moths.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a5315ea8-b42a-4521-8ee3-fe9b6e62a58f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41846818</td>\n",
       "      <td>Melese_erythrastis</td>\n",
       "      <td>0.766231</td>\n",
       "      <td>2.000000e-10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41479364</td>\n",
       "      <td>Haemanota_affinis</td>\n",
       "      <td>0.027746</td>\n",
       "      <td>2.580000e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>42022244</td>\n",
       "      <td>Opharus_roseistriga</td>\n",
       "      <td>0.469302</td>\n",
       "      <td>3.070000e-10</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14651446</td>\n",
       "      <td>Hyalarctia</td>\n",
       "      <td>0.635492</td>\n",
       "      <td>3.450000e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>42261991</td>\n",
       "      <td>Amaxia_juvenis</td>\n",
       "      <td>0.666043</td>\n",
       "      <td>3.839999e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    page_id           page_title  page_random           gap  1  2   3  4  5  \\\n",
       "0  41846818   Melese_erythrastis     0.766231  2.000000e-10  0  0   2  0  1   \n",
       "1  41479364    Haemanota_affinis     0.027746  2.580000e-10  1  1   0  0  1   \n",
       "2  42022244  Opharus_roseistriga     0.469302  3.070000e-10  3  1   0  0  1   \n",
       "3  14651446           Hyalarctia     0.635492  3.450000e-10  1  1  14  1  4   \n",
       "4  42261991       Amaxia_juvenis     0.666043  3.839999e-10  1  4   0  0  3   \n",
       "\n",
       "   6  7  8  9  10  11  12  total  \n",
       "0  1  1  0  0   0   4   0      9  \n",
       "1  2  1  1  0   2   2   0     11  \n",
       "2  1  1  1  0   0   3   0     11  \n",
       "3  2  5  5  3   2   2   3     43  \n",
       "4  1  1  0  0   2   1   0     13  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set_theme()\n",
    "from matplotlib import pyplot as plt\n",
    "import os\n",
    "\n",
    "img_dir = \"/home/colin/src/colinmorris.github.com/assets/wiki-floor/\"\n",
    "def savefig(fname, dpi=144):\n",
    "    path = os.path.join(img_dir, fname)\n",
    "    plt.savefig(path, bbox_inches='tight', dpi=dpi)\n",
    "\n",
    "\n",
    "df = pd.read_csv('merged_phaeg.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7e27f3c4-3301-44ba-92f4-d46f2ff29ad3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['random_total'] = df.total.sample(frac=1, random_state=1).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "987fe239-2b28-4d6e-847f-975c009e823c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>page_id</th>\n",
       "      <th>page_title</th>\n",
       "      <th>page_random</th>\n",
       "      <th>gap</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>total</th>\n",
       "      <th>random_total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41846818</td>\n",
       "      <td>Melese_erythrastis</td>\n",
       "      <td>0.766231</td>\n",
       "      <td>2.000000e-10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41479364</td>\n",
       "      <td>Haemanota_affinis</td>\n",
       "      <td>0.027746</td>\n",
       "      <td>2.580000e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>42022244</td>\n",
       "      <td>Opharus_roseistriga</td>\n",
       "      <td>0.469302</td>\n",
       "      <td>3.070000e-10</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14651446</td>\n",
       "      <td>Hyalarctia</td>\n",
       "      <td>0.635492</td>\n",
       "      <td>3.450000e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>43</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>42261991</td>\n",
       "      <td>Amaxia_juvenis</td>\n",
       "      <td>0.666043</td>\n",
       "      <td>3.839999e-10</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    page_id           page_title  page_random           gap  1  2   3  4  5  \\\n",
       "0  41846818   Melese_erythrastis     0.766231  2.000000e-10  0  0   2  0  1   \n",
       "1  41479364    Haemanota_affinis     0.027746  2.580000e-10  1  1   0  0  1   \n",
       "2  42022244  Opharus_roseistriga     0.469302  3.070000e-10  3  1   0  0  1   \n",
       "3  14651446           Hyalarctia     0.635492  3.450000e-10  1  1  14  1  4   \n",
       "4  42261991       Amaxia_juvenis     0.666043  3.839999e-10  1  4   0  0  3   \n",
       "\n",
       "   6  7  8  9  10  11  12  total  random_total  \n",
       "0  1  1  0  0   0   4   0      9            57  \n",
       "1  2  1  1  0   2   2   0     11            33  \n",
       "2  1  1  1  0   0   3   0     11            84  \n",
       "3  2  5  5  3   2   2   3     43            67  \n",
       "4  1  1  0  0   2   1   0     13            25  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "60199942-7e9c-467f-9ee4-b627f0cce152",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "FS = (8, 6)\n",
    "fig, ax = plt.subplots(figsize=FS)\n",
    "sns.scatterplot(data=df, x='gap', y='random_total', alpha=.5, marker='.')\n",
    "ax.set_xlabel(\"Random gap\")\n",
    "ax.set_ylabel(\"2021 page views\")\n",
    "ax.set_ylim(0, 200)\n",
    "ax.set_xlim(0, \n",
    "            #1e-6,\n",
    "            7.5e-7,\n",
    "           )\n",
    "savefig(\"moth_gap_views_null_hypothesis.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4a4fd03e-fe3e-42d1-afa3-4f188615d884",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\nax.axline(xy1=(0, 3), xy2=(1.3265e-6, 256),\\n          color='red',\\n          dashes=(5,2),\\n         )\\n         \""
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qj1q7t3KxarPNqdq9FTF5irHcQKSHLHaCIIgqoRiehmr3VqSzymsxX7xaIcVOEARRRRRDoVWrUizGckMpZavW85Yv5IonCIIgykLMKlc0C7CyX1nQckMpqMaAw8VAip0gCIIoGx1KEZb3KHD0pLkqFGk9ru2TYicIgiDKBpvNwshk+RVpunGqPeCwEGiNnSAIgigblQiSy5ZGV+0Bh/lCir2KqadgDoIgiBjlVKS55vbX07OWXPFVSr0Fc5SaelgXI4haY7H920tx3FTj1JurPRtksVch1Vw9qhqhalUEUX5K9bsrxXHrzdWejawWu9frxcGDBwEAP/vZz3DXXXdhZmYm5wFcLheuuuoq6HQ6AMDTTz+Nq666Ctu2bcNdd92FQCAAAPjud7+LTZs2Yfv27di+fTuefPLJAqZTHzTiG2Y+JL7N12NEK0Gko1ru72L/7mL7l/L33EjP0ayK/a677sKbb76JDz74AD//+c/R0dGBe+65J6eDHzp0CNdddx0mJiYAACdPnsQTTzyBp556Cr/73e/AMAx+9atfAQAOHz6M//qv/8KLL76IF198EZ/5zGcKn1Ud0KEUYfPaLrJAk0heoqCXIKJRqKbluWL+7hLnRb/n4pBVsWu1WvzzP/8z/vSnP+HjH/84br31VthstpwO/swzz+Dee++FWq0GAPD5fNx3332QSCRgsVhYvnx53Po/fPgwfvjDH2Lbtm24//774ff7C59VnUA39XzSvc3TSxBR71SjZ6oYv7tU86Lf8+LJusYeDAYBALt27cKdd96JcDgMjye3N8YHH3xw3t+dnZ3o7OwEAFgsFjz55JP49re/DbfbjRUrVuDOO+9EZ2cnvvGNb+D73/8+br/99pwnolRKct62HlCppJUWoWwkznXNUBtGJi0Y7G2p22veqNe2EVjMfGvt3s91rrU2r3RU072cVbGvWbMGH/3oR8HhcLB27Vp89rOfxfnnn7+oQQ0GA770pS/hmmuuwTnnnAMA+OEPfxj//gtf+ALuvvvuvBS72exqGAtXpZLCZHJWWoyykDxXWRMH565Qg2EidXkOGvna1juLnW+57/3FBLHlM9d6+E2X+15ms1kZX4KyKvZ77rkHBw8exODgINhsNr74xS/i4osvLligEydO4Mtf/jL+/u//Hl/4whcAADMzM9i9ezeuvfZaAEAkEgGXSwH7RGoa5QWOIJIp171f7swc+k0Xl6xr7Js2bcIrr7yCI0eOgGEY/N3f/R3Y7MLS310uF774xS/in/7pn+JKHQCamprwyCOPQKvVIhKJ4Mknn8SWLVsKGiORaliHIgiiONDvOT8Wm2NeSBBbPV6jWpxTVg39m9/8BsuWLcMPf/hDbNq0Cd/85jexa9euggZ79tlnMTc3hx//+MfxtLbHHnsMLS0tuP/++/GVr3wFV1xxBSKRCD7/+c8XNEaMaoogJQhicdDvOT+Kcb7yDWKrx2tUq3NiRSKRnF7FXC4X3njjDTz22GOYnZ3FsWPHSi1bXiSusbPZLLx1QAeb0w+5VIDNa7vqytXTSGuTjTRXoLLzLXcJ41znWi+/53Jd20qcr+QxP7llqOZ/t/mcx2pbY89qsf+///f/cN111+HKK6/EX/7yF9xyyy14++23iylj0aFcSILIj2q2TOj3nB+VOF/JY9YDtXzfZY1Q+/3vfw+Xy4UdO3bgoosuwllnnQUWq/rXHBqthCDRWGSzrvOxvmuhhHG23zM1TJpPJZ5/xRqzmq5lreqRrBb7q6++iqeffhqtra340Y9+hC1btuC2224rh2yLptYuBtEYLDYYJ5t1na/1XSuWSTq5qtnbUEkSz1e5AsAWe+9U47Ws1t9DJnIKb5fJZJDL5ZBIJHkVqCEIYj6LfXBlq0BWaIWyWq32VY0V2aqNalSWqaBrWTyyKvbrr78+nvJ2/vnn43e/+x1+9KMflUM2oszQD6m0FOPBlc26Xoz1XYuWSa14GyoBm82qKWVJ17J4ZF1j/+IXv4gLL7wQAoGgHPIQJSC2ZpVp7Ypan5ae2IMrdp6Tr8WM2YM9IyZ0tYozXoNs6361ui5YKB1KEXo0EoRCDIDqWqOtFLHf82C3IuM9V2002r1bKrJa7GeeeSZuvfVWXH755TCbzfjiF78Io9FYDtmIIjBj9uBP7+sworWndcfV0lt9rZPO5R27BnZ3IKdrkO3B10gPxhmzB2/s00Jv9tSM27mUJP6eR04FQ9bSMksj3bulIqtiv//++3HppZdCIBCgubkZQ0ND2LlzZzlkIxZJ7AfuD4Sxd9gAuyu10iAXWHlJdX5j10Am5tM1yINEJTZpdGJMZ1v0C2qtv9im+j3T/dRYZFXs09PT+NSnPgU2mw0ej4c77rgDer2+HLIRiyT2AxfwOdgwpIFMkl5p1GrwVD3RoRRh64VL6BrkQaIS61VLMdAlX9QLar1Y/PR7bmyyrrGzWCwwDBP/2+VyzfubqG4S16xW9MozPuzorZ6oRZLXZQtdo11sPn+1re1XkyxEeclqsV922WX4l3/5FzidTjz11FP47Gc/iyuvvLIcshFFIvYDpx86UQoq7bpOVqiF3ueLWZKqlKVf6XNPVCdZLfabb74ZL7zwAhiGwe7du/HpT38an/zkJ8shG0EQVU6lsymKPX4hUdmVqtxX6XNPVC85NT2/+uqrcfXVV5dYFIIgaolcFFop3dOLUaiZ5MpX3mxpjKWgFsoAE5UjrWK/7rrr8Otf/xpr1qxJWRv+wIEDJRWMIIjqJpe8/FJalIUq1FLIVe7860q8TBC1Q1rF/thjjwEAXn755bIJQxBEbZFOoRVqUeZr4eerUEtp6ZZbuVIxFyIdaYPn1Go1AODrX/86/va3v6GlpQWdnZ3x/wiCIIDMefn5BKIVGoCWb9ncZLlqOQCNlDqRiqxR8bfccgt27dqFzZs345vf/CY+/PDDcshFEESNk08udTmrHybKVS956wSRSNbguYsuuggXXXQRHA4HXnrpJXzzm98EwzB48cUXyyEfQdQM1ZbHXA3kej6KuWacy3WIWeqVDP5LBd1DRDHIqW1rKBTC3/72N+zatQtmsxnnnXdeqeUiiJqCLL/FU4xqaflch2zLBeW+pnQPEcUiq8X+7//+7/jDH/6AoaEhXHvttXjsscfA5/PLIRtB1ATlTj2qZ6tusZZ6vtchOQAtsRNiOYL/kmV3uAKYMjopKI5YFFkVu0QiwdNPP43u7u5yyEMQNUc5U49qqShJuV9ACr0Ose2Sz22+x0psldqZp2JmmAgGuxUY1zswZ/NBZ3JX/fUlqpesiv32228vhxwEUdOUI/WoloqSVOoFpNDrkOrc5nOsRIt7XO/AqM6GgS55XnPvVIkxqrMhFApX/fUlqpuc1tgJgshOqR/CtdJeN1FJjums4HLZ874rNYWcl3TnNt/gP7VSBKvTD6vDt2DuuRxjsd3p8qWWU/2I9ORUUpYoLvW8RpqJRp13MSmWZ6DU12J5twJjOivaWiR4Y58Wg90KRIC4qzoCYM+ICV2t4qxWbbFkzXacxZ7b2P46kzs+9zf3a7GiTwm1rCmvYwClf1GspWUdIj9yep30+XwYGRlBJBKBz+crtUx1TaNGvjbqvEvBYh/4pbwWsWOzAFyyrht6sws2px+TRifGdLZ5/7a7A1lz1osla67HWey5ZZgIOpQiXLKuG7MWF0Jh4LU9U9Bbc5dfZ3KX/LdSzroBRPnJqtgPHjyISy+9FDfddBMMBgM2btxIdeILpFF/TI0672qklNci8dgjWus893avWhp3M8f+LRPzM7qcC5U1ebvFzrmQcxQKMVjRp4Te7EYkEsHIpDXnscrxW6mVZR2iMLIq9ocffhg//elPIZfL0dbWhocffhgPPvhgOWSrOxr1x9So865GSnktUh07lpverhQt+PfWC5dkdAEXqyxtpfqsq2VNuGR9F7rVEizvVuS0Tzl/K8WoG0BUJ1nX2H0+H5YtWxb/e+PGjXj00UdLKlQ9U87GDdW0pl1Is45qkb3eKOU9mOrYyf/O59oWEpmeKmugFH3Wc5lHu0KETmV+45bzGUG/sfokq8XO5XJht9vjrVvHx8dLLlS9U44fUyXWtLO5DfNpq0nr8aWllPdgpmMXcm3zjUxPZ+0W2mc91fHyrXCXL5mWJwgiG1kV+80334y///u/x+zsLL7+9a/juuuuw1e+8pVyyEYUSCXWtIuljJNlJ+qHclzbYruXUx2vUjEj9MJL5EpWV/zmzZuxdOlS/PWvfwXDMPjHf/zHea55ovooRSW0TG7HxRZOSTx2suy1BC0fZCaXa1uMc5ht/3zHSGX55/r7KmaqXjGLE9G9Wt9ktdj37t0Lo9GIgYEBDA4Owmaz4fDhw3C5XFkP7nK5cNVVV0Gn0wEAdu/ejW3btuGyyy6bt05/7NgxXHPNNbj88svxb//2bwiFQouYEgEU13LJZikUOzipFoN6yJrKjUzXthznsFhj5HKPFnM+xQyqo3u1/slqsX/729/G8PAwBgYGwGazMTo6CpVKBa/XiwcffBCXXnppyv0OHTqEnTt3YmJiAkA0CO/uu+/GL37xC7S3t+Omm27CO++8g40bN+KOO+7AAw88gLPPPht33303nnnmGVx//fVFnWgjUk5LodjBSbVkTdRSqddqINW5Kcc5TK6I16ORIBRictovlSzZLPXksRZLMYLq6F5tDLJa7B0dHfjJT36CF198Ec8//zx+/etfY+3atXjxxRfxve99L+1+zzzzDO69916o1WoAwAcffIDe3l50d3eDy+Vi27ZtePXVVzE9PQ2fz4ezzz4bAPCJT3wCr776anFmV2XkshZX6vW6fI+fj6VQzOCkWqJe5lFJFnsOc7mvY2MomgXxinjZrNZU1m2hYx3X2rLul8txF7s/3av1T1aLXavV4pxzzon/fdZZZ2FiYgJtbW0Z90vOdTcajVCpVPG/1Wo1DAbDgs9VKhUMBkPOE6gVcinfWOoSj4Uev9zpUbVIvcyjkhR6DvO5rzuUIvRoooo2m9WayrrVmdwFjzUyacG5K9QVv0foXq1/sip2LpeLXbt24cILLwQA7Nq1CzweDxaLJa+18Ehk4U3EYrHSfp4vSuXiXV2lZM+ICUEG0M25sXpIU/A2MVQqaUlkqEYKmWst00jzLcZcC7mv1wy1YUJvR1+7LOOzY81QG0YmLRjsbYFSKcHfjhkLGivxGI1CI93HQHXNN6tiv/fee3HbbbeBxWKBYRgIBAI8/vjj+NGPfoQdO3bkPJBGo8Hc3Fz8b6PRCLVaveBzk8kUd9/ng9nsqoo30HTWQ1erGB5vAF2tYphMzpT75rINEL2BMn2fjnTHL2cziFyicRO3KXSu5SafKONM2ybOt96bdBTr2mb63aQ71263HzaHD+7mpnn7JG8va+LErWyTyZnzbzSR2DGUSsmCfQq5xun2KVakezHuu1r53RaLcs+XzWZlfEnMqtjPOussvPnmmxgdHQWHw8HSpUvB4XAwNDSUlyCrV6/GyZMnMTk5ia6uLrz88su45ppr0NnZCYFAgP3792PdunV44YUXcPHFF+d17GphsZWvSu0iS3X8cgbTVMNyRCnIR+Zct6Ugp9xJ97vJpABTndt02ycet9DfaLECBvOVPV/ovqsPsip2i8WC3/3ud3C7o80MGIbB5OQk/vM//zOvgQQCAR566CHceuut8Pv92LhxI6644goAwHe+8x3s3LkTbrcbK1euxA033FDYbCpMtvzWXH4gpf4RLSYndzHk8sBItU21k8+DMJ9ty3VdciFfS5DLZecUbV5McrmX0tVKiJW5zefaFEvmfK/xYmUvhUxE9cGKpFrkTuCGG25AU1MTjh8/jvPPPx+7d+/GunXr8Mgjj5RLxpyoFlc8UPriD6Vw+5SjYEUhFnstuPSKabEnz7fShUTytQRHtHbsHTZgw5AGg92yjNuW+tpmkz353JbaW5RuvoVc41LLvtj7rhZ+t8Wk5lzxMzMzeOONN3Dfffdhx44duPXWW3HbbbcVVch6o1peMPKhHDJncmPGHiS1GLGbj8z5zq/QCn7FIJ0HJd0YXC4be4cN0BmjD7hV/YqiW+75eAOynevkzyt17xWjlnyxZa+l3x+xkKx57K2trQCAvr4+jI6OQqPRVGVlOGqOUBukemAk5wrH3IvZqKZrvpgSpYWQPPdSVBNLzHke7FZAZ3JnHCMUYrBhSIMutRQbhjSLUuqpru2I1o6f/mEYI1p71n1i/06OJ8l0/OTt85VvMRTjeKSMiRhZFbtSqcSPfvQjnHHGGXjuuefw1ltv5VROttzsPjxLJRJrkFQNNXJRUo1cFjN57qVsShIrndqpEuc0hkzEwxlLWiAT8QoeM9W1TfQG7B02gMtlp9xHb/ak3D/b94uVbzE08r1MlIasiv3+++8Hn8/H+vXrccYZZ+Dxxx/Hv/zLv5RDtrxwuMvbaYkoDsmVsABk7QBWqe5alYbNZqWce6mriTFMBAwTwWC3Am2tYgymGYPNZmFYa8XEjAPDBV6XdNc2kzcgcZ8pkxPHp23z9k/8ftLoxJjOVvC9U+x7r1HvZaK0ZF1jVyqV+MxnPoOjR49i27Zt+Jd/+ZeCCsiUmmaxAF0qCbmjapDE9cHkqNxUNGLkbiw4arBbkXLu5VgfjgDwB8JIN0IxrkumYwx2y1Ku28f2GdNZoZA0wWTzgsvlzNs/dsxetRQRoGAZi33vNeK9TJSerFHx+/btw+233w4OhwOGYcDj8fD9738fg4OD5ZIxJ6xWd9lTbCpFI0ScxoKkMs210hHjiyWV/Knmy2az8NYBHWxOP+RSATav7QJQ/DXVbK15k2WIbZu8X67XpVjXNrYtj8fB63un4HAFoFaKcP6qtrRyLebeSbV+nwv1fC8n0wjPqERqLir+gQcewIMPPhgvGvPWW2/h3nvvxVNPPVU8KYtALf8oyvWjXuw45ZIzMXUnU5nGQpRJtZBPelK63OVkFnMOssmTzrJMtV8mGXKVMZUCTvUCoTO5Maazoq1FglmLC+1KCQAXetTSefsly1Wq81QotXTvEtVP1jV2APMqwW3evBler7dkAjUa5QqcqbaAoXQkrzlWk2zFopB11cT+35mCwwo5B7nKk9yDPN955CtjpoC3GbMHu4/M4sCoCf5AGHuHDbA5A5i1uHDp+u64jHqzB3/5QI/f/XVi0fcHrYcTtUJWxT40NIRXXnkl/veuXbuwfPnykgrVKJTrQbHYccr5QEsVTJeLbA5XAFNGZ0bZquVBXGiwW6oqY+kC6vIlmzzprN5Ya9KV/cqslno+MqYLeBvTWcHjcTCqtcJo9kAhFaBJwMWGIQ1kEj4Guk6vwbPZLEwanRietOC4zoYxnW1R90CpgxQTqZZ7lahNsq6xb968GTMzM5DJZOByuTCbzRAIBGCz2WCxWDhw4EC5ZM1INVWey4dCXHuFrOcs1oVY7hruMbdrLnPVmz0Y1ztgdfqxdrkqpXzVWIM+1zX2ZFLNpdD5JQbldaYJvst2bL3Vg5HJ7GPnW1UwUbYIMM/l3tYigd7smid3qvOZy72RL4UueeT6u63GezVfaI29tCx6jf0Xv/hFUQUi5lOualeLHafcVblyGSf2gO1UiTGqsyEUCqeslV2tjS2KeS0KuT6J52VEa0Vnitr8yR6RVOd2ZDK3c5uvjMnb97ZJ8freKdicfgDApeu7EQox8e9THbddKYrPqxaqslXrvUrUFlkVe2dnZznkKAuFRu8udpxsFLsMaK4lNHPdL5f9y02yVTPQJc/YfKeaU4pi537G7MGeERO6WsU5BdSl+yyfALVU5yVx/1j++rjegTmbDzqTe0Hns3zObSHpZUD0eh+ftqJTFbVSEl3uuR6jFqj2e5WoDbIq9nohWRGUyt1VSTfaYt2xteL6S2XVZLMGq7UGfezcr+xXYlRrRZBBtN93gbLmey2Tz0uq/bN5RAo5t/m8xLDZLIzprAiFgb3DRmz5SDdU0qacx6o1qvVeJWqHnKLia51kRcDlsrMG8hSzalY5KHTsWoz0TRfEVGqPQynqg8fO/bEJMwZ7FZCJ+QVbaoVey0RLPdX+DBPBQJc8Y9AYw0QWlHnNJqfdHchJToaJYEWfEnqzG+EwgyMnzPF9yv0by/R3MSGlTiyGhlDsyYogFGIyRrcWmjpUzqjZYo1dSZkLIfYwTU69KjWJqVfFeqAnnvuBLgXaFSJsvXBJ3nOKRcYv9lpm2j92vrtSrMMD2Ru0pBonn5cYtawJl6zvQo9GEo/AL3WaY+J1TpVuV0splkRj0TCu+GT3Vjp312KDVyrpRit07Fpx/SW7icslb2IA2bjegVGdDQNd8qK8VCz23KeK+i5VkKTO5E7p5i+kXWuHUoTVQ5q8IonbFdExj540A6eWLkoVZJZ4r3UlNcDp0UgowI2oatIq9gceeCDjjjt37iy6MIslW9BQqqCqVPsXo951pSh07Gp/MJUyWjiX+2Z5twJakxNWZwBsRDCmK54M+UayJ7rOY3naTk8QUhEvZdR6oQFryeOmO/+hEIMNKzUAsOh2rZlIjMCPLV2MTlmxoi9zDn0h48TmOqaLKvLEZ0LM40cBbkS1klaxS6VS/PSnP8XnP/95sNnV77E32Lw4Mm4uWp42vYVXF6WKFs412KxDKQKHDTCMC8OTFpx/RnvZ749UHotetRThcARWpx8DXfJ5MhUzKDLT+Z8xe2Awu/DR8/rQIuEvapxcZYgtXQBRCz5UxMDP2DixvPk39mkx2K2YVx+fnhFENZNWsf/TP/0TTpw4AYVCgX/4h38op0wFcXLGUbA1lxxMV40/2FqrhV4Kiv0wzZajnbztyVknjp00wxMIY9bixopeedmuSTqLOV2edik8HLHznzhW4jgfHDeVrEFNsgwME8krhz4TqX5bHUoRejRRpZ4uz7/Rf49E9ZLRFP+3f/s32O3Zg2Gqgf6O5nlBP7kGOM2YPXhzvxbtSknZA8jykTE5UKcWotdLQT7XNpdjDXYroJQL4znambbtVUsx2NuCvrbmBdZxqckU2MYwkbS5+/ne09nOrc7knncvJo4z2K1Y8H0pSMyCWGzgZ6YguGxBtgRRrWQMntNoNLjlllvKJcui0MiF0JxyleXqgky0NoDTlazKQSEyxqyS41ob3h+erZm882JS7Jz7bDnaiZSiilk+LLZyWzayndt0XoBESz7W2rVcnq/FeHFy8WqQy52oRTJa7O+99x6ef/55zM3Nzfv8+eefL6lQhRKz5nLN5U1ONyqXUi9UxlhTlJFJS9Z969GiL0XOfbYc7eQxUlnH5aQYgXCJJOaDZzu3uXgNKmHhJi4L5Eo+6YGk1IlaI63F/pOf/ARPPfUUent78e1vfxuPP/44zj33XADAz3/+c3z84x8vm5D5kG+QVSXeyBcjI8NEMNjbAo83kHbfWqsklyulCqBLdw/U63mMkTy/XM5ttVb4y+daUaAsUe+kVezPPfccnnvuOUgkEvz5z3/G7bffjp/+9KcYHBxEloZwFSffH2stuFUTt1vWLYdCxM07LanaKCQgsFQP4mLXM6h2ci3LG7tG+Vyrcp+nfK5VvV9XggAyuOK5XC4kkmjDhYsvvhj/+q//iq985SuwWq1gsarfzVvsH2spXNuLkTGT27AWekYvpnJXPq7XWFW2Qsao5HkstKRxtn70iWVik3upJytvvdWDP72vw4jWHq+6l891K9dyUD7XqlLLBQRRTtJa7C0tLXjuuedw1VVXQSAQ4OMf/zhGRkZw4403wulsnD67QO25ZMvhXlzMOSmG1ZTL+IvtxV2p81jIuc0211TfdyhFYLGBYxNmWE/1N4+NabT78OY+HcRNXGiNbkiFPEwanfAHwjldt3L/ZvK5VuR+J+qdtBb7fffdh+eeew6vvPJK/LNvfOMbWL16Naanp8siXDWQb8BWMa2UxRyr2JW4kv9eTBDbYq2mXMZPrMp2XGfDmM5WsOVeDNLJmGoeqT7LZolnmmvi9ydn7NCaXHHrfWTSCn8gjL3DBthdgXiTpGMTZrQrxfAGwtiwUgOZhI9etXRBoGE+8yo1+VwrUupEPZPWYu/p6cGvfvWrBZ/v3LkTX/rSl0oqVKnJd70w14CtYlopi7WIF/PgStw/lRzFCGJbjNWUy/ixvPN0VdnKSbprmW4eyZ9luxeyzTX2PcNE4A8yMNt8mLV6oZY1xSusbRjSxC32UIjBQFf080vXd0Mta8KK7tPHjF23TPMa7FVgZLLw+4MKMhFE4WTMY3/11Vfxu9/9DrOzs+BwOGhra8Oll16K7du3l0u+olOIwsxFCRUzKGcxx1rsy0Wm5he5NNHJh8Xsm8v4lc47B7Jfy1TzSK6ulsu9kG2u7UoRujUSvHVABwGfg9f2TOGS9V3zxkqspJcsV/KLQia5ZswejOmiPebVsvz7ptfa0hdBVBtpXfHf/e538eSTT2LLli2444478PWvfx2XXHIJnnvuOTzyyCPllLFoLMZFmE0xFMO9vNhjLdYFmrw/gIxyVNqiymX8VHnn5czxz+VapvssZrUO9bbkHBiW6ftQiMFQbwv0ZjcikQhGJq3zLON8Xdmp5hW7h6wOP46eNKc915k+r4QbnyDqCVYkTe7a5Zdfjpdeegl8/vymDoFAANu2bcMf//jHsgiYK2azK6cHU6mtgUJciOlkSncslUqatt1lMS322P6VdItmmmshVMoazPUcxuY7Y/bg+LQVMokQR06acd6qNvS3SYsii97qibvJ052DfCoj5pv/H/t+zVAbZE2cgseuNYp9L1czjTRXoPzzZbNZUColab9P64pns9kp89XD4TB4PF5xpKsApY6IXWwgWDr3Z2zbbMcvZH6Jx03V6KPSlnmxKFUOc3Ir1Vyt8nRwuexoAByLhd2H9XA4/WCYCAa6ZEWpjtiuEKFTubhc79g8Ux0j0z2YeOyRSQvOXaFesB1FrRPE4kir2Ldv347rrrsOV111Fdra2gAAJpMJL730Ej72sY8VPOBvfvMb/PKXv4z/rdPpsH37dni9Xuzfvx9CoRAAcMstt2DLli0Fj5OJQpVeqWTJJRAt0YpRqaQZZctH3lTWkc7kxqjWisFuBTpr5AGby3UqJOgv+bjJf8fO32C3AhFg0Zbmca0NR06YwEQAry+M889ox4cn5orS5zyT2z35u0znKReLOt25TTz2YG9Lxu0IgiiMtK54AHjnnXfwxhtvQK/XIxKJoL29HZdccgk2bdpUlMHHxsbw1a9+FU899RQ++9nP4oknnoBarS7oWLm64vOhnC7BTIqJzWbFm2vIpQJ8cssQDg0bFi1b8nFjLTffOqCDwxWAUi5EKMxgoEteMZdoLi6ufK9Tri9rycdN/jvx/LW1iuEPhGF1+OLnshDvzfsnzNh3dBYeXwgfWdWG81ZqwGazFq3UM52jfJaCUt0zhUa9K5USctfWKY00V6CGXPEAsHHjRlxwwQXgcudvZrfbIZPJFi3cfffdh9tvvx1NTU2YmZnBPffcg5mZGWzZsgW33HIL2OyMPWpKSrlLT2YLikq0oACkla0YqXzLuxWYMjoxZ/Pl1PWsUIrhDSnkOqVzESdb5onH7dFIFowDnE5N61VL51nsyWNwueysyplhIuhrl8HlDsDq9KNbJckrcDJ2jGxzSb5fsi0F5WPN5wpZ5ARROtJqzsOHD2PTpk1Ys2YNvva1r8HlcsW/+9znPrfogXfv3g2fz4crr7wSZrMZ5557Lr71rW/hmWeewb59+/Dss88ueozFsNgo92LToRRh89quuEWVSrZCyrQmHzf22fmr2rB2uapk819MSdlEinGdUsmSfNzE3tyJfcdZADav7UL7qUpuyecSAEa0dvz0D8MY0dqzyrKsW46LzmrHxy7oi3sJsp0nvdmDv3ygx8u7J+PlXzPNJTl1LdP5SzV+unkSBFEdpHXFX3fddbj55ptxxhln4Nvf/jZ0Oh1+/vOfg8/n4+qrr8YLL7ywqIFvu+02XHbZZbjqqqsWfPf666/jhRdewPe+971FjdFo/H7XOOzuAGRiPrZeuKTS4mSkmmQtRJZ89vl/z7yPGZMbHSoxbv3UmqLL9saeSRwcmwMLAJ/HhlImLNp5rabrRBBEbqR1xft8PmzcuBEA8J3vfAe33XYb7rrrLvznf/7nogcNBALYu3cvHnroIQDAyMgIJiYmcPnllwMAIpHIAvd/Nkqxxl4tJK+BplvP6WoVw+MNoKtVnHa9pxKpa6lcw7nICuS+dlXoujmQ23lLJp991ixTIRRisGaZKp7KliqlEMCCdedM48QKwbQrJVjW0Qy7K4ClnTLoza4F26c7P9nOW6rxY+Ou6CusAE0Muy+M94dnix4bUa000rpzI80VqKE1doZhYDaboVQqAQD/8R//gR07duB73/veoru7jYyMoK+vDyJR9McciUTwrW99C+eeey5EIhGefvrpqu33Xm5SrYGmI1uaUCXyg9MFoA12KwoOvMo2RjrSrScXkl6Vzz6D3TKs6o+681PJMG1yxxu0XLSma15ud7pxEo8DAJes646nnyVWkMt0fnI5b8njs9ksjOmsCIURr17Xrsj/XorWqbfkHBtRr7ntBFEK0q6xf+ELX8DVV1+Nd955BwAgFArx3//933juuecwOjq6qEG1Wm08hQ4AhoaGcOONN+K6667D1q1bsWLFipQu+lJRzdWtYmugie01s22fikpU9Eoek8tln85hPlXZbjHHTjVGpnllW2vOZ9zEfXJp1BJT6skyAJjXwGVk0rKg/Wo62WLHGeiKvjRkyxtPbipTyP3AMBGs6FMuqF6XatxsxxnMsaIeVaMjiPzImO528uRJ8Pl8dHZ2xj+z2+349a9/jZtvvrksAuZKoa74WrEEEquFrR7SFOT2qSaLPVcZUrm4FnvMQl266VqsjumsaEtqe5pt30QZEluqXrSmC263P6fKbanqDOTTBjaX85Zum0zV63K9HiqVtGoqRpaDRnJPN9JcgRpyxQNAf3//gs9kMlnVKfVCKXdKW6HE2mvG5Fw9pCnoOF0qcdnnmOzKXWxlvFTXLN9jFpp3nWpJZFRrRSAYbXsqFfJS3kfZ7rPEBi5KpQS/eX0YDlcAU0ZnxmONaK3x/TKNk+78ZDtvmeROV70u399UrteCqtERRO5ULlG8CqhkSlu+DWiS3bf5Ektb0pncRZMrl/1TWcf5nOfjWtu8dKt016zU1y7VkkjssyYBB+ec6lmerllOLo1gYp8PdiuglAsxZ/MtuF6Fpq4VUuGtkN9HKX9TpNQJIjfyCz2vQyphCZSqdWw6crWiit1AZrHHSxdgVSnrrUMpAosNHD1pRujUnGKfjU5lblOaj8ydKjFGdba0xYEyHavY5ybd8TJdW7KuCaKyNLTFHqPclnqhgUCLqfKVzYoqdsvXxEC5QgOeMgVY5XIuCvU+ZGopmrgkEgtyG5nM3qY0ncyptmeYCAa65PFiOPnKWexzk83dnm4OBEFUBlLsaShG5G26B14l3P/J1cKSZcs3+j6ZTJXacol6TseybnlBVc6yVWxLN6be7MHuI7PQp9jv9Dlqis9pMdczWcZEmWLXKwLgT+/rYLL74t8nVpoz2n05j5du3Bj5RMYnz5ki1Qmiemh4V3wqihGBW42uysTSs6lkS+VqzodCAuUW0yksHdmWHjI1PRnXOzA8aUE4HEnZ2Y4FQMDnIFGNFRoQGJNxTGcFiw2MTC7sUT6ms4JhgL0jRkQiEWwY0mDS6MSo1gqpmJ93Lnm6c5PvPZ8453qIWCeIeoIs9iRiDz67K5DSzZiLZVLNrspMsqVyNedLpkC55PzsaLETW9HzkzNZlNmujc3th9MThPVU4ZdE2GwWRrRWzM65MZLgik8173xkXNGnxOhUNLp+dMoy75gr+pSwuQOY1DswNmXD8KQFfW1SnLW0FU53ECwWMGVwgsvN7accXd5YeG4KuQ6xfSnHnCCqC1LsSTBMBO1KCZzeINqVkgWWXi6NSyoZbZ+NQqOqF0vMffy7v07Ez9+0yQ0uhw0ul5O2Acnvd40X1Cgmcekh8bplmuO0yQ25RIDlvQqsXa7KGN2e2Aim0EY2MRnVsia0tUhgtPmglAnnjauWNeG8VRqctbQVy7rkWNYpR5tChA1Dalx5bg/625vh8YXxwl9O5iTHjNkTD/SLWdfZrkMmqvleJ4hGhVzxSbDZLMxaXFDLmzBrccXLc+abn1vNkcHljKrmctlgmEi8uprTE4RUxEOPRoIRrRUOVwDqFGPGzneQQbRWeZqyqtnStZKt0XR57zFr3OEKQNMqQo9GkrLNamxfAPjT+9M53Q+JLVtTycxms6A3uyAV8jBn82JZu3TeNm0KETqU4vicYv/vUIoxaXBhfOL0ec01L/3YhBkdp8rQZroOuVDN9zpROLVem7+RIYv9FInuz4EuBfg8Dga65udJF5LTm228XOUqNtkUYjGItSsdnrKhVy3FUG8LlnXJMdAljwfXNUv46FFLF4wZO98ycerc8BmzB396X5c1eGza5AaPy0azJGplp8t7j48n5UMubsIb+7TzLODkEq+5WrmxczCqsy/w+MT+nja5T91bfKxckjpwMTHPPfGzHpUEQ32nz2sueemKZgHaWiR4Y582Pna665ArpADqi2K1VSYqA1nsWBhMVWilrkLHW+x21QiXy8beYQN0xmiZxc9dORSvkpZrcF2HUpSyfG6ujUjYbBZGdVaEGMBo9WJFX+biPh3KqKX+xj7tPEtcZ3IvKAebi5WbeA7EQh6UzYL4cXs0knkV5Dav7YoGLo6b0dUqzut6czksnLNSA1UOndaS5xgbmyxuIkatVOQk0tPwFnu64J90N/Jib/Bcg43yDUoqpBFHKQmFGGwY0qCnrRkXnNkeb1KS7P4u5HwyTAQr+5Qw2rxAhkYkseAz/ZwboVA45XbJfyen6QFIeR1ysXJj56BLLcWqvhYMdMrRrpJgMEU6IBCNire7UwdtpiL2gqE3uXF0wpw1gC52zFSpiNmuAwXFNQ4UN1H7ZGwCU0ssph97uS3jxVjsM2YPdHPueVZdPo0/ys2s1YvhSUvBDUiS5xpDb/ZgfNYBq8OPtctVGeeYrmFJJhkSXzoSm65EgLQNWNIRW2Mf0dpxYMyEtQMqDHbLUo6Tbr7pKLQJTfLY2cYoxb1EjUKqm8WssdfaXBdLTTWBqRey3aDlDv7JdbxUvbCTA8oALHCbpfqsEm/dbDYLI1MWBIJhjOlOy5GLqy9T8FyurvAYiQ1LYvdCNhkS/50YMPf2weloWppufgOWdPNnmAhCIWaeWz4cZuL92ZPHSVx6yOXBmm75IFUgYvL3udwT5JZtXOg61y515YpP5S7MJ0WtnOQ6Xqp0tMSAslRus2K70goN9GOYSDyNq63ldOpgLvKlC56LKbt8A74YJpJT2ltivvuC/U1u8HlcGKyn55PO/Z183+kMLiztlEPTIsaGIU3KiPvEMfMJXspW5W8x9wO5ZQmi9qgbi91g8+LIuHmBq7HerI1UAWWpPADVEOiXmMalN59OHcxVvuS5Jo+Rz/xyafeaya3NZrMwaXJiVGvH1KwDaoUQYAN7jxqwYUgTd62nGqtHI8Gw1gqXO4g1y1vnnYcYsZ7sLl8IawZa875vcwlELPR+oHQ2gqgt6sZiPznjSBkAVwnLtRKks3rzJbGaWq6NXLhcNsZ00cppx6et86zY5d2KjO1M85FrMRXO0t0Lycsc/kC0t3pi5cGYl2BJuwyt8iYoZU3oVImx92jUtb532DBvzsljhUIMBrsVaG0RQiMXLXCTs9mseJ7/cV20ulxydbhc57iY71NRaGU9giAqR91Y7P0dzfD4ggsehOWwXMtVyKHU48SsRrsrgKWdMsxaXGg/FaCRTsHMmD04Pm2FXCrEkZNmrOpX4s392rjVO9itwOa1XTlFXSe7w1MtQ8QC15JT0JKPkYpM90Ls+GM6KzYMaeKyJ4+zdqAVLVIBVNImbBjSgM1m4bxVbQtc68ljRQD4A2EkjpwYlNerliIcjsDlC2FZp3xeXEC6uZX6fqiWAEyCIPKjbhS7Ri6EJo0CKXaKWrL7thwPv8RxVCpp0Y+faDWyWCxYnD5IhTwALly6vjvtmvCoNmqpTxnm0NYixIcn5qBRCLF32ACpkIcRbfYgs0QFBwDjegeszmi0e+JcE4PY3jqgy5hrno5cFf+KXnnKcWJV4BgmAo0SkEn4GJ60QMDjLBg32RuQLsAxlkveqRJDqZTElx4y3WOlvu/qcRmLIBqFunHFA6n7RhfruOkCrUrVACPxWMku8VTbLBaGiUSrw/W1oEMlwYYhTdSF3pXeFRw7LwI+BxuGNOBx2dgwpAGfxz69fw4tW2NzmzI5oZ1zxV3SYzpbyjGTrweQOtc8dvx8z0Py/JIbpsT+z2azMDxpyXr9cw1wTHWeUt1j5Wi8QkFzBFG71G0eeyksmlSuz1KMk5w3nRzQtXpIg0PDhpJYbLNWDyZmnehTS9GRoyWcqOxS/T+X+Y7prGhXSjBn98IfZOD2BrF2uSpl5bnkcWPHKJZVm7xfbJzk4LrEvPZcxsjFnZ4qH7aSdQpK6e6nXOf6pZHmClAee1kolRsx1TFK0TQl1rRk0uiEPxCG1RFtIZroEi9kftke0lELNHpcnz+EroSyp5nGSQ5ES/5/NhJzsWNNWLas70rp/k81buwYqXL+CzlHo6dy5KeMzgW594FgeN4yQz7lWFOtl+eyXymzHrJBljpB1B515YqPUQo3YiZ3Z7EefrNWD/58aAZMBOByOehVSzHQJYdcKsBAVzS6esbswSt/HUe7UpLT/GJy55IXnXjeYg1TyuGOZbNZ8VxsmZSP/nZZVqWeroRsItlkT3eMwW4FlAohLE4/dCZ3/PPEZYdcy7Emj1Foc41SxI4QBFGf1KXFDhTXoimH29No9+HdIwbMmt0IhRh8ZFVbvGRpstUYq8aWLqgtWe6V/cqcrdfYeYv1Gs81qr1Qks8tiw0cPWlG+JSbe8+IaUGJ1WzXI3EpI53smY7RqRLjwHETxqZsYMIRdF3QB4aJxM/NtMkNq4uDbCvbqVz6FJBGEESpqUuLPUahD83k4KvFBCpl2j6xytmxCTPkYj76O5qxrEeObtX8Sm2JFddkYn7cgs90zJjcxybMeedFJ0Zsl4rkc8vlsjGmPb0MMaazLWiKkul6JAeWJcqevF1suWNMFx03+TrJxQJIRTwopIIFco/qrHC4/BjVnQ5mSyZVDYDY9VM0N1FAGkEQJaOuFXshJLtKF+OOzuR2TS5vOtClAIcDLOuUQSERzLMGE7ftUIqw9cIlaS3VVCVTB7oUaFeIsHltV04eh3K54BPHGepW4OiEFS5fCBGw4ssQySVl08m2sLf56e+Tr0Oslzqfx0W7UoJ3Ds7gd3+dmHfNl7Q3Y9USJZa0Ny+IlI+VyW1XSuKejcRrPGP24M392pTLJSwAAn52a58gCKJQ6tYVXwjp8o0LcesnWoXJbtd05U0Tm3n4/KF4/nesqluskUqusifLnanYSTLZ5pzuGMmfJ/8d63SWPA6bzcJP/zAMo8WNVUtb0a2RIBRiFkTFs9msBbIlWsfJAW2pyruO6mywO/3o7ZDC5vZjeNICpycIqYgX369dKYrLkDw/vdkFmYgPjz8IvdmdNj8dmB/wGGtek3h9yWonCKLYkMWeQHLwWKI1lu8DOGYVcrmclFZvKqszVnq0rVUcD15LtBATG6mkIlPJ1Bh6qwd/en86a/BWutQsIL0nIvnz5L9HtHb89A/DGNHa5+3HMNEOaB9ZocFQvxIebwhTBtcCmWLH0+dgHaey8Ie6FdCZXPHrIuTzEAoxWNIpx7IuOQa6Ttdw11s9eGOfdsEcGSaCoV4FWmRNmDF50NYiXjBubNkjebkkX09INZcwJgiieiGLPYlM1c1yVe6Z2opmC+xKLj2aqpFKMrkEiwGAye7Dnw5MQ2d0wekJxoPC0h0vVd50ukC8lJZxwt+9bdJ421IA8baliQz1yDFrcSPgD82zgGPnIZaGNq53YFRnw4q+lrTWcSKxazpr9eK1PVNgsYBV/S3Qm92wO/0L0uuMdh/e3KdDrMRD8vXTmpywewIIBEOYtcyvzBfLdV/Zr4Ra1pRWlmz3EpVzJQiiUMhiT0G6ymD57J+qrWi6wK4Yse+tDt+CgKt0VdyyHTNxu3G9HVIRDzwuC4rmhUFhycdLVelseNKMod6WlJ6BTKlywWAYG4Y06FJL07YtZZgIlnXKU57z2PHUShGsTj+sDt/8oMAMFfJiHJswo10pRiQCtLWIMNAlR7OEj26VFKEQM6+aXHurGCwWC4O9CysNGuY8kIn4UDQ3zbPKT18/P46eNC+wuHNtqFKOynIEQdQvdVt5rlgspvJWcmOTWCDXmM6KFX2pLbp0llrisZKrHOXaoGbW6sH4jAO+QBgrehRoT2MJprPYj0/boFGIYbC6cMYSFVok/AVjAYhXqxvsVixYR05eY0/cL1UMQPJcuVw2tCYXRqesWNmnhEYhBJvNwpTBNW/MWG58tnOf/F1HqwRz9qhC3Xh2x7zgOTablXFuma5FrhZ4bL6NYLFTdbL6pZHmClDluZpjMS8Lye735FztUIqHdjpXbSY50u2TqjRtTBnmezwWgGYxH+PTdvD5HLzy7gQuWd+FdkV6V32qBjDJSj3WUS7W9KVDKUorW2xbpzuIZd3NGNPZcPikBZFIBB5fCEyYwYTBgQmjC8MTFlxwZjskQt68c588r8RlhEAwjMMnLbA5fWCxWJgxuzE568TyLnm8dGzickcqOVONUUj+OvVAJwiiUCqi2G+44QaYzWZwudHh77//fkxNTeG///u/EQwG8bnPfQ6f+cxnCj5+udqo5kKqteeRycwP+UJkz+SinzKdLk175KQZGkVXXsdLjBnoVEtwbNKKSCSCkUkrOpWxyH3bvJz5kUlrTlXxYh3lkqPSU0XXTxqdGJm0gMPlwB8OIxRiMGVwgMdhY82gGlwOGwwTwYERA4wWLxTNArRIBTmVxI21bO1rl8Fk88IfDMNi9yMUCsdL+9qc0dz1bo0krYypFH7s+LEXjFyvb7XcwwRB1BZlV+yRSATj4+N4++2344rdYDDg9ttvx29/+1vw+Xzs2LED55xzDpYtW5b38avNhZn8UI+VTs33IV/ouGM6KxSSJphs3rQR+vnMoVMpRodKPE9x682eeKR5LGc+sZd4puPG+pBbnf54VHpis5XEynN9aikiERaOT9vQo5HAYPHizKUq+PwhLGlrRqdKDL3JDRabhf3DRizpkKG1uQmjTPZznWghD/XIAZxeUuhVS+c140nsNx+7z7Ldd7lY4DNmT8pKewRBEPlQdsU+Pj4OFouFL3/5yzCbzfjUpz4FsViMc889F3K5HABw+eWX49VXX8Utt9yS17HTNfCoNLEc9ZgbOh8362K8D8nNVZIj9HMdI1XueExxc7nsuDWvaT09z1QWbfJYbDYL7UpR3F2f7BbfP2pET1szjk9HPR3dbVKMTtvQp5Hg6ElLNIBNyscVH+mOW8rtKjFGpm1Y3iWD1eHF2UuV8ej6XF40Ev+fmCHBMJH4uUxsBJMqAyBbs5x05yKxXHC13LsEQdQeZY+KdzgcOO+88/C9730PP/3pT/HUU09hZmYGKpUqvo1arYbBYMj72AxzuoHHnM0Xb+BRLtJFL8+YF+ZE5/LQzqdhSLqxY7nxmlYxehMi9HMdI7maXaL8iTnkMikfcnET3tinhd7sSXlcvdmD3UdmMZv0fXLe+WCvAk0CDlb1KzEz54KiWYi/fDCLH79yDEqZEBFE8JEVGkhEPPSopJgyuOYda1mnHDwuGwOnIuVTVYfLlcR9Y96WWCOYWKZC7PN8MijSVThMrrRHEASRL2W32NesWYM1a9YAAEQiEa699lp8+9vfxs033zxvOxYrvxSfWISgK8hAf1iPMAPo5txYPaQpjuBZOK61YWTSgsHeFizrls/7bs+ICcEC5Mm0n0olzWlsABg3uKA1OKFSiObtl4tsmb7fM2JCIAw4vAFce+kQfr9rHEEGMDp88AfCC/bbM2LCiNYOYRMv5fexuehMbmxY1YEPj8+ho1UCo82LMa0dIj4H7x01YPP6bpisHqxf1Y7+Dll83NixVCrpvGMWev5T7Zt87BjpPs/1uPFj5CVd7ZN8P9Y7jTTfRporUF3zLbti37dvH4LBIM477zwA0TX3zs5OzM3NxbcxGo1Qq9V5HddsjlYq239UD4W0CXqzG91qcVlSENhsFt4fnoXN6YfHG4BCxJ1ncXW1iqPu1daoPLm615P3i5GYWpFqbOC0R4DLZWP3BzPQGZ3wBcJY3tk8LzI9m2zpZIh95/UF0KuJyhP7u6NFhDDDYGKWQXfCceesXoRDYeiNbqxeroRncv5xk+eyvEeB6Tk32lskaJE04b2js+hSS7Dr4DSkQh7cngCaBZyMMrLZrIzfZ6NbLV4gZzHI5drWO400V6Cx5ttIcwUo3Q1OpxOPP/44nnrqKQSDQTz//PN45JFHcMcdd8BisUAoFOK1117Dv//7v+d9bIaJNlMZ01lx2Ud6UuaJl4JsUc+J69P5BPflshafOHasDG7i8UMhBhtOWYSpCsNkky2TDKlS99jsaIR8IMTA4w+hRy2Ny7m0UwaL04f+juaUAXaJc4kF4YmEAhwcmcXKPiVE67qwf9iIM5e2wurwxs91Lul+hbSezVZFbjFQOhtBEKWi7Ip906ZNOHToEK6++mowDIPrr78e69atw+23344bbrgBwWAQ1157Lc4666yCjl+pB2a2cRMDw/LJZ85lHtnK4A52y7Cqf34N9Vxly+RdYLNZ8TarsSCySYMTerMbUwYn2CwWxAJuXLZ0pXETx0g8j2w2CyOTFtidAUzPuWB3BSAWcGFzeheUj02X7udwBTBpdC7Ip89GrIlPrIpcWwl60pNSJwiiFFQkj/1rX/savva1r837bNu2bdi2bVtRjp9Lyc5SPFRzUdKD3QpMGp0pA9lSkYusiZXb0nkOtCZXPEUtalmz0lrLie1OM1XBG5m2IRCOgMVmY2W/EqEQA4WkCVZnIJ6GlthYJdGzMG1yQzvnhELShJk514JKfLExBntbEAyGMWPyYGmnDJFIJG0v+uRzMtitwLjeEQ+kzCeFLFsTn0zjpsptr1aqXT6CIPKn4SrPVTrPPbnJSyZykTVV5bZkT0BiUxMWC2CxMU/Jx0i2llNZ8DH39LJOOY6MWzE+bcM5q9owPGkBelswM+dCMBCGQhlNQ0vVohUAdn2ohzcQwsHjZnSpJHhtzxQuXd+FCIN581k9pMHBEUPKhivpGNHasXfYgAvPakcozCAUCufVyCdTE59MJF+vSt9r2ah2+QiCKIyGaQKT3MykEs01UjV5ybZtsqyJ+yRWbjuus2FMZ1uQGx1tamJGj0YCFouFlUuU8cp3YzoruFz2vOMmut8HexVQNAuwsl85T9n7A2EcOD4Hty8IhgGOTVhgdZyuOtcs4WFJuyy+TyIx2XyBMI6Mm9GhlEBrdEEq4sFg9WDK5Jo3HwBY3iVHW6sYy3Ow1LlcdryL3O7Dsxjqmd8GNxdi3ovkJj6ZSL5eiT3iq7GRS6V/CwRBlI66sdgNNi9UzakDnBKDqMpR9S0d+ZQWzeQaXzPUBlkTJ23lNuD0nIe6FdAoJNg/asQFZ7ZDJW2KV6RLrqKWWFO+rUUCg9WFjlbJvOC4eOlVpQRzDi/Usib0aJqhN7viAW8sIF7H3e0Nxj0JiXPrUkkQCDEIByO44Mw2TBlcmJhxYUWfAkO9LfH5APl5ORKDBdcPqhFmIjnvm0i+sRqVqjBYKIWWuSUIovqpG8V+csYBjXxhc5Pktqab13bNe2Dns8aYbtt8jpGPwkjlGne5g9DPuaDoiSrx5MptMXnGdNHqbZOn6sSrZE2YMjiwtKMZXSoxetukeGOfFv5AtIqaQiyAze2H0eqNf6ZRCPHe0dMV1rpU4nlV9IbY8ngXtRW98ricE7NOaI1OzMy5wWax5tWAj8k3a3FB0sSBtJUPtzcEvSnaI17RzF/QZCXfaoKJwYKpgglzJV9ll3xtqz3yvdrlIwiiMOrGFd/f0ZzyARWzTBKrgiVatblWJEu3bT7HSJQpFancoYmu8aFuBZQKEd47Motjk7Z52yQfs61FAqPNhxZp06lWq150qiTQmz3Y9aEeb+7XgsNhIxwGzlmpgVIhxIHROSiam9Ak4GLDkAZ8HntehbWY1+CNfVrMmj2YNrvjFfUSK8f1qqXoVktx9oAaSzvl8zwJsW00SgkmZl0Q8njoUUkw1NuCZV1yLOuUx0vSxhjqVUApz62aYOwcxo6Rb0W4bNcjG8ljVLvSrHb5CILIn7qx2DM9ghfbSjNTKli+6WvpyKWPd49GgjcO6GC2+7B32IBV/QvXnGfMHkwZnTDbfJAKeTCfqgKnEAvg9ITwt6MGIAI0CTiYMblwwVkdWNnXgp+9OowTOitU8ibIpQLIRDys6I1azonWeMx6nja7413eAMybe6IXAVioPIx2H/YeNYDFAmbmXNi8tmuB1yHGca0NkwYn7J5A1iC4fPPwC7keBEEQ1U7dWOzjM46MFlYqSypXay7dtrkeI5vllylQLvFzholgw5AGHSrxvGIzydsbzR7IpQLIpQL0qqUY6JKjUyPGByfmwOey0aYUw+sPwxdgoJ/zIBKJoF0pRqdaAoPVC73JjWGtdd78Y16D5d0KqJUiGCxetLeKweVyMNi7cO4xL0JyAB2bzcKxCTPaW8Vgs9nxfVN5HWJ57IY5D2QiPlpkTfFAvnTn0O4KxM9hYkBgPsRy2CmwjCCIWqRuLPZ0rvhMFLrenenz5Ojy5EpwiST2704VyJTq88FuGS5c2xUvX5hsWca2X9IebWMaO1aXSgwhn4f9o0Ys727GGf0tGNVasaK35ZSbXw6xkAuZSBBvR5ociBcbo0slxrTJjZOzDmgUQoCZP5/Ef8+aPZi1edAuF6H9lDzLuxSYMDjQ1yYFm0kfozBjdoPFAiRiPpa1N4NJqnKXSDTeQAKdyYAVfS0Zz3s2Cs1hJwiCqAbqRrGnCpzLhWIEU8U+j+WU210BLO2UweryYc7mS+lCTlaWub44JJJqKSBx++R17VhQ2ZTBhVGtBR2tEoxqbXjvqAHrlqtw7grNPNd7ujEYJoJOlRijOhscLj9GdVbgVG58LLJ+VGvFqn4lThpcODRmxNmDagzrbBjokqNLJcb4rAOjUxYArPjniQrYaPfhrQPTaJWLYLZ7ceYyJY6dMKdd9ogF5KnlTbC6fNCb3QUtkRSaw04QBFEt1I0rvtKw2SxMmZw4Pm3DrNWNvcMGmCxeKKQCKJqb5ll+6Vzv2V4cUrmE0y0RpILLZYNhIhjVWuHzh/HhuCWeMz56Kmc8ef9MyxADXXLIpQKs6DudG6+dc+L4tB02px8zZheGpyywuQPYP2yE3XV6vlaHH5EIMDxpSbkEcWzCjL62ZkzM2BEOh3F0PJojn27ZIyqPAnweBz0qaVy2fC3u2HzzyWEnCIKoJurGYq80DBOBQtIElUKEYIDBUK8CerNrgUs8tm2+OcSJFr5KJc27wUmsGttHVmhO56K3y2CyeRfkwCeTizch1K3A8Wkrmvg8zNldiIAFjUyE81e1Y/+oEav6lfHGLaEQg7XLVTg+bYNGIV7g+o8p6ePTVlx2bi8mpm3xHPnkxjGZ5CzU2qY0MIIgapm6U+zprN/YOu5ia2NnymWfmXMhHGSgUQqxolced2mn2j7T2nzycWPBXLHAsNVDmnm5+bGI8nSyJVZjA4DPXTl0Ohe9R55y3GSS186TP+9QitDbJsVP/3AMJqsHve0ydGkkaAsx8ej9xH27VOL4/BNd/8nnR6mUYIlGktUbkSxPLtvmehyCIIhaoq4Ue6q66cDp9puxCmuJjVCA1A/xVEoyUwpUNABNgVmbB21yERgmEnd9pztmbButwbVAbjabFQ9QC4UZcDlsWJx+DPW2AMApq9uG5aeqs6WSLTE4b8OQBmw2Cxec2QatyYXRqdPr2oku8FjBmVRkmj+bzcL0rBMD3XLYXAEs6ZDFjxP7f7r4gmxLEKRkCYIgcqduFHti3XSnJxivdgZEA7kCwWg1NamQhzGdFWw2cGJ64UsAkF5JZstZt3uCODxugXglD/ZTru8NQxoMdstSHnNEa8fRSQtEAi50RiecniCaxTyw2MDkrBMeXwgmmwcubxBubxASER8Ga7RACwvRXHSHJ4jJI7MLgvR0Jve8l5kV3QpcsrYL03MuHJmwQj/nhtsbAovditEpKzpaJZiz+zE8acH5Z7RjsFu24Pymm/+M2QOtyYlIhIWDY0bIRHzYXb6UL0fFzP0nCIIgFlI3ip1h0tdNj60pbxjSRJVcnxLjM/YFLwExV30qxZNtXTzR3a1SCDFn88Zd32csaVlwTA4nur1+zoUzl6mwor8FFnvUIj960gyHK4BWhRDdGimCIQaRCODyBLGsUw4AGDn1sjKmtcdzvENhJl5ffVRrRTDExF9mThqdUava6IJQwAGPy0JbqxBjWhuCQQaTRhdGJiyYmXNDLhWk7N++vFuBEzNWrF6mmZefPqazIRgMY87pR6tcCKc7iIHu1Gv2hcQXEARBELlTN4odQMq66cD89ezYem44xKR8CcikeDIFVekMLiztlCMYYrCkvRl9mmZEIsCGIQ2CwfC8XuQ6kxvHp604c2krAGBJe/O8te7QqW3726KBdzNmNyYNTqzqa4HqVM/y5JeVxCC9WE73/lEjzlzaCqvDiz61FA5vEJYmP/hcNlqbmyBp4sPnDyPCA1gsYM1yFXrbmhEOR3DkpHVeY5hRrRUruxVolgrx6zdHsWFIDafbj3alBFwOG25vCGuWqWCwunHx6s55vdWToeA0giCI0lFXih3InjIW+3+nSjzvJSDRbZxJ8aRyLQPA8KkGLWuWt2LwlLWaWPI1sRd5rDEJAHz+oysQDIYzvkAMn0ol8/lDuGRd94JtYuMkWtGxnG6H24stG3oQiUTw5n4tBBxAKRdg3XINXt87hVCIgcnhh0TARU+HBKFwBD5/EHuHDWgW8TBpjDaRsbsCsHj8ePcDPcx2L3YdmsGq/hbsOWaATMSHqmV+wGDyOUqVnkYQBEEUn7rPY0/O/WazWfHGLTqTO1odzerB7iOz0Cc0cokpyeRyqInMmD340/s6GKzRNC6JmAe1/HQwWHIQWqJLXy4VYFmnAsFgOP59Ym/0xBeRoV4F2lVitCsleOfQDJ567RiMdh8YZn5TFr31tDxyqRAn9E5IRAK8/f40Xtk9CaVcCG8oghM6J3SzTgz1toDPZ2P9oArNEh46WiQY6JahScDBmUtb4fAEoWxuQluLGG5/CCEmgrOXq6CUCXHh6g7wuNEmMVIxL57znfhyETtHyU1yqEQrQRBE6ag7iz2R5IC1WIOUWKDZmM4KHp+NA2NzmNQ7EA5H4u7sxAj7dctVcXd0YkT9mM6KUBj4454pXLq+K6d8ciC1R2BEa1+Q792hFEXlmHUgGGLg9bmhm3ODzQKmDBO46oK+eU1ZRrQ2yKUCHBgzYdbigYjPwdEJC4LBMDQtYhw6PgenJwgmxGDcKMbkrANnLlFCb3ahUxWtQmd3BXDuGW348IQJankTLM5oE5lulRgHR+eglDTh79Z0QC4RYCIYntcsJvmcd6nEC2ILFlPqlSAIgshO3VrsiT3Jx3RWcLnseIOUWDW4FX1KjE/bMWfzwWz3web2x/eNRdifnLHDaPcuaArCMBGs6FPCYPVA3MTFyJQ1qzyJJCp1LpeN/aNGhMMM3j2ih8MdzVfnctlROSYs+PD4HOTSaJCf2e6Dyx3AsZMWDPaebsrS19aM6Tk3uGxgsEcBDoeNM5e04swlrTBavVA2C9GjkWLtCg1GJi2w2L346wd6BEOReBW6E9M2HJ+2YXmPAgI+B0vaZdFAuEg0ZU4o5KClWYjhSStm5+Y3i+HxOPMUOTC/Mh6AlBX3CIIgiOJRtxY7w0TQ1iLB+8dNuPDMdoRCTMoGKUyIQQQscNgsrOprie/be8q17A8y0Js8WNrVjEgkMi+grk0hxLohNfYeNWBlX+quY0D2FqAME8GqpUr87fAsPrJCA4fLH6/Q1quWIsxE4HQFweFwAASwZnkrnKci5NsVInSrJJgyuDCut2L9oAp/O2LAhWe144bLBxEKMeBy2ehQiTGmteKMJSoEgyFEGGBcb8dgjwL7R4z4yAo1NAoh/EEGRosXPa0SDPYo4lb8+hVqqGVN8TX00Kk8+ljgYaLHAUD8PCXXro8F/a3IcL4ysdgCQwRBEPVOXVvsBmvUxfzS7gmMTNvRoRRh89outCcUReGcKhDTrhTh6KQVL707gRmzB+1KES5e3QEOG+Dx2Ng7bMSqpcp5RW92H5nF8SkbpEIe9GZXSgs0XV34GHqzB3uHjTg4bEKzkAen249L13fPewHgcli44Kx2HBqbw4FhI0JMBEpZE9in5HhjnxYsAJvW9ODIuAUOpx+Hxubicr6xTwsWAwycerHZO2yC2erBuSs1GJ2yIhwKY2TKhr9b0wU2CwiFwpgwOjFpcGF40oJRrRXHJizzlCoLgIDPAQunU/2mZh04ctKMLRt65smfHBi4vEeBoyfN89bdcyHVej1BEAQxn7q12AHgjCUqPP3WGEwWD/YeNWBVr2JeQBubzcLRCTO6VWJMGBywuwMQcDnQzbnQpRJHS672tuC1PVOIRCI4csKMzWu7Tpd4dfqhlAsRZqLbpaoylyl9LubyPzZhgVQcTT1b3qOIW9lRSzi6hs5iARtWanD0pAV2ZwC2U8FzsYj1WGnZWIW581a1gWGiDV9c7iBsHj+MVi/szgCU8iZwOGxI+FysH1Tj2KQVq5cpEQiEMNAlx6jWij61FGBHAwCtTn+8wl1M7hHt6Uj92LgAsG65el5AYDLRHuv5F6ihwjYEQRC5UZeKPeb6XtGtwOZ1Xdh7NFoBLlWU+vIuBU4aHOhoFaNHLYXF4ce00Q1dqxsdShHUsiZcsr4r3pI0VuaViQBsDhtL25sRSeoTnmtL1sSiOnZXIJ7/ndiwZbBbgXG9A0aLDz2tUnzy75bC7Ari/eFZ9KmlsHuC0Bpd8ReLwW4ZZBI+hictaOJxMNStwITRhYkZF0RiHiwuP3o7mmF1+MAAkAp5UCmacHjcAj6XE5dVZ3JjbMqKlX1KaBRC6ExuvHVAt6Dve2Kf+MT0vnQUWqCGCtsQBEHkRt0p9kTL7pjWis1ruxZY6onE+ooHg2HYQ0GYrG443EG0NAvieefdKgm6VdFGJO8eNeDYhAX+QBgXnt2B7jYp3tyvRSjEQGtyokcjiUbLhxjo5pzxZivpFFGsqE6sRntiBTs+n4MbLh/E2LQNESaCCaMTHSoxlnXLoZTwohb5wWm0KYSwe3zgchWnrHQbHK4AJo1OXHRWB949ZoDZ5oVnOohOlQRHJywQ8jiYNDrBYrFw7KQFHl8IKoVwXhlem9OPIyfNaFd2Z+z7HiObUo9RaIEaKmxDELUJxcaUl7pR7FwuG4FA1AWcbNllasQCAANdcozprOhpa0aLRBB3Pc+Y3Jicc8HlDoKFCLo1UrDZwEC3HBwOGzanH+8cmgaXw4YjGIR7zgu92YN2pQTjegdcnhDe2KfFqn5lvGJcshyxZi9TJieWtMugkjVhw0oN+HwOlnbK8OyfxiGT8sDhsGF3BTBjcsPqCeHgyGy86luEB7i9YbyyexIalRAhhoFQyMOczQftrBNn9LdgxuyG0xOEpIkLLpcDpyuApacatYQZBv4AA5PVi2mTG50qMQZ7FRiZtMaD+FIFvVWiexo9HAiitsgWPEwUn7pR7M/9eRw9aimsDm/aHuWp8tpjZV43rYluHyvtCgAHT5jg8gTh9AVhsngQCDM4obPhwrM7Mal3oknAgVZnA4vNgscbRJtSjF0f6iGX8uH0+MFhs8FEInh9nxab1naiXbGw25zN7YPPH4bDE8BJvRNrlqtgMLvwsQv68ezbx2G2e9HE50KlEGFSa0ervAnhOTf8gTD2HDOgvUUEdyAMk8WNLpUURosf4zM2NIsFkDRxMaKz4owlShw6boJQwIMvyMBgcGJVvxLHJi1oaxFD3MSF3eUBE2ZwctaB8VkH7M7TkfBA1FpmJS05EARBZIJiYypD3UTFuz0B7Bs2wOkJYkS7MKc8+QaL5bXbnH6M6uZHq8cs6W5Vc7QyndmNYJjBtMkNf5DBe0cNUCuEmDV70CxuQptcjPUr2uD2hsAG0MTnYLBXARaLBa3BiWmjC2NaG7hcdjy/ns1iYe+wAR5PCA5vEOMzdtidfuw7ZoDdFcTeY3qcNdCK/nY5zlyihMcbRCgcgcniw2BvCwR8DjYMacDlsjDULceKvha0qYSYmLFjeNIKcRMXMgkfK/qUODxuhkIqRIiJwOsPIRyO4MMT5vjLwZTehWYRH5pWMXyBMEYmLBjX2+OR8LHzlxj0RjnoBEFkI7HSJsXGlI+6sdi7NVKEI8AJrS3lDZQcfJXoXm5rkeDN/Vq0tUhgsLogkwjx4Yk5nLtKg/4OKQR8DrRGF1b0KjCms2OoRwG7y4vzVrVBb3ZjRW8LNAohFFIB9g8bIW7iw+HyYaBbBgGfg2CAgUYhxhv7tBjqVqCtJdqg5axlrXB7AxA0ccCCHCyGhXa1CO8dNaCnrR1n9bZg3TIVwmEGSrkQB8fm0K4SY3TKghV9ynl55VIxD8d1Npyzqg0iIQ9DPQoM9ZzKOe+KzvP8VW0Ihhgcn7ZBoxBj1uJa0ERmxuSGUMDD8ClrPpfmOARBEOmg2Jjyw4pEInVxtt/aO4l9xwyIRIBlXTL83dmd8RspZl0mN3uJ1YJ/Y58WgWAYRpsPfW1SfHgymgveqZbgc1cOxceIBbeFQsy8NfK4DAd0CIYYGKxetLUIYbT50KZoglIuhM0ZgMcTwvI+OaZNLoRCYSgVQvgDDI6Mm8FisXDuGW04ODaHYDAMgYCLz1y6HOFwdKx3DukgFQlw5KQF3ZpmhEOh+PIBm83CWwd0cLgCaFOJcMEZHQtSzpLnnXgukr97++A0fP4QBHxOfIxUxykHKpUUJpOzbONVmkaabyPNFWis+TbSXIHyz5fNZkGplKT/vmySlJj2lmgKllohwsCpnuVAtADMXz7Q4+Xdk/HGKcDpYidagwvLuxVoEnBwzkoNmAiD889oR6daEk+Ri/0HnI78jh1HZ3LPawQTa6Ay5/BjqFeBGbMXIgEPXWoxZLImvHVAB5GQD4c3jJM6J5r4XHSqJFjSIYNSyMfKvhZwuGwMdMnwzsFpvH1oGrsOz4AFNj4ct2B5jwJWpw8drfMv6mC3Akq5EEaLD1Ozzpxc5YnWeOLLz7JOOfg8Dga6Uns+CIIgiOqlblzxarkQarkQAOI51yv7lZg0OjGqtUIq5uO1PVO4ZH0XOpWnm5OMnEqJY7GB0Slr3MW9bnlr1vStxEYwr+/TYv0KNaQiPmaMLnQqRRietEKjEMLq8kHR3IT3jurBMBF8cMIEu8MPNoeFIMOgSyXBhyfM6GmXwOkOgMsGpgwuBAIhCARceHwhsFgsWB1ezJoFsLkCmLP7oTdPQ6MQQ292YVW/EqEwAybMYFzvwOipcq/JQYLJzWyAhUGF5DojCIKoXSpisX/3u9/F1q1bsXXrVjz88MMAgLvuuguXXXYZtm/fju3bt+P111/P+7gxRTSqtcLuCmB40oz+tmactbQVLncQHA4Lk7NRd0ksoGOwWxENrJuywe4M4KTeHne3x0hu35o43oo+JfRmN4R8DvYdM8Js80LWzIdAwMW65WrweWwMdCowpXPgIys0EAm4WL1MhcG+FvRpZDj/jDZ8cMKMWbMbh8bMsLkDMJi9UEj4GOxTgM/mYEmHFMFQGKFwBGa7DxEmguHJaC793mED7K4Ajk6YsbxHDrVSBKvTD6vDtyBIcNLojDeziTXGSVfylpQ6QRBEbVJ2i3337t3YtWsXnn/+ebBYLHzpS1/C66+/jsOHD+OXv/wl1Gr1oo7PMBG0KyWYMRvRJ5FheMqClX1KSCV8HNfZoZ/zQGdyx63SaZMbfz40AwCQSQXw+MJ44S8nsXa56nTb1FPtW2OfJRKrTDemtUImEeLISTPOaBHD6vChp1WCZokCRyZMkMmFODBixEfP70OvShIvGTtjcuOsZa0Y5rKxokcBiZAHqZALjUIMo82N5b3NMDv9UCvEUEiasKxTBoc3gGYhf17w20CXAu0KETqV81ujJja/6VVLEQHiAYNv7NNisFtBQXEEQRB1RNkVu0qlwje+8Q3w+XwAwNKlSzEzM4OZmRncc889mJmZwZYtW3DLLbeAzc7focBmszBrcaFbJcaHJ+YgFfJwYsYONpsFs92LMBPBtNmFHk20klysVjuHw4ZKIcKczQun2w+VQogejQRTJifG9fZ4NHmiizoWSBarTPfmfi16NRJ8cDw67oTRCX8gDKmQj92H9TBZPNh9WI+By1cgFIoGtw1rrXB7QlizvDUexd6jiSpdm9OPZjEfo5M2GMxurFrailX9CigUYphMTqzolYPNZsUj4wEs6KjGZrMWuNZ726R4fe/UvKWIZNc7VYoiCIKoTcqu2AcGBuL/npiYwCuvvIJf/epX2LNnD+6//36IRCLcdNNNePbZZ/GpT30qr2PHlNFAlwLHp604Z6UG0yYX+tRSsNhAJAJYnX7YXUG88JeTWLdcFa/V7nQH0aEWg8NmoUstgdnhg87gQou0CT0aKQxWD3o00nnBdydmbGgWN8VT4+RSIfYMG/CRIQ2sDi/61FI4vEHojA6sX6GB1e6HXMbHnw7oYHP6sW65Cu1KCQ5YTFjG58UVcSjExCu/aWQiCId4OD5jh8cbwpTBBYUiWvb12KQN+0eNOG9VG/rbpAvOR6qKT7HiOO2nIipTWelUKYogCKJ2qVjw3NjYGG666SbceeedWLJkCb73ve/Fv/uHf/gHvPDCC3kpdqefwZHxOQz2tmD1kAZisQCjUxasX9WOcDiCKYMdTk8QM2Y3bHYfBAIu1C0ibL1wCc461Zns97vGIZfwMWVwwmTzQSLkQy7lw+sPg8tm429HDVDIRFjWLccf9+ng9gbx4bgFPn8Yk0YXLHYfWqRN2HvMgB2XDaK/Q4a39k3C6gpBIW9Ci1wAs9WHEa0FfB4X3e1S+ANh8HkcOH0B2H1hjE5ZoJQJYbZ7sX5VO/o7ZDg5Y8fhCQuCIQa6OTdWI5pe8cw7J8DjsvH6Xi0+vWUQy7rlAIDjWhsm9HbMmj1gs1nRfU7Ncc+ICYEw4PAG8MktQynP5Z4RE4IM5u1XSVSqhS8t9UwjzbeR5go01nwbaa5Adc23Iop9//79uO2223D33Xdj69atGBkZwcTEBC6//HIAQCQSAZebn2hHTpgwY3LB4w1AKeHh4IgBVocPkQgDn59BIBBCKAJo5EJ0KEUIMxF0tYrn5R52tYqhm3NBJRfB6Q6AxwE6lWJMzjoxbXIjHGZwcMQApYQHSRMXs2YX1g6qMaF3YGWXHL4OBm/s1aFZxMP+o3o0CzhoaxEhEgFmzW4YzV7YPQG0SIVgEEGXUoR3jxqhnXVAKRXg0KgBPn8II5NWSIU8uD0ByIVcHDg2C5mYD/2cG93qqLVuMjmxYVCNV/dMgc9h4+DILJQSHgDg/eFZOFwBKOVChMLMvHl2tYrh8QbQqRSnzbuMbZN8fioB5cPWL400V6Cx5ttIcwWqL4+97Ipdr9fjq1/9Kh599FGcd955AKKK/Fvf+hbOPfdciEQiPP300/j4xz+e13H7O5rh9YewvEsOncEFYRMXgSAPTXwe5uwuBAMMVvQpYHX5sKRdBo1CGHd7x4jGg0fQrRZD1MSBXNyEoxNzWNIhhVQYrezW1hLt076ssxkSERedSglamgX4cNICiYiDdYMqHB23oKNVghmzG7M2F3hcNpQyAYRNPFjsPrDBwrmrNDC7/BAJODhrqRIdrWKYbF6EwogHxA12K6AzuMDjcTFpsGHzmk50KsWn59wmxccvWoJRbXS8dw7OwO4KYGmnDMDpanKJrvZcUtko3Y0gCKJ2Kbtif+KJJ+D3+/HQQw/FP9uxYwduvPFGXHfddQiFQrjssstw1VVX5XVcFgABnwMul40xnQ1Wpx8yqQD7R4yYs3qwrFuBlX2nu70dm7Rh73C0T/tgtyya9nUqJ/24zogrz+vFoVETAsEwRu122F0+sFksGG1uyCQ8jOsdCAQZeP0O6ExO8FgcyCXRkrIWhw9WtxyTsw5oWsUI+sN474gJepMTV5zXCz6Pg0AwjGMnbfAGQuBz2fBO2xEOhqFWirCiV44VvXIAwBv7dTg2YUa3RoYPxs04eGIOF67ugqyJAwBoUwjB4Sqx65Aes+ZocxiJiItL13enbRebi8ImpU4QBFGblF2x79y5Ezt37kz53Wc+85mCj3tS74DR7IFQwIE/FI7mcLPZOOeMNoxy2DijvwVAVGFxuWzsGzHA6vBiwuDAqv5oWtiKPiVe2zOFSCSCD8ZMGOxVYExrxZJOGYw2L2yOAM7ob8WozgadwYkZiwctzU04e6AVXj+DoxNmCAU8qGQseL0h+IMMhiesaOJzsaSzGUAEJ2ecaGsRYtbiBYMIxqftEPI52LAyWuWuVy2Ny8lms9DE52CorwWzFg8c7gD8/jBUchHOXaGOb3N03Ay5mA8Bn4NIJFo5Ltfe6ARBEER9UTeV57hcNqQSAaaNHizrkkGwigN/gIHF5sdHz+uDyerFT/8wjI+s0EAm5GGgRw67W4yJaTuOnLRisFsWz0kfmbTG88LZAE7OumCY82KwX45jk5bourVaClETHxEG4LBZCDMhDPYq4POHEAwyiCCCFpkAzWEeeFwOwkwE7Qox+jqlcLj86NE0w+LyQiXvwOikDSqZEEM98njVvFhEen9bM7RzTvRqNDBYvLA6/RjsbZmX3jZwqsnLhkE1NAohWdsEQRANTN0odj6HDaPVAyGfA73ZhUvX9+DN/Tr4AkFojQ4cHrfAaHFj1uqB3c2B1enHyJQVZrsP+0YMWNUfddO3K0ToVkniDV9mrV7sHzbA6Q3CEwzC7w+DzWZBJORBKeGjVSHEnNUHlzuIZb3NcLLYOGawwO0NYv1KNf7u7C789UM9Jmft4LBYCIcZXLKu+5S1rcCf3tehs1UEvdmFlX2KBb2L25UidKqi6+rLu+QAAKVSArPZFVfgiWvipNQJgiAam7pR7EcmrRjokcNs82JJRzOOnLTA4w+Cy+FAJOBhWZccHa0STMw6sHpZKzgsYMOKNgxPWHDR6vZ4tbZ2pRjeQBAiAQ8muxeIIFpz3uDAyr4W6M0eBAMMVvYr4PYF0S4TQa0Q4bjOivYWKQJhB7rUEhhtXgh4XPzpgA4hhkG3WoJgkIHLE8SxSSs8/iCEfB44bDa4XA6Wd82vEpeYX55YSa5DKcJxrQ3vD8/OyzMnhU4QBEEAdaTYEYnA7vTD5QthROfAtMkFIZ8DHo+DMZ0dCjEf49N2tCvF2H/MBC6XhQ4Ay3qaMTPnwdEJC0LhCCIRwB9i4HQ7YHH44PIEoVQ04dxVbTBaPOCzWVCphWAAHJ2wgtXPhtPjRbNEgOPTNnw4boaIz4XLG8BJvQNWhw8dKimMFjcUzU2wOX1gsVmY1DshEHChkjXBYPViRZ8CwMKI9ORa7j0aCUYmTfOselLqBEEQRIy6advapZZi1uLBkRNm7D86i7MHWmFx+uF0BSAT8xGKMLjgrA7YPH7ImwUIMwzAZsNk9uLYlAXCJh7aWkWYmXNjXGcDiwW0ypuwckkLlM1NkAn5GOiUQyLmY1mHAnuPGmB3+rHn6CzETXyMTtnx9vvT6FJJYHf74XQFIRPxsX6FGse1Nsya3dAZXeBw2Dg6YcXolBUqWRP0ZjdCoTBGJlM3YGGYSLxhTaz2+2BvS/xvUuoEQRBEInVjsf/d2R04PN4EhbQJXA4bpjkPLjyzAwfHTFDJo4FpepMbQz0KON0BtEj46NZIYJHwoHAFwWaz4AuEoWxvQigkhtsbgkTEQyTMYOWACipZE2bMHvgDYQT8IZy5tBUHjpuwqk+J/SNGnD2ohlzShJk5NzasaMOHJ+bQ0SpGs4iHs5ercFxnw6r+FoxqbThnpQZHhTx0qyVY0RctHZtJSSdb8cu65VCIuKTUCYIgiAXUjWIPhRgM9chx5lIlXt87BV84gg9OzKFTKYQvGASHw8awzga3O4gl3c04o18JAPjZqyPw+4NQyIRweQKwutgQ8rlQy5swaXRD1sSH2eFFR+vpHu4njU4EQ2Gcv1KDPx+cQausCQdGjDhrSQt62lUwmn1Qy5tgcfowM+eG0xXA+kEVTDYvWiR8eHx+fGHrSgQCIQDR6nbZlHRyUxZS6gRBEEQq6kaxm2xejE1H26vyeexTFdzUMDv90Bk9mLNNgcdlQSEX4r2jRggFXITCDJZ2yaA1OtHfKYXdGYDHG4ZEzMOozo4NK1VweUMY1TqgM7rQ29YMAPFcc53ZgdUDrfjbYT3OPbMTfr8foWAEbl8Ifj+DNctlCIYYjGqtUIgFkEsFGNPaoJKJ8dqeSQx2K+KV4ZIVd+LfI1r7vGI6BEEQBJGOulljNzl8OKGzYXzGjj+/Pw2hkIuVfS3QGpw4MW3D/mEjmAjw/qgRXC4bB4+bMWN2g2EYKCRNOKF1YFLvgMPrx7sf6uH2BiDg8TA8aQUTicBo82HPsBGrlirjKWhSYRPePTyLqVkXPjhuwllLNdh7zIg9R/SQiHk4NmkBC8DmtV2IADg54wCPy8FxnQ0OVwDjegfePjiNEa0dbx3QYcbsARDtrhb7m8tlY++wATqjE3uHDeBy6+aSEQRBECWgbix2VXMTVi1RYtLghEwigFwcbYjSrZGCx+WgpbkJU0YH1g6psefILJr4HEiEArw/ZoLHF4BGIUFbqxihYARnLFWiic/Be8dmsXqgFUfHLdAanGgW8zE8YYFmdScAQCHi45wz2sDlsHHRWR0Y1VmgbhHB4w9hZs6NZiEPI4wV3RpJvO+7xxfC2iF1NA7A6gWfy8LeYQOkQl486j05l33DqQ5rG4Y0VFGOIAiCyEjdKHY2gI+s0IDDZWFK74LVFcCb+3VgsSNoVwrRKmtCE58Nu92Pref3Y9rkgKiJhdUDLfD6Gfg8QTRLBfD5w9BbPFjeLYOQz8PolB1nLFWgRyPF+yMmyCRN0Jnc8Z7mXHYEn//oCtidfpjtXoibuFjV34I2hRh6syseyR7r+253BbC8Sw6NQhg/TqzpS2zb5Fz2wW5ZvOwtQRAEQWSibhT7lNmDtz/UIxgMIxyOYNoUgIDPxfi0HZef040PTlhw9KQZ64c0GOhsxmC3DPtHDYiEWZizeCGXCnBk3AK70481g2q8snsSMqkA565UIwIW3h/Vw+zwYXzGDpvTB38gjH0jRmhaRPjjninweWyEgww0rSJccEZ7tPZ8rzy+Th5z30+b3Thy0oxgSDEv2j1x21Td1UipEwRBELlQNwu2h0+YsffILLo1UoiFfKxcooRUzIdMwodSLoRQwIVcIkCTgAM2mwUWiwWwWDipdyAQYrDn6Cy6VWKcd1Y7jp00QykTwuMLoa1Fgr3HjOhrb4ZcKsDK/hYs65RDwOfgvFVt0M+54fEFIRcLIJMK0K2SxpVwqsj1kcnTbvbEALnkbSnqnSAIgiiEurHYV/UrYXP5IRXxsLStGVNzTnS0CqGSN2FyxokWmQDBcDMsNh8OjM1hZs4NkYCNnjYpzFYfNqzQgMNmIxgKYfWAGqNaK674SA9kIh4+MqTB+8dNuGbjUnS1Ruu2xyzqJgEHI5PWlL3Pk4kVm0kuGUsQBEEQxaJuFPuUyYFL1ndhZY8CbDYLx6asEPA4mDY6ARagN7vhCYSgbG7C0ZNmGMwe8PlsXLymAxeduQSRSAS7PtTj8Ik5+ANhXLC6A0s7mtOuccdd7ApRPA89sQxsrsVmCIIgCKKY1I1iD/jD4HFYmLF4cFxnQbNEgIMnzDijXwmjyYP+ziZ4vEFw2ACXw4GqRQS3J4hxrQt8Dhd6swsdrRKs6G9BIBBGhzL3Ne7E7WbMnnkNW7JtTxAEQRDFpG7W2B1uPxyeEJ7703EAHOz+QA+xgIO9R2cBdgTHp2xweUM4rnXgpN6ByVkHJvQOcHksvPX+NDx+BuMzDoAFgMXCe0cN8bzyXElu2BKr/U4QBEEQ5aJuFPtATwv+dliPTrUEw5MWrB5QIRCKNn5xeoNYM6gCB2ysWqqEWMBDi1SI1QOtmHP4cEa/EnN2L4w2L46dtOD9USNOTNswprMtUM6ZlHVywxayzAmCIIhyUzeueLc3iA2r2uB2+dDSLIDbE8SSdhk+OD6HTWs60dUqBpfNxocnLFi1RAG7y48l7TK0KcV4f9SEtctVsDn9CIYYMJHo8Qa65Hm72WkNnSAIgqgkdaPY/f4QDHMemO1e2N1+qBQiDGutsDp8kAh56N+0DPo5N7hswGhx45J1PQiHGRybtKC1WYA5mweb13anbbSS7GbPpLxJqRMEQRCVom4Ue3e7GOEI0Czhwe4MQt3CR39HM7QGJ8JhBkdOWsDlsMHjcqBRSPDm/il0qSXg87n4cNyCC8/qyBogR6lqBEEQRLVTN4qdy+Hi/aOzcLgCuGB1O5gIMDJhgc0dAJsN+INhNAv56G6TwGB1g8vh4tAJC3QGJ+ZsPhwen8O65a0ZlTu52QmCIIhqp24U+5TBjWVdcgDArMULs90HtVwEqZgPHoeDoV45pk0uaOQidLRK8MY+LVplTThzaStO6h1YP5hbgxVS6gRBEEQ1UzeKvVsjxtiUDWuXKyF0ciFu4kFvdmPz2Z1gcVgYnbJiZb8SalkTAGDT2s7oZ30tuHRdF9ViJwiCIOqCulHswUAIHS1CHJmwYc7iRRgMNgxp0NMmxRv7tNH+5zN2tCmEYJjIvIpxpNQJgiCIeqFu8thVchEc3hDEAi76OprRphBDJRMiFGIw2K2AUi7EnM0Hnckd34fc6gRBEES9UTeK3e72w2Bx4+hJM8RCLq6+qD+ea96pEiMUZhAKhakiHEEQBFHX1I0rvkMphrMzCKvTj65WyYKGLQNdckpVIwiCIOqeulHsbS0itLWI5nVZS4RS1QiCIIhGoG4U+95hI6ZNbqxdrqKuagRBEETDUjeK/cS0DTqjG1IRjyxzgiAIomGpquC5l156CR/96EexZcsWPPnkk3ntu7RTjmVd8gWNWwiCIAiikagai91gMODRRx/Fb3/7W/D5fOzYsQPnnHMOli1bltP+G4bUWLc89fo6QRAEQTQKVWOx7969G+eeey7kcjlEIhEuv/xyvPrqqznvny5ojiAIgiAaiaqx2I1GI1QqVfxvtVqNDz74IOf9Gy03vZHm20hzBRprvo00V6Cx5ttIcwXKO99sY1WNYo9EFlrbLFbuJ0qhEBdTnKpHqZRUWoSy0UhzBRprvo00V6Cx5ttIcwWqa75V44rXaDSYm5uL/200GqFWqysoEUEQBEHUHlWj2M8//3y8++67sFgs8Hq9eO2113DxxRdXWiyCIAiCqCmqxhWv0Whw++2344YbbkAwGMS1116Ls846q9JiEQRBEERNwYqkWtwmCIIgCKImqRpXPEEQBEEQi4cUO0EQBEHUEaTYCYIgCKKOIMVOEARBEHUEKXaCIAiCqCNqXrEvpiNcLeJyuXDVVVdBp9NVWpSS8t3vfhdbt27F1q1b8fDDD1danJLz2GOP4aMf/Si2bt2Kn/zkJ5UWpyz8x3/8B77xjW9UWoySc8MNN2Dr1q3Yvn07tm/fjkOHDlVapJLy1ltv4ROf+ASuuOIKPPDAA5UWp2T85je/iV/T7du3Y926dbj//vsrLVaUSA0zOzsb2bRpU8RqtUbcbndk27ZtkbGxsUqLVTIOHjwYueqqqyKrVq2KaLXaSotTMv76179GPv3pT0f8fn8kEAhEbrjhhshrr71WabFKxnvvvRfZsWNHJBgMRrxeb2TTpk2REydOVFqskrJ79+7IOeecE7nzzjsrLUpJYRgmcsEFF0SCwWClRSkLU1NTkQsvvDCi1+sjgUAgct1110XefvvtSotVckZHRyNbtmyJmM3mSosSiUQikZq22BfbEa7WeOaZZ3DvvffWfaldlUqFb3zjG+Dz+eDxeFi6dClmZmYqLVbJ+MhHPoKf//zn4HK5MJvNCIfDEIlElRarZNhsNjz66KO4+eabKy1KyRkfHweLxcKXv/xlfOxjH8Mvf/nLSotUUl5//XV89KMfRVtbG3g8Hh599FGsXr260mKVnPvuuw+33347WlpaKi0KgCqqPFcIi+0IV2s8+OCDlRahLAwMDMT/PTExgVdeeQVPPfVUBSUqPTweD48//jh+/OMf44orroBGo6m0SCXjm9/8Jm6//Xbo9fpKi1JyHA4HzjvvPNx3333w+Xy44YYb0N/fjwsuuKDSopWEyclJ8Hg8fPGLX4TJZMKmTZvwta99rdJilZTdu3fD5/PhyiuvrLQocWraYo8ssiMcUd2MjY3hC1/4Au6880709fVVWpySc9ttt+Hdd9+FXq/HM888U2lxSsJvfvMbtLe347zzzqu0KGVhzZo1ePjhhyESidDS0oJrr70W77zzTqXFKhnhcBjvvvsuHnnkETzzzDP48MMP8fzzz1darJLy1FNP4fOf/3ylxZhHTSt26ghXv+zfvx+f+9zn8M///M/4+Mc/XmlxSsqJEydw7NgxAIBQKMRll12GkZGRCktVGl555RX89a9/xfbt2/H444/jrbfewre+9a1Ki1Uy9u3bh3fffTf+dyQSAZdb047SjLS2tuK8885DS0sLmpqacMkll9S1FzUQCGDv3r3YvHlzpUWZR00rduoIV5/o9Xp89atfxXe+8x1s3bq10uKUHJ1Oh507dyIQCCAQCODNN9/EunXrKi1WSfjJT36Cl19+GS+++CJuu+02bN68GXfffXelxSoZTqcTDz/8MPx+P1wuF55//nls2bKl0mKVjE2bNmHXrl1wOBwIh8P4y1/+glWrVlVarJIxMjKCvr6+qouJqelXR+oIV5888cQT8Pv9eOihh+Kf7dixA9ddd10FpSodGzduxKFDh3D11VeDw+Hgsssua4gXmkZg06ZN8WvLMAyuv/56rFmzptJilYzVq1fjS1/6Eq6//noEg0FccMEFuOaaayotVsnQarVoa2urtBgLoO5uBEEQBFFH1LQrniAIgiCI+ZBiJwiCIIg6ghQ7QRAEQdQRpNgJgiAIoo6o6ah4giAIgqhmXC4XduzYgR/84Afo6urKe/+bb745XqWRYRiMjo7i2WefxZlnnpl2H1LsBFGjDA4OYvny5WCz2WCxWPB6vZBIJLjvvvsy/ujz4dVXX8WTTz6JX/ziF0U5HkE0EocOHcLOnTsxMTFR8DF+8IMfxP/92GOP4eyzz876+ybFThA1zM9+9rN5jSeeeOIJPPDAA3j66acrKBVBEMDpxl3/+q//Gv/shRdewM9+9jMwDINVq1bh3nvvhUAgyHqsEydO4IUXXsBLL72UdVtS7ARRJ4RCIej1eshkMgDA3NwcvvnNb8JsNsNkMqGzsxP/9//+XyiVSmzevBkf//jH47Xpr7zyyvjD57HHHsNLL70EuVyO3t7e+PGdTif+z//5PxgeHgaLxcJFF12Er3/96+ByuTjzzDPxuc99Dm+//TZcLhfuuOMOvPrqqxgdHYVarcYPfvCDBdW5LBYL7rrrLkxNTUEul0OlUmFgYAC33nornn32WTz99NMIBoOw2+348pe/jOuvvx6//e1v8fvf/x4Mw8BgMECj0eChhx6q66Y5RO2S3LhrbGwMzzzzDJ566ikIBAL853/+J5544gn84z/+Y9Zj/fd//ze++MUvQiKRZN2WFDtB1DCf/exnwWKxYLFYIBAIsGnTJnz7298GAPz+97/H2WefjRtvvBGRSAQ33ngjXnzxRXzhC18AAHg8HvzqV7+CwWDAli1bcN1112FkZASvvfYaXnjhBTQ1NeGrX/1qfKwHHngAcrkcL730EoLBIL7yla/gxz/+MW688UYEAgGoVCq89NJL+N///V/s3LkTf/jDH6BSqXDttdfizTffxLZt2+bJ/sADD2DZsmX4n//5HxiNRnziE5/AwMAA3G43fvOb3+B///d/oVAocPDgQXz+85/H9ddfDwA4cOAAfvvb36K/vx/f+c538OCDD+Lxxx8v0xkniMJ57733MDk5iU996lMAgGAwiJUrV2J2djb+WSIvvfQSZDIZ7HY7/vrXv+bc4ZMUO0HUMDFX/NGjR/HlL38Za9asgVKpBBBV+vv27cNPfvITTExMYGxsbF5v7EsuuQRAtDSzUqmE3W7Hu+++iy1btsStgmuuuSa+vv7nP/8Zv/71r8FiscDn87Fjxw787Gc/w4033ggAuPzyywEAPT09WL58edyK7urqgt1uXyD7O++8E+/8pVarccUVVwAAxGIxfvCDH+Cdd97BxMQEhoeH4fF44vtdcMEF6O/vBwB86lOfwvbt24t0NgmitITDYVx55ZXYuXMnAMDtdiMcDqO5uRl//vOf0+73zjvv4OKLL87JZQ9QuhtB1AUrV67EXXfdhZ07d0Kn0wEAHnnkETz22GNQKBT49Kc/jQsuuGBeq+PEhwSLxUIkEon/PwaHw4n/m2GYeWMyDINQKBT/m8fjpfx3Orhc7ryx2Ozo42h2dhZXX301pqensW7dugX9vJNlSvybIKqZc845B6+//jrMZjMikQjuu+8+/OxnP8u638GDB7F+/fqcxyHFThB1wlVXXYWzzz473gZ1165d+OxnP4urr74aSqUSu3fvRjgczniMiy66CK+++iocDgcYhsGLL74Y/+7CCy/Ek08+iUgkgkAggGeeeQbnn39+wfJu3LgRzz77LADAarXijTfeAIvFwuHDh9HS0oJ//Md/xEUXXYQ//elPABCX/W9/+xsMBgOAaC/sTZs2FSwDQZSToaEh3HLLLfjsZz+LrVu3gmGYuMcrE1qtNq84EnLFE0Qdcc899+BjH/sY/vKXv+CrX/0qHn74YXz/+98Hh8PB2rVrMTU1lXH/jRs3YmRkBNdccw2am5sxNDQEq9UKANi5cyceeOABbNu2DcFgEBdddBFuvvnmgmWNeRi2bdsGuVyOjo4ONDU14YILLsCzzz6LK664AkKhEGeddRZaWlowOTkJILp0cMcdd8BkMmHZsmW4//77C5aBIMrBW2+9Ff/3Jz/5SXzyk5/Ma/8f/vCHeW1P3d0IgqgITz75JFauXIk1a9YgEAjg+uuvx6233oqNGzem3ee3v/0t/vjHP+J//ud/yigpQdQWZLETBFERli1bhn//938HwzAIBoO44oorMip1giBygyx2giAIgqgjKHiOIAiCIOoIUuwEQRAEUUeQYicIgiCIOoIUO0EQBEHUEaTYCYIgCKKOIMVOEARBEHXE/weIY5Xs/HNAaAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "FS = (8, 6)\n",
    "fig, ax = plt.subplots(figsize=FS)\n",
    "sns.scatterplot(data=df, x='gap', y='total', alpha=.5, marker='.')\n",
    "ax.set_xlabel(\"Random gap\")\n",
    "ax.set_ylabel(\"2021 page views\")\n",
    "ax.set_ylim(0, 200)\n",
    "ax.set_xlim(0, \n",
    "            #1e-6,\n",
    "            7.5e-7,\n",
    "           )\n",
    "savefig(\"moth_gap_views.png\")\n",
    "\"\"\"\n",
    "ax.axline(xy1=(0, 3), xy2=(1.3265e-6, 256),\n",
    "          color='red',\n",
    "          dashes=(5,2),\n",
    "         )\n",
    "         \"\"\""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}