Now using py files, for automation
[covid19.git] / hospital_data.ipynb
index b5ea101d36beae0de2a97ddce38cb405868a5bd0..d42d43c493970569df7027d99804570a7123e1a5 100644 (file)
@@ -2,9 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 91,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sql extension is already loaded. To reload it, use:\n",
+      "  %reload_ext sql\n"
+     ]
+    }
+   ],
    "source": [
     "import itertools\n",
     "import collections\n",
     "from scipy.stats import gmean\n",
     "import datetime\n",
     "\n",
+    "import sqlalchemy\n",
+    "\n",
     "import matplotlib as mpl\n",
     "import matplotlib.pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
-      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
-      "100  1292    0  1292    0     0   1196      0 --:--:--  0:00:01 --:--:--  1196\n"
-     ]
-    }
-   ],
-   "source": [
-    "!curl \"https://api.coronavirus-staging.data.gov.uk/v1/data?filters=areaName=United%2520Kingdom;areaType=overview&structure=%7B%22date%22:%22date%22,%22areaName%22:%22areaName%22,%22areaType%22:%22areaType%22,%22newAdmissions%22:%22newAdmissions%22,%22cumAdmissions%22:%22cumAdmissions%22%7D&format=csv\" | gunzip > hospital_admissions.csv"
+    "%matplotlib inline\n",
+    "%load_ext sql"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
+   "execution_count": 92,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [],
    "source": [
-    "raw_data = pd.read_csv('hospital_admissions.csv', \n",
-    "                       parse_dates=[0], dayfirst=True,\n",
-    "                      )"
+    "connection_string = 'postgresql://covid:3NbjJTkT63@localhost/covid'"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
+   "execution_count": 93,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "date             datetime64[ns]\n",
-       "areaName                 object\n",
-       "areaType                 object\n",
-       "newAdmissions             int64\n",
-       "cumAdmissions             int64\n",
-       "dtype: object"
+       "'Connected: covid@covid'"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 93,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data.dtypes"
+    "%sql $connection_string"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conn = sqlalchemy.create_engine(connection_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [],
+   "source": [
+    "normalisation_date = '2020-08-01' # '2020-05-15'\n",
+    "\n",
+    "hospital_normalisation_date = {\n",
+    "    'hospital_normalisation_date': normalisation_date\n",
+    "}\n",
+    "\n",
+    "with open('hospital_normalisation_date.json', 'w') as f:\n",
+    "    json.dump(hospital_normalisation_date, f)\n",
+    "    \n",
+    "hnd = pd.to_datetime(normalisation_date).strftime(\"%d %B %Y\")\n",
+    "with open('hospital_normalisation_date.js', 'w') as f:\n",
+    "    f.write(f\"document.write('{hnd}');\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [
     {
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>areaName</th>\n",
-       "      <th>areaType</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td>2020-03-23</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1687</td>\n",
-       "      <td>6794</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-24</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1931</td>\n",
-       "      <td>8725</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-25</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>1968</td>\n",
-       "      <td>10693</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-26</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>2222</td>\n",
-       "      <td>12915</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-27</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>2165</td>\n",
-       "      <td>15080</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-01</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>133</td>\n",
-       "      <td>132672</td>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>3341.0</td>\n",
+       "      <td>3771.7500</td>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1238.7142</td>\n",
+       "      <td>38144.0</td>\n",
+       "      <td>38057.168</td>\n",
+       "      <td>4076.0</td>\n",
+       "      <td>4015.8572</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-02</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>109</td>\n",
-       "      <td>132781</td>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3651.6667</td>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>1348</td>\n",
+       "      <td>1241.7142</td>\n",
+       "      <td>37266.0</td>\n",
+       "      <td>37915.600</td>\n",
+       "      <td>4066.0</td>\n",
+       "      <td>4027.3333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-03</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>89</td>\n",
-       "      <td>132870</td>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37561.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4077.0</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-04</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>126</td>\n",
-       "      <td>132996</td>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4032.0</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-05</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>128</td>\n",
-       "      <td>133124</td>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>136 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "                  areaName  areaType  newAdmissions  cumAdmissions\n",
-       "date                                                              \n",
-       "2020-03-23  United Kingdom  overview           1687           6794\n",
-       "2020-03-24  United Kingdom  overview           1931           8725\n",
-       "2020-03-25  United Kingdom  overview           1968          10693\n",
-       "2020-03-26  United Kingdom  overview           2222          12915\n",
-       "2020-03-27  United Kingdom  overview           2165          15080\n",
-       "...                    ...       ...            ...            ...\n",
-       "2020-08-01  United Kingdom  overview            133         132672\n",
-       "2020-08-02  United Kingdom  overview            109         132781\n",
-       "2020-08-03  United Kingdom  overview             89         132870\n",
-       "2020-08-04  United Kingdom  overview            126         132996\n",
-       "2020-08-05  United Kingdom  overview            128         133124\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
+       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
+       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
+       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
+       "2021-01-26             NaN               NaN        NaN          NaN   \n",
+       "\n",
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
+       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
+       "2021-01-24         610           NaN         37561.0               NaN   \n",
+       "2021-01-25         592           NaN             NaN               NaN   \n",
+       "2021-01-26        1631           NaN             NaN               NaN   \n",
        "\n",
-       "[136 rows x 4 columns]"
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2021-01-22           4076.0          4015.8572  \n",
+       "2021-01-23           4066.0          4027.3333  \n",
+       "2021-01-24           4077.0                NaN  \n",
+       "2021-01-25           4032.0                NaN  \n",
+       "2021-01-26              NaN                NaN  "
       ]
      },
-     "execution_count": 6,
+     "execution_count": 109,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "hospital_data = raw_data.dropna().set_index('date').astype({'newAdmissions': np.int64, 'cumAdmissions': np.int64}).sort_index()\n",
-    "hospital_data"
+    "qstr = '''select uk_data.date\n",
+    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
+    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
+    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
+    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
+    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date'''\n",
+    "hd2 = pd.read_sql_query(qstr, conn)\n",
+    "hd2['date'] = hd2.date.astype('datetime64[ns]')\n",
+    "hd2.set_index('date', inplace=True)\n",
+    "hd2.tail()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
+   "execution_count": 111,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c8fcb5d0>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAESCAYAAAAR2wXeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3deXiU1dn48e+dZbKTPSErYQmyb7IoKlpFBa0v2FYrXcTWt9RWW7X2V23fvrW19bWbtbV1qVtFa0VcWqlVcUMQZQvIFtYQloRAEgjZ98z5/THPxIRMNkhmvT/XNdfMnGeZ84x4z8k557mPGGNQSikVGII8XQGllFLuo0FfKaUCiAZ9pZQKIBr0lVIqgGjQV0qpAKJBXymlAkiIpyvQk6SkJJOTk+PpaiillE/ZvHnzCWNMsqttXh30c3JyyMvL83Q1lFLKp4jI4e62afeOUkoFEA36SikVQDToK6VUAOk16ItIuIhsFJFtIpIvIr+wyp8VkYMistV6TLHKRUQeFpECEdkuItM6nGuxiOy3HosH77KUUkq50peB3CbgUmNMrYiEAmtF5C1r2/8zxrxy2v7zgVzrMQt4DJglIgnAvcB0wACbRWSFMebUQFyIUkqp3vXa0jcOtdbbUOvRU2rOBcBz1nHrgTgRSQOuBN41xlRYgf5dYN7ZVV8ppVR/9KlPX0SCRWQrUIYjcG+wNt1vdeE8JCJhVlkGUNTh8GKrrLtyt2lutbvz45RSyuv0KegbY9qMMVOATGCmiEwAfgyMAWYACcDd1u7i6hQ9lHciIktEJE9E8srLy/tSvT55bUsxM+5/j7KaxgE7p1JK+Zp+zd4xxlQCHwLzjDHHrC6cJuBvwExrt2Igq8NhmUBJD+Wnf8YTxpjpxpjpyckubyg7I4XldVQ1tPDkmsIBO6dSSvmavszeSRaROOt1BDAX2GP10yMiAiwEdlqHrAButGbxnAdUGWOOASuBK0QkXkTigSusMreoamgB4O/rj3CytsldH6uUUl6lL7N30oClIhKM40diuTHmDRH5QESScXTbbAVusfZ/E7gKKADqgW8AGGMqROSXwCZrv/uMMRUDdyk9q25sIToshLrmVp5ee5AfzRvjro9WSimv0WvQN8ZsB6a6KL+0m/0NcGs3254BnulnHQdEVUMLw5OiyE6M5Ll1h1kyZwRxkTZPVEUppTwmYO7IrW5oITYilO9dOoraplZeziv2dJWUUsrtAifoN7YyJCKEMUOHkBBl49DJOk9XSSml3C5ggn6V1dIHSIq2cUIHc5VSAShggn51QwtDwp1BP4yTtc0erpFSSrlfQAT9xpY2mlrtDLFa+onRYdrSV0oFpIAI+tWNjjn6Qzp172hLXykVeAIj6De0AjAk3DFDNSk6jNqmVhpb2jxZLaWUcruACPrOu3E7tvQB7eJRSgWcgAj6zu6dz2bvOBKC6mCuUirQBEbQd7b0wz8byAVt6SulAk9ABf1Y7d5RSgW4wAj6jY6B3JgOA7mAzuBRSgWcgAj6VQ0thIUEER4aDEB4aDDRYSHa0ldKBZyACPrVHVIwOOlcfaVUIAqMoN/Y0j5d08mRikFb+kqpwBIQQb/KRUs/UZOuKaUCkF8G/Q/3ljHnt6uob3YM4FY3tLbfjevUn6Rrxafq+eTAiQGvp1JKuZtfBv38kmqOVNRTWO7Ime+qeycxOoyK+mZa2+y9nu+n/9rJjU9vpKiiflDqq5RS7uKXQb+y3tGCdy6U4qp7JznahjFQUd9za/9YVQNr9pXTajc8+uGBwamwUkq5iZ8GfcfNWIdP1mOM6ZRL36mvqRhe23IUu4HPnZPMK5uLOFrZMDiVVkopN+g16ItIuIhsFJFtIpIvIr+wyoeLyAYR2S8iL4mIzSoPs94XWNtzOpzrx1b5XhG5crAuyplg7fDJOmqbWrEbGBLRuU+/L6kYjDEszyti1vAEfnXtRAAe+7BgkGqtlFKDry8t/SbgUmPMZGAKME9EzgN+AzxkjMkFTgE3W/vfDJwyxowCHrL2Q0TGATcA44F5wKMiEjyQF+NUaQX9Qyfr2+/GdTVPH3oO+hsOVnD4ZD1fnpFFRlwE103PYvmmYo5VaWtfKeWbeg36xqHWehtqPQxwKfCKVb4UWGi9XmC9x9p+mYiIVb7MGNNkjDkIFAAzB+QqTlNV/1lL//Rka05JMb137yzPKyI6LIT5E9IAWHLRCJrb7KzceXwwqq2UUoOuT336IhIsIluBMuBd4ABQaYxptXYpBjKs1xlAEYC1vQpI7Fju4pgBVdngCOSl1U0cr24Eurb0Y8JCsAUHUd5NS/9UXTNv7jjGNZPTibA5/iAZlhhJeGgQxae0pa+U8k19CvrGmDZjzBQgE0frfKyr3axn6WZbd+WdiMgSEckTkbzy8vK+VK+LqoYW0mPDAdhZXAXQZcqmiJAUbeu2pf/46gM0tdr5xgU5nY7JjI/UoK+U8ln9mr1jjKkEPgTOA+JExDk6mgmUWK+LgSwAa3ssUNGx3MUxHT/jCWPMdGPM9OTk5P5UD3Asgt7YYmdSZhwA249aQf+07h34bIF0u92wbOMRCssdvVhl1Y0sXXeIBZPTGZ0a0+mYzPgIiit1vr5Syjf1ZfZOsojEWa8jgLnAbmAV8CVrt8XA69brFdZ7rO0fGGOMVX6DNbtnOJALbByoC3FyztyZlBULwA6rpX969w44BnPLa5r42Yqd3PPaDr742CdsL67kkVUFtLQZ7pg7ussxmfER2tJXSvmskN53IQ1Yas20CQKWG2PeEJFdwDIR+RXwKfC0tf/TwPMiUoCjhX8DgDEmX0SWA7uAVuBWY8yAr0zunKOfnRBJfGRoe59+dHjXS02KDmPV3nLyS6pZNDObj/aX85UnN9DU2sb107PISYrqckxmfCSV9S3UNLYQ4+KvB6WU8ma9Bn1jzHZgqovyQlzMvjHGNALXdXOu+4H7+1/NvnO29OMibAxLjOJUfSUxYSEEB3UdUnDO4Llpdg73XjOO49WNfO2pDRSfauD7l41yef7M+AgAjlY2MGaoBn2llG/pS0vfpzhTMMRFhpKTGMnWosoug7hOX5mZzbCESL48IwsRIS02gtdvu5ATNU2kxUa4PCYzPhKA4ooGxgwdMjgXoZRSg8T/gn6H9XCHJTq6Z7oL+lkJkdwwM7tTWXRYCNFh3X8tzpZ+8SkdzFVK+R6/y73jvDErNjKUnCRHqzw2YuB+2xKjbDpXXynls/wv6De0EBwkxISFkJ1gtfQHcMBV5+orpXyZ3wX9yoZmYiNCERFyEh0t/e66d86UztVXSvkq/wv69Z/lzk+IspERF8GwhMgB/Qydq6+U8lV+N5DbccEUEeHtOy4iPHRgk3nqXH2llK/yu5Z+VUMLcZGfBeKY8FBCgwf2MjvO1VdKKV/id0G/sr6FuAHuwz9dx7n6SinlS/ww6De7zLMzkHSuvlLKV/lV0G+zG6obW4mNtA3q5+hcfaWUr/KroF/T6My7M7gtfZ2rr5TyVX4V9J0ZNge7ewd0rr5Syjf5V9B3ZtiMHPygn5MYxYGyOlrb7IP+WUopNVD8KuhXuTHoT8mKo6Gljf1ltb3vrJRSXsKvgr4zrXJsxOAO5AJMznIsx7i1qHLQP0sppQaKXwX9qgb39ennJEYSFxnK1iMa9JVSvsOvgr47B3JFhMmZcWwr1qCvlPIdfhX0qxpaiLIFYwtxz2VNzopjX2kNdU2tbvk8pZQ6W34V9Dtm2HSHqVlx2A1sL65y22cqpdTZ6DXoi0iWiKwSkd0iki8it1vlPxeRoyKy1Xpc1eGYH4tIgYjsFZErO5TPs8oKROSegb6YqobmQb8btyMdzFVK+Zq+pFZuBe4yxmwRkRhgs4i8a217yBjz+447i8g44AZgPJAOvCcio63NjwCXA8XAJhFZYYzZNRAXAu5JttZRQpSNYYmRbNOgr5TyEb229I0xx4wxW6zXNcBuIKOHQxYAy4wxTcaYg0ABMNN6FBhjCo0xzcAya98Bc3paZXeYnBmnLX2llM/oV5++iOQAU4ENVtFtIrJdRJ4RkXirLAMo6nBYsVXWXfmAOVXf7PagPyUrjuPVjRyvanTr5yql1Jnoc9AXkWjgVeAOY0w18BgwEpgCHAMedO7q4nDTQ/npn7NERPJEJK+8vLyv1aOxpY0Ttc2kx0b0+ZiBMCVb+/WVUr6jT0FfREJxBPwXjDGvARhjSo0xbcYYO/Akju4bcLTgszocngmU9FDeiTHmCWPMdGPM9OTk5D5fiHMVq8wE9wb9MUNjANhXWuPWz1VKqTPRl9k7AjwN7DbG/KFDeVqH3a4FdlqvVwA3iEiYiAwHcoGNwCYgV0SGi4gNx2DvioG5DNrTHDtXtXKXSFsIGXERHCjXHDxKKe/Xl9k7FwBfB3aIyFar7CfAIhGZgqOL5hDwbQBjTL6ILAd24Zj5c6sxpg1ARG4DVgLBwDPGmPyBuhDnKlbOVa3caWRKNAWaeE0p5QN6DfrGmLW47o9/s4dj7gfud1H+Zk/HnY3iUw2EBgspMeGDcfoejUqOZuPBk9jthqAgV1+VUkp5B7+5I7f4VAPpcREEeyDojkqJprHF3j6uoJRS3sqPgn69R7p2wBH0AQq0X18p5eX8KOg3kBnn3kFcJ2fQP6D9+kopL+cXQb+xpY3ymiaPtfQTomwkRNl0MFcp5fX8Iuh7ao5+R6OSdQaPUsr7+UXQ99Qc/Y5GpkRTUF6LMV1uMlZKKa/hJ0Hfc3P0nUalRFNZ38LJumaP1UEppXrjJ0Hfc3P0ndpn8GgXj1LKi/lN0PfUHH0nDfpKKV/gJ0Hfc3P0ndJjw4m0BWvQV0p5NZ8N+s+vP8x7u0oBz87RdxIRRiZHa+I1pZRX60vCNa9jjOG3b+2huc3O8m+f79E5+h3lpkazdv8JT1dDKaW65ZMt/WNVjdQ0tdLUaufmpZsAz87RdxqXNoSymibKa5rayz7cW8brW496sFZKKfUZnwz6zgVLbr8st32KpCfn6DuNT48FYNex6vay363cyw9f3saRk/WeqpZSSrXzyaC/v9TRb754dg53zh1NaLAwPCnKw7VytPQB8kuqAKhvbmXP8Rpa2gy/e2evJ6umlFKAjwb9faU1JEU78t18/7Jc8n56OUnRYZ6uFrGRoWTGR7CrxNHS31ZURZvdMDU7jn9vK2GbrqOrlPIwnwz6+8tqyU2JaX8fGxHqwdp0Nj59SHvQ33LkFAB/XjSVxCgbD7y1W9M0KKU8yueCvjGGgrJaRqdGe7oqLo1Li+XgyTrqmlr59MgpRiRHkRkfyfcvy2V9YUX7D4FSSnmCzwX9kqpGaptayU2N6X1nDxifPgRjYPexaj49UsnUrHgA5k0YCkB+SXVPhyul1KDyuaDvnLkz2luDfoZjMPftncc5WdfMtGFxAKTEhBEdFqILrSilPKrXoC8iWSKySkR2i0i+iNxulSeIyLsist96jrfKRUQeFpECEdkuItM6nGuxtf9+EVl8JhXe3x70vbN7Z+iQcOIjQ3l5czEA07IdLX3HHbtRHCiva9+3tc3Oa1uKaW2ze6SuSqnA05eWfitwlzFmLHAecKuIjAPuAd43xuQC71vvAeYDudZjCfAYOH4kgHuBWcBM4F7nD0V/7CutJTkmjLhIW38PdQsRYXx6LFUNLUTZgjv9RXJ6mob3dpfyg+XbeGvncU9UVSkVgHoN+saYY8aYLdbrGmA3kAEsAJZauy0FFlqvFwDPGYf1QJyIpAFXAu8aYyqMMaeAd4F5/a3w/tIar23lO41Ld3TxTM6K65T5c2RKNMesMQmAbcWO+fzv7y51fyWVUgGpX336IpIDTAU2AKnGmGPg+GEAUqzdMoCiDocVW2XdlfeZ3W66TNf0RuOtoO/s2nEamey4geyg1cWzwwr6q/aWaxePUsot+hz0RSQaeBW4wxjT0xQUV0ntTQ/lp3/OEhHJE5G88vLyTttKqhqob24j18tb+jNyEogJD+FzY1I6lTtz7h+wllXccbSK1CFhVDW0kHdYp3IqpQZfn4K+iITiCPgvGGNes4pLrW4brOcyq7wYyOpweCZQ0kN5J8aYJ4wx040x05OTkzttW7XH8RHeOnPHKT0ugh0/v5Jzh3Vu6WcnRBEcJBwor6WoooGqhhb++8IR2IKDtItHKeUWfZm9I8DTwG5jzB86bFoBOGfgLAZe71B+ozWL5zygyur+WQlcISLx1gDuFVZZr4wx/HX1Af739Xxm5MQzOTOuTxfnbWwhQQxLiKSgrJbtRx0pGc4fmch5IxN5f3dZL0crpdTZ60tL/wLg68ClIrLVelwF/Bq4XET2A5db7wHeBAqBAuBJ4LsAxpgK4JfAJutxn1XWqwff2ccDb+3h85PSeP7mWdhCfO72gnYjrBk8O4qrsAUHMTo1hrljUyg8UacLsCilBl2vi6gYY9biuj8e4DIX+xvg1m7O9QzwTH8qCPDixiPMHZvKwzdMJciD6+AOhJEpUazZV86nEZWMTYvBFhLEpWNS+Nnr+by/u5SRyd49XqGU8m1e32Qur2niZF0zs0cm+nzAB8dc/eY2O3mHK5iY6ci/nxkfyZihMazeV97L0UopdXa8PujvPe64A3fMUO8evO0rZ0vebmBSxmdjE+cOi2d7URV2u2bhVEoNHu8P+s60C34T9D9b7GVCRmz768mZcdQ0tXLwZJ2rw5RSakB4f9A/Xk1StM0rFkkZCHGRNpKibYSFBHW632BSluMHYHuxLrSilBo8PhD0azjHT1r5TuPTY5maHUdo8Gdf/6jkaCJCg9lWVOXBmiml/F2vs3c8bV9pLTfMzOp9Rx/yxy9P6XIrckhwEBMzYrWlr5QaVF7d0m9utdPQ0uY3g7hO8VGO9X1PNykzlvySalo0D49SapB4ddBvbGkD4JyhQzxcE/eYlBVHU6u9fcaSUkoNNO8O+q2OFm9uSmDcsDQ50zmYq/36SqnB4d1Bv6WN7IRIosK8fuhhQGQnRBIXGar9+kqpQeP1Qd/fZu70RESYmBHL1iIN+kqpweHVTeimVjvneHka5YE2JSuORz88wIHyWoYnRtHcZmdrUSU7iqs4WtlASWUDX5iWybwJQz1dVaWUD/LqoA8EVEsfHAuwtNkLuOzB1UTZgmlus9PS5pjgGR0WQpvdcKK2SYO+UuqMeH3Q97fpmr25KDeJ/3z/QnYerWJXSTURthBm5MQzNTuehCgbD7y1m2fWHqSxpY3w0GBPV1cp5WO8OuhPSI8NuFTDIsL49FjGp8e63D5jWAJ/XV3ItqJKZo1IdHPtlFK+zqsHckXwi3TKA8m5BKOuqauUOhNeHfRVV/FRNnJTotl0qE+LjimlVCca9H3QjOEJbD58ijbNva+U6icN+j5oRk48NY2tmq5BKdVvGvR90PRhCQDkHdYuHqVU/2jQ90GZ8REMHRLOpkM6mKuU6p9eg76IPCMiZSKys0PZz0XkqIhstR5Xddj2YxEpEJG9InJlh/J5VlmBiNwz8JcSOESEGcMT2HSwAmO0X18p1Xd9aek/C8xzUf6QMWaK9XgTQETGATcA461jHhWRYBEJBh4B5gPjgEXWvuoMnTcigePVjdz24qcUVdSf0TkaW9pY+skhik+d2fFKKd/T681Zxpg1IpLTx/MtAJYZY5qAgyJSAMy0thUYYwoBRGSZte+uftdYAXD99CzKqpv465oDvJtfyrRhccRF2BiZEsVdl5/j8v4G5/oE4aHBbCuq5K6Xt1FQVsv6wpM89rVz3X0JSikPOJs7cm8TkRuBPOAuY8wpIANY32GfYqsMoOi08lmuTioiS4AlANnZ2WdRPf8WGhzEnZeP5oaZWfzlgwL2l9aSf6yKt/OPM39CGhMyOt/R29jSxkW/XUV5TRNDwkOoa24jOTqMuWNTWJl/nKOVDWTERXjoapRS7nKmA7mPASOBKcAx4EGr3NXts6aH8q6FxjxhjJlujJmenJx8htULHGmxEdx/7USW33I+y799PgDrC0922e/tnccpr2li8fnDuHZqBt+6aAQr75zDLxZMQER4ft1hd1ddKeUBZ9TSN8aUOl+LyJPAG9bbYqDjKuaZQIn1urtyNUDSYiPISYxkfWEF/33RiE7bXtpURHZCJPdeM75T109sRChXjEtl2aYj3H5ZLhE2TeKmlD87o5a+iKR1eHst4JzZswK4QUTCRGQ4kAtsBDYBuSIyXERsOAZ7V5x5tVV3Zg1PZNOhCuwd7tY9crKedYUnue7cTJd9/TfNzqGyvoXXtx51Z1WVUh7QlymbLwLrgHNEpFhEbgZ+KyI7RGQ78DngTgBjTD6wHMcA7dvArcaYNmNMK3AbsBLYDSy39lUD7LyRCVQ1tLD7eHV72SubixCBL03PdHnMzOEJjE0bwrOfHNIpoEr5ub7M3lnkovjpHva/H7jfRfmbwJv9qp3qt1nDHemW1xdWMD49lja74eXNxczJTSYt1vVArYjwtfOy+Z9/7iS/pLrLILBSyn/oHbl+Jj0ugmGJkWywBnNX7yvjWFUj10/P6vG4qyemERos/OtT7eJRyp9p0PdDs4YnsOFgBUcrG7jn1R1kJUQwd1xKj8fERdq4eHQK/95eotk7lfJjGvT90HkjEqlqaOH6x9dR19TKUzfOICyk91k5C6emU1rd1P5XglLK/2jQ90POZRRLqhp4eNHUPi8uP3dsKtFhIfxLZ/Eo5bc06PuhjLgIFkxJ55cLJnDZ2NQ+HxceGsyV44fy1o7j7SkblFL+RYO+n/rTDVP52nnD+n3cginp1DS1smpP2SDUSinlaRr0VSezRyaSEGXjrZ3HPV0VpdQg0KCvOgkJDmLu2BRW7SmjudXu6eoopQaYBn3VxZXjh1LT1Mo6axZPa5udJ9cUcqC81sM1U0qdLQ36qosLRiURaQtmZb6ji+e1T49y/5u7ufaRj11m8PxofznLNh5xdzWVUmdAg77qIjw0mEvOSebdXaU0NLfxx3f3MTZtCClDwvn60xs6JWarbWrl9mVbuee1Hazdf8KDtVZK9YUGfeXSleOHUl7TxA9f3kZJVSP/e/VYXr1lNlOz47lr+TZ2Hq0C4Jm1B6moayZ1SBh3v7qd2qZWD9dcKdUTDfrKpUvOSSEkSPjPjmNclJvE7FFJxEaG8sTXzyUx2sYdL22ltLqRJ9cUcsW4VB796jRKqhp44M3dnq66UqoHGvSVS7ERoZw/0nFn793zxrSXx0Xa+P11kykoq2XBXz6mtrmVH1wxmnOHJXDzBcN5YcMRthdXeqraSqleaNBX3bp73hh+f93kLqmWL8pN5qbZORyvbuSaSemMGToEgO9cMhKAjQcr3F5XpVTfnM3C6MrPTciI7Ta3/j3zx5AUbeO6DimbE6PDSIyysa+0xl1VVEr1kwZ9dUbCQ4O57dLcLuW5qdHsK9X5/Ep5K+3eUQNqdGoMBWW1uuyiUl5Kg74aULmpMdQ2tVJS1ejpqiilXNCgrwbU6JRoAO3XV8pL9Rr0ReQZESkTkZ0dyhJE5F0R2W89x1vlIiIPi0iBiGwXkWkdjlls7b9fRBYPzuUoTxud6liwZb8GfaW8Ul9a+s8C804ruwd43xiTC7xvvQeYD+RajyXAY+D4kQDuBWYBM4F7nT8Uyr/ER9lIjgnrcTD38Mk6Pv/nj/j1W3soPlXvxtoppXoN+saYNcDpE68XAEut10uBhR3KnzMO64E4EUkDrgTeNcZUGGNOAe/S9YdE+YnRqdE9tvRf2lREfkk1T6w5wJzfruJ3K/e4sXZKBbYz7dNPNcYcA7CeU6zyDKCow37FVll35V2IyBIRyRORvPLy8jOsnvKk3JQY9pfVYrd3ncFjjOGN7ce4cFQSH919KddMTueRVQdYvU//WyvlDgM9kCsuykwP5V0LjXnCGDPdGDM9OTl5QCun3GN0agz1zW0crWygtc3OR/vLaWlzLMiy42gVRyrquWZSOhlxEfzmi5PITYnm7le2U9XQ4uGaK+X/zjTol1rdNljPzgVVi4GsDvtlAiU9lCs/NDrVMYNnf1kNv3tnL19/eiN/fG8fAG9sP0ZosHDl+KGA4yavB6+fTHltE7/4d77O71dqkJ1p0F8BOGfgLAZe71B+ozWL5zygyur+WQlcISLx1gDuFVaZ8kO51gyeJ9YU8tfVhSRF23h8dSE7iqt4Y1sJc3KTiY0Mbd9/UmYc371kJK9tOcqCRz7m5bwiGlvaPFV9pfxaX6ZsvgisA84RkWIRuRn4NXC5iOwHLrfeA7wJFAIFwJPAdwGMMRXAL4FN1uM+q0z5odiIUFKHhLG+sIJJmbG8dfscEqNsfHPpJkqqGvn85LQux9wxdzS/XDiB+uY2/t8r27nu8XVU1Wt3j1IDTbz5z+np06ebvLw8T1dDnYFvPruJLUdO8cb3LiQzPpJ38o+z5PnN2EKC2PzTucSEh7o8zhjDmzuOc+dLWxmTFsPzN88iNsL1vkop10RkszFmuqttmnBNDYpff3EiTS12MuMjAbhi/FBump1DWGhQtwEfQES4elIa4aFB3PL3zdz4zEZeWnIe4aHB7qq6Un5NW/rKa7214xjfeWELP7lqDEvmjHS5T1FFPW/tPEZ+STXDEiIZlRrDxaeNGSgVaLSlr3zS/IlpXJSbxKMfHmDRzOxOfyGU1zRx+7JP+eTASQDSYsP597YS7AYSo2z87Jpx/NfkdERczRZWKnBpwjXl1X505Rgq61t48qOD7WV7jlez8JGP+fRIJXfPG8NHP/oc6358Gbvum8crt5xPZnwEty/byree29x+f4BSykFb+sqrTcyM5aqJQ3n6o0IuHJXEmn3lPPvJIaLCgnn5lvM7rewVHhrM9JwEXvvuBTyxppDfvL2Hp9ce5JaLXXcNKRWItKWvvN4PLh9NQ0sb1/91HY9+WMCMnHhev/XCbpdyDA4SvnPJSK4Yl8of39tHUYUmdVPKSQdylU94dXMxNY0tXD0pneSYsD4dU1LZwOV/WM30nASe/cYM7d9XAaOngVxt6Suf8MVzM7npguF9DvgA6XER3HXFOazeV87bO48PYu2U8h0a9JVfWzw7h/TYcP619ainq6KUV9Cgr/xacJBwUW4ynxw4SavO5FFKg77yfxfmJlHT2F6EFC8AABWvSURBVMqOo1V92n9faQ0r84/T0KxJ35T/0Smbyu/NHpkIwMcFJ5ia3f0qnWU1jTz07j5e2lSE3UB0WAifn5TGD688h6Tovo8lKOXNtKWv/F5idBjj04fw0f4T3e5TUdfMlQ+t4eW8YhbPzuG5b85k3oShvPbpUb7/4qcuVwFTyhdpS18FhAtzk3hm7UHqm1uJtHX9Z//39Yc5Vd/Cv269gClZcQDMGZ3MjJx47n51B0+tLew2/49SvkRb+iogXDgqiZY2w4aDjmUciirq21M0NLa0sfSTQ3zunOT2gO90/fQsrhyfyu9W7iW/pPcxgcr6Zsprmgb+ApQaIBr0VUCYkZOALSSIVXvKeODN3cz53SpuXppHc6udf356lJN1zXxrzogux4kIv/7CJBKibHzvxU+pbux+YZdVe8q49MHVXPK7VSzPK9KlH5VX0u4dFRDCQ4OZmZPAc+sOA3BRriOPzw+Wb2XXsWomZAzh/BGJLo+Nj7Lx8A1T+epTG7jtH5/yzOLphAR/1l5qsxv+783dPL32IGOGxhAXGcqPXtnOe7tKmT9xKMMSoxifPoSwEF0TQHmeBn0VMK6dmsGhk3X8/JrxzB2Xyl9XH+CBt/YA8KcbpvSYpmHWiETuv3YCd7+6g1/9Zzc//6/x7dv++N4+nl57kBvPH8ZPrhqLLTiIp9YW8vt39vHOrlIALh6dzNJvzhzcC1SqDzToq4DxxXMz+eK5me3vv33xSJpa7awvPMlVE7uu23u6L8/IZn9pLU+tPUhwkHD3vDF8cuAEf/6ggOvOzeS+BRPa910yZySLZ+dQVNHACxsO87ePD1FYXsuI5OhBuTal+koTrinVD212w33/zmfpusNMzorjyMk6UoeE88/vXkCEzXX3TVl1I+c98D63XDySH80b4+Yaq0A0aAnXROSQiOwQka0ikmeVJYjIuyKy33qOt8pFRB4WkQIR2S4i087ms5XyhOAg4RcLJvDIV6ZxoKyW5lY7j3x1WrcBHyBlSDgXj07mtS1HadP5/srDBmL2zueMMVM6/KrcA7xvjMkF3rfeA8wHcq3HEuCxAfhspTzi6klpvPeDi1nxvQsZ2Ycum+umZ3G8upG1Bd3fIKaUOwzGlM0FwFLr9VJgYYfy54zDeiBORHrvSFXKSw2NDe9TwAe4bGwKcZGhvLK5uF+fUVXfQmOL5gBSA+dsg74B3hGRzSKyxCpLNcYcA7CeU6zyDKCow7HFVlknIrJERPJEJK+8vPwsq6eUdwgLCWbB5HRW5h+nqr77uf4drd5XzoW/+YCvPbVB1/pVA+Zsg/4FxphpOLpubhWROT3s62o+XJcOTmPME8aY6caY6cnJyWdZPaW8x/UzsmhutfP3DYd73ff5dYf45rObGBIRSt7hUzz4zr7Br6AKCGcV9I0xJdZzGfBPYCZQ6uy2sZ7LrN2LgawOh2cCJWfz+Ur5kvHpsXzunGSe/KiQ2qZWl/vUNLbwg5e28r+v53PJ6GRW3jmHRTOzeXz1AVbtKXN5jFL9ccZBX0SiRCTG+Rq4AtgJrAAWW7stBl63Xq8AbrRm8ZwHVDm7gZQKFLfPHU1lfQvPrTvUXmaMoay6kbd3HmP+nz7iX1uP8v3LcnnixulEh4Vw7zXjGDM0hjuXb+U962av07XZTacuoJrGFnaVVLMy/zhPrz3I0k8O6foACjiLefoiMgJH6x4cN3n9wxhzv4gkAsuBbOAIcJ0xpkIctzv+BZgH1APfMMb0OAlf5+krf7T4mY3sOFrFO3fOYdnGIyxdd7g9SVt2QiQPfXkK5w7rnPf/0Ik6ljyfx77SWq6emMbP/2t8+3rB1Y0tLHzkYwrL64gOCyE4SKhq6DpukBEXwf9cPZb5E4bqIvF+rqd5+npzllJutuXIKb7w6CeEhQTR1Grn0jEpXJSbxLi0IUzOiiM81PWc/+ZWO0+sOcDDHxSQmxLNq9+ZTXhoMD/91w7+seGI4w7jFjstbXYy4iPIio8kK8HxvK+0hntX5LPneA13zh3N7XNz3XzVyp006CvlZX6wfCsllQ388IpzmJ6T0K9jP9hTyjefzeP66Zl8eUY2X3r8E74xezg/u2Zcj8e1ttm546WtrMw/zn++fxGjU2Nc7ldR18zXntrADTOzuPH8nH7VTXkHDfpK+ZkH39nLnz8oID4ylPDQYN79wcVEh/WeSutkbRNz/7CaEcnRvPzt8wkK6trN89iHB/jN245EdPctGN8l8J+sbcKALiHpxXoK+ppwTSkfdMfc0WwtquSj/Sd48sbJfQr44Fg68qdXj+Oul7fxwobDfP20gN5mN/x9/WFm5MQTF2njZ6/nc/CEI79QQ3MbawtOsOXIKWIjQnlpyfmcM9T1XwvKe+kiKkr5oOAg4bGvncuL3zqPy8el9uvYL0zL4KLcJH779l5O1HZe5WvVnjKOVjZw0+zhPPKVacyfMJS/fXyIX7+1hz+9v5+m1jZu+9wobMFBfO3pDRw6UTeQl6XcQLt3lApABWW1XPnHNSyamcWvFk5sL7/xmY3sPV7N2rsvJdRaKMY51VOE9kHm/aU1XP/XdUTaQrj/2glclJtMsIuuotM5F5h31a2kBs6gZdlUSvmmUSnRfHVWNi9uLKKgrAaAgyfqWLOvnEUzs9sDPkCELZgIW3CnWUW5qTE8f/Msmtvs3PS3Tcz57Spe7SWvUJvd8NWnNnD7S1sH56JUn2jQVypA3X5ZLpGhwfzfm3v4uOAE33txCyFBwldmZvfp+AkZsXx896U88pVpJMWE8aNXt7OrpLrb/f++/jDrCk/y720l7CjufZF5NTg06CsVoBKjw7jt0lF8sKeMrz61gZO1zfzhy1NIGRLe53PYQoK4elIaS78xg/jIUH782naXawaUVjfyu5V7mTk8gZjwEB79sGAgL0X1gwZ9pQLY4tk5fHFaJj/7/DhW/fAS/mty+hmdJy7Sxs+uGc+24iqe/eRQl+2/fGMXzW12fvPFSSw+P4e384+3dysp99Ipm0oFsPDQYB68fvKAnOuaSWn8c0sxD76zl6OnGshNjeZETRPv7S5lW3EVd84dzfCkKL554XCeXnuQRz88wB+unzIgn636ToO+UmpAiAi/unYidyz7lH9sPExjiyMB3JSsOO6ZP4ZvXjAcgIQoG4tmZrN03SHKqpsYlRLNZWNTuHBUEiJCY0sbz607xJ7jNdQ3tSECF4xKYu7YVCLDgjl8op6K+mYyrVQTthDtsOgPnbKplBpwdruh+FQDEbbg9sRwHVXWN/Obt/eSX1LF/tJaGlramD0ykasmpvHYhwc4WtlARlwEUWHB1DW1cbSyweXnBAlcOiaVH1w+mnHpQwb7snyGpmFQSnmtptY2/rHhCH/+oICKumbGDI3h3mvGc/7IRMCRerqgrJYPrPUEhiVGER8ZSvGpBvaW1rBs4xGqG1u5Ylwq8yYM5aLc5E4/NCdqm/jLBwXYjSEnMYrosBCOVNRztLKByZmxLJiSQXyU7ayuYcuRU9z6whZa7Ya4iFCumpjGnZePPqtzng0N+kopr1fT2MLOo9XMyIknJLjvXTZVDS08uaaQZZuOcKK2GYDzRySyaFY2wSL87+s7qWlsITwkmBpr8ZrgICExykZZTROhwcLVE9P4ydVjSYnp+8wlp4q6Zq5++COCRJgzOonC8jo2HKzggS9MZFEfp78ONA36Sim/Z7cbdh2r5v3dZbyypYiiCkeX0ISMITx43RRGp0ZTUddMbVMr6XERhAYHsaukmpc3F/HChiNE2oK595pxLJyS0WW9gdY2O5sOnaK5zc4FIxPbf5TsdsNNz25i/YGTvPqd2UzMjKXNbrjpbxvZUFjB8lvOZ0pWXJ/rv2JbCRnxEczoZ+bV02nQV0oFFLvdsLbgBGU1TSyYkt7pDmNXCspq+dEr29hypJJLx6Rw/7UTSIuNYO/xGp5bd4i3dx7nZJ3jr4i02HAWTs3AGNh1rJo1+8r51cIJfO28Ye3nO1XXzDV/WUtrm+GOubnMGZ1Mm93w4b5ydh+rZkpWHBePTibVuifiaGUDd7+ynbUFJwgSuOuKc/jOxSPb01XUNbVy/5u7eSf/ON+eM5IbZw8jLOSzO6Rb2uw89dFBCspqqW9u5fGvT9egr5RSPWmzG5795BC/W7mH0KAgxmcMYX1hBeGhQcwdm8pVE9MIEnhxYxFr9pcTEiSkxUYwf+JQ7pk3pstfB/klVXz7+c0Un+o8CB1pC6beymcUHxlKpC2EU/WOH5R75o9h06FT/HtbCReOSuL8kYnERYby+OoDFJ9qYEJ6LDuOVjEsMZI7547m85PSaGy1890XtrBmXzkZcRFE2oJ5765LNOgrpVRfHD5Zx//8cycHT9TxlVnZfGVmdpeB3vrmVsJDgntNHOcchF69r5zgIOHi0ckMT4pib2kNq/eWc7SygbqmNkKDhe9eMorsxEiMcfz4PLKqoH2MIjshkt9fN5mZwxNYva+c//vPbvaW1pAZH0FEaDCFJ+q4f+EEbrDGELR7RymlfFB9cyvHqxpJj4volPDObje8v6eMRz8soKC0lr98dRoXj05u366LqCillA+KtIUwIjm6S3lQkHD5uFQuH5dKa5u9X7Od3H4rm4jME5G9IlIgIve4+/OVUsqf9Cfgg5uDvogEA48A84FxwCIR6Xk1Z6WUUgPG3S39mUCBMabQGNMMLAMWuLkOSikVsNwd9DOAog7vi62ydiKyRETyRCSvvLzcrZVTSil/5+6g72p+U6fpQ8aYJ4wx040x05OTk13srpRS6ky5O+gXA1kd3mcCJW6ug1JKBSx3B/1NQK6IDBcRG3ADsMLNdVBKqYDl1nn6xphWEbkNWAkEA88YY/LdWQellApkXn1HrojUAHsH4FSxQNVpZUnAibM8x0DVxZvP0dv35GvX447z9Pff1mDVY6DOM1jnOJPvyVuux1N1cfWduTrHOcaYGJdnMMZ47QPIG6DzPHG253Z1joGqizefo7fvydeux011Oet/t152PYNyjjP5nrzlejxVF1ffWX+/20BZXPLfXnKOgTqPt5xjoM7jLecYyPOcLW+6Hm85x0Cdx9/q0q9zeHv3Tp7pJmmQN5/bn+j31H/6nfWNfk/919fvrKf9vL2l/4SPntuf6PfUf/qd9Y1+T/3X1++s2/28uqWvlFJqYHl7S18ppdQA0qCvlFIBxK+DvohcKyJGRMZ4ui7eyPpunu/wPkREykXkDU/Wy1eISK2n6+BLevu+RORDEQn4gd3Bjlt+HfSBRcBaHOke+szK+x8I6oAJIhJhvb8cOOrB+iilzjBu9ZXfBn0RiQYuAG7G+vJE5BIRWSMi/xSRXSLyuIgEWdtqReQ+EdkAnO+5mrvdW8DV1utFwIvODSIyU0Q+EZFPredzrPKPRGRKh/0+FpFJbq21l7D+Tb3R4f1fROQm6/UhEfmFiGwRkR36F2fP35fqMW5192/sKhHZIyJrReThvvyV7rdBH1gIvG2M2QdUiMg0q3wmcBcwERgJfMEqjwJ2GmNmGWPWur22nrMMuEFEwoFJwIYO2/YAc4wxU4GfAf9nlT8F3AQgIqOBMGPMdrfV2LecMMZMAx4Dfujpyiiv113c6sL6f/avwHxjzIVAn3LR+3PQX4QjoGE9L7JebzSOlbvacLRqL7TK24BX3VtFz7OCdQ6O7+fN0zbHAi+LyE7gIWC8Vf4y8HkRCQW+CTzrlsr6ptes5804vmeletJd3HJlDFBojDlovX+xh33buTXLpruISCJwKY7+aoMjo6fBEdROvzHB+b7R+iEIRCuA3wOXAIkdyn8JrDLGXCsiOcCHAMaYehF5F8dSl9cDgTz41krnxlP4adubrOc2/PT/t37q7fsKWD3ErRW4/s5cLUrVK39t6X8JeM4YM8wYk2OMyQIO4mjVz7Ty+QcBX8YxYBLongHuM8bsOK08ls8Gdm86bdtTwMPAJmNMxeBWz6sdBsaJSJiIxAKXebpCXk6/r+51F7fA9Xe2BxhhNcjAEc965a9BfxHwz9PKXgW+AqwDfg3sxPGFnr5fwDHGFBtj/uRi02+BB0TkYxytjo7HbAaqgb+5oYpeR0RCgCZjTBGwHNgOvAB86tGKeSn9vvqkp7jV5TszxjQA3wXeFpG1QCl9SNMcUGkYROQS4IfGmM97ui6+TkTScXT3jDHG2D1cHbcTkcnAk8aYmZ6uiy/Q72twiEi0MaZWRAR4BNhvjHmop2P8taWvBpGI3Ihjls//BGjAvwXHoNlPPV0XX6Df16D6lohsBfJxdMf+tbcDAqqlr5RSgc5vWvoikiUiq0Rkt4jki8jtVnmCiLwrIvut53ir/Ksist16fGL9+ek81zwR2SsiBSJyj6euSSmlBprftPRFJA1IM8ZsEZEYHPOiF+KYdVJhjPm1FcDjjTF3i8hsYLcx5pSIzAd+boyZZaVg2IcjJUExsAlYZIzZ5YnrUkqpgeQ3LX1jzDFjzBbrdQ2wG8jAMZd8qbXbUhw/BBhjPjHGnLLK1wOZ1uuZQIF1A1czjhskFrjnKpRSanD5TdDvyJq3OhXHYGOqMeYYOH4YgBQXh9yMIwcNOH4oijpsK7bKlFLK5/ndHYJWwqJXgTuMMdWOmUw97v85HEHfmY7B1QH+0QemlAp4ftXSt3LBvAq8YIxx5jwptfr7nf3+ZR32n4TjztIFxpiTVnExkNXhtJlAyWDXXSml3MFvgr51c8LTOAZn/9Bh0wpgsfV6MfC6tX82jmRYX7cy2jltAnKtVA02HOlNVwx2/ZVSyh38afbOhcBHwA7AecPQT3D06y8HsoEjwHXGmAoReQr4Io5cIACtxpjp1rmuAv6II/XAM8aY+912IUopNYj8JugrpZTqnd907yillOqdBn2llAogGvSVUiqAaNBXSqkAokFfKaUCiAZ9pXogIj8XkR/2sH2hiIxzZ52UOhsa9JU6OwsBDfrKZ+g8faVOIyL/A9yII/FeOY403VXAEsAGFABfB6YAb1jbqnDc7AeOZeuSgXrgW8aYPe6sv1I90aCvVAcici7wLDALR0LCLcDjwN+c+ZlE5FdAqTHmzyLyLPCGMeYVa9v7wC3GmP0iMgt4wBhzqfuvRCnX/C7LplJn6SLgn8aYegARceZdmmAF+zggGlh5+oFWhtfZwMsdsruGDXqNleoHDfpKdeXqz99ngYXGmG0ichNwiYt9goBKY8yUwauaUmdHB3KV6mwNcK2IRFjLbl5jlccAx6z03V/tsH+NtQ1jTDVwUESuA0fm145rLyvlDbRPX6nTdBjIPYxjfYVdQB3wI6tsBxBjjLlJRC4AngSagC/hyPD6GJAGhALLjDH3uf0ilOqGBn2llAog2r2jlFIBRIO+UkoFEA36SikVQDToK6VUANGgr5RSAUSDvlJKBRAN+kopFUA06CulVAD5//gkZ5TeVWreAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " * postgresql://covid:***@localhost/covid\n",
+      "390 rows affected.\n",
+      "Returning data to local variable res\n"
+     ]
     }
    ],
    "source": [
-    "hospital_data.newAdmissions.plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# data_by_day.newAdmissions.dropna()"
+    "%%sql res << select uk_data.date\n",
+    "    , uk_data.new_admissions, uk_data_7.new_admissions as new_admissions_7\n",
+    "    , uk_data.new_cases, uk_data_7.new_cases as new_cases_7\n",
+    "    , uk_data.new_deaths, uk_data_7.new_deaths as new_deaths_7\n",
+    "    , uk_data.hospital_cases, uk_data_7.hospital_cases as hospital_cases_7\n",
+    "    , uk_data.ventilator_beds, uk_data_7.ventilator_beds as ventilator_beds_7\n",
+    "    from uk_data left outer join uk_data_7 using (date)\n",
+    "    order by uk_data.date"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
+   "execution_count": 112,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>dateRep</th>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-17</th>\n",
+       "      <td>3725.0</td>\n",
+       "      <td>3939.0000</td>\n",
+       "      <td>28875.0</td>\n",
+       "      <td>37337.855</td>\n",
+       "      <td>671</td>\n",
+       "      <td>1217.5714</td>\n",
+       "      <td>38095.0</td>\n",
+       "      <td>38292.285</td>\n",
+       "      <td>3871.0</td>\n",
+       "      <td>3857.4285</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-18</th>\n",
+       "      <td>4054.0</td>\n",
+       "      <td>3872.8572</td>\n",
+       "      <td>44732.0</td>\n",
+       "      <td>35766.570</td>\n",
+       "      <td>599</td>\n",
+       "      <td>1223.5714</td>\n",
+       "      <td>39181.0</td>\n",
+       "      <td>38338.145</td>\n",
+       "      <td>3916.0</td>\n",
+       "      <td>3898.5715</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-19</th>\n",
+       "      <td>4132.0</td>\n",
+       "      <td>3825.8572</td>\n",
+       "      <td>39311.0</td>\n",
+       "      <td>34143.285</td>\n",
+       "      <td>1610</td>\n",
+       "      <td>1240.8572</td>\n",
+       "      <td>38765.0</td>\n",
+       "      <td>38348.430</td>\n",
+       "      <td>3947.0</td>\n",
+       "      <td>3939.5715</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
+       "      <th>2021-01-20</th>\n",
+       "      <td>4016.0</td>\n",
+       "      <td>3811.0000</td>\n",
+       "      <td>35015.0</td>\n",
+       "      <td>32707.428</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>1248.4286</td>\n",
+       "      <td>38650.0</td>\n",
+       "      <td>38294.000</td>\n",
+       "      <td>3953.0</td>\n",
+       "      <td>3969.8572</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
+       "      <th>2021-01-21</th>\n",
+       "      <td>3598.0</td>\n",
+       "      <td>3828.2000</td>\n",
+       "      <td>31430.0</td>\n",
+       "      <td>30620.428</td>\n",
+       "      <td>1290</td>\n",
+       "      <td>1239.7142</td>\n",
+       "      <td>37957.0</td>\n",
+       "      <td>38217.715</td>\n",
+       "      <td>3960.0</td>\n",
+       "      <td>3999.2856</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>3341.0</td>\n",
+       "      <td>3771.7500</td>\n",
+       "      <td>29094.0</td>\n",
+       "      <td>24870.428</td>\n",
+       "      <td>1401</td>\n",
+       "      <td>1238.7142</td>\n",
+       "      <td>38144.0</td>\n",
+       "      <td>38057.168</td>\n",
+       "      <td>4076.0</td>\n",
+       "      <td>4015.8572</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3651.6667</td>\n",
+       "      <td>20495.0</td>\n",
+       "      <td>22463.666</td>\n",
+       "      <td>1348</td>\n",
+       "      <td>1241.7142</td>\n",
+       "      <td>37266.0</td>\n",
+       "      <td>37915.600</td>\n",
+       "      <td>4066.0</td>\n",
+       "      <td>4027.3333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>14266.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>610</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>37561.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4077.0</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4482.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>592</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4032.0</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1631</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>232 rows × 6 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0\n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0\n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2021-01-17          3725.0         3939.0000    28875.0    37337.855   \n",
+       "2021-01-18          4054.0         3872.8572    44732.0    35766.570   \n",
+       "2021-01-19          4132.0         3825.8572    39311.0    34143.285   \n",
+       "2021-01-20          4016.0         3811.0000    35015.0    32707.428   \n",
+       "2021-01-21          3598.0         3828.2000    31430.0    30620.428   \n",
+       "2021-01-22          3341.0         3771.7500    29094.0    24870.428   \n",
+       "2021-01-23             NaN         3651.6667    20495.0    22463.666   \n",
+       "2021-01-24             NaN               NaN    14266.0          NaN   \n",
+       "2021-01-25             NaN               NaN     4482.0          NaN   \n",
+       "2021-01-26             NaN               NaN        NaN          NaN   \n",
+       "\n",
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2021-01-17         671     1217.5714         38095.0         38292.285   \n",
+       "2021-01-18         599     1223.5714         39181.0         38338.145   \n",
+       "2021-01-19        1610     1240.8572         38765.0         38348.430   \n",
+       "2021-01-20        1820     1248.4286         38650.0         38294.000   \n",
+       "2021-01-21        1290     1239.7142         37957.0         38217.715   \n",
+       "2021-01-22        1401     1238.7142         38144.0         38057.168   \n",
+       "2021-01-23        1348     1241.7142         37266.0         37915.600   \n",
+       "2021-01-24         610           NaN         37561.0               NaN   \n",
+       "2021-01-25         592           NaN             NaN               NaN   \n",
+       "2021-01-26        1631           NaN             NaN               NaN   \n",
        "\n",
-       "[232 rows x 6 columns]"
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2021-01-17           3871.0          3857.4285  \n",
+       "2021-01-18           3916.0          3898.5715  \n",
+       "2021-01-19           3947.0          3939.5715  \n",
+       "2021-01-20           3953.0          3969.8572  \n",
+       "2021-01-21           3960.0          3999.2856  \n",
+       "2021-01-22           4076.0          4015.8572  \n",
+       "2021-01-23           4066.0          4027.3333  \n",
+       "2021-01-24           4077.0                NaN  \n",
+       "2021-01-25           4032.0                NaN  \n",
+       "2021-01-26              NaN                NaN  "
       ]
      },
-     "execution_count": 9,
+     "execution_count": 112,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data_by_day = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
-    "data_by_day"
+    "hospital_data = res.DataFrame()\n",
+    "hospital_data['date'] = hospital_data.date.astype('datetime64[ns]')\n",
+    "hospital_data.set_index('date', inplace=True)\n",
+    "hospital_data.tail(10)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 113,
    "metadata": {},
    "outputs": [
     {
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
+       "      <th>new_admissions</th>\n",
+       "      <th>new_admissions_7</th>\n",
+       "      <th>new_cases</th>\n",
+       "      <th>new_cases_7</th>\n",
+       "      <th>new_deaths</th>\n",
+       "      <th>new_deaths_7</th>\n",
+       "      <th>hospital_cases</th>\n",
+       "      <th>hospital_cases_7</th>\n",
+       "      <th>ventilator_beds</th>\n",
+       "      <th>ventilator_beds_7</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>dateRep</th>\n",
+       "      <th>date</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
+       "      <th>2020-01-03</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-04</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-05</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-06</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-01-07</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-22</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-23</th>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-24</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-25</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01-26</th>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>232 rows × 6 columns</p>\n",
+       "<p>390 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff\n",
-       "dateRep                                                                    \n",
-       "2019-12-31      0       0           0            0         NaN          NaN\n",
-       "2020-01-01      0       0           0            0         0.0          0.0\n",
-       "2020-01-02      0       0           0            0         0.0          0.0\n",
-       "2020-01-03      0       0           0            0         0.0          0.0\n",
-       "2020-01-04      0       0           0            0         0.0          0.0\n",
-       "...           ...     ...         ...          ...         ...          ...\n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0\n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0\n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0\n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0\n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0\n",
+       "            new_admissions  new_admissions_7  new_cases  new_cases_7  \\\n",
+       "date                                                                   \n",
+       "2020-01-03           False             False      False        False   \n",
+       "2020-01-04           False             False      False        False   \n",
+       "2020-01-05           False             False      False        False   \n",
+       "2020-01-06           False             False      False        False   \n",
+       "2020-01-07           False             False      False        False   \n",
+       "...                    ...               ...        ...          ...   \n",
+       "2021-01-22            True              True       True         True   \n",
+       "2021-01-23           False              True       True         True   \n",
+       "2021-01-24           False             False       True        False   \n",
+       "2021-01-25           False             False       True        False   \n",
+       "2021-01-26           False             False      False        False   \n",
        "\n",
-       "[232 rows x 6 columns]"
+       "            new_deaths  new_deaths_7  hospital_cases  hospital_cases_7  \\\n",
+       "date                                                                     \n",
+       "2020-01-03        True         False           False             False   \n",
+       "2020-01-04        True         False           False             False   \n",
+       "2020-01-05        True         False           False             False   \n",
+       "2020-01-06        True          True           False             False   \n",
+       "2020-01-07        True          True           False             False   \n",
+       "...                ...           ...             ...               ...   \n",
+       "2021-01-22        True          True            True              True   \n",
+       "2021-01-23        True          True            True              True   \n",
+       "2021-01-24        True         False            True             False   \n",
+       "2021-01-25        True         False           False             False   \n",
+       "2021-01-26        True         False           False             False   \n",
+       "\n",
+       "            ventilator_beds  ventilator_beds_7  \n",
+       "date                                            \n",
+       "2020-01-03            False              False  \n",
+       "2020-01-04            False              False  \n",
+       "2020-01-05            False              False  \n",
+       "2020-01-06            False              False  \n",
+       "2020-01-07            False              False  \n",
+       "...                     ...                ...  \n",
+       "2021-01-22             True               True  \n",
+       "2021-01-23             True               True  \n",
+       "2021-01-24             True              False  \n",
+       "2021-01-25             True              False  \n",
+       "2021-01-26            False              False  \n",
+       "\n",
+       "[390 rows x 10 columns]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 113,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data_by_day.loc['2020-07-03', 'cases'] = 576\n",
-    "data_by_day"
+    "hospital_data == hd2"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 114,
+   "metadata": {
+    "Collapsed": "false"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "new_admissions       float64\n",
+       "new_admissions_7     float64\n",
+       "new_cases            float64\n",
+       "new_cases_7          float64\n",
+       "new_deaths             int64\n",
+       "new_deaths_7         float64\n",
+       "hospital_cases       float64\n",
+       "hospital_cases_7     float64\n",
+       "ventilator_beds      float64\n",
+       "ventilator_beds_7    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "data_by_day = data_by_day.merge(hospital_data[['newAdmissions', 'cumAdmissions']], how='outer',\n",
-    "    left_index=True, right_index=True)"
+    "hospital_data.dtypes"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 115,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "new_admissions       float64\n",
+       "new_admissions_7     float64\n",
+       "new_cases            float64\n",
+       "new_cases_7          float64\n",
+       "new_deaths             int64\n",
+       "new_deaths_7         float64\n",
+       "hospital_cases       float64\n",
+       "hospital_cases_7     float64\n",
+       "ventilator_beds      float64\n",
+       "ventilator_beds_7    float64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 115,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "data_by_day['deaths_m7'] = data_by_day.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_by_day['cases_m7'] = data_by_day.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "data_by_day['admissions_m7'] = data_by_day.newAdmissions.transform(lambda x: x.rolling(7, 1).mean())"
+    "hd2.dtypes"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "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>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
-       "2019-12-31      0       0           0            0         NaN          NaN   \n",
-       "2020-01-01      0       0           0            0         0.0          0.0   \n",
-       "2020-01-02      0       0           0            0         0.0          0.0   \n",
-       "2020-01-03      0       0           0            0         0.0          0.0   \n",
-       "2020-01-04      0       0           0            0         0.0          0.0   \n",
-       "...           ...     ...         ...          ...         ...          ...   \n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0   \n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0   \n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0   \n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0   \n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0   \n",
-       "\n",
-       "            newAdmissions  cumAdmissions   deaths_m7     cases_m7  \\\n",
-       "2019-12-31            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-01            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-02            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-03            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-04            NaN            NaN    0.000000     0.000000   \n",
-       "...                   ...            ...         ...          ...   \n",
-       "2020-08-14            NaN            NaN -723.714286   970.428571   \n",
-       "2020-08-15            NaN            NaN -736.285714  1051.714286   \n",
-       "2020-08-16            NaN            NaN -743.571429  1097.285714   \n",
-       "2020-08-17            NaN            NaN -744.000000  1094.142857   \n",
-       "2020-08-18            NaN            NaN -736.714286  1079.428571   \n",
-       "\n",
-       "            admissions_m7  \n",
-       "2019-12-31            NaN  \n",
-       "2020-01-01            NaN  \n",
-       "2020-01-02            NaN  \n",
-       "2020-01-03            NaN  \n",
-       "2020-01-04            NaN  \n",
-       "...                   ...  \n",
-       "2020-08-14            NaN  \n",
-       "2020-08-15            NaN  \n",
-       "2020-08-16            NaN  \n",
-       "2020-08-17            NaN  \n",
-       "2020-08-18            NaN  \n",
-       "\n",
-       "[232 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "cases               687.000000\n",
-       "deaths               43.000000\n",
-       "cases_culm       277855.000000\n",
-       "deaths_culm       42741.000000\n",
-       "cases_diff         -299.000000\n",
-       "deaths_diff         -87.000000\n",
-       "newAdmissions       347.000000\n",
-       "cumAdmissions    125307.000000\n",
-       "deaths_m7           134.428571\n",
-       "cases_m7            954.285714\n",
-       "admissions_m7       353.714286\n",
-       "Name: 2020-06-22 00:00:00, dtype: float64"
-      ]
-     },
-     "execution_count": 14,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day.loc['2020-06-22']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
+   "execution_count": 116,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01f6713410>"
+       "<AxesSubplot:xlabel='date'>"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 116,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAESCAYAAAAR2wXeAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAABH80lEQVR4nO3dd3gcxfnA8e97Rb1akpvkhnuv2Abjgmmm2gaSQAgBEyAQEwJJfqGmESCE0AKhBBMMJJTQezPGxgYbjHuTe5UtW7J6l+5ufn/sSpZkySqW7nTS+3keP7qb292Z1Z1fzc3OviPGGJRSSnUMjkA3QCmllP9o0FdKqQ5Eg75SSnUgGvSVUqoD0aCvlFIdiAZ9pZTqQFyBbkBDEhMTTe/evQPdDKWUCiqrVq06YoxJql3e5oN+7969WblyZaCboZRSQUVE9tZVrsM7SinVgWjQV0qpDkSDvlJKdSBtfky/LhUVFaSlpVFaWhropqgACAsLIyUlBbfbHeimKBV0gjLop6WlER0dTe/evRGRQDdH+ZExhqysLNLS0ujTp0+gm6NU0AnK4Z3S0lISEhI04HdAIkJCQoJ+y1OqmYIy6AMa8Dswfe9VR+P1tVwK/KAN+kop1REs2pJB3zs/ZuuhghY5ngb9dmDatGlNuoFt5cqV3HzzzU2u57zzziM3N7fJ+ymlmu+jDekArNuf2yLHC8oLuerEjBs3jnHjxjV5v48//rgVWqOUOp4Krw8Al7NlhjWDPuj/+YNNbD6Y36LHHNI9hj9eOPS42+zZs4dzzz2X0047jWXLlpGcnMx7773HwYMHmTt3LpmZmURERDBv3jz69+9P//792blzJ3l5eXTq1InFixczZcoUJk+ezPz58+nXr98xdaxYsYJbbrmFkpISwsPDmT9/PgMHDqSkpIQ5c+awefNmBg8eTElJSdU+UVFRzJ07ly+++IL4+Hjuv/9+fve737Fv3z4ee+wxLrroIhYvXsxDDz3Ehx9+yFdffcWvfvUrwBorX7JkCYWFhfzoRz8iPz8fj8fD008/zeTJk6tSYiQmJvLII4/w/PPPA3Dttddyyy231Ps7CQ8P5/HHH+eZZ57B5XIxZMgQXnvttRZ8x5RqvzwtOJ4POrxzQrZv387cuXPZtGkTcXFxvPXWW1x//fU88cQTrFq1ioceeohf/OIXOJ1OBgwYwObNm/n6668ZO3YsS5cupaysjLS0tDoDPsCgQYNYsmQJa9as4Z577uHOO+8E4OmnnyYiIoL169dz1113sWrVqqp9ioqKmDZtGqtWrSI6Opq7776bBQsW8M477/CHP/zhmDoeeughnnzySdauXcvSpUsJDw/nlVde4ZxzzmHt2rWsW7eOUaNG1dhn1apVzJ8/n++++45vv/2WefPmsWbNmnp/JwAPPPAAa9asYf369TzzzDMt8etXqkPw2D39ojJPixwv6Hv6DfXIW1OfPn2qAuLYsWPZs2cPy5Yt4wc/+EHVNmVlZQBMnjyZJUuWsHv3bu644w7mzZvH1KlTOfnkk+s9fl5eHldddRXbt29HRKioqABgyZIlVWPyI0aMYMSIEVX7hISEMGPGDACGDx9OaGgobreb4cOHs2fPnmPqmDRpEr/+9a+54ooruPjii0lJSeHkk0/mmmuuoaKiglmzZh0T9L/++mtmz55NZGQkABdffDFLly7loosuqvN3UtnOK664glmzZjFr1qxG/X6VUlDhtXr6BS0U9LWnfwJCQ0OrHjudTrKzs4mLi2Pt2rVV/1JTUwEr6C9dupQVK1ZUXRCtHOKpz+9//3tOP/10Nm7cyAcffFBjbnp90xbdbnfVaw6Ho6qNDocDj+fYD83tt9/Oc889R0lJCRMnTmTLli1MmTKFJUuWkJyczJVXXslLL71UYx9j6v+6Wft3UlnnRx99xNy5c1m1ahVjx46tsy1KqWMVl1v/VwpKNei3OTExMfTp04c33ngDsILjunXrAJgwYQLLli3D4XAQFhbGqFGj+Ne//sXkyZPrPV5eXh7JyckAvPDCC1XlU6ZM4eWXXwZg48aNrF+/vtlt3rlzJ8OHD+e2225j3LhxbNmyhb1799K5c2euu+46fvazn7F69eoa+0yZMoV3332X4uJiioqKeOedd457Hj6fj/3793P66afz4IMPkpubS2FhYbPbrFR7Vebxsi+ruEZZbrH1Db9Qg37b9PLLL/Pvf/+bkSNHMnToUN577z3A6gH36NGDiRMnAlbPv6CggOHDh9d7rN/97nfccccdTJo0Ca/XW1V+4403UlhYyIgRI3jwwQcZP358s9v72GOPMWzYMEaOHEl4eDjnnnsuixcvZtSoUYwePZq33nqr6kJvpTFjxnD11Vczfvx4JkyYwLXXXsvo0aPrrcPr9fKTn/yE4cOHM3r0aG699Vbi4uKa3Wal2qs/f7CZKX9fRF5JRVVZdlE5AIUtNLwjx/uq3haMGzfO1J6DnpqayuDBgwPUItUW6GdAtUdnPfIV2zMKeevGUxjbqxPGGAbe/SnlXh9nDu7Cc1c1fqq1iKwyxhyzg/b0lVKqjegaGwbAFvvu2+JyL+X27J2C0op692uKoJ+90x7Mnz+ff/zjHzXKJk2axJNPPhmgFimlAiEixAnAlnQr6FcO7UDLDe9o0G8D5syZw5w5cwLdDKVUgFWO5Vfm2cm3e/ehLkeLBX0d3lFKqTaicqbOriNFABSVWRM4usaG6ewdpZRqb/Ltnn5+SQXGmKq7cLvGhLXYzVk6vKOUUm1Erh30y70+fPPPp48jBbiIrrFhlO/2UebxEupynlAdGvSVUqoNKPf4KC73khwXjjtvF85939Ab+JEzhqT46wA4UlhOclz4CdWjwzvtQHvKp//3v/+dUaNGMWrUKIYNG1aV3kKp9q7yIm6PTuFMd6wFoCCsO3e5XmZknJVJNy27uL7dG02Dfgc0btw4Hn/88Sbv9/HHH7f6nbT/93//V5W36K9//StTp06lU6dOrVqnUm1BXok1PbNXp0jOdKyiJLYfbw99gghKGZf+CgD7c0qOd4hGCf7hnU9uh0MbWvaYXYfDuQ8cdxPNp9/6+fRfffVVLr/88qa8c0oFrcqZO4OjCpjoSGV51M9Ykd+JJDOec1NfJVpOJi3naE9/zb4cZj+1jC9/M5WTkqIaXY/29E+A5tNvvXz6xcXFfPrpp1xyySWNei+UCnaVwzsT8r/AIYY7dw3how3pvOyajZQVcE/46+zPPtrBe/6bPQB8tS2zSfUEf0+/gR55a9J8+q2XT/+DDz5g0qRJOrSjOoyMgjJCKaffnv+yzDuEvaYrAPvDBsKoXzJ72eNsTp8CjATgUJ71B+BwflmT6ml0T19EnCKyRkQ+tJ93EpEFIrLd/hlfbds7RGSHiGwVkXOqlY8VkQ32a49LfUnhg4Tm02/4d9LcfPqvvfaaDu2oDiU9r5SLnV/jLs7gce/FVeWRoS44/S7SQ/twXc6jUF5MaYWXdWl5AGw7XNCkepoyvPMrILXa89uBhcaY/sBC+zkiMgS4DBgKzACeEpHKiaVPA9cD/e1/M5rU2jZO8+nXran59PPy8vjqq6+YOXNms89LqWBzKK+EKaHbILob3/qGVJVHh7rAHcbnfW6jM1nw7VOk5ZRQ7rESsbVK0BeRFOB84LlqxTOBF+3HLwKzqpW/ZowpM8bsBnYA40WkGxBjjFlurK7iS9X2aTc0n/6xmppP/5133uHss8+uGj5SqiNIzytlhOyA5LE1yp0O65t7dsJYFnlHYr7/N/kl1pDO2F7xpOWUVK2u1RiNyqcvIm8CfwWigd8aYy4QkVxjTFy1bXKMMfEi8k/gW2PMf+3yfwOfAHuAB4wxZ9rlk4HbjDEXHK9uzaev6qKfAdXezHr4I94t+DGc8Qd6fzSoqnxkSizv3XQa85bsYvOnz/JoyNOsPvstLn6/jB+OS+H1lWl8c/v0Y27aanY+fRG5AMgwxqxqaNvKXeooM8cpr6vO60VkpYiszMxs2pVppZQKRkn5m60H3cdwUuLRb7lF5da3/MhQFwt9ozEOF7G7PgCsnDwAxU3Iy9OY2TuTgItE5DwgDIgRkf8Ch0WkmzEm3R66ybC3TwN6VNs/BThol6fUUX4MY8yzwLNg9fQbfTZBqiPm0++I56xUfQpKKxjg2QZuoPtoFvw6ltT0fC544uuqpGuRoU7yiaKw30X03v5fhsgAusQOA47+YWiMBoO+MeYO4A4AEZmGNbzzExH5O3AV8ID98z17l/eBV0TkEaA71gXbFcYYr4gUiMhE4Dvgp8ATjW5pO9YR8+l3xHNWqj6H8koZ5dhJQVQfosPjcALd7FW0KuyVs6JCrXD9fvdfcfGOz5nj/JSE2EuBlu/p1+cB4HUR+RmwD/gBgDFmk4i8DmwGPMBcY0zln6EbgReAcKxx/k+aW7kxpt5pi6p9a+vrOivVVNmFZYx07KQkaRrRdlmnyBCuPrU3F4+xZvBFhFjh+q5PDxDtHs7pzrUcjHQDLdzTr84YsxhYbD/OAs6oZ7v7gPvqKF8JDGtKnXUJCwsjKyuLhIQEDfwdjDGGrKwswsLCAt0UpVpMSXYanSWXg12PzoITEf500dCq55U9fYCF3tFc5FxOad4mgCbN3gnKO3JTUlJIS0tDL/J2TGFhYaSkpDS8oVJBwmTtAsDVZVC920SGHs2jv9g3ijLcxG9/CziraoWtxgjKoO92u+nTp0+gm6GUUi3CV3AIgMjE+jsz1Xv6eUSx1H0aZ6S+zoWOSPrsWAMT7m5UXZpwTSmlAkwKraAfkZBc7zaRoTX76G+GzASvhydC/skp2/8O2bsbVZcGfaWUCjB3cQalhCBhcfVuE+6uuUziBm8v5NoFvOmbZhVsfKtRdWnQV0qpAAsrzSBbOsFxJqY4HDVfK6nwQreR3O++ib2Rw2HLR42qS4O+UkoFWET5EfJcTUsjXjljJyLEye7QQZCRCj5fg/tp0FdKqQCLqcii0J3YpH1GpMQBEBniYp+zB3hKIG9fg/sF5ewdpZRqT+J92ewOndjo7d+bO4nedn6eiFAneyoz32Rug/jex91Xe/pKKRVIZYVEUUxZeFKjdxnZI47YcOtu3MgQFzt83a0XMrc0uK/29JVSKoA8OftwARXRDd9w+NeLh1NYWvPu24gQJ/sKIyCyM2RubfAYGvSVUiqAig7vJhYgrkdDm3L5+J7HlEWGuigu98K4qyC6W4PH0KCvlFIBVJK5i1ggNKF3s/aPCHFaM3mm6x25SinV5lVk7aPMuIhOrP9u3OOJCnORX+JpdPZZDfrtyLwlu+h9+0eUNCHNqlIqsCRvHwdMIkkx4Q1vXIf4iBDKvT5riKcRNOi3Iy8s2wNAZkFZYBuilGo0d2EaB0wiiVEhzdq/U4S1X05xeaO216DfjkSEWLk5Cpuwio5SKrCiig+QLp1rZNFsirgIa+pmTlFFo7bXoN+ORNgfmvzSxr35SqkAK8kh0pNDRkiPZi8I1SlSe/odVoSdhS+3WIO+UkEhcxsAORG9m32IOB3e6bgqh3fyShr35iulAuyIdTNVcUy/Zh+iqqdf1Lj/9zpPvx0JC9GevlLBxGRuoxw3jk7H3nTVWLHhbkQgu5H/7zXotyMhTuuLW16JBn2lgkF+2iYO+rox/qTG592pzekQYsPd5OrwTsdT7rFyaedq0FcqOGSkstMkM3VA84M+WHP1sxs5vKNBvx0ps4N+ng7vKNX2lRUQW5ZObnT/qouxzRUf4W70sK4G/Xak3FvZ09cLuUq1eRlWGuTcqOZfxK3UlJ6+jum3IxWVwzva01eq7cvYDEBW5IkH/VvOHICnEUslggb9dqWqp69BX6k2raTcS/HudUQQSmlk8xKtVTc8JbbR2+rwTjtSeSFX78hVqm2b9tAiUtd9y3aTQlio2691a9BvRyqDfmFZ49OsKqX869tdWRzOL2OgYz9bvCmE23fS+4sG/XakcnjHGBqdZlUp5V+r9uaQQB5Jks9W06PqTnp/0aDfDvh8hnlLdtXIvaGZNpVqm7YfLmCAIw2AraYH4SH+vbSqQb8dWLQ1g/s+TiW3uIJIu9dQUKpBX6m2aHtGIQPFDvq+FO3pq6ar8B4dv0+ICgWgwL6YezC3hDnzVzT6Fm2lVOvx+gw7MgqZEHOEPBNBJnEa9FXThbqOvo2VGfc8R3ZAURZ//2wri7Zm8tmmQ4FqnlLKdiCnhDKPj0GuQ+wy3QHRC7mq6ZyOo4svdImA7hzh5PfPhP/M4kihLp2oVFtxILcEgC4VaewyXQGI0DF91VQV3qN34s3Jf5plYTdbTw6tJ8teL/dQngZ/pQItt7icCEqJKD3MLl93AMLb2vCOiISJyAoRWScim0Tkz3Z5JxFZICLb7Z/x1fa5Q0R2iMhWETmnWvlYEdlgv/a4NHd9MFVD5fx8Fx4m5nxQ4zXPkR0AHMov9Xu7lFI1ZReX00esodZdphtAmxzeKQOmG2NGAqOAGSIyEbgdWGiM6Q8stJ8jIkOAy4ChwAzgKRGpPKungeuB/va/GS13Kh1X5fz8iY5UAG4s/xWvjv4vAKOMld/jUF5JYBqnlKqSW1xBH0kH4IDT6um3uQu5xlJoP3Xb/wwwE3jRLn8RmGU/ngm8ZowpM8bsBnYA40WkGxBjjFlurNtFX6q2jzoBlSmVT3VswiculjvHsdvVl/KQeMY7tpIYFcqhfB3eUSrQsovK6e3KAiAvxOrpt7mgDyAiThFZC2QAC4wx3wFdjDHpAPbPzvbmycD+arun2WXJ9uPa5eoEVQb9obKHvOi+uMMiKCjzcCBmFCfLFk7pm8BhHd5RKuByisvp7c6F0FgkLAZog2P6AMYYrzFmFJCC1WsfdpzN6xqnN8cpP/YAIteLyEoRWZmZmdmYJnZo1pi+YYhjD/mxg4kOdVFQ6mGTawi9HBmMji0hu6ic0gpNzaBUIOUUlZPiyILYZCJDrVk7bXr2jjEmF1iMNRZ/2B6ywf6ZYW+WBvSotlsKcNAuT6mjvK56njXGjDPGjEtKOrFlxDqCco+PzuSSJPkUxg8hKsxFYZmHbyoGADCgfCOgKZeVCrSc4gq6kgWxKUSFughxOWpMufaHxszeSRKROPtxOHAmsAV4H7jK3uwq4D378fvAZSISKiJ9sC7YrrCHgApEZKI9a+en1fZRJ6Dc42OoYw8AxQlDiYsI4btd2bx+oBNljnCS81YDR+/SVUoFRk5xOYm+DIhJJirU5ffxfGhcT78bsEhE1gPfY43pfwg8AJwlItuBs+znGGM2Aa8Dm4FPgbnGmMpxhRuB57Au7u4EPmnBc+mwyr1ehsoeAEoSBvPHC4dwztAuRISGkpswmqRsO+hrEjalAqqkqIAobz7EphAT7ibSz0M70IiVs4wx64HRdZRnAWfUs899wH11lK8Ejnc9QDVDucfHGMcedvu6UCqR9E2K4rHL7Lfsq3WYRfcTQ6EmYVMqgDxeH1FlhyEUiE3hhgF9mTmqu9/bocsltgNlHh9DZQ/rzUngrbVOZo/xCIYRjt06vKNUAOWVVNBLDltP4nszsGs0A7tG+70dmoahHXCU5dHTkclmX2+k9iSpzkMBGCBp2tNXKoAKSj0MsFMqkzQwYO3QoN8OxBbvA2DQiPGcM7RLzRejkvBFJDJA9mtPX6kAKij10N9xgNKwJAiPb3iHVqJBvx0ILz8CwEWnjcHlPPYtlaRBDHRoT1+pQCooq6CfpFEa1z+g7dCg3w5E2kGf6K51vi5dhjDAkUZBifb0lQqUgpJy+ssBPAmBG9oBDfrtQlR5Fj4EIuu5ka3zYCIpxVVwwL8NU0pV8eYeIFLKkMQBAW2HBv12INqTRYEjBpzuujdIGgxATOEOP7ZKKVWdI2c3AO6kvoFtR0BrVy0ixpNNrjOh/g06DwIgsWinn1qklKrNXWBNuAjt0i+g7dCg3w7EebPId3aqf4PweLKdiXQt2+W/Rimlaggr2EeFcRLaqVdA26FBvx2I9+VQ6D5OTx84HNqHZM9eP7VIKVVbVHEahyQJnIG9J1aDfrDz+YgzuQ0G/ayIk+jpSwOf77jbKaVaR1xZGunOumfY+ZMG/WBXkoMbD0UhicfdrDTuJMIppyx7n58appSqYgyJ5Qc44vJ/rp3aNOgHu0JrkeWS0OP39B32bd95+za1epOUUrUUpBPpK+RQWJ9At0SDftArsIJ+aejxF5uJSrambRYeTG31JimlajlsdbaORAR25g5o0A9+hdaCZWXhxw/6nbukkGciMJnb/NEqpVR1dtDPjwnsjVmgQT/oGbunXxF2/KDfNS6cnaY7Ibk6V18pv8vYzCEScEUGLtFaJQ36Qc5XcIhCE4aERh13uzC3k0PO7kQV7/dTy5RSlczhjaR6U4gOC/wSJhr0g5w3L50ME0dkaMMfpoKw7sRWZIJXE68p1dq+2HyY3rd/RG5+AWRuZZPpTVQj/p+2Ng36Qc5XcIhM4ogJqyfvTjUlkSk48EFemh9aplTH9rdPtwBwcMc6xOdhs68X0Y34f9raNOgHOSnMIMPEERveiKAflWI9yNW5+kq1tuyicgBM+gYAUk0vHd5RJ8gYXEXpHDKdiI1oOOhXRPWwHuRqOgalWlt2sRX0nRkb8boi2Gu6EKVBX52QoiM4vaWkmaRGDe8Qm4zHOPBm72n1pinVkeWVVGCM9TgqZzOFcQPx4SBGg746IfYwzQGT2KjhneiIMNJNAp4s7ekr1Zp2ZBTYjwwJhdvIibbuiI8K1TF9dSLyrKCfZpIaFfRjw92kmSRMzp5WbphSHVt6XikAPeQI4b5CMiKtm7J0TF+dGLunn+HoTJi74bcyNtzNfpOEM18v5CrVmjLyywA4NzETgINh1mLoGvTVicndT4kzCkd4DCLS4OYxdk/fXZwBFaV+aKBSHVNGQRkhTgcnh+7Di4N9zl6IQGSIBn11IvL2k+XqQkwjhnbgaE+/cl+lVOvIKCglKTqUYSUrWefrS1a5k6gQFw5Hw52z1qZBP4h58w9x2Ne4OfpQK+jn6MVcpVpLZkEZfSNL6VqUyiLvSPZlF7eJ6ZqgQT+oHc44xL7SsEbf2h0TZg3vADpXX6lWdDi/lLNkBYLhK99IdmYWtYnxfIC20QrVLFHefHJNFKnp+Y3aPsztIMeZQIWE4s7a0cqtU6qDKs7mz3l3cwrrKUocwfq0kyC7mLG9Ap9hE7SnH7y8HmKkmFwTxZ3nDW7ULiJCdHgoaeEDKd39LT6faeVGKtXxeD+4hVNYD0DR5LsBaxy/rfT0NegHq9I8AAaf1IuLx6Q0ereEyBBWevoih9bz5neaW1+plrIrs5DN23fiTH2Pf3pm8uZ5a4gdembV6/2Sjp/+3F806Aep8sIj1oOITk3ab2j3GL4o7EWoeNi5YVkrtEypjmn6w1/x1Pz5ACzwjqVPl3hCXc6q14d0jwlU02rQoB+kivOsmz6ckU0L+sNTYlnts+4ODDuwHI/X1+JtU6qjySywbsY61bGRMlcUG8xJ9E2KrLHN4G4a9FUzvbkqjVtfWAyAO6ppQX9ESiyZxLHZ14tTzBo2HWzcRWClVP0WbckADFOd69kWPopOUWHERYTU2KZvsAzviEgPEVkkIqkisklEfmWXdxKRBSKy3f4ZX22fO0Rkh4hsFZFzqpWPFZEN9muPS2NuI1XHeOCTLcRjJXQKi05s0r5DusUS4nKwM3YiY2UbmUcyWqOJSnUoq/flMFp2kCxZvFc2lpOqBfibTu/HKSclEOJqG33sxrTCA/zGGDMYmAjMFZEhwO3AQmNMf2Ch/Rz7tcuAocAM4CkRqRzYehq4Huhv/5vRgufSYcRFuImTIgDCYo+/IHpt4SFO3r7xVMac+UPc4sW9Z0lrNFGpDmVXZhHnOb+jzLj4X/5w+nU+GvR/e85AXr1+YgBbV1ODQd8Yk26MWW0/LgBSgWRgJvCivdmLwCz78UzgNWNMmTFmN7ADGC8i3YAYY8xyY4wBXqq2j2qCuHA3sVKIzwhRsU0b3gEYlhxL1yFTKDDheLd/zt8+3YIxOn1TqebanZnPRe4VLPUNp4CINjOUU5cmfd8Qkd7AaOA7oIsxJh2sPwxAZ3uzZKB6Ypc0uyzZfly7XDVRTLibeArJI5KYWuOGjeV0h7DCMZLBRd/z9OIdrNyb08KtVKpjyCupoEfxZrqYI3zktXr0tS/itiWNDvoiEgW8BdxijDne1b+6xunNccrrqut6EVkpIiszMzMb28QOo9zjo58cIK2Ri6fUZ334eLpJNoNkPy8s29NyDVQqQJ5YuJ2r56/wa50rdmdzufNLvA43X/jGAm3nom1dGhX0RcSNFfBfNsa8bRcftodssH9WXhFMA3pU2z0FOGiXp9RRfgxjzLPGmHHGmHFJSU0bs+4IiktLGe3YwUrfwBrzgJtqT9wpAExzrGWzzuJR7cDDC7axeGsmaTnFfqlv44E8HvvPG1ziXEr+8DmUOaMIcztIjgv3S/3N0ZjZOwL8G0g1xjxS7aX3gavsx1cB71Urv0xEQkWkD9YF2xX2EFCBiEy0j/nTavuoJuhavI1wKed738ATOk5RaBKpvp5Mc66joLSihVqnVGBUvy716cZDfqlzx+EC/uh+iWJ3LHEz7iQhKoSTEqPaRArl+jSmpz8JuBKYLiJr7X/nAQ8AZ4nIduAs+znGmE3A68Bm4FNgrjHGax/rRuA5rIu7O4FPWvJkOopBZVZej1//7MoTOk5hmYcvfaM42bEVZ2l2SzRNqYDJLCyrerxsZ5Zf6nTv+4rxjq24zrgbCY/nlJMSOH1Q2x6daDADkDHma+oejwc4o5597gPuq6N8JTCsKQ1Ux5rqWU56xAD69R1wQsdJiAzlI+9E5rreZ7r5jjLPpSc0XKRUIO3MKKp6nFVU7pc6U/Z/QL6JIHqc1QF75Eej/FLviWgbdwuoRvNl7WakbGdH57NP+Fj3zhrGT2ddQF5Eby50LKew1NMCLVQqMHYdKQRgXK94cov9EPQrShiQ8xVL3acg7rDWr6+FaNAPMuXbvgAgvduZDWzZsPjIEC6b0IsDKecx0ZFKcdaBEz6mUoGy+WA+UaEuBneLIccfPf2NbxHuK2ZF9Il3wPxJg36Q8R1YTbaJwht/UosdM6fPBTjE4EzV6+oqeK3Ync3YXvHER4aQX+pp3WSCPi+e5c+wS3pyJOHk1qunFWjQDzLO9DVs8J1EZFjz5+fX5ug8iM2+XsRse7PFjqmUP2UVlrE9o4CLEg4wNu9zZjhWkJ9lzeDx+Qwr92Tz3toT+yabV1LBF5sPY4zBt+gBXBkbeKLsfJJigmdoB3S5xOBSXkxI9jbWmQsZ3sh1cRsjOszF696p/Cn7JTi0AboOb7FjK+UPK3Znc7PzHS5ZY3VcpoZAxX/e4pupL3HFm+lV2104onuzp1POW7KLfy7awb1ndOLHyx/lHe8k3vGdxpy2OzuzTtrTDyZpKxDjZZ2vL1EtuPRaTJibd72T8DrcfPvOk2w9VNBix1bKH7ZtWc9NrnfxDZ7JivM+4ary23CU5tL9i1/g4ugEhT1ZRcc5yvEdyC0BoOirJ/B5vTzs+QEgTOnftqdo1qZBP5hsfg+PM5xvfMOIDGnZnn4u0WwLG0lS+mLOeWwJeSV6s5YKHv22Pw8iOM79G6HdhvCVbySbx95Dn9JU5jg/rdpu4wnceb4rs5DJKU6ucn/Jh76JpJnObPnLDE4f1LnhndsQDfrBwueF1A9I7zyFUkKJDG25+fSV3xreLhxGX0c6PeUwK3brzVoqOORlZzK97Eu2dzkXYroRbych3JJ4FksYwy3ut5nbJx23U9h4IK9ZdRhj2JFRyFUhiwgzJTzjuQiAMHfw3deiQT9YFB6GokwOxo0DrLz4LcXtdBDudvJ5xQgATnes5VB+aYsdX6mW9uv/rWXGY9ZaEFlL5xEu5ZSP+zkAcZHWJIeNB/K4vfRqPJFd+b/Dt/OjTjubnWMqPa+UonIvYwq+hB4TyYnuz8WjgzNJsAb9YFF4GIBcp5U/vyWHdwBKKrzsNV3JDO3BGc41HM7ToK/arrfXHGDLoQLKysvonPoSy71D6D7Q6hBFh7pwOYQ3V6VxkEQyf/QRJA7gzqK/Up65s1n17cosoo+k06lgGwydxbd3nBEUd9/WRYN+sCi0kphmO6xVKcNb6Wtl2OBzmeBIJTtX8+urtu/At28TVZrOK5xL5+hQAESEkT3iKCr3khIfTr+eKXD5KzjEwd0lf6es9GgGzrziCvZnN5yR82BeCZc7v8QgMPhCgnmlVw36wcIO+lnEEeZ2tHgWv2evHMsr104gesQFhFJBl4yvW/T4SrWU0orK/I2GiNXzOOLsws5Ok2sE4jvPGwzA7MohmPjerBl9HyMcuyj59M9V2533+FImP7iowTqLD+/iKudneEdcDrEpDW7flmnQDxb28E6miSWihYd2AM4e2pVT+yVCr0nkOTsxLu/zFq9Dqea4ev4Knli4HbButKq8GHuxYyldc1fxqvMieiXF1NhnbK94Pr91Cr+c3r+qLGT4hbzimU7MunmkrlrCuHu/qJqG6fUdf7nQUTuexIjgOuPuljy1gNCgHywKMyA0lgKPq9WGdgBwutiYcA7jPSuhUFctU4FV7vGxeGsmDy/YBsDz3+zm0meWkyKZ/Nn9IpvcQ3micBq9E49dnnBAl2hCXEdDXK+ESB7wXEZJSALJn1+Ht9rnO6taWuZjHNrIqJzPeC90JsQG58Xb6jToB4vCwxDVmeJyb4tO16zL3l6X4MZL1uIn2ZtVRJnHy8wnv+G/3+5t1XqVqrTnSBEPf76VLYdqzrbZtOprLnIs4yX3X3E6YG7xzyn3CX0SGl6TNiEyBBMax0u97iOyLIObXe9UvZZRcJyg/9XfKJIIFiX9uNnn05ZoGoZgUZgBUV0orvAS3grDO9Wl9B/Fgm/HMO77edy8eSSPzDmLdftzWbc/l+S48KC7GUUFn799uoVPNh6qMa/efPs0j+beDiGQZhJ5a9Cj7FljDevU1dOvTUQY0SOW9zMj6CJncIXzC573zmC/6cLh/FKGJcfW2D63uBzJ2Exs6vu85riUmLjElj3JANGefrCo7OmXeYho5RtCpgxIIuycPxFBKXMLnuCQPe4JcMfbGygq07z7qnWVeawMmWu27uI3rtd5P+Qu+OxOvvSO4tE+8/hw2idIr1Ortu+dGNGo447vnUBqej4PlMzCK05+43oDqNnT33qogLmvrGbUPQvY8OpdmJBo/llyNl2DLLFafTToB4uizKrhnYgWvDGrPpNPm8q3vedytnMVnb57gETyePDSERzKL+Wt1WmtXr/q2HZmFhIiHl4Pu5+5zvcoMuH8L+wH3GZu4gcXXcANpw+ge5wVhCNDnCRFhTbquOP7WPe5ZBBPzrBrmOVcxhDZw+FqNyO+umIfH61PZ7js4rSyr0kfdBU5JorOGvSV35QXQ1k+RHWmpMLbonfjHs+OflfxuXcsg3c8x9LQXzEzagsje8Txwjd7aixCrVRLKin3kpOdycfd5zOAvaw+9Ukur7ib23Nm8vNzxpISb/Xqu8WGA9bQTmPnzY/uGceALlH89eLhdD//DgiL497Q/5Bb7b6U7/dkc2XPTN5OepYsE82fsq0Fi05qxBBSMNCgHwyKrDn6RHWhuNzT4nfj1ic+MpTrK37DbV3nkSEJhH5xFxcO68yuI0Xk69KKqpXsyCjkVuebnJS9BM78M2bguVWvzRjWtepx98qg34iLuJXC3E4+v3Uql4/vCeFxcM79jGQrP9l+K3jKKSitoPxQKndl3Y3bAfdF383nO4oRgRE94lrqFANKg34wKKwe9P3X04+LsHKYLMrqxEsRV8GRrVy6dg4J5HFI0zSoVrLv4EF+6FxMQf/ZcNotNYZukuPCqx7HhLvokxjJuN7xza9s9BU8l3gH/co2wT9GsPutPzLf/Tcc7lC46kNSRk4HYEDnaKJacA2LQNKgHwzsG7NMZJLfxvQB4uxshRkFZWxPmA6z/0VM/jaeCvkH6bnNz0uu1PEkr3+CcMoJOe2XACRFHw361YdxRIRFv53GnEl9Tqi+Q73O5y7fDZTH9GLE9ieJc5Ti+MkbEN+Lc4Z2AWBUO+nlgwb94GD39MvDk/D6jP+CfvjRJRm7xobByMvIm3YfExxbcGz/zC9tUB1M1k6Gp73G23IG4T1HARAZ6uLi0cnMn9M6a9H2Tojk5fIpfDzmX/yy/Ca2/GARrpQxAAzpFsMNU/tyxcSerVJ3IGjQDwaFGYBQ4raTrflrTN/u6QOclBQFQNTEq9hvkui37Tm/tEF1MMv/iQ8H78RdVaP4kR+N4vSBrXN/SM8E68Lw17vy+MB3Kl27Hc2tIyLcfu4gRqTEtUrdgaBBPxgUHoaIBIo91lfbSD/19GOq9fSHdbduXHG7Q3jLeR7dC9ZD5ja/tEN1EGUFsPZVFrhPJ6JTd79VW3kheNmOIzgd0m7m49dHg34wqLwbt9zKLuivC7nOapk8h3Y/mtBqddyZ+HDAulf90g7VMexY/i54SnihcEKNC7atLTkuHIfAwbxSusaE4XK277DYvs+uvajKu2NNk2yNLJsNiY88OtQTFtedFa6xsPpFMrOyGsxQqFRD3lyVxqaFr5JtolhlBhAT5r/PeIjLUTV86c8/NoGiQT8YnPsgTP89vRMjeWHOyYzuGee3qvt3jmJMrfoGdInmoZILoDiLZx+5m3/YaW+Vaq5nv1jHWa7VePrNwOF0MXlAkl/rr5yl469v0YGkQT8YpIyFlLHEhLmZNrAziY285bwlLPj1VN668dQaZeN6x7PS25+tEWO43vURC9fvYd3+XL+1SbUv+7OLOTn/CyJMCZ2n3cC2e8/l5N6d/NqG84f77xpCoGnQVw2qfYv7mF7WLKLf55xPkuQxOvtjZj75DZ9vOhSI5qkg9+22A1zn/IjSxGGQMi4gSxEO7hbNfbOHcd/sYX6v29806KsmiwlzMzw5lhVmMJtMH37s/BIwPLtkV6CbpoJQ2Orn6O04TOiMv0CA1p4VEa6Y0Ksqr0971j7uK1Z+98yVYyku81D8zU8Yuf4vjJKdrNwrFJRWEB3mbvgASgEYw5jMd9kSNpJB/aYHujUdgvb0VbMkx4XTv0s0vU+fQ74jlicS3wEMOUUVgW6aCiKFO78l2RziQK9ZgW5Kh6FBX52Q2PgEYs79Iz0K1jDdsYac4vJAN0kFkZKFD1BowogcOTvQTekwNOirEzfmp5RF9+RW15tkF2n2TdU425a9S1L6Yp7hUoaclNLwDqpFNBj0ReR5EckQkY3VyjqJyAIR2W7/jK/22h0iskNEtorIOdXKx4rIBvu1xyUQl+hV63C6yZ/wW4Y79hC75bVAt0a1cR6vD+PzEfb1gxw0iVzyi3uJ0etAftOYnv4LwIxaZbcDC40x/YGF9nNEZAhwGTDU3ucpEam82+Fp4Hqgv/2v9jFVEHOPvozvfIMYtuFByNjC26vTOFhtbV2lvD5DSbmXfnd9wnv/vpeexZv4qvOV9OlyAvnwVZM1GPSNMUuA7FrFM4EX7ccvArOqlb9mjCkzxuwGdgDjRaQbEGOMWW6sdfZeqraPagdiwkP4TcUvqHCE4nn9an77+houfOLrQDdLtSF3v7uRwX/4lCGyh/PTHmOhdzShE+cEulkdTnPH9LsYY9IB7J+VOU+Tgf3Vtkuzy5Ltx7XL6yQi14vIShFZmZmZ2cwmKn9yOISSiO683/0WXEdSucS5hKyictJyigPdNNVGvLpiH2D4q/s5coni1xU3MqJHQqCb1eG09IXcusbpzXHK62SMedYYM84YMy4pyb85OFTzxUW4WeqeREbsCH7rep1wSrl83rfk6owehbUC1nTHGkY6dvE3z2WUuGLondD+b4Zqa5ob9A/bQzbYP+1FXEkDelTbLgU4aJen1FGu2pFOkSF8vPEwN2bMpovksibh9/TKXcEH69MD3TQVYMXlHjILSrk/4VOKIpJ51zuJfklR7T6NcVvU3N/4+0Dl0jZXAe9VK79MREJFpA/WBdsV9hBQgYhMtGft/LTaPqqdOJxfBsAqM5BbzG8IjYhhfsjfOfKdzujp6PZmFXOqYxNdCzaSO/oXeHAxsGt0oJvVITVmyuarwHJgoIikicjPgAeAs0RkO3CW/RxjzCbgdWAz8Ckw1xjjtQ91I/Ac1sXdncAnLXwuKsAm9LEyIw5LjmHQ9CuQaz4lI3ooN2f/lfR1XwS4dSqQ9mbkcpfrZSoiuxI/6WoiQ5x+TRGujhJrMk3bNW7cOLNy5cpAN0M1QmmFl5Jyb40FVzKPHKHgidPo4iom8if/ZW/MWK59cSW3zRjEmUO6BLC1yp+WvvhHJu9+jJKLXyJ8xEyOFJYRHxFSY3U21bJEZJUxZlztch1QUy0mzO2sEfABkhITeW/IYxzyRGJemsX6F39DekYGt7+9nmU7jgSopcqvvBUM3vtf1ruGEz5iJgCJUaEa8ANEg75qdWdMmsjMsnvYFH8GF+a/ymdxD9BJCrjy+RUczte0De1dzqo3SfQdYf/AawLdFIUGfeUHw5Nj6ZyUxAUHr+an5bfRvSKNtxL+hfgqWJ+WF+jmqdZkDL5v/skuX1f6T74k0K1RaNBXfiAi/P6CIQBkdZ2MXPQPog99y42uD9h4QIN+u7b/OxLyNvIy59Gvc0ygW6PQRVSUn5w+sDMf3zyZhKgQiJkM2z/n5o3v8Ic95wMDAt081VqWP0mBRLGt60U4dAy/TdCevvKbId1j6BITZj2Z8QBeh5sZB5+ENj6DTDVT5jbMlg95zXsGfVM6N7y98gsN+iowojqzvs91TDXfk7/8eQAyCkp5/uvd7MgoCHDj1Il46LOtnPPoEg69cycVjjCeKZ/B0O46tNNW6PCOChjfKb/k620LOXXB/1ESEccFH8WSUVBGuNvJV7+bRufosEA3UTXDPxft4CLHN3TNW8BDFT+gW3IPzhnWNdDNUjbt6auAGZoSzw0Vt3Ioehhh713HxKJF/GJaX0oqvKzckwNYOdgf/HQLuzILA9xa1RilFV76ONK53/1vNjoHM/Vn9/PGz0/VRVLaEA36KmCiw9wkJSbxQMJ9HIwZxaPuJ/ll2Tz6ujJZv8tK0rZidzZPLd7JrCe/oa3fPa4gNS2Tx11PEBISwoBf/I+TT+pMeIiz4R2V3+jwjgqoMT3jWbD5EGU9/sSFRY9zwboXWOjy4F3jgOxTWRdxLRBCfqmHZTuzmNQvMdBNVvVYvS+Htf/+Fde49pA140USEnoFukmqDtrTVwF1wYhu5Jd6+Gx7AQv63QW/XM2C3r/lKe8sfJlbuTL1Rq7skUmIy8GXWzIaPqAKmB3L3uMa16d8FX8JncbMDHRzVD006KuAOq3/0Z77pWNTIL4Xfc67lYcrLuWBHs9wxBfN73Pu4ofJWSzeqkG/zfKUMWXH39jvSGHq3KexMqirtkiDvgoot9PBxzdPZuFvpjK5v7VKWr/OUUzql8Cz68q4vPxuJCyWO3L/RPmRXRzQxdbbJLP6P3T1HGRBz1vAFRro5qjj0KCvAm5I9xj6JkXVKLthal8ADpKI6yevE0o5b4f8kS1bNgaiieo40jKzKFz4d1b6BhA66KxAN0c1QIO+apNO65fIqX0T+NlpfZCuwzBzPiOMCgYuvQW8FQDszCzkpldWc1B7/wFT7vHx/VPXEV12iFcirmTKAL3ztq3ToK/aJBHhlesmViVqc3cdzLy4W0gp2ggL/kBpuYfZT37Dh+vTeWNlWoBb23Glrl3GbLOQ7f2u4ZHbb6ZHJ13ovK3ToK+CRunAmbzknQHfPkXeGzdRVGqtybuo1gXebYcLKPN46zqEamGhyx6m0ITR9YI7A90U1Uga9FXQOLVvAn+s+Al7h9xAl+2v8kbIn3lmwCqcB1aQs3khlBfz2BfbOPvRJfz8P6vweH2BbnK79dW2TJ79xz0Myv6Sj6J/QHRcUqCbpBpJb85SQWPiSQmEuFz8peRShsREc1XBvxmz72FmhACvgwlPoKRgBhOSzmbx1kyeWryTm8/oH+hmtwsPfbaVL7dkMPf0fpw/vCt7v3yea7IfZVPYaMb+5N5AN081gQZ9FTTC3E5O7ZvAF6kZfMFo3Gd+xi/HhnLfv1+jzOdkbtin3FHyMqbwVT5OvppfLYTZo5Pp0SmCV77bR6+ECL2jtxmKyz08u2QXFV4Pa999lHO/+JCf5h9ga/gIht76AYRGB7qJqgk06Kugcu/s4Xy/O5ueCRGMSokDhzDkjCu49X/reInB9JUDfDZ6Oedvfp5E1zJ2LtpP91nXc+c7GwC4+/zB/HhCTyJC9KPfGBkFpTyzaCfnmSXclfAFSUXb2O8byVMV59L51J8xUAN+0NFPvgoqyXHhJI9OrlE2e3QKw5NjOfORJXTrOxLXpdfCylPp/ckDdNlwGyXZ7zFczmOD6cNjH60ir6SCa087idgIzfzYkD+9s47ztv+BC0K+xRcxiBei7uRPe4cCwjPdOwW6eaoZNOirdqFf52hS75mB1xhwOGD8dcw7fAplK+Zzd8abfBC6jHJXNCGeAhYuHc3UxTfx6W0X0DVWc/bXy+vh4j1/4kznt3zday6nXXUvZ+SWcv/DX1Hu9TEiJTbQLVTNoEFftRu1U/hOGtCZOd9MZ3fXGQxPf4vfjI3kcLmTKeuf42H+yccr+nDNWWPZn11Ml5gwQlw6ma2Kp5yi16/nTN8yvh/wG0778R8A6NEpgvV/OpsDuSV0jwsPcCNVc2jQV+3WuF7xOAS+3l/O4c6Xc9uFU+kC0KM/Z3z8W/KXzaS0+7+Y/B8Y3C2Gj355WodevDuvuIJ7PtzMpJgMLt5xJ5FHtvFAxWXMmn5Lje3C3M5j0mao4KFdG9VuRYe5qVx25eIxKUdfGH8db098g/3eToS98WN+7Xqd1PQ83llzICDtbAu27dnLU4/+kYs23MRFy39ITnYmN/huY12vOQzsohdr2xPt6at27Z6LhrIgNYNrJ/epUT5g+AQuXvxn/h7xH252vcsYdxqpS06FTmdB78nQAVIDV3h9fL1xNxP3PEWfNS9wBx5KY3uyPOLHvCLnUhLamb/PHqZpktsZaetL0I0bN86sXLky0M1Q7YzXZ+h758eA4c9JX3F58X8J8RYDUJY0gtyBP+LzQxFkxo4g34Rzy5n9iYsIadSxfT7T5oeJDuWV8vDz/+HXuffThRxe857OkAt+yagJp3eIP3gdgYisMsaMq12uPX3VITkdwiVjUvhqWyZDL7mDooQ/8+e3l8LORdxw+E16ZN7FlYDXCG95p/BZ9llcct4MvsyIYuvhQi4Zm1LnhczU9HwufmoZz1w5lqkD2mZqgq3701n+wl3c73mX4ohuPNHlfoaOn86oIV0C3TTlB9rTVx2Wz2cQocbwxeH8Ut5etZfo8ixmphQRvvszZOXzOLESuO2nC194RvFl2JkMGT6On00fQufoo9M+b3plNR+uT2dkSizvzp3UtoZGfD58614j+/27SDTZ5Pa/hLjZD0GEzrdvj+rr6WvQV6oB2Tk5PPLaR5C2kmmOtUx1b8btszJ8rnKNZvj5NxLiKyFr7yaWrNlMaFgYB0vcnDF2MH3GnA09J1Lq8eHxGaJCj365NsawfGcWw1JiqfD4+H5PDucM7dKsPxQ7Mgq59X9rOXNwF26a3g+nQ8grruDF5Xs4uG8nvfa9xZVhXxNVcpC1vr4UT7+XU6ed12K/I9X2aNBX6gSUlHsZ/ZfPKa3wsezWcXTf/Q679uwkIvUNukoOAKXGTZbE0zXKSWlhDpGUArDD2Zfdnk5k+qKJTOyBr7yUM0f05n87hNQDuQzrFkleaQVrcsL5+QWT6N/JxSF3L27/aDe3njmAM4d0weczXPvSShwiPPzDkUSHuqquG7zx9UbeX7CQniaNSG8B0/uEMyE5lM/W7SG6eB8THKk4MHztHcar3ukcSTmb126YhLONX3dQJ0aDvlInaO7Lq9mRUchnt04BrJ76BY8twpexhaG9umLiT+KCUd05fWBn3l6dxh/fWM5sxzdcErKcBFcpsd4con15eIwDBwaH1P9/z2McbDE9cTsMya58nA7YURpLjokm351IrieEM4Z0I+7IKsKPbKixr9cIXlcEhR7BxPYiYfiZ5A35CW/scjFtYBJ9k6La1rCTahUa9JU6QUVlHiq8vhqzeHZkFLIw9TDXTj7pmJ7z9sMF5JdWMLaXNWbu8xm2p+fw3Df7+Gbzbh6/MIV+XeO495OtXDy6O4nlaTz7yXfkekI5IyaNKRF7OFgkbC+OwGW89I0oZmBUCYXZhwgzJbjxsteRwkLGM2f2+USlDCXfFce0R78ju8RLUnQoS393OmHumncqq46hzQR9EZkB/ANwAs8ZYx443vYa9FV74/UZKry+OoPx5oP5lHm8jO4ZX1X22aZDLNtxhN+eM5DoMCtJ3LtrDnDL/9bSs1MET/54DMOr5cH5fNMh/vPtXn5/wRAG6I1VHVabCPoi4gS2AWcBacD3wOXGmM317aNBX6m6lVZ4CXU5dKhG1am+oO/vNAzjgR3GmF3GmHLgNWCmn9ugVLsQ5nZqwFdN5u+gnwzsr/Y8zS6rQUSuF5GVIrIyMzPTb41TSqn2zt9Bv65uyTHjS8aYZ40x44wx45KS2uZdjUopFYz8HfTTgB7VnqcAB/3cBqWU6rD8HfS/B/qLSB8RCQEuA973cxuUUqrD8mvCNWOMR0RuAj7DmrL5vDFmkz/boJRSHZnfs2waYz4GPvZ3vUoppXTlLKWU6lDafBoGESkAtgKxQF4dm7REeSJQ0YrHB+gJ7KujvCXriAXcwJFWPH5leWK1elrzvaldV2scv7K8dj2tdV6V9bT27609fh788X+1pX5vjd2ntX53XY0xx96SbYxp0/+AlfbPZ+t5/YTLgZWteXy7PPM459hidVf+vlrr+LXfl9Z+b2rX1ZrnVbue1jovf3ym2+vnwU//V1vk9xbo3119/2+CaXjngyAvz62n3B91B3t5fdpaO7Vcy9tK3fW2KRiGd1aaOvJHaB0dox5/1tXe6vFnXVpP26urvuMGQ0//Wa2jQ9fjz7raWz3+rEvraXt11XncNt/TV0op1XKCoaevlFKqhWjQV0qpDqRDBH0R8YrI2mr/eh9n28Ui0qSLKiJiROQ/1Z67RCRTRD48gWY3VOdsu95BrXDsQJxPYWsduzn1NedzUGv/Vnt/atVzl4hsEpH19md7QivWlSIi74nIdhHZKSL/sHNo1bf9LSIS0cQ6jIg8XO35b0XkTyfQ7PrqqYwJm0RknYj8WkRaNR76+zNenw4R9IESY8yoav/2tPDxi4BhIhJuPz8LONCUA4hIU1NiXA58jZW0rin1NGbB1BM+H9W896cpROQU4AJgjDFmBHAmNderaMm6BHgbeNcY0x8YAEQB9x1nt1uAJgV9oAy4WEQSm9POJqiMCUOxPt/nAX9s5TrbhI4S9I8hImNF5CsRWSUin4lIt2ov/0RElonIRhEZ38hDfgKcbz++HHi1Wl3j7eOtsX8OtMuvFpE3ROQD4PMmtD0KmAT8DDuoiMg0EVkiIu+IyGYReaay5yIihSJyj4h8B5zSiuezVERGVdvuGxEZ0YTzmlb924SI/FNErrYf7xGRP4vIahHZ0BI96OPVd4LHre/9qe/czhORLSLytYg83oRvVN2AI8aYMgBjzBFjzMH6Ptv2t5fHmvHZBpgOlBpj5tt1eYFbgWtEJFJEHrLfl/Ui8ksRuRnoDiwSkUVNqMeDNevk1toviEgvEVlo17FQRHqKSKz92aj8rEeIyH4RcTe2QmNMBnA9cJNYnCLydxH53q7r59Xa8Dv7PNeJyHHX966LiETZba/8HM+0y3uLSKqIzLO/fXxerdPVojpK0A+Xo0M779gfiCeAS40xY4HnqdljiTTGnAr8wn6tMV4DLhORMGAE8F2117YAU4wxo4E/APdXe+0U4CpjzPQmnM8s4FNjzDYgW0TG2OXjgd8Aw4G+wMWV5wNsNMZMMMZ83Yrn8xxwNYCIDABCjTHrm3BeDTlijBkDPA38tgWP29JmUff7cwz79/sv4FxjzGlAU1YN+hzoISLbROQpEZnaSp9tgKHAquoFxph8rNQi1wJ9gNH2N46XjTGPY62Vcbox5vQm1APwJHCFiMTWKv8n8FJlHcDjxpg8YB0w1d7mQuAzY0xFUyo0xuzCioedsf5Y5xljTgZOBq4TKx38uVjv7QRjzEjgwSaeF0ApMNv+HJ8OPCxSteZlf+BJ+9tHLnBJM47fIL9n2QyQEmPMqMonIjIMGAYssH/fTiC92vavAhhjlohIjIjEGWNyj1eBMWa9WNcKLufYLKKxwIsi0h9rpbDqvZAFxpjsJp7P5cBj9uPX7OcfASvsDy8i8ipwGvAm4AXeakoFzTyfN4Dfi8j/AdcALzSlzkZ42/65iqN/0Nqi+t6fugwCdhljdtvPX8XqdTbIGFMoImOByVgB5H/AvbTwZ9sm1LHKnV0+BXjGGOOxj93Uz3MNxph8EXkJuBkoqfbSKRx93//D0aD7P+BHwCKsb1ZPNbPqyuB7NjBCRC61n8diBeQzgfnGmGK7nc05TwHuF5EpgA9rudgu9mu7jTFr7cergN7NOH6DOkrQr02ATcaY+oY6an+4G3szw/vAQ8A0IKFa+V+ARcaY2XYgXVzttaJGHhsAEUnA+qo9TEQM1n9qgxWY62t3qf11vKmadD7GmGIRWYC12P0PgaZeCPVQ89tnWK3Xy+yfXlrms9tQfU12nPfn/XrqOqGVze33dTGwWEQ2AHNpnc/2Jmr1PEUkBmslvF1NOE5jPQasBuYfZ5vKOt8H/ioinYCxwJdNrUxETsL6XGVgvSe/NMZ8VmubGZz4eV6B9W1urDGmQkT2cPSzUFZtOy+gwzstaCuQJNaFMETELSJDq73+I7v8NKyvefVl0KvteeAeY8yGWuWxHL0QenWzW225FOsrbi9jTG9jTA9gN1avfrz9NdRhn0Njh3Lq05zzeQ54HPi+GT2hvcAQEQm1v9qf0cT9m6o16qvv/aGeurYAJ8nRGWU/amxFIjLQ/rZVaRSQSut8thcCESLyU3t/J/Aw1re5z4EbxJ6MYAdfgALg2CyPjWB/dl7HGmqptIyjF8avwP58G2MKgRXAP4APm9rBEZEk4Bngn8a6W/Uz4MbK6wIiMkBEIrHO8xqxZyRVO8+miAUy7IB/OtCrGcc4IR2yp2+MKbe/uj1u/wd0YfUsKlfxyhGRZUAM1jBFY4+bhvXBq+1BrOGQX9OMXkgtlwO1LyC9BdwILLdfGw4sAd45kYqacz7GmFUiks/xe2g12MGizBizX0ReB9YD24E1zW584Oqr7/35MVYQq1GXMaZERH4BfCoiR7CCV2NFAU+ISBzWt5YdWENDz9Lyn20jIrOBp0Tk91gdxo+BO7F6pQOA9SJSAczDGn9/FvhERNKbMa4P1h+Vm6o9vxl43h4+zATmVHvtf1jDi9MaeexwEVmLNTTpwRouesR+7TmsoZXV9nh7JjDLGPOpWBMVVopIOUfPv0GVnzmsaxEfiMhKYC3WH32/0jQM7YSITAN+a4y5IMDt6I413DDIGONr5D4jgXnGmKbMJmk2f9fXEBGJssfnBesi5nZjzKOtUM9irM/IypY+tjq+tvSZ66jDO6oV2F/9vwPuakLAvwHr4uLdrdm2QNXXSNfZvc5NWF///xXY5qiW1NY+c9rTV0qpDkR7+kop1YJEpIeILBLrZqtNIvIru7yTiCwQK43FAhGJt8vPEutGug32z+nVjnWfWDebtVgKB+3pK6VUCxLrDuhuxpjVIhKNNed+FtZMt2xjzAMicjsQb4y5TURGA4ftu6mHYd1clmwfayLWLLPtxpioFmmfBn2llGo9IvIe1mymfwLTjDHp9h+GxcaYgbW2FaxF0rtXptewywtbKujr8I5SSrUS+/6L0VgTHLoYY9IB7J+d69jlEmBN9YDf0jrkPH2llGptYiXeewu4xU4t0dD2Q4G/YaWBaDXa01dKqRZm3837FlbyucqcUYflaMbTblgpHyq3T8G6mfKnxpidrdk2DfpKKdWC7HH5fwOpxphHqr30PnCV/fgq4D17+zishHx3GGO+afX26YVcpZRqOXZeo6XABqxMmmCla/gOKxVHT6yU1D8wxmSLyN3AHVjpOSqdbYzJEJEHsVJ4dMdKVf2cMeZPJ9Q+DfpKKdVx6PCOUkp1IBr0lVKqA9Ggr5RSHYgGfaWU6kA06CulVAeiQV+p4xCRP4nIb4/z+iwRGeLPNil1IjToK3ViZgEa9FXQ0Hn6StUiIncBPwX2Y62PugrIw1p/NgRrLdorsRYi/9B+LQ8rWRZYSx4mAcXAdcYYv6+DqlR9NOgrVY2IjAVeACZgJSRcDTwDzDfGZNnb3IuV//wJEXkB+NAY86b92kLgBmPMdhGZAPzVGDP92JqUCgzNsqlUTZOBd4wxxQAi8r5dPswO9nFAFPBZ7R3trIqnAm9Uy6gY2toNVqopNOgrday6vv6+AMwyxqwTkauBaXVs4wByjTGjWq1lSp0gvZCrVE1LgNkiEm4vdXehXR4NpNspc6+otn2B/RrGmHxgt4j8AKxsiyIy0n9NV6phOqavVC3VLuTuBdKAzUAR8Du7bAMQbYy5WkQmAfOAMuBSrKyKTwPdADfwmjHmHr+fhFL10KCvlFIdiA7vKKVUB6JBXymlOhAN+kop1YFo0FdKqQ5Eg75SSnUgGvSVUqoD0aCvlFIdiAZ9pZTqQP4fdWplU1EFx4UAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
     }
    ],
    "source": [
-    "data_by_day[['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+    "hospital_data[['new_admissions', 'new_admissions_7']].plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
+   "execution_count": 117,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c41f2850>"
+       "<AxesSubplot:xlabel='date'>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 117,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
     }
    ],
    "source": [
-    "data_by_day.loc['2020-04-01':, ['cases_culm', 'cumAdmissions', 'deaths_culm']].plot()"
+    "hospital_data[['hospital_cases', 'hospital_cases_7']].plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
+   "execution_count": 118,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c40cbdd0>"
+       "<AxesSubplot:xlabel='date'>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 118,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEECAYAAAAh5uNxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOydd3hb5dn/P48sS7LlEa/Yjp3EGc7eG0LCThiF0DJbRihQoBRKS6GFl/ctFLpYZfRHoaw2lE0pZYewsoCQRUKWE2c4ieM9JQ/JGs/vj3Mky7ZsS7Idr+dzXb5sHZ3xKHbOfe71vYWUEoVCoVAMPgy9vQCFQqFQ9A7KACgUCsUgRRkAhUKhGKQoA6BQKBSDFGUAFAqFYpCiDIBCoVAMUoy9vYCOSE1NlTk5Ob29DIVCoehXbNmypUJKmdbZfn3aAOTk5LB58+beXoZCoVD0K4QQh0PZT4WAFAqFYpCiDIBCoVAMUpQBUCgUikFKn84BKBSKnsXlclFYWIjD4ejtpSgiwGKxkJ2dTXR0dETHKwOgUAxiCgsLiY+PJycnByFEby9HEQZSSiorKyksLGTUqFERnUOFgBSKQYzD4SAlJUXd/PshQghSUlK65L0pA6AY8EgpcXm8vb2MPou6+fdfuvq7UwZAMeB5d3sRc//wKXaHq7eXolD0KZQBUHSJoppGbnp5C1X1Tb29lHbZXWSjpsHF1iM1XT6X3eHive1F3bAqhaL3UQZA0SWeWn2AD3eU8Nme0t5eSruU2rQY6ZaCqi6f67/birjl1W/ZX1bX5XMpNF588UWmTZvG9OnTufLKK3nvvfeYP38+M2fO5IwzzqC0VPvbWrNmDTNmzGDGjBnMnDkTu90OwEMPPcTcuXOZNm0a99xzDwD19fWce+65TJ8+nSlTpvD666/32ufry6gqIEXEVNc38eaWowBsKqji4jnDe3lFwSnRDcDmw9VdPldRTSMA+8vsjB0a1+Xz9SV+994udhfZuvWck4YlcM95k9t9f9euXfzhD3/gyy+/JDU1laqqKoQQbNiwASEEzz33HA8++CCPPPIIDz/8ME8++SQLFy6krq4Oi8XCqlWryM/PZ+PGjUgpOf/881m7di3l5eUMGzaMDz74AIDa2tpu/VwDBeUBKCLm5W8O43B5GTs0js0FXb+59hRlNicA247W4O5iMri0VjMmB8rru7wuBXz++edcdNFFpKamApCcnExhYSFLly5l6tSpPPTQQ+zatQuAhQsXctttt/HEE09QU1OD0Whk1apVrFq1ipkzZzJr1izy8vLIz89n6tSpfPrpp/zmN79h3bp1JCYm9ubH7LMoD0AREU63hxVfH2bxuDQWjknhTx/lUW53khZv7u2ltUBKSYnNwdB4M2V2J3kldqZkRX4z8HkTAzEE1NGTek8hpWxTyXLLLbdw2223cf7557N69WruvfdeAO68807OPfdcPvzwQxYsWMCnn36KlJK77rqLG264oc25t2zZwocffshdd93FkiVL+O1vf3s8PlK/QnkAioh4Z1sR5XYnP1k0irmjkgHY3A0x9mB4vRIpZUTH2p1uGpo8nDM1E+j6GgeyAegNTj/9dN544w0qKysBqKqqora2lqysLABWrFjh3/fAgQNMnTqV3/zmN8yZM4e8vDyWLl3KCy+8QF2d9vs4duwYZWVlFBUVERsbyxVXXMHtt9/O1q1bj/+H6wcoD0ARES+sP8SEjHhOGpuKyyOxRBvYVFDN2fqNtju57sXNxFuMPH7ZzLCPLdNv2DNHDOHjXRY2H67m6oWRdU1CYAioLujTqyI8Jk+ezN13383JJ59MVFQUM2fO5N577+Xiiy8mKyuLBQsWcOjQIQAee+wxvvjiC6Kiopg0aRJnn302ZrOZPXv2cMIJJwAQFxfHSy+9xP79+7njjjswGAxER0fz1FNP9ebH7LMoA6AIG7fHS16JnVtPz0UIgckomDF8CJt6wAMotTn4Ym8ZCZZovF6JwRDeDbekVov/pydYmDUyia1dSATbHS7qmzyMSI7lSFUDxbUOhg2Jifh8Co3ly5ezfPnyFtuWLVvWZr+//vWvQY+/9dZbufXWW1tsGzNmDEuXLu2+RQ5QVAhIETYNLg8A8Zbm54e5OcnsKqqlzunu1mt9tKMYKaG20cXBivDDLr4S0PQEC3NGJlFU6/BX8kR6roVjUwDNC1Ao+jPKACjCprFJMwCxppYGwCvh2yPdWw304Y4SkmI1pcOth8Nv5CrxGwAzc0bquYoIvQCfN7FwrFaxovIAiv6OMgCKsKnXn/JjTVH+bbNGJmEQsOlQ94WBymwONh2u4qoTchgSG82WCG7cZTYH8RYjsSYjEzPjiYmOirghzGdMpgxLJMFiVAZA0e9ROQBF2DToHkBMgAGIMxuZNCyBTd3YD/DRzhKkhO9Ny+S7whq2RuBdlNgcZCRYADBGGZg1cgjr8isiSuCW1Gqho4xEC2OHxqkQkKLfozwARdj4DIDV1PL5YV5OCluPVOPQcwRd5YMdxYxLjyM3PZ7ZI5PIL6ujtiE8QbcSm5OMRIv/9bIZWRysqGdjBJ5Kic3BkNhoLNFRjEmLY3+ZagZT9G+UAVCETUOTFgIK9AAATspNwen2dktXcJnNwaaCKn/9/qwRSQBsPRreuctsDobGNxuA86YNI95i5JWNR8JeU0mt0+9NjB0aR0WdM2yDpFD0JUIyAEKIAiHEDiHENiHEZn1bshDiEyFEvv49Sd8uhBBPCCH2CyG+E0LMCjjPcn3/fCHE8vaup+jb+D0Ac0sDsGB0CtFRgrX55V2+xse7S5ESztUNwPThQzAI+DaMPIDHKymzO8lIbO5OjjFF8YOZWXy0oyRsBdNSm4N03QCMSdN0gParMFCfZdmyZf7+gPaIiwtPz+npp5/mxRdfDOuYoqIiLrroorCOOV6E4wGcKqWcIaWco7++E/hMSpkLfKa/BjgbyNW/rgeeAs1gAPcA84F5wD0+o6HoX/gMQGx0yxBQrMnInJHJrN3XdQNwoKyOOLOR3PR4AKxmIxMyEtgSRh6gst6Jxyv9N20fP5o/kiaPl7e2FIa1psB8gk8I7oBKBPdJampq2Lp1KzU1Nf5Gsu7gxhtv5KqrrgrrmGHDhvHvf/+729bQnXQlBLQM8PVprwAuCNj+otTYAAwRQmQCS4FPpJRVUspq4BPgrC5cX9FL+EJAsa08AIDF49LIK7H7a+YjpczuID2hpa7Q7JFJbDtSg8cbmixEaUATWCDjM7Scwqsbj4QsMeHyeKmoc5Ku5xOGJ8diijKoRHA3UFBQwMSJE/nJT37C5MmTWbJkCY2NjRw4cICzzjqL2bNns2jRIvLy8vB4PIwePRopJTU1NRgMBtauXQvAokWL2L9/PwBvvfUW5513Hpdddhmvvfaa/1qHDh3ihBNOYO7cufzf//2ff/vq1as5+eSTueSSSxg3bhx33nknL7/8MvPmzWPq1KkcOHAAgHvvvZeHH34YgCeeeIJJkyYxbdo0LrvsMiC4ZHVBQQFTpkwBtBGcP/7xj5k6dSozZ87kiy++AOCf//wnP/jBDzjrrLPIzc3l17/+NQAej4err76aKVOmMHXqVB599NFu/bcPtQpIAquEEBL4u5TyGSBdSlkMIKUsFkIM1ffNAo4GHFuob2tvewuEENejeQ6MGDEijI+iOF74PQBTMAOQygMrYe2+8i7JQ5fanG1u3LNHJvGvDYfZW2Jn0rCEEM6hGaGMVucB+NG8Efzqze18fbCSE8ekdnqucrsTKZvPFWUQjEq1DqxS0I/uhJId3XvOjKlw9p873S0/P59XX32VZ599lksuuYS33nqLf/zjHzz99NPk5ubyzTffcNNNN/H5558zbtw4du/ezaFDh5g9ezbr1q1j/vz5FBYWMnbsWABeffVV7rnnHtLT07nooou46667AK1r+Kc//SlXXXUVTz75ZIs1bN++nT179pCcnMzo0aO57rrr2LhxI48//jh//etfeeyxx1rs/+c//5lDhw5hNpupqdF6VIJJVgfiu+aOHTvIy8tjyZIl7Nu3D4Bt27bx7bffYjabGT9+PLfccgtlZWUcO3aMnTt3Aviv012E6gEslFLOQgvv/EwIsbiDfYPV1skOtrfcIOUzUso5Uso5aWlpIS5PcTxpaPIgBFiMbQ3AxIwEUuPMrMuv6NI1AuPtPnyJ4M2HQ6vgKQnoAm7NudMyMQj4cn9o6/SdKzOgomh8RjzfHavFG6JHomifUaNGMWPGDABmz55NQUEBX331FRdffDEzZszghhtuoLi4GNCe9NeuXcvatWu56667WL9+PZs2bWLu3LkAlJaWsn//fk466STGjRuH0Wj030C//PJLfvjDHwJw5ZVXtljD3LlzyczMxGw2M2bMGJYsWQLA1KlTKSgoaLPmadOmcfnll/PSSy9hNGrP0sEkqwNZv369/7oTJkxg5MiRfgNw+umnk5iYiMViYdKkSRw+fJjRo0dz8OBBbrnlFlauXElCQucPPuEQkgcgpSzSv5cJId5Gi+GXCiEy9af/TKBM370QCHz0ywaK9O2ntNq+ukurV3SZ4tpGDpTVs3Bsir8u3u3xsqmgmnmjkokKor3T4HQTEx0VVJfHYBAszk1l9b7yiLR7QJMILrM5GdoqBDQ8OYaclFg+2V3KVSfkdHqeUpsDg4DUOFOb9yzRUSTERGNrDE26wicCF2hMTp84lHe3F7HlSDVzc5JDOk+fJoQn9Z7CbG7+XUdFRVFaWsqQIUPYtm1bm30XLVrE008/TVFREffddx8PPfQQq1evZvFi7bn09ddfp7q6mlGjNNE/m83Ga6+9xu9//3ug/UHqgWswGAz+1waDAbe77d/JBx98wNq1a3n33Xe5//772bVrV1DJ6kAvoKOQY+t/A7fbTVJSEtu3b+fjjz/mySef5I033uCFF15o9xzh0qkHIISwCiHifT8DS4CdwLuAr5JnOfCO/vO7wFV6NdACoFYPFX0MLBFCJOnJ3yX6NkUv8sBHeVzx/Df88NkN7C2xs3pvGWc9vo4fPruBVbtKgh7T4PK0kIFozeJxaVTVN7GzKLIpTNUNLpo8XtLjWz65CyFYOiWDrw9UhlR+WWpzkBpnxhgV/M88wRKNLcRB8cW6AQjsKTh9Yjomo4EPdxSHdA5F6CQkJDBq1CjefPNNQLtxbt++HYD58+fz1VdfYTAYsFgszJgxg7///e8sWrQI0MI/K1eupKCggIKCArZs2eLPAyxcuND/88svvxzx+rxeL0ePHuXUU0/lwQcfpKamhrq6uqCS1YEsXrzYf919+/Zx5MgRxo8f3+51Kioq8Hq9XHjhhdx///3dLmsdSggoHVgvhNgObAQ+kFKuBP4MnCmEyAfO1F8DfAgcBPYDzwI3AUgpq4D7gU361336NkUvsuNYLTkpseSV2Dnr8bVc/Y9N/kauotrgidwGpzto/N/HSblaTD3SaiB/7D6xbejm7CmZuL2Sz/KCzyAuqKj3G4fWTWCtSYgxYneE6AHYHJiMBr8uEWjdzyePS2PlzhIVBuoBXn75ZZ5//nmmT5/O5MmTeecd7RnTbDYzfPhwFixYAGgegd1u94dqjhw54n8PtPBSQkIC33zzDY8//jhPPvkkc+fO7dKYSI/HwxVXXOFP5v7yl79kyJAhPPbYY0yZMoXp06cTExPD2Wef3eK4m266CY/Hw9SpU7n00kv55z//2eLJvzXHjh3jlFNOYcaMGVx99dX86U9/injNQZFS9tmv2bNnS0XPUe90yZw735d/WbVXVtU55UMr8+QL6w9Kh8stx9z1gXzgoz1Bj/vJik1y6aNrOjz3kr+skctf+CaidX2RVypH/uZ9ubmgss17Ho9XLvjjp/K6FZuCHrv4wc/lkr+skXUOl1z66Jp295NSyh8+87W88G9fhrSmn7+6VZ70wGdttv9n61F9rVUhnaevsXv37t5egqKLBPsdAptlCPdY1Qk8iMkrsSOlNrg7yWri9qXj+fHCUZiNUSRbTe02SjU0eTr0AABGp1k5UtkQ0bp8M3yHxrd9ejcYBEsnZ7B2X7lflM6HlJLiWgd7S+3c/uZ2SmxtS0kDCScEVFLrCFpNdPrEdExRBj5SYSBFP0QZgEHM7iIbAJODlFSmxJmpqGvPALg7zAEAjEyxcrS6IeSa/UB8IaDWSWAfZ03JwOn2sqZViKmhyUOT28voNCsf7SyhpsEV9KbtI95iDD0JHKQqCTQjsig3VReuU2EgRf9CGYBBzK4iG4kx0WQFmWqVYjVRWe8MelwoHsDIlFhcHhnR8JVSu4Ok2GjMQcpMQZs9kGI18dHOlknq6gbNYF2/aDTLZgwDYGgHBiAhJjQPQOqD5TPbySecMzWTYzWNbC+MPKasUPQGSg56ELO72MakzISgZXEpcSaOHAkewgnVAAAcqWpgeHJsWOsqqW3bBBZIlEFw5qR03ttehMPlwRKtraVGT/4mWU38+QfTGJcez5kT09s9T4IlmoYmD26PN2ilkJSSPcV2Pt5VgsPlbXdNZ0xKJ8og+GxPKTOGDwnnoyoUvYryAAYpbo+XvGJbux21KVZzxzkAc+chIICCyvAlkzUZiPYNAGilpvVNnhaduL71JsWaiDFF8bNTx5JkbdsD4CMhRvsM7VUC3fTyVs55Yh1PfJ7PrBFDOHXC0KD7JcZEkxRroqIuuMekUPRVlAcwSDlUUY/T7Q0a/wfNA6hzuls8YftoaHITG92xB5CZYMFkNESUCC61OZiQEd/hPj4DEXjT9YWAkq3RQY9pTYJF28/mcAU1FN8V1nLS2FQevXQGafHtJ5MB4sxR1Dm7Zw6CQnG8UB7AIGWXngBu3wPQboiVrbwAr1fS6OrcAzAYBMOTYsL2ADxeSbm94xAQNHf3VgYkqn0hoCGx7T/1B5IQoxuAdhLBNoeLsUPjOr35g6ZW2roqSRE+gWJr4bB69Wq++uor/+urr766zypw9iWUARik7C62YTIa/Lr2rUmJ0256Va0qgRxuD1IGF4JrTU6KlcNhegCVdU68suPkLUCqvr5AD8AXAhoSE5oHEG/RjFiwRLDXK6lzuv1GojOsZiN1ygD0Gq0NgCI0lAEYpOwqqmV8ejzR7cgkpOhP2BWtKoGax0F2bgBGpMRypKohrPLIUr0HIL2Tp+5YUxSWaEMLD6WmoYkEi7Fd6YfW+ENAjW0NgN3pRkpIsIQWJbWaovwy2Yrw+MMf/sD48eM544wz2Lt3L0BQKWiA9957j/nz5zNz5kzOOOMMSktLKSgo4Omnn+bRRx9lxowZrFu3DoC1a9dy4oknMnr0aL83UFxczOLFi5kxYwZTpkzx7ztYUTmAQYiUkt1FNpZOzmh3H38IqJUH0OD0DYTv/E8nJ8VKQ5OH8jpn0KauYJR0IAMRiBCCFKu5VQ4geCy/PTpKAtt1ryAcD6Agwsa3vsIDGx8gryqv8x3DYELyBH4z7zftvu/T6fn2229xu93MmjWL2bNnc/311weVgj7ppJPYsGEDQgiee+45HnzwQR555BFuvPFG4uLiuP322wF4/vnnKS4uZv369eTl5XH++edz0UUX8corr7B06VLuvvtuPB4PDQ39+3fWVZQBGISU2BxUN7g61NT3h4BaewAu7WYZqgcAcLiyIWQDUNqBhHNrUuNbNqtVNzSFHP+HgBxAkBCQLy8QqgcQp0JAEbFu3Tq+//3vExur/a2cf/75OBwOvxS0D6dT+zssLCzk0ksvpbi4mKamJr/iZzAuuOACDAYDkyZNorRU046aO3cu11xzDS6XiwsuuMAvQT1YUQZgEPKd3rDUXgUQaDd4s9HQxgOo93sAoeUAQDMAocoll+kSzikhPMmnWk1+jwE0A5AW13nC1kecyYgQwUNAPqPgCxN1xkBIAnf0pN6TtO5D8Xq97UpB33LLLdx2222cf/75rF69mnvvvbfd8waKrPnCkIsXL2bt2rV88MEHXHnlldxxxx1hj3gcSKgcwCDksz2lxJuNTM1qv2lJC7GY2shBNPqngXX+7JA1JAaDgMNhVAKV2pwdSjgHkhJnamGgqutdJIXhARgMgnizEVvQEJDuAYQRAmpo8ihV0DBZvHgxb7/9No2Njdjtdt577z1iY2PblYKura0lK0sbJLhixQr/eeLj47Hb7Z1e7/DhwwwdOpSf/OQnXHvttd0ur9zfUAZgkOHxSj7dU8apE4ZiMnb860+JM7eRg/DPAw7BAzAZDWQlxYRVCVQaQhNY6/X5nu5qwgwBAcRbooN7APq2+JBDQNq/R4NL9QKEw6xZs7j00kuZMWMGF154oV/Tvz0p6HvvvZeLL76YRYsWkZraPMrzvPPO4+23326RBA7G6tWr/fN633rrLW699dae/YB9HBUCGmRsOVxNVX0TSya3L5HgIyWurSJoR/OAgzEy2Rq2B5A1JDQDkBpnxuWR2BrdWEwG6ps8ITeB+dD0gNp6AOGGgHweUb3TTVwnPRKKltx9993cfffdbbavXLmyzbZly5axbNmyNtvHjRvHd99953/tMyQ+6uq0jvHly5ezfPlyFBrKAxhkfLyrBFOUgVPGB5c1CCTZampbBeQrAw3xJjcyJZbDVWF4AO2obgYjNaBUNdwmMB8JFmOHSeDQPQBtP5UIVvQnlAEYREgpWbW7hIVjU0J6Sk2N08osA+v4fSGgUJLAoCWCaxpcIY1wdLo9VNU3hR4CsmpJvsq6Jr8MRDg5ANA9gGB9AA4XsaaokHsKfAaxvyeCFYMLZQAGEXkldo5WNbKkg/r/QFKsJpxur/+pHwJCQJ1oAfnwl4JWdR4GKrfrTWAdDHEJJDVe9wDqnM1CcOGGgCzRQfsAbA5XyOEfAKueA1AegKI/oQzAIOLjXSUIAWd0IJEciK8XIDAMVN/kxmQ0hPxknONXBe08DLTtaA0A2UmhyUc3ewDNIaDwPQBjO0lgt79RLBTi/B5A/0sCq0E2/Zeu/u6UARhErNpVyuwRSSGJm0FzLX6gHERjkyekJjAfWUnasJniTgbDeLySJz7LZ0yalQWjU0I6d1JsNEJARRdCQPGWaOxOd5vJZXZnuB6AZgD6mxyExWKhsrJSGYF+iJSSyspKLJbQQqbBUOUKg4R6p5vdxTZ+dea4kI9JCaK4We/0hNQD4CPObMRqivJr/LTH+98Vsa+0jr/+cCZRhrYDaoJhjDKQFKtNLouO0o4ZEhtuCKg5eZsYUPNva3T7k8yhYDX1zyRwdnY2hYWFlJeXd76zos9hsVjIzs6O+HhlAAYJvkqX1BCf/iG4HESjyx1yCaiP9ASLX+IhGG6Pl8c/zWdCRjznTs0M69ypcSYq7E2YjVG6QFx4a2uWhHa1NAAOF6PTrCGfx5cD6G9J4Ojo6A7lFBQDGxUCGiT4bkyhlm9CQAgowAMIZRxkazozAO9sK+JgRT2/OGMchhCf/pvXqDWDVTc0hR3+gZZDYQKxO9zhhYD8HkD/ywEoBi/KAAwSfJUu8WEYAEt0FFZTVIsQUIPTE3IJqI/0BDOl9vYNwN9W72fysASWhtCc1hqfHER1fVPYFUDQrAgaOBRGSomt0RVyDwBoshKxpqh+5wEoBjfKAAwSfLHpuDBuaqCFgQJDQA0ut/9pN1Q0D8AZNNHodHs4UF7PkkkZQYfTd0ZqnJnyOqcmBd1NHkCjy4PbK0PWAfKh6QEpA6DoPygDMEjwh4DCvHknW00thq5E5gFYaHJ7/aWagZTWasYlM0T5h9akxpmwO9yU2RxhdwFDswEI7AXwC8GFEQICnyS0CgEp+g/KAAwS/CGgMD2A1DhTmxxAJB4AEDQMVFyrlYdmdjIApj18ieqiWgfJYVYAQWAIqNk4hSsE50OFgBT9jZANgBAiSgjxrRDiff31KCHEN0KIfCHE60IIk77drL/er7+fE3COu/Tte4UQS7v7wyjaxx8CClOoLMVqpjJg6lZ9kzuiHABASW1bA+DT84/YAATMDYjEA/D9ewSGgGxhTgPzoeYCK/ob4XgAtwJ7Al4/ADwqpcwFqoFr9e3XAtVSyrHAo/p+CCEmAZcBk4GzgL8JIcK7kygiJpIqIIBkXRFUSomUUmsEM4cfAgIoC9ILUFzrGwEZE9Y5fQSWtSZF4AEYowzEmY0tksA2R3jTwHzEDYChMIrBRUgGQAiRDZwLPKe/FsBpwL/1XVYAF+g/L9Nfo79/ur7/MuA1KaVTSnkI2A/M644Poegcu1OTcOhsBkBr0uLMuL2Syvommjxe3F4ZViMYwFDdAwhWClpS6yDebIxYQjnVGmAAwpgHHEhrRdDmEFAkSWCVA1D0H0K9GzwG/Brw6q9TgBoppe9xpxDI0n/OAo4C6O/X6vv7twc5xo8Q4nohxGYhxGbVndh91DncYZWA+shNjwNgX6k9YBpYeB6A2RhFUmx0i/GNPoprGzsdAN8RKQHdupFUAUHboTB+DyAMLSDQhsKoEJCiP9GpARBCfA8ok1JuCdwcZFfZyXsdHdO8QcpnpJRzpJRz0tLSOlueIkTqne6wwz8A4zPiAdhbYg97GEwgvlLQ1pTUOrpkAKxmIzF6929ypB5AjLFVFVB4w2D8azGpEJCifxGKB7AQOF8IUQC8hhb6eQwYIoTw3VGygSL950JgOID+fiJQFbg9yDGKHqYuwklVaXFmkq0m3QD4xkGGf570BAtlQauAHAyLMP7vw+cFhKsD5CPBEt0qBKSFy8KVlYhVc4EV/YxODYCU8i4pZbaUMgctifu5lPJy4AvgIn235cA7+s/v6q/R3/9cah1A7wKX6VVCo4BcYGO3fRJFh9gd7rCbwEAbDj8+PZ49XfYAzG2qgFweL+V1zi55ANBcChppCEgbC9myCijcBDA0zwWuV81gin5CV/oAfgPcJoTYjxbjf17f/jyQom+/DbgTQEq5C3gD2A2sBH4mpVQZs+NEfVPks2rHZ8STX2qnzhG5B5CRYKGizonb4/VvK7M7kTLyElAfqVYTJqMhIsMEehK4sWUjWLjhHwicCqb+rBX9g7D+J0spVwOr9Z8PEqSKR0rpAC5u5/g/AH8Id5GKrlPncDM6NTIDMCEjnoYmD3tL7UBkHsDQBAteCZUBIx9L9CawrnoAI1OsHKqsj0hKAjQPwEh2jioAACAASURBVO5wIaVECKHpAIXZAwABQ2FC9AC8XsnuYhuThyVEvHaFoiuoTuBBQp0zshAQNCeCtx7RJnZFmgSGls1gvh6AzC7mAH61ZByvXb8g4uPjLUa8Eur1EFekISBfh3SoieDn1h/ke39dz89f26Y0hBS9gjIAg4RIk8AA49LjEQK2Hq4GtGRnuGT45CACSkFL/E1gXfMArGYjQ+MjP4dfEE4vBbU1hjcNLHAdENpQGLvDxd9WH2B4cgzvf1fED/72FYcrO5+brFB0J8oADAJcHi8OlzdiA2A1GxmRHMsxfaxjqAPhA/HJQZTam0tBi2ocxJqiInra7k78Q2H0RLDdEd48YB/NQ2E6zwE8t+4QNQ0u/vaj2fzzx/MornVw/YtbOj1OoehOlAEYBNRHqAMUyPj0eP/PsWFKQYBWqRNlEJQGhIBKbFoTWG/Hv4fqchKH9cH1Nocr7C5gCEwCd+wBVNU38fz6Q5w9JYOp2YmcPC6Ny+eP4EB5XZvZxApFT6IMwCAgUiG4QCboeYAog8AUFf6fTZRBkBZnbhECKq51dLkCqDuYlj0EqymKdfnlNLk1bymyMtDQksBPrzlAfZOb2wLmM2ckWjTJjbqOZycrFN2JMgCDgEiHwQQyPiMB0BLAkT6xpyeYW8hBlNQ6yEjoWgK4OzAZDZwwJoV1+RXNXcARVAGF4gHYHS5WfFXA92dkkRvgVflyJMHkMhSKnkIZgEGAr36/SyEg3QOItNYetFJQnyKo2+OlzO7sEx4AwKLcNA5XNrDjWC0Q/iwAaM6NdDQUZuOhKpxuLxfNzm6x3ZcILw4ima1Q9BTKAAwC6iKUgg4kJyUWk9EQ9jCYQDISLP6hMBV1TXi8sssVQN3FotxUAD7cUQyErwME2lxgaydDYb46UInJaGDWyKQW233/DsEUUxWKnkIZgEGAzwBE8lTrwxhlYFx6XNjDYAJJTzBT0+DC4fJ0eRJYdzMq1Up2Ugwf7yoFIgsBgVYi25EB+PpAJbNHJLXRGUq1mjEaREgewJp95XykGyqFoisoAzAI6I4QEMAvTh/HTaeMjfj40WmatPS/vj7s7wHoahNYdyGEYFFuGrWNkSmB+ojrYCpYdX0Tu4ttLByb0uY9g0FoiqkhGIC/fbGfO/79nVIeVXQZZQAGAd0RAgI4Y1I6507LjPj4syZncM7UDP740R5e36yNhugrHgDAYj0MBJF7S1ZzVLtDYTYcrATghDGpQd9PTzCH5AHYHG7qnG7+u+1YRGtUKHwoAzAI6I4y0O7AYBA8cvEMpgxLZPXecsxGQ8QSzj3BiWNTMegFTpGGgKym9j2Arw5UYjVFMS07Mej7mYkxIeUAfJVKL204gia0q1BEhjIAA51V/8spe+4lziSIMvS+4FiMKYpnr5pDeoKZ7KSYXm8CCyQxJpoZw4dgEGCNMNfR0Vzgrw5UMG9UMtHt9FGkJ1gornV0elO3O9wkxkSzp9jm12dSKCKhdx8JFT1P3ofMqDrAXUYDcE5vrwbQKl7e+umJfXJ84mVzR5AYEx2xYbK2YwBKbQ4OlNdz2dwR7R6bmWih0eXBpt/ggyGlxO5wsfzEHN7cXMjLGw4zu1VFkUIRKsoDGMhICbZjNBjiuNz7HnzzTG+vyE92UiwT9OayvsQlc4fzjx+3UTkPGas5KmgfwNcHfPH/tglgH+mJbRVTW1Pf5MGrz1D4/sws3t9RTHV9U8TrVQxulAEYyDRUgdvBO4mX841pPqz8DRSs7+1VDWisJmNQaeevDlSQGBPNpMz2jZ4vId5RN7Av/h9vieaKBSNpcnv5+9qDXVy1YrCiDMBAxlYIQKFM46nk/4EoE+xb2cuLGthY25kLvOVwNXNzkjF0kIfJaDUoJxi+yWUJlmjGZ8RzyZxsnl5zgE92l3bD6hWDDWUABjK1WpngUXcS0bFxkDIWyvf18qIGNsEE4Rqa3BysqGfysI5DXkN1yeyS2vYF4Zo9AO069y2bwrTsRH75+jb2l9V1ae2KwYcyAAMZm2YACtxJxJuNkJoLFcoA9CTB5gLvLbEjJUzqxACYjVGkWE2U2DrwAFoZAEt0FE9fMRuz0cAN/9pMYzs9CApFMJQBGMjUFoIhmkKnVbsxpY6DmsPgUnozPYVvKExghdOeYm2Wckfxfx8ZiZYOk8B2vas7sE9h2JAY7r9gCgfK6/n2SHVE61YMTpQBGMjYjiEThmFv8mpS0KnjQHqhSiUNewqfWF5gInh3cS3xZiPZSZ3LXmTovQDtYXME13XyGZcipSaqCANlAAYytceQCVm4PFKLTafmattVGKjH8M8FdrT0ACZmJoTUW5CRaOmwG9jWjlZRRmLnCWSFojXKAAwQ7A4Xf1m11x8jBsBWiMuqaffEmY1aEhigIr8XVjg4GJ1mBWBbodah6/VK9hTbOo3/+8hIsFCtK6YGw+5wY4oyYDa2/K9riY4i2WpSHoAiLJQBGCDc995unvh8Px/vLNE2eL1gK8YRG2AATFZIHAEVe3txpQOb9AQL07IT+VQvyzxS1UBDkyek+D90PhfA7nARbzEG9SYyO8kfKBStUQZgALBqVwlvbtFq/nfqE62oLwOvi3pLBhAwDlJVAvU4Z0xM59ujNZTbnewutgEwMUwD0N6N3OZwtytUl5looahGhYAUoaMMQD+nos7JXf/ZwYJ0yQfxf6T0SJ72ht4DYDOlAwFKoKnjtBCQ1xvaBeylsO2V0PdXcMbEdKSEz/NK2VNsI8ogyE2PC+nYzmYD+zyAYGQmxqiZwoqwUAagn3PPO7uwO9w8fKKbya6djC37FLfH6+8Cro1OAwINQC64GsBe1PnJvR54czn896fw6W976iMMOCZmxpM1JIZPdpexu8jGmDRrmwlg7dGpB9DYvgHISLRQ0+BSvQCKkOnUAAghLEKIjUKI7UKIXUKI3+nbRwkhvhFC5AshXhdCmPTtZv31fv39nIBz3aVv3yuEWNpTH2qw0Njk4aOdxVy9MIdsUQ7AbHaTX1bn9wAqjUOBgGEwqeO076GEgTb8DY58Ddlz4au/9ikxub6MEIIzJ6Wzfn852wtrQ47/g6bxYzVFtVsKane4251WNmyIb7B8ZGGg7wprqFLCcoOKUDwAJ3CalHI6MAM4SwixAHgAeFRKmQtUA9fq+18LVEspxwKP6vshhJgEXAZMBs4C/iaEiHzArIK8EhteiSYHXHMEgLmGvew8Uql1ARtjqPJoVSn+p0afAehMEqJsD3x2P0z4HlzzMYw/Fz76NeR90FMfZ0BxxsR0HC4vFXXOkOP/PoYmWCivCy4HYXe42/cAErQ+g1CmirXG7fFy2TMbeHiVKhAYTHRqAKSGT2QkWv+SwGnAv/XtK4AL9J+X6a/R3z9daCULy4DXpJROKeUhYD8Que6ugl1FWoJx8rAEvwGIEw4q9m+E2qOQmEW9Hg7wh4DihoIlsWMPwN0Eb98I5jj43mNgiIILn4P0KfDp73r0Mw0U5o9O9t+oQy0B9ZFsNVFVF/xJ3OZwEd+JBxBJIvhodSMNTR42F1SFfayi/xJSDkAIESWE2AaUAZ8AB4AaKaWv26UQyNJ/zgKOAujv1wIpgduDHBN4reuFEJuFEJvLy8vD/0SDiF1FNhJjoskaEqPd8NOnABBTtEELASVkUed0IwTE+iZcCaEngtsxAF4PvH09FG+D8x6HOC2HgCkWJl+glZA2qJtEZ0RHGThlvBZ+C9cDSLGagoZi3B4vDU2edkNA6QmdzxNoj/xSTa5iX2kdtY2uTvZWDBRCMgBSSo+UcgaQjfbUPjHYbvr3YO2OsoPtra/1jJRyjpRyTlpaWijLG7TsLqpl8jC9w7TmKGTNosIykhz7t0jbMUjMxu5wE2dqVTfuqwQq3Q3/+j78dQ5s/Rd43PDBr2DX27Dk9zDxvJYXHK47bMe2HL8P2Y+5+dSx/M85E0iNM4d1XEqcicr6tiEgn75QeyEgS7QmJhdJM1h+gJKo0hMaPIRVBSSlrAFWAwuAIUII319iNuArKykEhgPo7ycCVYHbgxyjCBO3x0teiV0L/7gatbr/ISOoy1zAbJEHdaWQkEW9093cA+AjNRfqSuDpk+DYVu3p/t2b4S8TYcs/4KRfwom3tL3osFkgDFC46fh8yH7O+Ix4rl88Juzjkq0mqhtcbWYK+GcBdDCwXhOTCz8EdKCsjmSrCYOArYeVARgshFIFlCaEGKL/HAOcAewBvgAu0ndbDryj//yu/hr9/c+lNuX6XeAyvUpoFJALbOyuDzLYOFBej9PtZfKwRE31EyBxBLHjTiFeNCKkFxK1EJC/AsjHiBPBYIQ518DPv4Xr18ClL0F8Bsy7AU6/J/hFzXEwdDIcVb+2niTFasbjlW1CMa2loIORmRgTURI4v6yOycMSmJCRoAbNDyJCGQqfCazQK3YMwBtSyveFELuB14QQvwe+BZ7X938e+JcQYj/ak/9lAFLKXUKIN4DdgBv4mZRSFSxHyK4ireNXSwDv0TYOGUHa6FHwsfZSJmRR0+BqTgD7GDEf/q9Cywf4mHhe25BPMIbPhR3/1hrDDKqNpCdIiTMBUFnvJMlq8m+3t6MEGkhmooVNYSZyvV7J/rI6fjhvBDkpXv6ztRCPVxLVwfQyxcAglCqg76SUM6WU06SUU6SU9+nbD0op50kpx0opL5ZSOvXtDv31WP39gwHn+oOUcoyUcryU8qOe+1gDn11FNizRBkanxWnxf4AhwxHxGRQZswH45coKvj5YSe7QIF2oIShTBiV7HjhtUJ4X4coVnZFi1XIGla0qgXweQHtJYIDMIRZqG11B5xK3x7GaRhpdHsYOjWP2yCTqmzzsLbFHsHJFf0M9wvVTdhXVMiEjQXtKqzmihXTiNeG30uS52j518dy/bDL3XzCl+y6crZ1b5QF6jmT9qb91JZB/GExHBiDR1wwWehjIN0oyN10zAABbVCJ4UKAMQD9ESsnuIlvzjNnao5CQpdXrA2MuuJu8Offz4a/P4coTckKWIQiJlDEQkwyFKg/QU/hCQBWtDIBvFkBnOQCA4prwDcDYtDiyk2JIizerRPAgIZQcgKKPUVjdiM3h1hLAoHkAQ0b4308YlkvCsNyeubgQmhdwVHkAPUVSrO4B1AX3ADrLAUB4chD5ZXZS48z+fMPsEUlsUQZgUKA8gH6ILwHs7zCtOdrCAPQ4w+dqDWGN6ibRE5iMBhIsRqpa9QLYHS5iTVEYo9r/b+trBgsnBJRfVtciTzR7ZBJHqhoosytl0YGOMgD9kF1FmsTwhIx4TbbBXgyJwzs/sLvw5QFUQ1iPkRJnbhsCcrg6jP9DczNYqAZASsn+0jrGBhiAeaOSAfjgu+IwV63obygD0A/ZXljL2LQ4LbZvKwTk8fUAsmZrDWGH1h2/aw4yUoLoAXUkBBdI5hBLyCGgMrsTu9PdYl7BtOxEFoxO5skvDoRVTaTofygD0M/weCVbD1czd5RWreETgWPIcfQAzPEw5jTY8aamHaTodpKD6AGFagAyEmJC1gPKL9UTwAEegBCCO5aOp6LOyT++LAh90Yp+hzIA/Yw9xTbqnG7m5mhuenMPwHH0AABmXqFJTh9cfXyvO0gIpgdkc7g6lIHwkZ0UQ0FlfUheQH6ZVu+fOzS+xfbZI5M5fcJQ/r7mALUNShxuoKIMQD9j4yGty9MXp6X2qBaOSWgjrNqzjD8HYpLg25eO73UHCSlWM1X1TS30gDQPoHMDcOUJIzEIwa2vbdOmw3VAflkdiTHRpMaZ2rx3+9Lx2Bxu/r72QPgfQNEvUAagn7GpoIrspBh/vTc1RyB+GER1fmPoVoxmmHqxNiBGVQN1O8lWE14JNQF6QB2NgwxkTFocv79gChsPVfHE5/s73PdoVQM5KbEt1WJ1JmYmcN70Yfzzq4JODYmif6IMQD9CSsmmgirm+cI/oJeAHsf4fyAzLgePU9MGUnQrvmawwFLQjsZBtuYHs7K5cFY2f/08n68OVLS7X5nNyVC9dDQYi3JTaWjycCyCITOKvo8yAP2IQxX1VNQ1MXdUoAE4cnxLQAPJnA7pU2Hby71z/QFMaz0gh8tDk8cbkgfg475lk8lMsPDcukPt7lNmd5Ce0P68gtGp2kjRgxX1IV9X0X9QBqAf4VN59CeAG2ug9kjznN/jjRAw83Io+labIazoNnx6QJV6JZBfCC6EJLAPq9nInJzkdoXdnG4P1Q0u0uPb9wBG6QbgULkyAAMRZQD6ERsPVZNiNTEmTftPybHN2vfhc3tvUZP0UdD7Pu69NQxAUuNaGoBmIbjw1FvGZ8RzrKbRP00skDKbFl5K7yAElGw1EW8xckh5AAMSZQD6EZsKqpiTk9ScsDu6CRBaY1ZvkZCpzSLe/2nvrWEA4tPl8TWDhaIDFAyfxINv5m8gZXbNAKR1EAISQjA61UpBpTIAAxFlAPoJpTYHR6oamsM/oEkyD52kNWb1JmPPgCNfg8PWu+sYQERHaXpAvl4AnxJoqElgH+PStb8NX8NXIGU2rVmsoxAQaGGggyoENCBRBqAfsLfEzt1v7wAC6v+9Xijc3LvhHx+5Z4LXDYfW9vZKBhSpceY2IaBQ+gACGZ4ci9loYF8QD6DUZwA68AAARqXGUVTbiMOlur4HGsoA9GG8Xsltb2xj6WNr+fpAJb84I5epWboEdMU+cNZqE7p6m+HzwRQP+z/p7ZUMKJID9IBCmQccjCiDIDc9jr3BDIDdSXSU8MtPt8eoNCtSwuHKhrCurej7qHkAfZij1Q38Z+sxLpyVzf+eO7HFfFj/QJbhfcAAREXD6JMh/1OQMvJxk4oWJFtN/tj7vlI7RkPnN+tgjBsaz1cHKttsL7M5SYszY+hk9u+oFL0SqKKO8Rm9HG5UdCvKA+jD+MTAzp2W0fLmD1r83zIEksf0wsqCkHumpkxavre3VzJgSInT5CDsDhdvbi7k3GmZxJjCn+6Wmx5Pic1BbWNLTZ8yu6PDJjAfOamxAByqUB7AQEMZgD5MdYNmAII+9R3dpOnyG/rIr3DsGdp3FQbqNlJ0RdDXNx2lzunmmoWjIjrPOF3qeX9ZyzBQqa3jJjAf8ZZo0uLNHKpom0hW9G/6yN1DEYyqeu2JLdlqAmcdbHsV3E5w1EJ5Xt8I//hIzIa0iaoctBvx6QE9veYgc0YmMX34kIjO46sE2lvS8gZeanN22AMQyKhUq+oFGIAoA9CH8enAJFtN8M1T8N8b4fklsPMtQDZP5uor5J4JBV9qHcqB2Eu1qiVFWPiHw9c5ueakyJ7+AbKGxBBrimpRCeRweahtdDE0vnMPALQ8gDIAAw9lAPowVfUuoqMEcWaj1mmbOByqD8H7v6TXG8CCMekC8Lpg74fN2yry4dHJ8Na1anhMmPj0gLKGxLBkUnrE5zEYBLlD4/za/wDlehNYKDkA0CqBKuqa/NVIioGBMgB9mOr6JpJiTYj6Cq3mf+aVcMM6rfRz1GKwJPT2EluSNUsbTLPzP83btq7QegR2/QfeuVl5AmGQkajdnK8+MafDQfChkJsez76AZrDmHoDQQ0AABcoLGFAoA9CHqWpo0sI/+z8BJIw/C5JGwnWfwFXv9Pby2iIETP4+HPwCGqq0gfXbXoWJ34NT74btr8AHt2mloopOGTs0jtevX8CPF+Z0+Vzj0+Mptzup1ivLSnUdoFBDQD5VUBUGGlgoA9CH8XkA7FsJ8ZmQMa35zb5aaz/5+9oTf977sPcDaKiAWVfD4jvghJthyz+gZEdvr7LfMH90Spef/gH/0HdfHqDMHp4HMCIlFiFQkhADjE7/soQQw4UQXwgh9gghdgkhbtW3JwshPhFC5Ovfk/TtQgjxhBBivxDiOyHErIBzLdf3zxdCLO+5jzUwqGpoIi1WwP7PYdzSvnvTDyRzBiSNgl1vw5YVWt5izKna2k/8ubZP60qhhirwqNhyTzIxUwsXbi/UEvSlNl8XcGjSEmZjFFlDYpQHMMAI5dHCDfxKSjkRWAD8TAgxCbgT+ExKmQt8pr8GOBvI1b+uB54CzWAA9wDzgXnAPT6joQhOdX0TM+UeaLLDuLN6ezmh4Q8DrdEGxs+8Agx681J8ujZA5sDnzfu7HPDkPD2xregp0hMsTMxM4JPdpYAmBDc03hJ0FGR7jEq1clipgg4oOjUAUspiKeVW/Wc7sAfIApYBK/TdVgC6MDzLgBelxgZgiBAiE1gKfCKlrJJSVgOfAP3krnb88XglNY0upjd8DUYLjDq5t5cUOpO/D9KjD4y5ouV7Y0+DIxu0vgaA/FVQX64Nly/dffzXOohYMimdzYerqahzUmZ3MjSEJrBAcvRSUKlyOAOGsIKLQogcYCbwDZAupSwGzUgAQ/XdsoCjAYcV6tva2976GtcLITYLITaXl5eHs7wBRU1DE0J6GVvzpVbxY4rt7SWFTsZUGDoZxp+jNYgFMuZ0rVS0YJ32+rvXwZoG5gT47L7jv9ZBxNLJGUgJn+0p1bqAO5GBbs3IlFhsDjc1DSpcN1AI2QAIIeKAt4BfSCk7En4P5lPKDra33CDlM1LKOVLKOWlpaaEub2DhcePe+gqfmO4gofFo89St/oIQcM1H8INn2743YgFEx2p5gIYqzQOYegmcdCvs+wgOf3381ztImJgZT3ZSDB/vKg1ZBiKQHF0UTg2HGTiEZACEENFoN/+XpZS+Iu9SPbSD/r1M314IBE4pzwaKOtiuaM3rl5P++S9wYmL3ov8HM37U2ysKH0ticK/FaIacRbD/M9j9DniaYNolMP+nEJcBn96rykR7CCEESyZlsD6/ApvDHXITmA+fKJyShR44hFIFJIDngT1Syr8EvPUu4KvkWQ68E7D9Kr0aaAFQq4eIPgaWCCGS9OTvEn2bIhB7CexbyaHcH3NO0x/xTji/f1T/hMPY07WO5i8fh9TxkDldMxan/AaObtD6CBQ9wtLJ6TR5tGa8UHsAfGQnaaWgygMYOITiASwErgROE0Js07/OAf4MnCmEyAfO1F8DfAgcBPYDzwI3AUgpq4D7gU361336NkUgez8CYE/GeYDw68EMKMacrn2vPqQ9/fsM3IzLNYnrba/03toGOLNHJmnNhYTeA+DDEh3FsMQY5QEMIDodCCOlXE/w+D3A6UH2l8DP2jnXC8AL4Sxw0JH3ASTlcEiMAPZFNACkz5MyRpOMqDkCUy9u3m40w5QLNQPgsPU9qYsBgDHKwOkThvLmlsKwDQBoYaBwPACXx8vrm46ydHIGaWF6HIqeR3UC9yWcdji0BsafS1WDi1hTFJbo8AeA9HmEgPk3wuwfa9IWgUz/IbgbtfyAoke46oQcTh6XxsiU8CvLRqZYw9ID+s/WQv73vzu57Jmv/UPoFX0HZQD6Evs/05KiE85ploEYqJzwMzjvsbbbs+dAyljY/urxX9MgYWp2IiuumRfRw0VOSizVDS5qQygF9Xolf197kBHJsRTXOrjsmQ1+ETpF30AZgL7E3g8hJhmGL2gWghtsCAHTL4PDX0J1QW+vRtGKkXop6OGqzr2AT/aUcrC8ntuXjmfFNfMotTn40bMbaHIrRdi+gjIAfQWPSxN9G3cWRBmprh+kBgBg2mXa9+/e6N11KNrQ3AvQcSJYSsnTaw4wPDmGc6ZkMDcnmQcvms6B8nq+OlBxPJaqCIFOk8CK48Thr7RRjxPOATQhuNFpcb28qF5iyHCtV2DjM2AvhvhhWvdw9WGoOQz1FeCoAREF132q7a84LvjyBoc7yQNsKqjm2yM13Ldssl/N9PSJQ7Gaoli5s4RTxg/t8HjF8UF5AH2FvR9qmj9jTgOgut41sHMAnbHoV1pj2K7/whe/hzUPamEhEQXpusxEfTlseq63VzqosERHkZlo6dADsDlcPLxqL8lWExfPHt7i2NMmprNqdylujwoD9QWUB9BXOPHnMPpUMFlxuj3UOd0kW0OT6h2QjDkVfrpe+9nl0HIDxlZlhI1VsPVFOOUuiA6/pFERGSNT2i8F/XhXCb99Zyfldie/v2AqMaaWieazp2Tw3vYiNhZUceKY1OOxXEUHKA+gr5CYpU38Ar/YVtJgzQG0JtrS9uYPMPcnmhHY9fbxX9MgJicluCz002sOcMO/tpAUa+Ltmxbyo/kj2uxzyvg0LNEGVu4sOR5LVXSCMgB9kMo6bWxf8mAOAYXCqMWQOg42BRGdU/QYI1O0AfH2VgPiX990lHmjknnvlpOYPnxI0GNjTUZOHpfGyp0leL1K86m3UQagD1LdoBsA5QF0jBAw9zo4tgWObe3t1QwaclLaisIdqqjnUEU950zJILqTEZZnT8mkzO7k26M1PbpORecoA9AHqapXBiBkpl8G0VZY94gmL91VpASvSlB2RI4+ID7QAKzeq4kBnzYhvdPjT5s4lOgowcqdxT2zQEXIqCRwH8TnAagcQAhYEmHedZqy6N6PIOckrUooOkYbMjPnmvY1hRw2cNrAHA+uRq3v4NuXwNUAP/kc4lSpYjByUqyYjQbW7ivn3GmZAHyeV8boNCsjQpCXSLBEs2B0CuvyVT9Ab6MMQB/E5wEMiRnEVUDhcMbvtKE5ee9D3odQ9C001WtjKV0NcOr/tD2m6iA8c4rWexFI9jxNpO6ta+HK/zbPM1b4iTFFcfGcbN7YVMivlowjzmLkm4NVXHnCyM4P1pmWncjf1xzE4fJ0KEnx7ZFqHlm1j3mjkvn56bndsXxFAMoA9EGq65tIjIn2N9AoOkEIyJqlfZ3+W22blPDqD2HT83DSbS3LRL0e+O9N2j7nPqKVmXrdWm9B2jj49mV45yZY/Sc47X975zP1ca5fNIZXvjnCC18WMHtkEk0eL6dNCN1jmpSZiNsr2V9Wx5SsxDbvV9Y5uf/93fx3WxFGg+Drg5UsmZzOhAylENudqDtMH6SqwaXi/11FCDjhJmiogB2tJCU2/A2OfA1nP6AlkU+8GU76hXbzB5h5Ocy8EtY+BPmfS4Uq9gAAIABJREFUHP+19wNGpMRyztRMXt5wmHe3F2E1RTE3Jznk4ycN027ku4uCT5d99NN9fLCjmJtPHcuaX59KgsXIPe/sUgPpuxllAPogVfVOZQC6g5xFkD4Vvv5b85jJsjz47H4Yf64mPd0e5zykDbZ/5+a2YSIFADeePAa7081724s4KTcVkzH028nI5Fispih2Fwc3AFsO17BgdAq3Lx1P1pAYbl86nm8OVfH+dypx3J0oA9DHkFJyrLpRGYDuwOcFlO+BA59rg+j/9X0wWTUp6o5GbUbHwLL/B/Vl8Nl9x2/N/YgpWYmcNFbr5j01TG0fg0EwMTMhqAfQ2ORhX6md6dnNvQSXzR3BlKwE/vjhHhqa3F1buMKPMgB9jM2HqymobAgrnqrogCkXQlw6vH0DvHShVvFz5duhVfhkzYJ5N2h5hKMbe36t/ZBfnjmOCRnxnDGp8/LP1kwalsDuYlubhrDdxbV4vLJFM1mUQfC78ydTXOvgkVX7urxuhYYyAH2MF78+TLzFyLIZw3p7KQMDoxkW3KQpiJ74c7hhLQybEfrxp90NCcPgvVs1yW5FC2aPTGLlLxaTGhf+uMdJmQnUOd0UVje22L7tqBZym57dMjk8e2QyVy4YyQtfHmJTgRon3h0oA9CHKLM5+GhHMZfMGU6sSRVodRsLb4Xb82HJ/eGLxpnj4ZyHoWw3fPN0z6xvkOJPBBe3zLF8V1hDZqKFoUFmFt959gSyk2K4483tNDZ5jss6BzLKAPQitY0u/vTRHr+w1qsbj+L2Sq5YEHo9tSIEhIC4tMiPn3AOjD1TqwoK7DZ2NUJjddfXN0gZlx5PlEGwq1UeYPvRGqZlty0NBbCajTx44XQKKht48OO847HMAY0yAL3Iy98c5u9rDvK9J9bz3vYiXtl4mJPHpTFKb7VX9CGW3A9OO6x5QHvdWA3PnQEPj4cP74DaY22PKd4O6/4CbufxXWs/wRIdxZg0a4tEcG2Di4LKBqZlBxeTAzhhTArLTxjJP78qYOsRZYC7gjIAvYSUkn9vKWTysARGp1m55dVvKbU5uSqMbkrFcWToRJh9tTaApmgbvHwxVOzTvIPNL8Dj02H1n5t1hMr2wIrz4bPfaZVH3aFTNACZlJnQohT0u2OaQNyMdtREfdxx1gTS4y3c/fbOiIbLFFY38MDKvKCy1oMJZQB6ia1HajhYXs/yE3N488YTue6kUZw2YagalddFXt7zMl8Xfd0zJz/lf8AYA8+fqamPXvQCXPxPuGUrTFqmdQ6/fgWU7tJu+kYLLP0jFG6GZ0+Div09s65+zORhiRTXOvzyJ9t1hdBg3cGBxJmN3HPeJPYU21jx9eGQr1fT0MQfPtjNaQ+v4anVB3h4kFcUKQPQS/x7y1FioqM4Z2omJqOB//3eJF64ei5Rhg5q0/sJG4s3svyj5Tz73fHV6ZdS8sTWJ3h+5/M9c4G4NDj5Dq0a6IKnYOJ52vakkXDhc3DWA7BvJTx1oqZBdOV/4ISfwdXva6Jz797cM+vqx/gSwXt0L2B7YS2j06wkhqCDddaUDE4dn8ZfVu2luLax0/03FVSx5NG1PL/+EBfMHMYPZmWxcmcxZXZH1z5EP0YZgF6gscnDe9uLOWdqJnHmgVPtc6zuGDd/djPXrrqWrWVbeXt/907qklKyYtcKCu2FQd+3NdlocDewo3wHHm8PVYic+HOtomj6pS23CwELboSr/gsjToTL/62pkgIMn6dNLzuyAeore2Zd/ZRJmZoBeH79IcrtTrYfrWnRANYRQgh+d/4U3F7Jnz5sPyEspeSF9Yf44TMbsJqNvHfLSTx40XRuPnUsLo/k9Y1HI1q7y+PF6e7flUjKAPQCH+8qoc7p5uI52b29lG7jiO0IV310FZtLN/OLWb/g1lm3ctR+lNL60m67xobiDTy8+WHePfBu0PeP1WmJ2AZ3A/treijc0llF0ajFcM1H2k0/kPFnARLyV/XMuvopSVYTvz5rPOvyyzn14dWU2Z1t6v87YkRKLJfMGc4nu0txtZMLeGXjEe57fzenThjKOzcvZPIw7fyj0+JYlJvKKxuPhJ1H2HmsltMeWc25T6yntqH/9od0agCEEC8IIcqEEDsDtiULIT4RQuTr35P07UII8YQQYr8Q4jshxKyAY5br++cLIZb3zMfp+0gpeX3TUYYnxzAvDPGsvsxR21Gu+fgamjxNrDhrBddOvZYTh50IwNayzid1NbgacHs7b+9/Ne9VAIrqioK+X1zXrBOzvXx7KEs/fmRMh7gMLUSkaMFNp4xl5S8WM314IkLA/NEpYR2/YHQKjS5Pu8Jya/eVMzIllr9fMZsES8vQ0pULRlJc6+CzPG2gzdGqBg6U13V4vX9vKeTCp76iye3lcGU9P315S7vGp68TigfwT+CsVtvuBD6TUuYCn+mvAc4GcvWv64GnQDMYwD3AfGAecI/PaAwmahqauP5fW/j6YCVXzB+JoZ/G+6WU/Gr1r7js/cu47uPruGrlVTg9Tp5b8hzjk8cDMD5pPNZoK1tKt3R4Lq/0suydZTyx9YkW2ysaK1hZsNKv/nis7hhrCtcAUFQf3AD4PIBYYyzbyrZ16TN2OwYDjFuqaRK5mzretyxPm2ngGTyaN2PS4njp2vls/J8zmJgZnuTz3P/f3nnH13j9D/x9sqfIlCmREGKT2LRBqV1aWlp+qsNXdavuatH17fhWN1WbtmrXqBo1aleESIyExEpkyd7rnt8fz82VK+smSILn/Xp53XvPPc+553k8OZ/nfKaPspRUFh0cEZdJe8/GFf699WvlgrudBT/uieaFX0O5/4vdjPzhAJn5FT/VrwuNZfrqMAK97dnyUh8+fbg9B6NTmLEhgmvZBew7l8zaY7Hl6iU3VKoVAFLKf4Abr+xDwFLt+6XAyDLty6TCYaCxEMINeBDYIaVMlVKmATsoL1Tuak7GpjPkm33siUxixrDWTL7Pt76nVGuu5V1j+6XtFJQUUKgpxKeRj97iD2BsZExHl47VCoCotCgSchJYf349RWVSLXz272e8vvd1fj37KwCrIpWUzp1dOle+A8iJx8rEiu5u3TmRXLEA2H5xO+vP3VrbhMH4D1KMwZcPVt4nI07xGJofDJ/5KPmLEsLraob1ihACZ9uap5RwaWSBt6MV/14oLwBSsguIS8+jfSVeRSbGRjzerSlhV9LZG5nMmEAvsvKL+fXI5Qr7r/z3Cs1dbFj2VFecbMwZHejJ1GA/Vh69QtBHO5mw8F9eWx3G/V/sYfGBCxQWN+ydQW0tkE2klPEAUsp4IUSp76IHUNaiEqttq6y9HEKIySi7B5o2bVrL6TU83lobjkbCmik99ZJc3YnEZMQA8EaXN+jh3qPSfkFNgvgm9BvS8tOwt6h4w3c04SgA6QXp/BP3D/2b9iclL4Wdl3diZWLFF0e/wMvWi3Xn1tHPqx/ejbxZemopJZoSjG+o1hWXHYe7jTsdXTqy68ouUvJScLTUVyfMOTaHpNwk+nj2wcnS6WYuQ83xvR+MzSFqG/gGKymqc1PBuswct70NUgPDv4H4k0qVs4UPwsPzIWBY3c73DiLI24HdkUlIKRFlsryGxylpJqpyK32mjy9NHa0JbulMIwtT4tLzWLj/Ak/29NGrVhafkce/F1OZNsBfr1jT9IEtcbOzoKBYQ2u3RpgYG/H1zihmbTrNxrCrrHuup96cGhK32ghc0VnKKtrLN0o5X0oZJKUMcna+ifD9BsTFazmcjs/kmT7N7vjFH64LAF+7qncxgU0CgartACEJIXjYeOBk6cSm6E0AbDi/gWJNMQsGLsCnkQ8v7nqR9IJ0xrUah7uNO8WymOS85HJjxefE42btRgfnDkB5O8CVrCvEZsdSqCnk1zO/Gn7Ctwoza0UIRG5VFv5VE+ALX6WgvZRw/m84/Qfc95oSdDbsKyV5nUsr+P0J2PUxpERfr22goqNrM3tScwqJTtYP7IrQCoA2HpWrlSxMjRnRwV1nH5hyvx/JWQWsP64f3b1FW4tgmLYOcilGRoIJPXx4po8vPZs70bWZA788041pA/w5fjmdK6nVu6jWF7UVAIla1Q7a1yRteyzgVaafJ3C1ivZ7gq0RCYDit3w3EJMeg7WpNS5WVQettXFsg7mxeaVqII3UEJIYQlfXrgxtNpS9sXtJzU9lTdQagpoE0c65Hd/1+w4bUxuaN25OF9cuuNsoWVIrUgNdzb6Ku407rR1bY2JkUk4AlAaIBTgEsDJyJTlFVUeBXsu7RlZhVpV9aoz/g5B2AX7opgiCpj2VegMbX1BSSjj4Ka6mpdi6wpNboO1o+Odz+K4zfOkPm1+F7KTKf+ceo7Qa2Y12gPC4DJo5WZcz/lZFr+aOtPOw46e90ZSUSVW96WS8NnLfptoxhBAM1v69H4q5ZvBv1zW1FQAbgVJPnonAH2Xa/0/rDdQdyNCqirYBA4UQ9lrj70Bt2z3B1oh4Ong1xtPeqr6ncku4kHEBXzvfare1ZsZmtHduX6kAOJd2jszCTLq4dmG433CKNcXMPDiT2OxYxviPAcCrkRdrhq/hpwE/IYTA3VorAG4wBGcXZpNZmIm7jTsWJhYEOASUMwQfunoIV2tXZnSfQVZhFmui1lQ5/6k7p/L0tqcN8lAyGP9BIIyV3cDT22HSn3D/m3B8BaRGK5XITG7Qg5taKoFmz/8Lw+ZAsz4Qugy+7Qz756i5hoBmTtY42ZiVEwARcZnVRhXfiBCCKff7cTElly3hylP/5ZRcwq6kM7yD4Wnam7vY4GRjzqHoimM/zidlMfWXY8zceIqF+y9wPukWP2wYQLU2ACHEb0Aw4CSEiEXx5vkvsEoI8TRwGRij7f4nMAQ4D+QCkwCklKlCiA+Bo9p+s6WU90RylCupuZyMzeDtwa3qeyq3jJiMGJ2bZ3UENglk/sn5ZBdmY2Om/+RUqv8PahKEm40bLe1bsvvKbuzN7XnA+wFdPzcbt3Lvb9wBlAqE0h1CB+cOrI5aTVFJEabGppRoSjiScIQB3gNo59yOLq5dWH56OY+3ehxT4/JPhxqpITo9mkJNIUtOLeGZds8YdL7VYucJzx0AOy8w116Pvu+AcyvIiIXm/Ss+Tghwbqn8C3pKSSux/T3YORMu7oexv4FJBVXkCrKU3EUJ4ZB8VhE8Ni7QuCk0fwAsarY4NlSEEAR5O+gJgNScQuLS83iyp0+NxxvU1pVWrra8sSYMG3NjziYoi/PQdm7VHKk/p+6+DhyOSS1nmwBYfugS204lYmlqTHZBMV+bm7D1lT51+qBoiBfQOCmlm5TSVErpKaVcKKVMkVL2l1K20L6mavtKKeXzUko/KWU7KWVImXEWSSmba/8tvp0n1ZD4S6v+GdzW8BunIZNZmElyXjK+jQ3zYgpsEohGaiq0AxxNOIqnjaduUR/up6RWGNl8JGbGFZfEtDSxxMHCobwA0H4u3SF0dOlIQUkBZ1LPAHAq5RRZhVn0cFOM1pPaTCIxN5G/Llbsl5+cm0yhphAbUxvmnpjLhYwLBp2vQbgEXF/8S2n7MPR6qeL+FeHUHB5fCcO+Vkpdrp8MZaOfsxJhx/vwv1awdJhiXD6zSdk57JwJa55SVEmrJsLFA7fktOqbLs0cuJKaR0KGktrBEANwZRgbCZY/3Y3mLjY8u+wYC/ddoFPTxng51Gxx7u7rSEJmPhdTcvXapZTsikwi2N+Z8JkD2fHqfWik5LVVYXpqp9uNGgl8m/kzIp62Ho1o6nh3qH9i0g0zAJfS0bkjduZ2OjfOUkr1/0GuQbq2kc1HMsJvBE8EPFHlmO7W7sTn6BcH1wkA7Q4gqEkQliaWfHf8OzRSw8GrBxEIurl1A6C3R28cLBx0u5AbKY0peKvrW1iYWDDz4Ew0sgG69AVNggEfwqn1StnLXR/BitHwdTs4+J1ic3hiLbwWBW9egHfi4O04eHoHdP4/uLhPERDHllb/Ww2cG+MBwmOVxHJVGYCrwtnWnJWTe9DD15GUnEKGta95lb4efoqH141qoOjkbK6k5tG3lQtCCFo0seWDEW04ciGVBftiajXf2qAKgNvI1fQ8jl9Ov2ue/gHdk7ChAsDCxIIJARPYG7uX0ymnde1l9f+l2Jnb8XHvj2liXXV9WTcbtwp3AObG5jhaKH9wjpaOTA+azuH4w/we+TuHrh4iwDFA544qhKCFfQui0irOBhmbreQb6uDcgTe6vEFoUmg5IdZg6PUS9J4G4auV+gOZV5XF/YUQJWNpiwfAtsw1NbdRUlUM+QJePgl+/WDTS7D38zvaw6i1WyPsLE35cU80GXlFtTIA34iNuQmLnuzCD493ZkItCjX5OlnjYmvO4Rh9AfD3GcWA37dM7e8xgZ4MauPKl9sjOakVXrcbVQDcRjacUJ4iB99h3j/74/YzZccUvQW7lJiMGMyMzPCwqTCMo0IeD3gcW1Nbfgr7SddWVv9fU0p3ALLMYnU15ypu1m56etYx/mPo5d6Lr0K+4mTySZ36pxR/e3+i06MrTBwXmxWLQOBu484IvxF0d+vON6HfkJR73fNGSkmRpoFEfD7wAbwSDm/HwtSDMPRLcPSr/jhzGxi3EjqMg90fw8Fvqz+mgWJibMQ3YztyPimLSYv/JexKRq3UPzdiZmLE0PZK1t6aIoSgh58jh2JS9O7XXWeTaOVqi0djS72+nzzcDicbcx776TDrQitOengrUQXAbSK/qIRF+y/Sp4WTQW5jDYGEnASm7ZnGczuf48DVA7yz7x0KS/TTFsRkxOBt510uCKsqbM1sGd96PLuu7CIyNZLQxFAWRSzCu5G3TmVTE9xt3CkoKSAl//pTVakLaFmEEMzqOQszYzOKZXG5oDV/e3/yS/K5klU+G2RsVixNrJtgZmyGEIIZ3WdQWFLIZ/8qFcGu5V1j/NbxPLb5MQpKGogXTuOmYFYLVaOxqZLeusVAxauooOpcOA2Z4JYufDu2EyeupJOQmV9pBHBd0t3XkeSsAl2MQkZeESGX0ujXqrwbtYO1GRue70V7TzumrQrjjTVh5BZW74V2OSWX11aF1TgxnSoAbhOrQq5wLbuA5/s2r++pGMTBqwd5eOPD/BP7Dy91eomv+35NdEY080/O1+sXkx6Dn50BT5Y38ETAE1ibWvP6P6/z1LansDSx5H/3/69Wc60oFiA+J75CYdLEugkf9vqQbq7d6OTSSe+7FvYtACpUA8Vlx+Fpcz1ba9NGTZncfjLbL21nxekVjP9zPGdTznIu7ZxBdQ+i0qIaXn6isggB972hlLoMNcAeUJAFEesUY/K3neC3cUrN5Pj6T8I3uJ0bn4/ugKmxoHsNE8vdDnpo51CqBtp3LpkSjaxQAAA0aWTBL89044W+zVl9LJZBX++r1JW0lDWhsawNjWXW5lM1mpsqAG4DRSUaftobQ6C3Pd2aNbyMnxkFGfxw4gf+uvAXSblJrDi9gud2PoertSvrR6zn2fbP0r9pf4b7Dmdh+EIiUyMByC/OJy47zmD9f1nszO14vNXjXMi4QF+vvqwctlIvd1BN0AkAretnblEuqfmpOg+gG+nXtB8LHlxQzrPIz84PI2FUoQCIzYotp+aa1HYSvna+fHb0M/KK81g6eKlyjSIWcj6t6vTTb+97mwlbJ/Di3y/qIqkbHF5dwKePYjyuKrYgOVIxMq+ZBDF7wTkArp1TDNDzg+HAt/VuSxgd6MmpWYNoV4PU0rcLb0crPO0t+fbvc2w7lcCuM0k0tjKlU9PK82GaGBsx/cGW/D65B0YCxv18mOmrw/gnKpn8ovIqywPnr2FsJFgXGsfO04anYFcFwG1gw/E44tLzeKFv8waZA2RT9Cbmhc3j9X9ep//q/nx29DP6evVlxeAVeDW6HrD9Rpc3aGTeiBkHZpBfnM/FzItIJM0aN6vV7z7X8TkWP7iYr4K/wtbMttbz1wWDaXcACTmKq21N1UkWJhZ4N/LmXNo5vfb84nyS8pLwtNWv12BmbMYnvT9hgPcAVgxZQVuntkzvMh0bUxtmHqrcS6igpIDo9GjaOrYlJDGEh/94mC0xW8r1kwYumkWaonKquVtGn2mQFQ9hSuptshIhIeL693npytO+kQlM3AzTo2Dcr/BiCLxxAVoNgx0zlJ1BoQH1djUapWTmbYhqro3O/nYghGDe+EAcrM34z/JjbDgRx/3+zgZV/+vazIGtL9/H072bsSnsKv+36F86zd7B4gPX3ZKz8os4cSWdp3s3o5WrLe+sNzx5YMO4QncRJRrJ3L3RBLg1Irhlw8xldCT+CJ42nqwcupLpQdP5oMcHfBX8FVam+vrjxhaN+aDHB5xNPctLu17iTIriU1+bHQCAqZEpQa5BNy0UbcxssDWz1QmAUpfN2tgT/O39y+0ASse9UQAAtHFqw1fBX+FlqwhKBwsH3ujyBmHJYWw4v6HC34hOj6ZEljCp7SS2PLyF9s7t+ejwRzrBpZEaZh6cybM7njVozm/ve5uJWyfenqpnvn3BvZOSn+j38TCnNczrpbxPuwTrnoX0S/DociUiuawtyMoBHl0G/T+A0xtgXh+4fKTi38lNVXYK33WGBf3hqwD4fQJE/qXsJnJTFeFwl9DWw45NL/bmjUEtsTY3YVQnw50oLM2MmTGsNSfeH8iiJ4No7d6Ir3ZE6XYCR2JSKdFIgls68+WYDqTkGP5woAqAW8zOM4nEJOcwNdivQT79F2uKOZp4lB7uPWjj1IaJbSYy2n80RqLiW6Ff037M7jWbw/GH+fTfTzESRvg08qnbSVeAh42HLhag9LUyFVBVtGjcgtjsWL28QKUuoGVtAFUxzHcYzeyasf1SxdW+SlVorRxa4WDhwMe9P6ZElvDBwQ90dYzXnlvLkfgjOmFWFccTjxORElFpZbSbQgjoMx3SL8Olg9B9KvR9F87tVHT957bD4M/Au5IssEIou4j/+0Opnbx4EGyfAfkZ1/tE71ZyIe2YoeQ6eugH6DZFiWj+7TH4Pgg+b6bUVs6vuMjLnYipsRFTg5sTPvNBgltWnUerIizNjOnXqgnTBviTlV/MDq2qZ//5a1iYGhHobU9bDzueDzbcRnf3FKRtICzYF4OnvWWDdf2MuBZBTlGOLiDKEEY2H4mUkvcPvk9T26aVRunWJW7WbjrvnYuZFzExMsHZquY7Ln97fwDOp5/XZREtrTlc0Q6gIoQQdHXtyqboTRRrijEx0v+zOpt6FisTK914XrZeTA+azoeHP+SlXS+xJ3YPvT16sz9uP4evHuYR/0cq/a20/DSS8pIwEkZ8e/xbBvoMxNrUusbnXUpBSQHFmmL9MQKGwZT94OR/PS9R+8fg71lKCougp6sfuNl9ijvq9vcU19KQRdBhrJKK4sC3ythPrFJ2G6X0fx8uH1LUQemXFbfU7e/BiDvXNfV20MPXEXc7C9aGxjK8gzsHzl+jazNHzE2U3dhL/VvwmoFjqTuAW8iJK+kcvZjGpF7N9PKFNySOxCtb8q6uXavpqc+oFqOYEzyHVwNfvR3TqjEeNh5czb7KwvCFrDi9gqAmQZXuYqrC30ERAGXVQLHZsVgYW+iCygwhyDWI3OJcnZqsLJFpkfjb++vNb4z/GLq7ddct/t/2+xYXSxcOxR+q8ndK5zm1w1Su5V1jUcQig+dYEbMPzeaJLU+Ut1+4ttNPSmfvrQSVDZilPOUbgrmtUtfg2d0QMEJJQ3HgG+j0BEzerb/4g/J7vsHQ/lG4bzr0eEHxSDr/982c4l2HkZFgVGcP/olK5mRsOueSsund/Pq9WpO1p2GuUncoC/bFYGtuwmNdvKrvXE8cSThCK4dWlRZoqYoHvB/QS9JWn7hZu5FbnMvXoV8z0Gcg3/T9plbjuFu7Y21qTVTqdQEQlxWHp61njVR4pQFtIYkheu1SSiJTI8t5PAkh+KT3Jzzf8Xm+vP9LTI1M6e7enSPxR6pMOVEqAEb7j2Zws8EsPbVUrxZyTTmWeIzojGgOxN3GfEAenWHUXJh2Bv6zT1H5mBmwa+n7rrJT2PiSvgrJEIrylfKbJQ0kUO8W83BnTzRSKTQF0Kt57YobqQLAABIy8hk7/xCDv9nHEwsO896G8HI1P2PTctkakcC4bk2xMW+YmrW84jxOJJ2gu1v3+p7KTdPOuR3GwpiXO7/MF/d9Uc6AbShCCFo0blFuB2Co/r8UJ0snfBr5lBMAcdlxZBdlV+jy6mzlzJQOU3Tql+5u3UkvSNclsKuIqLQoHC0ccbR05JXOryAQTP17Kok55V3/pJTMDZvLtosVZ17PKMjQ2Rx+O/ubwedaa6ydwK294f1NLZQAtayrsHmaYa6l+Zmw/2vFTXX5KFg8RMmyepfh52xD56aNOR2fiYO1GQGutct3pAqAakjKyufxnw8TEZeJR2ML8os0/HrkMp/9dVav35IDFwGYWIvUs3XF8aTjFGmKaqT/b6h0cunE0fFHeabdMzdtbPe39+dc+jmklEgplRgAW8O9NEoJcg0iNDFUzzsnMk1rALavPh14aaRyaeGaiohKi9LZLdxt3Pm+//fE58Qzfut4XaK+UlZGruTHEz+yMHxhhWOdTVXu4Y7OHdkft5/LmRXXwa3s2Pzi/Eq/P5VyiohrEQa7tlaKZ5CyE4hYo8QZVEb8SUVIzGkDOz+AJm2UJHlJZxRvpDOba+9VpNEY5tJaxzwSqDyk9PRzrLDgvSE0zEfVBkJKdgFP/HyEhMx8lj3VlSBt1aEPN59m4f4LjOjgQddmDuyJTGLpoYsMb++ml9ujoXEk/ggmRiZ0dulc31O5JZga1T7JV1n87f1ZFbWKqzlXsTSxJLc4t8Y7AFDUQGui1nA27SxtHNsAigeQkTCiuX31EeFOlk60sG/B4auHK6w/UKwpJjo9mrEtx+raurl1Y/GDi3lu53NM2DqBN7q8wXC/4ZxMPsnn/36OpYklkWmRZBVmlYu9KBUA73V/j7Gbx/J75O+83uWJ5zt0AAAaYUlEQVT1aucZmRrJo5se5ZXAV3iq7VPlvi/RlPDs9mfJKszCu5E3Q5sNZWyrsbVSOwLQ5zXF9XTfl0o9hWb3QeSfipdSZhxkxkNOEphYQJtR0PVZ8FDKkdJyCKyeqJTUtPOCdqOVcpv2PtfHv/CPkggPFNWUlJCfrsQ85KUqLqmyBFzbQ5uR0OZhcKhdLMytZFh7d+b/E8OIGhSpuRF1B1AJUkqe/zWUy6m5LJgYpFv8AV4b6I+XgyVvrT3JwfPXmLLiGC1cbJn1UNt6nHHlSClJz0/n4NWDtHdqX2t1yd1KF9cumAgT3t3/LtHp0YDhHkBl0dkBEq6rgc6mnsW7kTeWJoY9GPRw60FoUih5xeXryF7OukxBSYHOcF1KgGMAK4aswKeRD+8deI/xf45n2p5puNm48UnvT9BIDceTjpcb73TKaVytXWnp0JIHvB9g/fn15Bbllut3IwvCFyCR/Jvwb4Xfn007S1ZhFqOaj6KJVRPmhs1l6PqhLDu1jKLa6OSFgKFzoPkA2PyKEjuw/T0lXsDaBVoOgiFfwmtnYdS864s/KHUTnvkbHv5ZKbpz4Fv4sScc/0VZ6CPWwYpHIO0iaIqVILiseMUg7dwSWg2F3q9C8NtK29+zFTfVsN+rn3dKNJxcBSW3sKJcGewsTdn7el8Gtqm9x6G6A6iEfeeucTgmlVkj2tDTT9/AYmVmwqej2jN+4REeX3CEZk7WLH2qK3aWt+aJ9Fby+dHPWRW5Spew7IWOL9TzjBoevo19+bj3x7y17y3e+uctwPAYgLI0sW5CU9umhCSGMLGNUjE1Ki2K9k6G6717uPdg2ellHE88Tk8P/aprpXaKlvbl7Qmetp4sH7KcLTFbmHNsDtlF2cwbMA8vWy9MjEwISQzhPs/79I45k3qGVg6Kampcq3H8dfEvPj/6OVM6TMHV2hUpJRcyLlAsi3Vqp4sZF9l2cRsWxhaEJYVRoikplxiwVAC+0OkFXKxciE6P5oujX/BFyBesP7+eX4b8YvBDSG5RLuvPryfAIYDOY5bArg/BwZei5v05o8mlvbMB19bUQvEsav8opF+B9VPgj6lw4hdlF9G0O4z7DSyr2aEEv6Ucv+E5pQBPZpwiHCpSQeZnKDaI9EtKUN3Aj5W03KAInuxESDqtJN5rOVhJyFcPqAKgAqSU/G97JB6NLRnbtWKPnt4tnPi/Ht7siUxm+dNdcbY1r7BffXI+7TzLTy/nfs/76ebWDVdrV3p79K7vaTVIhvgOIbMwk4+PfAzULqoYFDvAzks70UgN2UXZxGXHMdp/tMHHd3bpjKmRKRtjNtLDvYeefSMqNQoTYUIzu4rVD0bCiOF+w+nftD9ZhVm6ugptHduWq8ucW5TLxYyLDPYZDCg2lYf8HmLduXVsOL+BwCaBXMy4SFKekqLh/R7vM8Z/DIsiFmFmbMYLnV7gy5AvOZd+TidESglJDKGpbVNcrJRgJ7/GfswbMI9tF7cxfe90fjnzC8+2rzrqubCkkFWRq/g5/GdS81PxaeTDxpEbEYOVbKwLw+bxw4kfWDpoKZ2b1ECl2dgLJm5U6ibs+VR5wn9kgVJ32dDjx69VhMDfs5SFfNB/9YWAlLDxRUVADJgNIYvhl0fA3A4Eyo6gTOAhLq1h8OdKZHUdowqACvj7TBJhsRl89kg7XXBFRcwa0QYpqbUB5lZzY93RRRGLsDSx5KNeH9HYonE9zuzOYGyrseQX53M86Xit1WRBTYJYd24d3x3/ThcxfeMCWRVWplZMaD2BRRGLcLFy4dXOr+r+T6PSovCx86k2EM/K1Epv/kGuQSyJWEJuUa6uPTItEokkwDEAULyhPur9EVM6TGFN1Br2xu6lc5POdHfrzq4ru5h9aDZJuUlsit7EmJZjGOA9gC9DvuRY4jG989NIDaGJoRW6Cz/o8yCbozezOGIxj7Z8FDvzyhO1fR36NctPL6ebazdaO7VmccRijiYcpatbV4o0RbriPHPD5vLzwOqzsephZAz3v67UVrZyMDyuoRQTc3h4Adi4wuEfQGqUBbx0nJBFcPoPeGAW9HpZiXIOXQYp2oSBwkixQbgEKPaFHTOUqmy+weDdWynW492z+l2BRgOn10Oz+xUPq1qgCoAb0Ggk/9sRhY+jFQ93rloNIISo8b1zK5FSMi9sHofiDxGbFUt2UTYzus9guN9w4rLj+PPCn4xrNU5d/GvAk22f5EmerPXxfb360sOtBwvCF+jaaiIAAF7p/Ao5RTksjliMhbEFUztOBRQBcGNKa0MIbBLIgvAFhCWH6TyNSov9BDgE6PX1tPXklcBXeCXwFV3bcL/hTNszjXlh8zARJkxqMwk3GzdcrV05nnRcr4RnaaW3ygr9vNj5RUZvHM3CiIVMC5xWYZ8iTRGbozczwHsAXwV/RX5xPmuj1rI6ajVd3bqy6/IukvOS6enek4NXDxKaGFrlLuCf2H+UFN6tx9PHo8/1hyTrm0gVbWQED36sLPqHvgeEYouI2q4IgOYPQE9tjWcTc8UwXRn+Dyq2iVPrYLfW08lLq5ayqiSbcHGhosYKXw1uHWDSVsNiK248jRofcZezOTyeM/GZvPxAC0wbaDRvKb+e/ZUfw36kRFNCL49e+Nv7896B99h5aSdLIpYghNDpolXqBhszG+YPnM+2R7bxcueXmdx+Mk6WNXs6E0LwTrd3GNl8JHPD5vLhoQ+5lneN+Jx4nS6+JnRy6YSRMNJTA51NPYuDhYNOTVMVZsZmfBX8FY+0eIT/dPgPbjZKidPOLp0JTQzVc/UsjYOoTAD42/sz1Hcov575Va+6WlkOXz1MWkEaw32HA0rW1hF+I9h5eScpeSmsPLsSDxsP5gTPwcHCgR/Dfqxy/ktPLeVQ/CGe//t5JmydQMS1iCr7G4wQMPAj6P48/PuTovM/thia94dRPylCwhBMLSH4TXj+CLx5EUZ8B1dDYdGDSgK+GynMgZXjlMW//VhICId1k2vl5qruAMqQkl3ArI2naOvRiBEdau4HXpdEXIvgy5AvCfYM5tt+3yKEILcol8k7JvP6P69jhBHDfYfjat0wcxLd7bjbuFfoymkoRsKImT1mYm9uz+JTi9kTuwegVgLA2tSaAIcAvSC1MylnCHAMMDiGwszYjJk9Z+q1dXbpzJ8X/iQ2O1aXHTUkIQQPGw+dkKiIqR2n8teFv5gbNpcPenxQ7vs/L/xJI7NGevaqMf5jWHFmBV8d+4qQxBBeDXwVK1Mrnmr7lE4VFdgksNxYqfmphCSGMKntJLxsvZgXNo/JOyazatiqWnl67b68m+9PfM+0wGn08uilCIEHP4am3RQ3VJ8+tavKVoqlvVLP2cFPWeR/7gc+vcCmiaI6Sj6rLPh5aTD8WwicqKTU+OtN2Pa2kqfJxvBEcw37EbcOkVLy7voIsvKL+d+Yjgbl6q5LNFLDpcxLJOQkkJCTwPS903G2dOaj3h/p/oitTK34of8P+Nn5USyLmdR2Uj3PWuVmMDYyZlrQNL7r950u6Ko2AgAUNVB4cjgFJQW6+gStHVrf1PxK1S6hiaGA8jdU2UJcFi9bL8a2GsuaqDXljNN5xXn8fflvBngPwLSMDty3sS+dXTqzMXojZkZmjGo+CoBHWz6Kg4UDP5z4ocKgsz1X9qCRGgb7DGaM/xiWDFoCwLQ903SecTsv7WTqzql8d/w7QhNDKdZU7ra5MGIhUWlRTNk5hY8Of6S4zQoBrR9SVDk3s/iXxacXPLWdErcOSjDbyVVwfIVSia3lYMUQHajd3Xf7D3R5Bo7Mgx+6wGeGF69XdwBa/jhxlb9OJfDW4Fa0dK19sZJbjUZq2HV5F3PD5uqlKzARJiwZvKScIc3O3I7FgxYTlx1XqbeIyp1FsFcwa0esJSotSufZU1OCmgSx7PQyvj/+PU6WThTLYp0BuLb4NfajkVkjQpNCeaj5Q0SnR5NWkFap+qcsL3Z6kd1XdvPBwQ9YM3wNFiYWAOy9spe84jyG+g4td8yYlmMITQplULNBuqAySxNL/tP+P3z676fsuryL/t799Y7ZcWkHHjYeOjuMl60Xn/T+hBd3vcjsQ7ORUrIpZhPOls4cuHqA+Sfn09qxNb8M+aVcVteYjBjCksN4vuPzZBZmsvz0cvbH7ee97u/R26M3Ukr2xe3jQNwBRjQfoQsGrIz47Hh+i/wNf3t/Ojh3wNPmev6piGsRLDq9iD1cZNbgWQz3G175QELA4C9I9R/IwbgDHEyNANZX+dulqAIAJY/P+39EEOhtz7N9alfs5HaQkJOgFGJJPYNPIx/e6fYOZkZm5BTlEOAYoEtffCO2ZrY1NjyqNGxcrV1vSp0X5BqEh40HS04tAUAgql2gqsNIGNHJpROhiaHkFOWw7dI23W9Vh5WpFTN7zuTZ7c/yw4kfeC1ISWC85cIWXKxcKoxWH+g9kPDkcD2jMyi7gNVRq/ki5At6e/bG3Fhxyc4qzOJw/GGeaPWEnqor2CuYZ9o9w4LwBRgLY57r8BzPtn9WiTk4t57/HfsfW2K28FDzh/R+Z8P5DRgLY0b7j8bJ0om+Xn2ZfWg2z+18jv5N+xObFUtkWiQCwW9nf2OE3whe6vxSpXaWOcfmsPXiVt1nC2MLGpk1wtzEnCtZV7A1s8W7kTfvH3gfBwsHReVUCbtj9/LqoTcpkSU0Njfc6UPcdK6O20hQUJAMCQmpvuNNkFNQzCNzDxKXnsemF3rj41T73Oq3koScBJ7a9hRp+Wm83e1thjQbUu6JREWlpmQWZhKbFYtGamjrdPOR64siFjHn2BzdZy9bL7aM2mKwbWHWoVmsO7eOx1s9TiPzRsw/OZ8nWj3B9C7TazSPw/GHeXb7s7zY6UUmt58MwOaYzby9722WD15OR5eOev2LNcUsO72Mbq7daON0XRBKKXls82NkFmayadQmXbqRIk0RA1YPoJ1zO77r952uf2FJIQvDF/Jz+M942HjwTLtnuM/zPhZHLGb5meXYmtqyfMhyvBvpq2UuZFzgoQ0PMbHNRIb5DuNE0gmuZF0hszCT7KJsOjh3YLT/aDRSw6S/JnE56zKLH1ysN9dS8orzeGjDQ9iY2TC752wCHAIwMTY5JqWsXhKXJsBqiP8CAwPlrSA5K1/uOpMoU7IL9NpLSjTymaVHZbO3Nsu9kUm35LduBVezrspBawbJ7r90l2FJYfU9HRWVSknITpAz9s+Q807Mk3su75FpeWk1Oj6zIFM+vuVxGbg8ULZd0lZ2XNpRRqZG1mouL+96WXZZ0UXGZcXpPvf7vZ8s0ZTUaJy9V/bKtkvaylWRq3Rtuy/vlm2XtJV/X/q7wmMKigvK/c75tPOyz2995JC1Q2RqXqred+/ue1cGLQ+S13KvVTufpJwk+eCaB2Xv33rL0MTQct//eOJH2XZJW3k0/qiuDQiRBqyxdb4DEEIMAr4BjIEFUsr/VtbXkB1AUlY+EXEZxKblUVwiKdFIzEyMsLM0xcRYsDU8ge2nEygqkQgB7TzsaOdhh7W5CXFpeWwJj+eD4a2Z1Ktu9eXFmmJOpZwiMjWSNk5tCHAIIL84n5WRK1kUsQiNRsNPA36inXO7Op2Xikp9UaQpokRTorMH1JTYrFhG/jGSEk0JnZp0Ijw5nJHNR/Ju93drNI6UkvFbx5OYk8iWh7dgbmzOK7tf4XjScXaO2VmjJIQnkk7w9Lanae3Ymp8H/oyFiQVx2XEMXTeUca3G8WbXNw0a50rmFZ77+zmuZl9ldq/ZDPMdBih2hBEbRnC/1/18ef+Xuv5CCIN2AHUqAIQQxkAUMACIBY4C46SUpyvqf6MAKC7REJmYxdELqRy9mEbIpVQSMwuq/E17K1Me6ezJ/S2dOX45nX+ikolOzia/SENBcQlP9mzGjGGGu8NJKckqysJEmGBhYkGJLCE1L5WU/BSMhTH2FvZYmVhxJvUMxxKPcSblDPE58VzNuUqxphgnSyfszO2ISY8huyhbN66DhRLwkZqfSi+PXrwW+Bot7FsYNCcVFRWFyNRItl7Yyr64fZxPP8+ywcsqtZVVRalKqaV9S8xNzDl17RQTWk/Q2SpqwvaL23lt72v42fkxqsUozqaeZdvFbWx9eGuNjPoZBRm8svsVQhJDCPYKpkXjFoRfC+d40nE2jtyol76koQqAHsBMKeWD2s9vA0gpP62ov3VTd9l9xnPYWJiQV1hCXHoehcVKsIOdpSleDla4N7bEvbEljtZmGBsJBJLCkhJyi4rILyrGycYcE2NlcTcWxhgJIwQCjdRQrCmmUFNIfnE+BSUFWJhYYGNqg5mxGUWaIopKipBIjIQREsm5tHOEJYXp8qNUe74IfOx88LTxxN3GHVMjU1LyUkjJT8HL1ose7j1o5dCKk8knOXj1IDlFOTzZ5sma5TZRUVGpkCJNUa1Thksp+e+//yUyLRIzIzOsTa15o8sbVcY3VMW2i9tYemop4deUCl6P+j/KjB4zajxOUUkRc0LnsPfKXuKy4yiRJTzf8XmmdJii16+hCoDRwCAp5TPazxOAblLKF8r0mQxMBrDwsQhsPrP6POo3i4WxBabGpuQX51OkqTxdrYeNBx2cOxDgEIBE6nyzHS2VCk0aqSEtP42swiyaN25OR5eOVeY7UVFRubeISY9hX9w+RviNqH19BC1FmiKSc5NxtXYtVw/bUAFQ124lFelZ9CSQlHI+MB+gU2AnuWfsnhr/iJEwuv60r1XtSCnRSA0lsgSJxESYYCSMMDM207t4hSWFFJQUYGpkiqmRKUbCSDlGSr3AFBUVFZWa4tvYF9/Gt8bV3NTItNZZa0upawEQC5TNr+wJXK2ss7EwrvMnaDNjs3LZFk2E6n6poqJy91HXqSCOAi2EEM2EEGbAWGBjHc9BRUVFRYU63gFIKYuFEC8A21DcQBdJKU/V5RxUVFRUVBTqXLchpfwT+LOuf1dFRUVFRR81G6iKiorKPYoqAFRUVFTuUVQBoKKionKPogoAFRUVlXuUBp0OWgiRBURqP9oBGbdo6Ht5LCfg2i0aqzbcDWMZcg3vhvOsy7Fqc19WRkM9x9s9Vtlr2FJKWX1lK0NShtbXP8qkNAXm38Jx79mxMDBN7J18jrd7LEOu4d1wnnU8Vo3vyzvwHG/rWDeslwZdzztJBbRJHUsd6w4Z61aPdy+MdStpqOfY4MZq6CqgEGlIVRsVg1Gv6c2jXsNbj3pNb56y19DQ69nQdwDz63sCdyHqNb151Gt461Gv6c0zv5L3ldKgdwAqKioqKrePhr4DUFFRUVG5TagCQEVFReUepV4FgBBCCiGWl/lsIoRIFkJsrs953ekIIUZpr22r+p7LnYZ6T94+hBDZ1fdSMZTqrqcQYo8QokpDcH3vAHKAtkIIS+3nAUBcTQYQQq3WUgHjgP0o9RYMRghhfHumc0dx0/ekisqdQn0LAICtwFDt+3HAb6VfCCG6CiEOCiGOa19batufFEKsFkJsArbX/ZQbLkIIG6AX8DRaASCECBZC/COEWC+EOC2EmCeEUgdTCJEthJgthDgC9Ki/mTcoanNP7hNCdCzT74AQon2dzvoOQHsvbi7z+XshxJPa9xeFELOEEKFCiHB1B1s9VV1PQ2gIAmAlMFYIYQG0B46U+e4scJ+UshPwPvBJme96ABOllP3qbKZ3BiOBv6SUUUCqEKKztr0r8BrQDvADHta2WwMRUspuUsr9dT7bhklt7skFwJMAQgh/wFxKebLOZnz3cE1K2RmYC0yv78nc7dS7AND+kfigPGndWCjGDlgthIgA5gBtyny3Q0qZWieTvLMYh7KAoX0dp33/r5QyRkpZgvJE21vbXgKsrdspNmxqeU+uBoYJIUyBp4AldTLZu4912tdjKP8HKreRhqI/3wh8CQQDjmXaPwR2SylHCSF8gD1lvsupo7ndMQghHIF+KDpsiVJ2U6IsYjcGfJR+ztcKBRV9anRPSilzhRA7gIeARwE1qrViitF/8LS44fsC7WsJDWd9ashUdz2rpN53AFoWAbOllOE3tNtx3QD3ZJ3O6M5kNLBMSuktpfSRUnoBF1Ce9rsKIZppdf+PoRiJVSqnNvfkAuBb4Ki6O62US0BrIYS5EMIO6F/fE7rDuanr2SAEgJQyVkr5TQVffQ58KoQ4gPI0q1I144D1N7StBR4HDgH/BSJQhMKN/VTKUJt7Ukp5DMgEFtfBFO8otN56BVLKK8Aq4CTwC3C8Xid2h3KrrqeaCuIeQAgRDEyXUg6r77nczQgh3FFUQq2klJp6nk6DQgjRAfhZStm1vudyN3CrrmeD2AGoqNzpCCH+D8Vb6F118ddHCDEFxfHgvfqey93Arbye6g5ARUVF5R6lTncAQggvIcRuIcQZIcQpIcTL2nYHIcQOIcQ57au9tv0JIcRJ7b+D2m1P6ViDhBCRQojzQoi36vI8VFRUVO4G6nQHIIRwA9yklKFCCFsUX9+RKN4UqVLK/2oXc3sp5ZtCiJ7AGSllmhBiMDBTStlNm7IgCiVMPxY4CoyTUp6us5NRUVFRucOp0x2AlDJeShmqfZ8FnAE8UHynl2q7LUURCkgpD0op07TthwFP7fuuwHltYFMhSsDTQ3VzFioqKip3B/VmBNYG0XRCMZw1kVLGgyIkAJcKDnkaJUcLKELjSpnvYrVtKioqKioGUi+RdtqEZWuBV6SUmUKI6vr3RREApekLKjpAtWarqKio1IA63wFoc6WsBX6RUpbm/UjU2gdK7QRJZfq3R4mwfEhKmaJtjgW8ygzrCVy93XNXUVFRuZuoay8gASxEMex+VearjcBE7fuJwB/a/k1RkkNN0Ga3LOUo0EKb2sAMJe3xxts9fxUVFZW7ibr2AuoN7APCgdJgmXdQ7ACrgKbAZWCMlDJVCLEAeAQl3wVAsZQySDvWEOBrlHD8RVLKj+vsRFRUVFTuAtRAMBUVFZV7FDUVhIqKiso9iioAVFRUVO5RVAGgoqKico+iCgAVFRWVexRVAKioqKjco6gCQEVFReUeRRUAKioqKvcoqgBQUVFRuUf5f9CTrL0Vn0qUAAAAAElFTkSuQmCC\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
     }
    ],
    "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases', 'newAdmissions', 'deaths']].plot()"
+    "hospital_data[['ventilator_beds', 'ventilator_beds_7']].plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 119,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c4070190>"
+       "<Figure size 720x576 with 0 Axes>"
       ]
      },
-     "execution_count": 18,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 720x576 with 2 Axes>"
       ]
      },
      "metadata": {
     }
    ],
    "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot()"
+    "fig = plt.figure(figsize=(10, 8))\n",
+    "ax = hospital_data.loc['2020-03-20':, ['hospital_cases', 'ventilator_beds']].plot(\n",
+    "    secondary_y='ventilator_beds',\n",
+    "    figsize=(10, 8),\n",
+    "    title=\"People in hospital, and on mechanical ventilation\")\n",
+    "# axl.legend(['Number in hospital', 'Number on ventilator'])\n",
+    "plt.savefig('people_in_hospital.png')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
+   "execution_count": 120,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [],
    "source": [
-    "data_by_day['cases_m7n'] = data_by_day.cases_m7 / data_by_day.cases_m7.max()\n",
-    "data_by_day['deaths_m7n'] = data_by_day.deaths_m7 / data_by_day.deaths_m7.max()\n",
-    "data_by_day['admissions_m7n'] = data_by_day.admissions_m7 / data_by_day.admissions_m7.max()"
+    "hospital_data['cases_m7nd'] = hospital_data.new_cases_7 / hospital_data.new_cases_7.loc[normalisation_date]\n",
+    "hospital_data['deaths_m7nd'] = hospital_data.new_deaths_7 / hospital_data.new_deaths_7.loc[normalisation_date]\n",
+    "hospital_data['admissions_m7nd'] = hospital_data.new_admissions_7 / hospital_data.new_admissions_7.loc[normalisation_date]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
+   "execution_count": 121,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3fa8790>"
+       "96.1"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 121,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
     }
    ],
    "source": [
-    "data_by_day.loc['2020-03-01':'2020-07-02', ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
+    "(int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
+   "execution_count": 122,
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [
     {
      "data": {
+      "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c8407f90>"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYIAAAEECAYAAAAlEzNMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOydZ3hU1daA3zOT3nshCaRACIFAAqF3aaGDNEEUFEW9oAgXFT4bekW4iIoiiKg0QZEuICKd0AIkkEIgtFAS0ntPJpn9/RjIBUklkwKc93nmSeacvddZM8mcNXvtVSQhBDIyMjIyTy+K+lZARkZGRqZ+kQ2BjIyMzFOObAhkZGRknnJkQyAjIyPzlCMbAhkZGZmnHNkQyMjIyDzl6NS3Ao+CjY2NcHV1rW81ZGRkZB4rQkJCUoQQtv88/lgaAldXV4KDg+tbDRkZGZnHCkmSbpV1XHYNycjIyDzlyIZARkZG5ilHNgQyMjIyTzmP5R6BjIxMzVGpVMTGxlJQUFDfqshoGQMDA5ydndHV1a3SeK0YAkmSVgFDgCQhRKsyzkvAN8AgIA+YLIQ4d/fcJOCDu0M/E0Ks1YZOMjIyFRMbG4upqSmurq5oPqIyTwJCCFJTU4mNjcXNza1Kc7TlGloDBFRwfiDQ7O5jKvA9gCRJVsDHQEegA/CxJEmWWtJJRkamAgoKCrC2tpaNwBOGJElYW1tXa6WnFUMghAgE0ioYMhxYJzQEARaSJDkCA4D9Qog0IUQ6sJ+KDYpMRahqvsTPL84nqyirxnKEEOQXldRYjkztIhuBJ5Pq/l3rao/ACYi573ns3WPlHZepChkxoG8ChpZwfgPsmQ1+E2HgIqjmP0JoUihvHXqL9MJ0lJKSn/r/hL+D/yOpdSMll7d/DyUsJoOmdia42RhTohZ0cLPi9Z4ejyRTRkam9qirqKGy7kqiguMPC5CkqZIkBUuSFJycnKxV5R5Loo/A0nbwRVP4vhv88S+NQTizEk7/UC1Reao8/u/4/2GoY8jbbd/G3siez4I+Q1WiqpYcIQS/n73N4G+PcTMll9d6uONiacjt1DxupOSy8K8oDl9OqpZMGZmGwOHDh/H19S19GBgYsGPHjvpWS2vU1YogFnC577kzEHf3eK9/HD9SlgAhxEpgJYC/v//T3VYt5iz8NgGsPaBZf7gRCD3nQI/ZsHky/D0X7LzAvRcAEbGZbA6J4cDFRAqL1Rjr6/DREG/6etsD8M25b4jJjmHVgFW0d2hPU4umTD80nXUX1zHFZ0qVVMrIK+K9reH8HZlIZ3drvhrXBkdzw9LzhcUlDPrmGB/uuMD+mT0x1FNq+U2Rkak9evfuTWhoKABpaWk0bdqU/v3717NW2qOuDMFOYLokSRvRbAxnCiHiJUn6G/j8vg3i/sDcOtLp8aQwB357Dkzs4IXtYOrw4PlnV8KKbrB3Lrx+nKCbGYz/MQg9pYLeze2wNtEj5FY6b2w4y6sBudwqCiQwNpAJXhNo79AegJ4uPXnG5RlWhK3A1dyVPo37lIpPzkvmcMxhRnuORiFpFpS5hcW8uOoMl+KzmDvQi1e7u6NQPLjY09dRMn+kD8+tDGLhX5f4aGhLlArZP91Q+GRXJBfjar43dD/ejcz4eGjLSsetW7eOxYsXI0kSrVu3ZuzYsXz22WcUFRVhbW3Nhg0bsLe35+jRo8yYMQPQ+MADAwMxNTXliy++YNOmTRQWFjJy5Eg++eQTcnNzGTt2LLGxsZSUlPDhhx8ybty4Mq/v6urKhAkTOHz4MCqVipUrVzJ37lyuXbvGO++8w+uvv/7A+C1btjBw4ECMjIxK50+aNIldu3ahUqnYvHkzXl5eNXz36hZthY/+huabvY0kSbFoIoF0AYQQK4A9aEJHr6EJH33p7rk0SZL+A5y9K+pTIURFm84ywT9DXgqM3/iwEQDQM4Y+H8PmSajObWDOYRdcLI3YNb0b5kaamOKLKdFM2vlvfom+hqmODVNaTeG1Nq89IOb9Tu8z/eB03j78NsM9hjOvyzx0FDosPb+U7de2o5SUjPIchapEzbRfz3HhTiY/vOBPv7urjLLo5G7NC52asPbULcJiM5k70Iu2TSzRVcp5jU8rkZGRzJ8/nxMnTmBjY0NaWhqSJBEUFIQkSfz0008sWrSIL7/8ksWLF7Ns2TK6du1KTk4OBgYG7Nu3j6tXr3LmzBmEEAwbNozAwECSk5Np1KgRf/75JwCZmZkV6uHi4sKpU6eYOXMmkydP5sSJExQUFNCyZcuHDMHGjRuZNWvWA8dsbGw4d+4cy5cvZ/Hixfz000/afaNqGa0YAiHE+ErOC2BaOedWAau0occTT1EenFwK7r3BpX3547yHg5M/+X9/SkL2In5+pUepEUjMTeTlfRNQGki4Fr5EREQzIlQO7FOm4eNkjrutCQB2RnZsGLSBZaHL+PnCz7Sxa0Pfxn3Zc2MPCknBlyFfYq/Tlq/2xnHudgYLnvWp0Ajc49PhLWnXxJJPd19k3MogDHWVNLUzwcxQBzMDXcwMdGlmb8KAlg64WBlp5W2TqZyqfHOvDQ4dOsTo0aOxsbEBwMrKioiICMaNG0d8fDxFRUWlsfBdu3Zl1qxZPP/88zz77LM4Ozuzb98+9u3bh5+fHwA5OTlcvXqV7t27M3v2bN577z2GDBlC9+7dK9Rj2LBhAPj4+JCTk4OpqSmmpqYYGBiQkZGBhYUFAPHx8URERDBgwIAH5j/77LMAtGvXjm3btmnvDaoj5Mzix4lzayE3GXq+W/E4SeJm2/dw3TWGtY7b6OgxsvRU4J1AclW5bBqyCS8rL1aduMmivVEcjEpCkmDNSx3o6ampUqur1GVG2xmcSzrH8tDlJOQmUFhSyNe9vmb20Xd59c8PMcqYxJJxvozwq1qwlyRJjPBz4pkWdhy/msLp6FRup+WRVVBMUlYOGfkqfg+O4bM/L+HrYsFYfxeG+zbCWF/+V30SEUI8FOr45ptvMmvWLIYNG8aRI0eYN28eAHPmzGHw4MHs2bOHTp06ceDAAYQQzJ07l9dee+0h2SEhIezZs4e5c+fSv39/Pvroo3L10NfXB0ChUJT+fu95cXFx6fNNmzYxcuTIhzJ2781RKpUPjH9ckD9djwtFuXB8CTTpBk26VDhUCME7Z00IYCRT0rfDkYXQW7P1EhQXhJ2hHV5WXkiSxJRubrzQqQnRKTm89ksIC/ZcoltTm1L/vSRJzGo3ixf+eoGV4Svp6NCRbo16o8zsg47ZXuYP1iXA3YnU/FSO3TmGnkIPdwt3vKwq9pGaGegyyMeRQT6OD527lZrL35EJbA25w/9tj+CnY9H8NMm/dLUi8+TQp08fRo4cycyZM7G2tiYtLY3MzEycnDRfLNau/V+hgevXr+Pj44OPjw+nTp0iKiqKAQMG8OGHH/L8889jYmLCnTt30NXVpbi4GCsrKyZOnIiJiQlr1qzRir6//fYbCxYs0IqshoRsCB4XTi6FnAQYu67SoTtC73D2ZjqjRn4C8cZwdCHYe6NuMZQzCWfo7tT9gW9hejoKvBzMeGdAc6b/ep7t5+8wup1z6XlfO1/6Nu7LgdsHmNBiAuuDbpEa141m9hf5+twCWtk25Y0Db3Az6yYA+kp9Do45iLm++SO91CbWxkzt4cGr3d05cS2VtzaeZ8SyE3w/sR1dm9o8kkyZhknLli15//336dmzJ0qlEj8/P+bNm8eYMWNwcnKiU6dO3LhxA4AlS5Zw+PBhlEol3t7eDBw4EH19fS5dukTnzp0BMDExYf369aUbvQqFAl1dXb7//vsa63rz5k1iYmLo2bNnjWU1NCSN+/7xwt/fXzxVjWmy4jQ5A836w9iKSzElZxcy8JtjOFkasv2NLihECfzQHYoLiRq/jjF7xjO/23yGeQx7aK5aLRix/AQp2YUcmt0LA93/hXgm5SWxJ3oPI9yfo/fiQFo5mfP2EB0m752MoY4hQgi+7v01Qgj+dfBfzO0wlwktJmjl5cek5TFl7VmuJ+fyybCWTOzURCtyn3YuXbpEixYt6lsNmVqirL+vJEkhQoiHMkXlcI3HgUPzQV0MfedVOKywuITXfgkmp1DFgpE+mhBOpQ488yGkXSfo3AoAOjp0LHO+QiExZ6AXcZkFrD1584FzdkZ2vOA9iQ92XCQ9T8U7A5rTzr4dYz3HolKrWNJ7Cd2cutHduTve1t5svboVbX3JcLEyYusbXejRzIYPdlzgp2PRWpErIyOjQTYEDR1VPlzYAr7Pg1XFlQQ/3HGBc7cz+HKML96NzP53ovlAcPIn6PYRXM2aYG9cfnRPFw8bejW3Zdnha2TkFZUeF0LwwY4IdofHM2egF62dNVEU73d6nwOjD9DVqWvp2GebPsuV9CtcTL3IlfQrnE86/4gv/n+YGujy06T2dG9mw7LD1+Q6RjLVZuTIkQ9kB/v6+vL333/Xt1oNAtkQNHRun4LiAmg+qMJhZ26ksSk4lmm9PRjc+h8bsJKEqvf/cU5H0ElpUekl3wvwIruwmOVHrgOQmadi2q/n+O1MDNN6ezxQL0ghKbA2tH5g/kD3gRgoDXg38F3G7BrDq/teJb0gvYovuHyUCom3+jQjPU/F5pCYyifIyNzH9u3bCQ0NfeDxzzDQpxXZEDR0rh8ChS64dq1w2Nf7r2Bjos/03s3KPB9uYk6+QkGnuCioxGXTwtGMZ/2cWXX8BkOXHqff10fZF5nInIFezO7fvFKVzfTMGOg2kNicWAa7DaawpJCtV7dWOq8q+DexxK+xBT8du0FxiVorMmVknnZkQ9DQuX4EGnfSZAyXQ1B0KqeiU3mjl0e5NXyCEk6jQMI/6RrcOlHpZf9vkBcTOjbGylgPT3tTtr7Rhdd7elS5vO3/dfw/9o3ax+fdP6ejY0d+i/oNlbp6RezKQpIkXuvhzu20PP66kFBjeTIyMrIhaNjkJEFiBHj0rnDYkgNXsDPV5/mOjcsdczr+NN5WLTDXt9BUKK0EaxN9Ph3eirUvd2D9Kx1p41K5S+l+DHQMSvciJraYSFJeEgdvH6yWjPLo5+1AUzsTvtx3maJieVUgI1NTZEPQkIk+ovnp8Uy5Q64l5RAUncYr3d0eCPe8n1xVLhHJEXRs1Bn8XoBLuyHzTi0oXDY9nHvgYurC8tDl3Mi8UWN5SoXEB4NbcDM1jzUnay5PRuZpRzYEDZnrh8DQChzalDtkV1gckgQjfMsv8RCSGEKxKKajY0doPwUQcLrmCTZVRSEp+KDjB6TmpzJm1xg2X9lcY5m9mtvxjJcd3x68RnJ2oRa0lGmorFmzhunTp1drzqBBg8jIyKjWnBUrVrBuXeUJm3XBF198URrZ1KpVK5RKJWlptVePUzYEDRUhNCsC956gKPvPJIRgV3gcndyssTMzKFdUUHwQego9/Oz8wNIVWo2Gs6sgr+4KvXZx6sIfI/7Az86Pz09/Tkx2zaN+PhjcggJVCSsDr2tBQ5kniT179pQWiqsqr7/+Oi+++GItaVQ93nnnndLIpgULFtCzZ0+srKxq7XpyiYmGSlo0ZMeDW49yh0TGZRGdnMur3d0rFHU6/jR+dn4Y6Nw1Ft1mQsQmzV5Brzna1LpCbAxtmN9tPoO3DWZZ6DIWdl9YI3nutib0bWHP9vN3eDfASy5nXRP+mgMJEdqV6eADAyv/G48YMYKYmBgKCgqYMWMGU6dOZfXq1SxYsABHR0c8PT1Li7pNnjwZQ0NDoqKiuHXrFqtXr2bt2rWcOnWKjh07ltYUcnV1JTg4GENDwzL7EsyZM4edO3eio6ND//79Wbx4MfPmzcPExITZs2cTGhrK66+/Tl5eHh4eHqxatQpLS0t69epFx44dOXz4MBkZGfz88890796dyMhIXnrpJYqKilCr1WzdupVmzR6O4Lt58yYBAQF069aNoKAg2rRpw0svvcTHH39MUlISGzZsoEOHDg/M+e233xg/fnzp/IEDB9KtWzdOnjyJk5MTf/zxB4aGhg9dqzrIn5yGys1jmp+u5ZfP3RUWh45CIqBlGX0J7pKSn8KV9Csat9A97L2h+WAI+h4Ks7WlcZWwM7Lj+RbPsyd6D5fTLtdY3uh2zqTkFHH0sty+9HFl1apVhISEEBwczLfffsudO3f4+OOPOXHiBPv37+fixYsPjE9PT+fQoUN8/fXXDB06lJkzZxIZGUlERERpF7F77N27l0aNGhEWFsaFCxcICAggLS2N7du3ExkZSXh4OB988MFDOr344ov897//JTw8HB8fHz755JPSc8XFxZw5c4YlS5aUHl+xYgUzZswgNDSU4OBgnJ2dH5J5j2vXrjFjxgzCw8OJiori119/5fjx4yxevJjPP//8gbF5eXns3buXUaNGlR67evUq06ZNIzIyEgsLC7ZurXlotrwiaKjcPAEm9mDdtMzTarVgd3g8PTxtsTTWK1fM4ZjDgGbD9gG6zYTLf0L479D+Fa2pXRVeavUSm65sYun5pXzX57sayerZ3BYbEz22hMSWtt6UeQSq8M29tvj222/Zvn07ADExMfzyyy/06tULW1tNOfRx48Zx5cqV0vFDhw5FkiR8fHywt7fHx8cH0BSwu3nzJr6+vqVjfXx8HupLUFxcjIGBAa+88gqDBw9myJAhD+iTmZlJRkZGaXG5SZMmMWbMmNLz9/ceuHnzJgCdO3dm/vz5xMbG8uyzz5a5GriHm5vbAzr36dOn9PXck3ePXbt20bVr1wfcQm5ubqWv8X4daoK8ImiICAE3j4NrNygnbv/c7XTuZOQztM3DZZzv58CtAzQ2bYynpeeDJ5z9wd4Hzv2iLa2rjLm+OS96v8jR2KNcz6iZf19XqWC4rxMHoxJJzy2qfIJMg+LIkSMcOHCAU6dOERYWhp+fH15eXhXmq1S1dwCAp6cnISEh+Pj4MHfuXD799FN0dHQ4c+YMo0aNYseOHQQEBFRL57J6D0yYMIGdO3diaGjIgAEDOHToUKXz//kaytJ/48aNpW6hsuZrq/+BbAgaImnRkB2nMQTlsCssDn0dBf28y3cLZRZmcib+DH2a9Hn4gyVJ0PYFiA/Vvm+4CoxrPg4DpQHrLtY8SmN0O2dUJYKt52K1oJlMXZKZmYmlpSVGRkZERUURFBREfn4+R44cITU1tbQH8KMSFxeHkZEREydOZPbs2Zw7d46cnBwyMzMZNGgQS5YsecidZG5ujqWlJceOadyzv/zyS6Wlp6Ojo3F3d+ett95i2LBhhIeHP7LO98jMzOTo0aMMHz68xrIqQ3YNNURuHtf8LGd/oLhEzZ8R8fRpYYdJBZ27jsQcoVgU069xv7IH+IyBfR9qVgWDFtVU62phaWDJMI9hbL+2nTf93sTG8NH7DLRwNKODqxU/HotmYqcm5eZTyDQ8AgICWLFiBa1bt6Z58+Z06tQJR0dH5s2bR+fOnXF0dKRt27aUlDxakcGIiIiH+hJkZ2czfPhwCgoKNOXTv/76oXlr164t3Sx2d3dn9erVFV7n999/Z/369ejq6uLg4FBhN7Sqsn37dvr374+xcflVBbSGEKLGDyAAuIymOf2cMs5/DYTefVwBMu47V3LfuZ1VuV67du3EE82WV4T4opkQanWZp49dSRZN3tst/oqIq1DM9IPTRd/NfYW6HDlCCCE2vyTEgsZCFOXXRONH4kbGDeGzxkd8fOJjkVWYVSNZJ65p3pNVx6O1pN2Tz8WLF+tbBZlapKy/LxAsyrin1tg1JEmSElgGDAS8gfGSJHn/w9jMFEL4CiF8gaXA/d2d8++dE0I83C3laaOkGK4f1ISNluMn3Rl2BxN9HXo1tytXTJ4qj5N3TtK3cd+K6wP5vQAFGXC17svxupq7MtRjKFuvbqXX7714L/A9IlMjH0lWFw8bOrpZsfzIdQpUcolqGZnqoI09gg7ANSFEtBCiCNgIVOTUGg/8poXrPpncOAp5qeA9oszTxSVq/o5MpL+3fYUukKsZVylSF9HeoX3F13PtDkY2cHFnTbR+ZD7r+hkbBm1glOcojsYe5bndz/Fl8JePJOvtvp4kZxeyOVguUS1Tv6Smpj7U+8DX15fU1NT6Vq1MtLFH4ATc/8mLBcpsgSVJUhPADbh/S91AkqRgoBhYKITYUc7cqcBUgMaNyy+u9thzYRvom0HTvmWeDovNIDNfxTMtyl8NAFxJ14TbNbeqpGy0Uge8BsOFraAqAN3yM5RrA0mSaG3bmta2rXnT703+c+o/rL+0nhe9X8TWyLZasjp7WOPtaMaWc3d4obNr7SgsI1MFrK2tH9qEbshoY0VQlt+hvIL3zwFbhBD3r90bC00PzQnAEkmSPMqaKIRYKYTwF0L434svfuIoLoRLu8BrSLk35KNXUlBI0K2SJu5X0q5grGtMI+NGlV/XezgU5WhqG9UjpnqmvOn3JiXqEn6LerRF40g/J8JiMrienKNl7WRknly0YQhiAZf7njsDceWMfY5/uIWEEHF3f0YDRwA/Lej0eHLtIBRmQqtR5Q4JvJJMa2cLLIzKTyIDzYrA09Kzav0D3HqAgQVcqh/30P24mLnQ26U3m65sIr84v9rzh/k2QiHBH+frrrqqjMzjjjYMwVmgmSRJbpIk6aG52T90R5EkqTlgCZy675ilJEn6d3+3AboCF/8596nhwlZNtVH3smOWM/KKCI/NoIdnxSsiIQRX068+nERWHkpdjXsoag8U139S1gveL5BZmMmu67uqPdfezICuTW3YHnrnXlSajIxMJdTYEAghioHpwN/AJWCTECJSkqRPJUm6PwpoPLBRPPjpbAEES5IUBhxGs0fwdBqCgiyI+hNajtDcmMvg+LUU1AJ6elbsFkrMSyRblV11QwDQcqRmNRJW//v47ezb0dK6JasurEJVUv2uZiN8nYhJyyf4Vs37JMvIPA1oJbNYCLFHCOEphPAQQsy/e+wjIcTO+8bME0LM+ce8k0IIHyFEm7s/f9aGPo8lF3dAcT60mVDukMAryZga6NDGueLyuvc2iqtlCJr2hcZd4MDHkFu/kQ2SJPGm35vcybnzSL0LBrRywMxAh6WHrtWCdjK1ybx581i8eHG15x05coSTJ0+WPp88eTJbtmzRpmplsmHDhgeighQKxWO1SXwPucREQyH0N02BOWf/Mk8LIQi8kkK3pjboVFJu+Z4haGpRdsG6MpEkGPylZmVycF7V59USXRp1ob1De34I/4E8VV615pro6/BWn2YEXknmyOWkWtJQpiHxT0NQVzz//POlfQN++eUXXF1dHyh697ggl5hoCKRFw+2T0OejcpPIriblkJBVUOn+AGgihpxMnDDRM6meHvbe0PlfcHIptH4OXLtWb74WkSSJGW1nMHHPRJaFLmO2/+yqbXzf5cXOrqwPusX8Py9VyXg+7fz3zH+JSovSqkwvKy/e6/BepePmz5/PunXrcHFxwdbWlnbt2nH9+nWmTZtGcnIyRkZG/Pjjj3h5ebFr1y4+++wzioqKsLa2ZsOGDeTn57NixQqUSiXr169n6dKlAAQGBvLVV1+RkJDAokWLGD16NPHx8YwbN46srCyKi4v5/vvv6d697FIuJiYmTJs2jQMHDmBpacnnn3/Ou+++y+3bt1myZAnDhj2Y/3p/34B782fMmMHu3bsxNDTkjz/+wN6+YVbIlT8dDYGwjYCkufmWQ+AVTb39KhmCuxFDj0TPOWDRBP6YBkW5jyZDS7SxbcOoZqNYd3Ed80/Pp0Rd9YxhPR0Fcwe14GpSDksOXK1FLWVqQkhICBs3buT8+fNs27aNs2fPAjB16lSWLl1KSEgIixcv5l//+hdAaUOX8+fP89xzz7Fo0SJcXV15/fXXmTlzJqGhoaU39vj4eI4fP87u3buZM0fjlf71118ZMGAAoaGhhIWFVfjtPTc3l169ehESEoKpqSkffPAB+/fvZ/v27WXWEvr9998fMAS5ubl06tSJsLAwevTowY8//qi1903byCuC+iY7EU6v0PjozcvvOxx4NQUPW2OcLCruRJRRkMHNrJv0adLn0fTRN4ERy2HNYDjwSZ0Xo/snH3X+CDM9M1ZHriY8OZwJLSYw2G0wuuVsqN9Pf297xvo7893ha1gY6eLlYMaZG6l097TFv4lltVYYTzpV+eZeGxw7doyRI0diZGQEwLBhwygoKODkyZMP9AAoLNT0pY6NjWXcuHHEx8dTVFSEm5tbubJHjBiBQqHA29ubxMREANq3b8/LL7+MSqVixIgRFRoCPT290hLVPj4+6Ovro6urW2bfgNOnT2NkZESrVq0emH+v10G7du3Yv39/Nd6ZukVeEdQ3e2ZrMnoDFpQ7pEBVwunoVLo3q3w1sOTcEgACXKtXY/0BXLtBh9fgzA+a3IZ6RCEpmOU/i8+7fU5RSREfnviQj09+XKW5kiTx+Ugf+nvb89mfl5j482m+PXSNMStOMer7k1xNrNvubDJl80+DrFarsbCwKPW9h4aGcunSJQDefPNNpk+fTkREBD/88AMFBQXlyr2/bv+9YMUePXoQGBiIk5MTL7zwQoXN6nV1dUt1e5S+AffP11bfgNpCNgT1SeR2TRJXrzlgU35HozM30igsVtOzErdQWHIY265uY2KLiTSzLF9eleg7D2xbwLapkBVfM1laYKjHULYP386L3i+yK3oXF1OrFmWso1Tw7Xg/3hnQnBUT23H+w358Orwlt9Pyefb7k5y4llLLmstURI8ePdi+fTv5+flkZ2eza9cujIyMcHNzK+1DIIQgLCwM0NTod3LSrJzXrl1bKsfU1JTs7MoN+61bt7Czs+PVV19lypQpnDt3rsavQa1Ws3nzZp57rnzXbkNHNgT1gRBwajlsfQUa+UGXNyscHnglGT2lgo7uVuWOEUIwP2g+tka2vOH7Rs111DOCMWtAlafRU1X9LF9tI0kSr7V5DXN9c74OebiGfHkY6CqZ1rspAa0csDTW48XOruyY1gVHcwMmrTpDiJxvUG+0bduWcePG4evry6hRo0r9+xs2bODnn3+mTZs2tGzZkj/++APQhJeOGTOG7t27Y2Pzv3yaoUOHsn37dnx9fUsbypTFkSNH8PX1xc/Pj61btzJjxowav4bAwECcnZ1xd3evsax6o6za1A398dj3I9jznhAfm+6m+NoAACAASURBVAnx2wQh8tIrHd73yyNiwo+nKhxzOe2yaLWmlfg96ndtaakhdKNG1xXdhUi7qV3Zj8i6yHWi1ZpW4ljssRrJycgrEu0/2y9GLT9Rcc+GJxS5H8GTTZ32I5CpJreD4PT3mobx49aDYcXJYTdTcrmalMMzXhWHnZ2K01TueKhJfU1pMw7Gb4S0m7CyJ6TUfwTOuObjcDVz5f3j73Mn59FrCpkb6vJmn2YE30rnsJxvIPMUIxuCuqREBbtngpkz9P2k3JyB+9l/URPt0N+7YkNw4s4JPMw9cDAuv4fxI9N8IEw9DJICNk7QJJ3VI3pKPb555htUahXTD04nu+jRN32fa+9CE2sjFu29jFot1yZ6GunYseNDfQMiIuq+j3d9IhuCuuTYV5B0UROSqV+1ZK99FxNo4WiGi5VRuWMKigsISQyhc6PO2tL0Yaw9YMxaSL0O21+DasT01wbu5u583etrbmbeZPbR2RSrHy0iQ1epYFY/T6ISsnl3aziqErWWNW3YCLkwH6dPn34gQik0NBQfH5/6VqtGVPfvKhuCuuLYl3Dkc03DeK/BVZqSklNI8K30SlcD5xLPUaQuokujLtrQtHzcumvCXC/vgV1vgbp+b5odHTvyQacPOBl3koVnFj7yTW1Ym0a83bcZW0Jimbz6DJvOxnDudvoTf5M0MDAgNTX1iX+dTxtCCFJTUzEwqHqTKTmhrC4I+h4OfqoxAiNWVHnawUuJCAH9W1ZsCE7GnURXoYu/Q9l1irRKx9c0rTSP/heUejBoMSjKb5lZ24zyHMWtrFusjlyNnZEdU1tPrbYMSZJ4u68nDmYGfLwzkhPXNEX3xvm78OmIlujr1N/rq02cnZ2JjY0lOTm5vlWR0TIGBgY4OztXebxsCGqbojzNTdPjGRj5Q7Vumn9HJuJkYYi3o1mF407Gn6StfVsMdSrOOtYaveZquqmdWAIZMTDqRzC0rJtrl8Hb7d4mKT+JpeeXUlhSyHTf6Y+UNfxch8aMaudMfEYBvwffZtnh61xLzuGXKR0w0nvyPiq6uroVZubKPD3IrqHaJnQD5KdDj3erZQSSsgoIvJLM4NaOFd7UUvJTuJp+lU6OnbShbdWQJOj3CQz5GqKPwE99IT+j7q7/DxSSgvld5zOq2ShWhq9ky9VHLz+sq1TQ2NqIdwZ48e14P0JupfPtQbmctcyTjWwIahN1CZz6DpzbQ+Pq3ah/PxtDsVowvkPjCscFJwQD0NGh4yOr+cj4vwwvbIO0G5pSGfWIUqHko84f0dqmNWsj16IWNd+/GNamEaPbOfPTsWiuJcnlKGSeXGRDUJtE7Yb0m5rM4Wq4KkrUgt/O3KZbUxvcbIwrHHsm4QzGusa0sG5RQ2UfEbceGldRxGYI+71+dLiLQlLwfIvnuZV1i5Nx2qlNP2egF0Z6Sj7YcYGi4qcrokjm6UE2BLXJ1f1g6QZeQ6o17XBUEnGZBTzfseLVAMDZhLO0tWuLjqIefdjdZ0Hjzpocidjg+tMD6NekH7aGtmy4tEEr8mxM9Jk7qAVB0WkMWBIoJ57JPJFoxRBIkhQgSdJlSZKuSZI0p4zzkyVJSpYkKfTu45X7zk2SJOnq3cckbejTYBi2FF7+u9pRNRtO38LOVJ++lYSNJuUlcTPrJh0cOtREy5qjUMLo1WBiC+ufhfjwelNFV6nL2OZjOX7nOBHJ2kkKGt+hMatfao8kwUurz/Lz8RtakSsj01CosSGQJEkJLAMGAt7AeEmSvMsY+rsQwvfu46e7c62Aj4GOQAfgY0mS6i/8RNtIEphWryNRYlYBR68kM8bfGd1KumqdTdA08Wjv0P6RVdQaZo7w4k7QM4VfRkB8WL2pMtpzNKZ6pkzYM4GX9r7E+aTzNZbZu7kde2f0YGArB/6z+yJf/B3F6ehUErPKL4MsI/O4oI0VQQfgmhAiWghRBGwEhldx7gBgvxAiTQiRDuwHalBI//Fnx/k7qAU827byGOCzCWcx1TXFy8qrDjSrApZNYNJO0DGEtUPrzU1kY2jDzhE7ebvt28RkxzDpr0ksOL2AnKKcGsnV01GwdLwfw9o0Ytnh64xbGUTXhYdYfeKGnJQl81ijDUPgBMTc9zz27rF/MkqSpHBJkrZIkuRSzblPBUIItp6LpW1jCzxsKy9BcTbhLO3s26Gsx4Suh7D2gJf/0uQVrB2q6blQD9gY2jDFZwo7R+xkvNd4fo36lUHbBrHh0oZqtbz8JzpKBd8858u+mT1YP6UjvZrb8cmui7z523kKVPVbdkNG5lHRhiEoKxzmn1+PdgGuQojWwAHgXkeJqszVDJSkqZIkBUuSFPykZkJeuJPFlcQcRrWrfDVwJ+cOt7NvNwy30D+xaAwv7wP7VrB5Mvz9PhTW7Nv4o2Kka8TcjnPZOHgjnpaeLDyzsFq9DMpCkiQ87U3p1syGH19sx3sBXuwOj2fSqjNkFai0pLmMTN2hDUMQC7jc99wZiLt/gBAiVQhRePfpj0C7qs69T8ZKIYS/EMLf1rbylo2PI1tCYtDTUTCkdaNKx94rO93VqWttq/VomNrD5N2aXINT38HSthCytt6K1bW0acmP/X9kXPNxrL24lsO3D2tFriRJvNHLg2+e8yXkVjpjV5wiJi1PK7JlZOoKbRiCs0AzSZLcJEnSA54Ddt4/QJIkx/ueDgMu3f39b6C/JEmWdzeJ+9899tShVgv2XEigj5cd5oaVN2Y/GXcSOyM73M0bcFckHX1N9vGUA2DpqilUt6I7nP1Jk3MQfaROS1pLksS77d/F29qb90+8z41M7UX/DPd1YtXk9sRl5DNk6XGOXnkyV60yTyY1NgRCiGJgOpob+CVgkxAiUpKkTyVJGnZ32FuSJEVKkhQGvAVMvjs3DfgPGmNyFvj07rGnjvA7mSRnF1ZaYA6gRF1CUHwQXRp1eaSaOnWOS3tNGO2YtaDKhT//DdunwrrhsLCxZi/hdlCdqKKn1GNxz8XoKnR5ae9LXEm/ojXZPTxt2fVmNxpZGPLq2mCuJ9ePO0xGprpIj2O0g7+/vwgOrt/EJW2z+O/LfH/0OiEf9MXCSK/CseHJ4Ty/53kW9VjEQLeBdaShligphpwETdG69JsaAxCyBnKTwL03dHoDmvYDRe3mOkZnRvPqvlcpKC5g4+CNuJi5VD6piiRlF9Dny6O0amTOr692fDyMtcxTgSRJIUKIh8oUy5nFDYQDlxLxb2JZqREAjVtIQqrbQnPaQqkD5s6a6KKmfeCZ92FGqKZjW3IU/DoWvmkNB+ZB+q1aU8Pd3J01AWsoKiliRXjVS4NXBTtTA+YM9OJUdCrbzj16K00ZmbpCNgQNgJi0PKISsulXSSbxPU7FncLb2htLgyck907PGLq9DW9HwOhVYOsFJ76F77tA+OZau6yLqQujPUfzZ/SfxGbHEhgbSMDWAPbe2Ftj2ePbN6ZdE0sW/HVJDiuVafDIhqABcOCSpi9xnxaVG4I8VR7hyeGP52qgMpS60GoUTNyiWSXYt4Jtr8DuWRqXUi0wueVkFJKCT059wuyjs0nKS+KdwHf47vx3FJUUPbJchULi3/08SckpYmdomYFwMjINBtkQNAAOXkqiqZ1JpZVGAUKTQikWxQ0zf0CbWDSGyX9qKrcG/wy/T4SiXK1fxt7YnpFNRxIUH4SVgRV/jvyTEU1H8EP4D/Tb0o/locvJL85/JNmdPazxcjBllZx5LNPAkQ1BPZNVoCIoOpU+LeyqND44MRilpMTPzq+WNWsAKHWg/2eadphX/4af+0PKVa1fZmrrqQx2H8z3fb/H0cSRT7t8ysp+K/Gx8eH7sO8Zt3sckSmR1ZYrSRIvd3UjKiGbU9dTta63jIy2kA1BPXP0cjLFakG/KriFQFNWoqV1S4x0jWpZswZEh1dhwmbIioMfesL59aDFb9j2xvYs7L4QN3NN20ZJkujcqDPf9fmOH/v/SJ4qj4l/TSQwNrDasof5NsLKWI8fj0VrTV8ZGW0jG4J65sClRKyM9fBrXPnGb35xPhdSL9DOoV2lY584mvWF149DI1/4YxpsGK0xDLVMJ8dObB22lWYWzZh1ZBbnEs9Va76BrpJXurtx+HIyeyLia0lLGZmaIRuCekRVouZwVBLPeNmhVFQeax6WHEaxupj29k/4/kB5mDvBpN0w8Au4dRJWBUBGTOXzanpZfXON28jYkWkHp3Ek5kiZ4/JUeVxKvfRQm8xXu7vT2tmc97dHkJQtl62WaXjIhqAeOXszjayCYvpWwy2kkBRPx/5AeSgU0HGqpo5RfgasGQwptd9c3trQmh/7/4iLqQtvHnqThWcWci7xHAXF/7uxfxH8BWN3j6XP5j6surCq9LiuUsFXY9uQW1TC3K0R8saxTINDNgT1yIGLSegpFXRvZlOl8cEJwbSwaoGJXuUlqp94nNrBi9uhIAOWdYA/pkN2Yq1e0sHYgV8G/cIYzzFsuLSBSXsnMXDbQFLyU0gvSGfX9V10adSFxqaN+Trka1LyU0rnNrUzZe5ALw5GJbH6xM1a1VNGprrIhqCeKFEL9kTE062ZDcb6lfcbLiguICIl4skPG60OTu1g2hnNZnL4JvipDyRfrtVL6iv1+ajzRxwZe4TFPReTWZjJ1yFfs+XKFgpLCnm3/bvM6aDp1nrizokH5k7u4krfFvYs+OsS4bEZtaqnjEx1kA1BPXHqeioJWQU827ZqfXjCk8NRqVX42z9UJuTpxtQBBv4XpuzT1C/6uT+E/gYltdsXwNrQmgGuA5jccjI7r+9k9YXVdHbsjIeFB15WXtgY2nD8zvEH5kiSxOIxrbE10efVdcFciq+7yqsyMhUhG4J6Ytv5WEz1daq8PxCcGIyEhJ/9U7w/UBGNfOGV/ZpEtB2vw7d+cHQRpNVuo/lXfF7BwdiBbFU2E70nApobftdGXTkZd5Ji9f8yopPzkjmesI8hPS5SbHSSsT8cIVAuVy3TAJANQT2QW1jM3gsJDG7tiIFu1dpMnk04i5eVF2Z6ZrWs3WOMpSu8FggTNml+PzwfvvWF3TNB9WjZwZVhpGvE/K7zGe05mm5O3UqPd3PuRlZRFhdSLqAWajZd3sTQHUOZe2wuv11bSZHlZqQmnzFl23fM2xlJXlHtlNCQkakKlTunZbTO35EJ5BWVVKlBPUBhSSHhyeGM8xpXy5o9AUgSeA7QPDJj4dRyCFoGt07ByO+hkfZXVB0cO9DBscMDxzo7dkYhKdh0eRNLzi0hJDGEjg4dmek/E3dzdy6nXea/ZxYRpdjDmlO+/BkRzyvd3BjfsTFmBpU3JpKR0SayIagHtp27g4uVIf5NqlY9NCI5giJ10dObP/ComDtDwOeactc73oAfn4F2L4FbDzC2AecOoFN52e9HurS+Ob62vuyK3oWpnimfdvmUEU1HlPYm8LXzZZb/TF7++2Vmj1RxKtyEBX9FsXjfZdp7GNGnuT2DWrniaG5YK/rJyNyPbAjqmITMAk5cT+HNZ5qhqEISGcDZxLNISLS1b1vL2j2hNO0D08/Coflw9kdNETsAE3toOwk8ngHHNqCn3bIdr/i8wtHYo7zW+jVsjR7us93Ovh0Oxg5czDrChleWExGbyfawG2xNnElYVD4Ljoygv2s/Fo5qLa8SZGoV2RDUMTtC7yAEjPSrWrQQQEhCCJ6Wnpjrm9eiZk84BuYwaBH0fE/TIS3tBpxbC4FfQOAiUNwtgd35XxqjoAW6O3enu3P3cs8rJAWD3QazJnINKfkp+DjbcDDxCOqUFBobuxKrs4FDifEMWzqC7ye2o4WjvD8kUzvIm8V1iBCCrSGxtG1sUaWS06BpqXg28Sw9nHvUsnZPCcbWYN8SWgyB5zfD7KswfiO0mwyXdsEPPWBFdzjxDcSdr7U+CPcY4j6EElHC5iubCU0KZW3kWoZ7DGfns9sIcA3A0OYYucWpjFx+gq0hsbWqi8zTi1YMgSRJAZIkXZYk6ZokSXPKOD9LkqSLkiSFS5J0UJKkJvedK5EkKfTuY6c29GmoRMZlcTUpp8qbxAArwlagr9QvDU2U0TImttB8IAxeDLMuQsB/QaGE/R/Byl6w0AXWDNG4lWKDQa2uVGR1aGrZFG9rb5aHLueFv17AWM+Yf/v/G12FLjPazgAEg7pfxtfFgn9vDuP97REUFssdz2S0S41dQ5IkKYFlQD8gFjgrSdJOIcTF+4adB/yFEHmSJL0BLALuhcDkCyF8a6rH48DWc7HoKRUMae1YpfHXM66z98ZeXmr1ElYGVrWsnQyGFtDpdc0jMxZuB0HMGYgJgmOLNS4k00bQeRr4v6RpsakFvun9DaFJoRr3kK1PaQtSZ1NnhnoM5c8b29k1/hXWHrdkxdHrRNzJZOl4P5pYa+f6MjJSTQtgSZLUGZgnhBhw9/lcACHEgnLG+wHfCSG63n2eI4SoVvEcf39/ERwcXCO965oStaDTgoP4uViw8sWqZQe/c/QdAmMD2Ttq75PTn/hxJS8Nrh2Ac+vg5jEwstYYhPavgkHt+e5jsmIYumMo9kb2NLVsikLlwJFwXQpz3Hipc2um9W4qbyTLVBlJkkKEEA/dgLThGnIC7q8FHHv3WHlMAf6677mBJEnBkiQFSZI0Qgv6NEiColNJzi5kRBU3iVPyU9h/az9jPMfIRqAhYGQFrcdqqp6+vE9T5+jgp/BNG7iwtdYu62Lmwn+6/gcvKy8ScxM5kbwd7Deg7zGfdTffocfyRaw9dZ3iEu26rGSeLrQRNVRWDGSZywxJkiYC/kDP+w43FkLESZLkDhySJClCCHG9jLlTgakAjRs3rrnWdcwfoXcw0dfhGa+qtaTccW0HJaKE0Z6ja1kzmWrTuKNmoznuPPw5G7a8DBe2Qe/3wd5b65cb6jGUoR5DAVCpVVxLv8bR2KPsuPond3I3sijyL74P7cK/Ogxnol9nFAo5BkSmetSZa0iSpL7AUqCnECKpHFlrgN1CiC0VXfNxcw0VFpfg/9kB+nnb89XYyrdD1ELNkO1DsDeyZ3XA6jrQUOaRKSmGk99A4JegyoVm/aHti9BsQK0lq91DCMGxO8f46syPXM8KA0lgUdKVZf0/p7WzvKf0NJOSU8ivp2+TW1SMka4Oja0N8bQ3pZWTRZmuIW2sCM4CzSRJcgPuAM8BE+4fcHdf4Acg4H4jIEmSJZAnhCiUJMkG6IpmI/mJ4sjlZLILihnWplGVxgcnBBOTHcMbbd6oZc1kaoxSB7r/W5OxfGYlBK+C3ydq9hB8xoLvBHDw0ZS+0DKSJNHDuQc9nHuQmJvM3IPLOJu+lbHbZtBMOYVuHg4MauVIKyez0ozme6jVgtTcIkwNdKpc70qm4VOiFnx36Bo/BF4nX1WCrlJBUXHlbsMarwgAJEkaBCwBlMAqIcR8SZI+BYKFEDslSToA+AD3mrbeFkIMkySpCxoDoUazX7FECPFzZdd7nFYEQgieWxnEtaQcgv6vD7rKypft7xx9hxNxJzg05hAGOgZ1oKWM1igphusH4fx6uPwXqFVg4wnuvTX7DObO4NweLJpAcT4o9bWa0bz03ApWRiwDoURd0Ij8hKE0NfemlZM5tqb6JGQWcC0ph+jkXPJVmjBUUwMdbE30cTA3oGtTG3o0s8VAV/N/amdqgJmhzkOGRKbhoSpRM2tTGLvC4hjk48C/+zfHw9YEVYmamym5XE7MZmgbpzJXBFoxBHXN42QIfjtzm7nbIvh8pA8TOla+t3Em/gxT9k3h5VYvM7PdzDrQUKbWyE2FS39o9g/iQqEou+xxRjZg1wJcu2keTv6g++hfAE7GneR0/Gl2X99DnqoI59z3uZOqJDmnEDtTA5rameBha0JjK0Nyi0pIzi4kOaeQmym5RMY93CPBzECHXs3tCGjlQE9P2yo1UpKpOzLzVRy/msL6oFucik5lzkAvXu/pUebY8qKGZENQiyRmFdD3q6N4O5rx26udKq0tlKfKY9TOUSgkBVuGbcFQRy449kRRUgxp0RBzGnKTQNcIinIh4zbEh0J8OCA0qwT3Xhq3UvOBoKP/SJe7kn6F5/98nta2rVnedzn6ysrlJGQWEHwrTaOuWpCcXcjlhGwORiWRlluEvo6Cbk1t6OxhTWcPa7wdH3Y7ydQ+uYXFLNobReDVFG6k5AJgYaTLewFejO9Q/hdO2RDUMUIIXl5zlpPXU9n7do8qlZRYdHYRv1z8hdUDVuPvIHcie+rIz4Dbp+BGIETugOw4TWG8Tm9oiuMZVX8DeMe1HXx44kN0FDp4WnrSy7kXAW4BuJq5VusGXlyiJvhWOnsvJHD4chK3UvMAaGZnwuh2zoz0c8LOTHZj1hZFxWp2hcWRryrBydKQBXsucS0phz4t7PFxMqezhzV+LhboVOJ6lg1BHbP6xA0+2XWReUO9mdzVrdLxCbkJDNo2iGEew5jXZV7tKyjTsFGXQPRhOLUMrh8ChQ64doc246HlyGpFJJ24c4IzCWcITQrlfNJ5BAIjHSPczN0Y4j6Ekc1GYqxbvSzlhMwCDkYlsjUklnO3M1BI0Lu5HW/1aUYbF4vqvloZIDWnkMi4LC7GZ5GRp0JHIaGj1BjrbefucDstr3SspZEuS8e3pVszm2pdQzYEdcjFuCxGLDtB92Y2/DTJv0rfvBaeWcjvUb+z+9ndOJlUvTKpzFNAQoQmaS1yB6Tf0JS56DhVUyjPsHrJhom5iRyJOUJ0ZjQXUi4QnhKOqZ4pU1pNYaL3xCq5j/7J9eQctp2L5dfTt0nPU9G3hT2z+nni3UiulloZarXgq/1X2BISS0JWQelxPaUClVrNvduzt6MZ7wxoTlM7E64mZdOqkfkjrcBkQ1BHZBWoGP7dCXILi/lrRnesTSr/YKXkpxCwNYCBbgP5T9f/1IGWMo8larUmIunkUrhxFHSNNXsITftC84BqGwWA8ORwVoav5GjsUeyM7PCx8aGxaWPa2rfF394fE72qV3/JKSxm9fEbrDwWTXZBMZ3crbAzNcDJ0pDeze1o27hy18XTRIlaMHdbOJuCY+njZUcnd2taNjLDu5EZFkaaFZ9aLVCp1egpFVrZi5ENQR0ghOC1X0I4FJXEb1M70d61aj7dr0K+Ym3kWv4Y/geu5q61q6TMk0FCBJz+Aa7shdxk0DHU9FNo1k+Tt2DRRJPjUEWC4oPYcHEDt7NvE5sdS5G6CF2FLoPcBjHaczRKSUmJKMHDwgNTPdMKZWXmqfjpeDRHrySTla8iNj2fYrXA3FCXXs1tGdjKkX7e9iir2JjpSURVoubfm8LYGRbHW880ZWY/zzrZdJcNQS0jhGDxvsssO3ydD4d4M6Vb5fsCABkFGQzYOoCeLj1Z1OOJy6WTqW3Uaog/rymGF75Zk90MICnA2FYTcSQp/vcwtNRsQFu5afIbTBw0pbhtvUBXE6VWWFJIWFIY+27tY+f1neQX5z9wyaYWTXmt9WsMcB1QpZtXVoEmvPHgpSSOXE4iNbcIZ0tDJnZqwmAfR1ystNsZTpsUqEpIyy0iI09FXlExablFXE/OJSm7AGtjPWxN9bE11cfT3hRny6q9jsLiEt789Tz7LibyXoAXb/QqO9SzNpANQS0ihGDhX1H8EBjNOH8XFo7yqbJ1Xxa6jBVhK9g2bBvNLJvVsqYyTzSqAki+BAkXIDMGsuKgRAVCDQhQF0N+OmQnasJYSwr/N1ehA3bemmJ6zu01LicjKzILMwmKD8JQxxAhBFfSr7D35l6upF/By8qLns49aWbZjIyCDJLzk0nOTwagrV1bWtm0wkxPE16aXpCOQNDIyIkDUYn8ePo4l2KLURfZ09TOBC8HU5rbm9LcwRR/VyusjCveDBdCEJuez6X4LAqK1egqJPKKSsguUOHdyJx2TSxLVxxFxWpi0/O4lZZHbHo+JSVqJElCIWmKomXmqUjLKyI9t4i0PJXm593HvaS7f2KspyS36H/ndJUS66d0pKO7dYU6H7+WwsK/ooiMy+KTYS2Z1MW1Sn9abSEbglpCrRZ8siuStaduMbFTYz4d1qrKvYizi7IZsHUAHRw6sKT3klrWVEbmPtQlmvyF3BRNmGp8GNwJgTvnoTBTYxjceoKlK5g6QCM/jZEwsqJEXcKu6F38HvU7F9MuohaaEgYKSYGVgRUqtYrMwswqqeFm2Anj/AHEJFgRm65ZeegqJQa2csTFypDLCdnkFZVgqKvEQE+Jvo6CuIx8LsZlkVVQfvc4a2M9zI10ySssISm7AHUltzlTfR0sjfWwNNbDykgXS2M9rEuf62FhpIuxvg5mBrq42RpjZqBLgaqElJxCErMKeGdLOOm5RfwxrRuNrTUrg8x8FVHxWZy+kUZ4bAZRCdnEpufjZGHIB4NbMNCnan1JtIlsCGqBErXg/e0RbDwbwyvd3Hh/cItq+fl+CPuB70K/Y+OQjbS0blmLmsrIVBG1GhLC4cIWuHYQchIhL/V/563cwdEXzBqBqQPZhhbcEUVYFxdjqdBFx8oDtZ03V4vSuJpxlZyiHNRCjZWhFQiIyY5BIPC09ORS6iXWXVxHjiqH1ratGdBkCHbK1gRdga0hseSpSnC3McbcUJeC4hLyi0ooUKmxNdUv3VT1djTD1EAXVYkaQ10lRnpKTt9I43BUEkV3jzmaG9DE2pgm1ka4WBmhp1SgFqK0RLKZgS56OjXbxL6RksuIZSdQC4GJvg45BcVkF2oMlSRBU1sTmjuY0tHdmrH+zujr1E99J9kQaJn8ohJmbQrlrwsJvPlMU2ZVc7MnOCGYV/e/Sg+nHnzzzDe1qKmMTA0pzNGU3I49q1k1JERoDERxQdnjFTrQYpimi1vjzqAsv3FOVlEWO6/tZNOVTdzIvAGAlYEV1gY22BjaYGdki5Gu5hu2t7U3Aa4BDbb+VmhMBuuDbiEBxvo6NLIwwM3GhPaulqVRQPWNbAi0SEJmAa+uC+ZCXCYfDK76xvA9YrJiGL9nPJb6lqwftB5zUVVFAwAAFz9JREFUffNa0lRGppYQAgoyNQahMEeT9axQavYeru6Hc79oXEz65uDSXrOCsGsJrZ4Fk4d7cgghuJF1g5N3ThKdGU1yfjIpeSkk5ydTUFJAibqEHFUOFvoWeFt7Y6A0YKD7QAJcAyj8//buPEqusszj+PeppZd0Op2tEwNJk4QEAqJJmJ6oCIqEjIg6wRkVIiNB0RwPenRUPIKKR5xhBI9ncGPUGIW4wYAMh6i4hADKIpogkUQS6CaYfe+E7k7vVc/8cW83RdPVW3W6qnJ/n3Pq3Fv3vm/d93Z11VPv+973val27tx6J4dbD5OIJSiJl1ASL2HqmKnMHDeT0yeeTiKWeNmxtjZs5bQJpxGPRWvmVQWCEfJY/SE+fsdTtHWm+OayhSw+Y+qQ8rd0tnD5/ZdzsPUgP7v4Z9SMK76b7IgMqONYcGvPurVB/0PT3uAyV4vDrDcFYx/mLA6uVhpETdrdWb9vPXc/dzd7mvdwqPUQe47t4Z2z38mWhi3UH62nLF5GR7qjp8+i28SyiSw5ZQnzq+dTWVLJ9zd9n6cPPs3imsXc/KabhzWIrlgpEOSotSPF1x94jpWPbGNO9Vi+829nM2dK/9dT9+bufO7Rz/Grbb/iu0u+yzknnXOcSitSgA4+C3+9A7beD4eeDbaNOznocygbB6WVUNq9rIRJp8KM1/Vc1pqpK93FrRtvZdWmVVSXV3PDOTdw3vTzAEilU7Sn2tnTvIf6o/Ws3b6W3+/6Pe3hVVLV5dW8ZcZbuOu5uzh7ytm8ftrraU+105HuwN05Y9IZzK+ez/jS8VQkK15Wm+hKd7G9cTv7W/YzuTxovhqTGEM8Fqels4XmzmaaO5oBOGnsST1jLtydxo5GWrtaKU+UUxIvIZVOUZooJRkbvXtOKxAMUzrt/HrzPm7+zVZ2NLSwbNEMrn/HmYwpGfpUvHduvZMb/3QjH13wUT4y/yPHobQiReLozmCUdP06OPw8tDdBe2PwyPxFHy+B8TVBgCgbl7Gsgqrp1I2pZOrkMxk3YVYwRiJL7aIz1cmOph3sPbaXs6eczZjkGH657Zfc8PgNtKXaSMaSlMRLSHv6ZeMmDGNS+STGl46nqaOJhrYGOtOdgz7NsngZyXiSrnTXK8ZjAJQnylk4ZSHzq+czc9xMShOlHG49THminDnj5zB7/OwRrbEoEAzDE9sO88X7NvPc/mbmTBnLfyw9izecmv064f78fufv+fhDH+fck8/lWxd8i5hpqL3IK7hDZ0vQ/7BvM/z9kWBMRFvjS8GirTHY3z14rlssEQyiq6gO+iEqpgSD5SqmvDSIbtIcKKvqCRhd6S5iFuv5PKY9Td2ROrY0bKGpo4nGjkYOtBzgaNtRKksqmVQ+iTnj5zCtYhqH2g5xuPUwrV2tdKW7GJscS0WygrElY0l7mj3Ne2hoa6Aj1UEilmDqmKlUJCs41nmMznQniViC3c27Wb9vPc8ffR7v41bvMYtRU1nDxLJgloL5U+ZzxZlXMLn8pcnm9jbvZVL5JEriA3dIKxAMQVtniq/99ll+8NgL1Ewcw6f/6XTe/pppwxoS7+48vudxPvnwJ5lVNYvb3npbz1UQIpKDY4fg0HPBwLnmA8E9HpoPhssDQZ9E84HgLnGZEmXBzYAqJgVBo2p6MCXHhJlBp3ZXezDwrnF38NrtjcG2eDLIGy8NRmwnyoJZYBNlUFIRTAY4viZo0hpiJ3R7qp0djTvoTHcyuXwyzZ3N1B2po+5IHfVH62nuaKYz3cHGg38laQmuOvMKViz8GA/vfJhr/nANV8+/mg+/9sMDHidbINCthnrZtOtFPnXXRuoONPP+15/CdRfPG3Iz0NG2o2w8uLGnffKZw88wo3IGty6+VUFAZKRUTA4e/XGHtqPhaOrn4XB9ECCOHYaWQ0Gg2PPUy8dKZEqUB01RibJgZHZXG3R1BMtsTUSJMph4KpSPD4JHRwt46qW+j9KqYB6orvbgNS1OqcWYG4sFA/06W5kSSzB7zETeGktCVwwO7YPdT7LDO/jWhCr+Z/Mq/rD3CbY0bCHlqUEP4MtGgSD0Ymsn31pXx+2P/51JY0tY/cFFvPm06kHnP9hykAd3PMjaHWvZsG8DKQ+Gn88ZP4frX3897zz1nbrjmMhoMwv6DsonwJR52dO1N8GR7dC0L7hNaFlV0JHdT78D6VTwZZ5qD5qrmvYFl8/u3xws2xqDIFBSEbxGe3OQpr0JUh1BkInFgz6R7ofFgs7xVCe0NgQD/OKJoMZy9hXUVE3nqxbnHJq48fm7mV89n60NW4fUb9GXEQkEZnYR8A2Cm9evcvebeu0vBX4E/ANwGLjU3f8e7rsOuApIAR9399+ORJkGo70rxebdjdy/aS/3PrWbIy0dXFo7g+vedgZVYwbuyd/RuIOHdj7Euh3r2HhgI44zc9xMPnDWBzjv5POYO2HugDM1ikgBKK2EV50VPAYrFoeSMcCYIGBMOAVqXnfcitjNgHcB5y9cQWVJJYvvXkxXOvt0G4ORcyAwszhwK7AE2AWsN7M17v5MRrKrgCPuPsfMLgNuBi41szOBy4BXAycBD5jZae7e90xPg5BKO42twSRSR1s6aDjWyYGmNvY3trP/xTYONLXxYmsnR1s62d7QQirtlMRjvPn0aj6xeC5nnfzywV1pT3Ow5WDP9Lw7mnaws2knWxu2sr1xOwDzJs7j6gVXc2HNhZw6/lTdw1VEjrsJZcH9J5KxZEHUCBYB9e6+DcDM7gSWApmBYCnwpXD958C3Lfi2XArc6e7twAtmVh++3h/7O2B9w24u/tG1dHmatDsdnSnautK0dXbR3hXOtAgvLS1YL0/GKS+JU1pmlIyNseCUGFXlcSZXJonF0txe30W6Lrh0rT3Vzu6m3exq3tVz/TFA3OKcNPYkZlfN5n3z3sd5089jRuWMYf7pRERyk4glCiIQnAzszHi+C+hdP+pJ4+5dZvYiMCnc/kSvvH3ep9HMVgArAMpmlrMzHbQgGQZJsBIjhjHGDAvSEzPDMMyCy7DMgvSdQJcZ7ek4R1sT7G5LEI/FiVvwMDMSsQQ142o49+RzmVE5I3iMm8G0imkvG2AiIpJPyVgy/01DhL+3e+l9TWq2NIPJG2x0XwmshPDy0SvzP/uoiEi+JeO5Nw2NxKimXUBm28h0YE+2NGaWAKqAhkHmFRGRLBKWyLlGMBKBYD0w18xmmVkJQefvml5p1gDLw/V3Aw96MJJtDXCZmZWa2SxgLvDnESiTiEgkjESNIOemobDN/2PAbwkuH/2hu//NzL4MbHD3NcAPgB+HncENBMGCMN1dBB3LXcBHc7liSEQkakaiRjAivZ7ufj9wf69tX8xYbwPekyXvjcCNI1EOEZGoScaTdKQ6cnoNzXwmIlLEErEEnan8dxaLiEieJGNJujz/ncUiIpInyVhSNQIRkShLxBKqEYiIRJlqBCIiETcSk84pEIiIFLFErDBGFouISJ6oRiAiEnEjMfuoAoGISBEbifsRKBCIiBSxZCxJylOkPT3s11AgEBEpYsl4cH/1XJqHFAhERIpYwoK5Q3NpHlIgEBEpYqoRiIhEnGoEIiIRpxqBiEjEJWJhjSCH+YYUCEREilgyFtQIOj1PgcDMJprZWjOrC5cT+kizwMz+aGZ/M7OnzezSjH23m9kLZrYxfCzIpTwiIlHTEwjyWCO4Fljn7nOBdeHz3lqAK9z91cBFwNfNbHzG/s+4+4LwsTHH8oiIREp301A++wiWAqvD9dXAJb0TuPtz7l4Xru8BDgDVOR5XRETIqBHk8aqhqe6+FyBcTukvsZktAkqA5zM23xg2Gd1iZqU5lkdEJFJ6OotzCASJgRKY2QPAq/rY9fmhHMjMpgE/Bpa790yKcR2wjyA4rAQ+C3w5S/4VwAqAmpqaoRxaROSE1V0jyKVpaMBA4O4XZttnZvvNbJq77w2/6A9kSTcO+BXwBXd/IuO194ar7WZ2G3BNP+VYSRAsqK2t9YHKLSISBSNRI8i1aWgNsDxcXw7c1zuBmZUA9wI/cve7e+2bFi6NoH9hc47lERGJlJGoEeQaCG4ClphZHbAkfI6Z1ZrZqjDNe4E3AVf2cZnoT81sE7AJmAz8Z47lERGJlJHoLB6waag/7n4YWNzH9g3Ah8L1nwA/yZL/glyOLyISdYXQNCQiInmkuYZERCJOs4+KiEScagQiIhGn2UdFRCKu5/JRV41ARCSSCmH2URERyaO4xQF1FouIRJaZkYwl1VksIhJliVhCNQIRkShTjUBEJOJUIxARiTjVCEREIi4ZS6pGICISZWoaEhGJuGRcTUMiIpGWMNUIREQiTTUCEZGIU41ARCTi8lojMLOJZrbWzOrC5YQs6VIZN65fk7F9lpn9Kcz/v2ZWkkt5RESiKBlL5nX20WuBde4+F1gXPu9Lq7svCB//nLH9ZuCWMP8R4KocyyMiEjn5vnx0KbA6XF8NXDLYjGZmwAXAz4eTX0REAvkeWTzV3fcChMspWdKVmdkGM3vCzLq/7CcBR917bquzCzg5x/KIiEROrjWCxEAJzOwB4FV97Pr8EI5T4+57zGw28KCZbQIa+0jn/ZRjBbACoKamZgiHFhE5seVaIxgwELj7hdn2mdl+M5vm7nvNbBpwIMtr7AmX28zsYWAhcA8w3swSYa1gOrCnn3KsBFYC1NbWZg0YIiJRk++5htYAy8P15cB9vROY2QQzKw3XJwNvBJ5xdwceAt7dX34REelfIpbIax/BTcASM6sDloTPMbNaM1sVpjkD2GBmfyX44r/J3Z8J930W+JSZ1RP0Gfwgx/KIiEROrjWCAZuG+uPuh4HFfWzfAHwoXH8ceE2W/NuARbmUQUQk6vLdNCQiInmW76YhERHJs2QsScpTpD09rPwKBCIiRS4ZTwIMu1agQCAiUuQSFnT3DrefQIFARKTIqUYgIhJxqhGIiERcd41guFNRKxCIiBS5ZExNQyIikZaIqWlIRCTSumsECgQiIhHVXSNQ05CISESpRiAiEnHqIxARiTjVCEREIk6Xj4qIRJyahkREIk41AhGRiFONQEQk4vI615CZTTSztWZWFy4n9JHmLWa2MePRZmaXhPtuN7MXMvYtyKU8IiJR1D37aJfnp2noWmCdu88F1oXPX8bdH3L3Be6+ALgAaAF+l5HkM9373X1jjuUREYmcfM8+uhRYHa6vBi4ZIP27gV+7e0uOxxURkVC+O4unuvtegHA5ZYD0lwF39Np2o5k9bWa3mFlptoxmtsLMNpjZhoMHD+ZWahGRE8hx7yw2swfMbHMfj6VDOZCZTQNeA/w2Y/N1wDzgH4GJwGez5Xf3le5e6+611dXVQzm0iMgJrbtGsL1xO+4+5PyJgRK4+4XZ9pnZfjOb5u57wy/6A/281HuBe929J2R11yaAdjO7DbhmkOUWEZFQIpbg7bPfzr319/Ji+4tc/4brmVw+uWd/Kp3ikd2PZM+f4/HXAMuBm8Llff2kXUZQA+iREUSMoH9hc47lERGJpK+c+xXOnHgmtzx5C0t+voS3znwrc8bPoTPVyZrn17CreVfWvDacakRPZrNJwF1ADbADeI+7N5hZLfARd/9QmG4m8Bgww93TGfkfBKoBAzaGeZoHOm5tba1v2LBh2OUWETlRbW/czs+2/Iz7nr+PY53HAFg4ZSGXn3E5F8266El3r+2dJ6dAkC8KBCIi/Ut7mo5UBylPUZGsAMDM+gwEuTYNiYhIAYpZjLJE2eDSHueyiIhIgVMgEBGJOAUCEZGIUyAQEYk4BQIRkYhTIBARiTgFAhGRiCvKAWVm1gQ8C1QBLw7jJYaTbzSP1Ve+ycChUTze8cozmHzZzvVEOLdsBvv+jtTx8vk3KcT/5eHmG2ye3uecr3M73d0rX7HX3YvuAWwIlyuHmX/I+UbzWH3l6z7nQirn8TpWtnM9Ec5tqOdcSOU8kf+Xj/ffpPc55+vcsv3ti71p6BejmG80j1Us+YqhjMPNN9plHK4T+W9SDPmKoYwD5ivWpqEN3sd8GSeyKJ1zlM61W5TOOUrn2q1QzjlbOYq1RrAy3wXIgyidc5TOtVuUzjlK59qtUM65z3IUZY1ARERGTrHWCEREZIQoEIiIRFzBBQIzczP7ccbzhJkdNLNf5rNco8HM3hWe/7x8l+V4ifL7C2BmA96B70Qz0Dmb2cPhXQ2LVrF/dgsuEADHgLPMrDx8vgTYPZQXMLNiveHOMuBR4LKhZDKz+PEpznGR8/srUoCG9dktFIUYCAB+Dbw9XF8G3NG9w8wWmdnjZvZUuDw93H6lmd1tZr8Afjf6Rc6NmY0F3ghcRfjPZGbnm9kfzOxeM3vGzL5rZrFwX7OZfdnM/gS8IX8lH5bhvL+PmNmCjHSPmdlrR7XUIyR8X3+Z8fzbZnZluP53M7vBzP5iZpuK9Rdmb/2dc7Hr57Ob7T2+2My2mtmjZvbNQqgNF2oguBO4zMzKgNcCf8rYtxV4k7svBL4I/FfGvjcAy939glEr6ci5BPiNuz8HNJjZ2eH2RcCngdcApwL/Em6vADa7++vc/dFRL21uhvP+rgKuBDCz04BSd3961Eo8ug65+9nAd4Br8l0YGVC2z+4rhP/z3wPe5u7nAtWjVMZ+FWQgCD/gMwl+Ld7fa3cVcLeZbQZuAV6dsW+tuzeMSiFH3jKCL0jC5bJw/c/uvs3dUwS/nM8Nt6eAe0a3iCNjmO/v3cA7zCwJfBC4fVQKmx//Fy6fJPg7SWHL9tntyzxgm7u/ED6/o5+0o6aQ29LXAF8DzgcmZWz/D+Ahd3+Xmc0EHs7Yd2yUyjaizGwScAFB27kDccAJviR7D/Toft4WBodiNaT3191bzGwtsBR4L1DMnYtdvPxHWO87jLeHyxSF/RkdioHOuSj189ldQ9/na6NbwsEpyBpB6IfAl919U6/tVbzUuXjlqJbo+Hk38CN3P8XdZ7r7DOAFgl//i8xsVtg3cClBh9SJYDjv7yrgm8D6Iq75AWwHzjSzUjOrAhbnu0Cj4EQ952yfXej7fLcCs8MfORB8pvOuYAOBu+9y92/0seurwFfM7DGC6HsiWAbc22vbPcD7gD8CNwGbCf7BeqcrSsN5f939SaARuG0UijjiwqvZ2t19J3AX8DTwU+CpvBbsOIrAOff32X3F+bp7K3A18BszexTYz/CmlR5RmmKigJnZ+cA17v6OfJelEJjZSQRNRfPcPZ3n4gyZmc0Hvu/ui/JdltESxXMeiJmNdfdmMzPgVqDO3W/JZ5kKtkYgksnMriC4uujzRRoEPkLQMfiFfJdltETxnAfpw2a2EfgbQVPo9/JcHtUIRESiriBqBGY2w8weMrMtZvY3M/tEuH2ima01s7pwOSHcfrmZPR0+Hg+rn92vdZGZPWtm9WZ2bb7OSUSkWBREjcDMpgHT3P0vZlZJcP30JQRXjTS4+03hl/oEd/+smZ0DbHH3I2b2NuBL7v66cKqF5wimLdgFrAeWufsz+TgvEZFiUBA1Anff6+5/CdebgC3AyQTXjK8Ok60mCA64++PufiTc/gQwPVxfBNSHA7A6CAZ3LB2dsxARKU4FEQgyhdfXLiToGJzq7nshCBbAlD6yXEUwdw0EwWNnxr5d4TYREcmioEYthpM33QP8u7s3BldX9Zv+LQSBoHvahb4y5L/tS0SkgBVMjSCcQ+Ye4Kfu3j3Xyv6w/6C7H+FARvrXEow0Xeruh8PNu4AZGS87HdhzvMsuIlLMCiIQhAMrfkDQAfzfGbvWAMvD9eXAfWH6GoKJud4fzvjXbT0wN5ySoYRgStg1x7v8IiLFrFCuGjoXeATYBHQPFvocQT/BXUANsAN4j7s3mNkq4F8J5i8B6HL32vC1Lga+TjA9wQ/d/cZROxERkSJUEIFARETypyCahkREJH8UCEREIk6BQEQk4hQIREQiToFARCTiFAhERCJOgUBEJOIUCEREIu7/AX45HTw2rwuQAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 720x576 with 1 Axes>"
       ]
      },
      "metadata": {
     }
    ],
    "source": [
-    "data_by_day.loc['2020-03-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "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>cases</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>cases_diff</th>\n",
-       "      <th>deaths_diff</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "      <th>cases_m7n</th>\n",
-       "      <th>deaths_m7n</th>\n",
-       "      <th>admissions_m7n</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>1129</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>314927</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>120.0</td>\n",
-       "      <td>-5539.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>970.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.200248</td>\n",
-       "      <td>-0.766067</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>1440</td>\n",
-       "      <td>10</td>\n",
-       "      <td>316367</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>311.0</td>\n",
-       "      <td>5369.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>1051.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.217021</td>\n",
-       "      <td>-0.779374</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>1077</td>\n",
-       "      <td>4</td>\n",
-       "      <td>317444</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>-363.0</td>\n",
-       "      <td>-6.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>1097.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.226425</td>\n",
-       "      <td>-0.787086</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>5</td>\n",
-       "      <td>318484</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>-37.0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>1094.142857</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.225776</td>\n",
-       "      <td>-0.787540</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3</td>\n",
-       "      <td>319197</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>-327.0</td>\n",
-       "      <td>-2.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>1079.428571</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.222740</td>\n",
-       "      <td>-0.779828</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 14 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  deaths  cases_culm  deaths_culm  cases_diff  deaths_diff  \\\n",
-       "2019-12-31      0       0           0            0         NaN          NaN   \n",
-       "2020-01-01      0       0           0            0         0.0          0.0   \n",
-       "2020-01-02      0       0           0            0         0.0          0.0   \n",
-       "2020-01-03      0       0           0            0         0.0          0.0   \n",
-       "2020-01-04      0       0           0            0         0.0          0.0   \n",
-       "...           ...     ...         ...          ...         ...          ...   \n",
-       "2020-08-14   1129   -5359      314927        41347       120.0      -5539.0   \n",
-       "2020-08-15   1440      10      316367        41357       311.0       5369.0   \n",
-       "2020-08-16   1077       4      317444        41361      -363.0         -6.0   \n",
-       "2020-08-17   1040       5      318484        41366       -37.0          1.0   \n",
-       "2020-08-18    713       3      319197        41369      -327.0         -2.0   \n",
-       "\n",
-       "            newAdmissions  cumAdmissions   deaths_m7     cases_m7  \\\n",
-       "2019-12-31            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-01            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-02            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-03            NaN            NaN    0.000000     0.000000   \n",
-       "2020-01-04            NaN            NaN    0.000000     0.000000   \n",
-       "...                   ...            ...         ...          ...   \n",
-       "2020-08-14            NaN            NaN -723.714286   970.428571   \n",
-       "2020-08-15            NaN            NaN -736.285714  1051.714286   \n",
-       "2020-08-16            NaN            NaN -743.571429  1097.285714   \n",
-       "2020-08-17            NaN            NaN -744.000000  1094.142857   \n",
-       "2020-08-18            NaN            NaN -736.714286  1079.428571   \n",
-       "\n",
-       "            admissions_m7  cases_m7n  deaths_m7n  admissions_m7n  \n",
-       "2019-12-31            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-01            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-02            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-03            NaN   0.000000    0.000000             NaN  \n",
-       "2020-01-04            NaN   0.000000    0.000000             NaN  \n",
-       "...                   ...        ...         ...             ...  \n",
-       "2020-08-14            NaN   0.200248   -0.766067             NaN  \n",
-       "2020-08-15            NaN   0.217021   -0.779374             NaN  \n",
-       "2020-08-16            NaN   0.226425   -0.787086             NaN  \n",
-       "2020-08-17            NaN   0.225776   -0.787540             NaN  \n",
-       "2020-08-18            NaN   0.222740   -0.779828             NaN  \n",
-       "\n",
-       "[232 rows x 14 columns]"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data_by_day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "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>cases</th>\n",
-       "      <th>cases_culm</th>\n",
-       "      <th>deaths</th>\n",
-       "      <th>deaths_culm</th>\n",
-       "      <th>newAdmissions</th>\n",
-       "      <th>cumAdmissions</th>\n",
-       "      <th>deaths_m7</th>\n",
-       "      <th>cases_m7</th>\n",
-       "      <th>admissions_m7</th>\n",
-       "      <th>cases_m7n</th>\n",
-       "      <th>deaths_m7n</th>\n",
-       "      <th>admissions_m7n</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2019-12-31</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-01</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-02</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-03</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-01-04</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-14</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-5359</td>\n",
-       "      <td>41347</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-723.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.685296</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-15</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>10</td>\n",
-       "      <td>41357</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.285714</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.714571</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-16</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>4</td>\n",
-       "      <td>41361</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-743.571429</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.731537</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-17</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5</td>\n",
-       "      <td>41366</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-744.000000</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.732535</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-08-18</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>3</td>\n",
-       "      <td>41369</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-736.714286</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>-1.715569</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>232 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            cases  cases_culm  deaths  deaths_culm  newAdmissions  \\\n",
-       "2019-12-31    0.0         0.0       0            0            NaN   \n",
-       "2020-01-01    0.0         0.0       0            0            NaN   \n",
-       "2020-01-02    0.0         0.0       0            0            NaN   \n",
-       "2020-01-03    0.0         0.0       0            0            NaN   \n",
-       "2020-01-04    0.0         0.0       0            0            NaN   \n",
-       "...           ...         ...     ...          ...            ...   \n",
-       "2020-08-14    NaN         NaN   -5359        41347            NaN   \n",
-       "2020-08-15    NaN         NaN      10        41357            NaN   \n",
-       "2020-08-16    NaN         NaN       4        41361            NaN   \n",
-       "2020-08-17    NaN         NaN       5        41366            NaN   \n",
-       "2020-08-18    NaN         NaN       3        41369            NaN   \n",
-       "\n",
-       "            cumAdmissions   deaths_m7  cases_m7  admissions_m7  cases_m7n  \\\n",
-       "2019-12-31            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-01            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-02            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-03            NaN    0.000000       0.0            NaN        0.0   \n",
-       "2020-01-04            NaN    0.000000       0.0            NaN        0.0   \n",
-       "...                   ...         ...       ...            ...        ...   \n",
-       "2020-08-14            NaN -723.714286       NaN            NaN        NaN   \n",
-       "2020-08-15            NaN -736.285714       NaN            NaN        NaN   \n",
-       "2020-08-16            NaN -743.571429       NaN            NaN        NaN   \n",
-       "2020-08-17            NaN -744.000000       NaN            NaN        NaN   \n",
-       "2020-08-18            NaN -736.714286       NaN            NaN        NaN   \n",
-       "\n",
-       "            deaths_m7n  admissions_m7n  \n",
-       "2019-12-31    0.000000             NaN  \n",
-       "2020-01-01    0.000000             NaN  \n",
-       "2020-01-02    0.000000             NaN  \n",
-       "2020-01-03    0.000000             NaN  \n",
-       "2020-01-04    0.000000             NaN  \n",
-       "...                ...             ...  \n",
-       "2020-08-14   -1.685296             NaN  \n",
-       "2020-08-15   -1.714571             NaN  \n",
-       "2020-08-16   -1.731537             NaN  \n",
-       "2020-08-17   -1.732535             NaN  \n",
-       "2020-08-18   -1.715569             NaN  \n",
-       "\n",
-       "[232 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbds = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
-    "dbds.loc['2020-07-03', 'cases'] = 576\n",
-    "\n",
-    "dbds = dbds[['cases', 'cases_culm']].shift(-25).merge(dbds[['deaths', 'deaths_culm']], left_index=True, right_index=True, how='outer')\n",
-    "dbds = dbds.merge(hospital_data[['newAdmissions', 'cumAdmissions']].shift(-14), how='outer',\n",
-    "    left_index=True, right_index=True)\n",
-    "\n",
-    "dbds['deaths_m7'] = dbds.deaths.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "dbds['cases_m7'] = dbds.cases.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "dbds['admissions_m7'] = dbds.newAdmissions.transform(lambda x: x.rolling(7, 1).mean())\n",
-    "\n",
-    "dbds['cases_m7n'] = dbds.cases_m7 / dbds.cases_m7.loc['2020-05-15']\n",
-    "dbds['deaths_m7n'] = dbds.deaths_m7 / dbds.deaths_m7.loc['2020-05-15']\n",
-    "dbds['admissions_m7n'] = dbds.admissions_m7 / dbds.admissions_m7.loc['2020-05-15']\n",
-    "\n",
-    "dbds"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3e41e90>"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 720x576 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dbds.loc['2020-03-01':, ['cases_m7n', 'admissions_m7n', 'deaths_m7n']].plot(ylim=(0, 1.5), figsize=(10, 8))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f01c3b7bb90>"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dbds.loc['2020-03-01':'2020-07-02', ['cases_m7', 'admissions_m7', 'deaths_m7']].plot(ylim=(0, 6000))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "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>areaType</th>\n",
-       "      <th>areaName</th>\n",
-       "      <th>newCasesByPublishDate</th>\n",
-       "      <th>cumCasesByPublishDate</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>date</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <td>2020-03-10</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>373</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-11</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>83.0</td>\n",
-       "      <td>456</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-12</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>134.0</td>\n",
-       "      <td>590</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-13</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>207.0</td>\n",
-       "      <td>797</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-03-14</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>264.0</td>\n",
-       "      <td>1061</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-06-29</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>815.0</td>\n",
-       "      <td>311965</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-06-30</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>689.0</td>\n",
-       "      <td>312654</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-01</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>829.0</td>\n",
-       "      <td>313483</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-02</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>576.0</td>\n",
-       "      <td>283757</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <td>2020-07-03</td>\n",
-       "      <td>overview</td>\n",
-       "      <td>United Kingdom</td>\n",
-       "      <td>544.0</td>\n",
-       "      <td>284276</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>116 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "            areaType        areaName  newCasesByPublishDate  \\\n",
-       "date                                                          \n",
-       "2020-03-10  overview  United Kingdom                    NaN   \n",
-       "2020-03-11  overview  United Kingdom                   83.0   \n",
-       "2020-03-12  overview  United Kingdom                  134.0   \n",
-       "2020-03-13  overview  United Kingdom                  207.0   \n",
-       "2020-03-14  overview  United Kingdom                  264.0   \n",
-       "...              ...             ...                    ...   \n",
-       "2020-06-29  overview  United Kingdom                  815.0   \n",
-       "2020-06-30  overview  United Kingdom                  689.0   \n",
-       "2020-07-01  overview  United Kingdom                  829.0   \n",
-       "2020-07-02  overview  United Kingdom                  576.0   \n",
-       "2020-07-03  overview  United Kingdom                  544.0   \n",
-       "\n",
-       "            cumCasesByPublishDate  \n",
-       "date                               \n",
-       "2020-03-10                    373  \n",
-       "2020-03-11                    456  \n",
-       "2020-03-12                    590  \n",
-       "2020-03-13                    797  \n",
-       "2020-03-14                   1061  \n",
-       "...                           ...  \n",
-       "2020-06-29                 311965  \n",
-       "2020-06-30                 312654  \n",
-       "2020-07-01                 313483  \n",
-       "2020-07-02                 283757  \n",
-       "2020-07-03                 284276  \n",
-       "\n",
-       "[116 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbd = pd.read_csv('data_cases_2020-Jul-05.csv', index_col='date', parse_dates=True).sort_index()\n",
-    "dbd"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "date\n",
-       "2020-03-10         NaN\n",
-       "2020-03-11       456.0\n",
-       "2020-03-12       590.0\n",
-       "2020-03-13       797.0\n",
-       "2020-03-14      1061.0\n",
-       "                ...   \n",
-       "2020-06-29    313091.0\n",
-       "2020-06-30    313780.0\n",
-       "2020-07-01    314609.0\n",
-       "2020-07-02    315185.0\n",
-       "2020-07-03    315729.0\n",
-       "Name: newCasesByPublishDate, Length: 116, dtype: float64"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dbd.newCasesByPublishDate.cumsum() + dbd.loc['2020-03-10', 'cumCasesByPublishDate']"
+    "ymax = (int(hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].max().max() * 10) + 1) / 10.0\n",
+    "ax = hospital_data.loc[normalisation_date:, ['cases_m7nd', 'admissions_m7nd', 'deaths_m7nd']].plot(\n",
+    "    ylim=(0, ymax), \n",
+    "    figsize=(10, 8),\n",
+    "    title=\"Cases, hospital admissions, and deaths\\n(7-day moving averages)\")\n",
+    "\n",
+    "lvi = hospital_data.cases_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.cases_m7nd[lvi], s = f'{hospital_data.cases_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = hospital_data.admissions_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.admissions_m7nd[lvi], s = f'{hospital_data.admissions_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "lvi = hospital_data.deaths_m7nd.last_valid_index()\n",
+    "ax.text(x = lvi + pd.Timedelta(days=1), y = hospital_data.deaths_m7nd[lvi], s = f'{hospital_data.deaths_m7nd[lvi]:.2f}')\n",
+    "\n",
+    "\n",
+    "ax.set_xlabel(\"Date\")\n",
+    "ax.set_ylabel(f'Normalised units, scaled from {normalisation_date}')\n",
+    "ax.legend(['Cases', 'Admissions', 'Deaths'])\n",
+    "\n",
+    "plt.savefig('cases_admissions_deaths.png')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "Collapsed": "false"
+   },
    "outputs": [],
    "source": []
   }
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,