4-Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data analysis with inferential statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Helpful functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_results(pval, conf):\n",
    "    print(\"P-value = {}\".format(pval))\n",
    "    if pval < conf:\n",
    "        print(\"Reject null hypothesis.\")\n",
    "    else:\n",
    "        print(\"Fail to reject null hypothesis.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "csvfile = \"meetings_complete_clean.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "converters = dict(Time_dt=pd.to_datetime, Time_del=pd.to_timedelta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(csvfile, converters=converters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Day</th>\n",
       "      <th>Time</th>\n",
       "      <th>Video</th>\n",
       "      <th>Desc</th>\n",
       "      <th>Categories</th>\n",
       "      <th>Email</th>\n",
       "      <th>Phone</th>\n",
       "      <th>Time_dt</th>\n",
       "      <th>Time_del</th>\n",
       "      <th>...</th>\n",
       "      <th>Label_Game</th>\n",
       "      <th>Label_Blind / Visually Impaired</th>\n",
       "      <th>Label_Deaf / Hard of Hearing</th>\n",
       "      <th>Label_Email</th>\n",
       "      <th>Label_Professionals</th>\n",
       "      <th>Label_Meditation</th>\n",
       "      <th>Label_Seniors</th>\n",
       "      <th>Label_Newcomer</th>\n",
       "      <th>Label_24/7</th>\n",
       "      <th>Zoom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1 Hole in the Sky AA Meetings: AA Secular Dail...</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>5:00 pm</td>\n",
       "      <td>https://zoom.us/j/414948190</td>\n",
       "      <td>Tuesday: AA Secular Daily Reflections 3:00pm P...</td>\n",
       "      <td>Audio,Open,Video</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-17 17:00:00</td>\n",
       "      <td>0 days 17:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AA Friends</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>5:00 pm</td>\n",
       "      <td>https://aafriends.webs.com/</td>\n",
       "      <td>AA Friends currently holds three online meetin...</td>\n",
       "      <td>Forum,Open</td>\n",
       "      <td>aafriends@usa.com</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-17 17:00:00</td>\n",
       "      <td>0 days 17:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AA New Beginnings</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>5:00 pm</td>\n",
       "      <td>https://us02web.zoom.us/j/5662326551</td>\n",
       "      <td>A daily meeting that focuses on experience, st...</td>\n",
       "      <td>Audio,Big Book,Discussion,Open,Video</td>\n",
       "      <td>AANewBeginnings230@gmail.com</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-17 17:00:00</td>\n",
       "      <td>0 days 17:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Agnes Water</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>5:00 pm</td>\n",
       "      <td>https://us02web.zoom.us/j/8983968244</td>\n",
       "      <td>PW billw</td>\n",
       "      <td>Big Book,Discussion,Speaker,Video</td>\n",
       "      <td>agneswaterxa@gmail.com</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-17 17:00:00</td>\n",
       "      <td>0 days 17:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Beginners AA meeting</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>5:00 pm</td>\n",
       "      <td>https://us02web.zoom.us/j/88198562544?pwd=wfzm...</td>\n",
       "      <td>Zoom Passcode, if any: serenity</td>\n",
       "      <td>Big Book,Discussion,Open,Speaker,Video</td>\n",
       "      <td>liaazoom2020@gmail.com</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-17 17:00:00</td>\n",
       "      <td>0 days 17:00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Name      Day     Time  \\\n",
       "0  1 Hole in the Sky AA Meetings: AA Secular Dail...  Tuesday  5:00 pm   \n",
       "1                                         AA Friends  Tuesday  5:00 pm   \n",
       "2                                  AA New Beginnings  Tuesday  5:00 pm   \n",
       "3                                        Agnes Water  Tuesday  5:00 pm   \n",
       "4                               Beginners AA meeting  Tuesday  5:00 pm   \n",
       "\n",
       "                                               Video  \\\n",
       "0                        https://zoom.us/j/414948190   \n",
       "1                        https://aafriends.webs.com/   \n",
       "2               https://us02web.zoom.us/j/5662326551   \n",
       "3               https://us02web.zoom.us/j/8983968244   \n",
       "4  https://us02web.zoom.us/j/88198562544?pwd=wfzm...   \n",
       "\n",
       "                                                Desc  \\\n",
       "0  Tuesday: AA Secular Daily Reflections 3:00pm P...   \n",
       "1  AA Friends currently holds three online meetin...   \n",
       "2  A daily meeting that focuses on experience, st...   \n",
       "3                                           PW billw   \n",
       "4                    Zoom Passcode, if any: serenity   \n",
       "\n",
       "                               Categories                         Email Phone  \\\n",
       "0                        Audio,Open,Video                           NaN   NaN   \n",
       "1                              Forum,Open             aafriends@usa.com   NaN   \n",
       "2    Audio,Big Book,Discussion,Open,Video  AANewBeginnings230@gmail.com   NaN   \n",
       "3       Big Book,Discussion,Speaker,Video        agneswaterxa@gmail.com   NaN   \n",
       "4  Big Book,Discussion,Open,Speaker,Video        liaazoom2020@gmail.com   NaN   \n",
       "\n",
       "              Time_dt        Time_del  ...  Label_Game  \\\n",
       "0 2021-11-17 17:00:00 0 days 17:00:00  ...         0.0   \n",
       "1 2021-11-17 17:00:00 0 days 17:00:00  ...         0.0   \n",
       "2 2021-11-17 17:00:00 0 days 17:00:00  ...         0.0   \n",
       "3 2021-11-17 17:00:00 0 days 17:00:00  ...         0.0   \n",
       "4 2021-11-17 17:00:00 0 days 17:00:00  ...         0.0   \n",
       "\n",
       "   Label_Blind / Visually Impaired  Label_Deaf / Hard of Hearing  Label_Email  \\\n",
       "0                              0.0                           0.0          0.0   \n",
       "1                              0.0                           0.0          0.0   \n",
       "2                              0.0                           0.0          0.0   \n",
       "3                              0.0                           0.0          0.0   \n",
       "4                              0.0                           0.0          0.0   \n",
       "\n",
       "   Label_Professionals  Label_Meditation  Label_Seniors  Label_Newcomer  \\\n",
       "0                  0.0               0.0            0.0             0.0   \n",
       "1                  0.0               0.0            0.0             0.0   \n",
       "2                  0.0               0.0            0.0             0.0   \n",
       "3                  0.0               0.0            0.0             0.0   \n",
       "4                  0.0               0.0            0.0             0.0   \n",
       "\n",
       "   Label_24/7   Zoom  \n",
       "0         0.0   True  \n",
       "1         0.0  False  \n",
       "2         0.0   True  \n",
       "3         0.0   True  \n",
       "4         0.0   True  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4155, 37)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add column with time in total seconds for easier calculations\n",
    "df['Time_sec'] = df['Time_del'].dt.total_seconds()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For evaluating day and time patterns, best to remove ongoing meetings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df \"minus ongoing\"\n",
    "df_mo = df.drop(df[df['Day'].str.contains('Ongoing')].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4078, 38)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mo.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### One sample t-test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average time of all non-ongoing meetings:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Timedelta('0 days 14:10:38.357037763')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Average time of all non-ongoing meetings:\")\n",
    "df_mo['Time_del'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_time = df_mo['Time_sec'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Null hypothesis $H_{0}$:** The average time of men's meetings = 14:10:38\n",
    "\n",
    "**Alternative hypothesis $H_{a}$:** The average time of men's meetings $\\neq$ 14:10:38\n",
    "\n",
    "**Confidence level:** $\\alpha$ = 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "male_mask = df_mo['Label_Men'] == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('0 days 16:00:58.301886792')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mo[male_mask]['Time_del'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "57658.301886792455"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mo[male_mask]['Time_sec'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P-value = 0.0002425719732924799\n",
      "Reject null hypothesis.\n"
     ]
    }
   ],
   "source": [
    "sample1 = df_mo[male_mask]['Time_sec']\n",
    "tset1, pval1 = stats.ttest_1samp(sample1, avg_time)\n",
    "\n",
    "print_results(pval1, 0.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In other words, we are 95% confident that the average time of men's meetings is significantly different from the average time of all meetings. Keep in mind that because this is a dataset that is both international and timezone-naive, this effect could be due to local rather that time preference. (That is, perhaps there are more men's meetings in the eastern hemisphere, etc.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Two sample t-test\n",
    "\n",
    "It is a pop psych truism that women are more verbose than men. Here is an independent t-test to evaluate whether the description field for women's meetings is longer than that of men's meetings.\n",
    "\n",
    "First, we add a column indicating the total character length of the description field:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Desc_length'] = df['Desc'].str.len()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, separate out samples consisting of women's meetings and men's meetings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "women_mask = df['Label_Women'] == 1\n",
    "men_mask = df['Label_Men'] == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "women_desc_len_sample = df[women_mask]['Desc_length']\n",
    "men_desc_len_sample = df[men_mask]['Desc_length']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(79.1025641025641, 62.31192660550459)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "women_desc_len_sample.mean(), men_desc_len_sample.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The women's mean is greater than the men's mean, which is a nice preliminary support for doing a **one-tailed test:**\n",
    "\n",
    "**Null hypothesis $H_{0}$:** The average length of description of women's meetings $\\le$ the average length of description of men's meetings \n",
    "\n",
    "**Alternative hypothesis $H_{a}$:** The average length of description of women's meetings > the average length of description of men's meetings \n",
    "\n",
    "**Confidence level:** $\\alpha$ = 0.05"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Check key assumption: homogeneity of variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LeveneResult(statistic=2.378961556272901, pvalue=0.1237341501771085)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.levene(women_desc_len_sample, men_desc_len_sample, center='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the p-value is much greater than 0.05, the Levene's test is not significant, indicating the groups do not have a different amount of variation. Thus we can proceed to the independent t test:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.7424899816344992\n"
     ]
    }
   ],
   "source": [
    "tstat2, pval2 = stats.ttest_ind(women_desc_len_sample, men_desc_len_sample)\n",
    "print(tstat2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "According to scipy.stats.ttest_ind documentation, this only outputs two-tailed results, and gives a signed test statistic. For given t and p values from a two-tailed test, we reject the null hypothesis of a greater-than test when `p/2 < alpha and t > 0`, and of a less-than test when `p/2 < alpha and t < 0`. We are conducting a greater-than test and the test statistic is greater than 0, so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P-value = 0.04107821481145321\n",
      "Reject null hypothesis.\n"
     ]
    }
   ],
   "source": [
    "print_results((pval2/2), 0.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thus, we can say we are 95% confident the average length of the description of women's meetings is significantly greater than that of men's meetings."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chi square test of independence of variables\n",
    "\n",
    "A \"closed\" AA meeting is one which is more restrictive of who can attend. Another pop psych truism is that because women are much more likely to be victims of stalking and/or assault, female-focused groups are more often restrictive of who can attend in order to create a \"safe space\" for women. We can use a chi square test to examine whether the \"women\" category and \"closed\" category are correlated in this dataset.\n",
    "\n",
    "First, create a contingency table using pandas' cross-tabulation method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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>Label_Closed</th>\n",
       "      <th>0.0</th>\n",
       "      <th>1.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Label_Women</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>2943</td>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>99</td>\n",
       "      <td>213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Label_Closed   0.0  1.0\n",
       "Label_Women            \n",
       "0.0           2943  900\n",
       "1.0             99  213"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "women_closed_table = pd.crosstab(df['Label_Women'], df['Label_Closed'])\n",
    "women_closed_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.234192037470726, 0.6826923076923077)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sanity check\n",
    "900/(2943+900), 213/(99+213)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The chi square test for a contingency table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P-value = 7.766512354804441e-66\n",
      "Reject null hypothesis.\n"
     ]
    }
   ],
   "source": [
    "chi_stat, pval_chi, dof, expected = stats.chi2_contingency(women_closed_table)\n",
    "print_results(pval_chi, 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can reject the null hypothesis, which is that there is no relationship between these two variables in the population. This time we used a lower alpha value of 0.01, so we can say we are 99% confident there is a relationship.\n",
    "\n",
    "This test returns an array of the expected values if the null hypothesis was true; here is a side-by-side visual comparison of that table of expected values vs the table of actual values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>Label_Closed</th>\n",
       "      <th>0.0</th>\n",
       "      <th>1.0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Label_Women</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>2813.575451</td>\n",
       "      <td>1029.424549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>228.424549</td>\n",
       "      <td>83.575451</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Label_Closed          0.0          1.0\n",
       "Label_Women                           \n",
       "0.0           2813.575451  1029.424549\n",
       "1.0            228.424549    83.575451"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expected_table = pd.DataFrame(expected, index=women_closed_table.index, columns=women_closed_table.columns)\n",
    "expected_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "            'Your browser does not have WebSocket support. ' +\n",
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       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
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       "\n",
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       "\n",
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       "    canvas_div.setAttribute(\n",
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       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
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       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
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       "\n",
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       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
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       "        1;\n",
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       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
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       "\n",
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       "\n",
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       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
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       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
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       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
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       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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31lRaAACoS4YDcArV65I/fr11fW2bdvWZUz//v11H5CzzzlZtA3ArF8LJiUlyfLly13GfvXVV7q73rdo0cLjr59Xrlyp/lIxOjpann/+eTl//rzLuJ9++klq1qyprvOBBx5wu76rV6/qPvjnzZtXZs+eLVeuXHEZe/nyZVmyZIl07tzZ7boCuQbgG2+8oT4mf/78MnfuXLdfIH333Xe6BsTUqVPdru+3336T2NhYdVyrVq3k77//1o05e/as9O7d2+W4EAoNwKzX9thjj7k0dU+cOKHLKxUrVvT4PgrGfsrIyJCUlBR13M033+z2tO309HR55pln1ON3vnz55I8//nC7Tu3+jIqKkpiYGJk3b57L68qe3YzSNgCz9kffvn1dmkQXLlyQHj166N6r7v7uRK7/AlL7Xq1UqZLb/fDuu+9K3rx51XEdO3YM6DVoaRuAWXmvVq1a8t///tdlrHaf9enTR7e97r6gvnbtmsyZM0fdT5GRkbJhwwa322HkfX3gwAF58MEHZfPmzR4b+mfOnNF90VulShWvzX8jzbxAHjN16lTduMcee8zlPff333+reTNr/3v6LKBtAGbtz7Zt28pff/2lG3f16lXd64+IiAiZ66siuGgAAggbWYHF7Ie67777Tnewzn5NHO2HR1/fql28eFFuuukmdWy3bt1cxowePVpdPn/+/IC3e//+/erpBQkJCW6bjVqrVq1Sn7dGjRpuw742iCmKIgMHDvS5HStXrlTHlypVymvgunbtmhQrVkwdv3bt2lx5XdrTrVu3bu1xG9PT06VOnTq6fUADEAht2jm8fv36Hn/tYeQXIFp79uzRXULi5ZdfVpd9+OGH6r9HRka6/TVKluynxubJk8fr+LVr1+q+0HB3CnJGRobu14fefjklcv0DadYvl6Kjo12+CBMRmT9/vu4Dq7v52yh/m19nz55VL70RGRnp85IfO3fuVH8RlJSU5PZXjdomTa1atTyeMpeRkSHt2rXT/TcKhQagoigyZswYj+s7cuSIeo03RVE8NiCCsZ/efvttdUydOnW8XrdNRGTcuHE+M5h2fxp5z/tL2wBUFEV69OjhcWx6erru8imefmGpfV2JiYny559/elznp59+qnv+QC57o5X9dNjixYur13H0ZO3ater40qVLuzSCs3vzzTfV8ampqW7H5PRNQLSXT/jqq688jgtGA/DMmTO6Y8IjjzzicV2XLl3SfYmUkpLidpy2Aagoitx2221y9epVt2MzMzN16/T161M4Aw1AAGHhzJkzugPiSy+9FPC6fvrpJ926lixZoluu/fCYkJDg8VccWVasWKGOj46OdglUgwYNUpd//vnnAW+39lSoCRMmGHpMmzZt1Mf8+OOPLsu1QSwuLs7QhbczMjJ032B/9913HscuX75cHVeuXDm3zbqcfl07duzQ/ff1p6FIAxAIfdm/xPGnfDVmtB9w4+LiZPv27XLw4EHdr/R8zSHZG4B9+vTx+Zq0l65w9yu7zz//XF1+++23+1yfiP5mJS+++KLL8urVq6vLH3/8cUPr9MTf5tesWbPU8ffff7+h5xgyZIj6mE8++US37OTJk7pftX399dde17Vnzx5d0zUUGoBFixb1ebOYe+65Rx3v7lptwdpP2i/afvjhB6/rFLneUMtqABcsWNDtl3ja/dmgQQOf6/SXtgEYExPjs/n12GOPqeNHjx7tsjwzM1N3bU53f3PZtW3bVh3fvXv3gF+LiGsDcM6cOT4f07lzZ3X8O++843N8ZmamOm9ERES4bTDmdANw8+bNhhpwwWgAzp07V11erFgxn9fh026roijy22+/uYzJ3gDcunWr13XOmTNHHWvm7CiEDxqAAMLCX3/9pTsgvv766wGva8+ePbp1Zf/WWPvh0dM1nLQyMzN1d4n87LPPdMsnTJigLmvbtq3Hb/J80d5IY8+ePYYeoz01wV3TVBvE/Lmrsva0A28fznr16qWOe/LJJ92OyenXpb12Uf369X2uK/t/PxqAQGgLZgNQRN9EufHGG6VZs2bq/2/UqJFcu3bN6+OzNwBXrlzp8zm//fZbdXxiYqLLlymDBw9Wlxv9pbn2w2iXLl10yw4cOKDbRne/EPSHv80v7ely3m6KpbV48WL1MaNGjdIt+/LLL3Uf1I3cqEF7+nMoNAAHDBjgc53apq+7JlUw9tP//vc/dXmpUqV8ri+Ltvn1yy+/uCzX7s8ZM2YYXq9R2gZgy5YtfY7/4IMPvDZitF9O5smTx9AdYT/55BP1McWLFw/odWTRNgAjIiK8/tpZ5Popplm/GI2KijJ8k4kHHnhAfZ4vvvjCZbm/DcArV67IDz/8ILNnz5ann35aHnroId2vtrWnKHv77xSMBmC3bt3U5Q899JChddaqVUt9zNy5c12WaxuAFStW9Lm+jRs3quNvueUWQ9uA8EYDEEBYsOoXgLNnzza0Tu0NLLLfYW/Xrl26O0hWqVJFJk2aJD/99JOhcC0icvz4cd02Dxs2zNDpbNpr7ri7Xp82iD377LOGtkVE5JdfflEfV7BgQbfX2Llw4YLu1IidO3fmyusaOHCgumzEiBGGXo/2vx8NQCC0BeMagFqnTp1yuQC7oihSoEABj9cr09I2ACMiInyeDily/Rio/aVV9ufRfqjs3LmzoXlU+wVNvXr1dOvT3vG9SpUq/u0gN/xtfmlvGtK7d29Dr6dTp07qY+6++27d+p5//nl1WYcOHQxts/byHaHQAPR2Y4Es8+bNU8e7u+RHMPaTtolVsmRJw6fja78c/PLLL13Wq92fZk+PdUfbADTS3NE26Vu1auWy/N1331WX16xZ09A2HDlyRDfHHD582O/XkUXbAKxQoYLP8T/++KM6Pn/+/Ib/u9WrV89rhjbaALx48aI8/fTTuhvD+KqbbrrJ4/qC0QCsXLmyuvzDDz80tE7tKcvubmanbQB26tTJ5/p2796tjq9cubKhbUB4owEIIGxYcQ3A7M1BT7Snsbq7oPrMmTN1H960HxjbtGkjkydPdnsqQJbt27cbDkCeyt0v9bRBzMjpIFraD5wff/yxy/L33ntPXX7zzTfn2uvSfgicNm2aodfCXYCB8BHsBqDI9Tt5ar/YURRjp8iJ6BuAhQsXNvycWadEKoricqOopKQkU/NopUqVdOt76aWX1GVt2rQxvI2e+NP8OnfunOnjQvbToB966CF12bBhwwxts/Y05FBoAL755ps+16ltLrh7TcHYT6+88orp/57u/ra0+9PdF4xmaRuA2b/YdUfbYGvevLnL8pkzZ6rL3d1EyBPt3W7d/RLSKO32GTlleunSpab/u7m7rIuR9/XJkyddrs9spLw1NrXjjPL1GO1N6TzdvC+7KVOmqI/J/strEf3fqJHLQ2S/qzxAAxBA2LDiLsBGTs0SEXnqqafUx3g6bfiHH36QNm3auHxo1FbLli3d3pFt3bp1poOYu2Bu5losvkKM9vQdT6fnBON13X777eoyo7/g1P73owEIhLbcaABu375dd620+Ph4OXLkiKHHaj+wlS5d2vBzaq+9mv3YpP2CLJDK/sFR+0uwnLiulD/Nr+yX/Aiksjdg7r//fnWZkbvXi+hvghIKDUAjx3BfDcBg7CfteynQcvfaArmztD+0DUAj84ivBqD2cjDZf6Hqjba5n/0La3/42r7stL9YDLTc7Tcj71ntjWhiY2NlyJAhsmTJEtmzZ4+cO3dOd5kFow0w7XYZ5esxWTewUxRFfv31V0Pr1DbE3f1S1NffaHY0AJEdDUAAYUN7nQ9/PjRlp72YuruDZTB+Aah17Ngx+fjjj+Whhx6Sm2++2aUhmDdvXpeQpz1tOTEx0fBr9cVMA/DQoUPqtsfGxsqpU6fUZf/884/6gTQyMtLjxbOD8br4BSDgbMFuAF66dEn3C+isMvqrnmD8AlD7S5Sff/7Zr9fjjpW/ADx16pRuv54+fdr084fiLwB79+6d6w3AYOwn7S/f3N3AJlCh1gC00y8AjTQAP/vsM3V8nTp1An7e7Hy9Z//66y/1jBkjdwD/73//a1kDMNi/AKQBiEDQAAQQNrLfGSuQa76cP39ed126fv36uYwJ5BqAXbt2VR8zduxYv7bp2LFj8vLLL+uuc3LDDTfoxmgvoq0oivzzzz9+PYcnZu/G1qJFC/Xx8+bNU/9d+yvL1q1be3x8MF4X1wAEnC3YDcCRI0fqvozKulC+oijy8ssv+3x89msAnj171udjsl8DcN++fbrl2uulffTRRwG/tizaawBWrVrV9Pr8bdZof125ZcsW089vh2sAaq8XZuSGV3feeWeuNwCDsZ/ef/99j9nGjFBrAGp/UWd0Pxw9elSXkXLqGoBGGoAbNmxQxxcoUMDwNat98fWeffvtt9XlHTt29Lk+7anKud0A1P5NG513tTdJ8XUNQBqACAQNQABh4/z581KoUCH1QGfk4rjZzZgxQ3dA37hxo8sY7YfHnj17+lxnZmam7tSs7HcBNkobttx9wNNedD77nYsDZbYB+Prrr7sNlLfeeqv672+//bbXdeT069LeBTj7he3d4S7AQHgJZgPw66+/VhtxefLkkTVr1uhOgYyLi5Pt27d7XUf2uwAbucutr7sAa38t5u7mDv7K6bsAly9f3q9mzW233aaOf/755009t4g97gJct25ddX2bNm3yOb5ChQq53gAMxn76448/cvS9lCXUGoDauwBHRkb6vAuviMinn36qPiYn7wJspAF48eJFXSPezOnHWr7es9pfyD3xxBM+1/ef//zHsgag9i7A2e887slNN92kPsbXXYBpACIQNAABhBXttdoURZFPPvnE8GMPHDig+/Vf06ZN3Y7TfnhMSEjwefqR9oNZdHS0qV+xFS5cWF3Xhg0bdMu03xrWq1fP5QNgIMw2AE+fPq2enhIRESEHDx6UPXv2qOuMj4/3eYfLnH5d2pCtKIrs2rXL6/iVK1fqxtMABEJbsBqA//zzjxQvXlxd95gxY9Rl2l+B16pVy+2d0bNkbwAaudD7fffdp453dxrl4sWLdfPu0aNHA3uRGjVq1PDrg7g31atXV9e1e/dun+OnTp2qji9durSkp6ebev6TJ09KTEyMus6vv/7a6/g9e/bofnGZEw1A7Xvktdde8zp2y5YtuvdIbjUAg7WftO+l0aNH+9xOI0KtAZiZmambP1566SWf6+zYsaM6vkePHgG8CuPb5472Ws45cS1QEd/v2WnTpqnLR44c6XVdFy5ckGLFihlqgGlPpb5y5YqhbfXVAJw7d666vESJEj7nKe2dlRVFcXvzPxqAMIsGIICwcvHiRalZs6bug46RU4H//vtv3SlS8fHxHhtD2g+PiqLI0KFDvW6P9ts8dxd2PnbsmKHXlj14Zz9FaO/evboLDvvzwdbTNfjMNgBFRO6++251HVOmTJFnnnlG/f/33Xefz8cH43U1bNhQXV+bNm08/oohPT3d5U5zNACB0BasBmCHDh10X1ZoP0SeOHFC90vwhx56yON6sjcA8+TJI+vXr/c4fu3atbomy5dffuky5tq1a7rT0e644w7DH3LPnTsn58+fd/l37S8bo6OjZe3atYbW5472V2KrV6/2Of706dO6ax7279/f8JdDx44d090kIEv37t11TdqLFy+6fXxmZqa0a9dO998oJxqA2l82NWrUyOO4q1evSuPGjS1pAIoEZz8tXLhQHRMVFWXoV69ZPB3nQ60BKCIybtw4dUxSUpL89ddfHten/TWmogR22Rt/ty+777//3tD70J1Ac+fHH3+sLq9UqZJcvXrV43MMHTpUt33eGmDa+dno+8VXA/DMmTOSkJCgjvH2Rcnly5d1f9cpKSlux9EAhFk0AAGEne3bt+suvBsdHS1PPvmkHD9+3GXs5cuX5a233pLk5GR1fEREhLz11lse16/98JjVkBs9erTLLzr+97//6e44GxMTIzt27HBZX0pKirRr104+/PBDtx+yRET+/PNPad26tbquKlWquB2nDaRZ4cDT6X2yMM8AACAASURBVDTXrl2TFStWSO/evaVEiRJux+REA/Dzzz/XfVioUqWK+v+/+uorQ+vI6de1atUq3fp69uwpZ86c0Y05evSotGnTRvffmQYgEPqC0QB89dVX1XXmy5dPfv/9d5cxK1euVBt1ERERHn89pf3AFh0drTYD3I1fvny57tIXzZo189gIW7Fihe7LlIYNG0paWprH1/TLL7/IE088IYUKFXJ72nL2RlR8fLy8+uqrbhuLly9fliVLlni8yYP2g7qvG2VlyX7d3/bt23v84i4zM1M2bNggw4cP9/jL8507d+pOabzjjjtcmhRnz55VT6fWHhdyogF44MAB3U2/Hn/8cZdG5aFDh9TjknZbc7MBGIz9dO3aNWnZsqUuL02ZMsVjJjp37py8//77kpKS4vGOuaHYADx58qSuEVWtWjX56aefXMYtWrRId21RI9fCy4ntc0f7HouIiJBHH33Ubd4WuX6DpM8//1w6d+4s9evX97k+d+/ZkydPSnx8vC6/aW8yJ3K98TZo0CB1PjbSAEtNTVXHTZ061dBr99UAFNH/WllRFHn66afl8uXLujFHjhzRNcujoqI8XgaABiDMogEIICxt375dd922rAPqbbfdJr169ZIBAwZI27ZtdY3CrNC5aNEir+vWfnicPn26Gm4LFy4sd999twwaNEjatGmjC8iK4vl0Du36oqOjpW7dunLvvffK4MGDpUePHtK4cWPdh4LIyEhZvny523VlZmbqwlPW+Hr16kmvXr1k6NChct9990mTJk10pzsnJSW5XV9ONACvXLkiSUlJum1SFEWSk5O9fnMbzNclIjJq1Cjd+hISEqRTp04yaNAgadeunXo6SPny5XV3PqQBCIQ27Zxbv359GT58uOH6z3/+47K+nTt3St68edV1am94lJ32hgjFixd3+wvw7B/YtHPVTTfdJH379pW+ffu63Gk4OTlZ9u7d6/W1z5s3T9cEVJTrXyjdc889MmTIEOnTp4+0bt1a96WYoiger1t46NAh3Zc6inL9GoQdOnSQQYMGSb9+/SQlJUUKFCggiqJIwYIF3a5nxYoVunXceuut8sADD8jo0aPVcvfaxo4dq3tcRESE1KpVS3r06CFDhgyRXr16SUpKiu7XgoqieLz0hPbuxllNtrZt28qgQYOkc+fO6utITEzUNYByogEoIjJs2DDd85ctW1Z69eolAwcOlJSUFDVv3H777dKrVy9LGoAiwdlPx48f110HUVGuN5Vbtmwp/fr1k8GDB0u3bt2kdu3aamNcUTyfehqKDUARkTVr1ugaXBEREdKwYUMZMGCA9OrVy+XvrUqVKjlyg7RAG4CXLl3SfUGdlaWbNGkiffr0kSFDhkj37t2lfv36utNsb7nlFrfrM/Ke1f5SMit/t23bVgYOHCjt27dXm36RkZHy1ltvGWqAaX/RHBERISkpKTJixAjdHHTy5EndY7Tb4ElGRobuVO2sbJr1eSE1NdXl88LMmTM9ro8GIMyiAQggbB09elSGDh0qUVFRLs0nd9WqVSv5+eeffa5X++Fx9erV8sUXX7g0ErMHoVmzZnlcn/a0MV+VnJwsn3/+uc9tfOWVV3S/CvFWERERcuedd7pdT040AEVcT8NQFN/Xbgnm6xK53lQcPXq07tS57FWlShXZsWOH30EfgH1lv4yDP5W9gXX58mXdZQI8/cLN03h3c1T2D2xXrlxRf83iqSpXruzz5iJZvvvuO5cmgre64YYbvN5d9MSJE9KlSxdD6ypVqpTH9WgbWu7K06nBixcvlpIlSxp+PQ0aNPB6DcYXX3xR96u17FWsWDH54Ycf/P4gbkR6errLabPZq0OHDnLq1ClDx+dgNQBFgrOfLl686Fduy5s3r0yaNMntukK1ASgisnHjRqlYsaLP19+qVascaf75u33ZXbt2TcaOHatrXHqr6OhoGT58uNt1GXnPXrt2Tfr06eP1ORITE+Wzzz4z3AC7evWqpKSkeF1n9veRdpk3V69elREjRrh8+ZK9ChYs6PPvlAYgzKIBCCDs7d+/X2bOnClt2rSRSpUqSUJCgsTFxUmZMmWkUaNG8tRTT8nmzZsNry97A1Dk+im6Y8aMkVq1akliYqLkzZtXqlSpIiNGjHB7EV+tzMxM+fHHH2XatGly1113Sc2aNaVAgQISGRkp8fHxUq5cOenYsaPMnTvX5TRVb86ePSuvvvqqdO7cWSpUqCD58+eXqKgoKVSokNSqVUu6d+8ur732mhw8eNDjOnKqAbh+/XqXoOPt1DNvcuJ1aW3atEn69OkjZcuWldjYWClatKg0bNhQZsyYoe5vGoBA+MjJBuAjjzyiLitRooSha7pm/8Vg9js9evrA9u2338q9994rFSpUkLi4OClcuLA0btxYZs6c6fdNMDIyMuTjjz+W/v37S40aNaRQoUISGRkpCQkJUrlyZenQoYNMmjTJ7emHnqSlpcnDDz8sderUkSJFikhkZKTkz59fqlevLt27d5eFCxd6PKVT5Pqx8IMPPpAOHTpI6dKldb8W0h5v3bl06ZIsXLhQevToIZUrV5aCBQtKZGSkFChQQGrUqCFdu3aVmTNnuj01250dO3bIAw88IJUqVVL3dd26deW5555Tb6ASjAagyPX98N5770nr1q2lSJEiEh0dLaVKlVIvFZJ1irfVDUCR4O2n/fv3y4QJEyQlJUVKlSolcXFxEhMTI0WLFpVbb71VBg8eLIsXL/aaiUK5AShy/cuCN954Qzp27ChlypSR2NhYyZ8/v1SuXFn69esn33zzjfkXYWL73Pnnn3/khRdekNTUVClbtqzEx8dLdHS0JCUlyc033yx9+/aVhQsXem1a+vOeXbp0qXTs2FGSk5MlOjpakpOTpV69ejJhwgT1Swt/GmBXrlyR1157Te644w4pXry4S4M70AZgll9//VUeeeQRqV27thQuXFiio6OlWLFictttt8nkyZM9njqtRQMQZtEABAAAAGyCD2wAACAYaAACAAAANkEDEAAABAMNQAAAAMAmaAACAIBgoAEIAAAA2AQNQAAAEAw0AAEAAACboAEIAACCgQYgAAAAYBM0AAEAQDDQAAQAAABsggYgAAAIBhqAAAAAAAAAQBijAQgAAAAAAACEMRqAAAAAAAAAQBijAQgAAAAAAACEMRqAAAAAAAAAQBijAQgAAAAAAACEMRqAAAAAAAAAQBijAQhLpKenS1pamqSlpcn+/fvl0KFDFEVRFOWo2r9/v3osTE9Pt/rQHLbIHBRFUZTTi8wBERqAsEhaWpooikJRFEVRlKJIWlqa1YfmsEXmoCiKoqh/i8zhXDQAYQnCOEVRFEX9W4Tx4CFzUBRFUdS/ReZwLhqAsMT+/ft1E5DVP4mmKIqiqNwubWNq//79Vh+awxaZg6IoinJ6kTkgQgMQFjl06JA6AR06dMjqzQEAINdxLMwd7GcAgNNxLIQIDUBYhAkIAOB0HAtzB/sZAOB0HAshQgMQFmECAgA4HcfC3MF+BgA4HcdCiNAAhEWYgAAATsexMHewnwEATsexECI0AGERJiAAgNNxLMwd7GcAgNNxLIQIDUBYhAkIAOB0HAtzB/sZAOB0HAshQgMQFmECAgA4HcfC3MF+BgA4HcdCiNAAhEWYgAAATsexMHewnwEATsexECI0AGERJiAAgNNxLMwd7GcAgNNxLIQIDUBYhAkIAOB0HAtzB/sZAOB0HAshQgMQFmECAgA4HcfC3MF+BgA4HcdCiNAAhEWYgIDQkp6eLn///bfs27dPdu/eTVGOr3379smhQ4fkzJkzkpGREdDfFcfC3MF+BkILmYOiXGvfvn3y999/S3p6ekB/VxwLIUIDEBZhAgJCQ2Zmphw+fFh27txJUZSH2rVrl5w9e9bvvy+OhbmD/QyEBjIHRRmrw4cPS2Zmpl9/XxwLIUIDEBZhAgJCw7Fjx1xCh9XfgFKUHWrXrl26v4tAmoAcC3MH+xkIDWQOivJc2f82jh075tffF8dCiNAAhEWYgAD7u3z5si5oHD9+XK5du2b1ZgG2kJmZKefPn5eDBw/qmoD+nA7MsTB3sJ8B+yNzAN5du3ZNjh8/rvs7uXz5suHHcyyECA1AWIQJCLC/EydOqAHj6NGjVm8OYEuZmZm6JuCZM2cMP5ZjYe5gPwP2R+YAjDl69Kj6t3LixAnDj+NYCBEagLAIExBgf9qmRqAXHAac4Pz58+rfij/HNI6FuYP9DNgfmQMwJj09Xf1bOXjwoOHHcSyECA1AWIQJCLC/vXv3qqc1+nuhYcBJMjMz1WsC7tu3z/DjOBbmDvYzYH9kDsAYbebYu3ev4cdxLIQIDUBYhAkIsL+sCw7v3r3b6k0BbC+QvxeOhbmD/QzYH5kDMI7MgUDRAIQlmIAA+yOMA8YRxu2L/QzYH5kDMI7MgUDRAIQlmIAA+yOMA8YRxu2L/QzYH5kDMI7MgUDRAIQlmIAA+yOMA8YRxu2L/QzYH5kDMI7MgUDRAIQlmIAA+yOMA8YRxu2L/QzYH5kDMI7MgUDRAMxFR48elaVLl8rYsWMlNTVVkpKS1D/Cvn37+r2+5cuXS5cuXaRUqVISExMjpUqVki5dusjy5csNr+PChQsybdo0qV+/vhQqVEjy5csn1atXl9GjR8uff/7p9zYZxQQE2F8oh/Gs+WX8+PGWbsf+/fvVbVmwYIGl2+JJKGxjbilXrlzAx2S7hXEyx7/IHID9kTnMC4XjeShsY24Jp8yB0EEDMBdl/cG5K3/+8DMzM2Xw4MFe1zd48GDJzMz0up69e/dKtWrVPK6jYMGCsmzZMpOv2j0mIMD+zITx1atXWxqInRbGz58/L2+88Ybcc889UqVKFUlMTJTo6GgpWrSoNGzYUEaNGiUbN260dBtDQTiFcTLHv8gcgP2ROcwjc4SWcMocCB00AHORNuiWKVNGWrduHVAYf/LJJ9XH1a1bVz744ANJS0uTDz74QOrWrasue+qppzyu49y5c1K9enV17KBBg2TVqlWyYcMGmThxouTPn18URZH4+Hj55ZdfcuDV6zEBAfZHGDcvN4Lu/PnzpVixYl4bNFlVv359Wb9+fa5vY6gIpzBO5vgXmQOwPzKHeWSO0BJOmQOhgwZgLho3bpwsXbpUjhw5IiL6CdDoH/6ePXskKipKFEWRevXqycWLF3XLL1y4IPXq1RNFUSQqKkr27t3rdj3jx49Xn3vatGkuyzds2KA+T0pKin8v1AAmIMD+COPmBTPoZmRkyAMPPKCuP0+ePNK5c2eZP3++rF69Wn788Uf5+uuvZfr06dK0aVN1XKdOnXJtG0NNOIVxMse/yByA/ZE5zCNzhJZwyhwIHTQALRRIGB82bJj6GE8/rd64caM6ZsSIES7Lr1y5IomJiaIoitSoUUMyMjLcrmfIkCHqerZu3Wr4dRnBBATYH2HcvGAG3WeffVZdd6VKleTnn3/2Ov6HH36QunXrEsa9COcwTuYgcwB2RuYwj8wRWsI5c8C+aABayN8wnpmZKaVKlRJFUaR69epex2ZdZ6d06dIu1+X59ttv1eedMmWKx3VoQ/2TTz5p6DUZxQQE2B9h3LxgBd0ff/xRIiMjRVEUKV68uPz999+GHpeeni6LFy/OlW0MReEcxskcZA7Azsgc5pE5Qks4Zw7YFw1AC/kbxvft26eOHzJkiNex2gt2//HHH7plY8eO9fmNvojI1atXJV++fKIoijRr1szQazKKCQiwP6vC+Pnz52XRokVy//33S+3ataVAgQISFRUlRYoUkWbNmsn06dPl3LlzXteR/blXrFghHTt2lOLFi0tsbKxUqFBBhg8fbnj++e233+TBBx+UmjVrSoECBSQuLk4qVKgg/fr1kx9//NHj44IVdO+++251vR999JGpdRndxsuXL8urr74qLVq0kCJFikh0dLQUK1ZM2rZtK++8847HX3Zl+f3332XEiBFyww03SL58+SQ6OlpKlCghtWvXlv79+8uiRYvk0qVLHh9/8uRJmTBhgjRs2FCSkpIkJiZGSpQoIXfeead88sknhl7rsmXLJDU1VYoUKSJ58+aVKlWqyKhRo+Tw4cMiEt5hnMxB5gDsjMzxLzIHmcMXu2cO2BcNQAv5G8a//PJLdfzMmTO9jp0xY4Y6Nvtd9bST+KlTp7yu56abbhJFUaRo0aI+t88fTECA/VkVxps3b64+1lNVqFBBdu3a5XEd2ud+5plnPK6nQIECsmbNGq/b89xzz6nXJ3NXERERMm7cOLePDUYYP336tPpNfNmyZX2GYF+MbOOBAwekRo0aXv+bNG3aVE6cOOH28R9++KHExMT4/O+6fft2t49ftmyZehqpp2rfvr3XD2kPPfSQx8cmJyfL1q1bwzqMkznIHICdkTmuI3OQOYywe+aAfdEAtJC/YXzu3LnqeF/fvnz00Ufq2Ndee0237NZbbxVFUSRfvnw+n7N9+/bqerx9S5LdoUOHvFZaWhoTEGBzVoXxJk2aSK1ateSpp56Szz77TDZv3iybNm2SxYsXS/fu3SVPnjyiKIpUq1ZN0tPT3a4j67mzblBQrVo1eeONN2TLli2ycuVKGTJkiLqehIQEOXDggNv1aH+91LhxY3n99ddl48aNsnXrVnnvvfekUaNG6vKXX37Z5fHBCOPaxszQoUNNr8/XNp47d04qVqyojuncubMsWbJEtm7dKh999JHuw1OjRo3k2rVruscfOXJE/WVXcnKyPPfcc/Ltt9/Ktm3bZMOGDfLuu+/K4MGDpUiRIm7D+Lfffqt++ChfvrxMnTpVvv/+e9m2bZssXbpUevXqpT5/165d3b7GF154QR1TsmRJeeWVV2Tz5s2yZs0aeeyxxyQmJkbKly8vRYsWDdswTuYgcwB2RuYgc4iQOYyye+aAfdEAtJC/YXzatGnq+OXLl3sd+9VXX6ljX3jhBd2ymjVriqIoUqxYMZ/Pec8996jrOX78uM/xWXx946ItJiDAnqwK476eb8WKFWqQfv31192O0c4xN998s9tvad9++211zN133+2yPC0tTX2ep59+2u3zZGRkqGEwISHB5RdOwQjjEydOVNc5b9480+vztY2PPvqoutzdfsjMzJSePXuqY+bMmaNb/sYbb6jLPH3bLnL9WkHZ7zJ7/vx5KVasmCiKIq1bt5YLFy64fey8efPU51i5cqVu2ZEjRyQ+Pl4URZFy5cq5vXbRqlWrdL+4CMcwTuYgcwB2RuYgc4iQOYyye+aAfdEAtJC/Yfy5555Tx69atcrr2FWrVqljJ0yYoFuW9a1KmTJlfD5n7969A5ooCOP/3/gCVKiXg9n5gtydO3cWRVGkQ4cObpdr55ity98VObzNbbVt2UQURZGoqCj537ZvdMvuane7KIoit9xUQzL/+tHjOk7tXCOxsddPNZk/faxu2f5N/35zvmDGMx7X4U+NGvRv8P1iwUzT6/O2jZf+2CSJBRNEURSpWbWiXDu4xe06zvy2VpIKJarjtMsmPj5cFEWRQokF/N62V55/TBRFkbi4ODl69KjX90SDBg1EURTp2bOn7t+nTp2qvr6PP/7Y4+MfeOCBsA7jZA4yBxUC5WBkDjIHmcM4u2cO2BcNQAuF87fxnI7z/1kdJCnCuAl2CeP//POP7N69W7Zv367WoEGDvDYVsp67Vq1aXsPeR//377z6/quT1H+/cmCzxOeNE0VRZPKYB32Gxnq1r8+rA7p3CnoYH3hfl3+/eV40N6hhfP3nC9Rl055+yOt6HujTTR2r/WDz5ozx6r9//uYMv7at1W3XTx9t06aNz/dJ1q8GKlasqPv3O+644/qHgUKF5OrVqx4fv2XLlrAO42QOMgcVAuVgZA4yB5nDOLtnDtgXDUALhfP1eHxxzARkdZCkCOMmWBnG161bJ/fcc48ULlzY66958ubN6/bxWcsHDBjgNez9mbZMHfvkg/+O/fnbRV6f11O1a9k06GE8N7+N/7+pT6nL1nwy3+t6Fs58Vh377Qdz1H8/vv079Rv9iIgISWlcT2aMf0S2Ln/X47f7WZX1OH8qPj5e914oXry4KIoiLVu29Pqeu3r1qnrR8HAM42QOMgcVAuVgZA4yB5nDOLtnDtgXDUAL+RvGly5dqo43c0e+u+66S13GHfmCzOogSRHGTbAqjI8fP96v8OVO1rInnnjCa9i79McmdezQ3ner//7tB3MCCuMtGtULehjPOr1FURSZN+3poIbxyWMeVJf9tuZTr+v5+r3Z6thFcybrlq399HUpVTzZZX8VSMgvXdu1lKULZ7ms78qBzQH9N8j+noiNjRVFUaR79+4+33tZwT0cwziZg8xBhUA5GJmDzEHmMM7umQP2RQPQQv6G8X379qnjhwwZ4nXs4MGD1bF//PGHbpn2DlMbN270uI6rV6+qd1Fq1qyZoddklGMmIKuDJEUYN8GKML5y5Ur1cRUrVpQ5c+bIf//7Xzl9+rTuTm/aecydrGVjxowJKIwvf/cV9d+nj31Ytq/60FD9sXFp0MP4l2+95Habgx3Gf1/7mdf1aPdZ9jAuh7dJ+r6N8u4rz8t9XdpK6RLFXAJ0mxaN5MLe9brxWcvuuece3elYvkorK4z36NHD5/sv6+Lf4RjGyRxkDioEysHIHGQOModxds8csC8agBbyN4xnZmZKyZIlRVEUqV69utex1atXF0VRpFSpUpKZmalb9s0336jPO2XKFI/r2Lhxo/6AloMcMwFZHSQpwrgJVoTxe++9VxRFkcTERK8XYB4xYoShMB7o6Thpy95R/33SEyOCEnQDrdO71khkZKQoiiLlSpeQjENbgxbGc+J0HE+1b8MSeXnCY1K1Yjn1cQ8PvE83JuuaSK1bt/b3LajidJzryBxkDioEysHIHGQOModxds8csC8agBbyN4yL6O8Y5OmbdG2IHjZsmMvyy5cvS8GCBUVRFKlRo4ZLWM8yZMgQdT1paWmGX5cRjpmArA6SFGHcBCvC+I033iiKokjXrl29jmvYsKGhMO7rgtwfz5uujtVekPvC3vUSExMtiuJ6io3VYVwOb5O727dS1/vJ/OlBC+P+XJB7WF/3F+T2VWd+W6t+O1+yeFHdsib164iiXL9+3IULF/x5C6qyLshduHBhrxfk3rp1q9/HZC27h3EyB5mDCoFyMDIHmYPMYZzdMwfsiwaghQIJ47///rtERUWJoihSr149uXjxom75xYsXpV69eqIo128x72lS0P6Ufdq0aS7LN2zYoD5P8+bN/X1pPjlmArI6SFKEcROsCONZvyRKTU31OOann35S1+0rjCuKItu+ed9jEGzXsqkoiiKRkZEuAbJtyybqOjZ/+batwvjW5e9Knjx51AB79JeVhh536Y9NsnjuFMPbeOmPTepFsW+oVsnjBbTP/v6DFCmcKIqiSM2qFf1+PV3apoiiKBITE63796lPjfR6rDJi6tSp6jo+/fRTj+OGDRsW1mGczEHmoEKgHIzMQeYgcxhn98wB+6IBmIt++OEHWbBggVrTp//7LVCTJk10yxYsWOBxPU888YT6uLp168qiRYtky5YtsmjRIqlbt666zNspNGfPnpWqVauqYwcPHizfffedbNy4USZNmiT58+cXRbl+t6uffvopx/eFYyYgq4MkRRg3wYow3rFjR1EURfLnzy/79u1zWf7PP//IDTfc4FcYr1e7ppzfs94lAL43e6I65q52t7ssX/f5mxIRESGKokiFsqVk7/ovPIbJawe3yHuzJ8qhLctzJYzL4W0ybtQgdd1VKpSV/65c7HX8hi8WyM21qkunNi382sZHh/ZWl499eJDL8sy/fpQ+d3dQx8yZpL8G0tfvzfb67fzpXWvUi3VXq1Ret+zMb2vVkB8bGytfffWV1/fPunXrZM2aNbp/O3LkiOTNm1cURZHy5cvLkSNHXB73/fffqw2ocAnjZI5/kTmokCkHI3OQOcgcxtktcyB00ADMRX379tUdIHyVJxkZGTJgwACvj73//vslIyPD6/bs2bNHqlSp4nEdBQoUkKVLl+b0bhARB01AVgdJijBuQk6F8U6dOrk0G9zVnj175KOPPlIfV7p0aXnllVdkw4YNsn79epk+fbqUKFFCIiIipFGjRobCeNavk6pXLi8LZjwjW5e/K6sWvyYP9OmmfpudkD+f7N/0pdugOP6Rf29ukD9fvDx0fw9Z9vbLsu2b92XjkoXywZzJMvL+HlKyeFFRFEW2r/ow18J4xqGtMrhnV3X9efLkka7tWsobL46TNZ/Ml23fvC/fvP+qvDjuEWne6JZ//3v4GcbP/v6DVCxXWh3TpW2KLF04S378+j35eN50adGonrqs0S03uXxj37dbR4mOjpJ2LZvKrGcflZWL5sq2b96XNZ/Ml1cnPiE1qlRQHz/r2Uddnn/FB3PVoJwnTx7p1q2b2oTasmWLLFmyRMaPH6/eQfaVV15xeT+88MIL6nOUKlVKZs+eLWlpabJ27Vp54oknJDY2VsqVKydFixYNmzBO5vgXmYMKmXIwMgeZg8xhnN0yB0IHDcBclFNhPMuyZcukU6dOUrJkSYmJiZGSJUtKp06dfH5boXX+/HmZOnWq1KtXTxITEyU+Pl6qVasmo0aNkgMHDph5uV45ZgKyOkhShHETciqMG62sXyH179/f45jIyEiZNWuWjB8/3lAYHz9+vC5QuzQdEvLL9x97v9D0zGdGS2xsjM/tj4mJlj3rPs+1MJ5Vcyc/KUWTChnax43r1Za0Ze/4vY37N30p1SuX97ruJvXryIlfV7s8tm+3joa2bXi/ezxeXHzVqlXqhbV91VtvveX2PTFy5EiPjylSpIhs2bJFypUrFzZhnMzxLzIHFTLlYGSObWQOModhdsscCB00AGEJx0xAVgdJijBuglVhXETknXfekdtuu00SEhLUb0p79+4tmzdvFhHxK4zL4eunhLS/vakUK5okMTHRUr5MSRnWt5vLBpKlRAAAIABJREFU6TOe6q+tX8vYhwdJw5trSZHCiRIVFSX54vNK1Yrl5K52t8trU56UY9tXuQ2xwQ7jcnibnNu9TuZPHyt3t28llcqXlgIJ+SU6OkqKJhWShjfXkkcG93IJ4f5u4+X9m2X2xMeleaNbJKlQokRHR0mxokmSmtJY3nl5gscgfWrnGvlk/nQZ2vtuqVe7ppQqniwxMdGSNy5OqlYsJ/3u6SjrPn/T+2sUkQsXLsjs2bMlNTVVSpQoITExMRIXFydlypSR1q1by8SJE+W3337z+r5ctmyZtGnTRgoXLixxcXFSuXJlGTlypHocIoyHJ8fsZ6uPlxSZwwQyx79F5iBz+ELmQKBoAMISjpmArA6SFGHcBDNh3FaCFICpXKwQQBi3L8fsZ6uPlxSZwwQyB2WbCgFkDgSKBiAs4ZgJyOogSRHGTSCMU7apEEAYty/H7Gerj5cUmcMEMgdlmwoBZA4EigYgLOGYCcjqIEkRxk0gjFO2qRBAGLcvx+xnq4+XFJnDBDIHZZsKAWQOBIoGICzhmAnI6iBJEcZNIIxTtqkQQBi3L8fsZ6uPlxSZwwQyB2WbCgFkDgSKBiAs4ZgJyOogSRHGTSCMB6fO71kv21d9GFBdObDZ8u0njLtHGLcvx+xnq4+XFJnDBDJHcIrMEUCFADIHAkUDEJZwzARkdZCkCOMmEMaDU6s/muf33Qqzav+mLy3ffsK4e4Rx+3LMfrb6eEmROUwgcwSnyBwBVAggcyBQNABhCcdMQFYHSYowbgJhPDhFGA+gQgBh3L4cs5+tPl5SZA4TyBzBKTJHABUCyBwIFA1AWMIxE5DVQZIijJtAGKdsUyGAMG5fjtnPVh8vKTKHCWQOyjYVAsgcCBQNQFjCMROQ1UGSIoybQBinbFMhgDBuX47Zz1YfLykyhwlkDso2FQLIHAgUDUBYwjETkNVBkiKMm0AYp2xTIYAwbl+O2c9WHy8pMocJZA7KNhUCyBwIFA1AWMIxE5DVQZIijJtAGKdsUyGAMG5fjtnPVh8vKTKHCWQOyjYVAsgcCBQNQFjCMROQ1UGSIoybQBinbFMhgDBuX47Zz1YfLykyhwlkDso2FQLIHAgUDUBYwjETkNVBkiKMm0AYp2xTIYAwbl+O2c9WHy8pMocJZA7KNhUCyBwIFA1AWMIxE5DVQZIijJtAGKdsUyGAMG5fjtnPVh8vKTKHCWQOyjYVAsgcCBQNQFjCMROQ1UGSIoybQBinbFMhgDBuX47Zz1YfLykyhwlkDso2FQLIHAgUDUBYwjETkNVBkiKMm0AYp2xTIYAwbl+O2c9WHy8pMocJZA7KNhUCyBwIFA1AWMIxE5DVQZIijJtAGKdsUyGAMG5fjtnPVh8vKTKHCWQOyjYVAsgcCBQNQFjCMROQ1UGSIoybQBinbFMhgDBuX47Zz1YfLykyhwlkDso2FQLIHAgUDUBYwjETkNVBkiKMm0AYp2xTIYAwbl+O2c9WHy8pMocJZA7KNhUCyBwIFA1AWMIxE5DVQZIijJtAGKdsUyGAMG5fjtnPVh8vKTKHCWQOyjYVAsgcCBQNQFjCMROQ1UGSIoybQBinbFMhgDBuX47Zz1YfLykyhwlkDso2FQLIHAgUDUBYwjETkNVBkiKMm0AYp2xTIYAwbl+O2c9WHy8pMocJZA7KNhUCyBwIFA1AWMIxE5DVQZIijJtAGHdm/Zm2TEYP6S3VK5eX+LxxUiixgNSvc4NMH/uwXNi7Psee54M5k6V184ZSPLmIxMbGSLnSJaRX13aycclCwjhylGP2s9XHS4rMYQKZw5lF5ggMmQOBogEISzhmArI6SFKEcRMI486rL996SQoWyK/Oz9mrWqXysm/DElPPkb5vo3RodZvH58iTJ4889+gDhHHkGMfsZ6uPlxSZwwQyh/OKzBE4MgcCRQMQlnDMBGR1kKQI4yaEShgv9/iXYVu5GcR//naRxOeNE0VRJH++eJn4+HDZ8MUCWbX4NRnUs4s6Z1evXF7O7V4X8PPc16Wtuq6UxvXk8zdnSNqyd+SNF8dJpfKl1WXzp48ljCNHOGY/W328pMgcJpA57FFkjm1Wv8UMIXMgUDQAYQnHTEBWB0mKMG4CYdz6ys0GYItG9URRFImKipINXyxwWT7t6YfUefvZR4cG9BzffzxfXUfHO5rJtYNbdMuPbV8lZUsVF0VRpFBiATm1cw1hHKY5Zj9bfbykyBwmkDnsUWSObVa/xQwhcyBQNABhCcdMQFYHSYowbgJh3PrKrSCetuwddU4e0usut2MyDm2VGlUqqEH5yoHNfj9Pu5ZNRVEUiYyMlENblrsd88Gcyeq2vDB2FGEcpjlmP1t9vKTIHCaQOexRZI5tVr/FDCFzIFA0AGEJx0xAVgdJijBuAmHc+sqtBuCTDw5Q5+RNS9/yOG7ymAfVcd9+MMev5zi3e53ExsaIoiiSmtLY47jL+zdLgYTr1wRqXK82YRymOWY/W328pMgcJpA57FFkjm1Wv8UMIXMgUDQAYQnHTEBWB0mKMG4CYdz6yq0G4G231hVFUSRffF65+meax3Ebvligzt3jRg3y6zlWLX5NfezkMQ96Hdu6eUP11KArBzZb/RYzhDBuX47Zz1YfLykyhwlkDnsUmYPMgfBGAxCWcMwEZHWQpAjjJhDGra/cagAWKZwoiqJI7ZpVvY47ueN7de7u1uEOv55j9sTH1cd+9saLXseOvL+HOnbH6o+tfosZQhi3L8fsZ6uPlxSZwwQyhz2KzEHmQHijAQhLOGYCsjpIUoRxEwjj1lduBPH0fRvV+bj97U19js8Xn1cURZGGN9fy63keH95PfZ4tX73rdez0sQ+rY79+b7bVbzFDCOP25Zj9bPXxkiJzmEDmsEeROcgcCG80AGEJx0xAVgdJijBuAmHc+sqNBuA//12lzsf33tna5/jkIoVFURS5sXplv55nWN9u6vPsWvOJ17FzJo1Rx348b7rVbzFDCOP25Zj9bPXxkiJzmEDmsEeROcgcCG80AGEJx0xAVgdJijBuAmHc+sqNBuDBtK/U+bj3Xe19ji9TsrgoiiKVypf263kGdO+kPs++DUu8jn3jxXHq2HdenmD1W8wQwrh9OWY/W328pMgcJpA57FFkDjIHwhsNQFjCMROQ1UGSIoybQBi3vnKjAci38TmDMG5fjtnPVh8vKTKHCWQOexSZg8yB8EYDEJZwzARkdZCkCOMmEMatr9xoAHI9npxBGLcvx+xnq4+XFJnDBDKHPYrMQeZAeKMBCEs4ZgKyOkhShHETCOPWV240AOVw7tyR75XnH+OOfNk45lhoMcfsZ6uPlxSZwwQyhz2KzEHmQHijAQhLOGYCsjpIUoRxEwjj1lduNQBvu7WuKIoi+eLzytU/0zyO2/DFAnXuHjdqkF/PsWrxa+pjJ4950OvY1s0biqIoEhUVJZf3b7b6LWYIYdy+HLOfrT5eUmQOE8gc9igyB5kD4Y0GICzhmAnI6iBJEcZNIIxbX7nVABwzor86J29a+pbHcZPHPKiO++b9V/16jrO//yAxMdGiKIqkpjT2OO7y/s1SICG/KIoijW656fq/hwDCuH05Zj9bfbykyBwmkDnsUWSObVa/xQwhcyBQNABhCcdMQFYHSYowbgJh3PrKrQbg5i/fVufkIb3ucjsm49BWqVGlgiiKIokFE+TKgc1+P0/blk3Ub9kPbVnudswHcyar2zLt6YcI4zDNMfvZ6uMlReYwgcxhjyJzbLP6LWYImQOBogEISzhmArI6SFKEcRMI49ZXbjUA5fC/p+RERUXJhi8WuCyf9vRD6rw9/pHBLssXzHjG63I5rD8l587WzeXawS265ce2r5KypYqrgf/kju8J4zDNMfvZ6uMlReYwgcxhjyJzbLP6LWYImQOBogEISzhmArI6SFKEcRMI49ZXbjYAt33zvuSNixNFUSR/vniZ9MQI2bhkoXz34f/J4J5d1Tm7asVycvb3HwIK43J4m3Tv1EYdl9K4nnyxYKZs+epdeXPGeKlUvrS67LUpT/77uBBAGLcvx+xnq4+XFJnDBDKHPYrMsc3qt5ghZA4EigYgLOGYCcjqIEkRxk0gjFtfudkAlMPbZMmCmeq1cNxV1YrlZM+6z90+1mgYv7h3g7Rr2dTjc+TJk8f18SGAMG5fjtnPVh8vKTKHCWQOexSZY5vVbzFDyBwIFA1AWMIxE5DVQZIijJtAGLe+crsBKIe3yYHNX8qoQT2lasVyEp83ThILJki92jVl6lMj5cLe9R4fZzSMZ9V7syfKHc0aSnKRwhITEy1lShaX+7q0dXsqUCggjNuXY/az1cdLisxhApnDHkXm2Gb1W8wQMgcCRQMQlnDMBGR1kKQI4yaEShj3yYImGpXDFQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcco2FQII4/blmP1s9fGSInOYQOagbFMhgMyBQNEAhCUcMwFZHSQpwrgJhHHKNhUCCOP25Zj9bPXxkiJzmEDmoGxTIYDMgUDRAIQlHDMBWR0kKcK4CYRxyjYVAgjj9uWY/Wz18ZIic5hA5qBsUyGAzIFA0QCEJRwzAVkdJCnCuAmEcefU0V9WytKFs2Tsw4MkNaWxJBVKVOfovt06BuU5P5gzWVo3byjFk4tIbGyMlCtdQnp1bScblywkjCNHOWY/W328pMgcJpA5nFNkDvPIHAgUDUBYwjETkNVBkiKMm0AYd05lzcfuKqfDePq+jdKh1W0eny9Pnjzy3KMPEMaRYxyzn60+XlJkDhPIHM4pMod5ZA4EigYgLOGYCcjqIEkRxk0ImTBu9XskmGVBGC9Tsri0bt4waGH8vi5t1XWnNK4nn785Q9KWvSNvvDhOKpUvrS6bP30sYRw5wjH72er5ijJfDkbmsEmROax+hxlC5kCgaADCEo6ZgKw+iFPmy8EI4zaoXGoAjhs1SJYunCVHfl4hcnib7N/0ZVDC+Pcfz1fX2/GOZnLt4Bbd8mPbV0nZUsVFURQplFhATu1cQxiHaY7Zz1bPV5T5cjAyh02KzGH1O8wQMgcCRQMQlnDMBGT1QZwyXw5GGLdB5VIDMHsFK4y3a9lUFEWRyMhIObRludsxH8yZrD73C2NHEcZhmmP2s9XzFWW+HIzMYZMic1j9DjOEzIFA0QCEJRwzAVl9EKfMl4MRxm1QYdQAPLd7ncTGxoiiKJKa0tjjuMv7N0uBhPyiKIo0rlebMA7THLOfrZ6vKPPlYGQOmxSZw+p3mCFkDgSKBiAs4ZgJyOqDOGW+HIwwboMKowbgqsWvqeucPOZBr2OzrgcUFRUlVw5stvodZghh3L4cs5+tnq8o8+VgZA6bFJnD6neYIWQOBIoGICzhmAnI6oM4Zb4cjDBugwqjBuDsiY+r6/zsjRe9jh15fw917I7VH1v9DjOEMG5fjtnPVs9XlPlyMDKHTYrMYfU7zBAyBwJFAxCW+H/snX+Q33V95z/Aso6l0ooW6W6k/mhh67TW7S3WorVVx996mWhb5WY6WDLdDJHWepWWkKsycN5V5ELb80rm2qrM2UlsOK4KybYwsVztsNMEnVYxmQQ2zMAALUFqDKxG2O/r/qB8jpi839nsd5Pn5/N6Ph4zj3/YzZK85/t6PV99UtBmAalDHIfXGI7xDpioAPy9D36g/Zk7t32u+r2f/P3fbr/3r//iU+pP2KLgGO8uNu+s3lc4vMZwc3REbg71J2xRcHPAUqEABAk2C0gd4ji8xnCMd8BEBeDai3+l/Zm7/+//rn7vn/yXde333vQ/P6n+hC0KjvHuYvPO6n2Fw2sMN0dH5OZQf8IWBTcHLBUKQJBgs4DUIY7DawzHeAdMVABe8v6V7c+cu/OL1e/98//20fZ7/9cfX6P+hC0KjvHuYvPO6n2Fw2sMN0dH5OZQf8IWBTcHLBUKQJBgs4DUIY7DawzHeAdMVADyT+OPxCYLxdi8s3pf4fAaw83REbk51J+wRcHNAUuFAhAk2CwgdYjj8BrDMd4BExWA/Pd4jsQmC8XYvLN6X+HwGsPN0RG5OdSfsEXBzQFLhQIQJNgsIHWI4/AawzHeARMVgP/9P/8u/4t834dNFoqxeWf1vsLhNYaboyNyc6g/YYuCmwOWCgUgSLBZQOoQx+E1hmO8AyYqALd/fmP7M//rut+sfu9bfvE10TRNjIyMxKH7/kH9CVsUHOPdxead1fsKh9cYbo6OyM2h/oQtCm4OWCoUgCDBZgGpQxyH1xiO8Q6YqAD89p4vx+jo6dE0TbztDRcWv+/Qff8QZz7vB6Npmvj5f/fKp/96D+AY7y4276zeVzi8xnBzdERuDvUnbFFwc8BSoQAECTYLSB3iOLzGcIx3wEQFYDz41Xj7G1/b/lP2B3bOHPV7Nv3Jf23/3tf+pw9xjMPQ2Lyzel/h8BrDzdERuTnUn7BFwc0BS4UCECTYLCB1iOPwGsMx3gF7VAB+ZsNV7a/52H+cPur3PPtfyfn3b/nFeOr+nYd9ff/Xt8e54+dE0zTxwz/0vHjsG3dwjMPQ2Lyzel/h8BrDzdERuTnUn7BFwc0BS4UCECTYLCB1iOPwGsMx3gFP0vH95f/z5/GZDVe1Pvt/Ee+1F7zqsK99ZsNVSz7G48GvxvtXvrX9vjdcOBVf+Mz1sXPb5+LTGz4WL3/JivZrG//gyv//63oAx3h3sXln9b7C4TWGm6MjcnOoP2GLgpsDlgoFIEiwWUDqEMfhNYZjvAOepALw4l95d7uTF+Mwx/j8vXfGO974uuLPPvXUU4/89T2AY7y72Lyzel/h8BrDzdERuTnUn7BFwc0BS4UCECTYLCB1iOPwGsMx3gETFoDP+Bef+ni8+fWvibNfeFaMjp4eLx47J/7DqrfHnV/4zJHf3wM4xruLzTur9xUOrzHcHB2Rm0P9CVsU3BywVCgAQYLNAlKHOA6vMb05xo/FSSrR8ATaAzjGu4vNO6vzErk5hoCbAztjD+DmgKVCAQgSbBaQ+pBEjvEh4BjHztgDOMa7i807q/MSuTmGgJsDO2MP4OaApUIBCBJsFpD6kESO8SHgGMfO2AM4xruLzTur8xK5OYaAmwM7Yw/g5oClQgEIEmwWkPqQRI7xIeAYx87YAzjGu4vNO6vzErk5hoCbAztjD+DmgKVCAQgSbBaQ+pBEjvEh4BjHztgDOMa7i807q/MSuTmGgJsDO2MP4OaApUIBCBJsFpD6kESO8SHgGMfO2AM4xruLzTur8xK5OYaAmwM7Yw/g5oClQgEIEmwWkPqQRI7xIeAYx87YAzjGu4vNO6vzErk5hoCbAztjD+DmgKVCAQgSbBaQ+pBEjvEh4BjHztgDOMa7i807q/MSuTmGgJsDO2MP4OaApUIBCBJsFpD6kESO8SHgGMfO2AM4xruLzTur8xK5OYaAmwM7Yw/g5oClQgEIEmwWkPqQRI7xIeAYx87YAzjGu4vNO6vzErk5hoCbAztjD+DmgKVCAQgSbBaQ+pBEjvEh4BjHztgDOMa7i807q/MSuTmGgJsDO2MP4OaApUIBCBJsFpD6kESO8SHgGMfO2AM4xruLzTur8xK5OYaAmwM7Yw/g5oClQgEIEmwWkPqQRI7xIeAYx87YA/bs2cMx3lFs3lmdl8jNMQTcHNgZewAFICwVCkCQYLOA1IckcowPwdzcXOzatSt2794dCwsL6t/O0lEfkpj+GH/qqadi165dsWvXrpibm1v0r7PJQjE276zOS+TmGAJuDuyMHWdhYSF2797NzQFLggIQJNgsIPUhiRzjQ/Dggw+2pcaBAwfUv52loz4kMf0x/uijj7az8vDDDy/619lkoRibd1bnJXJzDAE3B3bGjnPgwIF2Vh566KFF/zqbLIQqFIAgwWYBqQ9J5BgfgoMHD7YHxp49e+LAgQP9/Kfy6kMSUx7jg8EgvvOd78S//Mu/tHOya9eu+O53v7von2GThWJs3lmdl8jNMQTcHNgZO8rCwkIcOHCg/U+O7Nq1Kw4ePLjoX2+ThVCFAhAk2Cwg9SGJHONDMBgM4r777jus3Ni9e3fs3bu3X379Luy76s/QUXzmX795tg8++OBxzZhNFoqxeWd1XiI3xxBwc2BnVH+GFnl33HfffTEYDBY9YzZZCFUoAEGCzQJSH5LIMT4kCwsLRxzkvfPOv8a+q/4MLcL9+/cf1yEeYZSFYmzeWZ2XyM0xJNwc2AnVn6FFeN999x33/4esTRZCFQpAkGCzgNSHJHKMLwODwSAOHjwYDz30UMzNzcn/Cehxu/V/YN9Vf4aO4r333hv3339/fPOb34xDhw4tabZsslCMzTur8xK5OZYBbg6Uq/4MFZybm4uHHnooDh48eNz/wDHCKAuhCgUgSLBZQOpDEjnGQf8ZQuawgE0WirF5Z/WcIrsO9J8hZA4L2GQhVKEABAk2C0gdYMgRAPrPEDKHBWyyUIzNO6vnFNl1oP8MIXNYwCYLoQoFIEiwWUDqAEOOANB/hpA5LGCThWJs3lk9p8iuA/1nCJnDAjZZCFUoAEGCzQJSBxhyBID+M4TMYQGbLBRj887qOUV2Heg/Q8gcFrDJQqhCAQgSbBaQOsCQIwD0nyFkDgvYZKEYm3dWzymy60D/GULmsIBNFkIVCkCQYLOA1AGGHAGg/wwhc1jAJgvF2Lyzek6RXQf6zxAyhwVsshCqUACCBJsFpA4w5AgA/WcImcMCNlkoxuad1XOK7DrQf4aQOSxgk4VQhQIQJNgsIHWAIUcA6D9DyBwWsMlCMTbvrJ5TZNeB/jOEzGEBmyyEKhSAIMFmAakDDDkCQP8ZQuawgE0WirF5Z/WcIrsO9J8hZA4L2GQhVKEABAk2C0gdYMgRAPrPEDKHBWyyUIzNO6vnFNl1oP8MIXNYwCYLoQoFIEiwWUDqAEOOANB/hpA5LGCThWJs3lk9p8iuA/1nCJnDAjZZCFUoAEGCzQJSBxhyBID+M4TMYQGbLBRj887qOUV2Heg/Q8gcFrDJQqhCAQgSbBaQOsCQIwD0nyFkDgvYZKEYm3dWzymy60D/GULmsIBNFkIVCkCQYLOA1AGGHAGg/wwhc1jAJgvF2Lyzek6RXQf6zxAyhwVsshCqUACCBJsFpA4w5AgA/WcImcMCNlkoxuad1XOK7DrQf4aQOSxgk4VQhQKwpxw6dCj+7M/+LN761rfGOeecE6Ojo3HGGWfEeeedF7/+678es7Ozi/o5MzMzsWrVqhgfH4/R0dEYHx+PVatWxczMzAn9/dssIHWAIUcA6D9DyBwW6EsWcnP0BPWcIrsO9J8hZA4L2GQhVKEA7CH3339//PRP/3Q7wCU//OEPx2AwOOrPGAwGMT09Xf3109PTxV8/LDYLSB1gyBEA+s8QMocF+pCF3Bw9Qj2nyK4D/WcImcMCNlkIVSgAe8aTTz552CH+yle+Mj772c/G7Oxs3HbbbfHRj340zjjjjPbr11577VF/zpVXXtl+z+TkZGzatCl27NgRmzZtisnJyfZr69evPyF/DpsFpA4w5AgA/WcImcMCXc9Cbo6eoZ5TZNeB/jOEzGEBmyyEKhSAPeOmm25qB/fnf/7n46mnnjrie+666644/fTTo2maeP7znx9PPvnkYV+/5557YmRkJJqmiampqZifnz/s60888URMTU1F0zQxMjIS995777L/OWwWkDrAkCMA9J8hZA4LdD0LuTl6hnpOkV0H+s8QMocFbLIQqlAA9owPf/jD7eB+8YtfLH7fqlWr2u/7+te/ftjX1q5d236t9N/tmZ2dbb/nsssuW9Y/Q4TRAlIHGHIEgP4zhMxhga5nITdHz1DPKbLrQP8ZQuawgE0WQhUKwJ7xwQ9+sB3cu+++u/h9H/nIR9rvu+uuu9q/PhgMYnx8PJqmiYmJierf6/zzz4+maWLFihXL/t/lsVlA6gBDjgDQf4aQOSzQ9Szk5ugZ6jlFdh3oP0PIHBawyUKoQgHYM/7oj/7ouP5p/CnIa4VeAAAgAElEQVSnnBIHDhxo//rc3Fz769esWVP9ez37P9i9b9++ZfszRBgtIHWAIUcA6D9DyBwW6HoWcnP0DPWcIrsO9J8hZA4L2GQhVKEA7BmPPPJInHnmmdE0Tbz2ta896n+P56tf/WqMjo5G0zRx0UUXHfa1W2+9tR3866+/vvr32rBhQ/u9W7duXdY/h80CUgcYcgSA/jOEzGGBrmchN0fPUM8psutA/xlC5rCATRZCFQrAHnLzzTfHc5/73PZ/Te/GG2+M2dnZuP322+Oqq66K5z3vedE0TbzqVa+Khx9++LBfe8MNN7SDv2XLlurfZ8uWLe33bty48bh+jw888EDVHTt2eCwgdYAhRwDoP0PIHBbowzHOzdEj1HOK7DrQf4aQOSzQh5sDTjwUgD3lG9/4RqxevTpOOeWUdpCf8UUvelFs2LAhHn/88SN+3bXXXtt+38zMTPXvsW3btvZ7r7vuuuP6/X3/76lm6gWkDjDkCAD9ZwiZwwJ9Oca5OXqCek6RXQf6zxAyhwX6cnPAiYUCsId873vfi/Xr18fZZ59dPHAvuOCCuPXWW4/4tVdffXX7Pdu3b6/+fbZv395+7zXXXHNcv0eO8X9DHWDIEQD6zxAyhwX6cIxzc/QI9Zwiuw70nyFkDgv04eaAEw8FYM94/PHH4/Wvf300TROnnXZa/O7v/m7s3r07Dh06FAcOHIjbbrstXve610XTPP0f4/7DP/zDw379yfqn8fzrOP+GOsCQIwD0nyFkDgt0/Rjn5ugZ6jlFdh3oP0PIHBbo+s0BJwcKwJ7xO7/zO+3gfvaznz3q9zz55JPxhje8IZqmiVNPPTX+6Z/+qf3ayfrv8RwLmwWkDjDkCAD9ZwiZwwJdz0Jujp6hnlNk14H+M4TMYQGbLIQqFIA9YjAYxFlnnRVN08R5551X/d6///u/bwf8t3/7t9u/fsstt7R/nf9FvpOAOsCQIwD0nyFkDgt0OQu5OXqIek6RXQf6zxAyhwVsshCqUAD2iIcffrgd2ve9733V7/3Od77Tfu/b3va29q/Pzc21f33NmjXVnzE9Pd1+7759+5blz/AMNgtIHWDIEQD6zxAyhwW6nIXcHD1EPafIrgP9ZwiZwwI2WQhVKAB7xP79+9uhfe9731v93m9/+9vt977rXe9q//pgMIixsbFomiYmJiaqP2NiYiKaponx8fEYDAbL8md4BpsFpA4w5AgA/WcImcMCXc5Cbo4eop5TZNeB/jOEzGEBmyyEKhSAPWJhYSHOPPPMaJomxsbG4sknnyx+77P/tZvf/M3fPOxrl156afu12dnZo/762dnZ9nvWrl27rH+OCKMFpA4w5AgA/WcImcMCXc5Cbo4eop5TZNeB/jOEzGEBmyyEKhSAPeOiiy5qB/eqq6466vc89thj8YpXvKL9vr/5m7857Ot79uyJkZGRaJompqamYn5+/rCvz8/Px9TUVDRNEyMjI7F3795l/3PYLCB1gCFHAOg/Q8gcFuh6FnJz9Az1nCK7DvSfIWQOC9hkIVShAOwZu3fvjh/4gR9oh/fd73533HTTTfHVr3417rzzztiwYUOce+657dff9KY3HfXnXHHFFe33TE5OxubNm2Pnzp2xefPmmJycbL+2bt26E/LnsFlA6gBDjgDQf4aQOSzQ9Szk5ugZ6jlFdh3oP0PIHBawyUKoQgHYQ26//fZ44Qtf2A5wyTe+8Y3x2GOPHfVnLCwsxCWXXFL99atXr46FhYUT8mewWUDqAEOOANB/hpA5LNCHLOTm6BHqOUV2Heg/Q8gcFrDJQqhCAdhTHn300fjEJz4Rv/RLvxQ/8iM/Eqeffno897nPjZe+9KXxq7/6q/FXf/VXi/qPaG/dujVWrlwZY2NjMTo6GmNjY7Fy5crYtm3bCf392ywgdYAhRwDoP0PIHBboSxZyc/QE9Zwiuw70nyFkDgvYZCFUoQAECTYLSB1gyBEA+s8QMocFbLJQjM07q+cU2XWg/wwhc1jAJguhCgUgSLBZQOoAQ44A0H+GkDksYJOFYmzeWT2nyK4D/WcImcMCNlkIVSgAQYLNAlIHGHIEgP4zhMxhAZssFGPzzuo5RXYd6D9DyBwWsMlCqEIBCBJsFpA6wJAjAPSfIWQOC9hkoRibd1bPKbLrQP8ZQuawgE0WQhUKQJBgs4DUAYYcAaD/DCFzWMAmC8XYvLN6TpFdB/rPEDKHBWyyEKpQAIIEmwWkDjDkCAD9ZwiZwwI2WSjG5p3Vc4rsOtB/hpA5LGCThVCFAhAk2CwgdYAhRwDoP0PIHBawyUIxNu+snlNk14H+M4TMYQGbLIQqFIAgwWYBqQMMOQJA/xlC5rCATRaKsXln9Zwiuw70nyFkDgvYZCFUoQAECTYLSB1gyBEA+s8QMocFbLJQjM07q+cU2XWg/wwhc1jAJguhCgUgSLBZQOoAQ44A0H+GkDksYJOFYmzeWT2nyK4D/WcImcMCNlkIVSgAQYLNAlIHGHIEgP4zhMxhAZssFGPzzuo5RXYd6D9DyBwWsMlCqEIBCBJsFpA6wJAjAPSfIWQOC9hkoRibd1bPKbLrQP8ZQuawgE0WQhUKQJBgs4DUAYYcAaD/DCFzWMAmC8XYvLN6TpFdB/rPEDKHBWyyEKpQAIIElwX0Y793K/ZcSID6kESO8QIuWajG5p3Vc4rsOtB/hpA5LGCThVCFAhAkuCwgdXmFFIAQ+kMSOcYLuGShGpt3Vs8psutA/xlC5rCATRZCFQpAkOCygNTlFVIAQugPSeQYL+CShWps3lk9p8iuA/1nCJnDAjZZCFUoAEGCywJSl1dIAQihPySRY7yASxaqsXln9Zwiuw70nyFkDgvYZCFUoQAECS4LSF1eIQUghP6QRI7xAi5ZqMbmndVziuw60H+GkDksYJOFUIUCECS4LCB1eYUUgBD6QxI5xgu4ZKEam3dWzymy60D/GULmsIBNFkIVCkCQ4LKA1OUVUgBC6A9J5Bgv4JKFamzeWT2nyK4D/WcImcMCNlkIVSgAQYLLAlKXV0gBCKE/JJFjvIBLFqqxeWf1nCK7DvSfIWQOC9hkIVShAAQJLgtIXV4hBSCE/pBEjvECLlmoxuad1XOK7DrQf4aQOSxgk4VQhQIQJLgsIHV5hRSAEPpDEjnGC7hkoRqbd1bPKbLrQP8ZQuawgE0WQhUKQJDgsoDU5RVSAELoD0nkGC/gkoVqbN5ZPafIrgP9ZwiZwwI2WQhVKABBgssCUpdXSAEIoT8kkWO8gEsWqrF5Z/WcIrsO9J8hZA4L2GQhVKEABAkuC0hdXiEFIIT+kESO8QIuWajG5p3Vc4rsOtB/hpA5LGCThVCFAhAkuCwgdXmFFIAQ+kMSOcYLuGShGpt3Vs8psutA/xlC5rCATRZCFQpAkOCygNTlFVIAQugPSeQYL+CShWps3lk9p8iuA/1nCJnDAjZZCFUoAEGCywJSl1dIAQihPySRY7yASxaqsXln9Zwiuw70nyFkDgvYZCFUoQAECS4LSF1eIQUghP6QRI7xAi5ZqMbmndVziuw60H+GkDksYJOFUIUCECS4LCB1eYUUgBD6QxI5xgu4ZKEam3dWzymy60D/GULmsIBNFkIVCkCQ4LKA1OUVUgBC6A9J5Bgv4JKFamzeWT2nyK4D/WcImcMCNlkIVSgAQYLLAlKXV0gBCKE/JJFjvIBLFqqxeWf1nCK7DvSfIWQOC9hkIVShAAQJLgtIXV4hBSCE/pBEjvECLlmoxuad1XOK7DrQf4aQOSxgk4VQhQIQJLgsIHV5hRSAEPpDEjnGC7hkoRqbd1bPKbLrQP8ZQuawgE0WQhUKQJDgsoDU5RVSAELoD0nkGC/gkoVqbN5ZPafIrgP9ZwiZwwI2WQhVKABBgssCUpdXSAEIoT8kkWO8gEsWqrF5Z/WcIrsO9J8hZA4L2GQhVKEABAkuC0hdXiEFIIT+kESO8QIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAEGCywJSBxhyBEDoyyukACzgkoVqXN5ZnZfIzQHMYQaz4pKFUIcCECS4LCB1gCFHAIS+vEIKwAIuWajG5Z3VeYncHMAcZjArLlkIdSgAQYLLAlIHGHIEQOjLK6QALOCShWpc3lmdl8jNAcxhBrPikoVQhwIQJLgsIHWAIUcAhL68QgrAAi5ZqMblndV5idwcwBxmMCsuWQh1KABBgssCUgcYcgRA6MsrpAAs4JKFalzeWZ2XyM0BzGEGs+KShVCHAhAkuCwgdYAhRwCEvrxCCsACLlmoxuWd1XmJ3BzAHGYwKy5ZCHUoAHvM/v374xOf+ERceOGF8aIXvShGR0fjR3/0R+PVr351fOQjH4k777zzmD9jZmYmVq1aFePj4zE6Ohrj4+OxatWqmJmZOaG/d5cFpA4w5AiA0JdXSAFYoE9ZyM3RfdR5idwcwBxmMCsuWQh1KAB7yl/+5V/GC17wgnaIj+bKlSuLv34wGMT09HT1109PT8dgMDghv3+XBaQOMOQIgNCXV0gBWKAvWcjN0Q/UeYncHMAcZjArLlkIdSgAe8iNN94Yp556ajRNE2effXZ87GMfi9tvvz2+8pWvxNatW+OP//iP481vfnP88i//cvFnXHnlle0CmJycjE2bNsWOHTti06ZNMTk52X5t/fr1J+TP4LKA1AGGHAEQ+vIKKQAL9CELuTn6gzovkZsDmMMMZsUlC6EOBWDP2LVrVzznOc+JpmniF37hF+Jb3/pW8XsPHTp01L9+zz33xMjISDRNE1NTUzE/P3/Y15944omYmpqKpmliZGQk7r333mX9M0T4LCB1gCFHAIS+vEIKwAJdz0Jujn6hzkvk5gDmMINZcclCqEMB2DPe9KY3RdM08cIXvjD279+/pJ+xdu3advhnZ2eP+j2zs7Pt91x22WXD/JaPissCUgcYcgRA6MsrpAAs0PUs5OboF+q8RG4OYA4zmBWXLIQ6FIA9Yvfu3e3QXnXVVUv6GYPBIMbHx6NpmpiYmKh+7/nnnx9N08SKFSuW/b/L47KA1AGGHAEQ+vIKKQALdDkLuTn6hzovkZsDmMMMZsUlC6EOBWCPuPrqq9uh/cY3vtH+9cceeyz27t0bjz766DF/xtzcXPsz1qxZU/3eZ/8Hu/ft2zf07//ZuCwgdYAhRwCEvrxCCsACXc5Cbo7+oc5L5OYA5jCDWXHJQqhDAdgj3vGOd0TTNPFDP/RDMRgM4nOf+1y88pWvPOx/Re+lL31pXHXVVXHw4MGj/oxbb721/d7rr7+++vfbsGFD+71bt25d1j+LywJSBxhyBEDoyyukACzQ5Szk5ugf6rxEbg5gDjOYFZcshDoUgD3iJS95STRNEz/zMz8TH/zgBw87wr/fn/qpn4oHH3zwiJ9xww03tN+zZcuW6t9vy5Yt7fdu3LjxuH6vDzzwQNUdO3ZYLCB1gCFHAIS+vEIKwAJdPsa5OfqHOi+RmwOYwwxmpcs3B5w8KAB7xJlnnhlN07T/i3w//MM/HBs3boxHHnkkvvvd78bOnTvj7W9/ezvYF154YSwsLBz2M6699tr26zMzM9W/37Zt29rvve66647r91r7PxS+38wLSB1gyBEAoS+vkAKwQJePcW6O/qHOS+TmAOYwg1np8s0BJw8KwB5x2mmntUN72mmnHfV/TW9hYeGwg/z7/4n7s/+bPtu3b6/+/bZv395+7zXXXHNcv1eO8adRBxhyBEDoyyukACzQ5WOcm6N/qPMSuTmAOcxgVrp8c8DJgwKwR5xxxhnt0L7//e8vft/dd9/dft973vOew752sv5pPP86ztOoAww5AiD05RVSABbo8jHOzdE/1HmJ3BzAHGYwK12+OeDkQQHYI84555x2aG+88cbq946Pj0fTNPHiF7/4sL9+sv57PMfCZQGpAww5AiD05RVSABbochZyc/QPdV4iNwcwhxnMiksWQh0KwB5xwQUXLPpfpXnNa17T/rd7ns0tt9zS/gz+F/lOPOoAQ44ACH15hRSABbqchdwc/UOdl8jNAcxhBrPikoVQhwKwR3zgAx9oh/a2226rfu8zh/sZZ5xx2F+fm5trf8aaNWuqP2N6err93n379g39+382LgtIHWDIEQChL6+QArBAl7OQm6N/qPMSuTmAOcxgVlyyEOpQAPaIT3/60+3Q3nDDDdXvfcELXhBN08R555132F8fDAYxNjYWTdPExMRE9WdMTExE0zQxPj4eg8Fg6N//s3FZQOoAQ44ACH15hRSABbqchdwc/UOdl8jNAcxhBrPikoVQhwKwRzz66KNx+umnR9M08eY3v7n4fXfccUc73KtXrz7i65deemn79aP9r/pFRMzOzrbfs3bt2mX7MzyDywJSBxhyBEDoyyukACzQ5Szk5ugf6rxEbg5gDjOYFZcshDoUgD3j2Yf0pk2bjvj6t7/97XjVq17Vfs+OHTuO+J49e/bEyMhINE0TU1NTMT8/f9jX5+fnY2pqKpqmiZGRkdi7d++y/zlcFpA6wJAjAEJfXiEFYIGuZyE3R79Q5yVycwBzmMGsuGQh1KEA7BmPPPJInHvuue2hfNlll8WXvvSluOuuu+Izn/lM+6/QNE0Tl156afHnXHHFFe33TU5OxubNm2Pnzp2xefPmmJycbL+2bt26E/LncFlA6gBDjgAIfXmFFIAFup6F3Bz9Qp2XyM0BzGEGs+KShVCHArCH7Nq1K378x3+8HeCjeckll8T3vve94s9YWFiISy65pPozVq9eHQsLCyfkz+CygNQBhhwBEPryCikAC/QhC7k5+oM6L5GbA5jDDGbFJQuhDgVgT3n88cfjk5/8ZPzcz/1cnHXWWTE6OhorVqyI973vffGlL31p0T9n69atsXLlyhgbG4vR0dEYGxuLlStXxrZt207g795nAakDDDkCIPTlFVIAFuhLFnJz9AN1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4G8v2CsAACAASURBVLKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQpAkOCygNQBhhwBEPryCikAC7hkoRqXd1bnJXJzAHOYway4ZCHUoQAECS4LSB1gyBEAoS+vkAKwgEsWqnF5Z3VeIjcHMIcZzIpLFkIdCkCQ4LKA1AGGHAEQ+vIKKQALuGShGpd3VuclcnMAc5jBrLhkIdShAAQJLgtIHWDIEQChL6+QArCASxaqcXlndV4iNwcwhxnMiksWQh0KQJDgsoDUAYYcARD68gopAAu4ZKEal3dW5yVycwBzmMGsuGQh1KEABAkuC0gdYMgRAKEvr5ACsIBLFqpxeWd1XiI3BzCHGcyKSxZCHQrARFx++eXtUDdNE3/7t397zF8zMzMTq1ativHx8RgdHY3x8fFYtWpVzMzMnNDfq8sCUgcYcgRA6MsrpAAs0Ocs5OboHuq8RG4OYA4zmBWXLIQ6FIBJ+Md//McYGRlZ9DE+GAxienr6sO//fqenp2MwGJyQ36/LAlIHGHIEQOjLK6QALNDXLOTm6CbqvERuDmAOM5gVlyyEOhSACVhYWIgLLrggmqaJs88+e1HH+JVXXtl+3+TkZGzatCl27NgRmzZtisnJyfZr69evPyG/Z5cFpA4w5AiA0JdXSAFYoI9ZyM3RXdR5idwcwBxmMCsuWQh1KAATcP3110fTNDExMRHr1q075jF+zz33tP/kfmpqKubn5w/7+hNPPBFTU1PRNE2MjIzEvffeu+y/Z5cFpA4w5AiA0JdXSAFYoI9ZyM3RXdR5idwcwBxmMCsuWQh1KAB7zv333x8/+IM/2B7fH/vYx455jK9du7b9ntnZ2aN+z+zsbPs9l1122bL/vl0WkDrAkCMAQl9eIQVggb5lITdHt1HnJXJzAHOYway4ZCHUoQDsOe9617uiaZq4+OKLIyKOeYwPBoMYHx9v/+l9jfPPPz+apokVK1Ys+3+Xx2UBqQMMOQIg9OUVUgAW6FsWcnN0G3VeIjcHMIcZzIpLFkIdCsAe8/nPfz6apomzzjorHnnkkYg49jE+NzfXfn3NmjXVn//s/2D3vn37lvX37rKA1AGGHAEQ+vIKKQAL9CkLuTm6jzovkZsDmMMMZsUlC6EOBWBP+dd//dc455xzomma+NM//dP2rx/rGL/11lvbr19//fXVv8eGDRva7926deuy/v5dFpA6wJAjAEJfXiEFYIG+ZCE3Rz9Q5yVycwBzmMGsuGQh1KEA7Cm/8Ru/EU3TxIUXXnjYvypzrGP8hhtuaL++ZcuW6t9jy5Yt7fdu3LjxuH5/DzzwQNUdO3ZYLCB1gCFHAIS+vEIKwAJ9Oca5OfqBOi+RmwOYwwxmpS83B5xYKAB7yJe//OU45ZRTYmRkJL72ta8d9rVjHePXXntt+/WZmZnq32fbtm3t91533XXH9Xt85tctxswLSB1gyBEAoS+vkAKwQB+OcW6O/qDOS+TmAOYwg1npw80BJx4KwJ5x6NCh+Mmf/MlomiYuv/zyI75+rGP86quvbr++ffv26t9r+/bt7fdec801x/X75Bh/GnWAIUcAhL68QgrAAl0/xrk5+oU6L5GbA5jDDGal6zcHnBwoAHvGM8f2ueeeG48//njx6+p/Gs+/jvM06gBDjgAIfXmFFIAFun6Mc3P0C3VeIjcHMIcZzErXbw44OVAA9ojdu3fH6OhoNE0TX/jCF476PV357/EcC5cFpA4w5AiA0JdXSAFYoMtZyM3RP9R5idwcwBxmMCsuWQh1KAB7xPT0dDRNEy972cti06ZNR/W9731vO9i///u/3/71Z/7J/S233NJ+nf9FvhOPOsCQIwBCX14hBWCBLmchN0f/UOclcnMAc5jBrLhkIdShAOwRF1988XH9d26e7X333RcREXNzc+1fW7NmTfXv98zx3zRN7Nu3b1n/LC4LSB1gyBEAoS+vkAKwQJezkJujf6jzErk5gDnMYFZcshDqUAD2iOU4xgeDQYyNjUXTNDExMVH9+01MTETTNDE+Ph6DwWBZ/ywuC0gdYMgRAKEvr5ACsECXs5Cbo3+o8xK5OYA5zGBWXLIQ6lAAJuNY/z2eiIhLL720/Z7Z2dmjfs/s7Gz7PWvXrl3236fLAlIHGHIEQOjLK6QALND3LOTm6BbqvERuDmAOM5gVlyyEOhSAyVjMMb5nz54YGRmJpmliamoq5ufnD/v6/Px8TE1NRdM0MTIyEnv37l3236fLAlIHGHIEQOjLK6QALND3LOTm6BbqvERuDmAOM5gVlyyEOhSAyVjMMR4RccUVV7TfNzk5GZs3b46dO3fG5s2bY3Jysv3aunXrTsjv02UBqQMMOQIg9OUVUgAW6HsWcnN0C3VeIjcHMIcZzIpLFkIdCsBkLPYYX1hYiEsuuaT63/BZvXp1LCwsnJDfp8sCUgcYcgRA6MsrpAAs0Pcs5OboFuq8RG4OYA4zmBWXLIQ6FIDJWOwx/gxbt26NlStXxtjYWIyOjsbY2FisXLkytm3bdkJ/ny4LSB1gyBEAoS+vkAKwQN+zkJujW6jzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44ACH15hRSABVyyUI3LO6vzErk5gDnMYFZcshDqUACCBJcFpA4w5AiA0JdXSAFYwCUL1bi8szovkZsDmMMMZsUlC6EOBSBIcFlA6gBDjgAIfXmFFIAFXLJQjcs7q/MSuTmAOcxgVlyyEOpQAIIElwWkDjDkCIDQl1dIAVjAJQvVuLyzOi+RmwOYwwxmxSULoQ4FIEhwWUDqAEOOAAh9eYUUgAVcslCNyzur8xK5OYA5zGBWXLIQ6lAAggSXBaQOMOQIgNCXV0gBWMAlC9W4vLM6L5GbA5jDDGbFJQuhDgUgSHBZQOoAQ44AYA4zmBWXLFTj8s7qOUV2HTCHGcyKSxZCHQpAkOCygNQBhhwBwBxmMCsuWajG5Z3Vc4rsOmAOM5gVlyyEOhSAIMFlAakDDDkCgDnMYFZcslCNyzur5xTZdcAcZjArLlkIdSgAQYLLAlIHGHIEAHOYway4ZKEal3dWzymy64A5zGBWXLIQ6lAAggSXBaQOMOQIAOYwg1lxyUI1Lu+snlNk1wFzmMGsuGQh1KEABAkuC0gdYMgRAMxhdoINPAAAIABJREFUBrPikoVqXN5ZPafIrgPmMINZcclCqEMBCBJcFpA6wJAjAJjDDGbFJQvVuLyzek6RXQfMYQaz4pKFUIcCECS4LCB1gCFHADCHGcyKSxaqcXln9Zwiuw6YwwxmxSULoQ4FIEhwWUDqAEOOAGAOM5gVlyxU4/LO6jlFdh0whxnMiksWQh0KQJDgsoDUAYYcAcAcZjArLlmoxuWd1XOK7DpgDjOYFZcshDoUgCDBZQGpAww5AoA5zGBWXLJQjcs7q+cU2XXAHGYwKy5ZCHUoAEGCywJSBxhyBABzmMGsuGShGpd3Vs8psuuAOcxgVlyyEOpQAIIElwWkDjDkCADmMINZcclCNS7vrJ5TZNcBc5jBrLhkIdShAAQJLgtIHWDIEQDMYQaz4pKFalzeWT2nyK4D5jCDWXHJQqhDAQgSXBaQOsCQIwCYwwxmxSUL1bi8s3pOkV0HzGEGs+KShVCHAhAkuCwgdYAhRwAwhxnMiksWqnF5Z/WcIrsOmMMMZsUlC6EOBSBIcFlA6gBDjgBgDjOYFZcsVOPyzuo5RXYdMIcZzIpLFkIdCkCQ4LKA1AGGHAHAHGYwKy5ZqMblndVziuw6YA4zmBWXLIQ6FIAgwWUBqQMMOQKAOcxgVlyyUI3LO6vnFNl1wBxmMCsuWQh1KABBgssCUgcYcgQAc5jBrLhkoRqXd1bPKbLrgDnMYFZcshDqUACCBJcFpA4w5AgA5jCDWXHJQjUu76yeU2TXAXOYway4ZCHUoQAECS4LSB1gyBEAzGEGs+KShWpc3lk9p8iuA+Ywg1lxyUKoQwEIElwWkDrAkCMAmMMMZsUlC9W4vLN6TpFdB8xhBrPikoVQhwIQJLgsIHWAIUcAMIcZzIpLFqpxeWf1nCK7DpjDDGbFJQuhDgUgSHBZQOoAQ44AYA4zmBWXLFTj8s7qOUV2HTCHGcyKSxZCHQpAkOCygNQBhhwBwBxmMCsuWajG5Z3Vc4rsOmAOM5gVlyyEOhSAIMFlAakDDDkCgDnMYFZcslCNyzur5xTZdcAcZjArLlkIdSgAQYLLAlIHGHIEAHOYway4ZKEal3dWzymy64A5zGBWXLIQ6lAAggSXBaQOMOQIAOYwg1lxyUI1Lu+snlNk1wFzmMGsuGQh1KEABAkuC0gdYMgRAMxhBrPikoVqXN5ZPafIrgPmMINZcclCqEMBCBJcFpA6wJAjAJjDDGbFJQvVuLyzek6RXQfMYQaz4pKFUIcCECS4LCB1gCFHADCHGcyKSxaqcXln9Zwiuw6YwwxmxSULoQ4FIEhwWUDqAEOOAGAOM5gVlyxU4/LO6jlFdh0whxnMiksWQh0KQJDgsoDUAYYcAcAcZjArLlmoxuWd1XOK7DpgDjOYFZcshDoUgCDBZQGpAww5AoA5zGBWXLJQjcs7q+cU2XXAHGYwKy5ZCHUoAEGCywJSBxhyBABzmMGsuGShGpd3Vs8psuuAOcxgVlyyEOpQAIIElwWkDjDkCADmMINZcclCNS7vrJ5TZNcBc5jBrLhkIdShAAQJLgtIHWDIEQDMYQaz4pKFalzeWT2nyK4D5jCDWXHJQqhDAQgSXBaQOsCQIwCYwwxmxSUL1bi8s3pOkV0HzGEGs+KShVCHAhAkuCwgdYAhRwAwhxnMiksWqnF5Z/WcIrsOmMMMZsUlC6EOBSBIcFlA6gBDjgBgDjOYFZcsVOPyzuo5RXYdMIcZzIpLFkIdCkCQ4LKA1AGGHAHAHGYwKy5ZqMblndVziuw6YA4zmBWXLIQ6FIAgwWUBqQMMOQKAOcxgVlyyUI3LO6vnFNl1wBxmMCsuWQh1KABBgssCUgcYcgQAc5jBrLhkoRqXd1bPKbLrgDnMYFZcshDqUACCBJcFpA4w5AgA5jCDWXHJQjUu76yeU2TXAXOYway4ZCHUoQAECS4LSB1gyBEAzGEGs+KShWpc3lk9p8iuA+Ywg1lxyUKoQwEIElwWkDrAkCMAmMMMZsUlC9W4vLN6TpFdB8xhBrPikoVQhwIQJLgsIHWAIUcAMIcZzIpLFqpxeWf1nCK7DpjDDGbFJQuhDgUgSHBZQOoAQ44AYA4zmBWXLFTj8s7qOUV2HTCHGcyKSxZCHQpAkOCygNQBhhwBwBxmMCsuWajG5Z3Vc4rsOmAOM5gVlyyEOhSAIMFlAakDDDkCgDnMYFZcslCNyzur5xTZdcAcZjArLlkIdSgAQYLLAlIHGHIEAHOYway4ZKEal3dWzymy64A5zGBWXLIQ6lAAggSXBaQOMOQIAOYwg1lxyUI1Lu+snlNk1wFzmMGsuGQh1KEABAkuC0gdYMgRAMxhBrPikoVqXN5ZPafIrgPmMINZcclCqEMBCBJcFpA6wJAjAJjDDGbFJQvVuLyzek6RXQfMYQaz4pKFUIcCECS4LCB1gCFHADCHGcyKSxaqcXln9Zwiuw6YwwxmxSULoQ4FIEhwWUDqAEOOAGAOM5gVlyxU4/LO6jlFdh0whxnMiksWQh0KQJDgsoDUAYYcAcAcZjArLlmoxuWd1XOK7DpgDjOYFZcshDoUgCDBZQGpAww5AoA5zGBWXLJQjcs7q+cU2XXAHGYwKy5ZCHUoAEGCywJSBxhyBABzmMGsuGShGpd3Vs8psuuAOcxgVlyyEOpQAIIElwWkDjDkCADmMINZcclCNS7vrJ5TZNcBc5jBrLhkIdShAAQJLgtIHWDIEQDMYQaz4pKFalzeWT2nyK4D5jCDWXHJQqhDAQgSXBaQOsCQIwCYwwxmxSUL1bi8s3pOkV0HzGEGs+KShVCHAhAkuCwgdYAhRwAwhxnMiksWqnF5Z/WcIrsOmMMMZsUlC6EOBSBIcFlA6gBDjgBgDjOYFZcsVOPyzuo5RXYdMIcZzIpLFkIdCkCQ4LKA1AGGHAHAHGYwKy5ZqMblndVziuw6YA4zmBWXLIQ6FIAgwWUBqQMMOQKAOcxgVlyyUI3LO6vnFNl1wBxmMCsuWQh1KABBgssCUgcYcgQAc5jBrLhkoRqXd1bPKbLrgDnMYFZcshDqUACCBJcFpA4w5AgA5jCDWXHJQjUu76yeU2TXAXOYway4ZCHUoQAECS4LSB1gyBEAzGEGs+KShWpc3lk9p8iuA+Ywg1lxyUKoQwEIElwWkDrAkCMAmMMMZsUlC9W4vLN6TpFdB8xhBrPikoVQhwIQJLgsIHWAIUcAMIcZzIpLFqpxeWf1nCK7DpjDDGbFJQuhDgUgSHBZQOoAQ44AYA4zmBWXLFTj8s7qOUV2HTCHGcyKSxZCHQrAnvGVr3wlPv7xj8fb3va2WLFiRYyOjsYZZ5wRP/ETPxEXX3xx/N3f/d1x/byZmZlYtWpVjI+Px+joaIyPj8eqVatiZmbmBP0JnsZlAakDDDkCgDnMYFa6noXcHP1CPafIrgPmMINZcclCqEMB2CNe//rXt0Nb89d+7dfi0KFD1Z81GAxienq6+nOmp6djMBickD+LywJSBxhyBABzmMGsdDkLuTn6h3pOkV0HzGEGs+KShVCHArBHvPzlL4+maWJsbCw+9KEPxU033RQ7duyI2dnZ2LBhQ4yPj7dDfdFFF1V/1pVXXtl+7+TkZGzatCl27NgRmzZtisnJyfZr69evPyF/FpcFpA4w5AgA5jCDWelyFnJz9A/1nCK7DpjDDGbFJQuhDgVgj3jnO98Zn//85+Opp5466tf3798f5513XjvYpX8155577omRkZFomiampqZifn7+sK8/8cQTMTU1FU3TxMjISNx7773L/mdxWUDqAEOOAGAOM5iVLmchN0f/UM8psuuAOcxgVlyyEOpQACbjlltuaQf7t37rt476PWvXrm2/Z3Z29qjfMzs7237PZZddtuy/T5cFpA4w5AgA5jCDWel7FnJzdAv1nCK7DpjDDGbFJQuhDgVgMg4ePNgO9jvf+c4jvj4YDNp/bWdiYqL6s84///xomiZWrFix7P9dHpcFpA4w5AgA5jCDWel7FnJzdAv1nCK7DpjDDGbFJQuhDgVgMr75zW+2g/3ud7/7iK/Pzc21X1+zZk31Zz37P9i9b9++Zf19uiwgdYAhRwAwhxnMSt+zkJujW6jnFNl1wBxmMCsuWQh1KACTcfPNN7eDffnllx/x9VtvvbX9+vXXX1/9WRs2bGi/d+vWrcv6+3RZQOoAQ44AYA4zmJW+ZyE3R7dQzymy64A5zGBWXLIQ6lAAJmJhYSFe/epXt4O9c+fOI77nhhtuaL++ZcuW6s/bsmVL+70bN248rt/LAw88UHXHjh0WC0gdYMgRAMxhBrPS52Ocm6N7qOcU2XXAHGYwK32+OWD5oABMxHXXXdcO9apVq476Pddee237PTMzM9Wft23btvZ7r7vuuuP6vTzz6xZj5gWkDjDkCADmMINZ6fMxzs3RPdRziuw6YA4zmJU+3xywfFAAJuGOO+6IkZGRaJomzj777Pjnf/7no37f1Vdf3Q7+9u3bqz9z+/bt7fdec801x/X74Rh/GnWAIUcAMIcZzEpfj3Fujm6inlNk1wFzmMGs9PXmgOWFAjABd999dzz/+c+PpmniOc95Ttxxxx3F7z1Z/zSefx3nadQBhhwBwBxmMCt9PMa5ObqLek6RXQfMYQaz0sebA5YfCsCes2/fvhgbG4umaeK0006Lm2++ufr9J+u/x3MsXBaQOsCQIwCYwwxmpW9ZyM3RbdRziuw6YA4zmBWXLIQ6FIA95sEHH4yXvexl0TRNnHLKKXHjjTce89fccsst7eDzv8h34lEHGHIEAHOYwaz0KQu5ObqPek6RXQfMYQaz4pKFUIcCsKfs378/XvGKV7RD/KlPfWpRv25ubq79NWvWrKl+7/T0dPu9+/btW47fdovLAlIHGHIEAHOYwaz0JQu5OfqBek6RXQfMYQaz4pKFUIcCsId861vfip/92Z9tB/gP/uAPFv1rB4NB+6/vTExMVL93YmIimqaJ8fHxGAwGw/62D8NlAakDDDkCgDnMYFb6kIXcHP1BPafIrgPmMINZcclCqEMB2DOeeOKJeO1rX9sO7/r164/7Z1x66aXtr5+dnT3q98zOzrbfs3bt2mF/20fgsoDUAYYcAcAcZjArXc9Cbo5+oZ5TZNcBc5jBrLhkIdShAOwRhw4dire85S3t4H7oQx9a0s/Zs2dPjIyMRNM0MTU1FfPz84d9fX5+PqampqJpmhgZGYm9e/cux2//MFwWkDrAkCMAmMMMZqXLWcjN0T/Uc4rsOmAOM5gVlyyEOhSAPeI973lPO7RvfOMb42tf+1p8/etfL7pnz57iz7riiivanzU5ORmbN2+OnTt3xubNm2NycrL92rp1607In8VlAakDDDkCgDnMYFa6nIXcHP1DPafIrgPmMINZcclCqEMB2COeGdjF+mM/9mPFn7WwsBCXXHJJ9devXr06FhYWTsifxWUBqQMMOQKAOcxgVrqchdwc/UM9p8iuA+Ywg1lxyUKoQwHYI5bzGH+GrVu3xsqVK2NsbCxGR0djbGwsVq5cGdu2bTuhfxaXBaQOMOQIAOYwg1npchZyc/QP9Zwiuw6YwwxmxSULoQ4FIEhwWUDqAEOOAGAOM5gVlyxU4/LO6jlFdh0whxnMiksWQh0KQJDgsoDUAYYcAcAcZjArLlmoxuWd1XOK7DpgDjOYFZcshDoUgCDBZQGpAww5AoA5zGBWXLJQjcs7q+cU2XXAHGYwKy5ZCHUoAEGCywJSBxhyBABzmMGsuGShGpd3Vs8psuuAOcxgVlyyEOpQAIIElwWkDjDkCID/196dB1ddX/8ff99LSDCEsBfoF0VEEOJewUEt1Fo7KEJFERGEEXSQCm3ROkVERaSjrLVudSmyjErRanVUtAKytCCEsLY4olIEQa2CigoIBcL5/ZHJ55dLkg9LlnNzzvMx8/on95Oby0fPct+QhDq0EKu8zEJtXu6zdp0Seh2oQwuxysssRDwOAKHCSwPSHmCEJQDUoYVY5WUWavNyn7XrlNDrQB1aiFVeZiHicQAIFV4akPYAIywBoA4txCovs1Cbl/usXaeEXgfq0EKs8jILEY8DQKjw0oC0BxhhCQB1aCFWeZmF2rzcZ+06JfQ6UIcWYpWXWYh4HABChZcGpD3ACEsAqEMLscrLLNTm5T5r1ymh14E6tBCrvMxCxOMAECq8NCDtAUZYAkAdWohVXmahNi/3WbtOCb0O1KGFWOVlFiIeB4BQ4aUBaQ8wwhIA6tBCrPIyC7V5uc/adUrodaAOLcQqL7MQ8TgAhAovDUh7gBGWAFCHFmKVl1mozct91q5TQq8DdWghVnmZhYjHASBUeGlA2gOMsASAOrQQq7zMQm1e7rN2nRJ6HahDC7HKyyxEPA4AocJLA9IeYIQlANShhVjlZRZq83KfteuU0OtAHVqIVV5mIeJxAAgVXhqQ9gAjLAGgDi3EKi+zUJuX+6xdp4ReB+rQQqzyMgsRjwNAqPDSgLQHGGEJAHVoIVZ5mYXavNxn7Tol9DpQhxZilZdZiHgcAEKFlwakPcAISwCoQwuxysss1OblPmvXKaHXgTq0EKu8zELE4wAQKrw0IO0BRlgCQB1aiFVeZqE2L/dZu04JvQ7UoYVY5WUWIh4HgFDhpQFpDzDCEgDq0EKs8jILtXm5z9p1Suh1oA4txCovsxDxOACECi8NSHuAEZYAUIcWYpWXWajNy33WrlNCrwN1aCFWeZmFiMcBIFR4aUDaA4ywBIA6tBCrvMxCbV7us3adEnodqEMLscrLLEQ8DgChwksD0h5ghCUA1KGFWOVlFmrzcp+165TQ60AdWohVXmYh4nEACBVeGpD2ACMsAaAOLcQqL7NQm5f7rF2nhF4H6tBCrPIyCxGPA0Co8NKAtAcYYQkAdWghVnmZhdq83GftOiX0OlCHFmKVl1mIeBwAQoWXBqQ9wAhLAKhDC7HKyyzU5uU+a9cpodeBOrQQq7zMQsTjABAqvDQg7QFGWAJAHVqIVV5moTYv91m7Tgm9DtShhVjlZRYiHgeAUOGlAWkPMMISAOrQQqzyMgu1ebnP2nVK6HWgDi3EKi+zEPE4AIQKLw1Ie4ARlgBQhxZilZdZqM3LfdauU0KvA3VoIVZ5mYWIxwEgVHhpQNoDjLAEgDq0EKu8zEJtXu6zdp0Seh2oQwuxysssRDwOAKHCSwPSHmCEJQDUoYVY5WUWavNyn7XrlNDrQB1aiFVeZiHicQAIFV4akPYAIywBoA4txCovs1Cbl/usXaeEXgfq0EKs8jILEY8DQKjw0oC0BxhhCQB1aCFWeZmF2rzcZ+06JfQ6UIcWYpWXWYh4HABChZcGpD3ACEsAqEMLscrLLNTm5T5r1ymh14E6tBCrvMxCxOMAECq8NCDtAUZYAkAdWohVXmahNi/3WbtOCb0O1KGFWOVlFiIeB4BQ4aUBaQ8wwhIA6tBCrPIyC7V5uc/adUrodaAOLcQqL7MQ8TgAhAovDUh7gBGWAFCHFmKVl1mozct91q5TQq8DdWghVnmZhYjHASBUeGlA2gOMsASAOrQQq7zMQm1e7rN2nRJ6HahDC7HKyyxEPA4AocJLA9IeYIQlANShhVjlZRZq83KfteuU0OtAHVqIVV5mIeJxAAgVXhqQ9gAjLAGgDi3EKi+zUJuX+6xdp4ReB+rQQqzyMgsRjwNAqPDSgLQHGGEJAHVoIVZ5mYXavNxn7Tol9DpQhxZilZdZiHgcAEKFlwakPcAISwCoQwuxysss1OblPmvXKaHXgTq0EKu8zELE4wAQKrw0IO0BRlgCQB1aiFVeZqE2L/dZu04JvQ7UoYVY5WUWIh4HgFDhpQFpDzDCEgDq0EKs8jILtXm5z9p1Suh1oA4txCovsxDxOACECi8NSHuAEZYAUIcWYpWXWajNy33WrlNCrwN1aCFWeZmFiMcBIFR4aUDaA4ywBIA6tBCrvMxCbV7us3adEnodqEMLscrLLEQ8DgChwksD0h5ghCUA1KGFWOVlFmrzcp+165TQ60AdWohVXmYh4nEACBVeGpD2ACMsAaAOLcQqL7NQm5f7rF2nhF4H6tBCrPIyCxGPA0Co8NKAtAcYYQkAdWghVnmZhdq83GftOiX0OlCHFmKVl1mIeBwAQoWXBqQ9wAhLAKhDC7HKyyzU5uU+a9cpodeBOrQQq7zMQsTjABAqvDQg7QFGWAJAHVqIVV5moTYv91m7Tgm9DtShhVjlZRYiHgeAUOGlAWkPMMISAOrQQqzyMgu1ebnP2nVK6HWgDi3EKi+zEPE4AIQKLw1Ie4ARlgBQhxZilZdZqM3LfdauU0KvA3VoIVZ5mYWIxwEgVHhpQNoDjLAEgDq0EKu8zEJtXu6zdp0Seh2oQwuxysssRDwOAKHCSwPSHmCEJQDUoYVY5WUWavNyn7XrlNDrQB1aiFVeZiHicQAIFV4akPYAIywBoA4txCovs1Cbl/usXaeEXgfq0EKs8jILEY8DQKjw0oC0BxhhCQB1aCFWeZmF2rzcZ+06JfQ6UIcWYpWXWYh4HABChZcGpD3ACEsAqEMLscrLLNTm5T5r1ymh14E6tBCrvMxCxOMAECq8NCDtAUZYAkAdWohVXmahNi/3WbtOCb0O1KGFWOVlFiIeB4BQ4aUBaQ8wwhIA6tBCrPIyC7V5uc/adUrodaAOLcQqL7MQ8TgAhAovDUh7gBGWAFCHFmKVl1mozct91q5TQq8DdWghVnmZhYjHASBUeGlA2gOMsASAOrQQq7zMQm1e7rN2nRJ6HahDC7HKyyxEPA4AocJLA9IeYIQlANShhVjlZRZq83KfteuU0OtAHVqIVV5mIeJxAAgVXhqQ9gAjLAGgDi3EKi+zUJuX+6xdp4ReB+rQQqzyMgsRjwNAqPDSgLQHGGEJAHVoIVZ5mYXavNxn7Tol9DpQhxZilZdZiHgcAEKFlwakPcAISwCoQwuxysss1OblPmvXKaHXgTq0EKu8zELE4wAQKrw0IO0BRlgCQB1aiFVeZqE2L/dZu04JvQ7UoYVY5WUWIh4HgFDhpQFpDzDCEgDq0EKs8jILtXm5z9p1Suh1oA4txCovsxDxOACECi8NSHuAEZYAUIcWYpWXWajNy33WrlNCrwN1aCFWeZmFiMcBIFR4aUDaA4ywBIA6tBCrvMxCbV7us3adEnodqEMLscrLLEQ8DgChwksD0h5ghCUA1KGFWOVlFmrzcp+165TQ60AdWohVXmYh4nEACBVeGpD2ACMsAaAOLcQqL7NQm5f7rF2nhF4H6tBCrPIyCxGPA0Co8NKAtAcYYQkAdWghVnmZhdq83GftOiX0OlCHFmKVl1mIeBwAQoWXBqQ9wAhLAKhDC7HKyyzU5uU+a9cpodeBOrQQq7zMQsTjABAqvDQg7QFGWAJAHVqIVV5moTYv91m7Tgm9DtShhVjlZRYiHgeAUOGlAWkPMMISAOrQQqzyMgu1ebnP2nVK6HWgDi3EKi+zEPE4AIQKLw1Ie4ARlgBQhxZilZdZqM3LfdauU0KvA3VoIVZ5mYWIxwEgVHhpQNoDjLAEgDq0EKu8zEJtXu6zdp0Seh2oQwuxysssRDwOAKHCSwPSHmCEJQDUoYVY5WUWavNyn7XrlNDrQB1aiFVeZiHicQAIFV4akPYAIywBoA4txCovs1Cbl/usXaeEXgfq0EKs8jILEY8DQKjw0oC0BxhhCQB1aCFWeZmF2rzcZ+06JfQ6UIcWYpWXWYh4HABChZcGpD3ACEsAqEMLscrLLNTm5T5r1ymh14E6tBCrvMxCxOMAECq8NCDtAUZYAkAdWohVXmahNi/3WbtOCb0O1KGFWOVlFiIeB4BQ4aUBaQ8wwhIA6tBCrPIyC7V5uc/adUrodaAOLcQqL7MQ8TgAhAovDUh7gBGWAFCHFmKVl1mozct91q5TQq8DdWghVnmZhYjHASBUeGlA2gOMsASAOrQQq7zMQm1e7rN2nRJ6HahDC7HKyyxEPA4AocJLA9IeYIQlANShhVjlZRZq83KfteuU0OtAHVqIVV5mIeJxAAgVXhqQ9gAjLAGgDi3EKi+zUJuX+6xdp4ReB+rQQqzyMgsRjwNAqPDSgLQHGGEJAHVoIVZ5mYXavNxn7Tol9DpQhxZilZdZiHgcAEKFlwakPcAISwCoQwuxysss1OblPmvXKaHXgTq0EKu8zELE4wAQKrw0IO0BRlgCQB1aiFVeZqE2L/dZu04JvQ7UoYVY5WUWIh4HgFDhpQFpDzDCEgDq0EKs8jILtXm5z9p1Suh1oA4txCovsxDxOACECi8NSHuAEZYAUIcWYpWXWajNy33WrlNCrwN1aCFWeZmFiMcBIFR4aUDaA4ywBIA6tBCrvMxCbV7us3adEnodqEMLscrLLEQ8DgChwksD0h5ghCUA1KGFWOVlFmrzcp+165TQ60AdWohVXmYh4nEACBVeGpD2ACMsAaAOLcQqL7NQm5f7rF2nhF4H6tBCrPIyCxGPA0Co8NKAtAcYYQkAdWghVnmZhdq83GftOiX0OlCHFmKVl1mIeBwAQoWXBqQ9wAhLAKhDC7HKyyzU5uU+a9cpodeBOrQQq7zMQsTjABAqvDQg7QFGWAJAHVqIVV5moTYv91m7Tgm9DtShhVjlZRYiHgeAUOGlAWkPMMISAOrQQqzyMgu1ebnP2nVK6HWgDi3EKi+zEPE4AIQKLw1Ie4ARlgBQhxZilZdZqM3LfdauU0KvA3VoIVZ5mYWIxwEgVHhpQNoDjLAEgDq0EKu8zEJtXu6zdp0Seh2oQwuxysssRDwOAKHCSwPSHmCEJQDUoYVY5WUWavNyn7XrlNDrQB1aiFVeZiHicQAIFV4akPYAIywBoA4txCovs1Cbl/usXaeEXgfq0EKs8jILEY8DQKjw0oC0BxhhCQB1aCFWeZmF2rzcZ+06JfQ6UIcWYpWXWYh4HABChZcGpD3ACEsAqEMLscrLLNTm5T5r1ymh14E6tBCrvMxCxOMAECq8NCDtAUYu1HcJAAAfQElEQVRYAkAdWohVXmahNi/3WbtOCb0O1KGFWOVlFiIeB4BQ4aUBaQ8wwhIA6tBCrPIyC7V5uc/adUrodaAOLcQqL7MQ8TgAhAovDUh7gBGWAFCHFmKVl1mozct91q5TQq8DdWghVnmZhYjHASBUeGlA2gOMsASAOrQQq7zMQm1e7rN2nRJ6HahDC7HKyyxEPA4AocJLA9IeYIQlANShhVjlZRZq83KfteuU0OtAHVqIVV5mIeJxAAgVXhqQ9gAjLAGgDi3EKi+zUJuX+6xdp4ReB+rQQqzyMgsRjwNAqPDSgLQHGGEJAHVoIVZ5mYXavNxn7Tol9DpQhxZilZdZiHgcAEKFlwakPcAISwCoQwuxysss1OblPmvXKaHXgTq0EKu8zELE4wAQKrw0IO0BRlgCQB1aiFVeZqE2L/dZu04JvQ7UoYVY5WUWIh4HgFDhpQFpDzDCEgDq0EKs8jILtXm5z9p1Suh1oA4txCovsxDxOACECi8NSHuAEZYAUIcWYpWXWajNy33WrlNCrwN1aCFWeZmFiMcBIFR4aUDaA4ywBIA6tBCrvMxCbV7us3adEnodqEMLscrLLEQ8DgChwksD0h5ghCUA1KGFWOVlFmrzcp+165TQ60AdWohVXmYh4nEACBVeGpD2ACMsAaAOLcQqL7NQm5f7rF2nhF4H6tBCrPIyCxGPA0DIxx9/LLfffru0b99esrOzpWHDhtKpUyeZPHmy7Nmzp0q+ppcGpD3ACEsAqEMLscrLLCyJnaPqaNcpodeBOrQQq7zMQsTjANC5OXPmSP369aNmcHhOO+002bRpU6V/XS8NSHuAEZYAUIcWYpWXWViMnaNqadcpodeBOrQQq7zMQsTjANCxdevWSXZ2toQQJCcnR+6//35ZtmyZLFiwQIYMGRI1iPbt28uuXbsq9Wt7aUDaA4ywBIA6tBCrvMxCEXaO6qBdp4ReB+rQQqzyMgsRjwNAxy6++GIJIUhGRoYsW7as1OOTJk2KmsR9991XqV/bSwPSHmCEJQDUoYVY5WUWirBzVAftOiX0OlCHFmKVl1mIeBwAOlVQUBA1gKFDh5Z5TWFhoXTo0EFCCNKwYUPZv39/pX19Lw1Ie4ARlgBQhxZilZdZyM5RPbTrlNDrQB1aiFVeZiHicQDo1OjRo6MGkJ+fX+5148ePj66bN29epX19Lw1Ie4ARlgBQhxZilZdZyM5RPbTrlNDrQB1aiFVeZiHicQDoVJcuXSSEIHXr1pUDBw6Ue92yZcuiRjFmzJhK+/peGpD2ACMsAaAOLcQqL7OQnaN6aNcpodeBOrQQq7zMQsTjANCpJk2aSAhBzj777Njrvv7666hR9OnTp9K+vpcGpD3ACEsAqEMLscrLLGTnqB7adUrodaAOLcQqL7MQ8TgAdGjv3r1R8V9xxRVHvL5u3boSQpDOnTsf9dfYtm1bbEr+LX9BQcERr6+p+b9bZpIaHu3/hwh1SOzWYcmfjbd58+YKTPb0xc5BryP0Ok/R/n+IUIflxcPOgSPjANCh7du3R8Xft2/fI17/gx/8QEIIcsYZZxz11yh+fkIIIYQcOQUFBRUZ7WmLnYMQQghJr1jdOXBkHAA6tHXr1qj4Bw4ceMTrTzzxRAkhSJs2bY76a2g3NUIIIaQmxeoyzs5BCCGEpFes7hw4Mg4AHaqOv40/0j9B3rhxo7z++utSUFAgmzdvVv8n0aRi/4zc8rdUEZKuoQZrfjZv3iwFBQVSUFAge/furchoT1vsHKQyQr8jRDfUYM2Ph50DR8YBoEPV8fN4YN+2bfwgWUATNYiagJ0DlYF+B+iiBgEbOAB0Svs38qHmYxEAdFGDqCnYOVBR9DtAFzUI2MABoFNdunSREILUrVtXDhw4UO51JX9z3pgxY6rxFSLdsQgAuqhB1BTsHKgo+h2gixoEbOAA0Kk777wzauL5+fnlXjd+/Pjourlz51bjK0S6YxEAdFGDqCnYOVBR9DtAFzUI2MABoFMrVqyImvjQoUPLvKawsFA6dOggIQRp0KCB7N+/v5pfJdIZiwCgixpETcHOgYqi3wG6qEHABg4AHSv+lpyMjAxZtmxZqccnTZoUNfp77723+l8g0hqLAKCLGkRNws6BiqDfAbqoQcAGDgAdW7NmjZxwwgkSQpCcnBx54IEHZPny5bJw4UK5+eaboybfrl07+e6777RfLtIMiwCgixpETcLOgYqg3wG6qEHABg4AnXvttdckNzc3auiHp127drJx40btl4k0xCIA6KIGUdOwc+B40e8AXdQgYAMHgJAtW7bIbbfdJu3atZPs7Gxp0KCBdOzYUSZOnCh79uzRfnkAAMAIdg4AAAAdHAACAAAAAAAAhnEACAAAAAAAABjGASAAAAAAAABgGAeAAAAAAAAAgGEcAAIAAAAAAACGcQAIAAAAAAAAGMYBIAAAAAAAAGAYB4AAAAAAAACAYRwAAgAAAAAAAIZxAAgAAAAAAAAYxgEgAAAAAAAAYBgHgAAAAAAAAIBhHAACAAAAAAAAhnEACOCoHDx4UDZs2CDz5s2Tl19+WWbNmiUvv/yyzJs3TzZs2CAHDhzQfokAAMAAdg4AACofB4AAyvXtt9/Kgw8+KD/+8Y8lMzNTkslkucnMzJSLLrpI/vCHP8g333yj/dIBk3hTDMAqdg4gvbBzAPZwAAigTNOmTZPGjRtHy3YikThiiq9t1KiRTJ06VfuPAJjAm2IA1rFzAOmBnQOwjQNAAKX8/ve/T1nA69evL926dZMRI0bIlClT5IknnpDp06fLE088IVOmTJERI0ZIt27dpH79+imL+bhx47T/KECNxptiANaxcwDpgZ0DsI8DQAAp8vPzpVatWpJIJKRVq1by/PPPy/79+4/qc/fv3y+zZ8+WVq1aSSKRkIyMDMnPz6/iVwzYxJtiANaxcwDpgZ0D8IEDQAApBg4cKIlEQtq2bStffvnlcT3Hjh075NRTT5VkMikDBw6s5FcI2MebYgAesHMA+tg5AD84AASQ4uSTT5ZkMikzZsyo0PNMnz49WiQAHBveFAPwgJ0D0MfOAfjBASCAFHXq1JFkMimrVq2q0POsWrVKEomE1KlTp5JeGeAHb4oBeMDOAehj5wD84AAQQIoWLVpIMpmU1157rULP89prr0kikZDmzZtX0isD/OBNMQAP2DkAfewcgB8cAAJI0a1bN0kkEnLppZfKoUOHjus5CgsL5ZJLLpFkMindunWr5FcI2MebYgAesHMA+tg5AD84AASQYvbs2dFv8urVq5d8+umnx/T5n376qfTq1St6jtmzZ1fRKwXs4k0xAA/YOQB97ByAHxwAAiilR48e0TJdu3Zt6d69u0ycOFFeffVVWb16tXzwwQeyefNm+eCDD2T16tXy6quvysSJE6V79+6SmZkpyWRSEomE9OjRQ/uPAtRIvCkG4AU7B6CLnQPwgwNAAKXs27dP+vfvL4lEIhrmR5viz+nXr5/s3btX+48C1Fi8KQbgATsHoI+dA/CBA0AA5Vq8eLF0795d6tSpEy3ZccnKypLu3bvLwoULtV86UOPxphiAJ+wcgB52DsAHDgABHNHu3btl4cKF8qc//UlGjRolw4cPl5tuukmGDx8uo0aNkscee0wWLlwou3bt0n6pgDm8KQbgCTsHoIedA7CNA0AAAGoA3hQDAIDqwM4B2MQBIAAAAAAAAGAYB4AAAAAAAACAYRwAAgAAAAAAAIZxAAig0t13330pAQAAqArsHAAAHB0OAAFUukQiIclkMgqA6sebYgAesHMA+tg5gJqBA0AAlS6RSERhGQd08KYYgAfsHIA+dg6gZuAAEEClmzlzZkoAVD/eFAPwgJ0D0MfOAdQMHAACAGAQb4oBAEB1YOcAagYOAAEAAAAAAADDOAAEAAAAAAAADOMAEECsgwcPyttvvy1jx46Vvn37yoUXXihnnXWWtG3bVs466yy58MILpW/fvjJ27FiZP3++HDx4UPslAwCAGoidAwCAqsMBIIAy7dmzR37/+99L48aNU36rV3EO/21fxWnUqJGMGzdOdu/erf1HAAAANQA7BwAAVY8DQAClfPTRR5KXlxct3SWTk5MjzZo1k5NOOkmaNWsmOTk5pa5JJpPSoUMH+eijj7T/KAAAII2xcwAAUD04AASQ4vvvv5f27dtHi3heXp5MmDBBli9fLjt37izzc3bu3CnLly+XCRMmSF5eXrSUd+jQQfbu3VvNfwIAxWbOnCnJZFJq1aql/VIAoBR2DsAOdg4g/XEACCDFlClTor9RnzJlihw6dOiYPv/QoUMy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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2)\n",
    "(100*(women_closed_table.T/women_closed_table.apply(sum, axis=1)).T)\\\n",
    ".plot(kind='bar', stacked=True, title='Observed', ax=axes[0]);\n",
    "\n",
    "(100*(expected_table.T/expected_table.apply(sum, axis=1)).T)\\\n",
    ".plot(kind='bar', stacked=True, title='Expected under no relation', ax=axes[1]);"
   ]
  }
 ],
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