analysis/tutorial_mental_health_in_tech_survey.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Privacy-Preserving Statistical Release\n",
    "### Analysis of OSMI data \n",
    "#### Mental Health in Tech Survey"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The purpose of this demo is to showcase the utility of the OpenDP SmartNoise library. The notebook will focus on statistical releases in the *trusted curator* setting.\n",
    "\n",
    "Throughout his notebook, we make statistical queries to data with and without privacy-preserving mechanisms. As we compare query results side-by-side, we show that conclusions about the data are similar in both settings: without privacy-preserving mechanism, and with differential privacy mechanism. More precisely, the goals of this tutorial are:\n",
    "\n",
    "- serve an audience with basic understanding of differential privacy;\n",
    "- focus on reproducibility by using open data;\n",
    "- showcase the easy usability of the SmartNoise package;\n",
    "- focus on utility.\n",
    "\n",
    "\n",
    "**Disclaimer:** The present notebook is not intended to serve as a study of mental illness in the tech industry, or make any conclusions about the scenario of mental illness in tech. We use the data set as a illustrative example of the SmartNoise tool in survey and human subject studies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 Data set\n",
    "\n",
    "Mental health in tech survey data set is an open data set licensed under CC BY-SA 4.0. \n",
    "\n",
    "The data consists in 27 questions, aswered by 1,259 volunteers. For details on the data set, we refer the reader to the [Mental Health in Tech Survey](https://www.kaggle.com/osmi/mental-health-in-tech-survey)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data used in the analysis was preprocessed. The original age, gender and country variables were mapped into categories for our analysis. We refer the reader to the [preprocessing notebook](data/Data%20set%20processing%20-%20Mental%20Health%20in%20Tech%20Survey.ipynb) for details on variable mappings."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The analysis will be focused on the following variables:\n",
    "- **age**: age of the participant. Categorical variable with 5 categories: 21-30yo (0), 31-40yo (1), 41-50yo (2), 51-60yo (3), 60yo+ (4) \n",
    "- **gender**: gender declared by the participant, and in the survey the participants could input any string. We categorized answers as follows: Male/Man (1), Female/Woman(2), all other inputs (0).\n",
    "- **country**: participant's country of residence. We categorized answers as follows: United States (1), United Kingdom (2), Canada (3), other countries (0).\n",
    "- **remote_work**: binary value that indicates \n",
    "    if participant work remotely more than 50% of the time\n",
    "- **family_history**: binary value that indicates if the \n",
    "    participant has a family history of mental illness \n",
    "- **treatment**: Binary value that \n",
    "    indicates if the participants has seeked \n",
    "    treatment for mental illness"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 Data Analysis and Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Import packages\n",
    "import os\n",
    "\n",
    "import opendp.smartnoise.core as sn\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats as ss\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(style = \"whitegrid\")\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = './data/survey_V2.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data length: 1213\n"
     ]
    },
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Country</th>\n",
       "      <th>state</th>\n",
       "      <th>self_employed</th>\n",
       "      <th>family_history</th>\n",
       "      <th>treatment</th>\n",
       "      <th>work_interfere</th>\n",
       "      <th>no_employees</th>\n",
       "      <th>...</th>\n",
       "      <th>coworkers</th>\n",
       "      <th>supervisor</th>\n",
       "      <th>mental_health_interview</th>\n",
       "      <th>phys_health_interview</th>\n",
       "      <th>mental_vs_physical</th>\n",
       "      <th>obs_consequence</th>\n",
       "      <th>comments</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-08-27 11:29:31</td>\n",
       "      <td>37</td>\n",
       "      <td>Female</td>\n",
       "      <td>United States</td>\n",
       "      <td>IL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Often</td>\n",
       "      <td>6-25</td>\n",
       "      <td>...</td>\n",
       "      <td>Some of them</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Maybe</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-08-27 11:29:37</td>\n",
       "      <td>44</td>\n",
       "      <td>M</td>\n",
       "      <td>United States</td>\n",
       "      <td>IN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rarely</td>\n",
       "      <td>More than 1000</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Don't know</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-08-27 11:29:44</td>\n",
       "      <td>32</td>\n",
       "      <td>Male</td>\n",
       "      <td>Canada</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Rarely</td>\n",
       "      <td>6-25</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-08-27 11:29:46</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Often</td>\n",
       "      <td>26-100</td>\n",
       "      <td>...</td>\n",
       "      <td>Some of them</td>\n",
       "      <td>No</td>\n",
       "      <td>Maybe</td>\n",
       "      <td>Maybe</td>\n",
       "      <td>No</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-08-27 11:30:22</td>\n",
       "      <td>31</td>\n",
       "      <td>Male</td>\n",
       "      <td>United States</td>\n",
       "      <td>TX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Never</td>\n",
       "      <td>100-500</td>\n",
       "      <td>...</td>\n",
       "      <td>Some of them</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Don't know</td>\n",
       "      <td>No</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows &times; 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Timestamp  Age  Gender         Country state self_employed  \\\n",
       "0  2014-08-27 11:29:31   37  Female   United States    IL           NaN   \n",
       "1  2014-08-27 11:29:37   44       M   United States    IN           NaN   \n",
       "2  2014-08-27 11:29:44   32    Male          Canada   NaN           NaN   \n",
       "3  2014-08-27 11:29:46   31    Male  United Kingdom   NaN           NaN   \n",
       "4  2014-08-27 11:30:22   31    Male   United States    TX           NaN   \n",
       "\n",
       "   family_history  treatment work_interfere    no_employees  ...  \\\n",
       "0               0          1          Often            6-25  ...   \n",
       "1               0          0         Rarely  More than 1000  ...   \n",
       "2               0          0         Rarely            6-25  ...   \n",
       "3               1          1          Often          26-100  ...   \n",
       "4               0          0          Never         100-500  ...   \n",
       "\n",
       "      coworkers supervisor mental_health_interview phys_health_interview  \\\n",
       "0  Some of them        Yes                      No                 Maybe   \n",
       "1            No         No                      No                    No   \n",
       "2           Yes        Yes                     Yes                   Yes   \n",
       "3  Some of them         No                   Maybe                 Maybe   \n",
       "4  Some of them        Yes                     Yes                   Yes   \n",
       "\n",
       "  mental_vs_physical obs_consequence comments age gender country  \n",
       "0                Yes              No      NaN   1      2       1  \n",
       "1         Don't know              No      NaN   2      1       1  \n",
       "2                 No              No      NaN   1      1       3  \n",
       "3                 No             Yes      NaN   1      1       2  \n",
       "4         Don't know              No      NaN   1      1       1  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "survey = pd.read_csv(path)\n",
    "print('Data length: '+ str(len(survey)))\n",
    "survey.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 Characteristics of survey participants"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following analysis we explore the distribution of participants according to the following variables:\n",
    "- age;\n",
    "- gender;\n",
    "- country;\n",
    "- remote_work;\n",
    "- family_history; \n",
    "- treatment.\n",
    "\n",
    "We make simple histogram queries for each of the variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Age histogram Geometric DP release:[458 555 148  48  25]\n",
      "Country histogram Geometric DP release:[257 810 186  63]\n",
      "Gender histogram Geometric DP release:[ 52 990 238]\n",
      "Remote Work histogram Geometric DP release:[355 898]\n",
      "family history histogram Geometric DP release:[517 709]\n",
      "treatment histogram Geometric DP release:[604 612]\n"
     ]
    }
   ],
   "source": [
    "# For multicategorical variables, we define the categories as lists\n",
    "age_cat =['0','1','2','3','4']\n",
    "\n",
    "country_cat = ['0','1','2','3']\n",
    "\n",
    "gender_cat = ['0', '1', '2']\n",
    "\n",
    "var_names =list(survey.columns)\n",
    "with sn.Analysis() as analysis:\n",
    "    data = sn.Dataset(path = path, column_names = var_names)\n",
    "#Releases with Geometric Mechanism        \n",
    "    age_histogram = sn.dp_histogram(\n",
    "            data['age'],\n",
    "            categories = age_cat,\n",
    "            null_value = \"4\",\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    gender_histogram = sn.dp_histogram(\n",
    "            data['gender'],\n",
    "            categories = gender_cat,\n",
    "            null_value = '0',\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    country_histogram = sn.dp_histogram(\n",
    "            data['country'],\n",
    "            categories = country_cat,\n",
    "            null_value = '0',\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    remotework_histogram = sn.dp_histogram(\n",
    "            sn.cast(data['remote_work'], 'bool', true_label=\"1\"),\n",
    "            upper = 1213,\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    \n",
    "    family_histogram = sn.dp_histogram(\n",
    "            sn.cast(data['family_history'], 'bool', true_label=\"1\"),\n",
    "            upper = 1213,\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    \n",
    "    treatment_histogram = sn.dp_histogram(\n",
    "            sn.cast(data['treatment'], 'bool', true_label=\"1\"),\n",
    "            upper = 1213,\n",
    "            privacy_usage = {'epsilon': 0.1}\n",
    "        )\n",
    "    \n",
    "    \n",
    "\n",
    "analysis.release()\n",
    "\n",
    "print(\"Age histogram Geometric DP release:\" + str(np.absolute(age_histogram.value)))\n",
    "print(\"Country histogram Geometric DP release:\" + str(np.absolute(country_histogram.value)))\n",
    "print(\"Gender histogram Geometric DP release:\" + str(np.absolute(gender_histogram.value)))\n",
    "print(\"Remote Work histogram Geometric DP release:\" + str(np.absolute(remotework_histogram.value)))\n",
    "print(\"family history histogram Geometric DP release:\" + str(np.absolute(family_histogram.value)))\n",
    "print(\"treatment histogram Geometric DP release:\" + str(np.absolute(treatment_histogram.value)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Due to sequential composition, given $q_i$ queries, where each provide $\\epsilon_i$-*differential privacy*, the sequence of queries provides $(\\sum \\epsilon_i)$-*differential privacy*. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pie_comparison(label, true_counts, dp_counts, title, subtitle1, subtitle2):\n",
    "    # Make square figures and axes\n",
    "    plt.figure(1, figsize=(20,25))\n",
    "    the_grid = GridSpec(2, 2)\n",
    "    plt.rcParams['text.color'] = '#000000'\n",
    "    plt.rcParams['axes.labelcolor']= '#000000'\n",
    "    plt.rcParams['xtick.color'] = '#000000'\n",
    "    plt.rcParams['ytick.color'] = '#000000'\n",
    "    plt.rcParams['font.size']=14\n",
    "\n",
    "    cmap = plt.get_cmap('GnBu')\n",
    "    colors = [cmap(i) for i in np.linspace(0, 1, 8)]\n",
    "\n",
    "\n",
    "    plt.subplot(the_grid[0, 0], aspect=1, title= subtitle1)\n",
    "\n",
    "    source_pie = plt.pie(true_counts, labels=label, autopct='%1.1f%%', shadow=True, colors=colors)\n",
    "\n",
    "\n",
    "    plt.subplot(the_grid[0, 1], aspect=1, title= subtitle2)\n",
    "\n",
    "    flavor_pie = plt.pie(dp_counts,labels=label, autopct='%.0f%%', shadow=True, colors=colors)\n",
    "\n",
    "    plt.suptitle(title, fontsize=24)\n",
    "\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_true = [478, 554, 149, 26, 6]\n",
    "age_geo = age_histogram.value\n",
    "epsilon_ = 0.1\n",
    "age_labels = ['21-30 years', '30-39 years', '40-49 years',\n",
    "         '50-59 years', '60+ years']\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Age of Participants'\n",
    "subtitle2 = 'Privacy-preserving: Age of Participants'\n",
    "pie_comparison(age_labels, age_true, age_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Country distribution "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "country_true = [ 240, 732, 175, 66]\n",
    "country_geo = country_histogram.value\n",
    "epsilon_ = 0.1\n",
    "country_labels = ['Other','US', 'UK','CA' ]\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Country of Participants'\n",
    "subtitle2 = 'Privacy-preserving: Country of Participants'\n",
    "pie_comparison(country_labels, country_true, country_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gender Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gender_true = [16, 955, 242]\n",
    "gender_geo = gender_histogram.value\n",
    "epsilon_ = 0.1\n",
    "gender_labels = ['Non-binary', 'Male', 'Female']\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Gender '\n",
    "subtitle2 = 'Privacy-preserving: Gender'\n",
    "pie_comparison(gender_labels, gender_true, gender_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Remote work distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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42IsHHp45FNVqr2b7eTurnzecrjXyTbY+yZflMtgl050nYLyocoiq26oRjWMb0bhr2VDvR+5efvv696y4Y0qDOpLUV1+uWq3LHFLoVENDGmj0zhtsLNuyEfVvR8S/JL1WUvd0561TtrezPWD7qtzdbPsXtjed7rwVbG9v+4RJTH+B7RMnK/1R5ONFtt+zinFWi7wCWGM8sx71S+tRv+jhgYcOvb33tlkP9t9fuaCOJPXX+6NLM6Y7G5gi9Rio9TeWzhmKvv0jGn+MiAslPW268wWMB1ehqKrtGlH/WSMaf186uPhNdyz755z7++6ZPV1vWAiFVgwuj25TKMDoNFQvB3iOi4iFqlaA5+6ImB8R8yXtJulWSb+c5jyVbStpx+nOxBR4kqR1pzsTANYK8xtR//NQY+j0B/vuf/K/em+ds3jgoa6GGtOdrzHrq69QftEB1iL1GHAK8Kx4WkTjDxHxV0n7TXe+gLEgsIOq2TDX0Llx8cCilxR3hybyLVdjtay+1IpadUs1mFZrQIBHkZ7t/R9Jj7O9pyTZ/rDtG2xfa/tLtrty/8NtX5Fr+pxge5btHts/sn1l7t7YPA/bJ9r+mu0LbS+0/frcf47tn9i+zvY1tg/PkxwraW/b32xK51rbu+fvP7F9XP6+r+3T2+U911K6Kc//nKY0v2L7p8UylvovtH1yrtG0Satlz+Pda/v4nP55tl9m+wLb/7T9zDzOLrb/P3v3HSdXVf4P/HPuzPbNZhPSsymb3ntCGm0mQRggIfTQIdI7hBoEYvmCij87IAgiVtCvDbF+VRClihQRUKQHSM+WKffOvec8vz9mNobULbN7pnzerxcSNsnkM2tm5tznnuc8j2af45NKqblKqUkAzgdwvlLqLKVUrVLq20qp57J/xsqd8kSVUk/s8N9ntD1/IqK9GG1E/1SLfmKrt3nRu4k3quNBi+1MOeEZVwGKhZ0SpcVvK/DsL2J+LSLPAjgEmem6RAWBhR0qFJUico0R827cbznnvcSbldvSm8P5dHcoqRNwnBBfU9QluynwvAPgNGTGxuY9EUkDeB3ABKVUDMAyZHaTzAQwBpniw2QA5wBYmN3psxHAamS2QfcVkZkAlgBYtIc/Zhgyd9SOAnB79mu3ANgiIlMARADcki0uXQrgbyJy0U6P8QiAaPbH0wAszv74cAC/3FP27K8ZD+BUEVnS9mBKqVsANAA4TUR2d1bSr0VkPID+e3juADAQwC9FZEL2v1eIyAHZ53Z59mvfBfAVEZkG4Apkdke9AeAuAHeJyLcA3AjgORGZDeBAAGuUUqN2yPJHAIOUUm07mc4AcP9uMhMRAcBAI+YeI+bl5vS2I9+Nv1HV4jcV1XrH0ymu4aitwFPjS2qOiHlYRP4GYK7tXETtUTB3gqlkOQBWGjFfdHWqeou3scY3aduZdsuIhq/TElLlSiM/M1LhaCvwOAjVhp2qOxScm7M7WP5kO1s7CIAUMgWWH4hICgCUUvchU0RQAMYCeEopBQDlAP4O4E4A45VSvwXwKwDX7uHxfyciopR6GUDf7NciAFYBgIhsVkr9HMDBAF7aw2M8AuBKpdQfAfwTmULUAGQKO8chUxDaXfZHAGzM7qhqczgyBZu5InvcPth2MOMhe3jubX6d/fc7AP6yw4/7KKVqAYwRkZ9kn+dTSqmtyBSadrQEQLVS6uzsf9cAmNz2k9nv3bcBnKqU+haAgSLCgyOJaGd1Rsx1AC5r9ZtD29JbKsxu69aFL5AAAkFm2Zk/Nw3JDiM+PPFrQqpsZhhVjwH4lVLqcgDrbGcj2hMWdiifRYzoOwMTDNnsbejxA5E7Ix60oHdZvYBbNylH/lvgCdeWOVW/BNSflVIXAXjTdrbdUUqVI1NoeAWZIsZHfhqZz50QgIdE5NLs76kFEBaRpuxunqUAYgD+rpSaLCJNOz2OC2wvULR9bec7rW1/1p48AeABZIogjwLYgExBp1xE3lVK7e3xdn4zehvADQC+rpRaKCK7uypo+z27fe5tvyi746nNzkUiB7u+t+zueYaQ2VH09+yfMRDAVgCn7I+kfDoAACAASURBVPBr7gfwG2S+lw/sJi8Rla4KEblYIDcng3h4q7epKsiDlvfu5gWulDllSsPOeY2Uf7T4SotfFVYVy0KoiAH4klLqfwDEbWcj2hm3HFI+mqpFPxaY4Beb3PXj1iXfLoiiDgAkdUJlpmMR5ZZBgEz/t7dERF4WkdsB9LKda0fZYshaAE+JyBvItPysVEpVKaXCAM5CZsfRowBWZM+bUcjs1LlcKbUMmVajR5DZMRNHpu2qPf6I7I4dpVQ/AEdn/5wAuynwZNulns7+OY9mf/8aZHYKtT3e7rLvzqsici+ABICdW7529ih289zb8wRFpAXAG0qpY7LPcz6AQQBe3ul5/hHABdlfMxiZXUvDd3qsd5C583gBgO+0588noqIXEpEzjJj3Ujq59v3kO702uh+WRFEHyEw4VXB4zg7tIhCvzDOtVQbBZSLyroichTxukVecWpo3k0BVD04tZWGH8kmDEf19I/rpbd7mxe8m3qhJBIVVEPdNGkYMHG6Go26ixQt7prXKiH/hDosLm+/lQ9oWDgBeBDAUwMkAICK/BPBLAH9Dpt3pHQBfFZEXkSkAtbVBOQBuQ6YNKZX92jMAfiIi/2hnjk8C6KuU+geAPwP4THbHyqsA6pVSuytePAKgRkReA/AYsmfc7C37PjJcAOAmpVTDnn7BXp57e50K4NLs8/wagGOyu3z+DOAUpdQl2cevyraq/RHANdlC285+COAVEfmgA38+ERWn+Ub0v9LG+9qHqXX916fW5W3re3fJHqBsOwblLYFvktVpk+gjMF8VkVex687kfMKppfmhx6aWqswQEyKryrI93Nc3p7eFmtJby6WA+5v7lveX2nAtAqS4OqBupRBCmVMVV3DWZc/f+cs+fxMRgOwupO8A+FHbmT1EVJJ6GzH/TyArN7sbqhJBq+081jhwMKJ2NDxTut8Daj9HlaFMVSYB9ddsi/zrtjO1UUqNBPCoiIzc4WvlyLSdHyQiLymlbkDmZpEG8DtkbgJplZkqejkyN56eQ2YnsgZwH4Ap2Ye7Q0Tu2enPvB9AMzKFjAYAa0XkW0qpagD3AJiOzAFWt4vIA0qplwCMAvDtHQdcZG9cnSAiryqlvgegRUQuyO5SvklEYrvLjswO798A2IxMm/l3ARwsImcqpb6IzA7nU3cccKGUehuZ3dszkBnKcdjOz11EXKXUegAPZ3/NhwDuQGbHdwOAM0XkMaXUOAB3I3P2YyL78wlkbrABwPUAfgTg69nvYwjAZ0XkB0qpM5E5F/I7AD4lIguz+c4AMF9ELkA7cMcO2TbXiH7V0+616xJvVW1Lby7oog6QacfCLsdzEOWetE3QktQEEfNbEfk52t+6RCUq2wL2ATILrJ9ZjkNEdigAxxkxb8X9lpPfi79Z0kUdADAw0KK565raxYjf1iIfEZEXReQmAGW2c+0Jp5YW/9RSvnORLTVGzG2ArNqU2lCZ0K1Fs7vF1Uk4ylEQTlagnpGd3lAdVhWHh1DxGoCrlVJ3gX8BaTcks1V3gO0cRGTNcCP6W1r0/hvd9TVegZxj2BNSQcpUhSscUyLnClHXafFCRtJVYaf6GkdCZyilViLTTp6POLV0V0UztZSFHbLhUCPmgWQQr9vsbawqxtGZST9uKsMVTiCu7ShUQgLxyrT4ZWVO9ecgzlnZxcV/bOciIqK8EBaRywWytsnbWt7kb+V1wE48k3KqpJLTTalDBALfJGocVdZYhqpHAXxLKXUt8mh6FqeWFv/UUvaLUE/az4h+KDDBTzek3h+40f2wKIs6AJDQcQfCyQrU8wQGaROvCcSdKSIvichVyOPJDURE1CNmG9Evezp1y7rE29Us6uyep13set1I1D5GfJUdcHFWdmjBYbYzAZxaihKZWsp3LuoJCsBKI+aNlnTzsvcSb1andNJ2pm6VChLg2HOySUs6lDbxKoFeKyLPA5hkOxMREfW4WiPmDiP68U3uhnEfpN6rCcS3nSlvecaDo7h+o64Q+JKq8k1ygIj5XxH5MYB+FoJwaul/lcTUUk7Fou423Ii+Xxs9b6P7YY1nSqc1aUjVcAkppTQ821GoxIVUuQmrSg/AbUqpWwFwVU9EVPyONGK+lQhaa7d4myqLdZd0rg2tHiEKRhl+VFIOhFWlF1LlHoCLslOeePFNe9SVqaXcsUPdxRGRS42YV5q8rQe8l3yrpIo6ABAPWpRCiG/eZJ2WtOOZ1iqBvkZEXkZmrCMRERWnKiPm3sAED65Pvd9vk7ueRZ0OcIMUJ2NRzgTiVqRNok5g7sruNuljOxPlp65OLeWOHeoO/YzoH/nGn7vR/bDGN+l9/44iFFZlaKgZibQp7fGhlF8cVSZlqsoFcLtSai0ArvaJiIrHJCPm4WQQH7LJ3VApHI7YYbXhOvQp72c0krwBTjmV3b3Tmj2L5XHbeai48A2Lcu1AI+a15nTTwveT75RsUQcAAvGhTQAHZbajEG3XdrCfQF+ZHaHY3sPviIgofykROdeIeXazu6Fxo/shizqd5OkUQo7DayTKuUDcCt8k+4nIb0XkVnBCNeUQ37QoV0JGzC3a6N9sSH2w37b05nLbgfJBPGgVB2Fui6M8I0ibRE0g3nQR+SeAFbYTERFRp9Ub0b9I6/SX3k++Ux0PWnj4bxf44iMz94OXSZR7BgGyN9guEZHnAIy0nYmKA1uxKBcGadE/SQfujI3e+iotge08eaMiVIVBlUPElwQXWZSXFEIod6qTgPqhUupiZKYeEBFRYVhgRP+sxWvus83fXCY8lzUnBlcOk7DjcAAGdauQKtdhVZkCcI5S6oe281BhYymaumqJMfrVJnfrvA/ddSzq7MTTqexBWHypUX4SaHimtdogWCkiLwEYazsTERHtk2PEfEIb/ceN7voBW/1NLOrkUMoklVIh2zGoyGlJh9ImXgvIvSLyAwC1tjNR4eLVJnVW2Ii5LTDBw+vdD+qbg6389NuDhB+XMlVhOwbRXvkmWRWIO0pEnheR423nISKiPRqsRf/FC9zr1yXfrkwGcdt5ik5auwArZdQDBCZzg038o0XkNQAzbWeiwsTCDnXGUC36qZSfvOz95NuVrk7azpPXkjquRBQXB5T3tKSdtInXAHK/iNwNgBVJIqL8cpgR81qTt3Xeh+573CndTTzjwnFCbKOnHuNLqtKX1BAR+YuInGY7DxUeFnaoo2LG6Fe3uVtmbPDer9TCScn7kgwSXBxQwdh+5wjBKSLydwANtjMREREcI+bWwAQ/WZ9aV9fsc6d0d9KiYcTAAb/N1HOM+Cpt4tWA3CUidwIcrUvtx8OTqb2UEXOzEXPtRveDSlfzfNWOGFTZIGVOiIfwUUEJqYogrCpalFKHAXjWdh4iohJVpY1+MK29pRu8DyoNb6r1iAEVQ0xluNwJxLUdhUpQmVOTdBB6RSl1JIANtvNQ/uOOHWqPCm30D73AuzbTesWiTkcldVwBjrGdg6gjtHhh3yT7isijInKC7TxERCVoUKCD5xLp1sPWu+tY1OlBrkk5YCs9WeKbRLUWb7qIvAyeu0PtwMIO7UtfP/CfTPjxo9e777H1qpMSQRwhJ8zXGxUcgwDZbcH3i8inALCtkIioZ0wPdPDPpvTW8Zv9DZx61cPSxgUUl25kTyBemW+S+2XP3eFgC9orvlvR3ozxA/+VFr9p2ub0+nIuKDpPS4DA+OKwVZYKUObcnXiVwFwhIj8FUGU7ExFRMTPGHBno4Kkt3oa+LcE2rtct8LSLkOIZiWSXQaB2uMH2GfD6nfaAfzFot7TWi/3Af3FbevMAjjLPjbjfqhyEWR2jAiVIm3iNQXCoiDwLYLDtRERERUj5fvpqbYL/3eC+X5nQHGVui0Dg86Yc5YHsDbZqgblMRB4GUG07E+UfFnZoF0EQnGbE/GFzen11XLfwTkWOpHQCind+qMD5JlkViDdORF4Ce76JiHKpzEu73wkk+PSH7nvlnuGhvba5QRIhFbYdgwjbb7CJHxGRvwLoazsR5RcWdmhHyvPcz2rR31zvrStP6aTtPEWlbYHG0ZlU6LR4Zb6k9hORvwBYYTsPEVERqPfS3l89452w3nu/PJDAdh4C4ImrRBSHX1De8CVVqSU9SUSeA9BgOw/lDxZ2qE1Fykv9LEBwxXrvvXLfpG3nKUqJoFUclLMdiwqeEV+lTaJaxHxXRC6ynYeIqICNTvvpVxK6ddZmf32ZgHWEfOHqFJRyeL1EeSUQtzwQt0FEngcw0XYeyg98oyIA2M9Nu8+mxYttTH9QxslX3ScZxBVfdlQsBLptYtbnRORG23mIiAqN1npBoP0Xm/wtg5qCLdzSm2d8k4ZSChwISflGSzqc3T39FID5tvOQfbzCpIa0n/5nQrdO3uJvCHPyVfdK6SQcx+HqgIqGQLIH+sn1IvIFcPVLRNQuXtpbasT8aZO3oYZnGuavtPYkhHLbMYh2YcRXvknWicgfAMRs5yG7WNgpYel0eriX9l5s9rcOaA628u9CDxAIUkFSwqrSdhSiHBKkM9MazhORe8DPFiKivWptbT3GcdQvN6U/rEjphO04tBcpnYSCwzuflJcMAmRa4+XHInKG7TxkDxffJWrL1i2jjeiXWoJtfVp1M+8S9aCkjiuIwwZ6KjKZaQ0CfZKI/BAAx4gQEe3Gxk0bz66orHhwo/dhuatTtuPQPqSNqwSKhR3KW9nW+CpA7hCR62znITtY2ClB/37935Orq6tfaNFNdSzq9LxkEIfjhPjao6KUNokaA32EiPwSQIXtPERE+WTd++tW967v/Y2N6Q/CHGdeGFztIsR1G+U5gWlrjf+EiPw/sDW+5PBNqsS8+I8XZzQMa3im1TSxn9sSLRq+SbNfm4qWbxLVBsGBIvJHADW28xAR5YP33n/vln79+9260Xs/nDae7TjUTloCiAgUL5so721vjT9XRD4HFndKCt+hSsjzL/59zrix455sNU1VLOrYFfdboRDitl4qWr5JVhnxZ4nIEwDqbechIrLp7Xff/nT//v1v3Jj+IOyLbzsOdZCrUxJSvCFHhUCQNokagblQRP7HdhrqOSzslIgXXnx+/oTxEx9vMdsqErqVRR3LUjqhlArx/wcqar6kKrWkx4vIkwB6285DRGTDG2+9ceugQQOv25h+PxSwqFOQXJ1SEB6gTIVCMgcqQy4VkU/bTkM9g4WdEvDCi88vnDBhwqMtZiuLOnkibTwIBA7Pl6UiF4hboSXdKCJ/AtuyiKjE/Ov1124fOnTI1RvTH4QCCWzHoU7KnIfEJTQVkkxbFiBXiMgtttNQ92Nhp8i9+NILB06YMPGPzXprRULH+YmURxJ+qzgo490fKnqBuBVG/Iki8hvwQGUiKhGvvPbKl4aPGHE5izqFz8scoMx1NBUYgZcp7lwtIjfaTkPdi4WdIvbiP16MjB8/4fdNektFQsdtx6GdJHVcQfElSKXBl1SlQTBbRH4GjkInoiL38qsvf6GxsfHiTSzqFAWBQWAC7rSmArS9uHM9R6EXN15VFqmnnnly0fhx43/dZLaUJ1nUyUspnYSjHMWXIZUK3ySrDPSBIvJ98C8+ERWpJ57665oxo8dctslnUaeYuDopjmJhhwrR9uLOJ0Rkte001D24sC5CD//q4RnTpk77fbPeUpYMWNTJZ0k/YcKcskAlxDeJaoGOicjd4IEFRFRkHv7VLy6YPWvO2s3+ehZ1ioxnXAVRxnYOos7ZXtxZKyIX2U5DucfCTpG58547Jhyw+IA/J6SVZ+oUgKSOO8IpC1RismM4TxKRL4DFHSIqEvd9+95TlkYP/cqWYGMobTzbcSjHXJ2CUg4/s6iAtR2ojM8DWG47DeUWCztF5Iabrx+1Yvkxj+syv7pVN/P/2wKQDOI8jI9KUra4c56IfMJ2FiKirrrtC7ctO/H4E+9t1ltDrk7ajkPdIG08OIprNipskhmFXpVti59vOw/lDi/+i8SZ554x+ONnn/NoZa/y+uZga8h2HmofA4O09iTEQUFUcgRpk6gG5FoRudR2GiKizrr2xmsXnHv2ud9LqkRZQrfywr+IZdZsbKGnwibQ8E2yOjutdKztPJQbLOwUgWXHH9X7qsuu+r9+A/YbvDXYxFPdCkw8aFWAw55tKkFtW4LlNgBH2U5DRNRRF1x2/vhLLrzkF6g0Va1BE9fVRS6lk1AIsYWeCp5BgEBSvUTkMQADbOehruMHUIGLxiLVV1xy5U9HjR41bkuwgUWdApQK4gg5Yb4WqSRltgQnq0TkBwCm2c5DRNRex5y0YtDlF1/+m159auqbgi3cLV0CPOMq4dFwVCS0+I4Wr5+I/BFAje081DW8mCxg0Vik/LxV5929YP6CAzcH68MC3kAoRL740KLhgHU5Kk0CDV9S1SLyfwAG2c5DRLQvy44/qvf119zw6yHDhjRwt3Tp8LSLEA9QpiISiFdmxB8tIj8HeDFSyFjYKVDRWCR07NHHfWr5UUeftMn/MKRF245EXZDwW8Th2HMqYUZ8pcWrF5HfAaiynYeIaE+isUjVpRde+tDkyZOmbPE38MZaCQnEB5QCL6GomPiSqhToBSLyDXBaacHiu1IBisYi6uADD774rDPOumJrsDHkm7TtSNRFSZ1QCoorQyppgXhlBsGY7KQGLiyIKO9EY5HwBedceNfiRQdEN/nrwwY8Iq/UuEFKQiizHYMop9ImUS0wJ4rIjbazUOewsFOApk6euuyyiy67tUVvC6c4UrMouDoFpRzFlySVOt8kqwRmqYh80nYWIqIdRWMR59ijj735qCOOOiWzWzqwHYkscE1K8QBlKkZpk6gB5DpwoEVB4lVkgYmtOHz6pRdd9o0g7JdzpGZxSfhxU6Y49pwou7C4UkROtJ2FiAjI7JaeMmnKqWeceubV24JN3C1dwjzt2o5A1E0E6cwY9O+DY9ALDgs7BSQai4y87KLL7hswqH9fTl8oPkkdd0TYjkWUWVgkqgHcB2Ce7TRERJWVlQddedlVX3BVsiypE7bjkEWecRFyQry5SkVJoBGIW50987DWdh5qPxZ2CkQ0FukX+1jsiwcfeMi0LcEGNvYWoWSQgMOFAhEAQGDgZ+4a/QbAMNt5iKh0RWORaVdeeuXX+vbv07s52Mq1c4kzojnNlIqalrRjxB8kIt8DzzwsGPxwKgDRWKRm7JixN114/kWxLcGGMCdgFSeBgaddCYHtWEQAYBAgEK+XiDwC8KRKIup50Vhk+LIjlt2+eOHi8VuCjXwfIgCAG6SMo1jYoeKVmZRloiKy2nYWah8WdvJcNBZxqquqz755zS2nJkxL2NUp25GoG8X9Vh7IR7QDLV7YQI8Wkc/ZzkJEpSUai9ROnDDxxvPPueDgzf6GsOGNNcpyjeuIOByJRkUtc+Yh1gI4xHYW2jcWdvJf9Lqrr7+4pnd1bUvQxP+/ilxKx9mORbQT3ySrATkXwBG2sxBRaYjGIk5dXd25N6+55YSWYFvYMzwwl/7L0yk4SnG9RkVO4JtElYj8FGyLz3ssFOSxaCwy9rhjjr9h9qzZjVt9bv8tBYEE0CYQh10nRDv4yJSGBttpiKgkHHbjtTdeXF5TVtOqm3kBTx+RNh4cxRtxVPwMNALxakTk1wDPi8hnLOzkqWgsUj9t6vQbzz7j7MWb/fVlBtztWSrifgschNmORbSDzJQGr1pEfgHwxEoi6j7RWGTC6aecvmbS5MkNW/2NfL+hXQgEvknzRhyVhExbfDBKRO62nYX2jIWdPBSNRcL19fUX3nT9J1Y0+1tDaePZjkQ9KKkTSvEuENEutHhhgR4vIrfazkJExSkai/Tdf+7+N6884eR5m/31ZQLeZ6HdSwVJhHiAMpUI3ySrADkOwDG2s9DusbCThxzHOfLmNbecpypQFdctvMAvMW19/IovT6JdpDPn7VwE4GO2sxBRcYnGImUDBwy8/Pqrr1++zd8U9k3adiTKY55xlRFuqafSkW2L/xaAIbaz0K545ZhnorHI1LNOP/u6MWPHDN4WbOZtgBKV8FslhHLbMYjykCBtklUi8iC4sCCiHInGIspxnGNvuXHtqiDklyd03HYkynOeceGoEK+lqGQINLR4VSLyQwDcfJBn+GaUR6KxSP9JEyZdf9yK42ZvSXP7bylLmoQCHP4FINqNHc7b+Tl43g4R5cbsk44/6eKGYUP7bws2h2yHofznmzQyg7F4OUWlIxCvTGBmicgltrPQR/GdKE9EY5GKcDh80Q3Xrjm0Odga8sW3HYksSgUJjj0n2gstXplATxKRG21nIaLCFo1FhgxrGH75qStPm7c12MTTcKndPO1KiAcoU4nxTbIGwK0AJtnOQv/Fwk4eiMYiCsAJ55x97uG96mvrWgOO1Sx1AoEbJCWsKm1HIcpbmfN2cA2AqbazEFFhisYiVUqpi29ec9PBcd3MgRXUIW6QglLc4EWlRWAQSKpSRH4G8OyIfMHCTn6YN27s+GOWHbFs1lafd4ooI6HjCuLwUD6iPZK2hcVDYEsWEXVQ9sbaqSefeMqigYMGDmgOtnFdTB3iiavAA5SpBGnxHYNgqIjcZjsLZfADzLJoLNLfcZxVN6+5aUFzsC0UsAWLspJBHI7DQ/mI9kaLrwR6mIhcYzsLERWcmQ1DGw495aRT5rMFizrD0ymu1ahk+SZVDeB8AAfazkIs7FgVjUUcAKef//HzJ/Xq3atva9DEFizaTouGb3xOxyLah2yv940AJtjOQkSFIRqL9FZKrVr7ibXz4rolzBYs6gwtGiIGCmzHolIk8DOTSn8MoN52mlLHwo5dC8eNGbfwqCOWzdvqb+SdItpFwm+BQojTsYj2QiAIxK3ItmRxdU1Ee5VtwVp58omnTBowcODg5mAr18PUaW6QkpDiMp5Kk0EALX4vEfmS7Syljh9klkRjkX6O45x205qbF7YE28KcgkW7k9QJpRSnYxHti5a0I9CjRORK21mIKO/NHDpkaPSUk05ZuDXgjTXqGtekFETxJhyVrEBSlQBOALDAdpZSxsKOBW0tWOeefe7kuvpe+7WwBYv2ILM1XODwXFiiffJNqgbAWgBjbWchovyUbcE6e+0nPjmXLViUC55xAXApT6XNl1SViHwPAIvllrCwY8eCsaPHLlp+1NFswaJ9ivut4qCMd4KI9iEzftMtF5Efgp9vRLSTthaslSeePHngoIFD2IJFueBpFyEnzMoOlTQjPgR6gIistp2lVPEDrYdFY5H9HMc5/aY1Ny9oDraF2IJF+5LUcQXFlypRe2hJhwRmvIhcbDsLEeWdGUOHDI2eetKpbMGinBEIAuNzdzWVvOzO6RsBjLQcpSTxarEHtbVgrTpj1aTefer6tQZN/P7TPqV0Co5yFF+uRO2TnZJ1K4ChtrMQUX6IxiJ1AFbdvObm2WzBolxLBUkeoEwlL7Nz2isXkfvA/sQexyvFnjV/v777zVux/Jh524LNfPendhKk/ISEFceeE7WHwECLFxaRL9vOQkT2ZVuwTl5yyJKRQ4c2NLQE27j+pZzyxFVGYGznILJNixcWyDwAx9jOUmr4wdZDorHIfgBOX3356nEpnXB4p4g6IqHjCuLwnB2idgrEKwckBk5oICJgRigUWnT+uRcsbNZbygT8OKXc8rQLR4V4XUWEzM5pEbkbQJ3tLKWEb0A9IHun6LRJEyfVz5wxc1qz3somXOqQpE7AcTj2vDu8+cZbOHb5iRjcbwRGj5iEa1evgeu6AIAXX3gJ0YMOR//6BsyfcwB+/9s/7PFxxo+eiqpw/S7/nPfxiwAA/3rt35g3axEG9xuBT6+99SO/946vfQOf+eRt3fckS5QvbqWIfBP8rCMqWW0tWKvO/PiAsopwTSKI245ERShtPDiKyzQiABBoGPGrReTztrOUEi52e8Y8ALNWX756XrO/zdGibeehAmNEI609CaHCdpSikk6ncezRJ6G8ogJ/evx3uP+Bu/HwLx7BzTd+Cps2bcbhS5ehcdQIPP7kH3DhxefhpONPw3N/e363j/WXp/6Et9b9a/s/9337GygvL8d5F5wDAPjEmrVYdMBC/Op3P8dXv3wn/vHSywAA13Vx7z334+LLLuix510qjPhKYIaLyGm2sxCRNSfU967vtfzI5Qc16S3saaZu42lPQuBfMSIgc3MNwGkAZtvOUiq4c6SbRWORagCnxg47onzgwEENH3jvsphGnZIIWtG7rI8BC7I58+wzz+GN/7yJx5/8A2prazFh4njctHYNrlu9BoOHDEJtr1rcefdXUVZWhgkTx+PZZ57Dl7/4NTzwvXt3eaz+/ftt/3EymcRNN34K16+5GrNmzwAA/Ptfr+Pc81Zh5qwZmDBxPP71r9cxddoU3H3XvTj+hGPQu3fvHnvepcQ3qdpyp+ZLAH4CoNV2HiLqOdFYZAyAA1ZfcfVYV5IhtsFTd3J1CrXhWgEPjSUCIAjErQyj8k6l1P4Ae2C7Gy8Qu9+hoVCodtWZqw5t1lvK+HeaOiupE8pxHL5mc2jc+LH42cM/Qm1t7favKaXQ1NSMt996BzNnzUBZ2X/POZ86bQqefuqZfT7u179yF5QCLr/qku1fGzasAc8//yKamprw1ptvYdiwBiSTSXzr3gdw4SXn5faJ0XbZ7cAVInKz7SxE1HOyk0hPGTd2HObMmjO3OWAbPHUvz7gKUFzo59jeWub/+fIrWHpIDP16D8W0SXPwg+8/tP33GWNw7qoLMaDPMHwseiQ2bty0/ec2bNiI/WcvRhAEPf58SomWtAJkEoDDbWcpBbxI7EbRWKQ/gKPOW3X+wHB5iH3d1CW+ScOIgcONdjnTv38/RJYcvP2/jTG46+v3IBI9GAMG9Mf76z74yK9/9533sGXz1r0+pud5+PIXv4bV11yBysrK7V+/4RPX4ou3fxlDB4zCoYctwf7z5+KuO76JlSefgLo6ni3XnXxxqwBcCGC07SxE1GPmABh19RVXL2hhGzz1AE+nDu8SfAAAIABJREFU4Dg8QDmX9tYy73kejj36JEydPgXP/P0vuOrqy3Du2Rfimaf/BgB45Je/xuN//ise++vvUde7Drd/9ovbH/f2z34Rl11xMcJhrqm7m29SNSLydQAh21mKHd98utexffr0cY6MHRFhXzflQtxvFQdlvBvUTa5ZfQNefOElfPrWW7Di2OV44fkXcefX74bv+3j6qWfxwP3fRTqd3utj/OTHP4OI4NTTV37k6wsW7o+33/833v3wP/jmt+5CIpHAA/d/FxdcfC7u/PrdGD96KpbFjv3IHSXKFUEgXpmI3GE7CRF1v2gsUgXglKWRpWVDhw4d2RI0cb1L3S6QAJmd+fzrlittLfP33HcHJkwcjwMOWoyb1q7Bgz/4EV595TW88/a7uOmWGzBqdCPOOOs0TJ02GX9+7C8AgH+99jrm7T8XEydNwMcOW4p//+t1AMCHH67Hnx97HCeuPN7mUysZBgEEup+InGE7S7HjO083icYiYwEsuPryqyekNPu6KTeSOq6g+LLNNRHBVVdci2/c8U18+3vfxKTJEzFx0gTcc98dWHvTp1FfMxAfP+t8XHTJ+air67XXx/rxQz/BimOXo7q6epefKy8vx3779QUA3PG1u3HKaSvR3NyCtTd9Go/99f8wYeL4XSZmUW5o8cKALAKwxHYWIup2Ucdxep378fMObQq2crw59Rg3cCWEsn3/QmqXvbXM9+nbBwBw/33fgTEGTz35DP712uuYOXM6AGDY8Aa89upr8DwPLzz/IoYNbwAAfO62L+Dyqy5FKMQNJD3FN24tgNsB7Lo4ppzhFWI3iMYiIQAnTxg/EbNmzprD8eaUK65OwVGO4ks3d4wxOO/jF+Geu+7Dd35wH45adsT2n1t5yon4YNPb+M87r+ClV/6G+j71GDFy+B4fy/M8PPqnx7H86KP2+me2trbiuw98HxdcdA7+9uxzGDd+HAYNGoglSyN45ulnc/bc6KOy24HvBrcDExWtaCyyH4Dlq85Y1b+iqrxXIuCZ6dRzXJ2EgsNKYo7srWV+xIjh+OSnb8JNaz6Juqr+OOSAQ3HZFRchuvQQAMCKY5ahV69e6NtrMP7v93/Elasvw7p17+OJvzyJE086ztIzKk0CDYOgQkRW285SzHh12D3mABi1+vKrFjb7TezrppxK+nETVuzsy5VrV6/Bgz/4MX74o+/g6BXLtn/9z48+jpUnnA7HcTB48CAopfDIw7/GgQcdsMfHevkfr8B1XSw6YMFe/8yvf+UunH7mqaitrYVSCsYYAEAQBBDherC7ZLYDm/4ATrKdhYi6zYq6XnXho5cdvaQpYBs89azsAcq2YxStHVvmgyDAf/7zBs48+zT8+Yk/4Ot3fRlf/fKd+NlPfwEgs0v6/x79Nd587zW88u8X0DhqJD5/2//DlVdfjtf//R8snHcQpk6cjV/98jeWn1VpCIxbDeBaAANsZylW3EmSY9m+7pMPjR5aPmTwkBEcb065ltBxpzJUxXGaOfD0U8/ia1+5E5/8zM2YNWcm1q/fsP3nxo4fi9//9g/42lfuxJFHHY4H7v8ennn6Wdxx91cAAFprbNq0GX379kF5eeba4ZV/voIRI4fvtg2rTXNzM77/vQfx5LOPAQBmzJiGV/75Kp584mn8+Ec/wdx5c7rxGVNgUrVlTs3nlVIPAuA4DKIiEo1FRgFYfNXlq8d44oY849qORCXG0y5CTkgFxnaS4iIiWH3ldbj7znvx/Ye+jUmTJ+KB+7+LJ594Gi+8/Awcx8Gs2TPw/rr38albbv3IjbqBAzN1hHfffQ9PP/UMvviVz2P5Ecfh9DNPxcJF8xE7dDlef/ufqKqqsvX0SoLAQEs6FEL5p5VS59rOU4xYdMi9JQB6nXHqGQc0623s66acSwUJOE6IRZ0c+On//hwAcNOatWhsGP+Rf/r374fvP/ht3PfNb2P29IV49E+P45Hf/hwNDUMBAOveW4fGhvF46omntz/ehg2btvd878nXvnwnzlp1BmpqagAAI0aOwI03X49jl5+Id95+D2tuuq6bni0BgIGGQPcSkdNtZyGi3MmON1/Zv1//YP+5++/fHGzlQSfU4wwMtGhOMM2hPbXMP/e35zF5yiQ4zn8vZ2fOnoG33nx7t4/z2f+5HVddcwUcx8HTTz2LQyIHYdr0qQiHw3j93//piadS8gLxKgCcBmCs7SzFSHHbf+5EY5F+AG6LHhwNX3n5VSd/4L3DRQV1i8FVwySsHKXBQ7mJOkohhHKnZpNSahjAFxFRMYjGIrMBXHrzmlsap82asmBrsIlX1mRF/4rBpipc4QTCHWO5cPWV1+Puu+7FDx56ALEjD9v+9ds+83k89OD/4u8vPbX9a7d/7kv44fcfwt9eeOIjj/H2W2/jpONPwxPPPAbHcTCw73A8+pffYeKkCWgYOAqP/PZnmD5jWo89p1IWUhVBWFX8Vil1pO0sxYY7dnJrBQBz6imnHdSqm7igoG6TCFoVD+cj6pzMIX66WkTOsZ2FiLouGotUADi1vr6+af68/fdv4RqMLPJMyoE4bMbKgbaW+Rtvvn57y3zbPytPOQHvvvMerr7yerz5xlv42U9/gS987ou45LILdnmcWz/zeVx93VXbd/fMmj0D3//ug3j4F49Aa42x48b09FMrWZkppYgAmGQ7S7FhYSdHsn3dixbNXyQDBwwcGg9a2CpD3SYZJOA4Yf4dI+qkwLg1ANYCqLCdhYi6LAKg/rxV509K6aQKxLedh0qYp10opbhGy4G9tcwPbRiKX/3u5/j7cy9g/9kH4BM3rMXaT9+EM8467SOP8eYbb+GlF/+BY45dvv1rn739M3j4F4/g0guvxJ33fHWvZyNS7gXilYvIZ2znKDZsxcqBaCyiAFwFYNTdX79nSe9BtWNagia+oVO3GlbdCEEAAy5giTqjzKmJOwhdo5S603YWIuqcaCxSC+D22pralge/+9Clm4P1FWnDDkuySaGxdiw802I7CFHeqnDqXKXUNACv285SLLhjJzdGApgye+YcGdYwrLE1aGZRh7pd3G8VB2FWZok6KTBuLTK7djgSmahwLQZQserMj09Ji6dY1CH7BGnjiQMetUm0J1q8sIh8ynaOYsLCTm4cASB19hlnHdQaNDmchEU9IanjSimHRUSiTpLMhKwqETlt37+aiPJNNBapArCsvLx805LIkoNadROLtJQX3CDFyVhEexFkztpZDqDRdpZiwcJOF0VjkQYAsydNnJwePWrM+Nagmd9T6hGecaGUguLLmKjT/Myunc8AXIETFaAFAKrOOu2scVoFYc9wChHlB8+4SgAeoEy0F1rSIRG5wXaOYsErwq47HIB/zlkfP7DVb3IM38OpB8X9uDjsIiHqtOyunRoAx9nOQkTtF41FygEsD4fCmw8/LBZpNc38MKS84ekUHBXidRbRXgTilQE4BUB/21mKAd9wuiAaiwwEsHBU46j4xAmTprRo7tahnpXUcY49J+qiwHi1InKj7RxE1CFzAdSdfOLJI5yQqnB10nYeou188ZEZjMVLA6I9E2jxlYhcYTtJMeC7Tdd8DIB/7qrzFrX6zcqItp2HSkwqSMBxQjxnh6gLDAIA0ghgnu0sRLRv0VgkDOAYpdSWZUctX9JqeLYO5R8vcCXEA5SJ9kqLVwngEgC1trMUOhZ2Oikai/QDcNCQwUNaZkybMatVN4dsZ6LSIxC4QUpCqLAdhaigBeJVish1tnMQUbvMALDfcSuOH1xRWV6T1AnbeYh24eqkUoqXB0R7IzAwCJSInGc7S6FjYafzlgCQc846Z27Cb4WWwHYeKlGJTDsWD3ci6gItaQeZM9MG285CRHsWjUVCAI4FsPXYFcdEebYO5SvPuJk7cES0V4HxagCsBmsTXcJvXidEY5F6AEvKyso2zJ0zb27ctHCaClmTDOJwnDBfy0RdpMWHiFxsOwcR7dUUAEMWLVhcXVdX1zcRtNrOQ7RbnnHZLk/UDplBFqYGwFLbWQoZLwY75xAAasWyFY0aOpQ2nu08VMK0BAiMLw77uIm6JNvnfTHA3kaifBSNRRSAFQCajj36mHlx3co+F8pbWjSMGDjgX1OifdGSrhWR1bZzFDIWdjooGov0AnAYgA2Hf+zwBSlp5RZgsi7utyoHYW73JeoCgYFAOwBOtJ2FiHZrIoCRdb3q4hMnTJoSD1q4jqW85gYp4yjeeCPaFy1pBWAxgGG2sxQqfiB23CIAZWNHj60cPGhIQ5xbgCkPJHUcSnG7L1FXZUefrwHA1xNRHsnu1jkaQHzlCSsnu0FKeL4h5TvXpByIwxtvRO2gJQ0ROd92jkLFwk4HZA/sOwzAppUnnDwr7rfwTDTKC23tgNzuS9Q12dHnQwEstJ2FiD6iAcA4AJsPOTiyIIk4d0xT3ksbF1C8T0DUHlrSlQAuBHi+RGewsNMxEwD0DofD7ry5c+clTCsPTaa8EfdbxEE5K41EXRSIVy0iN9jOQUQfsRCAP2/OvP696+r6JoO47TxE++RpFyHuqCZql0xLvAkBWG47SyFiYadjIgBSRx+1YoyB4aHJlFeSOqHYPULUddk+7yiA/razEBEQjUUqkRlcsfG4Y46f18qzdahACAQ+B1wQtVsgXi8Rudp2jkLED8Z2isYifQHMBLA5dtjh87kFmPKNq5PZsZp8WRN1lUGgReQk2zmICAAwFUBFTU2NTJ08ZVpCt/KDjgqGGyQRUtzkT9QeRnwg854/3nKUgsMPxvabB0DGjBpTM2Tw0OFxv8V2HqKPEAhSQVLCijVHoq7SJl2NTJ83Edl3KICWE489caKnPQSZhT9RQfDEVSIwtnMQFQot6bCIXGo7R6FhYacdsocmfwzAlpUnnjybhyZTvkoGrQricPFA1EWZQ5QxApmz1YjIkmgsMgTAGADblkSXLEhKK+9eUEFxdQpKhXjNRdROWrwyAGcA4Pt9B/BNpn3GA6gPh8OpeXPmzeWhyZSvkjoBx+HigSgXtKRDInKW7RxEJW4BAD1j+sz9+tT37Z/goclUYHyThuJkLKJ2EwgERgNYajtLIeEFYPtEAKSWH3n0aFEmzEOTKV9p0fB1WkIscBN1mZZ0OYCzwc9KIiuisUg5MgeZbzzh2BPmxIMWXh1TQUprT0KosB2DqGBoSfcSkVW2cxQSLlb3IRqL9AEwC8Dmww49bH8emkz5Lh60QCHMXkGiLsqO3awAcKDtLEQlagqAqsrKSj1j2oyZCd0Ssh2IqDNSOgkFh2szonbS4isAhwGotp2lULCws29zAUhdr7rQ8IZhjdwCTPkuqRPKcRze1STKAS3pGhE5x3YOohK1BED8qNiyUb5Jw+ehyVSg0sZVgGJhh6jdBALtAzjSdpJCwcLOXmQPTT4MwJYjDz9ydCpIBUa07VhEe+WbNIwIHPAoKKKu0uI7AI4GUGU7C1EpicYiAwFMBLD1gEUHTHWR5I5pKliudnkGIlEHaUnXicjHbecoFHyD2btxAPoASC5edMA0V5JsjqWCEPdbxEEZ7wwRdZlAoDWAZbaTEJWY+QBMOBzGmNFjxieDBHeiUsHSEkBEwEsvovbTmV2aBwLobTlKQeC7y94dBMCtrKwMjRrZOCap2YZFhSGpEwqKL2+iXAgyB/hdaDsHUamIxiJlyExD2bQ0cuhwLQECtmFRgXN1SsKKG8+IOsIg8AGssJ2jEPDKbw+isUglgNkANsc+Fhvpac9otmFRgXB1Eo5yFF/iRF1nMheU8wHUW45CVCrGItP+6B5y0MGTU5JkbzEVPFenFIQHKBN1hBa/VsScaztHIeBV356NBRACoA884KCpLlIssVNBSfpxwztDRLlhoD1kzlwjou43G4BWSmHihEmTUzrB9SoVvLRxbUcgKjiZm2tqFoABtrPkO35Q7tlcAOlwOKzGjRk3IRnE2dtNBSWp4w7vDBHlhhG/l4icaDsHUbHLDq7YH8DmRQsWD3JCKpw2nu1YRF3mahchJ8zrCaIOMggCETnOdo58x8LObmR7u+cB2LI0cujwwLC3mwpPMkjAcUJcQBDlQPYAv6UAx80RdbNGZNqw0ksOWTIxqRMh24GIckFgEJiAU0uJOkibdA0gp9vOke9Y2Nm9MQDKAPiHHHzIFFcSZbYDEXWUgUFaexICh7kRdZ1AYDSAhbaTEBW56QAMAEybOnVaSpIs7FDRcHXSOIqFHaKOMAgAqJkAamxnyWcs7OzebACBUgqTJkycnDTs7abCFA9alIJjbOcgKgZG/BoROcZ2DqJiFY1FFIBFALZOnTy1T1VVda2nU7ZjEeWMZ1wHorguI+oggXYBHGI7Rz5jwWIn2d7u+QC2HLj4oCFQKuSbtO1YRJ2SaccK83VOlANaghAA9ngTdZ8GZKbPpQ7/WGxiImi1nYcop1ydglIO2+SJOkhnzjo82naOfMYLvl01AqgGkF4aWTo5ZeLcL0kFKxAf2mg4YDchUVcJNAD0RWZqIhHl3lQAAgCzZs6a7nLMORWZtPHgKJ5/SNRRRgIF4CgAfP3sAQs7u5qBbG/3lClTpqZMkt8jKmjxoEUcxcIOUS4Y8SEiR9rOQVRssm1YiwFsGzliZG197/r9UjppOxZRzqW1J7zhRtQxAgNAagGMs50lX7FosYNoLOIgs6jYPHb02LrKisoqz7i2YxF1SVInlILi2HOiHNDiVwFyiu0cREVoAIBBAOJHHHbk+IQf5zkkVJRSOsnJWESdYCRQInK47Rz5ioWdjxoOoA6Ae+DiA0ckuaigIuDpFJRSii93oq7LTmaYisw5IESUO5PafjBjxowJabjc0kBFyTOuEt5wI+qw7M21E23nyFe80vuoacj2dk+bOm2Mr9LllvMQ5UTCj0uZ4thzolwQaA/AUts5iIrMYgDNjuOohsFDh7MNi4qVp12EeIAyUYdlb67NQuY8XNoJCztZO/R2bwWAESNGNrocsUlFIqnjSoR3h4hyQYtfKyIs7BDlSDQW6YPM8IqWubPn9jcw0BLYjkXULQLxAaXAyzCijuPY8z3jO8p/7QegH4BE48jG2sqKyuq08WxnIsqJzNhzTmEgygUjWgGI2s5BVETGZ/8tC/ZfONLVKX5eUVFzg5SEeIAyUYdlx56vsJ0jH7Gw818j2n5w4OKDRiT9BG8VUdEQCLwgJSGwHYuoq7JjzxsA9LYchahYzAaQAoCpU6aO5/k6VOxck1IKIe6kJuqg7M21JbZz5CMWdv5rEgAfAKZPmz7aVx6vgKmoJHRcKTg8EJwoB7JbgRfazkFU6LITSacAaHIcRw0ZPGRYiq3wVOQ8zam7RJ2Rvbk2GLy5tgsWdrD9fJ3pAJoAoHFk42ier0PFJhnE4ThhvuaJcsBIUCMiB9vOQVQEhgCoAODPnzd/gDZaeL4OFTvPuGyRJ+okgU4B2N92jnzDi7yMPgD6Akg1DG2orq6squH5OlRsAgkQGF8c9nQTdZkRHQLkcNs5iIpAY9sP5syaO9w1PF+Hip8RDSMaDsK2oxAVnOzNtcW2c+QbFnYytp+vc/CBh4xI+kneKqKilPBb4SDMnm6iLsqO3BwPoNJ2FqICNx1AEgAmTpw4KoDHuw9UEtwgZRzFwg5RRxnRYUA+ZjtHvmFhJ2MigAAAZkybMdpXXrnlPETdIqkTSilu/SXKBYFxAcyxnYOoUEVjkRCy5+sAwNAhQ4e5hmePUGnwjOtAePYhUUcZaABqGoCQ7Sz5hIWdjBnILipGjWoczTGbVKy87IJZ8X2QqMuMBJUicqDtHEQFbAiAcgBB48jG2vKy8grfpG1nIuoRrk5BKcVrDqIOEwDiA5hsO0k+KfnCTjQWqQfQD0ByyOAhVTXVtb083i2iIpbwWyWEcrZjEXWRkaAckJjtHEQFbHjbDxYtWDws6Se0zTBEPSltPDjcRU3UKUaCEDid9CNKvrADYCQyZT8sXrh4WDKd4Pk6VNSSOq740ifquuxW4FngVmCizpoMwAWAKZOnjAxUmq3wVDIEAt+kOdSCqBMMgmoRWWo7Rz7h1R0wHoABgHFjxg0KlM93VypqKZ2E4zi8Q0TUZQJANIAxtpMQFZpoLKIATALQDACNIxsbPePys4lKSipISogHKBN1mBENAIts58gnLOzscL7OyMbG4b6k+T2hoiYQuEFSworDfIi6ykAbANNs5yAqQH0A1AHwHMdR9b3r+3ras52JqEd5xnWMKB6gTNRBktmXUQ9ggOUoeaOkixjRWKQOwEAACQAY0K//oLThooKKX0LHFScxEHWdiK4Vkem2cxAVoOHItsJPGDehtzbaZBfqRCXDMy4c5ZT09RhRZwm0i8wmDUKJF3aww6Kib5++5ZUVVVWcxkClIBnE4TihUn/9E3WZgXEAmW87B1EBGoNsK/zkSVP6e4HLqg6VHN+kkRmMxSUZUUcZ0RXgZKztSv1dpKHtB3Nmzx2Y8lO+zTBEPUWLhm/SEgLPqSTqChENQE2xnYOoAE0F0AIAjSMb+2vl86ARKkmediXEA5SJOkxgKkVkju0c+aLUCztjASQBYOL4iYN88TjZhEpGwm+FQohjz4m6INs6sh+AWstRiApGNBYJI3NzLQEAI0aMGBog4BqMSpIbpKDgcD1G1EGZA5Rlpu0c+aLUCzujAMQBoHHkyKFaBbxbRCUjqRNKqRAnkBB1kcAkwa3ARB2xX/bfBgAG9B8wMM2Dk6lEeeIqgWJhh6iDMjfXVCMAXs+ghAs70VikFpmTtD0AGDhwEA9OppKS+fsucMB6JlFXiOgQMm0lRNQ+/dt+4DiOqutVV88zDqlUeTqFEM89JOoEafufhn38wpJQym8ig4D/jl+o713fl4sKKjVxv1UclPEuEVEXGOgaEZltOwdRARmI7B3WtolYhhOxqERp0RAxUCV9WUbUOQKdBsCzDsHCjgMADUMbqpVSjhZtORJRz0rquIIq5bcBoq4TMQBkf9s5iApIIwAXACZNnMyJWFTy3MCVkOJAC6KOMqKrwHZ4AKVd2BmFbBvWtCnT+3u+G1jOQ9TjUjoFRzmqtN8KiLrGQANQ48Aeb6L2GonswcmjGkdxIhaVPNckFYTn7BB1lECXi8hc2znyQSlfzTUiu6gYPWpUfx/pUv5eUMkSJP2EhHmXiKgLBABCyLSXENFeZCdiDQaQAjgRiwgAPOOitC/LiDrHZHZNT7edIx+U5DtINBZxAAxBdtT5iOEjBhmly+ymIrIjqeMKwjGbRF0hMB4yuxCIaO/6Zv+dnYjVnxOxqOR52kXI4aRSoo6SzK7pRpRoXWNHpfoN6A0gDEADwMCBAwemeXAylahkEIfDxQRRlwiMAjDcdg6iAjAA2W1umYlYvTkRi0qeQBAYXziplKhTDDKfLSWtVAs7/Xf8j5qa2l5aeMQOlSYDg7T2JIQK21GICpaIqQQLO0TtMRDZ9ee4sePrOBGLKCMVpBBSbCAg6qjsrumSH3leyoWd7TsUqiqrqgMWdqiEJYJWACGurIk6SWDKRWSs7RxEBWAkshOxGkc01qcDj589RAA8SSkRVjmJOkogCsAw2zlsK9XCznAAPgDU1taGw6Fw2HDUOZWwZBBXISdUqu8HRF2WHXnOwg7Rvm0fXjFgwIBazfUXEYDMOTtKcS1G1FEiuhws7JR0YScFACOHj+yVDtLcrkMlzRcfRjTY203UOZI5MmTE/2fvvqPjqq41gH/nlmmaUS8uJJRAQpIXIISaHuklJCIEUiHAg1RK8oCEPAiBhN5Dt8EYQjc2LrgzFDNjG3dssNx7lSWr9zL9vj9mEDMjyVY/M7rfby0vL90747VHIM2ZffbZW3YcRKmspLRYRdxErLzcXKchInzjIQIQiPihCLY8JOovA4bNMIzjZMchm1kTO3mIlQGPH3+MKxgOcruITK8t2Goo0Dkdi2gAotXzguPOiY4sL/Z3BABysnNdhhLhqHOiGH/Yb6iwyA6DKK1E12DG52XHIZvpEjslpcUC0VGbAQAYUzTGFTZCTI+T6XWE24QQpvuVQDREDACwAsiQHAhRKsuO/yI3LzcnHGHRNNEnfOFOCKjcZCPqh+hxeA6wMOOnOAeirzsCAPl5+S6WARPFFhNCEeb8tUA0FIxO8Iw30ZE447/IdLkyQ+yxQ9TFH/EJA9xvJuqfCAAxVnYUspnxE5wL+LTjfH5efnaEZcBEAID2YJuhC449JxoIA5EIuGNEdCROxK09HY4MZ5hTSYm6+MM+qIrKzA5RP8T6HOYAMPVnerMmdrrk5rIMmOgTHeE2YRiCozaJBsAwIhqY2CE6kjwAXYsuu81mZ2KH6FMhI4jo0V4zfkQjGpQAgELZQchkxt8aLuDTGsfMTFdW9JcoEXWE2qFw7DnRgBiIOAzDOEZ2HEQpLA+xHoe6riu6ZrFw3DlRIl/IZ6jQZYdBlFYMRAIw+XF4M36Ay0RyGTArdogARLvK+8M+QwWPYxH1lwFDwOS7RURH0ZXYOWb8MY5QOMSsDlESX7gDAgobKBP1Q+w41hjZcchkxsROAYAgAAghYLfabCGWARN1aQ+1Ck5kIBoIA/h0nDMRddc1lXT8uGOcwXCQiR2iJP6IT4ANlIn6yVARLeAwLbMmdvwAUJBfYDPQleEjInQdx+KKgqifDMMAYDCxQ9SDktJigei48wAAjCka42J/HaLu2ECZqP8Mw1ABZMmOQyYzJnbyEVtUjBs3PoO7RUSJQkYQ4UgICs93Ew1EtuwAiFKUJfYnDAD5efnOCMJmXIcSHVEEEYSNMBRoskMhSiOGBazYMZ1cxCp2HHa7ZhgRlusQJWkLthgKNP5sEPVDrPrT1LtFREfgBNA1dTE3J8cZERF+ciXqQWeoM6II/ngQ9ZUBQzUMI0d2HDKZKrFTUlr8ydm7IADY7Q49YnCyM1GyjnC7EIJlwET9YwAQTtlREKUoJ/Dp2Xen02k3hMH3GaIe+COdimEIfkgh6jP2OTRVYgefLioMALB6JFhiAAAgAElEQVTbbFq0JwIRxfNHfAAAYbpfEUQDF6vYyZAdB1GKciKuI6yu6zrXYEQ984d9EEJh4pOoj6JrMHP3OTTbp7YMxO0WWa02jY2TiXrWHmw1VFhkh0GURgwAcMiOgihFuRCX2NF0XQfXYEQ9CkT8UFk5TdR30Y0CHsUykYRusDabTTd4FIuoRx2RdgEoXHUT9Y8AYJMdBFEKSmhqqWuays01op4ZMBCI+A0OsiDqK/Y5NFtiJ6ELmc1q1QzwfDdRTzo59pxoIAIw+cKCqBdZALrmm6uaxuPwREfgC3VCFUzsEPVFbKPAJTsOmUyd2LFYLBob9xH1zIABX6jD0ASLD4j6zgiBiR2inlgQNxVLU1Uehyc6An/EJyI8WkDUD+YeYGG2xI6OuPPdVqs14WsiStQebhMwFC4qiPrIiH5wZQNlou40xDXV0TSNiR2iI/CHO6EI1Wyf1YgGxGCfQ9MldpIqdqwaYJjte0DUZx3R41j8GSHqM8OA+d5bifpCR1zFjqqqKo9iEfUuaAQhhADfUoj6zNQ/LGZ78QkHVS26rhmc50zUq7ARQigS5HQsov5RZQdAlIJ0xFXsqKqqcioW0ZH5wz5DZQNloj4wAPPlNhKY7cVriDt6ZbFadQguKoiOpC3YAgGNPyhEfWe291aivtAQV7GjqCqnYhEdhS/UIYTgXgFRH5m6xYrZFp8JiR2rxWJlGTDRkXWE24UQiql/URL1E1fhRN0lHsVSVE7FIjoKf8TX1TyEiI7KbLmNBNrRHzKqJB7Fslot/F1JdGSBiB+AAV3YubYgOgoBYYPJFxZEvUg+iqXwPYXoyPwRHxRFFZrBCaVEfWDq9ZfZEjs2JDTuU7ioIOqDWl+N4dRc/GEh6k4IISJCRN9MbKquC07FIupJQsWOoig8ikV0FGEjjGZ/Y0RX2OuQqCeKImLvK0LYVXP/nJgtsWNF3KIiEAgGhbmP4hH1SUe4VXSEW/nDQtSzrqNXxziOa7ao1laZwRClqISKHUVRVCPCxA7R0TQG60xdhUB0FAoACAgc5zwpIDsYmcz2iyIxseP3+4Uw27eAiIiGWVh2AEQpKKF5sojOcSYiIhq0WLGGqXcLzJbVSEjs+Pz+gMKKHSIiGirRz6pM7BB1pyFu0R0KhYLM7RAR0VAxYESO/qjRy2yJnYRFRSAQCBkGTP0/ABERDZ3Yx1Qmdoi6S6jYCYWCQcV0y1AiIhoW0Y0CU3+uN9s7agBx484DAX9QGMLUJVtERDSkBJjYIepJQmInGAwGFB6HJyKiIRD7gM/Ejon4Edfk0u8PhGDy/wGIiGgo8SgWUS8S1pyBQCDAPodERDQ0WLFjtndUH+Jes9/vDwqwYoeIiIaGgFAQ3UQgokQBJK7B/DyKRUREQyHWPDkoOw6ZzPaOmpTY8YV4FIuIiIaKIhQdQIPsOIhSkA9xVdM+v9/H5slERDQUFKHAgNEiOw6ZzJbYSdgt8vn9QXBRQUREQ0RAWAA0yY6DKAV1Ij6x4/OxYoeIiIaEKlTAMEy9sWa2d9Qg4qZi+XydIQUKK3aIiGjQoh9SDR/YY4eoJwkVOx0dHZ0C3FwjIqLBU4QKCFEnOw6ZzJbYCSEusdPp8wUF64CJiGgIKEKFAaNNdhxEKaoDiRU7AUCYutElERENDUWoEECN7DhkMltiJ6Fip7OzMyRM9y0gIqLhoAoVBtAsOw6iFJVwFKuzszMgDCZ2iIho8FShQEA5LDsOmcyW1QjFf9HR2RFUWLFDRERDQBGK6c93Ex1BcsVOEEzsEBHREFCFFhRC1MqOQyazJXYSKnaam5sDqqKZ7XtARETDIHa+u152HEQpKqFip6OzI6CAk0mJiGjwVKEGYPKppGZLaiRU7JQfOtiuqZra24OJiIj6SuX5bqIjSajY6ehoDwhhtmUoERENB1WoYTCxYyrBhC+CwUggGPCrQpMVDxERjRJK9Hx3pew4iFKUP/6L1rY2v8LEDhERDQFFqAaY2DGVUPKFjs6Odo2JHSIiGiRVaAHBo1hEvQkg7jh8+aGDrbqim20dSkREw0AVqgImdkzFDyChWXJrW2urpjCxQ0REg6MKNQiTLyqIjiAhsbN3395WXbNwAUZERIOmCEWDyddgZkvstCIpsdPU2NjIo1hERDRYilBDABplx0GUohISO8FgMOIP+H2smiYiosESUKxgYsdU/Ij22elq3ldXX9+oQOW4TSIiGhRVqIDJFxVERxBIvtDe0damKbqMWIiIaJQQ0bqNEJJ6uZmNqRI7HrfXAFAPwPrJtfr6ulYlonTrvUNERNQfqtAUcCoWUW9aky80Nzc3sWKHiIgGQxUqDBhtsuOQzVSJnZiExE51TXWLIlixQ0REg6MK1QFgn+w4iFJUM5LWnbW1dXUqK3aIiGgQNMUCA0a57DhkM2Nipw6A5ZMvKiorOJWBiIgGRRM6DBiNMHkZMNER+BD9+egq0amprWlk1TQREQ2GHt0g2CY7DtnMmNCoRlzFzoGDBziVgYiIBkVXdBgwDsiOgyhVxY7D1yGharqqRYEalhcVERGlO12xhBQoG2THIZsZEztN8V/U1tX6BGCIxGFZREREfaYrFghgq+w4iFJcDeISO+WHDjXrPIpFRESDYFGsHUKI3bLjkM2MiZ1WAF09dQzDQKfP18mpDERENFC6ogcVoW6SHQdRiqsGYPvkiz17dzdbWDVNRESDoCsWAGBiR3YAEnSbytDe2d6mcioDERENkK5YOwHskR0HUYqrAtC1k1ZdU90ZHVRrxuUoERENBU1oDjCxY8p30hYg8dxVQ0NDPUuBiYhooHTFIsBFBdHRNCO5arqzs0NTuLlGRET9pwoNBox2ABx3LjsACdqQlNjZv39/hWZobN5HREQDognNDlbsEB1NCwAj/kJrW2uLJri5RkRE/RcbXnFQdhypwHSJHY/bG0I0udM18nzP3t01GnSO2yQion6L2y1qlx0LUYprRtLmWmNTQwP7HBIR0UDE+uuYftQ5YMLETkw94qYylG0sq7bpdlViPERElKa4W0TUZ58ch+9K7hzYf6BSMzRurhERUb9x1PmnzJrYqULcVIb9B/a3GQYMVTC3Q0RE/RPbLdouOw6iVBermm5GXNX09p07qnRYeByeiIj6zaJYOOo8xqyJnT0AHJ98YRgGGpsb6y2K9QhPISIi6k4XeliBslF2HERpog5xVdPrPl5bZbPYeRaLiIj6jaPOP2XWxE4V4qYyAEBlZWUFEztERNRfumrlbhFR3yVUTVfXVPsCAb9PZwNlIiLqJ03odjCxA8C8iZ2a5Av79+8/rBpaUEYwRESUvqzRTYGtsuMgShP7EZfYAYDaurpqi2rr+dFEREQ9iA2v8CHav830zJrYqUe0Yqfr9e/YtaNGE5ZI708hIiJKpECBKjQrmNgh6qtKJI08379/30EdXIMREVHfWVUbDBibZceRKkyZ2PG4vWEAFQAyPrm2fsP6GrtuYx0wERH1mVW1IYLIdgCc6kPUN1VIGnm+a/euwxpYNU1ERH1nU2whBYpHdhypwpSJnZi9iEvs1NXV+v3BgF/jGW8iIuojq2ozBMQS2XEQpZEmAJ0AuhZc6zeWVdk0O0eTEhFRn9k0R4cQYpXsOFKF2RM7lvgL9Q31tRaVDZSJiKhvbKqjTRHKStlxEKULj9trILoGc35ybcfO7c2AMFTB3A4REfWNRbHaAHwoO45UYebETg2SzngfOnTokC4sRi+PJyIiSmBVbSq4qCDqr52Iq5o2DAMNTQ11nE5KRER9ER1zbjQCqJMdS6owe2Inwb59e6s4GYuIiPpCFRoERATRKT9E1HflSFqDlpeXlzOxQ0REfWFVbDCANbLjSCVmTuw0A/Aj7oz3R2UfV9o1h+j9KURERFGxaQxlSKr+JKKjqkLSz82ePXsqVUMPSIqHiIjSiE21+1ShemXHkUpMm9iJnfE+gLhS4A0by+qNiBFmA2UiIjqa2DQGLiqI+q8W0cRO1zp089ZNVVZW7BARUR/YNUcArNhJYNrETsweJJ3xPlR56KBNtUsMiYiI0oFNc7QLIVbLjoMo3Xjc3jCix7G61mAfr/+41qJZNQEWThMRUe8EBDSh2wGUyY4llZg9sVMOIGEEw+bNm3ZZYGWfHSIiOiKLYrUDWCs7DqI0tQtxk7H8AX+kvrGuxqY6JIZERESpzqraEEFkLwCf7FhSidkTOxXJF1atWbWfiwoiIjqS2DSGJnAaA9FA7UVcn0MA2Lp163arsIUlxUNERGnAqtgMAbFUdhypxuyJncOINlDWPrnw0fqP6gRERBNa788iIiJTi01j4JhzooHr1kB59do1e63CHpIUDxERpQGb5mhXhLJMdhypxtSJndgZ720Asj+5ZhgGKg5XlLNqh4iIemNT7X5VqItlx0GUxqoAiNgfAMAHy5ZWWDSLqgi192cREZGp2RSbABsnd2PqxE7MBgAJWZwtWzazzw4REfXKoWUEAXAiFtEAedxeH4CDSOqzU1VTVWHn5hoREfVAFRqEUASA3bJjSTVM7AD7kFwK/OHq/TbVbvTyeCIiMjFN6FCEGkZ0Y4CIBu4jAFnxFzZv2rTdAiuPYxERUTcO1QEDxhIkfX4nJnYAoBJACHF9dj5c92GtIlShss8OERElcWgZAIx3wEUF0WDtBBLnm69YvWKfXXVEJMVDREQpLEN3talCnSk7jlRk+sSOx+0NIdpnp2vHKBKJGJWHK8ttql1eYERElJIyNFerItQ5suMgGgX2x/7uWo+uWbumRkABh1gQEVEym+qwAHhHdhypyPSJnZgyABnxF7Zs3byTpcBERBRPQMCq2qwAFsmOhSjdedxeP6JVOwmba+UV5fvZZ4eIiOLZVDsMGAcQbb5PSZjYidqPpJL6NWs/PGBT7CwFJiKiLrFFxS4ADbJjIRolPkJcA2UA2LChbIcOW0BSPERElIIcmjOoQPAYVi+Y2Ik6BCAMoGu+5qo1K6tVRWOfHSIi6uLQnAEFChcVREOn22STpcuW7nVoGVyjEhFRlwzN5RNCWSA7jlTFN0109dnZgaRS4L379+5yqBm9P5GIiEzFoTn9Qgi37DiIRpFDSBpisWXblqZgKOjXFYu8qIiIKGVoQoMqVAFgrexYUhUTO5/q1mdn+fJlG21w+CXFQ0REKSS2qACiR0eIaAjENte2AMiOv75v/7497LNDREQAYNcyYMB4D9FTNtQDJnY+tS/5woK3F+yx6XZVEWpPjyciIhOJLSreB8D+a0RD6yMkba59vP7jnRbDys01IiJChuZqVYU6S3YcqYyJnU+VI6nPTltbW6j8UPn+DM3Z+7OIiMgUYouKN2XHQTQK7UPSEIuF7gW7HRanJrhUJSIyNQEBm2q3AnhPdiypjO+WMR63NwhgPYC8+OsrVq3YYDXsnMxARGRyNtVuARcVRMOhCkA7gK6mOvUN9f7DVZWHHBp7HRIRmVlsIulOAPWyY0llTOwkWgPAFn9hwVvzdzksGSp3jIiIzCu2qNgPoFZ2LESjjcftjQDYACAn/vrKVSvX2+Dg5hoRkYnFJpLOkB1HqmO2ItEOREuBu74v0R2jw9wxIiIysQzN5VegTJcdB9EotgGANf7CvIXzdmToTlVASAqJiIhky9CcASHEQtlxpDomduJ43N52AJsA5MZfX71m9QYbeByLiMisXHpmRAjxquw4iEaxHbG/u7I41TXVvura6sPcXCMiMiddsUARahDRCdZ0BEzsdLcSQMJ8zQXu+TsyLC7uGBERmZBdzYAB7EH0DxENA4/b24JocifhONbqNavX2+AIyomKiIhkculZQQAvI6nBPnXHxE5322N/d2VxKiorOurqa6vt3DEiIjKdTD2rXYEySXYcRCawHEDCKNL5b83bnqE7FW6uERGZj0vPCipCeVF2HOmAiZ0ksR2jnQCy469/uHZtmQ127hgREZmIgIBdy9CEEGzaRzT8tsb+7sriHKo41FFVW13p0Jy9PIWIiEYju+oAgAoAmyWHkhaY2OnZcgCu+Atvvb1we4bu4veLiMhEMjQXDBgrAdTJjoVotPO4vY2IHnnMir++bNmydXZksNchEZGJuPSsDgXKM7LjSBdMVPRsK6K7RV07Rrv37m5tbmluiGUOiYjIBDL1rFZVqM/KjoPIRJYhKbEze96b2x26Q1W4bCUiMgUBAYfmVIUQU2XHki74DtkDj9vbAGAfgMz466vXrPrIoTh5HIuIyARUocKi2jQAC2THQmQiW2J/d22uNTQ2BPaXH9iTobt6eQoREY0msYrp1QBqZMeSLpjY6d1yJO0YTZ81fWOG5lS4Y0RENPo5tcwIYMwD0Ck7FiKz8Li99QB2IanX4eIl3o9tcPjlREVERCMp05LdqgqVx7D6gRmK3m0BEkcwVB6u7Nx/8MCeDM3FcWtERKOcy5Ldrgj1edlxEJnQYiRVTc9dMHe3VbUpqtAkhURERCNBFRosilUFK6b7hYmd3tUAqERSE+W333WvcSguHsciIhrFdMUCTWghAEtlx0JkQpsBRBC3TvX5fOFtO7ZtdqqZEXlhERHRcHPqmRHAeBOsmO4XJnZ64XF7DQBeADnx1+e/NX+fiIiQRbHKCYyIiIadS8sMAngFQFh2LERm43F7WwFsBJAXf/2NGdNWObVM/kwSEY1imXp2hyLU52THkW6Y2Dmyj2N/d32fIpGIse6jtesyFFdIUkxERDTMXHpWUBHKS7LjIDKxZQDs8Rc+XPdhbWNjY12GxibKRESjkUWxQhVqB4AVsmNJN0zsHIHH7W0EsB5Afvz1N2a98bFTz4RIbMFDRESjgF11QAhxGNGKASKSYyuAEICEpjrvvPv28gzhCsgJiYiIhpNLz/IL4DkA7GnbT0zsHN0SJO0Y7di5o/lw1eFDTu4YERGNOtmWvDZFqPfLjoPIzDxurw/AKgAF8ddnvDljuwotwiPxRESjjYBLz4wIobwiO5J0xMTO0W0D0AbAFn9xoXvhCofCHSMiotFEVyywqjYDwFTZsRARFgOwxF/wB/yRNWvXrOGReCKi0cWluWBEW6Hslh1LOmJi5yg8bm8IgAdJO0Zz5s/eg7AIWhVbz08kIqK0k6Xn+ABMAOCTHQsR4QCA/QCy4y++NvXVdU49EwqXsUREo0a2Na9NFepdsuNIV3xH7JvViH6vuprqRCIRY+XqFau5Y0RENDooUODUM6EIZYLsWIioa0KpG0BW/PX9B/a37Tuwb3eGlskeDEREo4BddUAVag2A92XHkq6Y2OkDj9tbheiRrNz4669Nfe3jDN3FHSMiolEg05IdBoz5AKpkx0JEXTYC6ACQ0FRn9tzZK11qJjfXiIhGgZxof8O7wabJA8aMRN+9C8AZf6GisqJj7749O53cMSIiSntZlly/ItQHZcdBRJ/yuL1+AO8BKIy//r53UXlnp6/VrjrkBEZEREPColhhUW0hANNkx5LOmNjpuy0AWpE0IeuNmdOXu7TsEDj6nIgobWVEpxxuA7BecihE1N0KRBdaXetWwzDg8b7P0edERGku25LbKSAeBcDf54PAxE4fxZoovwsgP/76B8uXHq6trT3M0edEROkrx5LXpgr1HtlxEFF3Hre3DtGka8Igi9ffeH2zTbNDE7qcwIiIaFBUocKhOSGEeEZ2LOmOiZ3+WYWkHSMAmDp9qidTzQ7KCYmIiAbDqtigKXo7gIWyYyGiXi0CkDCKtKW1Jbhh44b1TjUzLCkmIiIahCw9JwhgCoAG2bGkOyZ2+sHj9jYAWIekc97vLnrnYFNTc51Ty5QTGBERDVi2Na9dQDwAgB8OiVLXTgA1ABJKpKdMm7LGqWcaHGRBRJReBAQyLTlhRSgPy45lNOC7YP912zECgJlvznjfpWTxXCARURrRhAa76hBCiBdlx0JEvfO4vREAbyFpQunmrZsb9+zZvcOlZUXkREZERAPh0rMMA8YHAHbLjmU0YGKn/3YD2IGkXjvzFs7b29HR0ZKhOXt+FhERpZxMS04AwIuINscnotT2EYAggISmOpP/M9mTqWdHWLVDRJQ+si15HWp0xDkNAb4D9pPH7TUAzEXS6HPDMDB77uz3XUo2q3aIiNKAIlRk6tkRRSiPyI6FiI7O4/a2A1iMpCPxm7Zsaty1e9c2l5bNqh0iojQQa5i8H8BK2bGMFkzsDMx2APuQVA48480ZOwP+YLtdzZATFRER9VmOJc+PaMO+A7JjIaI+WwpAQ9Ia9tnnn/WyamfkzXp9Nj6XeXKPfyrLK7FiySpc9J1f4CtjT8d/n/5DzHh1VtdzO9o7cNXF1+LU8V/DtZddB1+nr+ve9s07cPkFv5HwiohoJMSmkd4FwJAdy2jBd78BiFXtzAGQ0C05EokY8xfO97Bqh4gotalCg0vPiihC+ZfsWIio7zxubyWANQCK4q9v2balacfO7VtYtTOyfvyzUqzetazrz8odS/HlU7+EH174A/j9AfzxV9fgBxf8NxYsn4Pr/v5n3PG3u+F52wsAmP7KLNTXNmDOkpmorqzGGy/P6Pp3n3xgIm74x//KellENIwcagZ0Ra8FMFt2LKMJEzsDtxnAIQBZ8Rdff2PKViNs+G2qXU5URER0VLnW/E4AzwCokh0LEfXbAgBWJK1jJz3/7OLo8UpVTlQmZLPbUFBU0PXn3fmLcPjQYdz/1D14a/bb+NJXTsaf/u8aHPe5Y3HhxRfgp7++EPOmLwQA7N21F+d+52yccNIJOPc7Z2Pvzn0AgC0btqK9rR1nfv0MmS+NiIZJnq2oXRHq9eA00iHFxM4AxaYzzAaQE389FAoZb7/j9rJqZ/gdrfy34mAFrrzwd/ivMV/FD84oxZL3Puj13wqFQrj/1gdx9onfxCnjTsd1V/4FdTV1XffXrf4Y3zvl+zjz+HMTdpQA4P5bH8Sbr88ZttdJRENLFzoyNFdEEcr9smMhov7zuL0ViPZlSKja2b5jW/O27Vs3u9QsfliQoK21DRMefBp/ue16ZOVk4fyf/hB3PJJYFCmEQEtzCwBg3DFjsW3TDgSDQWzduB3jPjMWAPDk/RNwPat1iEYlp5ZpqELZieiUQxpCTOwMzgYANQBc8Rdffu3ljaqhhaxKt6noNISOVP479pixuPrXf0Z2bjbmLJmJn116Ef78P9ejfP+hHv+tJ++fiEVvefH0a09ilmc6GhuacOMfb+66f9f/3YOLf/NLPPHSY7j75vvQUN8IAKitrsXKpatx0SU/GZHXTESDl2st6BDAwwAaZMdCRAO2EIAF3ap2Ji3O1LMNVu2MvGkvTYfFasGvrvwFAOD4k47HV776X13362rqsPBNN77xvXMBABf/5leoKK/ElwpORW11LX7924ux8aNNCPgDOOOc06W8BiIaPgICedaCTkWo/wv21hlyTOwMgsftDSNatZPQRNkf8EcWeRYtyVRzWLUzjI5U/rvqgzXYu2sf7nvqbpx08om45sarcPrZX01o2hcvEgnj9oduxRnnfg2f/+JJ+M21V2DtirVd9/fs3IvzLvg+vvHdc5GZlYnyfeUAgEmPPoc/XPc7qCoXkETpwKJYYdcygkIoj8mOhYgGLtZrZzmAMfHXd+7a2bJl2+aNmWo2q3ZGkGEYmPbiDFxx9eXQdb3b/Y72Dlx72XUoGlOIy/9wKQAgNy8Hb6+ej1U7P8DCFXORlZOFJ2LVOutWfYTzzjwfpef+BGVrN4z0yyGiYeDSs8NCiBXgJKxhwcTO4H0EoBFAwiis516c/DFCws8JWSMjufy3bG0ZvnTKF+F0fTqV/oxzTsf6tWU9Pv+mO/+G7/3wuwCiO0ozXpmJc759Ttf9cceMxeYNW1FxsALNTc0YM74IVZXV+HDFWlzwy/OH9bUR0dDJtRa0C4g7AbTJjoWIBu0tADqSq3YmT1ri0rMMlVU7I2Zz2RYc3Hewxwrm1uZW/PZnf0T5/kN4fsazsDs+7UMphEB+YT4AYP2HZYhEIjj97K/ilj/fhlvuuQk3/usvuPnaf4zY6yCi4aFAQa41L6AI9S+yYxmtmNgZJI/bG0R0QlZ+/HWfzxeeOv31hdlablBOZOaSXP5bU1WLorGFCY/JL8xHVcWR+6Q+cvfjOPvEb2Ldqo9x2wO3dF2/6a6/4ZY/34bvnfoDXHXDH1A0tgiTHpmMq274Pat1iNKEVbXDpto7hRCTZMdCRIPncXurACxDUtXO7r27Wzdt3ljmYtXOiFm6aBlOO+MUFI1NaHuEhvpGXPbjK1G+vxxT3a/g2BM+2+u/8eT9E3DDP/4XTQ1N2Ld7P77+3XPxreJvYM/OvWhtbh3ul0BEwyjbkhsEMBfAVtmxjFZM7AyNDxHd/U0YhTVz9sydDfWNVS4ti2cIh1FP5b++Th8sFkvC4yxWCwKBI5+O+/mlP8WcJTNxzrfPwpUX/R6tLdFN/fMu+D4+2r8a6/atwl//eT0qDx3GR2s+xo9/cT4euesxfPNL38P1v7kRnR2dw/MiiWjQ8qwFbQLiZgB+2bEQ0ZB5C4AGIGGX5ZnnnlnKqp2RU7a2DGd986yEa4FAAH/85TVoqG/EtLen4ISTTuj1+etWfQRFVfHVs06DEAIAEIlEEAqFAETXekSUnlShItOSE1KE+nfZsYxmTOwMAY/b60e0aiehRMQwDDz97MSFWVpuWOG3etj0VP5rtVq7JXEC/gDs9iOPoT/+xONwyulfwaPPPYzO9k68u+C9rns2uw2Z2ZkAgGceeRZX//WPKFu7AQtmvYV31ixAOBzCq5OnDOErI6KhYlcdsCiWJiHEa7JjIaKh43F7qwEsRVLVzr79+9o+Wv/R2iw1NyQnMnPZuW0XTjr5xIRrLz39CjaXbcFDz9wPR4YdtdW1qK2uRVNDU7fnPxGr1gGArJwsfPa4z2DWlNmYPXUujj/xuK71FxGlnxxLvg/AcwDKZccymjHbMHRWIDphJWFC1pq1a2q27di2KSNN3ZAAACAASURBVEvLYTnwMOmp/LdoXCFqq+sSHldbXYuCMQXdnh+JRLDoLU/CeHO7w45jjh2Pxtj0q3gVByuwYd1GnP+zH2H92jKc+rVT4XQ58Y3vfh3r2eCPKCXlWQvbFKHeCIAf8ohGn7cRrdhJKM959IlHlliFPWhVj7ypQ4NXV1OP7JyshGvuue8gFArhip/8Fuec9K2uP1dd8qeEx61Z/iFsNitOPeOUrmv3PnU3Jj/xH7ww8SU8+PR9I/IaiGjo6UKHU88MK0K5W3Ysox0TO0MkVrXzOpJ67QDAY08++n6GlhnRFUv3J9Kg9VT+e9qZp2Hbpu3oaO/ourZu9cc47cxTuz1fURTc+X/3YN6MBV3XWptbcWDvAZz4+c91e/zEhyfhmhuvgqIoEBAwjAgAIBQKsVSYKAVlaC5oilYJ4E3ZsRDR0PO4vTUAliCpaqehsSEwa84sd46ax36Hw2xrzYauIRSfmLf0Texp2d7tz4z3piY87uxvnoX/zJyccO0b3z0Xy7cuxpKN7+OMc7823OET0TDJtRV2COABRAsgaBgxsTO0ygDsAJBQFnKo4lCHd4l3SZbKRsrDoafy37O/eSbGf2Ycbr72H9i5bRcmP/48ytZuwCVX/hJA9Nx3bXUtwuFoIdUVV12GSY9MxtJFy7Bj60789Q//h+NOPA7f+cG3E/7dg/vKsWXDVpT+9IcAgK+c/l9Ys3wttm3ajvcWvo/T4nabiEg+AYF8W1GHItQ/AIjIjoeIhs3biK5rE6p2Xpny8ubmppYa9jskIhpZVsUGu+rwC6E8LjsWM2BiZwh53N4IgKmIjj5P+N5OmPTUGiWs+jj+fOj1VP6rqiqenfY06mvrceG3f4450+Zh0usTcMyxxwAAPl6zHuec9C0cPnQYAPCH63+HK6+9Arde/y/8vPhiaLqO5954BoqS+CMy8eFncO3frupq7Hfm18/ABb84H5f86HI4HHZccfXlI/CKiaivcix5AQG4EZ2cQ0SjlMftrQWwCMC4+OuGYeCpp5+cl6XnhhU2UiYiGjH5tqJ2AXELgI6jPpgGTfDoyNArKS3+LYCvA6iIv37JLy/5wuWXXf7zw/5yXU5kRETmoSsWjHcc264I5UQAVbLjIaLhVVJa7ATwEIB2JH2QeOjeh3504hc/d3pDqFaTEhwRkYk4tUwj31a4VRHqKWDF9Ihgxc7wmBf7O6GpzvRZ03c0NjRVsxyYiGj45VuL2gXEP8GkDpEpeNzeNgBTABQl33v4sYe9NsUesiq2kQ+MiMhEFKEi31boU4T6P2BSZ8QwsTMMPG5vA6Ljz8fGXzcMA89Mfprjz4mIhlmG5oJVtVYJISbKjoWIRtQaALuR1O+wvqHeP3vuHHeOls9+h0REwyjPUtAJiFcArJcdi5kwuzB8PACakDT+fNWaVdU7dm7fkqXlcvw5EdEwEFA+aZj8W3C8OZGpxPodvgrAgaRGyi+++sKm1pbWOqeWycppIqJhYFXtyNBdnYpQ/i47FrNhYmeYxMafTwGQl3zvwUcefNeuZARtqn3kAyMiGuVyrfl+Ea2aZMNkIhPyuL0HEN1g66GR8lNzs7U8NlImIhoGhbYx7YpQrgHQIjsWs2FiZ3itB7ALSeXAVdVVnVOmvjY3VysICgg5kRERjUJWxQaXnuVThHq97FiISKp5AHwAEnbRVn+4umbzlk1lWWoOq/mIiIZQlp4bUoX6MYBZsmMxIyZ2htGRxp9Pmzltx4GDB3fzSBYR0dAptI/9ZKeoQXYsRCSPx+1tBTANwJjkew899vD7diWDjZSJiIaILnTkWPMCilCvAMDjrhIwsTPMPG7vPkSPA4xNvnfvA/cscChOHskiIhoCsZ2idQCmy46FiFLCKgB7AOTHX6yrq/XPnjvbnaMVBMHKaSKiQSuwj20XELcB2C87FrNiYmdkvAkgiGgjvy6Vhys7X582ZR6PZBERDY726U7Rb8CdIiIC4HF7wwBeA+BE0pr3xVdf2FRdVXUgm5XTRESD4tKyIhbFskcIMUF2LGbGxM4I8Li9TQBeQrQcOCGDM3XG1O0Hy8v38EgWEdHAFdrGtgvgLnCniIjixCqnveihkfId99wxx8FhFkREA6YKDXm2Qr8i1F8D4OdZiZjYGTnrAHyIHo5k3XP/3fN5JIuIaGCy9NyQRbVsE0J5VHYsRJSS5gIIIKmRckVlRcdLr748O08rDAouiYmI+q3ANqYDwMMAtsqOxez4LjZCPG6vgej48xB4JIuIaEhYFRtyrHk+Rag/A3eKiKgHHre3BdFhFt0aKc+aM3PX9p07NudoeZySRUTUD04t07CptsOKUO6XHQsxsTOijnYkq5xHsoiI+kxAoNA+rkMRym8BlMuOh4hS2koA65F0JAsA7rr3zrfViN6ZoTlHPioiojSkKxbk24o6FaFeiGhFJEnGxM7I6/1IVmxKlpVHsoiIjirPUuhXhTIXwCzZsRBRavO4vREAryBaOZ0Rf6+5pTn45MQnp+doBSFVqFLiIyJKFwICRbZxHQLiLwC2yI6HopjYGWFHOpJVUVnR8fobr8/L45EsIqIjcqhOw2nJrFOEerXsWIgoPXjc3kYAzwMoRNIaePFSb8XqD1evytUKg1KCIyJKE7mWgoCmaO8LIf4jOxb6FBM7EsSOZL2Mno5kTX99+8Hy8j3ZPOtNRNQjVWgosI3xKUK5CECb7HiIKK2UAVgKYHzyjQf//cASf0egyaVlGSMfFhFR6svQnHBZMhsUoV4BgL8rUwgTO/KsRS9Hsv55x21ztbClI0Nz8YeFiChJoXVspxDiXkSPthIR9Vmscno6gCYAWfH3/AF/5IF/PzA9S8sN6YpFSnxERKlKExryrWN8sb46zbLjoURM7EgSW1i8jh6OZNU31Psf+Pf9r+do+VxYEBHFydJyw1bNukERyoOyYyGi9ORxe9sBTAaQA0CLv1e2YX392++638vjkSwiogQF0Y21OxEtTqAUw8SORLGz3i+jhyNZa9auqXlzzpsLC/QxQcH/TERE0dHmtrwORai/ABCRHQ8RpS+P27sTwAL0cCRrwqQJ6+rrGiqztFz+niEiApCt54UsmnWtIpR/y46FesaMgXyfHMnqtrD4z8vPb9y5c+eWPL2Au0ZEZGoCCgpt4zoVoVwJoEJ2PEQ0KiwAcAhAQfxFwzBwxz23z3QIp9/BEehEZHJ21YFsa26bKtRfghtrKYuJHcliR7JeQfSsd07y/dvuuG1hsDPc7NKy+ENERKaVZyn0q4o6E8Ac2bEQ0ejgcXsDiB7JsgFIOPt+4OCB9keffPT1XK2Ax+KJyLRUoaLANtanCOUXAGpkx0O9Y2InBXjc3lYAEwG4AFjj73V0doRvv/v2KZlqTtCm2qXER0Qkk0vLjjgtznJFKH+SHQsRjS4et/cQgGnooXJ68VJvxdz5c98q0McEFS6ZiciE8i1jfIpQngLgkR0LHRnfpVKEx+3dj2i/nfFI6rezfce25hdefmFWnl4UVIUqIToiIjnsqgN51vw2Raj/DaBddjxENCotBrAZPUwqnfzCs2Vbt27dkKcX8Vg8EZlKlpYTsen27YpQbpMdCx0dEzupZRmAJQA+k3zjzbmzdq9dt3YNFxZEZBa6YkGhbaxPUdTzARyQHQ8RjU4etzcM4EUAAQCZyff/eec/325rbq/J0nLDIx4cEZEEDjUDOda8FlWoP0F0ijOlOCZ2Ukis385URBuDFiTfv+eBu73NDS1VXFgQ0WinQEGhdZxfEer/AlguOx4iGt08bm89gAkAcpF0LN4f8Edu+effp9rh8DtUNlMmotHNolijfXUU9TwA5bLjob5hYifFeNxeH4CnAegAHPH3QqGQcevt/3jDLjICDjVDSnxERCMh3zImqEB5UQjxguxYiMgcYiPQX0H0WHzCGvlQxaGOBx956LVcvSBoUaw9Pp+IKN2pQkWRbZxfEcoViE5upjTBxE4K8ri9VQAmASgCkNBU51DFoY4nJz45NVcv5JQGIhqVsrW8sEWxfqhr+vWyYyEi01mCaJPQbsfiV6xaXjVj1vT5BZYxQYU9D4lolBEQKLCMDShCfUAIMVN2PNQ/TOykKI/bux7AW+hhYfG+d9GhmW/OmF9oGRdUhTbywRERDROnmmm49Kxqi275MXimm4hGWOxY/DQAuwGMSb7/0msvbS7bUPZRvlbInodENKrk6YUhFepCVVHvlh0L9R8TO6ltDoAd6GFh8eKrL276YNkHHxRaxnIEJxGNCjbVjlxrQaeu6d8F0CQ7HiIyJ4/bGwDwDAAfgOzk+7fffft7TQ0th7O1PPY8JKJRIUvLjVgV21arxXYpAEN2PNR/zAikMI/bGwQwGUAQPUxpeOjRB5dv37Z9Y75lTDBpQjoRUVrRhI4C69iApmoXAtglOx4iMjeP29sI4ClE11+2+HuhUMi4+dabplkitk6nlskPQESU1pxqppGpZ9VZLbZiAH7Z8dDAMLGT4jxubwOizZS7TWkwDAO3/OuWt2oO1x7I0wt4ZIGI0pKAgkLL2IAilJsBvC87HiIiAPC4vXsBvABgHJLWzNU11b57H7zn1Sw1N2DnQAsiSlM21YFca36nrlm+DaBedjw0cEzspAGP27sd0YXFeAAJTXVCoZDx15v/Mt3fFqhjSTARpaN8vTCoKtp0VVGfkh0LEVGSlQDeAfDZ5BtrP1pb++iTj07J0wuCNtU+8pEREQ2CLnQUWMYEBJQfI9r+g9IYEzvpYzmAWYguLBL+u7W1tYX+9ve/vaqFLe0uNYslwUSUNvL0wpBFsa3SNf334JluIkoxsWbKMwFsBTC22/3F7x969vln38jXx4Q4Bp2I0oUiVBRaxwWEENepqrpYdjw0eEzspInYwmIhoiM4u+0aVR6u7Lzt9ltfcqpZfgdLgokoDeRo+WELbJusFut5iPYSIyJKOXE9D9sQPRqfYN7CeXtfnzZldqFlbEgX+ojHR0TUHwIC+XpREIaYrKnac7LjoaHBxE4a8bi9EQCvAyhDD2PQt27f2vTgvx98JVcvCFpZEkxEKSxbywtbYNtrt9m/jejkGSKilOVxe5sBPIloI2VX8v0pb0zZNn/hAnehdVxQFVq35xMRpYJoUmdMSIX2jtVi/YvseGjoMLGTZjxubwjRXaOD6KEkePnKZVXPvfDc9AJ9TFBXLCMeHxHR0WSqORFLxFadYc84C9EdcCKilOdxew8CeBTREeiO5PuTnn9m/dKlS5cWWsYFFaGOeHxEREcmkKcVhURYWWy32n8GICI7Iho6TOykIY/b24norlELgPzk+3Pmz9kzZ/4cd4FlLHeNiCiluNTsiA2Opo729tMBNMmOh4ioPzxu7w5E12CFSBqDDgAPPfbQivXr168t1McGBZfZRJRC8rTCkBE01jgznOcD4ETlUYbvOGnK4/Y2IbprJABkJd9/7oXJZUuXLl1SZGFJMBGlBqeaaWQorrb2tvavFhYWVcuOh4hoIDxu70ZEq6fHAuhWHn373f9atHvX7i0FljFBATHi8RERJcvTCsPBztCmrMzsYrCv4ajExE4a87i9VQAeQ/Ssd7eS4Icfe2jl4sWLFxdZxgc1JneISKIM1WVkqtmdTY1NZxYVFh2UHQ8R0WB43N5VAF4BcAyAhEWWYRi46dab5h8+VLU3Ty/iBygikipXKwz724M7Q8HQuQACsuOh4cHETprzuL17AExAtCS4267RI08+smqRZ9H7RdbxQY2TGohIAofqRLaW66+rqz933NhxO2XHQ0Q0RBYjOgr9s0haU4dCIeMvN90ws7m+pSJXL+SRByKSIlcrCAc7Qnuam5q+NqZojF92PDR8mNgZBTxu7wb0smsEAE9MePzDt9955z0md4hopNnVDORo+YHq6prvHTP+mI2y4yEiGioet9cAsBDA2wCOBRLPXfl8vvD1N1431d8aqM3VC5jcIaIRlaMVhEOdkQM1NTVfO+nEz3fKjoeGFxM7o8cSfLpr1C25M2HSU+sWvrXgnSLr+KDO5A4RjQCb6kCeXhisqjr8o89+5rOrZcdDRDTUYsmd6QA+QA/JnZbWluCfbvjTyx1NvioeyyKikZKj5YcjPuNQXV3daV/+4pc5gdQEmNgZJeJ2jaYjmtzplr155rlnPp43f6670Do+xFHoRDScHKoTeVphsKKi4qJjP3ucV3Y8RETDxeP2RhCtnF4H4DPJ95uaGgPXXHf1Kw01jQcL9LFsqExEwypby4sYfnG46nDVaSd//uRW2fHQyGBiZxSJJXfcAKYhurDoltyZ/MLkstlzZi8osoxjcoeIhoVTyzSylFz/9u3bzjv+uOPdsuMhIhpuHrc3BOB5ANvRQ3Knvb09dO1110ytOFixs8AyLqhwCU5EwyBby42IgFpdV1t76pe/9OUm2fHQyOG7yigTS+68A2AKoguLbtmb/7z8/MYZs2bMK7KMC1kU60iHSESjWKaWHXFEnJ3LVyz77qmnnLZYdjxERCPF4/b6AUwEcADRvocJgsFg5Lobr3tz57YdGwot44KqUEc8RiIavXK1gjD8alXV4apTP3/SFxpkx0MjSxiGITsGGiYlpcUlAK4EcAg9jLa74rIrv/TrX/36pzWBSi0QYZN0IhqcbC0vDJ/SvuCt+d+78vLffCw7HiIiGUpKi50ArgNwEoCDyfeFELj91juKzzrzzHOqA5V62GBfZSIaOAGBPK0o1NLYsmfrtm1n/6DkB82yY6KRx4qdUczj9noAvITorlG30pxXX39l62tTX3uz0DIuaFXtIx4fEY0euVph2N8SbJz8wrPfYlKHiMzM4/a2AXgcwCYAxyGpobJhGLjrvju9ixcvXjzGOj7Io/FENFCqUFGojwsdOljx8ZSpU05nUse8WLFjAiWlxd8B8HsAFQC6leZcdMFFJ1z9h6svbgzV6+2hVnb0I6I+ExDI04tCDTUNh5974bnv3n/XA3tlx0RElApKSostiK6/zkH0eFYk+TFX//7q0y76yUXn1wQOs3qaiPpFVywo0MeE161b55n47MQL33h1uk92TCQPEzsmUVJa/C0AfwBwGEC3H/qzzzy78La///MKn2i3NYcaeeibiI5KgYJ8fUyo/ED5rgmTJn7vmSeeqZYdExFRKikpLdYAXAagBNHkTjj5MZdefNnJ/3Pp//y8Llil+cKdIx0iEaUhq2pHvlYUdr/rfnPipAm/8bi9/OVhckzsmEhJafHXAVyNXpI7xx17nPPh+x6+QrWrOQ2hWg3g/xtE1DNVaCjQx4S2bdu+7vGnHjtvyouvt8iOiYgoFZWUFisAfg7gAkR77nRrqnPhjy884Zo/XntJfbBG7wy3j3SIRJRGHJoTOWpeaNr0aRNfm/ba3z1ub7deqmQ+TOyYTElp8TkArgVQDaAj+X6mK1N/9KFHf1k4tvC4ukCVHuleNUxEJqcJHYWWseG1a9e++9SkCb+YOWUmd4mIiI6gpLRYACgFcDF6GWpR8r3/PuZvN9x4eUuoydIabubReCLqxqVmGRkiM/jSqy/+c/a82Y963F5+WCMATOyYUklp8amITmtoB9CYfF9RFHHPHfd+/7RTTz2jNnBYDxrBEY+RiFKTXXUgVy8ML1myeOrDjz/8e4/by18QRER9EEvufAfA7wBUoofq6f/60n/l3H37PVdE9JCzMVSnjXSMRJS6srTcsBrU/ZOem/TH972LpnncXn6Qpy5M7JhUSWnxcQD+CsCCaPVON3+++s+n/7j0gh/WBat0nvkmokwtO5IhMsNvzHzjwSnTXrvL4/Z26xVBRERHVlJafDai1dO1iG6yJcjLzbM+8uCjl+QW5Ixn9TQRAUCuVhDytfhbJj478Zf33nGfV3Y8lHqY2DGxktLiPAA3ABgPoLynx1z44wtPuPoP11zcFObELCKzEhDI1QtC/tZA+4RJE/66cvXKl7lLREQ0cCWlxacgugZrAtCafF/TNHHP7fecd8opp5xeG6zSgxG20CAyI1WoyNUKQ9WVNVVPTHi8dOLjT2+SHROlJiZ2TK6ktNgB4CoAX0UvozjP/NqZBf/6x+1X+kSHvTnUoIx0jEQkjyZ05OtFwZ07dlb8+/F/X11VXbWISR0iosErKS3+AqLV02FEq3e6ufr315x20U8uKmVTZSLzsal25GmFoRWrVn707H8m/WLGazMPyY6JUhcTO/TJKM5fAfghemnod+xnj814+L6Hr9Az9NyGYI1mcGIW0ahnVx3I0wtDcxfMW/ufl56//r0Fi9bJjomIaDQpKS0eB+AvAHIAVPT0mO+X/OAzN/z5hl+3G62WllCjOqIBEpEULi074lIyw/956YUZc+bPvs7j9nbri0oUj4kdAtDV0K8YwP+glzPfTqdTe+DuBy48/oTjv1AXrGZZMNEoFuunE3p8wuNzPYvfv8Xj9u6THRMR0WhUUlrsAnA1gK+gl+rp44873nn/XfdfZnPZ8hqCNey7QzRKCSjI0wuCHS2+9vsfum/ilm1bHvS4vSzXo6NiYocSxM58X4foKPQeM8PX/OGar154wUU/agzV6e2hbsfCiSiNRfvpFIZ8Lb62u+6/65kdO3f82+P2NsmOi4hoNCspLdYRrZ4+D71UT9tsNvXeO+/70RdPPvkU9t0hGn0sihX5elFwfVnZ/gcfeeCxtra2Fzh9lPqKiR3qpqS0+FhEz3xb0cvErHPPPrfo73+75dKQGnA0hep5NItoFNCEjgJ9THDbtu2H7nvo3jubmpumcUFBRDQy4sah/wZAPXpoqgwAV/3uqlN/euHPzm8I1uod4bYRjJCIhotTyzSytdzwS6+9vHLGrOn3AXjf4/ayNI/6jIkd6lFJaXEuotMajkF056jb/yh5uXnW++9+4Gfjxo89vi5YrYcMfv4jSlcONQO5ekFo9rw5a1985YW/hcPh1WySTEQ08kpKi08G8L8AVPSywfbNr39rzE033nRZSAnYGoN13GAjSlMCAjlafggBxXfPA3fPLdtYdrfH7d0lOy5KP0zsUK9KSovtAK4E8HVEG/r5kx8jhMD1f7rhrB/+4IffbwzVaTyaRZReBASytbyQHrGGnpz4xDzvUu8tHrd3v+y4iIjMrKS0OB/AnwAcD6AcPfTdycvNs97xzzvP/9wJJ5xcH6zR/RHfSIdJRIPwyeTRfXv3Vd11313P1zfUT+DxdxooJnboiGJlwd8FcDmANvTSd+fcs88tuvnGm39t6JGMhmCdZrCpH1HKsyo25OmFwe07dlQ89MiDL9XU1jzpcXubZcdFRERASWmxFcAlAErQywYbAFx68WUnX/7ryy5qC7fqzaEGZSRjJKKB+aRSeu6Ceeuff/G5hyKRyDyP2xuSHRelLyZ2qE9KSouPB/BnANmILi66/Y+T6crU7779nvNPOumkL9UHq7lzRJTCsrTccIbiCj/3wnMr5y2cOxnAm+ynQ0SUWmIbbN9GtIK6BUCPu/nHH3e8847b7vxFbn7uuIZgtR7k8XiilKRAQbaWF9IiluAjT/z73WUrlt3pcXs3yI6L0h8TO9RnsXGcvwFwBqJ9d3pcNVx2yeVfvOySyy5qDTdpLaEm7hwRpRBdsSBPKwxWHa6quuOeO5ZVHq6cAGAN++kQEaWuktLizyHad8eFXjbYhBC47trrz/zReT/6fnOoQWsNNYuRjpOIemePVukEyzaU7Xvk8X/PbmhseMLj9vbYR4uov5jYoX4pKS1WAHwf0dLgFvRyNOsLn/9C1u233vErV5azoCFUy5GcRCnApWVHsrSc8PSZb6x55fVXVhmG8bTH7T0gOy4iIjq62AbbZYj2PqwC0NHT47562ul5/7jpH5dY7FpWQ6hWDxvhkQyTiJIoUJCt54W0iMX/5IQnVniXeqcCeMPj9vZ4vJJoIJjYoQGJHc26FkAeepmapSiKuPaPfzr9x6U/Pq811Ky2hBoVTm0gGnma0JCrFwbbmtoa77z3zuW79ux6E8Acj9vbKTs2IiLqu9jRrDMB/C52qaqnx1ktVuXWv9/2vbPOOOuchlCt1hHiWHQiGRxqBnL0guDGjRt23v/w/R+1tLY8B2AlK6VpqDGxQwNWUlrsAHApome/DwPo8UPi8ccd77z15tsuHDtu7LGNoVrdF+ZnSaKR4tQyjWwtL/zuonfKJkyasCocDk/2uL1bZMdFREQDF5ua9TsAX0b0aFaPpdH/Xfz9Y6679rqLQ0rA1hjiWHSikRLXS8f3xITHly3+YPFGAM943N6DsmOj0YmJHRqU2M7RWQB+DyAEoKa3x1568WUnX3rxpRf6jA6tOdSgRTg5i2jYqEJFjpYfDPuN9nsfuGdZ2caytwBM9bi9rbJjI6LRQwixCMAzhmHMiX39CIBrAOQahhGIXasE8A3DMPb18d80DMNIyf4wQoi7ALxvGMayIzzmZQBLDMN4eThjKSktVgEUI3o8vhNAXU+Py87Osdz1zztLTzrxpC81hut1Vu8QDa9PqnQ2bCjbft/D921sa2ubC2ABj17RcGJih4ZESWlxEYA/AjgJQCV6GclZWFBou/XmW3/4hc9/4csNoTqWBhMNg0wtO5Kl50SWrVi+5dEnH1nj8/n+A2Ady36JaKgJIW4BkGcYxk2xr8sQTTD8f3t3Hl91eecL/PP8lrPnZCUsSgigsogIKLK5YIIyRlu1am21Y+uudWpf05nO3Lm99/Vy7p3pq7u1M07taKutrVNvrYpTjyicAyLIqqxC2ALIZgJkO+fkLL/luX88v5Q0hlUgOcnn3ddpcg6Hk18Qkief5/v9Pt+VUiaEEBcAeEtKeeEpvGZfDnYWA3hCSrn4OM95Aecg2OlUW1czHMBDAM6Hao/vcajOjX91U/X9995/s2aKcKt9mCdnEZ1hGjSUmhWW7hi5nzz1k/feXfruegDPxWOJnb19bdT/MdihM8bbOboGwJcBuFDtWT264fq6EQ8/8PAXpOEEW+zDsKhKlAAAIABJREFUHOxHdAYE9RBKjArrUNOhg9//0fc+qN9WvwzAC/FY4khvXxsR9U9CiCsA/FRKOVMIcR6AVwH8CsAoKeU/CiHuBTBVSvl1IcR0AE8BCECFPw9LKXd4YUkzVFvRnQDWSimFEGImgBcA1AEYAeAHUDP9WgB8WUp5uMt1VAOY771uFsBcAD8EMBuADuAFKeWTQojZAL4DQAAYDeAVAG0AbvEeq5NSNgohbgLwLwA0AA0AHvZe8z+g5trcClUl83OoeYMdAL4hpVzbGex4r69LKf+nd43PA5gvpXz5M/2h96C2rsYH4GYAN0H9Wbb19Dy/z689/tg3p9fMrpmdtNu0drtFZ3sW0WcXNiIoNSrsD9d+uPm7P/zu+nQ6PQ/An1ilQ+cKgx0642rragYB+AqAyQAaAaR7el44HDb+8Vv/45qpU6dOb7OadR7LSXR6DGGg2Ci3DNfM/+rXv3x33p/mHZBS/g7AkngswZ5HIjprhBA6VKXuCKiNnVFQwc5rUspJXpgxD0AMwDYAd0gpVwsh7gDwD1LKqV6ws1hK+YT3mhJqDfFfAG6RUm4VQizynr9aCPE4gHop5TtdrqMawC4AI6WUu4UQjwC4SEr5LSGEH8DbAP43VMjzBlSIdASqhfzvpJS/8K51nfdx10K1j+0WQnwbwBVSyju6VuwIIZYB+BsvzBnvfc5jugQ7SwDEvT+TEIAtAC6UUp61H/Rq62rGQLXCHfNYdAAYNXJ00be/9e26EcOrRrc6R8w0K6iJTotP86NEL7fsnJN+6umfvr9k6ZINAJ6NxxINvX1tNLAw2KGzosupDV8F4Ida9PX4A+b0K6ZX/u3j37o9EPaXtNpHzLzLYJvoZAgIdYS5WeK+t2zpip889ePdmWxmO9SC4pgVc0REZ5IQYh5UdczfAHhaSvmeEGIbgGkAlntvhwN4UUo5ucvvawFQDRX8fF9K+Zb3uITaGPqDlPIb3mN/C+DvALwOYJ6UckG3a6gGsFJKOdi7/wqASQA6E4sIgJ8A2AzVJjbTe95uAHO8yqEnvOeuAXC/lPJW7znFAHZJKcs6gx3vOc3e63UaBGAigB/Da8XyAqknAFQBmCmlfPTk/2RPT21dTQQqZLsSx6neAYC6uTeOeODeB27RfCLUah/2sT2L6OToQkexXmYHtJAz77/nLfvlr5/b5zjOPABvskqHeoPW2xdwLgghFgghbu1y/0dCiJQQwtflsQNCiJGn8Jp9NhETQvyzEOKqEzznBSHE187WNcRjCRmPJVYB+CeoRd0IAMU9PXfFqhVNd3/trp8veHvhOxXGkGy5UWkZwjxbl0bUL4T0MIb6q6z2xlTDY9987A//+v1/2ZrJZv4LwHcZ6hDRORYHMAvqMIXl3mMLoVqDjkgp29DzmlNAVdAAnz5Z8y4AXxBCXAoAUsonodqqdgD4gRDiOz28XtfX0KEqfCZJKScBmA7gee/Xup8gZXe73/1aBQCj22M6gGzn63sfYxpUkNLVr7zP5S6otrKzLh5LpAA8BxW2WVBrMF9Pz429/eaeL9/zpX9b9t6yxYP951vFRpkjwAJqomMRECg2St2h/ip7y8atH9z9tbte+c9f/WKF4zhPxGOJVxnqUG8ZEMEO1IJjZpf7cwCsgNrJgDfYL32ypzUUgGtwdKHUq+KxRDvUoub7UBU7I9DDtdm2Lf/9mX9bc/e9dz+57oMNy4f4z7dKjHJHGzB/RYlOjilMDDKHWmE32v70M0//6cGvP/D+zl07lwH4p3gsEYvHEt1/QCEiOtsSAO4BsFFK2fk1aAFUhU1nZc1WAOVCiKkAIIT4IoA9UsruQQgAQEqZgNocelYIoQkhVgIoklL+FMCTAKacxDU9KIQwhRARAEuhgpeTsRLAdK8KCFCDiRd579sADC+s2i6E+Ir3+VwH1XrV3SsAagEMkVKuPMmP/5l5G2yboNrP/gCgEsBQ4NOpTS6fc3/45A+Xf/2bj/7s8L7mbcMCVVbYiJyrSyUqGGGjCMP8VVbrJ8md3/z7x1/6X098Z0trW+srAP45Hkv0l58jqUANiFYsDvbrM4P9glBD/W4EkITqbe9R9YjqyOOPfbN23NhxE9qtFi1pt2kc7kcDmYCGqFHiFBnFbmJxfOnPnv7Z3lw+9wmAXwPYwhOviKg3CSE+AfB/pZRPe/eLodY710gp3/cemwHgpwDCUGuqh6SU9d1Pmup6KpbXyvQ6gE1QrVQ21NrmESnlpi4fvxqq/anau29CtUTVQFXbPC+l/L63xnpCSjnbe95uALO9WTpPAICU8gkhxOcA/B+oSpc9UK1ZB4UQfw81w+Ye73N4BkAZVBXQo94MoBfQ5VQsIcSLUKHXDz7jH/Np8+YffhGqquq47Vk3XF834sH7HrhF82mhdqfFl3Oz5+oyifokvxZAiVGez3bk2v/zuV8sWLhooQU10+uFeCyxu5cvjwjAwAl2ONivbw32qwZwH9R/j4NQIVePJk+aUv7Yw4/dMGzY0Ko2u9lM2cmzdVlEfZKao1Mso2ap09DQsP17P/reh3v3fdwBtQO7OB5LcCACEVEfJIQQUEOMlwOolVJ+0pvX480/HA81/3AQ1Bqse1saAHV61kP3Pzxl7nVzayzk9XanxccZiDTQGMJAsV5m+UTAfm3eqwuef/H5I67rJgG8BGBNPJbgsb7UZwyIYAfgYL8ul9FXBvuZAK4CcAfUcOWDUH3gPbp+ztzh9331vhvDkVBZm9NsZpyOs32JRL1MoMiIymKj1Nm3f//up5/595XrNqxzALwH4NV4LNFj+wIREfUNXsX4fAD/LKV8qrevp5N3NHotgC9AVZkfxDFOzwqHw8ZD9z40ZU7tnGvzMqe3O6085IL6PQ0aiowSN2oUu8tXrVjxk6d+vCOZStpQPw/G47FE95lgRL1uIAU7jwMIQrUrXSSltIUQ/wFgFYAHpZSzhBATAfy6W7DTClXN8iq6lQlDfVN8Eao1ar33+AVQ7UZfBfCKlPJfu7xWNf6yTPg1qCDpVe9+BdTR4NNwgjJhAB8CuLdLsFMC4GMpZbRLsLMWwF4pZbTLNZwPdfzl8zga7Pw11LyhKu/jnrMecO/khuuhWtk6Fxc9np4lhMBdd9497o7b7rgBugy0Oc1cXFC/FDGiKNZLraZDTQee/dWzi5YtXyYA7APwm3gssa23r4+IiApfbV1NBdR4gRO2Z0UiEePhBx6ZWnNNzTU5N6u1uy2m5fZY7ENUsFSgU+xGzRJ3x84dW3/00x+v2b1nF6BmdL0WjyWOOUaCqLcNpGBnAoCXAeyQUt7sPXYrVP/0H71+aj+A7QBu89qpvgjgO1LKS4/V/y2EuAeqCmg6VOXPI17b0z0AbpZS3tblGqrxl8HON6ACjc9DVa2sgerbBk4c7PwcqiVrhvf4P0C1Zd0shFgI4HtSyoVCiA8APCml/K032O8XUHN1ugY7QQAbASS7hlrnkre4+DxUFU8Wqv2sx7+cfp9fe/iBRy6be93c2rzMakmnzWT/N/UHESOKqF5itba0Nj3/4gsLFiYWOFCVbC8DWMrByEREdCZ57VnjoDYkB0NVox+zGiFaFDUfefDRqbOvvubqrJvR2p1WBjxU8DShI6oXu0Vmibtt+7Ytzzz781Wb6zcbUD8XvsTByFQIBkywA3CwH/r4YD8AqK2rqQJwO4BLoXaOjtluEi2Kmvfec9/k2mtrr5aaa6bcNl+Hkz5Xl0p0hqiWqyK9xD5y5EjjS7//XXz+gvk5qH/XiwDMi8cSx9xFJSIi+qy89qyroA7eCEMFPMfcNSspKfU9+uAj066adfWVGadDJJ0W05Ic+UaFRRc6ivQSp8gslvVbt3z0zHPPLKvfWh+C+vnjdwDWxWOJHjsJiPqaARXs0Kf1tcF+wJ93j8ZCDboeAeAQjs4h+hTTNLW77rx73E11N10bDAaKkm6bTw1Z5t9t6rsEBCJGVEaNUruxqXH/b196MR5fFLehqveWA/jveCxxsJcvk4iIBhDvBNMroQKeINQpq8fsey8vK/c/+tDXp8+aMWtmh53S2p1Ww2bAQ32cIUwU6cV2xIzioy2bNjzz7DNLt+/YHgbgQI3fWByPJTjvgQoKg50Brq8O9gOA2roaHcAUqICnFCfYPRJC4KYbbhp5x213XDuoYtDQdrtNT9ltwu15ZA9Rr9CFgSI96kaMYvfAwQN7fv3bFxJLli5xoBbQa6AqdPb28mUSEdEAVltXE4Kq4LkFQAAnCHgqKgb5H3v4sZnTr5g2PetkkXaTvgyrqKmP8Wl+FGklVtAIytVrVq969vlnV+3dt7cYgAZ1WvAb8ViitXevkuj0MNihPq+2rsYPtXt0O1Q1w2EAxz0Wa+b0mYO/ctdfXzOqetSFSatNJJ023ZEcT0K9J6iHEBJF+aAREhs/2rj+pd//bsW6DesMqEBnI9RJV+zhJiKiPqO2riYM4BqoOYg+qIDnmEN1IpGIcfeXvjJhTs2cK0OhYDTptBtpu52bbNSrgnoIEa04r8NwFr+7eMkvX3hufWtbazkAASAB4J14LHGoly+T6DNhsEMFw1tczADwOQBRAC0A2o/3e8aOGVd83z33zpp4yaWT01YSSbfN4JA/OlcENESMqIzoRVYum08vWpxY9uJLL25sa28rhQp01gN4A0BDPJbgF2MiIuqTvFNMZ0OtwUycIOARQqBmdu35t996+6yR1SMvSFntSLtJg6eZ0rmiCx0RPSrDepGdzeZSb81/a/FvXvrN1nw+Vwk1r2EhgAU86Yr6CwY7VHC8AX+ToPq/hwJIAjjuF+Uhg4cE7//a/VNnTp81w5aWlkHal7KSkNxBorPA1HyIaFE7Ykax5+M9Da+98dqytxfM3yelHAy14/kBgD/FY4ndvXulREREJ6+2rqYI6tCPGwHoUAHPcYfqjKgaEb7n7q9OnX7FtGm2tLW0TPrSdvIcXC0NREE9jLAWyQeNsLZ1+9bNr7/x+qrFSxYd9tZgDoB3ACyMxxItvXypRGcUgx0qWLV1NRqA8VDlwRdC9X43AcdOa0zT1G753K2j5143d9r5551fnbZSbodMmVnnuJ1dRCclbEQQEkV5U5juqtWrVv3mpd+s3rV7Vx5AJdQCeCWANzlDh4iIClltXU0UwBwAc6E2LJqhNtqOye/za3fefufYv5p7w5UlJSUVKbtNTzntmiOdc3DF1J8ZwkBYj7oRI+qkUsm2xe8uXv77P/x+U3NLswmgAuq04jcBvBePJY5b7U9UqBjsUMHzTtEaCeAGAJdDHTff6L09pvOGnRe68/YvTZw1Y+YVgWAwknaSetpJajzNgU6FqfkQ0iJuxIg6ra2th+e//dbSl195uT6XzxUBKIEa+L0QwNJ4LNHYu1dLRER05nhDli+DquAZAvUD9CEcZ5MNAGZMmzH4zju+NGPsRWMv7rBSMoMOM2OnIXmiKZ2CsBFBUETyAT0oPtq8acMfX//j6uUrlzdCrb+KocY2vA5gVTyWOOYBLET9AYMd6ldq62qGQO0gzYYaiNaE45zi0OnKmVcNueVzN19+8fiLL8k5OWRk2pe2k1xgUI8MYSKsR2RQC1tCau5HmzdtfO2N19asWLXiCIBBUEO+9wGIAVjLxQQREfVnXhX1hQCugwp6XJzEGqxyUGXgztvvnDB9+owp5aXlg9JWUmZkh8kTtehYTM2HsFbkRIyobG5pPpRYFF/+8h9f3pJKpQTUGswEsBfAPADr47EET0+hAYHBDvVLtXU1JVDHdN4ANaQ2DTWH57h/4UPBkH7bLbeNqa2Zc8WQwUPOT1tJmZYpI+dkzv5FU59mCAMhPSKDImzpwpBbtm7ZtCC+YMOC+Dt7XdcNQC0mAGA51AkLHIhMREQDTm1dTQWAWVBtWiEArd7tuEaNHF10y003j592xbTLiotLStNWEh0ybbBdnkzNh5AelgGE8oZmYO36dR/+v1deXrN+4/pmqOqcKNSspyUAlgHYwzUYDTQMdqhf8wYtj4ca9DfBe7gZQOpEv3fUyNFFX7zti5deMfWKy4OBYLjDTsksMiwVHkB0YSBsRGQA4bxPM8XW7Vu3LEwsXDd/wfw9tm0DQBmACNTpbG8BWBGPJU64eCUiIurvautq/AAmArgJwAgcnYV4wqE6Y8eMK775xs9PuPzyqZMj4Uhx2k6KDpnWudE2cPi1AIJa2A3qYRsunPpt9ZvfXbL4o3cWvrMnl88ZODq/cBeAtwFsiMcS/AtCAxaDHRowautqyqDKg6+Dqq6woPrATzhUZ8L4CaXXz5l70ZTJUyYOqhg0uCOfsnMi6++w03AkKzz7E13oCOkRBEU459P92o6GHVsXLU6se/OtN3fl8jkXQABqEJ8OoB7AfAAfsdSXiIjo07xZiNUAroWq5NGgKnjaTub3T5wwsexzN35+wmWTp0wOBIPhtJ3UMm5az7nscu5fBIJ6EAERssNGBNlsNr1h08aN8UXxze8tW3JQSilwdEMtC1Ud/T6AA6zOIWKwQwOQ1wc+EsBMAFdCneaQhBqwdsJ/EJWDKgM3zK0bPWPa9AkjqqpHW07ezSLjyzhpkXdPOM6H+hgBgYAehF8EXb8IWj7Dp+/a3bB90buL1r3x5hs7s9msAzUzpzPMSUKV+q6IxxL7e/PaiYiICkltXU0xgCkAroGq4pFQ66+TOv986mVTB914w02XTJo4aZLf7w922GlpiZyZsdOwudFWcAQ0hIww/AhaETOitbS1Hvlw7Yfr314wv95rswLUhtogqEBwC9SBFB/FYwkuuom6YLBDA1ptXU0AqkVrDoAxUMP+jgA4qYZu0zS162quH371VVePHzd23HjTNP0ddkpkZcbIOh1s2eqj/FoAAT0ofTKQD/pCZnNL86HNWzbXr1y9cue7Sxbv9ypzfFBhjgE1o2kpgDUAdsVjieOe9kFERETHV1tXUwnVqjUbwHlQa7AWnES7PKDatWZfNXvU5EmTxgw/v2qkCxdZp0PLI2tk7A64xz+Yi3pJ5xrMlP58yBc2Pmn8ZP/KVSvXx95+c9vuPbs7/9sHAJRDhTkdABYAWMnTRYmOjcEOkcdbYEyFmsdT6j3cBjU/5YT/UIQQmDJpSkXttXPGTJ40+ZLy0vJBWStj5WXOyCOnZ50M27Z6ian5ENRDMKU/HzLDerojndyxY/u21R+s2bFw0cI9ra0t+c6n4uiJChkcDXN2xmOJE84EICIiolPjtWoNATAJKuQZBLXuOumNNk3TxLSp0ypnzbhy1CUTJowdUjn0vJydtXPImjk3o2WdDDfbesGfq6K1gBfkhMz2VLJt166Gnes3bmh46+1Yw5HmI52VNxGo9beAquB6H8A6qDUYF9BEJ8Bgh6gbb4ExDMA4ADOg2rYA9YN+M05i6B8AhMNhY9aMK4dOvnRy1ZgxY0YPrRxynoQUGScjbZH3ZZ0M2Lp1Ngj4NB/8egCm9FlBIwzHcexdu3ftWLt27bbEu/Fdez7e0/UcVQNHw5w81KlWqwBs50KCiIjo3PHWYOcBmAwV8pRCVfIchpqrclICgYA+++prz5s+ddrosWPHjS0tKa3I5DusvMj68m5O5NwcXMn9mjNNE7oKcuB3fCJg+82A0dzSfHj7ju071q1ft3vJsiV7Dx8+1Ln4FVCnWRV795ugNtQ2AtjL6miiU8Ngh+gEvH7wiwBMgyoZ1qHCnWacwiJDCIGJEyaWTb9ietX48RePrBpeVR0KhiKZfIdliZwv5+ZEzsmwdPgUCGjw6374ND8MaVo+4Xf9ZsBMdaSSn3xy8MCW+i0N7773bsPGjzY2d/la17mQiHr3baggZwVUmJP/9EciIiKic8kLeapwdCZPEdT38A6o4csnvflSXlbur722dsRlky8bPXx4VVVZaVmFK12ZtTOuI2xfXuZE3snBlic8T4M8AgKm5oNP88OEzw5oQdfQTa3xUOOBrfX1Oz5Y9+Gepe+/dyCdTnf976RBhXURqKqsXVDHk38EoIlDkIlOH4MdolPgHd05CsClUMOXI94vtUKVjZ7SP6jBlYMDV826evjECZdUjR59weiK8opKx3XcnJ11Hdi6I2zDcvPIu/kB38alCR1+7c8hTt6nBeAzTKO1va15//59+3bs3Llv0+ZNB9d8uLqp2yICAMIASqAWFIBaSHwAYBuAj+OxBFdyREREfVSXdq1RUEHPBKiKWwHVMt8OnPzOmBAC48eOL5l06eShF11w4dAR1dUjKsorKg3dMLNWxrZE3rClpefcLCx3YO/3CAgV3mg+GMJ0dWlYfj0gTN00kun2tkOHDjfVb61vWP3B6o9Xrl7RaNt297VwBKoqR4daJ38E1WZVH48lWs/xp0PUbzHYITpN3ula5wEYD3V85/k4GuykoBYZp1Tnq2mauOjCMdHxY8dVVI+orhg+vGro4MrKwcXRklLDMMyclbUsNy8czTFtmRd5Nw/LtXCKeVIfJWAIA6ZmwtBM6NClkLptwHB9hl/ThCaaW44c+njv3r3bd2zfv3HThoNr1689YllWTws5P9SOkM+73wg1K2cLgN3xWOKkevaJiIio76mtqzEADAdwAYDLAFzo/ZKE2mw7qQHM3Q0/vyp8+ZTLhoy5cMyQUaNGj6isrBwaCoRCWStjWTIvXOGaDmxhuRZs1+pXFT4aNFWBo/uhw3QMadh+3a8ZuqG3p5Kthw4favr444/379rdcGjzls2HNtdvbukhxNGgKquiUKEbABwEsAFAPVRlNNdgRGcBgx2iM6S2riYEtciohmrZuhBqd0KDatlqwym0bnU3uHJwYMLFl1RcMGp0xfDhVYOGDRs2rKy0rCIUDIUsO29bjuU60hFSuIarubrj2nCkDVvacKUDR7rorQBIQIMm1M0Qfw5uXE3qtiEMaeo+zdRNI5PLZFKpVHtLa0tzU2Pjocamprb9B/a17mzY2bJl65bW43y9CkHtCAWgPskk1MC9DQAauCNERETUf3mnnFYDGAvgcqhZiRJqgy0JdbrlafW6l5SU+i6fcnnliKoRZcOGDC0dMmTIoNLSsvJoUVGx3xcI5O28ZTl56cAWrnANF67mSAu2tw5zpNNrg5sFBHShQxcGdM1Q70OHkJqtQXN0YcDQTGEapiFdKdtT7a2HDjU17ekS4NRvq2/tIcDppENV43S2VgHAbgDrAeyAqoo+rZCNiE4Ngx2is6S2rkYHMBQq7LnYuxVDfeOTUBU9p9y+1V0gENDHjhlXMmzIsMjgysFF5eXlRWVlZdGy0tLSoqJoNBQKhf0+n980fD4pXWk5tuO4tutIB650ASGFBIR3GQIApJDCe18IAaEuWAKyc2kioQlNPVEKB1K4GoQUQpOa0IUuNKFputA1Xdc1XXNcx7Ft285b+VwqlWxvbm4+0tjYdKSx6ZPWfQf2t+3a3dDasKsheZyFQycB1VZVBDXsWHqPHQKwHcBmAA0AGtmnTURENDDV1tVEodq2xgEYA7UWA9SawYWq6EnhFOb09CQQCOgXXXBRcdXwqujgwUOiFeUVRYMqKkpLy8rKiiJF0VAoFPYZpqlpuu66juu4rutI9f+udKWEK1wpvXWX1KSQOoQUrnT/vMAREGoxppZq6n+dSzNACojOFwCEgAYNumYIUzd1XdO1XD6XzWQ7OtLpdKqtvb29ubm5paWlJXWk+Uiq6VBT6uDBA6m9+/am2trbTlR+JAAEodZhQe/j21Drr/VQbe5747EETwYh6gUMdojOEa8/vARHS4cn4uhCA1DfMHNQQwE7cIptXCcihEBZaZl/yOAhwYqKQaHysrJgNFoc1HVdMwxD0zUVwxiGoeu6F8nouqZrumYYuq6rx3VD13WhaVqmI5Pp6EhnM9lMvqOjI5dKp3PpdCrfnkzmksn2XGtra66ltSXf0tqSd133dL7Q6FA7QBEc7cuWAA5AzcbZCVXe+0k8ljjtSigiIiLq37zWrUqoOT0joA7FGAm1SdSpAyrsOePBhGEYIloUNYuLi33RoqivqCjqi0QivnAo7AuHQr5gKOQLBoK+YCDgCwaD/mAoFDRN07Asy7Jt27Esy7Ity7Ft27Fs27Ft27Fty7Es27Fsy7Ety7Esy8lblpPNZqzGpsb03n17U41NjZnT+FlPQFVCh3A0wOl8vBHAHqg5OXsAHOAJokR9A4Mdol5UW1djAigHUAF15HY11IJjGI6GGRrUjkhn4NOfpvj5oNqn/N7bzp00ARVs7YYKcXZDhThNHHRMREREn5U3K7EMKuw5HyrsuQBqQ8mFWn9JqDb6jPe2P4UYGo5W4HS2snfqDHAavPebABzhGoyo72KwQ9QHeYuNYqjApwJqwTECqsKnCEf7xDWoEMSCCnxy3lsLp9lLfgbpUCdWBHA0vOmsuhFQ156EWiw0QlXiHIEaetgM4HA8lujtz4GIiIgGCK+6ugjAYKjQpxJqs22o95gfn16D5brdzmjF9WkwoDbOut50qOvu/MGvM7Q6CBXg7MJfBjj9KcAiGhAY7BAVGG9IcxnUjlKRdxsEVflTDnUaVASqvLjrN3HR7W3n+533ZZfnd78BalGg42hVTfcvHl1fv3Ohk4ZaJHwCtXhohhoi3QqgLR5L9KfqIyIiIuqnvNAnCLXOinq3YqjAZxDURlw5VJDSfQ3Vlehy6xzw7OAvN766vu26TuvpbdfX1aCqu1sBtEBtmB323k91u3VwA42o/2CwQ9QPeYsPE2oBEuryNgD1Tb/zpnd538DRKhuj231ALRTSUOXInZVBuR7ezwGwuFggIiKigcY7PMPEX1bM+PHpKprOdvTOYcQGVKuX1eXWWYXtHOPmer/eGdak2S5FNDAx2CEiIiIiIiIiKlBab18AERERERERERGdHgY7REREREREREQFisEOEREREREREVGBYrBDRERERERERFSgGOwQERERERERERUoBjtERERERERERAWKwQ4RERERERERUYFisEMCL2wCAAACW0lEQVREREREREREVKAY7BARERERERERFSgGO0REREREREREBYrBDhERERERERFRgWKwQ0RERERERERUoBjsEBEREREREREVKAY7REREREREREQFisEOEREREREREVGBYrBDRERERERERFSgGOwQERERERERERUoBjtERERERERERAWKwQ4RERERERERUYFisENEREREREREVKAY7BARERERERERFSgGO0REREREREREBYrBDhERERERERFRgWKwQ0RERERERERUoBjsEBEREREREREVKAY7REREREREREQFisEOEREREREREVGBYrBDRERERERERFSgGOwQERERERERERUoBjtERERERERERAWKwQ4RERERERERUYFisENEREREREREVKAY7BARERERERERFSgGO0REREREREREBYrBDhERERERERFRgWKwQ0RERERERERUoBjsEBEREREREREVKAY7REREREREREQFisEOEREREREREVGBYrBDRERERERERFSgGOwQERERERERERUoBjtERERERERERAWKwQ4RERERERERUYFisENEREREREREVKAY7BARERERERERFSgGO0REREREREREBYrBDhERERERERFRgWKwQ0RERERERERUoBjsEBEREREREREVKAY7REREREREREQFisEOEREREREREVGBYrBDRERERERERFSgGOwQERERERERERUoBjtERERERERERAWKwQ4RERERERERUYFisENEREREREREVKAY7BARERERERERFSgGO0REREREREREBer/AxTa+fVQOExJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "remote_true = [360, 853]\n",
    "remote_geo = remotework_histogram.value\n",
    "epsilon_ = 0.1\n",
    "remote_labels = ['Does not work remotely', 'Works remotely' ]\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Remote work '\n",
    "subtitle2 = 'Privacy-preserving: Remote work'\n",
    "pie_comparison(remote_labels, remote_true, remote_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of participants with family history of mental illness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "family_true = [480, 733]\n",
    "family_geo = family_histogram.value\n",
    "epsilon_ = 0.1\n",
    "family_labels = ['Family history of MI','No family history']\n",
    "\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Family history of MI'\n",
    "subtitle2 = 'Privacy-preserving: Family history of MI'\n",
    "pie_comparison(family_labels, family_true, family_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of participants diagnosed with dental illness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "treatment_true = [615, 598]\n",
    "treatment_geo = treatment_histogram.value\n",
    "epsilon_ = 0.1\n",
    "treatment_labels = ['Not Diagnosed','Diagnosed']\n",
    "\n",
    "title = 'Comparison of Results: Geometric Mechanism - epsilon '+str(epsilon_)\n",
    "subtitle1 = 'True Counts: Participants diagnosed with MI'\n",
    "subtitle2 = 'Privacy-preserving: Participants diagnosed with MI'\n",
    "pie_comparison(treatment_labels, treatment_true, treatment_geo, title, subtitle1, subtitle2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Variable Interactions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the queries in the following analysis, we will make histogram queries of disjoint subsets of the data.\n",
    "\n",
    "Due to parallel composition, when queries are applied to disjoint subsets of the data, the privacy guarantee depends only on the maximum $\\epsilon_i$, not the sum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "epsilon_ = 0.4\n",
    "with sn.Analysis() as analysis:\n",
    "    data = sn.Dataset(path = path, column_names = var_names)\n",
    "    \n",
    "    ## percentage of patients \n",
    "    ##that received treatment in each Age class\n",
    "    \n",
    "    filter_age4 =  sn.filter(data['treatment'], mask = data['age'] == '4')\n",
    "    age4_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_age4, 'bool', true_label=\"0\"),\n",
    "            upper = 6,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_age3 =  sn.filter(data['treatment'], mask = data['age'] == '3')\n",
    "    age3_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_age3, 'bool', true_label=\"0\"),\n",
    "            upper = 26,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_age2 =  sn.filter(data['treatment'], mask = data['age'] == '2')\n",
    "    age2_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_age2, 'bool', true_label=\"0\"),\n",
    "            upper = 149,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_age1 =  sn.filter(data['treatment'], mask = data['age'] == '1')\n",
    "    age1_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_age1, 'bool', true_label=\"0\"),\n",
    "            upper = 554,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_age0 =  sn.filter(data['treatment'], mask = data['age'] == '0')\n",
    "    age0_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_age0, 'bool', true_label=\"0\"),\n",
    "            upper = 478,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "    \n",
    "    ## percentage of patients \n",
    "    ##that received treatment in each Gender class \n",
    "    filter_gender2 =  sn.filter(data['treatment'], mask = data['gender'] == '2')\n",
    "    gender2_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_gender2, 'bool', true_label=\"0\"),\n",
    "            upper = 242,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_gender1 =  sn.filter(data['treatment'], mask = data['gender'] == '1')\n",
    "    gender1_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_gender1, 'bool', true_label=\"0\"),\n",
    "            upper = 955,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_gender0 =  sn.filter(data['treatment'], mask = data['gender'] == '0')\n",
    "    gender0_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_gender0, 'bool', true_label=\"0\"),\n",
    "            upper = 16,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "    \n",
    "    \n",
    "    ## percentage of patients \n",
    "    ##that received treatment in each country class \n",
    "    filter_country3 =  sn.filter(data['treatment'], mask = data['country'] == '3')\n",
    "    country3_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_country3, 'bool', true_label=\"0\"),\n",
    "            upper = 66,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_country2 =  sn.filter(data['treatment'], mask = data['country'] == '2')\n",
    "    country2_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_country2, 'bool', true_label=\"0\"),\n",
    "            upper = 175,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_country1 =  sn.filter(data['treatment'], mask = data['country'] == '1')\n",
    "    country1_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_country1, 'bool', true_label=\"0\"),\n",
    "            upper = 732,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    filter_country0 =  sn.filter(data['treatment'], mask = data['country'] == '0')\n",
    "    country0_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_country0, 'bool', true_label=\"0\"),\n",
    "            upper = 240,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "    \n",
    "    ## percentage of patients \n",
    "    ##that received treatment in each class of remote work\n",
    "    filter_remote =  sn.filter(data['treatment'], mask = data['remote_work'] == '0')\n",
    "    remote0_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_remote, 'bool', true_label=\"0\"),\n",
    "            upper = 853,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "    filter_remote2 =  sn.filter(data['treatment'], mask = data['remote_work'] == '1')\n",
    "    remote1_histogram = sn.dp_histogram(\n",
    "            sn.cast(filter_remote2, 'bool', true_label=\"0\"),\n",
    "            upper = 360,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "\n",
    "    ## percentage of patients \n",
    "    ##that received treatment in each class of family history\n",
    "    filtered =  sn.filter(data['treatment'], mask = data['family_history'] == '0')\n",
    "    family0_histogram = sn.dp_histogram(\n",
    "            sn.cast(filtered, 'bool', true_label=\"0\"),\n",
    "            upper = 733,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "    filtered2 =  sn.filter(data['treatment'], mask = data['family_history'] == '1')\n",
    "    family1_histogram = sn.dp_histogram(\n",
    "            sn.cast(filtered2, 'bool', true_label=\"0\"),\n",
    "            upper = 480,\n",
    "            privacy_usage = {'epsilon': epsilon_}\n",
    "        )\n",
    "    \n",
    "  \n",
    "\n",
    "analysis.release()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Disposing all query results as a dataframe for our analysis. This dataframe will represent a contingency table that will display the frequency distribution of the variables.\n",
    "\n",
    "Contigency tables are heavily used in survey statistics, business intelligence, engineering and scientific research.\n",
    "\n",
    "The contingency table will allow us to explore the interrelations between two variables and also compute the Cramer's V coefficient, which is a statistic used to measure the strengh of association between two vaiables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dpage0 = np.absolute(age0_histogram.value)\n",
    "dpage1 = np.absolute(age1_histogram.value)\n",
    "dpage2 = np.absolute(age2_histogram.value)\n",
    "dpage3 = np.absolute(age3_histogram.value)\n",
    "dpage4 = np.absolute(age4_histogram.value)\n",
    "\n",
    "age0 = survey[survey.age == 0].treatment.value_counts(sort=False)\n",
    "age1 = survey[survey.age == 1].treatment.value_counts(sort=False)\n",
    "age2 = survey[survey.age == 2].treatment.value_counts(sort=False)\n",
    "age3 = survey[survey.age == 3].treatment.value_counts(sort=False)\n",
    "age4 = survey[survey.age == 4].treatment.value_counts(sort=False)\n",
    "\n",
    "d1 = {'Group': ['21-30', '31-40', '41-50', '50-60', '60+','21-30', '31-40', '41-50', '50-60', '60+'],\n",
    "     'Process':['true value', 'true value','true value','true value','true value','privacy-preserving','privacy-preserving','privacy-preserving','privacy-preserving','privacy-preserving'],\n",
    "     'Participants on treatment MI':[ age0[1], age1[1], age2[1], age3[1], age4[1],dpage0[1], dpage1[1], dpage2[1], dpage3[1], dpage4[1]],\n",
    "     'Participants not on treatment MI':[ age0[0], age1[0], age2[0], age3[0], age4[0],dpage0[0], dpage1[0], dpage2[0], dpage3[0], dpage4[0]],\n",
    "     'Variable': 'Age'} \n",
    "\n",
    "age_df = pd.DataFrame(data=d1)\n",
    "\n",
    "gender0 = survey[survey.gender == 0].treatment.value_counts(sort=False)\n",
    "gender1 = survey[survey.gender == 1].treatment.value_counts(sort=False)\n",
    "gender2 = survey[survey.gender == 2].treatment.value_counts(sort=False)\n",
    "\n",
    "dpgender0 = np.absolute(gender0_histogram.value)\n",
    "dpgender1 = np.absolute(gender1_histogram.value)\n",
    "dpgender2 = np.absolute(gender2_histogram.value)\n",
    "\n",
    "d5 = {'Group': ['Non-binary','Male', 'Female', 'Non-binary','Male', 'Female'],\n",
    "     'Process':['true value', 'true value','true value','privacy-preserving','privacy-preserving','privacy-preserving'],\n",
    "     'Participants on treatment MI':[ gender0[1], gender1[1], gender2[1],dpgender0[1], dpgender1[1], dpgender2[1]],\n",
    "     'Participants not on treatment MI':[ gender0[0], gender1[0], gender2[0],dpgender0[0], dpgender1[0], dpgender2[0]],\n",
    "     'Variable':'Gender'} \n",
    "\n",
    "gender_df = pd.DataFrame(data=d5)\n",
    "\n",
    "\n",
    "country0 = survey[survey.country == 0].treatment.value_counts(sort=False)\n",
    "country1 = survey[survey.country == 1].treatment.value_counts(sort=False)\n",
    "country2 = survey[survey.country == 2].treatment.value_counts(sort=False)\n",
    "country3 = survey[survey.country == 3].treatment.value_counts(sort=False)\n",
    "\n",
    "dpcountry0 = np.absolute(country0_histogram.value)\n",
    "dpcountry1 = np.absolute(country1_histogram.value)\n",
    "dpcountry2 = np.absolute(country2_histogram.value)\n",
    "dpcountry3 = np.absolute(country3_histogram.value)\n",
    "\n",
    "d2 = {'Group': ['Other','US', 'UK','CA' ,'Other','US', 'UK','CA' ],\n",
    "     'Process':['true value', 'true value','true value','true value','privacy-preserving','privacy-preserving','privacy-preserving','privacy-preserving'],\n",
    "     'Participants on treatment MI':[ country0[1], country1[1], country2[1], country3[1],dpcountry0[1], dpcountry1[1], dpcountry2[1], dpcountry3[1]],\n",
    "     'Participants not on treatment MI':[ country0[0], country1[0], country2[0], country3[0],dpcountry0[0], dpcountry1[0], dpcountry2[0], dpcountry3[0]],\n",
    "     'Variable':'Country'} \n",
    "\n",
    "country_df = pd.DataFrame(data=d2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dpremote0 = np.absolute(remote0_histogram.value)\n",
    "dpremote1 = np.absolute(remote1_histogram.value)\n",
    "dpfamily0 = np.absolute(family0_histogram.value)\n",
    "dpfamily1 = np.absolute(family1_histogram.value)\n",
    "\n",
    "remote0 = survey[survey.remote_work == 0].treatment.value_counts(sort=False)\n",
    "remote1 = survey[survey.remote_work == 1].treatment.value_counts(sort=False)\n",
    "family0 = survey[survey.family_history == 0].treatment.value_counts(sort=False)\n",
    "family1 = survey[survey.family_history == 1].treatment.value_counts(sort=False)\n",
    "\n",
    "d3 = {'Group': ['Does not work remotely', 'Works remotely', 'Does not work remotely', 'Works remotely'],\n",
    "     'Process':['true value', 'true value','privacy-preserving','privacy-preserving'],\n",
    "     'Participants on treatment MI':[ remote0[1], remote1[1],dpremote0[1], dpremote1[1]],\n",
    "     'Participants not on treatment MI':[ remote0[0], remote1[0],dpremote0[0], dpremote1[0]],\n",
    "     'Variable': 'Remote work'} \n",
    "\n",
    "remote_df = pd.DataFrame(data=d3)\n",
    "\n",
    "d4 = {'Group': ['No family history','Family history of MI','No family history','Family history of MI'],\n",
    "     'Process':['true value', 'true value','privacy-preserving','privacy-preserving'],\n",
    "     'Participants on treatment MI':[ family0[1], family1[1], dpfamily0[1], dpfamily1[1]],\n",
    "     'Participants not on treatment MI':[ family0[0], family1[0], dpfamily0[0], dpfamily1[0]],\n",
    "     'Variable': 'Family history'} \n",
    "\n",
    "family_df = pd.DataFrame(data=d4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs = [age_df, gender_df, country_df, remote_df, family_df]\n",
    "DF = pd.concat(dfs)\n",
    "DF['percentage'] = DF['Participants on treatment MI']*100/(DF['Participants not on treatment MI']+DF['Participants on treatment MI'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Observation 1\n",
    "\n",
    "Participants with family history of mental illness are twice as likely to be diagnosed with mental illness, when compared with participants with no family history."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Group</th>\n",
       "      <th>Process</th>\n",
       "      <th>Participants on treatment MI</th>\n",
       "      <th>Participants not on treatment MI</th>\n",
       "      <th>Variable</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Family history of MI</td>\n",
       "      <td>true value</td>\n",
       "      <td>357</td>\n",
       "      <td>123</td>\n",
       "      <td>Family history</td>\n",
       "      <td>74.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Family history of MI</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>356</td>\n",
       "      <td>119</td>\n",
       "      <td>Family history</td>\n",
       "      <td>74.947368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>No family history</td>\n",
       "      <td>true value</td>\n",
       "      <td>258</td>\n",
       "      <td>475</td>\n",
       "      <td>Family history</td>\n",
       "      <td>35.197817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>No family history</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>256</td>\n",
       "      <td>469</td>\n",
       "      <td>Family history</td>\n",
       "      <td>35.310345</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Group             Process  Participants on treatment MI  \\\n",
       "1  Family history of MI          true value                           357   \n",
       "3  Family history of MI  privacy-preserving                           356   \n",
       "0     No family history          true value                           258   \n",
       "2     No family history  privacy-preserving                           256   \n",
       "\n",
       "   Participants not on treatment MI        Variable  percentage  \n",
       "1                               123  Family history   74.375000  \n",
       "3                               119  Family history   74.947368  \n",
       "0                               475  Family history   35.197817  \n",
       "2                               469  Family history   35.310345  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DF[DF.Variable == 'Family history'].sort_values(['Group'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1319fcda0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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Av62qzyU5GbgI2AM4vaq+OFQNkiRJ0nwZLDgDVNXLgJdNm/cPwD8MuV9JkiRpvvnNgZIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNWgOzkmenuTVSe6S5FlDFiVJkiQtNk3BOcn/Al4EPAPYC3hFkpfteC1JkiRp19E64vy7wG8AN1fVvwGPBo4drCpJkiRpkWkNzluq6tZtE1X1XWDLMCVJkiRJi8/KxuWuT/JkoJKsAk4CrhuuLEmSJGlxaQ3OJwDvBh4K3AxcAjx7qKIkSZKkxaYpOFfVRuCIJHcBVlTVD4YtS5IkSVpcmoJzkncCNTJdwC3AFHB6Vd02THmSJEnS4jCbL0B5GHAVcDnwC8ADgCcBfz1AXZIkSdKi0nqO8yHAY7edopHkdOATwGPpRp0lSZKkXVrriPM9p53X/CPg7lVVwOb5L0uSJElaXFpHnC9J8h7gDCDAc4F1SY6i+5QNSZIkaZfWOuJ8PHA98EbgdcA36T6ibh/ghcOUJkmSJC0erR9H9yPgL/oLAEnuWlVnDVWYJEmStJi0fhzd0cCrgLvRnaqxArgXsPdwpUmSJEmLR+upGv8bOBX4FvDfgY8Bbx2qKEmSJGmxaX1z4M1VdVaSw4AfAy8CLh2uLEmSJGlxaR1xvjXJKuAbwGFVdTuwariyJEmSpMWldcT5Q8BHgDXA55M8Fvi3oYqSJEmSFpumEeeqOhV4XlXdADwF+DTwtCELkyRJkhaTpuCc5Pyq+hZAVV1WVW8CPjxoZZIkSdIissNTNZKcAzwY+LkkV47ctDtw+5CFSZIkSYvJnZ3jfBJwIPAO4I9H5m8Frm7ZQZLXAz9VVWv6T+V4B3B3utM9jq+qrbMtWpIkSVpoOwzOVbUB2JDk4P6TNGYlyRF0byj8SD/rPcBxVXVJkjOA5wNvme12JUmSpIXW+nF0T0uyIcn3knw/yQ+SfH9HKyS5F/Aaui9OIcnPAHtV1SX9ImuBY+ZYtyRJkrSgWj+O7jXAi4HLgGpc523AycD9++n9gU0jt28CDmjcliRJkjRWrcH5P6rqA60bTXIccH1VXZhkzbbZMyw669M/pqamZruKNHYTExPjLkFjNDk5Oed1F/rYscdqqbG/Lm8L3V9bg/O6JEdV1fmNyz8T2C/J5cC9gLvRjVTvO7LMfsDG5kp7q1evZtUqv7RQ0tKxlJ7Y7bGSlpKF7q+twfk3gBOSbAY2040eV1XtM9PCVfXEbdf7EefDq+q5SaaSPKaqPgc8B2gN4pIkSdJYtQbnI+Zpf88G3pFkb+DLwGnztF1JkiRpUK1fuX0d8Ai6j4+7Cfjlfl7Lumurak1//YqqemRVHVJVx1bVrXOsW5IkSVpQrV+5/b+AFwHPAPYCXpHkZUMWJkmSJC0mrZ/j/Lt05znfXFX/BjwaOHawqiRJkqRFpjU4bxk9raKqvgtsGaYkSZIkafFpfXPg9UmeDFSSVcBJQNM5zpIkSdKuoDU4nwC8G3gocDNwCd0nZEiSJEnLQlNwrqqNSY6m+6a/lcCeVfWdQSuTJEmSFpHWT9V4BvDlqrqF7tv/ppL81qCVSZIkSYtI65sDTwZ+FaCqvg5MAK8cqihJkiRpsWkNziuq6oZtE1V1/SzWlSRJkpa81vD7nSQvTLIyyYokzwP+ZcjCJEmSpMWkNTi/EHgB8CPgx/31Fw1VlCRJkrTYtH4c3c9X1USSewJbq+oHQxYlSZIkLTatI86nAlTVfxiaJUnTbd5y27hL0Jj4u9dy0jrifFWSk4HPAD/cNrOqLhukqoFs3nIbe+y+YtxlaAz83UvD2mP3FRz7kr8fdxkag394nd+HpuWjNTg/qr8cNzKvgIPmvaIB2diXLxu7JEnaWa3fHPizQxciSZIkLWat3xx4tyRvTnJhknsleVuSuw1dnCRJkrRYtL458DTge8B96T6Obh/g7UMVJUmSJC02rcH5F6vqZGBLVd0CPBs4bLiyJEmSpMWlNThP/6yZFcDt81yLJEmStGi1BudPJ3ktsFeSJwEfBC4arixJkiRpcWkNzn9O9/nNuwFvBi4H/myooiRJkqTFpvVznA8Cfrv/GeCxwE8D3xqoLkmSJGlRaR1xXgucDuzVX84BzhioJkmSJGnRaQ3Od6mqt1XVlqraXFV/Q/fRdJIkSdKy0Bqcv5nkl7dNJFkNXDtMSZIkSdLi03qO8/2Af05yBbAV+EXg20muBKiqhw5UnyRJkrQotAZnP0FDkiRJy1pTcK6qf57LxpO8Cng6UMAZVfWGJEcCb6B7k+FZVfWXc9m2JEmStJBaR5xnLcnjgScADwV2B9YnuRA4E3g8cD3wkSRHVdX5Q9UhSZIkzYfWNwfOWj9K/atVtZXuM59XAvcArqmqa/v57wGOGaoGSZIkab4MFpwBqmpLklcC64ELgf2BTSOLbAIOGLIGSZIkaT4MdqrGNlX1iiSvBT4MPGiGRW6fzfampqbmXMvExMSc19XSNzk5ObZ9e+wtbztz7C30sTPXHusxvrzZXzUuC91fhzzH+SHAnlV1eVXdkuQDdG8UvG1ksf2AjbPZ7urVq1m1atU8VqrlwuaqcVlKx549VnOxlI5x7VoW+tgb8lSNg4B3JFmVZA/gaOBtwMFJHphkBXAs4BsDJUmStOgNNuJcVR9N8ijgy3SjzO+vqvcmuQl4P7An8FHgnKFqkCRJkubLoOc4V9UrgFdMm3chcOiQ+5UkSZLm26CfqiFJkiTtKgzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQzOkiRJUgODsyRJktTA4CxJkiQ1MDhLkiRJDQYNzklekeTq/vK6ft6RSa5Mck2SVw+5f0mSJGm+DBackxwJ/Brwi8BhwESSZwFnAkcDhwCPSHLUUDVIkiRJ82XIEedNwJ9W1eaq2gJ8BXgwcE1VXVtVW4H3AMcMWIMkSZI0LwYLzlV1dVVdApDkQcAzgdvpAvU2m4ADhqpBkiRJmi8rh95Bkl8APgKcBGwBDp62yO2z2d7U1NSca5mYmJjzulr6Jicnx7Zvj73lbWeOvYU+dubaYz3Glzf7q8ZlofvroME5yWOA9wP/o6rem+TxwL4ji+wHbJzNNlevXs2qVavmsUotFzZXjctSOvbssZqLpXSMa9ey0MfekG8OvD9wLnBsVb23n70OODjJA5OsAI4Fzh+qBkmSJGm+DDnifBKwJ/CGJNvmvRVYQzcKvSfwUeCcAWuQJEmS5sVgwbmq/gT4k+3cfOhQ+5UkSZKG4DcHSpIkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0GD85J9kkyleTAfvrIJFcmuSbJq4fevyRJkjQfBg3OSR4FfBZ4cD+9F3AmcDRwCPCIJEcNWYMkSZI0H4YecX4+8EfAxn76kcA1VXVtVW0F3gMcM3ANkiRJ0k5bOeTGq+o4gCTbZu0PbBpZZBNwwJA1SJIkSfNh0OA8g8ww7/bZbGBqamrOO5+YmJjzulr6Jicnx7Zvj73lbWeOvYU+dubaYz3Glzf7q8ZlofvrQgfnG4F9R6b3479O42iyevVqVq1aNa9FaXmwuWpcltKxZ4/VXCylY1y7loU+9hb64+jWAQcneWCSFcCxwPkLXIMkSZI0awsanKvqx8Aa4P3AeuCrwDkLWYMkSZI0FwtyqkZVHThy/ULg0IXYryRJkjRf/OZASZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBmMJzkmOTbI+yTeS/NE4apAkSZJmY+VC7zDJ/YDXABPArcDnk1xUVesXuhZJkiSp1ThGnI8EPlVV/15VNwPnAE8fQx2SJElSswUfcQb2BzaNTG8CHtmw3gqAzZs379TO97nL7ju1vpamW2+9ddwlwJ57j7sCjcHOHntTU1MHAjdMTExsnZeCtm+ne6z9dXmyv2pcxtFfU1U7tdPZSvJS4C5V9Zf99HHAw6vq+B2tNzk5+SvAZxagRElabH52YmJiw5A7sMdKWqZm1V/HMeJ8I/DYken9gI0N632pX28TcNsAdUnSYnXDAuzDHitpOZpVfx3HiPP9gM/SnZ5xM/B54AVV9cUFLUSSJEmahQUfca6qG5OcDFwE7AGcbmiWJEnSYrfgI86SJEnSUuQ3B0qSJEkNDM6SJElSA4OzJEmS1MDgLEmSJDUwOEuSJEkNDM7zJMmBSSrJE6fN35DkwFls55VJvpnkxTtZz6uS/HZf14bGdba7bJLL72Tdi2ZfpVr0v5fNSS6fdrn/Tm734UlO769fnOTwxvVmXHbbMbeD9V6Q5FlzrXe2tve31P9Nfm3avJVJbkqytp8+JckpC1Wrdsz+an8dkj12bpZrjx3HNwfuyrYA70jy36rqB3Pcxu8Dv15VX9+ZQqrq5dA1hJ3Zzsj2DruTRQ6fj/1ouzY2/A5mpaouBY6bx+29/E4W+WXg4vnaX4Md/S3dpf87vaqfPgLwszkXN/urhmSPnb1l2WMdcZ5fG4ELgP8z041JXppkfZKrkvyfJCum3f5W4ADg3CSHJTkhybokU0muTHJIv9yGJK9NcnWSK5I8Ocmnklyf5Bn9MmuTrBnZ9t5J/jXJPv30gUmunqHMvZK8t9/nZ5Lcu1+++p9HJJlMcmmSC5LcJ8lp/W3r+p+/2f+3fmWSc5Pcd6Tus5J8Lclbkpw6Ut87kzxzLg/6cpZkdZKLknwpyXVJTuznn5LkzP53dX2SP0jyriRf7X8HSXJ4kounbe/dSV4wMn1RkkfNsOvj+m1/M8lv9cuuTbImyT5JPtLfPtmPzB0J/DbwqiRPSnLfJOf1x8hlSX59pO6P9X8nJyb5VpLd+tsen+T8GR6Dn/i7mv63NEP97weePjL9TOCc9kdeY2B/xf660Oyx9tifUFVe5uECHAhsAPYBrgOe2M/f0N/2G8AlwF50I/0fAv5ohu1sW34f4JPAXv38VwF/M7LMn/TX3wl8pt/m44Ev9/PXAmu21dXPexfwvP76y4E/n+E+3A48sp8+Z1uN3aFS0H3j4yP66ycCvzbt9p8GbgQO7Kf/DDh7pO41/fWDgGuBAHcFvgWsGvfvcTFe+t/LZuDykcuf9bf9NXDEyGP6g/76KcCXRo6L24Cf76evAQ6lG8W6uF/+4n76V4FP9/N+Brh6hnouBt7cX/9N4EvTjrk/AP62n3cI8PrR2/vr7wNePFL3RuC+fd0Xj+zrn4En9NfPBJ45rZbt/l31x9uB2/kbewxwVT+9B3BZX/vakcfvlHH/7r3c4W9gA/ZX++twx5c91h7bdHHEeZ5V1feB59O9pLj3yE1PAP6xqn5UVVvpDtAj7mQ7xwK/m+SvgN8C7jayyLb/Cq8D/rnf5nXAPXdQ3pl0L63Qb/vdMyyzsf7rK9CvBu4z7fZ/Aj6Y5M3AV6rqE9NufyTwxara0E+/nTvez3X9/fsm3R/X44DfAT5SVbfuoPblbmNVHTZyeX0//0+BPZP8BfAa7niMXDByXGyqqvX99I1s/zi5GNg/3UvQzwHXz4koAAAFNUlEQVT+bjvLndv/nOkY+TzwlCTnAr8C/H8zrP8E4Az4z2NhHbBt1GXdyHJnAr+f5C50x9G53NGs/q5G3Ah8L8lDgF8Dph/HWoTsr/bXAdlj7bFNDM4D6Jvd9JcUpz/WYQfnmKd7U8IXgHvQNfG1/TrbbB65vrWxtE8D90vyO8C1VbVxhmVGt1XT9klVvZHuv+ZvAK9LcvK09e/sfv5o5PqZdE8wx9LdP83e+4CnAuuBl067bdbHSHVDAe8CngU8g5mf/Ee3N9Mxcg3wEODvgccCX0ySO66+w+Nk9Bg5G3gi3Ut+H53hyX9Wf1fTnA0cQ3c/z2pcR2Nmf70D++vw7LHb386d2SV7rMF5OH8KPAnYv5/+FPCsJHslWQk8l+5lue15BPCNvpGuA44CVuxg+Ts18gd7GnNspP15dntX1V8DbwQe1t90W3+/1gGPzn+9aeYFbP9+nkP3n+u+VbVuO8tox54IvLyqPkT3ciGZdm7nHKwFjgeu386T/w4lOQF4ZVWdDfx3upeX7073RLCt4X4K+MN++YPoXtb7wvRtVdUtdMHmVGY+Zmf7dzXqbLqGfkhVfblxHS0O9teO/XV49lh77B34qRoDqarvJ3k+8PF++rz+BPpL6R73jwN/s4NNfAJ4UZL1wK10DXP1PJT2Xronnekvx7R6KbA2yVa6/1qP7+d/CLgCmKBr5h9MsgfdS1h/ONOGqupHSb4AXDXT7WpyCvDZJN8Fvkb38uzP7swGq+r6JN9i7qNUfwf8Y5Kr6D4J4ZSq+m6STwKn9rWeCLw9yXPpRlSOq6pNPzloAnTH7GNmevKfw9/V6Lob+1ounvU91FjZX+2vC+gU7LH22BHp/knWctC/c/Z44CFVdeKYawmwN91/wEdU1bfHWY86/e9lP7o3jKwe93mR/cjOa4DvVNUbxlmLtCP2V7Wwxy59jjgvLx8AHkD3Eue4PQL4GN3LTTb1xeNpwFuAF427ofcuBf6V7mOWpMXM/qoW9tglzhFnSZIkqYFvDpQkSZIaGJwlSZKkBgZnSZIkqYHBWctKkj9Msi7JV5L83yQXJHnUna8pSdoR+6uWAz9VQ8tGklPpvoL2GVV1XT/vCcB5SSaq6ltjLVCSlij7q5YLR5y1LCS5L/A/gGO2NXWAqvoU8GLgrkk2JDmrHy15apJfSHJRkiuTXJHkOf22Dk8yNbLt/5xOckqSs5N8JsnXk7wvyT4Le28laeHYX7WcOOKs5eKXgK9U1abpN1TVuwH6b1Saqqpn9l8t+jXgz6rqA0n2B76Y5JqGfT0aeDhwE/Ae4OXASfNzNyRp0bG/atlwxFnLRei+drSbSPZOcnl/+Ub/MiPAZ/qfDwb2rKoPQPfVocD7gV9v2NfZVfUvVXU7cAaL4wsRJGko9lctGwZnLRfrgIckuTdAVf2gqg6rqsPoRi22vdz3w/7nTH8buwG70z1BZGT+HtOW2zptndt2snZJWszsr1o2DM5aFvoRjTcBZyd5wLb5/fXH8JPN92vA5iS/0y+3P91XpV5A9xLhA5L8dLrXH58ybd2jk9w9yW7A84EPD3GfJGkxsL9qOfEcZy0bVXVykmcDf5/kbnSjGz8GzgL+Fjh6ZNktSZ4CnJbkFLq/lVdV1UUASd4GXApsAs6btqt/AT4K3Af4NHAqkrQLs79quUhV3flSkpr0TwL3qaoTxl2LJO1K7K9aDDxVQ5IkSWrgiLMkSZLUwBFnSZIkqYHBWZIkSWpgcJYkSZIaGJwlSZKkBgZnSZIkqYHBWZIkSWrw/wAwGpWATCnOAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"Group\", y=\"percentage\", col=\"Process\", data=DF[DF.Variable == 'Family history'], kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation 2\n",
    "\n",
    "participants working remotetly have the same probably of being diagnosed with mental illness as participants that do not work remotely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Group</th>\n",
       "      <th>Process</th>\n",
       "      <th>Participants on treatment MI</th>\n",
       "      <th>Participants not on treatment MI</th>\n",
       "      <th>Variable</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Does not work remotely</td>\n",
       "      <td>true value</td>\n",
       "      <td>424</td>\n",
       "      <td>429</td>\n",
       "      <td>Remote work</td>\n",
       "      <td>49.706917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Does not work remotely</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>421</td>\n",
       "      <td>420</td>\n",
       "      <td>Remote work</td>\n",
       "      <td>50.059453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Works remotely</td>\n",
       "      <td>true value</td>\n",
       "      <td>191</td>\n",
       "      <td>169</td>\n",
       "      <td>Remote work</td>\n",
       "      <td>53.055556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Works remotely</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>198</td>\n",
       "      <td>165</td>\n",
       "      <td>Remote work</td>\n",
       "      <td>54.545455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Group             Process  Participants on treatment MI  \\\n",
       "0  Does not work remotely          true value                           424   \n",
       "2  Does not work remotely  privacy-preserving                           421   \n",
       "1          Works remotely          true value                           191   \n",
       "3          Works remotely  privacy-preserving                           198   \n",
       "\n",
       "   Participants not on treatment MI     Variable  percentage  \n",
       "0                               429  Remote work   49.706917  \n",
       "2                               420  Remote work   50.059453  \n",
       "1                               169  Remote work   53.055556  \n",
       "3                               165  Remote work   54.545455  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DF[DF.Variable == 'Remote work'].sort_values(['Group'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x131d51240>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"Group\", y=\"percentage\", col=\"Process\", data=DF[DF.Variable == 'Remote work'], kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Privacy by design"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An adversarial researcher might try to drill down the data in order to get information about specific survey participants.\n",
    "\n",
    "Differential privacy mechanisms are designed to address such queries with suficient noise to mask the participation of any individual.\n",
    "\n",
    "In scenarios without a trusted curator, the SmartNoise library provides accuracy intervals to the researcher. An $\\alpha$-level accuracy guarantee a promise that (with probability $1-\\alpha$)\n",
    "\n",
    "$$\n",
    "M(D) \\in [M_{DP}(D)-a, M_{DP}(D)+a]\n",
    "$$\n",
    "\n",
    "where $M(D)$ is the query response of function $M$ on database $D$ without differential privacy, and $M_{DP}(D)$ is the response with differential privacy.\n",
    "\n",
    "Accuracy pitfalls and edge cases are discussed in [this notebook](https://github.com/opendifferentialprivacy/smartnoise-samples/tree/master/analysis/accuracy_pitfalls.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Observation 3\n",
    "\n",
    "The US has the biggest percent of professionals in the tech industry diagnosed with mental illness (around 54%). In other countries having the lowest percentages, fewer than 40% of tech workers have been treated for mental illness."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Group</th>\n",
       "      <th>Process</th>\n",
       "      <th>Participants on treatment MI</th>\n",
       "      <th>Participants not on treatment MI</th>\n",
       "      <th>Variable</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CA</td>\n",
       "      <td>true value</td>\n",
       "      <td>34</td>\n",
       "      <td>32</td>\n",
       "      <td>Country</td>\n",
       "      <td>51.515152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CA</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>Country</td>\n",
       "      <td>56.896552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Other</td>\n",
       "      <td>true value</td>\n",
       "      <td>93</td>\n",
       "      <td>147</td>\n",
       "      <td>Country</td>\n",
       "      <td>38.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Other</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>131</td>\n",
       "      <td>137</td>\n",
       "      <td>Country</td>\n",
       "      <td>48.880597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>UK</td>\n",
       "      <td>true value</td>\n",
       "      <td>88</td>\n",
       "      <td>87</td>\n",
       "      <td>Country</td>\n",
       "      <td>50.285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>UK</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Country</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>US</td>\n",
       "      <td>true value</td>\n",
       "      <td>400</td>\n",
       "      <td>332</td>\n",
       "      <td>Country</td>\n",
       "      <td>54.644809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>US</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>405</td>\n",
       "      <td>336</td>\n",
       "      <td>Country</td>\n",
       "      <td>54.655870</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Group             Process  Participants on treatment MI  \\\n",
       "3     CA          true value                            34   \n",
       "7     CA  privacy-preserving                            33   \n",
       "0  Other          true value                            93   \n",
       "4  Other  privacy-preserving                           131   \n",
       "2     UK          true value                            88   \n",
       "6     UK  privacy-preserving                            90   \n",
       "1     US          true value                           400   \n",
       "5     US  privacy-preserving                           405   \n",
       "\n",
       "   Participants not on treatment MI Variable  percentage  \n",
       "3                                32  Country   51.515152  \n",
       "7                                25  Country   56.896552  \n",
       "0                               147  Country   38.750000  \n",
       "4                               137  Country   48.880597  \n",
       "2                                87  Country   50.285714  \n",
       "6                                90  Country   50.000000  \n",
       "1                               332  Country   54.644809  \n",
       "5                               336  Country   54.655870  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DF[DF.Variable == 'Country'].sort_values(['Group'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x131db9828>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YnCVJkqQGBmdJkiSpgcFZkiRJamBwliRJkhoYnCVJkqQGBmdJkiSpgcFZkiRJamBwliRJkhoYnCVJkqQGBmdJkiSpQXNwTnJ4khOS7J7kaX0WJUmSJI2bpuCc5M+A5wJPAXYDXp7kpX0WJkmSJI2T1hnn3wMeB9xQVd8BDgaO6K0qSZIkacy0BufNVXXTtoWq+j6wuZ+SJEmSpPGzunG7a5M8Hqgka4DjgK/1V5YkSZI0XlqD8/OBdwP3B24AzgOO7KsoSZIkadw0Beequg44JMnuwKqq+lG/ZUmSJEnjpSk4JzkZqBnLBdwITAMnVdXN/ZQnSZIkjYeFfADKA4FLgYuA+wF3AR4DvKGHuiRJkqSx0nqN832Ah2+7RCPJScAngIczmHWWJEmSdmitM863nXVd80+AW1dVAZuGX5YkSZI0XlpnnM9L8h7g7UCAY4DzkzyWwbtsSJIkSTu01hnn5wDXAq8HXgv8F4O3qNsLeHY/pUmSJEnjo/Xt6H4C/Hl3AyDJrarq1L4KkyRJksZJ69vRHQa8CtiDwaUaq4DbAXv2V5okSZI0Plov1fg74ETg68AfAh8D3tJXUZIkSdK4aX1x4A1VdWqSdcBPgecCF/RXliRJkjReWmecb0qyBrgKWFdVW4E1/ZUlSZIkjZfWGed/Az4KrAc+n+ThwHf6KkqSJEkaN00zzlV1IvCMqvoG8ETgs8CT+ixMkiRJGidNwTnJGVX1dYCqurCq3gh8uNfKJEmSpDGy3Us1kpwGHADcPcklMx7aGdjaZ2GSJEnSOLmla5yPA/YH3ga8YMb6LcBlPdUkSZIkjZ3tBuequga4Jsm9unfSkCRJkiZS69vRPSnJNUl+kOSHSX6U5Ie39KQkr0pyeZLLkry4W3dokkuSXJnkhCVVL0mSJC2T1rejezXwYuBCoFqekOSRwK8D92dwTfTlSc4E3gE8ErgW+GiSx1bVGQstXJIkSVpOrcH5e1X1wYXsuKo+k+TRVbUlyZ26Y90GuLKqrgZI8h7gyYDBWZIkSWOt9VKN85M8dqE7r6rNSV4JXA6cCewLbJyxyUZgv4XuV5IkSVpurTPOjwOen2QTsAkIUFW11y09sapenuQ1DN73+Z5zbLKgFx1OT0/P+9jU1NRCdrVD2rBhw6Ke59gtfuzA8XPslmZ747fc42OPnZ9f54vn2C2N47d4w+6vrcH5kIXuOMm9gV2r6qKqujHJB4HDgZtnbLYPcN1C9rt27VrWrFmz0HImxqR/gyyFY7d4jt3SjNP42WPnN07/TyuNY7c0jt/iDXvsWj9y+2vAg4FnAdcDD+vWbc/dgLclWZNkF+Aw4K3AvZLcI8kq4Ai8vlmSJEkrQNOMc5I/A34DuDPweuDlSe5RVX8133Oq6vQkBwFfZjDL/IGqel+S64EPALsCpwOnLfEcJEmSpN61Xqrxe8BBwHlV9Z0kBwNfAOYNzjC4vhl4+ax1ZwIPWEStkiRJ0si0vqvG5qq6adtCVX0f2NxPSZIkSdL4aZ1xvjbJ44FKsgY4Drila5wlSZKkHUZrcH4+8G4GnwJ4A3AecGRfRUmSJEnjpik4V9V1SQ5j8J7Lqxm8zdy3e61MkiRJGiNN1zgneQrw5aq6EdgbmE7y271WJkmSJI2R1hcHHg88GqCqvgpMAa/sqyhJkiRp3LQG51VV9Y1tC1V17QKeK0mSJK14reH320menWR1klVJngH8d5+FSZIkSeOkNTg/GzgW+Anw0+7+c/sqSpIkSRo3rW9Hd9+qmkpyW2BLVf2oz6IkSZKkcdM643wiQFV9z9AsSZKkSdQ643xpkuOBc4Afb1tZVRf2UpUkSZI0ZlqD80Hd7Zkz1hVwt6FXJEmSJI2h1k8O/JW+C5EkSZLGWesnB+6R5O+TnJnkdknemmSPvouTJEmSxkXriwPfBPwA+GUGb0e3F/CPfRUlSZIkjZvW4HxgVR0PbK6qG4EjgXX9lSVJkiSNl9bgfPOs5VXA1iHXIkmSJI2t1uD82SSvAXZL8hjgX4Gz+itLkiRJGi+twflPGbx/807A3wMXAX/SV1GSJEnSuGl9H+e7AU/o/g3wcOCOwNd7qkuSJEkaK60zzqcAJwG7dbfTgLf3VJMkSZI0dlqD8+5V9daq2lxVm6rq/zB4azpJkiRpIrQG5/9K8rBtC0nWAlf3U5IkSZI0flqvcb4T8JkkFwNbgAOBbyW5BKCq7t9TfZIkSdJYaA3OvoOGJEmSJlpTcK6qz/RdiCRJkjTOWq9xliRJkiaawVmSJElqYHCWJEmSGhicJUmSpAYGZ0mSJKmBwVmSJElqYHCWJEmSGhicJUmSpAYGZ0mSJKmBwVmSJElqYHCWJEmSGhicJUmSpAYGZ0mSJKlBr8E5ycuTXNbdXtutOzTJJUmuTHJCn8eXJEmShqW34JzkUOA3gQOBdcBUkqcB7wAOA+4DPDjJY/uqQZIkSRqWPmecNwJ/XFWbqmozcAVwAHBlVV1dVVuA9wBP7rEGSZIkaSh6C85VdVlVnQeQ5J7AU4GtDAL1NhuB/fqqQZIkSRqW1X0fIMn9gI8CxwGbgXvN2mTrQvY3PT0972NTU1MLLW+Hs2HDhkU9z7Fb/NiB4+fYLc32xm+5x8ceOz+/zhfPsVsax2/xht1few3OSX4V+ADwR1X1viSPBPaesck+wHUL2efatWtZs2bNEKvcsUz6N8hSOHaL59gtzTiNnz12fuP0/7TSOHZL4/gt3rDHrs8XB94Z+BBwRFW9r1t9PnCvJPdIsgo4AjijrxokSZKkYelzxvk4YFfgdUm2rXsLsJ7BLPSuwOnAaT3WIEmSJA1Fb8G5ql4EvGiehx/Q13ElSZKkPvjJgZIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVKD3oNzkr2STCfZv1s+NMklSa5MckLfx5ckSZKGodfgnOQg4HPAAd3ybsA7gMOA+wAPTvLYPmuQJEmShqHvGednAc8DruuWHwJcWVVXV9UW4D3Ak3uuQZIkSVqy1X3uvKqeCZBk26p9gY0zNtkI7NdnDZIkSdIw9Bqc55A51m1dyA6mp6fnfWxqamqh9exwNmzYsKjnOXaLHztw/By7pdne+C33+Nhj5+fX+eI5dkvj+C3esPvrcgfnbwJ7z1jeh/+5jKPJ2rVrWbNmzVCL2pFM+jfIUjh2i+fYLc04jZ89dn7j9P+00jh2S+P4Ld6wx265347ufOBeSe6RZBVwBHDGMtcgSZIkLdiyBueq+imwHvgAcDnwH8Bpy1mDJEmStBjLcqlGVe0/4/6ZwAOW47iSJEnSsPjJgZIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNTA4S5IkSQ1GEpyTHJHk8iRXJXneKGqQJEmSFmL1ch8wyZ2AVwNTwE3A55OcVVWXL3ctkiRJUqtRzDgfCny6qr5bVTcApwGHj6AOSZIkqdmyzzgD+wIbZyxvBB7S8LxVAJs2bdruRnvtvvOiC1vpbrrppqXtYNc9h1PICrTksQP23PlWQ6hk5RnG2O20p19785ment4f+MbU1NSWnkuxx27HML7OJ7XH2l+Xxh67eH3011TVEstamCR/AexeVX/ZLT8TeFBVPWd7z9uwYcOvAecsQ4mSNG5+ZWpq6po+D2CPlTShFtRfRzHj/E3g4TOW9wGua3jel7rnbQRu7qEuSRpX31iGY9hjJU2iBfXXUcw43wn4HIPLM24APg8cW1VfXNZCJEmSpAVY9hnnqvpmkuOBs4BdgJMMzZIkSRp3yz7jLEmSJK1EfnKgJEmS1MDgLEmSJDUwOEuSJEkNDM6SJElSA4OzJEmS1MDgPI8keyR5c5Krklyc5Jwkh3SPHZvkad39U5KsH2mxK0SS/ZNcM8f66v59XpKLuvG+KMnRy17kGNve+CVZn+SUGev2TfLVJC9czhrHWZK9uu/p6e7r66wkD5zx+NpuLJ80yjonhT12+Oyxi2d/XZpJ6q+j+OTAsZckwIeBi4D7VtWmJAcCH01yBPAw4OwRlrjDSXIQ8EzgoVX1kyR3BC5IcnFVXTzi8laUJHsDZwJvqKp/GHU94yDJTsDpDN4/fl1VbUnyaOCMJPetqu8AxwCnAc8BPjC6and89tjlZ48dDvvrL5q0/uqM89weCdwVeHFVbQKoqi8DJzD4hnkC8Kokj+m2f3ySLyb5WpJj4WezKe9MsqH77Wvb7Mn67jexS5OcuOxnNr72BgLsDlBV3wYOB64fZVErTffD8FPA62zqP+fRwL7Ay6tqC0BVncWgma9Ksho4CjgeODDJ3UdW6WSwxy4/e+wS2V/nNVH91eA8twcDF9QvfjrMZxl8TPi/Ay+rqo9363cFDgIeD7y6W/eXwIaqmgIeARyf5G7dY/sBB1bVX/R4DivNGcA1wMYkn0nyCuA7VXXdSKtaWX6JQejYBXjniGsZNwcCX6qqrTNXVtXpXYB4PPC1qvoq8CHg2SOocZLYY5efPXZp7K/zm6j+anCeWzH3ZSy7zLP9v3U/AC4D7tCtOxR4TpKLGPwwuBVwv+6xC7f9VjZhts5e0f3JtqpqU1U9EbgvcCowBVyS5OBlrnGczTt+3eJvAX8HXAX8zTLWtRJsZTDbNp9jgH/u7p8KrE8y3/e7ls4e2w977OLZXxdvovqrwXlu5wMPSrLzrPUPBb40x/bb/jQxc/ZkFXBUVa2rqnXAwcDHusd+MuR6V4rvAbeete6OwPeSHJ3kkKq6qqr+oap+G3gD8PRlr3J8zTt+3f1/qap3As8Anp7ksctZ3Ji7AHhg94PwZ5KcmOSpwOOAP+5eHHQScFtgxb+IZYzZY/thj108++viTVR/NTjPoarOYTCz8YZtjT3JFIM/Df4VgyZ+Sy+s/DTw3O65+wCXAHfpq+aVoKp+BFw561W1xzK4ZmwV8NdJ7gDQXRN1APDlZS90TN3C+AHc1G33LQYvwDglyS8vb5Vj6xzg28DLk6wC6K6fPQbYHzizqvarqv2r6q4MLgdY0X9OHGf22H7YYxfP/rokE9VfDc7z+10G3yjTSS4H3shgduNsBt9If5Hk8O08/5XAbkmmGTT4l1TVf/Zc80pwFPCHGbwd0hXAWuB5VXUy8H7g3G79pcA08PbRlTqW5hy/2RtV1QcYzL69a/YswCTqZiqfANydwff0JcCfMpgJOQqY/UKffwAekuTey1roZLHH9sMeu3j210WYtP6aX3xthiRJkqTZnHGWJEmSGhicJUmSpAYGZ0mSJKmBwVmSJElqYHCWJEmSGhicNVGS/EGS85NckeQ/k3wyyUGjrkuSVjr7qybBLb3BvLTDSHIi8AjgKVX1tW7drwMfSTJVVV8faYGStELZXzUpnHHWROg+4emPgCdva+oAVfVp4MXArZJck+TUbrbkd5LcL8lZSS7p3hD/6G5fj+o+dIHZy0lekeT9Sc5J8tUk/5Jkr+U9W0laPvZXTRJnnDUpHgpcUVUbZz9QVe8G6D4Aarqqntp9HO28PZtBAAABgklEQVRXgD+pqg8m2Rf4YpIrG451MPAg4HrgPcDLgOOGcxqSNHbsr5oYzjhrUgT42cdkJtkzyUXd7aruz4wA53T/HgDsWlUfBKiq64APAL/VcKz3V9V/V9VWBh9n+5ihnYUkjR/7qyaGwVmT4nzg3kluD1BVP6qqdVW1jsGsxbY/9/24+3eu742dgJ0Z/IDIjPW7zNpuy6zn3LzE2iVpnNlfNTEMzpoI3YzGG4H3J7nLtvXd/V/lF5vvV4BNSX63225f4EnAJxn8ifAuSe6Ywd8fnzjruYcluXWSnYBnAR/u45wkaRzYXzVJvMZZE6Oqjk9yJPBPSfZgMLvxU+BU4M3AYTO23ZzkicCbkryCwffKq6rqLIAkbwUuADYCH5l1qP8GTgfuAHwWOBFJ2oHZXzUpUlW3vJWkJt0PgTtU1fNHXYsk7UjsrxoHXqohSZIkNXDGWZIkSWrgjLMkSZLUwOAsSZIkNTA4S5IkSQ0MzpIkSVIDg7MkSZLUwOAsSZIkNfj/A6EmlLOJWrcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"Group\", y=\"percentage\", col=\"Process\", data=DF[DF.Variable == 'Country'], kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Observation 4\n",
    "\n",
    "As we explore the percentage of participants in each age group that sought MI treatment, we observe that very similar conclusions can be drawn from true values and from privacy preserving values. The exception in for age group of participants 60+ years old. \n",
    "\n",
    "As expected, in very small data partitions the distortions are greater.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Group</th>\n",
       "      <th>Process</th>\n",
       "      <th>Participants on treatment MI</th>\n",
       "      <th>Participants not on treatment MI</th>\n",
       "      <th>Variable</th>\n",
       "      <th>percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21-30</td>\n",
       "      <td>true value</td>\n",
       "      <td>225</td>\n",
       "      <td>253</td>\n",
       "      <td>Age</td>\n",
       "      <td>47.071130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>21-30</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>229</td>\n",
       "      <td>250</td>\n",
       "      <td>Age</td>\n",
       "      <td>47.807933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31-40</td>\n",
       "      <td>true value</td>\n",
       "      <td>285</td>\n",
       "      <td>269</td>\n",
       "      <td>Age</td>\n",
       "      <td>51.444043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>31-40</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>262</td>\n",
       "      <td>267</td>\n",
       "      <td>Age</td>\n",
       "      <td>49.527410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41-50</td>\n",
       "      <td>true value</td>\n",
       "      <td>87</td>\n",
       "      <td>62</td>\n",
       "      <td>Age</td>\n",
       "      <td>58.389262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>41-50</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>92</td>\n",
       "      <td>60</td>\n",
       "      <td>Age</td>\n",
       "      <td>60.526316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>50-60</td>\n",
       "      <td>true value</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>Age</td>\n",
       "      <td>57.692308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>50-60</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>15</td>\n",
       "      <td>17</td>\n",
       "      <td>Age</td>\n",
       "      <td>46.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60+</td>\n",
       "      <td>true value</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>Age</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>60+</td>\n",
       "      <td>privacy-preserving</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>Age</td>\n",
       "      <td>33.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Group             Process  Participants on treatment MI  \\\n",
       "0  21-30          true value                           225   \n",
       "5  21-30  privacy-preserving                           229   \n",
       "1  31-40          true value                           285   \n",
       "6  31-40  privacy-preserving                           262   \n",
       "2  41-50          true value                            87   \n",
       "7  41-50  privacy-preserving                            92   \n",
       "3  50-60          true value                            15   \n",
       "8  50-60  privacy-preserving                            15   \n",
       "4    60+          true value                             3   \n",
       "9    60+  privacy-preserving                             3   \n",
       "\n",
       "   Participants not on treatment MI Variable  percentage  \n",
       "0                               253      Age   47.071130  \n",
       "5                               250      Age   47.807933  \n",
       "1                               269      Age   51.444043  \n",
       "6                               267      Age   49.527410  \n",
       "2                                62      Age   58.389262  \n",
       "7                                60      Age   60.526316  \n",
       "3                                11      Age   57.692308  \n",
       "8                                17      Age   46.875000  \n",
       "4                                 3      Age   50.000000  \n",
       "9                                 6      Age   33.333333  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DF[DF.Variable == 'Age'].sort_values(['Group'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x131e4e7b8>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"Group\", y=\"percentage\", col=\"Process\", data=DF[DF.Variable == 'Age'], kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparing associations between variables\n",
    "### Different variables and variable 'treatment for MI'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Intercorrelation of two discrete variables\n",
    "\n",
    "Cram&eacute;r's V, sometimes referred to as Cram&eacute;r's phi (denoted as &phi;c), is a measure of association between two nominal variables, giving a value between 0 and +1 (inclusive). It is based on Pearson's chi-squared statistic.\n",
    "\n",
    "&phi;c is the intercorrelation of two discrete variables. and may be used with variables having two or more levels. &phi;c is a symmetrical measure, it does not matter which variable we place in the columns and which in the rows. Also, the order of rows/columns doesn't matter, so &phi;c may be used with nominal data types or higher (notably ordered or numerical).\n",
    "\n",
    "Source: Wikipedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cramers_stat(confusion_matrix):\n",
    "    \"\"\" calculate Cramers V statistic for categorial-categorial association.\n",
    "        uses correction from Bergsma and Wicher, \n",
    "        Journal of the Korean Statistical Society 42 (2013): 323-328\n",
    "    \"\"\"\n",
    "    chi2 = ss.chi2_contingency(confusion_matrix)[0]\n",
    "    n = sum(confusion_matrix.sum())\n",
    "    phi2 = chi2/n\n",
    "    r,k = confusion_matrix.shape\n",
    "    phi2corr = max(0, phi2 - ((k-1)*(r-1))/(n-1))    \n",
    "    rcorr = r - ((r-1)**2)/(n-1)\n",
    "    kcorr = k - ((k-1)**2)/(n-1)\n",
    "    return np.sqrt(phi2corr / min( (kcorr-1), (rcorr-1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "Coefs_var = ['Family history', 'Gender', 'Remote work', 'Age', 'Country'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "coefs = []\n",
    "dpcoefs = []\n",
    "for variable in Coefs_var:\n",
    "    coefs.append(cramers_stat(DF[(DF.Variable == variable)&(DF.Process == 'true value')][['Participants on treatment MI', 'Participants not on treatment MI']]))\n",
    "    dpcoefs.append(cramers_stat(DF[(DF.Variable == variable)&(DF.Process == 'privacy-preserving')][['Participants on treatment MI', 'Participants not on treatment MI']]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = {'True Coef': coefs,\n",
    "        'Privacy Coef':dpcoefs}\n",
    "cramer_coef = pd.DataFrame(data=c, index = Coefs_var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>True Coef</th>\n",
       "      <th>Privacy Coef</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Family history</th>\n",
       "      <td>0.380581</td>\n",
       "      <td>0.385125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gender</th>\n",
       "      <td>0.196000</td>\n",
       "      <td>0.173099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Remote work</th>\n",
       "      <td>0.002006</td>\n",
       "      <td>0.026834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.046954</td>\n",
       "      <td>0.063414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <td>0.112341</td>\n",
       "      <td>0.022481</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                True Coef  Privacy Coef\n",
       "Family history   0.380581      0.385125\n",
       "Gender           0.196000      0.173099\n",
       "Remote work      0.002006      0.026834\n",
       "Age              0.046954      0.063414\n",
       "Country          0.112341      0.022481"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cramer_coef"
   ]
  }
 ],
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