbrD72HZVlI0xSqqs4Ms6TUtmEYpfMDarXazOuX3bVxmOeCJEmo1Wro9XpwXXfm/KTr334Eu/fxj6O6ygO5X5s5AFhuMwzDMAzDMAzD3AYoE6XAVOKWCZWLRZqm6Pf7CwcOyrI893FxHIvUZJFsv3Ycx9jZ2RFd3iSZwjDE9vY2JpOJSHuGYSgGUlarVVSrVWxubor9RgKIuqNN08z16lYqFZEyL/u8nudhMpmI7RiNRqXVHNVqFUeOHFmtegQAzpwB/uiPgDe9CShJgO8W/4EPxOiVr0Tw0IcufNwioU0kSYJOpzN3WCTVI9i2zVL7NkzpUMkkgXzXuwJPfepUbM5B8Tw03vEODH78x0Uiml6D7tjI1hGFYSiS/zR8clW5LUlS6XFIQ2bp8VEUiXOfEuXZ4ZXUEQ7MLjjatl163bpQfdtZLMtCp9MRqXSCxLeqqjPd4aviOA6kf/u35Q/kfm3mgGC5zTAMwzAMwzAMc5nj+35pZzUwFT7zUs4XmjiO0e12S4UndVpLkiQGRxYFMMnhsi5r6tempHan08mJL3rvbrcrxJjrulAUBbqui+T1iRMn0Gw2IcsygiDAZDKBqqqo1+tiQB6h6zoajUapsKLqkclkkkuaDofDmc+vaRo2Nzextra2muj9xjemncV/8RdLq0JWwXv0ozF+2csQPOhBcx8jy3KucmTRdi4S25QKrVQqLLW/A6AUcm6oZBhOz+Ff+qWFchsA2n/zN9j6sR+Doig5mUyVRL7vi0Wo7DVQluWcdF4mt+ddH7PDJOk16DPRXR50xwf9na7rGA6HM1UjZYuMaZpeFLnted5MqhyASGzvdRuSJMFwMMD65z638HHpk58M6R3v4H5t5kBguc0wDMMwDMMwDHOZMy+1Tfi+v7Au40IQBAG63W5pHUCj0RDD1+YJcM/zRKdzFkmSxHNvvfXWXHUIiaPJZIKdnR0EQZBLgNLQQkVRsLa2hjvd6U5QVRVxHIukdrPZnJGwiypIstUjWXkUxzGGw6EQ7vRZbNsWfd5Luf564DWvmfbTluzH3ZAqCtynPAXjl7wE0T3uUfoYWZZFOnuZ0CbmiW1JkoTUXimVztwmkCQJmqblBG4QBNPz+KEPBR7+cOBf/3Xu87VeDxv/9E/YfsQjxLlL6W9FUXLHWXYxq/h3Rbld/PO8Y9JxHFFHQsNlaTuozqg4TFKSpJlrcqVSKRXoJOqzlIlluiZFUYRKpbIvAU4LgIqiwDRN0YVfrVbFNXHZMNx5DIdDSLfcAnV7e+HjpMc9jsU2c2Cw3GYYhmEYhmEYhjls1tamHdvFnx0AVHuRpZiU9Dzvosptx3EwGAxKB7i1Wi0hUqIoQrfbzUkqGgZpGEYuIZ0kCaIogmEYor+a5E8YhmLA5ng8xmg0EolvTdOgKAocx4Esy2g2m6JX2zAMId/n7a95FSRUPVJWNxJFEYbDoUjQkzBWVTX3+UsZj4FPfQr4wz8E/umfFu7nVUhNE86znoXxi1+M+Ha3m/n7vQhtIkmS0oUJWjzYa80Bc3lTlNu54+OXfmmh3AaA1tVXQ/n+7wcwlcc0DJZEN51X2UR3tpsbWJ7cnlcpRHMBSHDrug5JkkT/d/ZaRdK7eA2guxXKKOvbzkrwJEkwHo9FjRIwvda02+09CegwDNHtdsVrVSoV+L4Py7JyC2x7kedBEMBxHOif/vTyBz/kIbt+fYaZB//LwjAMwzAMwzAMc9jI8oEOj8zied6MqKnVahhmOph93xfS50JCcqjY6wpMJU673RbCMwxDdDqd3GeJ4xiTyQS2bUNVVaRpCt/3hTyiGpLBYADXdREEgXi+7/tCKJummasUieMYlUoFm5ubME0Tuq5jfX0dcRwjTdPShOW8CpIoijAYDEqlNn2u4XAIRVFE4lKSpJnBlwCA0Qj43OeA6647/+srX1k4dG9Vknodkx//cUxe8AIkhWORusQtyxLbt+vXPye2i7KOxTaj63puKGxObj/pScB3fRfw5S/Pfb7x5S9DGwwgZ3qgqXKEKkOyfdyaps3IbUpY07G9ityOokgsHFIlEl2HqCYlDEPx3qqq5mQ3Ma+Pn143C0nlJEkwmUwwmUxmtjVNU/R6PWxsbOyqboruism+nizLM3VIJO93Aw3/BQD1P/5j8WMtC9JVV+3q9RlmEfyvC8MwDMMwDMMwzGVM8fZ3qrrIym2SwnTL+YVgXm82bSMNfgTOJ7az0oVSgNVqVXRVk2CyLAuKomB7exvj8Tj3POq6DoIAmqbNfGbLstBsNkVSm5KW8+S0oiio1WozSW5KlFMqvIwgCOD7vujrJlRVxZqqQvnkJ/Mi+7/+60BEdpZ4cxPjF70IzvOeh7TQ+atpGmzbhmVZ+6oKSdOUxTYzl+KCEKWgFUWZLvz94i8CL3zhwteodLsYHTsm6kDCMESlUhGvRXdkuK4rfp8kyXR4ZWaoJB2Lq8ht6tumwZWyLIvnG4aBNE1FmhuYHu9BEOSOd0VRFt41UzxnNE3DeDyeua4VocWk9fX1XdUFFRPspmmi2WzmqoSq1equF7gmk4l4vv7Zzy58rPSABwAlcwoYZq/wvzAMwzAMwzAMwzCXKXEcz0hZEpW6rufEyYWU22X1IgQNfswmKKnKYjwei27bMAxh2zYGg4GQPCSxRqNR7jZ9AGIQpeu64vNTUlNRFGiahrW1NZw8eRKO4wCYLgyMRqNdV5BQWrxsYCIwFWWUftR1HVK/D+1LX4L2xS/C/NKXoH/pS5C+9rXd79hdEN3+9hi/9KVwnv50IPO9U0rbtu0DGVzHYptZBlV4ZGVtNvGMJzxh6WuYvi9qP2ioZPa6AEyPbTons9Ukq8jtsgS07/sIgiAn4+nctm0bjuMgSRJxLcsOaTRNU3TzzxPFVKkCnK+X2s0dNmEYot/vo9VqLXwcie3i9VjXdbRaLUiShLW1Nfi+D0mSdv3vRBzH5+tbHAfmf/7n4idwJQlzwPC/MgzDMAzDMAzDMJcpWZkCnBeXwFSuZIWj53loNBqHvk2+76PX683II0mS0Gg0ciKZxGgURRiPx6KbmwbOUZWBJElCuriumxvKSBUEruvCdV3RvaueqzBQVRWapuHYsWM4evSouH2eRHqZzJlXQZIkiRDrZSiKgloYIvnMZ5B8+tOof+EL0L74Rajf+ta+9+uqBPe6F8Y/8zPwnvhEICPsDiqlnYW+v7KO4WzlDMNompY7ToIgOH/erXBdsjJyG5gK1SRJRAc3DZUtdmBTTQk9h1g2UJKG0YZhKGqdssMkVVVFGIa5u0/G4zHq9Tomk4noxV40KJbuRPF9H47jiLtSSj+/ZaFaraLX6+U+IyXV53V6U4VJcSFO0zS0220h0mVZXm2obQk0TyFJEjif/CTkOYt+goc+dE/vwzDz4H9pGIZhGIZhGIZhLlMogUyYpilkhWmauWqSOI4RhuGMsD1IJpOJ6F3NQrIzmxQm6UKCp9/vi0FnmqbBdV0hoKjf1nEcqKoqhh1SDUG/34eqqrAsS3RsA1P53Wq1sLGxIXplv/Wtb+U6wEmO0/uUVZAAU4lEHd5ZpG4X1oc+hMonPgH1+ush3XTTvvfjXvC/53swftnL4H/v9wLnjoGDTmlnWSS219bWDvU4Yy4/inI7J1sta1pTsUCK6ucWrqgahJLbsiznFvFIepOEnie0l9WSUGI7DEOxrZQaN01TDLQl2e6fk+/ZlHgYhphMJkK8FxkOh+j3+0JWlw2INE0TtVpNnE/tdhs7Ozu57R8Oh+K6WKTf78+co9T3fxCLXJ7nwfM8MTS3uqSSBAAnt5kDh+U2wzAMwzAMwzDMYZOmQEFEw7aFhNwLWely/iXPS1lKLWdTfp7nHYp0pDR0UbYD5xOCxdv+B4OBSJ7v7OxgZ2cHvu9D07RcGp26c+m16DNRFy6J8yiKcn23pmliY2MD9XodjUZDyOnicEtaELBtu7SCJI5jsa2E1O/D/NCHYH3wgzA+8QlIJfUrFwr3B38Q45e+FOH97id+dhgp7Sy0MMFim1mV4jGRu3ZJ0jS9vbMz9/mG64o7OOgaQDUjdC2gv4+iCLqui+Q2ka0AWSa3qW8bmIpu+ntaMKL3p0UjGjaZ/byapolhs81mU7yG53kYjUbY2dnJCffs8w3DmOnqp8c0m010u93cz/v9PtbX13OvQYN2i59zbW1tV4Mo55GmKYbDIcIwFOnt6pe+tPhJJ08Cx47t+70ZJgvLbYZhGIZhGIZhmMNmZwfY3Mz/bGsL2NjY80sWpYWiKDPpXMMwZuR2rTBUcL/EcSwS2EVoeGOxQ3Y0Gonb8IfDIc6cOQPXdYWQAs7LIqoVyb5GFEVCZsmyjMFgIKSXoihoNBpotVowDAOyLGNnZwdpmpaKnmq1imazOSOR0jSF4zgYDofT9xoMYH74w7A+8IGp0F526/0hkqoq3Kc/HeOXvATRXe4C4HBT2rn3Pie2s7IfYLHNLKZ4TFLyWcjYZnOh3FbGYzEokp4TRREMw0CSJLk+7SAIxLWkLLldNqixTG4HQYAgCJAkiTiuaUCk67oIwzBX5VGU24Tnedje3oZt2+J1aZuzaJoGXddRr9cXnsOmaaJer+fuzMkOmJRlubQ+SZKkA60LosGX4/FYLBjUbrhh8ZM4tc0cAiy3GYZhGIZhGIZhLjPKRK1lWTMS2TTNnOAIw1AMRjsIwjBEt9udkTQAUKvVSkX6ZDLBaDRCkiSiimQ0GkHXdZHIrtfrIkVNvbZUMRCGYS69SWKF9kGj0RDCK5tup25bQlEUbGxsYKNkgYEGtUXd7lRof/CDMK69FlKJwL+QRLe/Pbwf/EGMf/InkRw/DmAq1CqVyqGltLNQfUyZ2G632yy2mblQpUhxqKQQrUt6t+XhUAjrbM91mqZI01TI7WxNCd31QQthq8ptunaQ3M5uPyWy+/2+SIoDs8nt7DWWridnz54V52pZB/aRI0dWHuZYrVYRhmHu34EoitDv92EYhhjwSJDYPqiFryiKcPbs2dy/L+rZszDOnl38RJbbzCHAcpthGIZhGIZhGOYyg/pgs5QNAyMZlJU5vu+XdkrvFuq6zlaIAFOJ0mw2S7fH8zwMBgPRzzocDtHr9aAoCnzfF+Kdqkk0TUOj0UCSJBiPx0JUKYqCMAyFZKW+WV3XxaBIGkppGIaoLqABkpRwbrfbue1L0xSj06cRv+99qH7wgzA//nFIheqNC0V0+9sjvNe9EF51FYJ73xvhve+NtNUCMN3H9gVIaWchsV1cVDloacbcdtF1Pbcwkks+N5uLnzwYiJ794oBIWgSjOzWylUUAxFDJeXJbluXcwiAtglHKOvsYy7LEsMmswM5Kd2BaERWGIcbjce6uFvozPZYWp2q12spim2g2m2JB8Pxuml5fiz3fzWaztNN7L6Rpim9/+9s5sS1JEhpf/vLyJ/MwSeYQYLnNMAzDMAzDMAxzmVEUjJQmLCJJEgzDyD3e87x9y+3RaDSTDATODyor25YgCNDr9RCGIYbDYW74ZBiGiKIIsiyjXq+j1WqJ7lzqpaX0tmVZcF1XDHCjqgJJkpAkCSqViqgjcBwHjuOI1KVlWbAsSwgysZ3jMYL3vAfJ3/0dah/96AUX2tEd7oDgqqsQnpPY4b3uhbRE9l3IlHaWRWJ7bW2NxTazEpqm5eR2rspoSXJbGg6F3KbENA2PLL5Wmqa5VDjJbUp4r9K3DUyvs0mSiPeUZRm2bSOKonylCvKVJHEcI4qimTtpsp/bdV20Wi1Uq1VIkrSnc4gWlra3t0XafDQaiRQ5yexGo1G62LgX0jTFrbfemqtEAc4NvlzWt63rwH3ucyDbwTBZWG4zDMMwDMMwDMMcNu028M1vzv5sD8yrJJmHaZq5x/u+L27T38t7l0lOYJrKbLfbpdKV6ktc18V4PM6lvj3PQxRFosu23W6Lz0jpSBLXSZJgMBggjmMYhiGkEImnarU6894kxGlwJGGnKfDOdyL9u78D/vEfoZd8poMmlSSkd7kLwnvfG/697oXgXveaiux6fe5zaPsty7ootR80LJQT28x+KRsqKa5FS5Lb8mgkuvdpoQuYTWUD02MzDENxbSj2bhfldrGmKQgC0bkfx7EQ47quQ9M0sRhH8liSJFGBQl3cdG7U63W4ritSznQ+A9OFRhLmez2PFEVBq9XC1taWmA8ATBcg6e+KKe69kiQJtre30el0ZrZhbW0N9he/uPgF7n9/4IDS4wyTheU2wzAMwzAMwzDMYaMowO1vfyAv5XneTBXIIrldvBWduqd3ewt8HMfodrszXbHA9Bb8RqNRKszpeePxGJPJBEEQoN/v50SQruswDAO1Wg2KosBxHDHEjd4vSRLxc2AqtUzTRJqmsG1bCJw4joWQsixLCC4AkFwXxsc+BuuDH4T50Y8CjoPdK/4VkSTgu74L6f3vj/Cqq+Df856Y3OUuSFYQTZQyN01TdAg7jgNZlmGa5gWV3IPBAI7j5H5GYvugag6Y7wyKAjdNUyGnV+ncJqlNg2OpakhV1VK5DaB0qOSi5Dalsqmvn+pN0jSFZVlQVVUMwyUpTs+n1DQtyNG22LYNwzDEdSk75NdxHIRhiM3iwOFdoCgKoijKfS6qTjkosR1FEbrdLgaDQe59JEnCiRMnIEcR9C98YfGLcN82c0iw3GYYhmEYhmEYhrmMKIpGulV/HrIsQ9f13G37u5XbQRCg2+2WDmJrNBpzBUqSJOh0OmIIYRiGoprE9334vg9N06DrOmzbFrfTr6+vI4oiTCYTkaCcTCai19YwDCHKbNuGpmkIgkCIpGq1KgZOJr4P4+Mfh/Xe98L8yEcgF/bfQZHKMqRHPQp40pOQ3v/+CO5+d7iKAs/zSvdbEfqeSIxR2r24kDEajUTH+GGnufv9Pott5sDIDoYlwjCcHsNLktvSuRoMwzDgOE4uQa3ruhDl2SoSEtNZmUyLX8XtIqiSZDQaiY5+ksdUaUSJaxLYJNDpXM32b9MdJZVKRdz50u12c++fpik6nQ6azeaeFx0Nw4BpmqL2xTAMWJaFXq+Hdru9pzt1CLr+U50KIcsyNjY20Gw20fvIRyAVBs3OwHKbOSRYbjMMwzAMwzAMw1wmxHEs5AuxSn+2aZo5ue15HhpLkpKE4zgYDAYzklWWZbRarbmSM01T7OzsoNPpIAgCRFGEXq8n+rIVRYGiKNB1HaZpIooitNtt2LadGy5JaW2S39SxTbfzq6o6k3RO4hjpZz6D2nvfC+v974dckEkHRSrLiB/2MCjPeQ6kpz8dQbMJ13WnXb0r9HbTZ6TFCW+ZHDpHFEUYj8cYj8eHJrrnJbYXfecMswxd13OCVNwJskJyG4AYGqkoiujQBjAjt+nPlPCm+pNlyW26Tk4mE9G3DZyfa1A2TLJYi0LXp1qtJmYAAOcXhiaTiUh/0/OTJEG320WlUkG9Xl9JRtNzSN5Xq1Uh5Gu1GiRJgu/7GA6HK1/vi3ieh16vJ4b6Zj9js9nE+vr69D0//enlL8bDJJlDguU2wzAMwzAMwzDMZUJZ7/EqST/TNHMDwOI4Pp+YnEOaphiNRjmhQaiqina7nRuiVnzuzs4Otre3EUUR4jhGv9/HcDjMJS1VVRW/bzQaqFarcBwHQRCIZDdVcei6LupX0jQVn9swDNG/rXzjG7Df+15Y73kP1JtuWrpf9kIqSQge8hC4T3oS1Gc+E9U73xme500/287O/OedG3JH8omGYQKYSZLuhsMQ3YPBQHQEEyS2d5ssZZgsmqblrmNi0W1JclsZjyFhKscpGZ1NTGdFtyRJ4nwjsZzt5p4nt6myiTr/s3LbMAyoqjrTty3LMlRVzb2moiio1+uo1Wozn4MW6JrNJkaj0flalnNQdVOr1Zp7faXXKdZEkTyn/ZF9TU3Tdj1IODv0l+68AabX/0ajgUajIWpa9OuuW/xiV1wBnDixq/dnmFVhuc0wDMMwDMMwDHOZUDZIcpWEn6qqoqaD8DxvrgBNkgS9Xm8mJQ5MJU+r1SodHEl0Oh2cPXtWiKRer4edc+LXNE0oiiIqSVRVRb1ehyzL6Pf74j1JfkuSJLqz6fnr6+uo1WrTOpJTp5D8zd9Aufpq6J/97NJ9sRdSSULwoAfB/aEfgveEJyA5cgSNRkPc9l82YJMWEKi/l+pUioMtV0FV1VwNwzwOQnQPh0MW28yhUTwWqT5EWpIslsIQqePAOHf9ILlNIpdeRzz+XLUPSeis3C7ehZIdTpkkiRC51PtPwyRVVRXym55D/1uU2/PENL2HqqpoNpsYj8elgza3t7fRaDRKhXSapuj1erm7cYDpdWJtbQ1xHKPT6eQ+52AwEIuJqzAcDsXCJs07ACCGZGqaJgb4+r6P2rJr70MfOp1DwDCHAMtthmEYhmEYhmGYywAacJZl0SDJIoZhzMjtsmQhDQ4rk6jValXc7j6PnZ0dnD59Gmmais7tra0tKIoixHYURSJ1btu26JGmig4SRaqqwrZtIbLW1tawubkJNQiA974XePvbYXzoQ8AC4bsfwgc+EM6TngT3iU9EcuwYgHOit9mEJEnY3t4WaVH6fkhmkxgzDEN8hlWQJEn0kNOv7HPDMITruvA878BFd1ZoZbdnL13ADFNG8fijhLW+JLkNAPJoBLVeh6Io0DRNJLfpHCwOOqShs8D5uyPK7pKg84sW1rLnFlWg0EIc3QFD8poqRegXDaQMgkA8N9vBnRXStGhUrVZnqp+onzsIgplhvYPBYKbCSFEUtNttcQ1tNBro9/u51+v1elhfX184o4HeN7tgRxUtpmmiWq1CkiSxTWmaIjx1Cuq3vjX3NQFw3zZzqLDcZhiGYRiGYRiGOWy2t4HNzfzPtraAjY2VX6KYDlYUZVfdx6Zp5hK5VJGRFR2+74t+1SwkM5bd1r6zs4NTp04BmEqS7e1tbG9vC0lN76uqqhhCSbe967ou0sm0vSTDbdvG0Y0N2J/+NPCqVwHvfjcwGq382XfFQx6C+OlPR+/Rj0Zw5Ejur2RZRqPRgOd5cF1XDMYMgkBIM1VVYVnW0kGfBPWO0+fXNG3h4gE9pl6vH6jonldB02w2d7WIwjCLoBqP7PEahiH0FTqh5eEQ0okTQjTTeULd2sVzIEkSIYzLBHh2m4Dp9Y+S23Ec57qy6T2LwyRN04TrumLwLXVyj0aj3PWWBlOOx2OEYSj+TAtfjUYDw+FQ1BYRVNPUarWgaRqGw+FMF74syzM1UbZtIwzD3DbEcYxer4e1tbXSa0zZHTtBEMDzPFQqFXENp+sbMP3ulP/4j5JvqwDLbeYQYbnNMAzDMAzDMAxziUMdsFl2KxwpAZyVO77vC2GR7VfNQuJk0e3s1LF96623ApjKpq2tLXS7XSGy4zhGFEWoVCqQJAlBEAjxlO2zVRQFlmXBtm1YloXaN76B5j/8A5SrrwZOn97VZ16ZBz0IeOYzgWc8A+EVV6DT6cxIMBJROzs7cF03J7SB6X6qVCoLE84kybLJ7FUE+Dz2K7ppXwMoFdutVovFNnPgaJo2I7eXdW4D0+R2nCTiWkZCm6pGisnt7M8W9dpTvQl1/VMaXFEU0Y+v6zqSJBGLc4RhGBgOh2JoZbYPPAtVp1AKurid9Jii/Kb3H4/HsG27dOGRxHeRer2OKIpElQr9O9LpdFCv18X+ob9zHCd3d1CapphMJqjVauK6Jssy6vW6eIzv+8v7tlUVuP/9Fz+GYfYBy22GYRiGYRiGYZhLnKJIBbDr4WCSJMEwjJwk9zwPlmVhMBjMpAGBqYSiW93nkaYptra2cPbsWSGIOp1OTmxTZQf1TRcFCtULmKaJer2O+mCA2jveAfu974V64427+pwr84AHCKGNO9wBwFTUdHd2Zjp54ziG7/u5GpIshmGgWq3OCC2SYtlk9m77tldlL6I7juNSqQ1wYps5PHRdz12HwjAEVkxuB3EMwzCE3AbyqewkSXLnYRRFucGTxfOP5DEJ4OydGNSzLUkSdF2H53m5vm0aCpvt8aZkehllwyyzj5UkCbVaDb7vYzwez5y7o9EIhmGIHnAaxOu6rkiNZ2U1Ddnsdrsz163BYLD0/KbEdnZhs1arzdztU1smt+9zH4CvJcwhwnKbYRiGYRiGYRjmEqconukW+d1Ct9ATruuKwYdFLMtC81y39DySJMHW1ha2t7fF0LHhcIhOpyOqSHzfh+d50HUdpmkKCUS926qqwjAMrCUJNv/lX1B93/ug/9//C6kgmA+E7/ou4LnPBZ7zHOBOd8r9leu66Pf7YvvCMEQQBKJyoAxZllGtVsUt+vRZKJm9l+/oINiL6M7SbDZ3vXjCMKtSNkAxbTaxbNlHGo2QJIm404MEN8ll6rqnJDYtpNEdKzRUMku2kiQ7BFaSJJGeTtMUmqaJ6zDJ3eywSrpG0DWNXjcrs4vX2XkinD7fcDicOWd93xe1IbVaTXR8L6Jer+eubcD0Th2qRJpH8c4STdNy14UkSRC6LrTrr1/4/njoQxf/PcPsE5bbDMMwDMMwDMMwh02rBXzpS7M/WwHqgM2yV/GY7eiOogjD4RDVanVGcNRqtdJhk1miKML29jY6nQ6CIIDjOHAcR4ht0zQxGo1EYrvZbELXdQwGA0RRBCMMsf6f/4krv/IVrF9/PfT//M89faalHDkyldnPex5wv/sBJbKeKllIaJPoCoJgbtqa0tq6rsOyLJimuXBY48Vit6J7lW51htkPdE5lZWuYptCrVWDOnQQAIJ8bumgYRq62A4CQ19mKDxLfJJrjOF4ot2nYI0loSnWThKbrMAlf27aFXCaJTQMda7UaKpWKSE9TnzWlq5Nz9So0kLKYrFYUBc1mE5PJZKaSCpgO9111yKuqqqjVamIYJu2f0WiEZrM5c2dOts88S3GwZRAEUL78Zcgld/3k4L5t5pBhuc0wDMMwDMMwDHPYqCpwz3vu6al0KzwhSdKe6yKoJmM0GmE0GokaEZLbkiStVEcRBAF2dnbQ7XYxmUzgeZ6oIyExQklBwzDQarWgSxK0f/933Pmzn8WRL34Rra98BfKCHtx9YdvAD//wVGg/+tHT/T+HbreLTqcjhDYAkd6kGpUssiyj2Wyi2WxeskJ7HotE96pDQxlmv1C6OZtkDoIAerO5UG5Lw6GoMaK7V6h3mwQxnbfZwYwknssWdCjVHYahuNZS97+qqiIprigKPM8TwhuAuDMlK7epVz87jJLS2bIs566t9Xod1WoVAHLSm2R4HMeoVqvirhK6PtFA2N1gGAZs2xbpcxqK6TgOWq2WWCigPvN+v597frGeBJj+27S0bxtguc0cOiy3GYZhGIZhGIZhLmGKqT3qm90rlNgmKK2oKAra7fZSWeu6Lnq9HrrdrkhhB0GA7e1tIYbCMASSBEd3dnCHb34Ta5/7HFpf/CLUkgTigSHLwGMfOxXaT30qcE4alRGGIRzHwc7OTq5zOju4syh5FUVBvV7H5ubmyonJS5ms6CYRuJ/jimF2g6ZpObkterdvuWXuc6TMwFuq7iCBHUURFEWZponPJbYJOr7L+vKpb5vEOCXAKa0dRRF0XReVJ9nrI9U8ZTu3qRalmIYmgZ4lK4spia4oysw1uNFoYGNjQ9wJQ+cqVaeU/XneY3q9nqg1yX4XrXN3EtEMheI+KruTx/d91D772Zmf59jcFDMNGOawYLnNMAzDMAzDMAxziUKDDLPsNbWdpin6/f6MYKHb9tfX1xcOjgSA8XiM4XCI7e1tDM5VBIRhiLNnzyKKIlR3dnD0S1/C8S9/GUf/8z9hZST6oXH/+0+F9rOfDRw9OvdhcRyLlHkYhhiNRrl9S8LbMAwhrxVFgWEYsCwLa2trt9kBi8u+d4Y5aMp6t9FsLnyONBqJ31O3PR27NEixLJ2dJMmM8CYURcn1WJOopuQ21SrRohe9HyXHs5Ui9BiS0Fl5TYuI4rOcS3ivCtWU7JdWq4WdnZ3cfnJdF5qmoVqtYjQazeynRqMxs/AVRdF06Oay5PZDHlJaBcUwBwnLbYZhGIZhGIZhmEuUYmpbluU9pYbjOEa3283dbk9ywzRN2La9UHCmaYrhcIjxeIytrS2R/I7OnIH2L/+CB9xwA6648UbUt7d3vW174uTJqdB+7nOBu9996cOpMoVu/R8Oh0Lyp2kKx3EQhiEsy4Jt2zAMQyRDTdNEo9FgAcwwB0ix4iKKIqT1+sKhktS5DUBUhVAimdLZxeGOwPnKD/p9tmpIlmW4rivkNl0Xs4MedV0Xd3iU9W1T6pteW1EUDIdDWJYlpHBRbs/r8j9sZFlGu93Gzs5ObtglXdMnk0nu8bS4V8T3fUjdLtRvfGPxG/IwSeYCwHKbYRiGYRiGYRjmEsUpDOoq64BeRhAE6Ha7OZGhado0aV2twrKsmXR4Fkp8TyYTbJ86BeXaa3H7z3wGzeuuQ+Ob39zdB9oPzSbwzGcCz38+8D3fM60hWQH6/CS4qEoFOJ/WliQJ6+vrqNVquX7cRqNxm01rM8zFhCpFsvMEknodi5aQpOEQkiSJHuzswMds5zbVimRlMyWpoyjKJaaTJBG92QBE7QelsmlOAV0ji3KbFskoHU7vl6YpBoOBqPsoyu2i3L+QqKqKZrOJbreb+/mwcKcN9fCX4fs+9M9/fvmbcd82cwFguc0wDMMwDMMwDHMJQkMNs+xWtDqOI+pDspimCV3XhWAJwxBxHJf2xHa7XXj9PtI//VPc861vhZ7pvT10dB140pOmKe0nPAEwjF09PQxDIfapa5xqB0hW1Wq1ma5xy7JKb8VnGOZgoFqOrPRNarWFclseDoXIVlVVDJSkO1HSNEUcxwjDEJVKRdypQj8HpnexZM/1KIpyi3vU2U2VJLTYRUNX6ZpQqVQQBIHo6aZrLHV1A9M7byzLgmEYC/u2LwamaaJer88I7SyVSiWXYCfo+lldVkkiy8ADHrDfTWWYpbDcZhiGYRiGYRiGOWy2t4Hb3z7/s5tuAjY25j6lmNqm/udVSNMUo9EoNyyRUFUVGxsb6HQ6uTS37/u5IYpxHGPn7FlIb3871l//epiFIWOHRappiB/yEEQ/8iOIn/Y0SO32VCoBkIIgNyRtkXyOogjdbhdRFMF1XbiuKwRUmqYwTVOkszmtzTAXnqLcjqpVLGqhlsdjMRhSVVVRTUKLciS2gyBAvV6H7/viLhW61hX7pMMwFHKb7u4g+Z0kCSzLQhiGSNNUXCfovR3HEVKderoVRcldlwaDAZrN5swC48WW2wBQrVYRhuFM/RUw/fembIgkMF0ASNMU2rJhklddtXCwL8McFCy3GYZhGIZhGIZhLgQFWb2INE1nhENWPC8iSRL0er3SqhHDMNBqtSDLMgzDyL2H53niPSbjMQZvfzvav//7MJd1qh4A4T3vCf/hD4f/iEcgePCDkWY/a7+/8LlF2U21Bf1+H47jCBEDTNOiuq5DlmUoipLr0ua0NsNcWIoDFaNKZeHjldFIyG0AohefzlmqJqE6kSwkrrN3w9B1ll6PEti0XXEc566TdK3QdV2kxUlukxQvyu04jtHpdGY+96VynWk2m7l6FaLRaMytwPJ9H0gS6J/73OIX50oS5gLBcpthGIZhGIZhGOYSw/f9XKoaWK2ShERKsc4EmKb0arWaEBamaebktuu6GI1GcD/8YVR++7dxxSp9qnskvPJKBN/7vfAf/nAED3sYkrW1Pb9WcT/FcYytrS1MJpNcWlJVVVTPpQhVVRUim9PaDHNxKKaX4zlJYUIZj3MVIyS3AQjpnSSJELW06AVMF8Fo+KN4v/+fvfcOk+Qsz73vylWdu2d2V6uASJIMRgKESCYnY+AQDuEcgZCRCcbggAXGYBsb8EH+DAjbYBDGYAwim2CQETmDMQZMEEgggYhCYXemY3V35fr+6H3eraquTjM9cZ/fdfU1MzXVlbr6rar7vd/7CcNUJyAVpSQRO45j4dAGjovbxWJRrIuWmcz3zsY7dTodFAoFIZrvBtc2IUmSKDBJx8ayrKmFi13XhfqjH0Hu9aYvnItJMtsEi9sMwzAMwzAMwzC7jKxrm5yC06B87KywTUXBss5vwzAQxzE8z4PjOJCvvhrV178eB7/4xeXsRAK/Xod9z3vCvsc9YN/zniidffaYALRZyIV55MiRMReioigoHnOFmqaJYrEIWZbZrc0wOwgVYKROqKhSmTq/OhggOhYRAkDEklAnFYnMvu/D9/2UM5z+nxSiPc8bayuSLnASq6lNpTa4UCgIcZtc2/RecpIn9ysIAti2jVqtJkaP7CYURcGBAwfQ7/chy/LUUUIU/VKYFUkCsHOb2TZY3GYYhmEYhmEYhtlqajXg618fn5ZDFEVwHCc1bZarOI5jtFqtXKGm0WiMiSme52EwGKDX6yH6yU9w0hvfiPqVV0LK5MJulKhYhHeve8G9733ROvdcdE47bVRcDBBD97NQgTlVVUWGLQlH2d+zuK4L27bR7XbHxH1ZllEqlWCaJgqFgihCV61Wp7oTGYbZWkjoFZnXM8RtAJB6PeBYRxW1FySSAxDituu6KBaLoj2QZVmsJwgCaJoG13VTTm7KzQZGIi6J1DQPideGYQjHNkWhkEtckiSoqopyuSzaoyiKEEURhsMhCoXCrhO3gdG+TcrYTkLHUJtVTLLRAM44YxmbxjAzYXGbYRiGYRiGYRhmq9E04O53n2tWx3FSAq4kSVPFbRK2sxnbqqpiZWUlJdYMBgMMh0N4nofolluw+vd/j8a//RvkjCi+KLGmwTv33FFm9n3vC+8udwE0bVTYstkEEtEhuq4LITv5UlV1YsZrdn/pNRwO0e12Rc62ruvQjq2XWFlZQblcTuXllkoldmszzC6ARGYAiOYQV+NWS4jbwPFRLZSBHYahyJBWVRWe56X+R7EmqqpiOBym3N1xHKec26qqig41cm1TezUYDFLubRLYZVmGpmkoFouikC0xGAxQKBSWPmplO6HPSp/l3L7XvYA52nOGWQYsbjMMwzAMwzDMCQxlO5umOZewyGw92UgSwzCmCrGdTmfM6a0oChqNBmRZRrfbRa/Xw2AwGLkIOx2svP3tOHD55VAWKHKZxTv1VLiPfCQ8KgKZUwyOijmS+KRpGk4++WQYhrHh802SJPi+j263K5ZP+590RJqmiVNPPVXEkTAMs/tIicvV6sz5pW4XAETRSIomSeZkU6FHigZJOrtJ5KZIElo/RZUQYRiiWCyKtoWWTznfFHFCAjcAEY9CHXi1Wi1VTDLZVu1F4jiG67qQul2o1103fWaOJGG2ERa3GYZhGIZhGOYEJI5jtNttIaQqioJ6vb4rh0ufSGQLnAHTI0m63a4odkZQVuwvfvEL4S4EAMn3sfKBD+DgP/8ztFZrw9sYHDiA3vOfj+GTnzxypGdIurH7/b4QeoCR+LyZKBDf99Hr9YRAFMcxbNtOHTMqHHnKKafMzClnGGZnSYrb8zi30W5DUZQxcTsZIUJRIckCkSROk7idl8ufFLfJuU2xJvR+ao9pOeQGJ2E7uS5N01KxK8CozSIH917D931EUQTjO9+ZHWHFxSSZbYSv9AzDMAzDMAxzgkExFkkHWRiGWFtbQ7lcRqlUYhf3DpEVqmVZnigG9/t92LY9Ni27DEQRah//OE667DIYv/rVhrctLJfR/b3fg/O7v4v4mDBDbmyKA9E0LZV9S5EhxKzs8EkEQYBerzfmardtO+WsLBaLsCwLKysrLGwzzB6ACjBGUTSXcxudjpgfGI3QIFGZplNBScrWpjaIxO8gCDAYDFIjYgzDQL/fBwCxbFVVU+2LqqqiPU5mbk8St8MwhGEYGA6HQiTXNA3dbleI8nuJufO2JWnuGC6GWQZ8tWcYhmEYhmGYE4g4jtFsNsfcwUSv14PruqjX63vuwXs/kBVvLcvK7WgYDofodDri7ziO0el0MBwOj4u6cYzSV76Ck173OhR/9KMNb1Ok62g+5SlwL74Y0uoqFEVBuVwWotIkstnhABZ2bYdhKCJVspCwrSgKCoWCiG9pNBopNyjDMLsbyt2OTROxqkLKFIVNcUzcphEpVKCWnNeUv0+xI9mikpTH7TgODMMQizUMQ7i5yRUOQKxHURTRiUeidvJFedtJcdvzPEiShFKphHa7LQpSRlGETqeDRqOx9GO5lcydt33HOwLzdFQwzJJgcZthGIZhGIZhThBmCduE53k4evQoqtXqhp22zOJ4nidEGCLv+DuOg3a7Lf6O4xhra2vwPE/Eyhjf/jYOv/a1qH7nOxvenliW0XzMY9D6oz+CdeaZUBQFpVIJxWJxLmd/Nlt2EadiGIawbRuDwWBMIAdGDnfXdVEqlURevCRJaDQaHK3DMHsMEd0hSYgqFSjN5sR55V4POObABiCK05JzG4BwZ3ueh1qtlnJNh2EoOt6oE4yiS8ixHYahWBZldtP7aRnJ4pTA8bxtKo4LjNp0ep9pmmL5wKh9dBxnUzFN2wl1GCCOZ4vbHEnCbDMsbjMMwzAMwzDMCUAURWg2m+Jhm5BlGZZljYmIURSh1WrBdV1Uq1WOKdksa2vAHe6QnvaDHwCrq+LPrGtbVdUxodbzPLRaLfFZRVGEW265BUEQwDRNaNdfjwP/8A848OUvb2pzj973vli/+GIoZ58tBO1SqTTVqZ0kiqIxcXuejpIoimDbNvr9fq6oDRwXzRuNRipuoF6vp5yYDMPsDVJFJSsVYIq4rXS7CIGUUGyapog3AY4XlSSHNTmmDcMQgnShUBCidaFQSLVXURRBURTRBiXFbVVVMRgMRBwJbQd1sGWd20SpVBrrWO50OtB1fe52dSehbVd+8hPIic7VXLiYJLPNsLjNMAzDMAzDMPucacI2OV0ty0Kr1RIuNGIwGMDzPNTrdY562AxxPBK4s9PEr3FuJEkS3/fRbDaF4OL7Pm6++WbEcYxiHGP10ktx6D3vgZz5DBdh7dd/HT999rMxvPOdceqpp6LRaKBcLi8cUeO6bkqcliQp16EYxzE8z4PneXBdF77vTxS1adh/nhhUq9X2jAOSYZg0qaKSlcrUeWXbRpAQlYHjo0KonYqiSIjbQRCIuJAgCHI72crlMo4cOSL+DsMQuq6L66GqqkIcB9J522EYpopRJjPEk0UrJUnCysqKyPWm9XS7XdRqtXkP1Y4hIklm5W0D7Nxmth0WtxmGYRiGYRhmHxNFEdbX11MP2cBI2F5ZWRGigq7rOHDggMhtThIEAdbW1lCpVFAsFrdt208kXNdNiTVAWtwOwxDNZlPMMxwOcfPNN0MCcPirX8XJl14KIyHOLErn1rfGDy68EPb97gfdMNBoNHDw4EGUSqUNLS97DlEedhzH8H0frusKUXuSmE1IkoRCoQBVVdE5lrebpFarcXwOw+xhSJgOwxBxuTx93l5PuKYJwzCgqqroACPhOQgCBEEwMxKpWCyKzl9atqqquXnbAEQsCeVtAxDtEo22yV5zJUlCpVIRsSjEYDCAZVm7ftTJ3HnblQrwa7+2DVvEMMdhcZthGIZhGIZh9ikkiGYfshVFyS26J8uyiHbodDop8YAKFrqui1qttieGUe8lsmKwrusit5U6KEho6fV6uOWWW1D81a9w+9e+FtX//u8Nr7d/8CCuu/BCtB/xCMSShHKxiIMHD8IwjDEX/7xEUSSEEIoHUFUV6+vrc4nZhCRJsCwL5XIZvu+j1WqNzVOpVFAoFDa0nQzD7B5EocYZhQgV2xYFHOM4hiRJovOMXNOSJInOM3JrTxK3qTBuUtymeJFkIUpN04RwnXVuU942zQdgbKSUpmmQJAnVanVsZEun08GBAwd2bfyX7/viejDTuX3PewJ8f8BsM/tS3P7FL36Ba665BjfffDOiKMKhQ4dwxhln4Mwzz1zaOq666ir87Gc/wy233ALLsnDo0CGcc845OHTo0NLWwTAMwzAMwzAbJQxDrK+vjxUoVBQFKysrQjjNo1AoQNd1tFqtMWHccRwcPXoUtVpt1zvNdhXVKvD5z49Pw/R8aioCGgQB4jhGq9VC61e/wq3f9S6c+t73Qs58PvPiVCq47v/8H9zwqEfBqlZRLpfRaDRgGIYQWBzHQXWG0JRHr9dDv9+H7/tiu1VVHTsXJ0ERJuVyGaqqwnXdVM44US6XN+wsZxhmd6Hr+qjQ4xzObYoCCcNQCNq6rouikpIkIQgC0QaR8J1HuVzGcDhMFZOkIpJBEIhlUjFJ4Li4nZyXxG26LmbFbRLGFUVBpVJBp9MR/wuCAL1eD5UZkSw7BXVWSv0+1B/+cPrMHEnC7ADbJm73+31cc801uOqqq3DVVVfhe9/7Hn71q1+J/59yyin43Oc+t6l1fPGLX8Qb3/hGfPvb3879/1lnnYVnPvOZeMxjHrOh5UdRhHe84x14xzvegV/+8pdj/5dlGfe+973xx3/8xzjnnHM2tA6GYRiGYRiG2SybEbYJVVWxurqKXq8H27Zzl18qlVAul3et22xXoevAAx+Y+y/HccbyqS3LEsI2uZ2P3HILtI9/HHf/x3+EecstG9oM3zTxo8c+Fj/73/8bOCYONxoN3OpWt4JlWTh69KiYNwxD+L4/M2s9CAIRM0JCdFLYSQrmk9A0DYZhQNf1VKa253mpnHGCzj2GYfYH1M7MytxWbBtxHItca8I0TeGOliRJ5G2TwzpbnBc4HhXS6XSEM5mc22J9iiIEdBLUybFNESYUh0LxKlRLIEly/YVCAcPhMDVPv9+HZVm7srYFidvad78LKROfNQYXk2R2gC0Xt//1X/8VH/rQh/DjH/94LENuWcRxjL/5m7/B5ZdfPnW+a6+9Fi984QvxhS98AX/7t3+b27hNotVq4Y//+I/xta99beI8URThP//zP/H1r38dz3/+8/H0pz997uUzDMMwDMMwzDIIgiAVYUGoqoqVlZWFCgPSg79hGGi1WmP387Ztw/M81Gq1uQRzJp/BYJD6m4bYt1otuK47ipf55jdxq1e9CitTnkemEakqfvywh+H6//t/ER47DxqNBmq1Gk477TQR7ZF1WDuOkxJbKGYkmZudPNcoUzu7P1loiD8J2nkxN9kCmkShUNi1DkeGYTbGvOK2atsiaiTZ9iRzt4HjbRWJ3KZpjrVvVEz5pptuEu0MxYzQ34qiCNc2iea0XhqZQq5tErfzCuMm9SeKJ1lbWxPzUfTXysrKruowTgr1cxWTvOc9t3iLGGacLb8D/cY3voHrrrtuS9fxmte8ZkzYPvfcc3H22WdDURRce+21+OpXvyoajSuvvBKKouDVr371XMv3fR9/+Id/iG984xtimqqqeMADHoDb3e526Pf7+OY3v4lrr71WzP/KV74S5XIZT3rSk5a0lwzDMAzDMAwznWUK20kMw8CBAwfQbreFg4vwPA9ra2uoVqtc1G8DBEEw5vArFAqisKff60F69atxp8svh7KBCJJYknDD/e+Pa84/H/6pp45c4aaJRqOBQqGAW9/61inx2TAMIViHYSgya+nvWTnceS50yg8nIZvE+1nHZX19PbfI5kaiUhiG2d1QdEg8S9zu94UAnRWqk0UlKZKEXrT85HuKxSJkWRY1D+I4Fk5sanuyxSSDIBD/o5/kFidxOy9vO9vmaZqGUqmEXq8npnmeh8FgsKsKNyfrJGizikmedRbQaGzDVjFMmh2xVxQKBfz6r/86rr766jGXwqJ8/vOfx5vf/Gbxd6VSwete9zrcO5Pzc8011+A5z3kObr75ZgDAFVdcgbvd7W44//zzZ67j7/7u71LC9plnnok3vvGNOPXUU1PzXXHFFfjzP/9z4VR4+ctfjnPOOQdnnXXWhvePYRiGYRiGYebB9/1cMVDTNKysrGy6ACRFmti2jV6vlxIwoygSLuNqtbqrXGe7nWwhSSps1u/3gY99DAdf+lJYN964oWWv3/72+PaznoXBr/2ayKQtFAooFoswTROnnHKKiBQhAXswGKDdbqeWQ0Py54FEHXI7VioVHDx4cKGOlUnCtmmaqNVqfH4xzD5F0zREM+KGVNtG4PvCRU2QuK0oSiqahERuYJSvnXRyVyqVVAcjdeAVi0XR/qiqClVVx/K26XfK+KZ588TtSakBpVIJw+EwJbh3u12YprnhzuhlI+pBxDH0WeI2R5IwO8SWi9uGYeCcc87B2WefjTvd6U44++yzcbvb3Q6yLOPBD37wpsTtOI7xd3/3d+JvSZJw2WWX4e53v/vYvHe84x3xtre9DY997GOF2+T1r389Hve4x8E0zYnruPnmm/HOd75T/L2ysoLLL78c9Xp9bN7HPOYxiKIIL3rRiwCMHjBe+9rX4rLLLtvwPjIMwzAMwzDMLLZa2E5SKpVETEk203swGMDzPNTr9V2ZG7obyYrbcRxj+MMfovznf47yZz+7oWW65TK+d8EF+MkDHoAIgOb7wgkYRRE8z8Pq6iq63e7Ye0nITp5LnudNfWYCjufSGoaBUqkkhJl6vb6QSBOGIZrN5phD3DAM1Ot1FrYZZh+jaRq8GSMz5CBAPBym3NXASA+iaBISnD3PSzm4qR0kd7ZlWRgOh6m8bSqAG0WR6KSTJElc07KxJADENXZRcVuSJNRqNaytrYlpcRyj3W5jZWVl7uO2lZB+pvziF1AS25kLF5NkdogtF7f//u//fsuW/ZnPfCYVefLYxz42V9gmbnOb2+AZz3iGEJuPHj2K97///bjwwgsnvuctb3lLqmF6wQtekCtsE4973OPwgQ98QDi9P/vZz+KHP/whfu3Xfm3u/WIYhmEYhmGYeaGCe1lhW9d1NBqNpQrbhKZpQhzNmlWCIMDa2hrKx4oVbhYq3EWv7N/kICfRkxx7y/qdXHtbAUV+EG63i9pb34rqP/4jZHLLLUAsSfjJgx+M7z/lKXCKReEqpIzscrkMy7Jw+PDhiecFxYg4ifXnids0VJ+iRlRVRb/fT8XWyLKcm7c9iSiKcguh0rnMwjbD7G90XYczR6FYudtFHMe5nWAUTSJJkmj7yMG9urqKKIrg+z4KhQJ0XUe73RbLSV5TAKTEbboO5Dm3qT3VdT0VW5Lcr2n7XCwWR6N1juG6LobD4Y5HfZHLHcBs1zbAzm1mx9jTVV8+8YlPpP6+4IILZr7n/PPPx5ve9CbRGH3iE5+YKG7HcYxPfepT4u9qtYr/9b/+18x1PPnJT07FmHzyk59kcZthGIZhGIZZOp7nYX19Pbdw1VYJ24Qsy6jVajAMA+12O7UNcRyj2+2KYpOTtiMrVE8Tr3eSPCF3YdbXgbvdLTXJ+fzngWPir/zZz+Lkv/xLGD//+Ya2ce3Wt8b/PP3p6Jx11qhAo++L7aRh+sVicaqwTei6Dtd1UwXSKpWKcCUmi7YlybrQTdOcW5CO4xjNZnNM2NY0jYVthjlBUFUV0RyZ+nIip5pc2ABE0UhybpOoDRwv/pg1KzqOk8rQTraPybxtWkdS3Kbs76S4nXVtUxs6jXK5DMdxUmJ9p9OZqz7BVpLsrNRmFZMsFoE73WmLt4hh8tmz4nYQBPjSl74k/j58+DDOOeecme87dOgQ7nKXu+B/jn0xv/3tb6PZbKKRE3r//e9/H7fccov4+4EPfOBczoOHPOQh0DRNNKKf/exn8bznPW/m+xiGYRiGYRhmXlzXRbPZHBN/DcPYVjHQsixomoZ2uz32UO84Do4ePSryS7MC9m4QruchDEMMh0Mh3iqKkiqOOFfsRhQBGeF62O9DXl9H+WUvQ/HKKze0bW6hgO886Un4+cMfDqNQQMUwRFE0z/OgKApM00SxWISu66nzggqskfhCv8uyjCNHjqTmVVV1ajQJFZ9MMivKJEne+UOFUHdS3GEYZvuQZRmYUVASGDm3SVgOw1B05BUKBfE71S9IFpUMgmCsvSZROY5j+Mc6BSflbSevX/QzWSzSNM25I0my+12tVtFsNsW0KIrQ6XSmJgdsNUlxe6Zz+x73AHZJTjhz4rFnxe3rrrsulRF317vede733vWudxXidhiG+Na3voWHPvShY/P9T6Znat51mKaJO9zhDrjqqqsAANdeey263S4qczTSDMMwDMMwDDMLx3HQarXGxGHTNHckl5hEyF6vB9u2U/8LwzA323kvQ4UXKZJFVdWUs3vejGnrrW9F6U1vgrzBOkQ/uu998b2nPhXx6irMYwKLGEJ+bDs0TUO5XEaj0RDi9oEDB4SIPQnDMFIijeu6U8XqvMKY80aSdLvdsfdTAVMWthnmBKNWmzmLYtvCZZ2MALEsS4wsybq3k45rIo5j0fZQ52syCsQwjIl52/RzlnN7HnEbGF2/KQOcGA6HKBQKC8U7LYs4jo+L28MhtKuvnv4GjiRhdpA9K25ff/31qb/vcIc7zP3eO97xjqm/f/KTn8y1juz7ppEUt2kdd7nLXeZ+P8MwDMMwDMPksduEbUKSJFQqFRFTkhURNguJseQyppcsy+JYkGN5Wb9HUTSWnZoHOQKTYjcJ3dPE7soG6xOtn3Yavv2MZ6B/l7tATyybBGXTNIVbOwgClEqllMDiuu7MPPSsA9FxHFSnxAVsNJKk3++PdYjIsoyVlZWFClEyDLM/kOcQt+VuN1fcJpc1RTHlFZVM4rqumEbtPbU7yQ46EreTedp0jaP1kMidVzNgXiqVClzXTe1Tu93GwYMHt/3a7vu+2A79e9+DlNmvMbiYJLOD7FlxOytIn3zyyXO/9/Dhw1OXNWl69n3TyG4Pi9sMwzAMwzDMZhkOh2P51sDIrVar1XZFLrFhGDhw4ADa7XaqKOE0smJ1noC9U/sWBAE8z4PrumOiw7T3BEEgCoSpqgrz6FEULroIype+BGnC88csPMvCNeefj18++tGQNA0KjseFFAoFFItFkTlLESPlchm9Xi+13d1uF5qmTXUDmqaZctyT+5FEnuz+UiQjMU8hNNd1x1z9kiShXq9vWRFPhmF2N7KuIyoWIScKLGZRbBthFEFV1VRHahiGIpqErhvJopJZ4Xk4HI4VkyRxe1YxyaS4DSDV0Sr25Vj007xQfYN2u53ap263O7VzcStI5W3PU0zynvfcwq1hmOns2TuGZBY2AJx00klzvzc778033zxzHaqq4sCBA0tfB8MwDMMwDMPMw2AwSD3wEoVCAdVqdVcI24Qsy2g0Guj3+6mc6jwBe6PCdRRF6Pf7CIIAmqaNFf1aFiQUFwoFACNxw3VdIXhPFbuHQ5if+hQKH/gAjC9+EdIm3Oy/eMAD8MOnPx3+ygosw4BlWSiXyygWi2IbZVmGpmnQNA2qqsKyLCGurK+vp5bXarWwuro6UXihZSbFIMdxcsXtvEiSWW5F3/dzRyBUq9UdGYLPMMzuQJZlxOUyMEXcVm0bbhBA1/VUxxqJ28kcbBK34zge63AdDoeiDfd9H4qiiAKV1I4mryvJWBJqG2k9iqKMjVjayDWpUChgOBymxOV+vw/LshZygW+WVN72rGKSt7sdcPDgFm8Rw0xmz4rbg0wuXbFYnPu92Xmzy8qbblnWQo3SvOtgGIZhGIZhmFn0+310Op2x6YVCAbU5hnDvFMVicaH79HmIogi2baPf7wthlMRVSZJEFAi9tkrspv3yfV8I3Y7jIPA8aP/93yh84AMofeITUDKRG4vSvdWt8IPf/30M73EPrJTLqFQqqf0jMTs5FD+LYRioVCopl3QURULgnnSMDMMYE7fL5fLYfFnBaNazUxiGaDabYx0D5XJZdCIwDHNiIssyomoVyhSDoNLvi4KSyXYkiiLR4QeMBOdkHEm2rcoWk9Q0TVxXsnnbQNq5HQRBKm872xkILBZJkqRareLo0aOpzr9OpzO1vV4mURQdj6WK49niNudtMzvMvhG3F2k0sk6AecTtRd0D2e1hcZthGIZhGIZZFBJys5nEwEg43u5hyjsJObX7/f5EtzQVwCLHGQkTyWKPGxUGoigSrj0a3k7Ctud5wHXXofihD2Hliitg3HTThveTCCwLv3rmM2E//ek49cABWJY1JmQvQqlUgu/7KZe17/vodDoTO0hM0xTRKjR/GIapdS8aSRLHMZrN5pjDkZzoDMOc2CiKMnJuT0G17VxxOwxDlEqlVG52FEVC4CZxmv5Po2+ofbcsSwjKVEB3XnFb07QxcXujo1BUVUW5XE51SPq+j36/P7NewjJIurblG2+EkklOGIPFbWaH2bPidvLLBiwmbmfnnZQFmMoYyhl+t4x1MAzDMAzDMEwWeogdDodjsQ3ASKisVCo7sGXbzzyi9iTiOBbis23bKbGbXiRMZN83HA4xHA7F+0nUoFcURYjX11H5+MexcuWVqFxzzbJ2GcPHPhbRq16Fw7e+tYgbWQbValUUViMGgwE0Tct12NPxSR5313VT7upsJImiKBOfzeI4RqvVGhPDdV3f1SMQGIbZPmRZRjTj+qbadqqwI0WJxHEs6g5Q/BVwvHZCUtymaSR+zyomSe1+UtymQpIAxjpOs67vRSkWixgOh6n2stfrif3bShaKJAG4mCSz4+xZcTvbA5as5D2L7LzUI5e3DrpZy96ALWsdDMMwDMMwDEM4joN+vz9m5EhSLpdPCIdrFEUYDAawEyJGHqZpimKHs0iK3UTW2e15HtbX19Hr9eB5nuhcIAHE7/dR+tKXcPATn8DBb3wDcsaptxnis86C9PrXw3roQ5e2zCSUhb62tpZbYDIrSkuSlHomAkbn6DRxe9pzT7fbHTP9qKqKRqOxqzLjGYbZOWRZRriAuA0gJUxLkgTTNFM1HTzPEx17vu9D13URSQKM9B5JkiBJEhRFEfFTyWKSybxtIO3cjqJo7Bq02RoQkiShWq1ibW1NTIvjGO12G6urqxte7jykxO1ZxSQtCzjnnC3dHoaZxZ4Vt7NZbIuI29mHhUm5bhTkn/eeWWS3h7PjGIZhGIZhmDziOMZgMBDFEadRqVS2ZUjyThLHMfr9/kxRm2IsSHigjFDKv57XnOL7vihu2Ol0hFueXIC+78N1HFjf+x5O/sxncMpXvgJjkznaYxQKwF/+JaTnPx/Y4oJhqqqiVquh2WyKaeSoXl1dHYs7MU0zJWC7riuOT9YFDkyOJCH3fRIS25flTGcYZu8jyzKCWeL2sZoLURSNxPBE1EgcxygUClBVVYjWyaKSrusKVzR1XlIxSRK4TdMUzmsSqMndTesAIOZ3HGfMTb0MDUjXdZRKpVQ0med56Pf7S69nQVD8lNiGWc7t884DNuFQZ5hlsG/E7eyN0jSy804Tt6mqOFXRnffGa951MAzDMAzDMCcmYRii3+9jMBhMFXElSYJlWSgWi5sa4rwT+L4Px3EQRZEQAchJl30BECI/iad5rresqE3IsgzTNIVzOCl2k2svjuOxFwnbvV5PCCC+7yOKIli33IJTv/hF3OqLX0RlCTnaWeJyGdIFFwB/9mfArW619OVPwjTNMcEkDEO0Wi2srKykjnt2xCyJQ1nRG5gcSeI4zlhBVEmS0Gg0tnx4PcMwewtFUeaOJSGNJpu7TeI2ACFuU0ccGRcdx0EQBOI6oOv6zLxtWgZFociyLDr5kvMahrE0DahcLmM4HKYEZ+qILRQKME1zqR2EKWOn60L7/venv4HztpldwJ69kzh06FDq75unVNLNclPmxvSkk06auI5f/vKXAEYN2draGg4ePLjUdTAMwzAMwzBbD+U2R1EEVVWh67oYcrzdkOvKcZzcPG1ClmUUi0UUCoWFiwfuNFEUodvtzlVUPY5jOI4z9vAOICV+G4aBUqkklp0Vv/OE6zwhm16DwQDdblc45kWhsCjCKd/8Js78+Mdx8Ac/WPqxSe3f97+/raJ2knK5PHKlJ4QMz/PQ7XZThUplWRZxLcQkcTvPtU2dB1lqtdpCdZMYhjkxkGUZ8QLObUVRUteOrLitqqrouIyiKCVux3EssrRVVZ0qbtN8QPp64zhOKr5EluWl1hCQJAm1Wk0YLwnquKUO8EKhsJQ2NVV77uqrIc1KSWBxm9kF7Flx+3a3u13q7xtvvHHu92aF8Nve9rYT1/HNb34ztY6NitvZ7WUYhmEYhmG2hyiKsL6+PhZTQUOO6UWC91ZAD8D9fn9mnB4V97Msa8/lEFPESq/Xm1n8cZqonZxH13UhVJBrOPn/aS7vLCRUdLtdtNttOI4jhmDHrovbfOUr+LUrrkBlgWeLeemcfjqqP/95euKECI/tQJIk1Ot1HD16NHX8+/0+NE1LuQ5N00ydt47jwLKssc8tK26HYYhmsznWiVMulyfGlzAMwyDRwZaHknBuS5I0lr9dKpVEBzb9nwpK0mgiz/NS9RrI/ZwcgZJ1blObR85tijNJFq+s1WpL75AmJ3hehzFddweDAVRVRaFQQKFQ2JCbm+pSEHMVk2Rxm9kF7Btx+5oFqpNfffXVqb8nidvZ6ddccw3ucpe7zLWO7PZMWgfDMAzDMAyzdUwStoH84oKyLKfEbk3TNvWQSkUR+/3+RAGXME0TxWJxLAZir+B5HjqdzsysaxKoB4PB1GNCD/OTOhx830ev1xPLoMJek17kIG61WiKiBADMMMStPvUp3Pbf/x1WonDXMhjU6/jF/e6HW37zN1G87W1x3iMfudTlb5ZkgcmkAN3pdMT3ABidm91uV/w/DEP0er3UslRVTQlBURSh2WyOfcaFQuGEKIjKMMwmmOF8VgcDRMc6JrMjS8IwFBFVJDqTQ5tG7riuKwpE0ntpXsMwhCievP4kxW36nTpVaV6KCdkKarUaVFWdej8RBAG63S56vR5M0xRu7nk7yqmmAjGzmOStbgWcfPLc+8AwW8WeFbfPOOMMVCoVcZP1ne98Z+73fvvb3xa/K4qCc889N3e+u93tbmPve8pTnjJz+Y7j4Ic//KH4+6yzzuIbOIZhGIZhmG0mDEOsr6/PLNKYhIYsJ93BiqKMCd6zHFFBEIg87WnRI5IkoVAooFgs7tns4VkRJFScK45jDIdD2LYtRAESHegFQDi1p+WLO44D27ZTzm1y8eXN2263hRBOD/lGv4/bf/KTuP3HPgYjI9RuBl/XccM97oEbHvxgrJ19NnTLwqFDh3C40UDrn/8ZlUoFCp0/M4bebweapqFaraLdbotpcRyj2WziwIEDkGUZqqqKof1EKpcVadc2FajMdnQYhpGKPGEYhslljnZCPdZBmpe5raoqDMOAoiiigzpZT6Hb7abiqmgeul4BSBWTpEgSEpVd103lbJPbe6vbt1KphGKxKDqIs2I0Qdfb4XAIRVGEm3tWZ322XdcT2lku9773wvvAMFvB3ryDxsgZcP/73x8f/ehHAYxiQL773e/izne+89T33XLLLfjud78r/r7rXe+KRqORO++d7nQnHDp0CLfccgsA4Atf+AJc153ppvnMZz6TupF7yEMeMtc+MQzDMAzDMMthkrCtKIooLrXIssIwhOM4Yhq5VEnspodg13VFnvY0FEURedrLLAS1ncwTQULFHz3Pg23bkCRpoumDMrU1TRNZqnm52VT4kWJNKCvVNE0hZkRRBNu20Ww2RcFOGmZurK/j9ldcgdM/+UmomczoDR8LScItv/7ruP4+98Ha/e4H9Zjr0JRlHD58WEQbGhdcAGUXFpovFArwfR/9fl9MowKTjUZDZJ5P+94k3YqdTmdMJFFVFfV6fc9F7TAMs/1I9frMeRTbRhAEQtxOdnSSA1tVVZFLnSwI2el0UoI1xV4pijIxb5uE7TiOxfWMrt+qqoq2cqshAd40TYRhiOFwiMFgMLF9ppE2vV5PjIgyTTN3W5PttnzLLVCO1aCbCEeSMLuEPStuA8AjHvEIIW4DwLvf/e6Z4vZ73/ve1BCO3/qt35o4ryRJePjDH47LL78cwCib76Mf/Sie8IQnzFxHkoc//OFT52cYhmEYhmGWxyRhW1VVrKysCPGTXFye54nc5Xmhh2QqqEcPubOWoes6isXixAfLvcK0CBJykRWLRciyjGazOVUU1XUd5XJ5zECSdZjFcYy1tTW0223xAJ4UVMMwRKfTged5GAwGwqFHDvHijTfidh/8IE753OegLNC5MQ379NPxywc9CNeddx68gwdhGAbMY0Pa4zjGKaecIow0VPBrt1KpVMT3gXBdF7Zto1wuwzTNlPidJBlhYtv2mItfURSsrKzs2Y4chmG2F2mOgozqsSLR1N4mi0vGcZwaESXLMoIggOd5IhoriiLRUTqrmGQQBKITdzgcIgiCVK2HUqm0I5FiiqKgVCqhVCrBdV3h1p40YoxGpsmyLNzcdIyS4j8wRyQJwOI2s2vY0+L2Qx7yEJx55pm47rrrAAAf+chH8MQnPhF3v/vdc+f/6U9/in/5l38Rfx84cABPetKTpq7jGc94Bt773veKm7zXvOY1ePCDH4z6hJ7ED3/4w/jGN76R2sZf+7VfW2i/GIZhGIZhmI0xTdhO3r/JsgzDMFIPo5THSWI3iaPzQHmek7AsC8ViUbiH9yrkACM3dBiGInuUXHCGYcCyrIkxJcQkUTuPwWCAG2+8MVdc1XVdCNvkmvd9X+Sn1n/2M9zu/e/H4a9+FdKcn+c0vGoVRx76UNz0sIfh6KmnYjAcjgowHnOPS5KEMAxxq1vdCpVjsSOKouz6OA4qMLm2tpY6l3u9HjRNg2EYY8P/CRKDhsNhKps7udxlF1hjGGb/Mo9zW7Vt+JlCktTORFGEYrEo/ibRmzqyqZ0mnYfm03Vd/J4Vt0kcJ4GcOutkWd4VMbR0T1OpVISbe1INDBrdZNu2iALLtu0zxW1dB+5612VtPsNsij0tbkuShOc///n4vd/7PQCjh4rnPve5eN3rXod7Z7J/rrnmGjznOc9JDbP4gz/4g5lh/yeddBKe+tSn4q1vfSsAYH19Hb/927+NN77xjTj11FNT815xxRV4yUteIv7WNA3Pe97zNrWPDMMwDMMwzHyEYTgmzAHHi0QdPXoUwOgerVQqjbmnKZszeX8YBMGY4D0tQzu7XsrT3svCHh2DXq8n3NokZCehPOVZ7tx5Re0oitDv99HpdLC+vi7cePQ/+tu2bSE4kKht6DoaV1+N27///Tg4j/tsBqGmYf2+98Utv/mbaN397giPFaj0h0MYhgFN01Ln06mnnopSqSTeX6vV9oRrWVEU1Ot1rK+vp87zdruN1dVVGIYhRisksSwLnuelcruJer2+5zt1GIbZXuZxbmuDAdxj1yESq0mQpqKSydxtEreDIICqqmIEF3C8IDHVDsgWk6SO3KQrmtp7y7K2rIjkRpBlGcViEcViEb7vYzAYYDgcTuyszxbWJoxZedvnngvs0QLYzP5jy8XtX/3qV3jYwx6W+7/kg8evfvUr3PGOd8yd721vexvucY975P7vQQ96EJ71rGfhzW9+M4BRdMhFF12Ec889F+eccw5kWca1116Lr371q6kbtMc85jE4//zz59qHiy++GFdddRW++c1vAgCuu+46/NZv/RYe8IAH4La3vS0GgwG+8Y1v4Nprr02976UvfSnOOuusudbBMAzDMAzDbJwgCIQASsRxDM/zoOt66qHO9320Wq25cq+pkB498MZxLNxbJHZnnVGqqqJYLMKyrD0haALHneckZJNLjfbVPpZtmgftb56ASeIB5WLTfOQqS2ZpU2YqCQjD4RCe56Hf76fu4+lzpYJhQRCI4l6IIhz85jdx+w98AI0f/GDTx8Wv1XDzk5+MGx79aHjHIkUkSYJ8rAgZZX2rqgpZlqFpGg4cOJAqrrhTw9U3iq7rqFQq6HQ6YloURWg2myiVSmPiNolJzWZzrOOnUqnsKtGHYZi9gVIuI1ZVSFMipLRj14a8opLJWgwUG0bXI7qW0TUu6cCmtjpZTJLmpSKUdJ9B2deyLO/aDjwqGJx0c+cJ2WP4PtTvfGf6PFxMktlFbLm4PWuIZpJJ881yxzz/+c+H4zh4xzveIaZ961vfwrcmuDQe+chH4hWveMVc2wSMbvD+8R//Ec973vPw9a9/HcDooegzn/lM7vyqquLiiy+eGXnCMAzDMAzDbJ6ssE15mq7rolwuT8y2DsMQ3W4XvV5POKyTTq08JElK5QvT+uiBWVEU6Lq+q/O0kyJ2UsjO3nPTsOVsYUCCnOlZBzwdf8ooVRRFHLNJDjEAQtR2XVcc02wMCTnvyuUyFEURhTstTcOBL38Zp7373Sj/7GebODojvJNOwpGnPQ03PeIRoHAVTdOE+6/VagmXHzn8CoUCqtVqSszVNG1XDFdflGKxCM/zUkJ2MmM+iWEYaDabY67AYrGYcq8zDMPMi6woiMplKK3WxHm0Y/FYFBGS1JOoSKRpmsK5TdoUdUh7nieuUbSMvLxtYBTPRNdC6ow1TROapkGW5Zn3DjuNJEkiYzsIAuHmnqTBaT/4AaRZBZc5b5vZRezub+CcyLKMl7zkJbjf/e6Hyy67DN+Z0MN05pln4pnPfCYe+9jHLryORqOBt7/97bj88svxzne+E7/MqRoryzLuda974eKLL8Y555yz8DoYhmEYhmGYxcgK277vw7ZtAJgrIgMYPaj2+330+32YpolSqbSQC0uSJOi6vuucW+SCJgF73hzxOI6Fc3rSvKZpirgVci0n87cNw5jbsZssAElQYazsvsiyjNXVVTiOA8dxILsuTvr4x3Hae98L8+ab51rf1G054wwcffrTsfbQh8I+JtCTiK8oCobDIdrtdurzJqdzpVJJxc9IkoRarXZc+G+1gN/8zfQKP/UpYI5s2Z2gVquJ84agjgfaJ0mS4DjOmKvfNE2RN84wDLMosiwjrlZH7eYE1IRzmzoeCYolsSwLqqoK9zZdD6MoEtnZJG5TxBSQFrcdx0Gv1xPXQ3KKU4FgGrWzV1BVFZVKBeVyGa7rYjAYiI5iwrrqqtkLYnGb2UVsubh96qmnjsV1bBUPeMAD8IAHPAA///nPcfXVV+PIkSMIwxCHDh3CGWecsemIEFmWcdFFF+FpT3savve97+GnP/0pjhw5AtM0cejQIdz5znfGoUOHlrQ3DMMwDMMwzDSSwnYYhuj3+3BdF6qq5grbhUIBhmGg3+9PdA+TaKrrOorF4pgrebdCw62TQnaeG3sWFAOSFSspt9wwDNTrdSH2+r4v4kNoXfM42OI4huM4uc4xcm8TkiQhjmNYliUyn80bbsBpn/oUTvrIR6A3mwvtYx7One+Mm5/+dDR/4zcAWcZwOBRO/FKpBEVRROY4OQGBkYhbr9eFEJykUqmkBY8gAI7FHKam7VKSBSaznRzkYk8O8U/+LyXqMwzDLIgsy/BnjHrR+n1EUYQoinJjSaiGBrXXdC2hEUTJYpIkbtN9A7XdcRyPRZ5R4WRaLsWXbSlxDLzvfcAVV4wE/zvdCXj+84HDhze8SIpVMU0TYRiKyBJZllH47nenv/nkk4HTTtvwuhlm2ewL53aW008/HaeffvqWLV+SJJxzzjnszmYYhmEYhtkhfN/H+vq6GF7rOA7iOM4Vtg3DSAmNVPyu3++L92WhB995crm3k+Sw6qSQPW8M4CQogoQEXcuyhCubfpbLZZimKZxe5OKdBUW5kPhAojYA0XlAokO/34emaTAMQ8S7eJ4HwzCgrq+j8P73o/axj6H4/e9van8J5/73x/qznoW1O90JQ8eB2++LgmH0uUuShG63i36/L5x6wCh2o1ar4dChQ+j1eqnlGoaBYrG4lG3cSVRVRa1WQzPRgUCF23RdH3P7KYqCRqOxK74rDMPsXSRJGjm3p6DathC3NU1Lidt0TbQsKxUdkqyZQfNQe0WjjZLFJCmOJHmtIyc4deApirK1bZ7nARddBLznPcenfeITwD//M3D55cAGkgmyKIqSjtD67/+e/oZ73QvgDkxmF7EvxW2GYRiGYRhm/+L7PtbW1jAYDDA4lrkJjJxWlUol5byqVCq5xfwoVoIc38nlJNlILvdmIPE6iiLxk34nIXtRN3YeJDirqgrP8+A4zsR8csoVdV1XFNSaZ/k0JJyKPtq2Dd/3IcvymPAbRRE6nQ4kSUK1WoWmaej3+wg7HRz40pdQ+Y//QOlrX4O0SREfAGJJQvCYx6DznOegdaw4PGW0U8SGqqoiy7Xb7cL3fXEeSZKEYrGIlZUVHD58OCX8AiOhpFarbXo7dwumaaJcLqcE/CiKxvLQJUlCo9FIRbMwDMNslHhGtJFyrA0KggCWZYks7GT+NhWEpusLADHiiOal+bLFJF3XhW3b4voLQBSPTMZmkXi+JcQx8Hu/lxa2iW4XeMITgLe/HbjgguWt8+hR4Prrp8/DxSSZXQaL2wzDMNsMFcmi4XLU+88wDMPMxvd93Hjjjej1eim3clLYJgcSFfubhqIoqFQqKJVKGA6H4kE2SzKX27IsFIvFuTO26YE7KVhnhWv6uQzhOkuyoKOqquJnHMdot9tCzM1uMznhSfTN2y/aN9pu6jTQdV0UlrRte2IMDDASJui4GoYBp9dD9IlP4PCVV6L6xS9CnlXUak5iTYN04YWQ/vRPoZ55JpR2G2q7DeB4FIrv+9A0DaZpolAoiPOBBFuKKVlZWcEpp5yCZrM59pnVarV8gbdcBv71X8en7QHK5TJ83889D4h6vb6ncmcZhtnlzOgkVI91uFEGdvJ36qymaBK6NyDXdrLgMYBUoWhygbePXR+S17hisYher5e6t6C6E1vCq189ft1IEobAhRcCtg08+9nLWefXvjZ7Hs7bZnYZLG4zDMNsE3EcYzAY5GaZZod+J3/fDcJ3VowBjosa9Hv257zTsv+TZRmGYYhhhAzDMIRt2/jlL385JpSSsE3CY6lUWrjtJDdxoVCA4zhTc7mp2GIylzsMQ7iuK/K/swL2dkBDqbNC9qSH7m63K9xrtK3kYE5miCYF7OyLimlSjAgJ2snM7FnbHMcxqpUKlK9/Hdq//RsOffKTUKcUEVuYQgH43d+F9PznA6edhjiO0Wq1RgUpZVnsg23bqQ5ox3FSx0FVVZRKJRw4cACHDx/OFe0LhcLkQpqmORpavkep1WpYW1sbu4cBRsVb5y0gyjAMMxeznNu2PZa1HYahEKepg9ayLNHWS5KUGgUlyzLiOIau66Kt1zQNnU5HdHRToWTK746iaHvE7X//d+DFL549H7m7ez3gT/5k8+udJW6rKnC3u21+PQyzRFjcZhiG2WJmDXmneSblpW6l8J0VYCb93Aon4bRt8n0ftm1D0zRYliWyXxmGOTGhwpFHjhzJLWxXrVZRLBZRLpc33VZIkiTaHcrlHk5wDnueJwROcodtV4ckXQdIyKYCf/OsP45jNJtNrK2twXEceJ4nckh1XYdpmgiCIFfEBDAmaC+6z5Ikiexq77vfRemDH4T57/8O7Ze/XGg5M6nXgT/8Q+AP/xBRozG6vgwGWFtbE59rq9XCcDjEYDAQ4gbtT1LYpk7Xw4cP4+DBg+KzT6KqKiozxJi9jCzLosBk8r6gVCrti3xxhmF2GTOc20qvl1tIkgjDUIjbyVxs6sQEIO4ZdF0Xv1NsSXI5sizDNE3RsZsUs7fEjPQ//zOKGlnkGeyFLxwJ3C972ebysP/rv6b//y53ASxr48tnmC2AxW2GYZgtwvd98fC8GXF4HuE7K35LkjRRrE46CbdTtN4IVDCt2+1C13UhOHGhKoY5MYiiCL1eD51OB51OJ1fYPnjwoMhoXjYUr1Eul0UnJbmYXdfFcDhMtc+DwQCGYQixeTNtlSRJ4mE8+XMjyyZXOe1Du91Gt9sdO57FYnHicdysoA3geHHOdhve618P+b3vRXVJhSGTRIcPw/uDP8DwwgvhGwbc4RDeT38K3/fRbrdFcTAaSeW6LgzDEMeXssJVVRWihqZpOPXUU9FoNEScS/IaKkkSarXavr8+aZqGRqOBVquFKIpQLBb3taDPMMzOIc0Qt+WEc5sE5zwXNwnXNLpJURTEcZwqaEwdrlEUYTAYiGXQ8mhkCsWHJdv6pWdu/+pXwGMeA2wkkuuv/3okcL/mNRsTuMMQ+PrXp8/DkSTMLoTFbYZhmCVD+aKzhmRnb8A2AonV8w7/3st4ngfP89DtdoWDbjtdkgzDbB8kPFJb2ul0xjrjLMvCaaedBmsb3EOqqorYhfX1dXQ6nVxXcxRFIrIESLur6WeeYC3L8ti0Rdu2OI6F25qGXJMjmZzZwPGO1yyFQmFM2CZBm0TtadskSZIY9k37k5ymDQYwr7wSePe7gc99DuYWdK76t741Os9+NtqPfjQCRUHY7QohIgxDETsCjKJlssK2oigwDAOmaYrCYiR4n3LKKahWqwCQ+/mXSqW5M9j3OoZh4NChQwDA12CGYbaOY23uJMi5nVdIEoCYRiOrSLSmayyJ3KqqilitwWCAUqkklhGGISzLEu+l5ZOYnbx2LwXbBh79aODGGze+jL//+5HA/U//BCw6mu3qq4Gce4QUXEyS2YWwuM0wDLME4jjGcDhEv98Xw9wmYZomisUiDMMQYgRV4abXNLf2TkI3b+RyAJD7c9H/JR+OPc8bc0MmieMYjuPAcRxIkiQcdrOEF4Zh9gbD4RDdY6IkdWglhW2KRjj55JO3xSVLGdL9fl90JNZqNdFWJdt8cviSuJt90cO0ruspN9kiZK8XyWtIFEWiI5Byo5NQ4cYsyc5CWZZTI2WS4ntWwE7+zG1/gwC48krgne8E/uM/gC3oiI0sC72HPhStRzwCnXvec/QgHwSjV2a/6TwaDAbwfR+e54lCY7Isw7IslEol1Go1GIYhhO5isSg+J8dxUq4+YOTwT4ohJwJ8vWUYZquR6vWp/5d9H4rvwztmGMqK2/Q7dVzSNSs7epVGvjqOM9aRrut66lpKtSaoDZRleawg84YJQ+CpTwW+/e3NL+stbxmJ1G9/O7DIyLZZkSQAO7eZXQmL2wzDMJsgiiIxzHuaGE0ZrqVSKXUDJElSqjp3kqQLLylmbIXwneckzHMVbsfDrGmaKJfLQjhyHGeiw506FYbDoRAmLMs6YdxzDLOfCMMQrVZLFOjLCtvUjtbrdaysrGx5e0RDk/v9/libK0mSED8pPomK4U7brjiOhfhMkNhNgremaallUDs3GAyEgJ38H2VlJ93ZeVD9hySqqqJcLmNlZUUI3CT2boo4Bj78YeDP/gy49trNLStv8YoC94EPxNpv/iZa978/oinu/axTnSJJoihCtVoVrvSVlRXU63UcOHBg4rLCMES73U5NozgSFnsZhmGWy6xYEgDQ+n24pZKIkEp2ONO1W1VV0UlJBSGTRSFppE6/3091VJKjO3kN2dJiki9+MfCRjyxnWQDwnveMBO73vW9U0HgeZhWTPHAAuM1tNr9tDLNkWNxmGIbZAOQCo/zVSciyjGKxiGKxuPCNzzThm/Kz81zfSeFjN4nWi5AUjsg1SUL3pONNHQ39fh+KogiheytyeBmGWS6u64oMX2Bc2Cb3bKFQQL1e39I2a956CTRyZHV1FbquIwgCUZzR87y5Y6fCMExFmVDbT0OkHccZG2Y9zZ2dB7WPNDSbXpVKBaurq8s9nv/5n8Cf/inw1a8ub5nEve6F6ClPwU33ux+axwSKLMlrHcWOlEolaJomstI9z0OhUBCiBBUkbTQaU1ffbrfH1lmtVud37bXbwOMel5724Q/PLJrGMAxzIiLPaJMBQBsMEBUKiONYxIyQi5vaayoqSaOnkvUVHMeBqqrimp9sz2u1Gvr9fq5zm1iauP2WtwCXXjrfvI94BPCpT42c3rO44grgf/2v0bVmnhFGs8Tte997c8UqGWaLYHGbYRhmATzPg23bcBxn6nyqqqJUKokbqWVDovQk4ZsKnew20XojkIBkmiaiKILjOBgOh1Nzxilb1bZtaJqWGl7PMMzuotfrodfrib+TwramaaLIoWmaWyZsk4jc7/dTruo8qNOyUCik2hRq94mko5rc3fNuy2AwwNGjR8W2UHY3dWZOgx7c6aXrOjzPQ6PREAWHASz9eMY/+AHwZ38GaZmuMwA46yzggguApzwFwemn4xe/+MXofEmIDeRAp05bVVVF5jiNmKLzCgDK5bIYVl6pVFAoFNBoNKYei2QsDWGapihCNhe+D3zxi+PTGIZhmDHkGbEkAKDaNuKVFVE8EoBwcSdjSZLPAdSJHIahEMSDIBDiNzC6Tui6PlZjIStuL6WY5Oc+BzznOfPN+7//N/CBD4wc3uefD8y4ZwEAfPazwMMfPooJm9aZ2mwCP/zh9GVxJAmzS2Fxm2EYZgaLiB6GYaBYLIqK2jvBdmTQ7hSyLKNQKKBQKCAMQyF0T/tcSFTqdrvQdR3FYnFbCtAxDDOdKIrQbrdTnYWu66LX60FRFBSLRRExZFnWlkQ/hGEookdmOaCp/Zi3kC1leJL4GUWRyHme5Lomh3W2AzUbR0UP4KqqjonZlC1qGAZ0XUe73R7r2NN1fW5hm1xwYRiO/QzDELjpJlivfCWs97wH0rIis046CXjyk0ei9rnnApIE13Xx0x//eExgVlUVjUYD1WpVFO60bRu+74u2nq4BnuelomPK5TIsy5opbAdBIIRxQlEU1NhxzTAMs2XMytwGAMW2AYzaaXoGomtr0rlNbm1FUUShYXpPUgSnQsrUWZ0dFUuxJDSyKxsltjDXXgs84QmpOhETOfdc4B3vAGR5JHL/x3+MRgMdG/k1la9+FXjwg4FPfnIULZLH178+ezlcTJLZpbC4zTAMM4FpeatJyFlMw56Z7YHEr2KxiCAIxLD+aa5GEpUcx+GMVIbZQXzfR7PZFE5k13Xhui7CMEy5cOM43hJh2/M8ISLPih6xLAuFQmHTWf6UyU3ZnsDxzjfHcdBut2Hb9sTtIaE8zyWmaZoofkgP2nEcpzLMk8vJirmU102CdVbEzkPq9VB64xtR/Od/hjzPg/UsyuXRA/4FFwAPetCoMOQxer0efvGLX4y176qq4tChQ2g0GpBlGXEco9vtpvJRSZgmVx/tN7nvV1ZWpnYK03HMfi61Wm1fdyYzDMPsOJXKzFmUYx3i5NYGjmdtJzO3gdFoGypanxS36fpOo5voniPvOkjObbombCqWZH19FBmSqeWQyymnjMTsYvH4tN/8zVE8yaMeBWQ6YHP59reBBzwA+PSnR8vLMquYpCwD5503ez0MswOwuM0wDJMDRVpMc/KRi5gKlDA7B4lh5XJZDEWnm9c86H8kiDAMs30MBgOsr6/DcRwhaAMj1za1pa1WC8DxIk+O44gYCQC5v8/7P8dxZkaEUOdZoVDY0jaC4jI8z4NpmiK7m0RvevAuFAopxzE9jJumCcMwcq9B3W53zAGuKIoQc2lUErmc58bzYL3jHSj/wz9AbTY3tf+xpgG/9VuQnvpU4NGPBjKjauI4xvr6Om6++eax9lxVVZx22mmoHBM/4jhGu90W2eXAqJO62+0iiqLUMaICzysrKzOv371eb+z4FIvFVCfF3JRKwOtfPz6NYRiGGUfTEBcKkAaDibMotp0Sm4Hjju1k/rYsyzBNU9Se0HV9TPxWVTVVR4E6fYk4jkX04/FN3GAsieeNOnR//OPZ8xYKo+zsk08e/9997zuKNXn4w0di+Sx+8APgfvcbRZVkC0POyts++2y+ZjG7Fha3GYZhMti2PTb8OImiKCJPm4XR3QcV4SyXy/A8TxSizHZUeJ6HtbU1kUPLMMzW4vs+jhw5glarJR4WqWAsRUgkv4s0IoYEXXqo3EooWiopJG8Vw+EQvV4v5UYm0VrXdZHtbRiGELqp2K6u61O3r9frpdzLtGzq0KPiu7Pyu5OEQQDtwx9G/dJLYfzyl4vvcAL3nvcEnvIUGE99KjChYJjv+1hbW8P6+vqYsG2aJm5961sLgTmKIrRarVRkSRzH6HQ6Y8s1DAOlUmmutt91XdjHhrwTqqoKQX1hLAv4/d/f2HsZhmFOQOJqdbq43eulikcCSF0zyNFNRSUBiPoMQRCI3wGgVCql6ihkI8Gyrm1gg87tOAae/ezxGgx5SBLw7nePIkkmcbe7jZb10IcCN988e5k//elIFP/MZ4A73GE0LYqA//7v6e/jSBJmF8NP8wzDMAmCIEgVNkuyaN4qs7OQCGQYhnAodjqd1M1vEARC4N5s5ADDMOMEQSDcwevr60JMjaJIRJFQIUZqV6nw03Zl40uSJLL8tyNaigobTqoVQNtTLpfFA/Mi7dNgMBi7jkmShGq1KupHzMoXJ6gopvLlL+PQa16DwtVXz70dWaJqFfaznoXgKU9B5eyzpwrL/X4fzWYTnU5nTNgul8s4/fTTheM6iiKsr6+n3NUUTyJJUkrA1zQNlUoFKysrM48pOcGTSJK0ZUVNGYZhmHHiahW46aaJ/1dsG4qiIIoi4dLOZmQDx0dkEXTNoLgqRVGwurqaWnbWuZ1dPgnjC4vbr3oV8La3zT/vYx87e75f/3Xgy18eCdw///ns+W+8Ebj//UexJne966iQZE6HcAouJsnsYljcZhiGSdDtdsecgeQeZPFz70K5uaqqipxfgoSRWq3GhSYZZgmEYShGTFDkRq/XE7mVrusKYdcwDFiWlSqCuF0jKVRVFQVmt2MUDmU/Z6NCkliWhXK5vOFjQNndSaIogqZpaLfbU53vVGwrjmNR8FL5wQ9w8qtehcLnPreh7QGA2DDQ/53fgf2Hf4jiaaehnujIyEJFRm3bHuuMlGUZtVoNp5xyivi8fN9Hq9Uac6D3+33Ispw61oqioFKpoF6vzxUpkhdtVS6XubYGwzDMdjJjpIzS6wk3NYnPWec2MLrmG4YhxOlkZjYwqqOQjanKFpOkSJJsnMlC9xAf+hDw4hfPN+8zngG84AXzL/v2tz8ucF933ez519ZGNS4+/vFRXMks2LnN7GJY3GYYhjmG4zhjokOxWES1Wt2hLWKWjaZpWF1dRbPZHHP5kUBSLpd3cAsZZm8ShiEcx8FwOBTCdRzHGAwGGAwGwsGdFCHL5TJKpRIMwxCCIUVGkMhKy8n+vtH/AceLAJumudWHBcDo2Ni2jcFgMFFc1nUdlUplU52onueJrHIAotDurDxQTdNgmqYY4RIEAaRf/Qq1V78a5Q9+ENKcLu8ssSRh+PjHw37Ri6CfcQZWS6Wpoj1tv+u6Y8K2pmlYWVnBgQMHRF54v99Hr9cbO6aO40BRlFQsiyzLqFarqNfrc3diZnO2dV1HibNGGYZhtpW4Vpv6f9m2hWBN9RVIlM4K0XT9HyRiTkzTFHUYslDRa7EtmbzthcXtb34TeOpT55v3QQ8CLrtsFEuyCKedBnzpS6Nik1ddNXv+Tgd42MNGzu9p1OvAGWcsti0Ms42wuM0wDIP8bE5FUVjo3IfQsMNWqzXWmdHr9RCGIarVKg87Z5gZRFEkHNrJrGPgeJs6GAzguq54OKRRFCsrKylxmR4s95MrNo5jUZx4kqhNxXA3O2okCAI0m03EcQzf9zEYDOB5HgqFwkQRn5zy5KyP4xjB2hpKb3gD6pdfDjnzmS6C88AHovcXfwH97nfHSqk0tWgjHSfKH88K25ZloV6vi0KYQRCg3W7nxrqQIN3v91OdGZVKBbVaLTUkfRZZcXu7OkMYhmGY40gzTEbJzO0oisT9ezZChITolZUVETdCo3OLxWLu/UfWuZ1cfnKZc4nbN9wAPOYxQKLo8UTOPBP44AeBjXZ4HzoEfOELwCMeMTtHGwD6feDrX58+z73utbjQzjDbCIvbDMMwGBWRzBt+zAUj9yeUm9rtdseKrg0GA4RhiHq9zp8/w2SI4xjD4VA4tPNEWyoEOBgMxIOgruvQNA2lUgnlchmSJIls6WKxuK+KutIxos6yPGRZRrlcRqFQ2HRHWhiGWFtbw3A4FC55YCTGZsVccq0ZhiEc0kEQwO12Ubr8cpzy5jdDnZW5OQXv7LNh/+VfQn34w7FSKs1sQ8MwRLvdFh0gSWGbjhEVf6RCmHnxYQDEtKSwDYyu5bVabaHOauokSLKfOl4YhmH2DDOc24ptpwRtaqvDMISqquI6TJ2s5XJZCOFUIFiSpLE2PgxDEadGZJ3blNc983nBtoFHP3pqdrig0QA++tGRU3oz1OvApz89yuv+/Oc3tyyAI0mYXc/+eZJgGIbZIEEQwLbt1DRd11PVspn9BxVYU1V1zLXvuq4oNLmfRDeG2Qye56HT6YyJfgQV4Gs2m+IBk7LuZVlO5VsXi0UUi8V914HkOA56vd7EYyRJEorFIkpzCL/zEIYhbrjhhjEhPRuhQR0JNBx7bW1tVNCz30f5Yx/D6W94A4wbb9zwdgSnnQb7xS+GcsEFqM3ZMUz54FEUwfd9dLtdIWxT4UfTNLGysiJqI2RHCBCGYYgOhaTLrlQqoVaroTIjszVLGIZjAvpSrgWdDvCUp6SnvfvdAMefMQzD5CLNErePFVCWJAlhGIqaCnRNpJ9U+NE0TRFXous6FEXJFbezxSRp+cmRSBR1MpUwBC64APjOd2bvrKaNMrmXFf9RLgNXXgk86Umjn5uBi0kyuxx+YmcY5oSn0+mkHmJJ9GRODIrFIhRFQavVSp0HQRAIgZuLiTInMmEYotfrpTIqk0RRhMFggFarhTAMhaBND3wU8UTDf5fhVt5NkFObokAmUSgUUC6Xp0Z0zEsURbBtGzfeeOOY4EvCMLnJisUiDMNAr9fDDTfcAMdxEK+tofHv/47T3/c+6DffvOHtCOt1DC6+GNJzn4tqozHX5xrHMXq9nuhUTgrbJMJblgXTNNFoNDAcDlPCdxKKdWm32+h0OikholAooFaroVarLXy+ZTsnFEVZyucGzwM+9rHxaQzDMEw+MxzMyrFrCYnP1LlK14zktUNVVXieN3ZfnydSh2GYuqYoijJ2HaLO+6m8+MXAFVdMn4d405uABzxgvnnnxbJGgvmFFwL/9m8bW4YkAfe4x3K3i2GWDIvbDMOc0AyHwzFhYFLuGrN/MU1TFJpM3siSW7BWq206E5dh9hpUEDLrhiXCMMRwOITv+/A8D4ZhjD0c6rqORqMhXLj7SdQOgkAUzMw7PoRhGKhUKku5rgRBgH6/L+I5stcvRVHEuorFInRdx9raGm644QZ4ngfzxz/GSe9+N+of+xjkTM2BRYhNE4Pf/V3gRS9C6fDhuT/XIAjQarWEeOz7vuhgpk4QTdNgGAaq1WpubQSCHPBra2uiIDBhGAZqtRrq9fqGzrmsuM0jeBiGYXYGeU7nNrmxkxElwPGROJIkCXE7y6S87WwkiSRJKSPMTHH7LW8BLr106vYLXvQi4Hd+Z755F0XXR6OESiXgrW9d/P13vCOPMGJ2PXynxjDMCUscx+h2u6lpiqLkVstm9j+apgmBOylsxHEsHKl8bjAnCskIEnqQo4zKOI4RBAFkWYaqqnAcJ/fhrlar4dChQ/uqEF8cx3BdF4PBYKLoSpCDmoZIb4QwDBEEAYIggOd5GB4rRGXb9piwLcsyDhw4gHK5jDiOsb6+Psqw9n1UvvxlnPrud6M8q2DUDGJZhnP++cDLX47C7W63kHA8HA5TmdpJYdswDBHVYhgGLMvC2tpabqeBoiio1WowDAOtVisllgOj454sQLkROG+bYRhmlzBD3Jb7feBY8cik8Jw1qyiKMrGjcp5ikpS3Pbe4/dnPAs95ztRtFzz+8cDf/M18824URQHe/OaRwP261y32Xo4kYfYALG4zDHPCklfsq1Kp7LsMWGZ+FEXBysoKWq3WmHDU7XYRBAGq1eq+cp8yJw5xHCOOYyFSJ1803fd9EUGSnJ+QZVlkN1MURxbLsnD48OGFCvjtdih6pd/vTywSSZAD2bKsuWM6kiJ28pUn7g4GAyFyE6Zp4uDBgwCAm266Cf1+H1K3i8aHP4zV970Pxg03LLC3+bgPexjCSy6Bce65ADDmaJv2e/ZcIWEbGOVi08gYXdchSRLa7XbuNhQKBXGdDsMQt9xyS6qtVhQF9Xodq6urm7qWJ13gwBLF7WIReNWrxqcxDMMw+cxwDEtxDNm2IVuWuGZKkpS6flJW9qR4qbw2nq7LBAnktFyKMsm91lx7LfDEJwKZa0kud7sbcPnlwHY8f8oy8A//MMrivuSS+d/HxSSZPQCL2wzDnJDQ0O4k5BZjTmxkWUaj0UC32x07RwaDAcIwRL1e504QZlMMh0N4njdRFJyXae9JCtlZkTpvXsdxpkZsmKaJ4jEhrtvtptytkiTBNE1UKhWsrq7umxgHz/PQ7/dHOdUzPh/DMES+dZ6oHUVRroCdV7xwEo7jiHaJCmBRh8PRo0fhOA70n/4UJ7/nPahfcQWUjAi+EYZnn432X/wF4vvdbzThlls2tTwStmVZRqVSEeeKJEmpkQJJFEVBtVoVowCiKMINN9yQErYlSRLC9mbysbM5q8ASxe1CAXjhC5ezLIZhmBOBGc5tYJS7LReL8H0f0TEXdxiG4vekIJ0lr5gkMNm5TdcHWtbY88D6OvCoRwETOmlTnHLKKI97Ozs5JQl4xStGAveLXzzfe9i5zewB9seTB8MwzIJwEUlmGnQ+KIoyFl3jui7W19fRaDSWU2CMOaFwHAe9Xm8s9mAn8X0ftm2PuVUJVVVRKpWgaZpwdtPDnSzLME0TlmWhVCrti5ENVCCy3+/P/JxkWYZlWSgWi1BVdWEX9iK4rovesWxRRVEgSdJIzNZ1tNbXUfrqV3Hrd78blf/8z02th/BudSt0XvQi+I997OhheBnL9Dx0u10RQ0LuuiAIoGla7rljWRaq1aoQEMIwxPr6+ljbbJomDhw4sGkhOvuZU04rwzAMswPM8Xym9HqQDx8WHfpZcTsrSCeZVEwyiqJURycVq6Tnx1xx23VHESPXXz97vwoF4D/+Azj55NnzbgUvetFI4P79358+X6MB3OEO27NNDLMJ+E6NYZgTjklFJPnhlclSKpWgKAra7XaqM8T3faytraFer49VXGeYPEiYzCtktFNEUSRcyXkkI0gAiOKJsiyLon+maUKWZVSrVRQKhe3c/KVDI3qGw+FMITpZsNH3fQwGA3ieN9F5vBmogFVyJEkQBHAcB5rrovqJT2D1ve+F+bOfLWV9QaOBzh//Mdzf/m1giVnTnueh1+uhVCqJc4qOWaFQGBMX6LxKjqgKggDr6+vo9/tjcTmnnHLKUtrjLYskYRiGYRZnTud2spCkoijwfR9hGEJVVSFSS5IERVFSovU8xSTpOkyd2ECOuB3HwLOfDXzpS7P3SZJGBR7vetfZ824lz33uSOC+6CJg0n3Ps5+9PZEpDLNJWMlhGOaEIoqi3CKS+ykbllkulmVBURQ0m82x/L719XXU6/V9VTCPWS6+76Pb7Y51qO0kVBSRcpt1XYcsy5AkSeRHkltW0zTEcYx2uw3LssYEbEVR0Gg09qwAmIxjmeczUlVV7Gte3YbNQMWusq9+v48bbrhBxJe4rgv85Cc4/YorcPCjH4Vi20tZv3fyyehfdBGcpz0N8QaK5ybF6ezvnufBdV3UajUoiiLE+jiOhYM7iWmaYvSM2D7PE+1wskNGURSsrq6KyJzNwsUkGYZhdhFzOreJKIpSQnfyJ4CU2A1MzttOzkOCuKZpYln0PiFu//3fA29/+3z79KpXAY997HzzbjUXXjiKRbnwQiBbR+W884AXvGBntothFoTFbYZhTijyxIj9MIye2Vp0Xcfq6iqazWbK1RfHMZrNJiqVCkobEIOY/UsQBOj1emOF/5KQ+3kWG2mf6D2yLIuXJEliuygjO2+bqtWqcMA6joN2u516WCRM00StVtuT+fNhGAon+iSBmuIyoiiCqqpQFEVEjGwUco3lidjZ4xhFEW688Uasr6+PRG3HgfW1r+F2H/gAVr76VUhLcoj37353DJ/1LJSe8hSUdB3lKSL1rN+zUMRLp9MRncgUbaNp2piwTTnc2U4U13XRbDYRxzF83xcCtKqqqFarS40VY3GbYRhmF1EsIlYUSFM6k6mTV5IkhGEo7q3o+p68zheLRVHzRFGU3HpLWec2dcoCx2udpMTtG24A/uIv5tufZz5z9wnGj3/8qLDly14GXHXVyKn96EePtpOLHjN7BBa3GYY5YaCh40lM02TXLTMXqqpidXUVrVZrzOHZ7XYRhiEqlQp3lJzghGEoRO1J8RSqqqJcLsM0zW07X2jUSrYNJGRZRrlcFvEQcRyj1+vBznEFS5KEcrm8Jzt0XNfFYDAYKxAZx3EqH9v3ffHQu5FrhCzLuQI2ZWVPI45j2LaNG2+8EY7jwLdtVD78Ydz+gx9E6ac/XXhb8oh0Hf3HPQ6DZz4T5j3ugZUlt11RFGEwGKDf7wuBgNzaw+EQpmmOCduGYQhnd5LhcJiKhqIOI1VVUavVoKrq0q7j1KGRhMVthmGYHUSSRu7tZnPiLFnnNnUWk8s6KVRTfYYgCMTItSyTYkmS9w2pWJKPfxyYEPGW4sEPBi67bGl1LJbK6acD//qvO70VDLNhWNxmGOaEIa+IZKVS2cEtYvYasiyj0Wig0+mMiYQk4mSH0jMnBlEUwbZtEbWQh6IoKJVKufnCW0UcxxgMBuj1ehNzpC3LQqVSEedtEARotVq5xRQVRdlzWfNRFI0ViCQxm1zAQRAgjmNRIHOR7zFlkOu6Dk3ToGnahtsAz/Owvr6O9fV1uK4L6zOfwZmvex2sG2/c0PKyBIcOYXDRRRhccAGilRVUq9WlxXkAIwGh3+9jMBikzrdkIVLTNFNRYHQtztuOfr+PTqeTWr7nedB1XXQmFovFpX2fssL20otJdjoj116St7xlrmH3DMMwJyy12lRxWz7WEU/FI5MFiAGM3f9Qh/MksrEkJJgn7+9Szu0f/Wj2Ppx5JvCBDyy1lgXDMMdhcZthmBMCKvaVpFQqcRFJZmEkSRJuwWx+u+M4oyJvmiZGBbDrb39DRRmzBe6SyLKMUqm0VBFuHjzPQ6fTyRWpgdGDWaVSSUWjUIRE3r5QDvdeiCGhLO1er4fBYCCKRdLvsizDMAyoqgpJksR31jCMmZ+RqqrQdV2I2bSMzRCGIbrdLtrt9ugz+8EPcOt/+Acc+PrXN7Vcwrvb3WA/4xlwHvlIQNMgyzJW6vW5YnHmWr7nCVd2Fop/ieMYlmWlHP+6rov2NEuv10Mv4cYDRm2sYRjC9S1J0lILmWa/K8v4bFN43kjcSHLZZctbPsMwzH5kRgcgObdJ3CaSmdtxHM/dnlMkWXI5SXGb4t6AY9FcR45MX2C9Dnz0o6OfDMNsCazqMAyz78krIqmq6p4cUs/sHkqlEhRFSQ2XJ8gN2uv1oCiKELp1XefYkn0CRSzYtj1R1CZXaalU2lZBOAgC2LY9NYIkK7bHcZw7IgFIO2sdx0G/30cQBKL45DwvEiKXQRzHwlVFryiKEIYhgiAQYioJlZSvnX3gDYJAuLQnfUZZV/akIcyb2RfbttFqtdBut9G84QacfPnluN0HPwhlE9neABBrGoaPfjT6z3gG/LvcRUxXVRWNRmPTnbvUgdDv98c6j+n/tm3DcRyoqopCoSDEdIq2yevwmXQukjCRdH0XCoWlfh554jbDMAyzs0i12tT/J8XtrChN144wDOdq05P3FATlc9Oyk5EkkiQBR49OX+jDHgacccbMdTMMs3H4jo1hmH1P3nB8zkZmloFlWVAUBc1mc6LAScP0+/2+cIuSQ3QvOGCZNFQgL684LUFuUuoA2a7tcl0X/X5/LBM+STaCBJgeQ6KqKur1OuI4xtraWq6IOS/zCOD0Oz1Y5gnYed+1MAzFyAn6P4mv2eNB30PqbHJdV0RdlEollEqlpbqys8RxDM/zYNs2ms0mBoMB2q0WSp/+NO7x5jejMOshedbyDx6Ec9FF6Jx/PqJDh1L/MwwD9Xp9U21PXp523jxUuLRWq6VGsGiahnq9nisyxHGMVqsFJye7VNO0sc9imZEqABeTZBiG2ZXMcG6riVgSipdK3kuoqjq3uJ2Xt03ObZqeiiQBZovbBw/OXC/DMJuDxW2GYfY1vu+j3++npnERSWaZ6LqOAwcOoNfrpYS1PCj7dzgcQpKklNDNOd0bg1zz29FZRaJ2Npc3CYna2+X4JFdy1pmcRVVVVKvVsRiKwWAwVo+AKBQKKBaL4tzeLFEUTf1+LEocx/B9H8PhcEx0p+nJ9WmaJqJIgONFH0nEJvHU87y5iz/Ou52e54kX5X87jgPP8+B897u4w2WX4eC3v725FZ17LqI//EM0H/YweDnbXSgUUK1WN7xPk/K0s9Dnku3ckSRJdB7kbUMURbkFewGgVquNXcuTn+UyoBz2JEsXtwsF4KUvHZ/GMAzDTGaWc/uYuE3XFsrdTt53zHv/kc3bVhQFvu+LopJAppgkMFvcPnBgrnUzDLNxWNxmGGZfkyxEBYxueqpcuIlZMoqioFarCVGHHKTTRFBylZJoqOu66HjhofCz8TwPvV4PnueJQoDTXoqijLmE58V1XXS73YnZ1QBEkbztcnq6rovBYADHcSYWsAQmxz9EUYROp5ObkUwiZBiGWFtbm7r8nSCKIvHdyQr65KwnsVuWZViWBcuyRFZ2qVQSeZp550EQBOh2u+j1erAsC4VCYaECmlkxm87RZIxHFEXo33ILDr35zbjtRz4CeaMRJIoCPP7xwPOeB//ud0ez1crt5NhM4chpedrpTVFgGIbIxU4iSRLq9frEjuUwDNFsNse+Y/Q+SZLG/rfsaDEqKppk6d/nYhF42cuWu0yGYZj9zqzM7WPiNkFOa+B4UclpBoAkWee2oihwXReKokwWt2dlbrO4zTBbDj89Mwyzb8krIlkul9khy2wZkiSJQnOVSiUldE8TRgEIEazb7UJV1VRBSo7QOQ5lmWedxIu6gpMRGFnhO1koaFbMh2EYKJfLC4mfG4Wc/5R5PQ1ZloXzOtvm+b6PVquVuwxFUaBpGmzbnihqK4oiMqrpuE96LVMYp++T67qiQyPpsA6CAI7jQNd1lMtlkfFMed9Z17DneRgMBhgOh7nbGcexcMVrmoZCoYBCoZD7fSRRnYT1vBx+27bh+z4814V5xRU4901vgrW+vrGD0WgAv/u7wHOfC5x2GhzHQWt9fWy9siyjVqstPFppVp52El3XUSwWIcsyWq3W2PdQlmU0Go2J35EgCNBsNsfOR1mWUT9W9LLZbKb+p6rq0ophJrcjCbULDMMwzA4zZ+Y2kI4RAY47tjcjbtO1NS9zG4PB6DUNFrcZZsthcZthmH3JpCKSy87nZJhpaJoGTdNQLpdTmcB54lcSKgho2zZkWRZCN4ktJMyeSIRhiF6vN7FI4qIkixLO6njIQ9M0VCqVpQtseVC80iQRNomu6ygUCrAsK1eE7ff76Ha7Y8uhgkvkis4jrxDlLOI4nip8T/pfstPB9324roswDGGapigiSNsQRZEo7Fkul0UWfvKYVKvVMRdusiNqVqeB7/vodDopN7emaTPzp6MoEhEkQRAA11yD273mNVj57nfnOn5jVKvAy18OPOtZIs6i1+uhl3iwJzZSOHKePG3CNE2RT+44DprN5th5NWsbfN/H+vr6mCCuKAoajQY0TROdFkm24lrOedsMwzC7lBnObTlzDYyiSNwH0LVso7EkySKVdI1LZW7PUyeDxW2G2XJY3GYYZl/S7XbHbmI2kzXKMJtFURQUi0UUi0VEUQTXdYULdVZON7lHsySF7qQTOTtt0v/2wveBhMt+v7/t8RhhGCKO41T2sqqqQkDdSsgJnDcCJYskSbAsC8VicaIgF0UR2u32mEhIERqKokBV1dxjLEkSisWicGsvgiRJUBRl4REzQRAIQT+KItFRlIWc0uSgT57TkiShUqmk3NYkqCfFcVmWxXdzVtwLidVUUDSKIlGYMknS+RyGIby1NZz8lrfglA9+EPKc7rGxY/Lbvw3v5S+HdKxIZHwsLz37mUqSlOpUyxbGmoTjODPztKlYarFYFIL1pNx2TdPQaDQmfvau6+Y6vbOCeDZrm0YlLBsWtxmGYXYpM5zbeeI2teEbcW5Pug7mxpLMI25zQUmG2XJY3GYYZt9BQ82TWJa1LQ5LhpmHZA4wiYuTMoSnsegNe5ak0K1pGkql0q4RdOI4Rr/fF47cPGRZFpEgs+IxFonJIEE9GUdCTm1N0xCGIYbDoYjEWKaLPggC0Zkxy2VEo1Esy5q6DZ7noZWTxUxROFmnM0Gi+XbGOZEgPC0KBhid80EQQFXV3I4G0zRRrVbFdlNuNInWSdGdPkf6WavVUhEwyeNGn31S/M6OrqAIkjiOEUcRah/9KE557WuhbzCCJD73XLRf8QoM73zn0YRjgvCkHHiKM2q1WhtaXx7UOUeueWKSa9wwDNTr9Ynn5XA4RLvdnimIU+dekknRMJuFxW2GYZhdyizntudBcl3Ex6LIqKAksJhzmzqtk9f9pAuc7h9S4vasvG2AndsMsw2wuM0wzL4ijuPcIpKVSmWHtohhpiNJEgzDgGEYqFarC+V0bxaK5gAghv5nc4m3G3IskzM2D8pPppzfRZgmfIdhCNd10Ww2MRwO4fu+cKrqui7yvpNObgC5Iuk04ZuOdRAEIjea1j2PS5uiOebpsLNtG71eLyUi+r6PwWAgxPG8z9o0TVQqlW0rbkp587P2n45nHMe5+y/LMqrVqug4ooiN7HcpjmMEQYAgCHKFdPpcdF1HEAQYDofodrsIgmDseCVHV1iWBU3TYJomou98B4f/5m9Q+ta3Fj0cI+p1xJdcguYTngA3EZdCBS/zvh+lUmmpowooT9s0zdR+07U2b0RJoVCYOlKq3++PXaeBfEE8L4pnKyJJSNBIwuI2wzDMLmGGcxsYFZUMDAOyLKfEbTI2zGMEyeZtZ/O7s6P55nJuy/KoTgbDMFsKi9sMw+wrBoPBmIjBRSSZvUQyp5tEUNd14fv+QgUTN0Icx6JYY71e3zZhk3AcB71eb6KoT0JzqVTa8Hc6WSySIGG53+9jfX0dYRiKPGYiG41AwjUJ28lXUtQjkTSKIiGm0sMR7TM59slNnBTHVVUV66GChvPsexiGaLfbKeE2DEMRczKpCCZlUG9HgUxg9CDZ6/UwHA6nzmeaJlRVFZ0CecJpoVBApVJBFEXodDoi0mQjRFEEz/Pg+z6Gw6EoYknfRSpoSZ+NaZoiqmN4001Yed3rsPq+90HayPolaZSpfckl6Ok6XNsW/6JOgLzCkcssbEoxN3nLi+MYrVYrN5u9VCpN7Uye5PS2LAu1Wm1MQM9+7yaNMtgs2TaHPtel0+0Cf/RH6Wmvex3AHfAMwzCTmeHcBkZFJYOVFSFuJ6F7rKRQnUc2yktRFERRlKrxkbwuSpI0W9xeWRkJ3AzDbCksbjMMs2+ggnNJNE3jIpIMAIgcXRKi8nJydxuqqgonNZEsxJf9Oc//5onl8H0fR48eRblcXqh44EaZx7VL8RjLENwpCsZ1XeGWpnzneZlWjJJET3IKkRibzHmetF0kgBNUIJKKFzqOA03ToKqqeFCjddA20TJI2CVnseM4UFU1Ny6COlRM05z7GGyGKIpEgdBJ5yRlK5umieFwCDsh8iZRVVUIqq1Wa2akyTyQuz15TpJr3jTNVJFDyiq3u13Ur7gCt3vta6FtNBLkHvcA3vAG4LzzMBgMYLfb4l+UwZ4UXeM4Fvuf/G7kHdNZ0yheJZmnnSWKIjSbzdzvarVanXi9jeMY3W53TKwGRk7sSqUy9t1wXXeswOdWXc+3LZLEdYG3vz097dWv3pp1MQzD7BfmdG4D+bUlkjF+08TtrHNbURTxdzZvG5jTuc152wyzLbC4zTDMlkFuSBravdX0er0xl17eAzNzYuH7PjqdTkqM6ff7QsixLGtPCN0E3ZRv1FWYJ36TazkpdJEY5TgOarXalri453HtUqHAzbYhFD/hOA48zxP7Oi27mIpHAsfFbHplMxkJ3/fh+/5EoZ7c2SSAa5o29lnKsgzDMGBZlsiOtG07d915Lu9k8UQSROM4Fvnc2UgVKpC5Hd+BebLUk9tERQcnDScmJ3un05k55FhVVSGWZzsFqEOAjldWVE0iSRLK5TIOHTokCkdK3/gGDr/ylSheddX8ByNBvLoK76//Gv4FFyAC4Bw5gvX19dR3FRgJyEnhVdd1NBqNpea+TyIIAjSbzbFjI0kS6vX6xI6ROI7Rbrdzv+flcll8x7JkhXBN07bsXiL7/d/uUSsMwzDMFOZwbmuJa4YkSWKEFRk8gNm523niNl0fJorbszK3OW+bYbYFvnNjGGZL8H0fa2tr4kaA3LKUR7psEYWLSDJZKGIjK9oSyZzcvSp0bwQSV5MYhgHTNNFut8eEK8/zcPToUVQqlaW5JkmsnebapQKOG/0OR1EknNmu604Uorvdbu7DTrlcxsrKinDtkPiZXE4cxyK2guJj8rJ7k5A7m+JKhsOhKE6kqqpwZVP2+iynPXUiEsloE8/zxBDcbNSILMsit3y7zvfBYDA1Sz25TVEUTRRECU3TcjOZs1BG+TTxlbK5dV0Xw5CzHRq0rGRHgPa97+HApZfC/Mxn5jkE4+uWZQx++7fRfeELEddqwLFOjHa7PXYelcvllLA9K9t6mfi+j2azOfbZybKMRqMhzi36rvi+n/qZ9xlNc3r7vj/mwN/KUVhcTJJhGGYXM08sSaZDlFzaSUPArE7wSbEkwCac2yxuM8y2wOI2wzBbQraAWRiG6Pf76Pf7QuheVjREXhFJEnOYExPXddHpdKa6L5PkCd2macI4VnX9REDXdRw4cAC9Xm8s/oG+Y+Ti3qhrPIoi4dqdJEiSa7dQKCy0bBKaScymXORJ0OdN88iyLHK2V1dXJ7pJyalL4jw5tDVNS7lnk3Ew9GCVzGgmdzflN1JxRyouGcexcB4tehyS0SaGYaBUKoltkyQJxWIxNW2rcV13ojs+b5sGg0FupwPFyVDHwLSCqxRpUigUpkZskKhND7PU0ZBEURQUi0UUCgURNRP+z/9AveQSaFdeucihSOGddx7al1yC4E53Su1j3r5blpUS5yuVSiquaCuhIqvZkR1xHKNUKokCsPPWBZAkCbVabWrhy7yM+2UWykySNwpjy8RtywL+5E/GpzEMwzCT0TSgUAByihgTaiaakuqbJI0Js8TtZKQbABExl7wfo+uDGCnH4jbD7ApY3GYYZukks0jzSArdsiyLh/aNCt39fp+LSDIARudWt9ud6PaknOJpothuE7qT0QkkjiZfy0SSJFQqlYkubtd1hYt7EfGZnLF50UHERpzElEFNgvY8wloURbBtG67ripgDckurqopGozEmbJGomiz+CBwv/pmcj5zb9IBEQiwVmyRHMomoyQKUlKddKpWEwErLyrrHk0Ij5XnTOuh3Wj5RKBS2tW0kZ/y0DGzKUlcUBY7joN/vj0W6hGEoHNqzCmpSnYVpMSt0DRoMBlPPGcq8Ty3re9+D8rKXAR/60OQdn0F44AC6f/EXGD7xiaPikQl6vd7Y907XdeFapnzt7cpG7/f7Iook2RYBI+f1pBz0SciyjHq9PnVERhRFY214oVDYsvY3ez3I6+BYGqUSZ2wzDMNshFpturidiSWhIpLA8TiSadf8vMi55HWH3psUtwFw5jbD7BJY3GYYZuks8rBLTs6NZiBPKiK5qOuT2fv0+/2J4qkkSaIwoyRJogOG8pcnkRW6KQd5K4TupOOWcptnOSFJ1Ey+knnO2enzbjO5uPMKwEVRhFarhcFggEqlIoZ8kpMz+Tv9nVcYLrkPiziJKSN8MBjAdd2FnM30XsrxTh4PwzBShRZpXjpP5nWkapomYl4MwxBCLOVfHz16VLRxeYK87/totVqwLAuFQkGcdyRc0+cLpIuLZiNTkpimOVZwcCuhdjkbFZXEMAxRE4G+Y7Q/YRgKd/twOEQQBCgWixMFXUmSxPGalsk8TxFLAKKDwTTN4+fI1VcDL3858P73z3cQcogVBf3f+R30XvACxImRRfQ9JgHfNM1UJvvq6qoYGbCVHRPZSJFOp4NOpzN2rCgyaNHONV3XxzLD88hGSUmStKXX9GzbRJ2gDMMwzC6iWgVuvHHiv9WcUYdJowAw3bmdvY/KXgeysSRzi9vs3GaYbYHFbYZhlgo57JKQ085xnKU7Zrvd7tiD93ZlkDLLgcQsEnaTYl92GHze7+QOzRZ8Icjp6DgOhsNhyuFKsQWe5wkxeRLkJqRlbEboJjEyKWJPyqWdhohImDHMkkiK4VkRnJaXFaglSRIRL0nRGgBuuukmlEqlDediL+Ik9jxPHP95hGbaX13XYRiG6EjLizYol8ui44Py++cVtAHM1V4Nh0N0Op2U27tQKAgXedJxTb/HcSyyzuc5x6IoSmUd03ZtR0FfWr9t2xNz7oF0kU5ydUdRBM/zhDvedV3R6UTObnJhJc+VZFzILKHVcZyZRScpwiV1Pv/whyNR+33vAxb8fiYJ7nMfuJdeCunss1HL+f7RiIBsLvrq6uqWdEpQZ5rneeJ4J3NF+/1+7giYvI6hLNTJk82Rn+d7TqM8kliWtaWiPudtMwzD7AFqtan/ljNmp+Q1lUa8TbsHyMvbDoIgVaQ7aTCQJAkYDoFZpi4WtxlmW2Bxm2GYpZLnuCLxqlwuC8fscDhcSOjOExJd180V0rdLyGEWgwTd7CsbsTAvJIJMKigny7JweyYrpc+CxEGKAUmKjknHLAmtkiQJYTPl9DxGnht7XjF62STF8Gnfvyzlchm2bY/FDUVRhG63C9M0hTg8D/M6iamzbDAYzJ2frqqqcE5TW5DnQAdG50itVoOqqrBtW7iE52He2gGUoZy3fl3Xcdvb3lYcx7x1kwBcrVZnHi9qK7e7kO48sTPUmUT7Srno9JMKY5KoTZnZqqoK9zxw3MVLHRKzRvlMO/6EZVkoFovpa8d11wF//dfAe94DzNl25HLyycCll0I9/3yoE7aT3PpZ6vX60oRtyqQnMXvSqBAqxJsXJWNZ1ljOd1K8TorYG+1gTsb+EFtZSBJgcZthGGZPMKOopJIRmek+npj1LJB1biuKMmasETnbmLOYJMDiNsNsEyxuMwyzNEiQTpLNR6UM01KptFA0RJ6QmI0j4SKSO08yWiObEzyvuDwPvu/Dtu2JQuSiYmsSctZSnEayIybP+awoClzXFXE8SdczvYfm3ajgQxmwdGO+kc6AzUCdVIZhwLbtMfGJvsPlcnlq55Ku66hUKlPnoYKNFDsyz7blxYAAowebVquV276QOG3b9tT2J4mmaaL9mUcAowiXvP0wTRO1Wk08eNGxzSu2SVnnyWid3QIVE5zWKaBpGiRJQrPZFA5tmp8EbvqbOieyx5eEe9M0RdFNKiRM34+kyKppmvj887aNokyS+eYAgB//GPh//w945zs3J2qrKnDxxcBf/iUwoTgpMDpHssUagVHByM10UpCLnzoMZhVYpfdMKvxZqVRQqVTGhOxln4vZTgjKxN8q6JqVhMVthmGYXcgCzm2KzEteo8jcQaMSs+SJ28lnlyiKUteHucVtztxmmG2BxW2GYZZGXnGuaY6rpNBNDs1ZQjfl1uYNly6Xy0svsMfkkxSts2L2VkLREpMKltI5tQxxgoqdWpYlhG4S5hZ1PhPJ3ORs8T+60VYURYhzSREpCUWHUPGb7Cs7fVliuK7rqNfrYy5u2nbbtkWMBAlf1CEwy1FMHQmTnPh521IoFEQ+cRbP89BqtVLnJLlX6f3T3LwECaqmaS4UjRAEgSjEl6VUKo1FO1AHgmVZ6Ha7Y+c4OWqHw+G2FhSchOd56Ha7E9treqj0PA+9Xm8s9oIcxDSfYRjQdX3sGKuqOjP+hz7XZDQRXU8oGoNeFNVSrVbT6/rJT4BXvAK4/HJgM+2YogAXXgi85CXA7W43ddY4jtFsNsfazUKhMOaQngVFuyTF7EWgzgJ6eKeCpKqqYnV1dcvd0wBE+5pkq9ebFwe1Xdn0DMMwzALMcm5nTE90D0oki0rm3c/lxZIkr0nJDG+AndsMs9vguzeGYZYCZXQmsSxr7odERVFSQjdFl8zrqCShi9kaNlPEb15kWc4d0k6/Uw5ysrgY/Y+KEhaLxZTQmfw/QTevydcsV/k0oXsRkjfO5OimfSYRNZlVSwJ4FnrvvGJrngCeFcFpueQwn/b7wYMH4bquyLzPK7pTLBZnOk+DIBCxI/N0jJDQOattsW0bvV5PnKfkYHVdd2phwuR6CoXChrN+HcdBu90eO68kSUK1Wp3aVqmqikajMTEjmkTzXIF2C0nGWlA2dt48dJzp/Eq2FfTdISe7qqoi1kWWZei6Ll7k3pYkaa7iqgQVsyRxl+JOgPQIBN/3R8fu5z8fidpvexswZyRN7vGRZUgXXDByap9xxlzv6XQ6Y20IFV2cRRiGKTF73jidLCT427Y9dj7Jsox6vb5tMTfZewgaXbGVZDsB6HhsGb0e8OIXp6f97d9OdfczDMMwmMu5LUnSWJQITaP7qWz9DmKeWJIxcfvIkenbLElAozF9HoZhlgKL2wzDLIXhcLi0nEwqElYsFoXQTUXGJsFFJLeGIAhE9vkyYkUoPiDpCkw6KvPwfR+dTgdxHOeKgrqui9zkjZLMop70ohvcjQjd5M5O7m9eLu2kopYkZOcJzYu8km7qzaJpGizLQqfTGRM6wzDE+vo6isUiKpXKmHOGYkfm6Rwgp+08efpRFKHT6Yj2iITUIAigKMrU3Gr6XAuFwqac/7Zto9vtjk1XFAX1en3umgAUs9Lr9XILNFKbWC6X5y44OS8U1UBi9qyCp+TOdhxHdFIlCYJA5DwnXdpJIZu+E4VCAcVicaKrKlkwk35PHpO8WBfgeCFLVVVH2/KTn6B22WUw3vUuSBsYhSGOlSTBe8ITYLziFcBZZ839vn6/PxbjRedI3mdJ3xtqbzY6SkbTtNSxlyQJR48eHTsvFUVBo9HYtogOutYnWfZ5nce25207DnDZZelpL3sZi9sMwzCzmNHxK3e7oggkMHrmiKIIsiynjCx5zzNZswcwug5mR/8tHEuysjIa0cUwzJbD4jbDMEvBzhTxoAfnzTJJ6PY8TwgY5XKZMzKXCA3pn1d8zCNPvE4KtPNuxyRhDziesb4Mxz4Jv5OEz2QMSPZlGIb4naqqkwCdXP5myA6V3Cx5wnfSOZ/8OW3bSQAbDAbodrtjDwz9fl8UQ0xGRczj/DcMQ8SOzHP8giDA2tqaWGdStNJ1PTe2iDL8Z8VezEMcx2i327mRSZqmodFoLOyyliQJlUpFdCJkv49ULHE4HKJarW64zSXRmITsZPuaB7m4+/2+yNtOFvBMzuO6LsIwFG74QqEgxG36vmmahmKxCMuyZp5v2WNIcRzr6+vCjZ11jNN6JUmCfNNNKL/+9Si8+92QNti+ASNR23n0o+G+6EWo3vveI3fWnNCohySSJI2dI5sdMSNJ0piYnfwOxHGM9fX1sbZFVVWsrKxs26gAIL8Y9XaMxspzbjMMwzC7kBnObanbHbuHSIrbSed2lqxrO+9eZEOxJBxJwjDbBt/BMQyzaRzHGRsSvWhe6DwkhW4SNGgoO7N5PM8T0R/zuLSTgnD2tVkx13VddDqdiUPtLctCtVrdtoz1eWJAKDt4kuuSxO9kXvmyRet5SRa8TJI3OiIrducJ3yRYttvtsWUEQYD19fW5tmsjcSBxHKPT6eCWW27JFQCTwiYxK697UcIwRLPZzHXdW5aFWq22qe+EpmlYXV2d2Ing+z7W1tZQKBSEUz5ZCDVJFEVjzue8czAbX0OCMbmbqEChaZooJ1ynyexn+j9FsRiGkTrepmnOFV8zDc/z0Ol0ROQIcHwkBsXjSJKE6PrrYb3pTSi+612Q5ihUOo3hox6F3vOfD+nss7GysrLQZxsEAVqt1th5WqvVRCet7/sYDAYYDocLjZiRJCklZJMzexJ5mem6rqPRaGxr/Yo4jnOLUW/HNnAxSYZhmD3CDOe21OtBkSTQnQ85txVFSUWb5d3z5OVtAxDXarpvXti5zcUkGWbbYHGbYZhNk3Vta5q25TmZFFXAbI4oioRLe54CZORaoFzoZKY1iVoUPUDT6eek35PToigSTtQ8VFVFtVrdtgzYRZgmxMiyDFmWc4UTioDIit7bUaBzHqYJ8CT4k+hdKBSgKAr6/f7cgl8yDoTyDbN54DQt+5NiSPIKQ8qyjHK5LDq/KK+b1rMs8gpXEpVKZakdfSTI04iGLIPBALZtC6c0kI7yoBeRFayTYvYk6DPPOrUpBsbzPPE9LZVKY857cuQWi8VNRwl1u93c40CO90q5DPkrXwFe+1rgIx8BNhmtNPit34L9ghcguOMdhbt5EQE2iiI0m80xwZrOU9u2J3ZK5JHNKaeM8rn2ZTDIzbjebmEbQK6Ivx0FLIMgGFvvlovbpgk897nj0xiGYZjpzHJuxzHU4TAVA0LGE/qd7h+z5OVt03uA0T0HFYEn5srcZuc2w2wbLG4zDLMp8rKGt+OhlNkcNNR9nogIyosmUWwn3MaSJImCo/stW52iA2YJ3yRELvpaRlb6JGi7sm1AFEWiSCSJodnt0jRNOHmHw2GuSDmNIAhg23auEKiqKiqVisgFtyxrS0Z4DIdDtNvtse+QLMuo1Wpb0gEnyzKq1aqIKknuv+M4wo2bHD6bFK2TruZ51pWMFMoToyl6hFzSBw4cyI0XoZE3y3Dk+r6PVquVO7JDlmXULAvmhz8M/MM/AN/5zqbWBQD2Qx6CwQtfiODsswGM9mVRYTuO47FtjuMYsizD930cOXJk5mdCMTpJMXsjkNs9u+ydELaB8UKSlMG+1WTbDrrWbSnlMvCGN2ztOhiGYfYjcxRbVm07NV8UReL+L2meyJInbifvn6kw5Zi4zbEkDLNrYHGbYZhNkXVtK4oCy7J2aGuYaYRhKIpDziNOm6YJVVVnFkvcapZRMHKvMk34XoR5BHCKq1hGXIqiKCiVSmJUAIl2qqqKQon0gLCo+B5FEfr9/ljxOcKyLKyurooYjK3oDKE8+Gz7B4z2sdFobPn5quu6iCpptVpYX1+HbdsTo3xmQdE70wqeEnEcw/M8BEEAwzCwuro6seNJ13UUi8W5s9OnEcexyPnOE4KtbhfV97wH8pveBNxyy6bWBQCd+94XvRe8API97iGmybK8ofz0Xq8nInuCIIDjOAjDEJVKZeK5TCwzRicMw5mxKNtJNh8f2L4Oco4kYRiG2UPMcG4DgJIjbievm5PE7bxYkuR1kgwDY6NQWdxmmF3DiacUMAyzNOgBPQnlmzKTocJ6YRiKuApZloUjgF7LWpfjOKIg2SwURUGhUICmaSLiYKdYZsHIE51JWeDTINd4NiZl3rgUip8wTVMU+ttsDMVwOJyYQ6zrOg4cOLDl7tMoitBut3MFScMwUK/Xt8X9SgV2bdtGq9VCv98fE+vIeZ0lK2STmJ03H7lZ6afneXAcB5ZlwTTNXEFQkiRYloVisbg0wTAIArTb7dyONu3qq1G7/HJo//ZvwBI64rr3uQ9u/r3fw/CYU9uybRSLRSFsL7pPlJXuuq6oUUHu/knfS2qLLctaWkcJucez399SqbRjndJZ1zZ1gG0HWVGdxW2GYZhdzLzO7WOQsJ28J6MYtix5zu3k31EUjReTBDhzm2F2ESxuMwyzYbLCpyzLLETOgIqJzZOpmhS6JwngedNpPeTSnuWMpaHulEVs2zZ6vd7E+VVVha7rqSIr9HPS75OmTdue7SwYyYwzb1zKrJxwWZY3lJGePK+p2GkURcL1TYK9JEnCPbzVxWWDIECz2cx1RxeLRVHMcaugjHzHceC6LlzXhW3biKIIxWJRfO9pGC7Fg0wr+kqRI8nCofQ7HWfqWOj1euJ45yHLsogeWWa8w2AwQKfTSbcbYQjzM59B6V/+Bfp//udS1tP/jd/ATb/3e/DPOy8log+HQ3ieh1NOOWWhc4xywW+66SYRFQMczwTPHiPqFLAsa0vqCnQ6nbHOAcMwUgVBt5NJHeTbBYvbDMMwe4h5ndsJKE6ESNZyoenJuiNiOceKUCYZE7cdB5jyvASAndsMs42wuM0wzIYIw3Cs6N8yslT3M67rotVqzR3DkL3RmodkYcZZaJomnIFxHMO27VSERBZFUVAul3PzdDfCJAF8mc71rYQK9dErCAIhWu3GgpfLZJbwnRW9wzAUQvW8P4GR+NTtdiFJUq7oJUkSyuXytowYmfT9lSQJ1Wp1yzr2oiiC4zhCYKXvTb/fH2uDKWtc13UoipLKZs4Tr6dFjxCU4z0t7kTTNBSLxaW1DUSeS17q9VB43/tQfOtbof7850tZj3vf+6L3J38C3Oc+aMgybrrpprF5CoWCGDVQrVanuqk9z8NwOIRt27kFJEulUuq7YxiGcMJvVdvX7/cxGAxS01RVRb1e37HRVlnX9nZ2kOcNTWdxm2EYZhdTLI6KRU4ZPahmxG3qoCeo3U8W3s4aM+g+dKZze5ZrG2Bxm2G2ERa3GYbZEP1+P3WzMEl8YkbYto1ut7vl60kKxnnIsgzLskT0COUX27Y98X2yLKNcLqNQKCxVBNlIVMZOQC7lpIjt+/7EDoRms4mVlZUtdxHvVpJO4Y0SRRF6vd7UIpOFQgHlcnnrC8Bh1N5lC/ABx/OXl/1Z5wnaRBiGuWIzxcCcdNJJoi2mzqKN4HmeKE45CdM0USwWt6Qzx3VdtNtt8XCp/PznKL71rSi8972QlxSX5N773uj9yZ/Au9e9UC6Xoes6ms0marVaKi+eMsNpu44ePTpW4DaOYwwGAxEPE8cx2u32WDtBIraqqsKlvdX57K7rjl1/JEnatgidPGgUQpJlX2OmkXXkUVQPwzAMs0uRpFE0SbM5cRa134csy+LaS9cUmpYnbuflbWeNQski3bQ8FrcZZnfB4jbDMAsTRdGYA8yyLH4wzIEEjuxDPAAx7D9Z0G+aML0ZqCAZOSvJqU2RBnlIkoRSqSSyZk8Eoigac2OTUDUvcRyj2WxidXX1hCyCuRlIIOz1ehPPS13XhTt5O7an0+mMtXfAyOW5kcKCk5gmaBPJGBIAIiLEMAxUq9WxDOeNCIW+76PX600tcmgYBiqVypY4XSnKo9/vA3EM/b/+C8W3vAXmpz4FaQntYyzLcB75SPSf+Ux4d787FEXB6jGRd21tTQxVpoKkURSN7ScVFB0Oh6hUKuLvZIdD9m9gdNwOHDgglr0dTCogWa/Xd9SpnJedv9ORJNsirNs28PKXp6e99KVAqbT162YYhtnrzBC35W43JW4Dx7O3kyNik//Py9temrjNmdsMs23sy6fuKIrwve99D9dffz2azSZUVcXBgwdx5pln4va3v/1Obx7D7HnycpxL/GA2xrR8bdM0UavVxkTjpNCdfM2anieEKYoiXNp0Q5YUDycVBSQXfqlU2teidp4be55CifMQRZEQuPfzMVwmruui0+lMjL9QFAWVSmXbCt+RKJjnXDZNcylxDiRoU4b2pE6UZAwJZdJT5Igsy0uJRQnDEL1eL1fIJzRNW2rsTnZUBL3i4RDWRz6C0lveAu2aa5ayrqhaxeApT0H/oosQnnoqgFGnbLVaRRzHWFtby72u1et1OI6DTqcz1j4Mh0McPXoUiqKgWCyKjo5sAV/qXDz11FO3tROYOtqy+1Uul7etaGMedD4nMU1zW4/NtCzVLWU4BC69ND3tT/+UxW2GYZh5mJG7rdh26r6bRGqaRtfD5PV8HnGbRiUSc4nbkgSsrMzcJYZhlsO+Erc7nQ7e+ta34j3veU/u8GEAOOuss/C0pz0NT3jCE+Za5g033ICHPOQhG9qeQ4cO4Utf+tKG3sswu5VJD6XsUE0zLV+7UqlM7AygodGLPuRnxW/KRE6Kb1QQblp27nZGPWw3vu9jMBgcF9CW4AKVZVlkT/u+nxK0qPjgysrKnohf2SmCIEC3253oFKYRBMkIiK1mMBig2+3mfn/L5fKGCvBRDnlyRMA852EYhrCPPayRY52OA2Umb8aBG0URbNsei5pKoqqqyNvfKFkh2/O8sVER8toaSm9/OwqXXw5lbW3D60oS3Pa2sJ/xDAyf9CTEx5zBmqahVCrBsizREZUVrg3DQO3YQ7RpmjAMQ0TlUIFT6vgIggCe54lCmv1+H6qqwjAMcX1cXV3d9na13W6Pibimae5YAUnCdd2x69B2d5BzMUmGYZg9SLU69d/k3E4ShqGYRs9LyWt+XiwJgDFxO7lcWZaBI0emb2ujMcoIZxhmW9g3atRVV12F5z73uTg6owft2muvxZ//+Z/j05/+NC699FJ2mzLMgjiOMyYC8PcozaR8bVmWhVubsljpZin5yk6bJ5t6mihOeat5DnLCsiyUy+V920nh+76IHNgoqqpC0zTxk4r0EVEUYX19PXWcPc9Du91GvV7f1PbvR+YRVS3LQqVS2TZRMAgCdDqdVCcFIUkSarXaTIGXom2SAnYQBBsuDuv7PiqVylgbQK7jjY4MoI7KadFEG83bj+N4zI09Ld5H6nZR+qd/QvHNb4Y8xTm+CM7974/+M58J90EPgqyqMHRdiNR0PpGzOds26rqORqMxFvFSKBTgOA76/f7Ye+h4apqGWq2WEkvr9fq2t622becWHK3NcL1tB9kOck3TtrVGAXW0ZLeBYRiG2eXMuIZJvV7qvohqESWnhWE4M5Yk+6ybK27Pcm5z3jbDbCv7QsW46qqr8NSnPjX1MFooFHCf+9wHt7nNbRBFEa6//np89atfFfN8/vOfx/Oe9zy86U1vWuiBg4SmedivIhFzYmNnCnnR0Hhmdr62ZVno9XpTReZJTBO/86ZLkgTP89Dr9aYWhNN1XRRSAzBXLEf2Bm8v0Ol05ha2yfWeFLEpH30aVFxwbW0tdRyHw6GI1GDmy9XWNA3VanXb2hYSJnu93sSIn0ajkRLAoijKdWIvKmInoQxt0zTh+74QS7PzVCqVDecTx3EsRnFMiyaaN29/USE7xXCI4tvfjvI//iPkdnsDe5PZFtPE4AlPQP/pT4d09tkwDAMlw0i53ZPbnRc7o6rqmLCdjWyp1WpC5KbPW1VVFIvFsXN2mTEu8+I4zlgHK7VPO912Z0e4ANubtU3bkGXbxG3DAJ72tPFpDMMwzGwWdG5HUQRFUcbE7WRhyWQWNzC658vey2WNRnOJ25y3zTDbyp5XX23bxvOe97zUjfKDHvQgXHLJJVjJZBzddNNNeNGLXoT//u//BgB85StfwWtf+1q84AUvmHt9l1xyCR7/+McvZ+MZZo/huu7YQyG7tkdMytcmdzaJIxsle+M1a1uyma9ZVFVFqVQS270omqahWCyKApW7mWR8QJZkrEjSjb3RfSIRdH19PfV52bYtcnlPZGaNIlAURTiFtwvf93PjGwjTNFEoFOD7PobDoRBvl5XPToK2ZVkwDEN0kuV9fzcbQ0Ki56RoInInl0qliW55EsfpejAt5mgiQYDC+9+P8mteA+WmmxZ/f4bwpJMwuOgihM94BvSTT8ZKwp09iU6nMxaFoygKVlZWUtmck0YXUO654ziQZRmGYYy1G3Qst5MgCNDO6Sio1Wq7wnSRdW3LsrxtOfpEXt72tl3HKhXgbW/bnnUxDMPsN2Y5t7vd1PWfikRnBW+6R8/ez9G82Xub7D0FO7cZZvex83e5m+Sd73wnbrzxRvH3ve51L7z+9a/PvYE/fPgw3vzmN+PJT34yrr76agDA29/+dlxwwQU46aSTtm2bGWavknVtq6q6o0Wpdgt5+dphGGI4HIpjtIx85yyUG0euUXpNE8EnuQsXhQTBXq+HUqm0cGzBdhFF0ZiDUVVVVKtVqKq6JXEXmqahXq+j2WymPvdOpwNFUU7I78w8udrbXcQ0jmORoZz8nMIwFA5swzBEwcdlkBwVkBwZQPvsui7a7XaucD6pCO08eJ6Hbrc7dRTHrGiiKIrQ7/dTbuWFiWMUP/EJlF75Sig/+tHGlpHAv8tdEPzBH0D5v/8XpWJx7jao2+2OFc4kZ7OiKIjjWIja0yJbyEHv+z46nU5KNNV1HdUZDrNlQ/nh2W2uVCq7ot2JomhsZFNxgc9tWXAkCcMwzB5lxnVV6nRS15QoinJjSZLO7WwkiaIoqWtVHMdj14m5MrdZ3GaYbWXPi9vvete7xO+SJOFlL3vZVGeKYRh46Utfiv/zf/4PgNGD5D//8z/jr/7qr7Z8WxlmL+N53piTkF3b4/naSXdnMu4jC8WUJAtBZotCJgW3OI5FQbrka17RXFEUFAqFXHfhZgjDEJ1OB71eD8Vica4Yg+0kL/piO2ICDMNAtVodc1C2Wi2srq7uWzGFHhKyL9d1J56rpmmiUqlsq6vUdV10Oh3h2KHihr7vIwxDWJaFQqGw4XNZkqSUgE0/p3Wm9Hq93NEdm4kh8X0fvV5vqjhvGAYqlcrEc5IKWg4Gg4U76ZICvv6lL0F76UshffObCy0jSyzLCB/3OMgXXwztPveBtmB7Ztv2WEetJEloNBpQVVXE00wStfMiW3Rdx+rqKgaDgejUzMtJ32ra7faYcGtZ1q65VmfPIRopsN1wMUmGYZg9yqy6EceMJFnyBG8yCGXF7axzm8wOSdi5zTC7jz0tbv/oRz/CkUSP2XnnnYfb3OY2M9935zvfGWeeeSauu+46AMAnPvEJvOQlL9lVggzD7DayQ4kVRdn2ocS7iWS+dhzH8DxPiNpUtCvv5krXdRSLRZimOVH4oGJX1KFAP0lsoSgNchgmb9KocAohyzIKhcLU9S2DKIrQ6/Vg27YQuberCOAkKLM4iWma2+ZgLBQKY3E0VMBudXV1x4/PolAHy7TXIuKnpmnbnkcchiGazaaIRslmZCuKMlYMcBpJETspZC8SbRNFEVqtVm4MiaIoqNfrC4+0CIJACNKTmHX8fd+HbdtwHGfm50rHIRvxI0kS8I1vAH/2Z8BnP7vQPmSJazXgmc+E9Ad/APX00xd//zE3drYDQZIk1Ot1hGGYKw4n55sW2UKjD3YqeiivE4OKW+4GKNc+iWma294OUkZ8Eha3GYZh9giznNvt9pimI0nS2Ag9+pknbkuSlLo3jOM4ZcAQ+dssbjPMrmJPi9sULULc9a53nfu9d73rXYW4vb6+jm9961s477zzlrp9DLNfCIJgVwwl3i1QTrXneXAcB8PhUNwYmaaJUqk0dmwsy8qNA5m3GNsiD980/K5QKGyJk9rzPNi2nRtxkBzOT47Bncp57XQ6qb8lSdr2mIByuYwwDFMiYxiGWF9fx+rq6q7pVKXOkWnC9WYKJSaRZVnkam91G0LfL4rlaLVaueIlCZfTMuSzAja9NrMPnueh1WotLYaERG3qdJu0H+VyeWLnpOu6sG17amY/bZ9hGGkhO8kPfgC85CXAhz409/bncuaZwPOeB+m3fxvYoAM56dTPYhjGzEK/syJbdhrHccZEe4pZ2S3Xacdxxs7znXCU53XC7dbPlWEYhskwq8PWdaEGAWRZHrtvpWk0PXnfS+SJ27IspzpiZVkGXBfIxB6OwQUlGWZb2dN3c9nh3ocOHZr7vdl5v/GNb7C4zTATyCsAtRNDiXcDjuNgfX0dg8EAjuOkbn5KpVJKMCLBrFgsph6egyBAv98XUQibzeNWFCW3KOJWQe5nErnzIg/iOMZgMMBgMBAi93a64/KKSJbL5R1xS1erVRHNQVAHyU6LT/NkCy8L+j6Uy+UtE/VJzKYRD/Qdm9QZA4w6jrKdMIqiQNd18VpmwbkoisRojElRH5VKZSHhj1zW2U7IJNM6FeI4huM4ol2ahCRJoqNu4vf5F78AXv5yxG97G6TNnFPnngu8/OXAIx8JbPB8odikvDZqmphNmKaJcrm8q529vu+PFQUmN/puGh2SvY/QdX1Hjmv2c6d8VYZhGGYPMIdJRe33x8TtMAzFtKShI8+5DWDsnnhM3J7l2gbYuc0w28yeFrezDyuLDNvNDsP98Y9/vJRtYpj9RhRFY0PbN5NFu5dptVo4cuTIWH4wFRajB3VFUVAsFnOPU7/fR7fb3bCgvd1C9jR0XUej0ZgprA2HQwyHQxiGgVKptOUxFJOKSO5UXAAJTevr6ylhhYoH1uv1HdmuaW7WzSBJkhCMki/DMJZ+rlIkEInFvu+L71ZSsM37vlEnnWVZQsw2DEOI2cvaPooYIgf5tONNsSjzfkemdTAReRnRye0bDoewbXvqds2K5AAArK0h/pu/AS67DJLrYsNdAWecAbziFcATn7hhUZs6bWzbHvvsgyDAYDCAqqoTO2l1XUelUtl04d2thiJtsvu43XE/s6DvaJKdao93PJKk3wde/er0tBe+ENih48EwDLOnmCNqS7FtKOWyuK8hMVtRFDEtWTw8G08HYMy5nbx/YnGbYXYne1rcLpfLqb+zYsY0svP+5Cc/met9n/zkJ/Gxj30M119/PVqtFgzDQK1WwxlnnIG73/3ueMQjHoGDPASF2UdkhSHKFT2RGA6HuOmmm3KLvVHhMBKdS6VSbr51EARot9tTXZF5y84K2buxU0HTNNTrdZTLZfT7/YluVNd14boudF0Xx2kryCsGV61Wd9QhTREBa2trKYcIFZ/LXs+2EhL/p+UxT4OGZ057bTXU6dbv93MjPcitPcmdWygU0Gg0YFnWUkV3cmWTkJ3N9J4G3U/Msy2e56HX602NDklmQGeXOev4EbIszy4U2+shuPRSKH//95By2si5Oflk4GUvAy66CNiE4JjttElG0/i+L8T+vA4MTdNQLpe3LZd/M8RxnBuzQ6OFdhN5NTt26hhn24RtjyQZDEYjEpL8/u+zuM0wDDMPczi3FduGVKmIv+M4Pp6TfYwoiuC6buoeSJIkyLKce1/E4jbD7H72tLidjRZZxH1NedvETTfdNNf7vvCFL6T+Hg6HaLfb+NnPfoZPf/rTuPTSS/HEJz4Rf/Inf7LrHi4YZlHyCkCRy3G/Q47GTqeDZrOZ62qkfG0apj/JKTePW3uvCNnTUFUV1WoVpVJJiNx5wp7neWg2m9A0DcVicWrO8aJ4npd7zu4GF6OiKELgTp4LvV4PiqJsS9QPndOTBNdJruvkayc7CcIwRL/fn+jGpjicbOY0fb8Mw8DKysrSsn4pJz8ZgbIRyuVyblZ/Ftd10ev1pnaSTROk6fhN+m4SNNJhWi56OBjAf/3rob/qVVDX16du91Tq9VHByT/4A2ATRYqTESRBEKQEbapDQMV8syiKInLId0tG9SzyOjd0Xd/2ugLTmDSqZydrduy4c5thGIbZOPM4t4/dVxN0v5OcNimSJOnuJmRZTl2z5ha3V1dnz8MwzNLY0+J2toDkV77yFQRBMNOF0e/38fWvfz01baMOtiye5+Hd7343vva1r+Gf/umfcPrppy9luQyzE+QJICdCp43v+2g2mxgOh7kuYGCUr00i2aQ2Z5Zbu1AooFAo5Bdj28MoiiIygweDAWzbzj2Gvu+j3W6j1+uhVCptusBgHMe5RSQrCffGTkMu92yUQKfTEdEdW0EQBOh0OhOdviSK7Vahx/d99Pv9qYUSfd9Hr9dDGIZCzKZcX4rVqFQqG+40iqIoJWQv4srOQud5HMewLAuyLMNxHDH0ldxDtK2O40zNDQemi9rzFJoEMHX0CW3v0LYRvuMdsP6//w/mDTdsZPdHFArAH//xKJJhjofVScRxjF6vh2azKaJpsq4ry7JQKBREGxHHMQzDEOfEdhQ3XSYUJZNEURTU6/VdsR/0XcyLy6Hv4k6QVxh3t7Z5DMMwTA5zdODKvV7qPoja/bxpWXFbVdWxDtmsqUuWZeDIkekb0WgAXKyYYbaVPf2NW1lZwZ3vfGd897vfBQAcPXoUH/jAB3D++edPfd/ll18+5uyjYSmTHKlnnXUWHvrQh+Jud7sbbn/726NWqyGOY6ytreG73/0uPvzhD+NLX/qSmP8nP/kJnvWsZ+F973vfjuWpMsxmoMzSJKZp7vsHQcdx0Gw2xZD9LKqq4qSTTkK9Xp8okpHjvdfr5QpJi+bq7lVkWRZZvyRy5w31I8dlr9ebHYEwhcFgMObK26kiktMwTROVSiUlxFPEwMrKylK/Y7POxWlFBncDruui3+9PzZQm0TkIAlG4NLkvNKJg0e8bZXaTYDpPAcJJJMX2KIowHA6FM4gy6fPwPA/D4RBRFAnBOyl8S5IEVVVRKpVEHnZy3+fJ5AYwNQ+fcs2HwyHCz34Wlb/4CxSuvXbDxwKqCjz72cBLXgKcdNKGFkFRI91uF+vr6xP3L1ksNI5jtNttUVSKhikvs1joVhKGIRzHQRiG6PV6qW3eLQUkp4naxEbb92WQ/Q7T57+t6PooTz47jWEYhpmNpo06x6cYE+VuN3Wdoet9cho9j2TFbVmWx5zbueL2LOc2R5IwzLazp8VtAHj605+O5z3veeLvV73qVTjzzDNx7rnn5s7/5S9/GW94wxty/+c4zpgrtVar4b3vfe+YS5w49dRTceqpp+JRj3oUvvjFL+KFL3yhECx+/vOf4xWveAVe85rXbGTXGGZHoYfoJMsayr9bsW0bR44cwWAwGNt3ciMfPnx4qvg4y61dLBZRqVT2hJiyLCj7t1AoCAdqnlAYRRF6vR5s2xZioKqq4jUtEoPem2Qni0jOolgsIgzDVAdSFEVoNptYXV1N3UhTxEIYhiIzcNILgPidxL9JoqxpmqhWqzsuiGVJFoKc5lSmqAlJkmAYxpgwS+dduVxe6Ps2b3THJCRJEkI2OcfJmT0tBzy5X67r5rZDSRRFETFRjuOkBMVpuZFJLMsSHQJZfN8Xwnu0tobKJZeg9p73zNj7KUgS8JSnjPKGb3e7hd8eBIHI7adRNZNGImQjSCRJQhRFsCxLtCvA6Du3vr4uOpy2XeicA2rb6Hxot9uIogiGYcA0TaiqilqttqPFL+cRtekz2cn7iKxgsSOd9dUq8P73b/96GYZh9gvV6nRxO8e5TQJ3chowLm5LkpT7DJhEkiQWtxlmF7L77uIX5OEPfzge+MAHiizsfr+Ppz3tabjwwgvx2Mc+Fre5zW0QxzGuv/56fOhDH8J73vMecXNbKBREHIkkSbBysh5LpdJEYTvLAx7wAFx22WV42tOeJtZx5ZVX4tnPfjbOPPPMJewtw2wfWdc2CTX7lSNHjuDo0aO5D7+FQgHVahW1Wm2iSDbLIbtR9+h+gtpZy7KmxiyQK3OSyy7v1e12d10RyVlUKhWEYShcuyRq/upXv0K5XBZ5gIsKrFQskJabFcBlWUalUhERDcnpJMruhOBNedn9fn9mdnUy1iPvM95IzMq8LucsiqKkhOykc5yy+23bnrlPi4jahUIBhmFMbY8mLYNiIYrF4piYS+fjcDgcff/iGOYVV6D6V38FZW1t6vZP5VGPAi65BLjzned+Cx0PegVBII7npKK1wPEIEl3XRaeHpmlYW1ub6Bgmh/5GOkO2iiiK0O/3Yds24jhGHMfodrvic6UODdrmeWL5ls0iovZOOrYJzttmGIbZB9RqwJR6aVnnNoCUCQSY7NymznCxrGNF1FPLn8e5ffDgrL1gGGbJ7HlxW5IkvPKVr8TTn/50XH311QBGD6j/8i//gn/5l3+Z+L4/+qM/wpVXXonrr78ewEjEXsZN93nnnYcnPOEJeN/73gdg9HD28Y9/nMVtZk9Bw/CT7FfXtuM4uOGGG3IjSAzDQLlcFkUSJ8Fu7cUxTROmaS4kKE4SvaloWbLoYbFY3DbhgoSnpJN4FlEUIQgCaJqGdrstBE0S7Pr9/obOGdd1xzLOaduA48KfJEkTXa/A6AY/mVm9lQVOScTr9/szhXxJklL7k/f/RTKUSSzt9/tzxY4kXdnTOgLmFbVpREJS1J90DOYRtachy7IQtZPbTE75wWCQOieUX/4S1T//c5if+9zC6xLc5z7A3/4tcN/7zv0WOoc9z0t9ztRWTBLtdV1Ho9EQ8SpJobff7890sVMU13A4RKVSyTU8bAfUyZOs90DblifOWpYF27Zh2zZ0XRcdiFspJM/Tbu8mUZtgcZthGGYfMCN3W+p0ROQY3UfQz+R9ZLYOA90bZcXtLBxLwjC7kz0vbgOj6JB3vetdeMUrXoF///d/n/oAY1kWXvjCF+KCCy7A2972NjF9mQXHnvjEJwpxGwD+67/+KxWdwjC7naxrW1XVfec49jwPnU4HR48ezRW1CoUC6vU6KpXKRMf6PG7tnR4uvtshQYoE6knZw5Mg0ScIAiEiSpIEXddx8803i+IwyVfyxnZZL4LWbVkWTNMU0RAkylPESFLw1DRtbDkkHpXL5bmOQxRFsG17omBNuczzijlhGIqM3+QykqLuZrOKKZZlmgsXSLu0p81nGAZqtdpcrnMS1Ge5pGm5hmGkilNOgoTJaSIscHxECLnsKfYouZw4jhFFkRC16TyJokgMsaXf6ZUHdfYUCoXUQxrFe4wVmQwCFN/6VpRf9SrIC34fBeecA/zN3wCPfOQojmROBoMB2u12ahrFxOSd26qqwjRNNBqNiSNr8upH6LqOQqGQO+IjDEO0Wi3RwbSd7fdwOEy5s4FR52mv10MQBKnvAp0z2Yx1z/PQ7XZhmiYsy9pwZ0gee1XUBo53KCZhcZthGGYPMqsIdacjapMkr6dRFKWmJZ//knVNsuJ29lo2V0FJFrcZZtvZF+I2MBKtL7nkEjzjGc/ARz7yEXzta1/DDTfcgE6ng3K5jFNOOQUPetCD8PjHPx6HDx9Gp9NBt9sV77/97W+/tG25053uBE3TRIN54403Lm3ZDLPV+L4/JiKUSqV94zqmYdS2bY+JCMDxwlwHDx6cKuj7vo92uz3R7VkqlXbN8Pa9gKZpqNfrqFarQvxNCsGThDvHccYEi6SIRyItndPTxNFlQIJws9lEEASpqI9JQo8sy6hWqyJLl3AcRwibsiwLJ2pS5KXihFm3NkERFJZlbfpcTHYg0LKz7u55YhGoI8NxnLk+DyqmOAkqGjiP09b3ffT7/XFBN8O06I485hG1aX26rkOSJHS73akOdCrySLnR82xDVvCm84+OXxAEIrImbzvV738ftRe+EPpVV821zjFue1vg//0/4PzzgQWFTd/3x4qsZiNIZFlOdbCUy2WUy+WpImpeB0a5XBaZ1bZto9/vj30WnudhbW0NhUJhywvTOo6DXq83dj2h+KY4jmGaJorFohh1Me28oGM3HA5FNjvljW8Ez/OmZpwDxwsIZztRAIi4Hepk24nrYvY6sSPFJBmGYZjNM8O5jXZbFIek63/yPoKmJUfc0sjPvGeOXHGbndsMs+vYd3d1t73tbXHxxRfPnO973/te6u+zzz57adsgyzJqtRqOHmv0Wq3W0pbNMFtN1uEmy/KODc9eJuR+oyzZPMeepmk4+eSTUZviCCAXIAkOWditvTlkWc4tDkiuu6Tg7XmeqJtAqKoKy7IQxzGCIBDiNuVXz3LpbgWO4wghmBzA2RtlcmF2Oh1xg01O80qlkhuLQ2IgHa/k+RjHsRD/FEWZ6DZP/k3u8nkzvuM4Fk5RIis+JuNMKG5imkCWxyQhjMS+WaNKKLt5kvs3CRUhnTfWgUZv5MVe0DlIgiU532fFn9DntuhomWR2ehJyhw8Gg4nrlgYDlF/zGhTf/GZIG/mOHDoE/NVfAc98JrCBto+KqdJ5SQ7hKIrEyKFk58m8mep5ru1k+0L584VCAZ1OJ/f8GAwGcBwHpVJJiMvLglzW2Uir5EgMwzBQKBTEvkuShMOHD8OyrFTRz0ltG42QsG1bjBiY9/xeRNSedGxc18X6+npq36qzhIktIHvub3bkCcMwDLNDLODcJsgooSiKuB4krwt03529HmeXI0kS5CAAEp3xuXDmNsNsO/tO3J6Xb33rW6m/zznnnKUuPzlkc7/FOTD7lyAIxoYbL/thfrvJRh8knXCEoigol8s4fPjwVFGa3do7B4mmyc+n3W6jXq/DdV0hsmqalisW7TRJIZiEbtM0RYYyCXcHDhwYi2Xo9XpCGKdl9Xq9MbcpnXfkBN9opxR1HJDY7fv+3I73KIpEoTuCRKR5Mq1nQUVJ58lUJ1f7PAUqDcMQQvm8menk1E52BmSPHYnl8zhmKeN/GR1j1NYNh0O4rjs9zuULX0D1z/4M6i9+sfiKLAv48z8HLr4YKBY3vL3tdlt0QlEnBH3Oyc8jKUbPQ16nQ17Uj6qqWFlZgeM46Ha7Y+dLFEXodrsYDAaoVCpzu+knMa0QIwnKiqKgVqulzh1VVVGv18U0GjFRLpdFzMy0ERHUIdbtdoVonnfOL0PUBkbfh6zBYzAYoFQqbXvR2l2Ttz0YAG94Q3ra7/8+MOc5zTAMc8KzgHOboHu15PUqm7dNNVCSUJFJQpZlYJ4C2+zcZpht54QVt6+88krx+8rKCn7jN35jactutVro9Xqp5TPMXiBPLCtuQrDYScj5ltwnKtpGUIG1crmMlZWViQ/b7NbeeZLO7SAI0O/3sb6+nhKuKMYBgCgUk3Vt0/zkck1WT1/GNIr1yRbDoyHwyZeiKGPxEeTAzsYztFotrK6uIgxDdP5/9t483pW8LvN/aksllT3n3NsbSzdKgyCrjT9RFHnBqANCgwOCgLKqAy6tCKMjjEqLIIIbOoyCMC4DoqgIAiI6AyKiLDY02CA0yCZN9z3nZK+kUuvvj9xP3VpTlT055/N+vfK69+TkJJVKpZbn+3yfp9dLFWs1TUOtVlsq65aWL/j6JNaScJslFgeZ9VjP83KJyWlliGmvR9Ejs1zo8wjlRLT8kpzZUdd7XmdxMH5kVfsP6hPIGkwQj4/RuPFGFP/8zxd7oe/4DuB3fge45prF/v4ig8HAd5aTMKsoSkw0nXfbpmNAEJo5kUaxWISqqqldCrZto91uo1gsolarzR1r4TiO/36j0CwAy7ISBzlmFRMLguCX9NKgzng8Th3ko8EPwzD82VmapvkDZ8uK2vQanU4n9h2kCJ+8fQKrIsm5vRV0Hfhv/y1839OfzuI2wzBMXnI6t4Pni3QsSjuHDMaSRO8PIghCdt42wOI2w2yBMyluv//978cXvvAF/+frr79+pQ6O973vfaGf73nPe67suRlmXZATMUhSduauQ0I0iU/B+8glRxfzdGs2m6kX6ezW3ixJ8SPROBHP83ynJ0GCCxEUkzcJuSFJuKbsvrTvUVBkIqGTtstguabrujg+Pk4Va2VZRr1eX8tMISrJLBQK/mCX67ohsds0zdxxJkB+UTutDDEJih6ZVXZHz6lpmv855YFE7X6/7w9eJEW4UFHhrHMKWpcktK5q3+E4Dvr9fmYpqySKqL3lLSi+6EUQ2u35X+jwEPiN3wCe/OS5yiKTMAwDd9xxR2ggIlqUqCgK6vX63OJ/8BhA5CkPFwTBz3BPE6INw8BkMkG5XEalUsncNpMGW4NQFjp9x6IusUajkdstHix0zMpYp2WjAZtZ0Hcx72yuTqeTetzUdX2j2dsUERSEyyQZhmH2lJzO7ahLOym6jYhmdAfvD5IrbxtgcZthtsCZE7dN08TLXvYy/+dSqYSnPvWpK3t+y7Lw2te+NnTfQx7ykJU9P8OsiyTXdlLO765CbrDBYBASNFzXxWAw8OMgyKFGrvQ0Jxy7tTcDxTgEoxyyyCqRDBJ0SlP0xzoFFcrzC+K6rh8ZMCsiIih0A/DdkySAphVGViqVjZe0JWWjB13M9HlG3yv9HHS8J0HO3awiTCrOI8frLPI+ZxDLstDpdNDtdmGaZqpASIMSSYIZ5Y+n5a0vS9a+Crjk7NW++lUUfuzHIPy//7fYiz396cArXwmsYEbacDjEF7/4xVhJKRVEiqKIarXq76/ngQTbIMVicS5Bk2JBNE1LjDqi9U5RJUlRKUmDrVFon5A0SKqqKhqNxsIRHpTZX61W/Y6CvEWuhCRJflFk3s8hLXKFIHd53niZZbFtO/aeWdxmGIbZU7Kc2/0+pMj5OB2DZ4nbNOuTSDqnzy1uHx5mP4ZhmJVypsRtx3Hw/Oc/H5/97Gf9+37sx34MV111VeLj77jjDv/CIg+u6+Lnfu7ncOutt/r3nTt3Do961KOWWm6GWTc0HTpIsVjceCbmIpC4NRgMYsITORkdx/HL5+ikpl6vp0auOI6DdrudKJaRKM5u7fkJ5k4v4vYFkmcYKIqCSqXi588GBe1d+IyCMwXyCt3AVNTu9XoYDAa+MBp0+uaNvtgUtM4p65vckqZphiISZn0mlH2dx6VKwnNWRApFj8wzEGWaJm6//XZ0u93ZedWRsj8AfgEiCdrrnP0yHo/9fVwSJOgXJQnir/0acOONQIazPZGv+Rrgd38XePjDl1ziqZjb6/VwdHQU++zoc8rriE4jSUxeNAajUCjg8PDQHzyNrmvXddHtdqHruu8wp8HW4XCY+tnQRXSSe18QBNRqtZXFgtGsEFVV/Vz80Wg0s5tgEVEbmA4+BqP5APjTw4PHVF3XNyZuR4/l0SzWjVIoAI98ZPw+hmEYJh9Zzm3Pg6jrof08laenRXuJohgzkkTd30BOcbvZBHbk3JxhzhKnQty+8cYbcXBwgOuvvx53utOdEh/zyU9+EjfeeCM++tGP+vc94AEPwNOe9rTU5/3EJz6B//bf/hue+MQn4tGPfjTuda97pT723/7t3/DSl74UH/zgB0P3P+95z9vYyTvDLMpoNIoJAfvg2k4r/wKmTq1er4dCoYBareYL9YIgoNlspopnlmWh3W4nChKKosQKvph0yMkbFLSXQRAEGIaBQqHgZ+NJkoTLLrtsb4p7o0I3ObWThG4SuLrdrv84igY4d+7czn9HKYc8j7BdKpX8AYo8GIaBTqeTKjzPk9EdxLIsHB0d4eTkZObAS7FYRKlU8rPTg2L2JgYFqRgwTZwMuZ4/9CHgB38Q+MQn5n8hWQZe8ALgf/yPaXnkkstMjt7BYBDbb6uqilarhWq1ulScUFLWdpqrfh40TUOxWEyNF7EsC8fHxygWi36cUhLkBHMcJ/H7sO7jDH03NE2DbdsYj8cYjUb+MW9RURtILpAEgGazCc/z0A7E4NCxYROzn3YqkqReBwK9PwzDMMyc5DAeSsMhxJznEnQ94bpu6Pov6XxOFMXszG2OJGGYrXAqxO3j42O84Q1vwKte9Src/e53x73vfW+cP38eoiji+PgYN998c8hNDQD3uMc98OpXvzrzAkrXdbz+9a/H61//epw7dw73ute9cOc73xnVatU/Ub/55pvx6U9/Ova3z3rWs/A93/M9K32vDLNqklzbqqrurIBL0Q3D4TBVLDVNE5PJBPV6PfQdF0URrVYr9WJ6MpkkFmBtK/phn6DSQRKyF3FlEyT+RF3YruvGBCVN0/ZG2I4SFJnShG5RFFGr1dDpdHyXp6IoGI1GkGU5dw7vpqH9SlIpHyEIgi9AzyNmDodD9Pv9xN/JsuxndM/zXTVNE+12GycnJzOd4MVi0Rf+SNDeZK77rEJC4NI6rVarEHUduOEG4Ld/G5gjhsLnG78ReO1rgfved6XLHIzeIUqlEu5yl7usZHtOimdZVXkhfR8pqiQpemNWHAe9v7THzIrKWgeyLKNarfqxJZ7nLZwD77ou2u12bN3XajV/Hy3Lcuj7NRwO0Wq1lnsTOYieK+zq+Q3DMAyTgyznNgCh14N0/jwEQfCPS57n+TN3og5tWZbhOE7oGEZu7uh9mc5tFrcZZiucCnE7yK233hoTsqN8x3d8B1760pfOfbFzdHSEv//7v898XLFYxM/8zM/g+77v++Z6fobZBkn5xbvoCKX4keFwOFN8sm3bz20NIssyDg4OUl2V4/E4MYJAlmU0m02+GI7gOE4sK3ueHNcgkiT5oi39GxVXPM/D8fFx6D5yp54GgkK3aZoYDAYYDAYYj8e+MCNJkv87VVVhWRZUVUWtVtup7Hfbtv2M6iSChXfzRAN4noder5co7CqKgmq1Orc4ahgGer0eOp2On3GetLzVahXNZjOzLHJd0GDBcDhMHTSibUFRFOBtbwN+5EeA//iP+V+sUgFe+lLguc8FlnChU+51UGy2bTvkqpYkCdVqFVdeeeVK1qvjOLHB2mhszCqQZRmtVsuPWMmKxikWiygWi6nZ8POWRq6DZfYhnuclRgTRjAyiXC6j1+v5P9P5x7oHiFjcZhiGOUXkiYzt9SBefjkkSfKPTcHc7SRxO2rMoVgSFrcZZj84FeL2wx/+cHQ6HXzsYx9LvZgWBAHf+I3fiGc961l46EMfmut573GPe+DJT34yPvShD+Hf//3fM12I586dw+Me9zg85SlPweWXXz73+2CYbRCdvq0oyk45YfNklwKYma+sqiqazWaqkJbmBM36u7NC0JVN/876LGYhCIKfjU0Z0nliHJJEoWq1uhe58LNwXTe2bulYQ65g0zRhGIb//mlQYTgcolAoYDAYoFqt7kT+9mg0Qq/XSy1hrVQqcxU6EuQKTTrGl0olNBqN3M9Jsz8GgwH6/T5Go1Hi8gqCgEajgcsvv3yrgwez4peAS6WBxWIR6HanovQf//FiL/boRwP/838Cd77zwsubVu7reZ7v5KfBnGKxiFartbLtNuraXncxsqqqOHfuXOL7BeDHYlGMTNJ2ViwW0Wg09vo4MxgMYoNDFK8SpFQqxdYTFXKuC8dxYp/LtveTDMMwzBLkcG6j241lZruu688ODZ5TUcRc9Doj6bicS9w+fz57+RiGWTmnQty+/vrrcf3112MymeATn/gEvvjFL/pTizVNw13uchfc//73n3vq453vfGf8/M//PIDpyfdnP/tZ/Md//AeOj48xGo18d2ir1cK9731v3HmJi0GG2Qaj0Sh2IN8V1zYVB85yKgKXBLOkqe7A1LVXr9cThS/P89Dv92NOP2B+wew0sUpXtiiKvoid5srOszzRgjJFUfauz4AKFoNidlYOuSiKvuvTNE3ouu6fkHueh8lkgslkgsFggJOTE9TrdRweHm40KgOYfka9Xi81bqFSqSxcwjorB79Wq+XeZwUHymgWSNJzklP78ssv36qTlnoD0hzldA5SLpen6/Uf/gF46lOBL31p/he7/PJpfMn3fA+wxD5vlhBPZYw0Q4HKeUtLZnkTjuPEXP2Ui75Ogu+DMsUpt1pRFHS73cTPcNWlkduCvktBKAIsqYirVCqFjrmj0Wip8tAsksSKfR8UZRiGOdNUKoAoArOMh72en6VNxwESt0ulEizLguu6kGXZN5NEjxeyLMeufzhzm2F2l1MhbhOqquK6667Dddddt/Ln1jQN973vfXHfJbMnGWYXSBN1dyHDl6ay67o+U9RWFCUkHiQ5OilLNAnP89DtdjEej2O/K5fLqOdxBZwCVunKBhByZFNm9rL0+/3YyWXagMUu4bpuaL3SifSiUMazYRihAjjgkhvZMAwcHR35IvciLul5GY/H6PV6ie9NkiQ0Go2FZ4MYhoFut5uYgz+rGDZIcJ9iWRZ0XU8UG4Nlnb5gvAVc1/UzqtMGlShXW5IkwLKAF78YeNnLZl/opfHDPwz88i/nm+abgmma6Pf7qbPnxuMxBEFAq9XyRUxyNa+KaL57UjzVOhFFEfV63T920Hcx6XtxWsqJLctCt9sN3Uefc5qAXC6XQ+cerutiPB6vTeTnSBKGYZhThiBM3dsJBcY+3S5EUQwNnFJ3j6IoaLVacBzHd3cLghC7/lEUJXYM51gShtldTpW4zTBMNrZto9PpJDpGt1mYSFmpuq7PdAkXCgVUq1WoqgrbtnFychI7GREEAfV6PdXZOyviYB4n6D6yDld2MCt71e67yWQSG4DQNG2nMqaB6TYVdWVn5fDOIuh4pxgXQRBgGAbG4zGKxSLG4zFGo1HsxNt1XXQ6HfR6PZTLZT8retGiuDRc10Wv10scIAIuCbAkXomiCFmW/YKeLNLigiRJyhVlEdyn0DIkCcayLKNUKqHZbKJer28tHiItziMICcL+9n/rrcBTngJ8+MPzv+DXfR3wmtcAD3nIwsts27afDZ+GKIpQFCXk0BZFEc1mc2Xbo23bifuJbTh0Z80IApabxbBLpBVI1uv1mftnGkQPzvLQdf3siNvjMfD614fve+YzgRXNYGAYhjkTNBqzxe2Lzu2ouC2KIjzPgyAIMQNO8HqS4kti4rbjTCPgZsHiNsNsBRa3GWYFuK4Lx3Fm5j7vAmkuSGDqptpGzAMVjI3H45kiq6qqqFarKBQKfmRJv99PHFFvNpupTlHHcfzYoiCUr7uqKfK7wDpc2UFn9rqn+1OBYBBRFNeaz5pFUMS2bdu/LbNeoznksxzvpVIJpVIJruv6Du5ut5so2gYdwBQFQX+/7OAAFTFG37fnefA8z1/GJOcqXTDIsuznHNK/JEamFUcWCgU0m82ZomV0n0L55EmOHE3T/Jka2xwwmUwm6Pf7qTE1kiShVqtd2j953lQgu+EGIEVETaVQAF74QuCnfxpY0FGfx12uKArK5TL6/X5se876DOdl01nbaViWlVisCCw/iwG4dGG+bTzPS4wKynseUS6XQ+K2bdswDGMtM8eSpplvleEQ+NEfDd/3vd/L4jbDMMw8ZM2wneHcjkIidlKZZBTh5CR72Thzm2G2AovbDLMEnudhOBz6F9ahYq8dgoq8ormYQLbLeV1YluULULMolUqoVCqQJAmGYWA4HGIymaSenBwcHKRevKZl92YJ4vsAFROS2LouVzZlPBPrFAqC+dJEtVrdiLjjOE5oXdL/l4kVISRJSnRlzwMV8mmahlarBV3XcXJykhjhQpnllG2r6zokSfKF7nmcjFFXajBH3LIsP9ojLSc6+DdJAiDtU13X9cVuupELPW1dkYhNohk5t6PLoqoqSqWSP2BG+c/bwLZt9Pv91KxyEmlDs2pOToAf+iHgL/5i/hf81m8Ffvd3p67tBUkbWCRIiC8Wizg5OYk9rlarrXRfa9t2bCCkXC5v1LVtWZaft53EKkoj6XtH28Q2o3OSImjmiZlRVRWKooSEZ13XV37uRMaDIFt3bjMMwzDLkyVupzi3k5BlOVY+HBXG6T4hK28bYOc2w2wJFrcZZkFs245lPdu2jXa7jWKxiFqttn2HEKYCT6fTSYzgkGUZzWZzoxd7UQEqCSr7KJfL/rT3NEGbyHJ0TiYTdDqd2IlN3oiDXWFdomuWK5uiLqKDEZIk+VnQq3Rzb6JE0vO80PoM3lYhYgPTbTk6SLBq0Y0KEKvVKiaTCY6Pj9Hr9WKORSp9JEet4zgYDod+LEexWJz5PTBNE51OB4Zh+GI2DaCIoohKpbKUaElCb5ILvlKpQJZlHB0dxdzeAEIitud5iREkxWLRLxgsl8sbGyhJggYcZ8UwlUol1Gq18Pbyf/8v8AM/ANx223wvWK8Dr3gF8KxnTUuYFiCr4JK2ARJde71e7LhTLBZX7qiO7ic26drOGqRd1eAxvQ5waYBpPB5vZcbBaDSKRa5IkjR3zEy5XA7ldU8mE1iWtdJjcXQfmDQNnWEYhtlDsnpCEpzbnuclzoAicTt4/pkUoZerTBJgcZthtgSf4THMAmQ51wzDwGQy8QWUbbmr0gRdYCqcbDJfdjKZ+K7rNEjUVhQFpmni+Pg4l/O4WCzOvLAej8fodruJWbsHBwdbyWWdRZrouowTO8i8Wdmz4mwcx8FoNPKdk+RKJsF7USFhlSWSQadw9LaK9UlQ3EZw3W46qkhVVVx11VU4d+4cut2u7yYNuqSpBE5VVV90GwwGGAwGfjZyqVSCJEl+rMfJyQm63W7iOqMc/FnbED1X2j7TNM3ErGlBEPyM6VmO7+DzBCNIBEHwRW36bOr1+lYHs9IiXQhFUeLu5skEeNGLgFe+cv4XfMQjgN//feCqqxZaXs/zoOt6rLCREAQB5XIZlUrF3wbG43FiYXFjidLKJCzLignL5XJ57ce1PFnjiqKg2WyuRExNOm5aloXj4+ONDtSYphmLisoqkEyjVCrFzqN0XV/pNpIUSbL16DhFAR760Ph9DMMwTH4WcG4DU7OOLMuxCBLTNGP3RclVJgkAh4fZj2EYZuWwuM0wc5BVoBaEptePx+NwVuqGILEqColF6ypvikJRIknO8SAksFKOcBaCIPji3KypzGmldIVCAa1Wa6v5pZsSXRfNynZdF/1+P9fnQTiOg/F47H9HghEcqqrmeu1FSyQpDzvptkrI/Zd027pwcpFCoYDz58+jXq/7sRcUKUPrg34uFou+IGiaJnRdh2VZEAQBruumZrWTqJm0b5NlOeTop4uE4GdEAzj9fj9R2KZ4izzbDLnQaT8jiqIv0guC4Ge1b6NXILiMvV4vddYKLSMts8+nPgU8+cnAxz423wsWCsDLXgb8xE8s7NamgZC0LPBSqYRqtRr6jOhvggiCgGazufL9bfQYR+7xdUF57rP2iVEH+yqYdfzUdR2GYaz9PINmgUWPTY1GY6HBItp/BD9DOl9a1XYS3ffvxAytRgN473u3vRQMwzD7TQ7nNplORFH0zzFd14WiKKFB42KxGOvuSDoO5RK36/Xp+RfDMBuHxW2GyclkMkG3200UeWRZhqZp0HU99nu6IByNRqjVamu/uKL4iCSnF00dXvc0ZhI4R6NRqrBI7mQq7EgTT4KQoE15uVkXwP1+PzFnPMvpvU6C4u86nMNBoTWPKzuNWds7PV+e6I55xe48JZJpUSLLlDomQUWPUQE7rWRmF1FVFefOncN4PEa/34emabBtG5PJBKZp+kVuk8kEsiyHtknDMHwhNrg90XqpVqu+aB0cPAmK2VFo1gA5sSkm5eDgwM/Hpf0CDcDNionxPA+j0cgvj6Qs8WKx6H9GuxBBMq/z+eIfAr/zO8DzngfMiHFK5Ou+DnjjG4H733/hZU7raQDSyxHp+JM062LVxz7LsmIDBetybecpPhZFEeVyeS3LkHV8DJ5n1Ov1lUdveJ6HTqcT28dWKpWlBHVN00KCAn2fVzVAEV1vOyFuMwzDMMuTw7kNIFHcpvNEy7KgaRpkWY4dL5LO9XOJ21wmyTBbg8Vthskg6yJf0zQ/LoEu1JJyVCkLV9O0tQktlImbJPKtotBqFp7nwTAMjMfjmXnalNMriiJUVc0UCSmzmE5E8iy/53nodruJDvtyuYxarbZRcZIygMfj8cxYlrysU3SNFgZGKRaLqNfrkCQpJJJOJpOFxG7aDkjwJGcxRVg4jgNN09Dv91eeh02IoghZlmPrdNfiapaBvj+j0QiDwcDPnbYsy//86MTedd3YwBSte5r5QRnfxWIRhUJh7v2K67pot9shRyplI9ZqNTQajdC2TI7v4MDGeDz2s8UpNzy4T9mFCJLJZIJer5c6yKeqarIYeeHCNB/77W+f/0V/9EeBX/kVYEHRMWuZK5VKatwWRdcEKZfLa3HMJ7m2Vz0jibL/tyVq0zJEj+nlcjmWKQ9MP7ujoyNUq9WVOseT8tOpkHUZaDAq6ITXdX0ly04zo4KwuM0wDHNKyOHcBuLFkK7rwnXd0CBqWvlw9BibK3Ob87YZZmuwuM0wM7BtG51OJ9E1JYoi6vV6yLUUnPqeVLxFDj6aervKC35d1xNzigGgVqutbaq2aZq+WJkmOlqW5YuW5LzOunBVVdXPyp1HMJjlXF/neohCWcWj0QiGYSzk0CbRNSq8rkt0NU0zUZyiZYlus7Q8QYctid3RKAvP80LuvOCN1g+59gRBgOM48DzPdwSvIlqESgij63Sb0TSbJBgjous6hsOhH1lDQne328VwOEyMCFFVFY1Gw/9O0iAWDUDlFaMsy0K73U4chEv7jpLjG7g04AhMIxE8zwu9tiRJqFarW48godK/JJKOHz5//dfA05+er7QoyPnzwOtfDzzqUfMvMLJjiBRFmVlgmFQUTPnhq8Y0zdhrxZzvS0AxN0kCMkHFlevO+I6KyrTtVCqVxJibVRdO6roe2yaojHoV4jkJ9YTjODAMY+mIlaSZUVwmyTAMc0qY07lNJAnZjuPEznujudxATuc2i9sMszX4LI9hUhiNRuj1eokXtiTypImMVFRIUQDRg6jruuh2u/4U4mXcRLNywNOmji9L0H2bNl2ahM7JZOIXRWa5sYIO7UUEXMdx0G63Y8skCALq9fpGxC4qOBuPx7ljMqKiKwmvmxJds2YnBLd3cvlGBeroTRAEX+A3TROWZS0UGzLvYATl6yXlYZ8VETsLURR98ZcEPCoGBaYCMznnKeqD4geibmoqEw1mXM8S09LKSSmTeVZ+PpA84EjLRLNnth1BQu74tMG+1JiU8Rj46Z8Gfuu35n/h//yfgf/9v4HLLltgqeG74JOWWRCETCfwZDKJdRuIoohWq7WWWTLrcm3nFbUTY2TWRFq0hiRJaLVaqQWlqyicTPpcV52fTgOYQRFf1/Wlxe2kMkk+BjAMw5wSspzbhgFMJqnO7SDRGVJ0HRE9rrK4zTC7DYvbzM5AQokgCAuLm6tajm63mxitQRf5eQU3EmqHw2GsqAKYOrKOjo4Wvvi0LAudTifR1ZolwM9LMHaExM0oQUHbdV1/2vIs8V5RFF8UW2ZZ09yggiCg1WqtXOAP4rqunzGeJztcFEXflb5JETuJWW7taPnoeDxGp9PJ/dyUkU7r3nEcP5Ymj9hdKpVSnXb7UOq4qwRLHWkwYDQa+dEeQRFIkiQUi0U4jpP6vafn1HUduq77UQO0fRNp5a4k0mUN8s2anbILESRZ5YuKoqSX733849PSyFtume9Fi0XgFa8AfuRHgAW2+6ySy0KhgEajMdPx6jhOrEASAJrN5lqO43SMCZIWk5KXXRS1iahzOzp4RNFAg8EgMU5q0cJJGkiKro9ms7ny71m5XA69TxoUXcZ1znnbDMMwp5gs5zYA9HqQIrOrkpzb0chDURT9+MUgnLnNMLsNi9vMznB8fOwfRHq93tIu3kXIKo1c5KKOBPFSqYR+v58oIlBUCbkp81ykz3KWz8pEnRfLsvzCtiRXn23bvpvXtm0UCgVomjYzT5sE7WKxuJJpwqZpot1uJ0Yp5BHNFiGP2B8kWIYZLLvbFp7nYTgcxhyQRFTUIuFuGSRJ8sVSYLbYLYoiNE0LRbNEb8xskko30zLLk0SvaD6967qhbT4NEgop9qRUKsG27cS4i0KhkCmCknia9Jp5XMXrxnXdVGERCDvlY8vousCrXjV1bEdEzEzue99paeS9773QclPJZdL2QMuc5YZOKxqsVqtrG1CM7rMkSVp4Vo7ruqk9GQTNCKhUKhsfdPc8L5dIG4y5oRz6IPMWTtLnGt02KGd/1dB5XnA70nX9dIrbhgG86U3h+570pOlAFcMwDJOPLOc2AHS7EAPl50C+WBK6XkmMJeHMbYbZWVgdYHYCEl2CkHMnKHTPm7+cl6xYhlWUEMqy7E8hpnK8IBQvQhefaRd1nuf5j4siiiIajcbSF59ZTmRycZKgTYJlrVabGdVCn+EqhcnxeIxut5uYrdlqtVYuggZztPMUGyqKAk3TtjobIcosh2mSWEhxL4vkhs8iGL8iCILvKKZ8711aZ7sKlaYl3Rb9vNLijGjAQdO0XNFEwKUC2SRKpVKsODLKrLiMRQccV8ms5QOm7zF1v/jVr06ztd/97vlf+HnPA176UmABAdm2bXS73ZgjmAiWxmbR7/djz1MsFpcuGkyDMv2DVCqVuY/Nuy5qE0nf41mCb6FQwOHhoT9wsWjhZNLxYZ2fK7nigzM7DMOA4zgLr/ukWJKdYDAAnvGM8H2PehSL2wzDMPOQ17l99dWxSL08sSSiKMbFbccBsmawsrjNMFtjR870mLMOjZCmxRQEhe6g+3UVQndWaeQqxOIgxWIRqqqmXnxSTmYwOzZ4gZvkygLyOSBn4XkeJpMJRqNRohPZdV1f0LYsy3ciVyqVVHFJluVQ/Maq0XUdvYuFIUEKhQJardbKBkJs2/aFvDzFhmmxDNuG3NpJETnAVIhvNpshESDNmamqqh8BsuiNyQflXzuOkyhirxJN01Cr1TK/O5TDXalU5v5+AFMH6CyhbFaXALDa2SmLYNt2YmkwIcsy6vV6snvZsoA/+zPgx34MODmZ74WvuAL4gz8A/tN/mnuZs77/kiTNFV0xHo9jbnUaGFkXy7q2s9YBsBuiNhEV8vPkRlPRJbm45y2cHAwGse8dReqsE03TQudEVMC9SCFp0qDALh2LGYZhmCXJ6dwmjYHwPM93atPxNOrcJtNNFDFPNCOL2wyzNVjcZnYCQRBw7tw5/6JqliM2WFKoqiqKxeLCQvesDNdVZ1YHCV580kVm0rJ1Oh0IggBFUWCapu8spxFlutCt1WoLCds05ZmEqeh6jwrawPQCkaacJx34SdilHNB1QBfnSTEAxWIRzWZzadGLIhhGo1GqwzEIZcVrmoZCobBz4u0styZtj0kOyF6vl5j5uq6iuLMGOUjINUIn2NH/r5qkzHJFURZyN8qy7IvVWYWqgiCg0WjMFFBnxUOtqyQ3LzTLJ83xOzMm5QtfAH7v94DXv37q2p6Xxz4WeO1rgcPDxF/TzIdg1A+Vu9q2DV3X4TiOP7hEx0xyzdZqNciy7M+emDUIRfuT6Htf5aBiFMMwYvuieQY4PM/DyclJ6v6cio+rkSnM22SZaA2K5Uortk4qnDQMI7Gsc5UFkmnQzJDgcX00Gi00iBVdb5SfyjAMw5wScjq3k4RqOrem4xqdLxFpxwvh+Dj7NTlzm2G2BovbzM5AmZG1Wg2TyQSGYcyMfqDMY8Mw5s4zziqNDJborRNJktBsNqFpGvr9PizL8iNBgu896mqn+03TRLVahWmauOOOO0L5xNT0TP+nA3iw9NE0zURB2zRNGIbhXyBKkoRyuQxVVRMP+BRLUiqV1iZoE7NKNFcRH0PudcMwcsU6rHomwTqgbO00t3ZayZ2u67H4GxJMWNieTdBtnSZYO46z8qiXKGmZ5ZIkreUzVBQFiqKgVqvBNM3QwFlWjMisQStgGvFRr9e39j0zDAO9Xi91sCExzsOygLe/Hfjd353GjyzyeWsa8Bu/ATz72X5ppOu6IRHbsqzEfSK5X9Mc8OTAp0zmKEEhPPhv9EIQwNoLPaOiK0Vd5SFL2Can9s5EV1wkq0wyD6VSCaqqZhZOViqVxA6G6GyedVIul0PLSEXj856P7WzeNgDIMnDddfH7GIZhmPwUCkCpBKSc3wAAul2/OD14LR2MJiFjQJAkQVwURQhZZZIAO7cZZovw2RSzc5ADtlgs+lEZJPamCUFRoZuE1iR3sWEY6Ha7iaL5LKFvnZBL/Pj4ONGxmFZwGc1yJWE6eEHseR5M0wwVydFBPih6Uylk0O1Hn0NagVVQ0F632Jk1nTwr5mAWjuNgNBphNBrlcsnKsgxN01AqlXbaDZaVrTsr2mEymYTyT4H1OzP3Fcuy/O8dfc/W4baeRXAwKypib4tCoYBCoYBareZP/0zbT8watAqW5W0Dx3ES4x0ISZJQr9fD8VX//u9Tl/b//t/A7bcv/uLf8A1w/uiPYF1zDazhMLF8NQ2a7ZPmoC+VSpkFxp7n+QM1s6As9nWRlO2e19HreR7a7XbifpCc2rsmagPJF9yLDh7nKZxMiviq1WobnSVBUWbB75qu63OL29H1tlPidrMJfPjD214KhmGY/adeny1uXzyuRQ0dwfP0aCQJMD1mRK81RVEE8ojbKbPrGIZZP7t3Ns8wAaJCNwnYWUI3uQWDQnehUEh1LgGrcf0uAgkQdDHXaDR8J1UaxWIxtUSLCuaCYlsWJGYD0wM65YInjVpvUtAmZuWiC4KAer0+t7BC2xNljGchiqIvBu3UhXIKsyJ3ZFlGo9FIFUpofUf/dhsDP7sIidlpsx/WRVKUCN122UlPrpkksgat1hkPlQW5ntNmPVCchy+yWhbwtrdNXdp/+7fLvbYgYHzDDej/5E/ClWWg3c79t1SWOCsPfJWCrqIoqOeZHrwgFAUThETQPH/bbrdj60IURRwcHOz0/ix6vKPv/zJkFU4GKZVKqFQqS73eIpTL5dD5D802m0dk32nnNsMwDLMaGo3ZBoKL8WkUTUXXxLPEbTJ/LSRu12oLFX0zDLMaWNxm9gZympVKJT8LejweJ5YfEkGhO41E190GMAwDw+Ew5iYTRRHVahXFYhHD4dAXVWkUuVwuo1AohArlyHFtmmbidPE0SAShQYCDg4PYBWSWE36dZIlLSQWIWViWhdFolJntDsCPu9E0bePvPQ1yUbquG/p/8EaDG0lkDeK4rotOpxNbN9VqdWvO2W2zCTGbTrzp3+DMiugsi9NCVg78puKhkphMJuj1eqmDg6qqol6vT/c9n/vcJZf2HXcs/dr2lVei+6pXwXzwg+f+W8MwMJlMIIqiX4gYdF7TjJOgIzvp/3mhPOZ17hsNw4h9Dnlc2/ssbAPxSBJFUVaynrMKJ+m11l0gmQaVFQc/c13Xc4vbSTNndv2zZhiGYRYga2B9hnObzosoJpCg8+7ouX4ucZvzthlmq7C4zewlJPiS0G0YBsbjMUzTnOvCvFgsotFobEw0IrF9OBzOdFSTG/mKK66AbdsYj8e+WKEoiv+3lNlLrkZJklAoFELldGmlbLIsYzweh0QCErqDRZ15MszXwaIFiElQjvloNEp0f0dRFMUXgda5bURF6TSxOvqYRchbxNftdmPrqFgsLhz5so+sUswm13JUpI7+fxcGTjbJrJkFhUIBjUZjK1ERjuOklvwCgXgHSQLe8hbgNa8B/u7vVvb648c8Bt2XvQxeDmGRyoZJuBuNRv6+O0pIjM8gKHQnid/0ryAI0DRtra76JNe2oiiZA22e56HT6eytsA2sJm97FmmFk7vQq1Aul0MxKTTAkWf7TXK873J8GMMwDLMgWedKAXE7GuOZ5dxeSNzmvG2G2SosbjN7jyiKft5nUOieFTWxaVeg67rQdR26rs8Uyui9lMtl/yBcKBRQLBYxmUyg6zomk0lMsJ41XZnEiGCxpCAI6Pf7oXVEQonneX4W87YYjUbo9XqpkRqzSumIvHntxCZjR7KK6VYNRSdkCfWDwSDm4tumg29TBDOzJ5PJQmK2JElQVRWKoiRm2jNTZuVXzztotUqyZokAF79Ht98O8dd/ferSzpO9mBO3VkPvxhsxfvzj/dLIIKIo+kK2oih+HA0AP24rGC8V/LtarTZXbNMuiYHj8TjRtT0LEraj29g+CdvA5qI1aFbWaDSC53lrH7DIg6ZpGAwGoX2xruu54m+S1ttZGzxkGIY5E2QdEwKxJMHz8ai4neTcTiqZxIULs1+PxW2G2SosbjOniqDQ7ThOyNFNLBJlsSi2bUPXdf+iMQ1JklAul6FpWujga9s2BoPBzFiVJEioVlXVF9yCF3ck5hUKBd8RHMztHQwGcBwH9Xp9oxeFWcVtswoQCXK65y2HpNiRTTnU0/Ks10FetzYwFZGiDkmKHDhtAu0qxexCoQBVVbcuBu0Ds8p8s3Lg10lWBEnB89B473shvu51EN/znpW+tn311Rg9+cnQn/xkeM0mgOm2FRSx6d8oWYNkmqahVqvt7fc3ybVNg72z/iZN2G61WnsjbAcLoIl1fjdoZtiuQLMChsOhf99oNMo1SMt52wzDMGeEOZzbUXE7GEsSPN6SuB2dPSUIAju3GWbHYXGbObWQYFwul+E4DiaTiZ8fvW4R07IsDIfDTFFaURSUy2WUSqXQMjmOg+FwmCmKB5Fl2RezC4VC6gWg53nodru+yy86VYsYjUawbRutVmsj4sh4PEav10sUvrJE2mC2ep5ySEmS/EGQTYqSwXW/CsiJIAiC/3+60faQ57OzLAvdi+4GQhCEjQ0C5YGiEZLygef5OXhCOw8sZi+O67ro9/sYjUaJv99WmW9WBIn3mc+g9qY3ofxnfwbx5GRlr+spCozv+i6MnvpUON/2bVBUFZWLIjY5/7OWe9YgoCzLqNfrcxXw7SJJA5SzXNu0f00TtrcxcLIo0YvqtOP0aaZcLvszEoDp5zsajTJF+Ki4vSvHMJ/JZFo8G+Qxj+ESMoZhmHlZ0rnteR7HkjDMKWLHzvgYZj2QmLluDMPwo0NmoaoqKpVKTHyg+JLhcJgpgFK+NgnaeS98B4NB7OKPYgCiLjnTNHF0dLRWx5vruuj1eqkC0yz3oWmaGI1GMAwjVzlksVj0yyG3ga7rqRniQWE6SayO3gRBWIkY6Lou2u12bHur1WobX0+WZUHXddi2nShQbxIWs5cjGAuU5o7fVplvVgSJ/aUvofnyl6Py1rdCWOF259ztbrCf8Qx4P/ADUK68Eq05s9azlnubsS6rxvO8kGsXgP9dTHt8t9uNHUcEQdg7YRtg9zEw3T8Ui8XQZ6rrOsrlcur27XlebAbGzq27fh/43u8N33fhAosiDMMw87Jg5jZdYziOA8uyQudUXCjJMPsLi9sMsySU863r+syyQhJXqRQyCDmSohmT0b8Pim2LXLCZphkTDBRF8aM+ZFmOOYsdx8Hx8TGazebKRahZ0+qThC/P82BZlp+jnSd2ZFPlkFlYlhUbPJBlGYeHh1tbLprCH12PlPu+KVzX9XODtwWL2cvjeR4Mw/BvswYkSqUS6vX6xrf9tAgSz/Mw6fdR/b3fw+W/8zsQU1zm8+IVChC+53uAH/ohSN/+7ZAWFJ1N00Sv10s9xsxTGLkP6Lqe27U9S9g+ODjYO2EbWH+Z5L5QLpdDnyvFzaUViiZ9P3ZO3GYYhmFWQ4Zz2+t2IQAhUxCdm7quC8uyYtfdFGESE7ddF8iaxceDlAyzVU7HVRDDbBjbtn0BJ8mJG4SyIyuVSkwwozgNyrhO+/tyuYxKpbKUEEQCQPS5G42G74IqlUqQZRntdju0PJ7nod1uo1arrSSXMyumICh8kQOU1neeSIlNlkPmgUTkqNjXaDS2KrhHS0WBqYiSp7RrVYxGI/T7/YWiQpaBxezV4LpuyKGdp7h13oLDVZAWQeJ5HibrMP0hAAD7r0lEQVSGAfmv/xp3fsUroHzpS6t5wWuvBX7ohyD8wA8sdbGTNfAjiiLq9Xqq2LePJLm2aYZS0mOTZv7sq2Mb2BP38YYoFAooFAqh8yxd13OL28EuEYZhGOaUkeXc7vcB14UQmPlK17eu68I0zVjeNpkEYuJ2p5O9PCxuM8xWYXGbYXJAjmESWNOKx4KklUQShmEkRoQE0TQN1Wp1JcJbv9+PLXe1Wo1dNCuKgsPDQ3Q6nZhw3+/3YVlWSBCfF9M00e12E9chCTXFYtFf1/MU/hWLRZRKpY2VQ+ZlMBjE3m+lUtmq8KLrekwwkyQJzWZzI+vONE30+/3MwaE0yIERdGPk/VmWZRazl4Bmq9D3M29kTLFYRL1e33jOfVKUB7nMnVtuwVWveAXK73//8i9WKACPfzzwQz8EfNu3AUt+j8bjMfr9/qktjExD1/XYPj/Ntd3r9WKDpCRs72vmeHSKNHB2ndvA1L0dPE6YpgnLshIF/70YFJAk4F73it/HMAzDzEeGGUdwXWA4BGo135EdFbeD51gUSZJ0Xpure4XFbYbZKixuM0wKiziGgalTqFKpxEoiiTyiXrFYTBSeF2UymcSEzEKhkBo9IUkSDg4OEoWD8XgMx3HQbDbnEqk8z8NgMIg58ghFUfx8zXlKF2VZ9mNHdlGwnEwmqVEw24K2wSAkCK17HWa59mmmgqIoqQL1qvLGmfxQHADNVsn7/VRVFcViEcVicePfz6QIEhLmJxcu4LLXvAYHb3gDhByDlTO55z2ngvb3fz9weLjkUk8Ful6vl9rdoCgK6vX6qRQ8XdeN7S+LxWLie+12u6dO2AbikSS0Lzyr0L4jKEDouo5GgmNvL7LKWy3gllu2vRQMwzD7T5ZzG5jmbgfEbcJ1Xdi2HSuTTIokAXKK25y5zTBbhcVthglAAs5kMpnLkUh52JqmpeZS27aNfr8PwzBSn6dQKKBWq61UtHBdNzOOJAl6jCzLMSHUNE0cHx/nLpq0LAudTifmqqIij0KhANu2Y5nUaZAQXiwWd/Pi9SKLrvt14jhOYoFko9FY67rMkyu/DWfvPkHrbVNOXdofjsfj3A57QRBQKBT8GRTbcBUnRZCQqD3WdTT/8i9x9W/9FuQ8FyppqCrwhCdMRe2HPGRplzaQrzCyWq3OLNTbd4bDYS7Xdppju9ls7rWwDcQF2tM4iDEPNOAZPA8Zj8exWW00wy7ILp8fMAzDMEuSJ0ax2wXufGc/loSg0vpoLElSmaQgCBCyyiQBdm4zzJZhcZs58wTjRmZFhESRJAnFYtHPAk0TGxzHwWAwSHWqApecvKsubASQWNhYq9VyF49VKhXIshzLjKaiyUajkZp/Sdmpw+HQ/1vbtmGapi+WVatVP1t7FoVCwRe096U0LSlSYJWO/Hmh7PToSRvNNFgXWWV4siyjXq/vvSi1DmhQYDgc+ttS0NFOt7w/Z4mi8/QJEDS4R9/PbRakRsVh13X9AtriTTfh7q94BYrLuCa/7uuAH/7hqUu71VrRks+OawKmAz/z7Lf3kaTC46QBzF6vF5uJRML2Oo6hmybJuX3W0TQt9L2m/WJw4MNxnNh5BK87hmGYU0xe5zam1+3BAVG6Fgpep9FjYnnboghkidvV6tT4wDDM1ji9V0kMk4LneTBN0xdw0vJMkyDHMBXRzYKmV+u6nircSpKEarWaGmGyLOPxOFa0papqahxJGsVi0c/hDoovVJRo23bMXee6LtrtNkzThG3bvhvecRzfiTUrG5scoNuKNFgWwzBiAxrkaKV2bsp/3pQLs9vtxgRmisBZB2klfsRZcKIuyqyyWc/zYm6TvMwSvSnLNu/zqKqKUqkEVVW3nvscjSBxXRej0QiGYUC64w7c+VWvQuPtb1/8Ba6/Hnj+84Fv+ZaVuLSJrJgeSZJQq9VOVWFkElQMGUQQBNRqtdB9p13Ydhwn9n0/685t4FJJdPB7ous6KpWKf+yI7ruiU9AZhmGYU0Ze5zYQM3jQOXQ0lmRhcZtd2wyzdVjcZnaKaLFDXvLEh5CoPU9B4SICK7kHk6ZXE6IoolqtQtO0tYl6juPExAJRFBNzKvMQLJqMZsFSMSaVEbqui+PjYz+GJfiZyrKMarWa6EDcNcEsjeBUtuCN7rMsC8fHx3Acx78fAJrNJu64447Qc4mi6G9fs2YALMtgMIiJzLIsryUiJSteAQBKpRJqFzPwmDB5ymYXxfO8RAEtD4Ig+NvqrpS2RgdQHMfxndqYTHD+DW/A+de+FuKMmTMzude9gN/8TeARj1jhUl8avOj3+6nHiXK57M9sOe3ouh7b3qPHiX6/f6qFbSDu2qYBUGb6fQiK2zQrQ9M0AHuSt80wDMOsjkoFEEVg1nV9hnM7KZYk6VicKW5z3jbDbB0+Y2Z2hna7PTOPelOIouhPsZ9HYE2KD4giCAIqlQrK5fLaBYterxcTTZbNMxZFEa1WK1FkMAzDjyk5OTlBu90OXWwKguAXPwZFsU2Ju/MSLBKNCthZgyn9fj82AJAmUpHDdDQaLbzt5Xkv0Txz+ixXvR0mlfgFOc1leMuSp2x20+zi9zMoYNO6sm0b4/F42pXguqj9/d/jql/7NRS+9KXFXqTRAF78YuA5zwFWLJJlDV4oirL2DPxdIqlvQVGU0Ayjfr8fiyyh/oLTImwDLNDOQlEUqKoaOrbqus7iNsMwzFlFFIFazXdnJxJwbkczt4MGJCDDuX3hwuxlYec2w2wdFreZnYCKy7YF5WcXi0UUCoVcAg65dG3bhm3b0HU9VdAjYbdSqWzEqUrT8YOUSqWVTG0XBAH1et0vmgyeFJimiX/7t3+DbduhEwiKX6GLzUXW9yYZj8fodDoL/S0VkgYhwToLcqKNx+OV5RhTmWeUZrO5UkcgzRRI+x5vYrbCvmJZFgaDQWbZLBWoRWcN5Pl5HkjQLpVKO/H99DzP38f6AvbFQSYqkaPvnPr5z+OqV74S1X/8x8VeTBCAH/xB4CUvWfmFStbgBcVwnLXvSLfbTSy4pXWQJGzTY05bXEt02+BBwDDlcjl0fKXvvqqqMXF7Zx3vkwnwd38Xvu8Rj+CsVoZhmEVoNGaL2wHndvBais4tiWCfDceSMMx+sqNnfsxZI+1gsk4oPzupsIog8Zqm8Qf/n1RelESpVEqN4VgHtm3H4kgkSUI9Ty7ZHJTLZb9okgS022+/3RchNE1DoVDwXzso1O7yBbvneTEXYV4cx4mJMCTsR8na3j3P893ji+aPu64bKwIFpoWiqypvTCoNjaJpGmq12pmIV5gHcqymZZIDqymbJbF7lgjueZ4/c2DVgjZFoQRfc9a/wXgf+g6kDRwS4mCAy1/7Why+8Y0QMh6bykMeArzqVcADHrDY36eQZ/CiWCwuPbNmH9F1PSboVioV/5g8GAwShe1ms3nqhG0aqAnC7uMwVCgd3B/oug5ZlmPH051dd/0+8N3fHb7vwgUWRhiGYRYh6/o2krktCIJ/vRI8lpBrm+I1g7C4zTD7AYvbzE4giiKazebMnOplIKEmGPtADkjbtv1c6KiQPa/jMYiqqqjVahu9wPI8L9EFV6/X1yIsqqqKw8NDHB0d4ctf/nJIvBmNRvA8D1dddRXOnTu304J2kDxCGhEc5RcEAaPRyI9uoPtarZbvxAwW+QHwt71gvEISnuf5hZy9Xi8kdKcNmgTLPoPQDIJVYBgGer1eagxPoVBArVbbm89+U9AgCH1HkqBs+lXNttiGaOo4jh+5kzfj23Ecv/A31/fQdXHwtrfh8t/6LcgnJ4st6FVXAa98JfDEJ660LNJxHAwGg9SySGA1gxf7Cq2fILTdA1NhO2mg8TQ6tgEknnPwvjNOuVwODeAbhhEbrOWscoZhmDNCRpeU1+1CwKVzYUmS/PPLJHEbwGLiNmduM8zW4TM/ZmegixESQaLOweDPaf/P+p3rujBNE+PxGLZtr0VIp/iAVTlj5yHJBadp2lqFE9u20e12Y0KUIAgol8soFAp7dZGZlP2qaVpImCbhOjhgMBwOY647TdNmFnjKsoxKpYJKpeJH85DQPWtgxTRNP+IgOgOBSur6/b4fh0MUCoWVOPhpdkA0foUQRdGPV2Au4bouhsMhdF1P/XwlSUKlUtnraArTNKHrOgzDyDVAOLegjek2Vv/EJ3DZy18O9eMfX2xBVRV4wQuAn/kZIJDvvCx5P+darbYzxZzbIK0XQhAEDIfDVGH7tO5XosduWZZ5tksCpVIJg8EgtO0kDZIwDMMwZ4CM6xoSt4F47nbwui34u5i47XlAloGCndsMs3X47I/ZCTzPQ7vdzu3u2yUEQYAsy5Bl2c+p3QY09T2ILMuo1WpreT2K77jttttgmibK5bKfNy0IAi677DJUq1VYloXj42McHh7u/IU6DXoEyeOqTFv38wjJkiShXC6jXC7DdV1MJpNQvvCs17YsC/1+35+BIIqi7xZ1XdePkGk2m0sJaXkiSMrlcmp55lnF8zzouj5zZoooiiiXy6hUKnspdnqeh/F4DF3XU4sSgywqaKuqitott6D5G78B9X3vW3yBH/e4qVv7bndb/Dki0PdD1/WZnzNnz8MvBA2iaRpUVcVwOES/34/9zWkWtgEuRMyLKIrQNC0UV7M3kSTAtADtrneN38cwDMPMT4ZzG4GZPtHc7eCxY6Zzu9MBsswaLG4zzNZhcZvZCSgKxLIsiKK4U7mjwWlMkiRBluXQ/3dBxEuLI2k0GmtZPsdx0Ol0cHx87Lt3BUHwC+gajUZIELZtG/1+f6aLeReIZruSK3oWs9b9ouKVKIp+AShFkpDQnSSaua6Lfr+fKCqOx2N4noerr7566e9Vr9dLjVggV/hOiwobhgTfwWCQOnBHMxwqlcpO7EvmxXEc6LqO0WiUOROGZs5YlgXHcfx9qyzLfsRPMNKHfl8qlaYzUD76UYg33gi8+92LL/C97gX85m9OC9xWhOd5GI1GGA6HMz/nSqWCcrm8l5/zKnFdN9YLQbM90qJI6vX6qRa2AS6TnIeouB1lp49DBwfAF76w7aVgGIY5HWQZiTod/79R53aQoP4QE7fzxN6xuM0wW4fFbWYnkCQJ4/HYv1hRVXWjYk+WeL3rDrukSIxKpbKWi+PJZIJOp5MYS1EsFnH11VdDEAS02+3QycFoNEKlUtnZ6cKGYSSuwywGg8Fa170gCH7siOd5vtuVXNqmacamaEdRFAW6ri9VFNjtdhOFbYpXOI0ZuMtAovYsV7KmaahWqzs1mJeXyWTiR4/MgkRsuqCgbXkWNLhD5bPCBz8I/MIvAH/zN4svcKMBvPjFwHOeA6xQ+Mr6nCkaaBuzGWjWB/UA7Ar9fj8xjmQwGEDX9djj6/U6yiuMjdlFqLw6yE4LtFuGZsql7X943TEMw5wRsoxTgZlgUed2EBK3k66nWNxmmP1gN1Um5szhOA6KxSJEUfSdb6Zpxsroou7Y4M95fkcRIlEhe5cu/OeFxM0gVFK2SmjKfb/fx3A4DF1Ukvv0zne+s/95UdFk8HPo9/totVorXa5VEXWB0cXzLCaTSaLbe9XrnhAEAaqqQlVVVKtVtNttDIfD1Nx5z/N8kdAwDLTbbbRarbm396Bjm2ZYUFnkPjmOR6MRxuMxgHgZaNpt1u+TmEwmqS56olQqoVqt7uxATxqu6/rRI7NEe3JmU49Cnu0jJmgLAkCi9rvetfhCCwLwgz8IvOQlK73w2PXPmfbTwHSfdHBwsBPf08lkEhskU1U18X7gbAjbQDySRBAEFmgzoCi0KHSexzAMw5wBspzb3a7/31niNmkDLG4zzP7CZ3/MTkCjpdESRtM0/dzoXbgw3zUoEiOIIAhLRWIk4TgOut2uL+YGLyjJuXv55ZeHBiKoLDEovFNZ4q5Nt55MJrEp4VnZx67rbmTdJ0Gfh2mavrvctm1MJhM4jgNN0/w4k6AwNJlMcHJyglarlfv71O/3fTelYRi+YFav16Gq6l58L+l7QsL2KkgTu2eJnaqqolarLSRaBQfoNo1t29B1HePxOPGk3/M8f/vzPA+FQiGXW1iSJN/JHZpV8KEPTUXtv/7r5Rb8IQ8BXvUq4AEPWO55AtBgYlqZKjCdwVKtVrcmTkYH3SzLwsnJydYFbs/zYnEkgiD4HQNRzoqwDcQjSRRF2etB902gqioURYntcynmiGEYhjkDZDi3hYBzOy2WhMwskiTF4uUEQYBwdDR7GSoVgGewMszWYXGb2QlEUUSz2USn04mJJ6PRCJPJBI1GIyZ+n3X6/X7MQVmpVFYqqkwmE3S7XTiOg8FgEBK2yb17eHiYKFiXy+VYudpgMMDBwcHKlm8VJJVBZsVs9Pv92AnQJgSt4OcRRJZlVKtV1Ot1eJ4Hz/Pgum4sHsY0zdxC12Aw8EUywzAwGAwgCIIv0JITfJe/l7Zto91u5y4tzAut4zwUCgVUq1Woqup/LsFb0n1J9wOXBgLTopRWJV7S4Iiu64nCo+d5sCwLk8nEd/IXi8VMxyQJ2qVSKS7gfehD0+iQd75zuYW/6qppWeQTnzh1bq8A27YxGAxmDpAEP+dtkTToBkwFbvq+bkvgjsa30DYe/R7RIOFZijrivO3FKJfLse2dHe8MwzBniAzntjAeA6YJFAqp58kUDyiKYmzAVBRFIEvcZtc2w+wELG4zO4Oqqjh37hx6vV5sqqnjODg5OYGmaezivggJT0EKhUKunOi8BMu9go5typEtl8szxU1RFFGpVNAPjJpPJhNMJpOdEURN05zbtW0YRuLU+lWu+yQoFiYKCc5JLseDgwOcnJyEBG7LsnB8fIyDg4PUvOfhcOh/9iRsA1MBn4QXz/PQbrdxcHCwMjHGcRzYtp0aCzIP4/E4sexzWej5guIcCdHB/4ui6Jfg9Xq9kEi9KPQcaQ7xYAFuUPQOit9ZMxJGoxF0XY8NoJDgTd8ZihLJKkkMCtqJ28mHPzwVtd/xjnwrIQ1VBV7wAuBnfgZYkeOXBvWomDUJml2UFWO0CWaVl5qm6X9fN+1stSwr5Can7Sy6zxQEAc1mcyfW5SaJfp9ZoM1HqVSKZbjzumMYhjlDZGVuA0CvB5w7l+rcJuMIzSaL/o7FbYbZD1jcZnYKSZLQarUwGo0SS6fYxT1l3ZEYruui0+n4js3hcOg7FkVR9LPQm81m5udA7u2g4NLv93FuR04Eoq5tSZJmOgYpEiSIKIpo5Dm5WhD6vJPyRSVJQrPZTBWXKW+33W6HPgPbtv2IkqjbVtd1X0SPCtvRzzsocC8jKti2jX6/P7OgMEnwTvs/bbN0EhssNaTYFtd14TiOLxgH/x/9OSpez0KSJGia5q+r6ODJOqGIEIoJiRIUv6Oit2EYMRGXIiNM04RlWX5BYbQPIQrNfigWi+nbxUc+Mo0fWVbUVhTgWc8C/vt/B+5yl+WeC5dE/PF4DMMwUj9vSZJQrVZRKpV2IgYhacAzCgnci2TvL0o0PstxHPT7fdRqtdDjRFFEq9U6c65l27Zj5zpnbR0sCg3s0vZFA247jWkCH/hA+L5v/maAP3OGYZj5ycrcBqa52xfFbboeCB53SdwGsJi4ff78vEvNMMwaYHGb2UlIGKKc5yDk4i6Xy6jVajshKmyaXq8Xc+fVarWVlCiZpolOp+M/P2XtApem3ZOgmsddJwgCqtVqSNywLAvj8XjrF6Gmaca2ryzXNjlwg9RqtVQH9LJQnECSG1NVVTSbzcyZDCRwn5ycJArcBwcH/raj67qfizsej323ZbVa9T9vWZZj8QInJyc4PDycexukotLhcJgpGgdd0WmQ0zbJ2UwO26TiOuBSmcys1w6K27QcwftFUQznR+8YQfE7Dcdx/O8Grcdg4WPaOqJoksx4kn/5l6mo/fa3L/NWpqL2M58J/OzPLi1qe54H0zR9QXvWNkYzUsrl8s58zml51q1WKxZjNJlMNipw67rub0c0iBXdjkRRXHqAbF+JDn7N2g8xcTRNgyiKsG0bpVJp92f29XrAwx4Wvu/CBXb+MQzDLEJe5zYuGTyi4nbwuJsobl+4MPv5ef/NMDsBi9vMziJJEg4ODnwXaVT4oizYRqNxal1Onuf5JYyCIKBQKMB13Vjuq6qqKyneoigKWtej0cgXAsvlMjRN8x3i80wbL5VKGA6HIUFtMBigWCxuVRwKTpMHLjlu0xiNRjFncbFYnPk3y5C27QNTsblareZ+LlmWcXh4iJOTk9Dn4DiOH1FiWVaisF2pVPzPu1KpoFqtot1uhwYGSOAOCuVZTCYT9Hq9leVhU9lfkjBZLBYzBy5msUgsSp7nJDd50E0SvQVd6Y7j+DfbtkM/L4Nt276gHfw8yIGdVBBJ+yQStDMFuZtumoraf/VXSy0rZPmSqH3Xuy78NCRok2M9KzJGEASUy2VUKpWdE9CiedbAdNBNVVW0Wq1YNNFkMkGn00Gz2VzrPpiyyun/vV4v5q6lY/0qBmf3EY4kWZ6zFmPDMAzDXCSHc9vrdEBnOqIoxkw6siz753UcS8Iw+8vZvJJg9opyuQxVVdHr9WIuW9u2cXx87Atuu+KiW5bglPjgQZbiKRRFQaFQQOFiOcaykRhJsReUuyuKYihneZGiL3Jvdzod/z7btjEej9cmDGdhWVZMqJ7lxCRhJsgq1n0SNI0/qbyOylcXieWRJMkXuIOCiuu6+MpXvgJBEKAoiv/ZA1Mxmz7voKDearViAjfNqjg8PJwpdFIsQVo5H30G82RlB5c5+lxBcX7VRCNR8ojUwZ/nJU0ADMasREVvukXXp+M4fgZ+8CSfRGsqfYy+X1VVfUE7l8h7003TTO23vW3u9xtCloFnPGMqal999cJPE3Ro5xkUEAQBpVLJn7Wya5imGRuoKxQK/oBncOZG8HhiGMbaBe5er+eXj1LUWHDGlSzLM7P/zwJcJskwDMMwC5JD3Ha7XdBZBhmZaBYjxectFUvC4jbD7AQsbjM7AzmSRVGMOXrpAjjNyUplh/vs4rZtG6PRCOPxOFVwobIwx3FgGAYEQcDBwQEMw8jnnEwgGkMCTF27uq77MSQkYC0ibBPk3g6KqoPBYGt5tVExSBTFVPc7ic3R7a5er6/cwWnbNtrtdqKbmXLOlxGCaPp/u932RRXTNP2MbUVR/PvL5XKisA1cKn4LPg9wSeBOEqw8z4Ou66HZAVHK5bK/zUWjQKKFjZ7n+RnoruuiWCyGHk+DKrIsJ7py00TpWf8m3bcLBLO00/aBjuPAsizoug5d10PiLr2XJNFaFMWQoJ3rPV+4APz5nwNvehPwvvct9+ZkGXj604EXvnBhUZuikGbtX6OQwL/ovnUTRPOsgUv9C0EURfEHpKICd7fbXVlfQxDqyKD9i+d50DTNHzAh0X3XXPCbhGKCgrBz+5QjCMDhYfw+hmEYZn5UFSgWgRmdPV7AXEXnynSeROc+dJ4XvT4RPQ84OZm9DJy5zTA7AYvbzE7geV7ITUrZuFG3Jbm4u91uzO1E+cGVSmWp+IFN4jiOL7gkZQQHoXiSIJTt2+v10Ov1oCiKL0DNukCmgYTRaBR7XYqjIGGT1mOj0VjaZV2r1XASOEFwHAe6rqNSqSz1vPNCrvEgs1zbuq7H1r2maSt3A4/H40QRHcBKZydQcVun08FgMPCFJ3Jylstl1Ot1//Ou1WqJnxE9T9QJTgJ9ULgyTRO9Xi91Oy8UCqjX66HtNisKhPLIZVmOLV+xWESj0QgJZySI0/Puwz5iFdBnOx6PMZlM4Hle4joLQoOMpVIpf4Z4uw285S3An/wJ8H//L5AR85GJJF0Sta+5Zu4/J0HbMIzc0TcUs1IqlXZW0A6SFEdCAzpRCoWC/30N7mPG43GiIL4MNDvDMAw/Tz8Y+5S3L+C0QyWtQfZ1gJ7JyeFhtguQYRiGyU+jAdx+e/rvAyaAYNF8kFTndrebfT7Lzm2G2QlY3GZ2AnIUEiSOFYtF1Ov1kMgQdHFHHaCe52EwGPgu7l10QJHQRK62PMiyHHsslZoFsSwLlmVhMBhAkiRf6CZxajKZ+LnRSQIqCd71ej10gR0UOpdBVVWoqhp6L8Ph0C+E2hSUAUvMcm3T+gwiyzLqedq5c+J5Hvr9fmKshiiKc2ec54He89HRETzP84VPYPp9JHEsTdgOPs/BwQGOj49DIptlWTg5OUGz2cRwOEwtcRRFEbVabe7ta1Ye+Swx/qwwT0EiIUmS71RWFCWfoN3vA29961TQfve7gYxBulzLLkkQnva0qah9t7vN9bc0cDUej3ML2oqi+O97n3KfyYUfRFGUmf0LJHC32+3Qd4e+n6sSuHu9HnRdD82QocG5YrG49qzvfSE6aJr7e8cwDMMwzJR6faa4HXVuJ5Embkvtdvbrs7jNMDvB/lzFMacamiIUnS5uGAYmk0nMjU05uuTijrpBLcvys7h3wcUdFJrG43GuLOGg4NLtdlGv1+G6LkzThGmaKJVKM8U6ckX3+32Ypuk759JcmLSuo266er2+krJKolqtxooIdV2fqxxxGdJc20nrMi2OZJVT+G3bRqfTSXQ0K4qCZrO5FsGN4miq1WpooIXiJ/r9Pq688spcrnoSuINllSTYn5ycpDrONU1DrVabS3T2PA+9Xi9RLF8mj3ynGQ6Bd75zKiRXKsD97gfc/e7TuI4I88ZvULkfObRzoevAO94xjRx55zuBnIN0WXiShPHjH4/BDTfAvfrqaaP98XFifnnwBsB3pmfNgCGoKLNUKu2VoE0k7ZvIfZ21b6KSySSBWxCEpQfuDMNAu90OCe80YKJpGur1+taPybsCl0kyDMMwzJJkDMx7gc6ktGuO1ELJrEgSgMVthtkR9u+KjjmVUHZ0UtwIubHH43EsqkRRFBweHmI4HPpTn6N/ty0XNwnao9EIo9HIL3QL3uhxdKNsW1VVIUmSXyxJF8AUFdBqtVCv1zGZTGAYRsyZSa+dFGVCpYGFQgGqqkIURViWBdd1Y6JDrVZbqbANXJr2HyxzpBiUTThro1nbgiCkvsfBYBATHyqVysqmjVPebZKrdp0ikGmafjSBruuhnGbK2K5UKrAsC8PhMJfALUmS7+CeTCahfHXP80IlcoqixGYH5GHWQMAq8sh3kje9CfjJn4w7UopF4Ou/Hrjf/eB8/ddjcs97Qv/ar4WVwwFP7tlSqQRVVfNtY4YBvOtd0+X5q78CUpz4i+BJEsb/5b9gcMMNcChTOyGLeFlkWfbf976LiNH+AmD6nc37vigWpNPphI6buq5DEATUarWFlovKaYPCNs0yorgj5hJcJskwDMMwS5J1bhGIJUm6TpAkCYIg+PGFQYTj4+zXZ3GbYXYCFreZnUGWZRweHmI0GqHf78cEv2BUSa1W8912VBpHDuc0F3e1Wk3MVY4KztHiunl/prLHvDmvgiD4bllZliEIgh8vkoQkSb5QSLEjnuf5QmS324Wu66kxBCR802tQPmtUFKlWq2vLwq7VaiFxmwYi5hE+XNf13buyLEOWZf/kJA3KOA+SJqqTQBtEUZSlHeZUIEbZ5lHIOblMDIzrunBdN3F9UE6153kYDof++mi1WgCmgjt9nwD40R953rcgCJBlGRcuXAhtf6Zp+p8vRZDMK9rPGghYZR75zuB5wMtfDvz3/578e8MAPvIR4CMfgQRAu3iz73xnWPe6F+x73QvWxZtzl7sAFwfOaDZIroEk0wT+7u+mkSN/+ZdT5/gK8UTxkqi9QKZ2HoJRK6dFOKR9fRBFUebeX1M8SFTgHg6H/nF1HjzPw3/8x3/Elq1SqaBWq21sds6+QOXQQU7LNsowDMMwGyPDuS1kOLfTIkmAHOJ2uQysILqTYZjlYXGb2TmoqG8wGCRmEKdFlWS5uPv9vj/tOipIL4vneZhMJphMJjEnVhrkYM5d1naRpJI8iiEwTdOf/m2aJiaTSUwkJ/ciubaTqFaraxUiZFmGpmmhaInRaIRKpZLLees4Do6Pj2PCAImrJNbT/2kgJLpdpLm2bdtGNzDKT4+dJ47EdV3Yth26WZY1MypClmU0m82FXKXR7QBAaCZAsViE4zg4OTmB67r+rAZg6uKk71Kz2YwNylC2/Sw3Z3BQql6vo9frhU4SacbAvMI2DXwkDQSsK49867gu8FM/BfzGb8z9p/KXvwz5y18G/uZv/Pu8SgW4z30g3P/+00iT+90PuM99pifkUWwbeO97p4L2X/zFtCRyxXiiCOt7vxfjn/op2NdcA9F14TlOrlzwPFDfwFxRK3vCMnEkSVDxaieQRwlc6iXIexzwPA933HFH7HlUVcX58+dXPgPoNBA9NouiuJcROQzDMAyzVeZ0bpMWELwPiIvbgiBAzBK32bXNMDsDn0UzO4koir57tdfr5Y4qIbcZZXFHRbpVTnMnQZsysPOI5HmE5VnQewPgR5YkZXiTW7FUKsF1XViWBVEUffF3FuSCXTfVajW07PSZZhWaeZ6HdrudKBKTg51yhwlBECAIAvr9vp/vTg74oJhObuaoCE7LmyQ60/qNCtl58o6DlEol1Ov1ufOnqZw0aRsMCt6O42A4HEKSJJimCdu2/VkD5HpuNpsolUoYDofoR1y6w+EwMbrGsqzYd1SWZdRqNfT7fT+SgAZcer1e7tI6x3HQ6XQSB4zWmUe+VUwTeOYzgTe8YWVPKQyHwD/90/Tm3ylMc7tJ7L773YG//3vgz/4MuHBhZa8dolAAnvQkCC98IQrXXosk2ZlmHURvzkXxO3qjbZ4im0jQPlUu/gC6rsdE0XK5vFTMCkURJQnc1G8xC9d10W63cRLJpRRFEXe6051Y2E4hqUySOQNYFvCxj4Xvu//9Af78GYZhFiPruiJyTSOKYug6ja4Fo9dRoigCR0ezn5vFbYbZGU6ZKsCcNsiNPW9USaFQwLlz51Idn4viuq4vaFuWlUvQliTJd84qiuILrfPeFEWBKIoYDocYjUa5hHqKISiVSv4odVpON3Bp+vgmkCQJmqaF3Pmj0ShTqEnLXJ5FcDCEoPVqmiYURYHjOL6zPyow03okJ3xQxF7WbUr5tnkFIPoMx+MxDMPItQ06joNer+e/RxJVNE3zhSsStgH4Lu5eYBofMP18PM/zxWmaXZG0DIVCAVdddVUofoaeI09p3WQyQafT2Xge+VbRdeDxj59mW68bzwM+85np7c1vXt/LSBK8hz8c4vd9H/DYx2ZegARLInM9/8VZODR4d5qxbdt3VBOyLK9kMLJUKvmu8CD9fn9mLwEJ251OJ3RMEgQBV1111dqirU4DnLd9Rul2gW/8xvB9Fy6wQMIwDLMoGdcUYuR6RpKkkLidWibJ4jbD7BUsbjN7wSJRJSQaUhZ3Xtd2UFCmkV3LskJuV4q9iArQ9Pc0LZ6WO/j7eSExMxgjMQtybWuaFnO1RnO6KbrEtm1/eTdJtVr1BVNiMBj4+c9R+v1+bB2knZAEcV039nfknjcMA8fHxyGhgT5jSZLgeR4qlQomk8nc728WtA3lLYEzTdN3Yc8jqLuu6wvbQdenLMsoFAp+oSQV1NEgDGWRRyMQ6PVnudOLxSLq9bpfikoZ30RWaV2ScxxYTR75znJyAjzqUcAHP7jtJVkaTxRhPvjBGF9/PUpPfjLUq65a22vR/va0kxRHAmDhOJIkNE2D53mxQS36OSpwU8yRYRihgUNRFHFwcJC6H2cuzTIKws5thmEYhlmArMztiDFAVdXQdR/NAF9I3D5/Pv9yMgyzVljcZvaGRaNKyMVN4jQ5/IICdlSktiwr5G4mwXgWFPFA5WWrEBwmkwn6/X6mU5leW9M0qKqa67XpbyjmZBtQZEXQjWgYBkzTjLnYRqNRzIUviiIODw8hy3IsHoT+T9Ec0YzaUqkEXdcTY12o9FGW5dTCyTyQ8JaUAZ7nM6LiyfF4nLuclKIZZFnGaDTCHXfckShs0yBQrVZDoVDw41yGw2Eoq5viRYLrKE3olyQJ9Xo9lIGtqmpiad1gMIDrutA0LRQzQdn1Sc/darVOpwD05S/D+87vhPCpT217SZZi8qAHYXz99TAe9Sh4l12GVqu11f3LaSI444KoVCord/uWy2W/oyJIr9eDIAj+wJJt2zg5OfHd5MF4mEajgfN8sTcT27Zjxx12bjMMwzDMAmQ4t4V+H67jQLxohqBZZbZt+9dMQIq4nRXVx85thtkZWNxm9o5FokryCLmmafqC9jwubxK0F83RTsJxHPT7/ZAbLgkqZtQ0bWWvvWnK5TJ0XQ99joPBAAcHB/7Pk8kk5iakjGg6IQkKskFI5CYXPgne/X4/1XlMjuq8ec7BIstgoSWVlsyD4zi+oJ0nfiVtUIXc6pqm+WK/KIrwPM8vdSRhO0owqxuYiv3j8Tg0YyG6DOVy2Xd+0qBQNBu52+2Gfj4+PkalUskcOKLSu13cxikWw3Ecf3uSJAmiKOb6/O2PfxziIx8J8Stf2cTirhz7gQ+E/t3fjfF3fzfciw5t+m6ysL0abNuOic2riiNJgi76oq9J31/gUgZ/8HhJPQaNRuP0ZeGvmOhAhSzLO7l/Y9bEaZx9xDAMsy2ynNuuC6ffh9hsTn++2NEVJalQkmNJGGZ/4KsPZm9ZJKokCMVykKCdtwCQRFQStFeZ8+p5HnRdDznhopDrWNO0U+H0Ivd2UEgh966qqrBtO+b6BYB6vZ5LPDMMwxecycFcqVRCYjdFbHie54vEacsaFbEpvmSZ7YBEovF4nDv+pFAo+HnqUVHEdV2cnJzAsiz0+30/V7xUKqHRaMDzPN+haZpmZswJZb7TZ0TCled5/gALFXHOgr6vQYbDoe84T6JarW6k4DSJqHBNt+h9s6AM6aDg7W97738/Gk99KsRIznEq5TLwutdNixlvvvnS7fOfX/7NzsP97gc88YnoP/KRGEZO6knYTvs89wEafKEbfWbbotfrJe7/1pkxXqlU/NlQruv6EVbHx8d+sTHtT4HwrA3O2c6GI0nOMOfOTfsVGIZhmNWQ4dwGAOfkBPJFcTuNmHMbmMYGzoLFbYbZGVjcZvaavFElo9HIF0NnFSrOeh2KeygUCmsRFQzDQL/fT3WNUw4ylUOeJsi9HRQK+/0+Dg4O0G63E4sv8+Quu67rFx6Ox2OMRiMUCoWQ25ucyJqmoVqt+pEkJHhTrAiJ2KtikWJIWZZ9QTvqjCShngQn0zR9YZv+tl6vQxTFUFxEMHudCjOTUBQF9Xodg8EApmlCkiSUy+W53LmU9R4VwQeDge9AJ0RRXKv7dxXCdR7IqU4xBJSdXnzPe3DX5z8fUo4cfQDwDg6At78dwjd90/SOxz3u0i97PeATnwA+9rFLgve//iuQMfNjLu55T+BJTwKe+ETgnvdEv9+PfY7bErZJhA6K0lGBOu13Sf+PQgOKtVpt4yL3aDSKDXjN+71bBM/zUCgU4DhOYqSQIAh+pFNw33Iqi17XAJdJMgzDMMyKyHBuA4CXw0gSE7d7PSDrWoBj2BhmZ2BxmzkVBKNKBoNBTJRyHAftdhuCIOQSEYFLxYxUsLeuC3aacp5WFimKIqrVqh8lcRqh6WHdwImHaZq47bbbYmISiUx5GI1GMAwDuq77gwZRUbxQKKBer4ecc5IkrU08IsE9GsWSRrCcVJIkP2KEcrjpFtyuKTM3KmxLkoSDg4OQkBKN7HEcxxe6J5NJaBllWUaj0fBz6BeBIkhIGKXc+/F47M+IUBRl6agdz/NCIjUJ/6sUrudZFnLmO46Dxjvegbv8/M9DyBl/ZF95Jdp//Mdw7npXqO02qtVq2OlZrwMPecj0RjgOcOutl8RuEr5vuy3/gn/N10zF7Cc+EbjPfYCL+5/BYJDo0m80GhsVtinqJu/g0DKvQ/uSWq22sUJTiqcKIknSWmcyWJblv1ca3CsWi6GIrGDpZKFQQLVahSiKKJfLLNLmgAa7grBzm2EYhmEWJIdz2+t0Mh8TvS6TslzbADu3GWaHYHGbOVUEo0pGo1FiUeAsyBlLgvY6IQfrcDhMXa5yuewLB6edUqmE4XDoX/QPh0NYloVms+mL+oqioJFjdB6YijRf+cpXQoMGqqr6jmfKh83Ke14VjuNgOBwmbpdByEVK+daiKMKyLJycnGSK4eQ6D5ZHUlyALMtotVqZ4pMkSX6Ou+d5frkqubqpJDMNEqujN4p2oBsJ/MFtmxz0eQcW0sRr+v8mCa6XYNY4OfPpszv8oz/CVb/6q7mf17r2Wpy84Q1wr7wSuCiSG4aBUqmEarWanm0sSVO39T3vORWniePjcKTJzTcDn/wkQI79O9/5kqD9Dd/gC9rEYDCIRcsAQLPZ3Nh3KbgsWb0Eq8R1XXS7XYzHY/87tU56vV7sO7+O7HnK+R+NRokzhyhmhNZ1cECM9ie0P2Wyic6OodgnhmEYhmEWYF3O7XY7+7VZ3GaYneFUituu6+ITn/gEPve5z6HdbkOWZZw/fx7XXnstvvZrv3Ylr/GlL30Jn/zkJ3H77bfDdV1cdtlluPvd745rr712Jc/PLE5WVEmUQqGAYrGIYrG4sRKs8Xg8s9AwyU182iH3dqfT8Z2DwDR/u1gsQpIktFqtTPc6DRocHR3F3PDkfi+Xy37u9rqxbRvD4dCfwk+Qey8o0EqSBEVRUCgU4LpuZv42PYdlWX5xZvA15hW2owiCgEKh4P8dubpt2/ZF7KhonXedFgoFSJIUcgB7nod2u+3HpgQjQpLE63W6dYOQcE03et/R+wjLsvwBNioWdR0HrVe+Eq3XvCb365rf8A04+YM/gJeQEUiFn5qmzVV+isND4OEPn978FzKBL395muV9pzvFBG1iOBwmCtuNRmPjwvZkMsnMeF/nax8dHaX2OayC4D6QmGfgJ4t5c/6r1aq/X0rqmuA4kvxEz0nWOTOMYRiGYU49lcr03HWWeWgB57bIzm2G2StOlbjd6/Xw+te/Hn/8x3/sT5mNco973ANPe9rT8F/+y39Z6DX+/u//Hv/rf/0vfPSjH019/mc/+9l4zGMes9DzM6uDokqShGRVVX1Be5U5yllQwV+amEBTzjc17X3XKJVKODk5CRWE6rqOYrGIVquV+VkZhoFer+e7l4MUCgVomraxQQPLsnxROwjFkpBwpSgKVFXNFcPhuq4vZFuWFRN4BUEIFV3S9n1wcLCS90yu7lVRq9Xgui5Go5F/HwncgiDkzsRfhnmF61lQBA59v0VRnA4M2DbqL3whym96U+7lsv7Tf8Lgda+DdFHkT1sXo9EI4/HYd3IvtD8rFKYRJDMYDoexiAxgKmxven9FDuo0RFGEIAj+AAz9P/pznse5roterxcTmqnPYTweo9ForDSOIy2OZFln9CI5/8HiWkEQfOd6kFklvEycqHObo1wYhmEYZglEcRpNMsudnaINETRzNvS0x8ezX1fTpmXvDMPsBKdG3P74xz+O5z73uTg6Opr5uE9/+tP42Z/9Wfzt3/4tXvnKV/rTbbPwPA8vfelL8Yd/+IeZz/+CF7wA733ve/HLv/zLfNGyA5RKJaiqCsMw/OnUm475cF0Xw+HQLzeMsmk38a5immbMzU5OwVnibDS3PFoWKkkSrrzyStRzZLItCzlKowMYlNtLwhAVlM5y3LquC9M0fXc2OaZJdCVXMJVdRrcdURRXJmyvi0aj4Rd+EkknmIsSFKtpPS0iXM8iWt4ZYjxG87nPRend787/hN///VBe9zocBD43GgQYDocxoTu4bZGTe5WDdrquJwrbNENm0yTNeqnVaiiXyyt3wNKMERo4i76ubds4Pj6GpmkrK5xMiiOhwsZFoBLT8XicO+df07TE/RPFQtH3lWaHMPlJcm4zZwjbBj796fB997gHsKGZgwzDMKeSLHE7I5Yk6fxIyHJus2ubYXaKU3Em9fGPfxxPfepTQ2KSpmn4lm/5FlxzzTVwXRef+9zn8IEPfMB/zHve8x7ccMMN+N3f/d1c07l/9Vd/NSZsP/CBD8R97nMfSJKET3/60/jABz7gCzLveMc7IEkSXvGKV6zwnTKLIori1tzQaSWXhKqqG8lv3XVs20a73YaiKFAUxXe3VSoVWJYF13Vj4k5SbnlQKBUEAaVSCY1GY+0CjGEYGA6HMeGCygQpa5tE7STx0XEc35VNJ1kkwlKMBzlKZ0Fu8HK5vNGZCYtCAndaqeosgmJ/ULxOE/xXSVYZrNDrofWMZ0D94AfzP+lP/RTwK78ydaEEEEURlUoFmqZB1/XErH7P86DrOkaj0coGy3RdT5wJVa/XUd6CW4WyoYOoqpp7oHpRisUiVFVNLdNcVeEkuaqDLOKMpn0jFc9mIYqiX1w7a1BeEAQ/X91xHJRKpTM9IDsvtm3HLqDZBHHG6HSAr//68H0XLrBIwjAMswyNBvDFL6b/PsO5nSRuixmmSd5vM8xusfdq2nA4xA033BASth/2sIfhl37pl3BwcBB67Fe/+lX89E//ND54UWh4//vfj9/8zd/ET/3UT818jfe85z147Wtf6/9cq9Xwqle9Cg9+8INDj/vkJz+J5zznObj99tsBAG9729vwDd/wDXjSk5601Htk9hPLsmZmfm+60HCXcV0X7XbbP7Eol8vodrv+dHiK8qhWq/7fpDkpJ5MJHMeBoih+FvG6is5IkKXyyyimaULXdbiu64vaQSGIlj0YOyHLcmKmbRpURkbZ2IVCYe/EJhLMOp1OolA8S7zehnjvum5qaS2hHB+j9eQnQ7rllvxP/Cu/ArzgBTMfIooiqtUqyuVy6mwQEjZJ5C6XywttE6PRKFHYJpf0pnEcJ7Y8oijmLpldFkEQ/H120r592cJJikAJQh0S80ADhVmiNs1koizveVzvHEOyGNFtZlv7MIZhGIY5VWSdK80pbouiCLC4zTB7xd6L2//n//wf3Hbbbf7P3/RN34Tf/u3fTryovOKKK/Da174W3/d934dbLgoOf/AHf4CnPOUpuPzyyxOf3/M8/Nqv/Zr/syAIePWrX40HPehBscfe6173wu///u/j+uuv98X23/7t38ZjH/tYvhA8Q7iui36/H3MXEoIgrLWIbN/wPA+dTickxCiKgmq1GipPGw6H0DQNnuelumUpU7ZWq/l/WygUVlbCFnwdiohIcuRblgVd131nY7FYhCiKcBzHd1JKkuTn2M4jbgRLHul2GrYjQRD8+AfXdUPRIbvy/sgZnRQNQsiyjOrtt6N4/fUQvvCFfE8sScDv/R7w9KfnXhZRFH2RmYTsqMhNIryu66hUKnPFdoxGo8Rc61qttnaXdBppcR2bFgcVRcHBwYE/Kye6TIsWTq4ijsQwDHS73ZnxI8Ec7X0bCNt3ooOgHEnCMAzDMCsgw+gg9vuJs4CJhcTt8+fnWUKGYdbM3l/VvOENb/D/LwgCfuEXfmGmW0pVVfz8z/+8//NkMsFrXvOa1Mf/3d/9HT7zmc/4P19//fWJwjZxzTXX4FnPepb/89HREd785jdnvg9m/yHh68KFC6nCdrFYxLlz51CtVndGsNs2SQWbiqLgTne6U2gdua6LO+64A0dHR4nCNjmYg8I2gJUKcZSdfuHChUTXOImJg8EAqqqi0WhAFEXouo52u412uw3LsqBpGjRNy7UNUFxArVbD4eEhLr/8chwcHPji/2nbjigaQVVVyLK8M+9vPB7jwoUL6F88OY5CDttzX/oSSo94RH5hu1gE3vKWuYTtIJR5fP78+dQ4DBpwu3DhQmruf5A0YbtarW5N2A6WsBIk0G4D6kk4d+5c4jJQ4eTR0VFqgXAQwzBiRY002yMPNOgXnAETRJZlVKtVnD9/HoeHhwu7+ZnliDq3OZKEYRiGYVZAhnNbSDl/J9i5zTD7z15f2dx66624cOGC//N1112Ha665JvPv7ne/++Haa6/1f37Xu96VurN717veFfr5KU95SubzP+lJTwo5yaLPwZw+TNPE8fFxovMOmAoLrVYLrVbrzGdrB9F1Hbquh+4TRRGtVguFQsEX6yzLQrfbxfHxceJUe1VVcXh4CEEQQmKooigrmTURFAeTyuxoYKPb7cLzPCiKAsMw0G63MRgMYBiGH59Qq9VmOk3J0V2v13Hu3DlcfvnlaLVaqFQqp8alvTW6XeBf/gX4yEeAf/s34MtfBtptYDIBUgRf0zRxdHSETqeT6NKnmRjnz59H+Z//GcLDHpZ9Mkw0GsDf/i3w6Ecv/p4uIkkSGo0Gzp8/nyqIUqwHDcAlidzj8ThV2A7GAm0SyjYPsitFhpIkodlsotVqJX6vbdvGycnJTDf1snEkFOuUlAWuKAoODw9x/vx5VKtVPv5sEc/zYscvdm6fQc6dmx5vgjcWSBiGYZYjp3M7jURxO6AzJcL7bobZKfb6KueWSJbpAx7wgNx/+4AHPMB3ZJ+cnOCmm27CddddF3qMbdt43/ve5/98xRVX4L73vW/mc1922WW4//3vj3/5l38BAHz0ox9Fu91Gq9XKvXzM/jAcDmPCCyEIgp+Py6JkGMrMDkLRFCQSaZqGO+64I+TYHI1GvsgWzC03DCM25XtZMc5xnNTIB+BStrGu6xBFEaIoxlyakiShXC6nRqPIshyKGGHxaQ186lPAS14CvPnNQEI2OoBpNEilApTLQLkMT9NgF4twSyVUNA1eqQRP06a3chmupkGp11E8OIBYrQK33z4tg0zJ2I9x5ZXAu94F3Oc+q3ufmG5PzWYTlUrFH1iJ4jgOut0uhsMhqtWqL4anCduVSmVrwrbnef6gUZB54zrWTbBwMskdP6twMmnALGsQjLAsC+12O3HgRdM01Ot1PvbsCJZlxbYLdm4zDMMwzArI4dx25hG3AeD4ePZrsrjNMDvFXqso0Yvwyy67LPffRh/74Q9/OCZuf+YznwmJlvOK5yRuO46Dm266CY94xCNy/z2zH/T7/US3HDCdMp9XoDhrWJaFTqcTu7/RaKBQKPhO6MFgEBNmDMPwnc3VatUXuAaDQehxy7i2HcfBYDDAeDyOiRG2bfuZ2qPRCLIs++674GNFUYSmaSgWi6H3IEmSnwOuqipvH+vklluAX/xF4E//NNWZ7eM407KZiwMuAgDl4m3lXHst8Dd/A1x99TqeHcB0+2+1WjBNE4PBIDEaw7ZtdDodDIdDFItFDIfD2PZeqVTWVsiah+FwGItyKJfLO9ljsUjh5GQyicVYUTRPFlT4Gf3MaDm2Ufq5CobDISaTCURR9PeviqLs/b4yuj0oisIDDwzDMAyzCrKc24MBzAQjABETt/v96bXBLFjcZpidYq/F7agjbR4HTNRF+dnPfjb2mM997nOhn7/u674u9/Pf6173Cv387//+77n/ltl9PM9Dr9dLzNZOyn1mLuE4DtrtdkyQIVFoMpmg1+v507c1TYNhGP7jSbQOTtlPcm0vkg1MTuygyOe6LkzThGVZsCwLk8kEjuP48SFRBEFAsVj03fqCIPhCdqFQ4Gnom+ATn5iK2n/2Z9mi9qa57jrgne/c2AlxoVDAwcEBTNNEv9+PCWwA/G07Srlc3qqwbVlWbPBQluWtLlMe5imcjB5D8sSRUL52NNIJuBSTsq+O4PF4nDoTKih2B//dJQf/LLhMkmEYhmHWRJZzOyU6lIj+Tmq3s1+TCyUZZqfYa3E7Ok067YIoiehjk8Tn6H1XXnll7ue/4oorMp+f2U9omny0/Au4VLjGbqxkPM9LnEKvaRpKpRI6nU5svYqi6MeOkGPTtm2YpukLOEkC2DzOTs/zMB6PMRgM4DgOPM+DYRgwDMMX2T3Pg+M4vlidhKqqKJfLKJVKvqDN7rwN8vGPAzfeCPz5n297SZJ5xCOAv/gLYAsRH4VCAYeHh5hMJuj3+4lidpByubzVTGvP89DpdGKDYI1GYy++T1Q4WSwW0e/3Y/s1KpyMkjXbx3EcdDqdxEGKQqGAZrO51w7nJMGeoIHG6HuXJMl3d5PoLUnSzm0nXCbJMAzDMGsiy7ltGHANI/UcPCZun5xkvyY7txlmp9hrcTsaLZLkvk6D8raJr371q7HH3HHHHaGfL7/88tzPH33s7bffnvtvmd2FxNmkKf6NRiPXVPKzTKfTSXSvybKMo6Oj1BH1g4OD2EyNwWCAg4MDTCaTmGgwzwBDktin63pIjCKBLS0Pu1Qq+aWPqqrunKhy6vnoR6ei9l/+5baXJJ0nPhH4gz8AtjyjQ1VVnDt3DoZhYDAYJIrclNW8TQaDQax8r1qt7p0gSE5qiipJysYmVFWdeQwxTTO12JRc9vu877EsK1G0z8JxHDiOEzpGCIIQijSh/2/L5U3LGGTftmWGYRiG2VlynLe6nU6qIB2LJWFxm2H2jr0Wt6MZ2O9///th23ZmIZuu6/jQhz4Uui8pXiJ63zz5ldHHJj0/s1+4rot2ux27+BYEAc1mcyczYHeJfr8fE6g9z4PruqmzLhRFQb1eR6FQgK7roQLKyWSCyWQSc22nxYVEsSwrsXBvPB77wrYgCPA8LyYYkVOwWCzi4OBgoQgUZgXcdBPw4hcDb3vbtpdkNj/6o8Bv/iawQ/EJVIBIIjcJydt2bANI/F4rirLX37OswklBEGaud13X0e/3E/+u0Wjk2uftOkkRLYqiwLKsmVOJk/A8LzFuR5Ikv8RX07SNudyjy0ERK8wZxHGAL385fN+d7zwtNWYYhmEWI8O5DQBeQmk6Mbe4XSxOS+gZhtkZ9vrM+uDgAPe73/1w8803AwCOjo7wZ3/2Z3jSk5408+/+8A//MDb1NZijS0QvtJbJ9GZxe7+hnOjoBaogCGi1WpyvncFoNAqJVa7rYjweo1gsJroQRVFEtVqFpmm+sKxpGobDYejx3W439vdZrm3HcTAcDhOnv5umieFwCEmS4LquLySRyKIoip+bXalU/FxtZsN85CNTUfvtb9/2kmRz443Ai14E7OB2IggCSqWSH/UDbD8HmEoXg9AA4r5/12YVTtZqtUSxc1YMlizLaDabW//MVgFFQwUpl8t+/JzjOLAsyy/0tW0btm3HxP4syEFNRZ7nzp3biJs7qUySOaO028A114Tvu3CBHYAMwzDLkMeYkSJue54XNw9kidvnz+/kuT3DnGX2WtwGgGc+85m44YYb/J9/5Vd+Bddeey0e+MAHJj7+H/7hH/A//+f/TPwdZfoS0eiJecTt6GOj7lBmf3AcBycnJ7Ep8qIootVq8dTiDKggkjAMA6PRCNVqNdE1p2la4u8EQUC1Wg0JX1FhW5Kk1Gn9nudB13UMh8NEF6Bt2xiNRn6+N53kVKtVP2pEEAR/+falxOxU8aEPTUXtd75z20uSjSgCr3418MM/vO0lyUQQhJ0R2/r9fux7nSb87itUODkej2GaJlRVTXRe27adGOUETAfQm83mqdkPjcfj2H45uC+XJCl2TPA8LyR207+zol+CUH55q9Va+8AJ520zDMMwzBrJ4dxG4Ho0SNJ1oXh0NPu5eECSYXaOvb9a/M7v/E58+7d/O9773vcCmE7dfdrTnobv//7vx/XXX49rrrkGnufhc5/7HP7iL/4Cf/zHf+yLlJqm+Y5qcrAFibpx58mCjD6WIyv2E9u2cXJykiiitlqtnRGEdhUSZ0iEGA6HsCwL1Wo1tu6CESRplEolDIfD2EADkebaHo/HiaJZENd1oShKaJYFFcLRa1er1VMlsu0N//zPU1H7Xe9a6mk8QYDxqEdh+OxnwyuVII7HEMdjaJ4H1bYh6DoQvA2Hs3+m+4LioygC110H/PqvA9/8zUu+8bPFeDyOzXKiktbTBg2UpQ3GGYaBbrebeMF1GouLkz73rMgQGpSJHktc1/UjSYKid5LLmyJwogXlq4QiUoLwuQPDMAzDrJCczu2kuMnE6LPj49nPxeI2w+wce6/SCIKAl7/85XjmM5+JW265BcBUWH7d616H173udal/9+M//uN4xzvegc997nMApqJY1AEVveicR9yOur65aDAby7IwHA79SIptO9JM00S73Y4d8GRZRqvVYpEzA8Mw0Ov1fEc0TTnXNC002EOO7DwRHzStv91ux34nimLid7bX6yU6H+n5yuUyxuMxJpNJaIYFlbvlEd2ZNfGBD0xF7Xe/e6mn8QQBxqMfjcFP/ATse9wDwPSzL5bLifv+ubGsS2L34eHWSyP3EcdxQjM8gOl3upHHiXPKGAwGGAwGsftpfZy2wXLbtmPnV8ucM4miCFVVQwYFz/P8aJPoQOdgMPA7FNZBkrDOxxOGYRiGWSGqOs3BnjFbXhgM4LpubPA8lrctihDYuc0we8epUOcajQbe8IY34CUveQne8pa3zHRnlkolvOAFL8BTnvIU/P7v/75/f61Wiz02enGVlNGbRvSxLG7PxvM8nJyc+AcX0zRxeHi4NWfaZDJBu92OXZAqioJWq7WxEqp9hArqLMvyXXH0uRaLxZALs1QqoVarzbU+i8UiCoVCTAwJOhlt204ssAxC8SLtdhvHx8chN7iiKH7md71eP1UOyb3g/e+fitp/93dLPY0nCBhffz2GN9wA+9pr/fuLxSLq9frqvseKMp0OeQaF2FXR6/ViFxcr/Yz2AMobT9pvneZB1aQiyVULzYIgQJZlyLIMSZJwcnISOr53u10cHh6uZf1Gj1WyLG998J7ZIoeH0xk/QfgagWEYZnnq9ZnittjrxTrWgGRxG1ni9vnzCy8mwzDr4dRcJZVKJfzSL/0SnvWsZ+Gtb30r/vmf/xn/8R//gV6vh2q1iquuugoPe9jD8D3f8z244oor0Ov10O/3/b//2q/92thzXnbZZaGfb7/99tzL89WvfjX08+WXXz7nOzpbOI4TOrCQi3udU4XTMAzDj9IIUigU0Gq1+KI0haCoDUwHCILfMSphBKYX9/V6feEizmq1ipNA0Qe5tl3XxWAwwGg0Si0aU1UVtVoNiqLg6OgIt99+e2jbkyQJtVoN9XrdX15mTYzHwB13ALfffun25jcD/+//LfW0nihi/NjHTkXtwL5dFEXU6/XEfGNme+i6HhN0S6XSqf+cXNeFaZpQFAWu66LT6SRGLpVKJTQajVM5yOZ5XkzcDhYJr4NCoYBarRaaKUDrfx2D6hxJwoQQBOAURi0xDMNsnUZjel2RgnjRuR1lIXGbndsMs3OcGnGbuNvd7oaf/MmfzHzcJz7xidDP97nPfWKP+Zqv+ZrQz7fddlvu5YgK4Xe7291y/+1ZRJZlKIoSuggcDodQVXWj03dHoxF6vV5MGFVVdSOlU/vIZDLBYDAIudM8z8Mw4ExSFAW1Ws2PnMkTQTILVVVRqVQwHA4hCALq9TpGo1FqWSQw3cZqtZrvCDw6OsJXv/rV0GdN0/7PnTu3sPB+5rEs4MKFqVAdFa6j9wUGP1aBJ4oYP+5xGNxwA5zI/ltVVTQajTPlBN4HaJZFEEmSUM+TnbjH2LaN4+NjX+BOKkwEprPKTvMgm2EYM4sk10W5XIZpmn5cFjAVoXu93sqjcLhMkmEYhmE2QMa5o9Dv5xO3BYHFbYbZQ06duJ2Xm266KfTzfe9739hjouL2Jz/5ydzPT/nfBIvb2TQaDRwfH/tio+d56Ha7OHfu3EZEZV3XY5mvwOl2zS1DkqhN6LoO13UhyzI0TYOqqiuPgiDRhxzjaSWTJKiTG9DzPFy4cAF33HFHSNgWBAHNZhOXX375qZz6vxImE+BjHwNuvTVdtM4qYFkDniRh8oQnoPcjPwInsq+lnPbTWEq479A+PjqYWK/XT/0MmcFgAMdxoOs6xuMxCoVCSNAXRRHNZvPUD7JFXduFQmFj+996ve6XTQaXp1AorExgd103dmxi5zbDMAzDrIGMwWkxp7gtDQZAynWlD4vbDLNznFkF5x3veIf//4ODA3zzN39z7DF3v/vdUavVfFfZxz72sdzP/9GPftT/vyRJeOADH7j4wp4RKLYiWKRFrr51u/jSCrw4czmOaZoYDAax0lTCtm1YloVarYZCoQBBEHzn+yqZJa4Dl8oig4WBjuPg6OgIR0dHMUHt4OAAV1xxxakX1eai15uWOr7//dPbhz40M8tu03iSBPvJT0bnOc+Bfde7xn5fKBTQaDR4sGJHGQ6Hse9vuVw+dYWJURzHQbfbxXg89mcrmaYJy7KgKAoKhQKazeapn2XgOM5Wy7dpACE4qA5M898VRVmJCB2NJBEEgcVthmEYhlkHOZzbSd1s0WtCqd3Ofi0Wtxlm5ziTV/zvf//78YUvfMH/+frrr0+82JBlGd/2bd+Gt7/97QCmOdo333wz7ne/+818/jvuuAM333yz//MDHvCAlQt7p5VKpYLJZBISPHRdR7FYXJuDrdfrJZaFViqVxKLRs0qWqA1MvzOu64ac7hQbsgo8z8N4PIau6zHRIEipVEK1Wg2JmqZp4uTkJFRcSpw7dw5XXnnlSpZxr/nKV4B/+IdLYvbHPw6kZJdvFVmG+wM/gO5znwvjiitivxYEYSXxN8z6oF6FIBQddFqxbRuj0QgnJyexKBYAGI/HqNfrZ2ZANalIctM564qioNFooNPp+Pd5nufnby872BkdvFEU5Ux8tgzDMAyzcVbk3BYDvU6pcKEkw+wcZ07cNk0TL3vZy/yfS6USnvrUp6Y+/j//5//si9sA8MY3vjFT3H7Tm94UGhX8ru/6riWW+GwhCAIajUbMWUvxJKt01Xqeh16vF7vABk5/zuk8WJaFwWAQK3wLIkmSX/7Z7XZDv6tUKks7Z2n6/mg0Ss3UBi4VhUUzTUejEbrdLrrdbui7KQgCzp07hysSBNJTj+sC//ZvUxGbBO3AoN9OoijAM56B8U/8BLqNRmJpKIlV7I7cXUg8jH5+pzH+yfM8GIaB0WjkDwwmHXMEQUChUEClUjl16yCJpCLJUqm0lfdeKpVgmmZokNu2bXS73aWNCVwmycRwXSAqnBwcADxrjGEYZjkyzFS5Y0nyiNvs3GaYneNMiduO4+D5z38+PvvZz/r3/diP/Riuuuqq1L95+MMfjmuvvRaf+cxnAABvfetb8fjHPx4PetCDEh//+c9/Hq973ev8n8+dO4cnPOEJK3oHZwNy7wXzrx3HQb/fX1nRE4krSYJtvV7nfF7kF7UrlQo0TYPneTiKlG/Q7xeFBIdg6VcSsiyjWq3GXH+e52EwGGA4HKLf74eEBkmScHBwgMsvv3zh5dsrTBP4l3+5JGT/4z8Ceabd7QKKAjzrWXBe8AL0Go3pNpkgbFcqFVSr1TMhDu4z/X4/lkNcrVZPVdEeubSjA3LRjGfg0uCgoigYDocrLzTcRSaTSWxq8CYjSaLUajVYlhVyWhuGgeFwuPQxLMhp2saZBTk5iTv+LlxgoYRhGGZZMs6fhIt9J1Hmdm6rKsAmOIbZOU6FuH3jjTfi4OAA119/Pe50pzslPuaTn/wkbrzxxlAW9gMe8AA87WlPm/ncgiDgec97Hv7rf/2vAKZi2XOf+1y86lWvwoMf/ODYazznOc8JxTb86I/+6KnPD10H5XIZhmGE1uVoNEKxWFx6fbqui06nE4vXINf4pqdF7xq2bWMwGMwUlIOiNgmJ/YQcs0Wm1+eNHgGmona5XA4tBxH8nHVdD33elMV8/vz50yuE9nrAP/3TJTF7x/Kyc1EoAM9+NvAzP4Px4SF6vR7chPcgyzIajQYLR3sAfR+DUN/CvpPk0o4SHCxUFAWlUsnvJgCm0STVavXU521HXduryrheFCoUPjo6Cl3kDgYDFAqFhfYttm3HLph5H8UwDMMwa2JFzm3h+Hj265w7B5zW60eG2WNOhbh9fHyMN7zhDXjVq16Fu9/97rj3ve+N8+fPQxRFHB8f4+abb8att94a+pt73OMeePWrX50rLuFhD3sYfvAHfxCvfe1rAUxFvKc//el44AMfiPve974QRRGf/vSn8YEPfCA0zfoxj3kMnvSkJ632zZ4hKJ4keMCheJJFL/xd18XJyUliyVOz2TzTAxF5RG1RFFGpVGJZxpZlxQSreQciHMfBaDSCruszo0foucvlcmoOu2VZ6HQ6sG3bF5sIyuM+PDzcLwHJ84B+Hzg+njq/6Jb08+23A5/61G7mZc+iWAQuvxy4y12ARzwCeMYz4F55JXq9HsaBTNwgmqahVqtxEege4LpuLLaI9r37PMhELu3xeJzoCCI8z4NlWSiVSigWi5BlGZVKBbqu++cOnudhOByuvUR5m2y7SDINSZLQaDTQDsxoCeZvz3u8iLq2JUnar2MOwzAMw+wTWc7tfh+u48DzPP+80/O8uLid5dzmvG2G2UlOhbgd5NZbb40J2VG+4zu+Ay996Uv9jOA8PO95z4NhGPijP/oj/76bbroJN910U+LjH/nIR+IlL3lJ7udn4kiShFqtFhJDXNdFr9dbKAfTcRycnJzEpoSLoohWq3VmHVW2bWM4HCbmwBJpojYRjJABpoJV3mI4ih4xDCMxQzn4nJqmoVwuzxyUMgzDz/MNltYJgoBKpYJisYhWq7X97NN+H7jttnxi9cnJNEIksu3uBZIEXHbZVLSmf6M3ur9WCzkhJpMJukdHiYKhJEmo1+tnekBq3+j1erHPslarLZ3Jvw08z0ucFZKGqqrwPC8k5NM+yfO80ODgaDRCtVo9tQM24/E4tK8XBGFnZkwVi0VUq1UMBgP/Psdx/PzteQZhOG+bYRiGYTZIhjFAcF0IF01UNNicZKgSIjGbMThGimF2kv27okzg4Q9/ODqdDj72sY/FnDKEIAj4xm/8RjzrWc/CQx/60LlfQxRFvOhFL8K3fuu34tWvfjU+9rGPJT7u2muvxbOf/Wxcf/31c78GE0fTNBiGERI+R6MRZFlGqVSC53mhG4DYfXQzDCMmrIiiiIODgzN50UkOweFwmCoqi6KIcrmMcrmcKrSMRqPY9y6rRJI+D13XU7+zBEWPlEqlTLFnMBj4ogTltHueF8q0rdfrqY7vtfOZzwB/+qfAm98MfPzj21mGVXFwAFxxRbZgvUBRlud56Pf7sdkARKlUQr1eP7Xi32lkPB7HZoWoqrp3/QY0w2Q0Gs10aQPT/aemadA0DbIs48KFCyFxtFgs+gOHo9EodAzTdX2uAfh9IqlIcpe+y5VKBaZphgYtJpMJBoNB7kFbgPO2mRQODqYZ29H7GIZhmOXI0VkiXIwmIXE76Ro4VywJwzA7x6kQt6+//npcf/31mEwm+MQnPoEvfvGLvkNX0zTc5S53wf3vf/+lW+8B4KEPfSge+tCH4otf/CJuueUWXLhwAY7j4LLLLsPd73533OMe91jBOzqbmKaJ4XAI5+J0Ibo5joN2ux0aWW2322g2m0tN8aVCwX10DS7LZDJBr9eLudiJPKI2MB3t7vf7oftoqn3a43VdzyUMkfClqmqmW87zPHS7XV88I4e/67pQFMWPraD3tFFuvfWSoH3zzZt97VUhCMD97gc85CGXbjOKeJfBNE10u93EbVMURdTr9Z1xeTL5cBwnNrtDFMW9KU4kl/ZoNJpZsEsUCgWUy2UUi0V/32WaZmybpigOSZJQKpVCoq+u65n7331kMpmkroddIZi/HTxODYdDFAqFXLNFPM+Lvc+zOIjOJCCKLIwwDMOsgxyRbtHc7ViZpCiyc5th9pRTpeqpqorrrrsO11133dpf6653vSvuete7rv11zgqu68YEbIKmbgdFVM/zMBgMFhZHZFnGwcHBmcu/JDE6LYJEEASUy2VUKpVcoko/oZgjqUSSMrmj09GTXr9UKqFcLucWAmzbRqfT8aeAk+vXcRwUi0VUKhUIgoBisTiX624pPvvZqZj9p38KpMzy2GmKReD/+/8uCdkPfnCuE8ZlCTrvo6iqikajcea+s5vAcRzoup454JTErO8zkVSsV6/Xd/6znGcwThRFlEolaJqWuO+KzkKQZTk0g4Tc28HXHo1Gp6JoM0j02CPL8k46mkVRRLPZxMnJSWgb73a7ODw8zBwUtywr9t1gcZthGIZh1kgecXswCJ3TJYnbyBK3OXObYXaSUyVuM/tLUplDEFVVUSwWQ645y7IwGo3mdn0pioKDg4NT54jLYjQaJYrRwKU863lyXk3TTJxeHhRsDMPAcDjMjB6RJAnlchmaps31uUwmE3Q6ndB7Gg6HsCwLlUrFd/gqirL+0rrPfe6SoP3Rj67vddZBqzUVsb/1W6f/PvCBwAYFJyoaTHLFUn77vsVX7AuO4+D4+HghYXtRSqXSzrvvx+OxP/tjFoVCAZqmoVQqpe5fXNeNbdvR45Ysy7FjHLm397lsM0jSetjl73WhUECtVgvNOnBd1y+YnPW5RI95iqKcuXMOhmEYhtkoeWJJIud2MXFbELLFbXZuM8xOwuI2sxNIkhS7sI9SLpdhWVZIhBmPxygWi1AUBYIgJN4A+P+XZRmapp0asSAPtm2j2+2mCsyFQgH1en0uV5nneTNLJG3bRr/fz5zCnzR9Pw/kqIzmhVP+d6PR8N+PJElzF4Hl5vOfvyRo/8u/rP7518U114TF7HvcY+5c7FVhWRba7XaiuFooFNBoNM5kdNAmoDifTQrbVAS6q1CEyqx9V5ZLO0pSgWLSoGylUgm9LuV777IAPA+7XCSZRrlchmmaobx4y7LQ6/VmzhzjMkmGYRiG2TDV6jRKccasQnEwmC1uDwZA5Bgeg8VthtlJWDFgdoZmswnTNOG6bqo43Wq10Ol0/PuA6UVjlovqLJJVGCmKIqrV6kJi/2g0il28k+t7MBjMLKlcJHqEoKK14XAYOxmZTCaYTCah6AraZlYaf/CFL1wStD/ykdU977oQxXBe9rd8y9rysudlNBqh1+slbivVatWPlGHWw2AwCJXmrRtBENBoNHbWwTprdguQz6WdRDSShIokk55fVdXQZ6Lr+qkZkI3O9ElbD7tGo9GAZVmhDO3RaORvD0lwmSTDMAzDbBhRBGo1IGLACiL0ejNjSaR2O/t1WNxmmJ2ExW1mZxAEIRRpkYQsy7BtG8Ph0L/PsiwMh0NUq9V1L+LekFUYWSqVUKvVFhJ9XdeN5SLLsgxZlnF0dJT6mpIkQdO0hUrSPM/DaDTyC0ejWJblO7aDIlCz2VyNY+6LX5wK2m9+M/ChDy3/fKtCEKaRIgcHl26Hh9N/z58H7nvfjeVlzwM5/5Oy3yVJQqPRyNwXMMsxHo9D+1HgUrFhlEWF1ejfqaq6kw5Wx3HQ7XZThf5isYhqtbrQss8qkkyiUqmElsO2bRiGsfMO5yxM04wNiO5akWQaNEh6dHQUGojr9XpQFCW2XTiOEztO7eJ2z2wJzwOixz5Nmx7PGYZhmOWo12eK2+JgAGuGczuXuM2Z2wyzk7C4zewd1WoVhmGEBIPhcAhVVc+8O8p1XfR6vdAU6iAUCVAsFhd+jaiz0XVdeJ6HdsrJgCRJqFarc7sdgakIOh6PMYiUfwQhISE6uFGr1RZ7n54HDIfAV74CvPOdU4f2Bz84//PMi6JcEqajQnXaz40GsOOlfFGiBaBBCoUCms3mzhcN7jsUVRREEAQ0m80ztw/VdR39fj91dku9Xl9KWE4qUJw1cEPHsaDzdzgc7r24Pe962DVkWUaj0fBnjgHT4xPlbwcHbKP7NlEUWdxmLnF8HBdGLlxgJyDDMMwqaDSAL30p9ddCwnVsEHZuM8z+wuI2s3eQCHN8fOwLEpQde+7cuVMxfXsRsgojy+UyqtXqUusnWCLpeR4Mw4DjOKhUKomPp9dcxKltGAYGg0GqExyALwJFxVBN08LLZNvAyQlwxx3Ti8gLF2b/PyMrfGmqVeD664EnPGHqrj44ACqVU+/cMgwD3W43cRutVCpLb59MNq7rot1ux8TcWq12poRt27bR6/VS3dqlUgn1en2p2AzXdWMDjXncypVKJTRYaFkWDMNYalBymyy6HnaNUqkE0zRDMTM0UNRqtfz7ksokGYZhGIbZABmzVcUMcVs8Pp79/IXC9DqOYZidg8VtZi9RFAWVSiUUj0ElhrtcVrYO1lEYmUSwRJKiYFzXRbPZXOlrkqid5OwlVFVFpVLB6NZboXz+8xBPTiAdHUE8PobS7aLY64XF6pOTmeUiG6FSmQra3/u9wHd8B7CnQtUieJ7nZ7FHoRzmfXem7gtJcUUUF3QWoNz+wWCQ6NZexewWIm+RZJRisehHcBHD4XBvxW3DMPauSDKNWq3mx2ARhmFgOBz6A6rRY9dZGjRiGIZhmK0yo+wZyCFun5zMfv5z5069GYlh9hUWt5m9hbJJgxeZuq6jWCzu1XTnRclbGLkq0UrXdUwmE+i6DuOis7lSqYScjaIoolarLeTKyyNqFwoF1GQZyu/9HtzXvAbNW2+d/41skkoFeMxjpoL2d37nmRK0Cdd10el0Eh2ysiyj1WpBlvlQtAmGw2HMQasoypkZELQsC71eL3UgUNM01Gq1lZUc5i2STKJSqYSiY0zThGmaeymURteDqqp7Gz1EM8eOjo5CF8T9fh+KosQiZQB2bjMMwzDMxsg4pxUumhtc14UoijFxW8gjbjMMs5OwosDsLeT4jJY8UTzJqgSKXWSdhZFJOI6Do6Mj360NTIXJoJNwUWFoMplgMBikCk7AVNSuKgrU3/99eC97GYQ77sDOSiPlMvDoR08F7e/6LmBPHYqrwDRNdDqdxLz0UqkUKwBl1gd9z4KIoohms3nqP4OsgcB1lJjOWyQZpVQqxboGhsNhKP5iH7Asa2+LJNOQJAnNZhMnkQvgbreLRqMR28b2cUCCWSOtFvD5z8fvYxiGYZYny7l9cRay4zgQBGH+WBIuk2SYnYXFbWavkWUZtVrNj8sApgerfr+PRsbBbR+h95ZWGCnLMur1+kpFGsuy8OUvfzkmjFUqFQiC4Ds/572AN00Tg8EgNfMWmDreqoUCim94A/BLvwTcdht2UobTtLCgvefizSpIK+oTBAG1Wu3MxGDsAo7joNPpxD6LRqOxdtc85fTbtg1RFFEoFKCqKmRZ3oioblkWut1u6oyQcrmMWq228mVZtkBREARUKpXQsc0wDFiWtVdO4Oh6kCTpVMysUlUV1Wo1dFx0HCdWrCzL8qkeaGcWQJKAq6/e9lIwDMOcTnI4t4HpzNIkw4NwdDT7+dm5zTA7C4vbzN5TLpdhGEZIJB2NRlBVdW9zPZPYRGFkENd1MRwO0el0YsJ2sVicuqkvxp7M85qWZWEwGPjRJknIsoxqsYjSn/wJ8JKXzGy93hqaBnz3d09LIR/5SBa0L0LlrkkDMOR4ZCfj5vA8D51OJ7bfqFara8twpgLB0WgUE5Xpey+KIhRFgaqqKBQKUBRlpQIz5bzrup548SLLMhqNxlq2xVUVKGqahsFgEPrshsNhYs/BLuJ5XuJ6OC0zBarVKkzTDJ17RLe1fRqIYBiGYZi9J0fmNjA9V0u6pkaWc5vFbYbZWVjcZk4FFE8SPEj1ej0UCoWdz/b0PM/P/qJR5Oj/KW81iVUVRgYZj8fo9/uwbTtWAiiKIg4PD9FoNOZat7ZtYzAYpLrOgan4WS2VUPrzP4fwi78Yn7q7bUol4FGPmjq0H/nIaQQJ42PbNtrtdmJcjqqqaDab7GLcMP1+P7bvKBaLqK6h6X0ymWA0GsUKBJNwXReTycQXBgVBQKFQCN0WFUFN00S3203cDtcxEBhl0SLJKLSswcHF8XiMarW6Fzn14/E4duG475EkUSh/Oyl6CeBIEoZhGIbZKFnO7RnitiAI7NxmmD1m96+OGCYHkiShVquFCrhc10Wv19tYRqnjOJkiddrvFmGZ8sY0bNtGr9fzBSfDMEICkSRJuPLKK+dapySQR6enB5EkCZVSCdrb3gbhxhuBXSqK1LRp1Mj3fu9U2K5Utr1EO8l4PEa3203cniuVylrFRCaZ8XgcK/OjfOlV4bouRqORHz2yKJ7nxcRuKuijW9bAiOd56Pf7sfdMKIqCRqOxdjftMkWSUcrlMnRdj7m39yF2K7rP3+ciyTQot/7k5CRx38fObYZhGIbZIFnO7fEYsCw4jhM7JxEFAcgStzlzm2F2Fha3mVODpmmYTCYhZ7BhGBiNRit3i3meB9u2MZlMfFd14tSmNbHqwsikwjXXdX2RhpyH9Xo995R4ytqNuhiDiKKIiqah/Nd/DeHFLwY+9amVvJ9ctFrTE5TLLpv+m/b/q68G9sAluS0o/iHq8Aemn2+j0Vhb/AWTDmVNBxEEAa1WayXu+Xlc2rIso1QqwXGcxKLFJDzPi81YIbGbokyC72MymaDb7SY6aCm/mnoC1smyRZJRRFGEpmmh7xe5t3dZKLZtOzZj4LS5tolCoRDr/gAuDdAwDMMwDLMhMpzbACAOBnDr9di1u6TrQMpMaR92bjPMzsKKDXOqqNfrME0zJHBQPMmy07gty9qamE2sozDSMAw/giQICd2FQgGVSsV3fM4ShxzH8bN2ZwlYoiiiUi6j/O53Q/iFXwD+9V+XfyOFQj6x+vz56YkJiw5LQ0WFSZE5iqKg2WzuRXzCacN13cQCyWXjixzH8QessgRqQRBQLBahaVpsf0UiN93Syh6jWJYFy7L8QTcqafQ8L3VmyDpim2axbJFkEuTeps/T8zzouo5arbbU866T6HoQRfFUD3KVy2WYphkaXF91jjzDMAzDMBnkmNkm9Hpwr7wyLm5HSqETYXGbYXYWVh2YU4UoiqjX62gHDk5UcHdwcDB38SGVRW1KzBYEAaIo+v8G/68oCkql0soulieTCQaDQaIwSYJTrVbzhZlyuZwoEFGcwGg0wmQymeniFARhKmq/5z0QX/xi4KMfXe5NXHMN8HM/Bzz2sdORehYSNsYspyy5/FnY2Q5JedOapi3knJ3n+w1MxVx6rTSHuCRJKJVKfuFvsFeA9j154pps204V2QVBWKjwdhlWVSQZRZIkaJoWijvRdR2VSmUnM+yTBhtOU5FkGo1Gw8+Sp9gwholxdBSf1n7hAgsmDMMwqyCnc9txHBa3GeaUweI2c+ogt2Dw4to0TV8MSGNVYnZQmE4TqtP+v4mL/1miNuG6bqj8TxTFWAGdbdt+1m7WuhIEAWVNQ+Uf/xHiL/wC8OEPL/cm7nIX4H/8D+BpT2MH9hYYDocYDAYxAVIQBNTr9VMbP7APDIdDGIYRuo/cy/NALu3RaJRalkcIgoBSqQRN0xYq0CNXLzl7g5Ekk8kkt9hNqKqKer2+8VkDqyqSTILc2wS5t9dRDLoshmGc+iLJJARBwMHBAWzb9o/tDMMwDMNskJzObSehUDKXuM2Z2wyzs7C4zZxKarUaJpNJSJQZDAZQVdV3H5OYTQLKImK2LMuxDNhddaeZponBYOAXtiWRVtpWq9UgiiJc1/VzzGeJ44Qsy9BKJZT+6Z8gvfjFwAc+sNR7wFVXAS98IfDMZwIrjGZh8uF5HjqdTkw8Babu0larxRmzW2QymaB/sQWeoMK7PPslcmnruj5zP0EoigJN01AqlVYq5AmCAFVVoaoqqtUqPM+LxUIlid2CIKBWq6FcLq9sWeZhlUWSUSi3POgMpwHbXTvmRF3bq4gF2yfO0ntlGIZhmJ0ip3PbShK3T05m/6GiADwri2F2Fj4DZ04lVGR3EjhIkTCnKMrKxOxdLvQi8ojasiyjUqmgUCjgKNISTcJEt9udWQ5JhFyc//zPU4f1+9633Ju47DLgZ38W+KEfAk5xbusu43ke2u124nakqmrI6c9sHso/j9JsNjP3U67rYjgcYjwer92lvQiCIKBQKPivR2I3Cd22bUNRlJWW7M7Lqoskk6hUKiFx23VdjEajrYn5STiOE9tHnAXXNsMwDMMwO0CxODVAzbjuFfp9eJ4XO+cVs8Ttc+c4ApNhdhgWt5lTi6qqqFQqGA6H/n2zMlqT2Ecxm8gjakuShGq16md5n5yc+OI1ZYcCwPHxcebrFQoFaJo2dSvecQfw1KcC73jHUu/BOzyE8DM/AzznOQALJFvDdV202+1Et361Wt3JaISzBA3cRQfsgpn5aViWhXa7nSlqK4qCcrm8UjfyokTF7l1gHUWSURRFQbFYDM2cGA6HO5VnnVQkSdnqDMMAaDbjJdrN5naWhWEY5jRSr0+7DFIQL85yjGoCucRthmF2Fha3mVNNtVqFYRi5BW0Ss0nQ3icxm7AsC4PBIDE6gpAkCZVKJSSKGIYBwzBgWRYMw8BkMskUJagYTtO0S1OxP/zhacHjbbct/B7cZhPe858P6cd/HJiRk86snzRhm+IuVi3gMfPT7/djn0+xWJzZMQBMM6K73W7qbAwSJjVN47iZGayrSDKJSqUS2rc7joPxeLwT7uikIslVliAzzKlAloF733vbS8EwDHN6aTRyidux7qAsMxfnbTPMTsPiNnOqEQQBzWYTx8fHiQKOJEm+K3tfxWxiUVEbmLq8b7vtNui67rs/RVFMFEwoD1fTNKiqGhYu3vhG4FnPAmYswyzcWg3j5z4XpZ/+aUg5CkGY9eK6Lk5OTmBZVuh+URRxcHDAgucOMBqNYlnPsiyjkfH9GQwGGAwGib+jWRgsTOZjnUWSUWjwNTiYMRwOd+KzivZcABxJwjAMwzDMhsnI3RYi/TT+/ezcZpi9hsVt5tSjKAqazaZftEbiwGkpuVpG1HYcB91uF+12O+a4K5fLofgBWZZ9wSs2COC6wIteBLzsZQu9B7dSgf6DPwjnx38c9bvedesiDZMubHNx5O5gWRZ6vV7oPhrQS4sOmVUKWigUUK/X+bOdk+i+c93RLZVKBe122//Ztm0YhrH1+I/oelAUhbclhmEYhmE2S4bBQ0wTtyO9UzFY3GaYnWb/lT2GyUGxWETxlBUR2raNwWAQmw4fRBRFVCoVlMvlmGBMWbuTyST2HJTtmqs8bjAAnvIU4K/+au734Goa9Gc+E8Mf/mGU73IXNLiBeidwHAcnJyexOB9JknBwcHAqBoX2HYqLic5IaTQaqYKi4zhot9uxAQtgOphVq9V4YGlOTNOMrc91u5WLxSIURQm9Lrm3twUXSTIMwzAMsxNkObdTZi6CxW2G2WtYoWCYPWNZURuY5mt3Oh14nofhcBibUt9qtVCr1bKnuv/7vwOPeQxwyy1zvQe3WMTo6U/H8DnPgXt4iFqtlpkPzGwGFrb3g06nE4uAKJfLqQKnaZpot9ux0klBEFCr1VAul9e2rKeZTRRJJlGpVNDpdPyfLcvCZDLZWgZ+UjTLtp3kDMMwDMOcQbKc25FZjwAggJ3bDLPvsErBMHuCbdsYDocxMSUIidqapqVOi9d1Hb1eD7ZtQ9d13/0niiKKxSIODg7QarWyF+i97wUe/3ggK58sgKeq0J/6VAx/9Efhnj8/jVBoNFgE2RFmCduHh4d7nUl/mhgMBjGXbKFQQC1l5sNoNEKv14u5vLkUdDk2WSQZpVgsQpbl0Hd1OBxu7bNMKpJcZzQLwzAMwzBMIgs4t6XxGIicW8fgQkmG2WlY3GaYHcdxHN+pnVSKCUxFqnK5HMvJDuJ5Hvr9PgaDAUajEQzD8J9PURTU63XIsoxms5m9UP/rfwE//uNARASdxfg7vxO9l7wE7pVX+svcarXS406YjWLbNk5OTmJuYFmWcXBwwML2jmAYRqwIUpIkNJvN2CwL+s5HCyeB6efaarXYib8EmyySjCIIAiqVCrrdrn/fZDKBaZob36dOJpPYgBhHkjBMCkdHwNVXh+/7whfYEcgwDLMqFsjclvKYtXg/zTA7DV/VMsyOQpEh0diQIHlEbXqudruNbreL0WgUiiYoFouoVCoQBAH1en12DIllATfcMBW352DwEz+BwU/9FHBxGTniYrdgYXs/sG07JGYClwoko5+R67rodDoxhzcw/c43Gg121i7Jposko5RKJQwGg9D3djgc5pt5s0KSiiR50JJhZjBjBh7DMAyzJBnO7SRxWw5EvaXC4jbD7DSsLDHMDmIYBvr9fswNRwiCgHK5jEqlkimmOI6D22+/Hd1uN/Z85XIZmqZBkiTU6/XZpZsnJ8ATngC85z2534dbLKL7678O4zGP8e9TFAWtVosF0x0hTdjmz2m38DwPnU4nlpldrVZjQqJt22i324n7j0qlgmq1ysWRS7KNIskodBzoBy7SDMOAZVmppaKrxnVdGIYRuo9d2wzDMAzDbI0M57YwGACeBwTOhaV2O/t5WdxmmJ2GxW2G2SFs20a/34+JBcQ8ojYwnTb/5S9/OZYLKwgCqtWq79om53Yqt9wCPPrRwOc/n/u9OFdeifbrXw/rPvfx7ysWi4nxCcx2sCwLJycnMcFUURQcHByws3eH6PV6MTG1VCrFilgNw0C3200sjqzX6yw8rohtFUlG0TQNw+Ew9Hnruo5GxoXdquAiSYZhGIZhdoqszG3HgTAawQuUqYtZsSSynCmaMwyzXVjcZpgdIE8ESblcRrVazSU4uq6Lk5MT3H777TGRSxRF1Go1/5bpzP2rvwKe/GRgOMz9fuwHPQjHr3kN3EDxhqZp2bEnzMZgYXs/oNzsJDE1KmAOh8OQi5egTG6OilgN2yySjELRVMEc9vF4jGq1upFZF9uOZmGYvaPRAD70ofh9DMMwzGrIsU8Ver2QuJ2ZuX3uXMjpzTDM7sHiNsNsmawIkkKhgHq9nnua+Wg0woULF9Dr9WK/owzlXEWOnge8/OXAz/7s9P85cZ7yFFy48UYgEHGiqurGnIRMNqZpot1ux4TtQqGAVqvF4tSO4DgOOp0OTNMM3S8IAlqtlj9Q5Hkeer1eTGgEOF5mHWyzSDKJcrkcGhilwdJ6hnNpWXYhmoVh9g5FAR70oG0vBcMwzOklx/mPOBggeBWU6dzmSBKG2XlY3GaYLZEVQUIO67xigWma6Ha76Ha7MVchMBWY73SnO6FcLme7p8dj4NnPBt74xlyvfXGB4b785Th6ylNCYrgoiixs7xAsbO8HafEiANBoNPwy1jQBHJjGljQaDZ4tsWJ2za0siiI0TYOu6/59o9EIlUplrYMauxLNwjAMwzAM45PjujNaKikcH8/+Axa3GWbnYXGbYTbMqiNIHMfxYwsGgwEmk0no94IgoNFo4KqrrsondHzlK8DjHgd8+MO53g8AoFYD3vQm9L7pm+BGhPVc0SfMRphMJmi327HtTlXVkBOY2R6e52EwGGCYEANEudmUaWxZFtrtdqwMFJgWTVar1bUv71ljV93KlUoFo9Eo5N7WdR21Wm0tr7dL0SwMwzAMwzA+OZzbQlTcznJuB6I2GYbZTVjcZpgNYhgGer1eohgFzBdBEhTJHcdBr9eLRZsUCgVcfvnlaDab+RbwQx8CHvtY4Ktfzfd4APjarwXe9jaMr74a404n9KtisciCx47AwvbuM8uFLcsyms2mv28Yj8fodruxz1MQBDSbTRQDsUDM6thVt7IkSSiVSqHlI/f2OlzlXCTJMAzDMMxOUqtN87FnxGrGnNtHR7Ofk53bDLPzsLjNMBvAtm30er2Yq5qQJAm1Wi23ODAej9Hv9+E4jh9vEhTMJUlCtVrF+fPn8wsOb3wj8MxnAinLmMgjHgH86Z/CqdXQi5wUiKK49sxXJh9pwnaxWESz2WRheweYFUNSKpVQr9d9kXIwGIQKBAlJktBqtXLn8zPzsetuZXJvE67r+gL3qomK/Kqq8gwdhmEYhmG2jygC1SqQULJOxJzbHEvCMHsPi9sMs0YoYkDX9cQIEkEQUC6Xc7vrLMtCr9fznZ2maaLf7/vPTdmrmqbh4OAguzQSAFwXeOELgV/+5fne3I//OPCrvwrIMnoJGc71ep3Fjh3AMAx0Oh0WtneUrBiSWq2G8sU2d8/z0Ol0EnP6OTN9/exakWQUWZZRKpVCAvxwOMzXsxDA87yZN8dxdjKahWEYhmEYBsA0d3uGuB1ybnsewM5thtl7WNxmmDURdFcnoaoqarVaLpel67p+rnbw+YOCWKlUgqZpvshFhXMz6feBpz4V+Ku/yn4soSjAq189LZzE1MEXFdtKpRJPUd8B0qIruGhwN5gnhsRxHLTb7ZioCEyFxXq9zp/nmtm1IskkKpVKSNx2XRfdbheSJIUEatd1ZwrY8yBJ0k5EszDMXnB8DHzd14Xv+9SngMPD7SwPwzDMaSRj9rAQmAEpjscQEowjIThzm2F2Hha3GWbFrDKChErBhsOh74ym+0jAUBQFlUrFz35tNpvZgovnAX/zN8Dznje9qMrLuXPAn/858K3fCuBSmWX0/XEcyfZJE7ZZCN0NJpMJOp1OYgxJsVhEo9GAKIpwHAe6rmM0GsUeG3V2M+tjV4skoyiKAlVVQ8efaJTKqtE0jfcnDJMXz5sK3NH7GIZhmNXRaMz8tdjr+f+X2u3s52PnNsPsPCxuM8yKcF0Xw+FwJREknudhNBr5ZZHB+weDASaTCSRJQrlc9h1zuURLzwPe8Q7gxhuBD394vjd43/sCb3sbcNe7+nclZQQHs4GZ7TAajdDtdmP3s7C9fagINikzm8RqTdMwmUwSZ0UQoiii2WyyY3ZD7GqRZBKVSiV1cHXVUBQWwzAMwzDMzjCHc1s6Ocl+Pha3GWbnYXGbYVZAngiSer2eGRXieR7G4zEGg0HsuVzXRa/Xg+M4KJfLKJVKvkhZrVZRrVZnPfFUmL7xRuCmm+Z7cwDwuMcBf/iHQKCYTNf1mICiaRqKxeL8z8+sjDRhu1wus6N+yziOg263myg80owOx3Fw4cKF1H0JMBVWc0cPMUuz60WSUVRVjbm3l0UQBP8miiIEQfAHWLlbgWEYhmGYnSLLuR2YeSx1OtnPx+I2w+w8fGXMMEvgeR56vV7M1UfME0FCorZt27Hf2baNfr8PWZZDzmhBENBoNNKf33WBt7wF+MVfBG6+Of8bC/JzPwf8/M9Pm6cjyxOE3iuzPYbDYexzAVjY3gUmkwm63W6iaC2KImRZToyRiRKMLGE2w64XSSbRbDYxHA5h23ZImM5zI/E6eGMYZkXU68B73hO/j2EYhlkdGfvVkLid5dyWpEyxnGGY7cPiNsMsyKwyOIogqVarmcKAYRgYDAaJRXHANOvVMAzUarWQU1MURbRaLRQKhaSFm2Zj/+IvAv/6r/O9MaJUAv7gD4AnPCF0t+d5iSIcC27bpd/vhwpGiUqlwoMOW2YwGMRiSFzXhWmaEEURhUJhpstWFEW/MDZPAe1ZIrgeZVleyz5oH4oko4iiyN97htlFCgXg279920vBMAxzuskQo4WguJ2VuX3uXMjkxTDMbsLiNsMsgGma6HQ6iS7MvBEkk8kEg8EgURwnLMvyc3iDpMYSOA7wJ38CvOQl8xVFRrnTnYC3vhV44ANjv9J1PbbMwexvZrPMmj2QGVfDrBXXddHpdELCtW3bGI/HsG0blUplplitKEosgoi5hGVZaLfbof2wJEmQZRmKokCWZf//i66/fSmSZBiGYRiGYS6S5dwOmE7EaMlvFI4kYZi9gMVthpmT0WiEXq8Xcy5nRoRcxDRNvxQyDVmW4bpuovClqiqazWbYOWjbwBvfCPzSLwGf+cx8byjKgx8M/MVfAJdfHvuVZVkxB6osy+wQ3BLkoo/mAQNArVZDJZCRzmyW4ACY53mYTCYwDAOWZUFVVTQajUTBVRAE36WdOCuDATCdORMVtul+x3Fi+1cSuqPCd5bovU9FkgzDMAzDMAyyndu9nv9/MSuWhMVthtkLWNxmmJx4nod+vw9d12O/k2UZzWZzpguThGHDMFIfoygKNE3DaDSC67qx32uahnq9fkmQsSzg//yfqaj9uc/N/6bCTw4873nAi14EJIg3s+JI2FW6eTzPQ7vdThwkaTQa7C7dIsPh0I8aMgwDk8nE/z5XKpXEATBZlqFpGjRN2/nIi21D2/6s0s0o/397dx4mR13nD/xdVV3V9zkzSUgCIpIEIkeARAEPjriLAj9FjgWCK1nBi7B4gYu4LhEVkENdHgGXqOAFKoKCiqB4BDk0IIQAgYBBjiQkmaPvu7vq98dYRVdX39M9fb1fz5OHVE1V9bd7vjOk3/Xpz7dQKFjWM9AXRSyv8pYkCYIg9N1CkkRERESE+pXb6fT0+2hZhthIWxIi6nkMt4kaUKm9gK5iJXWJQqGAeDxesbpWZ7PZ4PV6IYoiwuFwxWDbVImby033w778cuCll1p6Tga3Gzj//Olge86cqoclEgnLx/M9Hg+rS7tAVVVMTU1Z2sMIgoBgMAiHw9GlkQ03/fdELBZDOp02/bxIkgSv12u6ASYIAhwOB1wuF6uBG6RpGsLhcNU1Cpq9VrXQW6/q7reFJImIiIiGXgMLQIqJBJwLF9ZfULLG+2Mi6h0Mt4nqyOfzCIfDlgAEmO417fP5KlYuFwoFJBKJir2QdXrg5XQ6kU6nMTU1ZamMFkURgUBgOrDMZoHvfhe44grg1Vdn9sS8XuCCC4BPfhIYHa15aD6ftyxWKMsy+zl3gd6OoTzcEwQBoVCIIWkFmqYhl8shlUohl8tVbClUTaNfKxaLSCaTFT91oSiK6feEJElGlbYkSa08paEVi8Usn36x2WwYGRmBpmnI5/MoFArGfyv93q5Hv065flhIkoiIiGjo1ancBoB5Dsf0cbt31z6QldtEfYHhNlENmUwG4XC4Yhjm9/srVvEVi0Uj1C4/TyeKIrxer3F+rXYnoVAItkIB+OY3gSuvBLZvn9mT8vuBT3xi+k8oVPdwvVKyvIKR7UhmX7FYxOTkpCWwE0URoVCIVfRl8vk80uk00ul0Uy0sWnmMSqE5ANOCkHa73Vh8lT87zUsmk5bfk/rc128SlC+yW1qdXRp8tzIfWLVNRDM2OQkcdph539/+BoyMdGc8RESDqIHKbeh9t8fHax/HcJuoLzDcJqoiHo9bFk8Epqsug8GgJUhUVRWJRALJZLJmqO3xeOB2u42erlXbnQgCgi++CPG73wWuuw547bWZPaFgEPjUp4D//M/G/of/T/F43BKmejyemv3Fqf0KhQImJyctoZwkSQiFQvx+/JPeJzmVSrWldUUleiV4eeuRUqIowufzwW63G1Xa5cErNS6TySBasvgP8PqnFWq9roIgQJZlyLJs6nWuqqol9C4UClVDb1mW+akIIpo5VQVeftm6j4iI2qeBym1EIkAyCdRoHQqA4TZRn+A7beoNxSJw++1QN2yAIIoQli4FjjwSWLwYmOWPgauqikgkUnHhR0VREAwGTa0E9HYEtUJtQRCMUFv/WLup3YmmQdqxA/Lf/gbl8cfhePJJSE8+CaFC6N20kRHgM58B1qwBfL6mTs3lchXbkRi9v2lW5HI5TE1NWdpdGJX9sxia5vN55HI5SJIERVF6ok2DpmnIZDJIp9PIZrNVfw5nSlVVZDIZZDKZmpW/iqJgZGQEXq8XDoeDVdozlMvlEA6HLfsDgUDLn1YQRRGKolS8SVkadhcKBeOTNkRERETUBxqt3K5XtQ2w5zZRn2C4Td03OQkcfTTw9NOwxGShEHDEEdNB95FHAitWTC+A2CGFQqHqYmUulwt+v99YZCybzSKVSlUMwXWCIMDtdsPj8ZhCwMzkJJLr18Pxt79BfvxxKI8/Dqlev69mjY0BF14IfPzj0/21m6RpGiKRiGkf25HMvmw2W7EXuyzLpnYMsyGRSCAWi5n22Ww2yLJsBIX6QnyzQa+eTqfTFRdhLSfLMlwuF2RZrhmAl3+tUCgglUohnU5DkiS4K/wO0jQNgiDA6/XC7/ezkr5NCoVCxfnv8/lMldjtIooi7HY7q7SJiIiI+pXDASgKkMtVPyYSqd9vG2DlNlGfYLhN3feBDwBPP135a1NTwK9/Pf0HACQJWLbMHHjvtRfQhjAtm80iHA5bQjJBEODz+eB2u00hV63KTUEQ4HK54PF4IAkC8MILwF/+AvzlLyg+/DDszzwDR4d6AGPuXOCznwU++tEZ3QiIxWKWdiRer5eh3Syq1vNdURSEQqFZq5rWNK1qX3i9ujX9z4/0CYIARVFMgXc7x1ksFo2fwUYWC5QkCU6nE06ns+m5m81mkUwmjRtY1c7XA2+Xy9UTleyDQlXVip9Y0H+3EhH1HZ8P+NWvrPuIiKi9AoHa4XWjldsMt4n6AsNt6q7du4F77238+GJxeuGdv/1teoFFAJg///Wg+8gjgUMOmb5T24RkMmnp5wpMV/EFAgFomobJycmKvbHLuXM5eJ55BtJjj00H2n/9K1DykfqO1dnusQfwX/8FfOQjwAwrGvVQr5SiKBUrVqkzUqmUpXIeAOx2O0Kh0KxVR+sLitb6hEL58dls1vSzMtPqbr0diN52pB5BEOBwOOByuaAoSlOPpWka0uk0kslk3Z7d+s8EW4+0nz7vym9g2O12+Bvpo0hE1IvsduCEE7o9CiKiwef31w63I5H64bYkTa9bRUQ9j+E2dVe1iu1m7NgB/Oxn03+A6Y8hLV/+eth9xBFVe2VpmoZoNIpUKmX5miAIUGQZ0R07oCUSEJJJ2FIpCMkkhFQKYioF4Z/bYioFxwsvQH78cQhbtsz8OTVj4ULg4ouBc86Zfu4zpPccL8V2JO2Xz+ehaVrFnsHVbrY4nc5Z/T4Ui0VMTU1VDHn19jyNqFTdXRp2V6ru1hdt1Fv/NPJYdrsdTqcTDoej6QpqvSI8mUzWbXHidDrhdrtb7vdM9UUiEcuNDFmWEQwG+XuIiIiIiGqr13e7kcrtkZFZX/+LiFrDcJu6a+nS9l8zkwEefHD6j27ffaeD7v33n14ROZmEGo8jFw7DHo/DkUpB/GdojdLwOp2G0KHF6WZsr72ASy4BVq+ergRqk1gsZmm54vP5ZnXRwkFWXgmtB3b66xuPxxGPxy3nlfZ8nw35fB5TU1OWuaDf6HA4HCgUCsjlcsYik420CQFeD65zJX3wSqu7i8Vi3dY/pec5nU64XK6W+o/n83kkk0mk0+maAbooinC5XHC73bPa53wYxeNx40aITpKkWW3FQ0RERER9rN4n/SIRoF7LQi4mSdQ3mFZRd82bB6xcCfz+9519nL//ffpPCRHAzOucu+CNb5wOtT/4wabbr9STyWQsVex2u33o2pHorSlyuZwRusqyPONgrVIldD6fx/j4OHw+HwqFQsW+1h6PB75Z7MlZrf+8KIoIhUJGxbL+uuhUVTVCaz3wbrW6uxZRFI0+2q1UT+utU5LJZN02JzabzeinzYrhzkulUpabO4IgzPriqURERETUxxqp3K73PoX9ton6BsNt6r5bbwXe/vbpRRepsj33BA4/HDj5ZOCUU+rfZW5BpXYkes/xYZLL5RCNRiu24rDZbMZiifqfRgPPXC5XcXE8YPq137ZtG1RVhdfrNYXoPp9vVhfPS6VSiEajllDaZrMhFArVrOAXRREOhwOOf7bH0TSt5erucoIgwG63w+VywW63Nx00F4tFI3xPJpN1x6Hf1HG0odUPNSabzVZsxxMMBrmQLRERERE1rpHK7Xpr+TDcJuobDLep++bMAZ55BvjRj4Dbbwcefnj6fzbDyumc7hl++OHTf976VmDBgo4/bDQatQSvPp9vaKolVVVFPB6vWDmt06uLdXrvaP2PvlhiuXQ6jUgkUrGKWdM0xONxo4I4HA7D4/HAbrcjEAjA5XK14dk1JhaLIZFIWPYritJSS4jS10fXbHW3LMtwuVxwOp0VH19VVaiqimKxaATY5X9XVbWhCnJBEIx+2gxTZ1c+n0c4HLZ8n/x+P28wEBEREVFzGqncrvC+x4ThNlHfYLhNvUGWp3tHr14NqCqwZct0yP3ww9Aeemj2F2mcTYsWvR5kH344cOCBHanMriWdTlvaQTgcjlkNVrsplUohFovVXUiwXKXe0aIomsLuSq8t8HqP6Z07d5rO10P20groTtM0DZFIpOI4272IZb3qbr1iXlEU2O12iKJo6sFdHmA32vakFkmSjH7a7Ok8+/R2PeU/fx6PZ+haIhHRgJuaAt7xDvO+P/8ZCIW6Mx4iokHVSOV2vfd+7LlN1DcYblPvEcXphR/33x845xwIANTxcSR//3vg4YehPPYY5I0bITbQm7fn+P3Tldh6kP2Wt0yvwtxFxWLR0gpAFEX46/2DoAHpdBrZbBZ2ux1Op3PG12u3QqGAaDRate+yzWaDKIrI5/MNh6iqqiKbzSKTyRgV2ZIkGWG2zWaDy+VCMBhEOByG0+lEoVAwgj1BEOD3+6FpGsbHxxEIBGBv44KhlcY7NTVlCth1s9Hru7S6O5vNolgsGos81qqibwdZluF2u+F0OtlPu0s0Tau4cKnT6ZzVPvNERLOiWAQ2b7buIyKi9mqkcrtensDKbaK+wXCbelZpdWbR5YJ2/PGIvf3t0xW22SzsW7bAtXEjXE8+CfeTT0J57bVuD9lEE0UU9tsP4hFHQHrb26bD7CVLpsP7HlKpHYnf759RO5LySuBUKoVCoQCv1zujsbaL3gokmUxWDK0FQYDX64Xb7YYgCE33ji4Wi4jFYsYx+jzOZrNwOp2w2WyYmJiAqqpQFAXBYBCJRAL5fB4+n89oiVEsFjE5OQmPxwOv19v2ALZQKGBqasryXPSAfbYq9wuFAmKxGDKZTEcfRxAEiKIIRVGM3t3UPZqmIRwOW/rbK4oydL3+iYiIiKiN6hVqTU1xQUmiAcJwm3pGPp83Ar5q7QZEUYTL5UK8WERq//2R2n9/4MwzAQDSzp3wPv003E8+CefGjXA++yzEFheva5QmitDcbmguF1SPB4U3vQn5ww5D7tBDgeXLEdxzz57uWZ1Opy2BotPpnFGVdbXANB6PQxTFrrcZyGQyiEajlkpRncPhsIT71XpH62009NBbrzqu1OJEEASjSlg/XyeKIoLBIJxOJ1KplOXcRCKBbDaLQCDQtl7Q1Ra41McyG8Gv3oIllUrNuL2IKIqQJMn4b6W/i6LICu0eUumGhr5wKb9PRERERNSyeoUSjbz3YLhN1DcYblNPUFUVk5OTDfU81qv69MpYvSI253Bgcvly2A4/HB6PB0ImA9ezz8K1cSPcmzbB8Y9/QMrlIHo8EHw+CG434PEApf+ttO+f/y04HMjJMjI2G3KyDNXlAux2oEII43K54Pf7ezqg0TQNsVjMtE+SpBm1I6m1cCIwXSUuSVJXFojT269Uqw7Wn3ujYxNFEXa73RQCJxIJTExMwOFwGItPqqoKURTh9XqhKErVxx4ZGYHNZoPb7UYkErG0Ssnn85iYmDBVlLeq2vdJkiSEQqGOL6aoaRpSqRTi8Xjdn3lBEOqG1pIk9fTPGlklEglL2xlRFFtauJSIqG/4fMBPf2rdR0RE7dWGFpvsuU3UPxhuU0/QNK2pxfz0BeAmJyeRTCYhiqLRH1kURRQKBfhHRqAceyyE446D5PVCdrmaDk3y+TwymQwymYzlo/PV+Hw+eDyeph6nG5LJpKV62e/3txQs6UF5Iz2Sw+EwRkZGqga97aZpGpLJJOLxeNUWJG63e8ZtP+LxOOLxOBRFMT03/fqaphmV3qXjsNlsGBkZMSrF9aA7mUwiFouZjtVf50wmg0AgAJut+V/h+jjLybKMUCjU8U8aZLNZRKPRqm1dJEmCx+OBoihGeE2DJZPJWG6sCYKAUCjU0pwmIuobdjtw2mndHgUR0eBrR4s7Vm4T9Y2BfBeZz+fx/PPPY8uWLcZicR6PB2NjYzjggAOwYMGCbg+RyuhVsJUW9tMrNPXqzFwuZyzSN2/ePGSz2Yq9k/P5PILBYFMfcdcDSD3QrtVXuZQgCLDb7UYo1+tUVUUikTDts9vtLVVUF4tFhMPhigsSyrIMRVFMobe+gNzo6GjHg6x6Qardboff75/ROMr7i5dfPxgMmgLa0pBbEISqixm63W4oioJIJGK5sZLL5TA+Pt5UX2xN0xCNRpFKpSxfczgcCAaDHa1+rrd4p34TwOPxMNAeYLlcDuFw2LI/EAj0xe9OIiIiIuoDM63cFkUgFGrPWIio4wYq3N61axfWrVuHu+66y1IVVmrRokVYtWoVTj/99LpVitu2bcPKlStbGs/cuXPxwAMPtHTusNGr9nK5HFRVNbUcEAQBhUIByWQS6XTa+LpOX6BPb3GgKAqcTidkWUY2m0UsFoPP56sa3Gmahlwuh3Q6jWw2W7UXczk9kHc4HHA4HH3VFqFSOwhfCx+LzWazCIfDFavuS1uz6G0odHobmtHR0Y5UCusLOlYKnIHpGyY+n29GvcX1x5mamqpY1e92uyvOO0EQLNXd1ciyjNHRUcTjccvNCD1U16u4awXCqqoiHA5XDJarjbNdGumr7XQ64fV6WbU74PR+/OXzoB0/i0REREREhplWbo+MTAfcRNQXBiZJuP/++3HJJZcgGo3WPfaFF17AF7/4Rfz85z/H9ddfjznspdQT9OrnUnpVdrU+yTq9ArdSOJ1MJo0qbj1I1TTNqM7OZrMNt0QRRdEIs+12e18F2rpCoWCp3tVvBjSjWnsLQRAsFcV+vx+qqpq+j3owPDIy0rZK3UZ6OestSGb6mHoFavl8EwQBPp+vbQtn6tdzOBwVHy+TyRhV3JUq72sF8H6/v2MLfDbyvZBlGX6/nxW7Q0BV1YoLmLpcrr5o40REREREfcTrndn5zIiI+spAhNsPPvggPvnJT5rCG5vNhsMPPxyLFy+G0+lEOBzGE088gWeffdY4ZtOmTTj77LNx++23N/zmWq8kbgSrEFujaRrS6bQRStciyzLcbrfR2qFa7+dcLoeJiQm43W6jrUm1KtJykiTB6XTC4XBAluW+DLRLlfee1sPTRqmqalQMl7PZbAgGg5agXBAEBINBTExMmL6n+Xwe4XC4qdYx1eRyOUSj0apzRlEU+P3+tiyWWG1BRlEUEQwGLTdp2kFRFIyNjSEWi1luTugBdnkVdj6fx9TUVMUAPhgMdmxhT72ncq2+2l6vt+GWKtTfNE1DOBy2zAf9piQRERERUVtJ0vSCvTU+0V8T+20T9ZW+T18zmQy+8IUvmAKtFStW4KqrrsL8+fMtxz/yyCO46KKLMD4+DgB48cUXcd111+GSSy5p6PG+8pWv4OSTT27P4MlE7wOdSqXqVlI7HA643W5LiKhXDcuyjGg0agof9VYVjZBl2ajQbkcY2iv09iul3G53w61BqoWlwPT3pFZ7DEEQMDIygomJCVPIlc1mEYlEEAwGm3gmr9PbXlRbzFIURSNIbceNiWoV6zabreML4omiiEAgAIfDgUgkYvk5SSaTyGazCAQCRiuSSgF8KBTqSLV0Pp9HLBar2Vfb4/HA4/H0/U0iaoyqqhV7rcuy3PE+70REREQ0xPx+httEQ6Lvw+0//OEP2LFjh7G9995746abbqpaEXjEEUfg29/+Nk455RQjYPvZz36GCy+8kB+N77LJycmaldqiKMLlcsHlctUNEF0uF2RZrhrEVqIoihFoD2rVfXkoK4piw59aSKVSlhsGOp/P19B19GB1YmLCFMym02mjD3YzUqkUYrFY1ZshLpcLXq+3LX29m104spMcDgfGxsYQjUYtFfSFQgETExMVz7PZbBgZGWl7n/N6NxiA6dY3Pp+vIz3Wqffo6yRU6rUuSRJCoRAXDiWi4RMOA//6r+Z9v/0t0OINfiIiqiEQAF59tbVzGW4T9ZW+T/AeeeQR0/bq1avrftR9v/32w8qVK3HfffcBmK52fOqpp3DYYYd1bJxUW6FQqBps22w2uN3upitvZVnG2NhY1YX09IX99EB70EM3vb94KY/HUzdg0jQN0WjU0goDaK0Nh17hPDk5aQq9EokEJElqqAd0JpNBPB6vOWf8fn/b2oO0snBkp+kBYa2bDqU6EcBrmoZkMolEIlH1BoOiKPD5fLx5OCRyuZyx+G8l+uLBg/77loiookIBeOwx6z4iImq/mbS/Y7hN1Ff6PtzetWuXaXvZsmUNnXfooYca4TYA7N69u53DoiZJkgRJkkxV1na7HW63e0Z9gfVK4UQigUQiYVxXD7SHpXJQ70VeqpEguVAoIBwOVwx1FUUxLdLZDP3c8rYZ0WgUoijC6XRWPK9eqC0IArxeL9xud9vC5lqtWDq5IGOjXC4XFEVBJBJBLpereozf729rAM++2lQqk8kgkUhUnYPA673eB6nVExERERH1qECg9XO5oCRRX+n7cLu8WrDRILQ8PGPfz+7S+zEnk0kj3GxXaxA98BzmPr/pdNoSQtarNs5kMhX7OgPTFd9er3dGr6fD4YDf70ckEjHtj0QiEEXRVHWdTqeRSCRqtq3Rr9fOitBuLBzZCr3diH4Tp3S8Xq8X3pmuFl6CfbVJpy/+m0gkqt7kAKbnhMPhgMfjYbBNRERERLODldtEQ6Pvw+2FCxeatl977TW88Y1vrHve9u3bTdtveMMb2jouap7eSqJThjVo0zTN0mtbluWq1dH68XqleylRFOH3+6ue2yyXy4VisWgan6ZpCIfDCIVCKBaLdUNtm80Gn883owr/cpqmIZFIdG3hyFboN3EcDofRJmSmn3wol0wmEYvFqrZAYV/t4aCqKlKpFJLJZM01DQRBgNvtbmrRWiKigeb1AjffbN1HRETtN5PKbYbbRH2lt9KZFrzjHe/AbbfdZmz/5je/wZFHHlnznGKxaGpJsmDBAixZsqRjYyTqpkQiYQmgqi3cWCwWEQ6HK7YWkGUZwWCw7aGu1+uFqqrGYoR6NejWrVvh8XiqhmI2m80Ic9t140J/7Hg8XjG0m+2FI1uhf5/aSW9rU23BSPbVHg76zaZKi0SW0lseuVyunv5ZISKadQ4HsHp1t0dBRDQcWLlNNDT6Ptw++uijsWTJEmzZsgUAcMcdd+DYY4/FMcccU/F4TdNw1VVX4aWXXjL2rVmzpuE34Pfddx/uuecebN26FeFwGHa7HYFAAIsWLcKKFSvwnve8B3PYn4l6hB5GlbLb7RXbaeRyOYTD4YqhrtPpRCAQ6Fj1u8/nQ6FQQDQaNbVQicVi8Pv9pp/PTobatdordKJvdT9QVRVTU1MVb3hIkgSfz9e2Sn7qTfl8HolEouoikTpZluF2u+F0Oofu54SIiIiIegx7bhMNDUGrVX7VJ7Zu3YpVq1YZvXtFUcTpp5+Ok046CYsXL4bT6UQ4HMbGjRtxyy234K9//atx7hlnnIEvfvGLVa+9bds2rFy5suGxKIqCU089FRdeeOGMF5pbuHAhtm/fjgULFmDbtm0zuhYNp2g0aqm2HRsbs/S91VtwlP86EAQBPp+vo4smllZLT05OWlqQyLIMv98PRVHg8XjaHqTqj12rZ3AvLBzZDbUW02xH33XqbZlMBslksmp/dV07Fv8lIiIiImqrm24CPvrR5s8TBCCfB9hWj6hvDES4DQCvvPIKPv/5z2PDhg0NHT86OooLLrgAp59+es3jmg23dfvssw++9a1vzaiXN8NtmolCoYDx8XFTYO1yuRAouYOt97fOZDKW8yVJQjAY7FiriUrV0qqqIhKJmMJUfbHEefPmtfXxM5kM4vF4zX7edrsdXq93KNttVFtMUxAEBAIBVmsPKP3nMplM1vzZ4CKRRERERNTTfvpToE7eU9HoKDA+3v7xEFHH9H1bEt1ee+2FH/zgB7jzzjtx5ZVXIhqNVj126dKlWLt2LQ4++OCGr79kyRK8613vwmGHHYZ9990XgUAAmqZhYmICTz75JH7xi1/ggQceMI5/8cUX8eEPfxg/+clP2t7/lqgR5Qv/6QsOlopEIhWD7U72ltY0DalUqmIvcH3BykgkAlEU4Xa7oSgKVFVFNBpty4Kj2WwW8Xi8YpsNnaIo8Hq9Fdu3DIN4PF5xMU1JkhAKhRhmDqBmFol0uVw1++ETEREREXVdq+8d2W+bqO8MTOX21q1b8ZWvfAUPPfRQw+ccddRRuOyyy2pWhCYSCbzwwgs45JBD6l5v/fr1uOiii0zB+oknnohrr7224TGVYuU2tSqXy2FiYsK0z+PxmBaSrBZger1eSwjeDrVC7VKKosButyOZTEJVVdPXfD4fPB5PS4+fy+UQi8VqhtqyLBv9vIeRXjlf6YaHoigIBoMMNAdQKpVCNBrlIpFERERENDj++lfg8MObP++oo4A//antwyGizhmIcPuhhx7CmjVrjMWuZFnGaaedhhNOOMHouR2JRLBp0yb8+Mc/NlVYh0Ih/PCHP8Sb3vSmtozlsccew9lnn220WRAEAXfffTcWL17c9LUYblOrJiYmTCGuKIqYM2eOEUplMhlMTU2ZzhFFEcFgsO3Vys2E2qXV0tlsFlNTU5bALRgMNtUSI5fLIR6P1+wbbLPZ4PP5hjbUBqbb2ExNTVXsPT6si2kOg1QqZaxXUYnNZjN63fP7T0Q0Q5EIcNJJ5n2/+MXMFj0jIqLKnnsO2H//5s879VTg9tvbPx4i6pi+b0vyyiuv4PzzzzeCbZ/Ph29/+9uWliNjY2NYuXIlVq5cidtuuw1r164FAExNTeHjH/847rrrrrb0kF2+fDlOOeUU/OQnPwEwHez95je/aSncJmpFJpOxVCd7vV4j2M7n8wiHw5bz2h1sa5qGZDJZt81BtRYgdrsdgUDAMla9ZUm9sebzecTj8YpVyDqbzWZUag9zcJfNZhEOhy2V8rOxoCh1j95XvRIuEklE1AH5PLB+vXUfERG1X6s3DtmWhKjv9P1ni6+55hqkUilj+7LLLqvbS/vMM8/EmWeeaWy//PLLuPXWW9s2plNPPdW0/cgjj7Tt2kS1aJqGWCxm2mez2eByuQAAxWKxYjW03+9vW7Ctqiri8Th27dqFWCxWNdhWFAUjIyMYHR2t+thOp9PUSgV4fRHMaovdFQoFhMNhjI+PVw22JUlCIBDA2NjY0FekJhIJTE5OWoJtURQRCoUYbA+oTCZTMdh2Op0YHR3FyMgIg20iIiIi6l/suU00NPo63I7H47j//vuN7b322gvvfve7Gzr3Ix/5iGn7rrvuatu4DjjgANOCazt27GjbtYlqSaVSlrYSXq8XgiAYoXB52OxyudoSYBaLRcRiMezevRvxeNwSlursdnvdULuUx+OxjE9VVUxNTZmeix5q79692/gkRzlJkuD3+zFnzhy4XK6hDrU1TUMkErHcDAGmWzs1+v1pp2KxiGg0ikgkUrE9CrWHXqlffpPL6/UiGAxCUZQujYyIiIiIqE0cDqCVf9fOmdP+sRBRR/V1W5KnnnrKFG6tWLGi4bBq/vz5WLhwodHL+oUXXkA2m21LmCOKIgKBAMbHxwGgYgsIonbTK6ZLKYpitNuJRqOWdiWKosDf6h3tfyoWi0gkEkilUjUXpLPb7fB6vS0FZ36/H6qqmkLrYrGIyclJBINBJJNJpNPpqo8viqIRkg9zoK0rFosIh8MVF9d0OBwIBoOz/jrl83lTBXk2m8WcOXP4/WozvS1R+c+K2+3uyEKyRERUwuMBvvlN6z4iImo/QZiu3v5nLtMwVm4T9Z2+DrcnJydN22NN/hIaGxszwm1VVRGJRDB37ty2jK20HcJsVz/ScEomk5Zqab2lhx4+l5IkCaFQqOXwsFAoIJFI1AyVgemw1OPxzLgaNBAIQFVV08KQhULBuIlUCUNtq1wuV7GCH5iu3O1GwFkebAPTAXwqlWJblDYqFAoVW9DoC4YSEVGHOZ3AmjXdHgUR0fAIBBhuEw2Bvg63y0PjWgvHVVLeukDvSzxT4XDYVEE7MjLSlusSVaNXT5dyOBxQFAWZTMbSekIQBIRCIWORyWbk83kj1K7F6XTC4/GYWvTMhCAICAaDmJycrNpvu/RYPdRu5TkOqlQqhWg0arkZob+23eixXCnY1iWTSYbbbVIt2HY4HAy2iYiIiGgwtfLvXIbbRH2nr8PtUChk2t66dWvD5+bzebzyyivGtqIobatYfOCBB0zb++23X1uuS1RNPB63BJY+nw/5fL7ionHBYLDp0DmXyyGRSNS8iSQIghFq22zt//WiL3I4MTFRsfJYEAS43W54PB6G2iU0TUM8HrfcAAGmFxxtZT60Q61gG5gOZDOZDBc2nCF9Idnynxm73d6VFjRERERERLMiEGj+HIbbRH2nr8PtpUuXQpZlo4pzw4YNGB8fb6g9ye9//3tTm4Zly5a1ZUz5fB7r1q0z7Xv729/elmsTVZLP5y0tR1wuF0RRxMTERMVWJc2EhdlsFolEwtQOpJwgCHC5XPB4PJAkqbkn0CS9nUppKDqbj99vVFVFOByu+P3Tw81u3AioF2zrkskkw+0ZUFUVk5OTlgU6FUWZUVsiIiIiIqKe12zltiAA/OQ9Ud/p69JGl8uFt771rcZ2NpvFl7/85brnhcNhXHXVVaZ9xx57rOW4Xbt2Vax6rUZVVfzP//wPXnjhBWPf2NgYTjjhhIavQdSs8kUk9ZYc4XDYEmjpVdWNyGQymJiYwOTkZNVgW+9pPXfuXPj9/lkLlmVZxtjYGDweD3w+H+bMmTOrj98vCoUCJiYmKn7/3G53y61pZqpasF1pgdNsNlu3DQ1VVi3YlmWZwTYRERERDb5mK7dDIaADn0Amos7q63AbANaULcpy77334oILLqi6yNymTZuwatUqbN++3dg3OjqK008/3XLsU089hWOPPRZf/epXsXnz5prjeO6557B69Wrceeedpv2f/vSn29bLm6hcNpu1tAnxeDwVK60VRUGgzv/cNU1DOp3G+Pg4pqamkMvlKh4niiK8Xi/mzJkDn8/XlYBUkiT4fD5Wa1eh35woDzYFQUAgEIDf7+9KuJnL5SoG23a7HSMjI8anDkolk8nZHOJA0DQNU1NTlhsDNputazc1iIiIiIhmVbOV22xJQtSX+v6W1KGHHoqPfexj+Na3vmXsu++++/DHP/4Rb3nLW7B48WK4XC5EIhFs3LgRTz/9tOl8WZZxzTXXVA2gk8kkvvvd7+K73/0uxsbGsHTpUuy5557wer1GePDkk09iy5YtlnPPOeccnHzyye19wkQlyheK1EPe8jYlkiTV7K2rh9qJRMIShpZfx+PxwOVyseqzhyUSCcvcAF6fB4qidGFU08H21NRUxWC7tJLY7XabPpGQTqe7dhOlH2mahnA4bLk5JUkSRkZGeDOIiKhbolFg1SrzvltvbW3BMyIiqq/Zym2G20R9qe/DbQD41Kc+BVmWccMNNxgLZuVyOTz44IN48MEHq54XCoVw5ZVX4ogjjmjoccbHx7F+/fq6xzkcDlx88cU488wzG3sCRC1Ip9OWqkxFUSyLBgqCgFAoVDHQyufzyGQySKVSFRdo1NlsNng8HjidzoZD7UKhgFQqhUKhALvdzkB8FhQKBUSj0YptSPRWFN0KNhsNtoHpllOJRMJYJFXTNCSTybYt+jvINE1DJBKxfKJDFEUG20RE3ZbLAffcY91HRESd0ezNwzlzOjMOIuqogQi3AeD888/Hsccei5tvvhn33XdfzcXvRkZGcOqpp+Lss8/GSI3FApYsWYJVq1Zhw4YNePHFF+sufDY2Nob3v//9OOusszBv3ryWnwtRPZqmVey1nclkjEBQFwgEIMuycV42mzXamdQKtIHpQNTj8cDhcDQUTKuqinQ6jVQqZQreM5kMcrkcAoEAA+4O0MPfeDxu+f4D073Wu/na661IysdWKdgGpiuMnU6n6RMIqVQKHo+H86eOaDSKdDpt2qcH2zb2DyQiIiKiYcK2JERDYaDe6S5duhRXX301vvKVr2Dz5s3YunUrYrEYMpkM3G43gsEgli5din322aehgGTPPffEpZdeCmA6WPn73/+Obdu2YWJiAqlUCoIgwOv1IhQK4c1vfjP23HPPTj9FIgAwKqJ1mqahWCxaqjK9Xi8URUEymTRC7UrhZzlFUYxQux49ME+lUjWvrwduDLjbK5/PIxKJVF10Ue9L3i3Vgm2Hw1GzVY7b7TaF28ViEZlMBk6ns6Pj7WexWMzSkkj/5IZ+g4uIiIiIaGiwLQnRUBiocFunKAqWLVuGZcuWte2aLpcLBx10EA466KC2XZOoFaqqmqq29X7Zet94TdNQKBSMSu7yCu9a7HY7PB4P7HZ73WNzuRzS6TTS6XTdTzXo0uk0BEHo2mKGg0Sv3k8mkxVvKEiShEAg0ND3slOy2SympqaaDraB6U8NKIpi6hudSCQYblcRj8ertiTqVo91IiIq43YDV11l3UdERJ3Bym2ioTCQ4TbRbNM0DZqmzcqCd4lEwhQmJ5NJKIqCbDaLXC6HXC4HURQRCASqVvOWkiQJDocDTqezbghWLBaNtiO1Fp4svbaqqqZwU68sDTR7F50M2WwW0Wi06vfA7XbD6/V2dQHGmQTbOo/Hg6mpKWM7n88jl8sxrC2jt6QpJQgCgsFgV29uEBFRGZcLuOiibo+CiGh4NPuekz23ifoSw22iGcpms4hEIigWixBFEYqiGFWnsiy3NWAsFotIJpPG3/U2BHa73QgRRVGEz+erGh4KggBZluFwOOBwOOr24dUrw9PpdM1e9qXX18Nyu91uLCTIgHvmVFWt2HpCZ7PZEAgEuh7+tiPYBqY/SSBJkqk3vH4zh6alUilEo1HLfr/f31BbISIiIiKigcXKbaKhwHCbaAbKg1tVVZHJZJDJZIxjbDabKfC22WwtteTQNA0TExOIx+PI5/PIZDJIJpPweDzG4wuCAJ/PZ+m9LYoi7HY7HA4H7HZ73cBd0zRT25FG+3S7XC44HA7T9e12O4LBIMLhsCXg1luUUH2ZTAbRaLTiIqCCIMDj8fTEgovVgu1WFrUUBAFutxuxWMzYl06nK87xYZTJZBCJRCz7/X6/0aaIiIiIiGhosec20VBguE3Uonw+XzHEK1coFEztI/TK6dLAu1ZQpy/WmEgkjBYNqqoimUxClmXTuR6Px1g4TpZlI9CWZbmhULFQKCCVSiGdTlcMUcvZbDY4nU44nc6aFeB6xW55wK1XoTPgrk6v0NcX5CynKAr8fn9PLBiYyWQs32OgtWBb53K5EI/HLfPG5/PNeLz9LJvNIhwOW/Z7vV642b+ViIiIiAho9j0Dw22ivsRwm6gFhUIBk5OTDS+kWEqvii5dKE+SJEvgnc/nEY/HjVYg+mJxmqYZiwiWth1wu91GKwKHw9FwZauqqkaFdumYqhFFEQ6HAy6Xq6n2EAy4m5dKpRCLxSrOM71K3+Vydb1aG+hMsA1MzzeXy2XME2D6dfF6vT3xvLuhUqsfYPrmltfr7dKoiIiIiIh6jCQBXi9Qtj5NVaOjnR0PEXUEw22iJlULtvU+07lcDvl8Hvl8vqF2HsB0dW6xWEQmk0E+n0cqlYKqqrDZbJBlGaqqGsFzMplEsVg0KrJlWYbP58PcuXOb7u+ttzWoF9ILggC73Q6n0wmHw9FyqMiAuzGFQgHRaLRqj3O73Y5AINAzrTk6FWzr3G63KdxWVRWpVGooK5SrfWLE5XINfTU7EREREZGF399YuB0KAXXWoyKi3sSfXKImFItFTE5OWlp26H2lBUGA0+kEMF1hrYfceuBd2p6knN4SpDTQLBQKyGQyRs9hPbx2uVyYM2eOEW6PjIw0FWxrmoZYLGYKDCuRZdloO9KuINXhcCAQCCASiVgCbr0aeVjpVfnlbTh0oijC7/cbc6wXVAu2XS4X/H5/W6qrbTYbHA6HqZd9MpkcunC72o01p9PJG0NERP0gGgXOPde879vfbn7BMyIialwgAGzbVv84tiQh6lsMt4kapKpqxWBbURSEQiFLiCcIAhRFgaIoRginV2CXBt65XM4SapfS94uiiGKxCL/fD6/XC1mWIYoigsFgU8F2sVhEOByu2oJEkiQj0O5UH2c9nC3vGay3XhnGgDufzyMSiSCfz1f8uh5gNlud30npdNpykwJob7Ctc7vdpnBbv/FT2ppnkOk31ip9YqQd1fFERDQLcjngZz8z77vhhu6MhYhoWDR6A5HhNlHfYrhN1AA92C6vvJZluWKwXY3er9rhcKBQKCAejyOXy0FRFIiiiHw+j2KxaFR8661JXC6XEfyKogi73Q5BEBAMBmsu5FiuVhsSvY+2fu1OY8A9TdM0xONxo496OUmSjF7qvaRWsB1odlXyBtjtdsiybAr/k8lkz70unZDNZhGNRmt+YoSIiIiIiCpo9L0Jw22ivsVwm6gOVVUxNTVlqai12WxNtwMBYITa6XTauI4kScZ1isUiRFGEx+OBzWYztSUBpivFBUGA3++H3W5v6DH1AFUPjkvp13K5XE09j3aoFXALgjDwi+PpoWW1djVutxs+n6/nwsvZDrZ1brcbkUjE2M5ms8jn8x37hEE3aZqGdDqNRCJRcX4oisJgm4iIiIionkYrt+fM6ew4iKhjGG4T1aBpWsUWHq0E24VCAYlEAqlUyrh2LpczAjpVVSGKItxuNxRFQS6XM1qW6CGiXqXtdrsbDqNrtSGx2WwIBoNdDQedTic0TTOFlgAQ/+eiH4MYcKuqilgsZsyFcrIsw+/3Q1GUWR5Zfel02nIzApiek53u++x0OhGLxUyfPEgmkx0N1GdbsVhEKpVCMpmsutCr/omRXmpRQ0REDXC5gEsvte4jIqLOYeU20cBjuE1UhR5sl/fCliQJoVCo4QUWi8WiUaldLBZNgbYeWuvtSkRRRDabNVVY22w2FAoFY3HHZhZdrNWGpJd6OOtB/TAE3JqmYWpqquLNBkEQ4PF44PF4erIiV188stxsBNvA9OvjdruNeQFMh+0+n68n5vFM5PN5JJNJpNPpiu1pdAy2iYj6mNsNrF3b7VEQEQ0X9twmGngMt4kq0CuJSxewA6ZD6JGRkYb6XBeLRSQSCcTjcWSzWSPQLqWqKiRJgiAIlseSJAl2ux0ej8cIuyVJgsvlMs6rNf5abUh8Pp+xyGWvqBVw66Fvv6v2SQBgus1EIBBoqof6bMrn810NtnV6/3k9ANY0Dclksm9vgOg3s6otKKuz2WzweDzGDS4iIiIiImoAK7eJBl5vpihEXRaNRo2e2LpGg+1isYhIJGKE4+X9cguFAgqFAkRRhKIo0DTNWChOlmUoigJFUYzH0TQNqVQKsizD4/FAFEXkcjmjX3Wlx+/lNiS1VAu49Z7j/R5wx2Ixy02MXr3ZUEpVVYTDYUtFscfjmfWFPyVJgtPpNLV0SaVSPVvtXkm9ftql7HY73G73UCycSURERETUduy5TTTwGG5TT1NVFZqm1fxT75jSrwPTYWKtP3oLET0oEwQBoigiFAqhWCxCVdWK5+VyOUxOTiISiVQMtHO5HAqFAhRFMYIqQRBMgXZpNbYoirDb7XA4HLDb7aawulq4nc1mEQ6HK7YhcTgcCAQCPd/OwOVyQdM0RKNR0/5uBNyaprUtME0kEkgmk6Z9oihidHS0Z6u1gderzcvntMvlmvVgW+d2u03hdrFYRCaTqXrDp1c00k8bmP694HQ64Xa7e/ZGFBERERFRX2DlNtHA691EhYZOJpMxKhlLw+jZlEwmLYv8CYIAv9+PZDJpCSeLxSIKhQLy+TwymYxpzPl83gi0NU2D3W6H1+s1Krb1P6Vhs9572+l0QlEUI1jVe3XryquyNU0zWqCU64fK4HL6WLsVcOuVyrlcDna7HcFgcEYhdzqdNsauEwQBoVCop4NtYPo1L2+ZoSjKrLYiKaffECr9OUgkEj0bbjfaT1tfUNblcjXc05+IiIiIiGpgz22igdfbqQoNjWptD2ZTOp2uGGz7fD7IsgxVVY2WIvl8HoVCwVR9qWmaKdDW2e12OJ1OOBwOI9AuDUr1NgsOhwOyLFcMURVFMW3n83moqgpRFI02KJV69kqShGAwaDm/H9QKuPWFBTtF75MOvH7TpdWeztls1tJmBQACgUDPf1/0KuNS+pzqdgsQj8eDqakpY1v/2eul15T9tImIiIiIuqzRyu3R0Y4Og4g6h+E29YRuVWrr9P63pQqFAhwOhxFu6n2xy+k9scsXi3Q4HPD7/RVDa1mW4XA4jK/Vo59f+hrlcjkIgoBIJFJxbP3ShqQWt9sNTdMsVc964N2JgFvvh1wqnU63FG7rizCWz22fz9ezVca6XC5nubEgCAKCwWBPVBXb7XZIkmSa+8lksuvhtj5/ksmk5XdCOfbTJiIaMrEYcMEF5n3XXQd0qc0XEdFQaKRyOxgE2A6QqG8x3KaeoFcvl4eK5fT+1/X6Zlc7BoClJ3cymTSCYr0yu1AowO12QxRFo8e2HujpQWXp+XqltiiK8Hq98Pv9sNvtprHrvbYdDkfTrSgEQYCiKEYFqKZppqrV8mO9Xm/fL76o05/HbAXc6XTa0g9Z75neTHBaLBYxNTVluZbb7e75740+9vJQ3u/3dz081unV+6XzIp1Ow+fzdSV811sDsZ82ERFVlc0C3/ueed/VV3dnLEREw6KRym22JCHqawy3qWd4vV6oqgpVVY2FFCVJsoTTM6G3DtFbGCQSCVNILEkSJEnCyMhIQ5W1yWTSCL5lWYbT6TSCNT2Q1gPtmQZueritqiri8ThUVUUwGDQd089tSGqpFXALggCXy9W2xypvw6FLp9MNv66qqmJqaspSUe9wOLq2CGOj9Bsn5QGtx+Np6+vcDi6XC/F43BTCJ5PJWX+NVVXF5ORkzUpt9tMmIiIiIuqCRiq3GW4T9TWG29QTNE3DxMSEEajl83kkEgmjR7Xdbrf0qm7m2nqbAH1xR2C67UJ5WApMV9ZWC7ZFUYQsy0bFpaqqpsphQRCMHtt2u72tLUH0BfT0YFt/bvprMghtSGrxeDzQNM2yaGYkEoGqqm2phtZvfFSSyWTg8/nqzkFN0xAOhy3XURSlJ3pV1xOJRCxj1xdD7TWiKMLlcpluSKRSKXg8nln7OSgWi5icnDT12S/FftpERERERF3kdE63HKnVMpDhNlFfY7hNPaFYLFb8KH8ulzMqrPVKaLvdDrvd3tBH+tPpNOLxuCV40oPt8rYLLpfLqE4VBMEIshVFgSzLRjsRTdMwPj5uCdBGRkY6VjVdacz5fN4IHnu91UU76AFrecAdi8WQy+VmHO5Xq9oGpudoLpeztJspF41GLQsI2mw2hEKhng83E4mEpTWQzWbr6VDe7Xabvm+qqiKdTnd0wVFdrWCb/bSJiMjC6QQuvNC6j4iIOkcQpqu3JyaqHzNnzuyNh4jajuE29QSbzQZZlmt+rF/TNGSzWSM4FEXRCLoVRTH1sc5kMojH4xWvl8/nLSGxIAjweDwYGRkxAm2bzVY10IvFYpZAy+v1diTYVlUV4XAY2WwWNpvN9JyKxWJHA/VeVC3gzmQyGB8fRyAQqBtAV6KHorWk0+ma147H40ilUqZ9oigiFAr1fEV9JpOxfJKhH8Zus9mMhV91yWSy4+F2tWBbvxnAftpERGTh8bDHNhFRNwQCtcNtVm4T9TWG29QzRkdHkUwmkc1mkcvlLFXV5fQwUg8k9XA7l8sBQMVArlAoIBaLQZIk2Gw244/P57P0r64mm81aKnxlWe5I5XQ+nzf1bi69AaAoSscC9V5XLeDWA0e9kr2ZauN0Om254eF2u5FIJIx9mUzG1AqmVCqVsoxHEASEQqGmFxCdbfl8HuFw2LI/EAj0/NiB6ert0nC7UCggk8l0rGq6UChgcnLS0lPdZrNhZGSEPbWJiIiIiHrJ8uXA3/9e/esrVszeWIio7Xo/taChoVdP672Vc7mcEXTrgXU1+Xwe0WjUdJzNZjPaiciybITd5e0hnE4nAo2soIzpQD0SiVjG3Ym2DdlsFuFw2NSuRVEUpFIpY2G6YrFYNWwddHqwH4lELCFjPB432pQ0GjSWV1zrbSVKw21VVZHJZCw92bPZLKLRqOWa/bC4p/7JgPKbST6fr29aauhtiko/1ZBMJjsyfgbbRERERER95vTTgR//uPLXQiHgX/5ldsdDRG3Vu581p6GmL8zo8/kwOjqKefPmIRQKwe12mypJ9UrsSCRiCcALhQJSqRSSySTy+TwEQbC0GtEXYWw0HI5Go5ZQy+fztb26NZVKYWpqytKHXFEUBAIBoy+4fhNgWNntdoyOjlZsFZLNZjE+Pm6q6K0ml8tZWti43W5IkmS5dnnrEr26vjwc9vv9PR8O64tflrfWcDqdfdfDvbwNSTabrdnmqBX5fB4TExOW3wGyLGN0dJTBNhERERFRLzrpJOAzn7HudziAu+8G/vn+moj6Eyu3qS+IogiHw2GEhdlsFpOTk0ilUlUDLJvNBqfTCbvdDkEQLEGx3W5vquK6tAVK6TXa3ds3FouZqoV1iqIgGAwiHA6bAu1GFjkcZJIkYWRkBIlEAvF43BQyq6qKqakpeDweeL3eqt/r8qptm81mvKZOp9O0QGQ2m4WqqhBFEcVisWKw7fF4ZmVBw5mKxWKWxS/1Gyj9xul0IhaLmX7Ok8lk255LPp/H5OSk5feILMsYGRnp6b7kRERERERD7+qrgfe9D/jOd4BEAli0CFizBli4sNsjI6IZYrhNfaVYLCIejxshs8/nAzBdpa1X36qqagTh1cJMPShuNNguFouWthOiKLY1BNSraCtVGuutUwRBgKIolnCbpgNlRVEQDoctlbWJRMJoU1JeZV9pIUlXyZ17fR7pAbamaUY/50rtKZxOpzEve5n+qYZSkiR1pMXObNB7pJf2PU+n0/D5fDMOnnO5XNVPUvT6gptERERERARAEIB3vGP6DxENFIbb1BeKxSISiQRSqVTFhSb1/toejwculwuFQgHZbNZoTVB6jizLTQdSkUjEEmz5/f62tSEoFouWimydx+MxhaXlPZz1xTf7MZBsN0VRMDY2hkgkYrlJkMvlMDExAb/fb+qZXWkhydKvi6IIu91uul4qlUI6nba087Db7X1R9ZzL5Sw3a/Te8f3cWsPlciGRSJhuRCSTSWMB0lYw2CYioraJx4GLLzbvu/JKYAb/nyIiIiIadgy3qaepqopEIoFkMlkx1Aamw0e32w23220ETYqiQFEUeL1eqKpqLEqpH9tMEJxMJi2tG5xOp2VRwVbpPZvLK4AFQYDf7zdVEQPWcFvTNOTz+Z5fuHC2iKKIUCiEZDKJWCxmaVMSDoeRzWbh9/shCIKletnhcFgCXqfTaQq3JyYm4PF4TMGmzWbri6rnaq1U/H5/388hSZLgdDpNbWZSqRQ8Hk9L35dsNlvxtbLb7ZaFaYmIiOrKZIAbbjDvW7uW4TYRERHRDDDcpp6kqiqSySSSyaSlYlKntyEoDxnLlffrboa+YGUpSZLg9/ubvlYl2WwW4XDY8hxFUUQwGKzYS1sURciybOo1nsvl+j6YbDe32220KSmvsNZ7tbvdbsvXym8mANOBtyiKxrzMZrOQZdm4waH3/e71Kl5N0ypWIeufeBgEbrfbFG4Xi0VkMpmmb0Yx2CYiIiIiIiLqfb2dxNDQ0TQNiUQCu3fvRjwerxhs66H2nDlz2tJPt9ZYwuGwJdwKBAJtecxkMlkxaLTZbBgdHa25SGR5kF1eWU7TZFnG6OhoxeA2n8/j1VdfNVVkly4kWUoQBDgcDqTTaSM41c8TBAGhUKgv2nlEIhHLAqx2u31GbTt6jSzLlp+PSgu01pLJZCoG2w6Hg8E2ERERERERUQ9h5Tb1jGw2i0gkYmnPodN7IXu93lkJEhOJhCUIdLvdNUPnRmiahng8XjFwa7SPr6IopnYa7Ltdnb7wp6IoiEajpn7M2WwWmUwGuVyubvWyIAim71mhUECxWMScOXMgy3LHn8dMJRIJy8KZ/dJKpVkejwdTU1PGdj6fb/jTDZlMpuJNLYfDMZCvFRERzSKHAzjvPOs+IiIiImoZw23qCXq7hGp9tfVQ22abnSmby+UQj8dN+2w2m2lhx1bo1eDlix0C088xEAg0FJ6x73bzXC6X0aYkn88jk8kY8y2bzaJYLGJsbKziublcDslkEpIkmW6+KIoy45sdsyGTyVja6+i9yXu9lUor7Ha75XuVTCbr/nyk02lEIhHL76FmfjaJiIiq8nqB66/v9iiIiIiIBsrgpRrUl4rFYsVg2+FwYGxsDMFgcNaCbU3TEIlETPsEQZhx1WaxWMTExETFYNvj8TR1fUmSLK9HLpdreWzDQm/54na7Ld8Hm82GqakpywKThULBqAIuDbL7pUd1Pp9HOBy27A8EArP2MzXb9NZFpdLpdNVPhehfr1Sx7XK5GGwTERERERER9SiG29QTbDabacFHu92O0dFRhEKhWW/5EI1GLYsMer3eGY0jn89jYmLC0uZEEAQEAoGWKsLLq1AZbjdG75/tcrlMVcsOhwOapiEajRq90FVVNfVF18Nth8MBt9uNYrHY06+7qqoVA1ufz9fSAqv9pPz7C8By40KXSqUq3gBgsE1ERERERETU2wazbI/6UigUQi6XgyiKXasozWQyxoKBOkVRLFWgzV6zUsAoiiKCwWDLbS3sdrtprL0csvaaVCoFu90Om82GeDwOTdNMNy8ymQzGx8chiqLpRofNZoPT6TTNh3Q63ZPtYPQWOOU3apxOJzweT5dGNXtEUYTT6TQF2qlUCh6PxxR6J5NJRKNRy/lutxt+v39WxkpERERERERErWHlNvUURVG6FmyrqlqxHclMKjeTyWTFXuJ6e4yZ9GsuD1RVVbVUhpNVsVg0WpJIkgS/34+RkZGKx5W/nrIsY+7cuab5kE6nq/aK76ZYLIZsNmvaJ8syAoFAdwbUBeU3pVRVNS2qWS3Y9ng8DLaJiIiIiIiI+gDDbaJ/ikQiRvsJnd/vbyls19tbVArOFEXB6OjojEN89t1uTXkYLYoi5syZg5GRkZqLK0qShFAoVDEwLQ+Ruy2VSllacOjjH6YWG+XtjoDXW5MkEomqwfZMF44lIiIiIiIiotnBtiREmA4DyxcY1PsyN0tvB1Fp4Uin09nWHr6KopjaTuRyuRm1UBkG5aGv0+mEKIqw2+0YGxtDJBKxhNWiKCIUCkGSJADTr3vpjYR0Ot0zPaxzuZwltNUXRNXHP0zKFw/VFwit9PPp9Xrh9Xpnc3hERDRMEgngi18077v0UmAI2oURERERdQrDbRp6hULBEgaKothSW4JisYipqamK7UE6EZwpimLqu91rFcS9JpvNolgsmvaV3sDQq5sTiQTi8TiA14Ph0p7cTqfTFG5nMhlomtb1qmhN0xCJRCxtUvx+f0/2BZ8NdrsdsiybfiYrBds+n28oepETEVEXpdPANdeY9332swy3iYiIiGaA4TYNtWphYCAQaLrKNZ/PY2pqyhKeCoIAv9/fUhV4PZX6bhcKha71Le915VXbsixbXkNBEOD1eo0A2263W+aCw+FALBYz5o2machkMnA6nZ19AnWkUinLApIej6cjc6+fuN1uSz/9Un6/n594ICIiIiIiIupD7LlNQy2ZTFr6VLtcrqZbTGQyGUxMTFiCbb2dRafCRZvNZglee6nvtqqqyGQyltelG4rFoqWyvdb3xWazweVyVbzJIUmSJRQvXaiwG1RVNarNdYqisM0GXm89UwmDbSIiIiIiIqL+xfJOGlr5fN4SBtpstoYXk9M0Del0Gul0umI7EJvNhlAo1PEqakVRTMFqNpvtiUrdQqGAiYkJqKoKQRAQCoVgt9u7Np5UKmWq0BcEYUaV1k6n0/R9z2azUFW15qKUnZRMJi0Lovp8vq63SukFgiDA7XZbft4DgUBP/KwQEdGQsNuBs8+27iMiIiKiljHcpqFUqx1JvXAyl8sZC1CWh4k6RVEQCoVmJegsD7d7pXI7kUgYr4/+eo+OjnZlUUNN00y9yYHa1byNcDgcEATB1JoknU53pQq4WCwikUhYxjesfbYr0ReWzOfzEAQBgUCg621kiIhoyPh8wC23dHsURERERAOF4TYNpXg8bln00ePxVA0Di8Ui0ul0xZ7G5ZxOJwKBwKxVzJZXQxeLxa733VZV1dKmo1gsIhKJIBQKzXo1caWFJGcaQouiCIfDYXqe3Qq34/G45UZNo59AGBaiKGJ0dBT5fB42m61rFfZERERERERE1D4Mt2noZLNZS5WrLMuW3sSapiGbzSKVSiGbzVrCw3KiKMLj8cAzyyve60FdaRV5LpfraridyWQqvl7ZbBbxeHzWg9fyqm1ZliHL8oyv63Q6LVXzs31joVAoWG4kuFwuLipagSAIrGYnIiIiIiIiGiBMP2ioqKqKSCRi2qe3KNCrifP5vFGlXa3tSCm73W4sQtmt/sZ2u90Ssnazl3B5mFwqkUhAUZSmF+1sVbFYRCaTMe1rV3W13W633FjIZDKzeoMjFotZeolzEUkiIiIiIiIiGgYMt2moxGIxS3sKr9cLSZKQTCaRSqUs7UoqsdlscLlccDqdXekhXa6X+m4XCoW6jx+JRDA2NjYrr1150C6KYtt6LeuLUiaTSdPjzVa4ncvlKgb3vTAniYiIiIiIiIg6jeE2DQ29GruUIAjI5/PYtWtX3bYjepDpcrl6rrVB+XgKhQKKxWJXQs7y11iSJLjdbsRiMWOfqqoIh8MYGRnpaLV7tYUk2/mY5eF2oVBAPp9vS9uTekpfU+D11jhERERERERERMOA4TYNhWKxiGg0avw9k8kgl8vB7/db+hWXUxTFaDvSq4vQVeu73a4K5UZVC5M9Ho/R7qV0fLFYDH6/v2PjqbSQZLvbtSiKAkmSTI+TTqc7Hm7rc7iU1+vt2TlKREQ09JJJ4OqrzfsuugjowmLURERERIOC4TYNPFVVMTU1hVQqhUwmY7Qd8fl8VYNASZKMKu1+WJhPXyivtEVFN8LtbDZr6VOuh8l+vx/5fB6FQsH4WjKZhKIoHRtnaUU1MB1EdyJ0djqdpkVK0+l0RxfN1DTNUrWtt8ohIiKiHpVKAV/8onnfmjUMt4mIiIhmoPdTO6IZKBQKGB8fRzgcNvXSdjgcsNvtpmMFQYDD4YDT6YTdbu/a4pCtKg+3s9nsrI+hvGpbURTj5oAoiggGg5iYmDC1gIlGo5Blue03EQqFguU16FT4Wx5uF4tFZLNZyxxrl1QqZbpJAExXbffbnCUiIiIiIiIimgmG2zSwstksdu/ejUgkYqomliTJ1JdYlmVjcch+bulQqe+2qqqz9pz0QLdUeZgsyzL8fj8ikYixT++/PTo62tZwtpMLSZaTZRmyLJtuoKTT6Y6E25qmmYJ0/fFnu0qfiIiIiIiIiKjbGG7TQEomk9i9ezfi8bipSliSJPh8PlPbkdlY+G82yLIMQRBMzzebzc5a6JlOp02PrVfCl3O5XMjlcqbwOZ/PIxqNIhAItGUss7GQZDmn02kKtzOZDDRNa/tjJhIJSx/xTrZAISIiojZRFODUU637iIiIiKhlDLdpoOi9iHfv3m0JN202G0KhEAKBABwOx8C1cND7bpdWT89m3+1KYXK1qnG/349cLmdqrZFKpYzFO2cqk8lYen+7O9zP0ul0mvpgq6qKbDZbMeBvlaqqlqrtSi12iIiIqAf5/cDtt3d7FEREREQDpX97MBCVUVUVExMT2LFjhyVodTgcmDt3LubOndvxCt5uKm9NksvlZuVxy4NqoHZ/a0EQEAqFLN+HaDRqqn5uVfn33263d3xhUEmSLK9/Op1u62OUfxIBmO61TUREREREREQ0jBhu00AoFArYtWsXdu/ebQl03W435s2bh5GRkb7uqd2I8grefD5vqWDuhEpV8uVBbzmbzWZpQ6JpGsLhsCXAbcZsLiRZrrxKvlIFeasKhYLldR6ktjpERERERERERM0a7KSPhkI2m8WOHTswMTFhqh4WBAE+nw977LEH/H7/wFZrl9L7bpfqdPW2pmmWCuVGw2Sn02lpF1IoFEwLTjar0kKS7WwNUkv5pwI0TUMmk2nLtcurtgVBYNU2EREREREREQ01htvU15LJJLZt24ZIJGKqkJUkCcFgEPPnz+94r+VeovfdLtXpcLt8IUnAWsFci8/ns1Qfp9NpJJPJpsdSaSFJl8s1azc2RFG0VM+3ozVJLpezXMftdkOSpBlfm4iIiIiIiIioXzHcpr6kt6/Yvn07EomEKVy12WwYHR3FHnvsMZQL7c12uF2pv3kzoasgCAgGg5aWMbFYrOn+25XagMxWSxJdebCfzWZRLBZndM3ShSqB6RDd4/HM6JpERERERERERP2usyusEXWAqqqYnJzE+Pi4Jfx0OBwYHR2tGJYOi/JwW++73YnXo1AoWMLzVsJkvf/21NSUsU+/gTE6Otrw2MurvWdjIclyDocDgiCYbrhkMpmWP0GQyWQsr7HH4xna+U1ERNS3Uing+uvN+9asAWb5RjwRERHRIGG4TX2lUChg9+7dmJqaslTDut1uzJ07d+j7ECuKYgpXNU1DPp/vSBV7pf7WrT6Ow+GAx+NBIpEw9un9t0OhUN3z8/l8W4L2mRIEAU6n0/TapFKplsJtTdMQj8dN+yRJGqpWO0RERAMjmQQ++1nzvtWrGW4TERERzQBL/6hvZLNZbN++HRMTE6ZgWxAE+P1+LFiwYOiDbWD69SjvYd2J1iTVFpKcSX9rr9drqTzPZDKmwLua8qBdkqRZW0iyXHlrknw+b1rstFHpdNry6QSfzzcUi6MSEREREREREdUzkJXb+Xwezz//PLZs2YJoNIpsNguPx4OxsTEccMABWLBgwYwf45VXXsHmzZuxc+dOqKqKuXPnYtGiRVi8eHEbngGVSyaTeO211yxtJ/SFI+fMmWMJdIeZoiimQDubzbY9+K/US7qZhSQr0ftvj4+Pm3pnx+NxKIpiCb51lYJ2p9PZtRBYURSIomh6Dul0uqnvQaWqbVmWZ/waExERERERERENioEKt3ft2oV169bhrrvusizAVmrRokVYtWoVTj/99KYWvgOA9evX48Ybb8QTTzxR8etLlizBueeei/e+971NXZcq0zQNkUgEu3btQjabNX1NlmWMjIxgdHS06e/joKvUd1vTtLaGveWV0oqitOUGg37DYnJy0tin998eGxur2Gs6nU5bFpLsZusOvTVJ6c2YZsPtZDJpuXng8/naNkYiIiKaZYoCHH+8dR8RERERtUzQSlc962P3338/LrnkEkSj0YbPOeigg3D99ddjzpw5dY/VNA2XX345vv/97zd07RNOOAFXXnll1UrTRixcuBDbt2/HggULsG3btpav069UVcXExATGx8ctLR0cDgfmzJmDQCDAFg0VqKqKnTt3mvaNjIy0re+2qqrYtWuXadFEv9/f1kA5Ho9bKpftdjtGRkYsx05MTJgq1R0OR0N9ujspl8thYmLCtG90dLSh3wmqqmL37t2mwL7acyciIiIiIiIiGlYDUbn94IMP4pOf/KSpN63NZsPhhx+OxYsXw+l0IhwO44knnsCzzz5rHLNp0yacffbZuP322+HxeGo+xrXXXmsJtg899FAceOCBkCQJW7ZswcMPP2yEfb/+9a8hSRKuvvrqNj7T4ZHP542FIytV5M6bN6/u92yYiaIIWZZNPxO5XK5t4XYqlTIF23qlcjt5PB7kcjlTxX42m0U8HjdVQPfKQpLlFEWBzWYz3ZhJp9MNhdvxeNwy71m1TURERERERERk1vfhdiaTwRe+8AVTiLdixQpcddVVmD9/vuX4Rx55BBdddBHGx8cBAC+++CKuu+46XHLJJVUf449//CPWrVtnbPt8Plx33XU44ogjTMdt3rwZH//4x42K2bvvvhuHHXYYzjjjjBk9x2GTyWSwc+dOxGIxS4Dq8/kwb968ri0U2E/sdrsl3G6X8pYkTqezYruQmRAEAYFAwLKAqN5/Ww/qKy0k2a4Qf6acTqep+jyTydRdELJQKFR8fdlTnoiIiIiIiIjIrL1pVBf84Q9/wI4dO4ztvffeGzfddFPFYBsAjjjiCHz729+GzfZ6rv+zn/2savCnaRq+9rWvGduCIOCGG26wBNsAsHTpUtxyyy2mYO2b3/wmMplM089rWMXjcbzyyiuIRqOmYFuSJIyMjGDhwoUMthtUXiGcy+XQji5EuVzO0iamU4scSpKEQCBg2R+JRFAsFqGqqiUIdrlcPdOqpvx1KRaLdW8yxOPxijd1iIiIiIiIiIjIrO/D7UceecS0vXr16rotCfbbbz+sXLnS2E4mk3jqqacqHnv//ffj+eefN7bf9773YcWKFVWv/cY3vhHnnHOOsT0+Po7bb7+95nhoWiQSwbZt25BOp037ZVnG3Llzsccee5huSlBt5eG2pmmmSu5WlYfJNputo5XSdrvdEu4Wi0VEIhGk02lLYN8LLUl0NpvNUnFdPr9L5fN5y9fdbjcXTCUiIiIiIiIiqqDvw+1du3aZtpctW9bQeYceeqhpe/fu3RWPu/fee03bZ511Vt1rn3HGGaYwqvwaZFUsFrFjxw5LVavD4cD8+fMxOjra9rYXg07vu11qpq1JNE2zfBKhU1XbpTwej6ViP5vNIhaLmfY5HI6eC4LLX59MJlO1gr78+YiiyN7yRERERERERERV9H0ZbPmia422rCgPnCq1MSgUCnjggQeM7T322AMHHXRQ3WvPnTsXy5Ytw9/+9jcAwBNPPIGpqSmEQqGGxjaMisWiparY7XZj/vz5PVWJ228URWlr3+10Om35mZut708gEMD4+Lip/3YvV23rnE6nKbRWVRWZTMbyOyibzZoWzwSmQ33e1CEiIhoQ6TTw3e+a933oQ8AsFAoQERERDaq+T00WLlxo2n7ttdcaOm/79u2m7Te84Q2WY55//nlTKHXIIYc0PK7SY4vFIh5//PGGzx1GNpsNPp8PoijCZrMhGAxir7326smwsp+0u+92ecsMu90+a5XSoigiGAxW7afdSwtJlqo0rvLXUdM0S9W2JElwu90dHx8RERHNkkQCOP98859EotujIiIiIuprfR9uv+Md7zBt/+Y3v6l7TrFYxH333WdsL1iwAEuWLLEct3XrVtP2/vvv3/C4li5datp+8cUXGz53GImiiAULFmDhwoVYuHAhFixYYAlmqXnlr6GqqpbFIBtVKBQslcWzffNBUZSqiyv20kKS5SpVaZdWwKfTacsnF7xeb88+HyIiIiIiIiKiXtD34fbRRx9tCqbvuOMO/PGPf6x6vKZpuOqqq/DSSy8Z+9asWVPxo//lgfT8+fMbHtcee+xR81pkpSgKgsEg/H5/z/VN7leSJFkW4SwPqBtVXm0simLDbYDaye12V2wr1MtV/g6HwxRUl/Yu1zQN8XjcdLwsy7PSy5yIiIiIiIiIqJ/1fc9tSZLw9a9/HatWrUIkEkGxWMR5552H008/HSeddBIWL14Mp9OJcDiMjRs34pZbbsFf//pX4/wzzjgDp5xySsVrly9WOW/evIbHVX7szp07m3hWRO2jKIqpWruVvtuapiGVSpn2OZ3OrlUW+/1+FAoFo9rZ7Xb39A0R/UZA6Q2CdDoNl8uFZDJp6iMOsGqbiIhoIMkycNRR1n1ERERE1LK+D7cB4E1vehNuv/12fP7zn8eGDRugqipuu+023HbbbVXPGR0dxQUXXIDTTz+96jHlYV4z/W/Ljy2/FtFsURTFNP9aCbdzuZwlgO1mpbQoihgZGUEmk4Eoij3Za7uc0+k0hdvZbBb5fB6Jsl6bdru9KxXxRERE1GGBAPCnP3V7FEREREQDpe/bkuj22msv/OAHP8AVV1wBv99f89ilS5fihhtuqBlsA9ZAupke0OVhG8Nt6pbyuaiqqqW/cz3l81eWZchdrjQSRREul8vS8qNX2e12S/ujqakpU+9tYLpqm4iIiIiIiIiI6huYcHvr1q340Ic+hM997nOIRqM1j928eTP+7d/+DR/5yEdqtgsp703cTLhdfqzeX5dotkmSZGnZ0Uz1tqqqlvnby/2te5UgCJaK7PJqeKfTyYVUiYiIiIiIiIgaNBDh9kMPPYRTTjkFDz30EIDpqtJVq1bhRz/6ER599FE8/fTTePDBB3HDDTfgne98p3He+vXr8f73vx9bt26teN3yitdmAsHyY9lmgLppJnM5nU5D0zRjWxAELnbYolqvmyAIrNomIiIiIiIiImpC34fbr7zyCs4//3yjl63P58OPfvQjXHrppVi+fDl8Ph9kWcbY2BhWrlyJdevWYe3atcb5U1NT+PjHP27qhasrr05tJhAsr/pmpSt1U3k1cDNzubwlicPhsLTXoMYoilJ14UuXywWbbSCWQSAiIiIiIiIimhV9n1Bdc801pvDtsssuw8EHH1zznDPPPBNnnnmmsf3yyy/j1ltvtRxXHkgnk8mGx1V+LMNt6qbycLtYLKJQKNQ9L5/PW/pzcy63rlrVuyiKrNomIiIiIiIiImpSX4fb8Xgc999/v7G911574d3vfndD537kIx8xbd91112WY+bOnWvartWfu9xrr71m2p43b17D5xK1m81ma6nvdnnVtiRJlhYn1JxK4bbb7WY1PBER0aDLZIBbbjH/4bo8RERERDPS15+Bf+qpp0wLsq1YsQKCIDR07vz587Fw4UJs27YNAPDCCy8gm82agrs3velNpnN27NjR8NjKg/B99tmn4XOJOkFRFFP7nVwuV7MKW9M0S7seVm3PnCzLsNvtRusim80Gj8fT5VERERFRx8XjwH/8h3nfCScAXJuHiIiIqGV9XSo4OTlp2h4bG2vq/NLjVVVFJBIxfb083N68eXPD137mmWdM2wy3qdvKW5OU94Uvl8lkoKqqaR/D7fYIBALweDzweDwYGRlp+KYcERERERERERG9rq/D7fL2CJkmP9ZXryp10aJF8Pl8xvbGjRsbvvYTTzxh/F2SJBx66KFNjY2o3Sr13S795EO58pYkdru96mKI1BxJkuDz+eDz+fiaEhERERERERG1qK/D7VAoZNreunVrw+fm83m88sorxraiKJYF3Ww2G975znca26+99hqefPLJutfetWuX6bhDDjnEMlai2SbLsqWvc7Xq7WKxaPkaq7aJiIiIZsBmA5YvN/+x9XWXSCIiIqKu6+twe+nSpZBl2djesGEDxsfHGzr397//vakyddmyZRWPe8973mPavvXWW+te+8c//rGpIrbRRS6JOq28ervaopLlVduiKMLBfpBERERErQsGgUcfNf8JBrs9KiIiIqK+1tfhtsvlwlvf+lZjO5vN4stf/nLd88LhMK666irTvmOPPbbisStXrsTixYuN7bvuuguPPvpo1Wv/4x//wHe+8x1je2xsDKeddlrdMRHNhvJWPo2G206nk32hiYiIiIiIiIiop/R1uA0Aa9asMW3fe++9uOCCC6pWcG/atAmrVq3C9u3bjX2jo6M4/fTTKx4vCAI+/elPG9uapuG8887DI488Yjl28+bNWL16tamdw/nnn8+KV+oZ5ZXbhULB0nc7m81a9rElCRERERERERER9RpB0zSt24OYqa9//ev41re+ZdqnKAre8pa3YPHixXC5XIhEIti4cSOefvpp03GyLGPdunU44ogjaj7GNddcg3Xr1pn2HXrooTjooIMgiiK2bNmChx9+GKUv53vf+15cffXVLT+vhQsXYvv27ViwYAG2bdvW8nWIdJqmYdeuXVBV1dgXDAbhdDqN7XA4bFpsVZZljI2Nzeo4iYiIiIiIiIiI6hmIcBsAvvnNb+KGG26wVJzWEgqFcOWVV+Koo46qe6yqqrj88svxgx/8oKFrH3/88bjyyistbSCawXCbOmFqagqZTMbYdrvd8Pv9AKbn+a5du0w3afx+P9xu96yPk4iIiIiIiIiIqJaBCbeB6bYgN998M+677z5Ta5ByIyMjOPXUU3H22WdjZGSkqcdYv349brjhBmzcuLHi1xcvXoxzzz0X73vf+5q6biUMt6kTEokEYrGYsV1amZ1MJhGNRo2vCYKAuXPnQhT7voMRERERERERERENmIEKt3W5XA6bN2/G1q1bEYvFkMlk4Ha7EQwGsXTpUuyzzz4zXhzv5ZdfxjPPPIPdu3ejWCxi7ty5WLRoEZYsWdKmZ8Fwmzojl8thYmLCtG/evHkQRRHj4+PI5/PGfqfTiWAwONtDJCIiIho82Sxw993mfe99LzCDT3oSERERDbuBDLcHBcNt6gRN07Bz505T65FQKARJkiwLsY6MjMyotQ4RERER/dP4ODBnjnnf7t0A1zYhIiIiapmt2wMgotklCAIURTG17qnUxkeSJCiKMptDIyIiIiIiIiIiahgb6RINofLQOpfLIZ1Om/a5XK4Zt+8hIiIiIiIiIiLqFFZuEw2h8nC7tM+2zul0ztZwiIiIiAafJAFLl1r3EREREVHLGG4TDSFFUSAIAqq13Lfb7bDZ+OuBiIiIqG1CIeCZZ7o9CiIiIqKBwrYkRENIEATIslz16y6XaxZHQ0RERERERERE1DyG20RDym63V9wviiIcDscsj4aIiIiIiIiIiKg5DLeJhlR5322d0+nkQpJERERERERERNTzGG4TDSm973Y5LiRJRERERERERET9gOE20ZCq1HdbluWqFd1ERERERERERES9xNbtARBR9zgcDuRyOWObC0kSERERdUg2C9x/v3nfu94FVFkHhYiIiIjqY7hNNMTcbjcKhQKy2SwcDgfcbne3h0REREQ0mGIx4MQTzft27wbGxrozHiIiIqIBwHCbaIgJgoBAINDtYRARERERERERETWNPbeJiIiIiIiIiIiIqO+wcpuIiIiIiKjTRBF4wxus+4iIiIioZQy3iYiIiIiIOm1kBHjppW6PgoiIiGigsFSAiIiIiIiIiIiIiPoOw20iIiIiIiIiIiIi6jsMt4mIiIiIiIiIiIio7zDcJiIiIiIiIiIiIqK+w3CbiIiIiIiIiIiIiPqOrdsDICIiIiIiGni5HPDww+Z9Rx4JKEp3xkNEREQ0ABhuExERERERdVo0ChxzjHnf7t3A2Fh3xkNEREQ0ANiWhIiIiIiIiIiIiIj6DsNtIiIiIiIiIiIiIuo7bEtCRERERETUaYIAjI5a9xERERFRyxhuExERERERddroKDA+3u1REBEREQ0UtiUhIiIiIiIiIiIior7DcJuIiIiIiIiIiIiI+g7DbSIiIiIiIiIiIiLqOwy3iYiIiIiIiIiIiKjvMNwmIiIiIiIiIiIior5j6/YAiIiIiIiIBl4+D2zcaN63bBkgy90YDREREdFAYLhNRERERETUaZEI8Ja3mPft3g2MjXVlOERERESDgG1JiIiIiIiIiIiIiKjvMNwmIiIiIiIiIiIior7DtiRERERERESzweXq9giIiIiIBgrDbSIiIiIiok4bGwOSyW6PgoiIiGigsC0JEREREREREREREfUdhttERERERERERERE1HcYbhMRERERERERERFR32G4TURERERERERERER9h+E2EREREREREREREfUdW7cHQERERERENPAKBWDLFvO+JUsAG9+SEREREbWK/5IiIiIiIiLqtHAYOOAA877du4Gxse6Mh4iIiGgAsC0JEREREREREREREfUdhttERERERERERERE1HcETdO0bg+CKlMUBfl8HqIoYo899uj2cIiIiIiIqFWqCrz2mnnfHnsAIuuNiIiIaLjMmzcPjz32WFuuxZ7bPaxYLAIAVFXF9u3buzwaIiIiIiJqq/Kwm4iIiIiawnC7hzkcDmQyGUiShDlz5nR7OEREREREREREREQzMm/evLZdi21JiIiIiIiIiIiIiKjvsMEbEREREREREREREfUdhttERERERERERERE1HcYbhMRERERERERERFR32G4TURERERERERERER9h+E2EREREREREREREfUdhttERERERERERERE1HcYbhMRERERERERERFR37F1ewBEgy4SieD555/Hyy+/jEgkAk3T4Pf7MX/+fCxbtgxer7ctj/PKK69g8+bN2LlzJ1RVxdy5c7Fo0SIsXry4LdefDblcDn/729+wfft2TE1NIRAIYN68eVi+fDlcLle3h0d1cK7Xl8lk8MILL2Dr1q0Ih8PIZDLw+XwYHR3FwQcfjHnz5nV7iNQAznUaJpzvzYvH49i4cSNefvllxONxSJKEYDCIPffcE/vvvz/8fn+3h0gVcK437qWXXsLmzZsxMTGBZDIJp9OJQCCA/fffH/vuuy8kSer2EKmGfp/rxWIRL730El544QXs3r0byWQSLpcLgUAAS5cuxb777gtBENryHPj+tP9xvtc3CO9RGW4TtZmqqnjsscfwu9/9Dn/5y1/w/PPPVz1WEAQcccQRWL16NY466qiWHm/9+vW48cYb8cQTT1T8+pIlS3Duuefive99b0vXf/nll/HUU09h06ZN2LRpE5599llkMhnj61dccQVOPvnklq6tSyQS+MY3voG7774b0WjU8nWXy4XjjjsOn/nMZzA2Njajx6L24VxvzNatW3HvvffioYcewqZNm5DP56seu+++++IDH/gATj31VMiy3NLzoPbjXG+f3/3udzj//PNN+xYsWIA//OEPHXk8ah7ne+see+wxrFu3Dn/+859RLBYrHiMIAhYtWoRTTjkFq1evbsvjUms415uTy+Xw/e9/H7fddhu2bdtW9biRkRGceuqpOPfcc+Hz+Vp+PGqfQZjrExMT+O1vf4sHHngAjz76KBKJRNVjQ6EQ/u3f/g1nn302QqFQ0+MH+P60n3G+N2bQ3qMKmqZp3R4E0SD513/9V7z88stNn3fCCSfgsssug8fjaeh4TdNw+eWX4/vf/37D17/yyiuhKErdY3fu3InPf/7zePrppxGJRGoeO9N/KD/zzDP4z//8T2zfvr3usaFQCNdeey2OPPLIlh+P2odzvb4vfOEL+OlPf9rUOQCwdOlSXHvttdhnn32aPpfaj3O9PeLxOI4//njs3r3btJ/hdm/hfG9eOp3GZZddhjvvvLPhcw4++OCW/v9A7cO53rgXX3wR559/PrZu3drwOXPmzMHXv/51LF++vKXHpPbp97n+i1/8ApdccknVm4bVjIyM4PLLL8fRRx/d1Hl8f9rfON+PrnvsIL5HZeU2UZtNTU1Z9u2999446KCDMDo6Crvdjp07d+KRRx7Bzp07jWN+/etfY/fu3fjOd74Du91e93GuvfZayy/SQw89FAceeCAkScKWLVvw8MMPQ79/9etf/xqSJOHqq6+ue+1wOIwHH3yw7nEztWPHDnzkIx/BxMSEsc/v9+OYY47BvHnzMD4+jgceeADj4+MApl/bNWvW4LbbbsN+++3X8fFRbZzr9U1OTlr2jYyM4LDDDsPcuXPh8/kQDofx+OOP47nnnjOO2bx5Mz74wQ/i1ltvxV577dWx8VFjONfb4+qrr7YE29R7ON+bk0gkcO6551oqtvbaay8sX77cqOibmJjAs88+i+eeew6qqs7K2Kg2zvXG7Ny5E2effbbl9/eb3/xmHHLIIQgEAkgmk3juueewYcMGI5DZvXs3PvzhD+OHP/wh3vzmN3d0jFRbv8/1SCRiCfpcLhcOOeQQ7LXXXggGg0in03j22Wfx6KOPGsdOTk5izZo1uO6667By5cq64wf4/nQQcL7Xn++D+B6V4TZRhyxYsACnnXYa3v/+91fsUVQsFvHTn/4UV1xxBbLZLADg0UcfxTe+8Q3813/9V81r//GPf8S6deuMbZ/Ph+uuuw5HHHGE6bjNmzfj4x//uPFL++6778Zhhx2GM844o6XntNdee8Hj8WDz5s0tnV9K0zRccMEFpn84nHjiibjsssvgdruNfblcDtdeey1uueUWAEAqlcJ5552H3/zmNw39T4c6j3O9Pq/Xi/e+97047bTTsP/++1c85i9/+QsuvvhivPbaawCA8fFxfPrTn8btt9/etr6BNDOc66179NFHjQqRsbEx400h9S7O9/o0TcMnP/lJU7C9ePFiXHrppVWrVXfv3o177rkHmzZtassYaOY412u74oorTMH2vHnzcO2111ac46+++iouuugi42cilUrhC1/4Au644w7+W6YH9Ptct9lsOOaYY3D66afj8MMPr9ge4dVXX8Ull1yCDRs2AAAKhQIuvPBC3HfffZgzZ07N6/P96WDhfK8934EBe4+qEVFb/b//9/+0n/3sZ1qhUGjo+D/96U/afvvtpy1evFhbvHix9uY3v1nbuXNn1eNVVdVOPPFE4/glS5ZoGzZsqHr8iy++qB144IHG8W9729u0dDpdc0zPPvus9o53vEM777zztBtvvFF78MEHtUgkommapt1xxx3GtRYvXqzdcccdDT3Pcvfcc4/pOqtXr9ZUVa16/MUXX2w6/uabb27pcal9ONfru/DCC7Wvf/3rWjweb+j47du3a0ceeaTpce+5556mH5fai3N9ZrLZrHbccccZ1//1r39terxjjjmmrY9HM8P53rif/OQnpmt98IMf1LLZbMvXo9nFuV7f7t27tSVLlpie8/PPP1/znHg8rq1cudL02I8//njTj03t0+9z/fvf/7726U9/WnvllVcaGn82m9XOOuss0xxcu3Zt3fP4/nQwcL7Xn++D+B5V7Ha4TjRo7rzzTpxyyikNrxJ+1FFH4YQTTjC28/k8fv/731c9/v777zctivC+970PK1asqHr8G9/4RpxzzjnG9vj4OG6//faaY9pvv/3wwAMP4Prrr8fHPvYxvO1tb4Pf72/k6TTsxhtvNP4uiiLWrl1b887fxRdfbOp/tW7dOhQKhbaOiZrDuV7fFVdcgU9+8pMN926bP38+PvnJT5r23XfffW0bD7WGc31mrr/+evzjH/8AALzjHe/A8ccfPyuPS63hfG/M1NQUrrnmGmN73rx5uP766xvqk0y9gXO9vr/85S/GR+oB4F/+5V+waNGimud4PB78x3/8h+U61D39PtfPPPNMXHvttdhzzz0bGr+iKPjSl75kem/529/+1jSXK+H708HA+V5/vg/ie1SG20RtZrM13+2n9JcpADz11FNVj7333ntN22eddVbd659xxhmmX+7l15htL730ErZs2WJsv/3tb8cb3vCGmuf4/X7T6zQxMYFHH320Y2Ok+jjX62vlNXr3u98NUXz9f8/86Hr3ca63bsuWLfjOd74DAHA4HLj00ku7PCKqh/O9MT/+8Y8RjUaN7c985jMNv0mk3sC5Xt+uXbtM2wcffHBD5x1yyCGmba630F39PtdbGf8b3/hGLF261NiemJjAjh07qh7P96eDg/O9/nwfxPeoDLeJekB5M/7SPl+lCoUCHnjgAWN7jz32wEEHHVT3+nPnzsWyZcuM7SeeeKLiQguzpfxO6HHHHdfQee95z3tqXod637DN9VZ4vV6EQiFju9KCH9T7ONcBVVXxhS98Afl8HgCwZs2ahqtQqL8M23zXNA133HGHsR0KhfiJhCExbHO9fPFTp9PZ0Hnlx/VUX1ZqyCDM9fJwuta/qfn+dLgN23xvRa+/R2W4TdQDksmkabvanbTnn38esVjM2C6viqil9NhisYjHH3+8yVG2z2OPPWbabvR5HHTQQaY7nuXXod43bHO9ValUyvh7K3fWqfs414Ef/OAHePLJJwEAixYtsnxMnQbHsM33jRs3Ytu2bcb2cccdx9/VQ2LY5vrChQtN27UqAUtt377dtF0eHFHvG4S53uhzAPj+dNgN23xvVS+/R2W4TdQDSj8CBaDiar4AsHXrVtN2tRVtKyn9mAoAvPjiiw2f226lj+1wOLDPPvs0dJ7b7Tb94/gf//hH3d5p1FuGba634pVXXjH9w6Haa0S9bdjn+o4dO/CNb3wDwHTF3tq1ayuu8k6DYdjmu37TRrd8+fIujYRm27DN9cMPP9z0u/u3v/2tpZq7knvuucf4uyAIOProozsxPOqgfp/rmqbhhRdeMO2r9W9qvj8dbsM231vR6+9RGW4T9YC7777btH344YdXPK78F+D8+fMbfow99tij5rVmSz6fN1U7zZs3r6mPKpY+50wmY6kMod42THO9VY2+RtTbhn2ur1271vgH8Kmnnsrwb8AN23wv78V54IEHAgAikQh++MMf4t///d9x9NFHY9myZXjnO9+J008/HV//+tctb56p/wzbXA+FQvi3f/s301i+9rWv1Tznt7/9LX7+858b2+973/uw9957d2qI1CH9PtcfffRR0ycNFi9ebGqpUIrvT2mY5nurev09am/VkRMNoQ0bNmDDhg3Gttfrxdvf/vaKx5Yv6tLM3bLyY3fu3NnEKNtnYmLCtIp0+S/5eubOnWva3rlzp+Ujk9Sbhm2utyISieAHP/iBaV95Lz/qfcM+13/5y19i/fr1AKaDkQsvvLDLI6JOGsb5Xlq5JQgCFixYgPvuuw+XXnopwuGw6dh0Oo1du3Zh48aN+L//+z+ccMIJWLt2Lbxe72wPm2ZoGOc6ML1Y6qZNm4ybOuvWrcOzzz6LD37wgzj44IPh9/uRSqXw3HPP4c4778Qdd9xhVK4eeOCB+MIXvtDN4VMLBmGuf/Ob3zRtv/vd7656LN+fDrdhm++t6If3qAy3iboonU5b/sH3H//xH3C73RWPL/0YCICqx1VSfmz5tWZL+eO6XK6mzu+V50HNGca53oqvfOUriEQixvbhhx/Oitc+M+xzPRKJ4PLLLze2L774YgQCge4NiDpqWOd7NBo1/h4KhfDzn/8c//3f/133PE3T8Ktf/QrPPvssbr75ZksgQr1rWOc6MD2e733ve7jyyitxxx13oFgs4sEHH8SDDz5Y9RxFUbBq1Sp86lOfgsPhmMXR0kwNwly//fbb8de//tXYDgQC+MAHPlD1eL4/HV7DON9b0Q/vUdmWhKiLvvjFL+Kll14ytvfZZx+ce+65VY8v/wWoKErDj2W322tea7aUL3RQPq56euV5UHOGca4368477zR93Mtut+N//ud/ujgiasWwz/UrrrjCWP398MMPx/ve974uj4g6aVjne+liUul0GmvXrjW2TzzxRPzwhz/EY489hieffBK/+tWvcN5558HpdBrHbN26FZ/4xCdMlYLU24Z1ruvcbje+9KUv4dZbb8W+++5b89jR0VFcccUVuPjiixls96F+n+svvPACvvKVr5j2/dd//Rf8fn/Vc/j+dHgN43xvVr+8R2W4TdQl3/ve90z96BRFwdVXX13zf6bZbNa03cwv0/JjM5lMw+e2Uy6XM203u8BYrzwPatywzvVmPPnkk6ZwBJj+h8mb3vSm7gyIWjLsc/3hhx/GL37xCwDTYyuf0zRYhnm+l74hTaVSKBQKEAQBX/3qV3HttddixYoV8Hq9cDgcWLRoET7xiU/gxz/+MYLBoHHeE088gdtuu60bw6cmDfNc18XjcfzP//wPPvCBD+Dvf/97zWMnJibwmc98BieeeCIee+yxWRohtUO/z/VwOIw1a9YgnU4b+4477jicfPLJNc/j+9PhNKzzvRn99B6V4TZRF9x777248sorTfsuu+wyHHDAATXPK/9FW/4/4lrKj+1WJUX5L/V8Pt/U+b3yPKgxwzzXG/WPf/wDH/3oR03/WDr55JNx1llndXFU1Kxhn+vpdNpUxfHRj34Ub3zjG7s2HuqsYZ/vld74nnXWWTjppJOqnrPffvvhy1/+smnfzTffDFVV2z08aqNhn+sAsGPHDrz//e/HT37yE+Pf7UcddRRuvPFGPPTQQ3j66aexYcMG/PCHP8SZZ55pBIN///vf8cEPfhD33HNPN4dPDer3uZ5Op/Gxj30ML7/8srFvv/32M7VKq4bvT4fPMM/3RvXbe1SG20Sz7JFHHsFFF11kejPzmc98Bu9///vrnlve/6uZX6bldxmb7SXWLuW9psrHVU+vPA+qb9jneiN27tyJc845x7QA2THHHIMvfelLXRwVNYtzHbjuuuvw6quvAgD23ntvfOQjH+naWKizON+tj22z2Rqa8+9617uw3377Gdvbt2/Hli1b2j4+ag/O9elxf+xjHzN+vwPTH+O/6aabcOyxx2J0dBSyLMPv92PFihVYu3YtfvSjHxkLphaLRXz2s5/F888/362nQA3o97mez+fxn//5n9i4caOxb+HChVi3bh08Hk/d8/n+dLgM+3xvRD++R2W4TTSLNm3ahPPOO8/0S/Ccc85pOAQo/wVY3h+slvJju/U/3Zk8h0rH8x8PvYlzvb6pqSl86EMfwvbt2419K1aswP/+7//CZuN6z/2Ccx145pln8L3vfc/Y/uIXv9jUxzSpf3C+TysPQpYuXdrw4pDHHHOMaftvf/tb28ZF7cO5Pu2nP/2p6QbMqlWrcMYZZ9Q85+CDD8Zll11mbOfzeVx77bUdGyPNTL/PdVVV8dnPfhZ//vOfjX1jY2O4+eabMWfOnIauwfenw4Pzvb5+fY/KcJtoljz//PP48Ic/bOrTeNppp+Gzn/1sw9cof+O0c+fOhs997bXXTNvz5s1r+Nx2Gh0dNf1SbOY5VDq+W8+DquNcry+RSODcc8/F1q1bjX1vfvOb8a1vfavpRWyoezjXp1199dUoFosAgJNOOgmHH354V8ZBncX5Xv2xFy1a1PC5ixcvNm3v2rWrLWOi9uFcf92dd95p2v7whz/c0Hnvec97sNdeexnb69evN1UAUm8YhLm+du1aU+sbv9+Pb3/726b5Vw/fnw4Hzvf6+vk9au/G7kQD5JVXXsGHPvQhRCIRY9+73/1uU1VDI8ob9+/YsaPhc8t/8e6zzz5NPXa7yLKMhQsXGqsS79y5E5qmQRCEhs4v/Z+C0+nEggULOjFMahHnen2ZTAYf+9jH8Mwzzxj79tlnH3z7299u20fJqPM4119XGljcfffd+OUvf9nU+du3b8fSpUuN7QULFuB3v/td28ZHM8f5bvamN70JGzZsMLb9fn/D55YfG41G2zYumjnO9dflcjk899xzxvaee+6J+fPnN3SuIAhYvnw5XnnlFQCApml45pln8Pa3v70jY6XmDcJcv+qqq/CTn/zE2Ha5XLjppptM7Z8awfeng4/zvb5+f4/Kym2iDtu1axdWr16N8fFxY99RRx2Fa665BqLY3I9g+S/TzZs3N3xu6S8poPtvCnWZTAYvvvhiQ+clEgnTogl77713w//ooM7jXK8vn8/jggsuwKOPPmrsW7BgAW655RaEQqEujoyawblenaqqKBaLdf+Uq/d16h7Od6vySu2ZLCjFFj69g3PdLBwOm34fj46ONnX+2NiY5XrUGwZhrt944434zne+Y2wrioIbbrgBy5Yta/gapfj+dHBxvtc3CO9RGW4TddDU1BRWr15t6lf0lre8Bdddd52xkngzFi1aBJ/PZ2yXLiJQzxNPPGH8XZIkHHrooU0/frscdthhpu3HH3+8ofM2bdpkWvhh+fLlbR0XtY5zvT69R9r69euNfWNjY7jlllsa7tVK3ce5TsOE872yFStWmLabaS1SXrnVL28aBx3nulX5R9CbXWQvnU6btp1O54zHRDM3CHP9Rz/6Eb7xjW8Y2zabDd/4xjdwxBFHNPzY5fj+dDBxvtc3KO9RGW4TdYjer6j0ru9BBx2EG2+8EQ6Ho6Vr2mw2vPOd7zS2X3vtNTz55JN1z9u1a5fpuEMOOaSrb6ZWrlxp2r7vvvsaOu/ee++teR3qDs71xlx66aWmHmmBQAA333xz23qkUedxrld21113YcuWLU39KbVgwQLT1/7whz905XmQGed7dYsXL8Yb3vAGY3vjxo2mcKOW0je3AEwteag7ONcr8/v9pvDnpZdeQqFQaPj80p6tADAyMtK2sVFrBmGu33XXXfjSl75kbIuiiK9+9aszfl/I96eDh/O9MYPyHpXhNlEHVOpXtHjx4rb0K3rPe95j2r711lvrnvPjH//Y9LHCd7/73TMaw0ztvffept5QDz30kOnjXJVEo1HTL93R0VFL5RTNPs71xlx11VX46U9/amx7vV585zvfaWoRMuouznUaJpzv9R1//PHG38fHx00VT9VEIhFTP3lZllnl12Wc69UJgoADDjjA2E6lUvjTn/7U0Lm7du0yfbzdbrdj//33b/cQqQmDMNd///vf45JLLoGmaca+yy67DCeeeGITo62M708HC+d7YwbpPSrDbaI2KxQK+MQnPmH6B93ee++Nm2++uakFh6pZuXIlFi9ebGzfddddpscq949//MPUn2lsbAynnXbajMcxUx//+MeNv6uqirVr15p+cZe78sorEY/Hje0Pf/jDplWtafZxrjfm//7v/0zjcjqd+L//+z/TG0bqbZzrNEw43xuzevVqeL1eY/uKK65AIpGoec6Xv/xlpFIpY/vkk0/ui0WaBhXnen3HHnusafvqq69GLBareY6maVi7dq2pv/yRRx7ZcqUkzdwgzPW//OUv+NSnPmX69MDnPve5tv6M8P3pYOB8b8ygvUdluE3URpqm4eKLLzZVNeiN+JtdhKUaQRDw6U9/2vSY5513Hh555BHLsZs3b8bq1atNPfLOP//8nvjH5XHHHYcDDzzQ2H744Ydx4YUXIplMmo7L5XK44oorcOeddxr7FixYgDPPPHPWxkpWnOuN+clPfoKvfe1rxra++Ed5Xz/qXZzrNEw43xsXCARMQcjLL7+Ms88+Gy+99JLl2EQigc997nP45S9/aezz+Xym82l2ca43ZtWqVQgEAsb2Sy+9hLPOOgvPPvtsxeN37dqF8847z9Jeas2aNZ0cJtUwCHP96aefxnnnnWc654ILLsDq1avbMn4d35/2P873xgzie1RBq3Urioiasn37dkuFgyAITa/Cu2DBAtPHViu55pprsG7dOtO+Qw89FAcddBBEUcSWLVvw8MMPm+42v/e978XVV1/d0BguueQS/OIXv7Ds1zTN1FdSFMWKK0KvWLEC3/ve92o+xo4dO3DqqadicnLS2Of3+3Hsscdi7ty5mJiYwPr1600rG7tcLtx2222mj43R7ONcf12tuX7ssceaFjABphcQadbvfvc7LFiwoOnzaOY411/XyO/1Ri1ZssT4+4IFC9hnu0dwvr+ukfmuaRo+9alP4Te/+Y2xT5ZlvPWtb8WSJUsgyzJeffVV/PnPfzZVu0qShBtuuAFHH310Q8+F2o9z/XX15vr69etx3nnnWfptH3TQQTj44IPh9/uRSqWwZcsWbNiwAfl83nTcBRdcwHC7iwZhrn/uc58zBclAa/+evvzyy3HSSSfVPIbvT/sb5/vras33QXyPys9MELVRpXtFmqaZ+is1opHjP/3pTyOTyeAHP/iBse/xxx+vurLz8ccfjy9/+csNj0FV1YbGUW0BpUYWVpo/fz5uuukmXHDBBcYv12g0ip///OcVjw8Gg7j22mv5D4cewLlef381zb5GQOXXm2YH53r9/TQ4ON/r7y8lCAK++tWvQpIk/OpXvwIA5PN5PPjgg3jwwQcrnuPxePC1r30NRx11VN3rU+dwrtffrzvqqKPwv//7v/j85z+PSCRi7N+0aRM2bdpU9TybzYYLLrgAH/3oR+uOjTpnEOZ6pefQyr+n+f508HG+v27Y3qOyLQlRnxJFEf/93/+Nm266CcuWLat63OLFi3HVVVfh61//Oux2++wNsEEHHHAA7rrrLvz7v/971R5YTqcTJ510En75y1/ibW972yyPkLptUOY6UT2c6zRMBmW+2+12XHvttfjf//1f08fZy7lcLqxatQr33HMPg+0hMwhz/V3vehd++ctf4txzz0UoFKp5rN1ux0knnYQ77riDwfaQGYS5DvD9KTVmUOb7oGBbEqIB8fLLL+OZZ57B7t27USwWMXfuXCxatMj00e9el8vl8Nhjj2H79u2YmpqC3+/HHnvsgeXLl8Ptdnd7eNQjBmGuEzWCc52GyaDM95dffhmbN2/G7t27kc1mEQwG8YY3vAGHHHIIZFnu9vCoB/T7XNc0DVu3bsWzzz6LcDiMZDIJh8MBn8+HfffdF/vvvz8URen2MKkH9PtcB/j+lBo3CPO9nzHcJiIiIiIiIiIiIqK+w7YkRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd9huE1EREREREREREREfYfhNhERERERERERERH1HYbbRERERERERERERNR3GG4TERERERERERERUd/5/41qmYGDAjvGAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 491,
       "width": 731
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the time series normalised so that intervention point (Q3 2016) is equal to 100\n",
    "gdp_at_intervention = df.loc[pd.to_datetime(\"2016 July 01\"), :]\n",
    "df_normalised = (df / gdp_at_intervention) * 100.0\n",
    "\n",
    "# plot\n",
    "fig, ax = plt.subplots()\n",
    "for col in other_countries:\n",
    "    ax.plot(df_normalised.index, df_normalised[col], color=\"grey\", alpha=0.2)\n",
    "\n",
    "ax.plot(df_normalised.index, df_normalised[target_country], color=\"red\", lw=3)\n",
    "# ax = df_normalised.plot(legend=False)\n",
    "\n",
    "# formatting\n",
    "ax.set(title=\"Normalised GDP\")\n",
    "ax.axvline(x=treatment_time, color=\"r\", ls=\":\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 611,
       "width": 689
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Examine how correlated the pre-intervention time series are\n",
    "\n",
    "pre_intervention_data = df.loc[df.index < treatment_time, :]\n",
    "\n",
    "corr = pre_intervention_data.corr()\n",
    "\n",
    "f, ax = plt.subplots(figsize=(8, 6))\n",
    "ax = sns.heatmap(\n",
    "    corr,\n",
    "    mask=np.triu(np.ones_like(corr, dtype=bool)),\n",
    "    cmap=sns.diverging_palette(230, 20, as_cmap=True),\n",
    "    vmin=-0.2,\n",
    "    vmax=1.0,\n",
    "    center=0,\n",
    "    square=True,\n",
    "    linewidths=0.5,\n",
    "    cbar_kws={\"shrink\": 0.8},\n",
    ")\n",
    "ax.set(title=\"Correlations for pre-intervention GDP data\");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the analysis\n",
    "\n",
    "Note: The analysis is (and should be) run on the raw GDP data. We do not use the normalised data shown above which was just for ease of visualization."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ":::{note}\n",
    "The `random_seed` keyword argument for the PyMC sampler is not necessary. We use it here so that the results are reproducible.\n",
    ":::"
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   "execution_count": 8,
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     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [beta, y_hat_sigma]\n"
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       "Output()"
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     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 80 seconds.\n",
      "There were 1 divergences after tuning. Increase `target_accept` or reparameterize.\n",
      "Chain 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "Sampling: [beta, y_hat, y_hat_sigma]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n"
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    "sample_kwargs = {\"tune\": 1000, \"target_accept\": 0.99, \"random_seed\": seed}\n",
    "\n",
    "result = cp.SyntheticControl(\n",
    "    df,\n",
    "    treatment_time,\n",
    "    control_units=other_countries,\n",
    "    treated_units=[target_country],\n",
    "    model=cp.pymc_models.WeightedSumFitter(\n",
    "        sample_kwargs=sample_kwargs,\n",
    "    ),\n",
    ")"
   ]
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   "metadata": {},
   "source": [
    "While we are at it, let's plot the graphviz representation of the model. This shows us the inner workings of the `WeightedSumFitter` class which defines our synthetic control model with a sum to 1 constraint on the donor weights (here labelled as `coeffs`). This will be particularly useful when we come to exploring custom priors (see below)."
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   "execution_count": 9,
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    "We currently get some divergences, but these are mostly dealt with by increasing `tune` and `target_accept` sampling parameters. Nevertheless, the sampling of this dataset/model combination feels a little brittle."
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 1MB\n",
       "Dimensions:        (chain: 4, draw: 1000, treated_units: 1, coeffs: 15,\n",
       "                    obs_ind: 30)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 32B 0 1 2 3\n",
       "  * draw           (draw) int64 8kB 0 1 2 3 4 5 6 ... 994 995 996 997 998 999\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "  * coeffs         (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Switzerland&#x27;\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "Data variables:\n",
       "    beta           (chain, draw, treated_units, coeffs) float64 480kB 0.2496 ...\n",
       "    y_hat_sigma    (chain, draw, treated_units) float64 32kB 0.02687 ... 0.03445\n",
       "    mu             (chain, draw, obs_ind, treated_units) float64 960kB 4.608 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.523740+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0\n",
       "    sampling_time:              79.63088774681091\n",
       "    tuning_steps:               1000</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-09fa7054-3f06-4362-bf10-44d6a5ff2218' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-09fa7054-3f06-4362-bf10-44d6a5ff2218' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>treated_units</span>: 1</li><li><span class='xr-has-index'>coeffs</span>: 15</li><li><span class='xr-has-index'>obs_ind</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-aed6b608-8880-4507-a597-ce827b4f6a81' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aed6b608-8880-4507-a597-ce827b4f6a81' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-884d5f7b-502f-4ced-bcc6-b6fce6b8072f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-884d5f7b-502f-4ced-bcc6-b6fce6b8072f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-286d4099-79c7-4a10-9429-8a4d6f41d8bf' class='xr-var-data-in' type='checkbox'><label for='data-286d4099-79c7-4a10-9429-8a4d6f41d8bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-988c1f8f-f51b-4f6d-91b2-4579fa610b5c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-988c1f8f-f51b-4f6d-91b2-4579fa610b5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6689e1eb-92b3-4791-89b0-f281936bc610' class='xr-var-data-in' type='checkbox'><label for='data-6689e1eb-92b3-4791-89b0-f281936bc610' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-a9f9072b-4a46-472b-8c23-3120883d2ca1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9f9072b-4a46-472b-8c23-3120883d2ca1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92bd1d30-242e-4028-ba1b-1c38ffe0dcac' class='xr-var-data-in' type='checkbox'><label for='data-92bd1d30-242e-4028-ba1b-1c38ffe0dcac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-3a9b6d3f-508e-4785-9708-938494898a27' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a9b6d3f-508e-4785-9708-938494898a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee45eb38-9ba3-4844-86ee-a6e561f29d88' class='xr-var-data-in' type='checkbox'><label for='data-ee45eb38-9ba3-4844-86ee-a6e561f29d88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-0bb3250b-10b3-4408-86d6-c153afd4dfe3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0bb3250b-10b3-4408-86d6-c153afd4dfe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdee82fb-c212-40c9-8904-92061c373fa0' class='xr-var-data-in' type='checkbox'><label for='data-cdee82fb-c212-40c9-8904-92061c373fa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-197be7be-b6c0-44da-a2c2-5e52c25c4c9e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-197be7be-b6c0-44da-a2c2-5e52c25c4c9e' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>beta</span></div><div class='xr-var-dims'>(chain, draw, treated_units, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2496 0.03484 ... 0.07178 0.2119</div><input id='attrs-7cd4aed8-2fb1-46b2-a5b9-f3da4bc714ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7cd4aed8-2fb1-46b2-a5b9-f3da4bc714ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b365a317-3533-4a15-9c11-d5596d920633' class='xr-var-data-in' type='checkbox'><label for='data-b365a317-3533-4a15-9c11-d5596d920633' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[0.24964953, 0.03483903, 0.01016717, ..., 0.13641841,\n",
       "          0.09281844, 0.07566757]],\n",
       "\n",
       "        [[0.1471535 , 0.01830209, 0.10707607, ..., 0.07083097,\n",
       "          0.12194576, 0.00783327]],\n",
       "\n",
       "        [[0.12698719, 0.01585318, 0.09649521, ..., 0.0746198 ,\n",
       "          0.1306532 , 0.01958531]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[0.03841868, 0.05856914, 0.00152453, ..., 0.03478133,\n",
       "          0.03979616, 0.11568492]],\n",
       "\n",
       "        [[0.06650663, 0.01460661, 0.04492623, ..., 0.02787876,\n",
       "          0.10140383, 0.0125553 ]],\n",
       "\n",
       "        [[0.01722413, 0.00807644, 0.01102455, ..., 0.15053799,\n",
       "          0.15680892, 0.21520378]]],\n",
       "\n",
       "...\n",
       "\n",
       "       [[[0.03899732, 0.03705022, 0.12621402, ..., 0.05317504,\n",
       "          0.09748177, 0.02207708]],\n",
       "\n",
       "        [[0.05113643, 0.04802957, 0.16000673, ..., 0.00748662,\n",
       "          0.07975709, 0.07859915]],\n",
       "\n",
       "        [[0.09018508, 0.02982258, 0.1169135 , ..., 0.02991824,\n",
       "          0.08156609, 0.01382839]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[0.08214324, 0.1189921 , 0.03410813, ..., 0.16242809,\n",
       "          0.11413517, 0.10763267]],\n",
       "\n",
       "        [[0.15711145, 0.0543644 , 0.05692044, ..., 0.02746687,\n",
       "          0.08591104, 0.02761149]],\n",
       "\n",
       "        [[0.08530209, 0.02965823, 0.02182958, ..., 0.12929759,\n",
       "          0.07177903, 0.21192664]]]], shape=(4, 1000, 1, 15))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_hat_sigma</span></div><div class='xr-var-dims'>(chain, draw, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02687 0.02277 ... 0.03396 0.03445</div><input id='attrs-2a5da284-a6c3-4084-9a6d-3312e7347edf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a5da284-a6c3-4084-9a6d-3312e7347edf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc1d9048-2e10-4157-b50d-02587ebc2b11' class='xr-var-data-in' type='checkbox'><label for='data-bc1d9048-2e10-4157-b50d-02587ebc2b11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.02687173],\n",
       "        [0.02277067],\n",
       "        [0.02362927],\n",
       "        ...,\n",
       "        [0.04720551],\n",
       "        [0.03513527],\n",
       "        [0.0371926 ]],\n",
       "\n",
       "       [[0.02468617],\n",
       "        [0.02792236],\n",
       "        [0.02880851],\n",
       "        ...,\n",
       "        [0.03428762],\n",
       "        [0.02528695],\n",
       "        [0.03370745]],\n",
       "\n",
       "       [[0.0285582 ],\n",
       "        [0.03479421],\n",
       "        [0.03314989],\n",
       "        ...,\n",
       "        [0.03256654],\n",
       "        [0.03302409],\n",
       "        [0.03239989]],\n",
       "\n",
       "       [[0.03675442],\n",
       "        [0.02805192],\n",
       "        [0.02807599],\n",
       "        ...,\n",
       "        [0.03104989],\n",
       "        [0.03395763],\n",
       "        [0.03444788]]], shape=(4, 1000, 1))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.608 4.587 4.603 ... 5.243 5.31</div><input id='attrs-b7072d38-7cf0-4b5d-a56c-4011140d4e0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7072d38-7cf0-4b5d-a56c-4011140d4e0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-664ca0e0-f4ae-4216-ba20-39a0f24e3193' class='xr-var-data-in' type='checkbox'><label for='data-664ca0e0-f4ae-4216-ba20-39a0f24e3193' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[4.60846076],\n",
       "         [4.58732774],\n",
       "         [4.60268619],\n",
       "         ...,\n",
       "         [5.24784827],\n",
       "         [5.2564293 ],\n",
       "         [5.31400598]],\n",
       "\n",
       "        [[4.59870243],\n",
       "         [4.57648822],\n",
       "         [4.59616138],\n",
       "         ...,\n",
       "         [5.26442844],\n",
       "         [5.26013106],\n",
       "         [5.33250622]],\n",
       "\n",
       "        [[4.60796689],\n",
       "         [4.58529377],\n",
       "         [4.60414588],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [5.26189513],\n",
       "         [5.24693281],\n",
       "         [5.31152118]],\n",
       "\n",
       "        [[4.61937463],\n",
       "         [4.59653554],\n",
       "         [4.62298842],\n",
       "         ...,\n",
       "         [5.27667729],\n",
       "         [5.2616224 ],\n",
       "         [5.3603241 ]],\n",
       "\n",
       "        [[4.62798042],\n",
       "         [4.60271056],\n",
       "         [4.62571738],\n",
       "         ...,\n",
       "         [5.25100748],\n",
       "         [5.24342594],\n",
       "         [5.31045907]]]], shape=(4, 1000, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a1bbb4c-0d03-4439-aa7c-ea7c228d8d7d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a1bbb4c-0d03-4439-aa7c-ea7c228d8d7d' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.523740+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd><dt><span>sampling_time :</span></dt><dd>79.63088774681091</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 968kB\n",
       "Dimensions:        (chain: 4, draw: 1000, obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 32B 0 1 2 3\n",
       "  * draw           (draw) int64 8kB 0 1 2 3 4 5 6 ... 994 995 996 997 998 999\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (chain, draw, obs_ind, treated_units) float64 960kB 4.62 ....\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.801057+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7cc23389-1b02-4894-b2b5-52ea3b972b7a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7cc23389-1b02-4894-b2b5-52ea3b972b7a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f746ffe7-9756-4151-ba24-75eedd9a1499' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f746ffe7-9756-4151-ba24-75eedd9a1499' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-12dd695f-07d3-428d-aab7-e581242149d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12dd695f-07d3-428d-aab7-e581242149d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c132e10-c536-430d-a2aa-f50675bd0268' class='xr-var-data-in' type='checkbox'><label for='data-7c132e10-c536-430d-a2aa-f50675bd0268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-f814ad46-923c-4a9c-b3c6-e9f602e893e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f814ad46-923c-4a9c-b3c6-e9f602e893e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-143c16e0-bd6f-4396-a5d4-86b791d72e92' class='xr-var-data-in' type='checkbox'><label for='data-143c16e0-bd6f-4396-a5d4-86b791d72e92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-00e22b7c-c2af-464c-b732-acf3e35b1696' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00e22b7c-c2af-464c-b732-acf3e35b1696' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14d06fce-f186-4266-aac0-d6926654280a' class='xr-var-data-in' type='checkbox'><label for='data-14d06fce-f186-4266-aac0-d6926654280a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-55af7a72-5e63-4b38-a2b0-1cf75ee5a6e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55af7a72-5e63-4b38-a2b0-1cf75ee5a6e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6ee35be-b894-488a-b480-e7bc37f8440a' class='xr-var-data-in' type='checkbox'><label for='data-f6ee35be-b894-488a-b480-e7bc37f8440a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9da9299d-bff2-4d79-82a2-6b6890be067f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9da9299d-bff2-4d79-82a2-6b6890be067f' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.62 4.604 4.603 ... 5.273 5.326</div><input id='attrs-efda43e3-2524-4047-af12-076321e2e0bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-efda43e3-2524-4047-af12-076321e2e0bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbd41b84-ee1d-4017-a65e-05dd0360dcbf' class='xr-var-data-in' type='checkbox'><label for='data-bbd41b84-ee1d-4017-a65e-05dd0360dcbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[4.61970201],\n",
       "         [4.60360062],\n",
       "         [4.60345977],\n",
       "         ...,\n",
       "         [5.25544394],\n",
       "         [5.22939768],\n",
       "         [5.31450343]],\n",
       "\n",
       "        [[4.57039485],\n",
       "         [4.63576884],\n",
       "         [4.59960868],\n",
       "         ...,\n",
       "         [5.29590041],\n",
       "         [5.27344571],\n",
       "         [5.32089887]],\n",
       "\n",
       "        [[4.61390571],\n",
       "         [4.59489239],\n",
       "         [4.62460026],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [5.26608884],\n",
       "         [5.19717247],\n",
       "         [5.32772629]],\n",
       "\n",
       "        [[4.59354559],\n",
       "         [4.57535888],\n",
       "         [4.6102472 ],\n",
       "         ...,\n",
       "         [5.21714256],\n",
       "         [5.1774473 ],\n",
       "         [5.32216061]],\n",
       "\n",
       "        [[4.63994779],\n",
       "         [4.60190922],\n",
       "         [4.66675624],\n",
       "         ...,\n",
       "         [5.26349995],\n",
       "         [5.27285699],\n",
       "         [5.32632389]]]], shape=(4, 1000, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-19d7259f-f5a8-4d39-9ab2-a47f61aee1e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-19d7259f-f5a8-4d39-9ab2-a47f61aee1e1' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.801057+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_sample_stats64b61ea0-256a-4ce9-b394-b034089cb8a9\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_sample_stats64b61ea0-256a-4ce9-b394-b034089cb8a9\" class = \"xr-section-summary\">sample_stats</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
       "\n",
       ":root {\n",
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       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
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       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, white)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 496kB\n",
       "Dimensions:                (chain: 4, draw: 1000)\n",
       "Coordinates:\n",
       "  * chain                  (chain) int64 32B 0 1 2 3\n",
       "  * draw                   (draw) int64 8kB 0 1 2 3 4 5 ... 995 996 997 998 999\n",
       "Data variables: (12/17)\n",
       "    perf_counter_diff      (chain, draw) float64 32kB 0.04945 0.0424 ... 0.04326\n",
       "    diverging              (chain, draw) bool 4kB False False ... False False\n",
       "    tree_depth             (chain, draw) int64 32kB 10 10 10 10 ... 10 10 10 10\n",
       "    max_energy_error       (chain, draw) float64 32kB 0.03267 ... -0.1361\n",
       "    perf_counter_start     (chain, draw) float64 32kB 1.065e+05 ... 1.065e+05\n",
       "    step_size_bar          (chain, draw) float64 32kB 0.001979 ... 0.001812\n",
       "    ...                     ...\n",
       "    n_steps                (chain, draw) float64 32kB 1.023e+03 ... 1.023e+03\n",
       "    smallest_eigval        (chain, draw) float64 32kB nan nan nan ... nan nan\n",
       "    process_time_diff      (chain, draw) float64 32kB 0.04573 0.04152 ... 0.0431\n",
       "    lp                     (chain, draw) float64 32kB 32.78 39.79 ... 35.35\n",
       "    reached_max_treedepth  (chain, draw) bool 4kB True True True ... True False\n",
       "    step_size              (chain, draw) float64 32kB 0.00164 ... 0.002034\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.532812+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0\n",
       "    sampling_time:              79.63088774681091\n",
       "    tuning_steps:               1000</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5b8f0459-8428-40e8-9f43-4e360e096123' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5b8f0459-8428-40e8-9f43-4e360e096123' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b6c012a2-4410-4811-9414-6d24a834628f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b6c012a2-4410-4811-9414-6d24a834628f' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-4ff4696b-43f1-4c2d-966e-258ae34d7f9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ff4696b-43f1-4c2d-966e-258ae34d7f9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98261fa6-dfe1-4c50-8049-a7070d1c64ff' class='xr-var-data-in' type='checkbox'><label for='data-98261fa6-dfe1-4c50-8049-a7070d1c64ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-cde5dfc6-4a82-4a70-9156-c7cc5e1d1434' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cde5dfc6-4a82-4a70-9156-c7cc5e1d1434' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b49d8bd-86f6-4ab0-b0b9-4a33a612df03' class='xr-var-data-in' type='checkbox'><label for='data-2b49d8bd-86f6-4ab0-b0b9-4a33a612df03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24514988-1992-485a-8f09-57fab215d2b7' class='xr-section-summary-in' type='checkbox'  ><label for='section-24514988-1992-485a-8f09-57fab215d2b7' class='xr-section-summary' >Data variables: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04945 0.0424 ... 0.04035 0.04326</div><input id='attrs-642f1adb-2ab4-4358-98e8-1fce57c4f6ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-642f1adb-2ab4-4358-98e8-1fce57c4f6ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-818aa5c6-e9b6-4246-ae31-60aecb782e36' class='xr-var-data-in' type='checkbox'><label for='data-818aa5c6-e9b6-4246-ae31-60aecb782e36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.04944921, 0.04239629, 0.04097783, ..., 0.03448971, 0.0346225 ,\n",
       "        0.03292221],\n",
       "       [0.05525596, 0.05438433, 0.0529305 , ..., 0.04064896, 0.04070179,\n",
       "        0.04255171],\n",
       "       [0.04870096, 0.04323758, 0.04064571, ..., 0.03536296, 0.03449479,\n",
       "        0.03582854],\n",
       "       [0.05643996, 0.05344779, 0.05493004, ..., 0.04140912, 0.04034571,\n",
       "        0.04325867]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diverging</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-697d4c87-4c10-4939-ab59-49d19d075af1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-697d4c87-4c10-4939-ab59-49d19d075af1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b77a2fa-4ae1-476e-821c-69d87fc2e174' class='xr-var-data-in' type='checkbox'><label for='data-5b77a2fa-4ae1-476e-821c-69d87fc2e174' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tree_depth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10 10 10 10 10 ... 10 10 10 10 10</div><input id='attrs-11306b36-6725-434e-a60f-09b1a2a5106e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11306b36-6725-434e-a60f-09b1a2a5106e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73377f6f-b0c6-48c2-9bb2-6ebe76ebf1f5' class='xr-var-data-in' type='checkbox'><label for='data-73377f6f-b0c6-48c2-9bb2-6ebe76ebf1f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10],\n",
       "       [10, 10, 10, ..., 10, 10, 10]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03267 -0.1543 ... 0.05913 -0.1361</div><input id='attrs-24a4f89e-8863-4363-b7f6-8fb0979476a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24a4f89e-8863-4363-b7f6-8fb0979476a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6aff8ff7-f19e-47ac-8844-4e78a71de92f' class='xr-var-data-in' type='checkbox'><label for='data-6aff8ff7-f19e-47ac-8844-4e78a71de92f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.03266648, -0.15425651, -0.12740746, ...,  0.05457645,\n",
       "        -0.07075316, -0.10715167],\n",
       "       [-0.08280064, -0.12434703, -0.03416169, ..., -0.00637034,\n",
       "        -0.34002809,  0.11382564],\n",
       "       [-0.26020771, -0.29440736, -0.07435699, ..., -0.09377657,\n",
       "        -0.22379783, -0.24246568],\n",
       "       [-0.09119369, -0.02183932, -0.01614251, ..., -0.00280421,\n",
       "         0.05913082, -0.13609552]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_start</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.065e+05 1.065e+05 ... 1.065e+05</div><input id='attrs-9f77524c-127c-49a0-b23a-72c09683aa38' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9f77524c-127c-49a0-b23a-72c09683aa38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60e3f12d-fda8-4a6d-99a7-6b175bc83645' class='xr-var-data-in' type='checkbox'><label for='data-60e3f12d-fda8-4a6d-99a7-6b175bc83645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[106458.00217521, 106458.0517155 , 106458.09418871, ...,\n",
       "        106502.37651533, 106502.41109929, 106502.44581379],\n",
       "       [106457.68894962, 106457.74433008, 106457.79879017, ...,\n",
       "        106501.98351392, 106502.02422746, 106502.06500079],\n",
       "       [106458.00288429, 106458.05169142, 106458.09500162, ...,\n",
       "        106502.316067  , 106502.35149617, 106502.38605621],\n",
       "       [106457.72018658, 106457.7767495 , 106457.83027183, ...,\n",
       "        106501.93443158, 106501.97592529, 106502.01633337]],\n",
       "      shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size_bar</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001979 0.001979 ... 0.001812</div><input id='attrs-c91820f1-a400-409c-a9b0-0df9f6492625' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c91820f1-a400-409c-a9b0-0df9f6492625' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c46d5b77-1ba8-4588-915f-f1519cd544d0' class='xr-var-data-in' type='checkbox'><label for='data-c46d5b77-1ba8-4588-915f-f1519cd544d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00197915, 0.00197915, 0.00197915, ..., 0.00197915, 0.00197915,\n",
       "        0.00197915],\n",
       "       [0.00194233, 0.00194233, 0.00194233, ..., 0.00194233, 0.00194233,\n",
       "        0.00194233],\n",
       "       [0.00189668, 0.00189668, 0.00189668, ..., 0.00189668, 0.00189668,\n",
       "        0.00189668],\n",
       "       [0.00181165, 0.00181165, 0.00181165, ..., 0.00181165, 0.00181165,\n",
       "        0.00181165]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>largest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a641a58-ccc4-4f5f-82fe-695539180397' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a641a58-ccc4-4f5f-82fe-695539180397' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52ceed2d-2341-4c97-a627-758f8a9c86f7' class='xr-var-data-in' type='checkbox'><label for='data-52ceed2d-2341-4c97-a627-758f8a9c86f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02131 -0.003949 ... -0.08462</div><input id='attrs-bfc34b55-25d4-4796-af07-63c0dea05aec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfc34b55-25d4-4796-af07-63c0dea05aec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80edfb0b-f912-4302-b2bd-ff35a623eb74' class='xr-var-data-in' type='checkbox'><label for='data-80edfb0b-f912-4302-b2bd-ff35a623eb74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 2.13093387e-02, -3.94916687e-03,  3.54395248e-02, ...,\n",
       "         2.26870935e-02, -2.29604863e-03, -1.81683009e-02],\n",
       "       [ 6.24032488e-03,  1.93217234e-02, -2.94682756e-02, ...,\n",
       "         1.47672801e-05,  3.78013300e-02,  2.94985626e-02],\n",
       "       [ 4.52635495e-02, -1.44761084e-02, -9.65669105e-03, ...,\n",
       "        -1.06729194e-02, -1.86880151e-02, -3.46026586e-04],\n",
       "       [-2.08086611e-02, -1.51914219e-02,  1.75065472e-03, ...,\n",
       "         5.92410270e-04,  2.08973429e-02, -8.46206469e-02]],\n",
       "      shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acceptance_rate</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9909 0.9988 ... 0.9813 0.9941</div><input id='attrs-e3e920af-c109-46aa-852d-7c966233345e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e3e920af-c109-46aa-852d-7c966233345e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f12a355c-5f3b-46aa-86bf-6256060ec43e' class='xr-var-data-in' type='checkbox'><label for='data-f12a355c-5f3b-46aa-86bf-6256060ec43e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.99086837, 0.99882357, 0.98538415, ..., 0.98122484, 0.99778679,\n",
       "        0.99723396],\n",
       "       [0.98992801, 0.98297498, 0.99894204, ..., 0.99978495, 0.98852646,\n",
       "        0.9694623 ],\n",
       "       [0.98854545, 0.99176879, 0.99927103, ..., 0.9977    , 0.99626108,\n",
       "        0.99099907],\n",
       "       [0.99927957, 0.99522932, 0.99581267, ..., 0.99958952, 0.98132188,\n",
       "        0.99407097]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-28.81 -25.42 ... -28.12 -31.29</div><input id='attrs-b9872bf5-cffc-4dd0-80fa-34b0697752a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b9872bf5-cffc-4dd0-80fa-34b0697752a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5618b3c1-0ef5-42e0-8bfc-38f7209a7bd1' class='xr-var-data-in' type='checkbox'><label for='data-5618b3c1-0ef5-42e0-8bfc-38f7209a7bd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-28.80629369, -25.42404915, -33.73610485, ..., -24.46701371,\n",
       "        -26.12720828, -28.3080102 ],\n",
       "       [-37.31087064, -39.07674631, -38.79859145, ..., -35.1735943 ,\n",
       "        -23.31758944, -26.11559932],\n",
       "       [-32.15334662, -31.80873375, -30.05996691, ..., -32.01062409,\n",
       "        -33.19118936, -34.05287501],\n",
       "       [-26.97644633, -31.77878937, -34.8958783 , ..., -26.89978463,\n",
       "        -28.12438538, -31.2879477 ]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>index_in_trajectory</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>718 666 118 616 ... -523 727 -505</div><input id='attrs-b936efa9-c275-43a7-ae31-06c26d4f1f0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b936efa9-c275-43a7-ae31-06c26d4f1f0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-083de7b0-6d1d-445c-9315-1c6b947d1dc2' class='xr-var-data-in' type='checkbox'><label for='data-083de7b0-6d1d-445c-9315-1c6b947d1dc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 718,  666,  118, ...,  226,  764, -483],\n",
       "       [ 202,  495, -577, ..., -434, -680,  640],\n",
       "       [ 541,  408, -186, ...,  530, -688, -772],\n",
       "       [-398, -586, -342, ..., -523,  727, -505]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_steps</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-8cdf5c1c-97b6-4b20-894b-65a13f251658' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8cdf5c1c-97b6-4b20-894b-65a13f251658' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0302f7a-6bd9-484f-8f4d-a1397ae1e6ae' class='xr-var-data-in' type='checkbox'><label for='data-d0302f7a-6bd9-484f-8f4d-a1397ae1e6ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.],\n",
       "       [1023., 1023., 1023., ..., 1023., 1023., 1023.]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smallest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5627a908-04fb-45bd-80a1-420b1ea57600' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5627a908-04fb-45bd-80a1-420b1ea57600' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40a3fc49-5d25-4e90-8916-8829ca36ac06' class='xr-var-data-in' type='checkbox'><label for='data-40a3fc49-5d25-4e90-8916-8829ca36ac06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>process_time_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04573 0.04152 ... 0.04023 0.0431</div><input id='attrs-ca0a3fca-6c3a-417e-ac5d-b50ed2befe6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca0a3fca-6c3a-417e-ac5d-b50ed2befe6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e01ed5-ba18-4278-afd9-5b7e4c9cf018' class='xr-var-data-in' type='checkbox'><label for='data-92e01ed5-ba18-4278-afd9-5b7e4c9cf018' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.045729, 0.041521, 0.040872, ..., 0.034223, 0.034341, 0.032849],\n",
       "       [0.050002, 0.048703, 0.048335, ..., 0.040467, 0.040585, 0.041866],\n",
       "       [0.045384, 0.042446, 0.040536, ..., 0.035296, 0.034439, 0.035432],\n",
       "       [0.050139, 0.04846 , 0.049978, ..., 0.04098 , 0.040226, 0.0431  ]],\n",
       "      shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lp</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.78 39.79 38.94 ... 37.35 35.35</div><input id='attrs-0879fd2a-a040-4ded-8aea-42c9552eac7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0879fd2a-a040-4ded-8aea-42c9552eac7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50c875a6-30c2-4f7f-8ea7-fc619cc54a03' class='xr-var-data-in' type='checkbox'><label for='data-50c875a6-30c2-4f7f-8ea7-fc619cc54a03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[32.78309132, 39.78780282, 38.94039048, ..., 33.16248801,\n",
       "        40.30207775, 36.60630113],\n",
       "       [42.46721787, 42.94117762, 41.80417224, ..., 41.11589702,\n",
       "        34.02738911, 40.47110987],\n",
       "       [40.90354096, 40.03080474, 40.74533567, ..., 39.54501264,\n",
       "        38.19923816, 39.09112538],\n",
       "       [37.95289205, 40.04948618, 40.92364137, ..., 34.38964863,\n",
       "        37.35102582, 35.35062255]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>reached_max_treedepth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... True True False</div><input id='attrs-31db5326-1dce-4b4c-91e2-3f7740f35eb2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-31db5326-1dce-4b4c-91e2-3f7740f35eb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e97c99b-8ec0-4b4d-ab97-918cca2aa000' class='xr-var-data-in' type='checkbox'><label for='data-5e97c99b-8ec0-4b4d-ab97-918cca2aa000' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True, False,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True,  True],\n",
       "       [ True,  True,  True, ...,  True,  True, False]], shape=(4, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00164 0.00164 ... 0.002034</div><input id='attrs-4f98efc9-c3d8-43d0-86ec-3e8f0665666f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f98efc9-c3d8-43d0-86ec-3e8f0665666f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ae16c5f-77bc-40fc-8108-65aeb34d60a3' class='xr-var-data-in' type='checkbox'><label for='data-5ae16c5f-77bc-40fc-8108-65aeb34d60a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00164014, 0.00164014, 0.00164014, ..., 0.00164014, 0.00164014,\n",
       "        0.00164014],\n",
       "       [0.00188633, 0.00188633, 0.00188633, ..., 0.00188633, 0.00188633,\n",
       "        0.00188633],\n",
       "       [0.00192616, 0.00192616, 0.00192616, ..., 0.00192616, 0.00192616,\n",
       "        0.00192616],\n",
       "       [0.00203402, 0.00203402, 0.00203402, ..., 0.00203402, 0.00203402,\n",
       "        0.00203402]], shape=(4, 1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2585fe96-7d69-4840-976d-0f0d009a9529' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2585fe96-7d69-4840-976d-0f0d009a9529' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.532812+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd><dt><span>sampling_time :</span></dt><dd>79.63088774681091</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_priorb178b2d8-95b9-4b01-a341-0ab6a2826ab6\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_priorb178b2d8-95b9-4b01-a341-0ab6a2826ab6\" class = \"xr-section-summary\">prior</label>\n",
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       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
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       "    --jp-content-font-color3,\n",
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       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, white)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
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       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
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       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
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       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "  display: inline-block;\n",
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       "\n",
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       "  display: inline-block !important;\n",
       "  list-style: none;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 189kB\n",
       "Dimensions:        (chain: 1, draw: 500, treated_units: 1, coeffs: 15,\n",
       "                    obs_ind: 30)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 8B 0\n",
       "  * draw           (draw) int64 4kB 0 1 2 3 4 5 6 ... 494 495 496 497 498 499\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "  * coeffs         (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Switzerland&#x27;\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "Data variables:\n",
       "    y_hat_sigma    (chain, draw, treated_units) float64 4kB 0.4183 ... 0.9914\n",
       "    beta           (chain, draw, treated_units, coeffs) float64 60kB 0.01287 ...\n",
       "    mu             (chain, draw, obs_ind, treated_units) float64 120kB 5.228 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.715718+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-105cf24f-21a4-4bd2-85e4-9f5d419373c2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-105cf24f-21a4-4bd2-85e4-9f5d419373c2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 1</li><li><span class='xr-has-index'>draw</span>: 500</li><li><span class='xr-has-index'>treated_units</span>: 1</li><li><span class='xr-has-index'>coeffs</span>: 15</li><li><span class='xr-has-index'>obs_ind</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-83c2f0cc-8e2d-4fd8-a3c5-4be11b0ef5e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-83c2f0cc-8e2d-4fd8-a3c5-4be11b0ef5e2' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-731b1c40-9260-4d11-86c5-7dabaf2d30e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-731b1c40-9260-4d11-86c5-7dabaf2d30e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23ae53fb-bcd6-4da9-beae-d68ae044ade3' class='xr-var-data-in' type='checkbox'><label for='data-23ae53fb-bcd6-4da9-beae-d68ae044ade3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 495 496 497 498 499</div><input id='attrs-e58e583d-8313-49c2-88c4-bf6be295d0b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e58e583d-8313-49c2-88c4-bf6be295d0b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-638dc383-433f-44b7-b5de-285a15fd5c66' class='xr-var-data-in' type='checkbox'><label for='data-638dc383-433f-44b7-b5de-285a15fd5c66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 497, 498, 499], shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-f506d7b9-401e-4f24-988f-3af5538272f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f506d7b9-401e-4f24-988f-3af5538272f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa6b6061-4d5d-428e-b4cd-a6fdbb1237b2' class='xr-var-data-in' type='checkbox'><label for='data-aa6b6061-4d5d-428e-b4cd-a6fdbb1237b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-a4c49ad1-124d-4437-a08f-26ae1e7a59c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4c49ad1-124d-4437-a08f-26ae1e7a59c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12a25ed2-878f-4a55-8281-15c485d2065c' class='xr-var-data-in' type='checkbox'><label for='data-12a25ed2-878f-4a55-8281-15c485d2065c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-0c9ee48c-e2f7-4a07-830a-537706c66c9a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c9ee48c-e2f7-4a07-830a-537706c66c9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-173607e6-8d91-4026-8452-730d553efae5' class='xr-var-data-in' type='checkbox'><label for='data-173607e6-8d91-4026-8452-730d553efae5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-58ede82f-8146-469a-9b7f-56de28f05268' class='xr-section-summary-in' type='checkbox'  checked><label for='section-58ede82f-8146-469a-9b7f-56de28f05268' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat_sigma</span></div><div class='xr-var-dims'>(chain, draw, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4183 0.6056 ... 0.9556 0.9914</div><input id='attrs-aeacdecc-9492-4e71-ad74-1ab15a778fb0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aeacdecc-9492-4e71-ad74-1ab15a778fb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14345a09-7776-418c-a841-9455629e5e35' class='xr-var-data-in' type='checkbox'><label for='data-14345a09-7776-418c-a841-9455629e5e35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.41832997],\n",
       "        [0.60557617],\n",
       "        [0.02878786],\n",
       "        [1.084246  ],\n",
       "        [1.46422098],\n",
       "        [0.29072736],\n",
       "        [1.33075642],\n",
       "        [0.03472346],\n",
       "        [0.28041847],\n",
       "        [0.10749307],\n",
       "        [1.92080086],\n",
       "        [1.57864499],\n",
       "        [1.00595719],\n",
       "        [0.45121505],\n",
       "        [0.59343367],\n",
       "        [0.09382112],\n",
       "        [1.85195867],\n",
       "        [0.25590475],\n",
       "        [0.28298637],\n",
       "        [0.415816  ],\n",
       "...\n",
       "        [0.00701465],\n",
       "        [1.35254573],\n",
       "        [0.55302397],\n",
       "        [1.00111538],\n",
       "        [0.4508672 ],\n",
       "        [0.6071619 ],\n",
       "        [1.72811239],\n",
       "        [0.38531025],\n",
       "        [1.0977206 ],\n",
       "        [1.21844911],\n",
       "        [1.0680861 ],\n",
       "        [0.81158037],\n",
       "        [0.88338946],\n",
       "        [0.61570669],\n",
       "        [0.07811817],\n",
       "        [0.42106163],\n",
       "        [1.15124221],\n",
       "        [0.64150838],\n",
       "        [0.95555201],\n",
       "        [0.99141828]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beta</span></div><div class='xr-var-dims'>(chain, draw, treated_units, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.01287 0.02406 ... 0.07148 0.1187</div><input id='attrs-7eeb33b6-7fb6-4a99-ab44-06a109d4f9f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7eeb33b6-7fb6-4a99-ab44-06a109d4f9f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e29974db-c30a-4ab5-b227-65e396ce3556' class='xr-var-data-in' type='checkbox'><label for='data-e29974db-c30a-4ab5-b227-65e396ce3556' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[1.28673019e-02, 2.40590691e-02, 8.81535474e-03, ...,\n",
       "          2.46062988e-01, 1.31710227e-02, 1.54113717e-01]],\n",
       "\n",
       "        [[2.06274725e-01, 4.16856090e-02, 1.58191866e-02, ...,\n",
       "          2.58501881e-02, 7.86743512e-02, 3.98640345e-02]],\n",
       "\n",
       "        [[6.00244931e-02, 5.34500947e-02, 7.57567030e-02, ...,\n",
       "          3.67472899e-03, 6.22890619e-02, 1.44055379e-01]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[9.57669162e-04, 2.08602266e-01, 8.96706706e-02, ...,\n",
       "          1.36173877e-04, 1.28634900e-01, 4.41735520e-02]],\n",
       "\n",
       "        [[9.99641177e-02, 2.66011054e-01, 3.69254414e-02, ...,\n",
       "          1.68997859e-01, 3.86290787e-02, 3.73123402e-03]],\n",
       "\n",
       "        [[1.09383888e-01, 3.85367885e-02, 2.97928720e-02, ...,\n",
       "          2.11351766e-02, 7.14798269e-02, 1.18669439e-01]]]],\n",
       "      shape=(1, 500, 1, 15))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.228 5.19 5.21 ... 7.134 7.139</div><input id='attrs-a0bcec90-6198-428c-869d-ba36237ac358' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0bcec90-6198-428c-869d-ba36237ac358' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fc16e3d-d405-413b-9583-e4f1ace7cf65' class='xr-var-data-in' type='checkbox'><label for='data-8fc16e3d-d405-413b-9583-e4f1ace7cf65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[5.22812388],\n",
       "         [5.18957389],\n",
       "         [5.21010906],\n",
       "         ...,\n",
       "         [5.83835914],\n",
       "         [5.84804287],\n",
       "         [5.87400261]],\n",
       "\n",
       "        [[4.24449492],\n",
       "         [4.23210444],\n",
       "         [4.25160337],\n",
       "         ...,\n",
       "         [4.87256063],\n",
       "         [4.88028663],\n",
       "         [4.945048  ]],\n",
       "\n",
       "        [[4.95677392],\n",
       "         [4.93122453],\n",
       "         [4.95750211],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [3.37579416],\n",
       "         [3.38558929],\n",
       "         [3.39770012]],\n",
       "\n",
       "        [[3.78606753],\n",
       "         [3.76418438],\n",
       "         [3.77808849],\n",
       "         ...,\n",
       "         [4.27239669],\n",
       "         [4.27550378],\n",
       "         [4.30812397]],\n",
       "\n",
       "        [[6.19248441],\n",
       "         [6.16187203],\n",
       "         [6.18703184],\n",
       "         ...,\n",
       "         [7.09438275],\n",
       "         [7.13352076],\n",
       "         [7.13871076]]]], shape=(1, 500, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc18b18f-4cf3-427c-941f-683d03fc7a4d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dc18b18f-4cf3-427c-941f-683d03fc7a4d' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.715718+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_prior_predictive2c61159f-2173-4b22-852c-00c715230ac7\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_prior_predictive2c61159f-2173-4b22-852c-00c715230ac7\" class = \"xr-section-summary\">prior_predictive</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, white)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 124kB\n",
       "Dimensions:        (chain: 1, draw: 500, obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * chain          (chain) int64 8B 0\n",
       "  * draw           (draw) int64 4kB 0 1 2 3 4 5 6 ... 494 495 496 497 498 499\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (chain, draw, obs_ind, treated_units) float64 120kB 5.753 ...\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.717978+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3dee603-13c1-456a-ae95-6eb676d7d03b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f3dee603-13c1-456a-ae95-6eb676d7d03b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 1</li><li><span class='xr-has-index'>draw</span>: 500</li><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f8a6b061-1b8c-4140-adb7-9f107be281e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8a6b061-1b8c-4140-adb7-9f107be281e3' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-fe6bce62-a013-4f7d-a040-945cd4ac6764' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe6bce62-a013-4f7d-a040-945cd4ac6764' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-128157e4-e8b3-4851-9cc4-cf79fab1c982' class='xr-var-data-in' type='checkbox'><label for='data-128157e4-e8b3-4851-9cc4-cf79fab1c982' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 495 496 497 498 499</div><input id='attrs-42949723-d706-4c53-9d5d-ad2494078188' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42949723-d706-4c53-9d5d-ad2494078188' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51cc0135-5845-4ae3-9cb2-2554238de4e4' class='xr-var-data-in' type='checkbox'><label for='data-51cc0135-5845-4ae3-9cb2-2554238de4e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 497, 498, 499], shape=(500,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-e293b7e3-125a-4460-8cea-b6c91a4ef637' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e293b7e3-125a-4460-8cea-b6c91a4ef637' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d82df15c-8df7-4517-8c55-c0eb55305483' class='xr-var-data-in' type='checkbox'><label for='data-d82df15c-8df7-4517-8c55-c0eb55305483' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-b594cca6-db66-44c7-9e49-aada8a86c3c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b594cca6-db66-44c7-9e49-aada8a86c3c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05b6a962-e2be-43c5-850b-6b97af498e7e' class='xr-var-data-in' type='checkbox'><label for='data-05b6a962-e2be-43c5-850b-6b97af498e7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fba83326-8289-46df-bd91-a9b327a89cf9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fba83326-8289-46df-bd91-a9b327a89cf9' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(chain, draw, obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.753 5.443 4.649 ... 9.24 6.403</div><input id='attrs-de64e291-b43e-4206-9105-e952be6d4c42' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de64e291-b43e-4206-9105-e952be6d4c42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af3835a-2995-4cb2-b4fb-e6f533c6d66f' class='xr-var-data-in' type='checkbox'><label for='data-9af3835a-2995-4cb2-b4fb-e6f533c6d66f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[5.75291647],\n",
       "         [5.44320293],\n",
       "         [4.64947261],\n",
       "         ...,\n",
       "         [6.26103258],\n",
       "         [6.74222739],\n",
       "         [6.17768012]],\n",
       "\n",
       "        [[4.99497194],\n",
       "         [4.78451752],\n",
       "         [4.52971517],\n",
       "         ...,\n",
       "         [4.76813062],\n",
       "         [5.634216  ],\n",
       "         [4.71930242]],\n",
       "\n",
       "        [[5.0034959 ],\n",
       "         [4.90657537],\n",
       "         [4.92329767],\n",
       "         ...,\n",
       "...\n",
       "         ...,\n",
       "         [3.78553821],\n",
       "         [2.84175721],\n",
       "         [2.51909707]],\n",
       "\n",
       "        [[2.81664768],\n",
       "         [4.09003099],\n",
       "         [4.64087193],\n",
       "         ...,\n",
       "         [4.29012915],\n",
       "         [3.82706251],\n",
       "         [3.98000262]],\n",
       "\n",
       "        [[6.09236151],\n",
       "         [7.02998798],\n",
       "         [4.93381987],\n",
       "         ...,\n",
       "         [6.7661309 ],\n",
       "         [9.2400526 ],\n",
       "         [6.403239  ]]]], shape=(1, 500, 30, 1))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8f02a8ca-5766-486f-a90d-49d9745fd9f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f02a8ca-5766-486f-a90d-49d9745fd9f5' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.717978+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
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       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 488B\n",
       "Dimensions:        (obs_ind: 30, treated_units: 1)\n",
       "Coordinates:\n",
       "  * obs_ind        (obs_ind) int64 240B 0 1 2 3 4 5 6 7 ... 23 24 25 26 27 28 29\n",
       "  * treated_units  (treated_units) &lt;U2 8B &#x27;UK&#x27;\n",
       "Data variables:\n",
       "    y_hat          (obs_ind, treated_units) float64 240B 4.619 4.604 ... 5.327\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.535402+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-615d8c3d-67b8-4f99-9b47-252007f577a1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-615d8c3d-67b8-4f99-9b47-252007f577a1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>treated_units</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fb2913e5-0154-469f-af6f-52297c292ae7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fb2913e5-0154-469f-af6f-52297c292ae7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-0c26d3d8-e2a9-4cc2-8182-68152b16e983' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c26d3d8-e2a9-4cc2-8182-68152b16e983' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1e13ece-5a1f-4e27-94a1-96dc5b92710c' class='xr-var-data-in' type='checkbox'><label for='data-a1e13ece-5a1f-4e27-94a1-96dc5b92710c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>treated_units</span></div><div class='xr-var-dims'>(treated_units)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;UK&#x27;</div><input id='attrs-c9f88560-4e18-45de-b5df-1402c3517a49' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9f88560-4e18-45de-b5df-1402c3517a49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e9b1fa3-e6c0-41a1-9280-ee1397d4de3b' class='xr-var-data-in' type='checkbox'><label for='data-3e9b1fa3-e6c0-41a1-9280-ee1397d4de3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;UK&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-120074a6-d56b-4384-bc4e-73dcd0467152' class='xr-section-summary-in' type='checkbox'  checked><label for='section-120074a6-d56b-4384-bc4e-73dcd0467152' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_hat</span></div><div class='xr-var-dims'>(obs_ind, treated_units)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.619 4.604 4.607 ... 5.297 5.327</div><input id='attrs-a385d1d0-181f-4892-88d2-a941e5708207' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a385d1d0-181f-4892-88d2-a941e5708207' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f1dbfc9-eccb-4e12-847c-bfd9d64e56eb' class='xr-var-data-in' type='checkbox'><label for='data-9f1dbfc9-eccb-4e12-847c-bfd9d64e56eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[4.61881],\n",
       "       [4.60431],\n",
       "       [4.60722],\n",
       "       [4.62152],\n",
       "       [4.6538 ],\n",
       "       [4.70655],\n",
       "       [4.73954],\n",
       "       [4.74526],\n",
       "       [4.7672 ],\n",
       "       [4.77202],\n",
       "       [4.78726],\n",
       "       [4.79335],\n",
       "       [4.82583],\n",
       "       [4.82299],\n",
       "       [4.88205],\n",
       "       [4.87   ],\n",
       "       [4.89236],\n",
       "       [4.92451],\n",
       "       [4.96229],\n",
       "       [4.98839],\n",
       "       [5.03492],\n",
       "       [5.07551],\n",
       "       [5.10988],\n",
       "       [5.13852],\n",
       "       [5.17165],\n",
       "       [5.20984],\n",
       "       [5.23783],\n",
       "       [5.27344],\n",
       "       [5.29673],\n",
       "       [5.32731]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c8d84cd-189a-4eba-8591-efae4cfb4b2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c8d84cd-189a-4eba-8591-efae4cfb4b2f' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.535402+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_constant_data7ab50c3e-e1ac-4c68-a9a0-bd43e0d2f26d\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_constant_data7ab50c3e-e1ac-4c68-a9a0-bd43e0d2f26d\" class = \"xr-section-summary\">constant_data</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
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       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
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       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
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       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
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       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, white)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
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       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
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       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
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       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
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       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
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       "\n",
       ".xr-wrap {\n",
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       "  min-width: 300px;\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
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       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
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       "\n",
       ".xr-obj-type,\n",
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       ".xr-group-name {\n",
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       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 4kB\n",
       "Dimensions:  (obs_ind: 30, coeffs: 15)\n",
       "Coordinates:\n",
       "  * obs_ind  (obs_ind) int64 240B 0 1 2 3 4 5 6 7 8 ... 22 23 24 25 26 27 28 29\n",
       "  * coeffs   (coeffs) &lt;U11 660B &#x27;Australia&#x27; &#x27;Austria&#x27; ... &#x27;Sweden&#x27; &#x27;Switzerland&#x27;\n",
       "Data variables:\n",
       "    X        (obs_ind, coeffs) float64 4kB 3.84 0.8028 0.9412 ... 12.37 1.719\n",
       "Attributes:\n",
       "    created_at:                 2025-12-20T10:56:11.536196+00:00\n",
       "    arviz_version:              0.22.0\n",
       "    inference_library:          pymc\n",
       "    inference_library_version:  5.23.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c61b4fee-c304-4263-826b-67451f76e016' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c61b4fee-c304-4263-826b-67451f76e016' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>obs_ind</span>: 30</li><li><span class='xr-has-index'>coeffs</span>: 15</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a33dfdde-92a8-4a67-8086-9b877aacb7b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a33dfdde-92a8-4a67-8086-9b877aacb7b7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_ind</span></div><div class='xr-var-dims'>(obs_ind)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 24 25 26 27 28 29</div><input id='attrs-afd9a537-f047-488f-bfd6-a3633f9e7aa4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-afd9a537-f047-488f-bfd6-a3633f9e7aa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7625ec9f-e601-469f-aebe-704d121709fb' class='xr-var-data-in' type='checkbox'><label for='data-7625ec9f-e601-469f-aebe-704d121709fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>coeffs</span></div><div class='xr-var-dims'>(coeffs)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Australia&#x27; ... &#x27;Switzerland&#x27;</div><input id='attrs-52a16e60-77f1-4084-9e15-ee642870e2ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52a16e60-77f1-4084-9e15-ee642870e2ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1c1a75f-fe8e-4a1d-bb14-ccf2756d17dc' class='xr-var-data-in' type='checkbox'><label for='data-d1c1a75f-fe8e-4a1d-bb14-ccf2756d17dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Australia&#x27;, &#x27;Austria&#x27;, &#x27;Belgium&#x27;, &#x27;Canada&#x27;, &#x27;Denmark&#x27;, &#x27;Finland&#x27;,\n",
       "       &#x27;France&#x27;, &#x27;Germany&#x27;, &#x27;Iceland&#x27;, &#x27;Luxemburg&#x27;, &#x27;Netherlands&#x27;,\n",
       "       &#x27;New_Zealand&#x27;, &#x27;Norway&#x27;, &#x27;Sweden&#x27;, &#x27;Switzerland&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-318a1a52-5398-4398-9be5-47ffb605c7f4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-318a1a52-5398-4398-9be5-47ffb605c7f4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>X</span></div><div class='xr-var-dims'>(obs_ind, coeffs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.84 0.8028 0.9412 ... 12.37 1.719</div><input id='attrs-e5ed2cdf-e931-45df-b1ad-d00521c4708c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e5ed2cdf-e931-45df-b1ad-d00521c4708c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ef0591c-28a3-4faa-81e9-f4f4e314ebd3' class='xr-var-data-in' type='checkbox'><label for='data-5ef0591c-28a3-4faa-81e9-f4f4e314ebd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.84048  ,  0.802836 ,  0.94117  , 16.93824  ,  4.50096  ,\n",
       "         0.51052  ,  5.0545   ,  6.63471  ,  5.18157  ,  0.114836 ,\n",
       "         1.634391 ,  0.47336  ,  7.78753  , 10.3222   ,  1.4765317],\n",
       "       [ 3.86954  ,  0.796545 ,  0.94162  , 16.7534   ,  4.41372  ,\n",
       "         0.50829  ,  5.05375  ,  6.6453   ,  5.16171  ,  0.116259 ,\n",
       "         1.634432 ,  0.47916  ,  7.71903  , 10.32867  ,  1.485509 ],\n",
       "       [ 3.88115  ,  0.799937 ,  0.95352  , 16.82878  ,  4.42898  ,\n",
       "         0.51299  ,  5.06237  ,  6.68237  ,  5.24132  ,  0.118747 ,\n",
       "         1.640982 ,  0.48188  ,  7.724    , 10.32328  ,  1.502506 ],\n",
       "       [ 3.91028  ,  0.803823 ,  0.96117  , 17.02503  ,  4.433    ,\n",
       "         0.50903  ,  5.09832  ,  6.73155  ,  5.22482  ,  0.119302 ,\n",
       "         1.650866 ,  0.48805  ,  7.72812  , 10.37107  ,  1.5151385],\n",
       "       [ 3.92716  ,  0.80051  ,  0.96615  , 17.23041  ,  4.47128  ,\n",
       "         0.51413  ,  5.11625  ,  6.78621  ,  4.91128  ,  0.121414 ,\n",
       "         1.647748 ,  0.49349  ,  7.87891  , 10.64833  ,  1.525864 ],\n",
       "       [ 3.95387  ,  0.811277 ,  0.97567  , 17.32057  ,  4.50184  ,\n",
       "         0.52833  ,  5.14098  ,  6.93903  ,  5.10614  ,  0.122733 ,\n",
       "         1.654981 ,  0.49609  ,  7.79516  , 10.86674  ,  1.5384847],\n",
       "       [ 3.98175  ,  0.81855  ,  0.97974  , 17.44332  ,  4.57321  ,\n",
       "         0.52616  ,  5.17273  ,  6.99577  ,  5.00671  ,  0.120794 ,\n",
       "...\n",
       "         0.52588  ,  5.39537  ,  7.53046  ,  5.61836  ,  0.135719 ,\n",
       "         1.708111 ,  0.54982  ,  8.43427  , 11.82275  ,  1.6761612],\n",
       "       [ 4.50884  ,  0.856751 ,  1.03446  , 19.36275  ,  4.79998  ,\n",
       "         0.52179  ,  5.4238   ,  7.49188  ,  5.51916  ,  0.134703 ,\n",
       "         1.718281 ,  0.55348  ,  8.41262  , 11.98956  ,  1.6733119],\n",
       "       [ 4.5137   ,  0.858388 ,  1.04141  , 19.31005  ,  4.82243  ,\n",
       "         0.52973  ,  5.42994  ,  7.5471   ,  5.86313  ,  0.135616 ,\n",
       "         1.723575 ,  0.5585   ,  8.45721  , 12.10879  ,  1.6853151],\n",
       "       [ 4.56084  ,  0.863285 ,  1.0434   , 19.37835  ,  4.83698  ,\n",
       "         0.52968  ,  5.44213  ,  7.58115  ,  5.81588  ,  0.134972 ,\n",
       "         1.729509 ,  0.56733  ,  8.55631  , 12.27554  ,  1.6959884],\n",
       "       [ 4.58825  ,  0.864379 ,  1.04775  , 19.39286  ,  4.84776  ,\n",
       "         0.53265  ,  5.45297  ,  7.61443  ,  5.9103   ,  0.13584  ,\n",
       "         1.729793 ,  0.57376  ,  8.48118  , 12.36629  ,  1.7029608],\n",
       "       [ 4.62773  ,  0.873659 ,  1.04835  , 19.49923  ,  4.9036   ,\n",
       "         0.53922  ,  5.48707  ,  7.67836  ,  5.73509  ,  0.139863 ,\n",
       "         1.745688 ,  0.57866  ,  8.49252  , 12.35977  ,  1.7101124],\n",
       "       [ 4.658    ,  0.872602 ,  1.05411  , 19.40335  ,  4.96993  ,\n",
       "         0.54006  ,  5.47082  ,  7.71241  ,  6.13539  ,  0.14183  ,\n",
       "         1.749799 ,  0.58517  ,  8.48983  , 12.36546  ,  1.7190255]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8b55ff6-ad07-470e-9fe1-6ef5cd847cd9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f8b55ff6-ad07-470e-9fe1-6ef5cd847cd9' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2025-12-20T10:56:11.536196+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.22.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.23.0</dd></dl></div></li></ul></div></div><br></div>\n",
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      "text/plain": [
       "Inference data with groups:\n",
       "\t> posterior\n",
       "\t> posterior_predictive\n",
       "\t> sample_stats\n",
       "\t> prior\n",
       "\t> prior_predictive\n",
       "\t> observed_data\n",
       "\t> constant_data"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.idata"
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  },
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   "metadata": {},
   "source": [
    "Check the MCMC chain mixing via the `Rhat` statistic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.172</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3963.0</td>\n",
       "      <td>2199.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y_hat_sigma[UK]</th>\n",
       "      <td>0.031</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1036.0</td>\n",
       "      <td>1488.0</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  \\\n",
       "beta[UK, Australia]    0.121  0.074   0.001    0.243      0.003    0.001   \n",
       "beta[UK, Austria]      0.046  0.042   0.000    0.123      0.001    0.001   \n",
       "beta[UK, Belgium]      0.052  0.048   0.000    0.140      0.001    0.001   \n",
       "beta[UK, Canada]       0.038  0.023   0.000    0.077      0.001    0.000   \n",
       "beta[UK, Denmark]      0.085  0.065   0.000    0.200      0.002    0.001   \n",
       "beta[UK, Finland]      0.041  0.039   0.000    0.113      0.001    0.001   \n",
       "beta[UK, France]       0.031  0.028   0.000    0.084      0.001    0.001   \n",
       "beta[UK, Germany]      0.026  0.025   0.000    0.072      0.001    0.001   \n",
       "beta[UK, Iceland]      0.154  0.041   0.075    0.230      0.001    0.001   \n",
       "beta[UK, Luxemburg]    0.049  0.045   0.000    0.134      0.001    0.001   \n",
       "beta[UK, Netherlands]  0.048  0.043   0.000    0.126      0.001    0.001   \n",
       "beta[UK, New_Zealand]  0.062  0.055   0.000    0.164      0.002    0.001   \n",
       "beta[UK, Norway]       0.082  0.045   0.000    0.156      0.002    0.001   \n",
       "beta[UK, Sweden]       0.100  0.031   0.043    0.160      0.001    0.001   \n",
       "beta[UK, Switzerland]  0.065  0.057   0.000    0.172      0.001    0.001   \n",
       "y_hat_sigma[UK]        0.031  0.005   0.023    0.040      0.000    0.000   \n",
       "\n",
       "                       ess_bulk  ess_tail  r_hat  \n",
       "beta[UK, Australia]       607.0     656.0   1.00  \n",
       "beta[UK, Austria]         808.0     703.0   1.01  \n",
       "beta[UK, Belgium]         784.0     618.0   1.00  \n",
       "beta[UK, Canada]          472.0     476.0   1.01  \n",
       "beta[UK, Denmark]         581.0     573.0   1.00  \n",
       "beta[UK, Finland]         873.0     935.0   1.00  \n",
       "beta[UK, France]          749.0     728.0   1.00  \n",
       "beta[UK, Germany]         680.0     897.0   1.00  \n",
       "beta[UK, Iceland]         844.0     943.0   1.00  \n",
       "beta[UK, Luxemburg]       738.0     553.0   1.00  \n",
       "beta[UK, Netherlands]     996.0     995.0   1.00  \n",
       "beta[UK, New_Zealand]     627.0     605.0   1.00  \n",
       "beta[UK, Norway]          621.0     568.0   1.01  \n",
       "beta[UK, Sweden]          837.0     719.0   1.01  \n",
       "beta[UK, Switzerland]    3963.0    2199.0   1.00  \n",
       "y_hat_sigma[UK]          1036.0    1488.0   1.00  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(result.idata, var_names=[\"~mu\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can inspect the traces in more detail with:\n",
    "\n",
    "```python\n",
    "az.plot_trace(result.idata, var_names=\"~mu\", compact=False);\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OHXvObTZu3KgPP/xQtm0rJiZGlmVp/vz5xT7Q8fjx4xo5cqRyc3NlWZZq1aqlJk2aBPMwUIExT0JFwTypeJZ9rktAAACSzkz4rr/+eh08eNAZTKpWraoePXqoR48eat26tTwej8/tZWZmasOGDVq6dKkWL16s48ePO+3WrFlTn3zyiWJiYkrxiFCR5F/V6XK5tHnz5nOun5eXpzFjxuijjz5yTowkOQWQqKgoeTweHTx4UHl5eQXeb9GihebOnavwcH7ABN/5cuVxsOR/lvryM21AksaPH6/Zs2dLOvM517t3bz3xxBNnfcjY8uXLNXr0aB06dMj5jFy4cKGaNWtW7DY33XSTtm7dKtu2NWvWrHMWmwFJGjVqlBYsWCDpTD67du2qsWPHFnll25IlS5wHh9q2rUmTJmnUqFHKyspSWFiY+vbtq169eikuLk4nT57UDz/8oJkzZ2rPnj3OZ+d9992nhx9++DwfJcoz5kkwGfOkwFE8BgA/rFq1Sg8++KDz0JH8kxhJCgsLU6NGjVSvXj3VrVtXHo9HkZGRioiIUHZ2trKysnTixAllZGRo3759Sk1NVW5ubqF23G63pkyZos6dO5fNQaJc8vekKN8///lPPf/8884Do4q7cjP/xCkmJkbvvPOOLrzwwqD0G6HjmmuuKbZ4vG/fPue9uLi4oO1z+fLlQWsLFdv+/fvVs2dPHTt2zBmTo6KidO211yoxMVF169ZVRESEjhw5om3btunf//63UlJSCkwYe/furZdeeqnYfRw4cEBdunRxru78/vvvz3mPZEA6c4X7TTfdpNOnTzv5jIiIUMeOHRUfH6+oqCjt379fa9euVWpqqrNOkyZN9Omnn+r555/XzJkzi/0M9s5xnTp1tHjxYlWtWvV8HiIqAOZJMBXzpMBRPAYAP23btk0PPvig9u7d65zIeA8kvnysFrW+ZVmKi4vTlClT1Lx58yD3GhVdSU+KJGn37t0aN26cVq1aJalwhvPz2qpVK02cOFENGjQITqeB/y+Q/ALBsnLlSg0ZMsQp0EnFj+ne71uWpcaNG+uDDz44672SZ82apeeee062batp06ZatGhR8A8CFda0adM0adKkIq+Cy+f9d5fLpXfeeUft27dXdna27rjjDm3cuLHA9t5tWJYlt9utt956S+3btz9PR4WKhnkSTMQ8KXAUjwGgBLKzs/XBBx9o6tSpzv0LS/Jxmj/Y1KpVS4MHD9aAAQMUERER1L4iNLRo0UK2bSssLKzExbd169ZpyZIl+v7775Wenq7Tp0+rVq1aat26tbp3767u3bsHudfAGRSPYYoVK1Zo5MiROnr0aJGFD6ngeG9ZlhITE/X3v/9dderUOWvbw4cP16+//ipJ6tGjh+68884g9x4V3ZtvvqnJkydLOvsXG5UqVdLzzz+vHj16OH8/ceKExo8fr4ULFxa5bYsWLTR+/HgelIeAMU+CaZgnBY7iMQAEIC8vT2vWrNHy5cu1du1a7dq1y/lZy9lUrlxZF154oTp06KCrr75aHTt2VFgYzzBFye3bt0/SmRPtevXqlXFvAP9QPIZJMjIy9Oabb+qjjz5STk5OsevVr19fd999twYOHMgYjvNmy5YtmjJliv7zn/8oKyurwHuWZenKK6/UiBEjin3gXWpqqr766iulpqY6t6m49NJL1aZNm/PRfYQQ5kkwBfOkwFE8BoAg27dvn9LT05WZmanMzEydOnVKlStXltvtltvtVt26dVW/fv2y7iYAGCP/fsjh4eFatmxZWXcHkHTmgU1r1qzR1q1bdfDgQWVlZalGjRqqU6eO2rdvr4suuqisu4gQlp2dra1bt+r333/XyZMnFR0drZYtW571IY9AWWOeBJRPFI8BAAAAAAAAAIVw7T8AAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAKoXgMAAAAAAAAACiE4jEAAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAKoXgMAAAAAAAAACiE4jEAAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAKoXgMAAAAAAAAACiE4jEAAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAKoXgMAAAAAAAAACiE4jEAAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAKoXgMAAAAAAAAACiE4jEAAAAAAAAAoBCKxwAAAAAAAACAQigeAwAAAAAAAAAK+X/xmrgfgLiL/wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 700x800 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 811,
       "width": 711
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.style.use(\"arviz-darkgrid\")\n",
    "\n",
    "fig, ax = result.plot(plot_predictors=False)\n",
    "\n",
    "for i in [0, 1, 2]:\n",
    "    ax[i].set(ylabel=\"Trillion USD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================SyntheticControl================================\n",
      "Control units: ['Australia', 'Austria', 'Belgium', 'Canada', 'Denmark', 'Finland', 'France', 'Germany', 'Iceland', 'Luxemburg', 'Netherlands', 'New_Zealand', 'Norway', 'Sweden', 'Switzerland']\n",
      "Treated unit: UK\n",
      "Model coefficients:\n",
      "    Australia    0.12, 94% HDI [0.0086, 0.27]\n",
      "    Austria      0.046, 94% HDI [0.0013, 0.15]\n",
      "    Belgium      0.052, 94% HDI [0.0016, 0.17]\n",
      "    Canada       0.038, 94% HDI [0.0025, 0.085]\n",
      "    Denmark      0.085, 94% HDI [0.0031, 0.23]\n",
      "    Finland      0.041, 94% HDI [0.0015, 0.14]\n",
      "    France       0.031, 94% HDI [0.0011, 0.1]\n",
      "    Germany      0.026, 94% HDI [0.00096, 0.086]\n",
      "    Iceland      0.15, 94% HDI [0.075, 0.23]\n",
      "    Luxemburg    0.049, 94% HDI [0.0011, 0.16]\n",
      "    Netherlands  0.048, 94% HDI [0.0021, 0.16]\n",
      "    New_Zealand  0.062, 94% HDI [0.0015, 0.19]\n",
      "    Norway       0.082, 94% HDI [0.0076, 0.17]\n",
      "    Sweden       0.1, 94% HDI [0.039, 0.16]\n",
      "    Switzerland  0.065, 94% HDI [0.0024, 0.2]\n",
      "    y_hat_sigma  0.031, 94% HDI [0.023, 0.041]\n"
     ]
    }
   ],
   "source": [
    "result.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effect Summary Reporting\n",
    "\n",
    "For decision-making, you often need a concise summary of the causal effect with key statistics. The `effect_summary()` method provides a decision-ready report with average and cumulative effects, HDI intervals, tail probabilities, and relative effects. This provides a comprehensive summary without manual post-processing.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>hdi_lower</th>\n",
       "      <th>hdi_upper</th>\n",
       "      <th>p_gt_0</th>\n",
       "      <th>relative_mean</th>\n",
       "      <th>relative_hdi_lower</th>\n",
       "      <th>relative_hdi_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>average</th>\n",
       "      <td>-0.178323</td>\n",
       "      <td>-0.179121</td>\n",
       "      <td>-0.227586</td>\n",
       "      <td>-0.127143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.164222</td>\n",
       "      <td>-4.005843</td>\n",
       "      <td>-2.278178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumulative</th>\n",
       "      <td>-4.101438</td>\n",
       "      <td>-4.119792</td>\n",
       "      <td>-5.234484</td>\n",
       "      <td>-2.924293</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.164222</td>\n",
       "      <td>-4.005843</td>\n",
       "      <td>-2.278178</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mean    median  hdi_lower  hdi_upper  p_gt_0  relative_mean  \\\n",
       "average    -0.178323 -0.179121  -0.227586  -0.127143     0.0      -3.164222   \n",
       "cumulative -4.101438 -4.119792  -5.234484  -2.924293     0.0      -3.164222   \n",
       "\n",
       "            relative_hdi_lower  relative_hdi_upper  \n",
       "average              -4.005843           -2.278178  \n",
       "cumulative           -4.005843           -2.278178  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate effect summary for the full post-period\n",
    "stats = result.effect_summary()\n",
    "stats.table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Post-period (2016-07-01 00:00:00 to 2022-01-01 00:00:00), the average effect was -0.18 (95% HDI [-0.23, -0.13]), with a posterior probability of an increase of 0.000. The cumulative effect was -4.10 (95% HDI [-5.23, -2.92]); probability of an increase 0.000. Relative to the counterfactual, this equals -3.16% on average (95% HDI [-4.01%, -2.28%]).\n"
     ]
    }
   ],
   "source": [
    "# View the prose summary\n",
    "print(stats.text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>hdi_lower</th>\n",
       "      <th>hdi_upper</th>\n",
       "      <th>p_gt_0</th>\n",
       "      <th>relative_mean</th>\n",
       "      <th>relative_hdi_lower</th>\n",
       "      <th>relative_hdi_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>average</th>\n",
       "      <td>-0.021407</td>\n",
       "      <td>-0.021822</td>\n",
       "      <td>-0.064357</td>\n",
       "      <td>0.021860</td>\n",
       "      <td>0.1635</td>\n",
       "      <td>-0.393064</td>\n",
       "      <td>-1.17724</td>\n",
       "      <td>0.406281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cumulative</th>\n",
       "      <td>-0.085627</td>\n",
       "      <td>-0.087289</td>\n",
       "      <td>-0.257429</td>\n",
       "      <td>0.087441</td>\n",
       "      <td>0.1635</td>\n",
       "      <td>-0.393064</td>\n",
       "      <td>-1.17724</td>\n",
       "      <td>0.406281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                mean    median  hdi_lower  hdi_upper  p_gt_0  relative_mean  \\\n",
       "average    -0.021407 -0.021822  -0.064357   0.021860  0.1635      -0.393064   \n",
       "cumulative -0.085627 -0.087289  -0.257429   0.087441  0.1635      -0.393064   \n",
       "\n",
       "            relative_hdi_lower  relative_hdi_upper  \n",
       "average               -1.17724            0.406281  \n",
       "cumulative            -1.17724            0.406281  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# You can also analyze a specific time window, e.g., the first year after Brexit\n",
    "stats_window = result.effect_summary(\n",
    "    window=(pd.to_datetime(\"2016-06-24\"), pd.to_datetime(\"2017-06-24\"))\n",
    ")\n",
    "stats_window.table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom priors\n",
    "\n",
    "The analysis above is all based upon the default priors for the `WeightedSumFitter` class. But this might not always be appropriate. In particular the default Priors are [Dirichlet distributed](https://en.wikipedia.org/wiki/Dirichlet_distribution) with an alpha parameter of 1. This corresponds to a uniform prior over the simplex.\n",
    "\n",
    "But we might have different prior beliefs. For example, we might think that some control units will play a larger role and some control units will be irrelevant. In which case, we could use as less concentrated prior, such as $\\mathrm{Dirichlet}(0.1)$.\n",
    "\n",
    "We can do this in the code below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [beta, y_hat_sigma]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e78b36c80b364291849d4a4166f78d93",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 105 seconds.\n",
      "There were 168 divergences after tuning. Increase `target_accept` or reparameterize.\n",
      "Chain 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "Chain 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n",
      "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n",
      "The effective sample size per chain is smaller than 100 for some parameters.  A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n",
      "Sampling: [beta, y_hat, y_hat_sigma]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n",
      "Sampling: [y_hat]\n"
     ]
    }
   ],
   "source": [
    "n_control_units = len(other_countries)\n",
    "\n",
    "result_custom = cp.SyntheticControl(\n",
    "    df,\n",
    "    treatment_time,\n",
    "    control_units=other_countries,\n",
    "    treated_units=[target_country],\n",
    "    model=cp.pymc_models.WeightedSumFitter(\n",
    "        sample_kwargs=sample_kwargs,\n",
    "        priors={\n",
    "            \"beta\": Prior(\n",
    "                \"Dirichlet\",\n",
    "                a=0.1 * np.ones(n_control_units),\n",
    "                dims=[\"treated_units\", \"coeffs\"],\n",
    "            ),\n",
    "        },\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main results plot shows only minor differences in terms of fitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 700x800 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 811,
       "width": 711
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = result_custom.plot(plot_predictors=False)\n",
    "\n",
    "for i in [0, 1, 2]:\n",
    "    ax[i].set(ylabel=\"Trillion USD\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also examine the effect of changing the Dirichlet prior on the posterior distribution of weights. TWe can see that the custom prior of $\\mathrm{Dirichlet}(0.1)$ results in more sparse weights over control countries. The posterior of many countries are more concentrated near zero (e.g. Austria, Canada, Germany, etc), while others have increased in importance (e.g. Denmark, and Australia).\n",
    "\n",
    "This is a rich area for discussion, but the key point is that users can define their own prior beliefs about the weights in the synthetic control model. There are some benefits from having 'sparsifying' priors in that they can help identify a smaller set of key control units that are most relevant to constructing the synthetic control."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x1000 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1011,
       "width": 811
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_forest(\n",
    "    [result.idata, result_custom.idata],\n",
    "    model_names=[\"Default prior\", \"Custom prior\"],\n",
    "    var_names=[\"beta\", \"y_hat_sigma\"],\n",
    "    combined=True,\n",
    "    figsize=(8, 10),\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    ":::{bibliography}\n",
    ":filter: docname in docnames\n",
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