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alemol/extracci-n-de-datos-de-redes-sociales-atropellados.ipynb

Created March 22, 2021 16:02
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extracción de datos de redes sociales: atropellados.ipynb
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extracci-n-de-datos-de-redes-sociales-atropellados.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "extracción de datos de redes sociales: atropellados.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyMRwPAK6u/nFMRczw6HrfQd",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/alemol/574ebf680f4f916d310e56dc6eb1e054/extracci-n-de-datos-de-redes-sociales-atropellados.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "fnxEQy_RRovn"
},
"source": [
"# Extracción de datos de redes sociales\n",
"Alejandro Molina Villegas\n",
"\n",
"**Objetivo:**\n",
"\n",
"Conocer la forma en la que se extraen datos de redes sociales a través de un lenguaje de programación con el fin de ser analizados para un caso de interés.\n",
"\n",
"**Lenguaje:** Python\n",
"\n",
"**Caso de interés:** Aproximar reportes de atropellados (ilustrativo) para generar un mapa."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hWbI9Z9OSSQb"
},
"source": [
"### Preparación"
]
},
{
"cell_type": "code",
"metadata": {
"id": "NXVMTlcYkdYO"
},
"source": [
"!pip install snscrape\n",
"!pip install simplejson\n",
"!pip install geopandas\n",
"!pip install contextily"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "YZBn-ggdtM9L"
},
"source": [
"# obtener tuits\n",
"import snscrape.modules.twitter as twitter\n",
"# georreferenciación con geoparsing\n",
"import requests\n",
"import simplejson as json\n",
"\n",
"# visualización en mapa\n",
"from shapely.geometry import Point\n",
"from geopandas import GeoDataFrame\n",
"import contextily as ctx\n",
"import matplotlib.pyplot as plt"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "cNhXNhzQSj8q"
},
"source": [
"### Obtención de tuits"
]
},
{
"cell_type": "code",
"metadata": {
"id": "gF5fwgkRSMBC",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "f5ffd365-4fe0-4d47-d040-22c30d3d6a08"
},
"source": [
"query = \"atropellado\"\n",
"limit = 5\n",
"\n",
"for i, tweet in enumerate(twitter.TwitterSearchScraper(query).get_items()):\n",
" if i == limit:\n",
" break\n",
" print(tweet, tweet._asdict,'\\n')"
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"https://twitter.com/pulzo/status/1371639856464498690 <bound method Tweet._asdict of Tweet(url='https://twitter.com/pulzo/status/1371639856464498690', date=datetime.datetime(2021, 3, 16, 1, 50, tzinfo=datetime.timezone.utc), content='#Video Alcalde de Cali @JorgeIvanOspina quiso tranzar con plata a joven atropellado por su conductor 👉🏻 https://t.co/4zZMkGRTJD https://t.co/LdDCw68mrt', id=1371639856464498690, username='pulzo', outlinks=['https://bit.ly/3rXDjys'], outlinksss='https://bit.ly/3rXDjys', tcooutlinks=['https://t.co/4zZMkGRTJD'], tcooutlinksss='https://t.co/4zZMkGRTJD')> \n",
"\n",
"https://twitter.com/911Jalisco/status/1371639219282661383 <bound method Tweet._asdict of Tweet(url='https://twitter.com/911Jalisco/status/1371639219282661383', date=datetime.datetime(2021, 3, 16, 1, 47, 28, tzinfo=datetime.timezone.utc), content='ATROPELLADO 🚑 en Guadalajara, Col. Lomas De Polanco, Calle 7 y Calle 16. Tome precauciones', id=1371639219282661383, username='911Jalisco', outlinks=[], outlinksss='', tcooutlinks=[], tcooutlinksss='')> \n",
"\n",
"https://twitter.com/911Jalisco/status/1371637125402214400 <bound method Tweet._asdict of Tweet(url='https://twitter.com/911Jalisco/status/1371637125402214400', date=datetime.datetime(2021, 3, 16, 1, 39, 9, tzinfo=datetime.timezone.utc), content='ATROPELLADO 🚑 en Guadalajara, Col. Lomas De Polanco, Laura Méndez y Longinos Cadena. Tome precauciones', id=1371637125402214400, username='911Jalisco', outlinks=[], outlinksss='', tcooutlinks=[], tcooutlinksss='')> \n",
"\n",
"https://twitter.com/iK0ZUMEK/status/1371629800469770246 <bound method Tweet._asdict of Tweet(url='https://twitter.com/iK0ZUMEK/status/1371629800469770246', date=datetime.datetime(2021, 3, 16, 1, 10, 2, tzinfo=datetime.timezone.utc), content='@TINYSH0TO NO SE MI VIEJA DIJO QUE HABÍAN ATROPELLADO A UN GATO QUE SE PAREFE AL MIO Y NO LO ENCRTUWTRO ESTOY ENTRAJFO EN PANIPC', id=1371629800469770246, username='iK0ZUMEK', outlinks=[], outlinksss='', tcooutlinks=[], tcooutlinksss='')> \n",
"\n",
"https://twitter.com/melisanunezf/status/1371628749075140611 <bound method Tweet._asdict of Tweet(url='https://twitter.com/melisanunezf/status/1371628749075140611', date=datetime.datetime(2021, 3, 16, 1, 5, 52, tzinfo=datetime.timezone.utc), content='Me duele el abdomen como si me hubiera aventado 300000000 abdominales o si me hubieran atropellado k pedo', id=1371628749075140611, username='melisanunezf', outlinks=[], outlinksss='', tcooutlinks=[], tcooutlinksss='')> \n",
"\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "kRAGmQU-Sr21"
},
"source": [
"### Georreferenciación"
]
},
{
"cell_type": "code",
"metadata": {
"id": "U0FKlH3dSJFj"
},
"source": [
"\n",
"def geoparseMX(text):\n",
" \"\"\"Geoparsing service for mexican spanish\n",
" see http://geoparsing.geoint.mx/mx/info/\n",
" \"\"\"\n",
" geoparser_url = \"http://geoparsing.geoint.mx/ws/\"\n",
" data = dict({\"text\" : text})\n",
" try:\n",
" response = requests.post(geoparser_url, json = data, headers={\"Content-Type\":\"application/json\"})\n",
" jresponse = response.json()\n",
" #print(json.dumps(jresponse, encoding=\"utf8\", indent=2, ensure_ascii=False))\n",
" for e in jresponse['entities']:\n",
" place = e['nominatim'][0]\n",
" if place['geojson']['type'] == 'Point':\n",
" coords = place['geojson']['coordinates']\n",
" return coords\n",
" except Exception as e:\n",
" coords = None\n",
" return None\n"
],
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bJ7AYQ-HyHL1",
"outputId": "8412bba9-d8f4-4113-e928-d1bfa9b04d13"
},
"source": [
"g = geoparseMX(\"Mi nombre es Alex y soy originario de la ciudad de México. Saludos\")\n",
"print(g)"
],
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"text": [
"{\n",
" \"labeled\": \"Mi nombre es Alex y soy originario de la <START:location> ciudad de México <END> . Saludos\\n\",\n",
" \"entities\": [\n",
" {\n",
" \"index\": 1,\n",
" \"entity\": \"ciudad de México\",\n",
" \"context\": \"la <START:location> ciudad de México <END> . Saludos\",\n",
" \"nominatim\": [\n",
" {\n",
" \"address\": {\n",
" \"city\": \"Ciudad de México\",\n",
" \"country\": \"México\",\n",
" \"country_code\": \"mx\",\n",
" \"county\": \"Cuauhtémoc\",\n",
" \"postcode\": \"06060\",\n",
" \"state\": \"CDMX\"\n",
" },\n",
" \"boundingbox\": [\n",
" \"19.2726009\",\n",
" \"19.5926009\",\n",
" \"-99.2933416\",\n",
" \"-98.9733416\"\n",
" ],\n",
" \"category\": \"place\",\n",
" \"display_name\": \"Ciudad de México, Cuauhtémoc, CDMX, 06060, México\",\n",
" \"geojson\": {\n",
" \"coordinates\": [\n",
" -99.1333416,\n",
" 19.4326009\n",
" ],\n",
" \"type\": \"Point\"\n",
" },\n",
" \"icon\": \"/nominatim/images/mapicons/poi_place_city.p.20.png\",\n",
" \"importance\": 1.144807457730147,\n",
" \"lat\": \"19.4326009\",\n",
" \"licence\": \"Data © OpenStreetMap contributors, ODbL 1.0. https://osm.org/copyright\",\n",
" \"lon\": \"-99.1333416\",\n",
" \"namedetails\": {\n",
" \"alt_name:vi\": \"Thành phố Mê-hi-cô\",\n",
" \"name\": \"Ciudad de México\",\n",
" \"name:ace\": \"Banda Meksiko\",\n",
" \"name:af\": \"Meksikostad\",\n",
" \"name:am\": \"ሜክሲኮ ከተማ\",\n",
" \"name:an\": \"Ciudat de Mexico\",\n",
" \"name:ang\": \"Mexicoburg\",\n",
" \"name:ar\": \"مدينة مكسيكو\",\n",
" \"name:arz\": \"ميكسيكو سيتى\",\n",
" \"name:ast\": \"Ciudá de Méxicu\",\n",
" \"name:ay\": \"Mïxiku marka\",\n",
" \"name:az\": \"Mexiko\",\n",
" \"name:ba\": \"Мехико\",\n",
" \"name:bat-smg\": \"Meksėks\",\n",
" \"name:bcl\": \"Mexico\",\n",
" \"name:be\": \"Мехіка\",\n",
" \"name:be-tarask\": \"Мэхіка\",\n",
" \"name:bg\": \"Мексико\",\n",
" \"name:bn\": \"মেক্সিকো সিটি\",\n",
" \"name:bo\": \"མེག་སི་ཀོ་གྲོང་།\",\n",
" \"name:br\": \"Kêr-Vec'hiko\",\n",
" \"name:bs\": \"Ciudad de México\",\n",
" \"name:ca\": \"Ciutat de Mèxic\",\n",
" \"name:ckb\": \"مەکسیکۆ سیتی\",\n",
" \"name:cs\": \"Ciudad de México\",\n",
" \"name:cv\": \"Мехико\",\n",
" \"name:cy\": \"Dinas Mexico\",\n",
" \"name:da\": \"Mexico City\",\n",
" \"name:de\": \"Mexiko-Stadt\",\n",
" \"name:diq\": \"Meksiko City\",\n",
" \"name:el\": \"Πόλη του Μεξικού\",\n",
" \"name:en\": \"Mexico City\",\n",
" \"name:eo\": \"Meksik-urbo\",\n",
" \"name:es\": \"Ciudad de México\",\n",
" \"name:et\": \"México\",\n",
" \"name:eu\": \"Mexiko Hiria\",\n",
" \"name:ext\": \"Ciá de Méjicu\",\n",
" \"name:fa\": \"مکزیکو سیتی\",\n",
" \"name:fi\": \"México\",\n",
" \"name:fiu-vro\": \"México\",\n",
" \"name:fo\": \"Meksikobýur\",\n",
" \"name:fr\": \"Mexico\",\n",
" \"name:fy\": \"Meksiko-Stêd\",\n",
" \"name:ga\": \"Cathair Mheicsiceo\",\n",
" \"name:gd\": \"Meagsago\",\n",
" \"name:gl\": \"Cidade de México\",\n",
" \"name:gn\": \"Méjiko táva\",\n",
" \"name:haw\": \"Mēkiko D.F.\",\n",
" \"name:he\": \"מקסיקו סיטי\",\n",
" \"name:hi\": \"मेक्सिको नगर\",\n",
" \"name:hif\": \"Mexico City\",\n",
" \"name:hr\": \"Ciudad de México\",\n",
" \"name:hsb\": \"Mexiko-město\",\n",
" \"name:ht\": \"Meksiko\",\n",
" \"name:hu\": \"Mexikóváros\",\n",
" \"name:hy\": \"Մեխիկո\",\n",
" \"name:ia\": \"Citate de Mexico\",\n",
" \"name:id\": \"Ciudad de México\",\n",
" \"name:io\": \"México\",\n",
" \"name:is\": \"Mexíkóborg\",\n",
" \"name:it\": \"Città del Messico\",\n",
" \"name:ja\": \"メキシコシティ\",\n",
" \"name:jbo\": \"mexygu'e tcadu\",\n",
" \"name:jv\": \"Mexico City\",\n",
" \"name:ka\": \"მეხიკო\",\n",
" \"name:kk\": \"Мехико\",\n",
" \"name:kl\": \"Mexico City\",\n",
" \"name:km\": \"ក្រុងម៉ិកស៊ិក\",\n",
" \"name:kn\": \"ಮೆಕ್ಸಿಕೋ ನಗರ\",\n",
" \"name:ko\": \"멕시코시티\",\n",
" \"name:ku\": \"Meksîko\",\n",
" \"name:kw\": \"Cita Mexico\",\n",
" \"name:la\": \"Mexicopolis\",\n",
" \"name:lad\": \"Sivdad de Meksiko\",\n",
" \"name:lij\": \"Çittæ do Mescico\",\n",
" \"name:lmo\": \"Cità del Messich\",\n",
" \"name:ln\": \"Mbóka ya Mexiko\",\n",
" \"name:lt\": \"Meksikas\",\n",
" \"name:lv\": \"Mehiko\",\n",
" \"name:mg\": \"Mexico\",\n",
" \"name:mhr\": \"Мехико\",\n",
" \"name:mk\": \"Мексико\",\n",
" \"name:ml\": \"മെക്സിക്കോ സിറ്റി\",\n",
" \"name:mn\": \"Мехико\",\n",
" \"name:mr\": \"मेक्सिको सिटी\",\n",
" \"name:mrj\": \"Мехико\",\n",
" \"name:ms\": \"Bandar Raya Mexico\",\n",
" \"name:nah\": \"Āltepētl Mēxihco\",\n",
" \"name:nan\": \"México Chhī\",\n",
" \"name:nl\": \"Mexico-stad\",\n",
" \"name:nn\": \"Mexico by\",\n",
" \"name:no\": \"Mexico by\",\n",
" \"name:nov\": \"Mexiko Urbe\",\n",
" \"name:nv\": \"Méhigoʼ sídii\",\n",
" \"name:oc\": \"Ciutat de Mexic\",\n",
" \"name:os\": \"Мехико\",\n",
" \"name:pap\": \"Ciudad di Mexico\",\n",
" \"name:pl\": \"Meksyk\",\n",
" \"name:pms\": \"Sità dël Méssich\",\n",
" \"name:pnb\": \"میکسیکو شہر\",\n",
" \"name:pt\": \"Cidade do México\",\n",
" \"name:qu\": \"Mishiku llaqta\",\n",
" \"name:rm\": \"Citad da Mexico\",\n",
" \"name:ro\": \"Ciudad de México\",\n",
" \"name:ru\": \"Мехико\",\n",
" \"name:rue\": \"Мексіко Сіті\",\n",
" \"name:sah\": \"Мехико\",\n",
" \"name:sc\": \"Tzitade de su Mèssico\",\n",
" \"name:scn\": \"Cità dû Mèssicu\",\n",
" \"name:sco\": \"Mexico Ceety\",\n",
" \"name:se\": \"México\",\n",
" \"name:sh\": \"Ciudad de Mexico\",\n",
" \"name:simple\": \"Mexico City\",\n",
" \"name:sk\": \"Mexiko\",\n",
" \"name:sl\": \"Ciudad de México\",\n",
" \"name:sm\": \"Mexico Siti\",\n",
" \"name:sq\": \"Meksiko\",\n",
" \"name:sr\": \"Мексико Сити\",\n",
" \"name:sv\": \"Mexico City\",\n",
" \"name:sw\": \"Mexico\",\n",
" \"name:szl\": \"Meksyk\",\n",
" \"name:ta\": \"மெக்சிகோ நகரம்\",\n",
" \"name:tg\": \"Мехико\",\n",
" \"name:th\": \"เม็กซิโกซิตี\",\n",
" \"name:tk\": \"Mehiko\",\n",
" \"name:tl\": \"Lungsod ng Mehiko\",\n",
" \"name:tr\": \"Meksika\",\n",
" \"name:tt\": \"Мехико\",\n",
" \"name:udm\": \"Мехико\",\n",
" \"name:ug\": \"مېكسىكا شەھىرى\",\n",
" \"name:uk\": \"Мехіко\",\n",
" \"name:ur\": \"میکسیکو شہر\",\n",
" \"name:uz\": \"Mexiko shahri\",\n",
" \"name:vec\": \"Sità del Mèsico\",\n",
" \"name:vi\": \"Thành phố México\",\n",
" \"name:vo\": \"Ciudad de México\",\n",
" \"name:war\": \"Syudad han Mehiko\",\n",
" \"name:xmf\": \"მეხიკო\",\n",
" \"name:yi\": \"מעקסיקא שטאט\",\n",
" \"name:yo\": \"Ìlú Mẹ́ksíkò\",\n",
" \"name:yue\": \"墨西哥城\",\n",
" \"name:zh\": \"墨西哥城\"\n",
" },\n",
" \"osm_id\": \"62270270\",\n",
" \"osm_type\": \"node\",\n",
" \"place_id\": \"100010\",\n",
" \"place_rank\": \"15\",\n",
" \"type\": \"city\"\n",
" },\n",
" {\n",
" \"address\": {\n",
" \"country\": \"México\",\n",
" \"country_code\": \"mx\",\n",
" \"state\": \"CDMX\"\n",
" },\n",
" \"boundingbox\": [\n",
" \"19.0482367\",\n",
" \"19.5927572\",\n",
" \"-99.3649242\",\n",
" \"-98.9403028\"\n",
" ],\n",
" \"category\": \"boundary\",\n",
" \"display_name\": \"CDMX, México\",\n",
" \"geojson\": {\n",
" \"coordinates\": [\n",
" [\n",
" [\n",
" -99.3649242,\n",
" 19.2777693\n",
" ],\n",
" [\n",
" -99.3619219,\n",
" 19.2757419\n",
" ],\n",
" [\n",
" -99.3561284,\n",
" 19.2749894\n",
" ],\n",
" [\n",
" -99.3482137,\n",
" 19.2739609\n",
" ],\n",
" [\n",
" -99.3475125,\n",
" 19.2730267\n",
" ],\n",
" [\n",
" -99.346479,\n",
" 19.2722294\n",
" ],\n",
" [\n",
" -99.3462968,\n",
" 19.2720221\n",
" ],\n",
" [\n",
" -99.3461511,\n",
" 19.2713079\n",
" ],\n",
" [\n",
" -99.3458457,\n",
" 19.2708068\n",
" ],\n",
" [\n",
" -99.3455245,\n",
" 19.2704374\n",
" ],\n",
" [\n",
" -99.3451284,\n",
" 19.2699922\n",
" ],\n",
" [\n",
" -99.3446866,\n",
" 19.2694752\n",
" ],\n",
" [\n",
" -99.3440752,\n",
" 19.2691158\n",
" ],\n",
" [\n",
" -99.3437085,\n",
" 19.268962\n",
" ],\n",
" [\n",
" -99.3434912,\n",
" 19.2688723\n",
" ],\n",
" [\n",
" -99.3430597,\n",
" 19.2685477\n",
" ],\n",
" [\n",
" -99.3427776,\n",
" 19.2684747\n",
" ],\n",
" [\n",
" -99.3422544,\n",
" 19.2682914\n",
" ],\n",
" [\n",
" -99.3419107,\n",
" 19.2681787\n",
" ],\n",
" [\n",
" -99.341552,\n",
" 19.2680943\n",
" ],\n",
" [\n",
" -99.340939,\n",
" 19.2677978\n",
" ],\n",
" [\n",
" -99.3391599,\n",
" 19.2676971\n",
" ],\n",
" [\n",
" -99.3376298,\n",
" 19.26404\n",
" ],\n",
" [\n",
" -99.3398572,\n",
" 19.2596529\n",
" ],\n",
" [\n",
" -99.3413169,\n",
" 19.2521495\n",
" ],\n",
" [\n",
" -99.3420687,\n",
" 19.2475392\n",
" ],\n",
" [\n",
" -99.342341,\n",
" 19.2411224\n",
" ],\n",
" [\n",
" -99.335772,\n",
" 19.2393271\n",
" ],\n",
" [\n",
" -99.3327165,\n",
" 19.2384682\n",
" ],\n",
" [\n",
" -99.3308215,\n",
" 19.2379353\n",
" ],\n",
" [\n",
" -99.330474,\n",
" 19.2374805\n",
" ],\n",
" [\n",
" -99.3267196,\n",
" 19.2325656\n",
" ],\n",
" [\n",
" -99.3243202,\n",
" 19.2326098\n",
" ],\n",
" [\n",
" -99.3222549,\n",
" 19.2326478\n",
" ],\n",
" [\n",
" -99.321297,\n",
" 19.232665\n",
" ],\n",
" [\n",
" -99.3153434,\n",
" 19.2291965\n",
" ],\n",
" [\n",
" -99.3155555,\n",
" 19.2273953\n",
" ],\n",
" [\n",
" -99.3156826,\n",
" 19.2262745\n",
" ],\n",
" [\n",
" -99.3161217,\n",
" 19.2225888\n",
" ],\n",
" [\n",
" -99.3162498,\n",
" 19.2215017\n",
" ],\n",
" [\n",
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" }\n",
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"[-99.1333416, 19.4326009]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "3rArDHm5zsKM"
},
"source": [
"query = \"atropellado\"\n",
"points = []\n",
"for i, tweet in enumerate(twitter.TwitterSearchScraper(query).get_items()):\n",
" try:\n",
" coords = geoparseMX(tweet.content)\n",
" if coords != None:\n",
" points.append(coords)\n",
" except:\n",
" continue\n"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "7cnLpETtSzDW"
},
"source": [
"### Mapa"
]
},
{
"cell_type": "code",
"metadata": {
"id": "9AgqH5XAS4nn"
},
"source": [
"def mapplot(list_points):\n",
" \"\"\"Points to Map\"\"\"\n",
" geometry_points = [Point(x,y) for x, y in list_points]\n",
" geodf = GeoDataFrame(geometry_points, crs=\"EPSG:4326\", geometry=0)\n",
" CRS_df = geodf.to_crs(epsg=3857)\n",
" ax = CRS_df.plot()\n",
" # we are using an extent around Mexico for the examples\n",
" ax.axis((-13000000, -9700000, 1800000, 3900000))\n",
" ctx.add_basemap(ax, source=ctx.providers.Stamen.TonerLite)\n",
" plt.show()\n"
],
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 285
},
"id": "c8bLqi093T5O",
"outputId": "f0ffeac4-b28f-4cb1-a570-bd517b8dcc65"
},
"source": [
"mapplot([[-99.1333416, 19.4326009]])"
],
"execution_count": 8,
"outputs": [
{
"output_type": "display_data",
"data": {
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aHNPD5PKNmraV7Y2o1+umyTdGy8RI4xj51jcTOs0l/SJ4EOjndLd5q19cje/BsJUHs3NT5FQnrfugCkcnJehEaPp8b6aX9j/a9/91I3n/OwC/0+X3nmi1WqhWq2CM4Rvf+Aai0SjC4bDg0Gw2G+r1uvisaRp2d3fhcrkwNTXV5jRtNBpoNpt9h+HpKQ2Hw4FoNIpIJIJ6vY58Po+1tTUwtpe8QrHB+v2GBb3ANP4j589JFECccxQKBZFEA+wtAk6n88BFuejlN3s5+rkXlK3aCXpBT8c+qfd7GLDqwzjs63c6nchms1AURZR8oHt/2KVLON+rfVMqlfpOzurnHJ2UoKMo8mbp6IwxG4BrABYAfJ5zfrXDdrMA5gD8i+5rJ2PsRQAqgD/gnH+11/larRY+97nP4eLFi6jX6wCA27dvI5lMol6vo9FooNVqYW5uDsvLyygWi5ifn8f29jbm5uYwNTUlNAJZlkU4Jv09yGShiedyueByuRCPx1GtVpHNZrG4uAiHw4FQKAS/3z90TdBoTRg1z5MISZLgcrnEPZMkCd/73vcwNTWFmZkZVKtVVCoV1Ot1+P1+FAoF4XB3uVxIpVKYmJhoq49kdDgftvC5FxbXo8IwHbq99pVlGYFAALlcDuFwuK0wYbeEsYOCFBXK8u+mnBitkEHOZTanTgq9A855C8AjjLEggK8wxi5yzl8z2fSj2OP8W7rvZjnnG4yx0wD+hTH2Kud80bgjY+yTAD4JABMTE3j729+O6elptFottFotnDt3TlSfI6Hq8Xhw7ty5ttAuSrkmLp8xhkgkgnw+j42NDUQiERGVc5AJI0kSPB4P3G43EokEKpUKstkstre34fF47orq6Re9+HnCYfCcpVIJ2Wy2bwei8bdms4lKpSKc4dVqFS+99BLq9Tpu3LgBWZZx+/ZtYS0tLS3B7XbjiSeewA9+8AO8973vFXkUQHsZgcMC3U99xcv7XeADhy9wjeeiqLpyuQy/3y8WnVKpJKpvGukVKs2iKAqazSZUVe2rdk69XoeqqqK0hJVxHgRm7zFwp6yz2XbDuOd92RGc8xxj7FsAngXQSeh/2rDPxv7/S4yxb2OP779L6HPOvwjgiwBw8eJFfvr0acRisbu0ZiOX26lMsH6SkoAuFArIZrOo1WpIJBJiMhnGIfa3CkrM8vv9UFUV+Xwe29vbIqOQ+H+rx7XCFfbi+w8CfeSSGTpZGMbv7XY7dnd38Wd/9md4+umnkUqlEA6H8ZOf/ASpVEq8WHa7HQsLC9ja2kI4HMbS0hKCwSD8fn9b5uFha0BmZvf9KOw7UShmFMugsLK/0+lEJpMRn1utFv75n/8Z73vf+yBJElZWVkTio6Io2NjYgKIoUFVV1OeiPgCKoiCfz2NsbAyZTAayLIt6RYRqtSoCNbqhH5pLHxFF0OfhdNpWH0BgXAAOSm9Zid6JAWjuC3wXgHcD+EOT7c4DCGGvmTl9FwJQ4ZzXGWNRAE8D+I9WBkblFowCUC/s+hHQVKWTanXv7u6iXq8jFAq1UT61Wg02m20gS4Ccxnr+P5fLYWVlBZIkIRgMCrNxWI5XukeDZCF2O24gEOirUFWnY/t8PoyPj0NVVaTTaczPz2NjYwNPP/00KpUKGGPwer0IBAKIRqNoNpuQJAnlcrkjbz9s6F+uNztv3wmcc2QyGaytraFQKCAcDiMajUKSJNEkJRqNCiXsoNy+lf3NFLJSqQTOOa5fv47NzU0kk0m4XC7Mz8/j5s2b4t0+d+4cVFVFuVzG5uYm/H4/fD4f3G43SqUSdnd38clPfhJut1s8f1VVLRU663Q9+r+NgpuO101mUVIW/W5mCRCjcRDBb0XTHwfw5/u8vgTgLznnX2OM/R6AFznnf7O/3UcB/H+8/e2/AOALjDFtf98/4Jy/YWVg+htvJvj1C0I30D71eh21Wk3cTE3TkM1mUalUEI/HhRlYqVSQy+WE5q4oSk+Nu9Pi5HQ6kUgkEI/HBf2j5/99Pt/Q+P+jcLAZz2f2P9A+ERVFEQlrtKBeuHDBlKaZnZ09gpGjbbxmUUD3m8BvtVr48pe/jFAohHw+L/pPfPvb30YgEEAsFoOmabhy5QrGxsbE+zPonLOqfNCzoQRLYE8bf+2115BOp4WALhaLWFxcRLPZRCgUgsPhwMrKCtxuNyqVCmq1GqLRKM6dO4eXX34ZtVoNtVpNVPEFIBIdgbtpRL3w1o9LP3fMHP70t/GaBnnnjWM5SEl2K9E719Eegknf/7bh8/9uss0LAB7qa0T7ICcfRVeYCVWafL1Cv4C9VZzikGl/YG8x2NzcFDUzCoUCVFVFJpNBoVBAPB5vi0AxA43FbBWn37xeLzwej0j60PP/oVCojf/XH0s/ufSTxVhwiXMOVVVNOWh9vZODwMyBTMfsJjBpco6NjWF9fR2nTp0SZSOOa6HSP6v7VdgTyLKLx+M4deoUHA4HqtUqQqEQFEWBz+dDo9Fo6zB2FJAkCT6fD6lUCmNjY7DZbHjHO96BYrGIS5cuIZ1O4+GHH0aj0RC1iGw2G5LJpODlaXHwer3w+XxIJBIiMsjtdguFjfY3Kx5nFPp6mL3rZtAHIXSbZ0a/SadzUlTfIH6uE5uR22g0sLW1hbGxMSEgjKCHYSZszaJbzG4MY3tJKblc7q7tiJ+3UkaBFqBeiwMlfwUCgbb4f3JC04tGlfbK5TIWFxdRLpcxPj4OxvZqiFOfUp/Ph2azCb/fj+9+97uYmJgQpR8ajQYYY0gmk+I7zjmi0ehA5quxfIP+XllBIBBAvV4XDttEIiEifA4LZhbJSNC3gzGG9773vZa1RqsKl5Xj9Prd6XRCURTU63U4nU7R7AXYC/gg6BUSsiwZY6JIG/3m8/nuqoNF2+qVKqPipZ8vxigyK9fSzzVbrTVkHI9VnFihzxhDo9FAOp3G+Pg4gLv5MD21Ygyh0pvsfD/2tpNm2e1BUIiosXWacZ9ONE+361MURfD/tVoNmUwGS0tLcLlceOmll7C9vY1nn30WKysrWFtbww9/+ENIkoSZmRlhiVy6dAk3b97Eww8/DFVV8fzzzyMSiaBcLot+qJlMBk6nE36/X7ScpEXFDPl8/q5QSf397eclN1oF8Xgc4XBYUF2nT5+23Ie0HxidYPqxjwR9OwaxuLppv8MEY0zQNBQM0Wk7I/WhlwX0fprRLb3kwlHSr5K01/zGCoxWhlWcWKEP7F0IlUKg5KxOwha42yQzToRBoKoq1tfX4XK5hMVB4WR0HuN4+o0AYmwvln1iYgJjY2Oo1Wo4c+YMxsbGEA6H8TM/8zMol8soFAqi7k4+nxfXHgqFMD4+jrm5OTz00EOo1+soFApYXFzElStXBHXkcDjQbDbBOReC1sw8JCpKj0H5Q+N9YGzP2R2LxSDLMpaWljA/P39XaN1BXrSTHIVTLpfxox/9CPV6HQsLC0gkEsc6Hv196uce6d+tQazGfvZRFAWlUgmtVqtn4pJeHujDbjudr9FoIJvN9l2t9Cis08Pa50QLfUI2m4Xb7e7IA1tZkbtptp1Ax2u1WigWiygWi4JbJ3pCPwn1fPugwtFms8Hj8eDChQttkzUajXbcT0+9kGnbaDTw0EMPwefztY2lUqlAVVX4/f62fTu9GFa5yG5jo2szXivVKV9eXsbc3FybNaVfiPq1LAYVZEcBSdrrO7uysoLp6Wm88MIL4j5Q9Mb6+jqmp6exs7ODSCSCM2fOHNp1HIdfRb8YW4Esy3C5XMhkMojFYpasaOCOld+LcmWMifaQVq/hsNCPBWV0PFvFiRf6pI02Go2O3L4VHLQbkl4AaZomGq4YnVsH0YCMx7HqpNZr67Stoih3UVK0rVlBLbNM14MKfP2xO/0WDAahqiqWlpYwNTV112JE25lxrWY4yQIf2OsKNzc3h1arhbW1NXz3u9+Fz+dDIBDA7u4uLl++jJdffhk3btxAuVzGwsICFhYWBtKm9X/rF1/9sU7yvdKDErWGvUjRtfdzXKu8O6Efy9+q0NcrN/1Slide6BMo63bQBJ1gMCiaJw8D1A3HDDQpDjJBjQ/f6JCk3/ulMFRVbas3Y1zMjFTZYQsDxhii0SjcbjeWl5cxPz8vCtnpr7nfRbtTVMNJEG52ux0ej0c49Ml/EolEcPv2bdjtdjgcDni9XqRSKdE8pV+YJbYZ7+UwFJN+5/mgfhVN06Cqqqky0wndOHtCvV4XzZasHhPozh5IktSW/9MPp99LqaFz66MR9b/1wj0h9Bnbi/HWt0Hsd5I5nU54PB6RnHVQEN3U6XwH1faND9M4eQdJJOKcm1bx05vDJPjNrIeDoNu9YGzPWRePx9uonl7afTcLyOjINe5jtu9RLQiTk5NIJBJQFAWxWAwOh0MkIzYaDdTrdbjdblSrVTidzoEKcBFVaPa9MdTvsC3SYYCeZ7/Jer3Gp2kaHA4HGo0GGo2GpWNaCZOsVqsip6EfbdzMijALNS6VSlBVtW1uWFWM7gmhzzlHOp0WWYGDvAT6OHFK0joIFEXpOgGHqe3Tv2EkcvXK3mWMtcX1H5UgJI2fMYalpSXMzMy0RfUcVJM0WkrdKCfjPoRhOYWp/yoAxOPxtt/0pS8OOy5+GAKfYFXwD0rP0vzv19mqX+TM5r2iKHc9g14gy6vTtaqqKkq99+vDMLPw9QofHUdVVVFNgGB1QbwnhD49vEKhgFarhWg02qb1Wz2GJEmi49RB0as2P435oFoQaebDqjtDPXbNoBf0B/WBDALG9orjybKMlZUV0YquV3Kc1WPr/wd61xAyK3trZn2cBMrIKobhp9GjH8E/iBOX0Gq1DlyS+6ic1hReapWfN4Mx5FRVVaysrMDr9Yr7kE6nxbuqD7HuhXtC6BMY2wvhpLDFQY8xDFiJBjJSMcbvrYyFtPthjdvv9yObzSIQCHSsAUQL5DCEQ7+OJsb2skO9Xq+oW0Shq8MuuNaNbjKDPgvSuH2/x3ozwargH1Tocs4F1XUQq/moaKharSZCzAeZ/3q0Wi289NJLCAQC+Nd//Ve43W7Y7XZIkiSU4FqthlOnTllW1A63bOEhQc9tHeW+BPIx9BL8nSgSKp3aaSwH8cz3Go/L5YLf70cul0O1Wj0Wjb4XGNvLOo5EIpifn0cmk8HGxsaxj5WeBQkOKnkB3Hmm9Fz1n7s966PGsOcUQT/Xu1lQg5y72Wyi2Wx2Tc6yOrajmEN6a+YgCx3ne3WH/vZv/xZLS0uYnZ2Fz+cTXQS9Xi8URRH9Kqye557S9PWw4pU3gjHWNy3UCVSiIRKJdD1eN365UxRFJ3phGGBsLxM4HA6jUCiIeuXGwnLD1PYPMlYKcVxcXMTOzo5wjh0XzKy0Tlqt/n+y9vRzttO86HTMYeGwjq23bI04iJJWLBYtlTy2MrZ+xqFpGra2tmCz2RCPx4WSR5GEnHNsbW0BABKJhODUqSrpIFa6ceG02+34xCc+gWaziWg0KpIYqc8IWUB2ux2f+cxnLJ3jnhL6xG1pmjZwGJvX60Umk7Gc6twNuVxOhNb1+2CBu4X6sJ223c4vyzJCoRCazSZyuRwikciRlDEeBHa7HfPz8/jxj3+MaDR6YG73KGAU7MbwUzOBrxdIh7XQHtXCMky0Wq2+wjQPAopwo4ZLzz33HFqtFk6fPo3l5WUEAgG43W6oqoozZ87ge9/7HlRVxcTEhCirsrm5KSqDPvnkk3dlt9N5eo1BlmVwvldChhzRNPfJgVupVETPAKsy7Z4S+gCEQ1dVVYyNjfX9cthsNsiyfGChz9helMvOzo7IGBzkGMbPRxUfT+ejCWMW3WDUOo5TSMiyDLvdjmq1ek8IfSOMDmCzeHk9JXCY95zmFz1v/fmGZV0aHZGDVIMkHMQh2gtmkTLZbBa///u/j09/+tNQFAW1Wg23bt1CKpVCs9mEzWZDKBRCsVhEOBxGqVQStbBWV1dF6ZjJyUkRfqs/F52HMvyJrqF7pu+cRYEXeoVXn1AmyzKy2SxCodCbK06fQBoq9ch1OBwIh8N9TaRhcqsk+Mm5fK9oTnroaZxOvx/VItQNjO1F9uzs7MDr9R56F63DhBn33U3zH9a9J2GytbWF9fV10YO6VqthfX0dPp9P1HE6LGqxX1AS5DCbhSB+JEkAACAASURBVJvFveut73A4jM985jMIh8Oikqf+PaBIIqfTiXg8jnK5jHq9jmAwCAC4efOmSLqjyraqqiKbzcLr9YrmLpVKBc1mE9VqFS6XC7VaDX6/H81mE+vr6201vgCIbnxkoTcaDZRKJQSDQWxublouNXNPCX0CTYBsNguPx9OXlt1qtQaqw9MNjUbjyMLBDgPdTMODcvv0sgzj/oTDYWQyGVGA716934ReET/DFvzf+c53cOPGDUxPT2NtbQ2ZTAaZTEY4SlutlnAWUjmMfmHU5g8aIkpWqN4SNWrndN5eiygAbGxsiOvTW1f67W02GyYnJ8E5h6IobWPXNA3JZBLFYlF04iN5Uq/XEYvF8MQTT4CxvUjDZrMJWZZRrVaRz+dFxA2dU5IkFItFFAoFMMZQLBbFeFVVRalUEttqmoZ8Pi9av25tbUFRFDQaDdGFzgruSaFPF6eqqvDqW73gw4iiKBaLcLlcfRVtOkmwYj4fRpZuv5AkCVNTU1heXobP5zsynvc40IkaOch9D4fDmJ6exoULF3Dp0iVsbm4iHA6LVqKSJIkcmIOCFvlBF/vd3V2sr6/j9OnTAPY0frJGqeOVLMviu0qlApfLJcZufM8ZY2g2m/jCF76An/qpn8Kzzz7bl8wgaJomyrQnk8k2AU4NmRjbqwDg9XqRTqfh8XiQyWQEP1+tVuF2uwVbQc+42WwCuNMqttVqwel0otVqifpjnHNsbGy0lVOhv4cm9BljTgDPAXDsb/9XnPPfMWzzcQD/CcDG/ld/zDn/z/u//fcA/rf97z/LOf9zSyOzAL2wMgqtTjeAOH1qMDKsMQwj4eu40Ktbj970NfYu6HUP9VTGMO63y+WC3W5Hs9l8Uwt9oP3e6TVm+q0fcM7xwAMP4MEHHwRwZwE9TOiTsayON5VKYXFxEZxzXLt2Dbdv3xbacqvVwtTUFBYXF+F2u+H1etFsNlEqlVAul/Hss892vSZFUfDrv/7rcLlcbfeSEiA7RdDp/S+MMUHppFKptuPrLYd8Po9isQhVVVEsFoXcUVVVlHCpVquilhD9rj8W+a7IwqHfybIY9H2younXATzDOS8xxuwAnmeM/QPn/PuG7f4L5/x/1n/BGAsD+B0AVwBwANcYY3/DOc8ONFoD9I5PIzq9HOSE2dnZGcYQTM9x0o7XC5IkWU42MxbusiKEhknxkNl7LzpzB4XeCWzWL8IKDsNZ2wmDOl4551hZWcFXv/pVfOhDHxKN2TnnoiT46uoq4vE4gsEgstksNE1DIpFAsVi0VGs/Ho+j2Wzi9ddfx5kzZ7C9vY0bN27gzJkzwnqsVCpYXV0VC2MkEmmzfojyocSoWq0msv0XFxcRj8dFAhVVBq5UKlhbWxORflRLjEIv6ZkQnXWYsNIjlwMo7X+07/+z+kR/FsDXOecZAGCMfR3AswC+3P9QzaEXRHp0iotmbK9fbT6fR6lUGlqJg3uZ16eYYivQX59eCNHnw6Z+6Hn3W23xXofe2gI653iY4SjCgI3n6jdah/a7dOkSLly4AEVRcPbsWeTzefh8PpGYRbQOvdsU2tirppQRW1tbkCQJ3/zmN6FpGtbW1qBpGnw+n5ANDocDdrsd73znO9vaNJIWHovFhOD/8pe/jCtXriCTyWBxcRHpdFoEHExNTSEQCCAajeL73/8+QqEQVlZWEA6HhbJFSVZPPvnk8Qv9/Yu0AbgGYAHA5znnV002+xBj7GcA3ATwHzjnawAmAazptlnf/87sHJ8E8EmgvfdlLySTSdjt9rZCVUB7iVJjBx2bzYZEIiH4uWGg0WigXC4PpU4MvQBHtYBomta3ADUKIWD4dV06gUo0HHZ/3Xq9jmQyiVAodCgtHQeBkWo7CWPSQ59rQnO4lzDWb0+huZxzNBoNVKtVRCKRjtm4g1h85LsolUp49NFH4XQ60Ww2USwWEY/HRcHBZrMJSZI6djej+0+RPLIs4/LlyyiXy9jZ2RG8PSVVLS0t4fLly/D7/aJxTqPRQDAYhM1mO7IMeUtCn3PeAvAIYywI4CuMsYuc89d0m/wtgC9zzuuMsU8B+HMAz/QzEM75FwF8EQAuXrxoyZJgjEFVVVQqlbuEvl7L0At/EkgOhwORSASbm5tDiZAgrz5lx91LMCu3bBVm9+wg3LOV80WjUSwuLt5ldg8DRB/pnXKFQgEOhwNOp1O86LIsw+PxoNVqoVKpIBwODy3b2wrI4rFS5GzYC3GvxCJJkpDL5YTA0y9O3awAY5QMZeLqnbPGMVi1Jmh7VVVRKBQEbUN0CmNMFErrRRMZqU1FUfCLv/iLbeO4ePGiOGelUkGpVML4+LjIfD9z5gyAPcWC+HyyXA4bfUXvcM5zjLFvYY+ieU33fVq32X8G8B/3/94A8Hbdb1MAvj3IQLtBn7RgBj3No58sLpcLPp9PxLweRLsmzaBQKBwonPCoNbdhWhX6Y9DzOAyLRVEUhEIhpFIpTExMDO34jUZDJNeQuT09PQ1gL0KLoisokmJ3d1dYeLu7u1hYWIDX6x3KWKyCKDYzoa4XsN1glX+3EvlG4ZV//dd/jUKhgE9/+tNt9BIlNLrd7q6VISkCxu/3i9DHer0uroWEo6Io8Hg8cDqdXRe2er2O3d1dEfEnyzIURQHnHF6vFzabTdSwMbtGvewwU2rM7j3nHLlcDul0WpRz149RVVXUajWR4XtUsBK9EwPQ3Bf4LgDvBvCHhm3GOedb+x9/AcCP9v/+JwD/J2MstP/5PQB+cygjv3NuEeNKK7fZg9drEAQq3QtAxCwfVEjlcjl4vd4DaaDHIfiH5dzTR5wYBf8wF5dQKISlpaWhhhju7u5CURTMzMwIa43GS4k3xn0I2WwWGxsbmJmZuaus7mE9T2O0iZ7nNvqxaJtO0W7doI/WMmu1qd+O/n//+9+PYrGIH/7wh3jooYdw7do1nD17VjhAaZw0ptXVVcRiMTidTtTrdREWubW11VX7LZfLohwKVWc1kwG04NRqNdhsNqiqit3dXfE7Pd9uQSH0eydBr0er1UIqlUI+n0ez2bzLCuSci25dR51oaEXTHwfw5/u8vgTgLznnX2OM/R6AFznnfwPg1xhjvwBABZAB8HEA4JxnGGP/B4Af7B/r98ipOyzQjaSqkYFAAIFAwNTs05vEQLs5SQtGMplsE07GWN9eY1FVFel0uq0A0yA4ak7/MGgYPf0wbDgcDkSjUdy+fbtN0A56HbVaDel0Gg888IBlek5/rmAwiGq1io2NDSQSCXi9XlEX5TAdznrNl3OO5eVlXL16FaFQCO94xzsAQAg54E4fiO9+97sIBAK4ePGiyHq9efMmzp07B03TYLfbxeKxsrIiQiHNKCzjQsLYXnlsTdPwne98B6VSCa+88goymQzK5TJisRimpqZw/fp1JJNJuN1urK6uYnp6GpVKBV6vF9nsXoDf5cuXLS3qFEVDCZtut1uEQtJ7Ts8kHA5DURRks1nU63VkMhlB31GyFBV401tLZuGnRAcai6tRMhY5mI37tFotuFyuY6l3ZSV65zqAyybf/7bu799EBw2ec/4lAF86wBgtgxxvpVIJkUjE1NGnF0bGyJ5gMAhZlrGzs9OmLREPpzcvu6FUKsHtdovFp1+QyX4UOExt1HivhznBGWOIxWKQZVn0lSXhPwgoy3fQdH9JkhCLxbC9vY1UKoVqtSoyNI8KZK1QfZg33ngDr776KqLRKFKpFBRFwc///M8DAF577TXho3jllVfgdruxuLiI1dVVUVNma2sLTqcTPp8PP/7xj1EsFvHwww/j/PnzQgjqrQejJUAUTSgUQqvVQjKZxJkzZ/Dyyy/DZrNhcXERLpcLKysr8Pl8yGazWFhYwKuvvgpZlnH69GkUCgVL95DmL7U9zOVysNlsokgZfW+z2VCpVOBwOOByuVCv16GqKnZ2dqAoCrxeL+r1eltAhl7gm4HkhV7muFwuuN1uVCqVtudD1CCAgep1DQP3ZEauGfRCi2J64/E4FEVpa1BMMGqhtErTw6aXhxyHiqJgY2Oja0N0Og7nHIVCQaR6D4rD1vYpQgI4XAriMI8dCoUQCASQyWSwurqKubk50+fdDZxz5PN5zM3NHWissiwjHo+jWq0ik8kIp2A6ncbq6irC4bCgE3d3dxEKhWC325FMJhGNRkV/YE3TIMsySqUS0uk0JicnIctyxwWJqIK/+Iu/wPnz5zE3N4fXXnsNqVQKhUIByWQSCwsL4JyjVCphZ2cHtVoN+Xwer7/+OhYWFnDz5k3EYjHs7OzgkUcewXPPPYfz588jm81ieXkZrVYLTz/9NG7fvo3z58+35cd0cto7nU488cQTePDBB1Gr1YQf5C1veQtWVlYQj8fhcrngcrnEwrC5uYkzZ86IDPd+4/31Y6CSKxShR3OxVqthe3u7bbGiUhTlcrmt3o0VKicej4v75PF4YLfbMTY2homJCWSzWSSTSXGPqPrmcVa0fdMIfT0Y2wuF2tjYgCzL8Pl8iEQibZOTVm4j/cAYg8fjweTkJHZ2dlCtVsVEcLvdyOfzPc/POYfdbr/rpThpUFUVmUzGlK8eJqy8OAc5ts1mQyQSgaqqWFxcxMzMTF/hnLVaDfV6/cBFvSgZx+FwQFEUXLt2DfV6HVtbW4jFYrh27ZoQrIVCQSTu2O12PPbYY/jmN78ptGiHw4HV1VWRiDY7O4snn3yy47ltNhtisRjcbjdu376N2dlZ4Vvyer2ilozb7YbNZsPHPvYx1Go13LhxA1NTU1AUBfl8HrIsY3l5GU899RQCgYBYxABgeXkZjz32GIB2nr/TfXa73XjsscfAGMMTTzwBTdOwurqKZrOJRCLR5vfopODoK04Ogm7+vU7O12q1imQyiVgsZlr+HIBwBjPGRGBBLpdDo9FArVYTvXcDgYBYwClA4DAVISt4Uwp94M4DbTabyGazwtFrfOBmNWXoQSYSCWxubqJYLIoXmRokdNPCGdsrnFSpVBAMBvuO5tE7Qw9zckiSZJrjcBg47NwDSdprfO90OrG6uiqe4djYWE8zetj9BEhoX7t2DclkElNTU1hb20tXISrA7XYLqzEYDKJWq+HRRx9FKpWC1+tFKpUCY0z0ETCL7tALTLvdjg984APgnOPKlSuCezYLj6RSDAAwMzMDxhhmZ2fbjmfMv6Bj6TOye4WBGs+bTqehaRocDgfq9fqJVIYYY0gkEsjn82g0GnfRhdVqVUTjeDwehEIhUVKBrGZZllGpVLC7u4tgMAiv1yuiBGu1GlKpVBt9fNR40wp9AgnPTCYDSZIQDAbvmmxmiS4kNIgPTCaTSCQSmJ2dRT6fx+7ubteHRgWsiB8dBHw/fVuSpK7mPcU022w2eDwey5OJHFVH6TQ+TJAADQQCqNfrSKfTWFpaEpq/WVQHaXU+n2+oY7HZbPjVX/1VQVlMT0+LxB99MAGNh8Zm1GxtNhseffTRuxYkYwIUzQ1j+Gavhcw457tto58vVuP+OeeCSsrlckOtezVskKxIpVLi3SV+H9i7fsrWrdfrIox0ZmYGqqqKZi+SJIkIJCoPQdaUw+FAs9lEMpk8kgxpM7zphT7Q/jApssBI9XSCz+dDpVIRTjIryTBOpxPj4+OiA0+j0egrrFDTNKTTaTgcDrzwwgviJSPKQlVVuFwuKIoi+Mrbt2+j1WrhwQcfxIULFyw7iUgAHSbHeJQTm7RLl8uFyclJeDwewWGfOnWqbVFsNBpYXl5GIpFANBod+jiotkosFhPOyl6Li5n2203g6+div/x3PzBy+FafKecc29vbqFarIlzzJAp8AvH7AETYKGXWejwe5PN58S4CEGGgVOWTjkFQVRWqqiKXy4mWh1R987iUrftC6AN3hPvu7q7wtPe64Ywx+Hw+pNNpwcelUilRQtnsoXHORSVIu90Ol8vVVgbVCiqVCj772c/iwx/+MCRJQrPZxBtvvAGPx4PTp0+LFoetVguFQgGapqFcLqPRaCAcDmNqaqovoX+QjFyrOAq6yuycoVAIwWAQpVIJq6ur8Hg8CIfDcLlcuH37NsLhMOLx+KGMi4Sw3+/H+Pi4aABzUOd+L217mNditCj65aP1ztLj5rKtQj9GTdNESGc2mxXRQFSigfO9UsedouD0CifVCKIF9LicufeN0AfuPIBisSicXFYEP7VMA/YmQS6X6xrbrte4HA6H0AKscpgulwu/9mu/JqoMSpKExx57TGgY9BLqx6TnWrtlOhqvrVdZ5WGBqIvj0G4Y24vKWlhYwMrKCpaWlsSiHIvFjmQ8gUAA29vbQ3nZ+6FXDnIO4E4OR79lNSgWnbKWT2r/5V6g6pl6S9vsfliRI61WC8Vi0TR2/yhxXwl9YO/mU12VcDhsKZaeHnalUhGcazf+U69lU0szKuls5UHbbDbMzc0BuPOCmxX8CgQCPY9l5VxHUe8DaKfSjkPw22w2BINBcW8PW3Dqz02Zl/l83vI8MEKf5dxt/4MurEZrgq6hn/3r9TpSqRTK5fLA4zgJoHkDtNNs/d5fffnko5p3nXDfCX0AgjJJpVJwOp1tafNm5lkotFdFIp1Oo1gsik42nR5cvV4XXn/yB6RSKaiqikAgIMK2eoG0ikFrqFuBPlvzMEFjPs7KkJSUcxxaFmMMk5OTWF1dhc/nw+bmJkqlEmKxmAguSKfTYq6RNkmlQex2u+i3arTM9HkJB11Y9Rmo/Qon2jeXyyGbzZ54/v6ooF84TgLuS6EP3DG3MpkMxsbGutIPtEKHQiGEQiHs7u6KXpZ6kHaUTqdRKBQgy7LIjuSci9TyXhmGRg7V2LhkmMLfZrMdWdcvGjNdWzqdFl2QEokEUqkUxsbG4PV6oWkaSqUSKpUK4vE4JEkSDvFB4unJ4XZcvXWJYqJooVdeeUWE+VFs/+rqKubn51Gv11GpVHDx4kWUy2X86Ec/EgXB3G43crkcJiYmsLOzA1mW8ba3va3NLzHowmo2v4i7pkQno6+Icy4KFhJ9QVmoI4F/MnHfCn0ChVT5/f6eNVdI2Ph8PiH0Seun0qgUx0//zJI7+uV1jWF1xpez2/a9cFi1cTqBMYYXXngBkUhEUB2vvfYarl27hlQqhXg8junpaeTzeaytrYnMzFAohK2tLTzyyCNtceZWwDlHuVwWtVWOC5qm4e/+7u/w1FNPIR6PY2ZmBq+88oqI5PD7/fD7/VhaWkKj0UA+n8fY2BhOnTqFmzdvCoqRyvFSow89haL30wyiqRsVinw+D1VV4ff7kUwmxYJMDUAymYxoDn4vOWvvZ9zXQp8EKBVrGx8ftzRpKVyy0WgIIaKqqtDszY5B56KMXrNsP4L+5TMew3i8Xk5Y2q6TAKDOQ0cFzjlefvllzM3N4cKFC1hcXEQoFEIikYDf7xcJcY1GA16vF+fPn0cymcTOzs7AAqXVaqFer1uK2DpM2O12/MZv/AaSySQURcH4+DhisZhwdFKc9yOPPAIAIjdjbm4OTz31FOr1OhYXFxGLxRCPx3HlyhURLTZM6O+R2+3G2toaMpkMGGOi0UexWBQWor6o2QgnH/e10AfuTHCqshiPx3vuY7PZRIy8kfvspkmSAKa6PIO+rGYRA51itPVZlmbHsNvtKJVKfSV1GY/d736f+MQnBOU1OTkpOHZa7PRcsD4hiPP+i7aRln/YXbasgDEmqje+8cYbCAQC8Pl8d1mYZhYnhQpevnxZHKtTGPAg2r5xftBnp9OJRCIh2gsSnUPPwmr0yggnB/e90NejUqkIDrPbJGaMidrfrVYLuVxOfN8L5DvY2dlBJBKB2+0eipbULZqIwufMXlCio8j30MlE1wsFfVq+/jzdLBPajygwvQVijDsfJgXTarXQaDSOVcvX+4kYu9MchNL2+4XV67Dq1DVG65BiAkAoJ/F4XOS4UIb4SNDfm3hTCH2j45Mmb78OrX6q3ymKgnA4DM73CjT16wylQlx2ux3xeLytst9hQH9d+mggzjkcDgcajQY8Ho+4l8Zt9SCBb6zP0mlbOo/RSW78Ta+Zcs4FT6wvUWCMaKJa5kSPGJ3FJ0XLJ9D4wuFwX13WOlF+3c4D9HbqmiV7kTafzWZFHZlisQjO7zQlPyn3c4T+8aYQ+gDuKnUQDAZRKBT6ikEn07ufF4uiGvqB/vhU+9vpdB5aWBe9yI1GQySHMLYXO+5wOKCqalsYKWXomjmLu1kUBKNV0CvBR/+ZhHg2m8X169fhcDhEnfyNjQ0oioJAIIBkMgmPx4Of/OQn8Pl8mJ2dxcrKCsLhsEibVxQFzWYTU1NTJ0pIMcbg9/uxtbWFarXac1Eyxsz3cx4rNI9R4LdaLVFrn2id404oGmF4sNIu0QngOQCO/e3/inP+O4Zt/hcA/yP2OmclAfwPnPOV/d9aAF7d33SVc/4Lwxv+HRibJ5NzqR+hXy6X+054stlsCIfDba3X+kWpVGpL2umkGR8EREOFQiGRDk6NJaimuR7G3IB+YCbUex2DFtAvfvGLuHz5MuLxOPx+P3K5HL7xjW+g2WzC7XYjk8mgWCxifn4eCwsLcLvdWFlZwdWrV1EqlRAMBnH+/HmsrKwgnU4jHA7j/e9/PxKJRF/XcFDoFzuza6UKoLdu3cL09HRbPahho5Pg11tXZFlRmWkS8pIkiaqyI7w5YEXTrwN4hnNeYozZATzPGPsHzvn3ddu8BOAK57zCGPufsNcY/SP7v1U5548Md9jtME5kt9vd1nLNCjjnIkmr33NbKefQbX+KINI79YZdroBeeMoMJV7WrKzyQTIPjehnf8YYTp06hVAohImJCUF/EO1EOQXU1HpqagrLy8t46KGHcP78eUHvULNsKuN71B2KjHRjJ8FP/X23tragqiqi0WhPX1K/0FNden7fuChRP1cKPybr77Cb7Ixw9LDSLpEDKO1/tO//44ZtvqX7+H0A/25YAxwE1CvTak0ZegGou0+/IYz6DN1BX0wqtxqPxwVvSg61W7duIR6PY3x8XGhdVPSJXlISeLIsm0Z/kDCs1Wpd6+cf58stSRLe+973CqFJkSrd0CnaKp/Pi76nx4FuYbIExvYK+tlsNiwtLSEUCplSKAdVAPT8vvGYeg7f5XKhXC6Levcjgf/mhCXpxvaaol8DsADg85zzq102/xUA/6D77GSMvYg96ucPOOdfHXSwVqFpmmic0mvC0sspSRIqlYrIpO0HJPQH5eTJJ0AlHiKRCKrVKq5duwa32w1ZlvHiiy9ifHwca2tryOfzmJmZQSaz12M+EAggm82iUqngiSeewMWLF00pFrfbjUKhcKIcm3qY+QUGGWej0RAJRUd9nUaHdDfQ7x6PB36/H7du3cLZs2c7WgYHgZ7fp3urH2MkEkGxWESxWES1WjVdfOg7KmOib9RC1sFR9XYeYXBYkm6c8xaARxhjQQBfYYxd5Jy/ZtyOMfbvAFwB8Dbd17Oc8w3G2GkA/8IYe5Vzvmiy7ycBfBIAJiYmBrgUcRwAaIv80H9vuC7xm81mw/T0NBRF6TtSAsBAETwEilkH9vwK1WoVlUoFX//61/HhD38YyWRS1OYnTT2TyWB+fh6SJIkFzu12dw0DJAugUqmYFnA7KbDqgOyEWq02EFV3HCBNe2pqCjdu3EA2m72rSuqwqD66r+Tnov+TySTeeOMNBINBOJ1OMY8dDgccDofI46DyI41GA9PT0208f7lcRiKRGAn9ewB9qbSc8xxj7FsAngXQJvQZY+8C8FsA3sY5r+v22dj/f4kx9m0AlwHcJfQ5518E8EUAuHjx4oG9RuSckmVZlCNuNBoisQSAKL+QyWRgt9uFhk/7GimbbtEPLpcL1Wp1YHrHeA6v14tPfepTgvvlnIvIlHq9jmq1Kmr46MMlezkDg8Eg8vk8OOeiI9CbDfrM6JMMzveqUSqKInrcJpNJhEKhtnpLwHApFtLO//7v/x65XA6XLl0SfSOoWFooFEI+n0c8HsetW7fwnve8B9lsFqdOncKLL74oIqU2NjZEAEIgEDhRhcVGMIeV6J0YgOa+wHcBeDeAPzRscxnAFwA8yznf1X0fAlDhnNcZY1EAT2PPyXvoIO2Zc45AICCaUDebTbRaLXDORZgihTHmcjnU63VEo1Hxm9Hh1cn0pkYdwxI2ejOcXlKqAW+32+Hz+drOY+VlI84/EAggk8mIdpAnUTjq+eZ+x2e321GtVofuDB8mqJsS0YLBYBA+nw9ra2tYXl7GqVOnhPIxrGvQU0+SJGFiYkLUNtrY2IDf74fH48HZs2extraG6elp1Ot1XLlyBbIsY3p6GqlUCg8++KAImJicnBQWhKIoR1ame4TBYUXTHwfw5/u8vgTgLznnX2OM/R6AFznnfwPgPwHwAviv+xOUQjMvAPgCY0zb3/cPOOdvHMaFmIHCADc3N+FyuZBIJEyrBE5MTCCTyWB3d1c0rKYQUBI8vbhau92ORCKBnZ0d0W7tMCJfaAHotL1+nJ1gs9lEOKRZxc/D0C4HAV1rv4JP36HouK/BDBSt5fF4RFPtVCoFADhz5gyWlpZw8+ZNEbbKGGtz4JuB8huM10v3QU8hAnv39sqVK9A0DWtra4hGoyJEU5IkhEKhtvwTmnNjY2Ntx9F/Hgn8ewNWoneuY4+SMX7/27q/39Vh3xcAPHSQAR4UJDiKxSIYYxgfH28TiGw/5JIKfpl1uKIXqVusMnHq09PTKJVKyGazQ6UY3G634OH19JMekiTh+vXrIh7/9OnTok3gzMwMAGB7e1tUcpQkCVNTU6KRjM1mQ7PZRD6fF30GSBgcF+j59cvtE8XTT5vKYaLbWMnfRH4Hl8sFWZaFpXju3DmUy2XRk7lUKuHVV1+F1+vFxYsXkc1mwTlHMBhEsViEx+NBMpkUmnij0YCiKNA0DYVCAfV6HdPT0211jmiMtJjonbzdhPdIsN/7eNNk5HYDCcpSqYTt7W2EQqE2Rx/93q3oGNEN3QQQYwx2ux3By4bInwAAIABJREFUYBAejwdra2ttL8lBNOh6vS6EmJ76AIC1tTV85Stfwcc//nFsb2/j/Pnz+Md//EdsbGyIxuwvvvgiZFnG+Pg4/H4/pqen8U//9E/Y2tpCsViE3W5HpVJBMBgUSTrj4+N4+umne9b/PywMGs1Dz6HfhvTDgBXrotlsttFqbD+cliqeyrKMaDSK559/HktLS/jABz6AarWKV155BdlsFq+//jpisRh8Ph+cTicCgYCooXT16lXhVN3d3UUikUAul0OhUEAkEmkr98E5R6lUsjzuEd4cuC+EPnCH+igWiyiXy4hEIm1t66wKE6J6jPvQd/S/3W6HoiioVCpt21EJ5n5fsGazKZqzG8csy7KI956fn8fm5iYefPBBtFotnD9/HtVqFZIkiQUpFothaWkJP/VTP4VSqYRQKIRGo4FMJiO4XK/Xa0qHHTXoGvuto6QoCkql0okTZuRXMqNpwuEwarWaoN0uXbqESCSCeDyOd73rXbh06RJarRYeeOABUaiPfD3UwPunf/qn4XA44PV6USqVhDVIfV7z+TwCgYCwFMvl8kh7v89w3wh9oF2AZLNZ07K2vfY3ayRuthBomgafz4dqtdq27aC165vNJra2toTTWC/IxsfH8cu//MvgnGNubg7z8/M9jzc2NgYAQst3Op2o1+vI5/OiIftJwSBOXUpYO2qhT1SJ2fflchnlchmapplaTzabDW63W/RiHhsbQ61Wg8fjgdfrRTgc7nruycnJjr9Rb2fKUi+VSsK6OM4WliMcPe4roU8gmqbVavUl9GlfM07drJiYx+NBoVAQLRllWcb6+jparZaInNA0Ddvb24hGo7Db7SgWi0ilUohEIqJbUSaTgSRJ8Pl8UBRFRO6sra1hfHz8LgrDKgdOWidZD8TjvxlAz4nKCRwnVFVFoVAAY0yUeO60qOp9K5qmifDcblnUVkBBDYwx7O7uol6vC2v0pFlDIxwu7kuhD9zR9sPhsKhHY3Xim1FCZvuur6/j+eefF23mvF4vtra20Gq1kEgk8Mgjj2BpaQmbm5twu9144IEHsL6+jkqlIoq/pdNp3LhxA7Ozs/B6vYhEIuJlvX79Os6dO4fHH38cDz/8cNu4rAp+VVX7XvjuBRBPTovaUcDM0U/zTO+I7wVZltFoNODz+RCPx1EoFA4s9Om4Y2NjaDabUFUVu7u7KBQKb5qFfgRruG+FPgAUCgWUSiVIkiQiVfSceTdY2WZnZwfValX0z61Wq6JtX7VaxUsvvYRyuYxgMIjV1VW0Wi34/X7EYjH8+Mc/Rj6fh8vlQiQSEREeqVRKRH/U63W8/vrrcDqdOHfunHBO66Mxegl+t9uNUqkEv9/fRlEdl+bXLUJKX8isVyQVAOFTIYF5nNqsLMuo1WqCW+8GyjMA9hblYQhlvULgcDhERNaozeH9h/tW6Ou5dwqLU1UVExMTIlb5oC8DhclRk/RsNguv1wtFUeB0OjE5OYmlpSVUq1VEo1FcvHgRmUwG6XQaFy5cQLFYhKqqCAaDbaGkVC/e4XAIQbi+vo6FhYW2a+vFgzO2174vk8kgk8lAVVVxXH1W6FGCoo02NzcxOTmJXC6HaDSKbDaLeDwOxhi8Xi9UVcWtW7cwPj4uiustLy/j3Llz8Pv9AO5kvG5ubmJubm4o2nIncM6FE9Zut4sYfKJykskkOL/T/JxgfDZ0HIrS0j/jYSZpkQIyEvj3H+5boU/QT/parYaVlRVRI79Twa5SqQSbzdYzsmViYgIf+chHwNheB6eNjY22c8qyjIWFBeEjoCgMamKib7Ku7wRG9I2exqnX6wM1OWdsr4tTKpWCoigi9judTos6+4cdp18qlfClL30JH/zgBwWdtbi4iPHxcVHtsVAoYGZmBowxnDp1Cq1WCy+99JIopTEzM4NarYbbt2/j9ddfRygUQjgcFvHuH//4xw9N6KuqKvIennvuOXEfiUen8MxisQi3242xsTHRieptb3vbXYurqqoitDIUCmF3dxf5fB4ej2cobQop0ofm2gj3F+57oW9Eq9VCq9XC7u4uFEUxzeAljb2X0NdratQTNZvNtnWlMjphqfUf/W0FROdQOKj+/L0yU+l7SZLg9XrBGBPx3xTy6PP5LI3DKozZzXQfJEnC+Pg4xsfHMTs7i0ajgUqlAmCvoF06ncbMzAwmJiaEVUKLViQSweOPP47t7W1omoapqSm43W6srq5ibGzsUHnrYrGIz33uc/jIRz4iaLJGo4FqtYpEIiEc9bVaDXa7Hbdu3RLRUvrsabovLpcLmUwGPp8PLpdLJF/V6/WOpaT7BVXEJOpxpPHfPxgJfR30E5+0Ieq4RNEXRBkYKyH2Oq7NZkM0GkW9Xoff70c2m0Wj0RjKy0bCvVqtClpAz3l3e6n5fsckfWlocoJ6vV4UCgWxGAwDnHNUKhVRhoDqvXzqU59q284o3KrVKgqFQluG8NmzZ9uoj0ajgbGxMYyPj0NRFMiyjKmpKdTr9UNN0goEAvjsZz8Ln88n7jtp0eRM1t9nj8cjwknNFnaPxwO73Y5sNguXyyXKIZBCMmjbQj3t5/P5RITQCPcXRkK/CyhbkTGGQqEA4I42ViqV+q5Lr2maqEM+MTGB7e1t1Gq1oQlUqhZKDkzKzKRxm/HH9XodhUJBlGLQgyqPFovFuwq8DYpqtYpMJoNYLIZGoyFoJEmSut5Ps5aO+m1zuRw432vyTsXzJEkSDUGGba3oQbVqzPxAdI/pb7fbbWp1GGsmVSoVEVUVCASgKArS6TSSySQSicTAz4KsQqq2OhL69x9OTgbOCQPRDqVSSdTtIQcvNe6ml9kqZFlGKBRCKpWCpmlDTYJibK+OyubmJlZXV7GzsyNi/PU0D4E07mKxiFAoZNrykTEmaKl+r9UMpO1SGQyfzyfoEFqkukXldALVfw8EAqJVZjQahdfrRaPRQKlUQqPRGOjYVmEWUaRpGvL5PBqNBvL5PABYppmIpqNoLYqntxpdZuX4TqdT+JNGuH8wEvo9QMJfbxqToM5ms301jaZsWkVRUCwWxXGGpW0ZSxa4XC7kcjkhcIgK4XyvDWOtVkM4HO4ap081iYYh9ImCIsFHXL7P50MoFEKtVkM+nxfUR6vVEkXI9GPXQ1VVEXKqL6cNQEQhTU5OIp/Po1arHZqA0wt9Gns2m4UkSYhEIkgkEndlUutBlhj98/l8iEQiiEQiKJVKoi/wsK6BKDw690jw3z8Y0TsHQKFQQLPZRDwet9wcnTEmytHabDaMj49ja2vrUF46EkSpVAoul0tEB+XzeWF1WLE0zEpP9As9vWR2ToqYqlQqSKfTogew3W5HoVAQVhaFQ9rtdnDOkc/n4fP52hrgGPsfKIqCcDiMbDaLVqvVtbDeQaEX+PqErG4JYiR0O5VvoFr1Y2Nj+MlPfgKfzzcUuq1er4vxHmduxghHi5HQHxD0glSrVWxubiIej1sSJoyxtnrvZK4fVv0TvfMZ2OO+fT5fX+0SbTbbgerYtFotlMtl1Ov1riGHZFW4XC40Gg34/X7xHTkvqT6Q2+0W2cR6yoSEl7EWkizLCIfDgvsfpnNaD8rHoAgoK+fodl+pNg61gPR4PFheXhbUGPkIrJ5HXy7E6XSK6KgR7h+MhP4BwRgTxdDC4bBIvqLfuu0H7AlU4vkPC6qqYmtrCzabDVNTU333jz0o71utVgWX3yvyhCKd9E5bvZbscrmgKApyuZygy8x8EWaLqP5eH5a2T8l+VjuS6bV8s+0VRREN7TnnoptVuVxGPp/HxsYGxsfHEY1GAdyZV/l8Huvr64jFYqLeD7C3iJDgDwaDqNVqqNVqUFX1RBXZG+HwMBL6QwAJmVQqhWw2i0AgILjqXvHxnPNDbeJNWj5py4O82HqB0a3RfCdQbftBQw2NsNlsXUNmO2n7RwFFURAIBJDP5xEOhw98buL3XS6XoIy8Xi88Hg9isRhKpRJu3ryJnZ0d0fowEAhgY2MDL7zwAux2O9xuN8LhsHCYy7IsnMM2m010fRvF698f6CkBGGNOxti/McZeYYy9zhj7XZNtHIyx/8IYu8UYu8oYO6X77Tf3v/8xY+xnhzv8kwMSNK1WC5lMBtvb2z1NZ3IKkzA+rPC5cDiM2dlZTE9PDyx4XS4X0uk00uk0CoUCKpWKoHx6QVGUvhzew4Deqa0/b61WG1oETKfzUj9mSm6zsk8v64f6ItM9JwHt9Xpx6dIlnD59Gj6fD1tbW1hdXYUsy7hw4YLw41A2OPVyptDZZDKJWq02cMnvEe49WHnSdQDPcM5LjDE7gOcZY//AOf++bptfAZD9/9l70yC5rutM8Lu57/tWWXthKYIokAABgqBILZQsyW2rTYqyJXom7AhP2/LY3WFr3O2YsCPc0eFFPR094SXC3eGW2yNbbdGOjiFpK0iPQjLDpCmSICUsJHagAFShKmvJyj1fru9l3vlRdQ5fZmVWZQEooADkF4FAVdbLt2W+c+895zvfJ6XcLYR4AavG6V8RQjwM4AUA+wHEAfyjEGKvlPK+7f3Wz+BJMK0XgS2bzYZsNss2d7dD+4d46wMDA8zQuRnvWAouTqeTdYTq9Tqb0Wy0L6Jp0n7uFPSfg/566/X6tq+shBDw+/3I5/Mol8stblWdtu8V5P5Wq9Xg9XphMBi4AcxkMsFut8Pv9+PFF1+Eoih4/vnnMTQ0xMX8WCwGn8/X0hRGTK5sNtsP/A8IevHIlQCUtV/Na//av6nPAvgPaz//vwD+VKw+Vc8C+FspZQ3AdSHENICjAN699VPf2RBCMC0zEolsqJ9OeWwSYqvX67dl1i+EYCnmTjzym9mf2WzmQSqXy6FWq20YRImGqRcZu1OglVSnga7RaGBlZYWL2gRyOlNVFS6XiwNrtVrlBjL9tiR+R0VlusfUA7FRPUTPMOoFFouFGVe5XA6NRgM2mw2FQgFGo5Hd044dO4ZarQaLxcL/j42NoVgsYm5uDkajEaOjo9ylXC6X2VCln965/9HT0C6EMAI4AWA3gP8ipXyvbZNBAHMAIKXUhBB5AMG11/Urgvm11zod46sAvgqsCpXdLygUCsyy2Aj6rs3bVVQjplCnB5mOoT8OtfkDH2kAtZ+PPqdvt9tRLBY3bDiq1+vwer133XaRQINALpfDP//zP2N0dBSapqFWqyEcDqNQKGBhYQEA2E84nU4jl8vBaDTC5/PhkUcewdzcHM6cOYPh4WEMDQ3h4sWL7C88NTWFU6dOcUGaxNJIgkFVVRw+fJgHBGIltaedKAjrGTcOhwNSSvj9flZEJQN0orhOTk7yPvS1j3A4DCklVlZWcOrUKTb2ITVXEnTTD1J6kb/2PoQ+t//eRE9Bfy0dc1AI4QPwihBiSkp59naeiJTyGwC+AQBTU1P3xbeJHpRSqbShxADNoMvlMs8ob8eMq5OKolyT7p2fn2c7RzIaMRqNOH36NAwGAwuWNZtN3Lhxg2eYIyMjzBSxWq1QFAWFQgFut7srz/xuzh71AYtWVBRMHQ4Hrl27hnw+zwGMguSVK1cgpUQmk0GxWGSrSofDgUgkgsXFRSSTSVSrVfh8PiwsLHAjXCwWY6mO6elpLC8v47HHHmPvhnw+j0ceeYTNUqSU+P73v4+DBw/y5280GjE/Pw+Xy8UzeGBVlycSiawT5qP0XS+U4WAwiG9961sYHBxEuVzmz5YUTYnVQwqmQghks1n4fD6enOzbtw+qqm7LZ9bH9mJLSTwpZU4I8U8AfhyAPugnAAwDmBdCmAB4AaR1rxOG1l57oFAsFhEIBDZUzXQ6nVhYWGCWDQWpW2GgCCFQqVRgsVg4xXP27Fm8+OKL+OIXv4h0Oo1kMom5uTn4fD488cQTWF5eBrDK51cUBUNDQyiVSrh+/TqKxSKOHDmCT3ziExxMA4EAFEVBLpdrMZoHVmeq9Xp9w5z2nYT+nno8Hhw+fBgWiwX1ep1TawaDAXv27GHDcPo7FekpXx+NRvHII49ACAGv18vKn1JK+Hw+RCIRluCuVCrw+Xwol8tctL927RrOnj2L9957Dy+88AJWVlbw5ptvwmg0skWiz+dDMplEpVLBsWPHcP36dcRiMfzET/zEOnvOrQyuBoMBv/qrv4pGo4E333yTfZLJlrNerwMAxsfHUSgUYLFY2OyH9Hr6Af/ehdhsiSaECANQ1wK+HcD3APwnKeWrum3+NYADUsr/fa2Q+7yU8stCiP0AXsRqHj8O4HUAezYr5E5NTcmXX375li5sJ0FKiXg8vqHoV7PZxMrKCnK5HDRNa2HZdOvW3AzNZhPlchnhcBiRSAQWiwWpVAonT57EQw89xEGJ0jyxWIyNs6lgC4AboSqVCrxeL2KxWEuAoWKgpmncHdtoNFhJc6vCdHT8q1evckrFZrPBbDa3yBATHfXKlSuIRCIIh8PI5XLw+XwcPAG0mJkUi0UAaKkxtGsStaNTH8BGoHoMpZLS6TS8Xi9LahuNRhw/fhwLCwuIRqPYs2cPHA4Hzp07B5PJxEVakl42mUxMs/R4PB0N0Kl+sNkAq5dcEEKgWq1yuqtUKvGgSMeUclUmmn7Wq4M+SFr8xMZSFIW1qtLpNGq1Gnw+HxwOByvnms1m2O12VCoVNrMnn2T9xOh2r4Cff/55nD17dtOd9jLTHwDwV2t5fQOA/ymlfFUI8bsAfiSl/A6AvwDwP9YKtRmsMnYgpTwnhPifAM4D0AD86/uZudMNFDA7BX19ntTr9a6j+d1KAVYIwTo/xWKR0w579uxBLBbjpid93vZmmpaEEJz7XllZ4VSDx+PpWZ6iHSsrK1hcXEStVkO1WuXZqNVqRb1eh91uh9VqxejoKM6fP49EIsGa+z6fD2azGT6fD7lcDkNDQwiHwyiVShgeHobX6wXw0b2nIN3tPPWfEW230YMrRKvAncPhQCaTYY49sMrYisfjOHbsGO/7yJEjAD6SqdguK0N9M5jdboeqqizJQNAP+gDWzewfpIAPrCruvvvuu8ywGx0dxcWLF6FpGgYHB2G325FKpVAoFDA8PAyLxYLl5WVEo1EWaJyZmcGhQ4eY0ksWp3cavbB3PgRwqMPr/173cxXAz3R5/x8A+INbOMd7HqSj3m0JrjdUCQQCbK1HweNmH3wK+gDYGCYYDHLawOl0IhAIcEGx/VhbOS7lpgcGBlpy6Dd77qQ5XygUOMCPjIygXC6zoffw8DAcDgcOHjwIp9OJd955h89Ffw3NZhMnT57EpUuX8JWvfAVer7claNF5bnau+uCvHyi63TP6zO12O5rNJubn5zE0NAS3240jR46sG0T0q7mt3jf9uXV6r36A068gAXBdp8/c6Y58Po9sNotKpYJisYhyuQxN07hbemlpCT6fD263G4lEggvj7777Lvx+Pw+iH3zwAUwmExwOB0KhUMdV23ajT8y9A9A0rWMOVB9o9a3xVqsV8/PzADqLk90MqE6Qz+dZA4eWpnR8Wvq3C5ZtBiklisUipyV6fd9GcLvdePrpp/l3/T0iPRrqQ6AHZ2BgYJ0hPAW2xx9/HJlMBi6Xi6+vvbuYrr1b7UV/T/RBtj1lQgyZEydO4NOf/jTXVCj46wOzfpV1K6CcfKPR6EqPbdfrp4kGqbD20R0ul4vrVwCYxjs8PMwpMpvNhmazyatTg8EAr9cLm82GSqWCYDDIaTOHw7GtHg8boR/0txmU/2wX+NIH1/aZos1mg9VqZYOVWynmtkPvo1sulzEzM4OBgQHOe9Px6Nx6KRDSrHcjieatggJSJ3RrIupEC6VroXuoaRq+973vYWJigimM+malZDKJUCi0zsC80/np/9cPAgaDAdlsFidOnMAnP/lJAODBKZ/PI5VKMb/fbDbDaDSiWq2uk+0guuxmvrhSSjbP6fYZ0OdIM85SqcQ1mkql0p/lbwKv14unn36ai/mkYWS1WrlPg76X+u8b1WTo7/qB926kdoB+0L8jMBqN/IVoX2Z3muUJsSoktrS0BCklVFW9LYbY7QHFbDajWq1iYWEBfr+faZf0r9dZKD0AOzlwUBMZFaIrlQreeecdZLNZBINBLspFIhH88Ic/xIEDBzjf3gvaB4GHHnoIv/Vbv8UPOvCRiU6lUgEAvPrqq3C5XBgfH8cbb7yBr3zlK8zaITnsd999F5/85CfZKjKdTsNgMHCx3Gq18qrNbrd3deWif5lMBqVSic81m83edVrtvQCqf3TC7Zzs3An0g/4dQPsMbKOAD3w026fAe7uEytqPQbNbTdOwsrLCgl7UQdytm7UdeiG2nQR92sVqtaJcLkNVVYyOjgJYTZ1NTU3B5XIhlUpxc5rX62VHL/rXa96fIIRo4c6XSiU2QCFevcFgwI0bN9gA/rvf/S6cTid745Kb2Msvv8yieVKuiqbF43HMzs7CZrPB5/PB5/Nh37598Pv9Xe8B0FqgvZ0ryD7uHfSD/jaj2WzC4XBwqmIz5geBcsClUmnbJW/pPKg5rFqtIhgMwuFwtMgIdDtfkirYiTNGPd3V4/Egn88jHA7DbDa3FNGGh4eZAlqpVJhqqa9vGI1GTr11WtnU63Vks1kujtN+qEjq8XhgMpnYkNzlcqFarSKTycDv96PZbMJqtUJVVTz22GM4e/Ys00zdbjcsFgtGRkawtLSEoaEh3LhxA16vF9FoFKdOncIzzzyz7trb74HVauXvVLsYXR8PBvpBfxvRTgkk6Cl93YKkEKudk1QkosC6nUGVxN4o+LtcLsRiMeaXd0vhmM3mHRv0CcRk8ng8yOVyCAQC62oDqqpieXkZoVAIFoulRaaC0mzVahWKorDtpR6zs7M4ffo0JicnsbKygkuXLsHlcqFWq+HRRx/F7t27+X1CCBw9epT194kPXywWcfjwYTgcDkSjUVQqFZhMJjaT1zQN4+PjbBTvcDiQSqWYCtiO9qI2WU/SZ7pTP68+tg/3fNDf6UtUsv2r1+sthcnNiqSU4onH41hcXITf70cul9tWah0xZCh/aTabW/oLOp0vFRupGYqCJW3Xrh9zN0HFYZJ61gd9spH0er2o1WrrnMXovVRgLxaL8Pl8LddqMplgMBhw/vx5zM3NseNVqVRCKBRCIBDgHgEAiEQi686RCs/E/CCMjY2xr3E4HAbwkWSEw+HY0H+3vdjcy6Sjj/sX93zQ3+mwWCwol8stD7OerrdZ4Lfb7XC73Vxw227QuTgcDpjNZmia1vF86edEIoHp6WmEw2F4PB5MT09jbGyMZ53kUmWz2TAwMHDHc/96tgTBZDKxmQidD+XRnU4nd6dSI1U7KAWTTqfZjUsIgWg0iscffxx2ux3VapVpstSlGQ6H1/kmdCri6/szOg087e/pJFCor0Xo3096S9vl3dDHzsc9H/R38kyFhLOEECgUCrDZbFs2tKZccCaTWbda2E7kcjkYDAYuaNK5UBB98803MT09jUOHDiEajSKRSODChQu4ePEiLl26hHK5jMOHD2NmZgbpdBqTk5Ob0iBvJ/SDbPtqkBRPs9ksr6jq9To7XVF3cbegL8Sqv4DJZMLi4iIXWPXOVqFQiI+Xy+V4lQCsN2/vtH+61wDYHpH6Knq5dvpfP+CRXEZ7cbePBwv3fNDfydA0jZuhaNZFDz+lPDYzTNE3DN2spMFWQQFHz+nXF5+bzSaCwSA0TcOuXbtw9epVxGIxOJ1ODA4OcrrH5XLBZrPBZDIhFovdsQGrnXHTPrM2GAxsCkOm7foO3V48gYUQbFxSKBRgMBg40OfzeW7CoW3b37tRek+fjslkMjAajXA6nRvy8NvR6XtFdY1SqdTP5z/A6Af9bUR7sUzKVQcj6hztFblcrqVZCtj+FY4+MJFOOx3TYDBg//79OHDgAIQQrBlDIMvIzZRFtxN6fZluM2sK3B6P56a6I81mM2KxWMv+pFz1PC4Wi9yQ10lpdKO8erPZRKlUQqlUYuOUjXjina69G730Vk3u+7j3cfera/c5aHZFDyI9zPl8nvPlG1Hnms0mN/MA6ztMtxM0SM3MzGBlZYWPu9mxDQYDB747HWA61U42GyD1Beytop2/L4Rgeex8Po+VlRVUKpUtDX6FQgGNRoNNzrd6Xt0K7vV6/Y57Ffex89Cf6W8zqAlK37adSCRYnIwe6vbCnX5WTQ5VBKfTuU4VcbvOnYLo0tISNE1jHZFoNNo1NUU5b2p4uhPeq+2NVN2uRVVVVCoV7kg2m80t3c7ERrqVQqe+FlIoFJDL5VCpVHqWmCYfAoPBsI4Wuhm6fSdUVeXPsD3X38eDhX7QvwOgwE+BPRgMIpPJIJVKwWAwsPxBJ7EzCqAU9IUQ3NlJv7fnsG/3uVPwIa19YqyQwFS3wG+1WlGr1XiWW61W0Wg02Cz+dp2rfvXRTfBNiFVLwkKhwGkX4t3rB1y6nm5FXOLVd+uW1n+GZEM4MDCAfD7Pg0yn1YgeRBulwWmr96HT94BqQsTc6Qf9Bxf9oH+HQA8hSQFQ2oY43NFolI0qKI1CQYH0VSgdRIbYwEeKk0Cr/rqewXE7zr09KLabvOivkWC1Wtm0m4IrNRr5/f7bIi/RLlzXaX9SrqqAKooCr9fL7B273c6Bku45nVO38zp37hy+853v4Md+7Mfw/e9/H7/2a7/Gpva0jxMnTmB0dLSluGs0GpHL5RAMBje9Zlp5kEbOVvj03WbxBoMBgUAApVKpRSe/jwcP/aB/h0EzTOAjVchsNsuMGJoF69MLFouFRbiklLBYLAiFQrh8+TJCoRAH0VOnTrGPLQVov99/26ztaNYPrPLvI5EIC4p1CkoWiwVut5s58dRsRKsG8tq9WfQa8BVFQb1eRyQSWceaoff1OvNdXl7GG2+8gXw+jwsXLuCll17C5cuX8bGPfQznzp1j165EIoFLly7hwIEDWFxcxMrKCj772c/yYEfH7gZ98byX4v1mqz16rd+U1cem33QhxLAQ4p+EEOeFEOeEEL/eYZvfFEKcXvt3VggVOKSTAAAgAElEQVTREEIE1v42I4Q4s/a3H23HRdxroJkfPaDUwJVIJDgPTkGbgr/f70ckEoHVasXVq1fxR3/0R1heXkYmk8F7772HhYUF1Go1hMNhnDlzBm+99RYSicRtX8ZTsFAUBUtLS6jVai0ppvZtbTYbAoEAG2zTykVvZ3gzoMawubk5loAgmindt2azCU3TUKvVWoLtrfDUDQYDhoeH8eGHHyIej+Pdd99lc/gLFy4gm82iUCjg1KlTbCgzPT2NWCyG6enpnoOtpmktQb9TEV1fx6DfN9r/vaCG2sf2o5eZvgbg30opTwoh3ABOCCG+L6U8TxtIKf8zgP8MAEKIfwng/5BSZnT7eEZKmbqdJ36/gYJ8JpNBuVzmAA98pN3j8XhgsVjQaDTgcDgQj8ehKAqOHj3KZtxkKVgqleB2u7et2CuE4IEqGAzC5XL1bKAihIDD4WBf160UK6WUmJ+fh8Viwfnz52E2mzE9Pc38dUVRWLiMUmHxeJzTKps1Rm2GkZERfPnLX0Y+n4fb7YbT6cSlS5ewa9cuPPfccyywFwwGceLECXg8HjzzzDNIJBI4cuQINE3r6XqFEJyGofuqT+PpfydsFtBVVUW5XN5ycbiP+wu92CUuAlhc+7kohLgAYBCrvred8LMA/ua2neEDBHpgq9UqFhcXEYvFmPFBwdvhcGBiYgITExO8PRUo6/U6FEVp6XzVWwdux/lqmoZkMol6vc7etL2ApI5J9bIXSLlqzP3tb38bIyMjiEQiUFUVqVQK5XIZu3btQiKRgMvlYp0aANwxq08D3Wy/w65du7Br166W1z7+8Y/zvSgWi7DZbLDb7Thy5EhL3UPfDbvZcW02G7LZLEqlEvsW69N+nVI5vVxLX36hjy3l9IUQY1j1y32vy98dAH4cwL/RvSwBfE8IIQH8NynlN7q896sAvgp01hJ5kEB5/6WlJQ78G6VprFYrwuEwFhcXAdye4m2voACazWahqirn+XuZ7RMdtRvai9E0Q//lX/5lmM3mFiYNFbcfffRRWCwWpNNpXL16FQ899NA6MTJaVel/38r1dnpNVVVks1k4nU4eqNuPSWYnpKW/EYghlUwmYbVaW5rjaODYaqqGzFfo3vflGB5M9Bz0hRAuAC8B+JqUstBls38J4O221M7TUsqEECIC4PtCiItSyn9uf+PaYPANAJiamnrgv4n6wB+Px3uSYAgEAqjX62yzeKegz/MbDAY2YdnsHLr50bbnqukYtG27UYgexMjRNA1Hjx7lWXL7+W4mfNYr6Fi5XA4ej2fDz4lkkC0Wy6ZWeVJKllXWyzsDq/ft2rVrKBQKCIfDGBgYQLVaxcrKCiKRCMs3CLHaxZvP5xGNRpFOp2GxWFruOa2e+nhw0FPQF0KYsRrwvy2lfHmDTV9AW2pHSplY+z8phHgFwFEA64J+H+tBgX95eRkDAwMts71OsFgsCAaDSCQSd/AsW6EoCue6NwM1rbXP6Dfj3G+GTkF9o21uNuCT9wDJT282MAux2q1brVa7+vlWKhVomsa+q8FgkO9DLpfDm2++iU996lO4fv069u7dizfeeANjY2NIJBJQFIW9coPBIKLRKJaWltgSkmwxs9ksq23G43GMjo720z4PEHph7wgAfwHggpTyDzfYzgvgkwD+Xveac634CyGEE8DnAJy91ZN+kCCE4Bx/uVzeUIKBUgh3S1+F0ia5XK4lmHeDyWRCvV5ndgrwUa6aVgo3E5D1khcbnUN7fn+rx8jlctA0DYFAYNOAr2/I6pbaqVarTG+12+2s+knvVxQFJ06cQKPRQCgUwuzsLLxeLxeVqQfB7XYjFApheHgYPp8PY2NjsFqtGB4ehsViQTgcxtDQEEwmExu69PHgoJeZ/lMAfg7AGSHE6bXXfhvACABIKf9s7bUvAvielLKke28UwCtrXyoTgBellN+9HSf+IIEC/8LCAhtmtJt8EGiWl8/nuYh7p1M9lUqlxTaw2/FtNhuSySQcDsdtMX4nqKoKRVG2RZWU0jmkrHmz2jjtxVwpJUqlErxe77piOA0YsVgMv/M7vwOj0YhDhw6tE+HTgwbOQCAA4CN+/uLiIlOCo9EoANy2Po4+7g30wt75AYBNv9VSyr8E8Jdtr10D8OhNnlsfOtDDrSgKyuUyYrEYywnoYTAY4Pf74Xa7kUwmoSjKHT/XZrOJbDbL50Ln3w6DwQCn04lMJoNQKHTLipz6gOz1envSumkv6m6GRqOBXC7XUzqnE8xmM3fa6kH0zE46RTRA0N8oyPeiaUTnZzAYoKoqGo1GP8g/4OgLcNxjoCCVTqe7FuCEEDCbzfD7/XdFY4UGqEwmg3w+v2H6xOFwwGazoVwu3/JxG43GOgbN7QAFSrJUdDqdWw747bP6Tvtv/zzbC9qdKKdbvY6+BEMf/aB/D0IIwSbaGz385Fd7N0CD08rKChRFgZQS+XyeUz/6HLfVauXroTz8zQQ1VVVhtVphs9luW8Cn815aWkIqlYLVar3pAaXTe+gelcvlFtljugc0ELQPGjcT+PvyC30Afe2dexYUjNxud9dl/p3S3e8G/Yy/Vqvh/fffh9VqxcLCAnbt2sVBqNls4urVqxywPR4PxsbG1jVBbYaNtGd6fe/8/Dzm5uawe/duFmar1+twuVyoVqs4d+4cRkZGWNYhkUjA6/XC5XJhfn4eqVQKu3btgtVqbQngmUwGqqqy41ipVEKhUMDVq1cxODjI+9cL0+llOKhwTMVaurdb4errxfn6eHDRD/r3KIjOqWla1zxwpVLhot3dgslkwjvvvIMrV67gmWeewczMDIQQuHjxIqrVKsbGxrCwsABFUWAymdBoNBCJRODxeLYU9KVc1cq/Ge3+M2fOoFwu48knn8TCwgKSySRSqRRKpRLr4FutVuTzeVy/fh0jIyPYu3cvnE4nTp48CVVV8cQTTyCVSsHhcOCf/umf0Gw2oaoqG6oUCgXMzs4iGAwiFAohGAzC4XBgfn4eRqMR5XIZc3NzHMy9Xi+MRiNSqRTMZjO8Xi8MBgNKpRKOHj2K8fHxltVSL5/xraSG+rh/0A/69zCazSZqtdq6Rh8pJarVKjKZTJd33jk0Gg0cOnQIU1NTiEajmJqaYoZPvV6HzWbDY489xsGIBilS5OwVdC+66eB3gxACMzMzyGQyePLJJxGJRDA6OoqVlRWuSTQaDYTDYXg8HpjNZrhcLk7zhMNhqKrKngiJRIK9d0OhEObm5uB0OlGv1zE4OAin0wlVVeFyueDxeOD1etlPd//+/Uin06wd5Ha70Wg02GwnlUqxuYqeytkr7pZ1ZR87C2InjvpTU1Py5Zc36gHrAwDPCKPRKAdNTdN4lnq3Z/ntEEIgFArB5/O1SAnQ3+j8l5eXYbPZYDQambO+mfY+6Q4RRXEroJ6C9kIpnU+xWEQgEFinZqln/tB1kJIlXVu74breK8FgMLCJPJmm+Hy+ltm73vCEZvZGo3Hd8egeboRqtYobN25s+f70cW/g+eefx9mzZzd94Psz/XscZMpiNptRr9exvLzMnro7KeADq7PxVCoFk8nEdNNGo9GiL18ul+FyubhjlTRtbDZbR4oq4VaKlEajsaVBjM6l/Xd905ueCqlHL7/rAzn5J1ssFnZHowGBjtl+rp32R+ez0T2g/fbz+g82+kH/HoZen8dms0FRFKiquuOCPUHP6DEajTyDpyBIeXmHw8Gy0haLBQ6HA7lcrqt8AXDrzJR26YZqtYq3334bfr8fwWAQjUYDFosFiqKgWCxyXwF9BiSx0Iv8hH6A0VNwKTW1VSqo3mpzo/y+oigolUobitz1cf+jH/TvcVB+vFwu3zRz5U6CguT8/DxisRjcbjenUwqFAsxmc0tQomtyOBw9BywyjSc1y17vCUk3fPOb38QXvvAFNmD5u7/7OwwMDCAUCuHDDz+Epmmc19+1axcuX76MUqmEp556Co8//vimcgztOXkK2PrZur7gutHqRk9vpZpIp1QY6QT1Kn3dx/2LftC/D3AvBHs9KKAlk0nuytUrSLaj2WxCURQ4HA5omtZRv0Y/089ms7BYLKjX6/D7/bxq6PXc7HY7yuUyp1KmpqaY+79//36YzWaYTCaYzWYYjUZmGW2l+Nwe4H0+H3dbkx4/1WVcLleLTIWeitspBdRpxq8oCtLp9Kbqnn3c/+gH/T7uCiifv7y8jHg8zjn7TCaDer3eEqhVVeWiKEkGtxu26HVojEYjvF4vcrkcarUajEZjzybsLpcLv/RLvwRgNdjrPXgrlQoURYHf72dqaKPRYNvHzRyp2ovX+nths9nYFY2YV/V6Hc1mk9NJDoej4z46SXHoA7+UsmUQ62P7sdkq7W6iH/T7uGsQQjDbyOv1ct68Wq22qD9SzwGxf6rVKouTUVCr1+stqZ9yuYxqtYparQZFURCNRnng2GgAaH9d3wRFnbjFYhF+v58bpkjymszeO+27PYXT6bgUyN1uN1wuF/cdkLxEuyLmZvvSF4wdDsem0tx93B7oWVY7sQu6L8PQx11HsVjE4uIiDAYDarXaugYrcgbz+Xwtsg1Ec6RZMc20nU4n0uk08/0p2JM3QaFQ6InBQjNk0quhGbkQAplMhhunPB4P3G43jEZjR3tKOkcKBrQ/TdNY/Ix+zmazXLSm+0A+wslkklc9qqryoKY3gW82m6jX68hkMiiVSvw3osD2ceewUwfZ/ky/j7sKmpUGAoEWb199ekII0ZI6MRgM8Pl8bKxOBUri1VMDEy2xzWYzzGYza9WTLILP5+s66yd+Pr3H5/PxTNvr9bLtIb2fgm+nQunZs2dZeiKTyaBSqSAYDEJRFM7Z02tzc3MwGo0wm81wOp3cDKZpGrO0hoaG8O677yIUCvH7yZCGcvaTk5Mol8tc0KZ/xDRqp6iSlaKqqv2O3VsEfafpO7jTAn8/6Pdx10GMHvq5vQmq0/YWi4UbsTRN4zw4NXRZLBYOalQEJV9dj8eDdDqN5eXlFm8CmtnXajWmjkYiEVSrVWSzWTgcDpZVaGcRSSlbrA3pNWB10KnVajh79izK5TLm5+fh9/sRDoeRTCaRz+exd+9eTlc1Gg3MzMxwwH788cd5xn7u3DksLS1hbm4Os7OzsNlsiMfjsNvtmJ+fh9lsxp49e2C322Gz2VCtVpnd5XK58M477yAcDnPXcKPRgN1u559p0LqbZjz3C6rV6t0+hY7oB/0+dgRIaIxmzr0EHL10g9/v5+AtxKrpDBV1yZ2rUCjA4/FwbaBQKKBer7OwGgAUCgUu1FIPgcvlgsPhQKFQgKIoHVk61FylF5F77bXXEA6HMTk5Cb/fD5vNxoVlOm99oTgQCCAQCMBsNuOJJ55AqVRCrVaDz+eD2+3G4uIi9u/fj1qthsOHD/P5UWqpUCigVCpx4DYYDHA4HLBYLPjLv/xL+P1+DA8Pw2g04o033gAARCIR1Go1WCwWXL16FUeOHEGpVILL5cKePXv62vs3iZ02u9dj06AvhBgG8C2sumBJAN+QUv5J2zafwqpN4vW1l16WUv7u2t9+HMCfADAC+O9Syv/rtp19H/cFaHbbHuQ7OUy1g7qR2w3QPR4Pv79er2NlZQUAeGBoNBooFAosYQGAJRFIklp/PkajEQ6HA4qitBRI9ddAwZ4GnUQiAZfLBa/XC5/Px9ttBLfbzT8Hg8GWv42Pj3d8D12n0+lErVbj9JZe8mFqagoGgwGhUAhSShw6dIitFZeXl1Gr1TA+Pg6j0YhgMAir1do3TL9P0ctMXwPwb6WUJ8Wq3+0JIcT3pZTn27Z7S0r5Bf0LQggjgP8C4LMA5gH8UAjxnQ7v7eMBx83aJVJhk0C5ajI5aTabcDqdLGqmP4a+YNy+EgBam6QoPWQ0GpHNZtcZ1FD6hY5pMpnw0z/90/B6vR39AToNGr2AUlAWi4XrGPru3nK5zHURff/GsWPHoCgKlpaWAACxWIz3OTQ0BAAtBivtOf8+7h/0Ype4CGBx7eeiEOICgEEAvQTuowCm5aptIoQQfwvg2R7f28cDBAqaeh2eXmC321Gr1ThgK4qC999/H4899hgURYHL5WLuu57502g0cO3aNWSzWaaLLi0tIRqN8kw/HA63zOpJamFpaQnNZpPz5pRaoTw/FfFoVt2+MugUUDcTTaOBo1ar4fd+7/fwUz/1Uzh27BgPSPl8nhu7KL2j3xfp+5DIm/5vnRhHfdy/2FJOXwgxBuAQgPc6/PlJIcQHABYA/Dsp5TmsDg5zum3mATxxU2fax30NYsv4/f6WmfZmejLE5CkUCigUCpiZmcGlS5eQTqdRLBZ5IEilUrDZbIhGowiFQrh+/TpmZmY4NRSLxZBMJrkgGwgE8PnPfx7f/OY38aUvfQkTExPcnBUMBmEwGJgaSakUu92+4bnqr4vQqRO5G88fWK0dfOUrX+HZOQ0WJD3h8/m6Fr/NZjMsFgsqlcqOpRP2sf3oOegLIVwAXgLwNSlloe3PJwGMSikVIcRPAPg7AHu2ciJCiK8C+CoAxOPxrby1jx0IfTqj1+BC/rbUjUupFTKK2Sjwezwe9q997rnncPHiRZRKJYRCIUQiEYyNjcFisfDM/6GHHsLu3bv5WIFAYJ2om8ViwfDwMLNbisUii6/98Ic/RCQSgdfrRTKZhMvlQrlc5saqXC7HncPnzp1DoVDAQw89xNdDuXtVVWE0Gjnn337v9NdI9+TQoUOQUiKRSGB+fp6vMZ/P4+rVq4hEIjCZTFheXmYtI/JdSCQS8Pl8TF3tlHrq4/5GT0FfCGHGasD/tpRyndC9fhCQUv6DEOK/CiFCABIAhnWbDq29tg5Sym8A+Aawqqff8xX0sSOx1a5E6s7N5/MIh8Ocj+51wDAYDLDZbAiFQvB6vfD7/Xj00Ud55ZDL5Zj33gnlchl2ux12u52LohaLBV/+8pehqioymQxr4BA9NJPJoFwuI5vNYnR0FAMDAygWiygUCrhy5QpqtRo+/elPY3Z2Fs1mE8ePH0cmk4GmaUzXHB8fx4EDB3rqtG3H9PQ0RkdH8d577yEajWJhYQGVSoVrFR6PB/v27cPZs2dhs9lw6dIlLC0tIRKJwG63IxaLYd++fX2GzgOGXtg7AsBfALggpfzDLtvEACxLKaUQ4ihWO33TAHIA9gghxrEa7F8A8L/crpPvY+dCrAmXmUwmlMvlnt9XKBTg9XpbZvs0y202m8hkMmg2mwgGg9yQRPINtVqNC7gUwAnUldtNH4dmxHoP23K5zCYleq0fo9GIQCDADVljY2MYGxuDyWTC7OwsNE1jR6xGo4Fdu3ZhZGQEMzMzvGqgfTkcjp5E0OSaG5rFYuG6x8DAAK5duwaXy8V+ycS6MZvNCAaDGBoaQiqVgtvthtfr5fOiVFQvDKk+7g70n43euKfbtr1iU+csIcTTAN4CcAYAJR5/G8DI2sH+TAjxbwD8ClaZPhUAvyGlfGft/T8B4I+xStn8f6SUf7DZSfWds+59EEfe4XCgWCxuiZ1it9sRCoVY8oAKmKVSCdeuXUOhUIDL5eI8uKqqiMVizHOnoEgPjaZpzLjpFvT1Ym56Zg4xctoLsXJN+z+fz7ccs5O+DukA+Xw+lmumLlzqJiauvb45jfYjpUSpVEIqlUIkEuG+AlpNqaqKYrHIvrr699L+9AEklUqxAJvJZNrS59PH9oA+c+rGJkkNi8XCq89yucwaVJ0E9770pS/hzJkzt+6cJaX8AYANdySl/FMAf9rlb/8A4B82O04f9xeIC5/P51us/3oJLpVKBYlEglMQRqMRJ0+exEsvvYSvfvWr3JlKjVLZbBYf//jH4ff7mcJJx1lYWIDRaITf799QS95oNCIUCiGVSrW4een57u0FWOLA66UcOunbOJ1OXqVIKTnAO51OOBwOThcRtTSfz8NiscDr9aJUKmFmZgY+n49XIVSIJdtEmt2Xy2VuHGtPF+lZRG63G8ViEfV6fUM3sj62H/pgHwwGWRiPJjT675Omacjlchz4S6USgM4TjY3Q78jtY9tAMxL97LWX9wAfGZ1TsJ2amkIkEsHg4CCGhoYwOjqKGzduIBQKwel0tujxkAKn0WiEzWbj4vBGDwY1cZH0Qfs56c+fHjKr1YpSqbROCroTKMADaJmN69NglUoFuVyOJZRTqRQPcA899BCOHz8Oq9WKdDqNaDTKAxUZpJB2jt1uRyAQwODg4DpDGmIZRaNR1ubpp3fuDPQrOCFEi8YSucXR59DexwGspiBDoRDva2VlBV6vF5qmtaQMN0M/6PexrdAHzE6zl41AwRAA56NpxupwOLibVh+wAoEA0uk0Sy0TBbMbDZIExjKZDBqNBiKRCBKJBCKRSIuUMXWnbrXATO9p17hv/7vFYmnpBHa5XKjX6zAajRgaGoKiKJibm8O+fftgMBhY8mFlZQUejweLi4vYtWsXFhcXIYTAW2+9hV//9V/Hvn37+Bh0zWQ+D4B1/PUrsfZBTu8h3Gw2+526m4DuHX3WtBKkWgrVZfT1mV6/T+0rOIvFwjWhTgNFJ/SDfh/bjo1mLxuhU0dotwBKAVyfC200GqhUKmg2m6ynoz+HWq2GXC7HVE5SovzBD36Az33uc7Db7Th58iRbIyYSCYyMjGB+fh5utxsTExP88PZ6HzrNqkmHBwBLKFutVn6Yjxw5gkajgYcffhhWq5VTZoqiQEoJr9eLSqUCo9GI/fv3w2Aw4Omnn+5KfRZCYG5ujlNJdOxgMIhcLsd6Q6VSiQfdUqkEi8WCUCiEaDTaD/xtoEBvMplYq4m+b2TiQ7gdq6pb6ZbuB/0+7hi2+mXf6Ivd3rhVLpc5MPn9fn7IYrEYd+xS6oZy58DqTLedI086QJcuXcKbb74Jq9UKq9WKgwcP4rXXXsPw8DCuXbuGcrmMXbt2tbx/s2vvlE6p1+vI5/O8HQ1ABJJEtlgsKJVKLEVNqwJqJrNarchms11dsvSz94GBAeRyOaysrMBqtSIajSKZTGJlZQWKoiAQCDBbaGhoCH6/n6mfAwMD/aC/Bn3THOksdeqIvt2oVqtMdNgq+kG/jx0HfZG0U/cqsF7gDFgN4KQ7QyCNGmrKqtfryOVyPOPvtPoQQuD1119HMBhk85Zms4mFhQXE43GMjo7CZDLhH//xH6GqKuLx+JbYSe0z/kqlwnRLTdPWdcvmcjlmQ+mDCuV36ZyllAgGg1wATqfTCIfDLSmE69ev48UXX8Sv/MqvYHx8HIODg9z8RkYumUyGtfr1ueeRkRHup+jjI4aa3++Hx+PpmEZsNBp4//33EY1GUa1WmUpLEt4Oh4MVWO8U+kG/jx0JKkbqA325XIaiKDCbzeyIpeeat0sVE+hnEl2z2WxQVbVjAVZKiS984QuoVCpwOp04dOgQp30oreLxeLB//3587nOfg8lk2lQqQn8eBoMB1Wq1pWhHAxw5ZLWDcvybFYspQFMOngxT9HC73ZiamoLD4cDc3BwURWGpikqlgnA4jKGhIR4IaHCia6R9U48EGdm43W7elj4T0vnRD3D0OZVKJbjdbh509fTaewG0aozH411JAm+++SaklJiensaVK1dQrVbZ6Ia0kGq1Gnbt2oVPfepTWzo+rerovm8F/aDfx44CBZVQKAS73Y5KpcLBltgLlUoFKysrPLMni0CHw8HFxo2W2ERz7BTwiVLZvmKQUsJms3Fg1gcxAC2DzUbBv1qtIpVK8blS6qbdIpJAdYpe6gYUNIUQbODePviFw2E899xzkFLirbfeQq1Ww7PPPot8Po+lpSWYTCZks1lomsaBP5vNwmg0YmJiArVaDadPn0Y0GsXk5CROnToFKSXi8TiklFhYWIDX64XT6eR7BoBpqLFYDKVSCTabDUtLS5ifn2eROJfLhXg8fs+kjqj43qlGI6Xk+3nw4EEUi0VYLBZkMhm+B9QA6HQ6ez5mOyniZnL7/aDfx46B0WhkzRyDwYDPfOYzaDQacLvdTEsjNczZ2Vns27cP9Xod09PTGBwc5OCZTqc59UGqmoRugmR6Hnunv1NqKBgMdlxFUHF5M1popVLhFczly5dRLpexb98+5t8DgKIobGSiaRqsVisURWlR0Oy2/2QyyQOJvtlLURQAqx3AlO752Z/9WZ7FFwoFRCIRzM3NIZVK8aqhXq9DURQMDQ1xL0Cz2UQul0Oj0eDaQLlcRi6X40Kmoii8MiO2FQCMj49DVVUoioLl5WUsLCzg4YcfxvLy8j3l1EW9HN2+S1JK/MzP/My69ORGK9FuoHtC+wVWC+t2u33LTDKgH/T72EEgH9if/MmfxOnTp3H8+HGMjIzg2rVraDabmJubQzweR7FYRKVSQaFQQCKRgMfjQaFQwI0bN+B0OuHz+XDmzBksLi7C6XSyZEIymcQLL7wAj8fDeXN9t2qnGgIZrpPEQyeJZKPRCFVVkUqlmD/fCUR3tNlsKBaLLDD3+uuvc7MN8eyJi59Op+H1ehEIBDA0NIRHHnmk6/3LZrPcnUzXQ9dQKpW4r4AMZogiSu5bNpsNXq8Xe/fuhclkYh9hGnioF2JwcJDfPzk5yV3BlPKxWq1QVRVXr17FoUOH2LqSVjahUAj1eh1DQ0M4dOgQrFYrdu/ezU1wOx0b9TV0+y4R9N3i+u2B9V3U+u3odfpMSbRvq4w4oB/0+9hBIPu/RCKBixcvwu12QwiB2dlZmEwmphPu378fly5dwvLyMrLZLEwmE+bm5tjLtlqtckHSaDRidHQUx48fRzqdxl/91V9hbGwMBw4cwO7du1vy0J3wox/9CHa7nWe95M1brVaxvLyMSqWCeDyOcrmMP//zP8d//I//EYFAoOMDTysJmularVZcvXoVbrcb1WoVgUAAbrcbJpMJXq8X9XodHo8He/fuZUG4bqAcM6WgALDGPrDa52CxWLgorAdxyPVyDJqmwefzcTG3k+Z++2uUlqnVahBCYM+ePcyEopUDbUODDW1/L1RhckMAACAASURBVIFSgO0pt80a3Tp1SXciKrQ3cbW/h6Q72icXPTdA7sSRta+982CCqJc3btyA3W7HyMgI5ubm4Pf7mW8fjUYxPz8Pn8/HAc3v97O+DuVKBwYGIMSqjk40GsWFCxcgxKoP7fHjx5FMJvEbv/EbzLjotkx/7bXXoGka0uk0FhYWMDw8zM1R+XweDocD4+PjmJychN1uRzwe76iLQg9sOp3G5cuX8e1vfxtf//rXuZu4ncJJYm+UTqIA0S2gNBoNpNNp1gGiTmGz2YxsNotwOAyr1cppFKPRyKmVUqnEdpLtM1FgNd1EHaOkyEnidcTmoX2qqsosJH1gp1XO/eDGRb0RRA+mz0RvT7kddE1KwzUaDfh8vpagL6XEY489hlOnTm164H7Q72NHQB/UKHcdCoV67t4lLC0tQUqJgYGBdX+jmTY5Z9nt9g0LsBSkhRAoFouYmZlhZy39CkEIgYGBAVit1o6zLf0SnoxY6vU6BgcHAbR2+eZyOWiaBpvN1mL0vhkURYGmafB4PKhWqyiVSggEAiiXy0in0xgaGuKZdrVaxQcffIC/+Zu/we///u/j7NmzmJ2dRSAQYPN2j8eDYrGIcDiMDz/8EEIIRKNRloTevXs3pqenkc/nEY1G4fF4kEwmkUgkEI/HeUAsFouIRCIAVk3Y9UJ59yqazSZisRiq1SqEEHC73bDb7ezXfLsCvr7ORLLjFouFV8D67arVKo4ePXp7BNf66GO7IaWE1WpFJBLhZat+hrwVdAr27UVaPWuHcqQUiNpnaWROTmyfQCDQkbFB6PS6/jVyryIJCf2xgVW2jl61s1fQvjKZDFRVZU0eomEajUbW+jcYDDh06BAOHDjAukRTU1MoFotYWlpCqVRiqYZIJIJoNIrFxUWWbpibm0MkEoGqqlhYWIDZbObUVK1WQyqV4tUDKYzSdRPb6l4GDfbUmZxKpXiwjsViPXdobwQpJXK5HKe+jEYj93J06gVIpVI9p3f6Qb+PHYH2fPR2gR6MVCqFDz/8EFNTU1zYJKojdfaSlAPwUQ46kUhgdHSUqaWlUgm1Wg0Wi4VTNRvBYrEwJ57YF7RvKojezEyR6K2k1kgrCo/H02IST527+sHtwIEDzPgpFAqo1+uoVCrYu3cvewxQ/QNYZeDY7Xa43W7s27ePqZl+v58plxTYq9Uq5ubmMDExAYvFcs/w8HsB1Smi0Sj3fXSiym4VjUYDiqJAVVVEo9F1x9SDBoeteFb0g34fOwKlUgm5XO6WH5jNUK1WkcvloKoqSqUSpqenMT8/DwCc53Y6nXA6nXj22We5kYZm0lQoNpvN3GTk8XiQTqfZP2AjCCHg9Xo5bUSt9AaDgVNT5O27lfsghOBVCUnw6gM+bVOr1TitVSwWAYClno1GI6eo8vk86+63n4cQAtVqFcBHgyj9rt8GWFUX3b9/P1RVvedn+IR2Rg01qzkcDh44t/r56fddLBa5WLsZBZjIC1vB9k6r+uijB9CDQ0vk7dg/HcNsNrNb1fDwMCwWC6xWK8bHx6FpGlwuFxtX6LX0KfCTEFmhUECxWITP54PNZttUeC2TySCRSDC1kXLgJB9NPQjBYJANY0j6WNM0LCws8O/0Hiklbty4wcqaNJsnwTmigOqbzprNJhYXF1mKgvoaCoVCS32DLCf19MGbAa1e7idQ0bodQqx6IpOj2lZAnys1xsVisRaZjU7bU79EX0+/j3sSQggOfL3qgt8MTCYTd9sSy+TgwYMAgEcffbRFp6YTJ99kMrGHr/5vROmk1QDtn2Z877//PnK5HOLxOOr1OtxuN2ZnZ+H3+zE+Po6lpSW4XC5cu3YN4+PjuHDhApaWlhCPxzE2NoZ33nkHIyMjAIBr165hbGwMIyMjeOmll+D1evELv/ALAIBXX30Vs7OzePbZZ/HOO+/gqaee4uYsv9/PLJpcLseOXZqmoVgsolarIRQK8bX5fD6euW5ERXzQQJIZQOemPqfTiUwmwzpJm83W6R4LIXhCstl7aDLSvsLqBb145A4D+BaAKAAJ4BtSyj9p2+Z/BfB/YtVhqwjgV6SUH6z9bWbttQYATUp5ZMtn2ccDgWazyU1E2xFg2ovDFKxrtRrMZjNMJlPXAqq+katTVyXl1KlzluoDbrebG7IOHDiAubk5nDp1CgcPHoTVakUqlUImk0Eul8PY2BhmZ2dhsVhQLBaxsLAATdPYDOXq1avwer1YXl6Gw+GAxWLBL/7iL7ZQIx9++GEMDg4iFotxh+2VK1dQKpWQz+cxPj6OUqmEoaEhXL9+HSaTiVk2ExMTeOaZZzhQkRdwvV6/qeByv4Iku+v1OprNJruV0YqIZJXz+XxLI1ynfHw+n0epVEI4HN6QIKB/D33/aBW4VfTikTsAYEBKeVII4QZwAsBzUsrzum0+hlXj9KwQ4l8A+A9SyifW/jYD4IiUMtXrSfUpmw8mKAgPDQ3d9sDfKVBrmsYpE5JZIFbNRudI/3fizutz3KQZVK/XOZVCVEYSfms0Guz5C6wGFFLJpLx7NBpl2QObzcZ6OOFwGC6Xq2MncaVSwfLyMlRVRSKR4HswOjqKTCbDA1y9Xsf58+cRiUQwNjaGycnJlhUODcRLS0tbTiPcjyD6pMPhwPT0NLxeL6ewiAZM21UqFVitViwtLcHn88FkMmFiYgIOh4P7Tmw2G2w226ZiesB6GQdN03D58mXuNXn++edx9uzZ2+KRuwhgce3nohDiAoBBAOd127yje8txAEObXkEffbSBUjzJZBLxeLyrCNnNoj1FoU/11Ot1LC0toVarbShz295spadc6pt0yJFKv43ZbOaHX99d6ff74Xa7AXxEGSXXLwoQJpOJheCINaSnQ+pN0SmdMzIyAqPRiL1793a9nnK5jIGBAUSj0Y5pNYPBAKfTyV7EDzIoFfPHf/zHnE4rl8s4c+YMqtUqdu/ejevXr8NsNmN+fh4WiwXj4+NoNpu4du0aMpkMbDYbJiYmuLmq1z6MTpOMarXKstxbwZaeKiHEGIBDAN7bYLN/BeD/058vgO8JISSA/yal/EaXfX8VwFcBdHX86eP+hxAClUoF2Wy2Jb+83SiXy/D5fD3NuPSo1WrMfCHOPz2YNCvUF3gpMNOyXNM02O121tGnugYt9Z1OJ7LZLLxeLzODqNBK8hDlchmFQoHF5OhfrVaDyWTaNK9MWkTdQHLS+Xz+ntDG2S4IIRCJRPC1r30NIyMjTKscHx9no/tcLodkMonPfOYz/BlTgb3RaCAcDt+0+Ql1+wJAoVDA4uLihtIc3dBz0BdCuAC8BOBrUspCl22ewWrQf1r38tNSyoQQIgLg+0KIi1LKf25/79pg8A1gNb2zhWvo4z5ELpeDzWaDy+W6rYG/W0GSeOpbgaqqeOWVVzgdRYYY6XQabrcby8vLSKVSGBsb4+3NZjOGh4fxwQcfsKzEnj178Pbbb2PPnj3I5XJYWlpi+iXp9ZPIGc02iTFEP6fTaWYGER1VURQ0Gg3E43HuCZBrAmzVahVOp5M9BdppiJ3uj8Vi4S7UBxG0MiRtpU6SyG63G0NDQy0pMkVRkEqlMDIyclN9KO15/HQ6jVwuByHETa2Ge3qHEMKM1YD/bSllx2S7EOIRAP8dwL+QUqZ1J5xY+z8phHgFwFEA64J+H30QaGa0vLzM0gK9dKhuFLhon90ClsPhQDKZZNXMXuHxeHDu3DnUajVUKhWMjIww9ZKW/fl8HslkEqqq4pFHHoGqqlhaWsKVK1ewf/9+OJ1OLCwsIJfLIZFIIJ1OY8+ePchms7Bardi1axf+7lQC//f3LmMxX4XPIvHchMALT+7GG2+8geeeew7JZBLVapWDvl7OOJVKwWazIRQKoVQq4bXXXoMQArFYDE6nE6lUCkePHuWBgVYZ+nt1swHmfsNmQbtTusbhcMBut/MAu9VBU796pDoP0XZrtdqWJ0a9sHcEgL/AaqH2D7tsMwLgZQA/J6W8rHvdCcCwVgtwAvgcgN/t+ez6eGBB+f2VlRXWaO9UMKVtgdVcejKZhMvlaimM0qxW/179jF+fEimXy7Bares497Q81wc+g8GAp556CrVaDYqitDTqGI1GTE5OYmlpiU1FDAYD0/j8fj+eeOIJnjF+4hOfgKqqmJqagpQSgUAApVIJlUoFb8/X8J9ePoNaY/Was3WB/3GxCVW9CHcuh1deeQWNRgMTExOYnp7G7t27USwWWTI5m83CbDbj8ccfR6VSgc/nw2c+8xnMz8/j+PHjSCQSKBaLCAaDGB8fZ2qo/v7qexQeRFDXMbB1aRAhVoX+qA/F6XTe1GqJUoaxWAzFYhE2mw25XI59GHpFL0P3UwB+DsAZIcTptdd+G8AIAEgp/wzAvwcQBPBf1y6GqJlRAK+svWYC8KKU8rtbOsM+HlhQEC0UCuselPn5eQghkEqlEI/H4XA4kMvlUK/XUSwW4XA4YDabWSLhxo0bXEA1m804f/48HA4Hs1XMZjMKhQLPrmmQaTab8Hg8uHDhAv7+7/8ev/mbv8l5f9KX3+gBnpiY6Dj7I2epZDIJt9vd0ohDKxJK8fxvr7zOAZ+gwYDvzDTxq8Ne5HI5DAwMwGg0Ynl5GWNjY1hZWcHw8DD3IgQCAaRSKTidTqTTaVy8eBFXr16Fpmnsq3vq1CkcO3asox4RsEpLNZvNqNfrD2SKp9eia6f3kTcuNVO1i6Z1A01Q6DPQF/lLpRJLX28FvbB3foBV/v1G2/wigF/s8Po1AI9u6Yz6YBCVsJtDz4MAmn0Xi0V+UIQQyOfzqFareP/99zE8PAyj0YhEIoF8Po+RkRHkcjkoioLdu3djdHQUFy5cwPXr1+FwOPDUU08hnU6j0Wjg7bffhs1mw+LiIs/mqtUqd+cGAgGMjIwgEongySef5M+i19xst+1UVWUTlU5FVGr4AYCFXGeOfLFhwmc/+1ku5IbDYQwPD6PRaOCRRx5BMpmEw+FANBpFqVTC3r17WYQtlUrh0KFDzBXP5XKYnJzk1Jbee1gf/E0mU0dt/fsZtKq81eeQJgmklUMqqltFvV7n7u5u3cEboZ+k28GgB26rH+r9BsrvU5ejz+fDwMAATp8+jSNHjsDv92N2dhbDw8Ps/uTz+WA2mzEyMgKHw4FCoYBQKASr1Yp4PI5IJIJQKIRkMolkMgkhBG7cuIEDBw5AURSYTCaoqgqLxYJwOIyBgQH2gb0dGjJk7dgpH6tPVwHAgNeKhfx6o5EBn42brQwGA2w2GxRFgVzTex8ZGeE0Vjqd5mC9d+/eFh1/KSVmZmbgcrmQSqUQi8Va6IT6VBrds0qlsu3ieDsBevkNasK6FVCKL51OczF+M3TqLyG2UD6f3/I59IP+DgaZcD/ooC98vV5nuV6r1YrDhw+zZdyePXsArOrVU3etvkWeXKAo108YHR2F1+vFrl27cPTo0a7ytUAri+JW0Gw2US6XWaKBGDUAWuiVFBD+3ecm8duvnEFV+yj42kwG/ObnPmqkout0uVzIZDIoFotsu0g6+n6/n60L6RiUJnA6nWzO0R7M9ddrs9kwMDCA5eXljmJs9xNosPN4PEwfvh3XS7NzWsX3cg562Gw2DA4OIpVK3dSEsB/0+7hnQA8c0RFJqnd6ehoDAwMYGRlp4S3rWQ/kIqVPmQGrDS56h6pu6NaBu1VQOoWatwBwmokMyKkWEYvF0Gw2cTgk8WtPhvGt01ksF1XEPFb8q8fD+PF9wZbGLyE+kk44deoUDAYD9u3bxzaUevMX/Sy+VCrB7/dv6CKmh9FohN/vR7VavW+7dOWaOJ/H4+FGKtK7uV3Xe7P7oXMhW8qtoh/0+7jnQIFJVVXk83m8/vrrOHTo0LouXn0BzGQysQVhsVjkAEjL7V6LardihUcBVkrZktYxmUwYHBxEOp3Gj370IywtLcFmsyEWiyGfz0PTNExOTuIff/0TMJlMvLwvFArQNA2KoqzTf/nggw9gNpsxPj7eorAJfNT1S7r3lMqioK9He96YrkFVVXi9XhSLRfYcuB9AQd1ut7PF5O0e1GjisVl6bKNGuEqlAk3T+kH/fsFmjTJ9rILYNS+88AKAVUcnj8fD5uJ074i2SV2v4XAYlUqFc7W9BvybneXT50mSyZ1WFdFoFF6vlwPwwsIC5+SJpkcNUkQdNJlMbHpCpi50nj//8z+PdDqNv/7rv4bP58Pg4CCOHj3K+8vn81BVFRcvXsT+/fvx/vvv47HHHoOmaQiFQrBYLMhmszh58iQmJibYJMVsNuPSpUt4//334fP5cOzYMaiqCrvdzo1bJENBaSNKXRkMBk5rlctlWCwWLhjfbeg1ldxuN8LhcMt36HaeY7Va5Wvf6Hz0zB39CoPkO24W/aC/A0EUrweNJXEzaJ815fN5lMtlBINBbk4i7fhIJMIPTq+UOQIFs5tZ3tdqNeRyOVSrVVitVtbh1+/H5/MBAGKxGADwtuR36/f7edtSqYT33nsPTzzxBNxuNxec6TwBcCqrUqlgYGAA8/PzMBqNqFarmJ+f5+CbTqeRTCZZMXJ2dhYHDx7Eww8/jO9+97tIp9OYnZ1lZc4vfvGL2Lt3L86fP4+PfexjOHnyJBKJBDweDzweDzeehcNhAGBDESklJiYm8MMf/hAHDhzA7Owsms0mPvnJT971lQIN5uRzQPpI3ba7VdDqqtu+9AOQEKu+yS6Xi1le+hrQzaAf9HcgKC+bTCZ3xCzoXgDx85vNJoLBIJaWlrhQWiqV4Ha7USgUUCqVcOXKFezevRvBYPCmdVC2AmK6kKhZOp3mVUc75JpcbrlcZl9bv9/P8slCCBQKBbz66qvYt28f/61T2kkIAb/fj6NHj6LRaOC9995DsVhEOp1m31zyBqjX65idnWUqKaV1wuEw5ufnefXUaDTw0ksvIRwOo1QqYXl5GYqiwGq1YmhoCCdOnOBGtYmJCczNzSEQCKDRaODy5csIhULQNI1lqO8U2p8jPe89l8tBSskG7pRS83q9XPNxOBzMHqPrW1hYwNjY2DqBPrpPUkq2ptSDtJU2ApnhFAoFLtjSQF6v19f1Smxl4OwH/R0ITdPYOu9BoMXdDlQqFXzwwQcQYtW9KJFIYGhoiJurEokEN7LMzs7i+vXr2L17N55++unNd45W962tDhJmsxkGg4GLzO2MC1qt1Go11mq32+1sdk36O3TcWCyGr3/967xqIKem9v16vV58/vOfx8jICOr1OiYmJmAwGBAIBLCwsIDBwUE2Nierv0qlguHhYQQCAezfvx/Ly8s4duwY5ufnWWJiz549aDab0DQNhw8f5sHF7/fz/SH1yT179mBkZAS1Wg2apnEtYHJyEg6HAwaD4bbO9PXBnbqjSXSOPgtVVXH16lVOWeVyOQQCAU5ZpdNpDvakpVOpVHD+/HlupHM4HBgdHcXp06dx+fJlBAIBLqjToO12u/H444+v63DeiLWjZ4iRuTytOujaiJarx1aKuv2gvwNBH14/n9873G43JicnIYRAsVhEPB7HxMQELl26BKvVikAggEAgACklP7Qkq9wrKMVDkrbAapcqFfsoB6vfntIGerML4tNTSiefz6Ner8Nms6HZbLJHL5mskHyypmmsg6+fXXq93o6TA7vdzgHHYrHg6NGj/DeS/B0bG4OqqhzkfD4fD0L79++Hy+WC0+nEwYMHWZvnYx/7WAsDSI9QKAQpJVKpFHw+H8bHx+FyubCyssLuUAB4gLidVop0/+n+1Wo1OBwOboIS4iPj+9OnTyMYDOKpp54CAF5Vp9NpHgBppu7xeJjhZTKZEAgE4Ha7cePGDWSzWRiNxhYxtbm5OR4UOk0UTCYTd4p3Aw0MKysrUFUVly9fxkMPPYRms4n5+XmMjo5CURT2PAbQ873c1ETlbqBvotLHVrFRZyLl8zvp5G9lYKXUSzab5QGjUChwWzzlxWlbWsaTWUkoFOLAsLKygmAwiHq93lLcbTabbLRisVjYNzUQCCCdTsPlcsHtdvOxaAatf3+7nHO3a8lms8jn8xgdHWXdIqvVyvLOlMrweDy8mqCBSm/m0cs91DQNpVKJdYpUVd3ypGazWCWE4JReOByGpmnI5/PMziJDG0VRWpyvqBGNmvf0xxNC8EqLBhWaeWuaxmk36guhmTq9BmBd6q1Wq6FYLHLdQ5/DpwnA3/7t3/7/7Z15eFRVtvZ/O6nMU2WsjCQhCUOITHoBh2YQUbARbdsBEfTigLbadstF/bqv2txGWkCvOFy1RdprqwhXRRQRZRAUkTCHKSCTEJKQeaikQiqVqjrfH5W9+1QIECSBKOd9njxJTp06Z+8zrL33Wu96F1lZWfj5+REfH09+fj7V1dU4HA6cTic9evSgqKiI6GgPbbe+vp4ZM2ZQWFh47kVUfkmQF9eYQf/yIF+0tqBpnqLr8fHx53zv5QwsMDBQCaPZ7XZF/dQHAE+cOIHT6VTnd7vdxMXFKSNQV1enZteyXceOHaOgoIDQ0FDi4+PVTM9ms5Gbm0tqaqpSy6yurqa6upoePXpw7Ngxpa1vtVpJSEjA6XSSlZXltaLRG85t27axevVqnnzySQBVhUtW9CovLyc8PFwJ0MkiKtKA6l0RZzL+JpOJiIgINRMvLi72mgH7+Pgo6Wk5O5bBTukW8vf3x8/PT51TuoX8/Py8Ct7LSmV+fn4EBgaqWA+g9Oxramqw2WyEhobS1OTJdpbaQvqkvtaJcnqczkUjr1Nrd5Psa+tVoXxeiouLiYqKonfv3oqpVVVVRd++fRXt2Ol04nQ6SU5OJiIiQsVHWicenvJetGuvXwD0LA/D6F9c0C/r9Uv9n3IcyZPX/3+ql00qe0oWjX5maTabsdvtJ7lmpPxuWVkZP/74I0VFRTQ1NdG9e3fKy8upq6sjMDCQfv36UVhYiI+PDwUFBZSUlGCxWDh+/DhNTU1YrVZKS0sJCQlRRl+2Q+r0XHXVVQwYMIDy8nL2799PVlYW5eXlyl1ht9upqanBZDIREBBAQUEBUVFRWCwWEhIS1DXQG0m57XTXMCgoSBVlkZCDWHBwsBrApWJqUFCQOr50tchAqhCCpKQknE4ndrud+Ph40tPT1blkVSmn00ltba3aHhERcRK1V16jc03A0n+3rb/1SXB6GqYsHBQZGekVN6msrFQZ1aGhoV6Z0NIFFRQU1G7p64vG6MPJyywDFw/cbreqNBQWFqZmdXDmlZ9++S1nkWcD6W6Af80O5ey0NdLS0jCZTCQnJ2O32+nfv78638CBA9UMV4qrSeaNEEJpscgUf0ApdYKHBmqz2dRMWWYFC+FRK920aRO1tbWkpKRw6NAhmpubqa2tJTo6mqSkJHbt2kV0dDS9e/c+adUkXUvtiUf5+PgQExOjirmYTCb1bkr6aGFhIXa7naSkJCIiIigtLcVms5GdnU1TUxPHjh2jrq5OGXX5ne7duyujr0drQy7lr+Vn8rd+Nt5ZtkKveSR/NzY2Ul9fT2ZmJv7+/qSkpKicjerqatxut6pt3FZug3Q/tQcXjdHvKI6tgZ8n5MvV0NBAQ0ODKkzu7++v9Hbkfq3hdrupqalRLoKzDQAD7Z6F+fv7071795O262fTDQ0N1NbWKh+0vs16Pn/rPthsNsLCwqivr1cGRxqL9PR0LBaL8uVL15Okg/r5+ZGamqoK2shZs3R1SYZSW66RtiBpyVVVVaxYsYJLL72U1NRUFeQcPHiwGmRlZS8Zt3G73Vx22WW4XC7lDpLbTlffuK1ZvN4PL9vc2baidb6H0+nk8OHDitIr83TkdfL19aWyspKmpiYSEhLa7cY5FS4ao2/AAPzLqLtcLsUTl8kvYWFhKvCqN1pNTU1Kh6UrEB9CQkIwmUxYrVa1amltpPSzV/lbupaCgoKoqanBbDZTXV1NaGgo4eHhNDY24nK5CA8PV+6b1pBuUlms3eVyUVtbS0REhNfAeSZ3j1yZSLlmyTRyu91UVlZisVjazDs4VZv02av6fkuYTCZMJpMKwusHYVncxGQy4e/vT1BQUKfN9DVNU8F/ORGpq6sjODjYa1UmIfNOpJheR7TJMPoGLlro/aJ1dXXU19erWW1AQAAhISEqYKtpmipHeLoi4p2B1gFTQMny1tTU4HQ6CQgIUO4KSRGtqalRBtjPz4+QkBAaGhowm804HA6qqqoICgpScY72KLrKOIZ0q4DHoDY0NHitOvTJZPrvyv4A1NfXs2DBAsaOHUtiYqIKEAshVFC3LUkS6Q6RLqrm5mbeeecdRowYoYLOxcXF+Pv7061bNyoqKkhKSlIsqoqKCsWOknRVyVByOp1UVVWplaBUbO2oAUC6a+SxhRCUlpaSlpbW5sAt9aJCQkK8GEHngvaUS0wB3sVTBUsD5mma9nKrfQTwMnA9cAL4d03Ttrd8djfwVMuuz2qa9s9zbrUBAx0M+cJJHr7dbqeurk4FMW02m5qVRkZGEhYWdl7qHOhdEq2NgslkIjo6Wkk1yCxQOYOUbivJm5dZpjKQ6XA4zlm6W9JYW1+L1gwfuU1+R7+PPqNY78Zpa9auaZ66sCdOnMDPz4+GhgbFkDKZTBQWFlJfX8/Ro0dpaGggJiZGSUHIc0peu1zVlZWVkZ6eTllZGaNHj1ZUWrvdTn19vcrU7QjItgcGBnLggKeybHx8vJIM0bt+XC4XNTU1Kp9Bxl/OFe0ZNpzAf2iatl0IEQZsE0Ks0jRtr26fMUBWy89g4A1gsBAiCvgLcBmeAWObEGKppmk159xyAwY6CfoXq7m5WSW9SB9zWVkZdrtd0S87E3q3RVvuDllMQzKFmpubKSsrIzY2VhkJTdMUj1+vOir94+cCmcUbFRV10mdyoGrtapH9CA0NZcqUKV7bwBPkrqmp8ZJ71n+3qalJUUklU+nuu+9WDBY5U5e/01oS0E6cOEFMTIxapdTW1tLc3ExcXBzNzc3K3SRdYLLMZllZWYfN9OUAlJiYSGRkpNKJkc/EMQAAIABJREFUaus6ORwOlc8gYyYdgfaUSywBSlr+rhdC7AOSAL3RvxF4V/O0eqMQwiyESACGA6s0TasGEEKsAkYDCzuk9QYMdDLaMrTSHSQLnHeW4T+Vn/p0BsjtdhMaGuo1K5Qumc6A3W4nKCiozVWPVDc9U4UoyTTSF7yRJSBlkRz9dZBSDtK909DQoAaYbt26kZSUBPwrttDU1KRUVuVg4Xa7qaqqIjw83Gtw1LdT5lecLjj8UyGEUNnC+m16Vk9zc7O6Nh15/87qSEKINGAAsKnVR0lAoe7/opZtp9puwMDPFvLFlDNJfe3ezjqfzWZj3759mEwmLBYLVquVyMhIxVsHlM+6oaHByz0CnhhARUUFmqZhNpu9XFc+Pj7Y7XZ2795NWloa0dHRquiKND5ytqmv7AUo15e+cL10kdlsNmw2GwkJCV7FbVojLy8PTdMoLCwkIyNDZdUWFhYqnZnw8HDi4uLw8/M7SaG0LTqmXMHYbDacTichISGqP/oVks1mIyoq6pSDUmBgIBaLpcMG9sDAQOrq6k75uRyoJNtK3tuOfL7abfSFEKHAYuCPmqadutU/EUKIKcAUgMTExI4+vAEDHQpp+MvKyrBaraeUeTgXHD9+nB07dnDttddSVFSEv78/JSUl7N27l8LCQmJiYjCbzdTX1wMet0hiYiJHjhwhLCwMTdOw2WykpKSQnJzM3r17KSoqUjVyS0pKlDxE9+7dyc/P58iRI1gslpMGtKKiIi6//HJycnK82ihjArIymdPppK6uTrFN5OBxOjQ3N5Ofn4/D4aC0tJSoqCgqKyuxWq34+/srY+1wOOjVqxfDhg3zig9I0bbWGb51dXU0NzcTHR3dplGX18jhcHTaSqg12nLjtLWPw+HgxIkTiiGlD+LqpSPk8TpcZVMI4YfH4C/QNK0tUZxiIEX3f3LLtmI8Lh799m/aOoemafOAeeDR3gkKCiIoKEg9RP7+/oSGhuJyuairqztr6pw8lqZpxMbGeiVhyFT39sDX15e4uDg0TaO8vLzdPtGwsDBlFOx2u6rz2tjYeF5ogPoKUTIwJKs4nQlCCEWhKy8vPydVRB8fH0WNlLOZpqYmxZYxmUw4HA7q6urUtZXiY+B54CU/W38dpcCWXOrLZbvk5kuBNAm5tJbP09n0SZ/uL2eisoCIPtHoXFFVVcX27dsZOXIksbGxFBYWEhoaisViUf2S8gOxsbHqulgsFgYOHIjb7Wbr1q2EhIRgsVgIDQ2ld+/eCCFITk4mPT2dPXv2qGMkJycTEhJCVlaW0tqx2+1UVlYSFxfX5rMuhKcQjcyulbNy+aw3NTXR2NjotRJojaysLOUmc7lcBAQEUFFRoQybDN4GBASQkJDgpY/jdruVQJoMdkqXjqTZnu5e+Pv7q5l3W9TXjsaZjL48v8lkIjg4mLq6OvLy8ti5cycBAQHcfvvtgGeAX716NRaLpc28jtOhPewdAfwD2Kdp2oun2G0p8IgQYhGeQK5V07QSIcQK4G9CCJkxci3wp/Y0LDExkVmzZnHLLbcQEhJCYmIic+fOZeTIkcTFxaklrF69EP61tNNfWKlNn5qait1uZ+XKlSQnJxMeHs7GjRu54YYbqK6uPum78iWWgwV4DND69esJDAykT58+WK1WL8ZEW0hISGDHjh0sXrwYPz8/br/9di677DK2bNlCnz59KCoqArx1uOX5ZfBNijsBXi9fW/2VVZT0+0VERLBr1y7Wr19PaGgovXr1YvTo0ZSUlKgqPHqJAXkcIQQBAQHs2bOHiooKhgwZgtVqPWlf2VbJOmgLfn5+pKWl8dFHH5Gbm0tkZCSTJ0+mW7du1NXVMX/+fIqLixk0aBB33HEHR44cUQb8xRc9j15sbCx33HEHK1asYOTIkQghiI+PZ968eUyZMoXDhw8TExPD1q1bWbZsGSEhIdx///1EREQowySFxF599VUyMzO57777OHz4cLsGcCEEcXFxPPfcc9xzzz0EBgaSnJzMc889x6233qrS+3+qAXnyySeZPXs2ADk5OfTs2RN/f38CAgI4duwYQ4YMwcfHh5ycHKxWq1LF1D8bjY2NlJWVsWPHDm688UZ8fHx47733yMvLIykpiXvvvZc9e/bgcDgYPXq0kjWQ1bm++OIL1q5dS3JyMlOmTCEnJ+eUwWTwGE7JMW+9T0REBG63m3nz5rFr1y4SEhJ45JFH1KQjLS2NmJgYYmJivI6pN2RyRSXZSkJ4dItKSkqUKNns2bO56667SEpKws/Pj5dffplx48aRnZ192usdEBBAZGSkSr7TD06dMRmT7pu2oM83ABRttaKiApvNRnl5Obt372bDhg2kp6dTVVWFzWYjKCiIVatWUV5e3q42tMdRdSUwCbhaCLGj5ed6IcSDQogHW/ZZDvwIHALeAh5q6UQ1MAPY0vLzVxnUPRN8fX15++23ee2117BYLOzevZuXXnqJnTt3kpiYSFJSEiaTie7duysJ17S0NMLDw0lKSvJ6iKKionjppZf48ccfCQ0N5aqrrqJnz57U19dz5MgRAgMDlTBVUlIS8fHxxMXFqYBQt27dVA1SgJKSEsrLy3E6naSlpZGZmUlKSgppaWkqozI1NVWl+tfX1/P000/z+OOP88gjj6j06j/9yTP+ZWRkkJGRga+vL0lJSUrbJCUlhcTEREJCQujRowexsbHExMRgsVgICgoiKyuLkJAQUlJSiIuLU9fAbDZjsVi8qGY+Pj58/fXXdOvWjREjRnDgwAGuueYaEhMTiYqKUiXxMjMziYiIICMjQ/HUExMT6d27N5dffrn6zN/fn4yMDNLS0pRmusViwWw2k5yc3KZxiIuLY9q0aRw4cIAnnniCcePGsXXrVhobGxk3bhxXXHEFzzzzDIDSgBHCI5W8bt06br/9dqKjo7n//vvJzMzkD3/4A0lJSbz44ovqOoPH8CUlJfHkk0/ym9/8hrvuusuLXRIbG8vkyZOZMmUKZWVl/OMf//C6v2dCc3Mz8+fPZ/78+cTHx7N27Vr+/ve/c/DgQSwWi5K/lYOfy+VSrBop7tUa8gXeuXMn4DEApaWlakB2u9385S9/Ubx86UqxWq34+fmpzE3JL589ezbDhw/H39+fiRMn4nQ6+c///E9+9atfkZeXx6BBg3jllVcUDVX+fvXVV1m5ciXTpk0jMzOTcePGqQmNpmkUFxd7DfYul4uSkhL1jDmdTlwuF8ePH1fyEG+88Qbl5eXMnDmTa6+9FqfTSW5uLv/3f//HiRMncLvdOBwOqqur1Sq+vLzca3VmsVhwOp2qYtS+ffuYN28edrsdTdN46623+Pvf/46vry8bNmzgtddeY9++fYBH1+fYsWPqfkgBt/LycrUiMJvN1NbW0tTU5GV4OxqtJ4d6Q68P3EvdHRl/iIuLIyQkhN27dyvRNSGEyjCvqKhoN/22Peyd9cBppywtrJ2HT/HZ28Db7WpNKyQkJCixoX/+859MmjQJ8LhHpk2bhsViITc3l48//pht27bxu9/9juuuu47t27fz/PPPExsby4kTJ6ivr2fbtm28/vrrXHPNNcqvKWcnISEh/O53vyM0NJSCggIeeughEhIS+I//+A+uvPJKgoKCmDJlipdA1BtvvKFG3UWLFjFjxgzuu+8+evbsyfTp0xk1ahSZmZkIIbDb7UpStkePHqSmprJu3Tp+/PFHZs6cyeTJk1myZAmNjY1s376dqVOnMnToUPr168fQoUM5duwYaS2aLHl5ecydO5c+ffowYcIE0tPTyc/P569//Ssul4sHHniA4cOHs2XLFv7nf/5HqfBJpKSkkJKSwoMPPqhm/haLhXvuuYd+/fqxZ88e1R+ZOXjjjTdSWlpKUVER99xzD9dffz2DBg1iz5499OnTh6eeeoqcnBxuuOEGDh48yJQpUxgyZIhK1Yd/rZpWr15NXl4eBQUFxMbG0r9/f1599VUmTpxI3759qaqq4vrrr8dkMmGz2by0asxms8r8vOyyy8jIyGDGjBnk5eWxePFiDh06BEB1dTWZmZnU1tZy4sQJL2qlv78/+/fvJz09neTkZO677z4efPBBxo8fr1Qk5cujzyqVcsMS2dnZ5OfnYzKZWLhwoVp2V1RUMGPGDMxmMzt27ODjjz9m5cqVPPvss1x99dVs2rSJefPmkZGRoY41b948vvnmG8xmM0ePHgXg448/Zvfu3RQVFXHppZdy4403sn//fubMmcOoUaNobGxky5YtlJeX06NHD6ZNm+Z1rYuKioiNjeXo0aPU1tZy//33Ax7jKWE2mykoKCA1NVVt+8c//sGWLVvw9fVl7NixfPbZZ2zYsIHNmzezYsUKBg0aRG5uLp988gm1tbU8/PDDDBgwgLy8PBYtWsSbb77JN998Q58+ffj+++9ZuXIlNptN6fVLTf+1a9eye/dunE4nN998M7fffjtXX301t912G/PnzycmJobDhw8zdepUBg0axKRJk1Tc4dlnn2Xt2rVs2LCBmTNnMn36dDIyMjhy5AiapvH+++8zYcIEwEPLfOqpp4iOjmbr1q0sXryY9evX86c//YlrrrlGvSdZWVmUlJRQWVmpktVaB4g7Aq1XEfoBRq7q5WpZbr/00kvZv3+/Wvnl5+ergjaSYnrVVVexfv36drWhy2fkjhs3jsWLF3P8+HGuvvpqwBMB//d//3e2bdum3C1ms5mBAwcya9Ys9u7dy8svv8ycOXMUs2DIkCE89thjZGRk8Morr3idY+fOnZSXlzNhwgQaGxt59dVX+f3vf4/ZbOaGG24gJydHGQSJG264gccee4xPPvmEhQsX8uCDD/L666/z0ksvsWHDBmbMmMHBgwcBSE5O5qmnnuKZZ55h//79TJ8+nZtuuomsrCxmzJiBj48PEyZMYMWKFbjdbhYuXMjQoUMJCAjglVdeobi4mPvvv58vv/ySFStWsHr1aoqLiwkLC2P06NHk5OQwb9487r33XgYMGMDzzz/P8uXLWbVqFXfeeedJ/uympiZ8fHxIT0+noKCADz74gN/+9rekp6dTXV3NN998w8GDB7n++utVssrSpUsB+Oqrr7juuuv4wx/+wBdffMHmzZsBT4LJ3LlzOXr0KDNnzmTYsGFe55RJMImJiTQ2NiofbHV1NcXFxVx55ZUqwaiqquqk5+DgwYPMmTOHkpISZTiefvppsrKy2LBhA0VFRV4vktPpZOHChaxfv54hQ4aowcPHx0dxwBsbG4mMjKS6uloZ97i4OKqrq2loaCAlJYXS0lKam5vp3r07ZWVlXoZ/+PDhLF26FKfTqVYSsbGx3HrrrezevZumpiZ27doFwLBhw/jb3/7GunXrePvtt5k5c6Y6zoIFC1i7di1CCC655BIARo8ejdPpJDY2lg8//JCHH36YPn36MH36dJVZa7fbKS8vZ9GiRcroCyEoLi5WPn5ZcKMtpKens3//fq9iHzJ7Vxqj1NRU5X687bbbmDRpEu+++y5LliwhPz+fMWPGkJOTQ2NjI8uXLwdg/PjxTJgwgSeffJJ9+/bxxz/+kVdffZXbbrsNTdN47733VEWvRx99lAMHDpCdnc1LL71Ebm4uJ06cYOzYsVitVl577TWqq6sxm82MHj2a7Oxs3nrrLSZPnkxtbS0zZ85U9+Taa6/l008/pb6+nqysLMAzsE2YMEFVVdu6dSsAV1xxBc899xybN2/mrbfe4oUXXiA5OVmt0Lp166YYSx1t+FsnrLXlNtPr98fFxak4jtQYao0RI0bw8ssvn7S9LXT5Wnw33XQT//Vf/8Wvf/1rtW3jxo28/vrrDB06lOzsbKWhIuVqIyMjVR1LQH0uA0KtYbVaEcKjNNjQ0MAf//hHRowYwUMPPcT777/PrbfeepLIlkxll+fq06cPhYWFfPjhh4wdO5bq6n95sZqbm7nuuuv44IMPWLNmDdOnT1efyaXcxIkTycnJYcSIEaq9UjwrMDCQqKgompubCQwMVAkpMtMyMDCQu+++G/CoKjY2NhIcHHzKEmrh4eFERESwY8cOLrnkEqxWK01NTVRWVjJy5Eiys7N58803cblcTJo0iSVLlqjv2u12QkJCFA1OovV5g4ODiY+PV0U3nE4nCQkJFBYWEhgYSEhICGazmaioKLKyssjPzyciIoKgoCDl2tLjkksu4cUXX2ThwoW8/fbbitYm3XD6gU1K8T7wwAN89NFHfPjhh7hcLiwWC9HR0cTHx1NaWkpoaCilpaXEx8d78aE3btzI8uXLOX78ON988w3Lly/3Ghgk7rjjDh555BE1ywdYvnw5H330EcOHDycrK+uUz6Y+DqPX+pHXa8qUKURFRTF69GgvkoH8zkMPPURoaKjyyesRFBSkBvaMjAzl5miNpqYmL8aREB4pBqk/X19fT35+Pj169FB9cLvdqg+y4EdlZSWXX365MkbR0dG4XC7VjqCgIB577DG+/vprxo8fzzvvvKP6Iq+pNGr6d7G5uZmHH37Y61kPDg5WK/7WLpjbbruNadOm8dvf/lZtW7NmDe+99x7Dhg2jZ8+eXvcD8LIV8fHx9O/fHyEEjY2NXlIJHQm5gjxVbWNAyT9IQy8ZPPL7rX/0K4Mzocsb/cDAQD777DNuvfVWtU1Smerq6li1apXavmzZMrZs2cJzzz3H2LFjlYF3uVwkJiaydOlSDh8+fNI5/u3f/k2JbiUmJuJ0OtmxYwcOh4Obb75ZaYrr8f7777Nr1y5ee+01xowZg81m484772Tq1KncfffdyhUkmQivv/46W7ZsYcGCBfTp0wfwGMLly5erknhCCC8Dezpcc801KmgpZ3Xtwffff8/nn3/Oww8/TFRUFP369WP8+PFs3LiRtLQ05RdetWoVffv2ZcSIERw7dkx9f9SoUSxcuJBly5bxxhtvnPI8fn5+vPTSS0q8Cjx1bB988EHuu+8+Dhw4wJo1a5g/fz533nknq1at4oMPPqCgoIDZs2dTWVnppXFTUlLCkiVLePnll1W1oFMhJiaGZcuWsWnTJt555x0iIiLw9fXlm2++Yfv27aSnp1NXV8eKFSuYOXMmEydOVL7z8vJyRo0axT333EN8fDy33HIL99xzj2IV6REdHc2XX37JqFGj1DabzYa/vz9VVVV8++23avtHH31EXl4e//3f/82vf/1rqqqqqKiowOVy0b17dxYsWMDChQvV8ymP89VXXylDlZiYyIcffsihQ4fU52vWrFETDCkcFhcXp56/uLg4Lr/8cqZNm6ZWGYsXLwY8fvEBAwZ49enPf/4zkydP5rvvvuOtt97C19eXgQMHAvC///u/7Nq1i/nz5zNq1Chuv/12Nm7cSGpq6kkFwPUUyY8++ojPP/+cDRs28NVXX9G3b18SExPZsGGDukaSBHDllVdSWlpKRESEKgQzatQoDh486PWsx8fHs2PHDlauXKmehfDwcJYtW8bYsWO97ofM8F2zZo3avmTJEjZs2MDzzz+v9pcz+9TUVMrKylQJxZ+K1r56aZzltTndYCLdmZ2BLlsucefOnXz77bcMGTKEiooKVVfU19eX1NRUli1bRllZGYMGDSIyMpLi4mI+/fRTevbsSWJiIiNHjlQ+Pslf/vrrrxW3WdIGS0pKyMzMxG638+mnn+JwOBg1ahTBwcF88cUXOBwOxo0bh6+vL1arlZCQEEUp3LhxIwMHDiQnJ4fm5mZKSkqYMWMGb775JsXFxYDn4U9JSeHrr7/m4MGDJCUlqQGprq6OzZs3c8UVV1BRUcG6desYNmwYDQ0NDB48mG+//ZZBgwbh4+NDXl4el1xyCQ0NDVRVVZGRkUF1dTVffPEFAGPGjCEoKIjCwkJVCLuqqorIyEjq6uowm82Ulpbyww8/qHqyycnJqvjG3r17yc3NJT4+nrFjx7Jt2za2bdtGcnIy48aNo7S0lMbGRjIzMyktLWXr1q1UVFTQ2NjIAw88QG5uLn379sXf35+dO3cyaNAgbrzxRj799FPla/fx8SE5OZkffviBjRs3EhUVxQ033KBmg19++SVFRUUMGTKE/v378+OPPyp64eeffw54ZmZDhw6lsrKSiIgIcnNzGTlypDoHeIzj7t272bp1KzExMdx44424XC6Ki4tVAQ85wGZkZDB48GCOHTvW7hc8PT2dDRs2MHDgQFX4Q7YnPj6eTz75hIaGBvr160diYiKbN29m9+7dxMbG0qNHDwYPHqx890FBQVgsFhYtWqSCdUOHDlWDXP/+/XE6nQwdOpSGhgbWrFlDamoqCQkJfPzxx2RnZyOEYMCAASxcuJCMjAyGDRvGCy+8wMiRIwkNDSUtLY28vDx27NhBcnIyY8aMobq6munTp7c5cO/du5f169eTkpLCddddhxCCuXPnEhMTw4kTJ7j88svp168fALt37+a7774jJiaGsWPHUlhYqK5Dfn4+8fHxNDc3s3r1aqxWK5deeimDBw9GCMGmTZsoLS1lxIgRHD58mH79+tHY2Ijdbldus+uuu47k5GTKysr44osv8PHxYcyYMYoRd/DgQW6++WbWrVvH8OHDAY8x3b9/PyEhISQlJbFkyRKsVisDBw4kLi6O/Px8vv/+e5KTk+nevTvDhw9XXHfJkhNCcOzYMUWakKUvT6WDI/WPzGazVwZ162eqvr5elag8HeTzKoXl2oObb76ZPXv2nHHnLmv0ly5dSmBgoIruAyqrz263q9JuMnX68OHDfPnllzz99NOUl5efxEH38fHxkjOVyyFZYs7Pz099LhkB8nyy6pGE1OUAlNjUgQMHePbZZ5k7dy5ms5mGhoaTzu3n54fL5aKhoUElrfj7+6sHTT5UkqUgefxS2VFy0n18fDhx4oSSgZVtlMHShoYGAgMD1X4Sko4mH1x9n6TqoJTNDQgI8GqvVFCMj4/n8ccfx2azUV1dzfz581UlH8kb9/PzIy4uTvHK9QFd/fVzu91KRVDqnUg9db27Rl4n+Fe2p1wiS3dS6zwLfX/kOYKDg9E0j0Kj5KbL2q1nA6nCqX82ZcUnh8OhJHDlhCM3N5cjR44wZcoUxdLRQ+ZQbNu2TdEX5UonICCA6upq8vLyFItMPhNJSUlomkZERAT79u3j6NGjpKWlkZ6eTkJCArt37yY4OJhNmzYxYMAAfH19qa+vJzk5maamJjWbbg9efPFF+vTpw7XXXvuT3B2SkXP48GHi4+NVMldZWZly9TU3N3Ps2DHCw8Pp3r07BQUFigBhsVhUopjMx8jJycHhcKgaxdLYNjQ04O/vj8lk4ttvv1XXVLps9u7dS15eHr///e85evQolZWV+Pv7q9WRzWajZ8+eVFZWommaGsCkxENxcTHdu3fn0KFD+Pj4kJWVxa5du1R9BrvdrqpZWa1WAgMD6d27N35+fl7xotOhubmZgoKCs9JG+tkb/bMpjO7j40Nqaiq+vr4cP37cy9CdD/j7+5OWlgZ4mCOVlZXn9fznE2azWVFBNU3j+PHjbRpNOVDZ7fbz3cQuBZPJpIKCsvRhW5CG1NfXV8Vc9H7c2tpa/P39veIoMh4UEBCg3IOS4udwOHC5XCq+IicXkpMvGSpnAzlzld872+9XV1ezf/9+rFYrJSUlylDbbDYCAwO57LLLqKqq4siRI0RFRVFQUIDD4SAwMJDY2FgiIiIoLi5Wq+e0tDTmzp3LX//6VyIjI1XOypw5c+jZsyc33XQTubm5FBcXq/qzl19+OVdddRU+Pj7s3LmT4uJiSkpKlCsxLCyM8vJyVRO4Z8+eREREsHPnTnx9ffnVr37F8ePHCQ4OZvPmzQQEBDBq1CiOHz9OXFwcO3bsoLCwEIvFgslkori4mMTERG666SbMZjMVFRU4HA5FBz8VbDYbxcXFZ3WNLyqj315I4Se5PNPP1AwY6AqQRtXPz0+5EOQqSK6+zqTDomkaFRUVKiO1oySgWyf8SeZJeyEVOevr62lqalJZ1PJ9jImJobS0VO0r++92uwkLC8PPzw+bzaZWvJGRkRw+fJjs7GwV9AQ4fPgwoaGhJCQkUF5ergZEp9NJZGSkKjYuC8boV15yoJWJnzKL3Wq1KsG2xsZGL/aNVOmsqalRWcX6BEmTyURiYqJa2cjVw+muc0VFRZvkgdOhvUa/y1M2zxYhISHExsbS1NSkkkbAM+MKCQmhuLiYnJwcvvvuO/r3709ZWdkpjxUZGYnZbMZqtXqxcQwY6CxIYy4prdKQ1dbW4uvrq2b7wcHBXjkMev63lLDoDM1/vRFqnb1+KsgVgq+vL6GhoV7l/lqvGlJTU6mqqsJsNquZu16OobWsQv/+/U86n6RrSnZXW+1LTk5Wf5+qxKQe0dHR1NXVcejQIa+6xXroj6MP4OoHaVnw5nSQtqsz1D2hixt9GXCVVC6Xy6UCJXV1dTgcDqKjowkKClI6KDExMTz66KNMnz6d1NRURR0DOHbsGIWFhfTp04fZs2ezfPlyTCYTtbW1yj9stVoJCAggODiYsLAwJk6cyPvvv4/JZMJutystbqvVitvtJioqioCAAJqbm1XJNfAEbFpz+w0YOFvojZWUWGhsbFTBRh8fH+Lj473iVY2NjacUGeuotugzR/WGW+850HP/9d/R76efMUt/vaQynqryVnvaKY2tPH5raqRemVRCnwUrk570kEw0mTcgB6PTXSt9G2TS1enui6Zpyj3d0VRRiS5r9BMSEsjNzWXhwoX4+voya9YsXC4X06ZNw+Fw8NBDD3HZZZcxe/ZsQkND+f7777nrrrvo168fK1euVLoiUrlv48aNPP300ypAWF9fz9SpU7FarfzlL38hKSmJOXPmKJmE1157jSuvvJLvvvuOxx57jIkTJxISEsJTT3mKgD3++OP07NmTWbNm4XA48PX15YorruDdd9/Fx8eHJ554gqCgoIvep22gY6Gf0UtCQllZmSqq3dzcrAxWZxkNfTukcW7LTaz/TBriqqoqQkND1SxW3x8ZnJdxh58aO5DefA1PAAALiElEQVTf0ctHyGNLw15RUaFcL1LQMTw8nPXr1xMREUFERIRyB8tBwOFwoGkaubm5pKenq0B7t27d2pz5t3WN5MpFrsicTqeiZtbU1KhiLwEBAYoAERAQgNPp9FrdAcq2nO2KoEsa/ZSUFOrq6njxxRf57LPP1EWbMmUKzz33HPHx8YwePZoNGzawevVqpk+fzr333suYMWNYu3Ytl156Kc8++ywxMTH8+c9/JiIiggULFrBlyxZ27tzJb37zG/bt28fSpUupqqpi6tSpfPzxx6xZs4ZHH30Ul8vFunXreOyxx+jVqxdz584FYOTIkSxYsAC3282kSZP4+uuvWbBgAYsWLSI7O5vrr7+exYsXq6QUvXvJgIHOgBAeGd6ioiKCgoIUE6YzDX7r87dl8OSAJA1rU1OT0tZpbGxUbKzY2Fi1v14/SJZyPNd+tJY92Lx5M6tXr+bmm2/GZrNRVFTEgQMHsFgsjBgxgpqaGpXweOTIETIyMvDz8+P48eNYrVZ69epFSUkJJSUl1NTUkJCQwK233nraegF6yJl+cXExq1atwmaz0atXL4KCgvjuu+9wu91kZWXhdrspKCjAbrfTrVs3amtriY+PV7Vy/f39OXLkCCaTSeUztHeC2SWNfrdu3cjPz+eqq65S1MCsrCyqqqro2bMnDQ0NxMXFqcLPV1xxhQr86CFHyhEjRlBRUeH1APXt25eAgAAyMzNP8te3NWuRVMrIyEj1ommahsVioU+fPkqHZPz48URFRfG3v/1NBY0NGOhM6N068uWX1ayCg4M7XSu+LcOsn+WCx08tXbAys1xm+FqtVurr64mNjfUqjN5RMtVyYHK73UpwMCEhgaKiIjIzM5VSZ0xMDCNHjlTSzDk5OURERLB9+3ays7OJjY1ViW8VFRVqNaBPIjwTpAv48OHDVFRUUFtbS0lJCWFhYVRVVREdHc2BAwfQNI2AgADCw8MVzVeq2+oHRLvdTllZmRpQ24MuafRLSkro0aMHr7/+OpGRkURFReFyuQgNDeX48eNER0dTVlamZjStl4GS3y65sHI5pccPP/yAEJ5K9JIGJ/m1mzb9qzBYa5qaw+FQS0XJrABPMO2aa65h7NixfPjhh7z//vtMnjzZcO8YOC/QP58Oh4P6+nqcTifR0dHExMR0urunNeR7Iw26lAuQ75oQQhky6epwOBzqvUpISPByz3RE2+VxJV2yrbq+MmYn4Xa7iYmJUTkk4JGMsNlsZGZmelFozwS5+vHx8VEsopiYGBoaGpQiaVpaGkVFRdjtdqKiomhqaiIsLExlYAMqn0c/mJ2u+ldrdEmj/+OPPxIXF8ctt9zCXXfdhclkYtasWbzwwgs88cQTuN1uJVQm08g1TVOR/ClTpvDMM88wevRoMjIyVDBYJn0AjB07lqlTp1JVVcWsWbMAmDRpEuPHj6dv37707dsXgMmTJ3PfffcxZcoU5syZwwMPPADACy+8AMCAAQNUEs5TTz1FdXU1breb6dOnGwbfwHmH3jiaTCasVit2u52YmJjTFjLpSMjkP6kDr2+XNJxy5Sz/lkXJfXx8aGpq4vjx44SGhhIbG+s1yfqpkN/Vxx+sVivl5eU/KV9B0mrP5vwyVuHr60t2djYWi4UTJ05QUlKi+ihtlNvtVoWfTCYTvXv3VmUrJZ1ULzAYFBTEBx980L62dFWe/pIlS4iOjlZBDsmrjY6OVkqJTU1Nqoiyw+HAbDYr8aTw8HBMJpPK+iwvLycuLk4VKpH66U6nk6qqKrW8lNulAJn0kzY3N6ssRvAkmkieb319vSrLFhwcrESoWmdeGjBwISBZM+Hh4aoQt8lkUu4TOJnd8lPP43Q6aWpqoqamRmVqn8335W9ZKUvq+ugzbs+lnZJJ43K5OHjwIImJie3WodfDZDKdlRibdL8VFBTQq1cvhPCIuhUXFysmUWt656mOo4d+3591cpYQoh7Yf6Hb0QGIAX4p6blGX7oefin9AKMvHYFUTdNiz7RTl3TvAPs1TTtZNPpnBiHE1l9CP8DoS1fEL6UfYPTlfKLLSysbMGDAgIGOg2H0DRgwYOAiQlc1+vMudAM6CL+UfoDRl66IX0o/wOjLeUOXDOQaMGDAgIHOQVed6RswYMCAgU7ABTH6QohbhRD5Qgi3EKLNKLcQIlAIsVkIsbNl3//SfZYuhNgkhDgkhPg/IcTZE207CO3sS4oQYq0QYm/Lvn/QfTZdCFEshNjR8nP9+Wv9Se08175ECSFWCSEOtvw+s2ZtJ6A9/WjZ720hRLkQYk+r7T+re9Ky36n60iXuSUtb2tuX0UKI/S3v9//TbX9HCHFEd19O1lU+T+iAvlw4G9a6eO/5+AF6Az2Bb4DLTrGPAEJb/vYDNgFDWv7/EBjf8vffgd9diH6cRV8SgIEtf4cBB4Dslv+nA9MuVPs7uC9zgP/X8vf/A2Z31X607DcUGAjsabX9Z3VPztCXLnFPzuL58gUOA90Bf2Cn7vl6B7jlQt+TDurLBbNhF2Smr2naPk3TTpt8pXkgU1r9Wn404UlBuxr4uOWzfwI3dVpjz4B29qVE07TtLX/XA/uA09dLuwDogL7ciOd+wAW8L+3pR8t+64AuXR2nA/rSJe4JtLsvg4BDmqb9qGmaA1iEpw9dCufSlwttw7q0T18I4SuE2AGUA6s0TdsERAO1mqY5W3Yrogsa0FNBCJEGDMCzcpF4RAixq2WJfsGW32eLNvpi0TRN6kmXApYL0KyOws/ynrSBn9s9SQIKdf+3fr9nttyXuUKI05eguvA4VV8uqA3rNKMvhFgthNjTxk+7R21N01yapvUHkoFBQoiczmrv6dARfWk5TiiwGPijpmlSB/UNIAPoD5QA/92hjT+5DZ3ZFwXNs27tNGpYR/XjFPhZ3pMzobPvCXR6X/4E9AL+DYgCnuyAY54S5+u+nG90mgyDpmnXdOCxaoUQa4HReF5AsxDC1DJSJgPFHXWuU5z/nPsihPDDYyQXaJqmqr5rmlam2+ctYNm5nut06My+AGVCiARN00qEEAl4Vmidgo58vto49s/unpwG5+2eQIf0pRhI0f2v3m/diqVJCPG/wLRzPNdp0Yl9qeI82zA9uqx7RwgRK4Qwt/wdBIwCfmiZrawFbmnZ9W7gswvTyvahxYf3D2CfpmkvtvosQffvbwAv9kVXw+n6AizFcz/gZ3BfToWf2z05A35u92QLkNXCbvEHxuPpg7ovLc/gTXT9+9JmXy64DTvfUe+WaPVv8PixmoAyYEXL9kRgecvffYE8YBeem/uM7vvdgc3AIeAjIOBC9OMs+nIVnmX1LmBHy8/1LZ+9B+xu+WwpkPAz7ks08DVwEFgNRHXVfrT8vxCP+6a5Zf97f4735Ax96RL35Cz7cj0eVthh4D9129e03Jc9wPu0sPt+pn25YDbMyMg1YMCAgYsIXda9Y8CAAQMGOh6G0TdgwICBiwiG0TdgwICBiwiG0TdgwICBiwiG0TdgwICBCwxxCsG8U+w7Vyc6d0AIUXtW5zLYOwYMGDBwYSGEGArYgHc1TWu38oAQ4vfAAE3T7mnvd4yZvgEDBgxcYGhtCOYJITKEEF8JIbYJIb4TQvRq46t34MnRaDc6TYbBgAEDBgycE+YBD2qadlAIMRh4HY86JwBCiFQgHU/SWrthGH0DBgwY6GJoETS8AvjIozoBQGtV0fHAx5qmuc7m2IbRN2DAgIGuBx888sunqw42Hnj4pxzYgAEDBgx0IWgeufIjQohbwSMyJ4ToJz9v8e9HArlne2zD6BswYMDABYYQYiEeA95TCFEkhLgXuBO4VwixE8jHu4LYeGCR9hPolwZl04ABAwYuIhgzfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iGAYfQMGDBi4iPD/AUOGkX6LCfUwAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "8gaFar6l4Wva"
},
"source": [
"mapplot(points)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "MoP1B7s-4y2j"
},
"source": [
""
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "UCAp6rAbTL9S"
},
"source": [
"# Referencias y Bibliografía\n",
"\n",
"* [Edwin Aldana-Bobadilla, Alejandro Molina-Villegas, Ivan López-Arévalo, Shanel Reyes-Palacios, Victor Muñiz-Sanchez, Jean Arreola-Trapala: Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text. Remote Sensing 12(18): 3041 (2020)](https://www.mdpi.com/2072-4292/12/18/3041/htm)\n",
"\n",
"* http://geoparsing.geoint.mx/mx/info/\n",
"\n",
"* https://pypi.org/project/snscrape/\n",
"\n",
"* https://www.geodatos.net/coordenadas/mexico\n",
"\n",
"* https://geopandas.org/docs/user_guide/projections.html"
]
},
{
"cell_type": "code",
"metadata": {
"id": "aKHaYa0RaJEa"
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}
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ghost commented Jul 2, 2021

exelente

@jmargalli
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Para fines prácticos del curso, buen aporte. A nivel de programación necesita optimización, recursividad y acceder a una BD para evitar la interacción. ! Gracias Alejandro ¡

@edukoski
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Me esta dando el siguiente error al correr la sintaxis

Traceback (most recent call last):
File "/home/eduardo/paparulo/main.py", line 2, in
import snscrape.modules.twitter as twitter
File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/init.py", line 15, in
_import_modules()
File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/init.py", line 12, in _import_modules
module = importlib.import_module(moduleName)
File "/usr/lib/python3.9/importlib/init.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/gab.py", line 13, in
class GabPost(typing.NamedTuple, snscrape.base.Item):
File "/usr/lib/python3.9/typing.py", line 1901, in _namedtuple_mro_entries
raise TypeError("Multiple inheritance with NamedTuple is not supported")
TypeError: Multiple inheritance with NamedTuple is not supported

Process finished with exit code 1

Lo estoy corriendo con python 3.9

@giovannilopez9808
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giovannilopez9808 commented Jun 9, 2022 •
edited
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Me esta dando el siguiente error al correr la sintaxis

Traceback (most recent call last): File "/home/eduardo/paparulo/main.py", line 2, in import snscrape.modules.twitter as twitter File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/init.py", line 15, in _import_modules() File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/init.py", line 12, in _import_modules module = importlib.import_module(moduleName) File "/usr/lib/python3.9/importlib/init.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "/home/eduardo/.local/lib/python3.9/site-packages/snscrape/modules/gab.py", line 13, in class GabPost(typing.NamedTuple, snscrape.base.Item): File "/usr/lib/python3.9/typing.py", line 1901, in _namedtuple_mro_entries raise TypeError("Multiple inheritance with NamedTuple is not supported") TypeError: Multiple inheritance with NamedTuple is not supported

Process finished with exit code 1

Lo estoy corriendo con python 3.9

Trata de desinstalar y volver a instalar el paquete de snscrape, puede haber algún conflicto de versiones

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