fundamentals_linear_regression_part1.ipynb

{
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   "source": [
    "<img align=\"left\" src=\"https://iili.io/HXJBlj9.jpg\" style=\"height:90px\" style=\"width:30px\"/>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "032881e1",
   "metadata": {},
   "source": [
    "# <a id='toc1_'></a>[Fundamentals of Supervised Machine Learning: OLS Linear Regression](#toc0_)\n",
    "This notebook serves as a primer on basic machine learning workflows, focusing on linear regression—a cornerstone model in supervised learning. Our journey will explore the construction of a linear regression model, and an analytical approach for feature selection and performance evaluation, utilizing both machine learning algorithms and statistical methods. The goal is to demonstrate a structured process for developing a predictive model, understanding its performance, and refining feature selection to ensure accuracy and reliability."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a35e359",
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   "source": [
    "**Table of contents**<a id='toc0_'></a>    \n",
    "- [Fundamentals of Supervised Machine Learning: OLS Linear Regression](#toc1_)    \n",
    "  - [Exploratory Data Analysis (EDA)](#toc1_1_)    \n",
    "    - [Dataset Introduction](#toc1_1_1_)    \n",
    "    - [Distribution Analysis](#toc1_1_2_)    \n",
    "    - [Linearity Analysis](#toc1_1_3_)    \n",
    "    - [Correlation Analysis](#toc1_1_4_)    \n",
    "  - [Data Split](#toc1_2_)    \n",
    "  - [Linear Regression Model](#toc1_3_)    \n",
    "    - [RFE | Recursive Feature Elimination](#toc1_3_1_)    \n",
    "  - [OLS Model](#toc1_4_)    \n",
    "    - [Libraries and Helper Functions](#toc1_4_1_)    \n",
    "    - [Training the OLS Regression Model: A Step-by-Step Guide](#toc1_4_2_)    \n",
    "      - [Incorporate Intercept](#toc1_4_2_1_)    \n",
    "      - [Model Instantiation and Fitting](#toc1_4_2_2_)    \n",
    "      - [Iteration 1](#toc1_4_2_3_)    \n",
    "      - [Iteration 2](#toc1_4_2_4_)    \n",
    "    - [Model Evaluation](#toc1_4_3_)    \n",
    "  - [Conclusion](#toc1_5_)    \n",
    "\n",
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  {
   "cell_type": "markdown",
   "id": "d3b70755",
   "metadata": {},
   "source": [
    "## <a id='toc1_1_'></a>[Exploratory Data Analysis (EDA)](#toc0_)\n",
    "EDA is essential for uncovering insights, ensuring data quality, and guiding the modeling process. It lays the groundwork for effective and informed analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ccb512e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing standard libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "220e5c38",
   "metadata": {},
   "source": [
    "### <a id='toc1_1_1_'></a>[Dataset Introduction](#toc0_)\n",
    "Initial examination reveals a dataset comprised entirely of continuous numerical variables, ideally suited for linear regression analysis. With no missing values present, data cleaning is unnecessary. The target variable for this machine learning endeavor is \"Yearly Amount Spent.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "89692082",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 500 entries, 0 to 499\n",
      "Data columns (total 5 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   Avg. Session Length   500 non-null    float64\n",
      " 1   Time on App           500 non-null    float64\n",
      " 2   Time on Website       500 non-null    float64\n",
      " 3   Length of Membership  500 non-null    float64\n",
      " 4   Yearly Amount Spent   500 non-null    float64\n",
      "dtypes: float64(5)\n",
      "memory usage: 19.7 KB\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Avg. Session Length</th>\n",
       "      <th>Time on App</th>\n",
       "      <th>Time on Website</th>\n",
       "      <th>Length of Membership</th>\n",
       "      <th>Yearly Amount Spent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34.497268</td>\n",
       "      <td>12.655651</td>\n",
       "      <td>39.577668</td>\n",
       "      <td>4.082621</td>\n",
       "      <td>587.951054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31.926272</td>\n",
       "      <td>11.109461</td>\n",
       "      <td>37.268959</td>\n",
       "      <td>2.664034</td>\n",
       "      <td>392.204933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>33.000915</td>\n",
       "      <td>11.330278</td>\n",
       "      <td>37.110597</td>\n",
       "      <td>4.104543</td>\n",
       "      <td>487.547505</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>34.305557</td>\n",
       "      <td>13.717514</td>\n",
       "      <td>36.721283</td>\n",
       "      <td>3.120179</td>\n",
       "      <td>581.852344</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33.330673</td>\n",
       "      <td>12.795189</td>\n",
       "      <td>37.536653</td>\n",
       "      <td>4.446308</td>\n",
       "      <td>599.406092</td>\n",
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      "text/plain": [
       "   Avg. Session Length  Time on App  Time on Website  Length of Membership  \\\n",
       "0            34.497268    12.655651        39.577668              4.082621   \n",
       "1            31.926272    11.109461        37.268959              2.664034   \n",
       "2            33.000915    11.330278        37.110597              4.104543   \n",
       "3            34.305557    13.717514        36.721283              3.120179   \n",
       "4            33.330673    12.795189        37.536653              4.446308   \n",
       "\n",
       "   Yearly Amount Spent  \n",
       "0           587.951054  \n",
       "1           392.204933  \n",
       "2           487.547505  \n",
       "3           581.852344  \n",
       "4           599.406092  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the dataset and display basic structure and initial rows for inspection\n",
    "df = pd.read_csv(\"customers_numeric.csv\")\n",
    "df.info()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9dd16934",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Avg. Session Length     500\n",
       "Time on App             500\n",
       "Time on Website         500\n",
       "Length of Membership    500\n",
       "Yearly Amount Spent     500\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# All datapoints are unique\n",
    "df.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed91e365",
   "metadata": {},
   "source": [
    "---\n",
    "### <a id='toc1_1_2_'></a>[Distribution Analysis](#toc0_)\n",
    "Our features predominantly follow a near-normal distribution, albeit with a handful of outliers present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ce0060f6",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 2000x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oJzrXV5+5OjP+Wza3Tbi6Z7JzPN797vkb+97uHU5kzvvVZ64uuM2xK22ye6qM95xiKnTsqgJeNYT88/L601Hs1UEzVapSdAAAAEhjNhCYwG+2d0uSjq619Ou+zhKPBlPRWhPQstqA2gdieqF9UG88qvDVqQCAhcctT+OWGHK5/RGKPck6lcbHczWJOt3m7GMnvsOxpA4OjMgx0nAspSGTVN9wQstqA9Nq8D7WRJO1ueWZnHFDmkLbcJuT//vje3WwYKgQ0F1b24s2QTx2DLu6I1PqCzNXJZKaqwLa3jmkPT3DSqSMbMuSz2upyp8e00TnrFRlm9xj+MiuHvlsWw0hX8Hm6chVylJ0AAAASCP0AMbhGKMHX02HHpuaqAS3mGxaUav2gU5t2U/oAQCLibsq4Mbf7pJlWXkNoYs9yVrKxsdTCVyk9ATqz1/o0EsdYYVjKYX8HrXWBNQbSSg5utLC7QueMkbtgzHVjK7GmK6JJmvHhjThWFK9kYRu/O0unb66PhNUTDbhe+UbV+m/nmvXoe7c144njLze4kwQjx1DOmyISkofKI9tKeT3qiHky1tZUuyeN25w8EL7oPb3jShpHFmylDJGqYRRUyj9b8yJ3ttz2YdnonEXo3l6scaymFZNTDfQBAAAQPERegDj+MPBsA6F0yUjXtdAN4/F5JQVtfrlS53aso++HgCw2Gxordbpq+vnJYyYyyvoJ5uonUrgsq0jrFsf35t5nM9jKRJPaX9fVH6vLZ9tK+mYnOc7jlEkkdtMfaommqwd22/FHZNlWROGI9nbcFfNXHXmGn31nj0590cSSdV6vXmPnw73mD+6q0fDcUceW/J5bEUTKcWTjlIm3dDQstPxx0gypQuPbcrbTrFW92QHB5FYSj6vpWRcMpaR17bk89gaSaR7mUz23p7vsk3jNk8fnn7z9NlYjKsmphpoAgAAYO4QegDjeHC0tNU56xrks/tLOxhMy0nLa2Rb0oGBEXWGY1pSHSj1kAAA0zBf5Xzm6gr6ySZqt3WE1RuJa0dXRH5Pbtmg7H18ZFdvTqkvr23Ja1sKej2qCngUSzp5oYcsqX84qa/e9+q0r4qfaLI2O6TJHlPAe3g17NhwZOw2XK8VWInSGR6RbR9eRTDeBPF4YZJ7zMOxpAaiyfSajpQ0HE8plXWInNH/SaaMVtdXaG9/fvA03uv+/IUO7ege7WnSFNLFG1snPLbZwUEs5chrW6rwe5RIGfk8lhJJo55kej/fuKZuSuMopomCuULN03sjCSVS6ebpc73SxLUYV02UcgUZAAAA0gg9gAJGEik9uqtHknT+sc2KH+wv7YAwLVUBr45ZUqVXDg1py/4BvXXDklIPCQAwDXMZRhSa5C12/4jeSOEJ+0dfS0/guoGIW6aqYzCmJcv8unjj0px97BqKKZZy8rYTTzmq9AcU8qdklFQi5chxJFlGXtuW12MpkTLa3jmkx3f3aUm1X+uaQpMGIBNN1r5p7eEgKntMjZW+zJ/HhiNjt+Eeqx89e0BS/gSwG6b0RhKy7XRT8ewxT6X8Vm8kIdtKl4+SlBN4SJK7dtcxRlUB75Suvh+74kaSnm8fVFckrqveuGrcY5odHAQ86RJRXtuS4xglkkaOMfJ5bDWGfHp8T79WN1TmbGsuyzpNFsyVunm6azGumihVDxYAAAAcRugBFLB5d5+iCUdLawI6vrVKzx0s9YgwXZtW1OqVQ0N6jtADABaM6UziFrucz1yVySm03Ve7IlpaE8hp+iylJ2oLXbluJO3vH9Hunoge3tmTOT4ey8pMlmfze2wd3Vypt6xv0E+eO6hY0pEtaSieUjJlFE866gzH1BdNZF63wueZdH8nmqw9rqUqE0Tt64/KMcrptyLlhyNjt+Eeq/6RhOrs/NAjEk9m9nV5bTDvHBU6dofCMV1/76uKJlLy2rYkI5/XUiph8h6bLTW6QmYqV9+PXXHj6o0kJlxxkB0cZJeIkqQKv53ZTyOprTea0x9FUtHfr9mfv4ODMQW8dt571N2fhTJxX4xVE/PdE6QUPVgAAACQi9ADKOA327skSecd0yTLop/HYrRpRY1+9OwBbd0/KMcY2ZxHACipUtfmn6syOYW2G/DYOb0PXEuq/eoMp69cz+6LIUmHwnHd+dT+TKPo9oERhWNJVfjzQ4/GkC8zibqmoVK/eLFDL7SH06/ts+UYo/aBmHzedDmseNbKjEL7mz0pHPTasiwp6ShvstYNoiYKNrLDkbETvrdsbpOUbow9ViwhxRxHNUGvltYEcsIUd8xjr/o/FI5pf/+ILEm2ld5PxzEK+GwFfbYSSaPRQleSDq/ykNLNzN0xT2RbR1hPtvWpZzguW5LPa8s7+tx4yplwxUF2cJBdIsoYKej1qDHkk5Ey7wPbsjKrc5KOI6+dW/os+1hM19jPX+9wQsaYnMbk0uEVFAtl4n624UupvnfmuwcLAAAAchF6AGN0DcX03P5BSdL5BZpbYnE4rqVKFT5bAyNJ7eoe1vrmUKmHBABHtFLX5p+rMjmFttsQ8qljMP/2c9Y16uGdPWofGMlbOZByHHlsW72Rw2FJdcCrgDc9ed8dictjWzp2SUgffsPKnCDikV29Wt8cUltvNBOQOMYokUr3AfF7DocMY/d37KRwQkZDsaSaQumA5uGdPTLG5JyjySbEsyd8t3WE9fDOHt21tV2v9QyrrsKnukqfEsO5xybgk2wnHdiMXaPhjnnsVf/u7bZlZVZ3WLYUSzry2ZYcI/k9lpKOkceyZGTkmPTjl1QH9L5Tl084ie8eG8eRbKVLZqUSjoI+O3NcJ1pxMPY4HddSlfMekNIrPLK5t0cTjip8Ru0DqZxgYqbv17GfP3cF0dhwbkm1P29lxKUnTdy7ZCamuvpituFLqb93AAAAUBqEHsAYv321R0bSiUur1VoTLPVwMENej62Ny2r0ZFu/nts/QOgBACVW6tr8c9VcuNB2qwNeLVnmV0PInzdRa4zRj7e05/TFSDpGSccoEUspmnDUEEtf3R+OJdUxGNP65pCW1x3+N4kxubGAe2yzSyjZVrp3hJReGTLe/v78hQ619UYVSzkKeGxV+Gz1RRPqiSS0uqFi3Cvjp3Il+9hAxXHSk/qt1fn/vqoJ+HRwKKZEPKXwyJBqK3xqHS0R5o557FX/CSd9DN0VLUGfrVjCUdIYeTyWAla6v8lIwlGFz5ajdOP1xkq/rjpzVcGJ80IloBpCPg3Fk5mSWYmUI6/tyay4mUih4+S+B6Tc/ijjrUnNDiZm+n4d+/lz3yuxZG7PmFV1wWmvjJhu+ajprr6YzaqJUn/vAAAAoDTy15YDRzBjjB4cLW3FKo/F75QVtZKkLfsGSjwSAEBzVaDg7bMNHabK7ZOQf/vsehSM3W44llRbb1R9w+kyRpee1Kqrz1ydswrivZuWqbHSJ8uyMuUXLVnpFQ5GmdJWvZFEzioNl9sQ3eUeW7eEUtDrkd9ryee1tbw2mFMqKnt/t3WE9cLBsEaSKRljNJJMqX0gpqRjMiWx3P258be7dMvmNm3rCOeNZ1tHWF+7f4c+8qOt+siPtupr9+/ITIRnaxgNX/qH8/tj9EQTSqYcGSM5RhocSWpvX1RDsWRmzO6xW14XlM9jq9Lnyay6kNKrWmzLUoXfoxOX1mhDa5XWN4e0prFC9SGfjm+t1plH1U8YePx4S7vaB0aUSBn1Dicygdaq+grVBr3y2pYsWTp5eY2uyjqv05G9HxU+W0GvR8trg3Ljh6RjJGMUiacUjTsajiUzz53O+3VbR1i3bG7TV+97VQcHYwpnbcd9rzSGfPJ5bC2vC+p9py5XW19+MCjlv+eyXyP7mLkBRqH3iWui1RfFVurvHQAAAJQGKz2ALK92RbSvf0QBr62zx5kcweKxaWU69HipI6xY0lHAS84LAKVS6sbIc9WjIHu7u7oi6o0k1BjyKejzTLhK4po3rdGPt7SrrTcqxxjJK6US6SbcUrpJdjzlaGlN/qTt2KvUx/aOcFcFrGkI6tl9g+oIR1Rf4dM7jl+Ss7+P7OrNa5TuGKNEUqry2zl9RyzLyuzPGWvqtLdvRF1DMXksS3v7opmm6ZL07P4BvXgw/XevMUYe21LI71VDyKdltUENDCek3AUGSiZNOgQaLW5lKb0ypLnKnzPm7Kv+7335kG57Yp+icSfTvytpHC2rqsjZdnXAK5/H1hcvWj/BmZy4BNTq+gpVN6eP6/K6oK4+c/WE25pMof4oAU9CQ/GkRkZLaEnpVSWxlFThs3XxxqVTfr+OXU0R8NpqHxjJKZVVHfDmlfi6a2v+Z1Qaf2XETMpHzefqi1J/7wAAAKA0CD2ALL97tUeS9MY19Qr5+XgsdivrgmoK+dQdSeilg+FMCAIAmH+laow83dI7M+FOYN+yuU1Bnyfv/kITwO7xuPG3u2RZlqoCHjWHbEWTjmJJRx5bOrGlWiMJJ297Y69SL3RsV9UF9fiefjWG/GoMpR//+J5+rW6ozIylayiWUxJLGi2LJaPGkE89WX1H3AsHwrGkfvLcQa2uTwcLO3uH1TecyJSYiiUdxRKOIkrJSPLYkpWyZJTUSDLdn+LUVXV6aU/uxHfScZQaLdvl9VgKeG35Pbbc6kuFzuOahsp075GhuJyUW9LKowp//jmYypX9Uy0BNZUJ85n0rIgmHA12J8esXkmvAmkI+af1WRkbRrgrO+IpR77RXiSFPn/TLQM3kwBjrkrNFbJQGrIDAABgfjGrC4xKOUYP70qHHm9Zz9Vf5cCyLJ2yolYPbO/Wlv0DhB4AUGKzqc0/E9PtHTBb050A3tBardNX1xecAF5eF8xZBZBt7KT72An2N61tmNIV+M1VASVSRstqg5mVJaFAOjCoCnjVntWMvbEyXZqqN5LI6UMRSzmZ1SHySrGEIyNlmpE7jmTbRomkkddvqXc4oeU1Ab2k3GNlJI1W+lIqZRRJpZTwGHnt9P7d+vjezGsHPMN6tXNITSG/WqoDaqk+vBomHEvmNecudMwKGTsZP9WgYKzZ9Kz43C9eVmc4rnjKkd9jqzHkU1XAO+1VEIXei1NZ8TLdlREzCTDme/XFfH/vAAAAoPQIPYBRL7YPqm/0l2Qmx8vHptHQ47n99PUAgCPNTErvzMZMJ4D//fG96slM6NuZBtnHtVRNepX6eBPs0URKFQVWnWRPnruTz9klsSTpjWvqtLd/RPv6o3JMOvCoGm2s7paxauuNqiHkU8Bja9iyMsFHdot12xptzm0kxzIKej2q8nv0zL7BvHEFvLZGUik5WYsqksbRi+1hbd0/qGgiJZ83vQJiJJnSgYGUDoVjWtcUytlOdcArr53uUTH2mBVafSEpc5vHsjJ9L3qzzsd7Ny3VW1/XMu45HLvd3kjhgGIq77t1TaGC5226qyBmuppiuisjZhJgsPoCAAAAc43QAxj1ux3pVR5nr2uQr0DTUCxObjPzXd3D6h9OqG70SlUAQPlzr3Z3m4K7k9gjiVTBx8+2FNZMr2B3gwIr+7bRUk+TXaXuBjtj99FrS8vrKvIenz3pPdnkc/ZKk0PhmA6ONqv2eKx074lkSnUVPvm8lhLJdEhhxryeZVmyJDVW+rW6oUI94wQCQZ+tlDGKGydzLCxJKWMUjiVlWZZSo70u3NJP0QKlvyTp6ObKvJ4bhcKhWx/fK0mZwCcho2gipYFoOvhwA6ixZcEm2+6OrohaawJ5q02mslpjNqsgst+/HsvSUCyZ08R+qtuZzsqImQYYrL4AAADAXCL0ACTFU442v5aeNHjz0ZS2Kid1lT6tbazUaz3Deu7AgN6yvqnUQwIAzJPmqoC2dw7lXPE+kkzpUDiubR3hnEnXYpTCmskE8CO7evNWWkhTX43SNRTLaTju7qPjGNXEkgXLPE2338QvXuzQwcGYZFkK+CwlUibTbHsk4WhVfYWSKUe7uoczwY1lScZIxjLyWOnwQJJCfq+cscnIqAq/R0GTvvAkGk/JjYHM6P8aRxqOpeTzWPJ5bVX6Cl+kUmgfC62+6I0kJEs5xygaT5eVWt2QGxiNdz4KrSbye2z1Rg6X2HIDKduWbtncNmGYNtMQYez7NyEjo3QD9KSjOV1NQYABAACAhYbQA5D07N4BDcVTagz5dMJSfmkrN6esqE2HHvsHCT0A4AhyzroGPb67L+/2xpAvbxK7WKWwxk4Ab+sI65bNbeMGDLu6I+oMxxWJJ5Vy0o2/Q37vuKsYxmquCmhn13Dmv5NOun+GLGkwmtSSKn/OpLcxJi/c+ffH96op5FfKmLwxbmit1iO7elXp92RWn3hso0Qq/eOxpavPXK27nz+o7khC4ZGkJCONlryyZGllfVDHtlTpnHWNenhnj/b25Jdd8tm2ZKUDG0lyjBTwuc2800GLK2WkVMLR8pqAgl5bO7ojkqRjmkO6eOPSgvtYaPVFdm+S7NusvFvHX6VRqHdGQ8injsHDq4zcQGp5bXBKYdpUQoSphDrVAa8aQv68VS/zZbYrp+bTYhorAAAAJkcNH0DSQzvTpa3OWdcoj13oV10sZptW1kiStuwbyEzYAADK34bWai2p9ivo9ci2LAW9Hi2vDRZsDD3dJuRT4V593z5aFsqd8N7WEc7c3xmOayieVDThKJ5yFE04Goon1TkUyzxuIuesa8hM3ied9AqMlDHyeSwNjCT0yqGIBkcS6VUXxuSFO+FYUgcGRrS9M1JwjFI6mIklUorEUorGHaUck+7TYYwqfB7t7onohYNhOcYo4LNl27aMMfJalkJ+j05cVqM3rW3QcS1VmT4aYy0JBZR00vtvW5Zqgt5MGaugz6PRTESWJI9lyeex1B1JaCTpaGVdhVbWVSiacDL7GI4l1dYb1atdEbX1RiWNruzIEvDYCnjtvNv8BcqcjtcLo7kqkHdbdcCrjcuqtbwuqP5oQkHf4fed69HXCodsU+G+r7Z3Dmln17Ae2tmjJ9r6dSic/x6ezft3NiZ77y8ki2msAAAAmBpWeuCIF02k9MSe9FWgb1lPaatydMLSmtHJkbj2949oZX1+jXMAQHmqr/CpMxzP9Jpw/3/sJPZMGz+Pde/Lh/TLlzrVH00omTJqqPRpSXXuxLi7euSRXb1qCPnUN5w7MZ1IGTVW5q9GKWRDa7U2Lq3W9q6I+oYT6UDAmw4L4ilHnmRKnUNxVfg8BRucu0FAfMyqB/e13WDGti2ZlFHSOEplZQe7uod18yN7FPTZ8nkO99tIOeku5hU+T97qhre9rlk/erwr5/V8XlvrmkLpUlDDCYX8HkXiKTVW+tQ+GFOFz6NEysjvsRQKeBVP5vcPcce9qzuSV+4r6RglxuxjQ8inkURKbb3RTC+UCr+tygKNxMf2wnBXBrgrdRpCvpxVJBdvXKrjWqrUGY7lrFJxzSaMcEOdnPerkQ4OjqjS78kZx3Tfv8VSrJVT82ExjRUAAABTQ+iBI94Tu/sUSzpaVhvQ+uZQqYeDORDw2jq+tVpbDwxqy/4BQg8AOEJs6wirKxLPlEwaSabUPpDS8tpg3iT2TBpIjy2J4/NI97/Snbl/OJ5SJJ5+7ezgw53wdleXOJIcxy0dZSngsQuuRhnPxRtb9eMt7YolncyKxmjckc9rK+kY9Q0nFEu6Dc4tLa87PKnvrhIZu7rBfW03mBlJphT02RqO5zeBTxkpEndU4Uv/nZtIpsfgOMr08pAOTyKvbQ5Jyg09Xjk0pIDfUmtNQKvrK7S8Lqg3rW3Qo6/1qi+ayDQVd1dLvNoVUaDAiox0qbDCjeqNkfb1RxVPOgp6bQV9HvWPNi3PrPM16WOxrz+9OsQtmZXdCyO7f0aFz6OGkE+9wwl5bVtHN1fm9M4oVpiWrWsolrdqxee1FEsY9Q4nckKPqTQunwtzsXJqriymsQIAAGBqKG+FI55b2urNRzfJsihtVa5OWVErSdq6f7DEIwEAzITbG+Or972qWza3Tan0jNskfFltMKfEVXOVP6+hs9tAenldUD6PreV1Qb3v1OXjNn4uVBLnly91KZnVpdutmHlozKSqO+HtsSy1D4zIliXbTv8YSV6PlfO4ybhjb6z0ZfbRP7raY2S0N4gxRiPJlAZGEhqKJTPPdYOD7HAi+7W7hmKZY1jlz71eypJyVlvEU448liVHRp7RElXZJZ0mmkROOUaDI0nt7YsqHEtmHmuM1BRKjyX7tdwQZKwl1X6F/LkrNdyyX7Yl1VX4lHSMhuIp9Q4n5Bgjxxi11gRU4bPVPhDTy4eG5Djpx7ols7KNXRlQHfBqdX2Fjm6u1NVnrs55z4xXzms2YURzVSCvH4nXtlQd9Mq2rCm9f+daobJfUuH39Ew+28U0nbECAABgcWClB45ogyMJPbNvQJL0ZkpblbWTl6f7erzQPqiUY+jdAgCLSPaV9ZKm1AxaOnwFd3XAm3P1e3KcHuHTaUJeqCROIpWeWPfa6Ul3n9dWKuHklTcaO+Ht81pKJQ4/xhrncRM1W97QWq1r3rQmc5zaeqPqG06vBvB5Dv+dF/J71VzlV0PIr85wXMe1hNQ1FM8JJ7Jf212p4B7Dvmh61YikvPJSjiOljFF1wJsJErJNZRI5lnS0pzeqznBM//hgJFM2auxqijeuqdPje/rznp9u1p4OOnojCcVTjhzHKOizVen35qyQiMRTqvClQ5+OwZgisZRSxsgyh1cFLasN5pU5ms7KADeQevS1XnWG45mG8rMJI85Z16DHd/dlVjC5ltYEdGxLVckal2eb6sqpmX62i2mysdLkHAAAYPEh9MARbfNrfUo5RuuaKrWKkkdl7ejmUKY++M7uiI5dUporHwEA0zfTmvszKS2U3athf3/6uUZSwDOsVzuHdOUbV2lDa3XBiW+fbeUEHF7bUtCXLinl89h5E94pY7SsNqje4YQspZQyjry2raDPzrtKfyqTw9kT7NGEo75oQkHv4T4bUnpFR9JRzsT4vS8f0q9e6lRfNKEKr63m6oDu2tqu5qqAVtUHc45hyO/JhB5jeWzJtixV+j2qHbPKQ5p8dYMxRilHknFkvHZO8OCGLsvrgpmxr26oLBgmGGMyQY2ULoVljFFjKN0fpJBIPCVndEWHnbUWvnc4kRdmTOd9NXbC3G3oPpnJAq4/27RUP9lyUPGUI39W6a9SlbMaa6phz9jPdjiWVG8koRt/u0unr66fl4BhorEuhFAGKIZUKqVt27apr69P9fX12rBhgzwez6zulzThcwAAxeF+B/f09GhwcFA1NTVqbGyc8Ht3su/1qbzebL/fi7WdmZpV6PG1r31Nf/d3f6dPfepTuummmySlf1n58pe/rO9+97vq6+vT6aefrm9/+9s6/vjjizFeoKgefS39i9ZC+QURc8djWzpxWbWe2NOv5w8MEnoAOCIt1iuWZ1pzf7p9OrInOPf3j2hwJF0GKuizZYzRgYGUfvFihza0Vhec+G6pDqh9MPc2r23pitNX6q0bluS9XnNVQImUyVmFIknL64KTTg67xgY/2atVvnb/Dm3vjGQmxit8tnoiCfVFE7plc1um9NITe/rl99oyRjoUjqtrKKGltYFM2a4z1tRpX/+IOsNxbVxWrRfbw+odTuSs9PDY0sr6Ci2pCsjnsXXpSa3jTiLfv61bY3lsKZ6ULEuqCXqVHatk96nIPudjV+Zk3549id1Y6VPAm+6TEvAkMiskqvwepUx2OTJLKWPky+oVEks6eWHGqvqgHt/dl2l+7q5GKdYqhqk8749f16I144Q+C8V45ydb9mc7uzm7NVr6bb4ChvHGSpNzlIMnnnhCd9xxhzo7OzO3LVmyRFdccYXOOOOMGd1fW1srY4wGBwcLPgcAUByFvoNd433vTva9Pt3Xm8n3e7G2MxszDj2efvppffe739XGjRtzbv/GN76hb37zm7rjjjt0zDHH6Ktf/aouuOACbd++XdXV/MMQC8fgSEJb96dLW529tnC9ZZSXk5fX6ok9/dq6f0DvOWVZqYcDAPNqoV+xPFEgM9Nm0NMtLZQ9wZndDDuRcjIlq3Z0RSQVDlSWVAf0htV1enb/gPqGE6qv9Okdx7cUDDy2dYTVG4lrR1dE/qyJ8/S280OZQsFPOJbUE3v61BkuHGK5Dc7dx7rHcHltMHP+g147c1807sgovQLl4OCIKv0eVQe82tc/krcy5EfPtqt7KC4jye+xtLwuqCWjvRGWVPsLTiK778FkUnkCPktxx1LAZ6u1JqCeyOFwIntlyXT6nLivn/3ebwj51D6Q3m5rTUBGGi2bZckx6b4kUroRvGOMfF5bq+qCOfvwxJ7+TLmtWNJR73BCFx7XPOOgaqzxnveLFzvyPiMzKWW1kMLP7M92dumxgPdw8FTKgIEm51jsnnjiCd1444069dRT9ZnPfEarVq3S3r179bOf/Uw33nij3vWud+kXv/jFtO6/99579R//8R+SpA984AN629velvOca6+9luADAIrA/Q5fu3atOjs7dcopp+iMM87Qk08+qeeee07V1dV537uTfe9P9B09m+fOxXZma0aNzIeGhvSBD3xAt956q+rr6zO3G2N000036Qtf+IIuueQSnXDCCbrzzjs1PDysH/3oR0UbNFAMT+zpl2OktY2VWp71yyzKl9vX46WOocykBgAcKSaagC21Qk3Bf7ylPdPQeDbNoDe0VuvqM1frixetz2synf36t2xu0yO7etTWm26knc3J+ivDjHbcGK/x+Z+fsUo3/+mJ+uGHN+nmPz1x3MDjx1vaNZJ0Mn0vOgZjqihQ1so1ttmyG1Q4RgWPmTvGM9bUqScS12vdw4onHdVX+GSU7vnxaldEz+wbUMdoyScna9WD46TDAOnwBO+2jrC+dv8Ofe+JfYrEkqrw2Qp4bPm9tip86VBoKJZUTyResCn1eO9BSUqk0qti/B5bRulwwpU9AT6T1bnZ56qh0q+jGitV5fdqf/+IDvSPqMrv0fGt1VpaE1BTyK9EKh142LbUUuXX43v6M/vh7oPbvHxpTUAy0k+fa8/b35lOmHcNxRSOJTPnqG20x8kL7eFxPyNTNdlnbSZm04g8+7Od3Zy9sfLw+S9lwECTcyxmqVRKd9xxh0499VRdd911OvbYY1VRUaFjjz1W1113nTZt2qR77rlHmzZtmvL9fr9f999/v0499VSddtppevDBB+X3+zPPOfXUU3XnnXcqlUpNPkAAwLjc7/BNmzZpcHBQp512mr7whS/oggsu0N/93d/p1FNPVTgc1qZNmzLfu5N970/0HT2b587FdophRis9rrnmGr397W/X+eefr69+9auZ23fv3q2Ojg5deOGFmdsCgYDOPfdcPfbYY/roRz86+xEDRfL70Umes1jlccRY3VChugqv+qNJvXJoSBuX1ZR6SAAwbxbyFcuTXRE/F82gXdmrAHz24T4SAa+t4dHVHtk9Ho5prsz8eSrlewrJ3t/sJusNIf+4+zR2ZYl7VXz25LCUe1W8uyqhMeRXz3BCxhh1ReJSRJk+H0nHKB5LKuC1M+Wd3H12V1gsqfZnjtOOroiiicOT0z6PpUTSqCsc05Iqv4Zi0sjo/dmriSTpybY+RROOAratkHJ7qYX8HgX9PvVHE2ofGNGy2mC630kkoZbqgJbXBWd1zt1zde/Lh/STLQcViScVTxr5vJa6I3H5R4OVZMoo5Pfm9MnIPq7jlWOyC5RjmukKJc/otlwjyZT6hhMKBfJrIE93FUSxyzXNdgVZ9md7X39Ujkm/p7P7wZQyYJhuiTxgIdm2bZs6Ozv1mc98Rrade72rbdvatGmTnn32WW3atGnK92dvU5I+//nPa9u2bTrhhBNk27YuvfTSnNsms3///iLtLRYKzunc4diWv+xz7H7fvutd79Kzzz6rz372s5nv4uzvW/f+bdu2SdKE3/sTfUdP9nfGVL/fi7WdYph26PHjH/9YW7Zs0dNPP513X0dHhySppaUl5/aWlha1tbXNcIhA8UViSW3Zly5t9aZxrh5F+bEsSyctr9XDO3v0/P5BQg8AR5SZTsDOh6kEMjMNGCaTPQmcXfrIN9qEPJE0CngsBb0eNYZ8unjj0gm3N5XSQTMJoMYGP7adLlM1tll49jay9y3gSQc6iaSRY4wSliXHGHlsSzLpEl4+r61UIh16+Dx2ZoXFOesa9fDOHkm5Zb+k9IqQCn96tUd9pV+dQ3G19UZz+l384sUORROOHCe9MjyeSik0Zv4+nkppKJKULSmWMmrrjer1q2onXJ0z3RJN2zrC+smWgxpJphRPGqWMUSphFPTZ6o0ktLqhQv3RhNY3h/Ke6x7X8cox+T355ZjGmzBfVV+hWza3TWvsTk4HlfxxTVWxw89ihCjuZ3tlXVA/2XJQ7YMxBTyJcXulzKe5DFyBudbX1ydJWrVqVcH7/X5/zv9P5f5C23Rvy749+7aJ/Mu//MuUHgeAz8uRxv0edb+Dx36Xu//t3l/ou3isib6jJ/s7Y6rf78XaTjFMK/TYt2+fPvWpT+n+++9XMDh+OSDLsnL+2xiTdxtQSk+29SvpGK2qD2pVfcXkT0DZOHl5jR7e2aPnDgzoQ1pR6uEAwLxZyFcsFyuQmclEePYkcHXAm1ldkHAcnbayVpKUdDSlyc7sq97DsaR2dg3r4Z09OnFptS7e2JrTo2R755B6I4mccGCyidTs4OeWzW2THrPsfXMDnaRJhw/uHL3XY8mypJRj5PfYOZP3xy2p0sUbW3VcS5Xu2pr/3pEOl8QysrSrO5K3QqF9IKXOcEzrmkI5odJYSSe9QsRjW6rw2bIsS9GEI2PyJ/tnurrgkV29mRJK2aW8EkmjuGfispfucc3+HOWUYwrll2MqNGG+qr5Cj+8+/EteobGnjMm8D90m9LZlFYw9pvsZKXb4WawQJadXyuh+90YSuvDYppIHDHMVuAJzzS1FvnfvXh177LF598fj8Zz/n8r92dsce1v27dm3TeRTn/qUVqzgd7Jysn//fibn5wifl/KX/flxv0fd7+Cx3+Xu9617/9jv4kLf+xN9R0/2d8ZUv9+LtZ1imFbo8eyzz6qzs1Onnnpq5rZUKqVHHnlEN998s7Zv3y4pveJj6dLDV8F1dnbmrf4ASsktbXX22tJP9GB+nbwivbpje2dE0UQqU4McAMrdQr5iuRiBzEwnwsdOArvlppbXBafdJNq96j277JGU/jsneyyr6oP63Y7uzP1uOHDhsU1Tfq2pHLPsfXMDnVc7I7IsI4+dXs3htS15bUtVAa/esLpu3PeGu62Q36PBkcM9T+zRC5uOaa7Uvv78yXRJmXJYmVBpKJH3mFQyPaXvOOn/d1eZFFoxMNPVBV1DMQU8tobiSaWMkTFKd2ixjfwe3+h+hHLKd7nc45pXjslRThksKT9ASOcr6dd7bnSl8URjb64KKJEymbJnUvo95fZYKTSuqSp2+FmsECW7V0r2fu8d5z0FYHIbNmzQkiVL9LOf/UzXXXddTpkRx3G0ZcsW2batLVu26KKLLprS/e4277rrLlmWpZaWFm3YsCHznJ/97Gc5t01mxYoVWrduXXF3HChTfF6OLO737ZYtW9Tc3JzzXe5+37r3Z3/vTvS9P9F39GR/Z0z1+71Y2ymGaTUyP++88/Tiiy9q69atmZ/TTjtNH/jAB7R161atXbtWra2teuCBBzLPicfjevjhh3XmmWcWffDATEQTKT2zt1+SdPbauU8WsbAsrQmqpTqglGP0h/aZN+0EgMVoKk29S2G8puDTGd9MG7XPpkn6WO5V79lljyQpProiwB3L3r50z4qg1yPbSpfOWl4bnNYE71SO2dh9qw54VeGzFfJ7VOHzyGtbSjpG0XhK4ZGkjJEuPam14HvD3VZrTUBBny2PnQ4MqgLpsV+8calC/sIXEmRfYFAd8Gp5bf4q28O9RNIhiturpNCKgZmuLmiuSo99JOHIXYRulC7RFfSlfy26eOPSgsfVGJNp1v3Irl69aW2Drv2jdVrdUJFXYsx97xRqGv7iwbDCsXRolN2s/Ik9fZkG4IXek9UB76w/I1JxPmu5+1qcz89C7jkELFYej0dXXHGFnn32WX3961/X9u3bFY1GtX37dn3961/Xli1b9Cd/8ifasmXLlO+Px+O64IIL9Oyzz+qZZ57R+eefr3g8nnnOs88+q8svv1weDxeWAcBsuN/hW7ZsUU1NjZ555hn9wz/8g+6//37dcMMNevbZZ1VdXa0tW7Zkvncn+96f6Dt6Ns+di+0Uw7RWelRXV+c1GQmFQmpsbMzc/ulPf1o33HCD1q9fr/Xr1+uGG25QZWWl3v/+9xdv1MAsPN3Wr3jKaFltQEc1Vk7+BJSdk5fX6L5XurT1wIBev7qu1MMBAGj2JWRmOmlazBUw7lXv2WWPpMP9HtyxdA3F8q5on8pYC419Q2t1pqzXXVvb88p6Bb22dnRHJKVXMWxaWaeuoZh6IwkNx5NKJI18XlsVfs+Eq2Oyj5PPthRJpBTyebWuuTJzvNY1hZR0jHqHE4olHQW8thorfUqkHL14MJzuG2JbaqkKyFYgZ/tej61UKpVpqO72dTiuJb+/xlRWFxQqdXbOugY9vrsv3asl5SgpIxkp4PXI67FyJv+z93+iVUQTvXcKBXF+j50JxbL3wTHKOfZzuSqrmOWaijXWhdxzCFjMzjjjDF177bW644479PnPfz5ze0tLi6699lqdccYZOuaYY6Z9f21trYwx+uEPf6gf/vCHec8BAMxe9ne4JD333HN67rnnMvcPDQ3lfe9O5Xt/Kq833efOxXZma9qNzCfzuc99TtFoVJ/4xCfU19en008/Xffff7+qq6mDioXhcGmrBnrNHKEOhx6DpR4KAJSNmfTTKKbZTJoWaxLYLR3kNg13uf0e3LEUc4J3W0dYtz6+N6s/yLC2dw7pgmOb9MSefknSyrr0yopowtEZa+r0xJ6UqgNetfVGZdvpcborK6Txy0RNdpzOWdeg9oGRnDCncyimrqG4bEuyrXQfjH19I1pdlRt6nLKyWgcGRtQ7nMj02xhJptQ1FNe2jnDO605WommikGJJtV8aUk4oUxXwyuexx52on2gV0dVnrh73mBQK4hpCPnUMxvJWA7nH3z32i6mPRDHGupB7DgGL3RlnnKHXv/712rZtm/r6+lRfX68NGzZkrrKd6f2Sxn0OAKA4sr+De3p6NDg4qJqaGjU2No77vTvZ9/pUX2823+/F2s5szDr0eOihh3L+27IsXX/99br++utnu2mg6EYSKT3V1i8pHXrgyHTSaF+P17qHNTiSUE3QN8kzAAATmWk/jWKa70nTQiGPlF5ZkXQcRROOQn6PltYEMuWP3LEUc6w/f6FDe/uiSiQdOUYasqSeSEyvdQ+rrsKnhpAvJ4TY1z+SuTJ/Z3dEQZ8nM/HvmmlJoUJX/e/vj8pruxeZ2EqmUgUbcv/xhiW675Uu9UeTisTTQUzI75FRfggz2eqC7JAiHEtmAqFvP7pHy2uDBft5TRQ4zaac1thwqzrg1ZJlfr3aFZFlWTnBy1S2Wa4Wcs8hV6mDXWA2PB5PXtWOYtw/0XMAAMUx2Xd0sZ5TjOfOxXZmqugrPYCF7Nl9AxpJOlpS7df65vxyCTgyNFT6taq+Qnv7onrhQFhnj1OPGgCOJLOZ0JtpY+lims9J00Ihz78/vldG6UntdU2hzGS717a0vC6YM5aZjrXQOXqpI6yR0cbbRkbO6AKTpONkGqQvqw1mgo/OcDxzZb4xKnpJobFX/T+8syfz50TSyDGFmwre/OgexVOO4ilHFaP9NRyT7oPhtfOfkf062zrCenhnT6a8167uiCp8nryG8r3DCQW8duY8ZZsocHLDi+wAJeCxC5beyt1mOtwa+7z3blqq+ko/5ZzGWMirW+Yz2CVcAQAAmD1CDxxRNu+mtBXSTl5Ro719UW09MEDoAeCIN9sJvYXShHi+Jk0LhTw9o+WK3Ml0t2fH8rqgrj5zdd7j3XE+sqtXneGYHt7ZI2PMuOMf7xwNxQ6X0TJOoWemJ/vdcWVPqs9kxcm2jrB+/kJHpk/I+qaQLt7YOu646yp86omk3wdJ48hIBVd69EQSShkjI5PTZD2RdLSrO6JbNrcVnPwtdFw6w3E1hHx5JaT8HltVo83cG0L+KQdO56xr0L8/vjcnpBiv9Fa2Da3VOmNNnX6y5aDio4FHY8inx/f064w1dQVDj/GOPRPhpTVfwe5CWDUHAABQDgg9cMRIphw9NVrb+syjmOQ+0p28vEb3vHiIvh4AoNlP6M1XE+L5nvgd7/UKhTyxlKNkylFbbzRzRX9DyDdu8JM9uRmOJbWza1gP7ezRxqXVBUOE8c6RY4wcx+SECZYkT9biiFjycBqSPak+3RUnbv+Q7HP9fPuguiNxXfnGVQXPxTuOX6I7n9qvpGPGDWWkdL+PpDFynNHxeu3MCpaAbeVN/rrn5sm2PjmOcsp4NYR86WbqYxrKu71Vko4KBlFj9zX73Ps9toJej+IpR/7R8KIq4NWjo73ixntf7u0b0eqGisxqD7dBe4XPnvKxZyK89OYr2F0Iq+YAAADKAaEHytbevXvV3d2d+e9dA46G4ilVeqWR9le15eDUV3ps27ZtLoaIEtq4rEa2Je3vH1H3UFxNVUduOQkAmO2E3nz005jvid+JXq9QyGNJiqcceUYbmLulpZaM8/eLO7k5tgTT9q5Iwf0qdI7CsaSMJMuW5BwOPYwkr22rrsKnkYQjj628Eluuqa6O2dYR1s2P7tH+/hHJGPm8dqZXR89wYtxJ2T9+XYsk6c4n98seHaenwD/BfB5bjpGStiPHMUqkjDy2JZ/HUqXfk9nfbz+6R5V+T2Y1R3gkqXjSUU8kruqgV601AVUHvPLatobjSfUOJ3JCCmnyMK7Qud/TF9XS0W27Y2nrjWrbobAee60vE7qMfV92DcXyzvFIMqUX2sN614mtOeHLto6wbtnclheeLIaJ8HJfiTJfwe5CWTUHAACw2BF6oCzt3btXx23YoOjwcOa2Yy/9lNac9z7tePSXev3VX53RdmOxwr+IYPGpGq25vqMroq0HBnT+sc2lHhIAlMxsJ/Tmo5/GfE/8TvR6hUIeS+mJ+3yFL7JwJzfHlmByV2WM3a9C56g3ki5bFU85iiUcmdEVH5Ykr8dSfzShZbXp8lqzORduCNA7nMisKkklHAV96eAjlnQmnJT949e16Hc7etQZjisST8pJ5R8Try05XkuphCXPaNBhTDrGaaz0ZYID27I0FEtpJJnS3r5ker9HtxGJpdQ+MKJltUEd11KlN62dWRhX6NwHPHamTNihcEwHB0bkmHTA5JikRpK5vVPc89dcFdDOruG87fk9ds45nihkW+gT4UfCSpT5CHal+QtXAAAAyh2hB8pSd3e3osPDevff3KimlWtlJLV7W5SSdNLr36g3nvazaW1v5zOP6Hc/+BclEonJH4xF45QVNaOhxyChB4AjWjEm9Oa6n8Z8T/xO9HqFQp6RREoJx6TLKiUdBby2Git9Sjq5HSzcK+Jf6xmW40iReFIe+3AIEPDaBfer0DmKpxwtrQnISNrTE5XkZDIWn8dWwGtrSVVg1uGTGwIEPLaGLUup0TAikXLktT3p15lgUnZbR1id4bhGkqn06o1C2ZAkr20p6LNVV+GVYyTHpAOPqoBXbb1RSemwwC1blUia9P6OHmJndFy9kUQmdMs+T147/VC34bm7GmHsKgW3EXq2hpBPHYPpVRsHB2JKjb6mkdHIaACU3TvFPX/nrGvIaebuahxT+myikG2hT4QvhpUoszUfwa40f+EKAABAuSP0QFlrWrlWS48+XsPxlPYdDMuypDVHrc2ZXJiK7n2vzdEIUUonLa/RT587qOcPDMoYQ3N7AEes+ZrQm435nvhtrgpoe+eQeiOJnB4d7jEZG/LcsrlN7QMjmUnvQuPLviK+rsKn9oERxZNOTqmoxkpfwf0qdI6Cvqy+Fz5bfm96Gx7Lks9jK5Z09GrX0ITNtqfCDYAaQj4NxZNKJYyMMUokJcdJyWNZWlVfMe7zH9nVq4aQT+0DqXEfY1tWpgzVVWeuljEmZ/LXDToaQz71RBIaSaYyIUfQZyuRcv/sUUt1IO88jbca4Yw1dXpitOebe7tbOiv7XFYHvFqyzK/9/SNydLj0ViLpKGXSAUzMc7iHiHv+NrRW68Sl1dreGcnrB5J9jicK2S49qXXWE+FzWX5qoa9EKZa5Dnbd11jo38UAAACLAaEHjgh90fQKjdqgd9qBB8rX8a3V8tqWuobiah+IaXldsNRDAoCSmY8JvdmYr74h7sRwJJbS3r5oJoxwe3RceGzTjMeXfUV8dcCrZbVBdQzGNBxPqSrgzaxqmGi/0vP8RsZIJy+vyUzYBzy2RpIpJR2jpExmNYbjaNxSQ1OdCHcDp+qAV6vqK7S/L6qheEqWJdWM9tF4fHefVtdXFHx+11Ass7+9wwklkvkdzdc1hbS8PrfviDv5u6srIscxcoxRTyTdBHwkmZJtWZJl5LUteW1Ly2uDqgp4C/59Pt5qhF+91KnGUG7A1BDyZUqHZbt441LdtbU9U15LkuS1lUo4cozJrNKRcs/fxRtzQwu3H8hIwtEtm9t0zrqGSUO9oNfWju6IJOmY5pAu3rh0yhPhc11+aqGvRFlsFvp3MQAAwGJA6IEjQt9wOvSor/CVeCRYSII+jza0VOnFg2FtPTBA6AEAC9hcXwE9dmL44GBMKccomUoHCD47XcJpb3/+5O5Uxzf2ivjqgFfVzV5FE46Obq6ccL8KTVy3D4zojDV12tc/omjCUedQTPGkk1kBIaVXRkj5pYamMxGeHehUB7yq9HvlKF1qypHUE0nISPrFix0FQ5Ts0KQ64FUyKfUP5B6/j529RktrA3nHVJIO9I9oeV1Q7QMjGkmmA4f6Cp88VlKJlKOgzzNpYDTeaoS+aCIv9KgOeOWzLS2vC+adk+aqgHqHE5lVK25JLseRWqoDBRvGZ783dnYNq3c4ocaQT0GfnbPipFBwsKoumDn2K+vSq2miCSfT72Qq5rr8FCWZAAAAsNAQeqDsxZOOIvH0L6Z1lYQe5Wzbtm3Tfs4SO/3e+N0f2rQ0diDnvqamJq1ataooYwOAcjGXZXImM5dXQI+dGI7Ek0qk0mWMQv50f4f+aKJgU+qpjm+8K+KPbq7U1Weuzhxbt+fEqvqg9vaNqGsopoODMQW8dt7qg339I7r6zNWS0ufmxt/u0kgit4ySlF9qaDoT4WMDnaSTXqnhhituU/F9fVG9rrVa4VhSO7uG9fDOHp24tFonr6gpuN9T4Y4zs1IkklA85SjhGJ2wrFp9wwkNx1Py2HbBwME19tiHY0n1RhIaSThq641mSoW5pcyOawlljmu2c9Y1ZJqlu/1bqgIevXfTMr11w5Jx98N9b9yyuU0VBZqa7OsfKRiaFeoHIk0vsJjr8lOUZAIAAMBCQ+iBsueWtqrye+T3jNM5E4vaUG+XZFn64Ac/OO3n1q07Saf/9S3a0tarf37f29y6IZKkispKvbJtG8EHAIya6zI5pTR2Yni0hYScMY3IhxPJaW/bDTN2dUcK9os4Z11j3rHd3jmk3+3o1rLaoKoDXvUOJ2SMyfy3K3viekNrtU5fXT+lUkPTmQgfG3Tt7rHzGrQnkkYej6VwLJnz+ts7IxpJOpkVKZ3huBorveofmPx1zlnXkDNOd6VIOJbUwcGYRhKOKnyeTNPxN61tGHeiPXs1QvYYl1T71TUUV3ck3Yzca1saSabUNRQv2AtlKhP8EwWDkx337PJlxpiiBBbzUX6KkkwAgP+/vTsPk7Ou873/ue/aq7t6S6/ZQwhJICQ4gJiogAsoKo4yZ46jg6OP45mLC3TgUcc5R895jOdR4FEvjs5hhsHlKM4MgzOjuIwjEEcMDDvEQAhN9qSzdXrvrq7qWu/f80d1VXpfq/uu7n6/risXpOruqm/ddXf3L79vfb9fACglJD2w6OVbW1HlsXglYlHJGL3r1i9r9cYt0/paI+mUceSPVOtj3/yp/MptZnWcPKqHv/EX6ujoIOkBAIPmuk3OZOayymTkxrDHlpSV7BGzwMr801s+D01mhHye3LyIeFpe29aFdWFdvX6ZjDG698nj6oqnCwPTu2JpZRyj410DCnhtJdOObFvqig+fNTFy43qqrYYm2ggfep49lqX2WKrwnGd6E4omMnKkwrwTSXJk5LcsdcXSwx4vNZg9GlqRcrY3qa+cPD7suKPtMT12sL3w93xCLei11ZVMDxson8o6w+Zn5E10HQ5NVjx7vHtYS6zOWFqOMYqnsgp6PaqP+FUe8E74eCOTE3mTJQbrygM60NY/7PXUlPkU8Nr6/359pHBbroVWYszXX1Pmm1YVBe2nAAAAsNSQ9MCi5shSXyK3ic08j8WvZsVaNV14ybS/ru9cv3oTGfnr16ipgrkeADCeuW6TM5G5rjIZuTFc5vfKKKPA4NyKgNfWsrBP62vD03rckYmifLXCiqpgoaXVQ3vOFCo58gPTUxlHqayRJcnvsWTbUiLtyFJ2RNzDN66n2mporI3waDKjYx1xPX6oc1jyJZHJDqswCfu9SmVzLbTy/7UtS36vreSIIeX5KtvJrpEXT/aOui2azOhoZ0o98bRsS/J5bRljFEtmtbJ69O/ryZ4jX43QFk2qK55WZyytlu4BxQaHstuy5Pda6hlIK+z3jFv1MtF1OFlicHV1UI8f6ijcnm8NZut8gi1/DSyvDCqVtYclp/L3Xb+xdsLXOvJ1034KAAAASwlJDyxqCSsgo9xGxVj9kwFJqgx61ZvIqC+RUVOF29EAQOmajzY545nrKpORG8ObGsrU3p9WecAz7Ljpfjp+skRR/nUFPLYSmfMJjVQ2Vz2Q3wjPD8z22JLPY0+4cT2VVkMjX6/XlvqTuQHuQ5MvWSc312RohUlNmU+tfUmtqQkVHi+azMiSpc5YatjryA9Sn+waefFkt7JGymQdJbMmNy/ESLKkgM9WOmuUzDjyB7yqCOaGv480leuwuTWqY51xtUVTsi2r8DyOkewhb3VXLD3muZ3sOpzs/W7pHj4PJOC1C/PnQiOqirpiadm2hs0yyc9qaemZ3owU2k8BAABgKSHpgUUtbuf+MV4d8smyrEmOxlJVEfJKPVJfIiPHGNlcKwAwJjfb5MxHlcnIjeHm1uisPx0/WaIo/7pqynw60zu0iiO34+/znP+d5LUtrakJ67+/a8O0YhjP0Nd7/1MnNJB2dKZv9GwTj61hFRyRgFf1y/2qKfMPOzfGGP3whVN6rbVfklTm9yjf+Gmya8QYqTeRluNItpVLQuQFvCp8eMU/WIHS2jf6ehj6HGO1QpOkh/ac0UDakZGUNUZZx8iylDvdOv+kqawzZsyTXYdTeb/z1T55B9tjYz5mKusoaNujjh/6fAAAAABGI+mBxcuylbACkqRq5nlgAmGfR17bUsYxiqWyozYWAAA5brbJcaPKpBifjp8sUZR/XZGAd1gFQFnAq5qwTwNpp1ARMJP2WlOV38wfWXGSH50xcobGB7Y2Fd735taodh/u1JGOmE71JBTwWEpmc79TW/uSuv7K2ildIyY/PH5IwsOypHTWFOaHpLLOuEmXofGM1YIqOPgajKSgz1Y668hxJEu5ahLHSJZlKeC1tam+fMyYPZalw13xYfM1IgFv4Tqc6vs9VMBjy/IrV3UyhN9ja0NdmRJDqlqiyUyhAuT+p04Uda4NAAAAsFiws4dFq3LtxXIsjzyWFBnRmgIYyrIsRYJedcfT6hvIkPQAgAm41SanFIYxz2SQ+mSJoqvX1+g7z7QMG1TdVBHQ9Zvq9Myx7lGPt7oqqPufOlH0Ye75zfiRFSdhv1c1ZT7VlweUccyo+H/12jn9aM9ZJbOO4smsMsaRpVwrLq+dax+193Sf3n1xw4TPbyRZtiQn9/+2lfuvMVIq40jGyOe1Ve7PremGJl1GGtmCKp8o6BlIqyrkk6Vc1YzX9sjnMUqmc0mloNdTaNn1ga2Nox63uTWq9iHtu4bO3shfh1N5v0dex/kWYEYa1vbqj35vudZUhwrHR5OZQsJkRWVwVnNtZnItAwAAAAsFO3tYtOq2vFmSVElrK0xB5WDSozeR0Qq3gwGASSzFDcu5qjKZ6rmczSD1KSWKrPP/tWRpTXVIa6pDw17v6qqgnjneM6MYJpPfjB9acZLKONrUUDZugqG5Naof7TlbSAKks7m2UbZtlM4Yef25F3WwPT7p8/tsW7YsZTTYbspSrtWVJI9tSZalZMbRhrqAPnz5ignf96EtqIYmCoxyiYrMYClJLvFhKRD0yue11VAe0Iqq4LjX1RNHukZV5AS8turLA8OOn+j9Hu86NsaMe23nj3/2eLeCXo+WlflUPuQDGkPn2kzlep7NtQwAAAAsBCQ9sGjVXbJDklQVorUVJlcRzP047E9m5DhmkqMBwD1LecOy2FUm0zmXczVIPb+RHgl4CxUJZ/oS+usnj+u2t67Vn+1YUzj2/qdOzEkM0liD3MsnTSo9caRLyezogeLGSM6Q+RiWhv9etcf4LErQaxe+xhpMeEiSbUshv0dhv0fLwj6tWxaeNNE1tIVUVyxduL3c71F2sIVUOmOUtnL/f0ljuf7kjasmfdx8MmXkjI3ueGpa1TfjXccTJUo2N0bUFk0qnR29RsnP95jq9TxX1zIAAABQKuzJDwEWnr6UUcXqjZIxqgqR28Pkgl5bPk9uWyaazLgdDgCMa6INS0zPdM7lXA1Szz9uviIhkcnKGKPOeFoP7Tmj5tbonMeQt7kxoj/bsUb//V0b9Gc71kwpCRDwnP/nhGdw6Loxkj2kynZD3fDHCftHtx1NOY6qgj5Fgl75bFuWJflsS5VBnzY3lGtNdUjlAe+UXmt+aLmkYUmZxoqAqkM+pTNGjoyqQz5dWBuWz2PLmMk/8FBXHhh1WzSZ0bloSmd6E0pnTSHRMPR9K5axnl86P9dmqtfzXF9HAAAAgNvYDcaidLAn9w9Xv0nL5yG3h8lZlqWKoFedsbT6Ehl+OAIoWWxYFs+RjpjaoqlRQ6nHOpdTGaQ+k7Zj+cdt7UtqIOXIMUa2Zal8cB7Z0E/fuzHMfSJ15QF1xdNq6c7kEgnO+UqNgNdW0OfRsrB/zPkYI62pCQ0bYH6ia0CJTFaprNGJrgEls44sSWGfR1959OCw8zvWeX/T2ir9cn+bBlJZ2ZbUEAmoPJD7PR/yD5/fIU2tRdRY8zi6YunCTI6h5qJqYrK5NlP92VBq1xEAAABQbOzrYVF6vSf3qb6QGf0POmA8lfmkRzKjmskPBwBXsGFZHM2tUbVFxx5KPVaFw2QbzuO1FnrT2iq1dCfGTYTkB5lHE5lCE6isMUpmHUWTmWEb1qUwzF06nxQ40hHTub6kso6RrFx1h21LIZ9H62pCWl9XNuW5K7VlAbUN2bSvKfPlkilZI09GyjhGibSjVNZRV9yrdNYUzu+zI+acfPeZFhlJy8r88nttnelNqHsgrZDfU6j8GJmomEqLKClXGXqoIyZJuqiuTA0Rv4K+0ZUrc5GEnGyuzVR/NpTKdQQAAADMFZIeWHRSWUeHe3PbBiGHpAemriLokzSg/mRWVRqj4TgAlAA2LIvjiSNdqinz6UxvdtjtXbH0mOdysg3nsVoLRZMZ/WjP2UJFwVgzFjY3RlRX5tdx74DSGUe2bcnnyQ3Y7oqnRw3Insow97kcdD80KRDyeWQkOcbI77Hl83uUyTpKZhwd7oirKuSbUtsoSdq+tko/e/Vc4e+RgFd+j62AJzeA3HGMgj47d15i6cJMjV/ub9OysuGb+p2DczzyszeWVwbVFUurdyCtZWGfAl67MAg8P0fFtnMzU7piw5MV+fu/+tghee1cNdCqqtz7OZB2VBXyKZEZPddkvCTkWO+NpCm/XxPNtZnqz4apXkcTxbyQZn8s9PgBAAAwfSQ9sOjsPxtVypGSvZ3yhdOTfwEwKOC1FfDaSmYcJS0+MQ2gNE13wxI5Izc+j3TEzm+Ix9NKZhwFvLYaIoFxz+VEG85jtRbqiqWVGmPQ98jWR1ljtLYmNOpT+qmMM+aGtZTbJD/cHtPLp/tU5vdofW1ZYQN9LgfdP3Gkq5AISGYdxVNZ+Ty2fB5bqayjRDr3eh3H6OUzfeqIpfTJ7asnfe4N9eX6o9/zDLuuE2lHQZ+taDKjQ+0xZdO5BErMkz3fiqw/qf5kdliLsnwrrLx88mMg7ag65NUrZ6MKeNIK+mz1DOTWiisqgzrTm9DB9piaKgKFwfL592Qg7SjkM4VqoHzSxRrnMxJjJc7GqiL5zjMthRjzt431fk1l4346PxsmupYni7mY19NcW+jxAwAAYGZIemDRef5EjySpff/T2nDl77kbDBaciqBX7f0pJayxh4UCQCmY6oYlcsba+GyLpgob5/kNZ0laURWc0XOM1VoovxE/0lgzFtJZU6hISGUd+T22NjWUjVnF8dCeM8M25DtjufZPZ3oTCnrHnmU21oyJiTbSm1uj+ukrrYVWThtqy/SBrY060hEb/jqNlEjnqjuGPrNt57IBrX1J/fWTx9VYESg8x8qqkMYy8rq+/6kTOtDWr5buAWWz5nz7L8eopXtAtWV+ZbJGCWt4izLbsuQfcd6jyYy64mmFfLaaKnKzSM72JVXm96ipIlCo/Ah4bHXFc5UkXbGxPzwztNIk42jKiYaxqoG6YmnJ0rBrUBo9Y2SqG/fF/tkw0XD0yWaglIKpxA8AAIDFh6QHFp180qPj1aclkh6YpkLSwybpAaA4SnlDcKkYa+OzpsxX2NweaqZtwsZqLRTw2GMOuR5vxsLIBMwHtjaN+tr8axm5Id/al1SXJ62egbSqQr5CQidvZKJlstkV33mmZVhyI1+1ka+MyPN5LWXTg0PMh5Q9+DyWMo5RLJ0tzNfIP8d7NtePel2pMVpEXb2+Rs8c61Y6Y2TZkhk8xLKkdNZRWzSlhkhA3SNisjR6ZsfQgeP585zM5JJL5UPOU02ZT619uaqdWCqjVMbIMUYeO/d6vLY1rHqnPuKfcqJhrGqg5BiVQNLw98vNjfvJhqOXeiXFVIe7AwAAYHEh6YFF5UxvQqd7E7ItqfP1590OBwtQRTD3YzEtn3xlFS5HA2ChK/UNwaVirI3PSMArr21rRVWwKG3CxmottH1tlZ4ZMmQ7b2hiJZ8UG0hnFU9lFfZ7dWFdeNxY8q9l6GZ5xjFKprMqC+RmbAwdyp5PfIxMtDxxpEtt0aTORZNKO0Y+21JDJKAnj3apsz+l450DSmcd2ZYlnzc3Y6QznlZmxCa917YU9NnKDKnEyM8kGUjlZpSMrLp47sToc5LKjp79sbkxovqIX53xlPKjQc7nVXKzT+ojAYX8nlEtyj7+xpVjtsoaKjDYkmuoSMCrQI2t0z0JxVK5CpKA15bHtgqPUe4/P7h8OkmysaqBAh5bY40RG/p+zWbjfqZJ1/zXvX6uX/GUI48tlfm9hWRaPr5Sr6SY6nB3AAAALC4kPbCo5Ks81kYsZRIxd4PBguT32Ar57Fzf7w1UCgGYnVLfEFwqxtv4vLAurD/bsaaoz5XbnDcyRlpTE9aamvC4rY9GDgUP+XKb6W+9oGbc5Ev+tQQ8thKZ3KZ8fgC6JJX7PcoOZgiGtmEauTm/70yfTvacPyeprNHJnoTSjqNYylE668goN28km84NEU9mHIV8tupDvmFtuJaV+VRX7ldbf2rYeXaMUdA7utqlMzb1T9lXh3yyZclYGpYcKPN7VBMeXrmRt6IqOGarrJHXQE2Zb1jFTDSZUWtfUpmso4yTS3aks0bpwYSMJWkglVXQm1srfGBr07SSZGNVA9WU+WSNkfUY+n7NdON+pknXoS3UEhknlxjKSkYZJTK5ZFo+vlKvpJjqcHcAAAAsLiQ9sKg839IjSdpYNc5USWAKKoJeDaRTWnbR5W6HAmCBK/UNwaViPjY+J9pgHi+xMpOkWP611JT5dKY3l/RwjBTw5tY+jRUBGUld8bTSWUcrqoJjVo209499DbZHU6oO+xW3pKHFF8m0I8dIHiuXTBnZPusDW5tkjNHP9rXqYHtclozKA15VBr3D2kdJuVZXHV1T+x7oS2TkyCjrGFmSLFuFJMH7tjTomWPdhWPzA9YT6azuf+rEsKqGsa6BSMCr6zfWqqUnoZdP9+lsXzJX3aJc9YwsSSZ3fjOOkc9jKezLDY0fSDs61hnT7sOdU66iGG/QuDFGTx7t0pH2mGKprMr8Hu0+3CljjDY3RgqxDx0gH/DY2r6uesJzN9Ok69AWavlKnnzypzzgVX15oHA9lXolxXSGuwMAAGDxIOmBRSORzmrfmT5J0saqsYd4AlNREfTqXDSlmo1XuB0KgAWu1DcEl4q53PjMtwF67kS3HCf3yX1Jhc3pv37yuG5769oxN5lnkhQb+lq8tq14OiOvnZHXY2lZ2FdIMEQCXq2oCo5KuOTjjaUycpzhSQQpV9lRU+ZTfyqjbDrX+skYo6yRApbUEDmfVPHa9qhWXENf58hEUN4Vq6p04GTbuK9x6Ncf7x5QwGtLcpR1chU0ZX5bq6pDevfmeq2pDhUSBvm5HWnH6Jlj3frt4U5tbYroA1sbJ7wGmlujevpot/weS+mMlFUu0WEG8x75s2OMCq26osmMfvS7s1pTnRvKPtUqinwFSv59+Je9Z1RXHtDq6qBO9yQUHKz2Gfl4b1pbpR/97mwu4eG1tSzs0zPHurWmOjTu88006TqyhZrXzrUrsy1La6pDuYTQoIVQSVHs4e4AAAAofSQ9sGjsOxNVOmtUX+5XXXDsoZDAVFQEvJIxKm9ap77U6B7jADBVC2FDcKmYi43PoZv6A2lHxhi1dGck5TaKpVxyYLzN8JkmxUa+lvGSCyOvs6HH+T0eJU1WjiPZdm5At89jy2tZigS8Wl0dUmtfUrFUVpmsUcBra011aNKkysg4hyYavLZkJD36+tQSHvc+eVzxVFYyuefPn9Og16P1teFh5+L+p04o6PMomswUzmnGMXqhpUf7zkZ16WDyY6x4nzjSVdjgty2r0B5MysVrNHrsRj6pNbL64mf7Wie9zsaqCnrmWPeo6hnpfFVGS3eikGAZ6/6x5K+vkTFuaiibML6xWqhJ5xM+Q69PKikAAABQikh6YNF46WSvJOnyVZWyrB53g8GC5vXY8imttPw62md0rdsBAViw2BAsrpkOZZ4rQ9sH5TeI05nchrnXbynjGDmO0cH22JgVH8VKik31Ohsab33Er1M9CXksyWNZCg0O+X7X5jod7xzIzcmoy/1T4WB7TMsH22ad6BoobJ4n0llNZmhlQ/61Zib5svyxXfG0fB5LibRRdnCIuNe2lMo6o85RvjohP6Mj4xgl0o4sSX6v0YG22LjJp/b+ZOH983ktZdKOxvrIg89jKf+xmuRgG6yhSatEJqtXzkTV3BqdUvuooZJZZ9gMlry2aErNrVE9d6JbA+nceR+aHJmoauPq9TX67jMto2Js708VYhzre2qsFmqSCrNZRp57KikAAABQakh6oCS0tLSoo6NjVo/x1KHcP3KrM11qbj5QjLCwhAWdpNIev472UTUEYHbYECyOmQ5lnktD2wflN4idwSqB/KZ70GfLGKPOMSo+ipkUm8p1NjTehkhAktTWn1Im66i23K/3XdKgd2+u169eO6df7m9T90Ba1SGf1taElMw4ozbPz0VTk27w5403X2KiYwOe3LkbOVNiU335qHOUr07IV2zkk0/5Ae+pwdvHqoyoKw+oK57Wmd5sro2TLGUH0x4+j+S1c8/vDA43jyYzSqYdpR1Htiz5vFahCsXvsSedmTFW26mAxy7EOJTXlh7ac0aOk2szlshkdaY3N0w8EvBOWBW0uTGi2jK/OkcMnS8PePXk0dw5Hu97Kn9d+mxLsXRWZT6v1o9oZTaXSi3BCQAAgIWFpAdc19LSok2bN2sgHp/xYwSrG3TNV38mJ5vRn77/ncoM9EuSksmxexkDkwmapKKK6Egf7a0ALF4LaWNxpkOZ50L+vB3tjBfmeEQCXi2vDOp454CyJrdBnq9MkDQ4l2J0vDNJis30fRvZTqshElBDJDCsTVVza1TPHu/RsjK/lpXlNtT7kxm19o1eUy0r8035/I83X2K8Y6PJjFJZR7FkVraVSyz4PbkWW5etyLWzGqs6IV+xkU8++TznkxHS2JURV6+v0ZnehJZXBtUVTyuWysrnySUy8u+bxzbKZI3KAx51xdNqiPh1qjehrDHKpk3hvV5W5pt0ZsZYbc1qynyFKpWhzJD7h1ZddMVzVSGTVQVljdGamtFtsdqiqQm/p/5sxxrXfhaUYoITAAAACwtJD7iuo6NDA/G4Pvi5r6t21QUzeox+K6wuSUErq//r7gd0+MUn9PjffUvp9Oh/PAJTETApOdmMupNetfYl1FgRdDskACiqqWwsllJSZKZDmYtt6HmrCvl0pjcx7JP365YNDrbuS8oMmQ0R8to60TWgwx0xGaMZn8ux3rfvPNOiujK/ssZM+D6NbKeVn/WQSDu6/6kTunp9zZgb4eUBr2wrKb/HM6piYKrnf7z5JWPxWFbh2MBglUcy7agq5NP2tVV65njPsNc/tDrhZ/ta9cqZqHweS/bgAO6MY5TKOjrYHtOysG9UdcrIiptyv0cZx6gvkVEslUs0lPk9umJVharDvkJsvYlMYSC840grqoMqn6T6Qhq7rVkk4NX1G2vV0pMYVvXzL3vPFO5fXhlU12DVhm1Z+vDlKyatuphobkxbtDS+p0YqpQQnAAAAFiaSHigZtasuUNOFl8zoaw+2x6R4WnXVlWqqalDHyaNFjg5LjS2j3uOvqXr9Vr18uo+kB4BFZ7KNxVL7tPVMh34X29DzNnQjuncgrU0N5bp6/TIZY/TXTx5XZzytgNdWyGureyD3QYyg1zOrcznyfcsP7u6Kp7WmOjThYw/d3D/cHldXPK1lZT4FfXbh6zpjKfUns4W5HfkqFr/X1qqq0RUDUz3/+Y3+aDKjrv60yjT6scbitc+3jrqwNqwT3WMnToZWJzS3RgvJjxxTqPwIeO0xz8/QiptfvXZODzx/ShnHSEZyjFEsmVVDxK/TQ67BxoqAzvQOttGyrMKQ96HVF+MlDqfa1mzodR8JeAuzPFZUBafUZmqiuTG7D3eWxPfUSKWS4AQAAMDCRdIDC54xRn2DGwlVIS5pFE/XgRdVvX6r9p7u07s217sdDgAU1WQbi6X2aetiDf2ejfEGSkcCXvk8dqFFlCTd9ta1hXhPdA0Ubs8Pg5Zmdi5Hvm9dsbQyjlF3PK1k5nxc4z12fnP//qdOFIaX5+USKEn5vbkkw9D5ERfVlWkgPXrmxETnf+SG/5qaoJ443K2M40jDn1r/tOeMoqm06soD6h5ID6tqyFeWZJypbYgPHZ4+NPm0LOwrJCYmOvct3QlVh3w605eUY4xs25LPY2n34S5trC9TerDpVCHpFU/LtiytqAoOS15Mljicyns/2+t+ogSLMcb176mxlEqCEwAAAAsXO8RY8PqTWWVN7pOAZX6P2+FgEek6+KLWv+cTevl0n4wxsizL7ZAAoGgm21gstU9bF3Po90zkN7CnOlB6WFVFR0xBr6fQEipvJudy5PsWS2WUSDvy2NawuHz2xL+zxnp/u2Jpee3Rx3bF0/qzHWtkjJny+R9rw/9E14BqynwKebzq6R1+fFs0Ja83d1xbNKWaMt+oWRT1Eb+M0ZQ3xDc3RtRYESjMJhn5fONp709qIO2MSgqlso5GLgXySa+xWk0VI3FYjOt+vASL299T4ymFBCcAAAAWNpIeWPB6E7kqj4qgl01pFFXP0VfltXKbPad6ElpVPbVWHACwEEy2sViKn7aeydDvYslvYE9noHQ+3uls1E9m5PuWHSy+yA/szouls5rIWO9vMuso7PcWhmrnqywaygOFjfCpnv+xNvyTWUddsbRWVEz8T5D880cCw4/Ltw6bzob4TK7juvKA9rf2j7rd77GVcTTlREGxEodzed27+T01nlJNxgAAAGDhIOmBBa9nICNJqqS1FYrMyaS0OmLpaJ/R3tN9JD0ALCqTbSzyaevh8hvYMxkoXcx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      "text/plain": [
       "<Figure size 2000x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the color palette\n",
    "sns.set_palette(sns.color_palette([\"#4796C8\"]))\n",
    "\n",
    "for i in df.select_dtypes('number').columns:\n",
    "    fig, ax = plt.subplots(1, 3, figsize=(20, 6))\n",
    "\n",
    "    # Plots\n",
    "    sns.histplot(data=df[i], ax=ax[0], kde=True, alpha=0.7)\n",
    "    sns.stripplot(x=df[i], ax=ax[1], alpha=0.7)\n",
    "    sns.boxplot(x=df[i], ax=ax[2])\n",
    "\n",
    "    # Stripplot median and mean line\n",
    "    median = df[i].median()\n",
    "    mean = df[i].mean()\n",
    "    ax[1].axvline(x=median, color='#6AA2D8', linestyle='-', linewidth=3, ymin=0.35, ymax=0.65, zorder=3)  # median\n",
    "    ax[1].axvline(x=mean, color='#6AA2D8', linestyle='--', linewidth=3, ymin=0.35, ymax=0.65, zorder=3)   # mean\n",
    "\n",
    "    # Title entire figure\n",
    "    fig.suptitle(i, fontsize=18, y=1)\n",
    "\n",
    "    # Hide ticks while keeping labels\n",
    "    ax[0].tick_params(bottom=False)\n",
    "    ax[1].tick_params(bottom=False)\n",
    "    ax[2].tick_params(bottom=False)\n",
    "    ax[0].tick_params(left=False)\n",
    "    ax[1].tick_params(left=False)\n",
    "    ax[2].tick_params(left=False)\n",
    "\n",
    "    # Hide x and y labels\n",
    "    ax[0].set(xlabel=None, ylabel=None)\n",
    "    ax[1].set(xlabel=None, ylabel=None)\n",
    "    ax[2].set(xlabel=None, ylabel=None)\n",
    "\n",
    "    sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6b1cf8c",
   "metadata": {},
   "source": [
    "---\n",
    "### <a id='toc1_1_3_'></a>[Linearity Analysis](#toc0_)\n",
    "Preliminary examination suggests that `Length of Membership` exhibits a noticeable linear relationship with the target variable. However, it's important to consider that in a multidimensional context, the combined effect of features may significantly influence the model's predictions, even if their individual linear relationships are not apparent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "350bbde0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1250x1250 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the color palette\n",
    "sns.set_palette(sns.color_palette([\"#4796C8\"]))\n",
    "\n",
    "# Pairplot\n",
    "pairplot = sns.pairplot(df.select_dtypes(include=['number']), corner=True)  # 'int32', 'float64'\n",
    "\n",
    "# Loop through axes; remove the ticks\n",
    "for ax in pairplot.axes.flatten():\n",
    "    if ax:\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b38d8118",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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E9GVt+vMOoKa25sM2DdbknFU/St4uuo2l0Wg0mqOCpY6EH20j5V4QMVbyCaL5U5C37pnka/fvrRM5oCateuKgPy+MMA0xpxnZEEnL6tiUBcfmu9JoNBrNMclSR8KPhpFyKSWTlYBpd/4qzHjJ5+sP7OXBPfUJyJYh6M3OGIolkqIbsLE7zVDP7Byd1bCVfKXRYkej0Wg0mlWCG6hJq/mqOVEk+fFvRrnt4WEqNbuvDAFpy8AUahlnhCQIldBJ2wav3bKurorlmAbdGRvHOvYdLVrsaDQajUZzhAmiiEf2FhgpuNUgwGbttV1jZW66bw/PjNUnIJ+yViUgT5aDmZwdT2Iago3daV67ZV111Nw0VMsq5xw/EuD4eacajUaj0axC7n1mnFse2se+KbcaBLg+79QJlIof8h+PHuAHT9UnIGcdkyvOWc9FJ/VgCMFgF5y2LjcrQdkQ4qhNP14OdIIyOkFZo9FoNIefSEp+sWOMf7r72WoQoGWKutbT258/hBdG/Mv9exlrCAd80YndvOXcQTpbSEA+mtOPlwNd2dFoNBrNshFJedRMOx1JKvH4+20P76fsR/RkbQTqOjmmwM7ajBU9vnj3sxQa1jys7XB4+/M3sGUg3+zQdRwL6cfLgRY7Go1Go1kWtu6Z5JsP7WP3RIUglFimYKg7zRXnDq7aHJulsBhhF0aSyYpPyQt5dqzM/oJHR8qqCh1Q01jTbkjRi+qCAU1D8NrnruWSLf0LmoqPpfTj5UCLHY1Go9Esma17JvnsT3dS8kI60zZ2Wu2i2jla4jN37eB3nzfIQGdqxao9h7uitBhhV/ZDJso+YaQkTKESEIYSKzVznl4QMVryZmXmnLwmyztesJHBrtmj441kbJPuOF9Ho9BiR6PRaDRLIpKSbz60j5IXsianknrdICKUahpopODxf+9+lg7HWpFqz+GuKM0n7D77052zEpnDSDJRVonNteTTFmbs0bEMmCwHTDVk6wjgki39vOHsdQuKN9s06EpbpI/zllUzjk+nkkaj0WiWje2HSuyeqNCZtin7EfsmK+yfchmecjlU9AklhKEkmzLI2GZVFGzdM7nk106Ex47REhnbpDdnL/tr1NIo7FKWgSEEKcugL+dQ9kK++dA+onj2p+gFHCi4s4QOwFBPmvV5h4mSz76pyiyhYxuCU9ZkFxQ6hhB0Z2zW5VNa6MyBFjsajUajWRKTZZ8glPhhxEjBxQ0ihKBuRDoCKn40pyhYDO0Kj+WgVtg1emGEEOTTNrsnKjw9UuTQtMd4yZ/z9afKAUEE5SCidu2VKSBrG/RkLV5/1sC8QifnWKzLp47ZNQ/Lhb46Go1Go1kSXRkb04Cx+MZuGgIJSFQbJrnVT7shPRlZJwq2Hyoten1Dq8JjKa/RSCLs7HRzAWKbgqlKxLNjJTpSzassUSS5a/so//rwMBW/PinZMQVZx2SwM1WXs9NIyjLoytg4x+koebtosaPRaDSaJbF5TZY1OYfRUhHLEAghaIxwEyjvihtEpG0T2xQUXLXRe7G0IjyW+hqNdGVsLFN5dFJW/etKKSn7IUKIOSstu8fLfPW+vewYLdV93TRgfUeKC0/sZsv6zjkTlE1D0JW2yTq6XdUOWuxoNBqNZkkYQnDRph6ePlgkDCWi5j6cVHdMQ/05jEWQH8pqBsximU94LNdrNLJ5TZah7jQ7R0s4OadaUQojSRBFTFeaL9x0g4hvP3qA7z95kKhGBwqgO2uRMg2m3ICf7RjjxL7cLKEjEHSkTPLHYfrxcqDrXxqNRqNZMucOdZNPWziWIJKqVZPckpNqjwDMuOpTqPgMdafZvCa76NdMhEeh4s+qJC3XazRiCMEV5w6ScUxGix4VP8QNQjVWXvKbLtz89b4p/tcdT/G9J+qFTtYx2NCVpjNlk7JMurM2FT/iu48fqPP5ZGyTdXmHroythc4i0WJHo9FoNEtm85osm/uypG2TgU6HdZ0p1nQ42KYgjCRhJLFNdaMeLXpkHJMrzh1c0s27UXi4QUQkVatsuV6jGeds7OKal2xiqCfDtBcyUQ6oBBEbu9O8/flDVZ/NRNnn//ziWT5z1zMcKs600gwBvVmbtblUXRaO2l1lsb/gsXu8gmUYrMk59OUcLO3NWRJ6NxZ6N5ZGo9EsB8kYeNkLyadt5ZmpBIyVPCKpllZmbHNlc3Yi1bpayZwdP4wYL/lUgrDpws1ISn76mzH+NV4FkWAKOG9jF08emKY7Z2MwW4RFSCbLAe99yYn81km9Ov14mdCeHY1Go1lBjqddUUnFIxEeBVcJj7MGO3nxSb0M5FcmQfmcjV2cvaHzsFznghswVQ6QSAwheE5vpu77eybK3HTvbAPy5jVZ3vH8jQSR5DejJYJQ4phNxE6kJrIGOtNa6CwjWuxoNBrNCnG87YqCwys8ajGEWLbx8mYEYcR42ccNoqbfTwzIP3jyILWbHjK2weXnrOe3N/dWqz7r8w57JirYNcs/hVCVn6lKwKa+7LL6jDS6jQXoNpZGo1l+Zq0UiKeGChWfjGPOWimgWb1MuwFTlWDOcMBH9xX42v176nw5AC84oYsrzxucNQ32xPA0X71vNxU/oiNlkbIMQon+bKwgurKj0Wg0y0xjsm/SjkhZAifnMFr0+OZD+zh7Q+cx29JaDSy1hRhGkrGSN2c1Z7Ls840H93HfrvqVFGtyDm+7YANnDuabPu+5Ax284/lDfP/JEfZNuZSDCMsQbOrLHtNVvyOJFjsajUazzByJZN+V4mj0HEVScsdjI3zviREOFT2QYFtGWy3EohswOUc1J5KSn20f41tbZxuQf+f0tVx65jpS1tzTUxnb5KWn9PHy09Ycddf2aEWLHY1Go1kE84mAI5HsuxIcjZ6jrXsm+dIvd7FjtEQklZfHsQSOZcy5lbyWMJLVSatm7J2ocNN9e9h+aLYB+e3P38DG7kzT5wFYhkF3pn4r+WoXu8cKWuxoNBpNmywkAo5Esu9yM8tzlFbvpxXBcKRIznmk4CKlEpUS8IKI8dBnbcfMctBmLcT5qjluEPGdOAG50YD8u89bz0tO7p2zKmMIQT5t0eGYesLqCKHFjkaj0bRBKyLg7A2dTVcKwEyy72qeuDkaPUfJORcqAVKCZc7s6BJCrakYL/usyTmzWogLVXMe3V/ga/ftVS2xGi44oYu3njdI9zyiNeuYdKXtuvBAzeFHix2NRqNpkXZEwBXnDvLZn+5ktOhVA/Zqp7FWItl3uTgaPUfJOadtg5IXISUEUVS3nqHiR5T9kFBSbSHOV82ZLPvc8tB+7n12ou7ra3I2V12wgbMH557edUyD7oyNM493R3P40GJHo9FoWqQdETBXwN7RMHFzNHqOknPOpgxAkviGk3cg4//GSr5qKaUsDk67TSetEgPyv24dpuTPVHuM2ID8+nkMyIYQdKUtcnNsPdccGfRPQ6PRaFqkXRFwpAL2lko+bSGRTFUC0pZByjLqxN1q9BwlPikD5dMBmixjgEhCGEZkHaOp0JnLgHxSnzIgD/XMbUDOORadaUu3rFYhWuxoNBpNiyzGeLzYZN/FjHwvx5j41j2T3PLQPopeSBAGmIbAMQU9WYesY65az1GyAX3bwSKJ2pEowVPboFL1GMHu8UrdqgcviPjOYyP85xMjswzIb37eABdv7sOYQ8ToltXqR4sdjUajaZHkhrrSxuPFjHwvx5h4rfm6J2OrBZ6RpCIlBwouvVkbP4xWpeco2YD+8R9tRxJiCQhlvdBxDCVY3VBSqATVrz+2v8DX7t/LwekGA/JQbEDONq9gGULQlbHIOfpWutrRMlSj0WhaJLmhZhyT0aJK1o2kxA0iRovesoiARHDsGC2RsU16czYZ26xOe23dM7ksz2mk0XzdlbFZl0+TttVu7jBS00wn9mZaHjuPpGTbwSL375pg28HinOsWloNISnIpixef1ItpEGfsqJucbUBPxmKgK41lGpiGGgWfLPv80927+NRPdtYJnb6czTUvOZH/9lvPmVPodDgWA50pLXSOEvRPSaPRHPMsZwrwShqPFzPyvVxj4s3M11nHJOOkcYOIih8ShPCuF57Aaf0dC76XwxlI2PhaQgiEkOTTFmnLwLEMBAKJpOgGbOhK8cxYqakB+VWnreWys+Y2IKcsg66MjWPqWsHRhBY7Go3mmGYlbrorZTxezMj3co2Jz2W+FgjSloljGoyV/Lr2z1wczkDCZq9lGXCo6DNZDjCyNrYFfhhRdAMsUzDlRnz1vr11x9nUl+Edz984pwHZNARdaZusYzb9vmZ1o8WORqM5ZlnJm+5ijcfzsZiR7+UaE1+u1OfDGUjY7LXCSJJ1LNYCoyWfqYqPH0bKaG0pwTZWmhFsaUsZkF96cnMDskCQS5l0pq1V5VHStIeuw2k0mmOSxhthyjIwhCBlGfTlZtYGrKSPpF1qBUczmgmOxTynGYn5ulDxkQ3XJDFfD3WnFzRft1NpWiq1rwWqehPGKYIZx2Jt3iFrW1xwQjeGEBwq+nUhg+cPdfHR153Gy09d01TopCyD/rxDd8bWQucoR4sdjUZzTHI4b7rLxWIEx2JFSqN5GFgW83W10mTOXWkKouUJJJws+/hBhCGUqGvUrYYQlP2QH28bZaw083q9WZv3vuRE/mQOA7JlCPpyDms7Utjam3NMoNtYGo3mmCS56VopqPghoZSYcWVHCLEqU4CTaa921kws5jnz+ZiWar4+nEtQs46JYQjcIKozDEspmfZCxkt+fcaOgFedtobLzhpoakAWCPJpk3zK0gs7jzG02NFoNMckXRmbSEr2TrqEkfqtXwiqAXmmIVZdCjAsbtqrneckPqaiG5CxLSxbICXsOFSs+pg+eunpizZfN8siknGFKIgk027AyWuWlkUkpUp3zqcsBvIOeyYq2FkbgcALI8ZK/qx05BN7lQH5hN7mBuSMbdKVtrB0JeeYRIsdjUZzTFJwAyp+iBdXLgyhAubcIGKk4JKyBKf2d6yqFOBkRD6IJO+8cAiAQiVoSXC0MiEWRBE3/mo3o/H27mnXBQRCxO2lsl81Dy/WfN1YabJNg4Ib4AWSSEoMAdNuyCN7pxZlDneDiPGSTxBFCAGv3bKOr963m/Gih0Qw7dVvLndMweXnrJ/TgGwZBt0Zi7Stp6yOZbTY0Wg0xxyRlHzroX3YlkEoQ6JIYhpC3fiFJIgkIoTLz1m/aoyn87WWWhUe802Ibd0zyY2/2s1TI8W63VGmoXJpvCBCCMH2Q6VZY+rt5hQllaYv/XIX20dLyDjgL20pr9Shotf2NJyUkslKwLRbP/r+3IEOXrJ5Df/x6DBeWF/NOWVtjj+66AR6mvhyDKGCBTscU7esjgO02NFoNMcciTm5N+uo5N+ShxdKpJQIBCkLUrZJPr06WlgrnUuTHH+yHNR5WCQQRGAZSgyGkaTohYyXPCBXfe5icorO3tBJR9oi55h0pEwsM14oimprtTOCXlvNqaVQCfjmQ/v45TMTdV/vTFu8/fkbOHeO88s6Jl1pWy/sPI5ouzn58pe/nImJiVlfn5qa4uUvf/lynJNGo9EsidqJoKxjMtidZn1XinV5h/VdKQa70xhCHHZzcrP1CSs9Il97/NwcgXhBBFEkEUI9vuCqVtBS1lBsP1Riz0SFnqxDR8ombZmIeA95q9NwUkomyj4Hp906oSOl5Ofbx/ir25+qEzoiNiBff+lpTYWObRqs7UjRG3u2NMcPbVd2fvKTn+B53qyvVyoVfvazny3LSWk0Gs1SaJwISlKAE9wgOuzm5LkqJBdt6l2WBOS5qB3BL3pzpx8HEpBgCuhIGUsOB1xq2OFc1Zx9kxW+dt9eno7H5RPmMyAbQtCZtuhI6WbG8UrLP/lHHnmk+ufHH3+c4eHh6t/DMOR73/seGzZsWN6z02g0mkVwuLaTt8p8bapnxsp4YURnuvk/x0sdkU+yaBxLMFVeeNVDJOHr9+/j4LS/JBG22BH0ubw5fhhxx+Mj3PH4wWpwIKjgvzc/b4CXzWFA1i0rDbQhds4555x4uZpo2q7KZDL8wz/8w7KenEaj0SyGxWTPrBQLVUgOFFzcIMILo7rqU8JSc2mGCy5FP2TKDerSg+fCNgXDBZeb79+LFyxehC1GcKpqjkfQcKJPDE/ztfv3cKBQ31U4b2Mnbz1/kN6s0+T8DHoyNs4cCz01xxcti52dO3cipeSkk07i3nvvZe3atdXvOY5Df38/pqlH9zQazepgJbeTt0okJT/eNsr2QyXSjgEN2koIQXfGZrjgMlHyWZc3WhIFrU5Hbd0zya0P70fK2enCc5FPW/RkbCXCwggviJqOZS8kwtoRnFJKJssB03GbLZKS3eMVDky53PPsOI/sK9Qduzdrc9X5zX+GumWlaUbLn4bnPOc5AEQN/VONRqNZrazUdvJWSDw62w+VmKoETLtQKAf0ZJ26zdmOpaaUbNNoqQrV6nRUbUWpvyPFyPTsikktAjUeno1HsbuzNsNTLhNln3VWayKskVYEZ2M154nhae54bJhnJ1zKXlg3PSYEvPLUNbzhrHVNBVjOsehMW7plpZmFkI3LVFrg6aef5ic/+QkjIyOzxM+HP/zhZTu5w8XU1BRdXV1MTk7S2dl5pE9Ho9Ec5dR6dNKWyaGiB6jqimEI+jtSVcHjBhFlP+TK8wa5e8eYEjGREgWNImaW96dBFNWOqG87WOS67z1NxjZJWQYlL2T/VGVWK0sAlimIIknKMhjsTiMQRFIyUnCxTQMpZVMR1upIfLNKlIC6ag4ooXPDr3YxWQ5o3GtqGYK3njfIS0/pm3V8xzTo1i0rzTy0Xef7p3/6J/7kT/6ENWvWMDAwUKf2hRBHpdjRaDSa5aLRowMwVRG4wUyWzXjJI+OkQVKtkFyypZ9LtvTPWYVqdzqqcRoq65is70xxoOBVx9ijeIVGFEkMQ63RSMbD/VCStk2uPHeQu3eOLakV2Bh22Myb4wYhX7l3N2OlemOyALoyFmEY8eDuCV5ycm/1mhhC0JWxyDm6ZaWZn7Y/IR/96Ef5m7/5G/7iL/5iJc5Ho9FojmqabVvvyTqMFNSOLiHUzb5QCfCCaFabaq7x8vm2uCNUO2z7oRI/3jbKy07pazoNlXUs1uUF4yWvujsqkpCxBL25mWpTbZvqkjP6ueSMuUVYO0RSMtVQzQF48sA0X75nd91mcoCMbdCbtbEMAy+M2F/w2D1e4cTeLLmUSWfaWjUJ2JrVTds1v/Hxcd7ylrcs2wns3buXt73tbfT19ZHNZjnnnHN44IEHqt+XUvKRj3yEwcFBMpkML33pS3nsscfqjuG6Lu9973tZs2YNuVyOyy67jD179izbOWo0Gk2rjJc8Kn6EH0ZU/BApJVnHpD+fijdtCyIJFT9iU1+25VZQbVBiLSUvZN9EhUPTHlOVgC/+4ln+6jtPUqj4DHWnKVR8at0KWcdkfZcSNoOdKdZkbVK2iWmo1pUbRIwWvToRllRmLjihm1PW5hYlMCp+yEjBrRM6BTfgy/fs5u/v3FEndEwhWJtz6O9IYRnqNmWZqirmBiH9eYfujK2FjqZl2hY7b3nLW/j+97+/LC8+Pj7Oi1/8Ymzb5rvf/S6PP/44n/jEJ+ju7q4+5uMf/zif/OQn+dznPsd9993HwMAAr3rVqygUZtz51157Lbfddhvf+MY3+PnPf8709DSXXnopYRg2eVWNRqNpj2bJx83YumeSm+/fS9ELOFBw2T/lsnuiwljJwxAwkHfoSltkbIPLzhrguted1nIrqLZSk1DyQkam1ei6EGAaoppw/LmfPcN5Q11kHJPRoqrkJGJmrOiTT1tcc/EmPvCKzWzqy1KoqHMuVAJObEOEtXLtxks+h4ozbSspJb/YMcb//M5T3L1zvO7xWcdksCtVZ+IGCEOJYwqGerLYejO5pk3abmOdfPLJ/M//+T+55557OOuss7Dt+rHDa665puVj/d3f/R1DQ0PccMMN1a+deOKJ1T9LKfn0pz/NX/7lX/LmN78ZgK985SusW7eOm2++mT/+4z9mcnKSL33pS3z1q1/lla98JQBf+9rXGBoa4oc//CGvfvWrZ72u67q4rlv9+9TUVMvnrNFoji9qp58qfoQhYH1nindcOMR5NWKg1jzsmMqjE0i1dNQNIsbxQai2kWUIvvfECI/tn2rZ+9KYW4NQVaRkyWkYqXZVR0rtohotejy4e5I/fckmvjXPNNTWPZMgJRKJ+n+SlufUF6Dih0yUfbwwYvd4hUIlwA0jfvT0IZ4eqU9APqEnjSlgtOhTV7AR6rfykhdw0prcqtpSrzl6aHsaa9OmTXMfTAh27NjR8rG2bNnCq1/9avbs2cNdd93Fhg0bePe7380f/uEfArBjxw42b97Mgw8+yLnnnlt93hve8Aa6u7v5yle+wp133skrXvEKxsbG6OnpqT7mec97Hm984xv567/+61mv+5GPfKTp1/U0lkajqSURMFOVgCCM8EM1USUBxxS8/QUbufycQSIp+avvPMmO0RJrcg4TZZ9DxbkTj3uzNh0pq62ppkhK7nhshJsf2IsfRmRsoyoM1FZxQX9+9pTXh19zKpvXZJt6btqZ7mqHpJrz5IFpHts/xdY9U4yVfcpehNuwmdw2BS86sYffPqmXsh/ytfv3UPEjcikLxzKIIsm0GyzpfDSatis7O3fuXLYX37FjB1/4whd43/vex//4H/+De++9l2uuuYZUKsU73vGO6kqKdevW1T1v3bp1PPvsswAMDw/jOE6d0EkeU7vSopYPfehDvO9976v+fWpqiqGhoWV7XxqN5ugnmX6aqgSx90a1iYQQRFGEF0puuncPJ/Vlq6sTOtM2CNVeMmIR0vjbpCFUxaM3a9MXT1Hd8tA+Mo5JoRI0NQA/uGeSm361m/1TLn4o8aOIkh8SSrCEIGWJWfk9tQnHjdNQte9vsbuv5qLih/xixxjfefQAz4yXKPtz/z6dsQ0c02Drnil+vb/A+rzDxSf38cTwNMMFl4qvhFFvzuG1W/o5e4P+ZVSzOBY9r+d5Hjt37mTz5s1Y1uIOE0URF1xwAddffz0A5557Lo899hhf+MIXeMc73lF9XOPkgZRy9jRCA/M9JpVKkUqlFnXOGo3m+CCZfgrCCCnBqvGJGIaBJSR+pATP7z1/Q3XMW61+UO0iIVR7KfGq2IYAAV6oWltp28Q2DR7dX+B/3fEUAjErJPBbW/fx1Xv34IUSgRoVt0yBIQykjMinLPpysye05ko4TjJvnhgusGO0RD5lLcsC0ijeUP7Arkm+dM8upsoBc0XQGnE7zwsiutIWtmUQhJI9ExXGyj7XXHwS+yYqfO+JEQ4VPUanPW55cB937xg7bOnXmmOLtl1epVKJq6++mmw2yxlnnMGuXbsA5dX527/927aOtX79erZs2VL3tec+97nVYw4MDADMqtCMjIxUqz0DAwN4nsf4+Picj9FoNJp2mSz78VSVbJrIK+L/9k+5TFXCqnk4jFSrKxEQtTpCogSLBEIpKXkhYyUvnrIy6M3ZVYPxZ3+6k//30F5uioWOaYBpKgHlh5IwjBBAwa2ftoKZ0fGh7nSdx2Xrnkn+6jtPct33nuam+/YwWQk4VPQoebOHOWxTEEStLSAt+yEHCi7TbsC3tu5jYj6hA1gNmzMMBGnbZG2Hg+tH3PDLXfzrw/s4VPToTNv0dTh112Xrnsl5z6dVQ7nm+KFtsfOhD32Ihx9+mJ/85Cek0+nq11/5yldyyy23tHWsF7/4xTz11FN1X3v66aerqyk2bdrEwMAAP/jBD6rf9zyPu+66i4suugiA888/H9u26x6zf/9+Hn300epjNBqNpl26Mna1FdWsSixRPpkIyKfM6pi3IYh9NJJIyrrpqSBSFRekxBAiNhir9ljaMjCEIGUZ9OUcSm7A1x/Yhx9JzLgS4oeqShRJCJJAQAkj0/XTVo2j4zDjP9oxWiJjm3RlLAyUt2ek4M4SPK0sIA0jyWjRY7ToEUaSZ8fK7JmozHtdI8APldiJpPq7ZQosQ2AYBh1pi2fGyxRc1V5LNVyXshfyzYf2zTsRlwi6T9y5g+u+9zR/9Z0nFxRImmObtsXOv/3bv/G5z32O3/qt36r7B2DLli1s3769rWP9+Z//Offccw/XX389v/nNb7j55pv54he/yHve8x5A/QNz7bXXcv3113Pbbbfx6KOP8q53vYtsNstVV10FQFdXF1dffTXvf//7+dGPfsRDDz3E2972Ns4666zqdJZGozl+Wexv+ZvXZFnfmUIyeyeglLI6BZUylV/minMHyTgm026IZSix4DfuPECJJJWzE6pgP6HMzqmaVQdCCNK2RdmPIBY2kZypJiX/8gaR2u69Lp+i7IeMlXzKfjgrv6fRn5OyjOoaCWRiKPaqFaK5KkO1JNWcsq9Ekh9G/MevD8xa89AMiRI5EpiKK2gJkVTVsYxtLthea6RR0DVWyrTgOX5p22xz8OBB+vv7Z329WCwu6KNp5PnPfz633XYbH/rQh7juuuvYtGkTn/70p/m93/u96mM++MEPUi6Xefe73834+DgXXngh3//+98nn89XHfOpTn8KyLK644grK5TKveMUruPHGG/UWdo3mOKfVpZm11O5xesVpa9lxqIgfgSVmWlBRpCoztgEn9GSqguBNZw/w778+gBtEaoQbqj6bxp1Uk5WAKDY992SdJjf2enNz47+u1XZYJPnTl5yIaRhzJhw3S18WqNcdmXYJQ4kbSCpBhCFE0wWkCWGkvDmJyAF4emSam+7by/CUSzsIwAskI9NudV+YF0RIqBN/tdQar2upFXR9ORsvlJT9CNMQ9OZsxor+ogzXmmODtkfPL774Yi6//HLe+973ks/neeSRR9i0aRN/+qd/ym9+8xu+973vrdS5rhh6EahGszI0WwDZ7o1mscdYzFh1M3HkmIIDBZdQJpvBBaahhE5nxuZPf/tE9k253Lp1f9PN4gYg4n5Y7XckKim4N2s3bRUVKgHDhXrxUPuuk2NZBnziTWdwWn/HnNfi/l0TfOLOHfTmZqcOl7yQsaKLG6qk54xtzikIS57KzUmqY8qjs5+f76j3TAKYBhDBfNGulgGmYRCEESnLYH1XipGCRyWIGMinmm42rx2przVOJ4tPRXxeXph4p1TlrCNlIWHW8zTHB21Xdj72sY/xmte8hscff5wgCPjMZz7DY489xi9/+UvuuuuulThHjUZzFLKYqspyHWMxY9WzxFF6Rhx1pW2yjslURRlvU6bghJ4M5w11ccM9u9k+Wqqr3BgNlZzutEXWMXFMgRf7bgpuQH+Hw3jJnzU9KqWk4gdkbEO1spKvN7xPgaqAFCoB89FsT1ZC1jExjBTTlZC3nj/IloH8LEHZWM2RUnLPMxPc8tA+pt0ZOSOAjpRJwQ2JotiIHLfhanHi1Q8ybqEZIvEOeeTTFgO22hSfsoxZ1yXZ2dXYXpuMz68uJsAQyNjH5IUeGdtsyXCtOfZo27Nz0UUX8Ytf/IJSqcTmzZv5/ve/z7p16/jlL3/J+eefvxLnqNFojjKWwzuxlGPMtzSzme+jmael1hQbScmaDofrXncaf/GKzfyv157G5ecOcvtjB9g5NiN0kleqFToRageUYyoDbjJunrFNLjljXdN1DqNFj2zK4tWnr53VvqqlK22Rdax5TcQwk77cuCcLlICYrgRs6svw+jPXzdp9VfLqvTkHCi6f/PFOvnTP7jqhM9Sd5n/8zsn80UXPoTtjYQgII+o8PAawtsPhhJ4MA51pUpYRCx51nfrzKa55ySauftEJc16Xudpr+bSlHhupmICZaTiBZRpEEVSCiHxab0g/HlnUT/2ss87iK1/5ynKfi0ajOQZot6rSrE0FLCnwrro0M91cKjT6PloRR3smKhhCcMEJ3dXE5IIbVjcrJM9KvDS1eKFk72SFvlyKjG3MbBTf0s/GrnS1etW4ziECbn9sBL/R8AOYAoIo4qTu2VWORgwhuOLcQT77052MFj3yTdp6jQKitpoTScnO0RI/2TbKvbsmCWvOxzEFbzx7gFecuqY6ov/7Fw7xb78e5sCUS4Rq17lhRE9mpmWnWmZp3CCiEqjFqddcvKnajrvmJZvmvC7zVgbF7Jw1KeVs05PmuGJRYicMQ2677TaeeOIJhBA897nP5Q1veMOiwwU1Gs2xQztVlaIbVG9ofjyZtCbncN7GrpaP0cx/MV/bBmaPVS9WHGVss2lGTTO8QHKg4JK2BJ0ZuyouztnYxdkbOpsKvr/6zpOkbAPphUQo0ZKMtYeRElGXn7O+JQ/TORu7uOYlm7jloX08M1rGjyJsw+DEvixXxgIiiCLu+s0YeybK5ByL55/QxdMjRb61Vf2MGjXX2YN5fu+CDfTlnOrXnh6Z5kdPH6LghnH4Igx0pgijiNFifctOxNWzaTfgpL5s3c9yrusy13stVAJSpkFFRoSRxDCYZShvpeWnOTZpW508+uijvOENb2B4eJjTTjsNUNk4a9eu5T/+4z8466yzlv0kNRrN0UOrwuHB3RP855MH48WZBm4Y4QWSyXKJHYdKCKHaGs2mcuaayEloXJq5kO8jn7aQSKYqQfx6sjoplbKMOcVRLmXOKhjMNfGRTE4JYfCnv31iXXWi2TqHbQeL7J6o0Jt1CNNqNNwLZTyCLkhZkLJN8un5W1izT2Rm6WckI0puwNMj09zzzDg/fOogRU9NQwngq/eqNlTQkBAogHza5JWnrqkKHYHgmbESX71vD2U/ojNt05m28EPJSMHFMASGIVquLM11XeaiK2OTcUyyjlk1KEfM+JoSg/JCLT/NsUnbYucP/uAPOOOMM7j//vur+6jGx8d517vexR/90R/xy1/+ctlPUqPRHD20UlUxBfxy5zglLyRrmxyc9pRR1RCYqOdGEg5OuxhC1O18So4xX+BdO22brXsmueWhfRS9kCBUv/VLlL/EiKeuTNPg1LW5OnEEUPEDLNMgjMel58IylFcliv0prQiUWtGYsgwyjmr5hHG+j20KxktBy4bbRgO2H0aMlXyePlTiqYMzmTUGqkUWSnCbFK3yKRVIOFUO+N4TI5w+0EEm/hne/MBept2Q/ryDIZRIrW09rsk5dKRM9ky67bWmWqBW4K7vTOGFklBKTKEm6sZKzY3NmuODtsXOww8/XCd0AHp6evibv/kbnv/85y/ryWk0mqOPVqoq6/IpRks++ZTFaFEJnWTJJoBlSPxIVRTGii4ZJ4OIayjzTeTUkrRt5vN91AqAnGMyUZ5pcUQAkaQcgRmFnDfUNSOOHtzLtBcQxPuqFkJtJTfIOgZjJb8lgZIIqqmKTzoOAExbM6LPDaIFE46r76XBR1X2Iw4lApP68fCI5gtMbVPQl3WqlbZcymK44PHArknu2zXBjtESk5UAA9g/6dYtJk1ajxOVgD+9eBOGEEuKI2hGrcAdK/nk0zaZuCo3Vpq7eqQ5Pmhb7Jx22mkcOHCAM844o+7rIyMjnHzyyct2YhqN5uiklarKRZt6uO2RA0hL+U4MQyChOikkDIER/7kSSAqVgI6UtWDbo5H5fB+1AiBrm7MybYDqficZwR2PjZAyDW59ZD9lX5ltx0oqc0Y0EQcJlqHEw3jJoy/ntCRQGgWVIXxSllEVEK0KvoRaHxWoc0lGvsMmS6yavZd8ypxpKQqqXpv/t3U/kVS7vQyYGSOvCQqEmdZjoRJwwQndC57zYmhF4GqOT9oWO9dffz3XXHMNH/nIR3jhC18IwD333MN1113H3/3d3zE1NVV9rA7o02iOTxa66eRSFt9+bKQ6Viyj2WnBhoCerM1EOaDiR3ihv6gb11y+j0QAOKbByLQ3y3xbSwTsm3L5wi+exRDQ35Eil7KwTYPxkhqPblyTYBmJoVgJKy9U002n1LTDmlFbbaoVVBU/4kBBeXj8MGpJ8CWTbvfvmqDiR+TTJm4QqTUVqMpZq6myiSgyDIEpwA3VFJUEBvIp3CBSlTkBliEIwojxkkfGSSPi1mSrlail0K6xWXN80LbYufTSSwG44oorqiXn5Lex17/+9dW/CyEIw9amFDQazbHHQlWVoe40TxyYnpVRAzP7owwB3RmL//rCE+hKW8t640o8MRU/aHlfVqR2eHJw2kPEXqKMnWai4jM67SOA3pytVkEky6wA4ukp2zTmFSiRlNzy4F6mKgH5lIVlCPo7HCbKvvKgRJLxss+Z6/PVCaq5qA1krPgRRS/AGw/IOpZ6Hwu81zgAuYptKp+QECqob6KkWnE9Gbs6VeWYQokeQ5m7vVDl46RMo61K1FJpx9isOT5oW+z8+Mc/Xonz0Gg0xyBz3XQMIbj83EE+cvuT1a8lE0DJ/wUYK/mcNdjJy07pa6mC0c5v8kmFwQtlVYC1gmnMLM7M2GmEEGQsE9NQosmxDPo7UtXpKRkbYCxTcNX5GzhnY9ec53vH4yM8OjxNFEHZ86qrDrozNqYhqnk077pwaN71EI1m5HzKxJ0IcUOJXw5aquYYBoiadQ9p20ACXhBRqPg4pgoEdOLWlhDxrq2CG49+i7giFTJdCbRnRnNEaVvsXHzxxStxHhqN5jgjn7LIOBbSC6uheYnQUYJC/ffik3rnvUEudqXE5jVZenM2E2Ufy5BNwwDnwqipWiTmYdMQhIHywWRsszo9FYQR027I5jU5TunPccuDe/nlznFGS37d+Z431MWtDw9Xv5acjxtEHJz26M+n6ExbjJX8ebNiGs3I6muqAjNa9GatbpjzOBHV0e3BzhRuICl6M63Ei07q5ZYH99VN3WUdk/58Km7tqRcKQpbNM7Mcu9Y0xycti52xsTFKpRIbN26sfu2xxx7j7//+7ykWi7zxjW/kqquuWpGT1Gg0xx6TZR9DCIZ60hQqAZOVoCaZV5Cy1MLNgXxqzmPMtc8qWSnRbNlngiEEr93Szz/+7BnCSLXMGn03tZhGLAAisEwlBMKaapAdz2xPuyGGMFTLB0HFj3Asg6Ib8OHbn6LgBkipRrJ7sg6WKdh2sMiv9xUwRLwlHVUpEYAwVD5PqwbnWjNyku2jXs8gZZsETUIQmwm9CMjYBq8+fS1/cNEJ7Bwtzwo9vHvH2Kypu6xjkrZSjEx7rMuneO/Fm2atoFgMy7FrTXP80vJurPe85z188pOfrP59ZGSE3/7t3+a+++7DdV3e9a538dWvfnVFTlKj0Rx7JHk8QQTdWbUvabArzbrOFOs7U6zJOWRsc84b+0L7rMpeyDcf2jdve+qSLf1s7ssqkTHPzdiM1YBjGhgGBKFqTRlCVHc2dWZs3v6CjZzUl6Xsh4wWPaYqPhnbJAglBwoVKkGEQJmX/VAyMu0xUvAouqq65YZqM3pQo7qEENVK0kTZZ6g7PafvJZKSJ4YLlLwALwzxQ2UAL1R89k5VKDYIHUG8lV2o9+iYkDaV8MvaJinT4Bc7x/nw7U9RdNUUVSJckqm7Zjus1Oi3xR+86ARO6+9YFqGz1F1rmuOblsXOPffcw2WXXVb9+0033URvby9bt27l3//937n++uv5/Oc/vyInqdFojj0al1MKIUjbJjnHqo41z3djb3fZZzMMIbj6RSewtsMhYxt0pS3MWY+ZeeyaDof+jhSGoTwt025A2Q/Z1Jflmpds4vJzBvnopadz5XmD9OUcBIKRaY8pN8ANwQ+jOElYCbMwkvEUU/1rRoAfRDNLO6UyJ89ncN66Z5K/+s6T/Mv9eyh6ESNTHvvGK+werzBWDmaNmKdMwYYuh/68w5qcw0A+RW/GxourXH05m74OZ15RkUzdbYoF3ljJr7sey1FxWQ5Rq9G03MYaHh5m06ZN1b/feeedvOlNb6ruw7rsssv42Mc+tvxnqNFojigr6ZO4aFMvz4yVOVBw6c7YOHEIXCtZOu3us5qLczZ28WcXn1RtkaRsEy9UQiMu4GCbBr1ZZRIuVAL68yne/Lz1DORTs67JI3unuPXh/ZS8UO21qqjEaFVlQeUHCVHXAqttn1UN2kK1oJIeU63BuZGteyb5zF07KMaZQWU/xAvrp6lqMeL3NFbyyTk2HSmDQMKBaR8poTtrE0qJF0RVUTHX8tWVHvVuR9TqCSzNXLQsdjo7O5mYmOA5z3kOAPfeey9XX3119ftCCFx3diiXRqM5elkpn0Ttcb1Q5b4MF1y1FsE2WzK0trvscz7O3tDJ7vEyI48eoOQFpC0Dy1Cj5aYhKPshlSAiiOS859ZYhSj5IaC8R0RK7KgKSzRvrk+yrmJNh4MhYNoNOXltjkvO6G/6mt+I1zT0ZG2CUBLJ+e3WEVQXmFYCj/GyIG2paSvLFEyUla8omQbryTrzioqVHPVuSdRWVPtOG5c1c9Gy2HnBC17AZz/7Wf7pn/6JW2+9lUKhwMtf/vLq959++mmGhoZW5CQ1Gs3hZynm33aO25m28MKIiZKPbRpced4gl2zpX/Bm1e6yz/nO50u/3MWO0VKc7SNwLMhaqkKScUzeev6GplWcWiIp+fG2UbYfKpF21MpttQIjXgAal2gkKpF5IUKpnudFknza4somVa4wkmzdO8mzExVyjslUJWCyxdHyCNXKyqZM/FCZmKMIEGpsPBFLlUAt8lzT4RBEC1fKlpuFRG2hEjDtBdz8wF4EQhuXNU1p2bPz//1//x///u//TiaT4corr+SDH/xg3X6sb3zjG3osXaM5Rlgpn8Rcx01bJuvyKaSU3L1jrKVjzWeQHS16C7bBIin5zqMH+PiPtleFjm0KDEONe4+WPExDUPJC7t4xxnlDXdXqxbaDRe7fNcG2g0UiKdm6Z5K//M6TfOFnzzBVCTg45bF3okLZC4mkJIhkdbwe6ndR1WIaMx4hgEoQzel/KfshI9MuBwserh8xWvRVRaalq6fwI8l0JSSfMqn4YbyyQ4moIN5NFkn1uENFD1Mc/q3hjd6uWopuwKGih5SSfMrSxmXNnLRc2TnnnHN44oknuPvuuxkYGODCCy+s+/5b3/pWtmzZsuwnqNFoDj8r5ZNY7uMudhdSsun80f0FgngCSqBGyWWc74OEQ0WflAnbR0tsP1Si6Aaz2nrdaYsD0x4lLyCK1y9IoOxHlP3Z5uNmqAktNXUlY3EkgLdfsIHXnzVQJ9jCSE1llf2Qohfw0+2jcbusfQyhRN9YSbWtIPb51IQ/x3/FDyUZ25y3UrYS/q65dq15odq/BWp9R9pW1vLaLevNPEaa45O2QgXXrl3LG97whqbfe93rXrcsJ6TRaI48izH/tnKjWy5TcS3tGGQjKbnj8RFuvn8vlSAiimQ1X0dl0qjH1TpevBD8SsDtjw3zyL5CXVvPCyJ2jJYIJdWR8sY9X0iwDUEQyVlVl+QMhVANriQTxxCCnGOyZX39jbroqTZVGEXct2uSbzy4j6mGgMGMbeD60Zzm5NrXNg1DVZ7CqKWKUDiP0Wglc3CaiVqkEshrsja5VP2tTBuXNY20naCs0WiOfdo1/7Z6o5vvuBLJtKt2Sj01otpDPVmnpepAKwbZZJP4o8PTBKGqnESoigoN7ZHavxlxmvNPfzOGbQrWdqRm9gJCg9FYYBiybsxbxu8tyfLpyliYAkZLavIpqSQlx3FMgWMKNq+Z8RupUEGfShBycNrjX+7fy6P7C03fZxBGccVm3suh3jfK3xTVvGdTzH5fKuQQSn7YVDyslL+rlkZRu3eywtfv30s+3fw2thjhrDl20WJHo9HMoh3zbzs3urmOW/JCxooulUBVP752357q2oWBzhSveW4/l5zR3LTcSkUpOcepShAnIIvYkDvTMppLG8hI3TjLfkRnOlV3LSpBWH2ehDpfTv05Qtoy6Mk6ZB0zFnXqe8mGdxE/LogNyYnfaNoNmKoEeGHED548yLcfPYDXEPWctQ0ytsGUG+LPFwMdY8Yv6AXNKzq2aVT9WDJu7SU7sBrFQ6MPK7k+K9FOqhW1XQeL2HFUwVKn8TTHPlrsaDSaWczlk2jMwAHautE1O64fRhycdglqbv4ibi1Ne6qS8IWfP8N/PjHCf33hEPm0XRU2BTfgWwtUlGpvxvmUpRZsovZbJR6d+eSBISCXMpkoBbP8N+Umqxea0Zm2qtdHSslYvDG8L2dT8kK1MBQQSISA3ozNcwc6ODjt4gYR2w8VueneveydrMw6toCqObs3azFRDnADiW2AZTZvaYWRnNMkHUogijCFqBqWDSHIpywksw3KRyoHZ7mm8TTHB1rsaDSaprRi/t12sNj2ja7xuOMln1DOjIaahqirkCQ33O2jJT7y3afJOCYGMxu1bcugN+vMWVGq2xUlZeyPmTEFz1cJSZmCNR0pgkgZjWu7XUU3oOi1MEMOdKTM6vWpBBFeGJGyBN1Zm+6sjRtEhJFUFRdgrOxz/65J1nY4/OvD+/npb8bmFGSqPQZeIDkUhwKqVpTy/XhBo4lo7uMklz2MQApZncDrztjVZORG8bASPqxWaFWQa3OyBhYhdkzTZP/+/fT314dbjY6O0t/fTxgubipAo9GsPhYy/y50o7MMdXO/f9cEQPW552zs4szBPLc8uJ9/3boPyzSYroSYhmrjJFTbS/GN2Aslhh+yvivFvkkPL5SEMiSMpFp02aSiVHuOAuWHcYMIYagbpm3Mbj/ZBnRn7GoV41AxIOeYTLs+Qkgsw2C05LV0DdXuKSXOvFCNxSOhIzbVCtToPagqlB9GeEHEA7sm+MXOcSYbDMiNfpxQgiUEEjnz9VghJkJyPkwDLENJzSTlWaCqUR0pC4FaizGXeFjOcMd2Wew0nub4o22x05hzkOC6Lo7jLPmENBrN6mI+8+98N7qSF3Ko6OGHEbc+PMwdj49UW0yg2l/bD5XUeHYQjzzXFCHqRp/jL5pCZb+UPFUJsUxBFG8EzzhpBAIhBB1pi52jZb796AE6UhZmvHgzFftmRgouYSRR93i1zsEyDfxQrUdYk3NwLAMvrhKYhiBnm+wvuBTjNlhrNR3ozdmUvZCJwKdSs+9qvORT8kJ6smovVxTn2yQj63c8cbDh5wBdaYupSoAZt/kSMRjM4RVqwb5TJ14sQyjztqE8TUUvXFA8HOl20kqvq9AcG7Qsdj772c8C6jeUf/7nf6ajo6P6vTAM+elPf8rpp5++/Geo0WhWLfMZjkcKLkGkRNDavE0Qws7REv/7zu2AurGnHYNCZaZSMZeASO7ZhiFUyF0oq6JBCIEbSFw/Im2bVbOzG0q+eu8eMo6JG0RUfJeBzjRZx6Q/n2K8FFeGYsPyloEOzh/q4sHdk+yeqDAd3+jX5BzGyj5FX/mSCm6A29Aasgy11LPZaHkYqTaWG++Z6k5bjJb8+JwiDhQq9OUcUqbBlBswUa6v5FiGqOb5RLHHyDSaTYItHSEECEmHY/JHL34OXWlrQfGwGtpJK7muQnNsIORcpZoGkiWgzz77LBs3bsQ0Z3YDO47DiSeeyHXXXTcrbPBoYGpqiq6uLiYnJ+ns7DzSp6PRHFUkk05lLySftrEM2Dvp4gURpgHr8kpgAEQy4tmxMgDP6clQCST7JistZbwIZqaoOlLmrLUIKcsgnzKZrASEodqivr4rhSEEYyVPrX6wDHpzKRVKF0RMlNWKiqvO31Cd9qqd7sqnLW68Zxc7x8p1BuOCGzBS8Kqv75iqohREUd3YecoU9OdT7JusEEllSE5bBuVArcdIzNFGk3FvgC0DHbzghG5ufXiY7qxFFEmGC17VKF3rN5p/G9bc2KaoCpEoiggiOK0/xyfffEZbAqUufiBS7aSh7jSXnztIPmXpqovmiNJyZWfnzp0AvOxlL+PWW2+tWxWh0WiOXxp9E5UgittBgr5cqip0QHluZGzCcUPVfmo0/s6FKdSouPL3zF6L4IcRo0WlNAyhJsJSlsALJfmUSRQpAVTyAuVzMVQ1oHFyq7YdEknJ7okKacuk5IeYsWE3n7YoVALKflRtIxlCVsfJ1TuEfNri4LRXbScdKvrV78GMOGlsNxkCXvPcft509jp2T1SwLQEI0rZR9RyZhlowmgT9LaXII6WM34cSbu+4cKhtQdKsnVSo+HNOy+nWk+Zw0nJl51hGV3Y0mqWTCIX7d01w68PDrM3bmKJ+/V7RCxiedBECenI2E6WgWtVI1jbMh2Wo1N8gjBBAUPOExMcCKrG4K2PNjHVLALXg8k1nD3D2YOesG2yzYERTwEhBGZGTCa6Uraa/AA4UKgRxDk8UyerrJ0Kn7Cvz9GLaTd0Ziz/5refQn0/x+Z8+w4GCS3+HU13MGcWTZcnIvjJCz1SKgoaeYLPKj4rOUdUsGV+3d7xgI5efM9j+CTcwK3+pprVlGILejM1EJVj2tGWNphlti50wDLnxxhv50Y9+xMjICFFU/7+oO++8c1lP8HCgxY5Gs3xsO1jkuu89TcY2SVn1YqcShOybqACCnpzFeDGIW1NS+XDix9VOHCV/FkDaNtQoNeprc/3j1ZW2KPkhUTzOLYSotmh6sjYfePlJ9Xk9FZ/P/eyZuhvz6LTHRMMkVIJpCAbyKfwwYrzsk7WVmbniRzimoK/DYSL25RgLjLfXH1eJljC2BHWkTNK22r5e9kKVwZN1MA0YLfrVa5Zcm6xjxgJSLfKsmr3nqJ6ZQrX/bNNgfWeKd7xgI+cNdc96XLs7ryIp+avvPMmO0VJd/hKokf3hgoshYH1nGicOBkz8PcuRtqzRNNL2NNaf/dmfceONN/K6172OM888c1a2hkajOb6ZbzpHeVsAJKn4z0kLpVbo2KZBFKkx6J6cjSUMSn5AZ9pmz8RMsJ5A3bARMwIBqO69sswasSUEhpBMV3w++p/byKWsalWh4qvt5Os70wghKLrBnEIHlLn64LRL1jY4c32ed104xJMHpvnGA/voSKu2nRf7hqIWyzqmADO+VsJQLbFpNySbMunPO4wXfbVRfdqrVmkMoXxMYSQxkNiGUZcjlDzGEA1VMEMFF1aCCNsUvPLUtZw5mCefVq27qocn3iX23cdHGItbcK1UYRqDBmW8jT6QqnUppfp5qJ+30Ms7NStO22LnG9/4Bt/85je55JJLVuJ8NBrNKmGxG6wXms5J8laKXoRlqDC82m5XEqwXSaqBdlKCG0ZcumUt/3zPbsJI3bBNw6h5XVldo+DFN/GEMK7qgGp1eVFEEPn05RwiJNNuiGmolRAZ22C0tHAAnhdKOjMGV547yGn9HZyyNsevnhlnx2ipuoaiHWovbW3BPAglw5MuXiir1SwJdKctenM2QQRjJQ8/iCh5Qfx+IW0JcimLohdS8WcOaAhY15FS33MDRqZdbvv1MD946lCdkAH40i93sX20FKcoK7GaN+0Fd17VZhuVvLA6+RZJWa3SRVIS1pSb9PJOzUrStthxHIeTTz55Jc5Fo9GsEO0Kl2b+lY1dKV58Uh8DnakFj7FQ2BvEOTujJbwwqE4wWfGOqCBU7Z+erINA4IURliHoiCsFAlkndIDq1xMxEMVbNmuXbNYSRJJDRY/OtArOk3HVQeQc/LC1FJ11HSl2jZfJOCanrM1x3lAXv95XmHNH1nwIIarhg7Xtp8lygJTKb1TLtBuQS1lkHZOBfIpDRY+BfIoXntjD7Y+N4EcRWcfCsQTDk8p3ZArozyuhU/LUUtFIgpCSbMrAFEY1HkBKWd2onghHL1RBhV0Zlfdz46928/eD+WooYUKSv1SoBIyXfFUtMgQGM+1HKcEPIqiJZ9PLOzUrRdti5/3vfz+f+cxn+NznPqdbWBrNUUCrG8lrH9+42LNQCfj1/gKP7CuQcUwytrlgKyOZztl2sMhTB6aRwOnrVAXEEIIzB/Pc9ZsxHt4zyVMHptk7WSGUIKOZ8L+sY9YF03VlLFKWQUWGBGFU9eNIKeN1C6ra44fRLINuI4ZQ7Z9CJUAYSmQp303Y0nQYwGPD0zw+PI1lCvo7HMp+2HZFB5SoSYRjo41SStWOqxVBoETDeMkjY6vWW2faZrTkc/4J3Zy+rqP6My/7IVKoRaS9Ndd0vOQRSSVCQ6ULSdkGdtbm2fEyUioBZhpU/603hEqbHi36CODpg0U+cNvjvOvCobrPweY1WTZ2pfj1/kKcCxQLOfWOqo+b9kK6MrJ6fL28U7NStC12fv7zn/PjH/+Y7373u5xxxhnYdv2H8tZbb122k9NoNEujnY3k0HyDtWpDxJkwEsIwIp1duJUB8MjeqaZC67ya8L7k6+u70kzEv9F3Z20c08ANorpgulzKImObZG21OdyLwwUFquXVkbLUUsxItUxqJ7QaSUSJF8oZE7RQVYV25EoySbZ30q1+baHMG0NA3jGZcuOt6VJl3CBEtcoVW5Gqbb1ZxzDUubuBClOsrYpccEJ3dbT7ieECNz+wl3zKIm0rP5EbROp9x8eufR11TUXspZJYNf6d5JpJVBsxkrBnojzrc2AIwYtP6uORfYU5haMllLhJzl8v79SsJG2Lne7ubt70pjetxLloNJplpJlwgbk3kkNzY+lYySOUMl44KUjsH30LGErnElpPj0zz8L4pMrZZt8CzUPFxLKM6kjztzl5VEElZNT+v70rFCchq4sqJJ6gSr48Mwmr7qpn4qM26ScL95Bwtr7lIjtv4lIUO4VgGjm1ycj5FyQ8ZmfZUArNU1SnHVOsjvCBqWkFPhFAEVd9LY1UkSRXevCbLPc+Ms3O0RMoyEGJm27shqNkrplpR6niqimRUr4+sRgPUXktDCLqzDkU3mPU5GOhMkXFMwjDCj6gTpUEkY+O2ElCNolabkzXLTdti54YbbliJ89BoNMtMo3CpZS4zaK2xVKI8LWV/ZtQ7uc2VvJB01pzTUDqX0HJMVWmJIlUhciy1nLNWgHWkLf704k0UKsEsb1Ct+Xms6JNP22RsNbo8VvSxLAMZSrrSNmEkGS16ah/VAtfKqKkAxdEzC4qeVhKLVcVkRkR1ZSyQ8F8u2MCWgXy1gtHY6it6IZ+6cweHAo8wimbd/C1DmZuEVBNc81VFmhnGk+MFocQ0Z7xRkEyEKf9Ts7H55G+RVCbotGVgiNmfg66MTcY2SWeV+EpEacoyKHsRo0Vlup72QtKW1Ms7NStK22JHo9EcHSy0kbyZGbTWWDpZiXdANT12oDZ1C0nZD3liuFAnSuYSWm4Q4YeqeuFH6u/Jxu9EgO2ZqGAIwQUndDd97fnMz+ds6OS2Rw5gm+qmmrHT7Jmo4IVKMNT6aWpv4bX3886MMv36QcRkJahOeDXSitCJNQnJpLUXRJy2roPXn7muTsCc1t/Baf0ddc//85efxMe+v41pL1RVESFImQaBVEtQiTNyAEaL3rxVkcZr5ocRRizC1uYcMo5BJVABiAKJELLanpvz/YlYJAmBbTLrs1QbQdCXcxA1i2IztkHaNjmxN8VVF2ygJ+voBGXNitK22Nm0adO8xuQdO3Ys6YQ0Gs3yMN9GcmhuBt28Jkt32mL7odKcSzmTseH9U5VqK+XmB/ZyzzPj1d/M5xJaSfvEjE2xYUP5pNVpnLk2XW8/VOLbj41U37MQgr6cw3C8lHQuaqs0BTcg51h0Z504cDBgZNpbUNw0IlEiqlYvlP2I6UrAI3unFqxgnLexiw+96mQ++ZMdVLyQjpRN1jGYdkPGSqpdZxqCShC1VBVpvGbDBZdbH97PVCVQo+tx0rQkzi5ifkFnCcg4Smw1+ywtFEGQdcxZxmaNZqVoW+xce+21dX/3fZ+HHnqI733ve/z3//7fl+u8NBrNEpkv3G8hM+hCN/ZqujEquTefsuoMy3MJLfWbu4xNuKIaopfQzjROs03X873n+Y81I0pkFE85OWrKKZ+xmKz4VAKJLcBvf9gKUKsZerMOh4regsbuhPOGuvnAyzZXKzLj5QDLEJw12MmLT+plIL9wDED9+6y/ZhU/5KZ79+BHyk9jxPu2ZDT/NFti/HaDiJRpzPlZWiiCQAsdzeFiUQnKzfj85z/P/fffv+QT0mg0y8NCv1k3a3tsP1RiohLQmbaYnCNBuPZeL+IbeDpeDZEYlq973WmzREfJCxkrujWVDuUJ6m0yYr7YaZzG99yRthgrugumGNdWXwxRM+VkmRBXUCwh56x2LYRKelZj3I5lMV3xW04KnquKtdSWTyQlD+6eJGMb9CfJyaif74GCR/KTTjJ2pJyZYItiN3fFD5muBAu20PTST82RZtkWge7YsYNzzjmHqamp5TjcYUXvxtIcy9Tl7ETqN+u5MnLu3zXBJ+7cQS5lsn+yghDKqhqh1hc0/mOxNmfTnZ1JhXODiLIf8uHXnErRDfjsT3dS9kJs01Ctl2hmeimZKDJiweSHUcu7kRYKSUze887RMhNtjJLXLtPszzvYhsFU2Vf+FgQT5blXSCTYhsqTSVp0ppgJ0jOYqZ6kLYOPXnr6EUsKbtxhliQdu0FUJ/6s+HwhHj+vmcrqzths6svoKo1m1bNsBuVvfetb9Pb2LtfhNBrNMtHOb9ZJ+ykZEVaLLMESBlKoMe9Qxosnrdntpsasl2tesolbHtrHo/sL8YoHNSKedczqRvIwkoyXfc5cn+fKFm6aW/dMcstD+3hmtIwfRdiGwYl9mbrnJu/5P349zBfv3gWyfl9UMwyhxumnKgF+GFF0Q0xDTXKNl8O6xwogZQoqoawbAwdmpSfXVY0MJaaCMKIQRjy4ewLgiFQ8Glc6JJvUGy9SEMlq6KEhBLYh8SM1Wv7/e9XJ1ZBIjWY107bYOffcc2f1/oeHhzl48CD/+I//uKwnp9Folodm/pZm1HpeujM2B+P8F8NIjMnqcaYh6M2lZnli/FAF+U1WAu7fNUFXxuYdL9jIX3/3aWzTIB3nuQgh6M6oVlEliPDDiHddODRrIikhqeQ8uHuCWx8epugF1ZBDIUJ+vc9n13iZ//7yzXXBdh0pq07kzCV0BGq6yDIEaRM2dKZZm09x/67JWaGEaUuwJpfCMgUHpiq48c6qVhCxYCDeSn7Lg/v49qMHCKP5F2xGUs6ZRL1YEmHrBVE1Tdk0hDJWN1ypIJTYFiAhiJQw/N3nrZ/z56XRrDbaFjtvfOMb6/5uGAZr167lpS99KaeffvpynZdGozkMNGsHJZ6XshfSk7UpuAFeoBKJhYCMZWAINT5ci5SSsaKLEIIbf7W7mozcmVbbxXuzJn4oKfkhplCj4WnbxLEMxko+hTk8QklLatd4mfGSXxUfpiC+OSvD83jJ50u/3MVnLj8TQwi27pnktkeGqxNG8yGBKFKeoZRlUAkkv3p2su4xScqyHy+0tE2TnqzD/im3+UEbEOoiEUpZNf+W/Ih8yqIrZ82ZbL11zyRf+uUunhkvVz0zliE4sSfD1S86YdHto0TYbjtYrKYpC7WGvq64k/w5CGW17bipN8slZ/Qv6nU1miPBsnl2jma0Z0dzPDLfziygLpMFYE3O4TXP7WewK8XnfvYMZS+sMz2PFV3KQTSTjBx/fbzkqTRkU9RUY9QG7Z6sE28bVz6fxupTbQpzyjTmHAFPbsi2Kfj7N26h7IV89qc7maoElLyw5cpLf4fNeCmY1YrqSlt0ZkwOTrlUQpVC3Zt1iCK5qLH0WiwD1uXTVZP2aNFjU1+Wj156Oo/sneJ/37md8ZIfG6WJV0qoV+zJ2nXVrHbZumeSj/9IHd8y1C+vSVpyhBJ4KmUZOtMWkZTk01ZLviqNZjWxKM9OGIb827/9G0888QRCCLZs2cJll12GaZrLfX4ajWYFaGVn1kcvPX1On0/jOLEZr5LI2GoDd+1qio6UScEN8UOJbSiDrkSZmUcKLilLcGp/x6wJrMYU5vmMxsnX/VDyw6cOsneiQskLWdehKi9lf+EUZQGMTNfn+6Qsg76sTcoyMOOt65WijxtIhqfcqpm59hi159MKQQTDUxUGOpXgSVKptx0scstD+1TmkATbmqmkCUMZoCfLPrc8uLelqa5mnLOxi6vO38D/vftZtU8sHkFP20bVV+UGKmTQEKJa+VuK0FnIXK7RrARti53f/OY3XHLJJezdu5fTTjsNKSVPP/00Q0ND3H777WzevHklzlOj0SwT7ezMaubziaQkl7J40/MGmKqE5ByD7YfK/Mevh0k7xswdH9XamiwH1cpLKFUY3YxvRSJCuPyc9bNueNsOFtk5WsY2BW4YIVuUEHc+dQjLNOjK2BiG2p7uFirVBZuNGChzcaNoyafN2F+k2mUlP2SsNCOG4unruudUx7Tj977Q5vWEUMJY0SVjZ6om7ycPTPPMqNo+bpn110YIgWGotRs7x8qz1nW0wyVn9POLnWP85mCRjpSJZca+KgRd6YiRaY91+RTvvXjTkn1C81UTdaVIs5K0LXauueYaNm/ezD333FOdvhodHeVtb3sb11xzDbfffvuyn6RGc7g5ln/7XMzOrITGm5UaSVf/lfyIaRcK5YCeODsn2a5tmar1YptGdeGl2okFKVtVMxpf559/uYuJio+QYBgBokWx40cRbijpy6ljZh2T3ozNwWJ91cYAZJMdWCf1ZXl2rMR0JWSaEMMQGKgpq8YzMGqeLyE2c6tyjxCtbM+awQsllSBS1zWSHJz28KMobvvN/uwlsiqIFk6cng9DCK6s8WnlTRMpwQvVcs582uIPXnTCks3IrVQTteDRrBRti5277rqrTugA9PX18bd/+7e8+MUvXtaT02iOBMf6b5+L2ZkFMzerQiUgbRuYhhI2YTydI+L/3CBiZNqlvyOFRK0gEKg2SH+HA2JmKaRtCsZLQd1rbd0zyWfu2sFEOUDE/h4pJUGLuiHjWPEKBJ98yiJlGfHaBx83niCXxKPiNcd0TMFlZw3ws+2j1a9ZpiCSEm+OCk2jUAolhPPsk5qPSMJIwcWPJKYQ/PCpg1TiJazJbqxa1KuIlhOn52Olk47bqSYeK79UaFYXbYudVCpFoVCY9fXp6Wkcx2nyDI3m6OF4+O1zMTuzIin50i93MVJwkZKq6Vei2lLJ7T2KR6jDSBmTe3MOIja4pm1Byjaq27VBCaPa10pe5+C0B4hZgqQVSq4aS58oB0y7IbahqjuWaVCZo5eVcwz+8KIT+PHTo7hBxLp8ioNFNXbfqrl5qUhUdccyYG2Hg2UIpt2ACPUzcWp+VlLG/hoBm3ozi0qcbqxenr2hkzMH89z1mzFGCi79+RQXn9yLZRgLH2wBllJN1GiWg7bFzqWXXsof/dEf8aUvfYkXvOAFAPzqV7/iv/23/8Zll1227Ceo0RwujpffPhezM+uOx0bYMVqKl3jW+1UCqSaKiKswYXwTdoMILwjjb6i03Vqh0+y17nh8hO2jJQAMsTiV4SeVJlQgXhBBOWg+1m4Zguf0pPm9CzaypsPhX6b20Zm2q1lAo0WPSqvGG+YPLWyFtAl9HcqoDNDfkWL/lIsE/CCaNY3VnbG58rwNbX8em1Uvu9PqdjBRCapf+9FTB5elsrPYaqJGs1y0Ldk/+9nPsnnzZl70oheRTqdJp9O8+MUv5uSTT+Yzn/nMSpyjRnNYaOe3z6OZZH9UxjEZLar1AJFUAX+jRW/WnqNISr73xAiRVBkrQcQs420QAUJVjVKWAQgiCW4g2dSbpSdrU/bD6mtVgpADBRdDCC46qbf6Ot99fEQJqrgatFgcU8zKAWr2mN+7YJBPvfkMLjqpl6n4Jp+YjLOOSW/WrgqnVpAooWUZ6gZum6Ll5+ZTJht7s1WhA5BLWaztcDDjKbZQKgFnGoLNfdlFjZ0n1csdoyUVE5CzEcD20RLbR0sIoDdnk7HNakVz657JhQ47L7XVxGa0swBWo1kMbVd2uru7+fd//3e2bdvGk08+iZSSLVu2cPLJJ7f94h/5yEf467/+67qvrVu3juHhYUD95vfXf/3XfPGLX2R8fJwLL7yQz3/+85xxxhnVx7uuywc+8AG+/vWvUy6XecUrXsE//uM/snHjxrbPR3N8czz99nn2hk7efPZ6vvfECIeKHgC2adR5NJI2xxPDBYYLblwpmfuYMoKMY5JxDKbdkCCU/OFFJ/DyU9fwyN6pmc3dpbBaLZFSpQjfvWOMizb1Mlb0q6bfpVRI3EBSmeMIyU83jCSP7J3iyvM2AM3be6apEo/DNuLIDAFmTevHMmavkGg8HyFgbd6hmTTKpy28MOKt5ykBupQE5WbVSykl0248MSdh2g3ozCivU2NFE1iUcX8x1USNZjlZ9G6sU045hVNOOWXJJ3DGGWfwwx/+sPr32qyej3/843zyk5/kxhtv5NRTT+WjH/0or3rVq3jqqafI5/MAXHvttXz729/mG9/4Bn19fbz//e/n0ksv5YEHHtC5P5q2WIyX5WiksYUhEPTmbF67pZ9LtvRX04eTx5T9kGk3XPC4ETAyVSGUSqwkbZA1Oae6q+qOx0a4+YG9SKAnY+NYRtUT9cyY2nXlmIJKq27kOZhz/xWqOpVol9qx7WY35CRfJ2jBuDNXC0uI+qmt6nnEFaBc2lLVshDMJv8i+6GaYjtjffMogHZoVr1MJuYMQ0mt2o3vtRXNOx4f4e4dY4sy7jduo68NoyxU/Hm3pms0y0HbYkdKybe+9S1+/OMfMzIyQhTV/6p36623tncClsXAwEDT1/n0pz/NX/7lX/LmN78ZgK985SusW7eOm2++mT/+4z9mcnKSL33pS3z1q1/lla98JQBf+9rXGBoa4oc//CGvfvWrm76m67q47kzE+9G4qV2z/BwPv33OZcAeK3rc+vB+NnalAeoeo37zX1jsANWpJVMoMfPMWLlq7D57Qyd37xwjknJW8KCTczhQcHGDiJ6MhVv0aaOY0jIRykSd4AZRtVJnCMHl5w7yqTt3MFxwyTmmquq02E9LdnA1tkDDSJK2DHIpk/FSQNoyEIYgZQpO6Mlw+Tnr+dbW/Yv63LUbkdCsehlKNTFnxMGQUsqqJwhURXOsFHLz/XuJpFy0cX+lJ740mvloW+z82Z/9GV/84hd52ctexrp165rmP7TDtm3bGBwcJJVKceGFF3L99ddz0kknsXPnToaHh/md3/md6mNTqRQXX3wxd999N3/8x3/MAw88gO/7dY8ZHBzkzDPP5O67755T7HzsYx+b1T7TaFbLb5/z3cDaubk1PnZTX2ZBA/YtD+0DKauPQcDB6daETi1SqrZYZ9qqtkEyjjmvJ6o7YzNcUGnHvVmLQ8XmpuKlUluBcf2IR/apX3aGp1x+sWMUL4yo+GrreSJg5sIy1NESPWQkBu24i5Xk7nRnlGfprME877pwiEIlqPv5GUK0/blbTERC01adEDNJ0PFeLNOomZjzQyp+SBhJ+nIOjiniqlf7xv2kwnesZlhpVi9ti52vfe1r3HrrrVxyySVLfvELL7yQm266iVNPPZUDBw7w0Y9+lIsuuojHHnus6ttZt25d3XPWrVvHs88+C8Dw8DCO49DT0zPrMcnzm/GhD32I973vfdW/T01NMTQ0tOT3ozn6OdK/fba6r2qhm1uz4/RlbfYXXLrmEBsdaYvfHCwhpSSXNiGeqEo2mbcTHxMBBwsVTujNVtsgTx2YntcT5cQb0W3TIAgjLGN+j9BiqX0bEXDrw/u5/bEDVPwIIaA369Cbtdgz6eLHyy9tQ/l2ElEQRvEW+DhosCNlcsW56/npb8bYPlrCDyWGUCbofFoJnYxjcuW5g03D+dr93C02ImGuVp1jCtxABRimbSM2mUPRDThQcOPWZMTwlFvdaZZ1zEWNjRtC6PFyzWGnbbHT1dXFSSedtCwv/trXvrb657POOosXvehFbN68ma985Su88IUvBGaXhJuFazWy0GNSqRSpVGoJZ645ljlSv33OdwP733duB1SlYKGb21zH2TNRpuRHZG2zejNLKHkhY0WXSqBu3mU/pFAOyDgmUSQx4tHydvAimIivX8FVx13IE5WxTa48b5C7d4zx5IFpgmhxaic5eiunHEXghxGRBCFhrOQTYcXVKVHNszFQAYOGIRCGJIogZRt0pCz+/GUncd7GLn73nEHueHyE7z4+wlic2CyhJbHc6uduKREJc1UvO1IWlcADAR0p9d6nKj6Hil4cCqmqWLU7zfrzKbKOeUwZ9zXHLm2LnWSC6stf/jKZTGZZTyaXy3HWWWexbds23vjGNwKqerN+/frqY0ZGRqrVnoGBATzPY3x8vK66MzIywkUXXbSs56Y5vjjcv33OdwOzczbPjpUBeE5PBiOe9Gl2cwPmPE531qE4WWG85JFLmdXJn5IXMjLtEobJTX0mCbkSRLN8Lu0wVvIJo3iflmOysSvFM2Pleb0pl8RG6R9vG+Uff/YMXhgRRbQ1EZWxBX4EQbjwRq0I8GqTlSPJ6LSPEGAJgRmPfPdkLYpuiBcqj4sUMNiV5g9fdEJVxBhCcOkZ67hkS39VtOTTltohOFLk2fHyvJNUrXzuGk3GEmUoTlKpO9LWvJWWuapIm/uUJ2iiEjBa9Ch6IYaA7qzNRDmonl+yhHS85JGx08eMcV9zbNO22HnLW97C17/+dfr7+znxxBOx7foP+IMPPrjok3FdlyeeeILf/u3fZtOmTQwMDPCDH/yAc889FwDP87jrrrv4u7/7OwDOP/98bNvmBz/4AVdccQUA+/fv59FHH+XjH//4os9DoznczJfxk9xcQeCFknRNUaZZ/k/jcWZuhhG2IdRYth+SsS0k6qaVCB3HUqNKXvz3pWTdgJpAGi/7mAK+cu8eutMWhiFa8qa87JQ+fvTUQXaMlsg5Bl4oGS36LSUal/y5H5Qs/mw2PZV8LQlNjKTENAykVDf03pxDxQ8J4v1e11y8qWlbKhEtW/dM8rm7dvLMeLk60WUZghN7MlxdI5KaX7vm/qxak3HJCxkvedXPiBBgG2CZxryVlrmqSKA+i48PF/jGA/voiJehqu3nEVbs1zGMmV1eRTc46o37mmOftsXOu971Lh544AHe9ra3Ldmg/IEPfIDXv/71nHDCCYyMjPDRj36Uqakp3vnOdyKE4Nprr+X666+vjrlff/31ZLNZrrrqKkC11K6++mre//7309fXR29vLx/4wAc466yzqtNZGs3RwHwZP2pxJgghm1Y3GtsItcdpvBlGUlU6RgoePVl1A3cDZUAxhKA3q1a+HJiqLKtfpierQuoOFT0MQ7Am5zBRCeb1phhCcPk56/nMXTuZKAVUwuVZ3dDO21LXQHlZxkpBdYlpBHQ4JkVvbvP21j2T/O87tzNe8iFJmY7Tj7fHrcm5QgHn824lJuNCJWC87BPFFR1hqEkqN5B4YcjwlDv7pGqYq4p0ytpc9bPkmGq9R0/WYWTaJQgj9VqoSttEyaMzY+uxcc2qp22xc/vtt/Of//mf/NZv/daSX3zPnj38l//yXzh06BBr167lhS98Iffccw/Pec5zAPjgBz9IuVzm3e9+dzVU8Pvf/341YwfgU5/6FJZlccUVV1RDBW+88UadsaM5qpgv48c01LQMCMwmN5TGNkJynDBSCzmTm6FkxmTshZKRaU9VOWJTam9sOgXoyTkcmvaqlQ+1jHNx780QM+bjpO3Wkbb404s3zZpKqqXkhfRkbTZ2Z3hg99ISfJux0NtJsnFiLUgQRtXrkKzM+NwcZuBISm55aJ8SDRLsGo9U0gaaLPvc8uDeWd6ahczHf/rbJ7KxO82v900RRfXHhpmFrL/YMcolZ/QvSoQ0fh6zjkl/R6oqnKP4w7CxO8O7LhzSY+OaVU/bYmdoaIjOzs5lefFvfOMb835fCMFHPvIRPvKRj8z5mHQ6zT/8wz/wD//wD8tyThrNkWC+jB816gsgcczZhv3GHJah7jQ7Rku4fkgUSSzTIIrkrBRfM0769YKIDsesW1Ngm4Ka6WPWdDhMVQIq8cROK5hCrThQ6x/UwZK2256JCqBuqpNln+2HSlXB44cRE2WfXz0zzlfv28tkZWVG0JtRFXfMiJ1as7NAkLZVpSNjG3OagbcfKvHMaBkZhyvWkrSBoqg+1BBaMx9/a+t+LtrUw8N7p0Co5yTttyhS2+V7sjZ7Jt1FL9Zs9nnMOiYZJ03FD5koB2zsSvP3b9qyLItCNZqVpm2x84lPfIIPfvCD/J//83848cQTV+CUNJrjj4UyfpKqzVjJX9DrcsW5g3zizh1MBgGmAVEU1bWkkhtjEKnvyfi4nWmran5W2StqEiltG+TTFpZhcKDgErSgdtTKBNWySVlG3fRXElL32bt2VvdRWaZgY1eKS88coCtt83/vfpZtB4vLdXnbRlVwBJYhSdsmuZSJGZuVU9bM5va5xq4nyz5+FMXtx9mVlcRNFUT1U0yt7me7UELWNgmlxA9l1YOUsgx6sg5p22Cs5C96Qmq+z2PRDelMW7zrwiEtdDRHDW2Lnbe97W2USiU2b95MNpudZVAeGxtbtpPTaI4nFspaAbjlwb3sHFNmV8sQbOrNcOV5G+raCOds7OLSM/v56n17gTght+Z1kqA8ibqpI1V7a+9khf58uroIM9lW3pW2cP0IiZqoqq20qJHkmfaYkZiak4WVQpBLmZT8sCoUpio+JS9k32SFzoxFT3z8p0ameeJH2/Gj+gTfw41tCPpyNkUvpL/DYawU0OFYTdtBc41dd2VsbMNAiLBpFIZ6d2LWFFOr+9kEag9ZOhaRoVTXOtnWXvHV6+6brLDtYHFR0QlHOnNKo1lO2hY7n/70p1fgNDQaDcyftbJ1zyQIEVcV1E4r5riBnTfUzbcfPYBlGHhxWyjRD7VTSLVBgV6gDKemacRCKsuBaZeDRQ8p1bOShxtAT86uZvaU/YjxkocbqLAaI147IJCMl4LqpJBA4sdVJtePOBR4jCfeGBXhu8xXdGGSdp0RK79IQtELyactXrtlHbc8tK/tfWmb12Q5sS/Dr/cp8VJrIUzCCIWATb2ZuimmVveznbauo9pm6mtoexbdgJFpFyEEX39g35zhk62kcevEY82xQtti553vfOec3zt48OCSTkaj0TSfkpllWo1viM/MkZi7eU2WE3oy7BwtkUtZ1cpD4y2qVvhEKOPsxaf08MrT1lL0Qj5x53YgJBE6tf6VlGmQttVdPOuYpK0UI9Me6/Ipzlif59uPHsCPwDRktaVVu9/TNFQVyDtM+qYxaNCIJ9B6sjZFN4iNt+oR6/Ip/uBFJ1T3ee0YLdGRMokk1QoVkqpfalNfhm0Hi3WC4MpzB9l+qMRUJSBqiJ8WQG/W5srzNtQJh1b3s52yNte0zVSoBNUt9muyNvm01TR8sp1VEzrxWHMssOit5wlSSr773e/yz//8z9x+++11CzY1Gs0M7S5trH1eu4m5tZ6L6YqPYQjChoC9ZjkzJT/ie08cZPd4maKr9iE9pzeDF8pqaF0YRgwXPEamXQYEINT4esUP6UiZ/P4Lh/jW1v1kbINIqmpEEM0eG/eXcbS9FSxTTVIl/qVIqkyaroxFV8ZS78ELqQSSV56+hoxjsu1gkf68w6/3TTFRDqqBi7YpsOLdX+cNdfHh25+aJRzOG+rCNkXTVRuWAW86e6CpsGh1P1tjm2mqElWDAPs7UuRS6p/3xs9JJCWf+9kzba+a0GiOZoSUixso3bFjB1/+8pf5yle+wvT0NK973ev43d/9Xd70pjct9zmuOFNTU3R1dTE5Oblsk2YaTS2LWdqYsO1gkeu+9zSZJmseQCUdl/2QD7/m1KYVoW8+tI+nRqYpeguri8Suk7IM3CCiL+c0TcadLPuMlXxAVm/kSVjeq7f0c8uD+8jYJo4pmIwTeY+gDQcgNhgr8ZWcSso0GOpJI4Soa/84hsCL841CKauqMNGmEuXteeVpa9i6d6qu4uaFERMln4ofYZqCwbyDF0ElCOPXFBS9iJP6snz00tObCt66z0vsz5rr85KI6NogwLQ1O3oj+Zz0ZdXC1TVNKkejRY9N85yXRnO00lZlp1Kp8K1vfYt//ud/5p577uFVr3oV+/fvZ+vWrZx55pkrdY4azVHNYpc2JrRqWm02eZN4LrYdLPK3P/gNBwrunKKjOkEV5+6U/YhCxaczY1WnjxJMQ+2JSlkGPSkTxzIQwHDB5cZf7SYMJfmUuuEW3WDRGT3LSSglMpoZKQdloq4EEV4QVds/nY7JtBcSyZlqlCUSQ7egK2ORsU0KZY+fbR/DjEMShZhJNK74as2GH0n2T7n05lL0ZJzquZhGtOBKh1a9MkmbqTYIsBm2KZgoR+yfcunKzD/ttdiRdY1mtdLy3OC73/1uBgcH+fznP89b3vIW9u7dy7e//e04M0KPH2o0zWhsQaUsAyOemunLOZS9sNpamIta0yoo90wlCCl6AZUgxAujeXcTGUJwWn8Hf3bxJnrjxxhipooDqqVlxk5dAdimOk8vVKsmaklWTEigL+fQnXFACsaKPmU/ouiGlIOIvZMuE/GNfyUQQMYSpJsYeZthCPW+BrvSDHalSVtqr9REyWe87GMIWNfh4IURUsq6nKEIdX2klJS9kLRlkHHUxFbKNqpCZ2TaxQ0ijJonu4FkpOBSqklbtk0xa+x89vkqEXPBCd1z7tKqpfFz0kiywT2KF5w2o5Xz0miORlpWKV/84hf5kz/5E77//e/znve8h76+vpU8L43mmKDV3JRkr1UzEtNqoeJTdAP2TVTYP+lyYMqL/1yhO20tuJvonI1dvO8Vm8mnzOruJ4jHx02BEa8ycExBR8rEsYSakmpYkFXxQ9xA4pgG6Xhv0khB3eSFUMZjUG2TQ6WAeBJ9WRFAX9amLxaQaUvM+ses9mrX5v4glKF6TT5FV9rmNVvWknNM1nemsUy1g8swRPXnlQgEiQpJTARgkqaczKmNl7xqiGPtj9owlOgdL3kkroGVWJ5Z+zlpdCck5ub1nSlS1vyCSC/11ByLtCx2brrpJu69917Wr1/PlVdeyXe+8x2C4PAlm2o0y00kJdsOFrl/1wTbDhbnra4slmoLagm/SSemVcMQDBdcKn6EQGLEKwvCSLWP7nhsZMH3cN7GLj70qpPpy9mkLBGLgJl1CIah0oENYZBPWQgB065aAhlJdZOfKAcIoaaJAHWTl8q8bAj130q7PSQwWvLZO6mux8tPXUN31lIVqthAXNvNSSav1PVS+62mKwGb+jKcPdiJQOBYRmykVt9vdikTU3coZxZvSpSw80JZrY7VXgNV/Z4RSYnwGOpOL+vyzORzknFMRote3c9stOiRcUzeceEQJ/Rk5hVEy31eGs1qoGXPzlVXXcVVV13FM888ww033MB73vMeSqUSURTx+OOPs2XLlpU8T41mWVmKYbgdWs1NWeg36bM3dNIbr1ZACLXMMjaUJILk/979LL/YOcaVC7yH84a6+cDLNnPLg3t5dHiaIJRIIavpu1nHREqJH0Zs7svSkbbYUxMqt7Erzf4pF9s0qjf5pG0jpSSK5LJXcpoh4raUbcDWvVO8ZHMftz8+QhRPfgkEKVPl90ipdoUhldg5UHBxTIOLTuqtW6w5VVF5RMkI+sz/T/XPapWEoOT75BwT148wUFUeKYiFkpwJbAyl2qUloRJETLvBrNTr5aKVIEADWpr20miOJRY9jSWl5D//8z/58pe/zH/8x3+wZs0a3vzmN/PZz352uc9xxdHTWMcXc2XWJP/YL+fobSQlf/WdJ5uGv7Uz/ZJMZCWJuSUvZDIOCjRN1U+JpGrP5NNWS+8hkpI7Hh/h5vv34ocR3VkbxzRmXYtGo+ymvgwfvv0pdo6WSNsmB6bc6mLMGaGwsgigv8Mhn1a/r40WPU7szSARbD9UpCNlYpkGKdNgsuIzWQ7wQ+XDSYRZyjTIOCYbu1KMFDz2F1yI21XN3oIVCxYrFliOZfKSzb3cu2uCiZJPqcGbJIB82iSIKzoRKo36pMOQQLxQzEE7014azbHAosVOLWNjY9x0003ccMMNPPzww8txXocVLXaOHxLxsWO0dNhGbxNxVfbCpr9JtyJM7t81wSfu3EFvzkYA+yYruEEUb0RX5xlEkv4Om4ofVd8DsOBEz4O7J7jp3j3sn3KJUKPRJ/Rk5r3xJe9pquxT8pR/JfG1NKNZ1sxSMOL04WQ4IhmrvuLc9Xzzwf2UgxDbEJT9UG2Aj701QqjFqms7UjiWEnZTZY+iFxFEysCLmFuwCZQHJzGZZ2wTxxAcmHZn7R8TKCG6NmdTcEP68ymuuXhTS2bjw8Fic580mqORZRE7Rzta7Bw/LCWzZiks9Tfp2vOWUo0zC0H15iTjys76rhQCdZO/8txB7t45NmerLqnsfPfxEcaKPkGkKh/rO1O848IhzpvnvMJI8osdo/zr1v08fbB02Jc8mAI1URUnOEdStabW5VMcmvaYdoO6fV0pyyAI1UJUyxD051PVLe9lP2TvZAUr9hw1Tp8lGCgjt2UIenM2KcvECyL2T1UII+hMW0zHY/aJIApC5a3qz6d0WJ9GcwRZcoKyRnM0sZTMmqWw1B1DtWsE0rapbqg1T63dLi4ljJdCbn5gL5GUTbN9XvvctXz/yUPsnayoVlhc8cinbQ4UXD5Xk/9TWwHoTFusy6coeiElL+JQyW8qdAzUuPZCmE0qQrYhCOYwCCckJuGEQiWoToV1Z21cPyAK40oMkHMMJsoSy5DVyaiMrcIEIymr+6oMMzZtCzWWLuIJtUiq95OslBgr+vRkRfwzEGrnVxixrjPFRMlXidNSmZOFgDc/b70WOhrNEUSLHc1xxXIZhhdDqzuG5movJGsECvHWceWhVWsckikqgcANQypBhAQG8qlZ6yX2TJT50j17Gl4T3FASlH3WNuT/fGvrfnZPVPDj/Jg1WQthGDw1Uqw7hmWIaitICFQK8QK9K4nywiR2F8eA/s4Ueycq8z9PzlS1oihirOSpNQl5By+UBFIQF30II8lUJSSKJHZsvEkmo9K2iSlmxu6DOLNIXTNRNTs3nnWSndOZsZBSTbQl01iDXWncICKUaiHqtBswkE/N+340Gs3KosWO5rii1UWLR2L0NpKSOx4b4XtPjKg0Xwm2ZdS1nq55yaa6KaqkRVM7RTVRUlWpniYpuaV491Mt1R1Z8aTSRNmnr8Nh+2iJT/5kB34QkUupUfWpSsjTh8p1zzcF/M7pa9nUl+Gme/eST1tYhqqM7Jtw563wRHImq0YIcGwTLwgXbIspM3SEG4g4v0YFHBrCIIziLevJGLih3peIJ6UE8dLTuDKUsoxqBk8kwappDQZNzDtCqIpOGEmmXbUkFSHUaolIIixRba+5QYRtGjq3RqM5wmixozmuaGfR4uFk655JvvTLXewYLRHFVQvHUtkvjWslzt7Q2XSKyg3UegfHVK0sp8GTJKVktNS8PVcreLxQjY9PVwJSlmBNRwo/lByc9nEbAgZP6svwjhds5JS1HRycVlkutqnaaWMlr6VWlmHASb1ZLj6ljwd3T84bsFjLZDkg68C6fIrhgludzFKm7VjYJHk3QomYIK6CqTyemZ+xbUBkKo9NGEUYcXsrkTpJ1ap6vYSoiii1D0vWpVDDkRfPGo1mhrb3PJx44olcd9117Nq1ayXOR6NZcZIKyaa+LGU/ZKzkU/ZDNvVlj4iJNJls2jlWQsZR/oYBXhAxXvLJ2GZdW8kQgkvPWMcHX7GZU9bmqPhR3Xv4LxdsIOOYs1Jy3SCalYZcSyJ4IikpugGRhIxtMlEO2D/l1gkdAWRtg9+7YANnD3bRl3M4tT9XTfCNpFobkTy29nl2HGJoGdDhmPz5S0/iM5efyeXnDPLRS0/n9Weum/W82ucbQlWBXrulnw+/5lTee/EmMvbM+01ZBo4ZpyWTZOMIOjM2QkAQt5tsU1QD9zozNu94/gY6UiZhXKGp7sUyqA8obLheWUeJrEQ7NQb56dwajebI03Zl5/3vfz833ngj1113HS972cu4+uqredOb3kQqpXvSmpVlOUdll2oYXi6S3VmFShBnuIhqNULElYPxsk9nymL7oRJ3Pn2IoZ4MhUpAV8bmutedxs7Rct17ALh7x9isVl0o68P+kpt1EpSXICWUgwgBTFQCGvVR1jbpzloUvRDbNKpTTbVVs5GChx8/sfY1TTHzekGkVj689JS+6nV/ZO8Uv3xmvO55tePeKulZiZXnbejklLU5IinrWpMIyKUs3NDHi9c6qJUSBmnbxA8i0pbBeDmYFbi3eU2OT/5kBxUvJGWZTFQCQFYzetR5y2quEBL8MKIna9ObsZmoBEy74azjajSaI8uiR88ffvhhvvzlL/P1r3+dIAi46qqr+P3f/33OO++85T7HFUePnq9+Dlfi8eEmGSkHyVgxwGpYKxFGEWHNpu6kRZME4s11DZpl+xTdkAMFV+14iieO/GaeFGi6UNI0BH1Zm6xjEkSqetFsRH/rnkn+KW7JCWYya2q3jVePKeCkvixXv+gEQCX7TsWTVY2PteJFnCIWMx993enV167m/lQCgjDCj6emkkNkbIOOlMVQd5rLzx0kn7IWDNzbNV5mvOTXjbDXtvtkfJ3OHOjgyvM2rArxrNFomrPknB3f9/nHf/xH/uIv/gLf9znzzDP5sz/7M/7rf/2vs8yRqxUtdlY3hzPx+HBQW6HaN1nh6w/sI5syODDlxS0aUX1cIjiSUe7kf1GGoDoJlJ3jGjRm+5gibmVFakw62e3UGCuTLLispTNl0ZWxsEwDA8lYyZ83fPGpkWn+1x1PYcf9n8mSh9ekg5YYk7szNjnHZKzk0ZOx1W6nUI2f11Z4UpbAMg1OXZub9drf2rqPm+7dgx9PhBlCxPu6VDvuqvM3cMkZ/S0JkMQs/pV7dzPthvGCUxFPv6lzyqdM3v6CjZza31GttGmBo9GsThZtUPZ9n9tuu40bbriBH/zgB7zwhS/k6quvZt++ffzlX/4lP/zhD7n55puX81w1xyFJm6fkhXWJx8kY9WjR45sP7ePsDZ2H7SazlHZaY4VKIuN2kIUTe0iS6k5YU9qo1QkqYwbGSwFpU7VVml2DZq26ghvwubgC4gchfjj7HGuFjmUIUvEWdCv2wYyXPSzL4Jz42M3e/ylrc5zUl2XnaInerE2hMrusYwjlT/ICJZ7GSj4CcAMPU6jsGiFmxJfyMxnk0xZXnDsIqMrYZNknn7Z4YPckGdugP22rxaRxyjGodRJ37xzjkjP6W/o5Ady9cwzTEKzvTDFRVtk5EuWnAkk+ZXH3znG++dD+Y6raqNEci7Rd2XnwwQe54YYb+PrXv45pmrz97W/nD/7gDzj99NOrj7nvvvt4yUteQrlcnudIqwdd2Vm9HKnE47lYSjutWYUqSeCNJPRkLKZclQcjhGg69gw1rRRUxccwZrd1FjqPmx/Yy56JCpV4nUJjOytjG7z5eetZ1+Hww6cPsW+yQiiJc2fURJOBmPf9J++3UAkoumGdYEtaZUBdu8wyVGUrilTZyRJK2EkpiVAtrz+MW17NRGN32iJtm4Q1YkfEqcgLfU5qRexkJeCGe3aRdaw4qFFWs3NMIaj4IaMltQi0J+sc9dVGjeZYp+3KzvOf/3xe9apX8YUvfIE3vvGN2Pbs/IgtW7bw1re+dVlOUHN8s9KJx+1UaWaJlYZU4maJw7Wm4WYVqrRt0t+hRqcnKwG9WYdCxcetycKxjRlvTeOZJfkwhXLAT35ziPt3TbC2w2FDd5qiG856T14Qsb4rzZ++5ER+sm2U2x8boeQHdcc8f6iL3z6pF9sUbOjOcP3rT2fnaJkHd0/wnUdH8KOoTqxtO1jk4z/aPqtNlEy9/fMvd/Ebd2ac3IhbQoYQVRNzLYYQVXO2YRqszdq4oWq9XXPxJspeOOvnMFUJ8MOAg0UfU/iAqO7B6sk6pG1j3s9Jo4iNpGQ6nkiTUgntJDtHSsmhosr26UjNiPAjWW3UaDTz07bY2bFjB895znPmfUwul+OGG25Y9ElpNAkrmXjcTpWm1XZaBHyryTEvOqmX3RMVOtOzg/5yKYs18dSVH0rStoVlSkp+QGfawjENDhS85m9CzExU3bp1GJiZdkpZquUz1J3m8nPWs6kvR9ELmCh73PirvTy6v1B3qL6czUs29/H0yDRfvX8PUUT1/C8/Zz0P753CjyI6UiZBFFH2I6ZdVRmadkP+793P8oudY1xZc/3O2djFey/exF995ymKXhBPVqmTDmU0y4QcRmrMW61ZkHhBRCWIcIOIk9eovJoP3/7UrJ9Dbe8tkmCb6jq4QcRIwaUna8/5OWkUsb6hxsZDCWMln4myT7omuNENIrxATWdZZn21UQi1cmP3RIXth0qHpdqo0WgWpm2xs5DQ0WiWk5VKPG61SpOw/VBpTrGS3OC2HyrxqTt3zFQ+ao75zFgZL4joTDf/n1w+beGFEW89f5ANXWnyaYsb79nFM2PlWWFYtYbdMJR1f49qHlMJItJBxPZDRT79k5287YIN/Hp/gR89fWiWyLhgqIuLNvVwy0P7qPghXZmZ1szOOEm57EWEkRI4USSrr2UZ6r8okvzmYHHW9TtlbY6T12R4eF9BZdjMs0JCQryWgqoReLToYwiYdkO+98TBWT8HKSXTXlh3DDVxNlMhGit5nLU+P+tz0ihiy37EoaKn2mjJ8SRUfCWa+vMpIqkqP2lLNG2tNlYb9XZxjebI05LY6enpaXmyamxsbEknpDn+mO9msBKJx4sxPS/UTrMMKHohgSVZ3zl7H9WBggrl8+J9TI34ocQ2DU5f14EhBJNlnxdv7uPA9H4KlaA6jdUoExqNy1Dv6ZmsBGzochgvBXz+58/UtcdAtcgcU7Brosz4Yx5uELG2o8k+rckKFT/CgJmMmZggUsdBqLZOEoCYXD9DCM4/oZuH99VXkhox1doqtXSz5o05pqrIHCp63Hz/3lmicbISUPHr22FBKLGMJCRRXZOLNvXO+pzUilgEjJeU0LFMAyOehpMkC0tV+8o2VCsun7YRTaIPa6uNx2pkgkZztNGS2Pn0pz+9wqehOV5p5WaQeD+SxxVcuaTQtlaqNI1tiIXaaSUvIpKSjrTZ9JjdWZvhKZeJss+62DSbkFSo1uQcbvzVbvbUXIvutEXWNnk2KCPDmURgI1Y0jQKnVugkjx0tBpQb5ssFandWR8rEMASHpl3GS37d4tCZY8hq8rIQs7eUA/jxaLtlGuRNs+76RVLy4O5Jso6JF0RVAdF4Psmm8aSokrTiNnanAVWpGi2qsELXD8k4FiUvZKzozTqejM+p9gv/+eRBhnoydZ+XWhHrBlF1mScooW0ZkiCaEZV+GHFiT5ZIEvt25JzVxmTyrdXqoUajWTlaEjvvfOc7AQiCgH/5l3/h1a9+NQMDAyt6Yppjn3ZaSUtJPG6sHI2XvLZNzwu106ZdH0MIcs7sqg2AY6oEX9s0OFBwSdsGjmWordiVAMMQjJV9Dha96rXwgojhgottCl68qUd5ZsKInGNhGIJCJai2b4zYqNysQdQodLK2UZ0gSozCGcekWPRnPb/khRwqetUsnvmWmEdxu8c0lFdmouwBuaq47M06OJY674PTnhorR02dyfjnpK6rehHTEPTFraXxkqd2dkklhvZPufTnJZPlYFYmUK3gEyQVI8GBgjvrc1UrYsNI1i0QBSVULUP5mYRQovZtL9iIbRjzVhsvP2c931plkQkazfFMW54dy7L4kz/5E5544omVOh/NccJiWkmGEG0bPptVjvqydjWwr1XT80LttLRjYpqSIASzyf+q/FCNa+cck+GCEinqRix4TncaIQQHi171WpS8sHqDn3Ylv9g5znN6MtUVDl4QVUezTAFiwT3hiq6MSXfaqYbtJdfdsYw44yYiE7fZSl7ISMGtbgdfCAkcmvaqizf/5b692IZBEMmquBQogSUQWFVREVdPJHVG466MupAjBbc67m4JUU1HHp7yqqskZDS72pSInkhC2hL0dziMlfy6z1WtiM2lzLoFolKqhagpyyCfsvBCSWhBd8bhlLW5eauNuZTVdvVQo9GsHG0blC+88EIeeughbVTWLInFtJLaZa7K0XDBpeKHhFHEQGe6ZdPzfO20y89Zz7e27mfHoSIdTULtxkqeEihSMpBPVSeFKn7IRMXHj6ArvhaJyKje4GPz74F4s/cV565XraQo4iv37qEcSBaaRbNiP0zWtrBMMauakKQNV/wQGfthxktevHh0xveykOyRqFaXbRoMT1X47E938uaz19e1AGdtJa+pnoRSMlZU4YIZ22CsqM5BPUcJENMQdGes6ioHGcVLOOXMOdT+XyGgJ+tgGMasz1WtiFU7rcALJKaprrkh1Og6MOtzMV+18f5dEysamaDRaNqjbbHz7ne/m/e///3s2bOH888/n1yu/kZ09tlnL9vJaY5d2snPWcw0y3yVozU5h+HIxQsiDk27dGZmh8LNZXqe7wa3Y7TEo/sLTLqVunUFlqEMs7Yp6sy/GdtEpi2GpypUAklfzkZKWRUZyQ2eOGSvI2UyVQm46d49OKaoW/Pgz6FCDAEZSy3rzKcsxkrerFablJLpSsCJPRmmvYDRokfKMvFCWU0vbqfRIgSsyTlkbIPRoscvdoyysTvNM6Ml7KxdPZ5arinjn4uqnkgpmSjNCAAvrohVl5nGlZburI1pCEamPbrSFvm0RRhJDk2ralgtvRm7uqy0mcioFbHbR0t4YUAQSRzToDd+nbk2mM9VbVzJyASNRtM+bYudK6+8EoBrrrmm+rXkNy4hBGHYJH9eo2mg1ZvBcMHlr77zZNvTLAtVjnqzDpMVZcgdLfltmZ6b3eC27pnkjsdHlA+nuohSEgaSyBQ4hqAvN9v8K4SgI2VT8l2KXohjGLNu8FLK6pbwih8SRLA259CZMZiuQDmoDwWsJWMZbOrL8tbzN2AZYl6fydU1ycTbD5VUqF9sOq7d07UQteIin7bZM+ly5XmD7Bov88xYuc73k/w5bStxVaj4VQEwUVJC14r/fQkjdV16sg4CQS5lYhYFQRiRMg2EJTDysH/Sja+bErddGbuagFwJIqSU5BsiAGpF7EO7J7h75ziHih6VeJdYu2b4lYpM0Gg0i6NtsbNz586VOA/NcUYrN4M1OYdbH96/qGmWVipHhhD83vM30J1xlpSBUltFGsinQKgWVSIWxkuB2nk1O5IFgKyjjMpFN8RICaSMp61iwkjiWAaFiq82oANCSFw/ZKI8W+jYpqDTMSgHksGuNH/7hudiqYVOLU21nb2hkx9vG+WLv3hW5dt4KlfHMmavsDBRk0qmocbFE3FRey4FV1J0A2UCnkMvjZd8wkiyeU22uvfqxl/t5umDRYK4nZSqCfYDCELIpUxsU1QFnGMZ2KbADdT59uZSdQbnMFKC+cZf7a4LP4QZEXvK2hyXnzu4pGyclYhM0Gg0i0eHCmqOCAsafm11c17sNMt8lSMppdrVFEmmKiHnDy0t5K1ZFSltzbSK/JSk7IeUvIh8erbiCSLIOSaOaTDtKvEi1YlWqxlZx2SipML1pISpSkilcV050J2xYu8PZCPJRCVg52i5WolqZarNEIKXndLHD586yK/3TRFFYMdKTYj6XVaGoU42ksps3dtQvfJDNZJ+985xSp7KCzJNUeNDllU/0EDe4brXnVYVZn8/mOcDtz3OnskK3Rm18yrJtUkE8eYav9TuiQqBK0nZJpEMcUy1jmIsrhAhlSjrydg8s4BgXowZvpHljkzQaDSLZ9Fbzx9//HF27dqF59XH2F922WVLPinN8cF8N4OLNvVyy0P7Fm1gnqtyVPJCxkqqPWEK9Rv+j546uKSbz0JVpFzKZLQomHZ9OlLmrCrWVNljfWeaF27q4Zc7xtgxWiYIVVXIMQWdGQcpI8Iak3Cj0ElEkGMamIaI/1NrHJ4YLswSNgvdyA0hePFJvTy8dwriQD3R8FoCCCTVDeVrO2aqLsl7K1R81uVTHCioXVLJiHxjgrMQsHfS5a7fjPGyU/rijBuDd104xGd/ulNVvYSBbTKrOnLOxi7O2dhVv9294vP/HtrHo8PT1Qpbyp6pDEkpD8v491IiEzQazfKxqN1Yb3rTm/j1r39d9erAzAir9uxo2mGum8GDuyeXNM3SrHLkhxEHpz3C/397dx7eRnnujf87izSSLHnfYxOc4Oz7QpoQGmgSICylh0JoKSQcoAd+DSUhUDilvAVaXlJCaUsL5dfQXmE7NPQ0QAsUQmggLCklCyZhy77YsR3vtqxlpJl53j9GM9Zqy7ZsOfb9uS6uYkmWHo1Ndft57kVjEHigwGmFKHBdgyznjMLFkwp7/UGUTP6RzaIfVZ1yy8i268ctQZWhxSMjoDLUuWX8be8piAKH4kwJbd4ANOhjJCwChw5/V0PBaAKnByAaAGuo2glAqA+Pghd2n9RLvXvZvbfYJcERmiAeVPXxEBwAm8gj224Bz3No8wVx3lm5+OhYKzr8QWhMP5ZTNJgByYKKHPylqi40VDP0/xeh1zArp5h+XLbhw+MRwWeyuyNGGfnBRg++rHeDATh/XD6OtfghCnpOkCTy5s7QYJZ/p2KXiBDSP70OdlavXo2Kigq8/fbbGDNmDD7++GM0NzfjjjvuwC9/+cuBWCMZ5uJ9GKSimiX8g/JEqw9tPgWqps80ys2QAADNnfqIBI2p+MOHx/Hh4WZcPWtUr3Z5uss/8sgKGjplcJw+liEQKn2XRB5CqGeMVeSRFXaM1+4LQBB45NpEtPsVtHiCMRVGHPQjK29AQVDVd1jslq7J3B5ZQZMnoI81kEQzuDLyna6YXoJil4QsuwUVeXYcbfbF7Dxk2S2wWwXYQkdYalg5PcfpHYcFjsOhRi+CGuBXGLxBGRwH2AQe5Tl2rDi7DC6bBS/vPQUG1Vx7IjYLH5OTlczuSFVNO/70rxM41uoz84qMLtOFLiniWNHQXcBM86wIGV56Hez861//wrZt21BQUACe58HzPBYuXIh169bhtttuwyeffDIQ6yQjTKqqWYwPSiPh1mbVS5x9AQ0NnTI0TS/x5qEn2B5q6n0r/0T5R26/HnAAQL7DYg77bPMGYRF4iIKe8Jtt00uuvQEVAIdMu4h2rxJKVOZiAh2RB3IdVkgWPWBq9gbBcYBTEsEYIKsqGjr1iqRCp2QGQJLIQbEIaHDL+MOHx5FhEczOxTzPgY/a/Zk2KtP8GeQ6LAioesAjKxqsAocWj4ygynCy3Q+bhYfFrgdnisrg1TTUdcj4a1UdrpxRgkKXFa1RQUW8XSqLwMElxeZkdbc7UlXTjke2HUarNwgw/fqA46CExlKccsvgOS7iiA1IHDDTPCtChp8E9SGJqaoKp9MJAMjPz0dtbS0APXF5//79qV0dGbGMAMJuFdDsMXZf9A9ao+fJgjG52FPdjoONHj0BtZvnyrKJ4DkOTmtYw7zQwEeO48yuv05JNAdZdvec0YxdpIo8B3xBFS2eIFp9ekKxsYPCcxxsot7vpt0XRIM7AE9ARU27jOo2P+o7Amhwy2jokOFXNJxo86MlrOdMjsOCy6cUYVxBBhSNwe1XwPEczsp3YGyeAwxAY2dA/9AHh7wMCzKkrr9nvAEVjZ4ANE0P7ESBgyegolNW4ZEV2Cw87BbB3FnZe7JDrxjiORxv9aG2XcapDhm17TKOtfjgC5VlewMqmj1BNHmCod45+q6KX9FwpMmDx98/hjNz7RFHV/GurNm8MOqIqTsaY3jxk1p9d4bpidQ8z4dyfozHAM0eGeHDNIyAuTzbFhEwG40ojzR7YbcIyM2wRFyTqpr2pH8nCCFDR693dqZMmYK9e/dizJgxmDdvHtavXw+r1YoNGzZgzJgxA7FGMkIlytfIz9A72r64pzbpv7zDj8UYWMTAR6BriKbI9z2XI/y45ct6N17YfRIuSYyYcm4GHHE+7Y3RBrJqfKXjOGDJuHxcPrUINouADGspGjsD6PAr5hFLVU07nv24BnUdMlSVQdH0RoFWQdATcsHCAjw9SdjtV8CY3uxQ1fTjnNJsG/LCqt2uDJWBGyvUrxML5d+ErpkQWZKuhaqeVI3BabPCIys43uKDyybAF9TMHZdwemDSlW8U74gp3tHS4SYvjjX7wJi+jnA8z0OABlUDZEV/v05JTFj+3ZcRJqlER2eEDJxeBzv33nsvPB4PAODBBx/EpZdeinPPPRd5eXl48cUXU75AMrJF52vUd8jY/GktfEGtV713wo/FbBY+YuBj+AwkSeTBgD638jeOW9p9QXDgYA1rrhMecPBc/KGa0TcVZ0r4/vxyjM51QOT1jr7WUL8ZQ1VNOx5//xi8ARVZdn1URV27DFlhaOiUUeiUwPMwAzzjNRStq3mhELpfVjR998lmwYlWH579dzVUjWF0rt3sU8NzQINb71sTnmAcvnOjagDP640VXTYLmr1BlGbaUN/hR0aGgHa/Ak9ACwWY+rWQxK7xGtFHTImOlmaMykRQ0/TXjxMYGJPUOU4fUhpQgwnLvwdjhEkidHRGyMDqdbBz4YUXmv8+ZswYfPHFF2hpaUFOTk7c/7MhpL+MAEJjDPe+9hV8Qa3Xf3mH59W4/QoAPcAxRjEYM5A4Tp823t9W/vESrGVFg6xo5nFNz+8b+M95ZTgzNwMum378Ff3fWLzdCMb015QVBlXVA6xsuz6mARzMPCVF7SonN75PDS3MInCQVYa6Djl0BMdDEhhkpsEXVKGo4UdCkes2x1SFytKNXZoFFTn422encKpTP0ozjrMCmt6jx+iMHJ2TlWjG2dFmL060+ULr75q1FY7B6FLN47/OGY0sm5hw16Q3I0xSqbv319v8MUJIfL3O2TEcOnQIW7Zsgc/nQ25ubirXREhcvfnLOx7jWOysggzwvD5bSh8pwKPQJZn9V+LlcvSWsZPk9gfBGANjDEFFMwODnoIdHnqJd1BlKHBZ475nIPaaGGMR7NZQP59QN2f9mImZ3YizbCL4sF0eYySFcYwUVJmetM30D3lvQEVtux91HbLepC9sDSwq2jG+Enh9p8bYpXFYu/62Ci0t4jmic7KMTsrhwZwk8mY35bwMKxRF3x3iOEQEYOZzagwcxzAmz4HzK/Mw54xscwBotPAANZ6BmGcVHaxGv7++5I8RQmL1Othpbm7G4sWLMW7cOFx88cWoq6sDANx000244447Ur5AQgzmX95C4r+8Fa37v7xnlGXh/146ATcvGI0chwV2i/6hYrPwMR+0/cmXCE+wbuqU4Q2o0EJhQDC28XHM+8h26GXfo3MdsAqJ/zMNvybhAUmbVzE/IDUGeIOqXnHF6f2FsuwWWAV9V8vY0bEK+oesEfCVZEqwWXi4/Qoa3DJkRQPHRY6yMJ7f2M0J/0jOsApo8wXR2Ckjx2HBB4ebzCOx0mwbSrIkFDj1n4GRXO0LqqjIc5i7GT0FuJl2K3iOQ4ZVBDggqGjQND2ZXdH0Y7YsuwVXzxrV488zOkANl6ogOFp/A3hCSHJ6HezcfvvtsFgsOHHiBByOrv/or776arz55pspXRwh4VL1lzfPcbh0ShHuWjwWlQUZ8Cv6SIHoD9r+mlziwsq5ZSjNssGnaPDJmrmdEf0OjI85qwCUuKzQNA1nZNugMYZdJ9oSVpwZ1yQ6IBF4fWfF+JbzK/Nx84LRKHBa4QuqCKgMWXb9AzYYmm6eZbcgoDAz4FtxdhnKsiS0hE1h1ye58wj/XI4XAAFAq09BkycIX1DDoUYP9tV3wirwoSMxPnTEpQebhRlWZFgFXD+vHA9eOsG8/skEuDzP4YrpxRib54AgcFCZno8k8BzG5jnwo2+MTernmUwFYKrnWaUigCeE9KzXOTtvvfUWtmzZgrKysojbKysrcfz48ZQtjJBoqZ4kncpW/uGVNC6biEKnFd6AhrEFGVhz/hh8UtOBV/edgjuQuMO4wAGZNgvcsgpB4NEpq3hwy0H4g3qeT0mmhBXzyjEr7IN7bL4DZVkS9tW5wULzqYzrwkGvnOJ5oKbNh/9v4WiUZdu6EmE1hgyrYPbZMSZ8n5lrxzlj8qAxoLLAiU9PuiPWaRx5GRVsYECe0wpZ0eD2KxFHXBz0+Vmapu8ANXn0wMkb0AMuPbFY/1AX+K4WAYZ4uU/GUZ3KGDRNv26zyrNx1cxSHGz0YP+pTjAAE4qcCY+sEhnseVapaJ5JCOlZr4Mdj8cTsaNjaGpqgiRJKVkUIfGkYpJ0vPLe/lbWVNW048VPanGs2YeAqkLgeIzKlnDxpCKcVeDAG1804h9fNESUZ3OcnpPDMYZA6HajM3F+hgUtviDq3DKCqoagoh/HdPgVPPCP/bju7DJcOaPUvCbnjMnD3lp3RKKwcTQlCBxy7BbUhI5C4gV45TkSNledQl27HwBwotWL53bWQGOhHZvQzo0ayvvhOA42kYfDKsAjK5BVBm9Qhd0iwGHl4Qno4Y4ocKF8Gg4qNCia0fNG7z9kHKsx6HlFAFDvliOubXSAGz7BnDF9hIXTKsAtK+A5DuMLnRhf6OzXzzMVQXCyZeSpDuAJIfElHezU1NSgrKwM5557Lp599ln8/Oc/B6D/H5mmaXjkkUdw/vnnD9hCCQH695f3QJT3Gt1727xBhAZrg4OGAw0KTrQeg1UUQk3+wt7DqEx8Z1YJPAENnbKCkiwJkijA7Vfgsol4+t/VqHOH8nyiTq5kleGZf9dgTJ4Ds8qzAejl6XarAFXVENS6dl6kUIm6zcKjxRs0j0LCuxH/taoW97xaC0+c1woNNDf7//DQm/Zl2kRk2UVw4GC3Cuj0q/jO7FI4JRFPfXgcPKdF7DABgMDzUDQ9oNErpGB++HPQOzPzPPDhkZaI+WThAW59hx9+hYWqrhDaydKf7/EUVy31Z55Vb37PUhHAE0J6lnSwM2XKFPzud7/Do48+ikWLFmHXrl0IBAK466678Pnnn6OlpQUffvjhQK6VEAB9+8t7IMp7Ncbwxx3H0eLRgwhjTAHTGBQGeAKaucsBADl2C747uxSzyvXXOcMqIMtmiWhueLDRg5o2fyhfRL8tomoJQFBjePKD4/jDd7K6ZlhZBNgc+lGHGspXMQZfyglK6f9aVYuN/66GliBhOvpmDXoCcJsvCKvAw27h0elXUJHnwGVTivThrcw4morX8ya8t1DXkVS8HajwQGNGWRZuPfdMrNt6CKqmhSq5ONgserm63cIPygTzZPTl92ywj84IGYmSDnYeeughrFq1CkuXLsXu3bvxxz/+EYIgwOPx4IorrsCqVatQUlIykGslxNSbv7wHqjPuvtoOHGvV+7yIgl72zTQW0yyQA/CNcXmYXZ6NgKKhutWP6aNcEaXYhnZfEP6gZiZhJ1pNbYcfBxs9GF/ojDgKycuwghNDJehBPQenU1b0kRJhRyGKpuHFPbX62Ai+5wqx8PeiqgzNHhk2i96d2dh5yLJbYOF5cJwat+dNVwMePchRQvnaiXagwrlsFv31JAECx0UEc8b9gzHBvDv9+T1LZf4YISRW0sHOD37wAyxbtgw33ngj5s6diz/84Q944IEHBnJthKREd+W9ACCJAg43efHOwWacX5nX4wdMQNXQ7gvi05MdUDRA5Iwdivgzn2aXZ6Ku3Y+nak5A0/TKmzNy7HH/as+yW8wZTt2tQtOA/ac6Mb7QGXMUYhF4uGUFAUXvXcNzQKesYu/JDvP1th9qgSegQgjtRsVfeSwVev5OQGU4M1fC9fPKzeccm+/AmXl27KsNVRiFJdzqgaD+75LIodAp6VPUk9iBArqqlnJtlrg/n4Fq+Ncb/e3A3J+jM0JI93qVoFxRUYFt27bh8ccfx5VXXomJEydCFCOfYs+ePSldICHJ6C4hNFFnXG9ANZNdVY1hw4fH8c/9jQmPDlSNocOvwBNQAHSFBxoQ9yjI6JT81SmPWdptNNlLdKwxNt+BbLsFnbLaVe0UYrxevJ42xlHIn/51AoebvaGJ6YBN1D9kmzyBiNdrcMv6Y8LK05PBQQ/uJIuIa+aMilg7z3G4emYpTrT60OoNIqhoZjClhnreWHi93NxIxjbfWw/JuOFVS1YBZjWWwEU2Lkxn1VK6OjATQnrW62qs48ePY/PmzcjNzcXll18eE+wQMth6SgiNV97rDahocMvQQsmuPAfYrHzCIMQjK2j3KxG9bkRzgGTkejjo+SmKcWQDhiKnBJ7X21p1d6zBcxwun1qEJ94/Hvre+AQeXWXjoe+dNioTTpuIDKsApyRANIKK0AiG8NcrdEngOITef3JHJRy65liJofEO0WaUZeFH3xiLP/3rBI61+vQgh+mByJk5diyqzMM/vmjodTKucVR3oKETKtNLsiPK1jlgXOhIL12ojJyQoatXkcpTTz2FO+64A0uWLMFnn32GgoKClC1k3bp1uOeee7B69Wr85je/AaD/tffAAw9gw4YNaG1txbx58/DEE09g8uTJ5vfJsow777wTf/7zn+Hz+bB48WL8/ve/j+kDRIanZBJCp43KjCjvBaAP5Awdo6ihIaAuSQSsiAgKFJWh1RdEUO3auumUFfy1qg4fHGmNWY/RG84IgAQOyM2wmoGOIfxY42CjBzzHmbtSyyYV4pVP63GyQ0Y8DHol0jMf12DbgSYzqDvc5EVNmx85Dqs5UDPe6x1u8mLRWbn4/z84hk5Zhciz8HSahATeqL5kyM2wJAwsZpRl4bErpyTseXNWfkavk3F5jsOs8ix8Wtuh99YJNU3UGIM/qFdyzSrPSmuOC5WREzJ0JR3sXHTRRfj444/x+OOPY8WKFSldxM6dO7FhwwZMmzYt4vb169fjV7/6FZ5++mmMGzcODz74IJYuXYr9+/fD5XIBANasWYNXX30VmzZtQl5eHu644w5ceuml2L17NwRBSOk6ydDSm4TQ8JwWSRQQCHUNVkOTv40hlOBgTvz+pKYdRa6u3lGMMXx0rA0vflKLTjmyOSBnPib0NQc4LTzAcQnHPVgEDq1eFb/bfhTtfiViV2rZ5EK89Gkd2n2KWdJuBCM8BxS5JFiEyJ0oRWNJH6OIfAaunlWKjf+u1hOFudiBnuF4Tg90FE2/bsvCysPjPz5xz5u+JONqjGFPdTvslq4Se5WFqrJEQBB47KluxxXTS9IW8FAZOSFDV9LjIlRVxd69e1Me6HR2duJ73/sennrqKeTk5Ji3M8bwm9/8Bj/5yU9wxRVXYMqUKXjmmWfg9XrxwgsvAADa29vxpz/9CY8++iiWLFmCmTNn4vnnn8e+ffvw9ttvJ3xNWZbR0dER8Q85/fQmIdTIaanIc8AXVEPHK6EhoE59CCig/94ZCbiN7oD5fKfcMh595yj+9FF1RKBTnm3DNbNLMaEwA05JgM3Kw2UTMK3UhevnnQG7RUg43sLtV+ANqKh3y7BbBORm6CXkR5u9+McXDbhiegmmlbqQaRPN8Qw2ASjJtMEpiTHDIl02sVfjNK6cUYr/nFcOpxT/jwIeRhdmYyq6HvSMzXPg4kmFSfyEEjOSccMHc2qM4WCjJ+54DONnneuwYlSOHSVZEopcVpRkSRiVY0euwzokZkhF/54NxBgSQkjvJb2zs3Xr1gFZwKpVq3DJJZdgyZIlePDBB83bjx49ivr6elxwwQXmbZIkYdGiRdixYwduvvlm7N69G8FgMOIxpaWlmDJlCnbs2IELL7ww7muuW7eOKsmGgd4mhBo7Cu8cbMaGD4/rgYkkmuXLWqjni6zoTfFcNhFBVcObXzbi9c8jOyBbBQ6XTy3GkvH5EHgO51fmo9kbQFDRkO2wmkcVO462xD3W0JiGFm8AHAcUOa1x83n2VLfj55dOwPZDLXHXC0QGdQDiHqMwMPiDKtp8CsqybKjIs5vff+WMUnxrWjG2H2pBg1tGgdMKT0DFi3tqEVQ1ZNlEgNMrpfxBFU5JwI3zz+hxd8JIGG/1BuCWVWTaBGTbrQl3cHrKuwr/Weu7OV0BmjEx3RdU8XldBzTG4PYraSvfpjJyQoaetGYXb9q0CXv27MHOnTtj7quvrwcAFBUVRdxeVFRkzuCqr6+H1WqN2BEyHmN8fzw//vGPsXbtWvPrjo4OlJeX9/l9kPToS0Ioz3E4vzIP/9zfiKPNXsCqBwOqxqAx/d89soKybBt8QRU/e/Mg6qJyZ6aVuvC9OaOQF8r/sQo8chwWlOfYES3RsYaeMwTk95DPc7TZZ86LclojAx2DEdS5/UrM6wVVfbyCrOjHT3UdMn76+v6I/BiR57F4XH7Ec47OsYfN0NJLwisLMpJqcmcELoebvKHOzHoSdYYkYGyc3Jxk8q4S/ayNijo5VGb/x39Vg+MASeBhtwr97pDdV1RGTsjQ0uup56lSXV2N1atX4/nnn4fNZkv4uOjjibjNyqL09BhJkpCZmRnxDzn9GAmhbn8QLCrhxEgILc+2xSSEGrkVNguPxk4ZnoAKhTEEVA1t3iCsIgee5/HLbUciAp0su4hbzjkDP/z6mXrzPuiBVGEofyaeRMcahS4JDosAly3+3xvh0657M+09/PXa/UGccsuQVQaryKPIJSHLbjGDiKqa9oTXdkZZFn52yXhcP68c35xShOvnleNnl4xPKtD57XtHsb+hE56Aah4LapoeRB5o9ES8dnTelSTy4EPl5OFHdBV59piftVFRZ0wnZ9BfR9UY/IoGDkjqvRJChr+07ezs3r0bDQ0NmD17tnmbqqp477338Pjjj2P//v0A9N2b8M7MDQ0N5m5PcXExAoEAWltbI3Z3GhoasGDBgkF6JyRd+pMQOq7QiWvnlOH1z0+hzh2AGtA/lJ2SiFZfEJ/VdU365gCcX5mHb00rNnN7JJFHtt2SMMgJF+9YQ2MMD245mNSuVLJVPhV5dhxs9EDRGFacXYYn3z8GRdX07sRhfW2S6Rod71ipux5EQFfg4pEVfZcsVO3GcRwEHlBUDaqqwRsKYIxrkkze1dFmX8TP2imJaPEGoBrZ29DziSwCb46g6JQVlGRKaPEGh8QoCUJI+qQt2Fm8eDH27dsXcdt//ud/YsKECbj77rsxZswYFBcXY+vWrZg5cyYAIBAIYPv27Xj44YcBALNnz4bFYsHWrVuxfPlyAEBdXR0+++wzrF+/fnDfEEmL3s4VMrofy4qG8UVOVBZmoLrVjxMtPrx3uBlHW3wRjy/LtmHF3DKMCe0O8RyHTJsIp9S7/3SijzU0xroNYDr8QRS7JLR6AzjcBFw5owSPv38sYVA3qzwLP319vxmcAEBnQEFOaG5WuJ66+fZ1jpgRuNgtIjyBgN6wMPR+AL2BYVADMkXefO3e5F3NOSPb/FkfafbCr2jmcNKgqpkzxjiOA8/rSeYBlQ2JURKEkPRKW7DjcrkwZcqUiNsyMjKQl5dn3r5mzRo89NBDqKysRGVlJR566CE4HA5cc801AICsrCzceOONuOOOO5CXl4fc3FzceeedmDp1KpYsWTLo72mk6q578WBIJiE0uvuxuXaNYV9dB177LDYB+ZtTi7BkfAFE3ihp55Fjt0CMs5vT22vQ3a5USyjRua5Dxq/fOWom6148qRB7qttjgrpZ5Vn4xxcNEcFJh18PIlq8QYi8PksqvONwom6+/ZnvZAQuokWvrGJR4zP0AZ76/ypq7BFdMnlXxs/6tc9O4dmdNciyi2AMONURiAgYOeidrVXGYBd56lxMyAg3pNsf33XXXfD5fPjBD35gNhV86623zB47APDrX/8aoihi+fLlZlPBp59+mnrsDJKeqmgGS6KEUMYYOgMq3FHdjwHgQIMHz+2siUlAnlrqwjWzR6HAaTWfO8suIiPO4E6g79cg3q6UxhgCigaLEBqsKXTtqtS7Zdz69Qq4JNEMFCry7Pjp6/tjghObRQDPBaFqDPVuOZTWzIHj9EDOKYlxu/mGHysBgD+oRgRJ3e2SGIGLP6jGn9geOnGSgxpEge/VEV143hXPcZhY7ILdIkDgeDCOhfoEsbAKNKOTNUediwkh4Fh0ZucI1NHRgaysLLS3t1Oyci/EHHdEHa2ku6+IUW6tRA2u6pQVbP60Hu8fbom4Pcsm4juzSzGnPMv80LRbBGTbLeYRSbTuroHNwuPb00tRnCl1u9tj7Aq1+QL4n50nUdfhR4FTivngb/YEUJHnwIOXTjCf52CjBz978wDsFiGiazIDQ3WrH7Kiv3eR14MEI4mXQe+X89iVUyLWtOtEGx7ddgQ2C492XxCBsLEM1lAA5lc03HH+GMw5Izvmffzk1S+xt9YdMfndbLgY+l+RB6aWZuL/ht6HcQ19ATXuEV283yONMdz72lc42uxFboYFde16orIYlrMjibyZsxN93QghI8uQ3tkhQ1d/jjsGmqJqaPMp8CuRXY4ZY/j38Ta8uKcW7rDGgByA8yrz8B9hCcg8xyHbbjG/jqe7a6BYBDR0yvjDjuNwWsVud3uMXamDjUCzN4gsu7XbZN3wXZWecl6inwNMD14SjVQ3kqcbOwN6JRXPgedCOzKKhsbOADKsQtxdEp7jcM6YPOytdUeMn4g4yoI+SuOcMbnm70Vv866M1zKOAVs8QTglEQFVP/4Dp9+vJzFT52JCCAU7pI960714sJJCjWZy+sTwyA3LBreM53edxBf1nRG3j8qyYcXZozA2v2uNPe3mGBJdA29ARWOn3keHYwwOSS+nPtjowfp/HsY1c0bh4jjjFvoyNTtRzousaFA1BoFDqDIK+qgHADYLD6ckos2vxPx8KvLsZnNFi8CZ74sDwPF6Do3GWERjwnDFmRLsVn2kg6yyiCGpAgdYRR4Cz6E4bAwH0LdGfNFBkt0iwB/ayZJEHgzoceYWIWRkoGCH9ElfPpgHkiegoMOvQI0aQa6oGrZ81YTXPj8V0afGKnC4bEoRlk7oSkDmOQ45jtjqpUTiXQPGmDlkVOQ5qAzwBzX4AmqoH4yKP3x4HB8ebsbVs0ZFfAj3pUliopwXVWPQQnOsbBYeeRkWaEwfnimJPBgDWrzBmJ/P0WYfeF4vFVc1Zg7/NI6GBF6vqjra7ENlQUZMYrbLJsJuEWBzWMzrrzH9e4wp8X5FS7gz1NvAODpIMvoWpbODMiFk6KFgh/RJXz6Y+6q7SqeAoqHNF0RA1WK+72CjB899XIPaqATkKSV6B2QjARkAHFYBWbaed3PCxbsGsqIhoOrHP4Ae/LR5g2DQP8wFnkHTgENNsWXcfU3WjVfVpYbycniOQ67DGhPABVQt7s+n3RcEDw4FTiksZ0ffEZJE3szZafcF4yZml2VJyLaJaPIEkJdhjRnrYOQdpXLyN3UrJoT0hIId0id9+WDui0SVTt+eXoKKfAe8ATXmezwBBZur6vFeDwnIGmM42SaDMYYCl4TsXgZm8a6BGsqJ4Tn92Ch8o0kLBQ0cx+CURLM7sJHX1NcmiYlyXpySAMYY7BY9cZlBn/ulqBo6ZRVnFWTE/HyMAM4i8CjNtnUdh4V2hAIKg6Ix1HfIeGlvXUwvnmMt+s4Qz3M0+ZsQMmRQNRaoGquv+lJF05fnD690CigaOvxBSKKA6+aWYWKx03w8YwwfH2/Dpj11cMuR/XSmlrhw0cQCVBbqE7a/rO/EW181oK5DhqqhzyXz0ddAYwx17bI5vsAQXZFU4NR3W3xBFT+9aFzEzkREgKfpgUsya4veAXP7g3j8/WPwBVRYBB5uv75To4Wqq8bmOXDj/DMinjO8yikvThDb7AngzDwHwBiOtvgiErPDH5OfYYXTJqKml++BEEIGAgU7oGCnP/r6wdwT40P3SLPX/EA1Eme10NFQWbYNa84fA57j0OCW8T+7TuLzqARkSeRgFXhw4CAIHEpcVkwtzcT2w83wB7WUlMyHX4OgqsEjqwiGbelEBzoAYBc5lGTb0OpVEpZxp6JRY1VNO/70rxM40uzVc2c4DlaRg0vSJ7rHe789BbFXTC/Bi3tqY8rdDbKiwRdUce+FleA5jiZ/E0LSjo6xSL/0pYomGdHN7YxEVwDgwCFDElHnDuBYsw9fnerEq1EJyCLPQRL1GeFOSS/9VlSGmjYfDjZ6IFkEFLuklJTMR1+DvbUd+GtVHcD0Lr7Rf02IPBDUAI+sJsxrSlUeyrRRmXBKAuxWAa5QI0EpNCfL2IWJfr89lYIrGksqOd3tV2KCOEIISQcKdki/xftg7u/ORLsviKCiIcMqxJ32LQocZL+GP+w4jmZPZEXR5GIn5KCKU50B5Dgs4IzOwVa97Nkd8ENQtZheM/0pmY++Bv/4vAEqY/AHNTPY4aAHYTzP6TtAARXj4uTNpNLhJi9q2mXkOqwxuzDdvd/ugtiDjZ5BS04nhJBUoGCHpFwqRkhYRR48z0FWNFijZlGpmj4/yhvUIhKUM20irp5ZgiKXhCc+OA6nJIKDHlwIHMyjMA76B7KsaBHVQkBqSuaz7BbYrQJsIg+/oqHFE9CTlnk9V0bVNDCm9/MZ6GTd/rQISLS7NFjJ6YQQkiqxB+6E9IOR73Gk2Qu7RUBuht63xpiYXVXT3u33y4qGU24Z2XYRxS4rPLJiNghkjMETUFDb4Yc3GFlqvuisXDx4yXjMOzMHnbIKVdWb4okCB5Hvao4nhKqeGBDTkwdIza6EEQx0ygqybCKKM22wWXgAekm4ygCnJOD288cMeLJueHl8PH15v0bVmN0qoNkTCPUP0oPHZk+AKq4IIUMOBTskZaLHJ0ii3jlYEnnkZVjNUuvogZxA125NY6eMoKqB5zgsm1QEm4VHmzcIb1BFQ2cATZ5gRDn3qCwb/nvJWFw3t8wc7eCyibCIXKgEPPIDVwp18DXKw8MZuxLl2bZ+7UpEBwMCz6E4U0J+hhX2UIO/Hy89C7MGoSrJCLzc/iCiaxH6836NvJ6KPAd8QRUt3iB8QRUVeY60z0QjhJBodIxFUqYvIyS6m0o+sdiJa2aX4YXdNWjoDETcJ/IcvjmlCBdM7OqArN/OY3Z5Fkbn2HG02Wsm44az8AAEDp2yCp7jB6QPTHSSr1GpNq7QOajl133t3ZOMgUpOJ4SQVKNgh6RMb/NDEk0lNxxu8uB/q+rQ0BmZTzKp2Inr5o5CgbNrvhIHvYlepk0E18MHfKbdgosnFWJPdXvSgyf7YqgEA30ZtJks6l5MCDkdULBDUibZERJOSURTZyBmKrnBG1Cx+dM6vHeoJaJs2yWJ+M6sEpw9Ojtit8Yi8MhxWCISmZP5gL9iesmAByJDJRgYKoEXIYSkAwU7JK7elI4bj231BpDnsKDeLSM/Q587JSsaVMbAcxzcvgBG5zqQYRXiBjqMMeyqbsem3bVo90d2QP762Fx8e0YxMqxdv7IcOLhsev+Y6KMqoOcP+KESiAyERD+/4fp+CSGkOxTskBi9KR2PfqzGGPxBFTWKH4zB7HisMT1XZnyRE/FipsbOAP5n10l8VueOuL00U8J1Z5fFfEhbBR7ZUbs58YzED/hUlP5HS1VHZ0IISQcaFwEaFxEu3jyqRKMUEj22we2HX2Fmzz4OgCjoycNOScB1c8vNmVaKxrD1q0a8+tkpBMLKoy0Ch0snF+HCCfkQwwIaDhwybSJcNorT4+nNz683z5nq4IkQQgYTfWIQU3TpeHejFADEfaxVQOjfGSw8kO2wgOc5cwemzRvEG1+cwviiDBxt9uK5nSdR0+aPWMfkYie+N2cUCl1SxO2SyCPbboGlh92ckao3P79kd2VigqfQdHOjbxKVmRNCTgcU7BBTb0rHAcR9rD+oIqBoEDhAZQDPc5CEri7FGZKI2g4ZGz48gd3V7UklIHPg4LQJaHAHcLzFR8coCfSl9L87AxE8EUJIOlCwQ0y9LR2PfqymMQQ0BsYAgdeDHU1jQCjWYYwhoGpo9ynYVR3ZSTk6AVljDNWtfviDKjoDKj461ooaOkbpVn9GQ8ST6uCJEELShYIdYkq2dNwYLWA81iLoiciM6S25OQ7QmJ6rw4ca/imqpnfZVSJ76sRLQP6yvhNvfNmAU24ZclCDN6iC54BchxW5GRY6Rkmgtz+/nqQ6eCKEkHShYIeYejvgsSxLwpFmL7Ls+mRxQB/gKQocZIVBEgALz6HdH0S7T4k4srIIHC6ZXIiLJhREJCB/Wd+J53fVwB/Uc0SMQZ+aBrT6grAIPBxWIaXHKMOl0ijVAzpTHTwRQki6ULBDTL0ZLdApK1gyvgDPfFyNNm8QGZIIUeCgqAwCZ8yd4lDXEYASNXBzdI4d/3XOGSiKSkAGgLf3N0JWNBQ4JciKhqDKIPD68E5F1dDqDcButaXsGGU4VRqlejQETTcnhAwXVNZCIvQ04HFSsQun3DLafEGML3LiurnlKMu2wa/ouTh+RUN5th0VeQ7IKosIdAQOuHhSIe698KyYQMcmCuiUVdR2yGaOiMr0ozHjI1bgOQRUfbo2oO8OKVrfj1H6O6F9KErlgE6abk4IGS5oZ4fEiNd5+MxcO9yygoZOOeKxE4udGF+UgepWPzp8QdS0+/HPA01o80V2QJ45KhMrzh4Fly3yyIPnOGTZRWRYRRxr8UbkiAgcB44DGPSAh+M4MMaghgKo/hyjDOdKo1SOhhjIuVqEEDJYKNghcYV3Hu6UFTR2BmKmkoc/1ikJ+Nu+euytjeyAXJIp4bq5ZRhXGHvMZBMF5DgsEEJJzNE5IpLIwypwkBUNXGgPkoO+w9PfY5ThXmmUys7RNFeLEHK6o2CHJCQrGtp8QQTV+FPJAb0K6+39TfjbvvqIDsgiz+HSKbEJyEDkbk64eDkiOQ4rGtyyWe1lJMr29xiFKo16ZySO3SCEDB8U7JAYqsbQ7g+alVCJHGn24rmPa1Ad1QF5YpET184dFTcB2W4RkG3v2s0JFy/B1mbRJ5q3eAMAAFHg4Q9q/T5G6anSKKBoYIyhtt2Pg40e2skghJDTGM3GAs3GMjDG0BlQ4fYrCY+sAMAXVPHyp/V452BzRDm5UxJw9cxSfO3M7JijIZ7jkG23wGEV0JOICilNzxEpy5Jwzpg8FGdKKTlG0RjDva99haPNXuRFVRp5QrlJHMfBaRVP6wotQgghFOwAoGAH0Mc8tPkUKFriIyvGGPbUdODPu0/GJCAvHJODK2eUwCnFbhZ2t5uTyGD0vjGqsXwB1SzTdvsVNHn0XaT8DCtcNrHfgzQJIYSkFwU7GNnBjqJqaPcr8AW7P7Jq9gTwwu6T+PRkZAJycaaEFXNHYVyhM+Z7erObky7hu0hBVYMnoIIxhkKnhIywwI0xhmZPABV5Djx46QQ60iKEkNMI5eyMUBpj6PAr8MgqGBLHu6rG8M8DTfjbvlNmfxtAT0C+ZHIhLppYEHcKeV92c9IhvNLoi3o3Nu2uhdMmwCZGBmjDoUKLEEJGKgp2RiCPrKC9h7wcADjW7MWzO2twojUyAXlCkRPXzhmF4szYBGSe45Dj0JvznS6MSiOj8soaJ3hjjEFjDL6gii/q3ZSwTAghpxEKdkaQZErJAT0B+ZW99dh2sBnh8ZDTKmD5rFLMj5OADAAOq4As29DfzUkkUYWWN6Ci1RuArDBoYNi0uxb/PtZKCcuEEHKaoGBnBEi2lBwA9lS348+7a9Ea1V/mnIocXDmzBK44CcgCzyHHboFtCO7m9CbROV6fH29ARYNbhhYaXWETOThtAk1dJ4SQ0wgFO8NYsqXkANDiCeCF3bWoOtkRcXuxS8K1c0dhQlFsAjIAZFhFZNnFIXmk09shn9F9fpySiBZvACpjAAMEgUNuhgSbKEDK4E/rkRKEEDKSUDUWhmc1VjKl5IC+67PtQBNeiZOAfPGkQiybFD8BWeT1SquhuJsDdJWVewMqMuNM/+5uR8YIko40e9HuV8ADkEQeOQ5rRGWZrGjwBVX89KJxlLBMCCFDGO3sDDOqxtDmC/ZYSg4Ax1q8ePbjkzjR6ou4fXxhBq6bOwrFmba43+e0isgcors5QP+HfBoVWq99dgrP7qxBll2E3SKAQ+RjaaQEIYScHijYGSYYY+iUVXT4lW5LyQF91+eVvafwz4NNMQnIV80swYKKnLgJyEN9N8eQiiGfPMdhYrELdosAgeNjAh2gf1PXCSGEDB4KdoYB/cgqCEXr+UTyk5p2vLC7Fq3eyN2IBRU5uCpBAjIw9HdzwqVqyGe8hGVD+NT1ijw7DjZ6aCI4IYQMURTsnMYUVUObT4Ff6fnIqsUTwJ/31OKTmsgE5CKXFdfNLUuYgHy67OaE62nIZ7I7MvEGk0bn/swqz8JPX9+fdBI0IYSQwUfBzmmIhbofd/bQ/RgANI1h28FmvLy3PiYBedmkAlw8qTBuAjIwtCutupPsjszYfEePzzWjLAu3fb3CrOpyy3qgVJHnwKzyLPzji4auJGibHghRWTohhAwtFOycZrwBFe3+INQkjqyOt3jx7M6TON4SmYA8LpSAXJIgAXko981JRjI7MstnliYdxIWPlDCOqiry7Pjp6/v7nARNCCFk8FCwM0BSPbU7qOrdj8N3ZxLxB1X8bd8pvH0gMgE5wypgeTcJyPpjTs/dnGjd7cj05YjJGClhONjo6XcSNCGEkMFBwc4A6G0zu+4kO7Az/LVf2F2LlngJyDNK4LLF/5Gfjrk5PYm3I5Oq5OFUJUETQggZeBTspFhMM7t+5HF4Ago6/EpSR1Yt3gD+vDt+AvK1c8owsTh+AjJwelVa9Vb0jkyqpCoJmhBCyMCjYCeF+tvMzhBQNbQneWSVKAFZ4Dlc3EMCsshzyHFYIYnx7yeJpTIJmhBCyMCiYCeF+tvMTtVCR1YBJanXO9Hiw7M7a3AsOgG5IAPXzh2F0qz4CcgA4JREZNnEhLk7pHv9SYJOdT4XIYSQ7lGwk0L9yePwyArakxjYCXSfgHzVjBKcMyZxArLI88hxWGg3JwX6kgSdynwuQgghyaFgJ4X6kschK3qVVVDt+cgKAKpOduCFXSdjEpDnn5mN5TNLEyYgA4BLEpFJuzkp1Zsk6FTmcxFCCEkeBTsp1Js8jt4M7ASAVm8Qf959EnuiEpALnVZcN3cUJha7En6vyPPIdVhgTWI3h45Yei+ZJOhU5XMRQgjpPQp2UiiZPI6rZpTAI6twy8kdWWkaw7uHmvHSp/XwRyUgL5uoJyAnCmI4cHBKQtK7OSP1iGUwArxUDCclhBDSNxTspFh3eRyXTy1GSZYN7f7keq+caPXh2Y9jE5ArC/QOyN0lIFsEPTfHmqASK9pIPWIZrACP+vIQQkj6ULAzAKLzODIkAXkOKwKqltRkclnR8Ld99Xh7fxPCH+4IS0BOtPPAgYPLJsAlRe7mdLd7MVKPWAYzwKO+PIQQkj5pLcl58sknMW3aNGRmZiIzMxPz58/HG2+8Yd7PGMP999+P0tJS2O12nHfeefj8888jnkOWZfzwhz9Efn4+MjIy8M1vfhM1NTWD/VZiGHkcE4ucyJQsCCSZgLz3ZAd++o/9eOuryEDna2dm48FLxuPcsbkJAw6LwKPAZY05Kqmqace9r32Fn715AI9uO4KfvXkA9772Fapq2gH07ohluIgO8CSRB89xkEQeeRlW+AIq/vJJbVJHjckw8rnc/iBY1HMa+Vzl2Tbqy0MIIQMgrcFOWVkZfvGLX2DXrl3YtWsXvvGNb+Dyyy83A5r169fjV7/6FR5//HHs3LkTxcXFWLp0Kdxut/kca9aswcsvv4xNmzbhgw8+QGdnJy699FKoanKJvwMtqLGkxjy0eYN48oPj+O17x9Ds6TrKKHBasfb8Ctw0/wxkJqi04sAh0yai0GmNObYydi+ONHthtwjIzbDAbhHM3YuqmvauIxYh8RGLog2vI5bBDvCMfC67VUCzJwBZ0aAxBlnR0OwJ9Ho4KSGEkORxLPrPzDTLzc3FI488ghtuuAGlpaVYs2YN7r77bgD6Lk5RUREefvhh3HzzzWhvb0dBQQGee+45XH311QCA2tpalJeX4x//+AcuvPDCuK8hyzJkWTa/7ujoQHl5Odrb25GZmZnS99PmC6JTTtwkMGECMgdcNKkQl3STgAx0n5ujMYZ7X/sKR5q9EcdTgL6b0OwJoCLPgZXzyvHgloOwW4S4/XdkRYMvqOKnF40bNsmzu0604dFtR5CbYUnY+K/FG8Qd54/BnDOyU/a6ETlCmn50NRKSwAkhJJ2GTM6Oqqr43//9X3g8HsyfPx9Hjx5FfX09LrjgAvMxkiRh0aJF2LFjB26++Wbs3r0bwWAw4jGlpaWYMmUKduzYkTDYWbduHR544IEBf089qW7VOyAfbY5MQD4r34Hrzi7DqG4SkJOptEp29wLAiBt9kK4cmoEcTkoIISS+tAc7+/btw/z58+H3++F0OvHyyy9j0qRJ2LFjBwCgqKgo4vFFRUU4fvw4AKC+vh5WqxU5OTkxj6mvr0/4mj/+8Y+xdu1a82tjZ2ewyIqGv+87ha37GyMTkC0CrpxZjIVjEuflAKHdHHvPfXOSrQBy+5U+jz44XaVzttVADSclhBASX9qDnfHjx6OqqgptbW3YvHkzVq5cie3bt5v3R+9IMMZ67BnT02MkSYIkSf1beB/tre3A/+w6GZGXAwDzRmdj+cySbncSets3pze7F5UFGb0efXA6689sK0IIIaeXtAc7VqsVZ511FgBgzpw52LlzJx577DEzT6e+vh4lJSXm4xsaGszdnuLiYgQCAbS2tkbs7jQ0NGDBggWD+C561uYNYtOeWuyqbo+4vcBpxbVzRmFySeIOyEDv++YAvd+9GGlHLH2ZbUUIIeT0k/ZgJxpjDLIso6KiAsXFxdi6dStmzpwJAAgEAti+fTsefvhhAMDs2bNhsViwdetWLF++HABQV1eHzz77DOvXr0/bewinaQzvHGzCS5/WwxeMTEC+cGIhLp3cfQJyor45yejL7sVIO2IZaQEeIYSMRGkNdu655x4sW7YM5eXlcLvd2LRpE9599128+eab4DgOa9aswUMPPYTKykpUVlbioYcegsPhwDXXXAMAyMrKwo033og77rgDeXl5yM3NxZ133ompU6diyZIl6XxrAIAjTR786p0jOBRVvjw234EVc8swKjtxAjLQt92caLR70bORFuARQshIk9Zg59SpU7juuutQV1eHrKwsTJs2DW+++SaWLl0KALjrrrvg8/nwgx/8AK2trZg3bx7eeustuFxdRz6//vWvIYoili9fDp/Ph8WLF+Ppp5+GIAjpelsAgDe+aMDv3jsak4D87RnF3TYGBPq3mxMP7V4QQggZyYZcn5106OjoQFZWVkr77Bxv8WLV/35mjoc4e3Q2ru4hARlIzW7OcEOT2AkhhPTHkMvZGS5G5zpw5YwSbDvQhGvmjMKUHhKQU72bM1yM1EnshBBCUod2djAwOzsAEFA0tPqCCPYwF4t2c+KLGdQZlVw9XCexE0IISS36dB1AVpGPO34hnEuKP9NqpBvsQZ2EEEKGL/qETROR51HolJBljx3lMNJpjOGdg8043OSFTYxNNB+uk9gJIYQMDMrZSQOXJCbdBXmkMXJ0Djd50eFX4Amo6PBzyHFY4bB2BT7GqIvhNImdEELIwKBgZxCJPI9cR88zrUaq8Bwdm5VHpwwADLLC0OCWUeiSzIBnoAZ1EkIIGX7oU3eQOCURRS4rBToJROfouCQRksiDMUDgOWiModUbAGPMHHVRnm0bVpPYCSGEDAza2RlgFp5DoVOiIKcHh5u8qG7zI9PWlcOU47CioVOGqjFwHBBQGTplFbKi0qBOQgghSaNgZ4BlSHSJk9HuC0JRGSy2ruDFYRVQ6JTQ6g1AVjRojMEXVDE2n0ZdEEIISR59EpMhIctugRjqoyOJkQGP3WqD26/AH9TwX+eMxvmVebSjQwghJGl0tkL6RGMMBxs92HWiDQcbPf3udzM234HybBvc/iBi+lwyvUHj2HwHBTqEEEJ6jXZ2SK8NxAgHnuOwfGYpfvveUTR7AnDF6ZhMOTqEEEL6gsZFYODGRQxHAz3CISKQ0vTycpqFRQghpD9oZ4ckLbo83KiakkQO1gwrmj0B/OWTWkwbldnnHZgZZVmYNiqTppwTQghJGQp2SNLilYcbokc4VBZk9Pl1eI7r1/cTQggh4ShBmSTNLA8X4u+yWAQOikYjHAghhAwttLMzQmiM9ftoKFF5uIFGOBBCCBmKKNgZAVJVPWWUhx9t9sIalrMDwBzhUJHnoBEOhBBChhQ6xhrmjOqpI81e2C0CcjMssFsEHG324rfvHUVVTXvSz2WUh9utApo9XV2NZUVDsydA5eGEEEKGJAp2hrHo6ilJ5MFzHCSRR16GFb6Air98UturhoAzyrJw29crUJHngC+oosUbhC+ooiLP0e+yc0IIIWQg0DHWMDZQ1VNUHk4IIeR0QsHOMBZvuGY4i8DBLfeteorKwwkhhJwu6BhrGAuvnoqHqqcIIYSMBBTsDGPdDdc0qqfKs21UPUUIIWRYo2BnGKPqKUIIIYSCnWGPqqcIIYSMdJSgPAJQ9RQhhJCRjIKdEYKqpwghhIxUdIxFCCGEkGGNgh1CCCGEDGsU7BBCCCFkWKNghxBCCCHDGgU7hBBCCBnWKNghhBBCyLBGwQ4hhBBChjUKdgghhBAyrFGwQwghhJBhjTooA+ZE8I6OjjSvhBBCCCG95XK5wHUzAomCHQButxsAUF5enuaVEEIIIaS32tvbkZmZmfB+jhnbGiOYpmmora01I8OOjg6Ul5ejurq624s3UtD1iETXowtdi0h0PSLR9YhE1yNSKq8H7ewkged5lJWVxdyemZlJv5Bh6HpEouvRha5FJLoekeh6RKLrEWkwrgclKBNCCCFkWKNghxBCCCHDGgU7cUiShPvuuw+SJKV7KUMCXY9IdD260LWIRNcjEl2PSHQ9Ig3m9aAEZUIIIYQMa7SzQwghhJBhjYIdQgghhAxrFOwQQgghZFijYIcQQgghwxoFO3H8/ve/R0VFBWw2G2bPno33338/3UtKi/feew+XXXYZSktLwXEcXnnllXQvKW3WrVuHuXPnwuVyobCwEN/61rewf//+dC8rbZ588klMmzbNbAY2f/58vPHGG+le1pCxbt06cByHNWvWpHspaXH//feD47iIf4qLi9O9rLQ5efIkrr32WuTl5cHhcGDGjBnYvXt3upeVFmeeeWbM7wbHcVi1atWAvi4FO1FefPFFrFmzBj/5yU/wySef4Nxzz8WyZctw4sSJdC9t0Hk8HkyfPh2PP/54upeSdtu3b8eqVavw0UcfYevWrVAUBRdccAE8Hk+6l5YWZWVl+MUvfoFdu3Zh165d+MY3voHLL78cn3/+ebqXlnY7d+7Ehg0bMG3atHQvJa0mT56Muro68599+/ale0lp0drainPOOQcWiwVvvPEGvvjiCzz66KPIzs5O99LSYufOnRG/F1u3bgUAXHXVVQP7woxEOPvss9ktt9wScduECRPYf//3f6dpRUMDAPbyyy+nexlDRkNDAwPAtm/fnu6lDBk5OTnsj3/8Y7qXkVZut5tVVlayrVu3skWLFrHVq1ene0lpcd9997Hp06enexlDwt13380WLlyY7mUMWatXr2Zjx45lmqYN6OvQzk6YQCCA3bt344ILLoi4/YILLsCOHTvStCoyFLW3twMAcnNz07yS9FNVFZs2bYLH48H8+fPTvZy0WrVqFS655BIsWbIk3UtJu4MHD6K0tBQVFRX4zne+gyNHjqR7SWnx97//HXPmzMFVV12FwsJCzJw5E0899VS6lzUkBAIBPP/887jhhhu6HeKZChTshGlqaoKqqigqKoq4vaioCPX19WlaFRlqGGNYu3YtFi5ciClTpqR7OWmzb98+OJ1OSJKEW265BS+//DImTZqU7mWlzaZNm7Bnzx6sW7cu3UtJu3nz5uHZZ5/Fli1b8NRTT6G+vh4LFixAc3Nzupc26I4cOYInn3wSlZWV2LJlC2655RbcdtttePbZZ9O9tLR75ZVX0NbWhuuvv37AX4umnscRHWEyxgY86iSnj1tvvRV79+7FBx98kO6lpNX48eNRVVWFtrY2bN68GStXrsT27dtHZMBTXV2N1atX46233oLNZkv3ctJu2bJl5r9PnToV8+fPx9ixY/HMM89g7dq1aVzZ4NM0DXPmzMFDDz0EAJg5cyY+//xzPPnkk1ixYkWaV5def/rTn7Bs2TKUlpYO+GvRzk6Y/Px8CIIQs4vT0NAQs9tDRqYf/vCH+Pvf/4533nkHZWVl6V5OWlmtVpx11lmYM2cO1q1bh+nTp+Oxxx5L97LSYvfu3WhoaMDs2bMhiiJEUcT27dvx29/+FqIoQlXVdC8xrTIyMjB16lQcPHgw3UsZdCUlJTF/AEycOHFEFr2EO378ON5++23cdNNNg/J6FOyEsVqtmD17tpkdbti6dSsWLFiQplWRoYAxhltvvRUvvfQStm3bhoqKinQvachhjEGW5XQvIy0WL16Mffv2oaqqyvxnzpw5+N73voeqqioIgpDuJaaVLMv48ssvUVJSku6lDLpzzjknpk3FgQMHMHr06DStaGjYuHEjCgsLcckllwzK69ExVpS1a9fiuuuuw5w5czB//nxs2LABJ06cwC233JLupQ26zs5OHDp0yPz66NGjqKqqQm5uLs4444w0rmzwrVq1Ci+88AL+9re/weVymbt/WVlZsNvtaV7d4LvnnnuwbNkylJeXw+12Y9OmTXj33Xfx5ptvpntpaeFyuWLytzIyMpCXlzci87ruvPNOXHbZZTjjjDPQ0NCABx98EB0dHVi5cmW6lzbobr/9dixYsAAPPfQQli9fjo8//hgbNmzAhg0b0r20tNE0DRs3bsTKlSshioMUhgxorddp6oknnmCjR49mVquVzZo1a8SWF7/zzjsMQMw/K1euTPfSBl286wCAbdy4Md1LS4sbbrjB/G+koKCALV68mL311lvpXtaQMpJLz6+++mpWUlLCLBYLKy0tZVdccQX7/PPP072stHn11VfZlClTmCRJbMKECWzDhg3pXlJabdmyhQFg+/fvH7TX5BhjbHDCKkIIIYSQwUc5O4QQQggZ1ijYIYQQQsiwRsEOIYQQQoY1CnYIIYQQMqxRsEMIIYSQYY2CHUIIIYQMaxTsEEIIIWRYo2CHEEIIIcMaBTuEkJS5/vrr8a1vfSvlz1tfX4+lS5ciIyMD2dnZKX/+VBqoa9CTp59+usdrk661EZJuFOwQcpoZCh9Yx44dA8dxqKqqGpTX+/Wvf426ujpUVVXhwIEDcR9z//33g+M4XHTRRTH3rV+/HhzH4bzzzhvglQ5tjz32GJ5++ul0L4OQQUeDQAkhQ97hw4cxe/ZsVFZWdvu4kpISvPPOO6ipqUFZWZl5+8aNG0/r4bWMMaiq2u+hiVlZWSlaESGnF9rZIWSY+eKLL3DxxRfD6XSiqKgI1113HZqamsz7zzvvPNx222246667kJubi+LiYtx///0Rz/HVV19h4cKFsNlsmDRpEt5++21wHIdXXnkFAFBRUQEAmDlzZtwdk1/+8pcoKSlBXl4eVq1ahWAw2O2an3zySYwdOxZWqxXjx4/Hc889Z9535plnYvPmzXj22WfBcRyuv/76hM9TWFiICy64AM8884x5244dO9DU1IRLLrkk5vEbN27ExIkTYbPZMGHCBPz+97837zN2r/7yl7/g3HPPhd1ux9y5c3HgwAHs3LkTc+bMgdPpxEUXXYTGxsaY537ggQdQWFiIzMxM3HzzzQgEAuZ9jDGsX78eY8aMgd1ux/Tp0/HXv/7VvP/dd98Fx3HYsmUL5syZA0mS8P777+PTTz/F+eefD5fLhczMTMyePRu7du2KeN0tW7Zg4sSJ5trq6urM+6J3Bc877zzceuutuPXWW5GdnY28vDzce++9oJGJZNgZtJGjhJCUWLlyJbv88svj3ldbW8vy8/PZj3/8Y/bll1+yPXv2sKVLl7Lzzz/ffMyiRYtYZmYmu//++9mBAwfYM888wziOM6eWq6rKxo8fz5YuXcqqqqrY+++/z84++2wGgL388suMMcY+/vhjBoC9/fbbrK6ujjU3N5try8zMZLfccgv78ssv2auvvsocDke3U55feuklZrFY2BNPPMH279/PHn30USYIAtu2bRtjjLGGhgZ20UUXseXLl7O6ujrW1tYW93nuu+8+Nn36dPbSSy+xs846y7z9xhtvZKtXr2arV69mixYtMm/fsGEDKykpYZs3b2ZHjhxhmzdvZrm5uezpp59mjDF29OhRBoBNmDCBvfnmm+yLL75gX/va19isWbPYeeedxz744AO2Z88edtZZZ7Fbbrkl4ufjdDrZ1VdfzT777DP22muvsYKCAnbPPfeYj7nnnnvM5z18+DDbuHEjkySJvfvuu4wxxt555x0GgE2bNo299dZb7NChQ6ypqYlNnjyZXXvttezLL79kBw4cYH/5y19YVVUVY4yxjRs3MovFwpYsWcJ27tzJdu/ezSZOnMiuueaahL87ixYtYk6nk61evZp99dVX7Pnnn+/x50XI6YiCHUJOM90FO//n//wfdsEFF0TcVl1dzQCw/fv3M8b0D7iFCxdGPGbu3Lns7rvvZowx9sYbbzBRFFldXZ15/9atWyOCHSMQ+OSTT2LWNnr0aKYoinnbVVddxa6++uqE72fBggXs+9//fsRtV111Fbv44ovNry+//HK2cuXKhM/BWFewEwgEWGFhIdu+fTvr7OxkLpeLffrppzHBTnl5OXvhhRcinuPnP/85mz9/fsR7/OMf/2je/+c//5kBYP/85z/N29atW8fGjx8fcQ1yc3OZx+Mxb3vyySeZ0+lkqqqyzs5OZrPZ2I4dOyJe+8Ybb2Tf/e53GWNdwc4rr7wS8RiXy2UGY9E2btzIALBDhw6Ztz3xxBOsqKgoYm3Rwc7EiROZpmnmbXfffTebOHFi3Ncg5HRFOTuEDCO7d+/GO++8A6fTGXPf4cOHMW7cOADAtGnTIu4rKSlBQ0MDAGD//v0oLy9HcXGxef/ZZ5+d9BomT54MQRAinnvfvn0JH//ll1/iv/7rvyJuO+ecc/DYY48l/ZrhLBYLrr32WmzcuBFHjhzBuHHjYt5vY2MjqqurceONN+L73/++ebuiKDF5LeHfW1RUBACYOnVqxG3GtTNMnz4dDofD/Hr+/Pno7OxEdXU1Ghoa4Pf7sXTp0ojvCQQCmDlzZsRtc+bMifh67dq1uOmmm/Dcc89hyZIluOqqqzB27FjzfofDEfF1+M81ka997WvgOC5irY8++ihUVY34ORJyOqNgh5BhRNM0XHbZZXj44Ydj7ispKTH/3WKxRNzHcRw0TQOg55OEf/j1VnfPnUj06/V3DTfccAPmzZuHzz77DDfccEPM/cZ6nnrqKcybNy/ivugP+PD3Y6wp+rae3l+8x77++usYNWpUxP2SJEV8nZGREfH1/fffj2uuuQavv/463njjDdx3333YtGkT/uM//iNmXcbrMcq/IYSCHUKGk1mzZmHz5s0488wz+1y5M2HCBJw4cQKnTp0ydzJ27twZ8Rir1QoAUFW1fwsGMHHiRHzwwQdYsWKFeduOHTswceLEPj/n5MmTMXnyZOzduxfXXHNNzP1FRUUYNWoUjhw5gu9973t9fp1EPv30U/h8PtjtdgDARx99BKfTibKyMuTk5ECSJJw4cQKLFi3q9XOPGzcO48aNw+23347vfve72Lhxoxns9MVHH30U83VlZSXt6pBhhYIdQk5D7e3tMT1ucnNzsWrVKjz11FP47ne/ix/96EfIz8/HoUOHsGnTJjz11FNJfYAtXboUY8eOxcqVK7F+/Xq43W785Cc/AdC1s1FYWAi73Y4333wTZWVlsNlsfS5r/tGPfoTly5dj1qxZWLx4MV599VW89NJLePvtt/v0fIZt27YhGAwmbLR3//3347bbbkNmZiaWLVsGWZaxa9cutLa2Yu3atf167UAggBtvvBH33nsvjh8/jvvuuw+33noreJ6Hy+XCnXfeidtvvx2apmHhwoXo6OjAjh074HQ6sXLlyrjP6fP58KMf/QhXXnklKioqUFNTg507d+Lb3/52v9ZaXV2NtWvX4uabb8aePXvwu9/9Do8++mi/npOQoYaCHUJOQ++++25MfsfKlSvx9NNP48MPP8Tdd9+NCy+8ELIsY/To0bjooovA88l1mhAEAa+88gpuuukmzJ07F2PGjMEjjzyCyy67DDabDQAgiiJ++9vf4mc/+xl++tOf4txzz8W7777bp/fyrW99C4899hgeeeQR3HbbbaioqMDGjRv73QAw+ggo2k033QSHw4FHHnkEd911FzIyMjB16lSsWbOmX68LAIsXL0ZlZSW+/vWvQ5ZlfOc734ko7//5z3+OwsJCrFu3DkeOHEF2djZmzZqFe+65J+FzCoKA5uZmrFixAqdOnUJ+fj6uuOIKPPDAA/1a64oVK+Dz+XD22WdDEAT88Ic/jMmhIuR0xzE60CWE9ODDDz/EwoULcejQoYgEWHJ6O++88zBjxgz85je/SfdSCBlQtLNDCInx8ssvw+l0orKyEocOHcLq1atxzjnnUKBDCDktUbBDCInhdrtx1113obq6Gvn5+ViyZAnlcRBCTlt0jEUIIYSQYY1mYxFCCCFkWKNghxBCCCHDGgU7hBBCCBnWKNghhBBCyLBGwQ4hhBBChjUKdgghhBAyrFGwQwghhJBhjYIdQgghhAxr/w+10gRE94D8+wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x=\"Length of Membership\", y=\"Yearly Amount Spent\", data=df)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bbb403e",
   "metadata": {},
   "source": [
    "---\n",
    "### <a id='toc1_1_4_'></a>[Correlation Analysis](#toc0_)\n",
    "\n",
    "The correlation heatmap highlights the relationship between features and `Yearly Amount Spent`, with `Length of Membership` emerging as a significant predictor of spending. This suggests that the duration of membership plays a crucial role in influencing spending patterns, potentially driven by factors like loyalty programs or cumulative expenditures over time.\n",
    "\n",
    "$$\n",
    "r = \\frac{\\sum (x_i - \\bar{x})(y_i - \\bar{y})}{\\sqrt{\\sum (x_i - \\bar{x})^2 \\sum (y_i - \\bar{y})^2}}\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a2286c06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation Matrix\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.heatmap(df.corr(), mask=np.triu(df.corr()), annot=True, cmap=\"coolwarm_r\", cbar=None, vmin=-1, vmax=+1, center=0)\n",
    "plt.title('Correlation Matrix')\n",
    "# Remove ticks from both x and y axes\n",
    "plt.tick_params(axis='both', length=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3baa44e",
   "metadata": {},
   "source": [
    "---\n",
    "## <a id='toc1_2_'></a>[Data Split](#toc0_)\n",
    "The train/test split is a fundamental step in model development, partitioning the data to train the model and independently evaluate its performance. This separation is critical to assess the model's ability to generalize to unseen data, ensuring its predictions are robust and reliable outside the training dataset. It guards against overfitting, where the model performs well on training data but poorly on new data, and is essential for validating the model's real-world applicability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "620dfabf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lib\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# Isolate the target variable\n",
    "X = df.drop(columns=\"Yearly Amount Spent\")  # independent variables\n",
    "y = df[\"Yearly Amount Spent\"]               # target variable\n",
    "\n",
    "# Test/Train Split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34ef69b5",
   "metadata": {},
   "source": [
    "## <a id='toc1_3_'></a>[Linear Regression Model](#toc0_)\n",
    "We swiftly construct a multiple linear regression model with just a few lines of code. In this notebook, we skip hyperparameter tuning, allowing us to reveal the model's test score immediately. Typically, we avoid examining test data early to prevent influencing the tuning process, which could lead to overfitting and diminish the model's ability to generalize to new data. Here, without tuning, we present a train score of 98.5 and a test score of 98 upfront. Our next step employs Recursive Feature Elimination (RFE) to eliminate redundant features, aiming to reduce noise and boost the model’s efficiency.\n",
    "\n",
    "$$\\hat{y}^{(i)} = w_0 + w_1 \\cdot x_1^{(i)} + w_2 \\cdot x_2^{(i)} + w_3 \\cdot x_3^{(i)} + w_4 \\cdot x_4^{(i)}$$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fd62b2d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ML Libraries\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.metrics import r2_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "eeb05391",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train score\n",
      "0.9854085989105928 \n",
      "\n",
      "Test score\n",
      "0.9808757641125855\n"
     ]
    }
   ],
   "source": [
    "# Build and Train Model\n",
    "scaler = StandardScaler()\n",
    "reg_model = LinearRegression()\n",
    "pipe = make_pipeline(scaler, reg_model)\n",
    "pipe.fit(X_train, y_train)\n",
    "\n",
    "# Predict and display model score on training data\n",
    "train_pred = pipe.predict(X_train)\n",
    "print(\"Train score\")\n",
    "print(r2_score(y_train, train_pred), \"\\n\")\n",
    "\n",
    "# Predict and display model score on test data\n",
    "test_pred = pipe.predict(X_test)\n",
    "print(\"Test score\")\n",
    "print(r2_score(y_test, test_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5444b40",
   "metadata": {},
   "source": [
    "### <a id='toc1_3_1_'></a>[RFE | Recursive Feature Elimination](#toc0_)\n",
    "\n",
    "Recursive Feature Elimination (RFE) is a feature selection method ideal for scenarios with numerous predictors. It enhances model performance by iteratively building models and removing the least significant feature at each iteration, based on the feature's importance as determined by the model's coefficients. This process mirrors backward elimination in linear regression, focusing on eliminating features with the smallest absolute coefficient to refine the model.\n",
    "\n",
    "Following RFE, the $R^2$ value on the test data remains at 98%, indicating the model's explanatory power is maintained even after reducing the number of variables. This streamlined model, with fewer variables, offers enhanced interpretability, making it easier to understand and communicate its predictions. Additionally, it reduces the risk of overfitting, ensuring robust performance on unseen data, and improves computational efficiency, which is critical for processing large datasets or in scenarios demanding quick predictions.\n",
    "\n",
    "We've utilized an automated method for feature selection through Recursive Feature Elimination (RFE). Next, we'll shift to a more statistical approach using backward elimination, where we'll examine p-values, coefficients, and the F-statistic to make informed decisions about our model's performance and feature selection. In many real-life machine learning applications, the value of an interpretable model—where a data scientist can fully grasp how decisions are made—cannot be overstated. For instance, in medical diagnostics, understanding the factors influencing a model’s predictions is crucial for trust and actionable insights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3a1d5ee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected Features:  Index(['Avg. Session Length', 'Time on App', 'Length of Membership'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "rfe = RFE(reg_model, n_features_to_select=3)\n",
    "rfe.fit(X, y)\n",
    "selected_features = X.columns[rfe.support_]\n",
    "print(\"Selected Features: \", selected_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7fcbd68d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train score\n",
      "0.9853755659819254 \n",
      "\n",
      "Test score\n",
      "0.9808648979354866\n"
     ]
    }
   ],
   "source": [
    "X_train_selected = X_train[['Avg. Session Length', 'Time on App', 'Length of Membership']]\n",
    "X_test_selected = X_test[['Avg. Session Length', 'Time on App', 'Length of Membership']]\n",
    "pipe = make_pipeline(StandardScaler(), LinearRegression())\n",
    "pipe.fit(X_train_selected, y_train)\n",
    "\n",
    "# Predict and display model score on training data\n",
    "train_pred = pipe.predict(X_train_selected)\n",
    "print(\"Train score\")\n",
    "print(r2_score(y_train, train_pred), \"\\n\")\n",
    "\n",
    "# Predict and display model score on test data\n",
    "test_pred = pipe.predict(X_test_selected)\n",
    "print(\"Test score\")\n",
    "print(r2_score(y_test, test_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2379d974",
   "metadata": {},
   "source": [
    "## <a id='toc1_4_'></a>[OLS Model](#toc0_)\n",
    "\n",
    "Ordinary Least Squares (OLS) is the cornerstone of linear regression, optimizing parameters by minimizing residual variances. It's the springboard for advanced modeling, setting the stage for regression work. Transitioning from LinearRegression() and RFE to OLS, we adopt the statistical rigor of backward elimination, sharpening our insights and model precision.\n",
    "\n",
    "Backward elimination is a discerning feature selection technique in linear regression, adept at isolating significant predictors by progressively stripping away the least impactful ones. It operates through a cycle of fitting, assessing, and refining:\n",
    "\n",
    "1. **Start with Full Model**: Begin with a model that includes all potential predictors.\n",
    "\n",
    "2. **Fit the Model**: Fit the linear regression model to the data.\n",
    "\n",
    "3. **Evaluate Significance**: Assess the significance of the predictors, often using p-values from statistical tests like the t-test for each coefficient.\n",
    "\n",
    "4. **Remove the Least Significant**: Identify the predictor with the highest p-value that is above a pre-defined significance level (commonly set at 0.05). If no coefficient has a p-value above this threshold, the process stops.\n",
    "\n",
    "5. **Refit the Model**: Remove the identified least significant predictor from the model and refit the regression with the remaining variables.\n",
    "\n",
    "6. **Iterate**: Repeat the evaluation and removal steps until all remaining predictors have a p-value below the significance threshold.\n",
    "\n",
    "This strategy mitigates overfitting, bolsters interpretability, and augments data generalization. It's especially potent when sifting through a multitude of predictors to unearth those truly instrumental to the model.\n",
    "\n",
    "In applying backward elimination judiciously, alongside a critical review of p-values, coefficient magnitudes, and the F-statistic, combined with VIF scrutiny, we wield enhanced control in finessing our model. Such detail-oriented analysis fortifies our grasp on the model's mechanics, culminating in a robust, reliable tool for prediction.\n",
    "\n",
    "**Note**: The OLS framework flags multicollinearity, which VIF analysis further elucidates. A VIF above 10 is widely accepted as indicating strong collinearity, prompting deeper investigation into affected variables."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26f10e41",
   "metadata": {},
   "source": [
    "### <a id='toc1_4_1_'></a>[Libraries and Helper Functions](#toc0_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "491dfc84",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Libraries\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "\n",
    "# VIF Function\n",
    "def calculate_vif(X):\n",
    "    \"\"\"Calculate VIF for each feature in a DataFrame\"\"\"\n",
    "    return pd.DataFrame(\n",
    "        {'feature': X.columns,\n",
    "             'VIF': [variance_inflation_factor(X.values, i) for i in range(X.shape[1])]\n",
    "        }).sort_values(by='VIF', ascending=False)\n",
    "\n",
    "import statsmodels.api as sm\n",
    "\n",
    "def train_ols_model(input_data, target_variable):\n",
    "    \"\"\"\n",
    "    Perform Ordinary Least Squares (OLS) regression and return the fitted model object.\n",
    "    \"\"\"\n",
    "    # Adding a constant term to the independent variables\n",
    "    X = sm.add_constant(input_data)\n",
    "\n",
    "    # Fitting the OLS model\n",
    "    model = sm.OLS(target_variable, X)\n",
    "    ols_model = model.fit()\n",
    "\n",
    "    # Returning the model\n",
    "    return ols_model\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29ca2adb",
   "metadata": {},
   "source": [
    "### <a id='toc1_4_2_'></a>[Training the OLS Regression Model: A Step-by-Step Guide](#toc0_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e04a754",
   "metadata": {},
   "source": [
    "#### <a id='toc1_4_2_1_'></a>[Incorporate Intercept](#toc0_)\n",
    "Add a constant to include an intercept in the model, which allows for the possibility that the response variable could have a non-zero value when the predictor variables are zero.\n",
    "In simple terms: we include the intercept in the model.\n",
    "\n",
    "$$\\bf{X} = \t\\begin{bmatrix} \n",
    "\t1 & x_1^{1} & x_2^{1}& \\ldots &x_n^{1} \\\\\n",
    "\t1 & x_1^{2} & x_2^{2}& \\ldots &x_n^{2}\\\\\n",
    "\t\\vdots & \\vdots & \\vdots & \\ddots & \\vdots\\\\\n",
    "\t1 & x_1^{m}& x_2^{m}& \\ldots &x_n^{m}\n",
    "\\end{bmatrix}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "922cd2f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_ols = sm.add_constant(X_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f87a6619",
   "metadata": {},
   "source": [
    "#### <a id='toc1_4_2_2_'></a>[Model Instantiation and Fitting](#toc0_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "0c46373a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an OLS model instance with the target variable y_train and predictor matrix X_train_ols\n",
    "model = sm.OLS(y_train, X_train_ols)\n",
    "\n",
    "# Fit the model to the training data and store the results for further analysis\n",
    "ols_model = model.fit()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7356aed2",
   "metadata": {},
   "source": [
    "#### <a id='toc1_4_2_3_'></a>[Iteration 1](#toc0_)\n",
    "The **high p-value** for Time on Website suggests that within the context of this model, Time on Website does not make a statistically significant contribution to predicting Yearly Amount Spent. Additionally, its **coefficient is significantly lower** than those of other variables, indicating a minimal impact on the predictions. Calculations of the Variance Inflation Factor (VIF) confirm **high multicollinearity**, implying that any information Time on Website might carry is likely redundant, given the other features in the model. Coupled with our understanding that Time on App correlates with spending—not Time on Website—we can confidently **exclude** `Time on Website` from our model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bb45c560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>    <td>Yearly Amount Spent</td> <th>  R-squared:         </th> <td>   0.985</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                    <td>OLS</td>         <th>  Adj. R-squared:    </th> <td>   0.985</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>              <td>Least Squares</td>    <th>  F-statistic:       </th> <td>   5825.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>              <td>Sat, 17 Feb 2024</td>   <th>  Prob (F-statistic):</th> <td>3.46e-315</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                  <td>16:38:19</td>       <th>  Log-Likelihood:    </th> <td> -1296.2</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>       <td>   350</td>        <th>  AIC:               </th> <td>   2602.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>           <td>   345</td>        <th>  BIC:               </th> <td>   2622.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>               <td>     4</td>        <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>       <td>nonrobust</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "            <td></td>              <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>                <td>-1050.6537</td> <td>   26.458</td> <td>  -39.710</td> <td> 0.000</td> <td>-1102.694</td> <td> -998.614</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Avg. Session Length</th>  <td>   25.7243</td> <td>    0.534</td> <td>   48.137</td> <td> 0.000</td> <td>   24.673</td> <td>   26.775</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time on App</th>          <td>   38.5971</td> <td>    0.528</td> <td>   73.045</td> <td> 0.000</td> <td>   37.558</td> <td>   39.636</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time on Website</th>      <td>    0.4591</td> <td>    0.520</td> <td>    0.884</td> <td> 0.377</td> <td>   -0.563</td> <td>    1.481</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Length of Membership</th> <td>   61.6747</td> <td>    0.516</td> <td>  119.540</td> <td> 0.000</td> <td>   60.660</td> <td>   62.690</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 1.523</td> <th>  Durbin-Watson:     </th> <td>   2.024</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.467</td> <th>  Jarque-Bera (JB):  </th> <td>   1.262</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td>-0.108</td> <th>  Prob(JB):          </th> <td>   0.532</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 3.199</td> <th>  Cond. No.          </th> <td>2.56e+03</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 2.56e+03. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}       & Yearly Amount Spent & \\textbf{  R-squared:         } &     0.985   \\\\\n",
       "\\textbf{Model:}               &         OLS         & \\textbf{  Adj. R-squared:    } &     0.985   \\\\\n",
       "\\textbf{Method:}              &    Least Squares    & \\textbf{  F-statistic:       } &     5825.   \\\\\n",
       "\\textbf{Date:}                &   Sat, 17 Feb 2024  & \\textbf{  Prob (F-statistic):} & 3.46e-315   \\\\\n",
       "\\textbf{Time:}                &       16:38:19      & \\textbf{  Log-Likelihood:    } &   -1296.2   \\\\\n",
       "\\textbf{No. Observations:}    &           350       & \\textbf{  AIC:               } &     2602.   \\\\\n",
       "\\textbf{Df Residuals:}        &           345       & \\textbf{  BIC:               } &     2622.   \\\\\n",
       "\\textbf{Df Model:}            &             4       & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}     &      nonrobust      & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                              & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{const}                &   -1050.6537  &       26.458     &   -39.710  &         0.000        &    -1102.694    &     -998.614     \\\\\n",
       "\\textbf{Avg. Session Length}  &      25.7243  &        0.534     &    48.137  &         0.000        &       24.673    &       26.775     \\\\\n",
       "\\textbf{Time on App}          &      38.5971  &        0.528     &    73.045  &         0.000        &       37.558    &       39.636     \\\\\n",
       "\\textbf{Time on Website}      &       0.4591  &        0.520     &     0.884  &         0.377        &       -0.563    &        1.481     \\\\\n",
       "\\textbf{Length of Membership} &      61.6747  &        0.516     &   119.540  &         0.000        &       60.660    &       62.690     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Omnibus:}       &  1.523 & \\textbf{  Durbin-Watson:     } &    2.024  \\\\\n",
       "\\textbf{Prob(Omnibus):} &  0.467 & \\textbf{  Jarque-Bera (JB):  } &    1.262  \\\\\n",
       "\\textbf{Skew:}          & -0.108 & \\textbf{  Prob(JB):          } &    0.532  \\\\\n",
       "\\textbf{Kurtosis:}      &  3.199 & \\textbf{  Cond. No.          } & 2.56e+03  \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{OLS Regression Results}\n",
       "\\end{center}\n",
       "\n",
       "Notes: \\newline\n",
       " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. \\newline\n",
       " [2] The condition number is large, 2.56e+03. This might indicate that there are \\newline\n",
       " strong multicollinearity or other numerical problems."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                             OLS Regression Results                            \n",
       "===============================================================================\n",
       "Dep. Variable:     Yearly Amount Spent   R-squared:                       0.985\n",
       "Model:                             OLS   Adj. R-squared:                  0.985\n",
       "Method:                  Least Squares   F-statistic:                     5825.\n",
       "Date:                 Sat, 17 Feb 2024   Prob (F-statistic):          3.46e-315\n",
       "Time:                         16:38:19   Log-Likelihood:                -1296.2\n",
       "No. Observations:                  350   AIC:                             2602.\n",
       "Df Residuals:                      345   BIC:                             2622.\n",
       "Df Model:                            4                                         \n",
       "Covariance Type:             nonrobust                                         \n",
       "========================================================================================\n",
       "                           coef    std err          t      P>|t|      [0.025      0.975]\n",
       "----------------------------------------------------------------------------------------\n",
       "const                -1050.6537     26.458    -39.710      0.000   -1102.694    -998.614\n",
       "Avg. Session Length     25.7243      0.534     48.137      0.000      24.673      26.775\n",
       "Time on App             38.5971      0.528     73.045      0.000      37.558      39.636\n",
       "Time on Website          0.4591      0.520      0.884      0.377      -0.563       1.481\n",
       "Length of Membership    61.6747      0.516    119.540      0.000      60.660      62.690\n",
       "==============================================================================\n",
       "Omnibus:                        1.523   Durbin-Watson:                   2.024\n",
       "Prob(Omnibus):                  0.467   Jarque-Bera (JB):                1.262\n",
       "Skew:                          -0.108   Prob(JB):                        0.532\n",
       "Kurtosis:                       3.199   Cond. No.                     2.56e+03\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 2.56e+03. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ols_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "44aad5e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>VIF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Time on Website</td>\n",
       "      <td>665.881815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avg. Session Length</td>\n",
       "      <td>637.177909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Time on App</td>\n",
       "      <td>140.765223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Length of Membership</td>\n",
       "      <td>13.131268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                feature         VIF\n",
       "2       Time on Website  665.881815\n",
       "0   Avg. Session Length  637.177909\n",
       "1           Time on App  140.765223\n",
       "3  Length of Membership   13.131268"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calculate_vif(X_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "221085a8",
   "metadata": {},
   "source": [
    "#### <a id='toc1_4_2_4_'></a>[Iteration 2](#toc0_)\n",
    "\n",
    "Removing `Time on Website`, our model maintains a $R^2$ score on training data of 98.5%, suggesting that this feature's exclusion hasn't detracted from our ability to account for `Yearly Amount Spent`. The significant increase in the F-statistic to 7771 indicates a stronger collective impact of the remaining features on the prediction. The F-statistic itself is a measure of the ratio of explained variance to unexplained variance, and a higher value typically means that the model explains a substantial portion of the variance in the dependent variable.\n",
    "\n",
    "$$ F = \\frac{\\text{Explained Variance per degree of freedom}}{\\text{Unexplained Variance per degree of freedom}} $$\n",
    "\n",
    "Hints of multicollinearity between `Avg. Session Length` and `Time on App` remain, but the statistical significance of all predictors suggests that each contributes uniquely to the model. A [Durbin-Watson](https://www.statology.org/durbin-watson-test/) statistic close to 2 signals an absence of autocorrelation in the residuals, and a consistent condition number suggests that any multicollinearity present doesn't unduly influence the model's estimates.\n",
    "\n",
    "In essence, our refined model captures the nuances of `Yearly Amount Spent` with fewer variables, striking a balance between simplicity and predictive power. Although multicollinearity is present, it doesn't overshadow the model's accuracy, warranting only a watchful approach to model assessment rather than immediate concern."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d2be397d",
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>    <td>Yearly Amount Spent</td> <th>  R-squared:         </th> <td>   0.985</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                    <td>OLS</td>         <th>  Adj. R-squared:    </th> <td>   0.985</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>              <td>Least Squares</td>    <th>  F-statistic:       </th> <td>   7771.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>              <td>Sat, 17 Feb 2024</td>   <th>  Prob (F-statistic):</th> <td>5.34e-317</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                  <td>16:38:19</td>       <th>  Log-Likelihood:    </th> <td> -1296.6</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>       <td>   350</td>        <th>  AIC:               </th> <td>   2601.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>           <td>   346</td>        <th>  BIC:               </th> <td>   2617.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>               <td>     3</td>        <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>       <td>nonrobust</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "            <td></td>              <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>                <td>-1034.1768</td> <td>   18.768</td> <td>  -55.104</td> <td> 0.000</td> <td>-1071.090</td> <td> -997.264</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Avg. Session Length</th>  <td>   25.7304</td> <td>    0.534</td> <td>   48.168</td> <td> 0.000</td> <td>   24.680</td> <td>   26.781</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time on App</th>          <td>   38.6275</td> <td>    0.527</td> <td>   73.281</td> <td> 0.000</td> <td>   37.591</td> <td>   39.664</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Length of Membership</th> <td>   61.6577</td> <td>    0.515</td> <td>  119.628</td> <td> 0.000</td> <td>   60.644</td> <td>   62.671</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 1.489</td> <th>  Durbin-Watson:     </th> <td>   2.010</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.475</td> <th>  Jarque-Bera (JB):  </th> <td>   1.230</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td>-0.113</td> <th>  Prob(JB):          </th> <td>   0.541</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 3.183</td> <th>  Cond. No.          </th> <td>1.26e+03</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 1.26e+03. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}       & Yearly Amount Spent & \\textbf{  R-squared:         } &     0.985   \\\\\n",
       "\\textbf{Model:}               &         OLS         & \\textbf{  Adj. R-squared:    } &     0.985   \\\\\n",
       "\\textbf{Method:}              &    Least Squares    & \\textbf{  F-statistic:       } &     7771.   \\\\\n",
       "\\textbf{Date:}                &   Sat, 17 Feb 2024  & \\textbf{  Prob (F-statistic):} & 5.34e-317   \\\\\n",
       "\\textbf{Time:}                &       16:38:19      & \\textbf{  Log-Likelihood:    } &   -1296.6   \\\\\n",
       "\\textbf{No. Observations:}    &           350       & \\textbf{  AIC:               } &     2601.   \\\\\n",
       "\\textbf{Df Residuals:}        &           346       & \\textbf{  BIC:               } &     2617.   \\\\\n",
       "\\textbf{Df Model:}            &             3       & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}     &      nonrobust      & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                              & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{const}                &   -1034.1768  &       18.768     &   -55.104  &         0.000        &    -1071.090    &     -997.264     \\\\\n",
       "\\textbf{Avg. Session Length}  &      25.7304  &        0.534     &    48.168  &         0.000        &       24.680    &       26.781     \\\\\n",
       "\\textbf{Time on App}          &      38.6275  &        0.527     &    73.281  &         0.000        &       37.591    &       39.664     \\\\\n",
       "\\textbf{Length of Membership} &      61.6577  &        0.515     &   119.628  &         0.000        &       60.644    &       62.671     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Omnibus:}       &  1.489 & \\textbf{  Durbin-Watson:     } &    2.010  \\\\\n",
       "\\textbf{Prob(Omnibus):} &  0.475 & \\textbf{  Jarque-Bera (JB):  } &    1.230  \\\\\n",
       "\\textbf{Skew:}          & -0.113 & \\textbf{  Prob(JB):          } &    0.541  \\\\\n",
       "\\textbf{Kurtosis:}      &  3.183 & \\textbf{  Cond. No.          } & 1.26e+03  \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{OLS Regression Results}\n",
       "\\end{center}\n",
       "\n",
       "Notes: \\newline\n",
       " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. \\newline\n",
       " [2] The condition number is large, 1.26e+03. This might indicate that there are \\newline\n",
       " strong multicollinearity or other numerical problems."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                             OLS Regression Results                            \n",
       "===============================================================================\n",
       "Dep. Variable:     Yearly Amount Spent   R-squared:                       0.985\n",
       "Model:                             OLS   Adj. R-squared:                  0.985\n",
       "Method:                  Least Squares   F-statistic:                     7771.\n",
       "Date:                 Sat, 17 Feb 2024   Prob (F-statistic):          5.34e-317\n",
       "Time:                         16:38:19   Log-Likelihood:                -1296.6\n",
       "No. Observations:                  350   AIC:                             2601.\n",
       "Df Residuals:                      346   BIC:                             2617.\n",
       "Df Model:                            3                                         \n",
       "Covariance Type:             nonrobust                                         \n",
       "========================================================================================\n",
       "                           coef    std err          t      P>|t|      [0.025      0.975]\n",
       "----------------------------------------------------------------------------------------\n",
       "const                -1034.1768     18.768    -55.104      0.000   -1071.090    -997.264\n",
       "Avg. Session Length     25.7304      0.534     48.168      0.000      24.680      26.781\n",
       "Time on App             38.6275      0.527     73.281      0.000      37.591      39.664\n",
       "Length of Membership    61.6577      0.515    119.628      0.000      60.644      62.671\n",
       "==============================================================================\n",
       "Omnibus:                        1.489   Durbin-Watson:                   2.010\n",
       "Prob(Omnibus):                  0.475   Jarque-Bera (JB):                1.230\n",
       "Skew:                          -0.113   Prob(JB):                        0.541\n",
       "Kurtosis:                       3.183   Cond. No.                     1.26e+03\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 1.26e+03. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_ols = X_train[[\"Avg. Session Length\", \"Time on App\", \"Length of Membership\"]]\n",
    "ols_model = train_ols_model(X_train_ols, y_train)\n",
    "ols_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9024f7e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>VIF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>Avg. Session Length</td>\n",
       "      <td>136.157428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Time on App</td>\n",
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       "    </tr>\n",
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       "      <th>2</th>\n",
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       "                feature         VIF\n",
       "0   Avg. Session Length  136.157428\n",
       "1           Time on App  129.311928\n",
       "2  Length of Membership   13.130358"
      ]
     },
     "execution_count": 27,
     "metadata": {},
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   ],
   "source": [
    "# Call the function and sort the results\n",
    "calculate_vif(X_train_ols)  # X_train_ols.drop(columns=['const']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73882efd",
   "metadata": {},
   "source": [
    "### <a id='toc1_4_3_'></a>[Model Evaluation](#toc0_)\n",
    "Our analysis culminates with the model's performance on unseen test data, yielding a commendable 98% score. Our final model is equivalent to the one arrived at by using the LinnearRegression and RFE models, however, this approach gives a more nuanced understanding and control over the decision making process. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "412c8d78",
   "metadata": {},
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       "0.9808648979354864"
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     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "X_test_ols = X_test[[\"Avg. Session Length\", \"Time on App\", \"Length of Membership\"]]\n",
    "X_test_ols = sm.add_constant(X_test_ols)\n",
    "r2_score(y_test, ols_model.predict(X_test_ols))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54e1bb26",
   "metadata": {},
   "source": [
    "## <a id='toc1_5_'></a>[Conclusion](#toc0_)\n",
    "The objective of this notebook was to demonstrate an analytical approach for enhancing the understanding of model performance and refining feature selection. We leveraged both automated algorithms and informed decision-making strategies on a foundational dataset, emphasizing the value of meticulous analysis. This rigorous approach, combined with keen attention to detail, proves invaluable, especially when applied to more complex challenges. Although outcomes as ideal as those presented here are not always guaranteed, this primer serves as an exemplar for what aspiring data scientists should strive toward—showcasing the synergy between algorithmic efficiency and analytical depth in pursuit of predictive accuracy and interpretability.\n",
    "\n",
    "**Questions?**\n",
    "\n",
    "Feel free to ask any questions or provide feedback.\n",
    "\n",
    "<div style=\"text-align: left;\">\n",
    "<a href=\"https://freeimage.host/i/HXsIQUv\"><img src=\"https://iili.io/HXsIQUv.md.jpg\" alt=\"HXsIQUv.md.jpg\" border=\"0\" width=\"450\"></a>\n",
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