{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Incidence de la varicelle" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données de l'incidence du syndrome grippal sont disponibles du site Web du [Réseau Sentinelles](http://www.sentiweb.fr/). Nous les récupérons sous forme d'un fichier en format CSV dont chaque ligne correspond à une semaine de la période demandée. Nous téléchargeons toujours le jeu de données complet, qui commence en 1991 et se termine avec une semaine récente." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pour nous protéger contre une éventuelle disparition ou modification du serveur du Réseau Sentinelles, nous faisons une copie locale de ce jeux de données que nous préservons avec notre analyse. Il est inutile et même risquée de télécharger les données à chaque exécution, car dans le cas d'une panne nous pourrions remplacer nos données par un fichier défectueux. Pour cette raison, nous téléchargeons les données seulement si la copie locale n'existe pas." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data_file = \"incidence-PAY-7.csv\"\n", "\n", "import os\n", "import urllib.request\n", "if not os.path.exists(data_file):\n", " urllib.request.urlretrieve(data_url, data_file)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "La première ligne du fichier CSV est un commentaire, que nous ignorons en précisant `skiprows=1`." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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.................................
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\n", "

1531 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202014 7 3881 2223 5539 6 3 \n", "1 202013 7 7341 5247 9435 11 8 \n", "2 202012 7 8123 5790 10456 12 8 \n", "3 202011 7 10198 7568 12828 15 11 \n", "4 202010 7 9011 6691 11331 14 10 \n", "5 202009 7 13631 10544 16718 21 16 \n", "6 202008 7 10424 7708 13140 16 12 \n", "7 202007 7 8959 6574 11344 14 10 \n", "8 202006 7 9264 6925 11603 14 10 \n", "9 202005 7 8505 6314 10696 13 10 \n", "10 202004 7 7991 5831 10151 12 9 \n", "11 202003 7 5968 4100 7836 9 6 \n", "12 202002 7 6534 4530 8538 10 7 \n", "13 202001 7 9835 7019 12651 15 11 \n", "14 201952 7 7941 5246 10636 12 8 \n", "15 201951 7 5823 3675 7971 9 6 \n", "16 201950 7 6424 4276 8572 10 7 \n", "17 201949 7 6621 4540 8702 10 7 \n", "18 201948 7 5542 3383 7701 8 5 \n", "19 201947 7 7536 5058 10014 11 7 \n", "20 201946 7 2638 1316 3960 4 2 \n", "21 201945 7 4492 2615 6369 7 4 \n", "22 201944 7 5728 3627 7829 9 6 \n", "23 201943 7 4834 2751 6917 7 4 \n", "24 201942 7 6279 3989 8569 10 7 \n", "25 201941 7 4130 2030 6230 6 3 \n", "26 201940 7 4211 2218 6204 6 3 \n", "27 201939 7 3137 1310 4964 5 2 \n", "28 201938 7 3078 1416 4740 5 2 \n", "29 201937 7 970 162 1778 1 0 \n", "... ... ... ... ... ... ... ... \n", "1501 199126 7 17608 11304 23912 31 20 \n", "1502 199125 7 16169 10700 21638 28 18 \n", "1503 199124 7 16171 10071 22271 28 17 \n", "1504 199123 7 11947 7671 16223 21 13 \n", "1505 199122 7 15452 9953 20951 27 17 \n", "1506 199121 7 14903 8975 20831 26 16 \n", "1507 199120 7 19053 12742 25364 34 23 \n", "1508 199119 7 16739 11246 22232 29 19 \n", "1509 199118 7 21385 13882 28888 38 25 \n", "1510 199117 7 13462 8877 18047 24 16 \n", "1511 199116 7 14857 10068 19646 26 18 \n", "1512 199115 7 13975 9781 18169 25 18 \n", "1513 199114 7 12265 7684 16846 22 14 \n", "1514 199113 7 9567 6041 13093 17 11 \n", "1515 199112 7 10864 7331 14397 19 13 \n", "1516 199111 7 15574 11184 19964 27 19 \n", "1517 199110 7 16643 11372 21914 29 20 \n", "1518 199109 7 13741 8780 18702 24 15 \n", "1519 199108 7 13289 8813 17765 23 15 \n", "1520 199107 7 12337 8077 16597 22 15 \n", "1521 199106 7 10877 7013 14741 19 12 \n", "1522 199105 7 10442 6544 14340 18 11 \n", "1523 199104 7 7913 4563 11263 14 8 \n", "1524 199103 7 15387 10484 20290 27 18 \n", "1525 199102 7 16277 11046 21508 29 20 \n", "1526 199101 7 15565 10271 20859 27 18 \n", "1527 199052 7 19375 13295 25455 34 23 \n", "1528 199051 7 19080 13807 24353 34 25 \n", "1529 199050 7 11079 6660 15498 20 12 \n", "1530 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 9 FR France \n", "1 14 FR France \n", "2 16 FR France \n", "3 19 FR France \n", "4 18 FR France \n", "5 26 FR France \n", "6 20 FR France \n", "7 18 FR France \n", "8 18 FR France \n", "9 16 FR France \n", "10 15 FR France \n", "11 12 FR France \n", "12 13 FR France \n", "13 19 FR France \n", "14 16 FR France \n", "15 12 FR France \n", "16 13 FR France \n", "17 13 FR France \n", "18 11 FR France \n", "19 15 FR France \n", "20 6 FR France \n", "21 10 FR France \n", "22 12 FR France \n", "23 10 FR France \n", "24 13 FR France \n", "25 9 FR France \n", "26 9 FR France \n", "27 8 FR France \n", "28 8 FR France \n", "29 2 FR France \n", "... ... ... ... \n", "1501 42 FR France \n", "1502 38 FR France \n", "1503 39 FR France \n", "1504 29 FR France \n", "1505 37 FR France \n", "1506 36 FR France \n", "1507 45 FR France \n", "1508 39 FR France \n", "1509 51 FR France \n", "1510 32 FR France \n", "1511 34 FR France \n", "1512 32 FR France \n", "1513 30 FR France \n", "1514 23 FR France \n", "1515 25 FR France \n", "1516 35 FR France \n", "1517 38 FR France \n", "1518 33 FR France \n", "1519 31 FR France \n", "1520 29 FR France \n", "1521 26 FR France \n", "1522 25 FR France \n", "1523 20 FR France \n", "1524 36 FR France \n", "1525 38 FR France \n", "1526 36 FR France \n", "1527 45 FR France \n", "1528 43 FR France \n", "1529 28 FR France \n", "1530 5 FR France \n", "\n", "[1531 rows x 10 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Y a-t-il des points manquants dans ce jeux de données ? Non" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n", "Index: []" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nos données utilisent une convention inhabituelle: le numéro de\n", "semaine est collé à l'année, donnant l'impression qu'il s'agit\n", "de nombre entier. C'est comme ça que Pandas les interprète.\n", " \n", "Un deuxième problème est que Pandas ne comprend pas les numéros de\n", "semaine. Il faut lui fournir les dates de début et de fin de\n", "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n", "\n", "Comme la conversion des semaines est devenu assez complexe, nous\n", "écrivons une petite fonction Python pour cela. Ensuite, nous\n", "l'appliquons à tous les points de nos donnés. Les résultats vont\n", "dans une nouvelle colonne 'period'." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "data = raw_data.dropna().copy()\n", "\n", "def convert_week(year_and_week_int):\n", " year_and_week_str = str(year_and_week_int)\n", " year = int(year_and_week_str[:4])\n", " week = int(year_and_week_str[4:])\n", " w = isoweek.Week(year, week)\n", " return pd.Period(w.day(0), 'W')\n", "\n", "data['period'] = [convert_week(yw) for yw in data['week']]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il restent deux petites modifications à faire.\n", "\n", "Premièrement, nous définissons les périodes d'observation\n", "comme nouvel index de notre jeux de données. Ceci en fait\n", "une suite chronologique, ce qui sera pratique par la suite.\n", "\n", "Deuxièmement, nous trions les points par période, dans\n", "le sens chronologique." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous vérifions la cohérence des données. Entre la fin d'une période et\n", "le début de la période qui suit, la différence temporelle doit être\n", "zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n", "d'une seconde.\n", "\n", "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives\n", "entre lesquelles il manque une semaine.\n", "\n", "Nous reconnaissons ces dates: c'est la semaine sans observations\n", "que nous avions supprimées !" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", " delta = p2.to_timestamp() - p1.end_time\n", " if delta > pd.Timedelta('1s'):\n", " print(p1, p2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Un premier regard sur les données !" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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E1AvAAwC+wRjbiUBFdDiAsQDWAbiBV1XczgzlpnvkMUwhorlENHfTpk2uQ+8Q+JPgAsxZsRXPLNloryih2nNx3eM/fdtLuGFaoKppaSsqD8Y5UMEf+dOLN2LWMvfDfaopxLeEEl5n5C6L4xyCB9XVVYodDac3QER1CAjDnxljDwIAY2wDY6zIGCsBuB3AhLD6GgAjhNuHA1gblg9XlCfuIaICgL4AUnIlY+w2xth4xtj4xsZGtxl2EDrD5tAV1+qnfj8L//a/L2e+r5JTcdm6dMTIRKSWbdqDvS1tQt2sI0t01I6b9ciyJkROWJeLSYVqxsBxr7L1O5vxj9feqV7HAoqeOABw81YiAHcAWMwYu1EoHyJU+wSAN8LfDwOYHHogjUJgeJ7DGFsHYBcRnRK2eRmAh4R7Lg9/XwRgButibHJqNJ2SPqPzsHb7Plxy20uYv8buXtkVUe6zu+Gpt7L3VcUXVQ3VRzUjpLl32Ntb9uIb986rSp8tbSWcdf0zeO6tQBvBzVO1rlYqONQ5HcDnACwgIv62/gvAJUQ0FsF3txLAFwGAMbaQiO4DsAiBp9NVjDEeSXQlgDsBdAfwePgPCIjPn4ioCYHEMLl908qOtmIJ0xZtwKQxByvF6JRBuloDE/vsxMU6e8UWzFq+BX9+aRWOv6hfu9ur9lTK7S8ZIW2ua9S+dJBqJsu8yn3k1YxzaGmr/hrfsLMZK4SU58WQQNW65GAlDoyxF6CW3B8z3DMVwFRF+VwAYxTlzQAuto2lI3Hniyvxk0cX41eTx+KCsWlnrJRBusa4Cm5s3deaIWLYgI5Qy5nfiUatZG203NF0PZS7ZnNVVP+3ZXQR2tncim17WnDowJ5l95l2YU3+X6vwEdIhdoYc4vJN6kNTuoBWqVNdWbMwj4vW7sQb7+ww1jlQJId3zwACG0o5qKa3kuxybCNoF97yIs74n2fa1aesKeAR0l6t5AEA6NO9DoA+mKga6TPaiiUUDF4aXSG3kssIeDK9ldd9pGMHkwG6cdveI0v8NldWbaGV2Fc7O+KnmmolWXAoMcB0rtbSjbvb3afcPPdQq3W1kpccQtSHmThFsfbpRRsw8upHsWxTegF2xLJp0QRqcYwaVL7o3F5w7qpS6rRKEtcsqSPag85iJDs7GjTXiSm7q8G9yz1wb6UaFxw8ceDgTILIJT26IDgT+PXV2xW5lSq/cmxRrn1D6eaE4X0r3rcrKjHrbXta8Md/rahASwFcXkW5UpdIeDprr+jsZAHVpA2dkcJCPuuD/90VJPXOhCcOIfgiVInQjHVMhPTKzXsSp3zttxAHvoarvWTfeGdHfApbBTr/7gPz8T9PLml/Qxmg22PKURXZ+6ps+oxOlxwciFOpxHDvy6uc0niYIHflShvac6SpTIC4OqnWJQdvcwihWlt8ne5vK2HjTungjwosnDPDw1Q4bB9WqZPE3b8LwUimzXTjrmb0rq+ztrd9b/Wzcpb7zGyqPhGqPVSVUuNAg0ucwz/nr8V/PrAAa7c345vnHlWxvl3fW1uJoVuZIo5sW+DfmTdIewCIuT3VB/5ff1+Qrt8B/LtVcuji4u6EqdPxnmGdp/IyodxnJiaJK2evqMS7MjHuF540HA+8ugYXjxuur9ROuEgO3JGjvem4ZWJq2qDFvkzG47tnrcTs5Vvx28+cpLwu97FzXxAV3zW/surBq5UkuHpmtJepuObB+akyu+QQ/l/lbJHiXG3zXmBxYVW3376H6XL3Y6H9KN13u7quSpsm6aNb6EjRq6Hj+LwsDHm5xHDt9n0AstkcTvrxtOi36byOax9aGNkPVZDpypyVQeaeGhccPHHgiG0ObvXbu3D+Omd1qsymwojUSu3rul2oxAcjb3YL1+5sf6PQP5e7Z63Eb2cuy9TWuEP72ytJUGdlrYQvq7qYMYa/zlkV/m5/Nzp0dPqMf7z2Dk67bgZmL08nA5SnNfLqR/H9h95I1StmOAY2dW+Nu6zq4IlDCJW3kgkdodqxSQ7lHvPYXnS0GiuLXl8F2+O49qGFmdtUB351ziaiW5GVila3wRR7s0GyxZVDDF95O3DKeHP9rtQ1plgad816O1XmctLfkd97DEs3pPvwxEENTxxCROJrFSQH3WK0GcA6y0CWUCtVYoM8AGy0qpQRnRbnoHle4jLqSIahm4Y4vLZqG07+6XT8bW5aClZBt+5N/JjrmnfZ4FuLTCmx17rhWQdPHELEtEFYqYZF257lpJMQXIlDZ67lrvgddYRko1KluPaiqtcRz01UpXTkayloQpSXbgiCQ+esiLPrm97F3bNWZu7bdV5tjmqlokLC8JKDGp44hGAZbQ7TFm0ouy8tEbCsUa596UxvpY7oub0bZ3vu191bTsoIpStrRUwO6kbEaP5iiWFbOz2FdChUKPPepl37rXXk9+HK1TvHQyjqZaUN2/e24LrH30RbO9WhXR2eOITgi6saeWR0a9G2SFkXkBxqBdU8w8AG3ZIUXTn/PHsVTvzxNG1usPagzpTcCMDfXlmDPfsD+0d7DPCMsRQxcCUOzuonRb2saqWpjy7G755dhicWrs90nw1NFcgTVUnUPHF4a8MuHPFfj2HV1r0AkpJDRwUw6Rajq1qp2jpSUZ/dMV27N6qMPu6AMRVUaqUyuNjKeHepce5Nz6XKdnYAcTAZpDlunBZEvItS7dyVWxMGYN2jEOeXTo3vNkbXx6yKpM6qVuLxSJVUR01btAHn3Pgs/vn6WnvlKqHmicM9c1ajrcTwxBsBF1CNPDZlapU6LX1GEu6961IatOcJV5oQ6FR01cxE2lloT8oJAIkX2arQ+V/0u1kJAuaSAVeu4q4uKt9wXe5zeHzB+opt5m+FRHTxusq4dVcCNU8c+B7AF1dV9gTNWnT2VqoidVi9dW/CdVBL2BQXbn02W2yBC5TG3g54IMocW473irdmXU+ya2jQRrqRh+apz1fO0l9HLCOTtK17T+L85HVUaZuDWq3kdi8HH+4TC9fjqzzn2LsQnjiE//MFUo1cOLoFb1NbuNKGUonhtzObMPLqR/Gjfy4y1l2/o9loyPzMH2Yn/p6lCFQC1B/YbMGLxYQs0oBxs6jgbpe36NlNaI9089//SAd4ySNpLZbw9Xvaf76yu5qs8mREZ8yVe3InDo62CZVayRvxlPDEIfzyilWUHHRL0bZG42yR5oozl2yMsp7aUmOf8rPpOFFIQyBDTpK3tyUOvBJF9Cx2kPY8Y1U3HeGtVM7pZ6Y7XDavV97epibUUsNPGgyhWdSirhyzi60grutGvH/0SJppYQq9UqVtDty2KCKrWqkjt4iuRKasxIGIRhDRTCJaTEQLiejrYfkAIppGREvD//sL91xDRE1EtISIzhPKxxHRgvDazRSuZCKqJ6J7w/LZRDSy8lPVzg9AeZ5A5XJUuvtsa9Q1fYZK/1tJ8PTdv38uVhupiIPrR5RltNVy41XGOVi6VuXvybKRXHjri5j79rZUudxGnwZ95tss/VXdsUH4PXPJRgBBwj4x4aT8fittc3h11Xbs2d+WKPNxDmq4SA5tAL7NGDsGwCkAriKiYwFcDWA6Y+xIANPDvxFemwzgOACTANxCRPmwrVsBTAFwZPhvUlh+BYBtjLEjANwE4OcVmFsmRFy5sDhtTFi5a0p3n22B88u2epV0w1Rxog+HRrgVwpnEquwFuufnqrqrlGfSKYcNyHxP1uQZW/e0lH1Gs3Us0oPkyfZUyERoXStnaNT13XKbzgk/fCrOD6UYk26tyxt6lnUhE4esRLIjnVa6kobLShwYY+sYY6+Gv3cBWAxgGIALANwVVrsLwMfD3xcAuIcxtp8xtgJAE4AJRDQEQB/G2CwWfPV3S/fwtu4HMJE68g0IkG0OFdN/G6Djfm3NuUZIq9wwOwLiMLI8C1fuv1IqpNGDexvG4g5X9YNqfq+s2p6hJzNeUUgXUd8d8R4cDMkubYpj061Qk81BvH/64mQQapZ1IafG7wrpM7qic1wmm0Oo7jkRwGwAgxlj64CAgAA4KKw2DICYwGRNWDYs/C2XJ+5hjLUB2AFgoKL/KUQ0l4jmbtq0KcvQDZNK/plpsyhbraQrd/NWsnXbGWf+tketpIOrZ1KHfNuKwbcaImJt7649Lo/yxmE6RS8bc1PmgMqEODadq3BaclBf+9NLb0v13CQMIJ3oMWugc8faHDqfUHE4Ewci6gXgAQDfYIyZnHF1ErlJUneS4hljtzHGxjPGxjc2NtqG7ARZDHbhbuK65fWpu8/2sbou4nKMqTqYmhLnoTxJT3Nz+pmr21d98Kp+bB+U6apuU1epR4zEwTiC9qGj7AiVdhO19yf8oUtDno50UPwCnl+62alPJXGQJIeu4K3UFU8MdCIORFSHgDD8mTH2YFi8IVQVIfx/Y1i+BsAI4fbhANaG5cMV5Yl7iKgAoC8ANz/IdqLcM2sB88fFGMPIqx/FDU+luTytWsm2yUWSg7lehVLhWJGMnG6HQTpDxHi10pWr6FqbgXon1R+VHkvlPZAA+zgPa+yJowb30l5Xjcq0yYnPSH1WO7NIDm7P31YuE4fMa6rr7eMdAhdvJQJwB4DFjLEbhUsPA7g8/H05gIeE8smhB9IoBIbnOaHqaRcRnRK2eZl0D2/rIgAzWAfuAp/+/Sz86umlymtZxDrTh8hF19/MbHK+r1LeSpV4clkfv4pD0xqk25EWXSk5WIZaqZU0uE+DoZPK9NFeZLL9uIQsI6MHn+FBiGPTLYH5a5K2mQTRNfWbYYxptVJ886mHDcSwft3dG6swtu1pwWqFu21nwIXHPB3A5wCcTUTzwn8fBnAdgHOJaCmAc8O/wRhbCOA+AIsAPAHgKsYYd46/EsAfEBiplwF4PCy/A8BAImoC8C2Enk8dAcYYZq/Yipuefktz3b0t04fIuROlvqzMILi2KM7BPC4Th8uxdvs+zHxzo/Lanv1tGHXNY7jlmTRhEyH28rdX1ihqtI/FUs7TMLXlm9XeQkYjqaZcNfLudXlFqXVYEWYu2YiRVz+aOcFalqeYhahbEz0ikAQqpQe3SQ4AcN/c5DoSp2OaWnskB5E41Bk8wTg6QgXEH8d9c9fg/b+YWfH2y4H14FnG2AvQr8+JmnumApiqKJ8LYIyivBnAxbaxVAK7JTc2eWK2z2DKBw7Dbc8tD+pqVNCtxRLmrwnOUlaLz+r7XIPgrGk2HIjDadfN0F5bH6Zw+Ntc1YYfQ9yIXtJETrtAN1qlWkllkLa1L1S48szDcesz9rQeREESxoRaw1Bf905EldCd/1oJIEhId8RBenWNaiyuyKJWcpEyKulFI3bn2m5ScshO5FVTlJknsY+6TsrG2xU1VTUXIS3742c50BwAjhvaR1m3WGLR5j310cVR2gnVR5DFACsikhyMtdwkBxN2NwcEtGd93rhoxW6WbUpzw65qJS2xtPSpwsirH8WUu+dq2zn76INw/glDzY0g4A7lcwxMXDlzICLPvhV42JkM27rRuCKLWmnjTvv5CoD+/WQlHAl7tOtxvI6SQxa7lcw8iX8W8mR9hq7z3rJ7P07+6dNYVMYZ6X94fnnmeyqNmiMOMveREhEt31aOCD+64DgAyYV3/A+exJnXB+Lga6tiP/QsvuB2byU3tVJ7Iz55kFCverNgKc5/9dZ9qeu64yVltNcgLZc9ZTiIiZD8uE0bnxxMKFdtLZZwyk+n44k31mXalFsyRrBnSqaXoekP3/y88Tqff6XMKTv2xunE1erWdFl7PapUxfL3If5dyOcqZqN6bukmbNi5H7c9lz0B5f9JrrqdgdojDtKLT3GxhmtAQBz4hi+6wO1pKUYbJEvUT7eh27utNoeI47Soldq5upvbAhNRg0HHDtg3Itv9UTua8hmLN+Jvc1cnkrS5zkx3BkWWjVYOJpTfz5bdLVi/sxnff3hhpg0l6wlinZUSo5CjTJ5SNqzZHjMQrh517jYHzf2KRy27rspqJdsz3NdaNF7n4CrlJoVUbUNPC2NWDdQecbBdtyyMfC7e8F3UQyrjld4gbR6bq0H6F0+8aa7giIDLzp6CmaOhzm15vbleOBBGmNw37p2H79w/H3e+uDIqU9sh0khuFgmS77TZEqWDCV333Zunqz3hONpKDDdNewtB93/KAAAgAElEQVQ/e2yx0LZb4zZ7UiV9/OpCya9SaqX9lk1VtZ7E921zHVdBdY9JcqjL56wSvOxNpD23JHxAb7yzE2u2mT2Q5GfZs5snDlWHvIhSBmkHtRLnCFy4NNfNTFW3ubWI06+bgeeXBrrqooPNYWdzK1ZuqYwrnG12qnxKIuoc1Uo/VmToFLFNzAzruPmZJIcEwdO2RwrJQeoD9o1L5y3zq+lL8fvnYr2yaSmJw3U+86MCyOc4IS2PmeH40K+ex92zVkpMgNu97g4B6nIXtVL6XovNQW5PMxkxGLXZUdqI+ugCFuraIw5ygfQWxIWi4jED4pCum+jDIgprJQfp7+Wb9uCd7fsw9dGAw4wlB/3ivfCWF7XXKo1yXRz/1aT3bFJNTfT4UvWofMaa6wQ3NY3a5hA3tHzTblz/5Fthm6Td7FT2nzYFVTU9SXEdWgl2RSUHMm5Srn0tXrcT1z60MFGmel4/fSwt8doCLaNrWjueWRoBkpx/WykdiCdDlqZ1BFlcPllPFuwK+Z5qjzjINgf5eiJcP/2C8jlBctB8HbY0Abr3bsu/w3XVpo9yaQUOKXf147apzstZ4Ko7xA9L3aZ9A+CQP+zpb6qN1wTgwnHDE2Xicz/7hmfxwKuxq69eGkyXtSkM0qaNT2VArwsPI/raxCOl/tSb6XfOG505ISP31irXu84EZ0Oz5neqngOjxpFSK0nPzDY2+THqJGhxrdk8COVvritkEa894iDni5evCwWqFxr4v1OqbhboXvyLy5IctcxsuEgOlUAibbmpXgeoOJRpOBy8i9LtCL/l+Qjt3fOymCMyiS994PDE33xTkQ9AIgqCClVQMRByhG4wRj3Ed8DnwsdiMprLz+r3nxvnPEYgcOskMsUQlL8OVc9ABXFsZldWXbnd5iAeYFVi9pQdskSpUyuJ1VQMgQlecugMSM+8aFCcq15oPkeRp0WcJVUiOMy8uWZVx/DmXGwOOvzxhRXRIeauHzVZ+rK1Uqn1bZMc1Ko79W+iJJemI35EAElfByfOcspnxpLHqYopwlUbhyrOwfSsdu1vi6RGXo9vYPJGZeI4Jx4zGGeNTies3LgrHe/Qq76A6y48XitFNm3cjScX6l2GbdjX4qaDT8zHMDft0buKMpk47NwXu9iWGDMSWMBdrSS+G5t7+cZdybPDveTQCZCfuSwdiAtDpRvOCwbpYkQc9P1lCYKz3Rud8FbGwvnRI4vw0ZtfwLJNu/Ht+17P3oACduOoWzv/dtrI6Lfqlq3C0ZnOkoMmm2cqI6zmflJsi3yDtn3oA3t1i36rnpFSrWR4qbua2/DtvwXvTG4uZRdJSEwx+FpSHQSlIlY/v/D4KMeQipk458ZnMUOTfsUFex2Jw4vL4uyr5URIK72VmJ44MJZ8hi4ZW3WSVy6hVtIzoT/65yLc/vwKpzariZojDiZjFJBcZKqPmCiOnOXXxQX03ftfT3xsKs4rq8i4r7WI3fvbIikn67LhH3dLsYRrHlyAB197J/O96mvWu536EFUjNoO0ay9GycFB9S6qD4FgU43et7Rm5JQsNocEpVrJ8qgemhfYo+QNUlYr6WwOHFnjFkxqpfbA1Xvn1zPi/F6mZ6SVHBTF8jfP43qA4PmKV5WMQEr7YH9CKhV1qcSws7lVec67Vyt1AuRnLn+nd896W7imVitx/32+wMV6981dkzgusl2SQ0hYVm3dizHff7Jsm4NYvW93/fnDqvq6db9xZ7PRd7suT1ZXV1UfaicAsa7b3E31nLyVkHx3px0+EK3hhOTNPUUchDm4nCegwnfOG60st0kOWkN8OGuVTdoo+eovRbjlMyc51ApwUO96AMAlEw5xvodDNcxbed+aObjEOYhVWotJg7RLfi/dNyL2s0JxhOxvZzbh+B88pRm3us1qovaIg/D7rOufUVJtDhW1zxFQXwgif7nuOevHVS5TECfey3afuMB7ayIv1++IdZ5i+zrxdsJPpxvPTC7kcs62lblvx0d3KCUHi2RhdWWVU6Y4Ms+i1FfIUfT8bbmRbGqJ5la75HDlGYen6gDZ7DwqtZIyEaSlVdt6nXjMQeYKAnrVF1DIEXp0c4ueT44jPZChoeori+QgKwQYi59PY+/6VM40W5suMS7ffWB+KsfSdINazquVOgHiAluhSfHMcfzwvqmynEpyMLohun+MhwzoId2bvM7VGpkN2g51TvnZ9Lh+OB8iKvuUrCCBmVvd+Wt2RM9S9aGJwUSuoxHTJjz4aqxGc01KSJT08c/ncpHNx8b5iz0crTi/WqVSsRGwOLYmqFcfppbeuS8ptdgOHcqSJZgPxPbE6hS5MHTSbZGxslVVqntsnoMuaiUGhtGDe+Mv/34yrvnQ0ThsUC+hruJ+qdG/a9S0cj05l1W/HnopviscF1qDxMG9rpyVEwg2Kp4zSKVWkpFFcki52Ur1uFGrubXkfCBIXsoV4zJ9XocxVnYSvyANgfu9PApa1d0tQopt52R8mpm2FkvOcRziPlqXp8ggbc2qKnSdz6f7UhIHabgyUxElwQvrjR3RDwAwtF/yACLd6+KtZY28tVXPKdKMmMbBmDlo0AS15xDvz869c4gMwrod+/Dkwg1YtXUvTjt8EHo31OHuKybgjKMCry4VcySX/FJzNoxtmfTv0U17rSscG1pzxMEF0XGcig0mR4LkEKmVsumVXEVgk27zdenELADKQ2TyueSH6GKvSNocyiMO+Vw29rDoaE9x9lbS1GttKzkbpBNqpXwuGmMWn3XVOJSurJZ2Io4/rPjB4w7GQ1edjotSgXoiI6Bev1n7Nr0TXYoU2zdRDmesukd6LIp70hCf0ak/C841Eb2nBvWqxzmhqsxFrdSqWQ82qdskOXQF1BxxcNlceB21/hupCOms3LVrbZNBV3Uq2Tk3PpsqO35Y3zI2eLPO1QUu2S1F8Lnau7NzcgDw5ML1yrtbS8yNOCCpVirkKDJIWzdTmw5fUWaPyuVZjkKVH4ATRvQDEeFvXzo1blto5ykhDiG2OSjGY1SLGoelJQ76XEcsILmVkhx49qcMkoMLiPTtyiV1CukQMMdQAW7OIZ2J2iMODquSSf+LEBPvRdGqGT1jXPWjN05bom3XdGSliJ71BefkZRy8/swlm8r2msjn7bpqEb+cHojm9qjrdJnqFtXZ3UAgOSRv1vfF391hjT2RzxGK3OZjmZjtumsgnwhZrSRu8uKZx/z65t378dW/vhaVx95K6RVpSrlio6MFzcZoko7LtjkY1Ur2e4b3D43XDouaP2/lty2V6QjkN+81xxNlTWdSbViJAxH9kYg2EtEbQtkPiOgd6Uxpfu0aImoioiVEdJ5QPo6IFoTXbqaQNBNRPRHdG5bPJqKRlZ1iEqaPkC+eSK3E0lxmt0IuXpAle5tKg7QjN/P0Yr03Q71jOmw54pP7y5tQCRfrQs6e+lgENxpbzzVup1rp4L4NELc8HbNAFKiSbr9sPO6ZcgpELZlV9ZUYR7LumaMbsVzl5WWZl2yQFtdVMoI8+F8n8cnrceXmPfjin14x9m2aruuBTokxgMpKvaF6V3yDTUU9N7fine37on5uuPgEPP2tMwC4eftxJwilWkn6+5iD+6TqiN5/5eBAycp6J4BJivKbGGNjw3+PAQARHQtgMoDjwntuISLO4t4KYAqAI8N/vM0rAGxjjB0B4CYAPy9zLk4wrYtInQTgxabN+PWMptSHMWpgT0FyCLBJkX6AY8e+1tSHsGTDLmVdlw9mcJ96ax0ZWbl/k3R16mEDMe7Q/tY2iNyJYKJvq+Sg+ljd+pn+7TMwZljfxIenM/zx0nOPHYyDejcgR7GaLMus5OF2y+eU0cG2OcinsiXmIPzmY5TjH3RqpQ07zZsYERnHpjuUxio5VEitVAiJkxyB/KFfPo/Tr5sRjbx7t3zk4eWiauJGdpVmSL59zsqtqZifr9/zGlRwVdNWgkFrL6zEgTH2HICttnohLgBwD2NsP2NsBYAmABOIaAiAPoyxWSz4+u8G8HHhnrvC3/cDmEgqdrtCcNGvMgbcL2TcFCF6ZvBFdv5vXjD2KYvtr76dNiYDbpvOMUMCLsX1MDFZcnCBqXpg4La3R5Z2dKic5JCueHhj4KIoLi6T5JD8O3bNtauV4gqrpU1DF+2tavO+L8a2BNllU2wlmZiQGfvJkotJ7kcFXbyCqV2Cfq1zLywVVPdwfb9sFH4nTIQYSVow2xFkcIFIpVZSEZefPLI48ffm3WqGcb7gSNIVCIAJ7bE5fIWI5odqJ85KDgMgprlcE5YNC3/L5Yl7GGNtAHYAGNiOcRnh8j4Co1n8WSz+UVJwighE2JjtA5MXU1uphJEDe+B3n01myXRZLFyMdo4ULgHLMh5TaGrZVV8sctqZ+raqbFQ6YKeiTJD5k5wgCdm4fHE93Dc3yWTojsdUtThh1IDIpTIXSQ6cOpjVSrrnKNOMrN5rMuQTy5il/2AMelfWDxzViNMOV3/+qja5vl/nXsw5f/4+c+QmSedMaiXF/bIEtbO5LV0Jye/WSEAPELWSCrcCOBzAWADrANwQlivtr4Zy0z0pENEUIppLRHM3bdqUbcS8YYeFwUVfju4Sd8QvuW5+6fw3weKTg+xc1CO2syRklBjD1/46z6luNA7Lh+36caltee4bq3ps9r5tKOfDy2WQHDh2NbemynRCsW0zl4+mFZeU2KJO9fXP+euU/dvcLW3PSmf70huIWSg5qCvkSN+naqicOOjciyPvrug5mtVkHHkNE7a/rYhF63am6vduSBIH1buXx9kV8ieZUBZxYIxtYIwVGWMlALcDmBBeWgNghFB1OIC1YflwRXniHiIqAOgLjRqLMXYbY2w8Y2x8Y2M69bDj6LVXSPPByZBtDnbIxIGlErsBjpJDni9at54ZggWdBRYXdaeBEqkXv3XzLyOVg+oO8xzs1EGukSP9xqsbj8q2oFUradriz0s+eEecg1pySLazIpQejx2SNJ666MBNz5IzPnwIsWrWvIh0lwmkfUbK/iO1klpy+P2zwVGsuUhycGNudAbpm6apzweXGUhVihS5vfYltex4lEUcQhsCxycAcE+mhwFMDj2QRiEwPM9hjK0DsIuITgntCZcBeEi45/Lw90UAZrAOPM3GZdNgTK8zBOxRmTLSib4YcpQ+gtFVXZOlb8aYc+78eBz6tl1j20iTdsGUuhhoP/HIWk8Llc3BNfFh5O2WvqTzXtS7NwcX8pJaSVw7iWNUmXqMPGDzMycfgu99+BhrvxyENKd9z5xVqb6zMDpmxsskXaXLuLfUTx5dnL4I4OHwdMWcQLxcvh3SEAedAT/vSNASp84Z6nUFqULtaiCAiP4K4EwAg4hoDYDvAziTiMYimN9KAF8EAMbYQiK6D8AiAG0ArmKM8Z3pSgSeT90BPB7+A4A7APyJiJoQSAyTKzExHVwe+QOvrsHMJUm11RPfeH8kEsq+1d3r8thnSEEsb4jFkoY4ZLA5uOY8KjEYx5aoW2LI5cypDcjRlhAYpBWSg8WQvtKS78o1zsE8B/MYgLR0IarJbLPnY1Q9J73kENT9xjlH4szRcSK72HU1rBdJDonBxu1oxsjzQRERxgyL1Zm2dyl7FjHGcPWDCxLXgWDzLQr9mw7fMfmbqFJxxPem23SNFRAlG5dPR44rkdsBgOe/exbe/4uZAPREX4aYusP07DufNDgQB8bYJYriOwz1pwKYqiifC2CMorwZwMW2cVQKLpvGS8vj4zo5Z3K04Muck77Uow7ujddXqz2QgLQ+tMSCjyDroeOAYJh0Jg7MWQVVZAw5mMXunOPHlcup69mI2pS75xqvu86b11KeaeBwvyrxXcmROpjUT9pXHlYe1Ks+4bHDOVdKVkusHXFjik8nTDZ/5ZlxlldxDIsV+nN5vCJBl72C+EYf/C9ufOr2nAzWmnLVLaL31f62YpQxOd2moFZy+CC4F1RLMclYiUzDCCFRpquDZalkf0aA+zrvSPgIaQtkXSIgGqTDNi0vUnXaXI5UH4F9bHHQj7Vq2JdbPUDcWEw3uelsCWoJwyYZtFoaV101nhCmuFSOp3QuJxikLe+JJ2ZUbUK6mBheUx6a3ETUpkatpBvjxUIOJrGL659SJ40T2xbbku1XkbpGGr/pGZk83oIMBOpr4j3D+3fH09/6QOJdLlmvjh8C4iy2OY26U0afMLWFnPVWNzZXRq/oKjl0Pm2oQeJg5IrThmZVmorY5zyoaRPN26SdnHsrmfS0O/aqvR3yOfdAHnGMKnzshKHJcfGIb0N7puC2xt5xgJ7ONnHx72YZWrenw3717W2p+qo03Db1hlxPhvypi7pq26M39fn80s3KcpWhObjA+0+Wi3+pguDkR6I6HtQFwbzjv+Xzs2WbQywZqNvjuZV013MKRw0OMVfR6MG9ccRByXToJpfthpDJc7U59AuJw459ye9QRwNcH2/ChmGSHDTlD817R7s3VBqeOAhQvd8GhauebHOw6dFlo1YplBxSxEH4LQdPcfDgHHe1kv7ahFEDkuN0UJuoPoJPnDgsVaZzeXW1f+ggGx6P+u/H8fn/fVlRU6/acUFarUTWjQ8IIthd6slQGZqB2BsnZXPQxDnoDNLlqDD5fWJbMnHQRV7rNuBPnjTcGHVNpLc7iB5AKukvrwsiAdAQqpt0LtYyeoWuqbv2y5KDemzymMVqImE22Rz696iLTspTPb8Vm/fg6/fMw9fvVUdfVxq1RxwybhcNCsmBJAnDxonIqpISC9sQFtAlEw5JfIQ61zzu0uisVjLM93xJcojSZptUAgp10SdPCoiDWGySMKoBk+SQcFnW7Jlpg7SbK+vRB/dxlihV45WHc/3FJwCII4fFrKwcDXV53Pa5cWGfyfY4xA3KRa126MBYn56QHCTiTpLkwKGa+phhffCdD442Sg77W0taLlw8nlU1BVMW1O4ZJYfo/Ut19ZJD8kJjr1iKFj2ZbEFwPDWNKmcV9zpsb94mV9Qecci4X/36khNTZbIv95sGXSeQVitxm4O4y9RJWUx1J5bpgnN0MEk18kLn4zQapBWG5njxxxdcOTQdjj44fYJaFvCulTYHMfGeZoyiUwKQjPg2Eb1Egj7XwQp15XcytF93DOvXPRozfzcyk8yJh25dZMkA+sJ/nhV5NNkkh2hTFLyBdOPo2a2AXI4im4PqOT742jspFRivt1+QHJTODjztu2IBc/Wwa+R+bDuRyzWSg1Q8MCQOA3t2S7wrUxAcA3Djp8ZiYM9uqaC64Hp1ma2aIw5GKN47z8cjQtSvzlq2JXVdhnwAfaBWokR0qcxN6SSHzMTBuJElJ9zsdCY2YcuelmQ7io2HMowRAI4anHzOuo/QNVV5rF5RXHP4yOZKto1EbiXDfaKrbzbJgUsE6nnzMWvrSapOuetcQnIwj2V4/1hqkG1HMnHgNiAXm0Pcr55xaCuVUu+e122xiMtccmhWBH1y9bCrt13E7sjPUfPsVARtwqgBmPEfZyYkB9GtXTWO7t3yOHZoH0tqjfJUhFlRc8TB6XsV6ug2PiD4+LfvbUldlzFt0YbE3zzOoaEujxPCFBokcWi6yNUR/c0HqsvIYmPhx1fqNs986GK1UzLSqc7xVUkOpuM1xwxNphLRLf8r3jdK24aImHtPz8XlJDeevp0jTl/BLE4NdqOsClFdxcRzOUQT0kkYsnu1vD7EDSrL1iLHtchqJZ7gTv5MVHPnYwz+Uz/HUikdUMb7l/uWwZeXKjo5Vis5ettJTiccrrYbxgIbQt/udYl7WoS1p5NAdR5V1dbSWuMc3m0wbaquH43o1eSyVh6Zvw6/uVQcQ6wWePDLp6PEGKY+ujipVhIW0Yxvn4Hh/Xtg/prtOKh3A4CFFbE5yOBiu+4R5UMPq0KeEmqvyEguVlbodn/xxJvKdof2bUjV1dkWdQeryIhtDulrLgGE3//YccnxkKjWMawhUcLI8DVzrli1nEQ7j97LJ6l2kqslpNQM1EHmtF/TxPPI3KzJ1sOlZNVUuLOGCF4vKTmk7+aSg8rpgevwxQSKJqQVpclyGWnnEhZ7cgkTEg+bumvW24l7Tj1soNMYqyM31KLkYLjmKq6JetVyRDyePgMIuPG6fHiAkDA4cfM9rLEXuhVyGD9ygHPqDv4xZDnLgYvjpiRwpGhTdu0NytLPetZytQquvi6falOnXsmaVkB5zKNDGzINEg/bsUljjDEs37Qbd7ywwnmcnHC+uiq9+YpxAS8s3RSOJ20w5+MDknO8eNxw9OhWLh+Y5LSve1xN4F28lf7VFLx/CgmO6j1wqVpu65W3t2HPfnWmU/FeAMp0MVGwnib+Jl0/+F+uqvveVfEpKk8uk/R806fHhvXVY4w91fTjriRqjzhkUTjqLgsLR6wq681HDuyBc44ZnDpjlsc5JLtM/q3zvIjD+s3z+PJZh+Ojxw/JtJlytdJTghrs0pMPiX4XckGAkmzwU8WHyIZMQJ2IDlB7kOgkHucIaa5eUTxGl2RzqbiCiDOPR3bOMYNT93F12mf+MBv3vLw6dV2HVVsD9Ywqp5doj/rBPxeF41GPVyU5HD1EPqnMfXdx5bRtkkuyd70r64Ce3VLDW7h2Jy689UX8WDgzQTUkzlA1G9RPcsrubgX1Fhg7ACQ70m3M8niYwDiKLrYm4sA9I4nU61bn7txRqD3iUIE2xEPNxU3+qW+ekeprcJ/61EHiPCuraWw6b6U4z7x0r7Q624oMprz5qtTIXK0kBmqJhCDwNKGUWkaVh4YoLWHoEgCq7BO6cbtKQkccFBDqO15YXlYb8usR7Sp8bCrjJCd0suFWBZFp4L9lzzbed1q9oZYcVIb49rgUcy5fhwkjB0T1kv2bVG96tdKvJsfegfwgIR5VLjp2iAGXHC6OAPI3oUulQZqd0TWrrsg4ilJoi4O9S5e0MpIcqqRYqj3ioHjq40Pf4vcM65u+qICYW99ExVvaSqlNcl9LEa+t2p7aKOW4AB13y5kQ+QOQ0zLs2NcacX1isNu3zz0q+i3r71Ucl9hPPkdKH3W1WsldcsiR+/GJNkmI++ePHRG809fX7MjcRjAmvdqGc3CqjYJv5C5eVeIwuKupkilQSFY6g7RKrdQeQ6bt/INbPntSOMQkg+ByEpxqXOKmPyL0mpLr/fD843Dtx45N3cufnd0VO66gWwuRzSG11tXtymudIZbmRAO7mxSmUYfysXnJoaOQfugfO2EoXvnvczB+ZH9dlQREEd7kvdDcWoR8mPqfZwdGqJSrpNStzqNGl7L7v/6+IPF3j/o8eO56kTsS/adTxEHhAnjRuPh4jjxRSt1yxEG9tKkZ5I9UxRU/8tX3KXWsxw1NH9outynHIgDBc+zTUIjaUw1NfB5ir38VUlHrN994w7hw3HCkEG7kqpxcHzl+SOJvcc48uFGldiB5oNBLNvx2sbq8uZs2l59+4j2pdnWb7aBe3TAo9OdP2zzS9fk64dy7MsuqIE3J0gjHZ04+RGlD0aVUF9envNZ0c4sDXdUqVI5Hvvo+5f2iYV38ZlyYIL3NIVQrWVuoDGqOOOgW7cBe9c7iWnxKKDO+qX2txZRhVuerLYvvukXEuRBZHJbd9755zlGRiiPhWSQRBJFTU7kAThg1AH/5wskAEAUwyZBOTQ3LkqLxrGVblHMfM6yvcgP65EmKjRfxB7JhZzMm3/ZS6joRhWnH9dy9TrK/RkxFLb1Y0RGA3z5qUA/IyIXWY5XkcPrhg5JzEX4XIrVSenCqdBMykeYbILdVJdVKUnupHgL89tKTEjYmXtlJ0oribxD+b76HgWH11nSKGDFYT7ajAMFaK2g81nSSQ30hGU8Up70xqJ/4ONP6vARGDuoZ9hlXXLdjH97esjfqRyROLp5yKpUsIKwXH+fQMVC9mpijcWvDVXIY2q87xENiAL2+UN4A+EL/7aUnJerJhr/lm3Zjx75WvNCUTOjWUJcPpZYkoZEjZZ/+1hkR96PzI+cfQODKKo0bSJ2pHcwn3shvfGoJLrn9pVS652hOoaj/25lNiXZV4B+h1rgNYPveVtw1623sam5VepeIH7KuH3mekeqsJHKm6bspbF8VH3Ps0D74vqAOET12Du7bAAAYFT5reSwqg6eIuuhEtJB7Fl5GyhMsw+bCiR0AzHxzo7aezOUbOd9QTP75E0tSdQLVZfg98vuEuehScgNC+hepb9HoLHLlZtsE7zuJtCNJWE+o+MlbXgQAvLaKBwjG18R6OtWjHPPEwfeRakkONRfnoFoP/OUlJAILKFS+617UHZePx5hhfXHrM8ucjOCyLp9zgCcflkyOR5LN4ewbnsVhig0FiHWXJuLQt3sd6hqD+5s1RlR+v/jhiuDSTEpyCAtuntGUugdS3RJj+J8n481Ct/nbpHLx2338jfUpl1RAr1ZKNiSPkfcvEBaNFMXStwMIUlzsbUm6Y3K71YmH9MeDr76Db33wqNR9KvdLOV8XESGfoygCV/R2ac/peZzYAcDn71QlOAwge6yZGGT+vlU5ggqCZw//Ka5fnXeRWE/uWmxTdAs220WSNpS4XPpbIiIL1uzAunBe/N6E5CB02q9HHfbtSK/zuhwppezobI8qUYcaJA7pFRFFbmagyVw81UkOE0M3R9kTR/tiJfUTlxzkzTxSKwmNLteckcDVNeKCVNkHYpWE+muJ9Pc5lQtlfL1XfSHyKEkcjmOBKmpVp35zNVwDoVRjkRz09ybvi9UmcZyD6lXyiGKd4VJuN95Mg1+qhGsqjyGVq3MhR5Fa6tVVsU1rUM+kZ0+WvcV8LGxSlw+YbQ5imyWmfg+yfUBuq95AHKJNX1oj4iMVHSXcJAfzWpGJCI8YB4Bdza1h//GckvYOddt9utdhV3M6piNLzFIl4NVKIiLR2N4O9+L45dPJw1L69Ui6rcpeSHxzl9Nck0QdRG5d7je4bh9jbHOIK6uIg8rbSEQ0FoVBGohTE3ziJHFObvYLHeEAACAASURBVGkKgv7TH8q5xwzGzZeciPu+eGqi3Obtcf4J8RjaSgyPv7E+VcdlXCn1mWiQjvzNFWqlcCN3TbMQqTg075tDHrJKRVfIBZHr2/a04L//ERzrfv4JQ3GRZDjPwnmajoUV3wVvk68VY06vXOAObfvOVGolleTwPxcdn+hTF6TJf/PPQSedipDHKDsMyEREdE/mDN61H42j7V1OguvdUMCu5rbUWo+OjLWOujKwEgci+iMRbSSiN4SyAUQ0jYiWhv/3F65dQ0RNRLSEiM4TyscR0YLw2s0UfllEVE9E94bls4loZGWnmIRqQZo4QR240Uj2Opr57TMx7ZsfiP7WGaR/9smkV0gg7sY1Y8kh+Yp0rqwc/XrURTYEzpGLi1CVfkK2Y3BwQ/ShA3vi/BOG4jeXnpSWHEAY0rc7nv/uWfjOB0fjslMPxe8+O845eIr3n3IZzBHOP2FoKseRbWMXj8N8TeCeD2uMVW8ux0TKG78qt5JScgjtPNq8/1Kx7PqpIjiq53Pa4QNT9Qr5HNqKpUSMxUePH2I8l9kGldTCIW6UqcR7ivpMqMuYnifnwaRD+3VPtAmoJYeLx49AQ11O6DvZsvguOMO0t6UNJ/14mmYEegKqO4yK9y0ayzmhjLwgkVy/uu+jd0MdiiWWSgMSq5WqQx5cJIc7AUySyq4GMJ0xdiSA6eHfIKJjAUwGcFx4zy1ExK0utwKYAuDI8B9v8woA2xhjRwC4CcDPy52MC1RLknsQxOfh2tvRBZj179kNRw7unagnJy4jSi/ytM3BLDnoNrjjh/cT0i0DgIvkEPxfYgyPL1gXlZ92xKDonpsvOTH0LFJ2ixEDeiCXI/zogjGYNOZga/CU3L9OXdRTclm0qYTE8YlzFW87eog9HbjOIC26ssrr5J4pp0REUbeGdDmITK63ovQ5pG8DPjV+eCJzKkddntBaSqq0VHmGdEZd1aPlxE4F0QuO99kapX3Xv6c8UeJ9y4Tu399/GO7/0ql4/5GNAJJrQzd2UV2UZjSE+YQM026F2kaEGOgqQg5ik5mAgmLNiXVEbyUdj8JVizIhivYp48grBytxYIw9B2CrVHwBgLvC33cB+LhQfg9jbD9jbAWAJgATiGgIgD6MsVkseNp3S/fwtu4HMJE6kjQqXoh8iLsLgs3cRXedXKwbd+1HQyFvpf5cdyzbHHRcfnw9/r1q615s3t2SWGSqvP6iysR64Lyzu685eEruX7eZyHntbUy/rELgOFyQHL55zlHWIDX59SSD4MI6oMRRq0P7do/sPLrXe/zwvjjpkH6pmAfVRiKOJdKns3TuIY7Nu1vwl9mrsH5nbOhVPdfRGc7KMEmAotstXxexx1Bcr1d9IVHGz+MWdf9/+9KpeP67Z0XXx48ckAg25dAZpEV3aFNGWs4wZUmRI0LesCMXZwUzp0p3kVQrqZ8rn6Nsd+PPW9ZWdBTKtTkMZoytA4Dw/4PC8mEAxIQya8KyYeFvuTxxD2OsDcAOAGmZuUJQvY5Il5eBOrgeVC6Gws9ZsRX3vLxayc2JGwAQGByJkFIJqLxm5HFxzAuTuG3YGUdP63Ta3PvK5oetMkjr6rnaHPIaKQxIz59vKNsUqdKf+85ZifriXP/7I7ELaSGfw0mH9rOMKtlvIreSsF5+fcmJGBaqP4hitYVIRK+/+AQ0Tf0QgMDF+MEvnx5F46clh/QD3ddSxNtb9oT17GqFRWtjAq+zTX3gqMYoPQWH6hWYguBaBYl0cOiKy5//hbcG7pyfO+VQ/O/n3xu2hej/UilWz5UY8N6RAzBiQFIaUhmFtesXemN4yubAYDE+ivaOGFv3tGB/GCj68FdOV9ZTBdiJI05cFx7sH/9tfPSbSw6yXcl2vnqlUWmDtOrNMUO56Z5040RTiGguEc3dtGlTWQNUbULluIjJqpBfhEYxGaJKQPQgSdWTIqnbSkzL5YseQqpxcXzvI8ekrss2jPi+tH1CV88FOl9tjjNHN+J3YeqFXC45H77ZcgwJNx4grneFwq3ykIHJzUUca32drMYzz0OnVmorMvzf7FWJa1HAXZh7iiGpysjn0oFbMlcc2xzSY1m2aQ+WbdoT9WUzISTOKdblDoL6W0jVM6w1sfhXYUbRkdI7+I8PjsbAnt3CtoKB53Ok3SSTfSftGADwioZr5mrMUomlNlHRBsOdH2QmaOLRByX+lvteu30fTvrxNDwyfx1GD+6N44f3U9YT9wRVIKZIrMUhnH10nMSxrhDUF9N7P75gnTJPWEeiXOKwIVQVIfyfR8esATBCqDccwNqwfLiiPHEPERUA9EVajQUAYIzdxhgbzxgb39jYWNbAlTaHSK3EbQ72DTCfS+pNRbWFCP4R/uH55fjHa+9o20tLDkzLJeUNapgTD4mNX6rzr/mmpdqsSow5GWtdYDsm9M7PT8CkMUOiuuJ8fjl5rPY+Prxte1u1deK6ok5c/Sz16cnVEtvfXlmN18MzDSKVAovrEAV5rsT+VBk25ayfJsnhGCGrqsl9+uxwgxMNxdrcQZT+FlTPQpcEDkg6VfTv2Q296wspSaV3QyEar5hOosji/nXSauSZ50DFeFT8v989F1+4e27imhhbwm0Ookps6ifG4I5/e2/inlgiCOqtEqK5u0kR12K9YkJtxPuM23XJ61QXSQ7xw7zyz68q07l3JMolDg8DuDz8fTmAh4TyyaEH0igEhuc5oeppFxGdEtoTLpPu4W1dBGAG68CT6VUtHxvm8eEvUT6JSoVCPicZUdX3cPXTTx5dbDxrWubkAslBz+Xr1AVXnhF766i8VPJE+OY5R+EfXz492X8kOWRTK2nrofw4B5M9QFTr2CBy0C7DFs+t1kkO+1rSHjrixs4ZgERmW+WmG/zPr8RcZnpcpx42EL1DvX2xpJccvnL2EQBk4qCuS1ATLdU4dc/7kgnJVBu5XJppyeUoFUeUp6TXl2mMputy3RIDpiuiuMUUMXw+NsZBtjkkjeLpg5NU9eI6guTgYJDmxMF2LGpHw8WV9a8AZgEYTURriOgKANcBOJeIlgI4N/wbjLGFAO4DsAjAEwCuYoxxBfuVAP6AwEi9DMDjYfkdAAYSUROAbyH0fOooiO+jV30Bc743EadJOW90HLtcR5dWW4RJLE9VDPHn2W/jhaWbteOQM0smr8nGN7kbwtfPOTIiiGLdIJo6+Ft3IH0qfYDBZdOVwstGTxMBYizJxZlQFHW2WtuIToctzzP4X3WimmizUvnO63T5AMDC582fu2qjyufEvEH6A6b4vaKuWsd1q1Kvq9tUM1TfOjcdyV0QIrSTffEfiMa3dMPuaPPTr2UYryfHqXeAuOv/TUjWY0nGQcUMxon3gBebNuPxN2IvvmRywLgeoE+1//vPjQMAPDRvbVSmNUhrvJWqDWuENGPsEs2liZr6UwFMVZTPBTBGUd4M4GLbOCoFeRMKjt3kf3Px14E4EElRqvqP0Ik2COP73t+DkBKuq5XB1TDyR8PPMBDH6AreJl+whbxu03SDyQNJ3bfYh74XXZvfOW90qizpaqluU9zMxabT3kpBQYPgSsnHWRcdQemuupIJi8kpIp/LRRs5Y3rmhReLm4pOTRhInw7MTZi6o2nj7kT51yYemW4zp5ZoOcPCx7fgnWQadZtzhS4nV2KcBsP5kL6xDSuyOZSS+4AWjOHSP8xOFL20PKn15s4cgP55n3fcwaqmlajTGKSrjdpLnyH81iXRcjmmWJYcdC/afTNNt6MLXuJqJbnPq846PPF31gRrolqpTqfScgyo4gZCFWQvGTlCWjfsQk6/ASizrwrEW77Kq9tcd+X63Fgolv3fF07GP19fqyXmqueQzkXEQm8nteQgRh7rXkG8mcbzzpJuRN1mMMamjXqVaDROIuXmGAsO6oHrtCf8WehORUzWdXQtD5kW0eagI+qyHVDbJmIVkYs2gUNvc0i/x85AzREH8W2nUyS4N1PIk1MCN3cdfXKzAEyqHSS4fI68tKGrOEzdeLiNIAq+c5QcdNPTBU+9dM1EDO4j5fpx5GILeb00oiLoJslB1YzpXanyb/Ffhzf2wjfOSatZOFRTS0sO+k0qnwvsW1xXbtrMADeD9NOLNyjL020G61xn/0qOM1ZVFXKEj4cpYmSDtAyTRxXgtuHq1F+qei75xnj/qjbff2RSDS1mVH5miZsX5QOvrNHOSxfnYBtvpVFzxMHkMx17kNjbcZUc3F0/eTv2RcsNf3KXshpJaXMw9M9YPHftZuC4LnXBUwcLbqnJuvq2mDAmxpiSA1U9Z3GTzEL4VVDGlzi2qcx2KrlAmiSCONmiOc6BP4OEWqmdvh18XeiYhUT/uXijL+QpkqTi+AZ1Gza1kosHne6AHBkB01JKHDmqZZg0doy7BRtG0Gb8HpdssEuibcUSvv2317XXI7WSxuagSs7YEai9xHsJyUG9mbosxoLkyqp1iXQcl6qeTnLgrqwvr0jqPuU1kyWnDncF5CK8u0Fa3R5RhiA4ycvF2KZG0lYGj7WKaiW3cetAio3KNVpcGa8S/s8EyUG36XP7D5cebGql7ftiN9/2aibyRNqYG11dIHAVFU9+C36o7zv32MHK8jglh8um75hQMRfsAZfcHh8UpZXEoJMw02uJVxs7whZcmXYSePRrydPkuOSgm3d7VYWuqDniUDIQB1nUNyGfyyUlB029rJuQ2M7KLWqvHAptDrKhLE3s3NVK3ObA56TbC1yn48rJBWMiLBUMniYpzCX4j6NZMDbrDozXQe4mCoJzNWSG+NCYg/GJE9On2qlsDjoHAr7JzlmxFa1Fu1pp8+44Ij6L5KCqWl+XQ0ux5OakEWVbZQmCkjPQhg+/52D8xwfTzgRAPB8nw7nC8aOhLoffXHpioky1hkxZA9xsDnHfJmL8pTMOR7dCLjXO44Ymz65XxTmIaHXxQa4Aao44iBx+ek24q5XSkoO6nqtRWGWQ1kGnskkn6VP2pG1TNNTphuEuObilF1G1qa+nfzfy8acAsLdVUB1I1+SsuC59A0i4atpGPahXPW797DhlPiCVt5LuMXCi8dk7ZifGohvjzn3xvD+o4cpVUKlQGgp5FEsMzULKl9GD1bmZ8rnAPhGpJsN3EnkBKgY+sGe9VsKNDNIurqwK9+5Hvvp+fPT4oYkylVeTnhFy8zQMsu2H79GweXDHApE4HTpQnUARUNscejcUAlfcKhira484CL/PTIXMB/+7SQ7ucQ4uUB1oLrumin2rxih/ZFlcWaPIUcUZxMl6ru0FH+sOh0hm+eOUI7tPGBFwVj26FYLgKcUmVq8iDoLkIBOgoX27y9UT0KV9TkoO5odhNnCH/QheLtqIeNk2ppUcgnLOcS75yaREhuBywOM6RB39QZJDAQd3j+X983FHuaiU9+j7js8ucbMlpALwFG2rGCujt1LGWBCRkP3w/OMS9Xg2WnE+N306nQ2gm0FyGNQrePZ7NUf6VhK1Z5AO38vtl43HmaOTKTj4EnEhDoHkEL88XQCOK1csjw8A3nfEIGUdXYS0TAyyubIGH0Kb4gxiEXJ+KB0B4h/Mxl1xhtBDBqS5pKBusg35HOWbPj0Wb23YjWsfegNFxpTSg4q7TKiVpGHaHo3cXKTiSGQiTWNQr27YvLtFez1uj0upsY5eddYGkCYONntQtDm31wqPmFAnDbh6IiZ6vPFxxulFVGpO/Rhjm4OdS1ZJlcr+4FYvGFsWtVIsOQzv3x0v/OfZ6THm0sSOR76LqJOC4MT0H326B4eJ7d1fRJ+GutS9lUTNSQ78dQ/r1z31McZGR3sruRyhtU1YOjpO23FUqvWpTU+siZCWNxEVJ6o7ZpHrYjlnrKOP/2raEv0ed2h//ObSk5T1OCcnJj3j2TlTdYVhjj+0f+p6j24FjB3Rz5jiQ1Umcldpg3S2jVMlOaj6NAXSJfqX6rcWS3oHBJk4aIiIbMDN6vKotDmE62WPQBy0XlWhNB0dVBWOM85iS6lxmZinrDYHOTpb1bQqklrvmJdOHsmzscr9iJKDKScakDQ0q94ld0DgjNqx1z4ZXesTprDf02I+j6ISqDniwF+iauHwIhcdZyFH2F8UJQc1nNUw0eEiyT5UyJE69YHO+woAvjtpNH54/nE4TkqbEfcfcFR8M+BnYJtw7UePTaVZFvvetrc1wXHqOB3dGQwy4pw8CuKg2ED2GiQHEY/OX5cqk1vj97+2Ok5+plIriiUmbyb55LTWCkoObcUSgiSA7Zcc+OE6e/bHz3KE4qAh3n+xxCJ9OB9n/57d0Ni7PlKz3P+l+OhXIwHNolYioKVN2vQ1korM/JnVSvHfQ/o2RNlYRdTlcxETVCzpHQu45CASsTqFi7Ccs0uEKDl0NGqPOIT/q95fTLHtokM+R9jfqk69IMJVrcQ/JHHTf1vjrZRXGNX4mBJ9C38P6lWPy08badRXlxhDfSGHhrocfnTBccp6nx4fJ901caazQzfbm6cvjcrktNnROMVmLDroQG2RviZuID3DCGzR39/0Gq76y6vYZzlPmJ8c9rpAHFSbuYtLLhCfR/HUouCM67ZSSblRAGn1kPFMDgCtjkFrMo4+OM048DUkSoA676KCrFYK51OXz+Hl750THXAkjs3F5tDm4MqaU0gO6nrpTVd1NggQurIKf+sSQo4Y0D3K91ViTGtg5+/NNh9eT/WN8/QtLnNtL2qPOHDJQbELZclpUshRYvNxPfXMhulC5OozS9IZJgEeQ6BSKyX/FgmTzU89lwPAgrkP799Dy8V+7tRDhf70bfIMtBt3xW6VDZojHpNqBsMYQ67vZ48vTl0b1Rgb7+++4mTlvSYcc+0TeGf7vuhvWTppVXypAxTpMkxxNCL487njhRUAgg1Dpy6Sm9EREdHmUAZtSCVjBGLCxA+5AQxEPvTga5NsDqk2HdVKsYeYi0E6bZtQbdKqVPJ7NFy47B5bryEOfRrqsLelDVt278djC9Zr+Rv+LEUvpH490mvI5BjDn317gxtdUHsGacXRfRx8MbtkQ8zncglu6r0jByjruYr2XP3y9XvmRWWqDQngm6RdrSRynDb9c8B5MWzd02IkJCLRcNFp9xTyKOk2NVHdZFLFcKIopyi4/0unYrzw/Pt2Ty9rl7ewSzhXWH66zY7eIa7pxOWI6yw2BzlNStxmzJmWIzmo+w7+Tx6Yo5dwiiWG+19ZYxynKqupCvHRoy4SAaWYOmWGAEpLCqI9Jdl/kukb0V/t4ZbPEZpbGa59eCEAJGJ2EuORJIefffI90RGq8lwAtaqUezJVI+1S7RGHSHJIg3NuLnnUCzmKuKkfX3Cc8mAdwMwJ26DTtepcWdMuj/prMnJEePj1IJ2w7C0kQjSSu6jMEgejaOqLKTVMe5ouk6jM8ar6yeo1JmO/RBwe+er7lPUSNgcHlQmfTmuxpJXW5LHrMubyV9xSLKFB43iQFbzv/a0icVDXzYffxI3T3gKgZwYKzpJi8L+453/ixGHKukTARuHsbEDNaLS0lRLSLABMGpPOmBo2kNigh/ZTEwe+Lm1MJX8cXMJxSZciI/YA63jJofbUSuH/qg+XL2YXLjGfp+iD0XFIgLu3kupVXzJhhKI0jpCWkZIchNVnUyuJt+7WcFJA8oN3kRz4Rv1JzUcNJOMajEbcnPqj0GXXTY7DMlAJcoZV7l+u+5vD1Vsp9gpj0d/aNOmuY+dqmGJJq6LiuP2y8cbrHPwdi2olHaHN5SixkevWR9LmYJIU0zbA88cOVdZ9c/2uVEYBVf/7FRv4oQP1pzi2CBMyxaEUmT3FCL8/Jg7m911kDGsFVScQE4xKndhoQu0Rh+jrTb8YvmhXb92L3vUFzLv2XG07hRyhOfxgTItCpfc8qLdiY1Fsel9432HKNvOOrqyuXkDydZN/vCgJmOb9ly8Een/Ocf+H4rwFDrEVG7etIg4yx53Vn14FecPg3CUnjrqpJ84LMRC6gb0C4tM7VKm1Fkv6NOnS2HUSpSiN2N63nBlXB75+XYz7eYnT1qqfEmolfd/8WjLBpfumaMtKPKhXPW781AmG/pN2RZPar1jSuxhzxN5KwRz0xIGiALzTrpuRuMb3HBePyvai5ogDh0ly2NNSxKjGnkpjEUc+F+s4dRwfoOZi75lySqpM9ar16gO1K6vsBSGuVdMYgzbF+/R16/Mxl29K7HfE4MBAvC8kDrr4iqBvNyKmO9DFpE6rFIgIA3p2i965jtj86QuxMdzESH4zTPHN0z/vbytpDb3y/HTedFkcEFyTBsYGaZE46DdJ8SCfTZL6RjU2cxBcWveeZU9UMTniM/rAUYPwyZPSea/isSWN3LpviJ9joVOjyeOJJAfD7qs7J55rNaqRe6/miIOLzQGwq0xcjb3y4u9WyOGwRnVajNR4NKuHiLB1T2xU44uyR30+VY8ji+RgWrTiYTcmCYO31xyq3nQBfcFAhZ8WHbTrkZEdARdd+UmH9MfHQ9WHaeNrqMujf4+6aD02t5aimAIZcl+6TdeVwAdjM15OtfPsW/ZzCp5enPSu07mIununBf+7pMZX3q9YcuK8dXbCqC6SEpNOfczVSjrJLx4PJw5myYFfU/EA/ES5aqiVas8gDT3nJ378Ns5L5CJMniEyN9Gvu3vIuz7SEli3M94gvnTG4bh43AgcIiXxypPbGNPtG9RKAgG1GY+BmNMxEQdXyUE+TrTaSBIHuyrRtv+K0br724payUFeqxeN09uiOFwcEFzQHkI78Wh1IKXrc4xsDoK3UhZDrGrNi2vbJM3y/vcJ9kdt8GEukBxsZ17wvtssNoeg7zQj9Nx3zsL2fQHBrUba7nZJDkS0kogWENE8Ipoblg0gomlEtDT8v79Q/xoiaiKiJUR0nlA+LmyniYhupkqEdmpgkhyyuGmK1011xQU67tD+SpWSOK7kePRqpWYpAE8mDLyeyxjluiZ1UWLeDj7q/OMyHVBCmt+qNuXNQRWYlOUciywQP37TRhA9S8swRDXZ/taSPg5EeM6XnXqo8l0H/Qr3uMS1OKDcU8c+e8oheM/wvsprrpJDZHMQ1KVZtkTVHMW+XSQH0c3VxKy1lZj1EJ58BslB5ZF4yMAexujpSqMSaqWzGGNjGWPc/eFqANMZY0cCmB7+DSI6FsBkAMcBmATgFiLib+dWAFMAHBn+m1SBcSlhSp8hLibbRyFu+iYpQ5QwvjbxSK1KSRVEZzoJTuRodAF4mVxZhbnr1BtBm27SCN+gm1uL6JbPmXXLQjP7DJ5iss1hcJ96LPrReal6onR26cmH4IErT03VKQeuRnt+zbatcu7w5ZVb8c72fVp/e/H52DYUjorZHMrcIczStN29GYjnOls41Eq3J/7us+kcX6p3JH6PdskhsD9yaJm1MPjPHmialIRsAZ+iWomnXj/QiIOMCwDcFf6+C8DHhfJ7GGP7GWMrADQBmEBEQwD0YYzNYoEcdbdwT8UR+yql30yS03bjAgCzsTchjRg+BNW71m3oS9bvinT5gOGMA0fpBkjOvUGj3kjd46BWai0y9G4way/Fd/Hisi3aerLN4Yr3jVJuLj3rC5EramOveow7VB2gmBViOhPT84zUSlY7T/Deb3tuOQAkjLkixHZMTfboFj9nq+eMo0BQrlrJlYjZbEwyuhU0G7SiIdU7Er9rm+QAUCIjqtbmEBqPbc88bZA2S94iAeDBcnxO1QiCay9xYACeIqJXiGhKWDaYMbYOAML/+aEJwwCsFu5dE5YNC3/L5SkQ0RQimktEczdtcjvIOzXgKENk+loWbw9XvWmdo45etb/rxNQd+5JnJOgOdMmiVlomRHXq1BsyjBukcMkUVAe4G0dlV9behpTFvM1y1CI2jtLWLr9k65pnruX1TBlzVb9VGBdmtbV5zrhqbstVK5kYprzjfGQG7ruTRuPMow5S1lW7rSokB6GezZ2XKJm80ezKyvC7Z5cZ28uiVuLH9nJwozzfEg4EV9bTGWMnAfgQgKuI6AOGuqonwQzl6ULGbmOMjWeMjW9sbFRVscL0SMV3b/sIXT8a8SMxSQ4fHjMk8ffK6z5i5UQA4O9fPg0nHpJOcw0kiZGN2Ini85hh6sytqfYdVAKAnUPLYhwtsSA7JgB8arzaMAvEkpjpPR01OK3iG9ave+pMXxWMaqXIIG2XHEosHqs2K2sGIt8jTFdi904zXhbqlUccXCQr2zjkrq8843Att+1qZxLH1dirwVAz2JhEt2FdF7J9QKfGlBPv2dRKYvocboCODgXr6sSBMbY2/H8jgL8DmABgQ6gqQvg/929bA0D8mocDWBuWD1eUdwwMNgcqU3IwQXRvM30w7xneN5IAPvKeIdp6QPLQHJPKJovkIOK7k452qmd24Y1/22IsXPcfosCFjzHgU+OHG/vnn47pPX194lGpsu9OGo0jDrKfnmZWCXC1krkNntiNqxnqtCoT8R5zm3zPmCdkj9X1LWLye9WEVnzGg3p1w7+uTh9io7yvAt5Q6SNp3evqkPBItHkX5ZJBcCb1reg9pFNjctrvplYitAp9czsFf65d2luJiHoSUW/+G8AHAbwB4GEAl4fVLgfwUPj7YQCTiaieiEYhMDzPCVVPu4jolNBL6TLhnorD5Moqvqu5b29LXRdhs0lwuCYZA4AtYezCzmbz0ZqfFj7kgT31onEWjlOEjoM1tS8jqaKz6b/juiZixzm0tpI9PQTn5EzzVjVhs4+4wHWj4gbpmWEiQd1zzxKv4grxsTz8ldNx3YXHK+uJz69PQx2GafILAUk1qOt6c3VUsMGZGGWww3Ur5BIOErrqOSLntOJAnIrEFBeRo2QAXrGUXM/VIA7t+RIGA/h7+HILAP7CGHuCiF4GcB8RXQFgFYCLAYAxtpCI7gOwCEAbgKsYY/zJXwngTgDdATwe/usQmFxZxQ9v8251oBGHqxdHllxEr4QE6fmlm431RO6nryFuolzJwRUu3DPgoP8Wft/1/yYYvSZziAAAErVJREFU2yyxQGdrcxsslezEQbXRutpbTOBDsxHZIM4hhm5Orq6fgLt6RZy7Sf0lPg/b/luXJ3DtpDNxMF5zX7OuhMTVVggE7yOxB2vq53PJg7904M+EO5OYvoscEd7aENsBo5QbOa5WsnbXbpRNHBhjywGkEpMwxrYAmKi5ZyqAqYryuQDGlDuWLODPVLUwsnBl81bHniWm9+TqrZQFfJF1r8ubN2jRNbfjQkfUfSfUSvZgI46hffWcKRGik8Zsaj0XtZLyGFVHTy0T+Dqye4glPVJ0ad/FZnQHQGWFuBxMS+MgwWhr+z6C92wPehRh1rs7NQHAfX1n8eCT56Cr3q2Qc0vzL0kOpu8inyMs3bgr+lu2UxwIBukDDiWDt1KW/XO7JjWAjEQGygo9bb6o+/cwR1t3tORggrjh19l87sPLw/p1T6TvlpGnwIOjtWR3G+TUwaT+UxFWU4yHK3i79ky4SV31N89N20B4PY6dzeazg93Pk4jbNHlnic4EtjUkcsKuKcPrDPXEeT/45dOM7bhKTOI7sREU+bno1EDvbNunLJfBx/jbmYFXkzEwlJJ7xwFlczhQ4apWssF1s82a4toFfIE3dDNvZGJ/Lu6ZHQabKiR87kcqvIfkeiUWeJDYVFWxzUFfR7U5mGI8XOM/eLsuhvhk7h51/YQUZpOYwvX9nmHq6GSxbw4bl3/1h44Ox2FXw3DoTk0z3SNDnKo1b5Gz5ODOrInP5ZxjDtKmC7epoDnkk+pM6yNHyUBXTgz6dK/D7z47DmccVZ63ZhbUYG6lEIr3kmXvFl/sWMWh43E9t9z1WcA5EFt74uVKcMTlYpYhsA2wRxJz5HIBB1VidiM3f88myUG1Gfeq10tj9YV8IvhQB9cYC4LbwVJZIp85vnTG4eY2hcVhIw45x/mIa92VkJr6FiUHm7rP2bU8k1op/mauu/B4rUu2qxODHAFvsknJbXKbQ0NdXn84UYVRc5IDZ61sEdLW9LvCptPXoN7JYgBzBW/TJhbnM3xcWfD9jx2LK880bz6Jcdh0745DyxFFqaNtXDmXHIxnbSien0mt9etLTnQZZnQu9L+azEQxR+SkqxbTZdvmzb3xbPXEjdxm3OfPybbhFxJqJTMzwgPQTH2LnPYRlkzGZdkcLPeIR9xmzW6gwi5JJWj6Lgb3Sa7DaqiRZNQccYjSZ1hsDiM1p0NxuHJwImfkyt3Yk/4Fbdq+B1e9clZ8/vRR+E/HWAjAvvlwQm37yMTN1K5WCv43u7Imr5kOfgGADziK8q7nTbsSh2OGxEGJVokpCqizEQeRcXALUmxUHVIl4ELhbARb4CN3iTVJDvtC16fjh/e12hRc+a6E55elTdFt15RocVSjea/gOHN0MrrbtOH3kSUHB1fZSqP2iIPB5iCKsb+5NJ3IqxxkMYC51uN7bRa1UgcmurXCtvm4xCQAgXqDq2GsKcidiEPyb9PBLxxfO/sInHKYOVfTLZ8J1o7q8HgRRG5qJbEdq+QQztv2fEQdvl1yCP7vY0hXAgBfFqTJnpa5R30biAM/LY+fYWCCq2rnfeHhSoD9O+snaARMzOC3z9WfciiisXc9JoyK1053g81QVgN3huRQezaHyFvJvDAG9NSfAgcApx0+EDPe3IiPnaA2UnEkbA6OpNjGoXHJwdZeOQRBeYRpO9HDYjjn697Fh9+VM+abbpaDmFzwrQ/aN4KDQpWAzXNIPIbyvSPVKVBk2CRWvom4RP9y2J6layJB8brtnXOYCNPw/j0w53sT0ag5r1vEEIMLtIiTDumP/j3qsG1vq4P3lZu90NVtF4gJUs9ueWNAIVcDczdZ8UyLaqH2iEP4v21bsC2cK943Ch87YWhKNyhD/PBsnH6fhgJ2NrfhtsvGGevxDcLVhtHz/2/vTIPtKKoA/J23JCHrI5AA2UiAmBBCTCAg0YQlJcYHkSC4sEgCiIAsgksVoLiVUoCllApWIWhSoCiUJWpAkAJKQARZooCEGFZLwLAVEJOggZDjj+nJm7x773Tfl5k3M++dr+rWm9e3b98+98zMmXO6+3TghQpwX2B6hGbwxaq7541pRPJeG5J3CtKfDvNy1eMbnq91oWs84VMH7BrU9tnzJ6e+v94Neg5LGViHrc/LUCPZ0wkb9YiTR6ZtxQswelj69RXT/Qa9ZE7j37Pr4SrcOISGkX3E95U5u++YWi8OA4/t2I7nXtvQcIOnPOl/xiElt1ISn8spIl7DAFu796FjDmkLwYAt6ahDXM1Hv/6h4Kc4yGkltfem78JKnnovrf3fluPQizXtFwqJ9/eE+MboHUNp6TIOoSlLxo+sv9FPTGwchvrSpDfhNYWsNu/ObjumDyBffNQMrv7Ts+wxOmzL3GZY+c0Fqed8LLpPnPYejBd+dFbdhNI1372bZ5wiDittP7id2y/q7PV1StAfxxzcX9/SfN+Wf6E04zmE1tt73Ah2HzUk6GlzxHbtwTceyGdswndix6s9fWGy5GriUJnSDGi8UjVrQvvWIrIl/NWMjtK4oHMqHYPbGdMR9sQdwrtbwn7h54Yv1LL/pJFcvXh2Lje9Qe2tniR9Ye3EDyvzp44Ovi6Oe9+E1Pfj6aw7ex4sY89BRGjzbJaVF/3Qc0gZkU6QVbqJpFJ9A5RDB7Z5V8BCtKnLnV88eFu71mv4Bno3B958ksbBF7aISYv7+8Z2eko82OsLpwld3kuoPD46996FTk9W32aJf8OspmLnjX99SZhnFxMy5hGz15j0dPfxdNYOT3aDeMyhiIHomH5nHGK800Bz8KnSZicAXPeZA7ht5Uup6yaqyBGeQfvQm887iTEC72wlR9q1NWNcBzsMGbAlG25WxGLU299663pdA9K+GUNF0pURtOCOZERsO0JvuyE2cfSwgbzz7uatduOrRxz2S0uYCV1hpSKNQx9RdziBjkOmieouPHzPoDnyk3Yc4l3Z2hcJncqaHCPwzbCJ8SUoS64hyIo4pLLfpPQpryKJJGwFxJTB/wQLXQa2yOnQWbLQPaz4pr82M0PovvPn8+BXPuitFz/g+DIWxGEl8xx6kbT9HJJkGQs9Zd5unDJvt8za62vE16Dv3pMcIwidrbTZc3Fp8PNjODsNH8SNZ7yfaR7DE+eKAr88Fx6+J3eueiW1TrPc8YWDvFO2ocsQ5zWA39uc9+GpnHHw7t51G3GW3JD1L6Hn47vuZPeNyQww49D7hHoOfeUpqQq8GxhWSi4Y82V6jdns8RwOnDzKm+aiJ+zTYOvWJEkJfJ5QHg8YoTOF4lDJf9/OZwC/t2ltEe8UWoi8yucuPizTe0F8s/cZh/grV7+8LrVenvS/sJL7a/f+rVl20n58beG0Qr67a8whvd7GRNI738UVT/edu0f6fPJTDyzOo0vuNrh+o38iQlEMGRiFQN4KSAsyfFBb8IK+KpD1Q+IW4+DxNF5bl+04WE/od55D5/Sdec9OQwvNUlpGDpkymkPCsgAE89szPxBUL3S2UjIBnW+NyYqvHhr03SLC+JHb8fzrYTn582L89unrF4pkwV47c9SssXxpgf8EeewbC3qhR/U58f0TM00wmQebAj0HXzr+3qDfGYdddxjCrp6ker6nTSOMmeMbpzJPEi9Y8sW/kzHvMSmpB5rl5rPm8dqGsJz8eTCgrcW7uK1IBrW3ctknZxbdDS/fOGKvorvgZVB7Kxs3bfYmwjx2v/G8tXGTd91EnpTGOIjIh4EfAK3AT1T1kiL68eS3i1mN2J/5yIwxrP3vO3xidnqKgPM7p3LuDY8A2U4YGDG4vdDpw5/thzPU+iszx3dw95OvesPaba0tnFbweVEKH0xEWoEfAZ3ANOBYESkkAD6grcWMQy/T0iIsnjPRm+b5SE9qgqpy1vw9iu6C0UtcftwsrjhuFuNKHEaMKYvnsD/wtKo+CyAi1wOLgCcK7ZVROm49Z553AVHVyCp1hlF+hg9qZ+GM9EWhZaEsxmEs8Hzi/xeA9xXUF6PE5LForShuPnsuDzz3etHdMIy6lMU41Ivj1ExQF5FTgVMBJkwobqDGMLJg+tgRTB87ouhuGEZdyuLPvgAkRyPHAf/uXklVr1LV2ao6e9SosC0bDcMwjOYpi3F4CJgsIpNEZABwDLC84D4ZhmH0W0oRVlLVTSJyFnAb0VTWpaq6suBuGYZh9FtKYRwAVPUW4Jai+2EYhmGUJ6xkGIZhlAgzDoZhGEYNZhwMwzCMGsw4GIZhGDVI2gbsZUZE1gGr67w1AfhXQBMjgLUZ1sujzVBZ8vjuPNo0ebKrl0ebRcqTh9xZ3wuaqVtmeaao6jBvK6payRfwcIPyVwM/f1WW9fJoM1QWk8fkqbo8Ocmd6b2gr8jT6N7Z/dUXw0pvBta7KeN6ebQZKkse351HmyZPdvXyaLNIefKQO+t7QTN1qyJPQ6ocVnpYVWeHlleRviQLmDxlx+QpN1nJE9pOlT2Hq5osryJ9SRYwecqOyVNuspInqJ3Keg6GYRhGflTZczAMwzByovTGQUSWisgrIvJ4ouy9InK/iPxdRG4SkeGufICILHPlj4rIwYnP7OvKnxaRH4r4dnHNhwzluUtEVovII+41ugBZxovIH0VklYisFJFzXPlIEbldRJ5yf7dPfOYCp4PVIrIgUV64fjKWp3L6EZEdXP31InJFt7Yqpx+PPFXUz6EissLpYYWIzE+0lb1+QqdbFfUCDgT2AR5PlD0EHOSOTwa+5Y7PBJa549HACqDF/f8gMIdoY6Fbgc6Ky3MXMLtg3ewC7OOOhwFPEu0B/h3gfFd+PnCpO54GPAoMBCYBzwCtZdFPxvJUUT9DgLnA6cAV3dqqon7S5KmifmYBY9zxdODFPPVTes9BVe8Buu+lOAW4xx3fDhztjqcBd7rPvUI09Wu2iOwCDFfV+zX6Ja8Fjsy77/XIQp5e6GYQqrpGVf/qjtcBq4i2fF0EXOOqXUPXb70IuF5VN6rqc8DTwP5l0U9W8vRurxvTrDyqukFV7wX+l2ynqvppJE9Z6IE8f1PVeBO0lcAgERmYl35Kbxwa8DhwhDv+OF27yD0KLBKRNhGZBOzr3htLtNtczAuurCw0K0/MMucSf7UINz+JiEwkerJ5ANhJVddAdAEQeT1Qf6/wsZRQP9soT0zV9NOIqurHR5X1czTwN1XdSE76qapxOBk4U0RWELljb7vypUQ/zMPA94H7gE0E7lFdIM3KA3C8qu4NzHOvE3q1xwlEZCjwa+BcVf1PWtU6ZZpSXggZyAPV1E/DJuqUVUE/aVRWPyKyF3ApcFpcVKfaNuunksZBVf+hqh9S1X2BXxLFelHVTar6eVWdqaqLgA7gKaIb7LhEE3X3qC6KHsiDqr7o/q4DfkFB4QwRaSc6sa9T1Rtd8cvO1Y1DEq+48kZ7hZdGPxnJU1X9NKKq+mlIVfUjIuOA3wCLVfUZV5yLfippHOKZBSLSAlwIXOn+HywiQ9zxocAmVX3CuWbrROQA5z4uBn5XTO9raVYeF2ba0ZW3AwuJQlO93W8BfgqsUtXLEm8tB5a44yV0/dbLgWNcnHQSMBl4sCz6yUqeCuunLhXWT6N2KqkfEekAfg9coKp/jivnpp9tHdHO+0X0JL0GeIfIQn4aOIdoZP9J4BK6FvNNJMrUugq4A9g10c5sohPgGeCK+DNVlIdoFsYK4DGigakf4GbJ9LIsc4nc18eAR9zrMGAHooH0p9zfkYnPfMXpYDWJGRVl0E9W8lRcP/8kmjCx3p2f0yqunxp5qqofogfHDYm6jwCj89KPrZA2DMMwaqhkWMkwDMPIFzMOhmEYRg1mHAzDMIwazDgYhmEYNZhxMAzDMGow42AYOSAip4vI4ibqT5REpl7DKJq2ojtgGH0NEWlT1SuL7odhbAtmHAyjDi4R2h+IEqHNIlqguBjYE7gMGAq8BpyoqmtE5C6i3FcfAJaLyDBgvap+V0RmEq16H0y0SOlkVX1DRPYlyp/1FnBv70lnGH4srGQYjZkCXKWqM4D/EO2vcTnwMY3yYC0FLkrU71DVg1T1e93auRY4z7Xzd+DrrnwZ8DlVnZOnEIbRE8xzMIzGPK9dOWx+DnyZaJOV212G51aiVCgxN3RvQERGEBmNu13RNcCv6pT/DOjMXgTD6BlmHAyjMd1zy6wDVqY86W9oom2p075hlAYLKxlGYyaISGwIjgX+AoyKy0Sk3eXWb4iqrgXeEJF5rugE4G5VfRNYKyJzXfnx2XffMHqOeQ6G0ZhVwBIR+TFRhszLgduAH7qwUBvRJkwrPe0sAa4UkcHAs8BJrvwkYKmIvOXaNYzSYFlZDaMObrbSzao6veCuGEYhWFjJMAzDqME8B8MwDKMG8xwMwzCMGsw4GIZhGDWYcTAMwzBqMONgGIZh1GDGwTAMw6jBjINhGIZRw/8BV7VFjY2akIUAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Un zoom sur les dernières années montre mieux la situation." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-200:].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Etude de l'incidence annuelle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A partir du zoom, nous définissons la période de référence entre deux minima de l'incidence, du 1er septembre de l'année $N$ au 1er septembre de l'année $N+1$.\n", "\n", "Notre tâche est un peu compliquée par le fait que l'année ne comporte\n", "pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n", "de référence: à la place du 1er août de chaque année, nous utilisons le\n", "premier jour de la semaine qui contient le 1er août.\n", "\n", "Comme l'incidence de syndrome grippal est très faible en été, cette\n", "modification ne risque pas de fausser nos conclusions.\n", "\n", "Encore un petit détail: les données commencent en semaine 49 de 1990, ce qui\n", "rend la première année incomplète. Nous commençons donc l'analyse en 1991." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", " for y in range(1991,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n", "\n", "Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_august_week[:-1],\n", " first_august_week[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " assert abs(len(one_year)-52) < 2\n", " yearly_incidence.append(one_year.sum())\n", " year.append(week2.year)\n", "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Voici les incidences annuelles." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style='*')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2002 516689\n", "2018 542312\n", "2017 551041\n", "1996 564901\n", "2019 584066\n", "2015 604382\n", "2000 617597\n", "2001 619041\n", "2012 624573\n", "2005 628464\n", "2006 632833\n", "2011 642368\n", "1993 643387\n", "1995 652478\n", "1994 661409\n", "1998 677775\n", "1997 683434\n", "2014 685769\n", "2013 698332\n", "2007 717352\n", "2008 749478\n", "1999 756456\n", "2003 758363\n", "2004 777388\n", "2016 782114\n", "2010 829911\n", "1992 832939\n", "2009 842373\n", "dtype: int64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Enfin, un histogramme" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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PupR7jk6NOTjug8jumLuu9/RtmfU+pYyIh1K9xfgysDUzbwd+H7gmMy+OiGuBd0TE44FtwFMi4pDMvDEivg/cGhH3Bt4HPCciDqX6Tv3/oXrbQmZeBlzWS8495N8AvJDqbdE7gBuA3xv23HX2To55nd1xd11fSuZO90v9HIZy3Je9hR8Rd6t/GOPA2VSHCD0OeGt9l98C34uIfTPzWqq3HQ+sn/j1VMeQAvyG6q3JXsCnqb4e9BTgOGBLZv52udkWyT0SEXeNiHPr5V0LvDczb4iIvaheSYcud5394Pr/RwLn0JExrzMfFNVxxFuA8+jWuB8aEQfXv7zn0pFxj4hDIuIhEfF+4Hy6Neb71P3yGKpdFZ0Y8zr73hGxb0Scw7B2zBL3Pe0H/Cnwb1QH/AP8OfCSevog4NvAsXXozcC6+raT6sCH1NPbgTVUHzJ8Fthn1nL2arKPbA+5LwY+WV/3NuBFs+6zuv7/pcCbhiT37jOgn061D28KGANe3oExn539q8AXqFbqoR/3ep77A8+jept9E7CxI+O+O/cXqLYCn9qhMd8beDHwGeBvgCOB04Z9zOdkv5Bqa/zoOt9QjvuiW/gRsTdwFfA04B2Z+cf1Tcfuvk9m/hz4Z+BlVL8ohwL3r2++BHgMcEdmXgh8GPgU8AGqraZfz5pPa6+6c3K/PTN3v3puBx4QEW+tX4n/LCLuDnwOuMegc9fzy4hYAzwDeE9mjmfmNNUr/O77DN2Yz5P93Zn5uMz8Nh0Y94g4kmr3wWOB1wA7gR9RfZC2ql7m0I37nNxnUO3T/WGdZ/0wj3ntJVQl9x6qv4n91Pryb+plDt2Yz5P93VTryFOo1pmxiNg8dOO+xFex84BT5lz3TODSWZfvBVxfT7+E6pTfg4B9qV657z3rvoe0/Uq7jNz3rrN9EjiZaiX73DDlrpf1YuCN9fTureanDvuYz81eX94XuGedb3JYx53qF/Yusy6fTbXB8ORhHvd5cn+Iamv/0I6s658B/qSefgFwat0v3xjWMV8g+/OBV9Ud88lhHPelPqmTqA72P4tq98LrgPtQnfF16Kz7XQQ8vJ5+E/CvVG8v/3KlfgB7yP1F4PVUH3ysnXWfvevndEJ9+c2Dzl3neEad6xTgW1Sv+E+m2s1wyKz7DdWYz5N9G/ARqiMUZq/YQznus/IdTLUP+XFU+1J/RnVM9NCO+5zcj68vd2FdfzHV7uJ/ojpK5UNUu0Z+DowO85jPyf4jqo2E+wNHDOO4L+eJfZ7qhIAjqF65TgO+RlX+Ady9/kHde9aTPAa466B+GPPk/ijV6clHzbr9HlQfhD5wyHIfVY/vX1NtDTwbeBfVcbivrEtoWMd8bvanU23Znzjs4z7neVwOPLWe/gjwtnp6KMd9Tu4n1dN7zbp+aMec6oiWs6n2Z78eOBOYrn93h3Zdnyf7GcDfAY8YxnFfzlE6T8nMt2Tmj4G3UB0e9T6qtyUXUL3KrcrMHwFk5q8z88rM/NUyltEPs3O/lWrwD4yIB0XEGVS7fX6Z1X7mYcr9I6pTpVdntQ/zwvq6C6k+jB7mMZ+bfSvwHeDYiPiDIR936iMqoPrA/Mh6+s3VTfEZhnTcF8i9V33EzqsZ4jEHHgBMZeaNVO9QVgEfZ/j7BX43+7nAbcD9IuLoYVvXl3wcfv7uQf2/oCr812bmxyLiOcBVmXl52wGbmpP7FqoTFa6meiXem+pIgGHMfXtEbKZ66wrVVs7xwObMvHzIx3xu9n2o3ua+keqoqX0Y0nGH6gOyiNj9bYQ/qK+7GnhlRJwCfGcYs8/JvaO+bldEPItq/RnKMY+IVcB1VF8x8A/ArVRnmb44M68d5nV9nuy/onqH+3aq3T13YYjGfcl/ACUi7gI8gersrqOpDp/6YGbu6l+85ubJvSUz3z3YVEsXEW+mOmHjWKr9fmfWW81Db072LwCvzP6ehdmqiJgGXpeZn9x9MtCgMy3F7NyDzrJUEXE/qkMU76BaZ84H3pTV2aVDbZ7sFwBnZOaKfxHbYpb1F68i4kVUJz7845C8lVqSrubeLSLGgB+afWXMOtPzwVSH9u7qQtl3Nfdu9ZmlRwH/npm3DTrPcnQl+9D+iUNJUrsG/hevJEkrw8KXpEJY+JJUCAtfkgph4UtSISx8SSqEhS9JhfhfHCg3qEW8+c0AAAAASUVORK5CYII=\n", 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