{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Incidence of chickenpox" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Downloading the data from the [Réseau Sentinelles](http://www.sentiweb.fr/)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The first line of the CSV file is a comment, which we ignore with skip=1." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020201474624260266467410FRFrance
1202013773715268947411814FRFrance
22020127812357901045612816FRFrance
3202011710198756812828151119FRFrance
420201079011669111331141018FRFrance
52020097136311054416718211626FRFrance
6202008710424770813140161220FRFrance
720200778959657411344141018FRFrance
820200679264692511603141018FRFrance
920200578505631410696131016FRFrance
102020047799158311015112915FRFrance
1120200375968410078369612FRFrance
12202002765344530853810713FRFrance
1320200179835701912651151119FRFrance
142019527794152461063612816FRFrance
1520195175823367579719612FRFrance
16201950764244276857210713FRFrance
17201949766214540870210713FRFrance
1820194875542338377018511FRFrance
192019477753650581001411715FRFrance
202019467263813163960426FRFrance
2120194574492261563697410FRFrance
2220194475728362778299612FRFrance
2320194374834275169177410FRFrance
24201942762793989856910713FRFrance
252019417413020306230639FRFrance
262019407421122186204639FRFrance
272019397313713104964528FRFrance
282019387307814164740528FRFrance
2920193779701621778102FRFrance
.................................
15011991267176081130423912312042FRFrance
15021991257161691070021638281838FRFrance
15031991247161711007122271281739FRFrance
1504199123711947767116223211329FRFrance
1505199122715452995320951271737FRFrance
1506199121714903897520831261636FRFrance
15071991207190531274225364342345FRFrance
15081991197167391124622232291939FRFrance
15091991187213851388228888382551FRFrance
1510199117713462887718047241632FRFrance
15111991167148571006819646261834FRFrance
1512199115713975978118169251832FRFrance
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15281990517190801380724353342543FRFrance
1529199050711079666015498201228FRFrance
15301990497114302610205FRFrance
\n", "

1531 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202014 7 4624 2602 6646 7 4 \n", "1 202013 7 7371 5268 9474 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 10 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": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "No missing data." ] }, { "cell_type": "code", "execution_count": 7, "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": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Converting the date into a format readable by the pandas library and sort is ascendingly." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "data = raw_data.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']]\n", "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Checking if all data are still present. Apparently, no gaps of more than 1 week." ] }, { "cell_type": "code", "execution_count": 12, "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": [ "Having a visual inspection :" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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BRD0B3A/gG4yxnQhURKMAjAOwDsD1vKricmYoN10jj+FyIppLRHM3bdrkOvQOgd8JLsCcFVvx9OKN9ooSqn0vrmv8p299EddPC1Q1LW1F5cY4Byr4I39q0UbMWua+uU81hfiWUMLrjNxlcZxD8KC6ukqxo+H0BoioDgFh+DNj7AEAYIxtYIwVGWMlALcBmBhWXwNguHD5MABrw/JhivLENURUANAHQEquZIzdyhibwBib0NTU5HaHHYTOsDl0xbn6qd/Pwr/970uZr6vkrbgsXTpiZCJSyzbtwd6WNqFu1pElOmrHxXpkmRMiJ6zLxaRCNWPguFfZ+p3N+Mer71SvYwFFTxwAuHkrEYDbASxijN0glA8Wqn0CwBvh8UMApoQeSCMRGJ7nMMbWAdhFRCeFbV4C4EHhmkvD4wsAzGBdjE1OjaZT0md0HtZu34eLbn0R89bY3Su7Isp9dtc/+Vb2vqr4oqqh+qhmhDT3Dnt7y158457XqtJnS1sJZ1z3NJ59K9BGcPNUrauVCg51TgXwOQDziYi/rf8CcBERjUPw3a0E8EUAYIwtIKJ7ASxE4Ol0JWOMRxJdAeAOAN0APBb+AQHx+RMRLUUgMUxp321lR1uxhGkLN2Dy2IOVYnTKIF2tgYl9duJknb1iC2Yt34I/v7gKx17Qt93tVftWyu0vGSFtrmvUvnSQaibLfZX7yKsZ59DSVv05vmFnM1YIKc+LIYGqdcnBShwYY89DLbk/arhmKoCpivK5AMYqypsBXGgbS0fijhdW4iePLMKvpozDeePSzlgpg3SNcRXc2LqvNUPEsAEdoZYzvxONWsnaaLmj6Xood87mqqj+b8voIrSzuRXb9rTg0AE9yu4z7cKa/F+r8BHSIXaGHOLyTepNU7qAVqlTXVmzMI8L1+7EG+/sMNY5UCSHd88AAhtKOaimt5LscmwjaOff/AJO+5+n29WnrCngEdJereQBAOjdrQ6APpioGukz2oolFAxeGl0ht5LLCHgyvZXXfqRjB5MBunHb3iNLHJsrq5bQSqyrnR3xU021kiw4lBhg2ldrycbd7e5Tbp57qNW6WslLDiEawkycolj71MINGHHVI1i2KT0BO2LatGgCtThGDixfdG4vOHdVKXVaJYlrltQR7UFnMZKdHQ2a68SU3dXg3uUeuLdSjQsOnjhwcCZB5JIemR/sCfz66u2K3EqVnzm2KNc+oXRz3LA+Fe/bFZW46217WvDHf62oQEsBXF5FuVKXSHg6a63o7GQB1aQNnZHCQt7rg//uCpJ6Z8IThxB8EqpEaMY6JkJ65eY9iV2+9luIA5/D1Z6yb7yzI96FrQKdf/f+efifJxa3v6EM0K0x5aiK7H1VNn1Gp0sODsSpVGK456VVTmk8TJC7cqUN7dnSVCZAXJ1U65KDtzmEUM0tPk/3t5Wwcae08UcFJs7p4WYqHLYPq9RJ4u7fhWAk02K6cVczejXUWdvbvrf6WTnLfWY2VZ8I1RqqSqlxoMElzuGf89biP++fj7Xbm/HNs4+oWN+u762txFBfpogj2xb4d+YN0h4AYm5P9YH/19/np+t3AP9ulRy6uLg7cep0vGdo56m8TCj3mYlJ4spZKyrxrkyM+/knDMP9r6zBheOH6Su1Ey6SA3fkaG86bpmYmhZosS+T8fiuWSsxe/lW/PYzJyjPy33s3BdExXfNr6x68GolCa6eGe1lKq5+YF6qzC45hP+rnC1SvFfbfc+3uLCq22/fw3S5+tHQfpTuu11dV6VNk/RRHzpS9GzsOD4vC0NeLjFcu30fgGw2hxN+PC06Nu3Xcc2DCyL7oQoyXZmzMsjcU+OCgycOHLHNwa1+eyfOX+esTpXZVBiRWql9XbcLlfhg5MVuwdqd7W8U+udy16yV+O3MZZnaGn9oP3slCeqsrJXwZVUXM8bw1zmrwuP2d6NDR6fP+Mer7+CUa2dg9vJ0MkD5tkZc9Qi+/+AbqXrFDNvApq6tcZdVHTxxCKHyVjKhI1Q7Nsmh3G0e24uOVmNl0eurYHsc1zy4IHOb6sCvzllEdDOyUtHqNphibzZItrhyiOHLbwdOGW+u35U6xxRT485Zb6fKXHb6G/29R7FkQ7oPTxzU8MQhRCS+VkFy0E1GmwGsswxkCbVSJRbIA8BGq0oZ0WlxDprnJU6jjmQY6jXE4dVV23DiT6fjb3PTUrAKunlv4sdc57zLAt9aZEqJvdYNzzp44hAipg3CTDVM2vZMJ52E4EocOnMud8XvqCMkG5UqxbUXVb2OeG6iKqUjX0tBE6K8ZEMQHDpnRZxd3/Qu7pq1MnPfrvfV5qhWKiokDC85qOGJQwiW0eYwbeGGsvvSEgHLHOXal870VuqIntu7cLbnet215aSMULqyVsTkoG5EjOYvlhi2tdNTSIdChTLvbdq131pHfh+uXL1zPISiXlbasH1vC6597E20tVMd2tXhiUMIPrmqkUdGNxdtk5R1AcmhVlDNPQxs0E1J0ZXzz7NX4fgfT9PmBmsP6kzJjQD87eU12LM/sH+0xwDPGEsRA1fi4Kx+UtTLqlaa+sgi/O6ZZXh8wfpM19mwtAJ5oiqJmicOb23YhcP/61Gs2roXQFJy6KgAJt1kdFUrVVtHKuqzO6Zr90aV0ccdMKaCSq1UBhdbGe8uNc6+8dlU2c4OIA4mgzTHDdOCiHdRqp27cmvCAKx7FOL9pVPju43R9TGrIqmzqpV4PFIl1VHTFm7AWTc8g3++vtZeuUqoeeJw95zVaCsxPP5GwAVUI49NmVqlTkufkYR777qUBu15wpUmBDoVXTUzkXYW2pNyAkDiRbYqdP4X/G5WgoC5ZMCVq7iri8o3XJf7HB6bv75ii/lbIRFdtK4ybt2VQM0TB74G8MlVlTVBMxedvZWqSB1Wb92bcB3UEjbFiVueyRZb4AKlsbcDHogyx5bjteKlWeeT7BoatJFu5MHX1PsrZ+mvI6aRSdrWvSfx/uR5VGmbg1qt5HYtBx/u4wvW46s859i7EJ44hP/5BKlGLhzdhLepLVxpQ6nE8NuZSzHiqkfwo38uNNZdv6PZaMj8zB9mJ37PUgQqAeoPbLbgxWJCFmnAuFhUcLXLW/TsJrRHuvnvf6QDvOSRtBZL+Prd7d9f2V1NVnkyojPmyj25EwdH24RKreSNeEp44hB+ecUqSg66qWibo3G2SHPFmYs3RllPbamxT/rZdBwvpCGQISfJ29sSB16JInoWO0h7nrGqm47wVipn9zPTFS6L18tvb1MTaqnhJwyG0CxqUVeO2cVWENd1I94/ejjNtDCFXqnSNgduWxSRVa3UkUtEVyJTVuJARMOJaCYRLSKiBUT09bC8PxFNI6Il4f9+wjVXE9FSIlpMROcI5eOJaH547iYKZzIRNRDRPWH5bCIaUflb1d4fgPI8gcrlqHTX2eaoa/oMlf63kuDpu3//bKw2UhEH148oy2ir5carjHOwdK3K35NlITn/lhcw9+1tqXK5jd6N+sy3WfqrumODcDxz8UYAQcI+MeGk/H4rbXN4ZdV27NnflijzcQ5quEgObQC+zRg7CsBJAK4koqMBXAVgOmNsNIDp4W+E56YAOAbAZAA3E1E+bOsWAJcDGB3+TQ7LLwOwjTF2OIAbAfy8AveWCRFXLkxOGxNW7pzSXWeb4Py0rV4l3TBVnOhDoRFuhbAnsSp7ge75uaruKuWZdNJh/TNfkzV5xtY9LWXv0Wwdi/QgebI9FTIRWtfKGRp1fbfcpnPcD5+M80MpxqSb6/KCnmVeyMQhK5HsSKeVrqThshIHxtg6xtgr4fEuAIsADAVwHoA7w2p3Avh4eHwegLsZY/sZYysALAUwkYgGA+jNGJvFgq/+Luka3tZ9ACZRR74BAbLNoWL6bwN03K+tOdcIaZUbZkdAHEaWZ+HK/VdKhTRmUC/DWNzhqn5Q3d/Lq7Zn6MmMlxXSRdR3R7wHB0OyS5vi2HQz1GRzEK+fvigZhJplXsip8btC+oyu6ByXyeYQqnuOBzAbwCDG2DogICAADgqrDQUgJjBZE5YNDY/l8sQ1jLE2ADsADFD0fzkRzSWiuZs2bcoydMNNJX9mWizKVivpyt28lWzddsaev+1RK+ng6pnUId+2YvCthohY27trj8ujvHCYdtHLxtyUOaAyIY5N5yqclhzU5/704ttSPTcJA0gneswa6NyxNofOJ1QczsSBiHoCuB/ANxhjJmdcnURuktSdpHjG2K2MsQmMsQlNTU22ITtBFoNduJu4bnl96q6zfayuk7gcY6oOpqbE+1DupKe5OP3M1e2rPnhVP7YPynRWt6ir1CNG4mAcQfvQUXaESruJ2vsTfujSkKcjHRRHwHNLNjv1qSQOkuTQFbyVuuKOgU7EgYjqEBCGPzPGHgiLN4SqIoT/N4blawAMFy4fBmBtWD5MUZ64hogKAPoAcPODbCfK3bMWMH9cjDGMuOoRXP9kmsvTqpVsi1wkOZjrVSgVjhXJyOl2GKQzRIxXK125iq61Gah3Uv1R6bFU3gMJsI/zsKYeOGJQT+151ahMi5z4jNR7tTOL5OD2/G3lMnHIPKe63jreIXDxViIAtwNYxBi7QTj1EIBLw+NLATwolE8JPZBGIjA8zwlVT7uI6KSwzUuka3hbFwCYwTpwFfj072fhV08tUZ7LItaZPkQuuv5m5lLn6yrlrVSJJ5f18as4NK1Buh1p0ZWSg2WolZpJg3o3GjqpTB/tRSbbj0vIMjJ68BkehDg23RSYtyZpm0kQXVO/GcaYVivFF5982AAM7dvNvbEKY9ueFqxWuNt2Blx4zFMBfA7AmUT0Wvj3YQDXAjibiJYAODv8DcbYAgD3AlgI4HEAVzLGuHP8FQD+gMBIvQzAY2H57QAGENFSAN9C6PnUEWCMYfaKrbjxqbc0593bMn2InDtR6svKDIJri+IczOMycbgca7fvw8w3NyrP7dnfhpFXP4qbn04TNhFiL397eY2iRvtYLOV9Gm5t+Wa1t5DRSKopV428W11eUWodVoSZizdixFWPZE6wluUpZiHq1kSPCCSBSunBbZIDANw7NzmPxNsx3Vp7JAeRONQZPME4OkIFxB/HvXPX4P2/mFnx9suBdeNZxtjz0M/PSZprpgKYqiifC2CsorwZwIW2sVQCuyU3NvnGbJ/B5R84DLc+uzyoq1FBtxZLmLcm2EtZLT6rr3MNgrOm2XAgDqdcO0N7bn2YwuFvc1ULfgxxIXpREzntAt1olWollUHa1r5Q4YrTR+GWp+1pPYiCJIwJtYahvu6diCqhO/61EkCQkO7wg/TqGtVYXJFFreQiZVTSi0bszrXdpOSQncirblFmnsQ+6jopG29X1FTVXIS07I+fZUNzADhmSG9l3WKJRYv31EcWRWknVB9BFgOsiEhyMNZykxxM2N0cENAeDXnjpBW7WbYpzQ27qpW0xNLSpwojrnoEl981V9vOmUcehHOPG2JuBAF3KO9jYOLKmQMReeatwMPOZNjWjcYVWdRKG3fa91cA9O8nK+FI2KNdt+N1lByy2K1k5kn8WciT9Rm63veW3ftx4k+fwsIy9kj/w3PLM19TadQccZC5j5SIaPm2ckT40XnHAEhOvGN/8AROvy4QB19dFfuhZ/EFt3sruamV2hvxyYOEejaYBUvx/ldv3Zc6r9teUkZ7DdJy2ZOGjZgIyY/btPDJwYRy1dZiCSf9dDoef2NdpkW5JWMEe6Zkehma/vBNzxnP8/uvlDllx944nbha3Zoua69HlapY/j7E34V8rmI2qmeXbMKGnftx67PZE1D+n+Sq2xmoPeIgvfgUF2s4BwTEgS/4ogvcnpZitECyRP10G7q122pziDhOi1qpnbO7uS0wETUadOyAfSGyXR+1oymfsWgj/jZ3dSJJm+ud6fagyLLQysGE8vvZsrsF63c24/sPLci0oGTdQayzUmIUcpTJU8qGNdtjBsLVo87d5qC5XvGoZddVWa1ke4b7WovG8xxcpbxUIVXb0MPCmFUDtUccbOctEyOfixd8F/WQynilN0ibx+ZqkP7F42+aKzgi4LKzp2DmaKxzm15vrhc2hBFu7hv3vIbv3DcPd7ywMipT2yHSSC4WCZLvtNgSpYMJXdfdm6arPeE42koMN065Ley9AAAgAElEQVR7Cz97dJHQtlvjNntSJX386kLJr1Jqpf2WRVU1n8T3bXMdV0F1jUlyqMvnrBK87E2k3bckfEBvvLMTa7aZPZDkZ9mj3hOHqkOeRCmDtINaiXMELlya62KmqtvcWsSp187Ac0sCXXXRweaws7kVK7dUxhXOdneqfEoi6hzVSj9WZOgUsU3MDOu4+JkkhwTB07ZHCslB6gP2hUvnLfOr6Uvw+2djvbJpKonDdd7zowLI5zghLY+Z4fjQr57DXbNWSkyA27XuDgHqche1Uvpai81Bbk9zM2IwarOjtBH10QUs1LVHHOQC6S2IE0XFYwbEIV030YdFFNZKDtLv5Zv24J3t+zD1kYDDjCUH/eQ9/+YXtOcqjXJdHP+1VO/ZpLo10eNL1aPyGWvOE9zUNGqbQ9zQ8k27cd0Tb4VtknaxU9l/2hRU1fQkxXloJdgVlRzIuEi59rVo3U5c8+CCRJnqef300bTEawu0jM5p7XhmaQRIcv5tpXQgngxZmtYRZHH6ZN1ZsCvke6o94iDbHOTziXD99AvK5wTJQfN12NIE6N67Lf8O11WbPsolFdik3NWP26Y6L2eCq64QPyx1m/YFgEP+sKe/qTZeE4Dzxw9LlInP/czrn8H9r8SuvnppMF3WpjBImxY+lQG9LtyM6GuTRkv9qRfT75wzJnNCRu6tVa53nQnOhmbNcaqeA6PGkVIrSc/MNjb5MeokaHGu2TwI5W+uK2QRrz3iIOeLl88LBaoXGvi/U6puFuhe/AvLkhy1zGy4SA6VQCJtualeB6g4lGk4HLyL0u0Ix/L9CO3d/ZKYIzKJL31gVOI3X1TkDZCIgqBCFVQMhByhG4xRD/Ed8HvhYzEZzeVn9fvPjXceIxC4dRKZYgjKn4eqZ6CCODazK6uu3G5zEDewKjF7yg5ZotSplcRqKobABC85dAakZ140KM5VLzSfo8jTIs6SKhEcZl5cs6pjeHMuNgcd/vj8imgTc9ePmix92Vqp1Py2SQ5q1Z36mCjJpemIHxFA0tfBibOc8pmx5HaqYopw1cKhinMwPatd+9siqZHX4wuYvFCZOM5JRw3CGWPSCSs37krHO/RsKODa84/VSpFLN+7GEwv0LsM27Gtx08En7sdwb9qtdxVlMnHYuS92sS0xZiSwgLtaSXw3NvfyjbuSe4d7yaETID9zWToQJ4ZKN5wXDNLFiDjo+8sSBGe7NtrhrYyJ86OHF+KjNz2PZZt249v3vp69AQXsxlG3dv7tlBHRseqSrcLWmc6SgyabZyojrOZ6UiyLfIG2fegDetZHx6pnpFQrGV7qruY2fPtvwTuTm0vZRRISUww+l1QbQamI1c/PPzbKMaRiJs664RnM0KRfccFeR+LwwrI4+2o5EdJKbyWmJw6MJZ+hS8ZWneSVS6iV9Ezoj/65ELc9t8KpzWqi5oiDyRgFJCeZ6iMmiiNn+XlxAn33vtcTH5uK88oqMu5rLWL3/rZIysk6bfjH3VIs4eoH5uOBV9/JfK36nPVqpz5E1YjNIO3ai1FycFC9i+pDIFhUo/ctzRk5JYvNIUGpVrI8qgdfC+xR8gIpq5V0NgeOrHELJrVSe+DqvfPrGXF+L9Mz0koOimL5m+dxPUDwfMWzSkYgpX2wPyGVirpUYtjZ3Krc592rlToB8jOXv9O7Zr0tnFOrlbj/Pp/gYr17565JbBfZLskhJCyrtu7F2O8/UbbNQazep5t+/2FVfd2837iz2ei7XZcnq6urqg+1E4BY1+3eTfWcvJWQfHenjBqA1vCG5MU9RRyEe3DZT0CF75wzRllukxy0hvjwrlU2aaPkqz8V4ebPnOBQK8BBvRoAABdNPMT5Gg7VMG/hfWvuwSXOQazSWkwapF3ye+m+EbGfFYotZH87cymO/cGTmnGr26wmao84CMdnXPe0kmpzqKh9joCGQhD5y3XPWT+ucpmCOPFetuvECd5LE3m5fkes8xTb14m3E3863bhnciGXc7atzH073rpDKTlYJAurK6ucMsWReRalvkKOoudvy41kU0s0t9olhytOG5WqA2Sz86jUSspEkJZWbfN10lEHmSsI6NlQQCFH6F7vFj2fHEd6IENC1VcWyUFWCDAWP5+mXg2pnGm2Nl1iXL57/7xUjqXpBrWcVyt1AsQJtkKT4pnj2GF9UmU5leRgdEN0/xgP6d9dujZ5nqs1Mhu0Heqc9LPpcf3wfoio7F2yggRmbnXnrdkRPUvVhyYGE7mORkyb8MArsRrNNSkhUdLHP5/LRTYfG+cv9nCkYv9qlUrFRsDi2JqgXkOYWnrnvqTUYtt0KEuWYD4Q2xOrU+TC0Em3RcbKVlWprrF5DrqolRgYxgzqhb/8+4m4+kNH4rCBPYW6iuulRv+uUdPK9eRcVn2766X4rrBdaA0SB/e6clZOIFioeM4glVpJRhbJIeVmK9XjRq3m1pLzhiB5KVeMy+3zOoyxspP4BWkI3K/lUdCq7m4WUmw7J+PT3GlrseQcxyGuo3V5igzS1qyqQtf5fLovJXGQhiszFVESvLDeuOF9AQBD+iY3INK9Lt5a1shbW/WcIs2IaRyMmYMGTVB7DvH+7Nw7h8ggrNuxD08s2IBVW/filFED0auxDnddNhGnHRF4damYI7nkl5q9YWzTpF/3eu25rrBtaM0RBxdE23EqFpgcCZJDpFbKpldyFYFNus3XpR2zACg3kcnnkh+ii70iaXMojzjkc9nYw6KjPcXZW0lTr7Wt5GyQTqiV8rlojFl81lXjULqyWtqJOP6w4gePORgPXnkqLkgF6omMgHr+Zu3b9E50KVJs30Q5nLHqGumxKK5JQ3xGJ/8s2NdE9J4a2LMBZ4WqMhe1UqtmPtikbpPk0BVQc8TBZXHhddT6b6QipLNy1661TQZd1a5kZ93wTKrs2KF9yljgzTpXF7hktxTB79XenZ2TA4AnFqxXXt1aYm7EAUm1UiFHkUHaupjadPiKMntULs9yFKr8ABw3vC+ICH/70slx20I7TwpxCLHNQTEeo1rUOCwtcdDnOmIBya2U5MCzP2WQHFxApG9XLqlTSIeAOYYKcHMO6UzUHnFwmJVM+i9CTLwXRatm9Ixx1Y/eMG2xtl3TlpUiejQUnJOXcfD6MxdvKttrIp+366pF/HJ6IJrbo67TZapLVHt3A4HkkLxY3xd/d4c19UA+Ryhym4/lxmznXQP5RMhqJXGRF/c85uc3796Pr/711ag89lZKz0hTyhUbHS1oFkaTdFy2zcGoVrJfM6xfaLx2mNT8eSu/balMRyC/eY85nihrOpNqw0ociOiPRLSRiN4Qyn5ARO9Ie0rzc1cT0VIiWkxE5wjl44lofnjuJgpJMxE1ENE9YflsIhpR2VtMwvQR8skTqZVYmsusL+TiCVmyt6k0SDtyM08t0nszNDimw5YjPrm/vAmVcLEu5Oypj0Vwo7F1X+N2qpUO7tMIccnTMQtEgSrptksm4O7LT4KoJbOqvhLjSNY9fUwTlqu8vCz3JRukxXmVjCAP/uskPnk+rty8B1/808vGvk2367qhU2IMoLJSb6jeFV9gU1HPza14Z/u+qJ/rLzwOT33rNABu3n7cCUKpVpJ+H3Vw71Qd0fuvHBwoWVnvADBZUX4jY2xc+PcoABDR0QCmADgmvOZmIuIs7i0ALgcwOvzjbV4GYBtj7HAANwL4eZn34gTTvIjUSQBeWLoZv56xNPVhjBzQQ5AcAmxSpB/g2LGvNfUhLN6wS1nX5YMZ1LvBWkdGVu7fJF2dfNgAjD+0n7UNIncimOjbKjmoPla3fqZ/+zSMHdon8eHpDH+89OyjB+GgXo3IUawmy3JX8nDr8zlldLDtHuRd2RL3IBzzMcrxDzq10oad5kWMiIxj021KY5UcKqRWKoTESY5A/tAvn8Op186IRt6tPh95eLmomriRXaUZki+fs3JrKubn63e/ChVc1bSVYNDaCytxYIw9C2CrrV6I8wDczRjbzxhbAWApgIlENBhAb8bYLBZ8/XcB+LhwzZ3h8X0AJpGK3a4QXPSrjAH3CRk3RYieGXySnfub5419ymL7K2+njcmA26Jz1OCAS3HdTEyWHFxgqh4YuO3tkaUdHSonOaQrjmoKXBTFyWWSHJK/Y9dcu1oprrBaWjR00d6qNu/9YmxLkF02xVaSiQmZsZ8suZjkflTQxSuY2iXo5zr3wlJBdQ3X98tG4XfCRIiRpAWzHUEGF4hUaiUVcfnJw4sSvzfvVjOM8wRHkq5AAExoj83hK0Q0L1Q7cVZyKAAxzeWasGxoeCyXJ65hjLUB2AFgQDvGZYTL+wiMZvFnsehHScEpIhBhY7YPTJ5MbaUSRgzojt99Npkl02WycDHaOVK4BCzLuE2hqWVXfbHIaWfq26qyUemAnYoyQeZPcoIkZOPyxflw79wkk6HbHlPV4sSR/SOXylwkOXDqYFYr6Z6jTDOyeq/JkHcsY5b+gzHoXVk/cEQTThml/vxVbXJ9v869mHP+/H3myE2SzpnUSorrZQlqZ3NbuhKS362RgB4gaiUVbgEwCsA4AOsAXB+WK+2vhnLTNSkQ0eVENJeI5m7atCnbiHnDDhODi74c3STuiJ9yXfzS+W+CyScH2bmoR2x7ScgoMYav/fU1p7rROCwftuvHpbbluS+s6rHZ+7ahnA8vl0Fy4NjV3Joq0wnFtsVc3ppWnFJiizrV1z/nrVP2b3O3tD0rne1LbyBmoeSgrpAjfZ+qoXLioHMvjry7oudoVpNx5DVM2P62Ihau25mq36sxSRxU714eZ1fIn2RCWcSBMbaBMVZkjJUA3AZgYnhqDYDhQtVhANaG5cMU5YlriKgAoA80aizG2K2MsQmMsQlNTenUw46j154hzQcnQ7Y52CETB5ZK7AY4Sg55PmndemYIJnQWWFzUnQZKpJ781sW/jFQOqivM92CnDnKNHOkXXt14VLYFrVpJ0xZ/XvLGO+I9qCWHZDsrQunx6MFJ46mLDtz0LDnjw4cQq2bNk0h3mkDaZ6TsP1IrqSWH3z8TbMWaiyQHN+ZGZ5C+cZp6f3CZgVSlSJHba19Sy45HWcQhtCFwfAIA92R6CMCU0ANpJALD8xzG2DoAu4jopNCecAmAB4VrLg2PLwAwg3XgbjYuiwZjep0hYI/KlJFO9MWQo/QWjK7qmix9M8acc+fH49C37RrbRpq0C6bUxUD7iUfWelqobA6uiQ8jb7f0KZ33ot69OTiRl9RK4txJbKPK1GPkAZufOfEQfO/DR1n75SCkOe2756xK9Z2F0TEzXibpKl3GvaV+8sii9EkAD4W7K+YE4uXy7ZCGOOgM+HlHgpbYdc5QrytIFWpXAwFE9FcApwMYSERrAHwfwOlENA7B/a0E8EUAYIwtIKJ7ASwE0AbgSsYYX5muQOD51A3AY+EfANwO4E9EtBSBxDClEjemg8sjv/+VNZi5OKm2evwb749EQtm3ultdHvsMKYjlBbFY0hCHDDYH15xHJQbj2BJ1Swy5nDm1ATnaEgKDtEJysBjSV1ryXbnGOZjvwTwGIC1diGoy293zMaqek15yCOp+46zROH1MnMgudl0N60WSQ2KwcTuaMfJ8UESEsUNjdabtXcqeRYwxXPXA/MR5IFh8i0L/ps13TP4mqlQc8bXpNl1jBUTJxuXTkeNK5HYA4LnvnoH3/2ImAD3RlyGm7jA9+84nDQ7EgTF2kaL4dkP9qQCmKsrnAhirKG8GcKFtHJWCy6Lx4vJ4u07OmRwp+DLnpC/1iIN74fXVag8kIK0PLbHgI8i66TggGCadiQNzVkEVGUMOZrE75/hx5XLqejaidvldc43nXe+b11LuaeBwvSrxXcmROpjUT9pXHlYe2LMh4bHDOVdKVkvMHXFhincnTDZ/xelxlldxDIsU+nN5vCJBl72C+EIf/BcXPnV7TgZrTbnqEtH7an9bMcqYnG5TUCs5fBDcC6qlmGSsRKZhuJAo09XBslSyPyPAfZ53JHyEtAWyLhEQDdJhm5YXqdptLkeqj8A+tjjox1o17MutHiAuLKaL3HS2BLWEYZMMWi2Nq84adwhTnCrHUzqXEwzSlvfEEzOqFiFdTAyvKQ9NbiJqU6NW0o3xQiEHk9jFdU+qk8aJbYttyfarSF0jjd/0jEweb0EGAvU58Zph/brhqW99IPEuF69Xxw8BcRbbnEbdKaN3mNpCznqrG5sro1d0lRw6nzbUIHEwcsVpQ7MqTUXscx7UtInmbdJKzr2VTHraHXvV3g75nHsgjzhGFT523JDkuHjEt6E9U3BbU684QE9nm7jwd7MMrdvTYb/y9rZUfVUabpt6Q64nQ/7URV217dGb+nxuyWZlucrQHJzg/SfLxV+qIDj5kai2B3VBcN/xb3n/bNnmEEsG6vZ4biXd+ZzCUYNDzFU0ZlAvHH5QMh26yWW7MWTyXG0OfUPisGNf8jvU0QDXx5uwYZgkB035g6+9o10bKg1PHASo3m+jwlVPtjnY9OiyUasUSg4p4iAcy8FTHDw4x12tpD83cWT/5Dgd1Caqj+ATxw9NlelcXl3tHzrIhscj/vsxfP5/X1LU1Kt2XJBWK5F14QOCCHaXejJUhmYg9sZJ2Rw0cQ46g3Q5Kkx+ndiWTBx0kde6BfiTJwwzRl0T6e0OogeQSvrL64JIADSG6iadi7WMnqFr6q79suSgHps8ZrGaSJhNNod+3euinfJUz2/F5j34+t2v4ev3qKOvK43aIw4Zl4tGheRAkoRh40RkVUmJhW0IE+iiiYckPkKdax53aXRWKxnu91xJcojSZptUAgp10SdPCIiDWGySMKoBk+SQcFnWrJlpg7SbK+uRB/d2lihV45WHc92FxwGII4fFrKwcjXV53Pq58WGfyfY4xAXKRa126IBYn56QHCTiTpLkwKG69bFDe+M7HxxjlBz2t5a0XLi4PavqFkxZULtllByi9y/V1UsOyRNNPWMpWvRksgXB8dQ0qpxV3OuwvXmbXFF7xCHjevXri45Plcm+3G8adJ1AWq3EbQ7iKlMnZTHV7VimC87RwSTVyBOdj9NokFYYmuPJH59w5dB0OPLg9A5qWcC7VtocxMR7mjGKTglAMuLbRPQSCfpcByvUld/JkL7dMLRvt2jM/N3ITDInHrp5kSUD6PP/eUbk0WSTHKJFUfAG0o2jR30BuRxFNgfVc3zg1XdSKjBeb78gOSidHXjad8UE5uph18j92HYil2skB6l4QEgcBvSoT7wrUxAcA3DDp8ZhQI/6VFBdcL66zFbNEQcjFO+d5+MRIepXZy3bkjovQ96APlArUSK6VOamdJJDZuJgXMiSN9zstCc2YcuelmQ7ioWHMowRAI4YlHzOuo/QNVV5rF5RnHP4yOZKto1EbiXDdaKrbzbJgUsE6vvmY9bWk1Sdcte5hORgHsuwfrHUINuOZOLAbUAuNoe4Xz3j0FYqpd49r9tiEZe55NCsCPrk6mFXb7uI3ZGfo+bZqQjaxJH9MeM/Tk9IDqJbu2oc3erzOHpIb0tqjfJUhFlRc8TB6XsV6ugWPiD4+LfvbUmdlzFt4YbEbx7n0FiXx3FhCg2SODRd5OrwfuYN1WVksbHw7St1i2c+dLHaKRnpVPv4qiQH0/aaY4ckU4nopv9l7xupbUNEzL2n78VlJzeevp0jTl/BLE4NdqOsClFdxY3ncohuSCdhyO7V8vwQF6gsS4sc1yKrlXiCO/kzUd07H2PwT/0cS6V0QBnvX+5bBp9equjkWK3k6G0nOZ1wuNpuGAtsCH261SWuaRHmnk4C1XlUVVtLa41zeLfBtKi6fjSiV5PLXHl43jr85mJxDLFa4IEvn4oSY5j6yKKkWkmYRDO+fRqG9euOeWu246BejQAWVMTmIIOL7bpHlA89rAp5Sqi9IiO5WFmh2/3F428q2x3SpzFVV2db1G2sIiO2OaTPuQQQfv9jxyTHQ6JaxzCHRAkjw9fMuWLVdBLtPHovn6TaSa6WkFIzUAeZ035VE88jc7MmWw+XklW3wp01RPB6SckhfTWXHFROD1yHLyZQNCGtKE2Wy0g7l7DYk0u4IXGzqTtnvZ245uTDBjiNsTpyQy1KDoZzruKaqFctR8Tj6TOAgBuvy4cbCAmDExffw5p6or6Qw4QR/Z1Td/CPIcteDlwcNyWBI0WbsmtvUJZ+1rOWq1VwDXX5VJs69UrWtALKbR4d2pBpkLjZjk0aY4xh+abduP35Fc7j5ITzlVXpxVeMC3h+yaZwPGmDOR8fkLzHC8cPQ/f6cvnAJKd97WNqAu/irfSvpcH7p5DgqN4Dl6rltl5+exv27FdnOhWvBaBMFxMF62nib9L1g/9yVd33ropPUXlymaTnGz89LqyvHmPsqaYfdyVRe8Qhi8JRd1qYOGJVWW8+YkB3nHXUoNQeszzOIdll8rfO8yIO6zffx5fPGIWPHjs402LK1UpPCmqwi088JDou5IIAJdngp4oPkQ2ZgDoRHaD2INFJPM4R0ly9oniMLsnmUnEFEWcej+ysowalruPqtM/8YTbufml16rwOq7YG6hlVTi/RHvWDfy4Mx6Mer0pyOHKwvFOZ++riymnbJJdk73pX1v496lPDW7B2J86/5QX8WNgzQTUkzlA1G9RPcsru+oJ6CYwdAJId6RZmeTxMYBxFF1sTceCekUTqeatzd+4o1B5xqEAb4qbm4iL/5DdPS/U1qHdDaiNxnpXVNDadt1KcZ166VpqdbUUGU958VWpkrlYSA7VEQhB4mlBKLaPKQ0OUljB0CQBV9gnduF0locMPCgj17c8vL6sN+fWIdhU+NpVxkhM62XCrgsg08GPZs433nVZvqCUHlSG+PS7FnMvXYeKI/lG9ZP8m1ZterfSrKbF3IN9IiEeVi44dYsAlh4sjgPxN6FJpkGZldM2qKzKOohTa4mDv0iWtjCSHKimWao84KJ76hNC3+D1D+6RPKiDm1jdR8Za2UmqR3NdSxKurtqcWSjkuQMfdciZE/gDktAw79rVGXJ8Y7Pbts4+IjmX9vYrjEvvJ50jpo65WK7lLDjly3z7RJglx//xxw4N3+vqaHZnbCMakV9twDk61UPCF3MWrShwGdzVVMgUKyUpnkFapldpjyLTtf3DzZ08Ih5hkEFx2glONS1z0h4deU3K9H557DK752NGpa/mzs7tixxV0cyGyOaTmurpdea4zxNKcaGB3k8I06lA+Ni85dBTSD/1jxw3By/99FiaM6KerkoAowpu8F5pbi5A3U//z7MAIlXKVlLrVedToUnb/19/nJ353b8iD564XuSPRfzpFHBQugBeMj7fnyBOl1C2HH9RTm5pB/khVXPHDX32fUsd6zJD0pu1ym3IsAhA8x96Nhag91dDE5yH2+lchFbV+8Y0XjPPHD0MK4UKuysn1kWMHJ36L98yDG1VqB5IHCr1kwy8Xq8uLu2lx+ekn3pNqV7fYDuxZj4GhP3/a5pGuz+cJ596VWVYFaUqWRjg+c+IhShuKLqW6OD/luaa7tzjQVa1C5Xj4q+9TXi8a1sVvxoUJ0tscQrWStYXKoOaIg27SDujZ4CyuxbuEMuOb2tdaTBlmdb7asvium0ScC5HFYdl975tnHRGpOBKeRRJBEDk1lQvgxJH98ZcvnAgAUQCTDGnX1LAsKRrPWrZFee9jh/ZRLkCfPEGx8CL+QDbsbMaUW19MnSeiMO24nrvXSfZXi6mopRcrOgLwy0cO7A4ZudB6rJIcTh01MHkvwnEhUiulB6dKNyETab4AcltVUq0ktZfqIcBvLz4hYWPilZ0krSj+BuF/8zUMDKu3plPEiMF6sh0FCOZaQeOxppMcGgrJeKI47Y1B/cTHmdbnJTBiYI+wz7jiuh378PaWvVE/InFy8ZRTqWQBYb74OIeOgerVxByNWxuuksOQvt0gbhID6PWF8gLAJ/pvLz4hUU82/C3ftBs79rXi+aXJhG6NdflQakkSGjlS9qlvnRZxPzo/cv4BBK6s0riB1J7awf3EC/kNTy7GRbe9mEr3HN1TKOr/dubSRLsq8I9Qa9wGsH1vK+6c9TZ2NbcqvUvED1nXj3yfkeqsJHKm6aspbF8VH3P0kN74vqAOET12Du7TCAAYGT5reSwqg6eIumhHtJB7Fl5GyhMsw+LCiR0AzHxzo7aezOUbOd9QTP7544tTdQLVZfg98uuEe9Gl5AaE9C9S36LRWeTKzbYJ3ncSaUeSsJ5Q8ZM3vwAAeHUVDxCMz4n1dKpHOeaJg68j1ZIcai7OQTUf+MtLSAQWUKh8172o2y+dgLFD++CWp5c5GcFlXT7nAE88LJkcjySbw5nXP4PDFAsKEOsuTcShT7c61DUF1zdrjKj8evHDFcGlmZTkEBbcNGNp6hpIdUuM4X+eiBcL3eJvk8rFb/exN9anXFIBvVop2ZA8Rt6/QFg0UhRLXw4gSHGxtyXpjsntVscf0g8PvPIOvvXBI1LXqdwv5XxdRIR8jqIIXNHbpT2753FiBwCfv0OV4DCA7LFmYpD5+1blCCoInj38UJy/Ou8isZ7ctdim6BZstoskbShxufRbIiLz1+zAuvC++LUJyUHotG/3OuzbkZ7ndTlSStnR3h5Vog41SBzSMyKK3MxAk7l4qpMcJoVujrInjvbFSuonLjnIi3mkVhIaXa7ZI4Gra8QJqbIPxCoJ9dcS6e9zKhfK+HzPhkLkUZLYHMcCVdSqTv3margGQqnGIjnor01eF6tN4jgH1avkEcU6w6XcbryYBkeqhGsqjyGVq3MhR5Fa6pVVsU1rYI+kZ0+WtcW8LWxSlw+YbQ5imyWmfg+yfUBuq8FAHKJFX5oj4iMVHSXcJAfzXJGJCI8YB4Bdza1h//E9Je0d6rZ7d6vDruZ0TEeWmKVKwKuVRESisb0d7sXxy6eSm6X07Z50W5W9kPjiLqe5Jok6iNy63G9w3j7G2OYQV1YRB5W3kYhoLAqDNBCnJvjECb0BQyMAACAASURBVOI9uaUpCPpPfyhnHzUIN110PO794smJcpu3x7nHxWNoKzE89sb6VB2XcaXUZ6JBOvI3V6iVwoXcNc1CpOLQvG8OecgqFV0hF0Sub9vTgv/+R7Ct+7nHDcEFkuE8C+dp2hZWfBe8TT5XjDm9coE7tO07U6mVVJLD/1xwbKJPXZAmP+afg046FSGPUXYYkImI6J7MGbxrPhpH27vsBNersYBdzW2puR5tGWsddWVgJQ5E9Eci2khEbwhl/YloGhEtCf/3E85dTURLiWgxEZ0jlI8novnhuZso/LKIqIGI7gnLZxPRiMreYhKqCWniBHXgRiPZ62jmt0/HtG9+IPqtM0j/7JNJr5BA3I1rxpJD8hXpXFk5+navi2wInCMXJ6Eq/YRsx+DghuhDB/TAuccNwW8uPiEtOYAwuE83PPfdM/CdD47BJScfit99drxz8BTvP+UymCOce9yQVI4j28Iubof5qsA9H9YUq95ctomUF35VbiWl5BDaebR5/6Vi2fVTRXBUz+eUUQNS9Qr5HNqKpUSMxUePHWzcl9kGldTCIS6UqcR7ivpMqMuYnifnwaRD+nZLtAmoJYcLJwxHY11O6DvZsvguOMO0t6UNJ/x4mmYEegKq24yK9y0ayzmhjLwgkZy/uu+jV2MdiiWWSgMSq5WqQx5cJIc7AEyWyq4CMJ0xNhrA9PA3iOhoAFMAHBNeczMRcavLLQAuBzA6/ONtXgZgG2PscAA3Avh5uTfjAtWU5B4E8X649nZ0AWb9etRj9KBeiXpy4jKi9CRP2xzMkoNugTt2WF8h3TIAuEgOwf8SY3hs/rqo/JTDB0bX3HTR8aFnkbJbDO/fHbkc4UfnjcXksQdbg6fk/nXqoh6Sy6JNJSSOT7xX8bIjB9vTgesM0qIrqzxP7r78pIgo6uaQLgeRyfVWlD4H92nEpyYMS2RO5ajLE1pLSZWWKs+QzqirerSc2KkgesHxPlujtO/695QnSrxvmdD9+/sPw31fOhnvH90EIDk3dGMX1UVpRkO4n5Bh2q1Q24gQA11FyEFsMhNQUMw5sY7oraTjUbhqUSZE0TplHHnlYCUOjLFnAWyVis8DcGd4fCeAjwvldzPG9jPGVgBYCmAiEQ0G0JsxNosFT/su6Rre1n0AJlFHkkbFC5E3cXdBsJi76K6Tk3Xjrv1oLOSt1J/rjmWbg47Lj8/Hx6u27sXm3S2JSabK6y+qTKwbzju7+5qDp+T+dYuJnNfexvTLKgSOUYLk8M2zjrAGqcmvJxkEF9YBJbZaHdKnW2Tn0b3eY4f1wQmH9E3FPKgWEnEskT6dpXMPcWze3YK/zF6F9TtjQ6/quY7JsFeGSQIU3W75vIg9huJ6PRsKiTK+H7eo+//bl07Gc989Izo/YUT/RLAph84gLbpDmzLScoYpS4ocEfKCHbk4K5g5VbqLpFpJ/Vz5Pcp2N/68ZW1FR6Fcm8Mgxtg6AAj/HxSWDwUgJpRZE5YNDY/l8sQ1jLE2ADsApGXmCkH1OiJdXgbq4LpRuRgKP2fFVtz90molNycuAEBgcCRCSiWg8pqRx8XxWpjEbcPOOHpap9Pm3lc2P2yVQVpXz9XmkNdIYUD6/vmCsk2RKv3Z75yRqC/e639/JHYhLeRzOOHQvpZRJftN5FYS5suvLzoeQ0P1B1GsthCJ6HUXHoelUz8EIHAxfuDLp0bR+GnJIf1A97UU8faWPWE9u1ph4dqYwOtsUx84oilKT8GhegWmILhWQSIdFLri8ud//i2BO+fnTjoU//v594ZtIfpfKsXquRID3juiP4b3T0pDKqOwdv5CbwxP2RwYLMZH0d4RY+ueFuwPA0Uf+sqpynqqADtxxInzwoP9479NiI655CDblWz7q1calTZIq94cM5Sbrkk3TnQ5Ec0lormbNm0qa4CqRagcFzFZFfKL0CgmQ1QJiB4kqXpSJHVbiWm5fNFDSDUuju995KjUedmGEV+Xtk/o6rlA56vNcfqYJvwuTL2QyyXvhy+2HIPDhQeI612mcKs8ZEBycRHH2lAnq/HM96FTK7UVGf5v9qrEuSjgLsw9xZBUZeRz6cAtmSuObQ7psSzbtAfLNu2J+rKZEBL7FOtyB0H9LaTqGeaaWPyrMKPoCOkd/McHx2BAj/qwrWDg+RxpF8lk30k7BgC8rOGauRqzVGKpRVS0wXDnB5kJmnTkQYnfct9rt+/DCT+ehofnrcOYQb1w7LC+ynrimqAKxBSJtTiEM4+MkzjWFYL6Ynrvx+avU+YJ60iUSxw2hKoihP95dMwaAMOFesMArA3LhynKE9cQUQFAH6TVWAAAxtitjLEJjLEJTU1NZQ1caXOI1Erc5mBfAPO5pN5UVFuI4B/hH55bjn+8+o62vbTkwLRcUt6ghjn+kNj4pdr/mi9aqsWqxJiTsdYFtm1C7/j8REweOziqK97PL6eM017Hh7dtb6u2TlxX1Imrn6U+PblaYvvby6vxerinQaRSYHEdoiDPldifKsOmnPXTJDkcJWRVNblPnxkucKKhWJs7iNLfgupZ6JLAAUmnin496tGroZCSVHo1FqLxiukkiizuXyetRp55DlSMR8X/+11z8YW75ibOibEl3OYgqsSmfmIsbv+39yauiSWCoN4qIZq7Xoq4FusVE2oj3mfcrktep7pIcogf5hV/fkWZzr0jUS5xeAjApeHxpQAeFMqnhB5IIxEYnueEqqddRHRSaE+4RLqGt3UBgBmsA3emV7V8dJjHh79EeScqFQr5nGREVV/D1U8/eWSRca9pmZMLJAc9l69TF1xxWuyto/JSyRPhm2cdgX98+dRk/5HkkE2tpK2H8uMcTPYAUa1jg8hBuwxb3LdaJznsa0l76IgLO2cAEpltlYtu8J+fibnM9LhOPmwAeoV6+2JJLzl85czDAcjEQV2XoCZaqnHqnvdFE5OpNnK5NNOSy1EqjihPSa8v0xhN5+W6JQZMV0Rxiyli+P3YGAfZ5pA0iqc3TlLVi+sIkoODQZoTB9u2qB0NF1fWvwKYBWAMEa0hossAXAvgbCJaAuDs8DcYYwsA3AtgIYDHAVzJGOMK9isA/AGBkXoZgMfC8tsBDCCipQC+hdDzqaMgvo+eDQXM+d4knCLlvNFx7HIdXVptESaxPFUxxJ9nv43nl2zWjkPOLJk8Jxvf5G4IXz9rdEQQxbpBNHXwW7chfSp9gMFl05XCy0ZPEwFiLMnFmVAUdbZa24hOhy3fZ/BftaOaaLNS+c7rdPkAwMLnzZ+7aqHK58S8QfoNpvi1oq5ax3WrUq+r21QzVN86Ox3JXRAitJN98QNE41uyYXe0+OnnMoznk+PUO0Dc+f8mJuuxJOOgYgbjxHvAC0s347E3Yi++ZHLAuB6gT7X/+8+NBwA8+NraqExrkNZ4K1Ub1ghpxthFmlOTNPWnApiqKJ8LYKyivBnAhbZxVAryIhRsu8l/c/HXgTgQSVGq+o/QiTYI4/ve34OQEq6rlcHVMPJHw/cwEMfoCt4mn7CFvG7RdIPJA0ndt9iHvhddm985Z0yqLOlqqW5TXMzFptPeSkFBo+BKycdZF21B6a66kgmLySkin8tFCzljeuaFF4uLik5NGEifDsxNmLpj6cbdifKvTRqdbjOnlmg5w8LHN/+dZBp1m3OFLidXYpwGw/ngPrENK7I5lJLrgBaM4eI/zE4Uvbg8qfXmzhyA/nmfc8zBqqaVqNMYpKuN2kufIRzrkmi5bFMsSw66F+2+mKbb0QUvcbWS3OeVZ4xK/M6aYE1UK9XpVFqOAVXcQKiC7CUjR0jrhl3I6RcAZfZVgXjLZ3l1m+uuXJ8bC8Wy//vCifjn62u1xFz1HNK5iFjo7aSWHMTIY90riBfT+L6zpBtRtxmMcelGvUo0GieRcnGMBQf1wHXaE/4sdLsiJus6upaHTItoc9ARddkOqG0TsYrIRZvAobc5pN9jZ6DmiIP4ttMpEtybKeTJKYGbu44+uVgAJtUOElw+R15a0FUcpm483EYQBd85Sg6629MFT7149SQM6i3l+nHkYgt5vTSiIugmyUHVjOldqfJv8aNRTT3xjbPSahYO1a2lJQf9IpXPBfYtris3LWaAm0H6qUUblOXpNoN5rrN/JccZq6oKOcLHwxQxskFahsmjCnBbcHXqL1U9l3xjvH9Vm+8fnVRDixmVn17s5kV5/8trtPeli3OwjbfSqDniYPKZjj1I7O24Sg7urp+8Hfuk5YY/uUtZjaS0ORj6Zyy+d+1i4DgvdcFTBwtuqcm6+raYMCbGmJIDVT1ncZHMQvhVUMaXOLapzHYquUCaJII42aI5zoE/g4RaqZ2+HXxe6JiFRP+5eKEv5CmSpOL4BnUbNrWSiwedboMcGQHTUkpsOaplmDR2jLsEG0bQZvweF2+wS6JtxRK+/bfXtecjtZLG5qBKztgRqL3EewnJQb2YukzGguTKqnWJdByXqp5OcuCurC+tSOo+5TmTJacOdwXkIry7QVrdHlGGIDjJy8XYpkbSVgaPtYpqJbdx60CKhco1WlwZrxL+Z4LkoFv0uf2HSw82tdL2fbGbb3s1E3kibcyNri4QuIqKO78FB+rrzj56kLI8Tsnhsug7JlTMBWvARbfFG0VpJTHoJMz0XOLVxg23BVemnQQe+VpyNzkuOejuu72qQlfUHHEoGYiDLOqbkM/lkpKDpl7WRUhsZ+UWtVcOhTYH2VCWJnbuaiVuc+D3pFsLXG/HlZMLxkRYIhg8TVKYS/AfR7NgbNZtGK+D3E0UBOdqyAzxobEH4xPHp3e1U9kcdA4EfJGds2IrWot2tdLm3XFEfBbJQVW1oS6HlmLJzUkjyrbKEgQlZ6ANH37PwfiPD6adCYD4fpwM5wrHj8a6HH5z8fGJMtUcMmUNcLM5xH2biPGXThuF+kIuNc5jhiT3rlfFOYhodfFBrgBqjjiIHH56TrirldKSg7qeq1FYZZDWQaeySSfpU/akbVM01OmG4S45uKUXUbWpr6d/N/L2pwCwt1VQHUjn5Ky4Ln0DSLhq2kY9sGcDbvnseGU+IJW3ku4xcKLx2dtnJ8aiG+POffF9f1DDlaugUqE0FvIolhiahZQvYwapczPlc4F9IlJNhu8k8gJUDHxAjwathBsZpF1cWRXu3Q9/9f346LFDEmUqryY9I+TmaRhk2w/fo2Hx4I4FInE6dIA6gSKgtjn0aiyAseoYq2uPOAjHp6dC5oP/bpKDe5yDC1QbmsuuqWLfqjHKH1kWV9YoclSxB3Gynmt7wce6wyGSWf445cju44YHnFX3+kIQPKVYxBpUxEGQHGQCNKRPN7l6Arq0z0nJwfwwzAbusB/By0UbES/bxrSSQ1DOF47FP5mcyBBcDnhch6ijP0hyKODg7rG8fz7uKBeV8hp93/HeJW62hFQAnqJtFWNl9FbKGAsiErIfnntMoh7PRivez42fTmcDqDdIDgN7Bs/eZS+K9qL2DNLhe7ntkgk4fUwyBQefIi7EIZAc4penC8Bx5Yrl8QHA+w4fqKyji5CWiUE2V9bgQ2hT7EEsQs4PpSNA/IPZuCvOEHpI/zSXFNRNtiHvo3zjp8fhrQ27cc2Db6DImFJ6UHGXCbWSNEzbo5Gbi1QciUykaQzsWY/Nu1u05+P2uJQa6+hVe20AaeJgswdFi3N7rfCICXXSgKsnYqLHGx9nnF5EpebUjzG2Odi5ZJVUqewPbvWCsWVRK8WSw7B+3fD8f56ZHmMuTex45LuIOikITkz/0adbXVTGjzsKNSc58Nc9tG+31McYGx3treRyhNY2YeroOG3HUanmpzY9sSZCWl5EVJyobptFrovlnLGOPv5r6ZboePyh/fCbi09Q1uOcnJj0jGfnTNUVhjnh0H6p893rCxg3vK8xxYeqbK+gCkkbpLMtnCrJQdWnKZAu0b9Uv7VY0jsgyMRBQ0RkA25Wl0elzSGcL3sE4qD1qgql6WijqnCccRZbSo3LxDxltTnI0dmqplWR1HrHvHTySJ6NVe5HlBxMOdGApKFZ9S65AwJn1I6+5onoXO+QIIjvo6NQc8SBv0TVxOFFLjrOQo6wvyhKDmo4q2GizUWSfaiQI3XqA533FQB8d/IY/PDcY3CMlDYj7j/gqPhiwPfANuGajx6dSrMs9r1tb2uC4+zdqOZ0dHswyIhz8iiIg2IB2WuQHEQ8Mm9dqkxujV//6uo4+ZlKrSiWmLyZ5J3TWisoObQVSwiSALZfcuCb6+zZHz/L4YqNhnj/xRJDWzHp8davRz2aejVEapb7vhRv/WokoFnUSgS0tEmLvkZSkZk/s1op/j24T2OUjVVEXT4XMUHFkt6xgEsOIhGrU7gIyzm7RPQO9zephlqp9ohD+F/1/mKKbRcd8jnC/lZ16gURrmol/iGJi/7bGm+lvMKoxseU6Fv4PbBnAy49ZYRRX11iDA2FHBrrcvjRecco6316Qpx018SZzg7dbG+aviQqk9NmR+MUm7HooAO1RfqcuID0CCOwRX9/02u48i+vYJ/lY+M7h70uEAfVYu7ikgvE+1E8uTDY47qtVFIuFEBaPWTckwNAq2PQmowjD04zDnwOiRKgzruoIKuVwvupy+fw0vfOijY4EsfmYnNoc3BlzSkkB3W99KKr2hsECF1Zhd+6hJDD+3eL8n2VGNMa2Pl7s90Pr6f6xrmaL0skdrmoPeLAJQfFKpQlp0khR4nFx3XXMxumC5GrTy9OZ5gEeAyBSq2U/C0SJpufei4HgAX3Pqxfdy0X+7mTDxX607fJM9Bu3BW7VTZqtnhMqhkMYwy5vp89tih1bmRTbLy/67ITldeacNQ1j+Od7fui37J00qr4GPsr0mWY4mhE8Odz+/MrAAQLhk5dJDejIyKizaEM2pBKxgjEhIlvcgMYiHzowdcm2RxSbTqqlWIPMReDdNo2oVqkVankRako0aZUt0FDHHo31mFvSxu27N6PR+ev1/I3/FmKXkh9u6fnkMkxpjF89tWIdag9g7Ri6z4OPpldsiHmc7kEN/XeEf2V9VxFe65++frdr0VlqgUJ4IukXa0kcpw2/XPAeTFs3dNiJCQi0XDRafcQ8ijpFjVR3WRSxXCiKKcouO9LJ2OC8Pz7dEtPa5e3sEvYV1h+us2K3ftUcE0nLkdcZ7E5yGlS4jZjzrQcyUHdd/A/uWGOXsIplhjue3mNcZyqrKYqxFuPukgElGLqlBkCKC0p6PT3geQQtzm8n9rDLZ8jNLcyXPPQAgBIxOwkxiNJDj/75HuiLVTlewHUqlL+/Xni0AGIJYc0OOfmkke9kKOIm/rxeccoN9YBzJywDboJoHNlTbs86s/JyBHhodeDdMKyt5AI0UjuojJLbIyiqS+m1DCtabpMojLHq+onq9eYjP0ScXj4q+9T1kvYHBxUJvx2WoslrbQmj12XMZe/4pZiCY0ax4Os4H3vbxWJg7puPvwmbpj2FgA9M1BwlhSD/+Ka/4njhyrrEgEbhb2zATWj0dJWSkizADB5bDpjathAYoEe0ldNHPi8tDGV/HFwCcclXYqM+ioSh9pTK4X/VR8un8wuXGI+T9EHo+OQAHdvJdWrvmjicEVpHCEtIyU5CLPPplYSL91t8IQQP3gXyYEv1J/UfNRAMq7BaMTNqUVtXXbd5DgsA5UgZ1jl/uW63xyu3kqxVxiLfmvTpLuOnathiiWtiorjtksmGM9z8HcsqpV0hDaXo8RCrpsfSZuDSVJM2wDPHTdEWffN9btSGQVU/e9XLOCHDtDv4tgi3JApDqXI7ClG+PUxcTC/7yJjWCuoOoF4nfDEoQMQi/3pF8Mn7eqte9GroYDXrjlb204hR2gOPxjTpFDpPQ/qpVhYFIveF953mLLNvKMrq6sXkHze5B8vSgKm+/7LFwK9P+e4/0Ox3wKH2IqN21YRB5njzupPr4K8YHDukhNH3a0n9gsxELoBPQPi0ytUqbUWS/o06dLYdQuDKI3Y3recGVcHPn9djPt5idPWqp8SaiV93/xcMsGl+6Joy0o8sGcDbvjUcYb+k3ZFk9qvWNK7GHPE3krBPeiJA0UBeKdcOyNxjn9PLh6V7UXNEQcOk+Swp6WIkU09lMYijnwu1nHqOD5AzcXefflJqTLVq9arD9SurLIXhDhXTWMM2hSv09dtyMdcvimx3+GDAgPxvnAy6+Irgr7diJhuQxeTOq1SICL071EfvXMdsfnTF2JjuImR/GaY4punf97fVtIaeuX703nTZXFAcE0aGBukReKgXyTFjXw2Seob1djMQXBp3XuWNVHF5IjP6ANHDMQnT0jnvYrHljRy674hvo+FTo0mjyeSHAyrr26f+OZQW1GswkZANUccXGwOgF1l4mrslSd/fSGHw5rUaTFS49HMHiLC1j2xUY1Pyu4N+VQ9jiySg2nSipvdmCQM3h6fzLqAvmCgwqFFB+26ZWRHwEVXfsIh/fDxUPVhWvga6/Lo170umo/NraUopkCG3Jdu0XUl8MHYjKdT7Tzzln2fgqcWJb3rdC6i7t5pwX+X1PjK6xVTTrxvnZ0wqoukxKRTH3O1kk7yi8fDiYNZcuDnVDwAl2CrITnUnkEaes5P/PhtnJfIRZg8Q2Ruom+GkHd9pCWwbme8QHzptFG4cPxwHCIl8cqT2xjT7RvUSgIBtRmPgdh+YyIOrpKDvJ1otZEkDnZVom39FaN197cVtZKDPFcvGK+3RXG4OCC4oD2EdtKR6kBK1+cY2RwEb6UsWWZVc16c2yZplve/T7A/aoMPc4HkYNvzgvfdZrE5BH2nGaFnv3NGlEyyy9sciGglEc0noteIaG5Y1p+IphHRkvB/P6H+1US0lIgWE9E5Qvn4sJ2lRHQTVSK0UwOT5JDFTVM8b6orTtDxh/ZTqpTEcSXHo1crNUsBeDJh4PVcxijXNamLEvft4KPOPy7TBiWkOVa1KS8OqsCkLPtYZIH48ZsWguhZWoYhqsn2t5b0cSDCc77k5EOV7zroV7jGJa7FAeXuOvbZkw7Be4b1UZ5zlRwim4OgQsmyJKruUezbRXIQ3VxNzFpbiVk34clnkBxUHomHDOgezYUuTxxCnMEYG8cY4+4PVwGYzhgbDWB6+BtEdDSAKQCOATAZwM1ExN/OLQAuBzA6/JtcgXEpYUqfIU4m20chLvomKUOUML42abRWpaQKojPtBCdyNLoAvEyurMK969QbQZtu0ghfoJtbi6jP58y6ZaGZfQZPMdnmMKh3Axb+6JxUPVE6u/jEQ3D/FSen6pQDV6M9P2dbVjl3+NLKrXhn+z6tv734fGwLCkfFbA5lrhBmadru3gzE9zpb2NRKJzj87rPpHF+qdyR+j3bJIbA/cmiZtTD4zx5ompSEbAGfolqJp17n7/hAIQ4yzgNwZ3h8J4CPC+V3M8b2M8ZWAFgKYCIRDQbQmzE2iwVy1F3CNRVH7KuUfjNJTtuNCwDMxt6ENGL4EFSTXregL16/K9LlA4Y9DhylGyB5740a9UbqGge1UmuRoVejWXspvosXlm3R1pNtDpe9b6RycenRUIhcUZt6NmD8oeoAxawQ05mYnmekVrLaeYL3fuuzywEgYcwVIbZjarJ7ffycrZ4zjgJBuWolVyJmszHJqC9oFmhFQ6p3JH7XNskBoERGVK3NITQe25552iBtlrxFyYEHyx1IxIEBeJKIXiaiy8OyQYyxdQAQ/uebJgwFsFq4dk1YNjQ8lstTIKLLiWguEc3dtMltI+/UgKMMkelzWbw9XPWmdY46etWr1ompO/Yl90jQbeiSRa20TIjq1Kk3ZBgXSOGUKagOcDeOyq6svTSJ/MQ2y1GL2DhKW7v8lK1rnrmW1zNlzFUdqzA+zGpr85xx1dyWq1YyMUx5x/uRGbjvTh6D0484SFlX7baqkByEejZ3XqJkgjuzKyvD755ZZmwvi1qJb9vLwY3yEXE4AFxZT2WMnQDgQwCuJKIPGOqqngQzlKcLGbuVMTaBMTahqalJVcUK0yMV373tI3T9aMSPxCQ5fHjs4MTvldd+xMqJAMDfv3wKjj8kneYaSBIjG7ETxeexQ9WZW1PtO6gEADuHlsU4WmJBdkwA+NQEtWEWiCUx03s6YlBaxTe0b7fUnr4qGNVKkUHaLjmUWDxWbVbWDES+e5iuxO6dZjwt1CuPOLhIVrZxyF1fcdooLbftamcSx9XUs9FQM1iYRLdhXReyfUCnxpQT79nUSmL6nKJMHLq65MAYWxv+3wjg7wAmAtgQqooQ/uf+bWsAiF/zMABrw/JhivKOgcHmQGVKDiaI7m2mD+Y9w/pEEsBH3jNYWw9IbppjUtlkkRxEfHfykU71zC688bEtxsJ1/SEKfN4ZAz41YZixf/7pmN7T1ycdkSr77uQxOPwg++5pZpUAVyuZ2+CJ3biaoU6rMhGvMbfJ16jXhOyxur5FTHmvmtCKz3hgz3r866r0JjbK6yrgDZXekta9rg4Jj0Sbd1EuGQRnUt+Ki7VOjclpv5taidAq9M3tFAcEcSCiHkTUix8D+CCANwA8BODSsNqlAB4Mjx8CMIWIGohoJALD85xQ9bSLiE4KvZQuEa6pOEyurOK7mvv2ttR5ETabBIdrkjEA2BLGLuxsNm+t+WnhQx7QQy8aZ+E4Reg4WFP7MpIqOpv+O65rInacQ2sr2dNDcE7OdN+qJmz2ERe4LlTcID0zTCSoe+5Z4lVcIT6Wh75yKq49/1hlPfH59W6sw1BNfiEgqQZ1nW+ujgo2OBOjDHa4+kIu4SChq54jck4rDsSpSExxETlKBuBxYtC3Wz3+8u8n4iyH/Vbai/Z8CYMA/D18uQUAf2GMPU5ELwG4l4guA7AKwIUAwBhbQET3AlgIoA3AlYwx/uSvAHAHgG4AHgv/OgQmV1bxw9u8Wx1oxOHqxZElF9HLIUF6bslmYz2R+zFtFViu5OAKF+4ZcNB/C8d3/r+JxjZLLNDZ2twGSyU7cVAttK72FhP4k/yabQAAEo1JREFU0GxENohziKG7J1fXT8BdvSLeu0n9JT4P2/pblydw7aQzcTCec5+zroTE1VYIBO8jwaBr6udzyY2/dODPhDuTmL6LHBHe2hDbAbnNob6Qwymj1NsHVxplEwfG2HIAqcQkjLEtACZprpkKYKqifC6AseWOJQv4u1ZNjCxc2WurY88SE8/g6q2UBXySdavLmxdo0TW340JH1H0n1Er2YCOOIX30nCkRop3GbGo9F7WSchtVR08tE/g8snuIJT1SdGnfxWZ0G0BlhTgdTFPjIMFoa/s+gvdsD3oUYda7OzUBwH1+Z/Hgk+9BV72+kHNL8y9JDqbvIp8jLNm4K/rtIplUGjWXPqNk8FbKsn5u16QGkJHIQFmhp80ndb/u5mjrjpYcTBAX/Dqbz314emjfbon03TLyFHhwtJbsboOcOpjUfyrCaorxcAVv154JN6mr/ubZaRsIr8exs9m8d7D7fhJxmybvLNGZwDaHRE7YNWV4naGeeN8PfPkUYzuuEpP4TmwERX4uOjXQO9v2Kctl8DH+dmbg1WQMDKXk2uGyy12lUXPEwVWtZIPrYps1xbUL+ARvrDcvZGJ/Lu6ZHQabKiR87qMV3kNyvRILPEhsqqrY5qCvo1ocTDEervEfvF0XQ3wyd4+6fkIKs0lM4fx+z1B1dLLYN4eNy7/qQ0eG47CrYTh0u6aZrpEh3qo1b5Gz5ODOrInP5ayjDtKmC7epoDnknepM8yNHyUDXahigU2Ooeo+djOgRK95LlrVbfLHjFJuOx/XcctdnAedAbO2JpyvBEZeLWYbANsAeScyRywUcVInZjdz8PZskB9Vi3LNBL425PkPXGAuC28ZSWSKfOb502ihzm8LksBGHnOP9iHPdlZCa+hYlB5u6z9m1PJNaKX7f155/rNYl29WJQY6AN9mk5DarsWe0jJojDpy1skVIW9PvCotOH4N6J4sBzBW8TZtYnM/wcWXB9z92NK443bz4JMZh0707Di1HFKWOtnHlXHIw7rWheH4mtdavLzreZZjRvtD/WmomijkiJ121mC7bdt/cG89WT1zIbcZ9/pxsC34hoVYyE1IegGbqW+S0D7dkMi7L5mC5RtziNmt2AxV2SSpB03cxqHdyHnrJoQqI0mdYbA4jNLtDcbhycCJn5Mrd2JP+BW3avgdXvXJWfP7UkfhPx1gIwL74cEJt+8jExdSuVgr+m11Zk+dMG78AwAeOcAu8dN1v2pU4HDU4Dkq0SkxRQJ2NOIiMg1uQYpNqkyoB5wt7I9gCH7lLrEly2Be6Ph07rI/VpuDKdyU8vyxtim67pkSLI5vMawXH6WOS0d2mBb+3LDl4g3THw2RzEMXY31ycTuRVDrIYwFzr8bU2i1qpAxPdWmFbfFxiEoBAvcHVMNYU5E7EIfnbtPELx9fOPBwnHWbO1XTzZ4K5o9o8XgSRm1pJbMcqOYT3bXs+og7fLjkE/3sb0pUAwJcFabKH5d6jvg3Ege+Wd84xmj2eBbiqdt43OnYDtX1nfQWNgIkZ/PbZ+l0ORTT1asDEkfHc6WawGcoqzM6QHGpvP4fIW8k8Mfr30O8CBwCnjBqAGW9uxMeOUxupOBI2B0dSbOPQuORga68cgqDcwrSd6G4xnPN57+LD78oZ80U3y0ZMLvjWB+0LwUGhSsDmOSRuQ/neEeoUKDJsEitfRFyifzlsz9I1kaB43vbOOUyEaVi/7pjzvUlo0uzXLWKwwQVaxAmH9EO/7nXYtrfVwfvKzV7o6rYLxASpR33eGFDI1cDcTbYzvJVqjziE/23Lgm3iXPa+kfjYcUNSukEZ4odn4/R7Nxaws7kNt14y3liPLxCuNowejh8qALzgmB4hC2y6ar6g2RYfca11yTsFmLnD/7+9Mw2Wo6oC8HfekoSsj0ACZCNhEQghJhCWQMKSEsIDJAguLJIAKiCLuFUBAi6lFGApJYtVCJoUKApliQoIUkAJiCBLFJAYw2oJyFpgSAKELMcffTuv82am752X7tfd752vamp67ty5c8+cnj59zr333Lxc9fiC52td6BpP+Ow+2wa1ffacHVPfX+kGPYelDKzDxudlqJHs6YSNesTJI9O24gUYPSz9/xXT/QK9YGbj37Pr5ircOISGkX3E15WZnoVscRh4bMdmvPjWqoYbPOVJ/zMOKbmVkvhcThHxGgbY2L0PHXNIWwgGbEhHHeJqPvmtQ4Lv4iCnldTei74LK3nqvbb8gw3HoX/WtF8oJN7fE+ILo3cMpaXLOISmLBk/sv5GPzGxcRjqS5PehNcUstq8O9ttmT6AfMnRU7nuzy+ww+iwLXObYcl35qae87HoPnHaezBe+InpdRNK13z3dp5xijistPngdu6+uLPX1ylBfxxzcM++pfm+Lf9CacZzCK2327gRbD9qSNDd5ojN2oMvPJDP2ITvxI7TD/vCZMnVxKEypRnQeKVq1oT2rUVkQ/irGR2lcX7nznQMbmdMR9gddwjrNoT9ws8NX6hlr0kjuW7+jFwueoPaWz1J+sLaiW9W5uw8Ovh/cfzeE1Lfj6ezbu25sYw9BxGhzbNZVl70Q88hZUQ6QVbpJpJK9Q1QDh3Y5l0BC9GmLvd+7cBN7Vqv4RvoXR948UkaB1/YIiYt7u8b2+kp8WCvL5wmdHkvofL46NxtGzo9WX2bJf4Ns5qKnTf+9SVhnl1MyJhHzK5j0tPdx9NZOzzZDeIxhyIGomP6nXGI8U4DzcGnSpudAHDjF/bhriWvpa6bqCJHegbtQy8+axJjBN7ZSo60/9bUcR1sMWTAhmy4WRGLUW9/643rdQ1I+2YMFUnXXgIFdyQjYtsRetkNsYmjhw1kzbr1G+3GV4847JeWMBO6wkpFGoc+ou5wAh2HTBPVXXj4LkFz5CdtOcS7srUvEjqVNTlG4JthE+PbMSu5hiAr4pDKnpPSp7yKJJKwFRBTBv8dLHQZ2CKnQ2fJEe5mxTf9tZkZQg+dN4dHL/iYt158g+NbbR+Hlcxz6EXS9nNIkmUs9POzt+Pzs7fLrL2+Rvwf9F17kmMEobOV1nv+XBp8/xjOVsMHccsZ+zLZY3jiXFHgl+fCw3fh3qVvpNZplnu+eoB3yjZ0GeK8BvB7m3MP3ZkzDtzeu24jzpIbsv4l9Hxc505235jMADMOvU+o59BX7pKqwLrAsFJywZgv02vMeo/nsP+Oo7xpLnrC7g22bk2SlMDnCeVxgxE6UygOlbz/YT4D+L1Na4t4p9BC5FW+eMlhmV4L1iX2ZUgj/splr69IrZcn/S+s5J7t2r8xi07ek28eMbmQ7+4ac0ivt3pNl3Hw/bni6b6zdkifT37q/sV5dMndBleu9k9EKIohA6MQyHsBaUGGD2oLXtBXBbK+SdxgHDyexlsrsh0H6wn9znPonLI1H9lqaKFZSsvIQTuN5qCwLADB/O7M/YLqhc5WSiag860xWXzRwUHfLSKMH7kZL70dlpM/L8Zvnr5+oUjm7ro1R08fy9fn+k+Qp749txd6VJ+T9p2YaYLJPFgb6Dn40vH3Bv3OOGy7xRC29STV891tGmFMG984lXmSeMGSL/6djHmPSUk90Cy3nzWbt1aF5eTPgwFtLd7FbUUyqL2Vyz8zrehuePn2kbsW3QUvg9pbWb12vTcR5nF7jue91Wu96ybypDTGQUQOBa4AWoGfquqlRfTjme8VsxqxP/PxqWNY/v4aPj0jPUXAeZ078+WbnwCynTAwYnB7odOHv9gPZ6j1V6aN7+D+Z970hrXbWls4reDzohQ+mIi0Aj8GOoHJwHEiUkgAfEBbixmHXqalRZg/c6I3zfNRntQEVeWsOTsU3QWjl7jq+Olcffx0xpU4jBhTFs9hL+A5VX0BQERuAuYB/yy0V0bpuPOc2d4FRFUjq9QZRvkZPqidI6amLwotC2UxDmOBlxKvXwb2LqgvRonJY9FaUdx+9iweefHtorthGHUpi3GoF8epmaAuIqcCpwJMmFDcQI1hZMGUsSOYMnZE0d0wjLqUxZ99GUiORo4D/tu9kqpeq6ozVHXGqFFhWzYahmEYzVMW4/AYsKOITBKRAcCxwK0F98kwDKPfUoqwkqquFZGzgLuIprIuVNUlBXfLMAyj31IK4wCgqncAdxTdD8MwDKM8YSXDMAyjRJhxMAzDMGow42AYhmHUYMbBMAzDqEHSNmAvMyKyAlhW560JwH8CmhgBLM+wXh5thsqSx3fn0abJk129PNosUp485M76WtBM3TLLs5OqDvO2oqqVfACPNyh/M/Dz12ZZL482Q2UxeUyeqsuTk9yZXgv6ijyNrp3dH30xrPS/wHq3ZVwvjzZDZcnju/No0+TJrl4ebRYpTx5yZ30taKZuVeRpSJXDSo+r6ozQ8irSl2QBk6fsmDzlJit5QtupsudwbZPlVaQvyQImT9kxecpNVvIEtVNZz8EwDMPIjyp7DoZhGEZOlN44iMhCEXlDRJ5OlH1URB4WkX+IyG0iMtyVDxCRRa78SRE5MPGZPVz5cyJypYhvF9d8yFCe+0RkmYg84R6jC5BlvIj8SUSWisgSETnHlY8UkbtF5Fn3vHniM+c7HSwTkbmJ8sL1k7E8ldOPiGzh6q8Ukau7tVU5/XjkqaJ+DhaRxU4Pi0VkTqKt7PUTOt2qqAewP7A78HSi7DHgAHd8CvBdd3wmsMgdjwYWAy3u9aPATKKNhe4EOisuz33AjIJ1sw2wuzseBjxDtAf494HzXPl5wGXueDLwJDAQmAQ8D7SWRT8Zy1NF/QwBZgGnA1d3a6uK+kmTp4r6mQ6MccdTgFfy1E/pPQdVfQDovpfiTsAD7vhu4Bh3PBm4133uDaKpXzNEZBtguKo+rNEveQNwVN59r0cW8vRCN4NQ1VdV9W/ueAWwlGjL13nA9a7a9XT91vOAm1R1taq+CDwH7FUW/WQlT+/2ujHNyqOqq1T1QeCDZDtV1U8jecpCD+T5u6rGm6AtAQaJyMC89FN649CAp4Ej3fGn6NpF7klgnoi0icgkYA/33lii3eZiXnZlZaFZeWIWOZf4oiLc/CQiMpHozuYRYCtVfRWiPwCR1wP19wofSwn1s4nyxFRNP42oqn58VFk/xwB/V9XV5KSfqhqHU4AzRWQxkTv2oStfSPTDPA78CHgIWEvgHtUF0qw8ACeo6m7AbPc4sVd7nEBEhgK/Ab6squ+mVa1TpinlhZCBPFBN/TRsok5ZFfSTRmX1IyK7ApcBp8VFdaptsn4qaRxU9V+qeoiq7gH8iijWi6quVdWvqOo0VZ0HdADPEl1gxyWaqLtHdVH0QB5U9RX3vAL4JQWFM0SknejEvlFVb3HFrztXNw5JvOHKG+0VXhr9ZCRPVfXTiKrqpyFV1Y+IjAN+C8xX1eddcS76qaRxiGcWiEgLcCFwjXs9WESGuOODgbWq+k/nmq0QkX2c+zgf+H0xva+lWXlcmGlLV94OHEEUmurtfgvwM2Cpql6eeOtWYIE7XkDXb30rcKyLk04CdgQeLYt+spKnwvqpS4X106idSupHRDqAPwDnq+pf4sq56WdTR7TzfhDdSb8KrCGykJ8DziEa2X8GuJSuxXwTiTK1LgXuAbZNtDOD6AR4Hrg6/kwV5SGahbEYeIpoYOoK3CyZXpZlFpH7+hTwhHscBmxBNJD+rHsemfjMBU4Hy0jMqCiDfrKSp+L6+TfRhImV7vycXHH91MhTVf0Q3TiuStR9Ahidl35shbRhGIZRQyXDSoZhGEa+mHEwDMMwajDjYBiGYdRgxsEwDMOowYyDYRiGUYMZB8PIARE5XUTmN1F/oiQy9RpG0bQV3QHD6GuISJuqXlN0PwxjUzDjYBh1cInQ/kiUCG060QLF+cAuwOXAUOAt4CRVfVVE7iPKfbUfcKuIDANWquoPRGQa0ar3wUSLlE5R1XdEZA+i/FnvAQ/2nnSG4cfCSobRmJ2Aa1V1KvAu0f4aVwGf1CgP1kLg4kT9DlU9QFV/2K2dG4BzXTv/AL7lyhcBX1LVmXkKYRg9wTwHw2jMS9qVw+YXwDeINlm522V4biVKhRJzc/cGRGQEkdG43xVdD/y6TvnPgc7sRTCMnmHGwTAa0z23zApgScqd/qom2pY67RtGabCwkmE0ZoKIxIbgOOCvwKi4TETaXW79hqjqcuAdEZntik4E7lfV/wHLRWSWKz8h++4bRs8xz8EwGrMUWCAiPyHKkHkVcBdwpQsLtRFtwrTE084C4BoRGQy8AJzsyk8GForIe65dwygNlpXVMOrgZivdrqpTCu6KYRSChZUMwzCMGsxzMAzDMGowz8EwDMOowYyDYRiGUYMZB8MwDKMGMw6GYRhGDWYcDMMwjBrMOBiGYRg1/B8LPzmx1+2eBgAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And zooming :" ] }, { "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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pUciO62+lhLOWMgemOQjW2mwI49BGMLdMX1xtaYlrxhz87IRpBlndxIxjHJbzwStPnjkcmEmjYFh4cbLo39Z44+BSe/GANhsvT6cBALPpgme8GuNgUbjMYaUkwoVqDoK1Nh3COLQRTJDujSvQK4jFjYAJ0rrvgcm74xamlxzjkAt2M/CRR2y1yU9QQZqD//8JNAY+YGAu7b1O6Wo0B6uoOYz22s1xur2ERjhzEPdesyGMQxvBBOneuNpS8dYIEaTZKnMpZyCn26+XQxLl+PyGoCgX3q0kHtDW4LH9J93XJ9PeSX2pKuZQdCux1XalCLaoo4Q5CJdmyyCMQxvBM4fWag7BxoGJl/tOLLtjYVnUpkVddhDkp1Y446CKUNaWYMrDHHxuJUeQLpQJbDApdcONmYjb7cZBRCu1D8I4tBFZ3YQmS0iockuzicPcSmxiODCTdsfYJFPyGRZ1dYUg5qBxbiXGHK6/7XH82/bDDRy5AA/euPs1B9etpJeJVrKoe220FcMcRLRSuyCMQxuRLZiIqxIUmbSUOYQJ0rxbiSHUrWRRtwVjEHMIilbK6RaeO7bQwJEL8CiYFIQAg0kVs5kQQbpchjSFJ5NYlggKZrgx6QbkfcyBZYCLYIjmQxiHJuH+54978gCCkC2YSGgylBbnOTA9I8w4ZHV7YumJKaHMweSZQyXjIBVf58qsZAVqg25aUGUJQyktNFopr1dyKxX/1mSp7PbdgILQHNoGYRyagPlMAe//zk7c8/SxsttldBNJTYEqkZZG9jBW4nchsFVm2glfHUypoZqDYVHPCs0PNeABBcpHzwjUBt2woMkShlMxnFyugzlweQ4AEFOlstt3A/zMQYSytg7CODQBLPInXaFEtu1WsplDKzunMcbgX02xVSMrHT6U1EKZg2VRzwptVV/M874WEMpq/w/BHJqFgmlBlQmGUhrmOLcSpbQoSFcsn1G8NposrQDNwfJoDozBdvt5RRHCODQBbDKu5FLJ6gaSmgxVllqaBBcaylrCHLRAzYFSWsIctqzq9WwTFMoKFA2lQONgbqVBn1spb1juNS7H1EyrmAQH2KJ0t0+iBcP0LFrY63yXM6IwdNJNK4xDE8Am4UoulWzBREKVocqt7bnMJo4St5KrOdg33FAy2Dgwu8UbhzPHegAU2zOqAaGsgNAcmomCQaHKEoZTGuYyutuAib9m5e45Sim4SwNNkbre7efPc1gJUViZgoGvPLSvZDE3uZDFKz51P359eK4jxyWMQxPAJuPKzMGy3UqSBIu2LjabD2X9n30zeO1nHkSmYLgTA3N/DaWC3UrsuPiH8IxR2ziM9NhtGUOZQ5lCcAK1QTdt//pQSoNpUTfgIe0xDuHft+lzK8UUuauNA6UUBdOrOawE4/DI3hl8/v492HHQawSOzWehm7Rj9bAqGgdCyHpCyEOEkBcJIc8TQj7kjA8RQn5BCNnr/B7k9vkkIWQfIWQPIeQqbvwiQsgu570vESdDhxASI4Tc5YxvJ4RsbP6ptg5Ft1Il5mC7lZiA26qIJYMLZd11dAFH57M4uVxwJxJW42kgqaJgWiUTDDMOGufbLRqHmPNecdJRPdFK3fuQRg26ozn0xBQAQNq5bnwocqXCex7NQeluQVo3KSj1LlpYRF0ro/9aDXY9Jxe8RoA9p506t2qYgwHgY5TScwBcCuAWQsi5AD4B4AFK6WYADzh/w3nvegDnAbgawFcJIWyW+RqAmwFsdn6udsbfB2COUnomgC8C+GwTzq1tYJNxJTE2qxfdSkDrwu90LpSVZdbmDdOdSDIFA5osoTduu4j87IGFwvLF9c5d24eRHg0XjPcD8DEHmdccBHNoFpjmEFPt75qVX+HdSuWMA6VeVheTJRS6mNkxw+aJVpIlSKS7mcOSwwgnF7yVd5k22Klzq2gcKKWTlNKnnNdLAF4EsA7ANQDudDa7E8C1zutrAHyfUpqnlB4AsA/AxYSQNQD6KKWPU7s4/bd9+7DP+gGAKxir6AawybSSSyWdN5GMycVyEy1nDtQVMnO65T5cFoVnRerXHVg+EZuUAFtr2PGXV+I3L1gLwKc5SCKUtRUomLbmkHCSEZnhZW4liVQSpIuF9wD7enbz9WGLLz5aCeh+RsQWZ8d87iOWj1ToUJhuTZqD4+65EMB2AKsopZOAbUAAjDmbrQNwhNttwhlb57z2j3v2oZQaABYADNdybJ2E7jKH8g/qct5Ab1x16xK16oYuag6WGwKZ003PCkRTJPTEbeOwFMIcYnLp7ZHU7AczPFqpe1emUQPLc0hoXuPAjPlAUivvVlphoaxBzAHo/vNiuUbHfczBdStFlTkwEEJ6APwQwIcppYvlNg0Yo2XGy+3jP4abCSE7CCE7pqenKx1y2+BqDmWYA3ug++KKu9JuVeIOH8o667qVLM+qUZWlUObAKrIGJcHFnVWsN8+huF23Z+BGCbppQVWI+52zKDPmXhpIqGUFaeo3Dl0eysrurZjfOHS50M7cSscWcphNF3DD7dtxYinnXucoaw4ghKiwDcN3KaU/coanHFcRnN8nnPEJAOu53ccBHHPGxwPGPfsQQhQA/QBm/cdBKb2NUrqNUrptdHS0mkNvC9gkX06MZTdAb1xxmUM7jMOc0xbSzxxUWXInHf9qPyhaiSERwBz4DOmCaYkKmU0C0xyKbiVvKHK/E1AQBpMrvAd0fyhrGHOIdbnR4wXp3ccX8cjeGTx/bNHVHCJrHBzf/+0AXqSU/gP31r0AbnJe3wTgHm78eicCaRNs4fkJx/W0RAi51PnMG337sM+6DsCDtIs6oVeTBMdugN646grSrarMyo6nYPg0B59bKe5oCn6jxowWewhZbgNg12PSZAl93Bg/AQHlwyujjLxh4re/+j94bP9Mpw8FQFFzYNeJGYUMxxyq7QQHdP8kWmQOK0tzYHPDfEbHYtbp1lgwkdErZ8G3EtUwh9cCuAHAmwghTzs/bwPwGQBXEkL2ArjS+RuU0ucB3A3gBQA/A3ALpZTNFh8A8E3YIvV+APc547cDGCaE7APwUTiRT63GkdkMvvTA3pLm7bWimmzVonFQOEG6VXkODpMxTDc2Pm+YngdIlUmJ0MlgOd8HYzgDyaIhiKsy/uOW1+B3txXJoerTJro1nPXwyQx+fXge218uIa0dgW7amoOf4eV0E4TYC42yneCoV5Du9kmUVZQN1hy6c0ECFL0KgD0nAfYCgLmVOiVIK5U2oJQ+imBNAACuCNnnVgC3BozvAHB+wHgOwDsrHUuz8frPPQQAuO6icawdSNT9OdUxB+ZWUlvuS2SC8sxSHszu5XTLE2qrKUWhM+s7bn9S3wDHEgDgvLX9nr99xKFrmQPrr3xiKRqtNFmeg9+IZwomkqpckQmYvsJ7mix3NXPIFuxjj5doDt3NiJbzBlKajHTBdBs8ZXWzK/IcViSePFhcHbKLUC94zeHuHUc8HbwYgphDKy46pdSNnuInuZzuZw5FX3bWd/7sfM5e3Yv+hIr//dazy/5Pf9RxtzKHCSeUcDoqxsGwPNoQu05Z3S79Xik01e9WsjWH7jTcAJB2CkamYt41bbczoqWcgSGn8kDGDTow3AKZwji0Gbsmik1pGg2/ZCv12XQeH//Bs/jRU0dLtvEK0q1LguM/kjdSWd30lAn3TDq+82c35WhvDM/8zVvwmjNGajqGKIezmhbFNx95OfAYJ+ZsSj+9VGrcO4GCSaEqvFvJEaSdviCVmIDlz3NQJOgmdWs0dRtYfkeP3zh0eyhrzsBQyq48kMkzzcFyF61R1hxWJHhr3ChzYD5B9sxlC6X1ihZzLJRVdUM/W7EiCDsvf7iqJkuIKRIIKc3sZivUpFbR6+jiQ1dsxh+94QwArTMOLFekETx3dAF/95MX8cjeUtH5aATdSposQZYINFnyhLImVLmiO8WipdFKQOvya1oNZhySsQBBukuNg+Xc08MpmzmwEikZ3SgaB8Ec2gt+1Z4JmMxr+izfxfOvxAF7dcAmZFaXqBWCdBgbWch6u9SpMgEhBHFFDmAOzDh4H8Jy+MiVW3DZZpthtMqt9PEfPIvz/+b+hgIImGsiaDI5yrmVorC6LhiWG9kWV6Wi5qCbSGiKrTmYFjZ+4icu6+Fhd4LzRisBXWwcnPuyhDl0cYjusnM/DiYdt5Lzd44TpFvZGKwcTlnjwK+wG3Yr+S5e0OS4mNPRG1dACGkpcwgqyRFTJCz6jANbRSa0UuPAJtBamAMAt+d0qyqz/vApO8G+kcmNXeug735iLgtCbAM7ny3f8rUdYHkOgB0l5kYrFUwkVMkTtbPzUGlZ55JOcKz3QZdqQum8AULgamUM3aw5sNIZw0xzKBSDDthzGPkM6ZUGfkJv1K3kz1cIYw69TrmKYlXW5q8I/J+ZUGX0JdSSEhls0kmoshsFwpCtgzkAcOPxWz35NOJCYOfqn0xyuonppTy2jNlNjU50WHewLG/DJd6IZ3QDSYc5MLCVp+czfIX3ut2tZEf1KCUBELEu1RxOLObw4e8/DYBjDvkiO+yKDOmVCH5Cb1a0EkOwcdDdKqhunkMLkuD8nzmU0hBXJTffgUFzV6RSyUq/HreS/Vn29q2IiFnIFI+/ERdCWATIzLKtM7zCqTp7YrGzugO7P3kjnvNpDrxxCJpATIuC+PIcgM4InLPpgicIpB5k8iZSsdJ7sls1h/tfmMITTtQk0xxY4luuYArNoVPgJ/TG3Uq+VWiAsfEwhxbWVvJ/5mBKRVyRS9xKHndFwW8c6nMrhZXjaAZemCyW82rEOLhuJd9nzDvGZ8squ29Fp0VpxgCZEY+pMrL+aCXOOARNjhYtzXMI27bV+OYjL+O9t29v6DOWC0ZJGCvQHW6lgzNp/O1/vuDRsvjClv1OoqnLHPgkOOFWai8M03KFrcbdSj7NIWDlvORoDgBamufABGnmTRhMaoirshstxeYK1RHFE2qwIK1IJLDwXjmwlWwrBGneODTysGRCRD4m2LOmRrPpDhsHgzEHdp0k14hndRNJTfaELQdNjv5oJVdz6ECuw0JWx0JWb0joTztuJT+6IZT1v/ecwO2PHsAMd1+xeeJNZ4/hwvUDAIr351Jed6+pcCu1GbpFEVclaLLUuHHw3Zj+pDKAMQevW6kVmgNjMWzVP5TSPII0e7jYKjJIkM4UzJpdSkBrmcNxrktWI5MbO1f/ZMqYw5p+O1O+0XuiUbAJQVU4hsd18kuosqf+f5DOY1reBEVm7LMFE39zz3N4cbJcceXmgi0YGglWCHMrqV3gVmLPOn+cbJ748u9d6NYqY/fn7HKhZN9245Q1DoZpQZHsEhKNJ8H5NQfvjUopxUJWdwvYFZPgWpHnYB8Lm6gZc2CuGPZwMeYQV+USY5YpGDW7lIBiWYNWMAd+sm5E8M6GRCsx5jDcYxvTIAPfTjDj5Q0cMGFZFHnDQkKT8YYtxcrE+YDVJaUUfNkrZhwe2H0Cdz5+CP/v/XtaeAZe5HwtauvBct4oCWMFbOZgWNFO7mPXkzcO7DmJK3JJfbKZNG8cBHNoKwyTQnHq1jSa5+C/eH5js5izE1pW98UBFHsut4Q5WIw52EaACdIMzGercZOO34dfL3NQZAmKRFrituAnlUb8y2ERIPNZ+2HsT6hIBrCpdsOvOTD3HzuuhCpj28YhPPPXbwEQ7GrzN/thbqWfPDsJADh7TW/rTsCHPKeX1It0yKKlG6KwmBbIH2NWN6EpEiSJQJaIJ5udv55Cc2gzdMsuh5zU5OZHK/k+j3V4Wt1vGweXObQkQ9o+Fja5D6Y0T4lj5lZSuWilTMHA9pdPusllmYJZkoVaLex4/OafV5rLjG6IOYRpDhkdMadUhb1g6LRx8DKHmPO9MuPAri9r5RpkkO02oaVuJZbs5y993Urkm8Ac0nkzUJAuainRNQ56IHMwPUUE/ewBAHpjiohWajdstxJpilvJn+fg96tOOv7ytQMOc2ihIM0a7bCKq0NJzdML2nUrcSvSqcU83nXbr/DkQTuRKlMwkFRrdysBdvYqW4U3E1nddMXVoImQUlrSZjEIrLCZfzU2n9Hd0uQJrdTV1m4USgRp+z5lx1XsyBcenkp9eQ7+5k2tqO0VBjcMt4FnLZ030BMSygp0boUE9yljAAAgAElEQVRdDcKMQ4Jj6FqAcVg3mBBupXaD77LVDObAR/b4J5ZJlznYYid74BdzRtNdMIyNJFzNQXUnEsB2MwHFByrO3Zws1j/bAHPYMJzEoZOlpRwaRTpvuIlCQZPAT3ZN4vWfe7BiRdVcGbfSQML+/KSmNOxqbBSlgrRdPqOYg2Ibb0kiUCQS7FbyFd5jQQjF99s36bBVfdD3Or2Ux3e3Hyq7v2lRJ0orWHMAOuebrwbBmoPpeTbVgOjAM8Z6hCDdbugmtWvlV+lWKjdZ6FxYLKvzwotjkws5EAKM9dqVFwmxfYy3/fJlfOre5xs8E9+xWEFuJfsypzQZax0DpXErUgYW0ZSuU3MAgNNHUzgwk67v4MsgUzAx6Kzsg9wHTx2ah25STwRPEMIE6fmM7saaB4X3thtBmoNhUbe6b0IrPrphfR1MSktKdvP7dIQ5BDxrdz15GH/xH8+5DDsI7PkLFKS7gDkw13PepznEOdeeKpOS/Vb1xkX5jHbDsCwojuZQya307MQ8zv3r+/HAi1OB7+smxVhvDH/w2o14xwVrAXhdS8cXshjrjXl8isz988uXmtuSkjEHtiKxBWn79RljPe6DxLuVGFiJDTsDtz630ukjPZhNFzCfaa5ryTYO9so+iG3tmbLDMk9WyE8ol+fAmhpFwa3k1xyY+4G1feWvj7/wHNuX+pLgxnpj+P3XbMR/ffQyKBKB2cYVKdOhghZie08sAwCmymSls37KYUlwQLQFad6ttO/EEm761hOYy+ge5u7XHPoTqn1thVupvdBNCkUijguh/ESw+/gSAODeZ44Fvm9YFjRFwt+84zxc4JRf4CeXyYWc61Ly4+h8tipfebVgk97V56/GH73hDIz1xtzVyaaRlNv6k8+QZmCr0kzBCIwnrwabRlIA0HT2kCkYGEzZk3fQCnGPc41OLpc3SrmQPIeFbFFzaEaQQqMohrLakzsraugaB95XzTGHwycz2PwX9+Fv//OFEkFakgg+9Vvn4cyxXsgSiQxz2OcYhxMBTbIYWKn2wPIZZXSXqIB3K+08NIeHX5rGnuNLHkHarzmM9GjQZALdtBpuZVwPTlnjYJjFLluHZzP4o+/sDF0tMhdLmD/bcAwNUFyJ55wbNZ03MDGXxVonUikITx0urahZL1go6+axXnzirWeDEALTubHGBxOuO4n5Nz1uJYc5pAteoawWbBptlXHgmUNpXaQZxyicTJc3Di5zCBCkWR5KJNxKhpc5jDpVOw85PYZ5t19Mkd3JZ2Lefv/2Rw+UdILjociSy17bAXbN/N+rZVHsn3aMQxm9iLmVAjOknXv53d/4FXYfb19iXy0wuCQ49l0sZHXPc+ZnDsM9treBUrT1WjGcusbBsvMc2EP2s+eP49mJ+cBtWRhlmHHQTctdkbPIIGZorvjCwzgwk8b4YDBziCkSdhxsnnFgN5HC+S+ZH358MOkeJ1ul8H7opZwBw7RQMKzAh7AarB9MQpZIU42DZVFkCiYGQozDSw5rAICTy+XdSkGaQ87JH2CfHwW3Epvs2fUZH0wCKJbmZoEFbBu2avYfd4ht6Bhz8DOyo/NZ1+X04O4TuOH27YHaAyttXc6ttJQz8M8P7GvqcTcLrlvJtDxubI/moHgv1mhPzF3EdUKUPmWNg+1WkjwrsN3cJMOD+eKnQyYew6KekEPAfhhMi+L4Yg4bh5N4v9MlzY8Nw0kcnW9edA+7iViiHVBcZZ451uMyHNZwiK/WupTT3VDPegVpTZEw2hML7KNdL5h+M+ATpPdOLeGjdz2Nz96/B5osoS+uVGQOuQDNgQnxrIRBFNxKfs1h/ZBtHJ46NIe+uOJW8QRsQx+WRyCTEOYgkbZFK1FKi8zBF9jBXEqAbRwe2TuDG29/okRXYv291wQwcD5E93SHuXYK9zx9FNff9njJOK858Hk65ZjDpacPuWOdcJmdssbBdisRj58vjJIyf+d8Rg8UQ1kpDqB4sbO66a4Q3n3xaRjpiXn2OXt1L/6vV41DkZpL75kgzTOHj199Nv753RfiNzYOlQjS/A25mNPdlWe9biWg+SWUeTHSFl/tvx/cfQI/+vVRPHNkHv90/VZsHEnhR08dxcZP/CTQf00pLeY5cMyBXd8+pzBiQlOQ1c2OlmPQDcfIO9exP6GiP6HCsChOH+3xdnhTJW7y9TGHEOrQLuYws5zHr48UGbnfeDGGyaoHALZAfd+u4zjiuHvTeQOHT2YgSwTrAhg4H6Lrz+VoN3YemsOvXp4tuXf0ALcSAE/1AvYsXn7WKH58y2vx3ks3dFRsr893sAJgu5UkTMwVKeyLk8HMYZlrlHNkNoMzx7xlBwpmKXPIFrhSBwET7c8+fBkA4JovP9pUyshCWRVuUuiJKXjHK9c6416j8M6LxiETgp/smsTMct59eOt1K9mfTZp6M7slxJ0eBnlf5Mtjn3gT1g4kcPeOI+4+R+ezGOvzrjJ1k7qGOKjXNouhZ9eQ1TDqBFy3Eme81w8lsHBUL1kd81VJ076VuVSWObTeOHz5wX2468nidfFrDoy5bl7Vg+OLObz9FWvw/LEFfHf7IXz94f3YfXwJN05swOHZDNYOxAOziD05Rh3WihgL9d87vFuJX2DyASEat2Db6lRp1dzGYBFkDoSQbxFCThBCnuPGPkUIOUoIedr5eRv33icJIfsIIXsIIVdx4xcRQnY5732JOEsfQkiMEHKXM76dELKxuacYDN20oEoEm536/a89cxgvTS0Frhb5pvZHZkv9oUzcBooX+993TrironiZMgWKLDW1AF+ROQRfWmbE2PEqsoTf/Y31GEiqmF7K42N3252p1g8FayTVQFNkFIzmTTyuwYrJHvE1q5uIqxLWDtjHOpQqsrOg/85PHPzDxjSllPMwM5daJxPh/G4lwNZzgGJZcQY+lJV9V2xtEHIbtI05HF/Ieb53P7NJ5w0k1GL+zblr+/CeSzbgyYNzrpvXtCgOzWawYSjYZcTbP39Xw3aDFXD0h8ez65k3LE95GU8SnO/Z5F9H0jgAuAPA1QHjX6SUbnV+fgoAhJBzAVwP4Dxnn68SQtjZfw3AzQA2Oz/sM98HYI5SeiaALwL4bJ3nUhNY4b0/eO0mPPLxy/GbF6xFpmC6dWd4LHHGIWhlwlgIULzY/+eZY/jQ935tj5VZfcoSaajpz907juCdX3+seCxmqSDNw63V46PfvXEFJ5byeOrwPD79W+fhog1DdR9Ts5qvZAsmphZznuZDMUXCicUcHtk7XVLff8gJdQWCy4bzE5POGS+XOcSYW8m+Xv/x66NlwytbgaWcjq8/vB/fe+IwAG/W7GmO7sDChRliPkFaIsW2k2HMQW5TnsOsTwNi3/Uje6fxx9/diaWc3cBnrM827Gev7sUNr97gNl0CbOZ++GTa1V382DzWg1t/+/xIRJkx4+A/Dq9bqfheQi3VHPhkuEgbB0rpLwHMVvl51wD4PqU0Tyk9AGAfgIsJIWsA9FFKH6d2wO63AVzL7XOn8/oHAK4g/iaxLQBLgpMlgvVDSbcRT5AQuZwzXDE0aNJhLATwupDYyszfEJ2HKje2gnvmyDyePDjnTg6sVAcvSPNg58HCNhlYrwkAePsFa+o+HsCmws3I6vzCz/fg7V96xA2xTWq2W+m/XjyBm771BE4uFzzfN98n2x/RtJjT3ZaMgH3NFjI6Lv37B/DIXjsRkTEHdr3+7icv4t+cSbpd+Pbjh/CZ+3aDgOB3t427xwQApw3bk+OZY17mwLMpVrmURfWEG4f2ZEj7kxKZ5nPD7U/gp7uOY3Ihh964gg3DKcgSwfnr+hFXZXz1Pa/CxRvtBcrkQg5zGR0bhoONAyEE77lkA0Z7Yy3pJVIL2L0axhzKag5Kkc27Y3Lnigo2ojl8kBByI4AdAD5GKZ0DsA7Ar7htJpwx3XntH4fz+wgAUEoNQsgCgGEAzU0d9kE3qTuhA+Ut9HLewEhPDPMZPbDiKGMhgNcQ9CdUnFjKe24APxRJgmHW775gN+N8toCdB+fwrf85gDefMxb6Py/bPIr7PvT6klUYM46aInkiYeqBpkhNqcy68/AcZpYLePKAPaknNcX1L1sUmFrKeaKqNgwXV9R8RMj+6WW87Z8ecR+wpGZPppOLWRxfzGHnIefznQmV/0z/yrfVWMza1WHv/8hlJe9du3UdemIKNo+VupV45pDUZPcc5LA8B4nAakNi1VzG2542WzA8Wsex+SxSMRnXbF2LC08bwCpHJzpzrBf/3w0X4cK//YXbBXBDCHNgYD0vOomiW8lCtmDi8GwGZ63u5TQH02M4EiGagzumMM2he0JZvwbgDABbAUwC+IIzHnQn0jLj5fYpASHkZkLIDkLIjunp6dqO2Aed0wmAIpULWk0t5wyM9JSWbigYFv76nudwfDHnWnt+YpnLsFIHZTSHBn2/TACbS+t4aM8JDKc0fPU9FyGMfEkSwTlr+krGGXMY7YmF7lstmtG20bQodjsBAv/llC2xNYfiNTuxmPcUYvtfr9+Ef7p+KwDvdTownUbesFxGdPpoCrppuSyRsS2XOXiuoXdyazX8xdh4pGIKrtm6ruT6+ENZk5rs1iDqZJ6DaVH3GQBsI5bVTTx/bMEdOzafRU9MgSpLJVoKYz+svAbTlsIQj0AfDtc4GCa+u/0Q3vHlR5HTzcAkOKCY+Q4U5yCNcyuxSKxIupWCQCmdopSalFILwDcAXOy8NQFgPbfpOIBjzvh4wLhnH0KIAqAfIW4sSultlNJtlNJto6OjQZtUDXu1X53ws5w3MOyEovIr4ueOLeDbj9vVJBkLiasyvv7eizDWG3NXnWEPO2BrA41oDizaYzZdwJ6pZZy9prfm3s9AMYyT+X4bgSpLDd/MB2bS7oP+0pQ9OSQ02dODYHop7zHGiixhm+OK4JkD+47+9C1nYf/fvw1b1w9AN6mb88DyV/zRSgAw12bmkNXNsouJIMTUojHOFEwkNMVlQaEZ0m3Ic1jI6uDJyVBSQ6Zg4kdPHXXH0gUzsJgeYBuTmCJhwskKH6rAaBOq1FHjkNNN9zrkCiaOzedQMCzMpgue8hmePIcAzUEJWLR2ovheXcbB0RAYfhsAi2S6F8D1TgTSJtjC8xOU0kkAS4SQSx094UYA93D73OS8vg7Ag7QNhUR0y/IIP4oUbhyWcjpGnBuTp4S7udBXnoVcff5qjA8m3Abw5Y2DVNIPohYw5jCbLmDv1BI2jzXW3YtVjm0EzchzYK6E15wx7I6lOLcSYIcF+ks4M2bBFz5kWkRfXIEsEdt4GUXmQKm9+mafzX/mXJMLCFZCTrfKuiGDwDO1TMFASpNdFhSWBNdoIEQ1mPXpDQNJFROzWdzx2EFceNqAOx6U9czQEysmNjK9LAwJVUa+g8aBPYuAff+x4pOz6YI3QzoklDUo90jtYJ5DNaGs3wPwOICzCCEThJD3AficE5b6LIDLAXwEACilzwO4G8ALAH4G4BZKKfsmPgDgm7BF6v0A7nPGbwcwTAjZB+CjAD7RrJMLg2lRUFo0CEC4b49SiuW8gT5WIZGb9PikOX/oKH/Dl4uVryXePKebnoxmoKg57Dq6gEzBxFmr6zMOTKC+9PThCltWhu3maNA4HFuEKhP83bXnu2MJVS6JsvJncrtdwXjm4Dy0zHWmyXY0Fb/K5PtX8J85HyG3Uhj8oawJTa7YA1yRW5/n4C+COJTSUDAtbB7rweevu8AdD2MOANDjMFpFImW3A5yyJx00Dgu8cdAtzDrGYT6je6OVPKGs/BxUGq3UyaKCFQVpSum7A4ZvL7P9rQBuDRjfAeD8gPEcgHdWOo5mQndzAUqZg791Z1Y3YVH7Bo4pUhnm4F2h8RNMec1BqnoF9/n792DHwVnc88HXuWNs4tt+4CQAYMuq+ozDG7aM4gd/9GpctGGwrv15aErjbqWTy3mM9MRw+mgPLtsyil++NA3JWfXz8BuHOFe+hGEpbyCuSp7scN20POIlHxLLT87tZg7ZOoxDTLF7PVgWRbZgYlVfzK1eGha9Y0crtXYi9X9344MJaIqEf/69Cz0JimWNg/PeQFKrqIXFlc4aB37hltNNV6+azRQ8eQ7hoazheQ4iQ7pNYEJcNfHELDu6J64grsruhaWU4kWeOUj+SYufbMIJmuqU5K0GU4s5HOPKe+d0010x/vqwXaKAjw+vBYQQ11/fKJqR55AzLHeSvOP3f8N96P3lS/wrZMVp1M4zl6Wc7gnVVWUJFvUmN/JGhp+sMgWzrtV8vcjX41biXA8Z3c79YN9LOiR6px0Z0swdxIIu/u83bcaH37wFawcSsCwKQmyXXjnjwBj4YAWXEuAI0h1MgvMzB6ZXzXPGoVA2CY5pDsV5yc3Wb0Ff9ko4JWsruVnEUoDw41vFswQ4xhzYRTq+mMNSznCFXD/4yaZchrRcw0NqmNS7Is55Q2BPG0p6JsFOgfn0G0G2UJyQJYm4kwQ/oQOlzIEQ4jHiALCY9V4nVv2Sf5iTPjfg3e9/Nf78bWcDaK9rKWfU51YCbIOYydtuJdZrOSzLux3RSmxyZGHTfQnVjTiSJII+514tpzn0usahcng167PdKSxmvcmycx7NwXErmXa00uq+OCQCDPcUz4sZB75kClsodIIRnZLGwa1cWgNz6HWYAxOTWPjjK50aKP5kH3bDxxQpNGKE/d9qmYNhWYFROAznrysNUe0EmsEc8oYZuIJezvuYQ0Dzl5gvz2LRxxzYw8cbh5TPyFy8acgtV9FO11LO1zqyGjCd5Y++sxMn0wUnz8FhDvlyzKE1q9Hdxxfxy5emcTJdQE9MwagT6ee/nn0J+xh7QhZY/Hv9VTAHliHdicY4gPd+SucNd/E2my64C0CWIX31+avx4MfeiDVcE7CgPAdWXaETRu+UNA6slhEvIjMq5/f/7zpqx2SvG0g6Td7tfWec3g4sZ8Df64HRwUqrwFryHHSTomBa7o3GR0cAwHlr+6v6nFZDkyXoJm2oqmnYJLmc955zMuD7LWEOOcMtxw0UHz7euAatXll/h3Yah6xee6Mlxhwef9nWnewMafsz0vn2M4er//ER3PitJzCfsbvr9SVUEFLa6Ywxh2o0h2rcSglNhmnRjiSMAV7jMMm5f09w7U+ZIB1XZWz0lUFhi9Ugt5IwDm2CW38oKEPat5q69+lj2DzWgy2rehBTipMOi40/b61tHPxlN9jDWSlmXa6hfAZjGOxGWfS5lV6xLiLGQQn+LmtB2CTJmBxbhQZF5fiZg605cG4lZhzKMAcAblvSuXQb3Up1aA5BEVyXnz2GnpiCG1+9MXCfdmgO85kCBpMaBpIqYopUIiizCLlKoaxAdW4lNxghoKx+O7CU05FQZSRU2dOw6MQSpxMaJgqmFVhaXFVKmYMqS1AkItxK7UJQxUvXOHC+8qPzWTxxcBbXbF3r+LKLkw5jCledtxo3X3a6J+QSsHsC2L/LGwdVkkoipMLAjJprHEqYQ0TcSk0IvwubJC/ZZIfaMpdPkFupoubgrMx4H3EyYIIa6gBzyOmmJ9GvGvhX5ElNxlhvHM99+iq8Yjx4wSDXECVXC3gX6dRiHgNJFReeNoBXnVYaBVcLcxioUnMAig2d2o1MwUQqJiOuSpictw1CXJU87U+Li5vSaxxUeI9t2wmh/ZSOVvKEsgaUz9jhFGp709mrANjCMhMnp5fyGEppiKsy/vxt55T8D7YSrdR8RJEJLGq3wiynTQDFlTjrT83cIl9/70V4YXLRzeLuNNjNXY9xWMzpyOTNULfSF9+1FX86n8Vf/ngX9p4I7lgX8+WjLOV0dyICisymnOYAFCekmQqtR5uJeiKj/KvKSjkOQOuYw+HZjOf16aMpvOeSDXjPJRtKtnU1hyryHKqKVuqgeAsUgyhMi7rMYdNID/Y75T8IKQaRBM0LQZoD4BiHDpzTKWkc2KTlSYILiCfeO7UMWSI4Y8z2DfIdt6aX8q7QFoRklcyBubYMi0KrYBzYSo/F57Mb7bItI7j6/NVl920nNIXVg6l98vnC/Xvwq5dn7Uky4LtLaDLOHOtBT4y19AxwK3FRK3nDDvcNdCtxmkPQ52iKhM1jPW7f5laD+ctrLZ/BugwyQbaaAAepRZrDy9PF3uHLeaNsVjNzK5UTpFN1MIdOGQdW10o3qas5nD6awotOtn9KU9xou1gAK3ZDWX1h8QlN6kjm9ynpVmIPhabwSXClgvTeE0vYOJx0aX5cKU46M8t5jPSG37BsRVvpQWeieDUNf0o0h6wORSI1Tyathht3XwdzOJkuYGopZ7uVyrhX2GRfiTm4pTMCBOmFrO6ynFSAewoAXrd5BE8enG2LIMj+R62aw2VbRvHo/74cn3jr2VXv06popZenlz1/DyTCnxHXrVSG6fTWmOcAlDYUahdsnUzxML8zONGZv1eDXIdu4T3Fu0jsVJ+KU9M4BOQ5yBIBIV6f6d6pZU+tohivOSyXZw5ssqkmWgkIrgZbctzONv4KnG1of1ETXLdSHeGsBcPCcs5wHrTw25O5IoKMQ1yV3etULJ1RqjlkCibGeuPO5wRPUK87cwQ53cJ/75nGJX//X24TnlagaBxqN/bjg0nccOkG/OO7tuK6i8Yrbt+qaCWeOQDl6yG945Vr8fGrz3LdS0G45PRh/O628VDthEenmUO2YCKhSq5xH0iqWM2FqvLus6AFQJAgbW8rjEPboAd0SyOEQJUk972cbuLgybQn45hFK1FKbbdSmSJ1QRU+gxDEWMJguMyhmIqv1ShetgOxBpiDblowLLvXcznm0OMyh+BoJWZAi0X3SvMcAOCs1b14zRnDoWVDLjl9GJoi4cN3/RpTi3n8dNdkzedULdye43UyQUkiuPbCdaEtYnkoEmko1DgM08t5j0HwN5XisXEkhT9+45llFzdDKQ2fu+6VVekonQz7BICMbjdaYvft+GDC052Qj8oKYg6shEtQSZhOsKFT0jgwF47fQqsycSfgAzNpWBTYzNUqiqsy8rqF5byBnG5VMA5VMgfmVqpila37opV00/LUfo8K+HIOtYLfp9x3V445xBTZTRb82fPHAcAj1vOtNweTGv7tf10a2OOC/Z9v3rjN7XEc1qqyGWBGP8gf3WzUEkJdCxayuqfpUjVaQbOQcN1KnSmhwYoesuMYH0h6zt/rViq9xts2DOLr770IF673LlQSquwGobQTp6ZxCMhzAJzy2c7kdOikTY/5fr0xJ/OXhbEOpyozh0r+43JNhvxgx8ZWmAXDqqt3Q6vRSN9bvrdzud7bv3nBGvzZVWcFrkzjqs0cdhycxdf+ez+uu2gcF3A5IPyioJzriuGyLaN48E/fiLX98ZbW1W/ErVQrWhWtNJ8pYN1A3H22KpXZbiY6zRxyBdNTOdhmDkXj4HUrlV5jSSK4+vzVJVGLCVXuSHhu9GaWNiAoz8H+m0B3HhgWbcB3n2IXlMUtl7vxq06Cc6vBVq85sBWmv5tdVNBInkOeZw5lDN+G4RRuuTzYJcGYwz4nhPAjV27xPHC8W6kadwWD2oRqs+XQTuPAekg3u9TEQtZAf0Jzn42BMm6lZiPe6Wgl3dYAWbHD8cGEJ3mPr6NUKcSdR6dKkUdvZmkDgvIcAG/BuOMLOWiK5ImSYCyAMYdyRe7iir2CKOdztf+nU/CvjmilyDKHBjQHfp96J8m4KiFnmDi2kAMhpQ2MTuMa1dfyP1RZaklphtl0AbsmFlyj347oM7aybyZ5oJRiIVtAf0J17/tqaiI1C+z5bDdzmFnO4zmnn0pCk93SOuODSc8C8spzi+HmtbgO7eRbYRzaAj0gWglwWnZyzGFNf9yzMmUiUtE4hK86JYngrve/OrR8gfs/nWOohuL7M6QLUWcO9biVuH3qnSRjih1rfnQui9GeWMl31BNTcJqjHQRpFmFQ5cYLCgbhCz/fg3fd9jjSBW9pkFZCdqPkmnc+do4FxUBSdX3tlRZHzYTLHNrsgvnKQ/tww+3bUTAsJFTZLcI5PpSAKkvuPMEvUmp5bkW0UhthBFRltf8uPvzHF3JYzTUkATjmsFzZOADA1vUDFVdO7CGtxl3BHmSPIB1B5tBItFKzmANg60ZrQprSs6ZI5VxXfmg19N6oBTsPzSFTMPHScbt5VLs0B6C6RUm1YNUD+hMqBpMqkr6e362GKktQ5fbXIZpZLriNffjFxjrn3mOuJUUm+Nf3XYILxvvdAIdq0KlS5NGbWdqAoKqsgLfO0eRiFmv6/cbBvvAzVbiVqoUaUg3WD0opF61UbBzir6sTBTQiSHuNQ33nxozTwZMZrPEZeIazVtshytM1lMaopbx6tVjOG3hpyjYKzzoVgNvhVpJryK+pFqwcyYDTt2FtiGFuJdq5ymbdBPkaZwlNwbf/8BJ88q1nu/PDoCNKa7KE120ewb0ffF1NlXcTqs2Eq63B1iyckuUz3H4OvqgAVSFuqemphbwngQUoTjpsQqnU07YaFDOkyz+k/PtF5kBL2E8U0EiGtF5lKGs5uEZ8OY/V/cHG4fKzxvCVh/a7Bfyqga1JNVdzeHZi3vX775qwjUM7Qlld5tBEDcVlDkkVf3rVWaHlwluJRlfZuyYW3BItlfD5+/fgsf0z3ug3VcZZq3s9vdyZbllN/kkQitVmLfS0cTF4ShoHN0Pa90Urkr0ynM0UUDCtUOYwvZRHT0xxV1+NoJgEV34i5ZkFK0kcVUG6oTyHJriV+MnVfw0Ztm0cwsN/9sbajIMiIZttbvlu1t51MKni+CKr5NkG5lDloqQWMObQn1DRF1c9iYftQkJrLGHsHV9+FABw8DNvr7jt04fnsf9EGmsHivdYkIbFqvvWu5Djy4I0Y0FaLaI3s7QBYdFKmmyXMT7uhLH6V50uc1jKh7YHrRXV+n75aKaoh7KqzQplrXMFzU9KYcwBsMNhK1XC5dEKzWHv1BLW9sex1ekoCJRvK9sstEJzWMjapc3bmSu5xO8AACAASURBVPjmR4IrndJqvDyTRlY3Pc18gtxFvFupHnQqfyN6M0sbwIyDGhCtpJuW6wNe5/OZsgt/Ml1oWq9mxl70Sm4ljjlkuWilKDKHWB3M4f7nj+Nff3WoKdFKr9886q7g1tQg/FVCKzSHI3NZrB9K4hXjtnHoiSltcRW2IlqJZw6dQrs0h6Wc7pZyX+LcZ0H3bKNupU7VjDol3UpsteR3CymyhHTBxI+fPoZ1Awmc6yupwKKXTItWjFSqFtW7lYrv5/k8hwgzh1r88+//zs6SsXrdK5oi4eE/uxz/tv2wZ0XeKFqR53BkNoM3bBnFBy8/E2/YMoqBpNqWQooyaU20kiKRwN4Y7UJclZoyiVbqr3JwJhM4HuRWuvLc1XbjozqNZqfyNyrOLISQbxFCThBCnuPGhgghvyCE7HV+D3LvfZIQso8QsocQchU3fhEhZJfz3peI8wQQQmKEkLuc8e2EkI3NPcVShJXP0GSCo3NZPLp3Gr994bqSm8Nu7mN/ZU0zDlWWz9A9gnS03UqyRCBLBAWzupv5xGIucLwR3/tobwwfevPmpjIrVZYa6m7nR043cWIpj/VDSWiKhIs2DOKM0cpCaDNQ7X1XC+azOvoT7TFuYWhW2Oe8w4I+c99ufOHne0ref3lmuWQMCDYOZ63uxd9ee35NLkweiQ7lb1Tz5NwB4Grf2CcAPEAp3QzgAedvEELOBXA9gPOcfb5KCGHf1tcA3Axgs/PDPvN9AOYopWcC+CKAz9Z7MtXCtCwQgpKLpUgSZpbzsCjwlvNWlexHCMG4I2A2y63EJvdKoax8TZ+oZ0gDtn+12on00X0zgfs3Q/BvJjSluZrDxJzdLWz9UPtDPuWWaA56WzOig9CoIM3wzJF5HF/I4esP78c/P7iv5P0DM+mAvVoTTOAK0lFjDpTSXwKY9Q1fA+BO5/WdAK7lxr9PKc1TSg8A2AfgYkLIGgB9lNLHqV3M5du+fdhn/QDAFaTFSw/DoiWsAfBW6wyruMp0iGYxh2p9v/z7WU8oazSNgyqTql0wj+0/WTLWjnDOWtEMzWE5b7gZ9kfmbNdELRFTzUItpeKrxUJG76jeADRPc/iDO57EB//tqdD3D53MBEYO1VKrq1ow5vD7//IkXji22PTPD0O9T+AqSukkADi/x5zxdQCOcNtNOGPrnNf+cc8+lFIDwAKA4TqPqyqYFg1clfJ5D2FheOsGmXFoEnOosvAem2glYjMHSmlkBWnAbhWar5I5TPncShKpraxFu9AMzeEz972IP7jjCQDAhNNvuZVlwMPACj5aTSy8t5DV21poLwiNuJX8RQh3lGkPe3g2g3PX9IFNGczd3Ir7dhWXyPn0kfmmf34Ymj2zBK34aZnxcvuUfjghNxNCdhBCdkxPT9d5iPZE66+rBBRdPLJEQi/yuGMcynWvqgVF3291eQ49MQU53XInqSj2cwCchjtVPqT+ZKk/fuOZ+MzvXNCKw2oIzaitNLWYx5QT+vjyTBqaIpXtKNgq1NKBsFrMO0X3OolGQlnLXVu/4Tgym8Fpw8V+DRuGUiCktmqr1WIopeGpv7oSAJAptC+xsN4zmXJcRXB+n3DGJwCs57YbB3DMGR8PGPfsQwhRAPSj1I0FAKCU3kYp3UYp3TY6OlrnoduaQxBzYBN1X1wJFdWKbqUmhbK6tZWqy3MY6YlhIau77o2oMoe+hIrFXHUJY8s+43Du2j5cfvZYyNadA8tzKFfm+vljC9jrhEIHIVMwkCuYWMjq+OHOCVy2eaRuobIRFDWHJoayZvSO5jgAxfLW9ZQiL/cM5n2a34mlPNZzVVc3jaSQ0sLnjUbBXFjtFKXrnVnuBXCT8/omAPdw49c7EUibYAvPTziupyVCyKWOnnCjbx/2WdcBeJA2u8i8D4YVXHaCMYe+MqsfJkg3LQlOrq4qK2MOq/vjWM4bbvvLqGoO/QkFi9nqVjnLOcNjrKN6TqosgdLy1+ovf/wc/p//fCH0/UzBREY38a+/OoTFnIEPv3lLKw61IpqtOZgWxWLOKPvstANxVYZp0brcf/4ACr7cNr/QOTpfDCRg2c8fuXIL/vFdW+s55KqgKRIUqb1FBasJZf0egMcBnEUImSCEvA/AZwBcSQjZC+BK529QSp8HcDeAFwD8DMAtlFJ2Nh8A8E3YIvV+APc547cDGCaE7APwUTiRT61EqObgMofwG/yV4/346JVb8MazmrOyZWylktDJ3me5FpML9g0a1Ym0L666SVGVsJw3PK6VqLIhFrBQbuJZzOqu4ByEbMGEaVG8MLmI9UMJnM91qGsnmh2ttJQrFt3rJBpp+MMbh/PW9uHarevcMttsMQbYLiXA1ooGUxo0WcKWVT1487mlEY7NREKTkWkjc6i4/KWUvjvkrStCtr8VwK0B4zsAnB8wngPwzkrH0UzY0UqlE5DiMofwr0WRJfzJFZubdizV+n5d49DPjIMt4kZ1Iu1PVGccKKVYzhvYMJxyawtFsZggwJUFMS0kEKxJ5Zwe42FgD/fMUt5tKN8J1Jvn8LG7n8FIr4ZPvvUczzgrutfOtqBB4EtN1Kp/sGfs89ddgN951ThkieCyLSP4wzt2eI2DE4I8PpjA2v44RntjbcntSKjNCdOtFqdshnQwc3CMQxsLhlXb7Id3KwHAMYfaRjFDGqjeOOR0Cxb1hg63QtRrBrQqWF5WN7GU00EpDZwwmHE4me6seCvX0GSKxzMT8xhOleoKUSidARR7gtcziTJdIabK7vzAtMUlzq00MZeBJktY1RvHh968BTdUaOjVLCQ1GZkouZVWIkLzHJyxVsQqh6EoSFeX58DC2o53AXPI6mbFRLilvP3QedxKcvTCWIHq+lRkCgZ0k4ayh6wTbTKznO9ouG690UrZgonFXOm5sYziqDCHRtxKfAQgy2fimcPkfA5rBuKQJIKhlFZVee9mIKEpXSFIdzXCopWYT5mtPtoBSSKQSPV5DkXNgblgonkJmTBZKWIpnbdvdp45qEq03UphNaMsi7phlHPp0vOmlLorv/mM3lG3Ur3RSpmC4WluwxAV5tCI5hAUAciYA3/OSzm9I+XIk5qMrB79UNauhmEGu5VYjFQ7mQNg6xiVm/3YN25fQkVClTlBOpoTKZskKrmWlp0VGW8couoqUytUm+XDHVkfYf/7fBxeMtZ9zCHj63zGsJCxy3X3JzocytpAeWt2XXnmGsQc0nkTqQ5cu2SbBeloPoUthmHRkl4OQHG10Y42jTxUiVSsyup2r5MJhnu0rhCkgSqMQ77UOESVDVXSHPgEpTlnsvS+732wo8EcqjcOpkWRNyws5Y2S/fj+0Z0EK6tfi3GYWc5jOW+4biV+wdWjKSDEqzks5Y22Nt1hiLdZkI7mU9hiGBZ1BTkezB9cS3/XZkCWSNXRSqosYaQnVjQOEZ1IXbdSHcYhqoJ0Jc2Bd2WcXA4yDl6XQCeZg1xHngN//MvcSno5b+DQbAZJTe74YsV1KxWqd5e995vb8fmf7S4yB+4cJImgJ6Z4dJZ03kCqA8YhqbWvPzZwykYrWSX9o4Hiw91uoVCVparLZygSwUhPkbp3+mEMQ7XMgZXOGE5pIMR27UX1nCoZB361GsQc/Ku+bmMO/PEv5ooVWD9619P4+QtTzT3AOlGPIH1kNoMNw8miIO27//riqs+t1DnjINxKLUaY5sC++Ha7lRSZVCFIF/teD6ei74JhuSKVmAProtUTV9zvParnVGx/Gnyt+Af3ZLoKt1IHJhgGFkJdi+bAHz9v9FnJ9dV94S1Z24Uic6hOuM3pJtIFE5mCyUUree+/3rjicSstd8itlFBFtFLLYYZoDpdusovBnre2vVmrilSNIF3UHMb6op9NXCtz6IkpLmOL6jlpSnnNgX9w5zjj8IWf78H1tz0eoDl03q1US7QSf/y80e+NK3j95hF87+ZLm3eAdYIJxdWusBnDS+eN0HplvXHFjbozTAt5w+qMcdAkZApGXXWj6sEp6VYyLIpkgObwzm3juOKcMQy3uUqmzRyqaxOqSBLGuBVaVDWHmCIjrkqBMfE8lnMGJGKzNbbqC8pBiQJq0RxmOePAmsW8Yp3X9ZLsKHOoPVqJD6Nkk6VlUZxcLuCCi/qxaSTV3IOsA3FFBiFAukrjwK5TOm+GupXWDSTw6L4ZWBZ1Q68741ZSYFE76q0VTYX8iObM0mKYIUlwhJC2GwbAflD1ioI0xxy6ILIHcLKkM5UF6VTMrmbJBM1Otpksh4rGoVDM2ZjhBOmNw3axxm88csCzfUeZg1y75sAmRgBuUcX5rA7DohjpwHMTBEkiSKoyMmVKmPBg+SjpguEK0v5n6vWbRzGzXMALk4tYLjCm2/5r10iYbj2I7szSQhgh5TM6BUWSYFahOSgSASHE0/wjqi4YwM7mPubkY4RhOW+g11mFJVQ5skwI4GsrBV8rxhxOG0p6iu+FiaPtzqfhodQhSGd8gjRgh4EC4Z0TO4FUTEG6Ss1h1nEreTQH3zP1+i0jAICHX5p2o7Q6JUgD1bvMGkV0n8QWwrSsSLkukjG5bLE2wJub4WUO0TkPPzYOp3DwZHCvXQY+8iOudj4Ushw0N0O6vFtpw1AS08t51zc8n9HB325sYdKJRCqGmFL7RMO7lRayOibmMnj6sN2ZLCrMAXCMQ75Kt5Jj3NJ5g0uC896DY71xnLumD4/unXGf004Yh4QwDq1H1JjDcCoWGN3CQzctt6WoJ5s4wpPpxpEUjs5lkTfCb+aT6QIGnZr4SS3izKFKQXr9kB0WeXQ+i6nFHPKGhVeuH3C3G0qx8+1sKGtPTPGEaFaCX5B+3Wcfwsd/+CyAaDEHO+SzWuZgM6C8YSHnnF/QPXjBeD9emlryBFC0G26YrjAOrYNhBmsOncJIj+bS8zAYZpE58D5RNUBYjwpOH0nBosX690GYXMhizYDtJktocmTrKgHVaw6nOT2hb7j9Cbz3m9sBAFs54zDo5Ad0kjkAdsOq+WwBV//jL/F73/iVR0QPAju/gaRaEmgQKeagKRWZOAMfVTaf1aFIJLAz36aRFE6mC27Zmk7kqLDFRLsS4U7JaCUzJEO6UxjpiWE2XYBl0dCWkYZluf0meHSixWS12OhErxyYyeDMsd6S9y2LYmoh75Yhf+8lGzAxX16j6CQqaQ4Z3YQiEdfYHZgputQuGC+GRyech7yTzAGws9iPzWex+7jd1vTOxw7iI1eGd6ZjzGF1X7wkRLlZnRGbgWRMrmjoGPjt5jJ6KBM/fdSuvLrr6AKADjEH163UnuJ70bmibYRhWZHy1Q/3aDAtioWsjsGAWvmAHa0UlNUdZWwaZsZhGUBpl6zZTAEF08IaR2B/zZkj7Ty8mqFVwRwSmuzRhBhW9yXc1wnV/pxORisBtnE4dLLI6ipNqOmCAU2WMNobw0kf041ShFkqppRlqzw8xiFdCI3+Y2G6u44uArCTNtsN4VZqA8Ka/XQKLHw2qJInQ043A5lDlNGfVDGU0nBgJvhBZT0pVvcnAt+PGtiCIkyQzukmEqqM0Z7STGG+z0FSUxBTpI5fz7646tboAooJiWFgxm+0J+ZhRVFDqoYyE3OZgntd57OFUOZw2lASEgGec5hDp6qyAu0TpE9R5hAxzcFhC9NLBZwZ0Jr64Ewav3hhCledt9ode/Bjb8DL09F9QBnGemOYDTF6bGJaO9D5sgvVQJYICClXldWePPsSCjRZ8pT2Hkxq+Kfrt2JiLosXji12tHQGg7+CaiU/faZgIqnJGO2NuZrDR968Bb/zqnUtO8Z6kKxScygYFo7MZrBpJIWXppYxl9ZDAyI0RcL6oSQOncxAlYkb7dVOMOPQLs2hu5aiTYJpRktzqMQcvvLQPigSwV+8vdi39/TR1jc0bwbKNUVn4h7THKIOQghUWSqb55BQZRBCSqJ3BpIqrtm6DrdcfibWDSawbqDzbInvlT6c0irmBmQd48CLz+et7cN6R4CPClIx+56rVGZix8FZpAumu+iaz4QzB8AOsAA6V5WAaQ7CrdRChPVz6BSGnSqrQWWeAeD4Yg5bVvd6kt+6BeUqSU4u5Owqs6noRLpUgiZLZauysgd4pDeGM0ZTIMQuQc6XO/jYW7ZEog4R381sfCiJ5YDcgLufPIJfvXwShmlhOW8gqSkY6S3qYoOpzvZvCEIqpri9J8Kwf3oZ//LYQWiKhCudRVa6YJad+G98zUZ3u06AaQ7CrdRCRE1zGExqkAhKRD6GxayOgWRnO2zVi4SqYDYdHIF0fCGHVX3xSEdc+RFXw41dpmC6D/CfveUsAMDH/v1pEHjPL6bIiIBXyXUryRLBmr449k8vl2zzuft344LxAXwhp+PJg3O4eOOQR1MZjOB9ycJM03kjsAYRpRTXfe0xzGV0vH7zSNUtai8/awyXbBpCrM1VmxkUWYImS8i0qVVoBG7R9sOIWIa07DQqnw5hDos5A6cNd76oWT1IanJJ+eQvPbAXMUXC1GLOU2G2GzCYVDEf0KvhyGwGL00t4Y1n2aLR6zbbkVfrBhJtrcFfC1hDpsGkip64UiJImxbFbLqAPceXcNQJMX726LyXOUTQOPDC7XDA+wtZHXMZHesGEvjzt53jCSmu5DL6focZX0KT3WS9VqMh40AIOQhgCYAJwKCUbiOEDAG4C8BGAAcB/C6ldM7Z/pMA3uds/yeU0vud8YsA3AEgAeCnAD5EW1SX1rIoLIpIMQfAzpotxxyiFEdeC1IxuYSG/8MvXgIAnLOmD2u7RG9gGEiqgY18/uqe5wAAH/PlCbz/DWe0rVBarWD31EBSQ0+sVMSdzxRgUbiGIa5K+PO3nYNRR3MgpGhgogQm9odpKEdm7fP5q988B+es6fO4CStVHOh0yG47G/40Q3O4nFK6lVK6zfn7EwAeoJRuBvCA8zcIIecCuB7AeQCuBvBVQgjjZ18DcDOAzc7P1U04rkCwEsVRYg6AnVQTdNEppVjM6ZF8CKuBv0EJ3zRlIVPoOnfZQFJz+yXzODCTxuVnjbmJfwxXnbca12yNVjQPA3MrDSU114jzazJ/SZcffuA1uPHVGzGY1CBLBP0JNXKLLIAzDiH1lY7M2aHV44O2kK7KkmsUolzlGLB1h0wXRytdA+BO5/WdAK7lxr9PKc1TSg8A2AfgYkLIGgB9lNLHHbbwbW6fpoNVoex0jLkfMUUOXGHmdAu6ST3iYTeB1blhk85LU0W/9lxGd0tJdAsGQ5hDOm9GIjy1FrAFx0BSRVIrFXH5ki4SAc5wsoQliWA4pUXSpQQUkwvDuhCyBDk+yortE9X+5QwJTe6aaCUK4OeEkJ2EkJudsVWU0kkAcH6zyP11AI5w+044Y+uc1/7xloD1ao4ac4irUmB0BSuNzIcddhMSmuw2KAGAPU6pBsAO/QzLCI8qBkOYQ6ZgdKTGfyNgxmEopbnlIHjXEh89t3Ek5RF3R3pinsS+KIFpCH9wx5O468nDJe8fmcugL6548jzmHUOyNgIhxuWQbKNxaHTGeS2l9BghZAzALwghu8tsGzQb0zLjpR9gG6CbAeC0006r9VgBFJlD1OhwXA1mDmz1063MIcWJg3FVxp7ji573ozrBhGEgqSFvWG62MGDrWHaCWHcZcDY5DqY0zhVjuHkMTAMbTKolrXPf/4bT3T7UUQOfvfzLl2bwrt/wzhVHZrMluRmf/q3zsJDR8Yev29SWY6wXCU2p2Hq3WWjobqaUHnN+nyCE/AeAiwFMEULWUEonHZfRCWfzCQDrud3HARxzxscDxoP+320AbgOAbdu21SVYR1VziCkScgGlrYvMobsmUQY2YWYKBoZSmsetBEQz2qUcmBtsLlNAQrNXmcwH3Okqq7Uipcm44dINePM5qzC9ZGere5hDugCJAD/649ei1xcQEVUdBfD2WggqJX5kLoMtvkKQN756Y6sPqylIqBKOL7QnlLVu008ISRFCetlrAG8B8ByAewHc5Gx2E4B7nNf3ArieEBIjhGyCLTw/4bielgghlxI7FOBGbp+mo8gcorXqiasy8nrRrWRaFLppue0YuzVayZ/VObWUwzDnSupG5gDAozuwlpTdxhwIIfjba8/HRRsGA0XcmeUChlIxbBpJRaokdyUMpzTcfNnpAEp1h4MzaRycSeOs1aVVgrsBSS04cKUVaORuXgXgP5zQLgX4/9u79xi56iqA498zMzu7s4/uUnf74lUClVJaQNgQjLykUaERNIARggqCUQhEiTGREIwPIKBRo6Ch9o82PgIKEiIqFp+1CooUrEJ5UwggbbcPdrfbdh+ze/zj3rt7d2a2u3s7M/f+Zs4nmXT27t47v5M7nTO/N/eq6noReRK4X0SuAd4APgagqltE5H7gOSAPXK+qQZTXMTGU9Xf+oyKSWnMobFY6/3sb2dE/yK0fXQ64XHOYPKtz98AwSxe0sfu1PYC7NYdwv0MwVNe1mkNYuFnpoX+/xdIFc9g9MERnq1v3B7ykd/OqE3jslV3jNe/A3X9+hWwmxRVnRGuWjlsuW7r5uRIiJwdV3QqcXOL4bmDlFOfcDtxe4vgmYHnUssxGsFdz0vocGgs6pF/u8ZpfXO9zCGoO+4bzjIyO0XdghOPmtfKEq8mhpbjmEEwei2MDmHJpDc0NuOWhZ1m1YiG79w2PL+3iojlNDeM1b/Amv/1q8//4xBlHM6/Nrfk1geaDzNAvN3ffzRGNj1ZK0NpK4A1lHcqPoaqTJtoEY80L23xdEXxg3vTgM5y31Bu4FmycAg42K+WCPodQzSHGfYXLJSh77/4R9g2P0rN3iF0DQ5x0RMc0ZybXnFxm0n4VG17sIT+mXHTKohhLdWhy2TQHRkaLPicqIVkN71WQT+xoJe9WFA5nfXnHQNHCbS4JmpXe2LOf+zd5I5kXtjfR1pihqcG9uII+h97QBLHgm1xzzJv3HIpWP4kHK+Xu6B9ke98gCxxb3iTMqzlMJPHfP7eDrrZGTnE44eWyaVS9+U+VVn/JYTShfQ7++vBDBTf9+e39zvY3wESzEkx8iM5tydLR0uBckxJ4yyu0ZNOTaw7DtVBz8O7T273eqKWtu/YxlB9L/Lj/g5mTm9jrWlXZ+OJOVi6d59RCj4Wag93gqtDvUHfJYXyGdMJGKzX6NYfB/OQlDLbu3OdskxKUHsHT2ZplbnPWuaUzAl1tjewMzR7eP+R+zSGTTtHUkOItf2mJYb8G63RyaGpgYChP3u/r2juUZ8l8N0cpBcJDwyvN3U+diII+h3TC+hyCmsPgyGhR01LhmGyXlPrAnNvSyKoVC6fcFyHpFrQ3sa13YhnyoOYQx6bz5fSulkZeLdhdMAmbEkUVrCowMJRne79XI5rvcDMZVHfDH7ffzRGMJngoK3h9DnsHJ38r+OCJyd/xbSqFa9WkxOvU/dw5x8ZUokO3qD3HE6/tYdfAELmG9HiHtGvzHAp1tTWy+c3eScdcrzmAN0ppfL9yBzfMCqvmhj9uv5sjSGqHdPAhumtgaLxKHwhG+biocETF3Jas022+4NUcdvQPcuk9j3PWki5amzI0pGXa5Z6TrnA2cVNDyrmFEcOCvrr+A3l6+r1mQBd3Uwyr5j7SdZccktrnENQcbrj33+PfDpYuaOOYzhZn2+YLNWZSzHVsob1SFnbkyI8pr+/ez6KOAZbMa3W+1gAwryA5LOrIxb5/waEIVhXoHxwZb1ZybXOpQtasVEFJrTkEQ1n3hIZIfvXCE3nvsaX2snLT4YflaiM5hL59bu8bZFFHbnyBQZcFNYfGjDch0+X+BgjXHLzkMLclS2PG7fs00SFtyaHsRhO6ZHepN63rHZyBj3cfyfz2JpYtnOP0iJ7AgtDuddv6Btk3lHd6GGsgSA7B2lfHdLq5NW0gWHW2f3CEnv5B55uUINznYKOVym4koctnBDWHsFaHh7CGffPSk+IuQlmFO2kPjIyyrW+Q5lpIDv7ienNyDaz+xGlOzkMJC2oO/+sdZHu/2xP6Ajnrc6iciZ3gkpYcarfmUGsOa26gMZNieHQMVXi1Z4AVR7RPf2LCBTWH9lxD0XanLmptzHDmcZ2s2fgqgyNjXH76kdOflHCdrVme/8b5Jb9MlluyemWrIJ/QDulS2xNackgmEeHiU4/gMn8Tmb1D+drokPabXdodnpFf6LsfP3l8kb0lDs8XCogIuWy6KgMF3H9Hz1Ji+xwKag7plFTl24GJ5o6LV/B27wHu+5e3DeVRBTuLuShYnruWksO8tiY2fOlc+g6MOLfIY9zqLjnkHelzaKnStwMTXXhewCWnJXdntJlqzKRZuqDN2Y1wppJKiXN7lSdB3SWHpPY5ZNMpRCBYVqnN0f0b6klDeiKhF+6x7Kr1N54ddxFMQtRdckjqPAcR8faRHhkjm0lZf4Mj1l7VTVer+0MkjSlUd59ASZ0hDcFWoWMcP7/N+hsccd5Sd9e9MuZg6i45JLXmAN6IpWwmxR0Xr2AstGy3McZUW90lh6SOVgKv5tCRg+WH10b7tTHGXXWXHE496jA+v3JJIlfQbMqkx/d1MMaYONVdcuhePJfuxXPjLkZJjQ0pSw7GmESou+SQZNeec2zJmdLGGFNtifkkEpHzReRFEXlFRG6KuzxxWLViIStPsNEvxpj4JSI5iEga+CFwAbAMuFxElsVbKmOMqV+JSA7A6cArqrpVVYeBnwMfiblMxhhTt5KSHA4H3gz9/JZ/zBhjTAySkhxKTToomgUmIp8VkU0ismnnzp1VKJYxxtSnpCSHt4DwThxHAG8X/pGqrlHVblXt7urqqlrhjDGm3iQlOTwJLBGRY0QkC1wGPBxzmYwxpm4lYp6DquZF5AbgUSANrFXVLTEXyxhj6lYikgOAqj4CPBJ3OYwxxoCoo6t/ishe4MUSv2oH+mZ5uU5gV4RiRHmtap1jMUV/najnWUyeWowJaiOuTqBFVafvtFVVJx/ApimOrynXtWZwXpTXqtY5FlPEnj/eswAABZBJREFU17GYLKZajWs2MSSlQ7qcfp3w16rWOVHVWkxRX8diOrTXqtbrJDmmQ3mt2ONyuVlpk6p2J+1aSWExucFickctxDWbGFyuOaxJ6LWSwmJyg8XkjlqIa8YxOFtzMMYYUzku1xyMMcZUSM0mBxFZKyI9IvJs6NjJIvIPEXlGRH4tInP841kRWecf/4+InBs653YReVNEBmIIY5JyxCQizSLyWxF5QUS2iMidMYUTlL9c92m9f2yLiKz2l4GPRbliCp37cPha1VbGe7TB37Nls/+YF0M448oYV1ZE1ojIS/7/q0tiCKf8ogyzcuEBnA2cCjwbOvYkcI7//GrgVv/59cA6//k84Ckg5f98BrAQGKiFmIBm4P3+8SzwN+ACl2Pyf57j/yvAg8BlrsfkH7sYuDd8LVfjATYA3XHFUcG4vg7c5j9PAZ1xx1aOR83WHFR1I7Cn4PDxwEb/+R+AIMMvA/7kn9cD9ALd/s//VNVtFS/wDJQjJlXdr6p/8Y8PA0/jLXQYizLep37/bzJ4SS+2zrRyxSQircAXgdsqXOSDKlc8SVPGuK4G7vB/N6aqUSafJk7NJocpPAtc5D//GBMrwf4H+IiIZETkGOA0Jq8Sm2SRYxKRDuBC/Dd9gkSKSUQeBXqAvcAvq1fcGYkS063Ad4D91SzoDEV9363zm5S+IiKlluqP26zi8v8PAdwqIk+LyAMiUhN7/dZbcrgauF5EngLagGH/+Fq8ZcM3Ad8DHgfysZRw9iLFJCIZ4D7gLlXdWtUSTy9STKr6IbwmwEbgvGoWeAZmFZOInAIcp6oPxVHYGYhyj65Q1RXAWf7jk1Ut8czMNq4MXs37MVU9FfgH8O1qF7oi4m7XquQDWMwUbbXAu4F/TfG7x4FlBcdi73MoZ0x4b/a74o6n3PfJP34l8AOXYwKuw9vT5HW8D6VhYIOr8ZQ4flXc96hM90mAfUz0PxwJbIk7rnI86qrmEIyOEJEUcAuw2v+5WURa/OcfAPKq+lxsBZ2FKDGJyG14i3TdGEuhpzHbmESkVUQW+sczwCrghVgKP4XZxqSq96jqIlVdDJwJvKSq58ZS+BIi3KOMiHT6xxuAD+M14SRKhPukeMtWnOtfYiXgxGfHtOLOThX8RnAfsA0YwfvmdQ3wBeAl/3EnE5MAF+Ot8Po88Efg6NB1vuWfP+b/+zWXY8KrAqt/fLP/+IzjMc3HG2XyX2ALcDeQcTmmgustJt7RSuW4Ry14I3yCe/R9IB1XTOW8T8DReJ3Y/8XrvzsqzrjK9bAZ0sYYY4rUVbOSMcaYmbHkYIwxpoglB2OMMUUsORhjjCliycEYY0wRSw7GVICIXCsin5rF3y+Oc+VVYwpl4i6AMbVGRDKqujruchhzKCw5GFOCiCwG1gNPAO/BmxT1KeAE4LtAK7ALuEpVt4nIBrwlFd4HPCwibXhLrnzbXydpNd5y6a8CV6vqOyJyGt4yJvuBv1cvOmOmZ81KxkzteGCNqp4E9OOt6X83cKmqBh/st4f+vkNVz1HV7xRc5yfAl/3rPAN81T++Dvi8qr63kkEYE4XVHIyZ2puq+pj//GfAzcBy4A/+atNpvOUXAr8ovICItOMljb/6h34MPFDi+E+BC8ofgjHRWHIwZmqFa8vsxVtxc6pv+vtmcW0pcX1jEsOalYyZ2lEiEiSCy4F/Al3BMRFpEJETD3YBVe0D3hGRs/xDnwT+qqq9QJ+InOkfv6L8xTcmOqs5GDO154ErReRHwMt4/Q2PAnf5zUIZvI1ftkxznSuB1SLSDGwFPu0f/zSwVkT2+9c1JjFsVVZjSvBHK/1GVZfHXBRjYmHNSsYYY4pYzcEYY0wRqzkYY4wpYsnBGGNMEUsOxhhjilhyMMYYU8SSgzHGmCKWHIwxxhT5P8Q7r4y81WsVAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][:300].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the peak arrives at the autumn, the year are re-sampled by starting on September 1st.\n", "First finding all the September 1st for each year :" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[Period('1991-07-29/1991-08-04', 'W-SUN'),\n", " Period('1992-07-27/1992-08-02', 'W-SUN'),\n", " Period('1993-07-26/1993-08-01', 'W-SUN'),\n", " Period('1994-08-01/1994-08-07', 'W-SUN'),\n", " Period('1995-07-31/1995-08-06', 'W-SUN'),\n", " Period('1996-07-29/1996-08-04', 'W-SUN'),\n", " Period('1997-07-28/1997-08-03', 'W-SUN'),\n", " Period('1998-07-27/1998-08-02', 'W-SUN'),\n", " Period('1999-07-26/1999-08-01', 'W-SUN'),\n", " Period('2000-07-31/2000-08-06', 'W-SUN'),\n", " Period('2001-07-30/2001-08-05', 'W-SUN'),\n", " Period('2002-07-29/2002-08-04', 'W-SUN'),\n", " Period('2003-07-28/2003-08-03', 'W-SUN'),\n", " Period('2004-07-26/2004-08-01', 'W-SUN'),\n", " Period('2005-08-01/2005-08-07', 'W-SUN'),\n", " Period('2006-07-31/2006-08-06', 'W-SUN'),\n", " Period('2007-07-30/2007-08-05', 'W-SUN'),\n", " Period('2008-07-28/2008-08-03', 'W-SUN'),\n", " Period('2009-07-27/2009-08-02', 'W-SUN'),\n", " Period('2010-07-26/2010-08-01', 'W-SUN'),\n", " Period('2011-08-01/2011-08-07', 'W-SUN'),\n", " Period('2012-07-30/2012-08-05', 'W-SUN'),\n", " Period('2013-07-29/2013-08-04', 'W-SUN'),\n", " Period('2014-07-28/2014-08-03', 'W-SUN'),\n", " Period('2015-07-27/2015-08-02', 'W-SUN'),\n", " Period('2016-08-01/2016-08-07', 'W-SUN'),\n", " Period('2017-07-31/2017-08-06', 'W-SUN'),\n", " Period('2018-07-30/2018-08-05', 'W-SUN'),\n", " Period('2019-07-29/2019-08-04', 'W-SUN')]" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "first_september_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", " for y in range(1991,\n", " sorted_data.index[-1].year)]\n", "first_september_week" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Starting from this list of weeks that contain September 1st, we obtain intervals of approximately one year as the periods between two adjacent weeks in this list. We compute the sums of weekly incidences for all these periods.\n", "\n", "We also check that our periods contain between 51 and 52 weeks, as a safeguard against potential mistakes in our code.\n" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_september_week[:-1], first_september_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": [ "Displaying the annual incidence." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style='*')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The year with the maximum number of cases :" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2010" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.idxmax()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The year with the minimum number of cases :" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2002" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.idxmin()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }