covid.ipynb

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    "# Коронавирус в Москве\n",
    "\n",
    "<p>Попытка ответить на два вопроса:</p>\n",
    "<b>\n",
    "<ol>\n",
    "    <li>Является ли эпидемия коронавируса выдумкой</li>\n",
    "    <li>Правда ли, что эпидемия коронавируса началась еще осенью 2019, но ее замалчивали до марта 2020-го</li>\n",
    "</ol>\n",
    "</b>\n",
    "<p>Для ответов анализируется смертность (абсолютные значения) по регионам РФ без разделения на причины смертности. </p>\n",
    "<p><b>Все умершие во время пандемии считаются жертвами пандемии.</b></p>\n",
    "<p>Причин для такого счета несколько:</p>\n",
    "<ul>\n",
    "    <li>\"Особенности\" официального счета умерших от коронавируса</li>\n",
    "    <li>Если эпидемия началась ранее, и ее замалчивали, то смерти от \"атипичной пневмонии\" являются \"ковидными\", но в статистику по \"ковидным\" они не попадут</li>\n",
    "    <li>Помимо смертности от ковида возможен рост смертей от неоказанной помощи, от причин, вызванных самоизоляцией и проч. Эти смерти логически являются следствием пандемии</li>\n",
    "    <li>Возможная неточность тестов на коронавирус</li>\n",
    "</ul>\n",
    "<p>Эти, и не перечисленные причины, не позволяют точно оценить смертность исключительно от коронавируса. Однако, можно оценить общие потери, рассматривая смертность в целом. По аналогии с 2010 годом: мы не знаем, сколько именно смертей вызвано лесными пожарами и задымлением Москвы, но мы видим внушительный рост сметрности в целом</p>\n",
    "<p>Отсюда можно сделать вывод, что необычный рост смертности вызван необычными внешними обстоятельствами - пожарами.</p>\n",
    "<p>Логично предположить, что необычный рост смертности во время пандемии вызван пандемией. Обратно: если роста смертности не наблюдается, возможно, пандемия - обман. Не такая опасная, не настолько всеобщая и т.д.</p>\n",
    "<hr>\n",
    "<b>\n",
    "<p>\"Необычный рост\" определим по следующему критерию: выделим отдельно ряд по месяцам - январь 2008, январь 2009 и т.д. построим доверительный интервал (t) по каждому такому ряду, и посмотрим, попадает ли последняя точка (2020 год) в этот интервал. Если НЕ попадает - значит, имеется необычный рост смертности в этот месяц</p></b>\n",
    "<p>С ряда предварительно снимем сезонность двумя методами: алгоритмом, разработанном в ЦМАКП и методом <a href=\"https://www.statsmodels.org/devel/generated/statsmodels.tsa.seasonal.STL.html\">STL</a> из библиотеки <a href=\"https://www.statsmodels.org\">statsmodels</a></p>\n",
    "\n",
    "<hr>\n",
    "<i>\n",
    "<p>Источник данных по смертности - Росстат. Однако, в настоящий момент эти данные у них скрыты, по неизвестным причинам. В доступе только годовые данные</p></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from cmasf import season as seas\n",
    "\n",
    "import locale\n",
    "import re\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.seasonal import STL\n",
    "from statsmodels.stats.weightstats import DescrStatsW\n",
    "#import scipy.stats as st\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cнимаем сезонность, получаем тренды"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/egor/anaconda3/lib/python3.6/site-packages/xlrd/xlsx.py:266: PendingDeprecationWarning: This method will be removed in future versions.  Use 'tree.iter()' or 'list(tree.iter())' instead.\n",
      "  for elem in self.tree.iter() if Element_has_iter else self.tree.getiterator():\n",
      "/home/egor/anaconda3/lib/python3.6/site-packages/xlrd/xlsx.py:312: PendingDeprecationWarning: This method will be removed in future versions.  Use 'tree.iter()' or 'list(tree.iter())' instead.\n",
      "  for elem in self.tree.iter() if Element_has_iter else self.tree.getiterator():\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(110, 149)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# locale.setlocale(locale.LC_TIME, 'ru_RU.UTF-8')\n",
    "lst_months=['январь', 'февраль', 'март', 'апрель', 'май', 'июнь', 'июль', 'август', 'сентябрь', 'октябрь', 'ноябрь', 'декабрь']\n",
    "\n",
    "dct_date=dict(zip(lst_months, ['{:02d}.'.format(i) for i in range(1, 13)]))\n",
    "\n",
    "def convert_dt(x):\n",
    "    x.replace(' г.', '')\n",
    "    ax=x.split(' ')\n",
    "    try:\n",
    "        return dt.datetime.strptime(''.join([dct_date[ax[0]], ax[1]]), '%m.%Y')\n",
    "    except:\n",
    "        return x\n",
    "\n",
    "pdf=pd.read_excel('dead.xlsx', header=1).rename(columns={'Unnamed: 0':'name', 'Unnamed: 1':'code'}).set_index('code')\n",
    "\n",
    "pdf.columns=pdf.columns.map(convert_dt)\n",
    "\n",
    "pdf.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Код для просмотра данных по отдельному региону можно выбрать ниже:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "code: 643.0, name - Российская Федерация\n",
      "code: 30.0, name - Центральный федеральный округ\n",
      "code: 14000000000.0, name - Белгородская область\n",
      "code: 15000000000.0, name - Брянская область\n",
      "code: 17000000000.0, name - Владимирская область\n",
      "code: 20000000000.0, name - Воронежская область\n",
      "code: 24000000000.0, name - Ивановская область\n",
      "code: 29000000000.0, name - Калужская область\n",
      "code: 34000000000.0, name - Костромская область\n",
      "code: 38000000000.0, name - Курская область\n",
      "code: 42000000000.0, name - Липецкая область\n",
      "code: 46000000000.0, name - Московская область\n",
      "code: 54000000000.0, name - Орловская область\n",
      "code: 61000000000.0, name - Рязанская область\n",
      "code: 66000000000.0, name - Смоленская область\n",
      "code: 68000000000.0, name - Тамбовская область\n",
      "code: 28000000000.0, name - Тверская область\n",
      "code: 70000000000.0, name - Тульская область\n",
      "code: 78000000000.0, name - Ярославская область\n",
      "code: 45000000000.0, name - Город Москва столица Российской Федерации город федерального значения\n",
      "code: 31.0, name - Северо-Западный федеральный округ\n",
      "code: 86000000000.0, name - Республика Карелия\n",
      "code: 87000000000.0, name - Республика Коми\n",
      "code: 11000000000.0, name - Архангельская область\n",
      "code: 11100000000.0, name - Ненецкий автономный округ (Архангельская область)\n",
      "code: 11001000000.0, name - Архангельская область (кроме Ненецкого автономного округа)\n",
      "code: 19000000000.0, name - Вологодская область\n",
      "code: 27000000000.0, name - Калининградская область\n",
      "code: 41000000000.0, name - Ленинградская область\n",
      "code: 47000000000.0, name - Мурманская область\n",
      "code: 49000000000.0, name - Новгородская область\n",
      "code: 58000000000.0, name - Псковская область\n",
      "code: 40000000000.0, name - Город Санкт-Петербург город федерального значения\n",
      "code: 32.0, name - Южный федеральный округ (по 2009 год)\n",
      "code: 37.0, name - Южный федеральный округ (с 2010 года)\n",
      "code: 40.0, name - Южный федеральный округ (с 29.07.2016)\n",
      "code: 79000000000.0, name - Республика Адыгея (Адыгея)\n",
      "code: 85000000000.0, name - Республика Калмыкия\n",
      "code: 35000000000.0, name - Республика Крым\n",
      "code: 3000000000.0, name - Краснодарский край\n",
      "code: 12000000000.0, name - Астраханская область\n",
      "code: 18000000000.0, name - Волгоградская область\n",
      "code: 60000000000.0, name - Ростовская область\n",
      "code: 67000000000.0, name - Город федерального значения Севастополь\n",
      "code: 38.0, name - Северо-Кавказский федеральный округ\n",
      "code: 82000000000.0, name - Республика Дагестан\n",
      "code: 26000000000.0, name - Республика Ингушетия*\n",
      "code: 83000000000.0, name - Кабардино-Балкарская Республика\n",
      "code: 91000000000.0, name - Карачаево-Черкесская Республика\n",
      "code: 90000000000.0, name - Республика Северная Осетия-Алания\n",
      "code: 96000000000.0, name - Чеченская Республика*\n",
      "code: 7000000000.0, name - Ставропольский край\n",
      "code: 33.0, name - Приволжский федеральный округ\n",
      "code: 80000000000.0, name - Республика Башкортостан\n",
      "code: 88000000000.0, name - Республика Марий Эл\n",
      "code: 89000000000.0, name - Республика Мордовия\n",
      "code: 92000000000.0, name - Республика Татарстан (Татарстан)\n",
      "code: 94000000000.0, name - Удмуртская Республика\n",
      "code: 97000000000.0, name - Чувашская Республика - Чувашия\n",
      "code: 57000000000.0, name - Пермский край\n",
      "code: 57100000000.0, name - Коми-Пермяцкий округ, входящий в состав Пермского края\n",
      "code: 33000000000.0, name - Кировская область\n",
      "code: 22000000000.0, name - Нижегородская область\n",
      "code: 53000000000.0, name - Оренбургская область\n",
      "code: 56000000000.0, name - Пензенская область\n",
      "code: 36000000000.0, name - Самарская область\n",
      "code: 63000000000.0, name - Саратовская область\n",
      "code: 73000000000.0, name - Ульяновская область\n",
      "code: 34.0, name - Уральский федеральный округ\n",
      "code: 37000000000.0, name - Курганская область\n",
      "code: 65000000000.0, name - Свердловская область\n",
      "code: 71000000000.0, name - Тюменская область\n",
      "code: 71100000000.0, name - Ханты-Мансийский автономный округ - Югра (Тюменская область)\n",
      "code: 71140000000.0, name - Ямало-Ненецкий автономный округ (Тюменская область)\n",
      "code: 71001000000.0, name - Тюменская область (кроме Ханты-Мансийского автономного округа-Югры и Ямало-Ненецкого автономного округа)\n",
      "code: 75000000000.0, name - Челябинская область\n",
      "code: 35.0, name - Сибирский федеральный округ\n",
      "code: 41.0, name - Сибирский федеральный округ\n",
      "code: 84000000000.0, name - Республика Алтай\n",
      "code: 81000000000.0, name - Республика Бурятия\n",
      "code: 93000000000.0, name - Республика Тыва\n",
      "code: 95000000000.0, name - Республика Хакасия\n",
      "code: 1000000000.0, name - Алтайский край\n",
      "code: 76000000000.0, name - Забайкальский край\n",
      "code: 76100000000.0, name - Агинский Бурятский округ (Забайкальский край)\n",
      "code: 4000000000.0, name - Красноярский край\n",
      "code: 4100000000.0, name - Таймырский (Долгано-Ненецкий) автономный округ (Красноярский край)\n",
      "code: 4130000000.0, name - Эвенкийский автономный округ (Красноярский край)\n",
      "code: 25000000000.0, name - Иркутская область\n",
      "code: 25100000000.0, name - Усть-Ордынский Бурятский округ\n",
      "code: 32000000000.0, name - Кемеровская область - Кузбасс\n",
      "code: 50000000000.0, name - Новосибирская область\n",
      "code: 52000000000.0, name - Омская область\n",
      "code: 69000000000.0, name - Томская область\n",
      "code: 36.0, name - Дальневосточный федеральный округ\n",
      "code: 42.0, name - Дальневосточный федеральный округ\n",
      "code: 98000000000.0, name - Республика Саха (Якутия)\n",
      "code: 30000000000.0, name - Камчатский край\n",
      "code: 30100000000.0, name - Корякский округ, входящий в состав Камчатского края\n",
      "code: 5000000000.0, name - Приморский край\n",
      "code: 8000000000.0, name - Хабаровский край\n",
      "code: 10000000000.0, name - Амурская область\n",
      "code: 44000000000.0, name - Магаданская область\n",
      "code: 64000000000.0, name - Сахалинская область\n",
      "code: 99000000000.0, name - Еврейская автономная область\n",
      "code: 77000000000.0, name - Чукотский автономный округ\n",
      "code: 39.0, name - Крымский федеральный округ\n",
      "code: 46001000000.0, name - Московская обл. в старых границах\n",
      "code: 45001000000.0, name - Москва в старых границах\n",
      "code: nan, name - nan\n"
     ]
    }
   ],
   "source": [
    "for c, v in pdf['name'].iteritems():\n",
    "    print('code: {0}, name - {1}'.format(c, v))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/egor/anaconda3/lib/python3.6/site-packages/scipy/optimize/_minimize.py:770: RuntimeWarning: Method 'bounded' does not support relative tolerance in x; defaulting to absolute tolerance.\n",
      "  \"defaulting to absolute tolerance.\", RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "per=12\n",
    "\n",
    "moscow=45000000000\n",
    "vlad_obl=17000000000\n",
    "mos_obl=46000000000\n",
    "sev_kav=38\n",
    "dagestan=82000000000\n",
    "bashkir=80000000000\n",
    "tatar=92000000000\n",
    "lenin_grad=40000000000\n",
    "nnovgorod=22000000000\n",
    "orenburg=53000000000\n",
    "krasnodar=3000000000\n",
    "novosib= 50000000000\n",
    "primorje=5000000000\n",
    "kalinin=27000000000\n",
    "krasno_kraj=4000000000\n",
    "habaro_kraj=8000000000\n",
    "\n",
    "# а еще тут можно работать совместно\n",
    "\n",
    "cur_code=moscow # сюда подставляем код выбранного региона - НЕ НАЗВАНИЕ!!\n",
    "\n",
    "strCurField='Смертей в {}, факт'.format(pdf.loc[cur_code, 'name'])\n",
    "\n",
    "pdfM=pd.DataFrame(pdf.loc[cur_code, [c for c in pdf.columns if c != 'name']]).rename(columns={cur_code:strCurField})\n",
    "\n",
    "dcres=seas.seasonal_decompose(pdfM[strCurField], period=per, correction_zlevel=3, \n",
    "                              row_correction=True, static=0) # тренд по алгоритму ЦМАКП\n",
    "\n",
    "pdfM['тренд ЦМАКП']=dcres.trend\n",
    "# pdfM['row']=dcres.observed скорректированный ряд, без выброса лета 2010 года\n",
    "\n",
    "# pdfM['тренд STL']=STL(pdfM[strCurField], period=per).fit().trend\n",
    "pdfM['тренд STL']=STL(dcres.observed, period=per).fit().trend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Строим график - \"общая картина\"\n",
    "<p>Убираем выброс 2010-го года</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
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       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
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       "\n",
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       "    this.format_dropdown = undefined;\n",
       "\n",
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       "\n",
       "    this.root = $('<div/>');\n",
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       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
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       "    this.ws.onopen =  function () {\n",
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       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
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       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"948.8889140258607\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axM=pdfM.plot.line(figsize=[9.5, 6]);\n",
    "\n",
    "axM.set_xticks(ticks=pdfM.index[::2])\n",
    "axM.set_xticklabels(pdfM.index.strftime('%b.%Y')[::2], rotation=90, fontsize=8)\n",
    "plt.tight_layout()\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Графики смертности по месяцам\n",
    "\n",
    "<p>При выходе последней точки за <b>верхнюю границу</b> интервала график соотв. месяца рисуется <font color=\"red\"><b>красным цветом</b></font></p>\n",
    "<p>При выходе последней точки за <b>нижнюю границу</b> интервала график соотв. месяца рисуется <font color=\"green\"><b>зеленым цветом</b></font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "fz=6 # размер шрифта графиков\n",
    "alfa=0.01 # граница доверительного интервала = 1-alfa\n",
    "\n",
    "def plot_m2m(pdf, axs, color='b'): # функция рисования\n",
    "    def plot_part(int_from, int_to, left=0):\n",
    "        for i in range(int_from, int_to):\n",
    "            tpdf=pdf.iloc[i::12]\n",
    "            tpdf_2019=tpdf#.iloc[:-1]\n",
    "            \n",
    "            dsw=DescrStatsW(tpdf_2019.iloc[:, 0])\n",
    "            pval_str=np.format_float_scientific(dsw.ttest_mean(tpdf.iloc[-1, 0])[1], exp_digits=2, precision=2)\n",
    "            ci=np.round(dsw.tconfint_mean(alpha=alfa))\n",
    "            cl='r' if ci[1] < tpdf.iloc[-1, 0] else color\n",
    "            cl='g' if ci[0] > tpdf.iloc[-1, 0] else cl\n",
    "            tpdf.plot.line(ax=axs[i-int_from, left], title=lst_months[i], fontsize=fz, \n",
    "                           legend=False, color=cl)\n",
    "            \n",
    "            axs[i-int_from, left].set_xlabel('CI={0}, last point = {1}, (p-val={2})'.format( (ci[0], ci[1]), \n",
    "                                                                    np.round(tpdf.iloc[-1, 0]), pval_str), \n",
    "                                  fontsize=8)\n",
    "    plot_part(0, 4)\n",
    "    plot_part(8, 12, left=1)\n",
    "    plt.tight_layout()\n",
    "    plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Для тренда ЦМАКП\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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eGpCCAgBIVCGCITBN3IWUoo9H2GAU+wx6vlCQAiUEQIEtW+4oVPvX3jhv0JJgwZma6xRUCDKZT9lnJMnL7OWLc322svs1VfNPA8wkRAQArFE4I8/zIg0WLLEuXDqfQ5vGsPgGxJSwptPPUkICAEhkBqBe+81O+MM97n77lCRCoPZhDqgFA9jnEuXLrNddjF77z2z554za9YsCj1TH4SAEMgGAULyMDqzbf78s7tz7Fizk0/OphVdmw8CYfANCSn5zJDuFQJCQAgEhUDz5mbPPus+Bx8cVKsZtRMGs8moIwW+yB/nuHFmbdo4mIFbJASEQPQR+P13swcfNBs50mzGDNdfsvTxHj/1lFnt2i7T+gYbRH8spdDDMPiGhJRSWCkagxAQAvFGgMB4Uq/XresKLmYZ+J7v4MNgNvQxk/paXbp0scWLF9ucOXNs0KBBVr9+fdt888292Mc6dep4cYt8n099LfITkHPg88/NXnvNuX6JhIAQiB4ClH164w0nmGApQVCBCNMjhO/008022oh6e2ZDhpiddJIZSghR4REIg29ISCn8POoJQkAICIHKEbjhBrPLLnOfgQNDRysMZpM4qMrqa/nXTZgwwX755Rc755xzrFGjRta4cWMvPX2HDh1szJgxedfXGjHCrEMHs2OOMXvkkdAh1wOFgBCoBIFffjEbPdoJJ2Tig8iufsIJTjjZf/8V408I6SO5ITqeCRPMWrcWvIVGIAy+ISGl0LOo9oWAEBAC6RAgSOLdd91np53SXR3492Ewm4qElIrqa3EdwknHjh1t5MiRVqtWLfNrbpExkiyS48aNy7u+FgG3W25phhEL/3bSEouEgBAoHgJLl5q9+KITTMaPN+Mdhdge27c3O+UUs3XWSd0/XL4OP9xZVnin11uveGMphyeHwTckpJTDStIYhYAQiC4CqAkRTHbc0UVzF4HCYDYVCSkV1dfCJezSSy+1W265xeri/pZAF198sZ111ln23nvvLbek5FNf66abzC65xOy001wArkgICIHwEUBRcM89LhAeF0yoZk2zU091VpPddsu8T+3amY0aVZT8I5l3skSuDINvSEgpkcWiYQgBIRBTBP7zH+fixQd3ryJQGMyGYWVSX6tBgwa2yy67eHW1jj76aC8eZeDAgVa1alWrXr263XrrrSvEpORTXwv/9s03N5s3z+yzz8zq1y8C+HqkEChDBIgLmzLFWU0ef9zsn38cCLhxIZgcf7zZmmtmD8yvv7r6tnPmmD3xhNkRR2Tfhu7IDIEw+IaElMzmQlcJASEgBIJHAP+GzTZzPkc4UxM8XwQKg9kUYVgrPbKicfbta9anjwu8HTQoCr1UH4RA6SKApeSuu5y1A0ECIhvXmWeaYQUhoUW+RN0UCrWyneL2hVVGFDwCYfANCSnBz5taFALlgcBff5m99ZYrQMhBO+SMVCUB8vPPu/yZRc6FGwazicJ8VTROAnRZvmh2v/rK+bOLhIAQCA4BCi2SnAKrCVseRNFF4kewmlBctWrV4J5HS8SvkA2sY0ezoUODbVut+XO4ii0j/VoBSUJKAcFV00KgZBFYtMjs0EPNXnnFDXH11V0UMnkht956xZ8SYFIvA9+BGrUiqsQiUTkLKUB+6aVmN95ohufdtdcWaRL0WCFQYggQbodgct99ZrhhQbADtr2zznK/F4rmznXJMH76SUVbC4VxGHwj3kIKUVasdpEQEALhIYAFhfyOOBI3aOAqaH36qdmPP1bcB1+ASRZe+BsuRTWuciQEPdT2qPC//76oPglhMJsoTHGqceJtt8UWZmus4bzuKssgFIVxqA9CIKoIkAr4gQeccEINIggWgPsVVpNDDgnP6P7QQ2YnnujebQSmtdaKKmrx7FcYfCPeQgrziiPxzTcHbyuM55pRr4VAYREghgKNP6qx7bc3e+kls/XXd8+cP99FH/NBaEn8+cMPqQUYOEgqC0wpCzBw8pNPdh/8EopIYTCbIg5v+aMrGyduIcOHm/XrZ9a9exR6qz4Igfgg8MknLvcHhRQXLnT9Jr4EwYTseXXqhD8WPJEIwKduyoUXmt1yS/h9KOUnhsE34i2kEG2FLW+//cweftj5xouEgBAoDALs+PjFkLd1002dqxc/MyEEGCImk4UX/k4nwCRaYLbd1qxp09JQSuCIjTVq8mSzFi0yQbFg14TBbArW+SwarmycLE+WF7UVvv46t8xCWXRFlwqBkkAAtkAg/AUXmGEcrl7dVX1HONlnnxULLhZjwBipcfv67TenU9t332L0ojSfGQbfiLeQgl3+2GPN3nzTbJNNnLi8116luRo0KiFQbASuu87siiuc5eTll4NJw8KY8A9ItsD4Vhg4TDKVgkoM5Qo1QDgRf/ut84coIoXBbIo4vOWPTjdOP9j21lvdoUskBIRAagQ4+GOBfPBB58LVs6fZRReZ1aoVLdQw/J9+ulNC/Pe/TpAS5Y9Auv00/yeYxVtIQYRfvNisc2dXCQiH4iFDXESWSAgIgeAQIP4L1RhOvaRnCUsZQCGLRAEGXxxo9ux4lxO+4w6zLl3c57bbgpunHFsKg9nk2LVAb0s3Tmpp7ryzMxCy7ILOOBToYNSYECgiAtOnuwxaWB2pNXT//c5yEkXiqIjhmropl19uhr5NlD8C6fbT/J9QCkIKKLACYfpdu7qKQOed5+JUiqydDGKC1IYQKDoCjz5qdtxxTlWGe1Lz5sXrEu/24MFm11zjrDpxpcaNzV5/3X323LPoowiD2RR9kF7a0/QpM1u1ch54uLBI3xWFWVMfooQAR6wBA8yoL8TvuHaR4jfqySa++cYVeUTv9eqrkdh2855Wjr7MQbFCNzPZT/MdZPwtKYkIvPii2QknuDgVypaS2kFxKvmuEd1fzgjwTh12mNmff7rgbjhSMYnoTKIxcZX68st4qroZA1nR8D34+OPiO21neHgv5rQH9exMmCoaYvzWmSIKwan8T1Doq524I4ABmyB42ALV4G+/3Qny1DyJA40YYdahgxNWKPGF801cCUsvoYzE0pEkk/wziR8qAvA3CQsKNT+Z7Kf54ltaQgpo+HEqrEDKjRKnEgFNZb4TpfuFQOgIvPOOC1In6J1S3GTSiwKRy5KSwjgat20bhR5l14devcyuvtp9evTI7t4CXR0GsylQ17NqNtNxsuw5iKHnIjuQSAiUOwIUYzz7bFfvZNddnc4KQT5OhOUBR4DnnjNjG8YaFEdCz3XQQWakTieskYK0qQhhsn59V8asIiGmRo3cEch0P839CaXi7pWMAHEqnTqZ3XuvE5WHDTM744x8cNK9QqC8EEBNgzqZ2ie9e5v16ROd8XN65BQJp0QZUSg1USFGDJfcaitnBUIFBueIAIXBbCIwzIzcvejnU0+5ati77ebyssRpiUUBZ/WhdBDgOHXxxf9WbcerHm/buFoh2Hp32ME5B/BuE4MWJ8L43qyZ2Zw5TmgkbTpjITboiy8ca/E//t8kOEhF5MFBeKlIiMFCU1lcXhh8o/QsKf5McBjAFsnbhdMeAaqUFFacSpzeR/W1GAiw+yGgsNNhPSHeK0qnNN7tPfYwe/ttsxdecAJLXIi0zaRMB18ypEWEwmA2URhqpuNMXGJPPuk8HkVCoNwQoABimzbO7RG3IfITIbzHnTgakr0PPRcFJ+NyLJw50wkoJL1s394JjlWqpJ8NhBTYeUVCzFdfmf3xR8Vt0DaJc1MJMZtskj7GL33vKr+idIUUf9xTp7o4lblzzQ44wNnvi1FVKN+Z0v1CIAwE2M0OPNCMNEeU6iVlSxSd8seMca5eRDnj+hUXIhMhnIUPuTsjQpke3iPS3Zy7kc04Kb0F6+B1gI2IhEC5IICQTn6SSy5xB9hDD3UCykYblQYC1CTmOIjOiCQA3bpFf1wffeQEFMqKwTqYn0wElHQjAwuEnlRCDAkHWA8Vk4SUlPhmw2w8Oxj1VNC8kluSOBU0sSIhIAT+RQC7PipjKl4dcohLcRRVm/5ffzn1DjVGsH/HwTkamzxcnnLMWKtwJo4IZbWfRqTPuXQjm3FigCfAdtYsd5iJanrVXHDQPUIgFQLoc3EjQveDhYFDPA4pQRyIo4Q6cR24enFIp3bK9ttHqXcr9uWDD5yAQk4o9Fw4N4Q1H7AtQr0rEmLeeENCSjBCCq1wACOtw+jR7uCFIx/VfURCQAiY/f23SzMMZyLRBJGF+UTUhYHpwIFm//mPiz+jPlLUiVTOrVu7D4qSCFE2h/cIdTvrrmQ7zlGjzNq1czUWJk3K+nG6QQjECgG8ZzFQE5C99dZm48aZ7b57rIaQVWevv97VTWnSxHnfRtFpAJc7BBSEx/PPd2W1ouJ9ne1+mtXk/P/Fpe/ulYgKNitmGBsmajKcEm+4IT4OibnMsO4RAukQ4L3gJHb33c4iwW5du3a6u4r/PWlmsIyiCkPVE/U+kyZq/Hj3wbIbIQqD2URhuNmOEy0ihzVSr777rtlOO0VhFOqDEAgWAQzT5EYhIB52QJ4h4jairqfKFwV0c1hI33jD7KabXKm9KBF7zsEHm/38szuu3nJLdAQUcMp2P80F2/ISUnyEUBfgb49oisPxgw8qTiWX1aN7SgMBVEmolIiQo0gEKT3iQuzccFMq0XfvHt1eI1Dh6kU+SByAI+ZGFwazicLk5DJO9FoXXugCiAnREgmBUkIANx4qx1PgEKGEcDn+LhfClYosfhREJBQTpUQUCBc0BBTSC190kROiomJB8fHJZT/NFtvyFFJAiTgV3C6oBYE2liTgpWzXzHZl6PryQMC3d6+7rrOgNGwYr3GTxnebbVzRVtKUROzwvxxMv4oYLqekRI8YhcFsojDkXMa5aJHZ5pu7wwLxKVE5xEQBT/Uh3ghQ6wRvWUphNW7shPCIZEUPFVhKVlE3BZ3188+HF++RapCETxMWim4Lxx/YdNQEFPqey36a7cSWr5ACUnAfDg1kCqpWzcWpUE5VJATKAQHcuygXjHafGBQcc+NIuE6hZGA8Ua2HRCoZEhLwIQVxxCgMZhOFIec6zv79Xd3NiMqYUYBWfYgRAr//7qoysGVy+L3iClfYMC6peIOGGnc3QjFxryJrFsHpxSJKfyGgkGjzssvMrrsumgKKhJQ0KyRXZrNSszhg4ujHaiBOBbs+Ymu5vq3FejP13HARIECewz0ciojgOCe/xwK0//4uYAAbedRUTlh4yERG2V8sP2GlZcliRQW2n2bxzGJcmus4OTDgBUk6VtxjNt64GL3XM4VA/ghwCMZ18dNP3Tq+7z4XmF3uhFMNgkr16ma4gGE9DZuIjSHdM/sNgiOZ1aLGzhIxyXU/zQbX8rakJCKFjY84FSKUKA5HnMoGG2SDpa4VAvFAAG0+O+GSJc6KGHcHZBQN+Cqwwz/zjFNDRYl8NTwxM8TORJDCYDZRGHY+4+TQgFYT9wvyrYiEQJwQIL/IzTe7miBYDigxdddd0c83EibGWEvZrps3N3vqqXAFBIpKUgFg3jyzK690rCLKAgrzks9+mum8SkhJRAqNJ3EqaGNRm+FCQkSVSAiUCgLYs3G8ZSe89VaXMqQUiFyZqAePOMLsiSeiMyIEKOJ8qOVCueDttotO3xJ6EgazicLA8xknRdQwhpGmlJDG9dePwojUByGQHgHWLp6wHLwJ27vxRrNzz43+ITj9yIK9AkspVejZqu+80yW9DINIWoCAQmxQz57O9S7qAoqElDQrIx9mU2nTxKm0b+8iyIhTIeCVxOEiIRB3BL74wmzffV12KVRGRAuWCpFLcqutXCriDz+MTgIAfCsoHMsHS09EqWD7acTGm+84zzvP+ayTrrV374gNTt0RAhUg8OSTTkD58Ue3LRIsr1TaqZcKFg3SEpPpDFZC0stCEgk18bZesMDtKewtcaF899NMxilLSkUoof3ELkqcCjZS8r8Rp0KOOpEQiCMCCCYEbBMT0bGjK34YB1VNNlijHrz0UqdkIAlGFIi9A4tVxK1WYTCbKExHvuPE2E52r5o1nTy89tpRGCghxXUAACAASURBVJX6IARWRgCrAG5DpK6F2Pb5nTwposoRgI3ATijiSvhmoVjlK684AYVEBlhPyDAWJ8p3P81krBJSKkOJjEcnneTiVEhYPXmys66IhECcEMC1izgr3BipKv/AA9EsrZsvpoyzXj3ncE31vWLHlGHdQQ3H/kEJ5zp18h1hwe4Pg9kUrPNZNBzEOE8/3QUbc4i5+OIsHq5LhUBICHzyidnJJ7sKC2SXHzkycvVjQ0Iit8fgULPzzmaffVa4sE1CQ/FOXrgw+mW+UqEYxH6aboYkpKRDCNXZ0Ue7Kj9k/iITmEgIxAUBguNR1bz4okvhQrxGVGuJBIEpJYN5R6OglpoyxezII93n8ceDGF3B2giD2RSs81k0HMQ4P/rIrFEjlxkJD8pSfp2ygFaXRgABnEDuucfs/PPd4ZfM56NHu1JwouwQmDbNhW+ut54Z7zyluIIi2HGLFm6OyOBFMoM4UhD7abpxS0hJhxDff/utE6vRiJKuFRugSAhEHQE0+SecYPboo65Q6QsvOEfbUibyw+KPU7u2i24upuXz1FNdbBsfgvojTGEwG4Y/e/Zs6927t82cOdNmzJhhs2bNsquuusqqVatmLVq0sGOPPdYmTJhgjz/+uC1ZssR69eplDRo0sJ49e9qCBQts3rx5NpigECPw91yrVauW1ahRw67OML4qqHGSX4XXCq9CvAtFQiAKCOBViocpWc6JbcDdi0QPotwQQNgbNMixURK+BkFTpzoBBWsN2QIvvzyIVovTRlD7aWW9l5CS6dwinBx1lEvpQoakQkdTZdovXScEKkIAlRqnJ1KUbLutKyIYYXejQCcRjvLww+GmZ0keAFGQqN44IZBaJ+KO4GEwm0SIWrZsaZMnT7b27dt7QkrdunXN/5//c86cOZ5Ag6DSr18/Gzp0qI0dO9aWLVvmfapUqWJt2rSxTp06WY8ePawern5pKKhxvv66y3pNrgYStylcMR3y+r7QCLDlUI6JKuVUVMAKIMoPATDdcUen74Kl4C2dDzEv6LgXL3ZhzsS+xJmC2k8lpAS1CkjXevvtZgcd5OoxSEURFLJqJ2gEsB9fe63zSSE6j9yp5UIzZrj0LPjkvP9+4aIeK8Pz3ntdSh0+lHWOOIXBbCoSUo466iibSGSqoQNyvyf/r1u3bjZ16lTj5/Tp023atGmekNK0aVPbe++9bcCAAdasWTNr0qRJWpSDHCfleAhbJFsS/v8iIVBMBNju2faJmcLlSxQMAhz1KCuGzolsX7mmHn/2WVebBg9sEhjgmRx3CnI/TYWFLCnZrBJWF4wQSwqVdijOJooHAqTPYJfAGhbBit+BgsgOSMW5ddZxFpQddgi0+Vg0hpCCsEL+TRLQh01UA2O9RbG4ZAVYhMFsKhJSEi0prVq1skmTJi23qCRaUvr3729Dhgyp0JLSuXNn6969e4WWlD59+lhf4pMSCAEnCEIrSj4V0rmSk6JQGYCC6KvaKG0EEq0oWPa22aa0xxv26M45xxnmTzvNDP1TtvT00y60mSMkIZOEN5cChcE3JKRku1LYAfDvJ78fkVUchkTRRoBDyTHHuFyCEU8FmzeQvga/enV3SC7X9YltHrcvVGBUMAuTyOSF61Hdui5PbQwsrmEwG6Zg4cKFdskll9iUKVPsiCOOsK5du3rxJMSkHHnkkV5Myvjx473viUkhFoWYFFy+5s+fX2FMSs2aNT2XsUwoyHGyraCzwvWLxI/4mYuEQDEQkBWlsKj/9pszzLO1Z/uuoyfj+MGR8bbbzLp0KWxfw2w9yP00Vb8lpOQyo3fdZXb22a4qPVYVNNai6CJA4DJBzBDuT9QKKWZAdaGQIoMU6hoIgYysUuVKJA1AnUh2Ply+wrQm+fVacDjG8TgGFAaziQIMQY/zscfcAQRdwMsvy5oShTkutz7IihLOjCOc4K5FODJuX7VqpX8uyTRJsvHnn2Z33GFGMdhSoqD304qwkZCSy4pBhXbKKWbjxpkdf7xL+yBbfy5IFv4egpYps/vLLy4CjgMr2YE6dy78s8N8Aqoeoib5SRGHtm3DfHo0n4VdHcffdu2crT4s2mUXp7zgE5PSzmEwm7Dgr+w5QY+TWr9sK6QoJa0oKV9FQiBMBGRFCQ9t2OqYMZnVC0aoIdAeAYXayZ06hdfPsJ4U9H4aqJBSKqkkc55MCsftuqsZKU+HDTPr0CHnpnRjARHwMz2de66zfuGqhwWMKk2rr17AB4fcNPkm8b3HeXbEiJAfHtHHzZ/vCgTgCIzbVZCJ7lMNGSEYwYSTK7WVYkJhMJsoQFGIcVKHAl91Qp9w7RAJgbAQINSSnChk9FIsSuFRpwoFOs8ff6w83JBksAgo1BUu5eNhIfbT5FnM25IS91SSeS3r114z228/l3/yzTed06IoOgj4cQmbb272wQdma6/t8v/hFoVmHQ17KRAcCk5FXsNPPzVjvCKHAC5XuF/16uWEuELTf/5jNnBg7BLgh8FsCg19Ju0XYpyJnoVvvWW2226Z9ETXCIH8EaDOxhVXKKNX/khm3kJFx4rEu3EBRTfKvkAdJfSGpUqF2E8LJqTEOZVkXgvI3yXweSeCkoBlUfERmDvXCY3JKo9XXzXbe+/SKnDQs6fLNoc9Gbuy6F8ESHBPMYt113XWlEK+n/j+YKUjupJnZVC3IypTFQazicJYCzVOXjuMtXj/PvRQFEaqPpQ6ArKiFG+Gec/Hjzej2CNVKXyaMMHspJPM/vnHbOTI0tGDpkK6UPtp4vMKYkmJWyrJvJY6BxPs/GRSIs7h/6sh59Wmbs4fAb/ad0XuT356WPw0/ID6/J9YnBaItcGKQuoQXNhwbxKtiABFLB54oPB2dz8nbbNmroBGjCgMZhMFOAo1TjwKeQ3RicycadagQRRGqz6UMgKyohRvdhNDXUnyuv/+rtgjrIYj4ahRrkRWqVOh9tNAhJRSSiWZ90KaM8ds553NfvrJDFGadA6i4iFAZiuyXKHJxs0rOQ0HuwrleLff3n0f57op1OoZMMCpcQcNKh7mUX6yXx58u+1cWpZCzTfug3AnPmeeGWVEVupbGMwmCoAUcpx4+eHtd9ZZZiSAFAmBQiEgK0qhkM28XQLoCaTfemuzHj1cyCsCCoU0iVErByrkfurjl7clpVgTEQY4WY1tyhSX8hW3Eip74fYhCh8B4jNw80JwJPYkVRpehBSEFTKz4UAaR8KljYxepA8hrXKM3ItChxtVFzliK1sT+XSKeCAC84mURM1Ws2Y+rYV+b+T20wIhUMhxkqeBcDAOkLyOYgEFmkQ1a7KiFH8RkOSV2tBk8YLQfVGmLO7OGdkgW8j9VEJKNjOR6bVU+abaN8H0L7zgAupF4SKAGvPuu9NHElIJnEJ/ZGJ6553CadcLOXoiJuFWyY6xhXxmXNt+5BGzY491JcJxzQyacCfD1s9n7NigWy94e2Ewm4IPIoMHFHqcfnjYBRe4urEiIRA0ArKiBI1o7u19+63TiVKrBu/xNm1ybyuOdxZ6PwUTWVKCXBlotKnqRYqX3r3NSAsrCg8B35q10UbOrWe99VI/GzUIAfRkaCMdByqROBGuhVhRSCHyxReuSKUoNQJEMm67rcMKSyfumUESVb5QqWVbjjjIPuTRVhjMJo/uBXZrocfJa+kn1yNnwwYbBNZ1NSQEPARkRYnWQiCh5qJFwbOUaI2y4t4Uej+VkFKIVcCKJQclq5ZAWtyKRIVHAF8LVBrffGOG1pwy0OkI1x9SEu+xh8vMFqeCnJdf7qqZX3ihGUULRekRIA0LKm4iGrG2BUWcTBEScfVEtRbD+jthMJug4M6nnTDGedFFzopCuBhJ90RCICgEZEUJCkm1EwQCYeynsqQEMVPJbVDx+/TTzTbZxFWdXn/9QjxFbSYi0LGjS0qejbsN1hSKO+LuhRXm8MPjgSkphLCiEKWHZaBu3Xj0u9i9hMMTt4MC4auvgrM+3XGHWZcu7nPbbcUeZU7PD4PZ5NSxgG8KY5yzZ7us12uu6TJRxyw8KWDE1VyQCPhWFAKziX8QCYFiIhDGfiohpVAzjJCCsEKWKTT7cdLSFwqTQrVLutdDDnG+FR99ZFa7duZPIhsbpWFx0yOwOg7z5Bco7NrVxUCJMkfAL7Z45ZVm/ftnfl9lVzZu7CxxuA7utVcwbYbcShjMJuQhVfi4sMZJph8yfF17rcv4JRIC+SKQaEUhzTXeqyIhUEwEwthPJaQUaoaJpMLti9oVaFrPO69QTyrvdtm5d9zRacYJXj7xxOzwwBpBfAKpiHHPO+ig7O4P++rvvzfbckv31C+/dBmlRJkjgDsgVijU26i511or83sruvKTT1xRDE4MH38cDyG3gnGEwWzyAzqYu8Ma56xZLsN5nTruNS1kDdFgkFErUUdAVpSoz1D59S+M/VRCSiHXFQH0BGeTmw4ta9DBuoXse1zaxsUGIZDMTVRTysUSMm6cS8uBgIKgEmXCekIMCtYUYlJE2SNAcnuS3FN4lQKs+VCvXmZXX2121VVmpHaKKYXBbKIATZjjRF9C9XnKF1HGSCQEckVAVpRckdN9hUQgjP1UQkohZ5C2ccchNTGF5N58M3/NbaH7G6f2X3rJ7IADXBYvsnmR1SsXIvNTw4ZmaMVx+dp331xaKfw91H7BioLQi3oWNa0oewRQHpAsYZttnPUj1+KOxDQRfMBcUBjDt3Bl36Oi3xEGsyn6IElnucoqtox5C4EIdcOYTiV6tpYY5lMIAaXCPIKkhyTa89lDYZ4SXquyooSHtZ6UOQJh7KcSUjKfj9yuxJ2oRQuzJ580O+ccsxEjcmtHd62IgJ/zD3c6Yn/QjudDlImlSjjB8wTRR5HI5EVgNpm94Fqi3BFo2tTsxRfNJk40I31wLjR9uhNo+SDcxpjCYDZRgCfscR5xhNv6CXIulyrUxZ5nZNAOHcxGjnS6CF7NNdYodq9yfz5WFDxUf/nFTLEoueOoO4NHIIz9VEJK8PO2cotkY8LVi3gCXItOOimMp5b2M/zCmaQQ5qCZi5tXIkJUCie2AK04QdB77hkt/Ehti9aeAqHE32STHCBaI4lGb1gzJLVAWKHwai6Eq9jQoe5DdrkYUxjMJgrwhD3OadNcFnoMte+/n7vRLgrYxaUPeF/ihelT3AtrDhzoki8oo1dcVmD59DOM/VRCSljriSrXVDivUcMVk0M1IsoNgVdfddm4CH7GzYtUz0EQVi5UcBR2pMBjlIiq8ji3d+tmNmBAlHoWz75g4UQoxRKH+xd+OdkQhVtxL0TNifKhssKh2bRbpGvDYDZFGtoKjw17nGj199/f7JVXMi/fFAWc4toHyh+ddZZjs2PHupJIP/9sNn68C1uMG8mKErcZK6/+hrGfSkgJc01dcYVz02nSxAwVm5yUs0d/yRKzXXd1sQR33mnWrl32baS6448/zLbe2hWELERV8lx7SuEF+oXPApYe1d3JFckV7yNwnqx7p55qNnp0dm0++qhZ69auaCgpxmNOYTCbKEBUjHH6NWNJQoiHITU/RcEj8PTTzrMaeuIJs+bNnefukUea1apl9vbb8QsbkxUl+HWiFoNDIIz9VEJKcPOVviVcivbbz7kTSSOeHq+KrgA3ig9glcLZO183r+Rn+IX5TjjB7MEHc+tj0HeRGmjIEJWwDhrXhQvNNt3UjHThCH8UesyUjj/eqWfjqqJNGmcYzCZTaAt5XTHGiTUFly/yfOD2xQF6880LOcryaxudEhYrLA9YU7Cg+OSzjLjFp8iKUn7rOG4jDmM/lZAS9qqgQjiWAA5GzzxjdvDBYfcgvs8jOxpWKIoO4Oa12WbBj2XxYqdu++EH9wyKHRSTvv7aZaFizBykY+5WVEwoK3x29+7OfQ6nb4TfTOjXX52rFyXFcfWKc1Tu/483DGaTCbSFvqZY4+TASUpiNPssHawr2XoYFhqbuLbPFkmmf5IfEo/So8eKIyHTF6FnuNzFKT5FVpS4rsjy6XcY+6mElGKsJ78uR926Zu++6yqliypHgBgAVGFEn2JV6NSpcIjdeKOrQ0LGMDKHFZMIyB4+3EWC9u1bzJ6U5rO/+87liKWoI251a6+dfpx+7BLxS8OGpb8+BleEwWyiAEMxx8lhmVwLZJ1iuVFDhexfotwRQF9Acj2yXrVv717HiozrePDusouLT6Gc1nHH5f7MMO6UFSUMlPWMfBEIYz+VkJLvLOV6/9lnm911l3OYnTRJaV/S4di7tyuYR8FFkhDkWtsi3XP4HjcgDq7kfKR0NPEgxSCyeGFF4UTD7+usU4xelP4z8Q0hR+ztt5uRoCAdUXwB3x3iyvAxKQEKg9lEAaZijxPXr2uucZ6bq67q9C0crkXZI0AIIV6/vIawUXKdkPwwFfnxKeRboYZNlMsayYqS/XrQHeEjEMZ+KiEl/Hl1T+QgvPvu7hB8881mF11UrJ5E/7lYm7CiVK3qLClhcBdOElde6QLzCdAvBnF6Qe3ap48ZQpqoMAjg0I4LJimeeR85PaYihEUy8yHEUsCxkMJyYUZbYathMJsQh5PyUVEZJ3ka2FoIU2Sb6dcv+PC6KOBdqD6QnO+UU8weeMCx0alTMzOCgjVbO/fg/hVFT01ZUQq1atRu0AiEsZ9KSAl61rJpj8NR48ZmqNdIqysn5ZXRg4uDEaqvW291TsVh0Pz5LroVjvHpp+5QGiYRu7Ttti6XJgdj0tOICocAsWHPP282YYLL2pWKiF9BDc6Hk2WJUBjMJgpQRWmclOdhqc2b5xLMYVhHDyNKj8Bll5ndcIPTF8yYYbbhhunv4Qpc7jDGU+CxSxdXGzdqJCtK1GZE/UmFQBj7qYSUYq8/XEw4eOPWQ70GDqWifxHwD4U4HmPXD1NzjQWDOBAcyUlXGyahZh01yrm49ewZ5pPL81l+nliy7+HKVRGhTCA9E+mvcYLfbruSwSoMZhMFsKI2TnJzEJdCOBSHZ2RkeXVWvlIQLC680OUQmT7dlTvKhohPwXA6d2704lNkRclmJnVtsREIYz+VkFLsWebgQ+Vr4lLwjSd/osghAAfHuoRggssXloUwiahMrCk4P2PZCKpoZLoxUGCQAzDO01hR+CkqLAL4jyCA4O712mtme+218vNQIuB2yOeNNwrbn5BbD4PZpBrSrFmzrEePHla3bl2rV6+ebbDBBvbaa6/ZokWL7PPPP7dXXnnFmjdvblvhjmckYbvW1llnHevZs6ctWLDA5s2bZ4MHD7bqZMBLQ8UcZ6qukbuB+h4Y1hs1cimKC5G4MB02cfgeIY7s37hpPfecq+mbC5G9HuEwavEpvhUlCjlbcsFV95QXAmHspxJSorCmUOnsvLMZ3ApnZWz/5U7Y5bGeUFPm+utdtq1ikO/EjOrullvC6cGZZ5rdc49Z//7OYV0UDgKkBiJr3Mknu3LVyUTcGC6HrAPWQwlRGMwmFVw333yzNWzY0A477DA744wzbMCAAbbJJpvY8OHDrVq1anb66afb0Ucf7QkxNWrU8L7/4YcfrF+/fjZ06FAbO3asLVu2zE4hSCGGQgpdJiM9KYo5PJP0EcMe2n7RvwhgNcErE50RGbryrSAftfiURCvKRx9lbyHSWhECYSMQBt+QkBL2rKZ6HpF/zZq5TE7EXxQro1RU8MDhGMdjNNpwp8qCmQvZ559+cvEoWLyoU5Kp83OuffrkE1ebhbLUPE/uf7kimf191MihuONvvznLWaI6G6EZSxo5TL/9tvDrIPve53VHGMwmVQfnzp1rffr0sTXWWMOwqmAhady4sR1yyCH2+OOPe/9funSpValSxRNcqlatag0aNLCpU6dat27dbPr06TZt2jS74oor0mJQzHGm6xzhd9RtJVcGmbBJUXz44enuKo/vMXBiNSHhYlChibzSsFy8O0nqh+d1MUlWlGKir2fngkAY+6mElFxmplD3EHtAMC7uJKQeKdcoSg7qWJZwwUFgww2nmHTJJWY33WR2+eVm111X2J6cdpqzppGCJoNDV2E7U4atU4+GinBY7rDg+eTnL8VHBH+cEqMwmE0mkLVu3dpGjBhhH330kT355JOe1SSRJk6caF9//bVxXf/+/W3IkCGVWlIQfvom1RfC6hJVomsMmYKE6GWGDjU755yo9jacflFXl2KN6GzYitFfBUXoG6ifgjMDQiGuZMWgxKz3sqIUYwb0zFwQCINvSEjJZWYKdQ+qnQMPdJaD5ENSoZ4ZtXb/+cdhgJAWFXcnShmTRoYk/JQ3Xn/9wqCGuhCBjIhQOHImhQUL05PybZUK8sQhVatmRoStb8nCBfP++92nTZuSwycMZpMKtG+//dZ69+5tf/31lx144IHWrl07z3Xruuuus02xbBl1VdtazZo1DavLsGHDbN1117VevXrZ/PnzYx+TUhEuiSmKEVjIn1FRkcKSW4hJA8IFimrxhIPhDocXZtC5U556ylmsiE95+22XiTxsQh+CDkyxKGEjr+flg0AYfENCSj4zVIh7OQSj2sHlBL/3rl3doalcyE/dQsA8aZlXXz0aIydf5R13OBUnmvZCkH8Qxu6Pq5uoOAj4mdX8+kUEDODmh2obte6aaxanXwV8ahjMpoDdz7jpOI2TjNikKCYbOgZW3MDKybiOzo6cMhguqZ+KMIHuoBBERnEsWLAddIRh1k+RFaUQM6o2w0AgjP1UQkoYM5ntMyZONDvpJLMlS9zB6IQTnGWFClSlTBTH22knsz//NHvzTefyFRUiRygqNjIIIUgGnScUG/8OO5htsIGLhyA2SVQcBCgYyjokFokaOVhPyLx3+ukuoUEJUhjMJgqwxW2cH3zgqqmz/RA/QXarciiZhNtbx45mI0a4ED0M64TpFYqKGZ8iK0qhZlXtFhqBMPZTCSmFnsVc2//xR7NBg9yHYF0IuzfCCn7xQdu8c+1nUPcRf0LqFhIIUF2dGiVRow4dHNfEkoJFJUgioxTlk3G4xvFaVFwEDj3U7JlnnKP68OHudz6HHFLcfhXo6WEwmwJ1Patm4zjOxBTF6DGwLPy/F1xWY4/TxXj6ssVutJEzqIfhTJAYn/Lgg043WGiSFaXQCKv9QiIQxn4qIaWQMxhE24sWOe0tgdvUz4BQLXGQxT2oUPbvIPqeTRtEiFI0cccdnRUlin4NfhV4VJnULwkq8xb1YBh3nTrOilKC7kTZLIVIXOsXUvCLN3Ja+t//ipdlrsCghMFsCjyEjJqP6zjxOOTQjMvTxhu7FMV4BZciwe7Iwk5IHvV7w0zFDL7oAHk28SmFTrIpK0opruDyGVMY+6mElLisJwLKKfiIph3bN4SfPLES1HYoVDB3GPjgPoWKkBSwFNKLslsbbj/33msWZNwIEaFo7P0YiDAw1zMqRwB/E9YkbnhQiSeyCIPZRGHJxXmcpChGj3Pnne4QTa2Qww6LAqrB9QFjJe5tEIIYBs2wCQsOlhyEI+JTCqUHlBUl7JnV84JGIIz9VEJK0LMWRnszZpjdeKNzUOYwheb9rLNckH0xUpPkM2b6D6eFO3Xr5qIXo0xk4MKSRewIGbjytXq8956LvaGCGzE5GVTNjjI8JdU3ToN+/lfKgUcpRipgoMNgNgF3Oafm4j5OtksO0GSrJ1wRT0TyPJQCvfuu2f77u8KWo0Y5a0oxiPgUPI+x4px3nsuXUgiSFaUQqKrNMBEIYz+VkBLmjAb9LA61aN/Z0XELI0clZXjR+jZpEvTTCtPeXXeZnX22O/hjXy+U2irI3pOCdty4YCqPH3ecEzaDqlAW5DjLvS0SVxBAjwD54osljUYYzCYKAJbKODHmsm1yoEZgoRRMnFMU40lJLRTibxgL5YqKSfQDdzpq+RYiPkVWlGLOrp4dFAJh7KcSUoKarWK2Q2A9MR2UzCVFKrTvvk5YadUqun70RCo2auRUZ7iwxUWwIuUOMSQ4hyMo5ipYoZ3HpyDfdoq59kr92WSaQ2XNp4QpDGYTBfhKaZzPPed0UqQoJvEcOT2iGMqXbt5//dVsv/2cZyWCF+OIgsD19NOufkoh4lNkRUm3KvR9HBAIYz+VkBKHlZBpH9H8jhnjXMFmznR3bbONcwMjliJf16RM+5HJdfgtHHWU2eTJwZcRzuT5+V7D6eCRR8yGDHExQbkQRRAefdT5E+BXIBICRUIgDGZTpKGt8NhSGyfZsonhoO4oLkrjx8crRfEffzhvXwyVBKw/9lh0SmOxcAoRnyIrShR2AvUhCATC2E8lpAQxU1Frg3S+U6a4IHtS+kIE1nMQ5kMWqWIQWmm4Kbb9F15wZZRJn4IzcpQEqEywwTWNAH9yY1JLI9uik/799eq5rG1hVg/LZHy6pqwQCIPZRAHQUhwnBukWLdw2GqcUxbApElTiOUsRRQQVrBZRItzpyDpO384911UEyJdkRckXQd0fFQTC2E8lpERltgvVD9L5YlkhexQZwjgMY1W5+GKzBg2CeyqWEdzOEEBSfb7/3gX6+4RNn92faMk4UsuWLgUNAdbZRq9iRSJb2+DBLmWPSAgUEYEwmE0Rh5ew5axiyxL3oCh0KoA+4PJFimJclDbZxG1LUc/zcPnlZhzYqZlKLhiyfEeREuNTKGVFMsZcCSvKFls4Vol7W5AsONc+6T4hkCsCYfANCSm5zk7c7iPNL8HZOPz+/rvrPQdl6q0gJKRzAsYu71tBfCGENhMFElIIp6LVVjPDarDZZv9+UFEddFDckPy3v1QZI9oTaxDudYwxE0Jw3HNPV5ENK4ysKJmgpmsKiEAYzKaA3c+46VIeJymK8TwlFwklnEhRXIwUvplMBh6uZM+nijxpfrfbLpO7indNUPEpODdcdpmzII0eXbzx6MlCIAgEwthPJaQEMVNxauO331zeSgQWVEQQB2aEFQ7blVlBKhvneuutKIAkCiP8jpqsFIOPmzc3e/ZZx3HgPJmQb4EZNsyMKvYiIVBkBMJgNkUeovf4Uh8nRqJ+/Vx2LHQmAskfnAAAIABJREFUbPVkp48SEcpHUkOC/Nk6CZqPA5FFDWxzrZ+SaEWhfm/UBbM4zIn6WFwEwthPJaQUd46L93TiQ3AGxhWMWh2VEfEWaP2TBQ//b76LmjNxWMiSTP/AA10KZbJ+ValS+ZNff92scWMXy/LJJ/FMxxMWtnpOaAiEwWxCG0wlDyqXcVK1nRI/xFT07u0+6YzlYcwPbl3NmplhmMcDGWElLpRvfIqsKHGZafUzUwTC2E8lpGQ6G6V6Hao31Flo9dmFkwURDtNUtk93+C5VfDIZF0IKwkomCfVJYfPkk87tzi8UmMkzdI0QKCACYTCbAnY/46bLZZwAwraOEEC8CjU/CKon2aP/wXC+zjoZQ5f3hehk9tnHxWPccovZhRfm3WToDSTGp6DjO+mkzLogK0pmOOmqeCEQxn4qISVea0K9jSICzzzjnL8p/Eftk1QqS9SIcGkiJ6lcn21GsCiOXX0qCQTCYDZRAKpcxuljTYriY44x++KLitGvXdsJLQgsyQJMrVrBzdiPP7rwPfpBRvybbgqu7bBbYrsnbTLOA2+95XBLR7KipENI38cRgTD2UwkpcVwZ6nO0EMAaBQd+7TWX6J+EBBURnI0IzFyygUVrxOpNiSEQBrOJAmTlMs5ErEn1S84TcnTwIeO5/zu1aPH8rYg22CC1AFOzZuaziRWB/ChvvOEykGGBiLthnpifq692Fip0T5XV85UVJfO1oivjhUAY+6mElHitCfU2qgiQ85OA+D32MCPuJNma8sorLkJ0q61cJjBZUaI6k2XZrzCYTRSALZdxZoo1WekTBZhEIQarRyoBhlJbyRYY3xpDZjGf8CCmZi01e9n+sEJUdqDPtN/Fvg7cSE5JGTIyyJNJPhXJilLs2dLzC4VAGPtpoELKrFmzrEePHla3bl2rV6+eLVq0yN5//33bYIMNrF27drbXXnvZhAkT7PHHH7clS5ZYr169rEGDBtazZ09bsGCBzZs3zwYPHmzVq1dPi2kY4KTthC4QAj4CWFMo7vjOOy7mBKtJIsHRnnvO7O67XZ0akRCIEALlsp+WyziDWFocxGfP/tfqkizAkPK4IiKE0RdYiD+hHBSZrNDTkASyVGjOHGdJwZUtVXyKrCilMtsaR0UIhLGfBiqk3HzzzdawYUM77LDD7IwzzrAtt9zSPvnkE0/o6Nu3r22yySbWsmVLmzx5ss2ZM8d69+7tCSr9+vWzoUOH2tixY71CW6ecckraFREGOGk7oQuEQCICEya4SNV99zV76aV/rSn8fsABTvVIBa9M66kIXSEQEgLlsp+WyzgLvWywkJCtPtF1zP8dCwzf+0T2eVyiKNpYapQuPkVWlFKbcY0nEYEw9tNAhZS5c+danz59bI011jCsKlhIGjdu7P1+7bXX2qhRo+yoo46yiRMneuPk927dutnUqVO9n9OnT7dp06bZFVdcsdJKoF0EnUQqxcrBegVijADO35R5JhXx88//W6iSnJsvvGB2771mp50W4wGq66WKQBjMJgrYlcs4i4k1Agp1fhFavvzS7OCDMwsuL2af83l2qvgUWVHyQVX3xgGBMPbTQIWURFBbt25tI0aMsNq1a9uvv/5qHTp0sIceeqhCS0r//v1tyJAhsqTEYVWqj5UjgN2/TRsnoCCo4LTM7w0aOOFFVhStoAgiEAazicKwy2WcUcC6XPqQGJ/SqZPZkCFu5LKilMsKKN9xhrGfBiqkfPvtt54L119//WUHHnig8fd3331nP/30k2cd2WOPPWz8+PE2ZcoULyYFSwsxKbh8zZ8/XzEp5bvWS2fkcKyGDV2hxpdfNrvySldDZcwYswzcGEsHCI0kTgiEwWyigEe5jDMKWJdTHxLjU8aONWvVymWaJyZH1eXLaSWU11jD2E8DFVLCnJ4wwAlzPHpWCSFAueczzzTbcktXGIBq9BQsWHXVEhqkhlJKCJTLflou4yyltRmXsVA8k3JZa63lvHqxqJx6qtno0XEZgfopBLJDIIz9VEJKdnOiq4VAegRIe4N7Fw7ZEKq1k09Of5+uEAJFQiAMZlOkoa3w2HIZZxSwLsc+9O5tdtVVbuTUgpEVpRxXQfmMOYz9VEJK+awnjTRMBIYPN+vY0bl+vfeerChhYq9nZY1AGMwm604V4IZyGWcBoFOTGSCQGJ8iK0oGgOmSWCMQxn4qISXWS0SdjywCpLi59VZn/99xx8h2Ux0TAiAQBrOJAtLlMs4oYF2ufZg712zQIDOC6KkZIxICpYpAGPuphJRSXT0alxAQAkIgQwTCYDapuqIiwBlOki4TAkJACEQIgTD4hoSUCE24uiIEhIAQKAYCYTCbVONSEeBizLieKQSEgBDID4Ew+IaElPzmSHcLASEgBGKPQBjMJhVIhSwCnPzMYo4z9otEAxACQkAIJCAQxn4qIUVLTggIASFQ5giEwWwygTjoIsB9+vSxvn37rvDoZcuWZdIVXSMEhIAQEAKVIBAG34i1kKLVIwSEgBAQAsEgUKzDe9hFgINBS60IASEgBIRAoflGrIWUQoOTuPyaNm1qU6dODW1FhiGhJg+m1McY9vjAN+x5DHuMYY8PTEt9jGGPrxjrNLSNNOlBxVivfheKMa/+szXu8FdcseZbc10+c13svTuMNS4hJcP1fPfdd9uZVBEPiYqx0ZT6GMMeXzE2kLDHqHUa/IYQ9hwWY50Gj1pmLRZjvfo9K8a8RkFI0bgzW5tBXaU1HhSSmbejNZ45VtleKSElW8RCur6YG01IQwzdyhDWuBKfU+rzWOrjK5cDfDnMY7nMZUX7XLnMb/LYy3Hc5ThmvdulG2cXWyGFgEg+pUqlPj7mTWOM/+rVHMZ/DsvlXSyncSavynJ4Tyt6E8tx3OU4Zr3bpXsWjq2QUhpHA41CCAgBISAEhIAQEAJCQAgIgZWsocvCjD4X/kJACAgBISAEhIAQEAJCQAgIgTQIyJKiJSIEhIAQEAJCQAgIASEgBIRApBCQkBKp6VBnhIAQEAJCQAgIASEgBISAEIikkPLss8/auHHj7Pfff7cddtjBTjjhBLvqqqusWrVq1qJFCzv22GNtwoQJ9vjjj9uSJUusV69ets0221i7du2sevXq9uOPP9rtt99uG2+8cWRnOJMxMoaHHnrILrjgAjv++OO9sfTs2dMWLFhg8+bNs8GDB3vjjSLlMr7vvvvOrrzySm84f//9t40aNcpWX331KA7P61MuY/QHc/XVV9trr71mkydPLrnxjR071qZPn+5lb+PdrF27dkmNcenSpSW313Tp0sUWL15sc+bMsUGDBln9+vVjs9f4iyuT9zHufKOiFymTcceZl6TaPHIZd9x4TPLYcxlznHhOkHNNW3HiRUG923HjT+kOB5EUUhI7fcQRR1i9evU8IaVu3brWsmVL72Dn/4Sp9u7d2wYOHGhdu3b1DrbDhw+3DTfc0I4++uh044/E96nGSOfIv7322mt7Qso333xj/fr1s6FDh3ovH+FEp5xySiTGUFknMh1fYhsIZny23nrryI+PDmYzxqefftp+/vlnGzNmTKSFlEzew+Q1OnfuXGvbtq3tvPPOnoDJuxllQTOXMf72228ludeABYf4X375xQ4//PBY7jX+fJYD36hoY8x0H4orL0nFDDIdd5x5TPLYsxlzHHlOvnMdZ16Uz7sdZ/5U0bgjLaTceeed9scff9iTTz5pEydO9Pp/1FFHeb/7P/3/PfbYY9a5c2fvIL9w4UKbNGmSd7iPOlU2xuQD4IwZM7yq9926dfM01dOmTbMrrrgi0kPMZnz+QN555x3PSjRixIhIj83vXDZj/Omnn2zAgAF28803Lxe0oz7IbMaHdQiFAlZOhLC//vor1CKouWKZzRhRDpTiXoNw0rFjRxs5cqR99NFHsdtrMnkfS4VvVLTOs1nDceQlqd7tbMYdVx6TPPZsxhxHnhPEXMeVF+X7bseVP6Wa88gKKTfddJNVrVrVzj//fGvfvv1yS0qrVq08ASTZkgJzxTXq2muvtSlTptgnn3xiF154Ya5nllDuSzfGZCEFAax///42ZMiQWFhSsh0f433hhRfsgQce8Nz14qCBz3aMDz74oD311FNWo0YNT9geNmyYNW/ePJT1lstDsh3ft99+67ns3XPPPZ5ygfcQi1iUKdsxvvXWWyW318yePdsuvfRSu+WWWzyLddz2Gn99pZvLUuAbFb1L6cYdd16Sav/Idtxx5DHJY892zHHjOUHNdRx5URDvdhz5U2Xng0gKKbgyEXtxyCGH2KqrruodcvDhJyblyCOP9GJSxo8f7wkjxKRw7WabbWZnn322rbvuuobfKdcTzxJVymSMHNZx7eKwjhB23HHHeT7+8+fPj3xMSi7j23333Y0Prm3EM1x22WW21VZbRXUKPUEx3TqtaA79AfkHpqgOMNfxYUn59ddfl8eGrbfeelEdYk5zyB5UantNgwYNbJdddvH2T9xkcSWJy17jL65M1mvc+UZFL1Im444zL0m1eeQy7rjxmOSx5zJmzg1x4TlBzjXjjhMvCurdjht/Snc4iKSQkq7T+l4ICAEhIASEgBAQAkJACAiB0kVAQkrpzq1GJgSEgBAQAkJACAgBISAEYomAhJRYTps6LQSEgBAQAkJACAgBISAEShcBCSmlO7camRAQAkJACAgBISAEhIAQiCUCElJiOW3qtBAQAkJACAgBISAEhIAQKF0EJKSU7txqZEJACAgBISAEhIAQEAJCIJYIlK2Q8v3339tFF11kb7zxhq2xxhpWv359r0YAtVlIDfvBBx9kNKEUzjn44IPt0UcftZo1a9qtt97qFSHk/9R34Rk+UfvjjjvusNVWW81atGhhAwcOtD///NNLL/zmm29alSpVvPubNm3q3UIa0Dlz5tjff/9t++23nw0aNMhLyZxM11xzjVHcie9uu+02O+ywwyrtO/Vk+vTpYzNnzrTXX3/d9thjj+XXp2orVV9IkUzhRZ691lpr2fDhw61hw4ZevZOuXbsub/fjjz+2cePG2THHHLNC3yjWefrpp9vbb79t66+/vncNc/Hjjz/aGWec4aWZTkcU7fz999/TXbbS98x3hw4dbM0118z63uQbwIF2GEsq+u9//+ulxyZFYL7EOqL/n3/+uVGsq3bt2l6TrDvqAz3xxBNef+6++27bbbfdvO/AlfoszBVrkDUHderUyZsv1v5ee+21PO31V199Zdtvv72RnhZq0qSJ910yUQTwpJNOMq7nGeTlJ5VtZbR48WKvqvnzzz9f4ZrOFx/up/DpDTfcYJMnT864uX/++cd7HzbZZJMK76sMXyr9nnPOOd7eQQrtu+66y/bee++Mn01++7POOssWLVrkrRH2Atrx6eGHH7YTTjjB27PoYzbvSMad0IWVIhA23+C9mjVrltcn1tc666xj7CNQun2fwpVffPFFSl6W7v5kIHLhG927d7d7773XS0meuEd//fXX1q5dO2/vIkX56NGjrV69et4jL7/8cq8Y7NKlS70aUsnvAdeIb+T2oubCN5gn9tA6deqssJZS8Q3OQr179/Z4EfwGnrHjjjuWLN9IxVcrmiH2bvgoKcEptVAZX850hlPxjb59+3rnKfg6pRxGjRpltWrVih3fKEshhZdnn3328Q7BvGgQFXjZ+Fhw2QgpHAaffvpp78DI4eTkk0/2Dv4sDA5hFF7cZpttvEMghRjZfBGKOGDw0iN4cFhkAfE/hAEWMgIL9VAQfOjviSee6NVJof1EojJ027Zt7dVXX/UOwGzqCAQVCTP+fQgntI9wxCHOF1IqaytVX/z/0zYbGZsgRfwSiUPs1ltv7RWISxYIEHA+/PBDDweYIAcxXmCIAxuHvn333bfS9zVXIYW5Bnv/gJ/pppDrdQgMPA+M8qV33nnHEwQQaBPHwHoEU+aCdUQxVCrv+pthReNlvg499FDvQIyQBd68FwgdmbwLHCo22GADr67N9ddfb3PnzrXrrruu0iHSRwT0RCE+X0yS789FSKFQGhixrisSbirDl/1k//3399YsY0PY4FCZKTVu3NhbG3vuuaeH+3nnneftB9CCBQs8xQbtco3/zmb6jmTaB12XGoFi8I3E3lxyySXeIYP6Nen2/QkTJnh76XvvvVehkJLu/opQyIVvwJc233xzjwcmCikI26xx3hkUFfC/++67z+OdKLemTZvmdQHlHMKUr7jz+yW+kdubmgvfYC7gsfCGROVtKr4B39liiy08vvrss89ajx49vPNJMpUK38j0HIECjPMZ9f4Q/BKFlHzOIan4xnPPPefxI86izAHKboqdZ3O2ym2VBXtXWQopbIpI+i+99NJKaGZ6MPNvPOWUUzxtPJsoh2yqiY8cOdL7moKSCCS8jAgZXEeBykTiIIK2FUEDwirDpoxG26e//vrLK2DJNWjWEolrETj+85//eP/mIMOCzESDS58ThZRM2qqsLxSaQmuWbP3AuvLiiy/amDFjVsIbqw8Fl3jReIk33nhjQ1vJgfmxxx7z8IQhVUa+kAITpBAdWjv62a9fP+/vhQsXevgjJPEMCjD+8MMPXoVtrARspgiRicTGAyOl39D999/vCVqJGkAO5jBXColimaIftAmujIc20X5i5eJv7seCgJa+W7duK81lLq928gaJ4NmsWbPlbTdq1MhjFFQRz2Qz5ZD+888/ewJ1pu8CGMLINtxwQ08zysHC1/6mGhNKAjClTwgTHLzQqH766afexsqcs64TCQyxTjAmyLcuolxA2AHb6tWre3NCn7IVUlgfHJrQ/oJDRUJKKnyxIu68886e5jrR+kE/sXbxnoMNQjqW1u22226FsWExZd44CELsJczbsGHDvL8ZH3sH72viO5vpO5LL2tI9KyJQDL7h9wABiX2GPnDgr2yvZh9EQca+y75XkVdAJnt9qvnPhW8kK5J4h9nbsZ4wNoQvFAMoVM4991x7+eWXvf+zFyC8YJ1PJPGN/N7ObPgGT0rHCxL5RmLPUFBiRaH6ezKVCt/IhK8ydhTZFOZGiENATyekBME3fMxRWlDI1j+DxYlvlKWQgkvUl19+aTfffPNKL07iy8hBK1ko8G9AwMGUiZYIJsDvWDA4FE+fPt07LCFwoPHEzYtqznyH9gHBBY0zhy4OLFhiOODPnj3bdt11V+9Q61eJxe0DKw9MB5N4soUETTnmQ1/I4RCFtO6/AJVtZcnMJl1bqfqCOZfxcFjkYA4TTSQOXxdffLH3YibTDjvs4GHim/rZuF555RVPcGBjY9zvv/9+pTuyzwDRFKC9xvrE5gguzCEvKAwRpg3NmzfPY4qVbS58hzXhiiuu8EymvNyTJk0yXCiYGw6z99xzj+fm98gjj6wkpFDZ+MYbb/QENn5y4KzMkpLJWqsIhOQxgDF95gAPwcwROFiHaLewvnCIZp0gNCcSgp2vlUGI4F3gMLHtttt6mCL0cWhIJqwFCGM+MXdYU1IR1gAOXAijEMIEFgO0u7xPjIGK7omVkrmO95XnYMZmbXBo51DP4YbDPy5stMX7zZwnCinJ7od+33hvfWUF7wzCI1aLVG5iqfDl2eDJYerdd9/1XOxwU2Ft0k+EDUzuvMsIQRw2EwlNGvPGOoG4jnlDUEL7CfYwmeR3NtN3pNIXSF9mhEAx+IbfMZQA7KG+i2ZlezWWiAMOOMDjJaksoen2+iD5Bm0lCymnnnqqp4jDNZV3lXedPQOXXxQ9KPoQUugn74H4RsUW+DD4BthXJqQk843EuWIfRfHkK1sSvysVvpGOrzJm9mkU2uz78LZEISXV/fnyjUSseR7vXJs2bbx/x4lvSEhJ2v3SaQySN0sOORxqfEKLizsG/+cAjuTM4YrfOaxzcCH+ggMRWlc0+1hBMM1tueWWngUAdxEEGp+WLFniCSG+AJLYh2RLDNfgupN8wKuI6SQfeDJpq7K+IGghcHB49wkN8U477eS5ooFFMiVq1PgOIQUhD2YFFhtttJGn2a+MfAbI9b6rAFp4NnAwZn4QdhA4eVl997F0QgoHWzYQ5oh++LEfjImx8H8sFLjpJVtSYKw8h75z8P/ss88qFVIyOiVVcFHyGLCkcdBOFFIGDBhgCE3MAZYqrEgILxy6OMz4xPyDG0I1hNCJVpa54HDUunVrzzUPgSWREHywXvmUTkihHwcddNByawvCBJZN32qFNY6DebISgY0VARxhJlFgQbi/4IILPGaIAIYQxNxnY0lBGPBduSq7LxW+HKgQihGwmW9cczDrMxdY3Py4HjDiHUKhkUho17g2UUhh3tB4sW8g4DLXye9spu9IrutL9/2LQKZCSiaYZco3/LY6d+7sWWJZV1CqvRpBGEsxCpXKeFkme32qceTCN5KFFBQUCCDszwceeKAnqOCaxh6L4OK7/LJv46Li72d+n8Q3Mlllqa/Jhm/QSrq1lMg3/KdiDeMsw8+KXKpLgW8w1nR8lWvwyuDdhUeceeaZKwgpFd2PkisfvsH77xMKZBRx8BLfyh8nvlGWQgoCAS5G/qEo8VXO1pLCi8ZBNNk1hTZxYeEQC4Nhs0VT6vvWcmjh5WUhJhKHRrQOBCwnEpp8tKvJ8QzJZnsO4Whqg3D3StVWqr7Q3+SNB6GMg61vxUjeNisz2yNcgANuOJWRzwAREBGSsDghRMCwmWs2ZA7RfEfsC0Icc5OpkEIAJ0IKwgibbaKQ4h/6k4UU3yUHzT9WNNZVGJaUZHckhONnnnnGW4eJhGaeQzRaSwhrD0IZG1mqeCY0OxwYEhMtcG+i2R5tKMJZZe5ezAVaXjCBUgkpvAtYTSCwA0csOcwh48TiiOUCqxZCGIIKAgvX0HY2lhQEBNxKsIggRGCdwcWStZRIqfBl84cB+WPiXQVjrHBYolgziYSAS58hnkOSDSyvCGAQ8QTMG8k1WMescYjDHW5xEydO9OYh03ek0hdIX2aEQDH4Bh3DQoyLKAGyvsU51b5PUD1uxvihcx97FlZR3oVECptvVBY3iPWb95h3hwMV7x+CFoSgzjuJy3QiiW84NIKypKTjG6mElFR845NPPvFcz9mnks8y/jyWAt9I3jiS+ar/PcpOFFkQPBLLP2ei5ERC/v3MRz58w7dc4TbMOwVvxyXZpzjxjbIUUnytJ1I+hwMITSabpe9ukml2Lw4mHNo5SEB+QDyHJQQTrAK4FuESxUGFQxdadQ4kvPj40dMfFhBMEA08JkE02CwkDpcwm9NOO807/KF9SiQEAALaCEyjfdr1A+f5P9cnxrck3pusEUvVFn1M1Re01757F9poDuu+SwLPAh8YIprziogDJ/1Fe487Cxo0skNBWJyuvPJKT7hAi854wCiZfAaIQAS2tIXmAA0dmjoYNgc7DuX0EVcC3LTwlUXjgLCSTKncvbBwcahM5+5VkZDC+HgeB+6gKFnQIjEDGxTMgXnAv5tgVOJyELbQ4LLOYfIIs6xR8IbZsO4SNzI/8w5CC2sVbSbaTrBMJALmEeLQFNEOlhoO15XNGe5erB1cH5PdvVq1auUFFlZkDWS9IADgAohbFYSFB0sj13NAQ3hJFlKywbsyS0oqfGkf4Yhnw1xgNrgVwiB4b9EOEx/Au07fsS4mE+8psTgIH7gV4m6YnAku+Z1NfEeyGaOuzR6BYvANesn+xx6aqFSrbN/3R1aZ9jsMvpGo7EgWUjiosY+g3MOK6v9k/+cdwqoJsf7hYbwPiSS+kf36TbwjU75R2VpKxTc4A7FPceZJtNQn97gU+EZlfDXVDCVaUiq7P1++wRkIF2T4GfGiiRQnvlGWQgqThYmNYFS0Uxxe/RTEaOAzyWjkTziHIrTp+Bn6BxUsKxyMcUnxD+e4oHDwQtPFdxxiceOAkXBgZJNGS8YGzQGOgx6HNbRKaF25lvbQKvkHUKxBEIINVgSYAsFZfkYgNM8cijfddNMVFigxFF26dPFM6/iFch0xG6naqqwvHL5wUQE3rChYevzAZsbGi4bAlmhpworhH8QYHwIYuHA/mmfc3iAOvGBFXzlwc6j2+5k4IJ8BwvjADFMmY0JwQyhB28SGSB9ozz8IIsywkSII+m42frush8QUyH7gPGNiHnlWZYHzFQkprAvmBmHBT6aQK6vB9QRBAM06WeJg5ol+3ODkB5GDNcIah3kIoRf/WPCEsA4hvCBMQwhhzBFCFT9Zc6wtBGzwhRDwOUTTNuPiAP6///3PE/JhXhxAKpsz3hf6gFDNJspaph8oB2BsFQXO81zWIlpl+uL3H6GFuWI+cAdDCAxSSPHTLjNe308+GV/6xhpG6YGbHJoz+sGaJv4NaypKBNYmvsF+3xPnH7zI1uWnZ2Z9JgfhJwspie9IrmtJ92WOQNh8g55xqEHZ42ei9Hubat/3v08WUsLmG/SDfY6903dpYd9AkYWlEOsl6xtlEkIHezO8DsUKByy+gzeyxvldfCN8vsEcEsfAHg3P47DL3sv+nYpvYJ0n1pY9EEpMd19qfKMyvprINxJ3mEQhpbL78+Ub8GZ4ju+tk1hCIE58o2yFlMzZUuVXsvlysKjo8BzUM3JpB3cVNhLMfXElDqu4H/nCD8JbskatUGPLNGNHoZ5fCu0isKaaM5QDCFrEL2UTO1IKuAQ5hsR3JMh21VZhERDfKBy+4huFwzaMlsU3Co9ynPiGhJQA1gOaY9xmkgOKA2i6bJvAykMQcrLPZliASEgpPNKkE8YCgtY026KLhe9d9J9Q7Hck+ghFu4fiG8HPT7HfCfGN4Oc0uUXxjfwwLvY7km3vJaRki5iuFwJCQAgIASEgBISAEBACQqCgCEhIKSi8alwICAEhIASEgBAQAkJACAiBbBGQkJItYrpeCAgBISAEhIAQEAJCQAgIgYIiICGloPCqcSEgBISAEBACQkAICAEhIASyRUBCSraI6XohIASEgBAQAkJACAgBISAECoqAhJSCwqvGhYAQEAJCQAgIASEgBISAEMgWAQkp2SKm64VVxau1AAAgAElEQVSAEBACQkAICAEhIASEgBAoKAISUgoKrxoXAkJACAgBISAEhIAQEAJCIFsEJKRki5iuFwJCQAgIASEgBISAEBACQqCgCEhIKSi8alwICAEhIASEgBAQAkJACAiBbBGQkJItYrpeCAgBISAEhIAQEAJCQAgIgYIiICGloPCqcSEgBISAEBACQkAICAEhIASyRUBCSraI6XohIASEgBAQAkJACAgBISAECoqAhJSCwqvGhYAQEAJCQAgIASEgBISAEMgWAQkp2SKm64WAEBACQkAICAEhEAEE/vrrL1t99dUj0BN1QQgEj4CElOAxVYtCQAgIASEgBISAEAgUgX/++ceGDRtm48ePt88//9x+/vlnW3fdde3rr7+2VVZZJdBnqTEhEAUEJKREYRbUh9AQmDp1qh100EH2/vvv2w477BDac/UgISAEhIAQEAK5IvD333/boYceat9995316tXLdt11V8+CUrNmTatTp06uzeo+IRBpBCSkRHp61LmgEZCQEjSiak8ICAEhIAQKjcD1119vd999t82YMcMTTERCoBwQkJBSDrNcxmPEX/f888+3MWPG2MYbb2zt27e3yy+/3G6++Wbv89tvv1mHDh3suuuusypVqnhI3XXXXXbLLbfYJ598YhtuuKEdeeSRds0119g666zjfd+nTx/r27fvclTXW28922+//eyOO+6wTTfd1Pt/06ZNrXbt2rbnnnva7bffbnPnzrV99tnHBg0aZNtvv/3yezt16mQvvPCCzZ4922inWbNmNnDgQNtoo41WmLUzzzzT7rnnnhX+t/nmm9tXX321vE88n+eIhIAQEAJCIBgE2FfZw7/88ktvTz/xxBM9flC9enVPaDjrrLNs2bJl3sPgN3w/c+ZMb1//448/bIsttkjZkQMPPNBQnEHjxo2zAQMG2GeffWaLFy9efo/f9t57723169e3H374wd5++23vmfALhJett97aux5+wPNGjhxpjz/+uD399NNWrVo1O+200zy+4seuwMPEL4JZH2qlsAhISCksvmq9yAhcffXVnsABM6lXr56dffbZ9s4779gBBxzgCQwffPCBtWvXzm688Ubr3LmzJ6z4Akzjxo1tzpw5dvHFF9taa61lzz33nOf3ywYP0/rwww89RoFvcJs2bTxBZezYscuFFJ4DE+H6JUuWWNeuXT1T/ccff+wxDuiKK66wo446yhOgYIIXXXSRrb/++vb888+vgNwZZ5xh7777rj355JPe/6+66ip74oknJKQUeX3p8UJACJQuAiNGjLBzzz3Xrr32WmvVqpXHL+AThx9+uKc0ShRS/vzzTzv++OM9IYP9G0UTMSQ//fTTcoBQWp100kl26aWXev+rWrWqp5xCIdawYUNDaQWfgN+MGjXKrrzyyuUC0JZbbunxCHjBJZdcYgsXLvR4E/Eo9IvYFF9IgYf07t3b6+drr73m9fm8887zxgFJSCndNVtqI5OQUmozqvGsgACWkI4dO3qHeuiZZ57x/HoRIHbZZRfvf3z/yiuv2BtvvGEbbLCB3XnnnR4j8QlhhPiVt956y3bbbbeVNngEGeJcDj74YE/wgbCkEPfyv//9z2M4EL/DaGB8aN8qIpgb7Xz77bee4OLTKaec4jEoTP0QTO7hhx+WkKL1LgSEgBAoEAJYq+EX7Nk+jR492k4//XRPOfXiiy96ezlKqOOOO84TGFBmpYoRwRKCVRwhIZEeeughzwLz/fffe9Z7CEtHly5dlgsp3LvGGmt4Vhrf6o/SC56CBQaBxRdS4GlDhw5d/oj+/ftbv3797JdffvEsQBJSCrRg1GzgCEhICRxSNRgVBObNm+e5aGHdOPnkk71uVRSTglWEQ//LL79se+21l7eJ+0zAHwtaq/vvv9+zmPjuXggfWFIWLVpk+++/v2fZWHvttZcLKZjWEYoSCbP80Ucf7VluoPvuu8/L1vLFF1/Y/PnzbenSpZ6pH6EJ9zCfcDnDlcBvryIhBRc0+oS1B+1ckyZNPLcEmJhICAgBISAEMkdgwYIFXuwHe3Tbtm2X34hr7mabbWaTJk3y3GsRUrBYYOXGUo+rVSpKJaTgvrX77rt7LlkIG6uuuupKQgpuXCiwktvfeeedjc+99967XEhBkDr11FOXdwPeBo967733bMcdd1yBh4lfZL4mdGX4CEhICR9zPTEkBIg3wQSOr69vGalMSHnppZcMFy+Emj322GOlXqLhqlGjhrfB33bbbfb6669718C0MNE3aNDAHnjggUqFlK222sqOOeYYT0h55JFHPPcA2jvssMM8geqjjz6y1q1be/7MWGN82mmnnTwmhgsAVJGQktinb775xi688ELPB/nNN98MCXE9RggIASFQGgj4Qkrygb8iIYX9GVdhFFAos7CqVESphBSuhSdg8eC5WExQSuFC5seksP9jyU+06nAfAgpeAbif+ZaU5D7D23BxThRSxC9KY52W+igkpJT6DJf5+HDfwh+3Mncv/IAx23OY53riREjxmIoqMpVjmieehEBJtGAIGPgJ4+K15pprLhdmsGoMHz7c075hyiewcdasWcsfhbsYgf6JQsqvv/7quQAQW4N/dCohJTkQ0u8TjC7ZMlTmy0LDFwJCQAikRQB3LxRI7Nk+kYSFQHSs3yi92MuxqBAHgiWEuA+EAWIgk6kyIQXeAd/AYgK/QtDAOu4LKTwTl2QUWf5+jnsYbWIxR1HmCynwvMGDBy9/PN/TZmXuXuIXaZeDLigCAhJSigC6HhkeAggbbNZomTbZZBPPHI9pnawqCATEm8BkYCwIDWjDCDiEObRs2dILbPz0008Nn2Ha8f15/cB5RkL8CEGJv//+uyeYQDAbntO8eXOvPXyWMeNj4UAoQVPG8xFsCL7EtWv69OnWo0cPj9H4QgqCE9nIYHoE3JNdpjIhhfYhfpIQAK0c8TciISAEhIAQyA4BP3Ae4QN+AL9AqYXgkhw4T8sIFMSwYAUhvjBZOVSZkIJ7FnEuCD4kVkmOSSHGkdooBM4jkOCCjEUdYSk5cB4+4VvoCZxHuYXgkhw4L36R3XrQ1eEjICElfMz1xBARQDvFBo3LF0IK6YYvu+wyu/XWW+2GG24wrBQILpjasYBAmOv5HqbA//zgSRjVaqutVmEKYoQM2sPlyxdSYBSY52E2aLBIIYmg46cgpjgXLlkPPvigF9dCdjCEHVwGfCEFtzP6TWBko0aNliOXKibFv4CYFPrEuLbddtsQEdejhIAQEAKlg0BiCmKsJbgOp0pBzKhJpIL7Fwqo7t27rwBEKiGFLJQIRLgQ++nnk4UUGpoyZYrHf8j0iKKL7JHwHdyIId+SQlsTJ070gvgReAj0T05BnJxGX/yidNZsKY1EQkopzabGkhaBsIo5+nVSyMAlEgJCQAgIASFQaAR8IYWgfiw/IiEQdwQkpMR9BtX/rBCQkJIVXLpYCAgBISAEYoKAhJSYTJS6mTECElIyhkoXlgICElJKYRY1BiEgBISAEEhGQEKK1kSpISAhpdRmVOMRAkJACAgBISAEhIAQEAIxR0BCSswnUN0XAkJACAgBISAEhIAQEAKlhoCElFKbUY1HCAgBISAEhIAQEAJCQAjEHAEJKTGfQHVfCAgBISAEhIAQEAJCQAiUGgKxFVJWWWWVUpsLjUcICAEhUDQE/MrWRetACA8W3wgBZD1CCAiBskGg0Hwj1kJKocEpm1WmgQoBIVDWCHB4L4f9tFzGWdaLWYMXAkIgFATC2E8lpIQylXqIEBACQiC6CITBbKIw+nIZZxSwVh+EgBAobQTC2E8lpJT2GtLohIAQEAJpEQiD2aTtRAgXlMs4Q4BSjxACQqDMEQhjP5WQUuaLTMMXAkKgjBGYP9/srrtsla5dQ3H3mj17tvXu3dtmzpxpM2bMsFmzZtlVV11l1apVsxYtWtixxx5rXbp0scWLF9ucOXNs0KBBVr9+fdt8883tiCOOsDp16njX8/25555rtWrVsho1atjVV1+d0SSGwVQz6oguEgJCQAjkicCHH5rNm2e2225m1arl2VgOt4exn0pIyWFidIsQEAJCoCQQuOMOsy5djDQkYcaktGzZ0iZPnmzt27f3hI66deua/z8f1wkTJtgvv/xi55xzjjVq1MgaN25sTZo0sQ4dOtiYMWOsSpUq1qZNG+vUqZP16NHD6tWrl3ZKwmCqaTuhC4SAEMgKgX/+MVuyxOyPP1J/NtrIbOuts2o21hd/8YVZo0YOl6pVzfbYw2y//cz23ddsn33Matcu/PDC2E8lpBR+HvUEISAEhED0EFi2zKxhQ7OPPy6akHLUUUfZxIkTPWwSf0c46dixo40cOdKzlixdutQTStq2betZTcaNG2dNmza1vffe2wYMGGDNmjXzBJh0FAZTTdcHfS8EShGBuXPNHnvMbOHCigWJdEJGZd8jpKQjDupvv+0O7uVArVubPfqo2S67mM2ebfbzzyuOervtnMDiCy4IcEEnxQ1jP5WQUg6rWWMUAkJACCQj8NxzZoccYtakia3y6qtFt6S0atXKJk2aZLiEXXrppXbLLbd4FpZEuvjii+2ss86y9957b7klpXPnzta9e/cKLSl9+vSxvn37rtDG0qXLAmfWWlxCoJwR+Oknp73/7LNgUFh9dbM11nAuTPys6JP43a+/mrGdNWtm9uyzwR/GgxlVcK0wxubNzerXN/voI4fTrFlmL79s9sor7mfyXNSp44QWX3DZdVdngcmHJKRUgl4Y4OQzebpXCAgBIRBpBI491uyRR8xGj7ZV2rYNRUhZuHChXXLJJTZlyhQvxqRr166eZYSYlCOPPNKLSWnQoIHtsssutu6669rRRx/txaMMHDjQqlatatWrV7dbb711hZiUmjVrei5jmRB848EHl9kJJ2Ryta4RAkIgHQJYTg46yOyNN9zB+bDD0gsVyUJHosDBwblKlXRPXfH7v/5yFgUO7A8+aCX9fv/9txsr8SgPP2x23HEVY/XDD2bTp/8ruLz1lhn3+gTmjRv/K7ggZK6zTna4h3EOlyUluznR1UJACAiB+CPwv/+ZbbGF2frre74Cq1SrFoqQUmzgYKp16y6zmTPNatUqdm/0fCEQbwQ49B59tNkTT7jD7jPPmFWvXpwx+YZhQtM+/thsrbWK049CP/X2280uuMCsaVOz55/P3Gq0aJETJH1rCwIMQfc+4QqGq5zvHsZ8YqmpzEVMQkolsx0GOIVebGpfCAgBIVAUBLp3NxswwOzKK83697dy2U9dxflldt55ZuQMEAkBIZAbAoS0nXOOlxzQiH/AzWi99XJrK6i7TjzR7KGHzNje+vULqtXotEPczzbbmJGU8Z13zHbaKfe+LV3qrDG+exg/v/pqxfY23njFuJaddzZbbbVEwabwRYBlScl9jnWnEBACQiB+CJAiZ9NNXaQlXGnTTctKSFl33WX2229mr75qttde8Zs+9VgIRAGBXr3MyPzNQRat/OabF79XGIi33965NXEAL7VsX+eeazZkiBk/Bw0KHu9vv3VCiy+4/Pe/ZggzPmGdIj+JH9dy6KESUlLOQrlo/oJfhmpRCAiBskZg9Giz004zIz3MhAkeFOWynzLOESOWWfv2zq8b94dEzWBZrwsNXghkiMCwYWadOpnVrGn20kv5afQzfGTGl2EgxpLSooXZ5MkZ3xb5C99919VDwU3100+dp26hacECs9de+1dwmTHD7PffE58qIUVCSqFXodoXAkKgvBDYe29nRvDT4ZSZkPLPP8vsgAMc473xRrOLLy6v6ddohUA+CJBmmJwbq65q9tRTLmg+SoSheIcdXHarSZPs/9g7E3irpi+OLyGFJkpSyJh5pjKVSJpeyt8QEREVIZnS8Jol/DM3mDL9yxQalDmh8Ed/Y0JIkshQaSDy/3zPdup2e+++c+49Z99zzl3r8+lTvXfO3nv99j577bXXJK1aRWl02Y0F1zpwfvVVEWJSLrkku3ZyfQsL1Ycfro9refRRVVJUScl1Ven7ioAioAi4CJDihapf+ETgD/FPVGQhWVIoWgnrWFLIMkRGoJ120iWiCCgCZSHATTppfqlpMm6cyBlnlPVGfn4/ZYpRTnbd1Wxz+ajGHiTnZPEiIyGB7bhgRcX6a0NuaExKkCtJ21IEFAFFIMoIdOokcv/9G13H2RA2UYAllU9yBlx/PUUkTRE6JUVAESgdATJmEYvw888i//63SI8e0UardWvj7kUAPe5fcaVVq8yd0vz5pgbM8cdHhxMbckOVlOjMt45EEVAEFIHwECBQnvycXMMRIYlD+T9kQ9iEx5j3llP5JCUnbiFffWXKxZx8svd29ElFoJAQ+O47U6yRg3LPniI33RR97ufNE9lnH+OWhoIVV2spJaCKizcIIYwM+DbkhiopkZluHYgioAgoAiEicOONIldfXWJqGBvCJkTOPDedzue0aSLNmxvdDbevSpU8N6UPKgIFgQDpbonhInC7fXun9qvvYov5AqpvX2NJ+de/TGriuBHZykjvTIYtajtR2ipKZENuqJISpRnXsSgCioAiEAYCf/1lEuxjNsBJmyvGFLIhbMJgy2+bJfGJX/2jj4pcfrnIiBF+W9TnFYHkIvDHHyItWqzPsUHRRuK44kJYS3GV4rBPockTTojLyM04UQrHj49u3RcbckOVlHitWR2tIqAIKAL+EcA5GydtUsRQpjiNbAgb/4MO/o2S+Fy0yNxWklqTlMSk+VRSBAodAW7vO3QwAfIUDZwxw6S/jRu5Qed841iDypePBwekdsaCRR2auXNFtt46euO2ITdUSYnevOuIFAFFQBEIFgF8mvBtQmKfcooqKWkIuAXSSHxGdmb82JUUgUJG4KqrTOwJRRop1shhOY5E+t6mTY01CH6IqYk6YfhmLyKTF+51Z50VzRGrkpJhXmyAE81loaNSBBQBRcAHAhQMwNWLwAvcvUrIX1ko+2lpfHJrTGAwhctuu02ke3cf+OqjikDCELjlFpO9a5ttTD0hrBBxJuLNDjxQpGJFY5WoVSva3Nx9t8iFF5o96fXX12WKj9ygbcgNtaREbtp1QIqAIqAIBIgA1QoJthg0SKRPnxIbtiFsAuQo66Yy8YkryKGHimy5pQlSrV076270RUUgtggQn0WcFrVFsD5wUE4CXXmlKd569tkiDz4YXY5+/dXcKZGM8e23jUUlqmRDbmStpCxYsECKi4tlzpw5MmvWLJk7d64MHDhQKlSoIC1btpR27dpJ06ZNZbfddnPwHTZsmFStWlX69u0ry5cvl6VLl8pdd93l/K5bt25SpUoVqVSpkgxCkHogBxyS25PkXkkRUAQUAUVgYwRWrDAWFP5esECkZk1VUvD/KIVcF5e4ZgPST0ARyAWBV14ROekkESqLT5gg0qZNLq1F612ylNWrJ/L99yLEexx9dLTG544GCxaWLEpa3XtvNMfojirSSoo7yFatWsnkyZOlc+fOjpJSq1YtcX/Wpk0b5/8oH0OHDpXFixfL4MGDZdSoUTJu3Dih8i9/ypUrJ+3bt5cuXbpInz59pA5CtQxywEHVJ2VDVFdbWUzo7xUBRUARCBMB12/gzDNFHnmk1J5sCJsw2fTadll8osuR+IxsQOQaaNnSa8v6nCIQbwQ++EDkmGNEOMyPGiVy0UXx5qek0RPfgSUF1693341e7BkWXJIU4Jb2+eel3ilFZmLK2k+DGGjWlpR0JaWoqEgmTpzo/Nj999q1ax0FZMyYMVK+fHmpV6+eTJ8+XXr16iUzZ86UGTNmOEpK48aNpWHDho4i06RJE2nQoMFGvPXv318GDBiwwc+d+7CqVU3aif33DwIPbUMRUAQUgWQggMXg4INNShscyzP4bdgQNlEA1QufkyYZAz0Bw2Rr3mqrKIxcx6AIhIcASnnDhiIUbcQj1KNDS3gDCqlltkQUMbbDO+80JaOiQowNK9bzz4tQ0gr3tKiTl/00Vx4CU1JSLSmtW7eWSez0/xDKy/z586Vt27YyZMgQGTlyZImWlK5du0rv3r29W1J69RK5/nqTdoL0E0gVJUVAEVAEFAETcYlERlHh2nCTTUpFxYawicKUeOWTBGi4u+D+NXx4FEauY1AEwkHg55+NMwq3+LgY3XNPdAO1g0CAjFnEnpFO+bPPRKpXD6LV3NtwL0f23FPkww/jkSrZ636aCzpZKykrVqyQnj17ytSpU6V58+bSo0cPJ56EmJQWLVo4MSkdOnSQypUry5IlS2T06NFSrVo16devnyxbtqzEmBSexWXMCzngkJLlggtE7rvPOBsilKOy4rwwoc8oAoqAIhAWAm4lME4d55+fsRcbwiYsNv2065XPb781ReBWrRJ57z3jgqGkCCQNAdY36XmxLFC08emnRTbfPGlcbszPxReLEBJNBq3Ro/PP7++/i+y7r8i8eSJTppi5iAN53U9z4SVrJSWXToN4dx04RHhx7YWr2RFHmHQUUax6EwTT2oYioAgoAl4QoELhTjuJVKokwomblFUZyIaw8TLssJ/xwyepiC+7TATvYw5x5cqFPTptXxGwhwC1OE49VeSpp0QOP1yEoPlCcW3EeoTFgr+jkEELa+011xjlBCUlLuRnP82Wp/grKXDOdcCJJxpLSrNmRmGJS1nRbGdO31MEFAFFoDQEsEgXF5vKZVQwK4NsCJuyxmDj93745BBXv77xlKPYY5cuNkaofSgC4SNA/MMllxhrwu67GyV8u+3C7zdKPbg5RfjGiRbI1yUE90koTKtXi3z0kXEKigv52U+z5SkZSgrc//KLyLHHmlmmPCeJsPO16rKdDX1PEVAEFIFcEVizRqRuXRGkHyli/kkDn6lZG8ImV7aCeN8vnygoGOgxSH36qcj22wcxCm1DEcgvAkOHivTubRQTDugetoj8DjiE3lMvIYgYOO+8EDrx0OS554o88IDn+yQPLdp7xO9+ms3IkqOkwP3ChSaDDakqSDZN5Z4MwaLZAKbvKAKKgCIQaQQef1zktNN8+Q7YEDZRwCwbPi+/XOTWW0UI8fnPf6LAhY5BEcgegbFjzYEc167p06NdLDB7Lr29+eabJqsZyhqV6EkWa5Peesu4k9I/QfwE88eJstlP/fKXLCUF7rnuIlUF5TpvuEHk6qv9YqLPKwKKgCIQXwQaNxZ59VVfEZg2hE0UAM2Gz+XLTRA9d2DPPWc8i5UUgTgiMG2aSKtW5u6WbFKkvC10IqPZ/feb+DOKKNoi8j5xp46i4iG3ia1h+eonm/3UVwcikjwlBQSIhDruOJGVK83qw56mpAgoAopA0hHA3ZWaUbvualy9PLq82hA2UYA+Wz5JR0x+FmAFYoqtKSkCcULgv/81xyIKlmJN6dgxTqMPb6yLF5s4kN9+E5k9217JPSISmAPSIXNk9bhVhwdEFi1nu5/66SqZSgoIcOXFlQERYuTV499KioAioAgkGYGuXU25aILlCZr3SDaEjcehhPpYtnwiRtq0MbfP110nMmRIqMPUxhWBQBEgtS1uTT/+KEI8CiXmlNYj4Gbya9TIZDkLO0oA6yzB8t9/X2ad3UhPU7b7qR+mkqukgMIjj4h06GCuvV58MWPFZT+g6bOKgCKgCEQOgaVLRWrXFiEiFN+kbbbxPEQbwsbzYEJ8MBc+588X2WcfEfISUBCOfyspAlFH4IcfzNEHRYX6ILffHv4hPOqYpI+PShbUvMVKOm6cyBlnhMsBSuKwYSJnnmmOqXGlXPZTrzwnW0kBhREjRK64QqRaNZHXXjMVc5QUAUVAEUgaAu51IIUbcXL2QTaEjY/hhPZornxioKIKPWGPhP3E0UUjNHC14cghgAsTLl7vvCPSrp3IY4+JbLpp5IYZiQHxPRPOt8MOJog+rHJ7X3xhjqGbbWb6qVMnEuxnNYhc91MvnSZfSQGFa681QfTcMpJvjyJnSoqAIqAIJAUB/JGI7kbqUSKda0EfZEPY+BhOaI/myidWFArfvf9+fINdQwNXG44UAqxVXBSnTjVK9fPPayxVWRNEBr/x482R8frry3o6u98zJ5TyGzzYpIGOM+W6n3rhvTCUFAQ4KRyIFttrL2NRqV7dCz76jCKgCCgC0UcAd9amTY3jORcxPsmGsPE5pFAeD4JPsvEAM8Z5kknWqBHKULVRRSBrBFKPPLglUuea9aqUGYFvvzVHxD/+MK5fxI0ESSiK1BunjNWcOSIVKgTZuv22gthPyxp1YSgpoIDTYdu2IpMnmzLCL71kEoUrKQKKgCIQdwROPlnkmWeMgzOOzj7JhrBhSAsWLJDi4mKZM2eOzJo1S+bOnSsDBw6UChUqSMuWLaVdu3YyYcIEmTJliqxevVr69esn9erVk759+8ry5ctl6dKlchdlskWkW7duUqVKFalUqZIMGjTIE8dB8dmtm6lCf845phCbkiIQJQT69jU39eo84n9WcLrBkoIygRUqqCB6LFsHHmiUkyefNO53caeg9tNMOBSOkgIKpCTmtpGbxubNjVDffPO4rxMdvyKgCBQyAkR0kxsX6zCFbLfYwjcaNoRN6qBatWolkydPls6dOztKSq1atcT9mfv3okWLHIUGRWXw4MEyatQoGTdunPz999/On3Llykn79u2lS5cu0qdPH6njwbk7KD5//dV415Gdh/uuJk18Q64vKAKhIEByP5L8Va5sLChkJFfyjsDvv4sccIAprkhiWNyzgiAKwlIYlr0Cw3dQyk8QY8u2jaD2U1VSUhH4+WeRY48V+fhjk/mLazCNfsx2jep7ioAikG8E3FQxffqIeLQopA/ZhrApSUkpKiqSiThoi4j77/Sf9erVS6ZPny78PXPmTJkxY4ajpDRu3FgaNmwoQ4cOlSZNmkgDSjeXQUHy+eijJgsQLiEffJCVbljWcPX3ioAvBHAn4v6VoGyqMBAIruQfAYpegiNuWZ98knssD6mf99hDhNTDxLPtt5//MUXxjSD307QdsAEAACAASURBVNL4KyxLiosCjofk5FuwwNQSIGWLkiKgCCgCcUNg9WqRHXcU+eUXka+/zjpVjA1hU5KSkmpJad26tUyaNGmdRSXVkjJkyBAZOXJkiZaUrl27Su/evUu0pPTv318GDBiwwayi4ARBNMNBhsNg//4ixcVBtKptKALZIcB6POQQkx774YdFzjoru3b0LYOA60HL9tGvX26odOkiMnq0SQF9xx25tRWlt23IjcJUUphlHANJeYFl5cYbRa68Mkpzr2NRBBQBRaBsBB56yARG4OCMo3OWZEPYMLQVK1ZIz549ZerUqdK8eXPp0aOHE09CTEqLFi2cmJQnn3zS+T0xKcSiEJOCy9eyZctKjEmpXLmy4zLmhYLm88svTTrRtWuNNYXK1UqKQD4QcIOyqWBOdfkkuBPlA0e3z6++Mi6d4MhxEatKNoTSiPJI4oLPP/dVviqb7qy+E/R+WtLgC1dJAQ3StOAgSKwKbl8IeyVFQBHwhgDOz3ffLXLEEeY7wrdAUx15wy6op0gC8vbbIi+/bAoiZEk2hE2WQwv0tTD4JFUpVeiBn/gUPRwGOmXamEcE2IKplk4tlFNP9fiSPpYRASykWFLIuTRhgn+wsG5RxZ6EsnfeSbIP/21E+Y0w9tN0fgtbSQEN0jcUFYmwmgikb9kyymtCx6YIRAMB92SWPhqiNJGW/CH2q2rVaIw3iaPguhQFkRyj5MvM4XRsQ9hEYQrC4JN0pdyUEuaod11RmOXCGwP3FNxX7L67SYutBRuDWQOrVpntFU9a4lTI+OWH3Lg1xCLlq4gVShKFsZ+qklLSCnFdJipWNFdhJMFXUgQUgY0RQJknv+WQISaFN87P7ORc4XGbP2/e+ndISMHpzVVacK/UtN/BrapzzzWn4gCu6GwIm+AYz76lsPh84w3jPUyCNQ6J226b/Rj1TUXALwKnnGJu+ol7uPBCv2/r85kQIMMXlhQSZHz4oUj58t7wwkGHmiuEPudo6PbWYR6eCms/TWVFLSkuGjffbOJScBwkbx/qs5IioAisRwAF5YorRG65RaRKFXO1lJ5RiXS4KCz8QeFfuHD9+1wjcd3nKi28G/dqVvlaH0uWmCB5JCYYV6qU00hsCJucBhjQy2Hy2bnz+ir099wT0IC1GUWgDATmzjWxEzVrihBHoVtqsEsGsXfSSSLE/FBD5eqrvbXvuoqhQD7xhLd34vZUmPupi4UqKamrgtVHED3Cn1oqZM1RUgQUAZG//jLJ94lB4bqYHfvggzMjw+7+xRfmGsm1tJCL0SWkKVn2XKXlsMO0bpHXtTZ8uMg11wSWLsaGsPHKWpjPhcknOVi4OWWJz5ghcswxYXKibSsCBoELLhC5916RYcPMlqAUPAIogrhsUYIKSylFMjMRd3XsBYhAns826D54ToJtMcz9VJWUkuaKFC3nnSfy4IPmaoJoJ7XbB7uqtbX4IfDnnyK4FlHNvFYtU4kqG0sjOzaO+ygt/Hn1VRGq4rm09dbmZOcqLZTnVefqjdcLCuNuu4kgCUniz16VI9kQNjkOMZDXw+YT78ezzzZTQlYfr64hgTCnjRQcAhhRd9nF1PGgjisGbqVwEEAB5G7ozDONKMxEp59uEhjkULoqHCYCbjXs/ZThqiUlfdLWrDEJsp991riycCBTP/qAl7Y2FxsEiApu3944PO+0k3HhIjozCOKwzUnOtbRw/bxixfqWCbonY5irtKAY5RAcHsSQI9HGpEkm2Qe4MB8BkA1hE8Awc24ibD7Rw5s2NdNC2BZZv5TsI0CYHPUocLXZdVf7/dvq8aqrTJm3a68VIZeJUngIUIgR68h335n7NfLClET8DrGFQw5WlCQfH8PeT1VJKW09c1A64QSRN98UadFChMipzTcPb/Vry4pAFBFA0iPlyYCHYsLJC0UlLOKCgIxVrtJCNPLvv6/vbbvtTJ5XrrTKcjULa4xRaJcUM7jboTgS0RkA2RA2AQwz5yZs8PnZZyIHHGD0aZKuYfRSsosANZr//W9zz4jndhLvNqjfynbMtkn2qe23t4txIfY2bpyxpJSWrYt7N+rUUFX+P/8x93tJJhv7qVpSSltBP/1kXE+o4kP9lLFjk7nTJfkLUt6yR4BrI27rp083rl1YFHH1sklUU581a73SQl0jXM+IZRkzxvjVFBpxAqZiIPFyVBIMKKelDWEThamyxSe1JalAf+KJJr9EEg/JUZjPksbAPQfKCd7bEDVOqXWaNBo6VKR3b5GLLhKhZJVS+AhgKcVKgtH/tttEunffsE/mgdDNo44y0QJJ/+5t7KeqpGRa1+SOI7D3229FsKvikKikCCQdAeJEmjc3lkQsFtzaEyyfb/rtNyON8W3gyurSS42vQyFZOXv0MNnVBg82J5SAyIawCWioOTVji08MgIRUEXDL7esZZ+Q0bH3ZIwJ4p5J/g1SxHTqYDOmkjsWilaRtAiP3zjuLcJfKGgvKA9cjzAX92AcfGLFYubLBHgM/hGVrjz1ESKDxzjsm+37SycZ+qkpKWauIwFQsKqy8W281ByMlRSCpCJDaluvf2bNNvSBis6JWkJFMYaedJsJYcQx+/PH1kiKp8wJfuKGSVoYTChcornQMgGcbwiaAYebchE0+MULinUhqWHzTo/YZ5QxmBBtAd6eME7fdeI3iGfnCCyIjR4p06RLBAWc5JPihejnbIAUDlewiwDHw9ttFzj/fpB2HLrvMWFfItkYSzEIgG/upKileVhJOrccfb/zjSXidRNuxFxz0mWQjsGiRicVCMed0NXGiCBm3okiksiEegzK+RCgSn3H44VEcaXBjwsUN346zzjJXxAGSDWET4HCzbso2n269TQ7IHCyVwkMAz+yDDhKhhiyWFKwL3LVwo42iSDb0qG5nflDB4xXrEDVR3n23MG7s/eBj41mcDZgD0o3jhUxwPJZT/v7880Dvj2ywk3UfNvZTVVK8Tg+HoH/9yyTKJoAYNzAlRSApCJDOFkWcivEki0AZJ69llAmLAqc/UobzXeIKxqkwiYQzNFKQ0xdxOulFNHPk2YawyXGIgbxum0+MfYQQYYjnrgvjpFLwCBB/gsMDGOOVjXe2S7h9kTJ2wACRfv2C79t2i+PHm4BsssjhiauUHwTuu89YUnAvxEpK2CY1wal3XChkYz9VJcXPasLd6/LLTe0UdkNUaSVFIO4IcMVIOltciMjmRVqSuBR44PBOrlFiNYhTufhik9YnLuP3unaIwsS1jWthHJ4Djsi0IWy8shrmc/ng8/77RTp1MhmBuPlOUmxEmHPlp222AIKYyaxEKF1qPgkyX6EosiVwBxOgl6SfIQbyLNsd8RBkj+KulG1bKT8IoBhz6fD226Z/1hjxKkkTPZnQtbGfqpLid32jJo8YYZKvc6MZ5x3PL+/6fPIQoLgiLl7ff28iTTlRBZQxyipYJKc/9VRjfz/6aBOnkqScnERe43xOaWlOvAGTDWET8JCzai4ffKZmBCLPA+lxlYJDAM/Pffc1oVro77h8pZMrtrnDQKGJK5Epjpwm3N5zOA74riKusORt3GSSq1/fVJYnU/9JJ+VtKHnp2MZ+qkqK36lFfebAwCEIH3iCeJNcrccvPvp8fBAgnoMgeVLEXHihcZrHoTuu5FqCkBw77GDiVJAgcSdihSiIQDoZMg2G4IZnQ9hEYRryxSd3ARye8UokdoIM0kq5I8DhsGVLc0Ds1UuEtLwlEVsc9WrIPUHIHVmY4kiECpKQAW9cjN5K+UcAL2NiVEg6WWhkYz9VJSWbVUX9BhxCX39dpHVrcxiK4+1zNrzrO8lAACsgV3JLlxoXRlykknAtx7dJ2hssQtjd77rLOA7HmXCm799f5MorRW68MRRObAibUAbus9F88skh5oYbTN4Vanco5Y4A+SMol4TnNS5QlFAqjYYNM4oMBtfHHsu9b9stEKBNKBoKForuppvaHoH2pwhsiICN/VSVlGxXHZGQBM+TKJvqPXfemYxDXrZ46HvxQQDrH8o114p9+ohQeS4JCoo7A1yvYhUiJySpcAiuJ54sjs7ClJOmIALueMQO4WYaAtkQNiEM23eT+eSTzw23JHJUTJli8lMoZY8Anp17720MwRTXI3A+E+EOxgF/4UKTkemII7LvOx9votw+9ZRJb0uaWyVFIN8I2NhPVUnJZZbJAUjk1OLFItdfX5j2vlzw03ftI4BfBNIOi0PS1yzB5mTk++EHc6GAj0StWvYxz6VHrnxPP934tEyenEtLGd+1IWxCG7yPhvPNJ1m927QR2WUXU2Bwyy19DF4f3QCBM880hTK5I8Rg6oXcjEyNGhlP7bjczVBnZ599TJgdxw7cBpUUgXwjYGM/VSUl11kmUo8db+VKk+eQnVNJEYgiArglEk/F7XyhFCYlhgPnbaJMUVBQVOKUPpy9hWtiimrinhcS2RA2IQ3dV7NR4BMlBWWld28Rig8q+UcAS1SrVqZEEvE+hGt5IRIAksmbd9D50f3jQHisomClp1eOw9h1jMlFwMZ+mrWSsmDBAikuLpY5c+bIrFmzZO7cuTJw4ECpUKGCtGzZUtq1aycTJkyQKVOmyOrVq6Vfv35Sr1496du3ryxfvlyWLl0qd/1z/dGtWzepUqWKVKpUSQYNGuRpRm2A42kgPMQBoqjIBB0/95wphKekCEQJARTojh1FSPyAv0Dc4zT8YEsRVtL6kBmL/K+UCqYoYtSJmigHHGAifj/7LNSkBpHaT0OclyjwibsXt+LcFZCydK+9QmQ4gU0vW2bc5rh/mDTJKCt+COUEb9f99hP53/+iH9sBn3h5YnUjk5lXhcwPJvqsIpANAjb206yVFJehVq1ayeTJk6Vz586OklKrVi1xf+b+vWjRIkehQVEZPHiwjBo1SsaNGyd///2386dcuXLSvn176dKli/Tp00fqcD1SBtkAp6wxbPB7Dn5kSKpSxQTUswMqKQJRQIC1yaEcJfqhh0wlsEIj4lSo2E4xBU6HnTsbZSXKfhPE0owebaVCWOT205DWZ1T45Eb8mmtEGjcWefnl+LgdhTQtvpolLwYhZ2xjlHTyS6kpobFOnHee3xbsPk++DIoEZspeZndE2psiYBCwsZ8GpqQUFRXJRGzYglHB/Dv9Z7169ZLp06cLf8+cOVNmzJjhKCmNGzeWhg0bytChQ6VJkybSwEM1ZRvg+F6IBCEPGWJs0FSUql3bdxP6giIQKAK33GIKHRI0Tp2Nk08OtPnYNUYRVty/CEQnPTFplqL4nZLTknFxoiLSt1q1UKGO5H4aAsdR4RM9maJ8uB1xb0CJIqWyEXBrmlJPmQxXNWqU/U5JT7iZshDVGClDyOqd3cDS3iI/D3kzWC9Y4GrWDKRZbUQRCAQBG/tpYEpKqiWldevWMmnSpHUWlVRLypAhQ2TkyJElWlK6du0qvXv3LtGS0r9/fxlAKs4UQsGJFDEeXGqQOrhpsKOqbTZSU1RQg0FhRnEmL+fTT4s0a1ZQ7JfK7HffmYB60jAj9YlToQBklIiYIVJDk8YHS1jIZEPYhMyCp+ajxKd74KYeMIHRIeuhnvCJ8kPk+iCeBKUiCMWOVMR8+qQmxqoVRSJmqW9fk6AQ65GSIhAlBGzsp1krKStWrJCePXvK1KlTpXnz5tKjRw8nnoSYlBYtWjgxKU8++aTze2JSiEUhJgWXr2XLlpUYk1K5cmXHZcwL2QDHyzg2euaPP0xuyZdeMrVUiPDDD15JEbCFAMoyUblk79p6axMhSgC20noEiFMhRTHuVNQ4QikgTVAU0v0QN0RuVU5js2eXXEI74LmM7H6acD5xNRo71l+GqoAhiU1zbGkUayR/BGI110/1889NbBC1mOfNE8E6EyUiF0/duibFMlsBoWlKikCUELAhN7JWUvINlA1wsuaRAnkkbSfwFcsKheVy3VGzHoy+WFAIoKBwA3/bbSJVq4pMm5aMquthTSJWiksuEeFygRMjyTwyVYQLaxyp7T7/vLF6HXWUiW+zQJHeTwPkP2p8UuujXj1TsRoP4bjV7ghwajI2RYD7YYcZtyxSN+MCFQSRT4NPHo9Y6tlGiSi9xtZEQkZSLSspAlFDwMZ+qkpKWLNOSg5ia/An79dPJM1VLaxutd0CRoD8mvgF3HOPSPXqIi+8YOUWPvaIczokTgU3sMMPN3EqO+6YP7bcHLVEBVtKcmBD2OQP0PU9R5FPN+fKIYeYTNlaSXzDlUI9VsLH3nvP5Lrg4B4UUeJs993NHQV1mbFcRIHgmcKTX39t+CZ+SUkRiBoCNvZTVVLCnHUsKfi6kzNRy8SGibS2TWTlueeadDfUA8HdEJchJW8IEEhPnMobb4gQJPD44yLHHuvt3SCf4lRCvlHGQL5REh5YIBvCxgIbZXYRRT7x7kNMECKFAZQEdErrEbjxRpGrrzbljYjjIUlhkMT9Yf/+ImedJfLww0G2nH1bbOOMB4MqxnAlRSCKCNjYT1VJCXvmyS950kmmPgVJ3UMsyBY2K9p+RBEgvgKfAILj8YNAQVEHZv+TxXUqfh/4fxCngv8H17bZumrieke07y+/bPgH357SfkYKH5QTomU9xuf5Z3TjN2wImyDGmWsbUeXz/fdFDj3UxEcQRM89g5LIF1+I7L+/EZ+4fIVx7/Lbb8aaglUlClYLto2DDjI1dDg+aNk1/RKiioCN/VSVFBuzz/XM2WcbCUT1aOz6SopAEAgQXdmunSkiin8ACko+XZWC4CnfbVA8gSB6lJZzzjFFCsDZVSwyKRnpygdt+KXttxd5912RHXbw+2bWz9sQNlkPLsAXo8znFVeIjBihMQjudHNYb9JEZPp0o6+jt4dFZM6i/gq5bggJyydNnWpy7xCfhCdqtnck+eRB+y4MBGzsp6qk2FpLpCUhPQkHEOz6UXF+tcW/9hM8AsuXm3LLKL4UDyUGhfWllDsCBAeg/BFTlg2R0Y+csu4fkhik/p9/l/azSpWC92kpgwcbwqa0IcydO9cp4kshYAr51qhRQ9566y1ZuXKlzJs3T9544w1p2rSp7PaPdXDYsGFStWpVJ2Pk8uXL12WKrOih2EU++SxrGfE5YylgyXFQ5sBcyOTG6mBJeeedcD0f8ZZlCyWLVr6xJxEjWzqhcWxBSopAVBGwsZ+qkmJr9rkWIqiZqtd77WV837fZxlbv2k/SEKDKF66DHKbxE8GSErUcmnHHHP8PrlfdIhZelQye23LLWF2B2hA2pS2HESNGyD777CPNmjWTjh07OkV9a9euLWPGjHFS2p9zzjnSpk0bR4mpVKmS8/vFixfL4MGDZdSoUetqbp155pllrrh88lnm4MTU7aB+B0ZR3H3ynWjOy5jDeIYcFqQHRnHDmkA+i7AJpYCwNILUUYqCjn3xMn7uL4m9IePbJ5/kZwxexqnPKAIgYGM/VSXF5lojZQcVv0nyTopirmwKVQrZxJ2+cDamXshFF8W/bO8PP5hrVk4xRNzCV5UqthHV/hKEgA1hUxpcS5YsEYr1brHFFoJVBQtJ/fr15YQTTpApU6Y4P1+7dq2UK1fOUVzKly/v1NyaPn269OrVS2bOnCkzZsyQa6+9tswZySefZQ5ORLjLatlSBJcfArpJDFloBAZYEAixwwUOb0sbRL8oCChFeGgTuG6bOB4884zIvfeKdOpku3ftTxHwh4CN/VSVFH9zkvvTROkRCcdVzWmnmQTo+biyyZ2TeLRA/ADOzARDE32Jn/9jj5kaFHEkfEGOP97kyzzhBCPJiXVSUgRyQMCGsPEyvLZt28rdd98tn3zyiUybNs2xmqTSxIkTZf78+cJzQ4YMkZEjR2a0pKD8DEhL//43p9EI05dfiuy7r1FYqAlCUHchkWtN2mUXU2rM5vZG9jCS+uGNjQF1iy3sIT9njrEeIaJYAzb7tsel9pQkBGzIDVVS8rFicCNp2FDkq69ErrxShByLSsEigIQnj2PPniZtC/7/KCZYscjcNHy4KXoYp6hE1gsKCn+3bm2ULbXEBbtuCrQ1G8KmNGgXLlwoxcXFsmbNGmnUqJF06tRJcN264YYbZMd/kkB06NBBKleuLFhdRo8eLdWqVZN+/frJsmXLEhOTkorP4MHmbuXEE00K2jhtU7l8QnixclBnyybEjnsY21RUZBJxktyPZH+2iFqyY8eK3HSTEVtKikDUEbAhN1RJydcq4CYc2zK7sibHD3YWcOallDBpYSDqh9xwg6k9gR2d35G2Fwdk/l+5crD9h9Ea6wUFBUvK6aeLPPSQCMHZSopAAAjYEDYBDDPnJuLCJ9vTgQcag+mjjxqjeyGQe1DH1YmtOR+E+CBYn3utefPM32HTggUmazxWIzKQkztDSRGIOgI29lNVUvK5Cgie5+BJmlKi9tq2zedo4t/3ihUigwYZJ2bif0jXgpsX8T+pRHwKCgoWiT33NNjzbFSJ2BNiUIhFQeGioryWpY7qbMVyXDaETRSAiROf1MhAPFAzBdejONyl5DLHWE6wHJGgEEWB/BP5ogsuMEoSYU7XXx/+KNz00yQAxYqmpAjEAQEb+6kqKfleCRyQSeeCAypSCTcwJX8I4NpFtOFll5lrKK6j8EO/9NLSrQ3Us+jY0dj1ycQ0erRIhw7++rXxNNm7KAbKeCkseOutGsNkA/cC68OGsIkCpHHjk+BtvFbZ2m65JQoIhjMG7pe4J/r6a5Ph7JRTwunHa6sYrMmwhmj5/HOROnW8vun/OZwpdtpJ5K+/RKjlisFfSRGIAwI29lNVUqKwEpA+OL+SQpYchOyOSt4QIMIQZYRYEwgLCRXRvEgVAumJTeH6in+TIpq5iErEIsnyqYNCHs5rrjFXeoXinO5t9vWpgBCwIWwCGmpOzcSNz++/Nxnr2QLItUJ63CSSa0nAmWDChGhweN11ZssN2/UM4z9Z3Mh2fued0eBdR6EIeEHAxn6qSoqXmbDxDEoKB2QcU2fO1OuUsjDHaZuEA0OGiKxebVLg3HGHSLNmZb258e9fecWUecad6rDDRB5/PP/FNklPTT7KVauMCxuKlCoo/udW3/CEgA1h42kgIT8URz45uGJErV/fiIakJYN86y0TnkkcBm5eZLeKAi1dasQxRmw8bsm4FjStXCmy886mDyw2ZDRTUgTigoCN/VSVlKisBm7yiY7E/euII4zrl83ci1HBwcs4cF4m+J1dHasHV15XX51bpiuqh4E/cUI4Q5Mov0ULL6MJ/hlc1xgLsUq2U8wEz422GAMEbAibKMAQRz5xA2rQwFhSRo0ypZ6SQmxx1KIl1TKhduefHy3OXCcHDNp4BgdN3Kt17y7Svr1x61NSBOKEgI39VJWUKK0Ibs3Juch1GSlmsXuTLlfJIICjMH4BpN6FiNVgl+e6Kwhas8ZESqIYQOQALS62G6RO3ZyzzzbuZ5xILrwwCM60DUUgIwI2hE0UpiCufKKgcHdFzVYyfiUlbmHgQLPFNmki8uKL0TMWY7DH3Y5YmVdfNTVUgiLEDZ7dxKH8738mm5uSIhAnBGzsp6qkRG1F/PSTsX1/9plJdcKNfo0aURul3fGQqev2243jLsUwiTchgBwH5jBcoLBmkQsTR3Cyaj3yiJ05uO8+EdLK4M9BwvwoBvLbnXntzRICNoSNJVYSq4zh8oXr1znniDzwQBTQzG0MuHYddJC5h6NoY1B3TbmNauO3sXCQwAB3O0JGgxI5iBW2eO7apk4NetTaniIQPgI25IYqKeHPo/8euLbBkoINvHZtkyg/rhXS/XO/4Ru4XxFRiFMw0ozYHZSVrbfOteXM76MkkmKGOUApwnoTZuY1auWQwofaJ+PHi7RrFy5/2roikIKADWETBcDjzCcxEtzqE0xPCahGjaKAaHZjwIWNzPAc+gktpKZxVAmj9uGHi5C5nnBFcrPkSmQNw3KCchb3ucwVC30/vgjY2E9VSYnq+iCirmtXkQcfNIdzihFyQA/qGieqfLvjWrLEZLTCugAh0ah5YrOeCXkxmQMKJzIH1F/BgTjoOSCFDHE1VI/Hxa9586jPjo4vYQjYEDZRgCzufOINeuaZInvvbVyEypePAqr+x4BhnKSMxKO8+Wb0vZpxRcOojnvWxx/nXkf32WdFWrYM3jrjfyb0DUUgewRs7KeqpGQ/P+G/yXULFaWw8+Mci3sTh3YbJXDD567kHri2IoKyVy8REsjj6oZygF08aOXAC4/MwZgxRqIS5Um1d8YXhCWHtvv0ERk61CRJmDxZpHFjL6PSZxSBQBGwIWwCHXCWjcWdT7YMDssvvWTS4xJCFzciBoNMWYg0Ym3iEotB4kiSLuJyh3E/FyK25bXXRJ56yiRxVFIE4oiAjf1UlZQ4rAyuzLAxz5snsuuuptpVEhPmz55tLBfkpEQh4d+U381n6WF3fSBNmQMkLD4XxK3ss0/2q4fTBpYxYmuIhp02zaTwUVIE8oCADWGTB7Y26jIJfOKJuv/+Jp8HcR1160YBWW9jYNvDUPzccyarepyqqyOGDzlEpHp1I4pJmZwNkRcH723ECFaZpKWUzgYTfSeeCNjYT1VJicvawCGZYG6uXki7i72cIOt8WBeCxgzeyKTFFRWWFGqVjBxp/o4SYdnBokOUI5aPu+82uSP9Eg7ZFI7EIoPE43ouiUqnX1z0+bwhYEPY5I25lI6TwidheZRPIjXuxInxEQN4zhL4X6+ecVfDwzVOxNjhAfwHDMhu5G3amDnDKQKRrqQIxBUBG/upKilxWh1cQ5G4nZogZLwiVS2H+bjWU4EfnKx79jTRoLix4fpE2l2uCaNIKFGMESnF+KnXgjua1yr1zFvHjiYpfq1axm8DB3MlRSCPCNgQNnlkb13XSeGTbPWE5335ZXxchqiVy1bHXQ+uTkcfHYUV4W8MGNL33NPEpHzxhcj22/t7H8sJ80Y+HOYurjFF/rjWp5OKgI39VJWUOK4e7MXERnz7rXHuxf0L23GciN2aIHSqvUMc3IcPCeqJegAAIABJREFUj08BACIpsaIQ4E8BA9K+7LRT5hnACZvK9k8/bcoMo6BENe9mnNaSjjVnBGwIm5wHGUADSeITD1Fcp3bc0bh9BREmFwDEpTbBdkniQuI5MJrHlchExr0UxnDuCP3Queea9NG8T8kvJUUgzgjY2E9VSYnrCvnxR+N6hKsQlhRchzgAR52IOxkyxGSxwhKBkkXWriCrZNnCACWRyvDk0dx2W2MdobZNSUS2NtIK44xNihgUFE4XSopABBCwIWwiwKYkjc9TTzV3VFddZe54okpUay8qMlseWd0rV47qSMseF5Yg7pYoo8VdG65rXuibb8x7xLJgkck2psVLX/qMImADARv7qSopNmYyrD6IbeDA37+/OfBzRUW1dK+uR2GNq6R2Ocgz1ilTzG+xk+O2RuYybOdxJTJ+wQcB8MQHUT6Z+JrUaEikGc7jM2YYW/8LL/j3E4grPjruWCBgQ9hEAYik8blwoTGir14twv2PzQztXueTkEPuohgr23+LFl7fjO5zKIRkyOfeiRwqXog8KXhrk9CReCIlRSDuCNjYT1VJifsqYfwceimJi3WFYHNcj6KQ8gXFiUpVpHB5+WWDNC5R7O6dOsUvajLTWqHY4/nni/z2mwi5Kh9+2ATF//KLKSn89ttmbvDRwOqipAhECAEbwiYK7CaRzxEjjOsQMR6vvhq9bFEkaRw1ytR3ocp6EoiYIGJTMKbjfV1Wnd+ffjKiD5GIFYXM+kqKQNwRsLGfqpIS91Xijp9rKuJUqNBOyl6KQHJ7nw9iJ6ZaFZYTLCjQ7rubgoUoU0mNFvz0U1OlHgdx/BpwWCbP5vvvmxMEdVBIN6ykCEQMARvCJgosJ5FPcnFw/8E2E7WMURiPGzUy9zJz5iTrcD52rMnOxdYOn5kSbQ4caIzsOA6QmFNJEUgCAjb2U1VSkrBSXB7WrDGKwE03mZ9gscCKQbV0G0TmK1Iko5zgewDhf8BBHefpqGbsChIbLCkXXWTiU1w64QQTLB/XLGxB4qNtRRIBG8ImCownlU+qth95pMg224jMnZt/Yy3JGsnUjlvTV18ZCwqWlCQR3tZkjv/wQ5FnnjExNyXRihUmT8qvv5qMYFFwckjSPCgv+UPAxn6qSkr+5je8njkQk0YEZ2AC0kmpQrrbsIirPPogNS/XZRBXezjftm4dPf+DsHBw28WShBUFHwwcsFFY4lYQIGyMtP1IIWBD2ESB4STzyd3ImDGmfBYlnGwS91PUuyXmBCM6/3aJiurkSUlCSa90TOG1ZUuTWvmDD0q+D8RycumlxokAL2AlRSApCNjYT1VJScpqSeeDJOxUSMeiUbOmqUdy3HHBcktKXdzKhg0zSd+hY44xlhOyXCVRKvlBkGhWVU78IKbP5gkBG8ImT6xt0G2S+STrFEH0hCbi9YtlJUziDozkkigmWE2og+LSLruYwzt/MCTbMuaHyW9JbXMf1aSJCb1EMURBTCWcG/B0JrMX7ngHHGB7hNqfIhAeAjb2U1VSwpu//LfMIfnyy0VGjzbWDBxje/XK3bJBOl1SHt94o4kchFBKUE7imEo4/zOlI1AE8oqADWGTVwb/6TzpfFKDAyM6h+F33w1WOeBATtgdSgl/Xn/d1BSGUEKIzXAVE5SlQrmj+u9/TamsHXYQ+fxzkS23XL/SqU5PlXoM6m5iyyh8BzoGRSAIBGzsp6qkBDFTUW8DGzO+ACgXVP9i58wmwxSpdKlpQppj99qsTRujnBx+eNRR0PEpAopAKQjYEDZRAD/pfKJING5sArmDKBjIPRf1dl03LuJLXNpuOyNOUEy4oyrknCDkrCHBI+GYhIVCuMChLFJLhaxren8XhR1AxxAkAjb2U1VSgpyxKLdFxikyT3EVRi5EdtT69b2NGD8CHGupBUJKXa7IKGLIbqz2a28Y6lOKQIQRsCFsosB+IfDJofigg0y5LEIE/daMXbBgvbWEmrOk23Xp0EPXW0sIO0wtBxWF+c3XGAiIJy4FK8q8eSb7PMkcCckkPTHud4ViWcrXHGi/9hGwsZ+qkmJ/XvPXY2rmKQookgWse/fSd8/Fi0VIwn/nnab+BzZ9qtxfe633Mrv541Z7VgQUAY8I2BA2HocS6mOFwidb9A03eCs2iMsWmeIJAsdiQrYql6iK3rSpUUywmoSZfyXUibfQOKL0jjtELrvMFG0kPBOXuEyZvywMS7tQBEJDwMZ+qkpKaNMX0YbxByBGhZ2UaumkBia+pHLl9QMmzoR4E1LFYO+nrgmFCqmsrvkTIzqxOixFIHsEbAib7EcX3JuFwidpb6nyTuHAkqq8L1li6sryu+eeMwZyl+rVW28tIc4kqWWtgltVpiU8oHfbTYR8MtSrOftskX32MUqfWpyCRlvbiwICNvbTQJWUuXPnSp8+faRWrVpSp04dWblypXz44YdSo0YN6dSpkxxxxBEyYcIEmTJliqxevVr69esn9erVk759+8ry5ctl6dKlctddd0nFihXLxN8GOGUOIs4PEFVJ9q+vvxbZYw+RJ54Q2Xprk6mLKlWkJcF23aWLSM+eJipQSRFQBBKJQKHsp4XCJ4t04kQRQgbJtPXRRyKffbbejYu6KtxXQSghxLG4Qe8ctJWyQ4C6MP36GaWEmBREaceO2bWlbykCUUfAxn4aqJIyYsQI2WeffaRZs2bSsWNH2XXXXeWzzz5zlI4BAwZI7dq1pVWrVjJ58mRZtGiRFBcXO4rK4MGDZdSoUTJu3Dj5+++/5UwPVZ9sgBP1BZLz+Lg+IxUM0gwHZuz+VKjCqoLtmsxgONcqKQKKQKIRKJT9tFD4dBcrSgrbO/dPeOy6VLu2yTiFYnL88eb3SrkjgAWLlMMUs6xTx8SnqCUqd1y1hWgiYGM/DVRJWbJkifTv31+22GILwaqChaR+/frOv4cNGyb333+/FBUVyUR2TaFCa5H06tVLpk+f7vw9c+ZMmTFjhlyLQ20a0S6KTiqh0CjliAAYEptCauKqVUV69BC5+GLzbyVFQBEoCARsCJsoAFkofLpY4+5FbhMUlAYN1ismBx6ogdxhrUc3DfSoUSapppIikFQEbOyngSopqRPRtm1bufvuu6V69eryyy+/yIUXXiiPP/54iZaUIUOGyMiRI9WSks+V/N13RjFJTfKez/Fo34qAImANARvCpjRm1E043GmmuCPuR9lknQ93ZMltHUvK9tsnlz/lTBEAARtyI1AlZeHChY4L15o1a6RRo0bC/7/77jv58ccfHevIYYcdJk8++aRMnTrViUnB0kJMCi5fy5Yt05gUXfeKgCKgCOQBARvCpjS21E04DxOuXSoCioAikCMCNuRGoEpKjvz6et0GOL4GpA8rAoqAIhBTBPK5n4bpJpw+HfnkM6ZLQ4etCCgCikCJCNjYT1VJ0cWnCCgCikCBI2BD2HiBOGg3YY1l9IK6PqMIKAKKgH8EbMiNWCsp/iHVNxQBRUARUARKQiBfiUhsuwnr7CsCioAioAgEg0DYciPWSkrY4KROYePGjZ0sZLbIhoaazkvSebTNH/jankfbPNrmD0yTzqNt/vKxTm3to+n95GO9umPIx7y6fSvf9ldcvuZb57pw5jrfe7eNNa5Kisf1PHbsWDmXmiKWKB8bTdJ5tM1fPjYQ2zzqOg1+Q7A9h/lYp8Gj5q3FfKxXd2T5mNcoKCnKt7e1GdRTusaDQtJ7O7rGvWPl90lVUvwiZun5fG40lli0bmWwxVdqP0mfx6TzVygH+EKYx0KZy5L2uUKZ3yhZzvIhb3SNF17tvKR/27FVUgiI5E9SKen8MW/KY/xXr85h/OewUL7FQuIzfVUWwnda0pdYiHwXIs/6bSf3LBxbJSUZRwPlQhFQBBQBRUARUAQUAUVAEVAENrKG/m0z+lzxVwQUAUVAEVAEFAFFQBFQBBQBRaAMBNSSoktEEVAEFAFFQBFQBBQBRUARUAQihYAqKZGaDh2MIqAIKAKKgCKgCCgCioAioAhEUkl58cUXZfz48fLbb7/JfvvtJ6eeeqoMHDhQKlSoIC1btpR27drJhAkTZMqUKbJ69Wrp16+f7LHHHtKpUyepWLGi/PDDD3L77bfLDjvsENkZ9sIjPDz++ONy6aWXyr/+9S+Hl759+8ry5ctl6dKlctdddzn8RpGy4e+7776T6667zmHnzz//lPvvv18233zzKLLnjCkbHl1mBg0aJG+99ZZMnjw5cfyNGzdOZs6c6WRv49usXr16onhcu3Zt4vaa7t27y6pVq2TRokVy5513St26dWOz17iLy8v3GHe5UdKH5IXvOMuS0jaPbPiOm4xJ5z0bnuMkc4Kca9qKkywK6tuOm3wq63AQSSUlddDNmzeXOnXqOEpKrVq1pFWrVs7Bzv0boVpcXCzDhw+XHj16OAfbMWPGSM2aNaVNmzZl8R+J35fGI4Mj//bWW2/tKCnffvutDB48WEaNGuV8fIQTnXnmmZHgIdMgvPKX2gaKGX923333yPPHAP3w+Pzzz8tPP/0kjzzySKSVFC/fYfoaXbJkiXTo0EEOPPBAR8Hk24yyopkNj7/++msi9xqw4BD/888/y0knnRTLvcadz0KQGyVtjF73objKktKEgVe+4yxj0nn3w3McZU6ucx1nWZTLtx1n+VQS35FWUu699175/fffZdq0aTJx4kRn/EVFRc6/3b/dnz3zzDPStWtX5yC/YsUKmTRpknO4jzpl4jH9ADhr1iyn6n2vXr2cm+oZM2bItddeG2kW/fDnMjJ79mzHSnT33XdHmjd3cH54/PHHH2Xo0KEyYsSIdYp21Jn0wx/WIS4UsHKihK1Zs8ZqEdRssfTDI5cDSdxrUE4uuugiueeee+STTz6J3V7j5XtMitwoaZ37WcNxlCWlfdt++I6rjEnn3Q/PcZQ5Qcx1XGVRrt92XOVTaXMeWSXl3//+t5QvX14uueQS6dy58zpLSuvWrR0FJN2SgnDFNWrYsGEydepU+eyzz+Syyy7L9sxi5b2yeExXUlDAhgwZIiNHjoyFJcUvf/D7yiuvyKOPPuq468XhBt4vj4899pg899xzUqlSJUfZHj16tDRt2tTKesumE7/8LVy40HHZe+CBB5zLBb5DLGJRJr88vvvuu4nbaxYsWCBXXnml3HLLLY7FOm57jbu+yprLJMiNkr6lsviOuywpbf/wy3ccZUw67355jpvMCWqu4yiLgvi24yifMp0PIqmk4MpE7MUJJ5wgm266qXPIwYefmJQWLVo4MSlPPvmko4wQk8KzO+20k5x//vlSrVo1we+U54lniSp54ZHDOq5dHNZRwk455RTHx3/ZsmWRj0nJhr9DDz1U+INrG/EMV111ley2225RnUJHUSxrnZY0hy5D7oEpqgxmyx+WlF9++WVdbNg222wTVRazmkP2oKTtNfXq1ZODDjrI2T9xk8WVJC57jbu4vKzXuMuNkj4kL3zHWZaUtnlkw3fcZEw679nwzLkhLjInyLmG7zjJoqC+7bjJp7IOB5FUUsoatP5eEVAEFAFFQBFQBBQBRUARUASSi4AqKcmdW+VMEVAEFAFFQBFQBBQBRUARiCUCqqTEctp00IqAIqAIKAKKgCKgCCgCikByEVAlJblzq5wpAoqAIqAIKAKKgCKgCCgCsURAlZRYTpsOWhFQBBQBRUARUAQUAUVAEUguAqqkJHdulTNFQBFQBBQBRUARUAQUAUUglggUrJLy/fffy+WXXy7//e9/ZYsttpC6des6NQKozUJq2I8++sjThFI45/jjj5enn35aKleuLLfeeqtThJCfU9+FPlyi9scdd9whm222mbRs2VKGDx8uf/zxh5Ne+J133pFy5co57zdu3FiWL18uxxxzzLp3qVtAJW/GmE7XX3+9UNyJdM233XabNGvWLOPYqSfTv39/mTNnjrz99tty2GGHrXu+tLZISbpo0SL5888/5eijj5Y777zT6Y9im+ecc4689957su2228r48eMdLOfPn++kiv7rr7+cd6h306VLl43GVdr7P/zwg3Ts2NFJM10WUbTzt99+K+uxjX4PlhdeeKFsueWWvt9Nf4FU0bQDFqXR//73Pyc9NikCcyXWEeOfN2+eUKyrevXqTpOsO+oDPfvss854xo4dK4cccojMnTtXTj/99HXdfvnll056RtYnaZQphsr622677ZwaJ9TKYG2Aj9sua6Zt27YbDZ0igLT99ddfO3NPXn5S2WaiVatWOVXNX375ZWcdhUEUPr3ppptk8uTJnpoHT75d0l/vv//+cv/99ztpz1MJnEjNyzOkBqcoJ98D9WA6derkpF7m++7Tp4+ceuqpnvp1HyK//XnnnScrV6501gh7Af1AYAr+/P/AAw+U//znP06KZ6/fiK+B6MOlImBbbvBd8e1CVJKuWrWqsI9Ape3VvXv3lgcffNBZi5n2xbDlxk8//SRnnHGGU3OHbxw51717d2fsFCJm7/nggw8cmUHaeZeuueYapxgsxN6Uum+5z6jcyO4j9Ss3Mu1rmfZ95pX5plwCcoVzVvpemhS5wb6PjEF2lnZuLE1uUEKjUaNGTikNzkl8BwMGDPA1uaXJDdrh2+JMSykH5FmVKlViJzcKUknhIHfkkUc6At49OFOBl42PQ5YfJYXD4PPPP+8cGFmgbMoc7lgYHMIovLjHHns4RQopxMjmi1LEAYNFzWEfBYUFxM9QBvig+bBTifzuHIiOPfbYDX5OZWiUlzfffNM5AFMY8NNPP8148EM5oX02EQ5xrpKSqS02G5QwsDvttNOcmi3wSmX4jz/+2OED5eeJJ55wijGifPEsvK5YscKpWTNz5kzn8JtKpb3PMxzYLrjgAjnqqKMyfrTZKinMNdi7B3xfO0MWD6Mw0B+CIleaPXu2owig0KbywHoEUzZN1hHKIZV3UwnFsXbt2s7Pd955Z0eQMLcQY2Mdo3RxWGYdc+hevHixHHDAAc4aS1cqrr76aqlRo4ZT1+bGG2+UJUuWyA033JCRRcbIGklV4nPFJP19P0oKh0/2BNZyxYoVnTWOonDuuedu0CyHvq222spRFsAJocL3hlLOOt9nn32c7/jggw922uJQ6ZXq16/v4H/44Yc7e9DFF1/s7Aeff/65Mx4UOubc3Tv8fCNex6DPlY5APuRG6mh69uzpHDJQkjPt1cgCvmvkTmlKig25wb6CgtWgQQPn20DOTJgwQfbee2/nQoPfI3+KiorWKSnIR2Qpl1PIYw5wrHt3f3LxULmR3ZfqV25k2tdK2/c5bHMx9tBDDzkXKiir7INJlBvMAgo3ZxAuKEtTUkqTG+wpfBu8714As/75ZrxSaXLjpZdeci66keFcmtE+xc7jJjcKUklh0ysuLpbXXntto3XA5ulHSTnzzDOd22YOixzSqSZ+zz33OO1SUJJDOh8zhwyeo0BlKnEQadiwoaNoQFhluOE64ogj1j3GIaVJkybyzTffrLtZdX/Jsygc3D5BWGhYkLRZFjHmVCXFS1tr1qxxLCSMlxsurDbcyPOhcPjdYYcdhAOfewPMGNikOLQhPPl9KmV6n9sH8EQgZSJXSWEjoBAdN4iMc/Dgwc7/2QTAnxs9xsjtHIduKmxTxA4lBSUylVBguAl/9dVXnR9zc7377rs7h1FuTrBecDBHuaSQKLfcjIM2wRU8aJPbT6xc/J/3sSCgIPTq1avEG8Ky5iz99+mKFoona8W9fdx3333lxRdf3EA5RKnmluWNN97YqDvWAOsM5TqVvvrqK4cHlBSUllQCQzbqmjVrOrhgWXBvf0vjB4UATBk/ygQHL4o+stbZWJnzdEWd/u+77z6BJ8i16HGYQdkBWxQM5oQx+VFSsBLyzb3//vvOgejkk092bn0zWSW52GAtoPSnEwodhQM5KGLt4jsHG6xbWGv22muvDV6hf+bNbYu9hHkbPXq0s3/sueeejsKeTl6/Eb/rSp/fGIF8yA13FBxm2GcYA2vKy16d6fLGy/ulrYFs5AZtoYzwTXGR5hKXAMhb15LCJQffMzIMomgq3yD7dyqp3MjtC81GbtBj6r5W2r7PRRl7+8MPP5xxkEmQGy6Dfs6NpckNLgWRacheZF2uciMVfC4HkEePPPKI8+M4yY2CVFJwieLQhWUinVIXW7qLTOqzKDiVKlVybqzQnvk3N6ocirEYcFhC4eD2CDcvqjnzu2nTpjmKC5sxC5EDC4dGKskuWLDAOcxzqE2tEosS4N46pY+Xm3K0blfJ4ZCKEEg1n3sVNmW1xc0yHxgWIjYgbkawkMBTnTp1nG7YeDj8cvDnQMuzX3zxhePaRvvplOn9hQsXOu9/+OGHGTc7VxhzU8CHziETUzK4MId8oCg7Y8aMcdpZunSpcyOZyZLC77CyXXvttY7JlI970qRJjqBlbrDC4RaFm99TTz21kZKC5evmm292bgT5mwNnJkuKl7VWEgjpPCDwGTObHYQwx4KX6tLHwZqbrtT5QEngcA92HO5RwCCsNPDKd8Gcl+TuxS0ZyphLzD3WlNIICwoHLpRZiP6wGHC7y/cEDxxOUr8BnuN7pR8ULNYGCj+Her4NDv8oT7TF982cpyopKIw9evTYaEh8t+5lBe5VuMrw7Z544onrNvT0lyZOnOgoDlg0sFihcKUSllSsgKxbFC3GibKByZ3vhz44bKYSODNvrBOI55g32kdhQknhu0LJZq5cl0Gv30jGD0h/6QmBfMgNd2BcAlxxxRXO9wiVtVfzTCYlxcv7pYGSrqR4aYvLHawiuAGlWkXSlZQXXnjB2Uv5m72ciwMUfKxIqaRyw6BhU26k72ul7ftYAnBBYn/kYgYFk70tnZIiN+DLi5KSSW5wPuSc1K1bN+esBOUqN1LxRqaeddZZ0r59e+fHcZIbqqSkfTleFlvqKxxyiB9xiYMeLhv8nI3U9Vvn39yUchAifgMlgrgADh1YQTDN7brrro4FgBtTFBqXcCHBdMrBN53SLTEoKRyw0g94JQmcdGHjpS18J1GIXGWIW20UgFQlBSWN+BSXUFY43PKRctueSpneB4vtt9/escRkIlcY8zwHUQQ6h0M2cDBmflB2sC7wsbruY2UpKRxsd9llF2eOGIcb+8GtN/PKz3FfYzNOt6RwwKQfxo4yygYUpLuXi0c6D1jSsNKkKilDhw5dt3ZQELBm4YqUPhe0yQ0rc5zuF4sywIECy1K6bzEuSFivXCpLSWE9HHfcceusLSgTWDZdqxX+9LglpF8isLGigKPMpCosKPeXXnqpY4XBggePzL0fSwrj55vBVRHhyWaOxRBLaWmEcgNOrmLBc6wFXDKx+KC8YN1D4UN5dwl8udBIJVzzmLdUJYV5QzFmzbLeiEsBA9rH4gPuXr+RjB+Q/tITAl6VFC+NeZUbbltdu3Z1LLHuYd3LXp1JSfHyfml8+JUbKBt877iDpl+epSsp9IlLCt8h7tDsu1yoEGenciN3N+Fs5Ub6vkY7pe37eGfg/s2exuUR5xH291QLWqb3S1t3UZQb7lj9nBtLkhu0wwUcMod9Brmeq9xwx8aFOH1iPXE9XOIkNwpSSUEhwDrhHopSPwq/lhQ+VA6i6a4ptMmNJ4dYBAyHZG4T2OAhDi2vv/76uhtrdwwcQLh1xW8X4jCC2xEBbCVRutmeAw03tUG4e5XWFlYFbnpRxry4ezFukgjwbLqQyvQ+ygU44KaViVxhjIKIVYcbfw513Fwz13zwHEL5HZsnmyZz41VJWbt2rSMs2ag5gKcqKRz4cR1LV1JcNzo2Hm5JWFc2LCnp7l4ox9xKurFAbFRggPWuJOIQzJyU5FuLkGG9pVpl3LXsunthQUE5y+TuxVxgMQQTqDQlhW/BVZbADhxxBWP88InFEQUeSw8KPIoKCgvP0LYfSwruVawP2oRwV+D7LMvVENcbvgXWBYcxrKeMw72xYg1jBWHNpBIKrnvpgGDi++BdFDCI2C7mjb0Aix5WQTc+hvnBlZHYFa/fSMYPSH/pCYF8yA0GhoUYF1Fup93LIC/7vh93r7DkBnsn6xt55Lokp4JdkpKS+nv8/PmWsLSmksoNg0ZQlpRMcqOkfS3Tvo/nAXspezbEWsXKjZKaSqnuXnGVGy4/fpQU3kmVG6mYcLmJpw3zkavcoF3kGkoKF67EUroUJ7lRkEoK/r0IfSwWHA4gtH4+RtfdxGt2L9rh0M6BGHKDWjksoZhgVcC1iEBkDiocurhV50DCwsaPnvGwgBCCLNJUVxAUGxZtaRkfuBFnIyfeg/Zp1w2c5+eY4lPjW1I/iPQbsdLaYowsag66CMyzzz7bOYjSNgdG+sOlDZ9HbsC48UWxwJqC6wyHUnDi4EXWpFQq7X2eweJ03XXXORseh2f4AaN0coUxViqwZSzcHOBegCWFwDHiHbAA4D5DzBBuWoyFm2qUlXQqzd0LCxdCtyx3r5KUFPChP3fz9nQyKuOhdEWLwFMOtlitcA3BfIyZ3iWSHSDgcUdyCQsEmybEfLChMVe4RO64446OgCFOhYMGSnN6ogGED0oct7y4tqG0YbLONGe4e9Evazvd3at169ZOrEdJ1kDGh1KAKxVjgbDSYd3jeeLAUDTSlZSysCaJAC5mYMWa5d8oRSgcqcT64lvnRgprD2PlW3cPY3wXuIKlEj/jJhi3B751xo5vdzrxnaIUoQTiVohyglsX6x/Bz7rhQgTlhgMr31fqN1IWj/r73BDIh9xgxMw/B73US7VM+77LZSYlxYbcwB0Yiw24labspyspKO9c7LC2+U6QNaz19KBrlRu5rWWvcoP5QN6VtK+Vtu8j7zmHcMnD/o51n1gk/k6lJMgNl5+ylJTS5AbKGReqWO85ZyGbkR+ux0cucoMzEHHQyNd0r4k4yY2CVFJYWJgOCbZlA+Tw6qYgZsH4CZznUMRtOocaiFtcDhIcjHFJwcwN4YLCwYv0kfyOQyzuXyxuFiaWGG7JOGBxgHMJFzAC0VIDbd0DKNZz+tksAAAgAElEQVQgCMUGKwIbOf6g7q0ThywOxRw0U4kYCjYN3Jf4OHgOl63S2uLQyWEMNxU2LcYNbxxe+RmCBL6wKnGYYszcAnNo5TCHkEKhcdPZYsVwD2Klvc9YOPCCFWPlwI2FyB1nKj+uMOaDZ5yYMuEJxQ2lhNsmNkQwpj33IIgyg/KI8pXqskPbrIfU9K5u4DzzxTzSV6bA+ZKUFNYFc8OB1k2mkK2owSSMIkBcB24RHGZRvlyswckNInctHyjhrAUUNxRnl9wMVeCDkg4m3NziYkiWLuaZ3zFvxEdAKPgcomkbvjiAo8jwPkoqSmGmOeN7wZUKYcYmylpG+eFyAAtKSYHz9MtaZGwo7awHCKWFuWI+sPZwmPerpNAOLgmMne8ISw94ImTBA4Jf8MAdjX0CfLmlwrWOdYYCm6qEu9YflD2sqVwisDbxDXbHnjr/4IXy6KZnZn263w/fEodVxsa7KJvp30i2a0nf846AbbnByDjIc8mTnsK9tH2fvYX9irEim/hWsfTalht8y3wPWHNdJQMXRvYqLgW5XOBAi/zlkgPFCXmAexfEHsWFi6vQq9ywLzcy7Wul7fvMHRe3zDX7F/PtxlkkUW5g6UOGcSZAGUA2Id+8yA1itJBdnAk4WyFHWedQrnID2YzMceNL2UPcMaWerbzvfvl5smCVlKDgRhBwsCjp8BxUH9m0QzAxHwrmvrgSh1Xck1B+cC1DeeOG2QbZTk9sgyfbfWSaMy4HULRIPuAndsQ2D1HvL/UbifpYdXzrEVC5Ed5qULkRHrY2Wla5ET7KcZIbqqQEsB64fcW1Kz2XewBNF2wTWHnIZuTe3NsGQpWU8BEnuJxbJMzSfoouhj+yePSQ728kHihFd5QqN4Kfm3x/Eyo3gp/T9BZVbuSGcb6/Eb+jVyXFL2L6vCKgCCgCioAioAgoAoqAIqAIhIqAKimhwquNKwKKgCKgCCgCioAioAgoAoqAXwRUSfGLmD6vCCgCioAioAgoAoqAIqAIKAKhIqBKSqjwauOKgCKgCCgCioAioAgoAoqAIuAXAVVS/CKmzysCioAioAgoAoqAIqAIKAKKQKgIqJISKrzauCKgCCgCioAioAgoAoqAIqAI+EVAlRS/iOnzioAioAgoAoqAIqAIKAKKgCIQKgKqpIQKrzauCCgCioAioAgoAoqAIqAIKAJ+EVAlxS9i+rwioAgoAoqAIqAIKAKKgCKgCISKgCopocKrjSsCioAioAgoAoqAIqAIKAKKgF8EVEnxi5g+rwgoAoqAIqAIKAKKgCKgCCgCoSKgSkqo8GrjioAioAgoAoqAIqAIKAKKgCLgFwFVUvwips8rAoqAIqAIKAKKgCKgCCgCikCoCKiSEiq82rgioAgoAoqAIqAIKAKKgCKgCPhFQJUUv4jp84qAIqAIKAKKgCKgCCgCioAiECoCqqSECq82rggoAoqAIqAIKAKKQO4IrFmzRjbffPPcG9IWFIGYIKBKSkwmSoepCCgCioAioAgoAoWBwMqVK+X222+XiRMnyjfffCM//fSTHHLIIfL6668XBgDKpSIgIqqk6DJQBBQBRUARUAQUAUUgIggsW7ZMjjzySNl6663l2muvlb333ls23XRT2XbbbaVatWoRGaUOQxEIHwFVUsLHWHtQBBQBRUARUAQUAUXAEwIXX3yxfPrppzJt2jR17/KEmD6UVARUSUnqzCpfOSFw7rnnygMPPCCdOnWSe++9d11bb7zxhhx99NHO///++29ZunSpXHrppTJjxgz5/vvvpWbNmlJUVCRDhgyRSpUqOc99/fXXsssuu8g999wjU6ZMkeeff14qVKggZ599tgwfPtwRQmPHjpXzzjuv1DEXFxdL//79c+JJX1YEFAFFQBHIDgFkwkcffSTvvPPOBg1Ur15dLrnkEmd//vPPP2Xw4MHOfv7dd9/JDjvs4MiQ3r17O5YQl3DjuuOOOxzZ8Mcffzg/3nnnnZ3/Q7Vq1XLkyPvvvy8ff/yxbLHFFtKiRQu56aabZLvttnOemT59uhx33HEyYcIExy1s1qxZjpWFsVx33XXr+ipt3NmhoG8pAnYRUCXFLt7aW0wQYGNHmVi+fLkjODCzQ6effrojDBYsWOAoKT/88IOMHj1aTjrpJKlRo4YjxLgFa9Kkidx///0bKCm0gbLBs2+99ZZ07drVeXbYsGGyatUqR+GBaPuII46QJ5980jH5Q5j9+aOkCCgCioAiYB8BL0oKysitt97qKA1cZhE/0r17d+nZs6cMGDDAGfTLL78sxx9/vHORddZZZzkKyMCBA+XZZ59dp6SUK1fOkS9XX321c3mFwoOs4ELr3Xffdf52lZQ6derI9ddfL/Xr15epU6c6fdF/ly5dnP5USbG/VrTH4BBQJSU4LLWlBCHgbuzcbqEwXHPNNbJw4ULZa6+91gkchEhJdN9990m3bt2EwEeEjWtJueiii2TUqFHrXkFIcev2888/S8WKFdf93H3+lVdekcaNGycIVWVFEVAEFIF4IlCWkoKMwJLRt29fx3LiEns8e/0vv/ziWNBvvPFG6devn3Mx5dKVV14pTzzxxDolZZNNNpETTjhBXnjhhXXPoJwcdthhzuVVu3bt1ikpKCjErbjUuXNn54Jt/vz5qqTEc6npqFMQUCVFl4MiUAICrkC6+eab5ZxzzpEvv/zSsYKgqBx66KHO7RhKCn9uu+02eeihh5wMLCgmf/31l6xevdp5FnO/q3Q8/PDDzs2ZS9yyHXPMMfLBBx/I/vvvr0qKrkRFQBFQBCKKADKBfT71QomhrlixwpENp5xyihxwwAHy2muvrXMJ5vf8/9hjj5UPP/xQ9ttvP8c9i2fHjx8vp512mqCQlKSkDBo0SPr06bMBGlWqVJHLLrvMsby4lhTkyFFHHbXuOeQMrsQE3+NynDpuLs2w+OMmhgUfVzUlRSDKCKiSEuXZ0bHlDYHUW7ODDjrIsaQgHAhknDlz5jolZcSIEY7/L7EluGZVrlxZnnvuOef3X331ldStW7dUJcUVXqqk5G2atWNFQBFQBDwhgEzAmvHUU09t8DyWduISsW4ceOCBjotXqtKQrqRwsYU8ueuuu5x4lPLlyzt/uxdaNI5r8BVXXLGBRYafo6RcfvnljutYaUoKihQXa6lKijtu+v7iiy8Eqz7jxnqjpAhEGQFVUqI8Ozq2vCGQqqQQOI/A4BaMwHkCHl1LSuvWrR0Bg2Li0lVXXeUEOKYrKcSgIJhcwkzPjZi6e+VtmrVjRUARUAQ8IeDV3QtXrtTAddet13X3ojNqnhBD0rZtW0dhwKrx4osvrnP3wsKOxQa3LZdmz57t1EnBEsN7rpJyww03OLErLtEel2mZ3L2w3OA2hoxSUgSijIAqKVGeHR1b3hBIFUi4bhEMSXwIgiVVSUEhGTNmjIwbN07q1avnKCvcchFQn66kYFonA0yzZs2cwHniVlBcEFCppDEpeZt27VgRUAQUgRIRKEtJYW8nFgX3X2QE1hQutci2xSWXGzhP1fimTZs68SsoHCW5exEATzavXr16OVaRRYsWOe2QIey9996TzTbbbJ2SsuOOOzoyBMsIygl9MYbUwHlczRiLa0nBzYz4ynSrkE69IhA1BFRJidqM6HgigUCmjCipSgomdYQBmVnWrl3rZO5q3ry5k3YyXUm5++67nerBL730khNAifBxUxCrkhKJaddBKAKKgCKQtZLipiAmsyMZuWrXrr1RCuILLrjAcRvDLWyrrbZy+kqPSeFnuG0hH+bOneu4EZeWghiLCErJm2++uUEKYpQfyE2nz7/5GTEpZBfDVZmU+UqKQJQRUCUlyrOjY0sEAq5lZNKkSdKqVatE8KRMKAKKgCKgCOQPAdfdyw3Iz99ItGdFIDwEVEkJD1ttWRFwEFAlRReCIqAIKAKKQJAIqJISJJraVlQRUCUlqjOj40oMAqqkJGYqlRFFQBFQBCKBgCopkZgGHUTICKiSEjLA2rwioAgoAoqAIqAIKAKKgCKgCPhDQJUUf3jp04qAIqAIKAKKgCKgCCgCioAiEDICqqSEDLA2rwgoAoqAIqAIKAKKgCKgCCgC/hBQJcUfXvq0IqAIKAKKgCKgCCgCioAioAiEjEBslRQ3B3jI+GjzioAioAgUBAIUeks6qdxI+gwrf4qAImATgbDlRqyVlLDBsTnR2pcioAgoAvlCgMN7IeynhcJnvtaR9qsIKAKFg4CN/VSVlMJZT8qpIqAIKAIlImBD2EQB+kLhMwpY6xgUAUUg2QjY2E9VSUn2GlLuFAFFQBEoEwEbwqbMQVh4oFD4tACldqEIKAIFjoCN/VSVlAJfZMq+IqAIFDACH38scvbZssns2eruVcDLQFlXBBSBGCKwdq3IypUif/whsmaN+dvivzeZOjV0uaFKSgzXpQ5ZEVAEFIFAELjiCpERI2QTkdCFTSDjzbERGzd/OQ5RX1cEFAFFoGwEfv9d5LDDRD76qOxnQ3rChtxQJSWkydNmFQFFQBGINAIIudq1RZYulU3+/FOVlEhPlg5OEVAEFIEUBO67T+T880W2287s45tvLlK+vPnj599+nk1te/PNZZP99gtdbqiSoqteEVAEFIFCRODxx0VOO03k5JNlk6efDl3YRAFitaREYRZ0DAWPAOnO//xzvXuS66bk928uWtx3dt3V7GeFQLh57buvyKefisyaJdKgQV64trGfqpKSl6nVThUBRUARyDMCJ50k8txzIpMnyyatWqmSkufp0O4VgVgjwF5yww3rYyTKUjjCqMv0xhsiRx4Zaxg9Df6ZZ5zLJTnmGJEZMzy9EsZDqqRkQNUGOGFMqrapCCgCikDeEfjmG5G6dUVq1RKZP1822XxzVVLyPik6AEUgpgh88YXIwQeL/PZbyQykuhThMrTFFutdk1wXJS9/l/be55+L3HGHSIsWIlOmxBREH8M+6iiRmTOdCyZp2dLHi8E+auMcrpaUYOdMW1MEFAFFIPoIDBwoUlwsct11IkOGiA1hEwVQCoXPKGCtYygQBMgqxY3+W2+J9OolcumlGyogKCibEGIdIjGGPfcU+fprkXffFTnkkBA7y3PTr79u8Mbd64MPRMqVy9uAbOynqqTkbXq1Y0VAEVAE8oAA/sy77WYEOjegu+2mSkoepkG7VAQSgUDfviKDB5u4iNdeE9lss/ywNXKkSLduIqecIvLEE/kZg41ei4pEJk0SeeABkXPOsdFjqX2okpIBfhvg5HX2tXNFQBFQBMJA4MUXRZo2FWncWOSVV5webO2nCxYskOLiYpkzZ47MmjVL5s6dKwMHDpQKFSpIy5YtpV27dtK9e3dZtWqVLFq0SO68806pW7eu7LzzztK8eXPZbrvtnOf5fbdu3aRKlSpSqVIlGTRokCekbPHpaTD6kCIQdwRQSthHttxS5P33RQhezxetXm36//57Eeo/7b13vkYSXr/wtd9+InXqiMybZyxWeSQb+6laUvI4wdq1IqAIKALWETjjDJFHHxV56CGRDh2sKikur61atZLJkydL586dHaWjVq1a4v7MfWbChAny888/ywUXXCD77ruv1K9fXxo0aCAXXnihPPLII1KuXDlp3769dOnSRfr06SN1ENxlkA2hWtYY9PeKQCIQ+PVXkQMPFCG+LQK3+g6mN98scuWVToFaefDBRMC8ARPnnScydqzIv/8t0qNH3vmzsZ+qkpL3adYBKAKKgCJgCYGffhLZYQeRihVFFi0yf1u0pKQrKUVFRTJx4kTnx6n/Rjm56KKL5J577nGsJWvXrnWUkg4dOjhWk/Hjx0vjxo2lYcOGMnToUGnSpImjwKRT//79ZcCAARv8+O8wsgpZmj7tRhGIDAJnnSXyn/+InH66yLhx4cedeGGcwP2dd3ZqP8lnn+XXsuNlvH6e+fZbw89WWxnFsFIlP2+H8qwqKRlgtQFOKLOqjSoCioAikC8EbrtN5LLLRLp2FbnrrnWjsL2flmRJad26tUyaNElwCbvyyivllltucSwsqXTFFVfIeeedJx988ME6S0rXrl2ld+/eaknJ15rSfgsPgUceMVbYHXc0bl7VqkUHA+JjiJO56CKRUaOiM65cR4KFCEvRP8lOcm0uiPdtyA21pAQxU9qGIqAIKAJRRwALwkEHmYwwaRlwbAgb4FmxYoX07NlTpk6d6sSY9OjRw7GMEJPSokULJyalXr16ctBBB0m1atWkTZs2TjzK8OHDpXz58lKxYkW59dZbN4hJqVy5suMy5oVs8ellLPqMIhBLBL76yuwjy5eLTJ8ucuyx0WIDNzSsKcSofPmlqcYed4InFEKymM2fL1KzZiQ4srGfqpISianWQSgCioAiEDIC77wjcvjh5oAxe/YGndkQNiFz56n5QuHTExj6kCLgFwGqxBMoT9HECN3ob8QGY7v+epHLLxcZMcIvl9F7Hl7gKWLWIRv7qSop0VuOOiJFQBFQBIJHABcv3B9uv13kkktUSQkeYW1REUg2AmTR69dP5LDDTDFBaqBEkX780VhTICwPNWpEcZTexoRFiMK7P/xg4mx2393bexaeUiUlA8g2wLEwx9qFIqAIKALhI7Bypaku//vvJmA+zYe8UPbTQuEz/AWlPRQcArNmmSKCVH3/3/9E9tgj2hBgRbn11mhbfLwgOGaMsaD8618ijz/u5Q1rz9jYT9WSYm06tSNFQBFQBPKEAOmGKfzVvr3JyJNGNoRNnjjfoNtC4TMKWOsYEoTAsmXGTZR4lHvuETn//Ogz52bDIoMh1pSqVaM/5vQR/vWXqffy+ecib79t3HUjRDb2U1VSIjThOhRFQBFQBEJBoFEjkRkzRCjkePzxqqSEArI2qggkFIFzzzW1UNq1M9XcN9kkHoxigcASQcav3r3jMebUUT75pLGgHHecyMsvR278qqRkmBIb4ERuReiAFAFFQBHwiwC3cHvuKbLLLiJffCFSrpwqKX4x1OcVgUJFgMKvFIClvhKZAbfdNj5IkN2LvQ8rytdfi2y9dXzGTjbG+vVF/vtfkWnTRJo1i9zYbZzD1ZISuWnXASkCioAiECACvXqJDBsmQppe6geUQDaETYAcZd1UofCZNUD6oiKQigBFA6kqTwrcUqywkQeM6vMPP2xqjFxxReSHu26ApHfGgnLAASYGKILWKxv7qSop8VmyOlJFQBFQBPwhQMrQnXYSWbzY3CSSa7/QlRT808FESRFQBEpHgHgIXENffVWEQoI33hhPtD75RGTffU3iECwrFSrEg48WLUSmTjUK1llnRXLMqqRkmBYb4ERyVeigFAFFQBHwisCkSSJFRSLNm4s8+2ypbxXKfurwSYYi/Ls328wrivqcIlB4CGB9xQp78MEiZPYiq1dc6ZRTRCZMEBk5UqRLl+hzgVsdFizSKOOuG9FUzzbkhlpSor9cdYSKgCKgCGSHwMknizzzjAl2RVCXQjaETXYMBPuWwydNFheL9O8fbOPamiKQFAQo/NqwoTkcv/uuyTAVZ4IHartQb4RaIxE99K+D2HVRI4XypZdGFnkbckOVlMhOvw5MEVAEFIEcEPj+e5E6dUS22UaEdJzly6uSgpKy1VYiq1aJvPKKyLHH5gCwvqoIJBCBFSuM9YQb/LhYHrxMg+s+RZYy0rFHlXBH3W03kSpVRIgJYr+KKKmSkmFibIAT0XWhw1IEFAFFoGwEbrhB5NprTbAoQaO6n4ojNzikdOxoFLj33zdKnJIioAgYBDp3NrVQWrc2VtgIBmxnNVVvvCFy9NEi9eqJfPyxyKabZtVM6C+5RSj79RMZMCD07nLpwMY5XC0pucyQvqsIKAKKQBQRIH3lXnsZ1wYE8j77qJIinLc2kb/BxnWnaNtWhFoESTmIRXEt6pjigwBxG7iF1qwp8uGHIjVqxGfsXkbauLFJBPDYYyKnnurlDbvP/PSTSerBHoVFJeL4q5KiN392PxDtTRFQBJKBwGuvGVemBg1M0GsZZEPYlDUGG79fxycVtA85RGTevGS5tNgAUftIJgILF5p0tz//bLJKnXRS8vh84QWRE080QemzZ0fvcmLQIBEsKBdfLHLHHZHH34bcUEtK5JeBDlARUAQUAZ8IuBWi775b5IILynzZhrApcxAWHtiAT4qkHXmkyfLFv/fbz8IItAtFIIIIrF1rDu8vvSRy2WUit9wSwUEGMKTUAomTJ4u0bBlAowE1QZwcVhSURIruUnw34mRDbmStpCxYsECKi4tlzpw5MmvWLJk7d64MHDhQKlSoIC1btpR27dpJ06ZNZTcCgIRaYsOkatWq0rdvX1m+fLksXbpU7rrrLud33bp1kypVqkilSpVkEJqkB7IBjodh6COKgCKgCEQLAawE1ATAhWnRIpFKlcocX6HspxvxSe2Hq682dRTefltkyy3LxEofUAQShwAxa9RCQVFHYY9LLZFsJoI4G7Iekr2MOJWouHpyHsaCcsYZIuPGZcOZ9XdsyI2slRQXjVatWsnkyZOlc+fOjpJSq1YtcX/Wpk0b5/8oH0OHDpXFixfL4MGDZdSoUTJu3DjHN5g/5cqVk/bt20uXLl2kT58+UoeAxjLIBjhljUF/rwgoAopA5BAYM0bkootEOnUSufdeT8MrlP10Iz65QaaGzPPPm/oJZDNSUgQKCQGqmR9xhEi5ciKkHk66RZFvHnevjz4y9ZKo6p5vouguAf0Um3zvPZNdLQZkQ24EpqQUFRXJxIkTHVjdf69du9ZRQMaMGSPly5eXevXqyfTp06VXr14yc+ZMmTFjhqOkNG7cWBo2bOgoMk2aNJEG+FGnUf/+/WVAWqYDJwBSSRFQBBQBRWA9AvXrG6sAt4S4M3kgG8LGwzBCf6REPknVzKHlhx9MEH27dqGPQztQBCKBwMqVpn7InDkit90m0r17JIYV+iDGjxdp316kSRPj4pZvevRRY0Fp2tRcmMSEbMiNwJSUVEtK69atZRKVjv8hlJf58+dL27ZtZciQITJy5MgSLSldu3aV3r17e7ekFNJHFZNFq8NUBBSBPCJARh6CX8ns9cknnl0ZbAibPKKyrutS+Zw2zVhUqlY1aYnxDVdSBJKOAO5FuBkRJP/ss573i9jD8tdfpkAltWBILFLCxbg1HrlsR1HEgkJg/wknWOs6145syI2slZQVK1ZIz549ZerUqdK8eXPp0aOHE09CTEqLFi2cmJQOHTpI5cqVZcmSJTJ69GipVq2a9OvXT5YtW1ZiTArP4jLmhRxw8CXEd+/00728os8oAoqAIpBsBNwc+8Ra4GPukWwIG49DCfWxjHyCF7751FKg0CMB9UqKQFIR4CK5qMikuf3gA5Htt08qpyXzdd99IuefL9KqlUjKpbp1EF580VhQyDaIu11UYmQ8AGFDbmStpHgYf6iPOODgQ0lBHtLlHX98qP1p44qAIqAIRBqB338X2WEHEQLnSSe63Xaeh2tD2HgeTIgPZuTzjz+Me9y774oUF4v07x/iSLRpRSCPCODiuP/+IkuWmAM6B/VCI7733XcXWbBAhLgcXD7zQWRVw4KCC1rMLtxtyI14KykEiF54ocleM3260USVFAFFQBEoRAQoUIaQo0AhRdl8kA1h42M4oT1aJp+4fyBH8NXHmkKtGSVFIEkIEDjeooXIc8+RWlXkzjuTxJ0/XqhFQhzOaaeJEBdim3DxOvRQkV13FZk7N3bW2zL30wDwjLeSgi+fW/yGW8OZM0X+SXkcADbahCKgCCgC8UGgWTMTdJlF/n8bwiYKQHri86GHRM45R4Qsk8SnbLNNFIauY1AEgkGAWF5qoRCTgXtRIafdpjYJ9UhImkHyADJs2SSC97GgoCiiMMaMPO2nOfIUfyUFReWSS0zwFwoKGW1q1swRFn1dEVAEFIEYITB/vhG2uHt9/bXvGzkbwiYKaHrm8+yzRR5+2FilyPgVIz/xKOCsY4goAiTWOPxwEawpZAA86KCIDtTisNxaSR07iowda6/jr74y7mbbbivC/l2xor2+A+rJ836aQ3/xV1JgnkwNuDkgTDDV4/rloYBZDrjpq4qAIqAIRAcB0rMTQ9G7t8jgwb7HZUPY+B5UCC945pO4HmTJvHmmdgo1VJQUgTgjsHq1UVCoD3LTTSI9e8aZm+DGvny5yM47m1g+Kr3XrRtc25la4nIdCwrJovr2tdNnwL143k9z6DcZSgoA8AGSRu/VV00KtylTRMqXzwEafVURUAQUgRggwCUNPs3ffGMO1fzbJ9kQNj6HFMrjvvik8jaB9GT54t9JL3IXCuLaaGQQcDP/cT4iHoXEQ0oGAfeSp2tX45UTNv34o1GMsNCyb2NNiSH52k+z5C85SgoALF0q0qiR8SOmMM4jj+iHmOXC0NcUAUUgJggQh0I8CpWTqaCcBdkQNlkMK/BXfPPpuoLsu69xjylk//3AZ0MbtIaAWweI+CpcvnALVVqPwM8/G6VhzRoR3LBq1QoXHbIHYkEhNuiWW8LtK8TWfe+nWYwlWUoKACxaZG6/8MtmAYwYof7EWSwMfUURUARiggCurmT2IobirLOyGrQNYZPVwAJ+yTef+O5T5BFFEJcvXL+UFIE4IcCtPemGFy82Wf+Is1LaGIFrrhEZPty4weEOFxatWGGKxXKpjuUb5Sim5Hs/zYLP5CkpgPDZZyJHHWVygA8bJsLiU1IEFAFFIGkI/PSTuRUl6JILmiyDL20IG6BfsGCBFBcXy5w5c2TWrFkyd+5cp4AvRYBbtmzpFAGeMGGCTJkyRVavXu0U/61Xr5707dtXli9fXmIR4EqVKjmFhL1QVnxSU4IaCmQAIu6xXTsvXekzikD+ESCxEAUbyfjXubMIZRuUSkYAJY54FGrvccldvXo4SLnZ1Tp0ECGTYIwpq/3UJ7/JVFIAAdN8kyYiaK333y9y7rk+odHHFQFFQBGIOAK33iqCr3mO9Q5sCJtUJFu1aiWTJ0+Wzp07O0pKrVq1xCBHYe4AACAASURBVP2Z+/eiRYschQZFZfDgwTJq1CgZN26c/P33386fcuXKSfv27aVLly7Sp08fqUPK4DIoaz5dd5mqVY07MTehSopA1BHA8sfesOeeItTk2GqrqI84v+O79FKR228X6dPHlLcImnAnI6MXcSjsIwccEHQPVtvLej/1McrkKimAQHAYlVS5TXjmGZGWLX1Ao48qAoqAIhBhBNjXuOHHx5wq6TkUs7UhbEpSUoqKimTixInOr9x/p/+sV69eMn36dOHvmTNnyowZMxwlpXHjxtKwYUMZOnSoNGnSRBo0aLDRZPXv318GEBSbQrybFV15pcjNN4scfbQp9EhAvZIiEFUEqPvBnvDnnyKzZokcdlhURxqdcVF9nlIWxJ6RFrhKlWDHRpw0FhRcSJ99Nti289CaDbmRbCWFScNPm5z3uEEQVFqCIMvD3GqXioAioAjkhgAZp444QuTgg80taQ5kQ9iUpKSkWlJat24tkyZNWmdRSbWkDBkyREaOHPl/9s4E7KppjeOvriZUQkgZQ3SNl6syJmOzMt0SEVEZk6FP86gMZW4QmctQaJBZQuG6MieZkkrkUomI3Oe3l/3d0+l839nnnL3XHs77Pk9PX317r+G/1l7veueMlpRu3bpJ7969g7WkMPjffjPxjgiEBL6S8llJEYgiAr/+au4677wjcu21Ir16RXGU0RzTeeeJ3HWXyLBhIiUl/o0R5Qh1ad57zyg5mjTxr+2QWrLBN5IvpLB4aL/QgpHZ4tVXTaVVJUVAEVAE4owAgdxjx4rcdpvIhRcWNBMbzIYBrlmzRnr27CkzZ86UZs2aSY8ePZx4EmJSmjdv7sSkTJ482fk9MSnEohCTgsvXqlWrMsakVK9e3XEZ80IFz3PhQqOd/vlnc9E48kgv3eozioBdBK680gR/k+30hRdMnIWSNwSolULledICE5viV0Y/12UUxdLrrycioVPB56mHFSkOIQUg3I92xx1F5swR8eC/7AE/fUQRUAQUAfsIEGtHmky0+wTM16xZ0BhsMJuCBujTy77Mk2DXs84yPAS/cpRfSopAVBB4/nmR444TIX4KrT13HqXcEOjQQWTiRJMemCyxfhAx0ig2HntM5OST/Wgx9DZ8OU+zzKJ4hBRSSXbqZNy/yHn/yisFM/bQd4gOQBFQBIoTgXvvNclAYKb4ORdINphNgUP05XXf5okLMbyEdK5k/KIom5IiEDYCZPsjGHvpUpGHHxY57bSwRxTP/j/4wKRtrlPHpAmuXLmwebiuuXvsIUKsUEIsW76dp+WgWzxCCiCQWYF0fJjdCH4k932eKTsL27H6tiKgCCgCBSCAmxGKFlw50NAVSDaYTYFD9OV13+a5erWJBeICQ4VqKlUrKQJhI3DOOSL33GMUGGQ1VcofARQQTzxhXGrPPz//dnjz1FONBcWPtgobia9v+3aeqpCSgsBPPxmmjmR70kkijz6qWVp83bbamCKgCASKAHWg8JnedVcR/KcrVCi4OxvMpuBB+tCAr/N86y2Rxo2NVhR+guZVSREICwESOpDBq1YtEWKn/M5MFda8wuqX7/uf/xTZbTeRBQvyvydyRpMCetttTYxLlSphzcj3fn09T8sYXXFZUlwQqMBKsUc+ZAocId2qud73DawNJhyBH380WaW4nMEYlewgQKaeESNMHn/y+ftANpiND8MsuAnf50lwMvGOuBBTm8uvINuCZ6oNFBUCZI4iSB7rasK09aGu4wknGI8b4tBIHZwPuQlO/M4Wls9YfH7H9/M0w/iKU0gBCCRa0kkSdNqvn0haLn2f11KbUwSShcC0acYETjVuaJ99TEpF/sAsg6rWmywUc58NNQ8IhKX6OXn8fUoAYoPZ5D5Z/9/wfZ7EOlLzgIsMlxGK5ylFAwHiM0hqUAwKSFyJcCkiHgXFUUJiHkLfSLNnG37WoIGpR5Wr1Zoq9jvvLFKxoingWGCCk9DxSBuA7+epCilpCJD54ogjRFatUr/iqO1+HU80EVi50lQ4x+8ZIovMF18Yt6NUwrriCi3ET6jQ4s96UviwTRuR5s1FZszwp03hHreJUyAx6RTIPBHUKaqJ4EgQfbt2SYcx+vMjsUTnziIXXSRy883RH28hI1y71pRVQPHqU4xaIcNJ3LvcESldkc+33bu3qbfSs6dJCZ0wCuQ8TReE/owpZ/INnJdfFsGkRyrPRx4ROeWUhG0jnY4i4BMCaIvPPVfk669N+ts77xRp0cI0TqVevqVZs8wfAoozCS1HH21qS5CDXil3BBBQEFTyYZjl9ObbeZr7jKy+Edg8n3lG5MQTTdpX0hLvtJPVeWlnKQhQYoBzBp4Ovfaa8ZpIKg0fbooOcjYQ6K3kLwJufRPqIxGn4tUyR3INzgHSxX/+uW9Wb38nV1hrgZ2nKcMqXnev1LWB4WMqxSQHs0lAJdDCtp6+rQikIMBhi989vs7QGWeI3HJL+fUhXKGFvPAILRzSqYRbQqqlRYWW7FsO11RcvXBhQVCsVCn7Ox6fsMFsPA4l0McCnadbi4vMkez7TTcNdC7aeAYEcKkh2BmrVqtWIrilYtUlqBz+njTCikdaWyrMf/ih+VnJXwSwMLOn2ENPPWXcO73QyJHGgpLgTGuBnqd/YaxCirvZxowxaSSrVxfBDxHzvZIiUOwIIGCQ1hJXAoLjEVRIzZgrcXlItbSkCi1optKFFi2QtzHCrsY0ANcBG8wm1y0TxPOBzhPNPRp7LjP9+4sMGBDEFLTNshBAY42A+M47hpfffruxqHDu4GrDd5M0Ou88kbvuSqw7UWSW6/HHjRsnCZdITpDNmsJZUK+eUSYhPBLTkkAK9DxVISXDjoGxDBoksv32pio9KT6VFIFiRODnn40LARYTiAq5BAX7lcWLoO9UoYW4FpdShRYuGfgEF7vQgjaPtMNkJPzoI+OD7iPZYDY+DjfvpgKfJ+uDWwjfD9YUXBuVgkeABAYULsQrgjMDjwgsJxTOQ+GI1ZHvJkluePPmiRx0kHGdZd/haqgUDALsLxRpCBwo7gimL4/cYrtY83DPTSgFfp4SL1n0MSmpm4eLABlaxo0zZlN8Wf26lCV0k+q0EogAAjomahgfwgEaydNPz649KgQKhBY3noW/sdykCi1cNFz3MGpTkHO+mMjNMsPcWR+fyQaz8XnIeTVnZZ6kKz3rLOODTnxKsQvYea1Uji9htSJDJ9rrN97YMObtmmtErr3W1EVDI54E4q7iWom0mKidFX3wQZOGmGQxxGeWRakCDVYXrHsJJRvnqQop6ZuHFJ/EpxCAhh/iiy+KbLFFQreYTksRSEGALDFYE3GN4KBt2dII7ATJ2yaEFCwtaKP5g7tYKhGbwffp/kGjmGRNYqdOIvfdJzJ+vEle4DPZYDY+Dzmv5qzN88wzRR54wFyMp0wJVsDPC4kEvURBZqwo1aqJvP76xq41WLWoY8OZ8uSTIq1bx3/y7Cms28wL9zaNfwp+TbkbYs3GVZmaSPCeTDR9uomHQqGEojuba1jwIw+sBxvnqQopmZbvl19Mxi+kYP7GXOdjkGpgO0YbVgTyRYCsJVyEcYkgLou0nfw7KgcsFwwsLAguVPdmnOkpc7F+ukILlZcPPFBk883zRSQ675H2GUGR2gcEzwegNLHBbKIAqLV5kmwCty9Sc6umO7ilx+WJOAEULATJu9kG03sk4Jnf4e7F2RHnc4EgeWIcuCyj0Uezr2QHATJaUh+svExquHhyd0TRzXMJJhvnqQopZW2gH34w/sQffGBMfPgY5lrIJ8GbU6eWEAQI8BsyxORy/+MPw/AIxMRSEWX66SdTtAyBBQGLv9PTHvO9omlEcEFo4W/8iuOmcCBZAW6oWFCwpARANphNAMPOuUmr82Rfok1FuGR/kmVKyT8EKJTHN00mwREjRK66qvy2KS9AzArP8Xxc6frrzRywdCOYKdlDAAERl8IlS0Sos5f+Tc+da5Jn7LWXiV9J+J3RxnmqQkp525uNyIbD1eTyy40bTFQ0y/Y+S+0pqQhwyGItwV0AzeKNNxotUVz3+H//awQWV2jhYsg3nEoIKMS3uEILlxyC0KNcoZkxMidiUbj0BkA2mE0Aw865SevzhGeQmhhhGReRzTbLecz6QgYEuCwSk8GlENc6lIjZzi0yLfGtY3VBwRFHoRHBDIsx3h4oUHE/UrKLAMlkLr1U5F//Epk4ccO+yXyJBQVFH8VEE042zlMVUrJtoo8/NuZkLkAdOpgCdsposqGmv48yAvjWokkk0HTdOpOpZMKEZGazwz0qVWhBcPn++w1Xh+8Z15zUGBe0ZdkuPTbWGEESoYrLFZq5gMZkg9nYgCtbH9bnSWwXdRVwy7ngAhFS3SsVhgBunlwA77lHpGFD4wZapYq3Nm+6SaRHD8PTSUYRN003e4g4wcsuExk1ytuc9Sl/ESDGaZddDB/hfujWpuFn3PBwzcUVr3Jlf/uNYGs2zlMVUrwsPBlaCLbDonLAAUZS3nlnL2/qM4pAtBAgJSfWEy7rVauKUHvjoovix6zzRZULDpnEmL/7h7oWxBCkEkH4rrUFjS1/wghORWOH5i7gOg82mE2+S+bne6HMk4J7CJoUGHzoIZH27f2cUvG15RbJq1PHfMO5JPZAQYMyAutxQEkoAlsQ7iEoUzibiHWqWTOwrrThLAi4NasQlrGaQG7NmuuuM9bTIiAb56kKKV430nffmQwiaG222UbkkUfMxUVJEYgDAsSboHnr08dUJ8ZtCE3knnvGYfTBjhFt9yef/F9owfJCQC5uIS6R8pisf5j4cQG1oYFlnXbYQWTVKuO2FmDaZRvMJthF9NZ6aPN84QUT74XVjv2Fz7pS7gjMnGliMdBSE5xMVr9ciRTFnH9c8tF+x6HMAMqVY44xmQ5vu03kwgtznbU+7ycCnMkoqomNJBYSBRZ19bDoocyuUcPP3iLblo3zNG8hZfHixdK/f3+ZP3++zJ07VxYsWCCDBg2SKlWqSIsWLaRdu3YyZcoUmTFjhqxdu1b69esn9evXl759+8rq1atl5cqVcgdZT0Ske/fuUqNGDalWrZoMHjzY04LYAGejgeAag4RM5iN82NHoXHxxYC4YnoDQhxSBbAigdaPuCekQickgUJ4YqyjHYWSbU9C/51vHvYoLDWlLcddB0INIKoCwwh8yiAXkgiUPP2z6oNIxAb8BUijnaYDzKavpUOcJb+vXz8SnsK/inGEqhLVzCjM2amSE9kmTTO2mfKl7d1OclnMRV9eoE2cQ6axx+8QFNAyrbtQxsj0+vmW+aTwRUD5gQbn6auOdUCRk4zzNW0hx16Bly5Yyffp06dKliyOk1K5dW9z/c/9etmyZI9AgqAwZMkTGjBkjEydOlD///NP5U6FCBWnfvr107dpV+vTpI3UpgpWFbIBT5hDQQJNtB00nrjP4GXv1ic02Mf29IuAXAlgIUARwcOJHi9aRAFMuSUq5IbBihchjj5nLEb7sbvpjLFEIErjw+K0dP/54keeeE5kxQ6R589zGm+PToZ6nOY61kMdDnWdqfArFHuEjQQm4hYAUxXeJCSX+BIUL1mCPyswyp/LjjyboHBc8LxXEw8SEDIyc2cwdS9KJJ4Y5Gu3bRYCYFKwpuBCi/OM++MUXxvpdJGTjPPVNSGndurVMpZ6IEL5hfk7/v5KSEpk1a5bw95w5c2T27NmOkNKkSRNp3LixDBs2TJo2bSqN0JZEWUhhbPjCkskBNwx81ymuFPW0rdlA1d8nBwHqiuAvi3sAWje0Pr16iVSsmJw5hjUTvnncPcnswjngEnEHCCtoeAmsLISIm8F9AIbHzwFbvWwwm0Lg8Ovd0OeJ2zDWN/ZQ3GIi/FqEXNvhEkjygeefNzwXZYEf7pbEB51xhrFOEKMS1dTkbgwOGFDvRSk6COBZQ7wgFGCK+OhMeMOR2DhPfRNSUi0prVq1kmnTppVaVFItKUOHDpXRo0dntKR069ZNevfundGSMmDAABlINqIUQsAJlUgHSO71V181/uK4ZBx+eKhD0s6LHAG+CS4/uHPhL0tdEKwnJHxQ8h8BtJtYVxBYKBLnEj7vCCzEsWy/fe79Dhhgsq/5oTX20LsNZuNhGIE/Eol5kkqajHooD6iQjnCrVDYCl1wicuut5izDZdWvYqaclcQJES9EnaiSkuitAkIt2aM4y99/3whUStFBgOyRKJOwduGOWGQpoW2cp3kLKWvWrJGePXvKzJkzpVmzZtKjRw8nnoSYlObNmzsxKZMnT3Z+T0wKsSjEpODytWrVqowxKdWrV3dcxryQDXC8jMPZnKQDxL8VpkMmHlzB1IzvCT59yEcE0M6SYeTpp43mHcsJFpSoagh9nHokmuIS4QosmP0hNL4k2EBgIbbES0YeYl9gfBSpIyhzt90Cn15kztOAZxqZeVKT6IorRHbf3QTSF0mgbc7L61b4JlkNVstCLZTpAyBhBvVS+E6JQbPwreWEgRs7Q+wrdwul6CGAOy7ZIXH7LTKycZ7mLaSEvRY2wMlpjhymZNwg4JaLIhk4iiBPdk4Y6cPBIUBabNy7fvjBaNuwnpBqU8k+AmhoKdyHwELwO9o2CFc7/MlhZqQ0L0sj/Mwz5rmmTY2W1wJF7jwNaM6RmSd7BKGV7xZrPO6DqtjacNVfflnk2GMNLnwHRxwRzK5wrZa4U3HhjMo6UKwRKxsC7MKFIltvHcz8tVVFIE8EbJynKqTkuTgZX6P67cknm0sJcTW4fxVREJWfUGpbHhEgTe5VVxl3CIhCZbguaCIHjwAG/BhWEVKl4g6GLz0BwBA1alq1MhYWLkepCg1SnT/6qMiDD5oCshbIBrOxMI2sXURqngRvU/cCqxsZI3FrUjIIgAlKFoKTg47d4QzFmoLrJt8oPDxsQoglcQZxOLo3wl4N7b8MBGycpyqk+L39li41GjJSTFJkCkEF/3QlRcBvBBYsMFp5gj5xh8B6EnAWKL+nUFTt4RrKpQOBBQ06fuYQmlICghFY8LvfaSeTnpazBGHGAtlgNhamkbWLyM2TQqLU3eFSijBLBqtiJ1xnwARLAsVMqRIfNJFFD6EApSK1U6pVC7rH8tufPt0oMYhxwI1UE56Eux7ae0YEbJynKqQEsflIRYcv6d13m8OFNLC4gCkpAn4hcN99Zo+tWSPSpInIAw+IUIFZKR4IkBKaTD0ILLiYcGZAWFT4GddRXEYtkQ1mU9ZUqLFF6nnS15N+vlatWvLGG2/Izz//LJ999pm89tprctxxx0m9evWcJoYPHy5bbrnlRjW3qnoQ6MKcZ5lLSQr7bt2McPr228Xt1kOaZpR81AUhqJ1vxFZNEKyWfI/EmFL4NixCmYFlh3gZC+nHw5qm9ht/BGycpyqkBLVP0IwRTI8miBSKXCg5+DSIOSjEi6NdtO/spfvvN8Ge+FNfc03gKWqLA9yQZrlypbmUcUFCowtxWcWqYolsMJuypjJq1Chp0KCBnHDCCdKpUycnFX2dOnVk3LhxTiKWs846S9q0aeMIMRT85ffLly/fqOZWBw+ucWHOs8ylhFd07ChCSlwsodOm+ZNi19Le8bWb3r2Nuyr1h8h85iXRhF8D+OYbU+sISw7JDEgVHQZhOcJt94QTTF2UqMTIhIGF9hlpBGycpyqkBL0FMOETGEnRKNIT4/O63XZB96rtJxGBefNMDQ6CKCl4yqUmqGDSJOIXhzmRcpRYBdKOWiQbzKas6axYsUJIMV+5cmXBqkImyIYNG8qxxx4rM2bMcP5//fr1TtFfBJdKlSo5mSLTa271IptdFgpznuUODeUDMRi4GkU1HW42cAv9PUI6gibuj7hLh5HOFa8HrJisBTGmAdcn2ggyYnDI+Iag9O67Wni30D2l7weKgI3zVIWUQJfwr8ZJJYrPOf7HuOQ8/rhmXrKBe1L6QNOK6w8pS3EFIDMUroSa7SUpKxz6PGwwGy+TbNu2rdx5553y0UcfydNPP+1YTVKJIsGLFi0SnkuvuZXJkhLJ+lplAUEK3EMOESGQ+8UXTS2VYiHSCx95pDnfcPHCihAGkeiCGFLGg8CCG55NItUwZz3W8ttvt9mz9qUI5IyADb6hQkrOy5LnC7/8YuqnEEuA3/m4cSJnnZVnY/pa0SCAZo3UwlOnGlfB668XgZGpC0DRbAEbE7XBbMqax5IlS6R///6ybt06Oeqoo6Rz586CwDFixAjZcccdndc6duwo1NHC6jJ27FipWbPmRjW3YhuTkgoMbpzwBQqAYjnNpxCojQ3jZx8kiMBywd+4RBMTEibhasl4CJ7HsmVrDSgGi4snqcnJNEYyFCVFIMII2OAbKqTY3ABoxCnI1LOnCBob4lW4dGrmjmBXAdxfeknk1VdFWrY0aT/jQLgK4v7w9dfGBYCaG3EZexzw1TGWImCD2UQB7ljMs0sXk3aXIqDEKNl2ObK5UCjvsBhhuUAZw7yjoIBBUCL1L+cvqcBtEKnIKcQ7cqSJSVFSBCKOgI3zVIWUMDYBpnxqIaAlhxFx+axVK4yRJLtPMsWQ6nX4cMMEXTrsMFOTABe8KAqICLDXXivSv78IczjjDJOEIey0mMneLUU9OxvMJgoAx2KeXNxJwUtq8T59RAYPjgJ0/o8hNWEAZzIFG6NSAHnVKlMUF+sOgiJFJYMkAuRJmkAsGqmXNcFOkGhr2z4hYOM8VSHFp8XKuZkvvxQ56SQTHLfzziZOJaxsIjkPPuIv4NdMSt7rrhOhlghE5V6EEoIz3f8j+BzfXzSXUTGtwxTJ9IPlZ7PNjF807h9R0C5GfNl1ePkjYIPZ5D86/96MzTxx98FqSgA1F9gTT/QPhKi0hPKopMSkXkaJtO22URmZGQdJbk491QgO770XXIHcdeuMmxeuZbj1Uh9FSRGIAQI2zlMVUsLcCNRKOPdckUmTTNG2u+4yBd2U8kMAhn7nncZcvmSJaQNXArL+EIjJRR/LBJox3O4I0ITQ3mGtwLqCMBMWcRlBIFmxwowDC1sYGW7Cmr/2GxoCNphNaJNL6ThW86QQMJkhSZBBfMpf8TlRwLHgMZBmuU0bw/dee03kgAMKbtL3BrD0tGhhhMSBA0X69fO9C6fBW281vAdrzbPPqkIqGJS11QAQsHGeqpASwMLl1CQH4Y03ilx9tblAk8EJVx9bBaxyGmxEHyZtKwc9WVF++MEMEgYIpmRqKYsolkUGlQkTjMYSQqiBYZBBy9YaYPmh1gn7ACIF5g03BKe5i+gy6rDCQ8AGswlvdv/vOXbzdGMjGjUSefnlZLgB4c7EuUzaZQQxijdGlT7/3KQBhk9T+d3v1OD//a+JN6RWEu59FHFUUgRigoCN81SFlKhsBjQo//qXuWRTaRfrylZbRWV00RzHokXmYk+wJX7cCBVYRK66SqRBA+9jxv/4nnuMoIObBYQLHsIClq4g1wEmyLrj7rDllia1MG5pSoqARQRsMBuL0ymzq9jNEwUGqXmpG0IwNVbiOBNWYtIsf/FFsNYJPzEiDTZFJuHLzzzjr6WD5DlY9cn8SdyhkiIQIwRsnKcqpERpQ3z2mYlTQdO0224mfoIDXWlDBMBnxAiDD0HmxG6cf75h4vg350tYsjDtwzQQGiHcEXDBIu0vGjU/CXcuxo2QRKAsxRkRjpQUAcsI2GA2lqeUsbtYzvOrr0y8Ilr3qFseyltkBK7jjzcWIRLHoIiLQ6wd48Ydbf58w3NQKvlBxKBgOYF/oRzT5Dl+oKptWETAxnmqQorFBfXUFSbws882zKhCBZOuGH9YLsvFTvguE2w5fbpBAgsHrlkXXeR/YUMYEpaVe+8VIXYIOuYY0x9+yoWkBaU9NGhuuk2CR1ljW+5lxb6PdP4bIWCD2UQB9tjO083+VL26KQqMi1CcCHcpCiOOHWsSApBenct5XAjBqkkTUzMF3oDVu1AiHf6MGaYMAW7eSopAzBCwcZ6qkBLFTcGBzgUWAYVYiT33NG5ApGksNgILAtwRTqhzAhFACjbnnSey+ebBIvLjjwZ74l1wUYCwciEYnXNO7swKK9Dpp4tQuAuGR/G2oNNbBouQtp4ABGwwmyjAFOt54nKE6xFa/blz4xWzRuwfZ+Z22xnX1jgmAUB5iNIKN2D4QSGE2xgZ2+rVE/nww+ikXi5kTvpu0SFg4zxVISXK22rxYpELLjAuSJjF0eIPHRr8xTwKmPz+u8luhVsXAYsQeesJhicDmu088riVYcHBFYw6NxACUqdOxhVsr73KRw1hi8xjWFDWrjXZxmB4MG0lRSBkBGwwm5Cn6HQf63lyJqLQQKuPmyhWiTgQ9U8477A+M3aSAMSRSNBCtkUUV8QIUZU+H2Idyd6IoorSA7h4KykCMUTAxnmqQkrUNwaX2/vuEyHLC4cjWny3GnHUx57P+HCFItsW2a2oJQPB1EgjTP54XODCJqwhCCvUYiFgH4IJI0SiHUsfI+vGpeLRR41LF9pQLEFRmEvYWGr/kUDABrOJwkRjP89ly0x8yvLlxgpLTaUoE7EWxFWSEAalDPF9cSZ4L3W1WIM338zPRZfaV1hjKOSMABeHuJw4r5mOPTAEbJynKqQEtnw+Nwxzwqf3ySdNw2QDoVhhUqqQw8RwCeDyj8YKatbMCCdHHBHNg/z7701tG0z/WL0gUlRiWcHCgv84GjcCLRG4dtnFBF7GVZPo85bW5qKDgA1mE4XZJmKeFHrFolKlinGdyiWToa1FIAkJLk0o10j1TswFsRdxJ+YFP5ozR+Tmm41iKheCz8EjSIJA7Zsw63LlMm59VhHIgICN81SFlDhtPawquEDh28sFmUxW48YZLX5ciaKLo0YZ1wWSBmBdIGaDNMJRLPCVCWfM9wiPCFizZ5snEB6xqmDO5/cUZcPdy4+Ay7iutY47sgjYYDZRmHxi5onbb58+xgUWjf4WW0QBXmNZxsJz000mwBzCAs45WEiykWjMzowC92MsKQT+M8c6dbyPym6opgAAIABJREFU7vLLDb/DGgPvVlIEYoyAjfNUhZQ4bpBvvzXa+kceMaPv3NnUC4nTBZjDnTHjyrZunQkcZB5o3HBpiytRkIusYA8+KPLrr0bbCcPG3UvN+nFd1cSP2waziQKIiZknGn2yQxGvSG0oBIMwz5dvvhHBjYlaH9RCgQ4/3KSFp7BuUgQUdxOjRMMydOqp/+fD2TY4FiXS2JOpc+FCjUfMhpf+PvII2DhPVUiJ/DYoZ4BTpoh07278k3fYwVgjYFxRJbRspFZGg0QKSgiXKPxzCShPUhA5LmuPPWYq2EfRHSOqe0THFQoCNphNKBNL6zRR88SajkYfV1POfhQhtum994xlgBpP1BNBGOHijnCS5Bpfa9aYc50aNmSfxDU5G7VuLTJtmkkGg5CjpAjEHAEb56kKKTHfJI7bFwwBTRqEVg1f2a23js7MSLGIqxNWE3xyIVIvEleD2btGjeiMVUeiCBQhAjaYTRRgTdw8SUVMRXqEA+IkqEESNGHFefppkZEjTeA3xBmOkIQrciEFdYMeu5/tT51qrES77mrSCJdXy+z5503FerwEyOqF54CSIhBzBGycpyqkxHyTlA6f9LikK166VGTbbY3p/eSTw5sdVhOyWWE1oQgjVLGiSLt2hplRGEuzW4W3PtqzIpCCgA1mEwXAEzlP3ElRVHEBptBjUG6/ZF5EGYblZMECs5z0iRWcmlFJSeKSy0YlfTDxiNSwGTIk85vEJGLxIisk1vUw+XIuc9NnFYEsCNg4T1VISdI2JNUtMR1knIII1iZjFkKLLSKoEKsJzIzxQGQzQTAh41WtWrZGov0oAoqARwRsMBuPQwn0sUTOk4QqnPW4/7Zta1xq/YxPIbMkfGTMGJOwBSLehCBwXJiSFm+Syw7E3YvkBcRVvvuu+TmdcMXDawCL16xZ/q5NLmPVZxUBnxGwcZ6qkOLzokWiueeeM9XYOUBx+yLrFAUQ/WRcqRNFw0YQP1YT3A8gii2iMUI4IS4jqL4jAbgOQhGINwI2mE0UEErsPFeuFDnoIJHPPjNuWFhWCiUu3W68CZdwhJHTTjNt51vIsNAxRfF9AuiJMYHPkR46ldexLrvvboS7t96y444XRYx0TIlEwMZ5qkJKIreOiKxebWqM4PYFofEi8woB9n4RTMy1mqxaZVqlIi+CCUW7ttnGr560HUVAEQgQARvMJsDhe2460fMksyA1mP74w1R2P/RQz7iUPki8CRnDEHRefNH8N/EmuBITb7Ljjrm3mfQ3EOCIBcKdK71g5ZVXmsLEZK50PRySjofOr2gQsHGeqpCS9O0Eszr3XKNhw1cZzRhuV/laNshqQq0WrCYUKoQIAsTdAOEkqoUXk77OOj9FoAAEbDCbAobn26uJnydKI87hunVNsUCviiKs4SQ2Ib4lNd6EYozEm0SlDotvO8Hnhoi7xAUOvMFvq61EPv3UZACDP5J+uHZtnzvV5hSBcBGwcZ6qkBLuGtvpHQZE4S8YEP7LFBnETzaXLCwwPAQT6n9gpYHwv4UhnnlmtLKJ2UFVe1EEEoOADWYTBbASP0/Od6zYDzxgivySHre8BCVuvAlWdqqgQyiaiDehCGMxx5vkumHJVDl+/P8LNRIf9MQTIsOGiZSU5NqaPq8IRB4BG+epCimR3wY+DpB4EczOH39sMrHgS1tekUGEkUmTjHCCPy2EVgi/ZN477LD8LTI+TkubUgQUgcIQsMFsChuhP28XxTyxdlOjhFS3gwcbBVU64RqGVX3iRBP0jTBy+ukm3uTgg/0Bu9haIe5kr71MMUsyfYH7zjsbfktRXyVFIGEI2DhPVUhJ2KbJOp21a0UGDhS57joR/I+bNjVxJalV3kljiWBCga6ffjJNYrbGL7ljR2PKVlIEFIHEIGCD2UQBrGKZp8yfb4QNznsSqXDOc95jWSHehABvSONN/N2WxKScffb/2yShDMUtlRSBBCJg4zxVISWBG8fTlLCM4GtMsN9mmxmTNNoehJO33zZN8G+0a1hNGjdWq4knYPUhRSB+CNhgNlFApVjm6WCNay5KJVLQ426ESxexERDFdIk34UKt8Sb+bU3c7Y4+2iQuIEZl9mzlm/6hqy1FDAEb56mvQsqCBQukT58+Urt2balbt678/PPP8v7770utWrWkc+fOcsghh8iUKVNkxowZsnbtWunXr5/Ur19f+vbtK6tXr5aVK1fKHXfcIVXLq9z61yLZACdi+8H/4fz2m8jQoUZAoeCUS/vsY6wmVK+vWdP/frVFRUARiBQCxXKeFss8SzcX9TmIP3SJWh24dGm8SXDf3xdfiPTta/6Q7VJJEUgoAjbOU1+FlFGjRkmDBg3khBNOkE6dOsluu+0mn3zyiSN0DBw4UOrUqSMtW7aU6dOny7Jly6R///6OoDJkyBAZM2aMTJw4Uf7880/p0KFD1iW1AU7WQSTlAVIJDxpkTP9YTRo2VO1PUtZW56EIeECgWM7TYpln6ZLj7kUc4qabilxyicabePgW9BFFQBHwhoCN89RXIWXFihUyYMAAqVy5smBVwULSsGFD5+fhw4fLhAkTpHXr1jJ16lQHAX4uKSmRWbNmOX/PmTNHZs+eLb2o75FGtIugk0oINEqKgCKgCCgChSFgg9kUNkJ/3i6WefqDlraiCCgCikDZCNg4T30VUlKn0rZtW7nzzjtlm222kR9++EHOP/98efTRRzNaUoYOHSqjR49WS4p+DYqAIqAIhICADWZT1rTUTTiEBdcuFQFFQBEoEAEbfMNXIWXJkiWOC9e6devkqKOOEv69dOlS+e677xzryMEHHyyTJ0+WmTNnOjEpWFqIScHla9WqVRqTUuCG0dcVAUVAEcgHARvMpqxxqZtwPium7ygCioAiEC4CNviGr0KKTbhsgGNzPtqXIqAIKAJhIRDmeapuwmGtuvarCCgCikD+CNjgG7EWUvKHVt9UBBQBRUARSEUgCjF+NtyEddUVAUVAEVAE/EEgaL4RayElaHBSl7BJkyZOgL8tsiGhps8l6XO0PT/wtb2Otudoe35gmvQ52p5fGPs09ewpFjfhMNbVxTmM79TtW+dt69Zg+tG1tot3GDwpdYZJX28VUjzu53vuuUfOTq0k6/G9fB8LY+MlfY625xcGw7A9R92n+X7hZb9new3D2Kf+o+atxTD2qzuyMNY1CkKKztvb3vTrKd3jfiHpvR3d496xyvVJFVJyRczS82EeNJamGKrGR+foDwK6T/3BMexWimEdi0kYS99PxbK+Ou9wLSlhnmO6x8NEP7i+YyukUDeFP0mlpM+PddM5xn/36hrGfw2L5Vsspnmm78pi+E4zfYnFOO9inLN+28m9C8dWSEnG1UBnoQgoAoqAIqAIKAKKgCKgCCgCG1lD/7QZfa74KwKKgCKgCCgCioAioAgoAoqAIpAFAbWk6BZRBBQBRUARUAQUAUVAEVAEFIFIIaBCSqSWQwejCCgCioAioAgoAoqAIqAIKAKRFFKef/55mTRpkvz000+yzz77yKmnniqDBg2SKlWqSIsWLaRdu3YyZcoUmTFjhqxdu1b69esne+yxh3Tu3FmqVq0q3377rdx6662yww47RHaFvcyROTz66KNyySWXyCmnnOLMpW/fvrJ69WpZuXKl3HHHHc58o0j5zG/p0qVyzTXXONP5/fffZcKECVKxYsUoTs8ZUz5zdCczePBgeeONN2T69OmJm9/EiRNlzpw5TvY2vs1tttkmUXNcv3594s6aiy++WH755RdZtmyZ3H777bLLLrvE5qxxN5eX7zHufCPTh+Rl3nHmJWUdHvnMO248Jn3u+cw5TjzHz7WmrTjxIr++7bjxp2yXg0gKKamDbtasmdStW9cRUmrXri0tW7Z0Lnbu3zDV/v37y3XXXSc9evRwLrbjxo2T7bbbTtq0aZNt/pH4fVlzZHDk395iiy0cIeXrr7+WIUOGyJgxY5yPj3CiDh06RGIO5Q3C6/xS20Aw48/uu+8e+fkxwFzm+Oyzz8r3338vDz74YKSFFC/fYfoeXbFihXTs2FH2339/R8Dk24yyoJnPHH/88cdEnjVgwSX+v//9r5x44omxPGvc9SwGvpHpYPR6DsWVl5TFDLzOO848Jn3uucw5jjyn0LWOMy8q5NuOM3/KNO9ICyl33XWX/Prrr/L000/L1KlTnfG3bt3a+dn92/2/J598Urp16+Zc5NesWSPTpk1zLvdRp/LmmH4BnDt3rlP1vqSkxNFUz549W3r16hXpKeYyP3ci8+bNc6xEd955Z6Tn5g4ulzl+9913MmzYMBk1alSpoB31SeYyP6xDKBSwciKErVu3zmoR1HyxzGWOKAeSeNYgnFxwwQUyfvx4+eijj2J31nj5HpPCNzLt81z2cBx5SVnfdi7zjiuPSZ97LnOOI8/xY63jyosK/bbjyp/KWvPICikjR46USpUqyUUXXSRdunQptaS0atXKEUDSLSkwV1yjhg8fLjNnzpRPPvlELr300nzvLFbeyzbHdCEFAWzo0KEyevToWFhScp0f833ppZfk4Ycfdtz14qCBz3WOjzzyiDzzzDNSrVo1R9geO3asHHfccVb2Wz6d5Dq/JUuWOC579957r6Nc4DvEIhZlynWO//nPfxJ31ixevFiuuOIKuemmmxyLddzOGnd/ZVvLJPCNTN9StnnHnZeUdX7kOu848pj0uec657jxHL/WOo68yI9vO478qbz7QSSFFFyZiL049thj5W9/+5tzycGHn5iU5s2bOzEpkydPdoQRYlJ4dqeddpJzzz1XatasKfid8jzxLFElL3Pkso5rF5d1hLCTTz7Z8fFftWpV5GNS8pnfQQcdJPzBtY14hiuvvFLq1asX1SV0BMVs+zTTGroTci9MUZ1gvvPDkvLDDz+UxoZttdVWUZ1iXmvIGZS0s6Z+/fpywAEHOOcnbrK4ksTlrHE3l5f9Gne+kelD8jLvOPOSsg6PfOYdNx6TPvd85sy9IS48x8+1Zt5x4kV+fdtx40/ZLgeRFFKyDVp/rwgoAoqAIqAIKAKKgCKgCCgCyUVAhZTkrq3OTBFQBBQBRUARUAQUAUVAEYglAiqkxHLZdNCKgCKgCCgCioAioAgoAopAchFQISW5a6szUwQUAUVAEVAEFAFFQBFQBGKJgAopsVw2HbQioAgoAoqAIqAIKAKKgCKQXARUSEnu2urMFAFFQBFQBBQBRUARUAQUgVgiULRCyjfffCOXXXaZ/Pvf/5bKlSvLLrvs4tQIoDYLqWE/+OADTwtK4ZxjjjlGnnjiCalevbrcfPPNThFC/p/6LvQBnX766bJgwQLnZyqCbrnllvLOO+84/7722muF4kykW77lllvkhBNOcCqS/+tf/3LqFfD/pCC++OKLM44p0/vlDZ56MgMGDJD58+fLm2++KQcffHDp42W1RUrSZcuWye+//y6HH3643H777c64Bg4cKJMmTXJwI13whAkTpEaNGqXtkS557733lrZt28ptt9220bAo1nnWWWfJ22+/LVtvvbXTFmvx7bffSqdOnZw009mIop0//fRTtsc2+j3rff7558tmm22W87vpL5AqmnaYS1nEepMemxSBhRJYMv7PPvtMKNa1zTbbOE2y76gP9NRTTznjueeee+Qf//iH8zueZ2+S3nnfffd11oq03u+++66zv0jnvemmmzqFNA855BCnGOP1119fOtT33nvPWSdS1aYSRQDZ319++aWzduTlJ5VtefTLL784Vc1ffPFFZx8FQRQ+veGGG2T69Omemu/cubPz7Lbbblvm979y5Urp2LGjfPXVV863QG2Rc845x2mfuVP/hvmA41tvveWpX/ch8tvT1s8//+zsEc4S1goCU75Z/r3//vvLQw89lNM3ktNA9OEyEbDNNxgINaP43tlTLVq0kOuuu05+++0355tlj1WoUMHZK02aNHHGze+oL8b+53fU1kpNQ+tOLmi+4YWHPfbYY3Lqqac6fBg+tGjRIqfEwB9//OF8X8yja9euG62H8o38PtJc+QY84aijjnJ4A+tBeQB4PsS6UNcM3g+/cMslsO48x5qeffbZGfk+7yeBb1AHDL5Byn2+zz59+jj7OZ0+/vhj52yHf/I9wjcgr++Xt9pl8Q3WA14OP9p8881l3Lhx0qBBg9jxjaIUUrjIHXrooc4l2D0AqcDLwcdFIxchhcvgs88+61wAEWwQLLj48+FyCaPw4h577LHBHuvZs6dzkacOAZWdufS8/vrrzgWWwn5saC73CDWNGjWSNWvWOAf4lClTnAt/KpX1fnkXP4QTmBdMjkucK6SU1xbjQQgDu9NOO81hesz1hRdekCOOOMKZLx8oBxkFNV3iwswlmloZmYQUPqIPP/zQEXoQnmBa5PSH+KjPO+88Oeyww8o9kfMVUlhrmLx7wc/v2Pf+FgID/WXCwXsr5sl58+Y5ggAXk9Q5sB/BlMs2TAImT+VdLlfsebCuWrWqs4ZchGEi/I0AjCDK+1yCuOCk0vvvv+/Uz/j88883GupVV10ltWrVcuraINSsWLFCRowYUe6UGCOXKVeIz3X+Xp7PVUiZPXu2sJcQNMtSUoANTJj5sa+pLwK27P9C91PDhg2dvfHPf/7TOYMuvPBCZ00WLlzorBcCHWuOAI8glcs34gUvfaZ8BMLgG1wCudTMmDHDUaa5a895yXePooH/Y5/wvXOu9+/f37nkDxkyRNavX+9cBtPPOBt8IxsPW716tSN0cQ6w7+FD/AzOzBW+R62zOXPmOAVGU0n5Rn5fa658g7VgHTgXXQUldx3uJRTrPf744x3FCWcmfJr7FM/TD2cof8rid0ngGwjVzNe9/B944IEOj0UJnUp8ozyLMpsz3BVSvL5f3mqXxTfcOxvvch9gHVizuPGNohRSYPYc5K+88spGa482OBchpUOHDo42nssil2yqiY8fP95pl4KSHLZ8jC7x0VN4kjEgvKDNgrFcffXVziMc2lz2GzduvMHYWrdu7Vwk06uTe30/0yZnzKlCipe21q1b52i6EKzQnqcSQhTF0tDAQ0j4XFoR1sq6nGM1ouASHxqMdYcddnAufRx8Tz75pIMnDKk8coUUrClcpNFqME6YNP/mEOGSh1WKPijAuHz5cueg4JIJA+cykEpcONGIvPzyy85/o7nefffdnYMGzQkXVC7mXBJYT7TcjIM2wZX50CZWM6xk/Jv3sSDUqVNHSkpKNsIvH7aTfjFG8GzatGlp23//+9/l+eefd5pG24XVBGHzpJNOcvYT+HPBQVhhPSkWNnXqVOfvVKKKPGvChSmdwJAL/nbbbefggqXNtRqWNScEJjBl/AgTCOwIslzIEXpZc76LVALDu+++W5gT5Fr0UC4g7IAtAhhrwphyFVJoM9v3j3DCHuCSyLMUnGXMjLUsIQVrFwIH2GDdwpq11157bTA3rJSsGwoEiLOEdRs7dqxzfuy5556OwJ5OXr+RfPaWvrMhAmHwDc4t+Av7LJXYT/AIzmEIaz7nN9/4jjvu6Ci60J6WRV7O+rLezYdv0FY6D+ObZV7woFQ+5PaLMoBLHwo8+EIqKd8o7Ov0yjdShUMsvJy5KF45i1Np5MiRjvImlT9kU8oliW+4WOy3337OHShdMe3+PvWekGkFU98vlG+ktg8/v++++0o9U+LEN4pSSMGl6osvvpBRo0ZttE9SLylctNIv4u4LCDi4duy8886OtoCfYQxcitH8cFmCcaAdwlzvEpe5yy+/vNQVBE03WgmX2XDJRBDBXOoSlyJMrrjbcMFMJS/ve2U22dpC447FCaHjgQce2MhNB+HujDPOkPbt2zsaPC5d999/v2NtKUtIQVOGdF+3bl1nmBxcr732miM4LFmyxOkLLX555AopaHo4SMEI7SG4soYITwg7mDshXHawZJWn+eZ3aIV69erluKAheE2bNs1htFiRsMLde++9jmbk8ccf30hIobLxjTfe6BwK/M2Fs7xD28tey4RB+hxYA8YMM4Fg5jAO9iEuIb1793b2JhowV5jkYsxzCNCsG/uXfZ1KuPJxsLFe6YTWCGHMJdYOa0pZhLYUwQ5hFEKYQFBCu0u/zIGK7ukuKnyv9IO7AXuDCw5jR2PE5R9zO23xfbPmqUIKAmOPHj02GhLfbaqyIpuQgvaXPcC3zs9Y/VAsQLvuuqujJUOY4zvmcgkxToQNMOT7YQ248KYS3wfr5gqUPMe6oQFDoERI4btAyEagc10GvX4j5X5A+ktPCITBN3CthKdwRqLwQunDBRFBFws+l4/Fixc7l3mUIfAcXDlRsLD/d9ttN0eDuv3224fGN+g4nYehaUeJxIUuXejBo4Bz/9NPP3WsuvCldFK+YRCxwTfoh33IenTv3t1Zk1RCIehq81E+uZRNSEkS32DOeNDg/cF9JV3B5mJSnpCS/n6hfIM+cfnizECRBw90hac48Q0VUtJOv2yXlPTDkksOlxWX0OLCFPh/DtKKFStuIAx169bN0ajj8gWla8S43HCBdC9oXLqPPvpox5UmVXBx+8v2fnncN505eGkL31QEKleYctvnQ+Cyx0WWSxoYMHa0wOUdVmjFESBShRQuycSncPjBXNHQlEeukMLzXEQRBDkkOMBxT2J9YHoInFyAXfexbEIKHzUXTy6GjMON/UDrzbry/2iaMOWmW1K4YNIPY+cA54DPdmh7uimlPZQ+By7MWGlShZRhw4Y5lxX2FJdqmAOCJBYxLIGXXHKJIwTzey73HGxcgFzCXQwtflnCIhdzrFcuZRNSuISwp11rC5cpLJuu1QqND5eYdCUCBysCPMJMqsDCJY05YNFg7yEE0XYQlhQsHOxPNIfsLYQ7xsr3zrzQ+GKl4/+51BIPhMUN4dslviGEnFTCVYd1SxVSWDcEY/Ys+424FDA48sgjHYsYuHv9RvLZW/rOhgh4FVK84OaVb8BDUPagYMCfHR7AvuPswfqOAohvm33gusay33Cb5XtmzHy/rkIiDL6RzsNcBRbnIedXOh9yx8j3RCwjll2stKmkfMPLLiv7Ga98A2WbSyiI4BnsqVRlFfcG+G2qMpZ3svG7JPEN7gCcy1j6UwW19BUoS0hJfx+vkEL5RmrfKDNQdKBYheLEN4pSSOFgx8XIvRSlLmaulhQ+NC6imSRnNJ5cYhFMIDT9uPrgBuVeytPN7lxI0LRiyucw51DgZ9cdLH3Tl/d+tmMsm9k+dSypbcHw0PS6vqZc3BBSuNS7LgZYVBBawIUPjosjWpjUeBXaLM9sj3BBDA5uWuWRK6QgIPIhYuXhUofmmrXmQOYSze9w00EIZG28CimsA0IKBwkX8FQhxb2UpgsprvsCBztaKPaVDUtKursXzOS5556TV1991Zk/2lYIVyv+D7cqrEqM0w3STtdwIfhxYOLylYlSzfZYUBDOynP3Yi3Q/IIJVJaQwqHvBmmCHTjiCsYaMk/mgi8wVi2YKYIKAgvP0HYQlhSEQCwe9AGxl9AI42aTSvwfSQkYJ1YQ9kwqccl0LwB84yTZQAuOAAZxyWTdsMBg0cMqiEue+83QPrErXr+RbGeB/j47AmHwDZQr7Dc3KJ5vje+W7zGV+FbYK7gRch6yLzh72XdoZPGTTyVbfCMTD8OSzdnMOCEsqrh6IoykJnHhd3wX8Ih0BZ3yDbOafllSyuIb6bFAKN+w6LkxFXgJwPdRTqbHwWYTUpLCNxDCObvhPyj/yqNMQkqm9/l+C+Ub6eNIFQrjxDeKUkjBrQWmj+aJQxBCk8lmcd1NvGb3oh0u7Ry6kBvYyGUJBoPW1c12xSUR5pAqHME8CDrD7xaGwmZHy8oHj4aCsZYXk1He+7SLqTz9AuVu3nQhpay28PVnU3NgIWideeaZzkWUthFEcGvhQpiu7XL7Ke+w4sLJfNHCYPpH04/GGEJzyMUY3NAgMx8uCunkCiloG7FY0BbjwjqA1pGgZpggl0bcZ4gZwk0Ltwg01Qgr6VSWuxeuF1wqs7l7ZRJSmB/9gYdflC5oEWDLZQWGjwsRgiFmZLSpuFDxM+5e/Myln4MVQZB3uOiwNxFKwB7ikoFrFtYpNLaZCCsfQhzWQZgWlgRcAspbM9rE8gHDS3f3atWqlRP3kykjEfsFARmrDtYECG0r1j2eJw4M4SVdSPGKdzZLKgoHvgOEXCxrWErACnczsEJDzjnCJQplA2cA3woJJIgv4Htm7PgepxPfKd86FzVcyhBOcOti/+NyyL5BIYJwg6IDa2PqN+J1jvpcfgiEwTewasIXENY52+AP7FHOZMaDUogzkcuj60JIQhMunVgrUdhwgUSRlEo2+IZXHpbKh1BIsa85o1BmwF8R2DmrU0n5Rn572H3LK9/gjEPhh+KKPce5hncECkz4NOc9+y5T/FM2ISUJfANlE/cBzvjU2OOyViddSCnv/UL5BvzVde/i3kPfbsbJOPGNohRS2ECYkgncg9lzeXVTEPNB5hI4z6UIbTqXPggNKxcJLsa4pMAoXEITyqGbnlIRBoMVgEOdzBn45yMkcTCjCXc1FLh/cGlxL6BYg6BM7/P/XEK5FBNImUrEUBA0zQHE4cNzuFyV1RaXTi6OuKnwUeF+wNyIAeBCBRN1NXvMD8aaSumHFRc89yJGmwg9pOdF0ucy5l6GOQDBkbHycXHpc8eZ2r4rpKDFZ5yYMpkTgh8fJ9omDkQ0i7TnXgQRZhgrl07XzSb1EE9NgewGznNB4AJNX+UFzmcSUtgXrC2XWQ40Lq35EiZ3BAG0kGR6Yl8gfHFxQXgEJzeI3NVO4lIFY2E/YcngeYQENLNcohFA+RbAx9XyI0CgyQXLVELAZx/TNvNiLqTlRcinD4TC8taM7wVXMy5d9MFexkrFvkdYyhQ4T//sRayRXNrYDxBCC2vFeuAOxn7LR0hBC8ZYWFsEbvpgnO5+Zr6cG3zH4M46gg0CEsIwwhIEjszNHR/xbwg3fCfsTayM7u9SMQUvfJpE8ld1AAAgAElEQVTd9MzsT6xbrCkCIMIKa8e7XESh1G8k372k73lHwDbfwALNecP5yNnFucL5y/7mwsiZhlUewRzBHyL+gzMV6yjfFN8Dv7PNN8rjYamIpwopWA/Z6+6+5yxzY7uUb9jnG8TBcrZy1sH7OedZB4i9hVLGVcJyWXd/x32KWEH2L3cM3IexeieNb3C/QHGZKkS7Vv9UvgG/gFeCCd8sdxas5ij/ynq/UL4BT+dew52WuxWeL27SmTjxjaIVUryzpfKfhGlxsch0efarj3za4WPggpWuQcunrbDe4bKKFtD9wGC0aJhtUKHpZG2MMep9cCiWtWYoBxC08JHNJ3Yk6nO3Nb7Ub8RWn9pP4Qgo3ygcw7JaUL4RHLY2Wla+ETzKceIbKqT4sB/QHOPWkZ55y4emi7YJrDxkMyKzURikQkrwqBNkiJYO17xcii4GP7J49BD2NxIPlKI7SuUb/q9N2N+E8g3/1zS9ReUbhWEc9jeS6+hVSMkVMX1eEVAEFAFFQBFQBBQBRUARUAQCRUCFlEDh1cYVAUVAEVAEFAFFQBFQBBQBRSBXBFRIyRUxfV4RUAQUAUVAEVAEFAFFQBFQBAJFQIWUQOHVxhUBRUARUAQUAUVAEVAEFAFFIFcEVEjJFTF9XhFQBBQBRUARUAQUAUVAEVAEAkVAhZRA4dXGFQFFQBFQBBQBRUARUAQUAUUgVwRUSMkVMX1eEVAEFAFFQBFQBBQBRUARUAQCRUCFlEDh1cYVAUVAEVAEFAFFQBFQBBQBRSBXBFRIyRUxfV4RUAQUAUVAEVAEFAFFQBFQBAJFQIWUQOHVxhUBRUARUAQUAUVAEVAEFAFFIFcEVEjJFTF9XhFQBBQBRUARUAQUAUVAEVAEAkVAhZRA4dXGFQFFQBFQBBQBRUARUAQUAUUgVwRUSMkVMX1eEVAEFAFFQBFQBBQBRUARUAQCRUCFlEDh1cYVAUVAEVAEFAFFQBFQBBQBRSBXBFRIyRUxfV4RUAQUAUVAEVAEFIGIILBu3TqpWLFiREajw1AE/ENAhRT/sNSWFAFFQBFQBBQBRUARCAyBr776Sm666SZ58cUX5ZtvvpEffvhBrrjiChk6dGhgfWrDikBYCKiQEhby2q8ioAgoAoqAIqAIKAIeEXj77beladOm0qJFC+nSpYvUrVvXeZO/q1Sp4rEVfUwRiA8CKqTEZ610pIqAIqAIKAKKgCJQpAjss88+0rZtWxk8eHCRIqDTLjYEVEgpthXX+ToIvPDCC3LttdfKu+++K7/88ovsvvvu0qtXL/nXv/7l/H7AgAEycODAjGh16tRJ7rnnHud3Z599tnzwwQdy0UUXOYzj66+/lv32209uvvlmOfTQQ0vfX7t2rdPmpEmTHBP9rrvu6mjCLr30Uvnb3/5W+hztnnPOORv1+8UXX8guu+wis2bNkqOPPlref/99gWEpKQKKgCKgCASDwJdffumc1enUv39/5zyHFi9e7PCOZ599VjjnGzRo4PyuWbNmpa9tsskmMmHCBIdfQBMnTpTOnTvLvffeK6eddprzf7fffrvzzMKFC2XTTTeVAw88UEaMGCEHHXSQ8/sFCxbIXnvtJX369JFHH31UGNt2220n8KN+/fo577i867bbbpP77rtPrrrqKqe9evXqOW21atWqdEzwk1NOOUVuuOGGYMDTVhUBHxBQIcUHELWJ+CHwxBNPyM8//ywHHHCAc7g/8sgjzkH/0ksvyVFHHeUwmVtvvVU+/PDDDSZ34oknOu+kCimTJ092/u/GG2+UypUrl7bz6aefyrbbbuu837x5c/n+++9l2LBhsttuu8k777wjXbt2lW7dupUyO56DScG8PvvsM9lss83k+eeflzPPPFNUSInfHtMRKwKKQLwR4NzlvL7//vvl2GOPdSbz97//XS6++GLn3OZM5+xv0qSJXHbZZVKjRg2ZNm2aXHnllc7Zzf9DqULKgw8+KOedd5488MADcvLJJ5cChGKrfv36sueee8qqVascXkHcySeffCJbbbWVzJ492+FNm2++uaMEO/LII+X11193FGQdOnSQ0aNHlwopKOAQlkaNGuXwIGJY7r77bofvuMotFVLivTeLZfQqpBTLSus8syLAoY+maty4cQ4DQhu1YsWKDd47+OCDnUM+VUiB6cDMXP/gn376SXbaaSeHkWGNeeWVVxzmsmTJEqldu3Zpe2jOSkpKHIbkEn1fcMEFjkYOgWf69OmO9kuFlKzLpw8oAoqAIuArAq714umnn5YTTjjBaXubbbZxBAN4BNZzrCIosxBEXDr11FPl119/lalTp24gpFSoUME533nnpJNOKnes8IDq1as7vAYhxLWiDxkyRHr37l36Lsqxq6++WpYtWya1atUq9QKYO3euNGrUyHlu/fr1jtDSsGFDx3oDqZDi61bRxgJCQIWUgIDVZqONAG5ZCBBop5YvXy6///67IxgQlIjZPhch5bXXXnNM6qmE1g2tGlYWzOlo1tCApdIff/zh9Ll06dJS4eW6665zzPm//fab82hZQkrVqlUFhrfFFlvI3nvvLX379nXGrqQIKAKKgCLgDwKc7YcffrikXvhThZSWLVsKAkx60DrnN25iCDkQAszxxx/vWFcQJHARpp1Uog+sJ7jyYqH5888/Zc2aNU7WrmuuuUZefvllxzKD0osxuTRv3jz5xz/+4bgwwwPgXVhScGOGR7iE9YZn//Of/5QKKfCeSpUqOd4EderUcdydEYBS3/MHSW1FEcgPARVS8sNN34o5Avvvv7+TV54DfeeddxYu/eeff76jcUJjVaiQcswxx8iWW27pCCkIHhz8aNsyHf5otFx/4ksuucRxF8ByUp6Q8tRTT8kee+zhWGHwNUaY4R3XvSzmy6PDVwQUAUUgdASwOhBH8u233zrCBZQqpODG++OPPzrxH+kEf4G3uEIKwgAxicOHD5ftt99ennzyydJXiGtB2dS6dWvH0sI5zvvwKRRc8COEF+IdX331VTnssMM2ElJwDSNe0RVSUIClWnfOPfdcx90rVUhBmUY8DUo6hJ/u3bs7LmJYipQUgSggoEJKFFZBx2AVAbRUMJqHHnpI2rdv7/SN5gvfYwLocxVScPciiBFNFIT2C3cvDnqsNcS5oOFCE4ZLWXmEOxnjIEamPCElNXAerdy+++7rjBu3MiVFQBFQBBSBwhEgKB3rw3vvvVfaWKqQQgA9bsHEEKKUKosQFrCo9+zZ03mWoHisHRdeeKHzCsosgthTreootXAtdoP0sYzQB//GsuISQgWCTLq71xtvvCGHHHKI8xjKN2Jp+Hd57l7wH3gJsZFKikAUEFAhJQqroGOwigAHNrEhaKUIKKRaLyZ13LxgHrkKKTAYzO0wIeJIYCKY3tMD5xEssHrAKGA4MD6yi2FpoUAXf99xxx2OS4DrulWWuxfaMHyMsaTgFz1+/PjSbC9WwdTOFAFFQBFIGAIorVAutWnTxrFMuFm5mCaXfTIw4mIL7+Ds33HHHR2FFEqu7777TubMmeMkPiGDI5Se3YtAfCz3b731ltMevAGryeWXX+5YMxYtWuTEmcAfiFt0M4nxf/AIkrrg8oUggqCDsi09cB4BZ+TIkY5VhkB7eER64DzpjBGWsKRgoWnXrp3zb7JOKikCUUBAhZQorIKOwToCmLY5iD/66CMnjSM/w1gIlM9VSMGSQZYuAhrRhKGJuuWWWzZIQUwQJWZ+1+pSrVo1J5PLWWed5WT5wupCoS5M75j8XSpLSHF/T0xKppSX1gHVDhUBRUARSAgCbpB6edNxU9Fz5iOwzJw50+EfW2+9tSO4YDVxlU3pQgrtduzY0VFUvfnmm05MC0lTiEkhRT0JXFBaETDvBunzDkIRAgtCDpaTHXbYwRGg6D89BTEB91hYPv/8c8c6j4IslbfgZowwBLkxKQg78LHUtPgJWVKdRkwRUCElpgunw44GAm6dFDRiSoqAIqAIKALxRwAhhbMdN95MhKDA79wsj1GacVnxlFEao45FEfCKgAopXpHS5xSBDAiokKLbQhFQBBSBZCGAVR3r+r///e+ME8O1l2B33KiiRiqkRG1FdDyFIKBCSiHo6btFj4AKKUW/BRQARUARUAQig4AKKZFZCh2IDwiokOIDiNqEIqAIKAKKgCKgCCgCioAioAj4h4AKKf5hqS0pAoqAIqAIKAKKgCKgCCgCioAPCKiQ4gOI2oQioAgoAoqAIqAIKAKKgCKgCPiHgAop/mGpLSkCioAioAgoAoqAIqAIKAKKgA8IqJDiA4jahCKgCCgCikB2BMiIRLHT+fPny9y5c2XBggUyaNAgp05EixYtnGJyxx13nNSrV89pjNpCVNmmDsTq1atl5cqVTjE7iKJ3NWrUEGoOUdBUSRFQBBQBRSBZCMRWSKE4kpIioAgoAoqAPwj8+eef/jTkoZWWLVsKhUqpyI2QUrt2bXH/jyrf/Bvhg+J2y5cvdwrMjRkzRiZOnCiMkz8VKlRwKm1TDLVPnz5St27drD0r38gKkT6gCCgCioBnBILmG7EWUoIGx/Mq6YOKgCKgCMQYAS7vNs9TVyChAvbUqVMd5Nyf169f7wggVOCuVKmS1K9fXyiuV1JSItSvmD17tjPWJk2aSOPGjR1BhsrejRo1yroCtueZdUD6gCKgCCgCMUXAxnmqQkpMN4cOWxFQBBQBvxCwwWxSx5rJktKqVSuZNm1a6WMIL4sWLZK2bdvK0KFDZfTo0RktKd26dZPevXtntKRQM2LgwIEbwGRTGPNrfbQdRUARUASihoANvqFCStRWXcejCCgCioAtBH77TWTBAtlkv/2sWFLWrFkjPXv2lJkzZ0qzZs2kR48eTjwJMSnNmzd3YlI6duwo1atXlxUrVsjYsWOlZs2a0q9fP1m1alXGmBSexWXMC9lgql7Goc8oAoqAIhBrBJYvl0223z5wvqFCSqx3iQ5eEVAEFIECEHj8cZF27YQIv2KwMKiQUsBe0VcVAUVAEVi2TOS660TGjpVNfvklcL6hQopuOUVAEVAEihWBNm1Epk5VIaVY11/nrQgoAoqAFwSWLBEZMUJk3DiRX38VqVpVhZTycFONmJddpc8oAoqAIlAGAsuXi9SpI1KzpmyyYkXgGrEorIPyjSisgo5BEVAEYoPAV18Z4WT8eBHcgzfbTOTCC0WuuEI22W67wPmGWlJis1N0oIqAIqAI+IjAqFEil18ucumlssnNNwfObHwced5NqZCSN3T6oiKgCBQTAl9+KXLttSITJoisWyeyxRYiF18s0qOHSK1aDhI2zlMVUopp0+lcFQFFQBEAAWqi7L+/yPvvi8ybJ5sceKAKKbozFAFFQBEodgQ+/1xk2DCRe+8V+f13kerVRS65ROSyy0S23noDdFRIKWez2ACn2Peqzl8RUAQSisC8eSL/+IcRVN55x4pGLApIKt+IwiroGBQBRSByCCxcaIST++8X+eMPkS23NIIJAkrNmhmHa+M8zduSsnjxYunfv7/Mnz9f5s6dK88995yMHz9eatWqJbfddpszoSlTpsiMGTNk7dq1TgpJinL17dtXVq9enTGVJBWGSUfphWyA42Uc+owioAgoArFD4NJLRW65RQSXr8suUyEldguoA1YEFAFFwAcEPv5YZOhQkYceElm/3ggkuAHj2lWjRrkd2LiH5y2kuCN3i3Lx7y+//FJuuOGGUiHF/d2yZcscgQZBZciQITJmzJiMRbm6du0qffr0yViUKx0pG+D4sPzahCKgCCgC0UKA4McddhBZuVKEjC3bbqtCSrRWSEejCCgCXhHAdfW550R++UWEbIVK3hD46CORIUNEJk0y7r+4cl1xhUj37sbFywPZuIcHKqS0bt1aqBoM8XNJSYnMmjXL+XvOnDkye/Zsxw+6SZMm0rhxYxk2bJg0bdpUGjVqtBE8WjnYw47RRxQBRUARyIbAX7VRHIb+xBPO0zaYTbZh2fh9sczTBpbahyIQKgIEc3PBvv56E1sHzZ0rkuH+GOo4o9Y5WOGx9NhjRjghCP7KK0W6dTPB8TmQjfM0UCElkyVl6NChMnr06IyWlG7duknv3r3VkpLDJtFHFQFFQBHICYG/aqMIwspJJ6mQkhN4+rAioAiEisDq1SYdLq6qixeboey0kwipck85ReTRR0MdXmQ7f+cdI5xMmWKGuN12IlddJXLBBSKbb57XsCMtpKxZs0Z69uwpM2fOlGbNmsk555wjt9xyi7z77rtyxhlnONaSyZMnO78nJoVYFGJScPlatWpVxpiU6tWry6BBgzyBZQMcTwPRhxQBRUARiAsCKbVRHFevSpVUSInL2uk4FYFiRoCzizi6O+4Q+fFHg0Tz5uai3bChEVS+/17k009Fdt21mJHacO7/+Y8RTp580vx/7doiV18tcv75TkHGQsjGPbxgS0ohEyzkXRvgFDI+fVcRUAQUgcghkFIbRW66qXR4xXKeFss8I7fvdECKQL4IfPKJyI03mpS4VDrfdFORM84w8RP77PP/VgcOFBkwwGSjuvnmfHtLzntvvimC0n/GDDOnunVFevUSOfdckSpVfJmnjfNUhRRflkobUQQUAUUgBgiQcvi995zaKHLAASqkxGDJdIiKQFEi8MYbItddJ45bKrETxEvgmkRmwh133BiS774z1pS//c24gZWRNjfxWBKXg3Dy9NNmqmBSUiJyzjkilSv7On0VUsqB0wY4vq6mNqYIKAKKQJgI4JN84IGltVFSh1Is52mxzDPMbaZ9KwJ5I0AK3JkzjXAye7ZphtgJ6nV07Wpqd5RHCDHjxokMH25cmoqJXn1VBGvS88+bWe+yi0jv3iJnnVXq1us3HDbOU7Wk+L1q2p4ioAgoAlFEAEaPG8TIkSI9emwwQhvMJgqQFMs8o4C1jkER8IwAadEnTjSZuj780Ly2554m61THjt7dk6j5sffeJsX6F18Edjn3PC8bD86aZSwnL71keqtXzwgn4FaxYqAjsHGeqpAS6BJq44qAIqAIRAABLgF16piA079qo6SOygaziQAKRZNqOQpY6xgUgawIrFolcuedJlMX5xLUuLEJhm/dWqRChaxNbPRAq1Yi06eL3HefyJln5v5+XN7A6nTyyaVp5B2hrk8fkfbtTdyOBbLBN1RIsbCQ2oUioAgoAqEiQD2Utm0N43ezvKQMyAazCXX+f3VeLPOMAtY6BkWgTASWLTOZukaPNkVlIc4mhJPDDisMOCwLRx9t3FqJvdtkk8Lai+rbjzwicvrpIjvvLDJsmPmZeByLZOM8VSHF4oJqV4qAIqAIhIIA9VAQTsiRj7CSRjaYTSjzLtJ5RgFrHYMisBECuGPdcIPI/feLYN3FHQlrB5m6cNPygwiyP/hgkbffFnnhBZGmTf1oNVpt/PGHyL77isyfb2JQjjkmlPHZ4BsqpISytNqpIqAIKAKWEPj2W+PqVaOGyNKlGf20bTAbS7Mtt5timWcUsNYxKAKlCMyZY4LhXStu9eomEJ5MXcSP+E0PPWTSFFNHxU3B63cfYbZH/E6HDiJHHCHy8suhWYtsnKcqpIS50bRvRUARUASCRoB6KATKl1M/wAazCXqaXtovlnl6wUKfUQQCRYCYCWJDEE5ee810hUBCAg8KCaI0CYrWrRPZbTeRr78W+egj/6w0QY03l3axolAfBqvUiy8a17aQyMZ5qkJKSIur3SoCioAiYAUB6qG8+65xfyAFcQaywWyszDVLJ8UyzyhgrWMoUgQouPjggyZTFxdpCFcuMnWh/fe5VkeZKONWRp/nnWeC85NCYEvmrqOOEiH+JkSycZ6qkBLiAmvXioAioAgEioBbG2W//UT4uYwgUhvMJtB5emy8WObpEQ59TBHwD4HVq00gPJZbAuMh3JEIhsftKp9MXYWMjoB8qqxjVVm0yNRbiTv9/rtIgwYiCxcaAQVBJUSycZ6qkBLiAmvXioAioAgEikA5tVFS+7XBbAKdp8fGi2WeHuHQxxQBfxCgRsfZZ4t89ZVRhJCoAysG6YTDJNxcEZr69TOFDuNOpFXu1MkkAyApQMhk4zxVISXkRdbuFQFFQBEIBIEstVFUSAkEdW1UESgeBH7+WaSkxKQThk49VWTwYJH69aOBwZdfmuKGW21lBKiqVaMxrnxGgRUFt7lPPxV55RWRww/PpxVf31EhpRw4bYDj62pqY4qAIqAI2EQgS20UFVJsLob2pQgkDIHXXzda/U8+MULAHXeYWh1RI8ZETZExY0QuuCBqo/M+nnvuETnnHJFjjxV57jnv7wX4pI17uFpSAlxAbVoRUAQUgdAQyFIbRYWU0FZGO1YE4osAFlpcp4YPFyGDV4sWJjC9du1ozunNN0UaNhSnIjt1RWzHxviBCnE1WKe++MJkSjv0UD9aLbgNFVLKgdAGOAWvoDagCCgCikAYCHiojaJCShgLo30qAjFG4L33TPFF/t5iCxPv0blzaHU6PCNJAP+rr4pMnSrSqpXn1yLz4F13mSxlJ5wg8vTTkRmWjXu4WlIis9w6EEVAEVAEfELAQ20UFVJ8wlqbUQSSjgDxEKQU7t/fZMtq0kRkwgSRXXaJx8xd19cIpO3NGTAsV1hRiK/BxQ6rUERIhRS1pERkK+owFAFFIFYIeKiNokJKrFZUB6sIhIMAMSfEnnBBrlJFZMQIkYsuipfbFAUQ99rLBJ2/9ZbIQQeFg2U+veJKR/FL0jjPmJFPC4G9o0KKCimBbS5tWBFQBBKKgMfaKCqkJHT9dVqKgB8IEG9y++0iV18t8ssvIoccIkIK3Khk7sp1jgT2X3ihKShJQcQ4EFaUPfYwmcmIrfnnPyM1ahVSVEiJ1IbUwSgCikAMEPBYG0WFlBispQ5REQgDAYofEmvy4osiFSuKDBhgijJuumkYo/GnT9Il77ijCEUeCUDn56gTGcm6dRNp2VJk2rTIjVaFFBVSIrcpdUCKgCIQYQRyqI2iQkqE11GHpgiEgcCff4qQ6vbSS0WoIL/vviL33y+y//5hjMb/Pvv0ERk6VOSKK0yMTZTp119Fdt9d5OuvI+uipkKKCilR/oR0bIqAIhA1BHKojaJCStQWT8ejCISIwDffiHTpIjJ9uok3wc2LQPnKlUMclM9dM8eddzaxNYsXi1Sv7nMHPjbnuqe1aSPCuR5BUiFFhZQIbksdkiKgCEQWgRxqoxStkLJwodFQKikCioBBgGKHuBX9978mBuLee0UaN04mOrixkZls5EiRHj2iOce1a0Xq1RNZulRk3jwREqFEkFRIUSElgttSh6QIKAKRRCDH2ihFK6QQ+Dt3rkjNmpFcRh2UImANAYQSgsknTTJdXnyxKdK42WbWhmC9o/ffF9lvP2NRIdtXFONsbr1V5JJLRNq2FZkyxTpEXjtUIUWFFK97RZ9TBBSBYkcgx9ooRSukMPFjjxV56ikTFKykCBQjAuz/c88VwQWKIHKsC8ccUxxIUBTx2WeNcHb66dGaM5nUsKIsWyby7rtGoIooqZCiQkpEt6YOSxFQBCKHQI61UYpWSIHpUzEb9xZSrG6ySeSWUgekCASGAAHxl18uMn686eKcc0RGjRKpUSOwLiPXMAIKggopfd94I1pngKtsOuUUkUcfjRx0tvmGVpyP9BbQwSkCioAi4AGBPGqj2GY2HmYR+COO5o/0qtR8WL5c5JZbjIuLkiJQDAjMmmWEEqqXb7edCIUCW7UqhplvOEeymJGxDNev2bNFjjgiGhiQJnm33URw3UWRss8+0RhXGaOItCVl8eLF0r9/f5k/f77MnTtXFixYIIMGDZIqVapIixYtpF27dnLcccdJPcxWgpvjcNlyyy2lb9++snr1alm5cqXcQfYCEenevbvUqFFDqlWrJoMHD/a0KDbA8TQQfUgRUAQUgbARIAAUDVyewaDFcp6WzpPq2U2aiKxbZ6o4n3hi2Cuo/SsCwSGAC1FJicjNN5s+Tj1VhPvXNtsE12fUWybVMgJblLJncX737Cly2mkiDz8cdQTFBt8o2JLSsmVLmT59unTp0sURUmrXri3u/7Vp08b5N8LHsGHDZPny5TJkyBAZM2aMTJw4Uf7880/nT4UKFaR9+/bStWtX6dOnj9StWzfr4tgAJ+sg9AFFQBFQBMJGIM/aKKnDLpbzdIN5Tpxoqk+ThpRA+gYNwl5J7V8R8B8BKpWfdZbIggUmWQTCCXEYxe7mSB2SXXYxFlWwIatZmLRmjbGifPedyAcfxOI8ssE3fBNSWrduLVOnTnWW2P15/fr1jgAybtw4qVSpktSvX19mzZolJSUlMmfOHJk9e7YjpDRp0kQaN27sCDJNmzaVRo0aZd0qNsDJOgh9QBFQBBSBsBF48kkRUg+3bi3Cz3lQsZynG82TOhCDBonsuqvxTa9VKw/09BVFIIIIoLzAM+Xaa0X++EOkWTMTh7LDDhEcbEhDGjZMpHdv3HlMfFqYRHHJq64Sad9e5KGHwhyJ575t8A3fhJRUS0qrVq1k2rRppRNFeFm0aJG0bdtWhg4dKqNHj85oSenWrZv07t07oyVlwIABMnDgwA3AQ8BRUgQUAUWgqBEgTSXFvkhVyc95kA1mk8ewfH9lo3muX28uBdSJOPxwkeefT1bxOt8R1AZjgQCxFlhPiFXbYgsTGE8mr2K3nqQvHimYyWzGXZLijltvHc7y/vSTUZQwng8/FNlrr3DGkWOvNvhG3kLKmjVrpGfPnjJz5kxp1qyZ9OjRw4knISalefPmTkxKx44dpXr16rJixQoZO3as1KxZU/r16yerVq3KGJPCs7iMeSEb4HgZhz6jCCgCikBoCOAagGaUzDwU/qpUKa+hFMt5mnGe+OsfdZTIv/8t0qmTScWql7m89pG+FDICWEzQyPfrZ+Kt2NfsZy7ASpkRuOgiY0UZMsRYVcKgESNEevUSOeMMkQceCGMEefVpg2/kLaTkNSMfX3LAQerUglw+oqpNKbQU+NYAACAASURBVAKKQKwQIBD2sstM4S83KDaPCdhgNnkMy/dXypwnNQnI+PX116aY3dVX+963NqgIBI5A377msl2linHz4lyoUCHwbmPdAQUd99zTZDsj61nlynanQ0pohMgffhCZP9+MJSZkg2/EW0j5xz9EnntOZKutYrKkOkxFQBFQBHxE4MADjUvH22+L8HOeZIPZ5Dk0X18rd57z5hmXLywrkyfn7Trn64C1MUXAKwIUZSSbKi6Mb70l8ve/e31Tn2vXTuTxx0Xuvttk/LJJblwM7nn33muz54L7ssE34i2kADEFzBBUijmVXsFbTRtQBBSB2CHg1kbZd19TmbgAFyUbzCYK+GadJ7E9XFiqVhV59dWCBL8ozFfHUEQIYFHFmkoK2xtuKKKJ+zBVvnVqpVCXhPokBZylOY1m1SqTYYy/P/5YZPfdc3o97Ieznqc+DDDeQsoxx4i88IIITJq/NTOLD1tCm1AEFIFYIODWRrnxRlNBugCywWwYnpf6WlOmTJEZM2bI2rVrnRhGskJara/l+ofXqSNC+lbNhlTAzgrpVVzBiS8gWPzgg0MahMVuCfrmgktM2uef610oV+gJnCerLN/700+bavQ2CNc8XPTOPtvEDsWMbPCNeAspVOekEA+WFEybCCr4FSopAoqAIpBkBNzaKPgxL1lS8Llng9mkLkd59bXc3y1btswpGIygYrW+FhcWXD5wveCC+/LLIpttluTdlKy5sX6nnGKy3ZEliUxXm26arDmmz6ZrV5GxY0X69DFph5VyR4AMf9SPOe44kWefzf39XN9YudJYUYhJ+eQTUyMlZmSDb8RbSOEwwn8Y8zzS7957i7z4osj228dsqXW4ioAioAjkgIBbG6VVK5G/6lPl8PZGj9pgNpmElEz1tdL/j7pa1utrUeiNy8orr5jq3JMmaQByIRvM5rtopDt3/n+PXN7PP9/mCOz2heWkfn2TaviLL0S23NJu/0np7fffjTVq0SLjPrvffsHOjJIaAwYYax/1a2JINvhG/IUUFnbtWpGTTxZ56inzsSKoqIk+hlteh6wIKAKeEHBroxDgjZKmQLLBbDIJKZnqa2WypIRSX2vFCpPxi4sfLhke0+MXuBT6eiEIfPaZiVPFy4L4jIsvNlZGMjhxiU8ikTb7vvvCTaGbFFxvukkEN1owveee4Gb144/GikKV+YULzc8xJBt8IxlCCouL5guNF0Uk99hD5KWXRPApVlIEFAFFIEkI+FQbJRUSG8yG/rzU15o8ebJTf4uYFGJRiEkJrb7WRx+JNG5sAlsffFCkQ4ck7aRkzQVN+JFHisyda+qEoKmm7gTVu9FY9++frPkyG1LWEuxNhlMsKtWqJW+ONmeE6xXFHRFysajUrh1M7+xFlB5Y+LD0xZRs8I3kCCksMn7a+BSSoYVUfAgqbDglRUARUASSgoBbGwUt8S23+DIrG8zGl4EW2Ehe88SVuEULkYoVDU9BaFGKHgLEYiCcYP0iWxPrRd0LvCv4GWtK0lzBue8QS+FD8ozoLWhII7rqKlMQ85prRIYO9X8QJHWgLgqhCuzJnXbyvw9LLeZ1nuY4tmQJKUyeKqvt25s892wEmMrOO+cIiz6uCCgCikBEEXBro/znPyLUivKBbDAbH4ZZcBN5z/O224zr0LbbmgxAylMKXgtfG2BNDj3UFOIjNTfeFC5dcYW5xF9wgciYMb52G2pjbgpytP24uZE2W6lwBCjoyt0RqxRZ0zbfvPA2U1sguQHCD8kORo/2t23LreV9nuYwzuQJKa6g0rGj0TDg64egElOfvxzWUh9VBBSBpCPgY22UVKhsMJsoLE1B87zwQpE77jAp7197TV1rorCgjAG/fgR3fPszBcmTAQ/PClz2yPRFgp0kUOvWxr399ttFundPwoyiMwfuj7h3opzgu/eLvv/e3EXx+sGKEnNPn4LOU4+YJlNIYfL4p1LBc+JEY05DUIlhijeP66iPKQKKQDEg4GNtFBVSctww8JTmzU3K+5YtjVvx3/6WYyP6uO8IuOl3yXRH1rtMhfiwpGBR4WLPM3GnN94wdT2w6C1YYCxISv4hMG+esVIj3IKvX985LmTXXmsEHwSgmJMKKeUsoCdwYCrku3/gAZG6dY2gErOKnjHfwzr8JCOAWZwaElzYatRI8kyjMTefa6OokJLHspKVh5gUqkNrZe88APT5FSwJCB644WEl4e9MRGIdaqYQo8KZRYB9nOn4442wfNddG6ZbjvOcojb2pk3NnZF6O2RTLJTIFogVhXsp7nkJSOzk6R5eIG7JtaS4wPzxh8lDTWEuNgXpiffcs0DY9HVFoMgRePhh4+NNQSp8dknZiM8+FwGlYBDwuTaKCil5LhNuGg0bihAAS30D+IuSfQSWLzeud2S7mz7dJDcoj8jyRbavf/5TBEtEJouL/Vnk3iNCVpMmJu6G7HNJL1SZO0L+vDFjhlHAHXaYScRQKF19tch11xk+6VPCk0KHVOj7KqSUg2BO4CCokOrt7rtNSjkEFb1MFbo/9f1iRAC/bg5Z8vLD5E84wWgmyVQCoeHj97jFVKhQjAgFN2efa6OokFLAUrHnKfZIQWE02lwalewhAO64d3GR7NbNxAplo/XrTeYvEk5QnJPMWHEj5o0ViEszQhdJgpSCQYD90qCBcfd6/XWjmMiXvv3WBOPTJlaUhNTxy+kenid2ybekuMCwOfBdvfNOU9wJQYUNqKQIKALeEKD+AJpIitthlURQwSROMCBuBwRwfvWVaQtf3osuMu6W6grmDd/yngqgNooKKQUuC0ovrCjUqOASk5pRqsCm9fUsCJClC+EErwjiBzbbzBtkuO9wZnFhpMZI3GI5nnlG5MQTTW0UqqKrIsjbuuf71LhxxmOAGnwkYsqXrrxS5IYbRC67TGTUqHxbidx7KqSUsyR5gYOgQsASBxy+qy+8YD52JUVAESgbAXxohwwxf7BKnnyyCIc3l7NU4jl8xDFlz5plfqOuYP7srABqo6iQ4sPSuJcPLssIKjVr+tCoNlEuAmi2yeZFuQEUJwcfnBtguPBggeGyyKUxLoQVBUvQW2/5FycRl7mHNU48BEhOgCION0+E21wJt0T3PQpuJqhWT1738BzxKx5LigsMH/oll5jMCttsYwSV/fbLETZ9XBEoEgQ4VEnHyGUAgePWW0XOPju7PzdBrDxL0opUVzC+vWbNVAOY6/YJoDaKCim5LkKG5xHa27UTmTpV5JhjRGbONIUDlYJBAMGEeihc1FGa9O6dez8ffmh4/pZbGtcb/o4DkU0Ol8+DDhL597+zn8FxmFMcxjhggMjAgSKXXipy0025j/jyy41AzN9kmUsQqZBSzmIWBA6CCqk80U5uvbXI88+LHHBAgraOTkURKBABvpH77zcuW6tXGw0eeeNzzY6nrmAFLoSY4nQIKQQJ4+IRQMBvQedp4TO01kIg8/zpJxNc+957xqWY+IgA1sgaSFHuqG9fI5yAN3FB+aaG7dLFJD2guviIEVGesRkbXiD77y/ywQdGEMblS8kOAsSTUMYC5QPFHXMRapctM6UvcMtD4UeoQYIokPM0DZ/is6S4AHAJI2/6yJHGRI+g4lP15gTtQZ1KMSJA8TP8vcngxeFKbvd+/QrTEJflCoZVBkFIE1mUvdMCqo2S2qENZhOFTymweRKLhSCPawfKLyyGSv4iQAFNgsax6CKs5+N6445o6VITQ4Ql7JNPzCU0ykSgP0HyCGevvKJCsO21IvES8cxk58LF0yvhTsh5wDu8mzAK7DxNwal4hRRAQFDp1ctsHqTjZ5816QmVFIFiRQDt5JlnGo0RjBt3rSOO8BcNNM64W2KpWbvWtE1WMHUF2xhn3FtIUkC62yVLAtPE2WA2/m6i/FoLdJ7EpJDlizUjJS5ujUr+IEBWQbwdSNpxzz0m5XmhhOJl8GBz3pEEJKqEgufvfzfCFIH/mknO/kpRF2nvvU29PSwiXlw6EYSxopAimn1bq5b9cQfcY6Dn6V9jL24hxRVU8GulCihZiMieUUiquYA3hTavCASCABcrfG/5DhDeO3Qw2bpyMW3nOrBMrmC4k2FZwcKiWcFMrEObNibdKj8HRDaYTUBDz6nZwOc5caL5dqpVM3FcXC6VCkeALIEIJyTtePRRfywJuLFy3pA5j7TEuFRGkSZMMAUbjz3WpLtWCgcBN+ECijuyXGYjUvGjjKM+yvDh2Z6O5e8DP09FRIUUV1Dp399oVWAuCCpUFVZSBIoBgYULzcWKYNTq1Y1PvZdD2C9s0BRyASfQ3s0KtsUWRlta7K5gBGU//rjI5MkmQDsgssFsAhp6Ts1amSe8ZNAg445E0cAEalBzAr3Qhx97zKSApcYZCTmII/WLRo8W6d7dCAB4UkQtlui330ya5UWLjNDbqJFfM9d2ckXATV+NMItQW95e+fprk4a/UiVjRSFJUwLJxnmqQkrqxiGDA9pkLkgEpx1+eAK3lU5JEfgLASwm1Dcha8nPPxt/Z1ywCvH1LhRcXMHcrGCuKxgFI3EFI1i0mOoCBFwbJXWpbDCbQreGH+9bmSdBzsQPUFeBb4oMknGrx+EH2H60gcsMCSNwd0R5iFuon4QFmTIEuFI9/bQpThslcoUotPikd1cKDwH4JZnVqMtDnb2jjy57LJS6QNlHPOfQoeGNOeCebZynKqSkLyKZQ8ggQnDeU0+ZQD0lRSBpCOBqRYYbtPRkyEH7W1Ji/GejQGW5gnH4k+UGiyd/UCjwN99rvpl+ojDfTGOg3gwCJG4D/Bwg2WA2AQ7fc9PW5kna7aOOMqlizzrLuCpFTUvvGbWQHkTYQzGBi1O+6V+9DN1N7YswxAU0KucIewh3NAS1t9+OrjuaF4yT8gwZLknJ36KFiTvLRCTRICkDiokvv9y4nlhSsMAVa5NN5E+EtwBJhZRM4OI/yIWNKrYUfdJAtQC3oDZtHQEy2eFK5Qb2cfBG1Y3AdQXjkk5Qf3nE95oquKT+7AozufzeS3BkkItHtkEuTbgWBJx50AazCRIqr21bnSfpR8n4hesHsV4kaVHyjoArpBPXg7BXtar3d3N5kksWyUHIHkb8B/FwUSAyj/bsKXLKKSYORyl8BLC84WlAEpOPPjLB9OlEGvKxY0X69DEhBAkmG+epCillbaDrrzc51DkYMbNSqEtJEYgzAr/+aoqfuQWlYMZcBLi4x4FwBSNokbz1BL3yhxoVqX/zM37cfhD+xGCzyy5GiKOIHLFq/DtorTgpVslmFGBtlFSIbDAbP5ak0Dasz5MaN7gNr1kTeFxRodhE6n0KLuJagwDx5pvGehokkZmNb5tMerh+ofAIkzjXuAzj5kZtlEyX4TDHV8x9kw2WYHg8EcaN2xAJYoewonBvxIpCeYsEk43zVIWU8jaQWyW0ShWRJ5/03x82wZtXpxYxBND6EBzP5ZeMXWh6TjstYoP0aTgIKTB5V4ApS5jx8ntSn+J2kUoU5OJC4/45+GD/tbxulWIESn4OmGwwm4Cn4Kn5UOYJ76BSOG5E1EygBlHQQq4nNCL6EMoUMmxyVuVal6KQKRGcT5D+sGHGkyJMYgwolKKeHjlMjMLq+8cfRXbc0aQax7Vr223/PxK3ngru08Q3J5xsnKd5CymLFy+W/v37y/z582Xu3LmyYMECGTRokFSpUkVatGgh7dq1kylTpsiMGTNk7dq10q9fP6lfv7707dtXVq9eLStXrpQ7CCwSkmt0lxo1aki1atVksEfzmA1wnMG5JmdcPwispyhPVPz2E/4B6PR8QABNJMGXuA0QiI7rIjUBOGSVsiMAfm5mHbLr8AftOG5oLnEekPElVXChxky+F1FLtVFSJ2/tPM2OeKBPhDZP3IguuMBcbEgnS3pvlF9KGyOABwOeDJxVuKbaihH59FNjsUAL/tln4WVl4xKMFQXlyoIFJkuUUrQQcIs0pgojZPEiExvxkVhRgkzfHxE0bJyneQspLkYtW7aU6dOnS5cuXRwhpXbt2uL+n/v3smXLHIEGQWXIkCEyZswYmThxohNww58KFSpI+/btpWvXrtKnTx+pS8GcLGQDnNIhjB9vgle55OFjfO+9WiE72wLp78NHALcoLkTEVXGRJssIwootph8+AsGMgExopGt2hRb+ButUIl1qqtCC64rXS6ml2igqpASzPcpslX1CnQ83VmXKFONepPR/BEhB3rSpSYWOe6ftSvBkESS7oIVkFWUuu1tkMpM7ke6VaCCAQEJSA9Jho8RCsD33XJG77zbpx0m+VARk4x7um5DSunVrmfpXsTH35/T/KykpkVmzZgl/z5kzR2bPnu0IKU2aNJHGjRvLsGHDpGnTptIoQxDvgAEDZCCWjBQKOqvABp2h0SDYmLz3XDYIhORAK6aUqEXw0SVmiqTQJuaEyzPanYceMj7eSv4jgLUFpsUldM4c8zcXrD/++H9fWGIJfk8VXMqyZlmqjaJCiv9bIWuLCCgEQrNPcBvEvUhT3RvYsCDst5/I4sXmvCKNs20i7TeXTxQRuMgSX2CT6J8q5bisYtlRi7dN9HPrC3dpEhoQl4JgXb++Ea6xovB3EVCshJRUS0qrVq1k2rRppRaVVEvK0KFDZfTo0RktKd26dZPevXtHz5LibjZcPPCRxdcQsz0pJjHjh1lXogg+BJ1iDggQP0FQH9pACBcT4howQSvZQ4BAaTISpVpbVqzYsH+06AgtbkA+LmPEwOywg0iNGib7GsH7FsgGs7EwjaxdRGKeXEBRcBEXhoVT41TMulFAFuGE2DkyDoZFKCCpbxFGVi3cyW+4wewP9oVSdBFAYY1Cfa+9TAwVHjaUsCCWqEjIxnmatyVlzZo10rNnT5k5c6Y0a9ZMevTo4cSTEJPSvHlzJyZl8uTJzu+JSSEWhZgUXL5WrVqVMSalevXqjsuYF7IBzv/aOxOwrYoqjp8yMzTLBVQQ9wVT0jKE0hTNBVfUCvcVFUVTU8vQFLDQcElccNdwxw1UcF/S0MjK1LRU0NwI0cRIEcXcen5zG7hc3v1733nv8j/PwwN83/veO/OfmXPO/5wzM2XbwYY+sir8zdGmOIGkZhutQa+lw/qMEKiGAHslOMOdk3FIQ3NR4847V/uWfh8CAbItREbjpIXbs7kLwguEhFLXl14KXm7SVn0aAv//vyNV/bzsMjPu/dE+lYicQFLIHJCFbGc9P4Eess8cHU3Gi0BCCCHLRhYFPwIdsMIKId6qd3QEAbKgHF2NLLNMlFEvSBaFLofQpw2TlI6MazO+GwKciu0kGsYmf6IulHVwUy1OoWqMmzG8ekY9CODsMhcpHcEZ3nrr6PI4IvKS9CLAxthktoUjRykh5W4UjiAOJG3Xp0Xtp/apRCckUeZFFpGbvNNwLxn688ADzTbZxOyRR8IEINkHM3p0dPXB6acHWhF6TYcQ4DJkynORAt6FFMJuiKR0aIZadIY7WZXnn4+iP5TZEBFSVqWjyOr71RAgcwI5YQMuQuSNDXtcJqW9UtXQS9/vIZjc0UAAhPtRAkoIYxOwO2Vflcp+FnmfCgE+7iDjolZKnSinToPQLvaQkdVBv3KEdCvF36/Bflei8WTCJelHwM8TgkvPPRdV1hRIQuhTkZRmTCjSw9wuyr0qOBootIsvXvD87Ga8R88QAiBAlB1ywv0LCBkTbrM++ODm39chxAuBQAhjkwYgU9vPou5T8Zcmc1kjNf6LLZaGaRK14d57zbbdNir94kJFDr9olaC7qcQoyP0arYKxLc9l/yFkpUBlXh7nEPpUJKWZs5q0MCcqUU/auXNEVDhyUiIEmoEAWTv2bHGkMML+BcgJRx/WerxtM9qhZ+QOgRDGJg2gpb6fRdqnQiaYI/19eeN666VhiizYhm22Mbv//uhem8MPb037Xnghup8FJ5csCodmSIRABhAIoU9FUpo9EbjFmppSLtBDOKmEEjA2VUmEQCMIPPZYdJHoPfdE3+buAG5EpmY6TZHHRvqm76QCgRDGJg0dzUQ/i7BPheqDjTaKDvngFCtOs0qjQKQo+yLoyAWPSy7Z/FZy2AmnmRVwT0PzwdQTQyIQQp+KpLRqRO+7L4pwc0IIF7txIeT227fqbXpuHhHg1BDICZE8ZNVVo6Mx2QMV6GjaPMKqPi2MQAhjkwbcM9PPvO9T8Td2k6ngTqc076FD3159dVTSTZltM4UyMg4N6NIlqsDQUfHNRFfPajECIfSpSEorB5HLqVDGnJ+NUHfKccUFrF1sJcxVn80+IfZxcEs4d1FwqSH3E6RVJk2KyAkn3SAcS8nZ6/vu29q66LTioXa1HIEQxqblnajhBZnqZ173qRDA4zRMqgs4mTDtpxBy+hj7UiBSHCPezPZSDs7G/HPOMTv66BpmsD4iBNKDQAh9KpISYrzZ4DxoUHT7N6U6XADJDaWS1iJAlOqGG6I/pOq9cALHpptGR11usUVEXNpNWiBSDz8ckRNOukG47ZjoHSWD7W5fa0dKT28zAiGMTZu76F6fyX7maZ/K229HJ9eRKeLI9Kzs2WTvH8cCUx1BVUQzhMBZr17RtQWQH+0rbAaqekZABELoU5GUUAPKbdODB0eKGeFM9JEjzRZfPFQLivEeNiHeeGNETKh39sKNsJCSJ580e/RRs/ffn/87MluQFggLn+F+ikUWCYMX5OTBByNyQruQHj2io4R3313kJMwoFP4tIYxNGkDObD/zsE8FXcct7mQOOGCGYF1WhKqINdc0mzUrusS5Z8+Ot3yHHczuuis6YOfQQzv+PD1BCARGIIQ+FUkJOagoaRxoTglB2REp59KojTcO2Yr8vYt0/E03RcSE6JQXjrXcY4/I2V9ttfk/54ZnLtEjc/HQQ9GNsWzk9MLpKpttNp+08Jxm10wzFzjiktO6cECQddeNyMmAAeFIUv5mg3rUAAIhjE0DzWr6VzLdz6zvU/EXJKKL2ZCetbJnNvhTvs3eUn/CYqMzlJvsuSgSLLhjTXsMG0VS32sjAiH0qUhKOwYYY3PIIZGiw/nlEisi6TqpqfbReOONKCsFMYFkeKF2eM89I2LCsY61CLXfHO/rSQsGZO7c+d9ceukFSQvlCo2SFsgJ0TPICe9EiMoNHRqVPjT63Fr6qc8IgTIIhDA2aQA/8/3M6j4VNoUT7CGDzZ47HPSsCdhjU+gL2e+OlGzzXQJk7Ffdb7+sIaH2CgGHQAh9KpLSrsmGs0pkic1ys2dHjioKi+MOJaUR4FZXSgUgJij4Tz+NPrfKKlHGhD8Yws99rmMIfvhhdLGYJy1kOviZFzZ89u0bZVr4QwakGrlgvCdOjMiJz/bQVsjJLrtU/37HeqRvC4GKCIQwNmkYgtz0M0v7VD7+OCqjJZjUihOyQk4sMvYEwLDTZOOr6f1SbeNAlC23NFtnneiSyFClxSFx0rsKgUAIfSqS0u6p9OqrZgMHRic5sTmach/uwGjl7bbt7nM973/3XbMJEyJiQnkUBg/hWOfddouICftNOkpMKrWJrAp3lUCMIC78m6iaF87Qxwj7jfhE23x7IFIcnAA5ocQBYaM+NwvvtFNjRq4e/PRZIVADAiGMTQ3NaPlHctXPrOxTOfXUiJywSZwsdZZtG8Em7A0EhbtNONSkHuH7ZJEYO0q/sWESIZBRBELoU5GUNEwOHFkuf+QSSNLhHJFLViWNN/CGwAsMKImCmFAS50uvll022ngJMWGje7siUOxfwch40kLWhX0uXpZbLiIsRNuuv97s6aej32CkISdsmGwlqQoxRnpHrhAIYWzSAFju+pn2fSo48+y5hJhwaAmHgmRdKFcjk04Gn/0k9ZzKhT3bccco4//EEwpSZX0uFLz9IfSpSEqaJhknU3HqCdEmNtKRYWGjXh4UezWcyUxwfj7EhMzDe+9F32Bz5a67RsSEFHkao3Bz5ixIWthr4jM+9IHIG+Rk221FTqrNA/2+LQiEMDZt6VjipbnsZ1r2qaCzX3452rPh/6DLp02LgnCHHZaGKdCcNuy8c5ThP+sss+OOq+2ZBCMJVEHW+C6ZdIkQyDACIfSpSEraJsgnn5idfbbZ8OHzj8kl8n7MMdFGvTxF4HHkKZ+CmIwbZ8Yxj0inTmb9+0fEBMe+nkhVGsYTYw3RJIq40UZmW2+dr3FLA8ZqQ1MRCGFsmtrgBh+W6362ep8Ktmn69IiAJMkIP+MesFLCgSA335wvHfjcc9F9L0suGd3BxT7FaoKNoxKgd++oZDhPtrxa3/X7XCIQQp+KpKR16rBJ/NJLzUaPjgwDsv76EVnh9KqsngRGTS7O+zXXRMcGe8NG5mi77SJiQjqcCxclQkAIBEEghLEJ0pEqL8l9Pzu6T+Wdd0oTEEjIK68sWNYax5oMN8fprr76/L/5N3+acZhJGiZPsg1khi65JMqkkFGpJBA87Pezz0YVAwSuJEIg4wiE0KciKWmfJOx1IAo1apTZ449HrV1++eiuFS6H7NIl7T2I2scBAddea3b11WZTp0Y/Y0/JVltFxIQTrpZaKht9USuFQM4QCGFs0gBZIfpZaZ8K2WvKr+IlWfHMCDfClxP22nnikfy7W7f27RFs18TiGHwueMRGszclfhdXsk3Yvn33jY6yp3pAWZR2jZre20QEQuhTkZQmDlhLH0UGgiMcKQW77TYz/k82BcXHvpU0brInKgfBImvCZkMvlEDRbo5yxPBJhIAQaCsCIYxNWzv4/5cXpZ/u9MGjjooi/ZwayUEjBIr4Q1S/lGBPPPnwWZH4/5XdXhg17jejNJtTvjjtq5RAYjjxkbIw7CBjIRECOUAghD4VScniRCHydd55ZldcMX+D+TbbmB17rBl/tzNKg0LmqGCICZsD/clcK68cEZN99onOh5cIASGQGgRCGJs0dLYo/ZyHdXyfCj/k6PZy2ZAVVtBpU/VOUvYfrrWWGVkVypjZGJ+Uyy+PLm/u18/snnvqfYM+LwRSi0AIfSqSktrhbeW0TgAAHldJREFUr6FhZCpQgBCW116LvsDFguxb2XvvaAN6CCGrwwWFEJOxY83eeit6KydzDRgQkROiR41cfBWi/XqHECg4AiGMTRogLko/F8AaB5oyLrIjiy+ehmHIVxvYO3roodGx89x3Fg8ScgkwJIYSO059pIpAIgRygkAIfSqSkofJQp3xrbdGpWCcGoJwwSB7Vti7QoSsFQIxotYWckJNLsI+E07kgphwQlcootSK/umZQqAgCIQwNuWgnDJlip100knWtWtX6969u73//vv2zDPPWJcuXWzgwIHWu3dvGz9+vN155502d+5cGzp0qPXo0cNOPvlkmz17tr3zzjt24YUXWqcadE07+1mQqVS8bmJ/2RTPiV/cg7L99vMxOP/8qOyOI4sp05YIgRwhEEKfiqTkaMK4rkBS2GTPcYfUHnNqFvWyZFdQpB0VboC/5ZaImLAB0AtpbogJm+C1z6SjKOv7QiAoAiGMTbkOjRo1ytZdd13r16+f7b///rb66qvb1KlTHek45ZRTbMUVV7Qdd9zR7rjjDpsxY4YNGzbMEZURI0bYxRdfbGPHjrXPPvvM9qrh9u929jPogOplYRGYODEKyrE39Kmnon1AXEpMaR0nWPKzZtjfsL3S24RARQRC6FORlLxOQjZIEsWhJhligXDPCmSFSE89pVdEijg2kZO5uJzL7zNZaaVojwnkhI2BEiEgBDKJQAhjUw6YmTNn2vDhw22xxRYzsipkSPr06eP+PXLkSBszZoz179/fJrDHzfAF+9sJJ5xgDz/8sPt78uTJNmnSJBsyZEhV7NvZz6qN0weyiwAlz5R7sTGeEuyDDjI780yz44+PAneUQUuEQM4QCKFPRVJyNmkW6s7s2WZjxpide2507CSy9trRiWD77We2xBKlEUDpPvHE/H0m/j4TLq/iQiqISd++9ZGdvGOt/gmBjCIQwtjUAs2uu+5ql112mXXu3NlmzZplgwYNsptvvrlkJuXUU0+1iy66qGImBfJDNiYuZF0kQqDpCLDnpE+f6HACbGfPnmazZkV3o/To0fTX6YFCoN0IhLAbIintHuVQ76f0i0gkpWCPPBK9demlzbiQ6ogjzFZcMfoZG/w4SpGsCTW2CPtMODUMUkNKW5svQ42a3iMEgiAQwtiU68j06dNdCddHH31kffv2Nf7/+uuv21tvveWyI7169bJx48bZ3Xff7fakkGlhTwolX++++672pASZIXpJTQiQNbnxxuj+lBdfNDvggChIKBECOUQghN0QScnhxKnaJU7igqygTCnlon6W7Mibb0b7THykccMNo4wJN9xzgaRECAiBXCIQwtikAbii9DMNWBeyDVQrcMQ+R/EvuqjZlCmVL3ksJEjqdF4QCKFPm0pSdEpLxqbe9Olmo0dHF36Rlka6d4+OL4acpPGCyIxBrOYKgSwgEMLYpAGHovQzDVgXtg3s+zznnKhK4aKLCguDOp5/BELo06aSFJ3SktFJOWeOGaeTcCoX+0wo75IIASFQGARCGJs0gFmUfqYB68K2gYNlqFKgOqHcns/CgqOO5wmBEPq0qSRFp7TkafqpL0JACBQFgRDGJg1YFqWfacBabRACQiDfCITQp00lKfHh0Ckt+Z6c6p0QEAL5QSCEsUkDWkXpZxqwVhuEgBDINwIh9GlTSYpOacn3hFTvhIAQyCcCIYxNGpArSj/TgLXaIASEQL4RCKFPm0pSQg5HCHBC9kfvEgJCQAi0C4Gi6NOi9LNd80jvFQJCoDgIhNCnmSYpxZkK6qkQEAJCoLUIFOGSQ4yqRAgIASEgBJqDQKvtRqZJSqvBiQ/h5ptvbg9zh0ggCcFQk13Jex9D9w98Q49j6D6G7h+Y5r2PofvXjnkaSI0u9Jp2zFffiHaMq3+3+h1+xrVrvDXWxRnrduvuEHNcJKXG+XzllVfaAdweG0jaoWjy3sfQ/WuHAgndR83T5iuE0GPYjnnafNRqe2I75qtvWTvGNQ0kRf2ubW4261Oa481CsvbnaI7XjlW9nxRJqRexQJ9vp6IJ1MXgWYZQ/Yq/J+/jmPf+FcWBL8I4FmUsS+m5ooxvsu9F7HcR+6y1/Vk73Jsg78wsSRk+fLjxJ6+S9/4xbupj9mevxjD7Y1iUtVikfiZnZRHWaamVWMR+F7HPWtv59YUzS1Ly4RqoF0JACAgBISAEhIAQEAJCQAgslA39LOTuc+EvBISAEBACQkAICAEhIASEgBCogoAyKZoiQkAICAEhIASEgBAQAkJACKQKgVSSlAceeMBuuOEGe++996xnz542YMAA+8UvfmFf+tKXbIcddrDvf//7Nn78eLvzzjtt7ty5NnToUFtrrbVs4MCB1qlTJ/vXv/5l559/vnXr1i1VYMcbU0sf6cPNN99sRx11lP3whz90Xz/55JNt9uzZ9s4779iFF17o+ptGaaR/r7/+up144omuOx9//LGNGTPGFl100TR2z7WpkT76zvzyl7+0P/7xj3bHHXfkrn9jx461yZMnu4MRWJudO3fOVR8//fTT3OmaI4880j744AObMWOGXXDBBbbqqqtmRtf4yVXLesy63Si1kGrpd5ZtSTnl0Ui/s2Zjkn1vpM9ZsjnNHGuelSVb1Ky1nTX7VM05SCVJiTd6u+22s+7duzuS0rVrV9txxx2dY+f/xqgOGzbMzjjjDDvmmGOcY3vppZfa8ssvbzvvvHO1/qfi9+X6SOM42u7LX/6yIyn//Oc/bcSIEXbxxRe7xUel3l577ZWKPlRqRK39iz8DYsafNddcM/X9o4H19PG+++6zt99+26677rpUk5Ra1mFyjs6cOdP22Wcf22CDDRzBZG2mmWg20sf//Oc/udQ1YIET/+9//9u23XbbTOoaP55FsBulFGOteiirtqScMai131m2Mcm+19PnLNqcjo51lm1RR9Z2lu1TqX6nmqRcccUV9uGHH9o999xjEyZMcO3v37+/+7f/2//s9ttvt8GDBztHfs6cOTZx4kTn3KddKvUx6QD+4Q9/cBdKnnDCCS5SPWnSJBsyZEiqu1hP/3xHnnzySZcluuyyy1LdN9+4evr41ltv2WmnnWajRo2aR7TT3sl6+kd2iIACWU5I2EcffRT0fqFGsaynjwQH8qhrICeHHnqoXX755fbss89mTtfUsh7zYjdKzfN65nAWbUm5tV1Pv7NqY5J9r6fPWbQ5zRjrrNqijq7trNqncmOeWpJy9tln2xe/+EX70Y9+ZIcccsi8TMpOO+3kCEgyk4JxpTRq5MiRdvfdd9vUqVPt6KOPbtRnCfK9an1MkhQI2KmnnmoXXXRRJjIp9faP/j700EN24403unK9LETg6+3jTTfdZPfee68tueSSjmxfcskltvXWWweZb428pN7+TZ8+3ZXsXXXVVS64wDokI5ZmqbePf/nLX3Kna6ZNm2Y/+clP7JxzznEZ66zpGj+/qo1lHuxGqbVUrd9ZtyXl9Ee9/c6ijUn2vd4+Z83mNGuss2iLmrG2s2ifKvkHqSQplDKx92KrrbayRRZZxDk51PCzJ2X77bd3e1LGjRvnyAh7UvjsyiuvbAcddJAtvfTSRt0pn2c/S1qllj7irFPahbMOCfvBD37gavzffffd1O9JaaR/3/rWt4w/lLaxn+GnP/2prbHGGmkdQkcUq83TUmPoO+QdprR2sNH+kUmZNWvWvL1hyyyzTFq72NAYooPypmt69Ohh3/jGN5z+pEyWUpKs6Bo/uWqZr1m3G6UWUi39zrItKac8Gul31mxMsu+N9Bm/ISs2p5ljTb+zZIuatbazZp+qOQepJCnVGq3fCwEhIASEgBAQAkJACAgBIZBfBERS8ju26pkQEAJCQAgIASEgBISAEMgkAiIpmRw2NVoICAEhIASEgBAQAkJACOQXAZGU/I6teiYEhIAQEAJCQAgIASEgBDKJgEhKJodNjRYCQkAICAEhIASEgBAQAvlFQCQlv2OrngkBISAEhIAQEAJCQAgIgUwiUFiS8sYbb9iPf/xj+/Of/2yLLbaYrbrqqu6OAO5m4WjYv/3tbzUNKBfnbLnllnbbbbfZV77yFTv33HPdJYT8nPtdeIcX7v4YPXq0feELX7AddtjBzjjjDPv444/dcaZPPPGE+/d+++3nLmtEOAZ0xowZ7uff/e537YILLnBHMiflV7/6lXG5E78777zzrF+/fhXbzn0yw4cPt+eee87+9Kc/Wa9eveZ9vtyzyrXlmGOOcXebIO+//747dpYbT/kZv/Py/PPP2w033GC77LLLAm3jsk76TP+XXXZZ9xnGgufsv//+7pjpasKlne+99161jy30e8Z70KBBtvjii9f93eQXOCqa59CXcvLUU0+547E5IrCjwjyi/f/4xz+My7o6d+7sHgnOBx54oMOTO3W4+8LLwIED3Q33yy233ALzu9x8qDQ34+3nEsDdd9/dXnnlFTd2nMvPUbaV5IMPPnC3mv/2t78tOac7ig/f5+LTs846y/W5FqHt3F/DOmKNPv744yW/xnNZ11xUCe6/+93vbMqUKQ4DLy+99JI7/jK+/qu1gfPtGTvWEXMEXcJR3OXWWD1rpNq79fv6EUiLDaHlTz/9tDumnuPpP//5zzu7xpH9m2++ubMhnTp1ch3k5nHWf1JabUPefvtt22OPPdz9O6wv2nrkkUe6Zrz66quGbkKPcVz5tddea927d5/XRPr0ta99zXbddVdnP5MiG1L/3OUb5WwIvgt3zN11113Opl155ZW24YYbznvJJ5984nyGFVdccQHdWsq/+e9//+vGGl3KvESnMSeTUiQbwt1o+GnYGNbib37zG1tppZXqGsRq65VLa7FB3o9lbPCTsC9Zk0KSFBbhxhtv7Jzgww47zI0ZN/Ci7HBU6iEpLGQUPw4jEwJFjOMP2cEJ4+LFtdZayzntOI3cxA0pwsFgguLQjR8/3jnnOCfrrruuc65oB8oZ4kN7d9ttN3dPCs+PCzdD77PPPvbYY485B5iLAXFUS5EZ/z3ICQoD5YET50lKpWfV0hYWArfFs+jiggJac801nYFKEgJulv/73//uCBjO8i233OIuc0RYUAcffLBtsskmFddVoyQFjFGe3sFv9eJF2fO+Uoa23neDM0QAhR/vA/MKow9p5vdxkjJp0iSnqCBScRJebj5Umpvx9h5//PHWpUsXd6/NmWeeaTNnzrTTTz+9YpcYdwxYPU58vRg1QlKqzQcIOLqDiyq5m8mv43jbMOIYcG48XmWVVWpudp8+fdzc2GijjZwOOuKII1ygIi7JNVbrGqm5EfpgTQikyYYQTMCJvOaaa2yDDTYwCMFSSy3lbAD6Ia7jS3UuhA3BfkDkv/3tb9ucOXOczcHuQT4GDBjg5jv2mKDFmDFjXF+84DB7AlNKd8qG1DRlF/pQORuCTwOmBHcgu1yojS7zwmWS6EnG1AeAyvk32HU+y5iiK9FnPBP/o6g25JFHHrFvfvObzhZffvnl9sADDzj/r1aptl5ZV/hRBC68nce3xI9izLMmhSQpKMJhw4YZkyUpRIPrISl77bWXi8ZjDHCyuU2ciYdwoSSEBCcOksHnuKAyLjjkRI5uvfVWd0EjShyFEL8Aj4gtF1hCRuLRWp4Do2bB/+xnP3OPJUNz0kkn2Xe+852qczFpwGp5VqW24LydcsopC92gfumll7po83XXXbdQm8j6EHHGQcO569atmxGhJIJ8++23OzxRmJXEkxSyKVxEx0WCtHPEiBHu/xhF8Ick8Q4uYHzzzTedA88ldpAUnw3y74HAYDxpN3L99dc7ohWP+uGYo3xxVslM0Q6eCa70h2fi1JLl4v98nwwCDizZsuRYVh2wEh8oR7Ti7Yl/rdL8Ts6HWuYmzwZDCNDyyy/vnAmyfjgklYS5Aqa0HzLBxYHM+RdeeME23XRTN+ZJQwaGEOD11lvPPdpnFwkuQHbAlogxY0KbWkFSaBfBAOZWOSFowTr4/e9/7z5CtgvCATaQdDKt66yzzgJfJ9r9ve99z2U3EXQJxouoW1ySa6zWNdLI3NJ3yiOQJhuCU8lawo4kpRaSUoveL4dEIzaEZxHpJZNCUI31jJ4newL5++pXv+ocYITsIoEPAn7lAjyyIR1bqUkbQvASXeTtE+ODLuratauzoZDJn//85wZZ8SSlnH+D3sMXwXdBqDphvvXu3XuBRhfJhsQ7TsUD68DbCtYwWRZsGr4g9iYZcK60XvGBWCv4XIxJPBhJJhK/I4l9x2ZP679dSJLCJHj55Zdt1KhRCyEcd+KSJRzxD0NwKA0hUspE4N9kMHCKJ0+e7JwlFiQRI6Kf3ObM74jAQlxQvDhdONP77ruvPfjggy6TwsJHSXih7IMsDxOPCZycsEQ5mMxeCfBdFD+3tleTpIGp9qxKbcF5px0+nR9/Nwrv2GOPdeQvKT179nSY+PQ+yooFC3GYPn266/czzzxTsSuepBBRBEOyT2RvaA9jSGQBI8jCRSCDGMJKmRR+R5ZtyJAhLsoBwZo4caIzrmS0UNRXXXWVy1hAMJMkhZuNf/3rX7tyNf5GyVfKpNQy10qB0EqSUm1u+vYQtYWMeWHsyKaUEzIoEDvIKAKZIMJGhIj1xDyhBDJ+UzKfY73yHggAcwPCj1OPQ4PzT/qcZ7G+GfM4SUmWH/q2sW59sGK11VZz2ScIMuuIoEJSfJkX2b/Zs2c7A3PAAQcs8DFKV4hss54Q2gnZWGONNdxaxsDj5MYFB4y5xjxB+ByZ13ipWqk1VusaqaYL9Pv6EEiTDSGLjzNPpBoijHPCXELQ8WRWsBusJwJYzO+4VNP7lZCp14bwLOZx3759XaQXXb333ns7x4mMCeuWdqI/WIvYDrIq2MdyJEU2JBqhZtkQ9C/zhyAQAglEF+HL4Ffg6KL74qW05fwbAjIEbcaOHWvTpk1zGQSCdkndXiQbklx7PmiJLSPYzBrAluF/EJRKlpBXWq+UBm+22WYO52SwnTGkBPS4446rT9m1+dMiKYkBqDeTgpPDgvVCFJeUND9HeS666KLOueLfKFxqMmHPLHZqBnFGSIniwOKAofRxTHCYvMydO9eREE9A4k1ORir4zDbbbLOQEig1z5IGppZnlWsL5T0QFAhZXIgQr7/++i76DBZJiUfR+B0kBZLH/hSc5BVWWMEZ2UriSQqfZ5ES1ScKj9IGY8YHskNkiIXry8eqkRQcW8aB7Avt8Hs/6BN94edEl3AOkiQFhcB7aDtk9MUXX6xIUhrVA60kKYxDtblJu3EmyF55qUZSmAtbbLHFvGwLZILMps9aXX311S4tnQwi4JBDwCEzccKC8TvqqKNcFgYHDBLE2NebSaFdZPLIsmGYcURR+EmjgrOE08RaYIzJZjBvEd7NMyAxZJaIbJFx87/nM3yPgEZcKIHA+MdJymmnneaIsZdSa6zWNdLo/NL3SiNQK0mpBb+O2hCCIKxT5hBkHf3PemKtsGZwgiDyZIYhBEmnpxa9X64f9doQgkisfUpDfSCNYAWOF7oa8oKTBoGBnPB5KhEqBXhkQ2qZZeU/k7QhVGOgi+IkBV2E3fOlYEndWs6/wUbieKMvV199dWfTKeEmYBuXItkQ32/KqVm72D3IA34jOPs9Y1QGUN5PUC4u5dYrQTCqRLAZpfxYCCN2h3dmSQpJUlgwlBh5pyg+YPVmUlhcOKLJ0hSeSQkLTuzgwYOdk0x0wm8aw2l59NFHnXNLxJ9sCuJLwoiGxYVIPoQmWZObTP3hhBOpbUa5V7lnlWoLzB1DCfOPC6QMh81nMZKLo1KqHnJBzTLkp5J4kgJBJCtDxgkSwaJlrFHCONH8jjZixBmbWknKp59+6kgKZAQHPE5SvFObJCm+DhziSZSJeZW1TArKsJa5GU/VEwHFca9U7sVYMF/ABClHUiAIXkGDHThSCsYYQsaJyLGHi6wWmSuICoSFz/DsejMp8TlGOReGI76nh9+PHDnSkQzGG6EdZEpwABEIC+0jeogwh9dee203Z+KC8abNCKWcHLJB5hUChlBTfP/99y9Q7lVqjdW6RrJklLLQ1jTZENqCbmONINgEIrEQgbigF9m72C4bgh5lrmObfHlycqz9vkzWL4SKLCe2FbJPAODwww93azAusiERGs3KpCTLvSAg6CKIOcSRuYUOhPgynsyrcv4NAZq4oNPJKmPX41IkG0K/qRaBrBEIxbdACPASKGP9xoVKjbgdpDojXuLv/TQO5mGLAfuhqSrBX8Efww765xOAq1SqnEbdW0iSQt0rzheTBOcAIQqFgvTlJrWe7sVzcNpxiBG/kRZniYVLNJrSIk5/wlFhshFVxyFBEXPC19SpU53Dxd4Jnsei53k4IJAcJhwkBufPl5D4yQQBIDKG8eH5PNdvnOfnfL5cDWIyClbuWTD6Sm1BOWIoKKFLlhLQHxYd0bNSgkNHe1mg48aNc5vmiTAgZJxOPPFEZ4CJCNIfDHJSPEmBEIEtz8K4EZUjOseiZb8DTidZKvYMUab19a9/3UUdICtJKVfuRQQIxVyt3KsUSaF/vM87E81QCK3MpBC5LzU32ZwbF5whFC1pZKI0KELmdaUxo9yLzAelj8lyr5122smd9pMsCeCdzBfIOiWAf/3rX10zqLUl08jnUdKspSRJqYY1aw8niqg2eoD5DNlnDceFlDwlXsxJooJ+/WPIESJffDd+igrrllIWAg/oHtpOdjEprFNqkCmroKyQdL8/Ca7cGouvkWp91O+bh0CabAiBEPQ+QS/WE5Fw5ijzkN8RWMGG4PSjh/1hMSFtCOVmBD3ALbnHkMAG+hnHiwyQ/zs+WpUCPLIhHZvXSRvC4T4QiQkTJrgSO4ghhwHFJZlJKeff4Dsw5ksssYSz3VQYJEtdeW6RbAi6HGIBvnGyhm1B70NgyKZQso5dSp78Vcnn82NUKpNCEA/Skjx8qWOzp/XfLiRJAVYYK/Xl1PLivPojiInA17NxHqeIaDo19AhRXDIrOMaUpHjnnCgQjhdsl9/hxFL+RYQIh4YJipPEv1mwOHo4a0QsiLryWZ5HFMMrD7JBCAufLAKGgPpkfyIQkWec4uQkh5ljxChfohaUz7Fno9yzKrWF7xBVpp3JCBcLBQcNwhbPNJHF8I4Y34OAgQtZKfZ/kBZGcHjBiraiLHEafTvjS8OTFIwdmOE80ieIG6QEpQCmtIHneUcQMoNyhQj6Mhv/XOZD/Ahkv3GePjGOvKvSxvlSJIV5wdgwzv4whUaXOFEtiAClEig0nFnIF/8HW38UKdgQnaf2e88993SEgLZTigRhZt6Wmw/l5iZthuDj7PAu+oUD/tprrzmSD8nE6ag0ZryXQydwrmgTcxlniuAA0bZSG+d5L3OR8hXaznxAIC2MFeNBiQsOTb0kBTIL2UFw6Gibfz5zBPHOHWPLBn4IefyYccgNa41nEZjwAnknm0oQgbmJs+ifHR9/8GL9++OZmZ+e9JdbY/E10uhc0vcaQyAtNoTWEyijVIT5gi5AN+DgsJaYc9gQMn7secROhLYhrGuCQpB5v6+S9tJWsoaUF9F2AkuQDvR0XJIkRTakdTYEUkFwE1vrDyKJX1PAuCRJSjn/Bj0MWcb2su+UABIBqiLbEMocqeLBjiHgwXpECNIS1MVHwBfF9nDaY1LK+Xz+c6VICpl7xjTUaaaNadWFv1VYktIsADFUOBalnOdmvaOR5+Ck4ghySlBWBQNL+QzkhRIFFjORhhAS+njiEH0K/Y5KY0ZwAKLF4QP17h0J3Y80vy++RtLcTrWtPAKyIa2bHbIhrcM2xJNlQ5qDMns8CVDEj/ZuzpNb/xSRlCZgTOSYshCi1ZLmIECWh7Rn8vLH5jy9+lNEUqpj1NFPkI0gA0JpXj2XLnb0vXn5frvXSF5wTEM/ZEOaPwrtXh+yIc0f0+QTZUNqw5g9RdzXV6q0vbYntO9TIintw15vFgJCQAgIASEgBISAEBACQqAEAiIpmhZCQAgIASEgBISAEBACQkAIpAoBkZRUDYcaIwSEgBAQAkJACAgBISAEhIBIiuaAEBACQkAICAEhIASEgBAQAqlCQCQlVcOhxggBISAEhIAQEAJCQAgIASEgkqI5IASEgBAQAkJACAgBISAEhECqEBBJSdVwqDFCQAgIASEgBISAEBACQkAIiKRoDggBISAEhIAQEAJCQAgIASGQKgREUlI1HGqMEBACQkAICAEhIASEgBAQAiIpmgNCQAgIASEgBISAEBACQkAIpAoBkZRUDYcaIwSEgBAQAkJACAgBISAEhIBIiuaAEBACQkAICAEhIASEgBAQAqlCQCQlVcOhxggBISAEhIAQEAJCQAgIASEgkqI5IASEgBAQAkJACAgBISAEhECqEBBJSdVwqDFCQAgIASEgBISAEBACQkAI/A8GEDvS0gcbjAAAAABJRU5ErkJggg==\" width=\"898.8889127013131\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1, axes=plt.subplots(nrows=4, ncols=2, figsize=(9, 8))\n",
    "\n",
    "plot_m2m(pdfM[['тренд ЦМАКП']], axes)\n",
    "\n",
    "# plot_m2m(pdfM[[strCurField]], axes) # !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Для тренда statsmodels.tsa.seasonal.STL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"898.8889127013131\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f2, axes2=plt.subplots(nrows=4, ncols=2, figsize=(9, 8))\n",
    "\n",
    "plot_m2m(pdfM[['тренд STL']], axes2, color='olive')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "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",
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