{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "28401062",
   "metadata": {},
   "source": [
    "# Analysis of alternative pathway scenarios\n",
    "\n",
    "## Aims: \n",
    "\n",
    "Analyse the performance of the following scenarios:\n",
    "\n",
    "1) Base: Uses the hospitals' recorded pathway statistics in SSNAP (same as validation notebook)\n",
    "\n",
    "2) Speed: Sets 95% of patients having a scan within 4 hours of arrival, and all patients have 15 minutes arrival to scan and 15 minutes scan to needle.\n",
    "\n",
    "3) Onset-known: Sets the proportion of patients with a known onset time of stroke to the national upper quartile if currently less than the national upper quartile (leave any greater than the upper national quartile at their current level).\n",
    "\n",
    "4) Benchmark: The benchmark thrombolysis rate takes the likelihood to give thrombolysis for patients scanned within 4 hours of onset from the majority vote of the 30 hospitals with the highest predicted thrombolysis use in a standard 10k cohort set of patients. These are from Random Forests models.\n",
    "\n",
    "5) Combine *Speed* and *Onset-known*\n",
    "\n",
    "6) Combine *Speed* and *Benchmark*\n",
    "\n",
    "7) Combine *Onset-known* and *Benchmark*\n",
    "\n",
    "8) Combine *Speed*, *Onset-known* and *Benchmark*\n",
    "\n",
    "The analysis will be at a global level (all hospitals together) as well as demonstrating analysis at a hospital level.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c27f9b0",
   "metadata": {},
   "source": [
    "## Load libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dd89ef45",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "\n",
    "from matplotlib.ticker import (MultipleLocator, FormatStrFormatter)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5d7ca82",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0151cbe3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scenario results\n",
    "results = pd.read_csv('./output/scenario_results.csv')\n",
    "# Pathway performance paramters used in scenarios\n",
    "performance_base = pd.read_csv('./output/performance_base.csv')\n",
    "performance_speed = pd.read_csv('./output/performance_speed.csv')\n",
    "performance_onset = pd.read_csv('./output/performance_onset.csv')\n",
    "performance_speed_onset = pd.read_csv('./output/performance_speed_onset.csv')\n",
    "performance_speed_benchmark = \\\n",
    "    pd.read_csv('./output/performance_speed_benchmark.csv')\n",
    "performance_onset_benchmark = \\\n",
    "    pd.read_csv('./output/performance_onset_benchmark.csv')\n",
    "performance_speed_onset_benchmark = \\\n",
    "    pd.read_csv('./output/performance_speed_onset_benchmark.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "08a1bd35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stroke_team</th>\n",
       "      <th>thrombolysis_rate</th>\n",
       "      <th>admissions</th>\n",
       "      <th>80_plus</th>\n",
       "      <th>onset_known</th>\n",
       "      <th>known_arrival_within_4hrs</th>\n",
       "      <th>onset_arrival_mins_mu</th>\n",
       "      <th>onset_arrival_mins_sigma</th>\n",
       "      <th>scan_within_4_hrs</th>\n",
       "      <th>arrival_scan_arrival_mins_mu</th>\n",
       "      <th>arrival_scan_arrival_mins_sigma</th>\n",
       "      <th>onset_scan_4_hrs</th>\n",
       "      <th>eligable</th>\n",
       "      <th>scan_needle_mins_mu</th>\n",
       "      <th>scan_needle_mins_sigma</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AGNOF1041H</td>\n",
       "      <td>0.154839</td>\n",
       "      <td>671.666667</td>\n",
       "      <td>0.425459</td>\n",
       "      <td>0.635236</td>\n",
       "      <td>0.681250</td>\n",
       "      <td>4.576874</td>\n",
       "      <td>0.557598</td>\n",
       "      <td>0.965596</td>\n",
       "      <td>1.665700</td>\n",
       "      <td>1.497966</td>\n",
       "      <td>0.935867</td>\n",
       "      <td>0.388325</td>\n",
       "      <td>3.669602</td>\n",
       "      <td>0.664462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AKCGO9726K</td>\n",
       "      <td>0.158892</td>\n",
       "      <td>1143.333333</td>\n",
       "      <td>0.395658</td>\n",
       "      <td>0.970845</td>\n",
       "      <td>0.428829</td>\n",
       "      <td>4.625486</td>\n",
       "      <td>0.597451</td>\n",
       "      <td>0.955882</td>\n",
       "      <td>2.834183</td>\n",
       "      <td>0.999719</td>\n",
       "      <td>0.908425</td>\n",
       "      <td>0.419355</td>\n",
       "      <td>2.904479</td>\n",
       "      <td>0.874818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AOBTM3098N</td>\n",
       "      <td>0.085885</td>\n",
       "      <td>500.666667</td>\n",
       "      <td>0.485470</td>\n",
       "      <td>0.619174</td>\n",
       "      <td>0.629032</td>\n",
       "      <td>4.603918</td>\n",
       "      <td>0.584882</td>\n",
       "      <td>0.935043</td>\n",
       "      <td>3.471419</td>\n",
       "      <td>1.254744</td>\n",
       "      <td>0.846435</td>\n",
       "      <td>0.267819</td>\n",
       "      <td>3.694918</td>\n",
       "      <td>0.518929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APXEE8191H</td>\n",
       "      <td>0.098634</td>\n",
       "      <td>439.333333</td>\n",
       "      <td>0.515679</td>\n",
       "      <td>0.716237</td>\n",
       "      <td>0.608051</td>\n",
       "      <td>4.590357</td>\n",
       "      <td>0.496452</td>\n",
       "      <td>0.966899</td>\n",
       "      <td>3.312930</td>\n",
       "      <td>0.714465</td>\n",
       "      <td>0.904505</td>\n",
       "      <td>0.258964</td>\n",
       "      <td>3.585094</td>\n",
       "      <td>0.751204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ATDID5461S</td>\n",
       "      <td>0.090689</td>\n",
       "      <td>275.666667</td>\n",
       "      <td>0.533546</td>\n",
       "      <td>0.573156</td>\n",
       "      <td>0.660338</td>\n",
       "      <td>4.427826</td>\n",
       "      <td>0.591373</td>\n",
       "      <td>0.878594</td>\n",
       "      <td>4.125690</td>\n",
       "      <td>0.549301</td>\n",
       "      <td>0.865455</td>\n",
       "      <td>0.315126</td>\n",
       "      <td>3.497262</td>\n",
       "      <td>0.608126</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>YPKYH1768F</td>\n",
       "      <td>0.105193</td>\n",
       "      <td>250.333333</td>\n",
       "      <td>0.321767</td>\n",
       "      <td>0.585885</td>\n",
       "      <td>0.720455</td>\n",
       "      <td>4.436404</td>\n",
       "      <td>0.569248</td>\n",
       "      <td>0.952681</td>\n",
       "      <td>3.779215</td>\n",
       "      <td>0.872809</td>\n",
       "      <td>0.844371</td>\n",
       "      <td>0.305882</td>\n",
       "      <td>3.982100</td>\n",
       "      <td>0.683223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>YQMZV4284N</td>\n",
       "      <td>0.104186</td>\n",
       "      <td>358.333333</td>\n",
       "      <td>0.508511</td>\n",
       "      <td>0.945116</td>\n",
       "      <td>0.462598</td>\n",
       "      <td>4.664536</td>\n",
       "      <td>0.494740</td>\n",
       "      <td>0.948936</td>\n",
       "      <td>3.574735</td>\n",
       "      <td>0.912298</td>\n",
       "      <td>0.798206</td>\n",
       "      <td>0.308989</td>\n",
       "      <td>3.285165</td>\n",
       "      <td>0.463749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>ZBVSO0975W</td>\n",
       "      <td>0.081602</td>\n",
       "      <td>449.333333</td>\n",
       "      <td>0.442130</td>\n",
       "      <td>0.465134</td>\n",
       "      <td>0.688995</td>\n",
       "      <td>4.562051</td>\n",
       "      <td>0.510524</td>\n",
       "      <td>0.972222</td>\n",
       "      <td>2.860226</td>\n",
       "      <td>0.990966</td>\n",
       "      <td>0.930952</td>\n",
       "      <td>0.273657</td>\n",
       "      <td>3.606046</td>\n",
       "      <td>0.575788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>ZHCLE1578P</td>\n",
       "      <td>0.112647</td>\n",
       "      <td>796.000000</td>\n",
       "      <td>0.484694</td>\n",
       "      <td>0.733668</td>\n",
       "      <td>0.671233</td>\n",
       "      <td>4.606557</td>\n",
       "      <td>0.546648</td>\n",
       "      <td>0.949830</td>\n",
       "      <td>3.306916</td>\n",
       "      <td>0.842940</td>\n",
       "      <td>0.892569</td>\n",
       "      <td>0.262788</td>\n",
       "      <td>3.276043</td>\n",
       "      <td>0.795401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>ZRRCV7012C</td>\n",
       "      <td>0.063058</td>\n",
       "      <td>597.333333</td>\n",
       "      <td>0.469504</td>\n",
       "      <td>0.779576</td>\n",
       "      <td>0.504653</td>\n",
       "      <td>4.636283</td>\n",
       "      <td>0.485394</td>\n",
       "      <td>0.977305</td>\n",
       "      <td>3.743456</td>\n",
       "      <td>0.662710</td>\n",
       "      <td>0.851959</td>\n",
       "      <td>0.189097</td>\n",
       "      <td>3.261270</td>\n",
       "      <td>0.803624</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>132 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    stroke_team  thrombolysis_rate   admissions   80_plus  onset_known  \\\n",
       "0    AGNOF1041H           0.154839   671.666667  0.425459     0.635236   \n",
       "1    AKCGO9726K           0.158892  1143.333333  0.395658     0.970845   \n",
       "2    AOBTM3098N           0.085885   500.666667  0.485470     0.619174   \n",
       "3    APXEE8191H           0.098634   439.333333  0.515679     0.716237   \n",
       "4    ATDID5461S           0.090689   275.666667  0.533546     0.573156   \n",
       "..          ...                ...          ...       ...          ...   \n",
       "127  YPKYH1768F           0.105193   250.333333  0.321767     0.585885   \n",
       "128  YQMZV4284N           0.104186   358.333333  0.508511     0.945116   \n",
       "129  ZBVSO0975W           0.081602   449.333333  0.442130     0.465134   \n",
       "130  ZHCLE1578P           0.112647   796.000000  0.484694     0.733668   \n",
       "131  ZRRCV7012C           0.063058   597.333333  0.469504     0.779576   \n",
       "\n",
       "     known_arrival_within_4hrs  onset_arrival_mins_mu  \\\n",
       "0                     0.681250               4.576874   \n",
       "1                     0.428829               4.625486   \n",
       "2                     0.629032               4.603918   \n",
       "3                     0.608051               4.590357   \n",
       "4                     0.660338               4.427826   \n",
       "..                         ...                    ...   \n",
       "127                   0.720455               4.436404   \n",
       "128                   0.462598               4.664536   \n",
       "129                   0.688995               4.562051   \n",
       "130                   0.671233               4.606557   \n",
       "131                   0.504653               4.636283   \n",
       "\n",
       "     onset_arrival_mins_sigma  scan_within_4_hrs  \\\n",
       "0                    0.557598           0.965596   \n",
       "1                    0.597451           0.955882   \n",
       "2                    0.584882           0.935043   \n",
       "3                    0.496452           0.966899   \n",
       "4                    0.591373           0.878594   \n",
       "..                        ...                ...   \n",
       "127                  0.569248           0.952681   \n",
       "128                  0.494740           0.948936   \n",
       "129                  0.510524           0.972222   \n",
       "130                  0.546648           0.949830   \n",
       "131                  0.485394           0.977305   \n",
       "\n",
       "     arrival_scan_arrival_mins_mu  arrival_scan_arrival_mins_sigma  \\\n",
       "0                        1.665700                         1.497966   \n",
       "1                        2.834183                         0.999719   \n",
       "2                        3.471419                         1.254744   \n",
       "3                        3.312930                         0.714465   \n",
       "4                        4.125690                         0.549301   \n",
       "..                            ...                              ...   \n",
       "127                      3.779215                         0.872809   \n",
       "128                      3.574735                         0.912298   \n",
       "129                      2.860226                         0.990966   \n",
       "130                      3.306916                         0.842940   \n",
       "131                      3.743456                         0.662710   \n",
       "\n",
       "     onset_scan_4_hrs  eligable  scan_needle_mins_mu  scan_needle_mins_sigma  \n",
       "0            0.935867  0.388325             3.669602                0.664462  \n",
       "1            0.908425  0.419355             2.904479                0.874818  \n",
       "2            0.846435  0.267819             3.694918                0.518929  \n",
       "3            0.904505  0.258964             3.585094                0.751204  \n",
       "4            0.865455  0.315126             3.497262                0.608126  \n",
       "..                ...       ...                  ...                     ...  \n",
       "127          0.844371  0.305882             3.982100                0.683223  \n",
       "128          0.798206  0.308989             3.285165                0.463749  \n",
       "129          0.930952  0.273657             3.606046                0.575788  \n",
       "130          0.892569  0.262788             3.276043                0.795401  \n",
       "131          0.851959  0.189097             3.261270                0.803624  \n",
       "\n",
       "[132 rows x 15 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performance_base"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fd8db4f",
   "metadata": {},
   "source": [
    "## Collate key results\n",
    "\n",
    "Collate key results together in a DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0b5b21b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add admission numbers to results\n",
    "admissions = performance_base[['stroke_team', 'admissions']]\n",
    "results = results.merge(\n",
    "    admissions, how='left', left_on='stroke_team', right_on='stroke_team')\n",
    "\n",
    "# Calculate numbers thrombolysed\n",
    "results['thrombolysed'] = \\\n",
    "    results['admissions'] * results['Percent_Thrombolysis_(mean)'] / 100\n",
    "\n",
    "# Calculate additional good outcomes\n",
    "results['add_good_outcomes'] = (results['admissions'] * \n",
    "    results['Additional_good_outcomes_per_1000_patients_(mean)'] / 1000)\n",
    "\n",
    "# Get key results\n",
    "key_results = pd.DataFrame()\n",
    "key_results['stroke_team'] = results['stroke_team']\n",
    "key_results['scenario'] = results['scenario']\n",
    "key_results['admissions'] = results['admissions']\n",
    "key_results['thrombolysis_rate'] = results['Percent_Thrombolysis_(mean)']\n",
    "key_results['additional_good_outcomes_per_1000_patients'] = \\\n",
    "    results['Additional_good_outcomes_per_1000_patients_(mean)']\n",
    "key_results['patients_receiving_thrombolysis'] = results['thrombolysed']\n",
    "key_results['add_good_outcomes'] = results['add_good_outcomes']\n",
    "\n",
    "# Remove same_patient_characteristics as not needed here\n",
    "mask = key_results['scenario'] != 'same_patient_characteristics'\n",
    "key_results = key_results[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e2066dd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stroke_team</th>\n",
       "      <th>scenario</th>\n",
       "      <th>admissions</th>\n",
       "      <th>thrombolysis_rate</th>\n",
       "      <th>additional_good_outcomes_per_1000_patients</th>\n",
       "      <th>patients_receiving_thrombolysis</th>\n",
       "      <th>add_good_outcomes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AGNOF1041H</td>\n",
       "      <td>base</td>\n",
       "      <td>671.666667</td>\n",
       "      <td>15.20</td>\n",
       "      <td>12.76</td>\n",
       "      <td>102.093333</td>\n",
       "      <td>8.570467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AKCGO9726K</td>\n",
       "      <td>base</td>\n",
       "      <td>1143.333333</td>\n",
       "      <td>14.91</td>\n",
       "      <td>13.21</td>\n",
       "      <td>170.471000</td>\n",
       "      <td>15.103433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AOBTM3098N</td>\n",
       "      <td>base</td>\n",
       "      <td>500.666667</td>\n",
       "      <td>7.80</td>\n",
       "      <td>5.67</td>\n",
       "      <td>39.052000</td>\n",
       "      <td>2.838780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>APXEE8191H</td>\n",
       "      <td>base</td>\n",
       "      <td>439.333333</td>\n",
       "      <td>10.40</td>\n",
       "      <td>7.59</td>\n",
       "      <td>45.690667</td>\n",
       "      <td>3.334540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ATDID5461S</td>\n",
       "      <td>base</td>\n",
       "      <td>275.666667</td>\n",
       "      <td>9.17</td>\n",
       "      <td>6.28</td>\n",
       "      <td>25.278633</td>\n",
       "      <td>1.731187</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>YPKYH1768F</td>\n",
       "      <td>speed_onset_benchmark</td>\n",
       "      <td>250.333333</td>\n",
       "      <td>22.20</td>\n",
       "      <td>23.54</td>\n",
       "      <td>55.574000</td>\n",
       "      <td>5.892847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1052</th>\n",
       "      <td>YQMZV4284N</td>\n",
       "      <td>speed_onset_benchmark</td>\n",
       "      <td>358.333333</td>\n",
       "      <td>13.51</td>\n",
       "      <td>12.02</td>\n",
       "      <td>48.410833</td>\n",
       "      <td>4.307167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1053</th>\n",
       "      <td>ZBVSO0975W</td>\n",
       "      <td>speed_onset_benchmark</td>\n",
       "      <td>449.333333</td>\n",
       "      <td>21.12</td>\n",
       "      <td>20.10</td>\n",
       "      <td>94.899200</td>\n",
       "      <td>9.031600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1054</th>\n",
       "      <td>ZHCLE1578P</td>\n",
       "      <td>speed_onset_benchmark</td>\n",
       "      <td>796.000000</td>\n",
       "      <td>13.89</td>\n",
       "      <td>12.82</td>\n",
       "      <td>110.564400</td>\n",
       "      <td>10.204720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1055</th>\n",
       "      <td>ZRRCV7012C</td>\n",
       "      <td>speed_onset_benchmark</td>\n",
       "      <td>597.333333</td>\n",
       "      <td>12.25</td>\n",
       "      <td>11.22</td>\n",
       "      <td>73.173333</td>\n",
       "      <td>6.702080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1056 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     stroke_team               scenario   admissions  thrombolysis_rate  \\\n",
       "0     AGNOF1041H                   base   671.666667              15.20   \n",
       "1     AKCGO9726K                   base  1143.333333              14.91   \n",
       "2     AOBTM3098N                   base   500.666667               7.80   \n",
       "3     APXEE8191H                   base   439.333333              10.40   \n",
       "4     ATDID5461S                   base   275.666667               9.17   \n",
       "...          ...                    ...          ...                ...   \n",
       "1051  YPKYH1768F  speed_onset_benchmark   250.333333              22.20   \n",
       "1052  YQMZV4284N  speed_onset_benchmark   358.333333              13.51   \n",
       "1053  ZBVSO0975W  speed_onset_benchmark   449.333333              21.12   \n",
       "1054  ZHCLE1578P  speed_onset_benchmark   796.000000              13.89   \n",
       "1055  ZRRCV7012C  speed_onset_benchmark   597.333333              12.25   \n",
       "\n",
       "      additional_good_outcomes_per_1000_patients  \\\n",
       "0                                          12.76   \n",
       "1                                          13.21   \n",
       "2                                           5.67   \n",
       "3                                           7.59   \n",
       "4                                           6.28   \n",
       "...                                          ...   \n",
       "1051                                       23.54   \n",
       "1052                                       12.02   \n",
       "1053                                       20.10   \n",
       "1054                                       12.82   \n",
       "1055                                       11.22   \n",
       "\n",
       "      patients_receiving_thrombolysis  add_good_outcomes  \n",
       "0                          102.093333           8.570467  \n",
       "1                          170.471000          15.103433  \n",
       "2                           39.052000           2.838780  \n",
       "3                           45.690667           3.334540  \n",
       "4                           25.278633           1.731187  \n",
       "...                               ...                ...  \n",
       "1051                        55.574000           5.892847  \n",
       "1052                        48.410833           4.307167  \n",
       "1053                        94.899200           9.031600  \n",
       "1054                       110.564400          10.204720  \n",
       "1055                        73.173333           6.702080  \n",
       "\n",
       "[1056 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "key_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f81eae2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "key_results.to_csv('./output/key_scenario_results.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83902221",
   "metadata": {},
   "source": [
    "## Overall results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9bbe115a",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['admissions', 'patients_receiving_thrombolysis', 'add_good_outcomes']\n",
    "summary_stats = key_results.groupby('scenario')[columns].sum()\n",
    "summary_stats['percent_thrombolysis'] = (100 *\n",
    "    summary_stats['patients_receiving_thrombolysis'] / summary_stats['admissions'])\n",
    "summary_stats['add_good_outcomes_per_1000'] = (1000 *\n",
    "    summary_stats['add_good_outcomes'] / summary_stats['admissions'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bd292825",
   "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>percent_thrombolysis</th>\n",
       "      <th>add_good_outcomes_per_1000</th>\n",
       "      <th>Percent increase thrombolysis</th>\n",
       "      <th>Percent increase good_outcomes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>scenario</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>base</th>\n",
       "      <td>11.60</td>\n",
       "      <td>9.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>speed</th>\n",
       "      <td>12.34</td>\n",
       "      <td>11.86</td>\n",
       "      <td>6.37</td>\n",
       "      <td>26.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onset</th>\n",
       "      <td>13.67</td>\n",
       "      <td>11.09</td>\n",
       "      <td>17.86</td>\n",
       "      <td>17.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>benchmark</th>\n",
       "      <td>14.51</td>\n",
       "      <td>11.70</td>\n",
       "      <td>25.05</td>\n",
       "      <td>24.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>speed_onset</th>\n",
       "      <td>14.52</td>\n",
       "      <td>13.98</td>\n",
       "      <td>25.16</td>\n",
       "      <td>48.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>speed_benchmark</th>\n",
       "      <td>15.43</td>\n",
       "      <td>14.82</td>\n",
       "      <td>33.01</td>\n",
       "      <td>57.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onset_benchmark</th>\n",
       "      <td>17.20</td>\n",
       "      <td>13.87</td>\n",
       "      <td>48.32</td>\n",
       "      <td>47.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>speed_onset_benchmark</th>\n",
       "      <td>18.27</td>\n",
       "      <td>17.57</td>\n",
       "      <td>57.54</td>\n",
       "      <td>86.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       percent_thrombolysis  add_good_outcomes_per_1000  \\\n",
       "scenario                                                                  \n",
       "base                                  11.60                        9.40   \n",
       "speed                                 12.34                       11.86   \n",
       "onset                                 13.67                       11.09   \n",
       "benchmark                             14.51                       11.70   \n",
       "speed_onset                           14.52                       13.98   \n",
       "speed_benchmark                       15.43                       14.82   \n",
       "onset_benchmark                       17.20                       13.87   \n",
       "speed_onset_benchmark                 18.27                       17.57   \n",
       "\n",
       "                       Percent increase thrombolysis  \\\n",
       "scenario                                               \n",
       "base                                            0.00   \n",
       "speed                                           6.37   \n",
       "onset                                          17.86   \n",
       "benchmark                                      25.05   \n",
       "speed_onset                                    25.16   \n",
       "speed_benchmark                                33.01   \n",
       "onset_benchmark                                48.32   \n",
       "speed_onset_benchmark                          57.54   \n",
       "\n",
       "                       Percent increase good_outcomes  \n",
       "scenario                                               \n",
       "base                                             0.00  \n",
       "speed                                           26.13  \n",
       "onset                                           17.87  \n",
       "benchmark                                       24.36  \n",
       "speed_onset                                     48.63  \n",
       "speed_benchmark                                 57.59  \n",
       "onset_benchmark                                 47.53  \n",
       "speed_onset_benchmark                           86.82  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Re-order\n",
    "order = {'base': 1, 'speed': 2, 'onset': 3, 'benchmark': 4, 'speed_onset': 5,\n",
    "    'speed_benchmark': 6, 'onset_benchmark':7, 'speed_onset_benchmark': 8,\n",
    "    'same_patient_characteristics': 9}\n",
    "df_order = [order[x] for x in list(summary_stats.index)]\n",
    "summary_stats['order'] = df_order\n",
    "summary_stats.sort_values('order', inplace=True)\n",
    "\n",
    "# Select cols of interest\n",
    "summary_stats = summary_stats[['percent_thrombolysis', 'add_good_outcomes_per_1000']]\n",
    "\n",
    "base_thrombolysis = summary_stats.loc['base']['percent_thrombolysis']\n",
    "summary_stats['Percent increase thrombolysis'] = (100 * (\n",
    "        summary_stats['percent_thrombolysis'] / base_thrombolysis -1))\n",
    "\n",
    "base_add_good_outcomes = summary_stats.loc['base']['add_good_outcomes_per_1000']\n",
    "summary_stats['Percent increase good_outcomes'] = (100 * (\n",
    "    summary_stats['add_good_outcomes_per_1000'] / base_add_good_outcomes -1))\n",
    "\n",
    "summary_stats = summary_stats.round(2)\n",
    "\n",
    "summary_stats.to_csv('./output/summary_net_results.csv')\n",
    "\n",
    "summary_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1a89cafd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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58mSULl0aHTt2hL29PbZu3Qrg9Zmitm3bwsPDA2XLlsXUqVPx559/IikpKc+xZs6cidq1a8PY2Bj169fHX3/9JT2XlZWFMWPGwMzMDNbW1rnqlqenJ8aNGwd3d3eULVsWbdu2xbNnz+Dn5wcTExM0bNgQ0dHR0v6CIODOnTsAgN27d6N+/fowNjZGtWrVMGfOHABAXFwc2rRpA1NTU1SoUAGffvopsrOzpZ9zTo0v6HMo55K4uXPnonLlyjA3N8fy5culHPmNTcWHjS0BAEJDQ9GtWzckJCTAx8cHQ4YMUXl+/fr12LVrFxISEhAZGQlfX1/88ssvePr0KVq3bo22bdsiPT1d2n/r1q04cOAAbt26hR07duCLL77Ajz/+iLi4OGRnZyM4OFjl/Y8cOYLbt29j//79mDlzplRQpk+fjrNnzyI8PBwRERE4f/48pk2blit/jx49sHfvXiQkJAB4fSRj48aN6NmzJ1JSUjBs2DDs2bMHSUlJOH36NBwdHXO9x/79+3H8+HHcunULCQkJ2LhxIypWrPjeP8uVK1fixYsXePDgAZ49e4ZFixahdOnSAF5/4Ojp6eHOnTu4fPky9u/fjz/++CPP97l69Srq1q0rPba1tcWJEyfw8uVLHDp0SPoF5ObNm+jevXue72FjY4OIiIj3/h6IqHitXbsW+/btw927d3Hr1i2prl26dAm9e/fG4sWL8ezZMwQGBsLHx0flF/o367Ge3n+btfP69etwcHCQHjs4OOD69evSczkHBPJ7/s3X1q5dGwYGBrh161aeY9WuXRsnTpzAixcvMHHiRPTo0UNaaWvJkiXYuXMnLl++jLCwMGzZsiXX6zds2IDVq1cjNjYWd+/eRZMmTRAQEID4+HjY2NjkuxRwnz59sHjxYiQlJeHatWvSCm9z585F9erV8fTpUzx58gQ//vgjBEHI9frCPoceP36MFy9eIDY2FkuXLsXgwYOlgzf5jU3Fh40tAQCaNm2K1q1bQ1dXFz179szVDA0bNgyWlpYoXbo0Nm7ciC+//BItWrSAvr4+xowZg5cvX+L06dPS/kOHDkWVKlVQrVo1fPrpp3Bzc4OTkxMMDQ3RoUMHXL58WeX9J06cCCMjI9jb2yMgIADr168H8Lr4T5gwAZUrV0alSpUwceJErF69Old+c3NzeHh4YPPmzQCAvXv3wszMDC4uLgAAHR0dXLt2DS9fvoS5uTlsbW1zvYe+vj6SkpLwzz//QBRF2NjYwNzc/L1/lvr6+nj27Bnu3LkDXV1duLi4wMTEBE+ePMGePXvwyy+/wMjICJUrV8bIkSOxYcOGPN8nISFB5QPFzs4OHTt2ROPGjXH//n189913GD58OIKDgxEcHAwPDw/4+flJzT0AGBsb57u2PBGpz5AhQ2BpaYkKFSpg7NixUs1bsmQJAgMD4ebmBl1dXfj7+8PQ0BBnz56VXvtmPf6vkpOTVc72lCtXDsnJyRBFMddzOc/nHJEt7Pm3de7cGRYWFtDR0UHXrl3x0Ucf4fz58wCATZs2YcSIEdLP5Pvvv8/1+oCAANSuXRvlypXDF198gdq1a6N58+bQ09ND586dc32u5NDX18eNGzeQmJiI8uXLw9nZWdr+6NEj3Lt3D/r6+vj000/zbGwL+xzS19fHhAkToK+vj9atW6Ns2bK4efNmgWNT8WFjSwCAqlWrSl+XKVMGaWlpKqe4LC0tpa8fPnyImjVrSo91dHRgaWmpcjNTlSpVpK9Lly6d63FycrLK+G++f82aNaV10N8e683n3ubv7481a9YAANasWYOePXsCAIyMjLBx40YsWrQI5ubm+PLLL/HPP//kev1nn32GIUOGYPDgwahSpQr69++PxMTEPMcqSM+ePeHt7Y1u3brBwsIC3377LTIyMnDv3j1kZGTA3NwcpqamMDU1RWBgYL43d5UvXz7XB8TIkSMRERGBjRs3YuPGjdKps5CQEBw6dAg2NjaYOXOmtH9SUlKelygQkXrlV/Pu3buHuXPnSjXC1NQUDx48UKl7b772vypbtqxKnUtMTETZsmUhCEKu53Kez/mFu7Dn37Zq1SrpEgtTU1Ncu3YNcXFxAF7X+rd/Jm9738+VHFu3bsXu3btRs2ZNNGvWDGfOnAEAfPPNN6hTpw5atmwJa2trldr5psI+hypWrKhy5LxMmTJSlvzGpuLDxpbeyZu/xVpYWODevXvSY1EU8eDBA1SrVq3I7//gwQPp6/v378PCwiLPsd587m3t27fHlStXcO3aNezcuVPlxjhvb28cOHAAjx49Qr169dCvX78832PYsGG4ePEirl+/jlu3bmH27Nl57mdkZITU1FTp8ePHj6Wv9fX1MXHiRNy4cQOnT5/Gzp07sWrVKlhaWsLQ0BBxcXFISEhAQkICEhMTpdN6b2vQoEG+p/SePHmCxYsXY8KECbh27RoaNGgAfX19NGzYUOV6vL///lvlVCERKUN+Nc/S0hJjx46VakRCQgJSU1Ph6+sr7Z/XUcWisrW1VTlDFxERIZ3RsrW1RWRkpMov2G8//+ZrIyMj8erVK3z88ce5xrl37x769euHX3/9Fc+ePUNCQgLs7OykGRjMzc1z/Uw+lIYNG2L79u34999/0b59e3Tp0gXA6zNac+fORWRkJHbs2IF58+bh0KFDuV7/Pp9D7zo2FR82tvTeunTpgl27duHQoUPIyMjA3LlzYWhoCHd39yK/59SpU5Gamorr169j+fLl6Nq1K4DXd+ROmzYNT58+RVxcHKZMmZLvnLulSpVCp06d0L17dzRq1Ag1atQA8LoJDA0NRUpKCgwNDVG2bFno6urmev2FCxdw7tw5ZGRkwMjICKVKlcpzPwBwdHTEhg0bkJGRket6sCNHjuDq1avIysqCiYkJ9PX1oaurC3Nzc7Rs2RKjR49GYmIisrOzcffuXRw7dizPMVq0aIFLly6p3FSSY9SoUZg8eTLKlCmDWrVq4cKFC0hOTsbRo0dVprg5duwYvvjii3x+6kSkLr/99htiYmIQHx+PH3/8Uap5/fr1w6JFi3Du3DmIooiUlBTs2rUr39P7ecnIyEBaWhqys7ORmZmJtLQ06SbVnPlhc260+vrrrzFv3jzExsbi4cOHmDt3Lnr16gUA+Pjjj+Ho6IjJkycjLS0Nf/31F65cuSLdqOvn54cdO3bgxIkTSElJwYQJE/DVV1/lecQ2JSUFgiCgUqVKAIDly5er3JzbpUsXBAcHIyYmBs+fP8/36On7Sk9Px9q1a/HixQvo6+vDxMREqus7d+7EnTt3IIqitD2vmv8+n0PvOjYVHza29N7q1q2LNWvWYOjQoTAzM8OOHTuwY8cOGBgYFPk9mzVrhjp16uDzzz/HmDFjpEUTxo0bB1dXVzRo0AD29vZwdnbGuHHj8n0ff39/XL16VboMAQCys7Mxd+5cWFhYoEKFCjh27Bh+//33XK9NTExEv379UL58edSsWRMVK1ZUmUP2TVOnTsXdu3dRvnx5TJw4UeXmrcePH6NTp04wMTGBjY0NmjVrJhXBVatWIT09XbobulOnTtLNE2+rUqUKPvvsM2zfvl1l+5EjR5CQkIAOHToAABo1aoQvv/wSlpaWOHLkiLQoQ1paGnbv3g1/f/98f15EpB7du3eXToFbW1tLdc3V1RVLlizBkCFDUL58edSpU0eapeBd9evXD6VLl8b69esxffp0lC5dWrom9MGDB6hZs6Z0hi0wMBBt27aFvb097Ozs8OWXXyIwMFB6rw0bNiAsLAzly5dHUFAQtmzZIjWntra2WLRoEfz8/FC5cmUkJSXlWVsBoH79+hg9ejSaNGmCKlWq4OrVq/jkk09UMnt7e8PBwQHOzs746quv3ut7Lsjq1athZWUFExMTLFq0SLpk7fbt22jevDnKli2LJk2aYNCgQXnOXfu+n0PvMjYVH0F8cyZmohLu/v37qFevHh4/fgwTExN1x/nPbty4AX9/f5w/f/69Tz8uWLAADx48wE8//VRM6YioKKysrPDHH3+gefPmso89bdo0VKpUSaV5JdIkbGxJY2RnZ2PUqFFITEzEsmXL1B2HiChP6mxsiTRdsV2K8ODBA3h5ecHGxga2traYP38+ACA+Ph4tWrTARx99hBYtWuSaqJ+oKFJSUmBiYoIDBw7kO5chkbZiPSYibVFsR2wfPXqER48ewdnZGUlJSXBxccG2bduwYsUKVKhQAUFBQZg5cyaeP3+OWbNmFUcEIiIC6zERaY9iO2Jrbm4uTURsbGwMGxsbxMbGYvv27dLNLP7+/ti2bVtxRSAiIrAeE5H2kOUa2+joaHh4eODatWuoUaOGyspI5cuX5+kvIiKZsB4TkSb7b4tMv4Pk5GR07NgRv/zyy3vdpR4SEoKQkBAAr+8M/5ArrRARva9nz55JqySVVKzHRKQJCqrHxXrENiMjA23atIG3tzdGjRoF4PUcqEePHoW5uTkePXoET09PaU3l/Li6uiIsLKy4YhIRFaqk1yHWYyLSFAXVoWK7xlYURfTp0wc2NjZSEQUAHx8frFy5EgCwcuVKtGvXrrgiEBERWI+JSHsU26UIp06dwurVq2Fvbw9HR0cAwI8//oigoCB06dIFS5cuRY0aNbB58+biikBERGA9JiLtUWyNbdOmTZHfVQ6HDh0qrmGJiOgtrMdEpC2K7VIEIiIiIiI5sbElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCHrF9ca9e/fGzp07UblyZVy7dg0AEB4ejgEDBiAtLQ16enr4/fff0ahRo+KKQEQliFXQLtnGip75pWxjKQHrMRFpi2I7YturVy/s3btXZdu3336LiRMnIjw8HFOmTMG3335bXMMTEdH/sB4TkbYotsbWw8MDFSpUUNkmCAISExMBAC9evICFhUVxDU9ERP/DekxE2qLYLkXIyy+//AJvb2+MGTMG2dnZOH36tJzDExHR/7AeE5EmkrWxXbhwIX7++Wd07NgRmzZtQp8+fXDw4ME89w0JCUFISAgAICYmBkePHpUxKRHJbbR9pmxjsZ6wHhORZhJEURSL682jo6PRpk0b6WaFcuXKISEhAYIgQBRFlCtXTjoVVhBXV1eEhYUVV0wiUgCl3zxW0usQ6zERaYqC6pCs031ZWFjg2LFjAIDDhw/jo48+knN4IiL6H9ZjItJExXYpgq+vL44ePYq4uDhUr14dkydPxpIlSzB8+HBkZmaiVKlS0qktIiIqPqzHRKQtiq2xXb9+fZ7bL168WFxDEhFRHliPiUhbcOUxIiIiItIIss6KQEREREQKJwjyjfWB5zDgEVsiIiIi0ghsbImIiIhII7CxJSIiIiKNwMaWiIiIiDQCbx4j0nJKX/GLiIjoXfGILRERERFpBDa2RERERKQR2NgSERERkUZgY0tEREREGoGNLRERERFpBDa2RERERKQR2NgSERERkUZgY0tEREREGoGNLRERERFpBDa2RERERKQR2NgSERERkUZgY0tEREREGoGNLRERERFphGJrbHv37o3KlSvDzs5OZfuCBQtQt25d2Nra4ttvvy2u4YmI6H9Yj4lIWxRbY9urVy/s3btXZduRI0ewfft2XLlyBdevX8eYMWOKa3giIvof1mMi0hbF1th6eHigQoUKKtsWLlyIoKAgGBoaAgAqV65cXMMTEdH/sB4TkbbQk3OwW7du4cSJExg7dixKlSqFOXPmoGHDhnnuGxISgpCQEABATEwMjh49KmNSIu0x2j5TtrEK+v9YKTm0BesxEeVrzhz5xvrA9UTWxjYzMxPPnz/H2bNnceHCBXTp0gWRkZEQBCHXvv3790f//v0BAK6urvD09JQzKpHW6BW0S7axov08FZ9DW7AeE1G+vLzkG0sUP+jbyTorQvXq1fHVV19BEAQ0atQIOjo6iIuLkzMCERGB9ZiINJOsjW379u1x+PBhAK9Pg6Wnp8PMzEzOCEREBNZjItJMxXYpgq+vL44ePYq4uDhUr14dkydPRu/evdG7d2/Y2dnBwMAAK1euzPO0FxERfTisx0SkLYqtsV2/fn2e29esWVNcQxIRUR5Yj4lIW3DlMSIiIiLSCGxsiYiIiEgjsLElIiIiIo0g6zy2RPT/rOSct3Xml7KNRUREpC48YktEREREGoGNLRERERFpBDa2RERERKQR2NgSERERkUZgY0tEREREGoGNLRERERFpBDa2RERERKQROI8tERERaTdBkG8sUZRvLC3EI7ZEREREpBHY2BIRERGRRmBjS0REREQagY0tEREREWkE3jxGsrIK2iXbWNEzv1R8DiIiIvpweMSWiEhNNm/ejKSkJADAtGnT8NVXX+HSpUtqTkVEVHKxsSUiUpOpU6fC2NgYJ0+exL59++Dv74+BAweqOxYRUYnFxpaISE10dXUBALt27cLAgQPRrl07pKenqzkVEVHJVWyNbe/evVG5cmXY2dnlem7OnDkQBAFxcXHFNTwRkeJVq1YNgYGB2LRpE1q3bo1Xr14hOzv7g4/DekxE2qLYGttevXph7969ubY/ePAABw4cQI0aNYpraCKiEmHTpk3w9vbG3r17YWpqivj4eMyePfuDj8N6TETaotgaWw8PD1SoUCHX9pEjR+Knn36CIOfydUREClSmTBlUrlwZJ0+eBADo6enho48++uDjsB4TkbaQdbqv0NBQVKtWDQ4ODoXuGxISgpCQEABATEwMjh49WszpSA6j7TNlG6ugfzNKyKGEDMyhXpMnT0ZYWBhu3ryJgIAAZGRkoEePHjh16lSxj816TIpw8aJ8Y7m45P/cnDny5SgJ//+U4J+HbI1tamoqpk+fjv3797/T/v3790f//v0BAK6urvD09CzGdCSXXnLOH+vnqegcSsjAHOr1119/4fLly3B2dgYAWFhYSNN/FSfWY1IMLy/5xhJF5edQihL885BtVoS7d+8iKioKDg4OsLKyQkxMDJydnfH48WO5IhARKYqBgQEEQZAuBUhJSZFlXNZjIoUSBPn+aCjZjtja29vj33//lR5bWVkhLCwMZmZmckUgIlKULl26IDAwEAkJCViyZAmWLVuGfv36Ffu4rMdEpKmK7Yitr68vmjRpgps3b6J69epYunRpcQ1FRFQijRkzBp06dULHjh1x8+ZNTJkyBUOHDv3g47AeE5G2KLYjtuvXry/w+ejo6OIamvJgJef1izO/lG0sopKuRYsWcHNzQ2bm65vn4uPj85zB4L9gPSYibVFoYxsWFoYTJ07g4cOHKF26NOzs7NC8efMPXniJiLTN4sWLMWHCBJQuXRo6OjoQRRGCICAyMjLP/efPn4+AgAAYGxujb9++uHz5MmbOnImWLVvKnJyISJnyvRRhxYoVcHZ2xowZM/Dy5UvUrVtXmm+xRYsW8Pf3x/379+XMSkSkUebMmYPr168jOjoakZGRiIqKyrepBYBly5bBxMQE+/fvx9OnT7F8+XIEBQXJmJiISNnyPWKbkpKCU6dOoXTp0nk+Hx4ejtu3b3PFGiKiIqpduzbKlCnzzvuL/5sWZ/fu3QgICICDg4O0jYiICmhsBw8eXOALHR0dP3QWIiKtMmPGDLi7u8PNzQ2GhobS9uDg4Dz3d3FxQcuWLREVFYUZM2YgKSkJOjqyzdpIRKR473zz2I4dOzBt2jS8evUK/fv3x6BBg4ozFxGRxgsMDMRnn30Ge3v7d2pQly5divDwcFhbW6NMmTJ49uwZli9fLkNSIqKSId/GNiIiQmWpxdWrV+Ps2bMQRREODg5sbImI/iM9PT3MmzfvnffX0dFBlSpVcOPGDWkWBSIi+n/5Nra///47RFHElClTULVqVVhaWmLs2LHQ0dGBhYWFnBmJiDSSl5cXQkJC0LZtW5VLEfKbdea7777Dxo0bUb9+fejq6gIABEGAh4eHLHmJiJQu38Z28eLFiIiIQGBgIFxdXTF16lScPn0aqampGD9+vJwZiYg00rp16wC8vtY2R0HTfW3btg03b95UaYKJiOj/FXiNrYODA7Zv344dO3bAx8cH/v7+6Nmzp1zZiIg0WlRU1Hvtb21tjYyMDDa2RET5yPduhUWLFsHJyQnOzs5ISUnB3r178fz5c3h7e+PEiRNyZiQi0kgZGRkIDg5Gp06d0KlTJ/z666/IyMjId/8yZcrA0dERgYGBGDZsmPSHiIheK/Aa2ytXriA9PR1NmjRBt27dMGzYMPTs2RNTp07Fp59+KmdOIiKNM3DgQGRkZEg3465evRoDBw7EH3/8kef+Pj4+8PHxkTMiEVGJkm9jW61aNYwfPx4vX75EvXr1pO3ly5d/r7t4iYgobxcuXEBERIT0+LPPPlOZjeZt/v7+SE9Px61btwAAdevWhb6+frHnJCIqKfJtbLdv3459+/ZBX18fLVq0kDMTEZFW0NXVxd27d1G7dm0AQGRkpDTbQV6OHj0Kf39/WFlZQRRFPHjwACtXruSsCERE/5NvY/vw4UO0bds23xeKoojY2FhUr169WIIREWm62bNnw8vLC9bW1hBFEffu3StwwYXRo0dj//79qFu3LgDg1q1b8PX1xcWLF+WKTESkaPk2tt988w2ys7PRrl07uLi4oFKlSkhLS8OdO3dw5MgRHDp0CJMnT2ZjS0RURJ9//jlu376NmzdvQhRF1KtXr8AZDzIyMqSmFgA+/vjjAm82IyLSNvk2tps3b8aNGzewdu1aLFu2DI8ePUKZMmVgY2OD1q1bY+zYsShVqpScWYmINMpvv/0GPz8/NGjQAADw/PlzLF26NN+VHV1dXdGnTx9p2sW1a9fCxcVFtrxEREpX4Dy29evXx/Tp0+XKQkSkVZYsWYLBgwdLj8uXL48lS5bk29guXLgQv/32G4KDgyGKIjw8PLi8ORHRGwpsbImIqPhkZ2dDFEUIggAAyMrKQnp6er77GxoaYtSoURg1apRcEYmIShQ2tsXMKmiXbGNFz/xStrGI6L9r2bIlunTpggEDBkAQBCxatAitWrXKtV+XLl2wadMm2NvbS03wm65cuSJHXCIixSu2xrZ3797YuXMnKleujGvXrgF4fUPajh07YGBggNq1a2P58uUwNTUtrghERIr2008/ISQkBAsXLoQoimjZsiX69euXa7/58+cDAHbu3FmkcViPiUhb5Lukbg5RFLFmzRpMmTIFAHD//n2cP3++0Dfu1asX9u7dq7KtRYsWuHbtGq5cuYKPP/4YM2bMKGJsIqKSb8GCBRgwYAC2bNmCrVu3IjAwEAsWLMi1n7m5OQDAzMwMlpaWqFmzJl69eoWIiAhYWFgUOg7rMRFpi0Ib20GDBuHMmTNYv349AMDY2FjlZof8eHh4oEKFCirbWrZsCT291weJGzdujJiYmKJkJiLSCCtXrsy1bcWKFfnu7+HhgbS0NMTGxuLzzz/H8uXL0atXr0LHYT0mIm1R6KUI586dw6VLl+Dk5ATg9V27Bd3c8K6WLVuGrl27/uf3ISIqadavX49169YhKioKPj4+0vakpCRUrFgx39eJoogyZcpg6dKlGDp0KL799lupNv8XrMdEpCkKbWz19fWRlZUl3bDw9OlT6OgUeqC3QNOnT4eenh78/Pzy3SckJAQhISEAgJiYGBw9evQ/jakuo+0zZRuroJ8RcygvhxIyMId6uLu7w9zcHHFxcRg9erS03djYWJrTNi+iKOLMmTNYu3Ytli5dCgDIzPxvPzdtqsekQHPmyDdWQf9umUOVUnIUQaGN7bBhw9ChQwf8+++/GDt2LLZs2YJp06YVecCVK1di586dOHToUJ539+bo378/+vfvD+D1pOSenp5FHlOdesk5K4KfJ3OUoBxKyMAc6lGzZk3UrFkTZ86cea/X/fLLL5gxYwY6dOgAW1tbREZGwsvLq8g5tK0ekwL9h3+/700UmaOk5SiCQhtbPz8/uLi44NChQxBFEdu2bYONjU2RBtu7dy9mzZqFY8eOoUyZMkV6DyIiTWFsbCw1lOnp6cjIyICRkRESExPz3L9Zs2Zo1qwZgNdz4JqZmSE4OLhIY2tlPS6gef/gPvCHNRG9m0KvKbh79y5q1aqFwYMHw87ODgcOHEBCQkKhb+zr64smTZrg5s2bqF69OpYuXYohQ4YgKSkJLVq0gKOjIwYMGPAhvgciohIpKSkJiYmJSExMRFpaGrZu3YohQ4bku3/37t2RmJiIlJQU1K9fH3Xr1sXs2bMLHYf1mIi0RaFHbDt27IiwsDDcuXMHffv2Rdu2bdG9e3fs3r27wNflzKLwpj59+hQ9KRGRhmvfvj1mzpyZ7/M3btyAiYkJ1q5di9atW2PWrFlwcXHBN998U+D7sh5TnngEmzRQoY2tjo4O9PT08Oeff2L48OEYOnToB7kLl4hI2/3555/S19nZ2QgLCyvwWteMjAxkZGRg27ZtGDJkCPT19Qvcn4hI27zTrAjr16/HqlWrsGPHDgCvi6vScSlbIlK6nJoKAHp6erCyssL27dvz3T8wMBBWVlZwcHCAh4cH7t27BxMTEzmiEhGVCIU2tsuXL8eiRYswduxY1KpVC1FRUejRo4cc2YiINNry5cvfa/9hw4Zh2LBh0uOaNWviyJEjHzoWEVGJVWhjW79+fZW7bmvVqoWgoKBiDUVEpA1iYmIwdOhQnDp1CoIgoGnTppg/fz6qV6+ust+aNWvQo0cPzJs3L8/3GTVqlBxxiYgUr9DGtlatWnlewxUZGVksgYiItEVAQAC6d++OzZs3A3jdwAYEBODAgQMq+6WkpAB4PYsCERHlr9DGNiwsTPo6LS0NmzdvRnx8fLGGIiLSBk+fPkVAQID0uFevXvjll19y7RcYGAgAmDhxolzRiIhKpEIb27fXLR8xYgSaNm2KKVOmFFsoIiJtYGZmhjVr1sDX1xfA62m53q65b4qKisKCBQsQHR2tspRuaGhosWclIioJCm1sL126JH2dMx0NT4cREf13y5Ytw5AhQzBy5EgIggB3d3csW7Ys3/3bt2+PPn36oG3bttDRKXR9HSIirVNoYzt69Oj/31lPD7Vq1cKmTZuKNRQRkTaoUaPGex1tLVWqlMqsCFRCcWEEomJTaGPLqWSIiJRh+PDhmDx5Mlq2bAlDQ0Npu7OzsxpTEREpR6GNLRERKcPVq1exevVqHD58WLoUQRAEHD58WM3JiIiUgY0tEVEJ8ddffyEyMhIGBgbqjkJEpEhsbImIZJbfQgs58ltwwcHBAQkJCahcuXJxxCIiKvEKbWw3b96MVq1awdjYGNOmTcOlS5cwbtw4XtNFRFREOTPL3Lx5ExcuXICPjw8AYMeOHfDw8Mj3dU+ePEG9evXQsGFDlWtsOd0XEdFrhTa2U6dORefOnXHy5Ens27cPY8aMwcCBA3Hu3Dk58hERaZychRZatmyJS5cuwdjYGAAwadIkdO7cOd/XTZ48WZZ8REQlVaGNra6uLgBg165dGDhwINq1a4dJkyYVdy4iIo13//59letlDQwMEB0dne/+zZo1kyEVEVHJVWhjW61aNQQGBuLgwYP47rvv8OrVK2RnZ8uRjYhIo/Xs2RONGjVChw4dAADbtm2Dv79/rv2MjY0hFDD3aWJiYrFlJCIqSQptbDdt2oS9e/dizJgxMDU1xaNHjzB79mw5shERabSxY8fiiy++wIkTJyAIApYvXw4nJ6dc++VckzthwgRUrVoVPXv2hCiKWLt2LVeCJCJ6Q75rMuYcAUhLS4OnpycqVqyI+Ph4GBoawtXVVbaARESaTFdXFzo6OtKfguzbtw+DBg2CsbExTExMMHDgQGzdulWmpEREypdvFe3evTsAwMXFBa6urnBxcZH+sLElIvrv5s+fDz8/P8TFxeHff/9Fjx49sGDBgnz319XVxdq1a5GVlYXs7GysXbtWug+CiIgKaGx37twJAIiKikJkZCSioqKkP5GRkYW+ce/evVG5cmXY2dlJ2+Lj49GiRQt89NFHaNGiBZ4/f/4BvgUiopJp6dKlOHfuHCZPnowpU6bg7NmzWLJkSb77r1u3Dps2bUKVKlVQpUoVbN68GevWrSt0HNZjItIWBZ/3AnDq1CmkpKQAANasWYNRo0bh/v37hb5xr169sHfvXpVtM2fOxOeff47bt2/j888/x8yZM4sYm4io5BNFUeWIq66uLkRRzHd/KysrbN++HXFxcXj69Cm2bdsGKyurQsdhPSYibVHozWMDBw5EREQEIiIi8NNPP6FPnz7o2bMnjh07VuDrPDw8ck1bs337dhw9ehQA4O/vD09PT8yaNavI4YmISrKAgAC4ubmhQ4cOEEUR27dvR58+ffLdPy0tDUuXLsX169eRlpYmbV+2bFmB47AeE5G2KPSIrZ6eHgRBwPbt2zF8+HAMHz68yHfhPnnyBObm5gAAc3Nz/Pvvv0V6HyIiTTBq1CgsX74cFSpUQMWKFbF8+XKMGDEi3/179uyJx48fY9++fWjWrBliYmKkxR3eF+sxEWmiQo/YGhsbY8aMGVizZg2OHz+OrKwsZGRkFHuwkJAQhISEAABiYmKkIwvvarR9ZjGkyltB2ZiDOfLLoYQMzKF+urq6EAQBgiAUOivCnTt3sHnzZmzfvh3+/v7o3r07vL29iz3jf63HijFnjnxjFfQzYg5lZQCY421KyVEEhTa2GzduxLp167B06VJUrVoV9+/fxzfffFOkwapUqYJHjx7B3Nwcjx49QuXKlfPdt3///ujfvz8AwNXVFZ6enu81Vq+gXUXKWBTRfp7MwRzvnUMJGZhDvebPn48lS5agY8eOEEURPXr0QP/+/TF06NA899fX1wcAmJqa4tq1a6hatWqBK5UVRM56rBheXvKNVcC10syhsAzModwcRVDopQhbtmxBQEAAPv30UwBAjRo18PXXXxdpMB8fH6xcuRIAsHLlSrRr165I70NEpAned1aE/v374/nz55g2bRp8fHxQv359fPfdd0Uam/WYiDRRoUdsHz9+jIYNG8LZ2Rm9e/eGt7d3gUs75vD19cXRo0cRFxeH6tWrY/LkyQgKCkKXLl2wdOlS1KhRA5s3b/4g3wQRUUn0vrMi9O3bF8Drm8HeZdrFHKzHRKQtCm1sp02bhqlTp2L//v1Yvnw5hgwZgi5duqBPnz6oXbt2vq9bv359ntsPHTpU9LRERBrkzVkRAGDbtm0FzopQVKzHRKQtCm1sAUAQBFStWhVVq1aFnp4enj9/jk6dOqFFixb46aefijsjEZFGGjVqFDw9PXHy5EmIoojly5fDyclJ3bGIiEqsQhvb4OBgrFy5EmZmZujbty9mz54NfX19ZGdn46OPPmJjS0RURPHx8bCyslJZZCEjI0O6SYyIiN5PoY1tXFwc/vzzT9SsWVNlu46OjrTsLhERvT9nZ2c8ePAA5cuXhyiKSEhIgLm5OSpXrowlS5bAxcVF2vfFixfYu3cvYmNjIQgCLCws4O3tDVNTU/V9A0RECpPvrAjx8fGIj4/HiBEjYGxsLD3O+QMANjY2sgUlItI0rVq1wu7duxEXF4dnz55hz5496NKlC37//XcMGjRI2m/VqlVwdnbG0aNHkZqaipSUFBw5cgQuLi5YtWqVGr+DdyQI8v0hIq2W7xFbFxcXafaDt+/SFQThve7IJSKi3MLCwrBo0SLpccuWLfHDDz9g3rx5ePXqlbR9+vTpuHjxYq6js8+fP4ebm1uRp2AkItI0+Ta2UVFRcuYgItI6FSpUwKxZs9CtWzcArxfEKV++PLKyslRWIRNFMc9pFnV0dAqcHoyISNu806wIoaGhOH78OADA09MTbdq0KdZQRETaYN26dZg8eTLat28PAGjatCnWrVuHrKwsbNq0Sdpv7NixcHZ2RsuWLWFpaQkAuH//Pg4cOIDx48erIzoRkSIV2tgGBQXhwoUL8PPzA/B6CchTp05hxowZxR6OiEiTmZmZYcGCBXk+V6dOHelrf39/+Pj4YN++fYiNjYUoivD09MSMGTNQvnx5ueISESleoY3t7t27ER4eLp0W8/f3h5OTExtbIiIZlS9fHt26dUN8fDwEQWBDS0SUh3xnRXhTQkKC9PWLFy+KKwsREeXh/v376NatGypXrgw3Nzc0bNgQlStXRrdu3RAdHa3ueEREilHoEdvvv/8eTk5O8PLygiiKOH78OI/WEhHJqGvXrhgxYgTWrl0LXV1dAEBWVhY2b96Mbt264ezZs2pOSESkDIU2tr6+vvD09MSFCxcAALNmzULVqlWLPRgRkaYaOnRonrMc5AgODlZ5HBcXh65du6ps09XVRbdu3XjzGBHRG95pVoQzZ87g5MmTEAQBWVlZ6NChQ3HnIiLSWK6uru+1v4uLCwYNGgR/f39pVoQHDx5g5cqVcHJyKo6IREQlUqGN7aBBg3Dnzh34+voCABYvXoyDBw/it99+K/ZwRESayN/f/732X7VqFZYuXYqJEydKsyJUr14dPj4+6NOnTzGlJCIqeQptbI8dO4Zr165Jp838/f1hb29f7MGIiDTd06dPMWvWLNy4cQNpaWnS9sOHD6vsZ2BggIEDB2LgwIFyRyQiKlEKbWzr1q2L+/fvo2bNmgBen/5q0KBBsQcjItJ0fn5+6Nq1K3bt2oVFixZh5cqVqFSpUp777tu3D9u2bUNsbCwEQYCFhQXatWuHVq1ayZyaiEi58m1s27ZtC0EQ8OLFC9jY2KBRo0YQBAHnzp2Du7u7nBmJiDTSs2fP0KdPH8yfPx/NmjWT/rxtxIgRuHXrFr7++mtUr14dABATE4Pg4GDs2bMH8+fPlzs6EZEi5dvYjhkzRs4cRERaR19fHwBgbm6OXbt2wcLCAjExMbn22717N27dupVre9euXfHxxx+zsSUi+p98G9u3jxokJiYiMzOz2AMREWmLcePG4cWLF5g7dy6GDh2KxMRE/Pzzz7n2K1WqFM6fP49GjRqpbL9w4QJKlSolV1wiIsUr9BrbkJAQjB8/HqVLl4aOjg5EUYQgCIiMjJQjHxGRxmrTpg0AoFy5cjhy5Ei++61YsQIDBw5EUlKSdCnCgwcPYGJighUrVsgRlYioRCi0sZ09ezauX78OMzOzDzbozz//jD/++AOCIMDe3h7Lly/nUQci0jpPnz7FkiVLEB0drXJGbNmyZSr7OTs749y5c3j8+LHKdF8fYrEc1mMi0iQ6he1Qu3ZtlClT5oMNGBsbi+DgYISFheHatWvIysrChg0bPtj7ExGVFO3atcOLFy/QvHlzfPnll9Kf/FStWhUuLi5wdXVF1apV8ejRI7x69arI47MeE5GmKfSI7YwZM+Du7g43NzcYGhpK299e8vF9ZGZm4uXLl9DX10dqaiosLCyK/F5ERCVVamoqZs2aVeTX9+zZE3fv3kXHjh0xZ86cIr0H6zERaZJCG9vAwEB89tlnsLe3h45OoQd4C1WtWjWMGTMGNWrUQOnSpdGyZUu0bNnyP78vEVFJ06ZNG+zevRutW7cu0usPHjwIURRx48aNIr2e9ZiINI0giqJY0A7u7u44ffr0Bxvw+fPn6NixIzZu3AhTU1N07twZnTp1Qo8ePVT2CwkJQUhICIDX8zW+7+mxq7EvPljmwthXK8cczPHeOZSQgTne3ZgxYxAWFvZBcxgbGyMlJQUGBgbS1F+CICAxMfGd3yM5ORlly5Yt0vhy1WNcvFikfEXi4sIcJSmHEjIwh3Jz5KOgelxoYzt27FjUrFkTbdu2VbkUoUKFCu8dBAA2b96MvXv3YunSpQBer4F+9uxZ/P777/m+xtXV9b0/UKyCdhUpX1FEz8z/mjjmYI78cighA3O8u6LUITnUqFED9+/fL9Jr5arH+N+S7LIo6CONOZSXQwkZmEO5OfJRUB0q9FKEdevWAXh9rW2O/zLdV40aNXD27FmkpqaidOnSOHToEFxdXYv0XkREJV1oaCiOHz8OAPD09JSmAHvTvHnz8nytKIpITk4u8tisx0SkaQptbKOioj7ogG5ubujUqROcnZ2hp6cHJycn9O/f/4OOQURUEgQFBeHChQvw8/MDAMyfPx8nT57EzJkzVfb74Ycf8M0330BPL3fJzs7OLvL4rMdEpGkKbWwzMjKwcOFClSMKgYGB0vVgRTF58mRMnjy5yK8nItIEu3fvRnh4uHRjrr+/P5ycnHI1ts7Ozmjfvj1c8rgW7Y8//vhPGViPiUiTFNrYDhw4EBkZGRg0aBAAYPXq1Rg4cOB/LqZERAQkJCRI9yy8eJH3DXTLly9HxYoV83xOidf9EhGpS6GN7YULFxARESE9/uyzz+Dg4FCsoYiItMH3338PJycneHl5QRRFHD9+XOV+hhx169bN9z2qVKlSnBGJiEqUQhtbXV1d3L17F7Vr1wYAREZGQldXt9iDERFpOl9fX3h6euLChQsQRRGzZs36IMvkEhFpq0Ib2zlz5sDLywvW1tYQRRH37t3D8uXL5chGRKSR/vnnH9SrVw+XLl0CAFSvXh0A8PDhQzx8+BDOzs7qjEdEVGIV2NhmZWUhIiICt2/fxs2bNyGKIurVq6cyny0REb2fefPmISQkBKNHj871nCAIOHz4cK7tWVlZCA4OxsiRI+WISERUIhXY2Orq6iI0NBQjR45EgwYN5MpERKTRclbx2rNnD0qVKqXyXFpaWp6v0dXVxfbt29nYEhEVoNBLEdzd3TFkyBB07doVRkZG0naeKiMi+m/c3d2lyxEK2pbjk08+YT0mIipAoY3t6dOnAQATJkyQtuV3qoyIiAr3+PFjxMbG4uXLl7h8+TJyVjZPTExEampqvq9jPSYiKlihje2RI0fkyEFEpDX27duHFStWICYmBqNGjZK2Gxsb48cff8z3dazHREQFK7SxffXqFbZu3Yro6GhkZmZK2988YkBERO/O398f/v7+2Lp1Kzp27PjOr3vy5Al++OEHPHz4EHv27MGNGzdw5swZ9OnTpxjTEhGVHIU2tu3atUO5cuXg4uLC2RCIiD6ANWvWoEePHoiOjsa8efNyPf/mUdw39erVCwEBAZg+fToA4OOPP0bXrl3Z2BIR/U+hjW1MTAz27t0rRxYiIq2QkpICAEhOTn6v18XFxaFLly7S6mR6enpcMIeI6A3vNCvC1atXYW9vL0ceIiKNFxgYCACYOHHie73OyMgIz549gyAIAICzZ8+iXLlyHzwfEVFJlW9ja2dnBx0dHWRmZmL58uWwtraGoaEhRFGEIAi4cuWKnDmJiDTGsGHDCnw+ODg4z+3z5s2Dj48P7t69i08++QRPnz7Fli1biiMiEVGJlG9jGxsbi/DwcBmjEBFpBxcXFwDAqVOncOPGDXTt2hUAsHnzZum5vDg7O+PYsWPSSpB169aFvr6+LJmJiEqCfBvbWrVqoWbNmnJmISLSCv7+/gCAFStW4MiRI1JzOmDAALRs2TLf16WlpeH333/HyZMnIQgCPv30UwwYMCDX6mVERNoq38b233//zfNu3Rz53bVLRETv5uHDh0hKSkKFChUAvL6Z7OHDh/nu//XXX8PY2BhDhw4FAKxfvx49e/bE5s2bZclLRKR0+Ta2WVlZSE5OllbEISKiDysoKAhOTk7w8vICABw7dgyTJk3Kd/+bN28iIiJCeuzl5QUHB4fijklEVGLk29iam5tzEQYiomIUEBCAL774AufOnQMAzJw5E1WrVs13fycnJ5w9exaNGzcGAJw7dw6ffPKJLFmJiEqCfBtbHqklIioely5dUnlsaWkJ4PWlCQ8fPoSzs3Oerzt37hxWrVqFGjVqAADu378PGxsb2Nvbc7YaIiIU0NgeOnSo2AZNSEhA3759ce3aNQiCgGXLlqFJkybFNh4RkZKMHj0awOubwcLCwuDg4ABRFHHlyhW4ubnh5MmTeb6uOBbLYT0mIk2Sb2ObczNDcRg+fDhatWqFLVu2ID09HampqcU2FhGR0hw5cgQA0K1bN4SEhEgL4Fy7dg1z5szJ93XFMVMN6zERaZJCVx770BITE3H8+HGsWLECAGBgYAADAwO5YxARqd0///yjsqqjnZ2drPOHsx4TkaYRRJkvpg0PD0f//v1Rv359REREwMXFBfPnz4eRkZHKfiEhIQgJCQEAxMTEYMOGDe81ztXYFx8sc2Hsq+W/pCVzMEd+OZSQgTne3ZgxYxAWFvZBc/j6+sLIyAg9evSAIAhYs2YNkpOTsX79+g86Tn7kqse4ePFDRS5cAQtcMIcCcyghA3MoN0c+CqrHsje2YWFhaNy4MU6dOgU3NzcMHz4cJiYmmDp1ar6vcXV1fe8PFKugXf816juLnvklczDHe+dQQgbmeHdFqUOFSUtLw8KFC3H8+HEAgIeHBwYNGgRDQ8MPOk5+5KrHEIT/mPQ9FPSRxhzKy6GEDMyh3Bz5KKgO6fzXPO+revXqqF69Otzc3AAAnTp1ynWHMBGRNihVqhRGjhyJv/76C3/99RcaNmwo6+I3rMdEpGlkb2yrVq0KS0tL3Lx5E8Dr2Rfq168vdwwiIkUIDw/Hd999BysrK4wfPx716tWTbWzWYyLSNLLfPAYACxYsgJ+fH9LT02FtbY3ly5erIwYRkVrcunULGzZswPr161GxYkV07doVoihKsyXIifWYiDSJWhpbR0fHD36tGhFRSVGvXj18+umn2LFjB+rUqQMA+Pnnn9WShfWYiDSJ7JciEBFpu61bt6Jq1arw8vJCv379cOjQIa72SET0AbCxJSKSWYcOHbBx40b8888/8PT0xM8//4wnT55g4MCB2L9/v7rjERGVWGxsiYjUxMjICH5+fti5cydiYmLg6OiImTNnqjsWEVGJxcaWiEgBKlSogMDAQBw+fFjdUYiISiw2tkRERESkEdjYEhEREZFGYGNLRERERBqBjS0RERERaQQ2tkRERESkEdjYEhEREZFGYGNLRERERBqBjS0RERERaQQ2tkRERESkEdjYEhEREZFGYGNLRERERBqBjS0RERERaQQ2tkRERESkEdjYEhEREZFGYGNLRERERBqBjS0RERERaQS1NbZZWVlwcnJCmzZt1BWBiIjAekxEmkNtje38+fNhY2OjruGJiOh/WI+JSFOopbGNiYnBrl270LdvX3UMT0RE/8N6TESaRBBFUZR70E6dOuH7779HUlIS5syZg507d+baJyQkBCEhIQBeF94NGza81xhXY198kKzvwr5aOeZgjvfOoYQMzPHuxowZg7CwsGJIo15y1GNcvPghor4bFxfmKEk5lJCBOZSbIx8F1WPZG9udO3di9+7d+P3333H06NF8C+mbXF1d3/sDxSpo13+J+V6iZ37JHMzx3jmUkIE53l1R6pDSyVWPIQj/IeV7KugjjTmUl0MJGZhDuTnyUVAdkv1ShFOnTiE0NBRWVlbo1q0bDh8+jB49esgdg4hI67EeE5Gmkb2xnTFjBmJiYhAdHY0NGzbgs88+w5o1a+SOQUSk9ViPiUjTcB5bIiIiItIIeuoc3NPTE56enuqMQEREYD0mIs3AI7ZEREREpBHY2BIRERGRRmBjS0REREQagY0tEREREWkENrZEREREpBHY2BIRERGRRmBjS0REREQagY0tEREREWkENrZEREREpBHY2BIRERGRRmBjS0REREQagY0tEREREWkENrZEREREpBHY2BIRERGRRmBjS0REREQagY0tEREREWkENrZEREREpBHY2BIRERGRRmBjS0REREQaQfbG9sGDB/Dy8oKNjQ1sbW0xf/58uSMQERFYj4lI8+jJPqCeHubOnQtnZ2ckJSXBxcUFLVq0QP369eWOQkSk1ViPiUjTyH7E1tzcHM7OzgAAY2Nj2NjYIDY2Vu4YRERaj/WYiDSNWq+xjY6OxuXLl+Hm5qbOGEREWo/1mIg0gSCKoqiOgZOTk9GsWTOMHTsWX331Va7nQ0JCEBISAgCIiYnBhg0b3uv9r8a++CA534V9tXLMwRzvnUMJGZjj3Y0ZMwZhYWHFkEb9irse4+LFDxHz3bi4MEdJyqGEDMyh3Bz5KKgeq6WxzcjIQJs2beDt7Y1Ro0YVur+rq+t7f6BYBe0qarz3Fj3zS+ZgjvfOoYQMzPHuilKHSgI56jEEoYjpiqCgjzTmUF4OJWRgDuXmyEdBdUj2SxFEUUSfPn1gY2PzTkWUiIiKB+sxEWka2RvbU6dOYfXq1Th8+DAcHR3h6OiI3bt3yx2DiEjrsR4TkaaRfbqvpk2bQk2X9RIR0RtYj4lI03DlMSIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINAIbWyIiIiLSCGxsiYiIiEgjsLElIiIiIo3AxpaIiIiINIJaGtu9e/eibt26qFOnDmbOnKmOCEREBNZjItIssje2WVlZGDx4MPbs2YMbN25g/fr1uHHjhtwxiIi0HusxEWka2Rvb8+fPo06dOrC2toaBgQG6deuG7du3yx2DiEjrsR4TkaaRvbGNjY2FpaWl9Lh69eqIjY2VOwYRkdZjPSYiTSOIoijKOeDmzZuxb98+/PHHHwCA1atX4/z581iwYIHKfiEhIQgJCQEA/PPPP6hXr54s+Z4+fYpKlSrJMpbScyghA3Mwh1JyREdHIy4urtjHkZOS67G2/ftiDuYo6TnkzFBQPdaTJcEbqlevjgcPHkiPY2JiYGFhkWu//v37o3///nJGAwC4uroiLCxM9nGVmEMJGZiDOUpKjpJIyfVYKX+vzMEczFFyMgBquBShYcOGuH37NqKiopCeno4NGzbAx8dH7hhERFqP9ZiINI3sR2z19PTw66+/wtvbG1lZWejduzdsbW3ljkFEpPVYj4lI08je2AJA69at0bp1a3UMXSh1XP6QFyXkUEIGgDnexhyqlJKjpFJqPVbK3ytzqGIOVcyhrAyAGm4eIyIiIiIqDlxSl4iIiIg0AhtbIiIiItIIbGypxHj16pW6IxAREViPSbnY2P7Py5cvcfPmTdnHvXTpUoF/5LZ58+Z32lbcevfurfI4OTlZLTe4zJ8//522Fbe8PkTi4+Nlz7Fnz55c2xYtWiR7jqVLl+baFhQUJHsO+vDUVYsB1uP8sB6rYj1Wpbh6LJIYGhoqfvzxx6KVlZUoiqJ4+fJlsW3btrKM7enpKXp6eoqNGzcW9fT0RBcXF9HZ2VnU09MTP/nkE1kyvMnJyemdthW3cePGiQMGDBBFURTj4+PFJk2aiMuWLZM9R17fu6Ojo+w5WrduLaanp0uPHz58KDo7O8ueo0mTJuKhQ4ekxzNnzhRbtWole45WrVqJa9askR4PHDhQ7N27t+w56MNSZy0WRdbj/LAeq2I9VqW0eqyW6b6UZtKkSTh//jw8PT0BAI6OjoiOjpZl7CNHjgAAunXrhpCQENjb2wMArl27hjlz5siSAXj9m9/u3bsRGxuLYcOGSdsTExOhpyf/P5OpU6fiu+++w4ABA3Dx4kUEBQWhY8eOso2/fv16rFu3DlFRUSoT1iclJaFixYqy5cjRvn17dO7cGVu3bsWDBw/g4+Mj67+PHKGhoWjTpg1mz56NvXv34p9//kFoaKjsOf7880/4+PhAR0cHe/bsQYUKFfD777/LnoM+LHXWYoD1OD+sx6pYj1UprR6zscXrScrLlSun1gz//POPVEQBwM7ODuHh4bKNb2FhAVdXV4SGhsLFxUXabmxsjJ9//lm2HH/++af0daNGjTB16lQ0atQIgiDgzz//xFdffSVLDnd3d5ibmyMuLg6jR4+WthsbG6NBgwayZHhTv379kJ6ejvbt2yM6OhqLFy+Gu7u77DnMzMwQGhqK5s2bw8XFBVu2bIEgCLKN/+bpvj/++APt27fHJ598ggkTJiA+Ph4VKlSQLQt9eEqoxQDrcQ7W47yxHr+m1HrMeWwB9OnTB59//jlmzpyJrVu3Ijg4GBkZGbJeq+Lr6wsjIyP06NEDgiBgzZo1SE5Oxvr162XLAAAZGRnIzMzE/fv3UbduXVnHBoCAgIB8nxMEAcuWLZMxzWv37t3D7du30bx5c7x8+RKZmZkwNjaWZex58+ZJX4uiiNWrV8Pe3h5OTk4AgFGjRsmSw9jYWKVgpqenQ09PD4IgQBAEJCYmypKjVq1aKjneLF+CICAyMlKWHFQ8lFCLAdbjHKzHqliPVSm1HrOxBZCamorp06dj//79EEUR3t7eGD9+PEqVKiVbhrS0NCxcuBDHjx8HAHh4eGDgwIGyZgCAHTt2YMyYMUhPT0dUVBTCw8MxYcIEWU9vZGVlITg4GCNHjpRtzPwsWbIEISEhiI+Px927d3H79m0MGDAAhw4dkmX8yZMnF/j8xIkTZckBvC5aDx48QI0aNWQbMy/Z2dk4c+YMPvnkE7XmoA9PCbUYYD1+E+vx/2M9zk2R9Vg9l/YqV2ZmpvjixQu1jJ2amir+888/ahk7h7Ozs5iQkKByQb69vb3sOTw9PWUfMy8ODg7iq1evVH4ednZ2smbIzMwUx4wZI+uY+VHHDRJ5ady4sbojUDFTZy0WRdbjN7Ee/z/W49yUVo853ReA7t27IzExESkpKbC1tUXdunUxe/ZsWTOEhobC0dERrVq1AgCEh4erXCQvF6Vc4+bu7o4hQ4bgxIkTap1ux9DQEAYGBtLjzMxMWa9hAgBdXV21fO95ady4MS5cuKDuGGjZsiW2bt2qcuqLSj4l1GKA9fhtrMf/j/U4N6XVY948BuDGjRswMTHB2rVr0bp1a8yaNQsuLi745ptvZMswefJktd4NnMPOzg7r1q1DVlYWbt++jeDgYLVcFH/69GkAwIQJE6RtgiDg8OHDsuZo1qwZfvzxR7x8+RIHDhzA77//jrZt28qaAXj978HHxwedO3eGkZGRtF2umzdyHDlyBIsXL0bNmjVhZGQEURQhCAKuXLkia4558+YhJSUFenp6KFWqlJRDrmvLqHgooRYDrMdvYz1WxXqsSmn1mI0tXl+gn5GRgW3btmHIkCHQ19eX/bdApfxmvmDBAkyfPh2Ghobw9fWVrnGTW860O+o2c+ZMLF26FPb29li8eDFat26Nvn37yp4jPj4eFStWVPkgEQRB9kKa14Tg6pCUlKTuCFQMlFCLAdbjt7Eeq2I9VqW0esybxwAEBwdj1qxZcHBwwK5du3D//n306NEDJ06ckC2DUu4GflNWVhZSUlJgYmKilvF37dqF69evIy0tTdr25hEDucXHxyMmJkYt08sozb///qvy96KOGxieP3+O27dvq+Tw8PCQPQd9OEqoxQDrcV5Yj5WL9fgt6ru8V9kyMjJkHS8lJUX84YcfRFdXV9HV1VUcO3as+PLlS1kziKIo+vr6ii9evBCTk5PFunXrilWrVhV/+ukn2XMEBgaKPXv2FKtXry5OmjRJtLOzU8tKJs2aNRNfvHghPnv2TLS0tBSdnZ3FkSNHyp7j5cuX4q+//ioOHDhQDAgIkP7Ibfv27WKdOnXEMmXKiFZWVqIgCGL9+vVlz7FkyRLRzs5ONDU1FT09PcVSpUqJXl5esueg4id3LRZF1uO3sR6rYj1WpbR6zMb2f3bu3CnOmjVLnDx5svRHHZKTk9Uybg4HBwdRFEVxzZo14siRI8X09HS13IWbM2bOf5OSksQWLVrIniPn7tslS5aIEyZMUMkkp06dOonjxo0Tra2txRUrVogtWrQQhw0bJnuOBg0aiHFxcdLP5fDhw2K/fv1kz2FnZye+fPlS+vf6999/i126dJE9B314SqnFosh6nIP1WBXrsSql1WPOigBgwIAB2LhxIxYsWABRFLF582bcu3dP1gynT59G/fr1YWNjAwCIiIjAoEGDZM0AqF7j1q5dO7Vd41a6dGkAQJkyZfDw4UPo6+sjKipK9hyZmZl49OgRNm3ahDZt2sg+fo47d+5g6tSpMDIygr+/P3bt2oWrV6/KnkNfXx8VK1ZEdnY2srOz4eXlJeuKTDlKlSolzSn66tUr1KtXDzdv3pQ9B31YSqjFAOvx21iPVbEeq1JaPWZji9dFbNWqVShfvjwmTpyIM2fO4MGDB7JmGDlyJPbt2yete+3g4CBNDi6nwMBAWFlZISUlBR4eHrh3755arulq06YNEhIS8M0338DZ2RlWVlbo1q2b7DkmTJgAb29v1KlTBw0bNkRkZCQ++ugj2XPo6+sDAExNTXHt2jW8ePFCLXdpm5qaIjk5GR4eHvDz88Pw4cPVsnZ99erVkZCQgPbt26NFixZo164dLCwsZM9BH5YSajHAevw21mNVrMeqFFeP1XasWEEaNWokiqIourm5ibGxsWJaWppYp04dtWR4c+LpBg0ayJohP+q4xu1NaWlpYkJCglozqNuSJUvE+Ph48ejRo2KtWrXESpUqiQsXLpQ9R3JyspiZmSlmZGSIK1asEOfPny/GxcXJnuNNR48eFbdv3y6+evVKrTnov1NCLX4zB+txbqzHrMcFUUI95nRf+P/fRr/99lu4uLgAgOxTiFhaWuL06dMQBAHp6ekIDg6WToPJ6dWrV9i6dSuio6ORmZkpbZf77tesrCzs2rUrVw651uLO8fTpUyxZsiRXDrnXSM/599isWTO1rb8NQJqzMTExUS3zR77p+fPnePDgAYyNjWFsbIxr167B2dlZrZnov1FCLQZYj9/GeqyK9Tg3JdVjNrYAxowZg4ULF+LEiRNo0qQJPv30UwwcOFDWDIsWLcLw4cMRGxuLatWqwdvbG7/99pusGQCgXbt2KFeuHFxcXGBoaCj7+Dnatm2LUqVKwd7eHjo66rtipl27dvj000/RvHlz6Orqqi1HQkICVq1alaugBwcHy5pj8eLFmDBhAkqXLg0dHR1pIm65i/v48eOxYsUKWFtbS/8+1DFhPH1YSqjFAOvx21iPVbEeq1JaPeY8tgC6dOkCY2Nj9OjRAwCwfv16JCQkYNOmTWpOJj87Oztcu3ZN3THQoEED2VdPyYujo6NaLsZ/m7u7Oxo3bpzrg8Xf31/WHB999BHOnDkDMzMzWcd9W926dXH16lWV5TWp5GMtVsV6rIr1WBXrcd54xBbAzZs3ERERIT328vKCg4ODrBkiIyMxfPhwnD17FoIgoEmTJvj5559hbW0taw53d3dcvXoV9vb2so77ti+++AL79+9Hy5Yt1ZqjTZs22L17N1q3bq3WHGlpaZg3b55aMwBA7dq1UaZMGXXHgJ2dHRISElC5cmV1R6EPSAm1GGA9fhvrsSrWY1VKq8c8YgugV69eGDBgABo3bgwAOHfuHFauXInff/9dtgyNGzfG4MGD4evrCwDYsGEDFixYgHPnzsmWAQDq16+P27dvw9raGoaGhmpbe/qvv/5Cjx49kJ2dDX19fbWtPW1sbIyUlBQYGBhId8KqI8fPP/+MsmXLok2bNiqnJCtUqCBrjsuXLyMgIABubm4qOeQ+BRcWFoZ27drBzs5OJUdoaKisOejDUkItBliP38Z6rIr1WJXS6rFWN7b29vYQBAEZGRm4efMmatSoAUEQcO/ePdSvX1/WU0Bubm65imbjxo1x9uxZ2TIAwL179/D8+XNpCUsPDw+YmpqiZs2asuawtrbGtm3bpL8jbffbb79h7NixMDU1lX4e6riWqlGjRmjatKnaT8HZ2toiMDAwV45mzZrJmoM+DCXVYoD1+G2sx6pYj1UprR5rdWNb2MTfchaPoKAgmJqaolu3bhAEARs3bsSrV68wePBgAPL9Jjh//nz88ccf+OqrryCKIrZt24Z+/fph6NChsoyfw9vbG3v27FHrjQo5QkNDpTksPT091TIxeO3atXHu3Dm1X0vl7u6O06dPqzUD8LpgHjt2TN0x6ANRUi0GWI/fxnqsivVYldLqsVY3tkpSq1Yt6euc3wBz/mrk/E2wQYMGOHPmjDSNSEpKCpo0aSL7qa9evXohMjISX3zxhcqpDbmnlwkKCsKFCxfg5+cH4PXNLC4uLpg5c6asOXx8fLBhwwa1X081duxY1KxZE23btlXrKbhRo0bB0NAQPj4+Kjk43Rd9CKzHqliPVbEeq1JaPebNYwoxa9YstGrVCiYmJpg6dSouXbqE8ePHy/4PQxRFlWlUdHV1oY7ffWrVqoVatWohPT0d6enpso+fY/fu3QgPD5eOVPj7+8PJyUn2QqqrqwtHR0d4eXmp9VqqdevWAQBmzJghbVPHKbjLly8DgMqpYU73RR8K67Eq1mNVrMeqlFaP2dgqxLRp09ClSxecPHkSBw4cwOjRozFw4EDZb1bIuRC9Q4cOAIBt27ahT58+smYAgIkTJ8o+Zn4SEhKk34BfvHihlgzt27dH+/bt1TL2m9SxPnxejhw5ou4IpMFYj1WxHqtiPValtHrMSxEUwsnJCZcvX8b3338Pe3t7dO/eXdomt0uXLuHkyZMQRREeHh5wcnKSPcOtW7cwZ86cXBNgy/0b4Pr16xEUFAQvLy+Ioojjx49jxowZalknXSlOnz6d6+/l66+/ljWDUlZkIs3EeqyK9Vi5WI9zY2OrEG3atEG1atVw8OBBXLx4EaVLl0ajRo1U5nTUJg4ODhgwYABcXFxUTsXlLLMpp0ePHuHChQsQRRFubm6oWrWq9Nz169dha2tb7BlOnTqFSZMm4d69e8jMzFTbCjM9e/bE3bt34ejoKP29CIIg+ym4Vq1aSSsyvfnvY/To0bLmIM3EeqyK9VgV67EqpdVjNrYKkZqair1798Le3h4fffQRHj16hKtXr6p9Qmx1cXFxwcWLF9Udo1DOzs64dOlSsY9Tr149/Pzzz7kKR8WKFYt97DfZ2Njgxo0bap/yRykrMpFmYj1WxXqsivVYldLqMa+xVYgyZcrgq6++kh6bm5vD3NxcjYnUIz4+HsDrtcl///13dOjQQa13exZGrt8Ly5Urhy+++EKWsQpiZ2eHx48fq/3fplJWZCLNxHr8Gutx3liPVSmtHvOILSlKrVq1IAhCngVKHad6ClPcRwhy3nvTpk3IysrCV199pZbpVNq2bQtBEJCUlITw8HA0atRILSvM5EwQn5mZqYgVmYg0GeuxKtZjVUqtx2xsif6D4i6kXl5e+T4n53QqhU2+LdcKM0qbyJ+IlIP1+DVtr8e8FIEU6bfffoOfnx9MTU0BAM+fP8f69esxaNAg9QZ7i4GBQbG+v1KmUckplFFRUTA3N0epUqUAAC9fvsSTJ09ky5FTKM+ePQtbW1sYGxsDAJKSknDjxg02tkTFgPX4NdZjVUqtxzxiS4rk6OiI8PBwlW1yTrdT2G/9ck/U/sMPP+Dbb79V+WCZO3cupk2bJmsOV1dXnD59WvoASU9PxyeffIILFy7ImsPJyQmXLl2SbprIzs6Gq6urLDeOEGkb1mNVrMeqlFaPecSWFCk7O1u6TgcAsrKyZF3xJmeakrS0NISFhcHBwQGiKOLKlStwc3PDyZMnZcsCAHv27MGPP/4oPS5fvjx2794teyHNzMxUOSpiYGCglpWI3vy3AQA6Ojoq8ycS0YfDeqyK9ViV0uqxjtpGJiqAt7c3unTpgkOHDuHw4cPw9fVFq1atZBv/yJEjOHLkCGrWrIlLly4hLCwMFy9exOXLl1GnTh3ZcuTIysrCq1evpMcvX75UeSyXSpUqqdyYsH37dpiZmcmew9raGsHBwcjIyEBGRgbmz58Pa2tr2XMQaQPWY1Wsx6qUVo95KQIpUnZ2NhYvXoxDhw5BFEW0bNkSffv2VZkzUA55nYLLa1tx++mnnxAaGoqAgAAIgoBly5bBx8cH3377raw57t69Cz8/Pzx8+BCiKMLS0hKrVq2S/cPl33//xbBhw3D48GEIgoDPP/8cv/zyCypXrixrDiJtwHqsivVYldLqMRtbogL4+vrCyMgIPXr0gCAIWLNmDZKTk7F+/XrZs+zZs0flg8Xb21v2DDmSk5MhiqJ0swARUXFjPc4b67EqNrakSEpZsjAtLQ0LFy7E8ePHAQAeHh4YOHCgdBeqtlHKmuBPnz7FkiVLcuVYtmyZrDmItAHrsTKxHueNjS0pklKWLAReXz91//591K1bV/axc/z555/47rvv8O+//0IURemDJTExUdYcSlkT3N3dHZ9++mmuHB07dpQ1B5E2YD1WxXqsSmn1mI0tKZKbmxvOnTun7hgIDQ3FN998g/T0dERFRSE8PBwTJkyQbWWXHHXq1MGOHTtgY2Mj67hvU8qa4Oq4ro5IW7Eeq2I9VqW0esxZEUiRvLy88M033+DMmTO4dOmS9EdukydPxvnz56X5Ch0dHREdHS17jipVqqi9iAL/vya4urVp0wa7d+9WdwwircB6rIr1WJXS6jGP2JIi5bV0oZxLFubIOVLx5mTkDRo0kH0N7OHDh+Px48do3769yprgX331law56tevjzt37qBWrVpqXRPc2NgYKSkpMDAwgIGBgdpOBRJpA9ZjVazHqpRWj7lAAymSUpYutLOzw7p165CVlYXbt28jODgY7u7usudITExEmTJlsH//fmmbIAiyF9I9e/bIOl5+kpKS1B2BSGuwHqtiPValtHrMI7akSE+ePMEPP/yAhw8fYs+ePbhx4wbOnDmDPn36yJojNTUV06dPlwqYt7c3xo0bp7V34QLAyZMncfv2bQQEBODp06dITk5GrVq1ZM0giiLWrl2LqKgojB8/Hg8ePMCjR4/QqFEjWXMQaQPWY+ViPc47EJHitGrVSty4caPYoEEDURRFMSMjQ7Szs1NbnuTkZLWNLYqiePPmTfGzzz4TbW1tRVEUxYiICHHq1Kmy55g0aZLYpk0b8aOPPhJFURRjY2NFd3d32XMMGDBAHDRokFivXj1RFEUxPj5edHV1lT0HkTZgPVbFeqxKafWYN4+RIsXFxaFLly7Q0Xn9T1RPT0/2VW4A4PTp06hfv750o0BERAQGDRoke45+/fphxowZ0NfXB/D6urINGzbInuOvv/5CaGgojIyMAAAWFhZqOQ117tw5/Pbbb9KRmvLly6tljXQibcB6rIr1WJXS6jEbW1IkIyMjPHv2DIIgAADOnj2LcuXKyZ5j5MiR2LdvnzRfo4ODgzQ5uJxSU1NzndbR05P/EnkDAwMIgiD9vaSkpMieAQD09fWRlZUl5Xj69Kn0oUtEHxbrsSrWY1VKq8e8eYwUad68efDx8UFkZCQ++eQTPH36FFu2bFFLFktLS5XH6jhSYWZmhrt370qFY8uWLTA3N5c9R5cuXRAYGIiEhAQsWbIEy5YtQ79+/WTPMWzYMHTo0AFPnjzB2LFjsWXLFkybNk32HETagPVYFeuxKqXVYza2pEj169dHhw4dUKZMGRgbG6N9+/b4+OOPZc9haWmJ06dPQxAEpKenIzg4WC3zF/7222/o378//vnnH1SrVg21atXC2rVrZc8xZswYHDhwACYmJrh16xamTJmCFi1ayJ7Dz88PLi4uOHToEABg27ZtiphXkkgTsR6rYj1WpbR6zFkRSJG6dOkCExMT+Pn5AQDWr1+P58+fY/PmzbLmiIuLw/Dhw3Hw4EFkZ2fD29sb8+fPV8tSksDrU03Z2dkwNjZWy/gA8PjxY5w/fx6CIKBhw4aoWrWqWnJcunQJJ0+ehCAI+OSTT+Ds7KyWHESajvU4b6zH/09J9ZiNLSmSg4MDIiIiCt2mLZ49e4bJkydLhaNp06aYMGGC7AX9jz/+wJQpU/DZZ59BFEUcO3YMEyZMQO/evWXNMWXKFGzevBkdO3aEKIrYtm0bOnfujHHjxsmag0gbsB6rYj1Wpbh6rLb5GIgK4O/vL545c0Z6fPbsWXHgwIGy57h7967Ypk0b0czMTKxUqZLo4+Mj3r17V/YczZs3F6dMmSJGRkaKkZGR4tSpU8XPP/9c9hwff/yxGBcXJz2Oi4sTP/74Y9lz1KtXT3z58qX0ODU1VZpqhog+LNZjVazHqpRWj3mNLSmKvb09BEFARkYGVq1ahRo1akAQBNy7dw/169eXPU/37t0xePBg/PXXXwCADRs2wNfXF+fOnZM1R3x8PMaPHy89HjduHLZt2yZrBgCoXr26ymk3Y2PjXDdzyMHKygppaWnS9DKvXr1C7dq1Zc9BpMlYj/PGeqxKafWYjS0pys6dO9UdQYUoiujZs6f0uEePHvj1119lz+Hl5YUNGzagS5cuAF7fhfvll1/KNv68efMAANWqVYObmxvatWsHQRCwfft2WVeXGTp0KARBgKGhIWxtbdGiRQsIgoADBw6gadOmsuUg0gasx3ljPX5NqfWY19gSFSAoKAimpqbo1q0bBEHAxo0b8erVKwwePBgAUKFChWId39jYGIIgQBRFpKSkSFPbZGVloWzZskhMTCzW8XNMnjy5wOcnTpwoS46VK1cW+Ly/v78sOYhIfqzHr7EeF4yNLVEB3lxzO2fOwpz/ZQRBQGRkpFpyve369euwtbVVdwwMHToUCxYsUHcMdOzYEVu3blV3DCL6gFiP34+21mMu1UNUgFmzZiEiIgJRUVEICAiAg4MDtm7diqioKMUUUQAqp+fU6dSpU+qOAACK+rshog+D9fj9aGs9ZmNLVIBp06bBxMQEJ0+exIEDB9CrVy8MHDhQ3bFy4YkXVTlHc4hIc7Ael0xy12M2tkQFyLmGateuXRgwYADatWuH9PR0NafKjY0cEWk61mN6F2xsiQpQrVo1BAYGYtOmTWjdujVevXqF7OxsdcdSLKUcqVBKDiL6cFiP349S6qDcOdjYEhVg06ZN8Pb2xt69e2Fqaor4+HjMnj1b3bFyMTAwkGWcvJbQfHPb8OHDZckxf/78ArfNmjVLlhxEJB/WY1Wsx3njrAhECnbp0qUCn5d7PW5nZ+dcmfLapo4cTk5OuHz5sqw5iEh7sB6/ew511mMu0ECkYKNHjwYApKWlISwsDA4ODhBFEVeuXIGbmxtOnjwpS449e/Zg9+7diI2NxbBhw6TtiYmJ0NOTr4ysX78e69atQ1RUFHx8fKTtSUlJsq/TTkTahfVYlVLrMRtbIgU7cuQIAKBbt24ICQmBvb09AODatWuYM2eObDksLCzg6uqK0NBQuLi4SNuNjY3x888/y5bD3d0d5ubmiIuLkz5kcnI0aNBAthxEpH1Yj1UptR7zUgSiEsDR0RHh4eGFbituGRkZyMzMxP3791G3bl1Zx37bvXv3cPv2bTRv3hwvX75EZmamyrrpRETFgfU4NyXVY948RlQC2NjYoG/fvjh69CiOHTuGfv36wcbGRvYce/fuhaOjI1q1agUACA8PVzkFJZclS5agU6dOCAwMBADExMSgffv2sucgIu3DeqxKafWYR2yJSoC0tDQsXLgQx48fBwB4eHhg4MCBKFWqlKw5XFxccPjwYXh6eko3BjRo0ABXrlyRNYejoyPOnz8PNzc3KYe9vT2uXr0qaw4i0j6sx6qUVo95jS1RCVCqVCkMGDAArVu3VuspJz09PZQrV05t4+cwNDRUmVInMzOTk6ITkSxYj1UprR7zUgSiEiA0NFQRp5zs7Oywbt06ZGVl4fbt2xg6dCjc3d1lz9GsWTP8+OOPePnyJQ4cOIDOnTujbdu2sucgIu3DeqxKafWYlyIQlQBKOeWUmpqK6dOnY//+/RBFEd7e3hg/frzsp+Cys7OxdOlSlRx9+/blUVsiKnasx6qUVo/Z2BKVAG5ubjh37pzKpNfqKKRvysrKQkpKCkxMTNSWAQDi4+MRExPD6b6ISBasx/lTQj3mpQhEJYBSTjl1794diYmJSElJga2tLerWrauWJS09PT2RmJiI+Ph4ODo6IiAgAKNGjZI9BxFpH9ZjVUqrx2xsiUqABQsW4Pr16zA0NET37t1Rrlw5/PLLL7LnuHHjBkxMTLBt2za0bt0a9+/fx+rVq2XP8eLFC5iYmODPP/9EQEAALl68iIMHD8qeg4i0D+uxKqXVY86KQFQClClTBtOnT8cPP/wAIyMjteXIyMhARkYGtm3bhiFDhkBfX18t11FlZmbi0aNH2LRpE6ZPny77+ESkvViPVSmtHvOILVEJcPr0adSvX1+aBDwiIgKDBg2SPUdgYCCsrKyQkpICDw8P3Lt3Ty3XdE2YMAHe3t6oU6cOGjZsiMjISHz00Uey5yAi7cN6rEpp9Zg3jxGVAG5ubtiyZQt8fHykmxXs7Oxw7do1NSd7/du6nh5P/hCRdmA9Vjbt/u6JShBLS0uVx7q6urJnePXqFbZu3Yro6GhkZmZK2ydMmCBrjqdPn2LJkiW5cixbtkzWHESknViP/5/S6jEbW6ISwNLSEqdPn4YgCEhPT0dwcLBa1iZv164dypUrBxcXFxgaGso+/ps5Pv30UzRv3lwtHyhEpL1Yj3PnUFI95qUIRCVAXFwchg8fjoMHDyI7Oxve3t6YP38+KlasKGsOpZxuc3R0RHh4uLpjEJEWYj1WpbR6zCO2RCWAmZkZ1q5dq+4YcHd3x9WrV2Fvb6/WHG3atMHu3bvRunVrteYgIu3DeqxKafWYR2yJSoDIyEgMHz4cZ8+ehSAIaNKkCX7++WdYW1vLmqN+/fq4ffs2rK2tYWhoCFEUIQiC7CvuGBsbIyUlBQYGBtDX1wcACIKAxMREWXMQkfZhPValtHrMxpaoBGjcuDEGDx4MX19fAMCGDRuwYMECnDt3TtYc9+7dw/Pnz3HixAkAgIeHB0xNTVGzZk1ZcxARqQvrsbJxHluiEkAURfTs2RN6enrQ09NDjx491DIR97Zt29CzZ0/ExcXh6dOn6NmzJ0JDQ2XPAQChoaEYM2YMxowZg507d6olAxFpH9bj3JRUj3nElqgECAoKgqmpKbp16wZBELBx40a8evUKgwcPBgBUqFBBlhwNGjTAmTNnpNV2UlJS0KRJE9lPfQUFBeHChQvw8/MDAKxfvx4uLi6YOXOmrDmISPuwHqtSWj1mY0tUAtSqVUv6OufIQM7/uoIgIDIyUpYc9vb2uHDhAkqVKgUASEtLQ8OGDXH16lVZxs/RoEEDhIeHQ0fn9UmnrKwsODk5yV7QiUj7sB6rUlo95qwIRCXArFmz0KpVK5iYmGDq1Km4dOkSxo8fD2dnZ1lzBAQEwM3NDR06dADw+lRYnz59ZM2QIyEhQToy8uLFC7VkICLtw3qcm5LqMY/YEpUADRo0wJUrV3Dy5En88MMPGD16NH788UfZb1YAgEuXLuHkyZMQRREeHh5wcnKSPcP69esRFBQELy8viKKI48ePY8aMGejWrZvsWYhIu7Aeq1JaPWZjS1QCODk54fLly/j+++9hb2+P7t27S9u01aNHj3DhwgWIogg3NzdUrVpVeu769euwtbVVYzoi0lSsx7kpqR6zsSUqAdq0aYNq1arh4MGDuHjxIkqXLo1GjRohIiJC3dEUydnZGZcuXVJ3DCLSQKzH70fueszpvohKgE2bNsHb2xt79+6Fqakp4uPjMXv2bHXHUiz+vk5ExYX1+P3IXY95xJaINA6P2BIRKQOP2BIRERERFQEbWyLSOAYGBuqOQEREkL8e81IEIioxCjudJfc8kkRE2kqp9ZiNLRGVGF5eXgBer7ATFhYGBwcHiKKIK1euwM3NDSdPnlRzQiIi7aDUesxLEYioxDhy5AiOHDmCmjVr4tKlSwgLC8PFixdx+fJl1KlTR93xiIi0hlLrMRtbIipx/vnnH9jb20uP7ezsEB4err5ARERaSmn1WE9tIxMRFZGNjQ369u2LHj16QBAErFmzBjY2NuqORUSkdZRWj3mNLRGVOGlpaVi4cCGOHz8OAPDw8MDAgQNRqlQpNScjItIuSqvHbGyJqER6+fIl7t+/j7p166o7ChGRVlNSPeY1tkRU4oSGhsLR0RGtWrUCAISHh8PHx0fNqYiItI/S6jEbWyIqcSZPnozz58/D1NQUAODo6Ijo6Gi1ZiIi0kZKq8dsbImoxNHT00O5cuXUHYOISOsprR6zsSWiEsfOzg7r1q1DVlYWbt++jaFDh8Ld3V3dsYiItI7S6jEbWyIqcRYsWIDr16/D0NAQ3bt3R7ly5fDLL7+oOxYRkdZRWj3mrAhEVGKlpKTAyMhI3TGIiLSeUuoxj9gSUYlz+vRp1K9fX5oEPCIiAoMGDVJzKiIi7aO0eszGlohKnJEjR2Lfvn2oWLEiAMDBwUGaHJyIiOSjtHrMxpaISiRLS0uVx7q6umpKQkSk3ZRUj/XUNjIRURFZWlri9OnTEAQB6enpCA4OVuva5ERE2kpp9Zg3jxFRiRMXF4fhw4fj4MGDyM7Ohre3N+bPny+dCiMiInkorR6zsSUiIiIijcBrbImoxImMjETbtm1RqVIlVK5cGe3atUNkZKS6YxERaR2l1WM2tkRU4nTv3h1dunTBo0eP8PDhQ3Tu3Bm+vr7qjkVEpHWUVo/Z2BJRiSOKInr27Ak9PT3o6emhR48eEARB3bGIiLSO0uoxr7ElohInKCgIpqam6NatGwRBwMaNG/Hq1SsMHjwYAFChQgU1JyQi0g5Kq8dsbImoxKlVq5b0dc6RgZxSJggCr7clIpKJ0uoxL0UgohJn1qxZiIiIQFRUFAICAuDg4ICtW7ciKiqKTS0RkYyUVo/Z2BJRiTNt2jSYmJjg5MmTOHDgAHr16oWBAweqOxYRkdZRWj1mY0tEJU7Oco27du3CgAED0K5dO6Snp6s5FRGR9lFaPWZjS0QlTrVq1RAYGIhNmzahdevWePXqFbKzs9Udi4hI6yitHvPmMSIqcVJTU7F3717Y29vjo48+wqNHj3D16lW0bNlS3dGIiLSK0uoxG1siIiIi0gi8FIGIiIiINAIbWyIiIiLSCGxsSZGmT58OW1tbNGjQAI6Ojjh37pzsGRYtWoRVq1bJPi4RkZKwHlNJwmtsSXHOnDmDUaNG4ejRozA0NERcXBzS09NhYWEhW4bMzEzo6enJNh4RkRKxHlNJwyO2pDiPHj2CmZkZDA0NAQBmZmawsLDAhQsX4O7uDgcHBzRq1AhJSUnIysrCN998g4YNG6JBgwZYvHgxAODo0aPw9PREp06dUK9ePfj5+UlL/E2ZMgUNGzaEnZ0d+vfvL2339PTEDz/8gGbNmmH+/PmYNGkS5syZAwAIDw9H48aN0aBBA3To0AHPnz9Xw0+GiEherMdU0rCxJcVp2bIlHjx4gI8//hiDBg3CsWPHkJ6ejq5du2L+/PmIiIjAwYMHUbp0aSxduhTlypXDhQsXcOHCBSxZsgRRUVEAgMuXL+OXX37BjRs3EBkZiVOnTgEAhgwZggsXLuDatWt4+fIldu7cKY2dkJCAY8eOYfTo0SqZvv76a8yaNQtXrlyBvb09Jk+eLN8PhIhITViPqaRhY0uKU7ZsWVy8eBEhISGoVKkSunbtisWLF8Pc3BwNGzYEAJiYmEBPTw/79+/HqlWr4OjoCDc3Nzx79gy3b98GADRq1AjVq1eHjo4OHB0dER0dDQA4cuQI3NzcYG9vj8OHD+P69evS2F27ds2V58WLF0hISECzZs0AAP7+/jh+/Hgx/xSIiNSP9ZhKGl60Qoqkq6sLT09PeHp6wt7eHr/99hsEQci1nyiKWLBgAby9vVW251wP9ub7ZWZmIi0tDYMGDUJYWBgsLS0xadIkpKWlSfsZGRkV3zdFRFQCsR5TScIjtqQ4N2/elH7LB15fT2VjY4OHDx/iwoULAICkpCRkZmbC29sbCxcuREZGBgDg1q1bSElJyfe9c4qmmZkZkpOTsWXLlkLzlCtXDuXLl8eJEycAAKtXr5aOFhARaTLWYyppeMSWFCc5ORlDhw5FQkIC9PT0UKdOHYSEhCAgIABDhw7Fy5cvUbp0aRw8eBB9+/ZFdHQ0nJ2dIYoiKlWqhG3btuX73qampujXrx/s7e1hZWUlnUorzMqVKzFgwACkpqbC2toay5cv/0DfLRGRcrEeU0nD6b6IiIiISCPwUgQiIiIi0ghsbImIiIhII7CxJSIiIiKNwMaWiIiIiDQCG1siIiIi0ghsbImIiIhII7CxJSIiIiKNwMaWiIiIiDTC/wEwm+2eOSOGdQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,7))\n",
    "\n",
    "ax1 = fig.add_subplot(121)\n",
    "x = list(summary_stats.index)\n",
    "y1 = summary_stats['percent_thrombolysis'].values\n",
    "ax1.bar(x,y1)\n",
    "ax1.set_ylim(0,20)\n",
    "plt.xticks(rotation=90)\n",
    "plt.yticks(np.arange(0,22,2))\n",
    "ax1.set_title('Thrombolysis use (%)')\n",
    "ax1.set_ylabel('Thrombolysis use (%)')\n",
    "ax1.set_xlabel('Scenario')\n",
    "ax1.grid(axis = 'y')\n",
    "\n",
    "ax2 = fig.add_subplot(122)\n",
    "x = list(summary_stats.index)\n",
    "y1 = summary_stats['add_good_outcomes_per_1000'].values\n",
    "ax2.bar(x,y1, color='r')\n",
    "ax2.set_ylim(0,20)\n",
    "plt.xticks(rotation=90)\n",
    "plt.yticks(np.arange(0,22,2))\n",
    "ax2.set_title('Additional good outcomes\\nper 1,000 admissions')\n",
    "ax2.set_ylabel('Additional good outcomes\\nper 1,000 admissions')\n",
    "ax2.set_xlabel('Scenario')\n",
    "ax2.grid(axis = 'y')\n",
    "\n",
    "plt.tight_layout(pad=2)\n",
    "\n",
    "plt.savefig('./output/global_change.jpg', dpi=300)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aba18f3d",
   "metadata": {},
   "source": [
    "### Plot changes at each hospital"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5dd5cde9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compare_plot(base_rx, test_rx, base_benefit, test_benefit, name):\n",
    "    \n",
    "    # Set up sublot\n",
    "    fig, ax = plt.subplots(1,2, figsize=(10,6))\n",
    "    \n",
    "    # Thrombolysis use    \n",
    "    x = base_rx\n",
    "    y = test_rx\n",
    "    for i in range(len(x)):\n",
    "        if y[i] >= x[i]:\n",
    "            ax[0].plot([x[i],x[i]],[x[i],y[i]],'g-o', alpha=0.6)\n",
    "        else:\n",
    "            ax[0].plot([x[i],x[i]],[x[i],y[i]],'r-o', alpha=0.6)\n",
    "    ax[0].set_xlim(0)\n",
    "    ax[0].set_ylim(0)\n",
    "    ax[0].grid()\n",
    "    ax[0].set_xlabel('Base thrombolysis use (%)')\n",
    "    ax[0].set_ylabel('Scenario thrombolysis use (%)')\n",
    "    ax[0].set_title('Thrombolysis use')\n",
    "    \n",
    "    # Benefit\n",
    "    x = base_benefit\n",
    "    y = test_benefit\n",
    "    for i in range(len(x)):\n",
    "        if y[i] >= x[i]:\n",
    "            ax[1].plot([x[i],x[i]],[x[i],y[i]],'g-o', alpha=0.6)\n",
    "        else:\n",
    "            ax[1].plot([x[i],x[i]],[x[i],y[i]],'r-o', alpha=0.6)\n",
    "    ax[1].set_xlim(0)\n",
    "    ax[1].set_ylim(0)\n",
    "    ax[1].grid()\n",
    "    ax[1].set_xlabel('Base benefit')\n",
    "    ax[1].set_ylabel(f'Scenario benefit')\n",
    "    ax[1].set_title('Clinical benefit\\n(additional good outcomes for 1,000 admissions)')\n",
    "    \n",
    "    \n",
    "    # Make axes places consistent\n",
    "    ax[0].xaxis.set_major_locator(MultipleLocator(5))\n",
    "    ax[0].yaxis.set_major_locator(MultipleLocator(5))\n",
    "    ax[1].xaxis.set_major_locator(MultipleLocator(5))\n",
    "    ax[1].yaxis.set_major_locator(MultipleLocator(5))\n",
    "    ax[0].xaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n",
    "    ax[0].yaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n",
    "    ax[1].xaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n",
    "    ax[1].yaxis.set_major_formatter(FormatStrFormatter('%.0f'))\n",
    "    \n",
    "    fig.tight_layout(pad=2)\n",
    "    plt.savefig(f'{name}.jpg', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "249288f2",
   "metadata": {},
   "source": [
    "#### Plot effect of speed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "45ea3ebc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JpfDkNRZ9303R36uIBHGuUIxmotG6kX/f+WOV0pf8Gc7l6TfjXGZfkW9SCc/tZnj6RHH/0wXUikjxCFxxm8brk4b9bBj+cxtpouOM2cfkjPzZHgZWjnKcXpwRtJFtPp3+uhcnkLqoqA+rMs7EZHIjwhuNMefijLr/fSmpFUz8s4CJX0un4gWKrkrmXusrOTGZbdj9ue+L7zt3RFuL7x/p33Hec16V+1v7FCdeoyP/loThr5/TNt7vwhjzfWPM63BeEwYnvWSk036fL+F1cAHDUz1OooGtmm4/BG4Up1yKB+dNMgk8dQb7/IfcKNJFOLlf+RmqPwA+LSILc/lIm3DyaU9inKT0e3HykNqMMR0A4kxce2eu80rifOLOjny+iKwTkdfkzikKJEZ7XM4u4E9ExCPORLt3F+3nWhG5JDf6FcF5U8kaJ63hZ8CdIlIpIpaIrBSRa0Y7gFKT6CFOXP4EZ8QkjjOpqxa4PX+HMeYQzizxO0TEKyKvY3hqwL3A28WZqOTFKd0z1vtQD06awrnjtGuViPyZOJNSbwYuBB4o4ZwqcP6e+3ACwH8q4Tl5PwQ+JiLLcnn5n8jfYYw5jNOX/bM4E0EvBf6SEx+Ux+uTfgi8X0QuzAX8hZ/rSCUcZxdwg4jUisgSnFG2YscY/nP9HvBmEfnj3M9ygYhclruE/UPg/4pIhThlrf6eMfrR8eRG7b4BfFFEFgHkfobX5b5/u4jkUxYiOP3nWH3oqfwsJpTrT/04V8Ukt5/iSVrbReQzuZv/g5OadlPuOZuA3xtjXsrd/22cYGxZbjRzI/Bfubbuw/nd3J47xh/h5JcOm7xcpALnZzGUu1L4kaL7HgQuEpF35a6QfpSTP8CclrF+FyKyWkTeKM6ExwROPzDa7+i03+fHex3kjvtq4Ofj7UMDWzWtjDF7cS71fxXnE/w7cCYBpM5gt4/jXLp4FPjXXO4QwD/ivMn+Hmfm6bO5bWNpxZko852ibRbOH2UX0I/zBv+/RnluJU6nPYBzCaYPJ69oNP+A8wl/ACfH7vtF9y3BefOP4CTJP86JN5H34VwWfDH33HtxRpGVmkrfxgmSArnbX8LJl+sFnsa5nFzsz3AmrfTjBGffzt9hnPz0DTiv+W6c1/GoC6UYY2I4+btP5i5dv3bE/X04VzQ24vy93Qa83RjTW+I5HcIZQXoxdx6l+gbOh8zf45RteghnUmf+Df5PcUaAu3CCoNuNMfk34jH7JGPMwzg/21/i9Ge/nKAd4x3nOzijWgdzbb17xHP/GSfADonI/5f7IH8Dzs+yHyf4yo86/i3Oh/UDwBM4v7tvTdC2sXwC59yezl1a/wXO6D84E+Z+gTN48Bvg/xljtpe43/F+FqV4A06Q9hAnJkQWLwSyHHgSwDi50TfhvDYHcF7rxXMd/hMnZ/Q54HmcALS4BvSfAGtzz/0c8O7cPkfz/+H8PQ3ivO4Kv8fc6/w9uX304fz8njyFcx7PWL8LX+54vTipBItwRpGHOcP3+fFeB+8EthtjxrryCjiTXEo4jlJznzgTX14ClhhjIjPdHqXOFiLyT8BxY8yXZrotZxsReRvwH8aYkWkRag4Qp5TdPcaYK2e6LfOdiPwW+EtjzPPjPk4DW6WcS1E45YIqjTHj1o9USs1fuZHra3FG9BbjXEZ+2hhz60y2Synl0MBWzXu5/NljOJcmr8/lbCml1Ely+a+P45T2i+Ncav6YXuVR6uygga1SSimllJoTdPKYUkoppZSaEzSwVUoppZRSc4J74ofMvOrqanPeeaOt+ja3RKNRysrKJn7gLKfnOffMl3MdeZ7PPPNMrzFm4ThPmdXmS99bbL68lovpOc8Pc+mcx+t7Z0Vgu3jxYnbu3DnTzZhy27dvZ/369TPdjCmn5zn3zJdzHXmeIjLesqez3nzpe4vNl9dyMT3n+WEunfN4fa+mIiillFJKqTlhygJbEVkuIo+JyB4ReUFEPpbb/hkROSIiu3JfN0xVG5RSar7RvlcpNZ9NZSpCBthojHlWRCqAZ0Qkv8TdF40xYy03qpRS6vRp36uUmremLLA1xnTjrAWOMWZQRPYAy6bqeEoppbTvVUrNb9MyeUxEVgCXA78Frgb+RkTeB+zEGVkYGOU5HwI+BLBw4UK2b98+HU2dUUNDQ3qec8h8OU+YP+c6287zdPpepZSazaZ85TERKcdZfvD/GmN+JCKLgV7AAJ8F6o0xHxhvH6tXrzZ79+6d0naeDebSjMXx6HnOPfPlXEepivCMMWbtzLVobKfb944YVHj1D3/4w2ls9cwbGhqivLx8ppsxrfSc54e5dM7XXnvtmH3vlI7YiogHuA/4njHmRwDGmGNF938DeGAq26CUUvPNmfS9xpivA18HZ1BhPnxgKTZfPqQV03OeH+bLOU9lVQQBvgnsMcb8W9H2+qKH/RHw/FS1QSml5hvte5VS89lUjtheDfwF8JyI7Mpt+xTwpyJyGc7lsIPAh6ewDUopNd9o36uUmremsirCE4CMctdDU3VMpZQ6VW2dbbTubqU91E5TdRMta1pobmie6WadNu17lVLzma48ppSat9o629i0fRO9sV6WVSyjN9bLpu2baOtsm+mmKaXUnNbW2caGBzdww/duYMODGyat39XAVik1b7XubiVjZ3jy8JP8z0v/w/PHnydjZ2jd3TrTTVNKqTlrKgcVpqWOrVJKnY1+d/R3dIQ7iKfjuC03iUyCl3pfIpaOzXTTlFJqzmrd3UqVr4q+eB998T5W1qwsbD/TVDAdsVVKzVuRZARBcFvOZ3yv24sgRJKRGW6ZUkrNXe2hdip9lURTUaKpKACVvkraQ+1nvG8NbJVS81altxKDAQGX5SKZSWIwVHorZ7ppSik1ZzVVN500gBBJRmiqbjrjfWtgq5Saty6vv5zzF5xPXaAOt+Um4A5w/oLzubz+8plumlJKzVkta1oIJ8PE03GMMYQSIcLJMC1rWs543xrYKqXmrZY1Lbhdbi5edDHXrbyOixddjNvlnpTOVSml1OiaG5rZvH4zQW+QcDJMXbCOzes3T0qpRZ08ppSat/Kda3Ed241XbpzVdWyVUmo2aG5o5qYLbgJg41UbJ22/Gtgqpea15oZmDWSVUmqO0FQEpZRSSik1J2hgq5RSSiml5gQNbJVSSiml1Jygga1SSimllJoTNLBVSimllFJzgga2SimllFJqTtDAVimllFJKzQlax1YppZRSSk2rts427ttzHwPxAQ4MHKBlTcuk1BTXEVullFJKKTVt2jrb2LR9E7FUjCpfFb2xXjZt30RbZ9sZ71sDW6WUUkopNW1ad7dS5asi4AkgIlT7q6nyVdG6u/WM962BrVJKKaWUmjbtoXYqfZWUecso85YBUOmrpD3Ufsb71hxbpZRSSik1bZqqm+iN9bKyZmVhWyQZoam66Yz3rSO2SimllFJq2rSsaSGcDBNKhLCNTSgRIpwM07Km5Yz3rYGtUkoppZSaNs0NzWxev5m6YB1HBo9QF6xj8/rNk1IVQVMRlFJKKaXUtGpuaJ6UQHYkHbFVSimllFJzgga2SimllFJqTtDAVimllFJKzQka2CqllFJKqTlBA1ullFJKKTUnaGCrlFJKKaXmBA1slVJKKaXUnKCBrVJKKaWUmhM0sFVKKaWUUnOCBrZKKaWUUmpO0MBWKaWUUkrNCRrYKqWUUkqpOUEDW6WUUkopNSdoYKuUUkoppeYEDWyVUkoppdScoIGtUkoppZSaEzSwVUoppZRSc4IGtkoppZRSak7QwFYppZRSSs0JGtgqpZRSSqk5QQNbpZRSSik1J2hgq5RSSiml5gQNbJVSSiml1Jygga1SSimllJoTNLBVSimllFJzgga2SimllFJqTnDPdAOUUrNPW2cbrbtbaQ+101TdxMXZi1nP+plullJKqXlOR2yVUqekrbONTds30RvrZVnFMnpjvWw9uJW2zraZbppSSql5TgNbpdQpad3dSpWvir54H+2hdqr91ZS5y2jd3TrTTVNKKTXPaWCrlDol7aF2Kn2VRFNRoqkoAGWuMtpD7TPcMqWUUvOdBrZKqVPSVN1EJBkZti2ajdJU3TRDLVJKKaUcGtgqpU5Jy5oWwskw8XQcYwyhRIhoJkrLmpaZbppSSql5bsoCWxFZLiKPicgeEXlBRD6W214rIj8XkZdz/9dMVRuUms/aOtvY8OAGbvjeDWx4cMOkTe5qbmhm8/rNBL1BwskwdcE6bllxC80NzZOyf3VmtO9VanJMVR+qptZUjthmgI3GmAuA1wIbRORC4JPAo8aYVwGP5m4rpSbRaJULNm3fNKnB7U0X3MQHr/ggW27cwgWVF0zKftWk0L5XqTM01X2omjpTFtgaY7qNMc/mvh8E9gDLgD8A8tOnW4E/nKo2KDVfjVa5oMpXNWmVC9o627hvz33c9exdbHhwA3sieyZlv+rMad+r1Jmb6j5UTZ1pWaBBRFYAlwO/BRYbY7rB6YBFZNEYz/kQ8CGAhQsXsn379ulo6owaGhrS85xDZvI8d+7fyULfQrqj3QAEEgGMMRzsPnjGbdoT2cPWg1vpT/XjFS8vHnqR3yR+Az9hzo/czrbXrva9p262/Y4ng57zyaayD50p8+X3POWBrYiUA/cBtxpjIiJS0vOMMV8Hvg6wevVqs379+ilr49li+/bt6HnOHTN5nmuja+mN9VLpqgRg6eKlhBIhzgmec8ZtuufBe2iqb8IVdgGwavEq9h3ex/Ou5/nI+o+cadPParPptat97+mZTb/jyaLnfLKp7ENnynz5PU9pVQQR8eB0rN8zxvwot/mYiNTn7q8Hjk9lG5Saj0arXBBOhielckG+jm2Zt4wybxmgdWzPNtr3KnVmprIPVVNrKqsiCPBNYI8x5t+K7voJkH9ltAD3T1UblJqvRqtcsHn95kmpXJCvY7uyZiUra1YCWsf2bKJ9r1Jnbir7UDW1pjIV4WrgL4DnRGRXbtungM8BPxSRvwQ6gPdMYRuUmrfylQsANl61cdL227KmhU3bNwFQ6askkoxoHduzi/a9Sk2CqepD1dSassDWGPMEMFZS15um6rhKqamVH8lo3d1Ke6idpuom1q9YryMZZwnte5VS89m0VEVQSs0tzQ3NwwLZ+TDTViml1NlPl9RVSimllFJzgga2SimllFJqTtDAVimllFJKzQka2CqlTti6FS6+GBYudP7funWmW6SUUkqVTCePKaUcW7fCxz8OgQAsWADhsHMb4JZbZrZtSimlVAl0xFYp5bjzTieoLS8HEef/QMDZrpRSSs0COmKrlHIcO+aM1BYrK3O2K6XUWa6ts21Yfe2WNS1aX3se0hFbpZRj8WKIRodvi0ad7UopdRZr62xj0/ZN9MZ6WVaxjN5YL5u2b6Kts22mm6ammQa2SinHxo0Qj8PQEBjj/B+PO9uVUuos1rq7lSpfFX3xPtpD7VT7q6nyVdG6u3Wmm6ammaYiKDVDzrrLZvkJYnfe6aQfLF4MmzfrxDGl1FmvPdTOsopldIQ7CtsqfZW0h9pnsFVqJuiIrVIz4Ky9bHbLLfD889DT4/yvQa1SahZoqm4ikowM2xZJRmiqbpqhFqmZooGtUjNAL5sppdTkaVnTQjgZJp6OY4whlAgRToZpWdMy001T00wDW6VmQHuonUpfJdFUlGjKmbCll82UUur0NDc0s3n9ZoLeIOFkmLpgHZvXb9aqCPPQuDm2InIl8OfA64F6IA48DzwIfNcYE57yFio1BzVVN9Eb6x22TS+bKaXU6WtuaOamC24CYONVOul1vhpzxFZEHgY+CGwDrscJbC8EPg34gftF5J3T0Uil5hq9bKaUUkpNvvFGbP/CGNM7YtsQ8Gzu604RqZuylik1h+Uvm9267VYG4gPUBevYeOXGCS+bnXWVFJRSSqmzyJiB7ShBLSLyJiAIPGKMSY/2GKVUaU71slm+kkKVr2pYJQXNI1NKKaUcJU8eE5E7gTcDrwXun7IWKaVGdaqVFNo627hvRyt3PfSPbPjIObR97N3QpqvwKKWUmrvGy7H9VxGpKtrUCHwKJ8e2caobppQa7lQqKbR1trHp/o8R62ynKi30VrjY5H2Ctn/5qAa3Siml5qzxRmz/B7hbRP5WRFzAt4GngV3A16ehbUqpIqdSgLx1dytVnT0EbAsZHKK6vYuq/hitdZ3QqrVylVJKzU1jBrbGmCeNMdcDIeCR3LbXGGPWGGO+Mk3tU0rlnEolhfZQO5U9EcoGE5QlDYhQGTe0Z3rhd7+bgdYrpZRSU2+8VAS3iNwIHAP+CLhcRH4iIpdOW+uUUgWnUoC8qbqJiEmyMuJh5aAzRzTiF5qG3BCJnPR4pZRSai4Yr9zXj3HSDoLAe40xLSKyFNgsIsYY81fT0D6lVJFSKym0rGlh08Pfg3SWyoQh4hfC7gwb95ZBZeV0NVcppZSaVuMFtucYY94uIl6c3FqMMV3AB0XksulonFKqRG1tTu5sezs0NdHc0sJm15tpDTxNeyBEUwg2HlhIc91KWL16plurlJqDtM62OhuMF9h+XUR2AQa4s/gOY8yuKWyTUupUtLXBpk1QVQXLlkFvL2zaRPPNN9N895CzvbISiEA4DC26uplSanJpnW11thhvgYavAl+dxrYoNS91hDvY8OCG0x/laG2FTAaefBISCVi8GOrrYedO2Lx52EguGzdCs77JKKUmV3Gd7b54HytrVha2T1ZgqyPCqhTjTR77tIjUjHP/G0Xk7VPTLKXmh45wB9v2b6M31jtslKOt8xRqzf7ud/DSSxCPg2U5/7/0krO9uRm2bIGHHnL+16BWKTUFTqXO9unIjwifUV9ZZE9kDxse3MAN37uBDQ9uOO39qLPPeKkIzwEPiEgCeBboAfzAq4DLgF8A/zTVDVRqLtvZtRO/2z/mKMdoIxQniURABNy5P2efD9JprX6glJo2TdVN9MZ6h20bq852qYr7v45wB0vKlkzKiHBbZxtbD26lqb6pECR/9OGP0lDZQNdQF5FkhEpvJZfXX45b3DRW65pUs8l4dWzvN8ZcDfw18ALgAiLAd4FmY8zfGWN6pqeZSs1N/fF+fC7fqKMcY41QdIQ6hu+kshKMcb53uyGVcm5r9QOl1DQ5lTrbpRjZ//XF+nip7yWODh494xHh1t2tlLnLCsuTpzIpDoYP8vSRp+kIdxBOhOmIdLC3dy+PHHjk5D5XndXGG7EFwBjzMvDyNLRFqTlv5Aisx/KQzCYJuAOFx+RHOcbKWdvRvWP4CMLll0MwCN3dMDgIfr+TT6vVD5RS0yRfZ/vWbbcyEB+gLljHxis3nnYO7Mj+rzZQSyQZoTfeS4WvAjj9EeH2UDtlrjL6Un0AdA92E/QE6RrsospXhdvlJmNn6B7qJuAKsKN7x2mdg5oZ4y2pq5SaRKONwIaTYQbiA6OOcoyWs5bMJNnTs4e7nr3rRF5YS4szUnvxxXDddc7/brdWP1BKTat8ne0PXvFBtty45Ywmdo3s/1YtWIXBEEvHznhEuKm6iWg2Wrg9mBoEA8YYDIZMNoOxDYOpQfxuPwPxgdM+DzX9NLBV6hS0dbad9oSD4hGI9lA71f5qavw1VPmrRl1NrKm6iUjyRJ7s8ehxnj7yNC7LRZWv6sTkiaU41Q/q6uDIEef/zZt1ophSatYa2f8tKlvE+XXnE/RMvPLiRFrWtBDNRAsDCl6Xl1gmRrm3nKzJApA1WSq8FSQyCWoCY86jV2chDWyVKtGZzsodbQTW7/aTzqZHHeUYmbP23LHnAFhStgQRodpfTZWvitbdrVr9QCk1p4yWs+u23Nx84c1nPCLc3NDMLStuKQwoXLb4Mpqqm1gQWEAmmyGZSZI1WerL64ln46yrXzfJZ6em0oSBrYisEpFHReT53O1LReTTU980pc4uo424FgLLEowcgQDGHQ3I56zlO9+0neY1y17DkoollHnLgMktp6OUUmeLkf1ffoR2sioUXFB5QWFA4d6b7+XL13+ZurI6agI1+D1+qnxVrK5bzfXnXq9VEWaZCSePAd8APg78J4Ax5vci8n3gH6eyYUqdbdpD7SyrWEZH+MQM2VMJLFvWtPDRhz/KKwOvkLEz9MR6SGVTXHPONSU9v8JXQTQVZWXtysK2My2no5RSZ6t8zi7Axqs2AvDrjl9P+bHyNl61kTufunOMZ6izVSmpCEFjzMhrrZmpaIxSZ7PRRlxPNbAUEQzGWajagCBjPjaf+hBLxajyVbGkfAm7ju1if/9+bGOfcTkdpZRSaq4pJbDtFZGVOG/FiMi7ge4pbZVSZ6EzrdPYuruVxqpGagO1LCxfyJvOfRM1/poxS8nkUx8CngAiwsqalVy25DKORo9yZPDIGU2eUEoppeaiUlIRNgBfB84XkSNAO/DnU9oqpc5CZ1qnMZ/KkMqkSGVTPNHxBEciRxAROpZ20FjVOOrj8/m04Iwae11eHnrvQ5N6bkoppdRcUMoCDQeAN4tIGWAZYwanvllKnZ1Gy/kqVX7JyVQ2RSgZIugJYlkWllhs27+N61ZeN+rj8wszgObUKqXmntGWDtcrUep0lVIV4WMiUgnEgC+KyLMi8tapb5pSc0s+lSGSiiBGGEoPkcwkWVK2BL/bz86unaM+PpQIaU6tUuqsNLK296kuP3umZRSVGqmUHNsPGGMiwFuBRcAtwOemtFVKzUH5VAbb2BgMglDuLafCV4HP5aM/3j/q4+uCdZpTq5Q664wWlD5y4JFTCm7PtIyiUiOVkmObn7Z9A7DVGLNbRMaeyq2UGlNzQzOLyxaTyqY4p+ocuga7GEwOcjR6lKydZcODG4ZdhmtuaNZAVil1VioOSvvifaysWUnAFRhzQuxozrSMolIjlTJi+4yI/AwnsN0mIhWAPbXNUmruWl65nIydIZ6Ok8wkORQ5RDKT1MtwSqlZZazVFAfiAyXvYzLKKCpVrJTA9i+BTwLrjDExwIuTjqCUOg3V/mpWL1hdWFHHZ/lYUb2CCl+FXoZTSs0ap7qa4mhKLaOYz+W969m7+NGeH03Lh/+2zjbu23Mfdz17Fxse3KADDrNEKYHt64By4FIReQNwEVA9lY1Saq6r9ldzU2Q5X/xpmu9/K8zG77Wzan8I0MtwSqnZYbSgNJ6Ns65+Xcn7GGvp3OIUrI5wRyGXt9JXSTQdnfIrW/lj5hfI0atps0cpObYfL/reDzQDzwBvnJIWKTUPVO5+iTX/006fN8vhCmFhNMst/9POg8FFdJy/RC/DKaXOeqPV9r7+3OtprG6c+Mkj9jNeGcWdXTtpqGygL95Hf6KfukBd4crWVM1ByB8znAgDzmAEMKXHVJOjlDq27yi+LSLLgc9PWYuUmqVG1mK8OHsx61l/0uNCiRA3bm8n7LNYGDMsiNscqk0DHi7dtovnmq5k45WnViNXKaVmwsig9M6n7pz0Y/TH+7lw4YV0hDuIJCIMJgfpjHRiiTXpNW87wh3s6NrB74/9noHEAGWeMqr8VYBeTZstSklFGKkTuHiyG6LUbDZa2ZutB7eedNmqrbONXcd20difxZ1Oc+Exm3VdcNUhgySSNPSltKSXKhCRj5WyTam5rDZQSyTpBLSRZIR0No3H8uCxPJOaHtAR7mDb/m3EUjHKPGVOxZqho1R4KgCd1DZbTDhiKyJfBUzupgVcBuyewjYpNeuMVvamzF027LJVW2cbH3vkY8RSMaJueN1hcNuQcglltovmIxmOXFLPFRrUqhNagC+P2Pb+UbYpNW1GXp1yi/uU0w9Oxdqla9nbt5ej0aNYYpGyU4RTYd7Q+Aa8Lu+kpQfs7NqJ3+0n4A6wqGwRoWQIDOzt34vX7SWcDOvVtFmglBzb4uWQMsAPjDFPTlF7lJqVRqvFWOYqG3bZ6vNPfp72UDuWWIicqJhnMNjGuX1OzYppa7M6e4nInwJ/BjSJyE+K7qoA+mamVUqduDpV5asqXJ3adWwX1597/WntKx8ghxKhMSedNVY18t5L3st1372OrMliYbG0fCmLyhZhG3tS0gPaOtt4sedFDIZybzn15fWsrV3L3t699MR6qAvWsfHKjXo1bRYoJcdW6w6pWWe61x5vqm6iN9Y7bFs0G+XC6gsLt3d07SDoDjLkHqIsnaFtuXBFlyGQhqRHkEvWcI7xT1kb1azyFNAN1AHFSYuDwO9npEVKMTmLMsDJAfIrfa/Q+vtWdnTt4PL6y0/qs5sbmrlg4QUcHDiIx+Wh3FsOTE56QL4tLsuFbWy8Li9Hh47SUNHAJYsvoS5Yx5Ybt5zRMdT0KWXEVqlZZbQRhU3bN51W7upoAXJHuIOdXTt5tP3RwraWNS1s2r6Jvlgf4WSYg6GD2Bmb99W/D9raoLUVKo+D20NVWZDuhVmqh7L8bJWNiPD2VW9nUdoLdXVT9FNRs4kx5hBwCLhyptuiVLHRrk6d6qIMcPJSusdjx8FAKBka1mcXW1e/jlf6X4Esw2renml6QL4t9eX1HI4cRhA8Lg/P9TzHebXnafrBLHM6k8eUOqtNxtrjbZ1tvPvud3Pj929k2/5teCwPe3v38s7/fidff+br7O3bi8fyFDpggJsvvJmeWA/xTJyaQA3L/Mv43Tf/kcE3vh7+4z9YdyBBLDmEry/MQ6+uYkHazYKUm4aKBieoDYehpWWClqn5QESeyP0/KCKRoq9BEYlM9HylpspkLMoAw1ct6wh34BIXNjbHo8fH7LMbqxtZVbuqkO86Ws3b05Fvy+LyxaxasAq/2086myadTetk3lnolEZsRcQCyo0x2rGqs9aZrj2eH/F9pe8VKrwVDKYGeezgYwTcAaLpKLaxSWQSPHH4Cd6w/A3DOuBzqs8hmo6ytGIptft6+dOfHMDOAOLitiehs8LQW57mt5VhsjfU8t5nMjSbemekduNGaNYOVAHwPgBjTMVMN0SpYvmrU/F0HL/bX1iU4Zr6a0567HgpYcXpW8lMEq/LSyKTwO1xwpJ8n31uzbnD9lkTqKEmUMP6FetHrXlbqj2RPdzXcx8D8QFclotUNsXKmpWF+0OJEHXBOg1qZ6EJR2xF5PsiUikiZcCLwF4R+XgJz/uWiBwXkeeLtn1GRI6IyK7c1w1n1nylTnama4/nR3xDyRDJbBIMpLIp4pk4GTtD1mQRBAzs699X6IDbQ+34XD5SmRTRVJTyA/t5VR9EPc5+m4+6+MrPLK7bL1xyDJa+8Q9p/O5Pqf7lU7Bliwa1qtg9ACLy6Ok8WftfBSeWob3hezdM2pKwo60UNtqiDKOVQCwuzVW8apnX5SWZSWIbm7qAk441laW12jrb2Hpwa2FVsSVlS9h1dBf7B/ZjG3vMZX3V7FBKKsKFuRHaPwQeAhqBvyjhef8FjDZN8ovGmMtyXw+V2lClSlXq2uMwesefvyzlttwksgkAbGOTtbMATlALuMTFYGqw0AE3VTc5gXCOlUxhLPAYAXG+mo+52fKg4aGfL2LLjVt0NECNxRKR24FVIvL3I79KeP5/of3vvDZRYHkm8osyfPCKD7Llxi2jlvqaKCWsOEAOeAIgUOYuo9xbPuWBZevuVsrcZQQ8AUSElbUruWzxZRwdOsqRwSOTluKgZkYpqQgeEfHgBLZfM8akRcRM8ByMMb8SkRVn2D6lTtloyzyOVqZlrElm5Z5yIskIC4MLORw5DEKuRJfgEQ/GOOW5siaL1zW8tuED+x6gJ9ZDOBHm2Dk2zy0SXtd5IrAlmwXLgnWlr6Wu5qU/welz3Tglvk6J9r9qtOoF+e3TEbCVkhJWvGpZR6iD+/fdXxgFzvfZ33vue4XJuqFECAvrlPN5R2tbmasMl9dV2NZU04TX7eWh9+rnvdmulMD2P4GDOIsy/EpEzgHOJMf2b0TkfTj1cTcaY05tKqVSJZho7XEYu+PP2lnCyTAucdFQ0UB3tBuAcm85ld5KZwWc9CDJbJLLFl/GbVffRnNDM1uf3Up/vJ9kJknWyhIt9/GdNTHWHRO8aSCddg7c1AS33TblPwM1exlj9gL/IiK/N8Y8PIm71v53njjTuQbFRsuVnchoJRDHSy9orG7kkkWXDMudbetsY9v+bfjdfi5ceCFdkS66hrpYvWD1KZ/DyLa9GH6RVTWrSmqbml1KqWP7FeArRZsOici1p3m8fwc+i7OS2Wdx6jN+YLQHisiHgA8BLFy4kO3bt5/mIWePoaEhPc9JtP/wfgC2p0Y/1s79O1noW1gIXAOJAMYYepI9vH/F+9nSs4VIOkK9p57VNat58+I3s2X/FqLJKMYYyt3lZCIZnnn2GZ559hk+8+JnMLbBK148loes38tLFy/gK0M9fPJXWYzPR+T882n/0IcYjMVgDv2u9bU7ZZ4VkW8CS40xbxORC4ErjTHfPI19ldT/zse+t9hceS17Y15eCb9CJOGMQ3XZXQxlhqjyVJ10fuOd857IHrYe3EqZu4wyVxkvhl/kb/b/DcsDy1nsX8z21PZhfW3++0uqLmFr91b6U/14xcu+1D6imSjrV6wfdqz84wH6Qn3sz+5ne2o7eyJ7+Pzez3MscQwRIRFN4BIX2XSWl4+/zH7P/lH79on6fYCLsxfzm8Rv2Hd4H2WuMqLZ6Khtm2vmymt7ImMGtiLy58aY746Tz/Vvp3owY8yxov1/A3hgnMd+Hfg6wOrVq8369etP9XCzzvbt29HznDzPPPUMAOuvGv1Ya6Nr6Y31UumqBGDp4qWEEiHOCZ7DR278CLGnYsMe/5GrPsJLD7/ED57/AW7LTWNlI75qH/dH7qfcU47ltgi6giSzScq95Zi0IbykjCfffxGunzuXt2pzX3ONvnanzH8BW4H/k7u9D7gbOOXAttT+dz72vcXmyms5eF6QTds34REPfrefYHWQdDLNp9Z/6qRUhPHO+Z4H76Gpvom+eB8JEqyqWUUoEaIz0slVK69i/VXrh/W1+e8/ctVHeHXnqwspYReec+GoC+XkHw9w+OBhVq5YSbAxyP3b7ychCcp95QylhziaPsoC/wKSJBlMD7IrtYv3n/f+Mfc3Vr8PsJ718BN43vU87aF2LqwevW1zzVx5bU9kvBHbstz/k1ZuRkTqjTHduZt/BDw/3uOVmkqjla2ZqNj3zq6duC03qWyKvkQfa/xrAHi682lq/DX0xfuclAVfJdFMlIH4ANeuON0LHEpRZ4z5oYj8bwBjTEZEsqezI+1/55dS5xpMZKyUhv54f+F2R6iDHd07Cnmw+aVxS0kJAwqL3rzc/zL98X5+c/g3VPmqcFkuhtJDTo1bY9M52IklFl6Xl1gqdtoL7wBcUHkBH1n/kVN+njr7jRnYGmP+M/f/HaezYxH5AbAeqBORTuB2YL2IXIZzKewg8OHT2bdSk2G0jv/6ldfTuruVzzz+GcKJMGuXrqWx6sSM3/54P27LTTwdJ5VJAU4nD7C0cimD6UG8lhcMJLIJ/B6/loxRZyIqIgtw+kxE5LVAeKInaf+roPTAcjxj5crWBpxrT22dbTxy4BECrgAXLbyIrkgXjxx4hLbOtpICzo5wRyGP1u/2E01HefzQ41y9/GqqfdX0xfoQEYztTNo1GHyWj4AnUKiyMNdHWtWpmTDHVkQ+D/wjEAceAdYAtxpjvjve84wxfzrK5tPJC1NqyhR3/K9vfP2wKgldg11s27+N61ZeVwhuawO1hJO5uCKVgiefIBLtZ115gCFvlNULVtMV6WIgMYCIcMc1d2inq87E3wM/AVaKyJPAQuDdEz1J+181Wca6srV26VrAmYQbcAWIZqK0h9qd0l2UXn1hZ9fOQkAbS8dYVrGMKn8Vzx9/noVlC6nyVRHNRImn43gsD26XGxGn5OLpToZTc1spVRHeaoy5TUT+COgE3gM8Bowb2Co124yskhBwOx30Y+2PUeGr4NH2RxlMDhJPx8lmUphonFDKTbjMxeauc2HfEK1vr8Zb4+Xa6mu5OHsxt1xxywyflZrNjDHPisg1wGpAgL3GmPQMN0vNI2OlNPy649eAk6rgd/sZSAwQTUUB8Lv9JQec/fF+Kn2VDMQHCrXCL1p4EU91PkW5txyf24dlWbjFzcLgQnriPYXnaiUDNZqS6tjm/r8B+IExpj//aUmp2aq4fE0+5WC0XLJ0Ns3B8EFeVfsqp9zMYBepdJxMMkmPC9rMEf7ywEKaa1ZCIkTzzjpnFTGYF7NP1bRoBlbg9NdXiAjGmG/PbJPUfDJaSkM+sG2qbqIr0jXs8f3xfobSQ9zwvRsK/etYagO1RNPRYdv8bj/XNF5D15BT3ivoCfL65a9n1/FdZO0slljE0/EJ50So+amUlcd+KiIvAWuBR0VkIZCY2mYpNXVGrsgTTUfZtn8bQXfwpKV4j0WPOZfZ0s5ltr6BI8QzSdIu8GVgQdTwYNVx/jvWBpWV0K6XxdTkEZHvAP8KvA5Yl/saO0pQapq1rGkhno2TzqYxxtAX6+PI0BGWlC0Z1r+OteLZ2qVrSWQSpG3nQkQ84wSst119GzddcBOvWfYaLll0Cc0NzVx/7vW4LBcZO0PQGzxp4lhbZxv37bmPu569a9KWEFazz4SBrTHmk8CVwNrcJbAY8AdT3TClpkpxysGuo7s4OniUrsEufnf0dxwKHSosxRvPxImn4ywpX0Iqk+JA/wGOJHox4sy+SVvQUQ1pgf+WPRCJOIsvKDV51gJXG2P+lzHmb3NfH53pRimVlw84DYa9fXs5FD6ES1xEUhEn59YdwO/2F5bSHamxqpHrVl6H1+Ulbacp85SNWemgsbqR+vJ6GqsauemCm04Kajdt30QsFaPKVzWpSwir2aWUyWM7gW8BPwAGjDFRIDr+s5Q6e+VTDl44/gKdg524xIXf5SeWjiEiZI2z8lhtoJaVNSuxLItEfIhQKuRMTTdOsmPGAslCfwC8JgXHw7BRL4upSfU8sATonuiBSp2p0VYYa25oLoyEDsQHODBw4ORKLwJZk+Wc6nM4GDqIhcW+vn0sr1zu5Mm6fOPm3DZWOauO7R/Yz7sueNdpTbjND1iEE87k3mp/dWG7TuCdX0rJsf0T4BZgRy7I3Qr8zBhjprRlSk2RfPma3ngvLnGRMRlS2RSNVY00VjVyOHL4xPrl4Q62Pf9jhuIhjGUjOKO1viy4bUh4AIFlURds3gzN2oGqSVUHvCgibUAyv9EY886Za5Kai/IjnvmqMPkRz5svvJm7X7z7pJHQ1QtWF6rF5Ot7R9NRDAYRwSUuemI9lHvLSWaTpzTJKx9g/7L9l8QzcRoqGiZ8Tn7AosxbVtimVRPmp1KW1H0F+D8i8g/A23FGb20R+RbwZWNM/7g7UGqaFXeKtYFaXt/4+mGf2FvWtPDRhz/qFBg3YGPjEherFqwqzM4tlgmHiLltAMSAyzhBrdiQcENFCj60v2paz1HNG5+Z6Qao+WFkVZgKbwWv9L3CRx/5KIvLF5PIJAh4AoVFaXZ27SwEtvn63qlMCr/LTzKbxMIikU4Qz8RJZBIl1/PuCHcUAuz8COy+/n10hDporG4c83n5AYuVNSsL27RqwvxUyogtInIpzqjtDcB9wPdwJjP8Erhsqhqn1KkqHnWo9FUSTUf52CMfY1nFMmKZGE3VTdT6azkYPkjGzgBQXOUjkoxQE6gBnA72xy/9mH6GcNlOUGtbzv8GSLmcAPcTbW7e0uGBTZt01FZNKmPM4yJyDvAqY8wvRCQIuGa6XWruKa4KM5QaYm9yLx7xkLbT2MamL9ZXWIxm5Mpj+freHstZvndhcCFHo0cxYijzlHHNOdeUnA6ws2snDZUNToCd6MPj8kAWdnTvGDewzdfbzbcvkoxo1YR5qpQc22eAEE5x708aY/KXw34rIldPYduUOmXFow79if5CbldPrIdrV1xL25E2nj36LC5xYWFhYzs5syI8d+w5zltwHssrlnPfnvvY07OHeCaOz4DHhqwF3oyTW2sEFsfhjp1l3LLHB0tqoaoKWls1sFWTRkT+CvgQUAusBJYB/wG8aSbbpeae4hXGemI9lHnKGEoP4bbcCIIlFrF0DBi+8hg4lQ1e7n8ZALe4cVtu6oJ1wxa3KVV/vJ8LF15IR7ijsLqj23KfdCVtpHy93eIc4dNZQljNfqWM2L7HGHNgtDuMMe+a5PYodUbyow4v9rzI0aGjpDIpfC4f8XScXUd3sad3D8Y4SzPaOOkFCGRMhrSd5uYLb+ZzT30OO2sTS8dI2SnSbqe0V2XSCW7jAnUxuOfHbppjZUAGVq3Scl9qKmzAqWP7WwBjzMsismhmm6TmouIVxhLpBEFPkGQmyeLgYlJ2CmMMGZMprDzWUNnAj/b8iEfbHyWcCFPtq6Y72k0ykyRlp7jmnGtOOagFZ/R3ZNnFjJ0pXEnL16+969m7ChPZ8sFrc0OzBrJq7MBWRP6+6PuT7jfG/NsUtUmp09ZU3cTevr0cjhwurGJjY5POpNk/sB/b2FhikTVZLCxEBEFwWS7evurt7OzeydJDA/TEe/FVGNxWrrSXG8pSLlxpWIBwXTs0H/NAU50T1C5aBKGQlvtSky1pjEnl+2ARceO8JJWaVMUrjIk4I7QNFQ1U+CpYUr6Enx34GcYY6oJ1XL/yev7lqX/B7/ZTF6zj+Z7nGUwO4nP5qPHVsKRsCbuP7WZJ+ZJTDm7XLl3L3r69hbKLGTtDxmRYV7+Oh/c9zKHwIQyGRCZB25E29g/sH7M8mJqfxqtjWzHBl1JnnZY1Lezr2wdQGJW1jY3P5SOaiuJ1eQvBbF7WZBGEljUtJJ76FRVHeqlMGCqdq2BUJcCdgYGAECvzUuepoCW+Gi69FC6+GOrqnKA2HIaW0iZIKFWix0XkU0BARN4C3AP8dIbbpOao/Apj71vzPs6rPQ+35cYYg9flpcxTxquXvJotN25hZ/dO/G4/fbE+njj8BMlMEhEhlU3RF++jI9JB12AXd79w97CVHEvRWNXI5vWbCXqDJLIJvG4vq2pX8ULPC/zy0C8xuc916Wya544/R1+sb8wauWp+GnPE1hhzx3Q2RKnJ0NzQTENFA/sz+xlKDQHOZawsWWxsfG4nwPVYHlJ2qjD2lS8Rs/7xDr56gWFlP3iyMBCAiA/8WUi4Da8bqOA26/U0f/Y254mtrU76QVOTU8NW82vV5Pok8JfAc8CHgYeAu2a0RWrOa6xq5L2XvJdbt93KQHygsIztvv59bHhwA7/r/h0+l49QMoTX8hYm4ubTu2LpGBXeCmKpGNv2b+O6lded0vHzAfb2g9sBCCVC/Lrj14WgNn8st7h5pf8VFpYtnJwTV3NCKZPHGoCvAlfjhAFPAB8zxnROcduUOslYBcSLXV5/OZ2RTmxjIyL4XD4SmYRzG2FJ+RJ6Yj0AWFhU+6vxurx87JGP8cFYhAt6IOyHc0KwdNAp79VT4eK893yYLTduGd4gDWTVFDLG2CLSipNja4C9WkNcTYd8cNkR7mBv314ssfC5fPTGeukc7MTn8pHJZgi4AogItp0riYiQsTMksgnKvGX43X52du087XaEEiF2HdvlDETkWGLhEhfZbJaYHdOSXmqYCZfUxVmQ4SfAUpwZuT/NbVNqWuVLefXGeocVEB+5ZOLa+rV0DXU5NwzOxAcM9RX1vG7561hetRwRwWN5qPBVFL7vifbw6EqLd78IYZ8T3GYsZ8Q26ZGS6zAqNVlE5EZgP/AV4GvAKyLytpltlZpNOsId/GjPj7jhezew4cENp7zE7M6unVT5qkhlU0TTUar91axasIqeWA+WWIVBg/xoqsEUgtuFwYX4XL5hpcHGat9vj/yWo0NHh6UuHA4fZmf3TqKp4YudWmI5xzAZPC6P9s1qmFKqIiw0xhQHsv8lIrdOUXuUGtPIAuL5Qtz5/Kr8SG5HuAO3uEmZVGHxBZ/bRzqbJpaJcdMFN/FK/yuksikydoZ4Ok40FcVluXhxEVxxDD7xFNx9sXCw2tAYgr871qiTE9RMuBO4NrdQDiKyEngQeHhGW6VmhbbONrbt34bf7efChReyt28v777n3TRUNHB5/eWjXvEaKV9+Kz8ZF5xJuq/0v8JgcpBQIgSCM4JqnMe4LBfVvmrKveXEM/FhpcHGal/AHWAgMcC2/dto62yj7Ugbz/c8XwiaBSkEz1k7SxZnbsTfvebvtG9Ww5QS2PaKyJ8DP8jd/lOgb+qapNToRhYQ7x7sJpKMkLbTPNP1DOdUn8OyimX8rvt3hQ5QELJ2FiOGTDJTuGQV9ASJJCMks4VVSnHZLg5WGR5bU8VrXo7zj9uzRH0W8YXVrHnD9TNyzmreO54PanMOAMdnqjHq7FFKWlbr7lb8bj/RdJTdx3bTPdQNBkLJ0LAlc+9/+X4+f+TzNFU34bbcwyoZjFZ+K5KMsKxiGUc4Qq2/lsODh0nbadzixjY2LsuFx/I4pcOyCa4555pRz6G4fdF0FJe48Lv9fOLnn+CpzqcKE3vzk31d4sIYg8EQ9AT5u9f8HZ9902cn+SerZrtSAtsP4FwC+2Lu9pO5bUpNq3wB8aHUEIcjh1kQWIDH5SGSjHAwfJCsyVLlr6I2UEsoERoW3GZMBmMMa+vX0p/oxy3uYUEtOFUUYj7hv1bHWWWWccgHnqEYa/xNWu1ATSsRydcIf0FEHgJ+iJNj+x5gx4w1TJ0VildYLE7LGln2qj3Ujs/lYyA+wCt9r5A1WRLZBD2xHlbXriZjZ7j98dtZ6VvJeRXnsbd3Lzu7d1Ltr+bAwAHclrtQfitrnAlk+Tq2a5eu5eXnX+bc6nPpjfciGcHv9pPOpgvHCXqDXLN07Hq2xe3Ljwins2mePvI0tnFydg0GCwuP5cHGmTfxqgWv4lvv/JaO1KpRTRjYGmM6gHdOQ1uUGle+gHj3UDeWWAylh8jYGfxuP0FPkMORw7gtN6sWrOKV/hODXBmTwSUugp4gH33ko8TSsROLMxTxuX1YYrFzueF4e5amENRd9DqqN9ymk8TUdHtH0ffHgPyQVw9QM/3NUWeT8dKyioO9puomuga7SGaSDKYGCbgDzscjgZ3dO8nYGcLJMOFYmBeGXijUrI+n48OC3LX1awsLNNQF69h45UZ+3fFrgp4giUxiWNssy6IuUMcliy5h/Yr1455Hvn3FjkWPYYmF2+XGZE0hsDUYLLFYVLZIg1o1rlKqIpwLfBl4Lc6fxG+AvxtrNTKlpkq+gPh1372ukHNVX1aPwTiXvHId7KKyRbgtN2k7DUDAE6DCU+GsXT5ObfuMncEtbqoqFvH2XxyalnNSajTGmFtmug3q7FWclpVX6aukPTR85cOWNS082v4og6lBLMsiZafImiyV3kqMMRyPHqfMW4ZlLCKpiDMpS4REJsHevr2Ak3aw6+guYukYQU+wkPLw645fs7xyOcdjxwu5tVmTxTY2yyuXl3Qe+fal7TQGZ0XIVDrForJFhJNhjDG4xEU6myZtpwl6gtxxzR0a1KpxlVIV4fs4l8HqcSoj3MOJfFulplVzQzMXLryQFdUraKpuosJXwaoFq4hlYrgtN5FEhEfbHyWVTTmZWSLU+msJJUPDFmUYTdbOIiKsW7pums5GKaVOXVN106h5ryPLXjU3NHPdyuuwjY3H8mCMM+o5lBriyNARbGzi6TjxTLwQRCYzSbImi8flIW2nnQCT3H3Z5LBKNNX+aq4/93rclpNb67bc1AXrqPZXl3Qe+fYZYxhMDjKUGiJlO9UX3JabBYEFeN1eLMsi6Any1eu/yi1X6Gc+Nb5SAlsxxnzHGJPJfX0XXdJRzaC1S9eSyCQKSy56XV6aqpuo8lZxKHIIDDRWNhZGABLpBKlsatT0g2IGw8qaldx29W3TdCZKKXXqWta0EE6GC31gPu91tLJXjVWNLC5fzHk159FQ2UDGzhSuZllYZEyGpEkWJmXlL/17XV5nRTGERDZX0ssYqnxVw1b6aqxuZEn5Eqr91SwpX0LQEzzl8xlKDWGTKxlmIBQPkcwk8Vge/C4/i8oWaVCrSjZmYCsitSJSCzwmIp8UkRUico6I3IZTbkapGdFY1ch1K68j6A0SToapC9bx5eu/zOIKp/NeUbMCy+V0zIIQSTuX2CaytHwp33znN/Uyl1LqrJZPywp6g3QPdfNCzwtEkhFad7eOWqd2eeVy4tk44WS4sLiBILgtNx7LA1AYCPBaXrwuL9FUFIPB4/KQyWYKOa6jpTyciQdffpBo+kSdWhHBsiyyJovB8K4L3sW977lXg1pVsvFybJ+hkGYOOMs55hlAa2yoM1JKuZqxNFY1Fmbavr7x9bTubuX3x35P0BMka7KkMk4qgiUWFd4KEulEYZRiNBcuuJCtf7hVg1p1VhGRKuAzwOtzmx4HNhtjwjPWKHVWaG5oZl39OvrifVy08CIqfZVjVkeo9ldzxZIr+Pbvv40xBhHB6/I63+f+BTwBLqy7kEORQyTSCUQEF05+a3+i36lIgIya8nC6tj67lQMDB4bNfciarBNsG7ho0UUnr/ao1ATGHMYyxjQZY87N/T/y69zpbKSae0pdRWwiHeGOwn7KPGWkMikORw6Typ5YftElLuKZ+Jj7qPRWalCrzlbfAiLAH+e+IujKjypnR/cOAq4AffE+2kPtVPurT0oVyGusbuTChRfid/vxuXx4LA9l3rJCJYSgJ8iHX/1h5z6Xh5XVK0GcMogWJ1b6OhQ6NCkrfbV1tnH747efNKFXjBQmk+lSuep0lFIVwQXcCKwofrwx5t+mrllqriu1XM1EdnbtpKGygb54Hx6Xp1Cbdig15GSLGUM8E8dlOeuK5zvRfKFvgC9d9yUNatXZaqUx5qai23eIyK6ZaoyafuNd2RqID1Dlqxq25Ox4qQJrl67lhZ4XiKfjuC3n7dxjeXDj5prGa7j7xbtJZVME3AEODx5GRJyqCWKRSWawxKKhsqFQFeFMtO5uJZ1N47W8pGxnIEIQbGxs26Y2UKtL5arTUsrksZ8C7wcWABVFX0qdtvZQO5W+SqKpaKFTTmQSPLDvgVNa07w/3l/Yj0tcNFQ04HP5iKVjJLNJbGzCyTDJrDMJwi1uZzUykwWBlktbNHdLnc3iIvK6/A0RuRoY+/KDmlMmurJVE6g5qY7seKkCjVWNXLLoEmoCNc5kLeOMijYFmzg8eJgqXxWprFOVIJVN4cJFKpui2leN1+0l6AkSy8Qm5dzaQ+3U+Gso85Y5wbW4C5PX/G4///zGf9YBB3VaSll5rMEYc+mUt0TNK/lVxPKODx3nt0d+S7mnfNyVdPLajrTx+KHH6Yv10TXYRV2gDoAKXwXHosdGrYBgY+N3+Qs5XF+5/isa1Kqz3UeA1lyurQD9OAMNah6Y6MrWuvp1PHLgEQD8bn+hOsLGKzeOuc9qf3WhpGF+AYX7nrmPgfgAFy28qLACWIW3gt5YL7Z9oi+1jT1p6QFN1U2ksikG04MEPAFiqRjxjDOSrBUQ1JkoJbB9WETeaoz52ZS3Rs0b+VXE4uk4fref53qeA6A2WEt7qJ2VNSvpi/fxgZ98gMaqxmGX4NqOtPHAvgfwuJwcsUQmwaHwIWfyhNVLX7xvzOP63D7ecu5bqAvWacepznrGmF3AGhGpzN2OjP8MNZdMtBBDY3Uj1597PTu6dzAQHyisClY8GNAR7uC548/x3LHnSGSd0oeVvsqTFlGoCdQMq427qnYVrwy8giAY41RMsI09aekB+feA1QtW0xXpwrZtKnwV3HHNHdo3qzNSSmD7NPA/ImIBaZxRA2OMqZzSlqk5LV+u5tZttzIQHyCdTfPaZa/lWPQYx4aOcWDgAJ3hTmxsjg8dZ1/fPp7peoavvO0rPH7ocTwuT2GCWH15PUcGjxBOhomlY+OuLhZNRycc0VBqponInxtjvisifz9iO6BzHOaLkVe24ORUg8bqRhqrnQoxG68a3q+1dbaxbf82hlJDpO20U5M2k8AlLvb27aUj3FGoLrOufh17+/eSNVkssfC6vQTcAacWeNZ5Tl2wbtLSA/LvAa27W/G6vFxbfe0pVcZRaiylBLZ3AlcCz5n8bBulJkFzQzM3XeDMizkwcIDeWC9DqSEORw6TttOFZRr74n2Ek2G6Brv4xM8/wWBqkDJ3GfG0k2ro9/gp85QRSoZI2slxj1nmKRszvUGps0hZ7n+dzzCPjbyyVUqqQbHW3a343X6GUkN4XB4ssTAYEtkEFd4KdnbtLAS2jdWNvPfS93L9964nlU1RF6zjkkWXFFIg2o60ndbiC+NpbmjWvlhNulIC25eB5zWoVVNpbf1abn/8do4OHkVECjVni0dfLbF4+sjTBD3BwizavMHU4ITHcOHizrfcqR2pOusZY/4zV5EmYoz54ky3R82MkVe2xko12Nm1k/54PwcGDgwb9WwPteNz+cjYGbJ2tjA5CwNuv5v+eP9Jx1tSvgSALTdu4R3ff8e4qV1KnY1KCWy7ge0i8jBQGA7TS2FqsnSEO/j5gZ+zqnYVx4aOnVhaEaf8i8GQMRl84sOIIeAOcDR6lKzJIgjHQkcKEx5yTzqJCxf/+3X/W3O31KxhjMmKyDsBDWznsIkWqim+sjUy1aAj3MG2/dvwu/2jLtDQVN3Ey30vYxvbWdFLLGzbJkuWWDp2Up7tZOsIdRTyf0cG3UpNlVLKfbUDjwJetNyXOkNtnW186eUvFUp65UcbqnxVhJMnFlOyRnlpZuwMVb4qBhID1JfXY+FcVgsnBxmWVmsPj22bqpp46i+f4rNv0sXy1KzzlIh8TUReLyJX5L9mulFqcpzpQjU7u3bid/uJpqP0J/pPWqChZU0LPbEep680pjAA4BIX0VSUtUvXTtm5DcQHeOTAI8RSMap8Vae9CI9Sp2rCEVtjzB0AIlLh3DRDU94qNSflO/FkOsl5FefRG+tl97HdJNIJ6oJ1vNz/cmF5R0ssbHNi5NYYg8/lw7IsAp4Afo8fv9uPlUqRkizp4qQFATGACIvKFvHf7/5vHSVQs9VVuf83F20zwBtnoC1qkp3pQjX5Ot4D8YHCtuKqCc0NzVT7q4mn44UFaQRnOV2P5Snk106mWDrGzq6dhYC6wlfB0oqlVPurT+nclDpdpaw8djHwHaA2d7sXeJ8x5oUpbpuaY/Kd+CvpVwolvfITIl7oeQGXuEDAI55hS+ICzsQHy2IoNcSyimUcHTpKPBPHiMEyYAy4ndQxbAEbCHi0yLea3Ywx1850G9TUmaic10RqA7VE09Fh20ZWTVhWsYyeaA8YsG0by7Lwu/2UectG7u6MxdPxE+lkxiCWMJQaoiPcwXm151EXrCv53JQ6XaXk2H4d+HtjzGMAIrIe+AYnRhKUKkm+E09kE4XVxnwuH363n3AijDHOErhGDJZYVHoqiaVjIBB0B6nx1WAw9MR66E+cmPRgA1jgToEfIWEZsCy2vG2L5tSqWU9EbgQuAvz5bcaYzWM/Q80WpZTzauts40d7fkR/vJ/fHP4NALFMjKbqJhoqG9h9bDdpO43H8oxaNaGhsoGnjzyNhYWIYNvOaozLKp2AekfXDvZE9nDfnvt4fePrT/tc0naazsFOMnYGODE/wu92Xrb7+vbhdXknbYEHpcZSSo5tWT6oBTDGbOdEKRqlStZU3TSsADhAMptkWcUyrjnnGsRy1gl3WS68Li8uy4VlWbgtN+fXnc+1TddS5ikjPtDD0jCs7oEVIaiLAQayLqhIWyyLWtw4uESDWjXrich/ADcDf4uTOv4e4JwZbZSaNC1rWggnw4VUgXxgml8EIZ++FU1HscTiicNP8MThJ/Ba3kIq15rFa/C6vMQzceqCdYWJY22dbWx4cAM/2/8zBME2tlOj1rKo9FVybOgY2/ZvI5aK4bE8xFKxQmmxUzUQHyCUCBWCWnAq2qTtNFk7S8bO0B/vH3ZuSk2VUgLbAyLyDyKyIvf1aZwJZUqdknwnnrSThU48kUmwdulabrv6NuqCdQTcAWr9tfjcPtLZNF6XF3CW3P3hCz9k79HnSbig3w9hH5Qn4erDsDAKWYEr+4OcZ9VxW6e+96s54SpjzPuAgdx8hyuBqZ3KrqZNvpxX0BsknAwPC0zhRPpWNB2lc7CToCeIMYZnup+h2l+N3+2nM9LJJYsu4TXLXsOWG7cUgtr8pDSDKSzs4RY3QXeQoCdIKBFyJp5loiTtJAFP4KRJvKVo62zjaPToqAvjWFikbWcGxILgAq0hrqZFKakIHwDuAH6Uu/0rQIfC1CnLd+IfuOcDhU78upXXFSYw+Cwf0XSUWNoZQXBbbmxjk86kORQ+5EwcSxnibki7wU5Cbxk0ROC8fugvE+pql7PxeD3Ni1bP8NkqNSnyw2cxEVkK9AF6LXcOGa+cVz59K5VJkcqk8Lq8DDHEUGqI40PH6R7sZig9xMLgwmGlu4onpRXLL3qTH1n1uXwMxAewjQ04+b0j5zeMJ5QI8Wj3o2Peb2Pjxs2liy7lK2/7iga1alqMG9jmCoTfY4x58zS1R81xzQ3NvKHuDXjqPGTsDD/b/zM8lod7XriHeCaOIHgsD16Xl0pvJUdjR8mSxS1usnaWuOdEKa+YF6oS8OJCJyXh9clFbOm4GMJh2KCXu9Sc8ICIVANfAJ7FmR9514y2SE2b4hxct8tNKpsq1O/e2b2TZDZJuaecVDbFS30vsfXZrezs3skPX/whC4MLsbAIuAOFOQ3GGLLGSQ2o9leTzA5fqTGSjBSukpXixZ4XiWfGT11YVrFMg1o1rcYNbHMFwmMiUmWMObXrE0rljCxAvieyh+5wN2sWr6HSV8n+/v24XW6GUkOFlXFsbNImTcAdYDA1WNjmKbralXZBxgW2gduegoVrzoVFdbBxIzRrJ6pmP2NMvvjyfSLyAODXvnjuGtlXrq1fy90v3k3aTlPmLiOWjpHKpPC4PACksikqfZUIQjqb5vbHb+fKhitZGFjIYHKQwdQgfpefgCdQqJ7gttysXuBc0eqJ9ZDOpjHGEE/HCSfDVPmqSmprR7iDgcTAmPdbYlEXqNNyi2ralZKKkACeE5GfA4W6IsaYj05Zq9Sckc/1qvJVFQqQP93/NF6PM/khv9Rjpd9ZNQdDoTpCMpMs1F7MX0LLWhBMg2WBJwtru2Bx3OK1r7qGBff8ciZPVakpISJXASvI9dcigjHm2zPaKHXGioPYcCJMQ2UDPz/w82F95d0v3s3NF97MS70vEbNjvGH5G9jXv48DAwdYUraEjJ0hnU0zlB4ilorhS/toD7VT7itnMO0sXBNNRxER3OKmzFvGkvIlhZqyV9Rfwf177ydLlqA3yOb1m3n//e+fsO1bn93Kt3d/e9S82rwqbxWfe9PnNKhV066UwPbB3JdSp+zzT36eV/pfKUxUWFm9kpSdwqQNPr/PubRmZ0mkE8OeZ4zBNvZJNRozAinLSUewDGTKA3y471wWfPZz03hWSk0PEfkOsBLYBeTXjTaABraz2MgP/F2DXWzbv4219WtPWqxhZ/dOLll0CQD33nwvdz51J/ftuY/llcv51aFf0Rfrw879y9gZXjz+Ik01zmjvk4efJJwIU+Ytw+1147E8w9rRWNXo7DsFN11wU0lBaFtnG7c/fvu4QW3AFeCRP39Eg1o1I0pZeax1OhqiZrfR1jsHeLzjcSq8FVhYxNNxnjn6jHPZzKSJpWPOjFljOB47joVFliwZkyGdya0lZhi+XK7lpB/4slCbdrE5cAPNn71NUw/UXLUWuNDkL12oOWHkimMBdwDb2HQNdRVSAY4PHWdv/156Yj2UecpoqGgoPH9d/Tr29u9lID5A1mQLQaZLXCTtJEciR7hq+VUsLV9K0ONUQeiL9Y3alryOcEdhmXOvyzvm0retu1sLFWv8br9zZQ1TWDWywlfBF9/6RQ1q1YwpZeWxq4HP4NROdOMMlhljzLlT2zQ1W4yWbrBp+ybKPeVUeasYTA2SzCbxu/0nJhoYZ5UaEcElrkLKQT6YLQS1kHvFOcvkWggen59yXyWXX/o6mm++d0bOWalp8jywBOie6YaoyTPaimMBd4CB+ABVvioGk4N0RjoBWBhYWFid8d13v5sXel6gNlDLBy//IL848IvC8y0sXJaLbDbLYGqQR9sfpXuom0qvk4M7nqSdZNv+baxZvAa35SZjZ5z6uanoSY9tD7VT46+hL95HbaAW27bpi/eRsTNU+au48y13ag1xNaNKSUX4JvB3wDOcuBSmVMFY650/fuhxAu4A/XFnlTBLLNziJkkSj+UhYzLYxkZEaKhsIJlNcix6DACTNRT3xZbtFF3O2gaPy8OKqhXcdvVt032qSk23OuBFEWkDClPYjTHvnLkmqTM12opjlf5Kkpkk8XScnlgPXpeXWCZGfUU9A4kBYpkYu47tYkFgAcejx7n98duxjY2VK0cvIiwMLqQz0knGZMBAU1UT/Yl+jseO43P5TkpFyBvKDLHYvZi+eF9hNLbKV8VLvS8R9AR5qfclemI9HI8d58DAAerL6/G6vXgtL16vF7flRkS49z336kitmnGlBLZhY8zDU94SNSu1dbbxwL4HnHqzdpq6QB0ra1aSyCToj/c7pWMEsnaWSDLCguACZxYuBp/LR8pO4RY3ly2+jKc6n3LqKRoYOcBgW+DLOHm1b2l6C7ddfZt2oGo++MxMN0BNvpY1LYVVvvxuP4lsApe4uOOaO/jG775BNB1lQWABXpeXjnBHYWJtT7SHRCbBUGrISfESC9vYGAyWsbDEQhCqfFWsqFnBofAhPJYHl7iIZ+J4vE5gG0qEOBw5zCv9rxDPxEnZKXwuH9FUdFhN21g6VlgNLS+TzXAwfJAVVSucOriJATwuD3dcc4f2yeqsMObKYyJyhYhcATwmIl8QkSvz23Lb1TyXT0HwWB48lod01lkr/PjQcXZ27cTCIpVNYYwprFMuCK+tfS0et8dZ3lGsQk5ZT6yHMecjiHNX81GLe2/WUQE1PxhjHgcOAp7c9ztw6tmqWWzkimNlnjKuW3kdt1xxC+uWrqPcW86x6DE6I52F9C2DKQwYuMRVGATIj8La2AiCy3KxrHwZ0VSUVMZZbMElLmzbCVjj6Tgv9b1UKBWWr42bv7KWF0lGyGazJ61EJpbgwkX3UDcralbwrgvexb3vuVfTD9RZY7wR2ztH3F5b9L0B3jj5zVGzST4FoTZYy/6B/YDTgbZ1tXEseqyQ72XjdKiWscjYGWq9tZR7y4dNZnjs4GOMNz9GbLioFzZFLpvSc1LqbCIifwV8CKjFqY6wDPgP4E0z2S515pobmlm3dB07u3bSH+9nZ9dOtj67lW37t1HhraB7qBtjDEPJocLkLJ/LRywTo9xT7ozyulxU+6rpi/dhG5vrzruOXx36FS5xDTtW1mSxLGccK5wM43f7SWVT9Cf6CwMTvbFeyjxlhcc/f+x5QsnQSe02timMFD/03oem/Oek1KkaM7A1xlwLICLnGmMOFN8nIjpxTBUmQLjExdLypRyPHSeacJbEdVtuZ8SWEyMGAAOJAR7ofgC3y025t5yh1BA98Z7C5a+T5GLdxiHhCy83ce3n/n06Tk2ps8UGoBn4LYAx5mURWTSzTVKTYeuzW2nd3YptbALuABk7w+2P347P7QNx+kyXy0U240xtcYkLt+W8Zadsp1/NVyZwW24ssdhy4xY+9tDHeOTAI4BTNjFjMmRNloA74Dw3m6LCW0E8HR82olvlryLoDRZSG7qj3YVBiWIGZ5/Vvuqp/hEpdVrGTEUoMtq083smuyFq9mmqbiKSjABQ7i3n3Opz8Xv9LKtYRsATIJ49sdRi1mQLqQf5jnEoNYRf3EjWMEr/WbA4bvHD7Lu49nM/0LJear5JGmNS+Rsi4mbshB01g9o629jw4AZu+N4NbHhww5jlsvKPvf3x2wu3Y5kYPbEeoskokUSEVCZFwBMg6A4S8ARwWS4WBBcglmCJ87a9KLgIl7hIZ9Nkss5E3Bu+dwM7undw2aLLCHqDJLIJvC4vi4KLCikLXpeXtJ0e1h7b2CytWMpNF9xUWLxhtIoIQCHY3bB2w2n/rJSaSuPl2J4vIjcBVSLyrqKv9wP+aWuhOmu1rGkhnAwTT8cLSzLGM3GWVSwjnUmf9Pj87N2syTolvWybaDpOVoa/TxffDNjCP7/mUzR/+V4NatV89LiIfAoIiMhbcAYVfjrDbVIj5Ocb9MZ6h5U8nKgWrDGGVDYFJpcHKzaDyUH64/1EU1GGUkOks+nCHIW6YB3NS5tpubSFurI6MnbGya0VwWBYVrGMWCrGruO7WFe/jtcsew2XLLqEgCdQOHaVr4q0nS6s5pi2ncm86+rX8fC+h+mJ9TCUGiqMCgtS6Lvzt99/6fv57Js+i1Jno/FybFcDbweqgXcUbR8E/moK26TOcluf3cqdT9/JsegxKr2VACSzSWoCNaysXsmRwSP4PD4SmQTZogpxLsuFJRbpbLowgjuy+oFlg52rW+sysOXFFdzyjneg1Dz1SeAvgeeADwMPAXfNaIvUScYqedi6u3XUia75WrDhZLgwt8BlucikM6TsFB48VHgrAAqpXV6Xl+vPvZ4DoQM0VjfSWN1IKBEilo5hWRbGGNpD7YUgdkf3DhYEFpx07IAnQENlAy/0vEA8EyfoCVLtqeaF4y/w2KHHRl1RzGW5wHaC2m+84xs6UUyd1cbLsb0fuF9ErjTG/GYa26TOYluf3crHf/FxAu4AC/wLiKaj9Cf6eft5b6e5oZmOUAfff+H7GGNwW25s2y5MfMhvy5ApjBYU5IJZy4DHBkT4eGwNt7hXQWurjtaq+SoAfMsY8w0AEXHltsVmtFVqmNEWXKj0VdIeah/18U3VTaSyKdpD7WRNlkQ2QTzjLFizILCASDJCNB2lwluB3+0na7JcsugSGqsbORAaNuWFWDqGINjYhfQBv9vPQHxg1MAWoNpfzZLyJYUA/LnO53ii84lRg1qD02+7LTevWfoaDWrVWW/CHFsNalWxO5++k4A7QDQd5XjsOOW+cjyWh8c7Hi88psJT4VxCy13iKhB4a181X3kgy4Pfha89CGs7nWDWn3FSEGyB88Iu/n3/aj471AyVldA++puDUvPAoziBbF4A+MUYj1UzpHi+QV77QDsd4Y5Rc25b1rTgttz43D6yJuukFBinXFc0FcXtclMXrKOppomgJ+ikK4wh6AmeFJAmMglqAjUltT2UCHE8eZxkNjlqYAuwtHwpaxav4V/e8i8l7VOpmVTK5LHTIiLfEpHjIvJ80bZaEfm5iLyc+7+0vzx11jgWPUaZp4x0Nk066+TReiwPQ6khOkIdPHLgEc6tORevy1voJAVnwsMbj5ez4YHj1MahsxIWxOCz2+GKI86Arc+GhiF4/sFGbql4g3PASASammbkXJU6C/iNMUP5G7nvgxM9Sfvf6TVyvsH+/v3sOraLJeVLRs25zdexzQesllgE3IHCYg3JTGGROdK2sxLYWBoqGjDGFL7i6TjxbJx19esmbPdLvS/xm87fELfjw7a7LXehko3bcnPdedfx5eu/rPXD1awwZYEt8F/A9SO2fRJ41BjzKpyRiE9O4fHVFFhctphoevhs2bSdptxbzo7uHQRcAWcxBWMKs3cNhoA7wJ89k6bHm2ZBDJoGIOyHkA/evxsSLmfEdl2PF+JxsG0IhSAchpaWGThTpc4K0eIFcUTk1UB8nMfn/Rfa/06bkQsuHI0e5bIllwFOmkK1v5oqXxWtu1uHPSefniUIWZOlJlCDIM7VLmOIZ+Kk7XRhEZvR1ARqKPOUISKEk2GC3iDXn3s9jdWN47Y5lAixf2D/qPXDs/aJVLFPXvVJtty4RYNaNWtMuKSuiFThLOv4+tymx4HNxpjwmE8CjDG/EpEVIzb/AbA+930rsB34RMmtVTNu42s38vFffJxkxrls1T7g5IitXbKWlwdeZjA1yAs9LzhrlRdJZBMs6slwuBLOKXrlRHzQFAIjsFJquG1wJSyIw5Ejzkjtxo2aX6vms1uBe0SkK3e7Hrh5oidp/zv9mhuauemCmwB4tP1RllUs4/njhQHzQs5tW2cbn3/y8+zo2kEim0AQp6qBMQQ9QQLuAEPpIRLZBGWeMs5fcD598b6xDgvk6tnafj54xQdLbm9fvK9wNc02Ni5xFeY+GJyBiUsXXqrVD9SsM2FgC3wLeB7449ztvwC2Au86jeMtNsZ0AxhjuscrNC4iH8JZcYeFCxeyffv20zjc7DI0NHTWn2cTTbyt7m18//D3sbHx4aPSVclz3c8xkBogzcllvgAydoYD1fCqPlgx4OTUViShqwxeroPyjIsv/H4FK48Kz2zYwOAFFzhPjMXgLP+ZjGU2/D4ny3w51+k+T2PMDhE5H6dKjQAvGWNG/yObWEn973zse4ud6u94T2QP245tozveTU+yB4BoNspu2Y1XvATdQbrsLoYyQ9jG5v13v5+jyaP4Lb8zqRYnhSBrsoSHwmSyGfyWnyXuJYQjYTpjnWRNFnfKzf7sfvpCfezPOis9xqIx+uw+0qk0WTvL/v37h7WtL+QExLF4jHTaednETIwXYy8W0iAKi+MYcOHCxqbeX8+ywDJuWXbLnP39z5c+q9h8OedSAtuVxpibim7fISK7pqg9BcaYrwNfB1i9erVZv379VB9yxm3fvp3ZcJ73RO9hcf9i0naaNUvWcGzoGHv79o4Z1ObnI7TVwx+/AG4bUhZUJmHxENx9CXyl4wKuX34lfLqFBXNkhHa2/D4nw3w51+k6TxFZBxw2xhw1xqRz6Qg3AYdE5DPGmP6pOvZ87HuLncrvuK2zjfu3309VdRVLypfwYvuLAFyx5Ar29u+lN9VLY7CRYE2QdDJNuaecI8eO4DEeEtkEbstdWCzBxiboD+LxekjbaQ4nD+MSF0mTJGuyHE4exlPnYYFrAStXONUMgpEgC2oW4El4SKfTrFy5clj7Dh88DEBoIEQ85mSwDNlD9MdPfvm4LGfE1sLiyhVXctvVt83p9IP50mcVmy/nXEqObVxEXpe/ISJXU1qO12iOiUh9bj/1wPHT3I+aQe2hdqdsl8lwbOgYhyOHydiZ0R9clL61KAa/WwJJN3htGPTC7iXwIV7NLd9+DrZs0bQDpRz/Cc561CLyBuBzwLeBMLmg8zRo/zvJiuvXPtP9TGGS14HQAa5suBKv20vXUBd1wTo2r99MLBNz0rhsZ5JX1mSRomLe1513HX94/h8ylBoilokRTUdJ2SkydoZIKsIDex84o/bGM3H6En2jVj9I2Snclpv/ffX/5t6b753TQa2a20oZsf0I0JrLtRWgH3j/aR7vJ0ALTifdAtx/mvtRM6ipuold3bsA6In14LJcJ3eUNictvvDLlc5orWVALOHooiBr61/N6kTZtLRbqVnEVTQqezPwdWPMfcB9Z3DFTPvfSVZcv3YoNYTXcgLbodQQi8oW8aqaVxFOhtly4xbA6Tv39e0jnAifVF7LYDg2dIxllcuIp+POaK2dLNQBB+iIdFBfUX9abR1MDg5b5jwvnw7hEhf/fsO/a51aNetNGNgaY3YBa0SkMnc7Mv4zHCLyA5yJCnUi0gncjtOh/lBE/hLoAN5zes1WM6Wts41jQ8fojfcCkHY5pWjynSMwalALYAw8sxTODUFVsJq3rLiGRWkv1NdNW/uVmiVcIuI2xmSAN5HLec0pZdKv9r/ToKm6id6Y0xf63X7S2TS2sfG5fcDJ9WRb1rTwTNczHAwdHHXU9Fcdv6I2UIvBDJuAazDOMuRi6BzsHLUtWZPlR3t+RH+8n9pALWuXri3cdyRyZNSg1sLCbbkxxrCqbpUGtWpOGLODFJE/N8Z8V0T+fsR2AIwx/zbejo0xfzrGXW861Uaqs0N+PfQqXxVlnjJndRw7SiqbIuh2ioinx5nX0lHlLJNbE4c3nP8GJ6gNh53KB0qpYj8AHheRXpzUr18DiMh5OOkI49L+d/K1dbbRuruV9lA7TdVNtKxpoWVNC5u2byKejrPAv4COSAcZk6EuUEcoESKejXNN/TWFfTQ3NPPhV3+Ytp+2jXqMvngfVf4qRISsnT1pRNcYQ/dgN3c9exe1gVriaSdYTdtpUtkU0XSUSl8l0XSUbfu3sTC4kEOhQ0RSo49H2dik7TRucbPxtdoPq7lhvBzb/PXhijG+1DyTzyc7MHCAaDqKS1xUeCrAQNqkKfM4LxkBRhmMoK8MDlXBEruMRaEU1NXB5s2aV6vUCMaY/wtsxKlH+zpzotioBfztTLVrvsp/qO+N9Q5bcAEo1K+1sVlRvYJafy1Zk6UuWHdSPdm2zjbufvFu3DL6mJIgRBIRPJanMIhUzMYmZafoj/dzPHqcnlgPoUSIRCYBUFjiPL/Yw+7u3RwePDzuubksFzc33KyjtWrOGHPE1hjzn7l1ySPGmC9OY5vUWSqfT3Y4cti5LIZBRHC73KSyKULZEJCLaQ1OhJv/P2dVMkjg1i/ARz4y7e1XajYxxjw9yrZ9M9GW+a54klhfvI+VNSsL27fcuKVQvxZg+8HtnFtzLhk7w88O/IzaQC2vb3w9zQ3Nhf143d5C+a1ixhj64n24LBc+y0cimxg1ZSGajpLMJrFtm8ORw2RtZxJaKnNi6d1wIsxgZnDc83Jbbr5+49dpiujqjmruGLcqgjEmC7xzmtqiZlBbZxsbHtww6rrm+fs7wh08sO8BBuID2MbGYEhmk84ls6LVa8RAYbDBnPh67x4XT/zFYydq1Cql1CzQHmp3LvGnokRTzsqL+QUXRgolQmzbv43eWG8hLSC/nG5+PxXe0S962thOTVs7SzKbHFYxAcAlLmdBB6SwoEIsHTtpAu+xoWMcCh+a8Lw+edUndaRWzTmlVEV4SkS+BtwNFNZSNcY8O2WtUtOqOHc2f5ntow9/lIbKBmKZGEF3kL19ewklQgzEB5zlHnOTGeysU9y7uFMVAV8GUrllcusjcFmqmu/W/ZmTdjAPCkQrpeaO4klieZFkhKbqk0c6D0cOU+2v5sDAAfb170MQhlJDfP7Jzxf243V5h630VSyfS5v/Ps8lrmEVEvLPD3qCZOyMM8fBdhZqGEgMjDrSW+yWS2/RVcXUnFRKHdurgIuAzcCdua9/ncpGqelVfJmtPdROKpPiYPggu47uYlnFMp4+8jR7+/YSS8eo8Ffgtk58HjK5f8Xs3CCDN+sslVuXsvj0sdXQ0jKdp6WUUpOiZU0L4WSYeDqOMYZQIkQ4GaZlzcl9WiwdI5VJ8XL/y2SyGbyWF9vYPN7xOGvr1xJOhklnT05DEAS3uAv9qYgMG7H1WB4nNze3KWWnEBGWVy7HY3nwuryFVIa0ncYS66QR37xbLr2Fb/3RtybhJ6PU2WfCwNYYc+0oX2+cjsap6THyMtu+/n0EPUFCyRDtoXZCiRAey8NQaohUNkWNv2b8HYozWpu2IJCGTwxdRvMnvqKTxJRSs1JzQ3Nhklg4GS4suDDaIgZBT5DjseOFEdV8SkGVt4qd3Tu5+cKbGUwPnjRaKyKFbflR2+IJZOW+cip9lWCcoBagLlBHtb+68JiMyeASFz6XDyv39u6xPIUA1y1uPv26T2tQq+a0UlIREJEbcUZt/fltxpjNU9UoNb1GXmYbTA3iFjduy13IJ7PEwjY2tm2Da+J9ZnOPec8Vt3CzdqJKqVmuuaG5MEls41Vjl8ZaXrmcZ48+i8/yYYxx0gTsFK9e8mp+d/R37B/Y7+TYGhhKDxWel08/sLCcXNvcogm2sRGE8xecz+HIYSLJCPXl9fzBqj/g5+0/Lzw/lU1BisKyuG6XG5dx0he8Li9uy81Xr/+q5tSqOW/CEVsR+Q+clW/+FuciyHuAc6a4XWoajbzM5nV5iWViLAwuBGBhcGFhPXNjDJHkxGt0CKIjA0qpeaMj3MF9e+5jb99e/C4/WZPFxsayLNbWr8Xn9hFJRqjyVZHKprCNjUtOjBJ4XV7KPeWFVASLE6kEllhU+6u5ZNElhf/zZcQ6wh0cjx0na7LEM/HCAIRt7ELa2KKyRRrUqnmjlBHbq4wxl4rI740xd4jIncCPprphavrkL7Pduu1WBuIDLK9Yzp6+PRwKHSLgCXBO1Tn0x53VPZN2koydGXd/llh86upP6cQEpdSc0hHqYEf3Dh5tf7SwSANA665W9g/sJ+AJ4BY3VYEquoa68Lq81Phq8Lq8hJNhKr2VVPoqSWVTTrkuYxf2XeWr4k8u+hNaf9960uCB1+UdtT0D8QGORo8O21Yow4gb29i8qvZVfOud3xo1bUKpuaiUyWP5dfhiIrIUSANa9G6OyV9me+u5b8Xn8XHxwosJeALEM3GORo/y0eaPckG8jMbeDO4MzrK5o0y6dVtuDWqVUnNOW2cbjxx4hFgqNqx6zMce+Rhdg1343X4SmQT9iX58Lh9Ly5aStbMksolCTu7l9ZfTHmp3ro6N6EDTdprG6kYuWXQJLsuF23JT7i3HLe5hI7vFeqI9o27PmAwul4syb5kGtWreKWXE9gERqQa+ADyLE87cNZWNUjNnR/cOllcupy/eR6W/knMD59JY1cjBpx4k299Pd61Twstlg7Gc+DY/8TZf7Fsvdyml5prW3a0EXAGimSjtoXZW1qzkmfgzYCCeieO23IXUgd5YLyuqV9Ad7eY1y17Dlhu3FPbz7nveDThpXcXBbX71sGp/NX6Xn6AnyILggsI8h5HajrSR5eRyYXkZO8NbG9+qQa2adyYMbI0x+aG3+0TkAcBvjJlwrXI1Ow3EB7ho4UV0hDsKq9h0D3Yz2PU7sgLBNGQEIn5wZUGsExPFtNi3Umqu+t3R39E91E0kFWEwOUiFt4JkJgmAZVmk7XRhAYVENkEikzgphaC5oZmGigaODR0bVhVBELL22EHqSC8ef5GOSMe4j6kL1nHb1bedwhkqNTeUWhXhKmBF/vEigjHm21PYLjVDagI1J+V37T62m2vCcLgSFsYg4gOThLjbGb21ES5bdJmmHyil5qS2zjY6I50ks0lc4iJtp9nZvRODwe/yU+4pJ5QIYef+uS038WycKl/VSfu6vP5ynu95HjttF1ZwNBhcVgnlZnBSFg5FDhXKeY3GwuKOa+7Q0Vo1L5VSFeE7OAsyvA5Yl/taO8XtUjNkXf26QoUEcC6xxTNxKtMWZWmhLgaXHIO6GJSn4U9fgAvrLuQ/3vEfM9xypZSaGq27W1lVu4p0Nk0qm8KFCwyks2kWli1ERJwgVsA2NkvLl3L9udeTzCbZfmg7C7+wkIv/38VsfXYrLWtaCgEtnFhdzO/2j9cEAA6HDxNKhMiaLGlz8iIPkJvn8LpP6dUzNW+VMmK7FrjQ5IvsqTmlrbON1t2ttIfa6Qx3YjBU+Co4Gj1KMpOkobKB5ZXL6a7t4ry+NFlLSJPl/F7Dohj8VfdS3H+gkxOUUnNXe6idppomnjv+HKFEiJSdos5XR7Wvmi9d/yX++N4/JpQOYYnllO3ylfPC8Rc4Fj2G1/KyoHwB4USYj//i43zhzV9gYXAhnYOdhRq1IoLH8ozbhl3du+gc6jxpu1uc6gc2Nj6Xj3+/4d81qFXzWimB7fPAEqB7ituipllbZxubtm+iyleF1/LSHmoH4I1NbySWinFk6Ahrl67lssWX8ZnQ3+FLZamNGeIuIeoX3nd0BVd99QegQa1Sag5o62zjSy9/ic8f+XyhnFdzQ3NhERu/25nUdX7d+TRWNZK1s7TubiWUCJHMJCnzluESF7FUjGd6nYllGZPheOw4i8sXA3Dn03cS8ATwu/ykSJ20AtloUtnUqEEtOCPEPrcP29ga1CpFaYFtHfCiiLQByfxGY8w7p6xVakoUj842VTdxbOgYVb4q+uJ97O3di9flJZlNEn/qcf5mR5xlfSkO1nyNl/7gDbzvdX/LLzzf5/ixLl4VdvMR91qu/dy/6DK5Sqk5If9BP5lOcl7FefTGetm0fROb12+mZU0Lm7ZvKixUE8/EORQ6hIjgslyF2t6RZASXuAh4AieWxzWGdNZ5XpmnjGPRY4XFb0qRNdlxg18bG0ssNr52owa1SlFaYPuZqW6EmnrFo7Mey8O2/dvoCHewrGIZZZ4yhlJDeF1eLmgf5DM/jbIwDr4snNdnE/rPX/PvsR6+/JEfaMqBUmpOat3dSpWvilfSrxTKeeW3b7lxC5vXb+aP7/1jIskIZZ4y6svrcVku+uJ9pLIpvJbXyX3NBb8ey0Mim3DycXOi6SiLyxYPW5hhPIcGDo0a1ObLihkMNf4aHnnvI9o3K5Uz4eQxY8zjwEHAk/t+B049WzWL5DvtAwMHeOLwE9jGxu/y0xProXOwE0FIJ6Lcuj1NUxgqk06tWpeBc0KGd/+0ndbdrTN9GkopNSXaQ+1U+ipJZBOF2rGVvspCilZzQ7OzlG1VI++64F3EMjEqfZVEU1EEcVb8QshPR6kL1gG5erXGMJQcIp6Js/G1G0tqTygRIpaNjXpf/liWWNz5ljs1qFWqSClVEf4KuBf4z9ymZcCPp7BNagrkO+3DkcNgIJlN4vP4nNEAA5lMkqF0lHXdEMvNYXDbkHELCa+LSw8nCh28UkrNNU3VTSeVOowkIzRVj77QZvHjPZbHmcCVG4mNp+MEvUEW+BcgIqTsFFX+Kr7w5i+UlC6QttOk7NSEj2u5pEXTD5QaoZQldTcAVwMRAGPMy8CiqWyUmlhbZxsbHtzADd+7gQ0PbqCts23cx+c74UQmgUtcZLIZbGNTX16P1+0llo5RlRTE4AS6FmQtENtgjA3ImB28UkrNdi1rWggnwyTtJMYYQokQ4WSYljUt4z4+no7jcXko85SBOIs1BL1Brj/3ehaVL2JBYAHXrbyO5//X8yUFoYfDh0lmk+M+xufycdc77uJbf/St0zpXpeayUgLbpDGm8NFRRNyAlv6aQfl82d5Yb2HN8k3bN40b3OY7YbflJmuyZEyGrJ2lsbLRWWHMOKuK7a2DyhSkXBD1gjsL/pTNvnMrx+zglVJqtmtuaGbz+s34XX7CyTB1wTo2r9885mX+/OOD3iBpO025r5yGigZq/bXcdMFNNFY3nnIbHt73MLuP757wcVr9QKmxlRLYPi4inwICIvIW4B7gp1PbLDWefL5sX7yP9lA71f5qqnxV4+bA5jvh+vJ6ktkkglDrr+WlvpeIZWL4M5ARwxdfC71B8GQhmAQjEFpSzeI7NI9LKTW3NTc0s7p8NbWBWtpDzryC8QYMmhuanSC2qpFLFl1CwBMAoCPUwX177qMj3MFgapCB+MCEx07baR479NiEj3v7yrdrUKvUOEqpivBJ4C+B54APAw8Bd01lo9T42kPtLKtYRkf4xFrhxZMcio0s8fXGpjeCgR3dO9jTs4cFwQUMJYdYnIIEaX6/BP7hWvjA74UFUcOKsqUs/s7/aFkvpdSc19bZxo6BHdRW1nLhwgvpjfXy0Yc/SkNlA7FMjBd7XpxwH6lsikcOPELAFXCW1s3E2de/j7bOtnEHB2LpGDbjV0s4p/IcfvrnOq6k1HhKGbENAN8yxrzHGPNu4Fu5bWqGlDrJYbSUhW37t4HATRfcxJLyJVy74lpqAjXUxYXVsQBlGdjeBHdf5ubli5aweOUaDWqVUvNC6+5WvJaXaDpKe6idVCbFwfBBdh3dxbKKZaQyKXpjvXSEOsbcRzKbJOAKEM1ESdtpLLFwi3vMK2oGQ9ZkJ8yrvXjhxfzwPT88o/NTaj4oJbB9lOGBbAD4xdQ0R5WieNLCeJMcRktZ8Lv9PNb+GPftuY+jQ0d57OBjnFtzLjVZD5Vpi2WmgqvCldzcs5i3+S6CJp0wppSaH9pD7XgtL6lMimgqyr7+fQQ9QULJEO2hdjwuD5ZY7OjeMeY+snYWv9tPKpMqVElwW+5Rr6jZ2CXVtA26g3zznd/UdDClSlBKKoLfGDOUv2GMGRKR4BS2SU0gny9767ZbGYgPUBesY+OVG0/q9PIpCy8cf4HeeC/7+vYxmBwkkUmwesFqZxQ33svevr1cuPpVyIt7GTJp/qS3nteUn8eClBtadMKYUmpuGpmqFXQHnTJbuTUVBlODuMWN23IXattaYo2bM+uyXCQyiWHbMnbmpCtqqWyqsGLZeAKuAF9729c0qFWqRKUEtlERucIY8yyAiLwaiE9ts9RE8pMWADZeNXrB76bqJvb27qVzsBOXuPC5fESSEWxsDkcOs7RiKVc2XMlzx55jv93P26+6gTt2QXM85ozUtrRoGoJSak4qXo0xn6p1ZPAIg+lBXOLCGIPX5WUoNTRsCVzb2NQEasbcr8/lI56Nk86mncUZMGRMZtgVtYH4wIR1ai0syrxlfPm6L+tkMaVOQSmB7a3APSLSlbtdD9w8ZS1Sk6ZlTQvvvufdYCCRSTCYGsRgcIszoaFrqIvzas/j2qZrOTJ4hC3vvXemm6yUUtOiOFWrL95XWEL3+MBxsq4s4WSYyxZfxpHBI4W0r3Q2jW1s1tWvG3O/XpeX68+9nvv33Y8xBpflYlXtqmEjrsejxyds31tWvmXccmNKqdFNGNgaY3aIyPnAakCAl4wx6SlvmTpjzQ3NNFQ28ErmFYbSQ7gtN16XF4PBEotqXzX7+vbhdXl18QWl1LwyVnWZtEmzZtEa1q9Yz8arNtLW2VZI+/K6vdS562isbiykMfyy/Zccix5jQWBBYT+N1U75r3jaubhZPML7ju++Y8LqBx7Lo0GtUqdpzMljIrJORJb8/+3deZycVZ3v8c+v1t6XpENWljYsAhlDEFpZ1DBeF5CXMqjgNtNyX3OZ8Ua9zo3inXslA7hx1YyjM6iDDNCMXAkDg4oIyCgRcWsCEghLMpgOTQiGdKerOt1d1V1dde4fz1OdSqe3LNVVXc/3nVe/6qmnnqrnnK7UqV+f53fOAfAD2TOBLwDrzWzeLJVPjtCqRatoijcBkMvlxm5DFiIairI3tXfK1XVERCrRZLPLNEQbxu7ng9e+VB/zquexrH4ZNdEauhPdYzPONMQbGM2NsrV361ggO5mrf3Y1P/7Dj6ct22fP/ayCWpHDNNWsCP8MjACY2ZuB64HbgCRwY/GLJkfDvKp5bE9sH1ttzMwAqI/VkxxOMr9mvnoGRCRwJptd5pS6UwAOCl4HM94sCalMisdeeWwsjWFvei9hCxMJRUgOJ6c85w2bbpi2XOctOY/Pv/XzR6WOIkE0VWAbds7t9bcvB250zt3tnLsaOLH4RZMj1bmzk46nOqgKVREihMPLEWusaqQ6Us3KRSu5+d03K6gVkcApXBK3cAndhVULAQ4KXqsj1UTMC177Un1esDsy6C1Jjjel10h26gFhAyMDGDbp4xcvv5hH/9ujR6+SIgE0VY5t2MwizrlR4K3AlTN8nsyy8VPWtK9sp21ZGx2bO8hkM9TEaghnw0TDUTLZDOnRNJloRj21IhJoE80ucyu3At7MBacvOJ3uZPeBwevICM3VzQelMYzmRomFY1Oery5Wx8DwAJkJhqlc8boruPnPbj7SKokE3lQ9tt8HfmFmP8Sb3uuXAGZ2Il46gpSBwstl+Slr1m1cR+fOTroSXTRXN2Mhoy5ex4LaBSypX0J9rJ6LT75YQa2IyCSmCl7PXnz2WBoD4KV65UZpjDcecHwml2HfyD5+9/LvWHPfGi45+RIwiFr0gJ7bi5dfrKBW5CiZNLB1zn0RWAvcCpzvnHMFz/lE8YsmM1F4uSy/ulhjvJGOzR20NrWypG4JsVCMeDiOc46BkQGi4agGi4mITGF88JoaTTHqvOD1uKbjxtIYUqMpIqEIp8w/hero/kU6n+95nr50H6nRFD1DPdz5zJ082/MsH1nxEeridURCEZqrmvnc+Z/j3o/cW6pqilScKZfUdc791jl3j3NusGDftvxiDVJ6hble+ZVxGuINdCW6aF/ZTiTsNbhVkSqS6SRmxrVvuVa9tSIiUxgfvNZGazl53sljwWs+jeENS9/AorpFNFU1jT33jqfv4IW+F8buOxx7U3t5ds+z9I/0s/ezexm5eoS9n92rgWIiR9mUga2Uv4kul/UP99Pa1Do2OOKUllM4oekELj31Uu56/11axUZEZAYKg9dLT710yhXH8oYyQzz+x8cP2u9wpLNpHtv1WDGKKiI+DQKbgwonBo+EInQnu0llUlRFqsamrFl7jjcQom1Zm3pnRURmQSqTYjAziMMd9JjDkc1lS1AqkWBRYDvHFK5v3hhvJD2apj/dzx+H/sjw6DADmQHWvnGtglkRkVnUnexmZ//OCYPaPDPj7CWTL8crIkdOge0cc8D65ule4qE4veleDGPFghUc33Q8G57dwOnHnK7gVkRkEoVXvpqrm3nTcW867DYzlUmxLbmNLFP3yB7fcDxXnXfVYZ1DRGZGObZzTFei64CJwXtSPdREa8jmspjZAbMiiIjIwfJXvnqGemiMNzI0MjQ2TeLh2D2we9qg9uTmk/n++76vDgeRIlOP7RzT2tTK1t6tbOvdRnI4Sc7lqIpUUR+rpzZWC+yfFUFERA42/spXS3XLYXcIvJh4kVQ2dcC+ECFy5ABormpm/dvWa9CuyCxRj+0cc9bis9i0axPJ4STOOQwjPZpmJDtCfawe2D8rgoiIHGz8lS84vA6B+7fdz5Y9Ww5+wCBsYUKEeODDDyioFZlF6rEtU507O/nKr74yNjXM2UvO5qrzrmLTK5uojdSSHk0zmhslbGHAW+Fma89WYuHYAbMiiIjIgVqbWukZ6jlgX75DwO2dfPBXoVueuIWHX3x4wsFiOZcjRIhFdYuUeiAyyxTYlqHOnZ188v5PsiO5g5poDTh49KVHefmBlzEzQqEQ86vnkxpNUR2tJmIRelO97EntoaWmhbXnaFYEEQmG/CCwrkQXrU2ttK9sn7b9a1/ZzrqN60hlUjjnSGVSYx0Ctz5867Tn7E50842t3xhLN5hIfbyeL1zwhUOtjogcIaUilKGOzR30pHpwOBLpBMO5YWqjtewZ3EP/cD/xcJyqSBUL6xbSEG8gHAqzqG4Rl512GTe86wYFtSISCIWDwJbWL6VnqGdGg8Dyi9fUxGpIZ9PUxGq4bvV1M247H3vlMTLZzNgVs0goQqjg6zQejvP1t39dKQgiJaAe2zLUlehieHQYl3NkshmioSixWIyBkQGOqT2G+lg9XYkunHNg3ko3JzSeQPvK9lIXXURk1hwwCCzVy/Lm5WP7pwtS86uKbdyxkdUnrJ72+O5kN4/teozeVC84qI5WEw1FyWVz4LycWuccsXCMb1/0bQW1IiWiHtsy1NrUSjwSJ+v2Tx8zkh0hHo6zavEqvvHOb3D+seeTdVmyuSznH3s+37zwm+qpFZFAKRwENjgyCBRnVphEOsGGLRvYM7iH0dwoOZdjaGSIrMvSEG0gZCFG3SjhUJjPnPMZBbUiJaQe2zLUvrKdx3c9ziv7XmE4O0x6NM2+kX0sb14+lj921+V3lbqYIiIlNdkgsJpIDWvuW3NIebdTeWHvC2ML4YQIEbIQOefl11rImBebRzQc5dq3XKugVqTE1GNbhtqWtfG217yN4dFhsi5LzuWoi9VRG60tddFERMpG+8p2ksPJsUFgiXSCFxMv8vK+lw8p77Y70c2a+9Zw0e0X8UjPI/Sl+g54bM+Q31NLDocjFokRD8dxzhEJR7j01Eu56/13KagVKQMKbMtQ585OOp7qoC5WR120jqbqJuKROHXxOq0oJiLiKxwElhxO0lLTwrKGZRzXeBy9qV66El3TrsaYSCd4YPsDY4FwOptm295tdCe6ueWJW+h4quOAtDDz/0XCEWLhmAbtipQZpSKUoY7NHWSyGWLhGMPZYaoiVcRCMXb17yIWjpW6eCIiZSM/CAxg7blruej2i1hav5TuZPfYMVPl3b7U/xJN8aaxAWjxUJxILsLDOx7mnq33jA0My7osDkeIEMPZYcIWpqmqSYN2RcqMAtsy1JXoorm6md5UL3WROhriDeCgL93HBU0XlLp4IiJla6rFF+DAeW+T6ST96X4W1S4aG3wG3vRdL/W/5HUqhGNUuSpGsiPegF2XJZQLMb92Pl/+0y+rp1akzCgVoQy1NrWypG4JsdD+PK6BkQGi4ah6B0REpjBR3m1yOEn7yvaD5r0dzAySGk2xN7V37PlD2SF6070MZAa8FR7dKI1VjSytX0pDrIFYOMapC07lRx/4kXJqRcqQAtsy1L6ynUg4winzT6EqUkUyncTMuPYt16p3QERkChPl3eYXXyic97Yr0UV1pJraaC2vDr1KKpNi3/A+dqd3M5obpS5aRzQUZSgzhDnzxjnE6lhYu5Cb332z2mKRMlWSVAQz2wHsA7LAqHPurFKUo1zlG+aOzR3EIjEuOOGCI56uRkQEgtH+js+7zetKdB2Uf1sb82abqYnV8PTupxl1o+DAzABoiDUwmBkk67JjU3qpLRYpX6XMsb3AOdcz/WHB1LasTY2niBRLINvfifJvM7kMJzSdwNlLzmbz7s1UhasgBNFwdGyFscHMIJeeeqk6GETmAKUilNAtT9zCim+tYMFXF7DiWyu4/5X7S10kEZGKNT7/NjWaIpPLcGz9sWx4ZgOZbIZ0Nk3YwsyrnkdtrJZIKKIpvUTmEHPOzf5JzbqAPsAB/+ycu3GCY64ErgRYsGDB6++8887ZLWSR3f/K/Xxn+3eIh+JUhapI59Kks2k+tvxjXLj4wlIXr6gGBgaoq6srdTGKLij1hODUdXw9L7jggsfn2qX86drfudj23vmSV8bLjr1syn0Az/U/xw1/uIH+TD8N0QbSo2lG3Ag9wz2ECJHOpTG81cRCFmIoO8T1f3I9pzacOnsVmmVB+fwWUp3ntqna3lIFtkucc7vM7BjgIeATzrlHJjv+lFNOcVu3bp29As6CFd9aQTKdpC6+/z9Zb38vxzQew5b/vqWEJSu+jRs3snr16lIXo+iCUk8ITl3H19PM5mJgO+P2d660vet/vR44MJ92on3jH+tOdnPzkzdjzhh1o0TDUWqoYdANknM5FtUu4oxFZ1T8EuZB+fwWUp3ntqna3pKkIjjndvm3rwL3AIG7vrN7cPdBS+RWharYPbi7RCUSkSBQ++vp3NnJbZtvY3BkkEwuQ9jCDGWGGHWjLKlbQn2snhPnn8hV511V6qKKyCGY9cDWzGrNrD6/DbwdqOwuygksrF3IYGbwgH3pXJqFtQtLVCIRqXRqfz3diW4e3P6gt5KYhcZWFWuMNZLOpUkOJ5lfM39smjARmTtK0WO7EHjUzDYDncB9zrkHSlCOklr7xrWkRlMMDA/gco6B4QGGc8OsfePBl81ERI6SwLe/nTs72fDsBgZGBhjODhMNRwmZ91WYdVmiFmXlopWaq1Zkjpr16b6cc9uBlbN93nKTX7Fm/W/Xs3twNwtrF/KhxR/SSjYiUjRBb3/zK48NZYaIhCLkx5g0VzWTGk0xlBliSdUS9dSKzGGlnMc2ODo7oaMDurqgtRXa26GtjSvOvOKAQHbjxo2lK6OISIXLrzxWE63BMLIuC0A6m6Y+Vk9DvIGrll+loFZkDtM8tsXW2Qnr1kFPDyxd6t2uW+ftFxGRWdOV6KIh3sCxDccSCUdoijcRsYi3bK6/bHklT+slEgTqsS22jg4YHYVf/QrSaVi4EBYv9va3qVdARGQynTs76djcQVeii9am1iNe+Su/8tiZi89kWf0ytu3dRtZlWda4bCynVlfOROY29dgW2+9/D88/D6kUhELe7fPPe/tFRGRC+XzYnqEeltYvpWeoh3Ub19G58/CvduVXHkukE7TUtrDimBUaKCZSYRTYFlt/P5hBJOLdxuPebX9/qUsmIlK28vmwvaleuhJdNFU10RhvpGNzx2G/ZtuyNq5bfR0tNS28vO9lWmpaNFBMpMIoFaHYGhogkfC2IxEYGQHnvP0iIjKhrkQXS+uX0p3sHtvXEG+gK9E17XM7d3Zy93N305fqY3vf9gNSGNqWtSmQFalg6rEttlWr4LWvhZYWCIehqsq7v2pVqUsmIlJ2Ond2sua+NTzz6jM8vONh9g3vG3usf7if1qbWaZ+/buM6hkaGaIw3HpUUBhGZOxTYFlt7u9dTu2IFvOMd3m0k4u0XEZExhXm1qxatYmBkgBeTL9Kf7ieRTpAcTtK+cuq2M5/CUB2txsyOSgqDiMwdCmyLra0NrrvO67F9+WXv9rrrNCOCiMg4hXm1A5kBzll2DrFIjF0Du2acD5uf0qs2VkttrBaYeQqDiMx9yrGdDW1tCmRFRKYxPq92efNyTmo+ieRwkhvedcOMXiM/pdfy5uVj+2aSwiAilUGBrYiIlIV8UFooPZqmubp50ueMHyh21uKz2PDsBsDrqe0f7ic5nGTtOWuLWnYRKQ9KRRARkbKQn2c2lUnhnCORTpDKpjh78dkTHj/RQLENz27g8tMu15ReIgGlHlsRESkL+XlmP/Xgp+hL9dFS08I7X/NOjms6bsLj8zm5yXQSgKaqJgA2vbJpxqkLIlJZFNiKiEjZaFvWxntPfS8Aa89dy/pfr5/02HxObn6QGGigmEjQKbAd52ivTS4iIsWhgWIiMp5ybAsUY21yEREpjnxObiKdIOdyM57rVkQqlwLbAsVYm1xERIojn5OrgWIikqdUhAJHsja5iIjMvrZlbQpkRWSMemwLtDa10j/cf8A+5WuJiIiIzA0KbAtMNIei8rVERERE5gYFtgXy+Vo1sRqSw0nla4mIlFB+VbGbnriJNfet0UBeEZmWcmzHGT+HooiIzL7uZPdBq4qt27hOnQ0iMiX12IqISNnZtGsTjfFGqqPVmJlmqRGRGVGPrYiIlI18+sFTu5+iL91HbbSWxqpGQLPUiMj0FNiOk29U+1J9bO/brpXHRERmSX6RnKGRIWqjtewb3se+4X0sq18GaJYaEZmeUhEKFDaqhTldGrAgIlJ8+UVyqqPVHFN7DJi3f+verZqlRkRmJFA9tp07O+nY3EFXoovWptaDemPzjWoynQSgqappbL96bUVEiiu/SE5trJbaWC0nzjuRrT1b2TO0h5aaFtaes1ZtsYhMKTCBbb43tjHeyNL6pROOsC1sVPOU0yUiMjtam1rpGephefPysX2xcIyWmhZueNcNJSyZiMwVgUlFyPfG9qZ66Up0TTjCNr/y2PLm5WMNq3K6RERmpnNnJ2vuW8NFt190WPPO5hfJSaQT5FxO6QcicsgCE9h2JbpoiDcwODLI4MggcHBvrBpVEZHDk78q1jPUc8BVsUMJbvOL5LTUtPDyvpe1SI6IHLLApCLkL3EVGt8bm29UC/NwldMlIjK9wqtivanesatehzpGoW1Zm9pcETlsgQls21e2s27jOlKZFFWRqrHe2LXnHLi6mBpVEZFDlx+j0J3sHtunMQoiMtsCk4qQ742tidWQHE7qEpeIyFGUH6NQSGMURGS2BabHFrzg9r2nvheAteeuneZoERGZqZleFRMRKabA9NjC/lXFbnripsMasSsiIhPTVTERKQeB6bGdbFUxNbwiIkeHroqJSKkFpse2cKlGM5twHlsRERERmbsCE9jm57HNL9UIGrErIiIiUkkCk4ow0VKNGrErIiIiUjkC02OrVcVEREREKltgAlst1SgiIiJS2QKTigBaVUxEpJjyUyr2pfrY3red9pXtanNFZFYFpsdWRESKZ7IpFTVfuIjMJgW2IiJyxDSlooiUAwW2IiJyxDSlooiUg0Dl2IqISHFoSkURKQfqsRURkSOmKRVFpBwosBURkSOmKRVFpBwoFUFERI4KTakoIqWmHlsRERERqQgKbEVERESkIiiwFREREZGKoMBWRERERCqCAlsRERERqQgKbEVERESkIpQksDWzd5rZVjN7wcz+VynKICISRGp/RaSSzXpga2Zh4AbgQuA04INmdtpsl0NEJGjU/opIpStFj20b8IJzbrtzbgS4A3hPCcohIhI0an9FpKKVIrBdCrxUcH+nv09ERIpL7a+IVLRSLKlrE+xzBx1kdiVwpX932My2FLVU5aEF6Cl1IWaB6ll5glLX8fU8vlQFOUzTtr8BbXsLBeX/ciHVORgqqc6Ttr2lCGx3AscW3F8G7Bp/kHPuRuBGADPb5Jw7a3aKVzqqZ2UJSj0hOHWtgHpO2/4Gse0tpDoHg+pcuUqRivAYcJKZtZpZDPgA8KMSlENEJGjU/opIRZv1Hlvn3KiZfRx4EAgDNzvnnpntcoiIBI3aXxGpdKVIRcA59xPgJ4fwlBuLVZYyo3pWlqDUE4JT1zlfz0Nsf+d8fQ+D6hwMqnOFMucOGrclIiIiIjLnaEldEREREakIZR3YBmnpRzPbYWZPm9mTZrap1OU5WszsZjN7tXDKIDObZ2YPmdl/+rfNpSzj0TBJPa8xs5f99/RJM7uolGU8GszsWDN72MyeM7NnzOx/+Psr6j2dop4V955OJkjtb16ltsOFgtImFwpK+5wXlHZ6MmWbiuAv/bgNeBveFDWPAR90zj1b0oIViZntAM5yzlXKHHMAmNmbgQHgNufcCn/fV4C9zrnr/S/MZufcZ0tZziM1ST2vAQacc18rZdmOJjNbDCx2zj1hZvXA48AlwEepoPd0inpeRoW9pxMJWvubV6ntcKGgtMmFgtI+5wWlnZ5MOffYaunHCuCcewTYO273e4AOf7sD7wM3p01Sz4rjnHvFOfeEv70PeA5v5aqKek+nqGdQqP2tUEFpkwsFpX3OC0o7PZlyDmyDtvSjA35qZo/7K/9UsoXOuVfA+wACx5S4PMX0cTN7yr8UVlGXfczsBGAV8Dsq+D0dV0+o4Pe0QNDa37wgtcOFKvbzO42K/ywHpZ0uVM6B7YyW3q0g5znnzgQuBNb4l05kbvs2sBw4A3gFWF/S0hxFZlYH3A18yjnXX+ryFMsE9azY93ScoLW/eWqHg6PiP8tBaafHK+fAdkZL71YK59wu//ZV4B68S4GVarefA5TPBXq1xOUpCufcbudc1jmXA75LhbynZhbFayxvd879u7+74t7TiepZqe/pBALV/uYFrB0uVHGf3+lU+mc5KO30RMo5sA3M0o9mVusneGNmtcDbgS1TP2tO+xHQ7m+3Az8sYVmKJt+A+P6MCnhPzcyAfwGec879fcFDFfWeTlbPSnxPJxGY9jcvgO1woYr6/M5EJX+Wg9JOT6ZsZ0UA8Kff+Af2L/34xdKWqDjM7DV4vQPgrQb3/yqlrmb2fWA10ALsBv4O+AFwJ3Ac0A283zk3pxP7J6nnarzLXA7YAfxVPr9prjKz84FfAk8DOX/3/8bL36qY93SKen6QCntPJxOU9jevktvhQkFpkwsFpX3OC0o7PZmyDmxFRERERGaqnFMRRERERERmTIGtiIiIiFQEBbYiIiIiUhEU2IqIiIhIRVBgKyIiIiIVQYFtgJhZ1syeNLPNZvaEmZ1bxHNdYmanFdzfaGZnFet8BefZYWYth3D8NWb26cM4z1+b2V8c6vOOJv93vM7f/oSZbTGzn/jzjmJm55tZ4RysC8zsgVKVV0RKb5a/B241s/cV6/X9c7zWr8/vzWy5mf3a33+CmX2omOeW8qTANlhSzrkznHMrgb8FvlzEc10CnDbdQYXMLFKcohx9zrnvOOduK3ExrgK+5W//JfA64PfAO/wJuq8GPp8/2Dm3B3jFzM6b7YKKSNmYze+B2XAJ8EPn3Crn3B+cc/lA/QRAgW0AKbANrgagD7z1pM3sZ/5f70+b2Xv8/bVmdp//l/0WM7vc3/96M/uFmT1uZg+OW8EFvwfg3cBX/b+kl/sPvd/MOs1sm5m9yT/2o2b2b2Z2L/BTM5tnZj8ws6fM7Ldm9jr/uGvMrMPMfur3yl5qZl/xy/uAv3xg3mf883Sa2Yn+84/36/iUf3vcuDIvN7MnCu6fZGaP+9vXm9mz/nO/VlCeT/vbnyx4/I7xv2i/jv9UcP/HZrbazMJ+j8YWvx5/U1CWB/zf7y/N7LUTvObJwLBzrqdgdxSoATLAnwM/cc71jXvqD4APj389EQmkon0PFPgvfju2zcwu9p8bNrOvmtljfrv5V/7+1eZd3bvLzJ43s9v9P9InPJ95i4h8CvhLM3vYP27AP+/1wJv876C/KcpvT8qTc04/AfkBssCTwPNAEni9vz8CNPjbLcALgAHvBb5b8PxGvODp18ACf9/leKsSjT/XrcD7Cu5vBNb72xcB/+FvfxRvXfp5/v1/BP7O3/5T4El/+xrgUf/8K4Eh4EL/sXuAS/ztHcD/8bf/Avixv30v0O5v/1fgBwWv+2l/+2HgDH/7S8AngHnAVvYvZtI0wfN2AfHCx8f9Lj4K/FPB/R/jrXrzeuChgv351/4ZcJK//Qbg5xO85hX536d//8/xemu/B9T7rxGd4HlLgadL/X9RP/rRT2l+SvA98ABeJ9pJfltfBVwJfM4/Jg5sAlr9djEJLPOf8xvg/KnOV9gW+/cH/NvV+fZfP8H6mTOXfuWoSDnnzgAws3OA28xsBV7j9SUzezPe8ntLgYV4y/F9zcz+L14D8Uv/+BXAQ/4f0mFgpssQ/rt/+zjeZaK8h9z+Zf3Ox2tIcc793Mzmm1mj/9j9zrmMmT3tnzefL/r0uNf7fsHt1/3tc4BL/e1/Bb4yQfluAq4ws/+J13C2Af1AGrjJzO7DC0rHewq43cx+gNcjOlPbgdeY2T8C9+H1WNcB5wL/5v9+wWv4x1sM7Mnfcc79q18vzOzvgG8CF5qXB/wSsNY5lwNeBZYcQhlFpLLM9vfAnX7b859mth14LfB24HW2P/+2ES/wHQE6nXM7/fI9ide2Jw7hfBJwCmwDyjn3G/MGWS3A60FdgPeXe8bMdgBVzrltZvZ6//Evm9lP8XpHn3HOnXMYpx32b7Mc+H9vsGDbOFh+3edhv+w5M8s45/L7c+Nez02yPdFrFrobbw3xnwOPO+d6AcysDXgr8AHg43g9yYXeBbwZL/3iajM73Tk3WvD4KAem/VT59egzs5XAO4A1wGV4l9US+S+eKaTwvgwOYGZLgLOdc9eaWSdeQP9Fv/wP+edOTfPaIhIAs/Q9ML6tdXjt/Ceccw8WPmBmq9n/PQH7vyvsEM4nAacc24Dy8zbDQC9egPSq35hdABzvH7MEGHLOfQ/4GnAm3mX5Bf5f+phZ1MxOn+AU+/AuiR+qR/BzQP1Grsc513+Ir3F5we1v/O1f4wWm+K//6PgnOefSwIPAt4Fb/DLUAY3OuZ/gBZ1nFD7HzELAsc65h/EGczUBdeNeegdwhpmFzOxYvJ5g/C+UkHPubryBXmf6de0ys/f7x5gf/I73HHDiBPs/778WQDXel0gOL/cW4GRgywTPE5GAmYXvAfDGVoTMG2vxGv+5DwIfM39shJmdbGa1UxT1UM6Xd7jfQTLHqcc2WKr9Szvg/QXc7pzLmtntwL1mton9uVcAf4I3ACyHNyDpY865Ef/y0Tf9FIEI8A/AM+POdQfwXTP7JHAo071cA9xiZk/h5dG2H1oVAYib2e/w/nD7oL/vk8DNZvYZvEv4V0zy3NvxUhZ+6t+vB35oZlV4v7PxgxDCwPf834UBX3fOJcYd8yugC++S3hYgP0htKV5d839g/q1/+2Hg22b2ObzcsjuAzeNe8xFgvZlZvufazFYBOOd+7x/zL/45XwKu9fddgJf2ICLBNJvfA+AFpb/AS2v4a+dc2sxuwksxeMIfHLYHb3aDCR3i+fKeAkbNbDNwq3Pu61McKxUkPyBGRADzZjpodM5dPe3BJWZm3wDudc79xyE85xHgPe7g2RJERETmPPXYivjM7B5gOQfn0JarL+HNmjAjZrYA+HsFtSIiUqnUYysiIiIiFUGDx0RERESkIiiwFREREZGKoMBWRERERCqCAlsRERERqQgKbEVERESkIiiwFREREZGK8P8BaqIDMPU4bvUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "base_rx = key_results[key_results['scenario'] == 'base']['thrombolysis_rate'].values\n",
    "scenario_rx = key_results[key_results['scenario'] == 'speed']['thrombolysis_rate'].values\n",
    "base_benfit = key_results[key_results['scenario'] == 'base']['additional_good_outcomes_per_1000_patients'].values\n",
    "scenario_benefit = key_results[key_results['scenario'] == 'speed']['additional_good_outcomes_per_1000_patients'].values\n",
    "\n",
    "\n",
    "compare_plot(base_rx, scenario_rx, base_benfit, scenario_benefit,\n",
    "                     './output/hospitals_speed')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fd0aba4",
   "metadata": {},
   "source": [
    "#### Plot effect of onset-known"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1d90b23f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "base_rx = key_results[key_results['scenario'] == 'base']['thrombolysis_rate'].values\n",
    "scenario_rx = key_results[key_results['scenario'] == 'onset']['thrombolysis_rate'].values\n",
    "base_benfit = key_results[key_results['scenario'] == 'base']['additional_good_outcomes_per_1000_patients'].values\n",
    "scenario_benefit = key_results[key_results['scenario'] == 'onset']['additional_good_outcomes_per_1000_patients'].values\n",
    "\n",
    "\n",
    "compare_plot(base_rx, scenario_rx, base_benfit, scenario_benefit,\n",
    "                     './output/hospitals_onset')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ff5f735",
   "metadata": {},
   "source": [
    "#### Plot effect of benchmark decisions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "358ba506",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "base_rx = key_results[key_results['scenario'] == 'base']['thrombolysis_rate'].values\n",
    "scenario_rx = key_results[key_results['scenario'] == 'benchmark']['thrombolysis_rate'].values\n",
    "base_benfit = key_results[key_results['scenario'] == 'base']['additional_good_outcomes_per_1000_patients'].values\n",
    "scenario_benefit = key_results[key_results['scenario'] == 'benchmark']['additional_good_outcomes_per_1000_patients'].values\n",
    "\n",
    "\n",
    "compare_plot(base_rx, scenario_rx, base_benfit, scenario_benefit,\n",
    "                     './output/hospitals_benchmark')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "827ba1fc",
   "metadata": {},
   "source": [
    "#### Plot effect of all changes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d80f5c3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "base_rx = key_results[key_results['scenario'] == 'base']['thrombolysis_rate'].values\n",
    "scenario_rx = key_results[key_results['scenario'] == 'speed_onset_benchmark']['thrombolysis_rate'].values\n",
    "base_benfit = key_results[key_results['scenario'] == 'base']['additional_good_outcomes_per_1000_patients'].values\n",
    "scenario_benefit = key_results[key_results['scenario'] == 'speed_onset_benchmark']['additional_good_outcomes_per_1000_patients'].values\n",
    "\n",
    "\n",
    "compare_plot(base_rx, scenario_rx, base_benfit, scenario_benefit,\n",
    "                     './output/hospitals_speed_onset_benchmark')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77218f1d",
   "metadata": {},
   "source": [
    "### Histogram of shift in distribution of thrombolysis use and benefit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "14c1036a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LSEiApaUl7O3toVKpKtVWRkYGLC0tqyiyqqXU2GpSXEIIpKamIiEhAa1btzZQZET/w/xlXEqNCyh/bBXNX8p7Jp0ULzs7G40aNap00iJSqVRo1KhRlfQ+EJUF8xdVlYrmLxZeVCFMWlRV+FkiufEzR1WlIp8lFl5UKSqVqlL/rKysSlxvaPHx8fjmm2/Kvd+6deswceJEA0RESnLz5k306tULTk5OcHZ2xtKlSwEA4eHhaNasGTQaDTQaDfbu3WvkSKkyqmv+ApjDqjMWXvRMKi1p5ebmyhwNKY2ZmRkWL16Mixcv4tixY1ixYgUuXLgAAJgyZQri4uIQFxeHfv36GTlSelYxh1VfvLmeqoQQokL7PX0zY1m/La5fvx6fffYZVCoV3NzcMH/+fISGhiI5ORlNmjTB2rVr0bJlS4SEhMDKygonT57EP//8g//85z8YNmwYZs6ciYsXL0Kj0SA4OBg2NjbYs2cPsrOz8eDBA3z77bcYM2YMbty4gbp16yIiIgJubm4Veo9U/ajVamlOWUtLSzg5OeHWrVtGjooMRe78BRg+h61duxajR4/GtWvXmMMUhj1eVO2cP38en3zyCX766SecOXMGS5cuxcSJEzFmzBicPXsWo0aNwuTJk6XXJyYm4siRI9i9ezdmzpwJAFi4cCF69OiBuLg4TJkyBQBw9OhRREZG4qeffsKcOXPg5uaGs2fPYsGCBRgzZoxR3isZX3x8PE6fPo0uXboAAJYvXw43NzeEhobi3r17Ro5OGcp6aY4KyJHDFixYAA8PD+YwBWKPF1U7P/30E4YNG4bGjRsDABo2bIijR49i+/btAIDRo0djxowZ0usHDx4MExMTdOzYEUlJSTrbDQgIQMOGDQEAR44ckaa2euGFF5Camor09HRDvSVSqMzMTAQFBWHJkiWwsrLCm2++idmzZ0OlUmH27NmYNm0a1qxZU2y/iIgIREREACgYvkCr1RZp88llJTF0bBVtuyrjatCgATIyMoqse3q5rPLy8krcV197e/fuxcCBA2FhYYGMjAyYm5vj119/RWRkJDIyMjB48GC8++67yMjIQE5ODvr06YMHDx6gRYsWSEpKQkZGBh4+fIjc3FzpWNnZ2fDz84O5uTkyMjJw9OhRbNy4ERkZGejUqRNSUlKk8cseP35c4fdcWbrOmRJUNLbs7OxyfT5ZeFG1I4TQ++35ye0WFhZF9tXlyVnpS3odv7E/W3JychAUFIRRo0Zh6NChAAA7Oztp+/jx4xEYGFjivmFhYQgLCwMAeHt7w8/PT9qm1WqLLCtJZWPT9fdV+LdT0bar8pxdvHix2FhNFR1XSte4T/ras7CwgIWFRbHLlJaWljA3N0dOTg5MTEykZWtra+m1QghYWlqibt26MDMzk9bXrl27yOsAoH79+tJy4cMAtWvXRq1atYw2llZNGserUO3ateHh4VHm1/NSI1U7/v7+2LZtG1JTUwEAd+/eRffu3bFlyxYAwKZNm+Dj41NqG5aWlqV+s/H19cW2bdsAFCT9xo0bw8rKqoreASmdEALjxo2Dk5MTpk6dKq1PTEyUft6xYwdcXFyMER5Vc3LksO7du2PTpk0AmMOUhj1eVCXk7A1ydnbGhx9+iJ49e8LU1BQeHh5YtmwZQkNDsWjRIunG1NK4ubnBzMwM7u7uCAkJgY2NTZHt4eHhGD16NNzc3FC3bl3psiM9G2JjY7Fhwwa4urpCo9EAABYsWIDNmzcjLi4OKpUK9vb2+Oqrr4wbKFUJuXuz5chh77//PiZPnswcpkSiGvDy8iqyHBMTY5xA9FBqXEJUbWwXLlyQfgZgkH9KcP/+fWOHUKKaGNeTn6lCT//dV1fVJX8JUfHY9P3dVvbvmvmr/GpinjC0isZW3vzFHi+qFFHBx7ALKfl6PxHVbMxfZAy8x4uIiIhIJiy8iIiIiGTCwouIiIhIJiy8iIiIiGTCwouIiIhIJiy8qEaxt7dHSkoKgIJRm0vSvXv3crWp1Wp1jlBeFU6ePCnNy6bVavHrr7/q3WfdunWYOHFimY+h61wQkXIwf5WspuUvDidBlbZ79+4qbc+QSQJAmRKDnLy9veHt7Q2gIHHVr1+/3MmViCqG+atymL/Kjz1eVC0NHjwYXl5ecHZ2liYjLqvCb0+F878NGzYMHTp0wKhRo3SO65OZmVni6w4dOgQPDw+4uroiNDQUjx49AgDMnDkTHTt2hJubG6ZPnw4ACAkJwYQJE9CjRw+0a9dOSviF30jj4+OxcuVKfPHFF9BoNPjll1+wa9cudOnSBR4eHnjxxRdLneS7MM6xY8fC1dUVbm5u+O6776RtH374Idzd3dG1a1epHV3th4eHIzQ0FH5+fnBwcMCyZcukdj7++GN06NABAQEBGDlyJD777DMAwLVr19C3b194eXmhR48euHTpEgAgKioKLi4ucHd3h6+vbzl+U0Q1E/NXyYyZv65evYohQ4bIkr/Y40XV0po1a9CwYUNkZWWhU6dOCAoKQqNGjcrdzunTp3H+/Hk0bdoUzz//PGJjY0ucI62k13l7eyMkJASHDh1Cu3btMGbMGHz55ZcYM2YMduzYgUuXLkGlUiEtLU1qJz4+HocPH8bVq1fRq1cv/PXXX9I2e3t7TJgwAfXr15eS3b1793Ds2DGoVCqsWrUK//nPfxAeHq7z/Xz88cdo0KAB/vjjD2l/AHjw4AG6du2KTz75BDNmzMDXX3+NWbNmwcfHp1j7ixcvBgBcunQJMTExyMjIQPv27fHmm2/izJkz+O6773D69Gnk5ubC09MTXl5eAIB//etf+Prrr+Ho6IjffvsNb731Fn766SfMmzcPP/74I5o1a1bkXBA9q5i/SmbM/BUWFobPPvsMHh4eBs9fLLyoWlq2bBl27NgBALh58yauXLlSocTVuXNnNG/eHACg0WgQHx9fYuIq6XWWlpZo3bo12rVrBwAIDg7GihUrMHHiRNSuXRuvv/46+vfvX+TSw4gRI2BiYgJHR0c4ODhI36p0SUhIwMsvv4zExEQ8fvwYrVu3LvX1Bw8elCbaBSDN31arVi0pDi8vLxw4cEBv+/3794eFhQUsLCxga2uLpKQkHDlyBIMGDUKdOnUAAAMGDABQ8E31t99+w/Dhw6X9C789P//88wgJCcGIESMwdOjQUuMnehYwf5XMmPnr119/RXBwMExMCi4EGjJ/8VIjVTtarRYHDx7E0aNHcebMGXh4eCA7O7tCbVlYWEg/m5qaIjc3F7/99hs0Gg2ef/55fP/99zpfp6tb38zMDMePH0dQUBB27tyJvn37StuenoxX3+S8kyZNwsSJE/HHH3/gq6++0vs+hRAltmlubi6tL4xfX/vlec/5+flo0KAB4uLipH8XL14EAKxcuRLz58/HzZs3odFokJqaWup7IKrJmL90M2b+sra2RmxsrCz5i4UXVTvp6emwsbFB3bp1cenSJRw7dqxK2+/SpQvi4uIQGxuLgQMH6nxdhw4dEB8fL3W3b9iwAT179kRmZibS09PRr18/LFmyBHFxcdI+UVFRyM/Px9WrV3Ht2jW0b9++SJuWlpbIyMgo8l6bNWsGAIiMjNQbe+/evbF8+XJpubCrXpfytu/j44Ndu3YhOzsbmZmZ2LNnDwDAysoKrVq1QlRUFICCBHrmzBkABfdOdOnSBfPmzUPjxo1x8+ZNvcchqqmYv3QzZv5q3bq11Atp6PzFwouqnb59+yI3Nxdubm6YPXs2unbtapQ4ateujbVr12L48OFwdXWFiYkJJkyYgIyMDAQGBsLNzQ09e/bEF198Ie3Tvn179OzZEy+99BJWrlyJ2rVrF2lzwIAB2LFjh3Rzanh4OIYPH44ePXqgcePGemOaNWsW7t27J90MGhMTU+rry9t+p06dMHDgQLi7u2Po0KHw9vZGgwYNAACrVq3C6tWr4e7uDmdnZ0RHRwMA3n33Xbi6usLFxQW+vr5wd3fXexyimor5Szdj5q9NmzZh/fr18uQvUQ14eXkVWY6JiTFOIHooNS4hqja2CxcuVFlb9+/fr7K2qlpVxxYcHCyioqIq3Y6xz1lGRoYQQogHDx4ILy8vcerUKSFE5eIq6TP19N99dVVd8pcQFY8NgCjtvxN92/Vh/io/5q+S6cpfQlQ8tvLmL95cT0TlEhYWhgsXLiA7OxvBwcHw9PQ0dkhERGWihPzFwotIJuvWrTN2CFXim2++MXYIRCQz5q+qw3u8iIiIiGTCwosqROh4LJeovPhZIrnxM0dVpSKfJRZeVG61a9dGamoqkxdVmhACqampxZ6OIjIU5i+qKhXNX7zHi8qtefPmSEhIQHJycqXbys7OVux/ukqNrabFVbt2bWlUbSJDY/4yLqXGBVQstorkLxZeVG7m5uZ6p34oK61WCw8Pjyppq6opNTbGRVRxzF/GpdS4APli46VGIiIiIpmw8CIiIiKSCQsvIiIiIpmw8CIiIiKSCQsvIiIiIpmw8CIiIiKSCQsvIiIiIpmw8CIiIiKSCQsvIiIiIpmw8CIiIiKSCQsvIiIiIpkYrPC6efMmevXqBScnJzg7O2Pp0qUAgPDwcDRr1gwajQYajQZ79+41VAhEREREimKwSbLNzMywePFieHp6IiMjA15eXggICAAATJkyBdOnTzfUoYmIiIgUyWCFl1qthlqtBgBYWlrCyckJt27dMtThiIiIiBTPYIXXk+Lj43H69Gl06dIFsbGxWL58OdavXw9vb28sXrwYNjY2xfaJiIhAREQEACAhIQFarVbalpmZWWRZKZQaF6Dc2JQaF6Dc2BgXEVH1ZfDCKzMzE0FBQViyZAmsrKzw5ptvYvbs2VCpVJg9ezamTZuGNWvWFNsvLCwMYWFhAABvb2/4+flJ27RabZFlpVBqXIByY1NqXIByY2NcRETVl0GfaszJyUFQUBBGjRqFoUOHAgDs7OxgamoKExMTjB8/HsePHzdkCERERESKYbDCSwiBcePGwcnJCVOnTpXWJyYmSj/v2LEDLi4uhgqBiIiISFEMdqkxNjYWGzZsgKurKzQaDQBgwYIF2Lx5M+Li4qBSqWBvb4+vvvrKUCEQERERKYrBCi8fHx8IIYqt79evn6EOSURERKRoHLmeiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiInnLz5k306tULTk5OcHZ2xtKlSwEAd+/eRUBAABwdHREQEIB79+4ZOVIiqm5YeBERPcXMzAyLFy/GxYsXcezYMaxYsQIXLlzAwoUL4e/vjytXrsDf3x8LFy40dqhEVM2w8CIieoparYanpycAwNLSEk5OTrh16xaio6MRHBwMAAgODsbOnTuNGCURVUcsvIiIShEfH4/Tp0+jS5cuSEpKglqtBlBQnN25c8fI0RFRdWNm7ACIiJQqMzMTQUFBWLJkCaysrMq8X0REBCIiIgAACQkJ0Gq1Rdp8cllJKhubvn0r2rZSz5lS4wKUG5tS4wLki42FFxFRCXJychAUFIRRo0Zh6NChAAA7OzskJiZCrVYjMTERtra2Je4bFhaGsLAwAIC3tzf8/PykbVqttsiyklQ2Nn37VrRtpZ4zpcYFKDc2pcYFyBcbLzUSET1FCIFx48bByckJU6dOldYPHDgQkZGRAIDIyEgMGjTIWCESUTXFHi8ioqfExsZiw4YNcHV1hUajAQAsWLAAM2fOxIgRI7B69Wq0bNkSUVFRxg2UiKodFl5ERE/x8fGBEKLEbYcOHZI5GiKqSXipkYiIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmZsYOgCpPpVKV6XVCCANHQkRERKVhjxcRERGRTNjjVYPo6tEqa48YEZEhlZaL2CNPzwoWXkRERBWQnp6O3bt369weGBgoYzRUXbDwIiIigyqtN4s98vSs4T1eRERERDJh4UVEREQkExZeRERERDIxWOF18+ZN9OrVC05OTnB2dsbSpUsBAHfv3kVAQAAcHR0REBCAe/fuGSoEIiIiIkUxWOFlZmaGxYsX4+LFizh27BhWrFiBCxcuYOHChfD398eVK1fg7++PhQsXGioEIiIiIkUxWOGlVqvh6ekJALC0tISTkxNu3bqF6OhoBAcHAwCCg4Oxc+dOQ4VAREREpCiy3OMVHx+P06dPo0uXLkhKSoJarQZQUJzduXNHjhCIiIiIjM7g43hlZmYiKCgIS5YsgZWVVZn3i4iIQEREBAAgISEBWq22SJtPLiuFsePSd+xn7Zylp6eXur1Bgwalbjf271MXxkVEVH0ZtPDKyclBUFAQRo0ahaFDhwIA7OzskJiYCLVajcTERNja2pa4b1hYGMLCwgAA3t7e8PPzk7Zptdoiy0ph7Lj0HftZO2eljSgN6D8fxv596sK4iIiqL4NdahRCYNy4cXBycsLUqVOl9QMHDkRkZCQAIDIyEoMGDTJUCERERESKYrAer9jYWGzYsAGurq7QaDQAgAULFmDmzJkYMWIEVq9ejZYtWyIqKspQIRAREREpisEKLx8fH53zcx06dMhQhyUiIiJSLI5cT0RERCQTFl5EREREMmHhRURERCQTFl5EREREMmHhRURERCQTFl5EREREMmHhRURERCQTFl5EREREMmHhRURERCQTFl5EREREMmHhRURERCQTg83VSERERLrt3r271O2BgYEyRUJyYo8XERERkUxYeBERERHJRG/hNXr06DKtIyJSIuYwIlISvYXX+fPniyzn5eXh1KlTBguIiKgqMYcRkZLoLLw+/fRTWFpa4uzZs7CysoKVlRUsLS1ha2uLQYMGyRkjVRGVSqXzH1FNwxxGREqks/B6//33kZGRgXfffRf379/H/fv3kZGRgdTUVHz66adyxkhEVG7MYUSkRHqHk/j0009x69YtXL9+Hbm5udJ6X19fgwZGVUcIAa1WCz8/v2Lb2NtFNR1zGBEpid7Ca+bMmdiyZQs6duwIU1NTAAX/WTNpEVF1wBxGREqit/DasWMH/vzzT1hYWMgRDxFRlapoDgsNDcXu3btha2uLc+fOAQDCw8Px9ddfo0mTJgCABQsWoF+/flUeMxHVXHqfanRwcEBOTo4csRARVbmK5rCQkBDs27ev2PopU6YgLi4OcXFxLLqIqNz09njVrVsXGo0G/v7+Rb4xLlu2zKCBERFVhYrmMF9fX8THxxs4OiJ61ugtvAYOHIiBAwfKEQsRUZWr6hy2fPlyrF+/Ht7e3li8eDFsbGyqrG0iqvn0Fl7BwcFyxEFEZBBVmcPefPNNzJ49GyqVCrNnz8a0adOwZs2aYq+LiIhAREQEACAhIQFarVbalpmZWWRZSSobm6H2VfI5y8vL07lNX8yl7VuW/Uuj1HOm1LgA+WLTW3i1bt26xCEHrl27ZpCAiIiqUlXmMDs7O+nn8ePHIzAwsMTXhYWFISwsDADg7e1dZCgXXUO7KEFlYzPUvko9Z9HR0dKTsiXRF/Pu3btL3V6Z96zUc6bUuAD5YtNbeJ08eVL6OTs7G1FRUbh7965BgyIiqipVmcMSExOhVqsBFDwt6eLiUiUxEtGzQ2/h1ahRoyLL77zzDnx8fDBv3jyDBUVUqLRvhLp6G4ieVNEcNnLkSGi1WqSkpKB58+aYO3cutFot4uLioFKpYG9vj6+++sqQoRNRDaS38Pr999+ln/Pz83Hy5ElkZGQYNCgioqpS0Ry2efPmYuvGjRtXpbER0bNHb+E1bdq0/73YzAz29vbYtm2bQYMiIqoqzGFEpCR6C6+YmBg54iAiMgjmMCJSEr0j16enp2Pq1Knw9vaGt7c3pk2bhvT0dDliIyKqNOYwIlISvYVXaGgoLC0tsW3bNmzbtg1WVlYYO3asHLEREVUacxgRKYneS41Xr17Fd999Jy3PmTMHGo3GkDEREVUZ5jAiUhK9PV516tTBkSNHpOXY2FjUqVPHoEEREVUV5jAiUhK9PV5ffvklgoODpXsibGxssG7dOkPHRURUJZjDiEhJ9BZeGo0GZ86cwf379wEAVlZWBg+KiKiqMIdVDyVN61QeQogqioTIsPQWXh988AFmzJgBa2trAMC9e/ewePFizJ8/39CxERFVGnMYGYu+uRjp2aT3Hq8ffvhBSlhAQTf93r17DRkTEVGVYQ5TNiGE3n8xMTE6txFVN3oLr7y8PDx69EhazsrKKrJMRKRkzGFEpCR6LzW+9tpr8Pf3x9ixY6FSqbBmzRoEBwfLERsRUaUxhxGRkugtvGbMmAE3NzccPHgQQgjMnj0bffr0kSM2IqJKYw4jIiXRW3gBQN++fdG3b19Dx0JEZBDMYUSkFHrv8SIiIiKiqsHCi4iIiEgmBiu8QkNDYWtrCxcXF2ldeHg4mjVrBo1GA41Gw0e6iYiI6Jmi8x4vV1fXEkcSFkJApVLh7NmzpTYcEhKCiRMnYsyYMUXWT5kyBdOnT69guEREZVPZHEZEZAg6C6/Kjrjr6+uL+Pj4SrVBRFRRHDWciJRIZ+HVqlUrgxxw+fLlWL9+Pby9vbF48WLY2NgY5DhUNco6fxpHkCalMVQOexZVdh5FIvofvcNJHDt2DJMmTcLFixfx+PFj5OXloV69etKEs+Xx5ptvYvbs2VCpVJg9ezamTZuGNWvWlPjaiIgIREREAAASEhKg1WqlbZmZmUWWlcLYcZV2bH2xVTbuiu6vL668vLwKH7O0fcuyv7F/n7owrvKpyhxGJKfSem0DAwNljISqkt7Ca+LEidiyZQuGDx+OkydPYv369fjrr78qdDA7Ozvp5/Hjx5f6wQkLC0NYWBgAwNvbG35+ftI2rVZbZFkpjB1XacfWF5u+uHX1aBV+E67o+9YXV2mJR98x9V1q0re/sX+fujCu8qnKHPasY882UeWV6anGtm3bIi8vD6amphg7dixiYmIqdLDExETp5x07dhR54pGIyFCqKocREVWW3h6vunXr4vHjx9BoNJgxYwbUajUePHigt+GRI0dCq9UiJSUFzZs3x9y5c6HVahEXFweVSgV7e3t89dVXVfImiIh0qWgOIyIyBL2F14YNG5Cfn4/ly5fjiy++wM2bN7F9+3a9DW/evLnYunHjxlUsSiKiCqpoDiMiMgS9lxp37tyJ2rVrw8rKCnPmzMHnn3/Ox7SJqNpgDiMiJdFbeEVGRhZbt27dOkPEQkRU5ZjDiEhJdF5q3Lx5M7755hv8/fffGDhwoLQ+IyMDjRo1kiU4IqKKYg4jIiXSWXh1794darUaKSkpmDZtmrTe0tISbm5usgRHRFRRzGFEpESljlzfqlUrHD16VM54iIiqBHMYESmRznu8fHx8ABR8O7SyspL+FS5TzaJSqUr8R1RdMYcRkRLp7PE6cuQIgIL7IYiIqhvmMCJSIr3jeAHA77//jiNHjkClUsHHxwceHh6GjotkwilA6FnAHFbzldZDzzxHSqK38Jo3bx6ioqIwdOhQAEBISAiGDx+OWbNmGTw4IqLKYg4jKo4TcBuP3sJr8+bNOH36NGrXrg0AmDlzJjw9PZm0iKhaYA6r2UrrzeJ9qqREegdQtbe3R3Z2trT86NEjtGnTxqBBERFVFeYwIlISvT1eFhYWcHZ2RkBAAFQqFQ4cOAAfHx9MnjwZALBs2TKDB0lEVFHMYUSkJHoLryFDhmDIkCHSsp+fnyHjISKqUsxhRKQkeguv4OBg6ed79+7h5s2bHPWZiKoN5jAiUhK993j5+fnh/v37uHv3Ltzd3TF27FhMnTpVjtiIiCqNOYyIlERv4ZWeng4rKyts374dY8eOxalTp3Dw4EE5YiMiqjTmMCJSEr2FV25uLhITE7Ft2zaO7UFE1Q5zGBEpid7C66OPPkKfPn3Qpk0bdOrUCdeuXYOjo6McsRERVRpzGBEpid6b64cPH47hw4dLyw4ODvjuu+8MGhQRUVVhDiMiJdHb45WQkIAhQ4bA1tYWdnZ2CAoKQkJCghyxERFVGnMYESmJ3h6vsWPH4tVXX0VUVBQAYOPGjRg7diwOHDhg8OCIiCqLOYyofEqbxxHgXI6VpbfHKzk5GWPHjoWZmRnMzMwQEhKC5ORkOWIjIqo05jAiUhK9hVfjxo2xceNG5OXlIS8vDxs3bkSjRo3kiI2IqNKYw4hISfQWXmvWrMG2bdvw3HPPQa1W49tvv8WaNWvkiI2IqNKYw4hISfTe49WyZUt8//33csRCRFTlmMOISEl0Fl6TJk2CSqXSueOyZcsMEhARUVVgDiMiJdJZeHl7e0s/z5kzB3PnzpUlICKiqsAcRkRKpLPwCg4Oln5esmRJkWWSV2nf2omoZMxhRKREeu/xAvgfP9HTOM5N9cIcRkRKofepRlIOIUSp/4io6oSGhsLW1hYuLi7Surt37yIgIACOjo4ICAjAvXv3jBghEVVHOgsvS0tLWFlZwcrKCmfPnpV+LlxPRKRklc1hISEh2LdvX5F1CxcuhL+/P65cuQJ/f38sXLjQUOETUQ2l81JjRkaGnHEQEVWpyuYwX19fxMfHF1kXHR0NrVYLoOAeMj8/P/z73/+u1HGI6NnCS41ERGWUlJQEtVoNAFCr1bhz546RIyKi6qZMN9cTEVHZRUREICIiAgCQkJAg9ZIBQGZmZpFlJdEXm7Hiruw5M2TceXl5Bmu7NPrek75zVpm4K3M+q/Pnv6qw8CIiKiM7OzskJiZCrVYjMTERtra2Jb4uLCwMYWFhAArGE/Pz85O2abXaIstKoi82Y8Vd2XNmqLijo6NhampqkLb10fee9J0zfU9mV+bYpanOn/+qwkuNRERlNHDgQERGRgIAIiMjMWjQICNHRETVDQsvIqISjBw5Et26dcOff/6J5s2bY/Xq1Zg5cyYOHDgAR0dHHDhwADNnzjR2mERUzfBSIxFRCTZv3lzi+kOHDskcCRHVJOzxIiIiIpIJe7zIqNLT0yt1kycREVF1wh4vIiIiIpmw8CIiIiKSCQsvIiIiIpmw8CIiIiKSCQsvIiIiIpnwqUYiIqrRSntyOjAwUMZIiAzY4xUaGgpbW1u4uLhI6+7evYuAgAA4OjoiICAA9+7dM9ThiYiIiBTHYIVXSEgI9u3bV2TdwoUL4e/vjytXrsDf3x8LFy401OGJiIiIFMdghZevry8aNmxYZF10dDSCg4MBAMHBwdi5c6ehDk8yU6lUOv8RERFRAVnv8UpKSoJarQYAqNVq3LlzR+drIyIiEBERAQBISEiAVquVtmVmZhZZVgpDx1WZto15zvQdNy8vzyjt6tu/tHNW2bYr41n9/BMR1QSKvbk+LCwMYWFhAABvb2/4+flJ27RabZFlpTB0XJVp21CxCSF0bivs7SrtuNHR0TA1Na3QsfW9H31TEenbv7RzVtm2K+NZ/fwTEdUEsg4nYWdnh8TERABAYmIibG1t5Tw8ERERkVHJWngNHDgQkZGRAIDIyEgMGjRIzsMTERERGZXBCq+RI0eiW7du+PPPP9G8eXOsXr0aM2fOxIEDB+Do6IgDBw5g5syZhjo8ERERkeIY7B6vzZs3l7j+0KFDhjokERERkaJxyiAiIiIimbDwIiIiIpKJYoeTICIi+TyLgx0PGDCgTK8rbdgcovJi4UVERFQKfeP2EZUHCy8yOH3fpHft2iVTJESkz7PYu6MrB5W1R4yoPFh4UaUZ69tgdf4WWlrsgYGBMkZCRERyYuFFBqOvJ4vfJomI6FnDpxqJiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMLCi4iIiEgmLLyIiIiIZMKR64l0SE9Pr9bTEhERkfKwx4uIiIhIJiy8iIiIiGTCwouIiIhIJiy8iIiIiGTCwouIiIhIJiy8iIiIiGTCwouIiIhIJiy8iIiIiGTCwouIiIhIJhy5XiFUKpWxQzCaAQMGlLp9165dMkVCRERkWCy8iAyAUw0REVFJWHgpjBDC2CHIZteuXcjLy4OpqWmJ2/X1hBEREVU3vMeLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwsKLiIiISCYsvIiIiIhkwgFUiYjKyd7eHpaWljA1NYWZmRlOnjxp7JCIqJpg4UXPLE7rQ5URExODxo0bGzsMIqpmWHgREVGNxunHSElYeBERlZNKpULv3r2hUqnwxhtvICwsrMj2iIgIREREAAASEhKg1WqlbZmZmUWWlUaJsRn6nOXl5VV4u759DSU6OrpKXlMRlfldKPnzL1dsLLyIiMopNjYWTZs2xZ07dxAQEIAOHTrA19dX2h4WFiYVY97e3vDz85O2abXaIstKo8TYKnrOhBBVckuBqalpievz8vJ0bjM2Q8ZWmc+Ikj//csXGpxqJiMqpadOmAABbW1sMGTIEx48fN3JERFRdsPAiIiqHBw8eICMjQ/p5//79cHFxMXJURFRd8FIjEVE5JCUlYciQIQCA3NxcvPrqq+jbt6+RoyKi6sIohRfHwCGi6srBwQFnzpwxdhhEVE0ZrceLY+AQERHRs4b3eBERERHJxCiFV+EYOF5eXtJYN0REREQ1nVEuNeobAweongMQVkVchnpfhjxnlR1AsDKDFxqaMY6t7/dUkz//REQ1nVEKr5LGwHm68KqOAxBWRVyGel+GPGeVGaCwLIP8GWuAQmMNjqjv91STP/9ERDWd7JcaOQYOERERPatk7/HiGDhERPJTqVTGDqFGKevE27t27TJwJFTdyF54cQwcIiIielZx5HoiomeIEELnNj4cUX66erTK2iNGzx6O40VEREQkExZeRERERDJh4UVEREQkExZeRERERDLhzfUy4aPcRERExMKL9KrMyPRERET0Pyy8ZFbao9xERERUs/EeLyIiIiKZsPAiIiIikgkLLyIiIiKZsPAiIiIikglvriciomqNT15TdcIeLyIiIiKZsPAiIiIikgkLLyIiIiKZ8B4vUrwBAwZUeN9du3ZVYSRERESVw8KLqJpJT08v9WbiwMBAGaMhIqLyYOFFilWZ3qrK9JIREREZCu/xIiIiIpIJCy8iIiIimbDwIiIiIpIJCy8iIiIimfDmeiKiakKlUhk7BCKqJBZeRESkaPqGUCF5VeZ3kZeX98wPh8PCi4iomhFCGDsEIqogFl7lwG7+mqOs43xx5HsiIqpKLLyIXfhEREQyYeFVAbq6+bVaLfz8/OQNhipFV48WR74nIiJD4HASRERERDJh4UVEREQkExZeRERERDJh4UVEREQkExZeRERERDJh4UVEREQkExZeRERERDLhOF5ERArB2TGUieP6/Q9n/ai8GlV4VVXS4jxoZCxMamRMpU1G/SxMXkwkhxpVeBlbaUkLMGzi0jftj74Z4anmMNZnkKoOv/wpg74vOHl5eTJFojyc9aPiamThVdGkxW5+UgomNSKimok31xMRERHJhIUXERERkUxYeBERERHJhIUXERERkUxYeBERERHJxCiF1759+9C+fXu0bdsWCxcuNEYIREQVxhxGRBUle+GVl5eHt99+Gz/88AMuXLiAzZs348KFC3KHQURUIcxhRFQZshdex48fR9u2beHg4IBatWrhlVdeQXR0tNxhEBFVCHMYEVWG7AOo3rp1Cy1atJCWmzdvjt9++03uMErFgVRrjsoOOKrUAUuVGldpaspo7NUhh5FyVMe/1apQ0953VeYvlZA5G0ZFReHHH3/EqlWrAAAbNmzA8ePH8d///rfI6yIiIhAREQEAuHTpEjp06CBtS05ORpMmTeQLuoyUGheg3NiUGheg3Nielbji4+ORkpJSZe1VlbLksOqYvwDlxsa4yk+psSk1LqBqYystf8ne49W8eXPcvHlTWk5ISEDTpk2LvS4sLAxhYWEltuHt7Y2TJ08aLMaKUmpcgHJjU2pcgHJjY1zGVZYcVh3zF6Dc2BhX+Sk1NqXGBcgXm+z3eHXq1AlXrlzB33//jcePH2PLli0YOHCg3GEQEVUIcxgRVYbsPV5mZmZYvnw5+vTpg7y8PISGhsLZ2VnuMIiIKoQ5jIgqQ/bCCwD69euHfv36VXh/XV34xqbUuADlxqbUuADlxsa4jK8yOUzJ50mpsTGu8lNqbEqNC5AvNtlvriciIiJ6VnHKICIiIiKZVKvCS8nTdNjb28PV1RUajQbe3t5GiyM0NBS2trZwcXGR1t29excBAQFwdHREQEAA7t27p5jYwsPD0axZM2g0Gmg0Guzdu1f2uG7evIlevXrByckJzs7OWLp0KQDjnzddcSnhnGVnZ6Nz585wd3eHs7Mz5syZA8D450zplJrDlJK/AOXmMOavqovN2OfN6PlLVBO5ubnCwcFBXL16VTx69Ei4ubmJ8+fPGzssSatWrURycrKxwxCHDx8Wp06dEs7OztK6d999V3z66adCCCE+/fRTMWPGDMXENmfOHLFo0SKjxFPo9u3b4tSpU0IIIe7fvy8cHR3F+fPnjX7edMWlhHOWn58vMjIyhBBCPH78WHTu3FkcPXrU6OdMyZScw5SSv4RQbg5j/qq62Ix93oydv6pNjxen6SgbX19fNGzYsMi66OhoBAcHAwCCg4Oxc+dOI0RWcmxKoFar4enpCQCwtLSEk5MTbt26ZfTzpisuJVCpVKhfvz4AICcnBzk5OVCpVEY/Z0rGHFY2Ss1hzF9VF5uxGTt/VZvCq6RpOpTwCyykUqnQu3dveHl5SSNWK0VSUhLUajWAgj+EO3fuGDmiopYvXw43NzeEhoYa/dJUfHw8Tp8+jS5duijqvD0ZF6CMc5aXlweNRgNbW1sEBAQo7pwpjZJzmJLzF6DsHKaEv8VCSs1fT8cGGP+8GTN/VZvCS5Tw8KWS5lSMjY3F77//jh9++AErVqzAzz//bOyQqoU333wTV69eRVxcHNRqNaZNm2a0WDIzMxEUFIQlS5bAysrKaHE87em4lHLOTE1NERcXh4SEBBw/fhznzp0zShzVhZJzGPNXxSjlbxFQbv4ClJnDjJm/qk3hVdaphoylMBZbW1sMGTIEx48fN3JE/2NnZ4fExEQAQGJiImxtbY0c0f/Y2dnB1NQUJiYmGD9+vNHOW05ODoKCgjBq1CgMHTpUis3Y501XXEo4Z4Wsra3h5+eHffv2KeKcKZWSc5iS8xegjL/Fkijlb1Gp+au02JRw3gDj5K9qU3gpeZqOBw8eICMjQ/p5//79RZ58MbaBAwciMjISABAZGYlBgwYZOaL/KfyQA8COHTuMct6EEBg3bhycnJwwdepUab2xz5uuuJRwzpKTk5GWlgYAyMrKwsGDB9GhQwejnzMlU2oOU3r+Aoz/t6iLEv4WlZq/SovN2OfN6PnLILfsG8iePXuEo6OjcHBwEPPnzzd2OJKrV68KNzc34ebmJjp27GjU2F555RXx3HPPCTMzM9GsWTOxatUqkZKSIl544QXRtm1b8cILL4jU1FTFxPbaa68JFxcX4erqKgYMGCBu374te1y//PKLACBcXV2Fu7u7cHd3F3v27DH6edMVlxLO2ZkzZ4RGoxGurq7C2dlZzJ07VwghjH7OlE6JOUxJ+UsI5eYw5q+qi83Y583Y+Ysj1xMRERHJpNpcaiQiIiKq7lh4EREREcmEhRcRERGRTFh4EREREcmEhRcRERGRTFh41RCpqanSTO/PPfecNPO7tbU1OnbsaPDja7VaBAYGlmsfe3t7pKSklPtY/fr1k8ZgMZZhw4bh2rVrePToEfr27QsXFxf83//9n7Q9LCwMp0+flpaXL1+OtWvXGiNUomfGP//8g1deeQVt2rRBx44d0a9fP1y+fBnx8fHSWFEnT57E5MmTK9T+ypUrsX79+lJfEx4ejs8++6zY+pCQEHz77bcVOm5ZXbp0CRqNBh4eHrh69Sq6d+8OoGC6nm+++cagx6ayY+FVQzRq1AhxcXGIi4vDhAkTMGXKFGnZxET/rzk3N1eGKKvG3r17YW1tbbTjnz9/Hnl5eXBwcMCPP/4ILy8vnD17Vprj7syZM8jPz4eHh4e0T2hoKJYtW2askIlqPCEEhgwZAj8/P1y9ehUXLlzAggULkJSUVOR13t7eFf5bnDBhAsaMGVMV4RrEzp07MWjQIJw+fRpt2rTBr7/+CoCFl9Kw8HoG5OXlYfz48XB2dkbv3r2RlZUFAPDz88MHH3yAnj17YunSpTh06BA8PDzg6uqK0NBQPHr0CEBBz9QHH3yAbt26wdvbG7///jv69OmDNm3aYOXKldJx7t+/jyFDhqBjx46YMGEC8vPzAQCbN2+Gq6srXFxc8N577xWLb/bs2Vi6dKm0/OGHH2LZsmVITEyEr68vNBoNXFxc8Msvv0jxpKSk4MGDB+jfvz/c3d3h4uKCrVu3Fmvbz88PJ0+eBACkpKTA3t4eQEHx1LlzZ2g0Gri5ueHKlSsAgI0bN0rr33jjDeTl5RVrc9OmTdKIxubm5sjKyipSuM6ePRvz5s0rsk/dunVhb2+vuKlYiGqKmJgYmJubY8KECdI6jUaDHj16FHndk73z4eHhCA0NhZ+fHxwcHIoUZOvXr4ebmxvc3d0xevRo6fWFvVlff/01OnXqBHd3dwQFBeHhw4d6Yzx48CB69OiBdu3aYffu3QAK8vO7776LTp06wc3NDV999ZUUp5+fH4YNG4YOHTpg1KhR0nyfp06dQs+ePeHl5YU+ffogMTERe/fuxZIlS7Bq1Sr06tULAFC/fn0AwMyZM/HLL79Ao9Hgiy++KP/JpSrFwusZcOXKFbz99ts4f/48rK2t8d1330nb0tLScPjwYbz99tsICQnB1q1b8ccffyA3Nxdffvml9LoWLVrg6NGj6NGjh9RlfuzYMXz00UfSa44fP47Fixfjjz/+wNWrV7F9+3bcvn0b7733Hn766SfExcXhxIkT2LlzZ5H4xo0bJ03TkJ+fjy1btmDUqFH45ptv0KdPH8TFxeHMmTPQaDRF9tu3bx+aNm2KM2fO4Ny5c+jbt2+Zz8nKlSvxr3/9C3FxcTh58iSaN2+OixcvYuvWrYiNjUVcXBxMTU2xadOmYvvGxsbCy8sLABAQEIB//vkHXbp0wYwZM/D999/Dy8urxDn4vL29peKRiKrWuXPnpL/L8rh06RJ+/PFHHD9+HHPnzkVOTg7Onz+PTz75BD/99BPOnDlT5IthoaFDh+LEiRM4c+YMnJycsHr1ar3Hio+Px+HDh7Fnzx5MmDAB2dnZWL16NRo0aIATJ07gxIkT+Prrr/H3338DAE6fPo0lS5bgwoULuHbtGmJjY5GTk4NJkybh22+/xalTpxAaGooPP/wQ/fr1k652xMTEFDnuwoUL0aNHD8TFxWHKlCnlPkdUtcyMHQAZXuvWraWixcvLC/Hx8dK2l19+GQDw559/onXr1mjXrh0AIDg4GCtWrMA777wDANKccq6ursjMzISlpSUsLS1Ru3Zt6X6rzp07w8HBAQAwcuRIHDlyBObm5vDz80OTJk0AAKNGjcLPP/+MwYMHSzHY29ujUaNGOH36NJKSkuDh4YFGjRqhU6dOCA0NRU5ODgYPHlys8HJ1dcX06dPx3nvvITAwsNg329J069YNn3zyCRISEjB06FA4Ojri0KFDOHXqFDp16gSgYA6vkiZJTUxMlN6PmZmZ1IWfk5ODPn364Pvvv8fUqVNx48YNjBkzRjp3tra2uHTpUpljJCLD69+/PywsLGBhYQFbW1skJSXhp59+wrBhw9C4cWMAQMOGDYvtd+7cOcyaNQtpaWnIzMxEnz599B5rxIgRMDExgaOjIxwcHHDp0iXs378fZ8+ele7/Sk9Px5UrV1CrVi107twZzZs3B1DQexcfHw9ra2ucO3cOAQEBAAp6zNRqdVWdDpIBC69ngIWFhfSzqampdKkRAOrVqwcA0DdzVGEbJiYmRdozMTGRLrOpVKoi+6hUKr3tFnr99dexbt06/PPPPwgNDQUA+Pr64ueff8aePXswevRovPvuu0Xur2jXrh1OnTqFvXv34v3330fv3r2L9MABBYVR4SXP7Oxsaf2rr76KLl26YM+ePejTpw9WrVoFIQSCg4Px6aeflhprnTp1irRV6P/+7/8QHByMo0ePolatWti6dSu6desmFV7Z2dmoU6dOmc4HEZWPs7NzhW5efzo/5ubmQghRLJ89LSQkBDt37oS7uzvWrVsHrVar91i6cuR///vfYoWbVqvVGZuzszOOHj1ahndHSsRLjQQA6NChA+Lj4/HXX38BADZs2ICePXuWq43jx4/j77//Rn5+PrZu3QofHx906dIFhw8fRkpKCvLy8rB58+YS2x0yZAj27duHEydOSAno+vXrsLW1xfjx4zFu3Dj8/vvvRfa5ffs26tati9deew3Tp08vth0o6E07deoUABRJyteuXYODgwMmT56MgQMH4uzZs/D398e3336LO3fuAADu3r2L69evF2vTyclJOk+F7t27h927d2PMmDF4+PAhTExMoFKpihRoly9flp6sIqKq9cILL+DRo0f4+uuvpXUnTpzA4cOHy92Wv78/tm3bhtTUVAAFueBpGRkZUKvVyMnJKfGWhJJERUUhPz8fV69exbVr19C+fXv06dMHX375JXJycgAU5IkHDx7obKN9+/ZITk6WCq/CS6OlsbS0REZGRpliJMNj4UUAgNq1a2Pt2rUYPnw4XF1dYWJiUuQm1bLo1q0bZs6cCRcXF7Ru3RpDhgyBWq3Gp59+il69esHd3R2enp7SjelPqlWrFnr16oURI0bA1NQUQME3vsJHo7/77jv861//KrLPH3/8Id0I/8knn2DWrFnF2p0+fTq+/PJLdO/evcjQFVu3boWLiws0Gg0uXbqEMWPGoGPHjpg/fz569+4NNzc3BAQEIDExsVib/fv3L/btdt68eZg1axZUKhX69OmDkydPwtXVFePHj5deExsbixdffLFc55SIykalUmHHjh04cOAA2rRpA2dnZ4SHh5d4v6U+zs7O+PDDD9GzZ0+4u7tj6tSpxV7z8ccfo0uXLggICECHDh3K1G779u3Rs2dPvPTSS1i5ciVq166N119/HR07doSnpydcXFzwxhtvlPqUea1atfDtt9/ivffeg7u7OzQajfT0oi5ubm4wMzODu7s7b65XAJUo67UgIgPKz8+Hp6cnoqKi4OjoaOxwSpWVlYVevXohNjZWKhL1OX36ND7//HNs2LDBwNEREZGSsceLjO7ChQto27Yt/P39FV90AQX3eM2dOxe3bt0q8z4pKSn4+OOPDRgVERFVB+zxIiIiIpIJe7yIiIiIZMLCi4jICLKystCzZ88SZ0fQRdc8gLrmItRqtUVuvC7LXIPl9eSx5VCReWF1WbBgQZW0Ux0sX74cbdu2hUqlKvKgkRACkydPRtu2beHm5lbk6fB9+/ahffv2aNu2LRYuXCitv3v3LgICAuDo6IiAgADcu3evwnHp+kyXpnAOyvL46KOPcPDgwXLvp0tycnK5Bu1+EgsvIiIjWLNmDYYOHVrmBzTK6sm5CJ8uvJQ+16DcamrhJYSQxi8s9Pzzz+PgwYNo1apVkfU//PADrly5gitXriAiIgJvvvkmgIKBWd9++2388MMPuHDhAjZv3owLFy4AKBgJ39/fH1euXIG/v3+RokwO+p7iLMm8efOq9KnyJk2aQK1WIzY2ttz7svAiIjKCJ+f8zMzMhL+/Pzw9PeHq6oro6GjpdZ988gnat2+PF198EX/++ae0/tSpU3B3d0e3bt2wYsUKaX1hj1B8fDxWrlyJL774AhqNBr/88kuR3oW4uDh07doVbm5uGDJkiNRr4efnh/feew+dO3dGu3btpGmu4uPj0aNHD3h6esLT01Pvf375+fl466234OzsjMDAQPTr108aS0/XvLC61u/btw8dOnSAj48Ptm/fXuLxsrOzMXbsWLi6usLDw0OaNmfdunWYOHGi9LrAwEBotVrMnDkTWVlZ0Gg0GDVqFICS52e8fv06/P394ebmBn9/f9y4cQNAwQCqb775Jnr16gUHBwccPnwYoaGhcHJyQkhIiHS8/fv3o1u3bvD09MTw4cORmZkJoGD+xI4dO8LNzQ3Tp08v9n7Cw8MxevRovPDCC3B0dCwyPtmiRYukuR3nzJkj/X6cnJzw1ltvwdPTEzdv3izSnoeHhzRX7ZOio6MxZswYqFQqdO3aFWlpaUhMTMTx48fRtm1bODg4oFatWnjllVekz2V0dDSCg4MBFMxy8vQ0cEDFPtN+fn6YMmUKfH194eTkhBMnTkgzizw5XFDhHJQlzeebl5eHkJAQuLi4wNXVVRo+o3CqO0D358ze3h5z5syRYi6caeTw4cPQaDTS8EaFY6INHjy4zGO4FSGIiEhWjx49EnZ2dtJyTk6OSE9PF0IIkZycLNq0aSPy8/PFyZMnhYuLi3jw4IFIT08Xbdq0EYsWLRJCCOHq6iq0Wq0QQojp06cLZ2dnIYQQMTExon///kIIIebMmSO9/unlJ/efPXu2+Ne//iWEEKJnz55i6tSpQggh9uzZI/z9/YUQQjx48EBkZWUJIYS4fPmy8PLyEkII8ffff0vHflJUVJR46aWXRF5enkhMTBTW1tYiKipKZGVliebNm4s///xTCCHE6NGjxRdffKF3/eXLl0V+fr4YPny49P6e9Nlnn4mQkBAhhBAXL14ULVq0EFlZWWLt2rXi7bffll7Xv39/ERMTI4QQol69etL6c+fOiXbt2onk5GQhhBCpqalCCCECAwPFunXrhBBCrF69WgwaNEgIIURwcLB4+eWXRX5+vti5c6ewtLQUZ8+eFXl5ecLT01OcPn1aJCcnix49eojMzEwhhBALFy4Uc+fOFampqaJdu3YiPz9fCCHEvXv3ir2fOXPmCDc3N/Hw4UORnJwsmjdvLm7duiV+/PFHMX78eJGfny/y8vJE//79xeHDh8Xff/8tVCqVOHr0aLG2ntSqVSvpPRaej19++UVafuGFF8SJEydEVFSUGDdunLR+/fr10nls0KBBkTatra2LHacin+mePXuKGTNmCCGEWLJkiVCr1eL27dsiOztbNGvWTKSkpAgh/vd7++yzz8T8+fOFEELk5uaK+/fvi5MnT4oXX3xRiqPw3AYHB5f6+Ss8N8uWLRNCCLFixQrp/QcGBoojR44IIYTIyMgQOTk5QgghEhIShIuLS6nnuyTs8SIikllKSgqsra2lZSEEPvjgA7i5ueHFF1/ErVu3kJSUhF9++QVDhgxB3bp1YWVlJU0/lZ6ejrS0NGkWiMLembJ6ev/g4GD8/PPP0vahQ4cCKDq3a05ODsaPHw9XV1cMHz5cuuyky5EjRzB8+HCYmJjgueeeQ69evQCUPC/szz//rHP9pUuX0Lp1azg6OkKlUuG1117TebzC89ChQwe0atUKly9fLvM50TU/49GjR/Hqq68CKDjPR44ckfYZMGAAVCoVXF1dYWdnJw0+7ezsjPj4eBw7dgwXLlzA888/D41Gg8jISFy/fh1WVlbS4Knbt29H3bp1S4xp0KBBqFOnDho3boxevXrh+PHj2L9/P/bv3w8PDw94enri0qVLuHLlCgCgVatW6Nq1a5nfM1DydHG6pnvTN43S0+2W5zNd6Ml5gZ2dnaFWq2FhYQEHB4divXidOnXC2rVrER4ejj/++AOWlpZwcHDAtWvXMGnSJOzbtw9WVlZF9tH1OStU0mf/+eefx9SpU7Fs2TKkpaXBzKxgtkVbW1vcvn27zOekEAsvIiKZPT3f56ZNm5CcnIxTp04hLi4OdnZ20vaS/rMTZZhLsDIK5wgsnB8QAL744gvY2dnhzJkzOHnyJB4/flxqGyX9x12R9UDZ/sPXtf+T87UCKHGe1cL9y3KcJ1+jbw5bIQQCAgIQFxeHuLg4XLhwAatXr4aZmRmOHz+OoKAg7Ny5U+dN2rrmdnz//felNv/66y+MGzcOwP/m3i2P5s2bFyloEhIS0LRpU53rAcDOzk6a1SMxMRG2trbF2i3vZ7pQWeYFLlQ4n2+zZs0wevRorF+/HjY2Njhz5gz8/PywYsUKvP7660X2Ke1z9uTxn/zsz5w5E6tWrUJWVha6du0qXYKs6Py7LLyIiGRmY2ODvLw86T+i9PR02NrawtzcHDExMdIcob6+vtixYweysrKQkZGBXbt2AQCsra3RoEEDqfdF130muuboa9CgAWxsbKT7t8oyN2t6ejrUajVMTEywYcMGvU9j+vj44LvvvkN+fj6SkpKkabZ0zQtb2vq///4bV69eBQBs3ry5xOP5+vpK5+Hy5cu4ceMG2rdvD3t7e8TFxSE/Px83b97E8ePHpX3Mzc2lORJ1zc/YvXt3bNmyBUDBefbx8Sn1fT+pa9euiI2Nld7Tw4cPcfnyZWRmZiI9PR39+vXDkiVLEBcXV+L+0dHRyM7ORmpqKrRaLTp16oQ+ffpgzZo10r1it27dkuaXrYiBAwdi/fr1EELg2LFjaNCgAdRqNTp16oQrV67g77//xuPHj7FlyxapN2rgwIGIjIwEAERGRpY4DVx5P9MVUdJ8vikpKcjPz0dQUBA+/vjjYnP4VmRe4qtXr8LV1RXvvfcevL29pcKrovPvmpV7DyIiqrTevXvjyJEjePHFFzFq1CgMGDAA3t7e0Gg00tx/np6eePnll6HRaNCqVSv06NFD2n/t2rUIDQ1F3bp1pYnlnzZgwAAMGzYM0dHR+O9//1tkW2RkJCZMmICHDx/CwcEBa9euLTXet956C0FBQYiKikKvXr309q4EBQXh0KFDcHFxQbt27dClSxc0aNCgyLywubm56NSpEyZMmAALCwud6yMiItC/f380btwYPj4+OHfuXInxTZgwAa6urjAzM8O6detgYWGB559/Hq1bt4arqytcXFzg6ekp7RMWFgY3Nzd4enpi06ZN0vyMpqam8PDwwLp167Bs2TKEhoZi0aJFaNKkid7z9KQmTZpg3bp1GDlypHQD9/z582FpaYlBgwYhOzsbQgid8yd27twZ/fv3x40bNzB79mw0bdoUTZs2xcWLF9GtWzcABTeab9y4Ue/TscuWLcN//vMf/PPPP3Bzc0O/fv2watUq9OvXD3v37kXbtm1Rt25d6f2ZmZlh+fLl6NOnD/Ly8hAaGgpnZ2cABT1AI0aMwOrVq9GyZUtERUUVO15FPtPlpdVqsWjRIpibm6N+/fpYv349bt26hbFjx0q9nJ9++mmRfXR9/kqzZMkSxMTEwNTUFB07dsRLL70EAIiJiUH//v3LHTdHriciMoJnYf7OzMxM1K9fH6mpqejcuTNiY2Px3HPPGTusaiE8PBz169cv8YlHUgZfX19ER0fDxsamXPuxx4uIyAg8PDzQq1cv5OXlVflYXkoRGBiItLQ0PH78GLNnz2bRRTVGcnIypk6dWu6iC2CPFxEREZFseHM9ERERkUxYeBERERHJhIUXERERkUxYeBERERHJhIUXERERkUxYeBERERHJ5P8BzM62NSJG3OIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "base_rx = key_results[key_results['scenario'] == 'base']['thrombolysis_rate'].values\n",
    "scenario_rx = key_results[key_results['scenario'] == 'speed_onset_benchmark']['thrombolysis_rate'].values\n",
    "base_benfit = key_results[key_results['scenario'] == 'base']['additional_good_outcomes_per_1000_patients'].values\n",
    "scenario_benefit = key_results[key_results['scenario'] == 'speed_onset_benchmark']['additional_good_outcomes_per_1000_patients'].values\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots(1,2,figsize=(10,6))\n",
    "\n",
    "bins = np.arange(1,32)\n",
    "ax[0].hist(base_rx, bins = bins, color='k', linewidth=2,\n",
    "           label='control', histtype='step')\n",
    "ax[0].hist(scenario_rx, bins = bins, color='0.7', linewidth=2,\n",
    "           label='all in-hospital changes', histtype='stepfilled')\n",
    "ax[0].grid()\n",
    "ax[0].set_xlabel('Thrombolysis use (%)')\n",
    "ax[0].set_ylabel('Hospital count')\n",
    "ax[0].set_ylim(0,30)\n",
    "ax[0].yaxis.set_major_locator(MultipleLocator(5))\n",
    "ax[0].set_title('Thrombolysis use')\n",
    "ax[0].legend()\n",
    "\n",
    "ax[1].hist(base_benfit, bins = bins, color='k', linewidth=2,\n",
    "           label='control', histtype='step')\n",
    "ax[1].hist(scenario_benefit, bins = bins, color='0.7', linewidth=2,\n",
    "           label='all in-hospital changes', histtype='stepfilled')\n",
    "ax[1].grid()\n",
    "ax[1].set_xlabel('Clincial benefit\\n(additional good outcomes per 1000 admissions)')\n",
    "ax[1].set_ylabel('Hospital count')\n",
    "ax[1].set_ylim(0,26)\n",
    "ax[1].yaxis.set_major_locator(MultipleLocator(5))\n",
    "ax[1].set_title('Clincial benefit')\n",
    "ax[1].legend()\n",
    "\n",
    "plt.savefig('./output/histograms.jpg', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb37be30",
   "metadata": {},
   "source": [
    "### Find which change makes most difference in each hospital"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3752947",
   "metadata": {},
   "source": [
    "#### Best thrombolysis rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "46bee4e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "benchmark    83\n",
       "onset        39\n",
       "speed        10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pivot results\n",
    "results_pivot = (key_results[['thrombolysis_rate', 'scenario', 'stroke_team']].pivot(\n",
    "    index='stroke_team', columns='scenario'))\n",
    "results_pivot = results_pivot['thrombolysis_rate']\n",
    "# Limit to single changes\n",
    "cols_to_drop = ['speed_benchmark', 'speed_onset', 'onset_benchmark', 'speed_onset_benchmark']\n",
    "results_pivot.drop(cols_to_drop, axis=1, inplace=True)\n",
    "# Find largest effect\n",
    "best_result = results_pivot.idxmax(1)\n",
    "# Count\n",
    "best_result.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0787719d",
   "metadata": {},
   "source": [
    "#### Best outcomes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4c87d099",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "benchmark    56\n",
       "speed        49\n",
       "onset        27\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pivot results\n",
    "results_pivot = (key_results[['additional_good_outcomes_per_1000_patients', \n",
    "        'scenario', 'stroke_team']].pivot(index='stroke_team', columns='scenario'))\n",
    "results_pivot = results_pivot['additional_good_outcomes_per_1000_patients']\n",
    "# Limit to single changes\n",
    "cols_to_drop = ['speed_benchmark', 'speed_onset', 'onset_benchmark', 'speed_onset_benchmark']\n",
    "results_pivot.drop(cols_to_drop, axis=1, inplace=True)\n",
    "# Find largest effect\n",
    "best_result = results_pivot.idxmax(1)\n",
    "# Count\n",
    "best_result.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a3751b5",
   "metadata": {},
   "source": [
    "## Bar charts of individual changes at all hospitals\n",
    "\n",
    "Here we summarise the effect of individual changes at each hospital.\n",
    "\n",
    "Note that actual combined changes will be more than additive, but these plots give an indication of what the most significant effects will be across all hospitals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a062a022",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pivot results by scenario type\n",
    "results_pivot = key_results.pivot(index='stroke_team', columns='scenario')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cb137034",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hosp_per_chart = np.ceil(results_pivot.shape[0]/2)\n",
    "\n",
    "# Thrombolysis chart\n",
    "fig, axs = plt.subplots(2,1, figsize=(12,12), sharey=True)\n",
    "# 4 subplots\n",
    "i=0\n",
    "for ax in axs.flat:\n",
    "    # Get subgroup of data for plot\n",
    "    start = int(hosp_per_chart * i)\n",
    "    end = int(hosp_per_chart * (i + 1))\n",
    "    subgroup = results_pivot.iloc[start:end]\n",
    "    # Get effect of speed (avoid negatives)\n",
    "    speed = subgroup['thrombolysis_rate']['speed'] - subgroup['thrombolysis_rate']['base']\n",
    "    speed = list(map (lambda x: max(0,x), speed))\n",
    "    # Get effect of known onset (avoid negatives)\n",
    "    onset = subgroup['thrombolysis_rate']['onset'] - subgroup['thrombolysis_rate']['base']\n",
    "    onset = list(map (lambda x: max(0,x), onset))\n",
    "    # Get effect of decision (avoid negatives)\n",
    "    eligible = subgroup['thrombolysis_rate']['benchmark'] - subgroup['thrombolysis_rate']['base']\n",
    "    eligible = list(map (lambda x: max(0,x), eligible))\n",
    "    \n",
    "    x = range(start, start + subgroup.shape[0])\n",
    "    ax.bar(x, speed, color='b', label = 'Speed')\n",
    "    ax.bar(x, onset, color='g', bottom = speed, label = 'Onset known')\n",
    "    ax.bar(x, eligible, color='r', bottom = np.array(speed) + np.array(onset),\n",
    "           label = 'Benchmark decision')\n",
    "    ax.legend()\n",
    "    ax.set_xlabel('Hospital')\n",
    "    ax.set_ylabel('Increase in thrombolysis use (percentage points)')\n",
    "    # Put y tick label son all charts\n",
    "    ax.yaxis.set_tick_params(which='both', labelbottom=True)\n",
    "    \n",
    "    i += 1\n",
    "      \n",
    "plt.tight_layout(pad=2)\n",
    "plt.savefig('./output/all_hosp_bar_thrombolysis.jpg', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c6080dca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hosp_per_chart = np.ceil(results_pivot.shape[0]/2)\n",
    "\n",
    "# Outcomes chart\n",
    "fig, axs = plt.subplots(2,1, figsize=(12,12), sharey=True)\n",
    "# 4 subplots\n",
    "i=0\n",
    "for ax in axs.flat:\n",
    "    # Get subgroup of data for plot\n",
    "    start = int(hosp_per_chart * i)\n",
    "    end = int(hosp_per_chart * (i + 1))\n",
    "    subgroup = results_pivot.iloc[start:end]\n",
    "    \n",
    "    # Get effect of speed (avoid negatives)\n",
    "    speed = subgroup['additional_good_outcomes_per_1000_patients']['speed'] - \\\n",
    "        subgroup['additional_good_outcomes_per_1000_patients']['base']\n",
    "    speed = list(map (lambda x: max(0,x), speed))\n",
    "    # Get effect of known onset (avoid negatives)\n",
    "    onset = subgroup['additional_good_outcomes_per_1000_patients']['onset'] - \\\n",
    "        subgroup['additional_good_outcomes_per_1000_patients']['base']\n",
    "    onset = list(map (lambda x: max(0,x), onset))\n",
    "    # Get effect of decision (avoid negatives)\n",
    "    eligible = subgroup['additional_good_outcomes_per_1000_patients']['benchmark'] - \\\n",
    "        subgroup['additional_good_outcomes_per_1000_patients']['base']\n",
    "    eligible = list(map (lambda x: max(0,x), eligible))\n",
    "    \n",
    "    x = range(start, start + subgroup.shape[0])\n",
    "    ax.bar(x, speed, color='b', label = 'Speed')\n",
    "    ax.bar(x, onset, color='g', bottom = speed, label = 'Onset known')\n",
    "    ax.bar(x, eligible, color='r', bottom = np.array(speed) + np.array(onset),\n",
    "           label = 'Benchmark decision')\n",
    "    ax.legend()\n",
    "    ax.set_xlabel('Hospital')\n",
    "    ax.set_ylabel('Increase in good outcomes (per 1,000 admissions)')\n",
    "    # Put y tick label son all charts\n",
    "    ax.yaxis.set_tick_params(which='both', labelbottom=True)\n",
    "    \n",
    "    i += 1\n",
    "      \n",
    "plt.tight_layout(pad=2)\n",
    "plt.savefig('./output/all_hosp_bar_outcomes.jpg', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d1a9c5b",
   "metadata": {},
   "source": [
    "## Results for individual hospitals\n",
    "\n",
    "We may plot more detailed results at an individual hospital level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "400f5cbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_hospital(data, id):\n",
    "    \n",
    "    hospital_data = data.iloc[id]\n",
    "    \n",
    "    max_val = max(hospital_data['thrombolysis_rate'].max(),\n",
    "                  hospital_data['additional_good_outcomes_per_1000_patients'].max())\n",
    "    \n",
    "    max_val = 5 * int(max_val/5) + 5\n",
    "    \n",
    "    team = hospital_data.name\n",
    "    \n",
    "    # Sort results\n",
    "    \n",
    "    df = pd.DataFrame()\n",
    "    df['thrombolysis_rate'] = hospital_data['thrombolysis_rate']\n",
    "    df['outcomes'] = hospital_data['additional_good_outcomes_per_1000_patients']\n",
    "    order = {'base': 1, 'speed': 2, 'onset': 3, 'benchmark': 4, 'speed_onset': 5,\n",
    "    'speed_benchmark': 6, 'onset_benchmark':7, 'speed_onset_benchmark': 8}\n",
    "    df_order = [order[x] for x in list(df.index)]\n",
    "    df['order'] = df_order\n",
    "    df.sort_values('order', inplace=True)\n",
    "    \n",
    "    fig = plt.figure(figsize=(10,7))\n",
    "\n",
    "    ax1 = fig.add_subplot(121)\n",
    "    x = df['thrombolysis_rate'].index\n",
    "    y1 = df['thrombolysis_rate']\n",
    "    ax1.bar(x,y1)\n",
    "    plt.xticks(rotation=90)\n",
    "    ax1.set_title('Thrombolysis use (%)')\n",
    "    ax1.set_ylabel('Thrombolysis use (%)')\n",
    "    ax1.set_xlabel('Scenario')\n",
    "    ax1.set_ylim(0, max_val)\n",
    "    ax1.grid(axis = 'y')\n",
    "\n",
    "    ax2 = fig.add_subplot(122)\n",
    "    y1 = df['outcomes']\n",
    "    ax2.bar(x,y1, color='r')\n",
    "    plt.xticks(rotation=90)\n",
    "    ax2.set_title('Additional good outcomes\\nper 1,000 admissions')\n",
    "    ax2.set_ylabel('Additional good outcomes\\nper 1,000 admissions')\n",
    "    ax2.set_xlabel('Scenario')\n",
    "    ax2.set_ylim(0, max_val)\n",
    "    ax2.grid(axis = 'y')\n",
    "    \n",
    "    plt.suptitle(f'Scenario results for team: {team}')\n",
    "\n",
    "    plt.tight_layout(pad=2)\n",
    "    \n",
    "    plt.savefig(f'./output/hosp_results_{team}.jpg', dpi=300)\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbf6776c",
   "metadata": {},
   "source": [
    "An example where speed makes most difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "0514a7fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_hospital(results_pivot, 103)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a057a079",
   "metadata": {},
   "source": [
    "An example where determining stroke onset time makes most difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bc0423ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_hospital(results_pivot, 64)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95ce5a16",
   "metadata": {},
   "source": [
    "An example where applying benchmark decion-making makes most difference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "844f0efc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dsake+4YeXsr7gI2AbWzfLGlzym109bDvTZRb5VfU592v50ZgbUmLdBWd6wB/Bm5h9lXJK7rWdeKdl/dmovMA3A0s07X94+fymq4HnjDOeVaWtHxXcdsd87y4HrgfWKVe3R3B9s2U5hiduwK/kHRuRm6Yu1yxjYiImD8vBx4GNqbc1t8ceDLwa0p70d9R2lDuK2kxSa8Enta1/4nAmyVtLGkZSnvV8fwTeKykFcdZfyKwk6Tn1Tan76MUTuf18DqWp1xNvEPSynOJY6zzfrh2QFsT+H9d686nFJUflLS4ypBlOwMn1KuYJwKfkbS8pHWB9wLHdB13X0lrSXoMsP8EMYx7nrp+JvDKemX6iZSmBt3+SWnn23E4sGd9LxeRtKakJ9m+nvJ+flbSUpKeWo91bA/v0wi2b6K0of2CpBXqeZ4g6dkAkl6j2R34bqd8sHl4nMNFlxS2ERER8+dNlDayf7d9c+dB6Xi1O/AI8EpKJ63bKW1Kf9TZ2fbPgC8DvwL+Wr+OyfafKB2Xrq63rtcYtf4qSsetQyhXQ3cGdrb9QA+v48uU9ri3UEZ3+HkP+3QcROlMdQ3wC+D/KAU19dy7UNqS3gJ8A3hjfS1QOnndDVwN/IbSjOO7dd23KR2vLgYupOt9G62H83wJeIBSwB7FnIXogcBR9X3d1fYfKJ3YvgTcCZxDubIMpd3uNMrV2x8DB9g+c67v0tjeSGmOcQXl9+P/gNXruq2B8yX9BzgZ2M/2NfN5nqGikU1/IiIiIuaPpHcAr7Pda+eziIUqV2wjIiJivkhaXdIz6q30jShNIH7cdlwxvNJ5LCIiIubXEpTe/OsBd1DatX6jzYBiuKUpQkREREQMhDRFiIiIiIiBkMI2OvNbHzP3LSfl3NMkWdI8N4uR9Bx1zUk+n+ffXdIZC3KMyVSHAbpgPvfdV9LBCzumiIjJtiD/G+r+/5G0/ty3HHf/y+uwYTHFpLAdAvUPvPN4RNK9Xc93bzu+Ntk+1vYL245jAp+iTI0JgKQvS7pd0u/qmJGd5btL+sqofb8F7CHpcUTE0JD0KUmXSnpI0oFz2VaSPifp1vr4nzq5Q2f9NElnSbpH0p8kPX/U/q+vM5bdLekndRzc1tlezvbVC7D/U2yfvRBDioaksB0C9Q98OdvLAX+njG3YWTZPA0vP76fnmHeSVgd2AH5Snz8N2Ioya85vgA/X5SsC7wc+0b2/7fuAn1HGSoyIATNBPv4rZUrWn/ZwmL0oE01sBjwVeCmwd9f64ymzkD0W+Cjwf5JWred/CqXj2BuA1SjT9KbjWLQqhW10LCHpe5Jm1Vsw0zsrJF0r6UOSLgHurjPo7FK3u0PS2ZKePGr7D0i6pH6KP1zSapJ+Vo//izqTTLe3SLpR0k2S3td1rCXrVcob6+PLkpYcHXw93w9HLTtE0pfr92+WdHU9/zWdK9V1+W/q95L0JUn/knRnjX+Tsd6s+hqf3/X80eYcKjPSHFOvftwh6Y+SVqvrVqzvx02SbpD0aY0/H/sLgAtrgQql1/FvbN8P/JLZM+V8Bvhf23eOcYyzgZ3GOX5EtKDmjw9LuqLegTlC0lJd618qaWbNH+epzHDVve+IfDz6+LaPqpM/zBq9bgxvAr5g+x+2bwC+QJlQAkkbAltSJiG41/YPgUuBV9V9dwdOsX2u7f8AH6fM8LX8OK97f0l/q3n4Ckmv6Fq3qKTPS7pF0tWMylv1/8yn6/vxH0mnSHqspGMl3VXz7LSu7a0yyxiSdqznm1Xz7vvr8lUknVrf59sk/VrSIl3v8/Pr9+P+H1JtEifpffV/x02S9uyKY8xzx+RJYRsdu1CGaVmJMsvJ10at342SaFaiFFTHA+8BVgVOA06RtETX9q+iFGYbUmbA+RnwEWAVyu/dvqOOvwOwAfBCYP+uovGjwLaUqSo3o0xH+bEx4j8GeLGkleDRKxmvBY6WtCzwVeAltpcHtqNMsTjaC4Fn1ZhXqvvfOsZ2c/MmYEXKPOePBfahTFcJZdabh4AnAlvUc75tnONsClzV9fxy4Jkq89M/D+h8ANnI9nHjHONKyvsWEf1ld+BFwBMoOedjAJK2pMy+tTclfxwGnDzqA/2j+dj2QwsYx1Mos3t1XFyXddZdbXvWBOsf3df23ygzfG04zrn+BjyTkh8/CRyjcmcK4O2Uq8VbANOBV4+x/+soV4fXpLxvvwOOAFam5LrxpgI+HNi75v9NmD3D2/sos6atSrni/BHK1LWjze3/0OPra1qTMsXu17su3ox37pgkKWyj4ze2T6vzdx/NnMXQV21fb/teSsH3U9tn2n6Q0gZ0aUrB2HGI7X/WKwC/Bs63fVG92vhjSvLq9knbd9u+lJKodqvLdwcOsv0v2/+mJMM3jA6+zrt9LvCauujFwC22Z9TnjwCbSFra9k22Lx/jPXiQMmf6kyhD4V1ZjzuvHqT8Q3qi7Ydtz7B9V71q+xLgPfW1/osyZePrxjnOSnRdcbF9GfBDypSX6wCfA75CmU99X0nn1qsXK3UdYxYl4UZEf/lazam3Ue66dHLe24HDbJ9f88dRlClqt+3atzsfL6jlKNPGdtwJLCdJY6zrrF9+nH1Hrx/B9g9s32j7EdvfB/5CKRIBdgW+3PWefHaMQxxh+2/17tTPgL/Z/kUt7n/AnP9XOh4ENpa0gu3bbV/YtXx1YF3bD9r+tcceA3Vu/4cerOsftH0a8B9go7mcOyZJCtvouLnr+3uApUbd4rq+6/s1gOs6T2w/Utev2bXNP7u+v3eM58uNOn/38a+r55jjXKPWjXYUZa506teja3x3U4rxfYCbJP1U0pNG72z7V5Qr1V8H/inpW5JWGOdcEzmaMsf5CfW21f9IWpwy1/jiNYY7JN1BuRozXueu2xn1D8L2l2xvZvu19TX9mvJ3vBflKu6VwP5duyzPnP94IqJ94+W8dYH3dXJEzRNrMzLvde+7oP4DdOe5FYD/1AJv9LrO+lnj7Dt6/QiS3tjVxOIOyhXMVerqNZjzPRltXv+vdLwK2BG4TtI5kp5el/8vpT3yGSpN1fYfZ/+5/R+6ddSV83u6Yhnv3DFJUthGr7o/xd5ISb5AaZtKSbw3LMDx1+76fp16jjnONWrdaD8BnqrSLvalwKMd42yfbvsFlE/nfwK+PdYBbH/V9laUW2wbAh8Y51x3A8t0PX981zEetP1J2xtTrmK/lNKB63rKlZdVbK9UHyvYfgpju4RxbunVq797AwdR/jlcUq+e/5HSAaTjyYy8zRgR/WG8nHc98JmuHLGS7WVsH9+1/cKcWelyRt6h26wu66xbf1Sb2dHrH91XZXitJYE/jz6JpHUpeff/AY+1vRJwGdAZgeEm5nxPFgrbf7T9MspFhJ8AJ9bls2y/z/b6lCZz75X0vDEOMS//h3o6d0yeFLYxP04EdpL0vHol8n2Ugu28BTjmxyUto9LLdk/g+3X58cDHJK0qaRVKz/8xx9ytnaz+DzgO+IPtv0MpAlU6uy1b4/wP8PDo/SVtLWmb+pruBu4ba7tqJvA6SYvXdq6PtgeTtIOkTVU6hd1FuRX1cG3WcAbwBUkrqMyt/gRJzx7nHGcCW6qrU0mXL1I6dNwDXANsLWk54DlA9xA3z6bcsouI/vIuSWupDI/1EWbnvG8D+9RcJEnLStpJ43TIGkvNS0tR/scvptKhddG6rjM+7LS6+fcoBd2aktag5PMjAWz/mZLrDqjHeAXlg3Ono+6xwM6Snlnz60HAj0a1ye1YllKQ/7vGsSflQ3nHiZRmVWvV9qnjXT2dJ5KWUBkOccX64f8ual5X6aT3xHpxprN8rJzf8/+hXs8dkyeFbcwz21dRbvUfAtxC+aS7s+0HFuCw51BuCf0S+LztzqQJnwYuoFy9vBS4sC4bz1GUTldHdy1bhJKsbwRuoxR77xxj3xUo/1Rup9xqupWuMWRH+Til88LtlPZW3Z23Hk8psO+iNA04h9lJ8I2UudWvqPv+H+Uq8hxs/5PS0eBl3csl7UDpNPLjut0fKMP6XE/phHdw3W4pyi2wo8Z5DRHRnuMoH3Svro9PA9i+gNLO9muUHPFX6igF8+DblFvzu1E6Pt3L7Daha1PyW+cO22HAKZT8ehkllxzWdazXUTpz3U7JLa+u7UypfRX2oRS4/6I0fRort2L7CsqIC7+jNCHYFPjtqJhPp9xhuhD40Ty+5om8AbhW0l013k6TtQ2AX1AudvwO+IbHHrt2Xv8P9XLumCQau510xNQkaR1KU4PH276r7XgWlKSNKYXp08bp1DDRvu8G1rb9wUkJLiLmi6RrgbfZ/kUL5/4Y8G/bh81144gpKIVtDAyV8Qe/CKxg+y1txxMRMZY2C9uIQTdpTREkra0yDd+VKgP571eXH6gySPHM+thxsmKI4VHbd91FGTt3vLEMI4ZS8nFEDItJu2KrMujy6rYvrI3eZ1Cm7duVMpTIeG0XIyJiIUo+johhMd480wus9gC/qX4/S9KVjBznNCIiGpB8HBHDopFREeqwIlsA59dF/0/SJZK+q9nTzkVExCRLPo6IQTbpncfq2JrnUAac/lEdWP4Wynh2n6LcHpujo4+kvSizKbH00ktvtfbaa4/eJCKiMX/+859vsb1q23EsiOTjiBgEE+XjSS1s60D3pwKn2/7iGOunAafa3mT0um7Tp0/3BRdcMDlBRkT0QNIM29PbjmN+JR9HxKCYKB9P5qgIAg4HruxOorUTQ8crKANCR0TEJEk+johhMWmdx4BnUGbcuFTSzLrsI8Bukjan3Pq6ljLffURETJ7k44gYCpM5KsJvAI2x6rTJOmdERMwp+TgihkUjoyJEREREREy2FLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDYbG2A4iIdk3b/6eNnevag3dq7FwRETF8csU2IiIiIgZCCtuIiIiIGAgpbCMiIiJiIKSwjYiIiIiBkMI2IiIiIgZCCtuIiIiIGAgZ7isi+kKGHYuIiAWVK7YRERERMRBS2EZERETEQJi0wlbS2pLOknSlpMsl7VeXryzpTEl/qV8fM1kxRERE8nFEDI/JvGL7EPA+208GtgXeJWljYH/gl7Y3AH5Zn0dExORJPo6IoTBpha3tm2xfWL+fBVwJrAm8DDiqbnYU8PLJiiEiIpKPI2J4NNLGVtI0YAvgfGA12zdBSbbA45qIISIiko8jYrBN+nBfkpYDfgi8x/Zdknrdby9gL4DVVluNs88+e9JijBhm79v0ocbONdHfcb/EMciSjyNi0Mn25B1cWhw4FTjd9hfrsquA59i+SdLqwNm2N5roONOnT/cFF1wwaXFGDLN+GT+2X+IYj6QZtqdPQjiNSD6OiEExUT6ezFERBBwOXNlJotXJwJvq928CTpqsGCIiIvk4IobHZDZFeAbwBuBSSTPrso8ABwMnSnor8HfgNZMYQ0REJB9HxJCYtMLW9m+A8RpwPW+yzhsRESMlH0fEsMjMYxERERExEFLYRkRERMRASGEbEREREQMhhW1EREREDIRJn6AhIiIiIqaQHidvWSgW8nwKuWIbEREREQMhhW1EREREDIQUthERERExEFLYRkS0RNJrJC1fv/+YpB9J2rLtuCIipqoUthER7fm47VmStgdeBBwFHNpyTBERU1YK24iI9jxcv+4EHGr7JGCJFuOJiJjSUthGRLTnBkmHAbsCp0lakuTliIj5lgQaEdGeXYHTgRfbvgNYGfhAqxFFRExhKWwjIlpi+x7gX8D2ddFDwF/aiygiYmpLYRsR0RJJBwAfAj5cFy0OHNNeRBERU1sK24iI9rwC2AW4G8D2jcDyrUYUETGFpbCNiGjPA7YNGEDSsi3HExExpaWwjYhoz4l1VISVJL0d+AXw7ZZjioiYshZrO4CIiGFl+/OSXgDcBWwEfML2mS2HFRExZc21sJU0HXgmsAZwL3AZ8Avbt01ybBERA8/2mZLOp+ZjSSuPl18l7QccAcwCvgNsAexv+4ym4o2I6GfjNkWQ9GZJF1J66y4NXMXsYWnOlHSUpHWaCTMiYvBI2lvSP4FLgAuAGfXreN5i+y7ghcCqwJ7AwZMeaETEFDHRFdtlgWfYvneslZI2BzYA/j4JcUVEDIP3A0+xfUuP26t+3RE4wvbFkjTRDhERw2Tcwtb21yfa0fbMhR5NRMRw+RtwzzxsP0PSGcB6wIclLQ88MimRRURMQT13HpO0M/AxYEngW7a/MWlRRUQMhw8D59U2tvd3Ftred5zt3wpsDlxt+x5Jj6U0R4iICCYobCVtZvvirkVvALal3Aq7GEhhGxGxYA4DfgVcSg9XXm0/Utvkbiwpo9pERIwyUWJ8Z2279QnbNwPXA5+hJN8bmwguImLAPWT7vb1uLOlzwGuBK4CH62ID505CbBERU85EbWz3lrQZcJikC4CPA9sBywCfaii+iIhBdpakvYBTGNkUYbzhFF8ObGT7/nHWR0QMtQlvZdWmCC+r7WtPBo6yfXQjkUVEDL7X168f7lpmYP1xtr8aWJyuIjgiImabqI3tPsDelCT7P8CLKc0TTgc+bfvXzYQYg2Ta/j9t7FzXHrxTY+eKmB+215vHXe4BZkr6Jb11NouIGCoTtrG1/VRJSwC/s30C8FVJR1OaJaSwjYhYAJIWB94BPKsuOhs4zPaD4+xycn1ERMQYJipsb5D0KcqsY3/qLLR9O9BzZ4eIiBjXoZSmBZ1RZt5Ql71trI1tH1UvNmxYF101QREcETF0JipsXwa8CHgQOLOZcCIihsrWtjfrev4rSRePt7Gk5wBHAddShl5cW9KbbGdUhIgIJi5s17B9yngr61Bga9r+x8IPKyJiKDws6Qm2/wYgaX1mD+M1li8AL7R9Vd1+Q+B4YKtJjzQiYgqYqLD9X0mLACcBM4B/A0sBTwR2AJ4HHACksI2ImD8foAz5dTXlCuy6TDyT2OKdohbA9p9rO92IiGDicWxfI2ljYHfgLcDqlB65VwKnAZ+xfV8jUUZEDCDbv5S0AbARpbD901zGqL1A0uFAZ9jF3SkXHiIigrmPY3sF8NGGYokYKhn6LCS9CzjW9iX1+WMkvdX2eFOWvwN4F7AvpRA+l0xvHhHxqEXaDiAiYoi93fYdnSd11Jm3j7ex7fttf9H2K22/wvaXMgtZRMRsE16xjYiISbWIJNk2gKRFgSVGbyTpRNu7SrqUMmnOCLafOvmhRsSkk5o7l+dIJQMhhW1ERHvOAE6U9E1KwboP8PMxttuvfn1pU4FFRExFcy1s67BeuwPr2z5I0jrA423/YdKji4gYbB8E9qK0nRWl0P326I1s31S/vQW41/YjdaivJwE/ayjWiIi+10sb228ATwd2q89nAV+ftIgiIobHu21/0/arbb/K9mHAuyfY/lxgKUlrAr+kDA12ZANxRkRMCb0UttvYfhdwHzzauWGONmARETHP3jTGsjdPsL1s3wO8EjjE9iuAjScjsIiIqaiXwvbB2qGh07lhVeCRue0k6buS/iXpsq5lB0q6QdLM+thxviOPiJiiJO0m6RRgPUkndz3OAm6deFc9ndI8rDNeXC9NypKPI2Io9NJ57KvAj4HHSfoM8GrgYz3sdyTwNeB7o5Z/yfbn5yXIiIgBcx5wE7AKZZrcjlnAJRPs9x7gw8CPbV9ep+A9q4fzHUnycUQMgbkWtraPlTSDMoWugJfbvrKH/c6VNG3BQ4yIGCy2rwOuo/RfmJf9zgHOAahTnt9ie98e9ks+joihMNemCJKeAFxj++vAZcALJK20AOf8f5IuqbfGHrMAx4mImNIkzZJ0V33cJ+lhSXdNsP1xklaQtCxwBXCVpA8sQAjJxxExUOS5DNAraSYwHZhGGV/xFGAj23Ntj1WvEJxqe5P6fDXKcDUGPgWsbvst4+y7F2UYHFZbbbWtTjjhhJ5eUPS3S2+4s7Fzbbrmio2da370y3uROHqzww47zLA9fRLCeZSklwNPs/2RcdbPtL25pN2BrYAPATN6maAh+ThiCpgxo7lzbbVV/8cxjonycS+F7YW2t5T0Qcr4iYdIusj2FnM78ehE2uu60aZPn+4LLrhgbpvFFDBt/5/OfaOF5NqDd2rsXPOjX96LxNEbSZNe2Nbz/N72tuOsuxzYHDgO+JrtcyRdbHuzHo47jeTjiP7WLzOP9Usc45goH/fSeexBSbsBbwR2rssWn+coSiCrdw00/gpK04aIiKEk6ZVdTxeh3B2bKMsfBlwLXAycK2ldYNymC3M5d/JxRAycXgrbPSnTPH7G9jWS1gOOmdtOko4HngOsIukfwAHAcyRtTknc1wJ7z1/YEREDYeeu7x+i5MWXjbex7a9SRqrpuE7SDnM7SfJxxFz0+RXK6F0voyJcAezb9fwa4OAe9tttjMWHz1N0EREDzPaevWwnaQ/bx0h67zibfHEu50k+joih0MvA3tcwxq0x2+tPSkQREUNC0lrAIcAzKHn2N8B+tv8xatNl69flGwwvImLK6aUpQnfj3KWA1wArT044ERFD5QhKR7DX1Od71GUv6N7I9mH16ycbjS4iYorppSnC6OkdvyzpN8AnJiekiIihsartI7qeHynpPeNtXPs4vJsy/OKj+dv2LpMVYETEVNJLU4Qtu552eu3mdlhExIK7RdIewPH1+W7A6IsJ3X5CaRt7CvDI5IYWETH19NIUoXse84eAa4BdJyeciIih8hbga8CXKG1sz6vLxnNfHRkhIiLG0EtThLkOJRMREfPO9t+BeWlG8BVJBwBnAPd3HefChR1bRMRU1MsV24iI6A+bAm8AnsvspgiuzyMihl4K24iIqeMVwPq2H2g7kIiIfrRI2wFERETPLgZWajuIiIh+1cuoCK8Bfm57lqSPAVsCn06broiI+TPBDGIA2B5vJrHVgD9J+iMj29hmuK+ICHprivBx2z+QtD3wIuDzwKHANpMaWUTE4OoMmbgRsDVwcn2+M3DuBPsdMJlBRURMdb0Utg/XrzsBh9o+SdKBkxdSRMRg68wgJukMYEvbs+rzA4EfTLDfOY0EGBExRfVS2N4g6TDg+cDnJC1J2uZGRCwM6wDdHcEeoMwqNoKkWZTRD8Zke4WFHllExBTUS2G7K/Bi4PO275C0OvCByQ0rImIoHA38QdKP6/OXA0eN3sj28gCSDgJurvsJ2J3MBBkR8ahxC1tJK9i+C1gKOLsuW5nSYeGCRqKLiBhgtj8j6WfAMylXZPe0fdEEu7zIdnf/hkMlnQ/8z2TGGRExVUx0xfY44KXADErCVdc6A+tPYlwREcPiYcpkC2b2pAvjbitpd+CEuv1uzO4HEREx9MZtK2v7pfXrerbXr187jxS1ERELSNJ+wLHAKsDjgGMkvXuCXV5PaR72z/p4TV0WERH0No7tM4CZtu+WtAdlHNsv1znOIyJi/r0V2Mb23QCSPgf8DjhkrI1tXwu8rLHoIiKmmF46jx0KbCZpM+CDwOGUjgvPnszAIiKGgBjZlOBhRjb7GrmxtBSlGH4Kpf8DALbfMlkBRkRMJb0M2/WQbVOuEnzF9ldIL9yIiIXhCOB8SQdK+iTwe8rFg/EcDTyeMlnOOcBawKxJjzIiYoro5YrtLEkfBvYAniVpUWDxyQ0rImLw2f6ipLOB7euiuY2K8ETbr5H0MttHSToOOH3SA42ImCJ6uWL7WsoQX2+1fTOwJvC/kxpVRMTweJjZIyLMbVSEB+vXOyRtAqzIGBM6RPREau4R0ZBeCttXA0fY/jWA7b/b/t7khhURMfjmY1SEb0l6DPAx4GTgCuBzkx5oRMQU0UtThMcDf5R0IfBd4PTa5jYiIhbMvI6K8J367blkLPGIiDnM9Yqt7Y8BG1A6NLwZ+Iuk/5b0hEmOLSJi0M3TqAgRETGxXq7YYtuSbqbMUf4Q8Bjg/ySdafuDkxlgRMQA64yK8OP6/OVMPCpCRERMoJcJGvYF3gTcAnwH+IDtByUtAvyFMrZtRETMo1GjIoi5j4oQERET6OWK7SrAK21f173Q9iOSXjo5YUVEDD5JKwPX1kdn2eK2Hxxj2xWBF1NGpjFwI6XPwx1NxBoRMRWM28ZW0so16X6ZMpbtyt0PANtXNhRnRMQguhD4N/Bnyh2wfwPXSLpQ0ladjSS9sW77HGAZYFlgB2BGXRcREUx8xXYG5aoAzNmZwaRHbkTEgvo58GPbpwNIeiHlquyJwDeAbep2HwW2Gn11tg79dT6QIRgjIpigsLW9XpOBREQMoem29+k8sX2GpP+2/V5JS3ZtJ2ZfaOj2CBlFISLiUT2NiiBpF+BZ9enZtk+dvJAiIobGbZI+BJxQn78WuL1OXd49C9lngAslnQFcX5etA7wA+FRTwUZE9Lu5jmMr6WBgP8oMN1cA+0n67GQHFhExBF4PrAX8pD7WrssWBXbtbGT7KGA6cA5livMHgLMpV3yPbDDeiIi+1ssV2x2BzW0/AiDpKOAi4MOTGVhExKCzfQsw3hS6fx217e3ACbXzruvziIjoMtcrttVKXd+vOAlxRETEOCStI+kESf+idBb7o6R/1WXTWg4vIqJv9HLF9rPARZLOonRSeBa5WhsR0aTvU4Ze3N32wwC1He5rKO1zt20vtIiI/jHXwtb28XVmnK3rog/ZvnlSo4qIiG6r2P5+94Ja4J4gKZ3HIiKqnkZFAJ5OmfLRlE4NP55484iIGI+kQxh7+C4AbO87atEMSd8AjmL2qAhrU6Y7zxS8ERHVXAvbmkyfCBxfF+0t6fm23zWpkUVEDK4L5nH7NwJvBT5JmVJXwD+Ak4HDF25oERFTVy9XbJ8NbGLb8OioCJdOalQREQOsDt81L9s/ABxaHxERMY5eCturKAOBX1efrw1cMmkRRUQMCUmrAh8CNgaW6iy3/dwxtn0R8HLKFVsDNwIn2f55I8FGREwB4xa2kk6hJM8VgSsl/aE+3wY4r5nwIiIG2rGUEQ92AvahtJn99+iNJH0Z2BD4HqUJApSJHfaV9BLb+zUSbUREn5voiu3nF+TAkr4LvBT4l+1N6rKVKUl8GnAtsGsGGY+IIfZY24dL2s/2OcA5ks4ZY7sdbW84eqGk7wN/pswOOa7k44gYFuNO0GD7nO4HpeftpV2PuTkSePGoZfsDv7S9AfDL+jwiYlg9WL/eJGknSVtQrsSOdp+kp42xfGvgvh7OcyTJxxExBHoZFWEv4FPAvcAjlN64BtafaD/b544xI87LgOfU74+izHX+oXkJOObPtP1/2ti5rj14p8bOFTHFfVrSisD7gEOAFYD/GmO7NwOHSlqe2U0R1gbuqusmlHwcEcOil85jHwCeUuc0X1Cr2b4JwPZNkh63EI4ZMc9S6Ec/sH1q/fZOYIcJtrsQ2EbS4+ka7msBJ8tJPo6IgaM6itf4G0g/B15p+555Pni5QnBqV5uuO2yv1LX+dtuPGWffvYC9AFZbbbWtTjjhhHk9fXS59IY7GzvXpmuumDh6iKMfYkgcvdthhx1m2J6+MOOooyK8ndLO9dELDbbf0uP+qwO32b6/h22nkXwc3WbMaO5cW23V3LnmR7+8F4mjJxPl414K2y2AI4DzgUeT5xgz44y17zRGJtKrgOfUqwOrA2fb3mhux5k+fbovuGBexzOPbv1yhTJx9FcMiaN3kiajsD0P+DUwA3i4s9z2D3vc/xfAE4Af2n7/XLadRvJxdJOaO9dcao3W9ct7kTh6MlE+7qUpwmHArygdxh6Z57OPdDJlOJuD69eTFvB4ERFT2TK257tdq+3nSxJlHNx5lXwcEQOnl8L2IdvvndcDSzqe0jFhFUn/AA6gJNATJb0V+Dvwmnk9bkTEADlV0o62T1uAYyxr+/KJNkg+johh0Uthe1ZtX3UKI5si3DbRTrZ3G2fV83oPLyJioO0HfETSA8we+su2V5iHY1xBmR1yXMnHETEseilsX1+/frhr2VyH+4qIiInZXr6X7SSNd9dMwHILL6KIiKltroWt7fWaCCQiYhhJ2gV4Vn16dtcQYN3+G/hf4KEx1o070U5E3+vzTkox9fQyQcPiwDvoSrzAYbYfHHeniIiYK0kHU2YPO7Yu2k/S9rZHzwJ2IfAT23OMwSPpbZMcZkTElNFLU4RDgcWBb9Tnb6jLkkwjIhbMjsDmth8BkHQUZfry0YXtnsCt4xxjoQ5BFhExlfVS2G5te7Ou57+SdPFkBRQRMWRWAjqdccecOcL2VePtbPufkxBTRMSU1Eth+7CkJ9j+G4Ck9ekaSDwiIubbZ4GLJJ1F6Qj2LEZ21I2IiHnQS2H7fsqQX1dTEu+6lNtiERGxAGwfL+lsSjtbAR+yfXO7UUVETF0TFraSFgU2AzYANqIk3j/1Mi95RESMTdKTbP9J0pZ10T/q1zUkrWH7wjH2WRTY1/aXGgs0ImKKmbCwtf2wpF1qIr2koZgiIgbde4G9gC+Msc7Ac+dYWPLxy4AUthER4+ilKcJ5kr4GfB+4u7NwrCsKERExd7b3qt++xPZ93eskLTXBrr9NPo6IGF8vhe129etBXcvGvKIQERHz5Dxgyx6WdSQfR0RMoJeZx3ZoIpCIiGEh6fHAmsDSkrag9F8AWAFYZrz9ko8jIibWy8xjSwKvAqZ1b2/7oPH2iYiICb0IeDOwFvDFruWzgI+Mt5Ok1SjT665h+yWSNgaebvvwSYw1ImLK6KUpwknAncAMIKMhREQsINtHAUdJepXtH87DrkcCRwAfrc//TGlvm8I2IoLeCtu1bL940iOJiBgSkvawfQwwTdJ7R6+3/cUxdgNYxfaJkj5ct3tIUibMiYioeh0VYVPbl056NBERw2HZ+nW5edzvbkmPpXQYQ9K2lDtqERHBBIWtpMuAR+o2e9aZx+6ndHKw7ac2E+L8mbb/Txs717UH79TYuSJi6rN9WP36yXnc9b3AycATJP0WWBV49UIOLyJiyproiu2awOYNxRERMTQkfXWi9bb3HWf5hZKezeyZIK+y/eAkhBgRMSVNVNheY/u6xiIZULlyHBFjmFG/PgPYmNIBDOA1XevmUCdveCewPaU5wq8lfXP0JA8REcNqosL2cWN1auiYoHNDRERMoI6KgKQ3Azt0rrpK+iZwxgS7fo8yJNgh9fluwNGUgjgiYuhNVNguSunYoAm2iYiI+bcGsDxwW32+XF02no1sb9b1/CxJF09WcDFJ1OC/Vbu5c0X0gYkK25syCUNExKQ6GLhI0ln1+bOBAyfY/iJJ29r+PYCkbYDfTm6IERFTx0SFba7URkRMIttHSPoZsE1dtL/tmyfYZRvgjZL+Xp+vA1wp6VKmwGg1ERGTbaLC9nmNRRERMUQkbTlq0fX16xqS1rB94Ti7ZrKciIgJjFvY2r5tvHUREbFAvlC/LgVMBy6m3CV7KnA+ZdSDOWSkmoiIiS3SdgAREcPG9g62dwCuA7a0Pd32VsAWwF/bjW6ASc09IqIVKWwjItrzpO7pym1fRibGiYiYbxO1sY2IiMl1paTvAMdQJlzYA7iy3ZAiIqauFLYREe3ZE3gHsF99fi7wjfbCiYiY2tIUISKiJbbvs/0l26+w/Qrgj0BmdYyImE+5YhsR0SJJm1Omxn0tcA3wo1YDioiYwlLYRkQ0TNKGwOsoBe2twPcB1ZESIiJiPqWwjYho3p+AXwM72/4rgKT/ajekiIipL21sIyKa9yrgZuAsSd+W9DwyjXlExAJLYRsR0TDbP7b9WuBJwNnAfwGrSTpU0gtbDS4iYgpLYRsR0RLbd9s+1vZLgbWAmcD+7UYVETF1pY1tREQfsH0bcFh9DJYmp5i1mztXRPSdXLGNiIiIiIGQwjYiIiIiBkIK24iIiIgYCClsIyIiImIgpLCNiIiIiIHQyqgIkq4FZgEPAw/Znt5GHBERwy75OCIGSZvDfe1g+5YWzx8REUXycUQMhDRFiIiIiIiB0FZha+AMSTMk7dVSDBERkXwcEQNEbmGWFklr2L5R0uOAM4F32z531DZ7AXsBrLbaaludcMIJ83SOS2+4c2GFO1ebrrli4kgc8xxHP8SQOHq3ww47zBjE9qdN5GNmzFhI0fZgq60Sx1SKox9iSBz9G8c4JsrHrRS2IwKQDgT+Y/vz420zffp0X3DBBfN03Gn7/3QBI+vdtQfvlDgSxzzH0Q8xJI7eSRrIwrbbZOXjvplSN3H0Xxz9EEPi6N84xjFRPm68KYKkZSUt3/keeCFwWdNxREQMu+TjiBg0bYyKsBrwY5VPA4sBx9n+eQtxREQMu+TjiBgojRe2tq8GNmv6vBERMVLycUQMmgz3FREREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEVgpbSS+WdJWkv0rav40YIiIi+TgiBkvjha2kRYGvAy8BNgZ2k7Rx03FERAy75OOIGDRtXLF9GvBX21fbfgA4AXhZC3FERAy75OOIGChtFLZrAtd3Pf9HXRYREc1KPo6IgbJYC+fUGMs8x0bSXsBe9el/JF01qVHNtgpwy7zsoM8NbBzzHEPi6M84Bvh3tMk41p2vvfpbP+fj+fp7Q2O9pMSROCYlhsSxoDHMfxzj5uM2Ctt/AGt3PV8LuHH0Rra/BXyrqaA6JF1ge3rT5+3HOPohhsSROKZKHFNU3+bjfvm5Jo7EkTimTgzQTlOEPwIbSFpP0hLA64CTW4gjImLYJR9HxEBp/Iqt7Yck/T/gdGBR4Lu2L286joiIYZd8HBGDpo2mCNg+DTitjXP3oPHmD+Pohzj6IQZIHKMljpH6JY4pqY/zcb/8XBPHSIljpMQxWz/EgOw5+glEREREREw5mVI3IiIiIgZCCtuIiIiIGAgpbGPKkLRk2zG0ZazXLmnlNmKJiEg+nmNZ8nGfSGFbSVpa0kYtnHfLiR4txPOaXpY1EMd3Rz1fjhY6uEjar5dlDfiRpMW7YlgdOLPpICS9ZIxl+7QQx1vHWHZw03HEwtdWLq7nTj4eO47k45GSj0ees6/ycQpbQNLOwEzg5/X55pKaGsvxC/XxdeB8Sq/Cb9fvv9pQDN0+3OOyyXaDpEMBJD0GOAM4poU43jTGsjc3HQTwE+AHkhaVNI0yPFMbP5ePS3pu54mkDwEvayGOV0vavSuObwCrthBHLEQt52JIPh5P8vFIPyH5uFtf5eNWhvvqQwcCTwPOBrA9s/6yTjrbOwBIOgHYy/al9fkmwPubiKGe7yXAjsCakroT+ArAQ03F0WH745I+J+mbwFbAwbZ/2NT5Je0GvB5Yb9Q/1uWBW5uKo8P2t+sA+j8BpgF72z6v6TiAXYBTJX0AeDHwpLqsaa8ETpb0CPAS4Dbb72whjli4DqSlXFzPl3w8huTjkZKP59BX+TiFbfGQ7Ts1OfM39+pJnSQKYPsySZs3eP4bgQsofxQzupbPAv6rqSAkvbLr6R+Aj9evlvRK2z9qKJTzgJsoc19/oWv5LOCShmJA0nu7n1KmP50JbCtpW9tfbCoWANu3SNoF+AXl9+TVbnDMwFHt2N5G+cfyW+AgSSvbvq2pWGJS9EMuhuRjIPl4tOTjkfo1H2ccW0DS4cAvgf2BVwH7AovbbqytiqTjgbspt3cM7AEsZ3u3pmKocSxO+cCzju2rmjx3Pf8RE6y27bc0FkwlaV1gA9u/kLQ0sJjtWQ2d+4CJ1tv+ZENxzKL8XnYsQbly5BKGV2gojmtGxdFdAdn2+k3EEZOjH3JxjSP5mOTjMc6dfDwyjr7MxylsAUnLAB8FXkj5wZwOfMr2fQ3GsBTwDuBZddG5wKFNxlDj2Bn4PLCE7fXqVYqDbDd2e0PSosC+tr/U1DkniOXtwF7AyrafIGkD4Ju2n9dgDItSbv19oKlzjhOHgLVt/73lOBYBnm77t23GEQtfP+TiGkfy8ewYko9HxpB8PDKOvsvHKWxHqb+0y9q+q4VzL01Ln8y7YpgBPBc42/YWddkltp/acBxnddq7tUnSTEqbv/O73o9LbW/acBy/bDJ5TxDHDNtb9UEcv7P99LbjiMnTZi6u508+nh1H8vHIOJKPR8bRV/k4oyIAko6TtIKkZYHLgatqY+wmY9iFdnsDdzxk+84WzjvaeZK+JumZanG4HeB+2w90nkhajJG3XpoyU9LJkt4g6ZWdRwtx/F7S1i2cd7QzJL1KfdAYMxaefsjFNY7k45GSj0dKPh6pr/JxOo8VG9u+S2W4itOAD1EaYv9vgzEcQIu9gbtcJun1wKL1Ns++lIb7Tduufj2oa5kpVy+adI6kjwBLS3oB8E7glIZjAFiZ0vu3+/UbaKrzRscOwN6SrqO0QRSlLVWjV5CA9wLLAg9Juq8rjkbalsWk6YdcDMnHoyUfj5R8PFJf5eMUtsXitZH+y4Gv2X5QUtOfAvulN/C7KW3c7geOp7ZxazqIfrjtVe0PvBW4FNib8s/2O00HYXvPps85jjkGBG+D7eXbjiEmRT/kYkg+HiH5eKTk45H6LR+nsC0OA64FLgbOrb0um27X1RefzG3fQ0mkH+1q49Zoh4kOSTsBTwGW6orvoPH3WPhsP0IZoP3bKkObrNXkcCodtTPLW5nz/Wi0V7Lt62o8j+uOow0qA8VvwMj349z2IoqFoB9yMSQfzyH5eLbk4zn1Uz5OG1vA9ldtr2l7RxfXUS7xN+ndlD+S+4HjgDuB9zQcQz+1cfsm8FrK+yLgNcC6LcRxdn0/Vqa0uTtCUqNjFVZHA48HXgScA6xFGcOxUZJ2kfQX4Joax7XAz1qI422UnuqnA5+sXw9sOo5YuPokF0Py8eg4ko9HSj4eGUdf5eOMilD1w6fRGseytu9u+rxd559pe/Paxm0rahu3FnrhXmL7qV1flwN+ZPuFDcdxke0t6h/u2rYPUDu9kjtxdN6PxYHTbTfaxk3SxZR2Zb+o8ewA7GZ7r4bjuBTYGvh9/X19EvBJ269tMo5Y+PolF9dYko9JPp4gjuRj+i8f54ot/fFpVNJ2kq4ArqzPN1OZb7lp3W3cTrL9IO30Or23fr1H0hrAg8B6LcSxmKTVgV2BU1s4f8eD9esdKtN7rkiZyrHxOGzfCiwiaRHbZwGbtxDHfZ1bspKWtP0nYKMW4oiFqB9ycY0j+Xik5OORko9H6qt8nMK22M72G4HbXWYOeTplqrwmfYlyW+NWANsXM3tw8CZ12rgtS7tt3E6VtBKlN/SFNaYTWojjIMptlb/a/qOk9YG/tBDHt2obpo8DJwNXAP/TQhx31Ks15wLHSvoKLcxdD/yj/n78BDhT0kmUaUhjauuHXAzJx6MlH4+UfDxSX+XjNEUAJJ1vextJvwdeSUlml9neoIUYLvLsgacvtr1ZUzFMENtittv4Y+mcf0lgqT4Zz3Go1bZ+neFcdqdcqTi2XjVoK6Zn1zh+3j3GZUw9/ZCLR8WRfDzn+ZOP+0Ty8dgyKkLR+TT6P5QxE6H5IUSul7QdYElLUHrhXtlwDJ2k9SrKbZXu349G27ip9ADeqTsOSdhutKOApFWBtzPq/Wi692v9/XzjGHHs22QcnfaGklagnfEjH1WvmKxN6bQxC9iEcjUppq5+yMWQfDw6juTjkXGsRPLxCP2Uj1PYFp+nzAv+TOB3wK+BQxuOYR/gK8CawA2U2y3vajgGgJMoPYBnUHoEt+UUyifRS4FHWozjJMrvwy+Ah1uM4zTg97T8fkjam/JP9d4ahyht/tZvOI5PAW8Grmb2+9HGgPGxcPVDLobk49GSj0dKPh4ZR1/l4zRFACSdSPmEcUxdtBuwku1d24uqHZIus71JH8TReE/XceKYaXvzPojjQtttTGE5Oo6/AE+3fUvLcVwFbJqmB4MluXik5OM54kg+HhlH8vEY0nms2Mj2W22fVR970XCPPknrSzpF0r8l/UvSSbVhfNPOk7RpC+cd7WeSGh1KZhynStqx7SCAoyW9XdLqklbuPFqI42/APS2cd7TLgJXaDiIWutZzMSQfjyH5eKTk45H6Kh/nii0g6Ujgm7Z/X59vA7zJ9jsbjOH3wNcp0yYCvA54t+1tmoqhxnEFZfaQqym3vlqZe1rSKyhXbRahDK3SytzTkmZReiQ/wOwhXtqI413AZ4A7mD3cj203fctpC+AI4Hy6bo023bZM0nTKbcnLRsWxS5NxxMLVD7m4njf5eGQcyccj40g+HhlHX+XjoS5sVQYVNrA45arA3+vzdYErmrwF1OmFO2rZ721v21QM9ZzrAo+htHGDMozIHa5T9zUYx9WUsRsv9TD/klaS/gZs0we3nP4A/IZRbctsH9VwHJdThkIaHcc5TcYRC0c/5eIaT/LxyDiSj7skH88RR1/l42HvPPbStgPocpak/SljA5oySPlPO7c3bN/WUBwvB94G/IjyqfxoytzchzR0/o6/UIb5aT2JStqF2WNYnm27jYHBL6c/bjk9ZPu9bQcB3GL7q20HEQtNP+ViSD4eLfl4pOTjkfoqHw/1Fdt+IumarqedH4o6z5u6xSHpEkpj9M4wIssCv2vh1teRlJ6dP2PkrY2mh5c5mDJV4LF10W6UKS33bziOH1OmGT2Ldm85fQa4jtJLujuOpv7Rd+L4Yj3/yaPiyHBfscCSj+eI40iSj7vjSD4eGUdf5eNhv2LbTz5EGdD4LkkfB7YEPtXCL4YYOYzKw8xO6E26pj6WqI+27AhsbvsRAElHARcBjSZSyowuP2n4nGN5ff364a5ljQ8vA2xRv3bfGs5wX7GwJB+PlHw80k9IPu7WV/k4hW3/+JjtEyVtD7wA+AJl/MZGOytQG6LXT6RQboUd3nAMuEyn2S9WAjqfgFdsI4Cm20yNx3Yb88PPwfYObccQAy35uEvy8UjJxyP1Wz5OYds/Op/Kd6L0Cj5J0oFNB2H7i5LOBranXBnY0/ZFTcchaUPg/cw5s0vTnwA/C1wk6SzK+/EsRn46boSkZwAHUjrTLMbsXsmND0FUZ2Saxsify/cajmHMGZlsNzojUwys5OMuyccjJR/PEUNf5eO0se0Tkk6lzHDzfGArykwif3AfzE3eBkkXA9+kzLjz6K042zPG3WnyYlmd0q5LwPm2b+5a9xTblzcQw5+A/2LO96PROcElHQ08AZjZFYdbaFv2c2bPyNT9fnyhyThiMCUfj5R8PEcMyccj4+irfJzCtk9IWgZ4MWU4lb/UP95NbZ/RcmitkDTD9lZtxzE3amgGmrGGH2qDpCuBjdvuHa0+mZEpBlPy8UjJx3OcJ/l4ZBx9lY/TFKFP2L6HMqRL5/lNwE3tRdSOrtlbTpH0TuDHtNjbsweT2pFDUidJnyXpfym/I232Or0MeDzt/26eJ2lT25e2HEcMoOTjIvl41MGTj8fTV/k4V2yjr9RhdszYCaqVNkwTmewrBLUt2XjcVBs3SadQfi7LA5sDf6CFGWa6BvJfjD6YkSlikCUfz3H85OORcfRlPs4V2+gr/dLLs1/0UW/Tz7cdQNVvA/lHDKzk45GSj+fQl/l4kbYDiBiLpHdJWqnr+WPqrbB+80ATJ5H032O8H59u4txQpkZ0mR7x75QOG53nf6AMEN5UHNe5TCe6OnBb1/PbKLfkImIhSz4eKfn40Tj6Mh+nKUL0JUkzbW8+atlFtrcYZ5eFff4Jb2c13ZZqrNfeVEeJUee8ANjO9gP1+RLAb21v3XAcFwFbdjpNSFoEuKDp9yNiGCQfj5R8PEccfZWP0xQh+tUiktT1h7Iozc540xmmZClgOnAxpd3QU4HzKeNKNmlRSUvavh9A0tLAkg3HALBYJ4kC2H6gJtOmPfq7UeN4RFLyWcTkSD4eKfl4pL7Kx2mKEP3qdOBESc+T9FzgeODnTZ3c9g61PdV1lE+i0+twN1sAf20qji7HAL+U9FZJbwHOBNqY/ebfkh7tmCDpZcAtLcRxtaR9JS1eH/tROi5ExMKXfDxS8vFIfZWP0xQh+lK9lbE38DzKJ/MzgO/YfnjCHRd+HGPdgptjWUOxvISu98P26S3E8ATgWGCNGsf1wBttN/rPRdLjgK9S5iI38EvgPbb/1WQcEcMg+XjMWJKPZ8fRV/k4hW3EBCQdD9xN+YRuYA9gOdu7tRpYyyQtR8kfs9qOJSKGQ/Lx2JKPR0phG31JfTIXt6SlgHdQ5iQHOBc41PZ9DcfxSuBzwOMo70Xn/Vih4Tj6Yk5wSasCbx8jjrc0GUfEMEg+niOO5OORcfRVPk5hG31JfTIXd41laWAd21c1fe6uGP4K7Gz7yrZiqHH0xZzgks4Dfj1GHD9sMo6IYZB8PEcMyccj4+irfJxexNGv7rT9s7aDqA3z/5fSA3g9SZsDBzU1s0uXf7adRKu1bL+47SCAZWx/qO0gIoZE8vFIyccj9VU+TmEb/apf5uI+AHgacHY9/0xJ0xqOAeACSd8HfsLI9+NH4+4xOfplTvBTJe1o+7SW44gYBsnHIyUfj9RX+ThNEaIvjTMnt93QXNxdcZxve5vuAbklXeKG58CWdMQYi910GyZJVwBPBK6hxTnBJc0ClqXMNPQALbVxixgGycdzxJF8PDKOvsrHuWIbfcn9Myf3ZZJeTxmQewNgX+C8poOwvWfT5xzHS9oOAMD28m3HEDEsko9HSj4eqd/ycSZoiL4kaTVJh0v6WX2+saS3thDKu4GnUD4NH0dpqP+epoOQtKGkX0q6rD5/qqSPNR2HyzzgawPPrd/fQwt5RMUekj5en68t6WlNxxExDJKPR0o+Hqnf8nGaIkRfqgn0COCjtjer0/NdZHvTluJZ1vbdbZy7nv8c4APAYV234C6zvUnDcRxAmdJyI9sbSloD+IHtZzQcx6HAI5SE/mRJj6EMkt7oHOkRwyD5eI7zJx+PjKOv8nGu2Ea/WsX2iZQ/Fmw/RNcwIk2RtF1tx3Rlfb6ZpG80HQel1+kfRi17qIU4XgHsQhkkHds3Am3chtrG9ruA+2oct9Ps3PURwyT5eKTk45H6Kh+nsI1+dbekx1Jml0HStpTbTk37EvAi4FYA2xcze3DwJt1Sp0/svB+vBm5qIY4HXG7zdOJYtoUYAB6UtGhXHKtS/+lGxEKXfDxS8vFIfZWP03ks+tV7gZOB9SX9FlgVeHUbgdi+XlL3osavVADvAr4FPEnSDZResLu3EMeJkg4DVpL0duAtwLdbiOOrwI+B1SR9hvK70Xgbt4ghkXw8UvLxSH2Vj1PYRr+6gvKHcg8wizJe4J9biON6SdsBlrQEpRdu4wNz274aeH79RL5IW3OC2/68pBcAdwEbAp+wfWYLcRwraQbwvLro5X0yYHrEIEo+7pJ8PEccfZWPU9hGv/oe5Y/1v+vz3YCjgdc0HMc+wFeANYEbgNMpn9YbVW8DHgBsT0nqv6HMuNP4lJbApcDSlNtObQ4MvgzQuf21dItxRAy65OMuycdj6pt8nFERoi9Jutj2ZnNbNiwknQmcCxxTF+0OPMf28xuO423AJ4BfUQbhfjYloX+34Tg+Qfmn+sMax8spvYE/3WQcEcMg+Xik5OM54uirfJzCNvqSpCOBb9r+fX2+DfAm2+9sOI71KVcItqV8Ev0d8F/1VlSTccywvdWoZRfYnt5wHFcB23WuTNQrF+fZ3qjhOK4EtrB9X32+NHCh7Sc3GUfEMEg+niOO5OORcfRVPs6oCNFXJF0q6RJgG8o82NdKuoaSwNro/XoccCKwOrAG8APg+BbiOEvS6yQtUh+7Aj9tIY5/UNrYdcwCrm8hjmuBpbqeLwn8rYU4IgZW8vG4ko9HupY+yse5Yht9RdK6E62vs6s0RnVu8lHLfm9724bOP4tyZUKUubg7PYAXBf7T1Fzckt5bv90c2BQ4qcb1MuAPtvdpKI5D6nnXAbYGzqzPXwD8xvbrmogjYhgkH89x/uTjkXH0ZT5OYRsxAUkHA3cAJ1D+YF9L+TT6dQDbt7UWXBdJT7F9+SQe/4CJ1tv+5GSde1Qcb5pLHEc1EUdENC/5+NHjJx9PIIVtxATqbbeOzh9LZxBF216/4ZDGJOlC21v2QRyH2H53H8TxQ9uvajuOiFh4ko/nOY6hzMdpYxsxsQ8Bm9lejzJX+sXAq2yv1y9JtNLcN2lEo3OUT6CffjYRsXAkH8+boczHKWwjJvYx23dJ2p7SbuhI4NB2QxpTbr2MlPcjYvAkH09Njb4fKWwjJtbpHLATZbibk4AlWownImJYJR/HXKWwjZjYDXUu7l2B0yQtSX/+3TzQdgBVv9yC65c4ImLhST6eN/2SBxuNox9/ISL6ya6UaRtfbPsOYGXgA02dXNKWEz062zU43M0cU2iOWvaVhuLYby7LPtREHBHRqOTjkfEkH48hoyJE9DFJZ9VvlwKmUzpLCHgqcL7t7RuOZ47evm30AB4njotsb9FkHBExPJKP5ymO1vLxYm2cNCJ6Y3sHAEknAHvZvrQ+3wR4f1NxSHoJsCOwpqSvdq1aAXiowTh2A14PrCfp5K5VywO3NhVHRAyf5OM54ujLfJzCNmJqeFIniQLYvkzS5g2e/0bgAmAXYEbX8lnAfzUYx3nATcAqwBdGxXFJg3FExPBKPi76Mh+nKULEFCDpeOBu4BjK0Cl7AMvZ3q3hOBanfCBex/ZVTZ57jFjWBTaw/QtJSwOL2Z41t/0iIhZE8vGYsfRNPk7nsYipYU/gcmA/4D3AFXVZ014MzAR+DiBp81G3oBoh6e3A/wGH1UVrAT9pOo6IGErJx136LR/nim3EFFE/Bbf6yVzSDOC5wNmdjgGSLrH91IbjmAk8jdJhoxPHpbY3bTKOiBhOyccj4phJH+XjXLGNmAIk7UIffDIHHrJ9ZwvnHe1+24+OFSlpMTLbT0Q0IPl4Dn2Vj1PYRkwNB1A+Ed8BYHsmMK2FOC6T9HpgUUkbSDqE0oGgaedI+giwtKQXAD8ATmkhjogYPsnHI/VVPk5hGzE19Msn83cDTwHuB44H7qK0MWva/sC/gUuBvYHTgI+1EEdEDJ/k45H6Kh+njW3EFCDpcOCXlATyKmBfYHHb+7QY06LAsrbvaiuGGsfKwFq2M9xXREy65OMJ42g9H+eKbcTU0P3J/DjgTlr4ZC7pOEkrSFqW0iv4KkmNTWnZFcfZNY6VKW3djpD0xabjiIihlHw8Mo6+yse5YhsxhUha1vbdLZ5/pu3NJe0ObEWZA3xGC71wL7K9haS3AWvbPqCN3sARMbySjx+No6/yca7YRkwBkraTdAVwZX2+maRvtBDK4nVQ8JcDJ9l+kHZ6vy4maXVgV+DUFs4fEUMq+XgOfZWPU9hGTA1fAl5EnX/b9sXAs1qI4zDgWmBZ4Nw620wbbboOAk4H/mr7j5LWB/7SQhwRMXySj0fqq3ycpggRU4Ck821v07nlU5ddbHuzPohtMdsPtR1HREQTko/722JtBxARPble0naAJS1B6YV7ZdNBSFqS0gt4GiPzx0ENx7Eq8PbRcdh+S5NxRMRQSj4eGUdf5eMUthFTwz7AV4A1gRsot33e1UIcJ1F6AM+g9Ahuy0nAr4FfAA+3GEdEDJ/k4znj6Jt8nKYIEdEzSZfZ3qQP4phpe/O244iIaEvy8djSeSxiCpC0vqRTJP1b0r8knVQb6DftPEmbtnDe0U6VtGPbQUTE8Ek+nkNf5eNcsY2YAiT9Hvg6ZdpEgNcB77a9TcNxXAFsAFxNufUlwC2MmziL0hP4AeDButi2V2gyjogYPsnHc8TRV/k4hW3EFNDphTtq2e9tb9twHOsCjwGeWRedC9xh+7om44iIaEvycX9LU4SIqeEsSftLmiZpXUkfBH4qaeU6jWFTXg4cDawCrFq/36XB8z9K0i6SPl8fL20jhogYSsnHo/RTPs4V24gpQNI1XU87f7TqPLfdSPsuSZcAT+9MI1nnKP9dC7e+Dga2Bo6ti3ajTCW5f5NxRMTwST6eI46+yscpbCOmAEm7Aj+3fZekjwNbAp+yfWHDcVwKbG37vvp8KeCPthvtwFAT+ua2H6nPFwUuamtu8ogYHsnHc8TRV/k4TREipoaP1SS6PfAC4Ejg0BbiOAI4X9KBkg4Efg8c3kIcACt1fb9iSzFExPBJPp7TSl3ft5qPM0FDxNTQGfR6J+Cbtk+qiaxRtr8o6Wxge8qttz1tX9R0HMBngYsknVXjeBbw4RbiiIjhk3w8Ul/l4zRFiJgCJJ1KmeHm+cBWwL3AH/phbvK2SFqd0q5LwPm2b+5a9xTbl7cWXEQMrOTjOfVTPk5hGzEFSFoGeDFwqe2/1CSyqe0zWg6tL0m60PaWbccREYMn+XjeNJ2PU9hGxMCRdJHtLdqOIyJi2DWdj9N5LCIGUT6xR0T0h0bzcQrbiIiIiBgIKWwjYhA90HYAEREBNJyP08Y2IqYMSRN2QGh6gPSIiGHVr/k4hW1ETBl1nESApYDpwMWU4WWeShliZvu2YouIGCb9mo/TFCEipgzbO9jeAbgO2NL2dNtbAVsAf203uoiI4dGv+TiFbURMRU+yfWnnie3LgM3bCyciYmj1VT7OlLoRMRVdKek7wDGUoWT2AK5sN6SIiKHUV/k4bWwjYsqRtBTwDsqc5ADnAofavq+9qCIihk+/5eMUthExJUlaGljH9lVtxxIRMcz6KR+njW1ETDmSdgFmAj+vzzeXdHKrQUVEDKF+y8cpbCNiKjoAeBpwB4DtmcC09sKJiBhafZWPU9hGxFT0kO072w4iIiL6Kx9nVISImIouk/R6YFFJGwD7Aue1HFNExDDqq3ycK7YRMRW9G3gKcD9wHHAn8J42A4qIGFJ9lY8zKkJETFmSlrV9d9txREQMu37Jx7liGxFTjqTtJF1BHQRc0maSvtFyWBERQ6ff8nEK24iYir4EvAi4FcD2xcweHDwiIprTV/k4hW1ETEm2rx+16OFWAomIGHL9lI8zKkJETEXXS9oOsKQlKL1wW5ubPCJiiPVVPk7nsYiYciStAnwFeD7lztPpwH62b201sIiIIdNv+TiFbUREREQMhLSxjYgpR9L6kk6R9G9J/5J0kqT1244rImLY9Fs+TmEbEVPRccCJwOrAGsAPgONbjSgiYjj1VT5OYRsRU5FsH237ofo4Bki7qoiI5vVVPk4b24iYciQdDNwBnEBJoK8FlgS+DmD7ttaCi4gYIv2Wj1PYRsSUI+marqedJKbOc9tpbxsR0YB+y8dpihARU9GHgM1srwccAVwMvMr2eilqIyIa1Vf5OIVtRExFH7N9l6TtgRcARwKHthtSRMRQ6qt8nMI2IqaiznSNOwHftH0SsESL8UREDKu+yscpbCNiKrpB0mHArsBpkpYk+Swiog19lY/TeSwiphxJywAvBi61/RdJqwOb2j6j5dAiIoZKv+XjFLYRERERMRBy6y4iIiIiBkIK24iIiIgYCClsoy9J+qikyyVdImmmpG1aiGEfSW9s+rwREf0k+TimkrSxjb4j6enAF4Hn2L5f0irAErZvbDCGxWw/1NT5IiL6UfJxTDWLtR1AxBhWB26xfT+A7VsAJG0NfAVYFrgfeB5wD3Aw8Bzq3NS2D5P0HOBA4BZgE2AGsIdtS/oEsDOwNHAesHddfnZ9/gzgZEnLA/+x/XlJmwPfBJYB/ga8xfbtk/ouRES0L/k4ppQ0RYh+dAawtqQ/S/qGpGdLWgL4PrCf7c2A5wP3Am8F7rS9NbA18HZJ69XjbAG8B9gYWJ+SIAG+Zntr25tQkulLu869ku1n2/7CqJi+B3zI9lOBS4EDFvJrjojoR8nHMaWksI2+Y/s/wFbAXsC/KQl0b+Am23+s29xVb029EHijpJnA+cBjgQ3qof5g+x+2HwFmAtPq8h0knS/pUuC5wFO6Tv/90fFIWpGSYM+pi44CnrVwXm1ERP9KPo6pJk0Roi/Zfhg4Gzi7Jrx3AWM1CBfwbtunj1hYbn3d37XoYWAxSUsB3wCm275e0oHAUl3b3b2QXkJExEBIPo6pJFdso+9I2kjSBl2LNgeuBNao7bqQtLykxYDTgXdIWrwu31DSshMcvpM0b5G0HPDqucVj+07gdknPrIveAJwzwS4REQMh+TimmlyxjX60HHCIpJWAh4C/Um6DHVGXL01pz/V84DuUW1oXShLlVtnLxzuw7TskfZvSLuta4I89xvQm4Jt16sCrgT3n9UVFRExByccxpWS4r4iIiIgYCGmKEBEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQEhhGxEREREDIYVtRERERAyEFLYRERERMRBS2EZERETEQPj/4rN06yNnCoUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_hospital(results_pivot, 54)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96a386d0",
   "metadata": {},
   "source": [
    "## Observations\n",
    "\n",
    "* The combined effect of the changes modelled were to increase thrombolysis use from 11.6% to 18.3% of all patients (57% increase), and to increase the number of thrombolysis-related good outcomes per 1,000 admissions from 9.4 to 17.6 (86% increase).\n",
    "\n",
    "* Overall the net improvements made to thrombolysis use were benchmark decisions > determining stroke onset time > speed improvement.\n",
    "\n",
    "* Overall the net improvements made to additional good outcomes  were speed improvement > benchmark decisions > determining stroke onset time.\n",
    "\n",
    "* Speed improvement therefore had least effect on the proportion of patients receiving thrombolysis, but most effect on the the predicted outcomes. This is due to improving the speed of thrombolysis improving the outcomes for all patients, including those that would have received thrombolysis anyway (without speed improvement). \n",
    "\n",
    "* When asking the question \"which single change makes most difference at each hospital?\" then for thrombolysis the order is: benchmark decisions (83/132 hospitals), determining time of stroke onset (39/132), speed (10/132). For improvements in clinical outcome the order is benchmark decisions (56/132 hospitals), speed (49/132), and determining time of stroke onset (27/132).\n",
    "\n",
    "* Combining improvements to the pathway had a greater effect than any single change alone.\n",
    "\n",
    "* Even with all improvements, there would still be expected to be a significant inter-hospital variation in use of thrombolysis and, the benefit gained. With the modelled improvements there is a general improvement across hospitals, and not a significant reduction in inter-hospital variation. The remaining variation is due to variation in patient populations.\n",
    "\n",
    "* Charts may be readily produced for each hospitals showing the potential benefit of each process change individually or combined."
   ]
  }
 ],
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