Statistics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import itertools\n",
    "import os "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_data = pd.read_csv(\"/Users/nehasheth/Desktop/Sem 1/Data, Stats /Loan Default Prediction/Code/clean data/full_clean_data.csv\")\n",
    "sample_data = pd.read_csv(\"/Users/nehasheth/Desktop/Sem 1/Data, Stats /Loan Default Prediction/Code/clean data/sample_clean_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "application_data = pd.read_csv(\"/Users/nehasheth/Desktop/Sem 1/Data, Stats /Loan Default Prediction/Code/raw_application_data.csv\")\n",
    "previous_application = pd.read_csv(\"/Users/nehasheth/Desktop/Sem 1/Data, Stats /Loan Default Prediction/Code/raw_previous_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA28AAAN6CAYAAAAZ1HHUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1wUR/8H8M/dAUdvFkBBUKpArIk1FmJXbI8FiKjYYklsWBEfxYoxUdEktnhwGBVBUSxRY4xg15jIYUHFRLFCNCIgRcrd/f7wxz0uB7NHF/m+X699KfudnZktV+ZmdlagVCqVIIQQQgghhBDyXhPWdAUIIYQQQgghhPCjxhshhBBCCCGE1ALUeCOEEEIIIYSQWoAab4QQQgghhBBSC1DjjRBCCCGEEEJqAWq8EUIIIYQQQkgtQI03QgghhBBCCKkFqPFGCCGEEEIIIbUANd4IIYQQQgghpBagxhshhBBCCCGE1ALUeCOEEEIIIYR8sM6ePYuBAweiUaNGEAgEiImJ4d3mzJkzaNu2LXR1ddGsWTNs3bpVLU10dDRcXV0hFovh6uqKgwcPVkHtuajxRgghhBBCCPlgZWdno2XLlvj+++81Sv/gwQP0798fXbp0QXx8PBYtWoQZM2YgOjpalebSpUvw8vLC6NGjkZCQgNGjR2PkyJG4cuVKVe0GAECgVCqVVVoCIYQQQgghhLwHBAIBDh48iCFDhpSaZsGCBTh8+DBu376tWjdlyhQkJCTg0qVLAAAvLy9kZmbi+PHjqjR9+/aFmZkZIiIiqqz+1PNGyHtEKpXC1NS0pqtBCCGEEPJey8vLQ2ZmJmfJy8urlLwvXbqE3r17c9b16dMHf/zxBwoKCphpLl68WCl1KI1WleZOSDl0794drVq1QkhICGd9TEwMhg4dCuosVnfmzBn4+/vj1q1baNSoEebPn48pU6aULROBoML1CFL+XOE8apoQVX99KcB/rCtaD03KqOo68KmMOvLh24faci7eB+/La6MiNNkHvjpUxnH4EPazOo5TdajouXgf9nMJBtRc4ZXw3aG8gpcuxbJlyzjrli5diqCgoArnnZqaCgsLC846CwsLFBYW4t9//4WVlVWpaVJTUytcPgs13gip5YrGZU+aNAm7du3ChQsXMG3aNDRo0ADDhg2r6eoRQgghhFS6gIAA+Pv7c9aJxeJKy19QrGFa1Hnw7vqS0hRfV9lo2CSptYKCgtCqVSv89NNPsLOzg4mJCby9vfH69WtVmu7du2PGjBmYP38+zM3NYWlpqfaLzPr16/HRRx/BwMAANjY2mDZtGrKyslTxoqGMR48ehbOzM/T19TF8+HBkZ2cjPDwcdnZ2MDMzw/Tp0yGXy1Xb5efnY/78+WjcuDEMDAzQvn17xMXFccqWSqVo0qQJ9PX1MXToULx8+bLMx2Hr1q1o0qQJQkJC0Lx5c0ycOBHjx4/Ht99+W+a8CCGEEEI0JhLW2CIWi2FsbMxZKqvxZmlpqdaD9vz5c2hpaaFevXrMNMV74yobNd5Irfb3338jJiYGR48exdGjR3HmzBmsWbOGkyY8PBwGBga4cuUK1q5di+XLl+PXX39VxYVCITZt2oSbN28iPDwcp0+fxvz58zl55OTkYNOmTdi7dy9OnDiBuLg4/Oc//8GxY8dw7Ngx/PTTT9i+fTv279+v2mbcuHG4cOEC9u7di+vXr2PEiBHo27cv7t27BwC4cuUKxo8fj2nTpkEmk8HDwwMrV67klJucnAyBQKDW6HuXJuOyCSGEEEKIZjp27Mj5rggAJ0+exMcffwxtbW1mmk6dOlVp3WjYJKnVFAoFpFIpjIyMAACjR4/Gb7/9hlWrVqnStGjRAkuXLgUAODo64vvvv8dvv/2GXr16AQBmzZqlStu0aVOsWLECU6dOxebNm1XrCwoKsGXLFtjb2wMAhg8fjp9++gn//PMPDA0N4erqCg8PD8TGxsLLywt///03IiIi8OTJEzRq1AgAMHfuXJw4cQJhYWFYvXo1Nm7ciD59+mDhwoUAACcnJ1y8eBEnTpxQlautra3q7SuNJuOyi8vLy1O7qVf8/wshhBBCiEZEteOe3qysLPz111+qvx88eACZTAZzc3M0adIEAQEBePr0KXbu3Ang7cyS33//Pfz9/TFp0iRcunQJEomEM4vkzJkz0bVrV3z99dcYPHgwDh06hFOnTuH8+fNVui/U80ZqNTs7O1XDDQCsrKzw/PlzTpoWLVpw/i6eJjY2Fr169ULjxo1hZGSEMWPG4OXLl8jOzlal0dfXVzXcgLeNIzs7OxgaGnLWFeV77do1KJVKODk5wdDQULWcOXMGf//9NwDg9u3b6NixI6duxf9u3Lgx7ty5g3bt2jGPgybjst8VHBwMExMTzhLMLIEQQgghpHb6448/0Lp1a7Ru3RoA4O/vj9atW2PJkiUAgJSUFDx69EiVvmnTpjh27Bji4uLQqlUrrFixAps2beLMJdCpUyfs3bsXYWFhaNGiBaRSKSIjI9G+ffsq3RfqeSPvHWNjY2RkZKitT09Ph7GxMWddUdd1EYFAAIVCoXGahw8fon///pgyZQpWrFgBc3NznD9/HhMmTOAMOSwpD1a+CoUCIpEIf/75J0QiESddUYOvsmbN1GRcdnEl3uRrYlIp9SGEEEIIeZ90796d+b1LKpWqrevWrRuuXbvGzHf48OEYPnx4RatXJtR4I+8dFxcXzgMPi1y9ehXOzs6VWtYff/yBwsJCrFu3DkLh247oqKioCufbunVryOVyPH/+HF26dCkxjaurKy5fvsxZV/xvTXTs2BFHjhzhrCs+Lrs4sVhcqTMyEUIIIaQOEtEgvupGR5y8d6ZNm4a///4bX375JRISEpCUlIQffvgBEokE8+bNq9Sy7O3tUVhYiO+++w7379/HTz/9hK1bt1Y4XycnJ4waNQpjxozBgQMH8ODBA1y9ehVff/01jh07BgCYMWMGTpw4gbVr1yIpKQnff/895343AHj69ClcXFzw+++/l1rWlClT8PDhQ/j7++P27dsIDQ2FRCLB3LlzK7wfhBBCCCHk/UGNN/LesbOzw7lz5/D333+jd+/e+OSTTyCVSiGVSjFixIhKLatVq1ZYv349vv76a7i7u2P37t0IDq6cu7/CwsIwZswYzJkzB87Ozhg0aBCuXLkCGxsbAECHDh2wY8cOfPfdd2jVqhVOnjyJxYsXc/IoKCjA3bt3kZOTU2o5mozLJoQQQgipdFqCmlvqKIGysm68IYTUbpXwUMkg5c+VUJGaJUTVvyUqwH+sK1oPTcqo6jrwqYw68uHbh9pyLt4H78troyI02Qe+OlTGcfgQ9rM6jlN1qOi5eB/2cwkG1FzhxjV4C0ZmHn+aDxD1vBFCCCGEEEJILUATlhBCCCGEEELKjiYsqXZ0xAkhhBBCCCGkFqCeN0IIIYQQQkjZiT6Me3prE+p5I4QQQgghhJBagHreCCGEEEIIIWVH97xVOzrihBBCCCGEEFILUOONEEIIIYQQQmoBGjZJCCGEEEIIKTsaNlntqPFGyP8TCNgzJo0dOxZSqRQA0Lt3b/z222+4cOECOnTowEnn5+eH8PBwAIBIJEKjRo0wYMAArF69GmZmZpy08fHxWLNmDc6ePYu0tDRYWlrio48+wuTJk+Hp6QmBQIDk5GQ0bdq0xDpdunQJCxcuxJkzZ0qtt62tLZKTk3n2HghS/sybhjcPwQBmfJXyMDNeABFvGfk8abSgYMZzley3PZFAyVuH1woxM64vyGfGLZDFW0YKjJhxE0EeM26oZMcLBPwfuAU8HxFveOI6kDPjfOcK4N8PPs8Fhsy4LgorlL8mNNkHIdjXHd/54jtX2hrsJ18eIp7z+ULJPtamgje8deA7VlkC9muPD981C/Bft4U8g5b4zmV14KtjZVCg4rMM8uXBdywr41hXx/mq6DWjzXNNkrqFGm+E/L+UlBTV/yMjI7FkyRLcvXtXtU5PTw8A8OjRI1y6dAlfffUVJBKJWuMNAPr27YuwsDAUFhYiMTER48ePR3p6OiIiIlRpDh06hJEjR6Jnz54IDw+Hvb09Xr58ievXr2Px4sXo0qULTE1NVelPnToFNzc3Tjn16tXDgQMHkJ//trHw+PFjtGvXjpNWJOJvEBFCCCGElBk9KqDaUeONkP9naWmp+r+JiQkEAgFnXZGwsDB4enpi6tSpaNeuHUJCQmBgYMBJIxaLVdtaW1vDy8tL1WsHANnZ2ZgwYQIGDBiAAwcOqNbb29ujXbt2mDhxIpRK7i9x9erVK7E+5ubmqv+/efOGmZYQQgghhNReNFCVkDJQKpUICwuDr68vXFxc4OTkhKioKOY29+/fx4kTJ6Ctra1ad/LkSbx8+RLz588vdTu+YZyEEEIIIaRuocYbIWVw6tQp5OTkoE+fPgAAX19fSCQStXRHjx6FoaEh9PT0YG9vj8TERCxYsEAVT0pKAgA4Ozur1l29ehWGhoaq5ejRo5w8O3XqxIkbGhpCLi/fOPi8vDxkZmZylsK8gnLlRQghhJA6SiSsuaWOqrt7Tkg5SCQSeHl5QUvr7YhjHx8fXLlyhXNvHAB4eHhAJpPhypUrmD59Ovr06YPp06cz827RogVkMhlkMhmys7NRWMidYCAyMlIVL1rKez9bcHAwTExMOMv5YHYPIiGEEEIIqVnUeCNEQ2lpaYiJicHmzZuhpaUFLS0tNG7cGIWFhQgNDeWkNTAwgIODA1q0aIFNmzYhLy8Py5YtU8UdHR0BgNPoE4vFcHBwgIODQ4nl29jYqOKsdJoICAhARkYGZ/k0YGS58yOEEEJIHSQS1NxSR1HjjRAN7d69G9bW1khISOD0foWEhCA8PFytp+xdS5cuxbfffotnz54BePuoAXNzc3z99dfVVX0OsVgMY2NjzqIl1ubfkBBCCCGE1BhqvBGiIYlEguHDh8Pd3Z2zFD0G4OefS39OWvfu3eHm5obVq1cDAAwNDbFjxw78/PPPGDBgAH755Rfcv38f169fx9q1awGoT/H/8uVLpKamcpai2SUJIYQQQsiHjxpvhGjgzz//REJCAoYNG6YWMzIyQu/evUucuORd/v7++PHHH/H48WMAwNChQ3Hx4kXo6+tjzJgxcHZ2xmeffYbTp09j79698PT05Gzfs2dPWFlZcZaYmJhK20dCCCGEkDLREtbcUkcJlMUfJkUIqZOCcKzCeWiDPftloGAQM75SeYS3DAXY49xFUDDjBWBP8pLPEweAQ/cdmXFL0xxmfLr4Am8Ztw3Yz+kr4HlM56dp95jx62Y2vHVIF+gx43zHygD5zHhgqy946xAs28qbhiUP7OHAfNcTAOjwXNd8BOD/mDVR5DLjCgH7i0qmQJcZL9Tgt1otntcOXx5CDfaTj7GSPZqA75os4Knj32/q8dbBRfcFM85XR75zURkq41jzXft8ZfDFNXltVbX3oQ5AxeuRq2S/338j6FWh/CvEuX7NlX3335oruwbRQ7oJIYQQQgghZVeHJw6pKXW3z5EQQgghhBBCahHqeSOEEEIIIYSUXR1+WHZNoSNOCCGEEEIIIbUANd4IIYQQQgghpBagYZOEEEIIIYSQsqNhk9WOjjghhBBCCCGE1ALU80YIIYQQQggpO3pUQLWjnjdCCCGEEEIIqQWo8UYIIYQQQgghtYBAqVQqa7oSpGwuXryILl26oFevXjhx4oRqfXJyMpo2bQqRSISHDx+icePGqlhKSgpsbGwgl8vx4MEDSKVSLFu2jFnOgwcPYGdnV2o8KCgIMTExkMlkqr+XLVuGyZMnY+vWrap0MpkMrVu3VssvOjoa3333HeLj4yGXy9GsWTMMHz4cX331FczNzQEAubm5WLNmDfbu3Yvk5GQYGRmhe/fuWLZsGdzc3Dh1WbZsGfr06cM5JgCwdu1aLFiwAN26dUNcXBwnfXHOzs64c+dOqftcdIxZli5diqCgIABAeHg4fvjhB9y6dQtCoRCtW7fG/Pnz4enpCQDw8/NDeHg4M7+il+iePXswevRoTJo0iXN8ASAuLg4eHh549eoVTE1NmfmVJgjHyrVdWWhBwYwvFgzkzSMydwczrldYwIznamkz4y90jHjr8ExowoznKHWYcQtBJm8ZuWDnwXcsTZW5zPg/AkPeOojA/njgq4MY7HNRCBFvHZ4pjJlxpZI9ZMdWlMaMK8A/5EdPWcibhiVToFuh7QFAyHMu8jU4llVNDPZxKtCgjgU8vymLIS9TnYp7zfPaBAAjQT4zbq7IZsYzhHq8Zcir+LdzEc9rUxNKnteGJq+dmqZJHfleW5VBm/e1wb6Lia+Oi+FZ5jpVmnbWNVf2709qruwaRD1vtVBoaCimT5+O8+fP49GjR2rxRo0aYefOnZx14eHhnMbc3LlzkZKSolqsra2xfPlyzjobG5sy101XVxcSiQRJSUnMdIGBgfDy8sInn3yC48eP4+bNm1i3bh0SEhLw008/AQDy8vLQs2dPhIaGYsWKFUhKSsKxY8cgl8vRvn17XL58mZOnlZUVYmNj8eQJ98UcFhaGJk2aqNXBzc2Ns78pKSk4f/48s942Njac9HPmzFHLZ+7cuQDeHuPJkydj5MiRSEhIwO+//44uXbpg8ODB+P777wEAGzdu5GxbVN/i64C3533+/PnYu3cvcnJymPUkhBBCCCEfHpqwpJbJzs5GVFQUrl69itTUVEilUixZsoSTZuzYsQgLC0NAQIBqnVQqxdixY7FixQoAgKGhIQwN//fLu0gkgpGRESwtLStUP2dnZzRs2BCLFy9GVFRUiWl+//13rF69GiEhIZg5c6ZqvZ2dHXr16oX09HQAQEhICC5duoT4+Hi0bNkSAGBra4vo6Gi0b98eEyZMwM2bNyEQvP1lrWHDhmjbti3Cw8MRGBgI4G0v5b///osRI0YgMTGRUw8tLa0y769IJOJsY2hoWGI+ly9fxrp167Bp0yZMnz5dtX7VqlV48+YN/P39MXjwYNjY2MDEhNuLY2pqqpZfcnIyLl68iOjoaMTGxmL//v0YM2ZMmepOCCGEEFKpaMKSakc9b7VMZGQknJ2d4ezsDF9fX4SFhaH4yNdBgwbh1atXql6k8+fPIy0tDQMH8g9Jqwxr1qxBdHQ0rl69WmJ89+7dMDQ0xLRp00qMFw3727NnD3r16qVquBURCoWYPXs2EhMTkZCQwImNHz8eUqlU9XdoaChGjRoFHR3+oTKVKSIiAoaGhpg8ebJabM6cOSgoKEB0dLTG+YWGhmLAgAEwMTGBr68vJBJJZVaXEEIIIYTUAtR4q2UkEgl8fX0BAH379kVWVhZ+++03ThptbW34+voiNDQUwNsv/r6+vtDWZt/rU1natGmDkSNHYuHChSXG7927h2bNmvHWJykpCc2bNy8xVrS++PBMT09PZGZm4uzZs6peyvHjx5eYx40bN1Q9kEXLxIkT+XZPI0lJSbC3ty+x0dioUSOYmJjwDi0tolAoIJVKVefd29sbly5dwl9//VXu+uXl5SEzM5OzFOax708ihBBCCOEQCWtuqaPq7p7XQnfv3sXvv/8Ob29vAG+H/Xl5eakaae+aMGEC9u3bh9TUVOzbt6/UBkxVWblyJc6dO4eTJ0+qxZRKpWqoY3kV9TYWz6eo4RoWFoZ9+/bByckJLVq0KDEPZ2dnyGQyzrJq1aoK1UtTZTkGJ0+eRHZ2Nvr16wcAqF+/Pnr37l3ieddUcHAwTExMOMv54JKHuRJCCCGEkPcD3fNWi0gkEhQWFnImHlEqldDW1sarV684ad3d3eHi4gIfHx80b94c7u7uqlkhq4O9vT0mTZqEhQsXqg3xc3Jywvnz51FQUMDsfXNyclK7T61I0YyQjo6OarHx48ejffv2uHnzJrPRqqOjAwcHB012p8yK9jE/P1+t9+3Zs2fIzMwsse4lCQ0NRVpaGvT19VXrFAoF4uPjsWLFCohEZZ9lLiAgAP7+/px1a8WxZc6HEEIIIYRUH+p5qyUKCwuxc+dOrFu3jtNTlJCQAFtbW+zevVttm/HjxyMuLq7ae92KLFmyBElJSdi7dy9n/eeff46srCxs3ry5xO2KJizx9vbGqVOn1O5rUygU2LBhA1xdXdXuhwPeziLp5uaGmzdv4vPPP6+cnSkjb29vZGVlYdu2bWqxb7/9Ftra2hg2bBhvPi9fvsShQ4ewd+9etV7CrKwsHD9+vFz1E4vFMDY25ixa4uoZVksIIYSQD4RIUHNLHUU9b7XE0aNH8erVK0yYMEFtdsLhw4dDIpGonh1WZNKkSRgxYkS5n/tVURYWFvD398c333zDWd++fXvMnz8fc+bMwdOnTzF06FA0atQIf/31F7Zu3YpPP/0UM2fOxOzZs3Ho0CEMHDgQ69atQ/v27fHPP/9g9erVuH37Nk6dOlXq0MPTp0+joKCAue+FhYVITU3lrBMIBLCwsKjwvnfs2BEzZ87EvHnzkJ+fjyFDhqCgoAC7du3Cxo0bERISotGjGH766SfUq1cPI0aMgFDI/a3F09NT7bzfuHEDRkbc55S1atWqwvtDCCGEEEJqHjXeagmJRIKePXuqNdwAYNiwYVi9ejXS0rgPo9XS0kL9+vWrq4olmjdvHrZs2YI3b95w1n/99ddo27YtfvjhB2zduhUKhQL29vYYPnw4xo4dC+DtM+NOnz6N4OBgLFq0CA8fPoSRkRE8PDxw+fJluLu7l1qugYEBb91u3boFKysrzjqxWKxW1/IKCQlBixYtsGXLFvz3v/+FQCBAmzZtEBMTo/HMn6GhoRg6dKhaww14e969vLzwzz//qNZ17dpVLV3x2UgJIYQQQipFHZ44pKYIlPTNjhACIAjHKpxHPtj33+mikBl3fpPKjAOAlx7PjKA+H7HjUbeY4e15u3jrkCNkP3oiGebMeH1BNm8ZClRsSIipMpcZ/0dgyIwDgCHyKlQHBc/IfCMlf/435OxnMfIdJzfRP8x4noD/nlGxUs6bhuVfAf+PSQKwP4q1oWDGhTzb5/G8NgFADPZ+vuH5vbeRIoMZTxfqM+MA0FD+mhlPFRkz44U811yukv83awMBe+bdBgp2HTXZzwKe8yEGuw4FPOfCUIPXFp8CAftY8r0usgRi3jK0eT4TCnmOk5DndZEFTepQsdeWJu/Vxkr2j8K5AvZtC2lKPWZ8naAnbx2qzGfNaq7s0/drruwaRM1lQgghhBBCCKkFaNgkKZWhYem/zB8/fhxdunSpxtpUn3Pnzqmm5S9JVlZWNdaGEEIIIeQ9VYcnDqkp1HgjpWI9WuDdxxV8aD7++ONqfawCIYQQQgghmqDGGylVVT0D7X2np6dXZ/edEEIIIURjNGFJtaMjTgghhBBCCCG1APW8EUIIIYQQQsqOet6qHR1xQgghhBBCCKkFqPFGCCGEEEIIIbUADZskhBBCCCGElB09KqDaUeONVIuLFy+iS5cu6NWrF06cOKFan5ycjKZNm0IkEuHhw4ecRxCkpKTAxsYGcrkcDx48gFQqxbJly5jlPHjwAHZ2drz1efLkCZo1a4ZmzZrhzp07anGBQACxWIy7d+/C1tZWtX7IkCEwNTWFVCoFAPj5+SE8PBzBwcFYuHChKl1MTAyGDh0KpVIJAJBKpZg1axbS09PVyjI1NUVISAj8/PxUZR88eBDp6ekYN24ccz+WL1+OzZs349atWzA3N1etT0hIwCeffIJ9+/Zh8ODBvMejsmhBwYyLeOJ6hQX8hfh8xI5H3GDHR7ozwzqKQt4qPBGZMuPZhdrMuJUWfxnZEDPjfMdaX57PjCu1+D9wFTyDM5Rg52GqyOEtg0+BUsSOK3gGkLA3h7aSfRwBQKxkX5d8x0FHIOctQwhlheL5fDuqgcIKDsZRCNjbK3iOEwAIlez95N2e5zjlKdmvTQAwELDPt5E8jxnPErJfuwBQwHO+8sCuJ+9+CvivB748CvnqKOA/lnwq+j7H99rTBN9x4MNXRwAo4Hlt8O0H3zVJ6hYaNkmqRWhoKKZPn47z58/j0aNHavFGjRph586dnHXh4eGcxtzcuXORkpKiWqytrbF8+XLOOhsbG43qI5VKMXLkSOTk5ODChQslphEIBFiyZAlvXrq6uvj666/x6tUrjcrWlJeXF2ffOnbsiEmTJnHWLViwADY2Nvjyyy9V2xUUFMDPzw+ff/55tTbcCCGEEFLHiIQ1t9RRdXfPSbXJzs5GVFQUpk6dCk9PT1Wv1bvGjh2LsLAwzjqpVIqxY8eq/jY0NISlpaVqEYlEMDIyUlvHR6lUIiwsDKNHj8bnn38OiURSYrrp06dj165duHGD3ZPTs2dPWFpaIjg4mLfsstDT0+Psm46ODvT19dXW7dy5E4cOHcL+/fsBAKtWrUJaWho2bdpUqfUhhBBCCCE1ixpvpMpFRkbC2dkZzs7O8PX1RVhYmGo4YZFBgwbh1atXOH/+PADg/PnzSEtLw8CBAyu9PrGxscjJyUHPnj0xevRoREVF4fXr12rpOnXqBE9PTwQEBDDzE4lEWL16Nb777js8efKk0uvLx8XFBatXr8bUqVPxyy+/IDg4GGFhYTA2Nq72uhBCCCGEkKpDjTdS5SQSCXx9fQEAffv2RVZWFn777TdOGm1tbfj6+iI0NBTA22GWvr6+0Nau+Jj6kurj7e0NkUgENzc3ODg4IDIyssS0wcHBOHHiBM6dO8fMc+jQoWjVqhWWLl1a6fXVxMyZM+Hu7o7+/ftj6tSp+Oyzz5jp8/LykJmZyVkK82hMPSGEEELKQCSouaWOosYbqVJ3797F77//Dm9vbwCAlpYWvLy8VI20d02YMAH79u1Damoq9u3bh/Hjx1d6fdLT03HgwAFVYxIAp9FYnKurK8aMGYMFCxbw5v31118jPDwciYmJlVZfTQkEAgQGBkKhUGDx4sW86YODg2FiYsJZzgdHVUNNCSGEEEJIedFsk6RKSSQSFBYWciYeUSqV0NbWVpvgw93dHS4uLvDx8UHz5s3h7u4OmUxWqfXZs2cP3rx5g/bt23Pqo1AokJiYCFdXV7Vtli1bBicnJ8TExDDz7tq1K/r06YNFixapZo4sYmxsjKysLMjlcs59eXK5HFlZWTAxManQfgFvG8bv/ssSEBAAf39/zrq14tgK14EQQgghdUgdnjikptARJ1WmsLAQO3fuxLp16yCTyVRLQkICbG1tsXv3brVtxo8fj7i4uCrpdQPeNibnzJmjVh8PD49Se99sbGzw1VdfYdGiRZDL2VN+r1mzBkeOHMHFixc5611cXCCXyxEfH89Zf+3aNcjlcjg7O1dsx8pILBbD2NiYs2iJK3+IKiGEEEIIqTzUeCNV5ujRo3j16hUmTJgAd3d3zjJ8+PASZ3mcNGkSXrx4gYkTJ1Z6fWQyGa5du4aJEyeq1cfHxwc7d+5EQUHJ930FBATg2bNnOHXqFLOMjz76CKNGjcJ3333HWe/q6op+/fph/PjxOHXqFB48eIBTp05hwoQJ6NevX4k9foQQQggh7zW6563aUeONVBmJRIKePXuWOCRw2LBhkMlkSEtL46zX0tJC/fr1NRr6V576uLq6wsXFRS02ZMgQpKWl4ciRIyVua25ujgULFuDNmze85axYsUJtNk0A2Lt3L3r27ImpU6fC1dUVU6dORY8ePRAREVH2nSGEEEIIIXWOQFnSt0xCSJ0ThGMVzkMB9i9hYhQy4x9lPeUtY9AXm9kJItjP5cNId2ZYums+bx3ua9dnxlMKjZhxB61/ecvIhpgZ14KCGW9UmMGM39eqx1sHA+Qz40qe822qyOEtg88fchtmvEDB/g2yrQ77muK7ZgFAT1mx4/Cv0JC3DCHYH8V88Xywn3Ep12A/RTxlFPL83mupVH/kyrvSBXq8deC7bp9pse8P5jufaQp93jqYC9nXbbMC9us3RZv/MS250OFNw8J3PWjzvNdqkkch7zVV8d//+a4pvvc5vn3I1WBqBzHYt0Pw4asDwH8+Cnjqyff6Xo5+vHWoMp+3qLmy91yvubJrEE1YQgipNLlK9luKUMDzQaulwX13UbfYcZ7GGaJuMsOFu/kf9G6qzGXGM0W6zDjfBzUA6PB8oeD7kpojYn851NXgyx0fXSX78RIZQvaXdQOeRhEAaAvYx0EkqtiXuzwB//kWomL3g/J98QIAAe+XcfZ+8n3JlWtQB748+L5oC5U854Ln9Q8Ab4RV+7VEW1DxRs1rEfuHFb5Gjyb0eH44yeO5JsXKijVIAICvvc/3+s0SsI8TABggjxnnO5ZaPO+Tmrz2+N5L+Ru5/I1YQ57zUcjzPpSt5HkPqskRhDRhSbWjI04+KIaGhqUufM9qI4QQQgghH67NmzejadOm0NXVRdu2bZnfDf38/CAQCNQWNzc3VRqpVFpiGk1usykv6nkjHxTWowXefVwBIYQQQgipoFo0cUhkZCRmzZqFzZs3o3Pnzti2bRv69euHxMRENGnSRC39xo0bsWbNGtXfhYWFaNmyJUaMGMFJZ2xsjLt373LW6eqyR+BUBDXeyAfFwcGhpqtACCGEEELeM+vXr8eECRNUM5qHhITgl19+wZYtWxAcHKyW3sTEhDPpXkxMDF69eoVx48Zx0gkEAlhaWlZt5d9BwyYJIYQQQgghtUpeXh4yMzM5S15eyfdR5ufn488//0Tv3r0563v37q32bN7SFM2ibmtry1mflZUFW1tbWFtbw9PTU+2ZvpWNGm+EEEIIIYSQshMJa2wJDg5W9Y4VLSX1oAHAv//+C7lcDgsLC856CwsLpKam8u5mSkoKjh8/rvYcYhcXF0ilUhw+fBgRERHQ1dVF586dce/evfIfUx40bJIQQgghhBBSqwQEBMDf35+zTixmz3IqEHDv0VMqlWrrSiKVSmFqaoohQ4Zw1nfo0AEdOnRQ/d25c2e0adMG3333HTZt2sSbb3lQ440QQgghhBBSdjU4YYlYLOZtrBWpX78+RCKRWi/b8+fP1XrjilMqlQgNDcXo0aOho8N+DI9QKMQnn3xSpT1vNGySEEIIIYQQ8sHS0dFB27Zt8euvv3LW//rrr+jUqRNz2zNnzuCvv/7ChAkTeMtRKpWQyWSwsrKqUH1ZqOeNEEIIIYQQUna16CHd/v7+GD16ND7++GN07NgR27dvx6NHjzBlyhQAb4dhPn36FDt37uRsJ5FI0L59e7i7u6vluWzZMnTo0AGOjo7IzMzEpk2bIJPJ8MMPP1TZflR7483Pzw/h4eEAAJFIhEaNGmHAgAFYvXo1zMzMAAB2dnZ4+PCh2rbBwcFYuHCh6u/o6Gj88MMPiI+PR15eHmxsbNC5c2dMnz4drVu3BvB2jOqsWbOQnp6u2i43Nxdr1qzB3r17kZycDCMjI3Tv3h3Lli3jPHgvKCgIy5Ytw+TJk7F161bVeplMhtatW+PBgwews7Nj7m9ycjKaNm2q+tvU1BQfffQRVqxYgW7duqnWP378GEFBQTh+/Dj+/fdfWFlZYciQIViyZAnq1aunSte9e3ecOXMGwNtfEWxtbeHn54cFCxZAJBKVuL/vlh0SEgI/Pz8Ab8f9Hjx4UG38bnGrV6/Gf//7X6xatUp1/Es7R0W6deuGuLg42NnZYdasWZg1a5YqdvHiRaxcuRKXLl1Cbm4uHB0d4efnh1mzZkEkEqnSCQQCiMVi3L17lzOzz5AhQ2BqagqpVMqsN6DZ9cban6Jrrug8xsfHo1WrVswyv/jiC0gkEuzevRve3t6qfWEZO3as6kGPBw8eRMeOHWFtbY2wsDD4+vqqpZ88eTIuXbqE69evq67T4pydnXHnzh1mue8SQqlx2tKIBOw88iFixl/oGPGWsT1vFzOuoyhkxgt3s+swUXsUbx2ClTHMuClymfFXSv7nv5gISp4xS1PpAj1mPI/nXACAiGdwhrkim50Bz2f6c4Ehbx12H3DjTcPSb+BtZjxRj//XUT2wryltJTuuybHme/3xvbYUYL/HiCHnrUMhzwnT5TkObwTaFcofAG6DPXzJCq+ZcREUzHhFX1cAIFSyz4WWBsdaznMs+M4nXzxPUPFrroDnK2Iez/nWBF8ZfPtZwPPa0uK5HjQpozLwvUcU8LxfV8Z1SwAvLy+8fPkSy5cvR0pKCtzd3XHs2DHVd8yUlBQ8evSIs01GRgaio6OxcePGEvNMT0/HF198gdTUVJiYmKB169Y4e/Ys2rVrV2X7USPN5b59+yIlJQXJycnYsWMHjhw5gmnTpnHSFB3Yd5fp06er4gsWLICXlxdatWqFw4cP49atW9i+fTvs7e2xaNGiUsvOy8tDz549ERoaihUrViApKQnHjh2DXC5H+/btcfnyZU56XV1dSCQSJCUlVWifT506hZSUFJw5cwbGxsbo378/Hjx4AAC4f/8+Pv74YyQlJSEiIgJ//fUXtm7dit9++w0dO3ZEWloaJ69JkyYhJSUFd+/exYwZM7B48WJ8++23FaofS1hYGObPn4/Q0FDVuqtXr6rOS3R0NADg7t27qnUHDhwoMa+DBw+iW7dusLa2RmxsLO7cuYOZM2di1apV8Pb2hrLYh6JAIMCSJUsqVH9NrjeA/5rTRE5ODiIjIzFv3jxIJBLV+nfzDAkJgbGxMWdd8TcFCwsLDBgwAGFhYWpl5ObmYu/evZzuezc3N7W6nz9/vkx1J4QQQgj5kE2bNg3JycnIy8vDn3/+ia5du6piUqkUcXFxnPQmJibIycnBpEmTSsxvw4YNePjwIfLy8vD8+XP88ssv6NixY1XuQs0MmxSLxaqH2VlbW8PLy0utF8XIyKjUB95dvnwZa9euxcaNGzFjxgzV+qZNm6Jbt25qDYB3hYSE4NKlS4iPj0fLli0BALa2toiOjkb79u0xYcIE3Lx5U9VT4uzsjIYNG2Lx4sWIiooq9z7Xq1cPlpaWsLS0xLZt22BtbY2TJ09i8uTJ+PLLL6Gjo4OTJ09CT+/try9NmjRB69atYW9vj8DAQGzZskWVl76+vurYfPXVVzh06BBiYmKwYMGCctevNGfOnEFubi6WL1+OnTt34uzZs+jatSsaNGigSmNubg4AaNiwIUxNTUvNKzs7G5MmTcKgQYOwfft21fqJEyfCwsICgwYNQlRUFLy8vFSx6dOnY926dZg7dy4++uijcu2DJtcbwL7mNLVv3z64uroiICAAVlZWSE5Ohp2dHSdfExMTjR7oOGHCBAwePFiVR5H9+/fjzZs3nB45LS2tan1AJCGEEEJIbRo2+aGo8SN+//59nDhxAtramne/R0REwNDQsMTeE4A9RG3Pnj3o1auXquFWRCgUYvbs2UhMTERCQgIntmbNGkRHR+Pq1asa15FFX18fAFBQUIC0tDT88ssvmDZtmqrhVsTS0hKjRo1CZGQks0Gqp6eHgoKCSqlbcRKJBD4+PtDW1oaPjw+nN6msTp48iZcvX2Lu3LlqsYEDB8LJyQkRERGc9Z06dYKnpycCAgLKXe67ynO9lYVEIoGvry9MTEzQv3//EnvONNW/f39YWlqqNTRDQ0MxZMgQznBaQgghhBDy4auRxtvRo0dhaGgIPT092NvbIzExUa3XaMGCBTA0NOQsRV2ZSUlJaNasGbS0/tdxuH79ek7ajIyMEstOSkpC8+bNS4wVrS8+RLJNmzYYOXIk53678srOzkZAQABEIhG6deuGe/fuQalUMuv06tUrvHjxQi2mUChw4sQJ/PLLL+jRo0eF61ZcZmYmoqOjVT08vr6+2L9/PzIzM8uVX9FxLW1fXVxcShyeGhwcjBMnTuDcuXPlKleT6w1gX3OauHfvHi5fvqzqOfT19UVYWBgUCv4x9yURiUQYM2YMpFKpqvH+4MEDnDlzRm3Goxs3bqjVvfiDJN+Vl5eHzMxMzlKYVzU/ABBCCCHkAyUU1NxSR9VI483DwwMymQxXrlzB9OnT0adPH7V7i+bNmweZTMZZ2rdvr4oX710bP348ZDIZtm3bhuzsbGZPVWmKtimp527lypU4d+4cTp48WeZ8gbc9SIaGhjAyMsKRI0cglUo1GgZYUp02b94MQ0ND6OrqYtCgQfD19cXSpUvLVS+WPXv2oFmzZqpeylatWqFZs2bYu3dvhfIt7dyU9qBEV1dXjBkzptzDQjW53gD+a46PRCJBnz59UL9+fQBve86ys7Nx6tSpctUbeDt08uHDhzh9+jSAt71u1tbW6NmzJyeds7OzWt1XrVpVar7BwcEwMTHhLOeCyz8smBBCCCGEVL0aabwZGBjAwcEBLVq0wKZNm5CXl6c2W179+vXh4ODAWYqGFTo6OuLvv//mDBU0NTWFg4MDGjduzCzbyckJiYmJJcaKZuZzdHRUi9nb22PSpElYuHBhuRqGkZGRSEhIwIsXL/D06VNVb5aDgwMEAgGzTmZmZqoGAQCMGjUKMpkMf//9N3JzcyGRSFRDMY2NjZGVlQW5nDvblVwuR1ZWFkxMTDSuc2hoKG7dugUtLS3VcuvWrXIPnXRycgIA3L5d8uxvd+7cKfHYA2+nYo2Pj0dMTEyZy9XkegPY1xwfuVyOnTt34ueff1YdK319faSlpVVoqKmjoyO6dOmi6sELDw/HuHHjIBRyX7o6OjpqdWc9dDIgIAAZGRmcpUvAyHLXkxBCCCGEVL0av+cNAJYuXYpvv/0Wz5490yi9j48PsrKysHnz5jKX5e3tjVOnTqnd16ZQKLBhwwa4urqq3Q9XZMmSJUhKSipXz5ONjQ3s7e3V7lOqV68eevXqhc2bNyM3lzu9eGpqKnbv3g0vLy9Oj5SJiQkcHBxgY2PDmVofeDv0UC6XIz4+nrP+2rVrkMvlcHZ21qi+N27cwB9//IG4uDhOb87Zs2dx9epV3Lx5syy7DwDo3bs3zM3NsW7dOrXY4cOHce/ePfj4+JS4rY2NDb766issWrRIrWFaVmW93jRx7NgxvH79GvHx8ZzjtW/fPsTExODly5flznvChAk4cOAAoqOj8eTJE4wbN67C9RWLxTA2NuYsWuKquQ+QEEIIIR8okbDmljrqvdjz7t27w83NDatXr1ate/36NVJTUzlL0b1WHTt2xJw5czBnzhz4+/vj/PnzePjwIS5fvgyJRAKBQKDWM1Fk9uzZaNeuHQYOHIh9+/bh0aNHuHr1KoYNG4bbt2+rti+JhYUF/P39sWnTpkrd/++//x55eXno06cPzp49i8ePH+PEiRPo1asXGjduzBz+Vpyrqyv69euH8ePH49SpU3jw4AFOnTqFCRMmoF+/fnB1deWkf/Dggdpwu6ysLEgkErRr1w5du3aFu7u7avn000/RsWPHcvUmGRgYYNu2bTh06BC++OILXL9+HcnJyZBIJPDz88Pw4cMxcmTpvT8BAQF49uxZhYYhAiVfbwD7mity9+5dteOVn58PiUSCAQMGoGXLlpzjNWzYMDRo0AC7drGfTcYyYsQIaGtrY/LkyejRo0eJzxYsLCxUq/s///xT7jIJIYQQQsj7571ovAFvn3r+448/4vHjxwDe9nJZWVlxlvnz56vSf/vtt9izZw/i4+Ph6ekJR0dHjBgxAgqFApcuXYKxsXGJ5ejq6uL06dMYO3YsFi1aBAcHB/Tt2xcikQiXL19Ghw4dmPWcN28eDA35HyxbFo6Ojvjjjz9gb28PLy8v2Nvb44svvoCHhwcuXbqkmopfU3v37kXPnj0xdepUuLq6YurUqejRo4faTI7A2+PeunVrznLx4kXs2rULw4YNKzH/YcOGYdeuXcjPzy/zvg4fPhyxsbF4/PgxunbtCmdnZ6xfvx6BgYHYu3cvc6ZQc3NzLFiwAG/evClzucUVv94A/msOeNtzW/x4xcfH4+effy7xeAkEAvznP/+p0NBJfX19eHt749WrVxg/fnyJaW7duqVW93cfbE4IIYQQUulEgppb6iiBsjw3cBFCPjjL8XOF8/hHwf5hIy7Zhhkf3OwebxkNlVnMeJpAnxk3VeYy43kCETMOAAGCIewEGz2ZYTfPjcw4AGw3iGbGf7NwZcbDNnRnxttMLvne03e11k9lxnWV7BlK7yvYj7OQvWjIW4eelg9407D8KzdgxnWE/MOw3yjYj0TVFRYy449ySv4x8V3pb3SZ8YYGOcy4i676jMTVrYHiNTP+Usj/w+fDQlNm3FYrnRnPA/v1O+OPX3nrsOVj9uzNjwvZ945barGPAwCIwb7uXit1mHEDAfu1l89zHDShBfZMyYU8v//zbQ8AuUr2a4tvPxVgf4HnqyMA6PCcCz5C8H+N5qsn37EyVbBf/18Ja/Ce9bmf1lzZ356vubJrUI08pJsQQgghhBBSy9Xhe89qCh3xCpoyZYra87WKlilTptR09T5ojx49KvXYGxoa4tGjRzVdRUIIIYQQQioN9bxV0PLlyzF37twSY6Xdd0cqR6NGjSCTyZhxQgghhBBCPhTUeKughg0bomFD/vs2SOXT0tKCg4NDTVeDEEIIIaRuqsMTh9QUGjZJCCGEEEIIIbUA9bwRQgghhBBCyq6U5yqTqkNHnBBCCCGEEEJqAWq8EUIIIYQQQkgtQMMmCSGEEEIIIWVHE5ZUO2q8kRL5+fkhPDwcwNtZHc3NzdGiRQv4+PjAz88PwmJjnHv37o3ffvsNFy5cQIcOHZCXl4c2bdqgc+fO2L59Oyft/PnzERkZiRs3bsDAwABr165FeHg4Hj58CD09PTg5OWHy5MkYN25cmer5rj59+uDEiRMAADs7Ozx8+BARERHw9vbmpHNzc0NiYiLCwsLg5+fHSQ8Aenp6aNasGaZPn47JkycDAKRSKWbNmoX09PRS6xUeHo4ffvgBt27dglAoROvWrTF//nx4enoiKSkJrVq1wo4dO/D555+rtlEoFPj0009hYWGBgwcPlmnfAEBXVxcWFhZo164dpkyZgs8++4z3+FU2fUE+M25pmsOM5yh1eMtIhjkznl2ozYxninSZcVPk8tYBGz3Z8ZlHmWG7cSv4y2AfKl5+/gbM+Hk/MX8m+uzwGwH7WOsKC5hxAzE7DgAGyONNw/Iv2MdBV8Bfh2wlez/fKNgfpZa62bxlpOXqMeOZ+ezXhlBXyYyLoOCtg5xnMI4Q7DKeCU2YcW0N6vAgw5QZt62XzpsHi8XVv/kTfdyDGVYq2V9WleD/MqvgSaMt4D9WNa1Ayb5edATyCpfBd5z4aGlwzfHhu+418Ybn67Yh2J+d+QL6uk7+h4ZNklL17dsXKSkpSE5OxvHjx+Hh4YGZM2fC09MThYWFqnSPHj3CpUuX8NVXX0EikQAAxGIxdu7cCalUqmpoAMDly5exYcMGSKVSGBsbIygoCCEhIVixYgUSExMRGxuLSZMm4dWrV2Wu57tLREQEJ42NjQ3CwsI46y5fvozU1FQYGKh/uVu+fDlSUlJw/fp1DBkyBFOmTEFkZKRG9Zk7dy4mT56MkSNHIiEhAb///ju6dOmCwYMH4/vvv4eTkxPWrFmD6dOnIyUlRbXdunXr8Ndff2Hbtm1l2reiut69exc7d+6EqakpevbsiVWrVmlUX0IIIYSQchEJa26po6gpT0olFothaWkJAGjcuDHatGmDDh06oEePHpBKpZg4cSIAICwsDJ6enpg6dSratWuHkJAQGBgYoG3btggMDMTEiRNx8+ZN6OrqYty4cfjyyy/h4eEBADhy5AimTZuGESNGqMpt2bJluetZmlGjRmHDhg14/PgxbGxsAAChoaEYNWoUdu7cqZbeyMhIlefKlSsRFRWFmJgYeHl5Mcu5fPky1q1bh02bNmH69Omq9atWrcKbN2/g7++PwYMHY/r06Th06BAmTZqEo0eP4s6dO1iyZAkiIiI4zw3UZN/erWuTJk3QtWtXWFlZYcmSJRg+fDicnZ2Z2xNCCCGEkNqh7jZbSbl89tlnaNmyJQ4cOAAAUCqVCAsLg6+vL1xcXODk5ISoqChV+sDAQFhZWWHGjBlYvHgxACA4OFgVt7S0xOnTp/HixYsqrbeFhQX69OmjGoaYk5ODyMhIjB8/XqPtdXV1UVDAP7wqIiIChoaGqiGW75ozZw4KCgoQHR0NgUCAsLAwnDt3Dj/++CP8/Pzg5eWFIUOGlGm/SjNz5kwolUocOnSoUvIjhBBCCCE1jxpvpMxcXFyQnJwMADh16hRycnLQp08fAICvr69q6CTw9n65nTt3Yt++ffjuu++wc+dO6On9796O9evX48WLF7C0tESLFi0wZcoUHD9+vEz1OXr0KAwNDTnLihXq9xSNHz8eUqkUSqUS+/fvh729PVq1asXMu7CwEFKpFDdu3ECPHuz7IAAgKSkJ9vb20NFRvz+lUaNGMDExQVJSEoC3vWQhISGYMmUKnj17ho0bN5Z734ozNzdHw4YNVeepuLy8PGRmZnKWwjz+xikhhBBCiIpIUHNLHUWNN1JmSqUSAsHbF41EIoGXlxe0tN6OwPXx8cGVK1dw9+5dVfrmzZtj2LBh6NWrFz755BNOXq6urrh58yYuX76McePG4Z9//sHAgQNVQzI14eHhAZlMxlm+/PJLtXQDBgxAVlYWzp49i9DQUGav24IFC2BoaAg9PT18+eWXmDdvXom9aWX17rEDgHHjxql6Jk1M1G/213TfNCnrXcHBwTAxMeEs54KjSkxLCCGEEELeD3TPGymz27dvo2nTpkhLS0NMTAwKCgqwZcsWVVwulyM0NBRff/21ap2WlpaqgVecUCjEJ598gk8++QSzZ8/Grl27MHr0aAQGBqJp06a89TEwMICDgwNvOi0tLYwePRpLly7FlStXcPDgwVLTzps3D35+ftDX14eVlVWpjaDinJyccP78eeTn56v1vj179gyZmZlwdHRUq1dpx0bTfSvu5cuXePHiRanHLyAgAP7+/px134pPl7kcQgghhNRhQuoHqm50xEmZnD59Gjdu3MCwYcOwe/duWFtbIyEhgdMzFBISgvDwcM6MlGXh6uoKAMjO5p9eu6zGjx+PM2fOYPDgwTAzMys1Xf369eHg4IBGjRpp3HADAG9vb2RlZXFmjCzy7bffQltbG8OGDStX3cti48aNEAqFpd5DJxaLYWxszFm0xOzp0AkhhBBCSM2injdSqry8PKSmpkIul+Off/7BiRMnEBwcDE9PT4wZMwZt27bF8OHD4e7uztnO1tYWCxYswM8//4zBgwczyxg+fDg6d+6MTp06wdLSEg8ePEBAQACcnJzg4uJSpnq+S0tLC/Xr11dL27x5c/z777/Q1+d5gBUPuVwOmUzGWaejo4OOHTti5syZmDdvHvLz8zFkyBAUFBRg165d2LhxI0JCQlSzXWpCk317/fo1UlNTUVBQgAcPHmDXrl3YsWMHgoODy9VrRwghhBCikTp871lNocYbKdWJEydgZWUFLS0tmJmZoWXLlti0aRPGjh2L+Ph4JCQk4Mcff1TbzsjICL1794ZEIuFtvPXp0wcREREIDg5GRkYGLC0t8dlnnyEoKKjUoYSl1fNdzs7OuHPnTonp69Wrp1G+LFlZWWjdujVnna2tLZKTkxESEoIWLVpgy5Yt+O9//wuBQIA2bdogJiYGAwcOLFM5muzbkiVLsGTJEujo6MDS0hIdOnTAb7/9pnocAyGEEEII+TAIlEplxR8dTwip9Zbj5wrn8VqpPsvmu669smLGPzKr+CMjsuXs4Z8GIvasmqaCXN4ygjZtYSeYeZQZHpAZz1vGopxfmfHfLFyZcaVgADN+Pu0Gbx26mT3kTcOSptRjxm+kN2TGAaCn2d8VqsNDuTkzbix6w5vHy0J2T71IwP4YFYL/YzbxlfpIgXfp67Cv2w7GT5hxERS8dZDz3EnBtx+5PL8Ha2tQh7MvbZnx7vWSmfE8iJjxVVu28tYhaOoXzPijAlNm3FL7NW8ZOpAz4/k8+1HR7TWhxXO+cpXs820g4J/BOFvJfr/WE5Tv9ouy4LuuNXn98skBez8Nkc+M6yvZcX/Bf8pcp0qztm/NlT3/RM2VXYOo8UYIAQAE4ViF8zBU5jHjDjnPmfHbBuwHkgOAnOdLiTbYH/YFPF8wXyl1eetw4kEzZtyuQSYz/rNxa2YcACYVnGPGG2uxy2ifeZ8Zv2vEbkgDQLqA3fhKU7AbNY2F6cy4Yw5/Yz1F15gZV4I9ZOe50IgZ1+P50gTwf3lT8NTBQMn/JVZXwU6TL2Bf9+lC9rngqyNQ8f1M53ntGAvY7w8A//nIBfsHIj7389mNeQBw0HnJjBsr2Q3+LIGYtwy+Y1nRc1EZDQ4+Ip4GJN977ds82A1Evh8UKoMmr42qLoPvfPE1xlejT5nrVGnW9a+5sudU/HtLbUQTlpD31qNHj9Secfbu8ujRo5quIiGEEEIIIdWG7nkj761GjRqpTQpSPE4IIYQQQmqIkCYsqW7UeCPvLS0tLZotkRBCCCGEkP9HwyYJIYQQQgghpBagnjdCCCGEEEJI2YmoH6i60REnhBBCCCGEkFqAet4IIYQQQgghZUcTllQ76nkjhBBCCCGEkFqAet4IIYQQQgghZUf3vFU7arzVYX5+fggPDwfwdlp+c3NztGjRAj4+PvDz84NQyH1B9u7dG7/99hsuXLiADh06IC8vD23atEHnzp2xfft2Ttr58+cjMjISN27cgIGBAdauXYvw8HA8fPgQenp6cHJywuTJkzFu3DiN6pmeno6YmJhy1bs0dnZ2ePjwIQBAT08PzZo1w/Tp0zF58mQAQFBQEGJiYtSeNZeeng4zMzPExsaie/fuSE5ORtOmTVVxbW1tNGnSBH5+fggMDIRAIGDmV6R79+5o1aoVQkJCAAD3799HYGAgzpw5g7S0NNSvXx9t27bFN998AycnJwCAQCDAwYMHMWTIEOYx04QQSo3TliYFRsx4gQH73ORCh7cMLSiY8WyImXEdyJlxE0Eebx22G0SzE+Sww5MKzvGW8aN2F2Z8ufIoM74ipycz3tnoMW8djJDPjDcWpjPjGdBjxm/rW/LWQV7BASL5EPHE2XUEgAIluw7aAvY1maI04S2Dr576Ava5MEcuM64A/9AmvvcAvjwcFS+Y8Rci9vsDADxXGjLjRjzHgc+Qwhu8aa7rNGbGnwvYdeR7j9IkTS7P1zMxz/tYoQavG77zyXc9aFIGn0Ke/azo51KBBnXU5jkXlfHZyHe++c6FCc/rm9Qt1Fyu4/r27YuUlBQkJyfj+PHj8PDwwMyZM+Hp6YnCwkJVukePHuHSpUv46quvIJFIAABisRg7d+6EVCrFiRMnVGkvX76MDRs2QCqVwtjYGEFBQQgJCcGKFSuQmJiI2NhYTJo0Ca9evaryevNZvnw5UlJScP36dQwZMgRTpkxBZGRkuep06tQppKSk4N69e1i2bBlWrVqF0NDQcuWVn5+PXr16ITMzEwcOHMDdu3cRGRkJd3d3ZGRklCtPQgghhBBSu1HPWx0nFothafn21+/GjRujTZs26NChA3r06AGpVIqJEycCAMLCwuDp6YmpU6eiXbt2CAkJgYGBAdq2bYvAwEBMnDgRN2/ehK6uLsaNG4cvv/wSHh4eAIAjR45g2rRpGDFihKrcli1bVku9+RgZGanyWblyJaKiohATEwMvL68y16levXqqvGxtbREaGopr165hwoQJZc4rMTER9+/fx+nTp2Fra6vKs3PnzmXOixBCCCGkStCEJdWOet6Ims8++wwtW7bEgQMHAABKpRJhYWHw9fWFi4sLnJycEBUVpUofGBgIKysrzJgxA4sXLwYABAcHq+KWlpY4ffo0XrxgD6mp7HqXh66uLgoKCipclz/++APXrl1D+/bty7V9gwYNIBQKsX//fsjl7OExhBBCCCGkbqDGGymRi4sLkpOTAbwdDpiTk4M+ffoAAHx9fVVDJ4G3953t3LkT+/btw3fffYedO3dCT+9/95GsX78eL168gKWlJVq0aIEpU6bg+PHjVV7vsigsLIRUKsWNGzfQo0ePcpXdqVMnGBoaQkdHB5988glGjhyJMWPGlCuvxo0bY9OmTViyZAnMzMzw2WefYcWKFbh//75aWh8fHxgaGnKW3bt3M/PPy8tDZmYmZynMq3ijlRBCCCF1iEhYc0sdVXf3nDAplUrVRBsSiQReXl7Q0no7ytbHxwdXrlzB3bt3VembN2+OYcOGoVevXvjkk084ebm6uuLmzZu4fPkyxo0bh3/++QcDBw7UeGhjeeutiQULFsDQ0BB6enr48ssvMW/ePNWEJWUVGRkJmUyGhIQEREZG4tChQ1i4cGG58gKAL7/8Eqmpqdi1axc6duyIffv2wc3NDb/++isn3YYNGyCTyTjLoEGDmHkHBwfDxMSEs5wLjmJuQwghhBBCahY13kiJbt++jaZNmyItLQ0xMTHYvHkztLS0oKWlhcaNG6OwsFBtMo6ieEmEQiE++eQTzJ49GwcPHoRUKoVEIsGDBw+qpN6amjdvHmQyGR4+fIisrCysXbtWNVulsbFxiZODpKenAwBMTLgzyNnY2MDBwQHNmzfHyJEjMWvWLKxbtw5v3rwp9/4YGRlh0KBBWLVqFRISEtClSxesXLmSk8bS0hIODg6cxciIPatbQEAAMjIyOEuXgJHlrichhBBCCKl61Hgjak6fPo0bN25g2LBh2L17N6ytrZGQkMDp2QkJCUF4eHiZZnZ8l6urKwAgOzu7Suqtqfr168PBwQGNGjVS67FzcXHBkydPkJqayll/9epVCIVCODg4MPMWiUQoLCxEfn7FprYuIhAI4OLiUinHTCwWw9jYmLNoibUroZaEEEIIqTOEgppb6iiabbKOy8vLQ2pqKuRyOf755x+cOHECwcHB8PT0xJgxY9C2bVsMHz4c7u7unO1sbW2xYMEC/Pzzzxg8eDCzjOHDh6Nz587o1KkTLC0t8eDBAwQEBMDJyQkuLi5VUu/K0Lt3bzRv3hze3t5YtWoVGjVqhOvXr2Pu3LmYMmWKWu/Wy5cvkZqaisLCQty4cQMbN26Eh4cHjI2NVWlyc3PVnvNmaGio1hCUyWRYunQpRo8eDVdXV+jo6ODMmTMIDQ3FggULKmX/CCGEEEJI7UKNtzruxIkTsLKygpaWFszMzNCyZUts2rQJY8eORXx8PBISEvDjjz+qbWdkZITevXtDIpHwNt769OmDiIgIBAcHIyMjA5aWlvjss88QFBRU6jDLitRb04d089HS0sLJkyexaNEijBo1Cs+fP4etrS0mTpyI+fPnq6Xv2fPtQ5FFIhGsrKzQv39/rFq1ipMmKSkJrVu35qzr1q0b4uLiOOusra1hZ2eHZcuWITk5GQKBQPX37NmzK2X/CCGEEEIqpA5PHFJTBEqlsuKPjieE1HrL8XNNV6HOUIB/uIcQ7LfmJQJPZjxIyT6ffPkD/PXUJI+qpsmxZHkf9uFDsQQDmPEgHOPNg+98VMc1WdFrqq6o6LkCgAKeu3e0oShTncojCP2rvIwPWngN3i8/tm5OtEY9b4QQQgghhJCyq8P3ntUU6uskNerRo0dqzyh7d3n06FG58t29e3epebq5uVXyXhBCCCGEEFL1qOeN1KhGjRqpTeBRPF4egwYNQvv27UuMaWvTrIqEEEIIIaT2ocYbqVFaWlq8U+6Xh5GREe+zzgghhBBCSAXQhCXVjo44IYQQQgghhNQC1PNGCCGEEEIIKTuasKTaUc8bIYQQQgghhNQC1HgjhBBCCCGEkFqAhk0SQgghhBBCyk5I/UDVjRpvdYifnx/Cw8PV1t+7dw8rV65Eeno6YmJimHk8efIEzZo1Q7NmzXDnzh21uFKpxI4dOxAaGopbt25BoVDA1tYWPXv2xPTp0zWaWTIoKAjLli1TW+/s7Kwqs3v37jhz5gyCg4OxcOFCTrr+/fvj+PHjWLp0KYKCgjjpAUBHRwe2trbw8/PDggULIBKJmPWJi4uDh4eH6u/69evj448/xpo1a9CyZUtV/q1atUJISAhnW6lUilmzZiE9PV21Ljc3F2vWrMHevXuRnJwMIyMjdO/eHcuWLeM8g67oOEyePBlbt25VrZfJZGjdujUePHgAOzs7JCcno2nTpiXW/dKlS+jQoQNz/4ooUPFx64bKPGa8zauHzPhNM+sK10Ffns+M54h0mPF0gR5vGWEbujPjfv4GzHj7jO95y1iR05MZVyh/ZsaDBAOY8VNpG3nrcNbMkRkv4Bm80UCZzYy7pz/lrcMpMxfeNCy28jRmPFOky5tHvcIcZlwhYL925Bq8ttxePWPG32ixH3Fy0dSeGec7VwCgDQUzzvcesQpHmHGhBnXo+jKJGY+r58yMi3j24YctHsw4AEyZeoYZb1LAvqZStI15yyjg+fqljcIq3V4TcrA/G3WVBcx4joD9XgsAZspcZvyNoOof7bMc7PfSyvhs1AP7cykbYnZcyT4O6wTszwvyYaHmch3Tt29fpKSkcJbSvviXRCqVYuTIkcjJycGFCxc4MaVSic8//xwzZsxA//79cfLkSVy/fh2bNm2Cnp4eVq5cqXE5bm5uavU8f/48J42NjQ3CwsI46549e4bTp0/DyspKLc9JkyYhJSUFd+/exYwZM7B48WJ8++23Gtfp7t27SElJwc8//4xXr16hb9++yMjI0Hh7AMjLy0PPnj0RGhqKFStWICkpCceOHYNcLkf79u1x+fJlTnpdXV1IJBIkJbG/0ADAqVOn1I5Z27Zty1Q/QgghhBCNiQQ1t9RR1PNWx4jFYlhaWpZrW6VSibCwMGzevBnW1taQSCTo3LmzKh4ZGYm9e/fi0KFDGDRokGp9s2bN0KNHDyiVSo3L0tLS4q2np6cnoqKicOHCBVU9pFIpevfujUePHqml19fXV+X51Vdf4dChQ4iJicGCBQs0qlPDhg1hamoKS0tLrFu3Dp9++ikuX76MPn36aLxfISEhuHTpEuLj41W9dra2toiOjkb79u0xYcIE3Lx5E4L//yXf2dkZDRs2xOLFixEVFcXMu169euU+t4QQQggh5P1HPW9EY7GxscjJyUHPnj0xevRoREVF4fXr16p4REQEnJ2dOQ23dwl4hhaVlY6ODkaNGsXpfZNKpRg/frxG2+vp6aGggD3sg7UtgDJvv2fPHvTq1UvVcCsiFAoxe/ZsJCYmIiEhgRNbs2YNoqOjcfXq1XLVlRBCCCGkSgiFNbfUUXV3z+uoo0ePwtDQULWMGDFC420lEgm8vb0hEong5uYGBwcHREZGquJJSUlwdubejzBr1ixVWdbWmt/PdOPGDU49DQ0NMXHiRLV0EyZMQFRUFLKzs3H27FlkZGRgwAD2vT4KhQInTpzAL7/8gh49emhcpyIvX77EsmXLYGRkhHbt2qnWb968Wa3OU6ZM4WyblJSE5s2bl5hv0friQyTbtGmDkSNHqt3bV1ynTp3UypfL5WXeP0IIIYQQ8n6iYZN1jIeHB7Zs2aL628CAPbFCkfT0dBw4cIBz35mvry9CQ0M5jarivWuBgYH46quvcODAAaxevVrjejo7O+Pw4cOcdUZGRmrpWrRoAUdHR+zfvx+xsbEYPXo0tLVLvrF38+bN2LFjB/Lz3944PHr0aCxdulTjOhU1PrOzs+Ho6Ih9+/ahYcOGqvioUaMQGBjI2aYs+100rLSkHsqVK1eiefPmOHnyJKfMd0VGRqo1DEubjCUvLw95edzJRQrFBdASV/3N4YQQQgghpHyo8VbHGBgYaDTjY3F79uzBmzdv0L59e9U6pVIJhUKBxMREuLq6wtHRUW0GygYNGqBBgwalNjhKo6Ojo3E9x48fjx9++AGJiYn4/fffS01X1LgSi8Vo1KgR7yyTxZ07dw7GxsZo0KABjI3VZxMzMTFRq3Px/XZyckJiYmKJ+RcdO0dH9Rn+7O3tMWnSJCxcuBASiaTE7W1sbDQ+ZsHBwWozenZb+jm6B43SaHtCCCGEEAjr7sQhNYWGTRKNSCQSzJkzBzKZTLUkJCTAw8MDoaGhAAAfHx/cvXsXhw4dqta6ff7557hx4wbc3d3h6upaarqixpWNjU2ZG24A0LRpU9jb25fYcNOUt7c3Tp06pXZfm0KhwIYNG+Dq6qp2P1yRJUuWICkpCXv37i13+UUCAgKQkZHBWT4NGFnhfAkhhBBC3lebN29G06ZNoauri7Zt2+LcuXOlpo2Li4NAIFBbindUREdHw9XVFWKxGK6urjh48GCV7gP1vBGVjIwMyGQyzjpzc3OkpaXh2rVr2L17N1xcuM9c8vHxQWBgIIKDg+Ht7Y0DBw7A29sbAQEB6NOnDywsLPDw4UNERkaWqcFUWFiI1NRUzjqBQAALCwu1tGZmZkhJSSl1uOT7ZPbs2Th06BAGDhyIdevWoX379vjnn3+wevVq3L59G6dOnSp1YhcLCwv4+/vjm2++KTH+8uVLtWNmamoKXV3151iJxWKIxdznymjh/T9+hBBCCHmP1KIp+yMjIzFr1ixs3rwZnTt3xrZt29CvXz8kJiaiSZMmpW539+5dzg/3DRo0UP3/0qVL8PLywooVKzB06FAcPHgQI0eOxPnz5zmj1SoT9bwRlbi4OLRu3ZqzLFmyBBKJBK6urmoNNwAYMmQI0tLScOTIEQgEAkRGRiIkJATHjh1Djx494OzsjPHjx8PGxkbtOW0st27dgpWVFWextbUtNb2pqanG9+/VJF1dXZw+fRpjx47FokWL4ODggL59+0IkEuHy5cu8D9SeN28eDA0NS4z17NlT7ZjxPXSdEEIIIaQuWL9+PSZMmICJEyeiefPmCAkJgY2NDWcuiJI0bNgQlpaWquXdzoiQkBD06tULAQEBcHFxQUBAAHr06IGQkJAq2w+BsiwP3yKEfLCCcKzCeRgq85jxNq8eMuM3zTSfkbQ0+vJ8ZjxHpMOMpwv0eMsI29CdGffzZ/+Q0C7je94yVuT0ZMZ7W95nxoME7FlXT6Vt5K3DWTP1+y/fJQf7F9cGymxm3D39KW8dTpmp/2hUFrbyNGY8U6TeM11cvcIcZlzB8xgUvuMEAG6vnjHjb7TYPeMXTe2Z8QINfqvVhoIZV/DshxiFzLhcgzp0fZnEjMfVc2bGtcGeYfeHLR68dZgy9Qwz3qSAfU2laPMPrS/gGfikzXMsK7q9JuRgj5bRVbIflZMjYL/XAoC+kv1+/UZQ9SNC+K5rvrgm9MDez2yI2XEl+zisE7A/L6rU0XE1VnRer61qk6+VNLIIAPLz86Gvr499+/Zh6NChqvUzZ86ETCbDmTPqr/u4uDh4eHjAzs4Ob968gaurKxYvXgwPj/+9jzRp0gSzZ8/G7NmzVes2bNiAkJAQPHzI/s5TXjRskhBSaQoE7C9n181smPEXgor3niq12B+0ujxfavJ4vrAAQJvJt5nx837sD2ITIyveMjobPWbGhWD/7sbXOOtpPpO3DleUh5nxPk9vMuOHG7dixhNNG/HWQR/sL4h8x4Gvcaan5P+Sy9fgz9fgmuFz36QBM67geW3xfcEU8RwnTfLgO9ZinmOZJWC/LgBAZl760CVNaPE03npOYF+zmniqbcqMKyvhy75VQSYznqxdjxnna9wBFT/fmjTO+Mgr+PzXymhYVUYefHLBPlZ8P/AUKHnOZ02OXKzB562VNPna0qVLERQUpJb233//hVwuV7v9xsLCQu2WkyJWVlbYvn072rZti7y8PPz000/o0aMH4uLi0LVrVwBAampqmfKsDNR4I9WutGF/AHD8+HF06dKlGmsD9OvXr9QbVhctWoRFixZVa30IIYQQQghbQEAA/P39OetK6nV7V/F5BZRKZalzDTg7O3OeX9yxY0c8fvwY3377rarxVtY8KwM13ki1Kz4pyrsaN25cfRX5fzt27EBubm6JMXNz82quDSGEEEJI7aCowUcFlDZEsiT169eHSCRS6xF7/vx5iZPhlaZDhw7YtWuX6m9LS8sK51lW1Hgj1a48z5mrSjXRYCSEEEIIIdVDR0cHbdu2xa+//sq55+3XX3/F4MGDNc4nPj4eVlb/u/WhY8eO+PXXXzn3vJ08eRKdOnWqnIqXgBpvhBBCCCGEkDJT1OA9b2Ut2d/fH6NHj8bHH3+Mjh07Yvv27Xj06BGmTJkC4O0wzKdPn2Lnzp0A3s4kaWdnBzc3N+Tn52PXrl2Ijo5GdHS0Ks+ZM2eia9eu+PrrrzF48GAcOnQIp06dKtMM62VFjTdCCCGEEELIB83LywsvX77E8uXLkZKSAnd3dxw7dkz1KKqUlBQ8evRIlT4/Px9z587F06dPoaenBzc3N/z888/o37+/Kk2nTp2wd+9eLF68GP/9739hb2+PyMjIKnvGG0CNN0IIIYQQQkgdMG3aNEybNq3EmFQq5fw9f/58zJ8/nzfP4cOHY/jw4ZVRPY1Q440QQgghhBBSZjU5YUldVXMDVQkhhBBCCCGEaIx63gghhBBCCCFlJhdRP1B1o8ZbLePn54fw8HC19ffu3cPKlSuRnp6OmJgYZh5PnjxBs2bN0KxZM9y5c0ctrlQqsWPHDoSGhuLWrVtQKBSwtbVFz549MX36dI2n+s/MzMTXX3+N6OhoJCcnw9TUFO7u7pg2bRqGDh2qeoDhrVu3sGzZMsTGxiIzMxNNmjSBt7c3AgICoK+vr8rPzs4ODx8+xKVLl9ChQwfV+lmzZkEmkyEuLk6VpjTdunVDXFwcs95FeURERMDb25sTc3NzQ2JiIsLCwuDn56daf/HiRaxcuRKXLl1Cbm4uHB0d4efnh1mzZkEkEqnSvfvQRpFIhEaNGmH48OEIDg5WPatEKpVi1qxZSE9PL/Hv4kq7Jvr06YMTJ04w9/VdQig1TluaAp63lDyBNjMu0qAOeshnxhUVHFAg0mD71vqp7AT67HA69HjLMOLdT/ZQlbNmjsz4FeVh3joECgYx48uVR5lxvmsqXcB/HCp6XeZChxnnuyYB/mNdGXK02fXkowVFJdWk/AoE7NeOJucyU6BboTzywD6fTjr/8tahkOc9gK8MTd7H+M7XI+2KPWM0TcnzJgRAoWRf16bCkp9/WoTvOGlyTb5WGjDjBoICZpz/ehAx4wCgXcHXjibvD3zHQgw5M24ozChTnciHjZrLtVDfvn2RkpLCWZo2barx9lKpFCNHjkROTg4uXLjAiSmVSnz++eeYMWMG+vfvj5MnT+L69evYtGkT9PT0sHLlSo3KSE9PR6dOnbBz504EBATg2rVrOHv2LLy8vDB//nxkZLx9I7p8+TLat2+P/Px8/Pzzz0hKSsLq1asRHh6OXr16IT+f+wVWV1cXCxYsKLXcq1evqo5J0VSud+/eVa07cOCARvW3sbFBWFgYZ93ly5eRmpoKAwPuh83BgwfRrVs3WFtbIzY2Fnfu3MHMmTOxatUqeHt7Q6nkfriEhYUhJSUFDx48wObNm/HTTz9pfFxLU9I1ERERUaE8CSGEEELI+4V63mohsVgMS0vLcm2rVCoRFhaGzZs3w9raGhKJBJ07d1bFIyMjsXfvXhw6dAiDBv3vV/dmzZqhR48eag2R0ixatAjJyclISkpCo0aNVOudnJzg4+MDXV1dKJVKTJgwAc2bN8eBAwcg/P9nhdja2sLJyQmtW7fGhg0bOI21yZMnY8uWLTh27BhnqtYiDRo0UP3f3PztL5cNGzaEqampZgfo/40aNQobNmzA48ePYWNjAwAIDQ3FqFGjVM//AIDs7GxMmjQJgwYNwvbt21XrJ06cCAsLCwwaNAhRUVHw8vJSxUxNTVXnz8bGBoMGDcK1a9fKVL/iKnJNEEIIIYSUB01YUv2o562OiY2NRU5ODnr27InRo0cjKioKr1+/VsUjIiLg7OzMabi9691hf6VRKBTYu3cvRo0axWm4FTE0NISWlhZkMhkSExPh7++vargVadmyJXr27KnWe2RnZ4cpU6YgICAACkXVDROysLBAnz59VMMRc3JyEBkZifHjx3PSnTx5Ei9fvsTcuXPV8hg4cCCcnJyYPWBJSUmIjY2t0ueBEEIIIYSQDwM13mqho0ePwtDQULWMGDFC420lEgm8vb0hEong5uYGBwcHREZGquJJSUlwdnbmbDNr1ixVWdbW1rxl/Pvvv3j16hVcXFyY6ZKSkgAAzZs3LzHevHlzVZp3LV68GA8ePMDu3bt561IR48ePh1QqhVKpxP79+2Fvb49WrVpx0vDtg4uLi9o++Pj4wNDQELq6unB2doabmxsCAgIqVNfi14ShoSFWrFhRavq8vDxkZmZylsI89r0FhBBCCCHvUgqFNbbUVXV3z2sxDw8PyGQy1bJp0yaNtktPT8eBAwfg6+urWufr64vQ0FBOuuK9a4GBgZDJZFiyZAmysrJ4yykaWqlJLx1fPiXl0aBBA8ydOxdLlixRuyeuMg0YMABZWVk4e/YsQkND1Xrdite1tPXF92HDhg2QyWRISEjA0aNHkZSUhNGjR1eorsWvCZlMhi+//LLU9MHBwTAxMeEs54KjKlQHQgghhBBSteiet1rIwMBA4xkf37Vnzx68efOGM0RPqVRCoVAgMTERrq6ucHR0VJuBskGDBmjQoAEaNmyoUTkNGjSAmZkZbt++zUzn5OQEAEhMTFTr0QKAO3fuwNGx5Bnz/P39sXnzZmzevFmjOpWHlpYWRo8ejaVLl+LKlSs4ePCgWpqifbh9+zY6deqkFr9z5w5cXV056ywtLVXnz9nZGa9fv4aPjw9WrlxZrvMKlP2aCAgIgL+/P2fdt+LT5SqbEEIIIXUT3fNW/ajnrQ6RSCSYM2cOp3cmISEBHh4eqt43Hx8f3L17F4cOHSp3OUKhEF5eXti9ezeePXumFs/OzkZhYSFatWoFFxcXbNiwQe3+tYSEBJw6dQo+Pj4llmFoaIj//ve/WLVqFTIzM8tdVz7jx4/HmTNnMHjwYJiZmanFe/fuDXNzc6xbt04tdvjwYdy7d6/UfShS9CiB3Fz2tMyVSSwWw9jYmLNoifmnTCeEEEIIITWHet4+MBkZGZDJZJx15ubmSEtLw7Vr17B79261e9F8fHwQGBiI4OBgeHt748CBA6rnrPXp0wcWFhZ4+PAhIiMjOc8sY1m9ejXi4uLQvn17rFq1Ch9//DG0tbVx7tw5BAcH4+rVqzA1NcWOHTvQu3dvDBs2DAEBAbC0tMSVK1cwZ84cdOzYEbNmzSq1jC+++AIbNmxARERElU340bx5c/z777+c5829y8DAANu2bYO3tze++OILfPXVVzA2NsZvv/2GefPmYfjw4Rg5ciRnm/T0dKSmpkKhUODevXtYvnw5nJycSr1vDgDkcrnaedXR0VH16uXl5SE1lfvsMS0tLdSvX78ce00IIYQQQt5H1Hj7wMTFxaF169acdWPHjoWRkRFcXV1LnERkyJAhmDp1Ko4cOYL//Oc/iIyMxI8//oiwsDCsXbsWBQUFsLa2Ro8ePbB+/XqN6mFmZobLly9jzZo1WLlyJR4+fAgzMzN89NFH+Oabb2BiYgIA6Ny5My5fvoxly5ahf//+qod0jx07FgEBAaoHV5dEW1sbK1aswOeff16GI1R29erVY8aHDx+O2NhYrF69Gl27dkVubi4cHBwQGBiIWbNmqd3zNm7cOABv7wm0tLRE165dsXr1amhplf5yzMrKUjuvtra2SE5OBgCcOHECVlZWnLizs3OJD2EnhBBCCKkMNGyy+gmUmj64ixDyQVuOnyucx5sK/h6ki0LeNNo8aeRg9w7rKtmzahoo8njrkC0s/UcFAHgjYA9Bfa4w5C2jsTCdGc8Du4w8nuMw9Gk8bx2ONW7BjC8ReDLjK5VHmPF8njoCwEtFyb3emnIU/MuMZwp0K5S/JjKU7OsFAIRgfxRrC9iPRlGA/QWKL//KyMNS+ZoZTxPwn0u+OmiBfRzMFdnMeLqwYtcTUD3HujrqoEmaiqjoPgL8deQrozLqUBn0wJ5cLRvs9wi+98o16F3mOlWW9Eszaqxs046aTdj3oaGeN0IIIYQQQkiZKerwlP01hY44KZfizxR7dzl37lxNV69Uu3fvLrXebm5uNV09QgghhBBCSkU9b6Rcik+e8a7GjRtXX0XKaNCgQaVObqKtTbMtEkIIIYSQ9xc13ki5lPd5ZDXNyMgIRkZGNV0NQgghhJBajyYsqX40bJIQQgghhBBCagHqeSOEEEIIIYSUmVxA/UDVjY44IYQQQgghhNQC1HgjhBBCCCGEkFqAhk0SQgghhBBCyowmLKl+1Hgj7yU/Pz+Eh4errb937x5WrlyJ9PR0xMTEMPN48uQJmjVrhmbNmuHOnTtqcaVSiR07diA0NBS3bt2CQqGAra0tevbsienTp2s0o2ZQUBCWLVumtt7Z2VlVZvfu3XHmzBkEBwdj4cKFnHT9+/fH8ePHsXTpUgQFBXFie/bswejRozFp0iRs3bqVE4uLi4OHhwdevXoFU1NTtb9rig7kzLg2T1yLJw4AhRAx46aKHGY8Q6jHLkCD8Qj3FfWYcV1hATPeWJjOW0YG2PXURSEz3kCZzYwfbtyKtw5CKJnxlcojzPhiwUBmfJXyMG8ddAXsY8knV8D+mBNBwZuHUIM0LGYC9nEEAAXYX4D44u+D1wIxM853PQGAFs+x5jsOaUIDZvy1Uoe3DkaCfGZcm+e1J+d5j9JERc93ZVwvFb0mNTnflZFHRVW0DE3eQ/j2k++z01SZyy7g/X97IJWIhk2S91bfvn2RkpLCWZo2barx9lKpFCNHjkROTg4uXLjAiSmVSnz++eeYMWMG+vfvj5MnT+L69evYtGkT9PT0sHLlSo3LcXNzU6vn+fPnOWlsbGwQFhbGWffs2TOcPn0aVlZWJeYbGhqK+fPnY+/evcjJYTdICCGEEEKqm0IoqLGlrqKeN/LeEovFsLS0LNe2SqUSYWFh2Lx5M6ytrSGRSNC5c2dVPDIyEnv37sWhQ4cwaNAg1fpmzZqhR48eUCo1/yVOS0uLt56enp6IiorChQsXVPWQSqXo3bs3Hj16pJY+OTkZFy9eRHR0NGJjY7F//36MGTNG4zoRQgghhJAPD/W8kQ9SbGwscnJy0LNnT4wePRpRUVF4/fq1Kh4REQFnZ2dOw+1dAkHl/qKjo6ODUaNGcXrfpFIpxo8fX2L60NBQDBgwACYmJvD19YVEIqnU+hBCCCGEVJRSKKyxpa6qu3tO3ntHjx6FoaGhahkxYoTG20okEnh7e0MkEsHNzQ0ODg6IjIxUxZOSkuDs7MzZZtasWaqyrK2tNS7rxo0bnHoaGhpi4sSJaukmTJiAqKgoZGdn4+zZs8jIyMCAAQPU0ikUCkilUvj6+gIAvL29cenSJfz1118a14kQQgghhHx4aNgkeW95eHhgy5Ytqr8NDNg3ohdJT0/HgQMHOPed+fr6IjQ0lNOoKt67FhgYiK+++goHDhzA6tWrNa6ns7MzDh/mTrxgZGSklq5FixZwdHTE/v37ERsbi9GjR0NbW1st3cmTJ5GdnY1+/foBAOrXr4/evXsjNDS0TPViycvLQ15eHmddobgAWmL1+hBCCCGEkPcDNd7Ie8vAwECjGR+L27NnD968eYP27dur1imVSigUCiQmJsLV1RWOjo5qM1A2aNAADRo0QMOGDctUno6Ojsb1HD9+PH744QckJibi999/LzFNaGgo0tLSoK+vr1qnUCgQHx+PFStWQCSq+ExmwcHBarNkdl/qA4+gURXOmxBCCCF1Q12eOKSm0LBJ8sGRSCSYM2cOZDKZaklISICHhwdCQ0MBAD4+Prh79y4OHTpUrXX7/PPPcePGDbi7u8PV1VUt/vLlSxw6dAh79+7l1F8mkyErKwvHjx+vlHoEBAQgIyODs3QJGFkpeRNCCCGEkKpBPW+kVsrIyIBMJuOsMzc3R1paGq5du4bdu3fDxcWFE/fx8UFgYCCCg4Ph7e2NAwcOwNvbGwEBAejTpw8sLCzw8OFDREZGlql3q7CwEKmpqZx1AoEAFhYWamnNzMyQkpJS4nBJAPjpp59Qr149jBgxAsJiN+N6enpCIpHA09Oz1LrcuHFDbchmq1at1NKJxWKIxdxnMmmBhkwSQgghRHOKOjxxSE2hxhupleLi4tC6dWvOurFjx8LIyAiurq5qDTcAGDJkCKZOnYojR47gP//5DyIjI/Hjjz8iLCwMa9euRUFBAaytrdGjRw+sX79e47rcunVL7VltYrEYb968KTE96yHaoaGhGDp0qFrDDQCGDRsGLy8v/PPPP6Vu37VrV7V1ZXnsASGEEEIIeX8JlPTNjhACYDl+rnAeCrDHvmtDzoxr8cQBoBDsXlETRS4zniHUY8bFykLeOtxX1GPGdYUFzLiF4DUzDgAZYNdTF+x6GitL/vGgSJpAnxkHACHYHw9aUDDjiwUDmfFVysPMOACkKdnHgU99QTYzrtDg7gEhz37ykfNcs2/rwX7t8MXfB3yvb7lGx5p9zVX0OLxW6vCmMRLkM+PaPK+92nK+K3qs+eJ8+VdWHhVV0TJEGrw/8L2H8F0z+kr2Nekv+A9vHapKcuKiGivbzrVyJnGrbajnjRACoHK+LPB9mQ9s9QUzvkq2nbcMI2UebxoWA54PwecCQ948ZC/Yk9oYiNmNt0/F93nLuK3PfvA73xdh9/SnzHiiaSPeOqQL2A2nfJ4vHHyNs0BByc9ZfFewMoY3DUsu2F/W5Rpc92KeRkllfME0V7AbmXxeC8XMeJ4Gw6LFYF+3fHnwf0Hlb7xV9EcHvvexx3mmvHVw0X3BjOvx/MCTLqj4EHS+/eB7r9VEIc/54CuDL67JZ0pVN84q43ONvxGrSWOd/XWb7zj8K9Bstu2aoKjk5+ISfjRQlRCG4s9ve3c5d+5cTVePEEIIIYTUIdTzRghD8UlR3tW4cePqqwghhBBCyHuGHhVQ/ajxRghDeZ4zRwghhBBCSFWgxhshhBBCCCGkzOhRAdWPjjghhBBCCCGE1ALUeCOEEEIIIYSQWoCGTRJCCCGEEELKTE6PCqh21PNGCCGEEEIIIbUA9bwRQgghhBBCyowmLKl+1HirJH5+fggPDwcAiEQiNGrUCAMGDMDq1athZmYGALCzs8PDhw/Vtg0ODsbChQtVf0dHR+OHH35AfHw88vLyYGNjg86dO2P69Olo3bo1AEAqlWLWrFlIT09XbZebm4s1a9Zg7969SE5OhpGREbp3745ly5bBzc1NlS4oKAjLli3D5MmTsXXrVtV6mUyG1q1b48GDB7Czs2Pub3JyMpo2bar629jYGM2bN0dgYCAGDhyoln716tX473//i1WrVqn2tbTjUaRbt26Ii4uDnZ0dZs2ahVmzZnG2u3TpEjp06KBKP2vWLMhkMsTFxanWZWZm4ptvvsGBAwdw//596Ovro1mzZhgxYgQmTZqkOjd8/vrrL6xatQq//vorXrx4gUaNGqFDhw6YM2cOPv74YwCAQCDAwYMHMWTIELXt4+Li4OHhgVevXsHU1FT1d0lSUlJgaWmp0XmSSqVYtmwZs+6anM/KYqjMY8aDZVuZ8WcKY94y8hUiZrxAyY5rC+TM+O4Dbsw4AMwdeZkZNwD7OKRosJ/yCg6MOGXmwozro4A3DyGUzPhLhT4zritglxGsjOGtQ4BgCDtBPT1muMONeGa8i+Uj3jo8LjBlxuVK9rChFuIU3jLShexjmcvzcW2MN8y4FhS8deA739pgv3ZeQ5cZ10Uhbx0UqNohWB/ppvKm4Xvt3VPWZ8aNBOzXP6DZsWDhO05vquHrHd/1ogm+/eArozLqUFGa1CFdyX6fMhfkMOOavF+TuoOay5Wob9++SElJQXJyMnbs2IEjR45g2rRpnDTLly9HSkoKZ5k+fboqvmDBAnh5eaFVq1Y4fPgwbt26he3bt8Pe3h6LFi0qtey8vDz07NkToaGhWLFiBZKSknDs2DHI5XK0b98ely9zv2zq6upCIpEgKSmpQvt86tQppKSk4MqVK2jXrh2GDRuGmzdvqqULCwvD/PnzERoaqlp39epV1TGIjo4GANy9e1e17sCBA6WWq6uriwULFjDrlpaWhg4dOiAsLAxz587FlStXcOHCBSxduhQymQx79uzRaB//+OMPtG3bFklJSdi2bRsSExNx8OBBuLi4YM6cORrlUZp397doadiwIWc/Wedp7ty5nG2tra3VrjEbG5sK1ZEQQgghhLwfqOetEonFYlhaWgIArK2t4eXlBalUykljZGSkSlPc5cuXsXbtWmzcuBEzZsxQrW/atCm6desGpbL0X3dCQkJw6dIlxMfHo2XLlgAAW1tbREdHo3379pgwYQJu3rwJwf/fWOrs7IyGDRti8eLFiIqKKvc+16tXD5aWlrC0tMSqVavw3XffITY2Fu7u7qo0Z86cQW5uLpYvX46dO3fi7Nmz6Nq1Kxo0aKBKY25uDgBo2LAhTE1NecudPHkytmzZgmPHjqF///4lplm0aBEePXqEu3fvonHjxqr1Li4u8PT0ZB7PIkqlEn5+fnB0dMS5c+cgfGd4QKtWrTBz5kzePFj49pfvPBkaGsLQ0FD1t0gkYl5jhBBCCCGVRUkTllQ76nmrIvfv38eJEyegra2t8TYREREwNDRU660rImC8QPbs2YNevXqpGm5FhEIhZs+ejcTERCQkJHBia9asQXR0NK5evapxHUtTUFCAH3/8EQDU9lkikcDHxwfa2trw8fGBRCKpcHl2dnaYMmUKAgICoFCoDwdSKBSIjIyEr68vp+H2LtbxLCKTyXDr1i3MmTOH03AroklDs6Iq8zwRQgghhJDaixpvlejo0aMwNDSEnp4e7O3tkZiYqDa0b8GCBarekqKl6B6tpKQkNGvWDFpa/+sQXb9+PSdtRkZGiWUnJSWhefPmJcaK1hcfetemTRuMHDmSc79dWXXq1AmGhobQ1dXFnDlzYGdnh5EjR6rimZmZiI6Ohq+vLwDA19cX+/fvR2ZmZrnLLLJ48WI8ePAAu3fvVou9ePEC6enpcHZ25qxv27at6lj6+PjwlnHv3j0Ab3vrqoK1tTXn/BavL1A556m4vLw8ZGZmcpbCPBpTTwghhBDNKYSCGlvqKmq8VSIPDw/IZDJcuXIF06dPR58+fTj3swHAvHnzIJPJOEv79u1V8eK9QePHj4dMJsO2bduQnZ2t0VC/4oq2KamnaeXKlTh37hxOnjxZ5nwBIDIyEvHx8Th8+DAcHBywY8cO1RBI4G2PYLNmzVQ9gq1atUKzZs2wd+/ecpX3rgYNGmDu3LlYsmQJ8vPzS0xTfJ8PHjwImUyGPn36IDc3l7cM1rGrDOfOneNcC7/88kuJ6Sp6nooLDg6GiYkJZzkfXP7hs4QQQgghpOpR460SGRgYwMHBAS1atMCmTZuQl5enNhNg/fr14eDgwFn09N7OQuTo6Ii///4bBQX/6wExNTWFg4NDqUP/ijg5OSExMbHE2J07d1T5F2dvb49JkyZh4cKF5WoY2tjYwNHREQMGDMCOHTvg5eWF58+fq+KhoaG4desWtLS0VMutW7cqZegkAPj7+yM3NxebN2/mrG/QoAFMTU1V+16kSZMmcHBwgJGRkUb5Ozk5AQBu375dKfUtrmnTppxrobRZISt6nooLCAhARkYGZ/k0YCT/hoQQQggh/08hENbYUlfV3T2vBkuXLsW3336LZ8+eaZTex8cHWVlZag0RTXh7e+PUqVNq97UpFAps2LABrq6uavfDFVmyZAmSkpIq3BvWrVs3uLu7Y9WqVQCAGzdu4I8//kBcXBynd+ns2bO4evVqibNSlpWhoaHqEQTvDsUUCoUYOXIkdu3ahadPn5Y7/1atWsHV1RXr1q0r8d66dx/VUNUq6zwBbyfXMTY25ixaYs3vzySEEEIIIdWPGm9VqHv37nBzc8Pq1atV616/fo3U1FTOUtTo6NixI+bMmYM5c+bA398f58+fx8OHD3H58mVIJBIIBIISJ80AgNmzZ6Ndu3YYOHAg9u3bh0ePHuHq1asYNmwYbt++rdq+JBYWFvD398emTZsqvM9z5szBtm3b8PTpU0gkErRr1w5du3aFu7u7avn000/RsWPHSut9++KLL2BiYoKIiAjO+tWrV6Nx48Zo3749QkNDcf36dfz99984ePAgLl26BJGI/Tww4O1wybCwMCQlJaFr1644duwY7t+/j+vXr2PVqlUYPHgwJ/2DBw/UhsVmZWWVmv/z58/Vrod3e17fVZnniRBCCCGE1D7UeKti/v7++PHHH/H48WMAb3tPrKysOMv8+fNV6b/99lvs2bMH8fHx8PT0hKOjI0aMGAGFQoFLly7B2Ljkh/vq6uri9OnTGDt2LBYtWgQHBwf07dsXIpEIly9f5jzMuiTz5s3jTDlfXp6enrCzs8OqVauwa9cuDBs2rMR0w4YNw65du0q9V60stLW1sWLFCrx5w31Ibb169fD7779jzJgx+Oabb9CuXTt89NFHCAoKgpeXl2p2TD7t2rXDH3/8oRq62Lx5cwwaNAi3bt1CSEgIJ62/vz9at27NWf74449S83Z2dla7Hv78889S01fWeSKEEEIIqSiasKT6CZSVcQMNIaTWC8KxCudhqmRPApMrYD9a8rHcjLeMPCW7x/SNnF2GrqiQGY844Mpbh7kjLzPjBshjxxX8P1qkCQ2YcQXYH1xveB7jaYiK/3CSomDfO6orYM9gWl+QzVtGQH2eWWFfsq+5rs9vMePt6/MPq/6ngL2fciX7XLTW4R86X8Bz/0Ye2MOaxWAfazn4RxqIIGfGFTy/92ZDhxnX4ckfAMyVOcx4mkCfGS/gqaM+z3ECADlPHqly9vVgLHrDjAOALtjvQ3yvbyHYX934Xv+a4DtffHXQREX3ky/Ol39l5KHJcUhTsq9bcwH7uucrYzE8eetQVa49Wc2fqIq0sV5UY2XXJHpINyGEEEIIIaTMFPSQ7mpHwyZJiaZMmaL2PLqiZcqUKTVdvUpz7ty5UveThicSQgghhJD3CfW8kRItX74cc+fOLTFW2n13tdHHH38MmUxW09UghBBCCCGEFzXeSIkaNmyIhg0b1nQ1qpyenh4cHBxquhqEEEIIIbWOvJRZ0EnVoSNOCCGEEEIIIbUA9bwRQgghhBBCyowmLKl+1PNGCCGEEEIIIbUA9bwRQgghhBBCyox63qof9bwRQgghhBBCSC1AjTdCCCGEEEIIqQVq3bBJPz8/pKenIyYmhrM+Li4OHh4eePXqFUxNTSGXy7Fp0yaEhYUhKSkJurq66NixIxYvXozOnTurtgsKCkJMTIzas77S09NhZmaG2NhYdO/eHcnJyWjatKkqbmxsjObNmyMwMBADBw4s0z7k5uaiUaNGEAgEePr0KfT09DhxOzs7PHz4EMDbqeybNWuG6dOnY/LkyQAAqVSKcePGqdJbWlqiS5cu+Prrr1V1fDcPXV1d2NraYsKECZg7dy4EGnRxF99fU1NTfPTRR1ixYgW6desG4O25CA8PBwCIRCI0atQIAwYMwOrVq2FmZsbJ7+LFi1i5ciUuXbqE3NxcODo6ws/PD7NmzYJIJOKkjY2NxTfffIMrV64gNzcXdnZ26NevH/z9/dG4cWPVuS5JSkoKLC0tkZ2djeXLl2Pfvn149uwZjIyM4Obmhrlz58LT0xMAcP/+fQQGBuLMmTNIS0tD/fr10bZtW3zzzTdwcnLiPUaxsbFYvnw5EhIS8ObNGzRu3BidOnWCRCLBxIkTVcemNEqlEgCwZ88ejB49GpMmTcLWrVs5aYrvq7m5OVq2bIkVK1agc+fOnPNckm7duiEuLo53XwBACKVG6VieC9gPNteBnBm3FaXxlqGtVLATiNhhvv3sN/A2bx1Oy9nXx78wYMbri7J5y8jn2RFdFDLjtnL2scwU6fLWIRc6zLij4F/29gL2Rwxf/gDQ4UY8M66jxb6mzjZ0Y8ZDFPt562Cr9YoZLxSwz1W2gH8/+WiBfd3zHUtNXt981xwffRQw44Ua/F78r4D92uE7DobIY8b/UfI/p9RckMOM871PFWpwHAt40vC9VyrA/hw3QS5vHRQ850PJU4aA55qSa3C+tXn2U5M8WDS57vN4zoW4gucCAKwEGcw43+v3zXv8dV1Jjwqodh/kEVcqlfD29sby5csxY8YM3L59G2fOnIGNjQ26d++u1vAri1OnTiElJQVXrlxBu3btMGzYMNy8ebNMeURHR8Pd3R2urq44cOBAiWmWL1+OlJQUXL9+HUOGDMGUKVMQGRmpihsbGyMlJQXPnj3Dnj17IJPJMGjQIMjlcrU8bt++jblz52LRokXYvn17ufb3zJkzMDY2Rv/+/fHgwQNVvG/fvkhJSUFycjJ27NiBI0eOYNq0aZw8Dh48iG7dusHa2hqxsbG4c+cOZs6ciVWrVsHb21vViAGAbdu2oWfPnrC0tER0dDQSExOxdetWZGRkYN26dZx87969i5SUFM5S9Gy6KVOmICYmBt9//z3u3LmDEydOYNiwYXj58iUAID8/H7169UJmZiYOHDiAu3fvIjIyEu7u7sjIYL/JAsCtW7fQr18/fPLJJzh79ixu3LiB7777Dtra2lAoFNi4cSOnXgAQFhamtg4AQkNDMX/+fOzduxc5OSV/aSja17i4ODRo0AADBgzA8+fPcfXqVVV+0dHRaseltOuLEEIIIaSu2bx5M5o2bQpdXV20bdsW586dKzXtgQMH0KtXLzRo0ADGxsbo2LEjfvnlF04aqVQKgUCgtrx586bK9uH9bcpXQFRUFPbv34/Dhw9zesW2b9+Oly9fYuLEiejVqxcMDNi/8JWkXr16sLS0hKWlJVatWoXvvvsOsbGxcHd31zgPiUQCX19fKJVKSCQSjBo1Si2NkZERLC0tAQArV65EVFQUYmJi4OXlBQAQCASquJWVFZYuXQpfX1/89ddfcHZ2Vstj4sSJ2LJlC06ePKnqwSvr/m7btg3W1tacPMRisaoMa2treHl5QSqVqrbPzs7GpEmTMGjQIE7DceLEibCwsMCgQYMQFRUFLy8vPHnyBDNmzMCMGTOwYcMGVVo7Ozt07doV6enpnLo1bNgQpqamJdb7yJEj2LhxI/r376/Ko23btqp4YmIi7t+/j9OnT8PW1hYAYGtry+mVZfn1119hZWWFtWvXqtbZ29ujb9++AAAdHR2YmJhwtjE1NVUdqyLJycm4ePEioqOjERsbi/3792PMmDFq5RXtq6WlJRYvXoyoqChcuXKFc32bm5vzHhdCCCGEkMpSmyYsiYyMxKxZs7B582Z07twZ27ZtQ79+/ZCYmIgmTZqopT979ix69eqF1atXw9TUFGFhYRg4cCCuXLmC1q1bq9IZGxvj7t27nG11dflHt5TXB9nztmfPHjg5OZU4nHHOnDl4+fIlfv311wqVUVBQgB9//BEAoK2trfF2f//9Ny5duoSRI0di5MiRuHjxIu7fv8+7na6uLgoKSh+SUjT0sqQ0SqUScXFxuH37dpnqWpy+vn6pZQBvhyGeOHGCU8bJkyfx8uVLzJ07Vy39wIED4eTkhIiICADAvn37kJ+fj/nz55eYf1kaJJaWljh27Bhev35dYrxBgwYQCoXYv38/p7eyLPmnpKTg7NmzZd72XaGhoRgwYABMTEzg6+sLiUTCTJ+Tk4OwsDAAZbvuCCGEEELqsvXr12PChAmYOHEimjdvjpCQENjY2GDLli0lpg8JCcH8+fPxySefwNHREatXr4ajoyOOHDnCSVfUofLuUpVqZePt6NGjMDQ05Cz9+vVTxZOSktC8efMSty1an5SUVK6yO3XqBENDQ+jq6mLOnDmws7PDyJEjNd4+NDQU/fr1g5mZGczNzdG3b1+EhoaWmr6wsBBSqRQ3btxAjx49Skzz5MkTfPPNN7C2tubcq7VgwQIYGhpCLBbDw8MDSqUSM2bM0Hxn35GdnY2AgACIRCLVPW/A/86Fnp4e7O3tkZiYiAULFqjiRce5tPPh4uKiSnPv3j0YGxvDyspKozpZW1tzroGiHkfgbS/rxYsXUa9ePXzyySeYPXs2Lly4oIo3btwYmzZtwpIlS2BmZobPPvsMK1as0KghDQAjRoyAj48PunXrBisrKwwdOhTff/89MjMzNdoeABQKBaRSKXx9fQEA3t7euHTpEv766y/mvm7YsAFt27Yt9XrQRF5eHjIzMzlLYR77fhVCCCGEkPdFSd9l8vJKvu81Pz8ff/75J3r37s1Z37t3b1y8eFGj8hQKBV6/fq0a6VQkKysLtra2sLa2hqenJ+Lj2fdqV1StbLx5eHhAJpNxlh07dpQpD00m7ShJZGQk4uPjcfjwYTg4OGDHjh1qJ7E0crkc4eHhqi/rAODr64vw8HC13p+ihpeenh6+/PJLzJs3jzPcMSMjA4aGhjAwMICNjQ3y8/Nx4MAB6Oj876bXefPmQSaT4cyZM/Dw8EBgYCA6depUpv0taqwaGRnhyJEjkEql+Oijj1TxonNx5coVTJ8+HX369MH06dPV8nn3vrbi64vOxbv/18S5c+c418C745C7du2K+/fv47fffsOwYcNw69YtdOnSBStWrFCl+fLLL5Gamopdu3ahY8eO2LdvH9zc3DTqlRWJRAgLC8OTJ0+wdu1aNGrUCKtWrYKbmxvnfjaWkydPIjs7W/XDQ/369dG7d+8SG/Pnzp3DtWvXEBERAVtbW0il0gr1vAUHB8PExISznAuOKnd+hBBCCKl7FAJBjS0lfZcJDg4usZ7//vsv5HI5LCwsOOstLCyQmpqq0b6uW7cO2dnZnE4bFxcXSKVSHD58GBEREdDV1UXnzp1x79698h9UHrXynjcDAwM4ODhw1j158kT1fycnJyQmJpa47e3bb2eSc3R0BPB2nGpJE1QU3V9V/L4lGxsbODo6wtHREYaGhhg2bBgSExNVE2Ww/PLLL3j69KnqvrUicrkcJ0+e5PQezps3D35+ftDX14eVlZVao8bIyAjXrl2DUCiEhYVFiffv1a9fHw4ODnBwcEB0dDQcHBzQoUMH9OzZk7euRSIjI+Hq6gpTU1PUq1dPLf7uudi0aRM8PDywbNkyVSOpqCfw9u3bJTYc79y5A1dXV1XajIwMpKSkaNT71rRpU+ZQSm1tbXTp0gVdunTBwoULsXLlSixfvhwLFixQNXKNjIwwaNAgDBo0CCtXrkSfPn2wcuVK9OrVi7d84G0P3ujRozF69GisXLkSTk5O2Lp1K5YtW8a7bWhoKNLS0lTDUYG3v+rEx8djxYoVnFk4i/bVyckJb968wdChQ3Hz5k2IxWKN6llcQEAA/P39Oeu+FZ8uV16EEEIIIdWtpO8yfN+Lin+f1rTjICIiAkFBQTh06BDnO3+HDh3QoUMH1d+dO3dGmzZt8N1332HTpk2a7EaZ1cqeNz7e3t64d++e2phU4G2ruV69eqov5y4uLnjy5Ilaq/vq1asQCoVqjcR3devWDe7u7li1apVG9ZJIJPD29lbrNRw1apTavU5FDa+iRwoUV1S3Zs2aaTTxipmZGaZPn465c+eW2gtWEhsbG9jb25fYcCvJ0qVL8e233+LZs2cA3nZHm5ubq80UCQCHDx/GvXv34OPjAwAYPnw4dHR0OJOAvKv4hCVl5erqisLCwlJnABIIBHBxcUF2Nv807iUxMzODlZWVRtu/fPkShw4dwt69e9Wuh6ysLBw/frzUbUePHg2FQoHNmzeXq57A2zc3Y2NjzqIlpnvoCCGEEKK5mux5K+m7TGmNt/r160MkEql933/+/Llab1xxkZGRmDBhAqKiong7QIRCIT755JMq7Xn7YBtvQ4cOxdixYyGRSJCcnIzr169j8uTJOHz4MHbs2KFq8PTu3RvNmzeHt7c3Lly4gAcPHuDQoUOYO3cupkyZAiMjI2ZZc+bMwbZt2/D06VNmuhcvXuDIkSMYO3Ys3N3dOcvYsWNx+PBhvHjxotKOQUm+/PJL3L17VzWlfFXo3r073NzcsHr1agBve+a2bduGQ4cO4YsvvsD169eRnJwMiUQCPz8/DB8+XNX9bGNjgw0bNmDjxo2YMGECzpw5g4cPH+LChQuYPHkyZ8gj8PYFl5qaylmKJlPp3r07tm3bhj///BPJyck4duwYFi1aBA8PDxgbG0Mmk2Hw4MHYv38/EhMT8ddff0EikSA0NBSDBw/m3c9t27Zh6tSpOHnyJP7++2/cunULCxYswK1btzR67t9PP/2EevXqYcSIEZxroUWLFvD09GROXCIUCjFr1iysWbOm1EcLEEIIIYSQt3R0dNC2bVu1W2N+/fVX5i1FERER8PPzw549ezBgwADecpRKJWQymcbzN5THB9l4EwgEiIqKQmBgIDZs2AAXFxd06dIFDx8+RGxsLIYMGaJKq6WlhZMnT6JZs2YYNWoU3NzcsHDhQkycOBHr16/nLcvT0xN2dna8vW87d+6EgYFBiZNMeHh4wMjICD/99FOZ97UsGjRogNGjRyMoKAgKBc+DjivA398fP/74Ix4/fgzgbY9abGwsHj9+jK5du8LZ2Rnr169HYGAg9u7dy+lZnDZtGk6ePImnT59i6NChcHFxwcSJE2FsbKw2Y6WzszOsrKw4y59//gkA6NOnD8LDw1WN86L78aKi3t7XZW1tDTs7Oyxbtgzt27dHmzZtsHHjRixbtgyBgYG8+9iuXTtkZWVhypQpcHNzQ7du3XD58mXExMRwJnQpTWhoKIYOHQphCQ+3HDZsGI4ePYp//vmn1O3Hjx+PgoICfP/997xlEUIIIYRUBYVAWGNLWfn7+2PHjh0IDQ3F7du3MXv2bDx69AhTpkwB8HYY5ruPa4qIiMCYMWOwbt06dOjQQdVR8O7tVsuWLcMvv/yC+/fvQyaTYcKECZDJZKo8q4JAWZYxdISQD1YQjlU4DyHYbyeFPL8X6SG/wnXQVrJ/mCjgecMv0OBW4DSlPjOuK2DP3GmCXN4yMqDHjOuDXYaYJ66nLOStQ7qAXQc+IrDPRQ74h+rmK0W8aVgagz0D7CzhcN48ss5+yYz/1OlTZrz7g9u8ZVyzacqMPxDXZ8Zzea5bEc9rEwDkYN/3wZdHPtjnShf819wbnv3gy0OrEq45vjK0eeIKDX4Xl/OkaVSofi/+u55omTLjfO/FmlDwXA98NKlDRT8zKqMO1bGfFa1DAc9xWIW+Fa5DeZ16VTX3dWmip1nZZ1DfvHkz1q5di5SUFLi7u2PDhg3o2rUrAMDPzw/JycmIi4sD8HYU15kzZ9TyGDt2rOqZxrNnz8aBAweQmpoKExMTtG7dGkFBQejYsWO594tPrZywhBBCCCGEEELKYtq0aZg2bVqJsaIGWZGiRhzLhg0bsGHDhkqomeY+yGGTNcXNzU3t+XNFy+7du2u6ehxTpkwpta5V2dVbW6xevbrU4/PurKCEEEIIIXVVTU5YUldRz1slOnbsmGrCjOL4ZrKpbsuXL1e7h6yIsbFxNdfm/TNlypRSH76up1exoWSEEEIIIYSUBzXeKpGtrW1NV0FjDRs21OjZdHWVubm5xg9fJ4QQQgipi+TCutsDVlNo2CQhhBBCCCGE1ALUeCOEEEIIIYSQWoCGTRJCCCGEEELKrDzPWyMVQ0ecEEIIIYQQQmoB6nkjhBBCCCGElJmyDk/ZX1PK1PPm5+cHgUAAgUAALS0tNGnSBFOnTsWrV69Uaezs7FRp3l3WrFnDySs6OhqfffYZzMzMoK+vD2dnZ4wfPx7x8fEa1UUqlXLyt7CwwMCBA3Hr1q1S6/zu0rcv92n08fHx8PLygpWVFcRiMWxtbeHp6YkjR45AqVQCAJKTkyEQCCCTyTjbhoeHo127djAwMICRkRG6du2Ko0ePctLExcVBIBDA3d0dcrmcEzM1NVV7MGBpio7v5cuXOetnzZqF7t27c9alpaVh1qxZsLOzg46ODqysrDBu3Dg8evRIlaakY/Pu4ufnx6xPhw4dMHXqVM66LVu2QCAQQCKRcNZPmDABnTp1Uv0tl8uxYcMGtGjRArq6ujA1NUW/fv1w4cIFznZlOddDhgzhrNu/fz90dXWxdu1a5n4AQFBQkKoMoVCIRo0aYdSoUXj8+DEnXffu3Us8VsWfjxcbGwtPT080aNAAurq6sLe3h5eXF86ePatKU3RdpKenl/u4FL+W09PTIRAINHq45LuEUFZ44aMDOXPRUxbyLmKlnLnoKfOZC9/2xso3vMsbhRZzeVmoz1w0OZYFSiFz4VOvMIe5aEIBAXPhv6YUzEUMOe/yT4FRhRYtpZy5ZJ39kncx7PoDc5nacS5zkdnY8i5W2enMpVXWY+aihIC5yDVYKpoH//XAf92LoGAufPj2Ikepw7vw4XuPqgxZIjFz4VMZ7+dV/XkA8L/HVLQMvvw1eR+rjDIq41gRUqTMwyb79u2LlJQUJCcnY8eOHThy5Ijak8qXL1+OlJQUzjJ9+nRVfMGCBfDy8kKrVq1w+PBh3Lp1C9u3b4e9vT0WLVqkcV2MjY2RkpKCZ8+e4eeff0Z2djYGDBiA/Pz8Euv87hIREaGKHzp0CB06dEBWVhbCw8ORmJiIffv2YciQIVi8eDEyMjJKrcPcuXMxefJkjBw5EgkJCfj999/RpUsXDP4/9u47LKpj/QP4d1lg6aCCgIoC0rFgTEQ0EVGKwQQ1ioIlEtRo4gUJ2JCISBTQn4rRxMRC0VykxGA3tgQsUYyJol6KoAlWuLFRFKm7vz98OJfDLucsLIjo+3meeR49M+fMewoLszNnZtw4fPPNN1Llb968iV27dsl9jrKoqalhyZIlnGUeP36MoUOH4uTJk9iyZQtu3LiB1NRU3Lx5E++88w7++usvAGBdk40bNzLXtCF9/fXXnPW4uLggIyODtS0zMxMmJiYyt7u4uAAAJBIJfHx8EBkZicDAQOTl5eHUqVMwMTHByJEjsW/fPta+8t7rxnbs2IFp06bhm2++weLFiznPo4G9vT2Ki4tx9+5dpKam4tq1azLXe5szZ47UM9W4gbhlyxaMHj0a3bp1Q2pqKvLy8vDDDz9g2LBh+OKLL5qtv6XXRVlZGb/88ovUtSaEEEIIaW/yNF7bK72pWjxsUiQSwcjICADQq1cvTJkyRarXSFtbmynTVFZWFtauXYuvv/4agYGBzHYzMzM4OzszvVzyEAgETD3Gxsb44osv4OXlhevXr6N///4yY27q2bNnmDVrFsaOHYv09HRme9++fTFkyBDMnj272ZiysrKwfv16bNq0idU4Xb16NaqqqhAcHIxx48bBxMSEyQsICMCKFSvg6+sLNTU1uc+1sblz5+K7777DkSNH4OnpKbNMWFgY7t+/jxs3bjDn3rt3bxw7dgyWlpaYP38+fv75Z9Z10dXVZV1Tebi4uCAmJgbFxcUwNjYGAJw6dQorVqzA6tWrmXJ37tzBX3/9xTTe0tLSsGfPHhw4cAAffvghU27btm149OgRZs+eDTc3N2hqagKQ/143WLt2LcLDw7F7925MnDhR7vNRVlZm6unRowfmzJmDwMBAlJeXsxYv19DQaPY63b59G0FBQQgKCsKGDRuY7WZmZhg2bBjruW+qpddFU1MTkydPxtKlS3HhwgW5z5MQQgghhHQ+Ck1Y8tdff+Ho0aNQUVGRe5/k5GRoaWlJ9dY1ELRy7GxpaSl2794NAC2K5/jx43j06BFnz0xzMTWcy9y5c6XyQkJCUFtbi59++om1PSgoCHV1dTJ75eRlamqKefPmITQ0FGKx9DASsViMlJQUTJs2TaqBoa6ujs8//xzHjh3D48ePWx1Dg+HDh0NFRYUZopebm4vnz5/D398f5eXlKCwsBPBiCKGqqiozbHL37t2wsrJiNVAahISE4NGjRzhx4oTMOvnu9dKlS/HVV1/h0KFDLWq4NVVSUoL09HQIhUIIhUK59/vpp59QW1vb7DPF9Yy35rpERETg2rVr2LNnj9wxEkIIIYSQzqfFjbdDhw5BS0sL6urq6Nu3L3Jzc6WG8C1ZsgRaWlqs1PDHfUFBAczNzaGs/L9Ovw0bNrDKcg1TbKysrAxaWlrQ1NREly5dkJKSAi8vL9jY2MiMuXH66quvmHgAwNramil/8eJFVtmm7681KCgoQN++faGqKj1GvkePHtDV1WWO30BDQwMrVqxAdHS03Ocpy5dffom///4bSUlJUnkPHjxAaWkpbG1tZe5ra2sLiUSCGzdutLr+BpqamnjnnXeY+5uZmYl3330XIpEIw4cPZ213dHSEhoYGgBfXjiu+hjIN5L3XP//8M9asWYP9+/fD1dW1xedz7do1aGlpQUNDA8bGxsjMzMT8+fOZnq4GW7ZskXqmdu7cycSto6PDajj/9NNPrLLXrl2TWX9Lrwvw4llbsGABwsLCUFcn3/sW1dXVKC8vZ6W66lq59iWEEEIIAQCxQNBh6U3V4sabi4sLsrOzceHCBQQEBMDDw4M1ZBAAFi1ahOzsbFZydHRk8pv2PPj7+yM7Oxtbt27Fs2fP5B46qa2tjezsbPz555/4/vvv0bdvX3z//ffNxtw4zZ8/v9njDhgwgCn37Nkzuf8gbkoikcjsZZk1axb09fWxZs2aVh0XAAwMDLBw4UKEh4dzvvfVXFxA63s5m3JxcWE10homTnF2dmZtHzVqVIuO2zg+ee/1gAEDYGpqivDwcFRUVLT4XKytrZGdnY2LFy9i9erVcHBwYA3/bDBt2jSpZ2rChAkyYwcADw8PZGdnM+/rNZ20piVk3bclS5bgwYMHiI+Pl+sY0dHR0NXVZaUz0WmtjokQQgghhLS/FjfeNDU1YWFhgQEDBmDTpk2orq7GypUrWWX09fVhYWHBSurq6gAAS0tL3Lx5E7W1//uWX09PDxYWFujZs2fLgldSgoWFBWxsbDB37lzMmDEDU6ZMaTbmxqlr165MPABw/fp1prxIJGLKcbGyssLNmzdlNp7u37+P8vJy5viNKSsrY9WqVfj6669x//79Fp1zY8HBwXj+/Dm2bNnC2m5gYAA9PT3k5ubK3C8/Px8CgQB9+/Ztdd2Nubi4oKCgAPfu3cOpU6fg7OwM4H+Nt9u3b+Pvv/9m3ncDXly75uLLy8sDANa1k/de9+zZE6dOnUJxcTHGjBnT4gacqqoqLCwsYG9vj2XLlsHBwUFqNk3gxfuBTZ+phnfiLC0tUVZWhpKSEqa8lpYWLCws0KdPH876W3pdGujp6SE0NBQrV65EZSX/TIKhoaEoKytjpfdCpSdmIYQQQghpjlig1GHpTaXwma9YsQLr1q2TuxHi6+uLp0+fSjU42sIXX3yBK1euYO/evXLv4+7ujq5du7aqF8zHxwdPnz7F1q1bpfLWrVsHFRWVZt+58vb2hr29vVTDtyW0tLSwfPlyrF69GuXl5cx2JSUlTJ48Gbt372Y1IAAwjT0PDw+mAauoYcOGQSQSYcuWLXj+/DkGDx4MAHj77bdRVlaGrVu3Qk1NDUOHDmX28fHxQWFhIQ4ePCh1vPXr16Nbt25wc3Nrtk6ue927d2+cOnUK//zzD9zd3VnXpqWWL1+O5ORkXLp0Se59Jk2aBBUVlVY/U629LgEBAVBSUuKdIRR48QWFjo4OKymL5H9XlBBCCCGEvHwKN95GjhwJe3t7REVFMdsqKipQUlLCSg1/QDs5OSEkJAQhISEIDg7G2bNncevWLWRlZSEuLo5ZY6s1dHR0MHv2bKxYsYI19LK6uloqnocPHwJ40QDasWMHDh8+jLFjx+LYsWP466+/cPXqVWbq9+Ymq3BycsKCBQuwaNEirF+/Hjdv3kR+fj6+/PJLfP3111i/fj1rpsmmYmJiEB8fj2fPnrXqfAHg008/ha6uLmvpA+DFjJdGRkZwc3PDzz//jDt37uD06dPw8PBAbW0tvv3221bX2ZS6ujocHR2xefNmDB8+nLleKioqcHJywubNm5kGXgMfHx9MmDABM2fORFxcHIqKinD16lXMnTsXBw4cwI4dO6TeM2usuXvdoFevXsjMzMSjR4/g7u7e6vcLzc3NMW7cOISHh7O2V1ZWSj1TDesd9u7dG+vXr8fXX3+NmTNnIiMjA0VFRbh06RI2bdoEoPlnSpHroqamhpUrVzJ1EEIIIYSQ10ub9DkGBwdj+/btzGLG4eHhMDY2ZqXGM++tW7cOu3fvxuXLl/HBBx/A0tIS3t7eEIvFOH/+PGtK9pZasGAB8vLy8OOPPzLbjh49KhXPu+++y+RPmDAB586dg4aGBj7++GNYW1tj1KhR+PXXX5GSkoIPPvig2fo2btyILVu2ICUlBf3798fgwYNx6tQp7Nu3T+pdwKZGjRqFUaNGtfqdOuBFA+mrr75CVVUVa7u+vj6ysrLg4uKCuXPnwtzcHJMnT4a5uTkuXrwIc3PzVtcpi4uLCyoqKqQWCnd2dkZFRQVryCTw4r2ttLQ0hIWFITY2FjY2Nnjvvfdw69YtZGRkSC22LYuse91YwxDK0tJSuLm5sRbCbomQkBAcPnyYNRX/9u3bpZ4pX19fJj8gIADHjx/HgwcPMGnSJFhaWsLT0xN///03jh49KnN5A0Dx6zJz5sw2v7eEEEIIIbLQhCUvn0DSkoXVCCGvrUgcbvc6lMD9caMlqeY9Bt/CnKoS7i9DagTcy1uKJPyzbhYKunPmV4m56+gj5F+mowzqnPka4I7TqJ57uHC5Ev86k08FIs58vvupAu57UQ/+JTjyqg14y3B5R/UuZ75IzH+/P3NayF3g4j3O7NWSA7x12D/jfvVAp/o5Z/4vXW04818FIvBP1FTH850y3zOnDOnlcxp7LOH+uQIAPUEVZ76OhDuf7+cGUPw8+T4HVeS41hKeYyi6CLI8+/OdZ1vU8Srgey75nodanvzVGNPimNrKnuc7OqzuSeqzO6zujtTiRboJIYQQQgghpP4N7gHrKK/sVC329vZS62g1JFlrm70OkpKSmj1ne3v7DokpKiqq2Zjef//9DomptZo7Dy0tLZw5c6ajwyOEEEIIIYTTK9vzduTIEdZyAo0ZGhq+5GheDi8vL9Z6eI2pqHTMTIDz5s3D5Mmyp5BvWP6hs8jOzm42r6XLVBBCCCGEEPKyvbKNN771sF5H2tra0NbW7ugwWLp27dpmSwp0NL51+wghhBBCiPze5IlDOsorO2ySEEIIIYQQQsj/vLI9b4QQQgghhJBXl5j6gV46uuKEEEIIIYQQ0glQzxshhBBCCCGkxST0zttLRz1vhBBCCCGEENIJUOONEEIIIYQQQjoBGjbJw8/PDzt37gQACIVC9OjRA2PHjkVUVBS6dOkCADA1NcWtW7ek9o2OjsbSpUuZ///000/49ttvcfnyZVRXV8PExATDhw9HQEAABg0aJFc8NTU12LhxI5KSklBYWAgNDQ1YW1tj9uzZmD59OlRUVODn54fS0lLs27cPAp7ubF9fX+zbtw87duzA1KlTme1isRjvvvsuDA0NsXfvXrmuUdPz3bdvHyZMmACJRMJsq6+vx6ZNm5CQkICCggKoqanByckJX375JYYPHw4AGDlyJE6dOtVsfX369EFRURFnTCNHjoSDgwM2btwoM18gEGDv3r1wcnJCr169kJCQgOnTp0uVmzt3Ls6fP4+rV68iIiICK1eulCpjbW2N/Px8znga3LhxA6tXr8aJEyfw4MED9OjRA0OHDkVISAjefvttVmylpaX45JNPOI8XGRmJLVu2ICcnh7Wkw5UrV/DOO+/gxx9/xLhx4+SKTQzFhz5oSao586sF3B855QI13jqqeD62VAX1nPk1EHLmV/PkA8DtSh3OfCO1Z5z5mhLZa1g2VizR5czXUOI+Rn0b3E8+ZRIRZ34XgYQzXx4DRMWc+UIJdx3PBKqc+R5/X+WNIflMJGf+XyIDzvwwgRdvHeVn/8WZ/+1wV858IbivgzLEvDHU8Xyfy3cMvudBRcAfA18dfJ9TfOcgD746+J4peT5LlXjul46kijO/VMC9zmq9HNdB0c98vv35zlGeMoreT3li4NMWvxv5fu/wPfcqcvz8dhRaKuDlo543OYwZMwbFxcUoKirCjh07cPDgQXz++eesMpGRkSguLmalgIAAJn/JkiWYMmUKHBwccODAAeTk5GDbtm3o27cvli1bJlccNTU18PDwQExMDD799FOcO3cOv//+O+bPn4/NmzcjJydHap/G8WzcuBE6Ojqsbd999x1iYmIQEBCA4uL//ZG0fv163LhxA1u3bpUrNjU1NaxZswZPnjxptoxEIoGPjw8iIyMRGBiIvLw8nDp1CiYmJhg5ciT27dsHAEhPT2fi+/333wEAJ0+eZLZdvHhRrpjkYWhoiLFjxyIhIUEq7/nz50hJScGsWbOYbfb29lL3+ezZs3LV9ccff2Dw4MEoKCjA1q1bkZubi71798LGxgYhISFS5adMmcKqx8nJCXPmzGFtW7JkCUxMTDB//nxmv9raWvj5+WHq1KlyN9wIIYQQQsirj3re5CASiWBkZAQA6NWrF6ZMmYLExERWGW1tbaZMU1lZWVi7di2+/vprBAYGMtvNzMzg7OzM6pnisnHjRpw+fRp//PEHq6fO3Nwc3t7eqKmpkdqncUy6uroQCARScQYEBGD//v2YM2cODh06hPz8fISHhyM5ORndu3eXKzZXV1fcuHED0dHRWLt2rcwyaWlp2LNnDw4cOIAPP/yQ2b5t2zY8evQIs2fPhpubG6sHqarqxbeP3bp1a/b6KmrWrFkYN24cioqKYGpqymzfs2cPqqqqWD1yysrKrYpDIpHAz88PlpaWOHPmDJSU/ve9iYODAxYsWCC1j7q6OtTV//ftqqqqKjQ0NKTq37VrF9566y3s2bMHkyZNwurVq/H48WNs2rSpxXESQgghhMirLXomSctQz1sL/fXXXzh69ChUVFTk3ic5ORlaWlpSvXUN+IY2NkhKSoKrq6vMIZYqKirQ1NSUO6am9SckJODMmTPYvn07/Pz8MGXKFIwfP17uYwiFQkRFRWHz5s24e/euzDK7d++GlZUVq+HWICQkBI8ePcKJEydadQ6K8PT0hJGRkVSDPD4+HuPHj0e3bt0UriM7Oxs5OTkICQlhNdwa6OnptfrYNjY2iIqKwmeffYZjx44hOjoaCQkJ0NHhHtpHCCGEEEI6F2q8yeHQoUPQ0tKCuro6+vbti9zcXCxZsoRVZsmSJdDS0mKlzMxMAEBBQQHMzc2hrPy/js4NGzawypaVlfHGUVhYCBsbmzY9twa9e/fGxo0bMW/ePNy/fx9ff/11i48xYcIEODg4YMWKFTLzCwoKYGtrKzOvYXtBQUGL61WUUCjExx9/jMTERKYX9O+//8apU6dYQyYB4Nq1a1L3efbs2bx1FBYWAkC73b8FCxagX79+8PT0xGeffYZRo0Zxlq+urkZ5eTkr1VXzv4dFCCGEEEI6DjXe5ODi4oLs7GxcuHABAQEB8PDwYL3PBgCLFi1CdnY2Kzk6OjL5TXvX/P39kZ2dja1bt+LZs2dyDZ2USCRy99K1xieffAJjY2MEBgZCV5d7soTmrFmzBjt37kRubm6r9m/P8+Mya9Ys3Lp1C7/++iuAF71uvXr1gqsre5IAa2trqfu8evVq3uM33N/2Oj+BQICwsDCIxWJ8+eWXvOWjo6Ohq6vLSmej09olNkIIIYS8nsQCpQ5Lb6o398xbQFNTExYWFhgwYAA2bdqE6upqqVkH9fX1YWFhwUoN7ytZWlri5s2bqK39X8+Gnp4eLCws0LNnT7njsLKyQl5eXtucVDOUlZVZPYQtNWLECHh4eMichMXKyqrZRl3DeVlaWra6bkVYWlrivffeQ0JCAsRiMXbu3IlPPvlEaoijqqqq1H02NDTkPb6VlRUAtOv9a7hv8ty/0NBQlJWVsdK7oZPbLTZCCCGEEKI4ary1wooVK7Bu3Trcv39frvK+vr54+vQptmzZolC9U6dOxcmTJ3H58mWpvLq6Ojx7xj09+csSExODgwcP4ty5c6ztPj4+KCwsxMGDB6X2Wb9+Pbp16wY3N7eXFaaUWbNmIT09HT/99BPu3r3LO01/Szg4OMDOzg7r16+HWCw95W9paWmb1SUPkUgEHR0dVlIWyf8eJyGEEEKIGIIOS28qary1wsiRI2Fvb4+oqChmW0VFBUpKSlipvLwcAODk5ISQkBCEhIQgODgYZ8+exa1bt5CVlYW4uDgIBAKZk1g0FRQUhOHDh2P06NH49ttvceXKFfz1119IS0uDo6Mj815VR+vfvz+mTZuGzZs3s7b7+PhgwoQJmDlzJuLi4lBUVISrV69i7ty5OHDgAHbs2NHqSVdkefDggdQQx5KSkmbLe3t7Q0VFBXPnzsXo0aNZM082qKurk7rP//3vf3ljaZgUpqCgACNGjMCRI0fw119/4erVq1i9ejVN6U8IIYQQQnhR462VgoODsX37dty5cwcAEB4eDmNjY1ZavHgxU37dunXYvXs3Ll++jA8++ACWlpbw9vaGWCzG+fPn5ZoZUCQS4cSJE1i8eDG2bt2KoUOH4p133sGmTZsQGBiIfv36tdv5ttRXX30l9R6fQCBAWloawsLCEBsbCxsbG7z33nu4desWMjIyWjS7pTx2796NQYMGsdL333/fbHkNDQ34+PjgyZMn8Pf3l1kmJydH6j736dNHrniGDBmCP/74A3379sWcOXNga2sLLy8v5OTkNLuYOCGEEELIq0osEHRYelMJJPIuMkYIea1F4IjCx9CRVHHmq0rqOPMfK/H3vFZDyJkvQr1C+9dIuPMB4M/HPTjzxRLuXypTu1zhreMSenHm9xCWc+aPfHidM/8vXQPeGG6rdOXMr5CocuZrC6TXnmysq5h/qHepkgZnvpDnfot5vqM0rX7EG4Pxs1LO/HKROmf+qOz/8Nah8+433AVczTmzI05s5sxXAv+ver5hSHzHKJOIOPP5ngcA0JM858wvFXBfa2VID0tv7D9V/O8o26n9w5mvIeE+j6cC7usA8F9LEbhn/30O7p+9V4E8zxxfmTqen1956lBUWwzPU/Rni2//SLzf4pjayrb65A6r+1Ohb4fV3ZGo540QQgghhBBCOgFqvL1C7O3tpdYQa0hJSUkdEtPt27ebjUlLSwu3b99+6TGdOXOGM6aO8CrGRAghhBDSnuoh6LD0pmr9nPCkzR05coS1nEBj8kxH3x569OiB7OxszvyX7e233+aMqSO8ijERQgghhJDXCzXeXiHyTnzxMikrK8PCwqKjw2BRV1enmAghhBBCOtibPHFIR6Fhk4QQQgghhBDSCVDjjRBCCCGEEEI6ARo2SQghhBBCCGkxyRs8cUhHoZ43QgghhBBCCOkEqOeNEEIIIYQQ0mJiAfUDvWxvzBX38/PD+PHjZeaZmppi48aNqKmpgb6+PlatWiWzXHR0NPT19VFTU4PExEQIBAKppKamJndMJSUlCAgIgLm5OUQiEUxMTPDhhx/il19+kYotMzNTZn2N01dffQVNTU3cuHGDVc/9+/fRpUsXfP3117wxmZqaQiAQICsri7U9KCgII0eOZG17/PgxgoKCYGpqClVVVRgbG+OTTz5hrf3GF7Ofnx9nPEOHDsVnn33G2vbdd99BIBAgLi6OtX3WrFkYNmwY8//6+nrExsZiwIABUFNTg56eHt5//3389ttvrP2a3ktDQ0N8+OGHyMnJYZWT9Qzt2bMHampqWLt2Led5NCgvL0dYWBhsbGygpqYGIyMjuLq6Ij09HRKJBAAwcuRIBAUFoaioiPf6ubi4QEVFBWfPnmXV8+zZM5ibm+OLL76QK662UitQ4kxinqQECW9SgZgzKbq/uqCON3XXrORMGqq1nKlGIORNGko1nIlPlbIKZ+K7F/L8QlYRiDmTGALOJI/nUOZM1VDhTBIIONPfIn3eVKkq4kw61c8507fDXXkTXM2508m/uBMPvnshz/3g219NUMeZ5NEWzwwXVaV63vQq4HuuXwZ5Po+5kjza+36/KjG0xbUipMEb03iTh6qqKqZPn47ExETmD+nGEhISMGPGDKiqqgIAdHR0UFxczEq3bt2Sq66ioiIMHjwYv/76K9auXYtr167h6NGjcHFxwfz586XKDxs2jFXP5MmTMWbMGNa2hQsXwsPDAzNnzoRYLGb2/fTTTzFo0CAEBgbKFZuamhqWLFnCWebx48cYOnQoTp48iS1btuDGjRtITU3FzZs38c477+Cvv178MdE4vo0bN0pdM74GpYuLCzIyMljbMjMzYWJiInO7i4sLAEAikcDHxweRkZEIDAxEXl4eTp06BRMTE4wcORL79u1j7dsQ1/3793H48GE8e/YMY8eORU1N838k79ixA9OmTcM333yDxYsXc54HAJSWlmLYsGHYtWsXQkNDcenSJZw+fRpTpkzB4sWLUVZWxipvYmLCulYhISGwt7dnbTt48CACAgLg5+eHZ8+eMfsuXrwYIpEI0dHRvHERQgghhLSGPF8MtVd6U9GwySZmzZqFr7/+GqdPn4azszOz/cyZMygsLMSsWbOYbQKBAEZGRq2q5/PPP4dAIMDvv/8OTU1NZru9vT38/f2lyquqqrLqUldXR3V1tVT9W7duRb9+/bBhwwYsXLgQiYmJOHPmDK5evQqBnGtxzJ07F9999x2OHDkCT09PmWXCwsJw//593Lhxg4mhd+/eOHbsGCwtLTF//nz8/PPPrPh0dXVbfM1cXFwQExOD4uJiGBsbAwBOnTqFFStWYPXq1Uy5O3fu4K+//mIab2lpadizZw8OHDiADz/8kCm3bds2PHr0CLNnz4abmxtz7RvHZWxsjC+++AJeXl64fv06+vfvLxXX2rVrER4ejt27d2PixIlyncuyZctQVFSEgoIC1uLmVlZW8PX1leq1FQqFrGulpaUFZWVlqesXFRWFo0ePYsmSJfjmm2+QkZGB7du349y5cy3qCSaEEEIIIa826nlron///njnnXeQkJDA2h4fH48hQ4agX79+Ctfx+PFjHD16FPPnz2c13Bro6em1+tgGBgbYunUrli9fjhMnTuCLL77A119/3aIFwE1NTTFv3jyEhoayevAaiMVipKSkYNq0aVINCXV1dXz++ec4duwYHj9+3OrzaDB8+HCoqKggMzMTAJCbm4vnz5/D398f5eXlKCwsBABkZGRAVVWVGTa5e/duWFlZsRpuDUJCQvDo0SOcOHFCZp2lpaXYvXs3AEBFRXp4ytKlS/HVV1/h0KFDcjfcGl+zxg23Bg0Ns9ZQU1PDrl27sG3bNuzbtw/+/v5YtmwZ3n777VYdjxBCCCGEvJqo8SaDv78/9uzZg6dPnwIAnj59ih9//JHV6wYAZWVl0NLSYiV3d3fe49+4cQMSiQQ2NjbtEv/48eOZYZUjRozgfa9Mli+//BJ///03kpKSpPIePHiA0tJS2NraytzX1tYWEolE6t271tDU1MQ777zDNN4yMzPx7rvvQiQSYfjw4aztjo6O0NDQAAAUFBRwxtdQpkHDvdTU1ESXLl2QkpICLy8vqXv0888/Y82aNdi/fz9cXV3lPo+HDx/iyZMn7XbP3377bYSGhmLixIno1q0bvvzyS87y1dXVKC8vZ6W66tp2iY0QQgghrycaNvnyUeNNBl9fX4jFYqSmpgIAUlNTmXeoGtPW1kZ2djYrNe2xk6XhfTp5hzG2xvLlyyEWi7F8+fJW7W9gYICFCxciPDyc870vWdr6/FxcXFiNtIaJU5ydnVnbR40a1aLjNo6v4V7++eef+P7779G3b198//33UvsMGDAApqamCA8PR0VFhdx1vYx7/uWXX0IsFmPp0qW8vXjR0dHQ1dVlpbPRae0WGyGEEEIIURw13mTQ1dXFpEmTmIZYQkICJk2aBB0dHVY5JSUlWFhYsFLPnj15j29paQmBQIC8vLx2iR8A88d7a4fiAUBwcDCeP3+OLVu2sLYbGBhAT08Pubm5MvfLz8+HQCBA3759W113Yy4uLigoKMC9e/dw6tQp5l3Ehsbb7du38ffffzPvuwEv3iNrLr6G625paclsa7iXNjY2mDt3LmbMmIEpU6ZI7duzZ0+cOnUKxcXFGDNmjNwNOAMDA3Tp0qVd73nDEE957nloaCjKyspY6d3Qye0WGyGEEEJeP9Tz9vJR460Zs2bNwm+//YZDhw7ht99+kxoyqYiuXbvCw8MD3377LWuGwAalpaVtVpcitLS0sHz5cqxevRrl5eXMdiUlJUyePBm7d+9GSUkJa5+Gxp6Hhwe6du3aJnEMGzYMIpEIW7ZswfPnzzF48GAAL4YKlpWVYevWrVBTU8PQoUOZfXx8fFBYWIiDBw9KHW/9+vXo1q0b3Nzcmq3ziy++wJUrV7B3716pvN69e+PUqVP4559/4O7uzro2zVFSUsKUKVOQlJSE+/fvS+U/e/YMdXXyTaXdFkQiEXR0dFhJWfRypp8mhBBCCCGt80Y13srKyqSGOTZek6wxZ2dnWFhY4OOPP4aFhQVGjBghVUYikaCkpEQqyZrko6ktW7agvr4eQ4YMwU8//YTCwkLk5eVh06ZNcHJyUvhc28qnn34KXV1dJCcns7avXr0aRkZGcHNzw88//4w7d+7g9OnT8PDwQG1tLb799ts2i0FdXR2Ojo7YvHkzhg8fDqFQCOBFT5OTkxM2b97MNPAa+Pj4YMKECZg5cybi4uJQVFSEq1evYu7cuThw4AB27Nghc7KYBjo6Opg9ezZWrFghc9mIXr16ITMzE48ePYK7u7vUNP+yREVFwcTEBI6Ojti1axdyc3NRWFiI+Ph4ODg4MO9YEkIIIYQQIssb1XjLzMzEoEGDWCk8PLzZ8v7+/njy5InMqfuBFwsuGxsbS6V//vmHNxYzMzNcunQJLi4uCAkJQb9+/eDm5oZffvkF3333XavPsa2pqKjgq6++QlVVFWu7vr4+srKy4OLigrlz58Lc3ByTJ0+Gubk5Ll68CHNz8zaNw8XFBRUVFVILhTs7O6OiooI1ZBJ48W5ZWloawsLCEBsbCxsbG7z33nu4desWMjIyml2wvbEFCxYgLy8PP/74o8z8hiGUpaWlcHNz4+0x7dKlC7KysjB9+nSsWrUKgwYNwnvvvYfk5GT83//9H3R1dXljIoQQQgh5VdQLBB2W3lQCiaxuBULIGycCRxQ+hjL4e5251ECocB11PN9JKbo/ACiB+2NT0Xx58I33VzQf4L9WleAeaqsG7qHAIvDPcMp3rfjO4zlUOfPr5bgOEp4yAp4YhXLcb0WfiQjBWM78nJsRvMew78td5vSD9dz5+lac+fI8cyo8z0w1zzPHV4c8n1F8x+D7nFJFPW8dij7Xr4K2OIe2+Cxs7xja4l4oep58n5VLMF6h4ytiDfZ1WN0ded4diRbpJoQQQgghhLRYZ/ii4XXzRg2bfFlu374ttf5b49Tce3btLSkpqdmY7O3tOySmqKioZmN6//33OySm1uK652fOnOno8AghhBBCSCdHPW/toEePHsjOzubM7wheXl5wdHSUmdcwzfzLNm/ePEyeLHuKenV19ZccjWK47rk8S0gQQgghhHQmYuoHeumo8dYOlJWVYWFh0dFhSNHW1oa2tnZHh8HStWvXNltSoKO9ivecEEIIIYS8Pqi5TAghhBBCCCGdAPW8EUIIIYQQQlqMbzZe0vao540QQgghhBDy2tuyZQvMzMygpqaGwYMH804od+rUKQwePBhqamowNzfH999/L1Xmp59+gp2dHUQiEezs7LB37972Ch8ANd4IIYQQQgghrSCGoMNSS6WmpiIoKAhhYWG4fPky3nvvPbz//vvNzgL/999/w9PTE++99x4uX76MZcuWITAwED/99BNT5vz585gyZQpmzJiBK1euYMaMGZg8eTIuXLjQ6mvKhxpvhBBCCCGEkNfahg0bMGvWLMyePRu2trbYuHEjTExM8N1338ks//3336N3797YuHEjbG1tMXv2bPj7+2PdunVMmY0bN8LNzQ2hoaGwsbFBaGgoRo8ejY0bN7bbeVDjjRBCCCGEENKpVFdXo7y8nJWqq6tllq2pqcGff/4Jd3d31nZ3d3ecO3dO5j7nz5+XKu/h4YE//vgDtbW1nGWaO2ZbeC0ab35+fhAIBBAIBFBRUYGhoSHc3NwQHx8PsVjMlDM1NWXKNU4xMTEAgKKiIpn506dP543h0aNHGDNmDHr06AGRSAQTExP861//Qnl5OavctWvX4OzsDHV1dfTs2RORkZGQSCRyn2tNTQ3Wrl2LgQMHQkNDA/r6+hg+fDgSEhKYB6nhejScV4N9+/ZBIBBIXbPmEp9//vkHc+fORe/evSESiWBkZAQPDw+cP3+eVe7cuXPw9PREly5doKamhv79+2P9+vWor6+XOmZGRgY8PT3RrVs3aGhowM7ODiEhIbh37x4AIDMzEwKBAKWlpVL7WltbQ1VVlSnb2MiRIxEUFMR7Ts1paVwN/29I3bp1w6hRo/Dbb7+xjiuRSLBt2zY4OjpCS0sLenp6ePvtt7Fx40ZUVlYCACIiIuDg4NBsbCNHjpR5/+bNm9fq820tFdRxpjoocSZ5VEPImeoh4Ex8+ytDzJv4CCHmTPIMB1H0WtVCiTO1BSVIOBOfaqjwplooc6Z6CDkTX4xCOZKAJ/GR55lS9Frm3IzgTPZ9+RPfMUZ4buBMbfHzzXc/+Sh6HeWh6PMA8A816wza4hxe9rC59jqP9o6hDkLO1JE6cthkdHQ0dHV1WSk6OlpmnA8fPkR9fT0MDQ1Z2w0NDVFSUiJzn5KSEpnl6+rq8PDhQ84yzR2zLbwWjTcAGDNmDIqLi1FUVISff/4ZLi4uWLBgAT744APU1dUx5SIjI1FcXMxKAQEBrGOdPHmSlf/tt9/y1q+kpIRx48bhwIEDKCgoQGJiIk6ePMn6A7q8vBxubm7o0aMHLl68iM2bN2PdunXYsGGDXOdYU1MDDw8PxMTE4NNPP8W5c+fw+++/Y/78+di8eTNycnKYsmpqalizZg2ePHki81hff/016xwBICEhQWobl4kTJ+LKlSvYuXMnCgoKcODAAYwcORKPHz9myuzduxfOzs7o1asXMjIykJ+fjwULFmD16tXw8fFhNVy3bt0KV1dXGBkZ4aeffkJubi6+//57lJWVYf369ZyxnD17FlVVVfD29kZiYiJv7C2hSFzXr19HcXExMjMzYWBggLFjx+Kff/5h8mfMmIGgoCCMGzcOGRkZyM7OxvLly7F//34cP35c7hjnzJkj9VyvXbu21edMCCGEEPIqCw0NRVlZGSuFhoZy7tO0c0IikXB2WMgq33R7S4+pqNdmqYCGnh8A6NmzJ9566y0MHToUo0ePRmJiImbPng3gxULVDeWa061bN94yTXXp0gWfffYZ8/8+ffrg888/x//93/8x25KSklBVVYXExESIRCL069cPBQUF2LBhA4KDg3lv9MaNG3H69Gn88ccfGDRoELPd3Nwc3t7eqKmpYba5urrixo0biI6OlvlHfMM3FI3p6enJfd6lpaU4e/YsMjMz4ezszJzzkCFDmDLPnj3DnDlz4OXlhW3btjHbZ8+eDUNDQ3h5eSEtLQ1TpkzB3bt3ERgYiMDAQMTGxjJlTU1NMWLECJk9bY3FxcVh6tSpcHZ2xvz587Fs2bI2+cFRNK7u3bsz1/XLL79EWloaLly4gA8//BBpaWlISkrCvn37MG7cONaxvby8pHptuWhoaLT4mSWEEEIIUURH9hSLRCKIRCK5yurr60MoFEr1iP3zzz9SPWcNjIyMZJZXVlZGt27dOMs0d8y28Nr0vMkyatQoDBw4EOnp6S+97vv37yM9PZ1p2AAvxsU6OzuzHjQPDw/cv38fRUVFvMdMSkqCq6srq+HWQEVFBZqamsz/hUIhoqKisHnzZty9e1exk5FBS0sLWlpa2LdvX7Pji48fP45Hjx5h4cKFUnkffvghrKyskJycDAD48ccfUVNTg8WLF8s8lp6eXrOxVFRU4Mcff8T06dPh5uaGZ8+eITMzs8XnJIsicTVWWVmJhIQEAC/uFfDiflpbW7Mabg0EAoFU45oQQgghhLScqqoqBg8ejBMnTrC2nzhxAsOGDZO5j5OTk1T548eP4+2332b+lmuuTHPHbAuvdeMNAGxsbFgNoyVLljANj4bU9A/9YcOGsfIvX74sd32+vr7Q0NBAz549oaOjgx07djB5zY2LbcjjU1hYCBsbG7ljmTBhAhwcHLBixQq595GXsrIyEhMTsXPnTujp6WH48OFYtmwZrl69ypQpKCgAANja2so8ho2NDVOmsLAQOjo6MDY2bnEsKSkpsLS0hL29PYRCIXx8fBAXF9eKs5KmSFwA0KtXL+Y5io2NxeDBgzF69Gjm2NbW1m0S55YtW6Se6507dzZbXtZLvnXVtW0SCyGEEELeDHzvmbdnaqng4GDs2LED8fHxyMvLwxdffIHbt28zrziFhobi448/ZsrPmzcPt27dQnBwMPLy8hAfH4+4uDhWp8SCBQtw/PhxrFmzBvn5+VizZg1Onjyp0DwLfF77xlvTcaeLFi1CdnY2Kzk6OrL2SU1NZeXb2dnJXV9sbCwuXbqEffv24ebNmwgODmblyzN2Vt5zkceaNWuwc+dO5Obmtmg/eUycOBH379/HgQMH4OHhgczMTLz11ltS75w1NyFL4/NRZHxwXFwca1KZ6dOnIz09nXdIozwUHbd85swZXLp0CcnJyejTpw8SExOZb2vackz0tGnTpJ7rCRMmNFte1ku+Z6PT2iQWQgghhJBXzZQpU7Bx40ZERkbCwcEBp0+fxpEjR9CnTx8AQHFxMWvNNzMzMxw5cgSZmZlwcHDAV199hU2bNmHixIlMmWHDhiElJQUJCQkYMGAAEhMTkZqaKtW2aEuvzTtvzcnLy4OZmRnzf319fVhYWHDuY2JiwlumOUZGRjAyMoKNjQ26deuG9957D8uXL4exsXGz42IByDU21srKCnl5eS2KZ8SIEfDw8MCyZcvg5+fXon3loaamBjc3N7i5uSE8PByzZ8/GihUr4OfnBysrKwAv7oGs7uP8/HymYWxlZYWysjIUFxe3qJcrNzcXFy5cwMWLF7FkyRJme319PZKTk1nvIbZGa+NqYGZmBj09PVhZWaGqqgoTJkzAf/7zH4hEolbdz+bo6uq26JkNDQ2V+mJhrSijTWIhhBBCCHkVff755/j8889l5sma8M7Z2RmXLl3iPOakSZMwadKktghPLq91z9uvv/6Ka9eusVrIL1NDj1PDO2FOTk44ffo0a2KR48ePo0ePHjA1NeU93tSpU3Hy5EmZwzjr6urw7NkzmfvFxMTg4MGD7brmRAM7OzsmDnd3d3Tt2lXmjIwHDhxAYWEhfH19Abx48FVVVZudIbG5XrS4uDiMGDECV65cYfU6LV68uE2GTrY2LllmzJgBsViMLVu2AHhxPwsKCrB//36pshKJBGVlZa2KWR4ikQg6OjqspCxSabf6CCGEEPL64V9Mpf3Sm+q16Xmrrq5GSUkJ6uvr8d///hdHjx5FdHQ0PvjgA9b41YqKCqneLw0NDejo6ChU/5EjR/Df//4X77zzDrS0tJCbm4vFixdj+PDhTMNs6tSpWLlyJfz8/LBs2TIUFhYiKioK4eHhcg2fCwoKwuHDhzF69Gh89dVXePfdd6GtrY0//vgDa9asQVxcnMz1wPr3749p06Zh8+bNCp1jY48ePYK3tzf8/f0xYMAAJo61a9cyE3Boampi69at8PHxwaeffop//etf0NHRwS+//IJFixZh0qRJmDx5MoAXvZ2xsbHM2ngff/wxTE1NcffuXezatQtaWlpSjcDa2lr88MMPiIyMRL9+/Vh5s2fPxtq1a3HlyhUMHDgQAPDgwQNkZ2ezyjX0lDanNXE1R0lJCUFBQVi1ahXmzp2LyZMnY+/evfD19cXy5cvh5uYGAwMDXLt2DbGxsQgICMD48eMBAM+fP5eKXUtLi+ltq6yslHquRSIRunTpIldshBBCCCHk1ffa9LwdPXoUxsbGMDU1xZgxY5CRkYFNmzZh//79EAr/t4BheHg4jI2NWam5mQRbQl1dHdu3b8e7774LW1tbBAUF4YMPPsChQ4eYMrq6ujhx4gTu3r2Lt99+G59//jmCg4Olhq81RyQS4cSJE1i8eDG2bt2KoUOH4p133sGmTZsQGBgo1YBp7KuvvmrRYuB8tLS04OjoiNjYWIwYMQL9+vXD8uXLMWfOHHzzzTdMuUmTJiEjIwN37tzBiBEjYG1tjQ0bNiAsLAwpKSmsRuvnn3+O48eP4969e5gwYQJsbGwwe/Zs6OjoyJyx8sCBA3j06JHMd7ssLS3Rv39/Vu/b7t27MWjQIFb6/vvvec+1pXFx8ff3R21tLb755hsIBALs3r0bGzZsYNbDGzBgACIiIjBu3Dh4eHgw+xUUFEjF3rD8BQBs375d6rlu6NUkhBBCCGkPHblI95tKIGnLv+gJIZ1WBI4ofAxliBXavwZC3jJ8ddTxfCel6P4AoATuj01F8+XB94tL0XyA/1pVgnuorRrqOPNF4J/hlO9a8Z3Hc6hy5sszYxnf8BwBT4xCOe63os9EhGAsZ37OzQjeY9j35S5z+gH3KIPT+lac+fI8cyo8z0w1zzPHV4c8n1F8x+D7nJKnDr4yneEPU0V/NuU5hqLaIga+Y7T3OQD8n5VLML7dY2jOUhzvsLpj4N5hdXek16bnjRBCCCGEEEJeZ9R4k9O8efOk1tFqSA3rQyjK3t6+2TqSkpLapA553b59u9lYtLS0WFOpdmZRUVHNnuP777/f0eERQgghhLyy6iWCDktvqtdmwpL2FhkZ2ez7TYpOdtLgyJEjqK2V3TUuz1ICbalHjx5SE2Q0zX8dzJs3j5k0pSl1dfWXHA0hhBBCCCHNo8abnLp3747u3bu3ax0NiwS+CpSVlVu91l1n0rVrV3Tt2rWjwyCEEEII6XQ6w/uZrxsaNkkIIYQQQgghnQD1vBFCCCGEEEJa7E1eLLujUM8bIYQQQgghhHQC1HgjhBBCCCGEkE6Ahk0SQgghhBBCWkxM/UAv3Wtxxf38/CAQCCAQCKCiogJDQ0O4ubkhPj4eYrGYKWdqasqUa5xiYmIAAEVFRTLzp0+fLncsiYmJGDBgANTU1GBkZIR//etfrPxr167B2dkZ6urq6NmzJyIjIyGRSOQ+fk1NDdauXYuBAwdCQ0MD+vr6GD58OBISEphlBhquR8N5Ndi3bx8EAoHUNWsu8fnnn38wd+5c9O7dGyKRCEZGRvDw8MD58+dZ5c6dOwdPT0906dIFampq6N+/P9avX4/6+nqpY2ZkZMDT0xPdunWDhoYG7OzsEBISgnv37gEAMjMzIRAIUFpaKrWvtbU1VFVVmbKNjRw5EkFBQbzn1JyWxtXw/4bUrVs3jBo1Cr/99hvruBKJBNu2bYOjoyO0tLSgp6eHt99+Gxs3bkRlZSUAICIiAg4ODs3GNnLkSJn3r6XrDypBonASop4z1UGJM8mjCsqcia8Ovv2VIeZNil5LMQS8SdFrxXd8ee6noufJpxoqvKkOQs4khhJn4iOEhDcJeBIfeZ4pRa/l6QfrOZO9z3bexHeMEQYhnKktfr65P0GEvPsreh3lOQbf8yDPzxbfz6ei5PmMae862ipORep4GfdC0XOQ7/cB9+cgebO8Fo03ABgzZgyKi4tRVFSEn3/+GS4uLliwYAE++OAD1NXVMeUiIyNRXFzMSgEBAaxjnTx5kpX/7bffyhXDhg0bEBYWhqVLlyInJwe//PILPDw8mPzy8nK4ubmhR48euHjxIjZv3ox169Zhw4YNch2/pqYGHh4eiImJwaeffopz587h999/x/z587F582bk5OQwZdXU1LBmzRo8efJE5rG+/vpr1jkCQEJCgtQ2LhMnTsSVK1ewc+dOFBQU4MCBAxg5ciQeP37MlNm7dy+cnZ3Rq1cvZGRkID8/HwsWLMDq1avh4+PDarhu3boVrq6uMDIywk8//YTc3Fx8//33KCsrw/r16zljOXv2LKqqquDt7Y3ExETe2FtCkbiuX7+O4uJiZGZmwsDAAGPHjsU///zD5M+YMQNBQUEYN24cMjIykJ2djeXLl2P//v04fvy43DHOmTNH6rleu3Ztq8+ZEEIIIYSPWCLosPSmem2GTTb0/ABAz5498dZbb2Ho0KEYPXo0EhMTMXv2bACAtrY2U6453bp14y3T1JMnT/Dll1/i4MGDGD16NLPd3t6e+XdSUhKqqqqQmJgIkUiEfv36oaCgABs2bEBwcDBvb9fGjRtx+vRp/PHHHxg0aBCz3dzcHN7e3qipqWG2ubq64saNG4iOjpb5R7yuri50dXVZ2/T09OQ+79LSUpw9exaZmZlwdnYG8GKduiFDhjBlnj17hjlz5sDLywvbtm1jts+ePRuGhobw8vJCWloapkyZgrt37yIwMBCBgYGIjY1lypqammLEiBEye9oai4uLw9SpU+Hs7Iz58+dj2bJlcvUe8lE0ru7duzPX9csvv0RaWhouXLiADz/8EGlpaUhKSsK+ffswbtw41rG9vLxQXl4ud5waGhotfmYJIYQQQkjn8tr0vMkyatQoDBw4EOnp6e1e14kTJyAWi3Hv3j3Y2tqiV69emDx5Mu7cucOUOX/+PJydnSESiZhtHh4euH//PoqKinjrSEpKgqurK6vh1kBFRQWamprM/4VCIaKiorB582bcvXtXsZOTQUtLC1paWti3bx+qq6tlljl+/DgePXqEhQsXSuV9+OGHsLKyQnJyMgDgxx9/RE1NDRYvXizzWHp6es3GUlFRgR9//BHTp0+Hm5sbnj17hszMzBafkyyKxNVYZWUlEhISALy4V8CL+2ltbc1quDUQCARSjWtCCCGEEPJme60bbwBgY2PDahgtWbKEaXg0pKZ/6A8bNoyVf/nyZd56/vrrL4jFYkRFRWHjxo3Ys2cPHj9+DDc3N6ZHrKSkBIaGhqz9Gv5fUlLCW0dhYSFsbGx4yzWYMGECHBwcsGLFCrn3kZeysjISExOxc+dO6OnpYfjw4Vi2bBmuXr3KlCkoKAAA2NrayjyGjY0NU6awsBA6OjowNjZucSwpKSmwtLSEvb09hEIhfHx8EBcX14qzkqZIXADQq1cv5jmKjY3F4MGDmZ7ZwsJCWFtbt0mcW7ZskXqud+7c2Wz56upqlJeXs1JddW2bxEIIIYSQN0M9BB2W3lSvfeNNIpGwhs8tWrQI2dnZrOTo6MjaJzU1lZVvZ2fHW49YLEZtbS02bdoEDw8PDB06FMnJySgsLERGRgZTrulQvoZ3vuQZ4tf0XOSxZs0a7Ny5E7m5uS3aTx4TJ07E/fv3ceDAAXh4eCAzMxNvvfWW1DtnzU3I0vh8WnNuDeLi4liTykyfPh3p6em8QxrloUhcAHDmzBlcunQJycnJ6NOnDxITE5meN0WP3di0adOknusJEyY0Wz46OpoZOtuQzkSntUkshBBCCCGkfbw277w1Jy8vD2ZmZsz/9fX1YWFhwbmPiYkJb5mmGnpmGjf0DAwMoK+vj9u3bwMAjIyMpHrYGiavaNojJ4uVlRXy8vJaFNeIESPg4eGBZcuWwc/Pr0X7ykNNTQ1ubm5wc3NDeHg4Zs+ejRUrVsDPzw9WVlYAXtyDYcOGSe2bn5/PXC8rKyuUlZWhuLi4Rb1cubm5uHDhAi5evIglS5Yw2+vr65GcnIzPPvtMofNrbVwNzMzMoKenBysrK1RVVWHChAn4z3/+A5FI1Kr72RxdXd0WPbOhoaEIDg5mbVsn+rVNYiGEEELIm0HyBk8c0lFe6563X3/9FdeuXcPEiRPbva7hw4cDeDG7YIPHjx/j4cOH6NOnDwDAyckJp0+fZk0scvz4cfTo0QOmpqa8dUydOhUnT56UOYyzrq4Oz549k7lfTEwMDh48iHPnzrXklFrFzs6OicPd3R1du3aVOSPjgQMHUFhYCF9fXwDApEmToKqq2uwMic31osXFxWHEiBG4cuUKq9dp8eLFbTJ0srVxyTJjxgyIxWJs2bIFwIv7WVBQgP3790uVlUgkKCsra1XM8hCJRNDR0WElZZFKu9VHCCGEEEIU99o03qqrq1FSUoJ79+7h0qVLiIqKwrhx4/DBBx/g448/ZspVVFSgpKSElVoyq19zrKysMG7cOCxYsADnzp3Df/7zH8ycORM2NjZwcXEB8OKPdZFIBD8/P/znP//B3r17ERUVJddMkwAQFBSE4cOHY/To0fj2229x5coV/PXXX0hLS4OjoyMKCwtl7te/f39MmzYNmzdvVvg8Gzx69AijRo3Cv//9b1y9ehV///03fvzxR6xdu5aZgENTUxNbt27F/v378emnn+Lq1asoKipCXFwc/Pz8MGnSJEyePBnAi97O2NhYfP3115g1axZOnTqFW7du4bfffsPcuXPx1VdfScVQW1uLH374Ab6+vujXrx8rzZ49G3/++SeuXLnClH/w4IHU0EK+dw1bE1dzlJSUEBQUhJiYGFRWVmLy5MmYMmUKfH19ER0djT/++AO3bt3CoUOH4Orqyhpu+/z5c6nYb9y4weRXVlZKPdfNLRNBCCGEEEI6p9em8Xb06FEYGxvD1NQUY8aMQUZGBjZt2oT9+/dDKPzfAobh4eEwNjZmpeZmEmypXbt2wdHREWPHjoWzszNUVFRw9OhR5h0nXV1dnDhxAnfv3sXbb7+Nzz//HMHBwVLD15ojEolw4sQJLF68GFu3bsXQoUPxzjvvYNOmTQgMDES/fv2a3ferr75q0WLgfLS0tODo6IjY2FiMGDEC/fr1w/LlyzFnzhx88803TLlJkyYhIyMDd+7cwYgRI2Btbc2sh5eSksJqtH7++ec4fvw47t27hwkTJsDGxgazZ8+Gjo6OzBkrDxw4gEePHsl8t8vS0hL9+/dn9b7t3r0bgwYNYqXvv/+e91xbGhcXf39/1NbW4ptvvoFAIMDu3buxYcMGZj28AQMGICIiAuPGjWOtEVhQUCAVe8PyFwCwfft2qee6oVeTEEIIIaQ9vIxFyttrofnOSiBpy7/oCSGdViQOK3yMUokaZ76eoIozXwgxbx264uec+WIB93dSShLuOqoE/MNH1SU1nPn3lbiXeXgu4a/DUvyAM/8zoQ9n/moc5MwXSep4Y6jluZaaEu4ZSisEIs58JTnudwW4nyk+GuCO8SlUFTo+wP/cVkkUf71cTcB9v9TBnV8nx3e1yjznwXeMCMFYzvxIySHeGHQk3J8RpQJ1zny+c5DnfqvxXEtFr5M8nvF8RmgLuD+DqiHkzAcACc8fv3zn+ZznudYU8M9gXCHhvh9859kWf8DznSdfHUrg/zNag+d3RqWA+zr0qivlzPdXnsYbQ3uZV3+mw+r+Xvheh9XdkV77CUsIIYQQQgghba+eJix56V6bYZPtbd68eVLraDWkefPmtUkd9vb2zdaRlJTUJnXI6/bt283GoqWlxcyg2dlFRUU1e47vv/9+R4dHCCGEEEIIg3re5BQZGdns+006OjptUseRI0dQWyt7mIE8Swm0pR49eiA7O5sz/3Uwb948ZtKUptTVuYfnEEIIIYS8yd7kd886CjXe5NS9e3d07969XetoWFLgVaCsrNzite46o65du6Jr164dHQYhhBBCCCG8aNgkIYQQQgghhHQC1PNGCCGEEEIIaTEJTVjy0lHPGyGEEEIIIYR0AtTzRgghhBBCCGkxmrDk5aOeN0IIIYQQQgjpBKjxRgghhBBCCCGdgEAikUg6OgjSOn5+fti5c6fU9sLCQqxatQqlpaXYt28f5zHu3r0Lc3NzmJubIz8/XypfIpFgx44diI+PR05ODsRiMfr06QNXV1cEBATItZxAREQEVq5cCQAQCoXQ09ODnZ0dPvroI3z22WcQiUSs8jk5OVi5ciUyMjJQXl6O3r17w8fHB6GhodDQ0GCVvXz5MqKionD69GmUlZWhd+/ecHZ2xqJFi2BlZYXMzEy4uLjgyZMn0NPTY+3r4OCA8ePHIyIiAgBgamqKW7duITk5GT4+Pqyy9vb2yM3NRUJCAvz8/Fjlm4qOjsbSpUtRVFQEMzMzGBgY4ObNm9DW1paq28/PD2ZmZpzXb8WKFUyMsly5cgUxMTE4e/YsHj58CFNTU8ybNw8LFizgPG5TkTjcovLtQZ7hF8oQK3QMJXB/5NXJ8Z0W3zHaYhiJonW0RYztHUNbeBlDdhQ9j84Q48sQLviAv4zkCGd+ZzhP0rlEwLOjQ+jUPq7J6rC6d6kO7bC6OxL1vHVyY8aMQXFxMSvxNQYaS0xMxOTJk1FZWYnffvuNlSeRSDB16lQEBgbC09MTx48fx9WrV7Fp0yaoq6tj1apVctdjb2+P4uJi3L59GxkZGfD29kZ0dDSGDRuGiooKplxWVhYcHR1RU1ODw4cPo6CgAFFRUdi5cyfc3NxQU1PDlD106BCGDh2K6upqJCUlIS8vDz/88AN0dXWxfPlyuWNrzMTEBAkJCaxtWVlZKCkpgaamplT5yMhIqesfEBDAKlNRUYF169Y1W1/jfUNCQphr1ZCaWxy+wZ9//gkDAwP8+9//Rk5ODsLCwhAaGopvvvmmhWdPCCGEEEJeZTRhSScnEolgZGTUqn0lEgkSEhKwZcsW9OrVC3FxcRg+fDiTn5qaipSUFOzfvx9eXl7MdnNzc4wePRot6bRVVlZm4uzRowf69+8PNzc3DBw4EGvWrMGqVasgkUgwa9Ys2NraIj09HUpKL75b6NOnD6ysrDBo0CDExsZiyZIlqKysxCeffAJPT0/s3buXqcfMzAyOjo4oLS1t1TWZNm0aYmNjcefOHZiYmAAA4uPjMW3aNOzatUuqvLa2Nu/1DwgIwIYNGzB//nyphd6FQiFrfy0tLda1koe/vz/r/+bm5jh//jzS09Pxr3/9S+7jEEIIIYS0RD0tFfDSUc/bGywjIwOVlZVwdXXFjBkzkJaWxuoFS05OhrW1Navh1phAoNgPrI2NDd5//32kp6cDALKzs5Gbm4vg4GCm4dZg4MCBcHV1RXJyMgDg2LFjePjwIRYvXizz2E2HSMrL0NAQHh4ezHDUyspKpKamSjWQWsLX1xcWFhaIjIxs9TFaqqysDF27dn1p9RFCCCGEkPZHjbdO7tChQ9DS0mKSt7e33PvGxcXBx8cHQqEQ9vb2sLCwQGpqKpNfUFAAa2tr1j5BQUFMXb169VI4fhsbGxQVFTH1AYCtra3Msra2tkyZwsJCZv+25u/vj8TEREgkEuzZswd9+/aFg4ODzLJLlixhXX8tLS1kZmayyggEAsTExGDbtm24efNmm8fb1Pnz55GWloa5c+c2W6a6uhrl5eWsVFdd2+6xEUIIIeT1IYGgw9KbihpvnZyLiwuys7OZtGnTJrn2Ky0tRXp6OqZPn85smz59OuLj41nlmvauhYWFITs7G+Hh4Xj69KnC8UskErl78BqXbc95dsaOHYunT5/i9OnTiI+P5+x1W7RoEev6Z2dnw9HRUaqch4cH3n333Va/iyevnJwcjBs3DuHh4XBzc2u2XHR0NHR1dVnpTHRau8ZGCCGEEEIUQ++8dXKamppyzfjY1O7du1FVVcVqaEgkEojFYuTm5sLOzg6WlpZSM1AaGBjAwMBA6t2t1srLy2MmWLGysgIA5Obmyuzpys/Ph6WlJatsfn4+nJycmj2+jo4OgBfDCJsOpSwtLYWurq7UPsrKypgxYwZWrFiBCxcusN6pa0pfX1/u6x8TEwMnJycsWrRIrvItlZubi1GjRmHOnDn48ssvOcuGhoYiODiYtW2d6Nd2iYsQQgghhLQN6nl7Q8XFxSEkJITVY3TlyhW4uLgwvW++vr64fv069u/f3y4x5Ofn4+jRo5g4cSKAF9Pn29jYIDY2FmIxezr4K1eu4OTJk/D19QUAuLu7Q19fH2vXrpV57IYJSywtLaGkpISLFy+y8ouLi3Hv3j2pYaEN/P39cerUKYwbNw5dunRR5DQZQ4YMwUcffYSlS5e2yfEay8nJgYuLC2bOnInVq1fzlheJRNDR0WElZZFKm8dFCCGEkNeXWCLosPSmop6311hZWRmys7NZ27p27YrHjx/j0qVLSEpKknpnzNfXF2FhYYiOjoaPjw/S09OZNdY8PDxgaGiIW7duITU1FUKhUO5Y6urqUFJSArFYjEePHiEzMxOrVq2Cg4MD0xMlEAiwY8cOuLu7Y+LEiQgNDYWRkREuXLiAkJAQODk5ISgoCMCLHscdO3bA29sbXl5eCAwMhIWFBR4+fIi0tDTcvn0bKSkp0NbWxty5cxESEgJlZWUMHDgQ9+/fR1hYGGxtbeHu7i4zXltbWzx8+FBqXbmmKioqUFJSwtqmoaHB9Pg1tXr1atjb20NZue1+9Boabu7u7ggODmbiEQqFMDAwaLN6CCGEEEJIx6Ket9dYZmYmBg0axErh4eGIi4uDnZ2dzMk+xo8fj8ePH+PgwYMQCARITU3Fxo0bceTIEYwePRrW1tbw9/eHiYkJzp49K3csOTk5MDY2Ru/evTFy5EikpaUhNDQUZ86cgZaWFlNu+PDhyMrKglAohKenJywsLBAaGoqZM2fixIkTrAW9x40bh3PnzkFFRQVTp06FjY0NfH19UVZWxlqDLjY2FrNnz8ayZctgb2+PadOmwczMDMePH+dsRHXr1g3q6uqc5xUeHg5jY2NWam4GTODFcE9/f39UVVXJc9nk8uOPP+LBgwdISkpixfHOO++0WR2EEEIIIU3VSwQdlt5UAkl7zvxACOk0InBE4WNoSao585Uh5sx/IJBeCL2pPvVPOPOVeD7SqpS4ez3zYMgbQ5WY+xh/l+lx5nt0K+St4x+JFme+roD7Wo94VMCZn921N28M5QI1zvw6nu//VFHPma8j4f8SQ8wzo5gSuO/3Q55nqgb8IwiEPM+tkCcGvuce4L8WfNehWsB9HvVynSf3/eI7Bt/P/2MB90gGAIgUeHLmh0u4P6euPuX++T14lv+5XzrmD878DRlvcebPHHGdtw4jYQVn/j/13D//3YXcE4bVyvHdvIjnfvPvzz1DcTX4h+Lz/fzy4fu5qJJjgBnf5xRfjIqegzw0JDWc+cGCj9o9huZ4P+f+eWlPP6q/3WF1dyTqeSOEEEIIIYSQToAab0RhTdc5a5zOnDnT0eF1evPmzWv2+s6bN6+jwyOEEELIG0os6bj0pqIJS4jCmk6K0ljPnj1fXiCvqcjISCxcuFBmXnMToxBCCCGEkNcPNd6IwlqzzhyRX/fu3dtsXT1CCCGEkLYieYMnDukoNGySEEIIIYQQQjoB6nkjhBBCCCGEtNibvFh2R6GeN0IIIYQQQgjpBKjxRgghhBBCCCGdAA2bJIQQQgghhLQY30LppO0JJBLJG7xSQufm5+eHnTt3Sm0vLCzEqlWrUFpain379nEe4+7duzA3N4e5uTny8/Ol8iUSCXbs2IH4+Hjk5ORALBajT58+cHV1RUBAgFwzTUZERGDlypUAAKFQCD09PdjZ2eGjjz7CZ599BpFIxCqfk5ODlStXIiMjA+Xl5ejduzd8fHwQGhoKDQ0NVtnLly8jKioKp0+fRllZGXr37g1nZ2csWrQIVlZWyMzMhIuLC548eQI9PT3Wvg4ODhg/fjwiIiIAAKamprh16xaSk5Ph4+PDKmtvb4/c3FwkJCTAz8+PVb6p6OhoLF26FEVFRTAzM4OBgQFu3rwJbW1tqbr9/PxgZmbGef1WrFjBxMjn0aNHGDhwIO7duyfznLlE4IjcZduLEjr+40ieGBT9ZdVZftm19/14GdeB7xw6y714U/Ddj0iBJ2d+hORwW4ZDSJto78/ScIxt1+Nz8Xp6ucPqPqA1qMPq7kg0bLKTGzNmDIqLi1mJrzHQWGJiIiZPnozKykr89ttvrDyJRIKpU6ciMDAQnp6eOH78OK5evYpNmzZBXV0dq1atkrsee3t7FBcX4/bt28jIyIC3tzeio6MxbNgwVFRUMOWysrLg6OiImpoaHD58GAUFBYiKisLOnTvh5uaGmpoapuyhQ4cwdOhQVFdXIykpCXl5efjhhx+gq6uL5cuXyx1bYyYmJkhISGBty8rKQklJCTQ1NaXKR0ZGSl3/gIAAVpmKigqsW7eu2foa7xsSEsJcq4bU3BpvssyaNQsDBgyQuzwhhBBCSGvVSwQdlt5UNGyykxOJRDAyMmrVvhKJBAkJCdiyZQt69eqFuLg4DB8+nMlPTU1FSkoK9u/fDy8vL2a7ubk5Ro8ejZZ02iorKzNx9ujRA/3794ebmxsGDhyINWvWYNWqVZBIJJg1axZsbW2Rnp4OJaUX3y306dMHVlZWGDRoEGJjY7FkyRJUVlbik08+gaenJ/bu3cvUY2ZmBkdHR5SWlrbqmkybNg2xsbG4c+cOTExMAADx8fGYNm0adu3aJVVeW1ub9/oHBARgw4YNmD9/vtR6bUKhkLW/lpYW61q1xHfffYfS0lKEh4fj559/bvH+hBBCCCHk1UY9b2+wjIwMVFZWwtXVFTNmzEBaWhqrFyw5ORnW1tashltjAoFi33rY2Njg/fffR3p6OgAgOzsbubm5CA4OZhpuDQYOHAhXV1ckJycDAI4dO4aHDx9i8eLFMo/dkuGCjRkaGsLDw4MZjlpZWYnU1FT4+/u36ngA4OvrCwsLC0RGRrb6GHxyc3MRGRmJXbt2SV07QgghhBDyeqC/8jq5Q4cOQUtLi0ne3t5y7xsXFwcfHx8IhULY29vDwsICqampTH5BQQGsra1Z+wQFBTF19erVS+H4bWxsUFRUxNQHALa2tjLL2traMmUKCwuZ/duav78/EhMTIZFIsGfPHvTt2xcODg4yyy5ZsoR1/bW0tJCZmckqIxAIEBMTg23btuHmzZttHm91dTV8fX3xf//3f+jdu7fc+5SXl7NSXXVtm8dGCCGEkNeXRCLosPSmosZbJ+fi4oLs7Gwmbdq0Sa79SktLkZ6ejunTpzPbpk+fjvj4eFa5pr1rYWFhyM7ORnh4OJ4+fapw/BKJRO4evMZl23OenbFjx+Lp06c4ffo04uPjOXvdFi1axLr+2dnZcHR0lCrn4eGBd999t9Xv4nEJDQ2Fra0t617yiY6Ohq6uLiudjU5r89gIIYQQQkjboXfeOjlNTU25Znxsavfu3aiqqmI1NCQSCcRiMXJzc2FnZwdLS0upGSgNDAxgYGAg9e5Wa+Xl5TETrFhZWQF4MQRQVk9Xfn4+LC0tWWXz8/Ph5OTU7PF1dHQAAGVlZVJDKUtLS6Grqyu1j7KyMmbMmIEVK1bgwoULrHfqmtLX15f7+sfExMDJyQmLFi2Sq7y8fv31V1y7dg179uwB8L+Grb6+PsLCwpiZPhsLDQ1FcHAwa9taUUabxkUIIYSQ15tY/Ob2gHUU6nl7Q8XFxSEkJITVY3TlyhW4uLgwvW++vr64fv069u/f3y4x5Ofn4+jRo5g4cSKAF9Pn29jYIDY2FmKxmFX2ypUrOHnyJHx9fQEA7u7u0NfXx9q1a2Ueu2HCEktLSygpKeHixYus/OLiYty7d09qWGgDf39/nDp1CuPGjUOXLl0UOU3GkCFD8NFHH2Hp0qVtcrwGP/30E65cucLcxx07dgAAzpw5g/nz58vcRyQSQUdHh5WURSptGhchhBBCCGlb1PP2GisrK0N2djZrW9euXfH48WNcunQJSUlJUu+M+fr6IiwsDNHR0fDx8UF6ejqzxpqHhwcMDQ1x69YtpKamQigUyh1LXV0dSkpKIBaL8ejRI2RmZmLVqlVwcHBgeqIEAgF27NgBd3d3TJw4EaGhoTAyMsKFCxcQEhICJycnBAUFAXjR47hjxw54e3vDy8sLgYGBsLCwwMOHD5GWlobbt28jJSUF2tramDt3LkJCQqCsrIyBAwfi/v37CAsLg62tLdzd3WXGa2tri4cPH0qtK9dURUUFSkpKWNs0NDSYHr+mVq9eDXt7eygrt92PXt++fVn/f/jwIYAX59DaiVsIIYQQQvi8yVP2dxTqeXuNZWZmYtCgQawUHh6OuLg42NnZyZzsY/z48Xj8+DEOHjwIgUCA1NRUbNy4EUeOHMHo0aNhbW0Nf39/mJiY4OzZs3LHkpOTA2NjY/Tu3RsjR45EWloaQkNDcebMGWhpaTHlhg8fjqysLAiFQnh6esLCwgKhoaGYOXMmTpw4wVrQe9y4cTh37hxUVFQwdepU2NjYwNfXF2VlZaw16GJjYzF79mwsW7YM9vb2mDZtGszMzHD8+HHORlS3bt2grq7OeV7h4eEwNjZmpeZmwAReDPf09/dHVVWVPJeNEEIIIYQQhkDSnjM/EEI6jQgc6egQoISO/ziSJwYxFPumUdH9X5b2vh8v4zrwnUNnuRdvCr77ESnw5MyPkBxuy3AIaRPt/VkajrHtenwubk+udVjdJ7r077C6OxINmySEvDS1PJ39ItTzHqOO5xiK/pIUQsxbplrBj04VOergw3eefOehLMe1rgb3e5Bdxc848x8raXLmt0XDqZ7nGFqo5tmff/i3gOdaS3hi4HtmAUBZwWeihuc82uJLCb5j8J2DPNfh6lNDzny+xlmEgPuP2KWSY7wxqKGOM7+K5+dfVY6fLUW/VHgVvuhqixjb+zxfxpdxbXEv+GJ4lb9kEtOwyZeOhk0ShTVd56xxOnPmTEeH1+nNmzev2es7b968jg6PEEIIIeS18eTJE8yYMYNZSmnGjBnMRHiy1NbWYsmSJejfvz80NTXRo0cPfPzxx7h//z6r3MiRIyEQCFjJx8enxfFRzxtRWNNJURrr2bPnywvkNRUZGYmFCxfKzGtuYhRCCCGEkPb2Oi6WPXXqVNy9exdHjx4FAHz66aeYMWMGDh48KLN8ZWUlLl26hOXLl2PgwIF48uQJgoKC4OXlhT/++INVds6cOYiMjGT+zze3gizUeCMKa806c0R+3bt3b7N19QghhBBCiGx5eXk4evQosrKymLWQt2/fDicnJ1y/fl3mElO6uro4ceIEa9vmzZsxZMgQ3L59G71792a2a2howMjISKEYadgkIYQQQgghpFOprq5GeXk5K1VXc7/nzOf8+fPQ1dVlGm4AMHToUOjq6uLcuXNyH6esrAwCgUBqyaakpCTo6+vD3t4eCxcuREVFRYtjpMYbIYQQQgghpMXEEkGHpejoaOa9tIYUHR2t0PmUlJTIHO3UvXt3qXV9m1NVVYWlS5di6tSprNdbpk2bhuTkZGRmZmL58uX46aef8NFHH7U4Rho2SQghhBBCCOlUQkNDERwczNrWeD3gxiIiIrBy5UrO4128eBEAIBBIv8cnkUhkbm+qtrYWPj4+EIvF2LJlCytvzpw5zL/79esHS0tLvP3227h06RLeeust3mM3oMYbIYQQQgghpMXEHbhqhUgkarax1tS//vUv3pkdTU1NcfXqVfz3v/+Vynvw4AEMDbmXMqmtrcXkyZPx999/49dff+WdVO6tt96CiooKCgsLqfFGCCGEEEIIIQCgr68PfX193nJOTk4oKyvD77//jiFDhgAALly4gLKyMgwbNqzZ/RoaboWFhcjIyEC3bt1468rJyUFtbS2MjY3lPxHQO2+EEEIIIYSQVqgXCzostQdbW1uMGTMGc+bMQVZWFrKysjBnzhx88MEHrJkmbWxssHfvXgBAXV0dJk2ahD/++ANJSUmor69HSUkJSkpKUFNTAwC4efMmIiMj8ccff6CoqAhHjhyBt7c3Bg0ahOHDh7coRup568T8/Pywc+dOqe2FhYVYtWoVSktLsW/fPs5j3L17F+bm5jA3N0d+fr5UvkQiwY4dOxAfH4+cnByIxWL06dMHrq6uCAgIkGuZgMbjjIVCIfT09GBnZ4ePPvoIn332mVSXd05ODlauXImMjAyUl5ejd+/e8PHxQWhoKDQ0NFhlL1++jKioKJw+fRplZWXo3bs3nJ2dsWjRIlhZWSEzMxMuLi548uSJ1Iw/Dg4OGD9+PCIiIgC86C6/desWkpOTpbrW7e3tkZubi4SEBPj5+bHKNxUdHY2lS5eiqKgIZmZmMDAwwM2bN6GtrS1Vt5+fH8zMzDiv34oVK5gYuSQmJmLDhg0oKCiAnp4eJk2ahG+++YZ3vwZKUHzsQxXPR8pfVV05801EpQrHUC1R4cxXEdRx5usK+GeqCvzjBGe+4cWbnPkfz1rKW8f4umuc+f/R6MGZ/+13Lpz5rrP+wxuDlepDzvxSJQ3O/AqJKmf+nWo93hj6q8n3gnhz/ivhHraiIajhPUYlz3koQdyimGS5X80dp6pSPWe+heojhWNQ9DPgKbivkxq4f/YA4ODZ3pz5DmO4n4elkmOc+TECD94YIiSHOfPL69U487sIK3nr4LvW9eD+w5Rv/1o5vpsXKni/63jqUAX3M9tWx+Ai5rmO8ngZvxs1UKtwHaTtJCUlITAwEO7u7gAALy8vqb+nrl+/jrKyMgAv/pY+cOAAgBd/3zWWkZGBkSNHQlVVFb/88gu+/vprPH36FCYmJhg7dixWrFgBoVDYovio8dbJjRkzBgkJCaxtBgYGcu+fmJiIyZMn4/Tp0/jtt99YrX+JRIKpU6di3759WLZsGWJjY9G9e3f8/fffOHHiBFatWoXExES56rG3t8fJkychFovx6NEjZGZmYtWqVfjhhx+QmZnJNGyysrLg6uoKV1dXHD58GIaGhvj9998REhKCX3/9FRkZGVBVffEHwqFDhzBx4kR4eHggKSkJffv2xT///IMff/wRy5cvR2pqqtzXoYGJiQkSEhJYjbesrCyUlJRAU1NTqnxkZCTrBVQArEYaAFRUVGDdunUyX5Q1MTFBcXEx8/9169bh6NGjOHnyJLNNS0uLN+4NGzZg/fr1+L//+z84OjqiqqoKf/31F+9+hBBCCCHkf7p27Yp///vfnGUkkv816k1NTVn/l8XExASnTp1qk/io8dbJiUSiVi/2J5FIkJCQgC1btqBXr16Ii4tjNd5SU1ORkpKC/fv3w8vLi9lubm6O0aNH8z6ojSkrKzNx9ujRA/3794ebmxsGDhyINWvWYNWqVZBIJJg1axZsbW2Rnp4OJaUX38j16dMHVlZWGDRoEGJjY7FkyRJUVlbik08+gaenJ9NtDQBmZmZwdHREaWlpq67JtGnTEBsbizt37sDExAQAEB8fj2nTpmHXrl1S5bW1tXmvf0BAADZs2ID58+dLTT8rFApZ+2tpabGulTyePHmCL7/8EgcPHsTo0aOZ7fb29nIfgxBCCCGkpSSS9hm+SJpH77y9wTIyMlBZWQlXV1fMmDEDaWlprMUCk5OTYW1tzWq4NSbPlKlcbGxs8P777yM9PR0AkJ2djdzcXAQHBzMNtwYDBw6Eq6srkpOTAQDHjh3Dw4cPsXjxYpnHbjpEUl6Ghobw8PBghqNWVlYiNTUV/v7+rToeAPj6+sLCwgKRkZGtPgaXEydOQCwW4969e7C1tUWvXr0wefJk3Llzp13qI4QQQgghHYMab53coUOHoKWlxSRvb2+5942Li4OPjw+EQiHs7e1hYWHBGmpYUFDAejkTAIKCgpi6evXqpXD8NjY2KCoqYuoDXrwsKoutrS1TprCwkNm/rfn7+yMxMRESiQR79uxB3759pcYwN1iyZAnr+mtpaSEzM5NVRiAQICYmBtu2bcPNm9zvQrXGX3/9BbFYjKioKGzcuBF79uzB48eP4ebmxrwo21R1dTXKy8tZqa6axtwTQgghRH4duUj3m4oab52ci4sLsrOzmbRp0ya59istLUV6ejqmT5/ObJs+fTri4+NZ5Zr2roWFhSE7Oxvh4eF4+vSpwvHLu+hh07ItGbLZUmPHjsXTp09x+vRpxMfHc/a6LVq0iHX9s7Oz4ejoKFXOw8MD7777LpYvX97m8YrFYtTW1mLTpk3w8PDA0KFDkZyczExXK0t0dDR0dXVZ6Ux0WpvHRgghhBBC2g6989bJaWpqyjXjY1O7d+9GVVUVq6EhkUggFouRm5sLOzs7WFpaSs1AaWBgAAMDA6l3t1orLy+PmW3RysoKAJCbmyuzpys/Px+Wlpassvn5+XBycmr2+A0LJJaVlUkNpSwtLYWurq7UPsrKypgxYwZWrFiBCxcusN6pa0pfX1/u6x8TEwMnJycsWrRIrvLyalgfxM7OjtlmYGAAfX193L59W+Y+oaGhCA4OZm1bJ/q1TeMihBBCCCFti3re3lBxcXEICQlh9RhduXIFLi4uTO+br68vrl+/jv3797dLDPn5+Th69CgmTpwI4MX0qjY2NoiNjYVYzJ56+8qVKzh58iR8fX0BAO7u7tDX18fatWtlHrthwhJLS0soKSnh4sWLrPzi4mLcu3dPalhoA39/f5w6dQrjxo1Dly5dFDlNxpAhQ/DRRx9h6VL+aeJbomGSmevXrzPbHj9+jIcPH6JPnz4y9xGJRNDR0WElZRH3FPuEEEIIIY29buu8dQbU8/YaKysrQ3Z2Nmtb165d8fjxY1y6dAlJSUlS74z5+voiLCwM0dHR8PHxQXp6OrPGmoeHBwwNDXHr1i2kpqa2aF2Kuro6lJSUSC0V4ODgwPRECQQC7NixA+7u7pg4cSJCQ0NhZGSECxcuICQkBE5OTggKCgLwosdxx44d8Pb2hpeXFwIDA2FhYYGHDx8iLS0Nt2/fRkpKCrS1tTF37lyEhIRAWVkZAwcOxP379xEWFgZbW1tmDY+mbG1t8fDhQ6l15ZqqqKhASQl73SENDQ2mx6+p1atXw97eHsrKbfejZ2VlhXHjxmHBggXYtm0bdHR0EBoaChsbG7i4cK/1RQghhBBCOg/qeXuNZWZmYtCgQawUHh6OuLg42NnZyZzsY/z48Xj8+DEOHjwIgUCA1NRUbNy4EUeOHMHo0aNhbW0Nf39/mJiY4OzZs3LHkpOTA2NjY/Tu3RsjR45EWloaQkNDcebMGdY6ZsOHD0dWVhaEQiE8PT1hYWGB0NBQzJw5EydOnGAt6D1u3DicO3cOKioqmDp1KmxsbODr64uysjKsWrWKKRcbG4vZs2dj2bJlsLe3x7Rp02BmZobjx49zNqK6desGdXV1zvMKDw+HsbExKzU3AybwoqHl7++PqqoqeS6b3Hbt2gVHR0eMHTsWzs7OUFFRwdGjR6GiQr1phBBCCGkfNGHJyyeQtOfMD4SQTiMCRzo6BCiB/+NIDMU+sOWp41WIoTOcpzLEnPl8+8tzjm1xHh3tZZynos+LPPhibIsYanm+U1bheebaQoRgLHe+5HC7x0BIY3w/e+Hgfmbb0+C7hR1W95+9LDus7o5EwyYJIYQQQgghLSZp/+9TSBM0bJIorOk6Z43TmTNnOjq8Tm/evHnNXt958+Z1dHiEEEIIIeQloZ43orCmk6I01rNnz5cXyGsqMjISCxculJnX3MQohBBCCCHk9UONN6Kw1qwzR+TXvXv3NltXjxBCCCGkrbzJE4d0FBo2SQghhBBCCCGdAPW8EUIIIYQQQlpM/AYvlt1RqOeNEEIIIYQQQjoBarwRQgghhBBCSCdAwyYJIYQQQgghLVZPE5a8dNR468T8/Pywc+dOqe2FhYVYtWoVSktLsW/fPs5j3L17F+bm5jA3N0d+fr5UvkQiwY4dOxAfH4+cnByIxWL06dMHrq6uCAgIkGumyYiICKxcuRIAIBQKoaenBzs7O3z00Uf47LPPIBKJWOVzcnKwcuVKZGRkoLy8HL1794aPjw9CQ0OhoaHBKnv58mVERUXh9OnTKCsrQ+/eveHs7IxFixbBysoKmZmZcHFxwZMnT6Cnp8fa18HBAePHj0dERAQAwNTUFLdu3UJycjJ8fHxYZe3t7ZGbm4uEhAT4+fmxyjcVHR2NpUuXoqioCGZmZjAwMMDNmzehra0tVbefnx/MzMw4r9+KFSuYGJtz8eJFLF26FH/++ScEAgHeeecdrF27Fg4ODpz7NaYEidxlm1PH05mvJ3nOma8qqeOtQ8ATp3Z9NWd+hVDEma8k4b8Of0hMOPMlPL/MBigX89bxj0CLM18V9Zz5vWsfc+bfU9HjjaEaKpz5fM+MCrjvp7oc97tQos+Zz3et+wi5r4MY/H94yBMnl2cCVd4yIgXreCzQ4Mzn+7kBAAnPteA7hjrP/eb7fACADRlvceYvcfmDM7+K58+a8no13hgiJIe58wVjOfPDJD/z1qEC7pWNa3mulYjn57+r+BlvDBVK3J+FYp4Y+J4XeX62+PAdg+8zSJ4Y2uJ3Hx8h7/0WcubzPdfkzULDJju5MWPGoLi4mJX4GgONJSYmYvLkyaisrMRvv/3GypNIJJg6dSoCAwPh6emJ48eP4+rVq9i0aRPU1dWxatUqueuxt7dHcXExbt++jYyMDHh7eyM6OhrDhg1DRUUFUy4rKwuOjo6oqanB4cOHUVBQgKioKOzcuRNubm6oqalhyh46dAhDhw5FdXU1kpKSkJeXhx9++AG6urpYvny53LE1ZmJigoSEBNa2rKwslJSUQFNTU6p8ZGSk1PUPCAhglamoqMC6deuara/xviEhIcy1akjNrfHW+PgeHh7o3bs3Lly4gLNnz0JHRwceHh6ora1t4RUghBBCCJGPRCzosPSmoqZ8JycSiWBkZNSqfSUSCRISErBlyxb06tULcXFxGD58OJOfmpqKlJQU7N+/H15eXsx2c3NzjB49GhI5eigaKCsrM3H26NED/fv3h5ubGwYOHIg1a9Zg1apVkEgkmDVrFmxtbZGeng4lpRffLfTp0wdWVlYYNGgQYmNjsWTJElRWVuKTTz6Bp6cn9u7dy9RjZmYGR0dHlJaWtuqaTJs2DbGxsbhz5w5MTF70rsTHx2PatGnYtWuXVHltbW3e6x8QEIANGzZg/vz5Uuu1CYVC1v5aWlqsayWP69ev48mTJ4iMjGRiXrFiBQYMGIDbt2+jb9++ch+LEEIIIYS8uqjn7Q2WkZGByspKuLq6YsaMGUhLS2P1giUnJ8Pa2prVcGtMIFDsWw8bGxu8//77SE9PBwBkZ2cjNzcXwcHBTMOtwcCBA+Hq6ork5GQAwLFjx/Dw4UMsXrxY5rGbDpGUl6GhITw8PJjhqJWVlUhNTYW/v3+rjgcAvr6+sLCwQGRkZKuPwcXa2hr6+vqIi4tDTU0Nnj9/jri4ONjb26NPnz7tUichhBBCCHn5qPHWyR06dAhaWlpM8vb2lnvfuLg4+Pj4QCgUwt7eHhYWFkhNTWXyCwoKYG1tzdonKCiIqatXr14Kx29jY4OioiKmPgCwtbWVWdbW1pYpU1hYyOzf1vz9/ZGYmAiJRII9e/agb9++zb47tmTJEtb119LSQmZmJquMQCBATEwMtm3bhps3b7Z5vNra2sjMzMS///1vqKurQ0tLC8eOHcORI0egrCy7c726uhrl5eWsVFdNQywJIYQQIj+xpOPSm4oab52ci4sLsrOzmbRp0ya59istLUV6ejqmT5/ObJs+fTri4+NZ5Zr2roWFhSE7Oxvh4eF4+vSpwvFLJBK5e/Aal23JkM2WGjt2LJ4+fYrTp08jPj6es9dt0aJFrOufnZ0NR0dHqXIeHh549913W/0uHpfnz5/D398fw4cPR1ZWFn777TfY29vD09MTz5/LniAkOjoaurq6rHQmOq3NYyOEEEIIIW2H3nnr5DQ1NeWa8bGp3bt3o6qqitXQkEgkEIvFyM3NhZ2dHSwtLaVmoDQwMICBgYHUu1utlZeXx0ywYmVlBQDIzc2V2dOVn58PS0tLVtn8/Hw4OTk1e3wdHR0AQFlZmdRQytLSUujq6krto6ysjBkzZmDFihW4cOEC6526pvT19eW+/jExMXBycsKiRYvkKi+v3bt3o6ioCOfPn2eGm+7evRtdunTB/v37pWbOBIDQ0FAEBweztq0T/dqmcRFCCCHk9Vb/Bk8c0lGo5+0NFRcXh5CQEFaP0ZUrV+Di4sL0vvn6+uL69evYv39/u8SQn5+Po0ePYuLEiQBeTJ9vY2OD2NhYiMXsaXWvXLmCkydPwtfXFwDg7u4OfX19rF27VuaxGyYssbS0hJKSEi5evMjKLy4uxr1796SGhTbw9/fHqVOnMG7cOHTp0kWR02QMGTIEH330EZYuXdomx2tQWVkJJSUlVg9mw/+bXscGIpEIOjo6rKQs4p4WnhBCCCGEdCzqeXuNlZWVITs7m7Wta9euePz4MS5duoSkpCSpd8Z8fX0RFhaG6Oho+Pj4ID09nVljzcPDA4aGhrh16xZSU1MhFHKvS9JYXV0dSkpKIBaL8ejRI2RmZmLVqlVwcHBgeqIEAgF27NgBd3d3TJw4EaGhoTAyMsKFCxcQEhICJycnBAUFAXjR47hjxw54e3vDy8sLgYGBsLCwwMOHD5GWlobbt28jJSUF2tramDt3LkJCQqCsrIyBAwfi/v37CAsLg62tLdzd3WXGa2tri4cPH0qtK9dURUUFSkpKWNs0NDSYHr+mVq9eDXt7+2bfRWsNNzc3LFq0CPPnz0dAQADEYjFiYmKgrKwMFxeXNquHEEIIIaQxMfW8vXTU8/Yay8zMxKBBg1gpPDwccXFxsLOzkznZx/jx4/H48WMcPHgQAoEAqamp2LhxI44cOYLRo0fD2toa/v7+MDExwdmzZ+WOJScnB8bGxujduzdGjhyJtLQ0hIaG4syZM9DS+t9ixA3vbQmFQnh6esLCwgKhoaGYOXMmTpw4wVrQe9y4cTh37hxUVFQwdepU2NjYwNfXF2VlZaw16GJjYzF79mwsW7YM9vb2mDZtGszMzHD8+HHORlS3bt2grq7OeV7h4eEwNjZmpeZmwAReDPf09/dHVVWVPJdNLjY2Njh48CCuXr0KJycnvPfee7h//z6OHj0KY2PjNquHEEIIIYR0LIGkPWd+IIR0GpE4rPAx6ni+D9KTyJ5ApYGqpI63DgG4P7K066s58yuEIs58JTk+Ev+QmHDmSyTc30QOUC7mreMfgRZnvirqOfNNax9x5t9T0eONoRLcQ2lFPDGogPt+qstxvwsl+pz5fNe6j/AxZ74Y/N8ayxMnl2cCVd4yIgXreCzgHiXA93MDABKea8F3DHWe+833+QAAazLe5sxf4vIHZ34Vz4Ci8no13hi6C7kn44oQjOXMD5P8zFuHCmQPaW9Qy3Ot+H72uoqf8cZQocT9WSjmiYHveZHnZ4sP3zGUeJ5JeWLgO0ZbEPLeb+6RTDU8+VHwaHFMbaVv3q0Oq/um7Zu5HBINmySEtBm+X4LlAu4/nFQE3H+QyOMpzx8kdTy/BJV5/igCACNUcObz/VHzFNwxvoiD+5c9n2IV2UN3G/DFCABCnvvJd7/rea51qYD/PUttAXdjnA/f/ZYHX+OrLf6IfSrgfya48DXm5aHoH8ryNM74zBxxXaH9+a5DF2GlQscH+BtnqwXv8x4jQsL9ZRlf447vXj1W0uSNQVF8z4M8jSJFG3gvo4HIR57zrFfwZ0PR3wftie8LNNL2aNgkUVjTdc4apzNnznR0eJ3evHnzmr2+8+bN6+jwCCGEEELIS0I9b0RhTSdFaaxnz54vL5DXVGRkJBYuXCgzr7mJUQghhBBC2lszk1qTdkSNN6Kw1qwzR+TXvXv3NltXjxBCCCGEdF40bJIQQgghhBBCOgHqeSOEEEIIIYS0GK3z9vJRzxshhBBCCCGEdALU80YIIYQQQghpsXrqeXvpqOeNEEIIIYQQQjoB6nkjhBBCCCGEtBi98/byUc/bK8rPzw8CgUAq3bhxA35+fhg/fjzvMe7evQtVVVXY2NjIzJdIJNi+fTucnJygo6MDLS0t2NvbY8GCBbhx44ZccUZERDCxKSsrQ19fHyNGjMDGjRtRXV0tVT4nJweTJ0+GgYEBRCIRLC0tsXz5clRWVkqVvXz5Mry9vWFoaAg1NTVYWVlhzpw5KCgoAABkZmZCIBCgtLRUal8HBwdEREQw/zc1NYVAIEBKSopUWXt7ewgEAiQmJkqVb5piYmIAAEVFRRAIBOjevTsqKipkLACuuwABAABJREFU1t1Qhis1jrE5CxYswODBgyESieDg4CCzzLVr1+Ds7Ax1dXX07NkTkZGRkEgkvMduTAyBwklR9VDiTbUQcqbnUOVMfPtXQ4U3iVDPmVR5kjzXUhlizsSnFsqcqS1ieBnPixrqFEp891ueZ44v1fEkeShB0q5JHoo+c23BSFjBmfjwXQcViHkTH779IySH+ZNgLGdSVFt8nvMlvudentTev1Nehrb4rON7bl+Fn03y6qDG2ytszJgxKC4uZiUzMzO5909MTMTkyZNRWVmJ3377jZUnkUgwdepUBAYGwtPTE8ePH8fVq1exadMmqKurY9WqVXLXY29vj+LiYty+fRsZGRnw9vZGdHQ0hg0bxmrYZGVlwdHRETU1NTh8+DAKCgoQFRWFnTt3ws3NDTU1NUzZQ4cOYejQoaiurkZSUhLy8vLwww8/QFdXF8uXL5c7tsZMTEyQkJDA2paVlYWSkhJoampKlY+MjJS6/gEBAawyFRUVWLduXbP1Nd43JCSEuVYNqbnFtxuTSCTw9/fHlClTZOaXl5fDzc0NPXr0wMWLF7F582asW7cOGzZs4D02IYQQQgjpPGjY5CtMJBLByMioVftKJBIkJCRgy5Yt6NWrF+Li4jB8+HAmPzU1FSkpKdi/fz+8vLyY7ebm5hg9enSLem2UlZWZOHv06IH+/fvDzc0NAwcOxJo1a7Bq1SpIJBLMmjULtra2SE9Ph5LSi+8N+vTpAysrKwwaNAixsbFYsmQJKisr8cknn8DT0xN79+5l6jEzM4Ojo6PMnjZ5TJs2DbGxsbhz5w5MTEwAAPHx8Zg2bRp27dolVV5bW5v3+gcEBGDDhg2YP3++1ELaQqGQtb+WlhbrWslr06ZNAIAHDx7g6tWrUvlJSUmoqqpCYmIiRCIR+vXrh4KCAmzYsAHBwcEQCDrHt5eEEEII6Vwk1PH30lHP22sqIyMDlZWVcHV1xYwZM5CWlsbqBUtOToa1tTWr4daYon/w29jY4P3330d6ejoAIDs7G7m5uQgODmYabg0GDhwIV1dXJCcnAwCOHTuGhw8fYvHixTKPraen16qYDA0N4eHhgZ07dwIAKisrkZqaCn9//1YdDwB8fX1hYWGByMjIVh9DUefPn4ezszNEIhGzzcPDA/fv30dRUVGHxUUIIYQQQtoWNd5eYYcOHYKWlhaTvL295d43Li4OPj4+EAqFsLe3h4WFBVJTU5n8goICWFtbs/YJCgpi6urVq5fC8dvY2DCNh4b31GxtbWWWtbW1ZcoUFhYy+7c1f39/JCYmQiKRYM+ePejbt2+z75EtWbKEdf21tLSQmZnJKtPwHty2bdtw8+bNNo9XHiUlJTA0NGRta/h/SUmJzH2qq6tRXl7OSnXVte0eKyGEEEJeH/USQYelNxU13l5hLi4uyM7OZlLD8Dk+paWlSE9Px/Tp05lt06dPR3x8PKtc0961sLAwZGdnIzw8HE+fPlU4folEIncPXuOyLZ1ooyXGjh2Lp0+f4vTp04iPj+fsdVu0aBHr+mdnZ8PR0VGqnIeHB959991Wv4vXFppe54Zr2Nz1j46Ohq6uLiudjU5r9zgJIYQQQkjr0TtvrzBNTU1YWFi0eL/du3ejqqqK1dCQSCQQi8XIzc2FnZ0dLC0tkZ+fz9rPwMAABgYGUu9utVZeXh4zwYqVlRUAIDc3V2ZPV35+PiwtLVll8/Pz4eTk1OzxdXR0AABlZWVSQylLS0uhq6srtY+ysjJmzJiBFStW4MKFC6x36prS19eX+/rHxMTAyckJixYtkqt8WzIyMpLqYfvnn38AQKpHrkFoaCiCg4NZ29aKMtonQEIIIYQQ0iao5+01FBcXh5CQEFaP0ZUrV+Di4sL0vvn6+uL69evYv39/u8SQn5+Po0ePYuLEiQBeTJ9vY2OD2NhYiMXst1uvXLmCkydPwtfXFwDg7u4OfX19rF27VuaxGyYssbS0hJKSEi5evMjKLy4uxr1796SGhTbw9/fHqVOnMG7cOHTp0kWR02QMGTIEH330EZYuXdomx2sJJycnnD59mjVb5/Hjx9GjRw+YmprK3EckEkFHR4eVlEUqLyliQgghhLwOxGJBh6U3FfW8dVJlZWXIzs5mbevatSseP36MS5cuISkpSeqdMV9fX4SFhSE6Oho+Pj5IT0+Hj48PQkND4eHhAUNDQ9y6dQupqakQCoVyx1JXV4eSkhKIxWI8evQImZmZWLVqFRwcHJieKIFAgB07dsDd3R0TJ05EaGgojIyMcOHCBYSEhMDJyQlBQUEAXvQ47tixA97e3vDy8kJgYCAsLCzw8OFDpKWl4fbt20hJSYG2tjbmzp2LkJAQKCsrY+DAgbh//z7CwsJga2sLd3d3mfHa2tri4cOH0NDQ4DyviooKqR4tDQ0NpsevqdWrV8Pe3h7Kym37Y3Xjxg08ffoUJSUleP78OXPf7ezsoKqqiqlTp2LlypXw8/PDsmXLUFhYiKioKISHh9NMk4QQQgghrxFqvHVSmZmZGDRoEGvbzJkzoa2tDTs7O5mTfYwfPx6fffYZDh48iI8++gipqanYvn07EhISsHbtWtTW1qJXr14YPXp0i9YIy8nJgbGxMYRCIXR1dWFnZ4fQ0FB89tlnrBkQhw8fjqysLKxcuRKenp4oLy9H7969MXPmTISGhrLKjhs3DufOnUN0dDSmTp2K8vJymJiYYNSoUaw16GJjY2FsbIxly5ahqKgI3bt3h4uLC1JSUjgbUd26deM9r/DwcISHh7O2zZ07F99//73M8lZWVvD398e2bdt4j90Ss2fPxqlTp5j/N9z3v//+G6amptDV1cWJEycwf/58vP322+jSpQuCg4OlhkUSQgghhLQlMS0V8NIJJO05OwQhpNOIwJGODgFK4P84UkEdZ341uId/qqOGM18M/t7KxxLuXlsVAfdvMw3wz+z5nOe7NRVw1yHiqcO4tpw3htsqXXnLcOG7lvJca0Wpop4z36iO/zo8FYo488sFapz5OpIq3jqqBdyjHfie65dxLfk8k3DHqCngf+7/qdfizO8u5J5Mi+861Mtxnfh+tmp53jjh218eEYKx3PmSwwrXQeTD93vpZfzsVfH8PoiB7JFGL0OX88UdVvcTJ+MOq7sjUc8bIYQQQgghpMUkb/C7Zx2FJiwhnJquc9Y4nTlzpqPD6/TmzZvX7PWdN29eR4dHCCGEEEJeIdTzRjg1nRSlsZ49e768QF5TkZGRWLhwocy85iZGIYQQQgghbyZqvBFOrVlnjsive/fubbauHiGEEELIy/QmT9nfUWjYJCGEEEIIIYR0AtTzRgghhBBCCGmxeloq4KWjnjdCCCGEEEII6QSo8UYIIYQQQgghnQANmySEEEIIIYS0GE1Y8vJRz9srys/PDwKBQCrduHEDfn5+GD9+PO8x7t69C1VVVdjY2MjMl0gk2L59O5ycnKCjowMtLS3Y29tjwYIFuHHjhlxxRkREMLEpKytDX18fI0aMwMaNG1FdXS1VPicnB5MnT4aBgQFEIhEsLS2xfPlyVFZWSpW9fPkyvL29YWhoCDU1NVhZWWHOnDkoKCgAAGRmZkIgEKC0tFRqXwcHB0RERDD/NzU1hUAgQEpKilRZe3t7CAQCJCYmSpVvmmJiYgAARUVFEAgE6N69OyoqKmTW3VCGKzWOsTkLFizA4MGDIRKJ4ODgIJWfmZmJcePGwdjYGJqamnBwcEBSUhLvcTuCEiScSR61UOZMfHVUQ0XhpCmo5UyqqOdMYgh4kwj1nEnR61Sk0o03yRMnV+KjDDFv4ruffIkvxrvKerypVKDOmfjq4Nu/VKCO51DlTIpe65dBW1DDmeTRXfiUM/Hhex5UIOZNfBT92ZRHhOQwdxKM5UxEfiqo50xt8XtL0WOooY4zkTcLNd5eYWPGjEFxcTErmZmZyb1/YmIiJk+ejMrKSvz222+sPIlEgqlTpyIwMBCenp44fvw4rl69ik2bNkFdXR2rVq2Sux57e3sUFxfj9u3byMjIgLe3N6KjozFs2DBWwyYrKwuOjo6oqanB4cOHUVBQgKioKOzcuRNubm6oqfnfL/dDhw5h6NChqK6uRlJSEvLy8vDDDz9AV1cXy5cvlzu2xkxMTJCQkMDalpWVhZKSEmhqakqVj4yMlLr+AQEBrDIVFRVYt25ds/U13jckJIS5Vg2puTXeGpNIJPD398eUKVNk5p87dw4DBgzATz/9hKtXr8Lf3x8ff/wxDh48yHtsQgghhJDWktQLOiy9qWjY5CtMJBLByMioVftKJBIkJCRgy5Yt6NWrF+Li4jB8+HAmPzU1FSkpKdi/fz+8vLyY7ebm5hg9ejQkEvm+TQIAZWVlJs4ePXqgf//+cHNzw8CBA7FmzRqsWrUKEokEs2bNgq2tLdLT06Gk9OJ7gz59+sDKygqDBg1CbGwslixZgsrKSnzyySfw9PTE3r17mXrMzMzg6Ogos6dNHtOmTUNsbCzu3LkDExMTAEB8fDymTZuGXbt2SZXX1tbmvf4BAQHYsGED5s+fL7Vem1AoZO2vpaXFulby2rRpEwDgwYMHuHr1qlT+smXLWP8PDAzEsWPHsHfvXnz44YctqosQQgghhLy6qOftNZWRkYHKykq4urpixowZSEtLY/WCJScnw9ramtVwa0wgUOwbDRsbG7z//vtIT08HAGRnZyM3NxfBwcFMw63BwIED4erqiuTkZADAsWPH8PDhQyxevFjmsfX09FoVk6GhITw8PLBz504AQGVlJVJTU+Hv79+q4wGAr68vLCwsEBkZ2epjtIeysjJ07dq1o8MghBBCyGusXtxx6U1FjbdX2KFDh6ClpcUkb29vufeNi4uDj48PhEIh7O3tYWFhgdTUVCa/oKAA1tbWrH2CgoKYunr16qVw/DY2NigqKmLqAwBbW1uZZW1tbZkyhYWFzP5tzd/fH4mJiZBIJNizZw/69u0r8z0yAFiyZAnr+mtpaSEzM5NVpuE9uG3btuHmzZttHm9r7NmzBxcvXsQnn3zS0aEQQgghhJA2RI23V5iLiwuys7OZ1DB8jk9paSnS09Mxffp0Ztv06dMRHx/PKte0dy0sLAzZ2dkIDw/H06f8L4bzkUgkcvfgNS7bkiGbLTV27Fg8ffoUp0+fRnx8PGev26JFi1jXPzs7G46OjlLlPDw88O6777b6Xby2lJmZCT8/P2zfvh329vbNlquurkZ5eTkr1VXXvsRICSGEEEJIS9E7b68wTU1NWFhYtHi/3bt3o6qqitXQkEgkEIvFyM3NhZ2dHSwtLZGfn8/az8DAAAYGBlLvbrVWXl4eM8GKlZUVACA3N1dmT1d+fj4sLS1ZZfPz8+Hk5NTs8XV0dAC8GCLYdChlaWkpdHV1pfZRVlbGjBkzsGLFCly4cIH1Tl1T+vr6cl//mJgYODk5YdGiRXKVbw+nTp3Chx9+iA0bNuDjjz/mLBsdHY2VK1eytjmvmIqREdPaM0RCCCGEvEZoqYCXj3reXkNxcXEICQlh9RhduXIFLi4uTO+br68vrl+/jv3797dLDPn5+Th69CgmTpwI4MX0+TY2NoiNjYVYzB6ofOXKFZw8eRK+vr4AAHd3d+jr62Pt2rUyj90wYYmlpSWUlJRw8eJFVn5xcTHu3bsnNSy0gb+/P06dOoVx48ahS5cuipwmY8iQIfjoo4+wdOnSNjleS2VmZmLs2LGIiYnBp59+yls+NDQUZWVlrPRu6OSXECkhhBBCyKvryZMnmDFjBnR1daGrq4sZM2bwTpYna4mvoUOHsspUV1cjICAA+vr60NTUhJeXF+7evdvi+KjnrZMqKytDdnY2a1vXrl3x+PFjXLp0CUlJSVLvjPn6+iIsLAzR0dHw8fFBeno6fHx8EBoaCg8PDxgaGuLWrVtITU2FUCiUO5a6ujqUlJRALBbj0aNHyMzMxKpVq+Dg4MD0RAkEAuzYsQPu7u6YOHEiQkNDYWRkhAsXLiAkJAROTk4ICgoC8KLHcceOHfD29oaXlxcCAwNhYWGBhw8fIi0tDbdv30ZKSgq0tbUxd+5chISEQFlZGQMHDsT9+/cRFhYGW1tbuLu7y4zX1tYWDx8+hIaGBud5VVRUoKSkhLVNQ0OD6fFravXq1bC3t4eyctv+WN24cQNPnz5FSUkJnj9/ztx3Ozs7qKqqMg23BQsWYOLEiUzMqqqqzU5aIhKJIBKJWNuUodKmcRNCCCHk9SZ+DScOmTp1Ku7evYujR48CAD799FPMmDGDdwmmMWPGsJakUlVVZeUHBQXh4MGDSElJQbdu3RASEoIPPvgAf/75Z4v+7qbGWyeVmZmJQYMGsbbNnDkT2trasLOzkznZx/jx4/HZZ5/h4MGD+Oijj5Camort27cjISEBa9euRW1tLXr16oXRo0djw4YNcseSk5MDY2NjCIVC6Orqws7ODqGhofjss89YDYThw4cjKysLK1euhKenJ8rLy9G7d2/MnDkToaGhrLLjxo3DuXPnEB0djalTp6K8vBwmJiYYNWoUaw262NhYGBsbY9myZSgqKkL37t3h4uKClJQUzkZUt27deM8rPDwc4eHhrG1z587F999/L7O8lZUV/P39sW3bNt5jt8Ts2bNx6tQp5v8N9/3vv/+GqakpEhMTUVlZiejoaERHRzPlnJ2dpSZYIYQQQgghsuXl5eHo0aPM2sQAsH37djg5OeH69evNjuoCuJf4KisrQ1xcHH744Qe4uroCAP7973/DxMQEJ0+ehIeHh9wxCiTtOTsEIaTTiMCRdq9DCa/+x40Y7T9+vy2uA1+cfHW8jPPkI891UDTOznAdXhdvyrV+Fc4zQjCWO19yuN1jeF2ooJ4zX8JzP+vkeAOpvZ+ZCHgqtL8iBEcedljdVaO1UV1dzdoma2RRS8THxyM4OFhqmKSenh5iY2Obncnbz88P+/btg6qqKvT09ODs7IzVq1cz80j8+uuvGD16NB4/fsx6ZWfgwIEYP3681DwEXKjnjRACoG0aFHy/xPjqEIJ//IW6hHtWzGoB99ADkYT7FzXf/gBQATXeMlw0wD+zpzx/EHBRQR1nfq0cH/+PJdxDi7sKKjnz2+KP2CoFf03p4jlnvjzXge+5FfDk18txLztDw4Yvxlqe81SR4+e7LY6hyPHlqaOr+Bln/mMlTd46FP5jnadxxte4k+cYnYGWpJozv1KgypkPALXg/sxvi9+NijbeFP0cbE+CDpywRNbkaytWrEBERESrj1lSUiJz4r7u3btLvUrT2Pvvvw9vb2/06dMHf//9N5YvX45Ro0bhzz//hEgkQklJCVRVVaXmWjA0NOQ8riw0YQnh1HSds8bpzJkzHR1epzdv3rxmr++8efM6OjxCCCGEkFeSrMnXQkNDZZaNiIiQmlCkafrjjz8ASC+lBfAvfzVlyhSMHTsW/fr1w4cffoiff/4ZBQUFOHyY+0uSliyr1eDVbcqTV0LTSVEa69mz58sL5DUVGRmJhQsXysxrbmIUQgghhJBXgbC+43reWjJE8l//+hd8fHw4y5iamuLq1av473//K5X34MEDGBoayh2bsbEx+vTpg8LCQgCAkZERampq8OTJE1bv2z///INhw4bJfVyAGm+ER2vWmSPy6969e5utq0cIIYQQQqTp6+tDX1+ft5yTkxPKysrw+++/Y8iQIQCACxcuoKysrEWNrEePHuHOnTswNjYGAAwePBgqKio4ceIEJk9+sTRTcXEx/vOf/zS7NFZzaNgkIYQQQgghpMWUxB2X2oOtrS3GjBmDOXPmICsrC1lZWZgzZw4++OAD1kyTNjY22Lt3LwDg6dOnWLhwIc6fP4+ioiJkZmbiww8/hL6+PiZMmAAA0NXVxaxZsxASEoJffvkFly9fxvTp09G/f39m9kl5Uc8bIYQQQgghhABISkpCYGAgs16wl5cXvvnmG1aZ69evo6ysDAAgFApx7do17Nq1C6WlpTA2NoaLiwtSU1Ohra3N7BMbGwtlZWVMnjwZz58/x+jRo5GYmNiiNd4AarwRQgghhBBCCACga9eu+Pe//81ZpvFKa+rq6jh27BjvcdXU1LB582Zs3rxZofio8UYIIYQQQghpMaUOXCrgTUXvvBFCCCGEEEJIJ0A9b4QQQgghhJAWE9R3dARvHup5e0X5+fnJXEDwxo0b8PPzw/jx43mPcffuXaiqqsLGxkZmvkQiwfbt2+Hk5AQdHR1oaWnB3t4eCxYswI0bN+SKs/Gih8rKytDX18eIESOwceNGVFdXS5XPycnB5MmTYWBgAJFIBEtLSyxfvhyVlZVSZS9fvgxvb28YGhpCTU0NVlZWmDNnDgoKCgAAmZmZEAgEKC0tldrXwcEBERERzP9NTU0hEAiQkpIiVdbe3h4CgQCJiYlS5ZummJgYAEBRUREEAgG6d++OiooKmXU3lOFKjWNszoIFCzB48GCIRCI4ODhwlr1x4wa0tbWhp6fHe9ymxBAonBStoy0oQcKZFN1fnmO0hfa+VnLdUwl3kudacaU6KPEmxc9TiTO1BQkEnKktfnZeBXz3k+86yEOEes6kKCEkvIlPhZKIM70KIiSH+ZNgLGfqDGoFSpxJHop+jsnjdfj5J68Oary9wsaMGYPi4mJWMjMzk3v/xMRETJ48GZWVlfjtt99YeRKJBFOnTkVgYCA8PT1x/PhxXL16FZs2bYK6ujpWrVoldz329vYoLi7G7du3kZGRAW9vb0RHR2PYsGGshk1WVhYcHR1RU1ODw4cPo6CgAFFRUdi5cyfc3NxQU1PDlD106BCGDh2K6upqJCUlIS8vDz/88P/s3XdYFMf/B/D33h2cdAsWrKBUMZZvosRoIghiDRIVFYFoUGNvgAWNiMQeC5rEJEo1sYARe4sFDEaxREEjKtbYwKgIggiCzO8PHu7HcXe7B3cU9fN6nnkSdmdmP7u3h8zO7MyvMDExwfz589WOrawWLVogMjJSbltSUhIyMjJgYGCgkD8kJETh+k+ZMkUuT05ODlauXKnyeGXL+vv7y65VaVK1QHdZjDH4+vpi2LBhvPkKCwvh6emJTz/9VLBOQgghhBDy9qFhk7WYVCpFkyZNKlWWMYbIyEisX78ezZs3R3h4OLp16ybbHxMTg23btmH37t1wc3OTbW/dujWcnZ3lZtERIpFIZHE2bdoUH3zwAXr16oUOHTpg+fLlWLRoERhjGD16NOzs7BAXFweRqOS5QatWrWBtbY1OnTphzZo1mD17NvLy8vDVV1+hX79+sjU0AMDCwgIODg5Ke9rU4eXlhTVr1uD+/fto0aIFACAiIgJeXl7YtGmTQn4jIyPB6z9lyhSsXr0akyZNUlhsWywWy5U3NDSUu1bqWrduHQDgyZMnuHTpksp833zzDWxtbeHs7IxTp05V6BiEEEIIIRUlpglLqh31vL2j4uPjkZeXBxcXF/j4+CA2NlauF2zr1q2wsbGRa7iVxXGafRltbW3Rt29fxMXFAQCSk5ORmpoKPz8/WcOtVIcOHeDi4oKtW7cCAA4fPoynT59i1qxZSuuuzJBAAGjcuDF69+6N6OhoAEBeXh5iYmLg6+tbqfoAwNPTE5aWlggJCal0Hdpw/PhxbN++HT/++GONxkEIIYQQQqoONd5qsX379sHQ0FCWPDw81C4bHh6O4cOHQywWw97eHpaWloiJiZHtT0tLk1spHgCmT58uO1bz5s01jt/W1hZ3796VHQ8oWbleGTs7O1meGzduyMprm6+vL6KiosAYw++//442bdqofI9s9uzZctff0NAQCQkJcnlK34PbsGEDbt26pfV41fHs2TOMGjUKUVFRMDY2VqtMQUEBXrx4IZeKCgqrOFJCCCGEvEtExTWX3lfUeKvFnJyckJycLEulw+eEZGVlIS4uDt7e3rJt3t7eiIiIkMtXvndt3rx5SE5ORlBQEHJzczWOnzGmdg9e2bwVGbJZUf3790dubi7+/PNPRERE8Pa6zZw5U+76Jycnw8HBQSFf79690b1790q/i6epsWPHYsSIEfjss8/ULrN06VKYmJjIpZNLY6swSkIIIYQQoil6560WMzAwgKWlZYXLbdmyBfn5+XINDcYYiouLkZqairZt28LKygrXrl2TK9ewYUM0bNhQ4d2tyrp69apsghVra2sAQGpqqtKermvXrsHKykou77Vr19C1a1eV9Zf2MmVnZysMpczKyoKJiYlCGYlEAh8fHyxYsABnzpyRe6euPFNTU7Wv/7Jly9C1a1fMnDlTrfzadPz4cezZs0c2cUrpZy2RSLBhwwalDdTAwED4+fnJbVshja+WeAkhhBDybhC9oXfeqhv1vL2DwsPD4e/vL9djlJKSAicnJ1nvm6enJ65fv47du3dXSQzXrl3DoUOHMHjwYAAl0+fb2tpizZo1KC6W7+tOSUnB0aNH4enpCQBwdXWFqakpVqxYobTu0glLrKysIBKJcO7cObn96enpePjwocKw0FK+vr44ceIEBg4ciHr16mlymjJdunTBoEGDMGfOHK3UVxGnT5+W+6xDQkJgZGSE5ORkfPHFF0rLSKVSGBsbyyWJVKeaIyeEEEIIIRVBPW9vqezsbCQnJ8ttq1+/PjIzM3HhwgVs3rxZ4Z0xT09PzJs3D0uXLsXw4cMRFxeH4cOHIzAwEL1790bjxo3x77//IiYmBmKxWO1YioqKkJGRgeLiYjx79gwJCQlYtGgROnbsKOuJ4jgOYWFhcHV1xeDBgxEYGIgmTZrgzJkz8Pf3R9euXTF9+nQAJT2OYWFh8PDwgJubG6ZOnQpLS0s8ffoUsbGxuHfvHrZt2wYjIyOMGzcO/v7+kEgk6NChAx49eoR58+bBzs4Orq6uSuO1s7PD06dPoa+vz3teOTk5yMjIkNumr6+v8r2yxYsXw97eHhKJdr9WN2/eRG5uLjIyMvDq1SvZ5962bVvo6uoqvEd4/vx5iEQitGvXTqtxEEIIIYSQmkWNt7dUQkICOnXqJLdt5MiRMDIyQtu2bZVO9uHu7o4JEyZg7969GDRoEGJiYrBx40ZERkZixYoVKCwsRPPmzeHs7IzVq1erHcuVK1dgZmYGsVgMExMTtG3bFoGBgZgwYQKk0v9fsLRbt25ISkrCwoUL0a9fP7x48QItW7bEyJEjERgYKJd34MCBOHXqFJYuXYoRI0bgxYsXaNGiBXr27Cm3Bt2aNWtgZmaGuXPn4u7du2jUqBGcnJywbds23kZUgwYNBM8rKCgIQUFBctvGjRuHn3/+WWl+a2tr+Pr6YsOGDYJ1V8SYMWNw4sQJ2c+ln/udO3dgbm6u1WMRQgghhKiLo6UCqh3HqnJ2CELIWyME+zWuoxj8v8RF4P91I7QfAHRQxLu/CPy9xhK84d1fqMYzrdcCxxCiKxADABRpOKpdAv6puIQ+K3ViEDoPofLqfN6aXgdNYwTUi5OPOtda0xi0cQxNafr9VyePpuepTnmhGHQE7qk3atxTteHzEhLM9effzzT/N0NTUvDPklwAzV8H0PT7rw6h+6FQ4J5ajD7aDKdC6ke/qLFjZ45Ub4btdw31vBFCCCGEEEIqTCz8LJJoGU1YQniVX+esbEpMTKzp8N5648ePV3l9x48fX9PhEUIIIYSQWoR63giv8pOilNWsWbPqC+QdFRISgoCAAKX71F1wmxBCCCGEvB+o8UZ4VWadOaK+Ro0aaW1dPUIIIYSQ6iSiCUuqHQ2bJIQQQgghhJC3APW8EUIIIYQQQipMRBOWVDvqeSOEEEIIIYSQtwA13gghhBBCCCHkLUDDJgkhhBBCCCEVxtGEJdWOet5qqVGjRoHjOIV08+ZNjBo1Cu7u7oJ1PHjwALq6urC1tVW6nzGGjRs3omvXrjA2NoahoSHs7e0xbdo03Lx5U604g4ODZbFJJBKYmpris88+Q2hoKAoKChTyX7lyBUOHDkXDhg0hlUphZWWF+fPnIy8vTyHvxYsX4eHhgcaNG6NOnTqwtrbG2LFjkZaWBgBISEgAx3HIyspSKNuxY0cEBwfLfjY3NwfHcdi2bZtCXnt7e3Ach6ioKIX85dOyZcsAAHfv3gXHcWjUqBFycnKUHrs0D18qG6Mq06ZNw4cffgipVIqOHTsqzcMYw8qVK2FtbQ2pVIoWLVpgyZIlgnWXVQyuypMIjDepU4eUveFNbyDiTULl1YmhCCLe9IpJeJMYbwSTEKFrWYcV8iZ1CJ2npveU0DloI3ECqTqoc09pSug6VEcdQve9OqQo5E1CNP3uqnNfC91V6tyXb4Ngtp8/cf15kzo0/V4YF+fzpur4LLRxTwnFmM8kvIm8X6jxVov16dMH6enpcsnCwkLt8lFRURg6dCjy8vLw119/ye1jjGHEiBGYOnUq+vXrhz/++AOXLl3CunXroKenh0WLFql9HHt7e6Snp+PevXuIj4+Hh4cHli5dik8++USuYZOUlAQHBwe8fv0a+/fvR1paGpYsWYLo6Gj06tULr1+/luXdt28fPv74YxQUFGDz5s24evUqfv31V5iYmGD+/Plqx1ZWixYtEBkZKbctKSkJGRkZMDAwUMgfEhKicP2nTJkilycnJwcrV65UebyyZf39/WXXqjSpWuOtLMYYfH19MWzYMJV5pk2bhrCwMKxcuRLXrl3D3r170aVLF8G6CSGEEEIqS/ym5tL7iprrtZhUKkWTJk0qVZYxhsjISKxfvx7NmzdHeHg4unXrJtsfExODbdu2Yffu3XBzc5Ntb926NZydncGY+k+jJBKJLM6mTZvigw8+QK9evdChQwcsX74cixYtAmMMo0ePhp2dHeLi4iASlTw3aNWqFaytrdGpUyesWbMGs2fPRl5eHr766iv069cPO3fulB3HwsICDg4OSnva1OHl5YU1a9bg/v37aNGiBQAgIiICXl5e2LRpk0J+IyMjwes/ZcoUrF69GpMmTVJYr00sFsuVNzQ0lLtW6lq3bh0A4MmTJ7h06ZLC/qtXr+Knn37CP//8AxsbmwrVTQghhBBC3h7U8/aOio+PR15eHlxcXODj44PY2Fi5XrCtW7fCxsZGruFWFsdpNozH1tYWffv2RVxcHAAgOTkZqamp8PPzkzXcSnXo0AEuLi7YunUrAODw4cN4+vQpZs2apbTuunXrViqmxo0bo3fv3oiOjgYA5OXlISYmBr6+vpWqDwA8PT1haWmJkJCQStehqb1796J169bYt28fLCwsYG5ujjFjxiAzM7PGYiKEEELIu09UXHPpfUWNt1ps3759MDQ0lCUPDw+1y4aHh2P48OEQi8Wwt7eHpaUlYmJiZPvT0tIUemmmT58uO1bz5s01jt/W1hZ3796VHQ8A7OzslOa1s7OT5blx44asvLb5+voiKioKjDH8/vvvaNOmjcr3yGbPni13/Q0NDZGQkCCXp/Q9uA0bNuDWrVtaj1cdt2/fxr///ovt27dj06ZNiIqKwt9//40hQ4bUSDyEEEIIIaRqUOOtFnNyckJycrIslQ6fE5KVlYW4uDh4e3vLtnl7eyMiIkIuX/netXnz5iE5ORlBQUHIzc3VOH7GmNo9eGXzVmTIZkX1798fubm5+PPPPxEREcHb6zZz5ky565+cnAwHBweFfL1790b37t0r/S6epoqLi1FQUIBNmzbh008/haOjI8LDwxEfH4/r168rLVNQUIAXL17IpaIC9SaxIIQQQgghNYPeeavFDAwMYGlpWeFyW7ZsQX5+vlxDgzGG4uJipKamom3btrCyssK1a9fkyjVs2BANGzZUeHersq5evSqbYMXa2hoAkJqaqrSn69q1a7CyspLLe+3aNXTt2lVl/cbGxgCA7OxshaGUWVlZMDExUSgjkUjg4+ODBQsW4MyZM3Lv1JVnamqq9vVftmwZunbtipkzZ6qVX5vMzMwgkUhk1w34/x7Oe/fuKX0PbunSpVi4cKHcth4LRsAx2KtqgyWEEELIO0P0hpYKqG7U8/YOCg8Ph7+/v1yPUUpKCpycnGS9b56enrh+/Tp2795dJTFcu3YNhw4dwuDBgwGUTJ9va2uLNWvWoLhYfqBySkoKjh49Ck9PTwCAq6srTE1NsWLFCqV1l05YYmVlBZFIhHPnzsntT09Px8OHD1VO3uHr64sTJ05g4MCBqFevnianKdOlSxcMGjQIc+bM0Up9FdGtWzcUFRXJDdssHYLaqlUrpWUCAwORnZ0tl7oHDq2WeAkhhBBCSOVQz9tbKjs7G8nJyXLb6tevj8zMTFy4cAGbN29WeGfM09MT8+bNw9KlSzF8+HDExcVh+PDhCAwMRO/evdG4cWP8+++/iImJgVgsVjuWoqIiZGRkoLi4GM+ePUNCQgIWLVqEjh07ynqiOI5DWFgYXF1dMXjwYAQGBqJJkyY4c+YM/P390bVrV0yfPh1ASY9jWFgYPDw84ObmhqlTp8LS0hJPnz5FbGws7t27h23btsHIyAjjxo2Dv78/JBIJOnTogEePHmHevHmws7ODq6ur0njt7Ozw9OlT6Ovr855XTk4OMjIy5Lbp6+vLevzKW7x4Mezt7SGRaPdrdfPmTeTm5iIjIwOvXr2Sfe5t27aFrq4uXFxc8L///Q++vr4IDQ1FcXExJk2ahF69esn1xpUllUohlUrltkmgo9W4CSGEEPJu497jiUNqCvW8vaUSEhLQqVMnuRQUFITw8HC0bdtW6WQf7u7uyMzMxN69e8FxHGJiYhAaGooDBw7A2dkZNjY28PX1RYsWLXDy5Em1Y7ly5QrMzMzQsmVLODo6IjY2FoGBgUhMTIShoaEsX7du3ZCUlASxWIx+/frB0tISgYGBGDlyJI4cOSLXmBg4cCBOnToFHR0djBgxAra2tvD09ER2drbcGnRr1qzBmDFjMHfuXNjb28PLywsWFhb4448/eBtRDRo0gJ6eHu95BQUFwczMTC6pmgETKBnu6evri/z8fHUum9rGjBmDTp064ZdffkFaWprs83706BEAQCQSYe/evbIF0vv37w87OzulC5ITQgghhJC3F8eqcnYIQshbIxgHNK6jGPxj33XBv6qmUHkAMGb8jeMXXJ0qLQ8A+QKDFgoZ/3Ox+lye4DEKBHpCReD/1a3PXvPuz+N0BWMQOk998E9y8xr8PfhC9wMAFGn4jFFH4BiFAjECwtdaiDrnIHQMTWNQ57sldAyhOl4y/nvWgBOeFEkP/PftK/Dft0IxqvNZCN2XEmje1aDpfV0bBHP9+fez/YJ1CH1eQvdkw+Ic3v3PRIa8+7URgzqfpab3TDaT8u5fxbloVL8mWq96WWPHvu1vUGPHrkk0bJIQAkDzPw7Voc4fkEJyOf5/xKq6PCD8D7EuJ9Rg0PxXr9C1VKdxJkToPDX9o0cb94OQNwJ/WGnjvtf0OmgjDm1cS03rUKdxJkTooYUQoeuozgMDIdr4vN8FQo0zocadOnUIeSHif9hWHd+L6vgdoo3vVlUR04Ql1e7tf/RDqlT5dc7KpsTExJoO7603fvx4ldd3/PjxNR0eIYQQQgipRajnjfAqPylKWc2aNau+QN5RISEhCAgIULpP1cQohBBCCCG1gUjzzmxSQdR4I7wqs84cUV+jRo20tq4eIYQQQgh5t1HjjRBCCCGEEFJhomJ656260TtvhBBCCCGEEPIWoMYbIYQQQgghhLwFaNgkIYQQQgghpMIEVsYhVYB63gghhBBCCCHkLUA9b4QQQgghhJAKo0W6qx/1vNVSo0aNAsdxCunmzZsYNWoU3N3dBet48OABdHV1YWtrq3Q/YwwbN25E165dYWxsDENDQ9jb22PatGm4efOmWnEGBwfLYpNIJDA1NcVnn32G0NBQFBQUKOS/cuUKhg4dioYNG0IqlcLKygrz589HXl6eQt6LFy/Cw8MDjRs3Rp06dWBtbY2xY8ciLS0NAJCQkACO45CVlaVQtmPHjggODpb9bG5uDo7jsG3bNoW89vb24DgOUVFRCvnLp2XLlgEA7t69C47j0KhRI+Tk5Cg9dmkevlQ2RlWmTZuGDz/8EFKpFB07dlSa5/Dhw/j4449hZGSEhg0bYvDgwbhz545g3dpWDI43aYMOinhTEUS8Sai8CEwwvWIS3vSS6fAmMYoFk9C1LISIN+mz17xJikLBJHSe1XE/CNUhlISuszqftxCh8hIUC6aqjkEdmtaRw3R5U3XEIHQ/vIZYMGlKnfvyXSB0jsFsv3Di+vMmIcbF+bxJG99voe+uNq6VEKF/U8j7hRpvtVifPn2Qnp4ulywsLNQuHxUVhaFDhyIvLw9//fWX3D7GGEaMGIGpU6eiX79++OOPP3Dp0iWsW7cOenp6WLRokdrHsbe3R3p6Ou7du4f4+Hh4eHhg6dKl+OSTT+QaNklJSXBwcMDr16+xf/9+pKWlYcmSJYiOjkavXr3w+vVrWd59+/bh448/RkFBATZv3oyrV6/i119/hYmJCebPn692bGW1aNECkZGRctuSkpKQkZEBAwMDhfwhISEK13/KlClyeXJycrBy5UqVxytb1t/fX3atSpOqBbrLYozB19cXw4YNU7r/9u3bGDhwIHr27Ink5GQcPnwYT58+xaBBgwTrJoQQQgghbw8aNlmLSaVSNGnSpFJlGWOIjIzE+vXr0bx5c4SHh6Nbt26y/TExMdi2bRt2794NNzc32fbWrVvD2dkZjKn3pBYAJBKJLM6mTZvigw8+QK9evdChQwcsX74cixYtAmMMo0ePhp2dHeLi4iASlTw3aNWqFaytrdGpUyesWbMGs2fPRl5eHr766iv069cPO3fulB3HwsICDg4OSnva1OHl5YU1a9bg/v37aNGiBQAgIiICXl5e2LRpk0J+IyMjwes/ZcoUrF69GpMmTVJYbFssFsuVNzQ0lLtW6lq3bh0A4MmTJ7h06ZLC/gsXLuDNmzdYtGiR7LoGBARg4MCBKCwshI4OPZUjhBBCiPaJaMKSakc9b++o+Ph45OXlwcXFBT4+PoiNjZXrBdu6dStsbGzkGm5lcZxmwzpsbW3Rt29fxMXFAQCSk5ORmpoKPz8/WQOjVIcOHeDi4oKtW7cCgKznaNasWUrrrlu3bqViaty4MXr37o3o6GgAQF5eHmJiYuDr61up+gDA09MTlpaWCAkJqXQdmvroo48gFosRGRmJN2/eIDs7G7/++itcXV2p4UYIIYQQ8g6hxlsttm/fPhgaGsqSh4eH2mXDw8MxfPhwiMVi2Nvbw9LSEjExMbL9aWlpsLGxkSszffp02bGaN2+ucfy2tra4e/eu7HgAYGdnpzSvnZ2dLM+NGzdk5bXN19cXUVFRYIzh999/R5s2bVS+RzZ79my5629oaIiEhAS5PKXvwW3YsAG3bt3SerzqMDc3xx9//IG5c+dCKpWibt26ePDggdL3+0oVFBTgxYsXcqmooLAaoyaEEELI205UXHPpfUWNt1rMyckJycnJslQ6fE5IVlYW4uLi4O3tLdvm7e2NiIgIuXzle9fmzZuH5ORkBAUFITc3V+P4GWNq9+CVzVuRIZsV1b9/f+Tm5uLPP/9EREQEb6/bzJkz5a5/cnIyHBwcFPL17t0b3bt3r/S7eJrKyMjAmDFjMHLkSJw7dw4nTpyArq4uhgwZovJaLl26FCYmJnIpcWlsNUdOCCGEEEIqgt55q8UMDAxgaWlZ4XJbtmxBfn6+XEODMYbi4mKkpqaibdu2sLKywrVr1+TKNWzYEA0bNlR4d6uyrl69KptgxdraGgCQmpqqtKfr2rVrsLKykst77do1dO3aVWX9xsbGAIDs7GyFoZRZWVkwMTFRKCORSODj44MFCxbgzJkzcu/UlWdqaqr29V+2bBm6du2KmTNnqpVfm3788UcYGxtjxYoVsm2//fYbWrRogTNnzuDjjz9WKBMYGAg/Pz+5bSulx6s8VkIIIYS8OzhaKqDaUc/bOyg8PBz+/v5yPUYpKSlwcnKS9b55enri+vXr2L17d5XEcO3aNRw6dAiDBw8GUDJ9vq2tLdasWYPiYvm+7pSUFBw9ehSenp4AAFdXV5iamso1RsoqnbDEysoKIpEI586dk9ufnp6Ohw8fKgwLLeXr64sTJ05g4MCBqFevnianKdOlSxcMGjQIc+bM0Up9FZGXlwexWH5669Kfy1/rUlKpFMbGxnJJIqX34wghhBBCajPqeXtLZWdnIzk5WW5b/fr1kZmZiQsXLmDz5s0K74x5enpi3rx5WLp0KYYPH464uDgMHz4cgYGB6N27Nxo3box///0XMTExCo0BPkVFRcjIyEBxcTGePXuGhIQELFq0CB07dpT1RHEch7CwMLi6umLw4MEIDAxEkyZNcObMGfj7+6Nr166YPn06gJIex7CwMHh4eMDNzQ1Tp06FpaUlnj59itjYWNy7dw/btm2DkZERxo0bB39/f0gkEnTo0AGPHj3CvHnzYGdnB1dXV6Xx2tnZ4enTp9DX1+c9r5ycHGRkZMht09fXl/X4lbd48WLY29tDItHu1+rmzZvIzc1FRkYGXr16Jfvc27ZtC11dXfTv3x9r1qxBSEgIPD09kZOTg7lz56JVq1bo1KmTVmMhhBBCCCE1h3re3lIJCQno1KmTXAoKCkJ4eDjatm2rdLIPd3d3ZGZmYu/eveA4DjExMQgNDcWBAwfg7OwMGxsb+Pr6okWLFjh58qTasVy5cgVmZmZo2bIlHB0dERsbi8DAQCQmJsLQ0FCWr1u3bkhKSoJYLEa/fv1gaWmJwMBAjBw5EkeOHIFUKpXlHThwIE6dOgUdHR2MGDECtra28PT0RHZ2ttwadGvWrMGYMWMwd+5c2Nvbw8vLCxYWFvjjjz94G1ENGjSAnp4e73kFBQXBzMxMLqmaARMoGe7p6+uL/Px8dS6b2saMGYNOnTrhl19+QVpamuzzfvToEQCgZ8+e2LJlC3bt2oVOnTqhT58+kEqlOHTokOA5EkIIIYRUlvhNzaX3FceqcnYIQshbIwT7Na6jGPxj30XQ/NeNGPxTTL0ReCalaXlA+DyF9ksEYlCnDiHqHENIkcC1EDqGUHl17gdNr4PQMdSpX9P7VtNzUEd1nGd1nIem9xR5twRz/Xn3L2eq31sHgFfQFTzG2/D9FhKMfjV27M4BBTV27HMrpcKZ3kE0bJIQQgghhBBSYbRId/WjR1iEV/l1zsqmxMTEmg7vrTd+/HiV13f8+PE1HR4hhBBCCKlFqOeN8Co/KUpZzZo1q75A3lEhISEICAhQuk/VxCiEEEIIIeT9RI03wqsy68wR9TVq1Ehr6+oRQgghhFQnEa3zVu1o2CQhhBBCCCGEvAWo540QQgghhBBSYZzmExuTCqKeN0IIIYQQQgh5C1DPGyGEEEIIIaTC3ufFsmsK9bwRQgghhBBCyFuAGm+EEEIIIYQQ8hagxlstNWrUKHAcp5Bu3ryJUaNGwd3dXbCOBw8eQFdXF7a2tkr3M8awceNGdO3aFcbGxjA0NIS9vT2mTZuGmzdvqhVncHCwLDaJRAJTU1N89tlnCA0NRUFBgUL+K1euYOjQoWjYsCGkUimsrKwwf/585OXlKeS9ePEiPDw80LhxY9SpUwfW1tYYO3Ys0tLSAAAJCQngOA5ZWVkKZTt27Ijg4GDZz+bm5uA4Dtu2bVPIa29vD47jEBUVpZC/fFq2bBkA4O7du+A4Do0aNUJOTo7SY5fm4UtlY1QmJSUFnp6eaNGiBfT09GBnZ4e1a9cq5Lt8+TJ69OgBPT09NGvWDCEhIWCM8dZdFURgvEk7xygWSPwxSPCGNxWD0zi9DdQ5D6FrWR3XQSiG6rjnquN+qOrzrI46tHEd3obvVnXcc5oyZAWCSYpCjVLD4hzepI06lrOdvGk29wVvUue+rw3fbyG1+XshesPVWHpfUeOtFuvTpw/S09PlkoWFhdrlo6KiMHToUOTl5eGvv/6S28cYw4gRIzB16lT069cPf/zxBy5duoR169ZBT08PixYtUvs49vb2SE9Px7179xAfHw8PDw8sXboUn3zyiVzDJikpCQ4ODnj9+jX279+PtLQ0LFmyBNHR0ejVqxdev34ty7tv3z58/PHHKCgowObNm3H16lX8+uuvMDExwfz589WOrawWLVogMjJSbltSUhIyMjJgYGCgkD8kJETh+k+ZMkUuT05ODlauXKnyeGXL+vv7y65VaVK1QHepv//+Gw0bNsRvv/2GK1euYN68eQgMDMQPP/wgy/PixQv06tULTZs2xblz5/D9999j5cqVWL16tbqXhhBCCCGEAHj+/Dl8fHxgYmICExMT+Pj4KO0oKEvVQ/rvvvtOlsfR0VFh//DhwyscH01YUotJpVI0adKkUmUZY4iMjMT69evRvHlzhIeHo1u3brL9MTEx2LZtG3bv3g03NzfZ9tatW8PZ2blCvTYSiUQWZ9OmTfHBBx+gV69e6NChA5YvX45FixaBMYbRo0fDzs4OcXFxEIlKnhu0atUK1tbW6NSpE9asWYPZs2cjLy8PX331Ffr164edO3fKjmNhYQEHBwfBL5AqXl5eWLNmDe7fv48WLVoAACIiIuDl5YVNmzYp5DcyMhK8/lOmTMHq1asxadIkhcW2xWKxXHlDQ0O5a6UOX19fuZ9bt26N06dPIy4uDpMnTwYAbN68Gfn5+YiKioJUKkW7du2QlpaG1atXw8/PDxz3/j6dIoQQQkjVEb2DE5aMGDECDx48wKFDhwAAX3/9NXx8fLB3716VZdLT0+V+PnjwIEaPHo3BgwfLbR87dixCQkJkP+vp6VU4Pup5e0fFx8cjLy8PLi4u8PHxQWxsrFwv2NatW2FjYyPXcCtL0z/4bW1t0bdvX8TFxQEAkpOTkZqaCj8/P1nDrVSHDh3g4uKCrVu3AgAOHz6Mp0+fYtasWUrrrlu3bqViaty4MXr37o3o6GgAQF5eHmJiYhQaSBXh6ekJS0tLuS9iVcvOzkb9+vVlP58+fRo9evSAVCqVbevduzcePXqEu3fvVltchBBCCCFvs6tXr+LQoUMICwtD165d0bVrV2zcuBH79u3D9evXVZZr0qSJXNq9ezecnJzQunVruXz6+vpy+UxMTCocIzXearF9+/bB0NBQljw8PNQuGx4ejuHDh0MsFsPe3h6WlpaIiYmR7U9LS4ONjY1cmenTp8uO1bx5c43jt7W1lTUeSt9Ts7OzU5rXzs5OlufGjRuy8trm6+uLqKgoMMbw+++/o02bNujYsaPSvLNnz5a7/oaGhkhISJDLU/oe3IYNG3Dr1i2tx1ve6dOnERsbi3Hjxsm2ZWRkoHHjxnL5Sn/OyMhQWk9BQQFevHghl4oKCqsucEIIIYQQLVL2t4yy+RYq4vTp0zAxMYGDg4Ns28cffwwTExOcOnVKrToeP36M/fv3Y/To0Qr7Nm/eDFNTU9jb2yMgIEBh3gR1UOOtFnNyckJycrIsrVu3Tq1yWVlZiIuLg7e3t2ybt7c3IiIi5PKV712bN28ekpOTERQUhNzcXI3jZ4yp3YNXNm9VTrTRv39/5Obm4s8//0RERARvr9vMmTPlrn9ycrLcl7lU79690b1790q/i6euK1euYODAgQgKCkKvXr3k9pW/zqXXUNX1X7p0qWwsd2lKXBpbNYETQggh5J0kelNzSdnfMkuXLtXofDIyMhRegwGARo0aqXwgXl50dDSMjIwwaNAgue1eXl7YunUrEhISMH/+fOzYsUMhjzronbdazMDAAJaWlhUut2XLFuTn58s1NBhjKC4uRmpqKtq2bQsrKytcu3ZNrlzDhg3RsGFDpTdtZVy9elU2wYq1tTUAIDU1VWlP17Vr12BlZSWX99q1a+jatavK+o2NjQGUDCMsP5QyKytLaVe0RCKBj48PFixYgDNnzsi9U1eeqamp2td/2bJl6Nq1K2bOnKlW/opKTU1Fz549MXbsWHzzzTdy+5o0aaLwC+W///4DAIUeuVKBgYHw8/OT27ZSelyLERNCCCGEVB1lf8uUfYWkrODgYCxcuJC3vnPnzgFQ/uC7Ih0SpfMp1KlTR2772LFjZf/frl07WFlZ4aOPPsKFCxfwv//9T626Aep5eyeFh4fD399frscoJSUFTk5Ost43T09PXL9+Hbt3766SGK5du4ZDhw7JXtTs2LEjbG1tsWbNGhQXF8vlTUlJwdGjR+Hp6QkAcHV1hampKVasWKG07tIJS6ysrCASiWRftlLp6el4+PChwrDQUr6+vjhx4gQGDhyIevXqaXKaMl26dMGgQYMwZ84crdRX1pUrV+Dk5ISRI0di8eLFCvu7du2KP//8U262zj/++ANNmzaFubm50jqlUimMjY3lkkSqo/XYCSGEEPLuqsmlApT9LaOq8TZ58mRcvXqVN7Vr1w5NmjTB48ePFco/efJE5QPxshITE3H9+nWMGTNGMO///vc/6OjoyF4XUhf1vL2lsrOzkZycLLetfv36yMzMxIULF7B582aFd8Y8PT0xb948LF26FMOHD0dcXByGDx+OwMBA9O7dG40bN8a///6LmJgYiMVitWMpKipCRkYGiouL8ezZMyQkJGDRokXo2LGjrCeK4ziEhYXB1dUVgwcPRmBgIJo0aYIzZ87A398fXbt2xfTp0wGU9DiGhYXBw8MDbm5umDp1KiwtLfH06VPExsbi3r172LZtG4yMjDBu3Dj4+/tDIpGgQ4cOePToEebNmwc7Ozu4uroqjdfOzg5Pnz6Fvr4+73nl5OQo9Gjp6+vLevzKW7x4Mezt7SGRaO9rVdpwc3V1hZ+fnywesViMhg0bAiiZFWnhwoUYNWoU5s6dixs3bmDJkiUICgqimSYJIYQQ8t4zNTWFqampYL6uXbsiOzsbZ8+eRZcuXQAAZ86cQXZ2Nj755BPB8uHh4fjwww/RoUMHwbxXrlxBYWEhzMzMhE+gDOp5e0slJCSgU6dOcikoKAjh4eFo27at0sk+3N3dkZmZib1794LjOMTExCA0NBQHDhyAs7MzbGxs4OvrixYtWuDkyZNqx3LlyhWYmZmhZcuWcHR0RGxsLAIDA5GYmAhDQ0NZvm7duiEpKQlisRj9+vWDpaUlAgMDMXLkSBw5ckTuacnAgQNx6tQp6OjoYMSIEbC1tYWnpyeys7Pl1qBbs2YNxowZg7lz58Le3h5eXl6wsLDAH3/8wduIatCggeD0rEFBQTAzM5NLqmbABEqGe/r6+iI/P1+dy6aW7du348mTJ9i8ebNcHJ07d5blMTExwZEjR/DgwQN89NFHmDhxIvz8/BSGEhBCCCGEaFNNvvNWFezs7NCnTx+MHTsWSUlJSEpKwtixYzFgwAC5EV22trYKr968ePEC27dvV9rrduvWLYSEhOD8+fO4e/cuDhw4AA8PD3Tq1EluKS91cKwqZ4cghLw1QrC/yo9RDM17Ags1fOYkBv+vPAmKefcDQL7AoAWhOtQ5RgH4e791NDyGOp+FpjHUBiKBz1sdmt632ohBiDa+W0KEzqNI4LupznV4LXDP6YL/LzahY1THdaoNquO+18a11rQOofJB3ADBGIJZ1f/bV9WC0a/Gjt17RFGNHfvwlqoZQJiZmYmpU6diz549AAA3Nzf88MMPcvMrcByHyMhIjBo1SrZtw4YNmD59OtLT0xXmXbh//z68vb3xzz//IDc3Fy1atED//v2xYMECueWf1EHDJgkhhBBCCCEEJa8h/fbbb7x5lPV9ff311/j666+V5m/RogVOnDihlfho2CThVX6ds7IpMTGxpsN7640fP17l9R0/fnxNh0cIIYQQotK7NmzybUA9b4RX+UlRymrWrFn1BfKOCgkJQUBAgNJ9qiZGIYQQQggh7ydqvBFelVlnjqivUaNGWltXjxBCCCGkOr3PPWA1hYZNEkIIIYQQQshbgBpvhBBCCCGEEPIWoGGThBBCCCGEkAoTvXk/lt+oTajnjRBCCCGEEELeAtTzRgghhBBCCKkwmrCk+lW65+3UqVMQi8Xo06eP3Pa7d++C4zhIJBI8fPhQbl96ejokEgk4jsPdu3cRHBwMjuN40927d3njKFuHSCRC06ZN4eXlhfv378vlc3R0VFp/+bW09u3bB0dHRxgZGUFfXx+dO3dGVFRUha/Pjh074OjoCBMTExgaGqJ9+/YICQlBZmYmACAqKkoujsaNG+Pzzz/HlStX5OoZNWqU0rjLXndzc3PZdj09PZibm2Po0KE4fvy4XF2ln01ycrLWrz3HcTAxMcGnn36qsAghx3HYtWuXQvnp06fD0dFR6blKJBK0bNkSEyZMwPPnz+XKlT3fsmnZsmUKx3B1dYVYLEZSUpLCPkdHR0yfPl1h+65du8Bx6g0DiIqKQt26dZXuU3be6txfCQkJ4DgOWVlZCnV27NgRwcHBsp/Lf/a2trb47rvvlC4eKaQYnMZJUyIwwaSDYt4kxRveJFS/Ouepize8SRvHEDrPYPTjTdr4PIVi0MbnWdWpAGLeVB33tTYIxSh0HdSh6X0rQTFvErpng9FP8Lul6XXSBm1ca03p4A1vqo77Whv1a3pfC5UPZvuFE9efN3V/fpM3qfN7iBBtqnTjLSIiAlOmTMHJkydx7949hf1NmzbFpk2b5LZFR0fLrQ0WEBCA9PR0WWrevDlCQkLktrVo0UIwFnt7e6Snp+PBgweIiYnB5cuXMXToUIV8Y8eOlas7PT0dK1askO3//vvvMXDgQHzyySc4c+YMLl26hOHDh2P8+PEq1+JSZt68eRg2bBg6d+6MgwcP4p9//sGqVauQkpKCX3/9VZbP2NgY6enpePToEfbv34+XL1+if//+eP36tVx9ffr0UYh769atcnlKr9v169exadMm1K1bFy4uLli8eLHSGLV97dPT03H69GlYWVlhwIAByM7OVvt6KTvXu3fvIiwsDHv37sXEiRMV8pWPNT09HVOmTJHLc+/ePZw+fRqTJ09GeHh4peLRJm3dX+WVXourV68iICAAc+fOxYYNG7QYOSGEEEKIIlqku/pVatjky5cvERsbi3PnziEjIwNRUVEICgqSyzNy5EhERkYiMDBQti0qKgojR47Et99+CwAwNDSEoaGhbL9YLIaRkRGaNGlSsZOQSGRlmjZtirFjx2Lq1Kl48eKF3ELH+vr6Kuu+f/8+/P39MX36dCxZskS23d/fH7q6upg6dSo8PDzg4ODAG8vZs2exZMkShIaGYtq0abLt5ubm6NWrl1xvCsdxsnjMzMwwY8YMuLm54fr16/jggw9k+aRSqeA1KXvdWrZsic8++wxmZmYICgrCkCFDYGNjI5e/Kq59kyZNsHDhQkRGRiItLQ2dO3euUF2A/Lk2b94cw4YNU9rzqU6skZGRGDBgACZMmIAuXbogNDQUBgYGFY5JG7R1fylT9lqMGTMGP/30E/744w+MGzdOa/ETQgghhJCaV6met5iYGNjY2MDGxgbe3t6IjIxUGKbl5uaG58+f4+TJkwCAkydPIjMzE59//rnmUfPIyMhAXFwcxGIxxGKx2uV+//13FBYWKu0BGTduHAwNDRV6u5TZvHkzDA0NlfYWAVA5xC4rKwtbtmwBAOjo6KgdN59p06aBMYbdu3drpT4hBQUFsmGE5RuLlXH79m0cOnSoUteDMYbIyEh4e3vD1tYW1tbWiI2N1TimytLW/cWHMYaEhARcvXpVa/cQIYQQQgipPSrVeAsPD4e3tzeAkmFuubm5OHbsmFweHR0deHt7IyIiAkDJMEtvb+8q+aPy8uXLMDQ0hL6+PszMzJCQkIBJkyYp9LKsX79e1uNUmqKjowEAaWlpMDExgZmZmUL9urq6aN26NdLS0gRjuXHjBlq3bq3WeWZnZ8PQ0BAGBgaoV68etm3bBjc3N9ja2srl27dvn0Lcpb2XfOrXr49GjRoJvrumidJrb2hoCD09PaxcuRJbt26V6/GsiNJz1dPTQ5s2bZCamorZs2cr5Js9e7bCNUlISJDtP3r0KPLy8tC7d28AgLe3d5UNnSz9HMunsrR1fylTei2kUimcnJzAGMPUqVN5yxQUFODFixdyqaigsFLHJ4QQQsj7iYZNVr8KD5u8fv06zp49i7i4uJIKJBIMGzYMERERcHFxkcs7evRodO3aFUuWLMH27dtx+vRpFBUVaSfyMmxsbLBnzx4UFBRg9+7d2L59u9J3vby8vDBv3jy5bY0aNVLrGIwx6OrqqpVP3ckujIyMcOHCBRQVFeHEiRP47rvv8PPPPyvkc3Jywk8//SS3rX79+mrHrW48lVF67QEgJycHMTEx8PDwQHx8PD766KMK11d6rnl5eQgLC0NaWprCu2wAMHPmTIwaNUpuW9n3KcPDwzFs2DBIJCW3uKenJ2bOnInr169rpVewrNLPsTwrKyu169Dkcyq9Fk+ePMG8efPQs2dPfPLJJ7xlli5dioULF8pt67FgBByDvSoVAyGEEEIIqXoVbryFh4ejqKhI7g9lxhh0dHQUZgVs164dbG1t4enpCTs7O7Rr1w7JyckaB12erq4uLC0tAZRMoHHjxg1MmDBBbnIQADAxMZHlK8/KygrZ2dl49OgRmjZtKrfv9evXuH37tsLMmspYW1vj5MmTKCwsFOx9E4lEsnhsbW2RkZGBYcOG4c8//5TLZ2BgoDJuPs+ePcOTJ09gYWFR4bLqKnvtAaBTp07YtWsXQkND8dtvvwEoadwom8AkKysLJiYmctvKnuu6devg5OSEhQsXKvQ0mpqaqrwmmZmZ2LVrFwoLC+UavW/evEFERASWL18OoGTCGFVxVaTnsOznqIq1tbXg/dWzZ09ZXEBJj175YbbKrlnptbC0tMSOHTtgaWmJjz/+WOFhSlmBgYHw8/OT27ZCGs97DoQQQgghZdEi3dWvQsMmi4qKsGnTJqxatQrJycmylJKSglatWmHz5s0KZXx9fZGQkABfX1+tBS1k/vz52Lp1q9LeEFWGDBkCiUSCVatWKez7+eefkZeXhy+//FKwnhEjRiA3Nxfr169Xul/Z9O+lZsyYgZSUFOzcuVPtuPmsXbsWIpEI7u7uWqlPXWKxGK9evZL9bGtri3PnzsnlYYzh77//FuwFW7BgAVauXIlHjx6pffzNmzejefPmSElJkbtPQ0NDER0dLev9tbW1xfnz5xXKnzt3Tuu9c4MHD+a9v16+fAlPT08AJQ8SRCKRwjVLT0/Hw4cPeWOrV68epkyZgoCAAN7lAqRSKYyNjeWSRErvyRFCCCGE1GYV6nnbt28fnj9/jtGjRys8/R8yZAjCw8MxYMAAue1jx46Fh4eHyok6qkLr1q0xcOBABAUFYd++fbLteXl5yMjIkMsrlUpRr149tGzZEitWrEBAQADq1KkDHx8f6OjoYPfu3Zg7dy4WLVqEdu3aCR7bwcEBs2bNgr+/Px4+fIgvvvgCTZs2xc2bN/Hzzz+je/fucrNQlmVsbIwxY8ZgwYIFcHd3lw2jKygoUIhbIpHA1NRU9nNOTg4yMjJQWFiIO3fu4LfffkNYWBiWLl1aqV47dRUVFcliKx02Wf49tYCAAIwcORK2trZwdXXFq1evsGHDBty6dQuTJk3ird/R0RH29vZYsmQJfvjhB9n20vMtS19fH8bGxggPD8eQIUMUPq9WrVph9uzZ2L9/PwYOHIiJEyfihx9+wKRJk/D1119DT08PR44cQXh4uEKvraaE7i9/f3/ZTJNGRkYYN24c/P39IZFI0KFDBzx69Ajz5s2DnZ0dXF1deY81adIkLF++HDt27MCQIUO0eh6EEEIIIaTmVKjnLTw8HC4uLgoNN6CkZyE5OVm2CHWp0kZG6btH1cXf3x/79+/HmTNnZNs2btwIMzMzuVTa2wGU9HzFxcUhMTERH330ESwtLeHv74+oqCjMnTtX7WMvX74cW7ZswZkzZ9C7d2/Y29vDz88P7du3x8iRI3nLTps2DVevXsX27dtl2w4dOqQQd/fu3eXKBQUFwczMDJaWlvDx8UF2djaOHTumdLIPbbpy5Yospo4dOyI2NhY//fSTXC/l0KFDERUVhejoaHTu3Bmurq64desWEhMT0apVK8Fj+Pn5YePGjXILr5eeb9k0a9Ys/P3330hJScHgwYMV6jEyMoKrq6ts4hJzc3MkJibi1q1bcHV1lS2YHRUVBQ8PDy1cHXkzZszAzp07ZfdXu3btsGXLFvz0009YuXKlXN41a9ZgzJgxmDt3Luzt7eHl5QULCwv88ccfgt+lhg0bwsfHB8HBwSguFl5ImRBCCCGkMmjCkurHMb6xVe+5zMxMODs7w9jYGAcPHoS+vn5Nh0RIlQnGAY3rEIH/10kx+MfGC5WvLTQ9D6Hy6tQRhP68+7XxeWpKG9fhXYiBlAhGP8E8IdjPu1/Tz0ud3zHV8f0WInSM6vgdo+l5qFNeAv4HjEJ1aONad39+k3e/S33lo6VKHcz+XvAYZ4xbVyimilLnu1VVhvWsuYfEMccrNWn+W+/9PGs11a9fH0ePHoWzszNOnz5d0+EQQgghhBBSa1DPW/Wr9Y03ZetnlabExMQqP36DBg0QFBQEZ2dnAMD48eNVxjN+/Pgqj6c61fS1rw3s7e1VXgNlE/QQQgghhBBSVar3RbRK4FtaoOxyBdUlJCQEAQEBSvdVdmHq2qq2XfuacODAARQWKl+8unHjxtUcDSGEEEIIeZ/V+sZbVc6UWBmNGjVSe2Hvt11tu/Y1QZ0JVQghhBBC3kfv8/DFmlLrh00SQgghhBBCCHkLet4IIYQQQgghtQ/1vFU/6nkjhBBCCCGEkLcA9bwRQgghhBBCKkz0htbKrG7U80YIIYQQQgghbwFqvBFCCCGEEELIW0CjxtupU6cgFovRp08fue13794Fx3GQSCR4+PCh3L709HRIJBJwHIe7d+8iODgYHMfxprt37/LGUbYOkUiEpk2bwsvLC/fv35fL5+joqLT+8otr79u3D46OjjAyMoK+vj46d+6MqKioCl+fHTt2wNHRESYmJjA0NET79u0REhKCzMxMAEBUVJRcHI0bN8bnn3+OK1euyNUzatQopXGXve7m5uay7Xp6ejA3N8fQoUNx/PhxubpKP5vk5GStX3uO42BiYoJPP/0UJ06ckMvHcRx27dqlUH769OlwdHRUeq4SiQQtW7bEhAkT8Pz5c7lyZc+3bFq2bJnCMVxdXSEWi5GUlKSwz9HREdOnT1fYvmvXLnCc8FCAa9eugeM4nDlzRm67g4MDpFIp8vLyZNtev34NfX19bNiwQeFc1flclZ1n2c+zVE5ODhwdHWFra6vwHeAjAtM4VYdicLxJKEah8uqk2nAdqoPQdRAiRjFvUoem96Smn+W79HkK0fQ6aOM61oYYNKWNe0rovi2CiDep83tMqA4hmpZXpw5Nfwep41S9NrzpYPb3vKmvyRTBpOm/OTp4w5tqkuhNzaX3lUaNt4iICEyZMgUnT57EvXv3FPY3bdoUmzZtktsWHR0tt8BzQEAA0tPTZal58+YICQmR29aiRQvBWOzt7ZGeno4HDx4gJiYGly9fxtChQxXyjR07Vq7u9PR0rFixQrb/+++/x8CBA/HJJ5/gzJkzuHTpEoYPH47x48erXJxbmXnz5mHYsGHo3LkzDh48iH/++QerVq1CSkoKfv31V1k+Y2NjpKen49GjR9i/fz9evnyJ/v374/Xr13L19enTRyHurVu3yuUpvW7Xr1/Hpk2bULduXbi4uGDx4sVKY9T2tU9PT8fp06dhZWWFAQMGIDs7W+3rpexc7969i7CwMOzduxcTJ05UyFc+1vT0dEyZMkUuz71793D69GlMnjwZ4eHhlYqHj62tLczMzBAfHy/blpubi4sXL6JRo0Y4deqUbPuZM2fw6tUrODk5KZyrOp8r33mWevLkCZycnJCbm4uTJ0+q9fkRQgghhJC3Q6UnLHn58iViY2Nx7tw5ZGRkICoqCkFBQXJ5Ro4cicjISAQGBsq2RUVFYeTIkfj2228BAIaGhjA0NJTtF4vFMDIyQpMmTSp2IhKJrEzTpk0xduxYTJ06FS9evICxsbEsn76+vsq679+/D39/f0yfPh1LliyRbff394euri6mTp0KDw8PODg48MZy9uxZLFmyBKGhoZg2bZpsu7m5OXr16oWsrCzZNo7jZPGYmZlhxowZcHNzw/Xr1/HBBx/I8kmlUsFrUva6tWzZEp999hnMzMwQFBSEIUOGwMbGRi5/VVz7Jk2aYOHChYiMjERaWho6d+5coboA+XNt3rw5hg0bprTnU51YIyMjMWDAAEyYMAFdunRBaGgoDAwMKhwTH0dHRyQkJGDOnDkAgMTERFhbW6NHjx5ISEiAi4sLACAhIQHNmjWDlZWVrGxFP1c+9+/fR69evWBmZoY9e/bAyMhIg7MihBBCCOH3PveA1ZRK97zFxMTAxsYGNjY28Pb2RmRkJBiTHwrg5uaG58+f4+TJkwCAkydPIjMzE59//rlmUQvIyMhAXFwcxGIxxGKx2uV+//13FBYWKu1hGzduHAwNDRV6RZTZvHkzDA0NlfYWAUDdunWVbs/KysKWLVsAADo6OmrHzWfatGlgjGH37t1aqU9IQUEBoqKiULduXYXGYmXcvn0bhw4dqtT1YIwhMjIS3t7esLW1hbW1NWJjYzWOqTwnJyecPHkSRUVFAID4+Hg4OjqiR48ecj1y8fHxcr1u2nT9+nV069YNtra2OHToEDXcCCGEEELeQZVuvIWHh8Pb2xtAydCv3NxcHDt2TC6Pjo4OvL29ERERAaBkmKW3t7fWGiZlXb58GYaGhtDX14eZmRkSEhIwadIkhV6W9evXy3qcSlN0dDQAIC0tDSYmJjAzM1OoX1dXF61bt0ZaWppgLDdu3EDr1q3VOs/s7GwYGhrCwMAA9erVw7Zt2+Dm5gZbW1u5fPv27VOIu7T3kk/9+vXRqFEjwXfXNFF67Q0NDaGnp4eVK1di69atcj2eFVF6rnp6emjTpg1SU1Mxe/ZshXyzZ89WuCYJCQmy/UePHkVeXh569+4NAPD29q6SoZOOjo54+fIlzp07B6Ckh61Hjx7o0aMHzp8/j7y8PLx+/RpJSUkKjTd1Pleh8wSAL7/8Em3atMGOHTsglUoFYy4oKMCLFy/kUlFBoWYXghBCCCGEVKlKDZu8fv06zp49i7i4uJJKJBIMGzYMERERsiFipUaPHo2uXbtiyZIl2L59O06fPi3rodAmGxsb7NmzBwUFBdi9eze2b9+u9F0vLy8vzJs3T25bo0aN1DoGYwy6urpq5VNnsgugZEjchQsXUFRUhBMnTuC7777Dzz//rJDPyckJP/30k9y2+vXrqx23uvFURum1B0omy4iJiYGHhwfi4+Px0UcfVbi+0nPNy8tDWFgY0tLSlL7jNXPmTIwaNUpuW9n3KcPDwzFs2DBIJCW3uaenJ2bOnInr169rpVewlJWVFZo3b46EhATY29vj4sWL6NGjBxo1agQLCwv89ddfkEqlePXqFXr27Kn0XMsq/7kKnScADBw4EDt37sSOHTuUvutZ3tKlS7Fw4UK5bY4LPOEU7CVYlhBCCCEEoGGTNaFSjbfw8HAUFRXJ/QHJGIOOjo7CrIDt2rWDra0tPD09YWdnh3bt2snNjKcturq6sLS0BFAygcaNGzcwYcIEuclBAMDExESWrzwrKytkZ2fj0aNHaNq0qdy+169f4/bt2wozaypjbW2NkydPorCwULD3TSQSyeKxtbVFRkYGhg0bhj///FMun4GBgcq4+Tx79gxPnjyBhYVFhcuqq+y1B4BOnTph165dCA0NxW+//QagpJGqbAKTrKwsmJiYyG0re67r1q2Dk5MTFi5cqNAjZWpqqvKaZGZmYteuXSgsLJRrHL158wYRERFYvnw5gJIJY1TFVZGeQ0dHR8THx6N9+/awsrKSPRAoHToplUrRqlUrmJubqzxXVfjOs9TcuXPRvn17eHl5gTGGYcOG8eYPDAyEn5+f3LaV0uMqchNCCCGEkNqgwsMmi4qKsGnTJqxatQrJycmylJKSglatWmHz5s0KZXx9fZGQkABfX1+tBK2O+fPnY+vWrbhw4YLaZYYMGQKJRIJVq1Yp7Pv555+Rl5eHL7/8UrCeESNGIDc3F+vXr1e6v+yEJeXNmDEDKSkp2Llzp9px81m7di1EIhHc3d21Up+6xGIxXr16JfvZ1tZWNqywFGMMf//9t2Av2IIFC7By5Uo8evRI7eNv3rwZzZs3R0pKitx9GhoaiujoaFnvr62tLc6fP69Q/ty5cxXqnXNycsKpU6dw5MgRuaUPSictSUhIUOh107ZvvvkG3377Lby8vATfzZRKpTA2NpZLEqn2hzMTQggh5N1FSwVUvwr3vO3btw/Pnz/H6NGjFXpMhgwZgvDwcAwYMEBu+9ixY+Hh4aFyoo6q0Lp1awwcOBBBQUHYt2+fbHteXh4yMjLk8kqlUtSrVw8tW7bEihUrEBAQgDp16sDHxwc6OjrYvXs35s6di0WLFqFdu3aCx3ZwcMCsWbPg7++Phw8f4osvvkDTpk1x8+ZN/Pzzz+jevbvcLJRlGRsbY8yYMViwYAHc3d1lwx0LCgoU4pZIJDA1NZX9nJOTg4yMDBQWFuLOnTv47bffEBYWhqVLl1aq105dRUVFsthKh02Wf08tICAAI0eOhK2tLVxdXfHq1Sts2LABt27dwqRJk3jrd3R0hL29PZYsWYIffvhBtr30fMvS19eHsbExwsPDMWTIEIXPq1WrVpg9ezb279+PgQMHYuLEifjhhx8wadIkfP3119DT08ORI0cQHh6u0GvLx8nJCS9fvkRERAQ2btwo296jRw+MGjUKYrFY6cOLinyuys6zvDlz5kAsFsPHxwfFxcXw8qJhkIQQQggh74oK97yFh4fDxcVFoeEGAIMHD0ZycrJsEepSpX+Mlr57VF38/f2xf/9+uQWUN27cCDMzM7nk6ekp2z9jxgzExcUhMTERH330ESwtLeHv74+oqCjMnTtX7WMvX74cW7ZswZkzZ9C7d2/Y29vDz88P7du3x8iRI3nLTps2DVevXsX27dtl2w4dOqQQd/fu3eXKBQUFwczMDJaWlvDx8UF2djaOHTumdLIPbbpy5Yospo4dOyI2NhY//fSTXC/l0KFDERUVhejoaHTu3Bmurq64desWEhMT0apVK8Fj+Pn5YePGjXKLTpeeb9k0a9Ys/P3330hJScHgwYMV6jEyMoKrq6ts4hJzc3MkJibi1q1bcHV1lS3IHhUVBQ8PD7WvgYWFBVq1aoWcnBz06NFDtr1Zs2Zo2bIl8vPzlc40WZHPtfx5qjJz5kysWLECI0eOrFADlBBCCCGkIqjnrfpxrPz8/kROZmYmnJ2dYWxsjIMHD0JfX7+mQyKkSoRgv8Z1FFV+AlsAgB5eC+aRMv7f2IUcfwxC5XWY8IRKT0T8SzHkCwxq0IXwvzpCeb7BAN79y7GLd/8rCE++JAL/Pw9S8M9QWgz+iZLUieEFqyOYh48Zp/hOa1kFEB4uLHQdhLyG+kvWVDYGTWNUh9DnacgKePcHcF8IHmMR9vHuF4pBiNB3ExD+7ukI7H+j4e9BQPg8tXE/aHottUHTGITOszrOUZ1jhHD9ePcHsQO8+4XOMxj89VelCTY114z46XrN38M1QfPfMO+4+vXr4+jRo3B2dsbp06drOhxCCCGEEELIe+qtaLyVX+OqbEpMTKzy4zdo0ABBQUFwdnYGAIwfP15lPOPHj6/yeKpTTV/72sDe3l7lNVA2QQ8hhBBCyPtAVFRz6X1VvS+hVRLf0gLl17uqDiEhIQgICFC6r7ILU9dWte3a14QDBw6gsFD58LDGjRtXczSEEEIIIeR99VY03qpypsTKaNSokdoLe7/tatu1rwnqTKhCCCGEEPK+Eb15P987q0lvxbBJQgghhBBCCHnfUeONEEIIIYQQQt4Cb8WwSUIIIYQQQkjt8j6vt1ZTqOeNEEIIIYQQQt4C1PNGCCGEEEIIqTDqeat+1drzdurUKYjFYvTp00du+927d8FxHCQSCR4+fCi3Lz09HRKJBBzH4e7duwgODgbHcbzp7t27vHGUrUMkEqFp06bw8vLC/fv35fI5Ojoqrb/8Wm779u2Do6MjjIyMoK+vj86dOyMqKqrC12fHjh1wdHSEiYkJDA0N0b59e4SEhCAzMxMAEBUVJRdH48aN8fnnn+PKlSty9YwaNUpp3GWvu7m5uWy7np4ezM3NMXToUBw/flyurtLPJjk5WevXnuM4mJiY4NNPP8WJEyfk8nEch127dimUnz59OhwdHZWeq0QiQcuWLTFhwgQ8f/5crlzZ8y2bli1bpnAMV1dXiMViJCUlKexzdHTE9OnTFbbv2rULHKf+jEuvXr3CggULYGNjA6lUClNTUwwZMkThs+S7V0s/G74UHBysdkzaIALjTUIKIRFMrzgd3iRU/iWny5ueiIwEkwTFvMkQr3mT0HUSgaEYHG8S8hJS3lQIkWDS9BhvIOZN6lyH+lyeRukVdHmT0HUuBociiDRKQveLBMUaf3eEqHOemsrjdHlTdRA6R30UCiYhhRDzpuq41tq4Z9WJU5NzqA3XobYIYgd4UwjXjzeZFufyJvJ+qdbGW0REBKZMmYKTJ0/i3r17CvubNm2KTZs2yW2Ljo6WW08sICAA6enpstS8eXOEhITIbWvRooVgLPb29khPT8eDBw8QExODy5cvY+jQoQr5xo4dK1d3eno6VqxYIdv//fffY+DAgfjkk09w5swZXLp0CcOHD8f48eNVrgWnzLx58zBs2DB07twZBw8exD///INVq1YhJSUFv/76qyyfsbEx0tPT8ejRI+zfvx8vX75E//798fr1a7n6+vTpoxD31q1b5fKUXrfr169j06ZNqFu3LlxcXLB48WKlMWr72qenp+P06dOwsrLCgAEDkJ2drfb1Unaud+/eRVhYGPbu3YuJEycq5Csfa3p6OqZMmSKX5969ezh9+jQmT56M8PDwSsUjpKCgAC4uLoiIiMC3336LtLQ0HDhwAG/evIGDg4NCo1HVvdqiRQu5c/H395e7tunp6RW6BwkhhBBCKkL0pubS+6rahk2+fPkSsbGxOHfuHDIyMhAVFYWgoCC5PCNHjkRkZCQCAwNl26KiojBy5Eh8++23AABDQ0MYGhrK9ovFYhgZGaFJkyYVikcikcjKNG3aFGPHjsXUqVPx4sULuYW29fX1VdZ9//59+Pv7Y/r06ViyZIlsu7+/P3R1dTF16lR4eHjAwcGBN5azZ89iyZIlCA0NxbRp02Tbzc3N0atXL2RlZcm2cRwni8fMzAwzZsyAm5sbrl+/jg8++ECWTyqVCl6TstetZcuW+Oyzz2BmZoagoCAMGTIENjY2cvmr4to3adIECxcuRGRkJNLS0tC5c+cK1QXIn2vz5s0xbNgwpT2f6sQaGRmJAQMGYMKECejSpQtCQ0NhYGBQ4Zj4hIaG4vTp07h48SI6dOgAoGQtuR07dsDBwQGjR4/GP//8I+vJU3Wvvnz5Uu58DA0N5fISQgghhJB3S7X1vMXExMDGxgY2Njbw9vZGZGQkGJMfCuLm5obnz5/j5MmTAICTJ08iMzMTn3/+eZXGlpGRgbi4OIjFYojFYrXL/f777ygsLFTauzFu3DgYGhoq9HYps3nzZhgaGirtLQKAunXrKt2elZWFLVu2AAB0dHTUjpvPtGnTwBjD7t27tVKfkIKCAkRFRaFu3boKjcXKuH37Ng4dOlSp68EYQ2RkJLy9vWFrawtra2vExsZqHFN5W7ZsQa9evWQNt1IikQgzZsxAamoqUlJSlJat7L1KCCGEEELeftXWeAsPD4e3tzeAkmFuubm5OHbsmFweHR0deHt7IyIiAkDJMEtvb2+tNUzKunz5MgwNDaGvrw8zMzMkJCRg0qRJCr0s69evl/U4labo6GgAQFpaGkxMTGBmZqZQv66uLlq3bo20tDTBWG7cuIHWrVurdZ7Z2dkwNDSEgYEB6tWrh23btsHNzQ22trZy+fbt26cQd2nvJZ/69eujUaNGgu+uaaL02hsaGkJPTw8rV67E1q1b5Xo8K6L0XPX09NCmTRukpqZi9uzZCvlmz56tcE0SEhJk+48ePYq8vDz07t0bAODt7V0lQyfT0tJgZ2endF/p9rL3jbr3akUUFBTgxYsXcqmoQPhdD0IIIYSQUjRssvpVy7DJ69ev4+zZs4iLiys5qESCYcOGISIiAi4uLnJ5R48eja5du2LJkiXYvn07Tp8+jaKiIq3HZGNjgz179qCgoAC7d+/G9u3blb7r5eXlhXnz5slta9SokVrHYIxBV1f4JW3GmNqTXRgZGeHChQsoKirCiRMn8N133+Hnn39WyOfk5ISffvpJblv9+vXVjrsik29UVOm1B4CcnBzExMTAw8MD8fHx+OijjypcX+m55uXlISwsDGlpaQrvsgHAzJkzMWrUKLltZd+nDA8Px7BhwyCRlHwtPD09MXPmTFy/fl0rvYLqKO2NLnvfqHuvVsTSpUuxcOFCuW2OCzzhFOylUb2EEEIIIaTqVEvjLTw8HEVFRXJ/KDPGoKOjozArYLt27WBrawtPT0/Y2dmhXbt2SE5O1npMurq6sLS0BFAyIcSNGzcwYcIEuclBAMDExESWrzwrKytkZ2fj0aNHaNq0qdy+169f4/bt2wozaypjbW2NkydPorCwULD3TSQSyeKxtbVFRkYGhg0bhj///FMun4GBgcq4+Tx79gxPnjyBhYVFhcuqq+y1B4BOnTph165dCA0NxW+//QagpJGqbAKTrKwsmJiYyG0re67r1q2Dk5MTFi5cqNDTaGpqqvKaZGZmYteuXSgsLJRr9L558wYRERFYvnw5gJIJY1TFpW7PoZWVFVJTU5Xuu3btGoCSe6KUuvdqRQQGBsLPz09u20rpcRW5CSGEEEIUvc89YDWlyodNFhUVYdOmTVi1ahWSk5NlKSUlBa1atcLmzZsVyvj6+iIhIQG+vr5VHZ7M/PnzsXXrVly4cEHtMkOGDIFEIsGqVasU9v3888/Iy8vDl19+KVjPiBEjkJubi/Xr1yvdX3bCkvJmzJiBlJQU7Ny5U+24+axduxYikQju7u5aqU9dYrEYr169kv1sa2uLc+fOyeVhjOHvv/8W7AVbsGABVq5ciUePHql9/M2bN6N58+ZISUmRu09DQ0MRHR0t6/21tbXF+fPnFcqfO3dO7d45T09PHD16VOG9tuLiYqxZswYfffQR2rZtq7J8Ze7V8qRSKYyNjeWSRKr94cmEEEIIIUR7qrznbd++fXj+/DlGjx6t0GMyZMgQhIeHY8CAAXLbx44dCw8PD5UTdVSF1q1bY+DAgQgKCsK+fftk2/Py8pCRkSGXVyqVol69emjZsiVWrFiBgIAA1KlTBz4+PtDR0cHu3bsxd+5cLFq0CO3atRM8toODA2bNmgV/f388fPgQX3zxBZo2bYqbN2/i559/Rvfu3eVmoSzL2NgYY8aMwYIFC+Du7i4b7lhQUKAQt0QigampqeznnJwcZGRkoLCwEHfu3MFvv/2GsLAwLF26tFK9duoqKiqSxVY6bLL8e2oBAQEYOXIkbG1t4erqilevXmHDhg24desWJk2axFu/o6Mj7O3tsWTJEvzwww+y7aXnW5a+vj6MjY0RHh6OIUOGKHxerVq1wuzZs7F//34MHDgQEydOxA8//IBJkybh66+/hp6eHo4cOYLw8HC1e8JmzJiB3bt34/PPP8eqVavg4OCAx48fY8mSJbhx4wb++usv3vKq7lVCCCGEEPJuq/Ket/DwcLi4uCg03ABg8ODBSE5Oli1CXaq0kVH67lF18ff3x/79+3HmzBnZto0bN8LMzEwueXp6yvbPmDEDcXFxSExMxEcffQRLS0v4+/sjKioKc+fOVfvYy5cvx5YtW3DmzBn07t0b9vb28PPzQ/v27TFy5EjestOmTcPVq1exfft22bZDhw4pxN29e3e5ckFBQTAzM4OlpSV8fHyQnZ2NY8eOKZ3sQ5uuXLkii6ljx46IjY3FTz/9JNdLOXToUERFRSE6OhqdO3eGq6srbt26hcTERLRq1UrwGH5+fti4caPcwuul51s2zZo1C3///TdSUlIwePBghXqMjIzg6uoqm7jE3NwciYmJuHXrFlxdXWULskdFRcHDw0Ot869Tpw6OHTuGL7/8EoGBgWjTpg26dOmCf/75B//88w/s7e0F61B2rxJCCCGEVCeasKT6caz8fP1EI5mZmXB2doaxsTEOHjwIfX39mg6JvAUOHjyIL774AitXrsTkyZNrJIYQ7Ne4DjGKefdnsTq8+024AsFjPBeow4DjnzXzJeMfHqpODPWLX/Luf83xP3h6ygnPFGqCV7z7Z8Odd78/O8q7v5AJPxwzEym+31lWNvR49zdiubz71bkO+tBsFtQ88H/eHKr+n0Adge8FABRDs0miDMB/3xZBeGkRCfj/GhKqw6zoBe9+X4nwhEirWRzv/lxOyru/SOCZtK7AOQLCn0W+wKAliRqft1Aeofu2DvgnchOKUR1Cv8/zBX6HCP0uBoR/Hxtxr3n3C31Womr5fgvfU4UC3x3TYv7flZPFw/gPUIN/ygdWbqJwrVjK/yvnnVVtSwW8L+rXr4+jR4/C2dkZp0+frulwyFuib9++OHjwIDIzM/H06dOaDocQQgghRJCoqObS++qdbLyVX8urbEpMTKzy4zdo0ABBQUFwdnYGAIwfP15lPOPHj6/yeKpTTV/72sDe3l7lNVA2QU8pJycnBAUFyb2XSAghhBBCSKnqfamsmvAtLVB2uYLqEhISgoCAAKX7KrswdW1V2659TThw4AAKC5UPF2ncuHE1R0MIIYQQUjXe53fPaso72XirypkSK6NRo0ZqL+z9tqtt174mqDOhCiGEEEIIIRX1Tg6bJIQQQgghhJB3zTvZ80YIIYQQQgipWjRssvpRzxshhBBCCCGEvAWo540QQgghhBBSYdTzVv2o540QQgghhBBC3gLUeCOEEEIIIYSQtwEjhJBy8vPz2YIFC1h+fv5bXQfFQDFQDLUzBm3UQTFQDBQDeR9xjDFW0w1IQkjt8uLFC5iYmCA7O7vSC8nXhjooBoqBYqidMWijDoqBYqAYyPuIhk0SQgghhBBCyFuAGm+EEEIIIYQQ8hagxhshhBBCCCGEvAWo8UYIUSCVSrFgwQJIpdK3ug6KgWKgGGpnDNqog2KgGCgG8j6iCUsIIYQQQggh5C1APW+EEEIIIYQQ8hagxhshhBBCCCGEvAWo8UYIIYQQQgghbwFqvBFCCCGEEELIW4Aab4QQAMCbN2/w+PFj/Pfff3jz5o3a5Vq3bo1nz55VYWSEEEIIIQSgxhsh772dO3eiW7du0NfXR9OmTWFmZgZ9fX1069YNu3btEix/9+7dCjX2KiMlJQVisVjl/r1791bp8Un1u3fvHmgyZEJIbfXw4UPBPJs3b1a5LyQkBHl5edoMibwnqPFGyHvsl19+wfDhw9G+fXvExMTg5MmTSExMRExMDNq3b4/hw4dj48aNNR0mAPD+IT9kyBCMHj0aubm51RhR7XX27Fm5BnX5a1dQUIDY2NjqDkuOUIPcwsICT5480egYPXv2RFZWlkZ1aErTBwv+/v54/fq1lqIhtcm///6LM2fO4OzZs/j3339rOhxERUUhOzu70uVv3LiBY8eO4ebNm2qXKf/g7+zZs0hKSkJBQUGFjq3taxkXF4f27dvz5unVqxeeP3+ucv+WLVvw1Vdfqdy/cOFC+jeLVA4jhLy32rRpw8LCwlTuDw8PZ61bt+atg+M4Fh8fz1JSUniTJpKTk5lIJOLd36lTJ2Zubs4SEhIqfRw7Ozv27Nkz2c9jx45l//33n+znx48fMz09PbXqSktLY9999x2bNGkSmzx5Mlu1ahW7deuWYLkvvvhCrcRHJBKxx48fy342MjKSO3ZGRgbv9ezbty/LysqS/bxo0SL2/Plz2c9Pnz5ldnZ2gufCJzk5mXEcp3I/x3Fy51AZmtZx4sQJtRIfXV1d5uvry3JycioVg4WFBWvbti27cOFCpcozxtiECRPkjr9p0ya5n58/f8769u1bZeWrUnBwMHvy5EmlyhYWFrI//viDhYWFsSNHjrCioiK1yhUVFbHbt2+zN2/eMMYYy8/PZzExMWzr1q0sIyNDsPzq1atZ8+bNmUgkYhzHMY7jmEgkYs2bN2dr1qxRK4Z9+/ax0aNHs5kzZ7KrV6/K7cvMzGROTk5q1VOWjo4OS01NVSvv0qVL2bFjx2THc3Z2ljuXPn36yP3OKO/OnTvsf//7HxOLxaxfv34sOzububi4yOpo3bo1u379umAcmlzLDRs2sCFDhjBPT0+WlJTEGGPs2LFjrGPHjkxPT499/fXXvOV79OjBunTpwnJzcxX2bd26leno6LDVq1erLK+N33Hk/USNN0LeY3Xq1GHXrl1Tuf/q1ausTp06vHWU/mNZ+g9n2VS6na+hoA6hxhtjJX+ILViwgEmlUubn58eePXvGsrOz5ZKQ8v+YKmv08DU4Si1ZsoRJJBImEolYkyZNWOPGjZlIJGI6Ojrsu+++4y07atQouaSrq8sGDx6ssL0i52FoaFih89C08acOoc+0NjTelN3TZe9tkUjExGIxbx2aPlh4+fIlmzhxIpNKpSwkJETWYKgITT9Pbd0PP/74I3N2dmYeHh6yP/xLPXnyhFlYWKgsW/67nJ2dzbKyspiOjg47c+aMWt/xKVOmsH379jHGGLt//z6ztbVlYrGYNW7cmInFYvbBBx+wBw8e8NaRnJzMmjRpwkQiEWvfvj27f/8+a9euHTMwMGCGhoasXr167OzZsyrLh4SEMGNjY7Zs2TJ28eJF9ujRI/bw4UN28eJFtmzZMmZiYsK+/fZb3hg2b97MxGIx69+/P+vevTurU6cO++2332T7hT6PevXqKU0cxzETExPZz3xatmwpeyg3ZswY1qlTJ3bhwgX26tUrlpyczD7++GM2evRoleUHDx7MevTowfbu3cuGDh3KunXrxhwdHdmDBw/Yo0ePWO/evZm7uztvDJpcy++++47p6OiwDz/8kOnr6zN9fX22ePFi1qBBA7UfCOTk5LAPP/yQOTs7s9evX8u2x8TEqPW7nuM4uYeDhKiLGm+EvMc+/PBD5ufnp3K/n58f+/DDD3nr4DiOnTt3jt29e5c38VH2h1nZlJiYqHZj4fDhw0wsFsv+uK5IA1KdRo9QPcePH2cikYgtWLCAZWZmyrY/e/aMzZ8/n4nFYsHemrLKx6AOTc9DG9dBiDqNt8WLF7O1a9fyJj4cx7GbN28K3l+qZGVlKU2PHj1is2fPZnp6esze3l7wXLXxYOH48ePMwsKCdenShcXFxbHdu3fLJaHrUNP3w9q1a5m+vj6bNGkS8/b2ZlKplC1ZskTtOsp+n5V9t9X5jpuZmcl6loYOHcpcXFxkf6Q/e/aMDRgwgA0ZMoS3DldXVzZkyBB2+fJlNm3aNNa2bVvm4eHBXr9+zQoLC5m3tzdzcXFRWb558+Zs586dKvfHxcWxpk2b8sbQqVMntm7dOtnP27dvZ4aGhrJRFELX0tDQkPXv359FRUXJUmRkJBOLxWzx4sWybXykUqns97q5ubnC77Tz588zMzMzleUbNmzILl68yBgr+Z5xHMcSExNl+//++2/WuHFj3hg0uZa2trYsPDycMcZYfHw84ziOOTs78/YWKvPff/8xW1tbNmjQIFZcXMxiY2OZjo4OW7ZsmWBZjuPYBx98wDp16sSbCClPUtPDNgkhNWfVqlXo378/Dh06BFdXVzRu3BgcxyEjIwNHjhzBv//+iwMHDgjW07JlSzRq1KjScdStWxccx6nczxjj3V8qLi4OEyZMwGeffYZ58+ZBIqn+X3E///wzxowZg+DgYLnt9evXR0hICDIyMvDTTz/hs88+q/bYqtOLFy949+fk5AjW8fPPP/O+F8dxHKZOncpbh7W1tcp9pfeVqgl3TExM5H4uLi5GREQEFi5cCJFIhB9//BEjR47kPT4ASCQSBAcH45NPPkG/fv0QGhqqdgylnJycsGbNGgwePBiDBw+W26dO+Zr2yy+/YOPGjRgxYgQAYOLEiXB3d8erV68QEhIiWN7MzAwdO3aEv78/RKKS1/UZY3BxcUFYWBgsLCwE63j+/Dnq1KkDADh16hR27NgBU1NTACXfz6VLl8LJyYm3jnPnzuGvv/6CnZ0dli5dih9++AGRkZHQ0dEBAMyZMwc9evRQWf7Zs2ewsbFRud/a2pr3PSoASEtLw4ABA2Q/DxkyBKampnBzc0NhYSG++OIL3vIXL17EiBEjcPz4cfz4448wNDQEAIwdOxbu7u5o27Ytb3kAaNWqFf755x+0atUKHMcp/K4Vi8V4+fKlyvL5+fmy75eRkRHEYjGMjIxk+42NjQUn89DkWv77779wcXEBADg6OkJHRweLFy9G3bp1eY9ZXsOGDfHHH3+ge/fucHFxwcmTJ7FgwQLMnj1brfK9e/eWXX9C1EWNN0LeYz169MA///yDn376CUlJScjIyAAANGnSBAMGDMD48eNhbm5e5XHEx8drVD4rKwsTJ07Enj17sHjxYkybNq1S9XAcp9BIVKfRWNbZs2fx66+/qtzv4+ODL7/8slLxVURqaqrs82SM4dq1a7KX458+fcpbVhvXQRsN8vPnz2v0UAAAfv/9d9SvX1+jOoCSBwNz587FkydPEBgYiClTpkAqlVaofGUfLLx69QqzZ8/Ghg0bMH/+/Bp7MKGJO3fu4JNPPpH93LVrVxw/fhzOzs4oLCzE9OnTectfunQJo0ePxrfffotff/0VzZo1A1ByX3bp0kWtBoe1tTXOnj0LCwsLGBkZKTxgyMnJQXFxMW8djDHZtS//X6Ck0cJXR5cuXbB48WJERUUpfIZFRUVYsmQJunTpwhuDsbExHj9+LNdgdXR0xN69ezFgwAA8ePCAt7ylpSVOnTqFefPmoWPHjoiOjka3bt14y5Q3duxYzJw5EzY2Npg8eTICAgLw66+/ok2bNrhz5w5mzJgBV1dXleXt7e0RERGBb7/9FtHR0WjQoAG2bduGDh06AAC2bt3K++AF0Oxa5ufnyxryAKCrq4uGDRuqe/oASu7JUt999x2+/PJLfPHFF/j888/l9vFNfDJz5kyNf8eR98/b9dufEKJ15ubmWL58eaXL9+jRA7q6uhrFwPekuhTfzINt27ZFy5Yt8ffff/M+iRXCGIOzs7PsD4FXr17h888/l51fUVGRYB2PHz/mbfBaWFjIGlVVydnZWW6WydIn9RzHCTacGGMYNWqUrHGSn5+P8ePHw8DAAADUmglO0wZ5RRuLqnTr1k2jP45OnDiB2bNn4/Lly5g2bRpmz56t0CPHR9MHC6dOncLIkSMhlUrx119/4cMPP6zoKQAAgoKCoK+vDwB4/fo1Fi9eLDsPdaYr17S8qakp7t+/L/fdsLe3x/Hjx9GzZ0/Badfr16+PnTt34qeffkKXLl2wcuVKeHp6Ch63rBkzZiAgIACNGzdGYGAgpk6diu+//x52dna4fv06pk2bhkGDBvHW8eGHH2L58uVYuHAhwsPDYWFhgR9++AEREREAgO+//x7t2rVTWf7777+Hq6srGjVqhB49esiNdvjzzz8hlUpx5MgR3hi6dOmCgwcP4uOPP5bb3qNHD1kDTohEIsHy5cvRu3dvjBgxAl5eXhX6zgUEBODevXto27Yt2rRpg7t378La2hoSiQRFRUX43//+h61bt6osHxwcDHd3d6xYsQJisRiHDx/GmDFjcOzYMYjFYpw7dw5btmzhjUHTaxkWFibr9SoqKkJUVJSsJ7YUX89+x44d5X6fMsYQGxuL7du3y3738vWKa+t3HHn/cIzRQjqEkMo7e/YsPvzwQ9nwtvINg4KCAuzevRtDhw6tcN2MMRw8eBBhYWHYv3+/ykbDokWLMHv2bNnQpcoKDg5W6x/UBQsWqNwnEomQkZGhssHw+PFjNG3aVOU/6Hv27JH72dPTE6GhoWjcuLHcdjc3N5UxqDtVdqtWrZRu55veuqzIyEi18lWG0HWsjjr69euHY8eO4auvvkJwcDCaNGlS4TqaNm2Kli1bIjo6ulIPFnR1dTF16lQsXry4Qj19ZTk6Oqp1X6tqcGtaHgBGjBiBRo0ayQ0ZLXXlyhU4OTnh2bNnag3/TE1NxYgRI9C2bVts374dKSkpavW8AcDq1asxf/58MMbw5s0buQcybm5u+PXXX3mHsZ07dw59+vRBVlYWTE1NER8fD19fX/z7778QiUR4/vw59u7dC2dnZ5V15OTk4LffflMY7dC1a1eMGDECxsbGvOdw4sQJnDp1CoGBgUr3JyQkIDo6Wu3v57NnzzB27FjEx8cjKSmpQvfp1atXsW/fPty+fRvFxcUwMzNDt27d4OLiInjP3LlzBxcuXMBHH32EVq1a4fHjx/jxxx+Rl5eH/v37Cw5hBSp/Lc3NzQXj4zgOt2/fVrlf09+z6vx+OnfuHDp37qzWccj7gxpvhBCNiMVipKeny/4BMjY2RnJyMlq3bg1AuLGizO3btxEREYHo6Gjk5uaif//+GDx4sMp3OcrHUJNEIhEWLVqk8g/AnJwcBAUFqbwepe/z8Hkb3nESeuetlKo/rhYuXIiZM2fKensqw8LCAufPn0eDBg2U7s/Pz8cPP/yAgIAApftFIhEkEgkMDAx4/9DLzMxUuU/TBws9e/bEvn37NLoOtcGlS5fw999/q3wwcOXKFfz++++8D0bKev36NebMmYP4+HjExcWp9c5bqaysLBw5ckShwWFlZaVW+dzcXFy/fh02NjYwNDREfn4+Nm/ejFevXqFXr14a9f6T98e///6Lli1b4uXLlxCLxdDT05PtS05Oxvz583HgwIFa/7ueVD9qvBFCNFL+6aGRkRFSUlLkGm9mZmaC75Lk5+fj999/R1hYGJKSktCrVy8cPHgQycnJvMOQlMVQWR07dsSYMWPg5eWFevXqVaoOdZ7oAiVPnavKvXv31MrXsmXLStV/9epV9O/fn/eptEgkUuudN1V/mGjrHJ4+fYozZ85AR0cHzs7OEIvFKCwsxPr167F06VIUFRWpfAcwOjparRj4Ji3R9MFCdTyYuHXrFsaOHYvjx4/XSHllJk6ciJCQEIVhbNVVvqbqKCwsRHp6eqW/m0DJEMBHjx5Vug5NywOan4c2YqhqK1aswJQpU2SNrj///BMODg6yHvKcnBzMnj0b69evV1r+wYMHGDZsGJKSkiAWizF58mQsWrQI48ePx9atWzFw4ED4+/uja9eu1XZO5O1AjTdCiEbUabwJ9bxNnDgR27Ztg42NDby9vTF8+HA0aNAAOjo6ag2JEolEePz4cYVfOC9v3LhxiImJQUFBAdzd3TFmzBje4U+1laqGU9khrRzHqfUOnzIpKSn43//+x/uZnjhxQq26VL3vqI1zOHXqFAYMGICsrCxwHIePPvoIkZGRcHd3R3FxMaZPnw5fX98q7dXS9MGCth5M8FHn86zK8sqU78Gv7vI1VYc2rmVt+DyrK4b169cjLi4O9evXx/jx49GzZ0/ZvqdPn6JLly5KHzKpmuHUxMQENjY2cHV1FRwFoemoE29vb1y+fBljx47Fjh078Oeff6Jjx47o0KED5s+fX6HeZPJ+oQlLCCE1bsOGDZg9ezbmzJkjN110RcyfP1/wj/DVq1fz7v/ll1+wdu1abN++HZGRkXB1dUWLFi3g6+uLUaNGVctT4Js3byI7O1tuYopjx45h0aJFePnyJdzd3TF37lzeOi5evKh0O2MM27Ztw7p166p8empNJ6HRxjnMnz8frq6u+OabbxAREYHQ0FAMGDAAwcHB8PHxUXvCgFevXuHIkSNIS0sDx3GwtraGi4uL3DAnPppOTPA+Tmyg6XNlbTyXri11EOXWrVuHwMBAfPXVV8jOzka/fv2wYMEC2buAb968Ufle2s6dO5Vuz8rKwsOHD2Fvb4/Dhw/zPjQp/9lW9LOOj49HbGwsunXrhiFDhqBp06bw8PDAnDlzKlQPef9Q440QAqBkyIe+vj4++ugj2bbz588jLy9PcE0yTaalB4BNmzYhMjISZmZm6N+/P3x8fNCnT58KxX/58mXeWS/V/QO4Tp068PHxgY+PD+7cuYOIiAiEh4cjJCQEzs7OGD16NO/kK/369cPWrVtlM/EtXrwYkyZNkq0f9OzZM3z66adITU1VWn7mzJlo166drPF2584dfP755/j000/Rvn17LF26FPr6+rxTq5dOt13W0aNHMWfOHKSlpWHWrFkq3/OqaupOQqONc0hJScGJEydgb2+PRYsWYe3atVi+fDk8PDzUjnfPnj0YM2aMwn1samqK8PBwfP7554J1aPpgoewMqKpcuHBBMA5S8/73v//x7n/16lWV1/GuxKDJ2oGqHg4BQHp6OkaMGIG5c+ciLCxMMI7KysjIQJs2bQCUTLKip6eHgQMHVtnxyLuDGm+EEAAlM8rZ2trKNSp8fHyQlpYmOHRFk2npgZKZ6EaMGIG7d+8iMjISkyZNQl5eHoqLi5GamqrWTHI7d+7U+tAyCwsLfPvttwgJCcGOHTswbtw4HD16lLfxdvjwYbkGyfLly+Hp6SlrvBUVFeH69esqy58/fx6zZs2S/bx582ZYW1vj8OHDAErWDPr+++8F18Uq9ffff2POnDlITEzEmDFjcODAgRqZ2EXZJDTbtm1Tq2xlzyEzM1M2lFZfXx/6+vro1KmT2jGfOnUKQ4YMgZubG/z9/WFnZweg5GHFqlWrMGTIECQkJAi+k6LpgwVayPfdkZqaiuHDh6scEpeeno60tLQqreNdiUHTtQNVMTMzw6JFi+Dj41Op8hVROkszUDJEuuzac4SoQo03QgiAkn8Iy8+Id+zYMRQWFgqW0xZzc3MsXLgQwcHBOHz4MCIiIuDt7Y3p06dj0KBBWLdundJyVTmsLD4+HpGRkYiLi4NEIsHYsWN582s6lObp06do3ry53PHL9u44OjrC399fsJ6bN29i3rx52LFjB4YOHYrU1FS137upV68e7zVV9105ZZPQpKenqzUJjabnAJTcFzk5OahTp47sIUJeXp7CTJiqZrxctGgRvvrqK/zyyy9y2z/55BN88sknGDduHL799lscOHCANw5NHyxoupBvp06deD9PoXXaNC1P/l+7du3g4OCACRMmKN2fnJyMjRs3Vmkd70oMmq4dyKdZs2b477//BPPxrRWXk5PDW1ZoXdFS1KtOyqPGGyEEgPK1aJo2bVqpchVV/sVvjuPQp08f9OnTB5mZmbJhlapo+72Se/fuISoqClFRUbh79y4+/fRTrF+/Hh4eHmq/51RZ9evXR3p6Olq0aIHi4mKcP38eM2bMkO1//fq14PlOnDgR4eHhcHJywvnz59GxY8cKxaBsLa6KKj8JzY4dO2ST0KizHIKm5wCU3BfW1tZyP5fteROa8fL06dO8C9hPmjRJ8N2+2vC+m7u7e42WJ/+ve/fuvD3vRkZGgsPUNa3jXYphx44d+PTTT+W2t23bFseOHVNrnThVUlJS5BqFyrRs2VKugdmkSRP8+uuvCnlUKb8sBg2ZJOqi2SYJIRp78eKFrPfiwIEDcj0zYrEY/fv35y2v6Yx60dHRGD58eKUXMS61ZcsWREZGIj4+Ho0bN8aXX36J0aNHw9LSUu06xGIxMjIyZMP1jIyMcOnSJdnwIKEZyEaMGIGcnBysX78e27dvx4IFC5CRkQEDAwMAwI4dOxASEoKUlBSVMZQOv7G1teWNtSqf6EokEqWT0FRkBlFNz0HTGS/19PRw7do1lQ8o/v33X9jZ2fH2PL0Ns01Wh5CQEAQEBKg9s+eECRPw7bffynoxNC1fm+og2qHJ2oGq1qHMzs7GuXPn4O/vjzFjxmDevHlajZkQbaDGGyHvKaGhcWXxLUK8b98+zJ8/X/YCuJGREV6+fCnbz3EcYmJiMGTIEJV1aPoH6p49e9TK5+bmxrtfV1cX/fv3x+jRo9GvXz+1eojKE4lE6Nu3r6whuXfvXvTs2VPW+CooKMChQ4dUNt7u3LmDXr164c6dOxCJRFi3bp3c0CJ3d3dYWFhgzZo1KmNYuHChWrGquyByZZQ2hE+fPi03CY2enp5ajbfqOocnT56oXGKiQ4cOmD59uso/DktnsLx06ZLK+jV9sFC6kK8mPXD5+fn4448/4OTkpDCb64sXL5CQkIDevXurjFHT8kDtWO+uttRREbVhvbp3MQa+dSg5jsO4ceMQGhqq8CpBVbl06RLS0tKgq6sLa2trwYdW5P1GjTdC3lNlFyB+9uwZFi1ahN69e8smXzh9+jQOHz6M+fPnyw3bK8/NzQ0DBw7E6NGjASiu87ZixQokJCTwvhckEokQHR0tm6GR71iqygvhGx5X6r///tP4j7JRo0ap9Yc23zDQwsJCpKamomHDhgpDV1NSUtC8eXM0aNBAozj5qNuw52vUlyqdhCYqKgp5eXnIzMwUbMxXNXVnvFyzZg0WLVqEX3/9Ff369ZPbt3//fowcORLz5s3j/X5o+mDBz89PrfJ8s1WuXbsWe/bswbFjx5Tud3Fxgbu7OyZPnlwl5YHa0QNZW+qoiNqwXt27GIOqXnljY2NYWVmpNUGQpjMLA8DZs2cxevRopKamyobDcxyHzp07IyoqStaIy8zMRP369StyuuQdRo03QggGDx4MJycnhT++fvjhBxw9ehS7du1SWdbc3By///67bImB8o23y5cvw9nZmfflb201vjSlrR682qT0iS7HcbCyskL79u0Fy5Rt2PMZOXKk2nEwxmST0OzZswempqa8k9AINaSLiopw4cIFdOnSRe0YlM14OXjwYHzxxRdK8xcXF2PYsGHYsWMHbGxs5GabvHHjBtzd3bF9+3be+1fTe1ud93Y4jsPx48dV7u/SpQvmz5+vclmDffv2ISQkBGfPnq2S8kDJdXj8+LHKXk4hmpavTXVURPnfpzVRB8WgnKaLdKempsLBwQF2dnaYMWMG7OzswBjD1atXsWbNGty6dQv//PMPdu3ahczMTHzzzTdaiZu8/ajxRgiBoaEhkpOTFd7tunHjBjp16iRbs02ZOnXq4OrVq7J3us6fP48OHTrIhpvcuXMHtra2Kns3gNrzXo82GpGDBw/Ghg0bKt0zpo2eFkD1E117e3uEh4ejc+fOlYpPG8pOQqPq3b3yfxjZ2dnh8OHDsgkAhP4wKqVsxsuDBw+qPeMlAMTExGDr1q2yqcutra0xfPhwDB8+XN1TrlH16tVDSkqKyskT7t27hw4dOuD58+dVUh4o+W61a9eu0uvVaVq+NtVREbWh0fIux3Du3DnZd7v0AZenp6davx/L/7tVvn6h31EeHh548+YNduzYoTDSgTGGQYMGITU1Fffv38fBgwcFJ0ci7w+abZIQggYNGmDnzp2YOXOm3PZdu3YJNkLq16+PW7duyRpvZRf5BkoagELDPTSdUW/Tpk1Kt5uYmMDGxkbt9weKi4s1igMoWZ/I3t4eGzduVGsB5/L4Fo9VV2pqKpydnWFnZ4fffvtN4Ymus7MzkpKS1Fo/r6zbt2/j1atXsLOzq9T7gKXq16+P6dOn867DVP654oMHDxSWKFBn1k1NZrwsNWzYMAwbNkzt/Nr24sULGBoaKsRcXFyM3NxclUsdlCoqKsKTJ09UNr6ePHnCu/yDpuVLabpenTbWu6stdZCaN2vWLKxcuRKGhoZo3bo1GGNISEjA2rVrERAQwDvTrDYkJCTg4MGDSv/94zgOc+fOhYODAzXciAJqvBFCsHDhQowePVpuweGkpCQcOnQIYWFhvGU/++wzrFu3Di4uLkr3r1u3TnDKZ00HAEybNk3p9tzcXBQXF6Nfv37YsmWLwmQL5fn6+mLt2rWC+fj89ddfWLlyJYYNGwZPT0+EhoZWqL74+PhKH7vUggUL0KtXL4Unup06dYKnpycGDRqE4OBgxMbGKi3/+vVrLF68GBcuXMDHH3+MOXPmwNvbW5bfxsYGBw4c4J1KOyQkRDBOjuMwf/78ip1cufJ8NmzYoHTGS3WpmpGuPL7G099//42AgADs3r1bIV92djbc3d0RGhqKDh06KC2/c+dOzJ49G8nJyQozHObn56Nz585YuXIl74MCe3t7HD16FB9++KHS/UeOHIG9vX2VlS+l6Xp1mpavTXWQmhUdHY3vv/8e69atw7hx42QjRQoLC/HTTz9h9uzZsLe3x5dffqmyDo7jFH4HVeRBZE5ODho3bqxyf5MmTaCjo4PevXurXSd5TzBCCGGMJSUlsREjRrBOnTqxjh07shEjRrCkpCTBchcuXGBSqZQNGTKEnT17lmVlZbGsrCx25swZNmjQICaVStnff//NW8eoUaPYixcvtHUqMm/evGFnz55l7du3Z/7+/oL5RSIRe/z4sVaOffXqVfbxxx+zVq1asVWrVrG1a9fKpcq6efMmc3Jy4s1jamrKzp07p3L/2bNnmampqcr9fn5+rGHDhmz06NGsdevWzM3NjdnY2LBt27ax2NhY9sEHH7ARI0bwxsBxHGvWrJnsflKWOnXqxFu+7GdhaGjIbt26Jfs5IyODiUQi3hg2b97MXFxcmIGBARs6dCjbu3cvKywsZBKJhF25coW3bGkMIpFIZSrdz8fT05OFhISo3L948WLm5eWlcn+vXr3Yxo0bVe4PDw9nrq6uvDH88ssvzMDAgO3du1dh3549e5iBgQH75Zdfqqw8Y5p/t7Tx3awtdVRE+fu+Jup4F2Po3LkzW716tcq8q1atYp07d+atj+M41q9fP/bFF1+wL774gkkkEubq6ir7uV+/fry/H2xsbNjvv/+ucv/27duZlZWVwFmR9xE13gghGtu1axczNTVV+OO2QYMGbOfOnWrX8+DBA7Z27Vo2adIkNnnyZLZu3Tr24MEDjeM7cuQIs7a2FsxXvsGgqY0bNzKxWMyaN2/OzM3NZcnCwqLSdSYnJws2GKRSKbt3757K/ffu3WNSqVTl/pYtW7L9+/czxhi7fv064ziOHThwQLY/ISGBNWvWjDeGvn37sjp16rCBAwey3bt3s6KiIt785YlEInbz5k2WnZ3NsrKymJGREUtJSWHZ2dksOzubpaWlCV6HUnfu3GFBQUGsZcuWsvt0+/btguUSEhLUSnxat27NUlJSVO6/dOkS7/1gZmbGbty4oXL/jRs3mJmZmeC5eHl5MY7jmJ2dHXN3d2dffPEFs7W1ZSKRiA0fPrzKy2v63dLGd7M21LFw4UL28uVLtfOPHz+ePXnyRKt1UAyM6evr8zYGb926xfT19XnrGzlyJBs1apRgUqX0d9Lly5cV9l26dIm1atWKzZ8/X82zI+8TarwRQhhjJT068+bNY56enrI/Tg4ePMj++ecftcq/fPmSxcXFseXLl7Ply5ezuLg4lpubq/bxf/zxRyaVShnHcaxu3brMxMSEcRzHpFIp+/HHHyt1TqXu3Lkj+A8xYyV/mP33338aHYuxkl6hAQMGsLp167KoqCiN6ytLncabOk90+RqzEolErtFcp04dlpaWJvv50aNHTCwWC8b66NEjtmTJEmZtbc2aNGnCZs2axa5duyZYjjHFXi9VP1dEcXExO3jwIPPw8GBSqZQ1a9aMTZkypUJ1VJRUKmW3b99Wuf/27dusTp06KvfXqVOHXb16VeX+1NRU3vJlxcTEsIEDB7K2bdsyOzs7NnDgQBYTE6NWWU3L3717lxUXF6t9LG2Xry111IbeP4qBMSMjI97v1bVr15iRkVFlQ1PLq1ev2CeffMLEYjHr06cPmzFjBpsxYwbr3bs3E4vFrGvXriwvL69KYyBvJ3rnjRCCEydOoG/fvujWrRv+/PNPLFq0CI0aNcKlS5cQFhaG33//XbAOfX19lVOuP3z4EM2aNVNZdv/+/Zg6dSqmT58Of39/mJmZASiZ/OO7777DtGnTYG5urrDWlrpu3bqF5s2bq5XX2tpa8L0FvvXNtm3bhsmTJ6Njx464dOkSWrRoUaFYtWHYsGHw8/ODjY2NwoyKly9fRkBAAO80/2/evJFbnFYikUAsFst+FolEar2naGZmhsDAQAQGBuLPP/9EZGQkOnfujA8++ABHjx6Fnp6eyrLaePev/IyVHMehT58+6NOnj9yMl+q6cuWK3MxxYrFY8F2vhg0b4vr167IJfcq7du0a78LD5ubmOH/+vMpJd86fP49WrVqpET0wdOhQDB06VGF7fn4+fvjhBwQEBFRZeXWXnwgKCqqS8rWlDnW+N0I0rYNiAD788ENs3rwZ3377rdL9v/76K/73v//x1hEWFoaePXtWegbMOnXqID4+HmvWrMHWrVtla89ZWVlh0aJFmDFjBu/C9+T9RUsFEELQtWtXeHh4wM/PT26643PnzsHd3R0PHz6sVL0ZGRlYvHgxwsLC8OrVK5X5evTogU8//RSLFi1Suv+bb75BYmKiyoVVVWGM4eLFi/D19YWLiwtWrlzJm18kEiE0NFRwsXC+ho+BgQGWLVuGKVOmVChWdaWkpOB///sf7xT5+fn5cHZ2xpkzZ9CrVy+59cmOHj2KLl264Pjx46hTp47S8uUXTS+deKX05fqsrCx89dVXFVp379WrV9i+fTt+/PFHXL58GRkZGYKzJGpK0yUoEhMT4efnh3PnzgEomQo8Ly9PbumFw4cPq5ysBwC++uor3Lx5E4mJiQr7GGP47LPPYGlpqbIROW/ePPz22284e/aswuQGGRkZcHBwgLe3NxYvXsx7Lk+fPsWZM2ego6MDZ2dniMViFBYWYv369Vi6dCmKiorw9OnTKivfqVMnlfs4jsP169eRn5+v8p7StHxtqaM2rDVHMZSsTeju7g4/Pz/4+/vLvlsZGRlYtWoVQkNDsXPnTgwYMEBlHQYGBsjPz0ezZs3g5OQEJycn9OzZU+WsrJraunUr3NzcYGBgUCX1k7cHNd4IITA0NMTly5dhYWEh13i7e/cubG1tkZ+fr7JsVlYWJk2ahD/++AM6OjqYM2cOJk+ejODgYKxcuRL29vbw8/ODp6enyjqMjY1x7tw52NjYKN1//fp1fPTRR8jJyVG6v169ekp7y3Jzc/HmzRv06dMHMTExgtN7a2O9uRs3bsDKygoPHz7Ejh07ZOsHWVtbY9CgQbw9kEDJH4d8PX95eXm4ceOGYMPp9evXsie65dcnE3qiq81F00+fPo2IiAjExsbC2toaX331FUaMGIG6devyltPGTI+afp6enp7o2rUrpk6dCqCk8bZ//360atUKjDGsW7cO//77L3bs2KGyjlu3buHDDz+EjY0N/P39YWNjA47jcPXqVaxatQppaWk4f/68whqLpXJyctC1a1fcu3cP3t7ecuU3b96MFi1aICkpiXc2zVOnTqF///7Izs4Gx3H46KOPEBkZCXd3dxQXF2P69Onw9fVVmM1SW+X5JCcnY86cOTh+/Dh8fX3x888/V2v56q6jNqw1RzGU+P777xEQEICioiLZg6rs7GyIxWKsWLGCdykToGRmyqSkJJw4cQLx8fFISkpCfn4+WrVqhZ49e8oadE2bNuWtR13lFwEn7y8aNkkIQd26dZGenq4wtOvixYuCjY25c+fizz//xMiRI3Ho0CHMmDEDhw4dQn5+vtrr0xQXF8sN0ytPR0eHd4hMaGio0u3GxsawtbWV9TwJ0XS9OaBkyMv69evh5+eH169fw8TEBIwxvHjxAjNnzsTq1asxceJEleXd3d01jgEAdHV1MXv2bMyePbvCZbWx3t2KFSsQGRmJZ8+ewcvLCydPnsQHH3ygdvm6devyfh6MMbUakIcPHxbsSXVzc1O6/dy5cwrLUDRv3lw2TNHHxwf9+/fnrbtNmzY4evQoRo0aheHDh8vOiTGGtm3b4siRIyobbkBJg/Gvv/5CYGAgYmJiZAth16tXD97e3liyZIngMgjz589H79698c033yAiIgKhoaEYMGAAgoOD4ePjI3jfa1pemTt37mD+/PmIiYnBoEGDcOXKFVhZWVVb+ZqsozasNUcxAFOmTMEXX3yB7du348aNGwBKHnANHjxYreHuOjo6+PTTT/Hpp5/im2++kTXm4uPjkZCQgK1bt6KgoECtNRDVQX0tRKZ6X7EjhNRGM2fOZN27d2fp6enMyMiI3bhxg508eZK1bt2aBQcH85Zt2bIlO3LkCGOsZIYujuPYtGnTKnT8Ll26CE7b3KVLlwrVWRl8M8llZmaydevWsQ4dOvDWsW/fPiYWi5m/vz979OiRbPujR4/YjBkzmEQikc3k+C7jOI61atWKTZo0SfYivrKkijZmeuQ4TjDxTXpSp04ddvfuXdnPO3bskJvd7u7du0xXV1fta3Lx4kUWGxvLYmJi2MWLF9UuV6q4uJj9999/7PHjxyonzTh58iTLz8+X29agQQPZxEMvX75kIpGIxcbGqn1cTcuX9eTJEzZ58mSmq6vLevbsyc6ePVut5Wu6jtow4yXFUDVevXrFjh49yubOncs++eQTpquryywtLbVWvzaWSyDvBup5I4Rg8eLFGDVqFJo1aybrEXjz5g1GjBiBb775hrfso0eP0LZtWwBA69atUadOHYwZM6ZCx584cSImTJgAqVSKr7/+WjYMpqioCL/88gu++eYbrF+/vnInVwHKepyOHj2K8PBw7Nq1C6amphg0aBBvHStWrMCcOXMU3t8zMzPD6tWroa+vj+XLl1d48pXXr1/j9evXaj1lVjWMtDy+iVcAYPv27bJhlxzHwcrKCiNGjMCQIUME6/7ss8/AcRyuXLmiMg9fjEI9ti9fvsTff/8tGIcmwyaNjIxw584dWU9b+c/+zp07FXpvr2PHjujYsSNvHr6hURzHCb7f07dvX4XymZmZsnL6+vrQ19fnfXerPE3LAyWf18qVK7F69WpYWlpi7969cHV1rbbytaUObfTua1oHxQDs2bNHrXyqeuWBkneLT506hYSEBBw/fhznz59H69at8dlnn2Hy5Mno0aOH1oZMElIWNd4IIdDR0cHmzZsREhKCixcvori4GJ06dVJrCFH5IY9isbjCL1SPHDkSly9fxuTJkxEYGIg2bdoAKHlfKDc3F1OnTsWoUaNUlheJRIL/kHMcp/bwlXv37iEyMhKRkZHIzc3F8+fPERsbi8GDBwuWvXjxIjZs2KByv4+PD9auXctbR2RkJC5cuICPP/4YXl5eCAwMxOrVq1FUVISePXti27ZtaNCggcryZYeRMsYwYcIEhISEqN2IKS4uhqenJ7Zv3w5ra2vY2tqCMYYrV65g2LBh8PDwwNatW3mveUJCglrHqqybN2/CycmJd9ikpn8gOjg4YNOmTXB0dFS6PyoqCg4ODhodozxWBbP4cRyHnJwc1KlTRzbcNC8vT+G9QlUNUU3LAyXDR3NycjBlyhR4enqC4zhcunRJIV/79u2rpHxtqUPTz1cbdVAMisPTOY5TqE9oWHbdunXRuHFjuLm5Ydq0aejRo4dG70sToi6asIQQohGRSIS+ffvKJsDYu3cvevbsqdCAi4uLE6wrKSkJW7dulXv/YPjw4fj44495y+3evVvlvlOnTuH7778HY4x3xksAiI2NRVhYGP766y/069cP3t7e6Nu3LwwMDJCSkiLrYeRjaGiIS5cuqXyp/Pbt22jfvj1yc3OV7l+8eDEWL16MTz75BBcvXsTQoUOxa9cuTJ8+HSKRCOvWrcOAAQPw008/CcZSquwkNOpYvXo1Fi9ejOjoaIXZ1vbs2YOvvvoK8+fPF3yhvyqpM+umphOWxMfHw8XFBX5+fpg5c6asnv/++w/Lly/H2rVr8ccff6Bnz56Vql+Zin5W6pQv/3CjtAFW/me+GRI1KV9aR6nyfyiX/iwUgybla0sd//77L1q2bKnRgwVN66AYFFXme+fg4IDk5GTY2NjA0dERPXr0gKOjI++DteqOkbybqOeNEALGGH7//XfEx8fjv//+Uxg+yNfwKj9tvre3d4WPHxISgoCAAHz88ceCDTVlBg4cqLDt2rVrCAwMxN69e+Hl5aVyPZ+yRowYgVmzZmHHjh2Ck0CoYm9vj927d2PGjBlK9+/atYt3bbCoqCiEh4fD09MT58+fh4ODA2JiYmRDFdu1a4fx48dXKjZ1RUVF4bvvvlM6TbabmxtWrFiB0NBQ3sZb27ZtcfLkSdSvXx8A8PXXX2Px4sWy4Xf//fcfzM3NkZeXVyXnAJTcm3xryQlxcnLC999/jxkzZmD16tUwNjYGx3HIzs6GRCJBaGioVhtuVUXTNfO0sebenTt3arR8bamjNqw1RzFox5kzZ/Dy5UskJiYiPj4eK1asgKenJ6ytrWWNOW32xrVq1Yp3Yi/y/qCeN0IIpk6dig0bNsDJyQmNGzdWeJJZkYWMK6P8YsqaePToERYsWIDo6Gj07t0bS5cuVVioWpWvv/4asbGxsLe3h4+PD4YNG4Z69epBR0dH7Z636OhoTJgwAStXrlT6/t7MmTOxfv16lcNApVIpbt68KZvtTCqV4tKlS7JlFB4+fAgLCwu8fv1arXMCKv7EVk9PD9evX1e5XtG///4LW1tb3p7M8r1e5d/levz4MczMzCo9s6U6PW/FxcUoLi6Wm0r88ePH+Pnnn/Hy5Uu4ubmhe/fugse6f/8+fv/9d1mPsJWVFYYMGVIlC7BXRc8bqT1qw1pzFIMibX1vcnJykJiYiCNHjsiG3WtrtklCZKp+ThRCSG1Xr169KpkB8c2bN2zPnj1s4MCBvPm0MWtYVlYWmzVrFtPT02Ndu3Zlf/75Z6XqycvLY1FRUeyzzz5jUqmUubm5MbFYzC5fvqx2Hf7+/ozjOGZsbMw6derEOnXqxIyNjZlIJGLTp0/nLVv+WpSfYSwjI4N3hkRlKjpLWb169VhKSorK/ZcuXWL16tXjrUPT89i9ezdvCg0NFbwOo0aNYmPHjpX9/OLFC9aiRQvWsGFD1r59+1o586eRkZFGM8opK5+dna1WUkXT8owxtnz5cpaXlyf7+cSJE3KzYr548YJNmDChysrXpjqUuXjxIuvduzfT0dFh48aNq3B5bdTxPseg6UyOb968YUlJSWzZsmWsd+/ezNDQkHEcx8zNzVWWKZ3ttnyqW7cuc3BwYDt27Kh0POTdRo03QggzNzdnV69e1Vp9aWlpbM6cOczMzIzVqVNHrcbbf//9V+njLV++nNWvX5+1bduW7dq1q9L1lFd6Hk2bNmXGxsbM09NT7X9QT58+zaZOncr69u3L+vbty6ZNm8ZOnz4tWI7jOBYfH89SUlJYSkoKMzAwYPv375f9fOzYMcFGS/np+HV1dZmvr6/a0/T369ePjR8/XuX+cePGsX79+gmehyaNN02n+WeMMSsrK3b48GHZzz/88AMzMzNjWVlZjDHGZs2axRwdHVWWnzBhAsvJyZH9vGnTJrmfnz9/zvr27csbQ0VV5o/Isg0nZeVV/ZFYmoSupablGWNMJBLJ3Q/lG5lC94Om5WtTHWXdvn2beXl5MYlEwoYOHcrS0tLULqutOiiGks/x9u3bFTre2bNn2fLly1nfvn2ZkZER4ziOtWjRgvn4+LCIiAh2584d3vK7du1SmqKiotjEiROZnp5epZfkIO82GjZJCEF0dDQOHTqEiIiISr8j9OrVK8TGxiI8PBxJSUl48+YN1qxZA19fX8Hp7UUiEdq1ayc3vE2ZCxcuqCyvp6cHFxcXiMVileXVmTRFmeLiYuzfvx/h4eE4ePAgCgoKKlUPAFy9ehX9+/fH7du3le4vnRxC2a9mdSdVcHJyEoyD4zgcP35c6b5Tp07B0dER7u7uCAgIkM02efXqVaxatQq7d+9GfHw8unXrprJ+sViMjIwM2TtuRkZGuHTpkmwh+MePH6Np06ZqDWmqLAMDA/zzzz+yYw4aNAjNmjXD999/DwBITU2Fo6Mj/vvvP5XnUHY4r7Khn9o+h5MnT6Jz586yCYBWrlyJgIAAlflfvHgBV1dXJCUlqcxz4sQJtY6tankGTcsDisNoyw9TE7qWmpavTXUAwNOnT7Fw4UJs2LAB3bt3x7Jly9C5c2feMtqu432OofxyKllZWTA2NpabkAbgX05FJBLBzMwMjo6OcHJygqOjIywtLSsUO58ff/wRmzZtwpkzZ7RWJ3k30IQlhBDZ1O+NGjX6P/bOOyyK6+vj35mlS7ERsaMREMEaa/xpxA42VFRUNKhoxI6iokaNBRN7IbZI1SjBFnvsii2KFYxgw4ZlUSMIiKjAef9A9nWXnd2F2YWN3s/zzPMwc+ece2bZMmfuvecLW1vbAouihZImAIiJiUFwcDCioqJgb28PLy8vbNu2DVWqVEH79u010iUDgE6dOml8riKDBw/WSsUxIXieR7du3dC5c2dcvXpVlK/379/j4cOHgu3aKKogtsDEt99+i6ioKIwYMQI7duyQaytTpgwiIyNVJm5AXhGcdu3ayRLyt2/folu3bjAyMgKAYlkHYmJiIrcu7/z581i8eLFcu1DVT6BgKfKiPOssbOEWxTV4M2fORLly5TBkyJACvjMyMtCpU6cCJfsVUaeZpw6x9oz/Rx+05lgM8nIqRSUhIUG2FlkTIiMj0b17d42ldDp27KhWZ5XxZcKSNwaDAW9vb1y+fBleXl5KC5ao4ttvv8XYsWMRExNTqB8yRT4txV5YwsPDi9xvYYiPj0eLFi10OlqULwgtlvT0dJw/fx4fPnxA06ZNUb58+ULZ9+zZE506dcKhQ4fkpBs6duwIMzMztfazZ8+W21dWEVSVbt7ly5fh7++P3bt3F9APe/36Ndzd3bFixQrUr19f0Ef9+vWxadMm/Pzzzzh9+jSSk5PlqkMmJibqXET35s2bconqH3/8gYCAAFnyRkTIysoStN+0aRMGDRqEMmXKyGlTZWRkoGPHjnj16hVOnTqlMoanT59i2bJlmDVrltLXcv78+fD390eFChV0Ys/4f/RBa47FULBKsjqUJV6F/b374Ycf0KxZM42Lorx9+xYmJiaF6oPxZcCSNwaDgf379+PQoUMaVd5TpG3btggJCcHz588xaNAgdOrUqdCjYLocNfuvIXQjbmVlhVq1amn01DYuLg6urq549uwZgLzpftu3b0f79u0LFYuZmRl69uxZKJt8FJM3dZw9exaNGzeWTRdcunQp2rZtq1T42crKCh06dMDixYvx+++/C/qcOXMm3NzcsHXrVjx79gze3t6oWLGirP3PP/9UO4KobYSmwwrh4eGB1NRUDBgwAPv374eLiwsyMjLQuXNnvHz5EtHR0WqTpmXLliEtLU3wtUxPT8eyZcuwcOFCndjnExwcLBtdz87ORnh4uOyhQnp6ukpbbdjrg4/8KbqLFi3C4sWLi6Q1J9YHi6HwFDbxUkZhR+43bNigsqIm48uFJW8MBgNVq1ZVemOmCYcPH0ZSUhLCwsLg6+uLt2/fol+/fgA0T8rELr0dOnSo2nM4jkNISIiofoqDNm3aCLZJJBL4+vpi6dKlKvV+AgICUK1aNWzbtg0mJiaYM2cOxowZg5s3b2oUw8aNGzU6b/DgwRqdpwmurq5y68kuXLiAgIAAwfO7deuG4OBglT5dXFxw+fJlHDlyBDY2NujTp49ce4MGDdC0aVOVPmbNmiUbaXz//j0CAwNhZWUFADrVqPsUHx8fvHr1Cu7u7ti9ezdmzpwJqVSK6OhouWRUiIMHD2LdunWC7YMHD8bw4cMFky+x9gBQrVo1bNiwQbZvY2ODTZs2FThHV/b64kMftOZYDIVHF+UhJk6cqPT469evcenSJSQmJuL06dNa75fx34cVLGEwGNi/fz+CgoKwbt062NraivJ15MgRhIaGYteuXahatSo8PDzg4eGBRo0aCdo8fPgQ1apV0zjZUywcoWp0KCcnB0ePHsW7d+9EP4HVRFtMcSG8ItnZ2Xjz5o2gj9evXys9npqaipiYGEyePBkjRozA9OnTBfv46quvcODAATRu3BgA8O+//+Krr77C69evNVpXyPM8zM3NYWBgIHjTwnGcysX8hUWx8IOJiQkSEhJkxUYUuX//PurUqaNSa66wdOnSBcHBwbKEqE2bNhq9J1WtMdRm4ZZp06Zh0aJFsLW1RXR0NKpUqaLJZaFUqVJISEgQTCoePXoER0dHvHnzRif2DMZ/HW3owCn6ECosZWlpidq1a2PUqFFam0bP+LxgI28MBgNeXl7IzMzE119/DTMzswKjOqpu0ocOHYqVK1fCwsICANChQwd06NABKSkp+P333xEaGoqFCxeqvDkt7A+UYkLx559/Kj1v9+7dmD59OoyNjTFr1iy1fpWtl/iUW7duqfUhdiF8/qiOsuPVq1eHkZERpk+frjJ5e/nypdyNdrly5WBmZoYXL15olLw5OjoiOTkZXl5eGDp0qMp1J7rC2toat27dEkzebt68Weh1fOo4deqUXDJ48uRJ0T7FFm7p1auX3L6hoSHKly+PcePGyR1XVUnV1NQUDx48EEy+Hjx4oLLKrFh7xv+zaNEijB07VvZ6nTp1Cs2aNZNNF05PT8fUqVOxZs0anflgMegHYgtLMb5c2Mgbg8FARESEynZVi7sVy6kr48qVKypH3gqLuqegZ8+exdSpU3H16lWMGTMGAQEBKFOmjFq/2ijTr2sePHgAZ2dnlVUSJRIJbt++LVcUo2rVqjhz5ozcyKqqqbIXLlxAaGgooqKiUKtWLQwbNgwDBw4s8vRadSj+T4cMGYK7d+8qnTZERGjdujVq1aqFsLAwncWgCRcvXlRZlvynn37SaPROaI2gsiqTylD1OnTp0gWVKlWSm+73KT4+Pnj69CkOHDigE3tA/FRcbUzl1Qcf2pCfEOuDxVB4dDHypopP5Wl27dpV5D4Znyds5I3BYBS68tanaPL8R5uJmypu3LiBgIAAHDx4EIMHD8Yff/yh8dQyQHtrKLZt24Zdu3bhw4cPaN++PUaMGKEVv0Be5T91VTmJCPb29gWO5S9+1yQJbdasGZo1a4YVK1Zg27ZtCAsLg7+/P9zd3REaGip7uq0rfvzxR3zzzTdo1qwZJk2aBAcHB3AcJ9Oau337tlYTN1VkZGRAIpHIjS5du3YNM2fOxIEDB1S+jj/99JOovrVxjf7+/ujQoQOsrKwwefJkWYGT5ORkLFq0COHh4Th8+LDO7IG8iraaTMUVSnrE2uuLD23IT4j1wWIoGapXr65yrTIA3LlzB6GhoYiIiEBKSgo6depUTNEx/lNoT++bwWB8DmRmZtLr16/lNlVwHEfPnz8vpujyMDc3p8TERNn+o0ePyNvbmwwMDMjd3Z3i4+OLNZ5PWb9+PXEcR/b29lSvXj3ieZ4CAgK04js5OZlcXFxo2LBhKs87efKkRlthiI6OpjZt2hDP8/Tq1Ssxl6EUCwsLuf8pEdHFixfJycmJOI4jnueJ53niOI6cnJwoJiZG6zEovq+SkpLo22+/JZ7nydDQkPz8/OjNmzc0aNAgMjAwoN69e9O5c+dU+qxfvz4FBQXp5DXLZ9u2bWrPWbduHRkbGxPP81S6dGkqU6YM8TxPxsbGtGbNGp3b16lTh8qVK0fjx4+n2NhYja5Lm/b64oPjOEpOTpbtK77npFIp8TyvUx8shsLj5OREjx490oovRTIzMyk8PJxatWpFhoaGxPM8rVy5ktLT03XSH+O/D0veGAwGZWRk0OjRo8na2lp2k/zppgqO42Q3c6o2baJ4o29qakpmZmY0depU2r17t+CmjoULF1JmZqZsPzo6mrKysmT7aWlp5Ovrq9KHs7Mz/fjjj7L9sLAwMjc31/jaGjRoQA0bNiyw1axZk4yMjKh+/fpyNyza4Oeff6aUlJQCxx8/fkyBgYFUq1YtqlixIk2ePJkSEhK02nc+ijden3L16lXaunUrRUVF0dWrV3XSv7IYBg4cSPXq1aOgoCBZ4tqoUSMaMmQI3bt3TyOfI0aMICsrKzIxMSFPT086evRooeP68OED/fPPP3Tr1i2547t27aJ69eqRkZGRRn4eP35My5Yto1GjRpGvry8tX76ckpKSNI5DrP358+dlr8c333xDa9asUftwSJv2+uBDH5IWFoN2+PSh0qdb6dKlqVmzZrRjxw6V9hcuXKDhw4eTpaUlNW7cmFasWEFSqZQMDAzoxo0bOoub8d+HrXljMBgYPXo0Tpw4gblz52Lw4MFYvXo1njx5gvXr1+OXX37BwIEDBW15nseKFSsEC23kI2ZqpiKKawd4nldro8laNW2soShVqhSuX78us8nJyYGpqSkePXoEGxsbtXHOmTNH6fH8CmQdO3aERCJR66cwKF7n1q1bERYWhujoaHTq1AlDhgxBly5dtN6vNlG8hqKg+L6qXLkytm7dipYtW0IqlaJSpUpYsGCBSgkDZWRlZcmmnkZHR6Nq1aoYOnQovL291Zamj4+PR9euXfHw4UMAeWLna9euRd++fREbGwsfHx+MHz8eVatWLdpFK0Gx6qa27d++fSt7PWJiYgo9FVesfUn64Hke8+fPlxUOmjp1KiZPniynEzdr1iyV3zFifbAY/n99syKWlpZwcHDAlClTChQLUmT37t1Kj+dXBg4LC0NEREQBiZJ8DAwMMHbsWIwcOVJO8NvQ0BCxsbGoU6eOyv4ZXy4seWMwGKhWrRo2btyINm3awNLSEleuXEGtWrWwadMmREZGqixEwPM8pFKp2nVY2uTMmTNo0qSJ1tddKV6L4s28JsmbstdDG4vddYmyZLhatWoYOHCgSgFoxYqHn5KYmIjAwECEhoYCyHuPfVpkRSKR4MyZM3I3Ldq8hqLw888/w9fXF6VLl5bF+OTJE1nSXapUKVy6dAmOjo5F7uP+/fsIDQ3Fxo0b8eTJE7Rr1w7Dhg1D3759lZ7fvXt3vHnzBn5+fti8ebOsgIyXlxf8/PxkVV61idjXUlP7U6dOYfbs2Th16hRevnypUVEhbdqXhA9bW1uNCtioWn8r1geLQXzipQmrV6/Gxo0bceHCBaXtHTt2xPnz59GtWzcMGjQInTp1AsdxLHljqKdkB/4YDIY+UKpUKXrw4AEREVWuXJkuXLhARET37t2jUqVKqbTleV70ND5HR0f6999/ZfvDhw+XW0eXnJxMpqamRfafnZ1Nf/75p9rztDWVJzAwkFauXCnbTExMaObMmXLHVLF161YaMGAA9enTh9avX682brEoXmf16tXJ1tZW5VajRg2VPsePH0/Tpk2T62PRokUUHh5O4eHh5OrqSj/88IPOroGI6M6dO3Tp0iW5Y0ePHqU2bdpQkyZNKDAwUKVPnufl3ofm5uYaT5dUR25uLm3bto3Kli2r8j1VoUIFunz5MhERpaSkEMdx9Ntvv2klBiFUTWEVay92Kq42pvLqiw+G/vLrr79S06ZNRfm4ffs2lS5dWuU5jx49ojlz5pCtrS1VqFCBxo0bRwYGBiW6bpuh/7DkjcFgUN26dWUFLDp06ECTJk0iIqKVK1dS5cqVVdoqJjxFQdGH4po2qVRKHMcV2m9CQgJNnjyZvvrqKzI0NCx0HEVJ3sQmProseCKE2Jt1ZTg5OdHx48cF+zh58iTVqlVLa/0puwZ3d3e59Yf37t0jU1NT6tixI40bN47Mzc1p+fLlgj45jqO6devK1h1KJBJycnIqsB6xsBw/fpwGDRpEpUqVIisrK5VJLMdxJJVKZfulSpUqsPZN2+gieYuKiqLOnTuTqakpubu70+7duyk7O1tjn2Lt9ckHQ//RJPFSR2xsLNnY2Gh8/uHDh8nT05NMTEzIzs6Opk2bJntww2B8Cps2yWAwsHz5ckgkEowbNw4nTpxAly5dkJOTg+zsbCxbtgzjx4/Xaf/amK6Yz5s3bxAVFYWQkBCcP38eLi4u8PT0hLu7u1pRZ22swxBL3bp14e7ujnnz5gEAwsPDMXbsWKSnp+usT7HT5OrWrYsDBw7IrbuysLDA9evXZbpyfn5++PHHH1GuXDkAwMOHD1G7dm05UWwxKLuGqlWrYuvWrWjRogUAYP78+di+fTuuXbsGAAgJCUFQUJBsXxGh9YeKCGm0fcqjR48QHh6O8PBwPHjwAK1atcKwYcPQp08flQLXEokEUqlUptlnaWmJ2NhYQfFybaCLaZNip+JqYyqvPvjQB605FoN64uLi0KlTJzx79qzQtvmMHTsWiYmJKpcdKCMlJQW///47QkNDERcXV6K6ogz9hCVvDAajAI8ePcKlS5fw9ddfo379+jrvTxvJ299//43g4GBs3boVdnZ2GDhwIKZOnYq4uDiN1w5oYx2GWMQWPCkKurhZt7KywpEjR9C0aVOlNjExMWjfvj3S0tKK1KciygqWmJqa4vbt27Kksl27dvj2229liXFiYiK++eYbpKamaiWGs2fPonHjxnJrMbds2YKwsDCcOHECFSpUwODBgzFs2DDUqlVLI588z8PKykr2vkxNTYWlpWWBIj2vXr3SyjUAunk/aPLZ4jgO9+7dU9om1l5ffPA8r5FOnKr/p1gfLAb1aJJ4TZw4Uenx169f49KlS0hMTMTp06dl+ppF4cqVK8Wmk8r478BEuhkMRgGqVaumtgqeNuE4rsANkSZJVD516tRBZmYmBgwYgAsXLsiStcJWBXzw4EGhzleG2KfBb9++lY38AXkjL8bGxsjMzBQdmxCtWrVSOfpTFJycnHD06FHB5O3QoUNwdnbWWn/Kbt7Kli2LZ8+eoWrVqsjNzcWlS5fg5+cna3///r1WhX1dXV0LJJDe3t7o0qULdu3aBTc3N40qo35KcQmR6xqxny1tfDb1wYejoyOSk5Ph5eWFoUOHol69esXug8WgeeKliqtXryo9bmlpic6dO2PUqFGoXr26oP2iRYswduxY2XfvqVOn0KxZM9nDn/T0dAQHB2PNmjWaXBLjC4IlbwwGAwBw7NgxHDt2DM+fP0dubq5cW37FQF1BRGjXrh0MDPK+kt6+fYtu3brByMgIAJCdna3S/u7du/D09ISLi4uoSoCa8OTJE1SuXFmw3dvbW6Onwaqm8gQHB8slcNnZ2QgPD5eb9qlqaldubi6WLl2KXbt24cOHD2jfvj1mzZoFExMTpecXdlqPJgwZMgQTJkxA/fr10aVLF7m2vXv34pdffsGKFSu01t9ff/1V4P/y3XffYd68eVizZg22bduG3NxcuLi4yNrj4+Nl0zq1gbL/9+PHj0VVYtWmxIYQycnJWL9+PWbNmgUAmD59OsqWLVts9l8SN27cwIULFxAaGorWrVujVq1aGDZsGAYOHAhLS8ti8cFiEJ94AcCJEyc0ilOIadOmwdvbW5a8de3aVe7hT2ZmJtavX8+SN0YB2LRJBoOBOXPmYO7cuWjcuDEqVqxYYNTrzz//1Hn/miC0tujJkycIDw9HWFgY3r59i/79+2PgwIFo1qwZrl27ppWSy1KpFIGBgQgODla5TsvJyUnUE2VtTO36+eef8eOPP6Jdu3YwNTXFoUOHMHjwYPz222+FikVThKbZ9e/fH1FRUahduzYcHBzAcRxu3ryJW7duoXfv3ti6daugz9TUVERGRsLX1xcAMHDgQLnXXSKRYMOGDbKy/sq4f/8+OnTogPv374PneaxatUrmDwDc3d1Ro0YNLF++vIhXLo+y12HPnj0a2Xbv3l1l+9u3b3HkyBHcvn0bHMfB3t4e7du318qIaWxsLBo1alTktTWa2M+dO1fpcSsrKzg4OKBjx44qRyXF2uuTj3z0Qa+OxaAbcnNzsX//foSEhGDXrl1Kz9HmWm/GF0axl0hhMBh6h42NDW3cuLGkw9AKx44do4EDB5KpqSlxHEeTJ0/WuDpfSkoKDRgwgMqXL08VK1aklStXUk5ODs2cOZNMTU2pcePGtGXLFrV+zp8/TyNGjCArKyv65ptvaM2aNfT69Wuxl6Yx9vb2tHr1atn+X3/9RcbGxpSbm6uT/lRVJ4yMjKQePXqQo6MjOTo6Uvfu3SkyMlKtz0WLFtHAgQPl+ujduzd5e3uTt7c3OTg40OzZs9X6ef/+PV27do2ePHlSoO3atWv08uVLtT40RdnrwHGc2k1dBdPdu3eTtbV1ATtra2vas2eP6LivXbumNgax9g0aNFC62drakqGhITVo0EBl1Vqx9vrkQ5Ho6Ghq06YN8TxPr169KpSttnywGP6fnJwc2rNnD/Xo0aPQtrdv36aAgACqWLEimZiYqPShjerGjC8TlrwxGAwqW7Ys3b17t6TD0Cqpqam0evVq+uabb2Ql39Xh6+tLVapUoUmTJpGTkxPxPE+urq7k4uIik1IoDJmZmRQREUFt2rQhMzMzGjBgAGVlZRXlcgRxdnamR48eyR0zNjamhw8fyvZzc3PJyMiIHj9+rNW+8ylKaXl12ntNmzal/fv3C/axc+dOatCgQaFjJSL68OEDpaenF8lWFbqQXDh79iwZGhpS79696dy5c5SSkkIpKSl09uxZ6tWrFxkZGdG5c+dE9VEcyZsqnj59Sm3atKFhw4aViH1J+NAHrTkWgzyFSbw+JTMzk8LDw6lVq1ZkaGhIPM/TypUr1X7HsOSNUVRY8sZgMGjKlCk0d+7cEuvfxcVFo62oXL16lcaOHSvbP3PmjNIkqlq1anTkyBEiIkpMTCSO42j8+PFF7jcfbTwNFkJotOdTcWmh84RwcXGhlJQUjWPYvHkzZWRkaHSuptp75cqVkxsx/eabbygpKUm2n5iYqFZAfv/+/QVGlOfPn0/GxsYkkUioQ4cOWv1/KOoTaoJUKqU5c+YItru6utKIESME20eMGEGurq6F6lORkk7eiPI+k+qE33VpX1w+9EFrjsXw/xQ18SIiunDhAg0fPpwsLS2pcePGtGLFCpJKpWRgYEA3btxQa89xHAUGBtLKlStp5cqVZGJiQjNnzpTtz58/nyVvDKWwNW8MBgPjx4/Hxo0bUa9ePdSrVw+GhoZy7cuWLdNp/zzPo3r16ujSpUuBvj9FW2uTlJWVBwBDQ0M8fPgQlSpVAgCYmZkhJiamSFURnzx5goiICISFheHNmzeyNXC1a9fWyjXkI6SpNWLECJiZmcmOrV69Gl5eXrCyspIdE/q/Kq7FEEtRtPfUvfbXr19Hs2bNVFbhbNu2LXr37o3Ro0cDAM6dO4dWrVph7ty5cHR0xIwZM+Dq6irq/Z2WliYrjlCUEvvq1ouVKVMGp06dQt26dZW2x8XF4bvvvkNKSopgH0KV9fJ58eIFtmzZIhiDWHtNePDgAZydnZGRkVEi9sXlQx+05lgMeVIlwcHBiIqKgr29Pby8vODp6YkqVaogNjZWo3XSBgYGGDt2LEaOHAkHBwfZcUNDQ4186IM0DeO/Cas2yWAwEBcXhwYNGgAA/vnnH7m2wpTsLyq//PILwsPDsW3bNgwcOBBDhw7Vahl5RYSeWeXm5soljxKJBKVKlSqU761btyIsLAzR0dHo1KkTli5dii5dukAikYiKuTC0bt0at27dkjv27bffyhU5KY7/qzLtvQsXLmDVqlVqb2xq1qyJK1euCL4PLl26pFao+p9//sHSpUtl+9u3b0eHDh0wY8YMAICJiQnGjx8vmLwtWbIE/v7+gv7T0tLQsWNHnD9/HgB0IqSelZWlsnKelZUV3r17p9KHUGW9T2ndurXO7DUhNjZWVOVPsfbF5aNatWrgOA5btmwRPIfjOJVJi1gfLIa878OxY8ciJiZGLvEqDG3btkVISAieP3+OQYMGoVOnToX6XtWGdAXjy4QlbwwGQ3TJY7FMmTIFU6ZMwd9//43Q0FC0bNkSDg4OGDp0KAYMGKBx6WixEBG8vb1lFcqysrIwcuTIAgnczp07BX14enqiWrVq8PPzQ4UKFfDgwQOsXr26wHmqbkrEcvLkSdE+0tPTBaUF8lH1fxGrvdezZ0/8+OOP6NixYwFx8mfPnmH27Nkq5Rbyr6FcuXKy/TNnzsDDw0O27+TkhKdPnwraz5w5E+XKlcOQIUMKtGVkZKBTp05aExkXwt7eHsePH1caA5An8aFO8Fvs51sb3w9Cr9Pr169x8eJFTJo0CT4+Pjqz1xcf+qA1x2IQn3gBwOHDh5GUlISwsDD4+vri7du36NevHwDtPRxTJ03D+EIp2VmbDAaDUZA3b95QeHg4NWnShEqVKqX1So1C67/yKxmq21RRvXp1srW1VbmJXVejybWIIb8CotCmSYVEQ0NDGjRoEB0+fFiuyqWm60HS0tLI0dGRLCwsaNSoUbRixQpauXIl+fr6koWFBdWuXZvS0tJU+qhZsyYdPHiQiIjS09PJyMiIzpw5I2u/fPkylS9fXtB+27ZtZGJiUqCwSnp6OrVo0YLs7e1JKpWqvRZVqFsvtmzZMipbtqxc8ZZ89u3bR+XKlaNly5aJiiEuLk7U2k5N7FW9pyQSCY0aNYrev3+vM3t98sHQDx49ekRz5swhW1tbqlChAo0bN44MDAwoPj6+SP4OHz5Mnp6eZGJiQnZ2djRt2jS6fPlykXw9e/aMxowZQyYmJkWyZ3zesJE3BoOBN2/e4JdffhEU6ValKaYLrly5gujoaCQkJMDZ2VnlOjhtEhYWVqjzHz9+jEqVKsnpOunDVBghLSpF8kWVlbF9+3ZRQsv3799HeHi47Il0vvaepk+kLSwscPbsWUybNg2RkZFITU0FAJQuXRoDBgzAggULYGFhodKHh4cHJkyYgOnTp+PAgQOwsbFB8+bNZe2XLl1SOWXKw8MDqampGDBgAPbv3w8XFxdkZGSgc+fOePnyJaKjo1WutQE0Wy+mivHjx+PcuXPo2rUrHBwcZCL08fHxuHPnDtzd3TF+/HiVPpSRlpaGyMhIhISE4NKlS4XWIyysvdDonaWlJezs7ORE6XVhry8+9EFrjsWQR9WqVTFr1izMmjULR44cQWhoKAwMDNCjRw94eHjAw8MDjRo1UhnDp3To0AEdOnRASkoKfv/9d4SGhmLhwoWCa0FTU1MxevRoHD58GIaGhggICMCYMWPw008/YcmSJXByckJoaKjG/TO+HFjBEgaDgf79+yM6OhqDBg1SKtJdlJvDwvL06VOEh4cjPDwcaWlpsgIf2hDYVkSoYElJ+RHDli1b0KNHD7mpnTzPo1KlSvjqq68E1/dxHIcrV64obdN2wZLjx48jNDQUO3fuRFZWFvz9/eHj4wN7e3uN7IlIluRYW1trnABmZmbihx9+wL59+2BjY4PffvsNrVq1krW7uLigc+fOmDp1qko/ixYtQmBgIHbv3o2ZM2fi2bNniI6O1mg6k4uLi0axqpuaGBUVhcjISNy+fRtA3nRKT09PeHp6auQ/n+joaISEhGDHjh3IysrC5MmT4ePjo3bqpbbsv3QaNmyo9HhqaiqePHkCJycnHDp0SOVnT6wPFoMwnyZecXFxogWyr1y5IpgAjho1Cnv37kW/fv1w8OBBJCQkoFOnTsjKysLs2bPx3Xffieqb8RlTsgN/DAZDH7CyspKbTlbcuLq6komJCXXv3p127dpFHz58KJT9w4cPCyVAra2phsr8uLq6Umpqqmx//vz5cmX3X758SY6Ojir95uTkUEhICHXp0oWcnJzI2dmZunXrRhERERpdZ/7r2aNHjyKVz1bUH9IWRdHe0xcCAgKI53mqWbOmnGTBf4GnT59SYGAgff3112RjY0N+fn508eJFjaewirUnytPQ8vT0VDoFOjU1lfr376/yMynWXp98CKEPenUshv9H3ZTHhQsXUmZmpmw/OjpaToImLS2NfH19Be11JU3D+PxhI28MBgM1atTAgQMHZFOyihue51GxYkV89dVXKkdVhEaKJBIJnj17prWRIk1RVhpeMRbF0bnk5GRUqlRJ8IkuEaFbt244cOAA6tevj9q1a4OIkJCQgOvXr6N79+7YtWuX2tiePXsmN5I5ePBgDB06VKPKajVq1MClS5fkin1om2vXriE0NBSrVq1S2u7i4qJ2hI3jOBw7dkyw/fnz5yrfEzk5Obh8+TKaNm2qtL1Xr15y+/n/E8URN1UFbAqL4vvlf//7H9q2bQsXFxe0aNFCbREZZZiYmKBPnz7w8vJChw4dZFPJNC1pLtYeAEaMGIHSpUtj0aJFStunTp2KtLQ0rF27Vif2+uRDFWfPnsWgQYNETVUX6+NLiGHRokUYO3YsTE1NAQCnTp1Cs2bNZMWq0tPTMXXqVKxZs0bQv9jvem1K0zC+LNiaNwaDgXnz5mHWrFmIiIiQ0wYrLmbPni3KXp+eQSnGUtjYwsPDcerUKRw7dqzAlLvjx4/D3d0dGzduVFtpsWLFipg2bRqmTZuGU6dOISwsDE2aNEHdunVx9OhR2U2LMopDV6hcuXIq9bTypSuUkb/eSl2J/IoVK8rdXDk6OuLQoUOoVq0aAODly5do0aKF4M3Vp5p4QN70Yl2j+H5xcHDAli1bMH/+fBgbG6NZs2ayZK558+YarQetXr06zpw5g2rVqqF69eqF1hoUaw/k3Rxv2rRJsL1v374YMGCAzuz1yYcqKleujOfPnxfZXhs+voQYpk2bBm9vb9n3YNeuXeUSr8zMTKxfv15l8ib2u14b0jSMLxOWvDEYDCxduhSJiYmoUKECbG1tC9wQCo14aQuxydvnRGRkJKZPn650rVTbtm0REBCAzZs3q03ePqVJkyZ48OAB4uPjcfXqVXz48EFl8ta2bVu1PtWNeqnj1atXiIiIEFyQr0yQPTs7G6tXr0ZgYCAqV66MefPmqexD8Wbq8ePHyM7OVnnOpxS2gI0uCAkJAZAX+/HjxxEdHY2IiAj89NNPMDU1xbfffou2bdti2rRpgj5u3bqFs2fPIiQkBE2aNJGJEgOalTQXaw8ADx8+VDkKWr58eSQlJenMXp98qEIf9Oq+hBjEJl7agLQgTcP4MmHJG4PBgLu7e0mHICMuLg63b98Gx3Gws7PTuApecHCw2kpv2tZWU3bjynFcgeOF0fyJi4sTnJIFAK6uroJTDRXJ183bunUr7O3tMWTIEI108+rXry/Ypumol7bZvHkzZs2ahbdv3+Knn37CiBEjYGAg/idMrB7T9u3b5bTjdEWVKlUwePBgWdKelJSE9evXIygoCMePH1eZvAFAy5Yt0bJlS6xatQqRkZEIDQ1FTk4ORo0ahQEDBsDd3R3W1tY6s7eyskJiYiKqV6+utP3u3btqxcjF2OuLD33QmmMx6Afff/+93H7+AxEGQy0lsM6OwWAwCnDhwgVydnaW6Yjl6ynVrVuXYmJiVNpyHEdVq1YtNm21fJQVLOE4jtzc3Khnz57Us2dPMjAwoI4dO8r23dzcVOp6GRoa0tOnTwXbnzx5QkZGRirjWrhwIdWuXZusra1pwoQJFBcXV7gLU8KHDx9oxYoVZG1tTbVq1aLIyEhR/tTpm+Xz119/Uf369cnS0pLmzp1LGRkZGvehWHhF8f8llUrVxvDhwwf6559/6NatW3LHd+3aRfXq1VP7vygsqorp3L17l4KDg8nLy4uqVKlC5ubm1KFDB5o/f36R+oqPj6dJkybRV199RQYGBjq179OnD7m7uwu2d+/enTw8PHRmry8+9EFrjsWgne8GjuMoMDCQVq5cSStXriQTExOaOXOmbH/+/PkafccxGIWFFSxhMBglTnx8PJo1awZHR0f4+fnB0dFRVqRj+fLluHXrFs6fPy9YGEHbpe01JSkpCZUqVYJEIpEdGzJkiEa2QlPyJBIJpFKp4CiGukXwQN7rUa1aNXTt2hVGRkaC5y1btkyjWD8d9frxxx+1MuoVGxuLRo0aCV5HTEwMpk6divPnz2PkyJGYMWMGypcvX6g+JBIJbt++DWtraxARqlatijNnzsimUiUnJ6N27dqCMcTHx6Nr1654+PAhAKBHjx5Yu3Yt+vbti9jYWPj4+GD8+PGoWrVqoeJShWLRg7CwMJw4cQInT57E69ev0bJlS3z33Xf47rvv0LhxY62MPn748AF79+4tUKBFm/ZXr15FixYt0LVrV0yZMkVWOOfmzZtYtGgR9u/fj3PnzgmWVRdrry8+oqOjlR4vjNacWB8shrzvyPnz58vOmTp1KiZPniz7jklPT8esWbNUfs/a2tpqNHJfHGuIGV8WLHljML5geJ5X+uNjaWkJBwcHTJkypcg3dIWhT58+yMnJwY4dOwrEQ0To1asXDA0NsXXrVqX22qo2OXToULXncBwnW4ekDRSFvnmeh6urq2wdhCLv3r3DwYMHVd5UtGnTRqNKjcePH1d5zsGDBxEQEID79+/D398fEydO1HhBvbr3TWpqKqKjowWvg+d5mJqa4ocfflC59kXVVFjF9zcRKd0XiqF79+548+YN/Pz8sHnzZkRFRaFWrVrw8vKCn5+fWpHwoqBYwTQ/EZ82bRqGDh1aJMF6oellighN9xNrn8++ffswdOhQ/Pvvv3LHy5Urh+DgYHTv3l2n9vrkg1Gy6EPiJVRRN19kfPTo0Vp9MMT4fGDJG4PxBbN7926lx1NTUxETE4OwsDBERESgT58+Oo3D2toaf/31Fxo3bqy0/eLFi3Bzc5MJNSuirZG3nj17Crbl5OTg6NGjePfunWjh1k9RHGkRO3KnDbQx6iX2OjS5ueI4TmUpcaEn84oIieHa2NjgwIEDaNSoEVJTU1G2bFmsX78ew4cP18gvANSsWRMXL17UWHbhzJkzaNKkiSx5X7t2LaKjoxEdHY2srCz873//Q5s2bfDdd9/hm2++0egGVOghTT7qklix9p/y9u1bHDx4EHfv3gURwd7eHh07dtS4yq1Y+5L2cefOHcyaNQvr168vkOy+fv0avr6+mD9/vpz8iLZ9sBiKjydPnhSQFsnHz89P6fHU1FRcvnwZ9+7dw5kzZ1RW3mV8mbDkjcFgCLJ69Wps3LgRFy5c0Gk/JiYmuHPnjuBTxqSkJNjZ2SErK0tp+5w5czB58mSdyRzs3r0b06dPx9OnTzF16lQEBARozbcyrbiSRhujXvfu3YOtra1sRPG/CM/zePbsGSpUqAAAMDc3x5UrV2Bvb18oH9qa0hsfH4/o6GicPHlSlsy1bNkSLi4u8Pf3F7QTm8SKtWf8P/qgNcdi0AxViZc6pFIpAgMDERwcjLdv3xbJx+jRo3H//n0cOHCgSPaMz5hiXmPHYDD+Q9y+fZtKly6t834cHBxo+/btgu3btm0je3t7wfaHDx9qtBWWM2fOUMuWLcnMzIymTJlCr169KrQPdagqUFFUHB0d6d9//5XtDx8+nJ4/fy7bT05OJlNTU0H76tWrqyz+okkBGJ7n5QoC9O3bl6RSqYirKjxPnjyhSZMm0evXrwu0paamkr+/v8qYeJ6Xe90sLCzo3r17hYpBsTCCtnjy5AnNmDGDLC0t/zNFET58+ECLFi2ihg0bUqlSpcjc3JwaNmxIixcvVlucQhv2+uDDwcFBZQGmS5cuqfyu04YPFoNqnj17RmPGjCETExOV56WkpNCAAQOofPnyVLFiRVq5ciXl5OTQzJkzydTUlBo3bkxbtmwpdP/5xMbGko2NTZHtGZ8vTCqAwWAI8vbtW5iYmOi8n379+mHixIlwcHCAs7OzXNv169fh7+9foKzyp9SoUUP2N32cTFCYtU2K3LhxAwEBATh48CAGDx6MP/74A1WqVCnMJRUZTdcYqtL+uXnzppye2R9//IGAgABZERQiEhzFBIAHDx5oFqwKSGFSx4EDB/Dzzz9rbK+pHIKq0b9ly5YhLS1N6VosKysrpKenY9myZVi4cKFSe/o4HS7/vZSRkYGGDRsWGE189eqVyhjj4+MhlUpVnqNOEiM5ORknT56Ubbdv34aRkRGaNWumVBPwU54+fYply5Zh1qxZSqeXzZ8/H/7+/rIRRm3bA3nfJR06dMDff/+N9u3bo3Xr1iAi3Lx5E1OnTsWePXtw+PBhwe8bsfb64kMftOZYDHlTE0ePHo3Dhw/D0NAQAQEBGDNmDH766ScsWbIETk5OghqU+UyfPh2nTp3C999/j4MHD8LPzw8HDx5EVlYW/vrrL9Ej0aampiq/pxlfLix5YzAYgmzYsAENGzbUeT/Tpk3D0aNH0aBBA3To0AGOjo4A8m56jx49iqZNm6rUseI4DlWqVIG3tze6detW5Ap8SUlJmDVrFn7//Xd07doVcXFxsliKCysrK637VEykAPH6ZrpGmUi3IhzHqUzeDh48iHXr1gm2Dx48GMOHDxdM3rS1rrBdu3aC/wN1DxZGjx6NEydO4NatWzAwMECTJk3g4eEBFxcXfPvttxo9XBGbxIq1B4Cff/4ZSUlJuHr1aoFENTY2Ft27d8cvv/yCn376SSf2+uJDH7TmWAzaSbz279+PsLAwtG/fHqNGjUKtWrVgb2+PFStWqLXVhMOHDxdqijbjy4GteWMwvmAmTpyo9Pjr169x6dIlJCYm4vTp08WSwL1//x7Lly9HZGQkbt++DQCwt7eHp6cn/Pz8BKsvAnnrCyIiIhAeHo6UlBR4eXlh2LBhhU68zMzMwHEcxo4di2+//VbwPG1Wk1MsWFJYFKtVAgXXWSmuq9NEbiA7O1vu/5Evmj5gwACMHz9ebdVDRckDCwsLxMXFyY2S6ppSpUohISEB1apVU9r+6NEjODo64s2bNzqLged5xMTEqBSwBiB4A9qiRQu4uLjAxcUFLVu2LNK6TmdnZ6xbtw7/+9//lLafO3cOw4cPx40bN3RiD+R9ln/++Wf07t1bafu2bdswY8YM2Wdf2/b64qNv37748OED/vzzT6XtPXr0gJGREbZt2yYYg1gfLIa8z1tISAjat2+Pe/fuoVatWhg3blyhEi9DQ0M8fPgQlSpVApD3+xETE1Ng9ogQe/bsUXo8X2Q8JCQE4eHhOi8YxvgPUhJzNRkMhn7Qpk0bpVv37t1pypQp9ODBg5IOsdCcPn2ahg4dShYWFtSsWTP67bffKCcnRyPbfHFwVZu21xeJXfNmYWFRwF5xrZa5ubncWi11ArSZmZnUsmVL4nmeOnbsSOPHj6dx48ZRx44died5atWqFb19+1ZlXOrEyvM3IVxcXCglJUXN1aumXLlyFB0dLdgeHR1N5cqVU+snMzOTdu/eTYsXL6YlS5bQnj17KDMzU6MYdLXmTQg3N7cCIu9mZmYq13w+fPiQzMzMBNvF2hMRGRsb06NHjwTbHz16RMbGxjqz1xcfV65cIWNjY+rduzdduHCBUlNTKTU1lc6fP0+9evUiY2Njunz5ssoYxPpgMRAZGBjQkydPZPumpqZ0/fp1lf0pou57Vh1CvzGWlpbUtGlT2rp1a6HiYXw5sOSNwWCUOK9evaJVq1YJFpYQalOFVColFxcX4nlernhHSfHgwQO6ceNGgUTy0aNHlJ2dXWS/ypI/juOobt261LBhQ2rYsCFJJBJycnKS7detW1dl8jZz5kyqVq0axcbGFmi7du0aVatWjWbPnq0yLm9vb402IbSR9Li5uZGPj49g+7Bhw8jV1VWlj927d5O1tXWBGyxra2vas2eP2hiKO3lT9n4Qm8RqIwm2tramS5cuCbbHxMSQtbW1zuz1ycfevXvJ2tqaeJ6X26ytrWn37t0qbbXl40uPQWziRST+ARWDUVTYtEkGg1HizJs3D3FxcSqn2NSvXx8zZsxQ6+vcuXMIDQ3Ftm3b4ODggKFDh2LEiBHFVrI+IiICKSkpmDBhguzYiBEjZMLeDg4OOHTokNbEV5VJDcyZM0cj29mzZys9ro3pZWLRRon9EydOoEOHDpgwYQImT54sK6iRnJyMRYsWYeXKlTh8+DDatm2r1P7cuXNo06YNunfvjkmTJsmtxVy6dCn27duHkydPokWLFoIxuLi44M8//0Tp0qWLfB2FQdn7oUuXLqhUqRI2bNig1MbHxwdPnz4VLEku1h7IK0qUnZ2NHTt2KG3v3bs3JBIJtm7dqhN7ffIB6Ide3ZccA8/zcHV1lU3H37t3L9q2bYtSpUrJnaeqMJQ+aHIyvlBKLm9kMBiMPOrXr09Hjx4VbD969Cg1aNBAsP3p06f0yy+/kIODA3311Vfk5+dH//zzT5Hj2bp1K/Xs2ZOcnJzI2dmZevbsSdu2bdPItnnz5hQaGirb/+uvv8jAwIB+//13unz5MrVo0YKGDRtW5NgU0YbUwJkzZygrK0u2r43pZWLhOI7u3r1Lr1+/VrmpY926dWRsbEw8z1Pp0qWpTJkyxPM8GRsb05o1a1Taurq60ogRIwTbR4wYoXbkLh/FqZe7d+/WeOplYVD2fjh+/DhJJBKaNGmSnDSCVCqliRMnkkQioWPHjgn6FGtPRHTjxg0yNzenZs2aUVRUFMXGxlJsbCxFRkZS06ZNydzcXOVnVqy9PvlglDxiZwZoi7S0NLp06RKlp6cTEdHly5dp0KBB5OHhQb///rvO+2f8N2HJG4PBKHHMzc3VrqmxsLAQbDc0NKTq1avTrFmz6NKlS7IbKsVNHTk5OdS3b1/iOI4cHByoR48e1L17d7K3tyee56lfv36Um5ur0kfZsmUpLi5Otj9y5Ejq1auXbP/EiRNka2urNhZN0UbyprhuThtTw8SSv75QaCvM+sPHjx/TsmXLaNSoUeTr60vLly+npKQktXalS5eW+18qEhsbq5EOotipl4VB6P0gJonVhj0R0d9//0116tSR+99yHEeOjo509uxZndvri4+S1ppjMegH0dHRZGFhQRzHUdmyZenQoUNkYWFBtWvXJicnJ+J5nn777beSDpOhh7BpkwwGo8QpXbo0Dh48iObNmyttP3/+PDp37ozU1FSl7Z9Oicwvga/41aaJztuyZcsQGBiIiIgIdO3aVa5tz549GDJkCGbOnCk3JVIRMzMzJCQkyKoH1q9fH0OHDsX48eMB5FU4dHBwwNu3b1XGoiliq1UCBafaaWtqmBh4nseOHTtQtmxZleeJ1VJShampKW7evClYCfLhw4dwdHREZmamoA9tTL0sDMqmTebz5MkTbN26VW56mYeHh8YahmLt87l69Sru3LkDIG+KboMGDYrVviR9KOrEOTo6ynTijh49ipYtWxZaa66wPlgM2sHFxUWp5IqVlRUcHBwwevRoldPjW7duDTs7O8yZMwdhYWFYtmwZfH19sWDBAgDA/PnzsX37dly7dk0n8TP+w5RQ0shgMBgy2rRpQ1OnThVsnzJlCrVp00aw/cGDB2q3q1evqo2jbt26FBISItgeHBxMzs7OKn3Url2bduzYQUREL168IIlEIjeKdeHCBapQoYLaWDRFGyNvij70YWqYNgt9FHUabL169eSmwCoSEhJCdevWVelDm1MvNUEb7weG7tBGMSCxPlgMeb85Li4uBTZ3d3eaOnWqymnj+UyYMEHp5u3tTXXr1qVSpUqp/N2xsrKihIQEIiJ69+4d8TxP165dk7XfuXOHzM3N1cbB+PJgyRuDwShxtm/fTgYGBhQUFCRXeTE7O5tWrVpFhoaGGq85+5TU1FRavXo1NWrUSKMpdiYmJiqnbz548IBMTExU+liwYAHZ2NjQ3LlzqU2bNuTk5CTXvnz5cmrXrp1mF6DQty6qVRIpv+HXxvQyMWiSvH348EFlu9hpsMuWLaOyZcvS/v37C7Tt27ePypUrR8uWLVMZg9ipl0OGDKG0tDSVfXzKggULBCUWxKzl1IZ9RkYGzZw5k5ycnGRT3OrWrUtz5syhN2/e6NxeH3zY2dnR9u3bBdu3bt1KdnZ2OvXBYhCfeGnCqFGjVD6YUfyOU/weVifpwvhyYckbg8HQC6ZPny7TuGnQoAE1bNiQLC0tied5laNyyjh27BgNHDiQTE1NqXbt2jRjxgy6cuWKWrsyZcqoXBsXFxdHZcqUUekjJyeHfvzxR2rQoAF17tyZ4uPj5do9PDwoODhY0D48PJyWL18ud2z48OGyBMrR0VGjp8KFQdVozdWrVykqKoqioqJE38wUBltbW3r58qXSths3bpCfnx999dVXKn0sXbqUypYtS3v37i3Qtnv3bipbtmyB1/pTcnJyyMPDgziOo9q1a8tKfzs4OBDP89SrVy+1GoImJiYq9RIfPHhApqamgu08z4segRSbxGpjLei7d+/om2++IWNjY3J3d6eAgACaOnUqde/enYyMjKh58+Yq1yiJtdcXH/qgNcdiUI+6xEsTYmNjycbGRrBdUa7AwsKiUHqcjC8XlrwxGAy94cKFCzRu3Dhyc3MjV1dXGj9+PF24cEEj26SkJJo3bx7VqFGDvvrqKxozZgwZGBjQjRs3NO7fzc2NRo4cKdj+ww8/kJubm0of+VXDikpxV6skUi70/fr1a6WJSU5OTqE197RBeno6bdiwgZo3b04SiYRatmypdtRLG9NgiYj++OMP6tGjBzk6OpKjoyP16NGDIiMjNYpb7NRLbUwfFZvEirUnIlqxYgVVqFCBbt68WaAtISGBKlSoQKtWrdKZvb740AetORaDetQlXppw+/ZtlaPqYvU4GV8uLHljMBj/eVxdXcnCwoL69+9P+/btk00jLGzydvbsWTI0NKQ+ffrQhQsX6PXr15Samkp///03eXh4kKGhIZ05c0alD1tbW5WCxuoo7mqVRAVH3nbu3El2dnZKp4C9efOG7O3ttV4lUYjTp0/T999/L5uaJpFI1P4P8tHGNFixiJ16yXGc3NP5oiA2idVGEty6dWv69ddfBdtXrVpFrVu31pm9vvjo27ev3OdZkV69elGfPn1UxiDWB4tBPeoSL0349ddfqWnTpoLtP/30k0Ybg6EIS94YDEaJ8/DhQ402ISQSCfn5+dHt27fljhc2eSPKS1zKly9foDR9uXLlVK6vyGfy5MlkaGhIEydOlNNO0xRTU1O5aXb16tWjFStWyPYfPnyo84SjQ4cOtGHDBsH2kJAQ6tixo05jWLhwITk4OFDlypXJ399ftpC/MP9TsdNgW7ZsSTNnzqTjx4/T27dvC3cBHxE79ZLjOFlpflWbKsQmsdpIgsuXL6+yyM3169epfPnyOrPXFx/6oDXHYlCPusSLKG/UWdm2ceNGGjt2LJmZmdHWrVuL1L8yFPU4GV8uLHljMBgljpCm16fHJRKJoP25c+fIx8eHLC0tqWnTphQUFETPnz8vUvJGlDe6tHPnTlq4cCEtXLiQ/vzzT42LGRDlFftwdHSkOnXq0OXLlwvVtzaqVd69e5eGDBki269atarcjX758uWVTvvKp2LFinTnzh3B9jt37lDFihU1vaQiIZFIaPr06QWKsRTmfyp2GuzQoUPp66+/Jo7jyMTEhL777juaM2cOnTp1qtAaUkWdeslxHK1cuZLCw8NVbqoQm8RqYy2ogYEBPXv2TLD96dOnZGhoqDN7ffKhD1pzX3oM2ki8FHUb87f83yFtJm5Eyqe3M75MmM4bg8EocWJjY5UeJyL88ccfWLVqFczNzfH8+XOVfjIzM/HHH38gNDQUMTExyMnJwbJlyzB06FBYWFjoInRB3r17hx9//BG//vorOnToAAMDA7n2nTt3KrX7+eefsWrVKowaNQrHjx/Hixcv8M8//8jaV6xYgX379uHo0aOCfU+YMAFmZmYyvSALCwvMmjULX331FQAgKioK1apVw7p165Tam5qa4urVq6hdu7bS9oSEBDRq1EhrWnXKWLBgAcLDw5GVlYX+/ftj0KBBcHZ2hqGhIWJjY1GnTh21PvI11tzd3eHv74/atWuDiJCQkIClS5di9+7dOHHiBFq2bKnSz+PHj3H8+HFER0fj5MmTuH//PkxNTfHtt9+ibdu2mDZtmrYuuwA8z0Mqlcr+d0WhS5cuqFatGtauXau0feTIkUhKSsL+/ft1Yg8AEokEUqkU1tbWStuTk5NRqVIlQS1Gsfb65CMffdCr+1Jj+FQb9FMsLCxQu3Zt+Pv7o0+fPoWOQ5eo0nBkfFmw5I3BYOglR48eRUBAAG7fvo2JEyfC398f5ubmGtvfunULISEh2LRpE1JTU9GhQwfs2bNHpc2qVas08j1u3Di156SlpWHs2LHYtm0bevfuXSB5CwsLU2qXm5uL2bNnY9++fbCxscGyZctkws4A0KdPH3Tu3BnDhg0T7NvZ2RlBQUFwcXEBUPBHPzo6Gj4+PrKbHUUcHR0xY8YMeHl5KW3ftGkTAgMDcfPmTeEXQEtER0cjNDQUO3bswNdff40bN24gOjpabcKVz59//okRI0bg1atXcsfLlCmD9evXo3fv3oWOKSkpCevXr0dQUBAyMjI0ulEvKhKJBM+ePROVvIlNYrWRBPM8D2dn5wKfg3yys7Nx48YNwddSrL0++WAwigJL3hj5sOSNwWDoFZcvX0ZAQABOnz4NHx8fuRGjopCTk4O9e/ciNDRUbfJWo0YNtf44jsO9e/dUnnP48GEMGzYMlSpVQkREhOAIljIyMjIKlaQqw8LCAtevX4etrS0AwM/PDz/++CPKlSsHAHj48CFq164tOHI2Y8YM/P7774iJiUGFChXk2qRSKZo1awYvLy8EBgaKirMwpKenY/PmzQgLC8Ply5fRtGlTeHh4YOLEiWptMzMzcejQIbkn8x07doSZmZnG/ScmJuLkyZOyLTU1FS1atMB3332HGTNmCNrxPA+O41T65jgO2dnZgvZiR94A8UmsWPs5c+ZoFOfs2bN1Yq9PPt68eYOFCxdi586dePDgATiOQ40aNeDh4QF/f3+N3pdifbAYtEN6ejpu374NBwcHmJub48qVK1ixYgXevn0Ld3d3DBw4UGt9seSNkQ9L3hgMhl5w9+5dzJgxAzt27EDfvn0xf/78/+SP1A8//ICIiAhMnz4dM2bMgEQiKZR9jRo1EBERgdatWxc5BisrKxw5cgRNmzZV2h4TE4P27dsjLS1NaXt6ejpatGiBR48ewcvLCw4ODuA4DgkJCdi8eTOqVq2K8+fPF/tU1HyuX7+OkJAQbNmyRe1UWnU8efIElStXVtoWFhaGEydO4OTJk3j9+jVatmyJ7777Dt999x0aN24sOPryKbt37xZsO3fuHIKCgkBEGk1BTU1Nxd27d8FxHL7++muULl1arc2niE1itZEEa8rZs2fRuHFjGBsbl4i9rny8f/8e3377Lf755x+4urrKjWIePHgQjRo1wqlTp2BoaCjoU6wPFkMeYhOvU6dOoWvXrsjIyECZMmUQGRkJDw8PVK5cGRKJBAkJCVi3bh2GDx+u0o+msOSNIaOY19gxGAxGAXx9fcnIyIg6depUrELQiri4uFBKSoooH05OToJFSnJycmjPnj3Uo0cPQXux1SqJiFq0aEGBgYGC7XPnzqUWLVqo9JGamkq+vr5UtmxZ2UL8smXLkq+vr+jXSBs8efKERo8eXWT7Z8+e0ZgxY1RWSeQ4jqpXr07r1q0rdIESVSQkJJC7uztJJBIaPHiwykqORET3798nNzc3kkgkcgV8unTpQvfv39daXPqE2OIM2ijuoAsf+qA1x2Igio6OJgsLC9n32qFDh8jCwoJq165NTk5OxPM8/fbbbyr7b9WqFQ0dOpSSkpJo7ty5VLp0aZo2bZqsfd68eVS/fn2VPgoDK1jCyIclbwwGo8ThOI5MTU1l4qRCW3HEIVYQ+d27dwWO3b59mwICAqhixYpkYmKiMnkjEletkojot99+IzMzM9q3b1+Btj179pCZmZnaG5N8cnNz6fnz55ScnEy5ublKz9FVCesbN27Qr7/+SuvXr5cljC9evKAJEyaQqakpOTo6qrRPSUmhAQMGUPny5alixYq0cuVKysnJoZkzZ5KpqSk1btyYtmzZImi/Zs0a6tevH9nY2FDp0qWpa9eutGTJErp48aLga6GKJ0+ekI+PDxkaGlLXrl3p+vXram0ePXpEFSpUoCpVqtCCBQvozz//pJ07d1JgYCBVqVKFbGxsKCkpSaWP8+fP04EDB+SORUREkK2tLVlbW9Pw4cNV/v/E2hcFRe3B4rbXlQ990JpjMWgn8bKysqKEhAQiyvve53leJmlClFeV19zcXND+4cOHhfoe0cb7kfF5wJI3BoNR4uiLWKk2krd8MjMzKTw8nFq1akWGhobE8zytXLmS0tPTNbLPysoif39/MjExoW7dusn0wfI3dXh6espKZru7u1PPnj3J0dGReJ4vsnCtELp4Irx3714yMjKSjfp9/fXXdPz4cSpfvjy1adOG9u7dq9aHr68vValShSZNmiR7mu7q6kouLi508uTJQsVz48YNWrNmDfXt25cqVKhAVlZW5ObmRosXL1Zrm5qaSlOmTCFTU1Nq0aIFnTp1SuN+hwwZQq1bt1aqM5eZmUmtW7emoUOHqvTRuXNn+uWXX2T7cXFxZGBgQD4+PrR06VKysbGh2bNn68y+KHyuyZs+aM2xGMQnXkQFfy8U/9dSqZR4nhe053lea783jC8LlrwxGAzGRziOo7t379Lr169Vbqq4cOECDR8+nCwtLalx48a0YsUKkkqlhdace/36NQ0ePJhMTU3Jy8uLvL295TZNiIyMlNMW6969u0baYoVFF0+EmzdvTuPGjaP09HRaunQpcRxH9vb2FB0drbGPatWq0ZEjR4iIKDExkTiOo/Hjx4uO7cmTJzRjxgyytLRUeXNGlCc2XrZsWapTpw7t2rWr0H1VrFiRTp8+LdgeHR2tVnPPxsaGLl68KNufPn06tWzZUra/detWlaOYYu2LwueavOmD1hyLQXziRZSXfD1//ly2b2FhQffu3dPYhzYfFjK+LNSvtmYwGIwvCHt7e8E2IgLHcSrLgH/77bcYO3YsYmJi4ODgUKQYPq1WeeXKlUJVq/wUT09PeHp6FjieX4HT3d29SH6Lg4SEBERERMDc3Bzjxo3DlClTsGLFikIVcnn69KlMD65mzZowMTGBj49PoWNJTk6WqzR5+/ZtGBkZoVmzZjI5BiECAgJgamqKWrVqISIiAhEREUrPE9L9+/fff2VVQ5VRs2ZN/PvvvypjSElJkasaGh0djc6dO8v2mzRpgqSkJJ3ZM/6f3NxclUWMeJ5XKzMg1geLIa/C66dVYBX3NYGI0K5dO1nhoszMTHTr1g1GRkYAIFhBlsEQC0veGAxGidOwYUONfjivXLmi81i2b9+OsmXLFtm+bdu2CAkJwfPnzzFo0CB06tSpUDcFYqtVquLmzZsIDQ1FREQEUlJS8P79e6351jZpaWmyaooGBgYwNTVVmVgrIzc3V67SnEQiQalSpTS2Hz16NE6cOIFbt27BwMAATZo0gYeHB1xcXPDtt9/CxMRErY/BgwcX+qbwUypVqoQbN26gSpUqStv/+ecfVKxYUaWPChUq4P79+6hatSrev3+PK1euyJW8T09PV1nVT6x9URDzmmnDXlc+FG/4FdHkhl+sDxaDdhIvRTmIHj16FDhHnYRGcHCwWmkYTXRFGV8WLHljMBgljj6NALVs2VKUptbhw4eRlJSEsLAw+Pr64u3bt+jXrx8AzW4Gz549i3PnzqFRo0YF2nJzc7F//36EhIRg165dGsXz5s0bREVFISQkBOfPn4eLiwsCAwP16jUXIj4+HlKpFEDezdatW7fw5s0buXPq1asnaE9E8Pb2lpVpz8rKwsiRIwskcEKjXleuXIG7uztcXFzQsmXLIpXEDw8PL9T5jx8/RqVKlcDzPIC8G8LJkyejUaNGsLa2ljv3+fPnmDp1qtr/ZefOnREQEICFCxdi165dMDMzQ6tWrWTtcXFx+Prrr3VmXxRIpIqRWHtd+VCl/5aPuht+sT5YDNpJvDTp/1OUSU+sW7dO5QM6juNY8sYoANN5YzAY/zm0ob+kDE0EkbOzszXS98rnyJEjCA0Nxa5du1C1alV4eHjAw8NDaXIG5GkX5T/9zefOnTtyI2adOnVSm7z9/fffCA4OxtatW2FnZ4eBAwdi6tSpiIuLk00l1BaWlpa4du2aVvWH8sWtlf1E5R9XN4V1yJAhGvUVFhZW5Dg/pUuXLggODlY7EqYKxdcyJSUFzZo1g1QqhZeXl2wKbXx8PLZs2QIbGxucP39e5Wjxixcv0KtXL5w9exbm5uaIiIhAz549Ze3t2rVD8+bNBUXXxdozio4+6NWxGLTTv+JnW5PfGwZDKcW8xo7BYDBEoyu9G1tbW3r58qXSths3bpCfnx999dVXRfL96tUrCgoKogYNGqhdCE8krlqlo6MjVa9enaZNmyZXJKWwRVM0RRcFSx48eKDRpk/oqkjGq1evaOTIkVSmTBlZ9c0yZcrQDz/8IPh+VUZqaiplZ2cXOP7vv//KSVwkJSVRTk6OVu3v3r1LQ4YMke1XrVqVypQpI9vKly+vVK9LW/b65KMw6INeHYtBO/0rfrZZtUlGUWHTJhkMxn8O0tGEgfv378vtZ2Rk4I8//kBISAguXryI5s2bIyAgQK2f3NxchIeHY+fOnXjw4AE4jkONGjXQu3dvXL58GdeuXRO0jYmJQXBwMKKiomBvbw8vLy9s27YNVapUQfv27dWujwCAu3fvwtPTEy4uLnB0dFR7vljS09O17rN69eqFOn/UqFGYO3cuypcvL3f84cOHOHz4MD58+IA2bdpofdSxOChTpgzWrl2LNWvW4MWLFwAAa2vrQq/JsrKyUnpccdSuTp06SkdSxdgHBQXBxsZGtp+SkoJZs2bJRh2ioqKwfPlyrFu3TmkfYu31yUdh0MZ3nVgfLAbd/Obo6neM8fnDkjcGg8FQ4MyZMwgODsaOHTtQo0YNxMfHIzo6Gi1btlRrS0To3r07Dhw4gPr166Nu3bogIiQkJGDIkCH4888/VU551Ea1yvv37yM8PFy25q5///4YOHCgxjf7iYmJCAwMRGhoKACgWrVqyMjIkLVLJBKcOXOmyPHpgt9//x3+/v5yydupU6fg5uaGzMxMAHmFTyIiItC/f/+SClMUHMcVyxQrXdxoHz16FEFBQXLHevfuLUvwbG1tVVYCFWuvTz4YDCBvzZwmD+MYDEVY8sZgMBgfWbRoEUJDQ5GRkYH+/fvjzJkzqF+/PgwNDVGmTBmNfISHh+PUqVM4duxYgTLyx48fh7u7OzZu3IjBgwcrtRdbrRIAKleujBkzZmDGjBk4fvw4QkND0bJlS2RnZyM8PBw+Pj4qKzcW9+iCNlCWMMycORMuLi5Yv349TE1NMW3aNEyZMuU/lby5uLio/f9zHIdjx44VU0RF4+HDh6hRo4Zs38fHR24kz9bWFo8fP9aZvT75YDAAoGfPnrh7967a81QVZWJ8mbDkjcFgMD4yffp0TJ06FXPnzi1yif7IyEhMnz5dqf5X27ZtERAQgM2bNwsmb2KrVSrrs23btnj9+jU2b96M0NBQLFmyBM7OzoiLi1Nq87mMLly/fh2nTp1CpUqVAABLly7Fhg0bkJKSonEyXtwo/o8bNGggeG5aWhoiIyPx7t07HUclHp7n8fz5c5lm3fLly+Xak5OTVcoNiLXXJx+MLxNln22xRZkYXyZ8SQfAYDAYhUUb+kvKmDt3LrZt24YaNWpg6tSp+OeffwrtIy4uTk7AWBFXV1fExsaq9FG1alXMmjUL9+/fx6ZNm/D8+XMYGBigR48emD59epH07qysrDBq1ChcunQJV65cQZs2bQTP/VxGF1JTU+WmGZYqVQpmZmZITU0tuaDUoHgjt3z58gLb4sWLYWtri71796Jy5crYvHlzCUWrOU5OTjh69Khg+6FDh+Ds7Kwze33yURj0Qa+OxaDc9tGjR4WaYqx47v3793Hv3j3cv3+/wJZ//N69e0WOmfEZU8wFUhgMBqMADx8+pNzcXI3P10V1w085efIkDR48mEqVKkX16tUjiURCZ86c0cjW0NCQnj59Ktj+5MkTMjIyKnRMha1WqYpHjx7JVcxTxNLSki5cuCDYfuHCBbKwsBAVg7ZR9p7gOI5OnDhBsbGxsq1UqVK0f/9+uWNCDBkyhNLS0jSOYcGCBZSSkiJ3rFevXoWqCPno0SOlFR3z+f3336lmzZpUsWJFWr16NX348EFj35qii8qAv/32G5mZmdG+ffsKnL9nzx4yMzOj3377TdCnWHt98lEYdFXB9EuPQRu/OaxaJKOkYMkbg8EocfT1RzAtLY3Wrl1LTZs2JYlEQi1atKClS5eqtOF5np4/fy7YLpVK1SZfOTk5FBISQl26dCEnJydydnambt26UXh4OOXk5NDly5eLdD35XLt2TWUMLVq0oMDAQMH2uXPnUosWLUTFoG2Ekjee52Xl9T/d8o+reh208b5s0aIFVahQgfbs2SPKz19//UX169cnS0tLmjt3LmVkZIjypwpd3Wh7enoSx3Hk6OhI7u7u1LNnT3J0dCSe56lPnz5q/Yq11ycfjJJFG59tjuO08rt1+/ZtWrx4MY0ePZrGjBlDS5cu1enDScZ/H5a8MRiMEkdbP4K6JC4ujsaPH0/W1tYqz+M4jtzc3Khnz55KNzc3N5UJQ25uLnXp0oU4jqMGDRqQp6cn9evXj+rVq0ccx1GPHj1EX4u65K24Rxe0wciRI+nFixdyx8RqxWnjfZmbm0uLFi0iU1NTGjp0aKFG8ojyRjnbtGlDJiYmNGHChALXqAmFvVFVHP0Ta/8pkZGR1KNHD3J0dCRHR0fq3r07RUZGauxbrH1J+9AHrTkWg3Y+29rwsWDBAjIwMCCe58nGxoYqVKhAPM+ToaEhLV68WJRvxucLR8SEJhgMRsnC8zykUmmxlEEXw5s3b/D333+jffv2gucMGTJEI19hYWGCx8ePH4/du3cLVqv89ddfBQueaEJsbCwaNWqkciF8//79ERUVhdq1a8PBwQEcx+HmzZu4desWevfuja1btxa5f0149OiRRudVq1ZNa30qasXxPI/k5GRYW1uL9n3z5k0MGTIEz549w7hx42BgIF8vbNy4cUrteJ6HqakpfvjhB1mRDGUI2ef7EPP5Ko7PZ05ODvbu3Qt3d/cSsS8uHxMmTICZmRkWLFgAALCwsChQybVatWoqK7mK9cFi0M57mud5zJ8/X225f6HP5okTJ9C+fXvMnDkT48ePlxVRevXqFVasWIEFCxbg+PHjaN26dZFjZHyesOSNwWCUOGJ/BIsLTZIesXTs2FFWlVIZCxYsQHR0NA4dOlTkPjS9jj/++AN//PEHbt++DQCws7ND//794enpWeS+NYXneaVFAuhjBTYgr4hAdna21vq0tLSUE5fmeR5WVlZqCx28evVKI//BwcEYOXIkKlasKJe8cRwnWJjA1tZWI6kAVYUN9Dl5u3nzJkJDQxEREYGUlBS8f/++WO2L24ezszOCgoJkD2YsLCwQGxsre89FR0fDx8cHd+7cEexLrA8Wg3Z+c3ieR5UqVVRWJlb12ezXrx9Kly6N9evXK20fMWIE0tPTERkZqTJGxpcHkwpgMBh6wbp169T+CJZ08lYcxMXFYdGiRYLtrq6uWLVqlUofvXr1UtmuabVFT09PpYmaNkYo1HH16lWlx4kIf/zxB1atWqV1gVtlzzLnzJkjV2mzKCQnJ8PHxwdnzpxBSEgIvv/+e41tHzx4IKrvfA4dOqT2Orp3764z+0958+YNoqKiEBISgvPnz8PFxQWBgYEav5/E2pekD33QmmMx5KGN35xLly4V+aFGTEwMNm3aJNg+aNAgUTMsGJ8xJThlk8FgMIjov7HmjUj9WjFtoI1qld7e3hpthSUhIYEmT55MX331FRkaGhbaXixHjhyhb775hiwsLGj27NmUnp6uVf+KhTa08b6MjGkO7mcAAEToSURBVIykcuXKUfv27enRo0diQ1SLs7NzgX6UFWxRVsBFCLH2+Zw7d46GDh1K5ubm1LBhQ1qyZAlJJBK6ceOGRtcm1l4ffGijkqtYHywG7Xy2xRY9MTU1paSkJMH2pKQkMjExKbJ/xucLG3ljMBgljq502/6L5OTkFFgP9SkSiUTtVMGZM2fC1tYWPC9eylMbIxRiuXz5MgICAnD69Gn4+PjgwIEDxbI+Uhvvy2HDhmHhwoUYM2aMFiJSz4MHD/Dhw4cCx8VOexRrX6dOHWRmZmLAgAG4cOEC6tSpAwCC04O1ba8vPvJ14po2baq0vTBac0X1wWLQzmebRK46ysrKgpGRkWC7oaFhkabwMj5/WPLGYDBKHLE/gtpiz549Ktvv37+v8xiICN7e3jA2Nlba/u7dO7U+7Ozs8OzZM9nNdr9+/bBq1SpUqFBB4zj+/vtvBAcHY+vWrbCzs8PAgQNx4cIFrFq1SnbDqmvu3r2LGTNmYMeOHejbty/i4+Nl61mKA228L93d3Qs1TVIX6INA8t27d+Hp6QkXFxc4OjoWu72++BgyZAgmTJiA+vXro0uXLnJte/fuxS+//IIVK1bo1AeLQTuf7dmzZ4ueuh0cHCzoIz09XZRvxucLS94YDEaJo40fQW2gyWiSrkcJNbnRV7cOQvHG5MCBA/j55581jkEbIxRiGTVqFEJCQuDi4oJLly6hQYMGxdZ3Prm5ubK/U1NTcffuXXAch6+//hqlS5fWyMcff/yB5cuXw8LCQkdRqkfsjao2bnTv37+P8PBw+Pr64u3bt+jfvz8GDhyo8edJrL2++Bg+fDiOHz+Obt26CVZyHT58uE59sBi085vTs2dP3L17V+159erVU3q8WrVq2LBhg0pbbVbTZXw+sGqTDAajxCmJsvCfM4rVARWrsKnDyMgInp6eGDRoENq3by+7MTU0NERsbGyxjLzxPA8TExPUrl1b5XlXrlzRWp++vr6YN2+eTCoAyJuGOHr0aBw6dEiWxHAch86dO+PXX39VWb4fKH4ZDGX/6yFDhmDVqlVFTiDF2ity/PhxhIaGYufOncjKyoK/vz98fHxgb29fLPb64EMblVzF+viSY4iLi9PIt1DiBfx/RVxlt9H5xzmO02l1YsaXCUveGAxGifNpxa9Pb5A/PcZ+BDVHIpFAKpXK9MksLCwQFxcnV5lNFU+ePEF4eDjCwsLkRheaNWuGa9euFUvyNmfOHI3Omz17dpH72LlzJ3766SfBG7mkpCQ0adIEhoaGGDVqFBwdHUFESEhIwNq1a5GdnY2LFy+iSpUqgn1oUytOEwqbqJckr1+/xubNmxEaGoorV67A2dlZ45tqbdjrk4989EGv7kuIQRuJ18OHDzWKo3r16hrHzGBoAkveGAxGiWNgYIAqVarA29sb3bp1EyzYUb9+fZ3GsXHjRqXHrays4ODgoHYUSF/geR6urq6ydXN79+5F27ZtUapUKbnzdu7cqdaXNkYoSpINGzbg8OHDMDQ0xPjx49GsWTMcP34ckyZNwq1btzBo0CBBnaWhQ4ciMTERhw4dgomJiVzb27dv0blzZ9SqVQshISGC/WtbK04dypI3Ic28T1GlmSfWXhOuXbuG0NBQtTIYurIvaR/6oFf3JcWgD4mXm5sbIiMjZfIGgYGBGD16tGxK9r///otWrVohPj5eZzEw/puwNW8MBqPEefz4MSIiIhAeHo5169bBy8sLw4YNK3JRgaIyfvx4pcczMjKQm5sLNzc3bNmypUTXL2mC4ro5Ly+vIvtq27Yt2rZtKze6sGTJElGjC4UlLi4Ot2/fBsdxsLOzUzmV6VOWLFmC6dOno169ekhISMDu3bsxY8YMLFu2DGPHjsXo0aPlpkgqcvDgQWzdurVA4gYApqammDdvnkbTu8RoxQUFBWHs2LEan79+/foChWl27twpmHydO3cOQUFBKte1ibXXhHLlyiEjI6PE7EvChz7o1X2pMWgzKbtz5w52796NBw8egOM41KhRA+7u7mpHvw8dOiRXgGrhwoXo37+/LHnLzs7GrVu3tBYn4zOi+FQJGAwGQz2nT5+moUOHkoWFBTVr1ox+++03ysnJKdGYcnJyKCYmhurVq0eTJk0q0Vj0gatXr9LYsWN13s+FCxfI2dmZeJ6X0xOrW7cuxcTEqLWvXbs2hYSEEBHRiRMniOM4ateuHaWkpGjUv5GRkVodJnWae2L1pMqUKUPt27dXGUdRSEhIIHd3d5JIJDR48GB6+PBhsdorIlZDURsajMXlo6S15lgM/8/t27dp8eLFNHr0aBozZgwtXbpUTutRHQsWLCADAwPieZ5sbGyoQoUKxPM8GRoa0uLFi1XaKn43KOpMSqVSneuKMv6bsOSNwWDoJVKplFxcXIjnefr3339LOhwiyhOJtre3L+kwSpxHjx7RkCFDdNrHjRs3yNzcnJo0aUJbtmyhq1ev0pUrV2jz5s3UuHFjsrCwUHuDZmpqKpdUGBkZ0fnz5zWOwdbWlg4ePCjY/tdff1H16tVV+hAr5PvkyRPq0qULlS5dmjZu3FhkP5/68/HxIUNDQ+ratStdv369WO2F+FKSN0dHR6pevTpNmzZN7v1rYGCgccIh1geLIQ8xiRcR0fHjx4nneZo9eza9evVKdvzff/+lmTNnkkQioejoaEF7lrwxigpL3hgMhl5x9uxZGjZsGFlaWlKTJk1o7dq1JT7yls/9+/fJzMyspMMocbRxk6sODw8P6tmzJ+Xm5hZoy83NJXd3d+rTp49KH+pujtQxfvx4qlu3Lj1//rxAW3JyMtWrV4/Gjx9fqBiKSlhYGJUpU4Z69uxJly9fptjYWLlNHampqTRlyhQyNTWlFi1a0KlTpwrVv1h7dXwpyZuhoSENGjSIDh8+LPfeLkzSItYHi0F84kVE1LdvXxoxYoRg+/Dhw8nT01Owned5ue8Wc3NzunfvnmyfJW8MIdiaNwaDUeI8e/YMGzduRFhYGFJSUjBw4ECcO3cOTk5OJR2aHImJiSorCzK0x8mTJ/HXX38pXWvFcRymT58ONzc3tX4+FcHNzs5GeHh4gXVu48aNU2o7e/ZsHDhwAF9//TW8vLxkBWvi4+OxZcsW2NjYYNasWSr7/1QrTgze3t6oUqUKOnfujN27d8uq4ZEGVfEWLVqEhQsXwsbGBpGRkejRo0eh+hZrz/h/9EFrjsUArFu3Dj4+Pvjpp5/kjpctWxZz586FVCrF2rVr0bp1a0EfMTEx2LRpk2D7oEGDVGpyEhG8vb1lhaWysrIwcuRIWWGpT9fDMRifwqpNMhiMEsfIyAiVKlXC999/j+7du8PQ0FDpeZoWqtA2RISrV69i6NChaN++PZYsWVIicegLsbGxaNSokU6lG0xMTHDnzh1UrVpVaXtSUhLs7OyQlZUl6MPW1lajKon37t0TbE9JScH06dMRFRWF1NRUAEDp0qXRt29fBAYGoly5cir99+rVS2V7Puoqfy5btgwzZ85Enz59MHPmzAIVWVUVYOB5Hqampmjfvr2cLIemMYi1B9S/DqmpqYiOjhZ8T4m11ycf+ZS01tyXHEONGjWwadMm/O9//1Pafvr0aQwePBj3798X7NPMzAy3b98WfKD3+PFj2NnZ4e3bt0rbhwwZouaq8ggLC9PoPMaXA0veGAxGicPzvOzv/Jttxa+m4tB5K1OmjNKb/YyMDOTk5KBz586IioqSjeR8qRRH8la7dm0EBgaid+/eStu3b9+OGTNmFFs1NiLCixcvAADW1tYajxCIvUG7d+8eBg8ejMTERKxbt65Io17e3t4axSsUg1h7QPzroI0bXX3xoYg+aM19aTGITbyAvN8tqVSKr776Sml7cnIyKlWqxPRJGVqHJW8MBqPE0URzJyUlBQ0aNNBpHBEREUqPW1paonbt2sUuXVBSaHN0oajMnj0b4eHh2L9/P5ydneXarl+/jm7duuH7779XK+ZNRLh79y4+fPgAe3t7QQ1BfcXc3BydO3fGunXrVMoa6Dv37t2Dra2t3IOa4rTXJx+q0Ae9ui8hBm0kXjzPY/78+YIP89LT0zFr1ixR35Pbt2+Hh4dHke0Znyf/rV8xBoPxWSI05Sv/KWpISAiuXbum8yeYivpoXyrqNMmsrKxUruXQBtOmTcPRo0fRoEEDdOjQQZY4x8fH4+jRo2jatCmmTZum0seDBw/Qo0cP/PPPPwCAqlWrYseOHfjmm280isHFxUWjaZfHjh0TbM/JycGNGzdgZ2cHU1NTubbMzEzcvXsXzs7OgslAQEAAJk+eLFsXUxTExiDWHgDs7Ozw7Nkz2c1yv379sGrVqgKadLqy1ycfqtAHvbovJYZP18Mqkp6ertZ/tWrVsGHDBrXnqCJfy83Q0FBuiufu3bsxa9Ys3Lx5kyVvjAKwkTcGg6F3fLp+oXr16ujduzd69+6Nhg0b6rRfIsKSJUuwa9cufPjwAe3bt8esWbOUijR/zuh6dEFT3r9/j+XLlyMyMhK3b98GANjb28PT0xN+fn5qE5p+/frh2rVrmD17NkxMTLB48WLk5OQgJiZGo/79/PwE29LS0hAZGYl3796pfKgQHh6OX3/9FRcuXCiwXiwnJwfNmjXDhAkTBIXUJRKJXLJQFMTGINYeKDjSYWFhgdjYWLVCxtqy1ycfqtDGlGSxPr6EGDRZDwtA5Zo3scTHx6Nr166ymSc9evTA2rVr0bdvX8TGxsLHxwfjx48XXPfL+IIp/gKXDAaDUZCkpCSaN28e1ahRg7766isaM2ZMocpGa4MFCxYQz/PUoUMH6t69OxkbG9Pw4cOLrX99QVGbrG/fviSVSkswoqJRsWJFOnnypGw/KSmJeJ6nzMzMIvv88OEDrVixgqytralWrVoUGRmp8vz//e9/Ks+JioqiVq1aCbZrQ2pAbAxi7YnEyzaItdcnH6rQB8kDFkPx0K1bN2rbti3t3buXPD09ieM4srOzozlz5lBaWlpJh8fQY0r2sSqDwWAAcHNzQ506dRAfH4+goCA8ffoUQUFBxR5HeHg4goKCcPjwYezevRu7du3Cxo0bCxRP+dxRvN4DBw7gzZs3JRRN0ZFKpbLy/gBQpUoVmJqaIjk5uUj+Nm/eDAcHByxcuBA//fQTEhIS4OnpqdLm1q1baN68uWB7kyZNkJCQoNJHYcqn6yIGbV2D4nUU5rrE2uuTD8bngZubG16/fi3bDwwMlFWkBYB///0XderUEbSPiYnB4sWL0bVrV6xduxYAMHnyZMyaNQsWFhY6i5vx34eteWMwGCXO4cOHMW7cOPj6+sLOzq7E4nj48CG6du0q2+/UqROICE+fPkXlypVLLK4vEaHKn4q8evVKsI3juAJTP3meL3QyfvDgQQQEBOD+/fvw9/fHxIkTZVpM6njz5g3S0tIE29PT05GZmanSx6daUEKoKtMvNgZtXAOp0bTKR+g6xNrrkw9GyePm5obIyEjZ+t7AwECMHj0apUuXBpCXeLVq1Qrx8fGCPg4dOiSnxbZw4UL0799f5iN/PZsQz58/l/2ulC5dGmZmZvjuu+9EXhnjS4AlbwwGo8Q5ffo0QkND0bhxY9SuXRuDBg1Cv379ij2O9+/fyxVk4DgORkZGX5xYqj6MLqxYsUK0DyKCvb29XOwZGRlo2LChXFInlADGxMRg6tSpOH/+PEaOHImjR48WuuKjnZ0dzp07J6hReObMGbUPLCwsLAoUCinOGLRxDYrFgFStj9OFvb740KSSq659sBjEJ15AwRkKhX0opPhwied5QY1TBuNTWPLGYDBKnBYtWqBFixZYuXIl/vjjD4SGhmLixInIzc3FkSNHULVq1WKbRjJz5kyYmZnJ9t+/f4/AwEC5CozLli0rllhKCn0YXdBG5U+x4rbNmzeHqakpfH19YWtriy1btig9b9y4cYI+BgwYgB9//BHffvttgeQnNjYWs2bNwpQpU1TGsWrVKlEFS8TGoI1rEPu/0IZQsT740EYlV7E+WAziEy9toPhwSdmDJUD17ALGlwmrNslgMPSSW7duISQkBJs2bUJqaio6dOiAPXv26LTPNm3aaFQa/vjx4zqNo6TRhRCxWNLT0+VusHie17lYuiYV6TiOw7179wTbP3z4gI4dO+LMmTNo3749ateuDY7jkJCQgKNHj6Jly5Y4cuSI4BN3bVSbFBuDWHvG/6MPWnMsBvVVQzXReZNIJJBKpbC2tpb5iIuLQ40aNTTyIaQrqgiTsGEUoLgrpDAYDEZhyM7Opj///JO6detW0qEwipGrV6+Sm5ubbN/c3Jx4npdtEomEYmJi1PrZunUrDRgwgPr06UPr16/XZciCvH//nhYuXEj169cnMzMzMjU1pfr169PChQvp3bt3Km21UW1SbAzasGfkoY1KrmJ9sBjybJ8/fy7bNzc3p3v37sn2pVKp2kqVHMeRm5sb9ezZk3r27EkGBgbUsWNH2b6bm5teV7tk/HdhI28MBoMhwMuXL8FxHMqVK1fSoXxxDBs2DLVq1ZIJcVtYWGD9+vWoXLkyiAihoaEgImzatEnQx2+//YaRI0fCzs4OJiYm+OeffzBlyhT8/PPPOom5bt26OHDggChdpsjISHTv3l02RTU6OhotW7aEgUHxrXJQjKG47T9n9EFrjsWQZ+vq6iqbGr537160bdtW9p599+4dDh48qHLkTewMhZSUFPz+++/4/vvvYWlpKdf2+vVrbNy4UWkbg8HWvDEYDMYnpKamYsaMGYiKikJKSgqAvMqHnp6emD9/vmxBO0O3nD17Ft7e3nLHmjdvLrsxMzU1Rd++fVX6CAoKwowZMzBv3jwAeVIQY8eO1Vny9uDBA3z48EGUjx9++AHNmjWTXWdsbCxiY2PV2qladyc2huK2ZzB0jSaFZ9StuRM7bfzXX39FXFwcxo4dW6DNysoKp0+fRlpaGmbMmCGqH8bnB0veGAwG4yOvXr1CixYt8OTJEwwcOBCOjo4gIiQkJCA8PBzHjh3DuXPnUKZMmZIO9bMnKSkJ1apVk+3PnTtXrtJjxYoV1eq13bt3T+7p+KBBgzBixAhIpVLY2NhoP2gtoDgZZvny5WptOI7TavImdkIOm9AjjD5ozbEYim+97vbt2+Hh4aG0bceOHVi6dKmg7Q8//AB/f3+WvDEKwJI3BoPB+MjcuXNhZGSExMREVKhQoUBbx44dMXfuXI1uqBniMDY2xuPHj1G9enUAgJ+fn1x7UlKSXFVQZbx9+1auqIlEIoGxsbFaTTJ94v79+yUdAkOLkB5ozbEYNENV4pVPvqSAoaEh7O3tZcd3796NWbNm4ebNm4I+EhMT1Up0JCYmFil2xucNS94YDAbjI7t27cL69esLJG4AYGNjg0WLFmHkyJEseSsGGjZsiF27dqFly5ZK23fu3ImGDRuq9RMcHCyXwGVnZyM8PFxuFE+bo1YMhir0QWuOxZCHmMQLAOLj49G1a1c8fPgQANCjRw+sXbsWffv2RWxsLHx8fLBv3z5Be4lEgqdPn8rNMPiUp0+fiqrGyfiMKYkqKQwGg6GPGBkZUVJSkmB7UlISGRsbF2NEXy7bt28nAwMD+vXXXyknJ0d2PDs7m1atWkWGhoa0bds2lT6qV69Otra2KrcaNWpoLWZzc3NKTEzUqo9jx46Ro6MjvX79usC5qampVKdOHYqOjhbVp7oYituewdA1N27coBo1asiq1/bs2ZOkUim1bt2arKysaNKkSfTo0SOVPrp160Zt27alvXv3kqenJ3EcR3Z2djRnzhxKS0tTG0ObNm1o6tSpgu1TpkyhNm3aFPraGJ8/bOSNwWAwPlK+fHk8ePAAVapUUdp+//59VnmymOjduzcmTpyIsWPHYvr06ahZsyY4jkNiYiIyMjIwceJEtVOaHjx4UDzB6pAVK1Zg+PDhSivOWVlZ4YcffsDy5cvRunXrEoiOwfhvEhAQgBo1amDVqlXYvHkzoqKi8M8//8DLywv79u2DhYWFWh8xMTE4cOAAGjVqhP/973+IiorC5MmTMXz4cI1iGDNmDDw9PVGlShX4+vpCIpEAAHJycrBmzRosX74cW7ZsEXWdjM8TJhXAYDAYHxk2bBju3r2LI0eOwMjISK7t3bt36NSpE77++muEhISUUIRfHufPn0dkZCTu3LkDIG8dSP/+/dG8eXPRvv/9919s2rQJEyZMEO0LALZs2YIePXqIKpHv7OyMv/76SyY3UL16dRw8eBCOjo5Kz7958yY6duyIR48eFblPdTEUtz2DoWtsbGxkiVdqairKli2L9evXa5x4AXlyA8+ePZNNszc3N8eVK1fkpmCqY8aMGfj5559hYWFR4AHV5MmT8csvvxT62hifPyx5YzAYjI88fvwYjRs3hrGxMUaPHo3atWsDyFvbsGbNGrx79w6XLl1iN6X/YYgIhw8fRkhICHbv3g1LS0u8ePFC6bkbN27UyKe6kuKfkp6eLleNked5uTV5iuTr09WqVUtp+927d1G3bl28fftWo/4fPnwIqVQKjuNQoUIFWUEYTRFrz2DoA9pIvCQSCaRSKaytrQEAlpaWiI2NRY0aNQoVS0xMDDZv3oy7d++CiGBvb48BAwagadOmhfLD+IIowSmbDAaDoXckJiZS586died54jiOOI4jnuepU6dOdOfOnZIO74th4cKFlJmZKduPjo6mrKws2X5aWhr5+vpq7O/+/fs0c+ZMqlq1KvE8T4MGDaIjR45Qdna2oE3p0qUFtzJlypCRkRHxPK+y36tXr5Kbm5ts39zcXLbOhud5kkgkFBMTI2hfs2ZN2rlzp2D7jh07NFq3t2zZMqpSpUqB93WVKlVo+fLlOrdnMPQJnufp+fPnsn0LCwu6d+9eoXxwHCf7LihTpgxxHEdWVlay/fxNW/j6+tKLFy+05o/x34WNvDEYDIYSUlJSZFP1atWqhbJly5ZwRF8WEokEz549w1dffQUg76n2tWvXZMLPycnJqFSpEnJycgR9vHv3Djt37kRwcDDOnTsHV1dXDBgwAP3790dsbCzq1KlTpNiePXuGOXPmIDQ0FG3btsXBgwcFzx02bBhq1aqFadOmAQAsLCywfv16VK5cGUSE0NBQEBE2bdqk1H7s2LE4efIkLl68CBMTE7m2t2/fomnTpnBxccGqVasEY5g3bx6WLFmC6dOno1OnTqhQoQKICM+fP8ehQ4fw888/w9/fHz/++KNO7BkMfYPneVhZWcl04VJTU2FpaVmguuOrV68EfURERGjUl2JVzKKi+B3I+HJhyRuDwWB8wsOHD3H48GFkZ2ejdevWcHJyKumQvkh4nodUKpUlbxYWFoiNjS1U8la+fHnUqVMHXl5e6NOnj0xc3dDQsEjJW3p6OhYuXIiVK1fCyckJP//8M1xcXFTa1K5dGxs2bECrVq2UXseFCxfQt29fWblxRZKTk9GoUSNIJBKMGTMGDg4O4DgOCQkJWL16NXJycnDlyhWl8hb5VK1aFUFBQXB3d1fa/ueff2LMmDF48uSJTuwZDH2juBMvbaD43cH4cmHVJhkMBuMjp06dgpubm0zE2cDAABEREejfv38JR8YoCjk5OeA4DhzHySq5FYX379/j119/xYIFC1C+fHmEhYWprXSZT1JSkpyO09y5c+U05ipWrIjk5GRB+woVKuDcuXPw9fXFtGnTZOvlOI5Dp06dsGbNGpWJG5BXmMXBwUGw3d7eHikpKTqzZzD0DW0kZSkpKfj999/x/fffF6gG+/r1a2zcuFFpG4MhFqb+x2AwGB+ZOXMmXFxc8PjxY/z7778YOnQopkyZUtJhMYrIs2fPMGLECERGRsLGxga9e/fGn3/+KZsqpQ4iQkREBOzs7LB06VIsWLAAN27c0DhxAwBjY2M8fvxYtu/n5yd3M5eUlAQzMzOVPqpXr44DBw7g5cuXuHDhAs6fP4+XL1/iwIEDsLW1lTv38ePHyM3NlTvWtGlTBAYGIjs7u4Dv7OxsLFiwQGVxBLH2DIa+kZKSgqCgIKSlpRVoe/36tWDbp/z66684deqUoIzH6dOnERQUpLWYGYx82LRJBoPB+EjZsmVx6tQpODs7AwDevHkDS0tLvHz5UjbljlE88DyP+fPnyyoxTp06FZMnT5aNWqWnp2PWrFkqp01+SmJiIsLCwhAREYEnT56gf//+8Pb2Rtu2bQVH5erVq4fExESMHTsWEyZMEEyyVD1Zb9euHRo1aoTFixcrbZ80aRKuXbuGY8eOaXQd6lC2Lub69evo2LEj3r17h++++w4VKlQAx3GQSqU4deoUjI2NceTIEcEpwmLtGQx9Y968eYiLi8O2bduUtvft2xf169fHjBkzBH00aNAAS5cuRbt27ZS2Hzt2DP7+/rh69apWYmbTJhn5sOSNwWAwPqK4zgrI+8GMi4srdPlnhjhsbW01GiG7f/9+ofzm5ubi0KFDCAkJwd69e2FhYYGXL18qPffT4gXKYiEicBynMoHcsWMHPD09sWLFCvj6+sp85gvxTpo0CVu2bCnUaJ4qhG7w0tPT8fvvv+P8+fOQSqUA8rSuWrRogQEDBqid2iXWnsHQJ7SReFlYWODGjRty06I/5dGjR3B2dlY7gqcpLHlj5MPWvDEYDMYnxMfHy25Ogbwb9ISEBKSnp8uO1atXryRC+6J48OCB2nOKUiCD53m4urrC1dUVL168kKvyGBkZie7du8tEtk+cOFFo/4r07t0bEydOxNixYzF9+vQCQrwTJ07UWuKmCgsLC/j6+sLX17dE7BkMfSIxMRF2dnaC7XZ2dkhMTFTpQyKR4OnTp4LJ29OnTwtUrxSDl5cXe0jCAMBG3hgMBkMGz/PgOA7Kvhbzj6sbaWHoHqlUigULFmDDhg0ai1Nrgi5LcZ8/fx6RkZEy+Qk7Ozv0798fzZs312o/hXk6n5ycjHfv3gnefAqRnZ2NEydO4NGjR7C1tUWbNm1EFYRhMIqb0qVL4+DBg4Kfv/Pnz6Nz585ITU0V9OHi4oJmzZrhl19+Udo+depUxMTEqH0IdPHiRURGRuL27dswMjKCg4MDBg0aVGQpE8bnDxt5YzAYjI8UdgoeQ3ekpqZi9OjROHz4MAwNDREQEIAxY8bgp59+wpIlS+Dk5ITQ0FCt9in0LPPJkyfYsWMHbt++DY7jYG9vj169eqFy5coa+27evLnWEzVNSU9Ph6+vL06fPo02bdpgw4YN8PPzw9q1a8FxHP73v/9h7969gk/1x40bh06dOqFLly54/PgxOnTogDt37qB8+fJ4+fIl6tSpg7/++qtQrweDUZI0bNgQu3btEvxM/vnnn2jYsKFKH2PGjIGnpyeqVKkCX19f2QOM/CnRy5cvx5YtW1T6mDJlCpYsWQJzc3PUrFkTRIQjR45g8eLFCAwMxNSpU5GVlYW///5brSwJ4wuiOBXBGQwG43PC19eXXrx4UdJhfJb4+vpSlSpVaNKkSeTk5EQ8z5Orqyu5uLjQyZMnddKnubk5JSYmyh1bvXo1GRsbE8dxVLp0abKysiKO48jY2JhWr16t1ufChQspMzNTth8dHU1ZWVmy/bS0NPL19dXaNVhYWBS4hjFjxlDt2rVp1apV1KZNG+rRowc5OzvTmTNn6NSpU+Ts7EzTp08X9FmxYkWKj48nIqK+fftS+/btZe/7f//9l7p27UoeHh5auwYGQ9ds376dDAwMKCgoiLKzs2XHs7OzadWqVWRoaEjbtm1T62f69OnEcRxZWlpSgwYNqGHDhmRpaUk8z9PUqVNV2oaHh5OJiQkFBQXR+/fvZcffv39PK1euJFNTU4qKiqI2bdrQvHnzin6xjM8OlrwxGAxGEVF2o8zQDtWqVaMjR44QEVFiYiJxHEfjx4/XaZ+Kydu+fftIIpHQpEmT6OnTp7LjT58+JT8/PzIwMKD9+/er9MnzPCUnJ8v2Fd8zUqmUeJ7X2TUQEVWtWpWOHz9ORERPnjwhjuNoz549svb9+/eTg4ODoE8TExO6d+8eERFVqVKFLly4INd+/fp1Kl++vLYugcEoFsQkXp9y4cIFGjduHLm5uZGrqyuNHz++wGdEGU2aNKFly5YJti9dupR4nqdGjRrRq1evNI6H8fnDpk0yGAxGESG2ZFhnPH36VLbmo2bNmjAxMYGPj0+xxrBo0SIEBARg/vz5cscrVqyIZcuWwczMDAsXLoSbm5ugD8X3iLbfM0SEFy9eyCqkxsfHo1KlSnLnPH/+HLVq1QIAVKpUCaampnKi205OTkhKShLsw97eHjExMahRowYsLCwKVM9LT08voC3HYOg7gYGB6NGjBzZv3oy7d++CiNC6dWsMGDCgULqFTZs21ej8UaNGYe7cuTK5kxs3bqBHjx6C57u7u8Pf3x/Hjh1D6dKlNY6H8fnDRLoZDAaDoXfk5ubC0NBQti+RSGRVIIuLq1evYtCgQYLtgwYNwpUrV3Qag5mZGV68eCHb79y5M549eybbf/78OSpWrCjbr1q1aoHiIeXKlZPz0aNHD7mbwYyMDBgbGwvG4OfnB39/f5w8eRLTpk3DuHHjcOzYMTx9+hQnTpzADz/8gF69eom5TAajRGjatClWrlyJ/fv348CBA1ixYoXSRGzUqFGCkiKa8vvvv8s9+JBIJHj//r3g+R8+fIC5uTlL3BgFYCNvDAaDwdA7iAje3t6ypCIrKwsjR44skMDt3LlTa31Wr15dLmFUTCAVMTQ01Pnoa1ZWllwfZ8+eLVBhU10M9erVw8WLF9GoUSMAKFBE4eLFi3B0dBS09/b2xqtXr9ClSxcQEXJyctCxY0dZe/fu3bF8+XKNr4nB+K/x+++/w9/fXzZqVhQUP6fffPMNNm/ejHnz5ik9f9OmTbLPLIPxKSx5YzAYDIbe8f3338vte3l5ab2PZ8+eITAwEL/++isA4J9//pFrd3Jywu7du+Hn56fUfteuXXByclLbT3BwMMzNzQHkldkPDw+X3QR+qh9YVNSJmW/evFml3lSFChUQGBio0sfEiRMxdOhQHDlyBPfu3UNubi4qVqyIli1bqtTLYjA+B3TxkGbSpElwd3fHu3fvMGnSJFSoUAFAnhTK0qVLsWLFCq0+nGJ8PrDkjcFgMBh6R1hYmFb8xMfH48SJEzA0NETfvn1RunRpvHz5EoGBgVi3bh1q1KghaDtq1Cj4+vrC2NgYI0aMgIFB3k9mdnY21q9fjx9//BFr1qxR2X+1atWwYcMG2b6NjY2cMHj+ObqkbNmyKttdXV3l9hXX5uRTunRp9OnTR21/QvYMBuP/6dq1K5YvXw5/f38sXboUVlZWAIDXr19DIpFg8eLF6NatWwlHydBHmEg3g8FgFBFfX1/MmzeP3aTqKfv27UPv3r3x4cMHAHmFTzZs2IC+ffvC2dkZkyZNQteuXVX68Pf3x7Jly2BhYYGvv/4aAJCYmIiMjAyMGzdOK9MFnzx5IqiRJpFIIJVKYW1tDSBPSDw2NlaWdCYnJ6NSpUpaFY4XK1auS7FzBqMksLCwQGxsrKj3tJCPx48fY9u2bbhz5w4AwM7ODh4eHqhataqomBmfLyx5YzAYjI88evRIo/N0PVLC0A4tWrRA06ZNERgYiN9++w3+/v6ws7PDhg0b0Lp1a439nD9/HpGRkbKbK3t7e3h6eooW3ZZKpViwYAE2bNhQYB1bPjzPw8rKSjY1MjU1FZaWlrJpkESEtLQ0rSZvYm9UtXGjy2DoE7pM3hiMwsKmTTIYDMZHbG1tla4fIiLZcY7jkJ2dXdyhMYpAQkICIiIiYG5ujnHjxmHKlClYsWJFoRI3AGjevHmRE7XU1FSMHj0ahw8fhqGhIQICAjBmzBj89NNPWLJkCZycnBAaGipor63powwGo2Tx8vKCpaWlbH/UqFFYtGiRbD3spk2b0LNnT9l+amoqBgwYgAMHDpRIvAz9hY28MRgMxkdiY2OVHici/PHHH1i1ahXMzc3x/PnzYo6MURR4nodUKpVpoFlYWODatWuy6Y/qiIuL0+i8evXqCbaNGjUKe/fuRb9+/XDw4EEkJCSgU6dOyMrKwuzZs/Hdd9+p9J2dnS1ba1dcsJE3BkMeVVPkL168iMjISNy+fRtGRkZwcHDAoEGDZDqVQkgkEjx79kz2/aQ43VgXU6IZnwds5I3BYDA+Ur9+/QLHjh49ioCAANy+fRtTpkyBv79/CUTGKCrx8fGQSqUA8pLwW7du4c2bN3LnCCVfDRo0AMdxKivNcRyn8uZq//79CAsLQ/v27TFq1CjUqlUL9vb2WLFihUbxV6pUCYMHD8awYcNUlvNnMBiFR9PEa+3atUrtp0yZgiVLlsDc3Bw1a9YEEeHIkSNYvHgxAgMDMXXqVGRlZeHvv/+Gi4uLnK3i9wobS2FoCkveGAwGQwmXL19GQEAATp8+DR8fHxw4cED2hJTx36Fdu3ZyN0X5BUrykzJVydf9+/dF9//06VPZjWDNmjVhYmICHx8fje39/PwQHh6O5cuXo2nTpvDx8UG/fv1kU6sYDEbREJN4AUBERASCgoKwatUq/PDDDzJNyA8fPmDt2rUICAhAjRo1sHbtWrRr106pDwajKLDkjcFgMD7h7t27mDFjBnbs2IG+ffsiPj6eTf/6jyI2+apevbroGBSFviUSSQGhcVVMmzYN06ZNw+nTpxEaGooJEyZgwoQJ8PDwgI+PD1q2bCk6RkUU1+YUtz2DoWu0kXitXr0aCxYswJgxY+SOGxoaYty4ccjOzkb//v3RoEEDjB49uliui/FlwNa8MRgMxkdGjRqFkJAQuLi44JdffkGDBg1KOiRGCZOWliZLRA4cOCBXrEYikaBLly4q7Xmeh6urK4yNjQEAe/fuRdu2bQskcJqK8b558wZ//PEHwsPDcfbsWdjZ2WHYsGGYMmWKoM3gwYOxevVqWFhYAMhb21mnTh25pFIVYu0ZDH2jadOm6N+/P/z8/JS2L1u2DJMnT0aDBg1w9OhRlClTpsA5pUqVwvXr1wUf7t27dw+1atXCq1evULp06QLtPM9jxIgRMDMzA5CXDHp5ecn03jIzM7Fhwwa25o1RAJa8MRgMxkd4noeJiQlq166t8rwrV64UU0QMMZw6dUrpcSsrK9SqVUvtCNi+ffswc+ZMXL16FUBeIY5P18txHIeoqCh4eHgI+hgyZIhGsRalquT+/fsxePBgpKamqrzBU1cYQR1i7RkMfUNs4gXkfQ5iYmIEfy9u3bqFJk2aIC0tTWl7mzZtlFY3VuTEiRNqz2F8WbBpkwwGg/GR2bNnl3QIDC3Spk0bwTaJRAJfX18sXbpUcATpt99+KzAl6u7du7IbvkWLFiE0NFRl8qbtUv+ZmZmIiopCWFgYzp49i6+//hqTJ09WaSO2MAIrrMD43JBIJHj//r1g+4cPH2Bubi6YuAHAN998g82bN2PevHlK2zdt2oRGjRoJ2p88eVLTcBkMOVjyxmAwGB9hydvnRUpKitLjqampiImJweTJk2FjY4Pp06crPS8uLg6zZs0S9O/q6oolS5ZoJVZ1nD59GmFhYdi+fTtycnLg4eGB+fPnF1qzjsFgiE+8AGDSpElwd3fHu3fvMGnSJFSoUAEAIJVKsXTpUqxYsULj6dBCXLx4EU2aNBHlg/H5wZI3BoPBUEJcXBxu374NjuNgZ2enUsuLoZ/krx1Rdrx69eowMjLC9OnTBZM3qVSKcuXKyfZPnDiBqlWryvbNzc3x+vVr7QatwIIFCxAeHo7ExEQ0btwYixcvRv/+/QtdEERRMuHmzZvIyMiQO0fVe1ysPYOhT2gj8eratSuWL18Of39/LF26VPZ98/r1a0gkEixevBjdunVTG0tGRgYkEglMTU1lx65du4aZM2fiwIEDbM0bowBszRuDwWB8QkxMDIYNG4b4+HjZ9DCO4+Dk5ISQkBD2FPQz4sGDB3B2di6QhORTqVIlbNy4Ee3bt1fafvjwYXz//fd49uyZzmK0traGl5cXhg0bBmdn5yL54HleUK9OE8kEsfYMhj4SFBQEf39/ZGdnF0i8Fi1ahAkTJmjk5/Hjx9i2bRvu3LkDALCzs4OHh4fcgx4hu379+uH8+fOQSCQYM2YM5s+fj5EjRyIyMhI9evTApEmT0KJFC1HXyfj8YMkbg8FgfCQ+Ph7NmjWDo6Mj/Pz84OjoCCJCQkICli9fjlu3buH8+fMFBFwZ/03OnTsHLy8v3Lt3T2m7p6cnMjMzsWfPHqXtXbt2RalSpRAVFaWzGD98+CC6quPDhw81Ok9IGkGsPYOhrxQ18dIGXl5euH79OoYPH44dO3bg1KlTaNCgAerXr4+ZM2eiRo0aOo+B8d+EJW8MBoPxkT59+iAnJwc7duwoUAWMiNCrVy8YGhpi69atJRQhQ1s8f/4cnp6eqFmzJoKDg5Wec/XqVbRo0QLdunXDlClTYG9vDyCvitzChQuxf/9+nDt3Tu3aGDGsWrVKo/PGjRunsxgYDEZBRo0ahUWLFsHc3BxA3jq5nj17yvZTU1MxYMAAHDhwQKl95cqVsXXrVrRs2RJSqRSVKlXCggULEBAQUGzXwPhvwpI3BoPB+Ii1tTX++usvNG7cWGn7xYsX4ebmhhcvXhRzZIyi0LBhQ6WluF+/fo3Hjx/D0dERhw8flpXAV8bu3bvh4+ODV69eyR0vU6YMgoOD4e7uru2w5dDk6TvHcYKjh0BeVcyxY8fK1tScOnUKzZo1k2nPpaenY+rUqVizZo1O7BkMfUNs4gWol9BITk5GpUqVBKcTSyQSPHnyBDY2NgDy5AsuXboER0dHrV0n4/OEJW8MBoPxERMTE9y5c0dwykxSUhLs7OyQlZVVzJExisKcOXOUHre0tETt2rXRsWNHSCQStX4yMzNx6NAhualVHTt2VKsTVxw8evQIP/30E0JDQwXP0cZNphh7BkPf0MZ7mud5SKVSmQ8LCwvExsYW6nMllUphbW0ts4+Li2PTJRlqYdUmGQwG4yO2traIiYkRTN4uXLjA1vX8h9CW9IOZmRl69uypFV/aJiUlBRERESqTN6bzxmDIow/vaSJCu3btYGCQdyv+9u1bdOvWDUZGRnLnXblypdhjY+g3LHljMBiMj/Tr1w8TJ06Eg4NDgcp+169fh7+/P77//vsSio5RVN6+fYsjR47IpB/s7e3Rvn17udLcynBzc0NkZKSsEl1gYCBGjx4tE+79999/0apVK8THx+v6EhgMxmeG4sOlHj16lFAkjP8aLHljMBiMj0ybNg1Hjx5FgwYN0KFDB9nag/j4eBw9ehRNmzbFtGnTSjhKRmHYs2cPfHx88PLlS7nj5cuXR0hIiEodpkOHDuHdu3ey/YULF6J///6y5C07Oxu3bt3SSdwMBkP/mTVrFszMzAAA79+/R2BgoOxhT2Zmpkrbws4MOHv2LBo3bixba8r4cmHJG4PBYHzExMQEJ06cwPLlyxEZGYno6GgAgL29PebPnw8/Pz/2w/kf4ty5c/Dw8ED37t0xadIkuWR86dKl8PDwwMmTJwV1lPRhapW2CA4OlhVjyM7ORnh4OMqXLw8gr+CIru0ZDH1DTOIFAK1bt5Z7ePPtt98WKBzUunVrrcXr6uoqty6P8eXCCpYwGAwG47PEzc0NVatWxfr165W2//DDD0hKShKsKCe2IIE26NWrl8r21NRUREdHq4zB1tZWadVNRe7fv68TewZD32jTpo1G7+kTJ04UQzSaofj9w/hyYSNvDAaDwfgs+fvvv7Fw4ULB9tGjR+O7774TbOc4rsANniY3fNokfyRAVfvgwYNVnvPgwQNRMYi1ZzD0jZMnTxZLPxcvXkSTJk2KpS/GlwNL3hgMBuMjZcqU0ejmXFHzi6GfZGVlwdLSUrDdyspKbk2bIkQEb29v2VTZrKwsjBw5UiYRoMpWW4SFhWnFT25uLsLDw7Fz5048ePAAHMehZs2a6N27NwYNGqT2fS/WnsH4r6Fp4pWRkQGJRCJXAOnatWuYOXMmDhw4wCQ0GFqHJW8MBoPxkRUrVpR0CAwtYm9vj+PHj2PIkCFK248dO4ZatWoJ2itWFvXy8ipwjrpRL32AiNCtWzf89ddfqF+/PurWrQsiQkJCAry9vbFz507s2rVLZ/YMhr4iJvF6/Pgx+vXrh/Pnz0MikWDMmDGYP38+Ro4cicjISPTo0QNnzpwpjstgfGkQg8FgMBifIcuWLaOyZcvS/v37C7Tt27ePypUrR8uWLSuByIqX0NBQsrCwoOPHjxdoO3bsGFlYWFBERITO7BkMfSMpKYm+/fZb4nmeDA0Nyc/Pj968eUODBg0iAwMD6t27N507d06lj4EDB1K9evUoKCiI2rRpQzzPU6NGjWjIkCF07949rcdsYWFBiYmJWvfL+O/BCpYwGAyGAOnp6XIVBnmel1XcY+g/ubm56NevH3bs2AEHBwe5apN37tyBu7s7tm3bBp7ni9zH9u3b4eHhoa2QdULHjh3Rtm1bBAQEKG1fsGABoqOjcejQIZ3YMxj6hpeXF65fv47hw4djx44dOHXqFBo0aID69etj5syZqFGjhloflStXxtatW9GyZUtIpVJUqlQJCxYsEPycKPLo0SNUrVpV4ynHrGAJIx+WvDEYDMZHrl27hhkzZmD//v0A8n4sPy0ZzXEc/v77b7YA/T9GVFQUtmzZgjt37gDIm07p6ekJT09Ptbb5Wm6Ghoawt7eXHd+9ezdmzZqFmzdvFsvaNzHY2Njg4MGDaNCggdL2q1evwtXVFVKpVCf2DIa+ITbxAgCJRIInT57AxsYGAFCqVClcunRJ9pBIE/tnz57JqtkyGJrC1rwxGAzGR4KCgvC///1P7timTZtQuXJlEBFCQ0OxatUqbNq0qYQiZBSGtLQ0AHn6SK6uroLtQkVN4uPj0bVrVzx8+BAA0KNHD6xduxZ9+/ZFbGwsfHx8sG/fPh1Frz1evXqFChUqCLZXqFABKSkpOrNnMPQNqVSKr7/+GkDewwlTU1P06NGj0H4kEonsb57nYWJiorEtGzthFBWWvDEYDMZHzp49C29vb7ljzZs3l01TMTU1Rd++fUsgMkZRKF26tMopSUQEjuMEixIEBASgRo0aWLVqFTZv3oyoqCj8888/8PLywr59+2BhYaGr0LVKTk4ODAyEf+4lEgmys7N1Zs9g6CNiEi8g7/ujXbt2ss/G27dv0a1bNxgZGcmdd+XKFfHBMhifwJI3BoPB+EhSUhKqVasm2587dy7Kly8v269YsSKSk5NLIjRGEfhUYJeI4ObmhuDgYFSuXFkj+5iYGBw4cACNGjXC//73P0RFRWHy5MkYPny4rkLWCaQgeaCIummfYu0ZDH1DG4nX7Nmz5faLMnIXHBysdh31uHHjCu2X8XnD1rwxGAzGR8qWLYu9e/eiZcuWStvPnj2Lbt26MZ23/yiFXfDP8zyePXsmmzJobm6OK1euyK19+y8gJJWgiJCmnFh7BkPfmDNnjkbnKSZoYjh79iwaN24sewjC8zyqVKkiNwKoCMdxuHfvntZiYHwesOSNwWAwPtKuXTs0atQIixcvVto+adIkXLt2DceOHSvmyBjaoLDJm0QigVQqhbW1NYC8tXGxsbEaVaJjMBifD4qJV1GwtLTEtWvXZN8/PM9DKpWygiWMQsOmTTIYDMZHRo0aBU9PT9ja2sLX11dWQj4nJwdr1qxBUFAQtmzZUsJRMooLIoK9vb1s3VxGRgYaNmxYQFqAjcQyGJ83rq6ucolXUVAcK9FUIoDBUIQlbwwGg/GR3r17Y+LEiRg7diymT5+OmjVrguM4JCYmIiMjAxMnTtR7TS+Gagpzw8SmATIYDEA3lSHZxDdGUWHJG4PBYHzCwoUL0bNnT0RGRsp0wVq1aoX+/fujefPmJRwdozD06tVLbj8rKwsjR45EqVKl5I7v3LlTqf33339fqP4iIyPRvXv3Av4ZDAZDkdmzZ6stVsJgKIOteWMwGAzGZ0lxF9pQXNPCYDA+Dwq7XlYTH48ePdLI7tMKyAwGwEbeGAwGQ8aiRYswduxYmJqaAgBOnTqFZs2ayRapp6enY+rUqVizZk1JhsnQkOKe9siehTIYDCEUp2x/Wvgo/7vj03PU6VAyvlzYyBuDwWB8RCKR4NmzZ7LqX4ojKcnJyahUqRL7MWUoRRtP5xkMhv6hbFT90aNHqFq1qsbraBW/HwwMDFClShV4e3ujW7duMs05RerXry/+AhifFWzkjcFgMD6i+CyLPdtiMBiMz4/CJl7Kfgtq1Kgh97BPHenp6XL7jx8/RkREBMLDw7Fu3Tp4eXlh2LBhcHR01Mgf48uFV38Kg8FgMBgMBoPxeVCjRg28ePFC4/PT09MLjKiLfbhnY2ODqVOnIiEhAdu3b0dKSgqaNWuG5s2bY8OGDcjNzRXln/H5wpI3BoPBYDAYDMYXg77Nqvjf//6HkJAQ3LlzB2ZmZhg5ciRSU1NLOiyGnsKmTTIYDMYnBAcHy8o3Z2dnIzw8HOXLlwdQcNoLg/Ep1atXh6GhYUmHwWAwiolPfy+EGDdunFo/586dQ2hoKLZt2wYHBwesXr0apUuX1lKUjM8NVrCEwWAwPmJra6vRGoj79+8XQzQMfSM9PV3uiT3P80ynicH4D8LzPObPny8q8eJ5HlWqVIFEIhE8h+M43Lt3T2nbs2fPsHHjRoSFhSElJQUDBw7EsGHD4OTkpNlFML5YWPLGYDAYheDJkyeoXLlySYfBKAauXbuGGTNmYP/+/QDyqsVlZmbK2jmOw99//40mTZqUVIgMBqMIiE288n1IpVKNC5YoYmRkhEqVKuH7779H9+7dBUft69WrVyT/jM8XlrwxGAyGBkilUixYsAAbNmzA27dvSzocRjEwbNgw1KpVC9OmTQOQl7ytX78elStXBhEhNDQURIRNmzaVcKQMBqMwiE28gILSMkWJIZ/8GR+Kt+RM542hDLbmjcFgMD6SmpqK0aNH4/DhwzA0NERAQADGjBmDn376CUuWLIGTkxNCQ0NLOkxGMXH27Fl4e3vLHWvevLms6pypqSn69u1bApExGAwxaCoRoAqxYx+aTL9PSUkR1Qfj84QlbwwGg/GR6dOn49SpU/j+++9x8OBB+Pn54eDBg8jKysJff/2F7777rqRDZBQjSUlJqFatmmx/7ty5suI1AFCxYkUkJyeXRGgMBkME2ph0Nnv2bFFrXqtXr670+OvXr7F582aEhITg2rVrbOSNUQCWvDEYDMZH9u/fj7CwMLRv3x6jRo1CrVq1YG9vjxUrVpR0aIwSwNjYGI8fP5bdZPn5+cm1JyUlwczMrCRCYzAYIhCbeAHAkCFD8PLlS7XnffoASBXHjx9HaGgodu7cierVq6N3794IDg4WFSPj84QlbwwGg/GRp0+fok6dOgCAmjVrwsTEBD4+PiUcFaOkaNiwIXbt2oWWLVsqbd+5cycaNmxYzFExGAyxaCPxqlGjhuzv/JG8T6djEpHaNWuPHz9GeHg4QkND8ebNG/Tt2xcfPnzAjh07ZL9FDIYiLHljMBiMj+Tm5spV/JJIJChVqlQJRsQoSUaNGgVPT0/Y2trC19dXVmAgJycHa9asQVBQELZs2VLCUTIYjMKijcSL4zhUqVIF3t7e6NatGwwMCndL7ebmhjNnzqBr164ICgpC586dIZFIsG7dukJeDeNLg1WbZDAYjI/wPA9XV1cYGxsDAPbu3Yu2bdsWSOB27txZEuExSoCpU6di8eLFsLCwQM2aNcFxHBITE5GRkYGJEydi8eLFJR0ig8EoJAYGBholXvXr1xf0IZVKERERgfDwcKSkpMDLywvDhg2Do6OjxjGMGzcOvr6+sLOzkx03NDREbGwsG3ljCMKSNwaDwfjIkCFDNDovLCxMx5Ew9In/a+9+Qpr+4ziOv3BYsFxUpIevB0vSxCIKhAoCIehQgRchGSLSJv07CNGtgxB4kAgPaafcZ1JEI8nDRiQGQioaO1lBEB5KsDbxsIkphc5+B/lJ9vvW2tx+a/p83NTv97PXFzzstc/4vF+9eqXHjx9rcnJSklRRUSG3260TJ07kOBmAdGy0eP1sdHRUfr9ffX19qq6ultfrldfrXTcO4Gfj4+MyxujJkyeqqqpSU1OTGhoaZFkW5Q2/RXkDAADAlpRO8fqVmZkZud1uvXz5UrOzs9qzZ0/SexYXFxUIBGSMUTgcViKRUGdnpzwej1wuVzqPhE0u9f9MAAC2gNu3b68byD48PKxv376t/Tw/P69r167lIhqADDl16pR8Pp8mJyfldDp15coVxePxlNYYGxtTS0uLKisr9eXLF927d0+7du36o3udTqc8Ho9GR0f19u1b3bhxQx0dHSopKVFdXV3qD4RNj503AABsOBwORSIRlZSUSJJ27typiYmJtSHdMzMzsiyLOUxAHhsbG5MxRn19fTp48KA8Ho8uXbqUdOctEonowYMH8vv9isViamxslNfr1aFDhzacKZFIKBQKyRijYDC44fWwuVDeAACwUVBQoGg0ulbeXC6XXr9+TXkD8lwmite2bdtkWZaam5tVV1e37qTiHx05ciRTsQFJlDcAAGxR3oDNKRPF68eduX/HDPz8ljrZuAEgHZQ3AABsUN6AzSkTxWtqairp68RiMR09ejS9kMAvMKQbAIBf6OnpUVFRkSRpeXlZvb292rt3r6TVA0sA5J8PHz4kvSYWi/3272VlZba/n5ub06NHj+Tz+TQxMcGHO8g4dt4AALCxb9++tU/lf+dP3ggC+PttpHgNDQ3JGKP+/n6VlZWpvr5e9fX1OnbsWBYTYyti5w0AABsfP35Mes2nT5+yHwRAVtkVr56enqT3TU9Pq7e3V8YYLSws6MKFC1paWtLTp08Zso2sYc4bAAApikajam1t1YEDB3IdBUAapqen1d7ervLycrndbu3evXuteLW3tyfdMTt37pyqq6v17t07dXV16fPnz+rq6vqf0mMro7wBAGAjHo+rsbFRxcXFsixLd+/e1crKitra2lReXq7x8XEZY3IdE0CKMlG8BgcH1dLSolu3bun8+fNyOBxZSgusx9cmAQCwcfPmTQ0PD6u5uVkDAwO6fv26BgYG9PXrVz1//ly1tbW5jgggDYODg2ptbdXVq1dVUVGR1hojIyMyxqimpkZVVVVqampSQ0NDhpMC/8XOGwAANp49eya/3687d+4oGAzq+/fvqqys1NDQEMUNyGMjIyOan59XTU2Njh8/ru7ubs3Ozqa0xsmTJ3X//n1FIhFdvnxZgUBApaWlWllZ0YsXLziNFlnDaZMAANgoLCzU1NSULMuSJDmdToXDYR0+fDjHyQBkwuLiogKBgIwxCofDSiQS6uzslMfjkcvlSnm99+/fy+fz6eHDh4rH4zpz5oyCwWAWkmMro7wBAGDD4XAoGo2quLhY0uqQ7jdv3mj//v05TgYg0zJZvBKJhEKhkIwxlDdkHOUNAAAbBQUFOnv2rLZv3y5JCoVCOn36tHbs2LHuuv7+/lzEA5AFFC/87ShvAADYuHjx4h9d5/f7s5wEAIBVlDcAAAAAyAOcNgkAAAAAeYDyBgAAAAB5gPIGAAAAAHmA8gYAAAAAeYDyBgAAAAB5gPIGAAAAAHmA8gYAAAAAeeAf4TPpa0XVadEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrmat = application_data.corr() \n",
    "  \n",
    "f, ax = plt.subplots(figsize =(8, 8)) \n",
    "sns.heatmap(corrmat, ax = ax, cmap =\"rainbow\") \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#relationship between numeric variables \n",
    "plt.scatter(application_data['DAYS_EMPLOYED'], application_data['AMT_CREDIT'])\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.        , -0.06683834],\n",
       "       [-0.06683834,  1.        ]])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.corrcoef(application_data['DAYS_EMPLOYED'], application_data['AMT_CREDIT'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The value of 0.002 shows a positive but weak linear relationship between the two variables. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinregressResult(slope=-0.1904205968037303, intercept=611177.698831808, rvalue=-0.0668383409309217, pvalue=2.2768790470443978e-301, stderr=0.005126100259994974, intercept_stderr=794.6470204294436)"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import linregress\n",
    "linregress(application_data['DAYS_EMPLOYED'], application_data['AMT_CREDIT'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Unnamed: 0', 'SK_ID_CURR', 'TARGET', 'NAME_CONTRACT_TYPE', 'CODE_GENDER', 'FLAG_OWN_CAR', 'FLAG_OWN_REALTY', 'CNT_CHILDREN', 'AMT_INCOME_TOTAL', 'AMT_CREDIT', 'AMT_ANNUITY', 'AMT_GOODS_PRICE', 'NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', 'REGION_POPULATION_RELATIVE', 'DAYS_BIRTH', 'DAYS_EMPLOYED', 'DAYS_REGISTRATION', 'DAYS_ID_PUBLISH', 'FLAG_MOBIL', 'FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 'FLAG_PHONE', 'FLAG_EMAIL', 'CNT_FAM_MEMBERS', 'REGION_RATING_CLIENT', 'REGION_RATING_CLIENT_W_CITY', 'WEEKDAY_APPR_PROCESS_START', 'HOUR_APPR_PROCESS_START', 'REG_REGION_NOT_LIVE_REGION', 'REG_REGION_NOT_WORK_REGION', 'LIVE_REGION_NOT_WORK_REGION', 'REG_CITY_NOT_LIVE_CITY', 'REG_CITY_NOT_WORK_CITY', 'LIVE_CITY_NOT_WORK_CITY', 'ORGANIZATION_TYPE', 'OBS_30_CNT_SOCIAL_CIRCLE', 'DEF_30_CNT_SOCIAL_CIRCLE', 'OBS_60_CNT_SOCIAL_CIRCLE', 'DEF_60_CNT_SOCIAL_CIRCLE', 'DAYS_LAST_PHONE_CHANGE', 'FLAG_DOCUMENT_2', 'FLAG_DOCUMENT_3', 'FLAG_DOCUMENT_4', 'FLAG_DOCUMENT_5', 'FLAG_DOCUMENT_6', 'FLAG_DOCUMENT_7', 'FLAG_DOCUMENT_8', 'FLAG_DOCUMENT_9', 'FLAG_DOCUMENT_10', 'FLAG_DOCUMENT_11', 'FLAG_DOCUMENT_12', 'FLAG_DOCUMENT_13', 'FLAG_DOCUMENT_14', 'FLAG_DOCUMENT_15', 'FLAG_DOCUMENT_16', 'FLAG_DOCUMENT_17', 'FLAG_DOCUMENT_18', 'FLAG_DOCUMENT_19', 'FLAG_DOCUMENT_20', 'FLAG_DOCUMENT_21', 'AMT_REQ_CREDIT_BUREAU_HOUR', 'AMT_REQ_CREDIT_BUREAU_DAY', 'AMT_REQ_CREDIT_BUREAU_WEEK', 'AMT_REQ_CREDIT_BUREAU_MON', 'AMT_REQ_CREDIT_BUREAU_QRT', 'AMT_REQ_CREDIT_BUREAU_YEAR']\n"
     ]
    }
   ],
   "source": [
    "columns_appdata = list(application_data.columns)\n",
    "print(columns_appdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the p-value of 0.2341 is greater than 0.05, we accept the null hypothesis that there is no relationship between the Number of children the client has and Credit amount of the loan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>TARGET</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>N</th>\n",
       "      <td>86357</td>\n",
       "      <td>7842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>196329</td>\n",
       "      <td>16983</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "TARGET                0      1\n",
       "FLAG_OWN_REALTY               \n",
       "N                 86357   7842\n",
       "Y                196329  16983"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#relationship between categorical variables\n",
    "pd.crosstab(application_data.FLAG_OWN_REALTY, application_data.TARGET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output above shows that applicants with their own house of aparment have a lower probability of defaulting on their loans or having payment difficulties than those without their own house or apartment. To test whether this insight is statistically significant or not, we use the chi-square test of independence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(11.57582729808418,\n",
       " 0.0006681470317545887,\n",
       " 1,\n",
       " array([[ 86594.42593598,   7604.57406402],\n",
       "        [196091.57406402,  17220.42593598]]))"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import chi2_contingency\n",
    "chi2_contingency(pd.crosstab(application_data.FLAG_OWN_REALTY, application_data.TARGET))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The second value of the above output — 0.0006681470317545887 -— represents the p-value of the test. \n",
    "As evident, the p-value is less than 0.05, hence we reject the null hypothesis that there is a relationship between applicants having their own house and having payment difficulties or defaulting on their payments.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This clearly shows that customers with an educational background or higher degrees have a much lower probability of defaulting on their payments, than those with a lower educational status such as Secondary / secondary special."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###FOR ALL VARIABLES TOGETHER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Business Entity Type 3\n",
       "1                         School\n",
       "2                     Government\n",
       "3         Business Entity Type 3\n",
       "4                       Religion\n",
       "                   ...          \n",
       "307506                  Services\n",
       "307507                       XNA\n",
       "307508                    School\n",
       "307509    Business Entity Type 1\n",
       "307510    Business Entity Type 3\n",
       "Name: ORGANIZATION_TYPE, Length: 307511, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "application_data.ORGANIZATION_TYPE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Unnamed: 0', 'SK_ID_CURR', 'TARGET', 'NAME_CONTRACT_TYPE', 'CODE_GENDER', 'FLAG_OWN_CAR', 'FLAG_OWN_REALTY', 'CNT_CHILDREN', 'AMT_INCOME_TOTAL', 'AMT_CREDIT', 'AMT_ANNUITY', 'AMT_GOODS_PRICE', 'NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', 'REGION_POPULATION_RELATIVE', 'DAYS_BIRTH', 'DAYS_EMPLOYED', 'DAYS_REGISTRATION', 'DAYS_ID_PUBLISH', 'FLAG_MOBIL', 'FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 'FLAG_PHONE', 'FLAG_EMAIL', 'CNT_FAM_MEMBERS', 'REGION_RATING_CLIENT', 'REGION_RATING_CLIENT_W_CITY', 'WEEKDAY_APPR_PROCESS_START', 'HOUR_APPR_PROCESS_START', 'REG_REGION_NOT_LIVE_REGION', 'REG_REGION_NOT_WORK_REGION', 'LIVE_REGION_NOT_WORK_REGION', 'REG_CITY_NOT_LIVE_CITY', 'REG_CITY_NOT_WORK_CITY', 'LIVE_CITY_NOT_WORK_CITY', 'ORGANIZATION_TYPE', 'OBS_30_CNT_SOCIAL_CIRCLE', 'DEF_30_CNT_SOCIAL_CIRCLE', 'OBS_60_CNT_SOCIAL_CIRCLE', 'DEF_60_CNT_SOCIAL_CIRCLE', 'DAYS_LAST_PHONE_CHANGE', 'FLAG_DOCUMENT_2', 'FLAG_DOCUMENT_3', 'FLAG_DOCUMENT_4', 'FLAG_DOCUMENT_5', 'FLAG_DOCUMENT_6', 'FLAG_DOCUMENT_7', 'FLAG_DOCUMENT_8', 'FLAG_DOCUMENT_9', 'FLAG_DOCUMENT_10', 'FLAG_DOCUMENT_11', 'FLAG_DOCUMENT_12', 'FLAG_DOCUMENT_13', 'FLAG_DOCUMENT_14', 'FLAG_DOCUMENT_15', 'FLAG_DOCUMENT_16', 'FLAG_DOCUMENT_17', 'FLAG_DOCUMENT_18', 'FLAG_DOCUMENT_19', 'FLAG_DOCUMENT_20', 'FLAG_DOCUMENT_21', 'AMT_REQ_CREDIT_BUREAU_HOUR', 'AMT_REQ_CREDIT_BUREAU_DAY', 'AMT_REQ_CREDIT_BUREAU_WEEK', 'AMT_REQ_CREDIT_BUREAU_MON', 'AMT_REQ_CREDIT_BUREAU_QRT', 'AMT_REQ_CREDIT_BUREAU_YEAR']\n"
     ]
    }
   ],
   "source": [
    "print(columns_appdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_columns = ['SK_ID_CURR', 'TARGET', 'NAME_CONTRACT_TYPE', 'CODE_GENDER', 'FLAG_OWN_CAR', \n",
    "                       'FLAG_OWN_REALTY', 'NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', \n",
    "                       'FLAG_MOBIL', 'FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 'FLAG_PHONE', 'FLAG_EMAIL', 'ORGANIZATION_TYPE']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cat = application_data[categorical_columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(306219, 18)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat_v1 = df_cat.dropna()\n",
    "df_cat_v1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_var1 = ('TARGET', 'NAME_CONTRACT_TYPE', 'CODE_GENDER', 'FLAG_OWN_CAR', \n",
    "                       'FLAG_OWN_REALTY', 'NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', \n",
    "                       'FLAG_MOBIL', 'FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 'FLAG_PHONE', 'FLAG_EMAIL', 'ORGANIZATION_TYPE')\n",
    "cat_var2 = ('TARGET', 'NAME_CONTRACT_TYPE', 'CODE_GENDER', 'FLAG_OWN_CAR', \n",
    "                       'FLAG_OWN_REALTY', 'NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', \n",
    "                       'FLAG_MOBIL', 'FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 'FLAG_PHONE', 'FLAG_EMAIL', 'ORGANIZATION_TYPE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_var_prod = list(itertools.product(cat_var1,cat_var2, repeat = 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.stats as ss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating an empty variable and picking only the p value from the output of Chi-Square test\n",
    "result = []\n",
    "for i in cat_var_prod:\n",
    "    if i[0] != i[1]:\n",
    "        result.append((i[0],i[1],list(ss.chi2_contingency(pd.crosstab(\n",
    "                            df_cat_v1[i[0]], df_cat_v1[i[1]])))[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TARGET', 'NAME_CONTRACT_TYPE', 1.3210821346035907e-66),\n",
       " ('TARGET', 'CODE_GENDER', 5.7018951392156825e-202),\n",
       " ('TARGET', 'FLAG_OWN_CAR', 2.0162941238237494e-33),\n",
       " ('TARGET', 'FLAG_OWN_REALTY', 0.00022554903355310722),\n",
       " ('TARGET', 'NAME_TYPE_SUITE', 1.1329313903575907e-05),\n",
       " ('TARGET', 'NAME_INCOME_TYPE', 4.977160476319552e-267),\n",
       " ('TARGET', 'NAME_EDUCATION_TYPE', 2.048550759970049e-218),\n",
       " ('TARGET', 'NAME_FAMILY_STATUS', 1.7254529122444815e-108),\n",
       " ('TARGET', 'NAME_HOUSING_TYPE', 1.2578680791247746e-88),\n",
       " ('TARGET', 'FLAG_MOBIL', 1.0),\n",
       " ('TARGET', 'FLAG_EMP_PHONE', 1.522466112273338e-143),\n",
       " ('TARGET', 'FLAG_WORK_PHONE', 2.3168389869963767e-56),\n",
       " ('TARGET', 'FLAG_CONT_MOBILE', 0.8899698286737141),\n",
       " ('TARGET', 'FLAG_PHONE', 1.4981802440893694e-39),\n",
       " ('TARGET', 'FLAG_EMAIL', 0.35215396103040886),\n",
       " ('TARGET', 'ORGANIZATION_TYPE', 5.673740404019712e-299),\n",
       " ('NAME_CONTRACT_TYPE', 'TARGET', 1.3210821346035907e-66),\n",
       " ('NAME_CONTRACT_TYPE', 'CODE_GENDER', 7.017696587854066e-14),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_OWN_CAR', 0.0005831438567590284),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_OWN_REALTY', 6.872216917297913e-292),\n",
       " ('NAME_CONTRACT_TYPE', 'NAME_TYPE_SUITE', 1.019162456555383e-12),\n",
       " ('NAME_CONTRACT_TYPE', 'NAME_INCOME_TYPE', 1.1993560513430518e-249),\n",
       " ('NAME_CONTRACT_TYPE', 'NAME_EDUCATION_TYPE', 2.9400941759841988e-307),\n",
       " ('NAME_CONTRACT_TYPE', 'NAME_FAMILY_STATUS', 7.091743225902182e-149),\n",
       " ('NAME_CONTRACT_TYPE', 'NAME_HOUSING_TYPE', 4.1092096165796997e-47),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_MOBIL', 1.0),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_EMP_PHONE', 3.175913621589982e-200),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_WORK_PHONE', 3.9839387483568994e-98),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_CONT_MOBILE', 0.0),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_PHONE', 5.747778861771426e-42),\n",
       " ('NAME_CONTRACT_TYPE', 'FLAG_EMAIL', 8.25199533208673e-10),\n",
       " ('NAME_CONTRACT_TYPE', 'ORGANIZATION_TYPE', 9.847324974821877e-257),\n",
       " ('CODE_GENDER', 'TARGET', 5.7018951392156825e-202),\n",
       " ('CODE_GENDER', 'NAME_CONTRACT_TYPE', 7.017696587854066e-14),\n",
       " ('CODE_GENDER', 'FLAG_OWN_CAR', 0.0),\n",
       " ('CODE_GENDER', 'FLAG_OWN_REALTY', 3.8858396084457064e-131),\n",
       " ('CODE_GENDER', 'NAME_TYPE_SUITE', 3.8352511329677773e-261),\n",
       " ('CODE_GENDER', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('CODE_GENDER', 'NAME_EDUCATION_TYPE', 1.0569037902673173e-42),\n",
       " ('CODE_GENDER', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('CODE_GENDER', 'NAME_HOUSING_TYPE', 2.108796316159923e-286),\n",
       " ('CODE_GENDER', 'FLAG_MOBIL', 0.38130449140759237),\n",
       " ('CODE_GENDER', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('CODE_GENDER', 'FLAG_WORK_PHONE', 9.257787758332419e-82),\n",
       " ('CODE_GENDER', 'FLAG_CONT_MOBILE', 0.003691126027732295),\n",
       " ('CODE_GENDER', 'FLAG_PHONE', 1.862329816565497e-28),\n",
       " ('CODE_GENDER', 'FLAG_EMAIL', 2.6174705030130737e-23),\n",
       " ('CODE_GENDER', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('FLAG_OWN_CAR', 'TARGET', 2.0162941238237494e-33),\n",
       " ('FLAG_OWN_CAR', 'NAME_CONTRACT_TYPE', 0.0005831438567590284),\n",
       " ('FLAG_OWN_CAR', 'CODE_GENDER', 0.0),\n",
       " ('FLAG_OWN_CAR', 'FLAG_OWN_REALTY', 0.2500488865470143),\n",
       " ('FLAG_OWN_CAR', 'NAME_TYPE_SUITE', 2.1249553484255595e-120),\n",
       " ('FLAG_OWN_CAR', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('FLAG_OWN_CAR', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('FLAG_OWN_CAR', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('FLAG_OWN_CAR', 'NAME_HOUSING_TYPE', 1.7865041468030153e-105),\n",
       " ('FLAG_OWN_CAR', 'FLAG_MOBIL', 0.7358822366436635),\n",
       " ('FLAG_OWN_CAR', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('FLAG_OWN_CAR', 'FLAG_WORK_PHONE', 5.031647348468501e-12),\n",
       " ('FLAG_OWN_CAR', 'FLAG_CONT_MOBILE', 0.0002771456751404461),\n",
       " ('FLAG_OWN_CAR', 'FLAG_PHONE', 0.00013620326362761127),\n",
       " ('FLAG_OWN_CAR', 'FLAG_EMAIL', 1.7235271569068536e-71),\n",
       " ('FLAG_OWN_CAR', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('FLAG_OWN_REALTY', 'TARGET', 0.00022554903355310706),\n",
       " ('FLAG_OWN_REALTY', 'NAME_CONTRACT_TYPE', 6.872216917297913e-292),\n",
       " ('FLAG_OWN_REALTY', 'CODE_GENDER', 3.8858396084457064e-131),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_OWN_CAR', 0.2500488865470143),\n",
       " ('FLAG_OWN_REALTY', 'NAME_TYPE_SUITE', 2.2214247185976567e-215),\n",
       " ('FLAG_OWN_REALTY', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('FLAG_OWN_REALTY', 'NAME_EDUCATION_TYPE', 1.4631977345384986e-58),\n",
       " ('FLAG_OWN_REALTY', 'NAME_FAMILY_STATUS', 1.1252932431539585e-173),\n",
       " ('FLAG_OWN_REALTY', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_CONT_MOBILE', 1.916839346513821e-06),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_PHONE', 2.307681968917806e-121),\n",
       " ('FLAG_OWN_REALTY', 'FLAG_EMAIL', 6.860389783721377e-58),\n",
       " ('FLAG_OWN_REALTY', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('NAME_TYPE_SUITE', 'TARGET', 1.1329313903575907e-05),\n",
       " ('NAME_TYPE_SUITE', 'NAME_CONTRACT_TYPE', 1.019162456555383e-12),\n",
       " ('NAME_TYPE_SUITE', 'CODE_GENDER', 3.8352511329677773e-261),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_OWN_CAR', 2.1249553484255595e-120),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_OWN_REALTY', 2.2214247185976567e-215),\n",
       " ('NAME_TYPE_SUITE', 'NAME_INCOME_TYPE', 2.2933635224338153e-163),\n",
       " ('NAME_TYPE_SUITE', 'NAME_EDUCATION_TYPE', 1.184053952004437e-130),\n",
       " ('NAME_TYPE_SUITE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('NAME_TYPE_SUITE', 'NAME_HOUSING_TYPE', 5.043485284173507e-103),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_MOBIL', 0.9997610425081656),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_EMP_PHONE', 8.523493289746945e-166),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_WORK_PHONE', 5.362223389894459e-51),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_CONT_MOBILE', 0.0036661854692670503),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_PHONE', 8.17209002688376e-18),\n",
       " ('NAME_TYPE_SUITE', 'FLAG_EMAIL', 2.0778811305316621e-07),\n",
       " ('NAME_TYPE_SUITE', 'ORGANIZATION_TYPE', 8.682125083892194e-165),\n",
       " ('NAME_INCOME_TYPE', 'TARGET', 4.977160476319552e-267),\n",
       " ('NAME_INCOME_TYPE', 'NAME_CONTRACT_TYPE', 1.1993560513430518e-249),\n",
       " ('NAME_INCOME_TYPE', 'CODE_GENDER', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_OWN_CAR', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_OWN_REALTY', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'NAME_TYPE_SUITE', 2.293363522433423e-163),\n",
       " ('NAME_INCOME_TYPE', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_MOBIL', 0.9957891680306096),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_CONT_MOBILE', 1.7328913541490809e-25),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_PHONE', 1.2684524667489908e-40),\n",
       " ('NAME_INCOME_TYPE', 'FLAG_EMAIL', 0.0),\n",
       " ('NAME_INCOME_TYPE', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'TARGET', 2.0485507599699323e-218),\n",
       " ('NAME_EDUCATION_TYPE', 'NAME_CONTRACT_TYPE', 2.9400941759841988e-307),\n",
       " ('NAME_EDUCATION_TYPE', 'CODE_GENDER', 1.0569037902673173e-42),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_OWN_CAR', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_OWN_REALTY', 1.4631977345384986e-58),\n",
       " ('NAME_EDUCATION_TYPE', 'NAME_TYPE_SUITE', 1.1840539520045719e-130),\n",
       " ('NAME_EDUCATION_TYPE', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_MOBIL', 8.197608753027372e-06),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_WORK_PHONE', 4.619360045977941e-21),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_CONT_MOBILE', 2.356150257960267e-31),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_PHONE', 1.0712384495991771e-66),\n",
       " ('NAME_EDUCATION_TYPE', 'FLAG_EMAIL', 0.0),\n",
       " ('NAME_EDUCATION_TYPE', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'TARGET', 1.725452912244531e-108),\n",
       " ('NAME_FAMILY_STATUS', 'NAME_CONTRACT_TYPE', 7.091743225901777e-149),\n",
       " ('NAME_FAMILY_STATUS', 'CODE_GENDER', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_OWN_CAR', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_OWN_REALTY', 1.1252932431539585e-173),\n",
       " ('NAME_FAMILY_STATUS', 'NAME_TYPE_SUITE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_MOBIL', 0.9668559819854107),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_CONT_MOBILE', 0.00019203221841497054),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_PHONE', 1.0099214597658868e-59),\n",
       " ('NAME_FAMILY_STATUS', 'FLAG_EMAIL', 2.380008236938805e-71),\n",
       " ('NAME_FAMILY_STATUS', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'TARGET', 1.2578680791247746e-88),\n",
       " ('NAME_HOUSING_TYPE', 'NAME_CONTRACT_TYPE', 4.1092096165796997e-47),\n",
       " ('NAME_HOUSING_TYPE', 'CODE_GENDER', 2.108796316159923e-286),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_OWN_CAR', 1.7865041468030153e-105),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_OWN_REALTY', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'NAME_TYPE_SUITE', 5.043485284173507e-103),\n",
       " ('NAME_HOUSING_TYPE', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_MOBIL', 0.9997079573960284),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_WORK_PHONE', 1.0779906213635431e-47),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_CONT_MOBILE', 0.9565358229532283),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_PHONE', 7.763026708190618e-89),\n",
       " ('NAME_HOUSING_TYPE', 'FLAG_EMAIL', 2.5042777623446407e-15),\n",
       " ('NAME_HOUSING_TYPE', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('FLAG_MOBIL', 'TARGET', 1.0),\n",
       " ('FLAG_MOBIL', 'NAME_CONTRACT_TYPE', 1.0),\n",
       " ('FLAG_MOBIL', 'CODE_GENDER', 0.38130449140759237),\n",
       " ('FLAG_MOBIL', 'FLAG_OWN_CAR', 0.7358822366436635),\n",
       " ('FLAG_MOBIL', 'FLAG_OWN_REALTY', 1.0),\n",
       " ('FLAG_MOBIL', 'NAME_TYPE_SUITE', 0.9997610425081656),\n",
       " ('FLAG_MOBIL', 'NAME_INCOME_TYPE', 0.9957891680306096),\n",
       " ('FLAG_MOBIL', 'NAME_EDUCATION_TYPE', 8.197608753027355e-06),\n",
       " ('FLAG_MOBIL', 'NAME_FAMILY_STATUS', 0.9668559819854107),\n",
       " ('FLAG_MOBIL', 'NAME_HOUSING_TYPE', 0.9997079573960284),\n",
       " ('FLAG_MOBIL', 'FLAG_EMP_PHONE', 1.0),\n",
       " ('FLAG_MOBIL', 'FLAG_WORK_PHONE', 1.0),\n",
       " ('FLAG_MOBIL', 'FLAG_CONT_MOBILE', 1.0),\n",
       " ('FLAG_MOBIL', 'FLAG_PHONE', 1.0),\n",
       " ('FLAG_MOBIL', 'FLAG_EMAIL', 1.0),\n",
       " ('FLAG_MOBIL', 'ORGANIZATION_TYPE', 0.0061348033093283905),\n",
       " ('FLAG_EMP_PHONE', 'TARGET', 1.522466112273251e-143),\n",
       " ('FLAG_EMP_PHONE', 'NAME_CONTRACT_TYPE', 3.175913621589982e-200),\n",
       " ('FLAG_EMP_PHONE', 'CODE_GENDER', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_OWN_CAR', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_OWN_REALTY', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'NAME_TYPE_SUITE', 8.523493289746459e-166),\n",
       " ('FLAG_EMP_PHONE', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_CONT_MOBILE', 1.6686727348497405e-12),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_PHONE', 2.6325669685088016e-19),\n",
       " ('FLAG_EMP_PHONE', 'FLAG_EMAIL', 1.565604117688853e-262),\n",
       " ('FLAG_EMP_PHONE', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'TARGET', 2.3168389869963767e-56),\n",
       " ('FLAG_WORK_PHONE', 'NAME_CONTRACT_TYPE', 3.9839387483568994e-98),\n",
       " ('FLAG_WORK_PHONE', 'CODE_GENDER', 9.257787758332682e-82),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_OWN_CAR', 5.031647348468501e-12),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_OWN_REALTY', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'NAME_TYPE_SUITE', 5.362223389894459e-51),\n",
       " ('FLAG_WORK_PHONE', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'NAME_EDUCATION_TYPE', 4.6193600459780084e-21),\n",
       " ('FLAG_WORK_PHONE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'NAME_HOUSING_TYPE', 1.0779906213635431e-47),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_CONT_MOBILE', 1.1437363138964826e-32),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_PHONE', 0.0),\n",
       " ('FLAG_WORK_PHONE', 'FLAG_EMAIL', 1.0225698397504854e-10),\n",
       " ('FLAG_WORK_PHONE', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('FLAG_CONT_MOBILE', 'TARGET', 0.8899698286737141),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_CONTRACT_TYPE', 0.0),\n",
       " ('FLAG_CONT_MOBILE', 'CODE_GENDER', 0.003691126027732295),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_OWN_CAR', 0.0002771456751404461),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_OWN_REALTY', 1.916839346513821e-06),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_TYPE_SUITE', 0.003666185469267058),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_INCOME_TYPE', 1.732891354149106e-25),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_EDUCATION_TYPE', 2.356150257960267e-31),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_FAMILY_STATUS', 0.00019203221841497054),\n",
       " ('FLAG_CONT_MOBILE', 'NAME_HOUSING_TYPE', 0.9565358229532283),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_EMP_PHONE', 1.6686727348497405e-12),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_WORK_PHONE', 1.143736313896466e-32),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_PHONE', 0.0006529616859960581),\n",
       " ('FLAG_CONT_MOBILE', 'FLAG_EMAIL', 0.004106329550372892),\n",
       " ('FLAG_CONT_MOBILE', 'ORGANIZATION_TYPE', 2.5732113772882937e-16),\n",
       " ('FLAG_PHONE', 'TARGET', 1.4981802440893694e-39),\n",
       " ('FLAG_PHONE', 'NAME_CONTRACT_TYPE', 5.747778861771426e-42),\n",
       " ('FLAG_PHONE', 'CODE_GENDER', 1.8623298165654838e-28),\n",
       " ('FLAG_PHONE', 'FLAG_OWN_CAR', 0.00013620326362761127),\n",
       " ('FLAG_PHONE', 'FLAG_OWN_REALTY', 2.307681968917806e-121),\n",
       " ('FLAG_PHONE', 'NAME_TYPE_SUITE', 8.172090026883817e-18),\n",
       " ('FLAG_PHONE', 'NAME_INCOME_TYPE', 1.2684524667489908e-40),\n",
       " ('FLAG_PHONE', 'NAME_EDUCATION_TYPE', 1.0712384495991465e-66),\n",
       " ('FLAG_PHONE', 'NAME_FAMILY_STATUS', 1.0099214597658868e-59),\n",
       " ('FLAG_PHONE', 'NAME_HOUSING_TYPE', 7.763026708190618e-89),\n",
       " ('FLAG_PHONE', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_PHONE', 'FLAG_EMP_PHONE', 2.63256696850882e-19),\n",
       " ('FLAG_PHONE', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('FLAG_PHONE', 'FLAG_CONT_MOBILE', 0.0006529616859960585),\n",
       " ('FLAG_PHONE', 'FLAG_EMAIL', 8.309680927733004e-16),\n",
       " ('FLAG_PHONE', 'ORGANIZATION_TYPE', 5.5088988322504664e-105),\n",
       " ('FLAG_EMAIL', 'TARGET', 0.35215396103040886),\n",
       " ('FLAG_EMAIL', 'NAME_CONTRACT_TYPE', 8.25199533208673e-10),\n",
       " ('FLAG_EMAIL', 'CODE_GENDER', 2.6174705030130737e-23),\n",
       " ('FLAG_EMAIL', 'FLAG_OWN_CAR', 1.7235271569068536e-71),\n",
       " ('FLAG_EMAIL', 'FLAG_OWN_REALTY', 6.860389783721571e-58),\n",
       " ('FLAG_EMAIL', 'NAME_TYPE_SUITE', 2.0778811305316621e-07),\n",
       " ('FLAG_EMAIL', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('FLAG_EMAIL', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('FLAG_EMAIL', 'NAME_FAMILY_STATUS', 2.380008236938805e-71),\n",
       " ('FLAG_EMAIL', 'NAME_HOUSING_TYPE', 2.5042777623446407e-15),\n",
       " ('FLAG_EMAIL', 'FLAG_MOBIL', 1.0),\n",
       " ('FLAG_EMAIL', 'FLAG_EMP_PHONE', 1.565604117689031e-262),\n",
       " ('FLAG_EMAIL', 'FLAG_WORK_PHONE', 1.0225698397504854e-10),\n",
       " ('FLAG_EMAIL', 'FLAG_CONT_MOBILE', 0.004106329550372892),\n",
       " ('FLAG_EMAIL', 'FLAG_PHONE', 8.309680927733004e-16),\n",
       " ('FLAG_EMAIL', 'ORGANIZATION_TYPE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'TARGET', 5.673740404018419e-299),\n",
       " ('ORGANIZATION_TYPE', 'NAME_CONTRACT_TYPE', 9.847324974821877e-257),\n",
       " ('ORGANIZATION_TYPE', 'CODE_GENDER', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_OWN_CAR', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_OWN_REALTY', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'NAME_TYPE_SUITE', 8.682125083892194e-165),\n",
       " ('ORGANIZATION_TYPE', 'NAME_INCOME_TYPE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'NAME_EDUCATION_TYPE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'NAME_FAMILY_STATUS', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'NAME_HOUSING_TYPE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_MOBIL', 0.0061348033093283905),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_EMP_PHONE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_WORK_PHONE', 0.0),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_CONT_MOBILE', 2.5732113772882937e-16),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_PHONE', 5.508898832250152e-105),\n",
       " ('ORGANIZATION_TYPE', 'FLAG_EMAIL', 0.0)]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>var2</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_CONT_MOBILE</th>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <th>FLAG_EMP_PHONE</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <th>NAME_FAMILY_STATUS</th>\n",
       "      <th>NAME_HOUSING_TYPE</th>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <th>NAME_TYPE_SUITE</th>\n",
       "      <th>ORGANIZATION_TYPE</th>\n",
       "      <th>TARGET</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>var1</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.691126e-03</td>\n",
       "      <td>2.617471e-23</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.381304</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.885840e-131</td>\n",
       "      <td>1.862330e-28</td>\n",
       "      <td>9.257788e-82</td>\n",
       "      <td>7.017697e-14</td>\n",
       "      <td>1.056904e-42</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.108796e-286</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.835251e-261</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.701895e-202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_CONT_MOBILE</th>\n",
       "      <td>3.691126e-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.106330e-03</td>\n",
       "      <td>1.668673e-12</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.771457e-04</td>\n",
       "      <td>1.916839e-06</td>\n",
       "      <td>6.529617e-04</td>\n",
       "      <td>1.143736e-32</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.356150e-31</td>\n",
       "      <td>1.920322e-04</td>\n",
       "      <td>9.565358e-01</td>\n",
       "      <td>1.732891e-25</td>\n",
       "      <td>3.666185e-03</td>\n",
       "      <td>2.573211e-16</td>\n",
       "      <td>8.899698e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <td>2.617471e-23</td>\n",
       "      <td>4.106330e-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.565604e-262</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.723527e-71</td>\n",
       "      <td>6.860390e-58</td>\n",
       "      <td>8.309681e-16</td>\n",
       "      <td>1.022570e-10</td>\n",
       "      <td>8.251995e-10</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.380008e-71</td>\n",
       "      <td>2.504278e-15</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.077881e-07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.521540e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_EMP_PHONE</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.668673e-12</td>\n",
       "      <td>1.565604e-262</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.632567e-19</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.175914e-200</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.523493e-166</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.522466e-143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <td>3.813045e-01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.358822e-01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>8.197609e-06</td>\n",
       "      <td>9.668560e-01</td>\n",
       "      <td>9.997080e-01</td>\n",
       "      <td>9.957892e-01</td>\n",
       "      <td>9.997610e-01</td>\n",
       "      <td>6.134803e-03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.771457e-04</td>\n",
       "      <td>1.723527e-71</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.735882</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.500489e-01</td>\n",
       "      <td>1.362033e-04</td>\n",
       "      <td>5.031647e-12</td>\n",
       "      <td>5.831439e-04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.786504e-105</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.124955e-120</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.016294e-33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <td>3.885840e-131</td>\n",
       "      <td>1.916839e-06</td>\n",
       "      <td>6.860390e-58</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.500489e-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.307682e-121</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.872217e-292</td>\n",
       "      <td>1.463198e-58</td>\n",
       "      <td>1.125293e-173</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.221425e-215</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.255490e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <td>1.862330e-28</td>\n",
       "      <td>6.529617e-04</td>\n",
       "      <td>8.309681e-16</td>\n",
       "      <td>2.632567e-19</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.362033e-04</td>\n",
       "      <td>2.307682e-121</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.747779e-42</td>\n",
       "      <td>1.071238e-66</td>\n",
       "      <td>1.009921e-59</td>\n",
       "      <td>7.763027e-89</td>\n",
       "      <td>1.268452e-40</td>\n",
       "      <td>8.172090e-18</td>\n",
       "      <td>5.508899e-105</td>\n",
       "      <td>1.498180e-39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <td>9.257788e-82</td>\n",
       "      <td>1.143736e-32</td>\n",
       "      <td>1.022570e-10</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.031647e-12</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.983939e-98</td>\n",
       "      <td>4.619360e-21</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.077991e-47</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.362223e-51</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.316839e-56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <td>7.017697e-14</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.251995e-10</td>\n",
       "      <td>3.175914e-200</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.831439e-04</td>\n",
       "      <td>6.872217e-292</td>\n",
       "      <td>5.747779e-42</td>\n",
       "      <td>3.983939e-98</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.940094e-307</td>\n",
       "      <td>7.091743e-149</td>\n",
       "      <td>4.109210e-47</td>\n",
       "      <td>1.199356e-249</td>\n",
       "      <td>1.019162e-12</td>\n",
       "      <td>9.847325e-257</td>\n",
       "      <td>1.321082e-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <td>1.056904e-42</td>\n",
       "      <td>2.356150e-31</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.463198e-58</td>\n",
       "      <td>1.071238e-66</td>\n",
       "      <td>4.619360e-21</td>\n",
       "      <td>2.940094e-307</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.184054e-130</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.048551e-218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_FAMILY_STATUS</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.920322e-04</td>\n",
       "      <td>2.380008e-71</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.966856</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.125293e-173</td>\n",
       "      <td>1.009921e-59</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.091743e-149</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.725453e-108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_HOUSING_TYPE</th>\n",
       "      <td>2.108796e-286</td>\n",
       "      <td>9.565358e-01</td>\n",
       "      <td>2.504278e-15</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.999708</td>\n",
       "      <td>1.786504e-105</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.763027e-89</td>\n",
       "      <td>1.077991e-47</td>\n",
       "      <td>4.109210e-47</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.043485e-103</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.257868e-88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.732891e-25</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.995789</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.268452e-40</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.199356e-249</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.293364e-163</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4.977160e-267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_TYPE_SUITE</th>\n",
       "      <td>3.835251e-261</td>\n",
       "      <td>3.666185e-03</td>\n",
       "      <td>2.077881e-07</td>\n",
       "      <td>8.523493e-166</td>\n",
       "      <td>0.999761</td>\n",
       "      <td>2.124955e-120</td>\n",
       "      <td>2.221425e-215</td>\n",
       "      <td>8.172090e-18</td>\n",
       "      <td>5.362223e-51</td>\n",
       "      <td>1.019162e-12</td>\n",
       "      <td>1.184054e-130</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.043485e-103</td>\n",
       "      <td>2.293364e-163</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.682125e-165</td>\n",
       "      <td>1.132931e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ORGANIZATION_TYPE</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.573211e-16</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.006135</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>5.508899e-105</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.847325e-257</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>8.682125e-165</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.673740e-299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TARGET</th>\n",
       "      <td>5.701895e-202</td>\n",
       "      <td>8.899698e-01</td>\n",
       "      <td>3.521540e-01</td>\n",
       "      <td>1.522466e-143</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.016294e-33</td>\n",
       "      <td>2.255490e-04</td>\n",
       "      <td>1.498180e-39</td>\n",
       "      <td>2.316839e-56</td>\n",
       "      <td>1.321082e-66</td>\n",
       "      <td>2.048551e-218</td>\n",
       "      <td>1.725453e-108</td>\n",
       "      <td>1.257868e-88</td>\n",
       "      <td>4.977160e-267</td>\n",
       "      <td>1.132931e-05</td>\n",
       "      <td>5.673740e-299</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "var2                   CODE_GENDER  FLAG_CONT_MOBILE     FLAG_EMAIL  \\\n",
       "var1                                                                  \n",
       "CODE_GENDER                    NaN      3.691126e-03   2.617471e-23   \n",
       "FLAG_CONT_MOBILE      3.691126e-03               NaN   4.106330e-03   \n",
       "FLAG_EMAIL            2.617471e-23      4.106330e-03            NaN   \n",
       "FLAG_EMP_PHONE        0.000000e+00      1.668673e-12  1.565604e-262   \n",
       "FLAG_MOBIL            3.813045e-01      1.000000e+00   1.000000e+00   \n",
       "FLAG_OWN_CAR          0.000000e+00      2.771457e-04   1.723527e-71   \n",
       "FLAG_OWN_REALTY      3.885840e-131      1.916839e-06   6.860390e-58   \n",
       "FLAG_PHONE            1.862330e-28      6.529617e-04   8.309681e-16   \n",
       "FLAG_WORK_PHONE       9.257788e-82      1.143736e-32   1.022570e-10   \n",
       "NAME_CONTRACT_TYPE    7.017697e-14      0.000000e+00   8.251995e-10   \n",
       "NAME_EDUCATION_TYPE   1.056904e-42      2.356150e-31   0.000000e+00   \n",
       "NAME_FAMILY_STATUS    0.000000e+00      1.920322e-04   2.380008e-71   \n",
       "NAME_HOUSING_TYPE    2.108796e-286      9.565358e-01   2.504278e-15   \n",
       "NAME_INCOME_TYPE      0.000000e+00      1.732891e-25   0.000000e+00   \n",
       "NAME_TYPE_SUITE      3.835251e-261      3.666185e-03   2.077881e-07   \n",
       "ORGANIZATION_TYPE     0.000000e+00      2.573211e-16   0.000000e+00   \n",
       "TARGET               5.701895e-202      8.899698e-01   3.521540e-01   \n",
       "\n",
       "var2                 FLAG_EMP_PHONE  FLAG_MOBIL   FLAG_OWN_CAR  \\\n",
       "var1                                                             \n",
       "CODE_GENDER            0.000000e+00    0.381304   0.000000e+00   \n",
       "FLAG_CONT_MOBILE       1.668673e-12    1.000000   2.771457e-04   \n",
       "FLAG_EMAIL            1.565604e-262    1.000000   1.723527e-71   \n",
       "FLAG_EMP_PHONE                  NaN    1.000000   0.000000e+00   \n",
       "FLAG_MOBIL             1.000000e+00         NaN   7.358822e-01   \n",
       "FLAG_OWN_CAR           0.000000e+00    0.735882            NaN   \n",
       "FLAG_OWN_REALTY        0.000000e+00    1.000000   2.500489e-01   \n",
       "FLAG_PHONE             2.632567e-19    1.000000   1.362033e-04   \n",
       "FLAG_WORK_PHONE        0.000000e+00    1.000000   5.031647e-12   \n",
       "NAME_CONTRACT_TYPE    3.175914e-200    1.000000   5.831439e-04   \n",
       "NAME_EDUCATION_TYPE    0.000000e+00    0.000008   0.000000e+00   \n",
       "NAME_FAMILY_STATUS     0.000000e+00    0.966856   0.000000e+00   \n",
       "NAME_HOUSING_TYPE      0.000000e+00    0.999708  1.786504e-105   \n",
       "NAME_INCOME_TYPE       0.000000e+00    0.995789   0.000000e+00   \n",
       "NAME_TYPE_SUITE       8.523493e-166    0.999761  2.124955e-120   \n",
       "ORGANIZATION_TYPE      0.000000e+00    0.006135   0.000000e+00   \n",
       "TARGET                1.522466e-143    1.000000   2.016294e-33   \n",
       "\n",
       "var2                 FLAG_OWN_REALTY     FLAG_PHONE  FLAG_WORK_PHONE  \\\n",
       "var1                                                                   \n",
       "CODE_GENDER            3.885840e-131   1.862330e-28     9.257788e-82   \n",
       "FLAG_CONT_MOBILE        1.916839e-06   6.529617e-04     1.143736e-32   \n",
       "FLAG_EMAIL              6.860390e-58   8.309681e-16     1.022570e-10   \n",
       "FLAG_EMP_PHONE          0.000000e+00   2.632567e-19     0.000000e+00   \n",
       "FLAG_MOBIL              1.000000e+00   1.000000e+00     1.000000e+00   \n",
       "FLAG_OWN_CAR            2.500489e-01   1.362033e-04     5.031647e-12   \n",
       "FLAG_OWN_REALTY                  NaN  2.307682e-121     0.000000e+00   \n",
       "FLAG_PHONE             2.307682e-121            NaN     0.000000e+00   \n",
       "FLAG_WORK_PHONE         0.000000e+00   0.000000e+00              NaN   \n",
       "NAME_CONTRACT_TYPE     6.872217e-292   5.747779e-42     3.983939e-98   \n",
       "NAME_EDUCATION_TYPE     1.463198e-58   1.071238e-66     4.619360e-21   \n",
       "NAME_FAMILY_STATUS     1.125293e-173   1.009921e-59     0.000000e+00   \n",
       "NAME_HOUSING_TYPE       0.000000e+00   7.763027e-89     1.077991e-47   \n",
       "NAME_INCOME_TYPE        0.000000e+00   1.268452e-40     0.000000e+00   \n",
       "NAME_TYPE_SUITE        2.221425e-215   8.172090e-18     5.362223e-51   \n",
       "ORGANIZATION_TYPE       0.000000e+00  5.508899e-105     0.000000e+00   \n",
       "TARGET                  2.255490e-04   1.498180e-39     2.316839e-56   \n",
       "\n",
       "var2                 NAME_CONTRACT_TYPE  NAME_EDUCATION_TYPE  \\\n",
       "var1                                                           \n",
       "CODE_GENDER                7.017697e-14         1.056904e-42   \n",
       "FLAG_CONT_MOBILE           0.000000e+00         2.356150e-31   \n",
       "FLAG_EMAIL                 8.251995e-10         0.000000e+00   \n",
       "FLAG_EMP_PHONE            3.175914e-200         0.000000e+00   \n",
       "FLAG_MOBIL                 1.000000e+00         8.197609e-06   \n",
       "FLAG_OWN_CAR               5.831439e-04         0.000000e+00   \n",
       "FLAG_OWN_REALTY           6.872217e-292         1.463198e-58   \n",
       "FLAG_PHONE                 5.747779e-42         1.071238e-66   \n",
       "FLAG_WORK_PHONE            3.983939e-98         4.619360e-21   \n",
       "NAME_CONTRACT_TYPE                  NaN        2.940094e-307   \n",
       "NAME_EDUCATION_TYPE       2.940094e-307                  NaN   \n",
       "NAME_FAMILY_STATUS        7.091743e-149         0.000000e+00   \n",
       "NAME_HOUSING_TYPE          4.109210e-47         0.000000e+00   \n",
       "NAME_INCOME_TYPE          1.199356e-249         0.000000e+00   \n",
       "NAME_TYPE_SUITE            1.019162e-12        1.184054e-130   \n",
       "ORGANIZATION_TYPE         9.847325e-257         0.000000e+00   \n",
       "TARGET                     1.321082e-66        2.048551e-218   \n",
       "\n",
       "var2                 NAME_FAMILY_STATUS  NAME_HOUSING_TYPE  NAME_INCOME_TYPE  \\\n",
       "var1                                                                           \n",
       "CODE_GENDER                0.000000e+00      2.108796e-286      0.000000e+00   \n",
       "FLAG_CONT_MOBILE           1.920322e-04       9.565358e-01      1.732891e-25   \n",
       "FLAG_EMAIL                 2.380008e-71       2.504278e-15      0.000000e+00   \n",
       "FLAG_EMP_PHONE             0.000000e+00       0.000000e+00      0.000000e+00   \n",
       "FLAG_MOBIL                 9.668560e-01       9.997080e-01      9.957892e-01   \n",
       "FLAG_OWN_CAR               0.000000e+00      1.786504e-105      0.000000e+00   \n",
       "FLAG_OWN_REALTY           1.125293e-173       0.000000e+00      0.000000e+00   \n",
       "FLAG_PHONE                 1.009921e-59       7.763027e-89      1.268452e-40   \n",
       "FLAG_WORK_PHONE            0.000000e+00       1.077991e-47      0.000000e+00   \n",
       "NAME_CONTRACT_TYPE        7.091743e-149       4.109210e-47     1.199356e-249   \n",
       "NAME_EDUCATION_TYPE        0.000000e+00       0.000000e+00      0.000000e+00   \n",
       "NAME_FAMILY_STATUS                  NaN       0.000000e+00      0.000000e+00   \n",
       "NAME_HOUSING_TYPE          0.000000e+00                NaN      0.000000e+00   \n",
       "NAME_INCOME_TYPE           0.000000e+00       0.000000e+00               NaN   \n",
       "NAME_TYPE_SUITE            0.000000e+00      5.043485e-103     2.293364e-163   \n",
       "ORGANIZATION_TYPE          0.000000e+00       0.000000e+00      0.000000e+00   \n",
       "TARGET                    1.725453e-108       1.257868e-88     4.977160e-267   \n",
       "\n",
       "var2                 NAME_TYPE_SUITE  ORGANIZATION_TYPE         TARGET  \n",
       "var1                                                                    \n",
       "CODE_GENDER            3.835251e-261       0.000000e+00  5.701895e-202  \n",
       "FLAG_CONT_MOBILE        3.666185e-03       2.573211e-16   8.899698e-01  \n",
       "FLAG_EMAIL              2.077881e-07       0.000000e+00   3.521540e-01  \n",
       "FLAG_EMP_PHONE         8.523493e-166       0.000000e+00  1.522466e-143  \n",
       "FLAG_MOBIL              9.997610e-01       6.134803e-03   1.000000e+00  \n",
       "FLAG_OWN_CAR           2.124955e-120       0.000000e+00   2.016294e-33  \n",
       "FLAG_OWN_REALTY        2.221425e-215       0.000000e+00   2.255490e-04  \n",
       "FLAG_PHONE              8.172090e-18      5.508899e-105   1.498180e-39  \n",
       "FLAG_WORK_PHONE         5.362223e-51       0.000000e+00   2.316839e-56  \n",
       "NAME_CONTRACT_TYPE      1.019162e-12      9.847325e-257   1.321082e-66  \n",
       "NAME_EDUCATION_TYPE    1.184054e-130       0.000000e+00  2.048551e-218  \n",
       "NAME_FAMILY_STATUS      0.000000e+00       0.000000e+00  1.725453e-108  \n",
       "NAME_HOUSING_TYPE      5.043485e-103       0.000000e+00   1.257868e-88  \n",
       "NAME_INCOME_TYPE       2.293364e-163       0.000000e+00  4.977160e-267  \n",
       "NAME_TYPE_SUITE                  NaN      8.682125e-165   1.132931e-05  \n",
       "ORGANIZATION_TYPE      8.682125e-165                NaN  5.673740e-299  \n",
       "TARGET                  1.132931e-05      5.673740e-299            NaN  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chi_test_output = pd.DataFrame(result, columns = ['var1', 'var2', \n",
    "                                                       'coeff'])\n",
    "## Using pivot function to convert the above DataFrame into a crosstab\n",
    "chi_test_output.pivot(index='var1', columns='var2', values='coeff')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Unnamed: 0', 'SK_ID_PREV', 'SK_ID_CURR', 'NAME_CONTRACT_TYPE', 'AMT_ANNUITY', 'AMT_APPLICATION', 'AMT_CREDIT', 'AMT_GOODS_PRICE', 'WEEKDAY_APPR_PROCESS_START', 'HOUR_APPR_PROCESS_START', 'FLAG_LAST_APPL_PER_CONTRACT', 'NFLAG_LAST_APPL_IN_DAY', 'NAME_CASH_LOAN_PURPOSE', 'NAME_CONTRACT_STATUS', 'DAYS_DECISION', 'NAME_PAYMENT_TYPE', 'CODE_REJECT_REASON', 'NAME_TYPE_SUITE', 'NAME_CLIENT_TYPE', 'NAME_GOODS_CATEGORY', 'NAME_PORTFOLIO', 'NAME_PRODUCT_TYPE', 'CHANNEL_TYPE', 'SELLERPLACE_AREA', 'NAME_SELLER_INDUSTRY', 'CNT_PAYMENT', 'NAME_YIELD_GROUP', 'PRODUCT_COMBINATION', 'DAYS_FIRST_DRAWING', 'DAYS_FIRST_DUE', 'DAYS_LAST_DUE_1ST_VERSION', 'DAYS_LAST_DUE', 'DAYS_TERMINATION', 'NFLAG_INSURED_ON_APPROVAL']\n"
     ]
    }
   ],
   "source": [
    "prev_columns = list(previous_application.columns)\n",
    "print(prev_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "prev_categorical = previous_application.select_dtypes(include=['object'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(849809, 16)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prev_categorical1 = prev_categorical.dropna()\n",
    "prev_categorical1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['NAME_CONTRACT_TYPE', 'WEEKDAY_APPR_PROCESS_START', 'FLAG_LAST_APPL_PER_CONTRACT', 'NAME_CASH_LOAN_PURPOSE', 'NAME_CONTRACT_STATUS', 'NAME_PAYMENT_TYPE', 'CODE_REJECT_REASON', 'NAME_TYPE_SUITE', 'NAME_CLIENT_TYPE', 'NAME_GOODS_CATEGORY', 'NAME_PORTFOLIO', 'NAME_PRODUCT_TYPE', 'CHANNEL_TYPE', 'NAME_SELLER_INDUSTRY', 'NAME_YIELD_GROUP', 'PRODUCT_COMBINATION']\n"
     ]
    }
   ],
   "source": [
    "c = list(prev_categorical1.columns)\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "prev_cat_var1 = ('NAME_CONTRACT_TYPE', 'WEEKDAY_APPR_PROCESS_START', 'FLAG_LAST_APPL_PER_CONTRACT', 'NAME_CASH_LOAN_PURPOSE', 'NAME_CONTRACT_STATUS', 'NAME_PAYMENT_TYPE', 'CODE_REJECT_REASON', 'NAME_TYPE_SUITE', 'NAME_CLIENT_TYPE', 'NAME_GOODS_CATEGORY', 'NAME_PORTFOLIO', 'NAME_PRODUCT_TYPE', 'CHANNEL_TYPE', 'NAME_SELLER_INDUSTRY', 'NAME_YIELD_GROUP', 'PRODUCT_COMBINATION')\n",
    "prev_cat_var2 = ('NAME_CONTRACT_TYPE', 'WEEKDAY_APPR_PROCESS_START', 'FLAG_LAST_APPL_PER_CONTRACT', 'NAME_CASH_LOAN_PURPOSE', 'NAME_CONTRACT_STATUS', 'NAME_PAYMENT_TYPE', 'CODE_REJECT_REASON', 'NAME_TYPE_SUITE', 'NAME_CLIENT_TYPE', 'NAME_GOODS_CATEGORY', 'NAME_PORTFOLIO', 'NAME_PRODUCT_TYPE', 'CHANNEL_TYPE', 'NAME_SELLER_INDUSTRY', 'NAME_YIELD_GROUP', 'PRODUCT_COMBINATION')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "prev_cat_var_prod = list(itertools.product(prev_cat_var1,prev_cat_var2, repeat = 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Creating an empty variable and picking only the p value from the output of Chi-Square test\n",
    "prev_result = []\n",
    "for i in prev_cat_var_prod:\n",
    "    if i[0] != i[1]:\n",
    "        prev_result.append((i[0],i[1],list(ss.chi2_contingency(pd.crosstab(\n",
    "                            prev_categorical1[i[0]], prev_categorical1[i[1]])))[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>var2</th>\n",
       "      <th>CHANNEL_TYPE</th>\n",
       "      <th>CODE_REJECT_REASON</th>\n",
       "      <th>FLAG_LAST_APPL_PER_CONTRACT</th>\n",
       "      <th>NAME_CASH_LOAN_PURPOSE</th>\n",
       "      <th>NAME_CLIENT_TYPE</th>\n",
       "      <th>NAME_CONTRACT_STATUS</th>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <th>NAME_GOODS_CATEGORY</th>\n",
       "      <th>NAME_PAYMENT_TYPE</th>\n",
       "      <th>NAME_PORTFOLIO</th>\n",
       "      <th>NAME_PRODUCT_TYPE</th>\n",
       "      <th>NAME_SELLER_INDUSTRY</th>\n",
       "      <th>NAME_TYPE_SUITE</th>\n",
       "      <th>NAME_YIELD_GROUP</th>\n",
       "      <th>PRODUCT_COMBINATION</th>\n",
       "      <th>WEEKDAY_APPR_PROCESS_START</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>var1</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>CHANNEL_TYPE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CODE_REJECT_REASON</th>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLAG_LAST_APPL_PER_CONTRACT</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.925254e-251</td>\n",
       "      <td>2.758995e-129</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.543912e-71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.003664e-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_CASH_LOAN_PURPOSE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.925254e-251</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_CLIENT_TYPE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.758995e-129</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_CONTRACT_STATUS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_GOODS_CATEGORY</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_PAYMENT_TYPE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.233746e-115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_PORTFOLIO</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_PRODUCT_TYPE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_SELLER_INDUSTRY</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_TYPE_SUITE</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.543912e-71</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAME_YIELD_GROUP</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRODUCT_COMBINATION</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEEKDAY_APPR_PROCESS_START</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.003664e-23</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.233746e-115</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "var2                         CHANNEL_TYPE  CODE_REJECT_REASON  \\\n",
       "var1                                                            \n",
       "CHANNEL_TYPE                          NaN                 0.0   \n",
       "CODE_REJECT_REASON                    0.0                 NaN   \n",
       "FLAG_LAST_APPL_PER_CONTRACT           0.0                 0.0   \n",
       "NAME_CASH_LOAN_PURPOSE                0.0                 0.0   \n",
       "NAME_CLIENT_TYPE                      0.0                 0.0   \n",
       "NAME_CONTRACT_STATUS                  0.0                 0.0   \n",
       "NAME_CONTRACT_TYPE                    0.0                 0.0   \n",
       "NAME_GOODS_CATEGORY                   0.0                 0.0   \n",
       "NAME_PAYMENT_TYPE                     0.0                 0.0   \n",
       "NAME_PORTFOLIO                        0.0                 0.0   \n",
       "NAME_PRODUCT_TYPE                     0.0                 0.0   \n",
       "NAME_SELLER_INDUSTRY                  0.0                 0.0   \n",
       "NAME_TYPE_SUITE                       0.0                 0.0   \n",
       "NAME_YIELD_GROUP                      0.0                 0.0   \n",
       "PRODUCT_COMBINATION                   0.0                 0.0   \n",
       "WEEKDAY_APPR_PROCESS_START            0.0                 0.0   \n",
       "\n",
       "var2                         FLAG_LAST_APPL_PER_CONTRACT  \\\n",
       "var1                                                       \n",
       "CHANNEL_TYPE                                0.000000e+00   \n",
       "CODE_REJECT_REASON                          0.000000e+00   \n",
       "FLAG_LAST_APPL_PER_CONTRACT                          NaN   \n",
       "NAME_CASH_LOAN_PURPOSE                     1.925254e-251   \n",
       "NAME_CLIENT_TYPE                           2.758995e-129   \n",
       "NAME_CONTRACT_STATUS                        0.000000e+00   \n",
       "NAME_CONTRACT_TYPE                          0.000000e+00   \n",
       "NAME_GOODS_CATEGORY                         0.000000e+00   \n",
       "NAME_PAYMENT_TYPE                           0.000000e+00   \n",
       "NAME_PORTFOLIO                              0.000000e+00   \n",
       "NAME_PRODUCT_TYPE                           0.000000e+00   \n",
       "NAME_SELLER_INDUSTRY                        0.000000e+00   \n",
       "NAME_TYPE_SUITE                             4.543912e-71   \n",
       "NAME_YIELD_GROUP                            0.000000e+00   \n",
       "PRODUCT_COMBINATION                         0.000000e+00   \n",
       "WEEKDAY_APPR_PROCESS_START                  1.003664e-23   \n",
       "\n",
       "var2                         NAME_CASH_LOAN_PURPOSE  NAME_CLIENT_TYPE  \\\n",
       "var1                                                                    \n",
       "CHANNEL_TYPE                           0.000000e+00      0.000000e+00   \n",
       "CODE_REJECT_REASON                     0.000000e+00      0.000000e+00   \n",
       "FLAG_LAST_APPL_PER_CONTRACT           1.925254e-251     2.758995e-129   \n",
       "NAME_CASH_LOAN_PURPOSE                          NaN      0.000000e+00   \n",
       "NAME_CLIENT_TYPE                       0.000000e+00               NaN   \n",
       "NAME_CONTRACT_STATUS                   0.000000e+00      0.000000e+00   \n",
       "NAME_CONTRACT_TYPE                     0.000000e+00      0.000000e+00   \n",
       "NAME_GOODS_CATEGORY                    0.000000e+00      0.000000e+00   \n",
       "NAME_PAYMENT_TYPE                      0.000000e+00      0.000000e+00   \n",
       "NAME_PORTFOLIO                         0.000000e+00      0.000000e+00   \n",
       "NAME_PRODUCT_TYPE                      0.000000e+00      0.000000e+00   \n",
       "NAME_SELLER_INDUSTRY                   0.000000e+00      0.000000e+00   \n",
       "NAME_TYPE_SUITE                        0.000000e+00      0.000000e+00   \n",
       "NAME_YIELD_GROUP                       0.000000e+00      0.000000e+00   \n",
       "PRODUCT_COMBINATION                    0.000000e+00      0.000000e+00   \n",
       "WEEKDAY_APPR_PROCESS_START             0.000000e+00      0.000000e+00   \n",
       "\n",
       "var2                         NAME_CONTRACT_STATUS  NAME_CONTRACT_TYPE  \\\n",
       "var1                                                                    \n",
       "CHANNEL_TYPE                                  0.0                 0.0   \n",
       "CODE_REJECT_REASON                            0.0                 0.0   \n",
       "FLAG_LAST_APPL_PER_CONTRACT                   0.0                 0.0   \n",
       "NAME_CASH_LOAN_PURPOSE                        0.0                 0.0   \n",
       "NAME_CLIENT_TYPE                              0.0                 0.0   \n",
       "NAME_CONTRACT_STATUS                          NaN                 0.0   \n",
       "NAME_CONTRACT_TYPE                            0.0                 NaN   \n",
       "NAME_GOODS_CATEGORY                           0.0                 0.0   \n",
       "NAME_PAYMENT_TYPE                             0.0                 0.0   \n",
       "NAME_PORTFOLIO                                0.0                 0.0   \n",
       "NAME_PRODUCT_TYPE                             0.0                 0.0   \n",
       "NAME_SELLER_INDUSTRY                          0.0                 0.0   \n",
       "NAME_TYPE_SUITE                               0.0                 0.0   \n",
       "NAME_YIELD_GROUP                              0.0                 0.0   \n",
       "PRODUCT_COMBINATION                           0.0                 0.0   \n",
       "WEEKDAY_APPR_PROCESS_START                    0.0                 0.0   \n",
       "\n",
       "var2                         NAME_GOODS_CATEGORY  NAME_PAYMENT_TYPE  \\\n",
       "var1                                                                  \n",
       "CHANNEL_TYPE                                 0.0       0.000000e+00   \n",
       "CODE_REJECT_REASON                           0.0       0.000000e+00   \n",
       "FLAG_LAST_APPL_PER_CONTRACT                  0.0       0.000000e+00   \n",
       "NAME_CASH_LOAN_PURPOSE                       0.0       0.000000e+00   \n",
       "NAME_CLIENT_TYPE                             0.0       0.000000e+00   \n",
       "NAME_CONTRACT_STATUS                         0.0       0.000000e+00   \n",
       "NAME_CONTRACT_TYPE                           0.0       0.000000e+00   \n",
       "NAME_GOODS_CATEGORY                          NaN       0.000000e+00   \n",
       "NAME_PAYMENT_TYPE                            0.0                NaN   \n",
       "NAME_PORTFOLIO                               0.0       0.000000e+00   \n",
       "NAME_PRODUCT_TYPE                            0.0       0.000000e+00   \n",
       "NAME_SELLER_INDUSTRY                         0.0       0.000000e+00   \n",
       "NAME_TYPE_SUITE                              0.0       0.000000e+00   \n",
       "NAME_YIELD_GROUP                             0.0       0.000000e+00   \n",
       "PRODUCT_COMBINATION                          0.0       0.000000e+00   \n",
       "WEEKDAY_APPR_PROCESS_START                   0.0      3.233746e-115   \n",
       "\n",
       "var2                         NAME_PORTFOLIO  NAME_PRODUCT_TYPE  \\\n",
       "var1                                                             \n",
       "CHANNEL_TYPE                            0.0                0.0   \n",
       "CODE_REJECT_REASON                      0.0                0.0   \n",
       "FLAG_LAST_APPL_PER_CONTRACT             0.0                0.0   \n",
       "NAME_CASH_LOAN_PURPOSE                  0.0                0.0   \n",
       "NAME_CLIENT_TYPE                        0.0                0.0   \n",
       "NAME_CONTRACT_STATUS                    0.0                0.0   \n",
       "NAME_CONTRACT_TYPE                      0.0                0.0   \n",
       "NAME_GOODS_CATEGORY                     0.0                0.0   \n",
       "NAME_PAYMENT_TYPE                       0.0                0.0   \n",
       "NAME_PORTFOLIO                          NaN                0.0   \n",
       "NAME_PRODUCT_TYPE                       0.0                NaN   \n",
       "NAME_SELLER_INDUSTRY                    0.0                0.0   \n",
       "NAME_TYPE_SUITE                         0.0                0.0   \n",
       "NAME_YIELD_GROUP                        0.0                0.0   \n",
       "PRODUCT_COMBINATION                     0.0                0.0   \n",
       "WEEKDAY_APPR_PROCESS_START              0.0                0.0   \n",
       "\n",
       "var2                         NAME_SELLER_INDUSTRY  NAME_TYPE_SUITE  \\\n",
       "var1                                                                 \n",
       "CHANNEL_TYPE                                  0.0     0.000000e+00   \n",
       "CODE_REJECT_REASON                            0.0     0.000000e+00   \n",
       "FLAG_LAST_APPL_PER_CONTRACT                   0.0     4.543912e-71   \n",
       "NAME_CASH_LOAN_PURPOSE                        0.0     0.000000e+00   \n",
       "NAME_CLIENT_TYPE                              0.0     0.000000e+00   \n",
       "NAME_CONTRACT_STATUS                          0.0     0.000000e+00   \n",
       "NAME_CONTRACT_TYPE                            0.0     0.000000e+00   \n",
       "NAME_GOODS_CATEGORY                           0.0     0.000000e+00   \n",
       "NAME_PAYMENT_TYPE                             0.0     0.000000e+00   \n",
       "NAME_PORTFOLIO                                0.0     0.000000e+00   \n",
       "NAME_PRODUCT_TYPE                             0.0     0.000000e+00   \n",
       "NAME_SELLER_INDUSTRY                          NaN     0.000000e+00   \n",
       "NAME_TYPE_SUITE                               0.0              NaN   \n",
       "NAME_YIELD_GROUP                              0.0     0.000000e+00   \n",
       "PRODUCT_COMBINATION                           0.0     0.000000e+00   \n",
       "WEEKDAY_APPR_PROCESS_START                    0.0     0.000000e+00   \n",
       "\n",
       "var2                         NAME_YIELD_GROUP  PRODUCT_COMBINATION  \\\n",
       "var1                                                                 \n",
       "CHANNEL_TYPE                              0.0                  0.0   \n",
       "CODE_REJECT_REASON                        0.0                  0.0   \n",
       "FLAG_LAST_APPL_PER_CONTRACT               0.0                  0.0   \n",
       "NAME_CASH_LOAN_PURPOSE                    0.0                  0.0   \n",
       "NAME_CLIENT_TYPE                          0.0                  0.0   \n",
       "NAME_CONTRACT_STATUS                      0.0                  0.0   \n",
       "NAME_CONTRACT_TYPE                        0.0                  0.0   \n",
       "NAME_GOODS_CATEGORY                       0.0                  0.0   \n",
       "NAME_PAYMENT_TYPE                         0.0                  0.0   \n",
       "NAME_PORTFOLIO                            0.0                  0.0   \n",
       "NAME_PRODUCT_TYPE                         0.0                  0.0   \n",
       "NAME_SELLER_INDUSTRY                      0.0                  0.0   \n",
       "NAME_TYPE_SUITE                           0.0                  0.0   \n",
       "NAME_YIELD_GROUP                          NaN                  0.0   \n",
       "PRODUCT_COMBINATION                       0.0                  NaN   \n",
       "WEEKDAY_APPR_PROCESS_START                0.0                  0.0   \n",
       "\n",
       "var2                         WEEKDAY_APPR_PROCESS_START  \n",
       "var1                                                     \n",
       "CHANNEL_TYPE                               0.000000e+00  \n",
       "CODE_REJECT_REASON                         0.000000e+00  \n",
       "FLAG_LAST_APPL_PER_CONTRACT                1.003664e-23  \n",
       "NAME_CASH_LOAN_PURPOSE                     0.000000e+00  \n",
       "NAME_CLIENT_TYPE                           0.000000e+00  \n",
       "NAME_CONTRACT_STATUS                       0.000000e+00  \n",
       "NAME_CONTRACT_TYPE                         0.000000e+00  \n",
       "NAME_GOODS_CATEGORY                        0.000000e+00  \n",
       "NAME_PAYMENT_TYPE                         3.233746e-115  \n",
       "NAME_PORTFOLIO                             0.000000e+00  \n",
       "NAME_PRODUCT_TYPE                          0.000000e+00  \n",
       "NAME_SELLER_INDUSTRY                       0.000000e+00  \n",
       "NAME_TYPE_SUITE                            0.000000e+00  \n",
       "NAME_YIELD_GROUP                           0.000000e+00  \n",
       "PRODUCT_COMBINATION                        0.000000e+00  \n",
       "WEEKDAY_APPR_PROCESS_START                          NaN  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prev_chi_test_output = pd.DataFrame(prev_result, columns = ['var1', 'var2', \n",
    "                                                       'coeff'])\n",
    "## Using pivot function to convert the above DataFrame into a crosstab\n",
    "prev_chi_test_output.pivot(index='var1', columns='var2', values='coeff') "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6 (default, Oct 18 2022, 12:41:40) \n[Clang 14.0.0 (clang-1400.0.29.202)]"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}