{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "80cb0e6e",
   "metadata": {},
   "source": [
    "# Regression Line\n",
    "The correlation coefficient $r$ doesn't just measure how clustered the points in a scatter plot are about a straight line. It also helps identify the straight line about which the points are clustered. In this section we will retrace the path that [Galton and Pearson](https://ise.ncsu.edu/fuzzy-neural/wp-content/uploads/sites/9/2025/01/Galton-Pearson-and-the-Peas-A-Brief-History-of-Linear-Regression-for-Statistics-Instructors.pdf) took to discover that line.\n",
    "\n",
    "As we have seen, our dataset on the heights of parents and their adult children indicates a linear association between the two variables. The linearity was confirmed when our predictions of the children's heights based on the midparent heights roughly followed a straight line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3a506012",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.279445Z",
     "iopub.status.busy": "2026-08-31T06:02:06.279229Z",
     "iopub.status.idle": "2026-08-31T06:02:06.651962Z",
     "shell.execute_reply": "2026-08-31T06:02:06.651687Z"
    },
    "tags": [
     "hide-input",
     "thebe-init",
     "runnable"
    ]
   },
   "outputs": [],
   "source": [
    "path_data = '../../data/'\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3ec55fa",
   "metadata": {},
   "source": [
    "```{contents}\n",
    ":local:\n",
    ":depth: 2\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9a86bcd",
   "metadata": {},
   "source": [
    "<!-- moved-from-landing: 1200-regression -->\n",
    "\n",
    "## Prediction and Regression Prelude\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "41bc755a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.653405Z",
     "iopub.status.busy": "2026-08-31T06:02:06.653311Z",
     "iopub.status.idle": "2026-08-31T06:02:06.659204Z",
     "shell.execute_reply": "2026-08-31T06:02:06.658992Z"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [],
   "source": [
    "path_data = '../../data/'\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')\n",
    "import matplotlib\n",
    "matplotlib.use('Agg')\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2831d725",
   "metadata": {},
   "source": [
    "Here is a historical dataset used for the prediction of the heights of adults based on the heights of their parents. We have studied this dataset in an earlier section. The table `heights` contains data on the midparent height and child's height (all in inches) for a population of 934 adult \"children\". Recall that the midparent height is an average of the heights of the two parents.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0e2915e7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.660252Z",
     "iopub.status.busy": "2026-08-31T06:02:06.660189Z",
     "iopub.status.idle": "2026-08-31T06:02:06.666187Z",
     "shell.execute_reply": "2026-08-31T06:02:06.665969Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "### data on heights of parents and their adult children\n",
    "\n",
    "original = pd.read_csv(path_data + 'family_heights.csv')\n",
    "heights = pd.DataFrame({\n",
    "    'MidParent': original['midparentHeight'],\n",
    "    'Child': original['childHeight']\n",
    "})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ff92cceb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.667221Z",
     "iopub.status.busy": "2026-08-31T06:02:06.667161Z",
     "iopub.status.idle": "2026-08-31T06:02:06.670960Z",
     "shell.execute_reply": "2026-08-31T06:02:06.670749Z"
    },
    "tags": []
   },
   "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>MidParent</th>\n",
       "      <th>Child</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75.43</td>\n",
       "      <td>73.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>73.66</td>\n",
       "      <td>73.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>66.64</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>66.64</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>66.64</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>65.27</td>\n",
       "      <td>66.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>65.27</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent  Child\n",
       "0        75.43   73.2\n",
       "1        75.43   69.2\n",
       "2        75.43   69.0\n",
       "3        75.43   69.0\n",
       "4        73.66   73.5\n",
       "..         ...    ...\n",
       "929      66.64   64.0\n",
       "930      66.64   62.0\n",
       "931      66.64   61.0\n",
       "932      65.27   66.5\n",
       "933      65.27   57.0\n",
       "\n",
       "[934 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "251777f0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.671916Z",
     "iopub.status.busy": "2026-08-31T06:02:06.671865Z",
     "iopub.status.idle": "2026-08-31T06:02:06.711156Z",
     "shell.execute_reply": "2026-08-31T06:02:06.710944Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='MidParent', ylabel='Child'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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MndYtEKkzIKpXmqDAuY0NG1u1j56jcrPRLT+nHV5legW7DWtrUuckff3YcI1nRZ3F9x7OUZHQ5P0H7Ge/84br1mtxe+/npJznIa3XPMgZL61uddzNAYQJnFvX0PqYM9+g/ILqrQkK+xTnWrHh+rLBBtIWDv2RRAjaxtumMf+sbHHOg/jNGSURqNa2eZesyyf5hT0qUjBB23jbpKbK0hZz626w91+Xt7JDPzUiDlwSW4AUsrV70th0DZD8wR4VKQg3tZhzHY4tT/U22IKb9Kxv91X/d/as8G9TkyjZexJbgLht7V6u7U7yDR0VKQg3tViUrd6zsDVrW/yUhGOrO6p1VklsUW5LfW2xg+QXqv4sw2bljR9B23gnpaaK2z5m+YXYkuTW4X7KwrjluLWPLdud26Coy+vvq9zbhnNUJBHS2so9ifmRuLYkvX28n8IuKcdi09xQ1k6K5JfsH7MIycH8SB63j+fcECkV6KhIUcnihm7ekM35kT16+Q8g+AVjdUaw8FvomtR7LBD2C2Ab5HhQ9716d5DqquY28Fq46xb+ycu+oONmvmEo1Hl62RomyG+SdpDiwqE/UjSSHiqLO9SF1+GPLJW/L66XflOWypGD/CX0wG24DO8RP0+nCSq7kPc6iC04yrBXpzFt8hrSQ9oXl2xsiffnxAwuqwPrhmmHoOHEsN97ocOSXrY67Tbteff4HonbQYoPHRUpCm5DZcWe0Hcb6kIvQtlSt1WqPbNm62fO8yCvr6ioaJOHTrNiY/NN0E0IETaYbdD7t2qa5f4avNdP/DoNWhJJ3GzR9qAuOh9nOpQHGbwG6T5fv6mVTU1NTVJT1+TaDs72ifq9B+UT5bs2vzPn9+cW5DdJO0g6cOiPFIWwQ2VpyKBRNiTfAP9CAu4loYe83i2PKIFhg4LZBr0fV90s99fgvTOALdrUT+6NY6iLXjbgFoxXtwlAmn5d27eyyS0obVA7hP3eC5Wse31nzu/PLchvknaQdKA83TJslojGIemeVJj28ZKiwxZ9w49ynleaoDzc6u8X/NYp8UdvAP/3Ck7rZouzfYKWDehtRMyYhUm0Q9jvvdAejJetXt+D1/XDnpRYfe/h0B8pKlms39E3HOfcQ5RAql43rSgy/KA5KT9bwQUzal3nTszeTdi28CIo+G3cdgj7vRfqHLxsdevpFdMOUlw49EcSIaxqKi11lZc0u1jlB819tJqDWl7XRqHm3KSwEGn52vpo6jw/RVxU1WaQqjHKuUmeE/d7L/b1SrVhONijIgUTVjWVprrKDACr5x6KVb6byg3labECXvUcFLaGhyADgWd1WmzFsba+qc1cktP+MAz64yqpb+wsHWeuksMGVAWq8/y2lI+q2gzTgwx7brGuu/sO7BIq77g2RYFqw/DQUZGCCKuaykJdhR9/WLVaXLxUbphf0s/KeMX7343vIYMeXqbe67SwQQf1hbN44OCervaHQa27Un6nQr1CLbiizl+dp0G7mPNKUVWbQapHv3rE+W7iX3fbhGnKol+vVBuW4NDfww8/LNttt53v37HHHtvqnHXr1snll18uI0eOlOrqahk1apRMnjxZ1q9fn1k9SpGwqqms1FVh1Wpx8VK5QZyglXt6q3q3tGHUhGFBGc3FN6lXqAWD1HkapDMdUVTVZpDq0a8ecb6bYl93xb5eqTYsQdXfnDlzZOrUqa6fPfnkk/Lhhx/KL3/5S7nwwgvVsS+//FKOPPJIee+99+SQQw6R0aNHqzxeeOEFGTNmjEybNs06VUselDd+hH0iLPTJMarqL+nyvfDqcbhtVR9nm/ko7fP+vEUycsetqj+/ttBzJF6OKKpq0y/QbhBubRW1vKB0UX9fxe7p2NSTqrP43pOLoT84Gvw5qa+vl3vuuUfat28vp5xySsvx2267TTmpiy66SK688sqW4/j/rbfeKnfeeadccsklqdlfDkR5Ui0mQeP+xSrf62buduONs818FLp3DM437PxIVNVm3B5h3Cgmxb7uin292uKkbCcXQ39eoJe1evVq+cY3vqGG9wBW0z/44IPStWtXufTSS1ulx3scnzJlSkYWk2LCIKz5bKc8Bvwl6ZJrR6Udzumnn95ybN68ebJs2TLZd999pUuX1gofvMfxzz77TBYvXpy6vXkkzE2skIjkSeYHgsb9/QK9uknMTVv9AsSa6Zzv/QKnesm58QpbF65raCOtD2q3hkb/oLNe8yNJSvi92svN5mJEMbHV2WX9UJBXcjH058bChQvl5Zdflh122EEOO+ywVo4KDBs2zPU8HH/++edVugEDBviO12YBhjPN1yw5Y/o6eXvVJhnTq7088PVusdO4Mfrx1bKyrkl6V1XInBN6hs7Pq33M8946ZruW+Yi20u3m/x+5Q4eW/HHus0salBqveos9Zn54Rcw73D6PcJxn2uqsE96b5wGdHrywrEG9HrJ9c546P4DzTGAXqK1vkk2N4tluGFFoaqySMZ/Wyuw1jS354N6/8Htbh/gg04YCTreTWTaI+n2aOOsd5tpBsFgzekQheF1bWf++4v5W0iLNtok6B5ZbRwUlYGNjo5qbateuXSu1H+jevbvred26dWuVzoulS5fK5s2tn0TTZPny5ZIleCqfWVMlKxsq1WLU+QsWSYfK6Gnc+GqTyIq6ztIkFUo+/fGni2Sb9tHyM9vHed7ixWvbnIdFsFhfBOk2eHNL/ur/n1dJ820VdjUqMYLOD+lWN+CcCjU0ZZ5nlolzzDq98+9FUlPXueW8N5ZvlMoKkVUNlfJWzUZpaoQ9zWXiPdpA51ehXGbr3iDyRN7NYnfvdsO5qMvMmgZZvbnZblDf2KRsNOev3Nqv+fyKSN+n87s16/1mxGtnTbTiQl9bWf++4v5WsmB5kdsG92uvjkRJOSo4KDgqREn+wQ9+UJQy+vfvL1mApxlcKH379pWOHd23k0iLsQv0E2AnGTa4T+w0bvSZrZ96K2XE0IGh8/Nqn6DzUAIWweoe1T7VW9Pts2Brj6pPVaVSzI1dsjU/s0eF8wYM6N0c9NUoc+SOfaTPnK112mvngVL9/taexb59O6mydHqzRzWuupOMGNpHxi7SvZqKNj0q2AVq62VLj8q93ZqaRJoaG2VM7w6OHlWFqpcX+nzt2KJ+nybVs7fW22xnrzILKSvKtZX176tY9S3Fe09JOKqXXnpJzTEddNBBMmTIENce09q1a13P1T0pnc6LrOWZuFCytuHRI/zlzWHTuDH3lP6u0uew+TnbJ8x5NRN2UPM1ev2S81w9X+KWn16ciygS456qVXM7jx5R3SqNs06I5I0tRcb06SCPHtY7MAitWaaeMzv75dXyQe0mVR4WA+Mzv3ZrbGh+WseNEO3jFnTWDWfZhajRdDv4BQB2a+Ok8Lq2sv59Fau+pXjvKQlH5Sai0Oy4447qdf78+a7n6uM6HfEnicCnXvhtARGHMOd53bDdbqrme9gaJpqArpNOW4NhwJXNgghnGW72mguUkReclC7PWYbbuXUN0mpIKYowIUqw2yDSCkpbaPlpY7uTshU7v00fIEfHgt0ePXrI0Ucf3eZzOKDtt99e3njjDbXw1wTvcXzw4MG+QgqSHW5KuCjnFhunWs5LXZZE5AG9lbxXHjYqyGy0yWbYXiXqqB599FE1lnrSSSdJp07NY/0mmLc67bTTVKikG2+8sdVneI/jEyZMSNFiEhYsQh340FL1h/9HPReBXqOeFzV/8N53+7VscY7YfXh1A2l02rhlojcGZ+XMo9j1jYONNtkM26uEh/4eeughz2E/DUIpodeFKBQInbTHHnvIu+++2xJC6fzzz0/RYhKGoK3TbQogGiVoa1w7zDLNoUM3e2yY97DRJpthe5Vwj2rWrFnywQcfyN577y277767Zzos7EXUCjikuXPnyu23365eL7jgAnniiSekc2fIZ4lNBG2dblsA0WIsUg0qM8xnWWGjTTbD9ipSUNqePVsvnIsDhuVWrWI3N6+BIdPAqYRz4rbVutnTSEK15mebM98w218UEqw3aoDdNK8ft/ILafs0ehW2/b5s6knVxWybNOoQeugPK94LJYk8SGkT5YJ3BlbFucXcjM7NNj8nlcSGkkHbY2SFl81xbSrXTQRtcVJxSet7C+2oMMfjxlNPPaW22MB6pvPOO0922WUXFSC2pqZGPvroI/nd736nYuv94he/cFXpEftI8gnJ2csJuyleUBq3jfmCxv2DeifAK73+f1APSn/uF/jVLMNrg8Ew7eX1GaIzOGMb9uvaPrHvOcz8SlDP2C+/qFuLuJFEHqXeg8rTPFtoRzVo0KA2x2bMmKG2zvj+978vt9xyixra0+y8885y4IEHytlnny0XX3yxclQQMrjlQ0rzCUnn5cQv7zDl/+cHHeXDmbWyYkvUhdqNjWohri7LbdzfL1989vzi5vhyhw6oarONOsD/UQ5C4XhtReHcqgLpTfu8ynDa7Gw3L5vd6oM4dwghhOgM2N5ei1PQEmvO3CFSO3uBuqBOXnOJbu0ZZr5G13nvvy4v6PqLu2VIsSm1XmPHdhWtrvFiOuCCHjngnCBMuOGGG1o5KSfXX3+9SvfrX/+6kOJIjrZ/MPPCTcN89co7TPk49q8vKlWIHv0pnMdby+vUeWDWt/u2uhH45WuqDfHnto06Psf/8bnXVhROFeDn6ze1RDHH65uf13mWYdrs1m5uNrvVB3kidBDi3KF9tJMCSAGbwrZz0PeKvLt3rFDRMpyfO9szTP6oO9oAFHL92bpliG1bqyQB2ta8xovZ1pWFqvDQc3Jbz2SCz5Fu5syZhRRHcqREMvPCk6356pV3mPJxbPdtG1U0cTzRa9XduL5VrbZBD5uvm9rQuY06Psf/zfKcZThVgBhqM9/v06/Ktwydn1u7hVX9IQ9EDEdgWd0+GqTQw3+FfM/muWgXt2gecdWbUbav98ujmGrMuJSiyq9rim1d0Fb0CNwKNeD7778fmHbkyJEqqgSikhO7VUk2z1Hp9unbf4B069K51VxEUN5R5qjc3keZo3J77zcP5jWfFmWOSsf6Q8RwBGPF9YM5qvUNjTKoW4dI7RFEmLZ21jVsnklcf17b2mf9+7J5jqouZtukMR9YUO7oJcHx/PnPf/ZNh8+XLFkiw4cPL6Q4khJJ/pCc8ePC5B0ljfkDCTovSEGnP9cRAzAX41eeG249LbcyzGNuEQrCtJdzDk7ZPH1dq20tLphRK4dPW+ka/aDQHnPQ51EVnLoNCr3+kMf+T9RYGfHBVidVCGn0Wgsq4ayzzlKS80mTJskVV1yhNjM0gXeePHmy/PCHP1RzWGeeeWah9hJSUnMJSZRn5oFtJPS8QV7mRYo1N2pznUmKjgox8773ve9JQ0OD3HnnnbLnnnuqYK/6FaGL7rjjDhWb78QTT2SMPQuw4YcbZEOhN6pCztdzCZjjSSsQbFB5QWWa8x/YPVZHT9fH+3RynyvS+TqFGkEklSaJ+RtnOUnmVaq/v7KM9XfXXXfJAQccoOLqffrppypCuRm1HOurIE/3i81HykceG2RDITZGlUX74aZiTbr9TBm6V3lh66MVg5ijWrRo615sOB/qO52PW9nAlOEXunwgTjtp+wtZ8F2MvErt91fWQWnhhPD3ySefqJh6iFDetWtXNSe10047JVEEKYEgmGEW5Ma10ZRFg7h19LIh6fYz80MHCGY7y4taH70flSko0OfjVQsMvMrGMD5k7X6LeMMs9I3bTlF7P37lJJlXqfz+8kyi0dPhlOiY7MRcVJmVPDbIhkJs1LJo3XMoZA8oNxuSbj/nIlenzUnUB04JEnE4KbxqFZxX2cCvfmHaIK3rLMly0rDZht9fnilInk6Sp9jyWRue5AqRkQe1TxxZdFgbksrbrRyvOkct0619vKTabmUXunwgSpokiFqO3/WThs02/P68yFq6n0iPChVIAjQCyQ4bfiSFyMgLzTtuPsWaXwiSoSdRHzcn5VV20ssH8riUotR/f3kktKOCgq9QuM1H/Kcsv0V1cedikvzRhF30Z/YQotqAMvQFi3OrPHoLfr0T5OF14w4zvzCzpj5yHczFwl7ri7wW/KJ+aFe3c7x6SpqF6xrUQl+ETgoTlNZ8b2tQVyd+33UcxZ9bL7oYPWgSDW7zkTFhntT9gmzGedJPuncQNgioqWLbbkt8n7A26DIQImjXbRCUdo2sqFutYtghq+UTdvCtG45PW9hctpk+yvzCMwvrpKauUQY+tLTF/qA6aHsQtBNzRTjryEGtFXxOm/X7mg2NLfEMj3Kc0/f3S1rmntzq0u+R1g+EQUFpzfd4tTGoqxO/7zrK9e2lriyWypOqvyI6qjVr1sTInhS6ONFvy/M4SqKk1Udht2R3qtj0OWFsaFVGXZNs2lwpqxu2tpVWtKFcL8UegsI600fpWf1ufA8Z+PCylvO91HrOOpuBZwH+p3tlbmpCZ7BazVvGOV5qPs2yr9rar4PSomflVyaC+67a2Dr4ro09q6TUmV7qSv3/Yqg8qfqLjn1XYBkRZnGiX+DHOIsbC1kQWUhgSmew0qAAtZ5lVFXIqC1BafVZWtHmVTe8IiisxlTAhV2ICRuqt9iA86MG2dUdMLyMrW6rJjSD0+r3Zo7jjHO0ms+rLttv09Z+v6C0ZpkI7mtjUFcnft91lOvbeV3qc5L+nSSdX7lB1Z8FmE9XXsobzlFtmaNqrG8VlNZt/sVLSec1RxVlSMbcGNGrDK95Dr85Kmf7xZ2jMq+fmvp2RZmjsqk3EHWOyuv3xTmqElH9keIR5sL1cwJxLvykfyxhn7yjKsycZdTVbT3Xbzt0t89w3K0nFWVIxtyOw1mHoO3ZvdrIy1bgNzwZNHSpI6a7OSmn7c73UWzNkqTUksVUXRYzv3IhtKPC5oigV69eMnHixFbHonDZZZdFPocQJ34OJorzSWohZtw5iDzNXeTJVlKmjgq79EJejq09tKPSx8Iq/pCWjqo0yCoEUxgHE9X5hIkNF7QoNkyZXsOCbueFGVIMIoqzDFNu1HalIyOpO6qTTz5ZOZp+/fq1OUbKiyyGf3SZe/VsJ1cNDXYwUQOT+qUz6wu86u5XplubmbL+977br+U8P+l42PbGvlTvrN4ceI5f3dzKDduutg0RkjJxVL/97W9DHSOlTRbDP2aZb69qkobBWz/zKzsJu1ov9t2oHsz86u7Vk3K2Gf5MWX8YuXrY9sZ+VNiXyi/ArJtdZlBav3LTXgJBiJ3aU2ItacpsTSWW235LaWCWDRlznLq7tZmXrN9POh62TLQP2inoHGdZqJ/eFytMuV6SfkqxSdJQnm4ZNktETYr9lOw2dLR1v6X02ydq4NagPDR+C6TjzFGZ109lh06R5qi82jzsUGaY+mZNXn5fWVBXLvL02tpatReVX6gkBqUtDYrdk3IbOnLut5Qmhcjq/c7zWyAddG6c8rzS+bV53KE925wUyS8FO6rFixfLtddeK88884xyVH4wKK3EfvK0bQGmc4FkITY466aHjjAnpIeOouTvt+gWi2T10Juf3V4LQJ0Lfv3K9PrMGQbLL58ogWw1X23a+v8woaK0PXv06iDvrmrwVR+GVf9FDVEVpl5BaQu5Br0WcJMScFTz58+XI444QlavXh0q4CyD0toRlDYJm80gniCuDX5104pSs473Hdgl0DanLW5BXvX8iVdQU7cgpdpWzAEhKG0YVZ7zM7O+zvLd0uqYgkGBbDWjH18tK+o6S5/Zq2VtfZNv4FqzTmgXtDaC/oYJyuqn/gsKmBv1+wuTtpBrUOejoVKxxBzV1VdfrXpIWFs1efJk2WeffaS6upqS9ZC4DaEUOyhtEjabQTzDKOG88KqbnxqtfvM2kdvTLcir3rID0dDdgpqa9XOq9HRQ2iB1nNMe9DLM+iIA7IqN4poP0sKxhglka4ZoWlnXJE1SodorKAiv2f4AZ+B83YsLura8elJ+AXP9iHI9R1VjhikzKMgwyY6C9FPTp0+XDh06yJ///Gc55phjpG/fvnRSEcgiKG0SNptBPOMq4UBY5RvKCJO/W3uYx8wzm1V83kFNzfo5VXo6KG2QOs5pD27YZn0RANYrH6RFENwwgWz1ceSBHlGFNCn1nl/gWmf7Iwfze4h7bQUFzPUjSplJqDGd+UQJlExypPrD4t9hw4bJjBkzkrWqzMgiKG2hmHM4XvM5YQmjfNP/D6NMKqU5Kr+gtG5lon0+/nSRjBja3D5R5qjc5sPiXlu2zVEFXT+co5LSVf2hQpx3KpwsgtIWii4ziTmyMMq3qE/JXsecN0+vfL2OO4PShrHP+ZmzV+yVNqhtvcrcxvhVh3EW2p5zX1njGRw3KnGdVNQyw1wjYeY4zd4qKbGhvxNOOEHmzp0rn332WXIWlSFeCyeTSl8M9LxN0BxbFnalkY+uf5S8nK9+ZcZpW50GkSkAekhBdTFtilqezj+oLn7HonweBxuvUZJyj+qSSy6Rp59+Ws466yy5//77ZfBgI7YNCUWcbbOzjqFm2pBE5PFi2FVI2wTl46UK9MvLiZvS0CwzjATcrRyMcDRurpJ1r6+STY3SRqHoV88o5UVVooZp02Jc11HbkZTINh9Ovv71r8s999wj++23nxxyyCGy0047yTbbeCuzGD09/tOeDTHUnDYgmCrI+gaQVNsE5eNUPYaNpacVZW7KMq8ywwaAbVvO1oESU6Hop0jE+7DlRVWi6nbya9NiXtdmvTAPQ8pgmw838BTX0NAg06ZN803DbT6Cn/b8Ii/Y8HRogw3FtCsoH6161D2qMLH0vHpUThWfW5lh6mGe39yj2izrNle26VG5KRKdZYadL0VPSveo3JSoznyD2rTY15Qt1ykpsurv/PPPT0R6fueddxacRzmq/rzSZ0VWNgS1T1J2BeUTRenoVJT59cAKsV3HQpy/YJEMGzxQNlU2y96LpRiNmm+YNi32NWWzsi1r6ixum4K2+SDJEPXHmbWTssWGYtoVlE8cZVpQr6VQ23WPXEeXhxOJqxwMQ1QlapJtSsoLbvNBSIlCxRspW0f1rW99S3r27Ck333xzqPRIh/SQspcDcW4GebmBeMmR/WTKTqLIrJMGdi5c13oSMIxU3Hz/+fpNLXmZ9Q6Tj07v1l44FlbSHSRzNwkTscEpYw/zfSKtM50p2ceC30Il7oWQ1DWUtH15+a3nWp6OCBT422uvveQnP/lJqHOQburUqfLyyy/Lm2++qeIBlipxJLY2yM3D4CVH9pMpx6lrsdpDB3jV1J65g2dZXlvBO+MFhgluq4/j1Qz+araXtg3Hv2kEn/WTeWu82sncit7c5t6tXcxAu7UbG9U6LL/vEzY8vbBO1aXvlnSmZB/3dn07PsoRTNet7DDXThSSuoaSti8vv/Xc96j+8pe/KEHFxRdfHKkQOCuokR577DEpVeIu0MzD0IybHNnveNy6Fqs9YJfTycyrrXcty2mDGSzWjZotwWX98lHBZ7e0Ez4120u3oWz5DGm9FlObx3COVzvprej1537t4gy0i1e/7xNlwUZdItKh96Ql+/gzrXlrSzBdv7KDrp0oJHUNJW1fXn7rJeGo3njjDaUGOfzwwyMVcthhh6nzcH6pYga3DCuxjXNOFngFj/ULmBunrsVqD9iFPE123K55sbJXUFq3YLFuVDuCy7rlg8+9gr/qNpQtnyGtjrfnF2DXL4Bq2K3o3QLt4tXv+0ResFHniHQIl2QGKjZLG2cE0/UqO+jaiUJS11DS9uXlt14SQWkHDRok/fv3l9dffz1yQVgQvGzZMlmwYIGUMnEktqbM12aJqJcc2U+m7CTsAlavNIW0D+xcXbdZBnXrEFiWV7BYzFH169q+5Qk7KLisedwM/upsL68NEv1k3m6fObeiB2EW8JqBdsN8n7qHZ6YzJft+wXTdyk4ar+816vWTtH02LC3xwuZ7T6Q5qg0bNkjXrl1jFYTzcH6pE/UizNO4tdcPNsoPOWxPsxjoHkyYstwWpQI4KZ2XV3qv79TsibrZFsYO81hQO53x0upQ15Yz0G6Y79PNqZrvwwalLYaTctpSCEnbZ6uTsp1I38J2220Xeyt5nNe9e/dY55YqpTRubZPtzuCuXp9FyUe/N//c0qIn4fedOm3zex9kb1De2o43P2+e9wqTR6GECQNWzPLDlGkDxVI7liqRelQIOvv222/LihUrpE+fPqHPq6mpUUN+Y8aMiWNjyaKfrvTTQlAIJVuxqVfotz153G3O9blQten7Cx60dUBanVYr5jBH5DYX4bTNDGzrfB91i3v9fq+e7eSqoSLnvvaFsgesrBcZ+NDSNtvCJ/29RQ08m8Z1Y9O1WWy1YykTqUc1fvx49XrvvfdGKgTpofpDAFvS9kmv0eInvzz1Ck1boELzUu8F2eml/NOKNvzh/858tWIOzuqfx1W3ujE68zRVclDRYat5/R6f+dnrp0yE2u+rTc2qPx0419wWvljfW1B+fjYX67qx6dosttqx1InkqCZMmCDt2rWTW2+9VV599dVQ57zyyisqffv27eX000+XQnjqqafk+OOPl6FDh6pt70ePHi1nn322LF68uCXNddddp4Yovf5sEnOUghLIpjr4bU/ut2W8Xz7muVrRhj/835mvqZhz26DRzNNUyUFFh63m9Xt8FmWLezMt1H7YOFGr/vRZzm3hk/7egvLzs7mYgWhtuTaLrXYsdSJvRT958mS5/fbbpWPHjnLhhRfKeeedJ7169XKdk7rrrrvkf/7nf1RkdQS1veaaa2IZid4Y1m498MADykkdeuihSpwBFeFrr72mthnZf//9WxwVtiQ55ZRTlErRCeyAw8pzUFobSUvNFDVor5caz+8cr2POJ3K3fJ0qMb/yTZUc8NoK3lmWX94ISmuq/rQCz0vckPT35mevl83Fvm5s/H0VS+1YCLa0TSIbJ/7yl7+UTz/9VEWbuOmmm+TXv/617LLLLjJkyBDp0qWLfPnll2rH348++kgaGxuVkznqqKPkqquuim0kHB6c1MSJE5UTQq/OZNOm5rA2JqeeemrLUKXt2PCkV0p1cPY+vD4LmscIc67zM/Pm45avl21eNvgp99zsM+c49ed+Crykv7cgpWGUNi3Fa1Njm5OynciOqrKyUh566CH5zW9+I7fccousWbNG/vWvf6k/RK2AY9L06NFDLrroIvnxj38c20BI2uGc4AixJ5bTSalKtC9oo2JSxrjNYyRxY4uSr1faYtlWLPJmL8kPse/wP/rRj9T80HPPPSf//Oc/ZenSpfLFF1/ItttuqxYFYygOESnQyyqEF154QWpra+X73/++bN68WW3OOG/ePCV1P/jgg2XYsGGu5yEm4axZs5RjRRqkjbsGzPZhgDjn+w0HeRF0s036pmTa6GVv1Lq7DT25bdrnVR8s+HWuO3JbfOu3GaCzLl5pkefonh1kzuqGVse9Fg7rYTeIOfT7RV80SI9O7VzbrpDvzO1cvN+jVwd5d1Vre/M2BEbso6CuCLacP+6449RfsZg9e7Z6RU/qwAMPlE8++aTlMzihSZMmydVXX93mPMxVmcCxoUeGuaswpLVl9ejHV8vKuibpXVUhc07oKfX1zbHZ9GvU88Mw6I+rlMwa94eF3wsn2UWQUyjJMEn/wNe7hf4sLqaNQP//kxO2bX5fXx+57k47zfNnHtujeeisrs6zPts/sqpVHDsAm7br2HxDdqa/78AuUr95m5Z8/dremRa21dRtLQ279urjsFkHt9V11zZjRKOpsUoqZq2SFRtb22mWV8h35nWutq1Xp+b6BP2G4ly7hRL191VO1KfYNlHnwKwfM1u5cqV6veOOO2SPPfZQPazhw4fLnDlz1LAihB0QWKB3B0aOHKmOfe1rX5N+/frJ8uXL5dlnn5Vrr71WOTU4LMyZBYEeInpwxQQy4hV1naVJKmRFXaN8/OkipdgCsLuQ871YW4+bfmd1m6tvbJL35y2S7s3LejzBE/rMmipZ2VCppNPYQVZvzuf3WVycNjbT/P+5i5Yrez9dsjxS3Z12ot7m+Z8uXKzO96rPyjrI0pttMoHTqalDF6YisP5h2x7fa01d67LedNgMa7TtOK5trlDHYYB2ZdrOreUV8p15nWteiys3NgV+H3Gu3SQJ8/sqV5YXuW3Q6fAaCcuto4IgA0Bl+PDDD8v22zcvkDvggAOUwAIOCY5JO6pjjjmmzSLlc889V0aMGKGk7eh9hXFUGL5Mgz6z9VNlpYwYOlA9zeBCgfwedY56fhBI0XGmfqqvkJE7Bp8Dxi7QT9GdZNjgPqE/i4PTRqD/P3xgX9U+Q3foK32q1kequ2nnyB37SJ85W9tu6KABLUNVbvVB7hUzvXpUzXf5oPpHafvq2a17VPtUt7YZN/jmHlWlymfsknUyayWUFBXS1NgoFZWVjh5V6/IK+c68zo16LUZNnwRRf1/lRL3FbRNZnp42kMNDuIE5r6effrrN54h2MX/+fKU0DJKd67QLFy6Ubt2SGaJKgkKD0kYd54fCDItMsX4nymp9G+aonO1T6BwVzj/3lTVtlGqFzlGFrZcfejNFZ3BXtzkqMzLFfw1eK8MGN8vT05yjMm0LS9pzVDZLsLOmzuK2sX4Wc+edd1avXnEC9fEwc0p6vZdtwXEL/aFGvVGrTfw2SuTV+mHk2Uli3ly9buxR285NAOAWvcCrPghKq4PbmmueotQ/SsBWpHXm7Qxua6rt0NMx64btTLzKK+Q78zo36vdBIQUJg/VXiV4LNXfu3DafYSExekhQFvbu3ds3H6zvwtoupHVboFwu+K3WTyKMTlrBZeOW6bZoF+1QXVXRRnGXRJlm2KK4efnZ4qwDBA7mfFNQiB63fM1z4gbxjXMtpHUOyR/Wz1FBKHHIIYcoEcWUKVNahWHCOq61a9fKSSedpNZSQR6PMdaddtqpVR7oQSGKBj6HzL3c111heMs5dFNo8M5iBjgF+v9Qk8Ut0y891gCa6ZwBYuOU2ff3S1SMPYQvcgaEDZuXny1OzDqECX7qVr55jimZjxLEF0S9FuJcPzYGnCXFIRd37JtvvlmOOOIItXAYETEwHAjV3/Tp09V4qo56sXr1ahk3bpyai4IyEJOCiNz+8ssvy5IlS2S33XYrKEJGKeHsSRWyUDPphZ7O/CC5hrCgOe9tYpUZdlGtGYAWQNkWZwEuelI6Dx0Q1hyCC5OXTuNmi1fd3l7VJA2D3YOfOtdcuW11r8+pUYF965WiMcqCZdgIhxnlWohz/XBxcXlh/dCf7lW9+OKLKiwS1lXdfffdasjvnHPOUT0tOCQdCQNhlnBjw0JkqAERyBYy9V/96lfy/PPPS8+e6azXyBOFBu8sdoBTBGkN2jI+qEyv9H4BaHWA2DhlwinhfLeAsGHz0mncbPHKSw/9BQU/dSvfPKdaBfaNHsTXGQw4zLUQ5/pJ+pojdmO96q/cyFJ5k0RPKOkAp85IEc72idP7CxvgFYRJW4jCL2zvwcsWZzozKG0YVaRb+eY5UZSefsGAw5DGOTYr27KmzuK2ycXQH0mHJHpCSeIVwLWQMsPmk5TCMUjhF7b3EAa3jTeDVHVueZvneJUdJeBuWNI6h+SPXAz9lTpZKJcK3bDNabNWt4VVscWxJYl2iltvXbbz/KC6uJWnj6HN9PlOZR/+j3R6LVUhFHK+m/1u80Nu5YQpt1gbB+ZFDZgXO7OGPaqMyUK5VOhW2E6btbqtYsvcRpCKzTw3rC3OrdbTrLdzq3l9flBd3MrTx8zbM+ZZ9Lbxelv6pxfWtUTBwNPkkYOiLc5O4vryai+3ILpxtpkv1pbseVED5sVOG6CjyhCvJ9NiEqQGi2ozIjVoVRqsD6Ni02nQowhji5uqLa16m2VrcD5s96sL2sVty3Gnk5ItCjv9zUM119jYHHRWg/RQ4KWpxgxqL3OJg5dy0q/cQq/DYtQ5TfJipy1w6C9DslAuFboVttNmRGrQ6jZYH0bFptNg/iaMLW6qtrTqbZbt3Grery5oF2d5pg0m6IWayr59+lW1Cn2L9FDgpanGDNNeQcpJv3KLtSV7XtSAebHTFqj6swDzaSot5U2hT7DOJ0CtbgurYnOLXRemTKeqLa16B2017/W52/byOg3aTIdiMnvT+r15LKzNbtdPIU/rfu3lp/oLW26xYv15lW2bss2mnlSdZW1jwqE/C8jiQi305uC0Wavb4qjYovRunKq2tOqtbXZbj+Q31+AW8Fbn4dw80ZlPUN5RbU+yvYJUf2HLLVasP1tu/qViZ9Zw6I+QIs0zRpmD9IoUkfYcZhhstYuULnRUZUbaNxW38rzkzHHyiprO67MgGbhXwFW/uQb8f6/eHdp8ZtbflGeb+bgdcxOnJEnY/Io1v0KHR7zg0F8ZkbYc1q08fUwTNaBskDzdr45en0Emjd6Blww8KOCqW5Bffd47KxuUs3Krv1a9QUSxXafmm/573+0nZ7y0WgY+tFSlwXGEBItSzzhEzc+rzmmVT8oLOqoyIW05rNfwkD4Gp4CbdNSAsn7ydL86en2GHg3k4V4y8LABV/2k+HBWXvUHkPebeaIcLfnXzswvkG4Soa/i5JdkT4pSbeIHh/7KhLTlsG7lmccgSY4TUNZPnh40DOf2GSbzIQ/3koHHDbgapv66GuhRmdJulKPl6m7tlPR3mbVUOuvyif1Qnm4ZxZaIpv206rXw15R0R8krjDw9SiBVPxm513lRF846lW1m/fGHz51tYgai9SrP7Xgh8vSsezJplG+zBDtr6ixuGw79lRlZPC17HYuzgDWMPD2op+NGlOCtYe32mncx62/+Pyh92LqEsSFufsUk6/KJvXDozwKyUDvFKdNPMRclzzjpnAo5PzWhX37ONEFbxTtBaCS3/LRtH63eGEvC7RZ2KG7A1rVbtCrN813BNji/vySux7SuaSoFywP2qDImC7VTktt+68CiHQzlml+eYct2Ku10kNbqqgrZdZuO8uHMNTK2+qs2ajqvfN22dA/aKt5Jj/uXKBvw3P/NQVUt+QEEqzXdSu2ZO7QJ3BpUV6DnaUY99nmsgK2D/rhK6hs7S8eZq6RHp0q1Q6/GzQbn96cp5HpM65qmUrB8oKMqs4WTcRRWfoo5rUpzKte85lTClO1Mt3nz1qCtK+qaZNPmSlndoLemb62mc8vXqaRzBtN12yreCdJrG/D6Zs3WLeLdQM8qjITbrCuc1KxvN+9WPejhZZEDtqptQ5RNFerVDKQLhbtb6Crn9xdFjZmlgo9KwfKCQ38ZkoXaKU6Zfoo5rV4zlWt+cyphynamM4O09qmqkFHbNqqelZuazi1fvDeVdM5gum5bxTtBep0rXvep3rpFvA5Wa7JLz04tZUdpW2fw2igBW1GH5qRN6hV5+gW1dfv+oqgxs7ymqRQsL6j6swDzaTAt5U3cp2UvxZypXEuqbKfSDn/tG+tV+/TtP0C6dekcKV9TSacJ6km59azgtJz56TZAT0o7qSi42R4nYCuun/fnLZKRO27dih745eP8/uKqMoPqUwyilmOzsi1r6ixuGw79WUAWT4Nxn5bd0DfBsHnGSad7TnV1wWrCKOVGcVJAOylnfroN4jgpL9viBmzt3tE/KK5XOWEUiLZd0+xJlQcc+iOkRIk7B8qgs8Q26KhIqpg3PS31tuFGaMrB3WTsZrqgfLzeO+XmUSX2UdsJvY09enWQPp2a5+Wi9GQZdJbYBIf+SGqYw0labg70DTEriTHs0vYYCu0WGbuZLkgCb35uvserKTf3C9gbJaCuHzrYLjADAYeBQWeJTbBHRVLBHE56Y9lWJwWyHGJCmW8t32oPZNr6z7QpaDjM+bm5gBeLbhH4VsvNIeCIsvdUnKE4lG/K07XMPQpJ9qQ4lEgKgY6KpII5nLTv9lvl5iBLiTHKHNd3qz2m5DxKIFg3mfnWYLYdVeBbLTeHgMMrYK0pu/fKO0w7oXwtT5eIMvek0fbq0imAIFHh0B9JDedwkpZ6Z71YU9tlBogFTpuChsOcnzvfm3Jzr7ywjUiYvMOAIcYw8vRio9tT9+ey/r5J/mCPiqSKeYPSUm8bblqwwZRpxw0E69bT0jidhTN6RtDwWJx20guIs4SLc0mhsEdlAWHDGCX5A086v6iLfsPgFvLHecGavZQwZXst8PXqRTkXv+oeitOZmY7Fb+GuVhe62eAWG7DQ9vRaNOyXr1dbFELS4owgopbFXp7d0FFlTBg1VNbbjgcRNTBtHBt1Gb2rKmTq2NblYv7FvMl7le0VhNYtYK1pg6Z2Y2NLfD9z23p9PnwYfIKZh9PGaQubyzFtMOuKrej1DbPQ78ks2wxsG6QudGuLJEjLEURtNyoS7YdDfxkSZrgnacVU0vn5BaZNykb0gnQZK+ua5KtNrcvFK5R7fmUjD2cQWmfAWlPpZ9qA/PFqBqHV29bDDn0+SjXzMG2s2aJ21GgbnHX1aoOo7elsH3ONWJC6ULcF6pU3hV7UdqMiMR/QUVk+dp/0+H7S+UUNTBvHRgyT6TLQo9qmfety8Qrlnl/ZyMMtCK1bwFpnoFsdqNVcY6UDvZpbx6NUMw/TxuotakeNtsHr+yj0e/IKbOuXr/5MtwXqlbfhsKjtxvmzfMCgtDkJSlsqc1RRynWdo9oSlFa3j98clVtZts5RebVLoUFXbZmjShuvayGt31ceqWNQWuJHmB9I0j+ipPMLE5g26lyAMy+UoYPSOst1pvcqyysIbZDKT796Kej86u200c2GuCrDIOLYWwo3bK9r4b4DuwSmJ/bBoT+SCmnOBQTNw3idUyxbwh5Le36kHOZjOAdVGtBRkVRIcy7Aqyw8WWOLd7yaeB0vFLd8vY4NfGip+kvahii2lSKcgyoNOPRHUiPNtTTOstyerPXcUzG2NPd6kvc6phWFWmlXzDYqVp1txbwWMA9D8gd7VCRV0rwhhomXV6wnbrd8/Y6lqbQrx15GOdSxlGGPiki59+iK1dNzy9fvGEhKMRnHNkJshY6KlBXFUtdFKS/ssWJHT6CTInmBQ3+EWA6Va6TcoaOygKw2DCwEr23VbZdYu214GOf8KPmEKSOo/Yoxp2SGVSLEZjj0lzFZBMRMOtipM3hrWnUpNPho3PM1YfKJEnTYma9fwFobAwkTUizoqMpsSKdQabIz2Km5rTq65ziehuQ5aj38toqPer5ZT798wtjola+bnD0p/AIJc96K2AiH/jIkC5lw0sFOzW3VdfDWNOpSaPBRc6v4qOeb9fTLJ2rQYWf7Fev6KEYgYUKKCYPS5iQobTHLjIMz2KkzeGuxcLZPoRvkxT0/Sj5hyvBrvyg2Rrl+irHZpe3YHHg1a+osbhv2qCwgi5tE0sFOncFb0yJqec70cc+Pkk+UoMNxpOvFDCRMiA3QUZFUCRuktZD8ksCpaiSEZAfFFCQ13BRwhSgQi6WY9NrCnRCSDexRkVRwU8AVonoslmLSawt3Qkh25MpRPfXUU3L88cfL0KFDpW/fvjJ69Gg5++yzZfHixa3SrVu3Ti6//HIZOXKkVFdXy6hRo2Ty5Mmyfv36zGwvd8IGaS0kvyTw2sKdEJIduRj6a2pqkosvvlgeeOAB5aS+853vSNeuXWXZsmXy2muvKaXKgAEDVNovv/xSvvWtb8l7770nhxxyiJx44okyZ84c+c1vfqPSTps2zTpFS7kQNkhrIfklAYb7vLZwJ4SkTy4c1V133aWc1MSJE+WGG26Qdu1ab+W9adOmlv/fdtttyklddNFFcuWVV7Ycx/9vvfVWufPOO+WSSy5J1X6ylaRVbcVWxNlEOcnICTGx79foYMOGDco5DRkyRK6//vo2Tgq0b9++pef14IMPqt7WpZde2ioN3uP4lClTUrOdkKQolx15Ccmlo3rhhRektrZWDedt3rxZnnzySbnlllvkvvvuk/nz57dKO2/ePDUcuO+++0qXLl1afYb3OP7ZZ5+1mdNKkjiT+oUKAbIIKvr5+k2Z25AESbd9mGC1bgINPzvMMFVRhCNZfydZl09KB+uH/mbPnq1e0ZM68MAD5ZNPPmn5rLKyUiZNmiRXX311i6MCw4YNc80Lx59//nmVTs9peRFny+ozpq+Tt1dtkjG92ssDX+8W65z6+uaYbvq1GGUWyvaPrBLcgjAIteyUXqnaELV9/CjUbuf5Qe/B6MdXy8q6JuldVSFzTugZaIdO375SpLqqQvbq2U4aGzZKXYO7TbpdTn+pVmavaUz1usj6ukz7+ik16lNsm6g6Aesd1cqVK9XrHXfcIXvssYfqYQ0fPlwJJDAPdfvttyuBBdR/UPuB7t27u+bVrVvzD0an82Pp0qWqBxeWhkaRmTVVsrKhUmbWbJT5CxapyNRxz1m+fHlRyiyUlXUiTdJZuakmaZI3P16Uug1h26eYbec8/+NPF/m+R/44Z0VdZ2mSCllR16jSoEwvO77atDV9Q2OT/GH0V9K9o8iiRWsDbXt7ZUPq34lZfhbXRJrXTymzvMhtg06HV2cit46qsbF5mKRjx47y8MMPy/bbNy/APOCAA5TA4mtf+5pyVnBUSdK/f//I54xdoJ8iO8mwwX1inYOnGVwokN+jzsUosxAGwkXN1D2qCtlnxEAZuzw9G6K2TzHbzjx/xNA+MnaR93udf5/ZukdVKSOGDgy0w0w/csfm9GHaZ0zvDlt6VOlcF1lfl1lcP6VGvcVtY72j0r2gPffcs8VJaXbbbTclssBcFeaxdNq1a92fOHVPSqfzI46E/dEjogdJ9ToHF0oYG+KUWShrztxBzVH169o+MxvCto8fhdrtPD/oPZh7Sv820nc/O9zSh2HKwdtJZYdOmakEs7gm0r5+SpWOFraNZR3ytuy8886+w3n6OOaUdtxxR/V/p8hCo4/rdMUgzg+z0B9zFjcD7aSytCEJkm77MMFq3ZyOnx1xpfJZfydZl09KB+t7VOPHj1evc+fObfNZQ0ODcj5Q9PXu3Vt1WdHreuONN9TCX1P5h/c4Pnjw4EAhBSGEEHuwvkcFoQQiTMAhOddAQaaOYT5I17GWqqKiQk477TQVKunGG29slRbvcXzChAkp14AQQkhJ96jAzTffLEcccYT8+Mc/lqlTp6rhQKj+pk+frjb5uuqqq1rSXnjhhSpMEqJQIA2Ugu+++65SC44ZM0bOP//8TOtCCCGkxHpUulf14osvyqmnnqrWVd19992qh3XOOecoB4QhPw2G++DM4JAwXAhFIF4vuOACeeKJJ6RzZ0irCSGE5AVuRW8ZNm8HbQNsH3/YPv6wffLZNrnoURFCCClf6KhIrmE8OUJKHzoqklsYUZyQ8oCOiuSSYm1FTwixDzoqkkuKtRU9IcQ+crGOipA0t6InhNgFe1Qk19BJEVL60FERQgixGjoqQgghVkNHRQghxGroqAghhFgNHRUhhBCroaMihBBiNXRUhBBCrIaOygIY/ocQQryho8oYBlYlhBB/6KgyhIFVCSEkGDqqDGFgVUIICYZBaTOGgVUJIcQf9qgsgE6KEEK8oaMihBBiNXRUhLhAYQsh9kBHRYgDLhkgxC7oqAgx4JIBQuyDjooQAy4ZIMQ+KE8nxAGXDBBiF+xREeICnRQh9kBHZQFR50E4b0IIKSfoqHKmMKMijRBSbtBR5UhhRkUaIaQcoaPKkcKMijRCSDlC1V/OFGZUpBFCyg32qCwgqtOhkyKElBN0VIQQQqyGjooQQojV0FERQgixGjoqQgghVkNHRQghxGroqAghhFgNHRUhhBCroaMisWD4JkJIWtBRkcgwMC4hJE3oqEgkGBiXEJI2dFQkEgyMSwhJGwalJZFhYFxCSJqwR0ViQSdFCEkLOipCCCFWQ0dFCCHEauioCCGEWE0uHNWoUaNku+22c/371re+1Srtww8/7JkWf6+88kpm9SCEEFLCqr9u3brJ+eef3+b4oEGDXNMfddRRysGFTU8IIcROcuOounfvLj/72c9Cp0dP6/vf/35RbSKEEFJ8cjH0RwghpHzJTY+qvr5ezT99/vnnsu2228qYMWNk7NixnunnzJkjq1evls2bN6vhvoMPPlh69uyZqs2EEELKyFEtX75cfvjDH7Y6Bmd17733ytChQ9ukv/vuu1u979y5s1x22WVy0UUXhSqvrq5OsqChoUHatWunXklb2D7+sH38YfvY0TZVVVWR0lfU1tZaH1X0+uuvl/33319222036dKli3zyySdyxx13yB//+EcZOHCgzJgxQ/WywKuvvioffPCBHHroodK/f39Zs2aNTJ8+XX71q1/J0qVL5YYbbpDzzjsv6yoRQggpJUflBRwOnNXVV18tF1xwgW/aDz/8UP7jP/5D9az+/e9/S/v2uelMEkJIWZNrMcWZZ56pXt94443AtLvuuqvst99+qof18ccfp2AdIYQQKXdH1atXL/X61VdfFSU9IYSQ7Mm1o5o5c2boRbxQ/73zzjvq/5jXIoQQkg+sd1Rz58517QHh+JVXXqn+f+KJJ7Ycnz17tquTQtr58+fL+PHjpV+/fkW2mhBCSFJYryj4y1/+InfeeacccMABqie0zTbbKNXfc889p2SUl1xyiRx44IEt6bFeavfdd1d/WvX32muvqXN22GEH+c1vfpNpfQghhJSY6g9yc6yVwgLeFStWqN4V5pr23ntvmThxohxyyCGt0l9xxRVqSBC9Jzipjh07qnVWRx55pFIGIjAtIYSQ/GC9o8obTz31lHKs7777rnKqffv2lXHjxskvf/lLGTBggEpz3XXXqfVcXuDcwYMHhy4TvUVI9LFeDGXuuOOOctZZZ6m/ioqK3LVPmIeJ999/vyW9HwhMvGjRItfP0BOfOnWqZA0irjgXszv5+te/Lk8++WTL+3Xr1qn1hThWU1Oj2vH4449Xi9q7du0aqfznn39ebr75ZvUwiOtljz32kEsvvVQOOuggyVPbYIRl2rRp8vTTT8vbb78tS5YsUfUZMWKEnHrqqXLGGWeoBa1hKcVrJ6/3HuuH/vJCU1OTXHzxxfLAAw+oHtx3vvMddcNYtmyZGnrEBe+8sZ5yyimuQhAE4A3LRx99JEcccYSKpIEb1fbbby9///vf5Sc/+Yn67MYbb5S8tQ9utm58+umn8qc//Ul22WWXUE4qbuT9tMEN0avOuMFgDSAWsGu+/PJLFXT5vffeUyMKmKOFk8GwNtoSN+uwK/+xDhHrEXv37q2uR/D444+rawnf1XHHHSd5aRtcHxMmTFDXFW7O3/zmN5VDf+aZZ9TvAb+LRx99NNINtNSunbzee9ijSojf/va3Kro7hiPxxOJ8ctu0aVPLImP9VIPeBcQdhYDtTBCZ47HHHpPDDz+8JS4ibjD//Oc/1YWzzz77SJ7axws85d9zzz2hFnhr9FYvuKnnDXyPcMq42SLaSnV1tTp+7bXXyn//93+rcGBaUATw/1tvvVX+67/+S83dBlFbW6t6T2h3PBFjDhegJ4IbvRYn6agvtrcNIs/ASeMmjAg2pmM/+uijleoXzhc31XK9dq7L6b3HetVfHtiwYYP68ocMGaKGY9yGF4oRCQPdblwouOD0hQIwL/fzn/9c/f/3v/+9lEL74KkNPwjU7eSTT5ZyAENLCKz8jW98o+VGg57pgw8+qHoNcNwmeI/jU6ZMCZX/3/72N1m7dq2ce+65LU4K4P/nnHOOrFq1Sv7v//5P8tI2EE/hQch0UgDv9fAYepzlwFSX9snzvYdDfwnwwgsvqKdT7H8FKTye6ubNm6e60VAhDhs2zPU8fNGzZs2SyspKlQZpo8wvQGgCnIISgNiI+IHa8MOM2z4meAJEHnhawzBVMSPv24J2OKeffnrLMbQbhksxnON2Q953333VnNPixYsDh0f9rh/kj4cKXD96SND2tvGjQ4cO6jXKHFWpXTt5vvfQUSWAXruFHwEmWfG0ocGFMGnSJDVc5QTdcBPcuHFzCHtjwE0LuN3oYQsmRTFWHGZYzcb2MUEvIsqNqZDI+zawcOFCefnll1Xv5rDDDgv1nevjcFRIF+SodF6YAHeij+k0eWgbPx566CHPG2u5XDt5vvdw6C8BVq5cqV4R0R2Tr+hB4IkWPYeddtpJbr/9dnVha0aOHKmO4QaOJzUobTDngEle3LRxXhgw/uw3AYonwMbGRlm/fr3kqX2cfPbZZ/LKK6+oGy8CC0cBvbgnnnhCBSLGHAbmYr73ve8pVdixxx4rX3zxhdgInuLx3eHGYfYCgr5ztK+Zzg+dRp9jouelwuRjS9t4gXkprLvEvBsm/8v12snzvYeOKgHwhejxWVwkeOJCNxqLlPEjQa8BF4fmmGOOkR/84AdqzgbqLDx9YJ5Aj+kG9S5KvX3cnoYxN4MbB9JG4f/9v/+nZNZ9+vRRi8VHjx6t9irDDQdKQxvm8NzaC+2EmweuExK/baD4w9wdggX87ne/k3K/do7J6b2HjioB9BPpnnvuqSSaJthDCxcFpLOYY/EDPwoMJ0ClE+ZJVpeLCXE38MSHCzbquhqb2gc/vEceeUQ5qCRv2lEi76fNSy+9pHqc6AGgbaJ85369pCi9L91bCJOPLW3jBKozyNUhJsAcZ1Kh0/J67eT53kNHlQA777yzbzdYHw+za7CO8A6lXBB6HgFROJxAtLBgwQL1xJT13luFtM8//vEPJZfGkF+SwYRtjqTvNxHu952bx93mnaLMQ/nNX+VBRPHss8/Kaaedpr5nOKkoN+1SvXbyfO+ho0oAvR4BgXKdYLU8vkyoYILUaljvgQlIpNUXjR86xiHmfJxgHQPyM+Mg5rF9ChFRJBV5P00gKcY8QY8ePdTaH7cbBHqleJrH92uC9ziOG0SYBdF+1w8EGWaaPLSN6aRwvSAdnFQYVWk5XDt5vvfQUSUAusxQE+GG61zDcsstt6juMSIJ4OkCXWJT9abBU8yFF16oPseCROeTCG7yzhs9eiqY54HQAJPFpqT2mmuuKcoNvtjt4xRhYI4BDgxRBryAs0PbYPiwkMj7NoDICfj+TjrpJOnUqVObzzGcgp4CJqmdK//xHscx3GWCNkCdneGATjjhBDWEg7kb9Fo1+D8WVuOGFfWGl2XbAPwOcM0jDBecVFCPsJyunS9yfO9hZIqEwIUORREC52KRHb5IhLWBUghDVhjCQjw2dIkxVwNBwfDhw9UxxGqDnBQ3CMzZYJFlz549W+Wv498553EQIgXlYdgMNx6Mw2NsHsexaNOWEEph28cEIYEmT56s5MH64ncDbYoIC8jHjCIACW5Q5H1EcbAJ2Ip5AqxBwQ4AbuBpFW2IeId4AEDdod7C0y2uKyz27Ny5c0t63Ewwie4Wn84MoYTrR4dQwmLf+++/P3QUBxvaBjdT9N43btyoQnRBUeoEvSCIcsrx2lmQ43sP11El2Gt48cUXVXgbDJvgpoELAV/YT3/6U6UcAuiWY/U8FtvhoseXj5sKLhzcMJDevMkEseuuu6ryoNbBRaIDQ950001y9tlnS97ax23tS9wnM9y0cPOCQ8RwhI68j5X0bpH3swbXBG402BnAy0kBDM/A4WDdC3oNcERoS4SVQty3KNcPFGxoEwSl/cMf/tAqKC0WgeapbbDmCU5Kbw/kBpy16ajK6drpkeN7D3tUhBBCrIZzVIQQQqyGjooQQojV0FERQgixGjoqQgghVkNHRQghxGroqAghhFgNHRUhhBCroaMihBBiNXRUhBBCrIaOipCInH/++Sr+mXM77zAg+C7OxeZ2hJBw0FGRskA7CPwhKGcQRx11VEv6cePGFd0+xOvT5Zl/CPSJ2HvYhfXNN9+UUgdBUfEAgPYgRENHRcoObDeCQKN+kd79PofzQPT3MPv2xGG//fZr+UPk7qVLl8qf/vQnFan6tttuk1IGwXZvuOEGefXVV7M2hVgEHRUpK0aMGKFe/Ybe8FlTU1NLWie/+MUv5K233lK9nGKAPbj0H8r517/+pfbjgk3YC2n27NlFKZcQW6GjImUF9mXq2rWrPPHEE64b4zU2NqoN6Nq1a6e2wLCB6upqtbkh9oyCs0LvipBygo6KlBXYy+m4445Tu5nCWTnBJnKLFy+Www47rM1GjmHFFNiAD3seYQ8ubBuPDe2wCeTmzZtj273tttuqvYaA3qUVu6k++eSTamNJlDFkyBBl86hRo9T+QthY0Q1soKfnwAD2FMJutdhLCHsWOXubKANOG8Od2DcMr6eeeqraoM8NtAvyRjuhznfccYeyD20xePBglZezV6hteuSRR9R7DP+Zc3WoEylf6KhI2aE3znMb/tPHcCOOAzakO/TQQ9VcCzbxw/AhnCJ2Kj7jjDMKshu9KRM4LGwqiZs7duTF7rXDhg2TNWvWqJ17sbnf008/7ZsndrHFbrgzZ85UTgRzYhrYj/zx9+yzz6rysVnepk2bZNq0aWqbejhgL+Ckvvvd78rPf/5ztQssHCFekReGMt9+++2WtFVVVWpOTm+gOWDAgFZzdWEEMKR0oaMiZQee7nFDR4/gs88+azmOHU/1Vty4kUZl5cqVat4KPR1s4f7RRx/JSy+9pHpY2D33H//4R2zlHpydvrHjhg8wFHj33XfLvHnz5OOPP5bp06crEQjeYxtwOIpJkya5DnGa821XXXWVOge7LmNH229/+9vqs8svv1z1puCcMF8Gx4gyIDbBUCR2g8V27F7CB2xpj3PQBrAd6bAL7b777isbNmyQK664oiUteoIoAz1Z/TBhztX9/ve/j9VupDSgoyJlCXpM6CHAgWj++te/qid+9AI6duwYOc/77rtP9WZw073rrrukW7dureTu//mf/ykNDQ2R862pqVEOEI4QW8XruTPMXeH/GK4z6dSpk9pWHD0l2IMbvV87/OhHP1Jzcho4oH//+99y//33qzqgd4ZejclJJ52kHBna0EuJiLqiHfbcc8+WY1BKYlgPwKmuXbs2cnuQ8oOOipQlJ598slRWVirhhB5S08N+P/jBD2IP+4EJEyaooSwnEydOlPbt2wfmc+SRR7b87bPPPrL77rurITw4KfSAzBu/nlfD8BqcFhyiPnfGjBnqc/SSvMCwnhuYv4OwBD0cDCm6ceyxx6pX9JTc5t9gN3qvTrAuDM4U7Y7eGSFBBP9qCClBMAdy0EEHyYsvvqiGs9ALmjVrlowePTr2xP3cuXPVK4bK3Ojevbv0799fFi5c6JvP66+/3vJ/ODyIENCjOfvss9WwmWb9+vVy2mmnqTr4sXr1as/PdtllF9fjWoiBoUo4PTe0g8cwHsrQ80uanXbayfU8OFykhWgFdSAkCDoqUrZgHgQ3efSktMJPCy3ioG+6zhu2CYbrghwV5srCAIEG7MdwGnpa48ePV4uRMXQHrrnmGjVX5TfcCBWknw1wJvgLwm0ebJtttvFMD2flJhAhxA06KlK2QLWGXg4EFLhhY14K81NxwfoszLmsWLHCd74pCaC8e+yxx1qUe4ha4QTzU3HRDuynP/2pmosiJEs4R0XKFgyrQeGG3gCcC5R+UPzFZfjw4eoVaj834MQQDikJIKzQPTi3eSCAqBZx2W233dQromKkie5pEWJCR0XKGqxtwlwV/iB2KAQtrYaUGmuQnNx7772qJ5QEengPLF++vM3nEFi8++67sfOHvB5O4+9//7un4y0GergQ816EaOioSFkDBRoUbvjDHE8hnHXWWWoo8fPPP1frl7D2SQOJ+E033SQdOnRIwOpmYcbIkSPV/3/2s5+1mtdC5HEIL9yUh2GBYg+KQMxvodcJ+53zScuWLZP//d//lVtuuUWSAtE8tHQd69EIAZyjIiQhIKLAAlwo8f7yl78oSTkiUyBqBAQUmBPDvJFX6KGo/OpXv1JzapDFw7FgITCGFxGOCMrFgw8+2DdyRBAQYqBng9iCkPMjlJF2JHDGcFTglFNOkaRAeCuIQDBsieFH1AmSfohdsE6NlCfsURGSIJByIwIF1jNBnPHhhx8qYQKiPyQdXQEhkp566inlkDBMh0W6WJ+EhcUIU+SnugsD7EcEir/97W+qVwWxCCJL4A/OA3t8wRFeffXViS4bwMLrww8/XPXg4LDg2AuZbyP5p6K2tpb6UEIIIdbCHhUhhBCroaMihBBiNXRUhBBCrIaOihBCiNXQURFCCLEaOipCCCFWQ0dFCCHEauioCCGEWA0dFSGEEKuhoyKEEGI1dFSEEEKsho6KEEKI1dBREUIIEZv5/1yky2XpEwqSAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "heights.plot('MidParent', 'Child', kind='scatter', figsize=(4,4), s=3)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67743477",
   "metadata": {},
   "source": [
    "A primary reason for studying the data was to be able to predict the adult height of a child born to parents who were similar to those in the dataset. We made these predictions in Section 8.1, after noticing the positive association between the two variables. \n",
    "\n",
    "Our approach was to base the prediction on all the points that correspond to a midparent height of around the midparent height of the new person. To do this, we wrote a function called `predict_child` which takes a midparent height as its argument and returns the average height of all the children who had midparent heights within half an inch of the argument.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c0ff25f1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.712277Z",
     "iopub.status.busy": "2026-08-31T06:02:06.712213Z",
     "iopub.status.idle": "2026-08-31T06:02:06.713804Z",
     "shell.execute_reply": "2026-08-31T06:02:06.713614Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def predict_child(mpht, heights):\n",
    "    \"\"\"Return a prediction of the height of a child \n",
    "    whose parents have a midparent height of mpht.\n",
    "    \n",
    "    The prediction is the average height of the children \n",
    "    whose midparent height is in the range mpht plus or minus 0.5 inches.\n",
    "    \"\"\"\n",
    "    \n",
    "    close_points = heights[\n",
    "        (heights['MidParent'] >= mpht - 0.5) &\n",
    "        (heights['MidParent'] <= mpht + 0.5)\n",
    "    ]\n",
    "    return close_points['Child'].mean()                       \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0733b92f",
   "metadata": {},
   "source": [
    "We applied the function to the column of `Midparent` heights, and visualized the result.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "19ef1542",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.714899Z",
     "iopub.status.busy": "2026-08-31T06:02:06.714838Z",
     "iopub.status.idle": "2026-08-31T06:02:06.816038Z",
     "shell.execute_reply": "2026-08-31T06:02:06.815810Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "### apply predict_child to all the midparent heights\n",
    "\n",
    "### apply predict_child() to every value in the 'MidParent' column\n",
    "heights_with_predictions = heights.copy()\n",
    "heights_with_predictions['Prediction'] = heights_with_predictions['MidParent'].apply(\n",
    "    lambda x: predict_child(x, heights)\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fd3477a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.817084Z",
     "iopub.status.busy": "2026-08-31T06:02:06.817023Z",
     "iopub.status.idle": "2026-08-31T06:02:06.860527Z",
     "shell.execute_reply": "2026-08-31T06:02:06.860327Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'MidParent')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JqdJfAPKJZY09dNrCLdQejlJlcYgenjGEdhw84NAJ/AVryKqEioSZWk80VJGVytiKadOmJZiu7WBnLmbx4sVJn7399tvK7e6xxx7CO/utt96yLavNUFl5q8A/GjjEacWKFSLUy4jWJrbbBCARVsbftPTR+s6IeOX3IHVAITuA14z7CrehSEGdeOX3uca5554rnKjYSYtnyUaampro448/jr/nWGWGncA4zleDFR/vyKUKh0sxv/rVr+Jmcw12MtPPtjksilmzZo1y/ey4FQ6HxeYo+vhoXgNnEz8rbX0sMwD5DpupeWaspyMcFcdBasit6V2KYQcusWacpWZqFTjsiJ3COGxpzz33FCFBvElHW1ubcIziDUNmzZolQqAYjs3l8KmHH35YOHYde+yxwmnq//7v/8Rsm0OhVOCYaA6luv3220V4FtfDa76s2N944w36+c9/LkKetDa5HDuqcWxxRUWF2P3L6JBl9BB/5ZVX6PHHHxehXdOnT6eGhgYRh8wKn0O5YLIGYABeM2YzNen2wKkoDmEtOYXkplZJNTmqjDXOOussYb7luGA2RXOMMM8gx44dK5Qizzb1cFzvtttuKzyVebMMDnn62c9+JnbcUlXIDM9e+UcA18H7brMJmx2u2Av6kEMOiZfjHwkcssXt3XHHHWLmu//++1sqZA774rhq/iHBSvivf/2rCGHi8/jHhxOPcADyBV4zZjM1z4xZGfN7kDpCTU1NWWV/4B2X2JTKMyJ+yGqww46ZF20+weuqPEO187LOVzIxPtlyb5p9t0CMfB4fFS/rfB4fv8ATGwAAgCUwU6cHKGQAQFYBpyKQq+T2YigAIGdATCzIdTBDBgBkBYiJBbkOFDIAIPAgJhbkA1DIAIDsiYnVgZhYkGtAIQMAsgJeM96mppDqygvEK2JiQa4Bpy4AQFbADlwfnDAKmYdAzpJTM2T9HsUABAHck/4DZQxylZxRyMXFxUmJ5wHINLx7EXYtAgDklULmvZabm5uRNB4EZmbc2dkpknJUViam7QQAgJxeQ+Z9iQcNGiTSA6rmyc1FuO/arAx7WWd2fLiNoUOH4joAAPJLITOcMIAfgPkMK5uWlhaRJQmm0mQwPgCAoIKf7gAAAEA2KmRORM+mYas/ThqvceONN1qW/e677/zuEwAAAJD7JmtOXH/VVVdJP+ME8F988QXNnDkz6TNOar/VVlslHa+trXUqAgAAAJBzOFbIu+yyi/gzwiFH99xzDxUVFQnla2TWrFl04IEHupcUAAAAyGF8W0N+8cUXacuWLXTEEUfQiBEj/KoWAJBBvCRvCFLiBztZgiQryF9887KeN2+eeD3zzDOlny9evJg++OADEQIyceJEmj59OlVVVfnVPAAgILmHg5S32E6WIMkKgC8KedWqVfT666/TmDFj6NBDD5WWYecu49rxTTfdJDVvm4WrMNpuXNiVSw7GxxqMj9rYzFrQTita++P5O4lmLdhMi48drFTPrAWNrs/1GztZnMiKe8cajI8cJ+GVvihk9rzmDRdYuRYWFiZ8NnnyZLrjjjvogAMOoFGjRtGGDRto/vz5dMMNN9BFF10kFPPRRx9t28a6desSduHieoA5GB9rMD7mrF2/gVq7yxJWtFq7e+nbVaupyGYb6d4ouT7Xb+xkcSsr7h1rMD4DsD5ki7AqoaamJk+LJ6yI2clr7dq19OGHH9KECROUzuMZ9fHHH0877bSTMGc7mSHzBeeNHXgjEJAIxscajI/a2Ex/RTdDJqKJ1QXKs9z9Xmh0fa7f2MniRFbcO9ZgfAIwQ37ttddozZo1dPDBBysrY4bLb7311vT555+LnZN4L2onneILjp2WzMH4WIPxsR6bR2aWibXVjnCUKvrXVsvK1B6yj8wc6vpcv7GTxY2suHeswfi4pyjVzlxW8DaXK1asEJvw2ylkAEB25B4OUt5iO1mCJCsAnsKeOMzppZdeosGDB9Oxxx7r6Nz29nZatmyZyIST7/tPAxBUvCipICk4O1mCJCvIXzwp5Mcee0ysG5x88slUWlqa9HlraystX7486TjPiC+55BLxOa8j82YiAAAAQD7jSRM+9NBDluZqnkHvueeetPvuu9P2228vFvs3btwoHLrYCWznnXem6667zosIAAAAQH4rZN7kgx2y9thjD5o0aZK0DJuyzzvvPFH21VdfFbmKy8vLhXL+6U9/Sueff754DwAAAOQ7rhUyK2JWsFawo9bcuXPdNgEAAADkDciHDAAAAAQAKGQAQNaAJBAgl4F7MwAg8CAJBMgHMEMGAAQeVsbftPTR+s6IeOX3AOQaUMgA5KEpN9WmX67frza4Hp4Z6+GtLmX155JJO0h9CZIsuQxM1gDkkSk31aZfrv/EVxqovjP2AB9dUUBPHDbUUxu8ixbLyukRNXjfaf3uWrlk0g5SX4IkSz6AGTIAeWTKTbXpl+tb0xGlviiJv9XtEV/aYEWwTU0h1ZUXiFd+n6sm7SD1JUiy5AOYIQOQpViZcmV7Mzst70aetp6BVIYa7T60YZUEItX9SidB6kuQZMkXMEMGIEuJm3LJ3JTrpbwbeapKkh8plT63ke5+pZMg9SVIsuQLUMgAZDF2plyv5d3IM7YiRIUhEn/jKgt8byMT/UonQepLkGTJB2CyBiCLcZrPN9X5f7n+paeMjnvlpms2lUt5jYPUlyDJkg9AIQOQAzh9WKb64Zqph3cuKY0g9SVIsuQyMFkD4AHEZ4JcBvd3esEMGQAXID4T5DK4vzMDZsgAuADxmSCXwf2dGaCQAUjhVo4AZBu4vzMHFDIADkF8JshlcH9nDihkAFyA+MzcATO/ZB6YPjjv7+/eDNwXcOoCwAWIz8x+4LhkPyZPHjaEJg0tpXxiWQbvC8yQAfAAlHH2Ascl+zE587VGyjdOy+B9AYUM8goVM5SqqSqVJq1MmlH1bXf1RsSfSlm/ciDb1WH1uZNr57fjkp/XzM980k7aNBsTq3sgl+jNsEMbTNYgr8xQbeEIlUbL6MHqXtp1lDtTVSpNWpk0l33Z1EtnLCmj7g8aKRrZQhu7Bz7jfakfOmQQHTW+MknOolCUwpEoNfSXd5sD2a7vVp87HTe2bLDcegpD7pYf/LxmqcgnrYpsTHr6IlQ3b51Ipcn3wDzdPZCLFCnk3k4lmCGDvDJDbeiM0qquAjrnrVbXpqpUmrQyaS7jMeGx4THSK2OGH8hn/qdJKifnP97QRZ5zINv13epzN+MWCoUs3/sldxDySatiHIPNPUQ8YeT5cdhwD+QqD2fQYRMzZJCfZqjexLyuqrlfU5kjNpP5Z0XbvdZmOVYQbLpkWYxyes2BbNd3O1Oi03Hjz8IGKyxbZZ2OtZ/XLJX5pFXbN46J2T1QVpS7c7kdM+iwmbujCoBVXGVRohlKNfYylTGamYz/FG0XWbfDJkt+EMvk9JoD2a7vVp+7GTe/xtrPa5aOfNJ27dtdV+0eyAeKMuCwmR8jC/IezQw1qjxEW5VF6L4Dql2bqlJp0pLVnS6HGh4THhseoxGGSBdt/VAmJ+c/HllGnnMg242r1edurolf19HP+yFT+aSTvidlIfE6d68qYh3NiqLYcA8A/wk1NTVlVVR8V1cXrV69msaNG0dlZWWZFidwYHysaevopPq1ayzHR9VUlUqTFtf96uoOsWaXLoca7d6pGzOWqirKY8f6fwyYzYqMZn/GD9O9VR12pmg3pmKVc+y+W37eD+nOJ23noKZipsazxzuYIYO8QuUBp/oQTOXDkutmZZwJhxp9v/ghbPUgNpr9/TLdu/3cranYD/y8H/waS78c1PLFTJ1pMMoABBCekfDMWOZQk06wrWT+IHNQ0xzKQHqAQgYggPCMhM3UelgVr2ztTZvpco+n1tPkf64Xr/we5DYyp65NXRHa++kNuP5pAgoZgIAic6BJV0wqtpXMTzSnLu3HIFtlcP3TBxQyAAHlsHEVNKq8IO3b+GV6+0CQOdiB690fjKRhpYkzZVz/9ACFDEBAyVRcMvLh5jeyeGhc//QAhQxAgMnUNn7I95zf4PpnBmydCUCAydQ2fsj3nN/g+mcGzJAByAIy9VDEwzi/wfVPL1DIeU6+OWqo9FcW6ys7z+5YW0+fY3n055jJKjuumrPYaRmVXLh2cho/t5LHLv+y3fm5dN9ng4zAX2CyzlMymXc3qPmQ//Vde9JWlVvXFCeNE2N1jB+kDd0DD1PeD/j8SbVSebQ6jt+qhG5ZOpCElb1cNecq7drIrtm3LWHT7TVVrrG+TEUR0Y3bhmhc//Hj/rUpnoaR8048aNi606x+7XhzT5SauyNUU0w0qKyQrp9WTdcsaZXKw2M/a2ETRU3yL6v2Jxfu+2yQEaQG7GWdY6iOD2/2wPGFGuy4wWtGuYqxvxOrC+i/J9YllBl+/1qxRaUGOxpvVV2YNE6M3TEjTeeMsZTHCu3ayK7Zqta+JJk3nT1G+Roby3Byifd+MJz2f7EpST593Vb1m/WNz9fLqpfHOPZO2nOClzrS9ezJ1u8mns3egck6D8m3OFOrfMhWW1VyeuA2yVaCxpy17T0R2/zARlO0XfkEWcMxs7F0W0OT7TVVrrGsTGckdn5rd7JC1W/daVa/TE79+TJ5+BzZKSrtOblns+G+zwYZQeqAQs5D8i3OVCUfsmyrSjbTVhnO43qMMZqVJQW2eWSrSgot5bGCrw3LZzxH5MkNqecsNl5jWRneh4TPry4dkNdYt9m5ZnLqz5fJw+fITlFpz8+cy0EgG2QEqQMKOU/JtzhDlXzIvP5qzP0qGye7Y8ZdjngN2UwerY4rJsfSHWpwHcZrI2tXJrOTa6wvw2b8uTt1x4/rcyKz4jdu5WlWv3Z8WFlM0Q4riZld+XwzefizkEX+ZdX+5MJ9nw0ygtSANeQcw+n45FucoUo+ZFnuV9k42R1jM7V+ZizDWMcHGzrpJ281x52sHpk5NMGhhx1+Zi3YTB29pJyvVuUac5nenu6EeyfuCNcTEVYBM+cis/q148bPreSxy7+s2h873NSR7mdPtn038Wz2DmbIeU42feHT1V+ZMpCdZ3fMThnL6mBlrCV1WNEaSdrUn9/zcSf5at3mgNYSTGzoilomGDCrXztu/NxKHrv8y3bn59J9nw0yAn+BQga2iNmTjVNJNjqdBE1mK0cpq89VYoX9kiVoY2Yk6PIBYAXikIEpbLI86dXNtK4j9rCvKw/Rk4cPSzKhZlvM5Ir2EJ3yQmOS2TcwDj0D4cjU0BWhqU9uiMtZFEpUOD19Eaqbt04ah+xVFmNbhaHgmlCz8T4EwAhmyMAUfsCtbo+FA/Hfmo6o1ISabXlzZ39RKjX7Bs2hR4vb1csZCiUqxM09sTL8k4lfeZMQvzC2ZXwfJLLxPgTACBQykGIWK8sxt/otEbPNrMmycaxtUGXWNvX/8MSRNLQs8evJY91jDOa1iN31Ao9H2FANVxuUcdKTjfchADKgkIEUs1hZjrnVO+tkW8wky8axtkGX2Szu2BgDbRW764VsurbZJCsAVkAhA0vz6bjK2IYZ/De2YmDf5myMmdRmTBxryzG3fsnst0OVhkoMNMc4m8Uh+9X+qLJQ4K9tNt2HAJgBpy5gaT799OS6uCKTzTiyIW9qcgIFosXHDqaiklJPMsuSUfjhUGU3tsZjnLjCKg7ZMwFeO86m+xAAOzBDBmoetzYPuSA/BPUOP+zMxU5dfsjMyjhVDlVOY6BToYyz0VEqyPchAHZAIQPPpMpk6xa7BAodffbOSXY5fGXJKOwcqlRzKquWNcul7DQ/sR+OUloeYzdyq36mb8spfjt4WfXTaozc1AvyB5isQWBNtn7FoibF9oZDNO3ZRnrmyELL/MB8nlkOX56R8mRM//zk97KZqkwuxiqXsFVZo0zGXMo1xSEaXl6QVGdTVx+1hIlqSwuotsQ6Vnd5c5g2GdzRZXHIfA+c3n8PaIwqL6BnjhhqK7e+fZU4Yjf3m9/xybIYdq2fZuOrIjfiqAGDvaxzjHSOjyx/sD5/bboxyyPLD7t9ntmUVF4lP7BVDt/tH1lLG2O5GAScjOGrWWOU5GJUcgnLyhplMsMuP7Gx//p7R5YPmR382KdAjyyPsarc+vZVcgC7ud/8zC3M47PX05toVVeBUi5srS0VubM1B7IePJu9A5M1cIUbk20qsTKxTqguSsgklJBP2Ma8bZbDl/8KChK/PoUFBVLzbLtCTmWrnMfGsjahyLZ1GvtihI8Z22Q4Ltkuh7RGm4Lc+rG0M4+7XSLwMz5ZFsNulQub2+JlBDu5EUcNNKCQgStk+YP9ioH1OxZV5AeWaORKhfzAZjl8VWNfZeVk8cRWOY+NZY0ymWGXn9gsVpePyeKdjeMluwc0qhTkdjKWbu43v+OTZTHsVrmwuS1OMGInN+KogQYUMnCNVS7eoMSiarMMlm0g91JUxNba5Qe2y+GrGvtqF0/MMdHGXML62F87mYy5lGuKSZ6fuCR2nThPsV2sLn/GcedaDDqbq2Xlxbga9AavIavI7XQs3dxvfscny2LY7cZXRW7EUQMGa8g5RibGJ6UxsC5gJcxOSTInmaa2Dqpft5a23sp6fJzk8FWNfTWWc+LsJeuXMV/yfzd20flvNpnmLzbLT2x171jFoCec22+ClYXI+T2Wbu43P+KT9eMji2G3HV8FubM5jhrPZu8E5ykKspYgKWOGH2hmMbRm5mtZHVbvVT+zKieT0Sr219gvY75kVsZW+YvN8hPbyayaQ1qMrULMtNexdHO/+a3krPpp1paK3NmqjIE/BOtJCgKJU+eSTDuj2DnJ9KZZPJnjkdTZS+IglCC3Rb/8dAzS4pm1NlXQ4pD9yK1td77Ve7f1pON8v74Xmfh+Zfo7nS8gDhmY4jQ2MiixlLK8wuwkw+beWQsaqbW7jKo/aUww96YCq/jT+75oEbNco4OQQCd3fWeEXl3dIc5j+Td3RUydf2R9djLj+seydrr6Q16P5h3HmmhY6YDDldm1NMYhc2uPzJDH2drl1rZCNT7caT1O71E3ubT9+l6k9fvVtZKobAIt27SRTnsjQhXhNdRRPBbx0SkGa8g5hp/j4zQ2MkixlNrDi2eJrJj4QaKZe9Mln1X86aD71iaVf+f44eLVGDOtnSeLkX7z+8OTNtfQ99nJw1Mmk91YyeKQVeJsreqU4SQ+3Ek9TmQwi0O2O9+v70U6vl/l9YdSMS0ZOGC4tgs370fTprwkPRfPZu9ghgykWJlAZbMup+XTnWwg3fJZxc2amf/GVhYKWfhxHzGcx2Zko/zszbttbbEvCRb0ZmoZsrEyi0NmMfUOTHa5te1kdRIfblWX13vAKpe2lZOaH/dduu5fVsYJtRmqnjF0MW3JYsezoIM1ZCDFaWxkUGMpM5W72SpulmNTZfBxs/P4M1X53fTJTCartszikIsV4myNubWtcBIf7rQeJ/eAm1zaft13abl/2UytIkvY3JIC0qyQH374YRo0aJDl33HHHZdwTktLC1199dU0efJkGjFiBE2ZMoXmzJlDbW1tHsUHqcRpbGRQYinNZqAsD8eQDi+JJMT+pgqr+FPOY6xH/97svFSP7w27sZlxYOx4DdmuLWMcMv9rFmdrl1vbCicxzSr1jCxNjNVWxU0ubb+uW8q/X2UT7MvwBS4d62+7wP0a8ieffEIvvvii9LPnnnuOvvjiC/rd735Hl1xyiTjW3t5ORx55JH366ac0Y8YM2mWXXUQdCxcupN13351eeuklR+sNWKdI//i4Ma9lYmas4vTC4/PtqtW2cch+YhV/yqZis9mp2XkpM7P33zuDR46mYTWVtm3px7u8MEr3TR9CU4dbj6lqXLPV+aoxzX4nRLGLQ3Yqu1tS+f1KWkM2EA5Np85Rz+THs7m3iahoULDXkFmh8p+Rnp4euueee6ioqIhOPfXU+PHbbrtNKONLL72Urr322vhx/v/WW2+lu+66iy6//HIvfQApxo15LRMkOG11xt7LnF5U4pD9xCr+1MpUbHZeqsdXL5NVW0YnuXPfaLJ1MvIqu5OYZqsc1gz/NuD3m852nqHMTT/8um6pvP6ddf+OOer3e1nHlVL3mryZGZc0XkdlXbfE33eVXUE9g+dk1xoyz5q3bNlCRxxxhDBLM9FolB588EGqqqqi2bNnJ5Tn93x83rx5fokAUhBT6Ef8oV3sqR9tyJIomMXhtvXrEKu8wWaxw8Y2nfbLWK9qDmE7eWIJIWIda+gIJ31mVodZXfp2ZTLaxnqb1OcHWj+c3sfpSogStPzgbugtGR/7R5sh5okyZlgZ808e7U+vnLPGy1pTrGeeeWb82DfffEP19fU0c+ZMqqxM/BXK7/fee29asGABrVmzhsaOzZ8LnimcxDH6EfNoF3vqVxtaHVYxusw9nzXT7PfYb6Gc6O3N0rzBx/1rUzylIs+kHzxkEG1dU5wg5wU7ltOv3mujPkP+X6t+fdsSTjCVXjypnG5d2plUB2Ns6+r32xJMrHp5iguImroi1Cpxkq4sIhpcEqL2XqLGnpgmKjaYafWycn97w2UULWqkaGRLQmpJYz+tYr0H6otSKBQSWaL8iJvVzM3a7wDu25Cy5C1C9RivhXFu6WdClKDlB3dDUPYSyBhsEcig+dqXOORVq1bR1KlTqa6uTqwPFxbGTF7z58+nU045hc4//3yaO3du0nk8S2Yz97PPPksHH3ywZRu8PqGZxjds2EAjR46kkpI8ulEUsRqf/V5oFNstarBzyuJjB0vrcVLWDGMdxnpS0QbriKFlIaooCtF9B1TTDoMGfnOOenSztA6tXZm8XN+4qoKk42Z1mPVrdVvENocxl2Os2lKVxwquY/WPYspf1mfVfn7Z1EvnvNVKHb3R+Hjze7P63FxfPeMe2ywdQyf3MSft2NwdjSvNv+9fSUeMU1vvtHv2GOXTj3O24OU7mSvP5hGNoxJ+uPEl3Th4vev6nKyn+zJDZs/rSCQi1o41Zax5VzO1tbXS82pqahLKWbFu3Trq6xuYBvCFB+YYx4e3i+QdqvSrFK3dvcLBybim6qSsGVxHS1diHUxLV6yeWJ3e2zDWMag4Qk/s1kVlfKi1jVa36s3UvAtVcuXc7tffrabmzmR5w9GokDnxeDSpHqt+NXf2Um9UM4CZ18HlQuKQeVu90ago52W1qS8aFf3lcTbKaofWTz63goge3zV2HcTsuqXNsj6n11cPGz/6oubXT/U+7ov00Rv7dYnPxD1CHbQ6dtmUkT17ZPJp4xxrJ/j48b3PhWdzb9E5NLr0vvj7dd3nUL3Tm6Qf1ocTJ05Mn0JmRcwKmU1Tp59+OqWK0aNH59SvsFRhNT68XeQmXdL46tIi4W0sw0lZM2o+aaQGtlfqj5UN1ONHG7I6thtvUsfb8hmydk7tp420OWmGHKKaskJDP5KfTlb9qi0vopakGXJyHVyOsWqrKBSi2vLCJDmdUBgKxcfIKKsd+n7KsKrPzfXVU/j2ZuGI5aReP+4xDbtnj1E+/ThnC17GK3eezTfSRroxbqbmb2W6rqJnhfzaa6+JNWA2OU+YMEE6A25ubpaeq82MtXJOpv18wXPCtT5FyMaH9242bq1YVib/4jgpawbXYVxD5mNaPX61oVoHx/rG1pBjs079GjKfw3UZ15D1a7ZaG7I15HmHcB2lpjKprCHzeYyxLbM1ZC5T5HINWbs39LJy/b3hXqKiQopEotI1ZP31s7sehf1ryOzj5Pb66mG5zdaQU3kfGzF79mjy6a9Vtj2j/Biv3Hk2j0p7i57XkM8++2x65pln6N5776UTTjgh4bPly5fTtGnThFPXU089lXQul2enrqVLlyo7deVcrJvPqIyPkzhGP2Ie7WJP/WpDpQ4eny9WrqadJpjHkmpe4UZnH9nWkd80h+nM1xpN8xcb69fHFrMDzawFW8QarN25sphkfRn+/5OGbpGCsTUcpWpdfVo5q3ho0eeebnHv1I0ZS1UV5bZ5jq0wyuZnqI7Wj3Tfx6rPnqDlB3eDm/HCs9k7nu4aDnPijT0GDx5Mxx57bNLn22yzjXD0evfdd8UGIXr4PR8fP348PKzTjNN8uH6050c+Ybs2VKnqd3Ow2gZU9kCVbR3Jytgqf7ERfb1cdkWr2rl28vD/Wj7kjYb6tHJWSsJYl0qeYyvM6vMDrR/pvo9VyXZlzGR6y9t8xdOd89hjj4l1g5NPPplKS2PmOj1srjrjjDPEFplGL2t+z8fPOussLyKALEYWs+q1rnRiF4trF/frV/5iN/Vla37bbJU728G4Z8Ea8kMPPZQUe2yEt9DkWTTvysUhUbvuuit9/PHH8a0zL7zwQi8igCxEi3Vs6uqjljBRbWkB1ZZ4j0NOZ9yk1u4mSewz5y+2i0c1i+N1OzPh8zgmOfFY8kwnW+NMs1XubAfjniUz5A8++IA+//xz2mOPPWjSpEmm5XgDEN7FixXvV199RXfccYd4/fnPfy7ij8vLY2tVIH/Qtlzc3BNL1dfQlWyydVqXzOybSrR2tZ2fWPFqG/5rjkesqvmV36cjWQDvjGf1PpPj5ZVslTvbwbhnyQyZFXFTk8muJgY4DvnGG28UfyC/McuN6ya/a6ZyMMvaHV4aond/MFJ8ZrY9o3Ft0Uv+YplMsVjngcb7oqEk56og5axWJVvlznYw7ukn+70PQFZhlhvXjck2UzmYZe1quX2t8iBb1ZcKmYxjEdSc1XZkq9zZDsY9/UAhg7SjmWqHlcTiYoeVOTfZak4mMrNvOhxQrMzNVnmQrfriR75nOxN4UHJWO+2f33JnrZNStJeoL3155LPhfkkVmbhHfNnLOp0g1i13xkczfTkxgZk5mXAd+sQGVvmQ/RwfK9nt4lGdOsyollcZT2mMdIbvHZX+eTWXenFSyuT4FISXUeXmYykUbYgf66ycS+Ga89PSvsq4Z/r+yQVHNsyQQcbQvuBOHrBmTiZcRyYcUKxkt4tHdSqvanmV8Qyi2VGlf17lzlYnpYrG06gg2pCQFrC8PTGlbSoJ4v2SKjJ5j0Ah5wGpNr0Y8x37ZYJ1kvNYNR+ySltm+ZvN6lLNf6uv18xhxizXr13/nI6/VRl9fzjHspYT2U1dqYijdhu/bjfmgc2HHO2lUNTETJ0i83XWmvQ94vf+ABnLhwzyz/RizHc8tISotKhAOf+tqnz6chs6Ex92PX0R2vvpDbb5kLU62sIRKo2W0YPVvbSrYataLnPiKw1U3xn78o2uKKAnDkvOUXz9tGq6ZkkrNXT0UXNvbLZSZJH/VpYX+pLJleIXuB4O/5r0eH1CbLbWlln/nOYfthrz+au76NxF5RSJNlKEGpP6wc5pD5nkUvZ6f3E/7PJZe41fl8V+85hPfXKDr/mafc+HHCqiaKiK8yglf1bIx/0j3+OOiwpCImGSnr5IJG0WAqwh5xj68dn/xdhWihrslMFhNn6xx1PrE+o3Ytee8Xyz8nbt6NGcxCoMDxNjHZzn9b8n1tm2wzIx+uPchixyi49vOnuMJ/lldRpz7Or7p5nXZMjG02rMh9+/1jZns76PqtdPBWNd3M6b3x+eoAzMxtFJu5rC4VkPK2N9f+3qsXv2GMfP7H4I8hqyl2uaK8/mYfevFakoNfjHdoNP19EOzJBzlFTHEFrFE6u0pyqfSjt6WFl9eOLIhPVbaVu9iW3x/22StIF8jGedeoxxxvrjRkcup/LL6jTrn13dxvG0GnNZ/LRVH7lOv+4vmVzcz21riy3LuGlXi/3mPvDMWG+l8PL94PpU48/dECnekVpHLY95WUe6fJ8ZM4g7JnG9jNZpfp+uhCFYQ85RUh1DaBVPrNKeqnwq7RjrMH5xpG0VJcfoVpUkfx34mPFcY5yx/rhK204wtqXvn13dTuKQZfHTZvJoySb8ur/cxlB7aZf74Of3w038uRTOwWtFqCglyphB3DH5dx1dAoWcw6Q6hpDrG1cZu4H5b0Qpifeq7anKpy/HbRTpYnw5x7GTOkaVh2irsgjdd0C1tMzYilC8P9wXPvbA9MEJbfDaIL/W9tuXQjbxxsZx4jZY7mJJP4yx2VpbZnHW+rHheu3G32zMuc6/718p1qHNHgrauqjT66eCkxhqL/HrGtxfv78fWvy53f0go6TxOqqpH0Q1myaIV36fCfI57tjtPgJ+gjXkHEM2PunYSpJxm/9Wtby+nMw0rFJHW0cn1a9dY5svmjHGNc+bPpgmDR3IaqaSZ1hWr1WeY7PYbLs4a6f5h7UyeieeiiKiG7dtp723HU2DqipEuf9u7KLz3mii9t4oVaUoNthpXW7i162cltg0rlKP3bNHq3tI+GvaUrzdwFixmZlnthawEtZLwHdKy7DlRMXDKBMgHzJlJK811pDzgHRsJemlPdXyxjy9XuuwK5PgMNVJIvex3sFFJc+wXdtm/ZCNqVEefq/J4zT/sLSPRDT7i1J6b8cBmTjHMudsZjYY2nTSnipOZHfTrtUYeqVm05709b7fxd+v2FxHVeEKCkXbKRqqpI6q2ylSsZ+ymbqmYVvx2l18FnUPu43SST6ZqYOU1xom6ywkW2IEVeX0sz9mMcTpiItNJapx1po8qrHIxjrZx8kuVtosHttNzLeb8m7H288Y097O1Ul171j1HbH/n/Y3saKeCvu+oYLIevFa1Xy0mAmXNlySWFlRsklUvwFIafgBSjfZ8ozJNTBDziKyJUbQTXyx1/6YxRC7rY9nCLyeqqcwlGjGS8f10LexyRC3LJPHyRjI4nLLdTmU2URujPvWx2SaxQXrY6dTFY/uZrwtc1ArmJWZusKf0Ygt78XeNBI1hg6mwrpnqajrS9tztSvFCrabEme8XWVXUFnXLQnlEgg3pMV8nS3PmFwFM+QsIlu2/VOV08/+8LlrOmKhO/y3uj3ieXyM4U7G9+m4Hvo2jBG4MnmcjoHeiYdjs+fu1J1Qn3GetKXHPq81b46Rii1B/Rhvo9PSUwdvoqqNe1D1xsnileN9rRhd9l7CLHhw9PXYBxU7JmtSK6svK1gdPYPnUEtdE0lSWMdI01pytjxjchXMkLOEbIkR9BJf7CWOVRZD3O5hfPg83vEq8ViiQ1Gqr4ddnLFRHjdjoM/J3NvTTatXx7Zi5Pet3cmbcEQs4pA1jPG4qYpHdzPexhzUVRuPEeZk/Z7RbSM+UDJTaxRuvpkqe2K53vUShmkMFRaWUUHfN8m6WaJgWaZff30N3bjd9QnlO0vOpHSQLc+YXAYz5CwhW2IEvcQXe4ljlcUQV3oYHzv50nE9nMQZex0D2fWpLo3tUqYah6wvYyZnEO4Xrb7YHtHtCcdD0Y6Y+Vp2Tvk46XFWxvo1X4Znu511nwnl3l18plDU2h87aZnJ9FTD6VQ4/zOq/Pe7NHjh67Td28soPOwvlA6y5RmTy0AhZxHZEiPoJr7YjzhWWQyxF+zk4/ds5k3l9XASZ+z3GPC5HPetoe3XbZRNJXY6aPfLwB7RiXtNR0MVlmvJ67r2EmZl7a8xdIBt0ofuYX8RCprDmPjVymNa6+OgkhoaVj4y7d/xbHnG5CqIQ85CrExIQRofN/HFfrTJ+Dk+MvnS7fziJM7YbgzMMBsbzWvbLAzEKnY61fHoXuE144otp1KIuoQy7hj8sNim0m58iqKb4jNmaQxxnc2OWzZk2kyMOOTMgBlyFpItJiQ/Y4OdtOn3+MjqS7fzi5M4Y7/HQNta0062TMSjJ5mXe9bLjxvpXC52w6pq2IcKIt9SKFJPPcXHmypjK/M1J3nQm6T5fbZ/xzPdfr4Cp64U/nK02+nFj1/B6fgl7XTHGuOMyauMWvv6ejhPb1VJoWX7Zp+1uUu8pBzP6mTHLGM5WV+tysuONXX10qAy66+21fhpNHSEaVhFsaib5XIy3sZjfu96JGa2DSdRqCAszM59kXFUHH1NV6KMIoVjBma8HcuEJ3R5/X5UTJ/HS+ml5rCjHpqj1L6+f5xxSWRdYjN1YVXsM5f9UvnOpOM7n+kZer4ChayIExOlXV5UP8yd6TCZOs3vaoxL5a0YO3qd5601tq/pvsEl7IgTpcbwQBneA/r8SbW2Y8KfHfXipv5zy4ne3pxwrhNk8az1nRGa/M/Y7Ky4gMWMUm80pBxXG41GqKF7wEOZ+zqkrCCpD8b+Mdqx9p4I9W+qJbhicjnN2TNxDfCez5pp9nsD65uyMfjl20300Er5rxa78dbLw8cu2LGcrn6/zdccwWUbz6SSvudiyrTfsbyAjJ7MXcJ7uoJnwNqh5tiLpZrhXbMkG3VorGgP0SkvNIr7Oukeaymh0xaud/WdVMn1nO64d8Qhpx+sIacgT6hdXlQ/8sia1eHn+DjN7+o1P7Jd+2Y0nWOfn9dMNu1cNw+ufZ7ZpFTWS55nqz7IcjXb9W/QfWtNy2j3zp5vxfaxtqvTjTx+5Ag2rtkyURNFazxuVk5l7ZfHZ6+nN9GqrgLl66N6v6vkevYz/7SqHPmYDzmTYA3Z5y33rPKiOq3LD3ncYtcPFZmMOJFR1r6V+dVqTPivpavP9FwjKjJOqC5S/vKYbTepkidZ3wdjeX4viz3Ww+Zrq74aj2/RWR+cjreKPOWFTab3UHwNuH2p/Nz6YUIZ+4l+7Zd3y7KC+2zYuMzy+qje71b3gh/1q5KONoA1MFl73XLPJJ+m/h7W59N0UpcbeWxcWZSx64eKTEac9FPWvhna2qbVuNaUFdImiULSr4s6Mdc5kc8yrrZT/Vxj+VjMaIg2mPzYYPRryWZrwPrjQ4rdj7eVPP9vm1vp/217T+zNppjy492pjGboOC2xjTU4llejmHpNZ8Hh0HTpGjJvyiErrxGmnalz+EuWZmoNvg68tajq9VG9363uBT/qV8WPZxPwBmbIKYjPs8un6UesXzriBZ3mBTXGpdYWe8tbq7Wvweuqg4uT1zSN7cfzFk8fnPDZwLnRpHPdeE7rx4dV1KjyWIwwx/9yPLDs2uhnG3p5R5YlbqjBfTWeG8/pXDbwmb6OaoO+5TVkI8Y+G98zp08wd/ayGm+jPPzK5adULRfKOL7lZL8DlUZRx7/ia8L6v2IaMK+X1x+UJIs2s+0pPI46Rz0Ti/Uduiz2OmqN2JQjTBMTZsH8Xnw+aEn/5h2LlZRxvP87dZvGnnv5Tqrkek7Hdx5xyJkFa8g55mWdivEJkpe1lhO4LWyen3fp5m4667VG6UyX8yF/vWoN7TQhOdaWnbJYGWvwQ+nTk0fZyq4fH7N4YavZt6qXtWodbr2sjfeOYy/r1iWxPZ3Z07jjWyoqGUzF7Q9Seccc6Zpvd+gU6h71N6quH0YFEtuOWNOteYuocrLpunHLyPVEBQr3eb+XtRcS4pBLSlPiBZ3NXtaZfjbnAjBZO8TJTWqnxPz4UqXDnOQ0XMUYl+pVRr25X5/P1iw/Lytjq7zBVYX+muv042MWL6yay1jfVyOqddgpY8Yu5IlhZazVbVo+0kXVG7anYrYxMwMO3HFkI8jHSqOPU3fkNuFhbuppVTmZqHuNuZAqypjxqIyNWN0XXu53le9MOr7zMFNnBpisQZygOm/o8+3aOZ14cUxxaq4ztpvK3MoiftqiDid1qRI/v/7hpM/YzMyz1poNo4QyNpqbjXs7m7YRbqW+aOJjSGxL2Z+cobjlHqrZMjnpPP68teYRT/0DIGhghgwCG3sok8tuFutlpmvMBKQiF+dM5jSInBnKbOxUZLK6BsZ4bH0dmgnfKhbY6fX8sqmXfrxoPX0+bUcq5kkyi1n/M2IH7M7+sKCK5jNtla0KRaXD6aJlf6E7d7yYCkMRikRDdO2y2XTVzF+ZbkvJLGzYj05/fTeqLF4fmPsVAK9AIQNLU2jQ5OKHL7/y7JAVkmwWq1LGCjvlnSCXXk1YjJ2dTFbXQKaMtRm87DzG8fXsWsluaeLfG996kz7f81ShjPUpl4UBu34SdY7k9IQK8VEGjLl+u0tiWY/O3/1EmrRwBvWGO6mouHxgbHQJGvTssngJLW1hh7VIoO5XALwChZznBDUHqplc29YW285iVWe6fslllFHWrpVMdjHUxnhsPnvR90eIepJigTkOWK9Fba5nef2hVExLxP81RDSikuil/frbMRTXPJ87xbptsVQp65Wu/nw+/sLGfei4D++l2uIGqigaEXOYsxqbwmQPcKYhzDt9RQJ1vwLgB1hDznPi5lQKVuyhnVyq8Z3pkMvJ2Mk+s+qrFu+cUN4iJ3FlSYGj68nKOGHNVwtNshq69qXUUTtvIJxIl47wXxv3FDl8r/ziWuqOEPVGSbwe/9/bhTJmmsPDTGOzjcgSNwTxfgXADzBDBp5NvH5hnOUERS4jerkK+9eQefMpLzJa9ZXjnY17itudpzRuwkztgsrJ1EuTqaWiSXhZL9uwgi5d3EHfhcfo2ruIJi38EYXDHVRcXEHXT6umz5a0Kl1Lq8QNsT73BPK+AMAriEPOMbyMT6bMfnZOZX7K5ef94yRHsZs6ncSDq2RcEttSlowiCjfEFFzZBGl8r/XOVom7Z5m1Z3ZNrfrn1Lkw3fcrnj3WYHy8gxkyiJMps5+dU1lQzZFmMcd+1WlEJSex7FjStpQ6wlRCxdSTlH0h0bO5kFprXo/FBCvKbnZNrfrn1LkwqPcFAG7BGrJDnMR2Wm6iH8C4X7OYVr/klI2HnUOTG6xieRktH7JeHru2rOSxq0elbj/r5fP0n8m2pRzYnrIntpXk4I9o4+D19EH7+7SO7qC+wm0oEhpG4YJtqH3YIltlrMmj/bmJmVaN1TZLkuEWN/dZKuK+jXUE7fkAUg9myFmaD9lPzHKx8rrfNUtaPctpNR48y+FYXj2RaIT2fnqD43bNxlU7vr6tj9ojA/mQQ/2/SIf3ZwyQtcXnnvTqZlrXEVOOdeUhevLwYaKMvl8hST2M1XU2k1dfL08Ch5QQFRQU2NbL552+sIlYXQ0vXUs3b38PnT3mCfsLxGvJZRNo/tdNdO6icopED6EIHUKFoV7qi8YeEXP3ajbNHc39OPGVBqrv5LzOev9n+5hpbTxUYrVVcjk7wc33UJYPmfEzv7lKbDvITbCGnKX5kP0cH7NcrCy3vh9u5bQbjyn/rKfVMU0pYKXd56Jds3FVyTts1pbsXK2MVb5mWW5gu7q91svnPTX1XDp2xDvxzyy9pQ05gO3yT5vljlbJg50UMy0ZD00p6Z219IrIKpezG5x+D83yITN+5zfXk4q8x6kAa8jewQzZ51hdqzzCWtKAIMX9WsXVGvvhRk6V8eCZgNUGEirtmo0rt6OSd1jWltnYcKwvm02t8jXzeVFDR+zq5s/d1svntR0yKWkzD6txZXpC05TzT8sSUgjztEUOZKuYaeN1tYrVtsrlrLIvtxE330NZPmSncd+qsnipD2QvUMgKBC0fsp9Y5WI19sONnG7Gw027ZuPK7ajkHZa1ZTY2HOvLSsAqH7IsN7Bd3fy5k3rHlH9Lazu3piV77UN1m5vFXh12M+KC+Z+JjTnKCzuosmTr+MxLJb+zTPHFEk8UmOZk1mKm47Ir3PeyYyq5nJ3g5nsoy4fM94LA5/zmehBnnT/AqStL8yH7iVku1vsOrvVFTqfjwZ+7addsXLXjlfG7PaZ1QoY8xrK2+D3nN2ZlxX+c51grY5YP2Sw3sKxu2ef6elmhjSilhDL/3e+HFDliEq0+6FjxWlfeHN/UQ4a2qcb60BmiDt4li5WxUZ6/718p1i9lDwVZ3mR9P3hceHz053If+B6y668qKrmcneBGHlk+ZNV6rJy09HXwWPI9F5TnA0gfWEPO8nzIqYhDNuYTfmD6YJo8tNS7bA7Hw+34mJ0nPIB7uumLlatFPmQqKpHmMTark5GVMcuHrNoPs89l9ZbX70fF9LmjxA76dWLL9vrvneF1Y2hQVYVjk7B+jD5u6KYfvy7PSe31vndrpraSW0Ueu3zIZvU4cR5LRWx7vjybcwHMkB0StHzIfqLJo+UTXt8ZEa/83g+cjofb8TE7Tzuu5UM2y2Nsdq5ZGbt6VOpWqbe8foQjZRxLY1hMHbWPOpJH364TxacfI1bG+ntIS3qh0r4dfipjt/I4uc6aM5tsLKzqCNrzAaQeKGSHeIkNDHpcoRZD6jafcBBIhZxO6nQTPy2LPe3tSf4RxDHDtrtq6faVXrB5b9oyciP1VhzlSgYtDlqlP37lpNa3q9KWk8/clPNKtn+fQHqBU5ciXmKHgxZ3bCefMS44G5xKUjHGTurUx+IyoysK6InDhlrKoNVfHf6ONhdsJbynZ291Hf1i/MCMdk3oUqoZ9nOihqekdSRcqSjRl22j6KAl82hT95hYuMyUkIP4V6LecBl1RLdQS+9AmcElIRpSViDtv9kYuXFc9BK/r3qt0v1dDJoTJwg2WENWxEvscCrjjlMRh8wOJSWFIdN40EDQvJiodj/HY6w0Pi3vEpWMpD1eLFO+blbxymZ8/vnBtM+gj5OOG9MW6qfFCVtaRok+btmett7xPZGBaVnP9pZxvKpymyHrj9m428UU+x2/r3r9vXwX3T573IxFNoI1ZO9ghqyAl9jhoMUdq8jHFsMPTxwp/g+CjHrK6+uoWJtudPBezOXUOnKdwzF+koguI+ptIirq9/juXE7lTdOpmPp3gmon+npfotc270IzljxqWadZLG67rHzncqLybam8fhjtM6jXNkxJ9rkWT9zYU0xHf/Qsfbp9lIoqJ9OOleQoD7Rd/KsRY/+t7m2nOam9xO8zKtc/U9/FVObnBrkFFHKKzU5BN1kFXT4jrIxDhveqfSivH0Q1RDSCraCNN0vrTzgjRDR96CeWdVrF4lZq5duXUnnLT4RDlqDf4dlOGVtRs2ARtfVyeJhaXmE38a9GjP1XGXdVWbzG76tc/0zf60H9ToHgAKcuRbzEUAYt7jjb5IuzZYH8ePNi2z7EwoX6kyr0ZzOS/cmYVv6d7bjoY3GHlDQIs//H+x0g0hvWtBwQ9462ascJ1cVDfLlWifGvBTSqOEK1hp/pvIbMsbeytvy8d7zE76vKkTX3OshLsIbsEC9mp3SYrLIxH7IdxS33UHn7bPk6qhZjyzl+i4fF+tDznUiWQJEuooLYGKjk/ZXB9UeIFUMNdQz7J0WKdzQtW9pwCZWGH0g45nY0rb6UXWVXUEftNb5eKy1Gm++dujFjqaqiXJiLV7b2KjlB+XnveInfd2Kudypvpp89QQfj4x2YrB3i5aETRGWXDfKxMjYqYY1wv7I1p5C6Cs5wrQhju3mxjbmJqhr2oe7iM6l72F+SZazfgYppg2MFbKZ4e+gg6iq7nGjw9NiPjc5viCp2iK95+/3FFftr6/5nWCmq5ij2897xEr/vxFwPQNDIO5O11/i/XIsftIv5tPtchpc43CT6BtLt6WkpfUrMjONmaNO/PiqL3J+kKKMmf2HamVoq51PLoCVJbXIdpeF5VFU/mgrCy6i37Qsqr99L/CBwo4yZCA2hliFLYzmJ65poY+3n4rWr7jnqqj4oVqh4GFHN3nFlbMx37DQftJN4YCcxtLL8zU7jsrmsWd5s7VVLNOGkXjf3cRCfEW7i3N22A9JP3syQvcYfBj2W2Cl2MZ92n/sxRkrlC032Kx4yMzZzVCBJGUeJljRtS/dufpTOmTxeyDAovIKaiifGZKgpieUINqmrkDqoatM+A8dsNHE8y1J/OVYNfTSK1nSW0dlLb6d14SK6YMdmuvr9NjHeUVor8iBHDWPP1+SM/zRRb399vMf1c0cNt43FNct3bXZ9vmzqpR8vWi/q2dyVqMhkTlCy/M38f1MPUbR/vd4uLptlPO5fm2hjd+w9x0Q/eMgg2rqmOC775p7Ec2qKQyIHtZfc5H6SymeEVV5uP8m151y2kTdryF5jgdMZS5yO8bGL+bT73I8xUi1vXEPurJxL4ZrzXa8Nd0eKqOyVj+Ntmsngdt3ZmOrwy7Zqmrz4LZpe/S09dcJ0cWyvp9bQVy1qtWtjL8tXrBKLaxZrbBxv7d455eMqWtE6oIi1hCNmMbR2eZTN2tMjk5Hb3ao68fo4rdfNfez2u5XKZ4SbOHc/2klHnDbIsxmy1/jDoMcSO8Uu5tPucz/GSBr/HO6Ulg8XH0Jhdtxi87VhxtxdfFbckcq4zmzcRKOPCqgvWkA//O+f48dbLWTuoWlUEl3iKERJU8S8Y9bR/72Lvu3cIf7Z5+Ed4qbAljDvx6xmRhWzza5eab7itu4+y1hcq3zQ0ljdKFG7NgXvh5Uxx6XLrr1KHmXLuOz+e6G1O1npcr2y4yr9MJPN7j52SyqfEVZ5uf18BuXacy4byYs15Hj8IbmLP/R6ftDQYj716GM+7T73Y4z05Y8etpC6Dt+VvjloNxqyYQQVdfxLHNfWZ2uaponX8o2HJ9XTPew2sebaUXm3SKTAyQOj/Z7IA++L6fj/3k6Vr74vZsYvNcyIn19tIXNX3b9pu7eX0b3fzUzYI1o/+9XDx99rGi1yDu+0aEGCMtbXLRsrK3jsB5UVJV0Tpqq00LTOhHzQEqSxuiGiyiJ5PTJk94oZ8bhsA3ysujQ5YQTXKztuxC43ubFOv5Vxqp8RZvcL52L28xmUa8+5bCQvFLIf8Yfa+aPKQjkRv2gX82n3uR9jrJV/evdfUGlBr3hYhihMFc2n9jtKfZXgoBXfWENCb82PqKVuE7WMXCcUdM/gObr3m+jUKT+knohmRotp1LO2LVHKWXzTujtpzBtf0LS336L3ytZRe2hikoLmv3CYaJ93XxXncV84X69Z3fOmD074jMtq4y3WqSVjz696XclryCqxuGb5rs2uz30HVMfrMYs/1iPL38xtsSrlZzn3heOy7eK4+TwNrofr1ctuhNeQveYm95NUxjhb5eX2E8RpZ5a8WUPWcGt+yRZnB6fjY2e+c2PeUx3j0oaLhdeynblZf1x4P5dvS25pauugL1etpV0nJo6Pm5zF7GVdVDqcmhqeokF1P03w5tWPmf5c431kzDWtH2+zsefjVukgrZYJRHiTTT5kvndWdhY4vt9l+Zut8kibyc5/xn7r6+N2OAWjn7nJ/fxupdLE63Q8vbSDOO30kzczZA23N7KTnKbZhN1Dys1DLD7Gei/oaC9Rz3rxL4cMVW3cQyhjxztXeVDGWn+GFFvIbILU1Fq1kwhJ0pSxVr9xzPTnGu8jY65p/blWZmI3sbjacZXvgJv7XZYX2uqHg5mMsn7r69PyITupNxVmajNSqSydjqeXdkD6yQunLq/ku7OD034ad6wyzngjVEqF1B/fooA28hwj7FRe6czWpU3IzCFJw2z2qZ/dGZ2UrBJW6Pug1W9s12om7KQvqvmMve6Q5RW3O3Fl8ruazc+JVDjAAXOgkFV/lRpyBBeGsvdLlmozPStj/cgYR6nARBkPKN7hVEyb4sd76EDqqnvekbx8vUKhEIUjMWcibS1s1oJGau0uo+pPGumRmdb5imX16uviuNA17ZG43LzuOUgX48to50UiEdrSk/xjwOg0o2+ruICopy9CDf3DxbGnc/eppSvfbZHGo6pcL2OZ66dV0zVLWsX7iiKiG7cNUUdLX1L8cX1nhO77ooXOn1SbkaUct/mO9f1L91JTtixzZTp+G+TxGrJbpvyznla3Dzyk2MHi05PrKON0LCOq2DEl46Mck6hPYxhuoJqGbS3N0EkhSf2v3XQCddfdO/ABm7hL3MeK62HZGTcxlrJxMNal0p6sjPEhbZefmB2TzGKRVa6XsYyxvq3KIlRUXJQQh6yn6ZwxGYnPd5vv2Ng/L/I5/W5ly94FfsVvYw3ZO5ghK5qceKaVeCyzpqjy+t2pmFbE3jTzrHIiddb915/Ko73UGy20NVuWNF5HZV23xD/nUCP2blahr3AbCkU7KBqqoI6q2ylSsV9yIQfK2C63L38WjTpfdpDVK6tLpT09bARc9P0RSc5fdvmJZeZ2jke12uZSb/o2ljHG6Xb0sWzm8dG8baW2hpuupRzVdpT6l6alpmxe5kpn/DZIBKObpfF5rIwTQ4L6lbMHCpqfF85W1Rsn06CGabRLzTdUW9xg2mdWxnoZ+D3HEHcXnhDfG1qPdqyn8DhqG/EBtY74VLxKlbFD7GJ7+TPOWez0GsrqldWl0p5dPKxKfLIhRDjWVknMkczuHpXVb4zTrSgkqmJbuQmaMk7n90K1HaX+pel7G8RnhirpjN8GiXga4eeff56OP/542nrrrWnkyJG0yy670Lnnnktr1qyJl7nxxhtp0KBBpn/fffcdZQOBis9jM7WT4zaU108Scb9VHWdQYd83VBBZL15f3u1YapxxMEWOmESPTPlNYp/ZTG2Av8McQ1za95R4H6ZKQ+KGfWOJE0bEQp0o5K+BJjG3b0gsK+ivF/9xXO3wkohlfK1xY33ZtdfiQkMGZamP8dWfxzG2RSbxsPr29Odw/SPLKCH2lM/j41yPMR5VJVbe2BeuTx9zPHen7ngccqXh6cCx0pn6Xujbsbp2Vv1L9/c2UM8Mh6Qzfht4XENmU9xll11G999/v1DGM2fOpKqqKqqvr6dFixbRPffcQ/vuu29cId9888106qmn0lZbbZVU14UXXigUsyqZXqcIhMkp0kU1G0ZJ8wK7GR+VPZu1m6Sz7PcUHnyx0nnxXMXda4hKx1K6sPKy5vH5dtVq2nqr5PGxc8Lx6mUt2teZ/azaM/OytjrHiRORzNyr5UPW7h2tjN5MrTLmqcJr/7zK5/bZE4hnhkucmKkz/WzOBVxNUe6++26hjM877zyhbAsLE7+svb1aZtUBZs2aRQceeCBlO5n8YrE5uKL5TJErKDkv8ER3lTa9qVRM63V512+pvP63IsEDrxlrZmtT0qyMGaOZNulzE4Htcv+abfto9d54TP9ws2rPrA9W56jmLjaTu9ekjJ0yNuu333jtX6bIVmXMwEydXhyPdmdnp1DCEyZMoJtuuilJGTNFRbnrK+ZnXlWndbEy5q0lQxTpV4LFtK58kZiFOnXo4lhhsU905/eSPrMymWjrxZx9iR24OmofpSiF4ntIJzekroy1PLdm7/26DjLHKG7LKvevVX5YTvygyaPPVWx1rpXTj/a5sY9W54g8wTa5i7X6ZDl1jXHI2uv6th7L62DWP7eY1WU3XkHKhwyAWxxrzoULF1JTUxOddtpp1NfXRy+99BJ98803VFtbS9OnT6eJE+UztcWLF9MHH3xABQUFogyXZTN3tuBnXJ6ruiJd8ZmxRl+0jyY+W0Y9kbVifc8YI+okVlj/WONHl/2ciAVoo96Ko6ilolHIV77xR1QcfS3+cTgUSzVoxz2fNdPs99ri748bV0TPrR6Yr+n75uU6sMnTGIf8bUs4Xp/xkc1OOMubw6Zm0uve30K3LO2UtsXjV1UU81qW5R+OO/10JrcnywvMfTQ759XVHaIPRgftDZ0RUZ/WR+1zsV92KJaj+I9718TjdAtDEYr0lVH3e1tEzLQR4z3mZ5ytXV3cR941zKmTFOJpQU6vIf/hD3+guXPn0sUXXyyU8fLly+OfsbK96KKL6Prrr48f09aQjbAC5xk2ry2rrk8wPT09tGHDBuFEVlKSviD7cY9tTorLW/2joWmta0TjODFDluX1ZdafOlRtfMINNKJ1ckJKQY7Q2VjwFNGg/amw90sa1H4ORbpWULFum8mE8kS0cXBsK0yvZupRj262LcN983od9nuhMSG+lp2DVrdFkhTZqPIQVRSFhHPTOW+1Jp2z+NjBynLr0Z/LfNnUK+rv6I2atmfso+ycQ19uNs1HbNZHfd0quYyN18FsPPX9c4JdXcbrzrx+VC3tMKgobd/bTD17sgWMjxwn6+mOZ8gNDbEwmDvvvJN23XVXMWPefvvt6ZNPPqFLL72U7rjjDuHoxd7WzOTJk8WxAw44gEaNGiUu2Pz58+mGG24QypsV89FHH23b7rp168SMXIPrSRe8aVFftDxhO4u+aJS+/m41lRWkr66Wgptom/KrhMm6x5DXl1XkFytXU1WhbHx6Ey41m2xHSIwT37ZsRUWtq3nuQb3Rx+kHS4pofXcJ7Vz+Ec0Y/l+6baeB9eLvumZTQxuXNcPqswHaxCVNHA/Z1iHcN54tuh077jPPjPWrNM2dHG+duJs2G94fndohxrG3pS3pnNbuXuEU1i6V2xrtXG0Nu4KIHt81Jhsf4/aaOxPbi8k+0EfjOV3NbUljoqe5K7mPxrrV+zBwj8nG09g/Vezqkn1n+DoVNNfT6tb0fG/1pPPZk41gfAbgJV0zq7EvCpm3AGT4F9DDDz9MdXWx3ar2228/4ejFipcVsKaQv/e9xDXK8ePH009+8hPaYYcdRMgUz6ZVFPLo0aMz+ius8O3NpF+uKgyFaLvx4zzVxTG+zeFhDuo6jTbRacI8POrxdsNnIdppwriE8Skv+FbMdEPRdoqGKqmp8j7qK4rl6H1w6Ul0xugn4mc/uO4kOmJyogwVnzTyNJw+75xKn6+aSi81nkeLjyomKqwSqshd7yW8bZxphqR983od2Ey9qWdgFlZbXkQthtkj16e1JTunurRIeGgL3nE2Q04414TaTxpps2GGXGTTR+OYJNRXVkQtveYzZK5bfYbsYGwcYleX2+vu5/cWM0BrMD7ecayQa2pqxOvUqVPjylhj5513Fs5eK1asEOvMVuFMBx98sJhJf/7559TS0hKvV3Xazxc8na71vPZkXIty2/7SQ/5A2xU/En//dXgWlZXd5aCGMpq7Vyhh3ZXX9/Ty8PgMbvkxFUb6NwyJEg3u+LHYiIN34tphmztpu4XXUXF4E4WLh4s1u7KyxC8Rr7Hyuh47z/B6nShT6f8XjWW3W0PW+ublOnB/Zi3YLGZf/MA3riFr9RWVlMbXJqVj0D9OV0wud7yGbBxjmYzGNWS7PmpjYlSsw0pDCX20XEPuiVBhQZQifTHry2aTNWS9HFZj4xS7utxedz+/t5l69mQbGJ80riHPmzdPrB8feeSR9NhjjyV9fsghh9CHH35Iy5YtEyZqKw477DB6//336csvvxS/qrIh1s2P7eOM8bvxeF0XTjCcPai6dGBP5Pj4jK2j4S3TxCYfGhEaRtHC2viMuWPww9RTuIPjzECpwhjvahX/6vY6mMUhc30rW3uV4oJlXtZa2kV9rmK7/MNu8gJb9q1/THjcZCkatc/N4ppjySXaaf/tx1BVRbko19ARFtfAKvTJz/vDri7X1z2N+ZDzFYyPdxzfoVos8VdffZX0WTgcFrPjyspKGjZsmGU97e3tQmlz2aFD3TlZZGVcnj5HsMpxm5hMnkmZ5atlpasnRM0JO3FVNJ6m9CBNVxyl8aFvpQS8XAfZGifXZ5UD2GoMBpUVxeXRK0In+YdV8wJboZXncZO1qX2uz6mr7zM7Vc3+YsA6wK+jqkps45D9vD/s6nJ73RFPC7IBx3cpm5lnzJghFC/PlvX8+c9/pubmZjrmmGNELHJra2uCF7Y+lvmSSy4Rn/M6ci7HLSdRPMzZcYcxmewhPbniBBravAdRtIf6QmMpUlBHfQUTKRpKDIvi5A5svlZtM9VYxcb6KY8sDtkuxjdV8tjF+LqpX0Vesz5zZJEsdtmLfPo63I6TLE7aC17rSMf3AeQfrjThLbfcQocffrgwXb/44ou03XbbCS/rN954Q5grrrvuOlFuy5YttOeee9Luu+8uPLHZLL1x40Z6/fXXae3atWLNWSubT3QXnyXigPXvnWAWj8rHi1vPprKCVfENpDtDE6lnxHti32hOHEF9AzNxzrRkt590OnK6Oslh60UeWRyyPi7YmPO6LxKhvZ/eQM09UWrujlBNMc+GC32Rxxh7bRZH7qR+rayVvLZ5vtl7uyCkHL9rJZ++Dp73Di+P/f53Mk52Oa6d3ote7+cV7SE65YVG6uh1LwMAvudD5gQSHLq0YMECoXhZ2R511FF05ZVX0vDhw0UZdtZihcsbgqxatUo4epWXlwvl/P3vf5/OP/988T5v1ynYTO1gZix7sOidYHYcVECd3+1Mo0o3xsut7x5B5eM/F4q3ILxMmKnjaQ8HP0yR4oFcypnK6eokh60XeezONea8FqFIkm+HH/IMum+tba5hp/Wb5VK2OsfY57rSCH34w+HS+F1ZPlwr+Yw5dVVlUumTkzpU5VV59uz19CZa1VWQlTmOU01OPZszhGtb8dixY+muu6w9g9lzmjcRASa4VMYM/yrnB0FSvts+jlQdgN8XRwuFcmHlq3lZq2RaSkdOVyc5bBm38tj1RZbz2swq6VUeMzO10YnNyfhb5VK2Oicpz3c0JodKPlw7M7+xDhWZVPukWoddfU7q4HKGzcKyJscxyA7g6ZBKjI5aYvtLfzEmIbhw2e30Zft4WtM1Qrxe9OUdyQ8LxbSH6cjp6iSHrRd57M5VkcMvecycpIzHndRvlUvZyTlsVWY5VPLhWskny6mrIpNqn1TrUJVX9fx+q7trGQCwAgo5BcQTNzRsK17L1x9PNfXDqWbDaPHKWZtSxTV77EaHv/8C7fPuv+mYj+fT7/fdK/A5XZ3ksPUij10+ZDM5OMcxP8eHlZBv8hhzC8tyDTutXytrJa9V/Vo+ZCf5cK3k09fBPzVGlSfmpzbDLD+0LMd1uu9nHh8ep2zMcQxyeA05U2TDOoUszjjxfTG11G1K6fjUjRkrYkn9Ih1mOSc5bN3KY5UP2U6OVMijkmvYaf1u4p9l+ZCdxO9ataWvw6qck/zQXu9FN3Xonz36zWNA9jybgw5myH6jFE/clxLztR6/HxbpePg4yWHrRR67vZbN5EiFPCrK2Gn9buKfzcqqxu9ataWvw6qcahy4H/ei1zqgjEEqgEL2O/5QyVGrkKjAn1+QfuZ5Neub3gnJTTysV1n9jvnkpAN+oMll1i+V/styE8vK825gVufo8yfrczL7gd91uc0P7UWudOZDzsUY5VzsUxDJox05vKGZ07YOL6Fvi6dZxh8a44w5L3BxdFF/PuNC6qhN3FDFDX7meTUzFRpjZXlvZM0xRiUeVqvvgh3L6er32xzL6ncM9MCYlYukA27HTJOroaOPmtlhXbfnNNen0v+ta4rpxFcaqL4z9qDjfaWfOCwWF62/toxelXBscXu/bq4rD9HcfWrpkkVN8b2v9fCa7TNHDMRau+2nX/mOT3p1M63riMRlf/LwYUr5oY0yMKpypTMfcjpi9tNNLvYpyGANWZHelaNoSMmAmXlLTxkVTTDJB2wWZ8xmap9mxsYYTy1O1M34mMVmymJljWVU6jNiFtOqKpffY+YUs/5p9an0f6vqwqQyWv+s4ndldVmVdRpnq793/Bx/2ZgY65PF1mtmbP05jKpcfl1zxu67lY6Y/XTjpE9YQ/YOZsiK5hpWxpwhR4Pfb7FzDDGar300U5vFiTrFzFSoN5HKcBMPa5TVan3S7xhoqzFzss+xVf+4Pjbvq/S/pStZYfN5shhgS3lsynKdbpNb+DX+ZmPGGab09Rlj62Xn8TkJX0QLufy65iqkI2Y/3eRin4IO1pAVKGp929HxVCOL8ZTFiXqJzeSECVa4iYd1IqvfMdB+jZlV/7g+dtJS6X9NWbIzF58niwG2lMemLNfpNrmFX+NvNmaVJckZqbTyZufxOapy+fk9CULMfrrJxT4FHShkFWr3S4xbYkL9xzOEapyol9hMY2wsryE7iYfVynI9bmT1OwZ6YMyinsZMk6u2aOBW0NdnlPvGaZVJ/ecyHFfLCoL/OL5W65/+2hq/oLyGrJ3D53PZEaVyOXkN2cuY+Tn+fC73US+7WX1mcciaDE7k8vN7EoSY/XSTi30KMlhDVqS8vo6KdR4nYSqnzrp6yjRG85uX8TEzReljZd3Ew5rJ6lUuN/D4fP3datpuvPf7R5PLrF+fbe6mM19rjDvE3HvQIJo6vCxpzbStJ0JVJQVJDjP6enkJQbNaLOV6/7MlIcHBtrXF9NmWHvrx643UFo5SlQsHHLN7x++tUhlZfapxyG7kSmc+5Fw06ar0CWvI3sEMWRFWvi11TdRS8ZJ4DYIyZvw0v5l94fSxsl5iW93K6vfDrcynIdPkMusXK2N9XO25bzQlfK45LG3oikpzWuvr1S8hnPVao8hdrI/XZVlYGYv6JHG8fvTTr7rM6nOaj9qJXOnMh5xryjhX+xRE8k8he92QI4Nm6qDGBJrJo5qX1239bsvbOUKpxvFa5ehViatVjbvVYne1P55RG8+TOZPp6zOTO1W4uWaq8ufidwiAvPKy5v2jK5rPTIgF7q04irKJoMUEmsmjHW/q6qOWMFFtaQHVljiX12l/7cpb5UPWYlZPX9gk7hCrOF6VHL1mcbV6h6WkXMShaELcLX/eGw3Rxs5IPBZZZO0y6JKNXREa/8j6JI/ihq6IqM+PXNKquG3DbrwyLR8A6SBvZsisjEMUphBFxGtMOWcXVia9IMmjHd/cE4uRZcXgRl6n/bUrz+/Z1Lupp0C8Gj8XG0jo3nM9sjb17azpiIp8wrI27RxiWJEb3xvr5teIYXavvWfnKNZhrIhloVI89np50nH/eGkjHQ5EQfsOAZB/M2Rhpu6T7yftU2xwvsUEmsnD5l6neXmd1G92vkq+Y6vPhZk6ah/H6yRHryxntVUu4nBf8jErhpcVUCQSke7SZZRH64uZrEG4R63GKwjyAZBq8mOGLJRuYcr2k87HmEAzedh5xmleXif1m51vV97uc5ZbFtNrjON1k6NXNV5bFmNrBZetLrVOTuFHLmlV/GojVfd00L5DAOSnQuZfwrXzRNrDaCwK1Zf9pPM9JtBMnnhe3pKYSZXz87qR12l/7crb5UPmGNVChThev3L0avWMKgtJY2y5bpZB/yUt0o3nvOmDk+KZR5bFYpr9ziWt6gQVtHs02+QD+U3+xSFnkZnaVe7ZDMQCWpmRnebldVK/m/Iq+ZDZfG0VniNrx00fneT/1eBjHIfMoU/68zgOWfvcTh6zz2T3jlsnqKCbgb3mQ0acbTIYH+/kzQw5TpYrYyZoDzorM7LV517rd1vebrtJYb5WaNNrjl4n+X/1PxBYGRvPM/6AsJLHiaxunaCCdo9mm3wgP8k/hZxj8YupjvHVEla4acdr/LAx37BVfaptiVjeqHXOZ6cYE3EYY4k1+Rs6wgl9cRN3axaHrM+H7BVtLERbDmTUt+9XDHpQv4NBkAHkHvnhZZ2D8Yte5bE7X8sjy8qLHz28b/OwikKldrzGD18/rZquWdIazzesMbgkREPKEreYVG2Ly8XzD0fLqe7DRnry8KH05rrOhJzPvO/2+ZNqlcbwuve30C1LBwJnz9q2hN7a2EfNPVFq7o5QSYio3URHPjpjkOO423ge5u5EZcDv6uat85zz9x/L2unqD8v5J0b/XzIyGfU5h/mjISX9Ga08xKAH9Tu4oj1Ep7zQmLBtKeKYgV/k3xqyS4KW69RMHtXxseuPWU5elX47HStjeSc5flXbMsvHK8tb3HSOWr5cq3zRdnAf3/z+8KT8v1YPd2MfWPlOqC6klS19CUF9bnP+2vVHk9koo0r+Zj++L5n+DvJ3a6+nN9GqroLAPAeCBNaQvYMZchbGL3rdZlAlJtcsJ69dv/2IH7bLB+w0tlZm5mVkOYmNyTTMsMsXbQeLPaG6SDnuVjZOHIf8+veG01YPr/ec81fFZD+0rCDuPKZhda/4+X0JwneQ2+o03EaIYwZ+gjXkLIxf9CqPSkyuWU5eu3b8iB+2ywfsNLaW33M2JSOynMSMnTJm7PJF28FiawpT1YEsKW7ZJH+ym5y/Kn2W5Va2ulf8/L4E4TvIbZUbhhVxzMBPoJCzNH7Rqzx252t5ZLVHDa8hq7bjNX6Y29bnG9avIbuNrU2I16Uoja2IrUUbcz4b31txxWReb6WENWQRf11WIMau0uLb5SYvr1lf/cr5e8NubGaMOs6trG+fPdg5P7MsBt2rI1QQvoNzd+oWMexBeQ6A3AJryA4JmnkqKeeww/Gx649m+nTTb6/xw8Z8w25ia420dXTS6jVrkuKQVczUZuhzFetlMcrPXtbchtdUgKZxxB5z/mr3zuCRo2lYTWV/Mg52opLna7ZqXz8G+oQZfjhCZeo7qP9uFZWUBuo5EAQy/WzOBTBDdkjQvoSpjvF1YlZ1Wrddeb0J3a4+J+Z6WRyyW2UsM18b4681+YdVFPuSl9esr37l/NXGIpaMwzxfs1X7+jHwO6FDEL6DQZAB5B5QyMB3jKZJzQEqW2I3jTG9dvG9Tpzp7I6ZteUlr7HbGHI/8hMjzzEA6sDLGviGMU70gBGF9MDynvjnlUVEoxRjmTMl/3H/2hTPnhTq/8XKj3hZfK+TGGhjOUZ/7IIdy+nq99uSYolVznXSruq4v7q6Q8xo9fRFYluKunLGQp5jAGzBGnKOkcnxkcX6yshk7KbV+NjJb4zvdRsDzeUYlbZUznXSrtW468dm3GObk2KL2dTf4CK+WVOWqvHWQY1RxrPHGoyPdzBDBr5glyc46LGbLE9rt/WPCX18r2pcrKwcv49Go7ZtsaNZ0rkcTx0KuWpXddy5j7JLydZgN45jyHMMgBpYQwa+YJcnOOixmyyPXW5hfXyvkxhoefxwgW1b7FylkjNZtV3Vcec+yi6lm/hmo0ypIOaol6iQC0NQxiD7gEIGvmGME+W4XD28hhzk2E2Wi2NoNfhxziraLL7XSQy0sZzxGMc/y2KJrc7V51FWbVcVbl+vzrR17aASMlgNjO8ByAZgsga+ITNN3nbgQJxu0E2ILP9Xs8bEMkJFovHZoJmZVtUUa1bOeIyTWhjbkp3La7ICG6XjxVTMDmWN51TGvb79CqlKBdy/sME5ncUO+v0GgJHgfstA1mJ8CGpxutnycGQ59QrIThk5iYG2O2bWlr6c07heL+PO8gRZGQdlW00A/CDY37QA4iTOMR0xkeloQ5bnNhWo5Nk1O+ZErjYbR3Bthmwnoz7fsVXOZq0+J/2LJcToc5QPWSajV/yIwbbqu18EYVtNDS99RRx1fgOTdQriHNMRE5mONvR5bnmuMbx/Z32/2zPri759/Rqm/tgNe1bR3cs6lcbhns+a+3MflxO9vTkp93FCzmQiGl1RQE8cNlTUp5eRHYh4jbKlO5KQr9mYs5nh+tZ2REUsM4/emMqBOmX927qmmI56cRM1hgfq1OQ0y4eszQb9vCdksjmNweYyJ726mdZ1xJR6XXmInjx8WErig1Ptya2Cl/FHHDVgEIecgjjHdMREes2HrIJVnls/+2TWF2P7mlVSNVeySr5ffe5js5zJXJ9qjLX+PEZ2jlX/tqo2z9Fslg9Ze3h7ve+s4pDdxGBbjWc2Yvfd8jL+mc717AeIQ/YOTNY+b/+Xjq0C09GGXZ5bv9oz6wuba43tczEnuZJV8v1qx81yJrNsPBaqMdb688zimttN+tcbJWo2ydHMjnGyfMjv/mCkUMZ+3hOya6/FYAs5Fdoyi0vnOOpcNMt6Gf90by8KggsUss9OI+lwMElHG3Z5bv1qz6wvsjy/XEw1V7Jq8gjtuFnOZJaNx0I1xlp/nllcs1keY94Jq9YkRzM7xsnimfVJHPy6J2TX3mkMtllcOsdR56KzlZfxh1Ma0IBCToHTSDocTNLRhj7PbWF/TlyV9pz+sneS59d4jNdXzcbBKMdAruOoNPdxQs7kENG4yoG1YL2MXIY/M+ZrNuZs1urTHqsss75OWf/4s8HFiXVqctpdcz/vCbscyypt8THurzaePBZBjUH3A7sxsfpeBMkpDWQOrCE7xInTSDocTLzmQ1ZBluc2FY4pTvL8Go8Z43TN5ODx+WLlatppgvn4aA9OmSz6dvT5jhmznM36B7Fq/7SMU7KZvd195fa+k907dltlqrRlNZ7ZhOp3yzgmTr4X2Rw7nelncy6AGbJDnHxZ0vHFSkcbsjy3MrzmvXWS59d4zEmcblWhwlaMJrIYzbKaLFY5m7X6nPQvZkIvdHXN/V668NqWVd9zEWNfnXwv8mmcQDJQyMAXguKYouRwZCNSOmW2assqFjpIDj9BkiVoBOV7AbIDxCEDX0hX3lsvcrDpcNaCRmrtLqPqTxrpkZmxeOBMxIJatWX2WTrjer32AQTrewGyA8yQgW8ExTHFTA5WHitaI7Spp0C8Gk2HXk3uTrBqy+wzfl3dHgtJ4r81HdGUyuilDyB43wsQfDBDBjm1W5KZHHY5c9OZU9fOjCn7zCwWWovrTfd4Iwdx9n0vQPDBDBn4TlAeOnZxsXrTYTpjQa3aMvvMLBY6U3G9iJ11DsYG2AGFDPIGNhVOrC6g4SUR8ZrKOF4VWczaMvvMbVxvqhyIYIoFwF8Qh5xjYHzsx+fbVatp662s45DTNZuxasvsM9W4XqdOV27vnXwxxeK7ZQ3GxzuYIYO8g7eotPw8jcrFqi2rWGgVGdPldJUPyhiAdACF7JCgxQ+mI/dtqnLtZiznbDR1OWzNEo6onu+kPavzZE5gqYp/tcoFDQBQB17WWRpzmY7ct7IcwOGI//mQ05lz1hiHzPiRw1Y2PnZ1O+2LVr65J0rN3RGqKeakEwPpF411bu6KpNTpSrtvNL2vzwWNeGQAnIM1ZEWClq/Uz3zIsry8nPvWKgdwpvrvd85Zxq/69KjU7bQvZu3pzzOW4Ws5rKxAKGO/15DN8mVn+ruRKrBGag3GxzuYIWdhzGU6ct9yvl6rHMCZ6L+X6yA7l2N4KRTyrb6EusNRikb9i3u2as8qhpmV8YcnjrTdk9rPfNmIRwbAHVhDzsKYy3TkvuXEBlY5gDO6LaYLOWTncgyvn/Ul5zwu8C3u2ao9lRhmv7HKl414ZADcAYWcpTGX6ch9K8sBnOn+e+m3LA7Za31W4+N3/mKtPM96hSm6hJRjmFOBdt/IckEDAJyDNWSHBM0U52c+ZLPct7IcwJnGS85fWRyyl37ZjY/f+Yv1Zm+nMcxWuL13tPsmKPdGrj57gg7GxzuYITskaA+cdOS+leUAzjRe5JDFIXuqz2Z8/M5frDd7+1WnF6xyQQMA1IFCBr5jlcc31W2kArP4bAAA8BN4WQPfsMrj61fMdDrjwc3iswEAIBVghgx8wyqPr19bOKYzB6+26QXPj/mV3wMAQKqAQga+YBZX6+cWjn7GX7uNz4b5GgCQKqCQgS84yePrNk41nfHgZvHZqYjpBQAAxtPT5fnnn6fjjz+ett56axo5ciTtsssudO6559KaNWsSyrW0tNDVV19NkydPphEjRtCUKVNozpw51NbWhquQQ1jl8fUrNjYTcbbG+GwAAAiMUxdvCXjZZZfR/fffL5TxCSecQFVVVVRfX0+LFi0SsWhjx44VZdvb2+mYY46hTz/9lGbMmEEnnngiffLJJ3T77beLsi+99BJi1nIEdq7iPYyN8ahmx/1sIxWwA9emsytN47MBACDjCvnuu+8Wyvi8886jm2++mQoLYxvpa/T29sb/v+2224QyvvTSS+naa6+NH+f/b731Vrrrrrvo8ssv99IHEDCstn9MdRupINuVca5v2AFAruD4SdPZ2SmU8IQJE+imm25KUsZMUVFRfCb94IMPitnz7NmzE8rwez4+b948SideHYCyNZZWhaaugR9SQZYzFaSijyq5ke1yGqvWKzuPQ8Q4+9Pkf64Xr/zeCUG/7kGXD4CUz5AXLlxITU1NdNppp1FfX58wOX/zzTdUW1tL06dPp4kTJ8bL8nE2Y8+cOZMqKxPjN/n93nvvTQsWLBBrzpqJO1V4jV/N1lhaFa57fwvdsrQz/v6KyeU0Z88hgZMzFaSij7I6Gf2x66dV0zVLWqXtquSnlslqPI8/2tjd/2FnrH2VtIhfNvXSjxetD+x1z4f7EuQnjhXyRx99JF55Zrz//vvT8uXL458VFBTQRRddRNdff31cITN6Ja2Hj7NC5nJ2Cpn3SWV6enoSXlXhxPQrWvtnHJ38fjMtPnZw2s5PVV1G3IyPXhlr72dP6UqpnJnCOD6p6KOsTkZ/TItxlrWr/4wngfx+9Y8KbWU1nhdXxv20hyPU1tFpar7WxuTsN1vo27ZoYK97pu5Lt8+efAHjI8eJj5RjhdzQ0CBe77zzTtp1113FjHn77bcXjlq8TnzHHXcIRy/2tmbvaoZnzzJqamrEq1bOinXr1okZucaGDRuUZe6NErV2lyVY6Fu7e0WSAdm+xn6fn6q6rFAdn2ZhpS7nPCO6o1H6eMXqtMiZKXh8UnEtZHW2xJcCBo71iVzJoaR2+fy+aOL14LJfrLS+Hl2R5PP4Ourfl0T7qH7tGlv5ORd2UK97ur4/Vjh59uQjGJ8BeOJqNiH1RSFHIrFfpiUlJfTwww9TXV2deL/ffvsJR68DDjhAKGVWyH4yevTo+K8vvuAcZsUyqFL9SSNt4oT02vvSIpHxJ13np6ouI07HR7T6TmwGN0CIdp04jqo/T52cmcI4Pqm4FsY6a8piX7OG8MCxwlBIzGJl7Ra+vTnhMy6704RxVL3UWlbZeeOrCqijN0oVRSG674BaGjeoyHZsOBf2pp5oYK97Kr8/Vrh99uQLGB/vOFbI2qx26tSpcWWssfPOOwtnrxUrVoh1Zq1sc3OztC5tZqyVczLt5wvuxBTwyMyhYt2Jd3aq6F93KisrSdv5qarLDCfjw2vGxjVkPjcdcmYKbXxS0UdZnYz+mLaGLGuX14yNa8gqssrO47Vnp17W9x9YQz9e1BbY657p+9LpsyffwPikUSFvt912lmZo7Tiv+W6zzTbif1bQMrTjWrlU4jV+NVtjaVVgB645e8a8rAf1z+aCKGcqSEUfzeo0HjNTlmbxz3aymp3ntF87DCoK9HXPh/sS5CeOFfKBBx4oXr/66qukz8LhsFCy7EE9bNgwYbrgWfS7774rNgjRe1rzez4+fvz4lHtY6/H6Bc7WWFoV9Mo4yHKmglT0USU3slW7KvmpnZznlKBf96DLB4BTHH9z2WGLd9xixWuMIf7zn/8szNO8MxfHIodCITrjjDPEFplz585NKMvv+fhZZ53lWGgAAAAg13C1U9ctt9xChx9+OF188cX04osvCjM2e1m/8cYbNG7cOLruuuviZS+55BIRq8y7cnEZ9sz++OOPhXf27rvvThdeeKGf/QEAAACyEle2LZ4l/+c//6FZs2aJuOS//e1vYsZ8/vnnC0XLpmoNNlOz0mbFy2Zu9sDm15///Of07LPPUnk5h2oAAAAA+Y2rGTLD6768D7UK7Oh14403ij8AAAAAJJPdu+YDAAAAOQIUMgAAABAAoJABAACAAACFDAAAAAQAKGSQlSAXLgAg13DtZQ1AJkAuXABAroIZMsgqWBl/09JH6zsj4pXfAwBALgCFDLLKTM0zYz2c8QfmawBALgCFDLIGTibAZmo9nH4PSQYAALkAFDLIKnjNeJuaQqorLxCvWq5hAADIduDUBbIK5MIFAOQqmCGDrATKGACQa0AhAwAAAAEAChkAAAAIAFDIAAAAQACAQgYAAAACABQyAAAAEACgkAEAAIAAAIUMAAAABAAoZAAAACAAQCE7BIkMAAAApAJsnakI8vACAABIJZghK4I8vAAAAFIJFLICyMMLAAAg1UAhK4A8vAAAAFINFLIiyMMLAAAglcCpSxHk4QUAAJBKMEN2CJQxAACAVACFDIANcN4DAKQDmKwBMAGx5wCAdIIZMgAmIPYcAJBOoJABkIDYcwBAuoFCBkACYs8BAOkGChkAExB7DgBIJ3DqAsAExJ4DANIJZsgA2ABlDABIB1DIDvHi1AOHIAAAAGbAZJ2GmFTEswIAALADM+Q0xKQinhUAAIAdUMgpjklFPCsAAAAVoJBTHJOKeFYAAAAqQCGnISYV8awAAADsgFNXGmJSEc8KAADADsyQHeJFoUIZAwAAMAMKGQAAAAgAUMgAAABAAIBCBgAAAAIAFDIAAAAQAKCQAQAAgAAAhQwAAAAEAChkAAAAIABAIQMAAAABAAoZxEHCCwAAyBzYOhMgXzMAAAQAzJAB8jUDAEAAgELOc5CvGQAAggEUcp6DfM0AABAMoJAB8jUDAEAAgFMXQL5mAAAIAJghgzhQxgAAkDmgkAEAAIAAAIUMAAAABAAoZAAAACAAQCEDAAAAAQAKGQAAAMhWhTxlyhQaNGiQ9O+YY45JKPvwww+bluW/N99806++AAAAAPkXh1xTU0MXXnhh0vGtttpKWv7oo48Wily1PAAAAJBPuFbItbW19Otf/1q5PM+cTzvtNLfNAQAAADkN1pABAACAbJ4h9/T0iPXh9evXU3V1Ne2+++40bdo00/KffPIJbdmyhfr6+oSZevr06TRkCPZMBgAAADwp5A0bNtDPfvazhGOslO+9917aeuutk8r/7W9/S3hfXl5OV111FV166aVK7XV1dcV/COhfQSIYH2swPuZgbKzB+FiD8ZFTVlZGqoSampocJ7696aabaN9996Wdd96ZKisrafny5XTnnXfS448/TuPGjaPFixeLWTPz1ltv0eeff04zZ86k0aNHU2NjI73xxhv0+9//ntatW0c333wz/fSnP7Vtc+XKlRSJRJyKCgAAAGSEgoICmjBhQmoVshmsWFkpX3/99fTzn//csuwXX3xBhxxyiJgpf/3111RUhMRTAAAA8hdfnbrOOecc8fruu+/alt1pp51on332ETPmL7/80k8xAAAAgPxWyEOHDhWvHR0dKSkPAAAA5Cq+KuQlS5Yob/bB3tYffvih+J/XnQEAAIB8xrFC/uqrr6QzWj5+7bXXiv9PPPHE+PGPPvpIqoy57IoVK+jAAw+kUaNGOZccAAAAyCEce1I99dRTdNddd9F+++0nZrYVFRXCy/rVV1+lcDhMl19+Oe2///7x8hxvPGnSJPGneVkvWrRInDNmzBi6/fbb/e4TAAAAkHU49rLmMCaONeaNPjZt2iRmy7wWvMcee9B5551HM2bMSCh/zTXXCFM2z4ZZGZeUlIg45SOPPFJ4YnOCCQAAACDf8TXsCQAAAAA5tJf1888/T8cff7yYSY8cOZJ22WUXOvfcc2nNmjWWG4ewCZxn3JdddhnlMk7Gh8fl4osvpsmTJ9OIESNou+22o2OPPZaeeeYZyvfx+eabb+iiiy4SO8yxHwOH4vF5L730EuUadmlQ+e+4445LOKelpYWuvvrq+L3D2drmzJlDbW1tlK9jw8tyzz77LF1wwQW01157iWfO2LFjxcZHbDlk/5hcw829k6/PZq8EajeOaDQqLtj9998vHqYnnHACVVVVUX19vVh3Xr16tbj5jfAOXrJUkLmG0/H5z3/+E8+wxUsEvGNMU1MTffbZZ/Taa68J5ZOv48PLKN/73vfEA/aoo44SDxRegmFlPmvWLPrVr34l/nIFVqa8Va2M5557TmzUw0pFo729XWRo+/TTT8UyFDtq8jIV+3zwWPKPFidbAubK2Hz77bd01llnifvqoIMOEvcO/3B5+eWX6YorrqBXXnmFHnvsMQqFQpSv904+Pptz0mT917/+VaR05LVo3lKzsLAw4fPe3l7pjl78kPjd734ntuPkX/S8Qcmf//xnyjWcjA8rH3auGz58uJgNG0PLzMYyX8bnpJNOEo6I/OufFY/GqlWrxLhxWf5lX1paSrkM7zu84447CqXCW9zyTJi54YYb6I9//KPYa16LnmD4/1tvvZV++9vfCgfOfBsb3u6Xf4yceuqpYttg/Q8YtjxxKCf/IMy1H7tO7p18fDbnnMm6s7NTPER5Fsd7ZRsfpoxMgXC41R/+8AcxM+JfcrmK0/H5n//5H/FF4VdZnHeuKWOn48PKlmcxhx12WEIZjqHnPdq5Pn7I5jovvviiyMJ2xBFHxB+obGl48MEHxSxw9uzZCeX5PR+fN28e5ePYcKQI/+DTK2OG32vJdtiCkA/Ixicfn81+Epin8sKFC4U5lU2svA7Dv0J5ja+2tlaETk2cODHpHC7H5hD+jB8UKlt2ZitOxocfqDwr5vSWBx98sIgFZ+94Ps5fDDa18abnuYTT+4fXi3kPdZ4l62fIbFngX/u8bpoP6UE1xXrmmWfGj/G4sZmfzZAyxbP33nvTggULxJq8bAkpl8fGiuLiYvEq+zGYb+OTT8/mnFTI2gYifDOzyZDjlDVYebDzDSet0MOzv48//pj+/e9/i3CqXMbJ+Hz33XcixGy33XYTJkc2oelhJ6dHH31UOFrkCk7vHw7H44cErwfyOuC2224bX0PmWfZ9991HuQ6b519//XVxHxx66KEJCpmR/QjWjrNC5nK5qpDNxsaKhx56SLwaQz/zcXzy6dnsJ4GZJjU0NIhXTuNYU1MjZjz8C5xnOvywvOOOO4QXowY7m/AaF3sQT506lXIdJ+PDioVhJ5wnn3xSnMMmWv6CsALi4/yaSzi9f7bffnsxO+YfJ6yEeV2LH6is0HmWLcvpnWvw+jk73fB6qH5Wx0sdDFsXZPD46svl09iYwT96+X5i69Phhx9OuY7V+OTbszknFbKW65h/TfHF5lAUXqviHcH4ZudZDj9UNWcCzRxi5v2XazgZH60sm43YkYIVDIccjB8/nm677TaaNm2a8DJ+++23KR/Hh/nggw/Eg5PHhT3O2VmHZ9k/+tGPhHc1h0nlMjxePE68jn766adnWpysHhv2sGazLPtq/O///i/l8/jk47M5JxWy9qubf1HV1dUlfMZONmxG5JADXidkcwiv8/FsKNe9YN2Mj1aWOfroo5Pq4hAoRkvukW/jw6FOP/7xj4WS5lkxn8NbwHIZ9i7mNWVeg3/nnXcoV+EfIWxB4BmdMYG6NpbNzc3Sc7WZsf4+y5exMcJhTmxtYqcmtrTkw778VuOTj8/mnFTIvGGFlZlMO97V1SVMrvwrjdcu9MHpHFfK8Pofv+d40lzByfiwuVUzI8nK68vm4/iw9yevs/N2r6yIjXDCE4bvs3x0yNlmm23EK293K0M7rpXLV2eu+fPn0xlnnCG2DtZ8D/IBq/HJx2dzTjp1aQ9Bflga4RkNPwTYw3PYsGF0yCGHxHMp69mwYYP4xcrrg+wJyuuDuYKT8eHwHt5FiE3Sy5Yto3333Teh/JdffqmcJjMXx2f9+vUJ685GtOO5+gufQ1V4bX3w4MEidtYIK1q2MrDTG4d+GeNt+Tgvf+SiQ5fd2OiVMSskLsfK2MwBLt/GJx+fzTmpkHlWx96J7IzDv8D0v77Y4YbNZyeffLJQNueff760jjfffFNcdPayzbXgcyfjw/AaKCtkjsn95z//GVcurLAeeeQRqq6uVvYezbXx4ZAnNreyYuHyeq9YNsXxmjOvj+mzluUSvJMUr/XxJg2yHx3cd575sWPO3LlzEzYG4fe8dWaubgpiNzYMO2/x/cUzPVbGuWopcDM++fhsztmduniNjx1t2EuYg83ZDMkmkDfeeEM4TLALPe9NbAZfdDaN5OpuME7Gh2OOzz77bLHvLpdjpcNrf/wA4Qxdd999t1BQ+To+rHQ5JIzXkbks/3LnX/EvvPCCUDicicwYZpcrsKMbr/PxBhacFlUGz4R5XJYuXSrunV133VV46fMPGHaY400hysvLKd/Ghn/QsjWmu7tbbM3KHvxG2PKkbVmbj/dOPj6bc26GrM1yeP9ldqzhOEf+8vMDlH91XXnllWIbyHzGyfjwLIfDfNh0zY5LrID4Fy2/59nNAQccQPk8Pvxjhc2u/MPkvffeE7/e2TTLpjT+LNd+rOi9y/mByuvnVg9UHgtWumxh4R9x/EDlseQfKuw9m4vKWGVs+EcbK2MtN7wMngXmokJWvXdAjsyQAQAAgHwlMF7WAAAAQD4DhQwAAAAEAChkAAAAIABAIQMAAAABAAoZAAAACABQyAAAAEAAgEIGAAAAAgAUMgAAABAAoJABAACAAACFDECWwHmaf/WrX1mWmTJlCt11111pkwkA4B9QyABkkAsvvFBkDbrsssuSPvvlL38pPuMyDO9J/pvf/MZR/aygtZy0o0ePFknln3nmGQoC+PEAQCJQyABkGM4rzIkKOjs748e6urroiSeeSMg5zDloOW2mU66++mqRA5uzXnGmJs64w6kn3cCp9wAAqQEKGYAMwxmmWPFyViUN/p+P6RO5G03WnGbylFNOoVGjRolynPdaRlVVlcjUxKkC//SnP4lMTS+//DL19fWJ7E18Ltcxbdo0+utf/5pwLs/OZ82aJc7bcccdRRktbzRnxeJUgxMmTKBTTz2Vvvvuu6Tzbr/9dtphhx1EJi6e8YfD4XhfVq9eLX4saDN4APIdKGQAAgCn63v44Yfj79k8bZfC76KLLqK1a9cK5T1v3jyRbrOhocHynKKiIvHHM91IJCLM2A888AC98847IkXlddddR08//XTCOTyz/vrrr8Xxxx9/XChVzgXMiv5f//oXzZ8/X/x/4oknJsyg33rrLZGjmuVjRf/II4+IP61/Y8aMic/e+Q+AfCdQ+ZAByFd4pvv73/+eVq1aJd6zSfkf//iHUGoyli9fTq+++qrI+cxmaIZno5zv2gxWlnfccQe1tLSIteTi4mKhEDV4pvv+++8LxfuDH/wgfryiokLUXVJSIt6zUmZlzsc47zZz5513ivzSLO+MGTPEsdraWpo7dy4VFhbS9ttvT4cffji9/vrrdNZZZwnze0FBQXz2DgCAQgYgEAwbNkwoLJ5BRqNR8f/QoUNNy/OMkme6U6dOjR9jpcdK0Mi1115Lf/jDH8S6dGVlpXh/xBFHiM/uueceMVtlEzR/zkqbna307LzzznFlzCxdupRWrFiRsL7N8Pk8I9bYaaedhDLWYMXLCe4BAHKgkAEICKeffjrNnj1b/M9rtn5x8cUXi/VcVsYjRoyIz2rZkWzOnDl0/fXX05577ikcxv7yl7/QkiVLEs7nGbKe9vZ28UOAlbkR/Y8I/sGgh9vlmTUAQA4UMgAB4dBDDxXrs6y4Zs6caVmWZ8O9vb300UcfxU3WvM7b3NycVHbIkCE0ceLEpOO8bswm7vPOOy9+TD/DNWPXXXel//u//xOz+pqaGnILz7rZsQwAEANOXQAEBDbv8toxK0q9qVfGdtttJxT4pZdeKma0rJh5Jswe1Kpss8024rwFCxaINWmeKX/44Ye255100kliJsyz7sWLF9PKlSvpzTffFE5h7GSmCnto8/nr1q2jzZs3K58HQK4ChQxAgOAZp+qskx2p6urqRAgRm7vZWYpnrapwPPKxxx4rXnlG3tjYSOeee67teWzCfumll8Qa8hlnnEF77703/eIXv6Du7m5HcdLsUMZObLvttpv4cQBAvhNqamqKZloIAAAAIN/BDBkAAAAIAFDIAAAAQACAQgYAAAACABQyAAAAEACgkAEAAIAAAIUMAAAABAAoZAAAACAAQCEDAAAAAQAKGQAAAAgAUMgAAABAAIBCBgAAACjz/H9yjZA0FI7nrgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw the original scatter plot along with the predicted values\n",
    "\n",
    "fig, ax = plt.subplots(figsize = (5, 5))\n",
    "ax.scatter(heights_with_predictions['MidParent'], heights_with_predictions['Child'], s=10, label=\"Child\")\n",
    "ax.scatter(heights_with_predictions['MidParent'], heights_with_predictions['Prediction'], s=10, color=\"gold\", label=\"Prediction\")\n",
    "ax.legend()\n",
    "ax.set_xlabel('MidParent', fontsize=10)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95647042",
   "metadata": {},
   "source": [
    "The prediction at a given midparent height lies roughly at the center of the vertical strip of points at the given height. This method of prediction is called *regression.* Later in this chapter we will see whether we can avoid our arbitrary definitions of \"closeness\" being \"within 0.5 inches\". But first we will develop a measure that can be used in many settings to decide how good one variable will be as a predictor of another.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1c953a85",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.861589Z",
     "iopub.status.busy": "2026-08-31T06:02:06.861528Z",
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     "shell.execute_reply": "2026-08-31T06:02:06.866681Z"
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    {
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       "      <td>female</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    family  father  mother  midparentHeight  children  childNum  gender  \\\n",
       "0        1    78.5    67.0            75.43         4         1    male   \n",
       "1        1    78.5    67.0            75.43         4         2  female   \n",
       "2        1    78.5    67.0            75.43         4         3  female   \n",
       "3        1    78.5    67.0            75.43         4         4  female   \n",
       "4        2    75.5    66.5            73.66         4         1    male   \n",
       "..     ...     ...     ...              ...       ...       ...     ...   \n",
       "929    203    62.0    66.0            66.64         3         1    male   \n",
       "930    203    62.0    66.0            66.64         3         2  female   \n",
       "931    203    62.0    66.0            66.64         3         3  female   \n",
       "932    204    62.5    63.0            65.27         2         1    male   \n",
       "933    204    62.5    63.0            65.27         2         2  female   \n",
       "\n",
       "     childHeight  \n",
       "0           73.2  \n",
       "1           69.2  \n",
       "2           69.0  \n",
       "3           69.0  \n",
       "4           73.5  \n",
       "..           ...  \n",
       "929         64.0  \n",
       "930         62.0  \n",
       "931         61.0  \n",
       "932         66.5  \n",
       "933         57.0  \n",
       "\n",
       "[934 rows x 8 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "galton = pd.read_csv(path_data + 'galton.csv')\n",
    "galton\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1439a362",
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    "execution": {
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     "shell.execute_reply": "2026-08-31T06:02:06.870291Z"
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    {
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       "      <th>MidParent</th>\n",
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       "      <td>57.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent  Child\n",
       "0        75.43   73.2\n",
       "1        75.43   69.2\n",
       "2        75.43   69.0\n",
       "3        75.43   69.0\n",
       "4        73.66   73.5\n",
       "..         ...    ...\n",
       "929      66.64   64.0\n",
       "930      66.64   62.0\n",
       "931      66.64   61.0\n",
       "932      65.27   66.5\n",
       "933      65.27   57.0\n",
       "\n",
       "[934 rows x 2 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights = pd.DataFrame(\n",
    "    {'MidParent': galton['midparentHeight'],\n",
    "    'Child': galton['childHeight']}\n",
    "    )\n",
    "heights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2f7abf7f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:06.871357Z",
     "iopub.status.busy": "2026-08-31T06:02:06.871303Z",
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     "shell.execute_reply": "2026-08-31T06:02:06.872510Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def predict_child(mpht):\n",
    "    \"\"\"Return a prediction of the height of a child \n",
    "    whose parents have a midparent height of mpht.\n",
    "    \n",
    "    The prediction is the average height of the children \n",
    "    whose midparent height is in the range mpht plus or minus 0.5 inches.\n",
    "    \"\"\"\n",
    "    \n",
    "    close_points = heights[(heights['MidParent'] >= mpht-0.5) & (heights['MidParent'] < mpht+0.5)]\n",
    "    return close_points['Child'].mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e8c0d8c7",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2026-08-31T06:02:06.976915Z"
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    {
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       "<p>934 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent  Child  Prediction\n",
       "0        75.43   73.2   70.100000\n",
       "1        75.43   69.2   70.100000\n",
       "2        75.43   69.0   70.100000\n",
       "3        75.43   69.0   70.100000\n",
       "4        73.66   73.5   70.415789\n",
       "..         ...    ...         ...\n",
       "929      66.64   64.0   65.156579\n",
       "930      66.64   62.0   65.156579\n",
       "931      66.64   61.0   65.156579\n",
       "932      65.27   66.5   64.229630\n",
       "933      65.27   57.0   64.229630\n",
       "\n",
       "[934 rows x 3 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### The map() function in Pandas is a tool used for applying transformations to data, \n",
    "### primarily within a Series or DataFrame. It allows for element-wise operations and \n",
    "### value substitutions based on a provided mapping or function.\n",
    "\n",
    "heights_with_predictions = heights.copy()\n",
    "heights_with_predictions['Prediction'] = heights['MidParent'].map(predict_child)\n",
    "heights_with_predictions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "53b5aadc",
   "metadata": {
    "execution": {
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     "iopub.status.idle": "2026-08-31T06:02:07.016020Z",
     "shell.execute_reply": "2026-08-31T06:02:07.015799Z"
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    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115b94410>"
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     "data": {
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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "ax.scatter(heights_with_predictions['MidParent'], \n",
    "           heights_with_predictions['Child'], \n",
    "           label='Child', \n",
    "           color='darkblue',\n",
    "          s=10)\n",
    "\n",
    "ax.scatter(heights_with_predictions['MidParent'], \n",
    "           heights_with_predictions['Prediction'], \n",
    "           label='Prediction', \n",
    "           color='gold',\n",
    "          s=10)\n",
    "\n",
    "x_label = 'MidParent'\n",
    "y_label = ''\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37123aad",
   "metadata": {},
   "source": [
    "## Measuring in Standard Units\n",
    "\n",
    "Let's see if we can find a way to identify this line. First, notice that linear association doesn't depend on the units of measurement – we might as well measure both variables in standard units. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cf0c889b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.017081Z",
     "iopub.status.busy": "2026-08-31T06:02:07.017018Z",
     "iopub.status.idle": "2026-08-31T06:02:07.018435Z",
     "shell.execute_reply": "2026-08-31T06:02:07.018224Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def standard_units(xyz):\n",
    "    \"Convert any array of numbers to standard units.\"\n",
    "    return (xyz - np.mean(xyz))/np.std(xyz)  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0bb35813",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.019398Z",
     "iopub.status.busy": "2026-08-31T06:02:07.019344Z",
     "iopub.status.idle": "2026-08-31T06:02:07.022186Z",
     "shell.execute_reply": "2026-08-31T06:02:07.022012Z"
    },
    "tags": []
   },
   "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>MidParent SU</th>\n",
       "      <th>Child SU</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>1.804156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.686005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.630097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.630097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.472085</td>\n",
       "      <td>1.888017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-0.767591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-1.326667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-1.606205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>-2.185390</td>\n",
       "      <td>-0.068747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>-2.185390</td>\n",
       "      <td>-2.724356</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent SU  Child SU\n",
       "0        3.454652  1.804156\n",
       "1        3.454652  0.686005\n",
       "2        3.454652  0.630097\n",
       "3        3.454652  0.630097\n",
       "4        2.472085  1.888017\n",
       "..            ...       ...\n",
       "929     -1.424873 -0.767591\n",
       "930     -1.424873 -1.326667\n",
       "931     -1.424873 -1.606205\n",
       "932     -2.185390 -0.068747\n",
       "933     -2.185390 -2.724356\n",
       "\n",
       "[934 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights_SU = pd.DataFrame(\n",
    "    {'MidParent SU': standard_units(heights['MidParent']),\n",
    "    'Child SU': standard_units(heights['Child'])}\n",
    ")\n",
    "heights_SU\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b820a4d2",
   "metadata": {},
   "source": [
    "On this scale, we can calculate our predictions exactly as before. But first we have to figure out how to convert our old definition of \"close\" points to a value on the new scale. We had said that midparent heights were \"close\" if they were within 0.5 inches of each other. Since standard units measure distances in units of SDs, we have to figure out how many SDs of midparent height correspond to 0.5 inches.\n",
    "\n",
    "One SD of midparent heights is about 1.8 inches. So 0.5 inches is about 0.28 SDs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6c46b994",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.023180Z",
     "iopub.status.busy": "2026-08-31T06:02:07.023120Z",
     "iopub.status.idle": "2026-08-31T06:02:07.024724Z",
     "shell.execute_reply": "2026-08-31T06:02:07.024533Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8014050969207576"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sd_midparent = float(np.std(heights.iloc[:,0]))\n",
    "sd_midparent\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e536ff81",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.025561Z",
     "iopub.status.busy": "2026-08-31T06:02:07.025512Z",
     "iopub.status.idle": "2026-08-31T06:02:07.027062Z",
     "shell.execute_reply": "2026-08-31T06:02:07.026886Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.27756111096536695"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.5/sd_midparent\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f26843",
   "metadata": {},
   "source": [
    " We are now ready to modify our prediction function to make predictions on the standard units scale. All that has changed is that we are using the table of values in standard units, and defining \"close\" as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f28a0bf0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.028025Z",
     "iopub.status.busy": "2026-08-31T06:02:07.027952Z",
     "iopub.status.idle": "2026-08-31T06:02:07.029366Z",
     "shell.execute_reply": "2026-08-31T06:02:07.029187Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def predict_child_su(mpht_su):\n",
    "    \"\"\"Return a prediction of the height (in standard units) of a child \n",
    "    whose parents have a midparent height of mpht_su in standard units.\n",
    "    \"\"\"\n",
    "    close = 0.5/sd_midparent\n",
    "    close_points = heights_SU[(heights_SU['MidParent SU'] >= mpht_su-close) & (heights_SU['MidParent SU'] <= mpht_su+close)]\n",
    "    return close_points['Child SU'].mean()   \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f0057102",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.030230Z",
     "iopub.status.busy": "2026-08-31T06:02:07.030179Z",
     "iopub.status.idle": "2026-08-31T06:02:07.132286Z",
     "shell.execute_reply": "2026-08-31T06:02:07.132099Z"
    },
    "tags": []
   },
   "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>MidParent SU</th>\n",
       "      <th>Child SU</th>\n",
       "      <th>Prediction SU</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>1.804156</td>\n",
       "      <td>0.937589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.686005</td>\n",
       "      <td>0.937589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.630097</td>\n",
       "      <td>0.937589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.454652</td>\n",
       "      <td>0.630097</td>\n",
       "      <td>0.937589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.472085</td>\n",
       "      <td>1.888017</td>\n",
       "      <td>1.025864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-0.767591</td>\n",
       "      <td>-0.444284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-1.326667</td>\n",
       "      <td>-0.444284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>-1.424873</td>\n",
       "      <td>-1.606205</td>\n",
       "      <td>-0.444284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>-2.185390</td>\n",
       "      <td>-0.068747</td>\n",
       "      <td>-0.703401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>-2.185390</td>\n",
       "      <td>-2.724356</td>\n",
       "      <td>-0.703401</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent SU  Child SU  Prediction SU\n",
       "0        3.454652  1.804156       0.937589\n",
       "1        3.454652  0.686005       0.937589\n",
       "2        3.454652  0.630097       0.937589\n",
       "3        3.454652  0.630097       0.937589\n",
       "4        2.472085  1.888017       1.025864\n",
       "..            ...       ...            ...\n",
       "929     -1.424873 -0.767591      -0.444284\n",
       "930     -1.424873 -1.326667      -0.444284\n",
       "931     -1.424873 -1.606205      -0.444284\n",
       "932     -2.185390 -0.068747      -0.703401\n",
       "933     -2.185390 -2.724356      -0.703401\n",
       "\n",
       "[934 rows x 3 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights_with_su_predictions = heights_SU.copy()\n",
    "heights_with_su_predictions['Prediction SU'] = heights_SU['MidParent SU'].map(predict_child_su)\n",
    "heights_with_su_predictions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "eac07f3a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.133188Z",
     "iopub.status.busy": "2026-08-31T06:02:07.133129Z",
     "iopub.status.idle": "2026-08-31T06:02:07.170401Z",
     "shell.execute_reply": "2026-08-31T06:02:07.170194Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115c03250>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "ax.scatter(heights_with_su_predictions['MidParent SU'], \n",
    "           heights_with_su_predictions['Child SU'], \n",
    "           label='Child_SU', \n",
    "           color='darkblue',\n",
    "          s=10)\n",
    "\n",
    "ax.scatter(heights_with_su_predictions['MidParent SU'], \n",
    "           heights_with_su_predictions['Prediction SU'], \n",
    "           label='Prediction_SU', \n",
    "           color='gold',\n",
    "          s=10)\n",
    "\n",
    "x_label = 'MidParent SU'\n",
    "y_label = ''\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c4f4142",
   "metadata": {},
   "source": [
    "This plot looks exactly like the plot drawn on the original scale. Only the numbers on the axes have changed. This confirms that we can understand the prediction process by just working in standard units."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac303559",
   "metadata": {},
   "source": [
    "## Identifying the Line in Standard Units\n",
    "The scatter plot above has a *football* shape – that is, it is roughly oval like an American football. Not all scatter plt are football shaped, not even those that show linear association. But in this section we will work only with football shaped scatter plt. In the next section, we will generalize our analysis to other shapes of plt.\n",
    "\n",
    "Here is a football shaped scatter plot with both variables measured in standard units. The 45 degree line is shown in red."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "be0671a5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.171479Z",
     "iopub.status.busy": "2026-08-31T06:02:07.171410Z",
     "iopub.status.idle": "2026-08-31T06:02:07.203938Z",
     "shell.execute_reply": "2026-08-31T06:02:07.203725Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = 0.5\n",
    "\n",
    "x_demo = np.random.normal(0, 1, 10000)\n",
    "z_demo = np.random.normal(0, 1, 10000)\n",
    "y_demo = r*x_demo + np.sqrt(1 - r**2)*z_demo\n",
    "\n",
    "plt.figure(figsize=(4,4))\n",
    "\n",
    "plt.xlim(-4, 4)\n",
    "plt.ylim(-4, 4)\n",
    "plt.scatter(x_demo, y_demo, s=3)\n",
    "#plt.plot([-4, 4], [-4*0.6,4*0.6], color='g', lw=2)\n",
    "plt.plot([-4,4],[-4,4], color='r', lw=2)\n",
    "#plt.plot([1.5,1.5], [-4,4], color='k', lw=2)\n",
    "plt.xlabel('x in standard units')\n",
    "plt.ylabel('y in standard units');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcc7e67c",
   "metadata": {},
   "source": [
    "But the 45 degree line is not the line that picks off the centers of the vertical strips. You can see that in the figure below, where the vertical line at 1.5 standard units is shown in black. The points on the scatter plot near the black line all have heights roughly in the -2 to 3 range. The red line is too high to pick off the center."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ba34495d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.204962Z",
     "iopub.status.busy": "2026-08-31T06:02:07.204900Z",
     "iopub.status.idle": "2026-08-31T06:02:07.238162Z",
     "shell.execute_reply": "2026-08-31T06:02:07.237955Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = 0.5\n",
    "x_demo = np.random.normal(0, 1, 10000)\n",
    "z_demo = np.random.normal(0, 1, 10000)\n",
    "y_demo = r*x_demo + np.sqrt(1 - r**2)*z_demo\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.xlim(-4, 4)\n",
    "plt.ylim(-4, 4)\n",
    "plt.scatter(x_demo, y_demo, s=3)\n",
    "#plt.plot([-4, 4], [-4*0.6,4*0.6], color='g', lw=2)\n",
    "plt.plot([-4,4],[-4,4], color='r', lw=2)\n",
    "plt.plot([1.5,1.5], [-4,4], color='k', lw=2)\n",
    "plt.xlabel('x in standard units')\n",
    "plt.ylabel('y in standard units');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7712eee1",
   "metadata": {},
   "source": [
    "So the 45 degree line is not the \"graph of averages.\" That line is the green one shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "679731f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.239228Z",
     "iopub.status.busy": "2026-08-31T06:02:07.239157Z",
     "iopub.status.idle": "2026-08-31T06:02:07.271395Z",
     "shell.execute_reply": "2026-08-31T06:02:07.271192Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gmDzM+SAzUSQjILFwrO5dYy23RG37styH8kggh09jJM7fpUuU/L59jgulVUC2y4GepoRqq7amS7yZfG5TWocbNiDv1FPhXrBAfQ17vah58kkEjjwyY23obLAJzUarQe9I7HI8rQ+dYKiIUZRtDDKkU01GQOzw6bYj6Hqz6vQbY7klahvJjM5J3bqit3LafrFnJx2ilGml/GwnlpzQN6FrM9V5Z2LO12ofqQjUUVGB3OOPh3vRIvU9nJeHmunTEYioG9loAUKj0C+1Ec34/vvvMW3aNCUCvMsuu+D8889vd0KeNtoGtmXWdjATDJUx9PuRiICkVhYtOqIxc0/pqnnwd4mi5LGn7NMb531YqY47stDbwEXaqDD3JiqVZCJ4xGofqQjZUVKCvGOPhevHH9X3UK9eqHnxRQRZ/sVGyxDaQw89hBtuuAH/+Mc/VBkWAXURjz/+eFVmgbXH3nrrLcycORNvv/22ne9lw0YbIxXBWP0uChpioSUikURzXOmKE5PMSGrS8fNTgkLMLtKmyncl2sa8v3SswFTLEu0jmeXqXLZMKeY7ly9X30PFxdj0yisIDRvWqPPsqmgyw8yfP199HssKqBpIcPX19dh1112VdUalDpZo+e9//6sU7m3YsNG2aIpFo0tTWf1utkQaY93oHT/JS3ctSt6blYs02XlEClYnbaO5DelYq4KJH1Tj68pg3L5k/yTlGeMKUu5DqmoLnN99pywzZ3m5+h4aPBgbX38d4c03T3r9bGSA0FjtuaCgQJViEaxYsQJffvmlqj7KemN0R5544olK1f6VV16xCc2GjQ6MZHJQzVH9SNTxm5fTDamH/yfaL626str46vKp5getiI4uWWmHvv4V33vxcaU/LvqSkMTrWSvqVRtIasmCZXQR5Jwvv0DehAlwrDcqkweHDjVEhvv1S+ve2GgmoVEHcauttopb9vHHH6vPo2kyR+bWRowYoTQUly5d2tRD2bBho4US09PRZWzsHJQ5oTqdNugdv1WyNefQdAmtRCREInlvRX00sVqMoGTzg1ZEp1tbTodDzeXR7frYHrlYutGpyIw93E59jOhLbqfbW7qlmSpYJnf+POSefjocNTXq98CoUWrOLNy7d8prZyNDhOb3+9U/HXQtUmF7r732ilteWFioBIFt2LDRdDTGjecPNX9/jRElTqT6QSJiXlm6x0jUJp10KmqDliQkLkr91HURjUTzg2ai00nu3RWGkj3JyphDzMWw7iEsrTFqQH+9zq/azH2PG5iNOSvq1DFTBatIW3LffB25554LR6Qv9Y8dq6IZ0a1bsltnI9OEVlRUpFyMnC/LyspSy95//31lme22225x61IQuGcXLmlgo23RGeS2GpPTdeaCanxZno1Rf1ZjxoHZTdpfIlFimR+yglV7GnOMRK5KPQKS2PN1Y47JXLBTJ6cqF1CfZhvNRCfHU5aexT7uHupD7+JCjJ65XrWV1ptuZSaDfpy8Z/6HnMsugyNkHMV/xBEqzwyR/tRG49FkRUuWY9m4cSPuvPNObNiwAVOnTsXvv/+ugkFYokVAK27ZsmUoLi5u6qFs2GgyOHqmhcDP9oh0y5FIZ23uxM3b8/uidQGs9TvVZ6L9y/7MgRZWx9NFidnJT5i9plltTtQGhukzmpEBIObweR6f7j2C7SC+OrbYMqn62xP6Ij/LsKDShbltJO0DB2Wptss/5t/JeuJWZVvX+wxLVPYjVqn5mdOfRe8DDyD3kkuiZOY79VTUPPVUQjJribI1nRFNttAuuugivP7667jvvvvUP4LuRi7X8eGHH6oQ/lGjRjW/tTZstHCdqdZEY/OczJaE1fb8bWQft5G/1ScraSBHqiKc+vGic1MA5qw0LDax1BJd13TD69mGUNhwFzKoggQnARn6PaR7T89VS6QPOfH9dQ2CQqzalupZ4PmJpqQuCCDuXLaRBKU/X0Qid6haXhPEQVP+iZx3n4gep37SJNTdemtCkeH2KqbcqSy0nXbaCc8++yyGDh0Kr9eLLbfcEg888AAOO+ywuPWYYE3su+++zW+tDRuNQCoLob2RbTpIFswgeHrfHnhj1zr1KeuaO8gdXihVc0KJjm8O0WfnPm6gN6riIUEPiSxgEl7UGkkjOlLcmbxXDL6QbWjt6FYb20ELjGRidc143HctgkIStS0Z+DsDUfRzoDv3yIXZ6tPq+RJ3pZU7dNd8F55+9RZcopFZ3XXXKTLTZb4y8Zx0FHy/9nuc+daZGdtfszKdx40bp/4lw4MPPoj7778/zg1pw0ZroakJuC2NxshCNWV7jzNxYIeEjJMkrMg+kUXwwvjCOPX7RNaIbs0ls4zN55AoudlstZHkrGS4uD7JTO/yzUZPum1LRCRmd665moBVgrixQx9envF3eD98RX0NOxyou+su+M45J6kF1tznpL2ibFMZbvv0Nkz/fjp6Z/due0JjQAjlrBjBmAwksjVr1mDVqlUYNCiDZV5t2EgT7bUTaC7ZpirNksjlmkz+KpWblhaSvswqQlAiDZ0WosL6cbg8Ubg+YW5rKhkuc+i81TEXrfGlbJvVsWU9sztXJyNeS3OCuNpXfS1yzzgDntmz1few243aRx+F/4QT1DqSvyYlbsxtaq+Dsqagxl+DhxY9hPu/vB+b/JuQaTSZ0IYPH44999xTyVqlwv/93//h008/xbp17XNi3oaNtkJzOqlUcyvSKbOjpNuOlg3XS9VBprII9GVWEYJ6hWszASZS1Eh0Llbh/1YyXHIMHiURqXEfDOCgZbrfgKyE0ZpWidWCKaO7Y+XK9RgyuLAB+Ut7SHj85PF++XMtXp1yIYb9+JX6PZydjZr//heBgw5Keuxk17wjIhQOYcbSGbj1k1tRsjGWwtXD2wNX7351+3A5mqVbMrWuDRs2kiNdNQ52ypwv01UprJJ9CZ1UOE/VHMtRT1CWpGTd5SkRk3QBUkk/1bnov7NtAp0M2cfQWGXgoIsBHNr2uvuSblYeU//NfDwrgpVz2T7Xi+cHJ7biJMhlxbJSvHDfORhW8pNaXp3dDbde+wQma2SmFw7V5w47ExasWIDrFlyHb9Z8E13mcrhw1vCzFJkV5CYfWDQGraIWXFNTA4/HCLm1YcNGcqRyL0lnS6QKeOFydpSp5mCsrI10kCj5WqwmK3eanuMluWVWrktpf7J5JL3dAl4TZ5YTpU1U1E80fyZzj6GgEfXotFA4ke3W/PQH3n3wbAxY/afadm33fBx47uMoKdoBV5lcrFZzh5kiNl8buip/rvgZN3x0A2YtmxW3/OAhB+PmvW/GNvnbZPyYLU5o5eXl+Omnn1Qitg0bNprnRtQ7TXbczMVKNIfWmDmYxgYfWIWo6wEjycLL6erT1+WxdPee1F6jU2fcICPoI9k56AQpc2PfWDQ/XUX9ZNeC++eZn/fxBiyuqGqQMsHv1d8sxasPnoOCitVqeWjgQFz7t6dQ4h0Y3Z/5Picj2KbilDYK919bsxZ3fn4npn4zFcFwLH1ix8Idceu+t2LMoDEtduy0CY0h+s8991zcsh9++AFHHHFEwm1qa2vx448/qk87bN+GjebnzYmFkyoXy4x0RunpBh/oHaU+XybJ13rbDXeaD6OK4olBn1uzCqyQoI85K+uigS9my0yvkcYkaF3JZGga10H+dlr8Zp4/EwIXO/CrtX6sqW8YKfl8/nLkPjgRzgoj0Tq41VbY9OqruGvQINyWokBpJvMmfW2Qg1kXqMPjSx7Hv7/4N6p91dHl/bv1x3V7XYeTtj8JTkeTM8UyS2jLly9Xtc4E9BNXV1fHLUsE5qpdd911TW+lDRtdAOlYSYnCwhvbYTW1gzN3lDKfpRPTTn3cpn0nViuxcnXy3KhYTwRCwMiXV0fn4OQacM6JAR5SI01vhw6rqXudQHSSsiJYUfiXe7OwrA5D80LIycnC4gqjfIwc0/Xhh8g7+WQ4Nm5U34PDhyvF/Pr8AjBG0ypwJll1geYQkLcVw/05d/nKz6/gHx//A8urjTpuRJ4nD5eOuhQXjbwIuZ5ctAbSJjQmTFM1X06AiiBU27/88sst1yfh5ebmYosttlARkTZsdGWkSyDJrCRzIrJVB5yOaynR+um4O5N1lNxmm+dKlJLItjNKFcnIvFMyi9O8P3FJfrXGj/W+UNz2hJ5HV5SdfA6RiiEiHmx1jsmEiWctr8OgZ0pRlOPETyf1i1NWYdK60xML4nDPnInc//s/OOojRLzXXtj03HM45csAvlrTUJw50X3OZIj+s60Q7v95yeeYvGAyvlz9ZXQZrbDThp2Ga/e8Fn3zYgE87YrQdtxxR/VP8M9//hM77LADTjnllJZqmw0bnQJml1qqDqYxuVGSl2Xu9BMhXXeXOb/NPD9m1VFym7UMmgCwpjak1knHSrDaH0u2rK8PIRCGIi49Z0xC41U0YUQL0QyxzKgYYiZD/dwTpR3QTVpeZ+yb5yIK/3pQSI9sYxvPjBnImTQJjqAxX+Q/6CDUPP00fN5sRWaJ3H7J7nN7x+9Vv+Omj2/C67+8Hrd8v832wy373IIdCndok3Y1OSjk22+/RUcAy9a89tprmD17Nn755ReUlZWhd+/e2H333XHppZfaGpM2WhQ6UTDQIVkplXRg7oD13Cohjbr4qk5xSDRvpJMlPTB67TGKEdPqSqWuQQIszHGivDakPvm9sVaCEI9SsBf5Kip0rPHFWVphOBTRSFkX8zFEIcRpKuWSyNVndY15r9ZEziU/xxUXFBLd9vHHkXN1LI/Kd8IJqH3kEYBR3WkSerJr0RxyO6UFgkKq6qpw1xd3YcqSKfCHYg/a9n22V0R2wOADkuqDtjRaJWy/LTFlyhQlnkzXJytns8r2b7/9hrffflv9e/LJJ3Hssce2dTNtdFLERvzGnE9jJumTSUZZ5VZJIEOqfVrNGxHx5GXse8LstVEyI1SuV2R9K5USsW5oUZnbm+j89DQEgttK8jRby63FAuUxJRVAwL8pSGyVKF2c40rL1WcGf6ebURcnluvGLX2BEHreeSey77gj1o5zzkHdv/4FOJ3NzulrLBmZz8mX4aAQX9CH/3zzH/zr83+hsq4yurwwtxCT95ysXIxuZ9vTSVotkErUnBPbeeed45Y1BqNHj0ZrY+TIkXjrrbew9957xy3/5JNPcNRRR+GKK65Q84NS082GjUxDV7tId7SeqENLpMqRaJ+p5KTMneDX6wJaNWa3UriPL5jpaGC9yPySdKJ01elJ04mCW8zRkSJ8zG0ZtbjitP5q3UTXTf4i1ehzijqsjAWrfK9kVqdsw7bSUhyaHUD+P25E9hOayPCVV6J+8mR1wHRz+vRcO/PyxpBRoqoLu2QgKIQDmLd+ews3fnQjllUtiy7PdmXjol0uUkEf3b3tR6c3LUI7/PDD1YO89dZb4/PPP49bli64bltIXx155JGWy1lVe5999sG8efNU+oEQtQ0bLQGrBNpESNShWXVcyfZJRXiJxNOThqliYaXcQ+Kgu5AoyHYoMWJdhYPgvrgPkpnMlelh9XpO2Pur6qMuVn3u0BzcIqTGY8gcnCRcy3XTrUFR1mCfUlkXiqsQLdcilTCRfi2JVNaQzCGO7An875nrkPf229HfaqmWf9FFkWOnH62qCyzr16cxZJSM/J5tZlDI4rLFKuDjk1WfxC0/cfsTcf1e12Ng94Fob0iL0AYOHKgenr59+zZY1pEh6iUuV+OKAdqw0VSk07kkCv5I1HFZ7ZM1u6gIr7vqWECTeV1SqsQcFEKSCJssMekU6dITkpG5MrHQdLejRCjSkhEXqz53KG7RRCr7emVsgZnIheA4z8d5tuJsw92quy7XJKmHpl9LIUar66q3iSTt8dfjkkevRMHX89TvYacTtfffD//pp1u2UQ/QsUro1nPtzHOrjXGNJiM/bxPIbEX1CtzyyS144ccX4paPHjAat+17G0YUj0B7hbupASAdJSgkWbWA+fPnK5IeNmxYyvVZ2M9G5sCir/pne0OqzqS5Sa+ptp06Og++YK4R5BF59nbOd2HRurD6DPnrEwZ/8JqyfMyI3k4sqQwpy4e5XJX1YfgjfaxyKfZ2Wu5HqW1ox5j4wXrMKTFckSSAtdU1+Pro3opU9PbJeT29dzf1N9U0mIC83m9UmWbHPeB/Jcqi6uWlFcWIwaDaXlmOkW15vHmr6jFwegnG9nVj8bqASmLmsas31apjKWtQux7ch0R7KkiUYyhs+e7KtlTPJ8zXldYtBwQj8nl8P3LrNuG1qRfjgF8MD1W924N/XXoPzqNi/qba6LGljWyf7EPAY0mNOh5rXinvjfGbkKtsK2BbUj0vVs9KU7DBtwEPLn4QU76ZgrpgbD9Deg7BDXvcgIM2P0iRf0v0hazckgk4qqqqupxqsN/vV/NnnEd77LHHcNJJJ6XcZtmyZQhGwnJtdG5c+YMX329wYlj3EO4e6mv0783ZNy0rqWVmhVS/m1ETAI77KlvV8PI4Yq/6Hr2CuHN7g/hkvyxcyfX6uEN4c7c69Zu+vQNh9PaEFeGx/cR3G5zYIfK3fl7cLtdtbH/Dz161XnXAAX9Yn/lyoMATwvbdQli60dj2ju18OOKLbKwLGA3T27xX72CD4+jXg9eWx6nwOxC+6QBgfRkKC4swc+bbltdNlqntqp3YoUdsn3ItePzeG6vw1pQLsOvy79R2m7w5OPqsB7Bkhz1UIVXZh7ldch68buHIub68S526LnJ84pofGz4Tetua+qyli0AogNdXvI4pP09Bhc9QOCF6enrinK3PwXGDj4PH2XJavPSQDRkyJCP7avuwlFYG81YuvPBCRWZnnHFGWmRG9O9vTFDbyAxoRTCFori4WFU8by/gaHjpl5VY6w9jaY0Lxf2LGgROJPu9OfvWrYJpY3ok3EfKOTjTtR25vBpLKgIY2cejyp8QtJ6OXuSJsxpG/Wkcn7W+WB5F2uN0AUUuYHhvF76pNBKd2X6x+D6tcqKnB6BHkssPXejBuvow3E7DEuMxFo/rjnM+2oD5qw1zsFfETTki34slFcHoNSnqV4hdizdiXinn1CKuz0iBz//sl4+93q6Krtu7uFBdC7kezw8yrs+oNypRHrkWbrcL1//eM+F1lXuyLhB/T+Ra5JaX4a1HzsWwst/U+sGePXHVJQ/hm/67YFQft7pO+rGj6RQLqrEh5Ffq/3KugAsnLMmLu+Zq28ENtzXa68LSmmCTnrV0QAt57vK5uPmzm/Fz5c/R5V6nF2fveDYuHXkpemX1QkeCu6uR2aRJk/Diiy9iwoQJuPfee1vdJLYRD3a47enasiWjimqicxI98nIa9XtT980OjQEcJIs5JX6c+dHGBmHo5jpiKcP7vV6c9fEmfF0ZxMhCb3Qb41hV6liKsCKKFzMOzI7ui4nE0h5dBFlvw7yVhioGj7xLkaGlyMhICfMnEXF77ue8T412jO3vxfT9jRpo5mAXdrCjZ65X12bZycY6EuHI/Rb0yMWootroPNmwVyvjBIy5v2yTIaEiIE3XVUrHcP+J7gmvReCX3+A/bCL6lq9Uy0LFxaiaMQOn53bDNQN7Wz4bBF2xJGSeP7nsuwn9jCTzV8qMQJiKYJzKiL6t/hx8XRlS900S2hvzrKXCd2u+w3UfXof5y+fHLT9m62Nw4943YvOem6MjolkuRxLEjBkzMGvWLOWS27hxY8K6ZxxpLVmyBG1tmbG9xx9/PB5//HE7GKQNQT885zFZxbw9EVpbzqFJ8AHJgCSi5y9JqLyEtzOsnQRlFfko17a4/0DDWomQkr4/HotRiBJlp0f3UbaKAR90efXKcjaIkiRINJInNi6yvZxX8X9XqYAHHomyUXpoPpcdFGm7juPeXYP3SwwizNKOK/XcGP0oKQIkjJEvl0WVPEga+w/Iio+UvGl/5XLs168/gjfMic6tcd+S26aftzloI3vp98g79lg4yw1bLzR4MDa+/jpO/Dk3WrtsxoENK4jwfuiBN9xj2cT+CaNUrZ4NPU0h0/JVpRtLcfunt2P699OVI1Swa99dlRL+7v13R0dGky20DRs2KGJYuHBhWsU72zIiUiczJlHbZGYjFZoqT2VGIv3CVGVVdKkngp0cq04TEtaeqsgn3YpmFRFCdayRiEZ2vPq23KeE5HMe59OjiqIqGebcMXNCt2xPMmKbijTLjudFwWEe890V9XFh+NR/FMJhC/mXREcOnVGCtZGpI5GguuiTqui1EDCqMhoQYtJy9EQkR1RCdCgmlcwEcPM14zk6Pvsczz1yAZybDMX44NChhshwUV989UmJmlujZZsomVnIjDDP2yXrKxMlY2diYLXJvwkPfvUgHvjyAdQEaqLLN+uxGW4afROO2eaYDh+13ixCu/POO/HFF1+oZOvTTjsNu+22GwoLC+F0tmx5gKa6GUlmRx99tFIOscnMRmugKdJDOqmJ1JMe5u1lhGCWEapNQkgUsi1h+2bS4b5EaUNZUNlO7NTHIE/+pofkMxdNyEwPdadlp+SfTBqLVoVHhbSe3DcfA58xSm5y251fLsOuRYaaPS0qwbgBWfC4HGo/JC2SmUMjhz1fL1e5crIF9947y7ACSZRmuqCWI5dxDm5EgQcflMTC5dfUhdRAgRCi7vnB+/jP45cgz2dEUwZGjULNiy8i3Ls3zpy7TkVsMlCE85FWAxWes5LiigR10HrV0y4SCTWbByepYGXJWSEYCuK5pc/htk9uQ+mmWMnTHt4euGr3q3DuTuci293+PCStTmhvvPGGIi/WSGvPtc5IvGxjt27dVHWAu+66q8E6VAqxKwJ0XbSEInlTpYfUHIpFXTGduCQJ10pcV8DOVAVjVAQbWHsSXceOXql6rKxXbkJaVlyXbj1KXlElJE4/MRxuYOWQ3LgO2ySuNlqEv53cT5GZWGLMgRPrS8iEHT/bRQIVdyTJzKyl6HYAPbOcqPaF4ipTEyHTOfPczKTG/cocoliKcv50HxIkmoHvvolHpv4NnqARuPLBdnti6xeeR17vHlHC4fnle8LR4Boz9PwzGSAI9Dp2ZqvQPBBIpQxiLp9j9Qx8sPwDNU/27ZpYihXlqc4afhYuH/U39OvWUCqsyxIao6g4/9GeyUzquBGc37v77rst12FZHJvQuiZaqqpvU6WH9FE+LRSOwq0qNqdbHZpKGkI6sg92/CaPnfpOsuAcHvUcxZJhO/h9fknMlcYWCDlxHXauJ80pj3O1iSuR1hctPbqzuH5hFlDtjz8+3Ws7vLBakaskgRtqH4ZqCD2GJECjXIxx/mvqjBkgkehS0lehmHiw+dxEGssMEh2V/Td7cToeev4fcIWNhr2183hceNbd8L23CeHwRtV+cXNW+h3KnTvjQOsgDfN8GSGqIPsNiNV1a0oFct3S4/UQAtTxU8VPuOHDG/Du7+/GLT9kyCG4ee+bcePifIx9i22LDVbQ1QmtT58+SrW+vePRRx9V/2zYMCPTAq76folUE/qJfpNACF3lQ6/YrAePWKlbEMz/+orzPPwaFtIxSJCWGF3xa+tjnT9dmSzVwn0uiSiCqP2FgNkrfXEkQUJktOL8VT6VJF3lC2NeSSyBuKfXgc2fKYUsIamNG+hROpFC8nQbsh3Sbla0poXH5Vs+V6p+q6qPHZVd/BgtQlLm3biG2xlzvZIEleUC67krUTshCrMdhtbk/fej54ybosuf2/MYTLv0dviqDJKP7CFaoYB2KhPGE2lBmpVISP9C4JzrS6bHmaoCuZW1zkEPrdkdeldjc88UPP3t0wiGYzmzOxXthFv3uRX7DNon0rbEJW26LKHtv//+ePnll1VwSPfu7Uec0oaNdJEpAddkGn2JhIUTheBLuxhFJ24ovZSLuCRFQNhKIoqdd2V9DgKmAARxZXJU//kxfaPzUX2yHPj1lP5xVh/1Hhk4YramJKKQVk3vbCeG53swNxItKTAHZ4gupJAtO19ZQ5YFQqGohcfjSWAKrZCeqpM3hJPZeetVBbg1z5lWHuW5SBi0gr7OdaF0fawNEvCga02y3tpTE67C3+Y+GV3vvrFn4PIjr0JxFeJSEJyR8yB5q/I6BaYgG83KNz9XhDwTvK/m5yxVUddk6xuSZRtQvv6/KC+bgnB4U3S9Ad0G4PrR12PCdhNU0c3WrmTdocL2V65cqRTsDz30UDz44IN2oIWNDhu2n6lRqhFOTteZ8UpJqDyhT+CzQ7YKwbfan+Qu0dXGfCbdncXOmcSSSLVeB9tCklpXZ7gcDQsoFCUr2b/eVtk/Kzfr+6M1xzNkUjX3S7em1C4zoyBClomCGQg9zF1vryAYCmOD35gvErec0qVcUad8nyRYWlqDppeodUiC+f8cj9LSEjh7FQM3zourCkDinr+iBve+cCsu+DSmV7j+msnYdrNTlTtT1qe7lUQq12JhWR22yw3gxYOL1XPL89GPywoB8izpkZziRk2ZFG8x6DGnTcjvoXAIL//0Mi6eeyPq/CXRfeR58nD5rpfjwp0vRK4n13Lfnc0ya7aF9ueff+Kaa67B9ddfj8WLF2PixIkq6IJRj+2pfIwNG6mQKcuMnQ8tgSxnTJmenbd5At9sKSQqfSJRjOzwub15Po0QYqRlMqLAqwI5Kutp7Ui2lQG6GNfVG0THwAluo3u3SMKcxxpZGCNGfjJsf8jy1XHtEvLi3nUitUJFfRjHv1eOlw4siiNiIXq230xmanm+C1+v9SsNR4HMn5HkpQE8l7kr6pV1lgjm2m/TRnfH+4dejAmL3zF+dzjw8Nk34qQrLwVeXK1qwQnxkcwYBUrCVEEqdNOGjPpoyYZhOhlxIJHOfKe5srnZHa4PBC7e7melhL+obFF0e6fDidOHnY5r97wWxXnFCfctVmRnRJMJTS8f8+OPP2IyawG1w/IxNmw0FY2JTNQn9hnhJ9uxEzRP4CtVDi08X3f96K4kfrIzDISMTlmf85D1JYCE81QflNSreSbOgZXXxVtUDDeXjl2CNNhRM8JRwKAMvZwL982cr0QIR8LxaZUK9EhGgsecs8qPrZ9dFXVfzooQEElCKY5EXJY6sZnJTF3LfC++q2xohXJWjCH7TNiWdi+J3Dav04GeeuRgTQ16TJyICYvnGNs63bj4jNvw2qgjcduLq5XVynulE/WclUZ7pVDr9rmGtaX273JEy9mIO1F/HjgYkcjLZHNW5vlcubfmEjdlG3/H3Mp7MfPb2XHbjxs8DjfvczOGFgxNue/Oap01i9A6Q/kYGzYIqxe8MdGPySb2rcLtBSQ1KxeTQDpVveCmmfiMABIjQpBkQTKjZiHnv1xuVzSST0LV5bsU3rRS9WC76CKLs4aUUDDw04l9MWRGvMVm9AMGjSWavyA5kVgFoqbPzp5h+QcMzEJQtd8Hp9Oh5tDMIJnJNSEq6kLR6gFCrgSvv3Tr+dlOLIkkKfsrqtDrlJPg/uwz9VutJwtnn3sf5g0fG0eStAR5fU6bR9WPmBVNq5Ku8rKSlXEWmnkOTH8eSJASjWlOn0j2DPG7vl9Wic7x3wVs/B/qFYUbGNpnqFL42H/w/gmufOefN8sIoXX08jE2bCQKf09nRGu1zEoFQncPWuotagQlCc8C3VqipUb3F0mP0MmWEYJ60AFLspChmIc27YDCBu44uiflmIxIpAXJiD8SJn+j9JWEqPN3gTPyJy0YmTMi2EadMKVjIZmIPBU3HTvAiIyMXsPIuZKUZHuGuPTOjp8DZNs4f2WWguKnLovFeTVaSkygNl/jC1/+CdfceAYKVv6ollVnd8Ph5zyMn3fYLY4ked5079Ky1q1ZIQKWuLniey9++rJSaUDqFaL1+2yuI2cV/GOGdXCIHw9+9ST+/cW/UFUfs5aLcoswec/JOG3YaXBRPToFns2whFZ7RZcSJ7ZhQ0ei8PdUI1qz9WalAkHIdukoOug5UmItyfoMTDCi7Yz9kzil9paeXC37oQtwXUSeiZaWHqpOsMNmR0uSYNQej8fP91YK2WhtcThwYCTknmBkJElOvDO04JTl4YjNrRF9IgExyuXK5Gi6EdcFsP9AI4CDx7dS9mBLpU0EA1gcpsGCbgn9fHL/qDXJcH8SrTqPTcGoFRf440/c8vcTMGSNkZNa1SMfN1z/FH7uvk3cPSQkXUKiLOkmFvkvym6d90E1Pqp0KR1EczVxuhfZMkZZkrx435ORmVWQhnyvD4Qw6/c38ZfZ16PGZ7SbyHHnYNLISbh01KXo7m1cdLm3k5MZYROajU6Bxo4+rcLf9e0TjWgTWW86AZojGvX19cg3M0Ey8pAdN4M7pu9vuAS5fxKB3k4S0czldarjJWEwGk+PfjQIIYwqn0FADBLhtn0YVMEk5fqwIhOHHjChmUQOjUh4PBKQECWPqTrt/i58X2kodyiRY9PkGc9DSEJFREb0GXnNxWqhC9MqOpJtkTaIYn80GtLinpyzoEK5MK2CS0J+P3odcgj6rDGiAJf36ouTL5uKHltsg1BEJYSI5cPF0iUEZrkttk5/ZtgmPVKT11aUVuScrTQjzfNjQq6Hvvk+Fi6/FX7/V1orHJiw3Ym4cfT1GNB9QMMTtaFgE5qNLqn2oZOQPoI2z4Uk20633qwiD82T++acMquAEhIB521oKdD6sGonO0sBLQkJCZf9GFlbRh0xPfqQ4eiCSL51A0i+lYBkxbB0FeYfYR/+z0RqugI530SLT0qlSAAELbizPliHCtNc2LpIB6+iLB3GfBXP2RwAokjQRFA8Bue1po7Jjw4KdCvbCn02VsC1wWj3yv5b4JiLnkTRNoPVedGaY+i/blGbhZYlbcLcuv37xcrxwNRW7o1kRheuJJPrz5I58ZrXin9/sfp3nPn21fjkt5fijubx7IbdBk/GlIPHJDhLG80mtJ122qlR67d1+RgbnQeJVBkaG8FltsISEaN5n4msNz3y0Dy5r3eOZvemzOEw6nD2SsMNR6uExPXC+IK443E/7CwFJB/p3OW4dLORJGKOu+TgWoVa5KNYFnokYbyFEiPIcQNopbiUhUKI1aVktKIuzBi4P3b0lNLicSXVQJ81U9N23I8FSzEqkyLHkjcnVracR1TdPuADj+6MuCp9Ow5Hj1dexqx8g4RI0mp5GBj2QqmyepVWpcO4HyQrfTChn/8+vYOYuk+8u0+sSdX+SBskf81qkKU/I/7gBnz850OoqJ6G1zTrMM+7Bbbr93esqNsHPXOy0Fj4usCcWcYITTQS04UdEWkjE0ilytDYFzgVMVrNl1klyOqdhz7KF5B0rMRpuX9Rr9eJCpHv+vHMIrYkHxKegMc9lUolan8mso24EHVhYYGUeZE2nTZvbZwqfbLoxbmr/CjIMnQUCadF6L4OLmdgiLgaeY68LgxGYfQlg1/U74lMrghI+CSiap8hScXq2JJg7Xx7JoZvqoSkGn+w5SiccOpD2PUbJ549wDhHznOJZWdYrtLisFpOaS0hNynlwjk0d8iH0+eUqzpzEhSiFPu1E6a1JsnmurvRnEu2+LgCPPfDNNzx2R2oqY1Z3fnZ+bhqt6sxcYf/w8hX1kU1LhtDUKdkWKO0o5BjkwntzTffTPhbTU0Nfv31V0ybNg2///47brnlFgwd2jA/woaNxiAR6WQigsuKGM3HSyQInGw+RF9HrDBZLgru0XImmhVAAjLnpyUSsZWOMl5xw0isjl6RMHDAoGxVroVzTtKZK/ckpZwi4fniXnMkUP1gorTONTwKE7YFVjykE5yqwaZ1/iQwfcBLq0b/XcrlVNaHoyH6ZheqEDWv79M3PYnLH/57tP11bi8OPu9x1HmNXDFxz9IiIwlazrtF5bsMcuOcHy02BoZUbwK+3+DEWn9MZ1M9i2GzyxUozo7lv0XnN6nOEgzjkxXvYcyz9+KXyp9j5+ry4oIRF+CKXa9Ar+xeallTBmu+Jngtkq3TUgLe7YrQKHuVDAceeCDOP/98XHzxxbjjjjuwYMGCph7Khg2FZNZYJkaPyfKJ9ERbvZNINB+SaB3Oj5EYRbJKt556eB1Kmoodak9PzNKzOnchM3Y2X6yuixbBtIKQCNvHeS3mqkk/zk9V4dlkU1lZWGvrw9i/P92FRpAKQdefVWFNnciSaeuRlKKRpuX12KUoKy7Ag+1edFzfBHNZsYhQ4sYvnsNfpt4c9/u6vF6ANzt6rM2eKVV5byQcNe8XIUx1zqx2HRFsFtV+XclFMKx7CJ9WOVWwDVMF9DlSWmbcN5Ot9TI/cv89oaXw1N+NKt9n0FPWj93mWNww+gb07zY4oXs73UGbN7KOeF9TbZOMsDpaUnaLVuOkviPrkTEZkZ82bDQXfOHoAmqpkaL5ZeVxaA1xhM4XXlf70F9up2ZlWHUkJESH1kGSXNhJcMTey+tADw/zvBxqToz5XVTVoNWld6TSFj2ghNGO1mRmROIVZMXyxUhcnNcyExDbFJm2SokPSwOqjc4Imc05rDDhuizWae5grI4hNMXAEHVtjimK+/20eeVIUugZXx1ThN/+mBZHZpu8OQ2OKARFkuTfvJfjBmWruThGN7K+I8mRRU8P3ixbKY/I/ea94LzbVi9VGEVDw5FKBMvrjEjWYw2pKe6bATR6Ej0/g8EyoGYy/BtOgN9nJHYTHs8IzDzhPUw9dCqu/bK7CiiSXEOBWHhWv1nBF3lmdMmvZOuaCct8bPNz36WjHKnEv+2222Lu3LktfSgbXQSt+VIlmkPTdQml86BeIomIf6s5FG3OBFoovLgmSWoskRIjGMOd2NNruLyYLM1oR704pe7yZMRfIjBsv0+WU1kLPbxihSUGg0KqIm49c/fHQA9x97HEDAmAx6bU1qhXyxPu84PSekOhnm7KMDBuUCwHjfOGVvN57FjHvb0mbtn80qC6blaiy16EUHDjZGQ99lh02a3jz0fVF68BkarT0XUjLkHj+hiDDD2PkMcm+Xd3G65QtlXA+yCu4e+rneo6EJz15FzeLyf3txzMbPJvwr0LH8DatQ8A4Vh7cjyD4M27AnsNPAJ7DShIagk11kryNmJeOZ11O1JSdquE7VdVVaGiwih1bsNGR0GijsQo2VGvSIcEI0m/Iv6rtg0bwRWcE9IjBklYMnonQc3VtBQRIUJaDV+W+7DeF1LHoEtuy2dWocIX0wQ0Rzvq4LF27xnEl9WOBvNOJCc152RanshtaNQh82BBqRH4QVJgcASPbS4Sap4v4/o6STLwg+dtzmszb2/VFnFd6vt3BQN4+qUbkfXZa9H1am+9FR9ueyKcC1+Li34cP9Ao5LlojR9VPkMmTA/YMHQafaqQKC1eKpdQmmvcwJi7UvY1rEcIH1bGbE/+RgFmQo5Z6w/gpZ+fw22f3IbVmzStS0cP3Lz3VThvp/PgcMQIJB13erouxMaSUDrrdgQyaxVC+/DDD1VEJMuE2LDREZBKMYQWBnOvRMRWpKTM/TsjBRlNx46TrkWxDoQUaaWws48jgbBRGywcDilFDrGs1mluRYa9cw5NiFS6GtnH/v08mF8ajhbY1EFyYscudb5k+0ROKREXdmjh6ENfLEsaxRh3LbUFJKqtnl0FV6QgJy1PzpvpOWgUcaLGR6r9Z/nrMWPalTj6u3nqe9DhxIUn/QN/bHuiGkSoqtzaNixS6tUku+guNVd65jU3EzJJjstlGS3OG7f2YdwX8V3nh6Uc2Bj73iz7C4x7/l/4fu332hpuwHsSCnpdiPNHbN8oS8jKhdiYubR00FEIq8UI7eOPP074m0qUXLMGX3zxBaZPn66WHXXUUU09lA0bGUOqzsDsYjR3MnoiL60tWht0K9I9qIIvLELd6YpUn1ob9LkKPYeJR2GOFr+zDM3Y/u64atD8nUEdVK+X6EK982enffduuRjxeowB9U5ayEmHrsqRCNye4sFBi211xZFUYNAF12aNNZIDg0B0HUgzCTsi84CsFiDt61a3Ca9NvRgH/PK5+l7v8uDkiXfhteHj4ZCCnCFrC4/3jIOQR0b3VpUEOC8lAT8kVhKSJHXzWlInkxCtzF36uNW1IiFysOGOBJWo5PLAr/D6/o2FlfEBcIdteRg2uC7HT9UD0nIBdmVx4XZRPiYZSG6jRo3C3/72t6YeyoaNJvvw00mcTuVi1OcyrOSyrFRC+DvzovSOUg8wEKkrkh07dVpNdGPSalFSUpEO2O10RglJrCSzS46Reqwezag7rvP3L2vi5r0KstlLh6IRfGbrR6Iq5fdEsCIzsXoaCwmNn2MSNTaDFptuweVvqsI7U87Hbsu/U983enNw7FkPYMnwveDVqmurcnAm0H3IuTEOSFgxQK6ruI15z3hPpFabbk3rc2ljVuWgKBtYfmo/FeW4cHUpnHUPArUvwaddpRFFI5QS/t4D904qUG2FdJP5bbRC+Rguz8vLw5AhQ3DIIYfgpJNOsita22gy0lXwSKaXZ1Uw0UrpI9lI2BzGrwcNyPEFIh9FhQmYOkohPbEGSGAM89YrUtOCoUUiahskqN9P6ReXQ6aWA1h2irHdwP+VoD4MvLvKj3x3GMPynfioPKzmhZyReSQr9Q5ifWR+rjHg+io60xmrfq0squxY+oEVdAJOlUCtW2z9q8rw3mPnYljZb+p7ZW5PHHLuo/hj+53x+VFFyuJSUlYJTuShvXph91fLou3iarS0YmV6Ggog64E4zOEzBhNGqkJ1fQ0W/P4QNm6cwvCP6LYDuw/E9XtdjxO2O0EV3WxsHpcecKTLa2WCzHydnBTt8jE22jXSVfBIpICfqGBiIiJMNRKW32llkZhkHkZcUiQucWupkX9kO5nvigUg1CttROnQ2REL2HEOeqY07rgs3cJt2cFt/VxJNEiBYSEMrmCulpQlU8nOASc+LKf8lQEeJhw2wu3NHGIVJCLLU5OcQ4WsK4FgBriwmKgp+VqHJIUTI18ui5aXSYUt1/yJ2Y+diy0qVqnvweJiTL76Kfyes7lqJwWEec1JlIny1S74qBLrtSgZkd4St7H52bCqxqAQDgH+tzHu+QexcaPRHqKbpxsu3/VyXDjyQqWK35QIRX19HpttSFV2Jl2c0oESpJsKW5zYRrtGOgoeotaQTAE/kaKI1UuezghWPx7dhrrbTVQ8KJ8k4BwLO02Zl2NHJZWaCXF2sH3cllaOLibMStQEt9OXE7QWtni2VLkNfVFLy9By1AlsTkRiy0xUeiJxOAWhmZftXOhRZBYtBZOAAWmNMsiF15luOqMqQHIyk2PtWPKTssz6bjDSFEqLBsE78w38/nt3gFGLEetQ5LP4aU4m4H6kOjfdpLxWdGUqbchINKNIXMl90HUi6aqkUkgv51eoqr4TCH4fldaiFXbGDmfgmj2uQVFeUZyl3tj5L9H2FCK1UupvipXl62AJ0k2FTWg22j2SKXiIakYyBfxEiiJNfcl1K0ssNKmFJe0h8TBogOBydrj6KF91VKGY25AuRz1nTYIthICob8iONxEH0PCQBGt22N1cYbhdTlXskhF+QlZK3d6kvC/zbfwtFApH92N1KJ2vuN3iNb4GSvkwrdM7kg9HIzUQCquq1InSBAQ856UnFOOKe2dh+iMXondttVr+Q/+tcdgFU/DnAi/CkThGkiXPmRYv5yLpuh00ORblaIYegCOBPHrJGHkO9MKlazb9gW2nXoaq6vfi9nXA4HG4cfTNGF40NOEAqbHzX+acw1QDsHTg7SKBJTah2egQML+AZgHgVAr46bzkjQXnijlyZydKtQ+SB9tlDh7pk2XMM+k11/RROMMI2NFbqdxHO12LaA6SBWHONWMH/epudSjs1x9XflXXwN3HQpjRc4gkS/MzVfK1GTxuMjKTdXS3olhJySDnfMktL+OVpy5DXiRB+rPBw3HouY+iknJWEfBadY8EtMjAgvl/5tIzZvB+HDDApcSVw1r9Nt31+OS++dh8+lIE6h4FfDNQps3odcvaFtv3uxYfrR+F8e9Q7Hitcl0mGiA1lkBIambJq+ZaWc+a3pHOaKU5qqqqGjsXbMNGs0E5tBUrVqj8xOxsI3k1XbSEkng6VaUFeikY85wULQVJxuX+pCSJfOr7j1WiNsiGrkuG4icSzdXBbogyTeJua/i74XLUXYQHDvTisb3zseWM1Y0OAGltHL/kXTwz/W/wBg0Smb3NnjjmrPuxKSsvvR3ctD+wvgzoWQzcZOSqiTXMAQRD71WNN9P1k+vldfjgq3sWqHscgGEdEk5nAUJZl6Cw+zFwOFxRS5PPwYGDjGjVTD6b5gCRdJ59Xxouys46n2ZbaDY6FDI1F2DeLt19SkfACD3CzCUkIloJK0/rr/YTT3zhuP1P378gWr2ZhCdKI7T2KuvCKuCDkGrTtKDEBfnbSX1VIESikHkpH6MTFyMcGa7eEiCR93AbCeBmspRk6XRx9mcv4fEX/gEXgy8AvDx8HE45/S743I23os0CynJNacGpIqMmsUkVvBN4D766e4HQCu2XbGxZeA626HM2lqx1Y5eCLDhZBy4SVSnzXRLJ2hgx4cYGiCQjrFNSBEt19vm0FhUnbi94/vnncdlll2Hs2LEoKipCr1698Mwzz7R1s2w0AanEUmk9JQNfXrPQq8yXWO1Tn+DXOwJ9HiYRZG6P+y3McRrzPPUhRWLsnNgG4tOjigz3ZWQ7ykU5I2+mWIAMKpGWqDmyyL4Lsxq2Yf++pJDm22Cq0KaGZOcq1yNsQSYk43Rx5bypePL5G6NkNnW3Y3DixH/HkZmRbJ3+Pj87ujiu7TyvcGTujbmCUQS+ATadDtRcoZGZA/AcDXSfiY2uSZi6T1+8sWsdnt63hyKI/QdmNbguupgw77OOZELBZshzKc+AVYCI/iz70giW6oiCw41Bl7DQbr31VuXe6tOnD4qLi9XfNjoeUtU/23ZGqaopxgjBnyNisTrialJFAgH40jPqzqhV5k5Y50yKiepzX4i4rhj0QIstEIJSjhCXo4CuRBKW1MrSlTH4N12AehkZZXVF+j2Zh9NFdSmnJedOBQ29izSKXTqVa83f3Ott6nuTdcVqDs6U4sbzGd7HgzmrktS2ie48jNvfvg/XzH0yuujfY8/AlUde1SDfVea8EkEFuWjfz/uwIm4wQAuYFhujLlUCdmgVQIvM/078Obl3R6/uV2ETtlf3lsfkdZeq2HwGGakq++YzIGLSUmpIt6ya4uZLFiDC4zNdhM9LVMmkMJYnmShYqjMnancJC+3BBx/EN998g99++w1nnXVWWzfHRhNgHolaWWYkM1Gg4PyUDn30StCyIegSZGdg1CrzRbfT119YVhcd3bKD4VwJR7cc6Ytlsuzkflg9sT9Wnm4QqYzOuW8GTrBNyfQJVZKym+H5Wcqq0RGKdNJcvl9/d9TtpEbdJoOUX+evNgIdPBZWVqax8tR+6t8BAxq6A0nC6ZCZMxTEoy/eHEdmtx9xiSKzaD6DCbq2pRn52U5kuWL5e/MibRD1FhIk/w4Gq/HRH3cAGw6PJzPnECD3YYRz/wOne3sVnSl14yZ+sD7uWHGtUwEwYZU2wMGRblklspYSQf+d9zvdkknPHtAnmgPJdyVZuaXORmZdhtDoatxss83auhk2mgidXKSkirkulORuCVTlY1M+kLgVGQzgcBgBAdwnOyzpfEhqJCJxy3CPJCRxD3KfKprt2GKlim922+htZccWTvCiWblGaOGwAKiV9SGh9tR1LP7vKnU80YhscL1CVNhwKCslWR2xZBBrMRU2f6ZURU1aEVc62kCegA/PTL8aF3z6gvoecjjwyLn/wMdnXqrOUfLjGgNeF1rN0e+R6z9uoJFEHQ77Eap/FuvWHYKaTf/hFTNWdPSGK+c6eHu8AqdnrCJTEqdEkXI/SyqCiqhlUMV0Cz4DBw/KUs8DBxB0D9NKloGPnlpi5eYzu8mtap8l0njk8TnQ4ac3Mm9nVYi2q6BLuBwzFZVnI3PwMQNY+0yFnfNdWLQurHKNOApmDlj1ptq4l/WbY/Jx2vwqfFMZUuuH/PWoi/ieOLJmZzS8t1P9zn2w06altkuBR4XNzys1KjGTiLjvu3fJVhJUikxqQzh+VjkWlPkN1yLnX/p5sPCIXjjv4w0qR4wdnYqe8zrUfkf2MV6vResCGN7bjblUZI+0lYK21f6w2qa3F6o0DMHj66HwcnZ6aD5dTEe/UxYVJ7aGET7SFLdjgRcYWeDG+6WBBikBZjAGkdfDCqJckgg5vlq89PTlOHTph8a+XG5cPPF2/DH+aJpP0eRnKyQLNFHb1BiN4v3ome3AiHwX/rt3Nxz82vMoX3MnEPpd28ILZJ2OPt3Pw+JjNlPP1EnzKjC/rGHjmad3zY9eLF1UiZF9Nqi5NF8wV20z8YNqlQJBNyafzy+P7G3s3eVQz9PU0XnRdaU/Gf5qhbL8OBjj86uXJrJ6xs2w2ufOkXfF/A60ZzQ20rlZhDZp0qRmH4hm/kMPPYSOipKSEgSDjYnVspEOysrK0lrvli0A/2CozuS7aie2zw2hrGRlg/Xu2DI237RiheEeuuJ7Lz6qdKnIv8Vr/BjaPYRQ0Ilh3UO4YztfdE7kijovlm409n3q7HL1t0QLsk9ZvIZFKY2VOaj+YnU9fv5jPRaWZcctr6gLoYc7jNraWtw91KfaTXywOidKEMyb6uMOYX3IESUzAzoLONDbFUJlUNKsEf3tA+VWNDOG8b0hj4QbbB+fth37dETm5d4v9cMfNnek+rZW+9ePQxJOrDvSs7Yabz0xCXv/vlh9D2Vl4fT/uwczth2LPuWGSjLlu6zamO8J44Wd6zD+i5zo/TEfO9qycBivjdyEZRt+wqEv3ofFFV/Gr+A5FMi+DHAOUMOJlSuNZ+q7CnawDY9P6Sw+f+sCBuEs+3OFen74zC1akw3GszJlYtucQPT5vPIHL77fYDxvfB4ENQFa3cY5UG/zp99XINcNbJ/rVc9nomdchwyirN4VjzP2DrRnUOeXur+tRmjPPvtsNJfGDH3CVv/dvLyjE1r//g2DDGw0HbTMSGYM0vF60w/HzvmzGq6aAHJysjBokKEJaMaZC6qVVUQLacro7vj8k1hQwPqAE3m5WVg0vnuDke+LgwxX0jkfbcCcklhiNLftnWWM8uevDhgBAgwCCDpx6Je5yiLzhgxri6C7ryLgwNIaF4r7FykL7qu1/gYWi9FhW8FoF+fNNoRIqg1/i1ckjP/dKAWjuVudjuhcmzfyXhoBH7Jt7JOLSboqnL3B657IUjDvJ3557LSN70Ub1uLdx87DiJKf1Pf12d1w89WP45X8EbSVsGuRMcHJe1jlk3nK2DFcTgdOWpJreV3MCIRDuOfXu/DSLy/Gn5BrZ7hy/oaga3jkGhnHHTK4UH0f9We1umdr6k3nFnZgaPcgfqp1YWSf2PqyDds8It+DaWN6GNc5GMbSLyux1h+OPg/6c1e4RCw0J7bdwqgZ+b/+sWjEZNCfc1qKNtIktKuvvjphJeqpU6fC7/dj5MiR2G677VRYfHl5OX788UcsWrRIdVb/93//p0LlOzIyZRJ3VLSUL57PR7rXVs0PVASNStEVQTg9sWi/ZOs4TC4yWh9cnm1OQiKBBcP4urIqjswI7s/tduPHCQXqmFJtWTrbHycUq+VDniuNkgej3XhuiyuqlBssnasntpjKR8tyYm2a4r1x1yCOAIxgE4lAJJGN7efC/NKYt8Fsu8kXBpVwV1rQZaPBfffxxo6/WUUJ5jx6NrZeu1x9L++Wj4PPexzf5w9V7eZ80LQDCtW11BPYdZjdkJy3kqrYckyPK6xmxkKhtXjpF2N+TsE5CO6cK+DwjFdJ0Kzx5ogEi0j1BCUCfWB2VG9TVx1xOI1AE7oTe+QZAsSCaQcYRKw/k3yeJOqRc2fmbRiNy/PkHBuRbiRkOu9CV0RahPb3v//dksz2228/pfTwyCOPYPfdd2+wDgt80l353nvvYd68WLa+jY6F9qIqkI4enZXOIyfMGakoicvsoEhIo4qyGpwPt5faWH0iZVCko3xneR22Wr5a5ZQZHgjjF7qLtnthtRFBJ/txQkknUYGEwSdxIfkmfHVMIfZ8fU2UCBn6bxhSzckli7ngHE4qhsTO44fK+MrMBw3KUvM+80voUjWWJSrB0pRWCJltV/YbZj96LgZSwQPA8l59Mf4vT+Lnoi3UjVFk7ojVn9PvryLGLKBaK/QpYC6YBEIgHMQO3d/C98FI/leU5XoAWRcA3pMRcHjjlJj5QeJi+R1edz4vrHjAsj48Fu/djxOMRHYeg+5Dq3eELkj9mSIhSm07plokKn0kZNaYhOemaDP6ukCASJODQm6//XYsX74cn332GbbeemvLdXbbbTflriTZ/fOf/1T/bHQsJHrJ2urlSCd/JpHOI8nly3If1vuMoBBzsql0QqIqwWg1TtbLd+kDWeOskEUzTQK37BTH9vcqIWG6JUUzkSRmJQosuPqLqrjEZJKJgzqJKQR8E8E8hyb7oQuT1gXPR64egwF5TSoiJV9SxHE0Gbss/w6zppyPgk1V6vtPhZtj/F+ewIreMVc+j0vyl3vFQYhoNCpitAgQoZwXw9qPf28N6ko+QLDuLnxb/VOcGObgPmdiue9chJ294gqfCngnoyQZNpRedn4pZmnLtRJBas5t6VGthJ4PxmXUkxRRaJiSohMNEBtLUo3JJTulnQxK2y2hzZo1C9tuu21CMhPwd7oiZ86caRNaB4TVS9ZSL4fueknVpkRI1lnoxCbr6H+TCBetiYWEsUOj4PDUMUZSNUOpGe1YqNc7CxtRl4hYfgw6EfeXWGOOiPqHldXD0/1mXSCp+8+qE06GRKv6TVaJVJuuZ1XQFNs2B2N+/QJvPjkJ3etr1PdFA7bHwec/jjXdGz474chzkKxQJyJtH9s/Cy+ML0DB1A8QqLkLCHzUYL2i3CJ8ffp9KHp6ldofr4E5HIaWn1jvAqky3sNjRKNuNcOwzOlqlEANXWdRx2nz1qn0D3Pz0xEYbmzCc7qW2VedVOoqY4TGebIePdKbiKSyNde30TGhv2Qt9XKIygc7jZ9O6hdd3pj9p9M2ndj06tFcn5JUdB/qYMfEel+0AtiuitqgqoysC8YyGZtlVNgprtHIIc6CS9A5003JuRyO7On2C5jngiL8TqUnEmwmCSdBGltGccR38/DCf/+K7IDhd/xgy1E48uyHUJ3TvcG6jsigIJV4MjstWsKLyksx7OnJCFQz4EM7GdcO8LhL4EcF3E63uj/69Zc/hdR3KcpSrkGSO+fjuG/mMRLBYEy8mM+nPDf6s8aBDV2K/IxVv46otvC+RQ6oP48ybEvkNs8kvF2kdEyzCK2goEAFfvzxxx/YfPPNE67H35cuXYp+/WKdVGtj2rRp+PTTT9XfP/zwg/r83//+h48+MkZ0e+65JyZOnNhm7esISFSLLBMvh67ywU+x1BpjCUpHI23bqU+sVEuy85EOiJ+suKxLJLFz1TX0aM19sboOGwKGZcPldFGy89u5MCtuDop7P2CABx+W+hvMm3HfXI/rkMxoGTJZ3FwjbL/+Hny02qib1vgE49T3JWYXtgxOW/gGnppxHdwhIwDlraFjcMIZ96DO2zAIKJUValhkXuXGC4RrMfvXxxGup7KIYfUpOPrBkX0Zwp5DEQyPU4sYeC3kZDXQMOfQsQ2Lyn0YWZSlyvnocl7MPeRzWak9P0JMekCJSFUpHUZNfV8GhIQctrWspWc7qdRVxgjt4IMPxn/+8x+ceuqpmDJlCoYNG9ZgHZLHeeedp9wyhxxyCNoKJLPnnnsubhnn/vhPYBNa678cEj3G/dAyEwuNnUY61pY+JyFadpzQ5/NGxQ1afbq1p29DcDvpeNghDZpeEmUNWk6sdcbOUGqlMShE+lwqPggZso3s/Njhvr/SpyLh+PcL4wujlqeUK6EkEt2StOS4L87XEFZ9uZAZ0Xhjyjovq7Vw0YJn8OCrt0e/PzPyMJx5ym3omeNBnUUufSqXKlMjHhndC1v970mg7n6Ew7GqAW5nN2xecAGqHafSllWBJZITXVYbhEcbUUjZHQ54+IwYifSx6yxBLKzbRvUPJtlzLpW7IPkxQf+2IbEBVCgy78cBCQNCCHmmaL2bXeltaS15M3ys9kiQTa6Htm7dOowZMwarVq1SD9Bee+2F7bffHoWFhVizZo2y3j7++GPVuQwYMADz589XVp0NG8SEd8uxaE29KsEhdcIYWabPoSWz0PT5C3Y6Yt0UZjmwLhLgwD0tP7WfZUg0rSJxNwo5iWgwAzjYOeluRXZKA5+JFcZcdlJf5Xqcubwuzj0oJE2LY+wALz4o8anOkPMxS7VIOR1iDTaYc0mjLlq7QziM6997FDfPeji66OHRJ+HiYycjLCUEmoLAQqDuLiD4vbbQBXiPB7ImwePqo0iR13nvvl7MPW/vaD00x03z4q4t7zf1DaV0D58HDizM15r3mB02Xc4iSM1ng4naQwYPwlkfb4oTu+Z+ZU5VjiFztPIctXVQVabQXoNMmmyhUbn+7bffxgUXXKAsHZLXJ5980iDJmhGOjz32mE1mNqKgS8ZIXHbC6Sf5GNaY+QVPZAma5y+Y5yPh0bsWG0Qk1p6VxiI/zcrkdDfq0PfPbUmKxSYrku5HgUQ6RtsYNuqPScv52+6vlTeYo5PfrNBaZCZBEc2FIxTCPa/ficsWTI8uu2X8+bjhkIsTigynRPAPoO7fQMCU9uMeA2T/FXBtGWfh8eObBMrFWRErWSqHC8Hwn+QV6uDgQ54T6jIqyys/plBpFWREq15IkhAZKxLiNs+VNCjyKuhIBOdrx0EmzdJyHDx4MN555x3l0ps9ezZ+/vlnbNy4Ed26dcM222yDcePGKcvNhg2BiKcaIeJh9Mlywuk0XvJEE+TmF8bsttGDPGQ9KQtDK0zvQHQbQbbjSF0PGiBBWs19SFBIfo5LuRLN5VKswNawC+QsjhWZtQd8fGQxtnsxPQmyRHAFA3jy+Rtw5sLXo8uuOOoq3Dv2zJTbeiLXJ45OQpVA/aOA7/n42T7ntkDO3wD3Hpb74jjanHgtzlcGbhC6Ej3JiO5qWsgkvDEMNlnjx9r6cHRe15iTdatBOpU5jijLxi5/rMcLB2XHpYlwX+Ju5L45cKP2qDqdSHI+WyOh/URLRg37WkoMoR0HmTTZ5UiLTHLNPJ74sFUbNpJBklC3zfHjxYOLk6ocJHvZk72w/E0CLegmWnRc3+goXGpi0a2oux4JRrmxBIxOpNIGkXDbMd+FuatiQsPuSJdrlcPF33pnxTpZfZ324lJMJ/csPwuoSGDFZfnrMWPalTj6O8OKCjqcOPfEf+Cp3Y9NXwy5iFa2D/4Qta6eAeoeB7BBa2QhkH0p4DkSHocrtejyTftHXY64yWiXkQto6CbS2mbFBLNlxnU4Z0bQmiN43ylPZb5VhdkOVEfWlShHcWGTABkhG7JwK/MZk2RwfR5W3JSZIIhTWsEl2J4ss2ZbaIcffriaG/vuu+8y2yIbnQ5WuTZUEZd8nkTBHrprg8m/VpZaou04WmbHxDX4ySRniQ0giUhiNSFzKOxt2NGI7JI5OMVAGGWr4rs2sR+sSIG/6e48rlOU7cR2vYAfq8JKvT0dS09wQH+vcqklUqFvCtIZ0SYis251m/Da1ItxwC+fq+/1Lg9OnngXXh0+Pu3jqyAMzl/63zUKbYZ1Qd4cIOssIOtMwJGr7ue3JxRjp5fLLFVXrEBe6ul1qoT6+pChAiMuQeYZ0jWsJ6Eb98ihyIX3n/JbdItLiSF9XQHncUXiSg/dt4zkdCCaJqCvnylrx9dKLsH2RmbNIjRqM/bt2zezrbHR6ZAs0Tmd9fnJEi7ldSFlSZmjFs3bydytRKaxE7Lq+Lhc5lI470GLjWDHwnpjHE1LThzXe3dFLKRfRx8PsC6FuWA+PM+lPBak1yjMLWkE+7Uw8jdV4Z0p52O35cagdqM3B8ec9QDmbLtX4yzAwJJIwMeS+K08xwDZFwPOouhS7odk1hi3Ei0t1kiT54DbLiyvV0E+5qewIMuQ36L1zmdDd6/xOQgFQ3hP3YN4WS6RvLKy6mndiSUuqiQkWZKm7jLPFEF427FLsN0S2tChQ1UFaBtdE+m8gI0ZKcqcgnl9Rj4OikQX6jlqiY4jYIdBF46AkWgkKeYSsfijRJ1xnkMi2IyON9ZVcn9SfDFRp5yKzNoOLRu237+qDO89di6GlRl9QEVuDxx67mP4fPOdGqwrc4gNEFppWGT+WfHL3XsC2VcCru0sj52uZUZQ6ovQxaGZ7CzWlX6VCrXoVh064bDm2AmzyvBppTt6Ttwukdwa/+nRsdQH5fysRNo2JuKxMaT3bBfJOzOjyXG0VNBn+Y+XX345sy2y0e5hVVE32UjRqkqv1f7oJjSvT/Jih8EHVaILrY6jkli1ZT29hsuIFtanRxWp/DQeni3QQ/HpKtJk/4yyKRqo6SeE17HQ9I6MrrFk2HLNn/jowdOjZFbavQBjJv3XksxgRWbhaqD2bmDD4fFk5hwC5D4K5D7RgMx4W5KpoiX6iaVz+CzRGmL+Gcu0CMkJuHzFqf3w3YR+am5XBlR8PoSU9KToe4b5sGxCvspT47M6MklAE/9J28TVKV4EseTSeZfSXU9HVyOzZlloxx9/vCoPc9FFF2HFihU4/fTTVSi/jc6NxvrnzSNF8/rx82T1qlMh9ORnuoDGDWSicuLUDyZGU0OPCbGETOxLYnNUxpBKEGt8USV0UewIS8kWr0NFpomLKJ25KvPcSlPADpcwh463BZIlOe9Y8pOyzPpuMDrWZfkDMe4vT+L3AqOWV1KEKZX/AlD/CBA2RIoVHPlA1kWA9zjAYd0l8fomC6BJ1OT8iIg077Lki9G7zIriFDsWQWQ+b/q8KwWo6RmQ/EIJEGHYPgtoSti/qIJI1KQZXI8h/4yc5Hwd15X5WxJmOuIB7TlMvtMQ2k47GaMx1kK7+eab1T8SWm5uruX67JSWLNF95DY6AlKFzKfzYunkJNuxdLy+P4YyszNhpyIdg/4iU4kj0YusJ1mzsyKXicithF4TjMVlbq9M3uviwUSs60sP4wZ48PTYAhU0oB+nKRGMTSWyxMfJvMtxz98X4+0nLkTv2mr1/dt+W+Og86egtGdsjssStEgC7xv5ZKE/9NYDWWcAWecAjm6Naosj0nmJx9coatpQQmtdXVA9G5y35LPBf5ISp19xedb4TOjuZRGZFnf2vNIQbhgcn4KSrBKFqNFwT3yGCZk7o7ch2bs0YfZafFBijKhIqKk8HTaaQWgsHWPG2rWRGkQW0CtY2+jYAR1N8c83HGXGBj66lqGMXPmyp0Oe5iRrRikySZprUslDl9SiC1LX25NkbBl9D8/3YMlaI/osHVCnkcfnCD+kvVAHbpYNXzCIOasyP8FmJrDubsA6j7jx71syEj7wx4/wylOXIc9Xq75/Nng4Dj33UVTmpSjcS2WPWgZ8LIxf7jncCMN3Jq4EnyyYROkwmta1snI5b1oZuaEc6PBW86tEnur5afKsQcrYRMjNnUDJRd/GqhIFn2t5Ng0rPhyJuDQCkZK9S0zC1s9D5cAd1zetahRdGU0mtDfffDOzLbHRrpDKzdHYUWIychJXT4RXlMUjJJpMLcQchSZKDVSsp3I9l0notYTgS6cjCul0VXI55Y0kktFhEidOBP6++6ur4wiQLq5AKJQWmaWT/2WGmXASiGI0yUJLRGbHL3kXz0z/G7xBg0Jmb7MnjjnrfmzKMqxsS4RKgboHAP8b8ctduwDZVwHuHZt9ffTfeA+CoTAqTNdDLDd9G6lwzedN8sc2e6Y0btAjYNI9XdQckJNURvZxq32euaBaVYrmMye5Y1ZqNBKSLyBRinIIB1V0W5qfbQ7oGBkp4LPIYBWbzFqQ0Pbee++mbmqjA6AlQn/N0WJWrp7KupAaSVsV30xkOZrLwYRMYfn6yFlPZOUnLUNz0iyP9tvJ/TDx/TWYVxKwnC8T9fuGc2xhLFkbSGu+jdF2year+niBKh9gaNU3FpnxiJz92Ut4/IV/wBU2Wv3y8HE45fS74HMbeVwNEN4EUAW//r+kmdhy52aGVJX7gLRlsBo7L2lF7qKtKaBo9JLIPBYt80dG98aQGUYOBZ8JzsPSNSgWlsx5FecYyfnukA/L/lyvFEO4nPO+id4ZXTlEZLZIkBJkpBf91KECoSKeBRaY5byy7WZsBekrG50bLRH6a96XRChGQ+cdQHG2MVega+RZzavplqPsV88ZErVzriPis3Qz0uWjiCUcxjoLBQh2IsT3lSYRYQfdkw41WqcSxDyWMmlwhg6MKHDHJevGfoEKEGBla7YllcJ8YuurdXDlvKm4681/R79P3e0YnDfhJgRdFt1GOAD4XwHqHgLCWiSeoweQdSHgPRFwJCDBFgQtdRl80MDhYENC9jl4InnoliDJzErvU+a8OA6jhUZL7f1Sf4N5XwnfJ0SBRicuPZAk2UCR0bnpFry1EYNNaDaSIlNkluzllJecrh26Vph7xuPqxTcTuRjN7ZMORQ+3VlqNJtbiV8oW6SH74o6qiiiLyER8MBRSEXG0HNkZ9vGGlYq+lR3GPLbp+xdgwP9KLAnrX7v1xPCXW6PYbTOCQsJh3P72fbhmLuuNGfj32DNw5ZFXWVtX/g+BuruB0K/aQjfgPRXIPh8OR89oi9oCnAOjgWkoxMQeBN7PYc+X4KBBWfiqvB67FhvajPqzZTWoU67ocDjqkpbn02oAZlXIU1fdTwabzNqI0Bi+/80336CiokJFPSbC1VdfnYnD2ehgSFSNWsCXm8mmtHxUhxCZQ0tEXIksR3ErSng2u4NxA41CjXoAAEfHThhKIrKco24VjBeZfyM4ZzKcmnya1JXUy0oEEh7dmAcMzIqWo9G3bR0yazqcoSAefulWXPDpC9Flkw+9BLePO68hmQV/NhQ+ArEqGwruA4HsywHXZuort+rtbWhxigZmukhnzjHROomOQ5cxQ+pZtVpIyDz4ipvvXVCNheXZ2BAMxLm2Cd1zIAn5iQp52i7EdkhoixcvxoUXXoiffvop6Xoi6moTWtcD1emtqlHrHQTnI3SpKhn16lGJZpjz2qzUQvgXizjShSg1zxgEssMLxjybufSLuSr0iAJWSG68aCLnVjg3s/trZXF6f81F41IBGt9hegI+THv2Wpy0+B31PeRw4KJjJ+PRvU+OXzG0Bqh7EPC/Gj/T5RoeCfgYGbc6r4A5WANNIDMmQJtryZlRNrG/esb2vsuFkvXGMj1CkWH9HGzQIqPVrXLO6gy3oFRoSCaGzWd1nd+pnhVuy2eLz5TZc5AqJN9GOyO0P//8E0cffTSqq6uxxx57KBkshu1PmDABlZWViuxY6DMnJwdHHHEEXK5YHSEbnRtmPTspfGlW+qgJMK/HqBbM112XqpKADgn2SGaRmV080STqSHerLL9ji9WxaS2K20nqYyWaS1u8xlq/MR1s9/xqRJqeERwcmXtrKeT4avHS05fj0KUfqu9+pxtnnHIbntvl8NhK4Vqg/mmg/j8AjPB9BUd/wyLzHNLAiiOB0Opt7qXgXoPB1Gwu5X2YfybgI6fC/Fl1OgyV1sH0jif3zY8SmIpgfHl1dGCVKLKXc2fUgdwQdKrnlutLiaJE8leZJDM7qbqFCO3BBx9UZPa3v/0N11xzDQ455BBFaCzmSQSDQTz77LP4+9//rlyRzz/PukY2OjusoglJVJSfYkcjmPhBNb5akx2NQmOnI6QzYfYatS3JR7fwzcEhTMZm58NPjq4lH0yqQ+/xWlk0/Jn75Tr6CJ8K7Azu4HyYVVcp+n9N6Yz1+mpWyHcDFY0wUczuy0zOofWsrcZbT1yIvX9frL7XerJw/Bn3YuawMZFdMYLlDSMMP6zXTesGZJ8HeE8DHEYulxmpAl8Eqa6zmvNM43oNf7nMsMi00NAeHvKsMzqQ4b3h9WSqBuez+LxJqRfRAE1kVT29bw8s+3MFjl6UFxUd5jPFZ5CuZhEpFmSSfNprlehOQWjvv/++UgW55JJLLH+nRUY5rB49eijdx0cffRSTJk1qTltttHPobj+9nAZfQJKZjC71itUksp4eVprOVqSjfot0LvGSUsa+k41QZU5MyRtF1pHtSWZcpneclCJastZIGUAkIITzZ4EkHS0tDraXhkg6sliFWQ5U1IcbhN43hsyahvQ60qINa/HuY+dhRIkxbbA+uxuOOOdhfLjlKGOFwOdGYnRoqbaVC/BOMKIXnbGovuYgHd5Lx91qtY7TabibzZqcfEb5XHy9zpgPI3p4Y9Z8KggBMmqWrmW6mqV4Z6atKKvoXsK21uLR5DCakpISDBo0CHl5eXFKIOagkKOOOgr9+vWzLbQuAJlH4EtOVwwDPTgPxtGkiKtKyLJUrN632IPvT+wfdc/odaT4ruoPKMOsGUkmx6LgMNUh+GnGWR/EJ2vTncRtD9nM2IYuPGpDknS5Dv/1pnCtdkCO1OkuFajghiyHqrBNAk7W50k3w8rHTcsja3mK2KyiBB89cHqUzMq75WO/C58yyCy4DNg0Cdh0VjyZuccC3V4Dcq7LGJllClaiyhQi5jNJ9yLz/gQcvPDek7h0YWsS05BnS9XzKqTR4DiRsH0+H3z2mJ/W0gGJfHbpgeBzKiktjRUr7gpo8m1glWpdt7F79+7qs7y8YRRXUVERfv/996YeykYHAucROGKVeQgreSq6+Ugqvd1hfFMZiCMpvXOh6gZFiaWzMCdckwSZdMpPdkz6HNz8EkPCim7FCtYfi4yemRLADoiuJl0xhInUdG3qI3xKJlFaSsAOkfvhP+a1cd+JoGsBtkdsV/YbPn7gNGy91pCwW96rL/a5eBoWD+gL1N4KbDwaCMyPbeDcDsj7D5D3MOAaYrlPXo6mdOzp2hjctyfJb8I/JCtR1C/Ocak5Ug5odDcw/2ROIp8BPguMhpWmc705K+qiAzCBTnB0Pcpgjc+ePrhKVSKpsdDFB/hu8Rm2stZsNMPlSKtLJ6/Bgw3FzoULF6pK1oL6+nosW7ZMFdiz0fmhy1jp8xC6Th5dPMN7u7BkbTCq3yhuGlp1JA4a/DLRLjqPuvqHVbQjXUUs90JXoBBTlS8Uncdhh8DaVLrkkZAs51OYf6a7GLkPic6TqDYB52nWaDlNHQm7LP8Os6acj4JNhuL9T4WbY/wFD2NF3lxgwxQ6aGMrO4qA7EsAz5GAI3Fg1/gBWZjdhKAVdkD52Y4Gai2CAwcaydjzS3wJ9RR5X/TfmPzuynGhtIqVtoOW5X/UM6ENkGitcy6N86m87yQ1PhsiUcXnUs0NR9T2iXRSSQR6MnVj57/sCMpWILQddthB6TnW1NQoS23s2LF44oknlOo+i39us802St7oqquuUsEju+++e1MPZaODQB9J0lrSVRP4EnO+gjlm7ChoDW3fLYSfal3Rl1K2Z2dSlGUUTeRyKbqoSwgRsg0Tp0VomCNYujJ1UjKD7WPnwjaoebpQKGFFatm8T6SSsQjGdtQx8Zhfv8CbT05C9/oa9X3RgO1x8FkTsMZ9HlC3SlszB8g621DDd1hX0NA7EVrEjYEMHAJJKg3Q6nI7nSqq0HwfzYr4cb85OG9pOHojHwkhAyRaahxojdGksQgeVrQc1dzwujD8EbX9Bu1NQmZCqk0t/2ImzK5awLPFCO3AAw/EK6+8grlz56qw/IMPPhg77rgjvv32WxXG37t3b2zYsAGBQEA9DImCR2w0D+3poU6l4qGPLI2R7iYU9y9Cj7ycpNubS9vTdcjuhpWnRftRB8mHOUZmOLSOkh0ZSVDlx6Xoi7kdE2/ZKbUEvjqmELu8uibDe234TBzx3Ty88N+/IjtgmJ0fDNkOR57sRLXrHxor0K93DJB9MeAsTOsogTQZXkq7iOJ9qv2SxN5bXtcgSIfKHlL/jkSqW2ccoOyY78K8NIxnughlgERNRpIYSU2CmfToWkKeW31eNRX0eWErD0Nj3mUr2biO1ke0W0I7/PDDMWPGDGy55ZbRSKIXX3xRJVrPmzdPheoTrJF200034dBDD81cq2202zDeVCNH+T3kr8eKFesbrKdvb1UMlB2PdIZWSbZ0G1pBUgdEdZ+gvFU6YAdGyapZK1pG5WP3jJNZQ5y28A08NeM6uEOGyfLWtgU44fgfUadPSrn3ArKvBFzbpr3fVALLOplxXiuL9erSIBvukk0z6w6xejnJjFY5I1S5oiQoSKmXbyvSC8NRc6YRySrdTZ7oGdSf23ShD9J0fdHWepdPaYd9REvCUVVVlXHvCefWmHjNpOrtt9++XSRVU57rjjvuwOeff66sRrpFmUZwzDHHoCOCL5doHbKzlhIWHQV0R7PSOSNls7OzEyZl66NjKQ8jOVk8Wz5Z5gh4dkyisycdnV51mFYd5+jonrRyd7HTrKoPJ+yoObJnInbbRC82Pg/togXP4MFXb4/+8syODpx5dBgBeS2dWxlE5t47bSX8xkJSMBpb+JRgi/I9TAUy3M98BsSFx1vaw+tEtS8md6asoX/sj1BVGfr164+dH/oQn6+uayC9xW3pYqRVluw90snNILSGz62+nhWShdm31Lvs6+B9RLsRJ2ZUI/+1FyxYsADHHXecegCPPfZYdOvWDW+88YbKj1u5ciUuvvhidDS0RHmXtoLIYVklZdMik/kLkcOSGlUiZDzomdKoy4kRbgz4YJg2X+g9XitXCbUkuDiLLiI0bO5gmTf2+dHF2O6F1QndaNyOBOkMx1sn5mrJqdDUpO20EQ7j+vcexc2zHo4uenhX4OJDwgirKJc+QPZFgOdYwNGyOuVRTcMmxtFU+AF3IKxqzTFAJBRH22GVP8bADYa26yVjhJ83BMyBKEaiNXMeadUl8iJKMIe4H/WgEHNl6mSWkAgXm6002UdLvMveTtRHtKmF1p5Aa2zXXXdVeXOzZ8/G8OHD1fL169fjgAMOUJW3v/zyS2y2mSGk2tHQUf3jYqEd9qWhuEBNPCEu0V0U0uKIXK8rZR7xstORoA49bJxXRR+1W8H8m7LmHEZOGsP2qbbUvi0xazhCIdzz2p247MPp0WW37AvcsB9/zDKCPbLOARxJinS2IpLdo3RRkAW4nIbeo1hoffv1Q/D6OdF5UkOw2qvIz6y+YiRJOzGqyCAlPZhDt85fG7kJN//ZM1rgk8FLySwh3VJyRkoISdqIToIt9S77Omgf0RSkNSz7+OOPM3Kw0aNHoy2sM+bAnXrqqVEyI3r27IkrrrhCzfk999xzHVY4OZ0Htb0+0NRylHBtfo4b6FHuH3Etivp+tAT9Gp/qBPjy66U6YuVn/GqEbp5GS9ZRmn9TQsVhIwdNFCA6GlzBAJ587hKc+dUH0WVXHAjcuxfZ+ggg+1LA2bDqQVvihxOKccmnVaoyAu99U647A4E8MJKPZe5tdU0IzoiEGQc7tOT4jKngDM7nReqlMZBoXb0hVCxSanqSP8H1RuQbflop8CnPp/xuBXPNPxFCTlYRPpPwNjEIpdMSGgNARAmkqeD269a1flb7Rx99pD7333//Br/RQsskYbdHtKdJYfMLlOs21MrFQmOINomLbkYhOvPIXTobiUrTE0vDkarKGWmryjNr2Kk2ZQ6oNZFV/wdm/PcsHL3U0FwMOoBzjwCe2nVURAl/B7Q3kFgojSbFNRu1bWS+VO4Uicyj6pXF1uEeC7Od2DHfifkllLkyLH4KFIvlTxc1g4Qk4EjlJdYbFpVY/pxvm7ZPd6xYUa2UQsRC04/Dbaw0Hc2FPds6l+yUdtQvtDqhDRw4MCGhlZaWKree2pnbjfz8fBXhKMuoKNK3r1EGpC3AKgCERGPqKC4uVvNpTPxOx0XW0aCHI/OzelNti744iUZ8XH7exxvUqJYdAVUWfD5jZPvlYd1w1ic1+LoiGK0qHZ3Y16Looh1WCDjr/TUqmpGdzE69nThtTjneK2kojliYBXxwaC+Mmbkea+rDGSGldktm4Y3oVv0IXvvvNBzwu3Gu9S7g5BMK8erIGwD3fi0W8JEuEgky79vXrYIteC/n08LWBKsTXW92XEqmLAwc0M+NJesC0Tp15shIrra2LoR5JaHodx7r6b274bT565Xlf878tdivnwdfkeD6GO5ukpvMc7JWHvPTJs6vwm1bAlP2yAZcRgg+2865Neao8bnU3zd1HpF3gseTd4T9ydTRefAFc6PfzWgpvUZfK/cL6cAcYNOihMbcMitce+21mDJlCs444wz85S9/wdZbb63C95mo+ssvvyhB4unTp6s8tdtuuw1tASZ1ExRJtgIlu2SdZOAcHCsIdDRsn+tFKOjE9rkhlJWsbLHjXPG9F0s3OjGsewh3D425Ya78wYvvNjhRHXDAH3aoF4hq5ZLLs7K0DEvWZmOt3wmPI4w+nrBalx1IT1cYLifUbzL973KE8X6pX+2LwQALy33YSDMkmndlrMfftssNYt+3KiJk6NDym2LrUn6riseLbKOvG9ufvkyiB3XrTb4n2w4JftP3Zz6GFUzrhwOA7yXkVz6Ed/5Xid1KjLU2eoFjTj8Jc4ZdDThiVkTDdqdCg7TlBO03t6/h3xuC1uc8p9SPoS+tiSh+yL0MY7eeQXxe5VL32nzMXXsGsXC9CwE4MLfUr6JdpTPjMoHXyWhUWvuxduzZK4jbhtTghFl1+KjSpe49n8s3dq0DIknTV9ca740isxCwIcSIWGDRWj9qBhvPrZ6PxkARJlxf86MX328w3rfT55Srv83vRLrv02dVhntzr97BBttzYJcoH86f5LfW7hfSAaPghwyxllNrLJoc2kSiYqmY++67DxMnToz7jaS27bbbqt9GjhyJyy67TIXJcx6ro6J///7oiHh+UEPLycqSao4/naVgPq405huW1rhUsrSEOS/9shLr/IY1Re/MLgVZGDK4UFloZWVlGNivGKOK6lRdNHZWdP98XRFQk/gejxMj8t2Yv9qvOjpaa/v186rvRv6RA5UBh2nuQs7BgR9r3FhrGq7Li26M/B2KzCT03xC+MsO8LLb//fu68P5qdpfJ1rOCw3J/jdpWyWwsAOruRv+q3/De/4BhkXS2ihwvDj33QXy+xd5pnE8qpLomyc7buDeGXWQMUuLXiX1W+Bvu59nxRTjno+qI9R37nUOPnJwsBNYbA0zet0DEIqd1xedDuv9A2BisCLxOB7rn5ahn9KcvK9UQhm1kMjWfSxacNZ5FYN9il3KD07PQO7J9OOzEuM9zlMdq/34e5W3Q8fzgmGU16o1KrPWH496Jxr5PxA+b3HHbS1Fc8XboODPJb6n6hc6AJhPa1KlTlSvRTGZm8Pd//vOfav22IDSxzBJZYVQz6dWrV6uZxG2B7BS+8+b40/lSfF0ZjLoI2TGI8gePO6qoJrpvkbLS4fV6Me2A7lG9xg/LAqqv5sS+RDjKHAmV7qfuV6CKMnJEzTkulYDrhBIRFpcTIsuo7kE1ENneKwU9Q+GoC1Lkl/TE3F5eh3IdpXIvflspZNbKCP6oiAyBT7HlOmD2/4AtDFlGlHbvjQMvmIrv+m+N9gBGFL630rgx4m3kdeacaarAD6cnC06Vwxrvp2QU6rzVwQbzcKyAIHJrg/4B1MsARlMm4T3l3BffZytJNf4m931uaRBeZzAq5cbEfNbYi+pArvUj4DTmw6zeN/3Zl3eiMe+Tfl6yvbSR7wo/eY30xO/FCX6zQsft0VpAbZ8uRQoUpwOu9/PPP6MtIHNnMpemgxbCxo0bM2butndY1VRKVGepsbkufOElHFkHCVJUyfWXi4Ed+j7YuTAkWrUzZBAPc8xISHqLqAVJUDFfSsFQ4XxUcZahsh7pBMYNzFYT/YrAIkEBLPrJSXt9Pg0amYUixx7ex61ktayU5PWl682TNS2NUDlQcz2w8XhFZjuuBj6aGiOzZfkDMfqS5/Bd/23QHsDr9f6qhq42Xv0Pj0iepyocwSAKM6zEYJhmwcEPw+MZAZufZbjr+mS7DAV8p3GPddFseTblmZVnmc+PtJPgMyY1/Wj50DXOVRgVyUCSRCVc9Ge/Ke8TSxytPN0orWT1uzmYxJvkt66CJhMa3YokCXP9MzP4O9drbpRkc1MFKMdlBnUo9XU6O6weeL2GGTt7KeXSGJg7Bqvj6mAl6m1ersTBn8fGiFIKhp2P1QtJGSTJU2OkI1X12YFxG2LeSiM2m2VA2Ano5GfUZwvhgo+sz42jeL2PnLfKiHzTHWO08kh2obYIEAnXAHWPABsOBfyvGPNAy4EPnnag7yZjlW/7bY29L/kffi8YpLU6hqa8fc19Y3l9EiWakxz6JKoFE7neLPnC9IkGwSCmdVWQB6MOI8n4fD5KawwLjqWDlNUWCSyi21MXzTaDzyGfH5IYz58DIilRRNCNN2f3WmVhsmVsHr0FiQaCTSEV/X2y2j4ZUT7bBBLtTGgyoXFujG68G2+8Mel61HFkEvOoUZEKuK2MMWPGYPPNN8dLL72Eb775JrqcbbrnnnuUy+ukk05CV4HVA2+uYdaU+krp1oCiZbamNqQ6A86bmC01s0UnBHfAoKwoGauQ+nqoxNjT5q3FzOV1atTO5XNWGsvE6iS6uYyOh6oQPE92VpS3irbRVJaEWwVCsZkXWneprgjdYFYFJpuFcBDwvQpsOAyop9qHETV34K85mP0/N3pHXHafDR6OMZOeRmnPxFYPO+BGHx4tg3EDvErtxe12xpGmWEZybLrOAqFYR8V7xshG8zhCBYQ4nWpARktMb3ddxAsRiCyUT0IvOmsGtR25KvdpfpaZbrJLH3e0MCy9C6mIqymej6b+7u2CllmzCY1JyQQDQ/bbbz88++yzWLx4sZKS4ieTlbmckY605i6//HK0BZhK8MADD6jIy8MOOwyXXnopJk+ejL333hu//vorrr/++mgtt64CK9VuvpSZdlVIh6G7ZDjfUJjjVA9evidsWereXGdKRt8E/9a7hsVr4j0E7H4kcZbnwxH+usgqStvR4VDuSj1/yApzV8XklUYUeKKVrxOBlkhjZK9SIvAZsHECUHsdEBZRZDeO/2lvvPmcH3l+Y15p9jZ7YtxfnkRlXvJ54EwkiGfiqSBpzVnlU4MRDjhIUmKpcbAhj4MjEuShJMb4rGQZS62sYt5epnyQezj/2dNk+Z31wbpoMFA0KEhztUvNM1muI2x6lhl0IZbaitP6q3+prCGr98BGO5S+mjZtmqp3xog1K5cik2SZh/avf/0LZ555JtoSX331lRIn/uKLL5QbVMSJqe1ow0Amo56SCaPyxf5idR2GdQvg+YOKkwbc6LJWtKzMwRoc7S9gUcbIUyykzE7m+PfKMWeVv0GHKgm16Sbxci6DMEslNQUqty5ZHlzwN6Du30AgpvKh4N4PZ3+9Ax5/6WG4IgnkLw8fh1NOvws+txU5Jwv9bxr27evBR6tj0Xfm5IVUSKR1qScv08VHNyF5hddJ5MtSISuybVQH9OqxwPoyoGcxiu+cHyelJgSkS1uJ3JokPiNCkjy+XgxWpK+GDG4oTpxI0LirCQR3aC1HBnvQApozZ44KstCTlseNG4eLLroI2223XSbaaqODwSp6Un/BCzwhLDqmIC4CTCdVuiN19QZWL2ZF4UQdHLdacWo/ZfWZt3VERuckEnZK4SRWi1mdhJ1lKEMWmJoLtCK00DrDreh7iaymNWYokHMVrlzwHe5689/RxVN3OwbnTbgJQVfLiQqLGH9rZl+aSdKqhIyZGEUfkWVlpFLDrLP3UlqOzl7FOPg/n1hqJUpxWFELIeHRzUniYfVzzuHJd6mfx8Pu2Sv5QEx/7unO12XauurcVmuh2W8DK1M/9NBD6m/OqTFqkOobiRKZbXQdWHUiEoTCiXQmdeq/WZWM0VUjpu9foDoHbmsVVq+7h74sjyc+Eh3D/RkwwG11RXYzzGLF3G+m3Il+8wHC9UD9NKD+CQCbtAMXK83F/NzDceVrD+CauU9Gf/r32DNw5ZFXtbjyBy2kRCV2WkqE2Hyk3tkOVJpK+ejzYDI/qAck8bnbLseJ1VW0vFzRIJBEzxqtJnNNNA6KJKxfiElSS5gszefais50VyafNQ7e5BgdWXe1oyCjwzuSmE1kNnQkitKi3I6uUKB3BCQsUgmFYmVEzjB8CRqh9UWtPSsXIH9jR2K24ia+vwbT9iuMjrrTha5BklHQbeifCdTdB4T1QqM5QNa5QNZEOMNe3Pbsrbjg0xeiv04+9BLcPu68hGTWGDdgqnV5DZtDZuxc2EwhI1rGIwqYl5a+6zYYNMiMRBM2BfBEtUYc8YU4SVblEXcy51CFVHQvgTlVhZ8836JsZ5QAzQMyEpzVQEyHPmAjQcoxurK+YocICrHRPtGUCMW2aItVYApfZBUu7WDSbYyRmFAtnQxfeobjs/wH57b0mBJVsPGtNZbzU/NKAhj4TKkSPeZ6+tEZmJCItCQ0O6MIfAVsOhmovVojMyfgOR7o/g6QfT48QReemX51lMxCDgcuPO463D7+/KSWWeyKp34OqLzSklAJ69oxWDR16ph8dd84SOF8pkVMUBwkoIfCwFba07K5nlxMUhBxYkY5WuVY6ukrIhQs6R201qx0FEkyXx7ZO6WMVaoUFCs0Nx/URoYstD/++APvvfeeEvilu5GBIFZgJyWuSRstg/Y0wmtMW/SXl8HyVXXUQzcg6iPsEMwlNzjPQUuNcx9Mhv62Iqh+S9Z1sE9kzSsq8zP0n+tyfoQh/S3ehQT/BOruAQJz4pe7RxtK+C5D3SPHV4uXnr4chy79UH33O90445Tb8NwuhzfiYKnZKqNRmQmgDy4YuEMLmS5f3vI+2Q5UW2VJqwAUFxZoaiAs6qnPpTECstqvKYBEwvNJTryfs7R1vaYcS93VGBUO1lyKuqtQt+okbzMdiDchXRdiVyzG2e4I7YYbbsDDDz8cJbFEZEbYhNaysBrhtdVLkWi0adUehkFTbJiPDudGREKLo3eO7hlhphdDlJIe/GTnSLcOO7UPuQ/JZWKdqwRWFTu3UDiEiojXKxwJ82fnKkEimSwRwxcsEKoC6h8DfM/Fyzg5twayrwQ8Mc3FnrXVeOuJC7H374vV91pPFo4/417MHDYGnQG6CzNZKsHSyqCymHTJKgHv8fcn9o8LtiABMb+RKSE7aRnbFAyReUC9+vnCsobq9uJS1F2FfHb141AhvzFozDvYkkU+uwqaTGhPPPEEHnzwQfU3Q+B32203FBYWqpwzG62P1hrhpfPCmduSKMqLgRkUUjW79CK6wVEy0wlSggq4LTspdl2c96CriJ2eKtoYShAxx/mckFEIUoc5fD/JuKxxCPsQIImRzMKalqijD5B9MeA5FnBILCFQtGEt3n3sPIwo+Ul9X5/dDUec8zA+3LIpogRG2D6vx57FHnxAQec2RKKQ/UTgPWIgD+/9nq+Xx90jDny4XOZTic2eKVXPhcor0+boKIG1s6bZSFf1O8vrlHVOEvzppH5x3gS6CoUcBfGDs1y0JGwyayNCe/rpp9Voh1Ya1fRttD1aaoQn+zSHIyc7jrSF/yR8nq4cvX0Mo6eavnS2UiFaJv/pSpT1hSDpBeBzx0+uyy2rIpECUuxRYO4/2RG2ysyEMjdnG+7F0Arth2wg6wwg62zAET/S36yiBHMePRtbr12uvpd3y8fB5z2OxYOGNqsp9Ohlksx45/pkGa5CIyAjtTVLUm2se5OrMyqVz5nZ88OoRroW9YKZtMxEgSauvQ7jWZR1mZgvAx2uX1EbtPQm6PuxXYFdgNA4Z1ZQUGCTWTtDpl84IbFowqopHDnZ/BglqFgU0arDY8fBWmlLawLKEpMcogmz12L+KrqG4iWF9E6JHRwV86Wbi+4/RacprsRkq/FoBwzMiibcNhqBb4G6fwHBRfHLPUeqMHw4Gxa73a7sN8x+9FwMZCIwgOW9+mL8X57Ez0VboL2B126tLu6c4poXZBkivubV0nHr0v3HPDEGk+jgHNw2z5VEq5rz+eR8GK21rWasbnDflAp95Nmle1kS2zmgoqakTlhWlaT1gWJTC/3arsR2Tmg5OTkYNEiEUG10RuiuPj351DzHYPWissOR+RLOhdD6EoIiSS5kLlk9izcanQ1BwvqgxIjUGNM/voS93imlk9dUkOXATn28mMv9RTC6rxuPjO6D7V6MCQCYwYhHqvQzkjKRkohya5p76FCJEYLvfzt+uWtXIOdvgMva0tpl+XeYNeV8FGwyJPN/Ktwc4//yBFb07t9oJY54ODI3B9iM7c3uXUG6c5S85+ZrzW31uThaXXyuLvyY9c3iQdURPZSe82tfrzOeIyqLiOtSf44T5U92hmCtzo4mT3hRbJgRjskCQWx0LnV+zmfp4cgkOKsXnSNljp4FDLkWxXJ2FLTw6C6kC5DRatw3R+KUuKJrUkSGzaKxEtYvDy2J8ocTinHoZtlqPzpoRczTyExC97dPQmYEw71JZpVa2oAORc5ZFDeOtCK8wXAtUkBYJzPn5kDug0DeUwnJbMyvX+D9R/4vSmaLBmyPfS6epshM7RrNQWbey0yqhEhOn5RyMf8mJXpEpJiuZRJQqk6K6jEcQNGqNp+1L2S4vcWyUwMmTSJNnl897F//3lzY4fgdhNAoNlxVVYUpU6ZktkU22rU6v7hgxAVpJbiqCxCTgF4YX2jZQfDV3jHfreZJlCtR+y0ko/NgOCruSlBY+ODNDELlCHvfNw3hXhbzNB/BqutI1Z2QCNn5WEWTs7Olcj/JeE2tD6ifYZR0qf8Puy5jJUcvIPtaoNtrgGf/hDljR3w3D7MePx/d62vU9w+2HIX9Jj2FNd0zN4LPdwMFXsPqTJXvlQiZ7H65Lw4Exvb3RkWC9XkxLmcdup7emLbiC+MLVJHQZOAgiPfEagjCCtXELFZkCBnrchDOlA+ztdQSIsLNqVFmk18ruhz33HNPFeX417/+FUuXLsXZZ5+NrbbaSrkibXQumF9C3f1ndjvK34weo6VmlUDNOTNDcNiB+aUBNdcm8xbsxAhdJFaXEqL1RBcTOyQ92KSHp+UDPtghrmMnQ+FgCgiHlmm/egDvaUA2VTys1XLEhXjawjfw1Izr4A4Z9s9bQ8fghDPuQZ03kzWEHagIGNGFQc45IrMw9ptcxopQRMqoxMjNEZcfr6XuUiUhSWVrY/8hfFVuWOlTx/TBkOdKG4TuM9BEthedzqi1x5JBJPVsw62ot5PVE8xVHhKlvaQ795VsvaYEa9luylYmtPz8/DjVff5LBroP1q2zyye0JTI1MZ0oRcD8EjJKzeqlpOvy+FnlmFvKEi0OldRMcVk90ZVkyE6HbTZLCbHjY4HP6HmFkleP1jtO6ceSzeHwpeiTY1RAVnWxqFLFH4JLgdq7gODn8Rt4DgGyLwOcA1O24aIFz+DBV2+PLn9m5GE485TbEHAlqXbZDLRE8jTP5acT+2Lb51dHFTmswEoILx1YqJ4LKtfzmi8orVeWtVXlBHO7peYdyYyWG2WsRP2eQUS0pihxxcATpgvpc571wdgcGp8jHo+kWRjxGJghz52uPKJHUSYjlXTIp7GWWXvJKe0yhNbYuTN7rq1tkekRn3nUaX4JSUgkIU7eW1lx08f2wHHvlOHTKnfUvWhuq0Dyg2jJySiend2BA7OUAjo7v6QEpYWNc71lJ/XFbq+uThiwUDKxP4Y9X6KOQXhQBtQ8APhfj3fCuUYA2X8D3Dul9fxf/96juHkWC3UaeHj0Sbj42MkIt0juZubLx+h7JpQ3L8lr/W1FQD0HHBjI/RGXn6pJZwq8URURLAJuuC2J6fdT+kXVOvgMcZ6Tq1IxRLfBwqY5NBITB9TjB3qVC1Mtt1DeJ2QvjLblPK5EUSYilZYgH1s1pA0I7euvv27GYW20JlpqxJdIRZ+ftM509XKzFbdTbxfu28GHycty8HVlMLqOVRK1kBvV9ounlUS7auoC0lIT4kkEc6mR3V8rsyQz7pOd3sD/lRidargGqH8K/vqnotWijRUHAjlXYMUZZ2DIc6tTWkGOUAj3vH4nLlswPbrslvHn44ZDLm5BxXxHiyZF0zozq94Tkgso1Z7N94d2qES7ioBw9Dcn1DzabAsZMh6fMmeSaM8gIiE+WomJppu4z1jIvjEna5Xor5OIzA+Lak2i4Cer7dJ9r1K9g7ZqSCsT2mabbdbUTW20MjI14kvnBeNImCNydggcjXMyXISFdbKaUxtCba0Xebnx1rveVkQ6Rf6jdUZXUVFOzLVE0kwX0uo+zItKILnEpaozDQcNa6zuASC8Jvq729kDAe/5gPcUwOHFoGeNQJVkcAUDePL5G3DmQlp3Bq446ircO7ZtC942F4lIfGz/rKhShwrW0MjMGSkHI89Cw4hERrfGkxndlvMi1cP5TE2YvUblNupRtBSvVoLWtSGVY8aq1esjc2iSaC9BGUSiwZ1OInr+pV6axgp6jiS3S6eCdTreEpvMGo+Wqw5oo12huSO+VC+hVc6azD/oodFcLknLP2xwwlUbaOCWlLYS4vqjq3HrZ1dFpdX468zldWnV2VJVoiOuLG7fOyuMdVqyru45C/s/AeruAkI/a3twA96TEMj6C+DslfY1y/LXY8a0K3H0d/PU96DDiXNP/Aee2r01qqRnzuXYmHm4u3fvieErjchTHY7IPdDvtZXH0nwP6daUqgAc+JDwzOtwubikmTjNZ+zrLBdKI9YbB0RLJ/RVSdREssFdsly06PUwNSBZkJQZ9vxYy8ImtC6E5lhmqV5CsxVoNcfGvznaFZUH6W/1iXhd1ZwkWqVV6qDixAEDPCqwgEadPtcSMrm7BNz3uIFZqmMUlRG3afKHf3nCv8JR92/4fAviT959AJB9BeDavFHXrFvdJrw29WIc8IsRQFLv8uDkiXfh1eHjE7r1qFAyd6UxJ2iFdEWTPzmsO/Z6W9OObCUwF7BvnjvaTod+fSO5Z1mRhdRnZICGniAtpYPEAueqSmkm8qgwiETcgAzzp4IIf+OAh0r5si3vs1GT3ADbwuOJtZXO4C7R7xTT/rI8G6P+rMaMA7Mb7QGx58daFo6qqqpmRWtQCmbWrFn45ptvUFFRAb/fOtzMVtvv2EjXTWLVEZg1IBmdxo6njzsEp8upOiTJOxKrbso+vaPFOCUh1xNRHCEofbU2Rd1EdpAsPUOoOZFQSJFiSCeH0Dqg/mHA91JcGrHDNQxhlnRx79roa5W/qQrvTDkfuy3/Tn3f6M3BMWc9gDnb7pVRAd9kYIduXLnWQ5ZGuLSFxg3KwqI1flWoVSxo3hOC95X3nGH8S9b6VCg9XcoMImGwCOfXCiP3Twq5CpHJutRhFKkrY+DiVRYan58lF++DkpISOHsVw/OPecr9yXUYTZvKhZjoWeezLR4DngetQnNgSabm0Gy0gYX27rvv4sILL0RlZWwuQ+ZDSGD6MpvQOgasXjRd2dycv2OGeVtzDTNCgkeCQSPcnh2hWSuSOWbi2glH5r42+OMlj3ShXKtEaI7oeUxzmRKeQXd3PdZVTwPqnwCwKfajo68Kwe+Vcxgqg+lFH+r2Xv+qMrz32LkYVvab+l6R2wOHnvsYPt+8YSRkHy9Q6Yu52TIZYt8WMcV61QTKZc2jJmfkektpHwaEEPoA57R561TAxrYzSlVfwfumNCOZLB2pVs19KzFruhPXBaJzVUzg5zPD9d1OZzT1Q7RZinNc2GlATJuTz1iy5ziZN4LBJHxePY4wRvZpGADSGIKyyaydEdr333+PiRMnIhgM4vjjj8cnn3yiRkRXXXWVIriFCxeqSEgmWp9zzjnIzW3Zsgs2mg+rkalVCH0qpX3z/ghdKov7Xltdgz3eWKdG9PyN+okM8iDRiStJBy2rRLNEiTpv7ttMZkzYDdW/jXXV9wFhPagjF8g6F8iaCDiyUWXSfDpwoBfvr/JZks7Yfl68X+rDlmv+xOzHzsUWFavU8tLuBTjwgifwXf9tLNu53gf0dAGVmdSXiiJzHabuOmxMx8LtSERy7kbZl5DKTZNow2hEqcU8KP8m0THvjBqitNbMc1UkMLGarNzhHFfTIpOgDYIWYCJPQyKXoBAdn6l8dxhTRndvyqW00cJocgIMVULoXrzzzjuV/JUIFV977bW46667MH/+fLz22mvIy8vDggULbFX+dg6rkam+jBFkutJ+Knkg3TIj6FpihyL6jBwhsx+TYp3sZAi6ccYNylajcv7jQJrr0P3kMLnniDX14TiS4TbjBiRIUg58Bf+GkxCs/btGZjzIBKD7OxGVj2zLzpsVk63C1AmS2Y4lP+GjB0+Pktmy/IEYfcl0RWZW+1PNQUuRWWbAa0ki//q4ouj1Tge8V8zlo3tY34xPwpxVhu4iwSKb5nlQAe+7WUOUnyIjJYMj/tu12JBCI/gcWT2b3JbqMkQqXUWz3JtOdGzXhqAD5328If0LYqP9Exotsm7duikrLRHGjBmDqVOnKkvt3nvvbeqhbLQCrDTn+I9kQ6h5p0jvZCY9M9ihCEFJ5yMK53T9kNQkyo375ahXd0myI1lxmtEhBkKGu5Gjc73DM6dvyYNMFYpnDyhU6hFRBP8ENl0KbJoIBL+PLi7oNga9818Fcm4EnMnnVZKVndnz98X44KEz0XeD0ZF+229r7H3J//B7waC4Dr11nUyNm0EjCZnBW8/o0uEvl6ftDuVg4peT+6s8MbqHVTqfaR26EhmRyIRoK/Be7j/AUI7R88QIKx1RLjOTlZWOg5SGSaarmEycmJ4JpgT4ww5VmNbWWuxEhFZeXo6BAwfC4zFGwxJOXV8f7xvaZ599MHjwYLz+eiwPx0b7hHlkSitLD1GmXiLdP9Ih0GVkttZ0q45gR8PRsaoWrIkOE8O6h9SIV+8W2JHwuNyP1LuiO4nBBTp03T62R8RuGUzAztTF5zFUBdTeAWw8EgjMiW3s3Aa9ej2JH/7vNbg9Wzfrmh3440fKzdi71ogq/GzwcIyZ9DRKexbFuUVTiGq0iKMw3e6Wx1x8XN+kx061L/YCtOZeOrDIeAbKG/qIHVpgB+fB9Dk3pb/oiFiFkcCNRIRjdjsSMicmHVqifHUr6yuZOLFOWmzPyD5uFHhC6tOeB+tEhMa5Ma83poLdvbvhUy4tjWnsCXr27IkVK/TKvTbaK8zqH5x0J7h0t77ZqqNhh8DRqlVZDLOlJx0Nt2NHpSe43rGdT5GkgAEBdEdt9kypsvDk2M5IB8VtGV2mu7/45weHFyrLTO0DwNwVG9AL0+DYeAjgmx6r6OUoAHJuBrq9hKzs0ThpTnmDObbG4Pgl7+LNJychz2eoiMzeZk+M+8uTqMyLz1WzslISIXNj/nCj1hzxUmmTjz1+QBYOGJSlSIqSUeoZiAR/mK3AX0/qi59P7q9c0GbwHnLAlCgKUa9ezudAniP5jRCOXFdn+HIpmWWGleSVlcvdiuCe3rcH3ti1Tn3a6ESE1q9fP5SVxWpLUWmf+Pjjj+PWW79+PX777Te4XEZSo42OAXmZ2WmsPLUfyib2j3P/mMVcdYgLSBRCBEKGxKg3KnHEwmzldlL5SZEItqhVVhvCp0cVoSjbGe2kuE+6HnVPD0f7TJilAr/yM/nfhX/Dkfhp9R0IhyUXKxtgUnT3mYD3OMbkK0uO9dGairM/e0klTXuDxj5eHj4Oh5/7CDZl5aEjoqLe2u2YDp6KlP8xhKPr1aCE9/rgQVnKcpP7ywhHSW6evn+8hUQLm+H9UjLIDDO5MGqaxCPL9IEUvQHiWdDroSXbp3kgRiSqY2YufWOjE0Q57rzzznj++edVTbRevXph/PjxePjhh3HTTTehuLhYlZch4V1zzTWoqanB2LFj0RZgfhyDU5YsWaLm8qj4P3r0aLz9tqmycAdBa+SvmEerOoHp6xDsNzjPJuRHMmMHweARgsVAzbk83KcRfh9REHECv51s5PQMml6iXFFUh2DnN6rIq/ZFpXVq+THaTfKO9h/gVUnS3CYU+AaOmn8hHFwcPRZDErJyjkad+2I4nMVxJUbSsUbYCdNimLOiPq5q85XzpuKuN/8d/T51t2Nw3oSbEHR1XJ0ClZKXQDo/mbtUuQpdDnV/BByU0G0s0YUSoWgOstAV8El2iZKNzakftOT5/Ohan1xHBlDcvq/TgbpIPbR0RYXNCdd2AnTHQ5PfwIMOOgjPPvssZs+ejRNOOEEFgJC0GN04YcKE6HpKmcHtxt/+9je0BUhc99xzj3KP0orsyCVsWqtGkkhUmaWrzOuYy7roKvvSv+mh1HoYv3RmQmtnfVChAkcEjChkZ8hw/iHPlqpoONZQIymRaFgFm/3vrD+XAXX3Av534hvo2h3PH34HJsw3ggV4nEQqG/R+aYdWoFuTZOZ0OFSFal6CytoQ/vH2fbhm7pPR9f499gxceeRVLSgybCDdObj4LRqHdUkS1XnN6RKkwr0emcj7wXvO4B1Bb48xpyXzXSQfkpqe/8V7u1buv8MRR0bJUj/Yn4jotbiZCeYt6gMo1kFjLCU/BTpZJQrP149vCwR3PDTZeD7kkENUpKNueU2fPh1nnnmmCtXng8d/O+ywA1544QXsscceaAscffTRimRXrVqFV199FR0VTSnl3tQoLHYioseYjDj5G8Op2YnokWMcjUvYvZWKPvHJYb2wb35QySVxHo2lOiRBVqIfWRqGau3Sgeqk9N6KdZjz6x3AhsPjycw5BMh9GMj7Dy76zHBvJgOPZSYztdwBFdhAvUjqPq6tCeDVd26LI7PJh17SZDKTIIh0R5QtGU+XrPXuyLEZcUqX7/4DjXlQDkgkN/miT6ri3HCVfqgkaYL3n88BBy8kHT5bQnTCgewnEnkB9GdmWG+nIkEOlvjM0H3NNnF7LuO/RO+G1XxYsgARgU1mXcRCY3Tj9ttvH7eMRMbw/Lvvvhtr165VgSM9erTt5Km5jZ2tqGamrTmzyHCq9utiwox6pPsPWhHGRCNijtTvHurDNb9lY15pIC4kn/NitIzoymxQGibsR33ti0D9I0BYU9t39AayJgHe4wGHR3WiuqpIusnCJJleWYb1GK2HFvBh2rPX4rDFBnGGHA5cdOxkPLr3yWlcUetjK3JuIZbiOfhU3Hp6z12yZohMGK0oBuqIhUZCC4WMcJvZy+vgcMZvw+eHCc8MDpGgGBIOrXd1TC2unvs2637KpzwzXH9+Sew5oWIHnzc+e3RXiotb3g09bD+Z+odNWJ0LLeL0ZwAI59E6E6hZ2VhQyJT5KgzxzURU1NTRefAFc9VLaNUevWy8FNfkZ/Wm2ka9uDvnu7BoXVjVLAv561GXpBq0fmwmyoqrkS4mHleXGAoFgwgGQ+rT5/OpiftvKoOqk1Jq7BELjOVd9u/H7VyYUxrJPGYPFZgP1P0bCP2uHdkLZJ1uqHw4ukfdhWP6urF4XUDVPQs3ohNnvlVQK22S46vFS09fjkOXfmj87nTjjFNuw3O7HB7dpiASbJdKWzLVsTOFiPhck7Y160ny3vA+MVpQlnPP4i4m1ONh4c5V6h2m8H3eRv3Z5V3eqbcz+pzxnZlX6o9a4iROWvN7vV0Ve05I2BFy5DMm7wXB5/yk98pRVms8N5wX5L7lmeZnus+0Ffjc6p82MoPsbEPQoM0ILT8/X7kRZ86cmXLdww8/HJ9++mmHnr+irBdlvtIFOwGqcq/1O9WLt+zPFS0aHXXlD158v8Gpcrto+Wyf60Uo6MT2uSGUlaxs1L5u2QK4osaLRWuCOGFWGe4Z5ouek9U5yPKheV584jOi2EhclLaS9tQEgLklOSopdW6JDytL16ttts3xIxgwVEOowMA/QnAolXWGRy9am42Kuh+B2ruA4Bdxxz2g70H4qv5yVIUGqo6ut9vQWdqxewg3bV4DbA78bakXn1e5Ip2xYRvle4yk43X+hhli/GWdWtmBnrXVeOuJC7H370agSa0nC8efcQ9mDqObPYyeCMPtMUqUbJcXwlp17ubZLp1YdKsp0d8N1zWEhpFkn7Fz46ef2qkMg3eHURmQc7Re17y8hyuE9QEHAtpvYW2f8n8sbTt+P7y2ut+YVlwoJL87EA4FsXLlytjz2S2E24bUYNmfRkTqwvJs+EKxh2xNXUhNF3D9ynrj2erhNo7OZ5v70p9Jee8kvqW8LogT3y1Tz6B/sPGcrlixHs0Bj6FHeNtovgE0ZMgQtCmhyRxZY9bvyOjfv3+jt2GJCcNCy8KQwYVoKdA6WvplJdb6w1ha40Jx/yI8PyjejdPY/f0U2d/HlU5VVZoVV6ysTd0Kff6gHlH1EI6oaSGyPZOXZeP90kBshO9woKi4CGd/UIXP17uNTk8b5Ksu2OmEu7cL4/JvwQs/vxhHErv13Q037XkTdijYGVu9VKGW8Vd23hy985hHL/IokVs9AdsQyHXgh+MLcNr8aswplWG6+Ro5ULRhLd597DyMKPlJLVmf3Q1HnPMwPtxylPruhAMer0MFUnC/X1Y71ctkREM2vOYxMtCXWP3dcFkyzY+xxU7ML9OJyvgk5WxsIK5szHv19NB60vIN6fITPUWXC/lu3V0rpOqIEkcvr1O7trH9HNjfg2ljeuK0+VWYWxo0pM2C8cYb9z9k8CA8PzjmUdCfoV2LEGehFWY7se0Wg5C1vBqBsF/t0+VyKqvtos82qvtsfib53r3niDxTYQeW1njUO5EJ9+LE+VVYtNaPkQUeTBubfm08G62DVokzpnoIIx2bismTJzfKxL/ggguw5ZZboq1NYtZLaokoKfM+2bJRRTXR+akeeTnR5U0BtxtZuCmqUL6kIqBIiJ3c4oognJ6sqGuT3/XlPSK5TKOKatW8BiPS5q+OkZnIGnk9XnxX7bSMPAyHN2HN+qnY7dmn6eyN/eAcpGqTvXzMRHTPchlVj7XteQgex2ruTJaw4z5tQTUWlCX2OW1WUYI5j56NrdcuV9/Lu+Xj4PMex+JBouFudJa6i5Fn/cep/TDwmYbCAkRvL1BheoS5DUlCpc81cbz3QZTMGkLfp9hplG767OhiDJkRE2ZmgEXsXFgZQ/TxY5CUBynJs3B1PdZp155v9/RxRUqlJeomTlB0VZ4fPmfmZ0jyFLkfuis5P8b1v66MEKR6No1nfHHF+gbPpNq/K1Y9gQMx7kPeieaAbV1SGVJeF37qx7TRRQht06ZN+OWXX9CnT9PDzJ9++mm1n3Rx5JFHZpzQmopMP/CJgj3SDTFOl2B1hXI90dQc4pwoUIVh2Cy6yA5HiQw7jGDAffoZRRY5jzK0ewgfVsbUQPK9QdTXvYYNG+8HwjH3dM+sXqh2nIew92Q4HV5kuY2QcAYFUOHKYeo1xRpL1NV/sMpvzPuY1ie2K/sNsx89FwPXGy6llb374oALnsTPRVskvFbcnueVDGYyI6g3yaAJqffVFJidiFaQa8/5TUYJXvBRhYpUZPI6A3CMUk+h6LyX1xmrXyZ1xniE+SX1qKwPq/QJ87FcJLwgw/PjBwp6uyS52lzI1arIK587UdAn5DmTIp36MitVfHE5FuU4M5biItJXnEKg18Umsw5MaMznMs+XLVu2DJMmTUq4TW1tLb788ktUV1c3K7GaPnQbqStHZzrykR2HVdVpHYmIlN/1ZFkhuHmrjLpXXx/dGz9sjJHZLr0XYuOGf2Hphh+0vbixeZ/T8e6x1+PyzxjgwgRdjyIy7pdRkOyk2VH29DoxosCNJWsDSnEi2o6Ii00PDjHbZrJ8l+XfYdaU81GwqUp9rx+yJXJefRU/z0usciMxLzyvLRJYZ4nADptJ28kQc2M2hE4WDclMXIVG1GY4EsihFO9X+hRJTR1jRKEynF2HbjW7nSzhEoiGzidCD69Dlf9Z7zPIMBxpe+8IYZKIJOrVXPCVCFnIW8k6iZ4zq9w12XZWxOXIaNlMgq5Nzoe35BSCjVYgtG+//VYlUpsFis3LrFBUVKQUQ2w0D80p356KDJMd0+rvROvo0DshJtXqslYrNvpRwaCM4K8I1d2Fhes/it/YPQ59el2J7fpuhX3frFfnSzJj9CTdmCQykgnz2CifRRKbv8qnenAu58S9xCaw7lgqj94Bv36BV5+chO71Ner74oHb45AzH0foY1esunUCyLGSd/nWSBVmlEycK/k5GWfP/80uWLaTKvqsCE6y0VU+zOB5UyYsFUiWc1YY5WAYKcnEeH/k2F5HWBGLOQJXr7OnW2iEngqiq9CkMzjj9+1zXCg1xiUZhy191QkIbe+99477zjpoVNs/9dRTLdfni8KinltssQX2339/u8BnhtBU9YLmkGFzIMdh+L5UF2b3uNeby+CofQhh38txVNAzZzg2ua6Ey7MLdu1rFHaU9AN20FEXZoS0mI/UmwoW9SGDdMIGydGVx22pDzl7ZfL51yO+m4cX/vtXZAeM9RZsOQpHnf0QqnK6Aym8gWwDXYcN8uXSRMuFSqW+vwbRNWyBJ0KkYU2dQydFSlWJyocZ1N6klRaXBxY2QuyFoETpQ6wvWtoioWZ+tq0GYekMzoSkrcSJbXReNIrQdFITQvv73/+O9oyff/45WotN8l84p/eXv/wlus6jjz6KjoSmklFbSvmoTujYYuz0wjKs2zAN/noqbhjWEDGw+0BM3vMGXPrFngiEndERu6jhsxNkFyv6ikJ0JLGK2lCcpUOLLBQOY0SBV8lphRPNe/V1YvCbr2HqjOvgDhl7mDl0DE484x7UZ2U36OtVqZvIMlog0fkrFUQRakYSNDIGkg3zuuaWBhpERzojLkTd2rRKMhi/WbZy54lUFZ+X499bg2/W+dUAgdZWonk/WtH8nQFBYrnSYqP7mSABkWtIlDxGMjWbZPJUyQZnKtI2Mokm4sT2fFfXgKOqqqpjx9OnwIcffogjjjgi6ToUWLaRHprSOdA9NGdFDUK+txCqux+hUGzOppunG/66219xwc4XwOXIjooTmzt76XgZZUe5LQk40X8z/22GRPqJ+sX585/BA6/eHv193t5H4qCjb0bA5bFMMlZq9GFDQYTE2s0FbAwawRZNAc+FsIrK5P67exxKdithsIeFK1TPHtOtNCZ/f3RUMS77rCpKRqKJSQtWP4Yo1lN6jKBmIq00RhdyHowuQH1OTaI12RZuy4ELVUW4DtvIyEoSmghX63Nj4nbk/mWddJ+5RMt5jJln7QWsL0N2fl+sXvYjMgUOilkKa9CgQRlLBrbRAaIcSRJMRma0YVZWw9pIrQUWGLUJq+kEpf/eFDktjvI/WfkRfBv+FVct2uVw4ehBR+Om/W7CoN6DostpfUkUHefzSWoc6UsLaamRzPQ6Zm6NeNwWQR9Ccux0l53cDxPnlWP00w/i5lkPR9d5ePRJuOSYyQhFCtUS5lB6c+00t9uJcDA5myUjWOZyJYLSJqwPN5oMNUGpuOUMy9/uxbK4pdRnnL5/AQb8ryReHSQUUtGKQtRCXkJwLNXDQBGSHsWjWQWBv4kbUSpDS+COuIxF0Z7PBCGkRxJcdFzfOFUZwhwJaUYyFX0B3dE2ug6aTGgsxfLWW2+pMjGcI9MjGy+66KKoEDCLe95333046qijMtNiGxmzpFIRlDkaLd2gEvntyJlf4vM/70B9/dy4371ZY7DbwKvx120K0dNbkDRdIBAKKQtCQsgl9Fy3yOi1kpaQjzj2F8uFD3hkak0tG/S/Vbjn9Ttx2QIW/jRwy/jzccMhFzdKZJjtSBX5R0g7rZySyQJNrF5SNk+IR08aT5dApT1RnRCHA6fNW9uQuJUFSr0WYxAgrkOe88DpJUpZn+H+EgXLe8XfSLLiRhTiEtLiPeP8GSG6iyRUcyHY5mqRmqMcW7gIgo3OQmhU1v/Pf/6DF1+kikMMt99+O1555ZXod1pH5557LrbeemsMHRpLTLXRckinM0g1sW7+PVnej74dj72wrAw5gcewvOLZ+Dg957ZAzt/gc++BLyqAfT8Jw+mswDhTzTTpKIniaSXRDjqWM2W4qIbTUlgbwJqIJcNfZH5mx3wXvq0IqrbOXlGn8pJcwQCefP4GnLnw9eixrjjqKtw79kzlkqsOGPsY3dcdJ4SbCaTaF/tzJpzz+potwegV1BeHrQMyFh1XjFNmr8aH5axc4LB0ne7bz4sfqwwLi2RkBbHOSJoMsllXb5yDkKjUPBMiMqqKO6IpFbw/egQl/2faRThspFrIPsYNbFjRoakRuQLur9hpxPPYQSFdC022x1k6hj7k/fbbL7qMah7//e9/lRI/S8b88ccfOP/88+H3+/HYY49lqs02MlBmxlyh1yqPzPy7udyGXpKDx9ngq8OCPx7DmvKDsLxiWrQrznIXwZ17K9DtRTjce6iOl6BeoIjMmtsp0Wz6UrqleHy2hxbK3FV+NcekqxWK2+ulA4vUugvL61VnnuWvVyLDQmZBhxNnnXSLIjOCElZsCzvb7yqCKngiXZAweE6cY0vW7Xoi65IDTAaJCjahMoaZzBJh3/4etQ+eLy0jfjK6cNAzpVhQHi9PzJpgJCX5/kFprCSL3ONxAzwJOwPm8PXJdkSPw/UYsSo1zwihDd5L7ptuRn7ymHQbG0nVXuxanK3+lm3ourS694RTKy2TCFbPN5elU7HaRudDky005qD169cPTm3O4YsvvsCGDRuUUgcrWBM33nijsuY+/vjjzLTYRrPD82XEmyrq0ep3syIDO605K2qx9bSn4Ku5F7X+FdF1XY4cZOeehdGbXwC3M7dBkjVzx0gBoh5hBjtMUbTQO9A5K+viKk/rwRHsyMTtRXcaCaJb3Sa8NvViHPDL52qdepcHJ0+8C68ON55R2Y+AZMm5F84lpROOT3klWgLJcsYIxlEeODBLzTuJK05A0jUfSy+CasaCiA4l3Xaq/eH4aEmJLmTbeM0f2qsXNvpDGP5yeXQdzlWOH+hVlhqjRhMF1khSNg81blC22heriZsLvYqLeI7mIpYyQrIuwXtDaatEBWR1kqQVRxe0qIOk44lQ825pVKy2Ix87H5pMaHQlDh48OG4ZCY1uhgMOOCC6jDXRNt98c/z222/Na6mNtJGMqMydQKqXOtmEPPfx6crPUVX9L/iCS7RfHcjOPgZ53S7FOn8Bvl7nxLcnxFQdJCiA69GqEcUHK/AYLEsjUXEkKX3uSFk6ekADgFPnrsM3FX4VkJC/qQrvTDkfuy3/Tv2+0ZuDY856AHO23SvhMbl/kuivJ/XF9i+sbhDFaFbvkLpgqeaxuJt5q+pVQrORhmCNwiwHdikyIgqLppUkbCOhR3qa5+lIko4w8M7yOgxZvtpSz19y9JJFUnLOTLkbw1QZqcOer5c3IBG+9+KaFtewLlMVt09XbP7N6vniMm4rWqJWdflSuSWtKla3duV3Gx3I5UiiYhFPHSwRQ+y+++5xy71eb5wlZ6PlkWhUygl5dgL8bI4r5peKP5BVdyUqK09BWCMzr3dPOLq9hHDOLdgYLFAdopCRyB7ROiEKPCGMyHclDS5Rc0oRTb8Js9eo0T/hiFg7K0/rr6oo65i7ynB79asqw4IHJ0bJrCK3B8b/5T+WZCauQIEK7Xc5VDVuuhNpLfGTxzWTl9kyO2BAEl3HiHhyouIT6ko4jAKnMeKPQc1VmdZnu9h2rk2LdslRPbFPbyOvTk+dDmuEKS5Gq9RqCRyhm7L8jAFx7lcu10lEJxYOApSbkeR2bLElmelINpjitgcOymqUS7ylKr/b6DhoMstss802WL58OZYuXaq+s9YZc74oQrztttvGrVtaWoqCguQPt432CfMLX1VXhZ2nX4ldp+2KV38xIlmJbXpvi2ePeB7IfQJh13ZG2HlI6lPVq7k2uo6kMyG26xbCkoqgIjmrY+md1o75Rqi43sW7I+4kpRFoIqMt1/yJDx44HcPKDM9AafcC7Dfpv1i23YgG50j62W+AVwVlOE1h8QaMHCxqReotjHj7GhAC5/ZknkwIiH8fPChLkS/Pp3eEHM0w3HvGgIMuVj3q3Bmxfg7ZLD7/aXgfl3LtSefeN9eNO7f3KZI2g+vsWpyl5hhJGDzPRO3gIHT1xkCcRcy8NbaJ1i8DQPR7xIhIaa45arEpIKnpc7ZmmOd0BekkazeWCG10cpfj0Ucfja+++gonnHCCCsl///33VVDIscceG7cekxBXr17dLHHijor25qcXi4MEk2jeKpFr5r9je2Dqt1Nx52d3oqLOCL8mHI58DO13OT44/i8IhV3AhzEXmbjADA3HsMpVomXCDnF4byeWrHWqmms8hh6qLx2UhH9v81wJ5q0y5mUE7LIkmITnwUhJcXkV/7YU7z52LvpuMIhyWf5AjPvLk1hVNAhjCzzROR6BP6JtyD5YVUOOWFEsBSPuQ843mTX8EnkNJUVgbD8Xst1uFexBKS6C50hy/raCSh6p8dvJ/bDTi6UqaMUIQ3coF6x+rDmr/KqdBw0yEpOZ/HvNj16lZqLfB0l6lvsubj9JlOZ9YRK1juEvxQpZcisKGg95tlSdu1j5EqK/5XOlCSWsGoPGbGteT57Z9UmiG9tSMcdGOyW08847D++8846KdnzkkUfUMobmX3311XHrST4aE5y7Eprjp2/Jl60xZWbYYdUHw3hv2UzsseJ+/Fb1q7aGF67sMxD0noO1oR6KzDhil05U1CZETJiWGjt5FcThAL6pJMUZlpCEj+tuIM6V0SJjEq+IGusg+eikLOeFTz+D+/Iz0bvWqID8bb+tcdD5U1Das0j16tynWf4pes5WtdnMbrhsp7KgrGCeO5uv6oIZrj+qc8jv5avilTnM+6BlxYGHJJDr6+7Q24O5JQ0jVRSxrTAInv9Ya05vu1gkTII2DxxIQAISHq0rEhTn+nTSJmHyeksKQNxcZoaeVyslkXTfId2d6JT6MTa6FJpMaJwXe/PNNxWpURuRUjCHHXZYAzkYltdmwc2ulFjdnDya1piwTrctocD3QM1dCAQXQg/pyc4+ArtvdhXysgY06HxCDSqUG904l3Pwz2KShjp+GAUeqMrDBT1y4857mKYEsmStX7nZzKRGxQ+zWyt3/jzknn46HLWGRuRng4fj8HMfRUVerLIwdR/9CUgkkcXF33p5oULOqRGZSMdQrirj/6wiHs1zWVbbhyPlXnxBo+iluR3/3S8fmz1jWEJm8JiMHnxot9y4WnPcjkR11gcVmLPSCLRINH8k6RK8thwwKCssJBGTES1F5nhFliWz/hs7MDO/NyKKnO47pEdcVkeiHK1gB4V0XjRL+oo+dpJYMiSrl9ZZ0VRl++YmlGYKKzesxC2f3AL/hufjlu/Rf0/8XH85KgLD8GN1fOQiwXMVFQjOOdESYGi+5Eqxo2NEI11cDCBQ1prJwpJQe0FlXViJ5U7Zp7eqtzV7eZ1SA+Hfemfkfu015J57Lhx+g65q9x2DU479N9aFc+LC+hOF1vf0GqLGtDDNFhwJhp05yUxPRI4qbmjBFfzXu4nq+3R39s5yKAFgWpLm49AyGvJcaUILk2Bk4NYr6uF2xMrekKjpJuS5STg9rWK59iQieVYlMVo6+wmz1yoS5D7Epcv1Ge3Irbm+mRR4nZpCGlZ10JpSHYJuWREnNidWt5d3zEYHrVjdVdEUP31LlnhJpy0bfBtw/5f346GvHkJdMDa+HdJrCP6x9z9w+JaH49R5sQ4vUbFPORcW8mTnyXkZTt5Hk6XDhrVVHXBg1BuVGFVUE80dM3fkpA8ej9uyo6QDj+5LvTPyTJuGnMsug4Px8/z9iCPge/JJbP/RRtREOmEqVjgibaGLTVlCkagOukRJQDLXxDB1ARVE1kXmAElmO/XxRK0cpb5vdr05jURkHSwvs1sxrRefkmJifTGdCAUHDMxS5yjXgG5Culx1dXszkbHNfZg0rawnlteJXANT+KJufTJJWo9A1O+bzKfx+tLtyGoFZhKUQYk5UpB/06KS+Ua2tbGkYX5vGrOtTlZy7ma1/bYqo2SjdWATWguiKS9LS0xYpxotB0IBTP9+Om7/9HaU18QSb3tl9cLVe1yNs4efDa8rceVgHXpHROj9r14PS9xV7ABp1Q38nxFMwug/6cjdTqdqNztSgoRi7ly9DzyAnBtuiB3j1FNRe//9VA7GswdkxeaCQrHtmNgsorfSJuZqyb6ZxE0LUgW0aKXUSIrs4CVwhEnN9KyK9BZfpp4eR/S7gARHy5LVm3cpNKxUuYY89sKyeuxUYLyKErAiARySTE4NRSEzsbzUnF6O4VaUhHWxfl0Ra6+qPhwtdRPVlaQFkyBhXu/saQWT/KVkj5CgFSlwf3ruGPfW1EhCq3alu520a01Ey9EqsdoOCum8sAmtHSLTllkyF8ucP+bg+g+vx9J1RvoF4XF6cN6I83DVblehV3avJrWPHbV0hrori8tEyHbbnAB+qvWoTlcsCJKGPj8m0Y+cG5LOSiXsHtAHnhtvQs7990WPWT9pEupuvTWqSMtzZafM+TeCHRwjLUlwUqqE50J3JuelpNP/4PBCpUxvBi03iQYsyjJcqIEQlUuMTjw/Qi5Ws2RSvVncdvr839r6sIpUFAjxCpmxjVQuESkp3UoTNRPZ708n9cPa6hpUlq3C5GU98XVlUEVVflhq1CGDyd1otob0JHeSo9wrDgJ06FadPmBiKoAEnXBfjZ1Da+7zL+0acbMLJVXWidXNPYaN9gub0Do5ErlYvl/7Pa5fcD3mLZ8Xt/6RWx2JyXvdhG3zhzT5mLSKpJAjO0MShkg9yXzayD5u3LLFJkxeloP5q/1RDlA5W5ERvyJj6hvWG3ND7CyV6xIhfHzihTj0veeix6y77jrU//WvUTJTOW/l9aqidUyXxJCIMgcakDjoImN72Yx93yyPv4ZOY1sJadetISEZgT5nY3YpSpK5TiAMYDDTnyjZC1GQgCTIxixJxfOj51S3lHg+5SFgSUXACCzRUgR4CiJFpadKEDL/yTkyEoM8N+qcXylrYOFzkML20+LmteO6vD9NIQ2eq/n4gqa47m10TdiE1gWgu1jKNpXhtk9vUy7GUDjW+Y7qOwq37nsrHli6NY58j+S3rkkRYNIJE3ppEOkcOQc1fX8jV2rlyvWq06XFoReCZEepUgZ0SyTicoTPh6wLL8Ch7xnpICGHA9eceB2uvPwKeDUy0yMRZW6MpCX1sXQCIOg+lKhCPbqQydC6i7KiNqh0DEnakiBupB84UVkXilO1D0fC/Lmcs2I8T2odEnI/GDxjFTXJ/ZMs2BaeN9eTemRmNXz1PRALxNg534VbtoAaNCyOVBwg9AhEXiNxD3K5vk8he3MJGH0QIJY/28dLqrsXGxsQIvuS4+v5hXZEoo3GwCa0LoJAqBb3ffmQCvrY5N8UXT6o+yDctPdNOHabY41giwXxk/2NEXbV3Zv6HBAhCdJ0z7EqNQkkGMzGhqDRIXJULu4ucXXp4F526xZAr4mnwTN7tlrmd7pxzqm3Ye3Rx8dZPcx90yFzOtL5f3pUkWqXbgExspDJ1XIsOTy1F8U6YUdL92VBpGq2jgVHNHRT8pg7F7ij+yX4N68Dgzi4T85n6Zac5NfprlJCrCq1ToRYt3s+liem56YtWheGfzDw9L494PTEcvXkvpGk9PnIkZF2iIWkW5H6YERfLnqLZvdiU6IIxYsgx9fD/u2IRBuNgU1onRD6i08rbMbSGbj1k1tRsjGm4tHD2wN/3e2vOH/E+ch2G7mDXpd1zTMdyUbMZvemkJm4DyWXjGTFkT27ckmu1udbuC2DNKJBDIy0DG3A5BsvhOe3RWpZODsb6//zNO4++KAGbbCyeqJRheGwEhwWsC2S9Kzy0ZyGtSapAyRBdqjvLa+Lhvyz7QM00WASMo9rdjFyX4vK48kVmnIKox65RTgu382pIh1ZMVpIlRYeSV6/5jweZbTM59nHY1hmompiDrAwW9CsGyfBHonmsKyCKLgfkhlJzax0rxNdujBHyMqnHZFoozGwCa2DIh01/Qu2+R7XLbgO36z5Jvq7y+HC/+34f/j7Hn9HQW5Dfc1kEWAy55Ms2VXcVEJm0h4SiW6F0L1YWR82qk2bygqT3CSqj+v+vJ8TGw49Ezus/FH9Xp3dDRMnPYLPNuwEvGiQk24lSNXreSvroxWLZX7MSnWEkLb19EgCcfzMljl/TU/OZsoTFeiLcpxqDo1uR5l3Y5SkvjeJTGRwDOuX9fAaNcaU7qWa3wsZEmERImfOGbfRrRSJZOR+6BIVUuN6blMhN50kzBY0A0rmrQqp9ApJq5BtzPfVHDwi+9GV8CViVIiOMBNxMlg9c3ZEoo3GwCa0DohEVlK0o9n4K+ZU3oOZ374ft93BQw5W+WTb5seLR5uRqPOQkHuJXNTXs5rzIMHoYsQxK8QR0XIMYq2foeUNLRDZ8+CKEgw4+ny4Vy5T38u75ePg8x7H1wOHIkSJo4h7kO4qfR/iolPh5C+VRhOdJX9M/Wbh1qQaCNssSvRsh6zGZflZgMvpVNGY0RpsYYNwlNCvxl5j+mepMH927hLcwp85j7hkrTH/REvQLCIsEmHc32dHF+PCjyujFg/PR1IK+Cnze6s3BTB+5lrVDnE5nrmgGu9H6qZJ2L0+lynRmdxmhxcY+WktN0XCEwJlFKWV5ST3XaJY2V5d6UMf5DQWNpnZaDVC++ijjzBr1iwsW7YMGzdu1CSP4sFR+BtvvNHcw3V5JJtXqK5fh2zf7cDGZ+GLaAgSOxbuqAI+xgwa0+zjsrPi6F4P72ZnRstN1EGkbYSem0QwJ4qdHLUct+8Wwo81TiWFZU7S5Zza+q9/wGsPnQt3hWGFlRf0w3U3TEOJdyAKtbbRJcd2yT7MQscUBtatGKYF8DhDZsRcj0S+F9GIzKiEV+STfTHV+MX64zyd6CyKCj7Pn+eqrhejDNf61DLZRq4DSW54H3c0VF8PJCHoLiTp850R9ygJSQiGxMJz5WacayN0NyKDQjgfumhdIDoXyfOXQpnyzJColO6hcqNay02ZCVSISXcRSlSrHsUqc47cN0nOKkrSho12Q2h+vx/nnntulKQSEZnA7Fay0TRYjY7rAnV4eNFjuP/Le1DtM0R5FRxF6NH9Mrw34TzkeJo3dkk0nxEVMQ4ZOV7sePVKxOxApY6ZWEeco5Kw/eL+Rbjgs5oG0ksnrv8R9z50NpwVhrL/T4Wb45TL/4NZp47EbZoLjTCqX4dV50nLwyx0TBeiUvUIA+MHZUfbbnYsbggYBEESptqF+YmmNcT9GZJe4ci5OLFrkWGNEgx4ERLhOiQ+biOkJu44fmdwiFmvkSBxSlVr2Zfsh23nOc5eabTPiFA0FEIkEOes99fguK+y4TAZRAxw0QdAhni0P+qWTSQ3VWiqGi6QaFREUhok0pHXgnmD4t4ludqBHTZaA03u5e699168/vrriqgOOugg7LbbbigsLLQLebYCZHTMkfzLP72Mi+bcgFr/qujveZ489O99LtbjdIwq7tVsMjMfN1mHpEfjCV4YXxjXmbOzdod8WLFivdqXWXppu28/w21PToKz3hAZ/nWLYTjuL49j8JaGu0sgfzMqjtqC7OFZI02sA3HRqY40khPHgAuSjrj1dEguFdsoQRXiVuQnE7JpcQm4bH2EcaQttCz1gBZacaJ3qJMarVpGStLVRzIStyM/SMAkDraDJMRlPK6E29NVKJYhz2eDP+YGppr+nBLWjWNRUqhCnmIJ6ndNtxhFNNp8j3X3MS1XnczMofYc0C46rm80GVyPopQK1nZgh42WRpN7uhdffFE9pE888QSOO+64zLbKRkosLvsCkxdMxperv9SWOjGw9/GYc/zN6JvXt0VGw+b98bsubpsod0g6c1pxrJu1Xz+PypUy7/fCPxbgb49fjOyA4UIL7LUXCp97Du9365HwXNip0wpgJy+EpKomr/GpY4lMVJUvbFgpCYR92V9LhJ5BgM6oNiJBa4quO30qiGHzet4UO/5Bz5RGfxcrim45/m52yYp1RFesKP6L25TXiudF8G8hQ90dKrqRrEKtu0sZPzoi340XDiyKukj1cHidcAhRGzHnmUlbre67OdReJ7w4VRfNzWnDRrskNFar7tevn01mrYzfq37HTR/fhNd/eT3+B/deQPaV8Gdtj/zsYrUoEx1Iso5IftNH9Ynm+KQTjSbvrvWrwAUdjmefw/V3XQRH0Jj/+2KX/bDty88COTmwCgAXq46dtVgs1IAU0tDzySQPjdYIH3oewWyhcd6KFqa4PcVCsiJAqnNINCM7cwE79cLsWJK2gERD6HJgbD8jDSEBKA6gONuwzPRrRUigBc9P3Lf6EagfqefLUVZs2hgjitVMKLr7mMeiRWiVZ5YsZF4Sr82h9vpgRo+ctMnMRrsmtJ49e6K42Og42ys4zzdz5kxVs23RokVYtWqVGrlvu+22OOWUU3DmmWeqem0dAVV1Vbjri7swZckU+EOxoPHt8rfDLfvcgid/HYEl6wKNduskI6xkOWcSCKJrIgoSJeLqI/pdNLce8dxf78EF/7k5+v2ZkYfh6rPuwGJvtiWZ6flUEnkpkXz6b3rxSiky6ogo1K+rjycFakqKe1B3u81ZURcN3JB8tf0GZkXdq9xGj7D8+eT+quwKgz8438VPPdKTZEjFEFqPbJOS+9KSy+W4syKCyYSQIPcvlhrPjdvLOpzn4n7p/nOabmmq3LJ0UjBSPRd6cIhc//YI21rsvGgyoY0ePRpz586Fz+dTxT7bI37//XecccYZ6NatG/bdd18ccsghqK6uVlGZf/3rX/Hee+9hxowZ7TpgxRf04T/f/Af/+vxfqKwzItqIwtxCXLvHtTh9h9PhdroxfovUL6pVcmwiwkoWTakHgqgCkBZzLvroXKCP6EP+ejWHxkgN9z/vxAX/uSO63psHnYorj7oWI7SK1InaJlYYAxL0+Tt26px3ElFdkW/SXXW0pDjHJfleVuVO2GaqcsjcEOfRRI5KYHWdXhgfs4qE/CUqkuQoVhbB44/pH38P6D6UY5lVV3SLi21jDhzJjGVhWHqG7sPvgkZ7nWlURjD/nez5MJOW+Rz5LjVVZb81YEtpdW40mdCuvPJKRQz//Oc/cYNWvqM9gUR299134+STT0ZeXl50+a233orDDz8c7777rgpsOfroo9HewA75rd/ewo0f3YhlVUYOFpHtysZFu1yEC3e+BPk5PeK2SdaB6DJP0iEmS5JOV6WBpMaINpKJeXRuNbqX/dSRD0IhdLvhBuQ98UT09+eOn4RDn7gVIyJKFGx3MkUSuVa6NqNoDHK+iwUxxw3MjrrixBXIVnw/wQjfJxjdaHWueg4WSVpSEyRx2Oy+S5YcbJSKqVNpCmadShKReWBgkIOjgeoK1zEPIGiZSR01rlodNGrNSTCG1YAl1eBHfz54L+UaETpp6QOcLGcYv1lUE28PsKW0Oj+aTGg9evRQZHbVVVdhyZIlOPvss7HVVlshNzc34TaDBg1Ca6J///4455xzGiwnubGSNn/7+OOP2x2hLS5brAI+Pln1SdzyCdtNwA2jb8DfvsjBnq9vwi6F/kaJvyoJp0g+EudNEiVJyza6RaWD69K9J1FyYq3oBKirWTAZtwECAWx+883Ie/vt6KIbj78aX558HsZF5ovYXj3gwqptMt+lt43EohfEFBV4Ei+DK0Ja+L4+X6YrxRPsxKUYJ9tC9RK2orvbCNJgtKQow+vRi/xutgT0uUY5JomYbk46CMyEbKWHaY46lPXEMpLkbkO6KyaxZe6807FS9CR6Ze2+vDqqqm9ulw69Cnl7gy2l1fnRZELbaaedon/Pnz9f/UsGvnDr1q1De4HHY4yw29Mc2orqFbjlk1vwwo8vxC3fa8BeuG3f27Bz8c6RDi+1gLAO6eSFgBhEwfthlSRt7vAIvfOT4+kh6NI5yO/8x/pi5mTcKOrq0POcc5A9a5b6GnY6ccWpN+O+kcegWEvIJmmwE5V5LXPb2G4rK5NuRjm+7IuQQAspaaO7z3htmM+mWzQMgZdcNaeubK9ND4n1okcvJnLLyb2QuSlVeDRs1FZje1LpYcq50hqSIBOxlPT7FAoGjaRml6tBuHw6Vooeks/Di6tUV9XX76dEujJ1gnvS71d7gy2l1bnRZEJLlUjd3PVbGtOnT1ef+++/f1rrs9xJS2GDbwMeXPwgpnwzBXXB2HGG9ByC6/e4HgdvfrDqmKQNVIKgvBE/ORel3Hcp8PTe3TDxgyCWVARVUjPBfezUO34fesepanWFw2pOhn9PeLdclXvh9lRy5z6lc9CvjzuSeyTK9Mw5k58dGzei55lnIuujj4zjuT04/6y7MXPn8SiKnNvEuWtUFGQ4QiI8dvWmWrW+3rbT5qyJKtKznTyPk+ZWK4WMqMKHA5iyZ576jee6JPIc0hUZ1W6MuP1iosH1OH5WGeaVMp8LKMgyEsFZt02PeGSYPdvL86NaCUFJLH5PdY9GvloREWiOfH95NUbku/Dk3j0wdXQefMHcuOtKGSumHfB8xGLkHOCnh/XSSC/iHQn6sbJ0PQb2KwZcngb3h22aVxpSbeW15r00Q9rPYwqhj+nrVu0z7494bI9c7PJ6XfRZkfvVVsQRrR8XDlu+u+m8M1ZgzID+aSMzyM42BNKbC0dVVVX7YppWwNNPP43LLrtMBYqkK8dFaa9gJJw8UwiEAnh9xeuY8vMUVPgMRQyip6cnztn6HBw3+DhVPdoKjG7TowTThb7dFd97sXSjU0lQ3TMs9oJe+YMX329wYlh3o5Pm31yH6671O1HgCeGNXetSHr8mAOS6Y8d0VVVhm0svRd4PP6jfgzk5OPGs+/DyVnurfb68i7HPIxdmq+N4HGF0d4exY/cQ7h7qU/u55kdvtD3fb3Siwm80oo87hOdH1uGkxdq2zjB27Glsy3P6pNKl3I3sYgMRKunjCWHbvBB+3uTE+oBD5YP19hiBItwP6YPEtVvPIO4a6sPhC7NR6XeodV7dpU6d3+Xfe/FRJS19o37A/D1q1XI5f/3ay+fYz3Ig9QZ6u8OoCMSOtVfvoGqzvp1+TdhXi1hyH08Ys3ava3Df9O3N4H3/MNLeZPfSfL31Z8QKcnyuyyhLq7Y09bltLA477DCUl5ejqKgIb2tubRvtD/SSDRnS9ILCHU6cePLkyY0aEV1wwQXYcsstLX9jIAvn/TifN2XKlEbNx2UKHDXOXT4XN392M36u/Dm63Ov04qwdz8JlIy9Dr6xeaEnQsvrpy0qs9YfxcaVTVY6eNsYYqT8/qKG6uppvWmBYPyP7ZGHI4MK0XDeyzXjHWjx9zyS4fzbOtzK3Byb/9WFsGLYriipDap/bbmEoNI78g4U/OXhwqGuVk5OF63/PiRzbjc/264aLPtuIjev90QhFl9uFU77Jg9MFFLlYQsWDh/boFo1OXPplJfyRUTutHEfYsHQ2BJ34tc6FEQVufFNpVHh2u5zKWlq8LoAqn0NFJX5c5cZRX3nww/H5yl3I4x+/2Imd+7jxc20sq43W3LZbDNKulWHN8vu8iFDw/v08KMwORCxY41izS2hVGsf6YZNbSYLp13bUn8b+qnzx2o/r/A7kFfZHN49TnSPv59Iaajn6lIVmjkCW+872Si003stEeH5w+mHufG4mflCtrHhadrRm2RY5F/M1sUKm3IEylcDPTM7dsx8qKytTKUvtNbq7K8PdUSyqTZtiRSlT4cgjj7QkNIbpM4yfo7Y333wTffvGBwG0hkn87Zpvcf2H12P+8vg5x2O2PgY37n0jNu+5OVoDPJuRhZtigrmVwbhikPrZyt8zDsy2DNFPNF+ikqkrgui+4g/c/vi5cK8z5LnKehRg3PlPYHXxVli0T091bfWAha8rQ6rgJqP2lB7iuoByufJvqsfv+ValihRU5WUcQA83GgQsMCJv9Mz10faNKqqJ5sAxoIXziNxfIFKb7cMyqsMb80SSW8f2nzJ3TVQ6al19GAGnFz3yHHi/tFId74PVgah+JXPOJFyf563C+yuCahueg7gruYyyV1xP3IWiDIKI4n+PvJzoNVRzlpFrz/kpPVpTnc+sanWebLdS0u/tUlYQO1zzc8tvvBZ6xGsqUkn3yed2fI6kijXnKtkmnov5mujPWkuE1EsqDj8z9e7qsLq2NtoeHYLQmBDdXDBEf+LEiejTp48is803bx3iEJRuLMVtn96GZ75/5v/bOxc4mer+j39n77ujZcUq99wvpcvj8kSE6kGlECJEPZQsulgR6SKVB09KLulRLilyi4RKPJUulEgk6kkSm9t/W/ZibzP7f31+6zfOHufMnJk5szNz5vt+vbbpzMw553d+c/w+5/v9fb/fn2JJR6JWl7USlfDbVG9D5Y1WYIcn9KqByM/U370r9xA9PXswpZ49Ld5z1qlDEx5fRCejqlHzpCJXCDpQHhdiJgNDEAmYklCa34RkYszTlA6YUWJNMaw5pqzyjuOp26euaiGvW4LjygANGSQD8dib6RCBERA+WZxXHfkpl3DRq7KBfWAJScGSbVT2l3pFaqAXKSnFD+5TuPbkdcpIToh1en6csJi8DYzwR1TU161ctNVI5REOqWfKRdAQ4g5g0UyaNKnMe0bBk9Ls2bMpGEgxS0lJEWJmlr/WCLlFufTqd6/SrJ2zKK+4tNguqJ1cm55p9wz1bNQzqIndvtTZUw9OMgxdPQhG79hBsyffQ7azZ8S2o1kzyl29ml66/HKacDaP/jpxzOOAWOOtDOFig+Agv0mZL4bP1WH7WseRIqwUCmXVeykQ0jrTCp//+s5UqpwYXSaqT55XuTSKPI8URWnN4nxInl7aucpFfa1e7gYYKSFWNZ7E0jjK1aHlSgDO84nVsCG0fl9PCeu+ioo7sXT3GYfUM+UmaO+88454bdSokUvQ8B4GYqPRi8EStM2bNwsxq1SpkhAzvbk1s3E4HbTsp2X0/FfP05+5F4rVJsclU3rrdHrgmgcoISY0XBa+DB7KEH1ZhUM5CMZs2UJJgwaRLa9UxItbtqS8lSupJCXFVVWicWIcrVRZEUohwECvnC9SpgYoK3lgTkvdBr2q8cpFRzH4y5B7Gc6vPL+yar8UM+X1q8+rtvrU50N1EFhQSjefsuq9sv/cibIsIQa3K/IJlVVZLtRyLC2G7I3FZZaouNvP3WccUs+Ui6CNGzdOvMJdp34vlPn5559p4MCBVFBQQDfccAOtWrXqou/Url2bBgwYYOp5PzvymUiM3nd6n+s9lKe676r7aPzfx9OliaGZo+MtSutIWTkiZu1aSho2jGxF5xew7NiR8pAmUaFCmUoep/Kj6d7PztCKLgmaicNSHDDLhHkqpftKiZyHksFzyu+prQ4gBQFWH3LN3A3i7qxnnFdZJURdFFmeT1lQWFTyV1lbsuq9utKIO1FG4rpWzUTs0/ejE7TrlEMEaGBOy5PFpfWAEKxKHyxmTMAFbfz48YbeCzUQjQQxA6tXr9atSWmWoB3MPEhPbXuKPvrtozLvd6vXjSbfMJkaVm5IVkGvokXskiWU+MgjZDtfRb6oe3fKW7CAKD5eI8nbJqIZ5ZyUPB7EBnlZsi6gXvCCsi1ApoipB2S1YCnrJKId/6gVX8bKUbfHnRhoiY7yvBB9zAdqrQmmLpuldY3uRFmr3Ba+iz5FiL/IGTxfqkvP4lJbcN5YdGxNMaFGWASF+Er79u0pKysr4Oc5lXeKpm6fSov2LiJHyYVctatTr6Yp7adQ+1rtyYqoAx/iZs2iREVdz8IBA+jcK68QxZS9zRAAMfCTkyJ4AeH6SncZjgfLqbQor02zxJJW3UlpISnntICyrJUUHbjkEGgCZOUUiXJA9xTEoLYY1cvoAGlJqctFye8ZcbNpuQK1ym0p24L8NvzX3RypWijdVThRw0V+mVDE0oIWaPKL82ne7nn00rcviWofkuoVqtOktpPo7qZ3U5QtuEVaA/EUfVFV/Sii+GefpYSZM13fKUhLo/wpUy6sYKnaF5UokNCrzIFS1zpUl1hSn1tZDkuuFQZrSF3fEFaYLKAsi+iSxrIxyvkuGTUI0H9Kq8/dYK4OQAHyCvT2V+5jxBKUYqkst6X+TNYgcff7a0VjGplD44hEJlRhQfMBZ4mTVh9cTc9++SwdzT7qet8ea6dHWj5CadelUVKsfpHm8iIQT9EXub8cDkpIH0vxCxe6vvP0baNp5LPPUJxKzJQWAMoqkWqBT6Bntei5AZXvyVB/6WLDStbKAso4vzKGSb1sDNAa0NUV990N5uq5LuD0cA3qSE2930s9l6a37hwStdXWrx5qoXRnMboLWGGYUIAFzUu+Pva1CPjYdWKX6z1YYYOaD6IJ10+gavbQWPQ0UE/RysGsTSWiisMfoLg1a8RnTpuNRvaaSG926E8jdSwzIObFKpcm/7o7j3pf9SCubo86dB77xaAqyPlDYd2wlITSXDaAqvSoaIFwfSRFa4kpRBBiJgsti6hOncHcUwCKLNqrvga5jzKYxIigKy1IZV9hDg3lp/SqcWj1taeHH/XnHJHIhCIsaAY5fOawqPCx/n/ry7x/U52bxIrRzao0o1AikE/RYjDLzqVK9w+h2M2bxXslMTE0Y+R0WtOkK93kZqCXc0ko4CsW+FTgrvK7ehBXrxKtntOS+8lkaaSXYF4OofnIZwNYMVpW7/jkaIGwxLDUjbINcMPBMpMWGra1IgGVIfXKPoeVhir+yhUB1O1Vzh3Keo9K96NyLTsjycnqPDR/H370PmcxY0INFjSDdF3RlY7nHndtN7u0mRCym+reRKFKoJ6iizKzKOWefhSzfbvYLklIoLzFi+nBLl3oPp0kXvVcjboAup6FAOHCQK9ct005wGKuTG8hUXlOgGOgVSiRheRs9ZI5ukvdIHq13+Vu59C03IxKcZUlqdSuQb2cNiADPpTpAFoRmVrXjD5pmlSah2YEZVCNllCyi5EJF1jQDFLkLI2gS01KpYnXT6QBzQeI3LJQx+zBZ8Tqg/TE04OpytEDYrskOZlyly0jR7t2bs/naW5GryoGtvWSnuHKw1pdsLTkQpvqc0qhkIEgeJUiJ6t9yEU84QLVy79SRifqRQaiPUqrUe/ataw7vZw2GeyizGNzB86FpVtOZFyY2/WEsnKK3lwruxiZcCD01kkPURKjE0WFj++GfEeDrxocFmJmNsWHf6fnxvehK8+LmbNKFcp5/32XmHnCU7SdMjlb/b4sSSWBuGEOrEQhUuoaiwBCgYFa3ujKBGYR1dirGqUmln5aKf7iOo2e2iqFCIIL1AEr6muHWxOLj+JViglEUIbew/pCqL3yHCtuqSry2NSJ4972sxZKgZZJ32Ycl2GCgc+jclFRkWvV50hgc7/NdHmF0rmXSCTq4EFK6dmTLj2VIbZPVrmcEje9T86G5iSL61Wo0LMMpCtPVtB35wpTFmGWCcxG88302qqurqFON9A6jjrAJPOcQ3fuSh19iBSEUjvS3FQMdicyVsJnQWvSpAn169dP1Els3LgxWZ1wFzN/BsHo3bsp6a67KCqzdBHS4voNKGHte+T0Y50ptSXgKbdLC3UFfb3z4DNlgrFeoIk3/aMlsJ7cquoAE9SHdCcmaks1UKLD7kSGIl3QMjMzad68eeKvTZs2NGjQIOrZsyclJpau48SEDv7ko0Vv20b2/v3JlpMjth0tWlDe6tVUUvVCQrS3g6Gs1tE0qXSJE39SDNx9TyuBOdACoXUsZTvUASZGxSTQosNixkT0HNq6deuEgGGhu+3bt9PIkSOFpZaenk579uwxt5WMz2iJhVFiNm4ke+/eLjErbtuWctavLyNmyjkgb9qD0PIfs0vnrLTm0Lxppy/XLeerAl22SasdWhGZRmDRYZgACVqHDh3ojTfeoAMHDtALL7wgXJDZ2dnivU6dOlHHjh1p4cKF4j0meOgFXHgidvny0uVfzhd3LurSRaxlRhUr+iWWsj0Iomh+yYXQcqXAeCuSavREUqst8vuBQt0OhmEChy0rK8u0f807d+6kxYsX09q1ayknJ0dMZCclJVGPHj3EXFvr1q3NOhXjJUaXBBEWxILXKVGxPFBhnz50bu5cIo0gIC13prsQdYkMLa9Vq1aZpeyxr7Kgr17OlR7q9nhy05VXkV110Eggz5Wfn09//PHHRX0bSTRr1owyMjKoevXqtH//ftOOy30b2pgae96yZUvxN3XqVLFcy1tvvSVEDouB4g9WHITtnnvuoeRkY2V5GP/xJDqu731ymm5c/DI9vv7CQqwFQ4dS/rRpRFHaYqgWDeW58CoDIDB3pERPZLQSqZW4Eyijc3HK4BDM5SmreKgrZJjp5gtkQV8O6mCYAOWh2e12qlOnjlg8MyYmRpQdwt9PP/1EEyZMoKuuuormzJlDVieQrixv2qAeSLVceoVFDrpz7rNlxCw/PZ3yp0+/SMz0cqzUFTyUIeqw1LT21Wor8sqQY6au5uHJFWnEzag8BsQTlUO0xNNXt6fe9fnq+jWCXltD4f5jmLC10I4fP05vv/02LV26lH7//XchYgga6dWrl7DMTp06RW+++SZ9/fXXNGnSJLFPWloaWRF/XFmBzDPStBRKHFRx9Ch6YOsy137npkyhnIfSRE2ouGhj16U+l9JCg9tRue+b7exelWAyan0ZrUgil5eBeEJklOLpa9Slp988EJGKevOY6fvj6Kedf1HL1Dxer4yJGPwWNKfTSZs2baIlS5bQ1q1byeFwCCG74ooraMiQIWI16EsvvfAPqnfv3vTBBx8IgUMAiZUETS/PyZtBLBBzOnrFcIVoFBVQ0v33U+zGjeKzkqgosShnn+q30palpUnUsqyUkevSK/N08b5JXpVgMhpq766v1cfA8jJa4ulLWL/R39xst6BWW8+ejyA9XaTtSmUYq+KzoB06dEjMkS1btoxOnjwpRAyVQ+644w6677776MYbb9Td9/bbbxduRzMna4ONWoh8yXMK1JIvWsVwxbHzcsjety/FfP65eL8kLo7yFiygvNu6084Vf7rqHyrbYuS6lO/LgBBP+2qVYFJ/R13415eHAWVVD6V4qs/nrTUVzIobWqsNIIL0p7zSxG0WMyZS8FnQEPwBIGSYLxs8eDANHDiQqipylNxRoUIFYc1ZAS0h8sW9VJ6DYvyZvyipd2+K2VW6rluJ3U55S5dScadOBMck3HFY9xhypGyLP24z5b6IFlOjde3qJVT0xMrbhwGleMqyWOpje3uNZroUfbl3lMxoVkjVqqdSsp0LHTCRg8+CFhUVRd26dRPWWOfOnb3eHzlqWoNaOKInRP4O+oHClpFB9l69KPrA+SLDlSpR3sqV5GjV6qJgAhTFVQdn+NM2T5U0lGH6ynXAZPV5PbHy5mFA+V0jx/b3+rzFLLczW2ZMpOGzoP34449UrZrvqzOnpqaSlTBTiAI5EEUdOkT2Hj0o6sgRse2sVo1y16whZ/PmQbEU1ZaV1vvKdcHctceb30C9snUgrtWX+yGQbmeGsTo+C5o/YmZVAj3w+Du4Re3bJyyzqJMnxbazTh3KWbeOSurWDVrBWnfWrfJ9o+3xxU0XiGv11coK5lwcw4Q7kbeoV5jirxsqescOEQBiO3NGbB+u3Ygqf7iOSi7XX0WgvAZTPUHRCnbwBW+EUBmp6s/5/LGyuPo9w/gGC1oY4G6ANDLwxWzZUlqXMS9PbG+v04KGjJ5P21IvEwEgoYCRiMlAPwjI70p8fXgww8piMWMY72FBCwP0Bkgjg3XM2rWUNGwY2YqKxPbuFu3onvtfoaa1UkJ20DQzUtCopaT8LiI7kbHgzxwWW1kMU/6woIUJ6gHSyGAdu2QJJT7yCNmcpQllRd27U70FC2hHTOjOzZiZWO5r5KPE3zmsUO1jhrEqlhe0FStWiLXbEJV5+vRpkTeHStlY4mbUqFGiGne44E01i7hZsyjxqadc24UDBogKIBQTEzJuxkBG+Ml9PSVj6z00sHXFMOGH5QUNVf9R1aRVq1YiMhOCtnfvXnrttdfECgAffvghNW3alMIRTbdWSQnFT55MCTNnut4qSEuj/ClTkC1NoYxZEX7+zIX5G4DCMEzwsLygYX02rXWLUHty9OjRYqkbfCdcKTPwOhyUkJ5O8QsXut7Kf/JJKhgzxq2YhZI14u/ck9lzYd6eO1T6kWEikYAsHxNK6C3Ch0VHAaw3S1BYSInDhrnErMRmo3MzZlBBerpbMfN3dehA4O+8lVymBVX+A7FcS7j0I8NEGpa30PT4+OOPxatRd2NIl+nKy6NKQ4dS3NatYrMkJobOzppF+b16oeG6uykXuMQrVpEuLwujsLCwzKuZlhGWpkE1f7wnq/0H8vcLZj8Gum/DFUwtyFczf3vu28Bg1urfESNo7733Hh04cIDOnTsnXrds2SKKKmPBUSNgOfdQLKYcnZ1NDR59lOL37BHbzvh4+nXqVDqDuox//OFx/6ZJceR0RFHTJCedyDhK5c2JEyf82h/rfmGpFFSXR0Feo5+Zjb/9WOQkio0Krb4NZ+S/Vbz+YeDfgbdEct+aTXR0NNWrV8+UY0WUoL3//vuu7WuvvVYsNlpXo+yTFqEYDRl16hRVGjKEYn/8UWw7L7mEspYsoeTrr6dkg8d4t1Zw5n7whItBAYE6WATWp2M4SsQillj3C0uloLq8Mq1B77NA4E8/Dvn8LO36v2K67tIYWtTB6C8X2L61wiApXxHVbBbct6FNWAjaxIkTvTLxhw8fTvXr178oCARkZWXRDz/8QFOmTBFrtmFNN3drt5ltEpuF7cgRUWQ4+vwcoLNKFcpdtYqir7mGFAtMGyKYV4ZBwde+xV5YkVlGRSqXSnH3WaDw5SoggrszHcJdideo2Hjz1sDzo2/DndLlj0pfA9EHkdy3oUxYCNqiRYsoNzfX8PexyKha0CSVKlWiDh060KpVq0Qo/0MPPUR79uwRi5OGC1EHD5K9Z0+KyihdUdpZsyblvvceORs2pEjDXVRkOFTr4GLEDBNhgnbs2DHTj5mcnCwWKd2wYYOIdGzcuDGFA9G7d1PSXXdRVGam2HY0aCDErMREt0q44akCSKgTDsLLMOGA5cP23XH8+HHxGi7WWfS2bWTv3v2CmLVoQbmbNkW0mFkFFjOG8R9LC1p2djb98ssvmp9h7uy7774TrkmzImwCSczGjWTv3ZtsOTliu7htW8pZv55KqlYNdtMYhmFCgrBwOfpKZmYmtW7dWkQ0NmzYUEQqIihk165dYt4Mbsd58+ZRqBO7fDklpqWR7XwoclGXLpS3aBFRYuADHRhjsMuQYYKPpQWtSpUqNHbsWPriiy/o008/FQKH6KTatWvTiBEjKC0tjWrUqEGhTNz8+ZQ4bpxru7BPHzo3dy78pAE/dyQN0v5cq5krBDAM4zuWFjS73W44cTrkQJHhadMo4cUXXW8VDB1K+dOmEUUF3lMcSYO0P9dq5goBDMP4h6Xn0MIWp5MSnniijJjlp6dT/vTppokZBl5vBmmr4u+1KmtHctg9wwQXS1toYUlxMSWOGkVxy5a53jo3ZQoVjhxZbhZJJOVGmXGtoRB2H+zzM0wowIIWSuTnU9L991Psxo1isyQqSizKWTRokGmnMOoiC4VBurww41qD2U+R5B5mGHewyzFUyM4me9++F8QsLk5EMpopZt66yCJBzML9WiPJPcwwnmALLQSwZWZSUu/eFLNrl9gusdspb+lSKu7UKSDnC2frK1zbXZ4u0/yiYLeKYYIDC1qQsWVkkL1XL4o+cEBsOytVoryVK8mB5V8CSDiKArvWrPeAwjBmwi7HIBJ16BBV6NrVJWaOatUod8OGgItZOBLJrjUj18pixjAsaEEjat8+snftSlFHjojt46m16PqRb1G/45cFu2khSaSGx8MqvWrlcfHKMIx72OUYBKJ37BABILYzZ8R2cdOm1GXwa/RDfBWqxsm5ukSaa42TthnGO9hCK2ditmwRa5m5xKxlS8rbuJFqNqwZcdaHL0RS30SqVcowvsIWWjkSs3YtJQ0bRrai0jC0oo4dRTQjVahA79zEEXzMxUSaVcow/sAWWjkRu2SJSJp2iVn37pT37rtCzCQ8aDFa8H3BMMZgQSsH4mbNoqTRo8nmdIrtwgEDKG/hQqL4+GA3jWEYxjKwyzHQFfMnT6aEmTNdbxWkpVH+lClENn7qZhiGMRMWtEDhcFBCejrFwxI7T/6TT1LBmDEsZgzDMAGABS0QFBZS4vDhFLdmjdgssdnE0i+FQ4cGu2UMwzCWhQXNbPLyKGnwYIrdvFlslsTE0Ll586ioT59gt4xhGMbSsKCZSVYW2fv1o5jt28VmSUIC5S1eTMVdugS7ZQzDMJaHBc0kbCdPlhYZ3rdPbJckJ1PusmXkaNeOQh3Oc2IYxgqwoJmA7cgRsvfoQdGHDoltZ5UqlLtqFTmvuYZCHa5gzzCMVeA8ND+JOniwtGK+FLOaNSl306awELNIrmDPMIz1YEHzg+jdu8nerRtFZWSIbUeDBpQDMWvYkMIBrhXIMIyVYJejj0Rv20b2/v3JlpMjth0tWlDu6tVUUrUqhRNcK5BhGKvAFpoPxGzcSPbevV1iVty2LeWsXx92YiZhMWMYxgqwoHlJ7PLllDRoENkKCsR2UZcuwjKjihWD3TSGYZiIJuIE7fDhw1SjRg2qVKkSPfroo17tGzd/PiUNH042h0NsF/bpU7r8S2JigFrLMAzDGCWiBM3pdNJDDz3kc8X8xHHjXNsFQ4fSufnziWJjTWwhwzAM4ysRJWhz5syhb7/9liZOnOj1vvGvvOL6//z0dFGbkaIiqvsYhmFCmoiJcvz555/p+eefF27Gq666yuv9nZUri9f8J56gIi4ybArR0dHBboJlifS+TUlJoYKCAvFqNpHet6GMLSsry/LZtA6Hg/7xj3/QuXPn6NNPP6UdO3ZQ9+7d6b777qOZirXKGIZhmPAlIiy0l156ifbs2UOffPIJxcXFBbs5DMMwTACw/CTQ3r17adq0aTR69Gi6JgzKUTEMwzAWttAQxFFYWGj4+8OHD6f69euLfRDVWK9ePRqniFBkGIZhrEdYCNqiRYsoNzfX8PfvuOMOIWhwNe7fv58+/vhjio+PD2gbGYZhmOBi6aCQe+65hzZu3Ojxe7feeiu988475dImhmEYJoItNF/p1KkTXXrpxWt8nThxQlhtjRo1ojZt2lCLFi2C0j6GYRjGPCxtoemxbds2DttnGIaxGJaPcgzVupDMBYqKimjdunUimKd169aiT2vWrEk33XQTvfHGGyKPkPHMrl27qE+fPlS7dm2qXr063XzzzfTee+8Fu1lhTUZGBs2dO5d69uxJV155JVWtWlV4dgYNGkQ7d+4MdvMsycsvvyzGVPyhspM3WNrlGKp1IZmy/PbbbzR48GCqUKECdejQgbp160Znz56lDz/8kMaMGSPcw8uXLyebjZe50ePzzz+nu+66ixISEqhXr16iL99//33hhTh69CiNGjUq2E0MS15//XUxwF5xxRViCqNKlSr066+/0oYNG8TfggULRH8z5oAgvhdffJHsdrtXgYAR7XI0g1dffZWeffZZmjx5Mk2YMIHdl34+BSN4p3///uJGluCGvv3222n37t0i0rVHjx5BbWeoUlxcTK1atRL9uHnzZtec8JkzZ4SVe+TIEWFNwHJjvAMPBZUrV6YbbrihzPtfffUV3XnnneJ+PXjwIEdRm+SpgVchNjZWpFqtWLFC3M+4t43CLscg1IVkygL32NChQ8uIGcB2Wlqa+P8vv/wySK0LD+sMVm7v3r3LBDhVrFiRHnvsMZGPuWzZsqC2MVxBCpBazEDbtm2pffv2lJWVJawKxn9mzJhBBw4coNmzZ/tcL5MFzUswnyOTtceOHRvs5lgePK0BLgirzxdffCFeO3fufNFnsNAAPxCYD9+b5vH999/Tv//9b1EAo0mTJj4fh+fQvITrQpYvS7GAqs5gzZSCOR2AYgJqqlWrJubTDh06FISWWZc//vhDFDq/7LLLqHnz5sFuTlhTUFAgjAR4ux5++GG/jsWC5gVcF7J8wbwZfOgIFMFqCYw2CKABycnJmp9fcsklru8w5sz1PPjgg2IgfuaZZ9hC85MXXnhBPJThAcHfvow4QeO6kKHXt1ogwhEu3Vq1aolIM4YJlejmESNGiKAQROb269cv2E0Ka7755hsRYDd+/Hhq1qyZ38eLOEHjupCh17dq0McYLFJTU2n9+vXCrcPoIy0zPSssOztb5PQw/osZgpRWrlxJffv25ahmE6JzYSTAZWtWHm/ECdqxY8d82u+HH34QNzTCSrVYuHCh+IvkupC+9q2Sjz76iO69915RsgxiVrduXVPaZmXkQwHcNmpXOMq85eTk0HXXXRek1lnLMkM+JKJJ582bR1FRHFPnD7gv5fwvEta1uOWWW1xz6Ujh8UTECZqvcF3IwCPFLCUlRYgZ3LuMZ9q1ayc8CFu3bhXJ1Uq2bNni+g7jv5ghiXr+/Pk8b2YC8HSh4ooWcOlC7FBkAcnsRnMoObHaT7gupDkg+GPgwIHCNfbBBx9Qw4YNg92ksHLdtGzZkv7880/dxGqUEKpTp06wmxq2bkbk8SGxH5VBYmLYDgg0cEWiz71NrOZfhgmJRHWIGaLGkMS6atWqi76DJ7QBAwYEpX2hDgbYWbNmCevstttuK1P6CuHlzz33HIuZj/zrX/8SAyv6s0GDBjR9+vSLvoM+Z89MaMCCxgQduG0hZmD16tWa34HLjAVNH6Q2IDIUdfBQkBih5YgaQ3k2rjXoO7Bu5XwPKllogYctFrTQgF2ODMMwjCXgMB2GYRjGErCgMQzDMJaABY1hGIaxBCxoDMMwjCVgQWMYhmEsAQsawzAMYwlY0BiGYRhLwILGMAzDWAIWNIZhGMYSsKAxQQWlmlCQGMVIGfPBsvboXxTRDiXC7XcP1X5kysK1HBnGAxjEvvjiCzGoGVmTiYkcsE7ihg0buHh2iMAWGhNUsMYclooJ5VWpIWaouo6Bi4lMrrjiCnGfJiUllXl/79694t6I1EV9Qw220Jig8sADD4g/hgllsBQPE/qwhcYwDMNYAhY0xhBPPfWUmBTHPFJWVpbmmmZwyeA7r7zyiinBAXgff7///jv9+OOPYlVwnCM1NVWs0AxXT2FhodfXgrXXZs+eLVZzxtwHlnjH4o1t27al9PR0+v7778u0AecBWOhRtkn+SdAOPMVjdWMcp27dulStWjXRXw8++CDt27dPsy24NuWxvv76a+rbt69wccENi2O9/vrrVFJS4naOr2fPnuJaatasSZ06daK33nrLbR9gfa93332X/vnPf1Lr1q3FvjjfddddR2PGjKHDhw/rnkveBwCLsd56663ietVBE6dPnxb92bx5c1dfjB07lv766y8KVHCGun16+2Lh05EjR1LTpk3F/YTPJk6cSGfPnjV8XryH3xt8+eWXF90b+G0luKeGDRtGV155pThfjRo1xP5YlPXVV191+/syxmGXI2OISZMmiX+03333HY0ePZqWLFlSZpl6DNqnTp2izp07i8/N5L///S+NHz9erMwM4cHr//73PyGGEDplWzzhcDjEgpe4FoCBHMfEIHvo0CHav3+/GIyuueYa8fnf//53Onr0qPirWrUq1a9fX/O4aM+9995LUVFR4ns4LhbZxMAJ4cCim4sXL6Zu3brptu3tt9+mUaNGUcWKFYVAYF+05/HHHxcLTU6ZMuWifXDtDz/8sBgQk5OTheD/+eef4jjY1928IH4z9CUG2Hr16lFeXp445xtvvEErV64Ubf7b3/6me4wnnniC5s2b59of55VgMMdKzug39EmTJk1EGxcsWECbN2+mLl26ULDAPYMV0vPz80W7YmNjxXXPmTOHvvnmG9q0aZPoF09A/OPi4ujXX38VfY8FVZUkJCSI108++YT69+8v7ge58jWOn5GRQVu2bBF/eKAzck7GPWyhMYbAP3oMdPiHC0sE/y+ZOXMmffrpp2Jge+2118hms5l6bjzVY/CFaOA8P/30E/3nP/8R50FbPv/8c8PHwmAFMatevboY1BGltnXrVtq9e7cYfDGQQ8QkWAVaRq/dfPPNYlv5J4GVN3/+fDG4HTx4ULQJ1ha2p0+fLoR0xIgRQjT0eOyxx4Ro4Toh4niFZQww2P72229lvo/zwAKCUKB/fvnlF7Ef+ufll18Wlp1SZJRAmCGwsMQgfOhXDOY///yz6G9YKmivnuWAwfjNN98U50A70Ic4Dqw9MHz4cNGfsIB27txJX331leiP7du3C4HDvsF8OOvatau41s8++0zcA2vXrhUBH99++y0tX77c0HHQf/jNAKwt9b0BqxQ888wzQszw4IHfCH2B+wO/L4JKsKo4+oTxH+5FxjCwGiBeAO4ZDGAYBGEpQVwgZhA1s4HbDf/o5RMv6NOnj+spXyksnsCAAu68807h/lGCJ+RbbrlFCJe34LrvvvtuSklJKfN+fHy8cDXBtQQr0F1b4WqEiERHR7vew4CJJ38Iy0cffVTm+3BVwdXZokUL4RbFuQB+iyFDhggrpLi4WPNcsOTQB7AYlFxyySXit4WoQ6hgkWsBgYbliDbLBxi8og1SvABEHtabpHHjxjR37lwxwAcLuHPhcoYlLLnxxhtFf3l7P3lzz+G3TExMLPNZrVq1hNCxoJkD27iMV2BgxtM85mgwpwWLA4Mm/lHC3RgIhg4dqvk+rAEMPnAVGgUDCMA1YI4HlpWZ4In/448/Fk/f2dnZwh0LYK0AWANweXp7nXh4UF8nXHdAL0oUbixYEXpAlNB/6Au4CNFeaZHBspTtxXylFnCxaiHbhQcRiK0aiCXcdbt27aJgMHjwYOFx0OpnWJze3E9G7zncD5hvxJwlEzhY0BivgTUAywxP8ADzLE8++WTAzoc5By0wVyUDHIyCeR1YJ3DLIVihffv2dP3114vBDH/SyvEWtGHQoEHC5eeOzMxMU67zzJkzIhAHwK2nBa4TVqeWlXb8+HFhXUGwfGkv8gdlu9TAleeuXQBzV8ESNDPvJyPgYQ9zmgi2gWWIoJ1WrVpRu3btxFwrYx5s5zJeg7mGNm3auLYxx6T1xGvm+bSQbhpvIsTg8sE8GtyAcLdhwv65556j7t27CwGAMLub53I3LwMxw0A/a9YsMSeH+StEhOIP81LAnavNbrcbvk7loKsnLHBdVq5cWfMzROdBzOBGxnwo5nIgkLK9cJ+6a6/eb6Jsm167QCBc08G4n4yABx14NPBvBpYw5g9hPcN6hXuby2mZBwsa4zWomIHoOjkAYH4LUWLhAtyMCNSAGwhzPQiggKBByPAELUOxjQILCMEkAPNDcMVhnkY5X+JPqLoWyrkvRJfquRS1LCwIFyLrZCoC3MhwiymtU3/aK9um1y5w8uRJn44t5+v0RMeXh5HyAPcX5kAR2IN75dFHHxX3CAJm0P94oGD8hwWN8Ypjx46J/B3wwgsviNqGcH/B4sEAGk5gcIRbDAEUeIJG2DxAuLpSCDxFbWIuTlolmDfSAtFzZoKABhlFd+DAAd1gBC13o8yPQgCLllsQ+8DC9JVGjRq5bZenz9whrVg9scRDSnnibUQvfjcEHj399NPinoDrEYE93qSeMPqwoDGGgWBBuPD0jrBnhGYj0g7JvAjHRrRjOKN0oyIsXe2iOnfunOZ+SktMzmupA0X27NljcmtL0wgAAhm0QNSpu/YiCETLooHV5s66MtoupEdoJZRj/tXX+TMZMYljaAlxeQuDp3vDHZjflHl+eukVjHewoDGGmTZtmgjJvvzyy4VrTT7lY0DFfM1LL70U8vMBcCmikgkSlZVgYJ86dar4f+TaKROo4RoCcA9pBQzgqVumACDZWFlJBf2ByDZlyoFZwFLG3CXEcsKECa6qKXDHYWCH1amVrAurDHN9EADM7SHBWLJu3ToaN26cX+1FsIN8OEAEprLqCKxGpCb4OucqE9OXLl1aJv8QeXNI6Dc7QtET8t6Axan1MIN2IaoSLl51VRtUD4E3ACDqk/EfFjTGEHjanjFjhpg3Q26RMthAloySFUPcRfIFG4TPw92DCXlE2iHiDAMwAkJg0UAAMKemtLqQjoAgBuyLyEhYIIiWxJ9k8uTJQtQRso7vdOjQga6++moxd4IHAFi2ZgNhwkMG3F54wMA1oK3IW8PgDjHBudXgGpHsC+BmhYuwY8eOYj8Mvoj6vOOOO/xqG+4RJK8j3QCDNfoY9wkiSSGkSPnwhX79+ok0gtzcXJFHhz5GDhmuAXO7CPApT3Afod/wQHTttdeK+0neGxA4/JvAQwLmyeDJQMoCSq5hP/Q5voPrgbeD8R8WNMYjcDFicITLEZPZGKzVIMkWAyFcdd4GVZQnsJYQyYhBEFYCnqwx7wLBQrQmcrLUeWKYt8GghEEelguerCHwsnwWgJCsX79eDFIQGFgiCLKA0CMYwF1UoD9AGFDlAufF4IlUCtRkRKSlOxcwIu9g5UBgEMmI9uIhBYKAUl3K5G5fQPQk+hL9jfbg+LBWkGuHaFB1ArpRIMZr1qwR1ikEAvcbUhBQyxIWGx4myhP81gjyQGkr9B9crPLegOWLRHVUtUF/I10AwTC4f9AX+PeCB5KNGzcG7P6INGxZWVlcFZNhGIYJe9hCYxiGYSwBCxrDMAxjCVjQGIZhGEvAgsYwDMNYAhY0hmEYxhKwoDEMwzCWgAWNYRiGsQQsaAzDMIwlYEFjGIZhLAELGsMwDGMJWNAYhmEYS8CCxjAMw1gCFjSGYRiGrMD/A0WBudPJFHgeAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = 0.5\n",
    "x_demo = np.random.normal(0, 1, 10000)\n",
    "z_demo = np.random.normal(0, 1, 10000)\n",
    "y_demo = r*x_demo + np.sqrt(1 - r**2)*z_demo\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.xlim(-4, 4)\n",
    "plt.ylim(-4, 4)\n",
    "plt.scatter(x_demo, y_demo, s=3)\n",
    "plt.plot([-4, 4], [-4*0.6,4*0.6], color='g', lw=2)\n",
    "plt.plot([-4,4],[-4,4], color='r', lw=2)\n",
    "plt.plot([1.5,1.5], [-4,4], color='k', lw=2)\n",
    "plt.xlabel('x in standard units')\n",
    "plt.ylabel('y in standard units');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c71420a",
   "metadata": {},
   "source": [
    "Both lines go through the origin (0, 0). The green line goes through the centers of the vertical strips (at least roughly), and is *flatter* than the red 45 degree line. \n",
    "\n",
    "The slope of the 45 degree line is 1. So the slope of the green \"graph of averages\" line is a value that is positive but less than 1. \n",
    "\n",
    "What value could that be? You've guessed it – it's $r$."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b44308f6",
   "metadata": {},
   "source": [
    "## The Regression Line, in Standard Units\n",
    "The green \"graph of averages\" line is called the *regression line*, for a reason that we will explain shortly. But first, let's simulate some football shaped scatter plt with different values of $r$, and see how the line changes. In each case, the red 45 degree line has been drawn for comparison.\n",
    "\n",
    "The function that performs the simulation is called `regression_line` and takes $r$ as its argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "46e6f15e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.272436Z",
     "iopub.status.busy": "2026-08-31T06:02:07.272376Z",
     "iopub.status.idle": "2026-08-31T06:02:07.274214Z",
     "shell.execute_reply": "2026-08-31T06:02:07.274045Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "def regression_line(r):\n",
    "    x = np.random.normal(0, 1, 10000)\n",
    "    z = np.random.normal(0, 1, 10000)\n",
    "    y = r*x + (np.sqrt(1-r**2))*z\n",
    "    plt.figure(figsize=(4, 4))\n",
    "    plt.xlim(-4, 4)\n",
    "    plt.ylim(-4, 4)\n",
    "    plt.scatter(x, y, s=1)\n",
    "    plt.plot([-4, 4], [-4*r,4*r], color='g', lw=2)\n",
    "    if r >= 0:\n",
    "        plt.plot([-4,4],[-4,4], lw=2, color='r')\n",
    "    else:\n",
    "        plt.plot([-4,4], [4,-4], lw=2, color='r')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0c64e16c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.275077Z",
     "iopub.status.busy": "2026-08-31T06:02:07.275019Z",
     "iopub.status.idle": "2026-08-31T06:02:07.302929Z",
     "shell.execute_reply": "2026-08-31T06:02:07.302743Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "regression_line(0.95)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cab71274",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.303927Z",
     "iopub.status.busy": "2026-08-31T06:02:07.303868Z",
     "iopub.status.idle": "2026-08-31T06:02:07.333079Z",
     "shell.execute_reply": "2026-08-31T06:02:07.332878Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "regression_line(0.6)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aeb8b13d",
   "metadata": {},
   "source": [
    "When $r$ is close to 1, the scatter plot, the 45 degree line, and the regression line are all very close to each other. But for more moderate values of $r$, the regression line is noticeably flatter."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84b55712",
   "metadata": {},
   "source": [
    "## The Regression Effect\n",
    "In terms of prediction, this means that for a parents whose midparent height is at 1.5 standard units, our prediction of the child's height is somewhat *less* than 1.5 standard units. If the midparent height is 2 standard units, we predict that the child's height will be somewhat less than 2 standard units.\n",
    "\n",
    "In other words, we predict that the child will be somewhat closer to average than the parents were. This is called \"regression to the mean\" and it is how the name *regression* arises.\n",
    "\n",
    "Regression to the mean also works when the midparent height is below average. Children whose midparent heights were below average turned out to be somewhat taller relative to their generation, on average. \n",
    "\n",
    "In general, individuals who are away from average on one variable are expected to be not quite as far away from average on the other. This is called the *regression effect*.\n",
    "\n",
    "Keep in mind that the regression effect is a statement about averages. For example, it says that if you take all children whose midparent height is 1.5 standard units, then the average height of these children is somewhat less than 1.5 standard units. It doesn't say that all of these children will be somewhat less than 1.5 standard units in height. Some will be taller, and some will be shorter. The *average* of these heights will be less than 1.5 standard units."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2134383",
   "metadata": {},
   "source": [
    "## The Equation of the Regression Line\n",
    "In regression, we use the value of one variable (which we will call $x$) to predict the value of another (which we will call $y$). When the variables $x$ and $y$ are measured in standard units, the regression line for predicting $y$ based on $x$ has slope $r$ and passes through the origin. Thus the equation of the regression line can be written as:\n",
    "\n",
    "$$\n",
    "\\mbox{estimate of }y ~=~ r \\cdot x ~~~\n",
    "\\mbox{when both variables are measured in standard units}\n",
    "$$\n",
    "\n",
    "In the original units of the data, this becomes\n",
    "\n",
    "$$\n",
    "\\frac{\\mbox{estimate of}~y ~-~\\mbox{average of}~y}{\\mbox{SD of}~y}\n",
    "~=~ r \\times \n",
    "\\frac{\\mbox{the given}~x ~-~\\mbox{average of}~x}{\\mbox{SD of}~x}\n",
    "$$\n",
    "\n",
    "\n",
    "```{figure} ../../figures/regline.png\n",
    "---\n",
    "alt: regline\n",
    "name: regression_line\n",
    "width: 450px\n",
    "---\n",
    "Regression Line in Standard Units and in Original Units\n",
    "```\n",
    "\n",
    "The slope and intercept of the regression line in original units can be derived from the diagram above. \n",
    "\n",
    "$$\n",
    "\\mathbf{\\mbox{slope of the regression line}} ~=~ r \\cdot\n",
    "\\frac{\\mbox{SD of }y}{\\mbox{SD of }x}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\mathbf{\\mbox{intercept of the regression line}} ~=~\n",
    "\\mbox{average of }y ~-~ \\mbox{slope} \\cdot \\mbox{average of }x\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9437ca65",
   "metadata": {},
   "source": [
    "The three functions below compute the correlation, slope, and intercept. All of them take three arguments: the name of the table, the label of the column containing $x$, and the label of the column containing $y$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3c9587bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.334261Z",
     "iopub.status.busy": "2026-08-31T06:02:07.334205Z",
     "iopub.status.idle": "2026-08-31T06:02:07.335917Z",
     "shell.execute_reply": "2026-08-31T06:02:07.335738Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def correlation(t, label_x, label_y):\n",
    "    return float(np.mean(standard_units(t[label_x])*standard_units(t[label_y])))\n",
    "\n",
    "def slope(t, label_x, label_y):\n",
    "    r = correlation(t, label_x, label_y)\n",
    "    return r*np.std(t[label_y])/float(np.std(t[label_x]))\n",
    "\n",
    "def intercept(t, label_x, label_y):\n",
    "    return float(np.mean(t[label_y]) - slope(t, label_x, label_y)*np.mean(t[label_x]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37d9a74c",
   "metadata": {},
   "source": [
    "## The Regression Line in the Units of the Data\n",
    "The correlation between midparent height and child's height is 0.32:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "524fbca0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.336866Z",
     "iopub.status.busy": "2026-08-31T06:02:07.336810Z",
     "iopub.status.idle": "2026-08-31T06:02:07.338128Z",
     "shell.execute_reply": "2026-08-31T06:02:07.337941Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def correlation(t, x, y):\n",
    "    return float(np.mean(standard_units(t[x])*standard_units(t[y])))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4bd292cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.339018Z",
     "iopub.status.busy": "2026-08-31T06:02:07.338951Z",
     "iopub.status.idle": "2026-08-31T06:02:07.340829Z",
     "shell.execute_reply": "2026-08-31T06:02:07.340672Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.32094989606395924"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "family_r = correlation(heights, 'MidParent', 'Child')\n",
    "family_r\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e20119b",
   "metadata": {},
   "source": [
    "We can also find the equation of the regression line for predicting the child's height based on midparent height."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "47bc01cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.341699Z",
     "iopub.status.busy": "2026-08-31T06:02:07.341628Z",
     "iopub.status.idle": "2026-08-31T06:02:07.343933Z",
     "shell.execute_reply": "2026-08-31T06:02:07.343772Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.6373608969694786, 22.636240549589772)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "family_slope = float(slope(heights, 'MidParent', 'Child'))\n",
    "family_intercept = float(intercept(heights, 'MidParent', 'Child'))\n",
    "family_slope, family_intercept\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4e82fd0",
   "metadata": {},
   "source": [
    "The equation of the regression line is\n",
    "\n",
    "$$\n",
    "\\mbox{estimate of child's height} ~=~ 0.64 \\cdot \\mbox{midparent height} ~+~ 22.64\n",
    "$$\n",
    "\n",
    "This is also known as the **regression equation**. The principal use of the regression equation is to predict $y$ based on $x$.\n",
    "\n",
    "For example, for a midparent height of 70.48 inches, the regression equation predicts the child's height to be 67.56 inches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "70d9af8f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.344834Z",
     "iopub.status.busy": "2026-08-31T06:02:07.344760Z",
     "iopub.status.idle": "2026-08-31T06:02:07.346277Z",
     "shell.execute_reply": "2026-08-31T06:02:07.346097Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "67.55743656799862"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "family_slope * 70.48 + family_intercept\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5928e49a",
   "metadata": {},
   "source": [
    "Our original prediction, created by taking the average height of all children who had midparent heights close to 70.48, came out to be pretty close: 67.63 inches compared to the regression line's prediction of 67.55 inches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f28ef478",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.347200Z",
     "iopub.status.busy": "2026-08-31T06:02:07.347143Z",
     "iopub.status.idle": "2026-08-31T06:02:07.349796Z",
     "shell.execute_reply": "2026-08-31T06:02:07.349625Z"
    },
    "tags": []
   },
   "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>MidParent</th>\n",
       "      <th>Child</th>\n",
       "      <th>Prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>70.48</td>\n",
       "      <td>74.0</td>\n",
       "      <td>67.634239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>70.48</td>\n",
       "      <td>70.0</td>\n",
       "      <td>67.634239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>70.48</td>\n",
       "      <td>68.0</td>\n",
       "      <td>67.634239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>70.48</td>\n",
       "      <td>67.0</td>\n",
       "      <td>67.634239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>70.48</td>\n",
       "      <td>67.0</td>\n",
       "      <td>67.634239</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    MidParent  Child  Prediction\n",
       "33      70.48   74.0   67.634239\n",
       "34      70.48   70.0   67.634239\n",
       "35      70.48   68.0   67.634239\n",
       "36      70.48   67.0   67.634239\n",
       "37      70.48   67.0   67.634239"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights_with_predictions[heights_with_predictions['MidParent'] == 70.48].head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "205edb84",
   "metadata": {},
   "source": [
    "Here are all of the rows of the table, along with our original predictions and the new regression predictions of the children's heights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4b7cb0c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.350742Z",
     "iopub.status.busy": "2026-08-31T06:02:07.350691Z",
     "iopub.status.idle": "2026-08-31T06:02:07.353701Z",
     "shell.execute_reply": "2026-08-31T06:02:07.353527Z"
    },
    "tags": []
   },
   "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>MidParent</th>\n",
       "      <th>Child</th>\n",
       "      <th>Prediction</th>\n",
       "      <th>Regression Prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75.43</td>\n",
       "      <td>73.2</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.2</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "      <td>70.100000</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>73.66</td>\n",
       "      <td>73.5</td>\n",
       "      <td>70.415789</td>\n",
       "      <td>69.584244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>66.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>65.156579</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>66.64</td>\n",
       "      <td>62.0</td>\n",
       "      <td>65.156579</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>66.64</td>\n",
       "      <td>61.0</td>\n",
       "      <td>65.156579</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>65.27</td>\n",
       "      <td>66.5</td>\n",
       "      <td>64.229630</td>\n",
       "      <td>64.236786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>65.27</td>\n",
       "      <td>57.0</td>\n",
       "      <td>64.229630</td>\n",
       "      <td>64.236786</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent  Child  Prediction  Regression Prediction\n",
       "0        75.43   73.2   70.100000              70.712373\n",
       "1        75.43   69.2   70.100000              70.712373\n",
       "2        75.43   69.0   70.100000              70.712373\n",
       "3        75.43   69.0   70.100000              70.712373\n",
       "4        73.66   73.5   70.415789              69.584244\n",
       "..         ...    ...         ...                    ...\n",
       "929      66.64   64.0   65.156579              65.109971\n",
       "930      66.64   62.0   65.156579              65.109971\n",
       "931      66.64   61.0   65.156579              65.109971\n",
       "932      65.27   66.5   64.229630              64.236786\n",
       "933      65.27   57.0   64.229630              64.236786\n",
       "\n",
       "[934 rows x 4 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights_with_predictions['Regression Prediction'] =  family_slope * heights['MidParent'] + family_intercept\n",
    "\n",
    "heights_with_predictions\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "99d13811",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.354551Z",
     "iopub.status.busy": "2026-08-31T06:02:07.354500Z",
     "iopub.status.idle": "2026-08-31T06:02:07.397288Z",
     "shell.execute_reply": "2026-08-31T06:02:07.397086Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115e5aad0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "\n",
    "ax.scatter(heights_with_predictions['MidParent'], \n",
    "           heights_with_predictions['Child'], \n",
    "           label='Child', \n",
    "           color='darkblue',\n",
    "          s=5)\n",
    "\n",
    "ax.scatter(heights_with_predictions['MidParent'], \n",
    "           heights_with_predictions['Prediction'], \n",
    "           label='Prediction', \n",
    "           color='red',\n",
    "          s=3)\n",
    "\n",
    "ax.scatter(heights_with_predictions['MidParent'], \n",
    "           heights_with_predictions['Regression Prediction'], \n",
    "           label='Regression Prediction', \n",
    "           color='green',\n",
    "          s=3)\n",
    "\n",
    "x_label = 'MidParent'\n",
    "y_label = ''\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e16b88d0",
   "metadata": {},
   "source": [
    "The green dots show the regression predictions, all on the regression line. Notice how the line is very close to the gold graph of averages. For these data, the regression line does a good job of approximating the centers of the vertical strips."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d294f0b",
   "metadata": {},
   "source": [
    "## Fitted Values\n",
    "The predictions all lie on the line and are known as the \"fitted values\". The function `fit` takes the name of the table and the labels of $x$ and $y$, and returns an array of fitted values, one fitted value for each point in the scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0e9d8c1e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.398354Z",
     "iopub.status.busy": "2026-08-31T06:02:07.398294Z",
     "iopub.status.idle": "2026-08-31T06:02:07.399758Z",
     "shell.execute_reply": "2026-08-31T06:02:07.399585Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def fit(table, x, y):\n",
    "    \"\"\"Return the height of the regression line at each x value.\"\"\"\n",
    "    a = slope(table, x, y)\n",
    "    b = intercept(table, x, y)\n",
    "    return a * table[x] + b\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "353cae39",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.400654Z",
     "iopub.status.busy": "2026-08-31T06:02:07.400595Z",
     "iopub.status.idle": "2026-08-31T06:02:07.404097Z",
     "shell.execute_reply": "2026-08-31T06:02:07.403924Z"
    },
    "tags": []
   },
   "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>MidParent</th>\n",
       "      <th>Child</th>\n",
       "      <th>Fitted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75.43</td>\n",
       "      <td>73.2</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.2</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75.43</td>\n",
       "      <td>69.0</td>\n",
       "      <td>70.712373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>73.66</td>\n",
       "      <td>73.5</td>\n",
       "      <td>69.584244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>66.64</td>\n",
       "      <td>64.0</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>66.64</td>\n",
       "      <td>62.0</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>66.64</td>\n",
       "      <td>61.0</td>\n",
       "      <td>65.109971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>932</th>\n",
       "      <td>65.27</td>\n",
       "      <td>66.5</td>\n",
       "      <td>64.236786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>933</th>\n",
       "      <td>65.27</td>\n",
       "      <td>57.0</td>\n",
       "      <td>64.236786</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>934 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     MidParent  Child     Fitted\n",
       "0        75.43   73.2  70.712373\n",
       "1        75.43   69.2  70.712373\n",
       "2        75.43   69.0  70.712373\n",
       "3        75.43   69.0  70.712373\n",
       "4        73.66   73.5  69.584244\n",
       "..         ...    ...        ...\n",
       "929      66.64   64.0  65.109971\n",
       "930      66.64   62.0  65.109971\n",
       "931      66.64   61.0  65.109971\n",
       "932      65.27   66.5  64.236786\n",
       "933      65.27   57.0  64.236786\n",
       "\n",
       "[934 rows x 3 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights['Fitted'] = fit(heights, 'MidParent', 'Child')\n",
    "heights\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08953723",
   "metadata": {},
   "source": [
    "It is easier to see the line in the graph below than in the one above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4278c21d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.405022Z",
     "iopub.status.busy": "2026-08-31T06:02:07.404965Z",
     "iopub.status.idle": "2026-08-31T06:02:07.434970Z",
     "shell.execute_reply": "2026-08-31T06:02:07.434765Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#heights.with_column('Fitted', fit(heights, 'MidParent', 'Child')).scatter('MidParent')\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "ax.scatter(heights['MidParent'], heights['Child'], label='Child', color='darkblue', s=5 )\n",
    "ax.scatter(heights['MidParent'], heights['Fitted'], label='Fitted', color='gold', s=5 )\n",
    "\n",
    "x_label = 'MidParent'\n",
    "y_label = 'Child'\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e2cf246",
   "metadata": {},
   "source": [
    "Another way to draw the line is to draw the fit line:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "70b12b71",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.435961Z",
     "iopub.status.busy": "2026-08-31T06:02:07.435901Z",
     "iopub.status.idle": "2026-08-31T06:02:07.464531Z",
     "shell.execute_reply": "2026-08-31T06:02:07.464330Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# heights.plot.scatter('MidParent', 'Child')\n",
    "\n",
    "x_data = heights['MidParent']\n",
    "y_data = heights['Child']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "m, b = np.polyfit(x_data, y_data, 1)\n",
    "minx, maxx = np.min(x_data), np.max(x_data)\n",
    "\n",
    "ax.plot([minx, maxx],[ m * minx + b, m * maxx + b], label='Best Fit Line', color='red', lw=2 )\n",
    "ax.scatter(x_data, y_data, color='darkblue', s=5 )\n",
    "\n",
    "x_label = 'MidParent'\n",
    "y_label = 'Child'\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb763236",
   "metadata": {},
   "source": [
    "## Units of Measurement of the Slope\n",
    "The slope is a ratio, and it worth taking a moment to study the units in which it is measured. Our example comes from the familiar dataset about mothers who gave birth in a hospital system. The scatter plot of pregnancy weights versus heights looks like a football that has been used in one game too many, but it's close enough to a football that we can justify putting our fitted line through it. In later sections we will see how to make such justifications more formal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "c2bf9002",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.465574Z",
     "iopub.status.busy": "2026-08-31T06:02:07.465509Z",
     "iopub.status.idle": "2026-08-31T06:02:07.467528Z",
     "shell.execute_reply": "2026-08-31T06:02:07.467343Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "baby = pd.read_csv(path_data + 'baby.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2f13dfed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.468450Z",
     "iopub.status.busy": "2026-08-31T06:02:07.468394Z",
     "iopub.status.idle": "2026-08-31T06:02:07.500853Z",
     "shell.execute_reply": "2026-08-31T06:02:07.500665Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115c67390>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#baby.plot.scatter('Maternal Height', 'Maternal Pregnancy Weight', fit_line=True)\n",
    "\n",
    "x_data = baby['Maternal Height']\n",
    "y_data = baby['Maternal Pregnancy Weight']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(4,4))\n",
    "\n",
    "m, b = np.polyfit(x_data, y_data, 1)\n",
    "minx, maxx = np.min(x_data),np.max(x_data)\n",
    "\n",
    "ax.plot([minx, maxx],[m * minx + b, m * maxx + b], label='Best Fit Line', color='red', lw=3)\n",
    "ax.scatter(x_data, y_data, color='darkblue', s=5, alpha=.8)\n",
    "\n",
    "x_label = 'Maternal Height'\n",
    "y_label = 'Maternal Pregnancy Weight'\n",
    "y_vals = ax.get_yticks()\n",
    "plt.ylabel(y_label)\n",
    "plt.xlabel(x_label)\n",
    "ax.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\", frameon=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "e6223bb9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.501863Z",
     "iopub.status.busy": "2026-08-31T06:02:07.501806Z",
     "iopub.status.idle": "2026-08-31T06:02:07.503812Z",
     "shell.execute_reply": "2026-08-31T06:02:07.503625Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.572846259275061"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "slope(baby, 'Maternal Height', 'Maternal Pregnancy Weight')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d306b937",
   "metadata": {},
   "source": [
    "The slope of the regression line is **3.57 pounds per inch**. This means that for two women who are 1 inch apart in height, our prediction of pregnancy weight will differ by 3.57 pounds. For a woman who is 2 inches taller than another, our prediction of pregnancy weight will be\n",
    "\n",
    "$$\n",
    "2 \\times 3.57 ~=~ 7.14\n",
    "$$\n",
    "\n",
    "pounds more than our prediction for the shorter woman.\n",
    "\n",
    "Notice that the successive vertical strips in the scatter plot are one inch apart, because the heights have been rounded to the nearest inch. Another way to think about the slope is to take any two consecutive strips (which are necessarily 1 inch apart), corresponding to two groups of women who are separated by 1 inch in height. The slope of 3.57 pounds per inch means that the average pregnancy weight of the taller group is about 3.57 pounds more than that of the shorter group."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d66a7a1f",
   "metadata": {},
   "source": [
    "\n",
    "## Example\n",
    "\n",
    "Suppose that our goal is to use regression to estimate the height of a basset hound based on its weight, using a sample that looks consistent with the regression model. Suppose the observed correlation $r$ is 0.5, and that the summary statistics for the two variables are as in the table below: \n",
    "\n",
    "|       |**average**    |**SD**     |   \n",
    "|------:|:-------------:|:---------:|\n",
    "|height |14 inches      |2 inches   |\n",
    "|weight |50 pounds      |5 pounds   |\n",
    "\n",
    "To calculate the equation of the regression line, we need the slope and the intercept.\n",
    "\n",
    "$$\n",
    "\\mbox{slope} ~=~ \\frac{r \\cdot \\mbox{SD of }y}{\\mbox{SD of }x} ~=~\n",
    "\\frac{0.5 \\cdot 2 \\mbox{ inches}}{5 \\mbox{ pounds}} ~=~ 0.2 ~\\mbox{inches per pound}\n",
    "$$\n",
    "\n",
    "\n",
    "$$\n",
    "\\mbox{intercept} ~=~ \\mbox{average of }y - \\mbox{slope}\\cdot \\mbox{average of } x\n",
    "~=~ 14 \\mbox{ inches} ~-~ 0.2 \\mbox{ inches per pound} \\cdot 50 \\mbox{ pounds}\n",
    "~=~ 4 \\mbox{ inches}\n",
    "$$\n",
    "\n",
    "The equation of the regression line allows us to calculate the estimated height, in inches,\n",
    "based on a given weight in pounds:\n",
    "\n",
    "$$\n",
    "\\mbox{estimated height} ~=~ 0.2 \\cdot \\mbox{given weight} ~+~ 4\n",
    "$$\n",
    "\n",
    "The slope of the line is measures the increase in the estimated height per unit increase in weight. The slope is positive, and it is important to note that this does not mean that we think basset hounds get taller if they put on weight. The slope reflects the difference in the average heights of two groups of dogs that are 1 pound apart in weight. Specifically, consider a group of dogs whose weight is $w$ pounds, and the group whose weight is $w+1$ pounds. The second group is estimated to be 0.2 inches taller, on average. This is true for all values of $w$ in the sample.\n",
    "\n",
    "In general, the slope of the regression line can be interpreted as the average increase in $y$ per unit increase in $x$. Note that if the slope is negative, then for every unit increase in $x$, the average of $y$ decreases."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47da00ae",
   "metadata": {},
   "source": [
    "## Endnote\n",
    "Even though we won't establish the mathematical basis for the regression equation, we can see that it gives pretty good predictions when the scatter plot is football shaped. It is a surprising mathematical fact that no matter what the shape of the scatter plot, the same equation gives the \"best\" among all straight lines. That's the topic of the next section."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-c09a86d4",
   "metadata": {},
   "source": [
    "\n",
    "## Section Practice\n",
    "\n",
    "Use this short exercise to check the main workflow from this section.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cell-218b895b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.504855Z",
     "iopub.status.busy": "2026-08-31T06:02:07.504803Z",
     "iopub.status.idle": "2026-08-31T06:02:07.506105Z",
     "shell.execute_reply": "2026-08-31T06:02:07.505927Z"
    },
    "tags": [
     "thebe-interactive"
    ]
   },
   "outputs": [],
   "source": [
    "### Exercise: Practice Regression Line\n",
    "# Using the coffee chain's data:\n",
    "#   1. Compute the slope (r * SD of sales / SD of temperature) and the intercept\n",
    "#      (mean of sales - slope * mean of temperature).\n",
    "#   2. Predict iced-drink sales on an 80-degree day.\n",
    "#   3. Print the slope, intercept, and prediction, rounded to 2 decimals.\n",
    "import numpy as np\n",
    "\n",
    "temperature = np.array([58, 62, 66, 70, 75, 79, 83, 88])\n",
    "iced_sales = np.array([120, 135, 150, 148, 180, 205, 210, 240])\n",
    "### Your code starts here\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "### Your code ends here\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "cell-2c6fce6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-31T06:02:07.507051Z",
     "iopub.status.busy": "2026-08-31T06:02:07.506992Z",
     "iopub.status.idle": "2026-08-31T06:02:07.508517Z",
     "shell.execute_reply": "2026-08-31T06:02:07.508324Z"
    },
    "tags": [
     "hide-input"
    ]
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Slope: 3.95\nIntercept: -113.22\nPredicted sales at 80 F: 202.62\n"
    }
   ],
   "source": [
    "### Solution\n",
    "import numpy as np\n",
    "\n",
    "temperature = np.array([58, 62, 66, 70, 75, 79, 83, 88])\n",
    "iced_sales = np.array([120, 135, 150, 148, 180, 205, 210, 240])\n",
    "\n",
    "def standard_units(x):\n",
    "    return (x - np.mean(x)) / np.std(x)\n",
    "\n",
    "r = np.mean(standard_units(temperature) * standard_units(iced_sales))\n",
    "slope = r * np.std(iced_sales) / np.std(temperature)\n",
    "intercept = np.mean(iced_sales) - slope * np.mean(temperature)\n",
    "\n",
    "print('Slope:', round(slope, 2))\n",
    "print('Intercept:', round(intercept, 2))\n",
    "print('Predicted sales at 80 F:', round(slope * 80 + intercept, 2))\n"
   ]
  }
 ],
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